Miracle-dz/UniFAR-FTUs huggingface dataset:
Alkanes as Membrane Regulators of the Response of Early Membranes to Extreme Temperatures

One of the first steps in the origin of life was the formation of a membrane, a physical boundary that allowed the retention of molecules in concentrated solutions. The proto-membrane was likely formed by self-assembly of simple readily available amphiphiles, such as short-chain fatty acids and alcohols. In the commonly accepted scenario that life originated near hydrothermal systems, how these very simple membrane bilayers could be stable enough in time remains a debated issue. We used various complementary techniques such as dynamic light scattering, small angle neutron scattering, neutron spin-echo spectroscopy, and Fourier-transform infrared spectroscopy to explore the stability of a novel protomembrane system in which the insertion of alkanes in the midplane is proposed to shift membrane stability to higher temperatures, pH, and hydrostatic pressures. We show that, in absence of alkanes, protomembranes transition into lipid droplets when temperature increases; while in presence of alkanes, membranes persist for longer times in a concentration-dependent manner. Proto-membranes containing alkanes are stable at higher temperatures and for longer times, have a higher bending rigidity, and can revert more easily to their initial state upon temperature variations. Hence, the presence of membrane intercalating alkanes could explain how the first membranes could resist the harsh and changing environment of the hydrothermal systems. Furthermore, modulating the quantity of alkanes in the first membranes appears as a possible strategy to adapt the proto-membrane behavior according to temperature fluctuations, and it offers a first glimpse into the evolution of the first membranes.
Predicting Popularity of YouTube videos using Viewer Engagement Features

Online Video platforms like YouTube have become a huge part of people’s lives. Not just for entertainment, but as a medium of learning and expressing themselves. So, Popularity Prediction becomes important to support the development of such online video services to help content producers understand their viewers’ needs, likes, and dislikes. Here a model is presented that aims to predict and classify the popularity based on various viewer engagement features of a video like view count, like count and subscriber count. These features help us understand the viewer’s liking for certain content. So, a popularity measure has been introduced using these features and a classification model is used to classify the popularity as high, medium, or low. The highest results were obtained using the Random Forest classifier, which showed an accuracy of 91.12%.
A Comprehensive Survey on the Detection, Classification, and Challenges of Neurological Disorders

Simple Summary This study represents a resourceful review article that can deliver resources on neurological diseases and their implemented classification algorithms to reveal the future direction of researchers. Researchers interested in studying neurological diseases and previously implemented techniques in this field can follow this article. Various challenges occur in detecting different stages of the disorders. A limited amount of labeled and unlabeled datasets and other limitations is represented in this article to assist them in finding out the directions. The authors’ purpose for composing this article is to make a straightforward and concrete path for researchers to quickly find the way and the scope in this field for implementing future research on neurological disease detection. Abstract Neurological disorders (NDs) are becoming more common, posing a concern to pregnant women, parents, healthy infants, and children. Neurological disorders arise in a wide variety of forms, each with its own set of origins, complications, and results. In recent years, the intricacy of brain functionalities has received a better understanding due to neuroimaging modalities, such as magnetic resonance imaging (MRI), magnetoencephalography (MEG), and positron emission tomography (PET), etc. With high-performance computational tools and various machine learning (ML) and deep learning (DL) methods, these modalities have discovered exciting possibilities for identifying and diagnosing neurological disorders. This study follows a computer-aided diagnosis methodology, leading to an overview of pre-processing and feature extraction techniques. The performance of existing ML and DL approaches for detecting NDs is critically reviewed and compared in this article. A comprehensive portion of this study also shows various modalities and disease-specified datasets that detect and records images, signals, and speeches, etc. Limited related works are also summarized on NDs, as this domain has significantly fewer works focused on disease and detection criteria. Some of the standard evaluation metrics are also presented in this study for better result analysis and comparison. This research has also been outlined in a consistent workflow. At the conclusion, a mandatory discussion section has been included to elaborate on open research challenges and directions for future work in this emerging field.
Expression of HK2, PKM2, and PFKM Is Associated with Metastasis and Late Disease Onset in Breast Cancer Patients

The reprogramming of energy metabolism is one of the hallmarks of cancer and is crucial for tumor progression. Altered aerobic glycolysis is a well-known characteristic of cancer cell metabolism. In the present study, the expression profiles of key metabolic genes (HK2, PFKM, and PKM2) were assessed in the breast cancer cohort of Pakistan using quantitative polymerase chain reaction (qPCR) and IHC. Expression patterns were correlated with molecular subtypes and clinical parameters in the patients. A significant upregulation of key glycolytic genes was observed in tumor samples in comparison to their adjacent controls (p < 0.0001). The expression of the studied glycolytic genes was significantly increased in late clinical stages, positive nodal involvement, and distant metastasis (p < 0.05). HK2 and PKM2 were found to be upregulated in luminal B, whereas PFKM was overexpressed in the luminal A subtype of breast cancer. The genes were positively correlated with the proliferation marker Ki67 (p < 0.001). Moreover, moderate positive linear correlations between HK2 and PKM2 (r = 0.476), HK2 and PFKM (r = 0.473), and PKM2 and PFKM (r = 0.501) were also observed (p < 0.01). These findings validate that the key regulatory genes in glycolysis can serve as potential biomarkers and/or molecular targets for breast cancer management. However, the clinical significance of these molecules needs to be further validated through in vitro and in vivo experiments.
Motivation to Participate in Intergenerational Programs: A Comparison across Different Program Types and Generations

Much research has attested to the benefits of intergenerational programs (IGPs) for older and younger participants, but there is a lack of understanding about what motivates them to participate and to persevere. We conducted structured interviews with 83 older (mean age = 77) and 96 younger (mean age = 23) participants who participated in 13 IGPs in Israel, some involving specific topics, and some providing assistance to older adults. Using a mixed-methods approach, we analyzed differences in motivation across generations and program types and compared initial and ongoing motivation to participate. We found differences regarding motivation by age group and program type: Among older participants, interest in the specific subject was a more prevalent motivation in topic-focused groups, while receiving support was more common in assistance groups. Among young persons, motivations relating to obligation, such as receipt of a financial scholarship, and the wish to help others were the most prevalent motivators. Ongoing motivation was often explained by positive intergenerational relationships and enjoyment. For older adults, offering more diverse topic-focused activities may motivate greater participation. For young adults, integrating IGPs within more and different settings, and promoting IGPs as opportunities to help others are potential motivators.
Exercise Stress Echocardiography in the Diagnostic Evaluation of Heart Failure with Preserved Ejection Fraction

More than half of patients with heart failure have a preserved ejection fraction (HFpEF). The prevalence of HFpEF has been increasing worldwide and is expected to increase further, making it an important health-care problem. The diagnosis of HFpEF is straightforward in the presence of obvious objective signs of congestion; however, it is challenging in patients presenting with a low degree of congestion because abnormal elevation in intracardiac pressures may occur only during physiological stress conditions, such as during exercise. On the basis of this hemodynamic background, current consensus guidelines have emphasized the importance of exercise stress testing to reveal abnormalities during exercise, and exercise stress echocardiography (i.e., diastolic stress echocardiography) may be used as an initial diagnostic approach to HFpEF owing to its noninvasive nature and wide availability. However, evidence supporting the use of this method remains limited and many knowledge gaps exist with respect to diastolic stress echocardiography. This review summarizes the current understanding of the use of diastolic stress echocardiography in the diagnostic evaluation of HFpEF and discusses its strengths and limitations to encourage future studies on this subject.
Prevalence, Genetics and Evolutionary Properties of Eurasian Avian-like H1N1 Swine Influenza Viruses in Liaoning

Swine influenza virus (SIV) is an important zoonosis pathogen. The 2009 pandemic of H1N1 influenza A virus (2009/H1N1) highlighted the importance of the role of pigs as intermediate hosts. Liaoning province, located in northeastern China, has become one of the largest pig-farming areas since 2016. However, the epidemiology and evolutionary properties of SIVs in Liaoning are largely unknown. We performed systematic epidemiological and genetic dynamics surveillance of SIVs in Liaoning province during 2020. In total, 33,195 pig nasal swabs were collected, with an SIV detection rate of 2%. Our analysis revealed that multiple subtypes of SIVs are co-circulating in the pig population in Liaoning, including H1N1, H1N2 and H3N2 SIVs. Furthermore, 24 H1N1 SIVs were confirmed to belong to the EA H1N1 lineage and divided into two genotypes. The two genotypes were both triple reassortant, and the predominant one with polymerase, nucleoprotein (NP), and matrix protein (M) genes originating from 2009/H1N1; hemagglutinin (HA) and neuraminidase (NA) genes originating from EA H1N1; and the nonstructural protein (NS) gene originating from triple reassortant H1N2 (TR H1N2) was detected in Liaoning for the first time. According to our evolutionary analysis, the EA H1N1 virus in Liaoning will undergo further genome variation.
SWI/SNF Chromatin Remodeling Enzymes in Melanoma

Melanoma is an aggressive malignancy that arises from the transformation of melanocytes on the skin, mucosal membranes, and uvea of the eye. SWI/SNF chromatin remodeling enzymes are multi-subunit complexes that play important roles in the development of the melanocyte lineage and in the response to ultraviolet radiation, a key environmental risk factor for developing cutaneous melanoma. Exome sequencing has revealed frequent loss of function mutations in genes encoding SWI/SNF subunits in melanoma. However, some SWI/SNF subunits have also been demonstrated to have pro-tumorigenic roles in melanoma and to affect sensitivity to therapeutics. This review summarizes studies that have implicated SWI/SNF components in melanomagenesis and have evaluated how SWI/SNF subunits modulate the response to current therapeutics.
Weight Gain and Nutrition during Pregnancy: An Analysis of Clinical Practice Guidelines in the Asia-Pacific Region

Nutrition and weight gain during pregnancy can influence the life-course health of offspring. Clinical practice guidelines play an important role in ensuring appropriate nutrition and weight gain among pregnant women. This study aims to identify clinical practice guidelines on gestational weight gain and/or maternal nutrition across the Asia-Pacific region and to determine the quality of the guidelines and variability in the recommendations. Through a systematic search of grey literature from 38 Asia-Pacific countries, 23 published guidelines were obtained. Of these, 10 eligible clinical practice guidelines reporting nutrition- or/and weight-related recommendations for pregnant women were selected and reviewed. Guideline quality was determined using the Assessment of Guidelines for Research Evaluation II (AGREE II) instrument. Of the 10 guidelines, 90% were classified as low-quality in the AGREE II appraisal. Several variations were found with respect to recommendations on gestational weight gain, including those specific to Asian populations. The recommendations on dietary advice, additional energy intake, and nutritional supplementation during pregnancy were varied. Clinical practice guidelines on weight gain and nutrition in pregnancy across the Asia-Pacific region are generally of poor quality, reflecting significant variation, and need to be improved to ensure pregnant women receive appropriate advice. (PROSPERO registration no. CRD42021291395).
In Silico Structure-Based Approach for Group Efficiency Estimation in Fragment-Based Drug Design Using Evaluation of Fragment Contributions

The notion of a contribution of a specific group in an organic molecule’s property and/or activity is both common in our thinking and is still not strictly correct due to the inherent non-additivity of free energy with respect to molecular fragments composing a molecule. The fragment- based drug discovery (FBDD) approach has proven to be fruitful in addressing the above notions. The main difficulty of the FBDD, however, is in its reliance on the low throughput and expensive experimental means of determining the fragment-sized molecules binding. In this article we propose a way to enhance the throughput and availability of the FBDD methods by judiciously using an in silico means of assessing the contribution to ligand-receptor binding energy of fragments of a molecule under question using a previously developed in silico Reverse Fragment Based Drug Discovery (R-FBDD) approach. It has been shown that the proposed structure-based drug discovery (SBDD) type of approach fills in the vacant niche among the existing in silico approaches, which mainly stem from the ligand-based drug discovery (LBDD) counterparts. In order to illustrate the applicability of the approach, our work retrospectively repeats the findings of the use case of an FBDD hit-to-lead project devoted to the experimentally based determination of additive group efficiency (GE)—an analog of ligand efficiency (LE) for a group in the molecule—using the Free-Wilson (FW) decomposition. It is shown that in using our in silico approach to evaluate fragment contributions of a ligand and to estimate GE one can arrive at similar decisions as those made using the experimentally determined activity-based FW decomposition. It is also shown that the approach is rather robust to the choice of the scoring function, provided the latter demonstrates a decent scoring power. We argue that the proposed approach of in silico assessment of GE has a wider applicability domain and expect that it will be widely applicable to enhance the net throughput of drug discovery based on the FBDD paradigm.
Research on Constructing Algorithm of Circulating Current in Delta Winding of Transformers

For Y-delta connected transformer, the currents in delta winding are not easily measurable. So the problem of current phase compensation has to be considered in the differential protection. However, using the present current phase compensation methods, the calculated differential current cannot really reflect the characteristics of the inrush. At the same time, the application based on the equivalent instantaneous inductance scheme is limited to identify the inrush. In this study, a constructing algorithm of circulating current in delta windings is proposed based on the voltage equations of two side windings. And the relationship between the circulating current and zero-sequence voltage and current in Y side windings is also obtained. The algorithm has nothing to do with the neutral grounding, so that its application is wide. The simulation and experimental results verify that the algorithm is correct and effective to identify the inrush.
Modification of Surfaces with Vaterite CaCO3 Particles

Former studies have demonstrated a strong interest toward the crystallization of CaCO3 polymorphs in solution. Nowadays, CaCO3 crystallization on solid surfaces is extensively being studied using biomolecules as substrates for the control of the growth aiming at various applications of CaCO3. Calcium carbonate exists in an amorphous state, as three anhydrous polymorphs (aragonite, calcite and vaterite), and as two hydrated polymorphs (monohydrocalcite and ikaite). The vaterite polymorph is considered as one of the most attractive forms due to its large surface area, biocompatibility, mesoporous nature, and other features. Based on physical or chemical immobilization approaches, vaterite can be grown directly on solid surfaces using various (bio)molecules, including synthetic polymers, biomacromolecules such as proteins and peptides, carbohydrates, fibers, extracellular matrix components, and even biological cells such as bacteria. Herein, the progress on the modification of solid surfaces by vaterite CaCO3 crystals is reviewed, focusing on main findings and the mechanism of vaterite growth initiated by various substances mentioned above, as well as the discussion of the applications of such modified surfaces.
Association Between Endometriosis and Prognosis of Ovarian Cancer: An Updated Meta-Analysis

Objective Increased risk of ovarian cancer (OC) among endometriosis patients has been proposed. However, the association between endometriosis and prognosis of OC remains controversial. This study evaluated whether endometriosis had influence on the survival outcomes of OC through a meta-analysis. Methods Relevant studies were retrieved from PubMed, Embase, and Web of Science databases and were evaluated using the Newcastle-Ottawa Quality Assessment Scale. Effect size was presented as hazard ratio (HR) and 95% confidence interval (CI). Heterogeneity test evaluation was performed using Cochran’s Q test and I2 statistics. Publication bias was determined using Egger’s test. Statistical analysis was performed using Stata 12.0 software. Results Twenty-one studies involving 38641 patients were included. For the total OC, there were significant differences in overall survival (OS) [HR (95% CI)=0.67 (0.55, 0.80), P<0.001] and progression-free survival (PFS) [HR (95% CI)=0.58 (0.42, 0.81), P=0.001] between endometriosis-associated ovarian cancer (EAOC) and non-EAOC patients in the random-effects models (P<0.05). For ovarian clear cell cancer, there were significant differences in terms of OS [HR (95% CI)=0.63 (0.48, 0.83), P=0.001] and PFS [HR (95% CI)=0.67 (0.52, 0.87), P=0.002] between EAOC and non-EAOC patients in the fixed-effects models (P>0.05). Subgroup analysis suggested no significant differences between EAOC and non-EAOC in OS and PFS in the univariate analysis per subgroup, and PFS in the American subgroup (P>0.05). Conclusion EAOC patients tended to have better OS and PFS than non-EAOC patients. Conducting higher quality prospective cohort studies with large sample sizes is recommended to confirm the authenticity of the current study’s results. Systematic Review Registration https://inplasy.com/inplasy-2022-3-0109/.
Pericarditis complicating COVID-19 infection: a report of two cases

COVID-19 infection is responsible for many complications, which can lead to a high risk of mortality. Respiratory manifestations are the most encountered, while that cardiovascular complications are classified as the most severe. We report two cases of COVID-19 infection complicated by pericarditis. In the absence of other etiology of pericarditis, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was considered as the behind cause. The treatment in these two cases was corticosteroids with colchicine, with good outcomes. In the presence of any cardiovascular symptoms, pericarditis related to COVID-19 should be suspected, in order to act swiftly and avoid complications as well as contamination.
The Potential Role of Peripheral Oxidative Stress on the Neurovascular Unit in Amyotrophic Lateral Sclerosis Pathogenesis: A Preliminary Report from Human and In Vitro Evaluations

Oxidative stress, the alteration of mitochondrial function, and changes in the neurovascular unit (NVU) could play a role in Amyotrophic Lateral Sclerosis (ALS) pathogenesis. Our aim was to analyze the plasma redox system and nitric oxide (NO) in 25 ALS new-diagnosed patients and five healthy controls and the effects of plasma on the peroxidation/mitochondrial function in human umbilical cord-derived endothelial vascular cells (HUVEC) and astrocytes. In plasma, thiobarbituric acid reactive substances (TBARS), glutathione (GSH), and nitric oxide (NO) were analyzed by using specific assays. In HUVEC/astrocytes, the effects of plasma on the release of mitochondrial reactive oxygen species (mitoROS) and NO, viability, and mitochondrial membrane potential were investigated. In the plasma of ALS patients, an increase in TBARS and a reduction in GSH and NO were found. In HUVEC/astrocytes treated with a plasma of ALS patients, mitoROS increased, whereas cell viability and mitochondrial membrane potential decreased. Our results show that oxidative stress and NVU play a central role in ALS and suggest that unknown plasma factors could be involved in the disease pathogenesis. Quantifiable changes in ALS plasma related to redox state alterations can possibly be used for early diagnosis.
Exploring the Determinants of Nascent Social Entrepreneurial Behaviour

Following the emergence of social, environmental, and public health issues, this study analysed the determinants of nascent social entrepreneurial behaviour. This research investigated the effects of empathy and prior experience with social problems on nascent social entrepreneurial behaviour through social entrepreneurial self-efficacy, outcome expectations of social entrepreneurship, and perceived social support. Through utilising the quantitative survey method, this study gathered a total of 560 valid responses, comprising 258 Chinese respondents and 302 Taiwanese respondents. Outcome expectations and perceived social support positively influenced nascent social entrepreneurial behaviour for the Chinese sample, whereas social entrepreneurial self-efficacy and perceived social support positively influenced nascent social entrepreneurial behaviour for the Taiwanese sample. This research enriches the existing literature by taking account of social entrepreneurial behaviour, instead of merely analysing social entrepreneurial intentions.