Miracle-dz/UniFAR-FTUs huggingface dataset:
Linking heart rate variability to psychological health and brain structure in adolescents with and without conduct disorder

Aims Heart rate variability (HRV) measures have been suggested in healthy individuals as a potential index of self-regulation skills, which include both cognitive and emotion regulation aspects. Studies in patients with a range of psychiatric disorders have however mostly focused on the potential association between abnormally low HRV at rest and specifically emotion regulation difficulties. Emotion regulation deficits have been reported in patients with Conduct Disorder (CD) however, the association between these emotion regulation deficits and HRV measures has yet to be fully understood. This study investigates (i) the specificity of the association between HRV and emotion regulation skills in adolescents with and without CD and (ii) the association between HRV and grey matter brain volumes in key areas of the central autonomic network which are involved in self-regulation processes, such as insula, lateral/medial prefrontal cortices or amygdala. Methods Respiratory sinus arrhythmia (RSA) measures of HRV were collected from adolescents aged between 9–18 years (693 CD (427F)/753 typically developing youth (TD) (500F)), as part of a European multi-site project (FemNAT-CD). The Inverse Efficiency Score, a speed-accuracy trade-off measure, was calculated to assess emotion and cognitive regulation abilities during an Emotional Go/NoGo task. The association between RSA and task performance was tested using multilevel regression models. T1-weighted structural MRI data were included for a subset of 577 participants (257 CD (125F); 320 TD (186F)). The CerebroMatic toolbox was used to create customised Tissue Probability Maps and DARTEL templates, and CAT12 to segment brain images, followed by a 2 × 2 (sex × group) full factorial ANOVA with RSA as regressor of interest. Results There were no significant associations between RSA and task performance, neither during emotion regulation nor during cognitive regulation trials. RSA was however positively correlated with regional grey matter volume in the left insula (pFWE = 0.011) across all subjects. Conclusion RSA was related to increased grey matter volume in the left insula across all subjects. Our results thus suggest that low RSA at rest might be a contributing or predisposing factor for potential self-regulation difficulties. Given the insula’s role in both emotional and cognitive regulation processes, these brain structural differences might impact either of those.
Regulation of PD-L1 expression in non–small cell lung cancer by interleukin-1β

Introduction Programmed cell death–ligand 1 (PD-L1) is a biomarker for prediction of the clinical efficacy of immune checkpoint inhibitors in various cancer types. The role of cytokines in regulation of PD-L1 expression in tumor cells has not been fully characterized, however. Here we show that interleukin-1β (IL-1β) plays a key role in regulation of PD-L1 expression in non–small cell lung cancer (NSCLC). Methods We performed comprehensive screening of cytokine gene expression in NSCLC tissue using available single-cell RNA-Sequence data. Then we examined the role of IL-1β in vitro to elucidate its induction of PD-L1 on NSCLC cells. Results The IL-1β gene is highly expressed in the tumor microenvironment, particularly in macrophages. The combination of IL-1β and interferon-γ (IFN-γ) induced a synergistic increase in PD-L1 expression in NSCLC cell lines. IL-1β and IFN-γ also cooperatively activated mitogen-activated protein kinase (MAPK) signaling and promoted the binding of downstream transcription factors to the PD-L1 gene promoter. Furthermore, inhibitors of MAPK signaling blocked upregulation of PD-L1 by IL-1β and IFN-γ. Discussion Our study reports high levels of IL-1β in the tumor microenvironment may cooperate with IFN-γ to induce maximal PD-L1 expression in tumor cells via activation of MAPK signaling, with the IL-1β–MAPK axis being a promising therapeutic target for attenuation of PD-L1–mediated suppression of antitumor immunity.
Computer-aided diagnosis using embedded ensemble deep learning for multiclass drug-resistant tuberculosis classification

Introduction This study aims to develop a web application, TB-DRD-CXR, for the categorization of tuberculosis (TB) patients into subgroups based on their level of drug resistance. The application utilizes an ensemble deep learning model that classifies TB strains into five subtypes: drug sensitive tuberculosis (DS-TB), drug resistant TB (DR-TB), multidrug-resistant TB (MDR-TB), pre-extensively drug-resistant TB (pre-XDR-TB), and extensively drug-resistant TB (XDR-TB). Methods The ensemble deep learning model employed in the TB-DRD-CXR web application incorporates novel fusion techniques, image segmentation, data augmentation, and various learning rate strategies. The performance of the proposed model is compared with state-of-the-art techniques and standard homogeneous CNN architectures documented in the literature. Results Computational results indicate that the suggested method outperforms existing methods reported in the literature, providing a 4.0%-33.9% increase in accuracy. Moreover, the proposed model demonstrates superior performance compared to standard CNN models, including DenseNet201, NASNetMobile, EfficientNetB7, EfficientNetV2B3, EfficientNetV2M, and ConvNeXtSmall, with accuracy improvements of 28.8%, 93.4%, 2.99%, 48.0%, 4.4%, and 7.6% respectively. Conclusion The TB-DRD-CXR web application was developed and tested with 33 medical staff. The computational results showed a high accuracy rate of 96.7%, time-based efficiency (ET) of 4.16 goals/minutes, and an overall relative efficiency (ORE) of 100%. The system usability scale (SUS) score of the proposed application is 96.7%, indicating user satisfaction and a likelihood of recommending the TB-DRD-CXR application to others based on previous literature.
Validation of the short version of the obsessive compulsive spectrum questionnaire

Aim In the recent years, a rising amount of research has stressed the importance of a dimensional perspective on mental disorders. In particular, the conceptualization of an obsessive–compulsive spectrum appears to be in line with the very first descriptions of Obsessive–Compulsive Disorder and has been partially acknowledged by the inclusion of the “OCD-spectrum related syndromes and disorders” section in the DSM-5. The goal of the current study is to ascertain the psychometric characteristics of the Obsessive–Compulsive Spectrum–Short Version (OBS-SV), a novel questionnaire designed to measure the complete range of obsessive–compulsive symptoms, from severe full blown to subthreshold ones. Methods Forty three subjects with a clinical diagnosis of OCD according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5); 42 subjects with a clinical diagnosis of social anxiety disorder (SAD), and 60 individuals without current or lifetime mental disorders (HC) were recruited from the Psychiatric Clinic of the University of Pisa. Subjects were assessed with the SCID-5, the Yale Brown Obsessive Compulsive Scale (Y-BOCS) and the OBS-SV. Results OBS-SV showed strong test–retest reliability for both the total and the domains scores, as well as a high level of internal consistency. The Pearson’s coefficients for the OBS-SV domain scores ranged from 0.771 to 0.943, and they were positively and strongly linked with one another (p < 0.001). The OBS-SV total score had a strong correlation with each of the OBS-SV domain scores. All correlation coefficients between OBS-SV and additional measures of OCS were observed to be strong, significant and positive. Both OBS-SV domain and overall score differences between diagnostic groups were found to be statistically significant. From HCs, to the SAD, up to the OC group, which had the highest values, the OBS-SV total score grew dramatically and progressively. Conclusion The OBS-SV demonstrated significant convergent validity with other dimensional OCD measures, excellent internal consistency, and test–retest reliability. Across the three diagnostic categories, the questionnaire functioned differently, with a rising score gradient from healthy controls through SAD patients to OCD subjects.
Fluorescence microscopy-based sensitive method to quantify dopaminergic neurodegeneration in a Drosophila model of Parkinson’s disease

Death of dopaminergic (DAergic) neurons in the substantia nigra pars compacta of the human brain is the characteristic pathological feature of Parkinson’s disease (PD). On exposure to neurotoxicants, Drosophila too exhibits mobility defects and diminished levels of brain dopamine. In the fly model of sporadic PD, our laboratory has demonstrated that there is no loss of DAergic neuronal number, however, a significant reduction in fluorescence intensity (FI) of secondary antibodies that target the primary antibody-anti-tyrosine hydroxylase (TH). Here, we present a sensitive, economical, and repeatable assay to characterize neurodegeneration based on the quantification of FI of the secondary antibody. As the intensity of fluorescence correlates with the amount of TH synthesis, its reduction under PD conditions denotes the depletion in the TH synthesis, suggesting DAergic neuronal dysfunction. Reduction in TH protein synthesis is further confirmed through Bio-Rad Stain-Free Western Blotting. Quantification of brain DA and its metabolites (DOPAC and HVA) using HPLC-ECD further demonstrated the depleted DA level and altered DA metabolism as evident from enhanced DA turnover rate. Together all these PD marker studies suggest that FI quantification is a refined and sensitive method to understand the early stages of DAergic neurodegeneration. FI quantification is performed using ZEN 2012 SP2, a licensed software from Carl Zeiss, Germany. This method will be of good use to biologists, as it with few modifications, can also be implemented to characterize the extent of degeneration of different cell types. Unlike the expensive and cumbersome confocal microscopy, the present method using fluorescence microscopy will be a feasible option for fund-constrained neurobiology laboratories in developing countries.
Asian elephants as ecological filters in Sundaic forests

Megaherbivores exert strong top-down influence on the ecosystems they inhabit, yet little is known about the foraging impacts of Asian elephants (Elephas maximus) on the structure of Southeast Asia’s rainforests. Our goal was to document Asian elephants’ dietary composition, selectivity, and foraging impacts in a Sundaic rainforest and test whether these differed between habitats. We conducted controlled direct observations of five wild-born captive elephants feeding on six plant types (bamboo, grass, monocot herbs, palms, lianas, and trees) of different age 2 in two habitats (mature vs. early successional forest) in Krau, Peninsular Malaysia. Palms, trees, and lianas formed the bulk of the elephants’ diet. In the mature forest, elephants showed a strong preference for monocots (preference ratio, PR = 5.1), particularly large palms (PR = 5.4), while trees were negatively selected (PR = 0.14). Conversely, in early successional habitats, large tree saplings were positively selected (PR = 1.6). Elephants uprooted (30%) and broke the main stem (30%) of the dicot trees, mainly large saplings, that they handled. Tree saplings broken by elephants had an average diameter of 1.7 ± 1.1 cm (up to 7 cm), with breaks happening at 1.1 ± 0.5 m of height. We estimated that, in a year, an elephant could damage (i.e., either uproot or break) around 39,000 tree saplings if it fed entirely in mature forest, and almost double the number (73,000) if it fed solely in early successional habitats. Assuming a density of 0.05–0.18 elephants/km2, elephant foraging could damage 0.2–0.6% of the tree sapling population per year. Slow growth rates of understory plants in mature forests could result in negative feedbacks, whereby elephants suppress palms, other monocots, and highly preferred tree species. Alternatively, elephants may initiate positive feedbacks by impeding succession along forest edges and in semi-open environments, thereby increasing the size of gaps and the availability of their preferred foodplants. Overall, our results show that Asian elephants act as ecological filters by suppressing the plants they prefer in Southeast Asia’s rainforests.
Differences in the organization of interface residues tunes the stability of the SARS-CoV-2 spike-ACE2 complex

The continuous emergence of novel variants represents one of the major problems in dealing with the SARS-CoV-2 virus. Indeed, also due to its prolonged circulation, more than ten variants of concern emerged, each time rapidly overgrowing the current viral version due to improved spreading features. As, up to now, all variants carry at least one mutation on the spike Receptor Binding Domain, the stability of the binding between the SARS-CoV-2 spike protein and the human ACE2 receptor seems one of the molecular determinants behind the viral spreading potential. In this framework, a better understanding of the interplay between spike mutations and complex stability can help to assess the impact of novel variants. Here, we characterize the peculiarities of the most representative variants of concern in terms of the molecular interactions taking place between the residues of the spike RBD and those of the ACE2 receptor. To do so, we performed molecular dynamics simulations of the RBD-ACE2 complexes of the seven variants of concern in comparison with a large set of complexes with different single mutations taking place on the RBD solvent-exposed residues and for which the experimental binding affinity was available. Analyzing the strength and spatial organization of the intermolecular interactions of the binding region residues, we found that (i) mutations producing an increase of the complex stability mainly rely on instaurating more favorable van der Waals optimization at the cost of Coulombic ones. In particular, (ii) an anti-correlation is observed between the shape and electrostatic complementarities of the binding regions. Finally, (iii) we showed that combining a set of dynamical descriptors is possible to estimate the outcome of point mutations on the complex binding region with a performance of 0.7. Overall, our results introduce a set of dynamical observables that can be rapidly evaluated to probe the effects of novel isolated variants or different molecular systems.
Is the internet a sufficient source of information on sarcoidosis?

Introduction Many patients use the internet as a source of health information. Sarcoidosis is a complex disease, and internet resources have not yet been analyzed for reliability and content on sarcoidosis. Aims Our study aimed to investigate the content and the quality of information on sarcoidosis provided by internet resources. Methods Google, Yahoo, and Bing were searched for the term “sarcoidosis,” and the first 200 hits were saved in each case. Those websites that met the inclusion criteria (English language, no registration fees, and relevant to sarcoidosis) were then analyzed by two independent investigators for readability, quality (HON, JAMA, and DISCERN), and content (25 predefined key facts) of the provided information. Results The websites were most commonly scientific or governmental (n = 57, 46%), and the median time since the last update was 24 months. Quality was rated with a median JAMA score of 2 (1; 4) and a median overall DISCERN score of 2.4 (1.1; 4.1), both scores represent partially sufficient information. In total, 15% of websites had a HON certificate. Website content measured by the median key fact score was 19 (ranging from 2.5 to 25) with the lowest scores for acute vs. chronic course of the disease, screening for extrapulmonary disease, and diffuse body pain. Poor results were achieved in industry websites and blogs (p = 0.047) with significant differences regarding definition (p = 0.004) and evaluation (p = 0.021). Discussion Sarcoidosis-related content of internet resources is partially sufficient; however, several important aspects are frequently not addressed, and the quality of information is moderate. Future directions should focus on providing reliable and comprehensive information on sarcoidosis; physicians from different disciplines and patients including self-support groups should collaborate on achieving this.
Effect of Shi-Zhen-An-Shen herbal formula granule in the treatment of young people at ultra-high risk for psychosis: a pilot study

Introduction To date, there is no conclusive evidence for early interventions on ultra-high risk (UHR) for psychosis. The Chinese herbal medicine is confirmed to be beneficial in improving psychiatric symptoms and cognitive impairments for schizophrenia patients. However, the effect of Chinese herbal medicine on treating UHR patients remains unknown. Methods Eighty UHR patients were recruited from the outpatient department. They were randomly assigned to receive either Shi-Zhen-An-Shen herbal formula granule (SZAS-HFG) combined with aripiprazole placebo or aripiprazole combined with SZAS-HFG placebo for a 12-week treatment. The psychiatric symptoms were assessed using the Structured Interview for Prodromal Syndromes (SIPS). The Trail Making Test part A (TMT-A), Brief Visuospatial Memory Test (BVMT), Hopkins Verbal Learning Test (HVLT), and Continuous Performance Test (CPT) were used to assess cognitive functions. we also employed the Global Assessment of Functioning (GAF) to evaluate social functioning. The linear mixed-effects models were performed to detect the difference in effectiveness between the two groups. Results After 12-week treatment, both groups showed significant effects of time on SIPS, TMT-A, HVLT, BVMT, and GAF. There was a significant effect of group only on CPT. Moreover, we also found a significant interaction effect on GAF. Conclusion SZAS-HFG can effectively alleviate psychosis symptoms, and improve cognitive impairments and overall functioning as well as aripiprazole. Clinical trial registration: Chinese Clinical Trial Registry, ChiCTR-IOR-17013513.
Purification, characterization and probiotic proliferation effect of exopolysaccharides produced by Lactiplantibacillus plantarum HDC-01 isolated from sauerkraut

In this study, an exopolysaccharide (EPS)-producing strain of Lactiplantibacillus plantarum HDC-01 was isolated from sauerkraut, and the structure, properties and biological activity of the studied EPS were assessed. The molecular weight of the isolated EPS is 2.505 × 106 Da. Fourier transform infrared spectrometry (FT-IR) and nuclear magnetic resonance (NMR) results showed that the EPS was composed of glucose/glucopyranose subunits linked by an α-(1 → 6) glycosidic bond and contained an α-(1 → 3) branching structure. X-ray diffraction (XRD) analysis revealed the amorphous nature of the EPS. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) showed that the isolated EPS had a smooth and compact surface with several protrusions of varying lengths and irregularly shaped material. Moreover, the studied EPS showed good thermal stability, water holding capacity, and milk coagulation ability and promoted the growth of probiotics. L. plantarum EPS may be used as prebiotics in the fields of food and medicine.
Optimization of macronutrients for improved grain yield of quinoa (Chenopodium quinoa Wild.) crop under semi-arid conditions of Morocco

In the context of climate change, quinoa represents a potential alternative crop for increasing crops diversity, agricultural productivity, and farmer’s income in semi-arid regions. However, appropriate crop management practices under limited water supply are still poorly documented. Quinoa, like other cultivated crops, needs optimum quantities of nutrients, especially nitrogen (N), phosphorus (P), and potassium (K), for better growth and high grain yield. To determine the adequate levels of nutrient requirements and their effect on quinoa growth and productivity, a field experiment was conducted during two growing seasons (2020–2021 and 2021–2022). The experiment was conducted in Ben Guerir region, north-central Morocco, and consisted of a randomized complete block design (RCBD) with three replications. The treatments studied consist of a combination of four N rates (0, 40, 80, and 120 kg ha−1), three P rates (0, 30, and 60 kg P2O5 ha−1), and three K rates (0, 60, and 120 kg K2O ha−1). The physiological, nutritional, and production parameters of quinoa were collected and analyzed. The results showed that the highest total biomass (3.9 t ha−1) and grain yield (0.8 t ha−1) under semi-arid conditions were obtained with 40 kg N ha−1, 60 kg P2O5 ha−1, and 120 kg K2O ha−1. The application of 40–60–120 kg ha−1 of N–P2O5–K2O increased plant height by 44%, chlorophyll content index by 96%, total biomass by 134%, grain yield by 112%, and seed weight by 118%. Among the three macronutrients, N was the most limiting factor, followed by K and P. Nutrients uptake data showed that quinoa needs 60 kg N, 26 kg P2O5, and 205 kg K2O to produce 1 t of grain yield. Our field results provide future recommendations for improving the agronomic and environmental sustainability of quinoa cultivation in dryland areas in Morocco.
Solution to a multisensor tracking problem with sensor registration errors

An on-line solution to the aircraft tracking problem with a distributed network of 3D sensors that are imperfectly registered is presented. Errors in the relative positions and orientations of the sensors are modelled and estimated by an extended Kalman filter [EKF], along with the track variables. This optimal solution, tractable for a limited number of targets, is compared through Monte-Carlo simulation with a suboptimal filter that neglects the sensor systematic errors. The registration errors substantially degrade the accuracy of the aircraft position estimates. The performance of the optimal filter depends on whether the registration errors are to be determined in an absolute or relative setting. When the sensor systematic errors are estimated relative to one of the sensors, the optimal filter performance is excellent. The simulation results are confirmed by a covariance analysis of the optimal filters.
Laboratory automation, informatics, and artificial intelligence: current and future perspectives in clinical microbiology

Clinical diagnostic laboratories produce one product—information—and for this to be valuable, the information must be clinically relevant, accurate, and timely. Although diagnostic information can clearly improve patient outcomes and decrease healthcare costs, technological challenges and laboratory workflow practices affect the timeliness and clinical value of diagnostics. This article will examine how prioritizing laboratory practices in a patient-oriented approach can be used to optimize technology advances for improved patient care.