Miracle-dz/UniFAR-FTUs huggingface dataset:
Adopting a High-Polyphenolic Diet Is Associated with an Improved Glucose Profile: Prospective Analysis within the PREDIMED-Plus Trial

Previous studies suggested that dietary polyphenols could reduce the incidence and complications of type-2 diabetes (T2D); although the evidence is still limited and inconsistent. This work analyzes whether changing to a diet with a higher polyphenolic content is associated with an improved glucose profile. At baseline, and at 1 year of follow-up visits, 5921 participants (mean age 65.0 ± 4.9, 48.2% women) who had overweight/obesity and metabolic syndrome filled out a validated 143-item semi-quantitative food frequency questionnaire (FFQ), from which polyphenol intakes were calculated. Energy-adjusted total polyphenols and subclasses were categorized in tertiles of changes. Linear mixed-effect models with random intercepts (the recruitment centers) were used to assess associations between changes in polyphenol subclasses intake and 1-year plasma glucose or glycosylated hemoglobin (HbA1c) levels. Increments in total polyphenol intake and some classes were inversely associated with better glucose levels and HbA1c after one year of follow-up. These associations were modified when the analyses were run considering diabetes status separately. To our knowledge, this is the first study to assess the relationship between changes in the intake of all polyphenolic groups and T2D-related parameters in a senior population with T2D or at high-risk of developing T2D.
Breath Analysis: A Promising Tool for Disease Diagnosis—The Role of Sensors

Early-stage disease diagnosis is of particular importance for effective patient identification as well as their treatment. Lack of patient compliance for the existing diagnostic methods, however, limits prompt diagnosis, rendering the development of non-invasive diagnostic tools mandatory. One of the most promising non-invasive diagnostic methods that has also attracted great research interest during the last years is breath analysis; the method detects gas-analytes such as exhaled volatile organic compounds (VOCs) and inorganic gases that are considered to be important biomarkers for various disease-types. The diagnostic ability of gas-pattern detection using analytical techniques and especially sensors has been widely discussed in the literature; however, the incorporation of novel nanomaterials in sensor-development has also proved to enhance sensor performance, for both selective and cross-reactive applications. The aim of the first part of this review is to provide an up-to-date overview of the main categories of sensors studied for disease diagnosis applications via the detection of exhaled gas-analytes and to highlight the role of nanomaterials. The second and most novel part of this review concentrates on the remarkable applicability of breath analysis in differential diagnosis, phenotyping, and the staging of several disease-types, which are currently amongst the most pressing challenges in the field.
Methods for monitoring cancer cell pyroptosis

Pyroptosis is a form of proinflammatory cell death that depends on the gasdermin family of proteins. The main features of pyroptosis are altered membrane permeability, cell swelling, membrane rupture, and the ability to mobilize a strong immune response. The relationship between pyroptosis and cancer has become a popular topic in immunological research. Multiple strategies for inducing pyroptosis in cancer cells have been developed for cancer therapy, including chemotherapy, small molecule drugs, and nanomedicines. In this review, we systematically discuss recent advances in research on the mechanisms of pyroptosis, and compare pyroptosis with apoptosis and necroptosis from several aspects. The development of various experimental systems has accompanied rapid progress in this field, but little consensus on monitoring pyroptosis is currently available. We focus on techniques commonly used to monitor pyroptosis, and describe future techniques that may be used to increase our knowledge in this field. Overall, the advancement of pyroptosis detection methods will help researchers to better investigate the relationships between pyroptosis and various cancers, and should provide insights into the use of these promising tools for cancer treatments.
Estimation of apple firmness using hyperspectral spectral indices

Abstract Non-destructive and rapid methods for estimating apple firmness are helpful to determine harvesting dates. However, few studies have used an approach of spectral indices for monitoring apple firmness from ground-based handheld hyperspectral data. Therefore, this study analyzed the performance of spectral indices in determining apple firmness based on the spectra of unpeeled apples. The reflectance spectra of apple samples were acquired at wavelength 350–2500 nm. Ten apple varieties were collected from orchards located in seven provinces of China. A two-band combination method (normalized, ratio, and difference type) was used to identify the effective spectral indices. Results showed that the newly developed two-band normalized difference spectral indices (R 840 − R 841)/(R 840 + R 841) (Rλ is the reflectance value at wavelength λ) was recommended as the optimal index for monitoring apple firmness, generated the coefficients of determination, root mean square error and residual prediction deviation values between the measured and predicted values of 0.6721, 0.886 kg/cm2, and 1.7, respectively. This study indicated that spectral indices offer low-cost and portable detection of apple fruit firmness.
Overview of the MOSAiC expedition—Atmosphere

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.
Unlocking the Memory Component of Alzheimer’s Disease: Biological Processes and Pathways across Brain Regions

Alzheimer’s Disease (AD) is a neurodegenerative disorder characterized by a progressive loss of memory and a general cognitive decline leading to dementia. AD is characterized by changes in the behavior of the genome and can be traced across multiple brain regions and cell types. It is mainly associated with β-amyloid deposits and tau protein misfolding, leading to neurofibrillary tangles. In recent years, however, research has shown that there is a high complexity of mechanisms involved in AD neurophysiology and functional decline enabling its diverse presentation and allowing more questions to arise. In this study, we present a computational approach to facilitate brain region-specific analysis of genes and biological processes involved in the memory process in AD. Utilizing current genetic knowledge we provide a gene set of 265 memory-associated genes in AD, combinations of which can be found co-expressed in 11 different brain regions along with their functional role. The identified genes participate in a spectrum of biological processes ranging from structural and neuronal communication to epigenetic alterations and immune system responses. These findings provide new insights into the molecular background of AD and can be used to bridge the genotype–phenotype gap and allow for new therapeutic hypotheses.
Personalized Nutritional Intervention to Improve Mediterranean Diet Adherence in Female Patients with Multiple Sclerosis: A Randomized Controlled Study

Background: Multiple sclerosis (MS) is a chronic immune-mediated central nervous system disorder that affects females twice as often as males. MS patients show increased susceptibility to obesity and related cardiometabolic disorders, while diet may influence disease course. In the present randomized controlled study, we aimed to increase Mediterranean Diet (MedDiet) adherence in MS women and improve their nutritional status. Methods: Adult women with relapsing-remitting MS (n = 40) were randomly allocated to intervention (n = 20) or control group (n = 20). Individual dietary plans based on MedDiet together with nutritional consultation were provided to the intervention group. Controls received general lifestyle advice according to “National Dietary Guidelines”. Medical history, anthropometry, dietary records, and blood withdrawal were performed at baseline and at 3 months. Results: Compared to controls, the intervention group demonstrated greater MedDiet adherence (p < 0.001), which was negatively associated with cholesterol intake levels (p < 0.05). At 3 months, women following MedDiet had ameliorated body weight and body composition compared to baseline (p < 0.001). Serum 1,25(OH)2D was significantly higher in both study groups at 3 months (p < 0.001), but in the intervention group, the mean increment was twofold compared to controls (p < 0.001). Conclusion: Personalized nutritional intervention in MS patients may improve MedDiet adherence and nutritional status towards cardioprotective health outcomes.
Multiparametric MRI and Machine Learning Based Radiomic Models for Preoperative Prediction of Multiple Biological Characteristics in Prostate Cancer

Objectives This study aims to develop and evaluate multiparametric MRI (MP-MRI)-based radiomic models as a noninvasive diagnostic method to predict several biological characteristics of prostate cancer. Methods A total of 252 patients were retrospectively included who underwent radical prostatectomy and MP-MRI examinations. The prediction characteristics of this study were as follows: Ki67, S100, extracapsular extension (ECE), perineural invasion (PNI), and surgical margin (SM). Patients were divided into training cohorts and validation cohorts in the ratio of 4:1 for each group. After lesion segmentation manually, radiomic features were extracted from MP-MRI images and some clinical factors were also included. Max relevance min redundancy (mRMR) and recursive feature elimination (RFE) based on random forest (RF) were adopted to select features. Six classifiers were included (SVM, KNN, RF, decision tree, logistic regression, XGBOOST) to find the best diagnostic performance among them. The diagnostic efficiency of the construction models was evaluated by ROC curves and quantified by AUC. Results RF performed best among the six classifiers for the four groups according to AUC values (Ki67 = 0.87, S100 = 0.80, ECE = 0.85, PNI = 0.82). The performance of SVM was relatively the best for SM (AUC = 0.77). The number and importance of DCE features ranked first in the models of each group. The combined models of MP-MRI and clinical characteristics showed no significant difference compared with MP-MRI models according to Delong’s tests. Conclusions Radiomics models based on MP-MRI have the potential to predict biological characteristics and are expected to be a noninvasive method to evaluate the risk stratification of prostate cancer.
Lack of Fetal Protection against Bovine Viral Diarrhea Virus in a Vaccinated Heifer

The aim of the report was to present the circulation of BVDV (bovine viral diarrhea virus) in the cattle population and determine the cause of the failure of vaccination failure leading to the birth of the PI (persistently infected) calf. The case study was carried out at the BVDV-free animal breeding center and cattle farm, where the vaccination program against BVDV was implemented in 2012, and each newly introduced animal was serologically and virologically tested for BVDV. In this case, a blood sample was taken from a 9-month-old breeding bull. Positive RT-PCR and negative ELISA serology results were obtained. The tests were repeated at 2-week intervals, and the results confirmed the presence of the virus and the absence of specific antibodies, i.e., persistent infection. Additionally, sequencing and phylogenetic analysis were performed, and the BVDV-1d subgenotype was detected. The results of this study showed that pregnant heifers and cows that are vaccinated multiple times with the killed vaccine containing BVDV-1a may not be fully protected against infection with other subgenotypes of BVDV, including their fetuses, which can become PI calves.
Developmental Transcriptome Profiling of the Tibial Reveals the Underlying Molecular Basis for Why Newly Hatched Quails Can Walk While Newly Hatched Pigeons Cannot

Birds can be classified into altricial and precocial species. The hatchlings of altricial birds cannot stand, whereas precocial birds can walk and run soon after hatching. It might be owing to the development of the hindlimb bones in the embryo stage, but the molecular regulatory basis underlying the divergence is unclear. To address this issue, we chose the altricial pigeon and the precocial Japanese quail as model animals. The data of tibia weight rate, embryonic skeletal staining, and tibia tissues paraffin section during the embryonic stage showed that the Japanese quail and pigeon have similar skeletal development patterns, but the former had a faster calcification rate. We utilized the comparative transcriptome approach to screen the genes and pathways related to this heterochronism. We separately analyzed the gene expression of tibia tissues of quail and pigeon at two consecutive time points from an inability to stand to be able to stand. There were 2910 differentially expressed genes (DEGs) of quail, and 1635 DEGs of pigeon, respectively. A total of 409 DEGs in common in the quail and pigeon. On the other hand, we compared the gene expression profiles of pigeons and quails at four time points, and screened out eight pairs of expression profiles with similar expression trends but delayed expression in pigeons. By screening the common genes in each pair of expression profiles, we obtained a gene set consisting of 152 genes. A total of 79 genes were shared by the 409 DEGs and the 152 genes. Gene Ontology analysis of these common genes showed that 21 genes including the COL gene family (COL11A1, COL9A3, COL9A1), IHH, MSX2, SFRP1, ATP6V1B1, SRGN, CTHRC1, NOG, and GDF5 involved in the process of endochondral ossification. These genes were the candidate genes for the difference of tibial development between pigeon and quail. This is the first known study on the embryo skeletal staining in pigeon. It provides some new insights for studying skeletal development mechanisms and locomotor ability of altricial and precocial bird species.
A New Framework for Evaluation Sustainable Green Service Supply Chain Management in Oil and Gas Industries

Oil and gas industries are among the industries involved in the international service supply chain, which include domestic and international transportation, import and export, and technology information. By creating utility and satisfaction from environmental perspective throughout the service supply chain, the supply chain managers of leading companies have recently tried to use green logistics and improve environmental performance in the entire of their service supply chain as a valuable resource for sustainable competitive advantage. Thus, the main reasons for investment in creating a sustainable green service supply chain includes management of unwanted environmental, social, and economic risks and creating sustainable services by increasing revenue and enhancing cooperation. Given the purpose of this article which is to provide a framework to assess sustainable green SSCM dimensions. Organizational factors, environmental factors were obtained. In this study, structural equation modelling (SEM) was used to test the hypotheses.
Design, Modeling and Validation of a Tendon-Driven Soft Continuum Robot for Planar Motion Based on Variable Stiffness Structures

Robotic structures based on variable stiffness enable high-performance and flexible motion systems that are inherently safe and thus allow safe Human-Robot Collaboration. This letter presents the design of a robotic structure based on variable stiffness. A robotic manipulator is developed using three variable stiff segments based on particle jamming with a backbone architecture and two tendons for an underactuated motion control of the whole structure. By switching the structural stiffness, the manipulator is able to perform complex planar motion with only one pair of tendons, reducing the number of actuators required. A kinematic modeling approach for the calculation of the forward kinematics of this soft continuum structure is presented, and the validation on the real system is explained. The kinematic simulation is performed with a multibody simulation model (MBS) using rigid body elements in combination with rotational springs. The validation of the model is carried out with visual measurements of the real system using defined target shapes. Simulation and experimental results are discussed and compared also with a common constant curvature model. The developed MBS-model demonstrates a promising modeling approach with a position error lower 3% for the calculation of the presented manipulator under gravity.
Stress measurement and correction with contour method for additively manufactured round-rod specimen

The contour method (CM) was applied to obtain residual stress field in the round-rod titanium alloy specimen fabricated by laser power bed fusion additive manufacturing. In order to improve the accuracy of CM, two methods were investigated. One employed a steel block glued to the specimen to shift the surface stress uncertainties. The other is to reconstruct the stress based on the eigenstrain inverse analysis method. Results show that both methods can improve the measurement accuracy on the surface layer stress to a certain extent. Attaching steel block would affect the cutting process and cause new test errors. The stress reconstruction method requires surface stress results and eigenstrain basis function with an order of at least 10.
Dynamic Refresh Strategy for Crawler in Search Engine

As for a search engine,keeping up with the evolving Web is necessary.We concern about modeling on an effective Web page collecting policy and propose an adaptive refresh strategy based on the relevance,which is used to adjust the process.On one hand,we think the refresh behavior follows the properties of the Poisson process and analyze the strategy on how to crawl the Web effectively.Further,the relevance is on the basis of the affiliation detecting and the contents analysis.It is used to adjust the process.This makes the process more targeted.The experimental results validate the feasibility of the approach.
Biogeochemical controls on ammonium accumulation in the surface layer of the Southern Ocean

Abstract. The production and removal of ammonium (NH4+) are essential upper-ocean nitrogen cycle pathways, yet in the Southern Ocean where NH4+ has been observed to accumulate in surface waters, its mixed-layer cycling remains poorly understood. For surface seawater samples collected between Cape Town and the Marginal Ice Zone in winter 2017, we found that NH4+ concentrations were 5-fold higher than is typical for summer and lower north than south of the Subantarctic Front (0.01–0.26 µM versus 0.19–0.70 µM). Our observations confirm that NH4+ accumulates in the Southern Ocean's winter mixed layer, particularly in polar waters. NH4+ assimilation rates were highest near the Polar Front (12.9 ± 0.4 nM d−1) and in the Subantarctic Zone (10.0 ± 1.5 nM d−1), decreasing towards the Marginal Ice Zone (3.0 ± 0.8 nM d−1) despite the high ambient NH4+ concentrations in these southernmost waters, likely due to the low temperatures and limited light availability. By contrast, rates of NH4+ oxidation were higher south than north of the Polar Front (16.0 ± 0.8 versus 11.1 ± 0.5 nM d−1), perhaps due to the lower-light and higher-iron conditions characteristic of polar waters. NH4+ concentrations were also measured along five transects of the Southern Ocean (Subtropical Zone to Marginal Ice Zone) spanning the 2018/19 annual cycle. These measurements reveal that mixed-layer NH4+ accumulation south of the Subantarctic Front derives from sustained heterotrophic NH4+ production in late summer through winter that, in net, outpaces NH4+ removal by temperature-, light-, and iron-limited microorganisms. Our observations thus imply that the Southern Ocean becomes a biological source of CO2 to the atmosphere in autumn and winter not only because nitrate drawdown is weak but also because the ambient conditions favour net heterotrophy and NH4+ accumulation.
Barreras para la atención de las conductas suicidas en Ciudad de México: experiencias del personal de salud en el primer nivel de atención

Objetivo: Identificar las barreras que existen para la atención de las conductas suicidas, desde la perspectiva de las/los profesionales de la salud mental del primer nivel de atención de la Ciudad de México. Metodología: Estudio cualitativo exploratorio, basado en 35 entrevistas semiestructuradas, dirigidas a personal de salud de dos unidades de salud mental de referencia nacional. El análisis de la información se hizo mediante el Framework Analysis. Resultados: Las/los participantes consideraron que las conductas suicidas no han sido definidas como una prioridad dentro de los trastornos de salud mental. La ausencia de políticas públicas, la sobrecarga de trabajo, la falta de seguimiento a las/los pacientes, entre otras, fueron identificadas como barreras para una atención adecuada y oportuna. Conclusiones: Los programas de prevención de las conductas suicidas deben tomar en cuenta el contexto socioeconómico de la población y las características de los servicios de salud, así como las necesidades de las personas prestadoras de servicios de salud. Se requiere ampliar el entrenamiento profesional y mejorar el sistema de referencia y contrarreferencia entre los distintos niveles de atención.