Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-Term Outcomes of Acute Osteoarticular Infections in Children

Background: Acute hematogenous osteomyelitis (OM) and septic arthritis require immediate diagnosis and treatment by an interdisciplinary team of pediatric infectious disease specialists and pediatric orthopedic surgeons. Adverse outcomes such as growth disturbance, bone deformity, and chronic infections have been described in older studies. However, there is only little known about long-term follow-up of patients of the last two decades. Therefore, we aimed to evaluate subjective and objective long-term outcomes of these children with osteoarticular infections treated in the millennial years. Methods: Cross-sectional study performed in two pediatric centers including patients admitted for OM and/or SA between 2005 and 2014 and follow-up consultations in 2019. Patients with symptoms of ≤2 weeks duration at initial presentation were contacted. Subjective outcomes were assessed by standardized interview, objective outcomes by clinical examination. Medical charts were used to extract data from the initial presentations. Statistical analysis was performed by non-parametric tests and Fisher's exact test. Results: Of 147 eligible patients 77 (52%) agreed to participate, of which 68 (88%) had an interview and physical examination and 9 (12%) an interview only. Thirty-three (39%) had OM, 26 (34%) SA, and 21 (27%) combined OM/SA. Median (IQR) age at follow-up was 13.3 (10.5–18.0) years with a median (IQR) follow-up of 7.1 (6.1–8.6) years. Persistent complaints including pain, functional differences and scar paresthesia, reported by 21 (28%) patients, were generally mild and only 3 (5%) required ongoing medical care. Objective sequelae including pain, limited range of motion, unilateral axis deformity or asymmetric gait were found in 8 (12%) participants. Older age, female sex, joint involvement, surgical intervention, persistent fever, and C-reactive protein elevation were associated with adverse clinical outcome. Conclusions: Adverse outcomes were observed in a considerable number of patients, most of which were minor, and only few required ongoing medical care. Long-term follow up is advisable for patients with risk factors identified during the initial presentation. This study was registered on ClinicalTrials.gov (NCT03827980).
The Role of Basement Membranes in Cerebral Amyloid Angiopathy

Dementia is a neuropsychiatric syndrome characterized by cognitive decline in multiple domains, often leading to functional impairment in activities of daily living, disability, and death. The most common causes of age-related progressive dementia include Alzheimer’s disease (AD) and vascular cognitive impairment (VCI), however, mixed disease pathologies commonly occur, as epitomized by a type of small vessel pathology called cerebral amyloid angiopathy (CAA). In CAA patients, the small vessels of the brain become hardened and vulnerable to rupture, leading to impaired neurovascular coupling, multiple microhemorrhage, microinfarction, neurological emergencies, and cognitive decline across multiple functional domains. While the pathogenesis of CAA is not well understood, it has long been thought to be initiated in thickened basement membrane (BM) segments, which contain abnormal protein deposits and amyloid-β (Aβ). Recent advances in our understanding of CAA pathogenesis link BM remodeling to functional impairment of perivascular transport pathways that are key to removing Aβ from the brain. Dysregulation of this process may drive CAA pathogenesis and provides an important link between vascular risk factors and disease phenotype. The present review summarizes how the structure and composition of the BM allows for perivascular transport pathways to operate in the healthy brain, and then outlines multiple mechanisms by which specific dementia risk factors may promote dysfunction of perivascular transport pathways and increase Aβ deposition during CAA pathogenesis. A better understanding of how BM remodeling alters perivascular transport could lead to novel diagnostic and therapeutic strategies for CAA patients.
Comprehensive Transcriptomic Analysis Reveals Dysregulated Competing Endogenous RNA Network in Endocrine Resistant Breast Cancer Cells

Background Tamoxifen and fulvestrant, both approved for endocrine therapy, have remarkably increased the prognosis of hormone receptor-positive breast cancer patients. However, acquired resistance to endocrine therapy greatly reduces its clinical efficacy. Accumulating evidence suggests a pivotal role of non-coding RNAs (ncRNAs) in breast cancer endocrine resistance, but the specific functions of ncRNAs in tamoxifen and fulvestrant resistance remain largely unknown. Methods Microarray analysis was performed for endocrine therapy sensitive (MCF-7), tamoxifen-resistant (LCC2), and dual tamoxifen and fulvestrant-resistant (LCC9) breast cancer cells. Gene ontology and pathway analysis were conducted for functional prediction of the unannotated differentially expressed ncRNAs. Competing endogenous RNA regulatory networks were constructed. Results We discovered a total of 3,129 long non-coding RNAs (lncRNAs), 13,556 circular RNAs (circRNAs), 132 microRNAs, and 3358 mRNAs that were significantly differentially expressed. We constructed co-expression networks for lncRNA-mRNA, circRNA-mRNA, and microRNA-mRNA. In addition, we established lncRNA-microRNA-mRNA and circRNA-microRNA-mRNA regulatory networks to depict ncRNA crosstalk and transcriptomic regulation of endocrine resistance. Conclusions Our study delineates a comprehensive profiling of ncRNAs in tamoxifen and fulvestrant resistant breast cancer cells, which enriches our understanding of endocrine resistance and sheds new light on identifying novel endocrine resistance biomarkers and potential therapeutic targets to overcome endocrine resistance.
Intake of Seven Essential Amino Acids Improves Cognitive Function and Psychological and Social Function in Middle-Aged and Older Adults: A Double-Blind, Randomized, Placebo-Controlled Trial

Background: To delay the onset of dementia, it is important for healthy adults to take preventive actions before the cognitive function clearly declines. Protein malnutrition is a potential risk factor for senile dementia, although the precise link between protein/amino acid nutrition and cognitive function is unknown. The purpose of this study was to examine the effect of the ingestion of seven selected essential amino acids as a granular powder, namely, leucine, phenylalanine, and lysine supplemented with isoleucine, histidine, valine, and tryptophan on cognitive and psychosocial functions in healthy adults. Methods: A double-blind, randomized, placebo-controlled trial was conducted. A total of 105 participants aged 55 years or older were randomly assigned to one of three groups: daily ingestion of 3 g (3gIG) or 6 g (6gIG) of the selected amino acids or daily ingestion of a placebo (PCG). Each group ingested the test powder for 12 weeks. As the main outcome, cognitive function was assessed before and after ingestion by a cognitive test battery. Psychosocial functions were also examined. Results: The numbers of participants excluding dropouts were 35 in PCG and 3gIG and 33 in 6gIG. Analysis of covariance revealed that the 6gIG showed significantly improved cognitive function (Trail Making Test B), social interaction and psychological health scores after ingestion compared to the PCG (multiplicity adjusted p < 0.05). Conclusions: Current findings suggested that ingestion of the seven essential amino acids led to improved attention and cognitive flexibility and psychosocial functioning, which is expected to prevent cognitive decline. Clinical Trial Registration: University Hospital Medical Information Network Clinical Trial Registry (URL: https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi? recptno=R000037779, Identifier: UMIN000033174).
Hypertriglyceridemia in Newly Diagnosed Acute Promyelocytic Leukemia

The primary aim of the present retrospective study was to investigate lipid profiles and kinetics in acute promyelocytic leukemia (APL) patients. We analyzed 402 newly diagnosed APL patients and 201 non-APL patients with acute myeloid leukemia (as control). Incidence of hypertriglyceridemia in APL patients and non-APL patients was 55.82% and 28.4% (p = 0.0003). The initial levels of triglycerides, total cholesterol, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol were higher in APL patients than in control (all p < 0.0001). In APL patients, triglyceride levels were significantly increased during induction treatment with all-trans retinoic acid and arsenic. Multivariable analysis showed that age, being overweight (body mass index ≥25) and APL were independent risk factors for hypertriglyceridemia in all patients before treatment. High triglyceride levels were not significantly associated with disease-free survival or overall survival in the APL patients. In summary, in the current study triglyceride levels were significantly elevated in APL patients before treatment, and they increased during induction treatment, but there were no significant corresponding effects on survival.
Estimating Walking Speed in the Wild

An individual's physical activity substantially impacts the potential for prevention and recovery from diverse health issues, including cardiovascular diseases. Precise quantification of a patient's level of day-to-day physical activity, which can be characterized by the type, intensity, and duration of movement, is crucial for clinicians. Walking is a primary and fundamental physical activity for most individuals. Walking speed has been shown to correlate with various heart pathologies and overall function. As such, it is often used as a metric to assess health performance. A range of clinical walking tests exist to evaluate gait and inform clinical decision-making. However, these assessments are often short, provide qualitative movement assessments, and are performed in a clinical setting that is not representative of the real-world. Technological advancements in wearable sensing and associated algorithms enable new opportunities to complement in-clinic evaluations of movement during free-living. However, the use of wearable devices to inform clinical decisions presents several challenges, including lack of subject compliance and limited sensor battery life. To bridge the gap between free-living and clinical environments, we propose an approach in which we utilize different wearable sensors at different temporal scales and resolutions. Here, we present a method to accurately estimate gait speed in the free-living environment from a low-power, lightweight accelerometer-based bio-logging tag secured on the thigh. We use high-resolution measurements of gait kinematics to build subject-specific data-driven models to accurately map stride frequencies extracted from the bio-logging system to stride speeds. The model-based estimates of stride speed were evaluated using a long outdoor walk and compared to stride parameters calculated from a foot-worn inertial measurement unit using the zero-velocity update algorithm. The proposed method presents an average concordance correlation coefficient of 0.80 for all subjects, and 97% of the error is within ±0.2m· s−1. The approach presented here provides promising results that can enable clinicians to complement their existing assessments of activity level and fitness with measurements of movement duration and intensity (walking speed) extracted at a week time scale and in the patients' free-living environment.
Influence of Line Strategy Between Two Turns on Performance in Giant Slalom

In alpine ski racing, different line choices can drastically affect turn or sectional performance. The straight-line transition between two turns is the main phase where skiers can gain speed in a race, open their trajectory, or reduce their path length. Between two turns, a skier can foster speed increase by spending more time in a straight line, inducing sharper turning phases (Z strategy). Inversely, speed can be conserved during the entire turn cycle by performing long curved turns separated by a short straight line (S strategy). This research aimed to evaluate the kinetic and kinematic specificities associated with the line strategy and to explore interactions of selected strategy with skier performance and energy dissipation. A mixed-level population of male alpine skiers (n = 17) skied a timed giant-slalom course while equipped with specialized force plates and a positional device collecting synchronized normal ground reaction force and position-time data, respectively. Time of edge switch was computed from the force signal as the period with the lowest force application on the outside ski. From positional data, turn cycles were separated into turning and straight-line phases (radius bellow and above 30 m, respectively). Time length, path length in the straight line, speed amplitude, and change in specific mechanical energy were computed for each turn and averaged for each skier. The path length during straight line was used to continuously characterize the line strategy within the spectrum between the Z (long straight line) and S (short straight line) strategy. Path length in the straight line was correlated with the amplitude of speed over a straight line (r = 0.672, p = 0.003) and relative and absolute time spent in the straight line (r = 0.967, p < 0.001). However, path length in straight line was not correlated with decrease of speed in the following turn (r = −0.418, p = 0.390) or time without force application on the outside ski (r = 0.195, p = 0.453). While higher-performing athletes on the course performed turns during which they dissipated less energy when normalized to entry speed (r = −0.620, p = 0.008), it appears they did so with variable turn strategies approaches.
Applications of Non-invasive Neuromodulation for the Management of Disorders Related to COVID-19

Background: Novel coronavirus disease (COVID-19) morbidity is not restricted to the respiratory system, but also affects the nervous system. Non-invasive neuromodulation may be useful in the treatment of the disorders associated with COVID-19. Objective: To describe the rationale and empirical basis of the use of non-invasive neuromodulation in the management of patients with COVID-10 and related disorders. Methods: We summarize COVID-19 pathophysiology with emphasis of direct neuroinvasiveness, neuroimmune response and inflammation, autonomic balance and neurological, musculoskeletal and neuropsychiatric sequela. This supports the development of a framework for advancing applications of non-invasive neuromodulation in the management COVID-19 and related disorders. Results: Non-invasive neuromodulation may manage disorders associated with COVID-19 through four pathways: (1) Direct infection mitigation through the stimulation of regions involved in the regulation of systemic anti-inflammatory responses and/or autonomic responses and prevention of neuroinflammation and recovery of respiration; (2) Amelioration of COVID-19 symptoms of musculoskeletal pain and systemic fatigue; (3) Augmenting cognitive and physical rehabilitation following critical illness; and (4) Treating outbreak-related mental distress including neurological and psychiatric disorders exacerbated by surrounding psychosocial stressors related to COVID-19. The selection of the appropriate techniques will depend on the identified target treatment pathway. Conclusion: COVID-19 infection results in a myriad of acute and chronic symptoms, both directly associated with respiratory distress (e.g., rehabilitation) or of yet-to-be-determined etiology (e.g., fatigue). Non-invasive neuromodulation is a toolbox of techniques that based on targeted pathways and empirical evidence (largely in non-COVID-19 patients) can be investigated in the management of patients with COVID-19.
COVID-19 Related Distress Is Associated With Alcohol Problems, Social Media and Food Addiction Symptoms: Insights From the Italian Experience During the Lockdown

Background: Several scholars hypothesize that one of the most negative impacts of the coronavirus disease 2019 (COVID-19) crisis would concern the increase of prevalence and severity of both substances and behavioral addiction. Despite the general concerns about the increase of prevalence and severity of addictions related to the COVID-19 emergency, few data are still available. Thus, the main aim of this study was to investigate the association between COVID-19 related distress and: (i) alcohol problems, (ii) social media addiction (SMA) symptoms, (iii) food addiction (FA) symptoms. Methods: A national online-survey was carried out during the Italian lockdown (i.e., 9 March 2020–4 May 2020). In the current study, 1,519 participants (365 men and 1,154 women, mean age: 28.49 ± 10.89 years) were included. The survey included socio-demographic related items (e.g., age, sex, residential regions, education level, civil status, tobacco use, etc.), as well as ad-hoc developed questions aimed to investigate COVID-19 related variables (e.g., isolation/quarantine, personal diagnosis to COVID-19, friends or relatives with COVID-19 diagnosis, etc.). Participants also completed the following self-report measures in order to investigate: the psychological impact of COVID-19, alcohol problems, SMA symptoms, FA symptoms, and impulsivity. Results: The psychological impact of COVID-19 was independently associated with alcohol problems (β = 0.058, p = 0.043), SMA symptoms (β = 0.259, p < 0.001), and FA symptoms (β = 0.150, p < 0.001). Conclusion: Taken together, our results seem to confirm the general concerns about the negative impacts of the COVID-19 emergency on addictive behaviors, suggesting that this issue should be carefully monitored.
Transformational Leadership and Team Performance: The Role of Team Identification

The present study aimed to explore the effects of transformational leadership (TFL) on team performance, especially the mediational roles of collective identification and relational identification. The multi-source data was collected at one time from 521 nurses in 48 teams and their supervisors with the questionnaire including the general information, group-focused TFL, team identification, and team performance. The results of Process analyses on the data indicated that TFL correlated positively with collective identification and relational identification; collective and relational identification related positively with team performance; TFL had a positive indirect effect on team performance through collective and relational identification in serial. Contributions and implication were discussed.
A Study on the Application of Bandwidth Index in the Performance of High-Frequency Trading of Genetic Algorithm

Continuous trading in Taiwan has received increased research interest in recent years. High-frequency trading is of particular interest. But, obtaining a high rate of return poses a lot of challenges. Many of these challenges can be overcome by algorithmic means. Genetic algorithms are an interesting class of algorithms for this kind of problem. Also, there is a growing body of literature that recognizes their importance. In this article we combined a genetic algorithm with a high-frequency trading perspective to consider bandwidth indicator application profitability. We used a simple genetic algorithm and develop an analytical model that examines the impact of different indicators on investment performance. We considered the following indicators: turnover rate, short-sale/margin ratio, bandwidth index and bid-ask ratio. Using these indicators, we select the highest-reward combination of stocks and the most appropriate trading frequency. Furthermore, we train and test the profit and loss performance of each stock group. Data for this study come from the Taiwan Stock Exchange Corporation (TWSE). We found the return rate of the bandwidth index is significantly better than other indicators. Five-minute intervals delivered the best trading results. Additionally, the findings show that the volatility of the bandwidth indicator has a high impact on the volatility of the return rate in high-frequency trading.
MIF-Dependent Control of Tumor Immunity

Initially identified as a T lymphocyte-elicited inhibitor of macrophage motility, macrophage migration inhibitory factor (MIF) has since been found to be expressed by nearly every immune cell type examined and overexpressed in most solid and hematogenous malignant cancers. It is localized to both extracellular and intracellular compartments and physically interacts with more than a dozen different cell surface and intracellular proteins. Although classically associated with and characterized as a mediator of pro-inflammatory innate immune responses, more recent studies demonstrate that, in malignant disease settings, MIF contributes to anti-inflammatory, immune evasive, and immune tolerant phenotypes in both innate and adaptive immune cell types. This review will summarize the studies describing MIF in tumor-specific innate and adaptive immune responses and attempt to reconcile these various pleiotropic functions in normal physiology.
Example-driven software language engineering

Language workbenches---tools to define software languages together with their IDEs---are designed to simplify language engineering and implementation: they free language engineers from many meticulous tasks, but oftentimes have a very steep learning curve even for experienced software professionals. With the assumption that meta-definitions are one of the key factors that hinder language engineering, we introduce an example-driven approach to language definition. We describe in this paper our vision of a web-based tool aimed at beginner language engineers, and list possible requirements for such a tool. A language is defined by giving examples of code written in it using illustrative syntax definition. These examples are then annotated to specify different concerns of language definition---abstract syntax, typing rules, validation rules, formatting rules, and dynamic semantics.
Termination analysis for evolving programs: an incremental approach by reusing certified modules

Research on program termination has a long tradition. However, most of the existing techniques target a single program only. We propose in this paper an incremental termination analysis approach by reusing certified modules across different program versions. A transformation-based procedure is further developed to increase the reusability of certified modules. The proposed approach has wide applicability, applicable to various program changes. The proposed technique, to the best of our knowledge, represents a novel attempt to the termination analysis of evolving programs. We implemented the approach on top of Ultimate Automizer. Experimental results show dramatic improvement of our approach over the state-of-the-art tool.
Certified and efficient instruction scheduling: application to interlocked VLIW processors

CompCert is a moderately optimizing C compiler with a formal, machine-checked, proof of correctness: after successful compilation, the assembly code has a behavior faithful to the source code. Previously, it only supported target instruction sets with sequential semantics, and did not attempt reordering instructions for optimization. We present here a CompCert backend for a VLIW core (i.e. with explicit parallelism at the instruction level), the first CompCert backend providing scalable and efficient instruction scheduling. Furthermore, its highly modular implementation can be easily adapted to other VLIW or non-VLIW pipelined processors.