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Abstract Introduction Rates of substance use are high among youth involved in the legal system (YILS); however, YILS are less likely to initiate and complete substance use treatment compared to their non legally-involved peers. There are multiple steps involved in connecting youth to needed services, from screening and referral within the juvenile legal system to treatment initiation and completion within the behavioral health system. Understanding potential gaps in the care continuum requires data and decision-making from these two systems. The current study reports on the development of data dashboards that integrate these systems’ data to help guide decisions to improve substance use screening and treatment for YILS, focusing on end-user feedback regarding dashboard utility. Methods Three focus groups were conducted with n = 21 end-users from juvenile legal systems and community mental health centers in front-line positions and in decision-making roles across 8 counties to gather feedback on an early version of the data dashboards; dashboards were then modified based on feedback. Results Qualitative analysis revealed topics related to (1) important aesthetic features of the dashboard, (2) user features such as filtering options and benchmarking to compare local data with other counties, and (3) the centrality of consistent terminology for data dashboard elements. Results also revealed the use of dashboards to facilitate collaboration between legal and behavioral health systems. Conclusions Feedback from end-users highlight important design elements and dashboard utility as well as the challenges of working with cross-system and cross-jurisdiction data.

The present study aimed to examine precision and variability in dart throwing performance and the relationships between these outcomes and bouncing, throwing and catching tasks in children with and without DCD. Children between the ages of 8 and 10 years (n = 165) were classified according to results obtained on the Movement Assessment Battery for Children (MABC-2) and divided into three groups: 65 children with severe DCD (s-DCD), 45 with moderate DCD (m-DCD) and 55 typically developing children (TD). All children performed the dart throwing test and the ball skill items of the Performance and Fitness Test (PERF-FIT). The accuracy and variability of dart throwing tasks were significantly different between TD and s-DCD (p < 0.01), and also between m-DCD and s-DCD (p < 0.01). Participants with s-DCD were also found to perform significantly worse on all PERF-FIT ball skill items than m-DCD (p < 0.001), and m-DCD were significantly poorer than TD (p < 0.001). The dart score and coefficient of variation of the long-distance task appear to be significant predictors for the ball skills and explain between 24 to 29% of their variance. In conclusion, poor results in aiming tasks using darts in children with DCD corroborate with the explanation of deficits in predictive control since the tasks require ballistic movements.

Abstract Globe-LFMC 2.0, an updated version of Globe-LFMC, is a comprehensive dataset of over 280,000 Live Fuel Moisture Content (LFMC) measurements. These measurements were gathered through field campaigns conducted in 15 countries spanning 47 years. In contrast to its prior version, Globe-LFMC 2.0 incorporates over 120,000 additional data entries, introduces more than 800 new sampling sites, and comprises LFMC values obtained from samples collected until the calendar year 2023. Each entry within the dataset provides essential information, including date, geographical coordinates, plant species, functional type, and, where available, topographical details. Moreover, the dataset encompasses insights into the sampling and weighing procedures, as well as information about land cover type and meteorological conditions at the time and location of each sampling event. Globe-LFMC 2.0 can facilitate advanced LFMC research, supporting studies on wildfire behaviour, physiological traits, ecological dynamics, and land surface modelling, whether remote sensing-based or otherwise. This dataset represents a valuable resource for researchers exploring the diverse LFMC aspects, contributing to the broader field of environmental and ecological research.

Inflammatory fibroid polyps (IFPs) are rare submucosal lesions that usually arise in the stomach. It represents 0.1% of all gastric polypoid lesions and are frequently asymptomatic. It’s usually revealed by an abdominal pain. Gastrointestinal bleeding can occur when the polyp is ulcerated. We report a case of a 72-year-old female with an IFP of the prepyloric region. The head of the polyp was thirty-five millimeters in diameter. It was revealed by an upper gastrointestinal bleeding and epigastric pain. An endoscopic resection was performed.

Antibiotic resistance of the Gram-negative bacterium Pseudomonas aeruginosa and its ability to form biofilm through the Quorum Sensing (QS) mechanism are important challenges in the control of infections caused by this pathogen. The extract of Myrtus communis (myrtle) showed strong anti-QS effect on Chromobacterium. violaceum 6267 by inhibiting 80 % of the production of violacein pigment at a sub-MIC concentration of 1/8 (31.25 μg/mL). In addition, the extract exhibited an inhibitory effect on virulence factors of P. aeruginosa PAO1 at half MIC (125 μg/mL), significantly reducing the formation of biofilms (72.02 %), the swarming activity (75 %), and the production of protease (61.83 %) and pyocyanin (97 %). The active fraction also downregulated the expression of selected regulatory genes involved in the biofilm formation and QS in the P. aeruginosa PAO1 strain. These genes included the autoinducer synthase genes (lasI and rhlI), the genes involved in the expression of their corresponding receptors (lasR and rhlR), and the pqsA genes. The analysis of the active fraction by HPLC/UV/MS and NMR allowed the identification of three phenolic compounds, 3,5-di-O-galloylquinic acid, myricetin 3-O-α-l-rhamnopyranoside (myricitrin), and myricetin 3-O-(2″-O-galloyl)-ß-d-galactopyranoside. In silico studies showed that 3,5-di-O-galloylquinic acid, with an affinity score of −9.20 kcal/mol, had the highest affinity to the active site of the CviR protein (3QP8), a QS receptor from C. violaceum. Additionally, myricetin 3-O-α-l-rhamnopyranoside (myricitrin) and myricetin 3-O-(2″-O-galloyl)-ß-d-galactopyranoside interact to a lesser extent with 3QP8. In conclusion, this study contributed significantly to the discovery of new QS inhibitors from M. communis leaves against resistant Gram-negative pathogens.

ABSTRACTThis study aimed to assess the kinetics of antibodies against the SARS-CoV-2, following natural infection in a cohort of employees of the Institut Pasteur de Tunis (IPT) and to assess the risk of reinfection over a 12-months follow-up period. A prospective study was conducted among an open cohort of IPT employees with confirmed SARS-CoV-2 infection that were recruited between September 2020 and March 2021. Sera samples were taken at 1, 3, 6, 9 and 12 months after confirmation of COVID-19 infection and tested for SARS-CoV-2-specific immunoglobulin G (IgG) antibodies to the spike (S-RBD) protein (IgG anti-S-RBD) and for neutralizing antibodies. Participants who had an initial decline of IgG anti-S-RBD and neutralizing antibodies followed by a subsequent rise in antibody titers as well as those who tested positive for SARS-CoV-2 by RT-PCR after at least 60 days of follow up were considered as reinfected. In total, 137 individuals were included with a mean age of 44.7 ± 12.3 years and a sex-ratio (Male/Female) of 0.33. Nearly all participants (92.7%) were symptomatic, and 2.2% required hospitalization. Among the 70 participants with three or more prospective blood samples, 32.8% were reinfected among whom 11 (47.8%) reported COVID-19 like symptoms. Up to 12 months of follow up, 100% and 42.9% of participants had detectable IgG anti-S-RBD and neutralizing antibodies, respectively. This study showed that humoral immune response following COVID-19 infection may persist up to 12 months after infection despite the potential risk for reinfection that is mainly explained by the emergence of new variants.

BackgroundDementia is defined as a cognitive decline that affects functional status. Longitudinal ageing surveys often lack a clinical diagnosis of dementia though measure cognition and daily function over time. We used unsupervised machine learning and longitudinal data to identify transition to probable dementia.MethodsMultiple Factor Analysis was applied to longitudinal function and cognitive data of 15,278 baseline participants (aged 50 years and more) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) (waves 1, 2 and 4-7, between 2004 and 2017). Hierarchical Clustering on Principal Components discriminated three clusters at each wave. We estimated probable or "Likely Dementia" prevalence by sex and age, and assessed whether dementia risk factors increased the risk of being assigned probable dementia status using multistate models. Next, we compared the "Likely Dementia" cluster with self-reported dementia status and replicated our findings in the English Longitudinal Study of Ageing (ELSA) cohort (waves 1-9, between 2002 and 2019, 7840 participants at baseline).ResultsOur algorithm identified a higher number of probable dementia cases compared with self-reported cases and showed good discriminative power across all waves (AUC ranged from 0.754 [0.722-0.787] to 0.830 [0.800-0.861]). "Likely Dementia" status was more prevalent in older people, displayed a 2:1 female/male ratio, and was associated with nine factors that increased risk of transition to dementia: low education, hearing loss, hypertension, drinking, smoking, depression, social isolation, physical inactivity, diabetes, and obesity. Results were replicated in ELSA cohort with good accuracy.ConclusionsMachine learning clustering can be used to study dementia determinants and outcomes in longitudinal population ageing surveys in which dementia clinical diagnosis is lacking.

National strategies for addressing chronic kidney disease (CKD) are crucial to improving kidney health. We sought to describe country-level variations in non-communicable disease (NCD) strategies and CKD-specific policies across different regions and income levels worldwide. The International Society of Nephrology Global Kidney Health Atlas (GKHA) was a multinational cross-sectional survey conducted between July and October 2018. Responses from key opinion leaders in each country regarding national NCD strategies, the presence and scope of CKD-specific policies, and government recognition of CKD as a health priority were described overall and according to region and income level. 160 countries participated in the GKHA survey, comprising 97.8% of the worlds population. Seventy-four (47%) countries had an established national NCD strategy, and 53 (34%) countries reported the existence of CKD-specific policies, with substantial variation across regions and income levels. Where CKD-specific policies existed, non-dialysis CKD care was variably addressed. 79 (51%) countries identified government recognition of CKD as a health priority. Low- and low-middle income countries were less likely to have strategies and policies for addressing CKD and have governments which recognise it as a health priority. The existence of CKD-specific policies, and a national NCD strategy more broadly, varied substantially across different regions around the world but was overall suboptimal, with major discrepancies between the burden of CKD in many countries and governmental recognition of CKD as a health priority. Greater recognition of CKD within national health policy is critical to improving kidney healthcare globally.

Despite continuous efforts of veterinary services to control rabies in dogs since 1982, rabies remains a cause of death in Tunisia, with more than five reported human cases in 2022. As little is known on the determinants of transmission of rabies in dogs, better understand which factors contribute to its spatial heterogeneity in Tunisia is critical for developing bespoke mitigation activities. In this context, we developed Bayesian Poisson mixed-effect spatio-temporal model upon all cases of rabid dogs reported in each delegation during the period from 2019 to 2021. The best fitting model highlighted the association between the risk of rabies and the mean average monthly temperature, the density of markets and the density of dogs in delegations. Interestingly, no relationship was found between intensity of vaccination in dogs and the risk of rabies. Our results provided insights into the spatio-temporal dynamics of dog rabies transmission and highlighted specific geographic locations where the risk of infection was high despite correction for associated explanatory variables. Such an improved understanding represent key information to design bespoke, cost-efficient, rabies prevention and control strategies to support veterinary services activities and policymaking.

Abstract Background Abortion in ewes causes high economic losses and represents a threat for human health due to abortive zoonotic pathogens. Objective The present study aimed to assess the knowledge, attitudes and practices (KAP) among sheep owners in the northern Tunisia regarding ewes’ abortions. Methods Between February 2021 and May 2022, a structured questionnaire containing both close and open‐ended questions was applied to 120 sheep owners in northern Tunisia. The data collected were analysed by chi‐square test using Epi info 6 software. Results The majority (75%) of participants reported a history of abortion in their sheep flocks. Sheep owners thought that the most frequent cause of abortion was physical factors, such as trauma, climate and stress (60% ± 5.5%; 48/80), followed by toxicity (15% ± 4%; 12/80), metabolic and nutritional conditions (12.5% ± 3.7%; 10/80), vaccination (5% ± 2.4%; 4/80) and infectious causes (7.5% ± 2.9%; 6/80) (p

Strobilurins, among the most used fungicides worldwide, are considered non-toxic to mammals and birds, but there is growing evidence that these compounds are highly toxic to aquatic species. Dimoxystrobin has been included in the 3rd Watch List of the European Commission, and it has been classified as very toxic to aquatic life. However, previous studies focused on acute toxicity and only two reports are available on its impact on fish, and none on its effects during the early life stages. Here, we evaluated for the first time the effects induced on zebrafish embryos and larvae by two dimoxystrobin sublethal concentrations (6.56 and 13.13 μg/L) falling in the range of predicted environmental concentrations. We demonstrated that short-term exposure to dimoxystrobin may exert adverse effects on multiple targets, inducing severe morphological alterations. Moreover, we showed enhanced mRNA levels of genes related to the mitochondrial respiratory chain and ATP production. Impairment of the swim bladder inflation has also been recorded, which may be related to the observed swimming performance alterations.

We present a method to automatically synthesize efficient, high-quality demosaicking algorithms, across a range of computational budgets, given a loss function and training data. It performs a multi-objective, discrete-continuous optimization which simultaneously solves for the program structure and parameters that best tradeoff computational cost and image quality. We design the method to exploit domain-specific structure for search efficiency. We apply it to several tasks, including demosaicking both Bayer and Fuji X-Trans color filter patterns, as well as joint demosaicking and super-resolution. In a few days on 8 GPUs, it produces a family of algorithms that significantly improves image quality relative to the prior state-of-the-art across a range of computational budgets from 10 s to 1000 s of operations per pixel (1 dB–3 dB higher quality at the same cost, or 8.5–200× higher throughput at same or better quality). The resulting programs combine features of both classical and deep learning-based demosaicking algorithms into more efficient hybrid combinations, which are bandwidth-efficient and vectorizable by construction. Finally, our method automatically schedules and compiles all generated programs into optimized SIMD code for modern processors.