Predisposing Infection with Orthopneumovirus (Hopv) and Orthorubulavirus (Horuv) Causes Increase Susceptibility To Infections with Human Metapneumovirus (Hmpv ) Leading To High Severity of (Artis) in Infants
Viruses are the important causes of acute respiratory tract infections (ARTIs) in infants . (hOPV, and ( hORUV) that included respiratory syncytial viruses whom predisposing viruses for infected with hMPV . Human metapneumovirus (hMPV) , human type 2 orthopneumoviruses hOPV and human orthopnjeumovirus hORUV are among viruses that causes severe (ARTIs) in infants .In this study we aimed to determine the role of (hOPV, hORUV) in decrease of immunity and causes infected with hMPV.That lead to severe (ARTIs). In the current study we aimed to study the human type 2 orthopneumovirus (Hopv ) and human orthorubulavirus (Horuv) in increase susceptibility to infectants with human metapneumovirus (HMPV) that lead to high severity of (ARTIs) in children between (two months to thirteen months)of age . Methodes :- we collected swabs from nasopharyngeal from (180) infants with age less than sex months , started December 2024 to April 2025 taken the samples and diagnosis by real time polymerase chain reactions (RT-PCR ) were used to determined for present of human metapneumovirus (hMPV) , human type 2 orthopneumovirus ((hOPV) include respiratory syncytial virus RSV) and human orthorubulavirus (hORUV), also taken the date for entry the hospital and after that taken the history for each patients and diagnosed if present of present three viruses during first three days and after five days of entry the central teaching hospital of peadiatric , in Baghdad , also determine clinical feature by the chest x-ray . Results :- A total samples that collection from children (180) nasopharyngeal swabs were screened for present of predisposing infection (hMPV) in infants infected with (hOPV) and ((hORUV) include ( respiratory syncytial virus )(RSV) , and the impact with the (hOPV) and (hORUV), for increase severity of (ARTIs) , we observed that higher infection with (hOPV)( from male 54(51.42%) and female 29(38.66%) ),(hORUV) from male 24 (22.85%) and female17 (22.66%) ) , rather than (hMPV) in male 3(2.85%) and female 2 (2.77%) , during the first three days of enter the hospital . While after five days of enter the hospital observed increase severity of ARTIs and increase infected of patients with hMPV,who infected with (hOPV) and (hORUV), during the first week . In this study observed infectious infants, 86(47.8% ) in groups coinfected (hMPV , hOPV), also seen 28(15.6% ) in group patients coinfection with (hORUV ,hMPV) and 60 ( 33.4% )in group of infants infected with the three viruses ( hMPV , hOPV and hORUV ) , while 23(12.8% ) in group infected with hMPV only, non negative results detection in all infants
Human metapneumovirus (hMPV) , human type 2 orthopneumovirus (hOPV )and human type 2 orthopneumoviruse (hOPV), and human orthorubulavirus (hORUV), acute respiratory tract infections (ARTIs) , infants . chest x-ray.
Sattar Gaber Ajeel, Rusul Sahib Hussien Mohmmed Shubber
Gene Expression–Guided Deep Hybrid Models for Robust Lung Cancer Classification and Diagnosis
Lung cancer continues to be the foremost cause of cancer-related deaths globally, accounting for approximately one in five cancer fatalities each year. Despite significant progress in diagnostic imaging and molecular profiling, early detection remains a persistent challenge due to tumor heterogeneity, overlapping histopathological features, and complex molecular signatures. Gene expression analysis has emerged as a powerful tool to understand the biological mechanisms of carcinogenesis and identify potential biomarkers for precision diagnostics. However, the high dimensionality, noise, and intricate correlations inherent in gene expression datasets limit the performance of conventional statistical and machine learning models. To address these challenges, this study introduces a Gene Expression–Guided Deep Hybrid Model (GE-DHM) that integrates Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and Genetic Algorithms (GA) to achieve robust, biologically interpretable lung cancer classification. The proposed framework utilizes GA for optimal gene feature selection, thereby reducing redundancy and dimensionality, followed by CNN and LSTM layers to capture spatial and sequential dependencies in the selected gene profiles. By embedding gene expression guidance within the deep learning structure, the model learns biologically relevant features that enhance both predictive performance and interpretability. Experimental validation using publicly available lung cancer gene expression datasets from The Cancer Genome Atlas (TCGA-LUAD/LUSC) demonstrated that GE-DHM outperforms traditional models, achieving a classification accuracy of 96.4%, with significant improvements in precision, recall, and F1-score metrics. Furthermore, pathway enrichment analysis revealed that top-ranked genes identified by the model were strongly associated with critical oncogenic signaling pathways, including EGFR, KRAS, and TP53, confirming the model’s biological relevance. The findings of this research highlight the potential of hybrid deep learning frameworks in integrating molecular-level insights with computational intelligence for reliable cancer diagnosis. The GE-DHM establishes a robust platform for precision oncology, paving the way for early detection, personalized treatment strategies, and enhanced clinical decision-making in lung cancer management.
Gene expression, deep learning, hybrid model, CNN, LSTM, lung cancer, genetic algorithm.
Manoj B. Mandake, Rahul N. Patil, Suchita Walke, Sanjay S. Jadhav, Yogesh B. Mandake
Fostering Sustainability Competencies Development in Academic Nursing Students Via Social Media-Integrated Educational Approaches
Background: The increasing relevance of environmental health and the global sustainability agenda necessitate the integration of sustainability competencies into academic nursing curricula. It is important to integrate social media into academic nursing curricula to foster the development of sustainability competencies among nursing students. As the healthcare sector significantly impacts environmental health, it is essential that future nurses are equipped with the knowledge, skills, and attitudes required for sustainable practices. Aim: This study aimed to compare the effectiveness of a social media-integrated educational approach in fostering sustainability competencies among academic nursing students. Methods: A quasi-experimental, two-group, pre-test/post-test design was employed. A total of 400 nursing students in the first academic year in faculty of nursing at Sohag university were conveniently sampled and assigned to either an experimental group (n=200), which received a sustainability education program via a dedicated social media platform, or a control group (n=200), which received conventional instruction on the same topic. Data were collected using (Sustainability Consciousness Questionnaire (SCQ) a validated questionnaire measuring knowledge, attitudes, and behaviors related to sustainability both before and after the intervention. Results: The experimental group showed a statistically significant increase in mean knowledge scores (P<0.001), positive attitudes, and self-reported behavioral intentions compared to their pre-test scores. The control group exhibited minimal change. The between-group comparison revealed that the experimental group's post-test scores were significantly higher than those of the control group across all measured competencies (P<0.001). Furthermore, strong positive correlations were found between increased knowledge and improved attitudes and behaviors in the experimental group. Conclusion: The social media-integrated educational approach is significantly more effective than conventional teaching methods in developing sustainability competencies among academic nursing students. Recommendations: These findings suggest that integrating modern, accessible platforms into the curriculum can better prepare future nurses to address the interconnected challenges of health and sustainability in their professional practice. Also, leveraging widely used digital platforms like social media can be an effective and innovative strategy for cultivating essential sustainability competencies in academic nursing students, aligning professional practices with global sustainability goals. Future research should continue to evaluate long-term impacts and explore the scalability of these approaches across diverse cultural and educational contexts.
Sustainability competencies development, Nursing students, Social Media,
Ghalia Elmoghazy Elkasaby, Amany Gamal elgharieb elbardan, Aimee Martinez Amponin, Sahar Hassan Helaly, Manal Mohamed Elkayal, Fatma Mohamed El swerky, Eman Mohamed Mohamed Elsherbeny, Eman Muktar Mohamed Gabr, Alshazaly Abdoalghfar Adam, Eslam Naseib Mou
Elevated IFN-λ and IL-28R Serum Levels and Upregulated IFNL3/IFNLR1 Gene Expression in Iraqi Women with Systemic Lupus Erythematosus
Background: Systemic lupus erythematosus (SLE) is a chronic inflammatory disease characterized by complex interactions of cytokines that are important mediators in the pathogenesis of SLE. However, the important roles of IFNL3 and IFNLR1 in immune responses and their correlation with gene expression levels and serum levels of SLE patients have been identified. Aim of the study: investigated serum IFN-λ and IL-28 levels along with IFNL3/IFNLR1 gene expression in Iraqi women with SLE to determine their association with disease activity . Materials and Methods: The study comprised of 90 participants (60 SLE female patients aged 20-40 years, in addition to 30 healthy females (control group)) , all patients were seen at Medical City (Consultants of Arthritis, Consultant of Dermatology, Lobby of Hematology and Arthritis)/Baghdad Teaching Hospital, with data collected between 1 December 2024- 1 March 2025. The samples were diagnosed by the consultant and the immunology unit in the previously described hospitals according to their protocols . The 60 patients were divided into two groups. Group 2 (G2) consisted of 30 newly diagnosed patients, while Group 3 (G3) included 30 patients who were being treated with hydroxychloroquine 200 mg and prednisolone 5 mg twice daily. The control group consisted of 30 healthy females (G1). 5ml peripheral blood samples were withdrawn from all participants divided into two parts .4.5ml for serological study which performed by elisa assay. Where as , 0.5 ml mixed with TRIzol™ Reagent to extract mRNA and to determine the level of gene expression Result: Newly diagnosed SLE patients (G2) showed a significantly elevated serum IFN-λ and IL-28R levels versus healthy controls (G1) and treated patients (G3) (p<0.001), with both markers exhibiting high diagnostic accuracy (AUCs 0.99 & 0.96). IFNL3 and IFNLR1 gene expression was also significantly upregulated in G2 compared to G1 and G3; IFNL3 expression itself had high diagnostic value (AUC 0.96). While IFNL3 and IFNLR1 expression correlated strongly, serum cytokine levels did not correlate with their corresponding gene expression. Conclusion: In newly diagnosed SLE patients (G2), serum IFN-λ and IL-28R levels were much higher than those present in treated patients (G3) and controls (G1), with these serum biomarkers normalizing after appropriate treatment. Both of these showed very high diagnostic accuracy (AUC 0.99 and 0.96, respectively), and gene expression of IFNL3 and IFNLR1 was upregulated in newly diagnosed SLE patients (G2) vs both age matched treated SLE patients (G3) and controls (G1). Finally, to note, BMI had no significant effect on serum IFN-λ or IL-28R levels in any patient group (G1, G2, G3) respectively. However, significant differences (p<0.001) were found across these three patient groups for both biomarkers across each age bracket.
IFNL3 , IFNLR1 , gene expression, Iraqi women with SLE.
Mohammed Amer Kamil, Hazima Mossa AlAbassi
MTHFR Polymorphisms and Their Association with Biochemical Risk Markers in Type 2 Diabetes Mellitus Complications
Background: Type 2 Diabetes Mellitus (T2DM) is a multifactorial disease with a strong genetic component. The MTHFR C677T polymorphism (rs1801133) has been implicated in various complications associated with T2DM. The present study investigates the role of the MTHFR C677T polymorphism in T2DM patients from Kerala, India. Methods: A cross-sectional study was conducted, involving 40 participants, consisting of 20 T2DM patients and 20 healthy controls. Genotyping of the MTHFR C677T polymorphism was performed using polymerase chain reaction (PCR) and quantitative PCR (qPCR). Sanger sequencing was employed for genotype confirmation. Biochemical parameters, including HbA1c, serum creatinine, and microalbuminuria, were measured using standard clinical assays. The data were analyzed for genotype-phenotype associations using non-parametric tests and Spearman’s correlation. Results: The T allele of the C677T polymorphism was more prevalent in T2DM patients (37.5%) compared to healthy controls (20%). A significant association was found between the T allele and higher HbA1c levels (8.1% ± 1.6% in T2DM patients with CT/TT genotypes versus 7.6% ± 1.5% in CC genotype carriers, p = 0.12). Additionally, microalbuminuria levels were higher in T allele carriers (213.7 mg/L) compared to CC genotype carriers (31.0 mg/L), although this difference did not reach statistical significance (p = 0.09). Serum creatinine levels were also elevated in T allele carriers (1.40 mg/dL) compared to CC genotype carriers (0.85 mg/dL). Spearman’s correlation analysis revealed a moderate positive correlation between HbA1c and microalbuminuria (Rs = 0.76, p = 0.001), indicating that glycemic control is linked to early renal damage in T2DM. Conclusion: Our study suggests that the MTHFR C677T polymorphism is associated with altered glycemic control and potential early renal complications in T2DM patients. Larger, longitudinal studies with homocysteine measurements and ethnically diverse cohorts are needed to validate these findings and better understand the role of MTHFR polymorphisms in T2DM progression.
Type 2 Diabetes Mellitus, HbA1c, Microalbuminuria, Genetic polymorphism
Betty Vincent P, Dr. Shree Laxmi V Hegde
Myocardial Scar Burden Independently Predicts Response to Cardiac Resynchronization Therapy
Objectives: Cardiac resynchronization therapy (CRT) has been shown to improve quality of life and reduce mortality in patients with heart failure. Around 30 - 45% are non-responders to CRT. Determinants of response to CRT have been extensively studied. Faithful efforts were exerted to improve selection criteria for CRT beyond standard measures of electrical dyssynchrony. We aimed to assess the predictive value of amount and distribution of myocardial fibrosis to identify responders to CRT compared to conventional measures. Methodology: 58 patients who underwent CRT implantation on the basis of standard indication were studied. All patients had available myocardial imaging (cardiac MRI or nuclear scan) prior to CRT. Images were analyzed for scar quantification and distribution. Multiple variables were studied. Receiver operator characteristic (ROC) curve analysis was used to evaluate the ability of Global scar to predict response to CRT. Results: 30 patients of 58 were non-responders to CRT. 27 patients had non-ischemic cardiomyopathy, while 31 patients had ischemic cardiomyopathy. 19 patients (70.3%) in the non-ischemic group, and 9 patients (32.2%) in the ischemic group were responders to CRT, with a statistically significant difference, p- value: 0.002. A cutoff threshold of myocardial scar at 22.9% independently predicted response to CRT with a sensitivity of 70% and a specificity of 92.9%. Conclusion: Global myocardial scar burden predicted response to CRT independent of etiology, regional distribution, and measures of electrical dyssynchrony
Cardiac resynchronization therapy, non-responders, myocardial scar, fibrosis distribution, electrical dyssynchrony, heart failure
Shireen Shaban Mohammad, Abdulmohsen Muhammed Almusaad, Dalia Mohamed Ahmed MBBS, Alaa Eldin Rabea Abdelrheim, Khaled Abdelghany Baraka
The diagnostic accuracy of serum lactate among patients with acute intestinal ischemia; A systematic review and meta-analysis
Acute intestinal ischemia (AII) is a rare but severe medical emergency with high mortality, particularly when surgical intervention is delayed, and early diagnosis remains challenging due to the limitations of current diagnostic tools. This diagnostic test accuracy meta-analysis aimed to synthesise evidence on the diagnostic performance of serum lactate, D-lactate, and L-lactate levels for the early diagnosis of AII. A systematic search of 10 databases and registries, including PubMed, EMBASE, and ClinicalTrials.gov, was conducted up to 9 September 2024. Thirteen studies involving 1,978 patients (600 with AII) were included. The pooled sensitivity and specificity of serum lactate were 0.84 (95% CI: 0.81–0.87, I²=82.2%) and 0.60 (95% CI: 0.57–0.62, I²=96.5%), respectively, with an area under the curve (AUC) of 0.836. D-lactate demonstrated higher diagnostic performance, with pooled sensitivity and specificity of 0.94 (95% CI: 0.89–0.98, I²=70.5%) and 0.54 (95% CI: 0.46–0.61, I²=96.4%), respectively, and an AUC of 0.9015. L-lactate showed pooled sensitivity and specificity of 0.81 (95% CI: 0.72–0.87, I²=76.4%) and 0.68 (95% CI: 0.64–0.72, I²=96.9%), with an AUC of 0.8288, while plasma lactate exhibited sensitivity and specificity of 0.82 (95% CI: 0.78–0.86, I²=86.7%) and 0.56 (95% CI: 0.53–0.60, I²=97.3%), with an AUC of 0.8196. All included studies showed a low risk of applicability concerns regarding patient selection, though two had unclear risk concerning the index test. Significant heterogeneity was observed across studies. Overall, lactate levels—particularly D-lactate—demonstrate promise as biomarkers for early AII diagnosis. However, variability in specificity and study heterogeneity necessitate further validation before routine clinical application. Integrating lactate biomarkers with other diagnostic modalities may enhance early detection and improve patient outcomes. This review was registered in the Prospective Register of Systematic Reviews (PROSPERO) under CRD42024583735.
Ischemia; Lactate; Prediction; Diagnosis; Emergency Medicine.
Dunya Alfaraj, Walaa Sadeq Alkhamis, Mohammed Ehsan Sheikh, Rakan S. Shaheen, Zahra Bassam Alamer, Abdulaziz Saud Altala, Abdulrahman Zuhair Fita, Zainab Abdulaziz AlKhamis, Zainab Mohammed AlObaidan, Hashim Alwarsh, Zainb Mohammed Alfarej
Ayurveda and Therapeutic Yoga in The Integrative Management of Amavata (Rheumatoid Arthritis): A Narrative Review
This review evaluates the role of therapeutic yoga as an adjunct in managing Amavata, the Ayurvedic correlate of rheumatoid arthritis (RA), characterized by joint pain, swelling, stiffness, and systemic symptoms. Integrating evidence from Ayurvedic principles and modern medicine, the review highlights how yoga comprising gentle asanas, pranayama, meditation, and relaxation addresses both physical and psychosocial dimensions of the disease. In Ayurveda, Amavata management focuses on eliminating Ama (metabolic toxins) and balancing Vata through diet, detoxification, and lifestyle modifications. Modern medicine employs pharmacological interventions to control inflammation and modulate immune activity. Yoga bridges these approaches by improving joint flexibility, enhancing circulation, reducing stiffness, regulating inflammatory cytokines, and modulating neuroendocrine-immune pathways. Specific practices like Tadasana, Bhujangasana, and Anulom Vilom enhance musculoskeletal strength, oxygenation, and stress regulation, while mindfulness techniques improve emotional resilience. Evidence shows yoga reduces inflammatory markers (CRP, IL-6, TNF-α), lowers stress hormones, and supports pain relief. Its integration with Ayurvedic and allopathic treatments optimizes outcomes, minimizes drug dependence, and promotes holistic well-being. Safety guidelines, such as using props and avoiding overstretching during flare-ups, ensure suitability for diverse patients. Overall, therapeutic yoga emerges as a safe, cost-effective, and empowering strategy that complements conventional care, aligning with global trends toward patient-centred, multidisciplinary management of chronic inflammatory disorders like Amavata.
Therapeutic yoga, Amavata, Rheumatoid arthritis, Ayurveda, Asanas, Pranayama, Immune modulation, Integrative medicine, Holistic care.
Physicochemical Characterization, Development and Evaluation of Curcumin-Loaded Nanoparticles for Antiproliferative, Activity against Pancreatic Cancer (PANC-1 ) Cells
Background: Pancreatic cancer is one of the most aggressive malignancies, associated with poor prognosis and limited therapeutic options. Curcumin, a bioactive polyphenolic compound from Curcuma longa, exhibits strong anticancer properties but is hindered by poor solubility and low bioavailability. Nanoparticle-based delivery systems can potentially overcome these challenges and enhance therapeutic efficacy. Methods: Curcumin-loaded nanoparticles were prepared using the nanoprecipitation method and optimized through a Box–Behnken design. The formulations were characterized for particle size, polydispersity index (PDI), zeta potential, morphology, encapsulation efficiency, and thermal behavior. In vitro drug release was assessed using the dialysis bag method. Antiproliferative activity against PANC-1 cells was evaluated through MTT assay, Annexin V–FITC/PI apoptosis assay, and cell cycle analysis. Stability studies were conducted on lyophilized nanoparticles under refrigerated storage for three months. Results: The optimized formulation displayed a mean particle size of 142.3 ± 5.6 nm, PDI of 0.212 ± 0.02, zeta potential of –24.7 ± 2.1 mV, and encapsulation efficiency of 89.2 ± 3.5%. Drug release was sustained up to 72 h with 86.2% cumulative release. Compared with free curcumin, nanoparticles demonstrated a 3.5-fold lower IC₅₀, significantly enhanced apoptosis, and G2/M phase arrest. Conclusion: Curcumin-loaded nanoparticles improved solubility, stability, and antiproliferative activity against PANC-1 cells, highlighting their potential as an effective therapeutic strategy for pancreatic cancer.
Curcumin, nanoparticles, pancreatic cancer, PANC-1, apoptosis, cell cycle arrest.
M. Sivakumar*, Preeti Mangala, Palash Chandra Biswas, Mohit Kumar, Abdul Kadir Jilani, Sunil Sugnomal Menghani, Jyothi Basini, R. Gopinath
Comprehensive Analysis of Clinicopathological Characteristics in Oral Squamous Cell Carcinoma Arising from Oral Submucous Fibrosis: A Retrospective Study
Oral squamous cell carcinoma (OSCC) remains one of the most prevalent malignancies in the oral cavity, particularly in regions with high consumption of areca nut and tobacco products. A significant proportion of these carcinomas develops against the background of oral submucous fibrosis (OSMF), a chronic, insidious, and potentially malignant disorder characterized by progressive fibrosis of the oral mucosa. The present retrospective study, titled “Comprehensive Analysis of Clinicopathological Characteristics in Oral Squamous Cell Carcinoma Arising from Oral Submucous Fibrosis: A Retrospective Study,” aims to delineate the clinical and pathological features of OSCC cases emerging from OSMF and to evaluate their prognostic implications. By systematically reviewing patient data collected over a defined period, the study investigates demographic variables, clinical presentations, histopathological grades, anatomical site involvement, and the correlation between fibrotic severity and malignant transformation. The analysis reveals that OSCC arising in OSMF patients tends to occur at a younger age compared to conventional OSCC, with a marked male predominance and a strong association with areca nut chewing habits. Clinically, trismus and mucosal blanching are frequently observed, complicating early diagnosis and surgical accessibility. Histopathologically, these cases often present as well-to moderately-differentiated squamous cell carcinomas, though the degree of fibrosis within the submucosa can mask early malignant changes, leading to diagnostic challenges. The study also highlights a distinct biological behavior of OSCC arising from OSMF. These tumors often demonstrate less local invasion but exhibit higher rates of nodal metastasis, suggesting an altered tumor microenvironment influenced by chronic fibrosis and tissue hypoxia. The retrospective evaluation further underscores the importance of early detection and routine surveillance in patients diagnosed with OSMF, as the malignant transformation rate remains significantly high. The findings advocate for a multidisciplinary approach integrating clinical assessment, histopathological grading, and molecular evaluation to enhance diagnostic accuracy and improve therapeutic outcomes. Preventive public health measures focusing on cessation of areca nut and tobacco use, along with community awareness programs, are essential to reduce the burden of OSMF-related oral malignancies. In conclusion, this comprehensive study contributes valuable insight into the clinicopathological spectrum of OSCC arising from OSMF, emphasizing the need for vigilant screening, timely intervention, and personalized management strategies to mitigate the morbidity and mortality associated with this high-risk condition.
Oral Squamous Cell Carcinoma, Oral Submucous Fibrosis, Clinicopathological Analysis, Areca Nut, Retrospective Study.
PET/CT in Mediastinal Lymphadenopathy; Merits and Pitfalls
Background: Enlarged mediastinal lymph nodes require assessment to ascertain their benign or malignant origin. Noninvasive techniques are crucial for diagnosing benign as well as malignant mediastinal lymph nodes. PET/CT, which combines morphological plus functional imaging, is a noninvasive technique utilized for evaluating mediastinal lymphadenopathy. In PET, the standard uptake value (SUV), as a semi-quantitative measure, indicates the level of metabolic activity in certain tissues. While FDG absorption levels are typically elevated in neoplastic conditions, they may also be attributed to physiological factors or artifacts. Furthermore, FDG uptake may manifest in benign diseases, including viral, inflammatory, as well as iatrogenic lesions. Results: This cross-sectional study included 120 cases; 67 male (56 %) and 53 female (44 %). 63 cases (52.5%) presented with mediastinal lymphadenopathy on CT and 57 patients (47.5%) came for metastatic work up. They were between the ages of 23 and 85, with 62 being the mean age. Three patients showed high FDG uptake suggesting malignant diagnosis, however, was to be benign. Thirty-four patients showed low FDG uptake, suggesting benign lesions yet with malignant final diagnosis, while thirty patients showed borderline FDG uptake so being indeterminate diagnosis. One patient showed metabolic activity of undetermined nature and proved finally as benign nature. All of these findings were considered as pitfalls for using PET/CT examination in assessment of the malignant, benign and metabolically active lesions. Conclusions: PET/CT examination merits; detection of primary lesions and metastasis, assessment of treatment response and being useful as non-invasive investigation for follow up. On the other hand, number of patients showed high FDG uptake suggesting malignant diagnosis, however, was to be benign, and others showed low FDG uptake, suggesting benign lesions yet with malignant final diagnosis, others showed borderline FDG uptake so being indeterminate diagnosis. Ultimately, implementing both PET FDG uptake and CT characteristics, such as size and attenuation, in a comprehensive integrated report, alongside high-quality clinical and laboratory data in a multidisciplinary meeting context, enhances the likelihood of achieving an accurate diagnosis for the patient.
Lymphadenopathy, PET/CT, malignant, benign.
Youssriah Yahia Sabri, Mostafa Ahmed Khairy, Sherif Talaat Hamed Saad, Yasmine Hamdy El-Hinnawy, Mohammed Raafat Mohammed
Awareness and Recommendations of Physiotherapists in Jeddah about Using Telemedicine in Rehabilitation
Background: Telemedicine is an emerging field with significant potential to enhance rehabilitation services. However, its successful implementation is critically dependent on the awareness and attitudes of clinicians. This study aimed to assess the level of awareness and gather professional recommendations regarding the use of telemedicine in rehabilitation among physiotherapists in Jeddah, Saudi Arabia. Methods: A descriptive, cross-sectional survey was conducted among 100 physiotherapists and physical therapy trainees in Jeddah. A custom-designed questionnaire was used to collect data on demographic and professional characteristics, prior awareness and experience with telemedicine, and professional recommendations for its use. A composite "Awareness and Recommendations Score" was created and classified as "Satisfactory" or "Unsatisfactory." Chi-square tests were used to examine the association between this score and participant characteristics. Results: The findings revealed a profound lack of practical experience, with most participants having never used telemedicine for treating patients (81.0%) or in a professional/training context (67.0%). Despite this, attitudes were positive, with 70.0% recommending its use to colleagues and 76.0% agreeing it could at least partially replace conventional therapy. Overall, 97.0% of participants were classified as having an "Unsatisfactory" level of awareness and recommendations. There were no statistically significant associations between awareness score and any measured demographic or professional variables, including age, gender, educational level, or years of experience (p > 0.05 for all). Conclusion: A significant gap exists between the positive professional disposition towards telemedicine and the current low levels of awareness and practical experience among physiotherapists in Jeddah. This knowledge deficit appears to be a systemic issue rather than one confined to specific subgroups. These findings highlight an urgent need for structured educational initiatives and supportive institutional policies to bridge this gap and facilitate the effective integration of tele-rehabilitation into clinical practice in Saudi Arabia.
Telemedicine, Tele-rehabilitation, Physical Therapy, Awareness, Attitude, Cross-Sectional Study.
Digital Twin Technology in Cardiovascular Care: Transforming Patient Monitoring and Surgical Planning Through Artificial Intelligence
Digital twin technology—the bidirectional coupling of high-fidelity computational models with continuously assimilated patient data—has emerged as a pragmatic pathway toward precision cardiovascular care. By integrating physics-based heart and vascular models with multimodal data streams (ECG/PPG, wearable telemetry, imaging, labs, and EHR), digital twins enable individualized state estimation, prospective risk stratification, and closed-loop decision support. In patient monitoring, twin-in-the-loop filters can detect latent decompensation and therapy drift while quantifying uncertainty. In procedural planning, AI-augmented electromechanical and hemodynamic simulators support target selection and lesion-set optimization for electrophysiology and endovascular interventions, with growing evidence of concordance between simulated and invasive substrates. Methodologically, recent work couples Bayesian/PDE-constrained inference and surrogate neural operators for real-time personalization, and leverages cohort-level twin populations for virtual trials and outcome prediction. Yet translation at scale still hinges on verifiable model validity, data governance, computational tractability at the bedside, and prospective demonstration of clinical and health-economic utility. This paper synthesizes current advances across sensing, modeling, and machine learning that operationalize cardiovascular digital twins for continuous monitoring and surgical planning, outlines validation and regulatory considerations, and proposes a research agenda emphasizing hybrid mechanistic–statistical modeling, prospective multi-site studies, and interoperable, privacy-preserving deployment.
Digital twin; Cardiovascular; Artificial intelligence; Patient monitoring; Surgical planning; Personalization.
Haroon Rasheed, Tasnim Salih Mahdi, Mohd Meraj, Afroj Alam, Nazir Ahmad Ahengar, Dr. Anurag Shrivastava
Climate Change and Human Health: Interdisciplinary Challenges in Medicine, Policy, and Environment
Climate change has emerged as one of the most pressing global health challenges of the twenty-first century, creating profound and interconnected impacts on human well-being, healthcare systems, and social structures. Rising temperatures, erratic weather patterns, and increasing frequency of natural disasters are intensifying health risks, from heat-related illnesses and vector-borne diseases to malnutrition and respiratory disorders. The relationship between climate change and human health is not linear; it operates through complex environmental, social, and economic pathways that require multidisciplinary attention. In many regions, particularly low- and middle-income countries, the degradation of ecosystems, water scarcity, and declining agricultural productivity are contributing to widespread health vulnerabilities and inequalities. These consequences are further compounded by inadequate healthcare infrastructure, limited adaptive capacity, and weak policy implementation mechanisms. From a medical perspective, climate change has altered disease epidemiology, leading to the resurgence of infectious diseases such as malaria, dengue, and cholera in areas where they were previously controlled. It has also exacerbated non-communicable diseases through increased exposure to air pollution, heat stress, and psychological trauma associated with displacement and loss. The environmental dimension underscores the role of deforestation, urbanization, and industrialization in accelerating greenhouse gas emissions, thereby deteriorating air and water quality. Such ecological disruptions not only intensify health hazards but also undermine the natural systems that sustain human life. Policy responses, though improving, remain fragmented and reactive rather than preventive. Integrating health considerations into climate policies demands collaboration between environmental scientists, medical practitioners, economists, and policymakers. Effective strategies must focus on mitigation, adaptation, and resilience-building, emphasizing early warning systems, sustainable resource management, and equitable healthcare delivery. Additionally, interdisciplinary research and data-driven policymaking can bridge existing gaps between scientific evidence and practical implementation. Ultimately, addressing the health implications of climate change requires a holistic approach that recognizes the interconnectedness of human, animal, and environmental health, an approach aligned with the “One Health” framework. This paradigm encourages cross-sectoral partnerships and community participation to reduce health disparities and strengthen climate resilience. As the world confronts the dual crises of environmental degradation and public health instability, the integration of medical, environmental, and policy disciplines stands as a pivotal pathway toward safeguarding future generations and promoting global sustainability.
Climate Change, Human Health, Environmental Policy, Disease Vulnerability, Sustainable Development.
Dr. Sakchhi Tiwari, Dr. Shaini G. S, Dr. G. Punithakumari, Dr Archana Chaudhary, Dr.Yazhini Kuppusamy, Mohammed Sheeba kauser
Oral Microbiota and Oral Squamous Cell Carcinoma: a Review of Their Relation and Carcinogenic Mechanisms
Oral Squamous Cell Carcinoma (OSCC) is among the most prevalent malignancies of the oral cavity, representing a significant global health burden due to its high morbidity and mortality rates. Recent research has revealed that beyond conventional etiological factors such as tobacco, alcohol consumption, and human papillomavirus infection, alterations in the oral microbiota play a pivotal role in oral carcinogenesis. The oral cavity hosts a complex and dynamic microbial ecosystem, comprising bacteria, fungi, and viruses that coexist in a delicate balance with the host. Disruption of this equilibrium, known as dysbiosis, has been increasingly associated with inflammatory and neoplastic processes within the oral mucosa. Emerging evidence suggests that specific bacterial species, including Fusobacterium nucleatum, Porphyromonas gingivalis, and Prevotella intermedia, may contribute to the initiation and progression of OSCC through mechanisms involving chronic inflammation, immune modulation, and the production of carcinogenic metabolites. These pathogens promote a pro-tumorigenic microenvironment by inducing cytokine release, activating oncogenic signaling pathways such as NF-κB and STAT3, and interfering with cell cycle regulation and apoptosis. Furthermore, microbial metabolites such as acetaldehyde, lipopolysaccharides, and reactive oxygen species contribute to DNA damage, genomic instability, and epigenetic modifications that accelerate malignant transformation. The interplay between host immunity and microbial activity further exacerbates these effects, fostering conditions conducive to cancer development. Advances in metagenomic sequencing and bioinformatics have enhanced our understanding of microbial diversity and its correlation with tumor biology, offering new diagnostic and prognostic biomarkers for early OSCC detection. This review comprehensively explores the intricate association between oral microbiota and OSCC, emphasizing microbial-driven carcinogenic mechanisms, host-microbe interactions, and potential therapeutic strategies targeting oral dysbiosis. By elucidating these complex relationships, this study underscores the importance of integrating microbiome analysis into oral cancer research and clinical management. Understanding the microbial contribution to oral oncogenesis may pave the way for innovative preventive and therapeutic interventions, including microbiota modulation, antimicrobial therapy, and probiotic-based approaches aimed at restoring microbial homeostasis and reducing OSCC risk.
Oral Microbiota, Oral Squamous Cell Carcinoma, Carcinogenesis, Dysbiosis, Microbial Pathogenesis.
Computational Discovery of Potential Acyl-CoA: Cholesterol Acyltransferase Inhibitors Using Structure-Based Virtual Screening
Hyperlipidemia is a major metabolic disorder characterized by elevated levels of plasma lipids, including cholesterol and triglycerides, which contribute significantly to the development of atherosclerosis and subsequent cardiovascular complications such as angina pectoris, myocardial infarction, and cardiac arrest. Acyl-CoA:cholesterol acyltransferase (ACAT) is a key enzyme involved in intracellular cholesterol esterification, and its inhibition represents a promising therapeutic strategy for the management of hyperlipidemia. In the present study, molecular modeling approaches were employed to identify novel ACAT inhibitors with potential antihyperlipidemic activity. Pharmacophore models were developed based on structurally diverse, known ACAT inhibitors to elucidate essential molecular features governing enzyme inhibition. Following an extensive literature survey, a focused virtual library of heterocyclic compounds was designed to explore alternative lipid-lowering targets and to determine whether the observed hypolipidemic effects could be attributed to ACAT inhibition. Heterocyclic scaffolds, comprising ring systems containing atoms of at least two distinct elements, are known to play a pivotal role in drug discovery due to their versatile biological activities. Representative heterocycles such as quinoline, benzothiophene, indole, benzofuran, benzothiazole, benzimidazole, and benzoxazole were considered as structural templates for pharmacophore development. Among these, benzoxazole and benzothiazole moieties were selected as key pharmacophoric cores for the design of novel derivatives. These compounds were subjected to in silico screening using molecular docking and related computational techniques to assess their interaction with the ACAT active site.Several designed derivatives demonstrated favorable docking scores and strong binding affinities toward the ACAT receptor, indicating potential inhibitory activity. These promising heterocyclic compounds will be further evaluated through advanced computational studies and experimental assays to identify lead candidates for the development of novel antihyperlipidemic agents targeting ACAT.
Hyperlipidemia, Obesity, Open Babel, Docking studies, Binding affinity.
Paediatric Mental Health Disorder Post-Pandemic: Anxiety, Depression and the Role of Nurses in Early Identification and Counselling
The COVID-19 pandemic has profoundly impacted the mental health of children and adolescents, leading to a significant rise in anxiety and depression worldwide. Prolonged school closures, social isolation, and family stressors have disrupted emotional stability and psychosocial development among the paediatric population. This narrative review explores the prevalence of anxiety and depression in children during the post-pandemic period and highlights the essential role of nurses in early identification, counselling, and preventive interventions. Findings from global and Indian studies (2020–2025) reveal that 25–27% of children experience depression and 20–25% suffer from anxiety, with higher rates reported in urban regions such as Chennai. Contributing risk factors include social isolation, excessive digital exposure, family conflict, and reduced physical activity. Nurses play a crucial role in recognizing early signs through tools such as the Child Depression Inventory (CDI) and Spence Children’s Anxiety Scale (SCAS), while providing psychoeducation, emotional support, and school-based counselling. Strengthening nursing involvement in community and educational settings can facilitate early intervention, reduce psychological distress, and promote mental resilience among children and adolescents in the post-pandemic era.
Paediatric mental health, anxiety, depression, post-pandemic, early identification, counselling, nursing interventions.
Prabhu S, Kayalvizhi R, Ambiga C, Gnanasowndharya, Gayathri P, Dr. Prema Krishnan
Non-Invasive bio- sensors for continuous and glucose and vital monitoring: The future of chronic disease management
The global rise in chronic diseases, particularly diabetes, demands innovative, patient-friendly monitoring systems to improve disease management and outcomes. Non-invasive biosensors, especially wearable technologies, offer a promising alternative to traditional blood-based glucose monitoring by enabling continuous, real-time tracking of physiological markers without the discomfort or risks associated with invasive methods. This manuscript explores the current advancements in non-invasive glucose monitoring (NGM) technologies, with a focus on electrochemical, optical, electromagnetic, and sonochemical sensors. Emphasis is placed on transdermal devices that use body fluids like sweat and tears, as well as techniques such as Raman spectroscopy and infrared sensing. The review addresses the shift from semi-invasive Continuous Glucose Monitoring (CGM) systems (e.g., Dexcom, FreeStyle Libre) to truly non-invasive alternatives under development, such as the MUS-IR and fluorescent-based sensors. Integration with digital health ecosystems through AI and machine learning is highlighted as a key factor in enhancing data analysis, providing personalized feedback, and enabling remote care. However, challenges remain, including sensor sensitivity, environmental interference, data overload, regulatory hurdles, and clinical adoption barriers. Despite these limitations, ongoing research and development in NGM technologies suggest significant potential for transforming diabetes management through painless, accurate, and user-friendly monitoring solutions.
Non-invasive glucose monitoring, Continuous glucose monitoring (CGM), Wearable biosensors, Electrochemical sensors, Digital health, Diabetes management, Artificial intelligence, Sensor accuracy, Sweat-based sensors, Raman spectroscopy, Data overload, Regulatory challenges.
Elavarasi E, Sophiya Rajakumari, Subulakshmi, Rajaselvi G, Prema K, Suriyakala S
AI-Based Peptic Ulcer Detection Using Deep Convolutional Neural Networks: A Diagnostic Accuracy Study
Peptic ulcer disease remains a major gastrointestinal disorder that often goes undiagnosed due to subtle visual cues and variability in endoscopic interpretation. To address these diagnostic challenges, this study proposes an AI-based diagnostic framework utilizing Deep Convolutional Neural Networks (DCNNs) for the automated detection and classification of peptic ulcers from endoscopic images. This study presents an AI-based diagnostic framework employing pretrained Deep Convolutional Neural Networks (DCNNs) — VGG16, ResNet50, InceptionV3, and the Hugging Face Vision Transformer (ViT) — for automated classification of ulcerous and non-ulcerous endoscopic images. The proposed model integrates transfer learning and Grad-CAM visualization, enhancing both diagnostic accuracy and interpretability. Comparative analysis reveals that the Hugging Face Vision Transformer (ViT) architecture achieved the highest classification accuracy of 96.8%, outperforming traditional CNN models. The developed system offers a clinically interpretable, scalable, and user-friendly diagnostic tool that assists in the early identification of gastric and duodenal ulcers, thereby reducing the dependence on manual endoscopic evaluation. Experimental results demonstrate that the DCNN models can effectively identify early-stage ulcers with reduced false negatives, highlighting its potential as a reliable clinical decision-support tool.
Peptic Ulcer Detection, Deep Convolutional Neural Network (DCNN), Endoscopic Image Analysis, Artificial Intelligence, Medical Image Classification, Computer-Aided Diagnosis, Gastrointestinal Disorder, Peptic ulcer disease (PUD), wireless capsule endoscopy (WCE), nonsteroidal anti-inflammatory drugs (NSAIDs).
Dr. S Pratap Singh, Dr. Madhusekhar Yadla, Dr. Vadhya Redya, Dr. A Nageswararao
Enhancing Burn Pain Management: The Therapeutic Potential of Cocoa Extract as a Tramadol Adjuvant in Modulating MCP-1 and Glutamate in Animal Model
Burn wound pain management remains a significant clinical challenge, with up to 80% of patients experiencing severe pain. This pain results from complex interactions between nociceptive stimuli and inflammatory cascades that can progress to chronic pain states. While multimodal analgesia combining NSAIDs and opioids is standard practice, novel adjuvants are needed to optimize pain control. Cocoa contains bioactive flavonoids with documented anti-inflammatory, antioxidant, and analgesic properties, including inhibition of key inflammatory mediators (IL-1β, TNF-α, MCP-1). This study investigated cocoa extract as a potential adjuvant to tramadol for burn pain management. In this randomized controlled experimental study, 15 male Wistar rats were equally divided into three groups: control (placebo), tramadol-ibuprofen combination (12.5 mg/kg and 15 mg/kg, respectively), and tramadol-cocoa combination (12.5 mg/kg and 0.5 g/kg, respectively). Second-degree burns were induced by immersing the right hind paw in 65°C water for 3 seconds. Pain sensitivity was assessed using Von Frey filaments at 24 hours post-injury. Plasma MCP-1 and tissue glutamate levels were quantified using ELISA. Von Frey testing revealed significant analgesic effects in both treatment groups compared to control (p=0.003), with the tramadol-cocoa combination (p=0.005) demonstrating comparable efficacy to tramadol-ibuprofen (p=0.010). No significant difference was observed between treatment groups (p=0.930). While MCP-1 levels showed no significant variation across groups (p=0.063), tissue glutamate concentrations were significantly reduced in both tramadol-ibuprofen (p=0.017) and tramadol-cocoa groups (p=0.046) compared to control, with no significant difference between treatments (p=0.069). Cocoa extract demonstrates promising potential as an analgesic adjuvant, achieving pain reduction comparable to standard tramadol-ibuprofen therapy. The significant reduction in tissue glutamate levels suggests a potential mechanism through modulation of excitatory neurotransmission. These findings support further investigation of cocoa-based adjuvants as a novel, natural approach to multimodal burn pain management.
Cocoa Extract, Tramadol, Burn Pain, Glutamate
Wahyu Prasetyo Andriyanto, Herdiani Sulistyo Putri, Prananda Surya Airlangga, Kohar Hari Santoso, Christrijogo Sumartono W., Mahmudah
Lactate-Pyruvate Ratio and Mortality Association in Traumatic Brain Injury
Traumatic brain injury (TBI) remains a leading cause of morbidity and mortality worldwide, particularly among young and productive populations. Prognostication remains a challenge, as traditional clinical tools such as the Glasgow Coma Scale (GCS) and vital signs often fail to capture underlying cellular metabolic derangements. The lactate-pyruvate ratio (LPR) reflects cellular redox balance and mitochondrial function and may serve as a novel prognostic marker. This prospective, observational, analytical study included 40 TBI patients admitted to Dr. Soetomo General Hospital, Surabaya, Indonesia, from May to July 2025. Demographic characteristics, vital signs, GCS scores, and blood levels of lactate and pyruvate were measured on admission. Patients were followed for seven days, and mortality outcomes were recorded. Logistic regression was used to evaluate the association between LPR and mortality. The majority of patients were male (72.5%) with a median age of 45 years. The mortality rate was 20% (8/48). Non-survivors had significantly higher heart rates, lower oxygen saturation, lower GCS scores, and markedly elevated lactate levels (median 3.99 mmol/L vs. 0.31 mmol/L in survivors, p<0.001). Pyruvate levels did not differ significantly. Higher lactate-to-pyruvate ratio (LPR) values were significantly associated with increased mortality, with most survivors clustering in the <20 group and non-survivors predominantly in higher categories (p < 0.001). Thus, LPR strongly correlates with in-hospital mortality and may serve as a valuable biochemical marker for early risk stratification in TBI patients. Routine measurement of LPR in emergency and critical care settings could improve prognostic accuracy and guide timely interventions. Larger multicenter studies are warranted to validate these findings.
Traumatic Brain Injury, Lactate-Pyruvate Ratio, Mortality, Prognosis, Biomarker
Nora Ismi Afriani, Prananda Surya Airlangga, Prihatma Kriswidyatomo, Bambang Pujo Semedi, Kohar Hari Santoso, Mahmudah
Association of Age Body Shape Index (ABSI) and Body Roundness Index (BRI) with Triglyceride-Glucose-Waist Circumference (TyG-WC) Index as a Cardiometabolic Risk Predictor Among Normal and Overweight Police Officers with normal LDL Level in East Java, Indo
Cardiometabolic disorders, including insulin resistance (IR) and visceral adiposity, are common in individuals with normal-low low-density lipoprotein (LDL) levels and non-obese body mass index (BMI). Police officers face higher risks due to occupational stress factors, but conventional screening often overlooks their metabolic risks. The Body Shape Index (ABSI) and Body Roundness Index (BRI) are innovative anthropometric measurements that could potentially offer more accurate predictions for insulin resistance (IR) when examining the combination of triglyceride-glucose index along with waist circumference (TyG-WC). To determine the association of ABSI and BRI with TyG-WC as a surrogate of cardiometabolic risk among Indonesian police officers with normal LDL and BMI. This cross-sectional study enrolled 524 active-duty officers. ABSI and BRI were derived from anthropometric measurements; TyG-WC was calculated from fasting triglycerides, glucose, and waist circumference. Spearman's correlation analysis was conducted, with a level of statistical significance established at p < 0.05. Noteworthy associations were found between ABSI and TyG-WC (r = 0.622, p < 0.001) as well as between BRI and TyG-WC (r = 0.805, p < 0.001). These findings suggest that higher central adiposity and body roundness are associated with elevated surrogate markers of insulin resistance, even in individuals without obesity or dyslipidemia. ABSI and BRI, particularly BRI, robustly associate with TyG-WC in normolipidemic police officers, suggesting their utility for early cardiometabolic risk stratification in high-stress occupations. Routine screening with these indices could enable targeted interventions before overt metabolic disease develops.
A Body Shape Index, Body Roundness Index, TyG-WC, Insulin Resistance, Central Obesity, Police Officers
Meity Ardiana, Raditya Rizki Muhammad, Nadya Noor Mulya Putri, Ricky Roosdiana Dewi, Elisabeth Sekaringtyas Medistya Putri, Anthony Martin, Faizah Sugiarto
The Role of Synthetic Biology in Vaccine Development
By enabling the planning, construction, and modification of biological systems with a degree of precision never seen before, synthetic biology an exciting interdisciplinary field has had a major impact on the development of vaccines. Inspired by engineering, biology, computer science, and other fields, this approach combines concepts to create new synthetic life forms or systems that may be trained to do certain tasks. Synthetic biology uses altered bacteria, cells, and genetic elements to provide more successful, safer, and reasonably priced vaccinations. Synthetic biology is used most importantly in the development of vaccines in the synthesis of novel proteins and enhancement of their expression. Knowing and altering the genetic coding lets scientists create antibodies resembling disease-causing germs without running the danger of infection. Vaccines using these antigens help the immune system function better without introducing live viruses into the body. Additionally made feasible by synthetic biology are RNA and DNA vaccines with autonomous multiplication capability. Using less of the active component, these vaccinations stay longer and perform better. Furthermore, synthetic biology has made it simpler to create vaccines utilizing non-traditional systems instead of the conventional egg-based approaches like plants, yeast, and bacteria. This fresh concept enables rapid vaccination during pandemics or new disease outbreaks by considerably improving scalability and reducing manufacturing costs. Vaccines should also be more specialized and effective by means of systems aiming at certain immune pathways and lowering of adverse effects. Making vaccines via synthetic biology also advances adjuvant design, improves vaccine delivery technologies, and generates tailored vaccinations grounded on individual genes. This field has also shown fast adaptation to newly emerging infectious illnesses. For instance, synthetic biology-based methods enabled extremely rapid synthesis of COVID-19 vaccines. These developments demonstrate how synthetic biology may entirely alter our approach to combat fatal illnesses. Synthetic biology raises significant societal, legal, and safety concerns even if it is making enormous advancement in the manufacture of vaccines. It is rather crucial to ensure that these fresh innovations are used in a method that preserves public health and lowers hazards as much as feasible as the area advances. Finally, synthetic biology is about to change the way vaccines are made, giving us new tools and ways to deal with present and future health problems around the world.
Synthetic biology, Vaccine development, Antigens, RNA vaccines, Vaccine production.
Gene Therapy for Rare Genetic Disorders: Recent Breakthroughs
Gene therapy has become an exciting new way to treat rare genetic diseases, with the possibility of long-lasting or even curing solutions. Recent improvements in gene therapy have made it much safer and more effective, making it a possible way to treat genetic diseases that couldn't be cured before. Researchers have made a lot of progress in the last few years in learning how genetic diseases work at the molecular level and how gene-based treatments can be used to treat them. Better and more accurate treatments have been made because of this, especially for rare genetic diseases like spinal muscular atrophy (SMA), cystic fibrosis (CF), haemophilia, and some inherited eye diseases. The FDA's approval of the first gene treatment for spinal muscular atrophy, a serious neurological disease that affects babies, is one of the most important steps forward in gene therapy. This treatment has been shown to stop the disease from getting worse and make movement skills much better, showing how gene therapy can change things. Also, improvements in viral vector technology, like adeno-associated viruses (AAV), have made it easier to get restorative genes to the cells that need them. Now, these vectors are being tweaked to make them more specific, lower defensive reactions, and make transport more effective overall. The creation of CRISPR-Cas9 gene-editing technology has also changed the field by making it possible to fix genetic changes at the DNA level. It looks like CRISPR could help treat a number of rare genetic diseases, such as sickle cell anaemia and β-thalassemia. These cutting-edge technologies have made gene therapy easier to get and more successful. They have also made it possible to precisely change genes. Even with these improvements, gene therapy for rare genetic diseases still has some problems. Some of these are worries about the long-term effects of changing genes, the high cost of treatments, and the lack of good delivery methods. Even so, these problems are still being worked on in continuing research and clinical studies, which brings gene therapy closer to becoming a common way to treat odd genetic diseases. Gene therapy has a bright future ahead of it. It could change the field of genetic medicine and give people with diseases that couldn't be treated before hope.
Gene therapy, Rare genetic disorders, CRISPR-Cas9, Spinal muscular atrophy, Genetic medicine
Improving Maternal And Neonatal Safety: The Role Of Nursing In Infection Control In Obg Departments
Maternal and neonatal infections remain a major global health challenge, significantly contributing to morbidity and mortality rates, particularly in low- and middle-income countries. The World Health Organization (WHO) reports that infection-related complications account for nearly 10% of maternal deaths and a substantial proportion of neonatal fatalities worldwide. Effective infection prevention and control (IPC) measures within obstetrics and gynaecology (OBG) departments are essential to ensuring safe childbirth, reducing puerperal and postoperative infections, and preventing neonatal sepsis. Nurses, as the cornerstone of maternity care, play a crucial role in implementing, monitoring, and sustaining these infection control practices. This review explores the pivotal role of nursing in improving maternal and neonatal safety through evidence-based IPC interventions, guided by international standards such as WHO and Centres for Disease Control and Prevention (CDC) protocols. The study synthesizes findings from recent global literature focusing on nursing-led IPC practices, including aseptic techniques during labour and delivery, sterilization of instruments, environmental cleaning, antimicrobial stewardship, and adherence to hand hygiene guidelines. Nurse-led infection surveillance, health education, and early detection of infection risks have been identified as essential components of effective IPC programs in maternity units. Despite strong evidence supporting the effectiveness of IPC measures, barriers such as inadequate staffing, limited resources, inconsistent training, and weak institutional policies continue to hinder optimal implementation. The findings emphasize the need for regular competency- based training, policy reinforcement, and leadership support to empower nurses as infection control champions. Furthermore, fostering inter professional collaboration and patient education enhances compliance and overall safety within OBG settings. Infection prevention is a shared responsibility, but nurses occupy a central and influential position in safeguarding maternal and neonatal health. Empowering the nursing workforce through continuous education, strong leadership, and adequate resources can significantly reduce preventable infections and improve health outcomes. Strengthened nursing participation in infection control represents a vital step toward achieving global targets for safe motherhood and neonatal care.
Maternal Safety, Neonatal Infection, Nursing Interventions, Infection Control, Obstetrics and Gynaecology, Patient Safety.
Investigating Developmental Toxicity of Phenylalanine and Phenylpyruvate: Insights from the Danio rerio Embryo Model
Phenylalanine (PA) as Essential amino acids required from the outer side the body for normal physiological function and development. Different scientific published literature is indicating the pathophysiological role of PA, specifically in PKU and responsible for Neurotoxicity, Birth Defects, Developmental Delays, Microcephaly, Seizures, Musty odor and Eczema. The metabolic pathway of PA also creates concern about the responsibility towards its metabolites Phenylpyruvate (PP). Therefore this current study will investigate the role of PA & PP about its developmental effect (Eye Diameter, Head Length, Head Width, Yolk Sac Area, Pericardial Area, Caudal Fin Length, Total Body Length, Heartbeat Rate, Axial Angle, and Circulation) on Zebra fish Embryo. The entire study has been done on Danio rerio embryo considering PA concentration 0.3 µg/ml, 0.5 µg/ml, 1 µg/ml and PP concentration 0.3 µg/ml, 0.5 µg/ml, 0.7 µg/ml. Finally it has been observed PA does not have major effect in the selected concentration except Total Body Length but PP has shown significant developmental effect in most of the parameters.
Developmental toxicity, Phenylalanine, Phenylpyruvate, zebrafish, embryo model, Teratogenic effects.
Samrat Bose , Asfakul Islam, Shreya Sarkar & Himangshu Sekhar Maji
Psychological and Pharmacological Strategies to Address Sleep Disturbances in Chronic Illness: A Review
Sleep disturbances are a significant and frequently neglected co-morbidity in chronic diseases that has a substantial effect on the course of the disease and patient well-being. This review describes a synthesis of evidence about the neurobiological and inflammatory processes of sleep disruption in such conditions as diabetes, cancer, cardiovascular disease, and neurodegenerative diseases. Central to this pathology is the disruption of a neurohormone system known as the hypothalamic/pituitary/adrenal (HPA), also called the "stress axis" - disruptions of the autonomic nervous system and neurotransmitters defined as gamma-aminobutyric acid (GABA), serotonin, acetylcholine. Chronic inflammation, mediated by inflammation mediators such as IL-6, TNF-α, and CRP, results in direct changes to neural circuits that control sleep-wake cycles, which then becomes a vicious cycle that worsens systemic disease. The review evaluates the available psychological treatments, especially the cognitive-behavioral treatment for insomnia (CBT-I), as well as pharmacological treatments, and their efficiency and defects. It highlights important areas for further research including lack of large-scale trials in specific disease groups, under-representation of elderly and multimorbid patients, and lack of data on longevity. Future directions focus on the concepts of precision medicine, digital therapeutics using AI, and interdisciplinary care models, as well as concentrating on the long-term quality of life outcomes to make sleep management the mainstay rather than an adjunct in chronic disease treatment.
Sleep Disturbances, Chronic Illness, HPA Axis, Inflammation, CBT-I, Precision Medicine.
Srajan Srivastava, Dr. Avinash D. Karambhe, Dr Ummedishvaramchandra S Raut, Dr Aashish Patel, Dr. Pooja Narain, Dr. Mohammad Zanul Abedeen, Nikhil Sharma
Prevalence Of Viral Infections In Hemodialysis Patients In A Tertiary Care Hospital Of Eastern India
Background: Hemodialysis patients are more vulnerable to infections, which are the leading cause of hospitalization and death after cardiovascular events. The primary aim of the study was to screen for the presence of viral infections in patients undergoing hemodialysis. Materials And Methods: Serum samples were collected from 150 end-stage renal disease patients receiving hemodialysis, as well as a control group of 150 healthy people with no predisposing factors. Enzyme-linked immunosorbent assay (ELISA) was used for screening of viral infections in patients for Cytomegalovirus (CMV), Hepatitis B virus, Hepatitis C virus and Human Immunodeficiency virus. Polymerase chain reaction (PCR) was done for confirmation of CMV which was the predominant viral pathogen isolated. The chi-square test and Statistical Package for the Social Sciences software 2.0 were used in the statistical study, with p-values less than 0.05 considered as statistically significant. Results: Out of 150 patients included in the study, 22% patients belonged to the age group of 61-70 and 41-50 years. Male (64%) preponderance was observed among the patients. Most common viral infection was by CMV. Seropositivity of CMV-IgM and CMV-IgG by ELISA were 5.3% and 58% respectively. PCR detected viral DNA 6.6%. Conclusion: CMV infection was common among HD patients in our region; therefore we recommend screening for anti-CMV IgG and IgM antibodies.
Hemodialysis, Viral infection, ELISA, PCR, CMV
Dr Roshni Dandapat, Dr Dipti Pattnaik, Dr Nirmala Poddar, Dr Kumudini Panigrahi, Dr Smrutilata Sahoo, Dr Preety Mishra, Dr Soumya Nayak, Dr Ankita Roy, Dr Aswini Prasad Patnaik, Dr Basanti Kumari Pathi
Comparative Study of Metoprolol Succinate and Metoprolol Tartrate: Therapeutic Efficacy and Safety through Oral and Nasogastric Tube Administration
Background: Metoprolol, a selective β1-adrenergic receptor blocker, is widely prescribed in cardiovascular conditions including hypertension, heart failure, and arrhythmia. The route and formulation significantly influence therapeutic outcomes. This study aims to compare the efficacy and safety of Metoprolol Succinate (extended-release) and Metoprolol Tartrate (immediate-release) administered via oral and nasogastric (NG) routes in hospitalized patients requiring β-blocker therapy. Methods: A prospective, comparative interventional study was conducted for six months at ESI Hospital, Ayanavaram, Chennai, including 108 patients aged 25–75 years diagnosed with cardiovascular diseases. Participants were categorized into four groups (n=27 each): Oral Succinate, Oral Tartrate, NG Succinate, and NG Tartrate. Baseline parameters such as systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) were recorded. Therapeutic efficacy, safety (adverse drug reactions, ADRs), and biochemical parameters were assessed. Statistical analysis was conducted using SPSS v27.0 with ANOVA and paired t-tests; p<0.05 was considered significant. Results: Oral Metoprolol Succinate exhibited the highest efficacy (77.8%), followed by Oral Tartrate (64.7%), NG Tartrate (55.6%), and NG Succinate (40.7%). Significant reductions in SBP and HR were observed across all groups (p<0.05), with the greatest decline in the Oral Succinate group (SBP 148.6±11.4 to 124.2±9.8 mmHg; HR 92.7±6.2 to 73.3±5.8 bpm). ADRs were mild, with fatigue and dizziness being most common. No severe ADRs or biochemical abnormalities were noted. Conclusion: Oral Metoprolol Succinate demonstrated superior therapeutic efficacy and safety compared to other groups, attributed to its stable plasma concentration and extended-release profile. NG Tartrate remains a suitable alternative when oral administration is not feasible. This study emphasizes the importance of formulation and administration route in optimizing cardiovascular pharmacotherapy.
Metoprolol succinate, Metoprolol tartrate, Oral vs nasogastric, β-blockers, Hypertension, Cardiovascular efficacy.
Keerthiga J, Mirudula S, Manuelita Sharon Christina B, Dr. Karthickeyan Krishnan, Dr. Palani Shanmugasundaram
Synergizing Odontology and DNA Profiling for Enhanced Disaster Victim Identification: Insights from Anthropological Perspectives in India
The disaster-prone areas of India need efficient DVI methods because thousands of people die from floods and earthquakes annually while upholding human dignity according to anthropological principles and allowing families to find closure. The combination of odontology with DNA profiling enables quick and budget-friendly victim identification through dental records and genetic markers. The current identification process faces multiple obstacles because postmortem deterioration occurs, while dental morphological differences between ethnic groups in Indian populations and insufficient forensic resources result in extended identification periods and ethical problems during mass casualty events. The research unites dental and DNA identification techniques to boost disaster victim identification speed while using anthropological knowledge from Indian disaster cases. The research aims to assess the combined method's precision and operational speed across different ethnic populations while developing an identification system that respects cultural diversity. The research used a mixed-methods approach to study 50 postmortem cases from Indian disasters which occurred during the 2018 Kerala floods and 2021 Chamoli glacier burst. I obtained antemortem dental records and X-rays, and DNA samples from teeth and bones for this study. The research combined odontology for preliminary victim sorting through FDI charting and digital scanning with DNA testing that employed STR and mitochondrial PCR for analysis. The researchers used SPSS statistical techniques to analyze their data, including t-tests for time efficiency, chi-square tests for match rates, and Kappa coefficients for evaluating inter-rater reliability. The study showed fewer identification errors in tribal communities, and the integrated identification system reduced the overall identification time from 72 hours to 48 hours while achieving 85% accuracy. The study demonstrates how this methodological approach addresses current protocol issues that are absent from India's National Disaster Management Authority guidelines. The study develops a unique hybrid system for Indian culturally diverse regions, yielding important findings regarding improved repatriation outcomes and suggestions for the creation of a national database and ethical standards for the indigenous population. The research links technological solutions with anthropological knowledge to build disaster response methods that show greater compassion.
DVI, Forensic Odontology, DNA Profiling, Anthropological Perspectives, Indian Disasters.
Satwik Chatterjee, Sidhvita Kaithepalli, Riya Mariya, Madhuri Vagal, Farheen Sheikh, Muskan