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Comparative genomics of vibrio vulnificus: Biology and applications
No full text[[abstract]]Vibrio vulnificus, a gram-negative marine bacterium, has been recognized as an important pathogen of both humans and eels for decades. V. vulnificus infection is characterized by the rapid spread of this organism from intestine or skin into deeper tissue and even the bloodstream to result in septicemia and/or necrotic skin lesions. One of gene regions, region XII, was found to be associated with one of the two lineages of V. vulnificus divided based on the multilocus sequence typing (MLST) data of six housekeeping genes. The superintegron is unique to each Vibrio species, containing different kinds of gene cassettes. The functions of gene cassettes and open reading frames (ORFs) in superintegrons remain largely unknown. The publication of nucleotide sequences of two BT1 V. vulnificus genomes and the BT2 virulence plasmid has opened up opportunities for mining new virulence genes for mice and eels as well as developing new diagnostic methods. Moreover, the complete genome information can be applied to epidemiology study and food safety monitoring. Because of the high mortality rate of systemic infection with V. vulnificus, an effective vaccine against this organism is desired, particularly for individuals at high risk. Contaminated bivalve molluscan shellfish, including oysters, clams, and mussels, are major sources of per os infection by V. vulnificus. The vast information generated from the genomes of major representative Vibrio species has enabled comparative analysis and provided an opportunity to investigate the biology of this group of marine bacteria
The epidemiology and identification of risk factors associated with severe dengue during the 2023 dengue outbreak in Kaohsiung City, Taiwan
No full text[[abstract]]After the previous major dengue fever (DF) outbreaks in 2014 and 2015 in Taiwan, the second-largest DF outbreak re-emerged in 2023. A total of 178 patients with laboratory-confirmed dengue virus (DENV) infection, including 92 DENV-1 and 86 DENV-2 cases, were enrolled in this study conducted during the 2023 dengue outbreak in Kaohsiung City, Taiwan. This study aimed to analyze epidemiological characteristics, clinical severity, and risk factors for severe dengue (SD), as well as the diagnostic implications of the non-structural protein 1 (NS1) antigen rapid test. Patients infected with DENV-2 exhibited significantly older age, higher incidence of secondary infections, diabetes mellitus (DM), hypertension (HT), and longer hospital stays than patients infected with DENV-1. Multivariate analysis revealed that older age (age ≥65), secondary dengue infection, DM, and HT were significant independent predictors of SD. Compared with non-SD cases, SD patients were significantly more likely to be older (age ≥65), to exhibit a higher incidence of secondary infections and a greater prevalence of chronic diseases, including DM and HT. Notably, dengue-confirmed patients with negative NS1 results had a shorter duration since symptom onset (p < 0.001). Our DENV-1 and DENV-2 isolates are related to strains from neighboring Asian countries. Our findings emphasize the important factors of old age, secondary infections, and chronic diseases that contributed to dengue severity. We should meticulously manage these high-risk groups to prevent dengue progression. Screening incoming travelers for DF during the epidemic season will be an important measure to prevent the introduction of DENV into Taiwan
Physalin A induces apoptosis through conjugating with Fas-FADD cell death receptor in human oral squamous carcinoma cells and suppresses HSC-3 cell xenograft tumors in NOD/SCID mice
No full text[[abstract]]IntroductionOral carcinoma cancer exhibits high global incidence and mortality. Physalin A (PA) was reported to induce programmed cell death in cancer cells. No study has yet investigated the influence of PA in oral squamous cell carcinoma. Herein, this study aims to explore PA-induced anti-cancer effects in human oral carcinoma.MethodsThis study used DNA gel electrophoresis and Annexin V/PI staining to detect DNA fragmentation and cell apoptosis. Western blotting and immunofluorescence analyzed protein expression. Flow cytometry measured Ca2+ release and mitochondrial membrane potential (triangle Psi m). Moreover, molecular docking models predicted the molecular binding affinity.ResultsDNA gel electrophoresis and annexin V/PI staining confirmed PA-induced DNA fragmentation and apoptosis. Flow cytometry showed PA increased Ca2+ release and reduced triangle Psi m levels. PA activated cleaved caspase-3, -8, and -9, upregulated Bax and Bid, and downregulated Bcl-2. PA dose-dependently increased Fas (CD95/APO-1), apoptosis-inducing factor (AIF), and cytochrome c release in western blotting analysis. Confocal microscopy confirmed increased Bax, AIF, cleaved caspase-3, and Fas, with decreased Bcl-2. Molecular docking showed strong PA binding via hydrophobic interactions with the Fas-associated death domain (FADD). Compared with cisplatin, PA inhibited HSC-3 cell xenograft tumor growth in NOD/SCID mice.DiscussionWe reveal that PA binds to the Fas-FADD complex, inducing caspase-8 activation and triggering extrinsic and intrinsic mitochondria-dependent apoptosis in HSC-3 cells. It also suppresses HSC-3 cell xenograft tumors in NOD/SCID mice. These findings suggest PA as a potential anti-oral cancer agent in the future
Association of long-term ozone exposure with the incidence and progression of hypertension, diabetes, and chronic kidney disease: A national retrospective cohort study
No full text[[abstract]]Evidence suggests that ozone is associated with an increased risk of hypertension, diabetes, or chronic kidney disease (CKD). However, the associations of ozone exposure with the dynamic progression of these diseases among Asian population remain unknown. This study included 9,256,945 participants from Taiwan's National Health Insurance Research Database between 2006 and 2021. Multimorbidity was defined as the coexistence of CKD and either hypertension or diabetes. The ordinary kriging method was used to estimate daily concentrations of ozone, sulfur dioxide, carbon monoxide, nitrogen dioxide, suspended fine particles, and suspended particles. Then, five-year average concentrations of pollutants were calculated. We performed multi-state survival models to analyze the association between ozone and dynamic progression of these diseases. During follow-up, 3,555,498 participants experienced hypertension, diabetes, or CKD; 656,515 experienced multimorbidity; and 792,555 died. Ozone exposure was significantly associated with incidence of the results in all transitions. The hazard ratios of each IQR (3.57 ppb) increment in ozone for the transition to incident disease were 1.016 [95 % confidence interval (CI): 1.014, 1.017], for the transition to death were 1.04 [95 % CI: 1.036, 1.043], for the transition to multimorbidity were 1.015 [95 % CI: 1.012, 1.017]. Furthermore, with each IQR increase of ozone, the hazard ratios for transition from the disease incidence to death and from multimorbidity to death were 1.03 [95 % CI: 1.026, 1.033] and 1.007 [95 % CI: 1.002, 1.013], respectively. Our results suggest long-term exposure to ozone might be an important determinant for the incidence and dynamic progression of hypertension, diabetes, and CKD in Taiwan
Accelerating innovation and ensuring the thoughtful withdrawal of lifeline medicines for people living with diabetes in Asia
No full text[[abstract]]At the 17th Scientific Meeting of the Asian Association for the Study of Diabetes (AASD), held in conjunction with the 46th Annual Meeting of the Diabetes Association and Endocrine Society of the Republic of China, insulin supply instability emerged as a pressing issue with continent-wide implications. The round table discussion, chaired by Professor Yutaka Seino (Kansai Electric Power Hospital/Kansai Electric Power Medical Research Institute) who is Chair of AASD, brought together expert voices from across Asia to discuss the multifaceted crisis in insulin access and formulate a regional response rooted in collaboration and equity
The risk of developing aphasia and exposure to air pollution in Taiwan
No full text[[abstract]](1) Background: The relationship between air pollution and the risk of developing aphasia is still unclear. We aimed to evaluate air pollution exposure as a risk factor for developing aphasia in Taiwan. (2) Methods: This retrospective population-based cohort study used the Longitudinal Generation Tracking Database (LGTD) and the Taiwan Air Quality Monitoring Database (TAQMD). The incidence rate ratio (IRR) and adjusted hazard ratio (aHR) were calculated to examine the association between aphasia and exposure to six air pollutants: sulfur oxide (SO2), carbon monoxide (CO), nitric oxide (NO), nitrogen oxide (NOx), and particulate matter (PM2.5, PM10) from 2003 to 2017. (3) Results: The incidence rate ratio (IRR) of aphasia showed that individuals with high levels of SO2, CO, and NO were at a higher risk of developing aphasia. Increased exposure to airborne particulate matter (PM2.5 and PM10) also increased the risk of developing aphasia. The adjusted HRs of the aphasia risk were statistically significant for all the air pollutants at higher concentrations. (4) Conclusions: Individuals exposed to ambient air pollutants have a significantly higher risk of developing aphasia. The greater the exposure to airborne particulate matter and gaseous pollutants, the more likely individuals are to develop aphasia
Association of DPP-4 inhibitors with respiratory and cardiovascular complications in patients with COPD: A nationwide cohort study
No full text[[abstract]]Aims: COPD is a comorbid condition often associated with type 2 diabetes (T2D) and cardiovascular diseases, but few studies have observed the impact of various antidiabetic drugs in patients with COPD and T2D. We conducted this study to investigate the long-term outcomes of dipeptidyl peptidase-4 (DPP-4) inhibitor use in patients with COPD and T2D. Materials and methods: We recruited 55 924 pairs of propensity score-matched DPP-4 inhibitor users and nonusers from Taiwan's National Health Insurance Research Database between 1 January 2008 and 31 December 2020. We used the Cox proportional hazards models with robust sandwich se estimates to compare the risks of all-cause mortality, major adverse cardiovascular events (MACEs) and respiratory outcomes in participants with COPD and T2D. Results: Compared with no use of DPP-4 inhibitors, the adjusted hazard ratios (aHRs) (95% confidence interval (CI)) for DPP-4 inhibitor use for all-cause mortality, MACEs, hospitalisation for COPD, invasive mechanical ventilation, bacterial pneumonia and lung cancer were 0.47 (0.45-0.49), 0.92 (0.88-0.95), 0.73 (0.62-0.85), 0.76 (0.71-0.82), 0.73 (0.70-0.76) and 0.74 (0.71-0.78), respectively. DPP-4 inhibitor users also exhibited a significantly lower cumulative incidence of hospitalisation for COPD (log-rank test, p=0.004), mechanical ventilation (log-rank test, p<0.001), lung cancer (log-rank test, p<0.001), bacterial pneumonia (log-rank test, p<0.001) and mortality (log-rank test, p<0.001) than nonusers. Conclusions: This nationwide cohort study showed that DPP-4 inhibitor use was associated with a significantly lower risk of mortality, cardiovascular events, respiratory complications and lung cancer in patients with COPD and T2D. Patients with COPD may benefit from DPP-4 inhibitors
Association between long-term ambient fine particulate matter exposure and risk of postneonatal infant mortality in Taiwan
No full text[[abstract]]Infants and children may be potentially susceptible to harm from ambient fine particulate matter (PM2.5) pollution because of the following characteristics (1) immature immune systems (2) not yet fully developed respiratory systems (3) possess a higher absorption rate of pollutants, and (4) and daily activities may expose infants to varying levels. However, few studies have examined the possible correlation between exposure to PM2.5 and mortality in infants. Therefore, the aim of this study was to investigate the association between long-term exposure to ambient PM2.5 and post-neonatal mortality in 65 municipal areas across Taiwan. The mean annual PM2.5 levels of each municipality were categorized from 2013 to 2022 and divided into tertiles. The natural logarithm of the annual post-neonatal mortality rates per 1000 live births was assessed with respect to PM2.5 level, urbanization level, physician density, and mean annual average household income. Weighted-multiple linear regression was utilized to compute the adjusted RRs and their 95% confidence intervals (CIs). When data were not stratified by PM2.5 levels, a significant positive association was observed between long-term lifetime exposure to ambient PM2.5 and post-neonatal mortality rates after adjustment for physician density, urbanization level, and average household income. When PM2.5 levels (in tertiles) were stratified, a positive but nonsignificant trend was found in post-neonatal mortality frequency from the lowest to the highest PM2.5 category. These findings suggest that long-term exposure to PM2.5 increases the risk of post-neonatal mortality rates in Taiwan
Transcriptome data-based prognosis prediction model for lung adenocarcinoma using an image deep learning approach
No full text[[abstract]]Background : In lung adenocarcinoma, therapies like EGFR TKIs and ICIs have improved outcomes for EGFR-mutant and wild-type patients, respectively. However, drug resistance and limited survival remain significant challenges. This study proposes a novel approach using whole transcriptome data to develop a prognosis prediction model through an image-based deep learning method. Methods: Four cohorts were analyzed: one training cohort (RNA-seq, n = 391) and three independent validation cohorts (TCGA RNA-seq, n = 394; GSE68465, n = 443; GSE13213, n = 117). RNA-seq data were transformed into images using pixel encoding strategies designed to preserve transcriptomic information. The Convolutional Neural Network (CNN) model was trained on all gene expression data without feature selection. To prevent overfitting, the training cohort was divided into subsets: training (n = 259), testing (n = 62), and validation (n = 77). The CNN model was trained on the training set, validated on the testing and validation sets, and independently evaluated on the three validation cohorts. Results: RNA-seq data were successfully transformed into images first. The image transformation process enabled effective training of the CNN model, which categorized patients into high- and low-risk groups. In the training cohort, high-risk patients had significantly shorter overall survival (all P < 0.01). Similar results were observed in external validation cohorts: TCGA (P = 0.001), GSE68465 (P < 0.0001), and GSE13213 (P = 0.003). Prediction accuracies were 0.71, 0.81, and 0.92 for the training, testing, and validation subsets, respectively. In the external cohorts, prediction accuracy averaged 0.7. Conclusions: This study introduces an innovative image-based deep learning strategy to analyze whole transcriptome data without requiring differential gene selection. This approach captures comprehensive transcriptomic information, offering potential for improved prognostic modeling and molecular guidance in lung cancer treatments
Taiwan population-based epigenetic clocks and their application to long-term air pollution exposure
No full text[[abstract]]Most epigenetic clocks have been developed in populations of European or Hispanic descent; therefore, population-specific models are needed for Asian cohorts to enhance predictive accuracy and generalizability. This study aims to develop epigenetic clocks in a Taiwanese cohort and examine the association between long-term air pollution exposure and epigenetic age acceleration (EAA). The Taiwan Biobank (TWB) has been recruiting community-based adults aged 30-70 years since 2012, enrolling 173,806 participants by the end of 2022. Among them, 2,469 participants were selected for serum DNA methylation (DNAm) analysis. Epigenetic ages were estimated using penalized elastic net regression, with residuals defined as TWB-based epigenetic age acceleration (TWBEAA) and healthy-subset-based acceleration (TWBhEAA). Additionally, four previously established EAAs were obtained using Horvath's online DNA Methylation Age Calculator: DNAmEAA, DNAmSBEAA, PhenoEAA, and GrimEAA. Air pollution exposure levels at participants' residential townships were estimated from pre-1 day to pre-1 year using a kriging-based spatial interpolation method. Associations were assessed using multiple linear regression models, with robustness verified through Bayesian Kernel Machine Regression (BKMR). The TWBAge (325 CpG sites) and TWBhAge (179 CpG sites) prediction models demonstrated high accuracy (R(2) = 0.95) in predicting chronological age. In the single-pollutant model, pre-1 year PM(2.5) exposure was significantly associated with TWBhEAA (β = 0.67 [0.14-1.19], year) and DNAmEAA (β = 0.93 [0.03-1.83], year), while O(3) exposure showed a positive association with DNAmSBEAA (β = 0.53 [0.29-0.77], year) and a negative association with GrimEAA (β = -0.44 [-0.70 to -0.17], year). BKMR analysis confirmed these findings. This study is among the first attempts to develop epigenetic clocks tailored for Asian population, providing evidence of air pollution's role in accelerating biological aging. Our findings highlight PM(2.5) and O(3) exposure as major contributors to EAA, emphasizing the need for air pollution mitigation strategies to promote healthier aging