Spatiotemporal link between El Niño Southern Oscillation (ENSO), extreme heat, and thermal stress in the Asia-Pacific region.

Climate change is closely monitored and numerous studies reports increasing air temperature and weather extremes across the globe. As a direct consequence of the increase of global temperature, the increased heat stress is becoming a global threat to public health. While most climate change and epidemiological studies focus on air temperature to explain the increasing risks, heat strain can be predicted using comprehensive indices such as Universal Thermal Climate Index (UTCI). The Asia-Pacific region is prone to thermal stress and the high population densities in the region impose high health risk. This study evaluated the air temperature and UTCI trends between 1990 and 2019 and found significant increasing trends for air temperature for the whole region while the increases of UTCI are not as pronounced and mainly found in the northern part of the region. These results indicate that even though air temperature is increasing, the risks of heat stress when assessed using UTCI may be alleviated by other factors. The associations between El Niño Southern Oscillation (ENSO) and heat stress was evaluated on a seasonal level and the strongest regional responses were found during December-January (DJF) and March-May (MAM).

Spatial analysis of food and water-borne diseases in Ahmedabad, India: Implications for urban public health planning.

Spatial analysis of infectious diseases can play an important role in mapping the spread of diseases and can support policy making at local level. Moreover, identification of disease clusters based on local geography and landscape forms the basis for disease control and prevention. Therefore, this study aimed to examine the spatial-temporal variations, hotspot areas, and potential risk factors of infectious diseases (including Viral Hepatitis, Typhoid and Diarrhea) in Ahmedabad city of India. We used Moran's I and Local Indicators of Spatial Association (LISA) mapping to detect spatial clustering of diseases. Spatial and temporal regression analysis was used to identify the association between disease incidence and spatial risk factors. The Moran's I statistics identified presence of positive spatial autocorrelation within the considered diseases, with Moran's I from 0.09 for typhoid to 0.21 for diarrhea (p < 0.001). This indicates a clustering of affected wards for each disease, suggesting that cases were not randomly distributed across the city. LISA mapping demonstrated the clustering of hotspots in central regions of the city, especially towards the east of the river Sabarmati, highlighting key geographical areas with elevated disease risk. The spatial clusters of infectious diseases were consistently associated with slum population density and illiteracy. Furthermore, temporal analysis suggested illiteracy rates could increase risk of viral hepatitis by 13 % (95 % Confidence Interval (CI): 1.01-1.26) and of diarrhea by 18 % (95 % CI: 1.07-1.31). Significant inverse association was also seen between viral hepatitis incidence and the distance of wards from rivers. Conclusively, the study highlight the impact of socio-economic gradients, such as slum population density (indicative of poverty) and illiteracy, on the localized transmission of water and foodborne infections. The evident social stratification between impoverished and affluent households emerges as a notable contributing factor and a potential source of differences in the dynamics of infectious diseases in Ahmedabad.

Changes of Mycobacterium tuberculosis specific antigen-stimulated CD27-CD38+IFN-γ+CD4+ T cells before and after anti-tuberculosis treatment.

BACKGROUND: The aim of the study was to investigate whether the expression of CD27-CD38+ in interferon (IFN)-γ+CD4+ T cells stimulated by the specific antigen early secreted antigenic target-6 (ESAT-6)/culture filter protein-10 (CFP-10) could be a potential new therapeutic evaluation indicator for anti-tuberculosis (TB) treatment. METHODS: Newly diagnosed active pulmonary TB patients, latent TB infection (LTBI) and healthy controls were enrolled from January 2021 to December 2021. PTB patients were treated by standard anti-TB regimen 2HREZ/4HR (2 months of isoniazid (H), rifampin (R), ethambutol (E), and pyrazinamide (Z) followed by 4 months of isoniazid (H) and rifampin (R)). The difference of CD27-CD38+ expression in IFN-γ+CD4+ T cells before treatment, 2 months after treatment, and 6 months after treatment were compared. RESULTS: Total 45 PTB patients, 38 LTBI cases and 43 healthy controls were enrolled. The expression of CD27-CD38+ decreased significantly after anti-TB treatment and was comparable with that in LTBI and healthy controls when the 6-month anti-TB treatment course was completed. The decline rate of CD27-CD38+ between 6 months after treatment and baseline was positively correlated with erythrocyte sedimentation rate (r = 0.766, P < 0.0001), C-reactive protein (r = 0.560, P = 0.003) and chest computerized tomography severity score (r = 0.632, P = 0.0005). The area under receiver operator characteristic curve of CD27-CD38+ in distinguish pulmonary TB patients before and after treatment was 0.779. CONCLUSION: The expression of CD27-CD38+ in ESAT-6/CFP-10 stimulated IFN-γ+CD4+T cells can well reflect the changes of the disease before and after anti-TB treatment, which is expected to be a potential new therapeutic evaluation index. Clinical Registry number chiCTR1800019966.

Associations between community green view index and fine particulate matter from Airboxes.

Urban greenery can help to improve air quality, reduce health risks and create healthy livable urban communities. This study aimed to explore the role of urban greenery in reducing air pollution at the community level in Tainan City, Taiwan, using air quality sensors and street-view imagery. We also collected the number of road trees around each air quality sensor site and identified the species that were best at absorbing PM2.5. Three greenness metrics were used to assess community greenery in this study: two Normalized Difference Vegetation Indices (NDVI) from different satellites and the Green View Index (GVI) from Google Street View (GSV) images. Land-use Regression (LUR) was used for statistical analysis. The results showed that a higher GVI within a 500 m buffer was significantly associated with decreased PM2.5. Neither NDVI metrics within a 500 m circular buffer were significantly associated with decreased PM2.5. Evergreen trees were significantly associated with lower ambient PM2.5, compared with deciduous and semi-deciduous trees. Because localized changes in air quality profoundly affect public health and environmental equity, our findings provide evidence for future urban community greenspace planning and its beneficial impacts on reducing air pollution.

DNA mini-barcoding reveals the mislabeling rate of canned cat food in Taiwan.

Background: Domestic cats are important companion animals in modern society that live closely with their owners. Mislabeling of pet food can not only harm pets but also cause issues in areas such as religious beliefs and natural resource management. Currently, the cat food market is booming. However, despite the risk that mislabeling poses to cats and humans, few studies have focused on species misrepresentation in cat food products. Methods: To address this issue, we used DNA barcoding, a highly effective identification methodology that can be applied to even highly processed products. We targeted a short segment (~85 basepairs) of the mitochondrial 16S rRNA (16S) gene as a barcode and employed Sanger or next generation sequencing (NGS) to inspect 138 canned cat food products in the Taiwanese market. Results: We discovered that the majority of mislabeling incidents were related to replacement of tuna with other species. Moreover, our metabarcoding revealed that numerous undeclared ingredients were present in all examined canned products. One product contained CITES Appendix II-listed shortfin mako shark (Isurus oxyrinchus). Overall, we uncovered a mislabeling rate of at least 28.99%. To verify cases of mislabeling, an official standardized list of vernacular names, along with the corresponding scientific species names, as well as a dependable barcoding reference sequence database are necessary.

Pure Sensory Lacunar Infarction in the Thalamus Presented as Bilateral Hypogeusia: A Case Report.

PURPOSE: While the gustatory pathway of animals has been well-researched, that of humans is still a mystery. Several theories have been established, and some earlier reports hypothesized the relation to laterality. However, some cases could not be fully explained by the laterality theory (1). To clarify the gustatory pathway, we reported a case with bilateral hypogeusia after right thalamic infarction. CASE: This 55-year-old, right-handed man suffered from sudden decreased sensitivity of taste. He was unable to differentiate sweetness and saltiness at bilateral anterior parts of tongue. Additionally, there was numbness at the upper palate and the lips. Neurological examination revealed decreased taste sense at both sides of his anterior tongue and decreased pin-prick sensation of the left part of his lips. Brain magnetic resonance imaging (MRI) revealed acute ischemic stroke at the right ventral posteromedial nucleus (VPM). Thus, single antiplatelet therapy was administered. Two weeks later, the symptoms improved significantly and completely recovered without sequelae. CONCLUSION: The exact gustatory pathway in humans remains uncertain nowadays. First, there were few reports about dysgeusia, which might be related to clinical neglect of taste deficits. Second, our knowledge of the human gustatory pathway depends solely on sporadic cases of taste-involved brain lesions. We reported a case of bilateral hypogeusia after right thalamic infarction. This finding indicates that, although there might be laterality of gustatory fibers to the left hemisphere, anatomical variations may exist in the human gustatory system. More research is needed to elucidate the understanding of the gustatory pathway in humans.

Extreme precipitation patterns in the Asia-Pacific region and its correlation with El Niño-Southern Oscillation (ENSO).

In the Asia-Pacific region (APR), extreme precipitation is one of the most critical climate stressors, affecting 60% of the population and adding pressure to governance, economic, environmental, and public health challenges. In this study, we analyzed extreme precipitation spatiotemporal trends in APR using 11 different indices and revealed the dominant factors governing precipitation amount by attributing its variability to precipitation frequency and intensity. We further investigated how these extreme precipitation indices are influenced by El Niño-Southern Oscillation (ENSO) at a seasonal scale. The analysis covered 465 ERA5 (the fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts) study locations over eight countries and regions during 1990-2019. Results revealed a general decrease indicated by the extreme precipitation indices (e.g., the annual total amount of wet-day precipitation, average intensity of wet-day precipitation), particularly in central-eastern China, Bangladesh, eastern India, Peninsular Malaysia and Indonesia. We observed that the seasonal variability of the amount of wet-day precipitation in most locations in China and India are dominated by precipitation intensity in June-August (JJA), and by precipitation frequency in December-February (DJF). Locations in Malaysia and Indonesia are mostly dominated by precipitation intensity in March-May (MAM) and DJF. During ENSO positive phase, significant negative anomalies in seasonal precipitation indices (amount of wet-day precipitation, number of wet days and intensity of wet-day precipitation) were observed in Indonesia, while opposite results were observed for ENSO negative phase. These findings revealing patterns and drivers for extreme precipitation in APR may inform climate change adaptation and disaster risk reduction strategies in the study region.

Effectiveness of aroma-Tea Tree Oil and Eucalyptus oil in alleviating COVID-19 vaccine discomfort side effects.

CONTEXT: Aromatherapy is considered a mild and non-invasive complementary treatment to relieve post-vaccination discomforts. There have been no studies that examine the use of aroma-Tea Tree oil and Eucalyptus oil to relieve the discomfort side effects related to COVID-19 vaccines. OBJECTIVE: This study examined the use of two aroma-essential oils to relieve discomfort side effects of COVID-19 vaccination. DESIGN: The study used experimental design to match two groups of participants. SETTING: The participants' home. PARTICIPANTS: Adults who had not yet been vaccinated against COVID-19 but were planning to receive it were recruited. The current study included 87 control participants matched to 83 experimental participants. INTERVENTION: The participants in the experimental group used Tea tree and Eucalyptus while the control group did not. MAIN OUTCOME MEASURES: A questionnaire was used to collect data on the topical and systematic symptoms related to COVID-19 vaccines. Both groups were asked to complete the online questionnaire and report their health status 24 h (T1) and 48 h (T2) after vaccination. RESULTS: The results revealed a statistically significant difference between the groups in swelling, injection side pain, lump, fever, and muscle ache (p = .05, 0.04, <0.00, 0.02, 0.02, respectively) for T1; but for T2, a significant difference between the two groups was found only in lump and fever (p = .05, 0.03). Aroma-Tea Tree oil and Eucalyptus oil may be recognized and accepted by more people worldwide to provide a safe and healthy option not only for post-vaccination care but also to relieve pain, fever, and skin lumps associated with other diseases or conditions.

Effects of temperature, rainfall, and El Niño Southern Oscillations on dengue-like-illness incidence in Solomon Islands.

BACKGROUND: This study investigated associations between climate variables (average temperature and cumulative rainfall), and El Niño Southern Oscillation (ENSO) and dengue-like-illness (DLI) incidence in two provinces (Western and Guadalcanal Provinces) in Solomon Islands (SI). METHODS: Weekly DLI and meteorological data were obtained from the Ministry of Health and Medical Services SI and the Ministry of Environment, Climate Change, Disaster Management and Meteorology from 2015 to 2018, respectively. We used negative binomial generalized estimating equations to assess the effects of climate variables up to a lag of 2 months and ENSO on DLI incidence in SI. RESULTS: We captured an upsurge in DLI trend between August 2016 and April 2017. We found the effects of average temperature on DLI in Guadalcanal Province at lag of one month (IRR: 2.186, 95% CI: 1.094-4.368). Rainfall had minor but consistent effect in all provinces. La Niña associated with increased DLI risks in Guadalcanal Province (IRR: 4.537, 95% CI: 2.042-10.083), whereas El Niño associated with risk reduction ranging from 72.8% to 76.7% in both provinces. CONCLUSIONS: Owing to the effects of climate variability and ENSO on DLI, defining suitable and sustainable measures to control dengue transmission and enhancing community resilience against climate change in low- and middle-developed countries are important.

Estimation of effects of extreme temperature on the risk of hospitalisation in Taiwan.

BACKGROUND: Extreme temperatures are triggering and exacerbating hospital admissions and health burdens; however, it is still understudied. Therefore, we evaluated the effects of the average temperature on overall hospitalisation and the average length of hospital stay. METHODS: Daily area-specific age-sex stratified hospitalisation records from 2006 to 2020 were collected from the National Health Research Institutes of Taiwan. The distributed lag non-linear model was used to estimate the area-specific relative risk (RR) and 95% CI associated with daily average temperature. Overall cumulative RR was pooled from area-specific RRs using random effects meta-analysis. Temperature effects of extreme high and low thresholds were also evaluated based on the 99th (32°C) and 5th (14°C) percentiles, respectively. RESULTS: Our findings suggested that the elderly (age ≥65 years) are vulnerable to temperature effects, while differential gender effects are not explicit in Taiwan. A higher risk of in-patient visits was seen among the elderly during extreme low temperatures (RR 1.08; 95% CI 1.04 to 1.11) compared with extreme high temperatures (RR 1.07; 95% CI 1.05 to 1.10). Overall, high-temperature extremes increased the risk of hospitalisation with an RR of 1.05 (95% CI 1.03 to 1.07) among the all-age-sex population in Taiwan. Additionally, lag-specific analysis of the study revealed that high-temperature effects on in-patient visits are effective on the same day of exposure, while cold effects occurred after 0-2 days of exposure. The average length of hospital stays can also increase with high-temperature extremes among age group 41-64 years and the elderly. CONCLUSION: Public health preparedness should consider the increased load on health facilities and health expenditures during extreme temperatures.

Parkinsonism mutations in DNAJC6 cause lipid defects and neurodegeneration that are rescued by Synj1.

Recent evidence links dysfunctional lipid metabolism to the pathogenesis of Parkinson's disease, but the mechanisms are not resolved. Here, we generated a new Drosophila knock-in model of DNAJC6/Auxilin and find that the pathogenic mutation causes synaptic dysfunction, neurological defects and neurodegeneration, as well as specific lipid metabolism alterations. In these mutants, membrane lipids containing long-chain polyunsaturated fatty acids, including phosphatidylinositol lipid species that are key for synaptic vesicle recycling and organelle function, are reduced. Overexpression of another protein mutated in Parkinson's disease, Synaptojanin-1, known to bind and metabolize specific phosphoinositides, rescues the DNAJC6/Auxilin lipid alterations, the neuronal function defects and neurodegeneration. Our work reveals a functional relation between two proteins mutated in Parkinsonism and implicates deregulated phosphoinositide metabolism in the maintenance of neuronal integrity and neuronal survival.

Quantifying the effects of anomalies of temperature, precipitation, and surface water storage on diarrhea risk in Taiwan.

OBJECTIVES: Diarrheal disease continues to be a significant cause of morbidity and mortality. We investigated how anomalies in monthly average temperature, precipitation, and surface water storage (SWS) impacted bacterial, and viral diarrhea morbidity in Taiwan between 2004 and 2015. METHODS: A multivariate analysis using negative binomial generalized estimating equations was employed to quantify age-specific and cause-specific cases of diarrhea associated with anomalies in temperature, precipitation, and SWS. RESULTS: Temperature anomalies were associated with an elevated rate of all-cause infectious diarrhea at a lag of 2 months, with the highest risk observed in the under-5 age group (incidence rate ratio [IRR], 1.03, 95% confidence interval [CI], 1.01 to 1.07). Anomalies in SWS were associated with increased viral diarrhea rates, with the highest risk observed in the under-5 age group at a 2-month lag (IRR, 1.27; 95% CI, 1.14 to 1.42) and a lesser effect at a 1-month lag (IRR, 1.18; 95% CI, 1.06 to 1.31). Furthermore, cause-specific diarrheal diseases were significantly affected by extreme weather events in Taiwan. Both extremely cold and hot conditions were associated with an increased risk of all-cause infectious diarrhea regardless of age, with IRRs ranging from 1.03 (95% CI, 1.02 to 1.12) to 1.18 (95% CI, 1.16 to 1.40). CONCLUSIONS: The risk of all-cause infectious diarrhea was significantly associated with average temperature anomalies in the population aged under 5 years. Viral diarrhea was significantly associated with anomalies in SWS. Therefore, we recommend strategic planning and early warning systems as major solutions to improve resilience against climate change.

Effects of Ambient Temperature, Relative Humidity, and Precipitation on Diarrhea Incidence in Surabaya.

BACKGROUND: Diarrhea remains a common infectious disease caused by various risk factors in developing countries. This study investigated the incidence rate and temporal associations between diarrhea and meteorological determinants in five regions of Surabaya, Indonesia. METHOD: Monthly diarrhea records from local governmental health facilities in Surabaya and monthly means of weather variables, including average temperature, precipitation, and relative humidity from Meteorology, Climatology, and Geophysical Agency were collected from January 2018 to September 2020. The generalized additive model was employed to quantify the time lag association between diarrhea risk and extremely low (5th percentile) and high (95th percentile) monthly weather variations in the north, central, west, south, and east regions of Surabaya (lag of 0-2 months). RESULT: The average incidence rate for diarrhea was 11.4 per 100,000 during the study period, with a higher incidence during rainy season (November to March) and in East Surabaya. This study showed that the weather condition with the lowest diarrhea risks varied with the region. The diarrhea risks were associated with extremely low and high temperatures, with the highest RR of 5.39 (95% CI 4.61, 6.17) in the east region, with 1 month of lag time following the extreme temperatures. Extremely low relative humidity increased the diarrhea risks in some regions of Surabaya, with the highest risk in the west region at lag 0 (RR = 2.13 (95% CI 1.79, 2.47)). Extremely high precipitation significantly affects the risk of diarrhea in the central region, at 0 months of lag time, with an RR of 3.05 (95% CI 2.09, 4.01). CONCLUSION: This study identified a high incidence of diarrhea in the rainy season and in the deficient developed regions of Surabaya, providing evidence that weather magnifies the adverse effects of inadequate environmental sanitation. This study suggests the local environmental and health sectors codevelop a weather-based early warning system and improve local sanitation practices as prevention measures in response to increasing risks of infectious diseases.

Automated Video Analysis of Audio-Visual Approaches to Predict and Detect Mild Cognitive Impairment and Dementia in Older Adults.

BACKGROUND: Early identification of different stages of cognitive impairment is important to provide available intervention and timely care for the elderly. OBJECTIVE: This study aimed to examine the ability of the artificial intelligence (AI) technology to distinguish participants with mild cognitive impairment (MCI) from those with mild to moderate dementia based on automated video analysis. METHODS: A total of 95 participants were recruited (MCI, 41; mild to moderate dementia, 54). The videos were captured during the Short Portable Mental Status Questionnaire process; the visual and aural features were extracted using these videos. Deep learning models were subsequently constructed for the binary differentiation of MCI and mild to moderate dementia. Correlation analysis of the predicted Mini-Mental State Examination, Cognitive Abilities Screening Instrument scores, and ground truth was also performed. RESULTS: Deep learning models combining both the visual and aural features discriminated MCI from mild to moderate dementia with an area under the curve (AUC) of 77.0% and accuracy of 76.0%. The AUC and accuracy increased to 93.0% and 88.0%, respectively, when depression and anxiety were excluded. Significant moderate correlations were observed between the predicted cognitive function and ground truth, and the correlation was strong excluding depression and anxiety. Interestingly, female, but not male, exhibited a correlation. CONCLUSION: The study showed that video-based deep learning models can differentiate participants with MCI from those with mild to moderate dementia and can predict cognitive function. This approach may offer a cost-effective and easily applicable method for early detection of cognitive impairment.

Comparison of Locking-Loop Suture Bridge Repair and Single-Row Suture Anchor Repair in Small to Medium Rotator Cuff Tears: A Prospective Cohort Study With Clinical and Ultrasound Evaluations.

Background: Single-row (SR) and double-row repair techniques have been described to treat rotator cuff tears. We present a novel surgical strategy of arthroscopic-assisted mini-open repair in which a locking-loop suture bridge (LLSB) is used. Purpose: To compare the functional outcomes and repair integrity of LLSB technique to the SR technique for arthroscopic-assisted mini-open repair of small to medium rotator cuff tears. Study Design: Cohort study; Level of evidence, 3. Methods: Included were 39 patients who underwent LLSB repair (LLSB group) and 44 patients who underwent SR suture anchor repair (SR group) from 2015 to 2018. We evaluated all patients preoperatively and at 3, 6, 12, and 24 months postoperatively using the visual analog scale (VAS) for pain, Oxford Shoulder Score (OSS), and American Shoulder and Elbow Surgeons (ASES) score. Also, shoulder sonography was performed at 12 months postoperatively to evaluate repair integrity using the Sugaya classification system. The independent-sample t test was used to analyze functional outcomes (VAS, OSS, and ASES scores), and the Fisher exact test was used to analyze postoperative sonography results. Results: Patients in both the LLSB and SR groups saw a significant improvement on all 3 outcome measures from preoperatively to 24 months postoperatively (P < .001 for all). However, when comparing scores between groups, only the scores at 3 months postoperatively differed significantly (VAS: P = .002; OSS: P < .001; ASES: P = .005). Shoulder sonography at 12 months postoperatively revealed no significant difference in repair integrity between the LLSB and SR groups (retear rate: 10.26% and 6.82%, respectively; P = .892). Conclusion: Better outcome scores were seen at 3-month follow-up in the LLSB group, with no difference in retear rates compared with the SR group at 12 months postoperatively. The LLSB technique was found to be a reliable technique for rotator cuff repair of small- to medium-sized tears.

The association of potentially inappropriate medications, polypharmacy and anticholinergic burden with readmission and emergency room revisit after discharge: A hospital-based retrospective cohort study.

AIMS: While certain drug-use indicators are known to be associated with clinical outcomes, the relationship is unclear for some highly prevalent conditions in in patients aged ≥65 years. We examine correlations between 3 drug-use indicators and postdischarge healthcare services use by older patients according to the presence of dementia, advanced age and frailty. METHODS: This retrospective cohort study analysed data collected from hospital electronic health records between April and December 2017. Potentially inappropriate medications (PIMs) and anticholinergic burden were assessed using the 2015 Beers Criteria and anticholinergic cognitive burden scale (ACBS) score. Minor and major polypharmacy were defined as the use of 5-9 and ≥10 drugs, respectively. Outcomes were set as emergency room revisits and readmissions at 1, 3 and 6 months postdischarge. The correlation between drug-use indicators and outcomes was analysed by multivariable logistic regression. RESULTS: The final cohort included 3061 patients for the analysis, and 2930, 2671 and 2560 patients were followed up to 1, 3 and 6 months after discharge. After controlling for confounders, all 3 drug-use indicators were significantly associated with readmission and emergency room revisits except for the relationship between PIMs and readmission within 6 months. These associations were significantly observed among patients without dementia, aged >80 years and with frailty. CONCLUSION: PIMs, polypharmacy and anticholinergic burden are common at discharge and correlate with future use of healthcare services. In older patients, the absence of dementia, advanced age and frailty should be given extra consideration with regard to medication safety.

Phylogenetic characteristics of Non-SARS human coronavirus in southern Taiwan, 2012-2013.

This study characterizes the phylogenetic relatedness of non-SARS human coronaviruses (HCoVs) in southern Taiwan by sequencing the nucleocapsid (N), spike (S), and RNA-dependent RNA polymerase (RdRp) genes directly from ten HCoV PCR-positive respiratory samples collected during 2012-2013. In the N, S1, and RdRp phylogeny, HCoV-OC43 in one and three samples was clustered with genotypes F and G, respectively, and HCoV-OC43 in sample YC101/TWN/2013 represented a recombination event between genotypes F and G. Amino acid substitutions in the S1 protein of HCoV-OC43 were also identified. In the N phylogeny, HCoV-HKU1 in one and two samples clustered with genotypes A and B, respectively, and HCoV-229E in two samples was clustered with genogroup 6. The genotypes and genogroup detected here were in line with the prevalent phylogenetic lineages reported outside of Taiwan during the contemporary period. In summary, three species of non-SARS HCoVs with different genotypes cocirculated in the community, with genetic evolution observed in HCoV-OC43.

Altered synaptic protein expression, aberrant spine morphology, and impaired spatial memory in Dlgap2 mutant mice, a genetic model of autism spectrum disorder.

A microdeletion of approximately 2.4 Mb at the 8p23 terminal region has been identified in a Taiwanese autistic boy. Among the products transcribed/translated from genes mapped in this region, the reduction of DLGAP2, a postsynaptic scaffold protein, might be involved in the pathogenesis of autism spectrum disorder (ASD). DLGAP2 protein was detected in the hippocampus yet abolished in homozygous Dlgap2 knockout (Dlgap2 KO) mice. In this study, we characterized the hippocampal phenotypes in Dlgap2 mutant mice. Dlgap2 KO mice exhibited impaired spatial memory, indicating poor hippocampal function in the absence of DLGAP2. Aberrant expressions of postsynaptic proteins, including PSD95, SHANK3, HOMER1, GluN2A, GluR2, mGluR1, mGluR5, ßCAMKII, ERK1/2, ARC, BDNF, were noticed in Dlgap2 mutant mice. Further, the spine density was increased in Dlgap2 KO mice, while the ratio of mushroom-type spines was decreased. We also observed a thinner postsynaptic density thickness in Dlgap2 KO mice at the ultrastructural level. These structural changes found in the hippocampus of Dlgap2 KO mice might be linked to impaired hippocampus-related cognitive functions such as spatial memory. Mice with Dlgap2 deficiency, showing signs of intellectual disability, a common co-occurring condition in patients with ASD, could be a promising animal model which may advance our understanding of ASD.

The impact of temperature and precipitation on all-infectious-, bacterial-, and viral-diarrheal disease in Taiwan.

BACKGROUND: The ongoing climate change will elevate the incidence of diarrheal in 2030-2050 in Asia, including Taiwan. This study investigated associations between meteorological factors (temperature, precipitation) and burden of age-cause-specific diarrheal diseases in six regions of Taiwan using 13 years of (2004-2016) population-based data. METHODS: Weekly cause-specific diarrheal and meteorological data were obtained from 2004 to 2016. We used distributed lag non-linear model to assess age (under five, all age) and cause-specific (viral, bacterial) diarrheal disease burden associated with extreme high (99th percentile) and low (5th percentile) of climate variables up to lag 8 weeks in six regions of Taiwan. Random-effects meta-analysis was used to pool these region-specific estimates. RESULTS: Extreme low temperature (15.30 °C) was associated with risks of all-infectious and viral diarrhea, with the highest risk for all-infectious diarrheal found at lag 8 weeks among all age [Relative Risk (RR): 1.44; 95 % Confidence Interval (95 % CI): 1.24-1.67]. The highest risk of viral diarrheal infection was observed at lag 2 weeks regardless the age. Extreme high temperature (30.18 °C) was associated with risk of bacterial diarrheal among all age (RR: 1.07; 95 % CI: 1.02-1.13) at lag 8 weeks. Likewise, extreme high precipitation (290 mm) was associated with all infectious diarrheal, with the highest risk observed for bacterial diarrheal among population under five years (RR: 2.77; 95 % CI: 1.60-4.79) at lag 8 weeks. Extreme low precipitation (0 mm) was associated with viral diarrheal in all age at lag 1 week (RR: 1.08; 95 % CI: 1.01-1.15)]. CONCLUSION: In Taiwan, extreme low temperature is associated with an increased burden of viral diarrheal, while extreme high temperature and precipitation elevated burden of bacterial diarrheal. This distinction in cause-specific and climate-hazard specific diarrheal disease burden underscore the importance of incorporating differences in public health preparedness measures designed to enhance community resilience against climate change.

State-of-Charge Estimation for Lithium-Ion Batteries Using Residual Convolutional Neural Networks.

State-of-charge (SOC) is a relative quantity that describes the ratio of the remaining capacity to the present maximum available capacity. Accurate SOC estimation is essential for a battery-management system. In addition to informing the user of the expected usage until the next recharge, it is crucial for improving the utilization efficiency and service life of the battery. This study focuses on applying deep-learning techniques, and specifically convolutional residual networks, to estimate the SOC of lithium-ion batteries. By stacking the values of multiple measurable variables taken at many time instants as the model inputs, the process information for the voltage or current generation, and their interrelations, can be effectively extracted using the proposed convolutional residual blocks, and can simultaneously be exploited to regress for accurate SOCs. The performance of the proposed network model was evaluated using the data obtained from a lithium-ion battery (Panasonic NCR18650PF) under nine different driving schedules at five ambient temperatures. The experimental results demonstrated an average mean absolute error of 1.260%, and an average root-mean-square error of 0.998%. The number of floating-point operations required to complete one SOC estimation was 2.24 × 106. These results indicate the efficacy and performance of the proposed approach.