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Objective This research aimed to analyze the prevalence, molecular characteristics, toxinotyping, alpha toxin production potential, and antibiotic resistance pattern of Clostridium perfringens (C. perfringens) isolates in meat samples collected from various sources. Methods Sixty meat samples were screened for alpha toxin using enzyme-linked immunosorbent assay, revealing a positivity rate of 13.3%, predominantly in raw poultry meat. Subsequent culturing on Perfringens agar identified nine samples harboring characteristic C. perfringens colonies, primarily isolated from raw poultry meat. Molecular confirmation through 16S rRNA gene amplification and sequencing authenticated twelve isolates as C. perfringens, with nine strains exhibiting genetic resemblance to locally isolated strains. Toxinotyping assays targeting alpha toxin-specific genes confirmed all nine isolates as type A C. perfringens, with no detection of beta or epsilon toxin genes. Hemolytic assays demonstrated varying alpha toxin production potentials among isolates, with accession number OQ721004.1 displaying the highest production capacity. Moreover, antibiotic resistance profiling revealed multi-drug resistance patterns among the isolates. Results The study identified distinct clusters within C. perfringens strains, indicating variations. Phylogenetic analysis delineated genetic relatedness among strains, elucidating potential evolutionary paths and divergences. Conclusion The findings underscore the need for robust surveillance and control measures to mitigate the risk of C. perfringens contamination in meat products, particularly in raw poultry meat. Enhanced monitoring and prudent antimicrobial stewardship practices are warranted in both veterinary and clinical settings to address the observed antibiotic resistance profiles and prevent foodborne outbreaks.

Abstract Background Nonspecific neck pain (NSNP) is a well-established global burden affecting. It is also a common problem in Pakistan. The burden of neck pain is also increasing day by day due to poor work ergonomics, and increased use of computers and mobiles after the pandemic. An individual’s poor posture is often associated with forward head posture (FHP). Limited evidence is available about the effects of neck stabilization (NSE) and dynamic exercises (NDE) for nonspecific neck pain particularly in patients with FHP. This aimed to compare the effects of NSE versus NDE among patients having NSNP with FHP in reducing pain, disability, forward head posture and improving neck range of motion. Methods It is a single-blinded randomized clinical trial with 60 patients aged 18–40 years, with moderate intensity NSNP for > 3 weeks and 0.05) for post-treatment mean VAS, neck ROM, NDI and plumb line measurement. Conclusion Between NSE and NDE, no one is more beneficial than another. Both are equally effective in alleviating pain, increasing ROM, decreasing functional disability, and improving forward head posture in patients with NSNP. Trial Registration Registered trial at ClinicalTrials.gov Identifier: NCT05298631, 28/03/2022, prospectively registered.

The food industry is faced with a significant challenge in maintaining the viability and stability of probiotics during processing and in model food. Encapsulation technology offers a promising solution to this issue. This study was aimed to investigate the effect of Sodium Alginate (SA) and arabinoxylan (AX) composite encapsulation on the viability & stability of Lactobacillus rhamnosus GG. The AX was extracted from maize and characterized, and then the SA-AX composite was used to encapsulate the probiotics. The resulting microbeads were analyzed for their morphological, molecular, and physicochemical properties. The MAX-SA microbeads demonstrated the highest efficiency at 97.9 ± 0.6%, followed by MAX at 95 ± 1.5% and SA at 92 ± 1.4%. The FTIR spectra revealed specific functional groups in the samples. The MAX-SA and MSA matrices had a dispersed structure, while the MAX matrix had a smooth microstructure. The microcapsules had an average size ranging from 718 ± 2 mm to 734 ± 2 mm. The viability of the encapsulated probiotics was assessed under storage conditions, simulated gastrointestinal conditions, and model food. Encapsulated probiotics showed higher viability than free probiotics in simulated gastrointestinal conditions, and pineapple juice fortified with encapsulated probiotics showed a higher probiotic count. Overall, the study found that MAX-SA was the most effective in maintaining probiotic viability under stressed conditions.

Abstract Background Bovine mastitis results in significant economic losses for the dairy industry globally due to milk production losses and decreased herd efficiency. This research aimed to isolate, select, and characterize indigenous lactobacilli with probiotic properties. A total of 40 lactobacilli were isolated from healthy milk samples of cattle and identified at the species level through 16S rDNA sequencing. All isolates were initially screened for antimicrobial activity, and selected isolates underwent in vitro assessment of probiotic properties. Results Among the lactobacilli isolates, varying levels of activity (9 to 19 mm) against cattle mastitogens; Stapylococcus aureus (Staph. aureus), Escherichia coli (E. coli) and Streptococcus dysgalactiae (Strep. dysgalactiae) were observed in the well diffusion assay. These isolates demonstrated auto-aggregation (ranging from 14.29 ± 0.96% to 62.11 ± 1.09%) and co-aggregate (ranging from 9.21 ± 0.14% to 55.74 ± 0.74%) with mastitogens after 2 h. Lactobacillus (Lb.) plantarum CM49 showed sensitivity to most antibiotics tested and exhibited strong inhibitory effects, with mean log10 reductions of 3.46 for Staph. aureus, 2.82 for E. coli, and 1.45 for Strep. dysgalactiae in co-culture experiments. Furthermore, Lb. plantarum CM49 significantly decreased the adhesion rate of mastitogens on the bovine mammary cell line and mouse model, demonstrating its potential effectiveness in preventing mastitis. Conclusion It is concluded that Lb. plantarum CM49 has remarkable probiotic potential with activity against cattle mastitogens in the laboratory and cell culture and competitively excludes mastitogens from bovine mammary cells and ameliorates Staph. aureus-induced mastitis in mice.

Abstract The concept of the Human Digital Twin (HDT) has recently emerged as a new research area within the domain of digital twin technology. HDT refers to the replica of a physical-world human in the digital world. Currently, research on HDT is still in its early stages, with a lack of comprehensive and in-depth analysis from the perspectives of universal frameworks, core technologies, and applications. Therefore, this paper conducts an extensive literature review on HDT research, analyzing the underlying technologies and establishing typical frameworks in which the core HDT functions or components are organized. Based on the findings from the aforementioned work, the paper proposes a generic architecture for the HDT system and describes the core function blocks and corresponding technologies. Subsequently, the paper presents the state of the art of HDT technologies and their applications in the healthcare, industry, and daily life domains. Finally, the paper discusses various issues related to the development of HDT and points out the trends and challenges of future HDT research and development.

Objective: The present study aimed to evaluate the clinical benefits and drawbacks of administering ECMO/ECLS therapies to drug-intoxicated patients.Methods: From inception until April 30, 2024, an extensive search was performed on four main databases:PubMed, Web of Science, Cochrane Library, and EMBASE. There was no restriction on the search period. Onlythe studies that reported survival to hospital discharge rates, adverse events, and the utilization of ECMO/ECLSin the treatment of intoxicated patients were included. On the other hand, articles that did not report adverseevents or hospital discharge rates as outcomes, as well as studies published in languages other than English,were excluded. The evaluated outcomes were the rate of survival to hospital discharge rate and the incidenceof adverse events associated with ECMO therapy. The Newcastle Ottawa scale was employed to appraise eachstudy to determine its methodological quality. The Comprehensive Meta-Analysis (CMA) software (version3.0) for statistical analysis was used, with the random effects model (due to high heterogeneity among thestudies) and a 95% confidence interval.Results: From a total search of 2216 search results, only 10 studies were included. The pooled analysis from10 studies indicated that ECMO therapies among drug-overdosed/poisoned patients were associated witha significant survival to hospital discharge rate of 65.6% ([95% CI: 51.5%-77.4%], p=0.030). However, theoutcomes were highly heterogeneous (I2=83.47%), which could be attributed to the use of several medicinesby different studies. In contrast, ECMO therapies among drug-overdosed patients were associated with asignificant incidence rate of adverse events of 23.1% ([95% CI: 12.3%-39.2%], p=0.002). However, the pooledanalysis had a significant heterogeneity (I2=70.27%).Conclusion: Despite various health complications, extracorporeal membrane treatment enhanced survival tohospital discharge with good neurological outcomes. Hence, it was a viable, effective, and feasible alternativefor managing drug-induced intoxication in patients.

Ebola virus disease (EVD) is a rare, highly contagious and a deadly disease with a variable fatality rate ranging from 30% to 90%. Over the past two decades, Ebola pandemic has severely affected the sub-Sahara region including Democratic Republic of the Congo (DRC), and Uganda. The causative agents of the most EVD cases are three distinct species out of six Ebolaviruses namely Zaire Ebolavirus (ZEBOV), Sudan Ebolavirus (SUDV) and Bundibugyo Ebolavirus (BDBV). In recent years, significant strides have been made in therapeutic interventions. Notably, the US Food and Drug Administration has approved two monoclonal antibodies: InmazebTM (REGN-EB3) and Ansuvimab or Ebanga™. Additionally, many small molecules are currently in the developmental stage, promising further progress in medical treatment. Addressing the critical need for preventive measures, this review provides an in-depth analysis of the licensed Ebola vaccines-Ervebo and the combination of Zabdeno (Ad26.ZEBOV) and Mvabea (MVA-BN-Filo) as well as the vaccines which are currently being tested for their efficacy and safety in clinical studies. These vaccines might play an important role in curbing the spread and mitigating the impact of this lethal disease. The current treatment landscape for EVD encompasses both nutritional (supportive) and drug therapies. The review comprehensively details the origin, pathogenesis, and epidemiology of EVD, shedding light on the ongoing efforts to combat this devastating disease. It explores small molecules in various stages of the development, discusses patents filed or granted, and delves into the clinical and supportive therapies that form the cornerstone of EVD management. This review aims to provide the recent developments made in the design and synthesis of small molecules for scientific community to facilitate a deeper understanding of the disease and fostering the development of effective strategies for prevention, treatment, and control of EVD.

Abstract Manuka honey (MH) has garnered much attention due to its remarkable antimicrobial, anticancer, immunomodulatory and wound-healing properties. This study compared the antiproliferative effects of raw and powdered MH (pMH) on various human and murine cancer cell lines. A detailed metabolomics analysis was also carried out using untargeted ultrahigh-performance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-Q-TOF-MS) to compare the constituents in raw MH and pMH. The results of the viability studies showed that both raw MH and pMH caused a dose-dependent inhibition of tumor cell growth at concentrations of > 1% w/v (equivalent to ~ 10 mg/ml). A differential susceptibility to MH was observed among the cell lines with the human MDA-MB-231 and A549 cells and murine B16.F10 cells being relatively resistant to MH while the murine MC38 colorectal adeno-carcinoma cells showing the most sensitivity. The effect of raw MH and pMH on cell viability was validated using 2 indepndent assays. Metabolomics analysis detected 2440 compounds, out of which 833 were successfully identified. Among these, 90 phytochemical compounds, predominantly comprising terpenoids, flavonoids, coumarins and derivatives, and phenylpropanoic acids, and 79 lipids were identifiable. Significant differences in 5 metabolite classes, including flavonoids, phenols, terpenoids, carbohydrates, and organic acids were observed between the raw and pMH. Moreover, several altered metabolic pathways were identified in pMH compared to raw MH, such as energy metabolism, amino acid metabolism, and various other pathways that collectively influence biological functions associated with cellular growth, signaling, and stress response.

Abstract Diabetes mellitus (DM) is a chronic metabolic disorder characterized by persistent hyperglycemia. It involves disturbances in carbohydrate, fat, and protein metabolism due to defects in insulin secretion, insulin action, or both. Novel therapeutic approaches are continuously being explored to enhance metabolic control and prevent complications associated with the disease. This study investigates the therapeutic potential of kaempherol-3-rhamnoside, a flavonoid, in managing diabetes by modulating the AMP-activated protein kinase (AMPK) pathway and improving metabolic enzyme activities in streptozotocin (STZ) -induced diabetic mice. Diabetic mice were treated with varying doses of kaempherol-3-rhamnoside and/or insulin over a 28-day period. Glycolytic and gluconeogenesis enzyme activities in the liver, fasting blood glucose levels, serum insulin levels, lipid profiles and oxidative stress markers were assessed. Treatment with kaempherol-3-rhamnoside significantly improved glycolytic enzyme activities, reduced fasting blood glucose, and enhanced insulin levels compared to diabetic controls. The compound also normalized lipid profiles and reduced oxidative stress in the liver, suggesting its potential in reversing diabetic dyslipidemia and oxidative damage. Furthermore, kaempherol-3-rhamnoside activated the AMPK pathway, indicating a mechanism through which it could exert its effects. Kaempherol-3-rhamnoside exhibits promising antidiabetic properties, potentially through AMPK pathway activation and metabolic enzyme modulation. These findings support its potential use as an adjunct therapy for diabetes management. Further clinical studies are warranted to validate these results in human subjects.

Background: Plumbago zeylanicum, commonly known as `Chitramula’ and `Chitrak’ and belonging to the family Plumbaginaceae, is a rambling perennial under shrub grown in most parts of India. The present work deals with the pharmacognostical and preliminary phytochemical studies on the roots of Plumbago zeylanica Linn. Objectives: This study aimed to look at the preliminary phytochemical screening and pharmacognostic characteristics of P. zeylanicum roots. Material and Methods: Macroscopy, microscopy, phytochemical screening, physicochemical parameters, and the production of thin-layer chromatograms were used to evaluate the pharmacognostic properties of the Plumbago zeylanicum root. Results: Macroscopic examination revealed brown roots with an unpleasant flavor. Transverse cuts displayed visible features like medullary rays, arteries, secondary xylem, and starch grains. Powder microscopy further revealed secondary xylem elements, trichomes, fibers, and starch grains. Physicochemical properties of Plumbago zeylanicum were determined, including thin-layer chromatography fingerprinting, ash levels, extractive values, and fluorescence analysis, indicating diverse phytoconstituents in the root extract. Conclusion: The extracts contain steroids, alkaloids, saponins, glycosides, terpenoids, flavonoids, and carbohydrates, suggesting potential medicinal applications. The method is a superior alternative to time-consuming and complex steam distillation-based isolation techniques.

Introduction: Undernutrition and tuberculosis (TB) are interrelated, with a bidirectional relationship. Despite its potential impact on nutritional status and TB patient outcomes, there is limited information available on the dietary patterns of TB patients in the Indian TB program. This study aims to address this knowledge gap by evaluating dietary patterns and factors associated with reduced dietary intake among TB patients in a tertiary care center. Methodology: This was a cross-sectional study conducted in a directly observed treatment short center working under the National Tuberculosis Elimination Program. A semi-structured, pretested interviewer-administered questionnaire was used to collect data related to the demographic profile and dietary patterns of 49 patients. Results: The mean calorie intake among the patients was 1525.2 (±897) kcal, whereas the required mean calorie intake was 2231.6 (±409.2) kcal. The mean protein requirement was 66.9 (±15.2) g, whereas the mean protein intake was only 39.2 (±15.4) g. Conclusion: To strive toward the goal of TB elimination in India, the nutritional care of the patient cannot be undermined. The need of the hour is to enforce the nutritional supplementation as well as support program by the government at the national level.

Abstract Background The disability and significant economic costs accredited to Low back pain (LBP) are likely to rise which is an essential problem in low and middle-income countries like Pakistan. The associated factors of LBP are age, sex, and race including physical activity, high spinal load, lifting, bending, and twisting occupations. The literature highlighted there is substantial differences in associated factors of LBP within available studies in developing countries. The objective is to investigate the association of demographic factors and lumbar range of motion with disability in patients with chronic low back. Methods A baseline data analysis was performed as an analytical cross-sectional study among 150 patients with chronic low back in a randomized controlled trial with a duration from March 2020 and January 2021. After recording demographics, Modified-Modified Schober’s test was used to measure lumbar flexion and extension and Oswestry disability index for disability. After the descriptive analysis the continuous variables, age and pain were analyzed with Spearman’s correlation. Variables that were significant in bivariate analysis were then fitted in a multivariable linear regression. The Kruskal–Wallis test was used to analyze variations of disability in gender, marital status, work status, education level, and duration of pain. The p-value of 0.05 was significant. Results The results showed a significant correlation between age and pain in sitting (rh=-0.189, p = 0.021 and rh = 0.788, p 0.05). Conclusions The female gender and unmarried marital status are associated with functional disability. Decreased lumbar range of motion accompanies more disability, while age, education level, and work status do not effect on disability.

Abstract Thermal evaluation of twin wall panel systems was assessed under vibrant hot and arid conditions of weather in the Arabian Peninsula. Two systems of wall panels (0.6 m × 0.6 m) were prepared. The first system was prepared with a 5.0 cm thick extruded polystyrene (XPS) board. While the second system was prepared with 5.0 cm thick layer of foam-mortar encompassing expanded polystyrene (EPS) beads. Both the thermal insulative layers were sandwiched between two 7.5 cm thick concrete layers. The two wall panel systems were thermally evaluated at the same time in a carefully designed test room. Comparison was accomplished between the two wall systems by measuring the U-value (thermal transmittance) and R-value (resistance). The U-value (air to air) for sandwiched XPS concrete wall system was 0.837 W/m2 K while it was 2.527 W/m2 K for sandwiched EPS beads foam-mortar concrete wall system. The mean U-values (surface to surface) of the sandwiched XPS concrete wall system was 1.143 m2 K/W and 0.293 m2 K/W for sandwiched EPS beads foam-mortar concrete wall system. The sandwiched XPS concrete wall system was more efficient than the sandwiched EPS beads foam-mortar concrete wall system in terms of thermal performance. About 4.5 h of time lag was observed for both the wall panel systems between the external surface temperature and the heat transmission in the internal surface. The output of the FEM simulation by ABAQUS is compared with the measured data for Set-1 (period 16-Aug-2022 to 26-Aug-2022). The hourly temperature change on the outer and inner surfaces has good agreement for both sandwiched XPS concrete wall system and sandwiched EPS beads foam-mortar concrete wall system. The simulation can also predict the heat flux through the two wall systems investigated.

Airways, alveoli and the pulmonary tissues are the most vulnerable to the external environment including occasional deliberate or accidental exposure to highly toxic chemical gases. However, there are many effective protective mechanisms that maintain the integrity of the pulmonary tissues and preserve lung function. Alveolar macrophages form the first line of defense against any pathogen or chemical/reactant that crosses the airway mucociliary barrier and reaches the alveolar region. Resident alveolar macrophages are activated or circulating monocytes infiltrate the airspace to contribute towards inflammatory or reparative responses. Studies on response of alveolar macrophages to noxious stimuli are rapidly emerging and alveolar macrophage are also being sought as therapeutic target. Here such studies have been reviewed and put together for a better understanding of the role pulmonary macrophages in general and alveolar macrophage in particular play in the pathogenesis of disease caused by chemical induced acute lung injury.

Key Clinical Message Concurrent recurrence of acute disseminated encephalomyelitis (ADEM) and poststreptococcal glomerulonephritis (PSGN) in a thalassemia intermedia patient is rare and underscores the complexity of autoimmune disorders. This case emphasizes the importance of considering ADEM in the differential diagnosis of children presenting with PSGN accompanied by neurological symptoms. Abstract Post‐streptococcal glomerulonephritis (PSGN) is a common group A streptococcal (GAS) infection sequela. The pathophysiology of PSGN involves immune complex deposition, with type 3 hypersensitivity reaction triggered by GAS. Certain neurological conditions may also arise following a GAS infection, possibly due to molecular mimicry in the brain, a pathophysiology similar to rheumatic fever, another common sequel of GAS infection. We present the case of a child with β‐thalassemia intermedia who exhibited the classic triad (edema, hypertension, hematuria) of PSGN along with neurological manifestations, including a low glasgow coma scale (GCS) score and seizures. Magnetic resonance imaging (MRI) of the brain indicated changes consistent with acute disseminated encephalomyelitis (ADEM). Initially treated with methylprednisolone, the patient eventually received intravenous immunoglobulin (IVIG) due to lack of response. The patient had a good outcome, with complete resolution of all symptoms and no residual neurological deficits. This case underscores the importance of considering ADEM in the differential diagnosis for patients presenting with neurological signs and symptoms following a recent throat infection with GAS. Furthermore, given the increased risk of infection in thalassemia, patients with thalassemia who have a throat infection and neurological symptoms should be evaluated for the possible presence of ADEM.

Background Tuberculosis (TB) remains one of the top infectious killers in the world and a prominent fatal disease in developing countries. This study proposes a prototypical solution to early prevention of TB based on its primary symptoms, signs, and risk factors, implemented by means of machine learning (ML) predictive algorithms. Further novelty of the study lies in the uniqueness of patient dataset collected from three top-ranked hospitals of Sindh, Pakistan, via a self-administered survey patient-records that comprises a set of questions asked by the doctors treating TB patients in real-time. A total of 1,200 survey patient-records were evenly distributed among all three hospitals, viz. ICT Kotri, LUMHS Jamshoro, and Civil Hospital Hyderabad. Methods To develop the required prototypes, the research made use of five distinct benchmark ML algorithms: decision tree (DT), Gaussian naive Bayes (GNB), logistic regression classifier (LRC), adaptive boosting (AdaBoost), and neural network (NN), whose performance was evaluated by considering various performance metrics, i.e., accuracy, precision, recall, F1 score, and confusion matrix. Results The experimental results, graphically visualized and systematically discoursed, demonstrate that early detection of TB classifiers, including DT, GNB, LRC, AdaBoost, and NN, attained accuracy rates of 92.11%, 89.04%, 90.35%, 93.42%, and 92.98%, respectively. These results indicate effective diagnosis of TB disease by each implemented ML algorithm.

Abstract Hylocereus undatus, occasionally referred to as the dragon fruit or white‐fleshed pitaya, is a rich in nutrients fruit appreciated because of its colorful look and health benefits. It is inexpensive in calories but packed with minerals like iron, magnesium, and calcium in addition to essential nutrients like vitamin C and B vitamins. Similarly rich in dietary fiber, particularly promotes gut wellness and improves digestion, is pitaya. It additionally contains antioxidants, such as phenolic compounds, flavonoids, and betalains, which help with scavenging free radicals and reducing the detrimental effects of oxidative stress on the human body. The substantial amount of betalains in Hylocereus undatus phytochemical composition is notable because it contributes to the plant's anti‐inflammatory and antioxidant properties. There has been an association among these phytochemicals and a decreased likelihood of contracting long‐term conditions such as diabetes, cancer, and cardiovascular disease. Omega‐3 fatty acids and omega‐6 fatty acids, in particular, that reduce cholesterol levels while improving blood circulation, are plentiful in the fruit's seeds and are beneficial to heart wellness. The objective of this review is to highlight the nutritional profile, phytochemical and health benefits of Hylocereus undatus in detail.

Cotton is globally known for its high-priority cellulose-rich natural fiber. In addition to providing fiber for the textile industry, it is an important source material for edible oil, livestock feed, and fuel products. Global warming and the growing population are the major challenges to the world’s agriculture and the potential risks to food security. In this context, improving output traits in cotton is necessary to achieve sustainable cotton production. During the last few years, high throughput omics techniques have aided in identifying crucial genes associated with traits of cotton fiber, seed, and plant architecture which could be targeted with more precision and efficiency through the CIRPSR/Cas-mediated genome editing technique. The various CRISPR/Cas systems such as CRISPR/Cas9, CRISPR/nCas9, and CRISPR/Cas12a have been employed to edit cotton genes associated with a wide range of traits including fiber length, flowering, leaf colour, rooting, seed oil, plant architecture, gossypol content, somatic embryogenesis, and biotic and abiotic stresses tolerance, highlighting its effectiveness in editing the cotton genome. Thus, CRISPR/Cas-mediated genome editing has emerged as a technique of choice to tailor crop phenotypes for better yield potential and environmental resilience. The review covers a comprehensive analysis of cotton phenotypic traits and their improvement with the help of the latest genome editing tools to improve fiber, food, feed, and fuel-associated genes of cotton to ensure food security.

Owing to the major development of social media platforms, the usage of technological adaptation increases by means of editing software tools. Posting media in social communication environments has become one of our common daily routines. Before posting, various editing generators are used to manipulate pixel values, such as for enhancing brightness and contrast. Undoubtedly, this software helps bring posting media from ordinary to outstanding. But such a type of editing crosses the line in terms of creating fakes—anything that comes from anywhere and does not retain its originality anyway. It poses a series of issues in the process of multimedia forensics investigation and chain of custody. In order to restrict the attempts at deep faking and make the investigation hierarchy more effective, efficient, and reliable in the socio-cyber space (SCS), this paper presents a novel framework called DF-SCW. A digital forensics-enabled socio-cyber world with artificial intelligence (AI), especially deep neural networks (DNNs), for detecting and analyzing deep fake media investigations on social media platforms. It compares pixels with their neighboring values in the same media (such as images and videos) to identify information about the original one. There is a media flag designed to filter out malicious and dangerous attempts, like a powerful leader declaring war. Putting flags on such fakes helps digital investigators resist sharing the posts. In addition, the other prospect of this research is to make the digital forensics ecosystem more appropriate to take qualitative judgments in real-time while media is uploaded on social media platforms. The simulation of the proposed DF-SCW is tested on three different platforms, such as Instagram, Facebook, and Twitter. Through the experiment, the DF-SCW outperformed in terms of detection, identification, and analysis of deepfake media by an increased rate of 3.77%.

Abstract Background The burden of breast cancer, the second leading cause of death worldwide, is increasing at an alarming rate. Cuscuta, used in traditional medicine for different ailments, including cancer, is known for containing phytochemicals that exhibit anticancer activity; however, the bioactivities of proteins from this plant remain unexplored. This study aimed to screen the cytotoxic potential of proteins from the crude herbal product of Cuscuta epithymum(L.) (CE) harvested from the host plants Alhagi maurorum and Medicago sativa. Methods The proteins from CE were extracted using a salting-out method, followed by fractionation with a gel filtration chromatography column. Gel-free shotgun proteomics was subsequently performed for protein characterization. The viability assay using MTT was applied to deduce the cytotoxic potential of proteins against MCF-7 breast cancer cells, with further exploration of the effect of treatment on the expression of the apoptotic mediator BCL2-associated X protein (BAX) and B-cell lymphoma protein 2 (BCL-2) proteins, using western blotting to strengthen the findings from the in vitro viability assay. Results The crude proteins (CP) of CE were separated into four protein peaks (P1, P2, P3, and P4) by gel filtration chromatography. The evaluation of potency showed a dose-dependent decline in the MCF-7 cell line after CP, P1, P2, and P3 treatment with the respective IC50 values of 33.8, 43.1, 34.5, and 28.6 µg/ml. The percent viability of the cells decreased significantly upon treatment with 50 µg/ml CP, P1, P2, and P3 (P

Background: Common mental disorders (CMDs) among adolescents may hamper their psycho-social development. Aim: This study evaluated the prevalence and determinants of CMD like depression and anxiety among late adolescents of an age of 15-–19 years residing in an urban resettlement colony of southeast Delhi. Methods: A community-based cross-sectional study was carried out among 556 randomly selected adolescents. CMD was assessed using Mini International Neuropsychiatry Interview – Kid version 6 (MINI-Kid) based on DSM-IV TR and compliant with ICD-10 definitions of CMD. The associated risk factors were studied using a self-developed semi-structured interview schedule and analyzed using multi-variable logistic regression. Results: A total of 491 adolescents were interviewed (a response rate of 88.3%), of whom 247 (50.3%) were female and 210 (42.8%) belonged to a lower-middle socio-economic status. The lifetime prevalence of CMD was 34% [95% confidence interval (CI): 29.8–38.2]. Of the total, 22.4% (95% CI: 18.7–6.1) of the participants reported depression and 6.7% (95% CI: 4.5–8.9) reported generalized anxiety disorder during their lifetime. Female sex [adjusted odds ratio (aOR) 2.1, 95% CI: 1.4–2.2], experiencing a stressful event in the past 6 months (aOR 4.7, 95% CI: 3.1–7.3), and smoking tobacco (aOR 2.0, 95% CI: 1.2–7.4) significantly increased the odds of having CMD in multi-variate analysis. Conclusion: There is a high prevalence of CMD among adolescents residing in urban resettlement colonies of Delhi, which is composed mostly of people belonging to lower socio-economic strata. Hence, tailored intervention at stress management with promotion of healthy lifestyle is needed for this age group.

Abstract Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intracellular signaling pathways that regulate various physiological processes. FFAR4 agonists are associated with enhancing insulin release and mitigating the atherogenic, obesogenic, pro-carcinogenic, and pro-diabetogenic effects, normally associated with the free fatty acids bound to FFAR4. In this research, molecular structure-based machine-learning techniques were employed to evaluate compounds as potential agonists for FFAR4. Molecular structures were encoded into bit arrays, serving as molecular fingerprints, which were subsequently analyzed using the Bayesian network algorithm to identify patterns for screening the data. The shortlisted hits obtained via machine learning protocols were further validated by Molecular Docking and via ADME and Toxicity predictions. The shortlisted compounds were then subjected to MD Simulations of the membrane-bound FFAR4-ligand complexes for 100 ns each. Molecular analyses, encompassing binding interactions, RMSD, RMSF, RoG, PCA, and FEL, were conducted to scrutinize the protein–ligand complexes at the inter-atomic level. The analyses revealed significant interactions of the shortlisted compounds with the crucial residues of FFAR4 previously documented. FFAR4 as part of the complexes demonstrated consistent RMSDs, ranging from 3.57 to 3.64, with minimal residue fluctuations 5.27 to 6.03 nm, suggesting stable complexes. The gyration values fluctuated between 22.8 to 23.5 nm, indicating structural compactness and orderliness across the studied systems. Additionally, distinct conformational motions were observed in each complex, with energy contours shifting to broader energy basins throughout the simulation, suggesting thermodynamically stable protein–ligand complexes. The two compounds CHEMBL2012662 and CHEMBL64616 are presented as potential FFAR4 agonists, based on these insights and in-depth analyses. Collectively, these findings advance our comprehension of FFAR4’s functions and mechanisms, highlighting these compounds as potential FFAR4 agonists worthy of further exploration as innovative treatments for metabolic and immune-related conditions.

Abstract An approach is presented to employ two different types of converters in bridgeless configuration for supply side power factor enhancement of the system. The isolated single‐stage electric vehicle battery charger uses two different converters in a bridgeless configuration to extract the advantages of both converters for supply‐side power factor enhancement. For the negative and positive semi‐cycles of the supply voltage, the power factor‐enhanced asymmetrical alternating current–direct current converter utilises a fourth order single‐ended primary‐inductor converter and a second order buck‐boost converter, respectively. The use of single‐ended primary‐inductor converter and buck‐boost converter in bridgeless configuration reduces the net order of the system with respect to conventional bridgeless‐single‐ended primary‐inductor converter schemes. The buck‐boost converter also needs the supply‐side filter to eradicate the unwanted harmonics in the supply current which increases the order of the system. The usage of both converters presents many benefits like input inductance of the single‐ended primary‐inductor converter can be utilised as a filtering element with a capacitor for the buck‐boost converter. The anti‐parallel diode conduction operation of both switches facilitates the elimination of extra reverse feed diodes (generally used in bridgeless schemes). The single‐stage charger itself comes with the benefit of elimination of extra stages and thus the losses associated with it. The presented charger also witnesses the elimination of the rectifier due to usage of bridgeless configuration. The isolated single‐stage electric vehicle battery charger is also garnished with electrical isolation which adds to the safety standard of the system. To attain power factor enhancement, the asymmetrical alternating current–direct current converter functions in discontinuous current conduction mode in the present work. The elimination of extra‐stages (with respect to two stage charger), a filter, a rectifier, two extra reverse‐feeding diodes, one voltage sensor, one current sensor (with respect to continuous current conduction mode), and electrical isolation not only makes the system compact and safer but also makes the system cheaper. Elaborated mathematical modelling and stability analysis of the presented alternating current–direct current converter using a pole‐zero map and bode plot have been included in the article. The prototype and MATLAB/Simulink model of isolated single‐stage electric vehicle battery charger system with discontinuous current conduction mode control has been built and results of both prototype and MATLAB/Simulink are deployed to verify isolated single‐stage electric vehicle battery charger system's performance during dynamic and steady‐state conditions.

Abstract Background Randomized controlled trials and real-world studies suggest that combination therapy with sodium–glucose transport protein 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1RAs) is associated with improvement in fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), systolic blood pressure (SBP), body mass index (BMI), and total cholesterol levels. However, a systematic review of available real-world evidence may facilitate clinical decision-making in the real-world scenario. This meta-analysis assessed the safety and effectiveness of combinations of SGLT2is + GLP-1RAs with a focus on their cardioprotective effects along with glucose-lowering ability in patients with type 2 diabetes mellitus (T2DM) in a real-world setting. Methods Electronic searches were performed in the PubMed/MEDLINE, PROQuest, Scopus, CINAHL, and Google Scholar databases. Qualitative analyses and meta-analyses were performed using the Joanna Briggs Institute SUMARI software package and Review Manager v5.4, respectively. Results The initial database search yielded 1445 articles; of these, 13 were included in this study. The analyses indicated that SGLT2is + GLP-1RAs combinations were associated with significantly lower all-cause mortality when compared with individual therapies (odds ratio [95% confidence interval [CI] 0.49 [0.41, 0.60]; p

Abstract The three-striped roofed (Batagur dhongoka) is a semi-aquatic turtle that belongs to family Geoemydidae. Due to anthropogenic pressure, it has been facing an intense decline of over 80% in its distribution range in the past 50 years. It is considered as 'Critically Endangered' so effective conservation strategies are needed to protect the species by determining their genetic diversity and population genetic structure. This study investigates the genetic diversity, population structure and demographic pattern of B. dhongoka from two Turtle Rescue and Rehabilitation Centre established near Ganga river using mitochondrial cytochrome b (Cyt b: 1140 bp) ; control region (CR: 451 bp) and ten nuclear microsatellite loci. mtDNA results show low levels of nucleotide diversity (π = 0.0022) in B. dhongoka haplotypes and provide evidence for a low substitution rate. The demographic pattern estimated by the Bayesian skyline plot (BSP) analysis indicates historical stability followed by growth in the effective population size, with a recent reduction in population size from ~ 2 thousand years ago. The microsatellite findings show a moderate level of observed heterozygosity (Ho: 0.49). Bayesian-based clustering analysis revealed weak genetic structures in B. dhongoka and presence of admixed assignations suggesting close genetic relationships. These findings shed light on B. dhongoka's genetic status and underline the necessity of comprehensive rehabilitation and relocation programs and conservation and management techniques to ensure the species' long-term survival. In order to ensure the effective protection and conservation of B. dhongoka, the Government of India has taken a proactive measure by incorporating it into Schedule I of the Wildlife (Protection) Act, 1972, as amended in 2022.

Abstract Objective Multi-drug resistance (MDR) has notably increased in community acquired uropathogens causing urinary tract infections (UTIs), predominantly Escherichia coli. Uropathogenic E. coli causes 80% of uncomplicated community acquired UTIs, particularly in pre-menopausal women. Considering this high prevalence and the potential to spread antimicrobial resistant genes, the current study was conducted to investigate the presence of clinically important strains of E. coli in Pakistani women having uncomplicated cystitis and pyelonephritis. Women belonging to low-income groups were exclusively included in the study. Seventy-four isolates from urine samples were processed, phylotyped, and screened for the presence of two Single Nucleotide Polymorphisms (SNPs) particularly associated with a clinically important clonal group A of E. coli (CgA) followed by antibiotic susceptibility testing and genome sequence analysis. Results Phylogroup B2 was most prevalent in patients and 44% of isolates were positive for the presence of CgA specific SNPs in Fumarate hydratase and DNA gyrase subunit B genes. Antibiotic susceptibility testing showed widespread resistance to trimethoprim-sulfamethoxazole and extended-spectrum beta-lactamase production. The infection analysis revealed the phylogroup B2 to be more pathogenic as compared to the other groups. The genome sequence of E. coli strain U17 revealed genes encoding virulence, multidrug resistance, and host colonization mechanisms. Conclusions Our research findings not only validate the significant occurrence of multidrug-resistant clonal group A E. coli (CgA) in premenopausal Pakistani women suffering from cystitis and pyelonephritis but also reveal the presence of genes associated withvirulence, and drug efflux pumps. The detection of highly pathogenic, antimicrobial-resistant phylogroup B2 and CgA E. coli strains is likely to help in understanding the epidemiology of the pathogen and may ultimately help to reduce the impact of these strains on human health. Furthermore, the findings of this study will particularly help to reduce the prevalence of uncomplicated UTIs and the cost associated with their treatment in women belonging to low-income groups.

The establishment of innovative and sustainable ways to utilize the food moieties is the major concern of the society in modern world. However, there are variety of food components which are being neglected despite of the fact that they are the excellent source of nutritional and bioactive components. Maize (Zea mays L.) is the leading cereal crop in the world, with the highest productivity for feed, food, and industrial uses. It is a milling by-product produced from the outer layer of the maize kernel and an economical and sustainable source of dietary fiber and phenolic compounds. Maize bran is a rich source of bioactive compounds, including non-starch polysaccharides (arabinoxylans and feruloylated arabinoxylans), ferulic, p-coumaric, and syringic acid among other cereal bran. These bioactive compounds have been extracted using different methods and have been reported to reduce the severity of various chronic diseases, like cardiovascular diseases, diabetes mellitus, oxidative damage, and neurodegenerative disorders. In the current review, we focused to conduct an integrative analysis of peer-reviewed research on maize bran; milling, nutritional profile, extraction of bioactive compounds, potential health benefits, and effects on the rheological and sensorial properties of the end product.

The aim of this study was to investigate the effects of different encapsulation materials, namely Sodium alginate, Whey protein isolate, Kappa-carrageenan, and Citrus pectin, on the viability and stability of probiotics. The probiotics were encapsulated using the internal gelation method and the resulting microbeads were measured for their size and encapsulation efficiency. The viability of Lactobacillus acidophilus, both free and encapsulated, was evaluated under gastric and intestinal conditions. The results revealed that all wall materials had a significant impact (p

Honey is a prebiotic food that has many health benefits. Honey contains oligosaccharides that can be used to protect sensitive bioactive compounds. The purpose of this study was to see how encapsulation affects the survival of probiotics under different conditions. L. rhamnosus GG was encapsulated with sodium alginate and honey. The study had three treatments: free probiotics (control), encapsulated probiotics with sodium alginate (MWS) and encapsulated probiotics with honey (MWH). The microcapsules were analyzed using morphology, scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FT-IR). The survival of both free and encapsulated probiotics was tested under simulated gastrointestinal conditions and high temperatures. Encapsulation with honey had significantly higher encapsulation efficiency (97%) and the probiotics encapsulated with honey had a higher survival rate compared to free cells. In conclusion, adding honey to encapsulated probiotics can improve their viability and stability under stressful conditions.

Food safety assurance systems are growing increasingly strict in both industrialized and developing nations as a result of increased, both real and perceived food safety concerns. This is happening as a result of developments in both public (such as direct regulation and product liability) and private (such as self and third-party certification) quality control systems. This study assessed the microbial safety, heavy metals contamination, and sensorial characteristics of beef seekh kababs made by local and branded restaurants in Faisalabad. A total of 24 samples were collected from four regions (R1 Lyallpur town, R2 Madina town, R3 Jinnah town, and R4 Iqbal town) of Faisalabad, and analyzed. Physicochemical parameters including moisture, fat, pH, ash, proteins and color (L*, b* and a*), microbiological parameters such as total plate count (TPC), total Coliform count (TCC), E. coli O157:H7, and heavy metals (Cd, Fe, Pb, and Zn) content were determined. Moreover, the lab supervisor and 18 food technology students, who had prior tasting experience, conducted sensory tests on the samples. They evaluated the samples right after they reached the laboratory, before any other analyses. Results showed that the R2 (Local) sample had the significantly (p

AbstractTriglyceride (TG) buildup in the liver is a hallmark of the metabolic disorder of non-alcoholic fatty liver disease (NAFLD). The four pathogenic categories mainly followed by the NAFLD pathway are hepatocellular carcinoma, non-alcoholic steatosis, steatohepatitis, and progressive fibrosis or cirrhosis. The likelihood of developing NAFLD rises with obesity and insulin resistance. Aging, gender, culture, and ethnicity are all associated with NAFLD, which substantially correlates to liver disorders in both kids and adults. It is prevalent throughout all age ranges. Visceral obesity appears to be exacerbated by poor lifestyle choices such as hypercaloric diets, particularly those high in trans-fat or saturated fat and cholesterol, and sugar-sweetened beverages. Decreasing calorie intake, boosting soy protein and whey ingestion, supplementing with monounsaturated fats, omega-3 fatty acids, and fiber, and changing one’s lifestyle are the initial steps in managing this condition. Polyphenolic substances also have both therapeutic and preventative benefits. Activity and exercise that promotes weight loss and lessen liver fat formation are just as important as maintaining a balanced diet. The patients turn into susceptible to liver transplantation owing to improper concern (the end stage of NAFLD). Examining the impact of nutrition on nonalcoholic fatty liver disease (NAFLD) is the goal of this review. Included in this is a result of an unbalanced intake of macronutrients. The pathogenesis of NAFLD involves nutrition. Individuals with NAFLD must be recommended to restrict calorie consumption and set intake limits when following low-fat/carbohydrate diets.

Background & Aims: Wilson disease (WD) is caused by accumulation of copper primarily in the liver and brain. During maintenance therapy of WD with D-penicillamine, current guidelines recommend on-treatment ranges of urinary copper excretion (UCE) of 200-500 μg/24 h and serum non-ceruloplasmin-bound copper (NCC) of 50-150 μg/L. We compared NCC (measured by two novel assays) and UCE from patients with clinically stable WD on D-penicillamine therapy with these recommendations. Methods: This is a secondary analysis of data from the Chelate trial (NCT03539952) that enrolled physician-selected patients with clinically stable WD on D-penicillamine maintenance therapy (at an unaltered dose for at least 4 months). We analyzed laboratory samples from the first screening visit, prior to interventions. NCC was measured by either protein speciation (NCC-Sp) using anion exchange high-performance liquid chromatography protein speciation followed by copper determination with inductively coupled plasma mass spectroscopy or as exchangeable copper (NCC-Ex). NCC-Sp was also analyzed in healthy controls (n = 75). Results: In 76 patients with WD with 21.3±14.3 average treatment-years, NCC-Sp (mean±SD: 56.6±26.2 μg/L) and NCC-Ex (mean±SD: 57.9±24.7 μg/L) were within the 50-150 μg/L target in 61% and 54% of patients, respectively. In addition, 36% and 31%, respectively, were even below the normal ranges (NCC-Sp: 46-213 μg/L, NCC-Ex: 41-71 μg/L). NCC-Ex positively correlated with NCC-Sp (r2 = 0.66, p

Internet of Things (IoT) has become an interesting research domain as numerous devices, preferably equipped with sensors, communication, and actuator modules, are deployed to capture real-time data in the different application areas, such as smart healthcare and industries. These devices have the built-in capacity to directly interact with the physical phenomenon and report any unusual situation within their respective coverage areas, i.e., monitoring a critical patient in the smart hospital but direct communication with a common destination module is not guaranteed and could possibly be very challenging if two or more devices, preferably those in closed proximity, are interested to transmit simultaneously. Therefore, in this manuscript, we are going to present a hybrid slot allocation approach, which is specifically designed for those devices resided in neighborhood and are eager to communication concurrently with a common destination device, i.e., server. In the beginning, the k-mean clustering algorithm is used to group these devices into clusters where server is forced to collect data from devices deployed in the respective coverage areas. Thus, every server generates dedicated slots for active devices and an additional slot for server(s). Similarly, the proposed neighborhood-enabled time division multiple access (TDMA) has the flexibility of assigning multiple slots to a requesting device if available, which is needed in scenarios, such as detection of pest in the field. Additionally, a member device is allowed to migrate (if needed and possible) from one server's coverage region to another. Simulation results confirmed that the proposed approach is better than the existing algorithms (opportunistic TDMA, hybrid TDMA, and non-orthogonal multiple access), particularly in terms of bandwidth, end-to-end delay, and empty slot utilization. The proposed scheme has improved bandwidth and empty slot utilization, which are approximately 15% and 12%, respectively, whereas it has achieved approximately 94.89% utilization of the available slots which was previously 93.4%.

Objective: To assess the relationship between the fingerprint patterns and academic performance of students in Anatomy. Methodology: This Cross-sectional study was conducted in the Anatomy department of Islam Medical and Dental College Sialkot. The duration of the study was from mid-November 2022 to mid-December 2022. A total of 300 healthy medical (1st and 2nd year MBBS) and dental (1st year BDS) students with no injury and deformity, voluntarily participated in this study. The student’s age were 20-22 years. Simple convenient sampling was used. Ethical clearance was obtained before study. Thumb prints were collected along with questionnaire. The study was done by categorizing the pattern into arches, loops and whorls. The academic performance was taken in percentage and classified as above 70 %, between 50 % and 70 % and below 50%. The statistical analysis of categorical data was done by using non-parametric test i.e. chi square test. A P value of < 0.05 was considered statistically significant. Results: The most common pattern observed among students was loops. The students with loop pattern were in high scoring group while students with whorl and arch pattern scored less marks in Anatomy. Conclusion: The percentage of academic performance was higher in students with loops as compared to whorl and arch.

This research paper reports an enhancement of thermal, optical, mechanical and antibacterial activities of the Polyvinyl alcohol–Nanodiamonds (PVA-NDs) composite required for the food packaging industry. The synthesis of composites was done by the wet processing method. The large surface area of NDs facilitated the robust interaction between the hydroxyl group and macromolecular chains of PVA to enhance the hydrogen bonding of PVA with NDs rather than PVA molecules. Thus, a reduction in PVA diffraction peak intensity was reported. NDs improved the thermal stability by preventing the out-diffusion of volatile decomposition products of PVA. The results also revealed an enhancement in tensile strength (∼60 MPa) and ductility (∼180 %). PVA-NDs composite efficiently blocked the UVC (100 %), most of the part of the UVB (∼85 % above 300 nm), and UVA (∼58 %). Furthermore, enhanced antibacterial activities were reported for PVA-NDs composite against E. coli and S. aureus. NDs accumulated around the bacterial cells prevented essential cellular functions and led to death. Hence, this composite could be a promising candidate for safe, thermally stable, strong, flexible, transparent, UV- resistant antibacterial food packaging material.

This research investigates the impact of sea level rise (SLR) on the Indus Delta, a vital ecosystem increasingly vulnerable to climate change repercussions. The objective of this study is to comprehensively assess the flooded areas under various shared socioeconomic pathway (SSP) scenarios based on the Intergovernmental Panel on Climate Change's (IPCC) 6th Assessment Report. The study employs a GIS-based bathtub model, utilizing historical (1995–2014) and IPCC-projected (2020–2150) tide gauge data from Karachi, Kandla, and Okha stations to identify potential inundated areas threatened by coastal flooding. Additionally, it analyzes LANDSAT-derived multispectral images to identify coastal erosion hotspots and changes in the landscape. A supervised random forest classifier is used to classify major landforms and understand alterations in land cover. Furthermore, neural network-based cellular automata simulations are applied to predict future land cover for 2050, 2100, and 2150 at risk of inundation. The results indicate that under different SSP scenarios, the estimated inundated land area varies from 307.36 km2 (5 % confidence on SSP1-1.9) to 7150.8 km2 (95 % confidence on SSP5-8.5). By 2150, the region will lose over 550 km2 of agricultural land and 535 km2 of mangroves (mean SLR projection). This work emphasizes identifying sensitive land cover for SLR-induced coastal flooding. It might fuel future policy and modeling endeavors to reduce SLR uncertainty and build effective coastal inundation mitigation methods.

Pakistan has a conducive condition for the development of a wide range of scrumptious fruits. As a result, the country grows a diverse assortment of tropical and subtropical fruits; the most prized and top-ranked fruit among all fruits grown in Pakistan is citrus. Citrus is the principal fruit that contributes significantly to Pakistan’s export earnings and national income. In this study, the cross-border determinants influencing Pakistan’s citrus exports to its topmost 22 trading partners are examined using a gravity model technique. This is the first large study from Pakistan by using gravity model to check the impact of various cross-border factors on citrus fruit export. The analysis is based on a panel dataset covering the years 2003 to 2021. To estimate the results, the study used fixed effect regression with time and country fixed effects. The results signify that per capita income, population, and some regional dummies are positively associated with citrus exports from Pakistan. Citrus price, distance, exchange rate, and other regional dummies are observed to have an adverse effect on citrus exports. Trade agreements between Pakistan and trade partners such as free trade agreements, preferential trade agreements, and SAFTA, have been observed as important determinants of citrus exports. Citrus exporters in Pakistan can also benefit from understanding the factors that influence export markets. By addressing the challenges identified in this study, Pakistan can enhance its citrus exports and boost its agricultural sector.

Introduction: The Macrophage Migration Inhibitory Factor (MIF), a key pro-inflammatory mediator, is responsible for modulating immune responses. An array of inflammatory and autoimmune diseases has been linked to the dysregulated activity of MIF. The significance in physiological as well as pathophysiological phenomena underscores the potential of MIF as an attractive target with pharmacological relevance. Extensive research in past has uncovered a number of inhibitors, while the ISO-1, or (S, R)-3-(4-hydroxyphenyl)-4,5-dihydro-5-isoxazole acetic acid methyl ester being recognized as a benchmark standard so far. Recent work by Yang and coworkers identified five promising dietary flavonoids, with superior activity compared to the standard ISO-1. Nevertheless, the exact atomic-level inhibitory mechanism is still elusive.Methods: To improve the dynamic research, and rigorously characterize, and compare molecular signatures of MIF complexes with ISO-1 and flavonoids, principal component analysis (PCA) was linked with molecular dynamics (MD) simulations and binding free energy calculations.Results: The results suggest that by blocking the tautomerase site these small molecule inhibitors could modify the MIF activity by disrupting the intrinsic dynamics in particular functional areas. The stability matrices revealed the average deviation values ranging from 0.27–0.32 nm while the residue level fluctuations indicated that binding of the selected flavonoids confer enhanced stability relative to the ISO-1. Furthermore, the gyration values extracted from the simulated trajectories were found in the range of 1.80–1.83 nm.Discussion: Although all the tested flavonoids demonstrated remarkable results, the one obtained for the potent inhibitors, particularly Morin and Amentoflavone exhibited a good correlation with biological activity. The PCA results featured relatively less variance and constricted conformational landscape than others. The stable ensembles and reduced variation in turns might be the possible reasons for their outstanding performance documented previously. The results from the present exploration provide a comprehensive understanding of the molecular complexes formed by flavonoids and MIF, shedding light on their potential roles and impacts. Future studies on MIF inhibitors may benefit from the knowledge gathered from this investigation.

The complex and dynamic networks of river system, vital for the maintenance of biodiversity and ecosystem services, are under pressure due to human-induced water stress disrupting ecological processes. Recognition of the importance of rivers as source of life though has led to efforts towards protecting large rivers, nevertheless the conservation and management of smaller rivers remained mostly neglected, creating significant gaps in ecological restoration initiatives. In the present study, we assess the distribution and population status of Gangetic dolphin (Platanista gangetica) in the small rivers in the Ganga River Basin for integrating it into the basin wide river conservation strategy. We observed that the Gangetic dolphin inhabited most tributaries and sub-tributaries of the Ganga River, with a naïve occupancy rate of Ψ̂ = 0.68 ± 0.04 (mean ± SE) having 606 ± 142.77 (mean ± SE) individuals and accounts for 15% of the total Gangetic dolphin population in the Basin. The results of N-mixture and MaxEnt models demonstrate that channel depth, presence of meanders and water discharge were key predictors of distribution in these rivers, and the proximity to confluences were identified as a critical predictor. About 54% (620 km) of 1150 km of the surveyed river stretches exhibited suitability for dolphins in the Basin, indicated by a probability distribution score of ≥0.50. Combining this data with the available information, we delineated a total of 2850 km stretch covering entire Ganga River System suitable for Gangetic dolphins within the Basin. Notably, the 620 km of suitable stretches identified in smaller rivers represent 22% of the overall suitable stretches across the entire basin. These stretches were translated to conservation priority stretches for systematic conservation planning involving various stakeholders for improved river conservation in the Basin.

Full Potential Linearized Augmented Plane Wave method (FP-LAPW) was employed to investigate the behavior of cubic perovskite CsBeO3 under the influence of pressure. The spin polarized study has been carried out in PBE-GGA approximation under the application of pressure. The variation of pressure is attained by the appropriate reduction of volume for the compound. At equilibrium volume and at 0 GPa, the compound CsBeO3 is found to exhibit energy gap in the spin up direction and the spin down direction is largely conducting. With the reduction of volume and their corresponding increase in pressure, the electronic behavior changes for the compound. At a pressure of about 10 GPa, the s-orbital of Cs atom undergoes energy excitation to higher energy level due to an ordered dispersive effect at s-orbital. This results in the disappearance of energy gap and the compound becomes conducting in spin up direction and the half metallic ferromagnetism is found to disappear at increased pressure. Thermal properties such as Debye temperature and Curie point have been reported in this work. Elastic constants and anisotropy factor have been determined and compared at different pressures.

Abstract A library of novel bis-Schiff base derivatives based on thiobarbituric acid has been effectively synthesized by multi-step reactions as part of our ongoing pursuit of novel anti-diabetic agents. All these derivatives were subjected to in vitro α-glucosidase inhibitory potential testing after structural confirmation by modern spectroscopic techniques. Among them, compound 8 (IC50 = 0.10 ± 0.05 µM), and 9 (IC50 = 0.13 ± 0.03 µM) exhibited promising inhibitory activity better than the standard drug acarbose (IC50 = 0.27 ± 0.04 µM). Similarly, derivatives (5, 6, 7, 10 and 4) showed significant to good inhibitory activity in the range of IC50 values from 0.32 ± 0.03 to 0.52 ± 0.02 µM. These derivatives were docked with the target protein to elucidate their binding affinities and key interactions, providing additional insights into their inhibitory mechanisms. The chemical nature of these compounds were reveal by performing the density functional theory (DFT) calculation using hybrid B3LYP functional with 6-311++G(d,p) basis set. The presence of intramolecular H-bonding was explored by DFT-d3 and reduced density gradient (RGD) analysis. Furthermore, various reactivity parameters were explored by performing TD-DFT at CAM-B3LYP/6-311++G(d,p) method.

Insulin therapy is integral to the treatment of diabetes mellitus. Epidemiologic studies have shown its benefits both in terms of improving glycemic control and reducing the risk for long-term diabetic complications for both type 1 and type 2 diabetes. Despite these benefits, barriers to insulin therapy are well documented and include perceived inconvenience, needle anxiety, and portability of device in case of insulin pumps. Therefore, this study aims to design and simulate a low frequency sonophoretic array for transdermal insulin delivery. This study utilizes COMSOL Multiphysics software to simulate the transducer used to increase the skin permeability for delivering drugs. It consists of $8\times 5$ array of a piezoelectric elements operated at 100 kHz and 1 volt. To evaluate the effectiveness of the transducer, an intricate skin model has been developed that includes all anatomical layers extending to the bone. The skin layers, particularly muscle and bone, exhibit reflective properties, leading to the formation of a standing wave. This phenomenon arises from the impedance mismatch between muscle and bone. Standing wave served to promote the transportation of the drug into the dermal layer, rich with capillary networks. We found that applying standing wave with 100 kHz the achieved pressure of 0.3 MPa induced acoustic streaming for the drug flow of $1605~\frac {\mathrm {\mu g}}{{\mathrm {cm}}^{2}}$ per 24 hours. Also, the precise modulation of ultrasound frequency and voltage is key to controlling peak acoustic pressure, thereby regulating the rate of insulin delivery through the skin.

Abstract The Rhus gall aphid, Schlechtendalia chinensis, feeds on its primary host plant Rhus chinensis to induce galls, which have economic importance in medicines and the food industry. Rhus gall aphids have a unique life cycle and are economically beneficial but there is huge gap in genomic information about this group of aphids. Schlechtendalia chinensis induces rich-tannin galls on its host plant and is emerging as a model organism for both commercial applications and applied research in the context of gall production by insects. Here, we generated a high-quality chromosome-level assembly for the S. chinensis genome, enabling the comparison between S. chinensis and non-galling aphids. The final genome assembly is 344.59 Mb with 91.71% of the assembled sequences anchored into 13 chromosomes. We predicted 15,013 genes, of which 14,582 (97.13%) coding genes were annotated, and 99% of the predicted genes were anchored to the 13 chromosomes. This assembly reveals the endogenization of parvovirus-related DNA sequences (PRDs) in the S. chinensis genome, which could play a role in environmental adaptations. We demonstrated the characterization and classification of cytochrome P450s in the genome assembly, which are functionally crucial for sap-feeding insects and have roles in detoxification and insecticide resistance. This genome assembly also revealed the whole genome duplication events in S. chinensis, which can be considered in comparative evolutionary analysis. Our work represents a reference genome for gall-forming aphids that could be used for comparative genomic studies between galling and non-galling aphids and provides the first insight into the endogenization of PRDs in the genome of galling aphids. It also provides novel genetic information for future research on gall-formation and insect-plant interactions.

In today’s world, technology has engulfed the internet with an excessive amount of unfiltered, spontaneous, and incessant data from multiple sources. Complex algorithms are designed to present information effectively based on user intent. The online experience of users is a combination of various behaviors exhibited to seek information, including searching, sharing, and verifying information. However, this multifaceted user behavior is yet to be explored comprehensively. This research contributes towards proposing a user intent-machine learning model for classifying users based on their online search, share, and verification behavior, identifying different types of users based on their online engagement, and demonstrating that dynamic online interactions can be classified based on their searching, sharing, and verifying behavior. User feedback on online behavior and practices is gathered through a questionnaire, encompassing participants from diverse gender, occupational, and age demographics. Following the extensive feature engineering, the significant features are presented to K-Mean clustering to identify user intent classes or profiles and their characteristics. A supervised learning Linear Discriminant Analysis Classifier (LDAC) is then trained on data to classify these classes. The proposed framework successfully predicted the user intent class with 80% accuracy. The model is further tested on users’ dynamic interaction data gathered through a second user study. The information search, share, and verify activity data is transformed to fit the model and labeled by human raters using the user profiles resulting from clustering. The research achieves an Inter-rater reliability (IRR) of 60%, whereas the model predicted the user with 67% accuracy. This research indicates that a user’s purpose in seeking information, their willingness to share information on social media, and their inclination to view information as credible can all contribute to understanding their intentions, identifying behavioral similarities, and can be used to recognize intent through dynamic interactions that can be used in targeted marketing, and search engine optimization.

Diabetic retinopathy (DR) can be defined as visual impairment caused by prolonged diabetes affecting the blood vessels in the retina. Globally, it stands as the primary contributor to blindness, impacting approximately 191 million individuals. While prior research has addressed DR classification using retinal fundus images, existing methods often focus on isolated lesion detection, lacking a comprehensive framework for the simultaneous identification of all lesions. Previous studies concentrated on early-stage features like exudates, aneurysms, hemorrhages, and blood vessels, sidelining severe-stage lesions such as cotton wool spots, venous beading, very severe intraretinal microvascular abnormalities (IRMA), diffuse intraretinal hemorrhages, capillary degeneration, highly activated microglia, and retinal pigment epithelium (RPE) damage. In this study, a deep learning approach is proposed to classify DR fundus images by severity levels, utilizing GoogleNet and ResNet models based on adaptive particle swarm optimizer (APSO), for enhanced feature extraction. The extracted features from the hybrid model are further used with different machine learning models like random forest, support vector machine, decision tree, and linear regression models. Experimental results showcased the proposed hybrid framework outperforming advanced approaches with a remarkable 94% accuracy on the benchmark dataset. This method demonstrates potential enhancements in precision, recall, accuracy, and F1 score for different DR severity levels.

A D.C. motor's rotational speed is regulated in this study using a PID controller and a fuzzy logic controller. In contrast to the fuzzy logic controller, which uses rules based on knowledge and experience, the proportional-integral-derivative (PID) controller requires a mathematical system model. This study investigates the regulation of a DC motor's velocity using PID and fuzzy logic controllers. The PID controller utilizes a mathematical model and parameter tuning by trial and error. Still, the fuzzy logic controller (FLC) operates on rule-based knowledge, enabling it to handle the nonlinear features of the DC motor effectively. The FLC design entails intricate determinations, including the establishment of a rule base and the process of fuzzification. A total of 49 fuzzy rules have been devised to achieve precise control. Based on MATLAB/SIMULINK simulations, the study concludes that the Fuzzy Logic Controller (FLC) beats the Proportional-Integral-Derivative (PID) controller. The FLC exhibits superior transient and steady-state responses, shorter response times, reduced steady-state errors, and higher precision. This study emphasizes the efficacy of the FLC (Fuzzy Logic Controller) in dealing with the difficulties associated with DC motor control. It presents a strong argument for the suitability and efficiency of FLCs in industrial environments compared to conventional PID (Proportional-Integral-Derivative) controllers. There are a wide variety of ways to construct a fuzzy logic controller. The speed error and the rate of change in the speed error are two inputs to the FLC. Defuzzification is done by focusing on the core of the problem. The results show that FLC is superior to PID controllers in efficiency and effectiveness due to its reduced transient and steady-state factors.

The cyber realm is overwhelmed with dynamic malware that promptly penetrates all defense mechanisms, operates unapprehended to the user, and covertly causes damage to sensitive data. The current generation of cyber users is being victimized by the interpolation of malware each day due to the pervasive progression of Internet connectivity. Malware is dispersed to infiltrate the security, privacy, and integrity of the system. Conventional malware detection systems do not have the potential to detect novel malware without the accessibility of their signatures, which gives rise to a high False Negative Rate (FNR). Previously, there were numerous attempts to address the issue of malware detection, but none of them effectively combined the capabilities of signature-based and machine learning-based detection engines. To address this issue, we have developed an integrated Anti-Malware System (AMS) architecture that incorporates both conventional signature-based detection and AI-based detection modules. Our approach employs a Generative Adversarial Network (GAN) based Malware Classifier Optimizer (MCOGAN) framework, which can optimize a malware classifier. This framework utilizes GANs to generate fabricated benign files that can be used to train external discriminators for optimization purposes. We describe our proposed framework and anti-malware system in detail to provide a better understanding of how a malware detection system works. We evaluate our approach using the Figshare dataset and state-of-the-art models as discriminators. Our results showcase enhanced malware detection performance, yielding a 10% performance boost, thus affirming the efficacy of our approach compared to existing models.