Augmenting cybersecurity through attention based stacked autoencoder with optimization algorithm for detection and mitigation of attacks on IoT assisted networks.

The Internet of Things (IoT) network is a fast-growing technology, which is efficiently used in various applications. In an IoT network, the massive amount of connecting nodes is the existence of day-to-day communication challenges. The platform of IoT uses a cloud service as a backend for processing information and maintaining remote control.

Machine Learning-Based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction.

Respiration-correlated cone-beam computed tomography (4D-CBCT) is an X-ray-based imaging modality that uses reconstruction algorithms to produce time-varying volumetric images of moving anatomy over a cycle of respiratory motion. The quality of the produced images is affected by the number of CBCT projections available for reconstruction. Interpolation techniques have been used to generate intermediary projections to be used, along with the original projections, for reconstruction.

Enhanced breast cancer diagnosis through integration of computer vision with fusion based joint transfer learning using multi modality medical images.

Breast cancer (BC) is a type of cancer which progresses and spreads from breast tissues and gradually exceeds the entire body; this kind of cancer originates in both sexes. Prompt recognition of this disorder is most significant in this phase, and it is measured by providing patients with the essential treatment so their efficient lifetime can be protected. Scientists and researchers in numerous studies have initiated techniques to identify tumours in early phases.

Characterizing the relationship between social determinants of health and risk of albuminuria among children with type 1 diabetes.

In a cohort of 2303 children with type 1 diabetes (T1D), we found that non-English speaking status (HR 2.82, 95% CI 1.54-5.

Assessment and management of construction and demolition waste in tier 2 cities of Karnataka, India: a case study of Hubli-Dharwad and Davanagere.

The present study examines the current practices for managing construction and demolition waste (CDW) in two tier-2 cities of Karnataka state: Hubli-Dharwad and Davanagere. The research highlights the quantification, characterization, and effective management strategies for CDW. CDW dumping sites were identified through field visits conducted across all wards of the cities and recorded using a mobile-based app.

Optimal directed acyclic graph federated learning model for energy-efficient IoT communication networks.

Federated learning (FL) stimulates distributed on-device computation systems to process an optimum technique efficiency by communicating local process upgrades and global method distribution from aggregation averaging procedure. On-device FL is a standard application in wireless environments, with several mobile devices participating as nodes in the FL network. Managing extensive multi-dimensional process upgrades and resource-constrained computations in large-scale heterogeneous IoT cellular networks can be challenging.

Deciphering the molecular landscape of the FAM72 gene family: Implications for stem cell biology and cancer.

Family with sequence similarity 72 (FAM72) is a protein-coding gene family located on chromosome 1 in humans, uniquely featuring four paralogs: FAM72A, FAM72B, FAM72C, and FAM72D. While FAM72's presence as a gene pair with the SLIT-ROBO Rho GTPase-activating protein 2 (SRGAP2) is intriguing, its functional roles, particularly in neural stem cells, remain incompletely understood. This review explores the distinct characteristics of FAM72, shedding light on its expression patterns, potential roles in cell cycle regulation, stem cell renewal and implications in neurogenesis and tumorigenesis.

Improving privacy-preserving multi-faceted long short-term memory for accurate evaluation of encrypted time-series MRI images in heart disease.

In therapeutic diagnostics, early diagnosis and monitoring of heart disease is dependent on fast time-series MRI data processing. Robust encryption techniques are necessary to guarantee patient confidentiality. While deep learning (DL) algorithm have improved medical imaging, privacy and performance are still hard to balance.

Advancing breast ultrasound diagnostics through hybrid deep learning models.

Today, doctors rely heavily on medical imaging to identify abnormalities. Proper classification of these abnormalities enables them to take informed actions, leading to early diagnosis and treatment. This paper introduces the "EfficientKNN" model, a novel hybrid deep learning approach that combines the advanced feature extraction capabilities of EfficientNetB3 with the simplicity and effectiveness of the k-Nearest Neighbors (k-NN) algorithm.

A novel deep learning framework for accurate melanoma diagnosis integrating imaging and genomic data for improved patient outcomes.

Background: Melanoma is one of the most malignant forms of skin cancer, with a high mortality rate in the advanced stages. Therefore, early and accurate detection of melanoma plays an important role in improving patients' prognosis. Biopsy is the traditional method for melanoma diagnosis, but this method lacks reliability.

Evaluation of 13 Formulae for Calculated LDL-C Using Direct Homogenous Assay in a South Indian Population.

Background: LDL cholesterol (LDL-C) is regarded as a significant therapeutic target and a known risk factor for atherosclerosis. It can be calculated using the results of the other lipid tests or tested directly. Despite its shortcomings, the Friedewald formula is most frequently utilized since it is simple and practical.

Feature fusion-based food protein subcellular prediction for drug composition.

The structure and function of dietary proteins, as well as their subcellular prediction, are critical for designing and developing new drug compositions and understanding the pathophysiology of certain diseases. As a remedy, we provide a subcellular localization method based on feature fusion and clustering for dietary proteins. Additionally, an enhanced PseAAC (Pseudo-amino acid composition) method is suggested, which builds upon the conventional PseAAC.

Rabies death in an adolescent tribal girl diagnosed postmortem, in Kerala - the precious life, preventable loss and equity concerns.

Background: Rabies is a neglected tropical disease endemic in 150 countries, including India where it is present in all states and union territories except Andaman and Nicobar Islands Lakshadweep. Kerala reports high incidence of animal bites. This article discusses the preventable death of a 17-year-old tribal girl due to rabies in Kerala and the equity concerns it raises.

An Insight into Knowledge, Perspective, and Practices of Indian Optometrists towards Childhood Myopia.

The current understanding of clinical approaches and barriers in managing childhood myopia among Indian optometrists is limited. This research underscores the necessity and relevance of evidence-based practice guidelines by exploring their knowledge, attitude, and practice towards childhood myopia. A self-administered internet-based 26-item survey was circulated online among practicing optometrists in India.

Determinants of Poison-related Mortality in Tertiary Care Hospital, South India.

Aims And Background: Acute poisoning is one of the most common emergencies in India and around the world. Understanding the factors associated with mortality can aid us in devising appropriate preventive strategies to curtail deaths due to poisoning. Purpose of this study is to find various factors that determine the mortality among acute poisoning cases admitted in a tertiary care center.

Simple virus-free mouse models of COVID-19 pathologies and oral therapeutic intervention.

The paucity of preclinical models that recapitulate COVID-19 pathology without requiring SARS-COV-2 adaptation and humanized/transgenic mice limits research into new therapeutics against the frequently emerging variants-of-concern. We developed virus-free models by C57BL/6 mice receiving oropharyngeal instillations of a SARS-COV-2 ribo-oligonucleotide common in all variants or specific to Delta/Omicron variants, concurrently with low-dose bleomycin. Mice developed COVID-19-like lung pathologies including ground-glass opacities, interstitial fibrosis, congested alveoli, and became moribund.

Multi-objective exponential distribution optimizer (MOEDO): a novel math-inspired multi-objective algorithm for global optimization and real-world engineering design problems.

The exponential distribution optimizer (EDO) represents a heuristic approach, capitalizing on exponential distribution theory to identify global solutions for complex optimization challenges. This study extends the EDO's applicability by introducing its multi-objective version, the multi-objective EDO (MOEDO), enhanced with elite non-dominated sorting and crowding distance mechanisms. An information feedback mechanism (IFM) is integrated into MOEDO, aiming to balance exploration and exploitation, thus improving convergence and mitigating the stagnation in local optima, a notable limitation in traditional approaches.

A technology platform for standardized cryoprotection and freezing of large-volume brain tissues for high-resolution histology.

Understanding and mapping the human connectome is a long-standing endeavor of neuroscience, yet the significant challenges associated with the large size of the human brain during cryosectioning remain unsolved. While smaller brains, such as rodents and marmosets, have been the focus of previous connectomics projects, the processing of the larger human brain requires significant technological advancements. This study addresses the problem of freezing large brains in aligned neuroanatomical coordinates with minimal tissue damage, facilitating large-scale distortion-free cryosectioning.

Evaluation of the hypothalamo-pituitary-adrenal axis during the post-COVID-19 period in patients treated with steroids during the illness.

Objective: COVID-19 is a multisystem immunoinflammatory disorder, and the hypothalamo-pituitary-adrenal (HPA) axis may be affected by SARS-CoV-2 as well as by steroid treatment during the illness. Information on the HPA axis after recovering from COVID-19, especially in those treated with steroids, is sparse. Hence, this study was performed to evaluate the hypothalamo-pituitary-adrenal axis during the post-COVID-19 period in patients treated with steroids during the illness.

Type 2 Diabetes and Precursors in Community Dwelling Asian Indian Adult Youth.

Background: Recent studies have shown a high prevalence of Type-2-diabetes (T2DM) (24%) and prediabetes (18.1%) in Kerala. There is no community based study from South Asia regarding the prevalence of type 2 diabetes and its precursors in the young adult population.

UK and Ireland Joint Advisory Group (JAG) consensus statements for training and certification in diagnostic endoscopic ultrasound (EUS).

Background And Aims: International endoscopy societies vary in their approach for credentialing individuals in endoscopic ultrasound (EUS) to enable independent practice; however, there is no consensus in this or its implementation. In 2019, the Joint Advisory Group on GI Endoscopy (JAG) commissioned a working group to examine the evidence relating to this process for EUS. The aim of this was to develop evidence-based recommendations for EUS training and certification in the UK.

Effects of yoga on anxiety, pain, inflammatory and stress biomarkers in patients undergoing cardiac surgery: A systematic review and meta-analysis.

Background: The most common surgical method of managing coronary artery disease is coronary artery bypass grafting (CABG). Stress, anxiety, and pain are commonly identified postoperative symptoms and are closely correlated to patient recovery.

Objective: The purpose of this review was to investigate the effects of yoga interventions on anxiety, pain, inflammatory and stress biomarkers in CABG surgery patients.

Autophagy: An Emerging Target for Developing Effective Analgesics.

Inadequate treatment of acute and chronic pain causes depression, anxiety, sleep disturbances, and increased mortality. Abuse and overdose of opioids and the side effects associated with chronic use of NSAID illustrate the need for development of safer and effective pain medication. Working toward this end, an tool based on an emergent intelligence analytical platform that examines interactions between protein networks was used to identify molecular mechanisms involved in regulating the body's response to painful stimuli and drug treatments.

Anaesthetic implications of a case of hyperthyroidism detected during the closure of an atrial septal defect.

A woman in her mid-20s who was clinically euthyroid presented with an ostium secondum atrial septal defect for closure. Preoperatively, heart rate ranged from 80 to 110 beats per minute. On the day of surgery, heart rate was 120 beats per minute, which settled after induction.