fecal and systemic estrogens

Unit SevenText A BiopharmaceuticsBefore the reader can appreciate the meaning and clinical significance of biopharmaceutics, it is necessary to introduce the concept of drug bioavailability.1. appreciate [ə'pri:ʃ ieit] vt.欣赏；感激；领会；鉴别vi.增值；涨价2. bioavailability ['baiəuə,veilə'biləti] n.生物利用度；生物药效率为了使读者能够理解生物药剂学的含义和其对于药物临床应用的重要意义，有必要先给大家介绍一下药物生物利用度的概念。

BioavailabilityThe therapeutic response of a drug is normally dependent on an adequate concentration of the drug being achieved and then maintained at the site or sites of action of the drug. In the case of systemically acting drugs ( i. e. drugs that reach these sites via the systemic circulation) it is generally accepted for clinical purposes that a dynamic equilibrium exists between the concentration of drug at its site(s) of action and the concentration of drug in blood plasma. An important consequence of this dynamic equilibrium is that it permits a therapeutically effective concentration of drug to be achieved at its site(s) of action by adjustment of the concentration of drug in blood plasma. Strictly speaking, the concentration of drug in plasma water (i. e. protein-free plasma) is a more accurate index of drug concentration at the site(s) of action than the concentration of drug in whole plasma since a drug may often bind in a reversible manner to plasma protein. Only drug which is unbound (i. e. dissolved in plasma water) can pass out of the plasma through the capillary endothelium and reach other body fluids and tissues and hence its site(s) of action. Drug concentration in whole blood is also not considered to be an accurate indirect index of the concentration of drug at its site(s) of action since drug can bind to and enter blood cells. However, to measure the concentration of an unbound drug in plasma water requires more complex and sensitive assay methods than to measure the total concentration of both unbound and bound drug in total plasma. Thus, for clinical purposes, drug concentration in blood plasma is usually measured and is regarded as an index of drug concentration at the site(s) of action of the drug and of the clinicaleffects of the drug. However, it should be realized that this is a simplification and may not always be valid. Indeed one should not draw inferences about the clinical effects of a drug from its plasma concentration until it has been established that the two are consistently correlated. It has been assumed that the plasma drug concentration is directly proportional to the clinical effect of that drug.1. systemically [ sistə'mætikəli ] adv.有系统地，有组织地，有条理地，全身地systemic [si'stemik; -'sti:-] adj.系统的；体系的；全身的2. purpose ['pə:pəs] n.目的；用途；意志vt. 决心；企图；打算3. dynamic equilibrium [dai'næmik] [,i:kwi'libriəm] 动态平衡；动力平衡4. plasma ['plæzmə] n.等离子体；血浆5. reversible [ri'və:səbl] adj.可逆的；可撤消的；可反转的n. 双面布料6. capillary endothelium [kə'piləri, 'kæpi-] [,endəu'θi:liəm] 毛细血管内皮7. assay [ə'sei] n.化验；试验vt.分析；化验；尝试vi.鉴定；经检验证明内含成分8. simplification [,sɪmpləfə'keʃən] n.简单化；单纯化9. valid ['vælid] adj.有效的，有根据的；正当的10. draw inferences ['infərəns] 作出推论11. consistently [kən'sistəntli] adv.一贯地；一致地；坚实地12. proportional to [prə'pɔ:ʃənəl] 与……相称，与……成比例通常情况下，药物达到其作用部位、并维持足够的药物浓度，才能发挥疗效。

会计理论和资产评估的替代方法埃尔温·戴沃特经济学系，不列颠哥伦比亚大学，温哥华，不列颠哥伦比亚省，加拿大，V6N 1Z1电子邮件：diewert@econ.ubc.ca1.介绍在这一章中，我们研究以下问题：在连续的会计期间内，如何对企业所拥有的耐用资产进行价值评估并得出每一期的相应评估结果。

众所周知，在对企业的资产进行评估时，存在多种评估方法。

在这里我们主要介绍七种评估方法：（1）重置成本法；（2）物价指数法；（3）市场法；（4）功能系数法；（5）净现值法；（6）根据资产的具体指数调整历史成本；（7）通过跨期成本分摊来确定价值的方法。

就目前而言，重置成本法广泛被评估师所采用。

但是，这一方法存在着假设前提，即不存在通货膨胀这一现象或通货膨胀影响甚小，可忽略不计。

上述七种评估方法中，第二条至第六条，资产的价格都会随着时间的推移有所变动。

最后一种方法与固定费用跨期分摊紧密相联，将在文章的第八部分作出详细的说明，此处不再赘述。

2. 重置成本法“今天的一美元的购买力肯定与1897年的一美元的购买力不同。

这是由于消费价格总水平的波动，因而美元的购买力发生变化。

这一不同的价格量度就好比英寸与厘米之间的代换或是用橡皮带来测量字段。

”利文斯顿（1918年；114-115）。

历史成本折旧（如：资产价值下跌超过一个会计期间）可定义为：当评估出资产的使用寿命和确定了资产的相应折旧期限时，资产的原值就要合理的分摊与这一会计期限内，而历史成本折旧就是这一相对的周期性折旧金额。

相应的会计期间终结时资产的历史成本价值成本可简单的表述为原值减去累计折旧后的余额除以总使用年限。

在第二章，我们了解到运用历史成本法计价资产时所面临的主要问题：倘若在资产的采购期至企业所处的会计期间这一段时期内，资产的价格有了大幅度的变化（例如由通货膨胀所引起），则运用历史成本计价可能无法真实的反映资产的当前市场价值。

因此在通货膨胀的情况下，历史成本的折旧额会被低估而相应的收入会被夸大，同时企业所得税可能转变为资本得税。

International Journal ofMolecular SciencesReviewBioinformatics Approaches for Fetal DNA Fraction Estimation in Noninvasive Prenatal TestingXianlu Laura Peng1,2and Peiyong Jiang1,2,*1Li Ka Shing Institute of Health Sciences,The Chinese University of Hong Kong,Hong Kong,China;laurapeng@.hk2Department of Chemical Pathology,The Chinese University of Hong Kong,Prince of Wales Hospital, Hong Kong,China*Correspondence:jiangpeiyong@.hk;Tel.:+852-3763-6056Academic Editor:William Chi-shing ChoReceived:18January2017;Accepted:11February2017;Published:20February2017Abstract:The discovery of cell-free fetal DNA molecules in plasma of pregnant women has created a paradigm shift in noninvasive prenatal testing(NIPT).Circulating cell-free DNA in maternal plasma has been increasingly recognized as an important proxy to detect fetal abnormalities in a noninvasive manner.A variety of approaches for NIPT using next-generation sequencing have been developed,which have been rapidly transforming clinical practices nowadays.In such approaches, the fetal DNA fraction is a pivotal parameter governing the overall performance and guaranteeing the proper clinical interpretation of testing results.In this review,we describe the current bioinformatics approaches developed for estimating the fetal DNA fraction and discuss their pros and cons. Keywords:noninvasive prenatal testing;circulating cell-free DNA;fetal DNA fraction1.IntroductionThe discovery of circulating cell-free fetal DNA in maternal plasma[1]has created a paradigm shift in noninvasive prenatal testing(NIPT),which has rapidly made its way into clinical practices worldwide,for example,cell-free DNA-based chromosomal aneuploidy detection[2–8]and diagnosis of monogenic diseases[9–15].The circulating cell-free DNA(cfDNA)in a pregnant woman is a mixture of predominant maternal DNA derived from the hematopoietic system of the mother[16,17]and fetal DNA released through the apoptosis of cytotrophoblast cells during fetal development[18,19]. The proportion of fetal DNA molecules among the total cfDNA molecules in maternal circulation is expressed as fetal DNA fraction,which is a paramount factor for determining the overall performance of NIPT[15,20–22]and interpreting clinical assessments[7,23–25].In noninvasive fetal aneuploidy detection,the fetal DNA fraction in maternal plasma is linearly correlated with the extent of chromosomal abnormalities present in plasma of pregnant women[3,6,7]. The fetal DNA concentration below4%in a maternal plasma sample would suggest a potential issue present in the quality control(QC)step,because the limited amount of fetal DNA molecules to be detected and analyzed may give rise to a false negative result[20,26–28].Therefore,it is important to estimate the fetal DNA fraction accurately,making sure that it has passed the QC threshold to guarantee a sufficient amount of fetal DNA present in a testing sample and make it possible to arrive at a proper interpretation of the sequencing result.In addition,the fetal DNA fraction has been incorporated into bioinformatics diagnostic algorithms by a number of laboratories[7,23,24].Monogenic diseases comprise a larger proportion of genetic diseases than chromosomal aneuploidies[15].However,the cfDNA-based NIPT for single-gene diseases is much more challenging, because the cfDNA in maternal plasma is generally of minor population,hampering the reliable deduction of the maternal inherence of fetus at single-nucleotide resolution.Technologically,the Int.J.Mol.Sci.2017,18,453;doi:10.3390//journal/ijmsdevelopment of relative haplotype dosage analysis(RHDO),which utilizes information regarding parental haplotypesflanking the variants of interest,has been demonstrated to greatly improve the accuracy of single-gene disorder detection[9,10,13].More recently,researchers have illustrated that the use of linked-read sequencing technology allows for directly ascertaining parental haplotypes surrounding the genes of interest,making RHDO analysis a universal NIPT method for single-gene diseases[29].This work has made an important step forward towards the real clinical utility regarding cfDNA-based single-gene disease testing.Such RHDO analysis took advantage of the fetal DNA fraction as a key parameter to determine the statistical thresholds,indicating if a particular maternal haplotype presumably inherited by the fetus exhibits a statistically significant over-presentation in maternal plasma of a pregnant woman[9,23].In this review,we discuss a number of existing approaches for the determination of fetal DNA fraction,as well as their advantages and disadvantages(Table1).The simplified principles for these approaches are diagrammatically depicted in Figure1.Figure1.Schematic illustration of current approaches for the determination of fetal DNA fraction in maternal circulating cell-free DNA(cfDNA).(a)Y chromosomal(chr)sequence-based fetal DNA fraction estimate[3,22];(b)Single-nucleotide polymorphism(SNP)-based approach.A direct way to estimate the fetal DNA fraction is to use the SNP loci,where both mother and father are homozygous but with different alleles.The resulting fetal genotype is obligately heterozygous.In maternal plasma,the fetal DNA fraction can be directly deduced by calculating the proportion of fetal specific alleles[9,30].Based on this concept,two extended versions of SNP-based methods for fetal DNA fraction estimate have been developed,namely FetalQuant and FetalQuant SD,which can be used without the need of both paternal and maternal genotype information[31,32];(c)cfDNA count-based approach.Read densities across the genome-wide50KB windows arefitted into a neural network model to predict the fetal DNA fraction[33];(d)Differential methylation-based approaches[17,26,34,35];(e)cfDNA size-based approach.The proportion of short cfDNA molecules is correlated with fetal DNA fraction[36];(f)Nucleosome track-based approach.Cell-free DNA distribution at the nucleosomal core and linkerregions is correlated with fetal DNA fraction[37].Table1.The summary of current approaches for estimating fetal DNA fraction. Approaches Advantages LimitationsY Chromosome[3,22]Simple and accurate NOT applicable for pregnancies with female fetusesMaternal plasma DNA sequencingdata with parental genotypes[9,30]Direct and accuratePaternal DNA may notbe availableTargeted sequencing of maternal plasma DNA(FetalQuant)[31]Sequencing maternal plasma DNAonly;accurateHigh sequencing depth is requiredShallow-depth sequencing ofmaternal plasma DNA coupled with maternal genotypes(FetalQuant SD)[32]Shallow-depth sequencing ofmaternal plasma DNA;accurateMaternal genotype requirementwill add additional costs;therecalibration curve is required tobe rebuilt for different sequencingand genotyping platformsShallow-depth maternal plasma DNA sequencing data(SeqFF)[33]Only shallow-depth sequencing ofmaternal plasma DNA;single-endsequencing;easy to be integratedinto the routine noninvasiveprenatal testing(NIPT)Large-scale samples are needed totrain the neutral network;need toimprove the accuracy when thefetal DNA fraction is below5%Differantial methylation [17,26,34,35]AccurateEither bisulfite conversion ordigestion withmethylation-sensitive restrictionenzymes may affect the accuracy;genome-wide bisulfite sequencingis too expensive and prohibitivefor the routine NIPTcfDNA fragment size[36]Only shallow-depth sequencing ofmaternal plasma DNA;easy to beintegrated into the routine NIPTModerate accuracy;paired-endsequencing would increasethe costsNucleosome track[37]Only shallow-depth sequencing ofmaternal plasma DNALower accuracy;high-depthsequencing data is requiredduring the training step2.Current Approaches Developed to Estimate Fetal DNA Fraction2.1.Y Chromosome-Based ApproachIn the early works,genetic markers located on Y chromosome which are paternally inherited, such as gene SRY,DYS14and ZFY,were used to indicate the fraction of fetal DNA molecules based on PCR assays[23,38,39].For instance,the ratio of the concentration of the sequences from Y chromosome to that of an autosome was used for the determination of fetal DNA fraction.In the context of NIPT using massively parallel sequencing,the proportion of all sequence reads from Y chromosome can be translated to the fetal DNA fraction[3,22].Although these methods are simple and accurate,they are only applicable to pregnancies carrying male fetuses.2.2.Maternal Plasma DNA Sequencing Data with Parental Genotype-Based ApproachWith the use of parental genotypes,fetal-specific alleles in maternal plasma can be readily identified from the sequence reads.Briefly,the fetal genotypes are obligately heterozygous at single-nucleotide polymorphism(SNP)loci,where both father and mother are homozygous but with different genotypes(e.g.,A/A for paternal genotype and C/C for maternal genotype).Then the fetal DNA fraction can be quantified by calculating the ratio of fetal-specific alleles(A)to the total alleles in plasma DNA[7,9,30,40].Even though this method is a direct and accurate way to assess the fetal DNA fraction and generally considered as a gold standard[9],the feasibility of this approachis sometimes hindered by the requirement of parental genotypes,because(1)only maternal blood samples would be collected and maternal plasma DNA are subject to sequence for NIPT in most clinical settings;and(2)it is not uncommon that the genotype of the biological father may not be available in practice[41].2.3.High-Depth Sequencing Data of Maternal Plasma DNA-Based ApproachTo obviate the requirement of parental genotype information,an approach called FetalQuant was developed to measure the fetal DNA fraction through the analysis of maternal plasma DNA sequencing data at high depth using targeted massively parallel sequencing[31].In this method, a binomial mixture model was employed tofit the observed allelic counts with the use of the underlying four types of maternal-fetal genotype combinations(AA AA,AA AB,AB AA,AB AB,where the main text and subscript represent the maternal and fetal genotypes,respectively).In this model,the fetal fraction was determined through the maximum likelihood estimation.The predicted result of this method is very close to the one deduced by the parental genotypes-based approach(the correlation coefficient is not available).However,the limitation of this approach would be that the sequencing depth is required to be as high as~120×by targeted sequencing to robustly determine the fetal alleles[31]. 2.4.Shallow-Depth Maternal Plasma DNA Sequencing Data with Maternal Genotype-Based ApproachAs an extended version of FetalQuant,FetalQuant SD[32]was recently developed based on shallow-depth sequencing data coupled with only maternal genotype information.The rationale of this approach is to take advantage of the fact that any alternative allele(non-maternal alleles)present at an SNP locus where the mother is homozygous would theoretically suggest a fetal-specific DNA allele. Briefly,the homozygous sites in a pregnant woman were identified by genotyping her blood cells using microarray technologies.Then,plasma DNA molecules with alleles different from the maternal homozygous sites(i.e.,non-maternal alleles)were identified,which were specifically derived from the father in theory.Thus,the fractions of such non-maternal alleles were hypothesized to correlate with fetal DNA fractions under the assumption that the error rates stemmed from sequencing and genotyping platforms are relatively constant across different cases.Therefore,a linear regression model wasfirst trained between the fraction of non-maternal alleles and actual fetal DNA fraction estimated by parental genotypes-based approach,and then the fetal DNA fractions were predicted with the use of the trained model in an independent validation dataset,exhibiting a very high accuracy(r=0.9950, p<0.0001,Pearson correlation)even using1million sequencing reads.However,the parameters in this model might be varied according to sequencing and genotyping platforms,because various platforms are characterized with different error properties,which may contribute to the measured non-maternal alleles.On the other hand,the extent of heterozygosity might be different in different ethnic groups,which could confound the accuracy of fetal DNA fraction prediction.The advantage of this model is that once thefinal well-trained model is achieved,it could be readily applied to any datasets,as long as they are generated from the same platform and population.2.5.Shallow-Depth Maternal Plasma DNA Sequencing Data-Based ApproachRecently,a new approach,named SeqFF,has been developed,attempting to make it possible to directly estimate fetal DNA fraction from the routine data of NIPT without any additional effort. In this approach,using single-end random sequencing of the maternal plasma,read count within each50KB autosomal region was analyzed tofit a high-dimensional regression model[33].The normalized read counts in50KB bins originating from chromosomes except chromosomes13,18,21, X,and Y were used as predictor variables,and the model coefficients were determined by making use of elastic net(Enet)and reduced-rank regression model[33].SeqFF showed a good correlation with Y chromosome-based method in two independent cohorts(r=0.932and0.938,respectively,Pearson correlation)[33].However,such high-dimensional model would require large-scale samples during training,and the performance appeared to be greatly deteriorated when the fetal DNA fraction isbelow5%,possibly because the number of cases with fetal DNA fraction<5%was not sufficient to train the Enet model.2.6.Fetal Methylation Marker-Based ApproachDNA methylation is a process by which a methyl group is added to cytosine nucleotides[42,43]. In mammalian somatic cells,the DNA methylation of cytosine in CpG dinucleotides is frequently methylated(~70%of the CpGs)[44].Different organs have been suggested to show variable methylation profiles,which would allow us to identify the tissue of origin analyzing the regions with differential methylation states[17,45].Indeed,researchers used the placenta-specific methylation markers to estimate the fetal DNA concentration[26,34].For example,a methylation-sensitive restriction enzyme has been used to digest hypomethylated maternal-derived RASSF1A promoter sequences,while it left the methylated counterparts of the fetal-derived sequences unaffected, thus allowing the discrimination of the methylated fetal DNA molecules from the unmethylated maternal background for the calculation of fetal DNA fraction[34].Similarly,based onfive differentially methylated regions comparing placental tissue and maternal buffy coat mined by using methyl-cytosine immunoprecipitation and CpG island microarrays,Nygren et al.developed a fetal quantitative assay(FQA)permitting the calculation of fetal DNA fraction in a plasma sample[26]. In FQA,by measuring the copy number of total DNA(maternal and fetal)and fetal methylated DNA after methylation-sensitive restriction enzyme digestion,the assay achieved good agreement with Y chromosome-based quantification(r=0.85,p<0.001,Pearson correlation).However,the analytical process used for quantifying these epigenetic markers involves digestion with methylation-sensitive restriction enzymes,and thus its stability needs to be further verified in large-scale datasets generated from different research centers.Furthermore,massively parallel bisulfite sequencing provides an alternative way to estimate the fetal DNA fraction according to the ratio of fetal-derived DNA molecules within differentially methylated regions[35].Using such bisulfite sequencing,the placenta has been demonstrated to exhibit a different methylation profile compared with other tissues[17,35].Therefore,a general approach, referred to as plasma DNA tissue mapping,for disentangling tissue contributors to cell-free DNA has been developed by leveraging the principle that different tissues within the body show different DNA methylation ing whole-genome bisulfite sequencing,the methylation profile of cell-free DNA across over5800DNA methylation markers was used to correlate the tissue-related methylation profiles,for the inference of the proportional contributions from different tissues in plasma[17].Using this new approach,placenta contribution was verified by genotype-based approaches.However,this genome-wide bisulfite sequencing-based tissue mapping algorithm in the present version would be too expensive for routine NIPT.2.7.Cell-Free DNA Size-Based ApproachFetal-derived and maternal-derived DNA molecules in a plasma sample have been observed to exhibit different fragmentation patterns,namely,fetal DNA being generally shorter than maternal DNA[9,46].Therefore,a higher fetal DNA fraction should be theoretically associated with an increased percentage of short DNA ing paired-end sequencing,Yu et al.developed a new method to estimate fetal DNA concentration based on the ratio between the count of fragments ranging from 100to150bp and from163to169bp[36].These size cutoffs gave their optimal performance among multiple size combinations.In the training dataset consisting of36samples,a linear regression model was established between the size ratio and fetal DNA concentration determined by the proportion of chromosome Y sequences(r=0.827,p<0.0001).Then using the derived model,the size ratio was translated to the fetal DNA fraction for each sample in the validation dataset.Intriguingly,the authors also proposed to calculate the size ratio using capillary electrophoresis of sequencing libraries directly, which is readily available before sequencing without additional costs.2.8.Cell-Free DNA Nucleosome Track-Based ApproachRecently,the investigation of nucleosomal origin of plasma DNA has been increasingly recognized as an appealing direction,which has been discussed in a number of studies[9,36,37,47].One important clue directing to such origin has been unravelled in two studies with the use of the high-resolution size profiling of maternal plasma DNA[9,36].It has been reported that the size distribution of the total maternal plasma DNA is characterized by a166bp major peak with a series of small peaks occurring at10bp periodicities,suggesting that a predominant population of plasma DNA molecules have a size of166bp.In contrast,fetal DNA molecules were found to have a dominant population with 143bp in size.It has been speculated that the166bp molecules would represent cfDNA containing the nucleosome core plus the linker[9].However,the143bp molecules would suggest molecules subject to the trimming of linker DNA[9].On the basis of this hypothetical model,Straver et al.pooled maternal plasma DNA from298cases to generate a hypothetical“nucleosome track”[37].Interestingly, the frequency of reads starting within73bp upstream and downstream regions of the inferential center of nucleosome was found to be positively correlated with the fetal DNA fraction,however,giving a relatively lower correlation coefficient than other methods(r=0.636,p=1.61×10−18,Pearson correlation).Thus,further development of a“nucleosome track”-based approach is needed for the clinical requirement.3.ConclusionsThe past decade has witnessed a tremendous advance in the technologies and bioinformatics algorithms for the analysis of circulating cfDNA.With the availability of massively parallel sequencing, noninvasive prenatal testing has become increasingly popular and presented itself as an exemplar in translational medicine research.In NIPT,a rapid,simple,accurate and cost-effective way to estimate fetal DNA fraction is highly desired,typically for the endeavors to make NIPT for single-gene diseases clinically practical.In particular,the accuracy of the estimation of low fetal DNA fraction is essential for determining the QC states and interpreting the clinical outcomes.On the other hand,the fetal DNA fraction could be related to pregnancy outcome;for example,the low fetal DNA fraction may be associated with small or dysfunctional placentas[48],suggesting its potential diagnostic value.Therefore,a large-scale validation for the accuracy of low-fetal DNA fraction estimation would still be needed for some aforementioned approaches,for example,size-,count-and nucleosome profile-based methodologies.We may expect that further in-depth analyses for such properties regarding size and nucleosome profiles would shed new insights into the mechanisms of cell-free DNA generation.As reported in the latest ultra-deep plasma DNA study[49],it was revealed that a number of preferred DNA ends in maternal plasma carry information directing to their tissue of origin(fetal-or maternal-derived DNA).The ratio of the number of fetal-preferred ends to maternal-preferred ends is positively correlated with the fetal DNA fraction in maternal plasma[49].This novel direction of cfDNA exploration regarding fragment ends has opened up new possibilities to study the complexity associated with non-randomness of plasma DNA ends,providing a new way to investigate the highly orchestrated cfDNA fragmentation patterns.More studies are needed to elucidate the relationship between the various factors as well as their interactions,for example,methylation[17],nucleosome footprints[47],and the underlying mechanisms governing the end-cutting patterns of plasma DNA. 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a systematic review and meta—analysis -回复问题：什么是系统审查和荟萃分析？回答：系统审查（Systematic Review）是一种研究方法，通过系统性、透明地综合和分析相关研究的证据，以回答特定的研究问题。

它的目标是总结和评估所有相关研究的证据，以提供一个全面的、客观的结论。

系统审查通常包括文献搜索、筛选和评估研究质量、数据提取和数据分析等步骤。

荟萃分析（Meta-analysis）是一种统计方法，用于合并和综合多个研究的结果，以得到一个整体的估计效应量。

荟萃分析通过对多个研究的数据进行汇总和分析，可以提供更可靠、统计上更有力的证据，从而增加研究结论的可信度和可靠性。

问题：系统审查和荟萃分析的目的是什么？回答：系统审查和荟萃分析的主要目的是提供一个全面的、客观的证据综合，以回答特定的研究问题。

通过对所有相关研究进行系统性的综合和分析，可以减少个别研究可能产生的偶然偏差和误导性结果的影响。

此外，荟萃分析还可以提供更精确的估计效应量，从而增加结论的可靠性和精确性。

问题：系统审查和荟萃分析的步骤是什么？回答：系统审查和荟萃分析通常包括以下步骤：1. 确定研究问题：明确研究目的，并制定明确的研究问题和目标。

2. 文献搜索：在各种数据库和文献来源中进行系统性的文献搜索，以收集所有相关的研究。

3. 筛选研究：根据预先设定的纳入和排除标准，对检索到的文献进行筛选和评估，以确定是否符合研究问题。

4. 评估研究质量：对纳入的研究进行质量评估，以了解其内部和外部有效性，并确定哪些研究对结果的贡献更大。

5. 数据提取：从纳入研究中提取所需的数据，并进行标准化和整理。

6. 数据分析：使用统计方法对提取的数据进行分析，计算效应量并进行合并。

常见的效应量计算方法包括标准化均差、风险比、比率等。

7. 研究结果的解释和报告：根据分析结果撰写系统审查和荟萃分析的报告，并解释所得到的研究结论。

考研英语翻译词汇之品质类整理提升翻译能力就必须要有充足的词汇量，无论是面还是深度都要广泛涉猎。

凯程在线分享各类翻译词汇，大家可以多看多记多了解。

下面是有关品质类的词汇，我们一起来学习下。

考研英语翻译分类词汇：品质类（A）Absolute deviation, 绝对离差Absolute number, 绝对数Absolute residuals, 绝对残差Acceleration array, 加速度立体阵Acceleration in an arbitrary direction, 任意方向上的加速度Acceleration normal, 法向加速度Acceleration space dimension, 加速度空间的维数Acceleration tangential, 切向加速度Acceleration vector, 加速度向量Acceptable hypothesis, 可接受假设Accumulation, 累积Accuracy, 准确度Actual frequency, 实际频数Adaptive estimator, 自适应估计量Addition, 相加Addition theorem, 加法定理Additivity, 可加性Adjusted rate, 调整率Adjusted value, 校正值Admissible error, 容许误差Aggregation, 聚集性Alternative hypothesis, 备择假设Among groups, 组间Amounts, 总量Analysis of correlation, 相关分析Analysis of covariance, 协方差分析Analysis of regression, 回归分析Analysis of time series, 时间序列分析Analysis of variance, 方差分析Angular transformation, 角转换ANOV A (analysis of variance), 方差分析ANOV A Models, 方差分析模型Arcing, 弧/弧旋Arcsine transformation, 反正弦变换Area under the curve, 曲线面积AREG , 评估从一个时间点到下一个时间点回归相关时的误差ARIMA, 季节和非季节性单变量模型的极大似然估计Arithmetic grid paper, 算术格纸Arithmetic mean, 算术平均数Arrhenius relation, 艾恩尼斯关系Assessing fit, 拟合的评估Associative laws, 结合律Asymmetric distribution, 非对称分布Asymptotic bias, 渐近偏倚Asymptotic efficiency, 渐近效率Asymptotic variance, 渐近方差Attributable risk, 归因危险度Attribute data, 属性资料Attribution, 属性Autocorrelation, 自相关Autocorrelation of residuals, 残差的自相关Average, 平均数Average confidence interval length, 平均置信区间长度Average growth rate, 平均增长率Bar chart, 条形图Bar graph, 条形图Base period, 基期Bayes' theorem , Bayes定理Bell-shaped curve, 钟形曲线Bernoulli distribution, 伯努力分布Best-trim estimator, 最好切尾估计量Bias, 偏性Binary logistic regression, 二元逻辑斯蒂回归Binomial distribution, 二项分布Bisquare, 双平方Bivariate Correlate, 二变量相关Bivariate normal distribution, 双变量正态分布Bivariate normal population, 双变量正态总体Biweight interval, 双权区间Biweight M-estimator, 双权M估计量Block, 区组/配伍组BMDP(Biomedical computer programs), BMDP统计软件包Boxplots, 箱线图/箱尾图Breakdown bound, 崩溃界/崩溃点Canonical correlation, 典型相关Caption, 纵标目Case-control study, 病例对照研究Categorical variable, 分类变量Catenary, 悬链线Cauchy distribution, 柯西分布Cause-and-effect relationship, 因果关系Cell, 单元Censoring, 终检Center of symmetry, 对称中心Centering and scaling, 中心化和定标Central tendency, 集中趋势Central value, 中心值CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测Chance, 机遇Chance error, 随机误差Chance variable, 随机变量Characteristic equation, 特征方程Characteristic root, 特征根Characteristic vector, 特征向量Chebshev criterion of fit, 拟合的切比雪夫准则Chernoff faces, 切尔诺夫脸谱图Chi-square test, 卡方检验/χ2检验Choleskey decomposition, 乔洛斯基分解Circle chart, 圆图Class interval, 组距Class mid-value, 组中值Class upper limit, 组上限Classified variable, 分类变量Cluster analysis, 聚类分析Cluster sampling, 整群抽样Code, 代码Coded data, 编码数据Coding, 编码Coefficient of contingency, 列联系数Coefficient of determination, 决定系数Coefficient of multiple correlation, 多重相关系数Coefficient of partial correlation, 偏相关系数Coefficient of production-moment correlation, 积差相关系数Coefficient of rank correlation, 等级相关系数Coefficient of regression, 回归系数Coefficient of skewness, 偏度系数Coefficient of variation, 变异系数Cohort study, 队列研究Column, 列Column effect, 列效应Column factor, 列因素Combination pool, 合并Combinative table, 组合表Common factor, 共性因子Common regression coefficient, 公共回归系数Common value, 共同值Common variance, 公共方差Common variation, 公共变异Communality variance, 共性方差Comparability, 可比性Comparison of bathes, 批比较Comparison value, 比较值Compartment model, 分部模型Compassion, 伸缩Complement of an event, 补事件Complete association, 完全正相关Complete dissociation, 完全不相关Complete statistics, 完备统计量Completely randomized design, 完全随机化设计Composite event, 联合事件Composite events, 复合事件Concavity, 凹性Conditional expectation, 条件期望Conditional likelihood, 条件似然Conditional probability, 条件概率Conditionally linear, 依条件线性Confidence interval, 置信区间Confidence limit, 置信限Confidence lower limit, 置信下限Confidence upper limit, 置信上限Confirmatory Factor Analysis , 验证性因子分析Confirmatory research, 证实性实验研究Confounding factor, 混杂因素Conjoint, 联合分析Consistency, 相合性Consistency check, 一致性检验Consistent asymptotically normal estimate, 相合渐近正态估计Consistent estimate, 相合估计Constrained nonlinear regression, 受约束非线性回归Constraint, 约束Contaminated distribution, 污染分布Contaminated Gausssian, 污染高斯分布Contaminated normal distribution, 污染正态分布Contamination, 污染Contamination model, 污染模型Contingency table, 列联表Contour, 边界线Contribution rate, 贡献率Control, 对照Controlled experiments, 对照实验Conventional depth, 常规深度Convolution, 卷积Corrected factor, 校正因子Corrected mean, 校正均值Correction coefficient, 校正系数Correctness, 正确性Correlation coefficient, 相关系数Correlation index, 相关指数Correspondence, 对应Counting, 计数Counts, 计数/频数Covariance, 协方差Covariant, 共变Cox Regression, Cox回归Criteria for fitting, 拟合准则Criteria of least squares, 最小二乘准则Critical ratio, 临界比Critical region, 拒绝域Critical value, 临界值Cross-over design, 交叉设计Cross-section analysis, 横断面分析Cross-section survey, 横断面调查Crosstabs , 交叉表Cross-tabulation table, 复合表Cube root, 立方根Cumulative distribution function, 分布函数Cumulative probability, 累计概率Curvature, 曲率/弯曲Curvature, 曲率Curve fit , 曲线拟和Curve fitting, 曲线拟合Curvilinear regression, 曲线回归Curvilinear relation, 曲线关系Cut-and-try method, 尝试法Cycle, 周期Cyclist, 周期性D test, D检验Data acquisition, 资料收集Data bank, 数据库Data capacity, 数据容量Data deficiencies, 数据缺乏Data handling, 数据处理Data manipulation, 数据处理Data processing, 数据处理Data reduction, 数据缩减Data set, 数据集Data sources, 数据来源Data transformation, 数据变换Data validity, 数据有效性Data-in, 数据输入Data-out, 数据输出Dead time, 停滞期Degree of freedom, 自由度Degree of precision, 精密度Degree of reliability, 可靠性程度Degression, 递减Density function, 密度函数Density of data points, 数据点的密度Dependent variable, 应变量/依变量/因变量Dependent variable, 因变量Depth, 深度Derivative matrix, 导数矩阵Derivative-free methods, 无导数方法Design, 设计Determinacy, 确定性Determinant, 行列式Determinant, 决定因素Deviation, 离差Deviation from average, 离均差Diagnostic plot, 诊断图Dichotomous variable, 二分变量Differential equation, 微分方程Direct standardization, 直接标准化法Discrete variable, 离散型变量DISCRIMINANT, 判断Discriminant analysis, 判别分析Discriminant coefficient, 判别系数Discriminant function, 判别值Dispersion, 散布/分散度Disproportional, 不成比例的Disproportionate sub-class numbers, 不成比例次级组含量Distribution free, 分布无关性/免分布Distribution shape, 分布形状Distribution-free method, 任意分布法Distributive laws, 分配律Disturbance, 随机扰动项Dose response curve, 剂量反应曲线Double blind method, 双盲法Double blind trial, 双盲试验Double exponential distribution, 双指数分布Double logarithmic, 双对数Downward rank, 降秩Dual-space plot, 对偶空间图DUD, 无导数方法Duncan's new multiple range method, 新复极差法/Duncan新法Effect, 实验效应Eigenvalue, 特征值Eigenvector, 特征向量Ellipse, 椭圆Empirical distribution, 经验分布Empirical probability, 经验概率单位Enumeration data, 计数资料Equal sun-class number, 相等次级组含量Equally likely, 等可能Equivariance, 同变性Error, 误差/错误Error of estimate, 估计误差Error type I, 第一类错误Error type II, 第二类错误Estimand, 被估量Estimated error mean squares, 估计误差均方Estimated error sum of squares, 估计误差平方和Euclidean distance, 欧式距离Event, 事件Event, 事件Exceptional data point, 异常数据点Expectation plane, 期望平面Expectation surface, 期望曲面Expected values, 期望值Experiment, 实验Experimental sampling, 试验抽样Experimental unit, 试验单位Explanatory variable, 说明变量Exploratory data analysis, 探索性数据分析Explore Summarize, 探索-摘要Exponential curve, 指数曲线Exponential growth, 指数式增长EXSMOOTH, 指数平滑方法Extended fit, 扩充拟合Extra parameter, 附加参数Extrapolation, 外推法Extreme observation, 末端观测值Extremes, 极端值/极值F distribution, F分布F test, F检验Factor, 因素/因子Factor analysis, 因子分析Factor Analysis, 因子分析Factor score, 因子得分Factorial, 阶乘Factorial design, 析因试验设计False negative, 假阴性False negative error, 假阴性错误Family of distributions, 分布族Family of estimators, 估计量族Fanning, 扇面Fatality rate, 病死率Field investigation, 现场调查Field survey, 现场调查Finite population, 有限总体Finite-sample, 有限样本First derivative, 一阶导数First principal component, 第一主成分First quartile, 第一四分位数Fisher information, 费雪信息量Fitted value, 拟合值Fitting a curve, 曲线拟合Fixed base, 定基Fluctuation, 随机起伏Forecast, 预测Four fold table, 四格表Fourth, 四分点Fraction blow, 左侧比率Fractional error, 相对误差Frequency, 频率Frequency polygon, 频数多边图Frontier point, 界限点Function relationship, 泛函关系Gamma distribution, 伽玛分布Gauss increment, 高斯增量Gaussian distribution, 高斯分布/正态分布Gauss-Newton increment, 高斯-牛顿增量General census, 全面普查GENLOG (Generalized liner models), 广义线性模型Geometric mean, 几何平均数Gini's mean difference, 基尼均差GLM (General liner models), 通用线性模型Goodness of fit, 拟和优度/配合度Gradient of determinant, 行列式的梯度Graeco-Latin square, 希腊拉丁方Grand mean, 总均值Gross errors, 重大错误Gross-error sensitivity, 大错敏感度Group averages, 分组平均Grouped data, 分组资料Guessed mean, 假定平均数Half-life, 半衰期Hampel M-estimators, 汉佩尔M估计量Happenstance, 偶然事件Harmonic mean, 调和均数Hazard function, 风险均数Hazard rate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Hessian array, 海森立体阵Heterogeneity, 不同质Heterogeneity of variance, 方差不齐Hierarchical classification, 组内分组Hierarchical clustering method, 系统聚类法High-leverage point, 高杠杆率点HILOGLINEAR, 多维列联表的层次对数线性模型Hinge, 折叶点Histogram, 直方图Historical cohort study, 历史性队列研究Holes, 空洞HOMALS, 多重响应分析Homogeneity of variance, 方差齐性Homogeneity test, 齐性检验Huber M-estimators, 休伯M估计量Hyperbola, 双曲线Hypothesis testing, 假设检验Hypothetical universe, 假设总体Impossible event, 不可能事件Independence, 独立性Independent variable, 自变量Index, 指标/指数Indirect standardization, 间接标准化法Individual, 个体Inference band, 推断带Infinite population, 无限总体Infinitely great, 无穷大Infinitely small, 无穷小Influence curve, 影响曲线Information capacity, 信息容量Initial condition, 初始条件Initial estimate, 初始估计值Initial level, 最初水平Interaction, 交互作用Interaction terms, 交互作用项Intercept, 截距Interpolation, 内插法Interquartile range, 四分位距Interval estimation, 区间估计Intervals of equal probability, 等概率区间Intrinsic curvature, 固有曲率Invariance, 不变性Inverse matrix, 逆矩阵Inverse probability, 逆概率Inverse sine transformation, 反正弦变换Iteration, 迭代Jacobian determinant, 雅可比行列式Joint distribution function, 分布函数Joint probability, 联合概率Joint probability distribution, 联合概率分布K means method, 逐步聚类法Kaplan-Meier, 评估事件的时间长度Kaplan-Merier chart, Kaplan-Merier图Kendall's rank correlation, Kendall等级相关Kinetic, 动力学Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验Kurtosis, 峰度Lack of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Large sample, 大样本Large sample test, 大样本检验Latin square, 拉丁方Latin square design, 拉丁方设计Leakage, 泄漏Least favorable configuration, 最不利构形Least favorable distribution, 最不利分布Least significant difference, 最小显著差法Least square method, 最小二乘法Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L估计量L-estimator of location, 位置L估计量L-estimator of scale, 尺度L估计量Level, 水平Life expectance, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布Likelihood function, 似然函数Likelihood ratio, 似然比line graph, 线图Linear correlation, 直线相关Linear equation, 线性方程Linear programming, 线性规划Linear regression, 直线回归Linear Regression, 线性回归Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布Logit transformation, Logit转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 损失函数Low correlation, 低度相关Lower limit, 下限Lowest-attained variance, 最小可达方差LSD, 最小显著差法的简称Lurking variable, 潜在变量Main effect, 主效应Major heading, 主辞标目Marginal density function, 边缘密度函数Marginal probability, 边缘概率Marginal probability distribution, 边缘概率分布Matched data, 配对资料Matched distribution, 匹配过分布Matching of distribution, 分布的匹配Matching of transformation, 变换的匹配Mathematical expectation, 数学期望Mathematical model, 数学模型Maximum L-estimator, 极大极小L 估计量Maximum likelihood method, 最大似然法Mean, 均数Mean squares between groups, 组间均方Mean squares within group, 组内均方Means (Compare means), 均值-均值比较Median, 中位数Median effective dose, 半数效量Median lethal dose, 半数致死量Median polish, 中位数平滑Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量Minimum distance estimation, 最小距离估计Minimum effective dose, 最小有效量Minimum lethal dose, 最小致死量Minimum variance estimator, 最小方差估计量MINITAB, 统计软件包Minor heading, 宾词标目Missing data, 缺失值Model specification, 模型的确定Modeling Statistics , 模型统计Models for outliers, 离群值模型Modifying the model, 模型的修正Modulus of continuity, 连续性模Morbidity, 发病率Most favorable configuration, 最有利构形Multidimensional Scaling (ASCAL), 多维尺度/多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple comparison, 多重比较Multiple correlation , 复相关Multiple covariance, 多元协方差Multiple linear regression, 多元线性回归Multiple response , 多重选项Multiple solutions, 多解Multiplication theorem, 乘法定理Multiresponse, 多元响应Multi-stage sampling, 多阶段抽样Multivariate T distribution, 多元T分布Mutual exclusive, 互不相容Mutual independence, 互相独立Natural boundary, 自然边界Natural dead, 自然死亡Natural zero, 自然零Negative correlation, 负相关Negative linear correlation, 负线性相关Negatively skewed, 负偏Newman-Keuls method, q检验NK method, q检验No statistical significance, 无统计意义Nominal variable, 名义变量Nonconstancy of variability, 变异的非定常性Nonlinear regression, 非线性相关Nonparametric statistics, 非参数统计Nonparametric test, 非参数检验Nonparametric tests, 非参数检验Normal deviate, 正态离差Normal distribution, 正态分布Normal equation, 正规方程组Normal ranges, 正常范围Normal value, 正常值Nuisance parameter, 多余参数/讨厌参数Null hypothesis, 无效假设Numerical variable, 数值变量Objective function, 目标函数Observation unit, 观察单位Observed value, 观察值One sided test, 单侧检验One-way analysis of variance, 单因素方差分析Oneway ANOV A , 单因素方差分析Open sequential trial, 开放型序贯设计Optrim, 优切尾Optrim efficiency, 优切尾效率Order statistics, 顺序统计量Ordered categories, 有序分类Ordinal logistic regression , 序数逻辑斯蒂回归Ordinal variable, 有序变量Orthogonal basis, 正交基Orthogonal design, 正交试验设计Orthogonality conditions, 正交条件ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outliers, 极端值OVERALS , 多组变量的非线性正规相关Overshoot, 迭代过度。

Unit 4 翻译环保的当今时代是约半个世纪之久。

那段时间意识不断壮大，我们所面临的挑战知识增加，而重要的实践已经取得了进展，例如在一些减少各种污染，并在建立保护区。

我们是，但是，仍然由协调人什么我们的星球能提供可持续的要求很远。

人与自然之间的不平衡的后果是出现在改变地球的气候，动物和植物的势头，并在关键的资源，包括野生鱼类资源，淡水和土壤的枯竭的大灭绝。

而这些环境压力不是一成不变的。

他们不断升级，随着我国人口的增长和国家继续为更多的经济增长的不懈追求。

如果我们要避免这些趋势的最严重后果则毫无疑问是较为迅速的进展将需要比迄今取得的，但我们在这里应该关注我们的努力？什么可能是在未来的半个世纪行动的优先领域？这让我感到眼前的主要挑战主要不是相对于良好的信息，更好的技术和良好的政策思路。

这些东西是至关重要的当然的，但所有这些东西都已经可用。

我们知道如何让清洁电力，节约资源，培育生物多样性。

我们知道如何规范污染，防止损坏的生态系统，如果我们想。

我们有这些能力的事实是不够的。

如果我们继续前进的决定性方式的争论它需要被重新定义。

我们需要从“做正确的事'上移动，谈到风险管理，促进抗灾能力。

要查看关爱地球的自然系统为某种道德选择的是完全误解了危机，我们都在这个挑战是关于人类社会的未来，而不是一些可选的慈善事业，我们可以留给慈善事业慷慨解囊，做社会改良。

嵌入了使我们从保护自然的人们保护自然为人们的叙述是这样的重新规划的重要组成部分。

我们正处在一个时期的后果，世界必须知道，健康的本质不是一些可选的精密而是一组不可缺少的物质资产。

如果这样的叙述是为了获得实际效果再想找性质后必须立即被看作不仅是一个环境的挑战，也是一个经济问题。

只要我们继续滑向两个方向行进，一方面是促进环保目标的同时，对其他直接矛盾与措施，以实现更多的经济增长，我们不再将无法取得真正的进展。

当涉及到经济学和生态学有大量的好思已经完成。

例如，在不同的经济措施，以取代成功与失败，生态税的改革更为现实的措施，收入转移的负担，污染，生态系统服务补偿，补贴的重定向和如何调动国内生产总值的原油措施融资以扩大清洁行业。

digestive system 相关英语词汇The digestive system is a complex network of organs and tissues responsible for breaking down food into nutrients that the body can absorb and use. It involves a series of physical and chemical processes that occur in the mouth, esophagus, stomach, small intestine, large intestine, and accessory organs such as the liver, pancreas, and gallbladder.Here are some key English vocabulary related to the digestive system:$$1. Mouth and Teeth:$$* **Mouth:** The entry point for food intake. * **Teeth (Teeth):** Hard, calcified structures used for chewing and grinding food. * **Tongue:** A muscular organ that moves food around in the mouth and helps in swallowing. ***Saliva:** A watery secretion that moistens food, begins the chemical breakdown of carbohydrates, and helps in swallowing.**2. Esophagus:*** **Esophagus:** A muscular tube that carries food from the mouth to the stomach. * **Peristalsis:** The rhythmic muscular contractions that propel food through the esophagus.**3. Stomach:*** **Stomach:** A hollow, muscular organ that stores food, secretes gastric juices, and mixes food with these juices to form a semisolid mass called chyme. * **Gastric Juice:** A mixture of hydrochloric acid, enzymes, and mucus secreted by the stomach. * **Hydrochloric Acid:** A strong acid that helps in the digestion of protein and creates an acidic environment that kills bacteria. * **Enzyme:** A biological catalyst that speeds up chemical reactions in the body, including the breakdown of food into nutrients. * **Mucus:** A slippery, viscous substance that coats the lining of the stomach, protecting it from the corrosive effects of gastric juice.**4. Small Intestine:*** **Small Intestine:** A long, coiled tube that continues from the stomach and is the primary site of digestion and absorption of nutrients. * **Duodenum:** Thefirst part of the small intestine, closest to the stomach. * **Jejunum:** The middle part of the small intestine. ***Ileum:** The final part of the small intestine, leading to the large intestine. * **Villi:** Tiny, finger-like projections on the inner lining of the small intestine that increase its surface area for absorption. * **Microvilli:** Minute projections on the surface of the villi that further enhance the absorption capacity of the small intestine.**5. Large Intestine:*** **Large Intestine:** A wider, shorter tube that absorbs water and forms feces. * **Colon:** The major part of the large intestine. * **Rectum:** The final, straight section of the large intestine, leading to the anus. ***Feces:** Solid waste product formed in the largeintestine and expelled from the body through the anus.**6. Accessory Organs:*** **Liver:** A large organ that produces bile, metabolizes fats, stores vitamins and minerals, and detoxifies the blood. * **Bile:** A yellowish fluid produced by the liver and stored in the gallbladder. It helps in the digestion of fats. * **Gallbladder:** A small,pear-shaped sac that stores bile until it is needed for digestion. * **Pancreas:** A gland that produces enzymes that break down carbohydrates, fats, and proteins, as well as hormones that regulate blood sugar levels.**7. Digestive Processes and Functions:*** **Digestion:** The process of breaking down food into smaller molecules that can be absorbed by the body. ***Absorption:** The process of nutrients passing through the walls of the small intestine into the bloodstream. ***Metabolism:** The set of chemical reactions that occur in the body to convert food into energy and building blocksfor cells and tissues.These are just a few of the many terms related to the digestive system. The digestive system is a highly complex and interconnected network of organs and processes, and its efficient functioning is crucial for maintaining overall health and well-being. Disorders of the digestive system can lead to a range of symptoms and health issues, makingit important to maintain a healthy diet and lifestyle to promote optimal digestive health.。

Estriol. Note two hydroxyl (-OH) groups attached to the D ring (rightmost ring).Estradiol. Note one hydroxyl group attached to the D ring. The 'di' refers both to this hydroxyl and the one on the A ring (leftmost).Estrone. Note the ketone (=O) group attached to the D ring.EstrogenFrom Wikipedia, the free encyclopediaEstrogens or oestrogens (see spelling differences)are a group of compounds named for their importance inboth menstrual and estrous reproductive cycles. Theyare the primary female sex hormones. Natural estrogensare steroid hormones while some synthetic ones are non-steroidal. The name comes from the Greek οἶστρος(oistros), literally meaning "verve or inspiration" butfiguratively sexual passion or desire,[1] and thesuffix -gen , meaning "producer of".Estrogens are synthesized in all vertebrates [2] as wellas some insects.[3] Their presence in both vertebratesand insects suggests that estrogenic sex hormones havean ancient evolutionary history.Estrogens are used as part of some oral contraceptives,in estrogen replacement therapy for postmenopausalwomen, and in hormone replacement therapy for transwomen.Like all steroid hormones, estrogens readily diffuseacross the cell membrane. Once inside the cell, theybind to and activate estrogen receptors which in turnmodulate the expression of many genes.[4] Additionally,estrogens bind to and activate rapid-signaling membraneestrogen receptors,[5][6] such as GPER (GPR30).[7]Contents1 Types1.1 Steroidal1.2 Nonsteroidal1.3 Type in common reference2 Biosynthesis3 Function3.1 Fetal development3.2 Estrogen and heart disease3.3 Immunological role3.4 Mental health3.5 Binge eating4 Medical applications4.1 Oral contraceptives4.2 Hormone replacement therapy4.3 Breast cancer4.4 Prostate cancerReference ranges for the blood content of estradiol, the primary type of estrogen, during the menstrual cycle.4.5 Miscellaneous4.6 Health risks and warning labels5 Cosmetics6 History7 Environmental effects8 See also9 References10 External linksTypesSteroidalThe three major naturally occurring estrogens in women are estrone (E1), estradiol (E2), and estriol (E3). Estradiol is the predominant estrogen during reproductive years both in terms of absolute serum levels as well as in terms of estrogenic activity. During menopause, estrone is the predominant circulating estrogen andduring pregnancy estriol is the predominant circulating estrogen in terms of serum levels. Though estriol is the most plentiful of the three estrogens it is also the weakest, whereas estradiol is the strongest with a potency of approximately 80 times that of estriol. Thus, estradiol is the most important estrogen in non-pregnantfemales who are between the menarche and menopause stages of life. However, during pregnancy this role shifts to estriol, and in postmenopausal women estrone becomes the primary form of estrogen in the body. Another type of estrogen called estetrol (E4) is produced only during pregnancy. All of the different forms of estrogen are synthesized from androgens, specifically testosterone and androstenedione, by the enzyme aromatase.Premarin, a commonly prescribed estrogenic drug produced from the urine of pregnant mares, contains the steroidal estrogens equilin and equilenin. There are estradiol skin patches such as Estraderm (the original brand, introduced in the late 1980s)that offer a completely natural alternative.NonsteroidalA range of synthetic and naturalsubstances have been identified thatalso possess estrogenic activity.[8]Synthetic substances of thiskind are known asxenoestrogens.Plant products with estrogenicactivity are calledphytoestrogens.Those produced by fungi areknown as mycoestrogens.Unlike estrogens produced by mammals, these substances are not necessarily steroids.Steroidogenesis, showing estrogens at bottom right as in pink triangle.Type in common referenceAlthough scientifically there are various estrogens, the word "estrogen" in typical general conversation is usually used in the singular (making it sound as if there were only one kind of estrogen). Such usage refers specifically to the steroidalestrogen estradiol (E2). This is analogous to how "alcohol" in general conversation refers specifically (although implicitly) to ethanol. This explains why "estrogen"is generally said to have its highest levels in females of reproductive age, which is true of estradiol (E2), as explained above, although not of all other estrogens.BiosynthesisEstrogens, in females,are produced primarilyby the ovaries, andduring pregnancy, theplacenta. Follicle-stimulating hormone(FSH) stimulates theovarian production ofestrogens by thegranulosa cells of theovarian follicles andcorpora lutea. Someestrogens are alsoproduced in smalleramounts by othertissues such as theliver, adrenal glands,and the breasts. Thesesecondary sources ofestrogens areespecially important inpostmenopausal women.Fat cells produceestrogen as well.[9]In females, synthesis of estrogens starts in theca interna cells in the ovary, bythe synthesis of androstenedione from cholesterol. Androstenedione is a substance of weak androgenic activity which serves predominantly as a precursor for more potent androgens such as testosterone as well as estrogen. This compound crosses the basal membrane into the surrounding granulosa cells, where it is converted eitherimmediately into estrone, or into testosterone and then estradiol in an additional step. The conversion of androstenedione to testosterone is catalyzed by 17β-hydroxysteroid dehydrogenase (17β-HSD), whereas the conversion of androstenedione and testosterone into estrone and estradiol, respectively is catalyzed by aromatase,enzymes which are both expressed in granulosa cells. In contrast, granulosa cellslack 17α-hydroxylase and 17,20-lyase, whereas theca cells express these enzymes and 17β-HSD but lack aromatase. Hence, both granulosa and theca cells are essential for the production of estrogen in the ovaries.Estrogen levels vary through the menstrual cycle, with levels highest near the end of the follicular phase just before ovulation.FunctionThe actions of oestrogen are mediated by the oestrogen receptor (ER), a dimeric nuclear protein that binds to DNA and controls gene expression. Like other steroid hormones, estrogen enters passively into the cell where it binds to and activates the estrogen receptor. The estrogen:ER complex binds to specific DNA sequences called a hormone response element to activate the transcription of target genes (in a study using an estrogen-dependent breast cancer cell line as model, 89 such genes were identified).[10] Since estrogen enters all cells, its actions are dependent on the presence of the ER in the cell. The ER is expressed in specific tissues including the ovary, uterus and breast. The metabolic effects of estrogen in postmenopausal women has been linked to the genetic polymorphism of the ER.[11]While estrogens are present in both men and women, they are usually present at significantly higher levels in women of reproductive age. They promote the development of female secondary sexual characteristics, such as breasts, and are also involved in the thickening of the endometrium and other aspects of regulating the menstrual cycle. In males, estrogen regulates certain functions of the reproductive system important to the maturation of sperm[12][13][14] and may be necessary for a healthy libido.[15] Furthermore, there are several other structural changes induced by estrogen in addition to other functions.StructuralPromote formation of female secondary sex characteristicsAccelerate metabolismIncrease fat storeStimulate endometrial growthIncrease uterine growthIncrease vaginal lubricationThicken the vaginal wallMaintenance of vessel and skinReduce bone resorption, increase bone formationProtein synthesisIncrease hepatic production of binding proteinsCoagulationIncrease circulating level of factors 2, 7, 9, 10, plasminogenDecrease antithrombin IIIIncrease platelet adhesivenessLipidIncrease HDL, triglycerideDecrease LDL, fat depositionFluid balanceSalt (sodium) and water retentionIncrease cortisol, SHBGGastrointestinal tractReduce bowel motilityIncrease cholesterol in bileMelaninIncrease pheomelanin, reduce eumelaninCancerSupport hormone-sensitive breast cancers (see section below) Lung functionPromotes lung function by supporting alveoli (in rodents but probably inhumans).[16]Uterus liningEstrogen together with progesterone promotes and maintains the uteruslining in preparation for implantation of fertilized egg and maintenanceof uterus function during gestation period, also upregulates oxytocinreceptor in myometriumOvulationSurge in estrogen level induces the release of luteinizing hormone, whichthen triggers ovulation by releasing the egg from the Graafian follicle inthe ovary.Sexual receptivity in estrusPromotes sexual receptivity,[17] and induces lordosis behavior.[18] In non-human mammals, it also induces estrus (in heat) prior to ovulation, whichalso induces lordosis behavior. Female non-human mammals are not sexuallyreceptive without the estrogen surge, i.e., they have no mating desirewhen not in estrus.Lordosis behaviorRegulates the stereotypical sexual receptivity behavior; this lordosisbehavior is estrogen-dependent, which is regulated by the ventromedialnucleus of the hypothalamus.[19]Sexual desireSex drive is dependent on androgen levels[20] only in the presence ofestrogen, but without estrogen, free testosterone level actually decreasessexual desire (instead of increases sex drive), as demonstrated for thosewomen who have hypoactive sexual desire disorder, and the sexual desire inthese women can be restored by administration of estrogen (using oralcontraceptive).[21] In non-human mammals, mating desire is triggered byestrogen surge in estrus.Fetal developmentIn rodents, estrogens (which are locally aromatized from androgens in the brain) play an important role in psychosexual differentiation, for example, by masculinizing territorial behavior;[22] the same is not true in humans.[23] In humans, the masculinizing effects of prenatal androgens on behavior (and other tissues, with the possible exception of effects on bone) appear to act exclusively through the androgen receptor.[24] Consequently, the utility of rodent models for studying human psychosexual differentiation has been questioned.[25]Estrogen and heart diseaseWomen suffer less from heart disease due to vasculo-protective action of oestrogen which helps in preventing atherosclerosis.[26] It also helps in maintaining the delicate balance between fighting infections and protecting arteries from damage thus lowering the risk of cardiovascular disease.[27]Immunological roleOestrogen has anti-inflammatory properties and helps in mobilization of polymorphonuclear white blood cells or neutrophils.[27]Mental healthEstrogen is considered to play a significant role in women’s mental health. Sudden estrogen withdrawal, fluctuating estrogen, and periods of sustained estrogen low levels correlate with significant mood lowering. Clinical recovery from postpartum, perimenopause, and postmenopause depression has been shown to be effective after levels of estrogen were stabilized and/or restored.[28][29]Compulsions in male lab mice, such as those in obsessive-compulsive disorder (OCD), may be caused by low estrogen levels. When estrogen levels were raised through the increased activity of the enzyme aromatase in male lab mice, OCD rituals were dramatically decreased. Hypothalamic protein levels in the gene COMT are enhanced by increasing estrogen levels which are believed to return mice that displayed OCD rituals to normal activity. Aromatase deficiency is ultimately suspected which is involved in the synthesis of estrogen in humans and has therapeutic implications in humans having obsessive-compulsive disorder.[30]Local application of estrogen in the rat hippocampus has been shown to inhibit the re-uptake of serotonin. Contrarily, local application of estrogen has been shown to block the ability of fluvoxamine to slow serotonin clearance, suggesting that the same pathways which are involved in SSRI efficacy may also be affected by components of local estrogen signaling pathways.[31]Binge eatingResearch suggests that estrogen may play a role in suppressing binge eating. Hormone replacement therapy using estrogen may be a possible treatment for binge eating behaviors in females. Estrogen replacement has been shown to suppress binge eating behaviors in female mice.[32] The mechanism by which estrogen replacement inhibits binge-like eating involves the replacement of serotonin (5-HT) neurons. Women exhibiting binge eating behaviors are found to have increased brain uptake of neuron 5-HT, and therefore less of the neurotransmitter serotonin in the cerebrospinal fluid.[33] Data has shown that estrogen works to activate 5-HT neurons, leading to suppression of binge like eating behaviors.[32]It is also suggested that there is an interaction between hormone levels and eating at different points in the female menstrual cycle. Research has predicted increased emotional eating during hormonal flux, which is characterized by high progesterone and estradiol levels that occur during the mid-luteal phase. It is hypothesized that these changes occur due to brain changes across the menstrual cycle that are likely a genomic effect of hormones. These effects produce menstrual cycle changes, which result in hormone release leading to behavioral changes, notably binge and emotional eating. These occur especially prominently among women who are genetically vulnerable to binge eating phenotypes.[34]In terms of the specific ovarian hormone changes, Edler, Lipson and Keel (2007) replicated results from animal studies that binge eating is associated with decreased estradiol and increased progesterone. Furthermore, they explain that it is important to further study ovarian hormones in binge eating as they may be an important neurobiological mechanism behind binge eating disorders.[35] Klump etal.[36] found that progesterone may moderate the effects of low estradiol (such as during dysregulated eating behavior), but that this may only be true in women who have had clinically diagnosed binge episodes (BEs). More broadly, they identified that dysregulated eating was more strongly associated with such ovarian hormones in women with BEs than in women without BEs.[36]A study by Cao et al. (2014) demonstrated the effectiveness of hormone replacement with 17β-estradiol as well as a glucagon-like peptide-1 (GLP-1) and estrogen conjugate designed to target the specific receptors linked to binge-eating behaviors. The study concluded that the implantation of 17β-estradiol pellets in ovariectomized mice significantly reduced binge eating behaviors and injections of GLP-1 in ovariectomized mice decreased binge-eating behaviors by 66% compared to control groups.[32]Research conducted by Klump et al.[37] extended previous work examining associations between binge eating and ovarian hormones in women with bulimia nervosa (Lester et al. 2003; Edler et al. 2007).[35][37][38] Data conducted by Klump et al. (2008) showed remarkable similarities to the work of both Lester et al. and Edler et al.. In all three studies, the magnitude of associations between binge eating, menstrual-cycle phase and ovarian hormones was remarkably similar. However, all participantsin study 2 of Klump et al. (2008) demonstrated ovulatory cycles. Thus, unlike studies of women with BN (Edler et al. 2007), no participants were lost to analyses due to menstrual irregularities, making the work of Klump et al. (2008) the first to examine associations between changes in binge eating and ovarian hormones using a non-clinical sample.[37]Medical applicationsOral contraceptivesSince estrogen circulating in the blood can negatively feed-back to reduce circulating levels of FSH and LH, most oral contraceptives contain a synthetic estrogen, along with a synthetic progestin. Even in men, the major hormone involved in LH feedback is estradiol, not testosterone.Hormone replacement therapyEstrogen and other hormones are given to postmenopausal women in order to prevent osteoporosis as well as treat the symptoms of menopause such as hot flushes, vaginal dryness, urinary stress incontinence, chilly sensations, dizziness, fatigue, irritability, and sweating. Fractures of the spine, wrist, and hips decrease by 50–70% and spinal bone density increases by ~5% in those women treated with estrogen within 3 years of the onset of menopause and for 5–10 years thereafter.Before the specific dangers of conjugated equine estrogens were well understood, standard therapy was 0.625 mg/day of conjugated equine estrogens (such as Premarin). There are, however, risks associated with conjugated equine estrogen therapy. Among the older postmenopausal women studied as part of the Women's Health Initiative (WHI), an orally administered conjugated equine estrogen supplement was found to be associated with an increased risk of dangerous blood clotting. The WHI studies used one type of estrogen supplement, a high oral dose of conjugated equine estrogens (Premarin alone and with medroxyprogesterone acetate as PremPro).[39]In a study by the NIH, esterified estrogens were not proven to pose the same risks to health as conjugated equine estrogens. Hormone replacement therapy has favorable effects on serum cholesterol levels, and when initiated immediately upon menopause may reduce the incidence of cardiovascular disease, although this hypothesis has yet to be tested in randomized trials. Estrogen appears to have a protector effect on atherosclerosis: it lowers LDL and triglycerides, it raises HDL levels and has endothelial vasodilatation properties plus an anti-inflammatory component.Research is underway to determine if risks of estrogen supplement use are the same for all methods of delivery. In particular, estrogen applied topically may have a different spectrum of side-effects than when administered orally,[40] and transdermal estrogens do not affect clotting as they are absorbed directly into the systemic circulation, avoiding first-pass metabolism in the liver. This route of administration is thus preferred in women with a history of thrombo-embolic disease.Estrogen is also used in the therapy of vaginal atrophy, hypoestrogenism (as aresult of hypogonadism, castration, or primary ovarian failure), amenorrhea, dysmenorrhea, and oligomenorrhea. Estrogens can also be used to suppress lactation after child birth.Breast cancerAbout 80% of breast cancers, once established, rely on supplies of the hormone estrogen to grow: they are known as hormone-sensitive or hormone-receptor-positive cancers. Suppression of production of estrogen in the body is a treatment for these cancers.Research suggests the common table mushroom has anti-aromatase[41] properties and therefore possible anti-estrogen activity. In 2009, a case-control study of the eating habits of 2,018 women in southeast China revealed that women who consumed greater than 10 grams of fresh mushrooms or greater than 4 grams of dried mushrooms per day had an approximately 50% lower incidence of breast cancer. Chinese women who consumed mushrooms and green tea had a 90% lower incidence of breast cancer.[42] However the study was relatively small (2,018 patients participating) and limited to Chinese women of southeast China.Hormone-receptor-positive breast cancers are treated with drugs which suppress production of estrogen in the body.[43] This technique, in the context of treatment of breast cancer, is known variously as hormonal therapy, hormone therapy, or anti-estrogen therapy (not to be confused with hormone replacement therapy). Certain foods such as soy may also suppress the proliferative effects of estrogen and are used as an alternative to hormone therapy.[44]Prostate cancerUnder certain circumstances, estrogen may also be used in males for treatment of prostate cancer.[45]MiscellaneousIn humans and mice, estrogen promotes wound healing.[46]At one time, estrogen was used to induce growth attenuation in tall girls.[47] Recently, estrogen-induced growth attenuation was used as part of the controversial Ashley Treatment to keep a developmentally disabled girl from growing to adult size.[48]Most recently, estrogen has been used in experimental research as a way to treat women suffering from bulimia nervosa, in addition to cognitive behavioral therapy, which is the established standard for treatment in bulimia cases. The estrogen research hypothesizes that the disease may be linked to a hormonal imbalance in the brain.[49]Estrogen has also been used in studies which indicate that it may be an effective drug for use in the treatment of traumatic liver injury.[50]Health risks and warning labelsHyperestrogenemia (elevated levels of estrogen) may be a result of exogenous administration of estrogen or estrogen-like substances, or may be a result of physiologic conditions such as pregnancy. Any of these causes is linked with an increase in the risk of thrombosis.[51]The estrogen-alone substudy of the WHI reported an increased risk of stroke and deep vein thrombosis (DVT) in postmenopausal women 50 years of age or older and an increased risk of dementia in postmenopausal women 65 years of age or older using 0.625 mg of Premarin conjugated equine estrogens (CEE). The estrogen-plus-progestin substudy of the WHI reported an increased risk of myocardial infarction, stroke, invasive breast cancer, pulmonary emboli and DVT in postmenopausal women 50 years of age or older and an increased risk of dementia in postmenopausal women 65 years of age or older using PremPro, which is 0.625 mg of CEE with 2.5 mg of the progestin medroxyprogesterone acetate (MPA).[52][53][54]The labeling of estrogen-only products in the U.S. includes a boxed warning that unopposed estrogen (without progestogen) therapy increases the risk of endometrial cancer. Based on a review of data from the WHI, on January 8, 2003 the FDA changedthe labeling of all estrogen and estrogen with progestin products for use by postmenopausal women to include a new boxed warning about cardiovascular and other risks.CosmeticsSome hair shampoos on the market include estrogens and placental extracts; others contain phytoestrogens. In 1998, there were case reports of four prepubescent African-American girls developing breasts after exposure to these shampoos.[55] In 1993, the FDA determined that not all over-the-counter topically applied hormone-containing drug products for human use are generally recognized as safe andeffective and are misbranded. An accompanying proposed rule deals with cosmetics, concluding that any use of natural estrogens in a cosmetic product makes the product an unapproved new drug and that any cosmetic using the term "hormone" in the text of its labeling or in its ingredient statement makes an implied drug claim, subjecting such a product to regulatory action.[56]In addition to being considered misbranded drugs, products claiming to contain placental extract may also be deemed to be misbranded cosmetics if the extract has been prepared from placentas from which the hormones and other biologically active substances have been removed and the extracted substance consists principally of protein. The FDA recommends that this substance be identified by a name other than "placental extract" and describing its composition more accurately because consumers associate the name "placental extract" with a therapeutic use of some biological activity.[56]HistoryIn 1929 Adolf Butenandt and Edward Adelbert Doisy independently isolated and determined the structure of estrogen.[57] Thereafter, the pace of hormonal drug research accelerated.The "first orally effective estrogen", Emmenin, derived from the late-pregnancy urine of Canadian women, was introduced in 1930 by Collip and Ayerst Laboratories. Estrogens are not water-soluble and cannot be given orally, but the urine was found to contain estriol glucuronide which is water soluble and becomes active in the body after hydrolysis.Scientists continued to search for new sources of estrogen because of concerns associated with the practicality of introducing the drug into the market. At the same time, a German pharmaceutical drug company, formulated a similar product as Emmenin that was introduced to German women to treat menopausal symptoms.In 1938, British scientists obtained a patent on a newly formulated nonsteroidal estrogen, diethylstilbestrol (DES), that was cheaper and more powerful than the previously manufactured estrogens. Soon after, concerns over the side effects of DES were raised in scientific journals while the drug manufacturers came together tolobby for governmental approval of DES. It was only until 1941 when estrogen therapy was finally approved by the Food and Drug Administration (FDA) for the treatment of menopausal symptoms.[58]Environmental effectsEstrogens are among the wide range of endocrine-disrupting compounds (EDCs) because they have high estrogenic potency. When an EDC makes its way into the environment,it may cause male reproductive dysfunction to wildlife.[59] The estrogen excreted from farm animals makes its way into fresh water systems.[60] During the germination period of reproduction the fish are exposed to low levels of estrogen which may cause reproductive dysfunction to male fish.[61][62]See alsoAnti-oestrogenic dietAtrophic vaginitisDiethylstilbestrolEndocrine disruptorEndocrinologyEquilinEquolEstradiolEstrogen receptorList of steroid abbreviationsPhytoestrogensProgesteroneProgestinSexual motivation and hormonesTestosteroneReferences1. "Greek Word Study Tool: oistros" (/hopper/morph?l=oistros&la=greek). Perseus Digital Library. Retrieved 2011-12-28.2. Ryan KJ (August 1982). "Biochemistry of aromatase: significance to female reproductivephysiology". Cancer Res.42 (8 Suppl): 3342s–3344s. PMID 7083198(https:///pubmed/7083198).3. Mechoulam R, Brueggemeier RW, Denlinger DL (September 2005). "Estrogens in insects"(/content/tr77034552r222m1/fulltext.pdf) (PDF). Cellular andMolecular Life Sciences40 (9): 942–944. doi:10.1007/BF01946450(https:///10.1007%2FBF01946450).4. Whitehead SA, Nussey S (2001). Endocrinology: an integrated approach(/books/bv.fcgi?call=bv.View..ShowTOC&rid=endocrin.TOC&depth=10). Oxford: BIOS: Taylor & Francis. ISBN 1-85996-252-1.5. Soltysik K, Czekaj P (April 2013). "Membrane estrogen receptors - is it an alternative wayof estrogen action?". J. Physiol. Pharmacol.64 (2): 129–42. PMID 23756388(https:///pubmed/23756388).6. Micevych PE, Kelly MJ (2012). "Membrane estrogen receptor regulation of hypothalamicfunction" (https:///pmc/articles/PMC3496782). Neuroendocrinology96(2): 103–10. doi:10.1159/000338400 (https:///10.1159%2F000338400). PMC 3496782 http://en.wik /wik i/Estrogen11/16。

systematic review and meta-analysis -回复什么是系统性回顾和荟萃分析？如何进行系统性回顾和荟萃分析？为什么系统性回顾和荟萃分析对研究和临床实践具有重要意义？第一步：什么是系统性回顾和荟萃分析系统性回顾和荟萃分析是一种科学方法，旨在总结和分析已有研究的数据以回答特定的研究问题。

系统性回顾是一种全面、系统地收集、评估和综合相关研究的方法，以回答某个特定问题。

它基于明确的研究目标和预先定义的研究策略，搜索出所有相关的研究，并对其质量进行评估。

最后，通过分析和综合研究的结果，得出结论并提供一种权威的证据。

荟萃分析则是通过将一系列系统性回顾的结果结合起来，进行统计分析和综合，以得出更准确、可靠的结论。

荟萃分析常用于结合多个小样本研究的结果，从而得出更具统计意义和临床实践意义的结论。

第二步：如何进行系统性回顾和荟萃分析1. 提出研究问题和目的：系统性回顾和荟萃分析的第一步是明确研究的问题和目的。

研究问题应该是具体和明确的，以便能够明确搜索策略和选择适当的研究。

2. 制定研究策略：制定一个详细的研究策略是进行系统性回顾和荟萃分析的关键步骤之一。

这包括明确搜索的数据库、关键词和筛选标准等。

研究策略应该充分涵盖所有相关研究，并尽量减少出错和偏见。

3. 检索研究文献：根据制定的策略，检索相关的研究文献。

这通常涉及到搜索多个数据库，并根据预先定义的标准筛选出符合要求的文章。

同时，还可以通过手动搜索和文献的相关引用来获取更多的研究。

4. 评估研究质量：选择包含在回顾中的研究后，需要对其质量进行评估。

这可以通过使用预定义的工具和准则，如Cochrane协作网络所提供的工具来完成。

评估质量是为了排除低质量的研究，并确保结果的可靠性。

5. 分析和综合研究结果：根据研究问题和目的，进行数据提取和分析。

这可能涉及到统计学方法，如计算效应量和合并风险比等。

然后，通过综合研究结果，得出结论并提供相应的证据。