Miracle-dz/UniFAR-FTUs huggingface dataset:
Raloxifene Modulates Microglia and Rescues Visual Deficits and Pathology After Impact Traumatic Brain Injury

Mild traumatic brain injury (TBI) involves widespread axonal injury and activation of microglia, which initiates secondary processes that worsen the TBI outcome. The upregulation of cannabinoid type-2 receptors (CB2) when microglia become activated allows CB2-binding drugs to selectively target microglia. CB2 inverse agonists modulate activated microglia by shifting them away from the harmful pro-inflammatory M1 state toward the helpful reparative M2 state and thus can stem secondary injury cascades. We previously found that treatment with the CB2 inverse agonist SMM-189 after mild TBI in mice produced by focal cranial blast rescues visual deficits and the optic nerve axon loss that would otherwise result. We have further shown that raloxifene, which is Food and Drug Administration (FDA)-approved as an estrogen receptor modulator to treat osteoporosis, but also possesses CB2 inverse agonism, yields similar benefit in this TBI model through its modulation of microglia. As many different traumatic events produce TBI in humans, it is widely acknowledged that diverse animal models must be used in evaluating possible therapies. Here we examine the consequences of TBI created by blunt impact to the mouse head for visual function and associated pathologies and assess raloxifene benefit. We found that mice subjected to impact TBI exhibited decreases in contrast sensitivity and the B-wave of the electroretinogram, increases in light aversion and resting pupil diameter, and optic nerve axon loss, which were rescued by daily injection of raloxifene at 5 or 10 mg/ml for 2 weeks. Raloxifene treatment was associated with reduced M1 activation and/or enhanced M2 activation in retina, optic nerve, and optic tract after impact TBI. Our results suggest that the higher raloxifene dose, in particular, may be therapeutic for the optic nerve by enhancing the phagocytosis of axonal debris that would otherwise promote inflammation, thereby salvaging less damaged axons. Our current work, together with our prior studies, shows that microglial activation drives secondary injury processes after both impact and cranial blast TBI and raloxifene mitigates microglial activation and visual system injury in both cases. The results thus provide a strong basis for phase 2 human clinical trials evaluating raloxifene as a TBI therapy.
Recommendations of Choice of Head Coil and Prescan Normalize Filter Depend on Region of Interest and Task

The performance of MRI head coils together with the influence of the prescan normalize filter in different brain regions was evaluated. Functional and structural data were recorded from 26 participants performing motor, auditory, and visual tasks in different conditions: with the 20- and 64-channel Siemens head/neck coil and the prescan normalize filter turned ON or OFF. Data were analyzed with the MRIQC tool to evaluate data quality differences. The functional data were statistically evaluated by comparison of the β estimates and the time-course signal-to-noise ratio (tSNR) in four regions of interest, i.e., the auditory, visual, and motor cortices and the thalamus. The MRIQC tool indicated a better data quality for both functional and structural data with the prescan normalize filter, with an advantage for the 20-channel head coil in functional data and an advantage for the 64-channel head coil in structural measurements. Nevertheless, recommendations for the functional data regarding choice of head coils and prescan normalize filter depend on the brain regions of interest. Higher β estimates and tSNR values occurred in the auditory cortex and thalamus with the prescan normalize filter, whereas the contrary was true for the visual and motor cortices. Due to higher β estimates in the visual cortex in the 64-channel head coil, this head coil is recommended for studies investigating the visual cortex. For most of the research questions, the 20-channel head coil is better suited for functional experiments, with the prescan normalize filter, especially when investigating deep brain areas. For anatomical studies, the 64-channel head coil seemed to be the better choice.
Quantifying Fatigue in the Rugby Codes: The Interplay Between Collision Characteristics and Neuromuscular Performance, Biochemical Measures, and Self-Reported Assessments of Fatigue

Locomotor and collision actions that rugby players complete during match-play often lead to substantial fatigue, and in turn, delays in recovery. The methods used to quantify post-match fatigue and recovery can be categorised as subjective and objective, with match-related collision characteristics thought to have a primary role in modulating these recovery measures. The aim of this review was to (1) evaluate how post-match recovery has been quantified in the rugby football codes (i.e., rugby league, rugby union, and rugby sevens), (2) to explore the time-course of commonly used measures of fatigue post-match, and (3) to investigate the relationships between game-related collisions and fatigue metrics. The available evidence suggests that upper-, and lower-body neuromuscular performance are negatively affected, and biomarkers of muscular damage and inflammation increase in the hours and days following match-play, with the largest differences being at 12–36 h post-match. The magnitude of such responses varies within and between neuromuscular performance (Δ ≤ 36%, n = 13 studies) and tissue biomarker (Δ ≤ 585%, n = 18 studies) measures, but nevertheless appears strongly related to collision frequency and intensity. Likewise, the increase in perceived soreness in the hours and days post-match strongly correlate to collision characteristics across the rugby football codes. Within these findings, there are specific differences in positional groups and recovery trajectories between the codes which relate to athlete characteristics, and/or locomotor and collision characteristics. Finally, based on these findings, we offer a conceptual model of fatigue which details the multidimensional latent structure of the load to fatigue relationship contextualised to rugby. Research to date has been limited to univariate associations to explore relationships between collision characteristics and recovery, and multivariate methods are necessary and recommended to account for the latent structures of match-play external load and post-match fatigue constructs. Practitioners should be aware of the typical time windows of fatigue recovery and utilise both subjective and objective metrics to holistically quantify post-match recovery in rugby.
Recent Progress in Interferon Therapy for Myeloid Malignancies

Myeloid malignancies are a heterogeneous group of clonal haematopoietic disorders, caused by abnormalities in haematopoietic stem cells (HSCs) and myeloid progenitor cells that originate in the bone marrow niche. Each of these disorders are unique and present their own challenges with regards to treatment. Acute myeloid leukaemia (AML) is considered the most aggressive myeloid malignancy, only potentially curable with intensive cytotoxic chemotherapy with or without allogeneic haematopoietic stem cell transplantation. In comparison, patients diagnosed with chronic myeloid leukaemia (CML) and treated with tyrosine kinase inhibitors (TKIs) have a high rate of long-term survival. However, drug resistance and relapse are major issues in both these diseases. A growing body of evidence suggests that Interferons (IFNs) may be a useful therapy for myeloid malignancies, particularly in circumstances where patients are resistant to existing front-line therapies and have risk of relapse following haematopoietic stem cell transplant. IFNs are a major class of cytokines which are known to play an integral role in the non-specific immune response. IFN therapy has potential as a combination therapy in AML patients to reduce the impact of minimal residual disease on relapse. Alongside this, IFNs can potentially sensitize leukaemic cells to TKIs in resistant CML patients. There is evidence also that IFNs have a therapeutic role in myeloproliferative neoplasms (MPNs) such as polycythaemia vera (PV) and primary myelofibrosis (PMF), where they can restore polyclonality in patients. Novel formulations have improved the clinical effectiveness of IFNs. Low dose pegylated IFN formulations improve pharmacokinetics and improve patient tolerance to therapies, thereby minimizing the risk of haematological toxicities. Herein, we will discuss recent developments and the current understanding of the molecular and clinical implications of Type I IFNs for the treatment of myeloid malignancies.
Antifungal Susceptibility Profiles and Resistance Mechanisms of Clinical Diutina catenulata Isolates With High MIC Values

Diutina catenulata (Candida catenulata) is an ascomycete yeast species widely used in environmental and industrial research and capable of causing infections in humans and animals. At present, there are only a few studies on D. catenulata, and further research is required for its more in-depth characterization and analysis. Eleven strains of D. catenulata collected from China Hospital Invasive Fungal Surveillance Net (CHIF-NET) and the CHIF-NET North China Program were identified using matrix-assisted laser desorption ionization–time of flight mass spectrometry and internal transcribed spacer sequencing. The antifungal susceptibility of the Diutina catenulata strains was tested using the Clinical and Laboratory Standards Institute broth microdilution method and Sensititre YeastOne™. Furthermore, ERG11 and FKS1 were sequenced to determine any mutations related to azole and echinocandin resistance in D. catenulata. All isolates exhibited low minimum inhibitory concentration (MIC) values for itraconazole (0.06–0.12 μg/ml), posaconazole (0.06–0.12 μg/ml), amphotericin B (0.25–1 μg/ml), and 5-flucytosine (range, <0.06–0.12 μg/ml), whereas four isolates showed high MICs (≥4 μg/ml) for echinocandins. Strains with high MIC values for azoles showed common ERG11 mutations, namely, F126L/K143R. In addition, L139R mutations may be linked to high MICs of fluconazole. Two amino acid alterations reported to correspond to high MIC values of echinocandin, namely, F621I (F641) and S625L (S645), were found in the hot spot 1 region of FKS1. In addition, one new amino acid alteration, I1348S (I1368), was found outside of the FKS1 hot spot 2 region, and its contribution to echinocandin resistance requires future investigation. Diutina catenulata mainly infects patients with a weak immune system, and the high MIC values for various antifungals exhibited by these isolates may represent a challenge to clinical treatment.
Treatment of Multiple Sclerosis With Teriflunomide. Multicenter Study of Real Clinical Practice in the Valencian Community-Spain

Introduction: We have different treatment alternatives for relapsing-remitting multiple sclerosis–RRMS–within the so-called platform drugs. It would be desirable to know the ideal drug for each patient. Real clinical practice studies provide us with data on drug efficacy in the medium and long term, safety beyond clinical trials, and can help us to know the patient profile appropriate for each therapy. Material and Methods: An observational multicenter study of real clinical practice in patients with RRMS who were treated with teriflunomide in the Valencian Community, since teriflunomide was authorized in Spain. The database created for this study collects retrospectively patients followed prospectively in the MS clinics. Objectives: To analyze the efficacy and safety of teriflunomide treatment in patients with RRMS under the conditions of real clinical practice, and to identify a patient profile responding to the treatment. Results: We obtained data from 340 patients who received at least one dose of 14 mg teriflunomide. The patients were 69.4% female to 30.6% male, had a mean age of 46.4 years, and a mean time of progression of MS of 11.5 years. The mean pre-teriflunomide relapse rate was 0.4 years, the mean EDSS scorewas 1.98, IgG Oligoclonal bands were present in the CSF of 66.2% of the patients, IgM Oligoclonal bands were present in 46.9%, and the mean number of gadolinium-enhancing lesions was 1.07 lesions per patient at the beginning of treatment. The average number of treatments previously received was 1.04, and 28.53% were naïve. After a follow-up of up to 4 years, a reduction in the annualized and cumulative annualized relapse rate was observed in the first year, in the second year, and in the third year, compared to the pre-treatment year. The EDSS scores were stabilized throughout the follow-up. Likewise, there was a reduction in gadolinium-enhancing lesions in the 1st and 2nd years compared to the pre-treatment period. Applying different generalized multiple linear regression models, we identified a profile of a responding patient to teriflunomide as a male without IgM oligoclonal bands in the CSF, a previous EDSS score of <3, and more than 5 years duration of MS.
Swarm intelligence‐based secure high‐order optimal density selection for industrial internet‐of‐things (IIoT) data on cloud environment

Industrial internet‐of‐things (IIoT) cloud computing gives users with the ease of outsourcing calculations and carrying the risk of privacy disclosure. To solve this issue, secure high‐order clustering algorithm by fast search (SHOCFS) technique is introduced recently. The major factors of SHOCFS algorithm are speed improvement and detecting optimal density peaks. The optimal selection of density points in the SHOCFS algorithm still becomes an important issue to be considered. The swallow swarm optimization (SSO) is introduced in the proposed work for choosing optimal density peaks in clustering algorithm. This paper motivates to design a new secure cloud service system for cloud in IIoT environment. The secure high‐order optimal density selection (SHODS3O‐CFS) approach is proposed in hybrid cloud environment. The major contribution of the work is to develop an optimization‐based secure clustering algorithm for finding the best density points in clustering algorithm. It may reduce the overlapping peak points in the cluster and increase the security of system in hybrid cloud. The experimental results of the proposed algorithm and existing methods are measured via clustering metrics such as accuracy, clustering center quality, and speed ratio. The metrics like clustering center quality, Rand index (RI), encryption time (ms), and speedup ratio have been used to measure the results of the proposed system and existing methods. From the results, it is concluded that the proposed work has achieved higher average RI of 93.4%, which is 29.68% and 17.4% higher when compared with the privacy preservation high‐order clustering algorithm by fast search (PPHOCFS) and SHOCFS methods.
Enhanced model for leadership development for trainees and early career health professionals: insights from a national survey of UK clinical scientists

Introduction The importance of shared or distributed leadership in healthcare is recognised; however, trainees, early career professionals and others for whom the exercise of leadership is a recent development report being underprepared for leadership roles. Trainee clinical scientists exemplify such groups, being both early in their career and in a profession for which clinical leadership is less well established. Their insights can inform understanding of appropriate forms of leadership development for health professionals. Methods We explored perceptions of leadership and its development for trainee clinical scientists on the UK preregistration Scientist Training Programme through semi-structured interviews with trainees, training officers, academic educators and lead healthcare scientists; and through an online questionnaire based on the UK multiprofessional Clinical Leadership Competency Framework (CLCF). Responses were analysed statistically or thematically as appropriate. Results Forty interviews were undertaken and 267 valid questionnaire responses received. Stakeholders recognised clinical expertise as integral to leadership; otherwise their perceptions aligned with CLCF domains and ‘shared leadership’ philosophy. They consider learning by ‘doing’ real tasks (leadership activities) key to competency acquisition, with leadership education (eg, observation and theory) complementing these. Workplace affordances, such as quality of departmental leadership, training officer engagement and degree of patient contact affect trainees’ ability to undertake leadership activities. Conclusions From our research, we have developed an enhanced model for leadership development for trainee and early career clinical scientists that may have wider applicability to other health professions and groups not traditionally associated with clinical leadership. To foster their leadership, we argue that improving workplace affordances is more important than improving leadership education.
Nanostructure and Dynamics of Humidified Nafion/Graphene-Oxide Composites via Molecular Dynamics Simulations

In this work, we elucidated the nanostructure and dynamics of Nafion-doped graphene-oxide (GO) systems from molecular dynamics simulations at varying hydration levels and temperature. It was found that the presence of GO resulted in the formation of Nafion layers along a direction normal to the GO surface. Chain conformations in the Nafion layers close to the GO interface were characterized by a backbone preferably oriented parallel to the GO plane, whereas the size of the formed nanochannels was found to be commensurate to the average dimensions of the Nafion side chains. The mechanism of water cluster growth was found to change drastically upon introduction of Nafion chains, although addition of GO in the membranes did not impart further measurable changes at the examined temperatures. Hydronium ions were found to adsorb partly onto the GO surface, whereas the pertinent adsorption/desorption rate increased significantly with hydration. Translational dynamics of water molecules was much slower close to t.
Thermal performance prediction of wickless heat pipe with Al2O3/water nanofluid using artificial neural network

Abstract A wickless heat pipe (WHP) comprises of an evacuated-close tube filled with an appropriate amount of working fluid. In this study, the effect of Al2O3/water nanofluid as the working media on thermal performance of WHP investigated and compared with pure water by designing an optimized Artificial Neural Network (ANN). ANN trained with the collected test data obtained from experimental setup and validated. Multilayer Perceptron configuration (MLP) adopted for the ANN. The MLP architecture consists of four input nodes representing the parameters; input power, volume concentration of nanofluid, filling ratio and mass rate in condenser section, and a single output node representing the thermal efficiency of WHP. According to sensitivity analysis results, volume concentration is the most significant parameter which affects the WHP performance. Also, since the ANN test output data are sufficiently close to experimental one, it can be inferred that the ANN model can be applied to accurately model WHP thermal performance.
Enhanced Direct Electron Transfer of Fructose Dehydrogenase Rationally Immobilized on a 2-Aminoanthracene Diazonium Cation Grafted Single-Walled Carbon Nanotube Based Electrode

In this paper, an efficient direct electron transfer (DET) reaction was achieved between fructose dehydrogenase (FDH) and a glassy-carbon electrode (GCE) upon which anthracene-modified single-walled carbon nanotubes were deposited. The SWCNTs were activated in situ with a diazonium salt synthesized through the reaction of 2-aminoanthracene with NaNO2 in acidic media (0.5 M HCl) for 5 min at 0 °C. After the in situ reaction, the 2-aminoanthracene diazonium salt was electrodeposited by running cyclic voltammograms from +1000 to −1000 mV. The anthracene-SWCNT-modified GCE was further incubated in an FDH solution, allowing enzyme adsorption. Cyclic voltammograms of the FDH-modified electrode revealed two couples of redox waves possibly ascribed to the heme c1 and heme c3 of the cytochrome domain. In the presence of 10 mM fructose two catalytic waves could clearly be seen and were correlated with two heme cs (heme c1 and c2), with a maximum current density of 485 ± 21 μA cm–2 at 0.4 V at a sweep rate of 10 mV .
Schools, Language, and Nations: Evidence From a Natural Experiment in France

This paper studies nation-building. We explore the role of statesponsored education in the adoption of a common language and the formation of a national identity in a fragmented society. At the time of the French Revolution, only ten percent of the population spoke the French language in France. Today, French is the common language. We digitize a detailed survey of the languages spoken across municipalities in France to document the process of homogenization in the nineteenth century. Using a regression discontinuity design, we demonstrate that state-sponsored education brought about the homogenization of language. Then, we study the geographical origins of the French language and the heterogeneous effects of schools. We find that elites and the demand for education were important drivers of homogenization. Finally, we document a persistent impact of nation-building on national identity and preferences for political centralization, with increased participation in the Resistance during World War II and votes against the 1969 referendum on regionalization. JEL codes: D83,H52,I25,N43,P16,Z13
Master 2 Internship Proposal: Using interpretability methods to explain Vision-Language models for medical applications

Recent advances in Deep Learning have led to the growth of interpretable Machine Learning, which seeks to help understand the decisions of a model. Indeed, in various fields such as Medicine, Finance and Security, it is important for models to be trustworthy and reliable. As part of this internship, we want to develop a method to explain the decisions of medical Vision-Language models. State-of-the-Art Vision-Language models such as UNITER [3] are built based on the transformer architecture to extract representations from texts and images. Those representations are then used in multimodal applications such as visual question answering [1] and image captioning [7]. However, due to the complex architecture of those models, explaining them remains a challenge. Applying interpretability methods to those models can be a way to make them more reliable. In the context of medical data, we want to be able to explain why a radiology report does or does not fit a X-ray. To this end, we will rely on medical datasets such as MIMICCXR [4]. This internship is focused on the development of interpretability methods for Vision-Language models.