Miracle-dz/UniFAR-FTUs huggingface dataset:
Considerations for the Analysis of Small Extracellular Vesicles in Physical Exercise

Physical exercise induces acute physiological changes leading to enhanced tissue cross-talk and a liberation of extracellular vesicles (EVs) into the circulation. EVs are cell-derived membranous entities which carry bioactive material, such as proteins and RNA species, and are important mediators of cell-cell-communication. Different types of physical exercise interventions trigger the release of diverse EV subpopulations, which are hypothesized to be involved in physiological adaptation processes leading to health benefits and longevity. Large EVs (“microvesicles” and “microparticles”) are studied frequently in the context of physical exercise using straight forward flow cytometry approaches. However, the analysis of small EVs (sEVs) including exosomes is hampered by the complex composition of blood, confounding the methodology of EV isolation and characterization. This mini review presents a concise overview of the current state of research on sEVs released upon physical exercise (ExerVs), highlighting the technical limits of ExerV analysis. The purity of EV preparations is highly influenced by the co-isolation of non-EV structures in the size range or density of EVs, such as lipoproteins and protein aggregates. Technical constraints associated with EV purification challenge the quantification of distinct ExerV populations, the identification of their cargo, and the investigation of their biological functions. Here, we offer recommendations for the isolation and characterization of ExerVs to minimize the effects of these drawbacks. Technological advances in the ExerV research field will improve understanding of the inter-cellular cross-talk induced by physical exercise leading to health benefits.
New neural fuzzy-based machine learning ensemble for enhancing the prediction accuracy of flood susceptibility mapping

ABSTRACT High-accuracy flood susceptibility maps play a crucial role in flood vulnerability assessment and risk mitigation. This study assesses the potential application of three new ensemble models, which are integrations of the adaptive neuro-fuzzy inference system (ANFIS), analytic hierarchy process (AHP), certainty factor (CF) and weight of evidence (WoE). The experimental area is the Trotuș River basin in Romania. The database for the present research consisted of 12 flood-related factors and 172 flood locations. The quality of the models was evaluated using root mean square error (RMSE) values and the ROC curve (AUC). The results showed that the ANFIS-CF model and the ANFIS-WOE model have a high prediction capacity (accuracy > 91.6%). Therefore, we concluded that ANFIS-CF and ANFIS-WoE are two new tools that should be considered for future studies related to flood susceptibility modelling.
In situ Electron Microscopy of Complex Biological and Nanoscale Systems: Challenges and Opportunities

In situ imaging for direct visualization is important for physical and biological sciences. Research endeavors into elucidating dynamic biological and nanoscale phenomena frequently necessitate in situ and time-resolved imaging. In situ liquid cell electron microscopy (LC-EM) can overcome certain limitations of conventional electron microscopies and offer great promise. This review aims to examine the status-quo and practical challenges of in situ LC-EM and its applications, and to offer insights into a novel correlative technique termed microfluidic liquid cell electron microscopy. We conclude by suggesting a few research ideas adopting microfluidic LC-EM for in situ imaging of biological and nanoscale systems.
The Current Process for the Recycling of Spent Lithium Ion Batteries

With the development of electric vehicles involving lithium ion batteries as energy storage devices, the demand for lithium ion batteries in the whole industry is increasing, which is bound to lead to a large number of lithium ion batteries in the problem of waste, recycling and reuse. If not handled properly, it will certainly have a negative impact on the environment and resources. Current commercial lithium ion batteries mainly contain transition metal oxides or phosphates, aluminum, copper, graphite, organic electrolytes containing harmful lithium salts, and other chemicals. Therefore, the recycling and reuse of spent lithium ion batteries has been paid more and more attention by many researchers. However, due to the high energy density, high safety and low price of lithium ion batteries have great differences and diversity, the recycling of waste lithium ion batteries has great difficulties. This paper reviews the latest development of the recovery technology of waste lithium ion batteries, including the development of recovery process and products. In addition, the challenges and future economic and application prospects are described.
Application of Predictive Inactivation Models to Evaluate Survival of Staphylococcus aureus in Fresh-Cut Apples Treated with Different Plant Hydrosols

In this study, inhibitory effects of bayleaf, rosemary, sage, and thyme hydrosols on the growth of Staphylococcus aureus inoculated on fresh-cut apples were investigated using several sigmoidal models (modified Gompertz, logistic, Richards, Stannard, and Whiting and Buchanan). In addition, these models were compared to describe the inactivation of S. aureus by fitting the experimental data using nonlinear models and various statistical parameters (the mean percentage error, the mean bias error, the root mean square error, the modeling efficiency, and chi-square parameters) as well as determination of coefficient (R2). The modified Gompertz, logistic, and Stannard models exhibited better fits than Richards and Whiting and Buchanan models regarding these statistical parameters. Rosemary and thyme hydrosols were found to be the most efficient sanitizers in reducing the S. aureus numbers. Results demonstrate that predictive models could be utilized for describing the inactivation or survival of S. aureus on fresh-cut apple with the effects of the treatments with plant hydrosols.
A Graphical Programming Language and Its Supporting Tool for Insect Intelligent Building

The emerging Insect Intelligent Building (I2B) platform is pioneering a new realm in intelligent buildings. I2B has a distributed and decentralized network structure with intelligent nodes, and the key enabler is an application (APP) that functions to process information from intelligent nodes and accomplish complex control tasks in a decentralized network. To develop APPs for I2B, a proper programming language is the foremost goal; however, existing programming languages cannot be applied directly due to I2B's unique structure and distinction of application domains. This paper aims to provide language support for a direct and friendly development of I2B APPs. We propose a graphical programming language that adapts to the operating characteristics of I2B and users' habits of buildings. Specifically, we first analyze the domain characteristics of the proposed language and present a general programming language model illustrated with a motivating example. Then, we investigate the detailed design, definition, and usage of graphic elements. Additionally, we implement a prototype support tool for the graphical programming language to develop I2B APPs. Moreover, we use the application example of a building's constant pressure control for evaluating the effectiveness of our work.
Ice Mass Loss in the Central Andes of Argentina Between 2000 and 2018 Derived From a New Glacier Inventory and Satellite Stereo-Imagery

Based on the recently released National Glacier Inventory (NGI), we analyzed the characteristics and the mass balance rates of ice masses in the Argentinean Central Andes (ca. 30°–37° S). The NGI provides unprecedented information on area, number and distribution of different ice masses, including debris-covered glaciers and rock glaciers. In the Central Andes, a number of 8,076 ice masses were identified covering a total area of 1767 km2. For the period 2000–2018, a general lowering of the ice surface was observed with a region-wide mass balance rate of −0.18 ± 0.19 m w.e. yr−1. Clear differences depending on the debris coverage of the different ice masses were identified, with mass balance rates ranging from −0.36 ± 0.19 m w.e. yr−1 for partly debris-covered glaciers to −0.02 ± 0.19 m w.e. yr−1 for rock glaciers. Considering different sub-periods, the region-wide mass balance rate was slightly positive (+0.12 ± 0.23 m w. e. yr−1) from 2000 to 2009 and negative (−0.21 ± 0.30 m w.e. yr−1) from 2009 to 2018. A comparison with the Randolph Glacier Inventory (RGI version 6.0) indicates that the NGI provides more detailed information regarding different type of ice masses whereas region-wide mass balance rates show limited sensitivity to the choice of the inventory. The inclusion of rock glaciers and “debris-covered ice with rock glacier” in the NGI causes mass balance rates to be slightly less negative than when using the RGI. Since the Central Andes are experiencing an unprecedented decade-long drought, our study provides crucial information to estimate current and future hydrological contribution of the different type of ice masses to river discharge in the arid subtropical Andes.
No Association Between G1246A Polymorphism in HCRTR2 Gene and Risk of Cluster Headache: Evidence From an Updated Meta-Analysis of Observational Studies

Background: The hypocretin receptor 2 (HCRTR2) gene may play a pathological role in cluster headache (CH). However, the conclusions of published reports on the relationship between the G1246A polymorphism (rs2653349) in the HCRTR2 gene and risk of CH remain controversial. This purpose of this article is to comprehensively study the current evidence and assess the association between G1246A polymorphism (rs2653349) in the HCRTR2 gene and risk of CH. Materials and Methods: Four electronic databases—ISI Web of Science, CNKI, PubMed, and EMBASE—were comprehensively searched on August 2020 to find and pinpoint all observational articles related to this study. The association between G1246A polymorphism in the HCRTR2 gene and risk of CH under five different genetic models was evaluated based on the summary odds ratio and corresponding 95 confidence interval (95% CI). Methodological quality was assessed based on the Newcastle–Ottawa Scale (NOS). To assist the analysis, RevMan 5.3 software was used to perform subgroup and sensitivity analyses. Egger's and Begg's tests were then conducted to evaluate and assess publication bias. Finally, a meta-regression was carried out by residual (restricted) maximum likelihood (REML). Results: Eight observation studies containing 3,161 healthy controls and 1,964 patients with CH were identified and to be used for the meta-analysis. With methodological quality NOS assessment, the incorporated studies showed an average score of 6.4 stars. The pooled data didn't support the association between G1246A polymorphism in the HCRTR2 gene and CH vulnerability in the overall population (OR: 0.85, 95% CI 0.69, 1.03; p = 0.10). Subgroup analysis by ethnicity showed no significant association between G1246A and CH in either Caucasians (OR: 0.89, 95% CI 0.77, 1.01; p = 0.08) or Asians (OR: 1.65, 95% CI 0.80, 3.41; p = 0.18). The robustness of the conclusion was tested and confirmed with the leave-one-out sensitivity analysis. Meta-regression analysis showed that chronological order of publication appeared to be significantly associated with the heterogeneity (t = 2.47, p = 0.039; residual I2 = 0%, adjusted R2 = 100%). Conclusion: Our present study showed that the G1246A polymorphism in the HCRTR2 gene did not appear to be an accomplice and associated with CH predisposition among either the Asian or Caucasian population.
Interaction Between Smoking and Internet Gaming Disorder on Spontaneous Brain Activity

Converging lines of evidence indicates that smoking and internet gaming disorder (IGD) affect spontaneous brain activity, respectively. However, little is known about whether these two factors work together on the human brain. In this study, we investigated the interaction between smoking and IGD on local spontaneous brain activity using amplitude of low-frequency fluctuation (ALFF) based on resting-state fMRI (rs-fMRI). Forty-six cigarette smokers, 38 IGD individuals, 34 participants with both IGD and cigarette smoking (IGD-Smoking), and 60 healthy individuals involved in the study. Voxel-wise analysis of covariance of ALFF revealed that there were significant interactions between IGD by smoking in the right medial pre-frontal cortex (MPFC)/ventral striatum, bilateral cerebellar, and visual-related regions as well as the left temporal gyrus. In the right MPFC/ventral striatum and left temporal gyrus, ALFF in smoking group was significantly higher than healthy group while there were no significant ALFF differences between IGD-Smoking group and IGD group. While in the bilateral cerebellar and visual-related regions, ALFF in the smoking group was significantly lower than healthy group while ALFF in IGD-Smoking group did not show significant difference with IGD group. In addition, in the smoking group, ALFF of the right MPFC/ventral striatum was associated positively with anxiety and depression scores while the ALFF value in the smoking group had a trend toward negative correlation with SDS scores in the bilateral cerebellar and visual-related regions. The ALFF value in the smoking group was associated positively with anxiety score in the left temporal gyrus. These findings indicate that smoking and IGD interacted with each other in the human brain. Our results, in terms of spontaneous brain activity, may imply the fact that IGD people are more tended to get smoking. Moreover, it is possible to predict that smokers may be more easily to get internet addiction than healthy people.
Identify and Validate the Transcriptomic, Functional Network, and Predictive Validity of FBXL19-AS1 in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common neoplastic diseases worldwide. Available biomarkers are not sensitive enough for the diagnosis of HCC, hence seeking new biomarkers of HCC is urgent and challenging. The purpose of this study was to investigate the role of F-box and leucine-rich repeat protein 19-antisense RNA 1 (FBXL19-AS1) through a functional network and inquire into its diagnostic and prognostic value in HCC. A comprehensive strategy of genomic data mining, bioinformatics and experimental validation was used to evaluate the clinical value of FBXL19-AS1 in the diagnosis and prognosis of HCC and to identify the pathways in which FBXL19-AS1 might be involved. FBXL19-AS1 was up-regulated in HCC tissues, and its high expression was associated with TNM stage and poor prognosis of HCC patients. The combination of FBXL19-AS1 and alpha-fetoprotein (AFP) in plasma could prominently improve the diagnostic validity for HCC. FBXL19-AS1 might stabilize FBXL19 to reduce the amount of macrophage M1, and then promote the occurrence and development of HCC. Meanwhile, FBXL19-AS1 might participate in regulating HCC related pathways through FBXL19-AS1-miRNA-mRNA network. Our findings indicated that FBXL19-AS1 not only serves as a potential biomarker for HCC diagnosis and prognosis, but also might be functionally carcinogenic.
Prevalence and Risk Factors for COPD at High Altitude: A Large Cross-Sectional Survey of Subjects Living Between 2,100–4,700 m Above Sea Level

Aim of Study: Four hundred million people live at high altitude worldwide. Prevalence and risk factors for COPD in these populations are poorly documented. We examined the prevalence and risk factors for COPD in residents living at an altitude of 2,100–4,700 m. Methods: We performed a cross-sectional survey in Xinjiang and Tibet autonomous region. A multistage stratified sampling procedure was used to select a representative population aged 15 years or older from eight high altitude regions. All participants underwent pre- and post-bronchodilator measurement of forced expiratory volumes. COPD was diagnosed according to 2019 Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria. Results: Between June, 2015 and August 2016, 4,967 subjects were included. Median age was 38.0 years (range: 15–91 years; inter-quartile range: 28–49 years); 51.4% participants were female. Overall prevalence of spirometry-defined COPD was 8.2% (95% CI 7.4–8.9%): 9.3% in male (95% CI 8.2–10.4%), and 7.1% in female (95% CI 6.1–8.2%). By multivariable logistic regression analysis, COPD was significantly associated with being aged ≥40 years (odds ratio: 2.25 [95% CI 1.72–2.95], P < 0.0001), exposure to household air pollution (OR: 1.34 [95% CI 1.01–1.79], P = 0.043), and a history of tuberculosis (OR: 1.79 [95% CI 1.23–2.61], P = 0.030), while living at a higher altitude (OR: 0.45 [95% CI 0.33–0.61], P < 0.0001) and having a higher educational level (OR: 0.64 [95% CI 0.43–0.95], P = 0.025) were associated with a lower prevalence of COPD. Conclusions: Our results show that the spirometry-defined COPD is a considerable health problem for residents living at high altitudes and COPD prevalence was inversely correlated with altitude. Preventing exposure to household air pollution and reducing the incidence of tuberculosis should be public health priorities for high altitude residents.
A Packet Scheduling Method Based on Dynamic Adjustment of Service Priority for Electric Power Wireless Communication Network

With the development of the energy Internet, power communication services are heterogeneous, and different power communication services have different business priorities. The power communication services with different priorities have different requirements for network bandwidth and real-time performance. For traditional unified service, a scheduling method cannot meet these service requirements at the same time, and electric power communication network cannot guarantee the quality of service. Therefore, how to make full use of the time-varying characteristics of communication resources to meet the business needs of different priorities and achieve the goals of high resource utilization and transmission quality has become one of the urgent problems in the power communication network. For this reason, in order to adapt to the real-time congestion of the network, we have designed a packet scheduling method based on the dynamic adjustment of service priority, which dynamically adjusts the priority of the power service on the node; in addition, an evaluation method for the trust value of wireless forwarding nodes is introduced to improve the security of data transmission; and finally, we valuate the channel quality to establish a reasonable and efficient packet scheduling mechanism for services of different priorities. Simulation results show that this method improves the communication performance of high-priority services and improves the spectrum resource utilization of the entire system.
Non-Alcoholic Steatohepatitis: A Review of Its Mechanism, Models and Medical Treatments

Non-alcoholic steatohepatitis (NASH) develops from non-alcoholic fatty liver disease (NAFLD). Currently, around 25% of the population is estimated to have NAFLD, and 25% of NAFLD patients are estimated to have NASH. NASH is typically characterized by liver steatosis inflammation, and fibrosis driven by metabolic disruptions such as obesity, diabetes, and dyslipidemia. NASH patients with significant fibrosis have increased risk of developing cirrhosis and liver failure. Currently, NASH is the second leading cause for liver transplant in the United States. More importantly, the risk of developing hepatocellular carcinoma from NASH has also been highlighted in recent studies. Patients may have NAFLD for years before progressing into NASH. Although the pathogenesis of NASH is not completely understood, the current “multiple-hits” hypothesis suggests that in addition to fat accumulation, elevated oxidative and ER stress may also drive liver inflammation and fibrosis. The development of clinically relevant animal models and pharmacological treatments for NASH have been hampered by the limited understanding of the disease mechanism and a lack of sensitive, non-invasive diagnostic tools. Currently, most pre-clinical animal models are divided into three main groups which includes: genetic models, diet-induced, and toxin + diet-induced animal models. Although dietary models mimic the natural course of NASH in humans, the models often only induce mild liver injury. Many genetic and toxin + diet-induced models rapidly induce the development of metabolic disruption and serious liver injury, but not without their own shortcomings. This review provides an overview of the “multiple-hits” hypothesis and an evaluation of the currently existing animal models of NASH. This review also provides an update on the available interventions for managing NASH as well as pharmacological agents that are currently undergoing clinical trials for the treatment of NASH.
Effects of Computerized Updating and Inhibition Training in Older Adults: The ACTOP Three-Arm Randomized Double-Blind Controlled Trial

Background: Working memory (WM) capacity declines with advancing age, which impacts the ability to carry out complex cognitive activities in everyday life. Updating and inhibition processes have been identified as some of the most critical attentional control processes of WM and are linked to age-related WM decline. The general aim of the Attentional Control Training in Older People (ACTOP) study was to perform a side-by-side comparison of updating and inhibition training to examine their respective efficacy and transfer in cognitively healthy older adults. Method: The study was a three-arm, double-blind, randomized controlled trial registered with the US National Institutes of Health clinical trials registry. Ninety older adults were randomly assigned to 12 half-hour sessions of updating (N-back type exercises), inhibition (Stroop-like exercises) computerized training or active control (general knowledge quiz game). A group of thirty younger adults completed all proximal and WM transfer tasks without training to assess age-related deficits prior to training and whether training reduces these deficits. Results: Piecewise mixed models show quick improvement of performance during training for both updating and inhibition training. During updating training, the progression was more pronounced for the most difficult (3-back) than for the least (1-back) difficult level until the ninth session. Updating and inhibition training groups improved performance on all proximal and WM transfer measures but these improvements did not differ from the active control group. Younger adults outperformed older ones on all transfer tasks prior to training. However, this was no longer the case following training for two transfer tasks regardless of the training group. Conclusion: The overall results from this study suggest that attentional control training is effective in improving updating and inhibition performance on training tasks. The optimal dose to achieve efficacy is ~9 half-hour sessions and the dose effect was related to difficulty level for updating training. Despite an overall improvement of older adults on all transfer tasks, neither updating nor inhibition training provided additional improvements in comparison with the active control condition. This suggests that the efficacy of process-based training does not directly affect transfer tasks. Clinical Trial Registration: www.ClinicalTrials. gov, identifier: NCT03532113