DREADD_agonist_21_HNMR_22851_MedChemExpress
人参皂苷治疗骨性关节炎的研究进展
特产研究163Special Wild Economic Animal and Plant ResearchDOI：10.16720/ki.tcyj.2023.093人参皂苷治疗骨性关节炎的研究进展郭校妍1，张伟东1，张扬1※（吉林大学药学院，吉林长春130021）摘要：人参在防治关节软骨损伤退变及参与体外培养软骨细胞修复关节软骨缺损中具有较好治疗前景。
人参皂苷作为人参的主要药理活性成分，在治疗骨性关节炎的进程中发挥关键作用。
人参皂苷根据不同的结构被分为不同的类型，各类型均含有多种人参皂苷单体成分，其治疗骨性关节炎的机制也各不相同。
本文对不同人参皂苷单体治疗骨性关节炎的研究进行梳理和总结，探讨其治疗骨性关节炎的潜在可能性和作用机制，为后期临床应用提供依据。
关键词：骨性关节炎；人参皂苷；信号通路中图分类号：R285文献标识码：A文章编号：1001-4721（2023）03-0163-06Research Progress of Ginsenosides in the Treatment of OsteoarthritisGUO Xiaoyan1,ZHANG Weidong1,ZHANG Yang1※（School of Pharmaceutical Sciences,Jilin University,Changchun130021,China）Abstract:Ginseng has pharmacological effects such as anti-inflammatory,antioxidant,antidepressant,anti-Alzheimer's and anti-athero-sclerosis.Current studies have found that it has good therapeutic prospects in preventing degeneration of articular cartilage damage and parti-cipating in in vitro culture of chondrocytes to repair articular cartilage defects.Ginsenosides,as the main pharmacological active component of ginseng,also play an important role in the process of treating osteoarthritis.Ginsenosides can be classified into different types because of their different structures,and each type contains a variety of ginsenoside monomer components with different mechanisms for the treatment of osteoarthritis.In this paper,we review the research progress of different ginsenoside monomers in the treatment of osteoarthritis,and ex-plore their potential possibilities and mechanisms for the treatment of osteoarthritis,so as to provide a basis for later clinical application. Key words:osteoarthritis;ginsenosides;signaling pathway骨性关节炎（Osteoarthritis,OA）是一种退行性病变，系由于增龄、肥胖、遗传、劳损、创伤、关节先天性异常和关节畸形等诸多因素引起的关节软骨退化损伤、关节边缘和软骨下骨反应性增生。
FDA批准的精准医疗诊断体外器械一览表List of Cleared or Approved Companion Diagnostic Devices
Drug Trade Name
NDA/BLA
Device Trade Name
PMA
Device Manufacturer
Intended Use (IU)/ Indications for Use (IFU)
(imatinibmesylate)
NDA 021588
The c-KitpharmDxis indicated as an aid in the differential diagnosis of gastrointestinal stromal tumors (GIST). After diagnosis of GIST, results from c-KitpharmDxmay be used as an aid in identifying those patients eligible for treatment withGleevec/Glivec(imatinibmesylate).
(deferasirox)
Gilotrif
NDA 201292
therascreenEGFR RGQ PCR Kit
P120022
QiagenManchester, Ltd.
ThetherascreenEGFR RGQ PCR Kit is a real-time PCR test for the qualitative detection of exon 19 deletions and exon 21 (L858R) substitution mutations of the epidermal growth factor receptor (EGFR) gene in DNA derived from formalin-fixed paraffin-embedded (FFPE) non-small cell lung cancer (NSCLC) tumor tissue. The test is intended to be used to select patients with NSCLC for whom GILOTRIF (afatinib), an EGFR tyrosine kinase inhibitor (TKI), is indicated. Safety and efficacy of GILOTRIF (afatinib) have not been established in patients whose tumors have L861Q, G719X, S768I, exon 20 insertions, and T790M mutations, which are also detected by thetherascreenEGFR RGQ PCR Kit.
安捷伦产品目录
15
Real-Time PCR
16
Mx3000P QPCR System
17
Brilliant III Ultra-Fast SYBR Green QPCR and QRT-PCR Reagents
18
Brilliant III Ultra-Fast QPCR and QRT-PCR Reagents
Agilent / STRATAGENE
Agilent website: /genomics
Welgene | Agilent Stratagene
威健股份有限公司 | Stratagene 總代理
Table of Content
Table of Contents
/ XL1-Red Competent Cells SoloPack Gold Supercompetent Cells
/ TK Competent Cells Specialty Cells
/ Classic Cells / Fine Chemicals For Competent Cells
適用於 UNG 去汙染或 bisulphite
sequencing
適用於 TA Cloning
最高敏感性
取代傳統 Taq 的好選擇
-
2
威健股份有限公司 | Stratagene 總代理
PCR Enzyme & Instrument
Agilent SureCycler 8800
市場上領先的 cycling 速度和 sample 體積 10 ～ 100 μL 簡易快速可以選擇 96 well 和 384 well 操作盤 優秀的溫控設備讓各個 well 都能保持溫度的穩定 七吋的高解析度觸控螢幕讓操作上更為簡便 可以透過網路遠端操控儀器及監控儀器 Agilent 專業的技術支援可以幫助您應對各種 PCR 的問題
丹参治疗肝癌分子机制的网络药理学探讨
丹参治疗肝癌分子机制的网络药理学探讨An network pharmacological study on molecular mechanism ofsalvia miltiorrhiza on liver cancer徐倩1曾柏荣2*（1.湖南中医药大学，湖南 长沙，410208；2.湖南中医药大学第一附属医院，湖南 长沙，410007）中图分类号：R285文献标识码：A文章编号：1674-7860（2020）31-0001-07证型：IAD【摘要】目的：基于网络药理学方法预测丹参治疗肝癌的可能作用靶点及机制。
方法：通过中药系统药理学数据库和分析平台（Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform，TCMSP）收集中药丹参的活性成分及其对应的靶基因，运用GeneCards数据库、DrugBank数据库获得肝癌相关靶基因，匹配共同基因作为丹参治疗肝癌的潜在靶标。
应用Cytoscape软件完成“中药-活性成分-作用靶点-疾病”网络，通过String数据库完成蛋白相互作用（Protein-protein interaction，PPI）网络，最后基于Metascape数据库进行基因本体论（Gene Ontology，GO）及京都基因和基因组百科全书（Kyoto Encyclopedia of Genes and Genomes，KEGG）富集分析。
结果：获得丹参酮ⅡA、隐丹参酮等59个丹参治疗肝癌的活性成分，作用于77个潜在靶标，预测可能与磷脂酰肌醇3-激酶/蛋白激酶B（Phosphatidylinositol 3-Kinase/Protein KinaseuB，PI3K-AKT）、乙型肝炎、人类T细胞白血病病毒1型（Human T Cell Leukemia Virus Type 1，HTLV-1）感染、癌症中的miRNAs 等信号通路有关。
碱基切除修复抑制剂甲氧胺联合β-榄香烯治疗恶性脑胶质瘤的实验研究
序言β-榄香烯属国家二类非细胞毒性抗肿瘤新药，临床研究证实其对包括脑胶质瘤在内的多种肿瘤疗效确切，且无其他传统化疗药常有的骨髓抑制、肝肾功能损害等毒副作用。
但目前临床应用的榄香烯乳注射液因其存在静脉炎发生率很高、剂型性质不稳定等缺点，其进一步的应用受到了较大的限制。
碱基切除修复抑制剂甲氧胺（Methoxyamine），可通过裂解核酸内切酶破坏DNA碱基切除修复过程，从而抑制肿瘤细胞对损伤作用的修复反应。
据此，可认为抑制DNA 碱基切除修复可能是增强肿瘤细胞化疗敏感性的潜在靶点，目前多项实验报道也已证实了甲氧胺可增强烷化剂和放疗的抗肿瘤效果。
近年来，通过纳米技术构建的纳米脂质体在提高药物溶解度、增加药物稳定性、降低药物副作用、缓控释给药等方面较普通的脂质体有了显著的提高。
研究表明，纳米脂质体对正常细胞和组织无损伤作用，并可长时间吸附于靶细胞周围，因此使药物能充分向靶组织渗透，也可以通过静电吸附效应与细胞膜接触而融合而进入细胞内。
因此将药物包封于纳米脂质体被认为可以改变被包封药物的体内分布，提高药物治疗指数，降低药物毒性。
基于增强β-榄香烯的疗效，减少毒副作用的目的，本课题研究内容分两部分：（一）联合碱基切除修复抑制剂甲氧胺，探讨是否在体内外抗瘤活性上具有协同作用，以期减少榄香烯用量，降低毒副反应，为其在临床的应用提供实验和理论依据。
（二）、利用纳米脂质体技术构建新型的β-榄香烯-纳米脂质体药物传递系统，初步探讨其体外抗瘤活性。
II碱基切除修复抑制剂甲氧胺联合β-榄香烯治疗恶性脑胶质瘤的实验研究中文摘要胶质瘤是成人神经系统最常见的原发性肿瘤，手术全切除率很低，复发率高，当前多种治疗效果仍不理想。
榄香烯属国家二类非细胞毒性抗肿瘤新药，临床研究发现其对多种肿瘤疗效确切，而且还具有提高和改善机体免疫功能，与放化疗协同作用等独特效果。
但是肿瘤细胞具有强大的DNA损伤修复机制，会对化疗药物产生抗性。
因此抑制这种内在的DNA修复过程，如碱基切除修复抑制剂甲氧胺的联合应用有利于提高化疗药物的抗瘤效果。
Bioanalytical Method ValidationGuidance for Indust
Guidance for Industry Bioanalytical Method ValidationU.S. Department of Health and Human ServicesFood and Drug AdministrationCenter for Drug Evaluation and Research (CDER)Center for Veterinary Medicine (CVM)May 2001BPGuidance for Industry Bioanalytical Method ValidationAdditional copies are available from:Drug Information Branch (HFD-210)Center for Drug Evaluation and Research (CDER)5600 Fishers Lane, Rockville, MD 20857 (Tel) 301-827-4573Internet at /cder/guidance/index.htmorCommunications Staff (HFV-12)Center for Veterinary Medicine (CVM)7500 Standish Place, Rockville, MD 20855 (Tel) 301–594-1755Internet at /cvmU.S. Department of Health and Human ServicesFood and Drug AdministrationCenter for Drug Evaluation and Research (CDER)Center for Veterinary Medicine (CVM)May 2001BPTable of ContentsI.INTRODUCTION (1)II.BACKGROUND (1)A.F ULL V ALIDATION (2)B.P ARTIAL V ALIDATION (2)C.C ROSS-V ALIDATION (3)III.REFERENCE STANDARD (4)IV.METHOD DEVELOPMENT: CHEMICAL ASSAY (4)A.S ELECTIVITY (4)B.A CCURACY, P RECISION, AND R ECOVERY (5)C.C ALIBRATION/S TANDARD C URVE (5)D.S TABILITY (6)E.P RINCIPLES OF B IOANALYTICAL M ETHOD V ALIDATION AND E STABLISHMENT (8)F.S PECIFIC R ECOMMENDATIONS FOR M ETHOD V ALIDATION (10)V.METHOD DEVELOPMENT: MICROBIOLOGICAL AND LIGAND-BINDING ASSAYS (11)A.S ELECTIVITY I SSUES (11)B.Q UANTIFICATION I SSUES (12)VI.APPLICATION OF VALIDATED METHOD TO ROUTINE DRUG ANALYSIS (13)A CCEPTANCE C RITERIA FOR THE R UN (15)VII.DOCUMENTATION (16)A.S UMMARY I NFORMATION (16)B.D OCUMENTATION FOR M ETHOD E STABLISHMENT (17)C.A PPLICATION TO R OUTINE D RUG A NALYSIS (17)D.O THER I NFORMATION (19)GLOSSARY (20)GUIDANCE FOR INDUSTRY1Bioanalytical Method ValidationI.INTRODUCTIONThis guidance provides assistance to sponsors of investigational new drug applications (INDs), new drug applications (NDAs), abbreviated new drug applications (ANDAs), and supplements in developing bioanalytical method validation information used in human clinical pharmacology, bioavailability (BA), and bioequivalence (BE) studies requiring pharmacokinetic (PK) evaluation. This guidance also applies to bioanalytical methods used for non-human pharmacology/toxicology studies and preclinical studies. For studies related to the veterinary drug approval process, this guidance applies only to blood and urine BA, BE, and PK studies.The information in this guidance generally applies to bioanalytical procedures such as gas chromatography (GC), high-pressure liquid chromatography (LC), combined GC and LC mass spectrometric (MS) procedures such as LC-MS, LC-MS-MS, GC-MS, and GC-MS-MS performed for the quantitative determination of drugs and/or metabolites in biological matricessuch as blood, serum, plasma, or urine. This guidance also applies to other bioanalytical methods, such as immunological and microbiological procedures, and to other biological matrices, such as tissue and skin samples.This guidance provides general recommendations for bioanalytical method validation. The recommendations can be adjusted or modified depending on the specific type of analytical method used. II.BACKGROUND1 This guidance has been prepared by the Biopharmaceutics Coordinating Committee in the Center for Drug Evaluation and Research (CDER) in cooperation with the Center for Veterinary Medicine (CVM) at the Food and Drug Administration.This guidance has been developed based on the deliberations of two workshops: (1) Analytical Methods Validation: Bioavailability, Bioequivalence, and Pharmacokinetic Studies (held on December 3B5, 19902 ) and (2) Bioanalytical Methods Validation C A Revisit With a Decade of Progress (held on January 12B14, 20003).Selective and sensitive analytical methods for the quantitative evaluation of drugs and their metabolites (analytes) are critical for the successful conduct of preclinical and/or biopharmaceutics and clinical pharmacology studies. Bioanalytical method validation includes all of the procedures that demonstrate that a particular method used for quantitative measurement of analytes in a given biological matrix, such as blood, plasma, serum, or urine, is reliable and reproducible for the intended use. The fundamental parameters for this validation include (1) accuracy, (2) precision, (3) selectivity, (4) sensitivity, (5) reproducibility, and (6) stability. Validation involves documenting, through the use of specific laboratory investigations, that the performance characteristics of the method are suitable and reliable for the intended analytical applications. The acceptability of analytical data corresponds directly to the criteria used to validate the method.Published methods of analysis are often modified to suit the requirements of the laboratory performing the assay. These modifications should be validated to ensure suitable performance of the analytical method. When changes are made to a previously validated method, the analyst should exercise judgment as to how much additional validation is needed. During the course of a typical drug development program, a defined bioanalytical method undergoes many modifications. The evolutionary changes to support specific studies and different levels of validation demonstrate the validity of an assay’s performance. Different types and levels of validation are defined and characterized as follows:A.Full Validation•Full validation is important when developing and implementing a bioanalytical method for the first time.•Full validation is important for a new drug entity.• A full validation of the revised assay is important if metabolites are added to an existing assay for quantification.B.Partial ValidationPartial validations are modifications of already validated bioanalytical methods. Partial validation can range from as little as one intra-assay accuracy and precision determination to a nearly full2 Workshop Report: Shah, V.P. et al., Pharmaceutical Research: 1992; 9:588-592.3 Workshop Report: Shah, V.P. et al., Pharmaceutical Research: 2000; 17:in press.validation. Typical bioanalytical method changes that fall into this category include, but are not limited to:•Bioanalytical method transfers between laboratories or analysts•Change in analytical methodology (e.g., change in detection systems)•Change in anticoagulant in harvesting biological fluid•Change in matrix within species (e.g., human plasma to human urine)•Change in sample processing procedures•Change in species within matrix (e.g., rat plasma to mouse plasma)•Change in relevant concentration range•Changes in instruments and/or software platforms•Limited sample volume (e.g., pediatric study)•Rare matrices•Selectivity demonstration of an analyte in the presence of concomitant medications•Selectivity demonstration of an analyte in the presence of specific metabolitesC.Cross-ValidationCross-validation is a comparison of validation parameters when two or more bioanalytical methods are used to generate data within the same study or across different studies. An example of cross-validation would be a situation where an original validated bioanalytical method serves as thereference and the revised bioanalytical method is the comparator. The comparisons should be done both ways.When sample analyses within a single study are conducted at more than one site or more than one laboratory, cross-validation with spiked matrix standards and subject samples should be conducted at each site or laboratory to establish interlaboratory reliability. Cross-validation should also be considered when data generated using different analytical techniques (e.g., LC-MS-MS vs.ELISA4) in different studies are included in a regulatory submission.All modifications should be assessed to determine the recommended degree of validation. The analytical laboratory conducting pharmacology/toxicology and other preclinical studies for regulatory submissions should adhere to FDA=s Good Laboratory Practices (GLPs)5 (21 CFR part 58) and to sound principles of quality assurance throughout the testing process. The bioanalytical method for human BA, BE, PK, and drug interaction studies must meet the criteria in 21 CFR 320.29. The analytical laboratory should have a written set of standard operating procedures (SOPs) to ensure a complete system of quality control and assurance. The SOPs should cover all aspects of analysis from the time the sample is collected and reaches the laboratory until the results of the analysis are reported. The SOPs also should include record keeping, security and chain of sample custody4 Enzyme linked immune sorbent assay5 For the Center for Veterinary Medicine, all bioequivalence studies are subject to Good Laboratory Practices.(accountability systems that ensure integrity of test articles), sample preparation, and analytical tools such as methods, reagents, equipment, instrumentation, and procedures for quality control and verification of results.The process by which a specific bioanalytical method is developed, validated, and used in routine sample analysis can be divided into (1) reference standard preparation, (2) bioanalytical method development and establishment of assay procedure, and (3) application of validated bioanalytical method to routine drug analysis and acceptance criteria for the analytical run and/or batch. These three processes are described in the following sections of this guidance.III.REFERENCE STANDARDAnalysis of drugs and their metabolites in a biological matrix is carried out using samples spiked with calibration (reference) standards and using quality control (QC) samples. The purity of the reference standard used to prepare spiked samples can affect study data. For this reason, an authenticated analytical reference standard of known identity and purity should be used to prepare solutions of known concentrations. If possible, the reference standard should be identical to the analyte. When this is not possible, an established chemical form (free base or acid, salt or ester) of known purity can be used. Three types of reference standards are usually used: (1) certified reference standards (e.g., USP compendial standards); (2) commercially supplied reference standards obtained from a reputable commercial source; and/or (3) other materials of documented purity custom-synthesized by an analytical laboratory or other noncommercial establishment. The source and lot number, expiration date, certificates of analyses when available, and/or internally or externally generated evidence of identity and purity should be furnished for each reference standard.IV.METHOD DEVELOPMENT: CHEMICAL ASSAYThe method development and establishment phase defines the chemical assay. The fundamental parameters for a bioanalytical method validation are accuracy, precision, selectivity, sensitivity, reproducibility, and stability. Measurements for each analyte in the biological matrix should be validated. In addition, the stability of the analyte in spiked samples should be determined. Typical method development and establishment for a bioanalytical method include determination of (1) selectivity, (2) accuracy, precision, recovery, (3) calibration curve, and (4) stability of analyte in spiked samples.A.SelectivitySelectivity is the ability of an analytical method to differentiate and quantify the analyte in thepresence of other components in the sample. For selectivity, analyses of blank samples of theappropriate biological matrix (plasma, urine, or other matrix) should be obtained from at leastsix sources. Each blank sample should be tested for interference, and selectivity should be ensured at the lower limit of quantification (LLOQ).Potential interfering substances in a biological matrix include endogenous matrix components, metabolites, decomposition products, and in the actual study, concomitant medication and other exogenous xenobiotics. If the method is intended to quantify more than one analyte, each analyte should be tested to ensure that there is no interference.B.Accuracy, Precision, and RecoveryThe accuracy of an analytical method describes the closeness of mean test results obtained by the method to the true value (concentration) of the analyte. Accuracy is determined by replicate analysis of samples containing known amounts of the analyte. Accuracy should be measured using a minimum of five determinations per concentration. A minimum of three concentrations in the range of expected concentrations is recommended. The mean value should be within 15% of the actual value except at LLOQ, where it should not deviate by more than 20%. The deviation of the mean from the true value serves as the measure of accuracy.The precision of an analytical method describes the closeness of individual measures of an analyte when the procedure is applied repeatedly to multiple aliquots of a single homogeneous volume of biological matrix. Precision should be measured using a minimum of five determinations per concentration. A minimum of three concentrations in the range of expected concentrations is recommended. The precision determined at each concentration level should not exceed 15% of the coefficient of variation (CV) except for the LLOQ, where it should not exceed 20% of the CV. Precision is further subdivided into within-run, intra-batch precision or repeatability, which assesses precision during a single analytical run, and between-run, inter-batch precision or repeatability, which measures precision with time, and may involve different analysts, equipment, reagents, and laboratories.The recovery of an analyte in an assay is the detector response obtained from an amount of the analyte added to and extracted from the biological matrix, compared to the detector response obtained for the true concentration of the pure authentic standard. Recovery pertains to the extraction efficiency of an analytical method within the limits of variability. Recovery of the analyte need not be 100%, but the extent of recovery of an analyte and of the internal standard should be consistent, precise, and reproducible. Recovery experiments should be performed by comparing the analytical results for extracted samples at three concentrations (low, medium, and high) with unextracted standards that represent 100% recovery.C.Calibration/Standard CurveA calibration (standard) curve is the relationship between instrument response and known concentrations of the analyte. A calibration curve should be generated for each analyte in thesample. A sufficient number of standards should be used to adequately define the relationship between concentration and response. A calibration curve should be prepared in the same biological matrix as the samples in the intended study by spiking the matrix with known concentrations of the analyte. The number of standards used in constructing a calibration curve will be a function of the anticipated range of analytical values and the nature of theanalyte/response relationship. Concentrations of standards should be chosen on the basis of the concentration range expected in a particular study. A calibration curve should consist of a blank sample (matrix sample processed without internal standard), a zero sample (matrix sample processed with internal standard), and six to eight non-zero samples covering the expected range, including LLOQ.1.Lower Limit of Quantification (LLOQ)The lowest standard on the calibration curve should be accepted as the limit ofquantification if the following conditions are met:C The analyte response at the LLOQ should be at least 5 times the responsecompared to blank response.C Analyte peak (response) should be identifiable, discrete, and reproducible witha precision of 20% and accuracy of 80-120%.2.Calibration Curve/Standard Curve/Concentration-ResponseThe simplest model that adequately describes the concentration-response relationshipshould be used. Selection of weighting and use of a complex regression equation should be justified. The following conditions should be met in developing a calibration curve:C#20% deviation of the LLOQ from nominal concentrationC#15% deviation of standards other than LLOQ from nominal concentrationAt least four out of six non-zero standards should meet the above criteria, including the LLOQ and the calibration standard at the highest concentration. Excluding thestandards should not change the model used.D.StabilityDrug stability in a biological fluid is a function of the storage conditions, the chemical properties of the drug, the matrix, and the container system. The stability of an analyte in a particular matrix and container system is relevant only to that matrix and container system and should not be extrapolated to other matrices and container systems. Stability procedures should evaluate the stability of the analytes during sample collection and handling, after long-term (frozen at theintended storage temperature) and short-term (bench top, room temperature) storage, and after going through freeze and thaw cycles and the analytical process. Conditions used in stability experiments should reflect situations likely to be encountered during actual sample handling and analysis. The procedure should also include an evaluation of analyte stability in stock solution.All stability determinations should use a set of samples prepared from a freshly made stock solution of the analyte in the appropriate analyte-free, interference-free biological matrix. Stock solutions of the analyte for stability evaluation should be prepared in an appropriate solvent at known concentrations.1.Freeze and Thaw StabilityAnalyte stability should be determined after three freeze and thaw cycles. At least three aliquots at each of the low and high concentrations should be stored at the intendedstorage temperature for 24 hours and thawed unassisted at room temperature. Whencompletely thawed, the samples should be refrozen for 12 to 24 hours under the sameconditions. The freeze–thaw cycle should be repeated two more times, then analyzedon the third cycle. If an analyte is unstable at the intended storage temperature, thestability sample should be frozen at -700C during the three freeze and thaw cycles.2.Short-Term Temperature StabilityThree aliquots of each of the low and high concentrations should be thawed at roomtemperature and kept at this temperature from 4 to 24 hours (based on the expectedduration that samples will be maintained at room temperature in the intended study) and analyzed.3.Long-Term StabilityThe storage time in a long-term stability evaluation should exceed the time between the date of first sample collection and the date of last sample analysis. Long-term stabilityshould be determined by storing at least three aliquots of each of the low and highconcentrations under the same conditions as the study samples. The volume of samples should be sufficient for analysis on three separate occasions. The concentrations of allthe stability samples should be compared to the mean of back-calculated values for the standards at the appropriate concentrations from the first day of long-term stabilitytesting.4.Stock Solution StabilityThe stability of stock solutions of drug and the internal standard should be evaluated at room temperature for at least 6 hours. If the stock solutions are refrigerated or frozenfor the relevant period, the stability should be documented. After completion of thedesired storage time, the stability should be tested by comparing the instrumentresponse with that of freshly prepared solutions.5.Post-Preparative StabilityThe stability of processed samples, including the resident time in the autosampler, should be determined. The stability of the drug and the internal standard should be assessedover the anticipated run time for the batch size in validation samples by determiningconcentrations on the basis of original calibration standards.Although the traditional approach of comparing analytical results for stored samples with those for freshly prepared samples has been referred to in this guidance, other statistical approaches based on confidence limits for evaluation of an analyte=s stability in abiological matrix can be used. SOPs should clearly describe the statistical method andrules used. Additional validation may include investigation of samples from dosedsubjects.E.Principles of Bioanalytical Method Validation and Establishment•The fundamental parameters to ensure the acceptability of the performance of a bioanalytical method validation are accuracy, precision, selectivity, sensitivity,reproducibility, and stability.• A specific, detailed description of the bioanalytical method should be written. This can be in the form of a protocol, study plan, report, and/or SOP.•Each step in the method should be investigated to determine the extent to which environmental, matrix, material, or procedural variables can affect the estimation of analyte in the matrix from the time of collection of the material up to and including the time ofanalysis.•It may be important to consider the variability of the matrix due to the physiological nature of the sample. In the case of LC-MS-MS-based procedures, appropriate steps should be taken to ensure the lack of matrix effects throughout the application of the method,especially if the nature of the matrix changes from the matrix used during method validation.• A bioanalytical method should be validated for the intended use or application. All experiments used to make claims or draw conclusions about the validity of the methodshould be presented in a report (method validation report).•Whenever possible, the same biological matrix as the matrix in the intended samples should be used for validation purposes. (For tissues of limited availability, such as bone marrow, physiologically appropriate proxy matrices can be substituted.)•The stability of the analyte (drug and/or metabolite) in the matrix during the collection process and the sample storage period should be assessed, preferably prior to sampleanalysis.•For compounds with potentially labile metabolites, the stability of analyte in matrix from dosed subjects (or species) should be confirmed.•The accuracy, precision, reproducibility, response function, and selectivity of the method for endogenous substances, metabolites, and known degradation products should beestablished for the biological matrix. For selectivity, there should be evidence that thesubstance being quantified is the intended analyte.•The concentration range over which the analyte will be determined should be defined in the bioanalytical method, based on evaluation of actual standard samples over the range,including their statistical variation. This defines the standard curve.• A sufficient number of standards should be used to adequately define the relationship between concentration and response. The relationship between response and concentration should be demonstrated to be continuous and reproducible. The number of standards used should be a function of the dynamic range and nature of the concentration-responserelationship. In many cases, six to eight concentrations (excluding blank values) can define the standard curve. More standard concentrations may be recommended for nonlinear than for linear relationships.•The ability to dilute samples originally above the upper limit of the standard curve should be demonstrated by accuracy and precision parameters in the validation.•In consideration of high throughput analyses, including but not limited to multiplexing, multicolumn, and parallel systems, sufficient QC samples should be used to ensure control of the assay. The number of QC samples to ensure proper control of the assay should be determined based on the run size. The placement of QC samples should be judiciously considered in the run.•For a bioanalytical method to be considered valid, specific acceptance criteria should be set in advance and achieved for accuracy and precision for the validation of QC samples over the range of the standards.F.Specific Recommendations for Method Validation•The matrix-based standard curve should consist of a minimum of six standard points, excluding blanks, using single or replicate samples. The standard curve should cover the entire range of expected concentrations.•Standard curve fitting is determined by applying the simplest model that adequately describes the concentration-response relationship using appropriate weighting and statistical tests for goodness of fit.•LLOQ is the lowest concentration of the standard curve that can be measured with acceptable accuracy and precision. The LLOQ should be established using at least five samples independent of standards and determining the coefficient of variation and/orappropriate confidence interval. The LLOQ should serve as the lowest concentration on the standard curve and should not be confused with the limit of detection and/or the low QC sample. The highest standard will define the upper limit of quantification (ULOQ) of an analytical method.•For validation of the bioanalytical method, accuracy and precision should be determined using a minimum of five determinations per concentration level (excluding blank samples).The mean value should be within ±15% of the theoretical value, except at LLOQ, where it should not deviate by more than ±20%. The precision around the mean value should not exceed 15% of the CV, except for LLOQ, where it should not exceed 20% of the CV.Other methods of assessing accuracy and precision that meet these limits may be equally acceptable.•The accuracy and precision with which known concentrations of analyte in biological matrix can be determined should be demonstrated. This can be accomplished by analysis ofreplicate sets of analyte samples of known concentrations C QC samples C from anequivalent biological matrix. At a minimum, three concentrations representing the entire range of the standard curve should be studied: one within 3x the lower limit of quantification (LLOQ) (low QC sample), one near the center (middle QC), and one near the upperboundary of the standard curve (high QC).•Reported method validation data and the determination of accuracy and precision should include all outliers; however, calculations of accuracy and precision excluding values that are statistically determined as outliers can also be reported.•The stability of the analyte in biological matrix at intended storage temperatures should be established. The influence of freeze-thaw cycles (a minimum of three cycles at twoconcentrations in triplicate) should be studied.•The stability of the analyte in matrix at ambient temperature should be evaluated over a time period equal to the typical sample preparation, sample handling, and analytical run times.•Reinjection reproducibility should be evaluated to determine if an analytical run could be reanalyzed in the case of instrument failure.•The specificity of the assay methodology should be established using a minimum of six independent sources of the same matrix. For hyphenated mass spectrometry-basedmethods, however, testing six independent matrices for interference may not be important.In the case of LC-MS and LC-MS-MS-based procedures, matrix effects should beinvestigated to ensure that precision, selectivity, and sensitivity will not be compromised.Method selectivity should be evaluated during method development and throughout methodvalidation and can continue throughout application of the method to actual study samples.•Acceptance/rejection criteria for spiked, matrix-based calibration standards and validation QC samples should be based on the nominal (theoretical) concentration of analytes.Specific criteria can be set up in advance and achieved for accuracy and precision over therange of the standards, if so desired.V.METHOD DEVELOPMENT: MICROBIOLOGICAL AND LIGAND-BINDING ASSAYSMany of the bioanalytical validation parameters and principles discussed above are also applicable to microbiological and ligand-binding assays. However, these assays possess some unique characteristics that should be considered during method validation.A.Selectivity IssuesAs with chromatographic methods, microbiological and ligand-binding assays should be shown to be selective for the analyte. The following recommendations for dealing with two selectivity issues should be considered:1.Interference From Substances Physiochemically Similar to the Analyte•Cross-reactivity of metabolites, concomitant medications, or endogenouscompounds should be evaluated individually and in combination with the analyteof interest.•When possible, the immunoassay should be compared with a validated reference method (such as LC-MS) using incurred samples and predetermined criteria foragreement of accuracy of immunoassay and reference method.。
网上文献资料大全
网上文献资料大全网上文献资料大全医学文献检索/PubMed/medline.htmlscience杂志/nature杂志/PNAS杂志JBC杂志protocol-online: CMS MBR 生物网站/srs5binscience online国内镜像/Cell杂志/美国科学院院刊PNAS网址(免费）/网上全文的生物学期刊/bio/journal.htm国家自然科学基金委员会//index.php3///retail生物教学资料与学生论文/teaching/index.htm美国生物技术信息中心(NCBI) /人类基因组数据库(NCBI) /dBest/index.html人类基因组数据库(NCBI) /web/Genbank/index.html 日本DNA数据库(DDBJ) http://www.ddbj.nig.ac.jp/蛋白质信息资源(PIR) /Dan/proteins/pir.html基因组数据库(GD) http://www.gdb/org/蛋白质结构数据库(PD) /Sander蛋白质二级结构数据库http://www.sander.embl-heidelberg.de/ Rutgers大学核酸数据库工程/蛋白质科学网络服务器/Pangea公司生物信息学服务台器/HIV基因数据库/冷泉港实验室//hotsite/006/00601.asp/web/Methods___Techniques/index.html (: Methods & Techniques).tw/bio86/bionet.htm/index.php3国际绿色和平组织/国际性环保网站，全面介绍气候环境、核能污染情况、海洋生物等生物谷中国生物论坛丁香园论坛/bbs/西陆生物探索者（西陆）全文数据库检索论坛/21世纪生物论坛/中国生物论坛/Bio-Engine论坛:8080/bbs/cgi- ... p;BypassCookie=true明白读书论坛/网上读书园地/club/index.asp37℃医学网/中国材料网讨论区/生命玄机BBS /BioSino BBS /cgi-bin/u***gi/Ultimate.cgi分子生物学个人交流网论坛/dvbbs/index.asp捌号楼医学论坛/bbs/index.asp上海医学生联盟论坛/dvbbs/boardstat.asp?boardid=0protocol online论坛/forums/index.php神经科学论坛/bbs/生命信息学专业论坛/postnuke免疫信息学论坛/forum/index.asp极酷论坛/cgi-bin/forum/leoboard.cgi实验技术与方法：目前最好的实验方法站点之一: 有近三百种经典实验方法的生物学网站: /目前最完美的生物技术收集网站之一: :包括动植物、果蝇、分子生物、细胞生物学等等晶美生物实验方法: /site/site/practice/practice.htmWiley公司细胞生物学实验技术方法（全部可下载）: /bioengineering/wiley/index.htm分子生物学实验方法大全（英文版）: /bioengineering/moletech.htm美国BD公司的中文网站：/china/:国内流式的老大（关于流式细胞术）：美国BD 公司成立于1897 年，是世界上最大的医疗技术及医疗设备公司之一。
生物信息学试题A卷2010
4、构建系统发生树，应使用 A、BLAST C、UPGMA B、FASTA D、Entrez
□□□□□□□□□□□□学生姓名：________________
5、在蛋白质一级数据库基础上，构建二级数据库应使用 A、近邻归并法 C、基因融合法 B、序列比对 D、Entrez
一、名词解释（每题 2 分，共 10 分） 1、基序（motif） 2、可读框（ORF） 5、 系统发生学 3、剪切变体
S 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Q 0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Y 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0
H 0.0 0.0 0.0 0.0 0.0 4.0 0.0 0.0 0.0 0.0 0.0
E
12
11
13
9
0
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159465..159895 /gene="rpl2" /number=2
ORIGIN 1 atgggcgaac gacgggaatt gaacccgcga atggtggatt cacaatccac taccttaatc 61 cacttggcta catccgcccc tactctgact caattaagag tcatgtcata tttcgtttta
7、欧洲生物信息研究所简称： A、SIB C、NCBI B、EBI D、MIPS
8、在蛋白质序列数据库中比较查询蛋白质序列，应使用 A、BLASTn C、tBLASTn 9、Profiles 数据库是 A、蛋白质序列数据库 C、蛋白质二级数据库 10、TreeBASE 系统主要用于 A、发现新基因 C、类群间系统发育关系研究 B、系统生物学研究 D、序列比对 B、核酸序列数据库 D、蛋白质结构数据库 B、BLASTp D、BLASTx
EHHADH是肝细胞癌脂肪酸代谢通路的关键基因：基于转录组分析
肝癌是我国一种常见的恶性肿瘤，恶性程度较高，病情进展较快［1］，也是60岁以下男性癌症死亡的主要原因［2］。
其中，肝细胞癌（HCC ）占原发性肝癌的70%~80%［3］。
由于HCC 通常被诊断为晚期，因此许多患者错过了最佳的治疗方法。
HCC 的发生机制还未研究透彻，且由于HCC 是由多种致病因素引起的复杂疾病，有必要阐明HCC 发生发展的潜在分子机制，特别是寻找潜在的分子生物学标记物来改善HCC 患者的预后。
既EHHADH is a key gene in fatty acid metabolism pathways in hepatocellular carcinoma:a transcriptomic analysisXIE Siyu,LI Miaosheng,JIANG Fengle,YI Qian,YANG WeiDepartment of Pathology,School of Basic Medical Sciences,Southern Medical University,Guangzhou 510515,China摘要：目的基于多数据库数据探索肝细胞癌（HCC ）发生发展的驱动基因并挖掘HCC 治疗的新生物靶点。
方法采用从TCGA 、GEO 和ICGC 数据库中获取的858例HCC 组织数据与493例癌旁组织数据（共1351例转录组和基因组数据），运用GSEA 筛选HCC 与癌旁的差异通路，进而筛选差异通路中显著富集的基因，获得Hub 基因3-hydroxyacyl CoA 脱氢酶（EHHADH ）。
基于TCGA 的HCC 数据集分析与EHHADH 转录组水平下调相关的基因突变，发现TP53突变最显著相关。
利用相关性分析探究TP53突变导致EHHADH 表达下调的机制。
基于Metascape 数据库预测EHHADH 参与HCC 发展的信号通路，发现与铁死亡信号通路显著相关。
对30例HCC 癌组织及配对的癌旁正常组织进行免疫组化染色，验证EHHADH 的表达情况。