Indus journal of bioscience research.

Sustainable aquaculture methods must be advanced to meet the problems presented by environmental stresses and the expanding worldwide need for food. This study examines cutting-edge methods for raising Nile tilapia (Oreochromis niloticus), emphasizing immunomodulatory techniques, microbiome modification, and the crucial task of reducing environmental stresses to increase resilience and production. Probiotics, prebiotics, and synbiotics are important in enhancing nutrition absorption, promoting disease resistance, and optimizing gut health, making microbiome modification an essential strategy. The use of functional feeds enhanced with bioactive chemicals and the creation of tailored vaccinations are two examples of advances in immunomodulatory approaches that have demonstrated promise in bolstering tilapia's immune systems against pathogenic threats. A holistic strategy to guarantee sustainable production is provided by simultaneously reducing environmental stresses, such as hypoxia, variable water temperatures, and pollutant exposure, through enhanced aquaculture systems, water quality control, and stress-resilient fish strains. The importance of addressing these environmental stressors is underscored, as they pose significant threats to the industry. Emerging technologies like genomics, transcriptomics, and precision aquaculture tools, which allow for the monitoring and adjusting of farming operations to suit the unique requirements of Nile tilapia, further facilitate the integration of these tactics. This review highlights the potential of comprehensive, science-driven methods in converting Nile tilapia farming into a resilient, sustainable, and fruitful enterprise and emphasizes the importance of addressing environmental stressors in this transformation.

Nanoparticles have become a transforming platform in drug delivery systems. Their remarkable advancement over traditional methods builds upon an improvement in bioavailability, stability, and controlled delivery of therapeutic agents. Here, we discuss the broad spectrum of potential in nanoparticle-based drug delivery systems. Challenges, innovations, and the surface modification strategies that affect their clinical translation are discussed. Notwithstanding the potential they present, challenges including biocompatibility, toxicity, stability, and targeting efficiency persist in restricting their extensive utilization. The review emphasizes recent advancements, including stimuli-responsive nanoparticles, which provide controlled drug release in reaction to environmental triggers, as well as targeted drug delivery, which facilitates the selective accumulation of therapeutic agents at designated sites of disease. Besides, surface modification techniques, such as PEGylation, ligand conjugation, and charge modulation, have been highly promising in improving the stability of nanoparticles, reducing immunogenicity, and enhancing cellular uptake. The future drug delivery systems that are based on nanoparticles will address these challenges through new innovations in nanoparticle design to effect more targeted and effective treatments. While research advances, nanoparticle-based systems are likely to bring revolution in personalized medicine, tailoring medical therapy for different diseases with minimal side effects and better patient outcomes.

With an emphasis on the identification of biomarkers for pancreatic cancer, this research investigated the use of artificial intelligence (AI) and machine learning (ML) in metabolomics for disease profiling. With the use of the Kaggle dataset "Pancreatic Cancer Urine Biomarkers," which comprises 591 samples from diverse patient cohorts, we examined the connections between distinct proteome and metabolomic markers and their diagnostic value. Plasma CA19-9, LYVE1, REG1B, REG1A, and TFF1 were among the key biomarkers that were assessed in order to create a prediction model that could differentiate between benign cases, healthy controls, and pancreatic ductal adenocarcinoma (PDAC). According to our findings, the XGBoost classifier performed much better than conventional statistical techniques, recognizing positive instances with 89% accuracy and 91% sensitivity. The research also demonstrated the intricate relationships between several biomarkers that affect diagnostic accuracy and emphasized the crucial significance of the REG1B/REG1A ratio as a new predictor. We verified our model's robustness and generalisability across various patient demographics using a thorough validation procedure that included cross-validation and sensitivity analysis. "This work demonstrates how artificial intelligence can revolutionize metabolomics, opening the door to more accurate illness characterization and individualized treatment plans. In order to enhance early identification and outcomes of pancreatic cancer and other associated disorders, our results ultimately support the use of machine learning techniques into clinical practice.

Significant environmental issues have been created by the growing outflow of urban and industrial wastewater, which calls for the development of sophisticated and effective treatment systems. Zero-valent iron (ZVI) and titanium dioxide (TiO₂) nanoparticles have become well-known among developing solutions because of their exceptional reactivity, affordability, and potential for large-scale applications. With an emphasis on their processes, efficacy, and difficulties, this paper examines the most recent developments in the application of ZVI and TiO₂ nanoparticles for wastewater treatment. TiO₂ nanoparticles have remarkable photocatalytic qualities, efficiently breaking down persistent organic pollutants under UV and visible light, whereas ZVI nanoparticles have high reductive capabilities, allowing the removal of heavy metals, chlorinated compounds, and organic pollutants. Their efficiency, stability, and reusability have been improved by recent alterations such as doping, surface functionalization, and hybrid nanocomposites. However, obstacles to wider use include recovery issues, possible ecotoxicity, and nanoparticle aggregation. To increase the sustainability and viability of ZVI and TiO₂ applications, this study also covers cutting-edge techniques, including magnetic separation, green synthesis, and integration with other treatment methods. Future studies should concentrate on creating scalable treatment plans, assessing long-term environmental effects, and improving nanoparticle design. ZVI and TiO₂ nanoparticles have enormous potential to transform wastewater treatment and support global water sustainability by solving these issues.

The increasing rate of cardiovascular diseases (CVDs) has posed a tremendous challenge to their early detection and personalized treatment. This research examines the potential of Artificial Intelligence (AI) for early detection and management of CVDs, in particular whether it can enhance diagnostic accuracy, personalize treatment guidelines, and reduce healthcare costs. A quantitative methodology was adopted and a survey strategy was employed for collecting primary data from 300 healthcare professionals consisting of cardiologists, general physicians, and professionals in AI fields from Punjab hospitals in Pakistan. The questionnaire was constructed to determine their knowledge, experiences, and perceptions regarding the use of AI in cardiovascular services. Data analysis revealed that application of AI had a strong correlation with increased diagnostic success, evident in a statistically significant chi-square test (p < 0.001). Furthermore, multiple regression analysis revealed that AI, together with years of experience and educational history, is an important contributor to personalizing cardiovascular treatment plans. The results indicate that AI has a key role in making more precise diagnoses and improving treatment methods, which can ultimately decrease the cost of healthcare and enhance patient outcomes. Yet, issues around data privacy, transparency, and clinician confidence in AI systems must be resolved in order for AI to be adopted more widely. Future research is suggested by the study into the integration of AI with other health technologies and the ethics of using AI in clinical practice.

Combining organic molecules and nanoparticles constitutes a pivotal study domain with substantial ramifications in the healthcare, energy, and environmental sustainability sectors. These materials are essential because of their distinctive qualities, such as the molecular adaptability of organic compounds and the nanoscale benefits of nanoparticles, facilitating advanced applications in medicine delivery, pollution reduction, and the creation of innovative materials. This review examines contemporary literature to offer a thorough grasp of their applications, emphasizing their synergistic potential and identifying significant gaps in their development and implementation. The results underscore significant developments in utilizing these materials, accentuating their roles in sustainable energy systems, cutting-edge medical technology, and eco-friendly industrial practices. Furthermore, the review highlights substantial deficiencies, including the inadequate comprehension of their prolonged environmental effects and the difficulties associated with expanding green synthesis techniques. The review identifies gaps and provides practical solutions and future research paths to improve the safe and effective utilization of organic chemicals and nanoparticles. It emphasizes the significance of interdisciplinary collaboration and the creation of strong regulatory frameworks to realize their full potential while maintaining sustainability and ethical accountability. The insights provided establish a significant basis for researchers, governments, and enterprises to utilize these materials for societal progress.

Maternal nutrition and its effects on birth weight especially with reference to dietary inadequacy, socio demographic status and health services. Using a mixed-methods approach, data from 300 postpartum women revealed significant nutritional gaps, including insufficient energy (mean intake: Energy (1800 kcal vs. recommended 2500 kcal), protein (45 g vs. 75 g), and micronutrients including iron, calcium, and vitamin D. These deficiencies were strongly associated with LBW, with multivariate regression showing significant odds ratios for energy (AOR: 2.privilege were significantly associated with higher energy intake (AOR: 5.0; 95% CI: 1.6–4.0) and higher protein intake (AOR: 3.1; 95% CI: 1.9–5.2). The study also realized that 33.3% of infants were categorized as LBW, which was similar to the current global statistics of low-income settings. The study affirmatively confirms maternal dietary interventions, use of supplementation, and the improvements in socio-economic wellbeing and its cruciality for decreasing the LBW prevalence. This research gives practical recommendations to both policy makers and health care practitioners who wish to enhance maternal and neonatal health.

This report explores the use of carbon nanoparticles for the detection of heavy metals, highlighting their potential in environmental and industrial applications. Various carbon nanomaterials, such as graphene-based materials, carbon nanotubes, and fullerenes, are employed for the extraction of heavy metals and wastewater treatment. Carbon nanoparticles have gained significant attention as heavy metal detectors and water purifiers due to their high reactivity, large surface area, and unique properties. These characteristics make them ideal for detecting and removing toxic heavy metals from contaminated environments. However, the widespread application of carbon nanoparticles is hindered by challenges such as high production costs, complex synthesis methods, and environmental concerns. Despite these limitations, ongoing research is focused on optimizing the use of carbon nanoparticles in several promising domains. These include nanoelectronics, smart materials, biomedical applications, energy storage and conversion, advanced water treatment systems, and sensing technologies. By addressing the existing challenges and exploring emerging opportunities, carbon nanoparticles have the potential to revolutionize various industries. With continued advancements in their production and functionality, carbon nanoparticles could provide more sustainable solutions for environmental pollution, particularly in the fields of water purification and heavy metal detection. As these technologies evolve, carbon nanoparticles are poised to contribute to a more technologically advanced and environmentally friendly future. Their successful integration into multiple industries could lead to breakthroughs in water treatment and pollution control, further improving environmental sustainability and human health. Carbon nanoparticles offer substantial promise, but overcoming the current challenges is key to unlocking their full potential.

This paper presents a systematic review exploring the role of genetic testing in precision medicine, focusing on its ability to predict disease risk, personalize treatment strategies, and enhance clinical decision-making. Genetic testing offers significant potential in early disease detection, particularly for conditions with strong genetic components such as cancer, cardiovascular diseases, and neurodegenerative disorders. By identifying high-risk individuals, genetic tests enable proactive interventions that can improve health outcomes and reduce disease burden. Additionally, genetic testing plays a crucial role in tailoring treatments, especially in oncology and pharmacogenomics, by providing insights into how patients will respond to specific drugs, leading to more effective and safer therapies. However, challenges remain in integrating genetic testing into routine clinical practice due to barriers like cost, accessibility, and the complexity of genetic data interpretation. Ethical concerns, insurance coverage issues, and the need for better clinician training also hinder its widespread adoption. Despite these challenges, genetic testing holds transformative potential, and with advancements in technology, policy, and education, it is poised to revolutionize healthcare by enabling more personalized, effective, and efficient care. This paper provides a comprehensive understanding of the current landscape and future directions for genetic testing in precision medicine.

This study investigated the levels of pollutants such as volatile organic compounds (VOCs), pesticides, herbicides, and heavy metals in air, water, and soil samples, using advanced chromatographic techniques. Air samples were analyzed via Gas Chromatography-Mass Spectrometry (GC-MS) after thermal desorption, while water and soil samples were assessed using High-Performance Liquid Chromatography (HPLC) and Gas Chromatography (GC) for organic contaminants and heavy metals. The research employed rigorous sampling techniques, including grab and composite methods, and calibration using certified reference materials. Results revealed significant variations in pollutant concentrations across different environmental matrices and sampling sites. Notably, water samples showed elevated pesticide levels, while soil exhibited concerning concentrations of heavy metals like lead and cadmium. Statistical analysis indicated significant differences in pollutant levels across locations, which could pose risks to both human health and ecosystems. The study underscores the importance of continuous monitoring and regulatory oversight to mitigate the environmental and health impacts of these contaminants. The findings suggest that stricter regulations and more sensitive analytical methods are necessary for effective pollution control.

Background: Chronic obstructive pulmonary disease (COPD) patients are at heightened risk for developing cardiac arrhythmias due to shared risk factors, hypoxemia, and the use of certain medications. Despite this, routine screening for arrhythmias in COPD patients is often neglected in resource-limited settings. Objective: To determine the prevalence and associated factors of cardiac arrhythmias in patients presented with Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD) at B&C Medical College Teaching Hospital in Eastern Nepal. Methods: This was a cross-sectional analytical study conducted at B&C Medical College Teaching Hospital and Research Center, Birtamode, Jhapa, Eastern Nepal, from February 10 to May 10, 2026. The study population comprises of 196 patients aged 40 years or above presenting with an acute exacerbation of a pre-existing COPD diagnosis. The primary diagnostic tool for arrhythmia detection was a standard resting 12-lead electrocardiogram (ECG) performed at the time of enrollment or at the earliest clinically appropriate moment during the acute admission. All data were entered and analyzed using IBM SPSS Statistics version 25. Results: Arrhythmia was present in 39.3% COPD patients. Gender distribution differed significantly, with a higher proportion of females in the arrhythmia group (39% vs 23.5%, p=0.021). Among current medications, LAMA use was significantly lower in patients with arrhythmia (51.9% vs 68.9%, p=0.017); LABA, ICS and theophylline use showed no significant difference. Quit duration was shorter in the arrhythmia group, though this only approached significance (p=0.057). When arrhythmia subtypes were further analyzed against demographic and clinical variables, no statistically significant associations emerged. Across arrhythmia subtypes, Conclusion: Cardiac arrhythmia was present in 39.3% of patients with acute exacerbation of COPD, with sinus arrhythmia and atrial fibrillation being the most common. Female gender was significantly associated with arrhythmias, while LAMA use was less common. These findings highlight the need for regular cardiovascular assessment and electrocardiographic monitoring for early detection and management of cardiac arrhythmias.

Background: Cardiovascular disease, type 2 diabetes, chronic obstructive pulmonary disease (COPD), and chronic heart failure account for a disproportionate share of hospital admissions, readmissions, and health-service expenditure worldwide. Integrated care coordinating services across primary, specialist, hospital, and community settings has been widely promoted as a remedy, but the effectiveness literature has repeatedly evaluated “integrated care” as a single, undifferentiated intervention. What remains unresolved is which specific intervention components drive the reductions in hospital utilisation that some, but not all, integrated-care programmes achieve. Objective: To identify, from systematic reviews, meta-analyses, and primary evaluation studies, which components of integrated care are most consistently associated with reduced hospital admissions, readmissions, emergency department (ED) use, and costs among adults with chronic disease, and to determine what implementation factors explain variation in effectiveness across components and conditions. Methods: A systematic review with narrative synthesis (synthesis without meta-analysis, SWiM) was conducted on systematic reviews, meta-analyses, and primary evaluation studies retrieved through structured literature searches, following PRISMA 2020 guidance for reviews of reviews. Study design, intervention components, population, utilisation outcomes, clinical outcomes, and cost outcomes were extracted and synthesised by intervention component rather than by individual study, under the guiding frameworks of the Chronic Care Model (CCM) and the Rainbow Model of Integrated Care (RMIC). Results: Thirteen sources met eligibility criteria. Interventions combining multidisciplinary team-based follow-up, structured transitional-care or discharge-management components, and cross-setting care coordination were the components most consistently associated with reduced utilisation. In this subset of evidence, patients with cardiovascular disease had a 37% reduction in hospitalization (RR 0.63, 95% CI 0.56–0.71), and patients with cardiovascular disease or type 2 diabetes had a 47% reduction in adverse events (RR 0.53, 95% CI 0.27–1.05). Transitional-care and post-discharge follow-up components reduced 30-day rehospitalisation by 21–37% depending on intensity and patient risk. A four-year, multi-component chronic-disease-management programme incorporating care coordination produced an 11.4% reduction in admissions, a 36.7% reduction in readmissions, and a 17.2% reduction in bed-days. Single-component self-management-support interventions, by contrast, showed less consistent utilisation benefit, although they improved intermediate clinical outcomes. Cost findings were more heterogeneous than utilisation findings across components, with net savings concentrated in high-risk heart-failure populations. Conclusion: The evidence indicates that hospital-utilisation benefits from integrated care are not uniform across intervention types, but are concentrated in programmes combining multidisciplinary teams, structured transitional care, and risk-stratified follow-up spanning more than one care setting. Evidence for these components is strongest in cardiovascular disease and heart failure and weaker and less consistent for type 2 diabetes and chronic respiratory disease. Future research should prioritise component-specific, standardised, longer-follow-up evaluations rather than further whole-programme effectiveness studies.

Background: Access to high-quality psychiatric services remains a major challenge in many low- and middle-income countries, including Pakistan. In Balochistan, limited mental health infrastructure, workforce shortages, financial constraints, and social stigma continue to impede access to appropriate psychiatric care. Despite increasing recognition of mental health needs, evidence regarding the quality and accessibility of psychiatric services in Quetta remains limited. Objective: To assess the accessibility and quality of psychiatric services in Quetta, Pakistan, from the perspectives of patients and healthcare providers and to identify factors associated with patient satisfaction. Methods: A cross-sectional study was conducted among 100 participants, comprising 50 psychiatric patients and 50 healthcare providers recruited from major psychiatric healthcare facilities in Quetta, Pakistan. Participants were selected using purposive sampling. Data were collected using structured questionnaires assessing service accessibility, quality of care, patient satisfaction, organizational support, and barriers to mental healthcare. Descriptive statistics were used to summarize participant characteristics, while chi-square tests, correlation analysis, and logistic regression were performed to examine associations between study variables. Statistical analyses were conducted using IBM SPSS Statistics version 26, with a significance level of p < 0.05. Results: Overall, 58% of patients reported moderate satisfaction with psychiatric services, whereas 24% reported high satisfaction and 18% reported low satisfaction. Financial constraints (42%), social stigma (36%), and transportation difficulties (22%) were identified as the principal barriers to accessing psychiatric care. Among healthcare providers, inadequate resources (46%), workforce shortages (34%), and infrastructure limitations (20%) were the most frequently reported challenges affecting service delivery. Greater accessibility to psychiatric services was significantly associated with higher patient satisfaction (p < 0.05). Healthcare providers also highlighted the need for increased organizational support and expansion of mental health resources to improve service quality. Conclusion: Psychiatric services in Quetta face substantial challenges related to accessibility, workforce capacity, infrastructure, and resource availability. Strengthening mental health infrastructure, expanding the trained mental health workforce, integrating psychiatric care into primary healthcare services, and implementing stigma-reduction strategies may improve access to care and enhance patient satisfaction. These findings provide evidence to inform future mental health policy and service planning in Balochistan and similar resource-constrained settings.

This study aimed to determine the prevalence of malnutrition and identify its associated risk factors among children under five years of age attending primary healthcare centers in Punjab, Pakistan. A quantitative cross-sectional research design was used, and data were collected from 384 children and their caregivers through structured questionnaires and anthropometric measurements based on WHO growth standards. Descriptive statistics were used to determine the prevalence of malnutrition, post hoc analysis was applied to assess differences across age groups, chi-square tests were used to examine associations between socio-demographic factors and malnutrition, and binary logistic regression identified independent predictors. The results showed a high prevalence of malnutrition, with significant age-related differences, where children aged 12–59 months had higher rates of stunting, wasting, and underweight compared to infants. Socio-demographic factors such as maternal education, household income, family size, and rural residence were significantly associated with malnutrition. Logistic regression analysis revealed that lack of exclusive breastfeeding (AOR = 2.48), inappropriate complementary feeding (AOR = 2.91), inadequate dietary diversity (AOR = 3.12), recent diarrheal episodes (AOR = 3.65), and incomplete immunization (AOR = 2.39) were significant predictors of malnutrition. The study concludes that malnutrition among children under five is highly prevalent and influenced by multiple modifiable factors, highlighting the need for integrated nutritional and healthcare interventions at the primary healthcare level in Punjab, Pakistan.

In the current experiment, green synthesis of AgNPs and ZnO nanoparticles was done by making use of an aqueous solution extracted from the leaves of Azadirachta indica. Nanoparticles were synthesized successfully through the green method, and their formation was evident through visible color changes and precipitation. Surface plasmon resonance peak was measured through UV-visible spectroscopy to be 432 nm, indicating successful and efficient synthesis of nanoparticles with good stability and uniformity. Functional groups present were O-H, C=O, C-N, and C-O, implying that some phytochemical compounds present in plants were utilized in the reduction process. High crystallinity of AgNPs and ZnO NPs was evident through XRD pattern results, which show a face-centered cubic structure and a hexagonal wurtzite structure of crystallite sizes ranging between 15-35 nm. The fabricated nanomaterials displayed good antibacterial behavior towards Staphylococcus aureus and Escherichia coli, whereby silver nanoparticles had better antimicrobial behavior compared to other fabricated nanomaterials. Better antibacterial behavior was due to the small size of nanoparticles, increased surface area, and good interaction with the membrane of bacteria cells. Generally, the results show that fabricated nanomaterials have promising properties for biomedical and environmental uses.

Background: Prediabetes is a high-risk metabolic state that can lead to poor cardiorespiratory fitness, functional deficits of lower extremities, surplus body fat, and high risk of type 2 diabetes. BFR is a lower-force exercise that may offer a beneficial exercise-training strategy for patients with high-force-intolerant mechanical loads. Objective: This study compared two-months of BFR training with conventional training on VO2 max, function, strength of quadriceps, training-volume, oxygen pulse, and body composition in prediabetics. Methods: A two-month randomized controlled trial was performed in gyms and fitness centers within Faisalabad. The 25–50 year-old, 40 prediabetics were divided into an experimental BFR group (n=20) or a control Conventional group (n=20). Exercise outcomes (VO2 max using Rockport Fitness Walking Test, functional status using the 6-Minute Walk test, strength of quadriceps by use of isokinetic dynamometer, training-volume using daily log, oxygen pulse by using a Heart rate/oximetry reading, body composition by using anthropometrics) were compared before and after the trial. Results: No differences were present at baseline. Post-trial BFR-trained group was better than the conventional-trained group in VO2 max (34.002.34 vs. 32.192.90 ml/kg/min; p=.036), 6-min walk distance (472.8713.13 vs. 445.6526.58m; p<.001), quadriceps strength (30.741.83 vs. 26.832.61; p<.001), training-volume (3.950.76 vs. 3.290.48; p=.002), oxygen pulse (14.750.87 vs. 12.721.55; p<.001), percentage of body fat (25.482.63% vs. 27.542.67%; p=.018), and body mass index (25.052.25 vs. 26.652.38 kg/m2; p=.036). Conclusion: BFR training led to a better increase in VO2 max, functional ability, strength of quadriceps, exercise tolerance, cardiovascular efficiency, and body composition than conventional training in prediabetics.

Introduction: Chronic nonspecific low back pain is an extremely common musculoskeletal disorder, characterized by pain, functional disability and fear of movement. Rehabilitation approaches such as core stabilization and graded activity programs are frequently prescribed, however the comparison of their effectiveness in physical and psychological measures has clinical significance. The objective of this study was to compare the effects of core stabilization exercises versus a graded activity program on the pain levels, functional disability and fear of movement in chronic nonspecific low back pain patients. Methods: The study was carried out as a single-blind randomized controlled trial for 12 weeks. The patients who met the criteria were randomly allocated into two groups; Group A, performing core stabilization exercises (n=15) or Group B, performing a graded activity program (n=15). Pain was measured by Visual Analogue Scale (VAS), functional disability by the Oswestry Disability Index (ODI) and fear of movement by the Tampa Scale of Kinesiophobia (TSK). Patients were evaluated pre- and post- intervention. Data were analyzed by paired t-test and independent t-test at p<0.05. Results: There were significant changes within the groups for the VAS, ODI and TSK in both Group A and B (p<0.001). In between-group comparisons, there was a significantly higher decrease in pain and disability in the core stabilization group (VAS: 3.67+/-0.72 vs. 5.07+/-0.70 and ODI: 31.93+/-4.07 vs. 36.87+/-4.51) while significantly higher decrease in fear of movement occurred in the graded activity group (TSK: 29.53+/-3.23 vs. 36.53+/-3.83). Conclusion: The core stabilization exercises were better than graded activity in improving pain and disability levels in patients with chronic nonspecific low back pain while graded activity resulted in better improvement in kinesiophobia. A combination of core stabilization and graded activity would be beneficial for patients with chronic nonspecific low back pain.

The study was carried out on the development of food attractants of Bactrocera zonata and Bactrocera dorsalis using McPhail traps filled with food-based lures at different ratios of Prima, Protein hydrolysate, Nulure, DAP, and Urea under field conditions in a guava orchard. Treatments included T1=Prima 10 ml, urea 3g, T2=Prima 5 ml, urea 6g, T3=Prima 10ml, DAP 3g, T4=Prima 5 ml, DAP 6g, T5=Protein hyd: 5 ml, DAP 6g, T6=Protein hyd: 10ml, DAP 3g, T7=Nulure 10ml, DAP 3g, T8=Nulure 5ml, DAP 6g. Monthly male and female Bactrocera zonata and Bactrocera dorsalis catches were recorded to assess the efficiency of food attractants. The results showed that the trap catches were significantly affected by food attractants for male Bactrocera zonata (P<0.0021), female Bactrocera dorsalis (P<0.0017), and male Bactrocera dorsalis (P=0.0022); while non-significant (P=0.6217). Seasonal variation was also significant (P<0.01). Overall, Protein hydrolysate 5 ml and DAP 6g (T5) produced the highest catches for both species, while Prima 5 ml, urea 6g (T2), and Nulure-based treatments showed lower performance in most cases. The Bactrocera zonata catches were in the range of 273.75-1040.50/trap, while Bactrocera dorsalis ranged from 133.75-11075/trap across treatments. Male and female populations of both species showed the lowest catches in April and increased progressively in May, June, and July. It was concluded that traps filled with Protein hydrolysate 5 ml and DAP 6g attracted maximum Bactrocera zonata and Bactrocera dorsalis, and in most cases, Prima 5 ml (urea 6 g)- based traps showed the lowest catches.

This study evaluates preventive healthcare strategies for improving population health outcomes through a comprehensive public health analysis. A quantitative research design was employed at Nishtar Medical University, where data were collected from a sample of 250 respondents, including healthcare professionals and community members, using stratified random sampling techniques. The study examined key preventive healthcare interventions such as vaccination programs, health education, screening services, lifestyle modification initiatives, and community-based health programs. Data were analyzed using descriptive statistics, regression analysis, and Chi-square tests to assess relationships between preventive strategies, policy influence, and implementation barriers. The results revealed that vaccination programs and early intervention strategies were the most effective in improving population health outcomes, while regression analysis confirmed a significant positive impact of public health policies, health education, and early intervention programs on disease prevention and health promotion (R² = 0.61, p < 0.05). Chi-square analysis further indicated that financial constraints, lack of awareness, and limited access to healthcare services are major barriers affecting the implementation of preventive healthcare strategies. The study concludes that preventive healthcare significantly enhances population health outcomes; however, its effectiveness is influenced by socioeconomic and systemic challenges that must be addressed through stronger policies, improved health education, and equitable healthcare access.

Background: Chronic kidney disease (CKD) is an important global public health issue and emerging non communicable disease that occurs more often in developing countries where few patients have access to renal replacement therapy and has a high burden of symptomatic illness. Methods: This descriptive cross-sectional study was performed Between September 2025 and February 2026, in the nephrology department of District Headquarters Teaching Hospital of Dera Ismail Khan Pakistan. A total 100 of hospitalized patients aged between 18 -80 years with CKD stage V and medical indication for the hemodialysis were recruited using successive sampling. Data were collected using a pre-tested structured questionnaire regarding clinical characteristics, utilization of healthcare services in the past, demography and acceptance of hemodialysis. Results: Out of 100 patients, 34% refused hemodialysis while 66% accepted treatment. Among those who refused, the mean age was 45.03 ± 7.08 years, with a slight female predominance (52.9%). Most patients were uneducated (67.6%) and belonged to lower socioeconomic class (67.6%). Family members were the primary decision-makers in 67.6% of cases. The most common reasons for refusal were fear of the dialysis procedure (88.2%), perceived poor quality of life (44.1%), financial constraints (29.4%), and influence of family or peers (26.5%). Clinical parameters indicated advanced disease at presentation. Conclusion: Refusal to hemodialysis is widespread and complex, mostly motivated by societal pressures, fear, and financial obstacles. Improved access to subsidized dialysis treatments, early counselling, and patient education are crucial for increasing treatment acceptability and lowering avoidable death.