Conditional spatial biased intuitionistic clustering technique for brain MRI image segmentation.

In clinical research, it is crucial to segment the magnetic resonance (MR) brain image for studying the internal tissues of the brain. To address this challenge in a sustainable manner, a novel approach has been proposed leveraging the power of unsupervised clustering while integrating conditional spatial properties of the image into intuitionistic clustering technique for segmenting MRI images of brain scans. In the proposed technique, an Intuitionistic-based clustering approach incorporates a nuanced understanding of uncertainty inherent in the image data. The measure of uncertainty is achieved through calculation of hesitation degree. The approach introduces a conditional spatial function alongside the intuitionistic membership matrix, enabling the consideration of spatial relationships within the image. Furthermore, by calculating weighted intuitionistic membership matrix, the algorithm gains the ability to adapt its smoothing behavior based on the local context. The main advantages are enhanced robustness with homogenous segments, lower sensitivity to noise, intensity inhomogeneity and accommodation of degree of hesitation or uncertainty that may exist in the real-world datasets. A comparative analysis of synthetic and real datasets of MR brain images proves the efficiency of the suggested approach over different algorithms. The paper investigates how the suggested research methodology performs in medical industry under different circumstances including both qualitative and quantitative parameters such as segmentation accuracy, similarity index, true positive ratio, false positive ratio. The experimental outcomes demonstrate that the suggested algorithm outperforms in retaining image details and achieving segmentation accuracy.

UMobileNetV2 model for semantic segmentation of gastrointestinal tract in MRI scans.

Gastrointestinal (GI) cancer is leading general tumour in the Gastrointestinal tract, which is fourth significant reason of tumour death in men and women. The common cure for GI cancer is radiation treatment, which contains directing a high-energy X-ray beam onto the tumor while avoiding healthy organs. To provide high dosages of X-rays, a system needs for accurately segmenting the GI tract organs. The study presents a UMobileNetV2 model for semantic segmentation of small and large intestine and stomach in MRI images of the GI tract. The model uses MobileNetV2 as an encoder in the contraction path and UNet layers as a decoder in the expansion path. The UW-Madison database, which contains MRI scans from 85 patients and 38,496 images, is used for evaluation. This automated technology has the capability to enhance the pace of cancer therapy by aiding the radio oncologist in the process of segmenting the organs of the GI tract. The UMobileNetV2 model is compared to three transfer learning models: Xception, ResNet 101, and NASNet mobile, which are used as encoders in UNet architecture. The model is analyzed using three distinct optimizers, i.e., Adam, RMS, and SGD. The UMobileNetV2 model with the combination of Adam optimizer outperforms all other transfer learning models. It obtains a dice coefficient of 0.8984, an IoU of 0.8697, and a validation loss of 0.1310, proving its ability to reliably segment the stomach and intestines in MRI images of gastrointestinal cancer patients.

A long-acting LEAP2 analog reduces hepatic steatosis and inflammation and causes marked weight loss in mice.

OBJECTIVE: The number of individuals affected by metabolic dysfunction associated fatty liver disease [1] is on the rise, yet hormonal contributors to the condition remain incompletely described and only a single FDA-approved treatment is available. Some studies suggest that the hormones ghrelin and LEAP2, which act as agonist and antagonist/inverse agonist, respectively, for the G protein coupled receptor GHSR, may influence the development of MAFLD. For instance, ghrelin increases hepatic fat whereas synthetic GHSR antagonists do the opposite. Also, hepatic steatosis is less prominent in standard chow-fed ghrelin-KO mice but more prominent in 42% high-fat diet-fed female LEAP2-KO mice. METHODS: Here, we sought to determine the therapeutic potential of a long-acting LEAP2 analog (LA-LEAP2) to treat MAFLD in mice. LEAP2-KO and wild-type littermate mice were fed a Gubra-Amylin-NASH (GAN) diet for 10 or 40 wks, with some randomized to an additional 28 or 10 days of GAN diet, respectively, while treated with LA-LEAP2 vs Vehicle. Various metabolic parameters were followed and biochemical and histological assessments of MAFLD were made. RESULTS: Among the most notable metabolic effects, daily LA-LEAP2 administration to both LEAP2-KO and wild-type littermates during the final 4 wks of a 14 wk-long GAN diet challenge markedly reduced liver weight, hepatic triglycerides, plasma ALT, hepatic microvesicular steatosis, hepatic lobular inflammation, NASH activity scores, and prevalence of higher-grade fibrosis. These changes were accompanied by prominent reductions in body weight, without effects on food intake, and reduced plasma total cholesterol. Daily LA-LEAP2 administration during the final 10 d of a 41.5 wk-long GAN diet challenge also reduced body weight, plasma ALT, and plasma total cholesterol in LEAP2-KO and wild-type littermates and prevalence of higher grade fibrosis in LEAP2-KO mice. CONCLUSIONS: Administration of LA-LEAP2 to mice fed a MAFLD-prone diet markedly improves several facets of MAFLD, including hepatic steatosis, hepatic lobular inflammation, higher-grade hepatic fibrosis, and transaminitis. These changes are accompanied by prominent reductions in body weight and lowered plasma total cholesterol. Taken together, these data suggest that LEAP2 analogs such as LA-LEAP2 hold promise for the treatment of MAFLD and obesity.

Impact of Ghrelin on Islet Size in Nonpregnant and Pregnant Female Mice.

Reducing ghrelin by ghrelin gene knockout (GKO), ghrelin-cell ablation, or high-fat diet feeding increases islet size and ß-cell mass in male mice. Here we determined if reducing ghrelin also enlarges islets in females and if pregnancy-associated changes in islet size are related to reduced ghrelin. Islet size and ß-cell mass were larger (P = .057 for ß-cell mass) in female GKO mice. Pregnancy was associated with reduced ghrelin and increased liver-expressed antimicrobial peptide-2 (LEAP2; a ghrelin receptor antagonist) in wild-type mice. Ghrelin deletion and pregnancy each increased islet size (by ∼19.9-30.2% and ∼34.9-46.4%, respectively), percentage of large islets (>25 µm2×103, by ∼21.8-42% and ∼21.2-41.2%, respectively), and ß-cell mass (by ∼15.7-23.8% and ∼65.2-76.8%, respectively). Neither islet cross-sectional area, ß-cell cross-sectional area, nor ß-cell mass correlated with plasma ghrelin, although all positively correlated with LEAP2 (P = .081 for islet cross-sectional area). In ad lib-fed mice, there was an effect of pregnancy, but not ghrelin deletion, to change (raise) plasma insulin without impacting blood glucose. Similarly, there was an effect of pregnancy, but not ghrelin deletion, to change (lower) blood glucose area under the curve during a glucose tolerance test. Thus, genetic deletion of ghrelin increases islet size and ß-cell cross-sectional area in female mice, similar to males. Yet, despite pregnancy-associated reductions in ghrelin, other factors appear to govern islet enlargement and changes to insulin sensitivity and glucose tolerance in the setting of pregnancy. In the case of islet size and ß-cell mass, one of those factors may be the pregnancy-associated increase in LEAP2.

Rehabilitation of a Chronic Guillain-Barré Syndrome Patient With Vibratory Motor Stimulation of Dorsiflexors: A Case Report.

There are various reports describing physiotherapy rehabilitation in Guillain-Barré syndrome (GBS) but the use of current to rehabilitate GBS patients has remained an untouched topic. To elaborate on this work, we describe a case report focusing on the intervention plan for the rehabilitation of a chronic GBS case by the use of vibratory motor stimulation (VMS) current. The study aimed to describe the therapeutic application of VMS current in improving muscle power of dorsiflexors and overall outcome measures in a case of GBS presenting in a tertiary care hospital in North India. A 29-year-old male patient came to Teerthanker Mahaveer University Hospital and consulted in the Department of Physiotherapy after 1.4 years of being diagnosed with acute motor axonal neuropathy-type GBS. Rehabilitation of this case included strengthening exercises of the upper and lower limbs along with balance exercises. Specifically, in this case, we gave VMS current after assessing the muscle power of the dorsiflexors, which was found to be grade-0 over the bilateral dorsiflexors, combined with passive dorsiflexion. Different outcome measures were used for assessment, including manual muscle testing, functional independence measurement, and the Berg Balance Scale. Improvement in the patient's condition was observed in his outcome measures after two months of treatment. There was an overall improvement in the muscle power of our patient's dorsiflexors, where muscle power was upgraded from grade-0 to grade-I and grade-I+ in the bilateral lower limbs by the use of VMS current. This study marks a novel application of VMS to the dorsiflexors of a GBS patient, yielding positive outcomes in upgrading muscle power grades from grade-0 to grade-I and grade-I+. Further research is needed to confirm VMS efficacy as an early intervention in GBS patient rehabilitation.

A comprehensive review on role of Aurora kinase inhibitors (AKIs) in cancer therapeutics.

Aurora kinases (AURKs) are a family of serine /threonine protein kinases that have a crucial role in cell cycle process mainly in the event of chromosomal segregation, centrosome maturation and cytokinesis. The family consists of three members including Aurora kinase A (AURK-A), Aurora kinase B (AURK-B) and Aurora kinase C (AURK-C). All AURKs contain a conserved kinase domain for their activity but differ in their cellular localization and functions. AURK-A and AURK-B are expressed mainly in somatic cells while the expression of AURK-C is limited to germ cells. AURK-A promotes G2 to M transition of cell cycle by controlling centrosome maturation and mitotic spindle assembly. AURK-B and AURK-C form the chromosome passenger complex (CPC) that ensures proper chromosomal alignments and segregation. Aberrant expression of AURK-A and AURK-B has been detected in several solid tumours and malignancies. Hence, they have become an attractive therapeutic target against cancer. The first part of this review focuses on AURKs structure, functions, subcellular localization, and their role in tumorigenesis. The review also highlights the functional and clinical impact of selective as well as pan kinase inhibitors. Currently, >60 compounds that target AURKs are in preclinical and clinical studies. The drawbacks of existing inhibitors like selectivity, drug resistance and toxicity have also been addressed. Since, majority of inhibitors are Aurora kinase inhibitor (AKI) type-1 that bind to the active (DFGin and Cin) conformation of the kinase, this information may be utilized to design highly selective kinase inhibitors that can be combined with other therapeutic agents for better clinical outcomes.

Influence of different pH milieu on the structure and function of human Aurora kinase B protein (AURK-B): Amalgamation of both spectroscopic and computational approach.

Aurora kinase B (AURK-B) is a serine/threonine kinase protein that plays an essential role in chromosomal separation during the cell cycle event. AURK-B is highly expressed in various types of cancer such as human seminoma, thyroid carcinoma, non-small cell lung carcinoma (NSCLC), oral carcinoma, and gastric cancer. Hence, it is a potential therapeutic target in the treatment of various cancers. The structure of AURK-B in complex with one of its substrate inner centromeric protein (INCENP) is present, but the structural and functional characterization of native AURK-B at different pH environment is still unexplored.This study determines the effect of different pH milieu on the structure and function of AURK-B protein wherein the influence of pH on the protein conformation was probed using Circular dichroism (CD) and fluorescence spectroscopy. The structural studies were further combined with functional activity assay to observe the change in kinase activity at various pH milieu (2.0-11.0). CD and fluorescence spectroscopy experiments dictate that at high acidic conditions (pH 2.0 - 5.0), the secondary and tertiary structures of AURK-B become distorted, leading to diminished activity. The protein, however, was observed to stabilize towards pH 7.0 - 8.0 with minimal structure alteration over the basic pH range (pH 9.0 -11.0). The measured spectroscopic structural features were found to be in-line with obtained experimental kinase activity assays. Further, in-vitro experiments indicate that the enzyme is maximally active at pH 8.0. More ordered conformation and compact structure was observed at this pH (pH 8.0) as compared to other pH values through molecular dynamics simulation studies (MDS). As AURK-B localizes itself in the intracellular compartment, this study may provide a clue about the role of different pH environments in enhancing cancer growth, proliferation, and invasion.

The acidic C-terminal tail of DNA Gyrase of Salmonella enterica serovar Typhi controls DNA relaxation in an acidic environment.

The intracellular bacteria, Salmonella Typhi adapts to acidic conditions in the host cell by resetting the chromosomal DNA topology majorly controlled by DNA Gyrase, a Type II topoisomerase. DNA Gyrase forms a heterodimer A2B2 complex, which manages the DNA supercoiling and relaxation in the cell. DNA relaxation forms a part of the regulatory mechanism to activate the transcription of genes required to survive under hostile conditions. Acid-induced stress attenuates the supercoiling activity of the DNA Gyrase, resulting in DNA relaxation. Salmonella DNA becomes relaxed as the bacteria adapt to the acidified intracellular environment. Despite comprehensive studies on DNA Gyrase, the mechanism to control supercoiling activity needs to be better understood. A loss in supercoiling activity in E. coli was observed upon deletion of the non-conserved acidic C-tail of Gyrase A subunit. Salmonella Gyrase also contains an acidic tail at the C-terminus of Gyrase A, where its deletion resulted in reduced supercoiling activity compared to wild-type Gyrase. Interestingly, we also found that wild-type Gyrase compromises supercoiling activity at acidic pH 2-3, thereby causing DNA relaxation. The absence of a C-tail displayed DNA supercoiling to some extent between pH 2-9. Hence, the C-tail of Gyrase A might be one of the controlling factors that cause DNA relaxation in Salmonella at acidic pH conditions. We propose that the presence of the C-tail of GyraseA causes acid-mediated inhibition of the negative supercoiling activity of Gyrase, resulting in relaxed DNA that attracts DNA-binding proteins for controlling the transcriptional response.

An Insight into the Development of Potential Antidiabetic Agents along with their Therapeutic Targets.

Diabetes is a metabolic disorder that has been reported to increase the mortality rate worldwide. About 40 million people across the globe suffer from diabetes, with people living in developing countries being affected the most due to this deadly disease. Although the therapeutic management of hyperglycaemia can treat diabetes, metabolic disorders associated with this disease are a greater challenge in its treatment. Hence, potential strategies to treat hyperglycaemia and its side effects are needed. In this review, we have summarized several therapeutic targets, like dipeptidyl peptidase-4 (DPP-4), glucagon receptor antagonists, glycogen phosphorylase or fructose-1,6- biphosphatase inhibitors, SGLT inhibitors, 11beta-HSD-1 inhibitors, glucocorticoids receptor antagonists, glucose-6-phosphatase and glycogen phosphorylase inhibitors. These targets can help in designing and developing novel antidiabetic agents.

Ghrelin deletion and conditional ghrelin cell ablation increase pancreatic islet size in mice.

Ghrelin exerts key effects on islet hormone secretion to regulate blood glucose levels. Here, we sought to determine whether ghrelin's effects on islets extend to the alteration of islet size and ß cell mass. We demonstrate that reducing ghrelin - by ghrelin gene knockout (GKO), conditional ghrelin cell ablation, or high-fat diet (HFD) feeding - was associated with increased mean islet size (up to 62%), percentage of large islets (up to 854%), and ß cell cross-sectional area (up to 51%). In GKO mice, these effects were more apparent in 10- to 12-week-old mice than in 4-week-old mice. Higher ß cell numbers from decreased ß cell apoptosis drove the increase in ß cell cross-sectional area. Conditional ghrelin cell ablation in adult mice increased the ß cell number per islet by 40% within 4 weeks. A negative correlation between islet size and plasma ghrelin in HFD-fed plus chow-fed WT mice, together with even larger islet sizes in HFD-fed GKO mice than in HFD-fed WT mice, suggests that reduced ghrelin was not solely responsible for diet-induced obesity-associated islet enlargement. Single-cell transcriptomics revealed changes in gene expression in several GKO islet cell types, including upregulation of Manf, Dnajc3, and Gnas expression in ß cells, which supports decreased ß cell apoptosis and/or increased ß cell proliferation. These effects of ghrelin reduction on islet morphology might prove useful when designing new therapies for diabetes.

Ghrelin-responsive mediobasal hypothalamic neurons mediate exercise-associated food intake and exercise endurance.

Previous studies have implicated the orexigenic hormone ghrelin as a mediator of exercise endurance and the feeding response postexercise. Specifically, plasma ghrelin levels nearly double in mice when they are subjected to an hour-long bout of high-intensity interval exercise (HIIE) using treadmills. Also, growth hormone secretagogue receptor-null (GHSR-null) mice exhibit decreased food intake following HIIE and diminished running distance (time until exhaustion) during a longer, stepwise exercise endurance protocol. To investigate whether ghrelin-responsive mediobasal hypothalamus (MBH) neurons mediate these effects, we stereotaxically delivered the inhibitory designer receptor exclusively activated by designer drugs virus AAV2-hSyn-DIO-hM4(Gi)-mCherry to the MBH of Ghsr-IRES-Cre mice, which express Cre recombinase directed by the Ghsr promoter. We found that chemogenetic inhibition of GHSR-expressing MBH neurons (upon delivery of clozapine-N-oxide) 1) suppressed food intake following HIIE, 2) reduced maximum running distance and raised blood glucose and blood lactate levels during an exercise endurance protocol, 3) reduced food intake following ghrelin administration, and 4) did not affect glucose tolerance. Further, HIIE increased MBH Ghsr expression. These results indicate that activation of ghrelin-responsive MBH neurons is required for the normal feeding response to HIIE and the usual amount of running exhibited during an exercise endurance protocol.

Enhancing accuracy in brain stroke detection: Multi-layer perceptron with Adadelta, RMSProp and AdaMax optimizers.

The human brain is an extremely intricate and fascinating organ that is made up of the cerebrum, cerebellum, and brainstem and is protected by the skull. Brain stroke is recognized as a potentially fatal condition brought on by an unfavorable obstruction in the arteries supplying the brain. The severity of brain stroke may be reduced or controlled with its early prognosis to lessen the mortality rate and lead to good health. This paper proposed a technique to predict brain strokes with high accuracy. The model was constructed using data related to brain strokes. The aim of this work is to use Multi Layer Perceptron (MLP) as a classification technique for stroke data and used multi-optimizers that include Adaptive moment estimation with Maximum (AdaMax), Root Mean Squared Propagation (RMSProp) and Adaptive learning rate method (Adadelta). The experiment shows RMSProp optimizer is best with a data training accuracy of 95.8% and a value for data testing accuracy of 94.9%. The novelty of work is to incorporate multiple optimizers alongside the MLP classifier which offers a comprehensive approach to stroke prediction, providing a more robust and accurate solution. The obtained results underscore the effectiveness of the proposed methodology in enhancing the accuracy of brain stroke detection, thereby paving the way for potential advancements in medical diagnosis and treatment.

Automatic Identification of Glomerular in Whole-Slide Images Using a Modified UNet Model.

Glomeruli are interconnected capillaries in the renal cortex that are responsible for blood filtration. Damage to these glomeruli often signifies the presence of kidney disorders like glomerulonephritis and glomerulosclerosis, which can ultimately lead to chronic kidney disease and kidney failure. The timely detection of such conditions is essential for effective treatment. This paper proposes a modified UNet model to accurately detect glomeruli in whole-slide images of kidney tissue. The UNet model was modified by changing the number of filters and feature map dimensions from the first to the last layer to enhance the model's capacity for feature extraction. Moreover, the depth of the UNet model was also improved by adding one more convolution block to both the encoder and decoder sections. The dataset used in the study comprised 20 large whole-side images. Due to their large size, the images were cropped into 512 × 512-pixel patches, resulting in a dataset comprising 50,486 images. The proposed model performed well, with 95.7% accuracy, 97.2% precision, 96.4% recall, and 96.7% F1-score. These results demonstrate the proposed model's superior performance compared to the original UNet model, the UNet model with EfficientNetb3, and the current state-of-the-art. Based on these experimental findings, it has been determined that the proposed model accurately identifies glomeruli in extracted kidney patches.

A novel fine-tuned deep-learning-based multi-class classifier for severity of paddy leaf diseases.

Introduction: Paddy leaf diseases have a catastrophic influence on the quality and quantity of paddy grain production. The detection and identification of the intensity of various paddy infections are critical for high-quality crop production. Methods: In this paper, infections in paddy leaves are considered for the identification of illness severity. The dataset contains both primary and secondary data. The four online repositories used for secondary data resources are Mendeley, GitHub, Kaggle and UCI. The size of the dataset is 4,068 images. The dataset is first pre-processed using ImageDataGenerator. Then, a generative adversarial network (GAN) is used to increase the dataset size exponentially. The disease severity calculation for the infected leaf is performed using a number of segmentation methods. To determine paddy infection, a deep learning-based hybrid approach is proposed that combines the capabilities of a convolutional neural network (CNN) and support vector machine (SVM). The severity levels are determined with the assistance of a domain expert. Four degrees of disease severity (mild, moderate, severe, and profound) are considered. Results: Three infections are considered in the categorization of paddy leaf diseases: bacterial blight, blast, and leaf smut. The model predicted the paddy disease type and intensity with a 98.43% correctness rate. The loss rate is 41.25%. Discussion: The findings show that the proposed method is reliable and effective for identifying the four levels of severity of bacterial blight, blast, and leaf smut infections in paddy crops. The proposed model performed better than the existing CNN and SVM classification models.

Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm.

Cloud computing plays an important role in every IT sector. Many tech giants such as Google, Microsoft, and Facebook as deploying their data centres around the world to provide computation and storage services. The customers either submit their job directly or they take the help of the brokers for the submission of the jobs to the cloud centres. The preliminary aim is to reduce the overall power consumption which was ignored in the early days of cloud development. This was due to the performance expectations from cloud servers as they were supposed to provide all the services through their services layers IaaS, PaaS, and SaaS. As time passed and researchers came up with new terminologies and algorithmic architecture for the reduction of power consumption and sustainability, other algorithmic anarchies were also introduced, such as statistical oriented learning and bioinspired algorithms. In this paper, an indepth focus has been done on multiple approaches for migration among virtual machines and find out various issues among existing approaches. The proposed work utilizes elastic scheduling inspired by the smart elastic scheduling algorithm (SESA) to develop a more energy-efficient VM allocation and migration algorithm. The proposed work uses cosine similarity and bandwidth utilization as additional utilities to improve the current performance in terms of QoS. The proposed work is evaluated for overall power consumption and service level agreement violation (SLA-V) and is compared with related state of art techniques. A proposed algorithm is also presented in order to solve problems found during the survey.

Prevention of COVID-19 Following a Single Intramuscular Administration of Adintrevimab: Results From a Phase 2/3 Randomized, Double-Blind, Placebo-Controlled Trial (EVADE).

Background: The prevention of coronavirus disease 2019 (COVID-19) in vulnerable populations is a global health priority. EVADE was a phase 2/3 multicenter, double-blind, randomized, placebo-controlled trial of adintrevimab, an extended-half-life monoclonal antibody, for postexposure (PEP) and pre-exposure prophylaxis (PrEP) of symptomatic COVID-19. Methods: Eligible participants (vaccine-naive, aged ≥12 years) were randomized 1:1 to receive a single 300-mg intramuscular injection of adintrevimab or placebo. Primary efficacy end points were reverse transcription polymerase chain reaction (RT-PCR)-confirmed symptomatic COVID-19 through day 28 in the PEP cohort (RT-PCR-negative at baseline) and through month 3 in the PrEP cohort (RT-PCR-negative and seronegative at baseline) among participants randomized before emergence of the severe acute respiratory syndrome coronavirus 2 Omicron variant (November 30, 2021). Safety was assessed through 6 months. Results: Between April 27, 2021, and January 11, 2022, 2582 participants were randomized. In the primary efficacy analysis, RT-PCR-confirmed symptomatic COVID-19 occurred in 3/175 (1.7%) vs 12/176 (6.8%) adintrevimab- and placebo-treated PEP participants, respectively (74.9% relative risk reduction [RRR]; standardized risk difference, -5.0%; 95% CI, -8.87% to -1.08%; P = .0123) and in 12/752 (1.6%) vs 40/728 (5.5%) adintrevimab- and placebo-treated PrEP participants, respectively (71.0% RRR; standardized risk difference, -3.9%; 95% CI, -5.75% to -2.01%; P < .0001). In a prespecified exploratory analysis of 428 PrEP participants randomized after the emergence of Omicron, adintrevimab reduced RT-PCR-confirmed symptomatic COVID-19 by 40.6% (standardized risk difference -8.4%; 95% CI, -15.35% to -1.46%; nominal P = .0177) vs placebo. Adintrevimab was well tolerated, with no serious drug-related adverse events reported. Conclusions: A single intramuscular injection of adintrevimab provided prophylactic efficacy against COVID-19 due to susceptible variants without safety concerns. Clinical trial registration. NCT04859517.

Ghrelin does not impact the blunted counterregulatory response to recurrent hypoglycemia in mice.

Introduction: Recurrent episodes of insulin-induced hypoglycemia in patients with diabetes mellitus can result in hypoglycemia-associated autonomic failure (HAAF), which is characterized by a compromised response to hypoglycemia by counterregulatory hormones (counterregulatory response; CRR) and hypoglycemia unawareness. HAAF is a leading cause of morbidity in diabetes and often hinders optimal regulation of blood glucose levels. Yet, the molecular pathways underlying HAAF remain incompletely described. We previously reported that in mice, ghrelin is permissive for the usual CRR to insulin-induced hypoglycemia. Here, we tested the hypothesis that attenuated release of ghrelin both results from HAAF and contributes to HAAF. Methods: C57BL/6N mice, ghrelin-knockout (KO) + control mice, and GhIRKO (ghrelin cell-selective insulin receptor knockout) + control mice were randomized to one of three treatment groups: a "Euglycemia" group was injected with saline and remained euglycemic; a 1X hypoglycemia ("1X Hypo") group underwent a single episode of insulin-induced hypoglycemia; a recurrent hypoglycemia ("Recurrent Hypo") group underwent repeated episodes of insulin-induced hypoglycemia over five successive days. Results: Recurrent hypoglycemia exaggerated the reduction in blood glucose (by ~30%) and attenuated the elevations in plasma levels of the CRR hormones glucagon (by 64.5%) and epinephrine (by 52.9%) in C57BL/6N mice compared to a single hypoglycemic episode. Yet, plasma ghrelin was equivalently reduced in "1X Hypo" and "Recurrent Hypo" C57BL/6N mice. Ghrelin-KO mice exhibited neither exaggerated hypoglycemia in response to recurrent hypoglycemia, nor any additional attenuation in CRR hormone levels compared to wild-type littermates. Also, in response to recurrent hypoglycemia, GhIRKO mice exhibited nearly identical blood glucose and plasma CRR hormone levels as littermates with intact insulin receptor expression (floxed-IR mice), despite higher plasma ghrelin in GhIRKO mice. Conclusions: These data suggest that the usual reduction of plasma ghrelin due to insulin-induced hypoglycemia is unaltered by recurrent hypoglycemia and that ghrelin does not impact blood glucose or the blunted CRR hormone responses during recurrent hypoglycemia.

Therapeutic Management with Repurposing Approaches: A Mystery During COVID-19 Outbreak.

The ubiquitous pandemic that emerged due to COVID-19 affected the whole planet. People all over the globe became vulnerable to the unpredictable emergence of coronavirus. The sudden emergence of respiratory disease in coronavirus infected several patients. This affected human life drastically, from mild symptoms to severe illness, leading to mortality. COVID-19 is an exceptionally communicable disease caused by SARS-CoV-2. According to a genomic study, the viral spike RBD interactions with the host ACE2 protein from several coronavirus strains and the interaction between RBD and ACE2 highlighted the potential change in affinity from the virus causing the COVID-19 outbreak to a progenitor type of SARS-CoV-2. SARS-CoV-2, which could be the principal reservoir, is phylogenetically related to the SARS-like bat virus. Other research works reported that intermediary hosts for the transmission of viruses to humans could include cats, bats, snakes, pigs, ferrets, orangutans, and monkeys. Even with the arrival of vaccines and individuals getting vaccinated and treated with FDA-approved repurposed drugs like Remdesivir, the first and foremost steps aimed towards the possible control and minimization of community transmission of the virus include social distancing, self-realization, and self-health care. In this review paper, we discussed and summarized various approaches and methodologies adopted and proposed by researchers all over the globe to help with the management of this zoonotic outbreak by following repurposed approaches.

Efficacy and Safety of Adintrevimab (ADG20) for the Treatment of High-Risk Ambulatory Patients With Mild or Moderate Coronavirus Disease 2019: Results From a Phase 2/3, Randomized, Placebo-Controlled Trial (STAMP) Conducted During Delta Predominance and Early Emergence of Omicron.

Background: Safe and effective treatments are needed to prevent severe outcomes in individuals with coronavirus disease 2019 (COVID-19). We report results from STAMP, a phase 2/3, multicenter, double-blind, randomized, placebo-controlled trial of adintrevimab, an extended half-life monoclonal antibody, for treatment of high-risk ambulatory patients with mild to moderate COVID-19. Methods: Nonhospitalized, unvaccinated participants aged ≥12 years with mild to moderate COVID-19 and ≥1 risk factor for disease progression were randomized to receive a single intramuscular injection of 300 mg adintrevimab or placebo. Enrollment was paused due to the global emergence of the Omicron BA.1/BA1.1 variants, against which adintrevimab showed reduced activity in vitro. The primary efficacy endpoint was COVID-19-related hospitalization or all-cause death through day 29 in participants with COVID-19 due to laboratory-confirmed or suspected non-Omicron severe acute respiratory syndrome coronavirus 2 variants. Results: Between 8 August 2021 and 11 January 2022, 399 participants were randomized to receive adintrevimab (n = 198) or placebo (n = 201), including 336 with COVID-19 due to non-Omicron variants. COVID-19-related hospitalization or all-cause death through day 29 occurred in 8 of 169 (4.7%) participants in the adintrevimab group and 23 of 167 (13.8%) participants in the placebo group, a 66% relative risk reduction in favor of adintrevimab (standardized risk difference, -8.7% [95% confidence interval, -14.71% to -2.67%]; P = .0047). Incidence of treatment-emergent adverse events (TEAEs) was similar between treatment groups (33.9% for adintrevimab and 39.5% for placebo). No adintrevimab-related serious TEAEs were reported. Conclusions: Treatment with a single intramuscular injection of adintrevimab provided protection against severe outcomes in high-risk ambulatory participants with COVID-19 due to susceptible variants, without safety concerns. Clinical Trial Registration. NCT04805671.