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The Karapinar basin, located in the Central Anatolian part of Turkey, is subjected to land subsidence and sinkhole activity due to extensive groundwater withdrawal that began in the early 2000s. In this study, we use Interferometric Synthetic Aperture Radar (InSAR), Global Navigation Satellite System (GNSS), and groundwater level data to monitor and better understand the relations between groundwater extraction, land subsidence, and sinkhole formation in the Karapinar basin. The main observations used in the study are InSAR-derived subsidence velocity maps calculated from both Sentinel-1 (2014-2018) and COSMO-SkyMed (2016-2017) SAR data. Our analysis reveals broad areas of subsidence with rates exceeding 70 mm/yr. The InSAR-derived subsidence was compared with GNSS data acquired by a continuously operating GNSS station located in the study area, which show a similar rate of subsidence. The temporal characteristic of both InSAR and GNSS time series indicate a long-term subsidence signal superimposed by seasonal variability, which follows the overall groundwater level changes, with over 80% cross-correlation consistency. Our results also indicate that sinkhole activity is limited to slow subsidence areas, reflecting strong cohesion of near-surface rock layers that resist subsidence but yield to collapse in response to aquifer system deformation induced by groundwater extraction.Life expectancy decreases with aging, with cardiovascular, mental health, and neurodegenerative disorders strongly contributing to the total disability-adjusted life years. Interestingly, the morbidity/mortality paradox points to females having a worse healthy life expectancy. Since bidirectional interactions between cardiovascular and Alzheimer's diseases (AD) have been reported, the study of this emerging field is promising. In the present work, we further explored the cardiovascular-brain interactions in mice survivors of two cohorts of non-transgenic and 3xTg-AD mice, including both sexes, to investigate the frailty/survival through their life span. Survival, monitored from birth, showed exceptionally worse mortality rates in females than males, independently of the genotype. This mortality selection provided a "survivors" cohort that could unveil brain-cardiovascular interaction mechanisms relevant for normal and neurodegenerative aging processes restricted to long-lived animals. The results show sex-dependent distinct physical (worse in 3xTg-AD males), neuropsychiatric-like and cognitive phenotypes (worse in 3xTg-AD females), and hypothalamic-pituitary-adrenal (HPA) axis activation (higher in females), with higher cerebral blood flow and improved cardiovascular phenotype in 3xTg-AD female mice survivors. The present study provides an experimental scenario to study the suggested potential compensatory hemodynamic mechanisms in end-of-life dementia, which is sex-dependent and can be a target for pharmacological and non-pharmacological interventions.Childhood overweight and obesity prevalence has risen dramatically in the past decades, and family-based interventions may be an effective method to improve children's eating behaviors. This study aimed to evaluate the effectiveness of three different family-based interventions group-based, individual-based, or by website approach. Parents and school aged overweight or obese children, 8-12 years of age, were eligible for the study. A total of 115 children were randomly allocated in one of the three interventions, and 91 completed the study (79% compliance); Group 1 (n = 36) received group-based interventions by various experts; Group 2 (n = 30) had interpersonal family meetings with a dietitian; and Group 3 (n = 25) received training through a specifically developed website. Anthropometric, dietary, physical activity, and screen time outcomes were measured at baseline and at the end of the study. Within-group comparisons indicated significant improvement in body weight, body mass index (BMI)-z-score, physical activity, and screen time from baseline in all three study groups (p less then 0.05). Furthermore, total body fat percentage (%TBF) was also decreased in Groups 2 and 3. Between-group differences varied with body weight and %TBF change, being larger in Group 3 compared to Groups 1 and 2, in contrast to BMI-z-score, screen time, and health behaviors, which were significantly larger in Group 2 than the other two groups. In conclusion, personalized family-based interventions are recommended to successfully improve children's lifestyle and body weight status.Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and gain patient related information in clinics. RPM can be achieved with noninvasive digital technology without hindering a patient's daily activities and can enhance the efficiency of healthcare delivery in acute clinical settings. In this study, an RPM system was built using radio frequency identification (RFID) technology for early detection of suicidal behaviour in a hospital-based mental health facility. A range of machine learning models such as Linear Regression, Decision Tree, Random Forest, and XGBoost were investigated to help determine the optimum fixed positions of RFID reader-antennas in a simulated hospital ward. Empirical experiments showed that Decision Tree had the best performance compared to Random Forest and XGBoost models. An Ensemble Learning model was also developed, took advantage of these machine learning models based on their individual performance. The research set a path to analyse dynamic moving RFID tags and builds an RPM system to help retrieve patient vital signs such as heart rate, pulse rate, respiration rate and subtle motions to make this research state-of-the-art in terms of managing acute suicidal and self-harm behaviour in a mental health ward.The number of patients with cardiovascular diseases is rapidly increasing in the world. The workload of existing clinicians is consequently increasing. However, the number of cardiovascular clinicians is declining. In this paper, we aim to design a mobile and automatic system to improve the abilities of patients' cardiovascular health management while also reducing clinicians' workload. Our system includes both hardware and cloud software devices based on recent advances in Internet of Things (IoT) and Artificial Intelligence (AI) technologies. A small hardware device was designed to collect high-quality Electrocardiogram (ECG) data from the human body. A novel deep-learning-based cloud service was developed and deployed to achieve automatic and accurate cardiovascular disease detection. Twenty types of diagnostic items including sinus rhythm, tachyarrhythmia, and bradyarrhythmia are supported. Experimental results show the effectiveness of our system. Our hardware device can guarantee high-quality ECG data by removing high-/low-frequency distortion and reverse lead detection with 0.9011 Area Under the Receiver Operating Characteristic Curve (ROC-AUC) score. Our deep-learning-based cloud service supports 20 types of diagnostic items, 17 of them have more than 0.98 ROC-AUC score. For a real world application, the system has been used by around 20,000 users in twenty provinces throughout China. As a consequence, using this service, we could achieve both active and passive health management through a lightweight mobile application on the WeChat Mini Program platform. We believe that it can have a broader impact on cardiovascular health management in the world.The aim of this study was to investigate the epidemiology of kidney replacement treatment (KRT) in Italy with a focus on gender and residence. As a population-based study using administrative databases from the Campania region of Italy between 2015 and 2018, the study outcomes included diagnoses of haemodialysis, peritoneal dialysis, kidney transplant, and mortality. A total of 11,713 residents in Campania were on KRT from 2015 to 2018. The annual prevalence ranged between 1000 and 1015 patients per million population (pmp) for haemodialysis, between 115 and 133 pmp for peritoneal dialysis, and between 2081 and 2245 pmp for kidney transplant. The annual incidence ranged between 160 and 185 pmp for de novo haemodialysis and between 59 and 191 pmp for kidney transplant. Annual mortality ranged between 12.8% and 14.2% in haemodialysis, between 5.2% and 13.8% in peritoneal dialysis, and between 2.4% and 3.3% in kidney transplant. In Cox regression targeting mortality, significant HRs were found for age (95%CI = 1.05/1.05), kidney transplant (compared to haemodialysis 0.37/0.47), residence in suburban areas (1.03/1.24), and de novo dialysis incidence in years 2015-2018 (1.01/1.17). The annual rate of kidney transplant was 2.6%. In regression targeting kidney transplant rate, significant HRs were found for female gender (0.67/0.92), age (0.93/0.94), residence in suburban areas (0.65/0.98), and de novo incidence of dialysis in 2015-2018 (0.49/0.71). The existence of socioeconomic inequities in KRT is suggested by the evidence that gender and suburban residence predicted mortality and/or access to kidney transplant.Quorum sensing is a type of chemical communication by which bacterial populations control expression of their genes in a coordinated manner. This regulatory mechanism is commonly used by pathogens to control the expression of genes encoding virulence factors and that of genes involved in the bacterial adaptation to variations in environmental conditions. In phytopathogenic bacteria, several mechanisms of quorum sensing have been characterized. In this review, we describe the different quorum sensing systems present in phytopathogenic bacteria, such as those using the signal molecules named N-acyl-homoserine lactone (AHL), diffusible signal factor (DSF), and the unknown signal molecule of the virulence factor modulating (VFM) system. We focus on studies performed on phytopathogenic bacteria of major importance, including Pseudomonas, Ralstonia, Agrobacterium, Xanthomonas, Erwinia, Xylella,Dickeya, and Pectobacterium spp. For each system, we present the mechanism of regulation, the functions targeted by the quorum sensing system, and the mechanisms by which quorum sensing is regulated.Chitosan and its derivative, chitosan oligosaccharide (CO), possess hypolipidemic and anti-obesity effects. However, it is still unclear if the mechanisms are different or similar between chitosan and CO. This study was designed to investigate and compare the effects of CO and high-molecular-weight chitosan (HC) on liver lipogenesis and lipid peroxidation, adipose lipolysis, and intestinal lipid absorption in high-fat (HF) diet-fed rats for 12 weeks. selleck inhibitor Rats were divided into four groups normal control diet (NC), HF diet, HF diet+5% HC, and HF diet+5% CO. Both HC and CO supplementation could reduce liver lipid biosynthesis, but HC had a better effect than CO on improving liver lipid accumulation in HF diet-fed rats. The increased levels of triglyceride decreased lipolysis rate, and increased lipoprotein lipase activity in the perirenal adipose tissue of HF diet-fed rats could be significantly reversed by both HC and CO supplementation. HC, but not CO, supplementation promoted liver antioxidant enzymes glutathione peroxidase and superoxide dismutase activities and reduced liver lipid peroxidation.