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Objective Spinal cord injury (SCI), one of the major disabilities concerning central nervous system injury, results in permanent tissue loss and neurological impairment. The existing therapeutic options for SCI are limited and predominantly consist of chemical compounds. In this study, we delved into the neuroprotective effects of myricetin, a natural flavonoid compound, and the underlying mechanisms, specifically in the context of SCI, utilizing an in vivo model. Previously, our investigations revealed an elevation in the phosphorylated form of Lin-11, Isl-1, and Mec-3 kinase1 (LIMK1) at chronic time points postinjury, coinciding with neuronal loss and scar formation. Our primary objective here was to assess the potential neuroprotective properties of myricetin in SCI and to ascertain if these effects were linked to LIMK inhibition, a hitherto unexamined pathway to date. Methods Computational docking and molecular dynamics simulation studies were performed to assess myricetin’s potential to bind with LIMK. Then, using a rat contusion model, SCI was induced and different molecular techniques (Western blot, Evans Blue assay, quantitative reverse transcription polymerase chain reaction and immunohistochemistry) were performed to determine the effects of myricetin. Results Remarkably, computational docking models identified myricetin as having a better interaction profile with LIMK than standard. Subsequent to myricetin treatment, a significant downregulation in phosphorylated LIMK expression was observed at chronic time points. This reduction correlated with a notable decrease in glial and fibrotic scar formation, and enhanced neuroprotection indicating a positive outcome in vivo. Conclusion In summary, our findings underscore myricetin’s potential as a bioactive compound capable of attenuating SCI-induced injury cascades by targeting the LIMK pathway.

Purpose: This study aims to gain insights into how students perceive online examination practices and evaluation, as well as identify the key factors that impact their intentions toward online exams. Design/methodology/approach: This empirical study conducted in India utilized an online survey method between May 24 and June 14, 2022. The data were collected from 712 undergraduate and postgraduate students through a Google Docs questionnaire. Descriptive analysis, exploratory factor analysis (EFA), regression and reliability analysis were conducted to analyze the data. Findings: There are many studies related to the adoption of online learning. However, there are limited studies that explore the adoption and acceptance of online examinations and evaluations. This paper intends to fill this gap and tries to highlight important factors influencing online examination usage by the students. Five important factors emerged in the study include "pedagogy, validity, reliability," "practicality," "security," "facilitating condition" and "intention," The study concludes that taking tests online is preferred for several reasons, including the perceived increased dependability of grades and the decreased cost, time and effort associated with taking exams. Research limitations/implications: This research explores students' perceptions of learning management systems (LMS)-based online exams and provides insights for students to better prepare and adapt. It assists policymakers in developing fair assessment policies and improving LMS platforms. The study contributes to the theoretical understanding of e-learning and calls for further research to enhance the effectiveness of online exams. It identifies gaps in existing literature and recommends larger sample sizes, broader representation, longitudinal data collection and conversational methods for future research. Originality/value: This study shows increasing research on e-learning and online examinations, mostly using quantitative methods. The important variables for understanding students' perceptions of online exams are "pedagogy, validity, reliability," "practicality," "security," "facilitating condition" and "intention." Concerns raised include validity, fairness and security. Electronic exams are more suitable for formative evaluation, and validity, reliability, security and adaptability are key pillars for successful online testing.

This study aims to examine the effects of e-learning management system -- quality characteristics and student characteristics on continuous intention to use e-LMS. This empirical and quantitative study focuses on emerging nations, specifically India, and explores the acceptance of e-LMS among students. While previous research has examined student acceptance of e-LMS, a limited number of studies investigate the impact of e-learning management system quality and student characteristics on continuing e-LMS usage. This study aims to fill this gap by identifying the key variables that influence the adoption of e-LMS. The survey was disseminated online over four weeks in several departments of an HEI located in a rural, remote, and isolated area of the Himalayan foothills. 469 valid replies were obtained using the purposive sampling technique. The data analysis using the structural equation model showed that learner control, technology experience, motivation for learning related to technology, information quality, system quality, and service quality all had a statistically significant impact on students' continued use of e-LMS. According to the neural network (NN) model results, the most significant factors influencing continuous intention to use e-learning are information quality, technological experience, service quality, system quality, motivation for learning, learner control, and personnel innovativeness.

OBJECTIVE: To compare the quadriceps isokinetic strength parameters of athletes and non-athletes. METHODOLOGY: The cross-sectional study was conducted from July to December 2019 at the Pakistan Sports Board, Islamabad. The sample size was 81, selected through a non-probability convenience sampling technique and calculated by the Rao Soft tool. The 41 participants were in the athletes' group, and 40 were in the non-athletes' group. Individuals with a history of sprain, strain, or fracture in the lower limbs within the last six months were excluded. The self-structured questionnaire includes demographic data, waist-to-hip ratio, thigh circumference, peak torque values and agility t-test score. The isokinetic strength of the right lower limb (RLL) was measured via Biodex system Pro 3. Data was analyzed through SPSS 22, and an independent t-test was applied for analysis between groups. Pearson test was used for the correlation coefficient. RESULTS: Athletes had significantly higher quadriceps muscle strength than non-athletes (p

Students' and instructors' adoption of "e-learning management systems (e-LMSs)" is critical to their success in a "virtual learning environment." Students can use "e-learning" to obtain instructional materials to supplement "traditional classroom" instruction. This study intends to highlight the important factors of e-learning adoption in higher education institutes. The aim is to determine the factors forming positive intention toward using e-LMS based on "individual characteristics" ("instructor quality," "course quality," "learning value," "social influence," "facilitating condition," "system quality," "perceived usefulness," and "perceived ease of use"). The questionnaire-based survey based on 369 responses is from LMS users. The proposed research model was tested using structural equation modeling. Initially, postadoption behavior was required to be investigated. The original measurement model contained eight independent constructs. A modified measurement model was created after the initial model was enhanced using exploratory factor and principal component analysis. The results of this study will help practitioners and policymakers in the effective development and implementation of e-LMSs in higher education institutions (HEIs), especially in developing countries, such as India. From the theoretical point of view, the result of this study will further enrich the IT adoption literature.

The Andean bear is the only extant member of the Tremarctine subfamily and the only extant ursid species to inhabit South America. Here, we present an annotated de novo assembly of a nuclear genome from a captive-born female Andean bear, Mischief, generated using a combination of short and long DNA and RNA reads. Our final assembly has a length of 2.23 Gb, and a scaffold N50 of 21.12 Mb, contig N50 of 23.5 kb, and BUSCO score of 88%. The Andean bear genome will be a useful resource for exploring the complex phylogenetic history of extinct and extant bear species and for future population genetics studies of Andean bears.

Glioblastoma (GBM) is the most aggressive form of primary brain cancer, with 5-year survival rates of less than 5%. Clinical management of GBM has not changed in the last 15 years, and current treatment approaches combine surgical resection, followed by radiotherapy and chemotherapy. Tragically, tumour recurrence is inevitable. Still, very little is known about how tumours evolve in response to therapy and become treatment resistant. In 2019, The Glioma Longitudinal AnalySiS (GLASS) consortium curated extensive, publicly accessible genomic profiling data captured from matched primary and recurrent tumours across 222 patients, along with comprehensive clinical annotations. Recently, this longitudinal genomic data resource was expanded by integrating matching transcriptomic and genomic data from 304 adult patients with isocitrate dehydrogenase (IDH)-wild-type and IDH-mutant glioma captured at two or more time points (Varn et al., 2022). This has enabled new insights into the dynamic changes in transcriptional programs, cellular compositions and microenvironment interactions within these brain tumours. In this commentary, we will focus on recurrent high-grade IDHwt and the implications of these findings for targeting tumour-microenvironment interactions that may pave new pathways for developing therapies for this type of brain tumour.

Cancer is a global health challenge, despite significant advancements in research. Addressing this issue, we report the design, synthesis and biological evaluation of pyrimidinyl indoles as potential antineoplastic agents. Pyrimidinyl indoles interact with pyruvate kinase isoform M2 (PKM2), which is commonly overexpressed in oral, lung, breast and colorectal cancers. In silico studies indicated that these molecules are having affinity towards PKM2 and targeting key residues such as Phe26, Leu27, Tyr390, Gln393, Leu394 and Glu397 at the interfacial active site region between the two chains of PKM2. Thereafter compounds were designed, synthesized and characterized using nuclear magnetic resonance (NMR), infrared spectroscopy (IR) and mass spectrometry (MS). This was followed by in vitro screening using cell lines and enzyme‐coupled assays. One of the designed PKM2 inhibitor demonstrated potent anticancer activity against MCF‐7 (Breast Cancer) cells while sparing normal MCF‐10 A breast cells. Molecular dynamics (MD) simulation studies showed that the developed inhibitor stabilized the PKM2 active site over a 100 ns simulation. [ABSTRACT FROM AUTHOR]

Objective: Spinal cord injury (SCI), one of the major disabilities concerning central nervous system injury, results in permanent tissue loss and neurological impairment. The existing therapeutic options for SCI are limited and predominantly consist of chemical compounds. In this study, we delved into the neuroprotective effects of myricetin, a natural flavonoid compound, and the underlying mechanisms, specifically in the context of SCI, utilizing an in vivo model. Previously, our investigations revealed an elevation in the phosphorylated form of Lin-11, Isl-1, and Mec-3 kinase1 (LIMK1) at chronic time points postinjury, coinciding with neuronal loss and scar formation. Our primary objective here was to assess the potential neuroprotective properties of myricetin in SCI and to ascertain if these effects were linked to LIMK inhibition, a hitherto unexamined pathway to date. Methods: Computational docking and molecular dynamics simulation studies were performed to assess myricetin's potential to bind with LIMK. Then, using a rat contusion model, SCI was induced and different molecular techniques (Western blot, Evans Blue assay, quantitative reverse transcription polymerase chain reaction and immunohistochemistry) were performed to determine the effects of myricetin. Results: Remarkably, computational docking models identified myricetin as having a better interaction profile with LIMK than standard. Subsequent to myricetin treatment, a significant downregulation in phosphorylated LIMK expression was observed at chronic time points. This reduction correlated with a notable decrease in glial and fibrotic scar formation, and enhanced neuroprotection indicating a positive outcome in vivo. Conclusion: In summary, our findings underscore myricetin's potential as a bioactive compound capable of attenuating SCI-induced injury cascades by targeting the LIMK pathway. [ABSTRACT FROM AUTHOR]

X-ray sources with a photon energy higher than 2140 eV are increasingly being used for routine x-ray photoelectron spectroscopy (XPS) on laboratory-based instruments. This analytical approach is termed "HAXPES" (hard x-ray photoelectron spectroscopy). This article provides an overview of the current and potential future uses of laboratory-based HAXPES in comparison to routine XPS performed using Al Kα and Mg Kα x-ray sources. The standardization of XPS has occurred over 30 years and many of the procedures and reference works are specific to the use of Al Kα and Mg Kα x-ray sources. In this article, we discuss the translation of standard XPS practices to HAXPES, indicate useful resources for HAXPES users, and highlight areas where there is a need for improved information and guidance. [ABSTRACT FROM AUTHOR]

Ion beams are used in x-ray photoelectron spectroscopy (XPS) to clean samples and perform compositional sputter depth profiles. The purpose of this article is to compile good practice, recommendations, and useful information related to the use of argon ion sources for inexperienced users of XPS instrumentation. The most used type of ion source generates monoatomic argon ions at a range of energies from a fixed direction relative to the instrument. The angle and direction of the ion beam with respect to the surface are normally altered by manipulating the sample, and this may involve tilting the sample to change the angle of incidence or rotating the sample to change the azimuthal incidence angle. Atomic argon ion beams cause damage to the structure of the material surface, which may exhibit itself as a change in stoichiometry or topography as well as the implantation of argon atoms. Therefore, caution is required in the interpretation of XPS depth profiles. Gas cluster ion sources offer new possibilities and choices to XPS users. Gas cluster sources enable the sputtering of organic materials with high yield in comparison to inorganic materials and offer the potential for nearly damage-free depth profiling of delicate organic materials as well as low damage cleaning of inorganic materials. It may be possible to use argon clusters to reduce damage during the depth profiling of inorganic materials, but there is currently insufficient evidence to make any general recommendations. [ABSTRACT FROM AUTHOR]

Estimation of Chlorophyll-a (Chl-a) concentration from remote-sensing reflectance derived from satellite imagery is highly effective in monitoring the spatial and temporal optical variations in water bodies. In turbid, productive and inland waters, implementation of traditional Chl-a estimation algorithms using the blue and green wavelength bands results in higher error in estimated Chl-a. To minimize the absorption and scattering effects of other water constituents like colored dissolved organic matter and particulate matter, the wavelengths bands in red and Near Infrared (NIR) are generally used for estimating Chl-a concentration in productive waters. Owing to a widely observed optical variability in natural waters, a single universal algorithm is not applicable to all waterbodies, hence, regional tuning of algorithms is necessary for estimating Chl-a in turbid and inland productive waters. Here, a 2-band based algorithm of the form and a 3-band algorithm of form were tuned for Chl-a estimation based on field measurements carried out in three water bodies, Chilika Lake of Orissa, Ujjani Reservoir of Maharashtra, Vallabh Sagar Reservoir of Gujarat, India, wherein the observed Chl-a concentration range is 5–33 mg/m3. Together with measured in situ reflectance spectra and concurrent Chl-a concentrations, tuning of red-NIR algorithms is performed. The optimal wavelengths to estimate Chl-a found by the proximal sensing method are = 691 nm and = 667 nm in case of 2-band red-NIR type algorithm. For 3-band red-NIR algorithm, the optimal wavelengths are = 670 nm, = 696 nm and = 740 nm. The mean absolute percentage error (MAPE) and root-mean-square error (RMSE) values obtained for the estimated Chl-a using the tuned 2-band red-NIR algorithm are 29.9% and 5.35 respectively. Similarly, RMSE and MAPE values for Chl-a concentration estimated using the 3-band tuned red-NIR algorithm are 4.24 and 22.5%, respectively. The tuned 2-band and 3-band algorithms resulted in better Chl-a estimates than the fourteen blue-green and red-NIR algorithms from previous studies. The 2-band and 3-band algorithms were re-calibrated to wavelengths present in the ocean land color imager (OLCI) sensor on Sentinel-3 satellite to monitor these water bodies. Spatio-temporal analysis of OLCI imagery derived Chl-a concentrations over Chilika lake (2019 and 2020) indicated seasonal variations. The tuned 3-band red-NIR algorithm exhibited robust performance in all seasons despite wide variations in colored dissolved organic matter and suspended sediments. The tuned red-NIR algorithms are useful in monitoring inland turbid productive waters with upcoming missions such as Plankton, Aerosol, Cloud Ecosystem (PACE) and Oceansat-3.

Tyrosine kinases are significant mediators of the signaling cascade that play vital role in various biological processes. The involvement of tyrosine kinases in regulating and functioning various metabolic pathways in the body has encouraged scientists to study their role in cancer onset and progression extensively. The human genome consists of over 90 tyrosine kinases, making it a wider research domain. To date, drugs incorporating a wide variety of heterocyclic scaffolds have been developed against many tyrosine kinases. However, factors such as drug resistance, undesirable side effects, and toxicity shown by current anticancer agents are significant challenges. These shortcomings compelled medicinal chemists to ponder the development of variable scaffolds with proficient anticancer activity and minimum toxicity. After the discovery of prontosil (the first sulfonamide antibiotic), molecules with sulfonamide moiety were synthesized and tested for bacterial infections, diabetes, inflammation, glaucoma, etc. and soon sulfonamides with oncotherapeutic effects surfaced. ACK1/TNK, BTK, LMTK3, and EGFR, etc., are some of the enzymes belonging to receptor tyrosine kinase family which are customarily mutated or overexpressed in different types of cancer. These enzymes are now widely explored and modulators of these enzymes having the sulfonamide moiety are steadily being launched. In this review we sight to summarize the chemical and biological aspects of these sulfonamide containing compounds as tyrosine kinase modulators and their role in preventing and terminating the progression of cancer.

Abstract The spatial and temporal variations in the hydrochemistry of the Sutlej river in the Indian Punjab were studied based on water quality parameters analysed during pre- and post-monsoon seasons of the years 2017 and 2018. The grab water samples were collected from the river using stratified random sampling and analysed for pH, electrical conductivity (EC), carbonate (CO3 −2), bicarbonate (HCO3 −), chloride (Cl−), nitrate (NO3 −), total hardness, calcium (Ca+2), sodium (Na+) and potassium (K+) using standard methods. Spatio-temporal variations in the parameters used to evaluate the water quality for irrigation (electrical conductivity (EC), residual sodium carbonate (RSC) and sodium absorption ratio (SAR)) were also studied. In order to rate the composite influence of all the physicochemical parameters, water quality index (WQI) was computed. Spatial variations in WQI for drinking and irrigation purposes were studied using the inverse distance weighted method in GIS. Results showed that the river water was alkaline in nature, HCO3 − and Cl− are the major anions, and Ca2+ and Na+ are the cations in the river water during both seasons. The regression analysis of EC with cations and anions showed that the regression coefficient was mainly significant with Ca2+ and HCO3 −, irrespective of the season. The concentration of ions was not significantly affected by season, but it was higher along transboundary of the river. Total alkalinity of water was significantly (p 85% of the water samples were in good categories for irrigation purposes. According to grades of WQI for drinking purposes, the poor WQI was observed in 3.6%, 3.7% and 5.9% of the samples during pre-2017, pre-2018 and post-monsoon 2018, respectively. The poor water quality index for irrigation purposes was observed in 16.7% and 4.7% of the samples during pre-monsoon 2017 and 2018, respectively. The water quality index values for drinking and irrigation were higher (poor water quality) along transboundary of the river. The ratio of Ca2+/Mg2+, (Na+ + K+)/TZ + and Ca2+ + Mg2+/(Na+ + K+) indicated both carbonate and silicate lithology contribute to hydrochemistry of the river besides anthropogenic factors. Non-metric multidimensional scaling showed that all the samples are of a similar origin across the river including transboundary, whereas cluster analysis resulted in the two main groups: pH and Cl in the one group, and EC along with the remaining cations and anions in the other group during pre-monsoon, but pH in the one group, and EC along with the remaining cations and anions in the other group during post-monsoon. The high concentration of Cl− is a signature of anthropogenic inputs in addition to the contribution of natural factors. These results suggest that the cultivation of crops on the soils along transboundary may cause the transfer of ions through the food chain to human beings affecting their health. Moreover, drinking of river water by inhabitants living along transboundary may affect their health.

Control over the agglomeration state of manufactured particle systems for drug and oligonucleotide intracellular delivery is paramount to ensure reproducible and scalable therapeutic efficacy. Ultrasonication is a well-established mechanism for the deagglomeration of bulk powders in dispersion. Its use in manufacturing requires strict control of the uniformity and reproducibility of the cavitation field within the sample volume to minimise within-batch and batch-to-batch variability. In this work, we demonstrate the use of a reference cavitating vessel which provides stable and reproducible cavitation fields over litre-scale volumes to assist the controlled deagglomeration of a novel non-viral particle-based plasmid delivery system. The system is the Nuvec delivery platform, comprising polyethylenimine-coated spiky silica particles with diameters of ∼ 200 nm. We evaluated the use of controlled cavitation at different input powers and stages of preparation, for example before and after plasmid loading. Plasmid loading was confirmed by X-ray photoelectron spectroscopy and gel electrophoresis. The latter was also used to assess plasmid integrity and the ability of the particles to protect plasmid from potential degradation caused by the deagglomeration process. We show the utility of laser diffraction and differential centrifugal sedimentation in quantifying the efficacy of product de-agglomeration in the microscale and nanoscale size range respectively. Transmission electron microscopy was used to assess potential damages to the silica particle structure due to the sonication process.

Abstract Outcomes of various clinical studies for the coronavirus disease 2019 (COVID-19) treatment indicated that the drug acts via inhibition of multiple pathways (targets) is likely to be more successful and promising. Keeping this hypothesis intact, the present study describes for the first-time, Grazoprevir, an FDA approved anti-viral drug primarily approved for Hepatitis C Virus (HCV), mediated multiple pathway control via synergistic inhibition of viral entry targeting host cell Angiotensin-Converting Enzyme 2 (ACE-2)/transmembrane serine protease 2 (TMPRSS2) and viral replication targeting RNA-dependent RNA polymerase (RdRP). Molecular modeling followed by in-depth structural analysis clearly demonstrated that Grazoprevir interacts with the key residues of these targets. Futher, Molecular Dynamics (MD) simulations showed stability and burial of key residues after the complex formation. Finally, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) analysis identified the governing force of drug-receptor interactions and stability. Thus, we believe that Grazoprevir could be an effective therapeutics for the treatment of the COVID-19 pandemic with a promise of unlikely drug resistance owing to multiple inhibitions of eukaryotic and viral proteins, thus warrants further clinical studies.

BACKGROUND: Data-driven practices are now crucial in the digital age for streamlining operations and boosting output across a range of industries. With e-Learning emerging as a cutting-edge and promising strategy to improve educational delivery and student engagement, higher education institutions are also adopting this trend. Despite the potential advantages, e-Learning adoption in higher education is still a developing topic with scant published research. OBJECTIVE: This study aims to conduct a thorough analysis of existing literature, seeking to determine the present status of e-Learning adoption in higher education while also identifying promising avenues for further research. METHODS: In this study, a systematic literature review methodology and a bibliometric approach are utilized to examine 63 papers sourced from the Scopus database, encompassing the years 2017 to 2021. These papers were specifically chosen due to their pertinence to e-Learning adoption in higher education institutions, following the exclusion and inclusion criteria outlined in the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework. The analysis techniques employed include descriptive overviews, citation analysis, and keyword co-occurrence. RESULTS: The systematic review of the literature revealed a significant increase in e-Learning adoption within higher education institutions (HEIs) in recent times. The findings highlighted several crucial factors influencing e-Learning adoption, including perceived ease of use, usefulness, learner attitude, self-efficacy, and facilitating conditions. However, further investigation is needed to better understand the impact of perceived learning and teaching styles on e-Learning acceptance in higher education settings. CONCLUSION: This study suggests conducting future investigations on e-Learning in developing countries, with a specific focus on intention, usage, adoption, and impact. Additionally, it emphasizes the importance of exploring the influence of learning and teaching styles on e-Learning acceptance within higher education institutions. These valuable insights will facilitate the development of effective strategies for the successful implementation of e-Learning in higher education settings. [ABSTRACT FROM AUTHOR]