Over the past two decades, genome-wide association study(GWAS) has identified numerous genetic variants and loci associated with heritable diseases. With the gradual maturation and saturation of GWAS methodologies, transcriptome-wide association study(TWAS) offers a novel perspective by linkinggenetic phenotypes to gene expression levels. By integrating TWAS with other multi-omics analyses, researchers can gain a deeper understanding of heritable diseases. This article provides an overview of recent groundbreaking and representative TWAS methods and tools, analyzes their strengths and limitations, and discusses future trends in TWAS development.

Background With China's socioeconomic development, significant lifestyle changes have occurred among occupational groups, leading to alterations in cardiovascular metabolic risk factors. However, few studies have examined the secular trends of these risk factors in China's working population. Objective To analyze the trends in cardiovascular metabolic risk factors among the occupational population in nine provinces of China from 2009 to 2018, and to explore the associations between different occupational types and these risk factors, along with their clustering patterns, thereby providing evidence for targeted interventions. Methods This study utilized data from the China Health and Nutrition Survey (CHNS) in 2009, 2015, and 2018. The dataset covered 13274 employed individuals aged 18-59 years. Only participants with complete blood test results and physical measurement data were included in the final analysis. The average annual percentage change (AAPC) in the positive rates of risk factors was calculated using Joinpoint regression to analyze temporal trends. Multinomial logistic regression and binary logistic regression models were employed to examine the cross-sectional associations between occupational types (categorized as white-collar workers, agricultural workers, blue-collar workers, service workers, and others) and nine cardiovascular metabolic risk factors and their clustering (defined as having ≥2 risk factors) in 2018. Results A total of 8451 participants were included. From 2009 to 2018, significant increasing trends (AAPC>0, P<0.05) were observed for overweight, obesity, central obesity, borderline elevated triglycerides (TG), borderline elevated to elevated total cholesterol (TC), borderline elevated low-density lipoprotein cholesterol (LDL-C), elevated blood pressure and hypertension, diabetes. The most rapid increases were found for obesity (AAPC=6.07%, 95%CI: 3.42%, 8.88%), hypertension (AAPC=4.10%, 95%CI: 0.62%, 7.77%), and central obesity (AAPC=3.27%, 95%CI: 1.24%, 5.36%). The clustering rate of risk factors increased from 62.3% in 2009 to 73.2% in 2018 (AAPC=1.87%, 95%CI: 1.02%, 2.73%). The cross-sectional analysis in 2018, after adjusting for confounders, showed that compared with white-collar workers, blue-collar workers had a significantly lower risk of overweight (OR=0.67, 95%CI: 0.48, 0.95), central obesity (OR=0.65, 95%CI: 0.45, 0.92), and borderline high TG (OR=0.54, 95%CI: 0.35, 0.82). In contrast, agricultural workers had a higher risk of hypertension (OR=1.76, 95%CI: 1.14, 2.72). Conclusion Between 2009 and 2015, the burden of most cardiometabolic risk factors increases significantly among the Chinese occupational population, with the rate of increase slowing by 2018. Risks vary across occupational types, among which blue- collar workers report lower target outcomes. Targeted interventions focusing on the rapidly increasing risk factors and high-risk occupational groups are recommended.

Background With rising obesity rates and earlier hypertension onset among occupational populations, there is an urgent need to elucidate the long-term cardiovascular impacts of dynamic body weight patterns. Current evidence lacks trajectory modeling studies examining occupation-specific prevention strategies. Objective To investigate the association between long-term body mass index (BMI) trajectories and incident hypertension risk in Chinese working adults, and to examine occupation-specific heterogeneity in this relationship. Methods A dynamic sub-cohort of 4 413 occupational participants was constructed from ten survey waves (1991–2018) of the China Health and Nutrition Survey (CHNS). Eligible individuals had valid key BMI records at three or more independent follow-ups before the outcome event; the individual baseline was set as the year of their first participation in the survey. Group-based trajectory modeling (GBTM) was used to identify BMI change patterns. Cox proportional hazards regression was used to calculate hazard ratios (HRs) and 95% confidence interval (CI) for hypertension incidence across trajectory groups, with stratified analysis by occupational categories. Results Among 4413 occupational participants, 1441 incident hypertension cases were reported during the follow-up window. Three long-term BMI trajectories were identified: low-stable, moderate-slowly rising, and high-rising. In Model 3 with all selected confounders adjusted, compared with the low-stable group, the moderate-slowly rising group showed a significantly higher risk of incident hypertension (HR=1.28, 95%CI: 1.12, 1.45; P < 0.001), as did the high-increasing group (HR=1.80, 95%CI: 1.45, 2.23; P < 0.001). The stratified analyses revealed occupational differences in the association. Among agricultural workers, the moderate-slowly rising group (HR=1.35, 95%CI: 1.15, 1.57) and the high-rising group (HR=2.00, 95%CI: 1.50, 2.66) both exhibited significantly increased risks of hypertension (P<0.001). Conversely, among white-collar workers, an increased risk of hypertension was observed only in the high-rising group (HR=1.97, 95%CI: 1.23, 3.17; P<0.05). Conclusion Rapid BMI escalation constitutes a significant risk factor for incident hypertension in occupational populations. Targeted long-term weight monitoring and tailored interventions are recommended for high-risk occupations.

AIM:To analyze the influencing factors of postoperative malignant glaucoma(MG)in patients with primary angle-closure glaucoma(PACG)using logistic regression and decision tree models.METHODS:A retrospective study was conducted on PACG patients who underwent surgery at Eye Hospital of Handan City from March 2020 to March 2025. Patients were divided into two groups: the MG group, who developed MG within 6 mo postoperatively, and the non-MG group. Data were collected from the electronic medical record system. Univariate analysis was performed, followed by multivariate logistic regression to identify independent risk factors. A classification and regression tree model was constructed to visualize the hierarchical relationships among predictors. The predictive performance of the two models was evaluated and compared using receiver operating characteristic(ROC)curve analysis.RESULTS:Totally 182 cases(182 eyes)with PACG were enrolled in this study, including 91 cases(91 eyes)in the MG group and 91 cases(91 eyes)in the non-MG group. In the MG group, there were 53 males and 38 females; 69 cases were aged ≥60 y and 22 cases were aged <60 y. In the non-MG group, there were 47 males and 44 females; 33 cases were aged ≥60 y and 58 cases were aged <60 y. The non-MG group comprised 91 patients, including 47 males and 44 females. Among them, 33 cases were aged ≥60 y, and 58 cases were aged<60 y. The MG group had significantly higher proportions of patients aged ≥60 y, diabetes, moderate-stage PACG, persistent high intraocular pressure(IOP), complete anterior chamber angle closure, lens thickness <4.5 mm, axial length <22 mm, and severe postoperative inflammation compared to the non-MG group(all P<0.01). Multivariate Logistic regression identified the following as independent influencing factors for postoperative MG: age [OR (95%CI)=2.136(1.401-3.255)], PACG stage [OR (95%CI)=2.996(2.044-4.391)], IOP [OR (95%CI)=3.527(1.604-7.755)],anterior chamber angle [OR (95%CI)=4.826(2.498-9.324)], axial length [OR (95%CI)=5.125(1.265-20.771)], and severe postoperative inflammation [OR (95%CI)=2.338(1.478-3.699)](all P<0.05). The decision tree model selected six explanatory variables: age, PACG stage, IOP, anterior chamber angle status, axial length, and severe postoperative inflammation. Axial length was the primary splitting factor at the root node. The areas under the ROC curve(AUC)for the logistic regression and decision tree models were 0.913(0.863-0.950)and 0.921(0.872-0.956), respectively, with no significant difference between them(Z=0.561, P=0.575).CONCLUSION:Both the logistic regression and decision tree models effectively identify key influencing factors for postoperative MG in PACG patients, including age, PACG stage, IOP, anterior chamber angle status, axial length, and severe postoperative inflammation. The decision tree model offers an intuitive, visual representation of risk stratification, facilitating clinical decision-making. Both models are applicable for clinical risk assessment.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

OBJECTIVES: Keratoconus (KC) is a progressive corneal ectasia disorder, arising from a myriad of causes including genetic predispositions, environmental factors, biomechanical influences, and inflammatory reactions. This study aims to identify potential pathogenetic gene mutations in patients with sporadic KC in the Han Chinese population. METHODS: Twenty-five patients with primary KC as well as 50 unrelated population-matched healthy controls, were included in this study to identify potential pathogenic gene mutations among sporadic KC patients in the Han Chinese population. Sanger sequencing and whole-exome sequencing (WES) were used to analyze mutations in the zinc finger protein 469 (ZNF469) gene. Bioinformatics analysis was conducted to explore the potential role of ZNF469 in KC pathogenesis. RESULTS: Five novel heterozygous missense variants were identified in KC patients. Among them, 2 compound heterozygous variants, c.8986G>C (p. E2996Q) with c.11765A>C (p. D3922A), and c.4423C>G (p. L1475V) with c.10633G>A (p. G3545R), were determined to be possible pathogenic factors for KC. CONCLUSIONS Mutations in the ZNF469 gene may contribute to the development of KC in the Han Chinese population. These mutation sites may provide valuable information for future genetic screening of KC patients and their families.
Adolescent ; Adult ; Female ; Humans ; Male ; Case-Control Studies ; China/ethnology* ; Exome Sequencing ; Genetic Predisposition to Disease ; Keratoconus/genetics* ; Mutation ; Mutation, Missense ; Transcription Factors/genetics* ; East Asian People/genetics*

Effective annotation of in vivo drug metabolites using liquid chromatography-mass spectrometry (LC-MS) remains a formidable challenge. Herein, a metabolic reaction-based molecular networking (MRMN) strategy is introduced, which enables the "one-pot" discovery of prototype drugs and their metabolites. MRMN constructs networks by matching metabolic reactions and evaluating MS² spectral similarity, incorporating innovations and improvements in feature degradation of MS² spectra, exclusion of endogenous interference, and recognition of redundant nodes. A minimum 75% correlation between structural similarity and MS² similarity of neighboring metabolites was ensured, mitigating false negatives due to spectral feature degradation. At least 79% of nodes, 49% of edges, and 97% of subnetworks were reduced by an exclusion strategy of endogenous ions compared to the Global Natural Products Social Molecular Networking (GNPS) platform. Furthermore, an approach of redundant ions identification was refined, achieving a 10%-40% recognition rate across different samples. The effectiveness of MRMN was validated through a single compound, plant extract, and mixtures of multiple plant extracts. Notably, MRMN is freely accessible online at https://yaolab.network, broadening its applications.

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

Objective To investigate the role of membrane-associated tyrosine/threonine-protein ki-nase 1(PKMYT1)in glucocorticoid(GC)-induced osteoblast(OB)apoptosis,providing a theoretical basis and potential therapeutic targets for early-stage steroid-induced avascular necrosis of the femoral head(SANFH).Methods(1)Mouse calvarial osteoblastic cells(MC3T3-E1)were selected for the study.The control group was cultured in standard medium,while the experimental group was subject-ed to osteogenic induction culture,with osteogenic capacity verified by alkaline phosphatase(ALP)and Alizarin Red S(ARS)staining.Then,mouse osteoblasts(mOB)were treated with different con-centrations of GC.After that,apoptosis was detected by using Annexin V-FITC/PI double staining as-say,while cell proliferation was assessed by using Cell Counting Kit-8(CCK8).Moreover,the expres-sions of anti-apoptotic protein B-cell lymphoma/leukemia-2(BCL-2),pro-apoptotic proteins cleaved caspase-3andcleavedcaspase-9(cleavedcaspase 3/9)weredetectedbyusing Westernblotting(WB).Meanwhile,proteomic analysis was employed to identify molecules potentially regulating GC-in-duced apoptosis in mOBs.What's more,quantitative real-time PCR(qPCR)and WB were used to further analyze PKMYT1 expression.(2)mOBs were treated with PKMYT1 inhibitor GSK-1520489A of different concentrations to screen the optimal one,and all subjects were then further divided into a control,a GC,a GSK-1520489A,and a GC+GSK-1520489A group.Later,the expression of PK-MYT1 and apoptosis-related proteins BCL-2 and cleaved caspase 3/9 of all groups were detected us-ing WB,and cell viability and cytotoxicity were evaluated by CCK8 assay,with cell proliferation by using 5-ethynyl-2'-deoxyuridine(EDU)assay and apoptosis by cell live/dead staining and Annexin V-FITC/PI double staining.(3)mOBs were infected with PKMYT1 overexpression lentiviral vectors,and its efficiency was verified by using immunofluorescence,qPCR,and WB.After successful overexpres-sion of PKMYT1,all cells were divided into the control,GC,PKMYT1 overexpression(OE),and OE+GC groups,whose cell proliferation was detected by EDU assay,and apoptosis was assessed by Annexin V-FITC/PI double staining and cell live/dead staining.(4)To verify the changes in PKMYT1 expression in human osteoblasts(hOB),hOBs extracted from human femoral heads of healthy individu-als were chosen into the control group,while those from patients with hormone-induced avascular ne-crosis of the femoral head(hSANFH)were selected into the hSANFH group.Then,PKMYT1 expres-sion in both groups was detected by using qPCR and WB.Results(1)After inducing the differentia-tion of mouse calvarial osteoblastic cells(MC3T3-E1)into mature osteoblasts,under the action of GC,compared with the control group,with the increase of GC concentration,the experimental group showed increased mOB apoptosis(P<0.01)and expression of cleaved caspase 3/9(P<0.01),but de-creased cell viability(P<0.01)and expressionof apoptosis-relatedprotein BCL-2(P<0.01).More-over,according to the proteomic sequencing,significant decrease was observed in the PKMYT1 expres-sion in mature mOBs treated with GC.(2)As to treatment of mOBs with different concentrations of PKMYT1 inhibitor GSK-1520489A,with the increase of concentration,cell viability decreased and cy-totoxicity increased(P<0.001).Moreover,compared with the control group,mOBs proliferation de-creased(P<0.001)and apoptosis increased(P<0.001)in the GSK-1520489A group.Meanwhile,com-pared with the GC group,mOB proliferation decreased(P<0.05)and apoptosis increased significantly(P<0.01)in the GC+GSK-1520489A group.(3)After overexpression of PKMYT1,in comparison with the control group,mOB proliferation increased(P<0.001)but apoptosis did not increase significantly(P>0.05)in the OE group.Moreover,compared with the GC group,mOB proliferation increased(P<0.001)but apoptosis decreased(P<0.001)significantly in the OE+GC group.(4)In hOBs extracted from human femoral head tissues,qPCR and WB results showed that PKMYT1 expression of the hSANFH group was significantly lower than the control group(P<0.001).Conclusion Down regulation of PKMYT1 expression promotes GC-induced apoptosis of mOBs.Conversely,over expression of PK-MYT1 inhibits GC-induced apoptosis of mOBs.Therefore,PKMYT1 may serve as a potential target for the early treatment of SANFH.