Miracle-dz/UniFAR-FTUs huggingface dataset:
SLEEP: intervention with weighted blankets for children with attention deficit hyperactivity disorder (ADHD) and sleep problems: study protocol for a randomised control trial

Introduction and objectives Children with attention deficit hyperactivity disorder (ADHD) have an increased risk of sleep problems. Weighted blankets are one possible non-pharmacological intervention for these problems in this group of children. However, the effectiveness of weighted blankets is insufficiently investigated. This study aims to investigate the effectiveness of weighted blankets in terms of sleep, health-related outcomes and cost-effectiveness as well as to explore children’s and parents’ experiences of a sleep intervention with weighted blankets. Methods and analysis This study is a randomised placebo-controlled crossover trial comparing the effect of weighted fibre blankets (active) with fibre blankets without weight (control). Children aged 6–13 years, recently diagnosed with uncomplicated ADHD with verified sleep problems, were included in the study. The study period is 4 weeks for each condition, respectively, and then an 8-week follow-up. A total of 100 children diagnosed with ADHD and sleep problems will enter the study. The primary outcomes are sleep and cost per quality-adjusted life years. The secondary outcomes are health-related quality of life, ADHD symptoms, psychological distress and anxiety. Interviews with a subsample of the participating children and parents will be conducted for exploring the experiences of the intervention. Ethics and dissemination Ethical approval of the trial has been obtained from the Swedish Ethical Review Authority (number 2019–-2158) and conforms to the principles outlined in the Declaration of Helsinki (WMA, 2013). Results will be reported as presentations at peer-review conferences, in articles in peer-review journals and meetings with healthcare providers. Trial registration number NCT04180189.
Routinely accessible parameters of mineralocorticoid receptor function, depression subtypes and response prediction: a post-hoc analysis from the early medication change trial in major depressive disorder

Abstract Objectives Previous studies indicated a relationship between aldosterone, the mineralocorticoid receptor (MR), and antidepressant treatment outcome. Physiological indicators of MR function (blood pressure and electrolytes) are easily accessible and may therefore serve as useful predictors. Thus, our aim was to investigate the predictive value of peripheral MR-related markers for antidepressant treatment outcomes. Methods 826 MDD patients who had participated in the randomised-controlled Early Medication Change (EMC) trial were analysed. Depression severity and MR-related markers were assessed weekly. In 562 patients, genetic variation of five MR-related genes was determined. Results Patients with blood pressure <120mmHg showed higher depression severity (p = 0.005) than patients with blood pressure ≥120mmHg. Patients with a melancholic subtype had significantly lower blood pressures (p = 0.004). Na+/K+ ratio was positively and K+-concentration was negatively correlated to depression severity and to relative changes in HAMD from baseline to day 14, and 56 respectively (p < 0.001). For none of the MR-related genes, genetic variation was associated with treatment outcomes. Conclusions We confirmed early observations of an altered peripheral MR sensitivity, reflected by lower blood pressure, low K+ or high Na+/K+ ratio in patients with more severe depression. These routinely collected biomarkers may potentially be useful for risk stratification in an early stage of treatment. Trial Registration: clinicaltrials.gov Identifier: NCT00974155; https://www.clinicaltrials.gov/ct2/results? term=NCT00974155
Strategies Employed by Forensic Community Mental Health Nurses to Resolve Difficulties in Supporting Offenders With Mental Disorders Under the Medical Treatment and Supervision Act in Japan

ABSTRACT Objective This study aimed to identify the strategies used by forensic community mental health nurses to resolve difficulties in supporting offenders with mental disorders under the Medical Treatment and Supervision Act in Japan. Method Interviews were conducted with 13 nurses, and the data were analyzed using content analysis. Results The study identified the strategies for difficulties in (a) assessing and managing risk potential of forensic service patients, (b) addressing offending behavior, (c) managing the transition of patients, (d) supporting patients to understand the impact of justice processes and applying knowledge of legislation to nursing, and (e) promoting the role of forensic community mental health nurses within the multidisciplinary team. Conclusions The findings can benefit and support forensic community mental health nurses' practices. The Japanese forensic community mental health nurses experiencing difficulties and providing home visits to patients can utilize the identified strategies.
Usability and Accessibility of the ArtontheBrain™ Virtual Recreation Activity for Older Adults With Low Vision Due to Age-Related Macular Degeneration

Experiencing visual art can inspire, be an overall positive leisure activity, and has been linked to improved cognition, especially in older adults. Access to artwork in a museum environment can comprise a variety of barriers, including difficulties linked to its visual experience for persons that are visually impaired. The present study explored the barriers and facilitators experienced by 15 older adults (age 65 to 93) living with age-related macular degeneration when using an iPad to access ArtontheBrain™, a virtual art museum recreation experience created by members of this team. Using the Concurrent Think Aloud method, participants were asked to continuously comment on their experiences with the application while being audio/video recorded. Indeed, codes were determined by identifying frequently stated and emphasized ideas or behaviors of participants using the ArtontheBrain™ application. Transcripts underwent thematic analysis and indicated that the main access barriers were linked to control of the contrast, magnification, and the tactile interface on the tablet device. The learn and play activities as well as the text-to-speech feature were identified as facilitators for ArtontheBrain™ engagement. The present findings should also be considered in the larger context of application development, as this study provides insight pertaining to the needs of low vision individuals regarding usability and accessibility.
Vitamin C Deficiency Causes Cell Type–Specific Epigenetic Reprogramming and Acute Tubular Necrosis in a Mouse Model

Significance Statement Vitamin C levels decline in patients with various kidney diseases, but the role of the vitamin as an epigenetic regulator in the initiation and progression of kidney diseases has not been characterized. Using Gulo−/− mice, which, like humans, entirely depend on dietary vitamin C, we applied single-cell RNA sequencing, whole genome bisulfite sequencing, and methylated RNA immunoprecipitation sequencing to create the first comprehensive renal cell type–specific transcriptional and DNA/RNA methylation profiles. Vitamin C deficiency induced acute tubular necrosis (ATN) and remodeled DNA/RNA epigenetic modifications in a cell type–specific manner. Cisplatin-induced ATN and AKI had similar transcriptional profiles as Gulo−/− mice. An oxidation-resistant vitamin C derivative, APM, can prevent kidney injuries in cisplatin-induced ATN mice. These findings will aid development of vitamin C as an epigenetic therapy for kidney diseases. Visual Abstract Background Vitamin C deficiency is found in patients with variable kidney diseases. However, the role of vitamin C as an epigenetic regulator in renal homeostasis and pathogenesis remains largely unknown. Methods We showed that vitamin C deficiency leads to acute tubular necrosis (ATN) using a vitamin C–deficient mouse model (Gulo knock-out). DNA/RNA epigenetic modifications and injured S3 proximal tubule cells were identified in the vitamin C–deficient kidneys using whole-genome bisulfite sequencing, methylated RNA immunoprecipitation sequencing, and single-cell RNA sequencing. Results Integrated evidence suggested that epigenetic modifications affected the proximal tubule cells and fenestrated endothelial cells, leading to tubule injury and hypoxia through transcriptional regulation. Strikingly, loss of DNA hydroxymethylation and DNA hypermethylation in vitamin C–deficient kidneys preceded the histologic sign of tubule necrosis, indicating the causality of vitamin C–induced epigenetic modification in ATN. Consistently, prophylactic supplementation of an oxidation-resistant vitamin C derivative, ascorbyl phosphate magnesium, promoted DNA demethylation and prevented the progression of cisplatin-induced ATN. Conclusions Vitamin C played a critical role in renal homeostasis and pathogenesis in a mouse model, suggesting vitamin supplementation may be an approach to lower the risk of kidney injury.
Estimating the Effect of Liver and Pancreas Volume and Fat Content on Risk of Diabetes: A Mendelian Randomization Study.

OBJECTIVE Fat content and volume of liver and pancreas are associated with risk of diabetes in observational studies; whether these associations are causal is unknown. We conducted a Mendelian randomization (MR) study to examine causality of such associations. RESEARCH DESIGN AND METHODS We used genetic variants associated (P < 5 × 10-8) with the exposures (liver and pancreas volume and fat content) using MRI scans of UK Biobank participants (n = 32,859). We obtained summary-level data for risk of type 1 (9,358 cases) and type 2 (55,005 cases) diabetes from the largest available genome-wide association studies. We performed inverse-variance weighted MR as main analysis and several sensitivity analyses to assess pleiotropy and to exclude variants with potential pleiotropic effects. RESULTS Observationally, liver fat and volume were associated with type 2 diabetes (odds ratio per 1 SD higher exposure 2.16 [2.02, 2.31] and 2.11 [1.96, 2.27], respectively). Pancreatic fat was associated with type 2 diabetes (1.42 [1.34, 1.51]) but not type 1 diabetes, and pancreas volume was negatively associated with type 1 diabetes (0.42 [0.36, 0.48]) and type 2 diabetes (0.73 [0.68, 0.78]). MR analysis provided evidence only for a causal role of liver fat and pancreas volume in risk of type 2 diabetes (1.27 [1.08, 1.49] or 27% increased risk and 0.76 [0.62, 0.94] or 24% decreased risk per 1SD, respectively) and no causal associations with type 1 diabetes. CONCLUSIONS Our findings assist in understanding the causal role of ectopic fat in the liver and pancreas and of organ volume in the pathophysiology of type 1 and 2 diabetes.
Improving zebrafish laboratory welfare and scientific research through understanding their natural history

Globally, millions of zebrafish (Danio rerio) are used for scientific laboratory experiments for which researchers have a duty of care, with legal obligations to consider their welfare. Considering the growing use of the zebrafish as a vertebrate model for addressing a diverse range of scientific questions, optimising their laboratory conditions is of major importance for both welfare and improving scientific research. However, most guidelines for the care and breeding of zebrafish for research are concerned primarily with maximising production and minimising costs and pay little attention to the effects on welfare of the environments in which the fish are maintained, or how those conditions affect their scientific research. Here we review the physical and social conditions in which laboratory zebrafish are kept, identifying and drawing attention to factors likely to affect their welfare and experimental science. We also identify a fundamental lack knowledge of how zebrafish interact with many biotic and abiotic features in their natural environment to support ways to optimise zebrafish health and well‐being in the laboratory, and in turn the quality of scientific data produced. We advocate that the conditions under which zebrafish are maintained need to become a more integral part of research and that we understand more fully how they influence experimental outcome and in turn interpretations of the data generated.
Deletion of murine Rhoh leads to de-repression of Bcl-6 via decreased KAISO levels and accelerates a malignancy phenotype in a murine model of lymphoma

ABSTRACT RHOH/TFF, a member of the RAS GTPase super family, has important functions in lymphopoiesis and proximal T cell receptor signalling and has been implicated in a variety of leukaemias and lymphomas. RHOH was initially identified as a translocation partner with BCL-6 in non-Hodgkin lymphoma (NHL), and aberrant somatic hypermutation (SHM) in the 5ʹ untranslated region of the RHOH gene has also been detected in Diffuse Large B-Cell Lymphoma (DLBCL). Recent data suggest a correlation between RhoH expression and disease progression in Acute Myeloid Leukaemia (AML). However, the effects of RHOH mutations and translocations on RhoH expression and malignant transformation remain unknown. We found that aged Rhoh−/− (KO) mice had shortened lifespans and developed B cell derived splenomegaly with an increased Bcl-6 expression profile in splenocytes. We utilized a murine model of Bcl-6 driven DLBCL to further explore the role of RhoH in malignant behaviour by crossing RhohKO mice with Iµ-HABcl-6 transgenic (Bcl-6Tg) mice. The loss of Rhoh in Bcl-6Tg mice led to a more rapid disease progression. Mechanistically, we demonstrated that deletion of Rhoh in these murine lymphoma cells was associated with decreased levels of the RhoH binding partner KAISO, a dual-specific Zinc finger transcription factor, de-repression of KAISO target Bcl-6, and downregulation of the BCL-6 target Blimp-1. Re-expression of RhoH in RhohKOBcl-6Tg lymphoma cell lines reversed these changes in expression profile and reduced proliferation of lymphoma cells in vitro. These findings suggest a previously unidentified regulatory role of RhoH in the proliferation of tumour cells via altered BCL-6 expression. (250)
I Look at my whole body and i feel better: attentional bias, emotional and psychophysiological response by pure exposure treatment in women with obesity

Abstract Obesity is one of the most important health problems nowadays. In addition to the direct physical consequences, it is also a risk factor in the development of psychological (Eating disorders, body dissatisfaction, depression, anxiety, etc.) and social problems. Among there, body dissatisfaction is key for development and maintenance of such problems. Objective: to deepen the effectiveness of the body exposure treatment, both in its pure form and guided modality in subjective, psychological and attentional levels in people with body dissatisfaction and obesity. Methods: Evaluations were carried out in a total of 16 women with obesity and body dissatisfaction at the beginning and end of 6 treatment sessions of pure exposure in front of the mirror. The changes experienced at the subjective level (questionnaires and subjective discomfort during the sessions) and psychophysiological (eye-tracking and heart rate) were analyzed. Results: Pure exposure treatment reduces negative thoughts and emotions towards the body itself, as well as the experienced discomfort towards the most conflictive parts. Selective attention to those parts of the body classified as uglier by the participants (especially the rear view of the body) show a decrease in physiological reactivity. Conclusions: Pure exposure treatment seems to be effective in reducing subjective and psychological symptoms associated with body dissatisfaction in people with obesity, this technique could be considered a good choice for the treatment of body dissatisfaction. This step is essential to guarantee the long-term therapeutic success of any other treatment (nutritional or/and physical activity) in the future.
Prognostic impact of albumin-bilirubin score on the prediction of in-hospital mortality in patients with heart failure: a retrospective cohort study

Objectives Liver dysfunction is prevalent in patients with heart failure (HF) and can lead to poor prognosis. The albumin-bilirubin (ALBI) score is considered as an effective and convenient scoring system for assessing liver function. We analysed the correlation between ALBI and in-hospital mortality in patients with HF. Design A retrospective cohort study. Setting and participants A total of 9749 patients with HF (from January 2013 to December 2018) was enrolled and retrospectively analysed. Main outcome measures The main outcome is in-hospital mortality. Results ALBI score was calculated using the formula (log10 bilirubin [umol/L] * 0.66) + (albumin [g/L] * −0.085), and analysed as a continuous variable as well as according to three categories. Following adjustment for multivariate analysis, patients which occurred in-hospital death was remarkably elevated in tertile 3 group (ALBI ≥2.27) (OR 1.671, 95% CI 1.228 to 2.274, p=0.001), relative to the other two groups (tertile 1: ≤2.59; tertile 2: −2.59 to −2.27). Considering ALBI score as a continuous variable, the in-hospital mortality among patients with HF increased by 8.2% for every 0.1-point increase in ALBI score (OR 1.082; 95% CI 1.052 to 1.114; p<0.001). The ALBI score for predicting in-hospital mortality under C-statistic was 0.650 (95% CI 0.641 to 0.660, p<0.001) and the cut-off value of ALBI score was −2.32 with a specificity of 0.630 and a sensitivity of 0.632. Moreover, ALBI score can enhance the predictive potential of NT-pro-BNP (NT-pro-BNP +ALBI vs NT-pro-BNP: C-statistic: z=1.990, p=0.0467; net reclassification improvement=0.4012, p<0.001; integrated discrimination improvement=0.0082, p<0.001). Conclusions In patients with HF, the ALBI score was an independent prognosticator of in-hospital mortality. The predictive significance of NT-proBNP +ALBI score was superior to NT-proBNP, and ALBI score can enhance the predictive potential of NT-proBNP.
Bus Service Frequency and Bus Size Optimization Model Considering Passengers' Perception

Based on the urban transportation demand,this paper studied the dispatching problem of bus service frequency and bus size associated with urban transit to transport passengers.For the operation characteristics of dedicated-line,optimization models of maximum passengers' perception utility dispatching and average passengers' perception utility dispatching were developed respectively with the algorithms provided.An application of the models to the case of K1 bus line in Jiangyin shows that the optimization models are practical and effective for reducing the cost of bus transit operation and improving the operating efficiency of bus transit system.
Balsa: Learning a Query Optimizer Without Expert Demonstrations

Query optimizers are a performance-critical component in every database system. Due to their complexity, optimizers take experts months to write and years to refine. In this work, we demonstrate for the first time that learning to optimize queries without learning from an expert optimizer is both possible and efficient. We present Balsa, a query optimizer built by deep reinforcement learning. Balsa first learns basic knowledge from a simple, environment-agnostic simulator, followed by safe learning in real execution. On the Join Order Benchmark, Balsa matches the performance of two expert query optimizers, both open-source and commercial, with two hours of learning, and outperforms them by up to 2.8× in workload runtime after a few more hours. Balsa thus opens the possibility of automatically learning to optimize in future compute environments where expert-designed optimizers do not exist.
Convergence and Complexity of Stochastic Block Majorization-Minimization

A BSTRACT . Stochastic majorization-minimization (SMM) is an online extension of the classical principle of majorization-minimization, which consists of sampling i.i. d. data points from a ﬁxed data distribution and minimizing a recursively deﬁned majorizing surrogate of an objective function. In this paper, we introduce stochastic block majorization-minimization , where the surrogates can now be only block multi-convex and a single block is optimized at a time within a diminishing radius. Relaxing the standard strong convexity requirements for surrogates in SMM, our framework gives wider applicability including online CANDECOMP/PARAFAC (CP) dictionary learning and yields greater computational efﬁciency especially when the problem dimension is large. We provide an extensive convergence analysis on the proposed algorithm, which we derive under possibly dependent data streams, relaxing the standard i.i. d. assumption on data samples. We show that the proposed algorithm converges almost surely to the set of stationary points of a nonconvex objective under constraints at a rate O ((log n ) 1 + ε / n 1/2 ) for the empirical loss function and O ((log n ) 1 + ε / n 1/4 ) for the expected loss function, where n denotes the number of data samples processed. Under some additional assumption, the latter convergence rate can be improved to O ((log n ) 1 + ε / n 1/2 ). Our results provide ﬁrst convergence rate bounds for various online matrix and tensor decomposition algorithms under a general Markovian data setting.
Robust photon-efficient imaging using a pixel-wise residual shrinkage network

Single-photon light detection and ranging (LiDAR) has been widely applied to 3D imaging in challenging scenarios. However, limited signal photon counts and high noises in the collected data have posed great challenges for predicting the depth image precisely. In this paper, we propose a pixel-wise residual shrinkage network for photon-efficient imaging from high-noise data, which adaptively generates the optimal thresholds for each pixel and denoises the intermediate features by soft thresholding. Besides, redefining the optimization target as pixel-wise classification provides a sharp advantage in producing confident and accurate depth estimation when compared with existing research. Comprehensive experiments conducted on both simulated and real-world datasets demonstrate that the proposed model outperforms the state-of-the-arts and maintains robust imaging performance under different signal-to-noise ratios including the extreme case of 1:100.
Decision Making for Connected Automated Vehicles at Urban Intersections Considering Social and Individual Benefits

To address the coordination issue of connected automated vehicles (CAVs) at urban scenarios, a game-theoretic decision-making framework is proposed that can advance social benefits, including the traffic system efficiency and safety, as well as the benefits of individual users. Under the proposed decision-making framework, in this work, a representative urban driving scenario, i.e. the unsignalized intersection, is investigated. Once the vehicle enters the focused zone, it will interact with other CAVs and make collaborative decisions. To evaluate the safety risk of surrounding vehicles and reduce the complexity of the decision-making algorithm, the driving risk assessment algorithm is designed with a Gaussian potential field approach. The decision-making cost function is constructed by considering the driving safety and passing efficiency of CAVs. Additionally, decision-making constraints are designed and include safety, comfort, efficiency, control and stability. Based on the cost function and constraints, the fuzzy coalitional game approach is applied to the decision-making issue of CAVs at unsignalized intersections. Two types of fuzzy coalitions are constructed that reflect both individual and social benefits. The benefit allocation in the two types of fuzzy coalitions is associated with the driving aggressiveness of CAVs. Finally, the effectiveness and feasibility of the proposed decision-making framework are verified with three test cases.