Miracle-dz/UniFAR-FTUs huggingface dataset:
Kobe University Repository : Kernel タイトル Tit le Car Trip Generat ion Models in the Developing World : Data Issues and Spat ial

In many countries of the developing world, it is difficult to conduct large-scale household travel surveys to collect data for travel behaviour model estimation and application. This paper focuses on two candidate solutions to the problem: (1) developing models that can be applied for prediction using secondary data collected for other purposes and include sociodemographic information but do not include transport specific information such as the car and/or transit pass ownership (e.g. census, public health records, etc.), (2) ‘borrowing’ a model developed using data from a similar city within the same region. In the first approach, we investigate the feasibility of developing car trip generation models which imputes the car ownership variable with estimated car ownership propensities. The proposed framework is applied in two East African cities, Nairobi and Dar-es-Salaam. The estimation results indicate that for both cities the proposed approach outperforms the models that exclude the car ownership variable. In the second approach, we investigate the spatial transferability of the models developed in the first approach between the two cities to evaluate if it is justified to apply models from one developing country to another in the absence of local models. Results indicate that though some of the estimated parameters are not significantly different from each other between the two cities, statistical tests do not support direct transferability of all the models from Nairobi to Dar-es-Salaam or vice versa. However, interestingly, the simpler model (which excludes car-ownership) outperforms the model with imputed car ownership propensity in terms of transferability. These findings provide useful insights into the development of trip generation models under data constraints which can practically be very useful for developing countries.
NDT_A_290104 1021..1034

1Institute of Primary Care, University of Zürich, University Hospital Zürich, Zürich, Switzerland; 2Department of Health Sciences, Helsana Insurance Group, Zürich, Switzerland Purpose: This study aimed to give a nationwide comprehensive picture of the prevalence and prescription patterns of benzodiazepines (BZ) and Z-drugs (ZD) in Switzerland and to analyze the association with adverse health care outcomes. Patients and Methods: A population-based, cross-sectional study was conducted, using a large health insurance database in Switzerland. Records from all adult patients with ≥1 prescription for a benzodiazepine and/or a Z-drug in 2018 were included. We calculated the prevalence of BZ and ZD user (extrapolated to the Swiss general population), the number of prescriptions and the type of provider (among each BZ and ZD only user). Multivariate logistic regression models were performed to estimate the association between drug prescription and the risk of hospitalization in different healthcare settings. Results: Of a total of 844ʹ692 patients, 95ʹ179 had ≥1 BZ and/or ZD prescription in 2018. The extrapolated one-year prevalence for the general Swiss population was 8.1% for a BZ prescription, 3.5% for a ZD prescription, and 10.5% for a BZ and/or ZD prescription, and continuously increased with age. The majority of the elderly (over 65 years) had ≥1 prescription (BZ: 51.9%; ZD: 56.9%; BZ and/or ZD: 53.5). The proportion of patients with ≥6 prescriptions per year was 23.1% for BZ only user and 35.2% for ZD only user. Most patients had ≥1 prescription from a general practitioner. Regression models showed a higher likelihood to be admitted to acute care, psychiatry, rehabilitation, or nursing home with ≥1 prescription for a benzodiazepine and/or a Z-drug. Conclusion: This study is the first to give a nationwide overview of the current use of benzodiazepines and Z-drugs in Switzerland based on health insurance claims data. The results revealed a remarkably high prevalence among the general Swiss population, especially in older generations. The negative consequences of heavy BZ and ZD use are a crucial public health problem, that should be addressed.
The mental health and wellbeing of spouses, partners and children of emergency responders: A systematic review

Emergency responders (ERs), often termed First Responders, such as police, fire and paramedic roles are exposed to occupational stressors including high workload, and exposure to trauma from critical incidents, both of which can affect their mental health and wellbeing. Little is known about the impact of the ER occupation on the mental health and wellbeing of their families. The aim of the current study was to investigate what mental health and wellbeing outcomes and experiences have been researched internationally in ER families, and to examine the prevalence and associated risk and protective factors of these outcomes. We conducted a systematic review in accordance with an a priori PROSPERO approved protocol (PROSPERO 2019 CRD42019134974). Forty-three studies were identified for inclusion. The majority of studies used a quantitative, cross-sectional design and were conducted in the United States; just over half assessed police/law enforcement families. Themes of topics investigated included: 1) Spousal/partner mental health and wellbeing; 2) Couple relationships; 3) Child mental health and wellbeing; 4) Family support and coping strategies; and 5) Positive outcomes. The review identified limited evidence regarding the prevalence of mental health and wellbeing outcomes. Family experiences and risk factors described were ER work-stress spillover negatively impacting spousal/partner wellbeing, couple relationships, and domestic violence. Traumatic exposure risk factors included concerns family had for the safety of their ER partner, the negative impact of an ER partners’ mental health problem on the couples’ communication and on family mental health outcomes. Protective factors included social support; however, a lack of organisational support for families was reported in some studies. Study limitations and future research needs are discussed. Progressing this area of research is important to improve knowledge of baseline needs of ER families to be able to target interventions, improve public health, and support ER’s operational effectiveness.
Elevated preoperative CA125 is associated with poor survival in patients with metastatic colorectal cancer undergoing primary tumor resection: a retrospective cohort study

Abstract Background The impact of the preoperative carbohydrate antigen 125 (CA125) level on the survival of metastatic colorectal cancer (CRC) patients undergoing primary tumor resection (PTR) remains uncertain. The aim of this study was to assess the prognostic value in overall survival (OS) and cancer-specific survival (CSS) between patients with and without an elevated preoperative CA125 level. Methods All metastatic CRC patients receiving PTR between 2007 and 2017 at the Sixth Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) were retrospectively included. OS and CSS rates were compared between patients with and without elevated preoperative CA125 levels. Results Among 326 patients examined, 46 (14.1%) exhibited elevated preoperative CA125 levels and the remaining 280 (85.9%) had normal preoperative CA125 levels. Patients with elevated preoperative CA125 levels had lower body mass index, lower preoperative albumin level, lower proportion of preoperative chemotherapy, higher carcinoembryonic antigen and carbohydrate antigen 19–9 (CA19–9) levels, poorer differentiation, and more malignant histopathological type than patients with normal preoperative CA125 levels. In addition, patients with elevated preoperative CA125 levels exhibited more advanced pathological T and N stages, more peritoneal metastasis, and more vessel invasion than patients with normal preoperative CA125 levels. Moreover, the primary tumor was more likely to be located at the colon rather than at the rectum in patients with elevated CA125 levels. Both OS and CSS rates in patients with elevated preoperative CA125 levels were significantly lower than those in patients with normal preoperative CA125 levels. Multivariate Cox regression analysis revealed that an elevated preoperative CA125 level was significantly associated with poor prognosis in metastatic CRC patients undergoing PTR. The hazard ratio (HR) in OS was 2.36 (95% confidence interval [CI], 1.67–3.33, P < 0.001) and the HR in CSS was 2.50 (95% CI, 1.77–3.55, P < 0.001). The survival analysis stratified by peritoneal metastasis also demonstrated that patients with elevated preoperative CA125 levels had lower OS and CSS rates regardless of peritoneal metastasis. Conclusion Based on an analysis of metastatic CRC patients undergoing PTR, an elevated preoperative CA125 level was associated with poor prognosis, which should be taken into consideration in clinical practice.
Association Between Some Different Obesity Anthropometric Indices and Type 2 Diabetes Mellitus in Middle-Aged and Elderly Chinese Men and Women in Beijing, China: A Cross-Sectional Study

Background Obesity can lead to the development of type 2 diabetes mellitus (T2DM). However, the predictive power of different obesity anthropometric indices (ObAIs) for T2DM varies with race and geographical area. Therefore, the study aimed to investigate the association between different ObAIs and T2DM and determine the best index for screening T2DM in middle-aged and elderly men and women in Beijing, China. Methods A cross-sectional study was conducted in Shijingshan district (Beijing, China) from November 2011 to August 2012, involving a total of 14,558 subjects aged ≥40 years. Data on demographic information, lifestyle, history of T2DM, hypertension and dyslipidemia were collected. Body height, body weight, waist circumference (WC), hip circumference, and blood pressure were recorded. The oral glucose tolerance test or a standard meal test and blood lipid test were performed. The relationship between different ObAIs and T2DM was analyzed using multiple logistic regression. Results After adjustment for age, smoking status, alcohol intake, occupation and education degree, diabetes family history, hypertension and dyslipidemia, body mass index (BMI), WC, waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were positively associated with T2DM in both men and women. Compared with the lowest BMI, WC, WHR, and WHtR quartiles, ORs of the highest quartiles were 2.131 (95% CI: 1.465–3.099), 1.752 (95% CI: 1.270–2.417), 1.342 (95% CI: 1.072–1.678), 2.739 (95% CI: 2.293–3.271) in men and 1.837 (95% CI: 1.584–2.130), 3.122 (95% CI: 1.980–4.924), 3.781 (95% CI: 2.855–5.007), 2.379 (85% CI: 2.040–2.775), respectively, in women. The areas under ROC curve of BMI, WC, WHR, and WHtR for men were 0.584 (95% CI: 0.568–0.600), 0.509 (95% CI: 0.492–0.525), 0.501 (95% CI: 0.485–0.518), and 0.642 (95% CI: 0.627–0.658) and 0.619 (95% CI: 0.607–0.632), 0.709 (95% CI: 0.697–0.720), 0.741 (95% CI: 0.730–0.752), and 0.654 (95% CI: 0.642–0.666), respectively, for women. Conclusion WHtR and WHR have been found to perform better as predictors of T2DM in middle-aged and elderly Chinese men and women, respectively.
Deep learning for behaviour classification in a preclinical brain injury model

The early detection of traumatic brain injuries can directly impact the prognosis and survival of patients. Preceding attempts to automate the detection and the assessment of the severity of traumatic brain injury continue to be based on clinical diagnostic methods, with limited tools for disease outcomes in large populations. Despite advances in machine and deep learning tools, current approaches still use simple trends of statistical analysis which lack generality. The effectiveness of deep learning to extract information from large subsets of data can be further emphasised through the use of more elaborate architectures. We therefore explore the use of a multiple input, convolutional neural network and long short-term memory (LSTM) integrated architecture in the context of traumatic injury detection through predicting the presence of brain injury in a murine preclinical model dataset. We investigated the effectiveness and validity of traumatic brain injury detection in the proposed model against various other machine learning algorithms such as the support vector machine, the random forest classifier and the feedforward neural network. Our dataset was acquired using a home cage automated (HCA) system to assess the individual behaviour of mice with traumatic brain injury or non-central nervous system (non-CNS) injured controls, whilst housed in their cages. Their distance travelled, body temperature, separation from other mice and movement were recorded every 15 minutes, for 72 hours weekly, for 5 weeks following intervention. The HCA behavioural data was used to train a deep learning model, which then predicts if the animals were subjected to a brain injury or just a sham intervention without brain damage. We also explored and evaluated different ways to handle the class imbalance present in the uninjured class of our training data. We then evaluated our models with leave-one-out cross validation. Our proposed deep learning model achieved the best performance and showed promise in its capability to detect the presence of brain trauma in mice.
CD4CD28 T cells in coronary artery disease: when helpers become killers

The crucial role of T cells in atherosclerosis and coronary artery disease (CAD) has been highlighted by recent observations. Helper CD4þ T cells can both aggravate or attenuate the atherogenic process and the development of CAD. CD4þCD28null T cells are an unusual subset of helper cells which expand and have deleterious effects in CAD. In this review, we discuss the current issues on the generation of CD4þCD28 Tcells and focus on their phenotypic and functional characteristics relevant to the development of cardiovascular events. The possible effects of the present day therapies for CAD on the CD4þCD28null Tcells are also explored. Targeting the CD4þCD28null Tcell subset in CAD could provide novel therapeutic strategies to prevent acute life-threatening coronary events.
Misleading graphs in context: Less misleading than expected

Misleading graphs are a source of misinformation that worry many experts. Especially people with a low graph literacy are thought to be persuaded by graphs that misrepresent the underlying data. But we know little about how people interpret misleading graphs and how these graphs influence their opinions. In this study we focus on the effect of truncating the y-axis for a line chart which exaggerates an upgoing trend. In a randomized controlled trial, we showed participants either a normal or a misleading chart, and we did so in two different contexts. After they had seen the graphs, we asked participants their opinion on the trend and to give an estimation of the increase. Finally we measured their graph literacy. Our results show that context is the only significant factor in opinion-forming; the misleading graph and graph literacy had no effect. None of these factors had a significant impact on estimations for the increase. These results show that people might be less susceptible to misleading graphs than we thought and that context has more impact than a misleading y-axis.
Stachys pilifera Benth: A Review of Its Botany, Phytochemistry, Therapeutic Potential, and Toxicology

Background Stachys L. (Lamiaceae) includes more than 300 annual or perennial species growing in temperate regions of Southern Africa, the Mediterranean, America, and Asia. Stachys pilifera Benth (S. pilifera), also known as Marzeh Kuhi, is an endemic species from Iran. It is found in the mountainous habitats of the Zagros area. It has various traditional uses, and the phytochemical ingredients and some biological activities of this species have been examined in previous studies. Methods PubMed, Science Direct, Google Scholar, Scopus, and Science Web databases were used to gather the data. The purpose of this review is to consolidate the scattered knowledge reported in the literature about botany, traditional uses, phytochemistry, pharmacological properties, and safety of S. pilifera and suggest its potential medicinal properties. Key Findings. In traditional Iranian medicine, S. pilifera manages various illnesses, such as rheumatoid arthritis, common cold, infections, asthma, and tussive. More than 30 compounds have been identified in S. pilifera essential oil. The compounds found in S. pilifera are phenolic compounds, monoterpenes, sesquiterpenes, flavonoids, alkaloids, and terpenoids, which have various properties such as antioxidant, nephroprotective, anti-inflammatory, antimicrobial, hepatoprotective, and anticancer properties. Conclusions The literature reveals that S. pilifera is an essential source of bioactive phytochemicals and illustrates the unknown area of this plant for new investigations. Moreover, we recommend that future research focus on toxicology and quality control studies for S. pilifera to fill the knowledge gap and provide theoretical support for the plant's possible functional and clinical uses.
Saireito, a Japanese herbal medicine, alleviates leaky gut associated with antibiotic-induced dysbiosis in mice

Antibiotics disrupt normal gut microbiota and cause dysbiosis, leading to a reduction in intestinal epithelial barrier function. Disruption of the intestinal epithelial barrier, which is known as “leaky gut”, results in increased intestinal permeability and contributes to the development or exacerbation of gastrointestinal diseases such as inflammatory bowel disease and irritable bowel syndrome. We have previously reported on a murine model of intestinal epithelial barrier dysfunction associated with dysbiosis induced by the administration of ampicillin and vancomycin. Saireito, a traditional Japanese herbal medicine, is often used to treat autoimmune disorders including ulcerative colitis; the possible mechanism of action and its efficacy, however, remains unclear. In this study, we examined the efficacy of Saireito in our animal model for leaky gut associated with dysbiosis. C57BL/6 mice were fed a Saireito diet for the entirety of the protocol (day1-28). To induce colitis, ampicillin and vancomycin were administered in drinking water for the last seven consecutive days (day22-28). As previously demonstrated, treatment with antibiotics caused fecal occult bleeding, cecum enlargement with black discoloration, colon inflammation with epithelial cell apoptosis, and upregulation of pro-inflammatory cytokines. Oral administration of Saireito significantly improved antibiotics-induced fecal occult bleeding and cecum enlargement by suppressing inflammation in the colon. Furthermore, Saireito treatment ensured the integrity of the intestinal epithelial barrier by suppressing apoptosis and inducing cell adhesion proteins including ZO-1, occludin, and E-cadherin in intestinal epithelial cells, which in turn decreased intestinal epithelial permeability. Moreover, the reduced microbial diversity seen in the gut of mice treated with antibiotics was remarkably improved with the administration of Saireito. In addition, Saireito altered the composition of gut microbiota in these mice. These results suggest that Saireito alleviates leaky gut caused by antibiotic-induced dysbiosis. Our findings provide a potentially new therapeutic strategy for antibiotic-related gastrointestinal disorders.
Prediction for Distant Metastasis of Breast Cancer Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging Images under Deep Learning

This research aimed to explore the effect of using magnetic resonance imaging (MRI) radiomic features to establish a model for predicting distant metastasis under dynamic contrast-enhanced MRI imaging with deep learning algorithms. The deep learning algorithm was used to segment the images. A total of 96 cases with 100 lesions were included in the metastatic group, including 2 cases of bifocal breast cancer and 2 cases of multifocal breast cancer. There were 192 cases in the nonmetastatic group, with 197 lesions, including 5 cases of multifocal breast cancer. After dynamic contrast-enhancement, the morphological features and grayscale statistical features were extracted from the lesions to establish a prediction model through sum-sum check and feature dimension reduction. The accuracy, sensitivity, specificity, and area under receiver operator characteristic curve (AUC) of prediction models based only on imaging features were compared with those created by combining radiomic features with clinical and pathological features. The created predictive model based on radiomic features for distant metastases in breast cancer showed a sensitivity of 66.7%, a specificity of 84.2%, an accuracy of 78.3%, and an AUC of 0.744. The sensitivity of the prediction model for distant metastasis of breast cancer was 67.7%, the specificity was 86.8%, the accuracy was 80.5%, and the AUC was 0.763. Bone, lung, and liver were the most common distant metastatic sites of breast cancer. Under the dynamic contrast-enhanced MRI of deep learning, the prediction model combining radiomic features with clinical and pathological features showed better predictive performance.
Role of maternal and child health services on the uptake of contraceptive use in India: A reproductive calendar approach

Background According to the latest round of National Family Health Survey—4 (NFHS (2015–16)) maternal and child health care (MCH) services improved drastically compared to NFHS-3. Previous studies have established that the uptake of MCH services increases the likelihood of early adoption of contraceptives among women. So, our study aims to examine if the early initiation of contraceptive has proportionately improved with the recent increase in MCH services. Methods This study used the reproductive calendar of NFHS-4, 2015–16, to evaluate contraceptive initiation within 12 months after the last birth among 1,36,962 currently married women in India. A complementary log-log regression model was created to examine the link between the time of initiation of contraception and MCH care at the national level. Results It was found that only a quarter of women within 12 months from last birth have adopted the modern contraceptive method. Among those majority of the females adopted sterilization mostly at the time of birth. The multivariable model identified, that the period of initiation of contraceptive depends on the gender composition of children and access to MCH services. It was found that the odds of early initiation of contraceptive use was higher when a women have only son (AOR = 1.15,95% CI– 1.22, 1.18) compared to women with only daughter. Also, it was found that women who have availed MCH services were more likely to adopt contraceptives earlier. Conclusion The number of women availing MCH services has increased in India, but it did not result in a proportional increase in initiation of contraception after childbirth. Facilitating family planning services alongside MCH services will be beneficial in low-resource settings. It is a golden opportunity to educate and encourage women for early adoption of contraceptive.