Fear, Stress, Susceptibility, and Problematic Social Media Use Explain Motivation for COVID-19 Preventive Behaviors Among Patients With Stroke and Their Caregivers.

The COVID-19 pandemic presented significant challenges for individuals who experienced stroke and their caregivers. It is essential to understand the factors affecting preventive behavior in these populations. Therefore, the present study examined the factors that influenced COVID-19 preventive behavior and motivation for COVID-19 vaccine uptake among patients with stroke and their caregivers. A cross-sectional study comprising 191 participants (81 patients with stroke and 110 caregivers) was carried out. Participants completed a survey assessing fear of COVID-19, stress, perceived susceptibility, problematic social media use, preventive behaviors, and motivation for vaccine uptake. Statistical analyses included descriptive statistics, Pearson correlations, and multiple linear regressions. Motivation for COVID-19 vaccine uptake was significantly positively correlated with problematic social media use (r = 0.225, P = .002), perceived susceptibility (r = 0.197, P = .008), and fear of COVID-19 (r = 0.179, P = .015), but negatively correlated with stress (r = -0.189, P = .010). Caregivers, compared to patients, showed a lower level of preventive behavior (standardized coefficient = -0.23, P = .017). Furthermore, higher levels of fear were associated with increased preventive behavior (standardized coefficient = 0.22, P = .006), while greater stress correlated with lower preventive behavior (standardized coefficient = -0.38, P < .001). Among patients with stroke and their caregivers, motivation of COVID-19 vaccine uptake and preventive behaviors were influenced by factors such as fear, perceived susceptibility, social media use, and stress. By using strategies such as targeted education, support, and communication campaigns, healthcare providers and policymakers may be able to enhance the well-being of patients with stroke and their caregivers during future pandemics.

Evaluating groundwater ecosystem dynamics in response to post in-situ remediation of mixed chlorinated volatile organic compounds (CVOCs): An insight into microbial community resilience, adaptability, and metabolic functionality for sustainable remediation and ecosystem restoration.

The in-situ remediation of groundwater contaminated with mixed chlorinated volatile organic compounds (CVOCs) has become a significant global research interest. However, limited attention has been given in understanding the effects of these remediation efforts on the groundwater microbial communities, which are vital for maintaining ecosystem health through their involvement in biogeochemical cycles. Hence, this study aimed to provide valuable insights into the impacts of in-situ remediation methods on groundwater microbial communities and ecosystem functionality, employing high-throughput sequencing coupled with functional and physiological assays. The results showed that both bioremediation and chemical remediation methods adversely affected microbial diversity and abundance compared to non-polluted sites. Certain taxa such as Pseudomonas, Acinetobacter, and Vogesella were sensitive to these remediation methods, while Aquabacterium exhibited greater adaptability. Functional annotation unveiled the beneficial impact of bioremediation on the sulfur cycle and specific taxa such as Cellvibrio, Massilia, Algoriphagus, and Flavobacterium which showed a significant positive relationship with dark oxidation of sulfur compounds. In contrast, chemical remediation showed adverse impacts on the nitrogen cycle with a reduced abundance of nitrogen and nitrate respiration along with a reduced utilization of amines (nitrogen rich substrate). The findings of this study offer valuable insights into the potential impacts of in-situ remediation methods on groundwater microbial communities and ecosystem functionality, emphasizing the need for meticulous consideration to ensure the implementation of effective and sustainable remediation strategies that safeguard ecosystem health and function.

Comparing Artificial Intelligence-Enabled Electrocardiogram Models in Identifying Left Atrium Enlargement and Long-term Cardiovascular Risk.

BACKGROUND: The role of P-wave in identifying left atrial enlargement (LAE) with the use of artificial intelligence (AI)-enabled electrocardiography (ECG) models is unclear. It is also unknown if AI-enabled single-lead ECG could be used as a diagnostic tool for LAE surveillance. We aimed to build AI-enabled P-wave and single-lead ECG models to identify LAE using sinus rhythm (SR) and non-SR ECGs, and compare the prognostic ability of severe LAE, defined as left atrial diameter ≥ 50 mm, assessed by AI-enabled ECG models vs echocardiography. METHODS: This retrospective study used data from 382,594 consecutive adults with paired 12-lead ECG and echocardiography performed within 2 weeks of each other at Chang Gung Memorial Hospital. UNet++ was used for P-wave segmentation. ResNet-18 was used to develop deep convolutional neural network-enabled ECG models for discriminating LAE. External validation was performed with the use of data from 11,753 patients from another hospital. RESULTS: The AI-enabled 12-lead ECG model outperformed other ECG models for classifying LAE, but the single-lead ECG models also showed excellent performance at a left atrial diameter cutoff of 50 mm. AI-enabled ECG models had excellent and fair discrimination on LAE using the SR and the non-SR data set, respectively. Severe LAE identified by AI-enabled ECG models was more predictive of future cardiovascular disease than echocardiography; however, the cumulative incidence of new-onset atrial fibrillation and heart failure was higher in patients with echocardiography-severe LAE than with AI-enabled ECG-severe LAE. CONCLUSIONS: P-Wave plays a crucial role in discriminating LAE in AI-enabled ECG models. AI-enabled ECG models outperform echocardiography in predicting new-onset cardiovascular diseases associated with severe LAE.

Microbial induced carbonate precipitation for remediation of heavy metals, ions and radioactive elements: A comprehensive exploration of prospective applications in water and soil treatment.

Improper disposal practices have caused environmental disruptions, possessing by heavy metal ions and radioactive elements in water and soil, where the innovative and sustainable remediation strategies are significantly imperative in last few decades. Microbially induced carbonate precipitation (MICP) has emerged as a pioneering technology for remediating contaminated soil and water. Generally, MICP employs urease-producing microorganisms to decompose urea (NH2CONH2) into ammonium (NH4+and carbon dioxide (CO2), thereby increasing pH levels and inducing carbonate precipitation (CO32-), and effectively removing remove contaminants. Nonetheless, the intricate mechanism underlying heavy metal mineralization poses a significant challenge, constraining its application in contaminants engineering, particularly in the context of prolonged heavy metal leaching over time and its efficacy in adverse environmental conditions. This review provides a comprehensive idea of recent development of MICP and its application in environmental engineering, examining metabolic pathways, mineral precipitation mechanisms, and environmental factors as well as providing future perspectives for commercial utilization. The use of ureolytic bacteria in MICP demonstrates cost-efficiency, environmental compatibility, and successful pollutant abatement over tradition bioremediation techniques, and bio-synthesis of nanoparticles. limitations such as large-scale application, elevated Ca2+levels in groundwater, and gradual contaminant release need to be overcome. The possible future research directions for MICP technology, emphasizing its potential in conventional remediation, CO2 sequestration, bio-material synthesis, and its role in reducing environmental impact for long-term economic benefits.

Problematic Gaming in Malaysian University Students: Translation and Psychometric Evaluation of the Malay Language Versions of Gaming Disorder Test and Gaming Disorder Scale for Young Adults.

As research on gaming disorder (GD) is growing globally, the need for a valid and reliable instrument to assess GD has become crucial. Therefore, the present cross-sectional study translated and evaluated the psychometric properties of Gaming Disorder Test (GDT) and Gaming Disorder Scale for Young Adults (GADIS-YA) into Malay language versions. The sample comprised 624 university students (females = 75.6%; mean age = 22.27 years) recruited via an online survey from May to August 2022, using a convenience sampling method. Participants completed both GDT and GADIS-YA scales and other relevant measures including Bergen Social Media Addiction Scale (BSMAS), Internet Gaming Disorder Scale-Short Form (IGDS9-SF), and time spent on social media and gaming. Results showed that both instruments reported satisfactory internal consistency, and confirmatory factor analysis supported the one-factor structure for GDT and two-factor structure for GADIS-YA. Both scales were strongly correlated with each other and with the IGDS9-SF, BSMAS, and time spent on social media and gaming, supporting concurrent validity. Measurement invariance of both scales was confirmed across gender and gaming time. These findings suggest that the Malay versions of GDT and GADIS-YA are reliable and valid measures of problematic gaming among Malaysian university students.

Development of a Machine Learning Model to Predict the Use of Surgery in Patients With Rheumatoid Arthritis.

OBJECTIVE: One in five patients with rheumatoid arthritis (RA) rely on surgery to restore joint function. However, variable response to disease-modifying antirheumatic drugs (DMARDs) complicates surgical planning, and it is difficult to predict which patients may ultimately require surgery. We used machine learning to develop predictive models for the likelihood of undergoing an operation related to RA and which type of operation patients who require surgery undergo. METHODS: We used electronic health record data to train two extreme gradient boosting machine learning models. The first model predicted patients' probabilities of undergoing surgery ≥5 years after their initial clinic visit. The second model predicted whether patients who underwent surgery would undergo a major joint replacement versus a less intensive procedure. Predictors included demographics, comorbidities, and medication data. The primary outcome was model discrimination, measured by area under the receiver operating characteristic curve (AUC). RESULTS: We identified 5,481 patients, of whom 278 (5.1%) underwent surgery. There was no significant difference in the frequency of DMARD or steroid prescriptions between patients who did and did not have surgery, though nonsteroidal anti-inflammatory drug prescriptions were more common among patients who did have surgery (P = 0.03). The model predicting use of surgery had an AUC of 0.90 ± 0.02. The model predicting type of surgery had an AUC of 0.58 ± 0.10. CONCLUSIONS: Predictive models using clinical data have the potential to facilitate identification of patients who may undergo rheumatoid-related surgery, but not what type of procedure they will need. Integrating similar models into practice has the potential to improve surgical planning.

Deciphering microbial communities and their unique metabolic repertoire across rock-soil-plant continuum in the Dayoukeng fumarolic geothermal field of the Tatun Volcano Group.

High temperature and sulfur concentrations in geothermal sulfur fumaroles host unique microbial ecosystems with niche-specific metabolic diversity and physiological functions. In this study, the microbial communities and their functionalities associated with the Dayoukeng geothermal field and the rock-soil-plant continuum were investigated to underpin the microbial modulation at different distances from the fumaroles source. At the phylum level, Bacteroidota, Planctomycetota, Armatimonadota, and Patescibacteria were abundant in plant samples; Elusimicrobiota and Desulfobacterota were in the rock samples while Nitrospirota, Micrarchaeota, and Deinococcota were dominant in the soil samples. Acidophilic thermophiles were enriched in samples within close proximity to the fumaroles, primarily at a distance of 1 m. The sulfur and iron-oxidizing acidophilic bacterial genera such as Acidothiobacillus and Sulfobacillus were abundant in the rock samples. The thermoacidophilic archaeon Acidianus and acidophilic bacteria Acidiphilium were abundant in the soil samples. Additionally, Thermosporothrix and Acidothermus were found abundant in the plant samples. The results of the functional annotation indicated that dark sulfur oxidation, iron oxidation, and hydrogen oxidation pathways were abundant in the soil samples up to 1 m from the fumaroles, while methanogenic and fermentation pathways were more prevalent in the soil samples located 10 m from the fumaroles. Interestingly, the results of this study indicated a higher microbial richness and abundance of acidophilic communities in the soils and plants compared to the rocks of the DYK fumarolic geothermal field.

Differential item functioning for the Tendency of Avoiding Physical Activity and Sport Scale across two subculture samples: Taiwanese and mainland Chinese university students.

Aims: The aims of the study were to examine the differential item functioning (DIF) of the Tendency of Avoiding Physical Activity and Sport Scale (TAPAS) among three subgroups (gender, weight status, and region) and to test the construct and concurrent validities of the scale. Methods: Using an online survey, university students (608 Taiwanese and 2319 mainland Chinese) completed the TAPAS. Rasch analysis examined if all the 10 TAPAS items fitted the same construct and displayed no substantial DIF across three subgroups: gender (male vs. female), weight status (overweight vs. non-overweight), and region (Taiwan vs. China). Concurrent validity was examined using the scores on the Weight Self-Stigma Questionnaire (WSSQ) and Weight Bias Internalization Scale (WBIS). Results: All TAPAS items, except for Item 10 ("Prefer to participate in physical activity in a more private setting"), fitted the same construct. None of the TAPAS items displayed DIF in any of the subgroups except for Item 10 across participants from Taiwan and China (DIF contrast = -1.41). Conclusion: The TAPAS can appropriately assess the tendency to avoid physical activity and sport among both Taiwanese and mainland Chinese university students. However, Item 10 may need to be further examined.

Machine learning-based prediction of acute mortality in emergency department patients using twelve-lead electrocardiogram.

Background: The risk of mortality is relatively high among patients who visit the emergency department (ED), and stratifying patients at high risk can help improve medical care. This study aimed to create a machine-learning model that utilizes the standard 12-lead ECG to forecast acute mortality risk in ED patients. Methods: The database included patients who visited the EDs and underwent standard 12-lead ECG between October 2007 and December 2017. A convolutional neural network (CNN) ECG model was developed to classify survival and mortality using 12-lead ECG tracings acquired from 345,593 ED patients. For machine learning model development, the patients were randomly divided into training, validation and testing datasets. The performance of the mortality risk prediction in this model was evaluated for various causes of death. Results: Patients who visited the ED and underwent one or more ECG examinations experienced a high incidence of 30-day mortality [18,734 (5.42%)]. The developed CNN model demonstrated high accuracy in predicting acute mortality (hazard ratio 8.50, 95% confidence interval 8.20-8.80) with areas under the receiver operating characteristic (ROC) curve of 0.84 for the 30-day mortality risk prediction models. This CNN model also demonstrated good performance in predicting one-year mortality (hazard ratio 3.34, 95% confidence interval 3.30-3.39). This model exhibited good predictive performance for 30-day mortality not only for cardiovascular diseases but also across various diseases. Conclusions: The machine learning-based ECG model utilizing CNN screens the risks for 30-day mortality. This model can complement traditional early warning scoring indexes as a useful screening tool for mortality prediction.

Validation of the Thai Assessment of Criteria for Specific Internet-use Disorders (ACSID-11) among young adults.

BACKGROUND: The Assessment of Criteria for Specific Internet-use Disorders (ACSID-11) is a consistent and comprehensive instrument to assess symptoms of specific internet-use disorders including those related to gaming, shopping, pornography use disorder, social networks use and gambling considering criteria in the eleventh revision of the International Classification of Diseases (ICD-11). However, to date, there is little evidence supporting instruments assessing major types of specific internet use disorders in Thailand. The aim of this present study was to assess the psychometric properties of the ACSID-11 among Thai young adults. METHODS: A total of 612 participants were recruited. A confirmatory factor analysis (CFA) examined construct validity of the ACSID-11. Cronbach's α and McDonald's ω were used to assess reliability of the ACSID-11. Pearson correlations examined relationships between ACSID-11 domains and Internet Gaming Disorder Scale-Short Form (IGDS9-SF) scores. RESULTS: The CFA supported validity of the Thai version of the ACSID-11 and a four-factor structure. Specific domains of the Thai ACSID-11, particularly gaming, were positively and significantly correlated with IGDS9-SF scores. CONCLUSIONS: Data indicate that the Thai version of the ACSID-11 is a valid and reliable instrument to assess major types of specific internet use disorders. Additional studies are needed to further examine the validity and reliability of the Thai ACSID-11.

Sleep Quality and Self-Stigma Mediate the Association Between Problematic Use of Social Media and Quality of Life Among People With Schizophrenia in Taiwan: A Longitudinal Study.

OBJECTIVE: Problematic use of social media (PUSM) may affect sleep quality and self-stigma in people with schizophrenia and consequently reduce their quality of life (QoL). This longitudinal study investigated if sleep quality and self-stigma mediated relationships between PUSM and QoL. METHODS: One-hundred-and-ninety-three outpatients with schizophrenia were recruited from a psychiatric center in Taiwan from April 2019 to August 2021 and participated in a longitudinal study at intervals of three months between measurements. QoL was assessed using the World Health Organization Quality of Life Questionnaire Brief Version; sleep quality using the Pittsburgh Sleep Quality Index; self-stigma using the Self-Stigma Scale-Short; and PUSM using the Bergen Social Media Addiction Scale. Via SPSS 20.0, general estimating equation models assessed temporal associations between variables. Via R software, mediating effects of self-stigma and sleep quality were examined through Monte Carlo simulations with 20,000 repetitions. RESULTS: Mean scores of physical, psychological, social and environmental QoL ranged from 11.86 to 13.02. Mean scores of sleep quality and self-stigma were 9.1±4.5 and 2.2±0.8, respectively. Sleep quality and self-stigma were directly related to QoL (p<0.001) and mediated indirect relationships between PUSM and all components of QoL with a range of 95% confidence intervals spanning from -0.0591 to -0.0107 for physical QoL; -0.0564 to -0.0095 for psychological QoL; -0.0292 to -0.0035 for social QoL; and -0.0357 to -0.0052 for environmental QoL. CONCLUSION: Sleep quality and self-stigma mediated relationships between PUSM and QoL in people with schizophrenia. Developing interventions targeting PUSM, sleep, and self-stigma may help improve QoL in people with schizophrenia.

Is moderate resistance training adequate for older adults with sarcopenia? A systematic review and network meta-analysis of RCTs.

BACKGROUND: Resistance training (RT) and nutritional supplementation are recommended for the management of sarcopenia in older adults. However, optimal RT intensity for the treatment of sarcopenia has not been well investigated. METHODS: This network meta-analysis aims to determine the comparative effectiveness of interventions for sarcopenia, taking RT intensity into consideration. RT intensity was classified into light-to-moderate intensity RT(LMRT), moderate intensity RT(MRT), and moderate-to-vigorous intensity RT(MVRT) based on percentage of one repetition maximum (%1RM) and/or rating of perceived exertion. RESULTS: A total of 50 RCTs (N = 4,085) were included after screening 3,485 articles. The results confirmed that RT with or without nutrition was positively associated with improved measures of muscle strength and physical performance. Regarding RT intensity, LMRT only demonstrated positive effects on hand grip (aerobic training + LMRT + nutrition: mean difference [MD] = 2.88; 95% credential intervals [CrI] = 0.43,5.32). MRT provided benefits on improvement in the 30-s chair stand test (repetitions) (MRT: MD = 2.98, 95% CrI = 0.35,5.59), timed up and go test (MRT: MD = -1.74, 95% CrI: = -3.34,-0.56), hand grip (MRT: MD = 2.44; 95% CrI = 0.03,5.70), and leg press (MRT: MD = 8.36; 95% CrI = 1.87,13.4). MVRT also improved chair stand test repetitions (MVRT: MD = 5.64, 95% CrI = 0.14,11.4), gait speed (MVRT + nutrition: MD = 0.21, 95% CrI = 0.003,0.48), appendicular skeletal muscle index (MVRT + nutrition: MD = 0.25, 95% CrI = 0.01,0.5), and leg press (MVRT: MD = 14.7, 95% CrI: 5.96,22.4; MVRT + nutrition: MD = 17.8, 95% CrI: 7.55,28.6). CONCLUSION: MVRT had greater benefits on muscle mass, lower extremity strength, and physical performance compared to MRT. Increasing RT intensity may be recommended for sarcopenic older adults.

Comprehensive Analysis of Risk Factors for Bronchopulmonary Dysplasia in Preterm Infants in Taiwan: A Four-Year Study.

Bronchopulmonary dysplasia (BPD) is a major respiratory condition mainly affecting premature infants. Although its occurrence is global, risk factors may differ regionally. This study, involving 3111 infants with birth weight ≤ 1500 gm or gestational age (GA) < 30 weeks, aimed to identify risk factors for BPD and BPD/mortality in Taiwan using data from the Taiwan Neonatal Network. The BPD criteria were based on the National Institute of Child Health and Human Development standards. Average GA was 27.5 weeks, with 23.7% classified as small for GA (SGA). Multivariate analysis highlighted low GA, low birth weight, and other perinatal factors as significant risk indicators for BPD. For moderate-to-severe BPD, additional risk factors included male gender and SGA, endotracheal intubation (ETT) or cardiopulmonary cerebral resuscitation (CPCR) in initial resuscitation. In the moderate-to-severe BPD/death group, SGA and ETT or CPCR in initial resuscitation remained the only additional risk factors. The study pinpoints male gender, SGA and ETT or CPCR as key risk factors for moderate-to-severe BPD/death in low-birth-weight infants in Taiwan, offering a basis for focused interventions and further research.

Insight interactions of engineered nanoparticles with aquatic higher plants for phytoaccumulation, phytotoxicity, and phytoremediation applications: A review.

With the growing age of human civilization, industrialization has paced up equally which is followed by the innovation of newer concepts of science and technology. One such example is the invention of engineered nanoparticles and their flagrant use in widespread applications. While ENPs serve their intended purposes, they also disrupt the ecological balance by contaminating pristine aquatic ecosystems. This review encompasses a comprehensive discussion about the potent toxicity of ENPs on aquatic ecosystems, with a particular focus on their impact on aquatic higher plants. The discussion extends to elucidating the fate of ENPs upon release into aquatic environments, covering aspects ranging from morphological and physiological effects to molecular-level phytotoxicity. Furthermore, this level of toxicity has been correlated with the determination of competent plants for the phytoremediation process towards the mitigation of this ecological stress. However, this review further illustrates the path of future research which is yet to be explored. Determination of the genotoxicity level of aquatic higher plants could explain the entire process comprehensively. Moreover, to make it suitable to be used in natural ecosystems phytoremediation potential of co-existing plant species along with the presence of different ENPs need to be evaluated. This literature will undoubtedly offer readers a comprehensive understanding of the stress induced by the irresponsible release of engineered nanoparticles (ENP) into aquatic environments, along with insights into the resilience characteristics of these pristine ecosystems.

Measurement Invariance and Psychometric Evaluation of the Tendency to Avoid Physical Activity and Sport Scale (TAPAS) Among Mainland Chinese University Students.

Introduction: Preventative factors in young people's physical inactivity require further understanding, including related psychosocial factors (eg, body image and weight stigma). The Tendency to Avoid Physical Activity and Sport Scale (TAPAS) is a recently developed instrument to address this issue and the present study examined its psychometric properties among Chinese university students particularly in relation to patterns across sex, physical activity (PA) level, and weight status. Methods: Using a convenience sample of 3142 students (mean age = 19.8 years; 56% female) in mainland China, data were collected using an online survey between August and October 2022. Psychometric instruments including the Weight Bias Internalization Scale, 21-item Depression, Anxiety and Stress Scale, and International Physical Activity Questionnaire Short Form were administered along with the TAPAS to assess convergent and discriminant validity. Multi-group confirmatory factor analysis (CFA) assessed the measurement invariance across specific groups. Results: The unidimensional structure of the scale was confirmed through CFA (CFI=0.995; RMSEA=0.046). All configural, metric and scalar models of invariance indicated that the scale was invariant across sex, PA level, and weight status. Acceptable convergent and discriminant validity for the scale were found. Conclusion: The TAPAS is a suitable instrument to assess body image and weight stigma concerns for avoiding physical activity and sport among Chinese university students.

A review on the effects of discharging conventionally treated livestock waste to the environmental resistome.

Globally, animal production has developed rapidly as a consequence of the ongoing population growth, to support food security. This has consequently led to an extensive use of antibiotics to promote growth and prevent diseases in animals. However, most antibiotics are not fully metabolized by these animals, leading to their excretion within urine and faeces, thus making these wastes a major reservoir of antibiotics residues, antibiotic resistance genes (ARGs) and antibiotic resistant bacteria (ARB) in the environment. Farmers normally depend on conventional treatment methods to mitigate the environmental impact of animal waste; however, these methods are not fully efficient to remove the environmental resistome. The present study reviewed the variability of residual antibiotics, ARB, as well as ARGs in the conventionally treated waste and assessed how discharging it could increase resistome in the receiving environments. Wherein, considering the efficiency and environmental safety, an addition of pre-treatments steps with these conventional treatment methods could enhance the removal of antibiotic resistance agents from livestock waste.

Comparison of antibiotic-resistant Escherichia coli and extra-intestinal pathogenic E. coli from main river basins under different levels of the sewer system development.

Antimicrobial-resistant Escherichia coli in the aquatic environments is considered a strong indicator of sewage or animal waste contamination and antibiotic pollution. Sewer construction and wastewater treatment plant (WWTP) infrastructure may serve as concentrated point sources of contamination of antibiotic-resistant bacteria and antibiotic resistance genes. In this study, we focused on the distribution of antimicrobial-resistant E. coli in two rivers with large drainage areas and different urbanisation levels. E. coli from Kaoping River with drainage mainly from livestock farming had higher resistance to antibiotics (e.g. penicillins, tetracyclines, phenicols, aminoglycosides, and sulpha drugs) and presented more positive detection of antibiotic-resistance genes (e.g. ampC, blaTEM, tetA, and cmlA1) than that from Tamsui River. In Kaoping River with a lower percentage of sewer construction nearby (0-30%) in contrast to a higher percentage of sewer construction (55-92%) in Tamsui River, antimicrobial-resistant E. coli distribution was related to livestock farming waste. In Tamsui River, antimicrobial resistant E. coli isolates were found more frequently in the downstream drainage area of WWTPs with secondary water treatment than that of WWTPs with tertiary water treatment. The Enterobacterial Repetitive Intergenic Consensus (ERIC) PCR showed that the fingerprinting group was significantly related to the sampling site (p < 0.01) and sampling date (p < 0.05). By utilising ERIC-PCR in conjunction with antibiotic susceptibility and antibiotic-resistance gene detection, the relationship among different strains of E. coli could be elucidated. Furthermore, we identified the presence of six extra-intestinal pathogenic E. coli isolates and antibiotic-resistant E. coli isolates near drinking water sources, posing a potential risk to public health through community transmission. In conclusion, this study identified environmental factors related to antibiotic-resistant bacteria and antibiotic-resistance gene contamination in rivers during urban development. The results facilitate the understanding of specific management of different waste streams across different urban areas. Periodic surveillance of the effects of WWTPs and livestock waste containing antibiotic-resistant bacteria and antibiotic-resistance genes on river contamination is necessary.

Problematic smartphone use and two types of problematic use of the internet and self-stigma among people with substance use disorders.

BACKGROUND AND AIMS: Guided by the Interaction of Person-Affect-Cognition-Execution (I-PACE) model and a self-stigma framework, this study aimed to investigate relationships between cognitive and affective self-stigma and behavioral self-stigma, problematic use of internet (PUI), and problematic smartphone use (PSU) among people with substance use disorders (SUDs). It also examined mediating roles for affective self-stigma in the relationships between cognitive self-stigma and behavioral self-stigma/PUI/PSU. METHODS: Using a cross-sectional design, 530 participants diagnosed with SUDs in Taiwan were recruited from a psychiatric center in Taiwan. Mediation models were investigated using the Hayes' Process Macro Model 4. RESULTS: Mediation analyses indicated that cognitive self-stigma was directly associated with behavioral self-stigma (p < 0.001), but not with either types of PUI or PSU (p-values ranging from 0.41 to 0.76). Affective self-stigma was directly related to behavioral self-stigma (p < 0.001), two types of PUI, and PSU (ß = 0.24-0.30; all p < 0.001); cognitive self-stigma was indirectly associated with behavioral self-stigma (ß = 0.53; 95  % bootstrapping CI = 0.46, 0.60), two types of PUI, and PSU (ß = 0.20-0.25; 95  % bootstrapping CI = 0.08-0.14, 0.31-0.37) via a mediating effect of affective self-stigma. DISCUSSION AND CONCLUSION: Findings support the I-PACE model in a self-stigma context. The findings also suggest that addressing affective self-stigma may help prevent or reduce behavioral self-stigma, PUI, and PSU among people with SUDs. Longitudinal studies are warranted to investigate over time relationships between self-stigma and PUI/PSU in people with SUDs.

Bacterial community analysis identifies Klebsiella pneumoniae as a native symbiotic bacterium in the newborn Protobothrops mucrosquamatus.

BACKGROUND: The study of the native microbiome of organisms is crucial. The connection between the native microbiome and the host affects the formation of the innate immune system and the organism's growth. However, the native microbiome of newborn venomous snakes has not been reported. Therefore, we aimed to determine the oral and skin microbiomes of newborn Protobothrops mucrosquamatus. RESULTS: We performed 16 S full-length sequencing on 14 samples collected from 7 newborn P. mucrosquamatus individuals, specifically targeting their oral and skin microbiomes. In terms of the oral and skin microbiome, the main species were Klebsiella pneumoniae lineages. According to subspecies/species analysis, the proportion from highest to lowest was K. quasipneumoniae subsp. similipneumoniae, K. pneumoniae subsp. pneumoniae, and K. pneumoniae subsp. rhinoscleromatis. These three bacteria accounted for 62.5% and 85% of the skin and oral activity, respectively. The oral microbiome of newborn P. mucrosquamatus did not comprise common bacteria found in snakebite wounds or oral cultures in adult snakes. Therefore, the source of other microbiomes in the oral cavities of adult snakes may be the environment or prey. Functional Annotation of the Prokaryotic Taxa analysis showed that the skin/oral native microbiome metabolism was related to fermentation and human infection owing to the dominance of K. pneumoniae lineages. The characteristics of K. pneumoniae may impact the development of venom in venomous snakes. CONCLUSION: The results of the native microbiome in the oral cavity and skin of newborn P. mucrosquamatus demonstrated that the habitat environment and prey capture may affect the composition of bacteria in adult snakes. We hypothesized that the native microbiome influences newborn venomous snakes and that K. pneumoniae lineages related to citrate fermentation may play a role in venom growth. However, further verification of this is required.