GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Texts.

Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests and genetic tests, to find a possible answer over a prolonged period of time. Addressing this "diagnostic odyssey" thus has substantial clinical, psychosocial, and economic benefits. Many rare genetic diseases have distinctive facial features, which can be used by artificial intelligence algorithms to facilitate clinical diagnosis, in prioritizing candidate diseases to be further examined by lab tests or genetic assays, or in helping the phenotype-driven reinterpretation of genome/exome sequencing data. Existing methods using frontal facial photos were built on conventional Convolutional Neural Networks (CNNs), rely exclusively on facial images, and cannot capture non-facial phenotypic traits and demographic information essential for guiding accurate diagnoses. Here we introduce GestaltMML, a multimodal machine learning (MML) approach solely based on the Transformer architecture. It integrates facial images, demographic information (age, sex, ethnicity), and clinical notes (optionally, a list of Human Phenotype Ontology terms) to improve prediction accuracy. Furthermore, we also evaluated GestaltMML on a diverse range of datasets, including 528 diseases from the GestaltMatcher Database, several in-house datasets of Beckwith-Wiedemann syndrome (BWS, over-growth syndrome with distinct facial features), Sotos syndrome (overgrowth syndrome with overlapping features with BWS), NAA10-related neurodevelopmental syndrome, Cornelia de Lange syndrome (multiple malformation syndrome), and KBG syndrome (multiple malformation syndrome). Our results suggest that GestaltMML effectively incorporates multiple modalities of data, greatly narrowing candidate genetic diagnoses of rare diseases and may facilitate the reinterpretation of genome/exome sequencing data.

Stereotactic hematoma puncture and drainage for primary pontine hemorrhage: Clinical outcomes and predictive model.

Primary pontine hemorrhage (PPH) is a particularly grave form of hemorrhagic stroke, characterized by its significant mortality rate. stereotactic hematoma puncture and drainage is a procedure that has been shown to improve the prognosis of patients with PPH. However, there are currently no established criteria for selecting patients for this procedure. We contrasted the clinical outcomes of PPH patients treated with stereotactic hematoma puncture and drainage with those who received conservative treatment in this study. We conducted logistic regression analysis to identify the risk factors associated with postoperative mortality. A mortality risk nomogram was then constructed using these risk factors. A total of 127 conservatively treated patients and 96 patients who underwent stereotactic hematoma puncture and drainage were included in this study. In the surgical group, the 30-day mortality rate stood at 28.1%, significantly lower than the 43.3% observed in the control group (p = 0.02). Age, along with the Glasgow Coma Scale (GCS) score and hematoma size, were identified as independent risk factors associated with death within 30 days post-surgery. The mortality risk nomogram was well calibrated and discriminatory, with a c-index of 0.878 (95% CI 0.80-0.95) as validated by bootstrapping, and a c-index of 0.849. This study provides a predictive model for selecting patients who are most likely to benefit from stereotactic hematoma puncture and drainage. The results of this study could be helpful to neurosurgeons in their decision-making process. However, further external validation is necessary to confirm these findings.

The association of peritoneal dialysis and hemodialysis on mitral and aortic valve calcification associated mortality: a meta-analysis.

Cardiac valve calcification (CVC), characterized by the accumulation of calcium in the heart valves, is highly prevalent among patients undergoing dialysis. This meta-analysis aimed to provide an updated summary of recent studies on the prognostic value of CVC in patients undergoing dialysis. We conducted a search of PubMed, Embase, and Web of Science to identify observational studies investigating cardiovascular or all-cause mortality associated with CVC in dialysis patients until March 2023. Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) were calculated for the meta-analysis, and the strength and significance of the associations between CVC and mortality outcomes in dialysis patients were assessed. From 6218 initially identified studies, we included 10 critical studies with a total of 3376 dialysis patients in a further meta-analysis. Pooled analyses demonstrated a significant association between CVC and an elevated risk of all-cause and cardiovascular mortality in dialysis patients. In our study, we discovered HRs of 1.592 (95% CI 1.410-1.797) for all-cause mortality and 2.444 (95% CI 1.632-3.659) for cardiovascular mortality. Furthermore, subgroup analysis revealed elevated all-cause mortality among patients with mitral valve calcification (HR 1.572; 95% CI 1.200-2.060) compared to those with aortic valve calcification (HR 1.456; 95% CI 1.105-1.917). Similarly, patients undergoing peritoneal dialysis faced a greater risk for all-cause mortality (HR 2.094; 95% CI 1.374-3.191) than those on hemodialysis (HR 1.553; 95% CI 1.369-1.763). This highlights the possibility of CVC being an independent risk factor for dialysis patients, particularly in relation to mitral valve calcification or peritoneal dialysis.

Factors Influencing the Fasting Time in Adult Patients After the Endoscopic Management of Sharp Esophageal Foreign Bodies.

Background: Sharp esophageal foreign body (SEFB) impaction can cause varying degrees of damage to the esophagus. There are few studies analyzing the postoperative fasting time in SEFB patients. Methods: We retrospectively collected 835 SEFB patients. According to the fasting time after the endoscopic removal (ER) of SEFBs, the patients were divided into two groups: short fasting time (SFT, fasted ≤24 h) and long fasting time (LFT, fasted >24 h). Results: There were 216 and 619 patients in the SFT and LFT group, respectively. The average age of the SFT group (52.97 years) was younger than that of the LFT group (55.96 years) (p = 0.025). The LFT group had lower proportion of duration of impaction (DOI) within 12 hours (14.2% vs 22.2%, p = 0.006) and erosion rates (89.0% vs 94.0%, p = 0.034) as well as higher proportion of esophageal perforation (19.5 vs 6.5%, p = 0.010) and patients who got intravenous anesthesia (63.78% vs 31.9%, p = 0.000) than the SFT group. The longest diameter of the foreign body (Lmax) in the LFT group (2.60 ± 1.01 cm) was greater than that in the SFT group (2.41 ± 0.83 cm; p = 0.01). Multivariate regression analysis found that age (OR = 1.726[1.208-2.465], p = 0.003), DOI (OR = 1.793[1.175-2.737], p = 0.007), Lmax (OR = 1.477[1.033-2.111], p = 0.032), perforation (OR = 3.698[2.038-6.710]; p < 0.01) and intravenous anesthesia (OR = 3.734[2.642-5.278]; p < 0.01) were the independent factors that prolonged fasting time in patients with SEFBs, while esophageal mucosal erosion (OR = 0.433[0.229-0.820]; p = 0.01) was the influencing factor leading to shortened fasting time. Conclusion: For the first time, we analyzed factors influencing the fasting time after ER in SEFB patients. Age, DOI, Lmax, perforation and intravenous anesthesia were risk factors for a prolonged postoperative fasting time.

Applications of deep learning for detecting ophthalmic diseases with ultrawide-field fundus images.

AIM: To summarize the application of deep learning in detecting ophthalmic disease with ultrawide-field fundus images and analyze the advantages, limitations, and possible solutions common to all tasks. METHODS: We searched three academic databases, including PubMed, Web of Science, and Ovid, with the date of August 2022. We matched and screened according to the target keywords and publication year and retrieved a total of 4358 research papers according to the keywords, of which 23 studies were retrieved on applying deep learning in diagnosing ophthalmic disease with ultrawide-field images. RESULTS: Deep learning in ultrawide-field images can detect various ophthalmic diseases and achieve great performance, including diabetic retinopathy, glaucoma, age-related macular degeneration, retinal vein occlusions, retinal detachment, and other peripheral retinal diseases. Compared to fundus images, the ultrawide-field fundus scanning laser ophthalmoscopy enables the capture of the ocular fundus up to 200° in a single exposure, which can observe more areas of the retina. CONCLUSION: The combination of ultrawide-field fundus images and artificial intelligence will achieve great performance in diagnosing multiple ophthalmic diseases in the future.

Enhancing phenotype recognition in clinical notes using large language models: PhenoBCBERT and PhenoGPT.

To enhance phenotype recognition in clinical notes of genetic diseases, we developed two models-PhenoBCBERT and PhenoGPT-for expanding the vocabularies of Human Phenotype Ontology (HPO) terms. While HPO offers a standardized vocabulary for phenotypes, existing tools often fail to capture the full scope of phenotypes due to limitations from traditional heuristic or rule-based approaches. Our models leverage large language models to automate the detection of phenotype terms, including those not in the current HPO. We compare these models with PhenoTagger, another HPO recognition tool, and found that our models identify a wider range of phenotype concepts, including previously uncharacterized ones. Our models also show strong performance in case studies on biomedical literature. We evaluate the strengths and weaknesses of BERT- and GPT-based models in aspects such as architecture and accuracy. Overall, our models enhance automated phenotype detection from clinical texts, improving downstream analyses on human diseases.

Classification of integers based on residue classes via modern deep learning algorithms.

Judging whether an integer can be divided by prime numbers such as 2 or 3 may appear trivial to human beings, but it can be less straightforward for computers. Here, we tested multiple deep learning architectures and feature engineering approaches to classifying integers based on their residues when divided by small prime numbers. We found that the ability of classification critically depends on the feature space. We also evaluated automated machine learning (AutoML) platforms from Amazon, Google, and Microsoft and found that, without appropriately engineered features, they failed on this task. Furthermore, we introduced a method that utilizes linear regression on Fourier series basis vectors and demonstrated its effectiveness. Finally, we evaluated large language models (LLMs) such as GPT-4, GPT-J, LLaMA, and Falcon, and we demonstrated their failures. In conclusion, feature engineering remains an important task to improve performance and increase interpretability of machine learning models, even in the era of AutoML and LLMs.

The association between alcohol, betel nut, and cigarette use with hepatitis C virus infection in Taiwan.

Hepatitis C virus (HCV) infection may cause chronic liver disease, liver cirrhosis, and liver cancer. It has been reported to associate with habits including alcohol, betel nut and cigarette use. We aimed to investigate the association between alcohol, betel nut, and cigarette use with HCV infection in Taiwan and to explore their effects. A total of 121,421 participants were enrolled from the Taiwan Biobank. They were stratified into two groups according to whether they had (n = 2750; 2.3%) or did not have (n = 118,671; 97.7%) HCV infection. All participants were also classified into four groups according to the number of habits, including a history of alcohol drinking, betel nut chewing, and cigarette smoking. There were 85,406 (no habit), 24,299 (one habit), 8659 (two habits), and 3057 (three habits) participants in the four groups, respectively. Multivariable analysis showed that the participants who had an alcohol drinking history (odds ratio [OR] 1.568; 95% confidence interval [CI] 1.388-1.773; p < 0.001), betel nut chewing history (OR 1.664; 95% CI 1.445-1.917; p < 0.001), cigarette smoking history (OR 1.387; 95% CI 1.254-1.535; p < 0.001), were significantly associated with HCV infection. Furthermore, the participants were classified into four groups according to the number of habits as follows: 85,406 (no habit), 24,299 (one habit), 8659 (two habits), and 3057 (three habits). The HCV infection rates in these four groups were 2.11%, 2.14%, 3.23%, and 4.78%, respectively. Compared to the participants with no or one habit, those with two habits had a higher HCV infection rate (all p < 0.001). In addition, compared to the participants who had no, one or two habits, those who had three habits also had higher HCV infection rates (all p < 0.001). The participants who had three habits had the highest prevalence of HCV infection. In an era when most HCV can be cured, understanding the epidemiology link between habits and HCV may help the case finding.

Unsupervised clustering analysis of comprehensive health status and its influencing factors on women of childbearing age: a cross-sectional study from a province in central China.

BACKGROUND: Most previous studies on women of childbearing age have focused on reproductive health and fertility intentions, and evidence regarding the comprehensive health status of women of childbearing age is limited. This study aimed to comprehensively examine the health status of women of childbearing age through a multi-method and multi-indicator evaluation, analyze the factors that influence their overall health, and provide sound recommendations for the improvement and promotion of healthy behaviors. METHODS: Data on women of childbearing age living in Shanxi Province were collected between September 2021 and January 2022 through online and offline surveys. The k-means algorithm was used to assess health-related patterns in women, and multivariate nonconditional logistic regression was used to assess the influencing factors of women's overall health. RESULTS: In total, 1,258 of 2,925 (43%) participants were classified as having a good health status in all five domains of the three health dimensions: quality of life, mental health, and illness. Multivariate logistic regression showed that education level, gynecological examination status, health status of family members, access to medical treatment, age, cooking preferences, diet, social support, hand washing habits, attitude toward breast cancer prevention, and awareness of reproductive health were significantly associated with different health patterns. CONCLUSIONS: The comprehensive health status of women of childbearing age in Shanxi Province is generally good; however, a large proportion of women with deficiencies in some dimensions remains. Since lifestyle greatly impacts women's health, health education on lifestyle and health-related issues should be strengthened.

Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT.

To enhance phenotype recognition in clinical notes of genetic diseases, we developed two models - PhenoBCBERT and PhenoGPT - for expanding the vocabularies of Human Phenotype Ontology (HPO) terms. While HPO offers a standardized vocabulary for phenotypes, existing tools often fail to capture the full scope of phenotypes, due to limitations from traditional heuristic or rule-based approaches. Our models leverage large language models (LLMs) to automate the detection of phenotype terms, including those not in the current HPO. We compared these models to PhenoTagger, another HPO recognition tool, and found that our models identify a wider range of phenotype concepts, including previously uncharacterized ones. Our models also showed strong performance in case studies on biomedical literature. We evaluated the strengths and weaknesses of BERT-based and GPT-based models in aspects such as architecture and accuracy. Overall, our models enhance automated phenotype detection from clinical texts, improving downstream analyses on human diseases.

Separation and purification of active ingredients in tobacco by free-flow electrophoresis.

The active ingredients from tobacco extracts were continuously separated and purified using a homemade free-flow electrophoresis apparatus. A rectangular free flow electrophoresis device was constructed for the continuous separation and preparation, and the operating conditions of the device were optimized. The fractions obtained from the free-flowing component collection unit were then detected by HPLC and GC-MS. The results showed that a 90% methanol-water solution could maximize the extraction of the active components from tobacco. Chlorogenic acid and nicotine were enriched in three and four of 24 fractions, respectively, after free-flow isoelectric focusing electrophoresis. 2-Hydroxy-2-cyclopentene-1-one, 1-(2-methyl-1,3-oxathiolan-2-yl) ethanone, nornicotine, cotinine, and scopolamine were separated and enriched synchronously. Overall, the use of free-flow electrophoresis technology for the separation and purification of the active substances in tobacco can improve the comprehensive utilization rate of tobacco.

The impact of the synergistic effect of SO2 and PM2.5/PM10 on obstructive lung disease in subtropical Taiwan.

Background: Chronic Obstructive lung diseases (COPD) are complex conditions influenced by various environmental, lifestyle, and genetic factors. Ambient air pollution has been identified as a potential risk factor, causing 4.2 million deaths worldwide in 2016, accounting for 25% of all COPD-related deaths and 26% of all respiratory infection-related deaths. This study aims to evaluate the associations among chronic lung diseases, air pollution, and meteorological factors. Methods: This cross-sectional study obtained data from the Taiwan Biobank and Taiwan Air Quality Monitoring Database. We defined obstructive lung disease as patients with FEV1/FVC < 70%. Descriptive analysis between spirometry groups was performed using one-way ANOVA and the chi-square or Fisher's exact test. A generalized additive model (GAM) was used to evaluate the relationship between SO2 and PM2.5/PM10 through equations and splines fitting. Results: A total of 2,635 participants were enrolled. Regarding environmental factors, higher temperature, higher relative humidity, and lower rainfall were risk factors for obstructive lung disease. SO2 was positively correlated with PM10 and PM2.5, with correlation coefficients of 0.53 (p < 0.0001) and 0.52 (p < 0.0001), respectively. Additionally, SO2 modified the relative risk of obstructive impairment for both PM10 [ß coefficient (ß) = 0.01, p = 0.0052] and PM2.5 (ß = 0.01, p = 0.0155). Further analysis per standard deviation (per SD) increase revealed that SO2 also modified the relationship for both PM10 (ß = 0.11, p = 0.0052) and PM2.5 (ß = 0.09, p = 0.0155). Our GAM analysis showed a quadratic pattern for SO2 (per SD) and PM10 (per SD) in model 1, and a quadratic pattern for SO2 (per SD) in model 2. Moreover, our findings confirmed synergistic effects among temperature, SO2 and PM2.5/PM10, as demonstrated by the significant associations of bivariate (SO2 vs. PM10, SO2 vs. PM2.5) thin-plate smoothing splines in models 1 and 2 with obstructive impairment (p < 0.0001). Conclusion: Our study showed high temperature, humidity, and low rainfall increased the risk of obstructive lung disease. Synergistic effects were observed among temperature, SO2, and PM2.5/PM10. The impact of air pollutants on obstructive lung disease should consider these interactions.

Research on the development methodology for clinical practice guidelines for organic integration of traditional Chinese and Western medicine.

Integrated traditional Chinese medicine (TCM) and Western medicine (WM) is a new medical science grounded in the knowledge bases of both TCM and WM, which then forms a unique modern medical system in China. Integrated TCM and WM has a long history in China, and has made important achievements in the process of clinical diagnosis and treatment. However, the methodological defects in currently published clinical practice guidelines limit its development. The organic integration of TCM and WM is a deeper integration of TCM and WM. To realize the progression of "integration" to "organic integration", a targeted and standardized guideline development methodology is needed. Therefore, the purpose of this study is to establish a standardized development procedure for clinical practice guidelines for the organic integration of TCM and WM to promote the systematic integration of TCM and WM research results into clinical practice guidelines in order to achieve optimal results as the whole is greater than the sum of the parts.

Arsenic exposure and lung fibrotic changes-evidence from a longitudinal cohort study and experimental models.

Introduction: Arsenic (As) exposure is associated with lung toxicity and we aim to investigate the effects of arsenic exposure on lung fibrotic changes. Methods: Participants (n= 976) enrolled via a general health survey underwent chest low-dose computed tomography (LDCT), spirometry forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and urinary arsenic examination during 2016 and 2018. Lung fibrotic changes from LDCT were defined. AsLtoL, low arsenic levels in both 2016 and 2018; AsLtoH, low arsenic in 2016 but high levels in 2018; AsHtoL, high arsenic in 2016 but low levels in 2018; AsHtoH, high arsenic levels in both 2016 and 2018. Mice exposed to 0. 0.2mg/L, 2 mg/L, 50 mg/L of sodium arsenite (NaAsO2) through drinking water for 12 weeks and 24 weeks were applied for histological analysis. Cultured lung epithelial cells were exposed to NaAsO2 and the mesenchymal changes were examined. Results: AsHtoH increased the risk (OR= 1.65, 95% CI 1.10, 2.49) of Lung fibrotic positive to positive (reference: Lung fibrotic negative to negative) compared with AsLtoL. Moreover, the predicted mean of FVC and FEV1 in AsHtoH (-0.09 units, 95% CI: -0.27, -0.09; -0.09 units, 95% CI: -0.17, -0.01) and AsLtoH (-0.13 units, 95% CI: -0.30, -0.10; -0.13 units, 95% CI: -0.22, -0.04) was significantly lower than ASLtoL. Significant lung fibrotic changes including the increase of the alveolar septum thickness and collagen fiber deposition were observed upon 2 mg/L NaAsO2 treatment for 12 weeks, and the damage was dose- and time-dependent. In vitro, sodium arsenite treatment promotes the epithelial-mesenchymal transition (EMT)-like changes of the normal human bronchial epithelial cells, including upregulation of several fibrotic and mesenchymal markers (fibronectin, MMP-2, and Snail) and cell migration. Inhibition of reactive oxygen species (ROS) and MMP-2 impaired the arsenic-induced EMT changes. Administration of a flavonoid, apigenin, inhibited EMT in vitro and pulmonary damages in vivo with the reduction of mesenchymal markers. Discussion: we demonstrated that continued exposure to arsenic causes lung fibrosis in humans and mice. Targeting lung epithelial cells EMT is effective on the development of therapeutic strategy. Apigenin is effective in the inhibition of arsenic-induced pulmonary fibrosis and EMT.

Small-diameter PCL/PU vascular graft modified with heparin-aspirin compound for preventing the occurrence of acute thrombosis.

The occurrence of acute thrombosis, directly related to platelet aggregation and coagulant system, is a considerable reason for the failure of small-diameter vascular grafts. Heparin is commonly used as a functional molecule for graft modification due to the strong anticoagulant effect. Unfortunately, heparin cannot directly resist the adhesion and aggregation of platelets. Therefore, we have prepared a heparin-aspirin compound by coupling heparin with aspirin, an antiplatelet drug, and covalently grafted it onto the surface of polycaprolactone/polyurethane composite tube. In this way, the graft not only showed a dual function of both anticoagulation and antiplatelet, but also effectively avoided the rapid drug release and excessive toxicity to other organs caused by simple blending the medicine with material matrix. The compound retained the original function of heparin, showing good hydrophilicity and biocompatibility, which could promote the adhesion and proliferation of endothelial cells (ECs) and facilitate the process of tissue regeneration. What's more, the compound showed more effective than heparin in reducing platelet activation and preventing thrombosis. The graft modified by this compound maintained completely unobstructed for one month of implantation, while severe obstruction or stenosis occurred in PCL/PU and PCL/PU-Hep lumen at the first week, verifying the effect of the compound on preventing acute thrombosis. In general, this study proposed a designing method for small-diameter vascular graft which could prevent acute thrombosis and promote intimal construction.

Association between ambient air pollutant interaction with kidney function in a large Taiwanese population study.

The associations and interactions between kidney function and other air pollutants remain poorly defined. Therefore, the aim of this study was to evaluate associations among air pollutants, including particulate matter (PM) with a diameter ≤ 2.5 µm (PM2.5), PM10 (PM with a diameter ≤ 10 µm), carbon monoxide (CO), nitrogen oxide (NO), nitrogen oxides (NOx), sulfur dioxide (SO2), and ozone (O3) with kidney function, and explore interactions among these air pollutants on kidney function. We used the Taiwan Air Quality Monitoring and Taiwan Biobank databases to derive data on community-dwelling individuals in Taiwan and daily air pollution levels, respectively. We enrolled 26,032 participants. Multivariable analysis showed that high levels of PM2.5, PM10, O3 (all p < 0.001), and SO2 (p = 0.001) and low levels of CO, NO (both p < 0.001), and NOx (p = 0.047) were significantly correlated with low estimated glomerular filtration rate (eGFR). With regard to negative effects, the interactions between PM2.5 and PM10 (p < 0.001), PM2.5 and PM10 (p < 0.001), PM2.5 and SO2, PM10 and O3 (both p = 0.025), PM10 and SO2 (p = 0.001), and O3 and SO2 (p < 0.001) on eGFR were significantly negatively. High PM10, PM2.5, O3, and SO2 were associated with a low eGFR, whereas high CO, NO, and NOx were associated with a high eGFR. Furthermore, negative interactions between PM2.5 and PM10, O3 and SO2, PM10 and O3, PM2.5 and SO2, and PM10 and SO2 on eGFR were observed. The findings of this study have important implications for public health and environmental policy. Specifically, the results of this study may be useful in individuals and organizations to take action to reduce air pollution and promote public health.

Arsenic exposure associated with lung interstitial changes in non-smoking individuals living near a petrochemical complex: A repeated cross-sectional study.

Arsenic exposure is associated with airway inflammation and decreased lung function tests. Whether arsenic exposure associated with lung interstitial changes remains unknown. We conducted this population-based study in southern Taiwan during 2016 and 2018. Our study recruited individuals aged over 20 years, residing in the vicinity of a petrochemical complex and with no history of cigarette smoking. In both the 2016 and 2018 cross-sectional studies, we conducted chest low-dose computed tomography (LDCT) scans, as well as urinary arsenic and blood biochemistry analyses. Lung interstitial changes included lung fibrotic changes that were defined as the presence of curvilinear or linear densities, fine lines, or plate opacity in specific lobes; additionally, other interstitial changes were defined as the presence of ground-glass opacity (GGO) or bronchiectasis on the LDCT images. In both cross-sectional studies conducted in 2016 and 2018, participants with lung fibrotic changes exhibited a statistically significant increase in the mean urinary arsenic concentrations compared to those without fibrotic changes (geometric mean = 100.1 vs. 82.8 µg/g creatinine, p < 0.001 for cross-sectional study 2016, and geometric mean = 105.6 vs. 71.0 µg/g creatinine, p < 0.001 for cross-sectional study 2018). After controlling for age, gender, body mass index, platelet counts, hypertension, aspartate aminotransferase, cholesterol, HbA1c, and educational levels, we observed a significant positive association between a unit increase in log urinary arsenic concentrations and the risk of lung fibrotic changes in both cross-sectional study 2016 (odds ratio [OR] = 1.40, 95% confidence interval [CI] = 1.04-1.90, p = 0.028) and cross-sectional study 2018 (OR = 3.03, 95% CI = 1.38-6.63, p = 0.006). Our study did not find a significant association between arsenic exposure and bronchiectasis or GGO. It is imperative for the government to take significant measures to reduce arsenic exposure levels among individuals living near petrochemical complexes.

Low Lung Function Is Associated with Low Baseline Calcaneus Ultrasound T-Score but a Slow Decline in T-Score in a Taiwanese Follow-Up Population with No History of Smoking, Bronchitis, Emphysema, or Asthma.

Osteoporosis is a common disease, and the prevalence is increasing in patients with chronic respiratory diseases, with important implications with regard to fractures, hospitalization, and death. Due to inconsistent data and a lack of large cohort follow-up studies on the association between lung function and osteoporosis, the aim of this study was to investigate this issue. We enrolled and followed for a median of 4 years a total of 9059 participants with no history of smoking, bronchitis, emphysema, or asthma from the Taiwan Biobank. Spirometry data, including forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC), were used to assess lung function. Changes in the calcaneus ultrasound T-score (ΔT-score) were calculated as follow-up T-score-baseline T-score. A ΔT-score ≤ -3 (median value of ΔT-score) meant a fast decline in T-score. Multivariable analysis showed that lower values of FEV1 (ß, 0.127, p < 0.001), FVC (ß, 0.203, p < 0.001), and FEV1/FVC (ß, 0.002, p = 0.013) were significantly associated with a low baseline T-score. In addition, after follow-up, higher values of FEV1 (odds ratio (OR), 1.146, p = 0.001), FVC (OR, 1.110, p = 0.042), and FEV1/FVC (OR, 1.004, p = 0.002) were significantly associated with ΔT-score ≤ -3. FEV1/FVC < 70% (OR, 0.838, p < 0.001) was significantly associated with ΔT-score ≤ -3. In conclusion, lower FEV1, FVC, and FEV1/FVC were associated with a low baseline T-score, and higher FEV1, FVC, and FEV1/FVC were associated with a rapid decline in T-score in follow-up. This suggests that lung disease may be associated with bone mineral density in the Taiwanese population with no history of smoking, bronchitis, emphysema, or asthma. Further research is needed to establish causality.

Blood lead (Pb) is associated with lung fibrotic changes in non-smokers living in the vicinity of petrochemical complex: a population-based study.

Lead (Pb) is a toxic metal that has been extensively used in various industrial processes, and it persists in the environment, posing a continuous risk of exposure to humans. This study investigated blood lead levels in participants aged 20 years and older, who resided in Dalinpu for more than two years between 2016 to 2018, at Kaohsiung Municipal Siaogang Hospital. Graphite furnace atomic absorption spectrometry was used to analyze the blood samples for lead levels, and the LDCT (Low-Dose computed tomography) scans were interpreted by experienced radiologists. The blood lead levels were divided into quartiles, with Q1 representing levels of ≤1.10 µg/dL, Q2 representing levels of >1.11 and ≤1.60 µg/dL, Q3 representing levels of >1.61 and ≤2.30 µg/dL, and Q4 representing levels of >2.31 µg/dL. Individuals with lung fibrotic changes had significantly higher (mean ± SD) blood lead levels (1.88±1.27vs. 1.72±1.53 µg/dl, p< 0.001) than those with non-lung fibrotic changes. In multivariate analysis, we found that the highest quartile (Q4: >2.31 µg/dL) lead levels (OR: 1.36, 95% CI: 1.01-1.82; p= 0.043) and the higher quartile (Q3: >1.61 and ≤2.30 µg/dL) (OR: 1.33, 95% CI: 1.01-1.75; p= 0.041) was significantly associated with lung fibrotic changes compared with the lowest quartile (Q1: ≤1.10 µg/dL) (Cox and Snell R2, 6.1 %; Nagelkerke R2, 8.5 %). The dose-response trend was significant (Ptrend= 0.030). Blood lead exposure was significantly associated lung fibrotic change. To prevent lung toxicity, it is recommended to maintain blood lead levels lower than the current reference value.

Association between air pollutants with calcaneus ultrasound T-score change in a large Taiwanese population follow-up study.

Exposure to ambient air pollution has been associated with increased rates of mortality and morbidity and a shorter life expectancy. Few studies have evaluated the associations between air pollution and change in calcaneus ultrasound T-score (∆T-score). Therefore, in this longitudinal study, we explored these associations in a large group of Taiwanese participants. We used data from the Taiwan Biobank database and Taiwan Air Quality Monitoring Database, which contains detailed daily data on air pollution. We identified 27,033 participants in the Taiwan Biobank database who had both baseline and follow-up data. The median follow-up period was 4 years. The studied ambient air pollutants included particulates of 2.5 µm or less (PM2.5), particulates of 10 µm or less (PM10), ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), nitric oxide (NO), nitrogen dioxide (NO2), and nitrogen oxide (NOx). Multivariable analysis showed that PM2.5 (ß, -0.003; 95% confidence interval (CI), -0.004 to -0.001; p < 0.001), PM10 (ß, -0.005; 95% CI, -0.006 to -0.004, p < 0.001), O3 (ß, -0.008; 95% CI, -0.011 to -0.004; p < 0.001), and SO2 (ß, -0.036; 95% CI, -0.052 to -0.020; p < 0.001) were negatively associated with ∆T-score, and that CO (ß, 0.344; 95% CI, 0.254, 0.433; p < 0.001), NO (ß, 0.011; 95% CI, 0.008 to 0.015; p < 0.001), NO2 (ß, 0.011; 95% CI, 0.008 to 0.014; p < 0.001), and NOx (ß, 0.007; 95% CI, 0.005 to 0.009; p < 0.001) were positively significantly associated with ∆T-score. Furthermore, PM2.5 and SO2 (ß, -0.014; 95% CI, -0.016 to -0.013; p < 0.001) and PM10 and SO2 (ß, -0.008; 95% CI, -0.009 to -0.007; p < 0.001) had synergistic negative effects on ∆T-score. In conclusion, we found that high PM2.5, PM10, O3, and SO2 were associated with a rapid decline in T-score, whereas high CO, NO, NO2, and NOx were associated with a slow decline in T-score. Furthermore, PM2.5 and SO2 and PM10 and SO2 had synergistic negative effects on ∆T-score, causing an acceleration in T-score decline. These findings may be helpful when developing policies on air pollution regulation.