Miracle-dz/UniFAR-FTUs huggingface dataset:
Biallelic variation in the choline and ethanolamine transporter FLVCR1 underlies a pleiotropic disease spectrum from adult neurodegeneration to severe developmental disorders

FLVCR1 encodes Feline leukemia virus subgroup C receptor 1 (FLVCR1), a solute carrier (SLC) transporter within the Major Facilitator Superfamily. FLVCR1 is a widely expressed transmembrane protein with plasma membrane and mitochondrial isoforms implicated in heme, choline, and ethanolamine transport. While Flvcr1 knockout mice die in utero with skeletal malformations and defective erythropoiesis reminiscent of Diamond-Blackfan anemia, rare biallelic pathogenic FLVCR1 variants are linked to childhood or adult-onset neurodegeneration of the retina, spinal cord, and peripheral nervous system. We ascertained from research and clinical exome sequencing 27 individuals from 20 unrelated families with biallelic ultra-rare missense and predicted loss-of-function (pLoF) FLVCR1 variant alleles. We characterize an expansive FLVCR1 phenotypic spectrum ranging from adult-onset retinitis pigmentosa to severe developmental disorders with microcephaly, reduced brain volume, epilepsy, spasticity, and premature death. The most severely affected individuals, including three individuals with homozygous pLoF variants, share traits with Flvcr1 knockout mice and Diamond-Blackfan anemia including macrocytic anemia and congenital skeletal malformations. Pathogenic FLVCR1 missense variants primarily lie within transmembrane domains and reduce choline and ethanolamine transport activity compared with wild-type FLVCR1 with minimal impact on FLVCR1 stability or subcellular localization. Several variants disrupt splicing in a mini-gene assay which may contribute to genotype-phenotype correlations. Taken together, these data support an allele-specific gene dosage model in which phenotypic severity reflects residual FLVCR1 activity. This study expands our understanding of Mendelian disorders of choline and ethanolamine transport and demonstrates the importance of choline and ethanolamine in neurodevelopment and neuronal homeostasis.
Deep Learning for Multi-Label Disease Classification of Retinal Images: Insights from Brazilian Data for AI Development in Lower-Middle Income Countries

Retinal fundus imaging is a powerful tool for disease screening and diagnosis in opthalmology. With the advent of machine learning and artificial intelligence, in particular modern computer vision classification algorithms, there is broad scope for technology to improve accuracy, increase accessibility and reduce cost in these processes. In this paper we present the first deep learning model trained on the first Brazilian multi-label opthalmological datatset. We train a multi-label classifier using over 16,000 clinically-labelled fundus images. Across a range of 13 retinal diseases, we obtain frequency-weighted AUC and F1 scores of 0.92 and 0.70 respectively. Our work establishes a baseline model on this new dataset and furthermore demonstrates the applicability and power of artificial intelligence approaches to retinal fundus disease diagnosis in under-represented populations.
Thalamocortical network neuromodulation for epilepsy

Objectives Despite the growing interest in network-guided neuromodulation for epilepsy, uncertainty about the safety and long-term efficacy of thalamocortical stimulation persist. Our evaluation focused on the use of a 4-lead open-loop implantable pulse generator (IPG) for thalamocortical network neuromodulation. Methods We retrospectively reviewed seven subjects with diverse seizure networks (SNs)-poorly localized, regional, or multifocal-undergoing thalamocortical neuromodulation. Employing a 4-lead system, electrodes targeted both thalamic and cortical SN nodes. We assessed seizure severity, life satisfaction, and sleep quality on a 10-point scale, and seizure frequency via telephone interviews and chart review. Six subjects underwent open-loop stimulation trials during intracranial EEG (iEEG) to confirm SN engagement and optimize settings, targeting the suppression of interictal epileptiform discharges (IEDs) and seizures. Outcomes were assessed by Wilcoxon sign-rank test, 0.05 significance level. Results After a median of 17 months post-implantation (range 13-60), subjects had a median disabling seizure reduction of 93% (range 50-100%, p=0.0156), with 100% responder rate ([≥] 50% reduction in seizure frequency). The median improvement in seizure severity was 3.5 out of 10 points (p=0.0312), life satisfaction 4.5 points (p= 0.0312), and quality of sleep 3 points (p=0.062). No perioperative complications occurred. Rare transient seizure exacerbations and stimulation-related sensory/motor side effects resolved with parameter adjustments. One subject required surgical revision due to delayed infection. Six subjects had permanent electrode placement refined by iEEG trial stimulation; five subjects had >90% reduction in seizure frequency during iEEG stimulation. Significance Thalamocortical network neuromodulation using a 4-lead open-loop system is safe, and is associated with significant improvements in seizure control and patient quality of life. Trial stimulation during iEEG shows promise for enhancing SN engagement and parameter optimization, but requires further study. Prospective controlled trials are needed to establish the validity of thalamocortical network neuromodulation for epilepsy.
VirGrapher: a graph-based viral identifier for long sequences from metagenomes

Abstract Viruses are the most abundant biological entities on earth and are important components of microbial communities. A metagenome contains all microorganisms from an environmental sample. Correctly identifying viruses from these mixed sequences is critical in viral analyses. It is common to identify long viral sequences, which has already been passed thought pipelines of assembly and binning. Existing deep learning-based methods divide these long sequences into short subsequences and identify them separately. This makes the relationships between them be omitted, leading to poor performance on identifying long viral sequences. In this paper, VirGrapher is proposed to improve the identification performance of long viral sequences by constructing relationships among short subsequences from long ones. VirGrapher see a long sequence as a graph and uses a Graph Convolutional Network (GCN) model to learn multilayer connections between nodes from sequences after a GCN-based node embedding model. VirGrapher achieves a better AUC value and accuracy on validation set, which is better than three benchmark methods.
Kinetics and mechanical work done to move the body centre of mass along a curve

When running on a curve, the lower limbs interact with the ground to redirect the trajectory of the centre of mass of the body (CoM). The goal of this paper is to understand how the trajectory of the CoM and the work done to maintain its movements relative to the surroundings (Wcom) are modified as a function of running speed and radius of curvature. Eleven participants ran at different speeds on a straight line and on circular curves with a 6 m and 18 m curvature. The trajectory of the CoM and Wcom were calculated using force-platforms measuring the ground reaction forces and infrared cameras recording the movements of the pelvis. To follow a circular path, runners overcompensate the rotation of their trajectory during contact phases. The deviation from the circular path increases when the radius of curvature decreases and speed increases. Interestingly, an asymmetry between the inner and outer lower limbs emerges as speed increases. The method to evaluate Wcom on a straight-line was adapted using a referential that rotates at heel strike and remains fixed during the whole step cycle. In an 18 m radius curve and at low speeds on a 6 m radius, Wcom changes little compared to a straight-line run. Whereas at 6 m s-1 on a 6 m radius, Wcom increases by ~25%, due to an augmentation in the work to move the CoM laterally. Understanding these adaptations provides valuable insight for sports sciences, aiding in optimizing training and performance in sports with multidirectional movements.
A Comprehensive Exploration of Bioluminescence Systems, Mechanisms, and Advanced Assays for Versatile Applications

Bioluminescence has been a fascinating natural phenomenon of light emission from living creatures. It happens when the enzyme luciferase facilitates the oxidation of luciferin, resulting in the creation of an excited-state species that emits light. Although there are many bioluminescent systems, few have been identified. D-luciferin-dependent systems, coelenterazine-dependent systems, Cypridina luciferin-based systems, tetrapyrrole-based luciferins, bacterial bioluminescent systems, and fungal bioluminescent systems are natural bioluminescent systems. Since different bioluminescence systems, such as various combinations of luciferin-luciferase pair reactions, have different light emission wavelengths, they benefit industrial applications such as drug discovery, protein-protein interactions, in vivo imaging in small animals, and controlling neurons. Due to the expression of luciferase and easy permeation of luciferin into most cells and tissues, bioluminescence assays are applied nowadays with modern technologies in most cell and tissue types. It is a versatile technique in a variety of biomedical research. Furthermore, there are some investigated blue-sky research projects, such as bioluminescent plants and lamps. This review article is mainly based on the theory of diverse bioluminescence systems and their past, present, and future applications.
Utilizing venous occlusion plethysmography to assess vascular effects: A study with buloxibutid, an angiotensin II type 2 receptor agonist

Abstract Buloxibutid (also known as C21) is a potent and selective angiotensin II type 2 receptor (AT2R) agonist, in development for oral treatment of fibrotic lung disease. This phase I, open‐label, pharmacodynamic study investigated vascular effects of buloxibutid in five healthy male volunteers. Subjects were administered intra‐arterial infusions of buloxibutid for 5 min in ascending doses of 3, 10, 30, 100, and 200 μg/min, infused sequentially in the forearm. Infusions of sodium nitroprusside (SNP) solution in doses of 0.8–3.2 μg/min were administered as a positive control. Forearm blood flow (FBF) was measured by venous occlusion plethysmography. Safety and tolerability of intra‐arterial administrations of buloxibutid were evaluated. Following infusion of buloxibutid in doses of 3–200 μg/min, the range of increase in FBF was 27.8%, 17.2%, 37.0%, 28.5%, and 60.5%, compared to the respective baseline. The largest increase was observed in the highest dose group. Infusions of SNP as a positive control, increased FBF 230–320% compared to baseline. Three adverse events (AEs) of mild intensity, not related to buloxibutid or SNP, were reported for two subjects. Two of these AEs were related to study procedures. There were no clinically relevant changes in arterial blood pressure during the study period. Intra‐arterial infusion of buloxibutid in low, ascending doses increased FBF, indicating that buloxibutid may be effective in conditions associated with endothelial dysfunction. Venous occlusion plethysmography was found to be a useful method to explore pharmacodynamic vascular effects of novel AT2R agonists, while avoiding systemic adverse effects.
Atmospheric Diffusion (3rd edn)

F Pasquill and F B Smith 1983 Chichester: Ellis Horwood 437 pp price £35 ISBN 0 8531 24264 In its first and second editions this book has become a standard text for those involved in the study of the dispersion of pollution in the atmosphere. This third edition maintains the high standards of its predecessors and includes a thorough coverage of material which has become available since the second edition.
A novel model of divergent predictive perception

Abstract Predictive processing theories state that our subjective experience of reality is shaped by a balance of expectations based on previous knowledge about the world (i.e. priors) and confidence in sensory input from the environment. Divergent experiences (e.g. hallucinations and synaesthesia) are likely to occur when there is an imbalance between one’s reliance on priors and sensory input. In a novel theoretical model, inspired by both predictive processing and psychological principles, we propose that predictable divergent experiences are associated with natural or environmentally induced prior/sensory imbalances: inappropriately strong or inflexible (i.e. maladaptive) high-level priors (beliefs) combined with low sensory confidence can result in reality discrimination issues, a characteristic of psychosis; maladaptive low-level priors (sensory expectations) combined with high sensory confidence can result in atypical sensory sensitivities and persistent divergent percepts, a characteristic of synaesthesia. Crucially, we propose that whether different divergent experiences manifest with dominantly sensory (e.g. hallucinations) or nonsensory characteristics (e.g. delusions) depends on mental imagery ability, which is a spectrum from aphantasia (absent or weak imagery) to hyperphantasia (extremely vivid imagery). We theorize that imagery is critically involved in shaping the sensory richness of divergent perceptual experience. In sum, to predict a range of divergent perceptual experiences in both clinical and general populations, three factors must be accounted for: a maladaptive use of priors, individual level of confidence in sensory input, and mental imagery ability. These ideas can be expressed formally using nonparametric regression modeling. We provide evidence for our theory from previous work and deliver predictions for future research.
NCAPH drives breast cancer progression and identifies a gene signature that predicts luminal a tumour recurrence

Abstract Background Luminal A tumours generally have a favourable prognosis but possess the highest 10‐year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post‐diagnosis. Identifying such patients is crucial as long‐term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment. Methods We conducted a study to explore non‐structural chromosome maintenance condensin I complex subunit H’s (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels. Results We found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)‐NCAPHErbB2 double‐transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10‐gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression. Conclusions The GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.
The Emergence of HIV Transmitted Resistance in Botswana : ‘ ‘ When Will the WHO Detection Threshold Be Exceeded ?

Background. The Botswana antiretroviral program began in 2002 and currently treats 42,000 patients, with a goal of treating 85,000 by 2009. The World Health Organization (WHO) has begun to implement a surveillance system for detecting transmitted resistance that exceeds a threshold of 5%. However, the WHO has not determined when this threshold will be reached. Here we model the Botswana government’s treatment plan and predict, to 2009, the likely stochastic evolution of transmitted resistance. Methods. We developed a model of the stochastic evolution of drug-resistant strains and formulated a birth-death Master equation. We analyzed this equation to obtain an analytical solution of the probabilistic evolutionary trajectory for transmitted resistance, and used treatment and demographic data from Botswana. We determined the temporal dynamics of transmitted resistance as a function of: (i) the transmissibility (i.e., fitness) of the drug-resistant strains that may evolve and (ii) the rate of acquired resistance. Results. Transmitted resistance in Botswana will be unlikely to exceed the WHO’s threshold by 2009 even if the rate of acquired resistance is high and the strains that evolve are half as fit as the wild-type strains. However, we also found that transmission of drug-resistant strains in Botswana could increase to ,15% by 2009 if the drug-resistant strains that evolve are as fit as the wild-type strains. Conclusions. Transmitted resistance will only be detected by the WHO (by 2009) if the strains that evolve are extremely fit and acquired resistance is high. Initially after a treatment program is begun a threshold lower than 5% should be used; and we advise that predictions should be made before setting a threshold. Our results indicate that it may be several years before the WHO’s surveillance system is likely to detect transmitted resistance in other resource-poor countries that have significantly less ambitious treatment programs than Botswana.
Prevalence and correlates of depression among students in a senior high school in Ghana: A school-based cross-sectional study

Objectives: Depression is one of the most widely reported mental health issues that affect adolescents globally. However, there is a dearth of data on its prevalence and associated factors among senior high school students in Ghana, since previous studies have focused more on adult populations. This can hinder policies needed to champion mental health and mental health care in senior high schools. Hence, this study sought to assess the prevalence of depression and associated factors among senior high school students in Ghana. Methods: An analytical cross-sectional study involving 289 students at the Manya Krobo Senior High School was conducted from December 2022 to February 2023. The students were selected using a two-stage random sampling method. A questionnaire was used to collect data on sociodemographics and individual characteristics. The primary outcome was depression, and this was assessed using the Patient Health Questionnaire-9. Summary statistics were presented as means, frequencies, and percentages. Multivariate logistic regression was used to identify factors associated with depression and odds ratios presented with 95% confidence intervals. Statistical significance was considered at p-value < 0.05. Results: The mean age of the students was 16.6 (±1.2) with a range of 14–20 years. Over a quarter (26.3%) of the students reported financial difficulties. The prevalence of depression among the students was 68.9%. The factors associated with depression in this study were female sex (adjusted odds ratio: 1.74, 95% confidence interval: 1.01–2.97), age (adjusted odds ratio: 1.41, 95% confidence interval: 1.10–1.81), history of chronic health condition (adjusted odds ratio: 3.74, 95% confidence interval: 1.36–10.25), and financial difficulties (adjusted odds ratio: 2.31, 95% confidence interval: 1.15–4.63). Conclusion: This study shows that depression is rife among students at the Manya Krobo Senior High School, Manya Krobo District, Ghana. These findings call for pragmatic interventions such as strengthening counseling units and professional mental health services to ameliorate the impact of depression on the lives of students.
(U-Th)/He Thermochronology of the Ottawa Embayment, Eastern Canada: The Temperature-Time History of an Ancient, Intracratonic Rift Basin

The Ottawa Embayment is an intracratonic rift basin in eastern North America that preserves a unique and eventful history through deep time. We report single-grain zircon and apatite (U-Th)/He and biotite 40Ar/39Ar data from samples collected along a 250-km transect across the crystalline rift flank and through the sedimentary sequences of the embayment. The data sets show significant intrasample age dispersions, and we investigate the influence of zircon crystallinity and nonideal crystal shapes on He diffusion through the application of Raman spectroscopy and X-ray microcomputed tomography. Ultimately, we utilize the relationship between radiation damage and helium diffusion to quantify observed age dispersion. We integrate our age data from the basement and overlying sedimentary unit of the embayment with regional geology to utilize multisample inverse modeling to reveal viable thermal histories that we then further evaluate by using the forward modeling method to improve our understanding of the thermal history of the rift system. Modeling of the thermochronometric data shows evidence of previously unrecognized reheating events in the embayment, including (1) during rifting and breakup of Rodinia in the late Neoproterozoic (ca. 750–590 Ma); (2) in the late Paleozoic, due to a combination of burial, an elevated geothermal gradient, and hydrothermal fluids, as associated with orogenic activity; and (3) maximum Mesozoic reheating to 150°C at 100 Ma, possibly related to passage of the Great Meteor hotspot or a major plate reorganization event.
The Study on Identifying the Relationship between Opportunity Recognition and Sustainability in Small Business in Sri Lanka

Entrepreneurship nowadays is one of the fastest developing and expanding fields in the modern economic settings. Present in every industry and on both corporate and small business level, entrepreneurs are often regarded as the driving economic force for improvements and expansion. Nevertheless, with both scholars and practitioners increasingly recognizing the importance of this field and related research areas, an aspect receiving the most attention is the opportunity recognition and idea generation process. This study intends to identify whether high level opportunities mediate the relationship between opportunity recognition and firm’s sustainability. The key constructs which give more concern in the research are sustainability & opportunity recognition. A questionnaire will be used to collect data as a methodology of the research. 150 samples of entrepreneurs are to be selected & descriptive statistics will be used to analyze data. The study will generate new factors which will restrict to identify high level of entrepreneurial opportunities for Sri Lankan entrepreneurs.