Miracle-dz/UniFAR-FTUs huggingface dataset:
IL-1β Implications in Type 1 Diabetes Mellitus Progression: Systematic Review and Meta-Analysis

During Type 1 Diabetes Mellitus (T1DM) progression, there is chronic and low-grade inflammation that could be related to the evolution of the disease. We carried out a systematic review and meta-analysis to evaluate whether peripheral levels of pro-inflammatory markers such as interleukin-1 beta (IL-1β) is significantly different among patients with or without T1DM, in gender, management of the T1DM, detection in several biological fluids, study design, age range, and glycated hemoglobin. We searched PubMed, Embase, Web of Science, and Scopus databases, and 26 relevant studies (2186 with T1DM, 2047 controls) were included. We evaluated the studies’ quality using the Newcastle–Ottawa scale. Meta-analyses were conducted, and heterogeneity and publication bias were examined. Compared with controls, IL-1β determined by immunoassays (pooled standardized mean difference (SMD): 2.45, 95% CI = 1.73 to 3.17; p < 0.001) was significantly elevated in T1DM. The compared IL-1β levels in patients <18 years (SMD = 2.81, 95% CI = 1.88–3.74) was significantly elevated. The hemoglobin-glycated (Hbg) levels in patients <18 years were compared (Hbg > 7: SMD = 5.43, 95% CI = 3.31–7.56; p = 0.001). Compared with the study design, IL-1β evaluated by ELISA (pooled SMD = 3.29, 95% CI = 2.27 to 4.30, p < 0.001) was significantly elevated in T1DM patients. IL-1β remained significantly higher in patients with a worse management of T1DM and in the early stage of T1DM. IL-1β levels determine the inflammatory environment during T1DM.
Spatial Distribution of Polyphenolic Compounds in Corn Grains (Zea mays L. var. Pioneer) Studied by Laser Confocal Microscopy and High-Resolution Mass Spectrometry

Desirable changes in the biochemical composition of food plants is a key outcome of breeding strategies. The subsequent localization of nutritional phytochemicals in plant tissues gives important information regarding the extent of their synthesis across a tissue. We performed a detailed metabolomic analysis of phytochemical substances of grains from Zea mays L. (var. Pioneer) by tandem mass spectrometry and localization by confocal microscopy. We found that anthocyanins are located mainly in the aleurone layer of the grain. High-performance liquid chromatography in combination with ion trap tandem mass spectrometry revealed the presence of 56 compounds, including 30 polyphenols. This method allows for effective and rapid analysis of anthocyanins by plotting their distribution in seeds and grains of different plants. This approach will permit a more efficient screening of phenotypic varieties during food plant breeding.
Trans-Biliary Gastric Outlet Recanalization and Stenting: A Case Report

Gastric ischemia is a condition of hypo-perfusion associated with hypotension, vasculitis, and thromboembolism. We report a case of a gastric outflow obstruction due to sizeable visceral artery thrombo-embolism leading to the ischemic conclusion, the frailty, multiple comorbidities deeming general anesthesia (GA) risky, and the patient’s decision not to have an open surgery under GA. Invasive procedures in patients with similar profiles like our patient are usually not risk-free, this leads the intervention radiology team to believe a minimally invasive procedure while avoiding GA might be optimal. A 63-year-old female with multiple comorbidities came eight weeks after significant surgery complaining of severe acute epigastric pain, abdominal distention and rigidity, and persistent vomiting. Further investigations showed obstruction in the gastric antrum and pyloric canal. Three separate endoscopic attempts to find and cross the stricture failed. Firstly, gastrostomy access was established, but due to the stomach being massively distended, passing a guidewire through the pylorus failed despite using multiple hydrophilic wires and pre-shaped catheters, this is due to the collapsed pylorus. Subsequently, two attempts under ultrasound guidance to puncture the duodenal bulb and pass a wire and catheter through the antrum stricture were unsuccessful, and another attempt was considered of high risk. An alternative approach through the gallbladder was established, and cholangiography was performed to delineate the anatomy. Then an approach through the right hepatic duct and ampulla of Vater was successfully performed. The attempted passage through the stricture was successful. The dilation was successful, and the patient tolerated both fluid and solids orally. Due to having such a frail patient, interventions of minimal invasiveness and favorable outcome are welcomed. This case report suggests that this technique showed satisfactory results and achieved the goal to improve the overall quality of life where the patient had a good oral intake with no post-operation complications.
Optimization Prediction of Big Five Personality in Twitter Users

Various kinds of information can be acquired from social media platforms; one of them is on Twitter. User biographical information and tweets are the essential assets for research that can describe the Big Five Personality, including openness, conscientiousness, extraversion, agreeableness, and neuroticism. Several previous studies have tried the prediction of Big Five Personality. However, the authors found problems in how to optimize the work of the personality prediction system. So, in this study, Big Five Personality predictions were carried out on users of Twitter and improved the performance of the personality prediction system. We implement optimization techniques such as sampling, feature selection, and hyperparameter tuning to enhance the performance. This study also applies linguistic feature extraction, such as LIWC and TF-IDF. By using 287 Twitter users that have permitted their data to be crawled acquired from an online survey using Big Five Inventory (BFI), and applying all optimization techniques, the average accuracy result is 84.22% which is a 74.44% gain over the specified baseline.
Antibacterial Activities and Synergistic Interaction of Citrus Essential Oils and Limonene with Gentamicin against Clinically Isolated Methicillin-Resistant Staphylococcus aureus

Citrus reticulata Blanco and Citrus aurantifolia are the edible plants which contain several biological properties including antibacterial activity. The aims of the present study were to determine the chemical compositions and evaluate antibacterial activities of citrus essential oils extracted from the fruit peels of C. reticulata (CREO) and C. aurantifolia (CAEO), alone and in combination with gentamicin, against a panel of clinically isolated methicillin-resistant S. aureus (MRSA) (n = 40) and methicillin-susceptible S. aureus (MSSA) (n = 45). Gas chromatography-mass spectrometry analysis revealed that 12 and 25 compounds were identified in CREO and CAEO with the most predominant compound of limonene (62.9–72.5%). The antibacterial activities were determined by agar disk diffusion and resazurin-based microdilution methods. The results found that almost all MRSA isolates were resistant to ciprofloxacin, erythromycin, and clindamycin, and some isolates were resistant to gentamicin. CREO and CAEO exhibited inhibitory effects toward clinical isolates (MIC: 1.0–32.0 and 8.0–32.0 mg/mL, respectively), with a similar trend to limonene (MIC: 1.0–32.0 mg/mL). However, the higher antibacterial effects were found in CREO and limonene when compared to CAEO (p < 0.01). In combination effect, the results showed the synergistic interaction of gentamicin with CREO and limonene on the MRSA and MSSA isolates (FIC indexes: 0.012–0.258 and 0.012–0.375), but that interaction of gentamicin with CAEO was observed only on MRSA (FIC index: 0.012–0.016). These findings demonstrated the potential of these citrus essential oils as natural antibacterial agents that may contribute to reduce the emerging of antimicrobial-resistant bacteria.
Grape Pomace Valorization by Extraction of Phenolic Polymeric Pigments: A Review

In recent years there has been a growing concern about environmental pollution linked to the generation of agroindustrial waste. The wine industry generates approximately 8.49 million tons of grape pomace per year worldwide; this residue can be used to obtain compounds with biological activity. Grape pomace is a source of anthocyanins, pigments that have antioxidant properties and help prevent cardiovascular disease. The development of sustainable extraction, purification and identification techniques constitutes an important step in adding value to this waste. Therefore, the present research has focused on presenting a review of works carried out in the last years.
LncRNA H19 inhibits oxidative stress injury of cochlear hair cells by regulating miR-653-5p/SIRT1 axis

Oxidative stress is one of the important mechanisms of inner ear cell damage, which can lead to age-related hearing loss (ARHL). LncRNA H19 is significantly downregulated in the cochlea of old mouse, however, the role of H19 in the development of ARHL remains unclear. In this study, we aim to investigate the expression and function of H19 in oxidative stress injury of cochlear hair cells induced by H 2O 2. RT-qPCR and western blot analysis confirms that HEI-OC1 cells stimulated with H 2O 2 decreases the expressions of H19 and SIRT1, but increases the expression of miR-653-5p. Overexpression of H19 could increase cell viability, ATP level and mitochondrial membrane potential, but reduce mitochondrial ROS generation and cell apoptosis ratio in H 2O 2-stimulated HEI-OC1 cells. MiR-653-5p is a target of H19, which can bind to the 3′-UTR of SIRT1. H19 is found to regulate the expression of SIRT1 through miR-653-5p. Further experiments demonstrates that H19 regulates HEI-OC1 cell viability, ATP level, mitochondrial membrane potential, mitochondrial ROS generation, and cell apoptosis ratio via the miR-653-5p/SIRT1 axis. In conclusion, lncRNA H19 inhibits oxidative stress injury of cochlear hair cells via the miR-653-5p/SIRT1 axis.
A New NVM Device Driver for IoT Time Series Database

Numerous IoT devices in IoT systems collect data concurrently, which brings great challenges to IoT time series databases to store and manage these data. NVM device has high read–write speed compared with HDD and Flash-based SSD, and it is a possible way to solve the storage bottleneck. However, there are some limitations that should be solved such as the overhead of the I/O software stack for NVM devices and the lack of optimization for IoT time series databases in a Linux environment. By analyzing the characteristics of IoT time series databases and NVM devices, we optimized the device driver of NVM in Linux and provide a new structure of a NVM device driver for IoT time series databases. A multi-queue management strategy and a lightweight load balance mechanism based on frequency were designed to improve the concurrency and efficiency of NVM device drivers. The prototype of an IoT-oriented NVM device driver named TS-PMEM was implemented based on an open-source NVM device driver. Six prototypes were used for evaluation with YCSB-TS, a test tool for time series databases. Results showed that TS-PMEM can improve write throughput of the time series databases by 18.6%, query throughput by 10.6%, and reduce the write latency by 8.3% and query latency by 6.4%.
Anti-Fatigue and Exercise Performance Improvement Effect of Glossogyne tenuifolia Extract in Mice

Glossogyne tenuifolia (GT) is a native perennial plant growing across the coastline areas in Taiwan. The current study aimed to examine the efficacy of GT extract in ameliorating physical fatigue during exercise and increasing exercise performance. Fifty male Institute of Cancer Research (ICR) mice were randomly segregated into five groups (n = 10) to GT extract orally for 4 weeks, at different concentrations (50, 100, 250, and 500 mg/kg BW/day): LGT 1X, MGT 2X, HGT 5X, and HGT 10X groups. Forelimb grip strength, endurance swimming time, serum biochemical marker levels, blood lipid profile and histological analysis of various organs were performed to assess the anti-fatigue effect and exercise performance of GT extract. The forelimb-grips strength and endurance-swimming time of GT-administered mice were increased significantly in a dose-dependent manner when compared to the control. Serum glucose, creatine kinase, and lactate levels were increased significantly in the HGT 10X group. Liver marker serum glutamic-oxaloacetic transaminase (GOT) was increased in the HGT 5X and HGT 10X groups, whereas Serum Glutamic Pyruvic Transaminase (GPT) was not altered. Renal markers, creatinine and uric acid levels, were not altered. Muscle and hepatic glycogen levels, which are essential for energy sources during exercise, were also significantly increased in a dose-dependent manner in all GT extract groups. No visible histological aberrations were observed in the vital organs after GT extract administration. The supplementation with GT extract could have beneficial effects on exercise performance and anti-fatigue function without toxicity at a higher dose.
Identification of Methicillin-Resistant Staphylococcus aureus (MRSA) Genetic Factors Involved in Human Endothelial Cells Damage, an Important Phenotype Correlated with Persistent Endovascular Infection

Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of life-threatening endovascular infections. Endothelial cell (EC) damage is a key factor in the pathogenesis of these syndromes. However, genetic factors related to the EC damage have not been well studied. This study aims to identify genetic determinants that impact human EC damage by screening the genome-wide Nebraska Transposon Mutant Library (NTML). A well-established MTT assay was used to test the in vitro damage of human EC cell line (HMEC-1) caused by each mutant strain in the NTML. We first confirmed some global regulators and genes positively impact the EC damage, which is consistent with published results. These data support the utility of the high-throughput approach. Importantly, we demonstrated 317 mutants significantly decreased the EC damage, while only 6 mutants enhanced the EC damage vs. parental JE2 strain. The majority of these genes have not been previously defined to affect human EC damage. Interestingly, many of these newly identified genes are involved in metabolism, genetic and environmental information processing, and cellular processes. These results advance our knowledge of staphylococcal genetic factors related to human EC damage which may provide novel targets for the development of effective agents against MRSA endovascular infection.
Pleiotropic Long-Term Effects of Atorvastatin on Posttraumatic Joint Contracture in a Rat Model

The antifibrotic effect of atorvastatin has already been demonstrated in several organ systems. In the present study, a rat model was used to investigate the effect of atorvastatin on posttraumatic joint contracture. Forty-eight Sprague Dawley rats were equally randomized into an atorvastatin group and a control group. After initial joint trauma, knee joints were immobilized for intervals of 2 weeks (n = 16) or 4 weeks (n = 16) or immobilized for 4 weeks with subsequent remobilization for another 4 weeks (n = 16). Starting from the day of surgery, animals received either atorvastatin or placebo daily. After euthanasia at week 2, 4 or 8, joint contracture was determined, histological examinations were performed, and gene expression was assessed. The results suggest that the joint contracture was primarily arthrogenic. Atorvastatin failed to significantly affect contracture formation and showed a reduction in myofibroblast numbers to 98 ± 58 (control: 319 ± 113, p < 0.01) and a reduction in joint capsule collagen to 60 ± 8% (control: 73 ± 9%, p < 0.05) at week 2. Gene expression of α-smooth muscle actin (α-SMA), collagen type I, transforming growth factor β1 (TGF-β1) and interleukin-6 (IL-6) was not significantly affected by atorvastatin. Atorvastatin decreases myofibroblast number and collagen deposition but does not result in an improvement in joint mobility.
Identifying Intrinsically Disordered Protein Regions through a Deep Neural Network with Three Novel Sequence Features

The fast, reliable, and accurate identification of IDPRs is essential, as in recent years it has come to be recognized more and more that IDPRs have a wide impact on many important physiological processes, such as molecular recognition and molecular assembly, the regulation of transcription and translation, protein phosphorylation, cellular signal transduction, etc. For the sake of cost-effectiveness, it is imperative to develop computational approaches for identifying IDPRs. In this study, a deep neural structure where a variant VGG19 is situated between two MLP networks is developed for identifying IDPRs. Furthermore, for the first time, three novel sequence features—i.e., persistent entropy and the probabilities associated with two and three consecutive amino acids of the protein sequence—are introduced for identifying IDPRs. The simulation results show that our neural structure either performs considerably better than other known methods or, when relying on a much smaller training set, attains a similar performance. Our deep neural structure, which exploits the VGG19 structure, is effective for identifying IDPRs. Furthermore, three novel sequence features—i.e., the persistent entropy and the probabilities associated with two and three consecutive amino acids of the protein sequence—could be used as valuable sequence features in the further development of identifying IDPRs.
An Exploratory Study on the Complexity and Machine Learning Predictability of Stock Market Data

This paper shows if and how the predictability and complexity of stock market data changed over the last half-century and what influence the M1 money supply has. We use three different machine learning algorithms, i.e., a stochastic gradient descent linear regression, a lasso regression, and an XGBoost tree regression, to test the predictability of two stock market indices, the Dow Jones Industrial Average and the NASDAQ (National Association of Securities Dealers Automated Quotations) Composite. In addition, all data under study are discussed in the context of a variety of measures of signal complexity. The results of this complexity analysis are then linked with the machine learning results to discover trends and correlations between predictability and complexity. Our results show a decrease in predictability and an increase in complexity for more recent years. We find a correlation between approximate entropy, sample entropy, and the predictability of the employed machine learning algorithms on the data under study. This link between the predictability of machine learning algorithms and the mentioned entropy measures has not been shown before. It should be considered when analyzing and predicting complex time series data, e.g., stock market data, to e.g., identify regions of increased predictability.
Controlling antimicrobial resistance: A daunting task ahead

Article history: Received 07-09-2021 Accepted 30-12-2021 Available online 28-02-2022 This is an Open Access (OA) journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
Do Life-cycle and Generation Moderate Sentiment and Diffusion?

ABSTRACT This study investigates the relationship between diffusion of new digital products and sentiment of product reviews with respect to the moderating effects of product generation and product life cycle. Results for a sample of 154 products and 105 thousand adopters show that the effect of sentiment on diffusion is significantly moderated by both product life cycle and production generation. Specifically, while there is a reciprocal causality between sentiment and diffusion in the early stage, the relationship is significantly weakened in the late stage of product life cycle. Moreover, while sentiment can trigger an effect on diffusion in a similar manner for both single- and multiple-generation products, the effect is likely to last longer for single-generation products than for multiple-generation products. The study discusses theoretical contributions to the Information System theory as well as practical contributions to the use of business intelligence platforms to manage product life cycle and product generation.
A K-Band Broadband Binary Phase Shifter

In this paper, a K-Band binary phase shifter that utilizes the architecture of a 180° rat-race coupler is presented. This structure takes advantage of the phase delay inherent in the coupler, along with fast switching PIN diodes, to create a binary system that has constant power usage and low insertion loss in its active states. The relative phase shift between states is controlled by forward and reverse diode bias voltages and the coupler exhibits binary phase states with absolute phase errors of ±10° over a 5.72 GHz bandwidth, making it suitable for use in K-band applications such as PMCW radar.
Expression of G-Protein-Coupled Estrogen Receptor (GPER) in Whole Testicular Tissue and Laser-Capture Microdissected Testicular Compartments of Men with Normal and Aberrant Spermatogenesis

Simple Summary Nowadays, there is no doubt that estrogens play an important role in male reproduction, affecting testicular cell differentiation, proliferation, apoptosis and metabolism. It is also widely believed that intratesticular balance of androgens and estrogens is crucial for the testicular development and function and that the increased testicular estrogen production may be associated with spermatogenic failure. There is also growing epidemiological evidence that the exposure of men to endocrine disruptors demonstrating estrogenic activity (xenoestrogens) may lead to impairment of male fertility via interference with estrogen signaling pathways. Besides the two classical nuclear estrogen receptors, the membrane-bound G protein-coupled estrogen receptor (GPER) was described in human testicular tissue. However, there are little data on its expression in testes with disturbed spermatogenesis. In this study, we investigated the GPER expression pattern in biopsies of azoospermic men with complete and aberrant spermatogenesis. Our results showed an increased expression of the GPER in testes with impaired spermatogenesis. Moreover, they indicate a possible involvement of estrogen signaling through GPER in disturbed function of Sertoli cells—the cells that support spermatogenic process. Abstract In this study, we retrospectively investigated GPER expression in biopsies of azoospermic men with complete (obstructive azoospermia—OA) and aberrant spermatogenesis (nonobstructive azoospermia—NOA). Each biopsy was histologically evaluated with morphometry. The testicular GPER expression was analyzed by the immunohistochemistry and RT-PCR technique in the whole testicular tissue and in seminiferous tubules and Leydig cells after laser-capture microdissection. In laser-microdissected compartments, we also analyzed transcriptional expression of selected Leydig (CYP17A1, HSD17B3, StAR) and Sertoli cell (AMH, SCF, BMP4) function markers. Immunohistochemical staining revealed expression of GPER in the cytoplasm of Leydig and Sertoli cells. Its stronger intensity was observed in Sertoli cells of NOA biopsies. The RT-PCR analysis of the GPER mRNA level unequivocally showed its increased expression in seminiferous tubules (i.e., Sertoli cells), not Leydig cells in NOA biopsies. This increased expression correlated positively with the transcriptional level of AMH—a marker of Sertoli cell immaturity, as well as FSH serum level in NOA but not in the OA group. Our results clearly demonstrate altered GPER expression in testes with primary spermatogenic impairment that might be related to Sertoli cell maturity/function.