Miracle-dz/UniFAR-FTUs huggingface dataset:
Detrimental effects of physical inactivity on peripheral and brain vasculature in humans: Insights into mechanisms, long-term health consequences and protective strategies

The growing prevalence of physical inactivity in the population highlights the urgent need for a more comprehensive understanding of how sedentary behaviour affects health, the mechanisms involved and what strategies are effective in counteracting its negative effects. Physical inactivity is an independent risk factor for different pathologies including atherosclerosis, hypertension and cardiovascular disease. It is known to progressively lead to reduced life expectancy and quality of life, and it is the fourth leading risk factor for mortality worldwide. Recent evidence indicates that uninterrupted prolonged sitting and short-term inactivity periods impair endothelial function (measured by flow-mediated dilation) and induce arterial structural alterations, predominantly in the lower body vasculature. Similar effects may occur in the cerebral vasculature, with recent evidence showing impairments in cerebral blood flow following prolonged sitting. The precise molecular and physiological mechanisms underlying inactivity-induced vascular dysfunction in humans are yet to be fully established, although evidence to date indicates that it may involve modulation of shear stress, inflammatory and vascular biomarkers. Despite the steady increase in sedentarism in our societies, only a few intervention strategies have been investigated for their efficacy in counteracting the associated vascular impairments. The current review provides a comprehensive overview of the evidence linking acute and short-term physical inactivity to detrimental effects on peripheral, central and cerebral vascular health in humans. We further examine the underlying molecular and physiological mechanisms and attempt to link these to long-term consequences for cardiovascular health. Finally, we summarize and discuss the efficacy of lifestyle interventions in offsetting the negative consequences of physical inactivity.
Impact of ambient air pollution on outdoor employees’ performance: Mediating role of anxiety

This paper aims to examine the direct and indirect impact of ambient air pollution (AAP) on employees’ performance. This study has used cross sectional survey design to collect the data from the outdoor employees of the pharmaceutical industry of Pakistan. The data were collected in time lags from 299. Partial least squares- structural equation modeling (PLS-SEM) approach was applied to analyze the data. The results show that AAP has a significant negative impact on the employees’ performance, and anxiety partially mediates the association between AAP and employees’ performance. This study reveals that AAP brings anxiety among outdoor employees, which in turn decreases their working performance. The implications, limitations, and future research directions are presented in the last section of this study.
Post-operative neutrophil-to-lymphocyte ratio and outcome after thrombectomy in acute ischemic stroke

Background Neutrophil to lymphocyte ratio (NLR) is a novel inflammatory marker to predict adverse cardiovascular events. However, there is a lack of data on hemorrhagic transformation (HT) and neurological outcome after mechanical thrombectomy in acute ischemic stroke (AIS). We investigated whether NLR before and after thrombectomy for patients with AIS was associated with HT and neurological outcomes. Methods We performed a retrospective analysis of consecutive patients with anterior circulation AIS who underwent thrombectomy. HT was evaluated by CT within 24 h after thrombectomy. Clinical data had been collected retrospectively; laboratory data were extracted from our electronic hospital information system. NLR was obtained at admission (NLR1) and immediately after thrombectomy (NLR2). The main outcomes were post-interventional intracranial hemorrhage and unfavorable functional status (modified Rankin scale scores of 3–6) 3 months post-stroke. Results A total of 258 patients with AIS, according to the NIHSS (median 14), were included. NLR2 was higher in patients who developed HT after thrombectomy and unfavorable neurological outcomes 3 months post-stroke (p < 0.001) than in those without HT or favorable outcomes, even after correction for co-factors [Odds Ratio (OR) 1.35 for HT, 95% confidence interval (CI)1.16–1.57, p < 0.001, and 1.85 for unfavorable outcome, 95%CI 1.57–2.17, p < 0.001]. The optimal cutoff value for the NLR2 as an indicator for auxiliary diagnosis of HT and the unfavorable outcome was 8.4 and 8.8, respectively. Conclusion NLR immediately after thrombectomy is a readily available biomarker of HT and neurological outcomes in patients with AIS.
The combination of sarcopenia and biochemical factors can predict the survival of hepatocellular carcinoma patients receiving transarterial chemoembolization

Background Transarterial chemoembolization(TACE) is the suggested treatment for hepatocellular carcinoma (HCC) not amenable to curative treatments. We investigated the role of sarcopenia on overall survival in HCC patients receiving TACE and proposed a new prognostic scoring system incorporating sarcopenia. Materials and methods We retrospectively analyzed 260 HCC patients who received TACE between 2010 and 2015. Total psoas muscle was measured on a cross-sectional CT image before the first TACE session. Sarcopenia was defined by the pre-determined sex-specific cutoff value. We assessed the impact of sarcopenia and other biochemical factors on the overall survival and compared the new scoring system with other prognostic scoring systems. Results One hundred and thirty patients (50%) were classified as sarcopenia before the first TACE. They were older with a higher male tendency and a significantly lower body mass index (BMI). Cox regression multivariate analysis demonstrated that sarcopenia, multiple tumors, maximal tumor diameter≥ 5cm, major venous thrombosis, sarcopenia, AFP ≥ 200 ng/ml, and albumin<3.5mg/dL were independent poor prognostic factors for overall survival in HCC patients receiving TACE. Our scoring system comprising these factors outperformed other major scoring systems in terms of predicting survival after TACE. Conclusion The current study demonstrated that sarcopenia was an independent prognostic factor for HCC undergoing TACE therapy. Our newly developed scoring system could effectively predict patient survival after TACE. Physicians could, based on the current score model, carefully select candidate patients for TACE treatment in order to optimize their survival. Further studies are warranted to validate our findings.
Malnutrition leads to increased inflammation and expression of tuberculosis risk signatures in recently exposed household contacts of pulmonary tuberculosis

Background Most individuals exposed to Mycobacterium tuberculosis (Mtb) develop latent tuberculosis infection (LTBI) and remain at risk for progressing to active tuberculosis disease (TB). Malnutrition is an important risk factor driving progression from LTBI to TB. However, the performance of blood-based TB risk signatures in malnourished individuals with LTBI remains unexplored. The aim of this study was to determine if malnourished and control individuals had differences in gene expression, immune pathways and TB risk signatures. Methods We utilized data from 50 tuberculin skin test positive household contacts of persons with TB - 18 malnourished participants (body mass index [BMI] < 18.5 kg/m2) and 32 controls (individuals with BMI ≥ 18.5 kg/m2). Whole blood RNA-sequencing was conducted to identify differentially expressed genes (DEGs). Ingenuity Pathway Analysis was applied to the DEGs to identify top canonical pathways and gene regulators. Gene enrichment methods were then employed to score the performance of published gene signatures associated with progression from LTBI to TB. Results Malnourished individuals had increased activation of inflammatory pathways, including pathways involved in neutrophil activation, T-cell activation and proinflammatory IL-1 and IL-6 cytokine signaling. Consistent with known association of inflammatory pathway activation with progression to TB disease, we found significantly increased expression of the RISK4 (area under the curve [AUC] = 0.734) and PREDICT29 (AUC = 0.736) progression signatures in malnourished individuals. Conclusion Malnourished individuals display a peripheral immune response profile reflective of increased inflammation and a concomitant increased expression of risk signatures predicting progression to TB. With validation in prospective clinical cohorts, TB risk biomarkers have the potential to identify malnourished LTBI for targeted therapy.
A matter of origin - identification of SEMA3A, BGLAP, SPP1 and PHEX as distinctive molecular features between bone site-specific human osteoblasts on transcription level

In oral and maxillofacial bone reconstruction, autografts from the iliac crest represent the gold standard due to their superior clinical performance, compared to autografts derived from other extraoral regions. Thus, the aim of our study was to identify putative differences between osteoblasts derived from alveolar (hOB-A) and iliac crest (hOB-IC) bone of the same donor (nine donors) by means of their molecular properties in 2D and 3D culture. We thereby focused on the gene expression of biomarkers involved in osteogenic differentiation, matrix formation and osteoclast modulation. Furthermore, we examined the transcriptional response to Vit.D3 in hOB-A and hOB-IC. Our results revealed different modulation modes of the biomarker expression in osteoblasts, namely cell origin/bone entity-dependent, and culture configuration- and/or time-dependent modulations. SEMA3A, SPP1, BGLAP and PHEX demonstrated the strongest dependence on cell origin. With respect to Vit.D3-effects, BGLAP, SPP1 and ALPL displayed the highest Vit.D3-responsiveness. In this context we demonstrated that the transcriptional Vit.D3-response concerning SPP1 and ALPL in human osteoblasts depended on the cell origin. The results indicate a higher bone remodeling activity of iliac crest than alveolar osteoblasts and support the growing evidence that a high osteoclast activity at the host-/donor bone interface may support graft integration.
An in-silico approach to studying a very rare neurodegenerative disease using a disease with higher prevalence with shared pathways and genes: Cerebral adrenoleukodystrophy and Alzheimer’s disease

Cerebral adrenoleukodystrophy (cALD) is a rare neurodegenerative disease characterized by inflammatory demyelination in the central nervous system. Another neurodegenerative disease with a high prevalence, Alzheimer’s disease (AD), shares many common features with cALD such as cognitive impairment and the alleviation of symptoms by erucic acid. We investigated cALD and AD in parallel to study the shared pathological pathways between a rare disease and a more common disease. The approach may expand the biological understandings and reveal novel therapeutic targets. Gene set enrichment analysis (GSEA) and weighted gene correlation network analysis (WGCNA) were conducted to identify both the resemblance in gene expression patterns and genes that are pathologically relevant in the two diseases. Within differentially expressed genes (DEGs), GSEA identified 266 common genes with similar up- or down-regulation patterns in cALD and AD. Among the interconnected genes in AD data, two gene sets containing 1,486 genes preserved in cALD data were selected by WGCNA that may significantly affect the development and progression of cALD. WGCNA results filtered by functional correlation via protein–protein interaction analysis overlapping with GSEA revealed four genes (annexin A5, beta-2-microglobulin, CD44 molecule, and fibroblast growth factor 2) that showed robust associations with the pathogeneses of cALD and AD, where they were highly involved in inflammation, apoptosis, and the mitogen-activated protein kinase pathway. This study provided an integrated strategy to provide new insights into a rare disease with scant publicly available data (cALD) using a more prevalent disorder with some pathological association (AD), which suggests novel druggable targets and drug candidates.
Efficacy of nGVS to improve postural stability in people with bilateral vestibulopathy: A systematic review and meta-analysis

Objective Noisy galvanic vestibular stimulation (nGVS) has been used to boost vestibular afferent information to the central nervous system. This has the potential to improve postural control for people for whom vestibular signals are weak, such as in bilateral vestibulopathy (BVP). The aim of this systematic review and meta-analysis is to investigate the evidence for nGVS as a modality to improve postural control in people with BVP. Methods A comprehensive systematic search was conducted of five databases up to July 2022 to find studies applying nGVS to people with BVP, with the aim of improving postural control. Two independent reviewers screened and identified eligible studies, completed a risk of bias evaluation (Cochrane) and extracted relevant data. The standardized mean difference (SMD) based on Hedges' g was calculated as a measure of effect size for the primary outcome measure that best identified postural control, and a forest plot generated. Results Seven studies met the eligibility criteria, with five being suitable for meta-analysis. Meta-analysis revealed a moderate effect in favor of nGVS improving postural control during standing and walking [pooled SMD = 0.47 95% CI (0.25, 0.7)]. nGVS-mediated improvements in postural control were most evident in observations of reduced sway velocity when standing on a firm surface with eyes closed, and in the reduced variability of gait parameters, particularly those measuring lateral stability. Conclusions Coincident nGVS in people with BVP improves postural control during standing and walking. This improvement appears to be context specific, in that vestibular augmentation is most effective in situations where visual inputs are limited, and where reliable context specific proprioceptive cues are available. Further research is warranted investigating additional circumstances in which nGVS improves postural control, including investigating the residual, and sustained effects of nGVS. Systematic review registration https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=342147, identifier: 342147.
Machine learning for autism spectrum disorder diagnosis using structural magnetic resonance imaging: Promising but challenging

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects approximately 1% of the population and causes significant burdens. ASD’s pathogenesis remains elusive; hence, diagnosis is based on a constellation of behaviors. Structural magnetic resonance imaging (sMRI) studies have shown several abnormalities in volumetric and geometric features of the autistic brain. However, inconsistent findings prevented most contributions from being translated into clinical practice. Establishing reliable biomarkers for ASD using sMRI is crucial for the correct diagnosis and treatment. In recent years, machine learning (ML) and specifically deep learning (DL) have quickly extended to almost every sector, notably in disease diagnosis. Thus, this has led to a shift and improvement in ASD diagnostic methods, fulfilling most clinical diagnostic requirements. However, ASD discovery remains difficult. This review examines the ML-based ASD diagnosis literature over the past 5 years. A literature-based taxonomy of the research landscape has been mapped, and the major aspects of this topic have been covered. First, we provide an overview of ML’s general classification pipeline and the features of sMRI. Next, representative studies are highlighted and discussed in detail with respect to methods, and biomarkers. Finally, we highlight many common challenges and make recommendations for future directions. In short, the limited sample size was the main obstacle; Thus, comprehensive data sets and rigorous methods are necessary to check the generalizability of the results. ML technologies are expected to advance significantly in the coming years, contributing to the diagnosis of ASD and helping clinicians soon.
Detoxification technology and mechanism of processing with Angelicae sinensis radix in reducing the hepatotoxicity induced by rhizoma Dioscoreae bulbiferae in vivo

Rhizoma Dioscoreae Bulbiferae (RDB) was effective on relieving cough and expectorant but accompanied by severe toxicity, especially in hepatotoxicity. A previous study found that processing with Angelicae Sinensis Radix (ASR) reduced RDB-induced hepatotoxicity. However, up to now, the optimized processing process of ASR-processed RDB has not been explored or optimized, and the detoxification mechanism is still unknown. This study evaluated the detoxification technology and possible mechanism of processing with ASR on RDB-induced hepatotoxicity. The optimized processing process of ASR-processed RDB was optimized by the content of diosbulbin B (DB), the levels of serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and histopathological analysis. The processing detoxification mechanism was evaluated by detecting the antioxidant levels of nuclear factor E2 related factor 2 (Nrf2) and its downstream heme oxygenase 1 (HO-1), quinone oxidoreductase 1 (NQO1), glutamylcysteine ligase catalytic subunit (GCLM), and the levels of downstream antioxidant factors of Nrf2. Besides, the antitussive and expectorant efficacy of RDB was also investigated. This work found that processing with ASR attenuated RDB-induced hepatotoxicity, which can be verified by reducing the levels of ALT, AST, and ALP, and reversing the pathological changes of liver histomorphology. And the optimized processing process of ASR-processed RDB is “processing at a mass ratio of 100:20 (RDB:ASR) and a temperature of 140°C for 10 min.” Further results corroborated that the intervention of processed products of ASR-processed RDB remarkably upregulated the Nrf2/HO-1/NQO1/GCLM protein expression levels in liver, and conserved antitussive and expectorant efficacy of RDB. The above findings comprehensively indicated that the optimized processing process of ASR-processed RDB was “processing at a mass ratio of 100:20 (RDB:ASR) and a temperature of 140°C for 10 min,” and the processing detoxification mechanism involved enhancing the level of Nrf2-mediated antioxidant defense in liver as a key target organ.
A brainnetome atlas-based methamphetamine dependence identification using neighborhood component analysis and machine learning on functional MRI data

Addiction to methamphetamine (MA) is a major public health concern. Developing a predictive model that can classify and characterize the brain-based biomarkers predicting MA addicts may directly lead to improved treatment outcomes. In the current study, we applied the support vector machine (SVM)-based classification method to resting-state functional magnetic resonance imaging (rs-fMRI) data obtained from individuals with methamphetamine use disorder (MUD) and healthy controls (HCs) to identify brain-based features predictive of MUD. Brain connectivity analyses were conducted for 36 individuals with MUD as well as 37 HCs based on the brainnetome atlas, and the neighborhood component analysis was applied for feature selection. Eighteen most relevant features were screened out and fed into the SVM to classify the data. The classifier was able to differentiate individuals with MUD from HCs with a high prediction accuracy, sensitivity, specificity, and AUC of 88.00, 86.84, 89.19, and 0.94, respectively. The top six discriminative features associated with changes in the functional activity of key nodes in the default mode network (DMN), all the remaining discriminative features are related to the thalamic connections within the cortico-striato-thalamo-cortical (CSTC) loop. In addition, the functional connectivity (FC) between the bilateral inferior parietal lobule (IPL) and right cingulate gyrus (CG) was significantly correlated with the duration of methamphetamine use. The results of this study not only indicated that MUD-related FC alterations were predictive of group membership, but also suggested that machine learning techniques could be used for the identification of MUD-related imaging biomarkers.
Life cycle energy analysis of residential wooden buildings versus concrete and steel buildings: A review

Around 40% of global energy consumption can be attributed to the construction sector. Consequently, the development of the construction industry towards more sustainable solutions and technologies plays a crucial role in the future of our planet. Various tools and methods have been developed to assess the energy consumption of buildings, one of which is life cycle energy analysis (LCEA). LCEA requires the energy consumption at each stage of the life cycle of a product to be assessed, enabling the comparison of the impact of construction materials on energy consumption. Findings from LCEAs of buildings suggest that timber framed constructions show promising results with respect to energy consumption and sustainability. In this study a critical analysis of 100 case studies from the literature of LCEAs conducted for residential buildings is presented. Based on the studied material, the embodied, operational, and demolition energies for timber, concrete and steel buildings are compared and the importance of sustainable material selection for buildings is highlighted. The results reveal that on average, the embodied energy of timber buildings is 28–47% lower than for concrete and steel buildings respectively. The mean and median values of embodied emissions are 2,92 and 2,97 for timber, 4.08 and 3,95 for concrete, and 5,55 and 5,53 GJ/m2 for steel buildings. Moreover, the data suggests that the energy supply system of residential buildings plays a larger role in the operational energy consumption that the construction material. In addition, climate conditions, insulation detail, windows and building surfaces, and building direction are the other energy use role players. Finally, it was found that the demolition energy contributes only a small amount to the total life cycle energy consumption. This study demonstrates the significance of embodied energy when comparing the life cycle energy requirements of buildings and highlights the need for the development of a more standardised approach to LCEA case studies.
Estimating the stopping power distribution during proton therapy: A proof of concept

Objective: We introduce a new treatment verification technique to estimate the primary particle’s stopping power from prompt gamma timing measurements in proton therapy. Approach: The starting point is the Spatio-temporal Emission Recostruction technique, which provides the time-depth distribution of the emitted prompt photons with a multiple Prompt-Gamma Timing detector setup based on Lanthanum Bromide crystals. A dedicated formalism based on an analytical approximation of the stopping power is developed to obtain the desired information. Its performance is evaluated in a proof of concept configuration via Monte Carlo simulations of monochromatic proton beams impinging on a homogeneous PMMA phantom. Main Results: Results indicate stopping power estimations as good as 3.8% with respect to NIST values, and range estimations within 0.3 cm (standard deviation), when considering 250 ps FWHM timing resolution. Significance: The current study shows, for the first time, the feasibility of evaluating the stopping power of primary beams with a technique that can be performed in-vivo, opening up new possibilities in the field of treatment verification and therapy optimization.