An efficient image encryption algorithm using 3D-cyclic chebyshev map and elliptic curve.

With the development of internet technologies, it is now usual to communicate enormous amounts of text and visual data over networks, which calls for stringent procedures to guarantee confidentiality and integrity throughout transmission. An important part of safeguarding image communication over secure channel is cryptography. This study proposes an effective way to secure sensitive data by creating tamper-proof cryptosystems and authentication mechanisms.

QbD Approach for the Development of Tea Tree Oil-Enhanced Microemulgel Loaded with Curcumin and Diclofenac for Rheumatoid Arthritis Treatment.

Rheumatoid arthritis, a chronic autoimmune disorder affecting millions worldwide each year, poses a significant threat due to its potential for progressive joint damage and debilitating pain if left untreated. Topical anti-inflammatory and analgesic treatments offer localized relief with reduced systemic side effects compared to conventional oral therapies, making them a promising option for managing rheumatoid arthritis. Therefore, the current study endeavored to formulate a microemulsion gel formulation loaded with diclofenac and curcumin for topical administration in the management of rheumatoid arthritis, utilizing Tea tree oil.

Electronic Structure Modulating of WO Nanospheres by Niobium Doping for Efficient Hydrogen Evolution Reaction.

Hydrogen, known for its high energy density and environmental benefits, serves as a prime substitute for fossil fuels. Nonetheless, the hydrogen evolution reaction (HER), essential in electrolysis, encounters challenges with slow kinetics and significant overpotential, which elevate costs and reduce efficiency. Thus, developing efficient electrocatalysts to reduce HER overpotential is vital to enhance hydrogen production efficiency and minimize energy consumption.

Harnessing the synergistic potential of TiO-CuSe composites for enhanced photocatalytic and antibacterial activities.

With growing environmental concerns, the removal of toxic industrial dyes from wastewater has become a critical global issue. In this study, TiO-CuSe composites were synthesized using a cost-effective and simple chemical method to determine the optimal concentration of CuSe for the efficient degradation of methylene blue (MB) under visible light. The TiO samples exhibited a mix of rutile and anatase phases, while CuSe formed in a hexagonal phase.

Genito Urinary Infection and Urinary Tract Infection in Patients with Type 2 Diabetes Mellitus Receiving SGLT2 Inhibitors: Evidence from a Systematic Literature Review of Landmark Randomized Clinical Trial.

Background And Purpose: SGLT2 inhibitors are class of drugs that are used in adults with type 2 diabetes through a novel mechanism of action by reducing renal tubular glucose reabsorption, leading to a reduction in blood glucose without stimulating insulin release. In this systematic review, we report the effects of treatment with SGLT2 inhibitors on urinary tract infection (UTI) and genitourinary infection (GUI).

Method: The study integrated data from landmark trials of SGLT2 inhibitors (CANVAS, CREDENCE, DECLARE-TIMI 58, and EMPA-REG) to interpret the association of SGLT2 inhibitors with genital infection (GI) and UTI.

Isolation of a novel isoprenylated phenolic compound and neuroprotective evaluation of extract against cerebral ischaemia-reperfusion injury in rats.

Dodonaea grows widely in Saudi Arabia, but studies evaluating its neuroprotective activity are lacking. Thus, this study aimed to isolate and identify the secondary metabolites and evaluate the neuroprotective effects of D. viscosa leaves.

Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs.

Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulatory chest radiographs (CXRs) frequently ordered, we investigated detecting type 2 diabetes (T2D) by combining radiographic and EHR data using a DL model. Our model, developed from 271,065 CXRs and 160,244 patients, was tested on a prospective dataset of 9,943 CXRs.

Validation of a deep learning, value-based care model to predict mortality and comorbidities from chest radiographs in COVID-19.

We validate a deep learning model predicting comorbidities from frontal chest radiographs (CXRs) in patients with coronavirus disease 2019 (COVID-19) and compare the model's performance with hierarchical condition category (HCC) and mortality outcomes in COVID-19. The model was trained and tested on 14,121 ambulatory frontal CXRs from 2010 to 2019 at a single institution, modeling select comorbidities using the value-based Medicare Advantage HCC Risk Adjustment Model. Sex, age, HCC codes, and risk adjustment factor (RAF) score were used.

Deep Learning-Based Digitally Reconstructed Tomography of the Chest in the Evaluation of Solitary Pulmonary Nodules: A Feasibility Study.

Rationale And Objectives: Computed tomography (CT) is preferred for evaluating solitary pulmonary nodules (SPNs) but access or availability may be lacking, in addition, overlapping anatomy can hinder detection of SPNs on chest radiographs. We developed and evaluated the clinical feasibility of a deep learning algorithm to generate digitally reconstructed tomography (DRT) images of the chest from digitally reconstructed frontal and lateral radiographs (DRRs) and use them to detect SPNs.

Methods: This single-institution retrospective study included 637 patients with noncontrast helical CT of the chest (mean age 68 years, median age 69 years, standard deviation 11.

Chemical constituents from and their antimicrobial activity.

A new sesquiterpene lactone, 3β,10α-dihydroxy-10β-(hydroxymethyl)-8α-(4-hydroxymethacrylate)-1α,5α,6β7α-guai-4(15), 11(13)-dien-6,12-olide (), along with twenty-one known compounds, were identified from the aerial parts of . The structures of the isolated compounds were elucidated on the basis of spectroscopic evidences and correlated with known compounds. Compounds (, , and ) were identified from for the first time.

Assessment of the knowledge beliefs and associated factors among Saudi adults towards blood donation in Saudi Arabia.

Background: Blood transfusion is essential in the treatment of a wide range of illnesses. There are two sorts of donors in the blood donation system voluntary and replacement donors.

Objectives: In this study, we examined Saudi adults' knowledge, beliefs, and associated factors towards blood donation in Saudi Arabia.

Cytotoxicity and molecular docking analysis of racemolactone I, a new sesquiterpene lactone isolated from .

Context: Traditionally, Hook. f. (Asteraceae) has been reported to be effective in cancer treatment which motivated the authors to explore the plant for novel anticancer compounds.

PI3K-AKT Pathway Modulation by Thymoquinone Limits Tumor Growth and Glycolytic Metabolism in Colorectal Cancer.

Colorectal cancer (CRC) is the third leading cause of death in men and the fourth in women worldwide and is characterized by deranged cellular energetics. Thymoquinone, an active component from Nigella sativa, has been extensively studied against cancer, however, its role in affecting deregulated cancer metabolism is largely unknown. Further, the phosphoinositide 3-kinase (PI3K) pathway is one of the most activated pathways in cancer and its activation is central to most deregulated metabolic pathways for supporting the anabolic needs of growing cancer cells.

Attitudes and Associated Demographic Factors Contributing towards the Abuse of Illicit Drugs: A Cross-Sectional Study from Health Care Students in Saudi Arabia.

: The purpose of this study is to compare the attitudes, views, and factors that influence drug abuse among pharmacy and nursing students at a Saudi Arabian university. : A cross-sectional study, was conducted among pharmacy and nursing students who are currently enrolled in the respective courses at the study site. The data were collected over 4 months from August to November 2019 using structured self-administered paper-based questionnaires.

Detecting Racial/Ethnic Health Disparities Using Deep Learning From Frontal Chest Radiography.

Purpose: The aim of this study was to assess racial/ethnic and socioeconomic disparities in the difference between atherosclerotic vascular disease prevalence measured by a multitask convolutional neural network (CNN) deep learning model using frontal chest radiographs (CXRs) and the prevalence reflected by administrative hierarchical condition category codes in two cohorts of patients with coronavirus disease 2019 (COVID-19).

Methods: A CNN model, previously published, was trained to predict atherosclerotic disease from ambulatory frontal CXRs. The model was then validated on two cohorts of patients with COVID-19: 814 ambulatory patients from a suburban location (presenting from March 14, 2020, to October 24, 2020, the internal ambulatory cohort) and 485 hospitalized patients from an inner-city location (hospitalized from March 14, 2020, to August 12, 2020, the external hospitalized cohort).

Diabetes Mellitus during the Pandemic Covid-19: Prevalence, Pathophysiology, Mechanism, and Management: An updated overview.

Background: Diabetes mellitus (DM) is among the most frequently reported comorbidities in patients tainted with the pandemic coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With a high pervasiveness of diabetes mellitus, there is an urgency to understand the special aspects of COVID-19 in hyperglycemic patients. Diabetic patients are at higher risk than the general population of viral or bacterial infections, thus require special attention since diabetes is linked with severe, critical, and lethal modes of COVID-19.

Amelioration of Experimental Hepatotoxicity in Rats by Portulaca oleracea Linn. from Kashmir Himalaya.

Background: Traditionally, Portulaca oleracea Linn. is used for treating abscesses, dysentery and liver diseases. In addition, recent studies have reported its efficacy as an analgesic, as neuroprotective, anti-inflammatory, bronchodilatory, and anticancer agent, besides antioxidant, wound healing and other important pharmacological actions.

Predicting Prolonged Hospitalization and Supplemental Oxygenation in Patients with COVID-19 Infection from Ambulatory Chest Radiographs using Deep Learning.

Rationale And Objectives: The clinical prognosis of outpatients with coronavirus disease 2019 (COVID-19) remains difficult to predict, with outcomes including asymptomatic, hospitalization, intubation, and death. Here we determined the prognostic value of an outpatient chest radiograph, together with an ensemble of deep learning algorithms predicting comorbidities and airspace disease to identify patients at a higher risk of hospitalization from COVID-19 infection.

Materials And Methods: This retrospective study included outpatients with COVID-19 confirmed by reverse transcription-polymerase chain reaction testing who received an ambulatory chest radiography between March 17, 2020 and October 24, 2020.

Box-Behnken Design (BBD)-Based Optimization of Microwave-Assisted Extraction of Parthenolide from the Stems of and Cytotoxic Analysis.

Parthenolide, a strong cytotoxic compound found in different parts of which motivated the authors to develop an optimized microwave-assisted extraction (MEA) method using Box-Behnken design (BBD) for efficient extraction of parthenolide from the stem of and its validation by high-performance thin-layer chromatography (HPTLC) and cytotoxic analysis. The optimized parameters for microwave extraction were determined as: 51.5 °C extraction temperature, 50.

Phytochemical screening and anti-oxidant activity of enhances the anti-bacterial activity against .

In this study, the phytochemical, phenolic, flavonoid and bioactive compounds were successfully screened from crude extract of by LC-MS analysis after NIST interpretation. Bacterial growth inhibition study result was shown with 24 mm zone inhibition at 200 µg/mL concentration against . The increased phenolic content was much closed to gallic acid and the range was observed at 250 μg/mL concentration.

Design, Synthesis, Molecular Modelling, and Biological Evaluation of Oleanolic Acid-Arylidene Derivatives as Potential Anti-Inflammatory Agents.

Introduction: Oleanolic acid, a pentacyclic triterpenic acid, is widely distributed in medicinal plants and is the most commonly studied triterpene for various biological activities, including anti-allergic, anti-cancer, and anti-inflammatory.

Methods: The present study was carried out to synthesize arylidene derivatives of oleanolic acid at the C-2 position by Claisen Schmidt condensation to develop more effective anti-inflammatory agents. The derivatives were screened for anti-inflammatory activity by scrutinizing NO production inhibition in RAW 264.

The Reproductive Toxicity Associated with , a Folk Medicinal Plant in Saudi Arabia.

is a medicinal plant which is being used to treat various diseases in humans. The available safety data suggest that the plant does not produce any side effects, or toxicity, in tested adult experimental animals. However, the influence of on fetus or embryonic development is largely not known.