bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antidiabetic Phytocompounds Acting as Glucose Transport Stimulators
Authors: Eddouks Mohamed , Akdad Mourad , Ameziane Rabii , Khallouki Farid , Bakri Youssef 
Published: May 2022

Aims:The present study aimed to provide summarized data related to the phytocompouds improving glucose uptake in the diabetic state.Background:Glucose uptake in peripheral tissues such as skeletal muscle and adipose tissue is considered as an important step in the regulation of glucose homeostasis. Reducing high blood glucose levels in diabetic patients via targeting peripheral glucose uptake is a promising strategy to develop new antidiabetic medications derived from natural products.Objective:The current review focused on antidiabetic natural phytocompounds acting on glucose uptake in adipocytes and skeletal muscles to highlight their phytochemistry, the mechanistic pathway involved, toxicity, and clinical assessment.Methods:A systematic search was conducted in the scientific database with specific keywords on natural phytocompounds demonstrated to possess glucose uptake stimulating activity in vitro or ex vivo during the last decade.Results:In total, 195 pure molecules and 7 mixtures of inseparable molecules isolated from the plants kingdom, in addition to 16 biomolecules derived from non-herbal sources, possess a potent glucose uptake stimulating capacity in adipocytes and/or skeletal muscles in adipocytes and/or skeletal muscles in vitro or ex vivo. Molecular studies revealed that these plant-derived molecules induced glucose uptake via increasing GLUT-4 expression and/or translocation through insulin signaling pathway, AMPK pathway, PTP1B activity inhibition or acting as partial PPARγ agonists. These phytocompounds were isolated from 91 plants, belonging to 57 families and triterpenoids are the most sous-class of secondary metabolites showing this activity. Among all the phytocompounds listed in the current review, only 14 biomolecules have shown an interesting activity against diabetes and its complications in clinical studies.Conclusion:Epicatechin, catechin, epigallocatechin 3-gallate, quercetin, quercetin 3-glucoside, berberine, rutin, linoleic acid, oleanolic acid, oleic acid, chlorogenic acid, gallic acid, hesperidin, and corosolic acid are promising phytocompounds that showed great activity against diabetes and diabetes complications in vitro and in vivo. However, for the others phytocompounds further experimental studies followed by clinical trials are needed. Finally, foods rich in these compounds cited in this review present a healthy diet for diabetic patients.
A Soil Mechanical Model for Deformable Grounds Under the Dynamic Action
of High-Mobility Tracked Vehicles
Authors: Li Qiang , Liu Xintian 
Published: May 2022

Background:
The mechanical properties of the soil are key factors for studying the
ground adhesion capability of high-speed tracked vehicles under the action of dynamic loads. Classic
mechanical models of ground surface soil are insufficient to predict the mobility of high-speed
tracked vehicles.

Objectives:
The aim was to study a soil mechanical model for deformable grounds under the dynamic
action of high-mobility tracked vehicles.

Methods:
According to the high loading and shear rate of high-speed heavy-duty tracked vehicles, a
three-dimensional soil simulation model for deformable grounds was established. Numerical calculations
were performed.

Results:
The correctness of the simulation model was validated through the comparison of the numercal
calculation results with the soil-bin test results.

Conclusion:
On the basis of the empirical pressure-sinkage and the Janosi shear model of ground
surface soil, and coupled with factors such as the loading and shear rate, a new improved mechanical
model of ground surface soil was built for the running conditions of high-speed heavy-duty tracked
vehicles. The correctness of the improved model was validated through the comparison of the calculation
results of the improved model with the numerical simulation results, which provides a basis for
studying the driving performance of high-speed heavy-duty tracked vehicles on deformable grounds.
Recent Evidence-based Treatments for COVID-19: A Review
Authors: Ali Faraat , Anjum Varisha , Chauhan Garima , Ali Asad , Ahamad Javed 
Published: May 2022

Abstract:Corona virus disease (COVID-19) is a pandemic disease caused by SARS-COV2 that attacks primarily the respiratory system of the host. This disease was first reported in early December 2019, and the World Health Organization (WHO) classified the ongoing COVID-19 outbreak as a pandemic disease causing global public health emergency by mid-January 2020. It is the human-to-human transmission that occurs by droplets, infected hands or surfaces with an incubation time of 2-14 days. It displays signs and symptoms, and if the disease progresses it leads to death. To avoid symptomatic symptoms or increase infection severity, early diagnosis, quarantine, and supportive care can help to cure the patient infected with COVID-19. Several attempts have been projected for the development of vaccines against COVID-19. As of July 2, 2021, 600 vaccine candidates worldwide were evaluated against SARS-CoV-2, in which 300 have reached out to the preclinical stage of their development. Presently, Moderna (mRNA-1273), Shenzhen Geno-Immune Medical Institute (LV-SMENP-DC), Shenzhen Geno-Immune Medical Institute (Pathogenspecific aAPC), CanSino Biologicals (Ad5-nCoV), Inovio Pharmaceuticals (INO-4800) have plunged into the phase I/II clinical trials (Source: ClinicalTrials.gov website; WHO). Scientists are increasingly seeking a key hide behind pathogenic pathways and epidemiological features, as well as future drug goals, which will lead to the development of successful strategies for prevention and treatment. Based on the current published data, we summarize the structure, life cycle of SARS-CoV2 and the various product categories available as anti-COVID-19 agents (antiviral), with special emphasis on Chinese herbal medicines, which were licensed as anti-COVID agent by the Chinese Government. Such knowledge can be used as guidelines for COVID-19 clinical therapy.
A Review on Some Indian Medicinal Plants useful in Hair Care
Authors: Bhargavi Manju N. , Devang Pandya J. 
Published: May 2022

Abstract:
Hair related problems are an ever-increasing problem. Compared with chemical herbal ingredients are more preferred because of their easy availability and lesser side effects. The utilization of novel medicinal plant ingredients in various formulations such as hair tonic, hair gels, hair oils and hair dyes has proved to be beneficial than the formulations containing chemical components. These novel ingredients have helped in the enhancement of the beauty of hair and help in the treatment of various hair problems such as dandruff, alopecia and many more. It is a universal problem affecting both sexes. Herbal cosmetics are now appropriate solution to the current problem. This review describes the use of some natural medicinal plants for hair growth promotion, Anti-hair fall and Anti-grey hair with a brief description of the major use, plant parts used and the active compounds responsible for the use of the herbal plants.
A Candidate for Health Promotion, Disease Prevention and Treatment:
Common Rue (Ruta graveolens L.), an Important Medicinal Plant in Traditional
Medicine
Authors: Shahrajabian Mohamad Hesam 
Published: May 2022

Background:
Ruta graveolens L. belongs to Rutaceae; it is a semi-wood perennial or a
small evergreen sub-shrub, which is native to Southern Europe, West Asia and Northern Africa.

Objective:
The goal of this manuscript was to outline the most notable traditional and modern advantages
and pharmaceutical benefits of common rue.

Methods:
The manuscript covers review articles, randomized control experiments, analytical studies
and observations, which have been gathered from different sources, such as Google Scholar, Scopus,
Science Direct and PubMed. A review of the literature was carried out using the keywords rutin, Ruta
graveolens L., rue, common rune, coumarin, natural products and pharmaceutical benefits.

Results:
Rue contains quinoline alkaloids, such as graveoline and graveolinine, acridone alkaloids,
such as furacridone and gravacridone, furanoquinoline dictamnine, coumarins, such as gravelliferone,
isorutarin, rutacultin, rutaretin, and suberenone, and the furanocoumarins 5-methoxypsoralen (bergapten)
and 8-methoxypsoralen (xanthotoxine). Most of its aromatic and medicinal properties are due to
the presence of rutin and its essential oil. It has been used in folk medicine as a stimulant, for its antiinflammatory
and analgesic properties, anti-androgenic activity, anti-hyperglycemic effects, antihyperlipidemic
effects, xanthine oxidase inhibition activity, and anticancer properties.

Conclusion:
According to pharmacological and phytochemical advantages, pennyroyal shows its importance
as a medicinal plant in both modern medicinal science and traditional medicine.
Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study
Authors: Baker William , Colditz Jason B , Dobbs Page D , Mai Huy , Visweswaran Shyam , Zhan Justin , Primack Brian A 
Published: May 2022

Background
Twitter provides a valuable platform for the surveillance and monitoring of public health topics; however, manually categorizing large quantities of Twitter data is labor intensive and presents barriers to identify major trends and sentiments. Additionally, while machine and deep learning approaches have been proposed with high accuracy, they require large, annotated data sets. Public pretrained deep learning classification models, such as BERTweet, produce higher-quality models while using smaller annotated training sets.

Objective
This study aims to derive and evaluate a pretrained deep learning model based on BERTweet that can identify tweets relevant to vaping, tweets (related to vaping) of commercial nature, and tweets with provape sentiment. Additionally, the performance of the BERTweet classifier will be compared against a long short-term memory (LSTM) model to show the improvements a pretrained model has over traditional deep learning approaches.

Methods
Twitter data were collected from August to October 2019 using vaping-related search terms. From this set, a random subsample of 2401 English tweets was manually annotated for relevance (vaping related or not), commercial nature (commercial or not), and sentiment (positive, negative, or neutral). Using the annotated data, 3 separate classifiers were built using BERTweet with the default parameters defined by the Simple Transformer application programming interface (API). Each model was trained for 20 iterations and evaluated with a random split of the annotated tweets, reserving 10% (n=165) of tweets for evaluations.

Results
The relevance, commercial, and sentiment classifiers achieved an area under the receiver operating characteristic curve (AUROC) of 94.5%, 99.3%, and 81.7%, respectively. Additionally, the weighted F1 scores of each were 97.6%, 99.0%, and 86.1%, respectively. We found that BERTweet outperformed the LSTM model in the classification of all categories.

Conclusions
Large, open-source deep learning classifiers, such as BERTweet, can provide researchers the ability to reliably determine if tweets are relevant to vaping; include commercial content; and include positive, negative, or neutral content about vaping with a higher accuracy than traditional natural language processing deep learning models. Such enhancement to the utilization of Twitter data can allow for faster exploration and dissemination of time-sensitive data than traditional methodologies (eg, surveys, polling research).
Developing Educational Animations on HIV Pre-exposure Prophylaxis (PrEP) for Women: Qualitative Study
Authors: Young Anna Marie , Fruhauf Timothee , Okonkwo Obianuju , Gingher Erin , Coleman Jenell 
Published: May 2022

Background
Despite experiencing the second-highest rate of HIV incidence in the United States, pre-exposure prophylaxis (PrEP) use remains low among Black women due, in part, to a lack of patients’ awareness and providers’ knowledge.

Objective
Our goal was to design animated educational tools informed by patients and women’s health providers to address these barriers, specifically for women at risk for HIV.

Methods
Two animation storyboards about PrEP for women were created by academic stakeholders (eg, HIV clinical experts, educators, and HIV peer counselors), one for patients and one for providers. Four focus groups with community members from Baltimore, Maryland and four with women’s health providers (eg, obstetrician/gynecologists, midwives, nurse practitioners, and peer counselors) at an academic center were conducted to discuss the storyboards. Transcripts were analyzed using conventional content analysis, and themes were incorporated into the final versions of the animations.

Results
Academic stakeholders and 30 focus group participants (n=16 female community members and n=14 women’s health providers) described important themes regarding PrEP. The themes most commonly discussed about the patient animation were understandability of side effects, HIV risk factors, messaging, PrEP access, and use confidence. Provider animation themes were indications for PrEP, side effects, and prescribing confidence.

Conclusions
We created two PrEP animations focused on women. Stakeholder feedback highlighted the importance of ensuring the understandability and applicability of PrEP educational materials while including necessary information to facilitate use or prescribing confidence. Both community members and women’s health providers reported greater use confidence after viewing the animations.
DESIGN AND DEVELOPMENT OF A PHARMACOGENOMIC MODEL FOR BREAST CANCER TO STUDY THE VARIATION IN DRUG ACTION AND SIDE EFFECTS
Authors: A. M. HIMA VYSHNAVI , NAMBOORI P. K. KRISHNAN 
Published: May 2022

Objective: The proneness of disease, as well as drug action and side effects, vary from person to person. This may be due to individual variations in the genome. The individual variation demands the need to design a population-specific 'predictive, preventive, participatory and personalized (p4)' pharmacogenomics drug molecule. The present work aims at designing a pharmacogenomic model for breast cancer to explain the individual variation in the proneness of the diseases and susceptibility towards drug action.
Methods: The drug action and side effects of drugs were analyzed from clinical trial reports. The genes responsible for the drug action and the genes responsible for side effects have been identified and included in the variation analysis. The pharmacogenomic gene models have been designed by inducing population-specific genetic variations within the gene sequence. The 3D structures of the 'variation-specific' protein models have been generated by 'homology modelling.' These models have been used further for docking studies with the known drug molecules. The kinetic stability of the protein-ligand complexes obtained out of docking studies has been studied by the molecular dynamic simulation.
Results: By the interaction studies and the computational analysis using the 'population-specific protein models,' the drug molecule, Capecitabine showed the highest binding affinity (–6.30kcal/mol) with the African population, Paclitaxel was found to be the most interacting with the European population with a binding affinity of–9.5603 kcal/mol, and Lapatinib is found to be the most suitable ligand for the American population with a binding affinity of–6.90 kcal/mol. These observations agree with the clinical trial data found in the 'ClinTrial database'.
Conclusion: The designed models are found to be suitable for representing the respective population-specific target models. The interaction studies of known drug molecules with these population-specific target models correspond to the observations in the 'ClinTrial database.'
Analisis Performa Algoritma Random Forest dan Naive Bayes Multinomial pada Dataset Ulasan Obat dan Ulasan Film
Authors: Awangga Rolly Maulana , Khonsa' Nuha Hanifatul 
Published: May 2022

Kemudahan akses informasi memberikan peluang pertukaran informasi antar individu maupun kelompok. Kemudahan akses tersebut memberikan dampak dengan munculnya banyak opini terhadap suatu produk atau topik terhangat. Data opini ulasan dapat diolah menjadi data informasi baru yang memiliki nilai lebih bagi perusahaan maupun pemanfaat data. Pengolahan data ulasan dapat dilakukan dengan menggunakan machine learning dengan algoritma klasifikasi untuk mendapatkan analisis sentimen terhadap produk tertentu. Dataset yang digunakan pada penelitian ini adalah datasetulasan obat dan ulasan film untuk melakukan analisis sentimen dengan mengulas performansi algoritma Random Forestdengan menggunakan beberapa pohon keputusan yang sama yang disatukandan Naïve Bayes Multinomialmenggunakan perhitungan probabilitas pada tingkat akurasi dan waktu latih data. Dalam preprocessing untuk pengolahan data dan penyesuaian tipe data pada metode yang akan digunakan dengan menggunakan CountVectorizer untuk mengubah token kata menjadi vektor dan mengubah data fitur menjadi tipe array. Pembagian data latih dan uji dengan rasio 75:25. Dengan hasil akurasi data terbaik 0,57% dengan menggunakan algoritma Naïve Bayes Multinomial pada data ulasan film. dan latih waktu terlama pada algoritma Random Forestsehingga disarankan untuk dapat menggunakan Term Frequency-Inverse Document Frequency (TF-IDF)sebagai term pembobotan kata untuk mendapatkan hasil akurasi yang lebih baik pada penelitian selanjutnya.
FLIPPING THE CLASSROOM IN THE EFL READING FOR ACADEMIC PURPOSE COURSE DURING COVID-19: BARRIERS AND BOOSTERS
Authors: Uran Stefanus Igolois G. 
Published: May 2022

The Flipped Classroom model has been a debatable issue, especially due to its triumph in the new set during the current outbreak of Covid-19. This study attempts to assess the effectiveness and explore the barriers and boosters of an FC approach in the Reading for Academic Purpose course in a private university in NTT Province, Indonesia. Employing a mixed-method design, this study generated data from the pre-and post-test and students TOWS (Threat-Opportunity-Weakness-Strength) analysis. Two groups of fourth-semester students, comprising 35 in a Blended Learning setting and another 23 in a Flipped Classroom, were taught similar reading skills and tasks. The paired-samples t-test indicates both FC (p=0.030.05, d=-0.70, medium effect size) and BL (p=0.000.05, d=-1.06, large effect size) settings were statistically significant by comparison. The independent-samples t-test used to contrast their effectiveness shows no statistically significant difference between groups (t[56]=1.11, p=0.27, d=0.29, small effect size). Although FC students benefited equally from the learning process in BL, they gained a lower mean score than their counterparts. TOWS analysis requires more improvement in FC due to students’ resilience to change, inability to self-learning management, poor collaboration and communication, technological setbacks, technical issues, and other socio-environmental constraints.
Reproductive Span of Caenorhabditis elegans Is Extended by Microbacterium sp.
Authors: Le Tho Son , Nguyen Thi Hong Gam , Ha Bich Hong , Huong Bui Thi Mai , Nguyen Thi Thu Hang , Vu Kim Dung , Ho Tu Cuong , Wang John 
Published: May 2022

Abstract
The reproductive span (RS) of organisms could be affected by different factors during their lifetime. In the model nematode, Caenorhabditis elegans, RS is affected by both genetic and environmental factors. However, none of the factors identified so far were related to environmental bacteria, which may incidentally appear anywhere in the habitats of C. elegans. We aimed to find environmental bacteria that could affect the RS of C. elegans and related species. We tested 109 bacterial isolates and found that Microbacterium sp. CFBb37 increased the RS and lifespan of C. elegans but reduced its brood size. We studied the effect of M. sp. CFBb37 on the RS of Caenorhabditis briggsae, Caenorhabditis tropicalis, and another Rhabditidae family species, Protorhabditis sp., and found similar trends of RS extension in all three cases, suggesting that this bacterial species may induce the extension of RS broadly among Caenorhabditis species and possibly for many other Rhabditidae. This work will facilitate future research on the mechanism underlying the bacterial extension of RS of nematodes and possibly other animals.
Formation of structural support of students' competencies as an element of the implementation of the concept of sustainable development
Authors: Бурнаева Е. М. , Матафонова А. Н. 
Published: May 2022

Базовыми методами формирования социальной компетентности являются групповая и партнерская работа, проведение ролевых или деловых игр, выполнение самостоятельной работы, проектная деятельность. С целью формирования социальной компетентности и совершенствования коммуникативных навыков в учебном процессе высшей школы также широко используются тренинги, ориентированные на развитие конкретного умения или навыки, необходимые для более профессионального выполнения поставленной задачи. Во время проведения тренинга используются новейшие методики и современные технические средства. Сущностью смыслового аспекта преподавания экономики является использование таких моделей, которые не только воспроизводят исключительно экономические аспекты современной жизни, а также изображают их связь с политическими и социальными событиями, что является неотъемлемой частью проблемы. Это дает возможность подготовить студентов к комплексному изучению экономической проблемы как социальной.
The basic methods of forming social competence are group and partner work, role-playing or business games, independent work, project activities. In order to form social competence and improve communication skills in the educational process of higher education, trainings focused on the development of a specific skill or skills necessary for more professional performance of the task are also widely used. During the training, the latest techniques and modern technical means are used. The essence of the semantic aspect of teaching economics is the use of such models that not only reproduce exclusively the economic aspects of modern life, but also depict their connection with political and social events, which is an integral part of the problem. This makes it possible to prepare students for a comprehensive study of the economic problem as a social one.
Éléments de sémiotique catégorielle. Théorie, méthode, schémas et pratique
Authors: Perusset Alain 
Published: May 2022

Depuis la parution de Sémantique structurale au milieu des années 1960, les principes de la catégorisation n’ont eu de cesse d’être discutés par les sémioticiens de tradition structuraliste : par Greimas lui-même avec le carré sémiotique, par Rastier ensuite avec la sémantique interprétative, ou, plus tard, par Zilberberg avec la grammaire tensive. Cet article vise à montrer comment la réunion de ces appareils conceptuels pourrait instituer ce qu’il conviendrait de nommer une « sémiotique catégorielle » ou « sémiotique des catégories ». Plus spécifiquement, l’objectif de cette contribution est de développer, à partir de ces procédures et modèles historiques, une méthodologie pour la classification des valeurs au sein des catégories (une taxinomie sémiotique), de même que des schémas idoines, comme le « trapèze tensif » ou l’« arborescence structurale ». L’intérêt de ce texte est ainsi double : il entend donner une consistance et une visibilité à un champ de la sémiotique qui pourrait avoir une même vocation méthodologique et opérationnelle que la sémiotique narrative ou discursive ; il vise à offrir aux autres sciences (biologie, sociologie, marketing…) une base théorique et des outils performants pour la conceptualisation et la classification des objets qu’elles étudient.