Artificial Neural Network to Predict Leaf Population Chlorophyll Content from Cotton Plant Images

Leaf population chlorophyll content in a population of crops, if obtained in a timely manner, served as a key indicator for growth management and diseases diagnosis. In this paper, a three-layer multilayer perceptron （MLP） artificial neural network （ANN） based prediction system was presented for predicting the leaf population chlorophyll content from the cotton plant images. As the training of this prediction system relied heavily on how well those leaf green pixels were separated from background noises in cotton plant images, a global thresholding algorithm and an omnidirectional scan noise filtering coupled with the hue histogram statistic method were designed for leaf green pixel extraction. With the obtained leaf green pixels, the system training was carried out by applying a back propagation algorithm. The proposed system was tested to predict the chlorophyll content from the cotton plant images. The results using the proposed system were in sound agreement with those obtained by the destructive method. The average prediction relative error for the chlorophyll density （μg cm^-2） in the 17 testing images was 8.41%.

Risk prediction models for hepatocellular carcinoma in different populations

Hepatocellular carcinoma （HCC） is a malignant disease with limited therapeutic options due to its aggressive progression. It places heaW burden on most low and middle income countries to treat HCC patients. Nowadays accurate HCC risk predictions can help making decisions on the need for HCC surveillance and antiviral therapy. HCC risk prediction models based on major risk factors of HCC are useful and helpful in providing adequate surveillance strategies to individuals who have different risk levels. Several risk prediction models among cohorts of different populations for estimating HCC incidence have been presented recently by using simple, efficient, and ready-to-use parameters. Moreover, using predictive scoring systems to assess HCC development can provide suggestions to improve clinical and public health approaches, making them more cost-effective and effort-effective, for inducing personalized surveillance programs according to risk stratification. In this review, the features of risk prediction models of HCC across different populations were summarized, and the perspectives of HCC risk prediction models were discussed as well.

Risk factors for acute kidney injury following coronary artery bypass graft surgery in a Chinese population and development of a prediction model

BACKGROUND Acute kidney injury(AKI)after coronary artery bypass graft(CABG)surgery is associated with significant morbidity and mortality.This retrospective study aimed to establish a risk score for postoperative AKI in a Chinese population.METHODS A total of 1138 patients undergoing CABG were collected from September 2018 to May 2020 and divided into a derivation and validation cohort.AKI was defined according to the Kidney Disease Improving Global Outcomes(KDIGO)criteria.Multivariable logistic regression analysis was used to determine the independent predictors of AKI,and the predictive ability of the model was determined using a receiver operating characteristic(ROC)curve.RESULTS The incidence of cardiac surgery–associated acute kidney injury(CSA-AKI)was 24.17%,and 0.53%of AKI patients required dialysis(AKI-D).Among the derivation cohort,multivariable logistic regression showed that age≥70 years,body mass index(BMI)≥25 kg/m2,estimated glomerular filtration rate(eGFR)≤60 mL/min per 1.73 m2,ejection fraction(EF)≤45%,use of statins,red blood cell transfusion,use of adrenaline,intra-aortic balloon pump(IABP)implantation,postoperative low cardiac output syndrome(LCOS)and reoperation for bleeding were independent predictors.The predictive model was scored from 0 to32 points with three risk categories.The AKI frequencies were as follows:0-8 points(15.9%),9-17 points(36.5%)and≥18 points(90.4%).The area under of the ROC curve was 0.730(95%CI:0.691-0.768)in the derivation cohort.The predictive index had good discrimination in the validation cohort,with an area under the curve of 0.735(95%CI:0.655-0.815).The model was well calibrated according to the Hosmer-Lemeshow test(P=0.372).CONCLUSION The performance of the prediction model was valid and accurate in predicting KDIGO-AKI after CABG surgery in Chinese patients,and could improve the early prognosis and clinical interventions.

Bayes Prediction of Future Observables from Exponentiated Populations with Fixed and Random Sample Size

Bayesian predictive probability density function is obtained when the underlying pop-ulation distribution is exponentiated and subjective prior is used. The corresponding predictive survival function is then obtained and used in constructing 100(1 – ?)% predictive interval, using one- and two- sample schemes when the size of the future sample is fixed and random. In the random case, the size of the future sample is assumed to follow the truncated Poisson distribution with parameter λ. Special attention is paid to the exponentiated Burr type XII population, from which the data are drawn. Two illustrative examples are given, one of which uses simulated data and the other uses data that represent the breaking strength of 64 single carbon fibers of length 10, found in Lawless [40].

ECG is not a reliable predictor of sudden cardiac death in the general population

Objectives: To determine the predictive value of the ECG for sudden death in the general population. Design: In the Copenhagen City Heart Study, a randomly selected population sample in Copenhagen, Denmarkhas been followed prospectively since 1976. From this population sample, we analyzed ECGs of individuals who had suffered sudden cardiac death (SCD) before the age of 50 years and compared them with ECGs of a randomly selected control individuals from the same population sample. Specific ECG signs that could point toward a condition associated with a risk of SCD were noted. Results: From a total of 18,974 individuals in the cohort, 207 had died at an age younger than 50 years. Among these, 24 persons with SCD were identified. The most prevalent ECG abnormality was QRS fragmentation. We found no ECGs with long or short QTc, Brugada sign or WPW. The prevalence of signs of left ventricular hyper-trophy, early repolarization, or fragmentation was not different from the prevalence of these signs in the control group. Conclusion: In the Copenhagen City Heart Study, the ECG failed to predict SCD in persons who died before the age of 50 years.

Thought and Method on Establishing the Prediction Model of TCM Dominant Population with Advanced Digestive Tract Malignant Tumors based on TCM Tumor Registration Platform

Advanced digestive tract malignant tumors,represented by advanced colorectal cancer,advanced gastric cancer and advanced esophageal cancer,have insidious onsets and high mortality.Western medicine based on targeted therapy greatly can improves the benefit and efficacy for patients through population stratification,but its population is limited.Traditional Chinese medicine(TCM)has a long history in treatment of tumors,which is an important part of comprehensive treatment of tumors.Clinical observation has shown that different patients could get different efficacy from TCM treatment.Based on real world registration studies,patients with advanced colorectal cancer,advanced gastric cancer or advanced esophageal cancer who had received TCM treatment were observed and followed,and a TCM dominant population that achieved significant efficacy was screened out to carry out multivariate regression analysis,further explore key factors that affect survival in advanced digestive tract malignant tumors,and establish a prediction model of TCM dominant population.It will provide reference for the follow-up TCM treatment,and provide reference for development of individualized treatment plans,making the TCM treatment for advanced digestive tract malignant tumors more targeted,and helping to improve the benefit rate in TCM.

MAPT as a predisposing gene for sporadic amyotrophic lateral sclerosis in the Chinese Han population

A previous study of European Caucasian patients with sporadic amyotrophic lateral sclerosis demonstrated that a polymorphism in the microtubule-associated protein Tau （MAPT） gene was significantly associated with sporadic amyotrophic lateral sclerosis pathogenesis. Here, we tested this association in 107 sporadic amyotrophic lateral sclerosis patients and 100 healthy controls from the Chinese Han population. We screened the mutation-susceptible regions of MAPT- the 3＇ and 5＇ untranslated regions as well as introns 9, 10, 11, and 12 - by direct sequencing, and identified 33 genetic variations. Two of these, 105788 A 〉 G in intron 9 and 123972 T 〉 A in intron 11, were not present in the control group. The age of onset in patients with the 105788 A 〉 G and/or the 123972 T 〉 A variant was younger than that in patients without either genetic variation. Moreover, the pa- tients with a genetic variation were more prone to bulbar palsy and breathing difficulties than those with the wild-type genotype. This led to a shorter survival period in patients with a MAPT genetic variant. Our study suggests that the MAPT gene is a potential risk gene for sporadic amyotrophic lateral sclerosis in the Chinese Han population.

The Use of Lipoprotein-Associated Phospholipase A2 in a Chinese Population to Predict Cardiovascular Events

Objective To explore associations between lipoprotein-associated phospholipase A2(Lp-PLA2)and the risk of cardiovascular events in a Chinese population,with a long-term follow-up.Methods A random sample of 2,031 participants(73.6%males,mean age=60.4 years)was derived from the Asymptomatic Polyvascular Abnormalities Community study(APAC)from 2010 to 2011.Serum Lp-PLA2 levels were determined by enzyme-linked immunosorbent assay(ELISA).The composite endpoint was a combination of first-ever stroke,myocardial infarction(MI)or all-cause death.Lp-PLA2 associations with outcomes were assessed using Cox models.Results The median Lp-PLA2 level was 141.0 ng/m L.Over a median follow-up of 9.1 years,we identified 389 events(19.2%),including 137 stroke incidents,43 MIs,and 244 all-cause deaths.Using multivariate Cox regression,when compared with the lowest Lp-PLA2 quartile,the hazard ratios with95%confidence intervals for developing composite endpoints,stroke,major adverse cardiovascular events,and all-cause death were 1.77(1.24–2.54),1.92(1.03–3.60),1.69(1.003–2.84),and 1.94(1.18–3.18)in the highest quartile,respectively.Composite endpoints in 145(28.6%)patients occurred in the highest quartile where Lp-PLA2(159.0 ng/m L)was much lower than the American Association of Clinical Endocrinologists recommended cut-off point,200 ng/m L.Conclusion Higher Lp-PLA2 levels were associated with an increased risk of cardiovascular event/death in a middle-aged Chinese population.The Lp-PLA2 cut-off point may be lower in the Chinese population when predicting cardiovascular events.

Machine learning models for predicting non-alcoholic fatty liver disease in the general United States population:NHANES database

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)is the most common chronic liver disease,affecting over 30% of the United States population.Early patient identification using a simple method is highly desirable.AIM To create machine learning models for predicting NAFLD in the general United States population.METHODS Using the NHANES 1988-1994.Thirty NAFLD-related factors were included.The dataset was divided into the training(70%)and testing(30%)datasets.Twentyfour machine learning algorithms were applied to the training dataset.The bestperforming models and another interpretable model(i.e.,coarse trees)were tested using the testing dataset.RESULTS There were 3235 participants(n=3235)that met the inclusion criteria.In the training phase,the ensemble of random undersampling(RUS)boosted trees had the highest F1(0.53).In the testing phase,we compared selective machine learning models and NAFLD indices.Based on F1,the ensemble of RUS boosted trees remained the top performer(accuracy 71.1%and F10.56)followed by the fatty liver index(accuracy 68.8% and F10.52).A simple model(coarse trees)had an accuracy of 74.9% and an F1 of 0.33.CONCLUSION Not every machine learning model is complex.Using a simpler model such as coarse trees,we can create an interpretable model for predicting NAFLD with only two predictors:fasting C-peptide and waist circumference.Although the simpler model does not have the best performance,its simplicity is useful in clinical practice.

Gastric intestinal metaplasia development in African American predominant United States population

BACKGROUND Gastric cancer significantly contributes to cancer mortality globally.Gastric intestinal metaplasia(GIM)is a stage in the Correa cascade and a premalignant lesion of gastric cancer.The natural history of GIM formation and progression over time is not fully understood.Currently,there are no clear guidelines on GIM surveillance or management in the United States.AIM To investigate factors associated with GIM development over time in African American-predominant study population.METHODS This is a retrospective longitudinal study in a single tertiary hospital in Washington DC.We retrieved upper esophagogastroduodenoscopies(EGDs)with gastric biopsies from the pathology department database from January 2015 to December 2020.Patients included in the study had undergone two or more EGDswith gastric biopsy.Patients with no GIM at baseline were followed up until they developed GIM or until the last available EGD.Exclusion criteria consisted of patients age<18,pregnancy,previous diagnosis of gastric cancer,and missing data including pathology results or endoscopy reports.The study population was divided into two groups based on GIM status.Univariate and multivariate Cox regression was used to estimate the hazard induced by patient demographics,EGD findings,and Helicobacter pylori(H.pylori)status on the GIM status.RESULTS Of 2375 patients who had at least 1 EGD with gastric biopsy,579 patients were included in the study.138 patients developed GIM during the study follow-up period of 1087 d on average,compared to 857 d in patients without GIM(P=0.247).The average age of GIM group was 64 years compared to 56 years in the non-GIM group(P<0.001).In the GIM group,adding one year to the age increases the risk for GIM formation by 4%(P<0.001).Over time,African Americans,Hispanic,and other ethnicities/races had an increased risk of GIM compared to Caucasians with a hazard ratio(HR)of 2.12(1.16,3.87),2.79(1.09,7.13),and 3.19(1.5,6.76)respectively.No gender difference was observed between the study populations.Gastritis was associated with an increased risk for GIM development with an HR of 1.62(1.07,2.44).On the other hand,H.pylori infection did not increase the risk for GIM.CONCLUSION An increase in age and non-Caucasian race/ethnicity are associated with an increased risk of GIM formation.The effect of H.pylori on GIM is limited in low prevalence areas.

Research on Population Prediction of Guizhou Province

In accordance with population development of Guizhou Province in 1977-2007,this paper adopts natural growth method,model prediction method and gray system GM (1,1) model prediction method to predict population of Guizhou Province in 2020. On the basis of overall consideration of many factors of population development and future development trend of Guizhou Province,it analyzes advantages and disadvantages of three prediction methods,and obtains the prediction value of total population of Guizhou Province in 2020.

Predator Population Dynamics Involving Exponential Integral Function When Prey Follows Gompertz Model

The current study investigates the predator-prey problem with assumptions that interaction of predation has a little or no effect on prey population growth and the prey’s grow rate is time dependent. The prey is assumed to follow the Gompertz growth model and the respective predator growth function is constructed by solving ordinary differential equations. The results show that the predator population model is found to be a function of the well known exponential integral function. The solution is also given in Taylor’s series. Simulation study shows that the predator population size eventually converges either to a finite positive limit or zero or diverges to positive infinity. Under certain conditions, the predator population converges to the asymptotic limit of the prey model. More results are included in the paper.

Prevalence and predictors of hospitalization in Crohn's disease in a prospective population-based inception cohort from 2000-2012

AIM: To analyze the prevalence, length and predictors of hospitalization in the biological era in the populationbased inception cohort from Veszprem province.METHODS: Data of 331 incident Crohn's disease(CD) patients diagnosed between January 1, 2000 and December 31, 2010 were analyzed(median age at diagnosis: 28; IQR: 21-40 years). Both in- and outpatient records were collected and comprehensively reviewed.RESULTS: Probabilities of first CD-related hospitalization and re-hospitalization were 32.3%, 45.5%,53.7% and 13.6%, 23.9%, 29.8%, respectively after one, three and five years of follow-up in Kaplan-Meier analysis. First-year hospitalizations were related to diagnostic procedures(37%), surgery or disease activity(27% and 21%). Non-inflammatory disease behavior at diagnosis(HR = 1.32, P = 0.001) and perianal disease(HR = 1.47, P = 0.04) were associated with time to first CD-related hospitalization, while disease behavior change(HR = 2.38, P = 0.002) and need for steroids(HR = 3.14, P = 0.003) were associated with time to first re-hospitalization in multivariate analyses.Early CD-related hospitalization(within the year of diagnosis) was independently associated with need for immunosuppressives(OR = 2.08, P = 0.001) and need for surgeries(OR = 7.25, P < 0.001) during the disease course.CONCLUSION: Hospitalization and re-hospitalization rates are still high in this cohort, especially during the first-year after the diagnosis. Non-inflammatory disease behavior at diagnosis was identified as the pivotal predictive factor of both hospitalization and rehospitalization.

Evaluating the performance of genomic selection on purebred population by incorporating crossbred data in pigs

Genomic selection(GS)has been widely used in livestock,which greatly accelerated the genetic progress of complex traits.The population size was one of the significant factors affecting the prediction accuracy,while it was limited by the purebred population.Compared to directly combining two uncorrelated purebred populations to extend the reference population size,it might be more meaningful to incorporate the correlated crossbreds into reference population for genomic prediction.In this study,we simulated purebred offspring(PAS and PBS)and crossbred offspring(CAB)base on real genotype data of two base purebred populations(PA and PB),to evaluate the performance of genomic selection on purebred while incorporating crossbred information.The results showed that selecting key crossbred individuals via maximizing the expected genetic relationship(REL)was better than the other methods(individuals closet or farthest to the purebred population,CP/FP)in term of the prediction accuracy.Furthermore,the prediction accuracy of reference populations combining PA and CAB was significantly better only based on PA,which was similar to combine PA and PAS.Moreover,the rank correlation between the multiple of the increased relationship(MIR)and reliability improvement was 0.60-0.70.But for individuals with low correlation(Cor(Pi,PA or B),the reliability improvement was significantly lower than other individuals.Our findings suggested that incorporating crossbred into purebred population could improve the performance of genetic prediction compared with using the purebred population only.The genetic relationship between purebred and crossbred population is a key factor determining the increased reliability while incorporating crossbred population in the genomic prediction on pure bred individuals.

Comparative Study of Genetic Structure and Genetic Diversity betweenWild and Cultivated Populations of Taxus cuspidata,Northeast China

Taxus cuspidata is a rare plant with important medicinal and ornamental value.Aiming at the obvious differences between wild and cultivated populations of T.cuspidata from Northeast China,a total of 61 samples,that is,33 wild yews and 28 cultivated yews were used to analyze the differences and correlations of the kinship,genetic diversity,and genetic structure between them by specific length amplified fragment sequencing(SLAF-seq).Finally,470725 polymorphic SLAF tags and 58622 valid SNP markers were obtained.Phylogenetic analysis showed that 61 samples were classified into 2 clusters:wild populations and cultivated populations,and some wild yews were categorized into the cultivated populations;the genetic diversity analysis showed that the Nei diversity index of wild populations(0.4068)was smaller than that of cultivated populations(0.4414),and the polymorphic information content(PIC)of wild populations(0.2861)was smaller than that of cultivated populations(0.3309).The genetic differentiation analysis showed that the total populations of gene diversity(H_(t))of cultivated and wild populations were respectively 0.8159 and 0.5685,the coefficient of gene differentiation(G_(st))of cultivated and wild populations was respectively 0.3021 and 0.1068,and the gene flow(N_(m))(2.4967)of wild populations was larger than cultivated populations(0.8199).The molecular variance(AMOVA)revealed that inter-population variation accounted for 29.57%of the total genetic variation,while intra-population variation accounted for 70.42% of the total genetic variation(p<0.001),this suggested that the genetic variation in the T.cuspidata is mainly attributed to within-population factors.In conclusion,the genetic distance between geographical ecological groups of wild populations was generally smaller than that of cultivated populations,and the degree of genetic diversity and genetic differentiation was smaller than that of cultivated populations.As evident,the utilization of SLAF-seq technology enables efficient and accurate development of SNP markers suitable for genetic analysis of T.cuspidata species.These developed SNP markers can provide a molecular foundation for T.cuspidata breeding,construction of genetic maps,variety identification,and association analysis of agronomic traits.

试论干旱区流域开发中PRED的协调机制——以宁夏黄河段流域开发为例

1.干旱区流域开发与PRED问题 流域开发是指在全流域范围内,以水土资源为中心,综合开发国土资源,合理布局工农业生产,使人口、资源、环境、经济发展相协调的一个地域经济过程,从流域的类型可将其分为内陆型和外流型两种。干旱区流域开发的奥型类型是内陆的,但也有外流型的,如我国黄河的宁夏段和额尔齐斯河上游,美国的科罗拉多河流。干早区流域的合理开发,对协调干旱区PRED有着重要意义。

FEV_(1)%pred、FEV_(1)/VC_(max)%在不同年龄哮喘患儿临床诊断中的应用价值

目的:研究FEV_(1)%pred(第1秒用力呼气容积占预测值的百分比)、FEV_(1)/VC_(max)%(第1秒用力呼气体积与最大肺活量的百分比)在不同年龄哮喘患儿临床诊断中的应用价值。方法:选取佛山市妇幼保健院2022年5月—2023年5月就诊的哮喘患儿,并按照年龄阶段不同分为学龄前组(5~6岁)、早学龄组(7~8岁)、中学龄组(9~10岁)、晚学龄组(11~12岁)、青春初期组(13~14岁),各30例,另外选取同期在医院进行体检的健康儿童90例作为学龄前对照组、早学龄对照组、中学龄对照组、晚学龄对照组、青春初期对照组,各18例。检测不同组别患儿的FEV_(1)%pred、FEV_(1)/FVC_(max)%,同时用受试者操作特征(ROC)曲线界定出不同组患儿诊断哮喘的FEV_(1)%pred、FEV_(1)/VC_(max)%的最佳界值,比较不同组FEV_(1)%pred、FEV_(1)/VC_(max)%切点值的敏感度及特异度。结果:五组哮喘患儿FEV_(1)%pred、FEV_(1)/VC_(max)%均低于对照组,差异均有统计学意义(P<0.05);以85.67%、84.11%为界点鉴别诊断在早学龄组患儿FEV_(1)%pred、FEV_(1)/VC_(max)%的AUC值最大,敏感度和特异度分别为83.3%、94.4%及76.7%、94.4%。结论:FEV_(1)%pred和FEV_(1)/VC_(max)%作为哮喘诊断指标,在不同年龄段哮喘患儿中显示出差异化的敏感度和特异度,其最佳切点值能有效指导临床诊断,对早期识别和治疗哮喘具有重要应用价值。

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

KCNQ1 rs2237895 gene polymorphism increases susceptibility to type 2 diabetes mellitus in Asian populations

BACKGROUND The association of single nucleotide polymorphism of KCNQ1 gene rs2237895 with type 2 diabetes mellitus(T2DM)is currently controversial.It is unknown whether this association can be gene realized across different populations.AIM To determine the association of KCNQ1 rs2237895 with T2DM and provide reliable evidence for genetic susceptibility to T2DM.METHODS We searched PubMed,Embase,Web of Science,Cochrane Library,Medline,Baidu Academic,China National Knowledge Infrastructure,China Biomedical Literature Database,and Wanfang to investigate the association between KCNQ1 gene rs2237895 and the risk of T2DM up to January 12,2022.Review Manager 5.4 was used to analyze the association of the KCNQ1 gene rs2237895 polymorphism with T2DM and to evaluate the publication bias of the selected literature.RESULTS Twelve case–control studies(including 11273 cases and 11654 controls)met our inclusion criteria.In the full population,allelic model[odds ratio(OR):1.19;95%confidence interval(95%CI):1.09–1.29;P<0.0001],recessive model(OR:1.20;95%CI:1.11–1.29;P<0.0001),dominant model(OR:1.27.95%CI:1.14–1.42;P<0.0001),and codominant model(OR:1.36;95%CI:1.15–1.60;P=0.0003)(OR:1.22;95%CI:1.10–1.36;P=0.0002)indicated that the KCNQ1 gene rs2237895 polymorphism was significantly correlated with susceptibility to T2DM.In stratified analysis,this association was confirmed in Asian populations:allelic model(OR:1.25;95%CI:1.13–1.37;P<0.0001),recessive model(OR:1.29;95%CI:1.11–1.49;P=0.0007),dominant model(OR:1.35;95%CI:1.20–1.52;P<0.0001),codominant model(OR:1.49;95%CI:1.22–1.81;P<0.0001)(OR:1.26;95%CI:1.16–1.36;P<0.0001).In non-Asian populations,this association was not significant:Allelic model(OR:1.06,95%CI:0.98–1.14;P=0.12),recessive model(OR:1.04;95%CI:0.75–1.42;P=0.83),dominant model(OR:1.06;95%CI:0.98–1.15;P=0.15),codominant model(OR:1.08;95%CI:0.82–1.42;P=0.60.OR:1.15;95%CI:0.95–1.39;P=0.14).CONCLUSION KCNQ1 gene rs2237895 was significantly associated with susceptibility to T2DM in an Asian population.Carriers of the C allele had a higher risk of T2DM.This association was not significant in non-Asian populations.

Changes in the adult sex ratio of six duck species breeding populations over two decades

Despite all efforts,long-term changes in the adult sex ratios of breeding duck populations are still unclear;this uncertainty is especially true for male-bias populations,which are often under the scrutiny of researchers lacking convenient results for the active protection of endangered species.Species with male-bias populations are usually strongly affected by a decline in population size that leads to a higher extinction risk.In this study,we examined our long-term data of the abundance of breeding populations in six duck species(Mallard Anas platyrhynchos,Gadwall Mareca strepera,Red-crested Pochard Netta rufina,Common Pochard Aythya ferina,Tufted Duck Aythya fuligula,and Common Goldeneye Bucephala clangula)from fishponds in South Bohemia,Czechia,between 2004 and 2022.This evidence was used to assess long-term changes in the adult sex ratio in these breeding populations and investigate the possible effects of the NAO index(North Atlantic Oscillation index)on them,indicating climate conditions in winter.We determined a long-term decrease of the proportion of females in the breeding season in two of the six examined species:Common Pochard and Red-crested Pochard,which is driven by the long-term increase in the number of males in contrast to the decreasing or stable number of females likely caused by different migration behaviours between females and males.In the case of Common Pochard,in breeding populations,we estimated 60-65%of males in the early 2000s rising to 75-80%in the early 2020s.However,we establish no significant effects linked to climate conditions of the previous winter in these species as a crucial cause of the changes of the proportion of females in the breeding population.