ALL classification using neural ensemble and memetic deep feature optimization.

Acute lymphoblastic leukemia (ALL) is a fatal blood disorder characterized by the excessive proliferation of immature white blood cells, originating in the bone marrow. An effective prognosis and treatment of ALL calls for its accurate and timely detection. Deep convolutional neural networks (CNNs) have shown promising results in digital pathology. However, they face challenges in classifying different subtypes of leukemia due to their subtle morphological differences. This study proposes an improved pipeline for binary detection and sub-type classification of ALL from blood smear images. At first, a customized, 88 layers deep CNN is proposed and trained using transfer learning along with GoogleNet CNN to create an ensemble of features. Furthermore, this study models the feature selection problem as a combinatorial optimization problem and proposes a memetic version of binary whale optimization algorithm, incorporating Differential Evolution-based local search method to enhance the exploration and exploitation of feature search space. The proposed approach is validated using publicly available standard datasets containing peripheral blood smear images of various classes of ALL. An overall best average accuracy of 99.15% is achieved for binary classification of ALL with an 85% decrease in the feature vector, together with 99% precision and 98.8% sensitivity. For B-ALL sub-type classification, the best accuracy of 98.69% is attained with 98.7% precision and 99.57% specificity. The proposed methodology shows better performance metrics as compared with several existing studies.

Functionalized Single Crystal Perovskite Materials for SERS and Their Potential Detection Applications.

Recent advances in detection and diagnostic tools have improved understanding and identification of plant physiological and biochemical processes. Effective and safe Surface Enhanced Raman Spectroscopy (SERS) can find objects quickly and accurately. Raman enhancement amplifies the signal by 1014-1015 to accurately quantify plant metabolites at the molecular level. This paper shows how to use functionalized perovskite substrates for SERS. These perovskite substrates have lots of surface area, intense Raman scattering, and high sensitivity and specificity. These properties eliminate sample matrix component interference. This study identified research gaps on perovskite substrates' effectiveness, precision, and efficiency in biological metabolite detection compared to conventional substrates. This article details the synthesis and use of functionalized perovskites for plant metabolites measurement. It analyzes their pros and cons in this context. The manuscript analyzes perovskite-based SERS substrates, including single-crystalline perovskites with enhanced optoelectronic properties. This manuscript aims to identify this study gap by comprehensively reviewing the literature and using it to investigate plant metabolite detection in future studies.

Thermal and solutal transport by Cattaneo-Christov model for the magnetohydrodynamic Williamson fluid with joule heating and heat source/sink.

This article scrutinizes the 2-dimensional and boundary layer flow of magnetohydrodynamic Williamson fluid flowing on a stretchable surface with variable viscosity. The thermal and solutal rates are examined through the Cattaneo-Christov model with Joule heating, heat source/sink, and chemical reaction. The authors are motivated to conduct this study because of its practical and scientific significance in various processes, including polymer processing, textile industries, food industries, solar energy, biomedical science, wind turbine blades, oil spill clean-up, metal rolling, and forging. With the mentioned assumptions, the partial differential equations are achieved by using the basic governing laws, including momentum law, energy law, and concentration law. This non-linear system of equations is transmuted into ordinary differential equations by taking similarity transformations. The main novelty behind the conduction of this work is the numerical technique, namely the 'Adams-Milne (Predictor-Corrector)' method along with the Runge-Kutta technique on Matlab software, which has not previously been studied by any researcher in the literature. The analytical solution of the determined equations is not possible due to their highly non-linear nature; therefore the multistep numerical method namely the 'Adams-Milne (Predictor-Corrector)' method, along with the Runge-Kutta technique is used to determine the numerical results. The outcomes are noted due to numerous parameters for velocity, temperature, and concentration profiles. The explanation of graphical and numerical results is discussed here. The graphical impression of the Williamson parameter reveals that the velocity and temperature curves diminish for higher inputs of this parameter. The movement of fluid shows the declining behavior for the Hartmann number and viscosity parameter. The solutal and thermal findings due to Cattaneo-Christov heat and mass relaxation coefficients mark the reducing behaviour in respective field. The rise in reaction coefficient decreases the mass distribution. The analyses of comparison of results are also presented here.

Estimation of population median using bivariate auxiliary information in simple random sampling.

To estimate the unknown population median, several researchers have developed efficient estimators but these estimators are unable to provide efficient results in the existence of outliers. Keeping this point in view, the present work suggests enhanced class of robust estimators to estimate population median under simple random sampling in case of outliers/extreme observations. The suggested estimators are a mixture of bivariate auxiliary information and robust measures with the linear combination of deciles mean, tri-mean and Hodges Lehmann estimator. Mathematical properties associated with the improved class of robust estimators are evaluated in terms of bias and mean squared error. Moreover, the potentiality of our suggested estimators as compared to already available estimators is checked by considering two real-life data sets with outlier(s). In addition, a simulation study is also added in this regard. From theoretical and numerical findings, it is observed that our newly suggested estimators outperforms as compared to its competitors.

Repurposing of US-FDA-approved drugs as negative modulators of ubiquitin specific protease-7 (USP7).

Ubiquitin-specific protease7 (USP7) regulates the stability of the p53 tumor suppressor protein and several other proteins critical for tumor cell survival. Aberrant expression of USP7 facilitates human malignancies by altering the activity of proto-oncogenes/proteins, and tumor suppressor genes. Therefore, USP7 is a validated anti-cancer drug target. In this study, a drug repurposing approach was used to identify new hits against the USP7 enzyme. It is one of the most strategic approaches to find new uses for drugs in a cost- and time-effective way. Nuclear Magnetic Resonance-based screening of 172 drugs identified 11 compounds that bind to the catalytic domain of USP7 with dissociation constant (Kd) values in the range of 0.6-1.49 mM. These 11 compounds could thermally destabilize the USP7 enzyme by decreasing its melting temperature up to 9 °C. Molecular docking and simulation studies provided structural insights into the ligand-protein complexes, suggesting that these compounds bind to the putative substrate binding pocket of USP7, and interact with its catalytically important residues. Among the identified 11 hits, compound 6 (oxybutynin), 7 (ketotifen), 10 (pantoprazole sodium), and 11 (escitalopram) also showed anti-cancer activity with an effect on the expression of proto-oncogenes and tumor-suppressor gene at mRNA level in HCT116 cells. The compounds identified in this study can serve as potential leads for further studies.

Biosafety and toxicity assessment of transgenic cotton-harboring insecticide and herbicide tolerant genes on albino mice.

Introduction: Genetic engineering has revolutionized agriculture by transforming biotic and abiotic stress-resistance genes in plants. The biosafety of GM crops is a major concern for consumers and regulatory authorities. Methodology: A 14-week biosafety and toxicity analysis of transgenic cotton, containing 5 transgenes ((Cry1Ac, Cry2A, CP4 EPSPS, VIP3Aa, and ASAL)), was conducted on albino mice. Thirty mice were divided into three groups (Conventional, Non-transgenic, without Bt, and transgenic, containing targeted crop) according to the feed given, with 10 mice in each group, with 5 male and 5 female mice in each group. Results: During the study, no biologically significant changes were observed in the non-transgenic and transgenic groups compared to the control group in any of the study's parameters i.e. increase in weight of mice, physiological, pathological, and molecular analysis, irrespective of the gender of the mice. However, a statistically significant change was observed in the hematological parameters of the male mice, while no such change was observed in the female study group mice. The expression analysis, however, of the TNF gene increases many folds in the transgenic group as compared to the non-transgenic and conventional groups. Conclusion: Overall, no physiological, pathological, or molecular toxicity was observed in the mice fed with transgenic feed. Therefore, it can be speculated that the targeted transgenic crop is biologically safe. However, more study is required to confirm the biosafety of the product on the animal by expression profiling.

A novel immunoinformatics approach for developing a poly-epitope vaccine targeting foot and mouth disease virus, exploiting structural VP proteins.

Foot and mouth Disease virus (FMDV) belongs to Picornaviridae family and Aphthovirus genus causing Foot and mouth disease (FMD) in cloven-hoofed animals. FMDV, a prevalent virus induces both acute and chronic infections with high mutation rates resulting in seven primary serotypes, making vaccine development indispensable. Due to time and cost effectiveness of the immunoinformatic approach, we designed in-silico polyepitope vaccine (PEV) for the curtailment of FMDV. Structural and immunogenic parts of FMDV (Viral Protein 1 (VP1), Viral Protein 2 (VP2), Viral Protein 3 (VP3), and Viral Protein 4 (VP4)) were used to design the cytotoxic T Lymphocyte (CTL), Helper T Lymphocyte (HTL), and B-cell epitopes, followed by screening for antigenic, non-allergenic, Interferon (IFN) simulator, and non-toxicity, which narrowed down to 7 CTL, 3 HTL, and 12 B-cell epitopes. These selected epitopes were linked using appropriate linkers and Cholera Toxin B (CTB) adjuvant for immunological modulation. The physiochemical analyses followed by the structure prediction demonstrated the stability, hydrophilicity and solubility of the PEV. The interactions and stability between the vaccine, Toll like Receptor 3 (TLR3) and Toll like receptor 7 (TLR7) were revealed by molecular docking and Molecular Mechanics/Poisson Boltzmann Surface Area (MMPBSA) with high stability and compactness verified by MD simulation. In-silico immune simulation demonstrated a strong immunological response. FMDV-PEV (Poly epitope vaccine) will be effectively produced in an E. coli system, as codon optimization and cloning in an expression vector was performed. The effectiveness, safety, and immunogenicity profile of FMDV-PEV may be confirmed by further experimental validations.Communicated by Ramaswamy H. Sarma.

The structural and immunogenic parts of FMDV were targeted for developing VaccineCTB-adjuvant and appropriate linkers, enhancing the immunogenicity of the PEVMinimal deformability and high stability of Vaccine using immunoinformaticsStrong antigen-specific humoral and cellular immune response of potential vaccineResults indicating the effectiveness, safety, and immunogenicity of the PEV.

An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.

In the field of medicine, decision support systems play a crucial role by harnessing cutting-edge technology and data analysis to assist doctors in disease diagnosis and treatment. Leukemia is a malignancy that emerges from the uncontrolled growth of immature white blood cells within the human body. An accurate and prompt diagnosis of leukemia is desired due to its swift progression to distant parts of the body. Acute lymphoblastic leukemia (ALL) is an aggressive type of leukemia that affects both children and adults. Computer vision-based identification of leukemia is challenging due to structural irregularities and morphological similarities of blood entities. Deep neural networks have shown promise in extracting valuable information from image datasets, but they have high computational costs due to their extensive feature sets. This work presents an efficient pipeline for binary and subtype classification of acute lymphoblastic leukemia. The proposed method first unveils a novel neighborhood pixel transformation method using differential evolution to improve the clarity and discriminability of blood cell images for better analysis. Next, a hybrid feature extraction approach is presented leveraging transfer learning from selected deep neural network models, InceptionV3 and DenseNet201, to extract comprehensive feature sets. To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. These optimized features subsequently empower multiple classifiers, potentially capturing diverse perspectives and amplifying classification accuracy. The proposed pipeline is validated on publicly available standard datasets of ALL images. For binary classification, the best average accuracy of 98.1% is achieved with 98.1% sensitivity and 98% precision. For ALL subtype classifications, the best accuracy of 98.14% was attained with 78.5% sensitivity and 98% precision. The proposed feature selection method shows a better convergence behavior as compared to classical population-based meta-heuristics. The suggested solution also demonstrates comparable or better performance in comparison to several existing techniques.

An efficient deepfake video detection using robust deep learning.

The creation and manipulation of synthetic images have evolved rapidly, causing serious concerns about their effects on society. Although there have been various attempts to identify deep fake videos, these approaches are not universal. Identifying these misleading deepfakes is the first step in preventing them from spreading on social media sites. We introduce a unique deep-learning technique to identify fraudulent clips. Most deepfake identifiers currently focus on identifying face exchange, lip synchronous, expression modification, puppeteers, and other factors. However, exploring a consistent basis for all forms of fake videos and images in real-time forensics is challenging. We propose a hybrid technique that takes input from videos of successive targeted frames, then feeds these frames to the ResNet-Swish-BiLSTM, an optimized convolutional BiLSTM-based residual network for training and classification. This proposed method helps identify artifacts in deepfake images that do not seem real. To assess the robustness of our proposed model, we used the open deepfake detection challenge dataset (DFDC) and Face Forensics deepfake collections (FF++). We achieved 96.23% accuracy when using the FF++ digital record. In contrast, we attained 78.33% accuracy using the aggregated records from FF++ and DFDC. We performed extensive experiments and believe that our proposed method provides more significant results than existing techniques.

Inversion of the Warburg Effect: Unraveling the Metabolic Nexus between Obesity and Cancer.

Obesity is a well-established risk factor for cancer, significantly impacting both cancer incidence and mortality. However, the intricate molecular mechanisms connecting adipose tissue to cancer cell metabolism are not fully understood. This Review explores the historical context of tumor energy metabolism research, tracing its origins to Otto Warburg's pioneering work in 1920. Warburg's discovery of the "Warburg effect", wherein cancer cells prefer anaerobic glycolysis even in the presence of oxygen, laid the foundation for understanding cancer metabolism. Building upon this foundation, the "reverse Warburg effect" emerged in 2009, elucidating the role of aerobic glycolysis in cancer-associated fibroblasts (CAFs) and its contribution to lactate accumulation in the tumor microenvironment, subsequently serving as a metabolic substrate for cancer cells. In contrast, within high-adiposity contexts, cancer cells exhibit a unique metabolic shift termed the "inversion of the Warburg effect". This phenomenon, distinct from the stromal-dependent reverse Warburg effect, relies on increased nutrient abundance in obesity environments, leading to the generation of glucose from lactate as a metabolic substrate. This Review underscores the heightened tumor proliferation and aggressiveness associated with obesity, introducing the "inversion of the Warburg effect" as a novel mechanism rooted in the altered metabolic landscape within an obese milieu. The insights presented here open promising avenues for therapeutic exploration, offering fresh perspectives and opportunities for the development of innovative cancer treatment strategies.

Assessment of historical and projected changes in extreme temperatures of Balochistan, Pakistan using extreme value theory.

The fundamental consequences of global warming include an upsurge in the intensity and frequency of temperature extremes. This study provides an insight into historical trends and projected changes in extreme temperatures on annual and seasonal scales across "Balochistan, Pakistan". Historical trends are analyzed through the Mann Kendal test, and extreme temperatures (Tmax and Tmin) are evaluated using generalized extreme value (GEV) distribution for historical period (1991-2020) from the observational data and the two projected periods as near-future (2041-2070) and far-future (2071-2100) using a six-member bias-corrected ensemble of regional climate models (RCMs) projections from the coordinate regional downscaling experiment (CORDEX) based on the worst emission scenario (RCP8.5). The evaluation of historical temperature trends suggests that Tmax generally increase on yearly scale and give mixed signals on seasonal scale (winter, spring, summer, and autumn); however, Tmin trends gave mixed signals at both yearly and seasonal scale. Compared to the historical period, the return levels are generally expected to be higher for Tmax and Tmin during the both projection periods in the order as far-future > near-future > historical on yearly and seasonal basis; however, the changes in Tmin are more evident. Station-averaged anomalies of + 1.9 °C and + 3.6 °C were estimated in 100-year return levels for yearly Tmax for near-future and far-future, respectively, while the anomalies in Tmin were found to be + 3.5 °C and + 4.8 °C which suggest the intensified heatwaves but milder colder extreme in future. The findings provide guidance on improved quantification of changing frequencies and severity in temperature extremes and the associated impacts.

Advancements in gene therapy approaches for atrial fibrillation: Targeted delivery, mechanistic insights and future prospects.

Atrial fibrillation (AF) remains a complex and challenging arrhythmia to treat, necessitating innovative therapeutic strategies. This review explores the evolving landscape of gene therapy for AF, focusing on targeted delivery methods, mechanistic insights, and future prospects. Direct myocardial injection, reversible electroporation, and gene painting techniques are discussed as effective means of delivering therapeutic genes, emphasizing their potential to modulate both structural and electrical aspects of the AF substrate. The importance of identifying precise targets for gene therapy, particularly in the context of AF-associated genetic, structural, and electrical abnormalities, is highlighted. Current studies employing animal models, such as mice and large animals, provide valuable insights into the efficacy and limitations of gene therapy approaches. The significance of imaging methods for detecting atrial fibrosis and guiding targeted gene delivery is underscored. Activation mapping techniques offer a nuanced understanding of AF-specific mechanisms, enabling tailored gene therapy interventions. Future prospects include the integration of advanced imaging, activation mapping, and percutaneous catheter-based techniques to refine transendocardial gene delivery, with potential applications in both ventricular and atrial contexts. As gene therapy for AF progresses, bridging the translational gap between preclinical models and clinical applications is imperative for the successful implementation of these promising approaches.

Examining factors influencing public knowledge and practice of proper face mask usage during the COVID-19 pandemic: a cross-sectional study.

Background: The COVID-19 pandemic had an enormous impact on people's quality of life worldwide. Appropriate use of facemasks is an important checkpoint in containing the spread of infection, which was believed to provide the desired level of protection and preserve the community. Given the relative novelty of facemask use in the general population, it is imperative to prioritize the promotion of appropriate facemask utilization and identify factors that may contribute to poor adherence. Aim: This study assessed the factors that determined facemask use among the public. Methods: A cross-sectional questionnaire-based study was conducted among the residents of the Kingdom of Saudi Arabia between November 2020 and January 2021. The current study explored the factors such as demographic characteristics influencing the knowledge and practice of proper use of facemasks. The study included a total of 198 participants. The results were derived through binomial logistic regression analysis to determine the relationship between the demographic characteristics and responses. Results: The key findings of the study which are crucial in developing targeted intervention strategies to enhance the responsible use and disposal of facemasks are gender, income and employment. A significant difference was found between male and female participants regarding a positive approach to using facemasks, such as washing their hands (P = 0.042). In addition, homemakers differed significantly from students, regarding the correct usage of facemasks (P = 0.026). The study participants were aware that hand hygiene is essential when putting on and removing facemasks. Despite wearing facemasks properly, adult participants possessed less knowledge about the hazards of reusing facemasks and appropriate disposal (OR = 0.202, 95% CI [0.032-1.298]). Conclusion: The present research identified gender, income, and employment as the primary attributes that play a pivotal role in the formulation of focused intervention tactics aimed at improving the cautious use and appropriate disposal of facemasks. It is essential to implement nationwide awareness activities, such as information campaigns, to enhance knowledge. Health authorities should establish a functional infrastructure for the collection and disposal of used facemasks by the general public, starting with the dissemination of knowledge. Moreover, the results of the present study have significant implications for health preventive programs aimed at preparing for future pandemics, since they highlight the specific demographic groups that should be prioritized in the development of such policies. Furthermore, it is advisable to integrate these interventional initiatives with national health polices to promote preparedness for handling future pandemics.

Outcome of fleur- de- lis skin paddle latissimus dorsi myocutaneous flap for breast reconstruction.

BACKGROUND: Reconstruction of breast following mastectomy is important in terms of rehabilitating patients of breast cancer. Numerous approaches have been used in the reconstruction process. A procedure that has gained interest of the patients is reconstruction of breast using the autologous form. Main objective of this study is to determine the outcomes of modified fleur-de-lis latissimus dorsi flap in patients undergoing breast reconstruction. METHODOLOGY: This is a retrospective case series which was conducted at the Department of Plastic Surgery, SIMS/Services Hospital, Lahore, from January 2020 till December 2022. 184 patients age 25-60 years and Females with a history of mastectomy, who had to undergo creation of breast shape using a tissue flap from another part of the body at the site of breast following mastectomy were included. All patients were subjected to standard procedure of breast reconstruction with latissimus dorsi flap using modified fleur-de-lis technique and postoperatively weekly assessment in the first month and then monthly until 3 months was carried out and outcome of the study was analysed. RESULTS: The mean age and VAS score of the patients was 49.7 ± 9.17 and 6 ± 2.21, respectively. 57.1 % patients have DCIS, benign in 38 % patients and other tumours were present in 4.9 % patients. Immediate versus delayed reconstruction was done in 63.6 % versus 36.4 % patients respectively. Good aesthetic outcome was achieved in 80.3 % patients CONCLUSION: Modified fleur-de-lis latissimus dorsi flap in patients undergoing breast reconstruction yielded a good aesthetic outcome in the majority of the patients.

Oxidized alginate-gelatin (ADA-GEL)/silk fibroin/Cu-Ag doped mesoporous bioactive glass nanoparticle-based hydrogels for potential wound care treatments.

The present work focuses on developing 5% w/v oxidized alginate (alginate di aldehyde, ADA)-7.5% w/v gelatin (GEL) hydrogels incorporating 0.25% w/v silk fibroin (SF) and loaded with 0.3% w/v Cu-Ag doped mesoporous bioactive glass nanoparticles (Cu-Ag MBGNs). The microstructural, mechanical, and biological properties of the composite hydrogels were characterized in detail. The porous microstructure of the developed ADA-GEL based hydrogels was confirmed by scanning electron microscopy, while the presence of Cu-Ag MBGNs in the synthesized hydrogels was determined using energy dispersive x-ray spectroscopy. The incorporation of 0.3% w/v Cu-Ag MBGNs reduced the mechanical properties of the synthesized hydrogels, as investigated using micro-tensile testing. The synthesized ADA-GEL loaded with 0.25% w/v SF and 0.3% w/v Cu-Ag MBGNs showed a potent antibacterial effect againstEscherichia coliandStaphylococcus aureus. Cellular studies using the NIH3T3-E1 fibroblast cell line confirmed that ADA-GEL films incorporated with 0.3% w/v Cu-Ag MBGNs exhibited promising cellular viability as compared to pure ADA-GEL (determined by WST-8 assay). The addition of SF improved the biocompatibility, degradation rate, moisturizing effects, and stretchability of the developed hydrogels, as determinedin vitro. Such multimaterial hydrogels can stimulate angiogenesis and exhibit desirable antibacterial properties. Therefore further (in vivo) tests are justified to assess the hydrogels' potential for wound dressing and skin tissue healing applications.

Prevalence of Misconceptions and Myths Regarding Oral Health Among Medical and Dental Students in Peshawar, Pakistan.

Background The aim of study is to assess the prevalence of dental myths and misconceptions among the students of medicine and dentistry in Peshawar, Pakistan, and to gauge the quality of dental education, knowledge, and awareness. Methods A cross-sectional descriptive study was conducted on the current students of medicine and dentistry at Rehman Medical College, Rehman College of Dentistry, Gandhara University, Khyber Medical College, and Khyber College of Dentistry. They were questioned regarding their beliefs in dental misconceptions and myths prevalent in Peshawar, Pakistan. Results The sample comprised 400 undergraduate students, of whom 47.5% (190) were males and 52.5% (210) were females. The most held beliefs were that eating sugar does not affect teeth as long as one brushes twice a day (46%), brushing right after a meal is better for teeth (70%), and the extraction of baby teeth does not matter as they are going to be replaced by the permanent teeth in any case (38%). Most of these misconceptions had a significant association with the field of study. Conclusion The issue of myths and misconceptions regarding dental health and care is widespread, even in the academic community. This should be of significant concern to the relevant authorities, and adequate measures must be taken to dispel such false information.

Benzimidazole Derivative (N-{4-[2-(4-Methoxyphenyl)-1H-Benzimidazole-1-Sulfonyl] Phenyl} Acetamide) Ameliorates Methotrexate-Induced Intestinal Mucositis by Suppressing Oxidative Stress and Inflammatory Markers in Mice.

Methotrexate (MTX)-induced intestinal mucositis (IM) is a common side effect in cancer treatment that impairs the immune system and gut microbes, resulting in loss of mucosal integrity and gut barrier dysfunction. The quality of life and outcomes of treatment are compromised by IM. The present study was designed to investigate the mucoprotective potential of the benzimidazole derivative N-{4-[2-(4-methoxyphenyl)-1H-benzimidazole-1-sulfonyl] phenyl} acetamide (B8) on MTX-induced IM in mice. IM was induced by a single dose of MTX in mice and assessed by physical manifestations as well as biochemical, oxidative, histological, and inflammatory parameters. B8 (1, 3, 9 mg/kg) significantly reduced diarrhea score, mitigated weight loss, increased feed intake and, survival rate in a dose-dependent manner. Notably, B8 exhibited a mucoprotective effect evident through the mitigation of villus atrophy, crypt hypoplasia, diminished crypt mitotic figures, mucin depletion, and oxidative stress markers (GSH, SOD, MDA, and catalase concentration). Gene expression analysis revealed that B8 downregulated the mRNA expression of tumor necrosis factor-α (TNF-α), cyclooxygenase-2 (COX-2), interleukin-6 (IL-6), IL-1ß, and nuclear factor-κB (NF-κB) and concurrently upregulated IL-10 expression in contrast to the MTX group. Further, B8 significantly improved the luminal microflora profile by augmenting the growth of Lactobacillus spp. and reducing the number of pathogenic bacteria (E. coli). Additionally, the enzyme-linked immunoassay showed that B8 decreased the levels of pro-inflammatory cytokines. Our findings suggest that B8 had mucoprotective effects against MTX-induced IM and could be used as an adjunct in chemotherapy to deter this side effect.

Association of burnout and harassment among cardiology trainees: Pakistan's perspective.

OBJECTIVE: This study explores the relationship between sexual harassment and burnout among cardiology trainees, shedding light on the prevalence and impact of these experiences in medical practice. METHODS: A cross-sectional online survey was conducted among 518 respondents, with 420 responding to the Sexual Experience Questionnaire (SEQ). The survey measured harassment experiences and their impact on burnout, especially among female physicians. Correlations were analyzed to understand the association between these variables. RESULTS: Out of 1,375 invitees, we received 671 (48.8 %) responses. The study population was divided into two main groups: males (359) and females (312). The study identified a high prevalence of sexual harassment experiences among female physicians, with incidents occurring primarily during training. Moderate to large correlations were observed between SEQ subscales related to colleagues and patients and their families. While sexual harassment was not significantly related to burnout, this study suggests the need for interventions to create a safer medical workplace. Approximately 22 % of male participants (n = 359) reported career-related inappropriate sexual incidents, with 28 % of male physicians experiencing weekly burnout. Among female participants (n = 312), around 37 % reported inappropriate incidents, while 42 % of female physicians felt weekly burnout. CONCLUSION: Sexual harassment in medicine is a pervasive issue with potential implications for physician well-being. Initiatives aimed at changing the organizational response and fostering a more equitable environment are warranted to address this critical concern.