In this paper, we address the problem of compatibility between digital signature schemes and in-network aggregation approaches. In the IoT world, the gateways alter the signed network flows when performing in-network aggregation. Therefore, existing conventional approaches are not suitable for verifying the authenticity of the original flows. This raises the need for energy-effective and secure schemes that enable the destination to validate aggregated network flows. In this regard, a lightweight homomorphic signature scheme is proposed which supports the implementation of aggregation procedures without affecting the verification process. We demonstrate the unforgeability and the privacy of our scheme. We also perform an analytical study of its energy-efficiency. The results suggest that the proposed scheme considerably decreases the processing overhead of the existing set-homomorphic signature schemes. Moreover, it does not add any communication overhead to traditional (non-homomorphic) signature schemes. This, in turn, improves the energy consumption by 30% compared to existing homomorphic signature techniques.

Blockchain is the consensus-based technology to resolve the conflicts in Byzantine environments. Vehicles validate the messages received from the neighboring vehicles using Gradient Boosting Technique (GBT). Based on the validation results the message source vehicle generates the ratings that are to be uploaded to Road Side Units (RSUs) through that trust offset value can be calculated. All RSUs maintain the trust blockchain and each RSU tries to add their blocks to trust blockchain. We proposed a blockchain-based trust management model for VANET based on Tendermint. It eliminates the problem of malicious nodes entering the network and will also overcome the problem of power consumption. Simulation results also show that the proposed system is 7.8% and 15.6% effective and efficient in terms of Packet Delivery Ratio (PDR) and End-to-End Delay (EED) respectively to collect the trusted data between the vehicles.

Skin disease is a very common disease for humans. In the medical industry detecting skin disease and recognizing its type is a very challenging task. Due to the complexity of human skin texture and the visual closeness effect of the diseases, sometimes it is really difficult to detect the exact type. Therefore, it is necessary to detect and recognize the skin disease at its very first observation. In today's era, artificial intelligence (AI) is rapidly growing in medical fields. Different machine learning (ML) and deep learning(DL) algorithms are used for diagnostic purposes. These methods drastically improve the diagnosis process and also speed up the process. In this paper, a brief comparison between the machine learning process and the deep learning process was discussed. In both processes, three different and popular algorithms are used. For the machine Learning process Bagged Tree Ensemble, K-Nearest Neighbor (KNN), and Support Vector Machine(SVM) algorithms were used. For the deep learning process three pre-trained deep neural network models

The environmental and economic concern is the biggest challenge that concrete industry is facing today. Advancement in utilization of wastes in concrete as a mixture reduces usage of natural resources. Phyllite is a kind of foliated metamorphic rock generates during underground mining .Phyllite was calcined at 850 to 900oC in furnace and ground in ball mill. In this study, cement was partially replaced by weight with calcined phyllite to make M30 grade of concrete with 0% (Control mix), 2%, 4%, 6%, 8%, & 10%, (which are designated as M1, M2, M3, M4, M5 and M6). The laboratory tests such as slump value, compressive strength, flexural strength, water absorption, chloride ion penetration and durability in acidic and basic medium were conducted on the phyllite concrete and results are compared with the control mix. Through results it is concluded that cement can be replaced in concrete at the tune of 8% with Calcine Phyllite (CP) without affecting the strength and durability. The aim of the experiment is to find the maximum content of mines calcined Phyllite that can be used as a partial replacement of cement without compromising the quality on any of the characteristics of concrete.

The study, conducted at the Department of Medicine, Maulana Azad Medical College and associated Lok Nayak Hospital, aimed to investigate the prevalence of iron deficiency anaemia among anaemic overweight and obese individuals. Fifty participants were included after screening and consent, undergoing socio-demographic assessment, clinical evaluation, and laboratory investigations. Middle to old-aged individuals predominated (Mean ± SD: 54.54 ± 11.32 years), with females comprising 62%. All subjects were obese (mean BMI: 37.27 ± 5.71 kg/m²), with common comorbidities including hypertension (68%), diabetes (36%), and obstructive sleep apnea-hypopnea syndrome (32%). Nutritional deficiencies, particularly iron deficiency, were prevalent, affecting 62% of subjects, with 48% having iron deficiency alone. Anemia of chronic illness was observed in 38%. Laboratory parameters showed low hemoglobin (8.53 ± 1.23 g/dL), MCV (78.75 ± 10.13 fL), and elevated ESR (20.56 ± 21.47 mm/hour) and CRP levels (4.71 ± 3.32 mg/dL), indicating inflammation. Correlation analyses revealed negative associations between BMI and serum iron/ferritin and positive associations with serum hepcidin. The study underscores the significance of addressing nutritional deficiencies and monitoring iron status in obese populations, suggesting potential associations between obesity and iron metabolism. Further research is needed to explore these relationships for clinical management implications.

Neurodegeneration is an age-dependent progressive phenomenon with no defined cause. Aging is the main risk factor for neurodegenerative diseases. During aging, activated microglia undergoes phenotypic alterations that can lead to neuroinflammation, which is well accepted event in the pathogenesis of neurodegenerative diseases. Several common mechanisms are shared by genetically or pathologically distinct neurodegenerative diseases, such as excitotoxicity, mitochondrial deficits and oxidative stress, protein misfolding and translational dysfunction, autophagy and microglia activation. Progressive loss of neuronal population due to increased oxidative stress leads to neurodegenerative diseases mostly due to the accumulation of dysfunctional mitochondria. Mitochondrial dysfunction and excessive neuroinflammatory responses are both sufficient to induce pathology in age-dependent neurodegeneration. Therefore, mitochondrial quality control is key determinant for the health and survival of neuronal cells in the brain. Research has been primarily focused to demonstrate the significance of neuronal mitochondrial health, despite the important contributions of non-neuronal cells that constitutes significant portion of the brain volume. Moreover, mitochondrial morphology and function are distinctly diverse in different tissues; however, little is known about their molecular diversity among cell types. Mitochondrial dynamics and quality in different cell types markedly decides the fate of overall brain health, therefore it is not justifiable to overlook non-neuronal cells and their significant and active contribution in facilitating overall neuronal health. In this review article, we aim to discuss the mitochondrial quality control of different cell types in the brain and how important and remarkable is the diversity and highly synchronized connecting property of non-neuronal cells in keeping the neurons healthy to control neurodegeneration.

Daily rainfall data was collected for the arid district of Ananthapuramu, Andhra Pradesh state, India from 1981 to 2016 at the sub-district level and aggregated to monthly, annual and seasonal rainfall totals and the number of rainy days. The objective of this study is to evaluate the homogeneity, trend, and trend change points in the rainfall data. After quality checks and homogeneity analysis, a total of 27 rain gauge locations were considered for trend analysis. A serial correlation test was applied to all the time series to identify serially independent series. Non-Parametric Mann-Kendall test and Spearman’s rank correlation tests were applied to serially independent series. The magnitude of the trend was calculated using Sen’s slope method. For the data influenced by serial correlation, various modified versions of Mann-Kendall tests (Pre-Whitening, Trend Free Pre-Whitening, Bias Corrected Pre-Whitening and two variants of Variance Correction Approaches) were applied. A significant increasing summer rainfall trend is observed in 6 out of 27 stations. Significant decreasing trends are observed at two stations in the south-west monsoon season and at two stations in the north-east monsoon season. To identify the trend change-points in the time series, distribution-free Cumulative SUM test and sequential Mann-Kendall tests were applied. Two open-source library packages were developed in R language namely, ‘modifiedmk’ and ‘trendchange’ to implement the statistical tests mentioned in this paper. The study will benefit water resource management, drought mitigation, socio-economic development and sustainable agricultural planning in the region.

French bean (Phaseolus vulgaris L.) a member of family Leguminosae is a useful source of protein (∼22%), minerals (folate), vitamins and fibre. Abiotic and biotic stresses are the constraints to high yield and production of French bean. Varieties reluctant to diseases as well as abiotic stresses is among the top breeding objectives for the French bean. Mendelian ratios could know the genetically reliable forms of resistance, whereas it's more robust to understand the intricate kinds, often referred to as quantitative trait loci (QTL). Here, we review and compile the information from the studies related to the identification of QTLs for critical biofortification traits, biotic and abiotic stresses in French bean. Successful map-based cloning requires QTLs represent single genes which could be isolated in near-isogenic lines, and also the genotypes could be unambiguously inferred by progeny testing. Overall, this information will be useful for directing the French bean breeders to select a suitable method for the inheritance evaluation of quantitative traits and determining the novel genes in germplasm resources to ensure that much more potential of genetic information may be uncovered.

Background: The practices of various health-care professionals have been improvised to accommodate the on-going covid-19 pandemic situation. Different guidelines have been set in place to ease the process of re-opening of non-elective healthcare services like out-patient physiotherapy clinics. Although the measures taken should be guided by evidence based information, major consensus amongst practicing therapists needs to guide the India physiotherapy clinics. Objective: To identify and present the opinions of different physiotherapists about the various strategies for re-opening the out-patient physiotherapy clinics. Methods: An online cross-sectional survey was conducted. Over 169 participants were selected to participate in the survey according to the pre-decided inclusion and exclusion criteria. The data was collected and saved via google forms. Result and conclusion: A majority of respondents had a consensus over different strategies for re-opening the physiotherapy OPDs. These were regarding different measures to be adapted including modifications in the clinic infrastructure and the practice pattern. This would help in smoothly re-instating the physiotherapy services post the covid-19 lockdown.

Optical networks are prone to power jamming attacks intending service disruption. This paper presents a Machine Learning (ML) framework for detection and prevention of jamming attacks in optical networks. We evaluate various ML classifiers for detecting out-of-band jamming attacks with varying intensities. Numerical results show that artificial neural network is the fastest ($10^6$ detection per second) for inference and most accurate ($\approx 100 \%$) in detecting power jamming attacks as well as identifying the optical channels attacked. We also discuss and study a novel prevention mechanism when the system is under active jamming attacks. For this scenario, we propose a novel resource reallocation scheme that utilizes the statistical information of attack detection accuracy to lower the probability of successful jamming of lightpaths while minimizing lightpaths' reallocations. Simulation results show that the likelihood of jamming a lightpath reduces with increasing detection accuracy, and localization reduces the number of reallocations required.

In this paper, we investigate an animal-human cohabitation problem with the help of machine learning and fiber-wireless (FiWi) access networks integrating cloud and edge (fog) computing. We propose an early warning system which detects wild animals nearby road/rail with the help of wireless sensor networks and alerts passing vehicles of possible animal crossing. Additionally, we show that animals' detection at the earliest and the related processing, if possible, at sensors would reduce the energy consumption of edge devices and the end-to-end delay in notifying vehicles, as compared to the scenarios where raw sensed data needs to be transferred up the base stations or the cloud. At the same time, machine learning helps in classification of captured images at edge devices, and in predicting different time-varying traffic profiles-- distinguished by latency and bandwidth requirements-- at base stations, including animal appearance events at sensors, and allocating bandwidth in FiWi access networks accordingly. We compare three scenarios of processing data at sensor nodes, base stations and a hybrid case of processing sensed data at either sensors or at base stations, and showed that dynamic allocation of bandwidth in FiWi access networks and processing data at its origin leads to lowering the congestion of network traffic at base stations and reducing the average end-to-end delay.

The independent set, IS, on a graph $G=(V,E)$ is $V^{*}\subseteq V$ such that no two vertices in $V^{*}$ have an edge between them. The MIS problem on G seeks to identify an IS with maximum cardinality, i.e. MIS. $V^{*}\subseteq V$ is a vertex cover, i.e. VC of $G=(V,E)$ if every $e\in E$ is incident upon at least one vertex in $V^{*}$ . $V^{*}\subseteq V$ is dominating set, DS, of $G=(V,E)$ if $\forall v\in V$ either $v\in V^{*}$ or $\exists u\in V^{*}$ and $(u,v)\in E$ . The MVC problem on G seeks to identify a vertex cover with minimum cardinality, i.e. MVC. Likewise, MCV seeks a connected vertex cover, i.e. VC which forms one component in G, with minimum cardinality, i.e. MCV. A connected DS, CDS, is a DS that forms a connected component in G. The problems MDS and MCD seek to identify a DS and a connected DS i.e. CDS respectively with minimum cardinalities. MIS, MVC, MDS, MCV and MCD on a general graph are known to be NP-complete. Polynomial time algorithms are known for bipartite graphs, chordal graphs, cycle graphs, comparability graphs, claw-free graphs, interval graphs and circular arc graphs for some of these problems. We introduce a novel graph class, layered graph, where each layer refers to a subgraph containing at most some k vertices. Inter layer edges are restricted to the vertices in adjacent layers. We show that if $k=\Theta (log\mid V\mid )$ then MIS, MVC and MDS can be computed in polynomial time and if $k=O\left({(log\mid V\mid )}^{\alpha }\right)$ , where $\alpha <1$ , then MCV and MCD can be computed in polynomial time. If $k=\Theta \left({(log\mid V\mid )}^{1+ϵ}\right)$ , for $ϵ>0$ , then MIS, MVC and MDS require quasi-polynomial time. If $k=\Theta (log\mid V\mid )$ then MCV, MCD require quasi-polynomial time. Layered graphs do have constraints such as bipartiteness, planarity and acyclicity.

The master molecular regulators and mechanisms determining longevity and health span include nitric oxide (NO) and superoxide anion radicals (SOR). L-arginine, the NO synthase (NOS) substrate, can restore a healthy ratio between the dangerous SOR and the protective NO radical to promote healthy aging. Antioxidant supplementation orchestrates protection against oxidative stress and damage—L-arginine and antioxidants such as vitamin C increase NO production and bioavailability. Uncoupling of NO generation with the appearance of SOR can be induced by asymmetric dimethylarginine (ADMA). L-arginine can displace ADMA from the site of NO formation if sufficient amounts of the amino acid are available. Antioxidants such as ascorbic acids can scavenge SOR and increase the bioavailability of NO. The topics of this review are the complex interactions of antioxidant agents with L-arginine, which determine NO bioactivity and protection against age-related degeneration.

The master molecular regulators and mechanisms determining longevity and health span include nitric oxide (NO) and superoxide anion radicals (SOR). L-arginine, the NO synthase (NOS) substrate, can restore a healthy ratio between the dangerous SOR and the protective NO radical to promote healthy aging. Antioxidant supplementation orchestrates protection against oxidative stress and damage—L-arginine and antioxidants such as vitamin C increase NO production and bioavailability. Uncoupling of NO generation with the appearance of SOR can be induced by asymmetric dimethylarginine (ADMA). L-arginine can displace ADMA from the site of NO formation if sufficient amounts of the amino acid are available. Antioxidants such as ascorbic acids can scavenge SOR and increase the bioavailability of NO. The topics of this review are the complex interactions of antioxidant agents with L-arginine, which determine NO bioactivity and protection against age-related degeneration.

Inside Central Nervous System (CNS) appears neurons and glia cells. There are more glial cells than neurons and have more functions than neurons. Glia name represents different kind of cells, ones from neural origin (astrocytes, radial glia, and oligodendroglia), and others from blood monocytes (microglia). During ontogeny, neurons appear first (rat fetal 15th) and after astrocytes (rat fetal 21th) indicating a bigger importance function in the CNS. Also, during the phylogeny, reptiles have less astrocytes compared to neurons and in humans, astrocytes are double in number than neurons. This data, perhaps means that astrocytes are more special cells and work in memory and learning? Astrocytes have an important role in different mechanisms protecting CNS across the production of antioxidant and anti-inflammatory proteins, cleaning extracellular medium and helping neurons to communicate with each other correctly. Inflammatory mediators production are important to prevent changes in normal physiology. But, excessive or continue production leads to many diseases, such as Alzheimer's disease (AD), Sclerosis Lateral Amyotrophic (ELA), Multiple sclerosis (MS), and neurodevelopment diseases, like Bipolar disorder, Schizophrenia, and Autism's symptomatology. Different drugs and thecniques can reverse oxidative stress and/or inflammatory excess. This review is intended to serve as an approximation to the field.

During the most recent years, a lot of research has been done in creating robots with more self-governance so that they can overcome the challenges that real world environments present. The robot's limited versatility in real world applications can be overcome by the development of Legged robots. Also, as they permit movement in unavailable territory to robots with wheels, Legged Robots are more advantageous. But the potency of the legged robots explicitly its energy usage among alternate points of view really fall behind robots that use wheels. So, the present status of development, there are as yet a few perspectives that need to be analysed, optimized and enhanced. This paper presents review of literature of various biologically inspired legged robots, various techniques adopted for their analysis and optimization and the analysis and optimization of the ones that are not biologically inspired

Angiogenesis mediated by proteins such as Fibroblast Growth Factor – 2 (FGF-2) is a vital component of normal physiological processes and has also been implicated in contributing to disease state associated with various microbial infections. Previous studies by our group and others have shown that Candida albicans, a common agent of candidiasis, induces FGF-2 expression in vitro, and angiogenesis in brains and kidneys during systemic infections. However, the underlying mechanism(s) via which the fungus increases FGF-2 expression and the role(s) that FGF-2/angiogenesis plays in C. albicans disease remain unknown. Here we show, for the first time, that C. albicans hyphae (and not yeast cells) increase the FGF-2 response in human endothelial cells. Moreover, candidalysin, a toxin secreted exclusively by C. albicans in the hyphal state is required to induce this response. Our in vivo studies show that, in the systemic C. albicans infection model, mice treated with FGF-2 exhibit significantly higher mortality rates when compared to untreated mice not given the angiogenic growth factor. Even treatment with fluconazole could not fully rescue infected animals that were administered FGF-2. Our data suggest that the increase of FGF-2 production/angiogenesis induced by candidalysin contributes to the pathogenicity of C. albicans.

Infectious illnesses have always posed a threat to human health, with tuberculosis being a major concern. The use of various medications and antibiotics in the fight against such TB has led to the emergence of drug-resistant tuberculosis, which has become increasingly difficult to manage. While there have been a few studies and proposed conceptual models on how to manage and prevent various drug-resistant TB mutations and lineages, a model aimed at limiting and con-trolling such mutations in rural areas burdened with tuberculosis is lacking. This study seeks to map a model that is to be used to bridge the gap by facilitating the exchange of knowledge among healthcare professionals in healthcare facilities, diagnostic laboratories, and research institutes, particularly for underprivileged communities in the Eastern Cape. The model will also serve as a guide to monitor and evaluate epidemiological TB management plans.

Infectious illnesses have always posed a threat to human health, with tuberculosis (TB) being a major concern. The use of various medications and antibiotics in the fight against such illnesses has led to the emergence of drug-resistant infectious diseases, which have become increasingly dif-ficult to manage as medical and scientific research has advanced. Inadequate medical infrastruc-ture, incorrect treatment practices that exacerbate resistance patterns, and transmission within communities and healthcare facilities are the main factors contributing to the spread of drug-resistant TB. Though treating individuals with multiple drug resistance (MDR) and extreme drug resistance (XDR) strains is challenging, early identification of resistance and the imple-mentation of a well-designed treatment regimen can result in a cure. Community-based inter-ventions that address socioeconomic barriers to adherence can also enhance treatment outcomes. While there have been few studies and proposed conceptual models on how to manage and prevent various drug-resistant TB mutations and lineages, a model aimed at limiting and controlling such mutations has been developed. This paradigm seeks to bridge the gap by facilitating the exchange of knowledge among healthcare professionals (HCP) in healthcare facilities (HCF), diagnostic laboratories (DL), and research institutes (RI), particularly for underprivileged communities in the Eastern Cape. The model guide will also monitor and evaluate TB management plans

Over the years, machine learning has emerged as a tool for automated translation and has been studied relentlessly for decades. RBMT, SMT, and NMT models have been used to achieve machine translation and the results have drastically improved from when research in this field first began. Although a few general-purpose translators such as Google Translate or Microsoft Translator have accurate translations compared to that of a human translator, many pieces of text containing highly technical terms or homonyms are often mistranslated completely. When considering the necessity and importance of translating technical patents from different domains, accuracy in translation is not something that can be compromised. This motivates the need to improve the performance of machine translation further. The scope of this paper covers three open-source machine translation models for the purpose of patent documentation translation from English to Japanese, evaluates their performance on patent data, and proposes a methodology that enabled us to improve one of the model’s BLEU score by 41.22%, achieving a BLEU score of 46.18.

Transcription factors (TFs) are the regulatory proteins that act as molecular switches in controlling stress responsive gene expression. Among them MYB transcription factor family is one of the largest TF family in plants, playing a significant role in plant growth, development, phytohormone signaling and stress-responsive processes. Pearl millet (Pennisetum glaucum L.) is one of the most important C4 crop plant of the arid and semi-arid regions of Africa and South-east Asia for sustaining food and fodder productions. To explore the evolutionary mechanism and functional diversity of the MYB family in pearl millet, we conducted a comprehensive genome-wide survey and identified 279 MYB TFs (PgMYB) in pearl millet and distributed unevenly across seven chromosomes of pearl millet. Phylogenetic analysis of identified PgMYBs classified them into 18 subgroups and members of the same group showed a similar gene structure and conserved motif/s pattern. Further, duplication events were identified in pearl millet that indicated towards evolutionary progression and expansion of the MYB family. Transcriptome data and relative expression analysis by qRT-PCR identified differentially expressed candidate PgMYBs (PgMYB2, PgMYB9, PgMYB88 and PgMYB151) under dehydration, salinity, heat and phytohormones (ABA, SA and MeJA) treatment. Taken together, this study provides valuable information for a prospective functional characterization of MYB family members of pearl millet and genetic improvement of crop plants.

UEDVT still remains an underdiagnosed entity due to a significant percentage of patients who remain asymptomatic. The etiology of UEDVT is overwhelmingly attributed to secondary causes including but not limited to central venous access devices and malignancy. Treatment modalities include anticoagulation, catheter directed thrombolysis, percutaneous mechanical thrombectomy or a multimodality approach along with the management of underlying etiology. We describe a case of a female with breast cancer, who came with left UEDVT and CVC malfunction and was successfully treated using the ClotTriever system to maintain continuous intravenous access.

Neurodegenerative disorders such as Parkinson’s disease (PD), Alzheimer’s disease (AD), Amyloidal lateral sclerosis (ALS), and Huntington disease (HD) are the most concerned disorders due to the lack of effective therapeutics and dramatic rise in affected cases. Although these disorders have diverse clinical manifestations, yet they all share a common cellular stress response. These cellular stress responses including neuroinflammation, oxidative stress, proteotoxicity, and ER-stress, which combats with stress conditions, but the overwhelming cellular stress response induces cell damage. Small molecules such as flavonoids could reduce cellular stress and have gained much attention in recent years. Evidence has shown the potential use of flavonoids in several ways such as antioxidants, anti-inflammatory, and anti-apoptotic, yet their mechanism is still elusive. This review provides an insight into the mechanistic ways of flavonoids against cellular stress response that prevent the pathogenesis of neurodegenerative disorders.

Aquaporin-3 (AQP3) is one of the aquaglyceroporins, which is expressed in the basolateral layer of the skin membrane. Studies have reported that human skin squamous cell carcinoma overexpresses AQP3 and inhibition of its function may alleviate skin tumorigenesis. In the present study, we have applied a virtual screening method that encompasses filters for physicochemical properties and molecular docking to select potential hit compounds that bind to the Aquaporin-3 protein. Based on molecular docking results, the top 20 hit compounds were analyzed for stability in the binding pocket using unconstrained molecular dynamics simulations and further evaluated for binding free energy. Furthermore, examined the ligand-unbinding pathway of the inhibitor from its bound form to explore possible routes for inhibitor approach to the ligand-binding site. With a good docking score, stability in the binding pocket, and free energy of binding, these hit compounds can be developed as Aquaporin-3 inhibitors in the near future.

The increasing environmental and human health concerns associated with medical waste have led to the development of environmental biotechnology as a means of mitigating its negative effects. This review paper discusses the various types of medical waste generated in healthcare facilities, as well as the potential environmental and health impacts of improper handling and disposal. It also provides an overview of the different environmental biotechnologies that have been developed to treat medical waste, including bioreactor systems, microbial treatment, and composting. The benefits and drawbacks of these technologies are also discussed. Bioremediation is a promising environmental biotechnology that can be used to treat medical waste contaminated with hazardous chemicals. Case studies from around the world demonstrate the successful application of environmental biotechnologies to medical waste management. These case studies highlight the challenges encountered, the methods used, and the results obtained. The findings of this review paper highlight the need for a comprehensive strategy for managing medical waste that includes environmental biotechnologies. Further research and development are needed to improve the effectiveness, efficiency, and sustainability of medical waste management.

Background: Metastatic cancer is associated with an invariably fatal outcome. However, DeltaRex-G, a tumor- targeted retrovector encoding a CCNG1 inhibitor gene, has induced long term (>10 years) survival of patients with chemo-resistant metastatic pancreatic adenocarcinoma, MPNST, osteosarcoma, B-cell lymphoma, and breast carcinoma. Objective: To evaluate the level of CCNG1 expression in tumors as a potential biomarker for CCNG1 inhibitor therapy. Methods: CCNG1 RNA expression levels were measured in tumors (TCGA, N=9161), adjacent “tissues” (TCGA, N=678) and GTEx normal tissues (N=7187) across 22 organ sites. Differential expression of CCNG1 and Ki-67 in primary (N= 9161) vs metastatic (N= 393) tumors were also compared and particularly in primary (N=103) vs. metastatic (N=367) skin cancer (i.e., melanoma). Results: Enhanced CCNG1 RNA and protein expression were noted in tumors compared to normal analogous counterparts, and CCNG1 expression correlated significantly with that of Ki-67. Further, CCNG1 expression tended to be higher than that of Ki-67 in metastatic vs primary tumors, particularly in skin cancer (melanoma). Conclusions: Taken together, these data indicate that (1) CCNG1 expression is frequently enhanced in tumors when compared to their normal analogous counterparts, (2) CCNG1 and Ki-67 expressions are higher in metastatic vs primary tumors, (3) CCNG1 expression is significantly correlated with that of Ki-67, and (4) CCNG1 may be a stronger marker of metastasis than Ki-67. Phase 2 studies are planned to identify patients who are likely to respond favorably to CCNG1 inhibitor therapy by correlating treatment outcome parameters with CCNG1 expression levels in various cancer types.

Bio-molecular reagents like antibodies required in experimental biology are expensive and their effectiveness, among other things, is critical to the success of the experiment. Although such resources are sometimes donated by one investigator to another through personal communication between the two, there is no previous study to our knowledge on the extent of such donations, nor a central platform that directs resource seekers to donors. In this paper, we describe, to our knowledge, a first attempt at building a web-portal titled Bio-Resource Exchange that attempts to bridge this gap between resource seekers and donors in the domain of experimental biology. Users on this portal can request for or donate antibodies, cell-lines and DNA Constructs. This resource could also serve as a crowd-sourced database of resources for experimental biology. Further, in order to index donations outside of our portal, we mined scientific articles to find instances of donations of antibodies and attempted to extract information about these donations at the finest granularity. Specifically, we extracted the name of the donor, his/her affiliation and the name of the antibody for every donation by parsing the acknowledgements sections of articles. To extract annotations at this level, we propose two approaches – a rule based algorithm and a bootstrapped relation learning algorithm. The algorithms extracted donor names, affiliations and antibody names with average accuracies of 57% and 62% respectively. We also created a dataset of 50 expert-annotated acknowledgements sections that will serve as a gold standard dataset to evaluate extraction algorithms in the future. Contact: madhavi@pitt.edu, madhavi@cs.cmu.edu Database URL: http://tonks.dbmi.pitt.edu/brx Supplementary information: Supplementary data are available at Database online.

SARS-CoV-2 is a newly emerging, highly transmissible, and pathogenic coronavirus in humans, which has caused global public health emergency and economic crisis. To date, millions of infections and thousands of deaths have been reported worldwide, and the numbers continue to rise. Currently, there is no specific drug or vaccine against this deadly virus; therefore, there is a pressing need to understand the mechanism through which this virus enters the host cell. Viral entry into the host cell is a multistep process in which SARS-CoV-2 utilizes the receptor binding domain of the spike glycoprotein (S) to recognize ACE2 receptors on the human cells; this initiates host cell entry by promoting viral-host cell membrane fusion through large scale conformational changes in the S protein. Receptor recognition and fusion are critical and essential steps of viral infections and are key determinants of the viral host range and cross-species transmission. In this review, we summarize the current knowledge on the origin and evolution of SARS-CoV-2 and the roles of key viral factors. We discuss the RNA dependent RNA polymerase structure of SARS-CoV-2, its significance in drug discovery, and explain the receptor recognition mechanisms of coronaviruses. We provide a comparative analysis of the SARS-CoV and SARS-CoV-2 S proteins, receptor-binding specificity, and discuss the differences in their antigenicity based on biophysical and structural characteristics.

Tuberculosis (TB), an infectious airborne disease caused by Mycobacterium tuberculosis (Mtb), is a serious public health threat reported as the leading cause of morbidity and mortality worldwide. South Africa is a high TB burden country with TB being the highest infectious disease killer. The study investigated the distribution and clustering of Mtb mutations and spoligotypes in rural Eastern Cape Province. The Mtb isolates included were 1,157 from DR-TB patients and analysed by LPA followed by spoligotyping of 441 isolates, of these, 36 were whole genome sequenced. Distribution of mutations and spoligotypes was done by spatial analysis and clustering analysis was done by Bayesian model-based clustering of allele frequencies at heterozygous sites, using Mclust package in R. The rpoB gene had highest number of mutations. The distribution of rpoB and katG mutations was more prevalent in four health care facilities, inhA mutations were more prevalent in three healthcare facilities and heteroresistant isolates were more prevalent in five healthcare facilities. The Mtb was genetically diverse with Beijing more prevalent and largely distributed. Spatial analysis and mapping of gene mutations and spoligotypes revealed better picture of distribution. Clustering of isolates indicates that there is transmission of mixed infection in this area.

Three different populations of sulfated polysaccharides can be found in the cell wall of the red alga Botryocladia occidentalis. In a previous work, the structures of the two more sulfated polysaccharides were revised. In this work, NMR-based structural analysis was performed on the least sulfated polysaccharide and its chemically modified derivatives. Results have revealed the presence of both 4-linked α- and 3-linked β-galactose units having the following chemical features: more than half of the total galactose units are not sulfated, the α-units occur primarily as 3,6-anhydro-galactose units either 2-O-methylated or 2-O-sulfated, and the β-galactose units can be 4-O-sulfated or 2,4-O-disulfated. SPR-based results indicated weaker binding of the least sulfated galactan to thrombin, factor Xa, and antithrombin, but stronger binding to heparin cofactor II than unfractionated heparin. This report together with our previous publication completes the structural characterization of the three polysaccharides found in the cell wall of the red alga B. occidentalis and correlates the impact of their composing chemical groups with the levels of interaction with the blood co-factors.

Infectious illnesses have always posed a threat to human health, with tuberculosis being a major concern. The use of various drugs in the fight against such TB has led to the emergence of drug-resistant tuberculosis, which has become increasingly difficult to manage. While there have been a few studies and proposed conceptual models on how to manage and prevent various drug-resistant TB mutations and lineages, a model aimed at limiting and controlling such mutations in rural areas burdened with tuberculosis is lacking. This study seeks to map a model that is to be used to bridge the gap by facilitating the exchange of knowledge among healthcare professionals in healthcare facilities, diagnostic laboratories, and research institutes, particularly for underprivileged communities in the Eastern Cape. The model information is based on three published manuscripts; therefore, this is a follow-up study. The model will also serve as a practical guide to monitor and evaluate epidemiological TB management plans.

An essential metric for determining the efficacy of tuberculosis (TB) control programs is the evaluation of TB treatment outcomes. Assessing treatment outcomes is fundamental to facilitating the End TB Strategy set target. Clinic records from 457 patients with DR-TB were examined for data collection while 101 patients were followed up prospectively. Data were analyzed using Stata version 17.0. The odds ratio and 95% confidence interval were calculated to check the association between variables. P ≤ 0.05 was con-sidered statistically significant. Of the 427 participants, 65.8% had successful treatment whilst 34.2% had unsuccessful TB treatment. A total of 61.2% and 39% of the HIV-positive and HIV-negative participants had a successful TB treatment whilst 66% and 34% of both HIV-negative and positive participants had unsuccessful TB treatment. From 101 patients that were followed up, smokers had longer treatment outcomes compared to non-smokers. In the study with HIV/TB co-infection, men predominated. HIV and tuberculosis co-infection made therapy difficult with unfavorable effects on TB management. The treatment success rate (65.8%) is lower than the WHO threshold standard with a high proportion of patients lost to follow-up. The co-infection of tuberculosis and HIV resulted in undesirable treatment outcomes. Strengthening TB surveillance and control is recommended.

In comparison to the general population, lung cancer patients are more likely to suffer from severe Coronavirus disease (COVID-19) and mortality associated with it. Considering this increased risk, and in order to prevent symptoms and severe disease, patients with lung cancer have been prioritized for COVID-19 vaccinations, primary and booster doses. Despite this, the pivotal clinical trials did not include these patients, which leaves open questions regarding vaccine efficacy and humoral immune response. This review outlines the findings of recent investigations into the humoral responses of lung cancer patients to COVID-19 vaccination, particularly the primary doses and first boost.

To understand the physiological basis of tolerance to combined stresses to low phosphorus (P) and drought in mungbean (Vigna radiata (L.) R. Wilczek), a core set of 100 accessions were evaluated in hydroponics at sufficient (250 μM) and low (3 μM) P, and exposed to drought (dehydration) stress. The principal component analysis and ranking of accessions based on relative values revealed that IC280489, EC397142, IC76415, IC333090, IC507340 and IC121316 performed superior while IC119005, IC73401, IC488526 and IC325853 performed poorly in all treatments. Selected accessions were evaluated in soil under control (sufficient P, irrigated), low P (without P, irrigated), drought (sufficient P, withholding irrigation) and combined stress (low P, withholding irrigation). Under combined stress, a significant reduction in gas exchange traits (photosynthesis, stomatal conductance, transpiration, instantaneous water use efficiency), P uptake in seed and shoot was observed under combined stress as compared to individual stresses. Among accessions, IC488526 was most sensitive while IC333090 and IC507340 exhibited tolerance to individual or combined stress. The water balance and low P adaptation traits like membrane stability index, relative water content, specific leaf weight, organic acid exudation, biomass, grain yield and P uptake can be used as physiological markers to evaluate for agronomic performance. Accessions with considerable resilience to low P and drought stress can be either used as ‘donors’ in Vigna breeding program or cultivated in areas with limited P and water availability or both.

Powdery mildew (PM), caused by the fungal pathogen Blumeria graminis f. sp. tritici (Bgt), significantly threatens global bread wheat production. Although the use of resistant cultivars is an effective strategy for managing PM, currently available wheat cultivars lack sufficient levels of resistance. To tackle this challenge, we conducted a comprehensive genome-wide association study (GWAS) using a diverse panel of 286 bread wheat genotypes. Over three consecutive years (2020-21, 2021-22, and 2022-23), these genotypes were extensively evaluated for PM severity under field conditions following inoculation with virulent Bgt isolates. The panel was previously genotyped using the Illumina 90K SNP Infinium iSelect SNP assay to obtain genome-wide SNP marker coverage. By applying FarmCPU, a multilocus mixed model, we identified a total of 113 MTAs located on chromosomes 1A, 1B, 2B, 3A, 3B, 4A, 4B, 5A, 5B, 6B, 7A, and 7B at a significance level of p≤0.001. Notably, four novel MTAs on chromosome 6B were consistently detected in 2020-21 and 2021-22 environments. Furthermore, within the confidence intervals of the identified SNPs, we identified 96 candidate genes belonging to different proteins including 12 disease resistance/host-pathogen interactions related protein families. Among these, protein kinases, leucine-rich repeats, and zinc finger proteins, were of particular interest due to their potential roles in PM resistance. These identified loci can serve as targets for breeding programs aimed at developing disease-resistant wheat cultivars.

Natural selection is commonly seen not just as an explanation for adaptive evolution, but as the inevitable consequence of “heritable variation in fitness among individuals”. Although it remains embedded in biological concepts, such a formalisation makes it tempting to explore whether this precondition may be met not only in life as we know it, but also in other physical systems. This would imply that these systems are subject to natural selection and may perhaps be investigated in a biological framework, where properties are typically examined in light of their putative functions. Here we relate the major questions that were debated during a three-day workshop[1] devoted to discussing whether natural selection may take place in non-living physical systems. We start this report with a brief overview of research fields dealing with “life-like” or “proto-biotic” systems, where mimicking evolution by natural selection in test tubes stands as a major objective. We contend the challenge may be as much conceptual as technical. Taking the problem from a physical angle, we then discuss the framework of dissipative structures. Although life is viewed in this context as a particular case within a larger ensemble of physical phenomena, this approach does not provide general principles from which natural selection could be derived. Turning back to evolutionary biology, we ask to what extent the most general formulations of the necessary conditions or signatures of natural selection may be applicable beyond biology. In our view, such a cross-disciplinary jump is in large part impeded by reliance on individuality as a central yet implicit and loosely defined concept. Overall, these discussions thus lead us to conjecture that understanding, in physico-chemical terms, how individuality emerges and how it can be recognised, will be essential in the search for instances of evolution by natural selection outside of living systems. [1] Natural Selection Beyond Life? Observing the physico-chemical world through Darwinian glasses; 12-15 November 2019 - Institut d'Etudes Scientifiques, Cargèse, France

Industrial effluents contain contaminants that pose threats to the environment and human health. Bioremediation is an environmentally friendly, sustainable, and cost-effective approach to degrade or transform pollutants using microbial enzymes. Laccase is a versatile enzyme that oxidizes a wide range of substrates, such as dyes, phenolic compounds, pesticides, and polycyclic aromatic hydrocarbons (PAHs), with the consumption of molecular oxygen. Laccase can also remove heavy metals by forming complexes with organic ligands or reducing them to fewer toxic forms. However, the application of laccase in bioremediation is limited by its low production, stability, and specificity. Recombinant technology has been employed to enhance the expression, activity, and stability of laccase in various bacterial hosts. Immobilization techniques have been developed to improve the reusability and stability of laccase in different environmental conditions. This review summarizes the recent developments in the production optimization of recombinant laccase enzymes and their role in the bioremediation of industrial effluents. It also discusses the challenges of laccase-based biocatalytic systems for environmental cleanup.

Dietary factors play an important role in shaping the gut microbiome which, in turn, regulates the molecular events in colonic mucosa. The composition and resulting metabolism of the gut microbiome have been implicated in the development of colorectal cancer (CRC). Diets low in dietary fibers and phytomolecules as well as other lifestyle-related factors may predispose to CRC. Emerging evidence demonstrates that the predominance of microbes, such as Fusobacterium nucleatum, can predispose the colonic mucosa to malignant transformation. Dietary and lifestyle modifications have been demonstrated to restrict the growth of potentially harmful opportunistic organisms. In this study, we aim to present evidence regarding the relationship of dietary factors to the gut microbiome and development of CRC.

Drug-resistant tuberculosis (DR-TB) is still a major public health concern in South Africa. Mutations in M. tuberculosis can cause varying levels of phenotypic resistance to anti-TB medications. There have been no prior studies on gene mutations and the genotyping of DR-TB in the rural Eastern Cape Province; hence we aimed to identify DR-TB mutations, genetic diversity and allocated lineages among patients in this area. Using Xpert® MTB/RIF, we assessed the rifampin-resistance of sputum samples collected from 1157 patients suspected of having tuberculosis. GenoType MTBDR plus VER 2.0 was used for the detection of mutations causing resistance to anti-TB medications. The next step was to spotlight type 441 isolates. The most prevalent rifampin resistance-conferring mutations were in rpoB codon S531L, in INH-resistant strains, katG gene at codon S315TB and the inhA gene at codon C-15TB had highest mutations; 54.5% and 24.7%, respectively. In addition, 24.6% of strains showed mutations in both the rpoB and inhA genes, while 69.9% of strains showed mutations in both the katG and rpoB genes. Heteroresistance was seen in 17.9% of all cases in the study. According to spoligotyping analysis, Beijing families predominated. Investigating the evolutionary lineages of M. tuberculosis isolates can be done using the information provided by the study's diversity of mutations. In locations where these mutations have been discovered, decision-making regarding standardization of treatment regimens or individualized treatment may be aided by the detection frequency of rpoB, katG, and inhA mutations in various study areas.

The ongoing evolution of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has resulted in the recent emergence of a highly divergent variant of concern (VOC) defined as Omicron or B.1.1.529. This VOC is of particular concern because it has the potential to evade most therapeutic antibodies and has undergone a sustained genetic evolution, resulting in the emergence of five distinct sub-lineages. However, the evolutionary dynamics of initially identified Omicron BA.1 and BA.2 sub-lineages remain poorly understood. Herein, we combined Bayesian phylogenetic analysis, mutational profiling, and selection pressure analysis to track virus genetic changes that drive the early evolutionary dynamics of the Omicron. Based on the Omicron dataset chosen for the improved temporal signals and sampled globally between November 2021 and January 2022, most recent common ancestor (tMRCA) and substitution rates for BA.1 were estimated to be 18 September 2021 (95% highest posterior density (HPD) 04 August – 22 October 2021) and 1.435×10-3 (95% HPD = 1.021×10-3 – 1.869×10-3) substitution/site/year, respectively, whereas 03 November 2021 (95% highest posterior density (HPD) 26 September – 28 November 2021) and 1.074×10-3 (95% HPD = 6.444×10-4 – 1.586×10-3) substitution/site/year for BA.2 sub-lineage. The findings of this study suggest that the Omicron BA.1 and BA.2 sub-lineages originated independently and evolved over time. Furthermore, we identified multiple sites in spike protein undergoing continued diversifying selection that may alter the neutralization profile of BA.1. This study shed light on the ongoing global genomic surveillance and Bayesian molecular dating analyses to better understand the evolutionary dynamics the virus and, as a result, mitigate the impact of emerging variants on public health.

Two putative boar pheromones (Androstenone and Androstenol) were discovered in endangered mouse deer during captive breeding program. This study further examined the molecular characteristics, pheromone synthesis pathway, and the functional role of these pheromones in reproduction of mouse deer. CYP17A1 and CYB5 genes were cloned and expressed in HEK-293, COS-7 cell lines and gonads of mouse deer to investigate CYP17A1 gene’s andien-β-synthase activity towards synthesis of sex pheromones in mouse deer. An enzyme immunoassay was also developed and standardized to measure the fecal androstenone during reproductive cycles of mouse deer. Results showed that mouse deer’s CYP17A1 gene possesses andien-β-synthase activity and could transform pregnenolone into 5,16-androstadien-3β-ol. The expression of CYP17A1 gene upregulated in the testis and ovary, compared to other tissues in mouse deer. Significantly elevated pheromones and estrogens were recorded prior to delivery and postpartum estrus / mating in mouse deer. Further, there were weak correlations between fecal pheromones and estrogens/ androgens in mouse deer during breeding season. The findings suggest that the boar pheromones might play a direct role in the reproductive activities of mouse deer which might be used for breeding of mouse deer elsewhere.

To meet an ever global population's food demand, crop yields must be sustained and increased. Drought, which is getting harsher as a result of global warming, is largely impeding the agricultural productivity. Maize is widely used as food and animal feed in many regions of the world, but its yields are largely effected by drought and heat stress. Historical data on climate change predicts that drought and heat stress becoming major threat for maize cultivation in coming years, which will have huge impact on food security of the world especially in Africa and Asia. Thus there is an immense necessary to develop drought tolerant and climate resilient maize to feed the predicted population of the world. Availability and accessibility of crop genetic resources plays a huge role in development of drought-tolerant maize cultivars. A huge genetic resources of maize, including its landraces and crop wild relatives (CWR) have been reported naturally and many of them have stored in National and International gene banks globally. Conventional breeding methods have been tremendously increased maize yields, but these methods frequently fall short of achieving the demand for improved drought stress resistance. In this article, we have briefly discussed about impact of climate variability on crop production, maize yield losses due to drought, drought tolerance in maize landraces and CWR, and origin and evolution of Mexican landraces. This information may help in utilization of these potential resources in various pre-breeding programs.

Background: The use of animal models for biomedical research provides us with a convenient and feasible route to establish causal relationships by recapitulating the temporal sequence of events in a controlled environment with a potential to manipulate the variables at multiple levels including genetic, protein, physiological or environmental. Objectives: The current review was conducted to gain insights into various animal models for the SARS-CoV-2 virus. Material and Methods: A literature review (PUBMED, PUBMED Central, PMC, Google Scholar, Google search engine) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines performed in early April 2020 revealed 9 articles of interest. Search terms included covid 19, covid-19, novel corona virus, SARS-CoV-2, animal models, experimental models, laboratory models & covid 19 animal models. Two independent reviewers extracted the data; the third reviewer was involved in case of discrepancy. Results: SARS-CoV-2 shares an identical receptor binding domain with the SARS-CoV virus and has a superior binding affinity to the host ACE2. Based on this, the role of rhesus macaques, golden Syrian hamsters, transgenic hACE2 mice and ferrets as animal models have been studied. All four animals are susceptible to infection with SARS-CoV-2 with variable clinical presentation but universal recovery. The respiratory tract is primarily involved in all four models. Involvement of intestines was also seen in at least one study in each animal. Transfer to naïve animals in close contact has been documented in case of hamsters and ferrets. Seroconversion was documented in all although the role of convalescent sera was tested in hamsters only, with positive results though. Air-borne transmission was documented in ferrets and the possibility of feco-oral transmission was suggested for hamsters. The possibilities of recurrence and re-infection were ruled out by experiments upon the rhesus macaques. The fulfilment of Koch’s postulates has been highlighted. Discussion: The various studies available on animal models have been able to establish models of infection and transmission that recapitulate different aspects of disease in humans. However, the response between different animals and the same animal in different experiments is not completely coherent. Some of them do not manifest the disease clinically while others behave differently at molecular and immunological levels. Moreover, the physiology of these animals is not identical to human beings and the findings may not be extrapolated to human beings in an ‘as-is’ manner. Conclusions: The review acknowledges the achievements made by these experiments in a short span of time and highlighted the urgent need for a deeper dive in search of a quintessential animal model which can be studied for efficacy and safety of newer drugs and vaccines before a make-shift from the petri-dish to the human body can be contemplated.

Background: There are no known medicines or vaccines to control the COVID-19 pandemic caused by SARS-CoV-2 (nCoV). Antiviral peptides are superior to conventional drugs and may also be effective against COVID-19. Hence, we investigated the SARS-CoV-2 Spike RBD (nCoV-RBD) that interacts with hACE2 for viral attachment and entry. Methods: Three strategies and bioinformatics approaches were employed to design potential nCoV-RBD - hACE2 interaction-blocking peptides that may restrict viral attachment and entry. Firstly, the key residues interacting with nCoV-RBD - hACE2 are identified and hACE2 sequence based peptides are designed. Second, peptides from five antibacterial peptide databases that block nCoV-RBD are identified; finally, a chimeric peptide design approach is used to design peptides that can bind to key nCoV-RBD residues. The final peptides are selected based on their physiochemical properties, numbers and positions of key residues binding, binding energy, and antiviral properties. Results: We found (i) three amino acid stretches in hACE2 interact with nCoV-RBD; (ii) effective peptides must bind to three key positions of nCoV-RBD: Gly485/Phe486/Asn487, Gln493, and Gln498/Thr500/Asn501; (iii) Phe486, Gln493, and Asn501 are critical residues; (iv) AC20 and AC23 derived from hACE2 may block two key critical positions; (iv) DBP6 identified from databases can block the three sites of the nCoV-RBD interacting with one critical position Gln498; (v) seven chimeric peptides were considered promising among which cnCoVP-3, cnCoVP-4, and cnCoVP-7 are the top three; and (vi) cnCoVP-4 meets all the criteria and is the best peptide. Conclusion: All the ten peptides need experimental validation for their therapeutic efficacy.

Inflammation is considered an important target for stroke therapy because it induces secondary brain damage after the initial ischemic insult. Peripheral monocytes migrate to the brain parenchyma after a central insult. They then differentiate to macrophages in a positive feedback fashion contributing to damage instead of ischemic resolution and inflammation control. A cyclic diterpenoid, (1S,2E,4R,6R,7E,11E)-cembra-2,7,11-triene-4,6-diol (4R), decreases neurodegeneration after ischemia with central anti-inflammatory activity. This study aims to determine whether the central anti-inflammatory effect of 4R is effective against peripheral inflammation triggered by brain ischemia. To investigate the anti-inflammatory effect of 4R, we treated macrophages with lipopolysaccharide (LPS) as an inflammatory model, followed by treatment with 4R. Microarray transcriptome analysis of over 30,000 genes identified the differential expression of 393 genes. Genes related to inflammation, cell adhesion, and transcription were validated with qPCR, and reduced expression was determined. Quantification of NF-kB phosphorylation served as a marker for the modulation of inflammation through gene transcription. Our results show that 4R was associated with a reduction in NFKB1 and ITGB5 gene expression, increased phosphorylation of NF-kB, and a decrease in macrophage adhesion in a blood-brain barrier model. These results indicate that 4R can partially modulate the peripheral immune response, making 4R a potential drug against post-ischemic inflammation.

Ranolazine (Rn) is a drug used to treat persistent chronic coronary ischemia. It has also been shown to have therapeutic benefits on the central nervous system and an anti-diabetic effect by lowering blood glucose levels and however, no effects of Rn on cellular sensitivity to insulin (Ins) have been demonstrated yet. The present study aimed to investigate the permissive effects of Rn on the actions of Ins in astrocytes in primary culture. Ins at 10-8 M, Rn (10-6 M) and Ins+Rn (10-8 M and 10−6 M respectively) were added to astrocytes during 24 h. In comparison to control cells, Rn and/or Ins caused modifications in cell viability and proliferation. p-AKT, p-ERK, p-eNOS, Mn-SOD, COX-2, and the anti-inflammatory protein COX-2 were all upregulated by ins. On the contrary, no significant changes were found in the protein expression of Cu/Zn-SOD, NF-κB and IκB. The presence of Rn produced an increase in p-ERK protein and a significant decrease in COX-2 protein expression. Furthermore, Rn significantly increased the effects of Ins on the expression of p-AKT, p-eNOS, p-ERK, Mn-SOD, and PPAR-γ. On the other hand, Rn+Ins produced a significant decrease in COX-2 expression. In conclusion, Rn facilitated the effects of insulin on the p-AKT, p-eNOS, p-ERK, Mn-SOD and PPAR-γ, signaling pathways, as well as on the anti-inflammatory and antioxidant effects of the hormone.

Objectives: Evaluate hand-held echocardiography (HHE) performed and interpreted by trained Advanced Practice Providers (APPs) on hospitalized CHF patients for image quality and interpretation, by comparing against expert echocardiographer and SE findings. Background: Congestive heart failure (CHF) is associated with increased hospital admissions and mortality. While standard echocardiogram (SE) is the gold standard for cardiac assessment, it is not readily available. Hospitalized CHF patients require rapid assessment for expedited treatment. Methods: Over 6 months, five trained APPs performed HHE on hospitalized CHF patients and interpreted: a) Left ventricular (LV) size, b) LV ejection fraction (LVEF), and c) right atrial pressure (RAP). The study echocardiographer reviewed and blindly interpreted HHE images and compared with APPs and SE findings. Kappa-statistics determined the degree of agreement between APPs and study echocardiographer interpretation of HHE images and SE. Results: 80 CHF patients [age 73±14 years, 58% males; LVEF (by SE) 45±19%; 36.3% body mass indexes ≥30 kg/m2] were enrolled. HHE interpretation by APPs had good agreement for LVEF (kappa 0.79) with study echocardiographer and SE (kappa 0.74), and good agreement for RAP (kappa 0.67) with study echocardiographer. Correlation between absolute LVEF interpretation by study echocardiographer on HHE and SE was r=0.88 (p<0.0001). Conclusions: Trained APPs obtained diagnostic-quality HHE images and interpreted LV function and RAP in CHF patients, with good agreement with the study echocardiographer. LVEF by HHE correlated with LVEF by SE. Our study suggests trained APPs can use HHE to evaluate LVEF and RAP in CHF patients leading to expedited and optimized treatment.

Multidrug-resistant tuberculosis emerged as a serious challenge to tuberculosis management and control. In the Eastern Cape, the Beijing variants are prevalent and a driving force of multidrug-resistant tuberculosis; hence, we investigated the distribution of gene mutations in Beijing strains compared to non-Beijing strains. Multidrug-resistant tuberculosis and heteroresistant isolates were identified in 412 sputum cultures by drug susceptibility testing. The isolates were analyzed for mutations in three genes associated with resistance to antituberculosis first-line drugs: katG and inhA promoters for isoniazid and rpoB for rifampicin. All isolates were genotyped by spoligotyping. There were more males than females and a more economically active age group in the study. The most prevalent mutations in rpoB resistance were in S531L, katG in S315Tb, and inhA in c-15tb. Heteroresistance was found in 18 isolates. Beijing variants were predominant. Most of the heteroresistant isolates were INH, with heteroresistance occurring more in the inhA gene mutation region c-15tb. Beijing and LAM variants were found more frequently in INH heteroresistant isolates. Mutations in katG S315Tb and rpoB S531L were higher in Beijing variants. The Beijing family is a major contributor to the epidemiological picture and accounts for most of the multidrug-resistant tuberculosis in the study area.

Conservation Agriculture (CA) is capable of improving soil health and ecosystem functions. Soil carbon sequestration is one of the ecosystem processes that is of importance in sustainable land management involving reduction in greenhouse gas emissions and adaptation to climate change. In this study, we wanted to determine, during the first year of the process of establishing a CA cropping system in rain-fed areas in Madhya Pradesh state of India, which soil health indicators show measurable signs of improvement. Four field trials were selected, each comprising two neighboring plots. One plot (15×15 m) was managed conventionally under farmer practice and was tilled before sowing seeds, and in the adjacent plot Conservation Agriculture practices were applied. No mineral fertilizers or pesticides were applied in both treatments. Soil health indicators of soil aggregate stability, soil-atmosphere CO₂ fluxes, water infiltration, soil moisture, potentially mineralizable nitrogen, soil organic content and bulk density were measured. Results demonstrate that soil CO₂ emissions in CA soils decreased and soil aggregates stability improved in the first year. Generally, in CA soils, there were measurable improvements in all soil health indicators but only some of them were statistically significant.

Immunosuppressed kidney transplant (KT) recipients respond weaker to COVID-19 vaccination than immunocompetent individuals. We tested antiviral IgG response in 99 KT-recipients and 66 healthy volunteers who were vaccinated with mRNA-1273 Moderna or BNT162b2 Pfizer-BioNTech vaccines. A subgroup of participants had their peripheral blood leukocytes (PBLs) evaluated for the frequency of T helper 1 (Th1) cells producing IL-2, IFN-γ and/or TNF-α, and IL-10-producing T-regulatory 1 (Tr) cells. Among KT-recipients, 45.8% had anti-SARS-CoV-2 IgG compared to 74.1% of healthy volunteers (p=0.009); also, anti-viral IgG levels were lower in recipients than in volunteers (p=0.001). When defined as non-responders (≤2,000 U/ml IgG), Moderna’s group had 10.8% and Pfizer-BioNTech’s group had 34.3% of non-responders at 6 months (p=0.023); similarly, 15.7% and 31.3% non-responders were in Moderna and Pfizer-BioNTech groups at 12 months, respectively (p=0.067). There were no non-responders among controls. Healthy volunteers had higher Th1 levels than KT recipients, while Moderna produced higher Th1 response than Pfizer-BioNTech. In contrast, Pfizer-BioNTech vaccine induced higher Tr1 response than Moderna vaccine (p&lt;0.05); overall, IgG levels correlated with Th1(fTTNF-α)/Tr1(fTIL-10) ratios. We propose that the higher number of non-responders in Pfizer-BioNTech group than Moderna group was caused by more potent activity of regulatory Tr1 cells in KT-recipients vaccinated with Pfizer-BioNTech vaccine.

In the current scenario of changing climatic conditions and rising global population, there is always a need to explore novel, efficient, and economical natural products for the benefit of human kind. Biosurfactant is one of the latest explored microbial biomolecules that have been used in numerous fields, including agriculture, pharmaceuticals, cosmetics, food processing, and environment-cleaning industries as raw material, lubrication, wetting, foaming softening, making emulsions, and stabilizing dispersions. The amphiphilic nature of biosurfactant biomolecules showed great advantage, distributing themselves into two immiscible surfaces by reducing interfacial surface tension and increasing the solubility of hydrophobic compounds. Furthermore, their eco-friendly nature, low or even no toxic nature, durability at higher temperatures, and wide range of pH fluctuations making the microbial surfactants preferable compared to their chemical counterparts. Additionally, the biosurfactants can obviate the oxidation flow by eliciting the antioxidant property, antimicrobial, anticancer activity, and drug delivery system, further broadening their applicability in the food, pharmaceutical, and pharma industries. Nowadays, biosurfactant has been broadly utilized to improve the soil quality by improving the concentration of trace elements and mixed with pesticides or applied singly on the plant surfaces for plant disease management. In the present review, we summarise the latest aspect of microbial synthesized biosurfactant compounds, limiting factors of biosurfactant production, and their application in improving soil quality, plant disease management.

Background: SARS-CoV-2 that are the causal agent of a current pandemic are enveloped, positive-sense, single-stranded RNA viruses of the Coronaviridae family. Proteases of SARS-CoV-2 are necessary for viral replication, structural assembly and pathogenicity. The ~33.8KDa M^pro protease of SARS-CoV-2 is a non-human homologue and highly conserved among several coronaviruses indicating M^pro could be a potential drug target for Coronaviruses.Methods: Here we performed computational ligand screening of four pharmacophores (OEW, Remdesivir, Hydroxycholoquine and N3) that are presumed to have positive effects against SARS-CoV-2 M^pro protease (6LU7) and also screened 50,000 molecules from the ZINC Database dataset against this protease target.Results: We found 40 pharmacophore-like structures of natural compounds from diverse chemical classes that exhibited better affinity of docking as compared to the known ligands. The 10 best selected ligands namely, ZINC1845382, ZINC1875405, ZINC2092396, ZINC2104424, ZINC44018332, ZINC2101723, ZINC2094526, ZINC2094304, ZINC2104482, ZINC3984030, and ZINC1531664, are mainly classified as β-carboline, Alkaloids and Polyflavonoids, and all of them displayed interactions with dyad CYS145 and HIS41 from the protease pocket in a similar way as with other known ligands.Conclusion: Our results suggest that these 10 molecules could be effective against SARS-CoV-2 protease and may be tested in vitro and in vivo to develop novel drugs against this virus.

Structural variations (SVs) play a key role in the pathogenicity of hematological malignancies. Optical genome mapping (OGM) is an emerging technology that enables genome-wide detection of all classes of SVs at a high resolution and sensitivity. Identification of cryptic SVs leading to gene disruption or predicted novel gene fusions could be important drivers for cancer development and/or portend a prognostic relevance, which could be used to modify the treatment plan. A cohort of 106 consented cases that had a successful OGM analysis performed were included in the study. Demographic, clinical, laboratory and treatment data were collected. Routine diagnostic and prognostic testing were done on the peripheral blood and bone marrow aspirate as indicated. Additional samples of peripheral blood and/or bone marrow were sent for OGM testing. OGM led to a change in risk stratification in 17/66 (25.75%) of patients with hematological malignancies, the majority of these patients (15/66, 22.72%), having their risk stratification upgraded with a resulting change in treatment of 14 patients. This study highlights the ability of OGM to detect rare, cryptic and clinically relevant variants that potentially impact disease diagnosis, risk stratification and actionable treatment targets.

Patient access to new oncology drugs in Canada is only possible after navigating multiple sequential systemic checkpoints for national regulatory approval, health technology assessment (HTA) and collective government price negotiation. These steps delay access and prevent health care providers from being able to prescribe optimal therapy. Eighteen Canadian oncology clinicians from the medicine, nursing and pharmacy professions met to develop consensus recommendations for defining reasonable government performance standards around process and timeliness to improve Canadian cancer patients’ access to best care. A modified Delphi methodology was used to confirm strong consensus on 30 questions involving five themes: accountability, disparities, endpoints, timeliness, and cost-effectiveness. It was agreed that greater transparency is required across regulatory and HTA processes. Health professionals in oncology are frustrated for their patients because they are unable to deliver the modern guideline-supported therapies they want to provide due to delays in approval or funding. Canadian patients and their health care providers request improvements in timely access to life-saving therapeutics in line with other countries. Clinicians expect urgent improvements in our health systems to give our patients their best chance of survival.