Bariatric surgery: trends in utilization, complications, conversions and revisions.

BACKGROUND: Sleeve gastrectomy (SG) increased in popularity after 2010 but recent data suggest it has concerning rates of gastroesophageal reflux and need for conversions. This study aims to evaluate recent trends in the utilization of bariatric procedures, associated complications, and conversions using an administrative claims database in the United States. METHODS: We included adults who had bariatric procedures from 2000 to 2020 with continuous enrollment for at least 6 months in the MarketScan Commercial Claims and Encounters database. Index bariatric procedures and subsequent revisions or conversions were identified using CPT codes. Baseline comorbidities and postoperative complications were identified with ICD-9-CM and ICD-10 codes. Cumulative incidences of complications were estimated at 30-days, 6-months, and 1-year and compared with stabilized inverse probability of treatment weighted Kaplan-Meier analysis. RESULTS: We identified 349,411 bariatric procedures and 5521 conversions or revisions. The sampled SG volume appeared to begin declining in 2018 while Roux-en-Y gastric bypass (RYGB) remained steady. Compared to RYGB, SG was associated with lower 1-year incidence [aHR, (95% CIs)] for 30-days readmission [0.65, (0.64-0.68)], dehydration [0.75, (0.73-0.78)], nausea or vomiting [0.70, (0.69-0.72)], dysphagia [0.55, (0.53-0.57)], and gastrointestinal hemorrhage [0.43, (0.40-0.46)]. Compared to RYGB, SG was associated with higher 1-year incidence [aHR, (95% CIs)] of esophagogastroduodenoscopy [1.13, (1.11-1.15)], heartburn [1.38, (1.28-1.49)], gastritis [4.28, (4.14-4.44)], portal vein thrombosis [3.93, (2.82-5.48)], and hernias of all types [1.36, (1.34-1.39)]. There were more conversions from SG to RYGB than re-sleeving procedures. SG had a significantly lower 1-year incidence of other non-revisional surgical interventions when compared to RYGB. CONCLUSIONS: The overall volume of bariatric procedures within the claims database appeared to be declining over the last 10 years. The decreasing proportion of SG and the increasing proportion of RYGB suggest the specific complications of SG may be driving this trend. Clearly, RYGB should remain an important tool in the bariatric surgeon's armamentarium.

Evaluation of 30-day outcomes for open ventral hernia repair using self-gripping versus nonself-gripping mesh.

BACKGROUND: The use of mesh is standard of care for large ventral hernias repaired on an elective basis. The most used type of mesh includes synthetic polypropylene mesh; however, there has been an increase in the usage of a new polyester self-gripping mesh, and there are limited data regarding its efficacy for ventral hernia. The purpose of the study is to determine whether there is a difference in surgical site occurrence (SSO), surgical site infection (SSI), surgical site occurrence requiring procedural intervention (SSOPI), and recurrence at 30 days after ventral hernia repair (VHR) using self-gripping (SGM) versus non-self-gripping mesh (NSGM). METHODS: We performed a retrospective study from January 2014 to April 2022 using the Abdominal Core Health Quality Collaborative (ACHQC). We collected data on patients over 18 years of age who underwent elective open VHR using SGM or NSGM and whom had 30-day follow-up. Propensity matching was utilized to control for variables including hernia width, body mass index, age, ASA, and mesh location. Data were analyzed to identify differences in SSO, SSI, SSOPI, and recurrence at 30 days. RESULTS: 9038 patients were identified. After propensity matching, 1766 patients were included in the study population. Patients with SGM had similar demographic and clinical characteristics compared to NSGM. The mean hernia width to mesh width ratio was 8 cm:18 cm with NSGM and 7 cm:15 cm with SGM (p = 0.63). There was no difference in 30-day rates of recurrence, SSI or SSO. The rate of SSOPI was also found to be 5.4% in the nonself-gripping group compared to 3.1% in the self-gripping mesh group (p < .005). There was no difference in patient-reported outcomes at 30 days. CONCLUSIONS: In patients undergoing ventral hernia repair with mesh, self-gripping mesh is a safe type of mesh to use. Use of self-gripping mesh may be associated with lower rates of SSOPI when compared to nonself-gripping mesh.

dbPTM in 2022: an updated database for exploring regulatory networks and functional associations of protein post-translational modifications.

Protein post-translational modifications (PTMs) play an important role in different cellular processes. In view of the importance of PTMs in cellular functions and the massive data accumulated by the rapid development of mass spectrometry (MS)-based proteomics, this paper presents an update of dbPTM with over 2 777 000 PTM substrate sites obtained from existing databases and manual curation of literature, of which more than 2 235 000 entries are experimentally verified. This update has manually curated over 42 new modification types that were not included in the previous version. Due to the increasing number of studies on the mechanism of PTMs in the past few years, a great deal of upstream regulatory proteins of PTM substrate sites have been revealed. The updated dbPTM thus collates regulatory information from databases and literature, and merges them into a protein-protein interaction network. To enhance the understanding of the association between PTMs and molecular functions/cellular processes, the functional annotations of PTMs are curated and integrated into the database. In addition, the existing PTM-related resources, including annotation databases and prediction tools are also renewed. Overall, in this update, we would like to provide users with the most abundant data and comprehensive annotations on PTMs of proteins. The updated dbPTM is now freely accessible at https://awi.cuhk.edu.cn/dbPTM/.

Application of machine learning to predict postoperative gastrointestinal bleed in bariatric surgery.

BACKGROUND: Postoperative gastrointestinal bleeding (GIB) is a rare but serious complication of bariatric surgery. The recent rise in extended venous thromboembolism regimens as well as outpatient bariatric surgery may increase the risk of postoperative GIB or lead to delay in diagnosis. This study seeks to use machine learning (ML) to create a model that predicts postoperative GIB to aid surgeon decision-making and improve patient counseling for postoperative bleeds. METHODS: The Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) database was used to train and validate three types of ML methods: random forest (RF), gradient boosting (XGB), and deep neural networks (NN), and compare them with logistic regression (LR) regarding postoperative GIB. The dataset was split using fivefold cross-validation into training and validation sets, in an 80/20 ratio. The performance of the models was assessed using area under the receiver operating characteristic curve (AUROC) and compared with the DeLong test. Variables with the strongest effect were identified using Shapley additive explanations (SHAP). RESULTS: The study included 159,959 patients. Postoperative GIB was identified in 632 (0.4%) patients. The three ML methods, RF (AUROC 0.764), XGB (AUROC 0.746), and NN (AUROC 0.741) all outperformed LR (AUROC 0.709). The best ML method, RF, was able to predict postoperative GIB with a specificity and sensitivity of 70.0% and 75.4%, respectively. Using DeLong testing, the difference between RF and LR was determined to be significant with p < 0.01. Type of bariatric surgery, pre-op hematocrit, age, duration of procedure, and pre-op creatinine were the 5 most important features identified by ML retrospectively. CONCLUSIONS: We have developed a ML model that outperformed LR in predicting postoperative GIB. Using ML models for risk prediction can be a helpful tool for both surgeons and patients undergoing bariatric procedures but more interpretable models are needed.

A retrospective quantitative implementation evaluation of Safer Opioid Prescribing, a Canadian continuing education program.

BACKGROUND: Continuing health professions education (CHPE) is an important policy intervention for the opioid epidemic. Besides effectiveness or impact, health policy implementation should be studied to understand how an intervention was delivered within complex environments. Implementation outcomes can be used to help interpret CHPE effects and impacts, help answer questions of "how" and "why" programs work, and inform transferability. We evaluated Safer Opioid Prescribing (SOP), a national CHPE program, using implementation outcomes of reach, dose, fidelity, and participant responsiveness. METHODS: We conducted a retrospective quantitative implementation evaluation of the 2014-2017 cohorts of SOP. To measure reach and dose, we examined participation and completion data. We used Ontario physician demographic data, including regulatory status with respect to controlled substances, to examine relevant trends. To measure fidelity and participant responsiveness, we analyzed participant-provided evaluations of bias, active learning, and relevance to practice. We used descriptive statistics and measures of association for both continuous and categorical variables. We used logistic regression to determine predictors of workshop participation and analysis of covariance to examine variation in satisfaction across different-sized sessions. RESULTS: Reach: In total, there were 472 unique participants, 84.0% of whom were family physicians. Among Ontario physician participants, 90.0% were family physicians with characteristics representative of province-wide demographics. Dose: Webinar completion rate was 86.2% with no differences in completion based on rurality, gender, or controlled substance prescribing status with medical regulatory authorities. Fidelity and participant responsiveness: Nearly all participants rated the three webinars and workshop as balanced, and each element of SOP was also rated as highly relevant to clinical practice. CONCLUSIONS: This evaluation demonstrates that Safer Opioid Prescribing was implemented as intended. Over a short period and without any external funding, the program reached more than 1% of the Ontario physician workforce. This suggests that the program may be a good model for using virtual CHPE to reach a critical mass of prescribers. This study represents a methodological advance of adapting evaluation methods from health policy and complex interventions for continuing health professions education. Future studies will assess effectiveness and impact on opioid prescribing and utilization within evaluation models of complex interventions.

Characterization and identification of lysine glutarylation based on intrinsic interdependence between positions in the substrate sites.

BACKGROUND: Glutarylation, the addition of a glutaryl group (five carbons) to a lysine residue of a protein molecule, is an important post-translational modification and plays a regulatory role in a variety of physiological and biological processes. As the number of experimentally identified glutarylated peptides increases, it becomes imperative to investigate substrate motifs to enhance the study of protein glutarylation. We carried out a bioinformatics investigation of glutarylation sites based on amino acid composition using a public database containing information on 430 non-homologous glutarylation sites. RESULTS: The TwoSampleLogo analysis indicates that positively charged and polar amino acids surrounding glutarylated sites may be associated with the specificity in substrate site of protein glutarylation. Additionally, the chi-squared test was utilized to explore the intrinsic interdependence between two positions around glutarylation sites. Further, maximal dependence decomposition (MDD), which consists of partitioning a large-scale dataset into subgroups with statistically significant amino acid conservation, was used to capture motif signatures of glutarylation sites. We considered single features, such as amino acid composition (AAC), amino acid pair composition (AAPC), and composition of k-spaced amino acid pairs (CKSAAP), as well as the effectiveness of incorporating MDD-identified substrate motifs into an integrated prediction model. Evaluation by five-fold cross-validation showed that AAC was most effective in discriminating between glutarylation and non-glutarylation sites, according to support vector machine (SVM). CONCLUSIONS: The SVM model integrating MDD-identified substrate motifs performed well, with a sensitivity of 0.677, a specificity of 0.619, an accuracy of 0.638, and a Matthews Correlation Coefficient (MCC) value of 0.28. Using an independent testing dataset (46 glutarylated and 92 non-glutarylated sites) obtained from the literature, we demonstrated that the integrated SVM model could improve the predictive performance effectively, yielding a balanced sensitivity and specificity of 0.652 and 0.739, respectively. This integrated SVM model has been implemented as a web-based system (MDDGlutar), which is now freely available at http://csb.cse.yzu.edu.tw/MDDGlutar/ .

Design of vessel ligation simulator for deliberate practice.

BACKGROUND: Surgical residents develop technical skills at variable rates, often based on random chance of cases encountered. One such skill is tying secure knots without exerting excessive force. This study describes the design of a simulator using a force sensor to measure instantaneous forces exerted on a blood vessel analog during vessel ligation and the development of expert-derived performance goals. MATERIALS AND METHODS: Vessel ligations were performed on Silastic tubing at an offset from a Vernier Force Sensor. Nine experts (surgical faculty and senior residents) and 10 novices (junior residents) were recruited to each perform 10 vessel ligations (two square knots each) with two-handed and one-handed techniques. Internal consistency for the series of vessel ligations was tested with Cronbach alpha. Maximum forces exerted by novices and experts were compared using Student t-test. RESULTS: Internal consistency across the 10 ligations on the simulator was excellent (Cronbach alpha = 0.91). The expert group on average exerted a significantly lower maximum force when compared with novices while performing two-handed (0.76 ± 0.39 N versus 1.12 ± 0.49 N, P < 0.01) and one-handed (0.84 ± 0.32 N versus 1.36 ± 0.44 N, P < 0.01) vessel ligations. CONCLUSIONS: Although the expert group performed vessel ligations with significantly lower peak force than the novice group, there were novices who performed at the expert level. This is consistent with the conceptual framework of milestones and suggests that the skill of gentle knot-tying can be measured and develops at different chronologic levels of training in different individuals. This simulator can be used as part of a deliberate practice curriculum with instantaneous visual feedback.

Incorporating significant amino acid pairs and protein domains to predict RNA splicing-related proteins with functional roles.

Machinery of pre-mRNA splicing is carried out through the interaction of RNA sequence elements and a variety of RNA splicing-related proteins (SRPs) (e.g. spliceosome and splicing factors). Alternative splicing, which is an important post-transcriptional regulation in eukaryotes, gives rise to multiple mature mRNA isoforms, which encodes proteins with functional diversities. However, the regulation of RNA splicing is not yet fully elucidated, partly because SRPs have not yet been exhaustively identified and the experimental identification is labor-intensive. Therefore, we are motivated to design a new method for identifying SRPs with their functional roles in the regulation of RNA splicing. The experimentally verified SRPs were manually curated from research articles. According to the functional annotation of Splicing Related Gene Database, the collected SRPs were further categorized into four functional groups including small nuclear Ribonucleoprotein, Splicing Factor, Splicing Regulation Factor and Novel Spliceosome Protein. The composition of amino acid pairs indicates that there are remarkable differences among four functional groups of SRPs. Then, support vector machines (SVMs) were utilized to learn the predictive models for identifying SRPs as well as their functional roles. The cross-validation evaluation presents that the SVM models trained with significant amino acid pairs and functional domains could provide a better predictive performance. In addition, the independent testing demonstrates that the proposed method could accurately identify SRPs in mammals/plants as well as effectively distinguish between SRPs and RNA-binding proteins. This investigation provides a practical means to identifying potential SRPs and a perspective for exploring the regulation of RNA splicing.

Updates in Bariatric Surgery.

Bariatric surgery is currently the most effective long-term treatment for morbid obesity as well as type-2 diabetes mellitus. The field of metabolic and bariatric surgery has seen tremendous growth over the past decade with dramatically reduced risks. This article aims to provide an update on bariatric surgery, highlighting the latest outcomes, improvements, and challenges in the field. Recently, the American Society of Metabolic and Bariatric Surgery (ASMBS) and the International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) released a major update to the indications for bariatric surgery at BMI ≥35 kg/m2 regardless of co-morbidities and 30-34.9 kg/m2 with obesity-related comorbidities. Sleeve gastrectomy has emerged as the most popular bariatric procedure in the last 10 years with its remarkable efficacy and safety profile. The implementation of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) and Enhanced Recovery After Surgery (ERAS) protocols have significantly improved the quality of care for all bariatric patients. The recent introduction and FDA approval of Glucagon-Like Peptide-1 (GLP-1) agonists for chronic obesity has garnered significant media coverage and popularity, but no guidelines exist regarding its use in relation to bariatric surgery. This update underscores the need for tailored approaches, ongoing research, and the integration of evidence-based medicine and innovations to enhance patient care.

Comparative analysis of readmission rates and outcomes: Sleeve gastrectomy with versus without Nissen fundoplication using a National Database.

Laparoscopic sleeve gastrectomy (LSG) is the most frequently performed bariatric procedure. To study the safety of LSG done with Nissen Fundoplication (NF) in patients affected by obesity and GERD and assess the complication rate. A retrospective cohort study using the Nationwide Readmissions Database from 2016 to 2019. A total of 236111 patients underwent LSG with and without NF. A matched cohort of 1096 without NF and 548 with NF was obtained. The median age of patients was 47 years old. Median length of hospital stay was higher in the LSG with NF group. Median total charge was higher in the LSG with NF group. There was no statistically significant difference in 30-day readmission rates in patients with obesity and GERD who received LSG with NF compared to those who received LSG alone. Complications after both procedures were low, which highlights the safety of both procedures.

A Study of Disease Prognosis in Lung Adenocarcinoma Using Single-Cell Decomposition and Immune Signature Analysis.

Background: The development of tumors is a highly complex process that entails numerous interactions and intricate relationships between the host immune system and cancer cells. It has been demonstrated in studies that the treatment response of patients can be correlated with the tumor microenvironment (TME). Consequently, the examination of diverse immune profiles within the TME can facilitate the elucidation of tumor development and the development of advantageous models for diagnoses and prognoses. Methods: In this study, we utilized a single-cell decomposition method to analyze the relationships between cell proportions and immune signatures in lung adenocarcinoma (LUAD) patients. Results: Our findings indicate that specific immune cell populations and immune signatures are significantly associated with patient prognosis. By identifying poor prognosis signatures (PPS), we reveal the critical role of immune profiles and cellular composition in disease outcomes, emphasizing their diagnostic potential for predicting patient prognosis. Conclusions: This study highlights the importance of immune signatures and cellular composition, which may serve as valuable biomarkers for disease prognosis in LUAD patients.

An ensemble deep learning model for predicting minimum inhibitory concentrations of antimicrobial peptides against pathogenic bacteria.

The rise of antibiotic resistance necessitates effective alternative therapies. Antimicrobial peptides (AMPs) are promising due to their broad inhibitory effects. This study focuses on predicting the minimum inhibitory concentration (MIC) of AMPs against whom-priority pathogens: Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 25922, and Pseudomonas aeruginosa ATCC 27853. We developed a comprehensive regression model integrating AMP sequence-based and genomic features. Using eight AI-based architectures, including deep learning with protein language model embeddings, we created an ensemble model combining bi-directional long short-term memory (BiLSTM), convolutional neural network (CNN), and multi-branch model (MBM). The ensemble model showed superior performance with Pearson correlation coefficients of 0.756, 0.781, and 0.802 for the bacterial strains, demonstrating its accuracy in predicting MIC values. This work sets a foundation for future studies to enhance model performance and advance AMP applications in combating antibiotic resistance.

An enhanced computational platform for investigating the roles of regulatory RNA and for identifying functional RNA motifs.

BACKGROUND: Functional RNA molecules participate in numerous biological processes, ranging from gene regulation to protein synthesis. Analysis of functional RNA motifs and elements in RNA sequences can obtain useful information for deciphering RNA regulatory mechanisms. Our previous work, RegRNA, is widely used in the identification of regulatory motifs, and this work extends it by incorporating more comprehensive and updated data sources and analytical approaches into a new platform. METHODS AND RESULTS: An integrated web-based system, RegRNA 2.0, has been developed for comprehensively identifying the functional RNA motifs and sites in an input RNA sequence. Numerous data sources and analytical approaches are integrated, and several types of functional RNA motifs and sites can be identified by RegRNA 2.0: (i) splicing donor/acceptor sites; (ii) splicing regulatory motifs; (iii) polyadenylation sites; (iv) ribosome binding sites; (v) rho-independent terminator; (vi) motifs in mRNA 5'-untranslated region (5'UTR) and 3'UTR; (vii) AU-rich elements; (viii) C-to-U editing sites; (ix) riboswitches; (x) RNA cis-regulatory elements; (xi) transcriptional regulatory motifs; (xii) user-defined motifs; (xiii) similar functional RNA sequences; (xiv) microRNA target sites; (xv) non-coding RNA hybridization sites; (xvi) long stems; (xvii) open reading frames; (xviii) related information of an RNA sequence. User can submit an RNA sequence and obtain the predictive results through RegRNA 2.0 web page. CONCLUSIONS: RegRNA 2.0 is an easy to use web server for identifying regulatory RNA motifs and functional sites. Through its integrated user-friendly interface, user is capable of using various analytical approaches and observing results with graphical visualization conveniently. RegRNA 2.0 is now available at http://regrna2.mbc.nctu.edu.tw.

RegPhos: a system to explore the protein kinase-substrate phosphorylation network in humans.

Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in intracellular signal transduction. With the increasing number of experimental phosphorylation sites that has been identified by mass spectrometry-based proteomics, the desire to explore the networks of protein kinases and substrates is motivated. Manning et al. have identified 518 human kinase genes, which provide a starting point for comprehensive analysis of protein phosphorylation networks. In this study, a knowledgebase is developed to integrate experimentally verified protein phosphorylation data and protein-protein interaction data for constructing the protein kinase-substrate phosphorylation networks in human. A total of 21,110 experimental verified phosphorylation sites within 5092 human proteins are collected. However, only 4138 phosphorylation sites (∼20%) have the annotation of catalytic kinases from public domain. In order to fully investigate how protein kinases regulate the intracellular processes, a published kinase-specific phosphorylation site prediction tool, named KinasePhos is incorporated for assigning the potential kinase. The web-based system, RegPhos, can let users input a group of human proteins; consequently, the phosphorylation network associated with the protein subcellular localization can be explored. Additionally, time-coursed microarray expression data is subsequently used to represent the degree of similarity in the expression profiles of network members. A case study demonstrates that the proposed scheme not only identify the correct network of insulin signaling but also detect a novel signaling pathway that may cross-talk with insulin signaling network. This effective system is now freely available at http://RegPhos.mbc.nctu.edu.tw.

Predicting readmission after bariatric surgery using machine learning.

BACKGROUND: While bariatric surgery is an effective method for achieving long-term weight loss, postoperative readmissions are associated with negative clinical outcomes and significant costs. OBJECTIVES: We aimed to use machine learning (ML) algorithms to predict readmissions and compare results to logistic regression. SETTING: Hospitals participating in the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program, United States. METHODS: Patients who underwent sleeve gastrectomy (SG), Roux-en-Y gastric bypass (RYGB), and biliopancreatic diversion with duodenal switch between 2016 and 2020 were selected from the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) database. Patient variables reported by the MBSAQIP database were analyzed by ML algorithms random forest (RF), gradient boosting (XGB), and deep neural networks (NN), and the results of the predictive models were compared to logistic regression using area under the receiver operating characteristic curve (AUROC). RESULTS: Our study included 863,348 patients, of which 39,068 (4.52%) were readmitted. AUROC scores were XGB .785 (95% CI .784-.786), RF .785 (95% CI .784-.785), and NN .754 (95% CI .753-.754), compared with .62 (95% CI .62-.621) for logistic regression (LR) (P < .001). The sensitivity and specificity for XGB, the best performing model, were 73.81% and 70%, compared with 52.94% and 70% for logistic regression. The most important variables were intervention or reoperation prior to discharge, unplanned ICU admission, initial procedure, and the intraoperative transfusion. CONCLUSIONS: ML demonstrates significant advantages over logistic regression when predicting 30-day readmission following bariatric surgery. With external validation, models could identify the best candidates for early discharge or targeted postdischarge resources.

Comparison of Robotic, Laparoscopic, and Open Unilateral Repair of Non-recurrent Inguinal Hernia.

BACKGROUND: There is a paucity of data comparing open, robotic, and laparoscopic approaches on unilateral, non-recurrent inguinal hernias. Our study presents a large, retrospective triple-arm outcome analysis between robotic, laparoscopic, and open unilateral, non-recurrent inguinal hernia repairs at a single institution. METHODS: 706 patients who underwent elective, non-recurrent inguinal hernia repair performed by 8 general surgeons at a single institution from 2016 to 2019 were reviewed retrospectively. Patient baseline characteristics, operative times, resident involvement, and postoperative outcomes were analyzed for all repair types. A cost analysis of the different procedures was performed. RESULTS: There were 305 laparoscopic repairs, 207 robotic repairs, and 194 open repairs. Open and laparoscopic repairs were performed on patients who were older (p =< .001) and with a higher Charlson Comorbidity Index (p =< .001). Patient BMI was higher in minimally invasive repair than open repair (P = .021). There were no significant differences in complication rates on pairwise analysis. Robotic and open repairs had significantly longer operative times than laparoscopic repairs (P < .001). There was less resident involvement in robotic repair than with the other approaches (P < .001). Resident involvement was associated with shorter OR times (P = .001) and no significant difference in postoperative complications. There was a trend over the study period toward faster operative times and more robotic repair. Robotic repair is the most expensive repair, followed by laparoscopic and open repairs. CONCLUSION: All 3 repair techniques can be performed without significant differences in outcomes. The technique utilized should be based on surgeon preference and patient characteristics.

Assessing Non-Specific Neck Pain through Pose Estimation from Images Based on Ensemble Learning.

BACKGROUND: Mobile phones, laptops, and computers have become an indispensable part of our lives in recent years. Workers may have an incorrect posture when using a computer for a prolonged period of time. Using these products with an incorrect posture can lead to neck pain. However, there are limited data on postures in real-life situations. METHODS: In this study, we used a common camera to record images of subjects carrying out three different tasks (a typing task, a gaming task, and a video-watching task) on a computer. Different artificial intelligence (AI)-based pose estimation approaches were applied to analyze the head's yaw, pitch, and roll and coordinate information of the eyes, nose, neck, and shoulders in the images. We used machine learning models such as random forest, XGBoost, logistic regression, and ensemble learning to build a model to predict whether a subject had neck pain by analyzing their posture when using the computer. RESULTS: After feature selection and adjustment of the predictive models, nested cross-validation was applied to evaluate the models and fine-tune the hyperparameters. Finally, the ensemble learning approach was utilized to construct a model via bagging, which achieved a performance with 87% accuracy, 92% precision, 80.3% recall, 95.5% specificity, and an AUROC of 0.878. CONCLUSIONS: We developed a predictive model for the identification of non-specific neck pain using 2D video images without the need for costly devices, advanced environment settings, or extra sensors. This method could provide an effective way for clinically evaluating poor posture during real-world computer usage scenarios.

Corrigendum: Systolic blood pressure as the mediator of the effect of early menarche on the risk of coronary artery disease: A Mendelian randomization study.

[This corrects the article DOI: 10.3389/fcvm.2022.1023355.].

Hypertension as a Novel Link for Shared Heritability in Age at Menarche and Cardiometabolic Traits.

CONTEXT: Extremely early age at menarche, also called precocious puberty, has been associated with various cardiometabolic traits, but their shared heritability remains unclear. OBJECTIVES: This work aimed to identify new shared genetic variants and their pathways for age at menarche and cardiometabolic traits and to investigate the influence of central precocious puberty on childhood cardiometabolic traits. METHODS: Using the conjunction false discovery rate method, this study analyzed genome-wide association study data from the menarche-cardiometabolic traits among 59 655 females of Taiwanese ancestry and systemically investigated pleiotropy between age at menarche and cardiometabolic traits. To support the novel hypertension link, we used the Taiwan Puberty Longitudinal Study (TPLS) to investigate the influence of precocious puberty on childhood cardiometabolic traits. RESULTS: We discovered 27 novel loci, with an overlap between age at menarche and cardiometabolic traits, including body fat and blood pressure. Among the novel genes discovered, SEC16B, CSK, CYP1A1, FTO, and USB1 are within a protein interaction network with known cardiometabolic genes, including traits for obesity and hypertension. These loci were confirmed through demonstration of significant changes in the methylation or expression levels of neighboring genes. Moreover, the TPLS provided evidence regarding a 2-fold higher risk of early-onset hypertension that occurred in girls with central precocious puberty. CONCLUSION: Our study highlights the usefulness of cross-trait analyses for identifying shared etiology between age at menarche and cardiometabolic traits, especially early-onset hypertension. The menarche-related loci may contribute to early-onset hypertension through endocrinological pathways.

GPMiner: an integrated system for mining combinatorial cis-regulatory elements in mammalian gene group.

BACKGROUND: Sequence features in promoter regions are involved in regulating gene transcription initiation. Although numerous computational methods have been developed for predicting transcriptional start sites (TSSs) or transcription factor (TF) binding sites (TFBSs), they lack annotations for do not consider some important regulatory features such as CpG islands, tandem repeats, the TATA box, CCAAT box, GC box, over-represented oligonucleotides, DNA stability, and GC content. Additionally, the combinatorial interaction of TFs regulates the gene group that is associated with same expression pattern. To investigate gene transcriptional regulation, an integrated system that annotates regulatory features in a promoter sequence and detects co-regulation of TFs in a group of genes is needed. RESULTS: This work identifies TSSs and regulatory features in a promoter sequence, and recognizes co-occurrence of cis-regulatory elements in co-expressed genes using a novel system. Three well-known TSS prediction tools are incorporated with orthologous conserved features, such as CpG islands, nucleotide composition, over-represented hexamer nucleotides, and DNA stability, to construct the novel Gene Promoter Miner (GPMiner) using a support vector machine (SVM). According to five-fold cross-validation results, the predictive sensitivity and specificity are both roughly 80%. The proposed system allows users to input a group of gene names/symbols, enabling the co-occurrence of TFBSs to be determined. Additionally, an input sequence can also be analyzed for homogeneity of experimental mammalian promoter sequences, and conserved regulatory features between homologous promoters can be observed through cross-species analysis. After identifying promoter regions, regulatory features are visualized graphically to facilitate gene promoter observations. CONCLUSIONS: The GPMiner, which has a user-friendly input/output interface, has numerous benefits in analyzing human and mouse promoters. The proposed system is freely available at http://GPMiner.mbc.nctu.edu.tw/.