scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.

Previous studies on enhancers and their target genes were largely based on bulk samples that represent 'average' regulatory activities from a large population of millions of cells, masking the heterogeneity and important effects from the sub-populations. In recent years, single-cell sequencing technology has enabled the profiling of open chromatin accessibility at the single-cell level (scATAC-seq), which can be used to annotate the enhancers and promoters in specific cell types. A comprehensive resource is highly desirable for exploring how the enhancers regulate the target genes at the single-cell level. Hence, we designed a single-cell database scEnhancer (http://enhanceratlas.net/scenhancer/), covering 14 527 776 enhancers and 63 658 600 enhancer-gene interactions from 1 196 906 single cells across 775 tissue/cell types in three species. An unsupervised learning method was employed to sort and combine tens or hundreds of single cells in each tissue/cell type to obtain the consensus enhancers. In addition, we utilized a cis-regulatory network algorithm to identify the enhancer-gene connections. Finally, we provided a user-friendly platform with seven useful modules to search, visualize, and browse the enhancers/genes. This database will facilitate the research community towards a functional analysis of enhancers at the single-cell level.

EnhancerAtlas 2.0: an updated resource with enhancer annotation in 586 tissue/cell types across nine species.

Enhancers are distal cis-regulatory elements that activate the transcription of their target genes. They regulate a wide range of important biological functions and processes, including embryogenesis, development, and homeostasis. As more and more large-scale technologies were developed for enhancer identification, a comprehensive database is highly desirable for enhancer annotation based on various genome-wide profiling datasets across different species. Here, we present an updated database EnhancerAtlas 2.0 (http://www.enhanceratlas.org/indexv2.php), covering 586 tissue/cell types that include a large number of normal tissues, cancer cell lines, and cells at different development stages across nine species. Overall, the database contains 13 494 603 enhancers, which were obtained from 16 055 datasets using 12 high-throughput experiment methods (e.g. H3K4me1/H3K27ac, DNase-seq/ATAC-seq, P300, POLR2A, CAGE, ChIA-PET, GRO-seq, STARR-seq and MPRA). The updated version is a huge expansion of the first version, which only contains the enhancers in human cells. In addition, we predicted enhancer-target gene relationships in human, mouse and fly. Finally, the users can search enhancers and enhancer-target gene relationships through five user-friendly, interactive modules. We believe the new annotation of enhancers in EnhancerAtlas 2.0 will facilitate users to perform useful functional analysis of enhancers in various genomes.

EAGLE: An algorithm that utilizes a small number of genomic features to predict tissue/cell type-specific enhancer-gene interactions.

Long-range regulation by distal enhancers is crucial for many biological processes. The existing methods for enhancer-target gene prediction often require many genomic features. This makes them difficult to be applied to many cell types, in which the relevant datasets are not always available. Here, we design a tool EAGLE, an enhancer and gene learning ensemble method for identification of Enhancer-Gene (EG) interactions. Unlike existing tools, EAGLE used only six features derived from the genomic features of enhancers and gene expression datasets. Cross-validation revealed that EAGLE outperformed other existing methods. Enrichment analyses on special transcriptional factors, epigenetic modifications, and eQTLs demonstrated that EAGLE could distinguish the interacting pairs from non- interacting ones. Finally, EAGLE was applied to mouse and human genomes and identified 7,680,203 and 7,437,255 EG interactions involving 31,375 and 43,724 genes, 138,547 and 177,062 enhancers across 89 and 110 tissue/cell types in mouse and human, respectively. The obtained interactions are accessible through an interactive database enhanceratlas.org. The EAGLE method is available at https://github.com/EvansGao/EAGLE and the predicted datasets are available in http://www.enhanceratlas.org/.

EnhancerAtlas: a resource for enhancer annotation and analysis in 105 human cell/tissue types.

MOTIVATION: Multiple high-throughput approaches have recently been developed and allowed the discovery of enhancers on a genome scale in a single experiment. However, the datasets generated from these approaches are not fully utilized by the research community due to technical challenges such as lack of consensus enhancer annotation and integrative analytic tools. RESULTS: We developed an interactive database, EnhancerAtlas, which contains an atlas of 2,534,123 enhancers for 105 cell/tissue types. A consensus enhancer annotation was obtained for each cell by summation of independent experimental datasets with the relative weights derived from a cross-validation approach. Moreover, EnhancerAtlas provides a set of useful analytic tools that allow users to query and compare enhancers in a particular genomic region or associated with a gene of interest, and assign enhancers and their target genes from a custom dataset. AVAILABILITY AND IMPLEMENTATION: The database with analytic tools is available at http://www.enhanceratlas.org/ CONTACT: jiang.qian@jhmi.edu or tank1@email.chop.eduSupplementary information: Supplementary data are available at Bioinformatics online.

EKPD: a hierarchical database of eukaryotic protein kinases and protein phosphatases.

We present here EKPD (http://ekpd.biocuckoo.org), a hierarchical database of eukaryotic protein kinases (PKs) and protein phosphatases (PPs), the key molecules responsible for the reversible phosphorylation of proteins that are involved in almost all aspects of biological processes. As extensive experimental and computational efforts have been carried out to identify PKs and PPs, an integrative resource with detailed classification and annotation information would be of great value for both experimentalists and computational biologists. In this work, we first collected 1855 PKs and 347 PPs from the scientific literature and various public databases. Based on previously established rationales, we classified all of the known PKs and PPs into a hierarchical structure with three levels, i.e. group, family and individual PK/PP. There are 10 groups with 149 families for the PKs and 10 groups with 33 families for the PPs. We constructed 139 and 27 Hidden Markov Model profiles for PK and PP families, respectively. Then we systematically characterized ∼50,000 PKs and >10,000 PPs in eukaryotes. In addition, >500 PKs and >400 PPs were computationally identified by ortholog search. Finally, the online service of the EKPD database was implemented in PHP + MySQL + JavaScript.

CPLM: a database of protein lysine modifications.

We reported an integrated database of Compendium of Protein Lysine Modifications (CPLM; http://cplm.biocuckoo.org) for protein lysine modifications (PLMs), which occur at active ε-amino groups of specific lysine residues in proteins and are critical for orchestrating various biological processes. The CPLM database was updated from our previously developed database of Compendium of Protein Lysine Acetylation (CPLA), which contained 7151 lysine acetylation sites in 3311 proteins. Here, we manually collected experimentally identified substrates and sites for 12 types of PLMs, including acetylation, ubiquitination, sumoylation, methylation, butyrylation, crotonylation, glycation, malonylation, phosphoglycerylation, propionylation, succinylation and pupylation. In total, the CPLM database contained 203,972 modification events on 189,919 modified lysines in 45,748 proteins for 122 species. With the dataset, we totally identified 76 types of co-occurrences of various PLMs on the same lysine residues, and the most abundant PLM crosstalk is between acetylation and ubiquitination. Up to 53.5% of acetylation and 33.1% of ubiquitination events co-occur at 10 746 lysine sites. Thus, the various PLM crosstalks suggested that a considerable proportion of lysines were competitively and dynamically regulated in a complicated manner. Taken together, the CPLM database can serve as a useful resource for further research of PLMs.

UUCD: a family-based database of ubiquitin and ubiquitin-like conjugation.

In this work, we developed a family-based database of UUCD (http://uucd.biocuckoo.org) for ubiquitin and ubiquitin-like conjugation, which is one of the most important post-translational modifications responsible for regulating a variety of cellular processes, through a similar E1 (ubiquitin-activating enzyme)-E2 (ubiquitin-conjugating enzyme)-E3 (ubiquitin-protein ligase) enzyme thioester cascade. Although extensive experimental efforts have been taken, an integrative data resource is still not available. From the scientific literature, 26 E1s, 105 E2s, 1003 E3s and 148 deubiquitination enzymes (DUBs) were collected and classified into 1, 3, 19 and 7 families, respectively. To computationally characterize potential enzymes in eukaryotes, we constructed 1, 1, 15 and 6 hidden Markov model (HMM) profiles for E1s, E2s, E3s and DUBs at the family level, separately. Moreover, the ortholog searches were conducted for E3 and DUB families without HMM profiles. Then the UUCD database was developed with 738 E1s, 2937 E2s, 46 631 E3s and 6647 DUBs of 70 eukaryotic species. The detailed annotations and classifications were also provided. The online service of UUCD was implemented in PHP + MySQL + JavaScript + Perl.

Inflammatory Factor IL1α Induces Aberrant Astrocyte Proliferation in Spinal Cord Injury Through the Grin2c/Ca2+/CaMK2b Pathway.

Spinal cord injury (SCI) is one of the most devastating traumas, and the aberrant proliferation of astrocytes usually causes neurological deficits. However, the mechanism underlying astrocyte over-proliferation after SCI is unclear. Grin2c (glutamate ionotropic receptor type 2c) plays an essential role in cell proliferation. Our bioinformatic analysis indicated that Grin2c and Ca2+ transport functions were inhibited in astrocytes after SCI. Suppression of Grin2c stimulated astrocyte proliferation by inhibiting the Ca2+/calmodulin-dependent protein kinase 2b (CaMK2b) pathway in vitro. By screening different inflammatory factors, interleukin 1α (IL1α) was further found to inhibit Grin2c/Ca2+/CaMK2b and enhance astrocyte proliferation in an oxidative damage model. Blockade of IL1α using neutralizing antibody resulted in increased Grin2c expression and the inhibition of astrocyte proliferation post-SCI. Overall, this study suggests that IL1α promotes astrocyte proliferation by suppressing the Grin2c/Ca2+/CaMK2b pathway after SCI, revealing a novel pathological mechanism of astrocyte proliferation, and may provide potential targets for SCI repair.

CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations.

Biological databases serve as critical basics for modern research, and amid the dynamic landscape of biology, the COVID-19 database has emerged as an indispensable resource. The global outbreak of Covid-19, commencing in December 2019, necessitates comprehensive databases to unravel the intricate connections between this novel virus and cancer. Despite existing databases, a crucial need persists for a centralized and accessible method to acquire precise information within the research community. The main aim of the work is to develop a database which has all the COVID-19-related data available in just one click with auto global notifications. This gap is addressed by the meticulously designed COVID-19 Pandemic Database (CO-19 PDB 2.0), positioned as a comprehensive resource for researchers navigating the complexities of COVID-19 and cancer. Between December 2019 and June 2024, the CO-19 PDB 2.0 systematically collected and organized 120 datasets into six distinct categories, each catering to specific functionalities. These categories encompass a chemical structure database, a digital image database, a visualization tool database, a genomic database, a social science database, and a literature database. Functionalities range from image analysis and gene sequence information to data visualization and updates on environmental events. CO-19 PDB 2.0 has the option to choose either the search page for the database or the autonotification page, providing a seamless retrieval of information. The dedicated page introduces six predefined charts, providing insights into crucial criteria such as the number of cases and deaths', country-wise distribution, 'new cases and recovery', and rates of death and recovery. The global impact of COVID-19 on cancer patients has led to extensive collaboration among research institutions, producing numerous articles and computational studies published in international journals. A key feature of this initiative is auto daily notifications for standardized information updates. Users can easily navigate based on different categories or use a direct search option. The study offers up-to-date COVID-19 datasets and global statistics on COVID-19 and cancer, highlighting the top 10 cancers diagnosed in the USA in 2022. Breast and prostate cancers are the most common, representing 30% and 26% of new cases, respectively. The initiative also ensures the removal or replacement of dead links, providing a valuable resource for researchers, healthcare professionals, and individuals. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://www.co-19pdb.habdsk.org/. Database URL: https://www.co-19pdb.habdsk.org/.

RANKL/RANK signaling recruits Tregs via the CCL20-CCR6 pathway and promotes stemness and metastasis in colorectal cancer.

TNF receptor superfamily member 11a (TNFRSF11a, RANK) and its ligand TNF superfamily member 11 (TNFRSF11, RANKL) are overexpressed in many malignancies. However, the clinical importance of RANKL/RANK in colorectal cancer (CRC) is mainly unknown. We examined CRC samples and found that RANKL/RANK was elevated in CRC tissues compared with nearby normal tissues. A higher RANKL/RANK expression was associated with a worse survival rate. Furthermore, RANKL was mostly produced by regulatory T cells (Tregs), which were able to promote CRC advancement. Overexpression of RANK or addition of RANKL significantly increased the stemness and migration of CRC cells. Furthermore, RANKL/RANK signaling stimulated C-C motif chemokine ligand 20 (CCL20) production by CRC cells, leading to Treg recruitment and boosting tumor stemness and malignant progression. This recruitment process was accomplished by CCL20-CCR6 interaction, demonstrating a connection between CRC cells and immune cells. These findings suggest an important role of RANKL/RANK in CRC progression, offering a potential target for CRC prevention and therapy.

A computational approach to fighting type 1 diabetes by targeting 2C Coxsackie B virus protein with flavonoids.

Autoimmune diabetes, well-known as type 1 insulin-dependent diabetic mellitus (T1D). T1D is a prolonged condition marked by an inadequate supply of insulin. The lack is brought on by pancreatic cell death and results in hyperglycemia. The immune system, genetic predisposition, and environmental variables are just a few of the many elements that contribute significantly to the pathogenicity of T1D disease. In this study, we test flavonoids against Coxsackie virus protein to cope the type 1 diabetes. After protein target identification we perform molecular docking of flavonoids and selected target (1z8r). then performed the ADMET analysis and select the top compound the base of the docking score and the ADMET test analysis. Following that molecular dynamics simulation was performed up to 300 ns. Root means square deviation, root mean square fluctuation, secondary structure elements, and protein-ligand contacts were calculated as post-analysis of simulation. We further check the binding of the ligand with protein by performing MM-GBSA every 10 ns. Lead compound CID_5280445 was chosen as a possible medication based on analysis. The substance is non-toxic, meets the ADMET and BBB likeness requirements, and has the best interaction energy. This work will assist researchers in developing medicine and testing it as a treatment for Diabetes Mellitus Type 1 brought on by Coxsackie B4 viruses by giving them an understanding of chemicals against these viruses.

AVPCD: a plant-derived medicine database of antiviral phytochemicals for cancer, Covid-19, malaria and HIV.

Serious illnesses caused by viruses are becoming the world's most critical public health issues and lead millions of deaths each year in the world. Thousands of studies confirmed that the plant-derived medicines could play positive therapeutic effects on the patients with viral diseases. Since thousands of antiviral phytochemicals have been identified as lifesaving drugs in medical research, a comprehensive database is highly desirable to integrate the medicinal plants with their different medicinal properties. Therefore, we provided a friendly antiviral phytochemical database AVPCD covering 2537 antiviral phytochemicals from 383 medicinal compounds and 319 different families with annotation of their scientific, family and common names, along with the parts used, disease information, active compounds, links of relevant articles for COVID-19, cancer, HIV and malaria. Furthermore, each compound in AVPCD was annotated with its 2D and 3D structure, molecular formula, molecular weight, isomeric SMILES, InChI, InChI Key and IUPAC name and 21 other properties. Each compound was annotated with more than 20 properties. Specifically, a scoring method was designed to measure the confidence of each phytochemical for the viral diseases. In addition, we constructed a user-friendly platform with several powerful modules for searching and browsing the details of all phytochemicals. We believe this database will facilitate global researchers, drug developers and health practitioners in obtaining useful information against viral diseases.

Jagged1 contained in MSC-derived small extracellular vesicles promotes squamous differentiation of cervical cancer by activating NOTCH pathway.

PURPOSE: Cervical cancer is the fourth most common cancer in women and poses a major threat to women's health, urgently requiring new treatment methods. METHODS: This study first successfully extracted and identified small extracellular vesicles secreted by human umbilical cord-derived mesenchymal stem cells. We studied the effects of MSC-sEV on the squamous differentiation levels of cervical cancer CaSki cells in vitro, and explored the effects of MSC-sEV on the NOTCH pathway, the growth, proliferation, migration abilities and squamous differentiation levels of cervical cancer cells. The roles of MSC-sEV were also verified in human keratinocyte HaCaT cells. RESULTS: The results showed that Jagged1 protein on MSC-sEV can bind to NOTCH1 on cervical cancer cells, activate NOTCH signaling, and promote squamous differentiation levels in CaSki cells, thus inhibiting the growth, proliferation and migration abilities of CaSki cells. MSC-sEV can also activate the NOTCH pathway in HaCaT cells, but promote the viability of HaCaT cells. CONCLUSION: MSC-sEV can activate the NOTCH pathway to promote squamous differentiation of CaSki cells and inhibit the growth proliferation and migration abilities of CaSki cells which may be a new mechanism for cervical cancer treatment.

miR-221/222 induce instability of p53 By downregulating deubiquitinase YOD1 in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a hematological malignancy characterized by the impaired differentiation and uncontrolled proliferation of myeloid blasts. Tumor suppressor p53 is often downregulated in AML cells via ubiquitination-mediated degradation. While the role of E3 ligase MDM2 in p53 ubiquitination is well-accepted, little is known about the involvement of deubiquitinases (DUBs). Herein, we found that the expression of YOD1, among several DUBs, is substantially reduced in blood cells from AML patients. We identified that YOD1 deubiqutinated and stabilized p53 through interaction via N-terminus of p53 and OTU domain of YOD1. In addition, expression levels of YOD1 were suppressed by elevated miR-221/222 in AML cells through binding to the 3' untranslated region of YOD1, as verified by reporter gene assays. Treatment of cells with miR-221/222 mimics and inhibitors yielded the expected effects on YOD1 expressions, in agreement with the negative correlation observed between the expression levels of miR-221/222 and YOD1 in AML cells. Finally, overexpression of YOD1 stabilized p53, upregulated pro-apoptotic p53 downstream genes, and increased the sensitivity of AML cells to FLT3 inhibitors remarkably. Collectively, our study identified a pathway connecting miR-221/222, YOD1, and p53 in AML. Targeting miR-221/222 and stimulating YOD1 activity may improve the therapeutic effects of FLT3 inhibitors in patients with AML.

Discovery and characterization of cross-reactive intrahepatic antibodies in severe alcoholic hepatitis.

The pathogenesis of antibodies in severe alcoholic hepatitis (SAH) remains unknown. We sought to determine if there was antibody deposition in SAH livers and whether antibodies extracted from SAH livers were cross-reactive against both bacterial antigens and human proteins. We analyzed immunoglobulins (Ig) in explanted livers from SAH patients (n=45) undergoing liver transplantation and tissue from corresponding healthy donors (HD, n=10) and found massive deposition of IgG and IgA isotype antibodies associated with complement fragment C3d and C4d staining in ballooned hepatocytes in SAH livers. Ig extracted from SAH livers, but not patient serum exhibited hepatocyte killing efficacy in an antibody-dependent cell-mediated cytotoxicity (ADCC) assay. Employing human proteome arrays, we profiled the antibodies extracted from explanted SAH, alcoholic cirrhosis (AC), nonalcoholic steatohepatitis (NASH), primary biliary cholangitis (PBC), autoimmune hepatitis (AIH), hepatitis B virus (HBV), hepatitis C virus (HCV) and HD livers and found that antibodies of IgG and IgA isotypes were highly accumulated in SAH and recognized a unique set of human proteins as autoantigens. The use of an E. coli K12 proteome array revealed the presence of unique anti- E. coli antibodies in SAH, AC or PBC livers. Further, both Ig and E. coli captured Ig from SAH livers recognized common autoantigens enriched in several cellular components including cytosol and cytoplasm (IgG and IgA), nucleus, mitochondrion and focal adhesion (IgG). Except IgM from PBC livers, no common autoantigen was recognized by Ig and E. coli captured Ig from AC, HBV, HCV, NASH or AIH suggesting no cross-reacting anti- E. coli autoantibodies. The presence of cross-reacting anti-bacterial IgG and IgA autoantibodies in the liver may participate in the pathogenesis of SAH.

Discovery and characterization of cross-reactive intrahepatic antibodies in severe alcoholic hepatitis.

The pathogenesis of antibodies in severe alcoholic hepatitis (SAH) remains unknown. We analyzed immunoglobulins (Ig) in explanted livers from SAH patients (n=45) undergoing liver transplantation and tissues from corresponding healthy donors (HD, n=10) and found massive deposition of IgG and IgA isotype antibodies associated with complement fragment C3d and C4d staining in ballooned hepatocytes in SAH livers. Ig extracted from SAH livers, but not patient serum exhibited hepatocyte killing efficacy. Employing human and Escherichia coli K12 proteome arrays, we profiled the antibodies extracted from explanted SAH, livers with other diseases, and HD livers. Compared with their counterparts extracted from livers with other diseases and HD, antibodies of IgG and IgA isotypes were highly accumulated in SAH and recognized a unique set of human proteins and E. coli antigens. Further, both Ig- and E. coli-captured Ig from SAH livers recognized common autoantigens enriched in several cellular components including cytosol and cytoplasm (IgG and IgA), nucleus, mitochondrion, and focal adhesion (IgG). Except IgM from primary biliary cholangitis livers, no common autoantigen was recognized by Ig- and E. coli-captured Ig from livers with other diseases. These findings demonstrate the presence of cross-reacting anti-bacterial IgG and IgA autoantibodies in SAH livers.

DBHR: a collection of databases relevant to human research.

BACKGROUND: The achievement of the human genome project provides a basis for the systematic study of the human genome from evolutionary history to disease-specific medicine. With the explosive growth of biological data, a growing number of biological databases are being established to support human-related research. OBJECTIVE: The main objective of our study is to store, organize and share data in a structured and searchable manner. In short, we have planned the future development of new features in the database research area. MATERIALS & METHODS: In total, we collected and integrated 680 human databases from scientific published work. Multiple options are presented for accessing the data, while original links and short descriptions are also presented for each database. RESULTS & DISCUSSION: We have provided the latest collection of human research databases on a single platform with six categories: DNA database, RNA database, protein database, expression database, pathway database and disease database. CONCLUSION: Taken together, our database will be useful for further human research study and will be modified over time. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://habdsk.org/database.php.

The Cancer Research Database (CRDB): Integrated Platform to Gain Statistical Insight Into the Correlation Between Cancer and COVID-19.

BACKGROUND: The advancement of cancer research has been facilitated through freely available cancer literature, databases, and tools. The age of genomics and big data has given rise to the need for cooperation and data sharing in order to make efficient use of this new information in the COVID-19 pandemic. Although there are many databases for cancer research, their access is not easy owing to different ways of processing and managing the data. There is an absence of a unified platform to manage all of them in a transparent and more comprehensible way. OBJECTIVE: In this study, an improved integrated cancer research database and platform is provided to facilitate a deeper statistical insight into the correlation between cancer and the COVID-19 pandemic, unifying the collection of almost all previous published cancer databases and defining a model web database for cancer research, and scoring databases on the basis of the variety types of cancer, sample size, completeness of omics results, and user interface. METHODS: Databases examined and integrated include the Data Portal database, Genomic database, Proteomic database, Expression database, Gene database, and Mutation database; and it is expected that this launch will sort, save, advance the understanding and encourage the use of these resources in the cancer research environment. RESULTS: To make it easy to search valuable information, 85 cancer databases are provided in the form of a table, and a database of databases named the Cancer Research Database (CRDB) has been built and presented herein. Furthermore, the CRDB has been herein equipped with unique navigation tools in order to be explored by three methods; that is, any single database can be browsed by typing the name in the given search bar, while all categories can be browsed by clicking on the name of the category or image expression icon, thus serving as a facility that could provide all the category databases on a single click. CONCLUSIONS: The computational platform (PHP, HTML, CSS, and MySQL) used to build CRDB for the cancer scientific community can be freely investigated and browsed on the internet and is planned to be updated in a timely manner. In addition, based on the proposed platform, the status and diagnoses statistics of cancer during the COVID-19 pandemic have been thoroughly investigated herein using CRDB, thus providing an easy-to-manage, understandable framework that mines knowledge for future researchers.

Association of metabolic syndrome and the risk of bladder cancer: A prospective cohort study.

Background: Metabolic syndrome (MetS) and its components have been shown as risk factors for several solid cancers. However, current epidemiological evidence about the relevance of MetS and bladder cancer risk was limited. Methods: We conducted a prospective cohort study of 476,986 participants with undiagnosed bladder cancer based on the UK Biobank. MetS was defined as the presence of at least three of the five selected indicators: hypertension, central obesity, raised triglyceride, reduced HDL-cholesterol, and raised fasting plasma glucose. Bladder cancer has been identified through contact with the British Cancer Registry (median follow-up time: 6.6 years). We assessed hazard ratio (HR) and 95% confidence interval (CI) through Cox proportional hazard regression after adjusting for demographic and lifestyle factors. Non-linear associations for individual MetS components were assessed by the restricted cubic spline method. Results: During a follow-up of 3,112,566 person-years, 487 cases of bladder cancer were ascertained. MetS (HR = 1.32, 95% CI = 1.08-1.61), central obesity (HR = 1.39, 95% CI = 1.15-1.68), dyslipidemia for HDL cholesterol (HR = 1.31, 95% CI = 1.04-1.66), and hyperglycemia (HR = 1.44, 95% CI = 1.16-1.79) were associated with elevated risk of bladder cancer. Bladder cancer risk increased with the number of MetS components. In stratified analyses, MetS showed similar effects in bladder cancer independently with sex, age, cigarette and alcohol use, physical activity, and dietary factors. Higher waist circumference, BMI, fasting blood glucose, and glycosylated hemoglobin were independently associated with increased risk of bladder cancer, with no evidence against non-linearity. Conclusion: MetS might be an independent risk factor for bladder cancer. Our findings highlighted the importance of individualized management of MetS components for preventing bladder cancer.

Factors Associated With a Patient's Decision to Select a Cost-effective vs the Most Effective Therapy for Their Own Eye Disease.

Importance: Ten percent of the Medicare Part B budget is spent on aflibercept, used to treat a myriad of ocular neovascular diseases. A substantial portion of these costs can be attributed to a few hundred ophthalmologists, raising concerns regarding the influence of pharmaceutical companies on the choice of medication by a relatively small group of clinicians. One approach to protect patients' health care interests is to include them in deliberations on the choice of therapy for their eye disease. Objective: To examine factors associated with patients' choice between an effective and less expensive off-label drug or a more effective, but also more expensive, US Food and Drug Administration (FDA)-approved drug. Design, Setting, and Participants: This retrospective cohort analysis used data from the satellite office of a tertiary referral center from August 2, 2013, to April 9, 2018. Insured patients initiating treatment with anti-vascular endothelial growth factor were included in the analysis. Data were analyzed from March 26, 2018, to June 10, 2020. Interventions: Patients were asked to choose between bevacizumab (approximately $100 per dose), a chemotherapy that is effective, but not FDA approved, for the treatment of ocular vascular disease, or aflibercept (approximately $2000 per dose), an FDA-approved drug for ocular vascular disease that may be more effective than bevacizumab in some patients. Independent of this choice, patients were separately asked by a study coordinator to participate in an invasive clinical study for which they would not be compensated, there was a small risk for an adverse event, and they would not personally benefit from participating (a surrogate marker for altruism). Main Outcomes and Measures: Factors associated with patients' choice of medication, including age, sex, ocular disease, race, and participation in an invasive clinical study. Results: A total of 189 patients were included in the analysis (106 women [56%]; mean [SEM] age, 74.6 [0.8] years). Despite being told that it may not be as effective as aflibercept, 100 patients (53%) selected bevacizumab for their own eye care. An act of altruism (ie, participation in an invasive clinical study) when the patient was making a choice between the 2 drugs was associated with a patient's choice of bevacizumab (odds ratio [OR], 7.03; 95% CI, 2.27-21.80; P < .001); the OR for selecting bevacizumab for patients who never agreed to participate in the clinical study was 0.45 (95% CI, 0.25-0.83; P = .001). Age (OR, 1.00; 95% CI, 0.97-1.03; P = .86), race (OR, 0.70; 95% CI, 0.41-1.22; P = .21), sex (OR, 0.72; 95% CI, 0.39-1.35; P = .31), presence of diabetes (OR, 1.52; 95% CI, 0.59-3.93; P = .39), and type of eye disease (OR, 0.56; 95% CI, 0.30-1.04; P = .07) were not associated with choice of therapy. Conclusions and Relevance: These findings suggest that clinicians must consider the ethical implications of the influence of altruism when patients participate in the decision between cost-effective vs the most effective medicines for their own health care.