Miracle-dz/UniFAR-FTUs huggingface dataset:
The Uso1 globular head interacts with SNAREs to maintain viability even in the absence of the coiled-coil domain

Uso1/p115 and RAB1 tether ER-derived vesicles to the Golgi. Uso1/p115 contains a globular-head-domain (GHD), a coiled-coil (CC) mediating dimerization/tethering, and a C-terminal region (CTR) interacting with golgins. Uso1/p115 is recruited to vesicles by RAB1. Genetic studies placed Uso1 paradoxically acting upstream of, or in conjunction with RAB1 (Sapperstein et al., 1996). We selected two missense mutations in uso1 resulting in E6K and G540S in the GHD that rescued lethality of rab1-deficient Aspergillus nidulans. The mutations are phenotypically additive, their combination suppressing the complete absence of RAB1, which emphasizes the key physiological role of the GHD. In living hyphae Uso1 recurs on puncta (60 s half-life) colocalizing partially with the Golgi markers RAB1, Sed5, and GeaA/Gea1/Gea2, and totally with the retrograde cargo receptor Rer1, consistent with Uso1 dwelling in a very early Golgi compartment from which ER residents reaching the Golgi recycle back to the ER. Localization of Uso1, but not of Uso1E6K/G540S, to puncta is abolished by compromising RAB1 function, indicating that E6K/G540S creates interactions bypassing RAB1. That Uso1 delocalization correlates with a decrease in the number of Gea1 cisternae supports that Uso1-and-Rer1-containing puncta are where the protein exerts its physiological role. In S-tag-coprecipitation experiments, Uso1 is an associate of the Sed5/Bos1/Bet1/Sec22 SNARE complex zippering vesicles with the Golgi, with Uso1E6K/G540S showing a stronger association. Using purified proteins, we show that Bos1 and Bet1 bind the Uso1 GHD directly. However, Bet1 is a strong E6K/G540S-independent binder, whereas Bos1 is weaker but becomes as strong as Bet1 when the GHD carries E6K/G540S. G540S alone markedly increases GHD binding to Bos1, whereas E6K causes a weaker effect, correlating with their phenotypic contributions. AlphaFold2 predicts that G540S increases the binding of the GHD to the Bos1 Habc domain. In contrast, E6K lies in an N-terminal, potentially alpha-helical, region that sensitive genetic tests indicate as required for full Uso1 function. Remarkably, this region is at the end of the GHD basket opposite to the end predicted to interact with Bos1. We show that, unlike dimeric full-length and CTR∆ Uso1 proteins, the GHD lacking the CC/CTR dimerization domain, whether originating from bacteria or Aspergillus extracts and irrespective of whether it carries or not E6K/G540S, would appear to be monomeric. With the finding that overexpression of E6K/G540S and wild-type GHD complement uso1∆, our data indicate that the GHD monomer is capable of providing, at least partially, the essential Uso1 functions, and that long-range tethering activity is dispensable. Rather, these findings strongly suggest that the essential role of Uso1 involves the regulation of SNAREs.
Examining the Impact of Physical Activity on Sleep Quality in Children With ADHD

Objective: Sleep problems have been commonly observed in children with attention deficit hyperactivity disorder (ADHD). The aim of current study was to investigate the impact of physical activity on sleep quality in young adolescent with attention deficit hyperactivity disorder. Method: A total of 33 children diagnosed with attention deficit hyperactivity disorder (mean age = 10.12 years) were randomized into intervention group and control group respectively. Mention the intervention detail here. Four specific sleep parameters, including sleep efficiency, sleep onset latency, sleep duration, and wake after sleep onset, were assessed before and after the intervention period in both groups. Results: Results revealed the significant improvements in sleep efficiency, sleep onset latency and wake after sleep onset in the intervention group but not in the control group. Conclusion: Current findings highlight the benefits of PA on enhancing sleep quality among children with ADHD.
Neural Network Reduction with Guided Regularizers

Regularization techniques such as $\mathcal{L}_1$ and $\mathcal{L}_2$ regularizers are effective in sparsifying neural networks (NNs). However, to remove a certain neuron or channel in NNs, all weight elements related to that neuron or channel need to be prunable, which is not guaranteed by traditional regularization. This paper proposes a simple new approach named"Guided Regularization"that prioritizes the weights of certain NN units more than others during training, which renders some of the units less important and thus, prunable. This is different from the scattered sparsification of $\mathcal{L}_1$ and $\mathcal{L}_2$ regularizers where the the components of a weight matrix that are zeroed out can be located anywhere. The proposed approach offers a natural reduction of NN in the sense that a model is being trained while also neutralizing unnecessary units. We empirically demonstrate that our proposed method is effective in pruning NNs while maintaining performance.
The ubiquitin ligase Uhrf2 is a master regulator of cholesterol biosynthesis and is essential for liver regeneration

Fibroblast growth factors (FGFs) are key regulators of the remarkable regenerative capacity of the liver. Mice lacking FGF receptors 1 and 2 (Fgfr1 and Fgfr2) in hepatocytes are hypersensitive to cytotoxic injury during liver regeneration. Using these mice as a model for impaired liver regeneration, we identified a critical role for the ubiquitin ligase Uhrf2 in protecting hepatocytes from bile acid accumulation during liver regeneration. During regeneration after partial hepatectomy, Uhrf2 expression increased in an FGFR-dependent manner, and Uhrf2 was more abundant in the nuclei of liver cells in control mice compared with FGFR-deficient mice. Hepatocyte-specific Uhrf2 knockout or nanoparticle-mediated Uhrf2 knockdown caused extensive liver necrosis and impaired hepatocyte proliferation after partial hepatectomy, resulting in liver failure. In cultured hepatocytes, Uhrf2 interacted with several chromatin remodeling proteins and suppressed the expression of cholesterol biosynthesis genes. In vivo, the loss of Uhrf2 resulted in cholesterol and bile acid accumulation in the liver during regeneration. Treatment with a bile acid scavenger rescued the necrotic phenotype, hepatocyte proliferation, and the regenerative capacity of the liver in Uhrf2-deficient mice subjected to partial hepatectomy. Our results identify Uhrf2 as a key target of FGF signaling in hepatocytes and its essential function in liver regeneration and highlight the importance of epigenetic metabolic regulation in this process. Description Liver regeneration in mice depends on the suppression of cholesterol biosynthesis by the ubiquitin ligase Uhrf2. Editor’s summary Signaling mediated by growth factors of the FGF family and their receptors Fgfr1 and Fgfr2 contributes to liver repair and regeneration by promoting the detoxification of hepatocyte-damaging compounds. Slabber et al. identified a role for the ubiquitin ligase Uhrf2 in FGFR-dependent hepatoprotection. Partial hepatectomy increased the expression of Uhrf2 in the liver in a manner that required Fgfr1 and Fgfr2. In hepatocytes, Uhrf2 interacted with chromatin remodeling proteins and inhibited the expression of genes involved in cholesterol biosynthesis. Hepatectomized mice lacking Uhrf2 in hepatocytes developed liver failure characterized by increased necrosis and the accumulation of cholesterol and bile acids, which was rescued by a bile acid scavenger. Thus, FGF-induced Uhrf2 protects the regenerating liver from damaging bile acids by reducing the expression of cholesterol biosynthesis genes, likely in cooperation with epigenetic regulators. —Annalisa M. VanHook
Establishing Core Symptoms of Acute Serotonin Reuptake Inhibitor Withdrawal: Results from an International Survey of Online Peer-Support Communities

Abstract Background Serotonin reuptake inhibitor (SRI) antidepressants are commonly associated with withdrawal reactions. The Discontinuation Emergent Signs and Symptoms (DESS) checklist has been considered the gold standard research and screening tool for SRI withdrawal but has several limitations, including its length, lack of specificity, and omission of baseline symptom and symptom severity scores, making it impractical for use in clinical or research settings. We investigated the prevalence and severity of common SRI withdrawal symptoms to determine whether a very small subset of symptoms can capture most occurrences of SRI withdrawal. Methods We surveyed 344 members of online peer-support communities aged 18–65, reporting withdrawal symptoms after chronic SRI treatment. The severity of nine common withdrawal symptoms was evaluated at baseline and during the withdrawal period. Results Dizziness, brain zaps, irritability/agitation, and anxiety/nervousness demonstrated the largest increase in severity during withdrawal relative to baseline. Nearly all (97.7%) of the 344 subjects and all (100%) 153 subjects with relatively low baseline symptom scores (total<5) reported a worsening of one of these four symptoms. The presence of a baseline anxiety disorder did not affect rates of withdrawal-emergent anxiety/nervousness. Conclusion Nearly all surveyed subjects reported worsening either of dizziness, brain zaps, irritability/agitation, or anxiety/nervousness in acute withdrawal. A screening test incorporating these four core symptoms may be sufficiently sensitive to rule out SRI withdrawal and may be valuable in clinical and research settings. Incorporating withdrawal symptom severity may further enhance specificity.
Multi-scale dissection of wing transparency in the clearwing butterfly Phanus vitreus

Optical transparency is rare in terrestrial organisms, and often originates through loss of pigmentation and reduction in scattering. The coloured wings of some butterflies and moths have repeatedly evolved transparency, offering examples of how they function optically and biologically. Because pigments are primarily localized in the scales that cover a colourless wing membrane, transparency has often evolved through the complete loss of scales or radical modification of their shape. Whereas bristle-like scales have been well documented in glasswing butterflies, other scale modifications resulting in transparency remain understudied. The butterfly Phanus vitreus achieves transparency while retaining its scales and exhibiting blue/cyan transparent zones. Here, we investigate the mechanism of wing transparency in P. vitreus by light microscopy, focused ion beam milling, microspectrophotometry and optical modelling. We show that transparency is achieved via loss of pigments and vertical orientation in normal paddle-like scales. These alterations are combined with an anti-reflective nipple array on portions of the wing membrane being more exposed to light. The blueish coloration of the P. vitreus transparent regions is due to the properties of the wing membrane, and local scale nanostructures. We show that scale retention in the transparent patches might be explained by these perpendicular scales having hydrophobic properties.
for Shape Reconstruction from Images

In reconstructing 3-D from images based on feature points, one usually defines a triangular mesh that has these feature points as vertices and displays the scene as a polyhedron. If the scene itself is a polyhedron, however, some of the displayed edges may be inconsistent with the true shape. This paper presents a new technique for automatically detecting and eliminating such inconsistencies by using a special template.
Evaluation of an interprofessional primary healthcare team as a new model of primary care in Quebec: a protocol for a type 2 effectiveness-implementation hybrid study

Introduction One family medicine group (FMG) in Quebec has commenced a 5-year pilot project, which is herein referred to as the Archimède model, to implement a patient-centred model based on interprofessional care and the optimal use of healthcare providers’ practice scopes. A research project will be conducted to: (1) assess this model’s effect on the FMG’s operational performance, and its users’ resource utilisation at the public health system level; (2) investigate its optimisation with respect to professional roles, interprofessional teamwork and patient-centredness and (3) document users’ experience with the model. The aim of this article is to describe the protocol that will be used for this research. Methods and analysis A hybrid implementation approach (type 2 model) will be used. We will collect both quantitative and qualitative data. Regarding the quantitative dimension, and because this is a single-unit intervention study, we will use either or both synthetic control methods and one-sample generalised linear models for analyses at the FMG level. To evaluate the broader impact of Archimède on the public health system, we will use mixed-effects models and propensity score matching methods. Regarding the qualitative research dimension, using an interpretative descriptive approach, we will document users’ experience and identify the factors that optimise professional scopes of practice, collaborative practices and patient-centredness. We will conduct individual in-depth semistructured interviews with healthcare providers, administrative staff, stakeholders involved in the Archimède model implementation and patients. Ethics and dissemination This study was approved by the Ethics Committee of the Sectoral Research in Population Health and Primary Care of the Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale (#2019-1503). The results of the investigation will be presented to the stakeholders involved in the advisory committees and at several scientific conferences. Manuscripts will be submitted to peer-reviewed journals.
Telehealth-delivered naturalistic developmental behavioural intervention with and without caregiver acceptance and commitment therapy for autistic children and their caregivers: protocol for a multi-arm parallel group randomised clinical trial

Introduction Timely access to early support that optimises autistic children’s development and their caregiver’s mental health is critical. Naturalistic developmental behavioural interventions (NDBIs) and acceptance and commitment therapy (ACT) are evidence-based supports that can enhance child learning and behaviour, and adult well-being, respectively. The traditional face-to-face delivery of these approaches is resource intensive. Further, little is known about the benefit of parallel child-focused and caregiver-focused supports. The aims of this trial are to evaluate the effectiveness and social validity of telehealth-delivered, caregiver-implemented, child-focused NDBI and caregiver-focused ACT when delivered alone and in parallel, on autistic children’s social communication and caregiver well-being. Methods and analysis The study will use a randomised, single-blind clinical trial with three parallel arms: NDBI; ACT and ACT+NDBI. We will recruit a minimum of 78, 2–5-year-old autistic children and their families throughout Aotearoa New Zealand. Support will be delivered over 13 weeks using a combination of culturally enhanced web-based modules and online group coaching. Primary outcome variables include children’s social communication/engagement with their caregiver as well as caregiver stress and will be evaluated using a repeated measures multivariate analysis of variance. Outcome variables are assessed at baseline (before randomisation), immediately postparticipation and at 3-month follow-up. Ethics and dissemination The trial is approved by the Health and Disability Ethics Committee (2022 FULL 12058). The findings of this trial will be disseminated through peer-reviewed journals and national and international conference proceedings regardless of the magnitude/direction of effect. Additionally, data will be shared with stakeholder groups, service providers and health professionals. Trial registration number Australian New Zealand Clinical Trials Registry (ACTRN12622001134718).
On the Reliability of the Area Under the ROC Curve in Empirical Software Engineering

Binary classifiers are commonly used in software engineering research to estimate several software qualities, e.g., defectiveness or vulnerability. Thus, it is important to adequately evaluate how well binary classifiers perform, before they are used in practice. The Area Under the Curve (AUC) of Receiver Operating Characteristic curves has often been used to this end. However, AUC has been the target of some criticisms, so it is necessary to evaluate under what conditions and to what extent AUC can be a reliable performance metric. We analyze AUC in relation to ϕ (also known as Matthews Correlation Coefficient), often considered a more reliable performance metric, by building the lines in the ROC space with constant value of ϕ, for several values of ϕ, and computing the corresponding values of AUC. By their very definitions, AUC and ϕ depend on the prevalence ρ of a dataset, which is the proportion of its positive instances (e.g., the defective software modules). Hence, so does the relationship between AUC and ϕ. It turns out that AUC and ϕ are very well correlated, and therefore provide concordant indications, for balanced datasets (those with ρ ≃ 0.5). Instead, AUC tends to become quite large, and hence provide over-optimistic indications, for very imbalanced datasets (those with ρ ≃ 0 or ρ ≃ 1). We use examples from the software engineering literature to illustrate the analytical relationship linking AUC, ϕ, and ρ. We show that, for some values of ρ, the evaluation of performance based exclusively on AUC can be deceiving. In conclusion, this paper provides some guidelines for an informed usage and interpretation of AUC.
A Review on Path Planning Technique for Bio-Inspired Robot

Bio-inspired robotic systems have grown in popularity during the last few years. It is the study of biological systems, the search for mechanisms, and the application of these processes to real-world constructed systems. Bio-motivated algorithms have as of late gotten a great deal of interest as a method for tackling complex streamlining issues. In the writing, the intricacy of way getting ready for bio-inspired robots has not been entirely tended to. This paper investigates seven bio-inspired algorithms ordered into two methodologies i.e., Evolutionary Algorithms and Neural Networks, late improvements in robot way arranging are likewise examined. Moreover, in the wake of gauging the advantages and downsides of every algorithm, a full examination is advertised. Transformative algorithms were viewed as dreary and inclined to the youthful combination. Bio-inspired neural networks, on the other hand, were shown to be more suitable due to their superiority in real-time performance for difficult path concerns.
Analytical review of existing techniques IoT based Home Automation and securing its data over Edge Computing using Machine Learning

Future home designs heavily rely on the smart home concept. The primary goal of Home automation is to provide pleasant, secure, efficient, and easy management or monitoring of home appliances, using sensors that save energy too. For controlling the home appliances, existing systems use Bluetooth, Zigbee, GSM Module, WLAN, or Internet Technology. Home automation systems have been further enhanced using Arduino, Node MCU, Raspberry Pi, and WIFI Module. When billions of devices are online and this data-rich world enabled by the Internet of things is fully operational, cloud computing won't be able to handle the workload. Every IoT sensor produces a significant amount of data. Data is promptly transferred to a central cloud database in cloud computing, where it is managed and stored. But occasionally, a response may be interrupted or delayed owing to a network error or a poor internet connection simply because the data centre is too far away from the device. This problem is solved by the use of edge computing, IoT device itself or the nearby node network is behind the data processing and can response in an exact manner if a specific action is needed. In the proposed paper a detailed review conducted regarding existing technologies and existing home automation system (HAS). With the same reference to IoT, new architecture needs to be developed and providing data security using the edge computing instead of Cloud Computing.
Mental Health Classification on Social-Media: Systematic Review

In recent years, digitization of clinical psychology has helped experts and researchers to determine and handle the mental health problems of masses. The mental health problems are addressed with multiple names. The social media text may or may not entitle the user for any such mental health problem due to subjective interpretation. Many learning-based approaches and computational intelligence techniques have evolved to identify the potential users under threat of clinical depression and suicidal tendency. In this manuscript, efforts have been made to encapsulate the information from recent research works from 2016 to 2021 and state-of-the-art approaches to classify the microblogs which are associated with mental health misbalancing.
Features Selection for EEG During Mental Arithmetic Task – Brain-Computer Interface

Our objective is to find an efficient technique for obtaining features that can describe the continuous and underlying temporal dynamics of electroencephalography (EEG) data during the performance of mental tasks. The statistical technique known as the paired t-test is proposed to evaluate each feature. From the alpha, beta, and gamma bands of EEG, the features like mean, root mean square, skewness, mode, data range, interquartile range (IQR), and three Hjorth parameters are extracted to differentiate a signal before-during mental arithmetic task. The results suggest how essential the feature selection procedure is for the recognition task. Hjorth parameters seen between datasets during and before the arithmetic exercise have shown a significant statistical difference (p0.05). Studying an efficient way to distinguish mental task performance based on the extracted characteristics is of tremendous relevance and practical value because they accurately capture the continuity and internal dynamic changes of the EEG signals.