Klinefelter syndrome （KS） （47, XXY） is the most abundant sex-chromosome disorder, and is a common cause of infertility and hypogonadism in men. Most men with KS go through life without knowing the diagnosis, as on...Klinefelter syndrome （KS） （47, XXY） is the most abundant sex-chromosome disorder, and is a common cause of infertility and hypogonadism in men. Most men with KS go through life without knowing the diagnosis, as only 25% are diagnosed and only a few of these before puberty. Apart from hypogonadism and azoospermia, most men with KS suffer from some degree of learning disability and may have various kinds of psychiatric problems. The effects of long-term hypogonadism may be difficult to discern from the gene dose effect of the extra X-chromosome. Whatever the cause, alterations in body composition, with more fat and less muscle mass and diminished bone mineral mass, as well as increased risk of metabolic consequences, such as type 2 diabetes and the metabolic syndrome are all common in KS. These findings should be a concern as they are not simply laboratory findings; epidemiological studies in KS populations show an increased risk of beth hospitalization and death from various diseases. Testosterone treatment should be offered to KS patients from early puberty, to secure a proper masculine development, nonetheless the evidence is weak or nonexisting, since no randomized controlled trials have ever been published. Here, we will review the current knowledge of hypogonadism in KS and the rationale for testosterone treatment and try to give our best recommendations for surveillance of this rather common, but often ignored, syndrome.展开更多
BACKGROUND Transgender individuals receiving masculinising or feminising gender-affirming hormone therapy with testosterone or estradiol respectively,are at increased risk of adverse cardiovascular outcomes,including ...BACKGROUND Transgender individuals receiving masculinising or feminising gender-affirming hormone therapy with testosterone or estradiol respectively,are at increased risk of adverse cardiovascular outcomes,including myocardial infarction and stroke.This may be related to the effects of testosterone or estradiol therapy on body composition,fat distribution,and insulin resistance but the effect of genderaffirming hormone therapy on these cardiovascular risk factors has not been extensively examined.AIM To evaluate the impact of gender-affirming hormone therapy on body composition and insulin resistance in transgender individuals,to guide clinicians in minimising cardiovascular risk.METHODS We performed a review of the literature based on PRISMA guidelines.MEDLINE,Embase and PsycINFO databases were searched for studies examining body composition,insulin resistance or body fat distribution in transgender individuals aged over 18 years on established gender-affirming hormone therapy.Studies were selected for full-text analysis if they investigated transgender individuals on any type of gender-affirming hormone therapy and reported effects on lean mass,fat mass or insulin resistance.RESULTS The search strategy identified 221 studies.After exclusion of studies that did not meet inclusion criteria,26 were included(2 cross-sectional,21 prospectiveuncontrolled and 3 prospective-controlled).Evidence in transgender men suggests that testosterone therapy increases lean mass,decreases fat mass and has no impact on insulin resistance.Evidence in transgender women suggests that feminising hormone therapy(estradiol,with or without anti-androgen agents)decreases lean mass,increases fat mass,and may worsen insulin resistance.Changes to body composition were consistent across almost all studies:Transgender men on testosterone gained lean mass and lost fat mass,and transgender women on oestrogen experienced the reverse.No study directly contradicted these trends,though several small studies of short duration reported no changes.Resu展开更多
Here,a new integrated machine learning and Chou’s pseudo amino acid composition method has been proposed for in silico epitope mapping of severe acute respiratorysyndrome-like coronavirus antigens.For this,a training...Here,a new integrated machine learning and Chou’s pseudo amino acid composition method has been proposed for in silico epitope mapping of severe acute respiratorysyndrome-like coronavirus antigens.For this,a training dataset including 266 linear B-cell epitopes,1,267 T-cell epitopes and 1,280 non-epitopes were prepared.The epitope sequences were then converted to numerical vectors using Chou’s pseudo amino acid composition method.The vectors were then introduced to the support vector machine,random forest,artificial neural network,and K-nearest neighbor algorithms for the classification process.The algorithm with the highest performance was selected for the epitope mapping procedure.Based on the obtained results,the random forest algorithm was the most accurate classifier with an accuracy of 0.934 followed by K-nearest neighbor,artificial neural network,and support vector machine respectively.Furthermore,the efficacies of predicted epitopes by the trained random forest algorithm were assessed through their antigenicity potential as well as affinity to human B cell receptor and MHC-I/II alleles using the VaxiJen score and molecular docking,respectively.It was also clear that the predicted epitopes especially the B-cell epitopes had high antigenicity potentials and good affinities to the protein targets.According to the results,the suggested method can be considered for developing specific epitope predictor software as well as an accelerator pipeline for designing serotype independent vaccine against the virus.展开更多
文摘Klinefelter syndrome （KS） （47, XXY） is the most abundant sex-chromosome disorder, and is a common cause of infertility and hypogonadism in men. Most men with KS go through life without knowing the diagnosis, as only 25% are diagnosed and only a few of these before puberty. Apart from hypogonadism and azoospermia, most men with KS suffer from some degree of learning disability and may have various kinds of psychiatric problems. The effects of long-term hypogonadism may be difficult to discern from the gene dose effect of the extra X-chromosome. Whatever the cause, alterations in body composition, with more fat and less muscle mass and diminished bone mineral mass, as well as increased risk of metabolic consequences, such as type 2 diabetes and the metabolic syndrome are all common in KS. These findings should be a concern as they are not simply laboratory findings; epidemiological studies in KS populations show an increased risk of beth hospitalization and death from various diseases. Testosterone treatment should be offered to KS patients from early puberty, to secure a proper masculine development, nonetheless the evidence is weak or nonexisting, since no randomized controlled trials have ever been published. Here, we will review the current knowledge of hypogonadism in KS and the rationale for testosterone treatment and try to give our best recommendations for surveillance of this rather common, but often ignored, syndrome.
文摘目的探讨维持性血液透析(maintenance hemodialysis,MHD)患者伴发代谢综合征(metabolic syndrome,MS)时人体成分的变化。方法选择上海交通大学医学院附属仁济医院MHD患者93例。应用人体成分监测仪(body composition monitor,BCM)进行人体成分分析。同时测量身高、腰围、臀围和肱三头肌皮下脂肪厚度,并计算体质量指数(body mass index,BMI)。进行主观综合性营养评估(subjective global assessment,SGA)。记录年龄、性别、透析龄、空腹血糖、血脂、白蛋白等生化指标。根据2005年国际糖尿病联盟标准,筛选出MS患者,比较MS和非MS患者的人体成分组成情况和生化指标。结果 93例血液透析患者中伴发MS者28例(30.11%)。MS患者的空腹血糖、甘油三酯、C反应蛋白均高于非MS患者(P<0.05),而高密度脂蛋白水平相对较低(P<0.05);两组患者SGA评分相似;MS患者的体质量、BMI、腰围、臀围均高于非MS患者(P<0.05);BCM测量中,MS患者脂肪组织含量、脂肪量、脂肪组织指数高于非MS患者,差异有统计学意义(P<0.05),而瘦组织含量、瘦组织指数、水负荷则无明显差别。结论伴发MS的MHD患者存在脂肪(尤其是内脏脂肪)过度积聚,体质量增加、而肌肉量、SGA、白蛋白等营养指标和体内水分含量无明显变化。
基金Supported by Australian Government National Health and Medical Research Council,No.APP1143333Endocrine Society of Australia+2 种基金Austin Medical Research FoundationViertel Charitable Foundation Clinical Investigator Award,No.VIERCI2017009Royal Australasian College of Physicians Vincent Fairfax Family Foundation
文摘BACKGROUND Transgender individuals receiving masculinising or feminising gender-affirming hormone therapy with testosterone or estradiol respectively,are at increased risk of adverse cardiovascular outcomes,including myocardial infarction and stroke.This may be related to the effects of testosterone or estradiol therapy on body composition,fat distribution,and insulin resistance but the effect of genderaffirming hormone therapy on these cardiovascular risk factors has not been extensively examined.AIM To evaluate the impact of gender-affirming hormone therapy on body composition and insulin resistance in transgender individuals,to guide clinicians in minimising cardiovascular risk.METHODS We performed a review of the literature based on PRISMA guidelines.MEDLINE,Embase and PsycINFO databases were searched for studies examining body composition,insulin resistance or body fat distribution in transgender individuals aged over 18 years on established gender-affirming hormone therapy.Studies were selected for full-text analysis if they investigated transgender individuals on any type of gender-affirming hormone therapy and reported effects on lean mass,fat mass or insulin resistance.RESULTS The search strategy identified 221 studies.After exclusion of studies that did not meet inclusion criteria,26 were included(2 cross-sectional,21 prospectiveuncontrolled and 3 prospective-controlled).Evidence in transgender men suggests that testosterone therapy increases lean mass,decreases fat mass and has no impact on insulin resistance.Evidence in transgender women suggests that feminising hormone therapy(estradiol,with or without anti-androgen agents)decreases lean mass,increases fat mass,and may worsen insulin resistance.Changes to body composition were consistent across almost all studies:Transgender men on testosterone gained lean mass and lost fat mass,and transgender women on oestrogen experienced the reverse.No study directly contradicted these trends,though several small studies of short duration reported no changes.Resu
文摘Here,a new integrated machine learning and Chou’s pseudo amino acid composition method has been proposed for in silico epitope mapping of severe acute respiratorysyndrome-like coronavirus antigens.For this,a training dataset including 266 linear B-cell epitopes,1,267 T-cell epitopes and 1,280 non-epitopes were prepared.The epitope sequences were then converted to numerical vectors using Chou’s pseudo amino acid composition method.The vectors were then introduced to the support vector machine,random forest,artificial neural network,and K-nearest neighbor algorithms for the classification process.The algorithm with the highest performance was selected for the epitope mapping procedure.Based on the obtained results,the random forest algorithm was the most accurate classifier with an accuracy of 0.934 followed by K-nearest neighbor,artificial neural network,and support vector machine respectively.Furthermore,the efficacies of predicted epitopes by the trained random forest algorithm were assessed through their antigenicity potential as well as affinity to human B cell receptor and MHC-I/II alleles using the VaxiJen score and molecular docking,respectively.It was also clear that the predicted epitopes especially the B-cell epitopes had high antigenicity potentials and good affinities to the protein targets.According to the results,the suggested method can be considered for developing specific epitope predictor software as well as an accelerator pipeline for designing serotype independent vaccine against the virus.
