Miracle-dz/UniFAR-FTUs huggingface dataset:
Patterns of brain neurodegeneration in early-stage relapsing-remitting multiple sclerosis

Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in early-stage RRMS using volumetry and voxel-based morphometry (VBM). RRMS patients (N=354) underwent 3T structural MRI at diagnosis and 1-year follow-up, as part of the Scottish multicentre 'FutureMS' study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter [GM] only), to establish patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the cerebrum, cerebellum and brainstem. Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, multiple subcortical structures, cerebellar GM and the brainstem. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 28 regions and 17/28; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal lobe and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe. Widespread neurodegeneration was observed in early-stage RRMS; particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions. Volumetric and VBM results emphasise different as well as overlapping patterns of longitudinal change, and provide potential response markers for existing therapies and trials of neuroprotective agents.
COVID-19 Surveiller: toward a robust and effective pandemic surveillance system based on social media mining

The outbreak of the novel coronavirus, COVID-19, has become one of the most severe pandemics in human history. In this paper, we propose to leverage social media users as social sensors to simultaneously predict the pandemic trends and suggest potential risk factors for public health experts to understand spread situations and recommend proper interventions. More precisely, we develop novel deep learning models to recognize important entities and their relations over time, thereby establishing dynamic heterogeneous graphs to describe the observations of social media users. A dynamic graph neural network model can then forecast the trends (e.g. newly diagnosed cases and death rates) and identify high-risk events from social media. Based on the proposed computational method, we also develop a web-based system for domain experts without any computer science background to easily interact with. We conduct extensive experiments on large-scale datasets of COVID-19 related tweets provided by Twitter, which show that our method can precisely predict the new cases and death rates. We also demonstrate the robustness of our web-based pandemic surveillance system and its ability to retrieve essential knowledge and derive accurate predictions across a variety of circumstances. Our system is also available at http://scaiweb.cs. ucla.edu/covidsurveiller/. This article is part of the theme issue ‘Data science approachs to infectious disease surveillance’.
Influence of Near-Fault Ground Motions on the Response of Base-Isolated Reinforced Concrete Buildings considering Seismic Pounding

Performance of base-isolated buildings subjected to near-fault ground motions containing long-period pulses is of increasing concern, because these ground motions have the potential to impose large seismic demands on structures. A review of previous studies on the performance evaluation of base-isolated reinforced concrete (RC) buildings under near-fault ground motions shows that these studies lack in the consideration of seismic pounding and the use of lower bound and upper bound values of isolator properties according to the current state of practice. Accordingly, in this study the performance of a typical four-story base-isolated RC building is evaluated using a three-dimensional nonlinear finite element model, considering bounding values of isolator properties, to investigate the influences of (i) pulse-like nature of near-fault ground motions and (ii) seismic pounding with retaining walls at the base. Two sets of ground motions containing 14 far-fault non-pulse-like ground motions and 14 near-fault pulse-like ground motions, representing the risk-targeted maximum considered earthquake (MCER), are used. It is found that the response indicators of the building under near-fault motions are significantly larger than those under far-fault motions. Analysis results reveal that the building response indicators are significantly increased due to seismic pounding. Nonetheless, if a bounding analysis is conducted, consideration of seismic pounding in the analysis does not have appreciable consequences on the prediction of damage to structural elements and drift-sensitive nonstructural components, while dramatic increase in floor accelerations due to pounding is critical for acceleration-sensitive nonstructural components.
Behavioural response to heterogeneous severity of COVID-19 explains temporal variation of cases among different age groups

Together with seasonal effects inducing outdoor or indoor activities, the gradual easing of prophylaxis caused second and third waves of SARS-CoV-2 to emerge in various countries. Interestingly, data indicate that the proportion of infections belonging to the elderly is particularly small during periods of low prevalence and continuously increases as case numbers increase. This effect leads to additional stress on the health care system during periods of high prevalence. Furthermore, infections peak with a slight delay of about a week among the elderly compared to the younger age groups. Here, we provide a mechanistic explanation for this phenomenology attributable to a heterogeneous prophylaxis induced by the age-specific severity of the disease. We model the dynamical adoption of prophylaxis through a two-strategy game and couple it with an SIR spreading model. Our results also indicate that the mixing of contacts among the age groups strongly determines the delay between their peaks in prevalence and the temporal variation in the distribution of cases. This article is part of the theme issue ‘Data science approaches to infectious disease surveillance’.
Introducing linguistic transformation to improve translation memory retrieval. Results of a professional translators’ survey for Spanish, French and Arabic

Translation memory systems (TMS) are the main component of computer-assisted translation (CAT) tools. They store translations allowing to save time by presenting translations on the database through matching of several types such as fuzzy matches, which are calculated by algorithms like the edit distance. However, studies have demonstrated the linguistic deficiencies of these systems and the difficulties in data retrieval or obtaining a high percentage of matching, especially after the application of syntactic and semantic transformations as the active/passive voice change, change of word order, substitution by a synonym or a personal pronoun, for instance. This paper presents the results of a pilot study where we analyze the qualitative and quantitative data of questionnaires conducted with professional translators of Spanish, French and Arabic in order to improve the effectiveness of TMS and explore all possibilities to integrate further linguistic processing from ten transformation types. The results are encouraging, and they allowed us to find out about the translation process itself; from which we propose a pre-editing processing tool to improve the matching and retrieving processes.
Employing Wikipedia as a resource for Named Entity Recognition in Morphologically complex under-resourced languages

We propose a novel approach for rapid prototyping of named entity recognisers through the development of semi-automatically annotated datasets. We demonstrate the proposed pipeline on two under-resourced agglutinating languages: the Dravidian language Malayalam and the Bantu language isiZulu. Our approach is weakly supervised and bootstraps training data from Wikipedia and Google Knowledge Graph. Moreover, our approach is relatively language independent and can consequently be ported quickly (and hence cost-effectively) from one language to another, requiring only minor language-specific tailoring.
Using Transfer Learning to Automatically Mark L2 Writing Texts

The use of transfer learning in Natural Language Processing (NLP) has grown over the last few years. Large, pre-trained neural networks based on the Transformer architecture are one example of this, achieving state-of-theart performance on several commonly used performance benchmarks, often when finetuned on a downstream task. Another form of transfer learning, Multitask Learning, has also been shown to improve performance in Natural Language Processing tasks and increase model robustness. This paper outlines preliminary findings of investigations into the impact of using pretrained language models alongside multitask fine-tuning to create an automated marking system of second language learners’ written English. Using multiple transformer models and multiple datasets, this study compares different combinations of models and tasks and evaluates their impact on the performance of an automated marking system This presentation is a snap-shot of work being conducted as part of my dissertation for the University of Wolverhampton’s Computational Linguistics Masters’ programme.
Recent Updates in Experimental Research and Clinical Evaluation on Drugs for COVID-19 Treatment

Since the outbreak of corona virus disease 2019 (COVID-19) in Wuhan (China) in December 2019, the epidemic has rapidly spread to many countries around the world, posing a huge threat to global public health. In response to the pandemic, a number of clinical studies have been initiated to evaluate the effect of various treatments against COVID-19, combining medical strategies and clinical trial data from around the globe. Herein, we summarize the clinical evaluation about the drugs mentioned in this review for COVID-19 treatment. This review discusses the recent data regarding the efficacy of various treatments in COVID-19 patients, to control and prevent the outbreak.
Analysing Student Perceptions of Intellectual Property Rights in a Self-plagiarism Framework

The volume of material, especially in electronic form is increasing at a rapid pace. Together with improved access to the Internet, the opportunities for plagiarism or the reuse of material among students and researchers alike are increasing. In this regard our paper reports on a survey done among 86 students at a residential university. The questions asked were aimed at evaluating the students’ understanding of what the stealing of intellectual property entails. Coupled with this survey is an analysis of a previously developed framework for testing the view of a number of researchers about self-plagiarism. This paper further investigates to what extent the survey questions fit into the self-plagiarism framework. The conclusions are that students are not sufficiently capable to detect acts of plagiarism. It was also found that the framework could be usefully enhanced to model plagiarism, cheating and the copying of material among students. Some solutions to these problems are offered.
Assessment of Isocitrate Dehydrogenase 1 Genotype and Cell Proliferation in Gliomas Using Multiple Diffusion Magnetic Resonance Imaging

Objectives: To compare the efficacy of parameters from multiple diffusion magnetic resonance imaging (dMRI) for prediction of isocitrate dehydrogenase 1 (IDH1) genotype and assessment of cell proliferation in gliomas. Methods: Ninety-one patients with glioma underwent diffusion weighted imaging (DWI), multi-b-value DWI, and diffusion kurtosis imaging (DKI)/neurite orientation dispersion and density imaging (NODDI) on 3.0T MRI. Each parameter was compared between IDH1-mutant and IDH1 wild-type groups by Mann–Whitney U test in lower-grade gliomas (LrGGs) and glioblastomas (GBMs), respectively. Further, performance of each parameter was compared for glioma grading under the same IDH1 genotype. Spearman correlation coefficient between Ki-67 labeling index (LI) and each parameter was calculated. Results: The diagnostic performance was better achieved with apparent diffusion coefficient (ADC), slow ADC (D), fast ADC (D∗), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), mean kurtosis (MK), and intracellular volume fraction (ICVF) for distinguishing IDH1 genotypes in LrGGs, with statistically insignificant AUC values from 0.750 to 0.817. In GBMs, no difference between the two groups was found. For IDH1-mutant group, all parameters, except for fractional anisotropy (FA) and D∗, significantly discriminated LrGGs from GBMs (P < 0.05). However, for IDH1 wild-type group, only ADC statistically discriminated the two (P = 0.048). In addition, MK has maximal correlation coefficient (r = 0.567, P < 0.001) with Ki-67 LI. Conclusion: dMRI-derived parameters are promising biomarkers for predicting IDH1 genotype in LrGGs, and MK has shown great potential in assessing glioma cell proliferation.
Effect of Transcutaneous Upper Eyelid Blepharoplasty on Blink Parameters and Lipid Layer Thickness

Purpose: This study aimed to investigate the effect of transcutaneous upper eyelid blepharoplasty on lipid layer thickness (LLT) and blink parameters in young women during the early postoperative period. Methods: This prospective study included 110 eyes of 55 young female patients (age range, 19–31 years) who underwent transcutaneous upper eyelid blepharoplasty. The LLT and blink parameters measured using a LipiView interferometer were recorded before the surgery and 1 week and 1 month after the surgery. Ocular Surface Disease Index (OSDI) score, noninvasive tear film breakup time (NITBUT), and palpebral fissure height (PFH) measurements were also performed at each time point. Results: The number of blinks significantly decreased (P < 0.001), and the number of partial blinks and partial blink rate (PBR) significantly increased 1 week after the surgery (P = 0.002 and P < 0.001); they all returned to baseline in 1 month. The LLT and OSDI score increased significantly 1 week and 1 month after the surgery (P < 0.001 and P < 0.001). A significant increase in the NITBUT and a significant decrease in the PFH were observed 1 week after the surgery (P < 0.001 and P < 0.001), and the values returned to baseline 1 month after the surgery. No clinical correlation was found between blink parameters and ocular surface parameters. Conclusions: Transcutaneous upper eyelid blepharoplasty led to a change in blink parameters and ocular surface parameters during the early postoperative period. However, this influence was temporary, and the transitory change in blink parameters had no effects on the ocular surface environment.
A Mutation-Related Long Noncoding RNA Signature of Genome Instability Predicts Immune Infiltration and Hepatocellular Carcinoma Prognosis

Background: Long noncoding RNAs (lncRNAs) have been discovered to play a regulatory role in genomic instability (GI), which participates in the carcinogenesis of various cancers, including hepatocellular carcinoma (HCC). We endeavored to establish a GI-derived lncRNA signature (GILncSig) as a potential biomarker and explore its impact on immune infiltration and prognostic significance. Methods: Combining expression and somatic mutation profiles from The Cancer Genome Atlas database, we identified GI-related lncRNAs and conducted functional analyses on co-expressed genes. Based on Cox regression analysis, a GILncSig was established in the training cohort (n = 187), and an independent testing patient cohort (n = 183) was used to validate its predictive ability. Kaplan-Meier method and receiver operating characteristic curves were adopted to evaluate the performance. The correlation between GI and immune infiltration status was investigated based on the CIBERSORT algorithm and single sample gene set enrichment analysis. In addition, a comprehensive nomogram integrating the GILncSig and clinicopathological variables was constructed to efficiently assess HCC patient prognosis in clinical applications. Results: A total of 88 GI-related lncRNAs were screened out and the functional analyses indicated diversified effects on HCC progression. The GILncSig was established using four independent lncRNAs (AC116351.1, ZFPM2-AS1, AC145343.1, and MIR210HG) with significant prognostic value (p < 0.05). Following evaluation with the GILncSig, low-risk patients had significantly better clinical outcomes than high-risk patients in the training cohort (p < 0.001), which was subsequently validated in the independent testing cohort. High-risk group exhibited more immunocyte infiltration including B cells memory, macrophages M0 and neutrophils and higher expression of HLA gene set and immune checkpoint genes. Compared to existing HCC signatures, the GILncSig showed better prognosis predictive performance [area under the curve (AUC) = 0.709]. Furthermore, an integrated nomogram was constructed and validated to efficiently and reliably evaluate HCC patient prognosis (3-years survival AUC = 0.710 and 5-years survival AUC = 0.707). Conclusion: The GILncSig measuring GI and impacting immune infiltration serves as a potential biomarker and independent predictor of HCC patient prognosis. Our results highlight further investigation of GI and HCC molecular mechanisms.
Rapid-Onset Anti-Stress Effects of a Kappa-Opioid Receptor Antagonist, LY2795050, Against Immobility in an Open Space Swim Paradigm in Male and Female Mice

The kappa-opioid receptor (KOR) / dynorphin system is implicated with behavioral and neurobiological effects of stress exposure (including heavy exposure to drugs of abuse) in translational animal models. Thus some KOR-antagonists can decrease the aversive, depressant-like and anxiety-like effects caused by stress exposure. The first generation of selective KOR-antagonists have slow onsets (hours) and extremely long durations of action (days-weeks), in vivo. A new generation of KOR antagonists with rapid onset and shorter duration of action can potentially decrease the effects of stress exposure in translational models, and may be of interest for medication development. This study examined the rapid onset anti-stress effects of one of the shorter acting novel KOR-antagonists (LY2795050, (3-chloro-4-(4-(((2S)-2-pyridin-3-ylpyrrolidin-1-yl)methyl) phenoxy)benzamide)) in a single-session open space swim (OSS) stress paradigm (15 min duration), in adult male and female C57BL/6 J mice. LY2795050 (0.32 mg/kg, i.p.) had rapid onset (within 15 min) and short duration (<3 h) of KOR-antagonist effects, based on its blockade of the locomotor depressant effects of the KOR-agonist U50,488 (10 mg/kg). LY2795050 (0.32 mg/kg), when administered only 1 min prior to the OSS stress paradigm, decreased immobility in males, but not females. With a slightly longer pretreatment time (15 min), this dose of LY2795050 decreased immobility in both males and females. A 10-fold smaller dose of LY2795050 (0.032 mg/kg) was inactive in the OSS, showing dose-dependence of this anti-stress effect. Overall, these studies show that a novel KOR-antagonist can produce very rapid onset anti-immobility effects in this model of acute stress exposure.
Effects of Xylooligosaccharides on Lipid Metabolism, Inflammation, and Gut Microbiota in C57BL/6J Mice Fed a High-Fat Diet

Xylooligosaccharide (XOS) is a source of prebiotics with multiple biological activities. The present study aimed to investigate the effects of XOS on mice fed a high-fat diet. Mice were fed either a normal diet or a high-fat diet supplemented without or with XOS (250 and 500 mg/kg), respectively, for 12 weeks. The results showed that the XOS inhibited mouse weight gain, decreased the epididymal adipose index, and improved the blood lipid levels, including triglyceride (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) levels. Moreover, XOS reduced the activity of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), and alleviated the damage to the liver caused by the high-fat diet. XOS also reduced hyperlipidemia-associated inflammatory responses. Additionally, quantitative real-time polymerase chain reaction results showed that XOS intervention activated the AMP-activated protein kinase (AMPK) pathway to regulate the fat synthesis, decomposition, and β oxidation; upregulated the mRNA expression levels of carnitine palmitoyl transferase 1 (CPT-1), peroxisome proliferator–activated receptors α (PPAR-α), and cholesterol 7-alpha hydroxylase (CYP7A1); and downregulated the mRNA expression levels of acetyl-CoA carboxylase (ACC), CCAAT/enhancer-binding protein alpha (C/EBPα), and lipoprotein lipase (LPL). On the other hand, XOS enhanced the mRNA expression levels of zonula occludens-1 (ZO-1), occludin, and claudin-1 in the small intestine; increased the strength of the intestinal barrier; and optimized the composition of the intestinal microbiota. Therefore, it was concluded that XOS regulated the intestinal barrier, changed the intestinal microecology, and played an important role in preventing hyperlipidemia through the unique anatomical advantages of the gut–liver axis.
Paeonol Attenuated Vascular Fibrosis Through Regulating Treg/Th17 Balance in a Gut Microbiota-Dependent Manner

Background: Paeonol (Pae) is a natural phenolic compound isolated from Cortex Moutan, which exhibits anti-atherosclerosis (AS) effects. Our previous work demonstrated that gut microbiota plays an important role during AS treatment as it affects the efficacy of Pae. However, the mechanism of Pae in protecting against vascular fibrosis as related to gut microbiota has yet to be elucidated. Objective: To investigate the antifibrosis effect of Pae on AS mice and demonstrate the underlying gut microbiota-dependent mechanism. Methods: ApoE-/- mice were fed with high-fat diet (HFD) to replicate the AS model. H&E and Masson staining were used to observe the plaque formation and collagen deposition. Short-chain fatty acid (SCFA) production was analyzed through LC-MS/MS. The frequency of immune cells in spleen was phenotyped by flow cytometry. The mRNA expression of aortic inflammatory cytokines was detected by qRT-PCR. The protein expression of LOX and fibrosis-related indicators were examined by western blot. Results: Pae restricted the development of AS and collagen deposition. Notably, the antifibrosis effect of Pae was achieved by regulating the gut microbiota. LC-MS/MS data indicated that the level of SCFAs was increased in caecum contents. Additionally, Pae administration selectively upregulated the frequency of regulatory T (Treg) cells as well as downregulated the ratio of T helper type 17 (Th17) cells in the spleen of AS mice, improving the Treg/Th17 balance. In addition, as expected, Pae intervention can significantly downregulate the levels of proinflammatory cytokines IL-1β, IL-6, TNF-α, and IL-17 in the aorta, and upregulate the levels of anti-inflammatory factor IL-10, a marker of Treg cells. Finally, Pae’s intervention in the gut microbiota resulted in the restoration of the balance of Treg/Th17, which indirectly downregulated the protein expression level of LOX and fibrosis-related indicators (MMP-2/9 and collagen I/III). Conclusion: Pae attenuated vascular fibrosis in a gut microbiota-dependent manner. The underlying protective mechanism was associated with the improved Treg/Th17 balance in spleen mediated through the increased microbiota-derived SCFA production. Collectively, our results demonstrated the role of Pae as a potential gut microbiota modulator to prevent and treat AS.