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Transition metals and chemical compositions determine the oxidation capacity of atmospheric particulate matters
No full text[[abstract]]The knowledge of the causal relationship between exposure to airborne particulate matter (PM) and respiratory-related health issues remains unsatisfactory, owing to the complexities of physical and chemical characteristics in PM. One measure that greatly lifts the complexity is oxidative potential (OP), the overall production capacity of reactive oxygen species. We analyzed PM at different size fractions from three localities, exhibiting different source emission properties and photochemical aging states. We also investigated possible causes for their OPs, which were assessed using cellular and acellular assays. We found that higher PM mass did not always yield higher OP. Instead, chemical composition, modified by photochemical alteration (particle oxidation), played a critical role in the PM's reactivity. From a pollution hot spot to a downwind country town, the PM(2.5) levels (mean ± SD) were 9.3 ± 4.5, 9.7 ± 4.9, and 6.6 ± 4.7 μg/m(3), respectively. In contrast, the PM mass-normalized OP values in the downwind region were approximately 20 % higher than those in the upwind region based on the cellular assay and about three times higher from the acellular assay. Enhanced PM OP is associated with atmospheric oxidation, approximated by sulfur and nitrogen oxidation ratios. We further identified transition metals, particularly copper, a single most important species group, the primary determinant to the values of OP measured, contributing directly to OP and indirectly through metal-oxides enhanced photochemical alterations to PM
Rare APOE p.Gly4Glu: A putative disease-causing variant for early-onset Alzheimer's disease identified by next-generation sequencing
No full text[[abstract]]OBJECTIVES: We aimed to identify the early-onset Alzheimer's disease (EOAD)-causing variants in the Eastern Taiwanese population. MATERIALS AND METHODS: Twenty-one patients diagnosed with EOAD in the memory clinic at Hualien Tzu Chi Hospital were enrolled during 2014-2018. We conducted whole-exome sequencing to identify the disease-causing variations and validated by Sanger sequencing. SIFT, PolyPhen-2, and AlphaFold were applied to predict the functional impact of the identified variants. RESULTS: Two unrelated normolipidemic EOAD patients were carrying a rare heterozygous APOE variant (rs373985746, NC_000019.10:g. 44905879G>A, NM_001302688.2:c. 11G>A, and NP_001289617.1:p.Gly4Glu) with the allele frequency as 0.000206. Sanger sequencing uncovered the ∑ haplotypes in which the c.11G>A variation resided. SIFT predicted that the variant severely impacts protein structure and, maybe thus, function. AlphaFold predicted a dysfunctional conformation of the mutant APOE precursor a protein (p.Gly4Glu). CONCLUSION: Our data strongly suggest that the rare p.Gly4Glu variant is associated with EOAD but does not cause dyslipidemia
History, concepts, and conventional medicare technologies using artificial intelligence
No full text[[abstract]]The history of how artificial intelligence (AI) has been integrated into the Medicare process has been responsible and contingent, aiming to achieve personalized and effective healthcare. Core AI concepts, such as machine learning (ML), deep learning (DL), natural language processing (NLP), computer vision, and predictive analytics, have revolutionized conventional Medicare technologies. These advancements optimize disorder diagnosis, provide treatment plans tailored to individual cases, enhance medical imaging, and improve patient care. Current trends in AI adoption focus on disease detection, personalized treatment, remote access to healthcare, and they address major roadblocks such as data privacy, security, interoperability, mitigation of bias, regulatory compliance, and change resistance. Looking ahead, AI is poised to revolutionize not only drug discovery but also predictive analytics, promising the governance of ethical AI to further enhance healthcare accessibility and quality. To unlock the full potential of AI in Medicare services, ethical and regulatory considerations, including data privacy, transparency, mitigation of bias, and AI governance, must be carefully navigated. Additionally, stakeholders need to address change management, provide continuous education, and ensure a framework for ethical AI governance. These efforts will be essential for realizing the transformative benefits of AI in the realm of Medicare services
Reply to letter to the Editor regarding “Real world clinical outcomes when discontinuing denosumab or bisphosphonates in patients with surgically managed osteoporotic vertebral compression fractures: A population-based cohort study”
No full text6-chlorocoumarin conjugates with nucleobases and nucleosides as potent anti-hepatitis C virus agents
No full text[[abstract]]On the basis of a “chemo-combination strategy”, (6-chloro)coumarin was incorporated to purines and pyrimidines, as well as their corresponding nucleosides, with a –SCH2– linker at different positions under alkaline conditions. These conjugates were found to exert an antiviral effect on the 1b subgenomic replicon replication of the hepatitis C virus (HCV) in Huh 5-2 and Huh 9-13 cells. In this compound library containing 14 new compounds, 6-[(6′-chlorocoumarin-3′-yl)methylthio]purine, 6-(6′-chlorocoumarin-3′-yl)methylthio-9-(β-D-ribofuranos-1″-yl)purine, and 2-[(6′-chlorocoumarin-3′-yl)methylthio]uracil showed great inhibitory abilities, with EC50 values between 6.6 and 9.4 μM and selectivity indexes >16–41. Moreover, the structure–activity relationship between purines and pyrimidines is elucidated, which reveals the critical factor of the attachment of the coumarin moiety at different positions in purines and pyrimidines
Comparing organophosphate and pyrethroid resistance levels of Aedes aegypti (Diptera: Culicidae) in frequent and infrequent application areas of Taiwan
No full text[[abstract]]Aedes aegypti mosquitoes spread a number of diseases that cause significant impacts to public health. In Taiwan, Ae. aegypti are mainly controlled using chemical insecticides, but previous studies indicate that Ae. aegypti may have developed resistance to several insecticides. We hypothesized that Ae. aegypti resistance levels could be affected by insecticide application frequencies and therefore compared transcriptome information, expressions of metabolic resistance genes, and gene mutations of field adult mosquitoes collected from Kaohsiung City (frequent application area, insecticides applied once a week) and Tainan City (infrequent application area, insecticides applied only when dengue cases were discovered); a laboratory strain was established as control. Next-generation sequencing was used to identify potential resistance genes from four main detoxification categories, bioassays were used to determine knockdown effects and mortality rates, and point mutations relating to target resistance were further analyzed. A total of 50 detoxification differential transcripts were identified following comparison with the laboratory strain, and more differential transcripts were found in mosquitos collected from the frequent application area (Kaohsiung). Mosquitoes from areas with frequent applications displayed lower mortality rates, confirming a difference in resistance levels. Additionally, mosquitoes from frequent application areas showed higher levels of resistance to pyrethroids compared with organophosphates. We found silent mutations at G923, L982, and A1007, as well as point mutations at S989P, V1016G, F1534C, and D1763Y. V1016G occurred in all four strains we collected, indicating that pyrethroid resistance in Ae. aegypti has begun to develop in all regions
Wastewater SARS-CoV-2 monitoring in a university hospital forecasts multilevel epidemic curves in Taipei City, Taiwan
No full text[[abstract]]As COVID-19 shifts toward endemicity, ongoing surveillance remains critical to identifying and containing potential outbreaks, particularly in high-risk settings. Wastewater monitoring at targeted institutions offers a promising approach for early detection; however, its utility in forecasting broader epidemic trends remains underexplored. This study aimed to establish the wastewater surveillance platform for SARS-CoV-2 in a University Hospital to forecast the epidemic at the hospital, the surrounding community, and the city levels. During April and October 2022, we conducted routine wastewater sampling at seven sampling wells across the campus twice weekly. The direct viral RNA capture method was adopted for the pretreatment, concentration, and extraction of viral RNA. The presence of SARS-CoV-2 RNA in the wastewater samples was detected and quantified with RT-qPCR targeting N1, N2, and E-gene. SARS-CoV-2 signals relative to pepper mild mottle virus were calculated. Simple linear regression models were used to model the future moving averages of cumulative confirmed cases per 100,000 population at the hospital, community, and city levels. High consistency was observed in the E, N1, and N2 gene targets. Even with only eight new cases in the Zhongzheng District (5.42 per 100,000 population) and 145 cases in the entire city (5.85 per 100,000 population), the virus can be detected in sewage, indicating promising sensitivity. The relative viral signals in the wastewater were strongly associated with future epidemiological indicators at the hospital, community, and city levels. Wastewater sampling and quantification of SARS-CoV-2 is proven to be an efficient and robust method for the tracking and forecasting of infection trends within and beyond hospital settings
Assessing ChatGPT for clinical decision-making in radiation oncology, with open-ended questions and images
No full text[[abstract]]PURPOSE: This study assesses the practicality and correctness of Chat Generative Pre-trained Transformer (ChatGPT)-4 and 4O's answers to clinical inquiries in radiation oncology, and evaluates ChatGPT-4O for staging nasopharyngeal carcinoma (NPC) cases with magnetic resonance (MR) images. METHODS AND MATERIALS: A total of 164 open-ended questions covering representative professional domains (Clinical_G: knowledge on standardized guidelines; Clinical_C: complex clinical scenarios; Nursing: nursing and health education; and Technology: radiation technology and dosimetry) were prospectively formulated by experts and presented to ChatGPT-4 and 4O. Each ChatGPT's answer was graded as 1 (Directly practical for clinical decision-making), 2 (Correct but inadequate), 3 (Mixed with correct and incorrect information), or 4 (Completely incorrect). ChatGPT-4O was presented with the representative diagnostic MR images of 20 patients with NPC across different T stages, and asked to determine the T stage of each case. RESULTS: The proportions of ChatGPT's answers that were practical (grade 1) varied across professional domains (P < .01), higher in Nursing (GPT-4: 91.9%; GPT-4O: 94.6%) and Clinical_G (GPT-4: 82.2%; GPT-4O: 88.9%) domains than in Clinical_C (GPT-4: 54.1%; GPT-4O: 62.2%) and Technology (GPT-4: 64.4%; GPT-4O: 77.8%) domains. The proportions of correct (grade 1+2) answers (GPT-4: 89.6%; GPT-4O: 98.8%; P < .01) were universally high across all professional domains. However, ChatGPT-4O failed to stage NPC cases via MR images, indiscriminately assigning T4 to all actually non-T4 cases (κ = 0; 95% CI, -0.253 to 0.253). CONCLUSIONS: ChatGPT could be a safe clinical decision-support tool in radiation oncology, because it correctly answered the vast majority of clinical inquiries across professional domains. However, its clinical practicality should be cautiously weighted particularly in the Clinical_C and Technology domains. ChatGPT-4O is not yet mature to interpret diagnostic images for cancer staging
Association between telomere length and atopic dermatitis among school-age children
No full text[[abstract]]BACKGROUND: Atopic dermatitis is a common chronic skin disease in children. Whether telomere length is associated with atopic dermatitis remains unclear. This population-based case-control study aimed to investigate the association between telomere length and atopic dermatitis in school-age children. METHODS: In this cross-sectional analysis, we included 1084 singleton term-born children (608 males; mean age 6.4 years) from the Longitudinal Investigation of Global Health in Taiwanese Schoolchildren cohort. Telomere length was measured using quantitative real-time polymerase chain reaction, log-transformed and was analyzed in quartiles. The main outcome was atopic dermatitis defined as having physician-diagnosed atopic dermatitis and the presence of atopic dermatitis in the last 12 months. Regression analyses were used to assess the relationship between telomere length and atopic dermatitis. RESULTS: Telomere length was significantly inversely associated with childhood atopic dermatitis after adjusting for child's age, sex, overweight or obesity, birth season, childhood allergic diseases, environmental tobacco smoke, parental history of allergic diseases, parental educational level, and breastfeeding status (p_(trend) = 0.01). Specifically, when telomere length was classified into quartiles, children in the shortest (fourth) telomere length quartile had a 1.88-fold higher probability of atopic dermatitis compared to those in the longest (first) quartile (95% confidence interval: 1.13-3.14). Stratified analyses showed that the associations were stronger in males and non-breastfed children, with no significant associations observed in females or breastfed children. CONCLUSION: This study provides new evidence suggesting an association between shorter telomere length and atopic dermatitis in school-age children
Hybrid neural networks in the mushroom body drive olfactory preference in Drosophila
No full text[[abstract]]In Drosophila melanogaster, olfactory encoding in the mushroom body (MB) involves thousands of Kenyon cells (KCs) processing inputs from hundreds of projection neurons (PNs). Recent data challenge the notion of random PN-to-KC connectivity, revealing preferential connections between food-related PNs and specific KCs. Our study further uncovers a broader picture-an L-shaped hybrid network, supported by spatial patterning: Food-related PNs diverge across KC classes, whereas pheromone-sensitive PNs converge on γ KCs. α/β KCs specialize in food odors, whereas γ KCs integrate diverse inputs. Such spatial arrangement extends further to the antennal lobe (AL) and lateral horn (LH), shaping a systematic olfactory landscape. Moreover, our functional validations align with computational predictions of KC odor encoding based on the hybrid connectivity, correlating PN-KC activity with behavioral preferences. In addition, our simulations showcase the network's augmented sensitivity and precise discrimination abilities, underscoring the computational benefits of this hybrid architecture in olfactory processing