Impact of Heavy Metals in Ambient Air in Insulin Resistance of Shipyard Welders in Northern Taiwan

Exposure to metals poses potential health risks, including insulin resistance (IR), to those exposed to them in excess. Limited studies have examined such risks in occupational workers, including welders, and these have yielded inconsistent results. Thus, we examined the associations between exposure to welding metals and IR in welders. We recruited 78 welders and 75 administrative staff from a shipyard located in northern Taiwan. Personal exposure to heavy metals, including chromium (Cr), manganese (Mn), iron (Fe), nickel (Ni), copper (Cu), zinc (Zn), and cadmium (Cd), was monitored through particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) and urine analysis by inductively coupled plasma mass spectrometry (ICP–MS). After each participant fasted overnight, blood samples were collected and analyzed for IR assessment through updated homeostasis model assessment (HOMA2) modeling. Air sampling in the personal breathing zone was performed during a Monday shift prior to the blood and urine sample collection the following morning. The welders’ median personal Cr, Mn, Fe, Ni, Cu, and Zn airborne PM2.5 levels and urinary Cd levels were significantly higher than those of the administrative staff. After adjustment for covariates, logarithmic PM2.5-Mn, PM2.5-Fe, PM2.5-Cu, and PM2.5-Zn levels were positively correlated with logarithmic fasting plasma glucose (P-FGAC) levels (PM2.5-Mn: β = 0.0105, 95% C.I.: 0.0027–0.0183; PM2.5-Fe: β = 0.0127, 95% C.I.: 0.0027–0.0227; PM2.5-Cu: β = 0.0193, 95% C.I.: 0.0032–0.0355; PM2.5-Zn: β = 0.0132, 95% C.I.: 0.0005–0.0260). Logarithmic urinary Zn was positively correlated with logarithmic serum insulin and HOMA2-IR levels and negatively correlated with logarithmic HOMA2-insulin sensitivity (%S; βinsulin = 0.2171, 95% C.I.: 0.0025–0.4318; βIR = 0.2179, 95% C.I.: 0.0027–0.4330; β%S = −0.2180, 95% C.I.: −0.4334 to −0.0026). We observed that glucose homeostasis was disrupted by Mn, Fe, Cu, and Zn exposure through increasing P-FGAC and IR levels in shipyard welders

Stimulatory Effect of 5-Hydroxytryptamine (5-HT) on Rat Capsaicin-Sensitive Lung Vagal Sensory Neurons via Activation of 5-HT\u3csub\u3e3\u3c/sub\u3e Receptors

5-hydroxytryptamine (5-HT) is an inflammatory mediator known to be released in lung. Capsaicin-sensitive lung vagal (CSLV) afferents function as a primary sensor for detecting chemical stimuli and produce consequent reflexes during lung inflammation. To characterize the effect of 5-HT on CSLV afferents, responses of cardiorespiratory reflexes and single-unit C-fiber afferents to right-atrial injections of 5-HT were investigated in anesthetized Sprague-Dawley rats. Bolus injection of 5-HT (8 μg/kg) caused an immediate augmented breath and apnea, accompanied by hypotension and bradycardia. These initial responses were then followed by a brief pressor response and a more sustained depressor response. After a perineural treatment of both cervical vagi with capsaicin to block the conduction of C fibers, 5-HT still triggered the augmented breath, but no longer evoked the apnea, bradycardia and hypotension, indicating an involvement of C-fiber activation. The remaining augmented breath induced by 5-HT after perineural capsaicin treatment was totally eliminated by vagotomy. To further study the effect of 5-HT on CSLV afferents, activities arising from these afferents were determined using the single-fiber recording technique. Right-atrial injection of 5-HT evoked an intense discharge in CSLV afferents in a dose-dependent manner. The highest dose of 5-HT (16 μg/kg) activated 79% (19/24) of CSLV afferents which were also sensitive to capsaicin (0.8 μg/kg). The pretreatment of tropisetron, a selective antagonist of the 5-HT3 receptor, completely blocked CSLV-afferents stimulation induced by 5-HT but did not affect that by capsaicin. Furthermore, a similar afferent response of CSLV afferents was mimicked by phenylbiguanide, a selective agonist of the 5-HT3 receptor. In isolated rat lung vagal C neurons, 5-HT induced intense calcium transients in a dose-dependent manner. The highest concentration (3 μM) of 5-HT activated 67% (18/27) of the CSLV neurons. The 5-HT-induced response was totally abolished by pretreatment of tropisetron. In conclusion, 5-HT exerts an intense stimulatory effect on lung C-fiber terminals mediated through an activation of the 5-HT3 receptor, which may contribute to the airway hypersensitivity under lung inflammation

Knowledge-Enriched Visual Storytelling

Stories are diverse and highly personalized, resulting in a large possible output space for story generation. Existing end-to-end approaches produce monotonous stories because they are limited to the vocabulary and knowledge in a single training dataset. This paper introduces KG-Story, a three-stage framework that allows the story generation model to take advantage of external Knowledge Graphs to produce interesting stories. KG-Story distills a set of representative words from the input prompts, enriches the word set by using external knowledge graphs, and finally generates stories based on the enriched word set. This distill-enrich-generate framework allows the use of external resources not only for the enrichment phase, but also for the distillation and generation phases. In this paper, we show the superiority of KG-Story for visual storytelling, where the input prompt is a sequence of five photos and the output is a short story. Per the human ranking evaluation, stories generated by KG-Story are on average ranked better than that of the state-of-the-art systems. Our code and output stories are available at https://github.com/zychen423/KE-VIST.Comment: AAAI 202

Toward Transparent Sequence Models with Model-Based Tree Markov Model

In this study, we address the interpretability issue in complex, black-box Machine Learning models applied to sequence data. We introduce the Model-Based tree Hidden Semi-Markov Model (MOB-HSMM), an inherently interpretable model aimed at detecting high mortality risk events and discovering hidden patterns associated with the mortality risk in Intensive Care Units (ICU). This model leverages knowledge distilled from Deep Neural Networks (DNN) to enhance predictive performance while offering clear explanations. Our experimental results indicate the improved performance of Model-Based trees (MOB trees) via employing LSTM for learning sequential patterns, which are then transferred to MOB trees. Integrating MOB trees with the Hidden Semi-Markov Model (HSMM) in the MOB-HSMM enables uncovering potential and explainable sequences using available information

Characterization of the RNA-binding properties of the triple-gene-block protein 2 of Bamboo mosaic virus

The triple-gene-block protein 2 (TGBp2) of Bamboo mosaic virus (BaMV) is a transmembrane protein which was proposed to be involved in viral RNA binding during virus transport. Here, we report on the RNA-binding properties of TGBp2. Using tyrosine fluorescence spectroscopy and UV-crosslinking assays, the TGBp2 solubilized with Triton X-100 was found to interact with viral RNA in a non-specific manner. These results raise the possibility that TGBp2 facilitates intracellular delivery of viral RNA through non-specific protein-RNA interaction