Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Genome Analysis of Hungarian and Global Strains of Salmonella Infantis

Introduction The emergence and spread of new strains of zoonotic bacteria, such as multidrug resistant (MDR) Salmonella Infantis, represent a growing health risk for humans in and outside Europe due to foodborne infections of poultry meat origin. Objectives In order to understand genome relations of S. Infantis strains from Hungary and from different geographic regions, we performed a comprehensive genome analysis of nine Hungarian and 67 globally selected strains of S. Infantis and 26 Salmonella strains representing 13 non-Infantis serovars. Results Analyses of whole-, and accessory genomes, showed that almost all S. Infantis strains were separated from the non-Infantis serovars. S. Infantis strains from Hungary formed subclusters based on their time of isolation. In whole genome sequence analysis, the Swiss strains of S. Infantis were closely related to each other and clustered together with subclusters of strains from Hungary, Japan, Italy, United States, and Israel. The accessory genome analysis revealed that the Swiss strains were distinct from most of the strains investigated, including the Hungarian ones. Analysis of the cloud genes offered the most detailed insight into the genetic distance and relationship of S. Infantis strains confirming that the Swiss and Hungarian strains belonged to different lineages. As expected, core genome analysis provided the least discriminatory power for analysis of S. Infantis. Genomic sequences of nine strains from Brazil, Israel, Mexico, Nigeria, and Senegal (deposited as S. Infantis) proved to be outliers from the S. Infantis clade. They were predicted to be Salmonella Rissen, Salmonella Ouakarm, Salmonella Kentucky, Salmonella Thompson, and Salmonella enterica subsp. diarizonae. Conclusion Accessory genome of S. Infantis showed the highest diversity suggesting a faster evolution than that of the whole genomes contributing to the emergence of multiple genetic variants of S. Infantis worldwide. Accordingly, in spite of the comprehensive analysis of several genomic characteristics, no epidemiologic links between these S. Infantis strains from different countries could be established. It is also concluded that several strains originally designated as S. Infantis need in databanks reclassification.
Dissecting the Dual Role of the Glial Scar and Scar-Forming Astrocytes in Spinal Cord Injury

Recovery from spinal cord injury (SCI) remains an unsolved problem. As a major component of the SCI lesion, the glial scar is primarily composed of scar-forming astrocytes and plays a crucial role in spinal cord regeneration. In recent years, it has become increasingly accepted that the glial scar plays a dual role in SCI recovery. However, the underlying mechanisms of this dual role are complex and need further clarification. This dual role also makes it difficult to manipulate the glial scar for therapeutic purposes. Here, we briefly discuss glial scar formation and some representative components associated with scar-forming astrocytes. Then, we analyze the dual role of the glial scar in a dynamic perspective with special attention to scar-forming astrocytes to explore the underlying mechanisms of this dual role. Finally, taking the dual role of the glial scar into account, we provide several pieces of advice on novel therapeutic strategies targeting the glial scar and scar-forming astrocytes.
Measurement Invariance and Differential Item Functioning Across Gender Within a Latent Class Analysis Framework: Evidence From a High-Stakes Test for University Admission in Saudi Arabia

The main aim of the present study was to investigate the presence of Differential Item Functioning (DIF) using a latent class (LC) analysis approach. Particularly, we examined potential sources of DIF in relation to gender. Data came from 6,265 Saudi Arabia students, who completed a high-stakes standardized admission test for university entrance. The results from a Latent Class Analysis (LCA) revealed a three-class solution (i.e., high, average, and low scorers). Then, to better understand the nature of the emerging classes and the characteristics of the people who comprise them, we applied a new stepwise approach, using the Multiple Indicator Multiple Causes (MIMIC) model. The model identified both uniform and non-uniform DIF effects for several items across all scales of the test, although, for the majority of them, the DIF effect sizes were negligible. Findings from this study have important implications for both measurement quality and interpretation of the results. Particularly, results showed that gender is a potential source of DIF for latent class indicators; thus, it is important to include those direct effects in the latent class regression model, to obtain unbiased estimates not only for the measurement parameters but also of the structural parameters. Ignoring these effects might lead to misspecification of the latent classes in terms of both the size and the characteristics of each class, which in turn, could lead to misinterpretations of the obtained latent class results. Implications of the results for practice are discussed.
Local Dose Effects for Late Gastrointestinal Toxicity After Hypofractionated and Conventionally Fractionated Modern Radiotherapy for Prostate Cancer in the HYPRO Trial

Purpose: Late gastrointestinal (GI) toxicity after radiotherapy for prostate cancer may have significant impact on the cancer survivor's quality of life. To date, little is known about local dose-effects after modern radiotherapy including hypofractionation. In the current study we related the local spatial distribution of radiation dose in the rectum to late patient-reported gastrointestinal (GI) toxicities for conventionally fractionated (CF) and hypofractionated (HF) modern radiotherapy in the randomized HYPRO trial. Material and Methods: Patients treated to 78 Gy in 2 Gy fractions (n = 298) or 64.6 Gy in 3.4 Gy fractions (n = 295) with available late toxicity questionnaires (n ≥ 2 within 1–5 years post-treatment) and available 3D planning data were eligible for this study. The majority received intensity modulated radiotherapy (IMRT). We calculated two types of dose surface maps: (1) the total delineated rectum with its central axis scaled to unity, and (2) the delineated rectum with a length of 7 cm along its central axis aligned on the prostate's half-height point (prostate-half). For each patient-reported GI symptom, dose difference maps were constructed by subtracting average co-registered EQD2 (equivalent dose in 2 Gy) dose maps of patients with and without the symptom of interest, separately for HF and CF. P-values were derived from permutation tests. We evaluated patient-reported moderate to severe GI symptoms. Results: Observed incidences of rectal bleeding and increased stool frequency were significantly higher in the HF group. For rectal bleeding (p = 0.016), mucus discharge (p = 0.015), and fecal incontinence (p = 0.001), significant local dose-effects were observed in HF patients but not in CF patients. For rectal pain, similar local dose-effects (p < 0.05) were observed in both groups. No significant local dose-effects were observed for increased stool frequency. Total rectum mapping vs. prostate-half mapping showed similar results. Conclusion: We demonstrated significant local dose-effect relationships for patient-reported late GI toxicity in patients treated with modern RT. HF patients were at higher risk for increased stool frequency and rectal bleeding, and showed the most pronounced local dose-effects in intermediate-high dose regions. These findings suggest that improvement of current treatment optimization protocols could lead to clinical benefit, in particular for HF treatment.
Auditory Contagious Yawning Is Highest Between Friends and Family Members: Support to the Emotional Bias Hypothesis

Contagious yawning differs from spontaneous yawning because it occurs when an individual yawns in response to someone else’s yawn. In Homo sapiens and some non-human primates contagious yawning is higher between strongly than weakly bonded individuals. Up to date, it is still unclear whether this social asymmetry underlies emotional contagion (a basic form of empathy preferentially involving familiar individuals) as predicted by the Emotional Bias Hypothesis (EBH) or is linked to a top-down, selective visual attention bias (with selective attention being preferentially directed toward familiar faces) as predicted by the Attentional Bias Hypothesis (ABH). To verify whether the visual attentional bias explained the yawn contagion bias or not, in this study, we considered only yawns that could be heard but not seen by potential responders (auditory yawns). Around 294 of auditory yawning occurrences were extrapolated from over 2000 yawning bouts collected in free ranging humans for over nine years. Via GLMM, we tested the effect of intrinsic features (i.e., gender and age) and social bond (from strangers to family members) on yawn. The individual identity of the subjects (trigger and potential responder) was included as random factor. The social bond significantly predicted the occurrence of auditory yawn contagion, which was highest between friends and family members. A gender bias was also observed, with women responding most frequently to others’ yawns and men being responded to most frequently by others. These results confirm that social bond is per se one of the main drivers of the differences in yawn contagion rates between individuals in support of the EBH of yawn contagion.
Adaptive Servo-Ventilation: A Comprehensive Descriptive Study in the Geneva Lake Area

Background: Use of adaptive servo-ventilation (ASV) has been questioned in patients with central sleep apnea (CSA) and chronic heart failure (CHF). This study aims to detail the present use of ASV in clinical practice. Methods: Descriptive, cross-sectional, multicentric study of patients undergoing long term (≥3 months) ASV in the Cantons of Geneva or Vaud (1,288,378 inhabitants) followed by public or private hospitals, private practitioners and/or home care providers. Results: Patients included (458) were mostly male (392; 85.6%), overweight [BMI (median, IQR): 29 kg/m2 (26; 33)], comorbid, with a median age of 71 years (59–77); 84% had been treated by CPAP before starting ASV. Indications for ASV were: emergent sleep apnea (ESA; 337; 73.6%), central sleep apnea (CSA; 108; 23.6%), obstructive sleep apnea (7; 1.5%), and overlap syndrome (6; 1.3%). Origin of CSA was cardiac (n = 30), neurological (n = 26), idiopathic (n = 28), or drug-related (n = 22). Among CSA cases, 60 (56%) patients had an echocardiography within the preceding 12 months; median left ventricular ejection fraction (LVEF) was 62.5% (54–65); 11 (18%) had a LVEF ≤45%. Average daily use of ASV was [mean (SD)] 368 (140) min; 13% used their device <3:30 h. Based on ventilator software, apnea-hypopnea index was normalized in 94% of subjects with data available (94% of 428). Conclusions: Use of ASV has evolved from its original indication (CSA in CHF) to a heterogeneous predominantly male, aged, comorbid, and overweight population with mainly ESA or CSA. CSA in CHF represented only 6.5% of this population. Compliance and correction of respiratory events were satisfactory. Clinical Trial Registration: www.ClinicalTrials. gov, identifier: NCT04054570.
TNF-Signaling Modulates Neutrophil-Mediated Immunity at the Feto-Maternal Interface During LPS-Induced Intrauterine Inflammation

Accumulation of activated neutrophils at the feto-maternal interface is a defining hallmark of intrauterine inflammation (IUI) that might trigger an excessive immune response during pregnancy. Mechanisms responsible of this massive neutrophil recruitment are poorly investigated. We have previously showed that intraamniotic injection of LPS in rhesus macaques induced a neutrophil predominant inflammatory response similar to that seen in human IUI. Here, we demonstrate that anti-TNF antibody (Adalimumab) inhibited ~80% of genes induced by LPS involved in inflammatory signaling and innate immunity in chorio-decidua neutrophils. Consistent with the gene expression data, TNF-blockade decreased LPS-induced neutrophil accumulation and activation at the feto-maternal interface. We also observed a reduction in IL-6 and other pro-inflammatory cytokines but not prostaglandins concentrations in the amniotic fluid. Moreover, TNF-blockade decreased mRNA expression of inflammatory cytokines in the chorio-decidua but not in the uterus, suggesting that inhibition of TNF-signaling decreased the inflammation in a tissue-specific manner within the uterine compartment. Taken together, our results demonstrate a predominant role for TNF-signaling in modulating the neutrophilic infiltration at the feto-maternal interface during IUI and suggest that blockade of TNF-signaling could be considered as a therapeutic approach for IUI, the major leading cause of preterm birth.
Muscles and the Media: A Natural Experiment Across Cultures in Men’s Body Image

An increasing number of studies are evidencing relationships between the drive for muscularity and potentially harmful behavioral strategies, such as unhealthy dieting and steroid use amongst men in WEIRD (Western, Educated, Industrialized, Rich, Democratic) populations. As such Western appearance standards proliferate around the world via the media, men who live in other cultural contexts are also at risk of potentially negative effects from aspiring to the “muscular ideal. ” However, few studies have explored these relationships in non-WEIRD populations. We investigated men’s body ideals and body image in two non-WEIRD, non-White populations, Uganda (Africa) and Nicaragua (Central America), and compared them with an ethnically diverse sample of men in the United Kingdom. We also examined whether socio-cultural factors including media and ethnicity, predicted the drive for muscularity and body change behaviors among our participants. Results showed that Ugandan men had the least desire for muscularity relative to men in the United Kingdom. Supporting the Tripartite model we found that media and peer influences significantly predicted the drive for muscularity, particularly among men from White British and Nicaraguan Miskitu ethnic groups. By contrast, Creole / Garifuna and Mestizo men from Nicaragua were more likely to want to increase muscularity relative to Black African men from Uganda. Overall, our findings support previous research in demonstrating that there are cultural differences in the kind of body men desire, and that men from WEIRD and non-WEIRD populations may experience similar pressures to aspire to and attain a muscular body type.
Grant Proposal Narrative

The international Decision Support Initiative (iDSI) will continue to grow and consolidate a global platform for realising value for money in healthcare spending. We shall work together with lowand middle-income country (LMIC) governments and global development funders to create lasting, country-owned institutional capacity for evidence-informed priority-setting and investing in the most cost-effective and equitable priorities for better population health.
Detecting Advertising Materials via Multi-Scale Instance Segmentation Network

In this paper, we introduce a completely new application in computer vision: detecting advertising materials in commodity pictures. Diﬀerent from the conventional detection tasks, the success of advertising materials detection greatly relies on successfully capturing the semantic and contour information of candidate targets. In our work, we ﬁrstly adopt a fully convolutional instance segmentation network to capture the semantic information and link information of pixels. Secondly, ASPP module and multi-scale prediction structure are introduced to handle materials with various scales. Then, we jointly optimize the network with semantic loss, link loss, and contour loss, to obtain ﬁner detection results. Finally, we provide a dataset specially targeting at advertising materials detection. Experiments on this dataset show the promising performance of the proposed method.
Nuclear Norm Minimization in Frequency Domain for Complex Noise

Recovery of minimum rank matrices is important in many real world applications and has been attracting signiﬁcant research interest in recent years. Traditional methods for low-rank matrix recovery are eﬃcient for the simple type of noise, however noise in real-world data is much more complex than considered so far. As a result, methods based on spatial data representation are insuﬃcient. In this paper, we present weighted nuclear norm for matrix recovery in frequency domain based on the eﬀect of noise in the image. Experimental results clearly show that the weighted minimization in the frequency domain outperforms many state-of-the-art de-noising algorithms in terms of both quantitative measure and visual perception quality.
Individual patient profiling using clinical and neuroradiological biomarkers in acute ischemic stroke: application of advanced multimodal neuroimaging

The aim of the thesis is to study clinical and neuroradiological biomarkers towards individual patient profiling in acute ischaemic stroke (AIS). There is existing evidence that individual patient profiling using a combination of initial stroke severity, infarct topography and surrogate neuroimaging markers provide clinicians with prognostically relevant information that can guide the selection of patients for acute interventions and/or planning and conduct of rehabilitation. Perilesional brain perfusion neuroimaging and cortical venous drain angiography may be additional measures of prognostic relevance. Combinations of these prognostic variables could potentially allow the development of more sophisticated approaches to selection of post-stroke patients for recovery assistance interventions and AIS patients for thrombolytic and/or endovascular treatments. The overall goal of the thesis is to examine specific subgroups of AIS patients and assess functional outcome, where subgroups are defined by, (a) clinically in terms of stroke severity profile (measured using National Institute of Health Stroke Severity (NIHSS) scale), and (b) neuroradiologically depending upon: lesion topography, presence or absence of peri-lesional hyperperfusion, and presence or absence of delayed late venous phase cortical vein filling (delayed-LCVF). Advanced neuroimaging such as arterial spin labelling (ASL) magnetic resonance imaging (MRI) and dynamic computed tomography angiography (dCTA) can be effectively used to discern surrogate imaging biomarkers, investigate underlying post-ischemic pathophysiological mechanisms, identify stroke subtype, and predict the clinical course of AIS patients receiving reperfusion therapy.
Deep Context-Aware Embedding for Abusive and Hate Speech detection on Twitter

Violence usually spread online, as it has spread in the past. With the increasing use of social media, the violence attributed to online hate speech has increased worldwide resulting rise in number of attacks on immigrants and other minorities. Analysis of such short text posts (e.g. tweets etc.) is valuable for identiﬁcation of abusive language and hate speech. In this paper, we present Deep Context-Aware Embedding for the detection of Hate speech and abusive language on twitter. To improve the classiﬁcation performance, we have enhanced the quality of the tweets by considering polsemy, syntax, semantic, OOV words as well as sentiment knowledge and concatenated to form input vector. We have used BiLSTM with attention modeling to identify tweet with hate speech. Experimental results showed signiﬁcant improvement in the classiﬁcation of tweets.
‘Our NGO family has suffered a tragedy, and we will survive.’ Evaluating a crisis response intervention with expatriate aid workers in Afghanistan

In 2008, Taliban forces killed four aid workers in Afghanistan. Immediately afterwards, expatriate and national field staff undertook crisis management activities on the ground. While this was a devastating event, field and headquarters staff agreed that the organisational response to the crisis was positive. Nine months later, 19 expatriate staff members involved in the crisis response participated in an evaluation to reflect on personal and organisational factors that contributed to their post crisis resilience. Results suggest that clear security protocols, crisis simulation preparedness training, team cohesiveness, strong leadership, staff mobilisation, well timed psychological support and support from managers may all contribute to staff resilience in high stress environments. Recommendations are offered to the international nongovernmental organisation community seeking to support staff following critical incidents.
Can you hear me now? Sensitive comparisons of human and machine perception

The rise of machine-learning systems that process sensory input has brought with it a rise in comparisons between human and machine perception. But such comparisons face a challenge: Whereas machine perception of some stimulus can often be probed through direct and explicit measures, much of human perceptual knowledge is latent, incomplete, or unavailable for explicit report. Here, we explore how this asymmetry can cause such comparisons to misestimate the overlap in human and machine perception. As a case study, we consider human perception of adversarial speech - synthetic audio commands that are recognized as valid messages by automated speech-recognition systems but that human listeners reportedly hear as meaningless noise. In five experiments, we adapt task designs from the human psychophysics literature to show that even when subjects cannot freely transcribe such speech commands (the previous benchmark for human understanding), they can sometimes demonstrate other forms of understanding, including discriminating adversarial speech from closely matched nonspeech (Experiments 1 and 2), finishing common phrases begun in adversarial speech (Experiments 3 and 4), and solving simple math problems posed in adversarial speech (Experiment 5) - even for stimuli previously described as unintelligible to human listeners. We recommend the adoption of such "sensitive tests" when comparing human and machine perception, and we discuss the broader consequences of such approaches for assessing the overlap between systems.
A Swarm based Optimization of the XGBoost Parameters

The Extreme Gradient Boosting (XGBoost) is deﬁned as an implementation of gradient boosted decision trees and it has been performing well in several applications and in online competitions. The XGBoost parameters should be carefully selected when XGBoost is used in applications. This paper proposes a general framework for selecting machine learning algorithms parameters and deploys it over the XGBoost. The Particle Swarm Optimization (PSO) algorithm was utilized to select the XGBoost parameters. The proposed method was deployed over a monthly rainfall prediction task. The method was extensively explored by investigating the eﬀect of two PSO attributes: number of particles and iterations. The results demonstrated the applicability of PSO in ﬁnding the best solutions in the available search space in parameters selection tasks. The results have also shown that the XGBoost with PSO can be utilized as an eﬃcient forecasting algorithm.