Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving patient flow through hospitals with machine learning based discharge prediction

Background: Advanced analytics, underpinned by large-scale electronic health record (EHR) data, have the potential to transform the efficiency of healthcare delivery. Methods: We used data from 4 hospitals in Oxfordshire, UK (01-February-2017 to 31-January-2020), to develop machine learning models for predicting hospital discharge in the next 24 hours, conditional on the duration of hospitalisation to date. We fitted separate XGBoost models for patients in hospital after planned and emergency admissions and for patients with different lengths of stay since admission. Models were trained and tested using data from 126,054 emergency and 45,609 planned admissions. Findings: In held-out test data (01-February-2019 to 31-January-2020), individual patient discharge was predicted with positive and negative predictive values of 87.5% and 94.1% respectively in emergency patients (sensitivity 82.3%, specificity 98.5%, AUPRC 87.6%, AUC 87.5%) and 95.6% and 97.8% after a planned admission (sensitivity 83.5%, specificity 98.1%, AUPRC 90.5%, AUC 90.1%). Combining individual discharge probabilities allowed accurate estimates of the total number of discharges from hospital, mean average error 5.8% for emergency and 3.1% for planned patients. Previous hospital exposure, procedures, antibiotic use, and comorbidities were the most predictive features, but the most important features differed between planned and emergency patients, and over the course of admission. Performance was best in short-stay and planned admission patients, but generally robust over time, across subgroups, and different model training strategies. Interpretation: Our approach could help improve flow of patients through hospitals, resulting in faster care delivery and patient recovery, and better use of healthcare resources. Funding: National Institute for Health Research.
Heuristic Problem Solving with Abstract Knowledge in the Context of the Travelling Salesperson Problem

Computationally hard problems like the Travelling Salesperson Problem, can be solved remarkably well by humans. Results obtained by computers are usually closer to the optimum, but require high computational effort and often differ from the human solutions. This paper introduces Greedy Expert Search (GES), which strives to show the same flexibility and efficiency of human solutions, while producing results of similarly high quality. A particular focus is on how to use abstract knowledge in the solution process. The Travelling Salesperson Problem serves as an example problem to illustrate and evaluate the approach.
Defining and emulating target trials of the effects of postexposure vaccination using observational data

Postexposure vaccination has the potential to prevent or modify the course of clinical disease among those exposed to a pathogen. However, due to logistical constraints, postexposure vaccine trials have been difficult to implement in practice. In place of trials, investigators have used observational data to estimate the efficacy or optimal timing window for postexposure vaccines, but the relationship between these analyses and those that would be conducted in a trial is often unclear. Here, we define several possible target trials for postexposure vaccination and show how, under certain conditions, they can be emulated using observational data. We emphasize the importance of the incubation period and the timing of vaccination in trial design and emulation. As an example, we specify a protocol for postexposure vaccination against mpox and provide a step-by-step description of how to emulate it using data from a healthcare database or contact tracing program. We further illustrate some of the benefits of the target trial approach through simulation.
Persistent immune abnormalities discriminate post-COVID syndrome from convalescence

Innate lymphoid cells (ILCs) are key organizers of tissue immune responses and regulate tissue development, repair, and pathology. Persistent clinical sequelae beyond 12 weeks following acute COVID-19 disease, named post-COVID syndrome (PCS), are increasingly recognized in convalescent individuals. ILCs have been associated with the severity of COVID-19 symptoms but their role in the development of PCS remains poorly defined. Here we used multiparametric immune phenotyping, finding expanded circulating ILC precursors (ILCPs) and concurrent decreased group 2 innate lymphoid cells (ILC2s) in PCS patients compared to well-matched convalescent control groups at > 3 months after infection. Patients with PCS showed elevated expression of chemokines and cytokines associated with trafficking of immune cells (CCL19/MIP-3b, FLT3-ligand), endothelial inflammation and repair (CXCL1, EGF, RANTES, IL1RA, PDGF-AA). These results define immunological parameters associated with PCS and might help find biomarkers and disease-relevant therapeutic strategies.
Transcriptomics Analyses of ALS Post-mortem Motor Cortex highlight alteration and potential biomarkers in the Neuropeptide Signalling pathway

Background: Amyotrophic lateral sclerosis (ALS) is a fatal heterogeneous neurodegenerative disease that typically leads to death from respiratory failure within two to five years. Despite the identification of several genetic risk factors, the biological processes involved in ALS pathogenesis remain poorly understood. The motor cortex is an ideal region to study dysregulated pathological processes in ALS as it is affected from the earliest stages of the disease. In this study, we investigated motor-cortex gene expression of cases and controls to gain new insight into the molecular footprint of ALS. Methods: We performed a large case-control differential expression analysis of two independent post-mortem motor cortex bulk RNA-sequencing (RNAseq) datasets from the King's College London BrainBank (N = 171) and TargetALS (N = 132). Differentially expressed genes from both datasets were subjected to gene and pathway enrichment analysis. Genes common to both datasets were also reviewed for their involvement with known mechanisms of ALS pathogenesis to identify potential candidate genes. Finally, we performed a correlation analysis of genes implicated in pathways enriched in both datasets with clinical outcomes such as the age of onset and survival. Results: Differential expression analysis identified 2,290 and 402 differentially expressed genes in KCL BrainBank and TargetALS cases, respectively. Enrichment analysis revealed significant synapse-related processes in the KCL BrainBank dataset, while the TargetALS dataset carried an immune system-related signature. There were 44 differentially expressed genes which were common to both datasets, which represented previously recognised mechanisms of ALS pathogenesis, such as lipid metabolism, mitochondrial energy homeostasis and neurovascular unit dysfunction. Differentially expressed genes in both datasets were significantly enriched for the neuropeptide signalling pathway. By looking at the relationship between the expression of neuropeptides and their receptors with clinical measures, we found that in both datasets NPBWR1, TAC3 and SSTR1 correlated with age of onset, and GNRH1, TACR1 with survival. We provide access to gene-level expression results to the broader research community through a publicly available web application (https://alsgeexplorer.er.kcl.ac.uk). Conclusion: This study identified motor-cortex specific pathways altered in ALS patients, potential molecular targets for therapeutic disease intervention and a set of neuropeptides and receptors for investigation as potential biomarkers.
Effectiveness of home-based conventional exercise and cryotherapy on daily living activities in patients with knee osteoarthritis: A randomized controlled clinical trial

Background: Knee osteoarthritis (KOA) is a prevalent joint condition associated with aging that causes pain, disability, loss of function, and a decline in quality of life. This study aimed to evaluate the effectiveness of home-based conventional exercise and cryotherapy on daily living activities in patients with KOA. Methods: In this randomized controlled clinical trial, the patients who were diagnosed with KOA were assigned to 3 groups: an experimental group (n = 18), the control group 1 (n = 16), and the control group 2 (n = 15). Control and experimental groups engaged in a 2-month home-based exercise (HBE) program. The experimental group received cryotherapy along with HBE. In contrast, the patients in the second control group received regular therapeutic and physiotherapeutic services at the center. The patients were recruited from the Specialized Center for Rheumatic and Medical Rehabilitation in Duhok, Iraq. Results: The patients in the experimental group had statistically significant better daily activity functions compared to the first and second control groups in pain (2.22 vs 4.81 and 12.7; P < .0001), stiffness (0.39 vs 1.56 and 4.33; P < .0001), physical function (5.72 vs 13.31 and 38.13; P < .0001), and the total score (8.33 vs 19.69 and 55.33; P < .0001) at 2 months. The patients in the experimental and the first control groups had statistically significantly lower balance scores compared to the second control group at 2 months, 8.56 versus 9.30. At 3 months, similar patterns were observed for the daily activity function and balance. Conclusions: This study showed that combining HBE and cryotherapy may be an effective technique to improve function among patients with KOA. Cryotherapy could be suggested as a complementary therapy for KOA patients.
Drug Repurposing Flubendazole to Suppress Tumorigenicity via PCSK9-dependent Inhibition and Potentiate Lenvatinib Therapy for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most lethal malignant cancers across the world. It has a poor prognosis and lacks effective therapies, especially for patients with advanced-stage cancer, indicating an urgent need for new therapies and novel therapeutic targets. Here, by screening the U.S. Food and Drug Administration drug library against HCC cell lines, we identified that flubendazole, a traditional anthelmintic drug, could prominently suppress HCC cells in vivo and in vitro. RNA sequence analysis and cellular thermal shift assays showed that flubendazole reduced the expression of PCSK9 protein by direct targeting. The increased expression of PCSK9 in HCC tissues was demonstrated to be correlated with poor prognosis, and the inhibitory ability of flubendazole was selectively dependent on PCSK9 expression. PCSK9 knockdown abolished the antitumor effects of flubendazole in HCC. Mechanistically, flubendazole inhibited the Hedgehog signaling pathway induced by PCSK9, resulting in the downregulation of smoothened (SMO) and GLI Family Zinc Finger 1 (Gli1). Moreover, combining flubendazole with lenvatinib was found more effective than administering lenvatinib only for HCC treatment in vivo and in vitro. These findings reveal the therapeutic potential of flubendazole against HCC and provide clues on new repurposed drugs and targets for cancer treatment.
The microbiome of an outpatient rehabilitation clinic and predictors of contamination: A pilot study

Background Understanding sources of microbial contamination in outpatient rehabilitation (REHAB) clinics is important to patients and healthcare providers. Purpose The purpose of this study was to characterize the microbiome of an outpatient REHAB clinic and examine relationships between clinic factors and contamination. Methods Forty commonly contacted surfaces in an outpatient REHAB clinic were observed for frequency of contact and swiped using environmental sample collection kits. Surfaces were categorized based on frequency of contact and cleaning and surface type. Total bacterial and fungal load was assessed using primer sets specific for the 16S rRNA and ITS genes, respectively. Bacterial samples were sequenced using the Illumina system and analyzed using Illumina-utils, Minimum Entropy Decomposition, QIIME2 (for alpha and beta diversity), LEfSe and ANCOM-BC for taxonomic differential abundance and ADONIS to test for differences in beta diversity (p<0.05). Results Porous surfaces had more bacterial DNA compared to non-porous surfaces (median non-porous = 0.0016ng/μL, 95%CI = 0.0077–0.00024ng/μL, N = 15; porous = 0.0084 ng/μL, 95%CI = 0.0046–0.019 ng/μL, N = 18. p = 0.0066,DNA. Samples clustered by type of surface with non-porous surfaces further differentiated by those contacted by hand versus foot. ADONIS two-way ANOVA showed that the interaction of porosity and contact frequency (but neither alone) had a significant effect on 16S communities (F = 1.7234, R2 = 0.0609, p = 0.032). Discussion Porosity of surfaces and the way they are contacted may play an underestimated, but important role in microbial contamination. Additional research involving a broader range of clinics is required to confirm results. Results suggest that surface and contact-specific cleaning and hygiene measures may be needed for optimal sanitization in outpatient REHAB clinics.
Exploration of spatial heterogeneity of tumor microenvironment in nasopharyngeal carcinoma via transcriptional digital spatial profiling

The heterogeneity of nasopharyngeal carcinoma (NPC) leads to mixed clinical outcomes. We collected 92 regions of interest from 41 biopsies of patients with untreated NPC and obtained their transcripts using GeoMx Digital Spatial Profiling (DSP) technology. Spatial heterogeneity was determined by measuring the expression of marker genes in tumor cell-enriched (PanCK-expressing), immune cell-enriched (CD45-expressing), and normal epithelial (Endo) regions. We screened 16 prognostic markers in tumor cell-enriched regions and 4 prognostic markers in immune cell-enriched regions. The levels of CD8+ T follicular helper T cells, activated NK cells, and M0 macrophage contents were higher in tumor cell-enriched regions than in immune cell-enriched regions. Conversely, plasma cell and M2 macrophage levels were lower. The follicular helper T cells in tumor cell-enriched regions were negatively correlated with resting NK cells and positively correlated with activated NK cells. In immune cell-enriched regions, this relationship was reversed. We also explored the heterogeneity of HLA gene families, immune checkpoints, and metabolism-related genes in the three regions. In tumor cell-enriched regions, we obtained 19 prognosis-related metabolism genes via univariate cox analysis. We used multiplex immunofluorescence to verify the elevated expression of SLC8A1 and MDH1 in immune cell-enriched regions and tumor cell-enriched regions, respectively, both of which were associated with prognosis of NPC. In conclusion, we explored the spatial heterogeneity of the NPC tumor environment and found specific diagnostic and prognostic markers that can be used to differentiate tumor cell-enriched regions from immune cell-enriched regions in NPC.
Bankart repair with subscapularis augmentation: A case control study

To examine the effect on functional shoulder scores of Bankart repair with arthroscopic subscapularis tendon augmentation applied to cases of anterior shoulder instability with < 25% glenoid defect and ligament-labral failure. A total of 83 patients underwent Bankart repair with subscapularis tendon augmentation between 2015 and 2021. The range of movement of the patients was measured by 2 doctors using a goniometer. The Constant Murley score, American Shoulder and Elbow Surgeons score, Rowe score, and the University of California at Los Angeles scores were recorded preoperatively and postoperatively. Statistically significant increases were determined in the postoperative functional scores compared to the preoperative values as mean 41.4 ± 2.08 unit increase in the Constant Murley score, mean 41.4 ± 1.8 unit increase in the American Shoulder and Elbow Surgeons score, mean 13.8 ± 1.45 unit increase in the University of California at Los Angeles and mean 49.3 ± 7.45 unit increase in the Rowe score (P = .001; P < .01). Compared with the preoperative evaluation, there was found to be a postoperative statistically significant unit decrease of 10.2 ± 1.47 in the external rotation measurement (P = .001; P < .01). The number of dislocations was determined to have a negative correlation with the internal rotation measurements (r = −0.305; P = .005; P < .01), and a weak negative statistically significant relationship with external rotation measurements (r = −0.329; P = .002; P < .01). Unlike other techniques, as this repair technique includes both the tendon and the capsule as a single piece, it was seen to be a sufficient and reliable technique that is easy-to apply.
Classification of uncertain data in the framework of belief functions : nearest-neighbor-based and rule-based approaches

In many classification problems, data are inherently uncertain. The available training data might be imprecise, incomplete, even unreliable. Besides, partial expert knowledge characterizing the classification problem may also be available. These different types of uncertainty bring great challenges to classifier design. The theory of belief functions provides a well-founded and elegant framework to represent and combine a large variety of uncertain information. In this thesis, we use this theory to address the uncertain data classification problems based on two popular approaches, i.e., the k-nearest neighbor rule (kNN) andrule-based classification systems. For the kNN rule, one concern is that the imprecise training data in class over lapping regions may greatly affect its performance. An evidential editing version of the kNNrule was developed based on the theory of belief functions in order to well model the imprecise information for those samples in over lapping regions. Another consideration is that, sometimes, only an incomplete training data set is available, in which case the ideal behaviors of the kNN rule degrade dramatically. Motivated by this problem, we designedan evidential fusion scheme for combining a group of pairwise kNN classifiers developed based on locally learned pairwise distance metrics.For rule-based classification systems, in order to improving their performance in complex applications, we extended the traditional fuzzy rule-based classification system in the framework of belief functions and develop a belief rule-based classification system to address uncertain information in complex classification problems. Further, considering that in some applications, apart from training data collected by sensors, partial expert knowledge can also be available, a hybrid belief rule-based classification system was developed to make use of these two types of information jointly for classification.
Treatment of last resort? Psychological therapy seeking in chronic pain patients.

OBJECTIVE Our goal was to assess how many chronic pain patients seek psychological treatment for their condition and what psychological and demographic characteristics are associated with that decision. METHODS The association between pain intensity, quality of life and psychological treatment seeking was tested in two hypothetical models which differed according to beliefs about either external or internal control over pain. RESULTS A minority of patients had experience with psychological treatment of chronic pain. Patients who had that experience were younger, suffered from more intense pain, and applied many more coping strategies than patients who never tried this kind of treatment. Intense pain and low quality of life motivated chronic pain patients to seek psychological treatment only if they believed that doctors could control their pain. DISCUSSION The study results stress the importance of diversifying the methods used to treat chronic pain and educating patients about the benefits of psychological treatment. Low numbers of chronic pain patients who take advantage of psychological treatment indicate that encouragement from medical professionals might be necessary.
Dipo: a miniaturized hopping robot via lightweight and compact actuator design for power amplification

Kangaroo rats are well known as representative hoppers in small-scale animals. Especially kangaroo rats show rapid movement when a predator approaches. If this amazing motion can be applied to small-scale robots, they will be able to traverse lands at high speed while overcoming size limitations. To take advantage of hopping locomotion, in this paper, we present a lightweight and small-scale clutch-based hopping robot called Dipo. To make this possible, a compact power amplifying actuation system has been developed using a power spring and an active clutch. The power spring is possible to take out and use the accumulated energy little by little whenever the robot starts to hop. Moreover, the power spring needs low torque to charge the elastic energy, and a only tiny space is required to install. The active clutch controls the motion of hopping legs by adjusting the timing of energy release and storage. Thanks to these design strategies, the robot weighs 45.07 g, has the height of 5 cm in the stance phase, and achieves the maximum hopping height of 54.9 cm.
Numerical study on performance of perforated plate applied to cryogenic fluid flowmeter

The perforated plate is one of the effective devices for measuring flow rate accurately. In this study, a perforated plate is investigated for its characteristics, mainly including discharge coefficient C and pressure loss coefficient ζ, when applied to cryogenic fluids with the help of ANSYS Fluent. Three cryogenic fluids are studied, including liquid nitrogen (LN2), liquid oxygen (LO2), and liquid hydrogen (LH2). For comparison, two states of water are also investigated. The realizable κ-ε model with standard wall function is used to describe the turbulence and simulate the near-wall flow. The Schnerr-Sauer cavitation model is used to investigate the effect of cavitation on the performance of the perforated plate. Simulation results indicate that the upper limit of Reynolds number of the perforated plate is significantly dependent on the properties of the measured fluid when the temperatures of the fluids are set as the normal boiling point temperatures and the outlet pressures are 0.2 MPa. 中文概要目 的相较于常温流体,低温流体的物性存在显著不同,因而对流量计的工作特性也会带来相应的影响。 本文旨在探讨多孔板应用于低温流体流量测量时的性能(即流出系数与压力损失系数)特征。 创新点基于数值研究结果,发现多孔板流量计应用于低温流体流量测量时,其稳定测量区间上限雷诺数显著增大,并基于物性特点从空化特性的角度探讨上限雷诺数显著增大的原因。 方 法采用数值模拟的方法,经网格独立性验证(表1和图5)和模型验证(图6 和图8)后,结合Realizable κ-ε 湍流模型与Schnerr-Sauer 空化模型,研究同一种结构的多孔板应用于液氮、液氧、液氢三种低温流体和水流量测量时其流出系数与压力损失系数变化的异同(图11、图12和表5);并基于低温流体的物性特点(表3),对其具有较大上限雷诺数的计算结果进行原因分析。 结 论对于同一种多孔板结构,与水相比,低温流体具有较宽的稳定雷诺数测量范围,其中,与多孔板结构相关的下限雷诺数差异较小,而受空化影响的上限雷诺数差别较大;低温流体具有较大的上限雷诺数,其原因在于,与水相比较,低温流体的密度与运动粘度平方的乘积ρv2明显较小
Fast calculation of EM scattering from randomly rough surface with buried PEC target

In order to analyze EM scattering of a randomly rough surface with a buried PEC target,a fast Cross coupling iterative approach based on conjugate gradient method(CG) and forward backward method(FBM) is presented in this paper.At first,the integral equations of the induced currents on the rough surface and the target are derived.An iterative approach is developed to solve the two EFIE and scattering from both the target and underlying surface.The EFIE of the rough surface and the target are solved by using FBM and CG separately.The mutual effect of bath the rough and the target are finished by iterative calculation.The scattering form a Gauss rough surface with a buried PEC cylinder is studied.The accuracy,efficiency,and convergence of the method are then studied for various rough surfaces.The relationship between the scattering pattern and the target's size and station are also discussed.