Miracle-dz/UniFAR-FTUs huggingface dataset:
Water-soluble vitamin insufficiency, deficiency and supplementation in children and adolescents with a psychiatric disorder: a systematic review and meta-analysis

ABSTRACT Nutrition is fundamental for brain development, but relatively little is known about water-soluble vitamin (WSV) levels and the effect of supplementation on psychiatry symptoms in children and adolescents (CAD) with psychiatric disorders. Our team systematically reviewed all studies concerning WSV abnormalities or supplementation in CAD with any psychiatric disorder. We searched for original studies published between 1990 and 15/05/2020 which were not based on retrospective chart review and which included WSV blood level measurements or investigated the effect of WSV supplementation on psychiatric symptoms in psychiatric patients aged 18 or under. Forty-two articles were included, 69% of which (N = 29) examined Autism Spectrum Disorders (ASD), with most of these assessing folate or vitamin B12 supplementation (N = 22, 75.9% of ASD studies). Meta-analyses showed significantly lower vitamin B12 levels in ASD and ADHD patients vs. healthy controls (HC), while folate levels were higher in ADHD patients vs. HC. Most of the studies (9/10, 90%) showed a decrease in symptoms as measured by clinical scales after supplementation. There was significant heterogeneity between the studies, however many found different types of vitamin abnormalities in CAD with psychiatric disorders.
Educational responses to the challenges of the COVID-19 global pandemic: online provision and its consequences for the social resilience of minority communities

ABSTRACT Social resilience can be defined as the individual’s willingness to mobilise for the communal good, combined with the ability of societal institutions to both resist and adapt to changing conditions. Social resilience has become increasingly important as we respond to the challenges the COVID-19 pandemic poses to education. As individuals, we are expected to act for the communal good by wearing masks, following social distancing and allowing contact tracing. At the institutional level, education providers have responded to the current situation to a great extent by rapidly moving education online. However, online education provision has connotations which threaten the quality of education provision for minorities (ethnic, religious, and others). This paper looks at potential scenarios of online education disadvantaging minorities and suggests principles which can guide socially resilient education transformation in response to crises like the global COVID-19 pandemic.
Prediction of SARS-CoV-2 spike protein mutations using Sequence-to-Sequence and Transformer models

In the study of viral epidemics, having information about the structural evolution of the virus can be very helpful in controlling the disease and making vaccines. Various deep learning and natural language processing techniques (NLP) can be used to analyze genetic structure of viruses, namely to predict their mutations. In this paper, by using Sequence-to-Sequence (Seq2Seq) model with Long Short-Term Memory (LSTM) cell and Transformer model with the attention mechanism, we investigate the spike protein mutations of SARS-CoV-2 virus. We make time-series datasets of the spike protein sequences of this virus and generate upcoming spike protein sequences. We also determine the mutations of the generated spike protein sequences, by comparing these sequences with the Wuhan spike protein sequence. We train the models to make predictions in December 2021, February 2022, and October 2022. Furthermore, we find that some of our generated spike protein sequences have been reported in December 2021 and February 2022, which belong to Delta and Omicron variants. The results obtained in the present study could be useful for prediction of future mutations of SARS-CoV-2 and other viruses.
Consolidating regulatory and personal accounts of student migration: a mixed methods study in the UK and Japan

ABSTRACT Taking the UK and Japan as contrasting national case studies, this article supplements existing research into student migration by consolidating a regulatory perspective with individual narrative accounts. Reported here are the results of a mixed-methods two-phase study. Phase 1 is a concerted trajectory analysis of student migration policy in the UK and Japan from 2004 to 2018, while phase 2 draws on biographical-narrative interviews with 26 student-migrants. The paper reveals tangible effects of the receptivity, stability, and transparency of regulatory frameworks in student-migrants’ trajectories, while also demonstrating that seemingly receptive regulatory environments do not necessarily equate to smooth and risk-free post-study transitions.
Revealing the drivers of antibiotic resistance trends in Streptococcus pneumoniae amidst the 2020 COVID-19 pandemic: Insights from mathematical modeling

Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built in into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus- bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.
Developing a robust technique for denoising and extracting speech and breath sounds in voice recordings from asthmatic patients

Auscultation and processing cough, voice and breath sounds play an important role in diagnosis of several pulmonary ailments. There have been a number of studies using machine learning algorithms on such sound files to build classification and prediction algorithms. Since these studies used specialized microphones in controlled environments, it is difficult to test and deploy these algorithms in real-life settings. Recorded speech files consist of breath and wheeze sounds and it is challenging to extract from this single sound file. Hence, several audio processing and editing software are used to demarcate these sounds. The proposed technique uses a combination of a denoiser and an extraction technique to overcome these drawbacks. The developed pipeline ensures that the audio files are free of any environmental and background noises, and the audio can be recorded through any kind of microphone and environmental settings. The extraction technique further is the result of combinations of filters to output the speech and breath sounds as individual sound files, ready for processing and eliminating the need of audio editing and processing software.
Evolution during uncorrelated environmental fluctuations: bet-hedging or phenotypic plasticity?

Evolution in fluctuating environments is predicted to select for phenotypic plasticity or bet-hedging, depending on the accuracy of environmental cues and type of fluctuations. While these two alternatives are often contrasted in theoretical studies, their evolution are seldom studied together in empirical work. We used experimental evolution in the nematode worm Caenorhabditis remanei to simultaneously study the evolution of plasticity and bet-hedging in environments differing only in their temperature variability. We exposed worms for 30 generations to either fast fluctuating or slowly increasing temperature, these two environments had the same average temperature over evolutionary time. After experimental evolution, we scored size at sexual maturity and fitness in full siblings reared in two different temperatures, optimal 20°C and mildly stressful 25°C. Experimental evolution in the fluctuating environment resulted in the evolution of increased body size plasticity but not increased bet-hedging, compared to evolution in the slowly changing environment. Plasticity followed the temperature size rule as size decreased with increasing temperature and this plastic response was adaptive. In addition, we discovered substantial standing genetic variation in body size, which represents a potential for further evolutionary change.
Supporting central nervous system neuroprotection and remyelination by specific TLR4 antagonism

ApTOLL is an aptamer specifically designed to antagonize toll-like receptor 4 (TLR4), which is involved in the innate immunity that promotes inflammatory responses in several diseases, including multiple sclerosis (MS). MS is a chronic, immune, demyelinating and neurodegenerative disease of the central nervous system that represents the second most important cause of neurological disability in young adults. The drugs currently available to treat this disease are immunomodulators and, to date, there are no therapeutic remyelinating drugs available to manage MS. In this study, we show that TLR4 is located in post-mortem cortical lesions of MS patients and as a result, we evaluated the effect of its inhibition by ApTOLL in two different animal models of MS, that of experimental autoimmune encephalomyelitis (EAE) and the cuprizone model. ApTOLL administration ameliorated the clinical symptomatology of the affected mice, which was associated with better preservation and restoration of myelin and oligodendrocytes in the demyelinated lesions of these animals. This revealed not only an immunomodulatory but also a remyelinating effect of the treatment with ApTOLL which was corroborated on purified cultures of rodent and adult human oligodendrocyte precursor cells (OPCs). In summary, the molecular nature of ApTOLL and its mechanism of action strongly supports its further study and use in novel strategies to treat MS and eventually, other demyelinating diseases.
Aspartyl protease in the secretome of honey bee trypanosomatid parasite is essential for the efficient infection of host

Exoproteome represents the proteome consisting of all secreted proteins and proteins derived from the cell surface and lysed cell. The exoproteome of the trypanosomatid parasite should interact with the host cells and the associated microbiota; however, the roles of infecting insect hosts are not yet understood. To uncover the functions of exoproteome, we identified the exoproteome of honey bee trypanosomatid parasite, Lotmaria passim, and found that approximately 28 % are shared with that common between Leishmania spp. It demonstrates a core exoproteome with conserved functions exists in the Leishmaniinae lineage. The bioinformatic characterization suggests that L. passim exoproteome may interact with the host and its microbiota as well as their metabolites. Deletion of genes encoding two secretome proteins revealed that an aspartyl protease but not chitinase affects the development of L. passim under the culture condition and is necessary for the efficient infection in the honey bee gut. Our results demonstrate that the exoproteome represents a resource to uncover the mechanisms of trypanosomatid parasites to infect the insect host by interacting with the gut environment.
Aurora B Kinase Dependent Phosphorylation of Keratin 8 is required for Cytokinesis in Mammalian Cells of Epithelial Origin

Keratins are the most diverse family of intermediate filaments and are expressed in most epithelial tissues and malignancies. They form highly stable polymers that need to be cut through during cytokinesis. Previous work suggested a role of phosphorylation, but keratin regulation during cell division is not understood in detail. Depletion of Keratin 8 in an epithelial cancer cell line (HeLa) caused chromosome segregation and cytokinesis defects. Aurora B kinase localization to midzones and cleavage furrows was reduced in Keratin 8 knockouts, suggesting that Keratin 8 helps scaffold Aurora B during cytokinesis. We mapped eleven Aurora B kinase sites in Keratin 8 that were associated with cell division. Keratin 8 S34 phosphorylation occurred specifically at the cleavage furrow and persisted at the midzone until the end of cytokinesis. Inhibition of Aurora B kinase or non-phosphorylatable Keratin 8 mutant prevented the disassembly of keratin bundles at the cleavage furrow, which blocked furrow ingression. Our data reveal a functional inter-dependency between Keratin 8 and Aurora B kinase in epithelial cells. Keratin 8 promotes the translocation of Aurora B to the midzone. Aurora B kinase then generates a local zone of Keratin phosphorylation which promotes keratin filament disassembly and allows the cleavage furrow to cut through the keratin network.
Capturing the dynamics of microbiomes using individual-specific networks

Background Longitudinal analysis of multivariate individual-specific microbiome profiles over time or across conditions remains a daunting task. The vast majority of statistical tools and methods available to study the microbiota are based upon cross-sectional data. Over the past few years, several attempts have been made to model the dynamics of bacterial species over time or across conditions. However, the field needs novel views on how to incorporate individual-specific microbial associations in temporal analyses when the focus lies on microbial interactions. Results Here, we propose a novel data analysis framework, called MNDA, to uncover taxon neighbourhood dynamics that combines representation learning and individual-specific microbiome co-occurrence networks. We show that tracking local neighbourhood dynamics in microbiome interaction or co-occurrence networks can yield complementary information to standard approaches that only use microbial abundances or pairwise microbial interactions. We use cohort data on infants for whom microbiome data was available at 6 and 9 months after birth, as well as information on mode of delivery and diet changes over time. In particular, MNDA-based prediction models outperform traditional prediction models based on individual-specific abundances, and enable the detection of microbes whose neighbourhood dynamics are informative of clinical variables. We further show that similarity analyses of individuals based on microbial neighbourhood dynamics can be used to find subpopulations of individuals with potential relevance to clinical practice. The annotated source code for the MNDA framework can be downloaded from: https://github.com/H2020TranSYS/microbiome_dynamics Conclusions MNDA extracts information from matched microbiome profiles and opens new avenues to personalized prediction or stratified medicine with temporal microbiome data.
Fast triangular formulation of the square root filter.

A new, triangular formulation of the square root Kalman filter is presented. An efficient analytic algorithm is derived for maintaining the covariance square root matrix in triangular form during the incorporation of measurements. The triangular form provides significant computational savings in the square root time update calculations. This savings tends to offset the computational disadvantage of square root methods in general, due to the greater complexity of incorporating process noise. The new square root method is shown to be typically 50% faster than the Potter square root method, 100% faster than the Joseph conventional method, and comparable in speed to the standard Kalman method. Numerical precision of the new method is greater, and storage requirements equal to or less than those of other methods.
Molecular characterization and functional analysis of cytochrome P450-mediated detoxification CYP302A1 gene involved in host plant adaptation in Spodoptera frugieprda

The fall armyworm (FAW) Spodoptera frugiperda is a destructive and polyphagous pest of many essential food crops including maize and rice. The FAW is hard to manage, control, or eradicate, due to its polyphagous nature and voracity of feeding. Here, we report the characterization and functional analysis of the detoxification gene CYP302A1 and how S. frugieprda larvae use a detoxification mechanism to adapt host plants. Results demonstrated that CYP302A1 expression levels were much higher in midgut tissue and the older S. frugiperda larvae. Our current studies revealed the enhanced P450 activity in the midguts of S. frugiperda larvae after exposure to rice plants as compared to corn plants and an artificial diet. Furthermore, higher mortality was observed in PBO treated larvae followed by the exposure of rice plants as compared to the corn plant. The dsRNA-fed larvae showed downregulation of CYP302A1 gene in the midgut. At the same time, higher mortality, reduced larval weight and shorter developmental time was observed in the dsRNA-fed larvae followed by the exposure of rice plant as compared to the corn plant and DEPC-water treated plants as a control. These results concluded that the inducible P450 enzyme system and related genes could provide herbivores with an ecological opportunity to adapt to diverse host plants by utilizing secondary compounds present in their host plants.
Prediction of hydrocarbon source rock distribution using logging curves: A case study of Es3 2 source rock in Nanpu Sag, Huanghua depression, Bohai Bay Basin

The Es3 is the main hydrocarbon source rock system in the Nanpu Sag. Finally, the TOC and hydrocarbon potential of each sub depression of Es3were predicted. The study shows that the hydrocarbon source rocks of Es3 2 and Es3 4 sections are mainly of type II2 and type II1 respectively, with good organic matter type and high maturity. Biomarker compound parameters indicate that the Es3 2 section hydrocarbon source rocks developed in a semi-saline, low to medium terrestrial source organic matter supplied reduction environment with a high algal contribution; the Es3 4 section hydrocarbon source rocks formed in a freshwater, low terrestrial source supplied reduction environment with a medium-high algal contribution. The multiple linear regression method is more effective than the ΔlgR method in predicting hydrocarbon source rocks in the Nanpu Sag, and the prediction accuracy is higher; the correlation between TOC and S1 + S2 is the best in the model for predicting hydrocarbon potential. The TOC and hydrocarbon potential of the hydrocarbon source rocks in Es3 1 are generally low; the high value area of TOC and hydrocarbon potential of the hydrocarbon source rocks in Es3 2 is partly between the No. 1 tectonic zone and No. 5 tectonic zone in Linque sub depression, and the TOC and hydrocarbon potential of the hydrocarbon source rocks in Liunan sub depression are larger; the high value area of TOC and hydrocarbon potential of the hydrocarbon source rocks in Es3 4 is mainly concentrated in Shichang sub depression.
Behind the scenes: How RNA orchestrates the epigenetic regulation of gene expression

Non-coding DNA accounts for approximately 98.5% of the human genome. Once labeled as “junk DNA”, this portion of the genome has undergone a progressive re-evaluation and it is now clear that some of its transcriptional products, belonging to the non-coding RNAs (ncRNAs), are key players in cell regulatory networks. A growing body of evidence demonstrates the crucial impact of regulatory ncRNAs on mammalian gene expression. Here, we focus on the defined relationship between chromatin-interacting RNAs, particularly long non-coding RNA (lncRNA), enhancer RNA (eRNA), non-coding natural antisense transcript (ncNAT), and circular RNA (circRNA) and epigenome, a common ground where both protein and RNA species converge to regulate cellular functions. Through several examples, this review provides an overview of the variety of targets, interactors, and mechanisms involved in the RNA-mediated modulation of loci-specific epigenetic states, a fundamental evolutive strategy to orchestrate mammalian gene expression in a timely and reversible manner. We will discuss how RNA-mediated epigenetic regulation impacts development and tissue homeostasis and how its alteration contributes to the onset and progression of many different human diseases, particularly cancer.
Opposite pattern of transcranial direct current stimulation effects in middle-aged and older adults: Behavioral and neurophysiological evidence

Introduction Episodic memory (EM) exhibits an age-related decline, with overall increased impairment after the age of 65. The application of transcranial direct current stimulation (tDCS) to ameliorate cognitive decline in ageing has been extensively investigated, but its efficacy has been reported with mixed results. In this study, we aimed to assess whether age contributes to interindividual variability in tDCS efficacy. Methods Thirty-eight healthy adults between 50 and 81 years old received anodal tDCS over the left prefrontal cortex during images encoding and then performed an EM recognition task while event-related potentials (ERPs) were recorded. Results Our results showed an opposite pattern of effect between middle-aged (50–64 years) and older (65–81 years) adults. Specifically, performance in the recognition task after tDCS was enhanced in older adults and was worsened in middle-aged adults. Moreover, ERPs acquired during the recognition task showed that two EM components related to familiarity and post-retrieval monitoring, i.e., Early Frontal and Late Frontal Old-New effects, respectively, were significantly reduced in middle-aged adults after anodal tDCS. Discussion These results support an age-dependent effect of prefrontal tDCS on EM processes and its underlying electrophysiological substrate, with opposing modulatory trajectories along the aging lifespan.