An IoT Real-Time Potable Water Quality Monitoring and Prediction Model Based on Cloud Computing Architecture.

In order to achieve the Sustainable Development Goals (SDG), it is imperative to ensure the safety of drinking water. The characteristics of each drinkable water, encompassing taste, aroma, and appearance, are unique. Inadequate water infrastructure and treatment can affect these features and may also threaten public health. This study utilizes the Internet of Things (IoT) in developing a monitoring system, particularly for water quality, to reduce the risk of contracting diseases. Water quality components data, such as water temperature, alkalinity or acidity, and contaminants, were obtained through a series of linked sensors. An Arduino microcontroller board acquired all the data and the Narrow Band-IoT (NB-IoT) transmitted them to the web server. Due to limited human resources to observe the water quality physically, the monitoring was complemented by real-time notifications alerts via a telephone text messaging application. The water quality data were monitored using Grafana in web mode, and the binary classifiers of machine learning techniques were applied to predict whether the water was drinkable or not based on the data collected, which were stored in a database. The non-decision tree, as well as the decision tree, were evaluated based on the improvements of the artificial intelligence framework. With a ratio of 60% for data training: at 20% for data validation, and 10% for data testing, the performance of the decision tree (DT) model was more prominent in comparison with the Gradient Boosting (GB), Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) modeling approaches. Through the monitoring and prediction of results, the authorities can sample the water sources every two weeks.

Efficacy of a Smartphone App in Enhancing Medication Adherence and Accuracy in Individuals With Schizophrenia During the COVID-19 Pandemic: Randomized Controlled Trial.

BACKGROUND: Poor medication adherence or inaccuracy in taking prescribed medications plays an important role in the recurrence or worsening of psychiatric symptoms in patients with schizophrenia, and the COVID-19 pandemic impacted their medication adherence with exacerbated symptoms or relapse. The use of mobile health services increased during the COVID-19 pandemic, and their role in improving mental health is becoming clearer. OBJECTIVE: This study aimed to explore the effectiveness of a smartphone app (MedAdhere) on medication adherence and accuracy among patients with schizophrenia and to measure their psychiatric symptoms and cognitive functions. METHODS: In this 12-week experimental study, participants were provided interventions with the MedAdhere app, and data were collected between June 2021 and September 2022. A total of 105 participants were randomly assigned to either the experimental or control groups. We used the Positive and Negative Syndrome Scale and Mini-Mental State Examination to measure the participants' psychiatric symptoms and cognitive functions. Generalized estimating equations were used for data analysis. RESULTS: A total of 94 participants met the inclusion criteria and completed the protocol, and the medication adherence rate of the experimental group was 94.72% (2785/2940) during the intervention. Psychotic symptoms (positive, negative, and general psychopathology symptoms) and cognitive functions (memory, language, and executive function) were significantly improved in the experimental group compared to the control group after the intervention. CONCLUSIONS: The MedAdhere app effectively and significantly improved medication adherence and, thereby, the psychiatric symptoms of patients with schizophrenia. This artificial intelligence assisted app could be extended to all patients who need to be reminded to take medication on schedule. TRIAL REGISTRATION: ClinicalTrials.gov NCT05892120; https://clinicaltrials.gov/study/NCT05892120.

Adaptive Autonomous Protocol for Secured Remote Healthcare Using Fully Homomorphic Encryption (AutoPro-RHC).

The outreach of healthcare services is a challenge to remote areas with affected populations. Fortunately, remote health monitoring (RHM) has improved the hospital service quality and has proved its sustainable growth. However, the absence of security may breach the health insurance portability and accountability act (HIPAA), which has an exclusive set of rules for the privacy of medical data. Therefore, the goal of this work is to design and implement the adaptive Autonomous Protocol (AutoPro) on the patient's remote healthcare (RHC) monitoring data for the hospital using fully homomorphic encryption (FHE). The aim is to perform adaptive autonomous FHE computations on recent RHM data for providing health status reporting and maintaining the confidentiality of every patient. The autonomous protocol works independently within the group of prime hospital servers without the dependency on the third-party system. The adaptiveness of the protocol modes is based on the patient's affected level of slight, medium, and severe cases. Related applications are given as glucose monitoring for diabetes, digital blood pressure for stroke, pulse oximeter for COVID-19, electrocardiogram (ECG) for cardiac arrest, etc. The design for this work consists of an autonomous protocol, hospital servers combining multiple prime/local hospitals, and an algorithm based on fast fully homomorphic encryption over the torus (TFHE) library with a ring-variant by the Gentry, Sahai, and Waters (GSW) scheme. The concrete-ML model used within this work is trained using an open heart disease dataset from the UCI machine learning repository. Preprocessing is performed to recover the lost and incomplete data in the dataset. The concrete-ML model is evaluated both on the workstation and cloud server. Also, the FHE protocol is implemented on the AWS cloud network with performance details. The advantages entail providing confidentiality to the patient's data/report while saving the travel and waiting time for the hospital services. The patient's data will be completely confidential and can receive emergency services immediately. The FHE results show that the highest accuracy is achieved by support vector classification (SVC) of 88% and linear regression (LR) of 86% with the area under curve (AUC) of 91% and 90%, respectively. Ultimately, the FHE-based protocol presents a novel system that is successfully demonstrated on the cloud network.

Acidosis-related pain and its receptors as targets for chronic pain.

Sensing acidosis is an important somatosensory function in responses to ischemia, inflammation, and metabolic alteration. Accumulating evidence has shown that acidosis is an effective factor for pain induction and that many intractable chronic pain diseases are associated with acidosis signaling. Various receptors have been known to detect extracellular acidosis and all express in the somatosensory neurons, such as acid sensing ion channels (ASIC), transient receptor potential (TRP) channels and proton-sensing G-protein coupled receptors. In addition to sense noxious acidic stimulation, these proton-sensing receptors also play a vital role in pain processing. For example, ASICs and TRPs are involved in not only nociceptive activation but also anti-nociceptive effects as well as some other non-nociceptive pathways. Herein, we review recent progress in probing the roles of proton-sensing receptors in preclinical pain research and their clinical relevance. We also propose a new concept of sngception to address the specific somatosensory function of acid sensation. This review aims to connect these acid-sensing receptors with basic pain research and clinical pain diseases, thus helping with better understanding the acid-related pain pathogenesis and their potential therapeutic roles via the mechanism of acid-mediated antinociception.

Core Stabilization Exercise in Prenatal and Postnatal Women With Urinary Incontinence: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

OBJECTIVE: The aim of the study is to evaluate the effect size of core stabilization exercise for prenatal and postnatal women through measures of urinary symptoms, voiding function, pelvic floor muscle strength and endurance, quality of life, and pain scores. DESIGN: The PubMed, Embase, Cochrane Library, and Scopus databases were searched. Randomized controlled trials were selected and subjected to meta-analysis and risk of bias assessment. RESULTS: Ten randomized controlled trials were selected, and 720 participants were included. Ten articles using seven outcomes were analyzed. Relative to the control groups, the core stabilization exercise groups exhibited superior results for urinary symptoms (standardized mean difference = -0.65, 95% confidence interval = -0.97 to 0.33), pelvic floor muscle strength (standardized mean difference = 0.96, 95% confidence interval = 0.53 to 1.39), pelvic floor muscle endurance (standardized mean difference = 0.71, 95% confidence interval = 0.26 to 1.16), quality of life (standardized mean difference = -0.9, 95% confidence interval = -1.23 to 0.58), transverse muscle strength (standardized mean difference = -0.45, 95% confidence interval = -0.9 to -0.01), and voiding function (standardized mean difference = -1.07, 95% confidence interval = -1.87 to 0.28). CONCLUSIONS: Core stabilization exercises are safe and beneficial for alleviating urinary symptoms, improving quality of life, strengthening pelvic floor muscles, and improving transverse muscle function in prenatal and postnatal women with urinary incontinence.

The electronic medical record management systems may improve monitoring and control of disease activity in patients with ankylosing spondylitis.

To investigate the impact of an electronic medical record management system (EMRMS) on disease activity and the frequency of outpatient visits among patients with ankylosing spondylitis (AS). We identified 652 patients with AS who were followed up for at least 1 year before and after the first Ankylosing Spondylitis Disease Activity Score (ASDAS) assessment and compared the number of outpatient visits and average visit time within 1 year before and after the initial ASDAS assessment. Finally, we analyzed 201 patients with AS who had complete data and received ≥ 3 continuous ASDAS assessments at an interval of 3 months, and we compared the results of the second and third ASDAS assessments with those of the first. The number of annual outpatient visits increased after ASDAS assessment (4.0 (4.0, 7.0) vs. 4.0 (4.0, 8.0), p < 0.001), particularly among those with a high initial disease activity. The average visit time was reduced within 1 year after ASDAS assessment (6.4 (8.5, 11.2) vs. 6.3 (8.3, 10.8) min, p = 0.073), especially among patients whose with an inactive disease activity was < 1.3 (ASDAS C-reactive protein (CRP) 6.7 (8.8, 11.1) vs. 6.1 (8.0, 10.3) min, p = 0.033; ASDAS erythrocyte sedimentation rate (ESR) 6.4 (8.7, 11.1) vs. 6.1 (8.1, 10.0) min, p = 0.027). Among patients who received at least three ASDAS assessments, the third ASDAS-CRP tended to be lower than the first (1.5 (0.9, 2.1) vs. 1.4 (0.8, 1.9), p = 0.058). The use of an EMRMS increased the frequency of ambulatory visits among AS patients with high and very high disease activity and reduced the visit time among those with an inactive disease. Continual ASDAS assessments may help control the disease activity of patients with AS.

Sustaining Improvements of Surgical Site Infections by Six Sigma DMAIC Approach.

BACKGROUND: SSIs (surgical site infections) are associated with increased rates of morbidity and mortality. The traditional quality improvement strategies focusing on individual performance did not achieve sustainable improvement. This study aimed to implement the Six Sigma DMAIC method to reduce SSIs and to sustain improvements in surgical quality. The surgical procedures, clinical data, and surgical site infections were collected among 42,233 hospitalized surgical patients from 1 January 2019 to 31 December 2020. Following strengthening leadership and empowering a multidisciplinary SSI prevention team, DMAIC (Define, Measure, Analyze, Improve, and Control) was used as the performance improvement model. An evidence-based prevention bundle for reduction of SSI was adopted as performance measures. Environmental monitoring and antimicrobial stewardship programs were strengthened to prevent the transmission of multi-drug resistant microorganisms. Process change was integrated into a clinical pathway information system. Improvement cycles by corrective actions for the risk events of SSIs were implemented to ensure sustaining improvements. We have reached the targets of the prevention bundle elements in the post-intervention period in 2020. The carbapenem resistance rates of Enterobacteriaceae and P. aeruginosa were lower than 10%. A significant 22.2% decline in SSI rates has been achieved, from 0.9% for the pre-intervention period in 2019 to 0.7% for the post-intervention period in 2020 (p = 0.004). Application of the Six Sigma DMAIC approach could significantly reduce the SSI rates. It also could help hospital administrators and quality management personnel to create a culture of patient safety.

Accuracy of MRI derived cerebral aqueduct flow parameters in the diagnosis of idiopathic normal pressure hydrocephalus.

Idiopathic normal pressure hydrocephalus (iNPH) is a potentially reversible cause of dementia-like symptoms among the elderly. Current diagnostic guidelines for iNPH rely on clinical manifestations and ventricular morphology, which often lack accuracy. While magnetic resonance imaging (MRI) CSF flowmetry of the cerebral aqueduct provides a noninvasive aid to differential diagnosis, previous studies suffered from small sample sizes. This study compares the accuracy of different CSF flow parameters for iNPH diagnosis in a general patient population. From 2016 to 2018, a total of 216 subjects over 60 years of age were retrospectively enrolled, including 38 patients with iNPH and 178 patients with non-iNPH neurological conditions. All participants received phase-contrast MRI (PC-MRI) CSF flowmetry, with measurements performed independently by two radiologists. Flow parameters of iNPH and non-iNPH groups were compared along with their diagnostic accuracy. Absolute stroke volume (ABSV), forward flow, backward flow, mean flux and peak velocity were significantly higher in iNPH patients (P < 0.001, P < 0.001, P < 0.001, P = 0.008, P = 0.038, respectively). Backward flow had the highest diagnostic accuracy, followed by ABSV and forward flow. Net caudocranial aqueductal flow was observed in both groups, but with greater volume in the iNPH group. PC-MRI provides a non-invasive method of CSF flowmetry across the cerebral aqueduct and may aid in iNPH diagnosis. ABSV and its component flow values may provide better accuracy in identifying iNPH than other parameters.

Cinnamaldehyde decreases the invasion and u-PA expression of osteosarcoma by down-regulating the FAK signalling pathway.

Cancer metastasis is the major cause of the high mortality risk of patients with osteosarcoma. Cinnamaldehyde has been shown to exhibit multiple tumour-suppressing activities, but its role in human osteosarcoma is not yet completely defined. In this study, the antimetastatic effect of cinnamaldehyde on highly metastatic human osteosarcoma cells was observed in vitro and in vivo using Saos-2 and 143B cells. Cinnamaldehyde reduced the activity and protein level of urokinase-type plasminogen activator (u-PA) and suppressed the invasion ability of osteosarcoma cells by inhibiting the phosphorylation of focal adhesion kinase. In addition, cinnamaldehyde reduced cell movement, cell-matrix adhesion, and the expression of the mesenchymal markers of epithelial-to-mesenchymal transition, namely, fibronectin and N-cadherin. Importantly, the oral administration of cinnamaldehyde remarkably suppressed the pulmonary metastasis of osteosarcoma in mice. Results indicated that cinnamaldehyde has therapeutic potential for inhibiting osteosarcoma metastasis.

Effectiveness of question prompt lists in patients with breast cancer: A randomized controlled trial.

OBJECTIVES: To evaluate the effectiveness of a question prompt list (QPL) in decision self-efficacy, decision-making participation, patient-physician communication, decisional conflict or regret, and health status in patients with breast cancer. METHODS: A total of 240 patients with breast cancer were randomly assigned to a QPL group or control group (n = 120 each). The intervention and control groups received an additional educational QPL booklet and routine care, respectively. RESULTS: The intervention group exhibited significant improvements in decision self-efficacy, perceived patient-physician interactions, and patient-physician communication compared with the control group. Multilevel modeling analyses revealed significant group-time interaction effects on decision self-efficacy (ß = 9.99, P < 0.01), perceived patient-physician interactions (ß = 8.10, P < 0.01), patient-physician communication (ß = 5.02, P < 0.01), and anxiety status (ß = -3.78, P < 0.05). The QPL intervention exerted more favorable effects than routine care, with repeated measurements of the same patients and the data of patients under the care of the same surgeons accounted for. CONCLUSIONS: The QPL intervention exerted multidimensional effects on decision-making outcomes among patients with breast cancer. PRACTICAL IMPLICATIONS: Clinicians can integrate a QPL into routine care for patients with breast cancer.

The BASDAI Cut-Off for Disease Activity Corresponding to the ASDAS Scores in a Taiwanese Cohort of Ankylosing Spondylitis.

Objectives: The Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) has been widely utilized to evaluate disease activity in patients with ankylosing spondylitis (AS) by an arbitrary cut-off of ≥4 to indicate high disease activity and initiate biological therapy. The Ankylosing Spondylitis Disease Activity Score (ASDAS) is a new composite index to assess AS disease activity states that have been defined and validated. ASDAS ≥2.1 was selected as a criterion to start biological therapy. The purpose of this study was to estimate the corresponding BASDAI and ASDAS cut-off in a Taiwanese AS cohort. Methods: From November 2016 to October 2018, we assessed the ASDAS and the BASDAI regularly and recorded demographic data for 489 AS patients in Taichung Veterans General hospital (TCVGH) using an electronic patient-reported data system linked to electronic medical records. We used receiver operating characteristic curves with Youden's J statistic to determine the BASDAI values that correspond to ASDAS disease activity cut-offs (i.e., 1.3, 2.1, and 3.5). Results: In our population, the best trade-off BASDAI values corresponding to ASDAS -C-reactive protein (CRP) 1.3, 2.1, and 3.5 were 2.1, 3.1, and 3.7, respectively. The optimal BASDAI values corresponding to ASDAS-erythrocyte sedimentation rates 1.3, 2.1, and 3.5 were 2.0, 2.6, and 4.8, respectively. Conclusion: We propose a revised BASDAI cut-off based on our data, as BASDAI scores are commonly used globally. A more reasonable, lower BASDAI cut-off to initiate or change biological therapy will bring us closer to better decisions to treat AS patients.

Reduction of invasion and cell stemness and induction of apoptotic cell death by Cinnamomum cassia extracts on human osteosarcoma cells.

Cinnamomum cassia possesses antioxidative activity and induces the apoptotic properties of various cancer types. However, its effect on osteosarcoma invasion and cancer stemness remains ambiguous. Here, we examined the molecular evidence of the anti-invasive effects of ethanoic C. cassia extracts (CCE). Invasion and migration were obviously suppressed after the expression of urokinase-type plasminogen activator and matrix metalloprotein 2 in human osteosarcoma 143B cells were downregulated. CCE reversed epithelial-to-mesenchymal transition (EMT) induced by transforming growth factor ß1 and downregulated mesenchymal markers, such as snail-1 and RhoA. CCE suppressed self-renewal property and the expression of stemness genes (aldehyde dehydrogenase, Nanog, and CD44) in the 143B cells. CCE suppressed cell viability, reduced the colony formation of osteosarcoma cancer cells, and induced apoptotic cell death in the 143B cells, as indicated by caspase-9 activation. The xenograft tumor model of immunodeficient BALB/c nude mice showed that CCE administered in vivo through oral gavage inhibited the growth of implanted 143B cells. These findings indicated that CCE inhibited the invasion, migration, and cancer stemness of the 143B cells. CCE reduced proliferation of 143B cell possibly because of the activation of caspase-9 and the consequent apoptosis, suggesting that CCE is a potential anticancer supplement for osteosarcoma.

Review of an intelligent indoor environment monitoring and management system for COVID-19 risk mitigation.

The coronavirus disease (COVID-19) outbreak has turned the world upside down bringing about a massive impact on society due to enforced measures such as the curtailment of personal travel and limitations on economic activities. The global pandemic resulted in numerous people spending their time at home, working, and learning from home hence exposing them to air contaminants of outdoor and indoor origins. COVID-19 is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which spreads by airborne transmission. The viruses found indoors are linked to the building's ventilation system quality. The ventilation flow in an indoor environment controls the movement and advection of any aerosols, pollutants, and Carbon Dioxide (CO2) created by indoor sources/occupants; the quantity of CO2 can be measured by sensors. Indoor CO2 monitoring is a technique used to track a person's COVID-19 risk, but high or low CO2 levels do not necessarily mean that the COVID-19 virus is present in the air. CO2 monitors, in short, can help inform an individual whether they are breathing in clean air. In terms of COVID-19 risk mitigation strategies, intelligent indoor monitoring systems use various sensors that are available in the marketplace. This work presents a review of scientific articles that influence intelligent monitoring development and indoor environmental quality management system. The paper underlines that the non-dispersive infrared (NDIR) sensor and ESP8266 microcontroller support the development of low-cost indoor air monitoring at learning facilities.

IL-4 and IL-13 Promote Proliferation of Mammary Epithelial Cells through STAT6 and IRS-1.

T helper (Th)2 cytokines such as interleukin (IL)-4 and IL-13 control immune function by acting on leukocytes. They also regulate multiple responses in non-hematopoietic cells. During pregnancy, IL-4 and IL-13 facilitate alveologenesis of mammary glands. This particular morphogenesis generates alveoli from existing ducts and requires substantial cell proliferation. Using 3D cultures of primary mouse mammary epithelial cells, we demonstrate that IL-4 and IL-13 promote cell proliferation, leading to enlargement of mammary acini with partially filled lumens. The mitogenic effects of IL-4 and IL-13 are mediated by STAT6 as inhibition of STAT6 suppresses cell proliferation and improves lumen formation. In addition, IL-4 and IL-13 stimulate tyrosine phosphorylation of insulin receptor substrate-1 (IRS-1). Prolonged treatment with these cytokines leads to increased IRS-1 abundance, which, in turn, amplifies IL-4- and IL-13-stimulated IRS-1 tyrosine phosphorylation. Through signaling crosstalk between IL-4/IL-13 and insulin, a hormone routinely included in mammary cultures, IRS-1 tyrosine phosphorylation is further enhanced. Lowering IRS-1 expression reduces cell proliferation, suggesting that IRS-1 is involved in IL-4- and IL-13-stimulated cell proliferation. Thus, a Th2-dominant cytokine milieu during pregnancy confers mammary gland development by promoting cell proliferation.

Using deep learning convolutional neural networks to automatically perform cerebral aqueduct CSF flow analysis.

Since the development of phase-contrast magnetic resonance imaging (PC-MRI), quantification of cerebrospinal fluid (CSF) flow across the cerebral aqueduct has been utilized for diagnosis of conditions such as normal pressure hydrocephalus (NPH). This study aims to develop an automated method of aqueduct CSF flow analysis using convolution neural networks (CNNs), which can replace the current standard involving manual segmentation of aqueduct region of interest (ROI). Retrospective analysis was performed on 333 patients who underwent PC-MRI, totaling 353 imaging studies. Aqueduct flow measurements using manual ROI placement was performed independently by two radiologists. Two types of CNNs, MultiResUNet and UNet, were trained using ROI data from the senior radiologist, with PC-MRI studies being randomly divided into training (80%) and validation (20%) datasets. Segmentation performance was assessed using Dice similarity coefficient (DSC), and CSF flow parameters were calculated from both manual and CNN-derived ROIs. MultiResUNet, UNet and second radiologist (Rater 2) had DSCs of 0.933, 0.928, and 0.867, respectively, with p < 0.001 between CNNs and Rater 2. Comparison of CSF flow parameters showed excellent intraclass correlation coefficients (ICCs) for MultiResUNet, with lowest correlation being 0.67. For UNet, lower ICCs of -0.01 to 0.56 were observed. Only 3/353 (0.8%) studies failed to have appropriate ROIs placed by MultiResUNet, compared to 12/353 (3.4%) failed cases for UNet. In conclusion, CNNs were able to measure aqueductal CSF flow with similar performance to a senior neuroradiologist. MultiResUNet demonstrated fewer cases of segmentation failure and more consistent flow measurements compared to the widely adopted UNet.

Association of urate-lowering drugs with the risk of future urolithiasis in patients with gout: A population-based nested case-control study.

BACKGROUND: Patients with gout have an increased risk of urolithiasis and usually need urate-lowering therapy (ULT) for the prevention of disease progression. However, there is a paucity of clinical data regarding the risk of future urolithiasis in ULT users. METHODS: This nested case-control study was performed using the Taiwan National Health Insurance Research Database. The aim of this study was to examine whether ULT (xanthine oxidase inhibitors [XOIs] or uricosuric agents) is associated with risk of future urolithiasis in patients with gout. Data were collected from January 2000 to December 2012. RESULTS: This study included 2307 case patients and 2307 matched controls. Case patients had gout that developed into urolithiasis, and control patients had gout but were not diagnosed with urolithiasis during the study period. Patients had a mean age of 56.3 years at diagnosis of gout, and 83.2% were male patients. No association was detected between use of XOIs or uricosuric agents and risk of future urolithiasis. Furthermore, there was no significant difference in the risk of future urolithiasis in patients exposed to various cumulative days of XOI or uricosuric prescriptions. CONCLUSION: The present study provides evidence that neither XOIs nor uricosuric agents are associated with risk of future urolithiasis in patients with gout. Before the availability of more clinical evidence, ensuring high fluid intake and prospective monitoring of urolithiasis development are still important for uricosuric agent users.

The effect of weather, air pollution and seasonality on the number of patient visits for epileptic seizures: A population-based time-series study.

OBJECTIVE: The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures. METHODS: Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7 days' lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined. RESULTS: The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH4, and NO. Six air pollutants, namely CH4, NO, CO, NO2, PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R2 = 0.422). CONCLUSION: The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.

Gender difference in ASAS HI among patients with ankylosing spondylitis.

OBJECTIVE: To assess the associations of the Assessment of Spondyloarthritis International Society Health Index (ASAS HI) with gender and other factors in patients with ankylosing spondylitis (AS). METHODS: From November 2017 to October 2018, we measured the Ankylosing Spondylitis Disease Activity Score (ASDAS), the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Bath Ankylosing Spondylitis Functional Index (BASFI), the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS) and the ASAS HI score for AS patients at the Taichung Veterans General Hospital. After adjusting for disease activity (ASDAS-erythrocyte sedimentation rate [ESR], ASDAS- C-reactive protein [CRP], BASDAI+ESR or BASDAI+CRP), mSASSS and other potential confounders including medications, comorbidities, and laboratory data, any associations between gender and the sum score of ASDAS HI were assessed using multiple linear regression analysis, as well as any associations between gender and an ASAS HI score >5 using multivariable logistic regression analysis. RESULTS: A total of 307 AS patients (62 [20.2%] females, mean age 46.4 years [S.D. 13.3], mean symptom duration 20.6 years [S.D. 12.1]) were included. Multiple linear regression analysis showed that the male gender was significantly associated with a lower ASAS HI (B = -1. 91, 95% confidence interval [CI], -2.82--1.00, p <0.001). Multivariable logistic regression analysis revealed that males also had a lower risk of achieving scores of ASAS HI > 5 than females (odds ratio = 0.15, 95% CI, 0.07-0.36, p <0.001). Disease activity measures, including ASDAS-ESR, ASDAS-CRP and BASDAI, had positive correlations with ASAS HI. CONCLUSION: This single-center, cross-sectional study revealed that a higher ASAS HI score was significantly associated with female gender and higher disease activity measures.

PPARα plays an important role in the migration activity, and the expression of CYP2S1 and CYP1B1 in chrysin-treated HCT116 cells.

OBJECTIVE: This study aimed to examine the metabolising effect of chrysin by investigating the mRNA expression levels of PPARα and its related cellular mechanisms in HCT116 cells. RESULTS: The mRNA expression of PPARα was significantly induced in HCT116 cells following treatment with chrysin for 36 h, but the mRNA expression of PPARα was inhibited, when the cells were treated with a combination of chrysin and MK886 (PPARα inhibitor). This phenomenon proved that the incorporation of MK886 lowers the expression levels of PPARα, thus enabling us to study the function of PPARα. The cell population of the G0/G1 phase significantly increased in chrysin-treated cells, which was accompanied by a decrease in the percentage of S phase cell population after 12 h of treatment. However, treatments of HCT116 cells with chrysin only or a combination of chrysin and MK886 did not show the opposite situation in the G0/G1 and S phase cell populations, indicating that the expression of PPARα may not be associated with the cell cycle in the treated cells. The migration rate in chrysin-treated HCT116 cells was reduced significantly after 24 and 36 h of treatments. However, the activity was revived, when the expression of PPARα was inhibited, indicating that the migration activity of chrysin-treated cells is likely correlated with the expression of PPARα. Comparison of the CYP2S1 and CYP1B1 mRNA expression in chrysin only treated, and a combination of chrysin and MK886-treated HCT116 cells for 24 and 36 h showed a significant difference in the expression levels, indicating that PPARα inhibitor could also modify the expression of CYP2S1 and CYP1B1. CONCLUSION: The study indicates that PPARα may play an essential role in regulating the migration activity, and the expression of CYP2S1 and CYP1B1 in chrysin-treated colorectal cancer cells.