Global symmetries and 't Hooft anomalies in brane tilings

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陶氏化学EVOQUETM预复合聚合物荣获2013年美国总统绿色化学挑战奖

陶氏化学EVOQUETM预复合聚合物荣获2013年美国总统绿色化学挑战奖
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氯化石蜡的环境分析方法研究进展

氯化石蜡的环境分析方法研究进展

引用格式:周婷婷, 杨倩玲, 翁冀远, 等. 氯化石蜡的环境分析方法研究进展[J]. 中国测试,2024, 50(4): 1-15. ZHOU Tingting,YANG Qianling, WENG Jiyuan, et al. A review on analysis of chlorinated paraffins in environment[J]. China Measurement & Test,2024, 50(4): 1-15. DOI: 10.11857/j.issn.1674-5124.2022080162氯化石蜡的环境分析方法研究进展周婷婷1,2,3, 杨倩玲1,2,3, 翁冀远1,3, 乔 林1, 高丽荣1,2,3, 郑明辉1,2,3(1. 中国科学院生态环境研究中心,环境化学与生态毒理学国家重点实验室,北京 100085;2. 国科大杭州高等研究院 环境学院,浙江 杭州 310000; 3. 中国科学院大学,北京 100049)摘 要: 短链氯化石蜡(SCCPs )具有持久性、生物毒性和生物累积性等,是一种持久性有机污染物,被列入《斯德哥尔摩公约》附件A 中,中链氯化石蜡具有SCCPs 相似的性质也备受关注。

氯化石蜡(chlorinated paraffins ,CPs )拥有成千上万种同系物、异构体、对映体,加之环境基质中存在其他有机卤素化合物,CPs 分离分析困难,目前我国仍没有环境样品中CPs 分析的标准方法。

该文对近年来不同环境基质中的CPs 分析所采用的样品前处理技术和仪器分析方法两个方面进行综述,提供CPs 分析方法最新发展动态,为相关人员对开展此方面的研究提供参考。

关键词: 短链氯化石蜡; 中链氯化石蜡; 分析方法; 前处理方法中图分类号: TB9; X-1文献标志码: A文章编号: 1674–5124(2024)04–0001–15A review on analysis of chlorinated paraffins in environmentZHOU Tingting 1,2,3, YANG Qianling 1,2,3, WENG Jiyuan 1,3, QIAO Lin 1, GAO Lirong 1,2,3, ZHENG Minghui 1,2,3(1. State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; 2. School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310000, China; 3. University of ChineseAcademy of Sciences, Beijing 100049, China)Abstract : Short-chain chlorinated paraffins (SCCPs) are persistent organic pollutants with persistence, toxicity,bioaccumulation, and were listed in Annex A of the Stockholm Convention. Medium-chain chlorinated paraffins (MCCPs) have also gained attention due to its similar properties to SCCPs. Chlorinated paraffins (CPs) have thousands of congeners, isomers and enantiomers and the presence of other organohalogen compounds in the environmental matrices makes the separation and analyze of CPs difficult. At present, there is still no standard analytical method to analysis CPs in the different environmental matrices. This article will review the sample preparation and instrumental analysis of CPs in different environmental matrices in recent years and provide an update on the latest developments in the analytical methods for CPs.Keywords : short-chain chlorinated paraffins; medium-chain chlorinated paraffins; analytical methods;preparation methods收稿日期: 2022-08-27;收到修改稿日期: 2022-10-04基金项目: 国家环境保护环境监测质量控制重点实验室开放基金(KF202203)作者简介: 周婷婷(1997-),女,福建漳州市人,硕士研究生,专业方向为新污染物的分析方法与环境行为的研究。

Therapeutics targeting angiogenesis Genetics and epigenetics, extracellular miRNAs

Therapeutics targeting angiogenesis Genetics and epigenetics, extracellular miRNAs

INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE 32: 763-767, 2013Abstract. Angiogenesis is a process of neovascular formation from pre-existing blood vessels, which consists of sequential steps for vascular destabilization, angiogenic sprouting, lumen formation and vascular stabilization. Vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF), angiopoi-etin, Notch, transforming growth factor-β (TGF-β), Hedgehog and WNT signaling cascades orchestrate angiogenesis through the direct or indirect regulation of quiescence, migration and the proliferation of endothelial cells. Small-molecule compounds and human/humanized monoclonal antibodies interrupting VEGF signaling have been developed as anti-angiogenic therapeutics for cancer and neovascular age-related macular degeneration (AMD). Gene or protein therapy delivering VEGF, FGF2 or FGF4, as well as cell therapy using endothelial progenitor cells (EPCs), mesenchymal stem cells (MSCs) or induced pluripotent stem cells (iPSCs) have been developed as pro-angiogenic therapeutics for ischemic heart disease and peripheral vascular disease. Anti-angiogenic therapy for cancer and neovascular AMD is more successful than pro-angiogenic therapy for cardiovascular diseases, as VEGF-signal inter-ruption is technically feasible compared with vascular re-construction. Common and rare genetic variants are detected using array-based technology and personal genome sequencing, respectively. Drug and dosage should be determined based on personal genotypes of VEGF and other genes involved in angio-genesis. As epigenetic alterations give rise to human diseases, polymer‑based hydrogel film may be utilized for the delivery of drugs targeting epigenetic processes and angiogenesis as treatment modalities for cardiovascular diseases. Circulating microRNAs (miRNAs) in exosomes and microvesicles are applied as functional biomarkers for diagnostics and prognos-tics, while synthetic miRNAs in polymer-based nanoparticles are applicable for therapeutics. A more profound understanding of the spatio-temporal interactions of regulatory signaling cascades and advances in personal genotyping and miRNA profiling are required for the optimization of targeted therapy.Contents1. Introduction2. Physiology of angiogenesis3. Anti-angiogenic therapy4. Pro-angiogenic therapy5. Conclusion6. Perspectives1. IntroductionAngiogenesis is a process of neovascular formation from pre-existing blood vessels during embryogenesis, adult tissue homeostasis and carcinogenesis (1-4). As blood vessels are involved in the delivery of oxygen and nutrients, as well as in the withdrawal of carbon dioxide and metabolic waste from the whole body, the dysregulation of angiogenesis causes a variety of diseases. Vascular malformations, DiGeorge syndrome and hereditary hemorrhagic telangiectasia, are congenital disorders associated with abnormal angiogenesis. Cancer, neovascular age-related macular degeneration (AMD) and diabetic reti-nopathy are caused or promoted by aberrant angiogenesis, whereas ischemic diseases of the heart, brain and limbs are caused by insufficient angiogenesis or vessel obstruction (1). Therapeutic modalities targeting angiogenesis are divided into anti-angiogenic therapy for cancer and neovascular AMD, as well as pro-angiogenic therapy for cardiovascular diseases. In this review, the physiology of angiogenesis is briefly summa-rized to obtain a bird's‑eye view of this field. Subsequently, anti- and pro-angiogenic therapy is also reviewed to obtain a ‘frontal’ and ‘rear’ view of angiogenesis, respectively. Based on the three dimensional view of angiogenesis research, future directions of vascular medicine are also discussed.2. Physiology of angiogenesisVascular endothelial cells, constituting the luminal surface of the inner vessel wall, are leading players in angiogenesis, while pericytes and the basement membrane, associating withTherapeutics targeting angiogenesis: Genetics and epigenetics, extracellular miRNAs and signaling networks (Review)MASARU KATOHDivision of Integrative Omics and Bioinformatics, National Cancer Center, Tokyo 104-0045, JapanReceived June 10, 2013; Accepted July 15, 2013DOI: 10.3892/ijmm.2013.1444Correspondence to: Dr Masaru Katoh, National Cancer Center,5-1-1 Tsukiji, Chuo Ward, Tokyo 104-0045, JapanE-mail: mkatoh-kkr@umin.ac.jpKey words: bevacizumab, sunitinib, sorafenib, dovitinib, ponatinib,AZD4547, breast cancer, lung cancer, colorectal cancer, gastriccancer, field cancerization, poly(lactic-co-glycolic acid), chitosan,vascular medicineKATOH: ANTI-ANGIOGENIC AND PRO-ANGIOGENIC THERAPY 764and coating endothelial cells, are supporting players of angio-genesis (5). Angiogenesis occurs in multiple steps as follows: i) vascular destabilization induced by degradation of the basement membrane and decreased adhesion of endothelial cells; ii) angiogenic sprouting resulting from the migration of endothelial tip cells and the proliferation of endothelial stalk cells; iii) lumen formation by endothelial cells and the recruit-ment of pericytes to the surrounding region of the endothelial lumen; iv) vascular stabilization depending on tight junctions and basement membrane (1).Vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF2), angiopoietins (ANGPT1 and ANGPT2), Notch ligands [jagged 1 (JAG1) and Delta like ligand 4 (DLL4)] and transforming growth factor-β (TGF-β) regulate angiogen-esis through their receptors on vascular endothelial cells. VEGF activates the eNOS, SRC, RAS-ERK and PI3K-AKT signaling cascades through VEGFR2 receptor on endothelial cells, which induce vascular permeability, endothelial migration, proliferation and survival, respectively (6,7). FGF2 promotes angiogenesis directly through FGFR1 receptor on endothelial cells via signaling cascades similar to VEGF, or indirectly through VEGF secretion from endothelial cells, cardiomyocytes and stromal cells (8). ANGPT1, secreted from pericytes, acti-vates TEK/TIE2 receptor to maintain endothelial quiescence or stabilization, whereas ANGPT2, secreted from endothelial cells themselves by VEGF or hypoxia signaling, inhibits TEK to promote endothelial activation or sprouting (9). JAG1-Notch signaling promotes angiogenic sprouting, whereas DLL4-Notch signaling inhibits angiogenic sprouting (10). TGF-β signaling through TGFBR1/ALK5 receptor to the Smad2/3 cascade inhibits endothelial cell activation, maintaining endothe-lial quiescence, whereas TGF-β signaling through the ACVRL1/ALK1 receptor to the Smad1/5 cascade promotes the migration and proliferation of endothelial cells (5). The VEGF, FGF, Notch and TGF-β signaling cascades are directly involved in the angiogenic signaling of endothelial cells.The VEGF, FGF, Notch and TGF-β signaling cascades cross-talk with WNT and Hedgehog signaling cascades to constitute the stem-cell signaling network (11,12). Indeed, DVL2-binding deubiquitinase FAM105B regulates WNT signaling and angiogenesis (13), while Hedgehog signaling is involved in the regulation of liver sinusoidal endothelial cells (14). FGF, Notch and canonical WNT signaling are involved in cell-fate deter-mination based on mutual transcriptional regulation, whereas FGF, Notch, TGF-β, Hedgehog and non-canonical WNT signaling are involved in epithelial-to-mesenchymal transition (EMT) due to the upregulation of SNAI1 (Snail), SNAI2 (Slug), ZEB1, ZEB2 and TWIST (15). EMT is a cellular process similar to endothelial-to-mesenchymal transition (EndMT). Hypoxia induces angiogenesis as a result of VEGF upregula-tion (16) and controls cancer stem cells and EMT transition through the stem-cell signaling network (17). Angiogenesis is orchestrated by the VEGF, FGF, Notch, TGF-β, Hedgehog and WNT signaling cascades, which directly or indirectly regulate the quiescence, migration and proliferation of endothelial cells.3. Anti-angiogenic therapyHuman/humanized monoclonal antibodies and small-molecule inhibitors targeting VEGF and VEGFRs have been developed as anti-angiogenic therapeutics. Bevacizumab (Avastin) is a humanized anti-VEGF monoclonal antibody, which is applied for the treatment of patients with metastatic colorectal cancer (18), non-small cell lung cancer (NSCLC) (19), ovarian cancer and other types of cancer (20,21). Sunitinib (Sutent) (22) and sorafenib (Nexavar) (23) are multi-kinase inhibitors, targeting VEGFR2 and other protein kinases. Sunitinib is applied for the treatment of renal cell carcinoma (RCC) and gastrointestinal stromal tumor (GIST), while sorafenib is applied for the treatment of RCC and inoperable hepatocel-lular carcinoma (HCC) (24).The most important clinical problem associated with cancer therapy using VEGF- or VEFGR-targeting agents is drug resistance, as a result of clonal expansion or subclonal evolution of tumors with the upregulation of other angiogenic factors, such as FGF2 (15,25). Dovitinib (TKI258) (26), ponatinib (AP24534) (27) and AZD4547 (28) are multi-kinase inhibitors, targeting VEGFR2 and FGFRs. FGFRs are aber-rantly activated in cancer cells due to gene amplification, translocation, point mutation or other regulatory signaling mechanisms. Since the dual inhibition of VEGFR and FGFR induces antitumor effects directly through cancer cells and indirectly through endothelial cells, VEGFR/FGFR dual inhibitors have been investigated in clinical trials for various types of human cancer (15).Adverse effects associated with the systemic administration of VEGF- or VEGFR-targeting drugs, include hypertension, proteinuria, cardiac ischemia, cerebral thrombosis, hemor-rhage and gastrointestinal perforation (29). Ranibizumab (Lucentis) is a derivative of bevacizumab with better penetration to the retinal pigment epithelium. To reduce the adverse effects of the VEGF- or VEGFR-targeting systemic therapy to non-cancerous patients, an intravitreal injection of bevacizumab or ranibizumab is applied for the treatment of neovascular AMD (30).4. Pro-angiogenic therapyGene (31-34), protein (35,36) and cell therapies (37-39) have been developed as pro‑angiogenic therapeutics to artificially reconstruct vasculature for patients with ischemic heart and peripheral vascular diseases.Viral vectors derived from adenovirus, adeno-associated virus (AAV), herpes simplex virus (HSV) and lentivirus, as well as non-viral plasmid vectors are applicable for gene therapy ectopically, expressing pro-angiogenic factors such as VEGF and FGFs. Adenoviral vector expressing VEGF (AdVEGF121) (31), adenoviral vector expressing FGF4 (Ad5.FGF4) (32), plasmid vector expressing VEGF (phVEGF-A165) (33) and plasmid vector expressing FGF1 (NV1FGF) (34) have been investigated in clinical trials for the treatment of ischemic diseases; however, they have failed due to adverse effects or non-effectiveness.The intravenous infusion or local arterial injection of recombinant VEGF, FGF1 or FGF2 have failed to show beneficial effects for the treatment of patients with ischemic diseases, as a result of a short half-life or instability (35). Polymer-based hydrogel technology was thus applied for the treatment of ischemic diseases, as polymers or copolymers, such as chitosan, alginate, gelatin and lactic-co-glycolic acid,INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE 32: 763-767, 2013765can be cross-linked to form microparticles, nanoparticles or films for the delivery and controlled release of pro‑angiogenic factors (35,36). Endothelial progenitor cells (EPCs), mesen-chymal stem cells (MSCs) and adipose tissue-derived stem cells (ADSCs), as well as the VEGFR2-positive population of embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) are also applicable for the treatment of ischemic diseases, as these stem/progenitor cells are able to differ-entiate into endothelial cells and to secrete pro-angiogenic factors (37-39). However, large-scale randomized clinical trials are mandatory to demonstrate the effectiveness of the polymer-based protein therapy or stem/progenitor cell therapy for patients with ischemic diseases.5. ConclusionThe clinical application of anti-angiogenic therapeutics for cancer and neovascular AMD has been more successful than that of pro-angiogenic therapeutics for cardiovascular diseases, since the interruption of angiogenic signaling is tech-nically feasible compared with the re-construction of vascular structure.6. PerspectivesHuman diseases, such as cancer, cardiovascular diseases, hypertension and diabetes mellitus, occur and progress as a result of mutual interactions of genetic factors and envi-ronmental factors (40,41). Genetic factors include common variations and rare mutations caused by single nucleotide changes or germline copy number changes, while environ-mental factors include infectious agents, chemicals, X-rays, ultra-violet light and lifestyle habits, such as smoking, high calorie diet, high salt intake, low fruit/vegetable intake and infrequent exercise. Epigenetic changes and microRNA (miRNA) dysregulation have also been implicated in human diseases. Although the strategy and device used are signifi-cantly distinct in anti- and pro-angiogenic therapeutics, the effectiveness of both these therapeutic modalities is affected by genetic variations, epigenetic alterations and miRNAs. Genetics and epigenetics, miRNAs and signaling networks are discussed in the following section as issues to be further addressed.The single nucleotide polymorphisms (SNPs), rs699947 (-2578C>A), rs833061 (-1498T>C) and rs2010963 (-634C>G), are located within the promoter region or 5'-untranslated region (UTR) of the VEGF gene. RCC patients with an ACG haplotype for the rs699947, rs833061 and rs2010963 SNPs have a risk of sunitinib-induced hypertension (42), whereas RCC patients with a CC genotype of rs699947, a TT genotype of rs833061 and a CC genotype of rs2010963 are the worst responders to sunitinib (43). The CC genotype of rs2010963 is associated with higher serum levels of VEGF protein in patients with proliferative diabetic retinopathy (44), and breast cancer patients with a higher plasma VEGF concentration are the worst responders to bevacizumab (45). The therapeutic and adverse effects of anti-angiogenic drugs targeting VEGF signaling cascades are affected by SNPs of the VEGF gene that regulate circulating VEGF levels. Common variants are genotyped by using array-based technology, while rare vari-ants by using personal genome sequencing. Genotypes of the VEGF gene, as well as other genes encoding angiogenesis regulators should be utilized for the selection and dosage of anti- and pro-angiogenic drugs.Epigenetics regulates lineage‑specific or disease‑associ-ated transcription depending on DNA methylation, histone modifications or non‑coding RNAs, rather than changes in the genomic DNA sequence itself (46,47). Chronic inflamma-tion associated with epigenetic changes gives rise to various types of cancer, such as colorectal, breast and gastric cancer and is known as the concept of field cancerization (48‑50). In addition, epigenetic alterations associated with smoking or environmental pollution are associated with the increased risk of cardiovascular diseases (47). These facts indicate that cancer and non‑cancerous diseases occur from a field of epigenetic alterations. Polymer-based hydrogel film may be utilized for the delivery of drugs targeting epigenetic processes and angiogenesis for the pro-angiogenic therapy of cardiovascular diseases.miRNAs are single-stranded RNAs of approximately 22 nucleotides in length, which are derived from non-coding primary miRNAs as a result of sequential processing by Drosha, Dicer and RISC. miRNAs bind to complementary sequences of target mRNAs through perfect or imperfect base-pairing, thus repressing target genes through direct cleavage or translational repression, respectively (12,51). miR-15, miR-16, miR-20a and miR-20b are anti-angiogenic miRNAs targeting VEGF mRNA, whereas the miR-17-92 cluster, miR-27b and let-7f are pro-angiogenic miRNAs (52,53 and references therein). A hot topic in this field are the circulating miRNAs in the blood plasma or serum, which are carried by nano-sized exosomes or micro-sized microvesicles (54,55). Expression profiles of exosomal miRNAs are applied for the differential diagnosis of schizophrenia and bipolar disorder (56), while microvesicles derived from EPCs are involved in kidney protec-tion from ischemia-reperfusion injury in a miRNA-dependent manner (57). Circulating miRNAs in exosomes and microvesicles are functional biomarkers to be used for the diagnostics and prognostics of human diseases (58), while synthetic miRNAs in polymer-based hydrogel nanoparticles are applicable for therapeutics.VEGF, FGF and ANGPTs transduce signals through receptor tyrosine kinases (RTKs). Spatio-temporal interac-tions of RTK, Notch, TGF-β, Hedgehog and WNT signaling cascades regulate a variety of processes during embryogenesis, adult-tissue homeostasis and pathogenesis, such as carcinogen-esis (11). The sequential delivery of ANGPT2 and ANGPT1 using AAV effectively promotes post-ischemic angiogenesis, as ANGPT2 and ANGPT1 are involved in vascular desta-bilization and subsequent maturation during angiogenesis, respectively (59). A more profound understanding of the spatio-temporal interactions of regulatory signaling cascades and advances in personal genotyping and circulating miRNA profiling are mandatory to optimize the permutation and dosage of drugs for targeted therapeutics. AcknowledgementsThe present study was supported in part by the National Cancer Center Research and Development Fund.KATOH: ANTI-ANGIOGENIC AND PRO-ANGIOGENIC THERAPY 766References1. Carmeliet P: Angiogenesis in life, disease and medicine. Nature 438: 932-936, 2005.2. Ferrara N and Kerbel RS: Angiogenesis as a therapeutic target. Nature 438: 967-974, 2005.3. Folkman J: Angiogenesis: an organizing principle for drug discovery? Nat Rev Drug Discov 6: 273-286, 2007.4. Carmeliet P and Jain RK: Molecular mechanisms and clinical applications of angiogenesis. Nature 473: 298-307, 2011.5. Gaengel K, Genové G, Armulik A and Betsholtz C: Endothelial-mural cell signaling in vascular development and angiogenesis. Arterioscler Thromb Vasc Biol 29: 630-638, 2009.6. Coultas L, Chawengsaksophak K and Rossant J: Endothelial cells and VEGF in vascular development. Nature 438: 937-945, 2005.7. Olsson AK, Dimberg A, Kreuger J and Claesson-Welsh L: VEGF receptor signalling-in control of vascular function. Nat Rev Mol Cell Biol 7: 359-371, 2006.8. Presta M, Dell'Era P, Mitola S, et al: Fibroblast growth factor/fibroblast growth factor receptor system in angiogenesis. Cytokine Growth Factor Rev 16: 159-178, 2005.9. Fagiani E and Christofori G: Angiopoietins in angiogenesis. Cancer Lett 328: 18-26, 2013.10. Bridges E, Oon CE and Harris A: Notch regulation of tumor angiogenesis. Future Oncol 7: 569-588, 2011.11. Katoh M and Katoh M: WNT signaling pathway and stem cell signaling network. Clin Cancer Res 13: 4042-4045, 2007. 12. Katoh Y and Katoh M: Hedgehog signaling, epithelial-to-mesen-chymal transition and miRNA (Review). Int J Mol Med 22: 271-275, 2008.13. Rivkin E, Almeida SM, Ceccarelli DF, et al: The linear ubiquitin‑specific deubiquitinase gumby regulates angiogenesis. Nature 498: 318-324, 2013.14. Diehl AM: Neighborhood watch orchestrates liver regeneration. Nat Med 18: 497-499, 2012.15. Katoh M and Nakagama H: FGF receptors: cancer biology and therapeutics. Med Res Rev: May 21, 2013 (Epub ahead of print).16. Dewhirst MW, Cao Y and Moeller B: Cycling hypoxia and free radicals regulate angiogenesis and radiotherapy response. Nat Rev Cancer 8: 425-437, 2008.17. Bao B, Azmi AS, Ali S, et al: The biological kinship of hypoxia with CSC and EMT and their relationship with deregulated expression of miRNAs and tumor aggressiveness. Biochim Biophys Acta 1826: 272-296, 2012.18. 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Penn JS, Madan A, Caldwell RB, et al: Vascular endothelial growth factor in eye disease. Prog Retin Eye Res 27: 331-371, 2008.31. Rajagopalan S, Mohler ER 3rd, Lederman RJ, et al: Regional angiogenesis with vascular endothelial growth factor in periph-eral arterial disease: a phase II randomized, double-blind, controlled study of adenoviral delivery of vascular endothelial growth factor 121 in patients with disabling intermittent claudi-cation. Circulation 108: 1933-1938, 2003.32. Roth DA, McKirnan MD, Canestrelli I, et al: Intracoronary delivery of an adenovirus encoding fibroblast growth factor‑4 in myocardial ischemia: effect of serum antibodies and previous exposure to adenovirus. Hum Gene Ther 17: 230-238, 2006. 33. Sarkar N, Rück A, Källner G, et al: Effects of intramyocardial injection of phVEGF-A165 as sole therapy in patients with refractory coronary artery disease-12-month follow-up: angio-genic gene therapy. J Intern Med 250: 373-381, 2001.34. Belch J, Hiatt WR, Baumgartner I, et al: Effect of fibroblast growth factor NV1FGF on amputation and death: a randomised placebo-controlled trial of gene therapy in critical limb ischaemia. Lancet 377: 1929-1937, 2011.35. Formiga FR, Tamayo E, Simón-Yarza T, et al: Angiogenic therapy for cardiac repair based on protein delivery systems. Heart Fail Rev 17: 449-473, 2012.36. Hoare TR and Kohane DS: Hydrogels in drug delivery: Progress and challenges. Polymer 49: 1993-2007, 2008.37. Aranguren XL, McCue JD, Hendrickx B, et al: Multipotent adult progenitor cells sustain function of ischemic limbs in mice. J Clin Invest 118: 505-514, 2008.38. Meirelles L da S, Fontes AM, Covas DT and Caplan AI: Mechanisms involved in the therapeutic properties of mesen-chymal stem cells. Cytokine Growth Factor Rev 20: 419-427, 2009.39. Suzuki H, Shibata R, Kito T, et al: Comparative angiogenic activities of induced pluripotent stem cells derived from young and old mice. PLoS One 7: e39562, 2012.40. Lichtenstein P, Holm NV, Verkasalo PK, et al: Environmental and heritable factors in the causation of cancer-analyses of cohorts of twins from Sweden, Denmark, and Finland. N Engl J Med 343: 78-85, 2000.41. Zimmet P, Alberti KG and Shaw J: Global and societal implica-tions of the diabetes epidemic. Nature 414: 782-787, 2001. 42. Eechoute K, van der Veldt AA, Oosting S, et al: Polymorphisms in endothelial nitric oxide synthase (eNOS) and vascular endothelial growth factor (VEGF) predict sunitinib-induced hypertension. Clin Pharmacol Ther 92: 503-510, 2012.43. Scartozzi M, Bianconi M, Faloppi L, et al: VEGF and VEGFR polymorphisms affect clinical outcome in advanced renal cell carcinoma patients receiving first‑line sunitinib. Br J Cancer 108: 1126-1132, 2013.44. Petrovič MG, Korošec P, Košnik M, et al: Local and genetic determinants of vascular endothelial growth factor expression in advanced proliferative diabetic retinopathy. Mol Vis 14: 1382-1387, 2008.45. Miles DW, de Haas SL, Dirix LY, et al: Biomarker results from the AVADO phase 3 trial of first‑line bevacizumab plus docetaxel for HER2-negative metastatic breast cancer. Br J Cancer 108: 1052-1060, 2013.46. Baylin SB and Jones PA: A decade of exploring the cancer epigenome-biological and translational implications. Nat Rev Cancer 11: 726-734, 2011.47. Ordovás JM and Smith CE: Epigenetics and cardiovascular disease. Nat Rev Cardiol 7: 510-519, 2010.48. Issa JP, Ahuja N, Toyota M, et al: Accelerated age-related CpG island methylation in ulcerative colitis. Cancer Res 61: 3573-3577, 2001.49. Kang GH, Lee HJ, Hwang KS, et al: Aberrant CpG island hypermethylation of chronic gastritis, in relation to aging, gender, intestinal metaplasia, and chronic inflammation. Am J Pathol 163: 1551-1556, 2003.50. Rivenbark AG and Coleman WB: Field cancerization in mammary carcinogenesis - Implications for prevention and treatment of breast cancer. Exp Mol Pathol 93: 391-398, 2012.51. Wittmann J and Jäck HM: Serum microRNAs as powerful cancer biomarkers. Biochim Biophys Acta 1806: 200-207, 2010.52. Kuehbacher A, Urbich C and Dimmeler S: Targeting microRNA expression to regulate angiogenesis. Trends Pharmacol Sci 29: 12-15, 2008.INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE 32: 763-767, 201376753. Wang S and Olson EN: AngiomiRs - key regulators of angiogen-esis. Curr Opin Genet Dev 19: 205-211, 2009.54. Gallo A, Tandon M, Alevizos I and Illei GG: The majority of microRNAs detectable in serum and saliva is concentrated in exosomes. PLoS One 7: e30679, 2012.55. Turchinovich A, Weiz L and Burwinkel B: Extracellular miRNAs: the mystery of their origin and function. Trends Biochem Sci 37: 460-465, 2012.56. Banigan MG, Kao PF, Kozubek JA, et al: Differential expression of exosomal microRNAs in prefrontal cortices of schizophrenia and bipolar disorder patients. PLoS One 8: e48814, 2013.57. Cantaluppi V, Gatti S, Medica D, et al: Microvesicles derived from endothelial progenitor cells protect the kidney from ischemia-reperfusion injury by microRNA-dependent repro-gramming of resident renal cells. Kidney Int 82: 412-427, 2012.58. Lässer C: Exosomal RNA as biomarkers and the therapeutic potential of exosome vectors. Expert Opin Biol Ther 12 (Suppl 1): S189-S197, 2012.59. Qin D, Trenkwalder T, Lee S, et al: Early vessel destabilization mediated by Angiopoietin-2 and subsequent vessel maturation via Angiopoietin-1 induce functional neovasculature after ischemia. PLoS One 8: e61831, 2013.。

地黄叶斑病病原鉴定及室内药效检测

地黄叶斑病病原鉴定及室内药效检测

河南农业科学,2024,53(4):92⁃101Journal of Henan Agricultural Sciencesdoi:10.15933/ki.1004-3268.2024.04.010地黄叶斑病病原鉴定及室内药效检测李海骋1,王繁珍2,姜永成3,宋欣3,陈招荣1(1.天津农学院园艺园林学院,天津300384;2.天津农学院计算机与工程技术学院,天津300384;3.天津农学院工程技术学院,天津300384)摘要:为明确天津市蓟州区地黄叶斑病病原种类及生物学特性,筛选防治地黄叶斑病病原菌的有效农药,通过采集病叶、菌株分离、显微观察、离体回接以及ITS 、EF 1-α、Tub 多基因序列比对和进化树分析的方法,对地黄叶斑病致病菌进行分离纯化、形态学鉴定、致病性鉴定以及分子生物学鉴定,并对分离菌在3种培养基、4种碳氮源条件下的生物学特性进行研究,同时选取4种杀菌剂对其进行毒力测定。

结果表明,从天津市蓟州区地黄叶斑病发病叶片部位分离出的病原菌A1为木贼镰孢菌(Fusarium equiseti )。

生物学特性研究表明,该菌最适培养基、氮源、碳源分别为Czapek 培养基、甘氨酸、蔗糖。

室内药效检测结果表明,45%咪鲜胺水乳剂对该病原菌的抑制效果最好,半效应质量浓度(EC 50)为63.69mg/L ,对病原菌菌丝生长的抑制率最高可达83.64%;75%百菌清可湿性粉剂的抑制效果最差,EC 50为355.06mg/L ,对病原菌菌丝生长的抑制率最高为64.63%。

综上,天津市蓟州区地黄叶斑病病原菌为木贼镰孢菌(F.equiseti ),45%咪鲜胺水乳剂对地黄叶斑病病原菌的防治效果最好。

关键词:地黄;叶斑病;木贼镰孢菌;生物学特性;药剂筛选中图分类号:S435.672文献标志码:A文章编号:1004-3268(2024)04-0092-10收稿日期:2023-07-17基金项目:河北省重点研发计划项目(22347402D )作者简介:李海骋(2000-),男,河南西平人,在读本科生,研究方向:植物病害检测鉴定。

美国阔叶木外销委员会对木制品生命周期评估研究的初步成果

美国阔叶木外销委员会对木制品生命周期评估研究的初步成果
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IBM和斯坦福大学研制出新型催化剂

IBM和斯坦福大学研制出新型催化剂
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岛屿生物地理学理论与生物多样性保护

岛屿生物地理学理论与生物多样性保护

图 1 自 MacArthur 和 Wilson 1963 太平洋诸岛陆地和淡水鸟种数与岛屿面积之间的关系
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此种情况也表示 如果原始生态系统只有 10 的面积保存下来 那么 该生态系统有 50 的 物种丢失 如果 1 的面积保存下来,则该生态系统中有 75 的物种丢失 由上表可以看出 大部分分类群的 z 值介于 0 18 0 35 之间 当然 如果面积与岛屿的海拔高度和岛屿高大 陆的距离有关 那么 z 值可能增加 同时 经过对数转换后 z 值还取决于我们所观测的目标 是隔离种群 Isolate 还是样本 Sample 在这里 隔离种群指组成一个生态群落的全部 个体 而样本则是群落中的部分个体 一般说来 样本的 z 值要比隔离种群小 前者一般为 0 12 0 17 而后者则多介于 0 18 0 35 之间 Preston 1962 MacArthur 和 Wilson 1967 种 面积曲线以及 z 值的狭窄范围主要是由于下列两方面引起的 其一是个体数目和 面积近似直线的关系 其二是个体总数和物种数目之间的关系非常接近对数正态分布 或者 说物种的多度分布 Distribution of species abundance 是一对数正态分布曲线 对于种

Graph Regularized Nonnegative Matrix

Graph Regularized Nonnegative Matrix

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1 INTRODUCTION
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techniques for matrix factorization have become popular in recent years for data representation. In many problems in information retrieval, computer vision, and pattern recognition, the input data matrix is of very high dimension. This makes learning from example infeasible [15]. One then hopes to find two or more lower dimensional matrices whose product provides a good approximation to the original one. The canonical matrix factorization techniques include LU decomposition, QR decomposition, vector quantization, and Singular Value Decomposition (SVD). SVD is one of the most frequently used matrix factorization techniques. A singular value decomposition of an M Â N matrix X has the following form: X ¼ UÆVT ; where U is an M Â M orthogonal matrix, V is an N Â N orthogonal matrix, and Æ is an M Â N diagonal matrix with Æij ¼ 0 if i 6¼ j and Æii ! 0. The quantities Æii are called the singular values of X, and the columns of U and V are called

Aging of Population

Aging of Population

Aging of PopulationLeonid A. Gavrilov and Patrick HeuvelineThis is a manuscript of our article in The Encyclopedia of Population. New York, Macmillan Reference USA, 2003.[Note: This original manuscript is slightly different from the final publication because of small editorial changes.]Reference to the published article:Gavrilov L.A., Heuveline P.“Aging of Population.”In: Paul Demeny and Geoffrey McNicoll (Eds.)The Encyclopedia of Population. New York, Macmillan Reference USA, 2003Available at:/servlet/ItemDetailServlet?region=9&imprint=000&titleCode=M333&ty pe=4&id=174029Aging of population(also known as demographic aging, and population aging) is a summary term for shifts in the age distribution (i.e., age structure) of a population toward older ages. A direct consequence of the ongoing global fertility transition (decline) and of mortality decline at older ages, population aging is expected to be among the most prominent global demographic trends of the 21st century. Population aging is progressing rapidly in many industrialized countries, but those developing countries whose fertility declines began relatively early also are experiencing rapid increases in their proportion of elderly people. This pattern is expected to continue over the next few decades, eventually affecting the entire world. Population aging has many important socio-economic and health consequences, including the increase in the old-age dependency ratio. Itpresents challenges for public health (concerns over possible bankruptcy of Medicare and related programs) as well as for economic development (shrinking and aging of labor force, possible bankruptcy of social security systems).Defining and measuring population agingAs the study of population aging is often driven by a concern over its burdening of retirement systems, the aging of population is often measured by increases in the percentage of elderly people of retirement ages. The definition of retirement ages may vary but a typical cutoff is 65 years, and nowadays a society is considered relatively old when the fraction of the population aged 65 and over exceeds 8-10%. By this standard, the percentage of elderly people in the United States stood at 12.6% in 2000, compared with only 4.1% in 1900 and a projected increase to 20% by the year 2030.A related measure of population aging is the elderly dependency ratio (EDR): the number of individuals of retirement ages compared to the number of those of working ages. For convenience, working ages may be assumed to start at age 15, although increasing proportions of individuals pursue their education beyond that age and remain, meanwhile, financially dependent, either on the state or, increasingly, on their parents or bank managers. The ratio of the elderly dependent population to the economically active (working) population is also known as old-age dependency ratio, age-dependency ratio or elderly dependency burden and is used to assess intergenerational transfers, taxation policies, and saving behavior.Another indicator of the age structure is the aging index (sometimes referred to as the elder-child ratio), defined as the number of people aged 65 and over per 100 youths under age 15. In 2000, only a few countries (Germany, Greece, Italy, Bulgaria, and Japan) had more elderly than youth (aging index above 100). By 2030, however, the aging index is projected to exceed 100 in all developed countries, and the index of several European countries and Japan are even expected to exceed 200. To date, aging indexes are much lower in developing countries than in the developed world, but the proportional rise in the aging index in developing countries is expected to be greater than in developed countries.These indicators of population aging are mere head-count ratios (HCR), that is, they simply relate the number of individuals in large age categories.These indicators fail to take into account the age distribution within these large categories, in particular among the elderly. When the fertility and mortality trends responsible for population aging have been fairly regular over time, the population growth is positively correlated with age (i.e., the oldest age groups are growing fastest). This implies that if the proportion of the population over age 65 is increasing, within that 65-and-over population the proportion over, say, age 80 is also increasing. As health, financial situation, and consumption patterns may vary greatly between 65 year-olds and 80 year-olds, simple ratios conceal important heterogeneity in the elderly population. Increasingly, attention is paid to the "oldest olds" (typically age 80 and over). A long-time subject of curiosity, the number of centenarians is growing even faster. Estimated at 180,000 worldwide in 2000, it could reach 1 million by 2030 (United Nations 2001).The second class of indicators for population aging is the group of statistical measures of location (median, mean and modal ages of population). The median age -- the age at which exactly half the population is older and another half is younger -- is perhaps the most widely used indicator. For the year 2000, the median age in the United States was 36 years, a typical age for most developed countries and twice the median age for Africa (United Nations 2001). Because it is more sensitive to changes at the right-hand tail of the age distribution (i.e., the oldest old ages), the mean age of population might in fact be preferred to the median age to study the dynamics of population aging.Since population aging refers to changes in the entire age distribution, any single indicator might appear insufficient to measure it. The age distribution of population is often very irregular, reflecting the scars of the past events (wars, depression etc.), and it cannot be described just by one number without significant loss of information. Were the age distribution to change in a very irregular fashion over the age range, for instance, much information would be lost by a single-index summary. Therefore, perhaps the most adequate approach to study population aging is to explore the age distribution through a set of percentiles, or graphically by analyzing the population pyramids. Demographers commonly use population pyramids to describe both age and sex distributions of populations. Youthful populations are represented by pyramids with a broad base of young children and a narrow apex of older people, while older populations are characterized bymore uniform numbers of people in the age categories.Figures 1-5 About HereDemographic determinants of population agingTo understand the demographic factors that cause population aging, demographers often refer to stable populations (Preston et al. 2001). This population model assumes that age-specific fertility and mortality rates remain constant over time, and this results in a population with an age distribution that stabilizes and eventually becomes time invariant as well. Conversely, this theoretical model suggests that any change in age structure, and population aging in particular, can only be caused by changes in fertility and mortality rates. The influence of changes in fertility rates on population aging is perhaps less intuitive than that of mortality rates. Everything else constant, however, a fertility decline reduces the size of the most recent birth cohorts relative to the previous birth cohorts, hence reducing the size of the youngest age groups relative to that of the older ones.The effects of changes in mortality rates on population aging appear more intuitive, but are in fact more ambiguous. If increases in the human life span are correctly linked to population aging, reductions in mortality rates do not necessarily contribute to population aging. More specifically, mortality declines among infants, children and persons younger than the population mean age tend to lower the population mean age. A moment of thought suggests that indeed a reduction of neonatal mortality (i.e., death in the first month of life) adds individual at age 0 and should lead to the same partial alleviation of population aging as an increase in childbearing.Population aging is thus related to the demographic transition, that is the processes that lead a society from a demographic regime characterized by high rates of fertility and mortality to another one with lower fertility and mortality rates. In the course of this transition, the age structure is subjected to different influences. In the typical sequence, the transition begins with successes in preventing infectious and parasitic diseases that benefit infants and young children most. The resulting improvement in life expectancy at birth occurs while fertility tends to remain unchanged, thereby producing large birth cohorts and an expanding proportion of children relative to adults. Other things being equal, this initial decline in mortality generates a younger population age structure.After initial and sometimes very rapid gains in infant and child mortality have been achieved, further mortality declines increasingly benefit older ages and are eventually accompanied by fertility declines. Both changes contribute to reverse the early effect of mortality decline on the age structure, and this synergy is known as the double aging process. This corresponds to the experience of most developed countries today, but further decomposition suggest that their history of declining mortality is the dominant factor in current aging (Preston, Himes and Eggers 1989). Mortality declines continue in these countries and the decrease in mortality rates among the oldest-old (85+ years) has actually accelerated since the 1950s (Gavrilov, Gavrilova, 1991). This latest phase of mortality decline, which is concentrated in the older age groups, is becoming an important determinant of population aging, particularly among women.The rate of population aging may also be modulated by migration. Immigration usually slows down population aging (in Canada and Europe, for example), because immigrants tend to be younger and have more children. On the other hand, emigration of working-age adults accelerates population aging, as it is observed now in some Caribbean nations. Population aging in these countries is also accelerated by immigration of elderly retirees from other countries, and return migration of former emigrants who are above the average population age. Some demographers expect that migration will have a more prominent role in population aging in the future, particularly in low-fertility countries with stable or declining population size. The effects of migration on population aging are usually stronger in smaller populations, because of higher relative weight (proportion) of migrants in such populations.Dynamics of population agingThe current level and pace of population aging vary widely by geographic region, and usually within regions as well, but virtually all nations are now experiencing growth in their numbers of elderly residents (for selected regions and countries, see Table 1). The percentage of world population aged 65 and over only increased from 5.2% in 1950 to 6.9% in 2000. In Europe, however, the proportion is 14.7% in 2000. For a long time, the highest proportions where found in Northern Europe (e.g., 10.3% in Sweden in 1950), but had moved South by 2000 (18.1% in Italy). The proportions of elderly arelower outside of Europe with the notable exception of Japan where it increased from 4.9% in 1950 to 17.2% in 2000. The age structure of the United States continues to be marked by the large birth cohorts of the baby boom (people born from 1946 through 1964), not yet aged 65. The proportion of the elderly population in the U.S., 12.3% in 2000, hence remains low compared to the developed-country standards. .Table 1 About HerePopulation aging has the following notable features:(1) The most rapid growth occurs in the oldest age groups – the oldest-old (80+ or 85+ years) and centenarians (100+ years) in particular. In other words, population aging is becoming “deeper” with preferential accumulation of particularly old and frail people.(2) Population aging is particularly rapid among women, resulting in “feminization” of population aging (because of lower mortality rates among women). For example, in the United States, there were 20.6 million older women and 14.4 million older men in 2000, or a sex ratio of 143 women for every 100 men. The female to male ratio increases with age reaching 245 for persons 85 and over.(3) Another consequence of lower female mortality is the fact that almost half of older women (45%) in 2000 were widows, thus living without spousal support.(4) Population aging also causes changes in living arrangements resulting in increasing number of older people living alone (about 30% of all non-institutionalized older persons in 2000 lived alone in the United States).(5) Since older persons have usually lower income and a higher proportion of them are living below the poverty line, population aging is associated with poverty, particularly in developing countries.Projections of population aging in the 21st centuryFuture population aging will depend on future demographic trends, but most demographers agree that the fertility and mortality changes that would be required to reverse population aging in the coming decades are very unlikely. According to current population forecasts, population aging in the first half of this century should exceed that of the second half of the 20thcentury. For the world as a whole, the elderly will grow from 6.9% of the population in 2000 to a projected 19.3% in 2050 (Table 1). In other words, the world average should then be higher than the current world record. All regions are expected to see an increase, although it should be milder in some regions, such as Africa where the projected increase is from 3.3% in 2000 to 6.9% in 2050. But in Latin America and the Caribbean, the increase should be from 5.4% in 2000 to 16.9% in 2050, higher than the current European average. The increase should be even more spectacular in China: from 6.9% in 2000 to 22.7% in 2050.If population aging is thus far from limited to the most developed regions, the countries of these regions will likely continue to experience the highest proportions ever known. The forecasts suggest 29.2% of elderly in the European population as a whole, but more than 30% in a number of specific European countries, and perhaps as much as 36.4% in Japan. Again, the forecasted increase from 12.3% in 2000 to 21.1% in 2050 appears less dramatic in the U.S. than in other most developed countries.There is of course some uncertainty with any forecast, but it is important to note that previous population forecasts underestimated rather than overstated the current pace of population aging. Before the 1980s the process of population aging was considered as an exclusive consequence of fertility decline and it was predicted that the pace of population aging would decrease after stabilization of fertility rates at some low levels. Rapid decline in old-age mortality observed in developed countries in the last decades of the 20th century significantly accelerated population aging. Now the old-age mortality trends are becoming the key demographic component in projecting the size and composition of the world's future elderly population. Current and future uncertainties about changing mortality may produce widely divergent projections of the size of tomorrow's elderly population. For example, the U.S. Census Bureau's middle-mortality series projection suggests that there will be 14.3 million people aged 85 and over in the year 2040, while the low-mortality (i.e., high life expectancy) series implies 16.8 million. Alternative projections, using assumptions of lower death rates and higher life expectancies, have produced estimates from 23.5 to 54 million people aged 85 and over in 2040 in the United States (see Kinsella, Velkoff, 2001).Social and economic implications of population agingWhile population aging represents, in one sense, a success story for mankind (massive survival to old ages has become possible), it also poses profound challenges to public institutions that must adapt to a changing age structure.The first challenge is associated with dramatic increase in the older retired population relative to the shrinking population of working ages, which creates social and political pressures on social support systems. In most developed countries, rapid population aging places a strong pressure on social security programs. For example, the U.S. social security system may face a profound crisis if no radical modifications are enacted. Cuts in benefits, tax increases, massive borrowing, lower cost-of-living adjustments, later retirement ages, or a combination of these elements are now discussed as the possible painful policies, which may become necessary in order to sustain the pay-as-you-go public retirement programs such as Medicare and Social Security.Population aging is also a great challenge for the health care systems. As nations age, the prevalence of disability, frailty, and chronic diseases (Alzheimer’s disease, cancer, cardiovascular and cerebrovascular diseases, etc.) is expected to increase dramatically. Some experts raise concerns that the mankind may become a “global nursing home” (Eberstadt, 1997).The aging of the population is indeed a global phenomenon that requires international coordination of national and local actions. The United Nations and other international organizations developed recommendations intended to mitigate the adverse consequences of population aging. These recommendations include reorganization of social security systems, changes in labor, immigration and family policies, promotion active and healthy life styles, and more cooperation between the governments in resolving socioeconomic and political problems posed by population aging.On the positive side, the health status of older people of a given age is improving over time now, because more recent generations have a lower disease load. Older people can live vigorous and active lives until a much later age than in the past and if they're encouraged to be productive, they can be economic contributors as well. Also the possibility should not be excluded that current intensive biomedical anti-aging studies may help to extend the healthy and productive period of human life in the future (de Greyet al., 2002).Word Count: 2,793BIBLIOGRAPHYAdministration on Aging. 2001. A Profile of Older Americans: 2001. U.S.Department of Health and Human Services.De Grey, Aubrey D. N., Leonid Gavrilov, S. Jay Olshansky, L. Stephen Coles, Richard G. Cutler, Michael Fossel, and S. MitchellHarman. 2002. “Antiaging technology and pseudoscience.” Science, 296: 656-656.Eberstadt, N. 1997. “World population implosion?” Public Interest, 129: 3-22.Gavrilov, Leonid A., and Natalia S. Gavrilova. 1991. The Biology of Life Span: A Quantitative Approach. NY, etc.: Harwood Academic Publ.. Kinsella, Kevin, and Victoria A. Velkoff. 2001. An Aging World: 2001. U. S.Census Bureau, Series P95/01-1, Washington, DC: U.S. GovernmentPrinting Office.Lutz, Wolfgang, Warren Sanderson, and Sergei Scherbow. 2001. “The end of world population growth.” Nature 412: 543-545.Preston, Samuel H., Christine Himes, and MitchellEggers. 1989. “Demographic conditions responsible for populationaging.” Demography 26: 691-704.Preston Samuel H., Patrick Heuveline, and Michel Guillot. 2001.Demography. Measuring and Modeling Population Processes. Oxford: Blackwell.United Nations 2001. World population prospects: the 2000 revision. New York: United Nations.Table 1. Dynamics of Population Aging in the Modern World Observed and Forecasted Percentages of the Elderly (65+ years) in Selected Areas, Regions, and Countries of the World: 1950, 2000 and 2050.Major Area, region and country 1950 20005.2%6.9%WorldAfrica 3.2% 3.3% Latin America and the Caribbean 3.7% 5.4% China 4.5% 6.9% India 3.3% 5.0% Japan 4.9%17.2% Europe8.2%14.7% Italy8.3%18.1% Germany9.7%16.4% Sweden10.3%17.4% U.S.A.8.3%12.3% Source: United Nations 2001.Figure 1. Youthful population.Figure 2. Aged population.Figure 3. Intermediate population.Figure 4. Projected extremely old population.Figure 5. Projected old population.。

symmetrical

symmetrical

symmetricalSymmetricalIntroductionSymmetry is a fundamental concept in various fields of science, art, mathematics, and nature itself. It refers to a balanced arrangement of parts on either side of a central axis, resulting in a mirror image. The concept of symmetry has intrigued humans for centuries and has been used to create aesthetically pleasing designs, to study patterns in nature, and to understand fundamental principles in various disciplines. In this document, we will delve into the concept of symmetry, explore its different forms, discuss its significance, and look at some real-world examples.Understanding SymmetrySymmetry can be defined as a balanced and harmonious arrangement of parts. It can be observed in different aspects of our daily lives, ranging from the human body to plants, animals, and even inanimate objects. The concept ofsymmetry can be categorized into different types based on the nature of the objects being observed.Types of Symmetry1. Reflectional Symmetry: Also known as mirror symmetry, reflectional symmetry occurs when an object can be divided into two equal halves along a line or a plane. The two halves are mirror images of each other. Examples of objects exhibiting reflectional symmetry include butterflies, human faces, and buildings that have symmetrical facades.2. Rotational Symmetry: Rotational symmetry occurs when an object can be rotated around a central point and still maintains its original appearance. The object may have multiple axes of rotational symmetry. Examples of objects with rotational symmetry include wheels, flowers like sunflowers, and snowflakes.3. Translational Symmetry: Translational symmetry occurs when an object can be shifted along a specific direction and still maintains its original appearance. This type of symmetry is commonly observed in patterns such as wallpaper designs, textiles, and some architectural elements.4. Rotational-Reflectional Symmetry: This is a combination of both rotational and reflectional symmetries. An object with rotational-reflectional symmetry can be both rotated and reflected to create a perfect match. Examples include snowflakes and many intricate geometric designs.The Significance of SymmetrySymmetry holds great importance in various disciplines, from mathematics and physics to biology and art. Here are some ways symmetry influences these fields:1. Mathematics: Symmetry is an essential concept in the field of mathematics, exhibiting deep connections with geometry, group theory, and topology. Symmetry is used to study patterns, shapes, and fundamental principles in these areas.2. Physics: Symmetry plays a crucial role in physics, particularly in quantum mechanics and particle physics. The laws of physics are often described by symmetrical equations and principles. Symmetry has aided in predicting the existence of new particles and understanding the behavior of fundamental forces.3. Biology: Symmetry is evident in the natural world, from the bilateral symmetry of animals like insects and humans to the radial symmetry of plants like flowers. It is believed that symmetrical features in organisms are associated with better health and genetic fitness.4. Art and Design: Symmetry has been utilized by artists and designers throughout history to create aesthetically pleasing compositions. It is seen in various art forms, architectures, and even in the human perception of beauty. Symmetry provides a sense of balance and harmony in visual compositions.Real-World Examples of Symmetry1. Taj Mahal: The iconic Taj Mahal in India is known for its symmetrical design. The mausoleum is perfectly mirrored along a central axis, creating a stunning reflection in the surrounding water.2. Butterfly Wings: The intricate patterns on butterfly wings often exhibit reflectional symmetry. The wings are divided into two equal halves, each mirroring the other.3. Snowflakes: Snowflakes are renowned for their symmetrical and intricate structures. Each snowflake exhibits both rotational and reflectional symmetries, making them unique and beautiful.4. The Sunflower: The spiral arrangement of seeds in a sunflower exhibits rotational symmetry. The seeds form concentric circles, giving the flower a harmonious and balanced appearance.ConclusionWhether found in nature, mathematics, or art, symmetry is an intriguing concept that captivates our attention. The different types of symmetry, including reflectional, rotational, and translational, are present in various aspects of our lives. Symmetry plays a crucial role in understanding the world around us, from predicting the behavior of subatomic particles to appreciating the beauty of a natural flower. As we continue to explore the wonders of symmetry, we gain deeper insights into the principles that govern our universe and the underlying harmony that exists in our surroundings.。

苋属四种外来入侵植物及其近缘种繁育系统的比较研究毕业论文

苋属四种外来入侵植物及其近缘种繁育系统的比较研究毕业论文

本科毕业设计(论文)题目苋属四种外来入侵植物及其近缘种繁育系统的比较研究常熟理工学院本科毕业设计(论文)诚信承诺书本人郑重声明:所呈交的本科毕业设计(论文),是本人在导师的指导下,独立进行研究工作所取得的成果。

除文中已经注明引用的内容外,本论文不含任何其他个人或集体已经发表或撰写过的作品成果。

对本文的研究做出重要贡献的个人和集体,均已在文中以明确方式标明。

本人完全意识到本声明的法律结果由本人承担。

本人签名:日期:常熟理工学院本科毕业设计(论文)使用授权说明本人完全了解常熟理工学院有关收集、保留和使用毕业设计(论文)的规定,即:本科生在校期间进行毕业设计(论文)工作的知识产权单位属常熟理工学院。

学校有权保留并向国家有关部门或机构送交论文的复印件和电子版,允许毕业设计(论文)被查阅和借阅;学校可以将毕业设计(论文)的全部或部分内容编入有关数据库进行检索,可以采用影印、缩印或扫描等复制手段保存、汇编毕业设计(论文),并且本人电子文档和纸质论文的内容相一致。

保密的毕业设计(论文)在解密后遵守此规定。

本人签名:日期:导师签名:日期:苋属四种外来入侵植物及其近缘种繁育系统的比较研究摘要苋属(Amaranthus)中有很多为入侵广泛的外来入侵植物,通过其繁育系统的研究可以为进一步研究其繁殖特征与入侵性的关系提供基础资料。

本文以苋属中的反枝苋( A. retrofleus L. )、皱果苋( A. viridis L. )、刺苋(A. spinosus L.)和凹头苋(A. lividus L.)为实验材料,通过人工控制授粉的方法,对其繁育系统进行了野外生境下以及开放式大棚中的近缘种比较研究,并对开放式大棚实验中四种苋属的结实量做了统计。

结果表明,在开放性授粉和单个花序分枝套袋的情况下,反枝苋的结实率最高,分别为76.48%、71.68%,而四个近缘种均有较高的结实率,从高至低依次为:反枝苋、皱果苋、刺苋凹头苋,其具有的自交亲和性和自主结实特性可能有利于其入侵,但是其与入侵性并不成完全正相关。

2005-A global Malmquist productivity index

2005-A global Malmquist productivity index

A global Malmquist productivity indexJesu ´s T.Pastor a ,C.A.Knox Lovell b ,TaCentro de Investigacio ´n Operativa,Universidad Miguel Herna ´ndez,03206Elche (Alicante),SpainbDepartment of Economics,University of Georgia,Athens,GA 30602,USA Received 2June 2004;received in revised form 24January 2005;accepted 16February 2005Available online 23May 2005AbstractThe geometric mean Malmquist productivity index is not circular,and its adjacent period components can provide different measures of productivity change.We propose a global Malmquist productivity index that is circular,and that gives a single measure of productivity change.D 2005Elsevier B.V .All rights reserved.Keywords:Malmquist productivity index;Circularity JEL classification:C43;D24;O471.IntroductionThe geometric mean form of the contemporaneous Malmquist productivity index,introduced by Caves et al.(1982),is not circular.Whether this is a serious problem depends on the powers of persuasion of Fisher (1922),who dismissed the test,and Frisch (1936),who endorsed it.The index averages two possibly disparate measures of productivity change.Fa ¨re and Grosskopf (1996)state sufficient conditions on the adjacent period technologies for the index to satisfy circularity,and to average the same measures of productivity change.When linear programming techniques are used to compute and decompose the index,infeasibility can occur.Whether this is a serious problem depends on0165-1765/$-see front matter D 2005Elsevier B.V .All rights reserved.doi:10.1016/j.econlet.2005.02.013T Corresponding author.Tel.:+17065423689;fax:+17065423376.E-mail address:knox@ (C.A.K.Lovell).Economics Letters 88(2005)266–271/locate/econbasethe structure of the data.Xue and Harker(2002)provide necessary and sufficient conditions on the datafor LP infeasibility not to occur.We demonstrate that the source of all three problems is the specification of adjacent periodtechnologies in the construction of the index.We show that it is possible to specify a base periodtechnology in a way that solves all three problems,without having to impose restrictive conditions oneither the technologies or the data.Berg et al.(1992)proposed an index that compares adjacent period data using technology from a baseperiod.This index satisfies circularity and generates a single measure of productivity change,but it paysfor circularity with base period dependence,and it remains susceptible to LP infeasibility.Shestalova(2003)proposed an index having as its base a sequential technology formed from data ofall producers in all periods up to and including the two periods being compared.This index is immune toLP infeasibility,and it generates a single measure of productivity change,but it fails circularity and itprecludes technical regress.Thus no currently available Malmquist productivity index solves all three problems.We propose anew global index with technology formed from data of all producers in all periods.This index satisfiescircularity,it generates a single measure of productivity change,it allows technical regress,and it isimmune to LP infeasibility.In Section2we introduce and decompose the circular global index.Its efficiency change componentis the same as that of the contemporaneous index,but its technical change component is new.In Section3we relate it to the contemporaneous index.In Section4we provide an empirical illustration.Section5concludes.2.The global Malmquist productivity indexConsider a panel of i=1,...,I producers and t=1,...,T time periods.Producers use inputs x a R N+toproduce outputs y a R P+.We define two technologies.A contemporaneous benchmark technology isdefined as T c t={(x t,y t)|x t can produce y t}with k T c t=T c t,t=1,...,T,k N0.A global benchmarktechnology is defined as T c G=conv{T c1v...v T c T}.The subscript b c Q indicates that both benchmark technologies satisfy constant returns to scale.A contemporaneous Malmquist productivity index is defined on T c s asM scx t;y t;x tþ1;y tþ1ÀÁ¼D scx tþ1;y tþ1ðÞD scx t;y tðÞ;ð1Þwhere the output distance functions D c s(x,y)=min{/N0|(x,y//)a T c s},s=t,t+1.Since M c t(x t,y t,x t+1, y t+1)p M c t+1(x t,y t,x t+1,y t+1)without restrictions on the two technologies,the contemporaneous index is typically defined in geometric mean form as M c(x t,y t,x t+1,y t+1)=[M c t(x t,y t,x t+1,y t+1)ÂM c t+1(x t,y t,x t+1, y t+1)]1/2.A global Malmquist productivity index is defined on T c G asM Gcx t;y t;x tþ1;y tþ1ÀÁ¼D Gcx tþ1;y tþ1ðÞD Gcx t;y tðÞ;ð2Þwhere the output distance functions D c G(x,y)=min{/N0|(x,y//)a T c G}.J.T.Pastor,C.A.K.Lovell/Economics Letters88(2005)266–271267Both indexes compare (x t +1,y t +1)to (x t ,y t ),but they use different benchmarks.Since there is only one global benchmark technology,there is no need to resort to the geometric mean convention when defining the global index.M cGdecomposes as M G c x t ;y t ;x t þ1;f y t þ1ÀÁ¼D t þ1c x t þ1;y t þ1ðÞD t c x t ;y t ðÞÂD G c x t þ1;y t þ1ðÞD t þ1c x t þ1;y t þ1ðÞÂD t cx t ;y t ðÞD Gc x t ;y t ðÞ&'¼TE t þ1c x t þ1;y t þ1ðÞTE t c x t ;y t ðÞÂD G c Àx t þ1;y t þ1=D t þ1c x t þ1;y t þ1ðÞÁD G c x t ;y t =D t cx t ;y t ðÞÀÁ()¼EC c ÂBPG G ;t þ1cx t þ1;y t þ1ðÞBPG cx t ;y tðÞ()¼EC c ÂBPC c ;ð3Þwhere EC c is the usual efficiency change indicator and BPG c G,s V 1is a best practice gap between T c Gand T c s measured along rays (x s ,y s),s =t ,t +1.BPC c is the change in BPG c ,and provides a new measure of technical change.BPC c f 1indicates whether the benchmark technology in period t +1in the region[(x t +1,y t +1/D ct +1(x t +1,y t +1))]is closer to or farther away from the global benchmark technology than is the benchmark technology in period t in the region [(x t ,y t /D ct (x t ,y t ))].M c G has four virtues.First,like any fixed base index,M cGis circular,and since EC c is circular,so is BPC c .Second,each provides a single measure,with no need to take the geometric mean of disparate adjacent period measures.Third,but not shown here,the decomposition in (3)can be extended to generate a three-way decomposition that is structurally identical to the Ray and Desli (1997)decomposition of the contemporaneous index.M cGand M c share a common efficiency change component,but they have different technical change and scale components,and so M c Gp M c without restrictions on the technologies.Finally,the technical change and scale components of M c Gare immune to the LP infeasibility problem that plagues these components of M c .paring the global and contemporaneous indexes The ratioM G c =M c¼M G c =M t þ1cÀÁÂM G c =M t cÀÁÂÃ1=2¼D G cx t þ1;y t þ1=D t þ1c x t þ1;y t þ1ðÞÀÁD G c x t ;y t =D t þ1c x t ;y t ðÞÀÁ"#ÂD G c x t þ1;y t þ1=D t c x t þ1;y t þ1ðÞÀÁD G c x t ;y t =D t c x t ;y t ðÞÀÁ"#()1=2¼BPG G ;t þ1cx t þ1;y t þ1ðÞBPG G ;t þ1cx t ;y tðÞ"#ÂBPG G ;t c xt þ1;y t þ1ðÞBPG G ;t c x t ;y tðÞ"#()1=2ð4Þis the geometric mean of two terms,each being a ratio of benchmark technology gaps along differentrays.M c G /M c f 1as projections onto T c t and T c t +1of period t +1data are closer to,equidistant from,orfarther away from T c G than projections onto T c t and T ct +1of period t data are.J.T.Pastor,C.A.K.Lovell /Economics Letters 88(2005)266–271268J.T.Pastor,C.A.K.Lovell/Economics Letters88(2005)266–271269 Table1Electricity generation data,annual means1977198219871992 Output(000MW h)13,70013,86016,18017,270 Labor(#FTE)1373179719952021 Fuel(billion BTU)1288144116671824 Capital(To¨rnqvist)44,756211,622371,041396,386 M c G=M c if BPG c G,s(x t+1,y t+1)=BPG c G,s(x t,y t),s=t,t+1.From the first equality in(4),this condition is equivalent to the condition M c G=M c s,s=t,t+1.If this condition holds for all s,it is equivalent to the condition M c t=M c1for all t.Althin(2001)has shown that a sufficient condition for base period independence is that technical change be Hicks output-neutral(HON).Hence HON is also sufficient for M c G=M c.4.An empirical illustrationWe summarize an application intended to illustrate the behavior of M c G,and to compare its performance with that of M c.We analyze a panel of93US electricity generating firms in four years (1977,1982,1997,1992).The firms use labor(FTE employees),fuel(BTUs of energy)and capital(a multilateral To¨rnqvist index)to generate electricity(net generation in MW h).The data are summarized in Table1.Electricity generation increased by proportionately less than each input did.The main cause of the rapid increase in the capital input was the enactment of environmental regulations mandating the installation of pollution abatement equipment.We are unable to disaggregate the capital input into its productive and abatement components.Empirical findings are summarized in Table2.The first three rows report decomposition(3)of M c G, and the final three rows report M c and its two adjacent period components.Columns correspond to time periods.M c G shows a large productivity decline from1977to1982,followed by weak productivity growth. Cumulative productivity in1992was25%lower than in1977.M c G calculated using1992and1977data generates the same value,verifying that it is circular.The efficiency change component EC c of M c G(and M c)is also circular,and cumulates to an18% improvement.Best practice change,BPC c,is also circular,and declined by35%.Capital investment in Table2Global and contemporaneous Malmquist productivity indexes1977–19821982–19871987–1992Cumulative productivity1977–1992 M c G0.685 1.064 1.0390.7570.757EC c 1.163 1.0890.929 1.176 1.176 BPC c0.5890.977 1.1180.6440.644M c0.4310.895 1.0390.4000.592M c t0.7130.902 1.0530.678 1.333M c t+10.2600.887 1.0240.2360.263pollution abatement equipment generated cleaner air but not more electricity.Consequently catching up with deteriorating best practice was relatively easy.Turning to the contemporaneous index M c reported in the final three rows,the story is not so clear.Cumulative productivity in 1992was 60%lower than in 1977.However calculating M c using 1992and 1977data generates a smaller 40%decline,verifying that M c is not circular.Neither figure is close to the25%decline reported by M cG,verifying that technical change was not HON,but (pollution abatement)capital-using.The lack of circularity is reflected in the frequently large differences between M ct and M c t +1,which give conflicting signals when computed using 1992and 1977data,with M c tsignaling productivitygrowth and M ct +1signaling productivity decline.Although not reported in Table 2,we have calculated three-way decompositions of M cG and M c .All three components of M c G are circular,and LP infeasibility does not occur.In contrast,the technical change and scale components of M c are not circular,and infeasibility occurs for 13observations.The circular global index M cGtells a single story about productivity change,and its decomposition is intuitively appealing in light of what we know about the industry during the cking circularity,M c and its two adjacent period components tell different stories that are often contradictory.Thedifferences between M cGand M c are a consequence of the capital-using bias of technical change,which was regressive due to the mandated installation of pollution abatement equipment,augmented perhaps by the rate base padding that was prevalent during the period.5.ConclusionsThe contemporaneous Malmquist productivity index is not circular,its adjacent period components can give conflicting signals,and it is susceptible to LP infeasibility.The global Malmquist productivity index and each of its components is circular,it provides single measures of productivity change and its components,and it is immune to LP infeasibility.The global index decomposes into the same sources of productivity change as the contemporaneous index does.A sufficient condition for equality of the two indexes,and their respective components,is Hicks output neutrality of technical change.The global index must be recomputed when a new time period is incorporated.Diewert’s (1987)assertion that b ...economic history has to be rewritten ...Q when new data are incorporated is the base period dependency problem revisited.The problem can be serious when using base periods t =1and t =T ,but it is likely to be benign when using global base periods {1,...,T }and {1,...,T +1}.While new data may change the global frontier,the rewriting of history is likely to be quantitative rather than qualitative.ReferencesAlthin,R.,2001.Measurement of productivity changes:two Malmquist index approaches.Journal of Productivity Analysis 16,107–128.Berg,S.A.,Førsund,F.R.,Jansen,E.S.,1992.Malmquist indices of productivity growth during the deregulation of Norwegian banking,1980–89.Scandinavian Journal of Economics 94,211–228(Supplement).Caves,D.W.,Christensen,L.R.,Diewert,W.E.,1982.The economic theory of index numbers and the measurement of input output,and productivity.Econometrica 50,1393–1414.J.T.Pastor,C.A.K.Lovell /Economics Letters 88(2005)266–271270J.T.Pastor,C.A.K.Lovell/Economics Letters88(2005)266–271271 Diewert,W.E.,1987.Index numbers.In:Eatwell,J.,Milgate,M.,Newman,P.(Eds.),The New Palgrave:A Dictionary of Economics,vol.2.The Macmillan Press,New York.Fa¨re,R.,Grosskopf,S.,1996.Intertemporal Production Frontiers:With Dynamic DEA.Kluwer Academic Publishers,Boston. Fisher,I.,1922.The Making of Index Numbers.Houghton Mifflin,Boston.Frisch,R.,1936.Annual survey of general economic theory:the problem of index numbers.Econometrica4,1–38.Ray,S.C.,Desli,E.,1997.Productivity growth,technical progress,and efficiency change in industrialized countries:comment.American Economic Review87,1033–1039.Shestalova,V.,2003.Sequential Malmquist indices of productivity growth:an application to OECD industrial activities.Journal of Productivity Analysis19,211–226.Xue,M.,Harker,P.T.,2002.Note:ranking DMUs with infeasible super-efficiency in DEA models.Management Science48, 705–710.。

Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease trans

Reproduction  numbers and sub-threshold endemic equilibria for compartmental models of disease trans

Reproduction numbers and sub-threshold endemicequilibria for compartmental models of disease transmissionP.van den Driesschea,1,James Watmough b,*,2aDepartment of Mathematics and Statistics,University of Victoria,Victoria,BC,Canada V8W 3P4b Department of Mathematics and Statistics,University of New Brunswick,Fredericton,NB,Canada E3B 5A3Received 26April 2001;received in revised form 27June 2001;accepted 27June 2001Dedicated to the memory of John JacquezAbstractA precise definition of the basic reproduction number,R 0,is presented for a general compartmental disease transmission model based on a system of ordinary differential equations.It is shown that,if R 0<1,then the disease free equilibrium is locally asymptotically stable;whereas if R 0>1,then it is unstable.Thus,R 0is a threshold parameter for the model.An analysis of the local centre manifold yields a simple criterion for the existence and stability of super-and sub-threshold endemic equilibria for R 0near one.This criterion,together with the definition of R 0,is illustrated by treatment,multigroup,staged progression,multistrain and vector–host models and can be applied to more complex models.The results are significant for disease control.Ó2002Elsevier Science Inc.All rights reserved.Keywords:Basic reproduction number;Sub-threshold equilibrium;Disease transmission model;Disease control1.IntroductionOne of the most important concerns about any infectious disease is its ability to invade a population.Many epidemiological models have a disease free equilibrium (DFE)at whichtheMathematical Biosciences 180(2002)29–48/locate/mbs*Corresponding author.Tel.:+1-5064587323;fax:+1-5064534705.E-mail addresses:pvdd@math.uvic.ca (P.van den Driessche),watmough@unb.ca (J.Watmough).URL:http://www.math.unb.ca/$watmough.1Research supported in part by an NSERC Research Grant,the University of Victoria Committee on faculty research and travel and MITACS.2Research supported by an NSERC Postdoctoral Fellowship tenured at the University of Victoria.0025-5564/02/$-see front matter Ó2002Elsevier Science Inc.All rights reserved.PII:S0025-5564(02)00108-630P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–48population remains in the absence of disease.These models usually have a threshold parameter, known as the basic reproduction number,R0,such that if R0<1,then the DFE is locally as-ymptotically stable,and the disease cannot invade the population,but if R0>1,then the DFE is unstable and invasion is always possible(see the survey paper by Hethcote[1]).Diekmann et al.[2]define R0as the spectral radius of the next generation matrix.We write down in detail a general compartmental disease transmission model suited to heterogeneous populations that can be modelled by a system of ordinary differential equations.We derive an expression for the next generation matrix for this model and examine the threshold R0¼1in detail.The model is suited to a heterogeneous population in which the vital and epidemiological parameters for an individual may depend on such factors as the stage of the disease,spatial position,age or behaviour.However,we assume that the population can be broken into homo-geneous subpopulations,or compartments,such that individuals in a given compartment are indistinguishable from one another.That is,the parameters may vary from compartment to compartment,but are identical for all individuals within a given compartment.We also assume that the parameters do not depend on the length of time an individual has spent in a compart-ment.The model is based on a system of ordinary equations describing the evolution of the number of individuals in each compartment.In addition to showing that R0is a threshold parameter for the local stability of the DFE, we apply centre manifold theory to determine the existence and stability of endemic equilib-ria near the threshold.We show that some models may have unstable endemic equilibria near the DFE for R0<1.This suggests that even though the DFE is locally stable,the disease may persist.The model is developed in Section2.The basic reproduction number is defined and shown to bea threshold parameter in Section3,and the definition is illustrated by several examples in Section4.The analysis of the centre manifold is presented in Section5.The epidemiological ramifications of the results are presented in Section6.2.A general compartmental epidemic model for a heterogeneous populationConsider a heterogeneous population whose individuals are distinguishable by age,behaviour, spatial position and/or stage of disease,but can be grouped into n homogeneous compartments.A general epidemic model for such a population is developed in this section.Let x¼ðx1;...;x nÞt, with each x i P0,be the number of individuals in each compartment.For clarity we sort the compartments so that thefirst m compartments correspond to infected individuals.The distinc-tion between infected and uninfected compartments must be determined from the epidemiological interpretation of the model and cannot be deduced from the structure of the equations alone,as we shall discuss below.It is plausible that more than one interpretation is possible for some models.A simple epidemic model illustrating this is given in Section4.1.The basic reproduction number can not be determined from the structure of the mathematical model alone,but depends on the definition of infected and uninfected compartments.We define X s to be the set of all disease free states.That isX s¼f x P0j x i¼0;i¼1;...;m g:In order to compute R0,it is important to distinguish new infections from all other changes inpopulation.Let F iðxÞbe the rate of appearance of new infections in compartment i,Vþi ðxÞbe therate of transfer of individuals into compartment i by all other means,and VÀi ðxÞbe the rate oftransfer of individuals out of compartment i.It is assumed that each function is continuously differentiable at least twice in each variable.The disease transmission model consists of non-negative initial conditions together with the following system of equations:_x i¼f iðxÞ¼F iðxÞÀV iðxÞ;i¼1;...;n;ð1Þwhere V i¼VÀi ÀVþiand the functions satisfy assumptions(A1)–(A5)described below.Sinceeach function represents a directed transfer of individuals,they are all non-negative.Thus,(A1)if x P0,then F i;Vþi ;VÀiP0for i¼1;...;n.If a compartment is empty,then there can be no transfer of individuals out of the compartment by death,infection,nor any other means.Thus,(A2)if x i¼0then VÀi ¼0.In particular,if x2X s then VÀi¼0for i¼1;...;m.Consider the disease transmission model given by(1)with f iðxÞ,i¼1;...;n,satisfying con-ditions(A1)and(A2).If x i¼0,then f iðxÞP0and hence,the non-negative cone(x i P0, i¼1;...;n)is forward invariant.By Theorems1.1.8and1.1.9of Wiggins[3,p.37]for each non-negative initial condition there is a unique,non-negative solution.The next condition arises from the simple fact that the incidence of infection for uninfected compartments is zero.(A3)F i¼0if i>m.To ensure that the disease free subspace is invariant,we assume that if the population is free of disease then the population will remain free of disease.That is,there is no(density independent) immigration of infectives.This condition is stated as follows:(A4)if x2X s then F iðxÞ¼0and VþiðxÞ¼0for i¼1;...;m.The remaining condition is based on the derivatives of f near a DFE.For our purposes,we define a DFE of(1)to be a(locally asymptotically)stable equilibrium solution of the disease free model,i.e.,(1)restricted to X s.Note that we need not assume that the model has a unique DFE. Consider a population near the DFE x0.If the population remains near the DFE(i.e.,if the introduction of a few infective individuals does not result in an epidemic)then the population will return to the DFE according to the linearized system_x¼Dfðx0ÞðxÀx0Þ;ð2Þwhere Dfðx0Þis the derivative½o f i=o x j evaluated at the DFE,x0(i.e.,the Jacobian matrix).Here, and in what follows,some derivatives are one sided,since x0is on the domain boundary.We restrict our attention to systems in which the DFE is stable in the absence of new infection.That is, (A5)If FðxÞis set to zero,then all eigenvalues of Dfðx0Þhave negative real parts.P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–4831The conditions listed above allow us to partition the matrix Df ðx 0Þas shown by the following lemma.Lemma 1.If x 0is a DFE of (1)and f i ðx Þsatisfies (A1)–(A5),then the derivatives D F ðx 0Þand D V ðx 0Þare partitioned asD F ðx 0Þ¼F 000 ;D V ðx 0Þ¼V 0J 3J 4;where F and V are the m Âm matrices defined byF ¼o F i o x j ðx 0Þ !and V ¼o V i o x jðx 0Þ !with 16i ;j 6m :Further ,F is non-negative ,V is a non-singular M-matrix and all eigenvalues of J 4have positive real part .Proof.Let x 02X s be a DFE.By (A3)and (A4),ðo F i =o x j Þðx 0Þ¼0if either i >m or j >m .Similarly,by (A2)and (A4),if x 2X s then V i ðx Þ¼0for i 6m .Hence,ðo V i =o x j Þðx 0Þ¼0for i 6m and j >m .This shows the stated partition and zero blocks.The non-negativity of F follows from (A1)and (A4).Let f e j g be the Euclidean basis vectors.That is,e j is the j th column of the n Ân identity matrix.Then,for j ¼1;...;m ,o V i o x jðx 0Þ¼lim h !0þV i ðx 0þhe j ÞÀV i ðx 0Þh :To show that V is a non-singular M-matrix,note that if x 0is a DFE,then by (A2)and (A4),V i ðx 0Þ¼0for i ¼1;...;m ,and if i ¼j ,then the i th component of x 0þhe j ¼0and V i ðx 0þhe j Þ60,by (A1)and (A2).Hence,o V i =o x j 0for i m and j ¼i and V has the Z sign pattern (see Appendix A).Additionally,by (A5),all eigenvalues of V have positive real parts.These two conditions imply that V is a non-singular M-matrix [4,p.135(G 20)].Condition (A5)also implies that the eigenvalues of J 4have positive real part.Ã3.The basic reproduction numberThe basic reproduction number,denoted R 0,is ‘the expected number of secondary cases produced,in a completely susceptible population,by a typical infective individual’[2];see also [5,p.17].If R 0<1,then on average an infected individual produces less than one new infected individual over the course of its infectious period,and the infection cannot grow.Conversely,if R 0>1,then each infected individual produces,on average,more than one new infection,and the disease can invade the population.For the case of a single infected compartment,R 0is simply the product of the infection rate and the mean duration of the infection.However,for more complicated models with several infected compartments this simple heuristic definition of R 0is32P.van den Driessche,J.Watmough /Mathematical Biosciences 180(2002)29–48insufficient.A more general basic reproduction number can be defined as the number of new infections produced by a typical infective individual in a population at a DFE.To determine the fate of a‘typical’infective individual introduced into the population,we consider the dynamics of the linearized system(2)with reinfection turned off.That is,the system _x¼ÀD Vðx0ÞðxÀx0Þ:ð3ÞBy(A5),the DFE is locally asymptotically stable in this system.Thus,(3)can be used to de-termine the fate of a small number of infected individuals introduced to a disease free population.Let wi ð0Þbe the number of infected individuals initially in compartment i and letwðtÞ¼w1ðtÞ;...;w mðtÞðÞt be the number of these initially infected individuals remaining in the infected compartments after t time units.That is the vector w is thefirst m components of x.The partitioning of D Vðx0Þimplies that wðtÞsatisfies w0ðtÞ¼ÀV wðtÞ,which has the unique solution wðtÞ¼eÀVt wð0Þ.By Lemma1,V is a non-singular M-matrix and is,therefore,invertible and all of its eigenvalues have positive real parts.Thus,integrating F wðtÞfrom zero to infinity gives the expected number of new infections produced by the initially infected individuals as the vector FVÀ1wð0Þ.Since F is non-negative and V is a non-singular M-matrix,VÀ1is non-negative[4,p.137 (N38)],as is FVÀ1.To interpret the entries of FVÀ1and develop a meaningful definition of R0,consider the fate of an infected individual introduced into compartment k of a disease free population.The(j;k)entry of VÀ1is the average length of time this individual spends in compartment j during its lifetime, assuming that the population remains near the DFE and barring reinfection.The(i;j)entry of F is the rate at which infected individuals in compartment j produce new infections in compartment i. Hence,the(i;k)entry of the product FVÀ1is the expected number of new infections in com-partment i produced by the infected individual originally introduced into compartment k.Fol-lowing Diekmann et al.[2],we call FVÀ1the next generation matrix for the model and set R0¼qðFVÀ1Þ;ð4Þwhere qðAÞdenotes the spectral radius of a matrix A.The DFE,x0,is locally asymptotically stable if all the eigenvalues of the matrix Dfðx0Þhave negative real parts and unstable if any eigenvalue of Dfðx0Þhas a positive real part.By Lemma1, the eigenvalues of Dfðx0Þcan be partitioned into two sets corresponding to the infected and uninfected compartments.These two sets are the eigenvalues of FÀV and those ofÀJ4.Again by Lemma1,the eigenvalues ofÀJ4all have negative real part,thus the stability of the DFE is determined by the eigenvalues of FÀV.The following theorem states that R0is a threshold parameter for the stability of the DFE.Theorem2.Consider the disease transmission model given by(1)with fðxÞsatisfying conditions (A1)–(A5).If x0is a DFE of the model,then x0is locally asymptotically stable if R0<1,but un-stable if R0>1,where R0is defined by(4).Proof.Let J1¼FÀV.Since V is a non-singular M-matrix and F is non-negative,ÀJ1¼VÀF has the Z sign pattern(see Appendix A).Thus,sðJ1Þ<0()ÀJ1is a non-singular M-matrix;P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–483334P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–48where sðJ1Þdenotes the maximum real part of all the eigenvalues of the matrix J1(the spectral abscissa of J1).Since FVÀ1is non-negative,ÀJ1VÀ1¼IÀFVÀ1also has the Z sign pattern.Ap-plying Lemma5of Appendix A,with H¼V and B¼ÀJ1¼VÀF,we have ÀJ1is a non-singular M-matrix()IÀFVÀ1is a non-singular M-matrix:Finally,since FVÀ1is non-negative,all eigenvalues of FVÀ1have magnitude less than or equal to qðFVÀ1Þ.Thus,IÀFVÀ1is a non-singular M-matrix;()qðFVÀ1Þ<1:Hence,sðJ1Þ<0if and only if R0<1.Similarly,it follows thatsðJ1Þ¼0()ÀJ1is a singular M-matrix;()IÀFVÀ1is a singular M-matrix;()qðFVÀ1Þ¼1:The second equivalence follows from Lemma6of Appendix A,with H¼V and K¼F.The remainder of the equivalences follow as with the non-singular case.Hence,sðJ1Þ¼0if and only if R0¼1.It follows that sðJ1Þ>0if and only if R0>1.ÃA similar result can be found in the recent book by Diekmann and Heesterbeek[6,Theorem6.13].This result is known for the special case in which J1is irreducible and V is a positive di-agonal matrix[7–10].The special case in which V has positive diagonal and negative subdiagonal elements is proven in Hyman et al.[11,Appendix B];however,our approach is much simpler(see Section4.3).4.Examples4.1.Treatment modelThe decomposition of fðxÞinto the components F and V is illustrated using a simple treat-ment model.The model is based on the tuberculosis model of Castillo-Chavez and Feng[12,Eq.(1.1)],but also includes treatment failure used in their more elaborate two-strain model[12,Eq.(2.1)].A similar tuberculosis model with two treated compartments is proposed by Blower et al.[13].The population is divided into four compartments,namely,individuals susceptible to tu-berculosis(S),exposed individuals(E),infectious individuals(I)and treated individuals(T).The dynamics are illustrated in Fig.1.Susceptible and treated individuals enter the exposed com-partment at rates b1I=N and b2I=N,respectively,where N¼EþIþSþT.Exposed individuals progress to the infectious compartment at the rate m.All newborns are susceptible,and all indi-viduals die at the rate d>0.Thus,the core of the model is an SEI model using standard inci-dence.The treatment rates are r1for exposed individuals and r2for infectious individuals. However,only a fraction q of the treatments of infectious individuals are successful.Unsuc-cessfully treated infectious individuals re-enter the exposed compartment(p¼1Àq).The diseasetransmission model consists of the following differential equations together with non-negative initial conditions:_E¼b1SI=Nþb2TI=NÀðdþmþr1ÞEþpr2I;ð5aÞ_I¼m EÀðdþr2ÞI;ð5bÞ_S¼bðNÞÀdSÀb1SI=N;ð5cÞ_T¼ÀdTþr1Eþqr2IÀb2TI=N:ð5dÞProgression from E to I and failure of treatment are not considered to be new infections,but rather the progression of an infected individual through the various compartments.Hence,F¼b1SI=Nþb2TI=NB B@1C CA and V¼ðdþmþr1ÞEÀpr2IÀm Eþðdþr2ÞIÀbðNÞþdSþb1SI=NdTÀr1EÀqr2Iþb2TI=NB B@1C CA:ð6ÞThe infected compartments are E and I,giving m¼2.An equilibrium solution with E¼I¼0has the form x0¼ð0;0;S0;0Þt,where S0is any positive solution of bðS0Þ¼dS0.This will be a DFE if and only if b0ðS0Þ<d.Without loss of generality,assume S0¼1is a DFE.Then,F¼0b100;V¼dþmþr1Àpr2Àm dþr2;givingVÀ1¼1ðdþmþr1Þðdþr2ÞÀm pr2dþr2pr2m dþmþr1and R0¼b1m=ððdþmþr1Þðdþr2ÞÀm pr2Þ.A heuristic derivation of the(2;1)entry of VÀ1and R0are as follows:a fraction h1¼m=ðdþmþr1Þof exposed individuals progress to compartment I,a fraction h2¼pr2=ðdþr2Þof infectious individuals re-enter compartment E.Hence,a fractionh1of exposed individuals pass through compartment I at least once,a fraction h21h2passthroughat least twice,and a fraction h k 1h k À12pass through at least k times,spending an average of s ¼1=ðd þr 2Þtime units in compartment I on each pass.Thus,an individual introduced into com-partment E spends,on average,s ðh 1þh 21h 2þÁÁÁÞ¼s h 1=ð1Àh 1h 2Þ¼m =ððd þm þr 1Þðd þr 2ÞÀm pr 2Þtime units in compartment I over its expected lifetime.Multiplying this by b 1gives R 0.The model without treatment (r 1¼r 2¼0)is an SEI model with R 0¼b 1m =ðd ðd þm ÞÞ.The interpretation of R 0for this case is simpler.Only a fraction m =ðd þm Þof exposed individuals progress from compartment E to compartment I ,and individuals entering compartment I spend,on average,1=d time units there.Although conditions (A1)–(A5)do not restrict the decomposition of f i ðx Þto a single choice for F i ,only one such choice is epidemiologically correct.Different choices for the function F lead to different values for the spectral radius of FV À1,as shown in Table 1.In column (a),treatment failure is considered to be a new infection and in column (b),both treatment failure and pro-gression to infectiousness are considered new infections.In each case the condition q ðFV À1Þ<1yields the same portion of parameter space.Thus,q ðFV À1Þis a threshold parameter in both cases.The difference between the numbers lies in the epidemiological interpretation rather than the mathematical analysis.For example,in column (a),the infection rate is b 1þpr 2and an exposed individual is expected to spend m =ððd þm þr 1Þðd þr 2ÞÞtime units in compartment I .However,this reasoning is biologically flawed since treatment failure does not give rise to a newly infected individual.Table 1Decomposition of f leading to alternative thresholds(a)(b)Fb 1SI =N þb 2TI =N þpr 2I 0000B B @1C C A b 1SI =N þb 2TI =N þpr 2I m E 000B B @1C C A Vðd þm þr 1ÞE Àm E þðd þr 2ÞI Àb ðN ÞþdS þb 1SI =N dT Àr 1E Àqr 2I þb 2TI =N 0B B @1C C A ðd þm þr 1ÞE ðd þr 2ÞI Àb ðN ÞþdS þb 1SI =N dT Àr 1E Àqr 2I þb 2TI =N 0B B @1C C A F0b 1þpr 200 0b 1þpr 2m 0 V d þm þr 10Àm d þr 2d þm þr 100d þr 2 q (FV À1)b 1m þpr 2mðd þm þr 1Þðd þr 2Þffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffib 1m þpr 2mðd þm þr 1Þðd þr 2Þs 36P.van den Driessche,J.Watmough /Mathematical Biosciences 180(2002)29–484.2.Multigroup modelIn the epidemiological literature,the term‘multigroup’usually refers to the division of a het-erogeneous population into several homogeneous groups based on individual behaviour(e.g., [14]).Each group is then subdivided into epidemiological compartments.The majority of mul-tigroup models in the literature are used for sexually transmitted diseases,such as HIV/AIDS or gonorrhea,where behaviour is an important factor in the probability of contracting the disease [7,8,14,15].As an example,we use an m-group SIRS-vaccination model of Hethcote[7,14]with a generalized incidence term.The sample model includes several SI multigroup models of HIV/ AIDS as special cases[8,15].The model equations are as follows:_I i ¼X mj¼1b ijðxÞS i I jÀðd iþc iþ iÞI i;ð7aÞ_S i ¼ð1Àp iÞb iÀðd iþh iÞS iþr i R iÀX mj¼1b ijðxÞS i I j;ð7bÞ_Ri¼p i b iþc i I iþh i S iÀðd iþr iÞR i;ð7cÞfor i¼1;...;m,where x¼ðI1;...;I m;S1;...;S m;R1;...;R mÞt.Susceptible and removed individu-als die at the rate d i>0,whereas infected individuals die at the faster rate d iþ i.Infected in-dividuals recover with temporary immunity from re-infection at the rate c i,and immunity lasts an expected1=r i time units.All newborns are susceptible,and a constant fraction b i are born into each group.A fraction p i of newborns are vaccinated at birth.Thereafter,susceptible individuals are vaccinated at the rate h i.The incidence,b ijðxÞdepends on individual behaviour,which determines the amount of mixing between the different groups(see,e.g.,Jacquez et al.[16]). The DFE for this model isx0¼ð0;...;0;S01;...;S0m;R01;...;R0mÞt;whereS0 i ¼b i d ið1Àp iÞþr iðÞd iðd iþh iþr iÞ;R0 i ¼b iðh iþd i p iÞd iðd iþh iþr iÞ:Linearizing(7a)about x¼x0givesF¼S0i b ijðx0ÞÂÃandV¼½ðd iþc iþ iÞd ij ;where d ij is one if i¼j,but zero otherwise.Thus,FVÀ1¼S0i b ijðx0Þ=ðd iÂþc iþ iÞÃ:P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–4837For the special case with b ij separable,that is,b ijðxÞ¼a iðxÞk jðxÞ,F has rank one,and the basic reproduction number isR0¼X mi¼1S0ia iðx0Þk iðx0Þd iþc iþ i:ð8ÞThat is,the basic reproduction number of the disease is the sum of the‘reproduction numbers’for each group.4.3.Staged progression modelThe staged progression model[11,Section3and Appendix B]has a single uninfected com-partment,and infected individuals progress through several stages of the disease with changing infectivity.The model is applicable to many diseases,particularly HIV/AIDS,where transmission probabilities vary as the viral load in an infected individual changes.The model equations are as follows(see Fig.2):_I 1¼X mÀ1k¼1b k SI k=NÀðm1þd1ÞI1;ð9aÞ_Ii¼m iÀ1I iÀ1Àðm iþd iÞI i;i¼2;...;mÀ1;ð9bÞ_Im¼m mÀ1I mÀ1Àd m I m;ð9cÞ_S¼bÀbSÀX mÀ1k¼1b k SI k=N:ð9dÞThe model assumes standard incidence,death rates d i>0in each infectious stage,and thefinal stage has a zero infectivity due to morbidity.Infected individuals spend,on average,1=m i time units in stage i.The unique DFE has I i¼0,i¼1;...;m and S¼1.For simplicity,define m m¼0. Then F¼½F ij and V¼½V ij ,whereF ij¼b j i¼1;j6mÀ1;0otherwise;&ð10ÞV ij¼m iþd i j¼i;Àm j i¼1þj;0otherwise:8<:ð11ÞLet a ij be the(i;j)entry of VÀ1.Thena ij¼0i<j;1=ðm iþd iÞi¼j;Q iÀ1k¼jm kQ ik¼jðm kþd kÞj<i:8>>><>>>:ð12ÞThus,R0¼b1m1þd1þb2m1ðm1þd1Þðm2þd2Þþb3m1m2ðm1þd1Þðm2þd2Þðm3þd3ÞþÁÁÁþb mÀ1m1...m mÀ2ðm1þd1Þ...ðm mÀ1þd mÀ1Þ:ð13ÞThe i th term in R0represents the number of new infections produced by a typical individual during the time it spends in the i th infectious stage.More specifically,m iÀ1=ðm iÀ1þd iÀ1Þis the fraction of individuals reaching stage iÀ1that progress to stage i,and1=ðm iþd iÞis the average time an individual entering stage i spends in stage i.Hence,the i th term in R0is the product of the infectivity of individuals in stage i,the fraction of initially infected individuals surviving at least to stage i,and the average infectious period of an individual in stage i.4.4.Multistrain modelThe recent emergence of resistant viral and bacterial strains,and the effect of treatment on their proliferation is becoming increasingly important[12,13].One framework for studying such sys-tems is the multistrain model shown in Fig.3,which is a caricature of the more detailed treatment model of Castillo-Chavez and Feng[12,Section2]for tuberculosis and the coupled two-strain vector–host model of Feng and Velasco-Hern a ndez[17]for Dengue fever.The model has only a single susceptible compartment,but has two infectious compartments corresponding to the two infectious agents.Each strain is modelled as a simple SIS system.However,strain one may ‘super-infect’an individual infected with strain two,giving rise to a new infection incompartment。

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本学科研究范围相当广泛,使之成为一门综合 性的边缘学科。与植物分类学、植物地理学、 植物生态学、地植物学、药用植物学、园艺学、 工艺化学、栽培学、微生物学、经济学、民族 学 、地理学等学科有密切关系。研究的对象为 各种与人类直接或间接利用的植物资源。可见, 植物资源学是研究所有过去、现在和未来对人 类有用植物的科学,包括不少已有学科的全部 或一部分,有基础、应用和社会科学的内容。 图1就是Wickens(1990)的一种认识。
四、国内外植物资源发展概况
五、植物资源学研究内容与任务
一、植物资源
(一)植物资源的概念
广义的理解 植物资源是地球上或生物圈内一切 植物的统称。植物是自然界第一生产力, 是人类和动物维持和延续生命的基本物 质条件,又是人类赖以生存的环境和生 产建设的重要原料来源。是一个国家物 资基础的本底,是人类的宝贵财富。
森林学 forestry
民族植物学 botany 农学 agriculture 园艺学 horticulure
图1 资源植物与相关学科的关系示意图 Fig 1 Diagrammatic represntation of the reiationship between economic botany , ethnobotany,agriculture,forestry and horticulture(Wickens 1990)
茯苓
另外日本发现有l0种生药对癌细胞和正常细 胞有选择毒性的功能,其中最好的是仙鹤 草 (Agrimonia pilosa) 和 败 酱 (Patrinia spp.) ,它们对癌细胞的抑制作用率分别达 100% 和 98.2% ,相反,对人体的正常细胞 有100%的促进生长作用。这类试验还正在 继续。 同时,日本对收集这方面的情报十分重视, 从中探索,筛选新药物,近几年他们从喜 马拉雅山南坡各国收集植物标本 80 余万份。

国际动物学会主办全球变化生物学国际学术研讨会

国际动物学会主办全球变化生物学国际学术研讨会

文缩写 :IB )主办 ,中国科学 院西双版纳热带植物 园 、中国科学 院 US 动 物研究所 、中国科学 院昆明动物研究所 、中 国动物学会 和 国际生物 科 学联合 会 中国委员会 ( CU S 承办 ,中国科协 国际合作部及学会 C IB ) 学 术部 、科技部 基础研究 司及 国际合作 司、国家 自然科 学基 金委生命

1 , 4 日,第 四届 整合 动 物学 国际研 讨会 暨全 球 变化生 物学 2 ~6 q 国 际学 术研 讨 会 在 昆 明召 开 。会 议 由国 际动 物 学 会 ( 文 名称 : 英 Itra oa oit o o lg a Sin e ,英 文缩写 :IZ ne t n S c y f ooi l c cs n il e Z c e S S)与 国际生 物科 学联合 ( 英文 名称 :I ent nl n no Bo gi c ne ,英 n ra o a U i i oc S i cs t i o f l a e l
回 际动 物 学 会 主 办 全 球 变 化 生 物 学 国 际 学 术研 讨 会
2 1年 学 生 志愿 者 千 万村 O0 环保 科 普 动 深 入 农材 彳
l 月1 日,中 国环 境科学学 会在河 北农业大学 举办 了 “ 0 0 2 0 2 1 年大学 生志愿者 千乡万村 环保科普行 动”经 验交流研讨 暨表彰 大 会。会议邀 请 到了环保部科 技司 副处 长王泽林 ,环保部 生态司孔 源博士 ,中 国科协 科普部基 层处副处 长路剑 武等 出席指 导 。中华 医学会 、河 北省环 保厅科技处 、河北 省科协科普 部 、河北 农业大 学 党委副 书记等有关 领导也 出席 了会 议。参加会 议 的还有 云南等
( 国 环 境 科 学 学会 ) 中

2010计算生物与系统生物学国际会议

2010计算生物与系统生物学国际会议
里大学的 D n iS au ens a hb教授应邀作 主题报告 。另 l
有来 自世界各地的 2 余位科学家作大会报告 。 0 开幕 式于 1 0月 2 上午举行 ,大会主席魏冬青教授代 3日
表共同主席林标扬教授致开幕辞。
ad yt s ioy n 0 0 IC B 0 0 n s m o g 1,C S 2 1) S e B l i2 在浙江省杭 州市举行。
始 ,系统生物学的发展进入了细胞信号转导与基因 表达调控研究 的细胞 、 分子系统生物学时期 , 国际、 国内的系统与合成生物学、系统遗传学等研究机构 纷纷建立而进入了系统生命科学时代 。而随着人类 基因组草图的完成 , 许多学者开始探索基因与蛋 白 质如何相互作用。人类基因组 中编码蛋白质的基因 数远少于人类蛋 白质组中的蛋 白指数 , 这个发现对
此次会议会议共收到全文及摘要 5 篇 , 7 其中国
内论文 4 篇 , 0 国外论文 l 篇。会议期间 , 7 众多世界
来自 全球各地包括美国、 国、 本 、 德 日 韩国、 加拿 会人员进行 了大会报告 、分会 报告 以及一场 P s r oe t 展示讨论 。参会代表分别来 自美 国范德 比特大学
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( aoa R s r oniC a a ,以及 中国科学 N tnl ee c Cu c a d ) i  ̄ h a ln

甘蔗二点螟性信息素地理变异假说

甘蔗二点螟性信息素地理变异假说

甘蔗二点螟性信息素地理变异假说胡玉伟;管楚雄;林明江;李继虎;温莉茵【摘要】甘蔗二点螟是严重为害我国甘蔗的钻蛀性害虫,化学防治效果不佳且污染环境.其性信息素防治技术早已开始,然而多年田间实验发现其在不同生态型蔗区活性差异很大,可能存在地理变异.本项目提出理论假说,认为二点螟性信息素可能因地理隔离存在组分或含量的地理变异,并给出该假说的理论依据,便于地理变异机制等实验的开展和实施,丰富此类昆虫的化学生态学理论.%Chilo infuscatellus is a very important pest in the sugarcane and it is not working to control it by pesticides.Researchers have paid close attention to the application of its sex pheromone.However,the effects of sex pheromone were found different in populations,which delayed the application of sex pheromone in field.One hypothesis is that there may be variation in composition of sex pheromone because of geographic isolation.This paper give the theory basis of this hypothesis to conduct the next experiment and to enrich the study of chemical biology of this species.【期刊名称】《甘蔗糖业》【年(卷),期】2013(000)003【总页数】4页(P15-18)【关键词】二点螟;信息素;变异【作者】胡玉伟;管楚雄;林明江;李继虎;温莉茵【作者单位】广州甘蔗糖业研究所广东省甘蔗改良与生物炼制重点实验室,广东广州510316;广州甘蔗糖业研究所广东省甘蔗改良与生物炼制重点实验室,广东广州510316;广州甘蔗糖业研究所广东省甘蔗改良与生物炼制重点实验室,广东广州510316;广州甘蔗糖业研究所广东省甘蔗改良与生物炼制重点实验室,广东广州510316;广州甘蔗糖业研究所广东省甘蔗改良与生物炼制重点实验室,广东广州510316【正文语种】中文【中图分类】S566.11 理论假说的提出及研究意义过度使用化学杀虫剂控制农业害虫,极大地影响着我国农业生产安全、农产品质量安全、农业生态安全和农业贸易安全。

“第四届欧米伽3与人类健康国际论坛”隆重召开

“第四届欧米伽3与人类健康国际论坛”隆重召开

“第四届欧米伽3与人类健康国际论坛”隆重召开作者:来源:《沪港经济》2017年第03期2017年3月2日,“第四届欧米伽3与人类健康国际论坛”在重庆召开。

解放军总医院营养科主任刘英华博士等9位中国专家,与来自美国、加拿大、英国、日本的5位著名科学家同台演讲,内容涉及婴幼儿发育、心血管疾病、慢病防治、精神抑郁、炎症免疫、高血压、糖尿病等课题。

论坛上还展示了目前国内最新的欧米伽3研究成果。

美國哈佛医学院康景轩教授说:“随着全球生物医学界对欧米伽3脂肪酸越来越深入的研究,发现它可以影响到许多重大慢性疾病的发生、发展,有意识地补充欧米伽3,可以大大降低心脏病、癌症、糖尿病等多种慢性病的患病风险,并有助于患者的康复。

”希腊字母“ω”就像躺着的3,“ω-3”中文通常写作“欧米伽3”。

“欧米伽3脂肪酸”主要存在于深海鱼、亚麻、紫苏以及核桃等坚果内,是一种人体不可缺少的必需脂肪酸。

上世纪80年代至今,全球5万多个欧米伽3的研究成果显示:人体对它的缺乏几乎与所有的慢性疾病发生、发展有密切的关系。

2009年诺贝尔生物医学奖得主伊丽莎白·布莱克本教授发现,欧米伽3对端粒酶的影响大大延长了人体心脏细胞的寿命。

前不久,美国哈佛医学院又发现欧米伽3可以减轻雾霾对人体的损害。

中国的研究虽然起步较晚,但近年来已有快速进展。

会上,中国健康促进与教育协会与国际脂肪酸与类脂研究学会签约,共同在中国开展相关的学术交流和科普活动,聘请国际知名专家进行巡回演讲。

青岛大学与上海展望集团、增爱公益基金会三方签约,联合成立“青岛大学展望脂肪酸研究中心”,并开展欧米伽3生物医学的基础及应用研究。

论坛由中国健康促进与教育协会和国际脂肪酸与类脂研究学会(ISSFAL)、国际欧米伽3研究学会(ISOR)、亚太临床营养学会(APCNS)、美国遗传营养与健康中心以及增爱公益基金会等5大机构共同主办,其主题是“欧米伽3在中国”。

在与听众互动时,汤姆·布莱纳教授表示,“我之所以钻研欧米伽3,起因于27年前,我太太怀孕不足6个月生了一对早产儿,儿子出生体重1公斤,女儿仅500多克。

Beta多样性研究进展

Beta多样性研究进展

生物多样性2010, 18 (4): 323–335Biodiversity Science http: //Beta多样性研究进展陈圣宾欧阳志云*徐卫华肖燚(中国科学院生态环境研究中心城市与区域生态国家重点实验室, 北京100085)摘要: Beta多样性度量时空尺度上物种组成的变化, 是生物多样性的重要组成部分, 与许多生态学和进化生物学问题密切相关, 并且其信息可用于保护区选址和布局规划, 因此在最近10年间成为生物多样性研究的热点问题之一。

多年来, 学者们利用各种度量方式和分析方法, 在不同地理区域, 对许多生物类群beta多样性的时空格局和形成机制进行了大量研究。

本文主要从beta多样性的度量方法、时空格局、形成机制及其在生物多样性保护中的应用等几个方面, 总结了最近10多年来相关研究的进展。

Whittaker(1960)最初提出beta多样性概念时就缺乏严格的定义, 随着概念的不断演化, 度量方法也同样呈现出多样化, 而度量手段的多样化非常不利于不同研究之间的比较。

目前应用最普遍的度量方法是采用相似性指数, 如Jaccard和Sørensen指数。

最近几年, 新的度量方法还在不断出现, 其中一些方法非常值得注意。

Beta多样性具有时空尺度和分类尺度依赖性, 一般随分析粒度(grain)的增加而降低。

虽然有些研究表明beta多样性随纬度增加而降低, 但学者们并没有达成共识。

山区和生物地理区的交界处beta 多样性都比较高, 因而需要在这些地区增加保护区的面积或者数量以囊括物种变化梯度。

对时间尺度上beta多样性的研究表明, 气候变化确实导致了物种组成在时间上的变化, 并且物种在不同大陆和地区间的迁移导致了生物同质化。

扩散过程和生态位过程共同决定了beta多样性, 只是这两个过程的相对重要性依尺度、地理区域和物种类群的不同而有所差异。

综上所述, 我们认为未来beta多样性研究的热点问题是:(1)不同生物类群的进化历史和生物学特征对beta多样性的影响; (2)不同的时空尺度对beta多样性及其维持机制的影响; (3)人类活动对beta多样性的影响。

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Abstract
We investigate the relation between gauge theories and brane configurations described by brane tilings. We identify U(1)B (baryonic), U(1)M (mesonic), and U(1)R global symmetries in gauge theories with gauge symmetries in the brane configurations. We also show that 2 U(1)M U(1)2 B and U(1)R U(1)B ’t Hooft anomalies are reproduced as gauge transformations of the classical brane action.
UT-06-21 hep-th/0609163 Sep 2006
arXiv:hep-th/060916etries and ’t Hooft anomalies in brane tilings
Yosuke Imamura∗ Department of Physics, University of Tokyo, Tokyo 113-0033, Japan
Anomalies arise as one-loop corrections in gauge theories, and have topological nature in the sense that their coefficients are quantized, and are invariant under continuous variation of parameters. This makes analysis on the string side tractable. In general it is difficult to determine the precise shape of branes in a brane system. By the reason we mention above, for the analysis of anomalies, we do not need the precise shape of the branes. We only need the topological structure and the asymptotic shape of branes. In [17], the relation between cancellations of gauge (SU(Nc )3 ) and U(1)B SU(Nc )2 anomalies and flux conservations on the brane system is discussed, and it is shown that if the boundary conditions imposed on the fields on branes at fivebrane junctions are satisfied, the anomaly cancellations are automatically realized. In this paper, we discuss so-called ’t Hooft anomalies which are in general not canceled. We show that some of the anomalies can be reproduced as the variations of the classical brane action by gauge transformations. (In this paper we are not very careful about signs.) This paper is organized as follows. In §2, we briefly explain the relation between the tiling diagrams and the structure of the branes in the system. In §3, we identify global U(1) symmetries in gauge theories with gauge symmetries in the brane system. Using this identification, we compute some of ’t Hooft anomalies, 2 2 in §4. We only discuss U(1)3 B , U(1)M U(1)B and U(1)R U(1)B anomalies, where U(1)B , U(1)M , and U(1)R are the baryonic, mesonic (flavor), and R-symmetries, respectively, which are defined in §3. Among these three classes of anomalies, the U(1)3 B anomalies are known to vanish, and we use this fact to fix the ambiguity of the regularization. We show that the other two kinds of anomalies are reproduced as variations of the classical brane action. The last section is devoted for discussions. In Appendix A, we discuss the action of fivebrane junctions and boundary conditions imposed on the gauge fields. In Appendix B, we solve a differential equation which appears in §4.

E-mail: imamura@hep-th.phys.s.u-tokyo.ac.jp
1
Introduction
String theory is a useful tool to study dynamics of gauge theories. An advantage of using string theory for the analysis of gauge theories is that we can translate quantum corrections and non-perturbative effects in gauge theories to classical phenomena associated with geometries of spacetime and brane configurations. Among many kinds of dualities, the duality between conifolds and N = 1 superconformal gauge theories attracts a great deal of attention. The first nontrivial example of this duality was proposed in [1]. It is the duality between the conifold over T 1,1 and a certain SU(N ) × SU(N ) superconformal gauge theory at the IR fixed point. This duality has been generalized to more complicated ones. The recent discovery of the explicit metrics of classes of Sasaki-Einstein manifolds[2, 3, 4] provides us many examples of dualities we can explicitly check the validity. For example, it has been confirmed that the volumes of the SasakiEinstein manifolds and some supersymmetric cycles in them correctly reproduce the central charges and conformal dimensions of baryonic operators in superconformal gauge theories, which can be determined on the field theory side with the help of the a-maximization technique[5]. There are also many attempts to generalize the correspondence to non-conformal cases. One way to break the conformal symmetry on the field theory side is to change the ranks of the SU(N ) gauge groups. This is realized by the introduction of fractional D3-branes on the gravity side. The coupling running[6, 7] and the duality cascade[8] caused by the introduction of the fractional branes are studied by using dual gravity solutions. The brane tilings[9, 10, 11, 12, 13, 14], proposed by Hanany et al. are different, but closely related way to realize N = 1 quiver gauge theories with fivebranes in type IIB theory. The brane configurations are conveniently described with tilings on tori. Each face is identified with a stack of N D5-branes, and an SU(N ) gauge group lives on it. An edge shared by two faces represents the intersection of the D5-branes and NS5-branes, and corresponds to a chiral multiplet belonging to a bi-fundamental representation of the two gauge groups associated with the two faces. Thus, the tilings can be regarded as dual graphs of quiver diagrams drawn on tori, which are often called periodic quiver diagrams. An advantage of the brane tilings (and the periodic quiver diagrams) to the ordinary quiver diagrams is that we can easily read off the superpotential from the diagram. There are many rules proposed to read off the properties and phenomena in gauge theories from the diagrams. For example, we can easily obtain anomaly free charge assignments of global symmetries from the brane tilings[15]. We can also determine IR behavior of non-conformal gauge theories depending on the rank distributions[16]. It is important to obtain these relations between the graphical information in the tilings and the properties of gauge theories directly by using action or equations of motion of branes and supergravity. In this paper, we particularly discuss how anomalies in gauge theories show up in the brane tilings. 1
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