Virtual histopathology methods in medical imaging - a systematic review.

Virtual histopathology is an emerging technology in medical imaging that utilizes advanced computational methods to analyze tissue images for more precise disease diagnosis. Traditionally, histopathology relies on manual techniques and expertise, often resulting in time-consuming processes and variability in diagnoses. Virtual histopathology offers a more consistent, and automated approach, employing techniques like machine learning, deep learning, and image processing to simulate staining and enhance tissue analysis.

LSSF-Net: Lightweight segmentation with self-awareness, spatial attention, and focal modulation.

Accurate segmentation of skin lesions within dermoscopic images plays a crucial role in the timely identification of skin cancer for computer-aided diagnosis on mobile platforms. However, varying shapes of the lesions, lack of defined edges, and the presence of obstructions such as hair strands and marker colours make this challenge more complex. Additionally, skin lesions often exhibit subtle variations in texture and colour that are difficult to differentiate from surrounding healthy skin, necessitating models that can capture both fine-grained details and broader contextual information.

LMBiS-Net: A lightweight bidirectional skip connection based multipath CNN for retinal blood vessel segmentation.

Blinding eye diseases are often related to changes in retinal structure, which can be detected by analysing retinal blood vessels in fundus images. However, existing techniques struggle to accurately segment these delicate vessels. Although deep learning has shown promise in medical image segmentation, its reliance on specific operations can limit its ability to capture crucial details such as the edges of the vessel.

GC-MS profiling and biological investigations of L. & L.

The objectives of the study were to conduct phytochemical screening of crude extracts of L. and L. and assessing their biological potentials against protein kinase enzymes, followed by the evaluation of antioxidant and antimicrobial capacities.

Antibiotic resistance genes prediction via whole genome sequence analysis of Stenotrophomonas maltophilia.

Background: Stenotrophomonas maltophilia (S. maltophilia) is the first dominant ubiquitous bacterial species identified from the genus Stenotrophomonas in 1943 from a human source. S.

and antioxidant therapeutic evaluation of phytochemicals from different parts of Jacq.

Natural antioxidants are vital to promote health and treat critical disease conditions in the modern healthcare system. This work adds to the index of natural medicines by exploring the antioxidant potential of Jacq. (Plant-DV).

A Novel Monopole Ultra-Wide-Band Multiple-Input Multiple-Output Antenna with Triple-Notched Characteristics for Enhanced Wireless Communication and Portable Systems.

This study introduces a monopole 4 × 4 Ultra-Wide-Band (UWB) Multiple-Input Multiple-Output (MIMO) antenna system with a novel structure and outstanding performance. The proposed design has triple-notched characteristics due to CSRR etching and a C-shaped curve. The notching occurs in 4.

Teeth Lesion Detection Using Deep Learning and the Internet of Things Post-COVID-19.

With a view of the post-COVID-19 world and probable future pandemics, this paper presents an Internet of Things (IoT)-based automated healthcare diagnosis model that employs a mixed approach using data augmentation, transfer learning, and deep learning techniques and does not require physical interaction between the patient and physician. Through a user-friendly graphic user interface and availability of suitable computing power on smart devices, the embedded artificial intelligence allows the proposed model to be effectively used by a layperson without the need for a dental expert by indicating any issues with the teeth and subsequent treatment options. The proposed method involves multiple processes, including data acquisition using IoT devices, data preprocessing, deep learning-based feature extraction, and classification through an unsupervised neural network.

Synergistic Impacts of Plant-Growth-Promoting Bacteria and Selenium Nanoparticles on Improving the Nutritional Value and Biological Activities of Three Cultivars of Sprouts.

Due to the growing world population and increasing environmental stress, improving the production, nutritional quality, and pharmaceutical applications of plants have become an urgent need. Therefore, current research was designed to investigate the impact of seed priming using plant-growth-promoting bacteria (PGPB) along with selenium nanoparticles (SeNPs) treatment on chemical and biological properties of three cultivars [Southern star (VA1), Prominence (VA2), Monotop (VA3)]. With this aim, one out of five morphologically different strains of bacteria, namely, JM18, which was further identified via 16S rRNA gene sequencing as a species with strong plant-growth-promoting traits, isolated from soil, was used.

Analysis of Homogeneous/Heterogeneous Reactions in an Electrohydrodynamic Environment Utilizing the Second Law.

In this study, we investigate what happens to entropy in the presence of electrokinetic phenomena. It is speculated that the microchannel has an asymmetrical and slanted configuration. The presence of fluid friction, mixed convection, Joule heating, presence and absence of homogeneity, and a magnetic field are modelled mathematically.

Classification and Multifaceted Potential of Secondary Metabolites Produced by Group: A Comprehensive Review.

Despite their remarkable biosynthetic potential, have been widely overlooked. However, their capability to withstand harsh conditions (extreme temperature, Ultraviolet (UV) and γ-radiation, and dehydration) and the promiscuous metabolites they synthesize have created increased commercial interest in them as a therapeutic agent, a food preservative, and a plant-pathogen control agent. Nevertheless, the commercial-scale availability of these metabolites is constrained due to challenges in their accessibility via synthesis and low fermentation yields.

An Effective Method for Lung Cancer Diagnosis from CT Scan Using Deep Learning-Based Support Vector Network.

The diagnosis of early-stage lung cancer is challenging due to its asymptomatic nature, especially given the repeated radiation exposure and high cost of computed tomography(CT). Examining the lung CT images to detect pulmonary nodules, especially the cell lung cancer lesions, is also tedious and prone to errors even by a specialist. This study proposes a cancer diagnostic model based on a deep learning-enabled support vector machine (SVM).

An overview of dengue viral infection circulating in Pakistan.

Background & Objectives: Dengue virus (DENV) is an RNA virus that infects approximately 2.5 billion people around the world. The incidence of dengue fever has rapidly increased at an alarming rate in the last few years and has affected thousands of people in Pakistan.

An in vivo evaluation of anti-inflammatory, analgesic and anti-pyretic activities of newly synthesized 1, 2, 4 Triazole derivatives.

Background: In recent years, 1, 2, 4-triazole and its derivatives have been reported to be pharmacologically significant scaffolds. They possess analgesic, anti-tubercular, anti-inflammatory, anti-convulsant, anti-oxidant, anti-fungal, anti-cancer, anxiolytic and anti-depressant activity. This study was designed and conducted to evaluate the potential anti-inflammatory, analgesic and antipyretic activities of Triazole derivatives.

A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection.

Artificial Intelligence (AI) is the domain of computer science that focuses on the development of machines that operate like humans. In the field of AI, medical disease detection is an instantly growing domain of research. In the past years, numerous endeavours have been made for the improvements of medical disease detection, because the errors and problems in medical disease detection cause serious wrong medical treatment.

Effects of core muscle stability on low back pain and quality of life in post- menopausal women: A comparative study.

Objective: To determine the effects of core stability exercises on backache and quality of life of postmenopausal women.

Methods: he comparative study was conducted at the Department of Physical Therapy, Margalla General Hospital, Rawalpindi, Pakistan, from February to June 2018, and comprised post-menopausal woman aged 40-60 years having backache who were randomly divided into experimental group A and control group B. Group A underwent core stability exercises along with traditional therapy, while group B had traditional low backache physical therapy.

Desert Soil Microbes as a Mineral Nutrient Acquisition Tool for Chickpea ( L.) Productivity at Different Moisture Regimes.

Drought is a major constraint in drylands for crop production. Plant associated microbes can help plants in acquisition of soil nutrients to enhance productivity in stressful conditions. The current study was designed to illuminate the effectiveness of desert rhizobacterial strains on growth and net-return of chickpeas grown in pots by using sandy loam soil of Thal Pakistan desert.

Apocynin and catalase prevent hypertension and kidney injury in Cyclosporine A-induced nephrotoxicity in rats.

Oxidative stress is involved in the pathogenesis of a number of diseases including hypertension and renal failure. There is enhanced expression of nicotinamide adenine dinucleotide (NADPH oxidase) and therefore production of hydrogen peroxide (H2O2) during renal disease progression. This study investigated the effect of apocynin, an NADPH oxidase inhibitor and catalase, an H2O2 scavenger on Cyclosporine A (CsA) nephrotoxicity in Wistar-Kyoto rats.

The protective potential of a ethyl acetate fraction against CCl-induced oxidative stress in the cardiac tissue of rats.

Secondary metabolites present in medicinal plants offer a golden opportunity to fight different ailments, such as cancer, infections, diabetes, neurodegenerative and cardiovascular diseases, The traditional use of various parts of is known to serve as a cure for pneumonia, pain, jaundice, malaria, fracturing of bones, and internal wounds. The aim of this research was to validate the antioxidant and cardio-protective properties of leaves. The antioxidant potential was evaluated by employing different assays on the crude methanol extract, as well as its derived fractions.

Iron deficiency anemia in reproductive age women: A survey study of district Bahawalpur, Punjab, Pakistan.

Iron deficiency anemia (IDA) is one of the foremost health issues among women of reproductive age. The study highlights to assess the level of awareness about the causes, symptoms, prevention and treatment of IDA among women of reproductive age in district Bahawalpur, province Punjab, Pakistan. A randomized study was conducted by using a self-designed standardized questionnaire disseminated to the hostels of female residents and homes in the immediate vicinity of Islamia University Bahawalpur.

Bio-guided profiling and HPLC-DAD finger printing of Atriplex lasiantha Boiss.

Background: Plants represent an intricate and innovative source for the discovery of novel therapeutic remedies for the management of various ailments. The current study has been aimed to validate the therapeutic potential of ethnomedicinally significant plant Atriplex lasiantha Boiss.

Methods: The polarity based extraction process was carried out using fourteen solvents to figure out best extraction solvent and bioactive fractions.