Miracle-dz/UniFAR-FTUs huggingface dataset:
ProtoCell4P: an explainable prototype-based neural network for patient classification using single-cell RNA-seq

Abstract Motivation The rapid advance in single-cell RNA sequencing (scRNA-seq) technology over the past decade has provided a rich resource of gene expression profiles of single cells measured on patients, facilitating the study of many biological questions at the single-cell level. One intriguing research is to study the single cells which play critical roles in the phenotypes of patients, which has the potential to identify those cells and genes driving the disease phenotypes. To this end, deep learning models are expected to well encode the single-cell information and achieve precise prediction of patients’ phenotypes using scRNA-seq data. However, we are facing critical challenges in designing deep learning models for classifying patient samples due to (i) the samples collected in the same dataset contain a variable number of cells—some samples might only have hundreds of cells sequenced while others could have thousands of cells, and (ii) the number of samples available is typically small and the expression profile of each cell is noisy and extremely high-dimensional. Moreover, the black-box nature of existing deep learning models makes it difficult for the researchers to interpret the models and extract useful knowledge from them. Results We propose a prototype-based and cell-informed model for patient phenotype classification, termed ProtoCell4P, that can alleviate problems of the sample scarcity and the diverse number of cells by leveraging the cell knowledge with representatives of cells (called prototypes), and precisely classify the patients by adaptively incorporating information from different cells. Moreover, this classification process can be explicitly interpreted by identifying the key cells for decision making and by further summarizing the knowledge of cell types to unravel the biological nature of the classification. Our approach is explainable at the single-cell resolution which can identify the key cells in each patient’s classification. The experimental results demonstrate that our proposed method can effectively deal with patient classifications using single-cell data and outperforms the existing approaches. Furthermore, our approach is able to uncover the association between cell types and biological classes of interest from a data-driven perspective. Availability and implementation https://github.com/Teddy-XiongGZ/ProtoCell4P.
Prenatal assessment of pulmonary vasculature development in fetuses with congenital diaphragmatic hernia: A literature review

Pathophysiological studies have shown that pulmonary vascular development is impaired in fetuses with a congenital diaphragmatic hernia (CDH), leading to a simplified vascular tree and increased vascular resistance. Multiple studies have described prenatal ultrasound parameters for the assessment of the pulmonary vasculature, but none of these parameters are used in daily clinical practice. We provide a comprehensive review of the literature published between January 1990 and February 2022 describing these parameters, and aim to explain the clinical relevance of these parameters from what is known from pathophysiological studies. Prenatal detection of a smaller diameter of the contralateral (i.e. contralateral to the diaphragmatic defect) first branch of the pulmonary artery (PA), higher pulsatility indices (PI), higher peak early diastolic reverse flow values, and a lower vascularization index seem of added value for the prediction of survival and, to a lesser extent, morbidity. Integration within the routine evaluation is complicated by the lack of uniformity of the methods used. To address the main components of the pathophysiological changes, we recommend future prenatal studies in CDH with a focus on PI values, PA diameters and pulmonary vascular branching.
Association of Remdesivir use with bradycardia: A systematic review and meta‐analysis

Remdesivir has been used for coronavirus disease 2019 (COVID‐19) pneumonia with oxygen requirements that do not require mechanical intubation, and several studies showed a reduction in disease duration. However, there is a concern about bradycardia as its side effect. We aimed to investigate the association between Remdesivir and bradycardia by integrating findings from prior studies. We queried PubMed and EMBASE in February 2023 and performed a meta‐analysis of studies investigating bradycardia in patients who did or did not receive Remdesivir. The outcome of interest was the rate of bradycardia and in‐hospital mortality. We identified eight studies involving 8993 patients, of which seven studies investigated bradycardia. Six studies were observational, one was a case–control, and one was a randomized trial. Incidence of bradycardia was 400/3480 patients (22.3%, 95% confidence interval, CI: [6.5–54.4], I2 = 99%) in the Remdesivir group and 294/5005 (9.8%, 95% CI: [2.8–29], I2 = 98.61) in the non‐Remdesivir group. The odds ratio of bradycardia was 2.11 (95% CI: [1.65–2.71], I2 = 22%, p < 0.001) for the Remdesivir group. There was no difference in mortality between the two groups. Patients who received Remdesivir for COVID‐19 were more likely to develop bradycardia. The effect of confounding factors should be considered to further clarify the possible association.
Developing and deploying deep learning models in brain magnetic resonance imaging: A review

Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to alleviate the burden on radiologists and MR technologists, and improve throughput. The easy accessibility of DL tools has resulted in a rapid increase of DL models and subsequent peer‐reviewed publications. However, the rate of deployment in clinical settings is low. Therefore, this review attempts to bring together the ideas from data collection to deployment in the clinic, building on the guidelines and principles that accreditation agencies have espoused. We introduce the need for and the role of DL to deliver accessible MRI. This is followed by a brief review of DL examples in the context of neuropathologies. Based on these studies and others, we collate the prerequisites to develop and deploy DL models for brain MRI. We then delve into the guiding principles to develop good machine learning practices in the context of neuroimaging, with a focus on explainability. A checklist based on the United States Food and Drug Administration's good machine learning practices is provided as a summary of these guidelines. Finally, we review the current challenges and future opportunities in DL for brain MRI.
Clinical Prediction Models and Predictors for Death or Adverse Neurodevelopmental Outcome in Term Newborns with Hypoxic-Ischemic Encephalopathy: A Systematic Review of the Literature

Background: Although many predictive parameters have been studied, an internationally accepted, validated predictive model to predict the clinical outcome of asphyxiated infants suffering from hypoxic-ischemic encephalopathy is currently lacking. The aim of this study was to identify, appraise and summarize available clinical prediction models, and provide an overview of all investigated predictors for the outcome death or neurodevelopmental impairment in this population. Methods: A systematic literature search was performed in Medline and Embase. Two reviewers independently included eligible studies and extracted data. The quality was assessed using PROBAST for prediction model studies and QUIPS assessment tools for predictor studies. Results: A total of nine prediction models were included. These models were very heterogeneous in number of predictors assessed, methods of model derivation, and primary outcomes. All studies had a high risk of bias following the PROBAST assessment and low applicability due to complex model presentation. A total of 104 predictor studies were included investigating various predictors, showing tremendous heterogeneity in investigated predictors, timing of predictors, primary outcomes, results, and methodological quality according to QUIPS. Selected high-quality studies with accurate discriminating performance provide clinicians and researchers an evidence map of predictors for prognostication after HIE in newborns. Conclusion: Given the low methodological quality of the currently published clinical prediction models, implementation into clinical practice is not yet possible. Therefore, there is an urgent need to develop a prediction model which complies with the PROBAST guideline. An overview of potential predictors to include in a prediction model is presented.
Symptom Clusters in Patients With Advanced Cancer: A Prospective Longitudinal Cohort Study to Examine Their Stability and Prognostic Significance

Abstract This study’s purpose was to assess symptom cluster (SC) stability during disease progression and determine their strength of association with survival in patients with advanced cancer . Consecutively eligible patients with advanced cancer not receiving cancer-specific treatment and referred to a Tertiary Palliative Care Clinic were enrolled in a prospective cohort study. At first consultation (D0) and in subsequent consultations at day 15 (D15) and day 30 (D30), patients rated 9 symptoms through the Edmonton Symptom Assessment System scale (0-10) and 10 others using a Likert scale (1-5). Principal components factor analysis with varimax rotation was used to determine SCs at each consultation. Of 318 patients with advanced cancer, 301 met eligibility criteria with a median age of 69 years (range 37-94). Three SCs were identified: neuro-psycho-metabolic (NPM), gastrointestinal, and sleep impairment, with some variations in their constitution over time. Exploratory factor analysis accounted for 40% of variance of observed variables in all SCs. Shorter median survival was observed continuously for NPM cluster (D0 23 vs. 58 days, P < .001; D15 41 vs. 104 days, P=.004; D30 46 vs. 114 days, P = .002), although the presence of 2 or more SCs on D0 and D15 also had prognostic significance (D0: 21 vs. 45 days, P = .005; D30: 50 vs. 96 days, P = .040). In a multivariable model, NPM cluster (D0 hazard ratio estimate: HR 1.64; 95%CI, 1.17-2.31; P = .005; D15 HR: 2.51; 95%CI, 1.25-5.05; P = .009; D30 HR: 3.9; 95%CI, 1.54-9.86; P = .004) and hospitalization (D0 HR: 2.27; 95%CI, 1.47-3.51; P < .001; D15 HR: 2.43; 95%CI, 1.18-5.01; P = .016; D30 HR: 3.41; 95%CI, 1.35-8.62; P = .009) were independently and significantly associated with worse survival. Three clinically relevant SCs were identified, and their constitution had small variations, maintaining a stable set of nuclear symptoms through disease progression. Presence of the NPM cluster and hospitalization maintained their prognostic value over time.
Effectiveness of physical activity interventions for core symptoms of autism spectrum disorder: A systematic review and meta‐analysis

In this paper, systematic review and meta‐analysis were used to demonstrate the effectiveness of physical activity intervention on core symptoms of autism spectrum disorder (ASD). Physical activity intervention for core symptoms of ASD were retrieved by computer from the PubMed Cochrane Library, Web of Science, APA PsycNet, and CNKI database during December 1, 2022. Two researchers evaluated the quality of the included literature and extracted the data. Sixteen studies were eventually included, with a total of 587 patients with ASD. Meta‐analysis showed that the core symptoms of ASD patients decreased after physical activity intervention, ES(g) = 0.681(95% CI: 0.380–0.982, p = 0.000), specifically, physical activity improved the reduction of social disorder ES(g) = 0.749(95% CI: 0.524–0.973) and repeated rigid behavior ES(g) = 0.553 (95% CI: −0.079 to 1.186). Subgroup analysis showed that preschool children with ASD who were 3–6 years old, exercised for more than 12 weeks, more than 3 times a week, and exercised for more than 90 min per session had better improvement in core symptoms after participating in physical activity. The conclusion of this paper is that physical activity intervention can improve the core symptoms of ASD, especially the reduction of social disorders and repetitive behaviors.
History of working conditions and the risk of old-age dependency: a nationwide Swedish register-based study.

AIMS There is substantial evidence that previous working conditions influence post-retirement health, yet little is known about previous working conditions' association with old-age dependency. We examined job strain, hazardous and physical demands across working life, in relation to the risk of entering old-age dependency of care. METHODS Individually linked nationwide Swedish registers were used to identify people aged 70+ who were not receiving long-term care (residential care or homecare) at baseline (January 2014). Register information on job titles between the years 1970 and 2010 was linked with a job exposure matrix of working conditions. Random effects growth curve models were used to calculate intra-individual trajectories of working conditions. Cox regression models with age as the timescale (adjusted for living situation, educational attainment, country of birth, and sex) were conducted to estimate hazard ratios for entering old-age dependency during the 24 months of follow-up (n = 931,819). RESULTS Having initial adverse working conditions followed by an accumulation throughout working life encompassed the highest risk of entering old-age dependency across the categories (job strain: HR 1.23, 95% CI 1.19-1.27; physical demands: HR 1.36, 95% CI 1.31-1.40, and hazardous work: HR 1.35, 95% CI 1.30-1.40). Initially high physical demands or hazardous work followed by a stable trajectory, or initially low-level physical demand or hazardous work followed by an accumulation throughout working life also encompassed a higher risk of dependency. CONCLUSIONS A history of adverse working conditions increased the risk of old-age dependency. Reducing the accumulation of adverse working conditions across the working life may contribute to postponing old-age dependency.
Communication Networks: An Optimization, Control, and Stochastic Networks Perspective

Provides a modern mathematical approach to the design of communication networks for graduate students, blending control, optimization, and stochastic network theories. A broad range of performance analysis tools are discussed, including important advanced topics that have been made accessible to students for the first time. Taking a top-down approach to network protocol design, the authors begin with the deterministic model and progress to more sophisticated models. Network algorithms and protocols are tied closely to the theory, illustrating the practical engineering applications of each topic. The background behind the mathematical analyses is given before the formal proofs and is supported by worked examples, enabling students to understand the big picture before going into the detailed theory. End-of-chapter problems cover a range of difficulties, with complex problems broken into several parts, and hints to many problems are provided to guide students. Full solutions are available online for instructors.
KEANEKARAGAMAN JENIS EKHINODERMATA DI PERAIRAN TELUK KUTA, NUSA TENGGARA BARAT

Biodiversity of Echinoderms at Kuta Bay, West Nusa Tenggara. Observation on echinoderms diversity was carried out at coastal waters of Kuta bay in the Nusa Tenggara Barat, Nopember 2005. A total of 21 species of echinoderms, consist of 4 species Holothuroidea, 7 species Echinoidea, 5 species Asteroidea and 5 species Ophiuroidea have been found in the Kuta of Nusa Tenggara Barat. The Echinoidea were relatively common in the sea gras zone. On the basis of population density, Echinoidea was the dominant group and relatively highest in the individual density. In general the number of species of echinoderm fauna is smaller than in the Sekotong Lombok Barat Bay.
A conceptual model of a shallow circulation induced by prescribed low-level radiative cooling

AbstractA conceptual bulk model for a dry, convective boundary layer with prescribed horizontally homogeneous and heterogeneous low-level radiative cooling rates is developed. For horizontally homogeneous radiative cooling, the response of the system to varying its prescribed parameters is explored and formulated in terms of nondimensional parameters. Large-eddy simulations with prescribed radiative cooling rates match the results of the bulk model well. It is found that, depending on the strength of the surface coupling, the height of the boundary layer (BL) either increases or decreases in response to increasing radiative BL cooling. Another property of the system is that, for increasing surface temperature, the BL temperature decreases if the prescribed radiative BL cooling rates are strong. This counterintuitive behavior is caused by the formulation of the entrainment rate at the inversion. Heterogeneous radiative BL cooling is found to cause a circulation induced by pressure deviations between the ar.
Persepsi Guru Tentang Pelaksanaan Fungsi Kepemimpinan Kepala Sekolah

This study aims to find out (1) describe the teacher's perception of the implementation of the principal's leadership function in Public Middle School, Nanggalo District, Padang City, (2) describe the implementation of the principal's leadership seen from the implementation of the instruction function from teacher perceptions in Nanggalo District Public Middle School, Padang City , (3) describes the implementation of the principal's leadership seen from the implementation of the consulting function from teacher perceptions in the Nanggalo District Public Middle School, Padang City, (4) describes the implementation of the principal's leadership seen from the implementation of the participation function from teacher perceptions in the Nanggalo District Public Middle School, Padang City, ( 5) describe the implementation of the principal's leadership seen from the implementation of the delegation function from the perceptions of teachers at SMP Negeri Nanggalo District, Padang City, and (6) describe the implementation of the leadership of the school principal from the implementation of the control function from teacher perceptions at SMP Negeri Nanggalo District, Padang City. This type of research is descriptive research. The population in the study were teachers at Nanggalo District Public Middle School, Padang City, totaling 57 samples. Sampling using simple proportional random sampling technique. The instrument used for research is a closed questionnaire using descriptive analysis. The results showed that: (1) the teacher's perception of the implementation of the leadership function based on instruction was very good with the highest average of 4.7, (2) the teacher's perception of the implementation of the leadership function based on consultative was very good with the highest average of 4.74, ( 3) the teacher's perception of the implementation of the leadership function based on participation is good with the highest average of 4.58, (4) the teacher's perception of the implementation of the leadership function based on delegation is very good with the highest average of 4.67, and (5) the teacher's perception of the implementation leadership function based on good control with the highest average of 4.58.
Field Evaluation of Entomopathogenic Fungi against White Grub, Holotrichia consanguinea Blanch in Sugarcane

Field experiments were conducted on sugarcane for white grub management using two entomopathogenic fungi i.e., Beauveria bassiana and Metarhizium anisopliae in Andhra Pradesh during 2013-14. Among the treatments imposed at the time of planting, M. anisopliae @ 5×10 13 spores ha -1 mixed with farm yard manure (FYM) was found effective followed by B. bassiana @ 5×10 13 spores ha -1 applied in FYM enriched field and registered 93.6 % and 88.09 % decrease in white grub damage and 77.22 % and 74.08 % decrease in white grub population. The highest cane yield was recorded when M. anisopliae @ 5x1013 spores ha -1 (81.44 t ha -1 ) applied with FYM followed by B. bassiana @ 5×10 13 spores ha -1 (76.6 t ha -1 ) with FYM . Similar trend was observed by imposing treatments at one month after planting i.e., after the onset of monsoon in the month of july. M. anisopliae @ 5×10 13 spores ha -1 (79.73 t ha -1 ) recorded highest cane yield followed by B. bassiana @ 5×10 13 spores ha -1 (76.45 t ha -1 ) when applied with FYM at one month after planting. However, highest percent yield increase was recorded in M. anisopliae @ 5x10 13 spores ha -1 (71.56 %) applied with FYM at the time of planting.
Leak Propagation Dynamics for the HIE-ISOLDE Superconducting Linac

In order to cope with space limitations of existing infrastructure, the cryomodules of the HIE-ISOLDE superconducting linac feature a common insulation and beam vacuum, imposing the severe cleanliness standard of RF cavities to the whole cryostat. Protection of the linac vacuum against air-inrush from the three experimental stations through the HEBT (High Energy Beam Transport) lines relies on fast valves, triggered by fast cold cathode gauges. To evaluate the leak propagation velocity as a function of leak size and geometry of the lines, a computational and experimental investigation is being carried out at CERN. A 28 m long tube is equipped with cold-cathode gauges. A leak is opened by the effect of a cutting pendulum, equipped with an accelerometer for data acquisition triggering, on a thin aluminium window. The air inrush dynamics is simulated by Finite Elements fluid dynamics in the viscous regime.
Chronic Diabetic Complications: Endothelial Cells at the Frontline

We are approaching the 100-year anniversary of Dr. Frederick Banting's discovery of insulin for the treatment of diabetes. The population of patients with diabetes is ever-increasing. However, with the availability of insulin, the cause of mortality has shifted from diabetic coma and ketoacidosis to chronic secondary complications. Dysfunction and failure of selected organs is now the most prominent cause of morbidity and mortality. These 'target' organs include the eyes, kidneys, heart, lower limbs, and the nervous system. A common feature of these complications is the aberration in the vasculature of the target organs. Studies over the past few decades have shown that dysfunction of the vascular endothelial cells may be the key to the development and progression of the chronic diabetic complications. We present the hypothesis and supporting evidence that preservation and restoration of the endothelial cell function may potentially be the most efficient means of targeting the adverse effects of diabetes.
Generalized fractal dimensions of invariant measures of full-shift systems over compact and perfect spaces: generic behavior

Abstract In this paper, we show that, for topological dynamical systems with a dense set (in the weak topology) of periodic measures, a typical (in Baire’s sense) invariant measure has, for each q>0{q>0}, zero lower q-generalized fractal dimension. This implies, in particular, that a typical invariant measure has zero upper Hausdorff dimension and zero lower rate of recurrence. Of special interest is the full-shift system (X,T){(X,T)} (where X=Mℤ{X=M^{\mathbb{Z}}} is endowed with a sub-exponential metric and the alphabet M is a compact and perfect metric space), for which we show that a typical invariant measure has, for each q>1{q>1}, infinite upper q-correlation dimension. Under the same conditions, we show that a typical invariant measure has, for each s∈(0,1){s\in(0,1)} and each q>1{q>1}, zero lower s-generalized and infinite upper q-generalized dimensions.