Miracle-dz/UniFAR-FTUs huggingface dataset:
Dietary phytochemicals, gut microbiota composition, and health outcomes in human and animal models

The role of the composition of the gut microbiota on human health is not well understood. However, during the past decade, an increased emphasis has been placed on the influence of the impact of nutrition on the composition of gut microbiota and how the gut microbiota affects human health. The current review focuses on the role of some of the most studied phytochemicals on the composition of the gut microbiota. First, the review highlights the state of the research evidence regarding dietary phytochemical consumption and gut microbiota composition, including the influence of phytochemicals such as polyphenols, glucosinolates, flavonoids, and sterols that are present in vegetables, nuts, beans, and other foods. Second, the review identifies changes in health outcomes with altered gut microbiota composition, in both animal and human model studies. Third, the review highlights research that includes both associations between dietary phytochemical consumption and gut microbiota composition, and associations between the gut microbiota composition and health outcomes, in order to elucidate the role of the gut microbiota in the relationship between dietary phytochemical consumption and health outcomes in humans and animals. The current review indicated that phytochemicals can beneficially alter gut microbiota composition and decrease the risk for some diseases, such as cancers, and improve some cardiovascular and metabolic risk biomarkers. There is an urgent demand for high-quality studies that determine the relationships between the consumption of phytochemicals and health outcomes, examining gut microbiota as a moderator or mediator.
Some New Results for the Square Subgroup of an Abelian Group

The complete description of the square subgroup of a torsion abelian group and an elementary construction of a mixed abelian group (A, +, 0), such that the quotient group of A modulo the square subgroup □A is not a nil-group, are given (also for the associative case). Some A. M. Aghdam's results concerning square subgroups for the associative case are proven. The relationship between square subgroups for both the cases of associative and general rings is partially investigated.
Racial Differences in Blood Pressure and Autonomic Recovery Following Acute Supramaximal Exercise in Women

Despite the growing popularity of high-intensity anaerobic exercise, little is known about the acute effects of this form of exercise on cardiovascular hemodynamics or autonomic modulation, which might provide insight into the individual assessment of responses to training load. The purpose of this study was to compare blood pressure and autonomic recovery following repeated bouts of acute supramaximal exercise in Black and White women. A convenience sample of twelve White and eight Black young, healthy women were recruited for this study and completed two consecutive bouts of supramaximal exercise on the cycle ergometer with 30 min of recovery in between. Brachial and central aortic blood pressures were assessed by tonometry (SphygmoCor Xcel) at rest and 15-min and 30-min following each exercise bout. Central aortic blood pressure was estimated using brachial pressure waveforms and customized software. Autonomic modulation was measured in a subset of ten participants by heart-rate variability and baroreflex sensitivity. Brachial mean arterial pressure and diastolic blood pressure were significantly higher in Blacks compared to Whites across time (race effect, p = 0.043 and p = 0.049, respectively). Very-low-frequency and low-frequency bands of heart rate variability, which are associated with sympathovagal balance and vasomotor tone, were 22.5% and 24.9% lower, respectively, in Blacks compared to Whites (race effect, p = 0.045 and p = 0.006, respectively). In conclusion, the preliminary findings of racial differences in blood pressure and autonomic recovery following supramaximal exercise warrant further investigations of tailored exercise prescriptions for Blacks and Whites.
Real or Nominal Variables, Does it Matter for the Impulse Response?

This paper analyzes impulse response functions of vector autoregression models for variables that are linearly transformed. These impulse responses are equal to the linear transformation of the original impulse responses only if the shocks are equal to the linear transformation of the original shocks. Sufficient conditions are derived both for shocks in one error term only, orthogonalized shocks and generalized shocks. A vector autoregression model with ination, the overnight target rate and a real interest rate that replaces the corresponding nominal interest rate, illustrates the applicability of our results for the empirical researcher.
Lung Ultrasound in the Evaluation of Lung Disease Severity in Children with Clinically Stable Cystic Fibrosis: A Prospective Cross-Sectional Study

With the increasing longevity of cystic fibrosis (CF), there is a growing need to minimise exposure to ionising radiation in patients who undergo regular imaging tests while monitoring the course of the lung disease. This study aimed to define the role of lung ultrasounds (LUS) in the evaluation of lung disease severity in children with clinically stable CF. LUS was performed on 131 patients aged 5 weeks to 18 years (study group) and in 32 healthy children of an equivalent age range (control group). Additionally, an interobserver study was performed on 38 patients from the study group. In CF patients, the following ultrasound signs were identified: I-lines; Z-lines; single, numerous and confluent B-lines; Am-lines; small and major consolidations; pleural line abnormalities and small amounts of pleural fluid. The obtained results were evaluated against an original ultrasound score. LUS results were correlated with the results of chest X-ray (CXR) [very high], pulmonary function tests (PFTs) [high] and microbiological status [significant]. The interobserver study showed very good agreement between investigators. We conclude that LUS is a useful test in the evaluation of CF lung disease severity compared to routinely used methods. With appropriate standardisation, LUS is highly reproducible.
Evaluating the Effects of Precipitation and Evapotranspiration on Soil Moisture Variability Within CMIP5 Using SMAP and ERA5 Data

The effects of precipitation (Pr) and evapotranspiration (ET) on surface soil moisture (SSM) play an essential role in the land‐atmosphere system. Here we evaluate multimodel differences of these effects within the Coupled Model Intercomparison Project Phase 5 (CMIP5) compared to Soil Moisture Active Passive (SMAP) products and ECMWF Reanalysis v5 (ERA5) as references in a frequency domain. The variability of SSM, Pr, and ET within three frequency bands (1/7 ∼ 1/30 days−1, 1/30 ∼ 1/90 days−1, and 1/90 ∼ 1/365 days−1) after normalization is quantified using Fourier transform. We analyze the impact of ET and Pr on SSM variability based on a transfer function assuming that these variables form a linear time‐invariant (LTI) system. For the total effects of ET and Pr on SSM variability, the CMIP5 estimations are smaller than the reference data in the two higher frequency bands and are larger than the reference data in the lowest frequency band. Besides, the effects on SSM by Pr and ET are found to be different across the three frequency bands. In each frequency band, the variability of the factor that dominates SSM (i.e., Pr or ET) from CMIP5 is smaller than that from the references. This study identifies the spatiotemporal distribution of differences between CMIP5 models and references (SMAP and ERA5) in simulating ET and Pr effects on SSM within three frequency bands. This study provides insightful information on how soil moisture variability is affected by varying precipitation and evapotranspiration at different time scales within Earth System Models.
Development of a point-of-care genetic test for effective treatment of ischaemic stroke: an early model-based cost-effectiveness analysis

Background: People who have experienced a stroke are at high risk of recurrent strokes. Clopidogrel is prescribed to people who have had a non-cardioembolic stroke. There is evidence that clopidogrel is not effective for patients with CYP2C19 loss-of-function alleles. Pharmacogenetic testing is a potential strategy to identify such patients and guide prescription of appropriate antiplatelet treatment. This study aimed to provide an early estimate of the cost-effectiveness of using a point-of-care pharmacogenetic CYP2C19 test in the UK National Health System. Methods: A decision-analytic model comprising a linked decision tree and Markov model were created in R comparing pharmacogenetic testing with current prescribing practice. In the pharmacogenetic testing arm, patients identified to have one of three loss-of-function alleles were prescribed modified-release dipyridamole and aspirin or aspirin alone. Indicative data were sourced from reviews of the literature supported by expert consultation to select the most appropriate value for the input parameters. The healthcare costs (£;2021) and quality adjusted life years resulting from each strategy were estimated and the incremental cost-effectiveness of testing calculated. Deterministic threshold analysis and probabilistic sensitivity analysis (PSA) was conducted to account for uncertainty in the parameter estimates. Results: The pharmacogenetic testing strategy generated 0.107 additional QALYs per patient tested and saved £512. Pharmacogenetic testing dominated current prescribing practice. The results were robust to extreme changes in key input variables. The PSA suggested that there was a 77% chance that pharmacogenetic testing would be cost-effective with a 62% chance it is cost-saving. Conclusions: A point-of-care pharmacogenetic test to guide prescription of clopidogrel for people who have experienced a stroke has the potential to provide a significant health gain by preventing secondary strokes and may save resources in the health system. This early economic analysis has also informed the direction for future research.
Novel Mechanisms and Future Opportunities for the Management of Radiation Necrosis in Patients Treated for Brain Metastases in the Era of Immunotherapy

Simple Summary As the incidence and survival of patients with brain metastases improve, the burden of treatment-related neurotoxicities will increase for patients and healthcare systems. Radiation necrosis, or injury and inflammation to normal brain tissue, is an increasingly common and deleterious adverse effect of radiation therapy that can contribute to patient morbidity and mortality. We aimed to characterize the biological mechanisms that drive necrosis and the risks associated with multimodal therapy, including immunotherapy. This review additionally provides management guidelines and an overview of novel opportunities for investigation. Awareness of the presentation, risk factors, biological mechanisms, and management options for necrosis are crucial for optimal patient-centered care and discovery. Abstract Radiation necrosis, also known as treatment-induced necrosis, has emerged as an important adverse effect following stereotactic radiotherapy (SRS) for brain metastases. The improved survival of patients with brain metastases and increased use of combined systemic therapy and SRS have contributed to a growing incidence of necrosis. The cyclic GMP-AMP (cGAMP) synthase (cGAS) and stimulator of interferon genes (STING) pathway (cGAS-STING) represents a key biological mechanism linking radiation-induced DNA damage to pro-inflammatory effects and innate immunity. By recognizing cytosolic double-stranded DNA, cGAS induces a signaling cascade that results in the upregulation of type 1 interferons and dendritic cell activation. This pathway could play a key role in the pathogenesis of necrosis and provides attractive targets for therapeutic development. Immunotherapy and other novel systemic agents may potentiate activation of cGAS-STING signaling following radiotherapy and increase necrosis risk. Advancements in dosimetric strategies, novel imaging modalities, artificial intelligence, and circulating biomarkers could improve the management of necrosis. This review provides new insights into the pathophysiology of necrosis and synthesizes our current understanding regarding the diagnosis, risk factors, and management options of necrosis while highlighting novel avenues for discovery.
Retrospective Analysis of Artifacts in Cone Beam Computed Tomography Images Used to Diagnose Chronic Rhinosinusitis

Background: Cone beam computed tomography (CBCT) is frequently used to corroborate the signs and symptoms of chronic rhinosinusitis (CRS). However, artifacts induced by dental restorations might complicate the diagnosis of CRS. Here, we assessed the frequency and location of artifacts in CBCT images taken to confirm the CRS. Methods: All CBCT images of the patients referred to the Emergency Radiology unit, Turku University Hospital, with an indication of CRS in 2017 were re-examined. The prevalence of the artifacts was analyzed in three cross-sectional views and three horizontal levels delimited by anatomical landmarks. Results: In total, 214 CBCT images of patients with CRS were evaluated. The diagnosis of apical periodontitis (AP) was impaired by artifacts present in 150/214 images (70%). The diagnosis of CRS was impaired in 5 of the 214 images (2.3%). The main origins of the artifacts were large dental fillings or crowns, and endodontic fillings were present in 95% (203/214) and 52% (111/214) of the images, respectively. Conclusions: AP as an etiology of CRS is possible to miss because of artifacts originating from dental and endodontic fillings in the CBCT images of the paranasal sinuses.
Non‐parametric Kernel Estimation of the Coefficient of a Diffusion

In this work we exhibit a non‐parametric estimator of kernel type, for the diffusion coefficient when one observes a one‐dimensional diffusion process at times i/n for i = , . , n and study its asymptotics as n←∞. When the diffusion coefficient has regularity r≥ 1, we obtain a rate 1/nr/(1+2r), both for pointwise estimation and for estimation on a compact subset of R: this is the same rate as for non‐parametric estimation of a density with i.i. d. observations.
LC/MS-Based Untargeted Metabolomics Analysis in Women with Morbid Obesity and Associated Type 2 Diabetes Mellitus

Obesity is a chronic and complex disease, with an increasing incidence worldwide that is associated with metabolic disorders such as type 2 diabetes mellitus (T2DM). Thus, it is important to determine the differences between metabolically healthy obese individuals and those with metabolic disorders. The aim of this study was to perform an untargeted metabolomics assay in women with morbid obesity (MO) compared to a normal weight group, and to differentiate the metabolome of these women with MO who present with T2DM. We carried out a liquid chromatography-mass spectrometry-based untargeted metabolomics assay using serum samples of 209 Caucasian women: 73 with normal weight and 136 with MO, of which 71 had T2DM. First, we found increased levels of choline and acylglycerols and lower levels of bile acids, steroids, ceramides, glycosphingolipids, lysophosphatidylcholines, and lysophosphatidylethanolamines in MO women than in the control group. Then, in MO women with T2DM, we found increased levels of glutamate, propionyl-carnitine, bile acids, ceramides, lysophosphatidylcholine 14:0, phosphatidylinositols and phosphoethanolamines, and lower levels of Phe-Ile/Leu. Thus, we found metabolites with opposite trends of concentration in the two metabolomic analyses. These metabolites could be considered possible new factors of study in the pathogenesis of MO and associated T2DM in women.
Natural Language Processing Algorithms for Divergent Thinking Assessment

The manual assessment of creativity by human raters is coupled with unavoidable subjectivity and often costs much time and human resources. To address these issues, this paper explores how to apply natural language processing (NLP) methods to the assessment of creativity. Using the Alternative Use Task (AUT), participants were encouraged to generate ideas as fast as possible for a fixed time. It was hypothesized that the similarity of ideas would decrease over time in the AUT, considering the design fixation and the limitation of working memory. In the first study, 12 university students completed the AUT in paper-pencil form and generated a total of 376 responses. We applied two NLP models, namely BERT (Bidirectional Encoder Representations from Transformers) and USE (Universal Sentence Encoder), to assess the similarity of responses between individuals. The results did not confirm our hypothesis. One prominent reason might be that the applied models represent millions of sentence structures that are over-ecological and too dissimilar to the sentence structures participants had used while finishing the AUT. Nevertheless, the results did show that BERT and USE could more accurately express the semantic information of responses pace with the Latent Semantic Analysis, a popular computer-aided model for AUT response assessment. In study 2, we proposed an algorithm to reanalyze the 376 responses in study 1 based on word embedding with crowdsourced responses. There were 1690 crowdsourced responses collected from 550 participants who completed an online version of the AUT. The results supported our hypothesis and showed that the similarity of responses increases as time passes. This indicates the proposed algorithm would alleviate the influence of sentence structure in AUT tasks. The differences between BERT, USE, and proposed algorithms are discussed in relation to the assessment of creativity, and the implications for future work are explored in-depth.
From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on “Allosteric Intersection” of Biochemical and Big Data Approaches

The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric regulation, the emerging structural biology technologies and AI approaches remains largely unexplored, calling for the development of AI-augmented integrative structural biology. In this review, we focus on the latest remarkable progress in deep high-throughput mining and comprehensive mapping of allosteric protein landscapes and allosteric regulatory mechanisms as well as on the new developments in AI methods for prediction and characterization of allosteric binding sites on the proteome level. We also discuss new AI-augmented structural biology approaches that expand our knowledge of the universe of protein dynamics and allostery. We conclude with an outlook and highlight the importance of developing an open science infrastructure for machine learning studies of allosteric regulation and validation of computational approaches using integrative studies of allosteric mechanisms. The development of community-accessible tools that uniquely leverage the existing experimental and simulation knowledgebase to enable interrogation of the allosteric functions can provide a much-needed boost to further innovation and integration of experimental and computational technologies empowered by booming AI field.
Diffuse-interface modelling of thermocapillary flow instabilities in a Hele-Shaw cell

In this paper we present the results of a diffuse-interface model for thermocapillary or Marangoni flow in a Hele-Shaw cell. We use a Galerkin-type spectral element discretization, based on Gauss–Lobatto quadrature, for numerical implementation of the governing equations resulting from the diffuse-interface model. The results are compared to classical results for a linear and circular fixed interface. It is found that the diffuse-interface solution converges to the classical solution in the sharp-interface limit. The results are sufficiently accurate if the interfacial thickness is only small compared to the size of the thermocapillary boundary layer, even if the interfacial thickness used is much larger than the real interfacial thickness. We also consider freely movable interfaces with a temperature gradient perpendicular to the interface. It will be shown that this situation can lead to a destabilizing Marangoni convection.
The Effects of Methylfolate on Cognitive Decline and Dementia: A Protocol for Systematic Review and Meta-Analysis

Introduction: Dementia and cognitive decline are highly prevalent in later life and are growing public health concerns worldwide due to the increasing aging population. Individuals diagnosed with dementia have reduced mental function, resulting in social and cognitive skill deficits, increased dependence, and reduced autonomy—all of which are conditions associated with higher mortality rates. This systematic review aims to assess the effectiveness of treating dementia and cognitive decline with methylfolate. The main outcomes analyzed will be dementia and changes in cognitive function measured by different instruments in older adults treated with methylfolate. Secondary outcomes, such as inflammatory markers, plasma folic-acid levels, and total homocysteine, will also be assessed. Methods and Analysis: This study will be carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. This protocol is registered in the International Prospective Registry of Systematic Reviews, under the code CRD42021275755. We will include clinical trials conducted with older adults diagnosed with dementia or cognitive decline and treated with folic acid. The searches will be conducted on the PubMed, Scopus, and Embase databases, and the articles will be selected by reading their titles and abstracts first, followed by the full text. The quality of the selected studies will be assessed using GRADE and the risk of bias will be assessed using the Downs-and-Black method. Ethics and Dissemination: The results will be presented at scientific conferences and disseminated by publishing a scientific article in an international English-language journal. We hope to find robust and significant evidence regarding the effectiveness of methylfolate supplementation in improving dementia symptoms and cognitive decline among older adults. By systematizing this evidence and possibly performing a meta-analysis study, we expect to significantly contribute to the treatment of this health problem, reduce mortality, and improve the quality of life and health of this population, boosting the development of medical protocols capable of reducing the financial effects of public health.