Essential Role Research Articles

The non-mitotic role of HMMR in regulating the localization of TPX2 and the dynamics of microtubules in neurons.

A functional nervous system is built upon the proper morphogenesis of neurons to establish the intricate connection between them. The microtubule cytoskeleton is known to play various essential roles in this morphogenetic process. While many microtubule-associated proteins (MAPs) have been demonstrated to participate in neuronal morphogenesis, the function of many more remains to be determined. This study focuses on a MAP called HMMR in mice, which was originally identified as a hyaluronan binding protein and later found to possess microtubule and centrosome binding capacity. HMMR exhibits high abundance on neuronal microtubules and altering the level of HMMR significantly affects the morphology of neurons. Instead of confining to the centrosome(s) like cells in mitosis, HMMR localizes to microtubules along axons and dendrites. Furthermore, transiently expressing HMMR enhances the stability of neuronal microtubules and increases the formation frequency of growing microtubules along the neurites. HMMR regulates the microtubule localization of a non-centrosomal microtubule nucleator TPX2 along the neurite, offering an explanation for how HMMR contributes to the promotion of growing microtubules. This study sheds light on how cells utilize proteins involved in mitosis for non-mitotic functions.

Distinct effects of phyllosphere and rhizosphere microbes on invader Ageratina adenophora during its early life stages.

Microbes strongly affect invasive plant growth. However, how phyllosphere and rhizosphere soil microbes distinctively affect seedling mortality and growth of invaders across ontogeny under varying soil nutrient levels remains unclear. In this study, we used the invader Ageratina adenophora to evaluate these effects. We found that higher proportions of potential pathogens were detected in core microbial taxa in leaf litter than rhizosphere soil and thus leaf inoculation had more adverse effects on seed germination and seedling survival than soil inoculation. Microbial inoculation at different growth stages altered the microbial community and functions of seedlings, and earlier inoculation had a more adverse effect on seedling survival and growth. The soil nutrient level did not affect microbe-mediated seedling growth and the relative abundance of the microbial community and functions involved in seedling growth. The effects of some microbial genera on seedling survival are distinct from those on growth. Moreover, the A. adenophora seedling-killing effects of fungal strains isolated from dead seedlings by non-sterile leaf inoculation exhibited significant phylogenetic signals, by which strains of Allophoma and Alternaria generally caused high seedling mortality. Our study stresses the essential role of A. adenophora litter microbes in population establishment by regulating seedling density and growth.

Altered Hippocampal Glutamatergic Neurotransmission and Cognitive Impairment in APP Knock-In Mice.

It is well established that glutamatergic neurotransmission plays an essential role in learning and memory. Previous studies indicate that glutamate dynamics shift with Alzheimers disease (AD) progression, contributing to negative cognitive outcomes. In this study, we characterized hippocampal glutamatergic signaling with age and disease progression in a knock-in mouse model of AD (APPNL-F/NL-F). At 2-4 and 18+ months old, male and female APPNL/NL, APPNL-F/NL-F, and C57BL/6 mice underwent cognitive assessment using Morris water maze (MWM) and Novel Object Recognition (NOR). Then, basal and 70 mM KCl stimulus-evoked glutamate release was measured in the dentate gyrus (DG), CA3, and CA1 regions of the hippocampus using a glutamate-selective microelectrode in anesthetized mice. Glutamate recordings support elevated stimulus-evoked glutamate release in the DG and CA3 of young APPNL-F/NL-F male mice that declined with age compared to age-matched control mice. Young female APPNL-F/NL-F mice exhibited increased glutamate clearance in the CA1 that slowed with age compared to age-matched control mice. Male and female APPNL-F/NL-F mice exhibited decreased CA1 basal glutamate levels, while males also showed depletion in the CA3. Cognitive assessment demonstrated impaired spatial cognition in aged male and female APPNL-F/NL-F mice, but only aged females displayed recognition memory deficits compared to age-matched control mice. These findings confirm a sex-dependent hyper-to-hypoactivation glutamatergic paradigm in APPNL-F/NL-F mice. Further, data illustrate a sexually dimorphic biological aging process resulting in a more severe cognitive phenotype for female APPNL-F/NL-F mice than their male counterparts. Research outcomes mirror that of human AD pathology and provide further evidence of divergent AD pathogenesis between sexes.

Knowledge of tuberculosis among physicians working at community health stations in Vietnam

Tuberculosis (TB) remains a significant health problem worldwide, including in Vietnam, where around 174,000 newly diagnosed cases and 13,200 patients died in 2018. There are challenges in the diagnostic process, treatment, and follow-up. The physicians with knowledge of TB working at commune health stations play an essential role in this struggle. The primary purpose of this study was to evaluate knowledge of TB and related factors among physicians working at community health stations in the Northern provinces of Vietnam. A cross-sectional survey was implemented on 335 physicians working at community health stations in 5 Northern provinces in Vietnam from September 2019 to October 2020. The result showed that the TB knowledge of physicians was not good. There were some severe knowledge gaps concerning at-risk groups, the main symptoms of TB, sputum tests for both diagnosis and follow-up and management of attack therapy. The TB training participants had better TB knowledge than others (aOR=1.68; 95%CI: 1.047-2.712). This study underlines the importance of clinical experience and TB training to TB knowledge. We suggest that a TB training plan is required for physicians. Our survey results could inform the process of defining the physicians who work at community health stations' role in TB management in the future.

An Updated Review on Molecular Biomarkers in Diagnosis and Therapy of Colorectal Cancer.

Colorectal cancer is one of the most common cancer types worldwide. Since colorectal cancer takes time to develop, its incidence and mortality can be treated effectively if it is detected in its early stages. As a result, non-invasive or invasive biomarkers play an essential role in the early diagnosis of colorectal cancer. Many experimental studies have been carried out to assess genetic, epigenetic, or protein markers in feces, serum, and tissue. It may be possible to find biomarkers that will help with the diagnosis of colorectal cancer by identifying the genes, RNAs, and/or proteins indicative of cancer growth. Recent advancements in the molecular subtypes of colorectal cancer, DNA methylation, microRNAs, long noncoding RNAs, exosomes, and their involvement in colorectal cancer have led to the discovery of novel biomarkers. In small-scale investigations, most biomarkers appear promising. However, large-scale clinical trials are required to validate their effectiveness before routine clinical implementation. Hence, this review focuses on small-scale investigations and results of big data analysis that may provide an overview of the biomarkers for the diagnosis, therapy, and prognosis of colorectal cancer.

An Adaptive Image Segmentation Network for Surface Defect Detection.

Surface defect detection plays an essential role in industry, and it is challenging due to the following problems: 1) the similarity between defect and nondefect texture is very high, which eventually leads to recognition or classification errors and 2) the size of defects is tiny, which are much more difficult to be detected than larger ones. To address such problems, this article proposes an adaptive image segmentation network (AIS-Net) for pixelwise segmentation of surface defects. It consists of three main parts: multishuffle-block dilated convolution (MSDC), dual attention context guidance (DACG), and adaptive category prediction (ACP) modules, where MSDC is designed to merge the multiscale defect features for avoiding the loss of tiny defect feature caused by model depth, DACG is designed to capture more contextual information from the defect feature map for locating defect regions and obtaining clear segmentation boundaries, and ACP is used to make classification and regression for predicting defect categories. Experimental results show that the proposed AIS-Net is superior to the state-of-the-art approaches on four actual surface defect datasets (NEU-DET: 98.38% ± 0.03%, DAGM: 99.25% ± 0.02%, Magnetic-tile: 98.73% ± 0.13%, and MVTec: 99.72% ± 0.02%).

AutoDLAR: A Semi-supervised Cross-modal Contact-free Human Activity Recognition System

WiFi-based human activity recognition (HAR) plays an essential role in various applications such as security surveillance, health monitoring, and smart home. Existing HAR methods, though yielding promising performance in indoor scenarios, highly depend on a massive labeled dataset for training which is extremely difficult to acquire in practical applications. In this paper, we present an automatic data labeling and HAR system, termed AutoDLAR. Taking a semi-supervised cross-modal learning framework with a hybrid loss function as the core, AutoDLAR transfers rich visual information to automatically label WiFi signals for WiFi-based HAR. Specifically, we devise a lightweight and multi-view WiFi sensing model with a parallel feature embedding method to accurately identify activities and accelerate recognition speed. Then, we exploit the video data to fine-tune a well-established visual HAR model, generating effective pseudo-labels for guiding the WiFi model’s training. We also build a synchronized Video-WiFi dataset with seven types of human activities under different scenarios to enable training and validating the semi-supervised HAR system. Extensive experiments on our collected activity dataset and the emotion recognition benchmark demonstrate that AutoDLAR attains an average accuracy of over 95.89% without manual labeling and only spends the inference time of 3.35 ms, outperforming the state-of-the-art (SOTA) methods.

Targeting Cysteine Proteases and their Inhibitors to Combat Trypanosomiasis.

Trypanosomiasis, caused by protozoan parasites of the Trypanosoma genus, remains a significant health burden in several regions of the world. Cysteine proteases play a crucial role in the pathogenesis of Trypanosoma parasites and have emerged as potential therapeutic targets for the development of novel antiparasitic drugs. This review article aims to provide a comprehensive overview of the role of cysteine proteases in trypanosomiasis and their potential as therapeutic targets. We discuss the biological significance of cysteine proteases in Trypanosoma parasites and their involvement in essential processes, such as host immune evasion, cell invasion, and nutrient acquisition. A comprehensive literature search was conducted to identify relevant studies and research articles on the role of cysteine proteases and their inhibitors in trypanosomiasis. The selected studies were critically analyzed to extract key findings and provide a comprehensive overview of the topic. Cysteine proteases, such as cruzipain, TbCatB and TbCatL, have been identified as promising therapeutic targets due to their essential roles in Trypanosoma pathogenesis. Several small molecule inhibitors and peptidomimetics have been developed to target these proteases and have shown promising activity in preclinical studies. Targeting cysteine proteases and their inhibitors holds great potential for the development of novel antiparasitic drugs against trypanosomiasis. The identification of potent and selective cysteine protease inhibitors could significantly contribute to the combat against trypanosomiasis and improve the prospects for the treatment of this neglected tropical disease.

Towards Antiviral Potential of Biomolecules Derived from Adhatod avasica as Competent Natural Molecules to Treat COVID-19 Virus Variant

Abstract: Adhatoda vasica (L.) (Acanthaceae) has essential therapeutic roles and is widely used in the indigenous medicine system or Ayurvedic system of medicine. The important goals of the present study are to report the in-silico anti-corona (COVID-19) activity of different phytochemicals present in A. vasica. This study will help to find specific bioactive compounds, and their use as anti- COVID-19 action for human welfare. A. vasica has chemical phytoconstituents with diverse pharmacological activities. These phytoconstituents have been found active against many diseases such as antibacterial, antitubercular, antivirus, antitussive, hepatoprotective, antiinflammatory, antiulcer, antiurolithiatic, abortifacient, radio modulator, cardio-protection, antidiabetic, antioxidant, anticancer, thrombolytic, antimutagenic, etc. Researchers have been lured to the use of natural and sustainable products with substantial therapeutic potential in the current climate of environmental preservation and safe use. These materials permit biological activity, safety, and compatibility with the environment. Using the SARS-CoV-2 spike receptor (6M0J), we evaluated Adhatoda vasica biomolecules for the Covid-19 variant (RBD- COV-2-S). This study is very encouraging and indicates that herbs should be studied more extensively for their therapeutic benefits.

Traffic-Aware Energy-Efficient Resource Allocation for RSMA Based UAV Communications

Traffic measurement will play an essential role in future networks to reveal the traffic requirements of the users, which will support network operations like resource allocation. In this paper, we study the traffic-aware resource allocation problem for downlink rate-splitting multiple access (RSMA) based unmanned aerial vehicle (UAV) communications. Specifically, with the help of traffic measurement, user requirements on achievable rate are known as prior knowledge to the UAV. Considering user requirements, we maximize the energy efficiency of the UAV by jointly optimizing the UAV deployment, beamforming, rate allocation, and subcarrier allocation. To overcome the non-convexity of the above problem, a joint optimization is developed to solve it iteratively. First, a heuristic approach is proposed to find the three-dimensional location of the UAV. Then, successive convex approximation approach is utilized to optimize RSMA parameters. Moreover, we formulate the subcarrier allocation problem as a many-to-one two-sided matching game, which is tackled by the swap matching algorithm. Numerical results suggest that the proposed subcarrier allocation scheme outperforms benchmark schemes, and RSMA based schemes perform close to that based on non-orthogonal multiple access, which all outperform orthogonal frequency division multiple access based scheme.

A New Grey Wolf Optimizer Tuned Extended Generalized Predictive Control for Distillation Process.

The distillation process plays an essential role in the petrochemical industry. However, the high-purity distillation column has complicated dynamic characteristics such as strong coupling and large time delay. To control the distillation column accurately, we proposed an extended generalized predictive control (EGPC) method inspired by the principles of extended state observer and proportional-integral-type generalized predictive control method; the proposed EGPC can adaptively compensate the system for the effects of coupling and model mismatch online and performs well in controlling time-delay systems. The strong coupling of the distillation column needs fast control, and the large time delay requires soft control. To balance the requirement for fast and soft control at the same time, a grey wolf optimizer with reverse learning and adaptive leaders number strategies (RAGWO) was proposed to tune the parameters of EGPC, and these strategies enable RAGWO to have a better initial population and improve its exploitation and exploration ability. The benchmark test results indicate that the RAGWO outperforms the existing optimizers for most of the selected benchmark functions. Extensive simulations show that the proposed method in terms of fluctuation and response time is superior to other methods for controlling the distillation process.

RICH1 is a novel key suppressor of isoproterenol‑ or angiotensin II‑induced cardiomyocyte hypertrophy.

Cardiac hypertrophy is one of the key processes in the development of heart failure. Notably, small GTPases and GTPase‑activating proteins (GAPs) serve essential roles in cardiac hypertrophy. RhoGAP interacting with CIP4 homologs protein 1 (RICH1) is a RhoGAP that can regulate Cdc42/Rac1 and F‑actin dynamics. RICH1 is involved in cell proliferation and adhesion; however, to the best of our knowledge, its role in cardiac hypertrophy remains unknown. In the present study, the role of RICH1 in cardiomyocyte hypertrophy was assessed. Cell viability was analyzed using the Cell Counting Kit‑8 assay and cells surface area (CSA) was determined by cell fluorescence staining. Reverse transcription‑quantitative PCR and western blotting were used to assess the mRNA expression levels of hypertrophic marker genes, such as Nppa, Nppb and Myh7, and the protein expression levels of RICH1, respectively. RICH1 was shown to be downregulated in isoproterenol (ISO)‑ or angiotensin II (Ang II)‑treated H9c2 cells. Notably, overexpression of RICH1 attenuated the upregulation of hypertrophy‑related markers, such as Nppa, Nppb and Myh7, and the enlargement of CSA induced by ISO and Ang II. By contrast, the knockdown of RICH1 exacerbated these effects. These findings suggested that RICH1 may be a novel suppressor of ISO‑ or Ang II‑induced cardiomyocyte hypertrophy. The results of the present study will be beneficial to further studies assessing the role of RICH1 and its downstream molecules in inhibiting cardiac hypertrophy.

Recent Advances in Molecular Imprinting for Proteins on Magnetic Microspheres.

The separation of proteins in biological samples plays an essential role in the development of disease detection, drug discovery, and biological analysis. Protein imprinted polymers (PIPs) serve as a tool to capture target proteins specifically and selectively from complex media for separation purposes. Whereas conventional molecularly imprinted polymer is time-consuming in terms of incubation studies and solvent removal, magnetic particles are introduced using their magnetic properties for sedimentation and separation, resulting in saving extraction and centrifugation steps. Magnetic protein imprinted polymers (MPIPs), which combine molecularly imprinting materials with magnetic properties, have emerged as a new area of research hotspot. This review provides an overview of MPIPs for proteins, including synthesis, preparation strategies, and applications. Moreover, it also looks forward to the future directions for research in this emerging field.

Across Time and Space: Senju ’s Approach for Scaling Iterative Stencil Loop Accelerators on Single and Multiple FPGAs

Stencil-based applications play an essential role in high-performance systems as they occur in numerous computational areas, such as partial differential equation solving. In this context, Iterative Stencil Loops (ISLs) represent a prominent and well-known algorithmic class within the stencil domain. Specifically, ISL-based calculations iteratively apply the same stencil to a multi-dimensional point grid multiple times or until convergence. However, due to their iterative and intensive nature, ISLs are highly performance-hungry, demanding specialized solutions. Here, Field Programmable Gate Arrays (FPGAs) represent a valid architectural choice as they enable the design of custom, parallel, and scalable ISL accelerators. Besides, the regular structure of ISLs makes them an ideal candidate for automatic optimization and generation flows. For these reasons, this article introduces Senju , an automation framework for the design of highly parallel ISL accelerators targeting single-/multi-FPGA systems. Given an input description, Senju automates the entire design process and provides accurate performance estimations. The experimental evaluation shows remarkable and scalable results, outperforming single- and multi-FPGA literature approaches under different metrics. Finally, we present a new analysis of temporal and spatial parallelism trade-offs in a real-case scenario and discuss our performance through a single- and novel specialized multi-FPGA formulation of the Roofline Model.

L’approche variationnelle de la rupture : un exemple de collaboration fructueuse entre mécaniciens et mathématiciens

This article reviews some important steps in the development and application of the variational approach to fracture. It emphasizes the essential role played by the permanent dialogue between mechanicians and applied mathematicians in bringing about this new paradigm and ensuring its undeniable success.

An All-Inclusive Taxonomy and Critical Review of Blockchain-Assisted Authentication and Session Key Generation Protocols for IoT

Authentication and Session Key Generation Protocols (SKGPs) play an essential role in securing the communication channels of connected Internet of Things (IoT) devices. Recently, through blockchain integration, scholars have tried to enhance the security and applicability of SKGPs. In brief, blockchain is a distributed ledger technology that can provide interesting features such as immutability, transparency, and accountability without any need for the active participation of trusted parties. This survey presents a comprehensive critical review of blockchain-assisted authentication and SKGPs, suggested for different IoT domains, including Internet of Vehicles, Internet of Drones, and Industrial IoT. Our survey categorizes existing schemes based on several criteria, including IoT application domains, security aspects, and blockchain components. By presenting an unbiased critical review and taxonomy of protocols, we aim to clarify the key challenges. Our review will specifically indicate what properties authors gained or lost through the integration of blockchain. To our best knowledge, this survey is the only one that offers all prerequisites for interested readers in blockchain-integrated SKGPs, such as security features and attacks, attack models, verification tools, blockchain types, blockchain platforms, and consensus mechanisms. Further, our survey elaborates existing research gaps in blockchain-assisted SKGPs. In doing so, we aim to guide future research in this field and provide researchers with the essential information they require.

Solvothermal synthesis of Bi12TiO20/Bi4Ti3O12 heterostructure with highly efficient photodegradation of MO under UV irradiation

The sillenite-structured bismuth titanate (Bi12TiO20) is thought to be a viable photocatalyst for environmental remediation. However, the performance of Bi12TiO20 as a photocatalyst is severely constrained by its limited range of light sensitivity and the rapid photoinduced electron-hole pair recombination. A practical and effective way to overcome these limitations is to combine Bi12TiO20 with adequate photocatalysts to create heterojunctions. Here, a one-step solvothermal technique is used to synthesize Bi12TiO20/Bi4Ti3O12 heterojunction (BTO). The electric field that exists between B12TiO20, Bi4Ti3O12 and the closed interfacial contacts had a synergistic effect on the constructed composites, which resulted in high charge transfer abilities. Therefore, the BTO heterojunction demonstrated increased photocatalytic efficacy in the presence of ultraviolet irradiation. The MO removal efficiency of optimal BTO was 97.15%, significantly higher than that of pure Bi2O3 (46.9%). Furthermore, the cycling experiment demonstrated that the BTO heterojunction is stable and reusable. The probable mechanism of photocatalytic MO oxidation over BTO heterojunction was studied by various scavengers. The •OH radicals and holes played essential roles in BTO system of photocatalytic oxidation process.

PH-Responsive Aminobenzocoumarins as Fluorescent Probes for Biological Acidity.

Regulation of pH plays an essential role in orchestrating the delicate cellular machinery responsible for life as we know it. Its abnormal values are indicative of aberrant cellular behavior and associated with pathologies including cancer progression or solid tumors. Here, we report a series of bent and linear aminobenzocoumarins decorated with different substituents. We investigate their photophysical properties and demonstrate that the probes display strong pH-responsive fluorescence "turn on" behavior in highly acidic environments, with enhancement up to 300-fold. In combination with their low cytotoxicity, this behavior enabled their application in bioimaging of acidic lysosomes in live human cells. We believe that these molecules serve as attractive lead structures for future rational design of novel biocompatible fluorescent pH probes.

Women and Members of Socially Diverse Groups in a Sport Management Program: Key Lessons From Creating and Leading a Student-Led Equity, Diversity, and Inclusion Club

This manuscript shares insights on the process of creating and operating a student-led equity, diversity, and inclusion (EDI) club centered in a sport management program through five reflective stories (i.e., three students and two faculty members). Sport Helps Everyone Make Allies is a student-led EDI club created at one of the largest sport-management-specific degree programs in North America. Based on critical reflections from the five stories, we identify key lessons for the creation and management of student-led EDI clubs: (a) resisting the chilly climate, (b) EDI initiatives within hierarchal systems, (c) EDI initiatives and the challenges of performative allyship, (d) EDI initiatives as agents of change, and (e) the essential role of faculty. By sharing our insights and reflections, we hope to help future social-justice-focused student groups navigate the development of a student-led EDI club.

تخامد لانداو للأمواج السوليتونية الصوتية الغبارية في بلازما غبارية غير شاملة

تم دراسة الأمواج السوليتونية الصوتية الغبارية تحت تأثير تخامد لانداو للبلازما الغبارية الفضائية تحوي أيونات خاضعة لتوزع سرعة غير شامل. قمنا بالتحقيق في تأثير تخامد لانداو والبارمتر غير الشامل على البنى السوليتونية الصوتية الغبارية من خلال الحل العددي لمعادلة كورديفيك- دي فريس المعدلة بحد تخامد لانداو. باستخدام طريقة الاضطراب الاختزالية قمنا باستنتاج معادلة كورتيفيك – دي فريس مع إضافة حد تخامد لانداو. أظهرت هذه الدراسة أنً كثافة حبيبات الغبار تلعب دوراَ أساسياً في ظهور أو عدم ظهور الأمواج السوليتونية DA في البلازما الغبارية، والتأثير الواضح للخاصية غير الشاملة للأيونات على ظاهرة تخامد لانداو للبنى اللاخطية المتشكلة في البلازما الغبارية. تفيد نتائج هذه الدراسة في محاولة فهم الآلية الفيزيائية للانتشار الأمواج السوليتونية تحت تأثير تخامد لانداو في بيئات البلازما المغبرة غير الشاملة كالمناطق الكوكبية، والأغلفة المغناطيسية، وبيئات البلازما الفضائية.