Peer-Reviewed • Open Access • Semi-Annual Scientific Insights and Perspectives Scientific Insights and Perspectives is a peer-reviewed, open-access journal dedicated to publishing cutting-edge research across all disciplines of science and technology. Our mission is to foster the dissemination of high-quality, interdisciplinary research that advances knowledge and contributes to solving global challenges. Publisher: MIND QUEST RESEARCH & EDUCATIONAL CENTER (SMC-PRIVATE) LIMITED Frequency: Semi-Annual We aim to provide a platform for researchers, scholars, and practitioners to share their insights and innovations, offering a wide range of scientific perspectives on emerging trends and established theories alike. The journal publishes original research articles, reviews, and case studies in Natural Sciences, Engineering and Technology, Health Sciences, Social Sciences, and Humanities & Arts. Submit Article Current Issue
MIND QUEST RESEARCH & EDUCATIONAL CENTER (SMC-PRIVATE) LIMITED
EXPLORING THE USE OF ARTIFICIAL INTELLIGENCE IN EARLY DETECTION AND DIAGNOSIS OF DISEASES IN VETERINARY MEDICINE
Artificial intelligence is increasingly being integrated into veterinary medicine to enhance diagnostic accuracy, disease prediction, and clinical decision support. This study systematically evaluated the performance of AI-driven models using a mixed-method experimental approach that combined quantitative analysis of large-scale veterinary datasets with qualitative expert validation. Results from multiple experimental evaluations demonstrated consistently high diagnostic accuracy, sensitivity, and specificity across veterinary specialties, disease categories, and species. Convolutional neural network–based imaging models showed superior performance in complex diagnostic tasks, while predictive analytics effectively forecasted disease onset and epidemiological trends. Graphical and tabular analyses revealed strong model robustness under varying noise conditions, improved learning efficiency with increasing data volume, and reduced false-positive rates compared to conventional approaches. The findings confirm that AI-based systems can process multimodal veterinary data efficiently, identify subtle diagnostic patterns, and support earlier and more precise clinical interventions. Importantly, the study highlights that AI serves as a reliable decision-support tool that complements veterinary expertise rather than replacing it. While challenges related to data availability, standardization, and ethical considerations remain, the results provide strong evidence that artificial intelligence can play a pivotal role in advancing preventive, personalized, and data-driven veterinary healthcare.
Copyright (c) 2025 Muhammad Inam Farooq, Rabia Kiran (Author) https://creativecommons.org/licenses/by/4.0
INVESTIGATING THE EFFECTS OF ENVIRONMENTAL STRESSORS ON ANIMAL HEALTH AND WELFARE: A FOCUS ON LIVESTOCK IN INTENSIVE FARMING SYSTEMS
Intensive livestock farming systems are increasingly challenged by environmental stressors that compromise animal health, welfare, and productivity, particularly under the growing pressures of climate change and rising global demand for animal-derived food products. This study investigated the effects of key environmental stressors—including thermal load, humidity, air quality, stocking density, and management-related factors—on livestock health and welfare within intensive production systems. Using a mixed-methods experimental approach, quantitative physiological and productivity indicators were integrated with qualitative behavioral assessments and precision livestock farming data. The results demonstrate that elevated environmental stress levels were consistently associated with increased physiological stress responses, including higher cortisol concentrations, reduced feed intake, impaired productivity, and deteriorating composite welfare scores. Behavioral indicators revealed heightened discomfort and abnormal activities under unfavorable environmental conditions, while prolonged exposure led to increased morbidity and mortality risks. Advanced sensor-based monitoring and precision livestock technologies proved effective in detecting early stress signals, enabling real-time environmental and management interventions. Overall, the findings highlight that environmental stressors exert cumulative and interrelated impacts on livestock well-being, extending beyond immediate physiological strain to long-term welfare and productivity consequences. The study underscores the importance of integrating environmental management, welfare assessment frameworks, and digital monitoring technologies to develop climate-resilient, welfare-oriented intensive farming systems. Such integrated strategies are essential for balancing production efficiency with ethical responsibility, animal health protection, and sustainable livestock development in the face of ongoing climatic and socio-economic challenges.
Copyright (c) 2025 Aftab Ahmed, Muhammad Waqar Ali (Author) https://creativecommons.org/licenses/by/4.0
THE ROLE OF ARTIFICIAL INTELLIGENCE IN EARLY DETECTION OF ANIMAL DISEASES: A CASE STUDY OF LIVESTOCK EPIDEMICS IN DEVELOPING COUNTRIES
Livestock diseases pose a persistent threat to food security, rural livelihoods, and economic stability in developing countries, where traditional disease surveillance systems often fail to provide timely and accurate outbreak detection. This study investigates the role of artificial intelligence in enhancing early detection of livestock diseases through an experimental mixed-methods approach. Quantitative analyses were conducted using multi-source livestock health, environmental, and epidemiological data to evaluate the performance of machine learning models in outbreak prediction and disease classification, while qualitative insights were used to contextualize AI adoption within resource-constrained veterinary systems. The results reveal that AI-based surveillance significantly improves detection accuracy and reduces outbreak detection lead time compared to conventional monitoring methods. Across multiple regions and livestock species, AI models consistently identified early disease signals prior to laboratory confirmation, enabling more effective and timely interventions. Visual analytics further demonstrated strong associations between livestock density, environmental stressors, and AI predictive performance. The study also highlights the scalability and robustness of AI systems across diverse epidemiological settings, emphasizing their potential to support decision-making in low-resource environments. Overall, the findings confirm that artificial intelligence can substantially strengthen livestock disease surveillance, mitigate epidemic impacts, and contribute to more resilient agricultural systems in developing countries.
Copyright (c) 2025 Muhammad Bilal, Hammad Ur Rehman (Author) https://creativecommons.org/licenses/by/4.0
EVALUATING THE EFFECTIVENESS OF CRISPR-CAS9 TECHNOLOGY IN VETERINARY MEDICINE FOR GENETIC DISEASE TREATMENT IN COMPANION ANIMALS
The emergence of CRISPR-Cas9 genome editing technology has opened new avenues for the treatment of inherited genetic diseases in veterinary medicine. This study experimentally evaluated the effectiveness, safety, and clinical relevance of CRISPR-Cas9–based therapeutic interventions in companion animals. A mixed-method approach integrating molecular, clinical, and longitudinal analyses was employed to assess gene-editing efficiency, off-target effects, tissue-specific performance, immune responses, and therapeutic outcomes. Quantitative results demonstrated consistently high editing efficiencies and stable genetic correction across follow-up periods, accompanied by significant reductions in disease-associated biomarkers and marked clinical improvement. Comparative analyses revealed superior survival and recovery outcomes in CRISPR-treated animals relative to conventional therapies. Off-target mutation frequencies were minimal, and immunological evaluations indicated favorable host tolerance. Visual analyses using multiple graphical models further supported the robustness and reproducibility of the findings. The results confirm that CRISPR-Cas9 enables precise, durable, and clinically meaningful genetic correction in companion animals, positioning it as a promising alternative to traditional veterinary treatments. This study provides comprehensive experimental evidence supporting the translational potential of CRISPR-Cas9 technology and highlights its role as a next-generation therapeutic strategy for genetic disease management in veterinary medicine.
Copyright (c) 2025 Usama Raza, Uzair Nisar (Author) https://creativecommons.org/licenses/by/4.0
EXPLORING THE POTENTIAL OF USING CRISPR-CAS9 FOR ENHANCING NUTRITIONAL QUALITY OF STAPLE CROPS IN SUB-SAHARAN AFRICA
Micronutrient malnutrition remains a critical public health and development challenge in Sub-Saharan Africa, largely due to the reliance on nutritionally limited staple crops. This study evaluated the effectiveness of CRISPR-Cas9–based genome editing as a biofortification strategy to enhance the nutritional quality of major staple crops. Using a mixed-methods experimental framework, targeted gene editing was applied to improve iron, zinc, and provitamin A accumulation while reducing antinutritional factors such as phytic acid. Quantitative analyses revealed substantial increases in micronutrient concentrations and bioavailability across edited crop lines, accompanied by stable or improved yield performance. Off-target mutation analysis confirmed high editing precision, and economic evaluation demonstrated superior cost-effectiveness relative to conventional breeding and transgenic methods. Graphical and tabulated results consistently showed strong correlations between editing efficiency and nutritional gain, validating the robustness of the approach. Qualitative assessment of regulatory and socio-economic contexts further indicated that CRISPR-Cas9 biofortification is scalable and well-suited to resource-constrained agricultural systems. Collectively, the findings establish CRISPR-Cas9 as a safe, efficient, and economically viable tool for developing nutritionally enhanced staple crops, offering a sustainable pathway to combat hidden hunger and improve food and nutritional security in Sub-Saharan Africa.
Copyright (c) 2025 Muneeba, Muska Hayat (Author) https://creativecommons.org/licenses/by/4.0
ROLE OF PLANT SPACING AND SOWING ORIENTATION IN CABBAGE GROWTH AND HEAD FORMATION
A field experimentation was piloted at Lasbela University, Balochistan, Pakistan, to evaluate the influence of different plant spacings and sowing orientations on the growth and yield performance of cabbage (Brassica oleracea var. capitata). The study included six treatment combinations involving three plant spacings (45×45, 60×45, 60×60 cm) and two sowing orientations (north-south and east-west). Data were recorded on plant tallness (at 30, 60 days after transplanting and at maturity), leaves, leaf area, stem diameter, head initiation (days), diameter & weight, marketable & unmarketable yield. Results showed that wider spacing, particularly the 60×60 cm configuration combined with north-south orientation (S3O1), significantly enhanced the growth of cabbage plants. This treatment also delayed head initiation slightly but produced significantly larger and heavier heads. Consequently, it resulted in the maximum marketable yield (29.0 Mg ha⁻¹) and the lowermost unmarketable yield (2.5 t ha⁻¹). The improved performance under wider spacing and favorable orientation is attributed to reduced interplant competition and better resource utilization. These results provide useful recommendations for farmers in Balochistan and similar agro-ecological zones aiming for efficient cabbage cultivation.
Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0
BIODIVERSITY OF ENDEMIC PLANTS IN ISOLATED ECOSYSTEMS: A CONSERVATION GENETICS PERSPECTIVE
Evolution tends to occur everywhere; especially in isolated environments. They contain localized plant species of endemic nature that have unique genetic markers that are highly significant in terms of biodiversity conservation. Within this mixed-methods experimental study, the biodiversity and conservation genetics of three alpine, coastal and island native plants were investigated. On quadrat sampling, field-based quadrat sampling indicated that number of different species was large in the region and in some places, Shannon-Wiener Index (H?) exceeded 2.5. People interviews provided valuable ecological data, as ethnobotanical conversations with the residents of the region highlighted the species, which are part of their culture and should be safeguarded. Populations were found to be very genetically diverse (mean F st = 0.27) with an observed heterozygosity (Ho) between 0.42 and 0.68 using microsatellite and chloroplast DNA markers. Isolation was the contributor of the divergence explored in the geographic-genetic correlation (Mantel test r = 0.63, p < 0.01). There was predictive species distribution modeling indicating that some of this population would change upslope or microrefugia with changing habitats as a result of climate change scenarios (RCP 4.5 and 8.5). Peculiar combination of ecological, genetic, and geographical information assisted in the identification of high-priority areas of conservation, which are characterized by the presence of great genetic wealth, and the weather conditions are quite steady. These findings indicate the significance of the employment of genetically advised and transdisciplinary conservation designs, particularly in regions, which are ecologically fragile and poorly surveyed. Conservation that encompasses the entire community and which is possible to alter over time that uses both molecular technology and traditional wisdom is encouraged at the end of the paper.
Copyright (c) 2024 Hammad Ur Rehman, Noor Ullah (Author) https://creativecommons.org/licenses/by/4.0
COVER CROPS FOR GREENHOUSE GAS EMISSION REDUCTION IN AGRICULTURAL SOILS
The increasing contribution of agriculture to greenhouse gas (GHG) emissions has prompted the urgent need for sustainable soil management practices that mitigate climate impacts. This study investigates the effectiveness of integrating cover crops, microbial inoculants, biochar, and conservation tillage in reducing soil-based GHG emissions and enhancing carbon sequestration. Through a combination of field trials and stakeholder analysis, the research evaluates the biophysical and agronomic responses under various treatment conditions. Results indicate that cover cropping significantly boosts soil organic carbon and microbial biomass while decreasing nitrous oxide emissions, particularly when combined with biochar and chitin amendments. No-till practices further contribute to carbon retention, while advanced nitrogen management using nitrification inhibitors enhances nitrogen use efficiency and reduces environmental leakage. Soil pH, temperature moderation, and crop yield metrics also improved under integrated strategies. Notably, degraded lands cultivated with bioenergy crops exhibited the highest carbon sequestration potential. Correlation analysis revealed strong inverse relationships between N₂O emissions and both SOC and microbial biomass. Visual analyses confirmed the efficacy of sustainable treatments in improving soil health and reducing emissions. The study concludes that adopting region-specific, climate-smart agricultural practices can substantially contribute to climate mitigation, food security, and ecosystem resilience. These findings support policy initiatives aimed at promoting environmentally sustainable farming systems.
Copyright (c) 2025 Ayesha Irum (Author) https://creativecommons.org/licenses/by/4.0
EXPLORING WILDLIFE-LIVESTOCK DISEASE INTERFACES IN TRANSBOUNDARY PROTECTED ECOSYSTEMS
The study aimed to examine the animal-cattle interaction within transboundary protected Areas to determine the prevalence and the dynamics of transmission of zoonotic diseases and the related socio-ecological risks. They applied a mixed-method design that included field observation, laboratory diagnostics (ELISA and PCR) and community-based survey in three areas surrounding protected reserves. The results showed a high prevalence of Foot-and-Mouth Disease Virus (FMDV) in cattle (35.6%) and buffalo (40.2$), as well as high detection of Peste des Petits Ruminants Virus (PPRV), Rift Valley Fever Virus (RVFV), and Mycobacterium bovis in various livestock and wild species. The contact between wildlife and livestock was significantly greater (71.2%) during the dry season when the animals could drink at the same water points and also graze in the same fields. Serology revealed similar exposure signatures between domestic and wild ruminants suggesting possible transmission between species. Surveys of the community revealed that the individuals were not very aware of the dangers of zoonotic diseases and were not making optimum use of quarantine and fencing practices. Quarantine was reported by only 27.5 percent of the people. Diagnostic tests demonstrated moderate reliability, and PCR was more specific than ELISA but requires more time to obtain the results. The report stresses the urgency of integrated One Health surveillance systems, enhanced diagnostic infrastructure, and biosecurity awareness through community engagement. The findings provide policymakers, veterinarians, and conservationists with the basic information they need to improve disease control measures, as well as support sustainable co-existence in ecologically fragile settings.
Copyright (c) 2025 Hidayatullah (Author) https://creativecommons.org/licenses/by/4.0
COMPARATIVE STUDY OF RADIOMICS VS. PATHOMICS FOR BREAST CANCER SUBTYPE PREDICTION
Breast cancer remains a leading cause of cancer-related morbidity and mortality among women worldwide, necessitating more accurate and non-invasive methods for early diagnosis and molecular subtype classification. This study presents an integrative framework combining radiomics and pathomics to enhance the precision of breast cancer subtype prediction. Radiomic features were extracted from medical imaging modalities, capturing tumor heterogeneity, shape, and texture, while pathomic features were derived from digitized histopathology slides, quantifying cellular morphology and tissue architecture. A series of machine learning models, including Random Forest, SVM, and XGBoost, were applied to unimodal datasets, with XGBoost achieving the highest accuracy of 84% (AUC: 0.88) using radiomic features and 82% (AUC: 0.85) with pathomic features. Multimodal fusion models outperformed unimodal approaches, with the Fusion-CNN model reaching an accuracy of 88% and an AUC of 0.91. SHAP analysis revealed that Texture_Homogeneity, Mitotic Count, and GLCM_Correlation were the most influential predictors across modalities. Visualizations further demonstrated clear separability between subtypes such as Luminal A and Triple Negative, validating the discriminative power of the selected features. The integration of radiomics and pathomics not only improved classification performance but also offered greater biological interpretability and clinical relevance. This study highlights the transformative role of AI-driven, multimodal diagnostic pipelines in supporting precision oncology and individualized patient management in breast cancer care.
Copyright (c) 2025 Hassan Yar Mahsood (Author) https://creativecommons.org/licenses/by/4.0
DISRUPTION OF CIRCADIAN RHYTHMS BY ARTIFICIAL LIGHT POLLUTION IN NOCTURNAL INSECTS
Artificial light at night (ALAN) poses a growing threat to nocturnal biodiversity, particularly through the disruption of circadian rhythms in sensitive insect species. This study investigated the physiological and behavioral impacts of varying artificial light spectra and intensities on three nocturnal insects—Acheta domesticus, Galleria mellonella, and Photinus pyralis. Insects were exposed to dark (control), low-intensity LED, high-intensity LED, and blue-rich LED lighting conditions in controlled experiments. Behavioral monitoring revealed a significant reduction in locomotor activity under high-intensity and blue-rich LED conditions, with P. pyralis displaying the sharpest decline. Quantitative real-time PCR analyses showed a consistent downregulation of circadian genes (per, tim, clk, and cry) under artificial lighting, particularly in the blue-rich spectrum, indicating severe molecular disruption of internal biological clocks. These gene expression alterations correlated strongly with behavioral impairments and reduced reproductive success. Reproductive metrics, including egg production, hatch rate, and survival, were significantly lower in all ALAN-exposed groups compared to the control, with G. mellonella exhibiting the greatest reproductive decline. Behavioral assays further revealed reductions in courtship and feeding events and an increase in stress-related avoidance behavior. Across all metrics, the blue-rich LED light condition emerged as the most disruptive. These findings provide robust empirical evidence linking ALAN to circadian and reproductive dysregulation in nocturnal insects, underscoring the need for revised lighting practices in ecological and urban planning. By integrating behavioral, genetic, and reproductive endpoints, this study highlights the systemic consequences of light pollution and informs conservation strategies aimed at protecting vulnerable nocturnal insect populations.
Copyright (c) 2025 Mashal Shahzadi (Author) https://creativecommons.org/licenses/by/4.0
GENETIC SUSCEPTIBILITY TO PANCREATIC CANCER: A GENOME-WIDE ASSOCIATION STUDY
Pancreatic ductal adenocarcinoma (PDAC), the predominant and most lethal form of pancreatic cancer, continues to pose significant diagnostic and therapeutic challenges due to its aggressive progression, late-stage detection, and resistance to conventional therapies. This genome-wide association study (GWAS) aimed to identify common genetic variants associated with PDAC susceptibility and elucidate potential molecular mechanisms underlying disease pathogenesis. A total of 4,500 individuals (2,250 PDAC cases and 2,250 matched controls) were genotyped using high-density SNP arrays, and rigorous quality control and statistical analyses were applied. Eight SNP clusters across multiple chromosomal regions achieved genome-wide significance (p < 5×10⁻⁸), with the strongest associations observed on chromosomes 3p, 9p21, and 17q, implicating loci near CDKN2A, BRCA1/2, and inflammation-related genes. Replication analysis in an independent cohort of 2,400 individuals confirmed the direction and magnitude of association for several top-ranked SNPs. Looking at the function of these variants, many are found non-coding regions and eQTL studies connect them to changes in the expression of nearby genes in pancreatic tissues. These methods also pointed out that DNA repair, immune signaling and the KRAS pathway are disturbed in the mechanism of epidermal growth factor receptor activity. In aggregate, these results indicate that PDAC risk may be caused by many genes working together and reveal fresh information about its genetics. It supports findings for certain regions suspected in pancreatic cancer and also finds new possible regions which increases our understanding of the disease and forms a base for future use in precision medicine, risk predictions, early detection and targeted treatments.
Copyright (c) 2025 Rida Naz, Muska Hayat (Author) https://creativecommons.org/licenses/by/4.0
REAL-TIME GLUCOSE MONITORING AND INSULIN TITRATION ALGORITHMS IN TYPE 1 DIABETES MANAGEMENT
Continuous glucose monitoring (CGM) and automated insulin titration promise to transform Type 1 diabetes management by reducing patient burden and improving glycemic outcomes. In this prospective, single-center, 14-day interventional study, 30 adults (mean age 35.4 ± 10.2 years; duration of diabetes 12.3 ± 5.1 years; baseline HbA1c 8.1 ± 0.6%) underwent closed-loop insulin delivery driven by a personalized reinforcement-learning algorithm trained on two weeks of retrospective CGM and dosing data. Primary endpoints included percentage time in range (70–180 mg/dL), mean glucose, and glycemic variability; secondary endpoints encompassed rates of hypoglycemia (<70 mg/dL), hyperglycemia (>180 mg/dL), total daily insulin dose, and user satisfaction..
Copyright (c) 2024 Hassan Yar Mahsood, Saad Abdullah (Author) https://creativecommons.org/licenses/by/4.0
BIOMOLECULAR MODELING FOR UNDERSTANDING THE PATHOPHYSIOLOGY OF AUTOIMMUNE DISEASES: APPLICATIONS IN DRUG DEVELOPMENT AND PERSONALIZED MEDICINE
The modeling of biomolecules is essential for understanding the complexity of autoimmune diseases as well as for the development of drugs to cure them. Nowadays, the addition of computer based simulations has opened new doors to understanding the molecular processes that underlie autoimmune disorders, especially the mechanisms that trigger and sustain an aberrant immune response. With the models of protein-ligand binding, it is now possible to evaluate the interaction of specific molecules with immune proteins, which further elucidates the pathways of the disease. This computational method speeds up the process of potential targets identification as well as increases the effectiveness of rational drug design by forecasting the outcome of the candidate drugs during preclinical phases of studies. Furthermore, biomolecular modeling plays a fundamental role in the personalized treatment approach. Extracted patient specific genetic information enables the design of tailored treatments and therapies according to the different responses by individual patients’ immune systems. This form of treatment is more effective while at the same time lowering the chances of adverse side effects when drugs are given. Additionally, biomolecular modeling simulations can help in the prediction of the optimal doses and the determination in your endeavor toward the evolution of precision medicine; novel biomarkers for disease monitoring are studied here. This work will discuss the growing role of biomolecular modeling in research on autoimmune diseases, with a concentration on drug discovery to revolutionize the treatment of autoimmune diseases. In this capacity, an advanced computational technique is used to transform our way of thinking about immune system dysfunctions and apply such knowledge to enhance patient outcomes, ultimately toward an improved and personalized therapeutic strategy for autoimmune disorders.
Copyright (c) 2024 Muhammad Inam Farooq, Rizwan Ullah, Ashraf khan (Author) https://creativecommons.org/licenses/by/4.0
SEROPREVALENCE AND RISK FACTORS OF HEPATITIS E VIRUS AMONG PREGNANT WOMEN IN URBAN SETTINGS
Hepatitis E virus (HEV) poses a significant threat to maternal and fetal health in low-resource urban settings, yet data on its prevalence and determinants among pregnant women remain scarce. We conducted a cross-sectional survey of 500 second-trimester antenatal attendees in three metropolitan hospitals from July to September 2023 to estimate HEV seroprevalence and identify modifiable risk factors. Participants provided demographic and behavioral data via structured interviews and 5 mL blood samples for anti-HEV IgG and IgM ELISA testing. Overall, 55 of 500 women (11.0%) were IgG-positive and 20 (4.0%) were IgM-positive, indicating both prior exposure and recent infection. Multivariable logistic regression revealed that reliance on unimproved water sources more than doubled the odds of seropositivity (adjusted OR = 2.10; 95% CI 1.50–2.90; p < 0.001), and consumption of undercooked meat increased risk by 80% (adjusted OR = 1.80; 95% CI 1.20–2.70; p = 0.010), while age and educational level were not independently significant after adjustment. These findings highlight water sanitation and dietary practices as critical intervention targets. Incorporation of HEV screening into routine antenatal care, paired with community-based WASH (water, sanitation, and hygiene) initiatives and food-safety education, could substantially reduce HEV burden in pregnant populations. Future longitudinal studies should monitor incident infections, genotype distributions, and vaccine efficacy to guide public health strategies. Addressing these modifiable risk factors through integrated water-safety improvements, hygiene promotion, and culturally tailored nutrition guidance will be pivotal for safeguarding maternal and child health in rapidly urbanizing environments.
Copyright (c) 2024 Abdul Ghaffar, Rabia Kiran (Author) https://creativecommons.org/licenses/by/4.0
INNOVATIVE APPROACHES IN CANCER IMMUNOTHERAPY: TARGETING THE TUMOR MICROENVIRONMENT
Cancer immunotherapy has revolutionized the landscape of oncology by leveraging the body’s immune system to identify and eliminate malignant cells. However, the tumor microenvironment (TME) presents a significant barrier to the effectiveness of such therapies due to its immunosuppressive composition and complex cellular architecture. Comprised of stromal cells, immune regulatory cells, extracellular matrix (ECM), and signaling molecules, the TME fosters tumor progression, immune evasion, and therapeutic resistance.This study explores innovative immunotherapeutic strategies that specifically target components of the TME to enhance anti-tumor immune responses. A multifaceted approach was adopted, incorporating immune checkpoint inhibitors, adoptive T cell therapies—including CAR-T and tumor-infiltrating lymphocyte (TIL) therapies—and therapeutic cancer vaccines. Additionally, methodologies to modulate hypoxia, ECM density, and chemokine signaling were simulated to assess their synergistic effects with immunotherapy.The findings indicate that personalized biomarker-guided immunotherapy, when combined with TME-modulating interventions, significantly improves immune cell infiltration, enhances antigen presentation, and reduces tumor-associated immunosuppression. Increased levels of CD8+ T cells, elevated cytokine activity, and decreased regulatory cell populations were observed in treated models. CAR-T cell therapy demonstrated potent efficacy in hematological malignancies, while checkpoint inhibitors and cancer vaccines showed enhanced responses when used in combination protocols.In conclusion, targeting the immunosuppressive elements of the TME is essential for overcoming resistance and maximizing the efficacy of cancer immunotherapy. Combination strategies that integrate immune modulation, genetic engineering, and vaccine-based stimulation represent a promising direction for future therapeutic development. This research underscores the importance of personalized, multi-pathway immunotherapy regimens in achieving durable responses and improved clinical outcomes in diverse cancer types.
Copyright (c) 2024 Zafar Aleem Suchal, Rabia Kiran (Author) https://creativecommons.org/licenses/by/4.0
STRATEGIES FOR REDUCING FOOD WASTE IN AGRICULTURE
Food waste in agriculture poses a critical global challenge, contributing significantly to environmental degradation, resource inefficiency, and food insecurity. An estimated one-third of all food produced globally is lost or wasted, with a substantial portion occurring at the production and post-harvest levels due to technological, logistical, and behavioral inefficiencies.This study adopts a multi-dimensional approach to explore strategies for reducing food waste across the agricultural supply chain. Methodologically, it integrates quantitative data analysis with visualizations and comparative assessments, focusing on harvesting techniques, post-harvest handling, cold chain logistics, market accessibility, and sustainable farming practices. Advanced metrics are employed to evaluate usable yield efficiency and to simulate the environmental and economic impacts of waste mitigation strategies.The results reveal that improved harvesting methods and precision agriculture significantly reduce post-harvest losses, especially in perishable commodities. Cold chain innovations and digital platforms enhance storage efficiency and align production with demand, minimizing overproduction. Additionally, the integration of biotechnology and agroecological practices increases shelf life and reduces spoilage. Visual analyses highlight regional disparities, showing that food loss is highest in regions lacking infrastructure and policy support, while hybrid strategies demonstrate up to 40% improvement in waste reduction performance.The study concludes that reducing food waste requires a systemic and coordinated response involving farmers, policymakers, consumers, and technological stakeholders. Interventions must be tailored to regional contexts, supported by strong governance, and driven by innovation and education. A shift toward sustainable, data-driven agricultural systems can significantly mitigate food loss, improve food security, and support climate goals. The findings reinforce the importance of integrating technological solutions with circular economy principles to build a resilient and equitable food system.
Copyright (c) 2024 Muhammad Arif, Syed Muhammad Ali Ramish (Author) https://creativecommons.org/licenses/by/4.0
THE ROLE OF STEM CELLS IN REGENERATIVE MEDICINE: CHALLENGES AND OPPORTUNITIES
Stem cell therapy has emerged as a transformative modality in regenerative medicine, offering the potential to repair, replace, or restore damaged tissues and organs through cellular differentiation and self-renewal. The pluripotent and multipotent nature of stem cells enables therapeutic applications across diverse domains, including cardiovascular, neurological, orthopedic, and autoimmune disorders.This research undertook a comprehensive review and meta-synthesis of peer-reviewed literature, clinical trial data, and translational studies focusing on embryonic, adult, and induced pluripotent stem cells. Methodologically, the study analyzed stem cell classification, immune compatibility, gene editing technologies, and tissue engineering outcomes through comparative modeling and graphical visualization frameworks.The results demonstrate that induced pluripotent stem cells exhibit superior compatibility, lower immunogenicity, and broader differentiation potential than other stem cell types. Clinical trial success rates have increased steadily over the past decade, particularly for therapies involving mesenchymal and iPSC-derived cells. Tumorigenicity and ethical controversies remain significant obstacles, though exosome-based and CRISPR-enhanced therapies offer promising mitigation strategies. Advances in 3D bioprinting and scaffold engineering further enhance tissue integration, while personalized autologous therapies show significant potential in reducing immune rejection.In conclusion, while ethical, regulatory, and biological challenges persist, the synergistic integration of stem cell biology with gene editing, personalized medicine, and bioengineering continues to redefine the clinical landscape. With ongoing innovation and supportive regulatory frameworks, stem cell-based therapies are poised to become central to future therapeutic paradigms, providing targeted and sustainable solutions for chronic and degenerative diseases. The findings emphasize the need for standardized methodologies and long-term safety protocols to fully realize the translational potential of regenerative medicine.
Copyright (c) 2024 Rizwan Ullah, Uzair Nisar (Author) https://creativecommons.org/licenses/by/4.0
ADVANCEMENTS IN CRISPR-CAS9 GENE EDITING: IMPLICATIONS FOR HUMAN THERAPEUTICS
CRISPR-Cas9 technology has revolutionized the field of molecular genetics by enabling precise, efficient, and cost-effective genome editing across a wide range of organisms. Originally derived from the bacterial adaptive immune system, this versatile system allows targeted manipulation of DNA sequences, opening new avenues for therapeutic applications in genetic disorders, oncology, and regenerative medicine.This study provides a comprehensive examination of advancements in CRISPR-Cas9, incorporating high-fidelity Cas9 variants, next-generation editing systems such as Cas12, Cas13, and prime editors, as well as improvements in delivery mechanisms including viral vectors, lipid nanoparticles, and electroporation. A structured methodology was employed to evaluate editing efficiency, off-target risk, and delivery performance across model organisms, tissue types, and clinical applications.Results indicate a high degree of editing accuracy with minimal off-target effects when using engineered Cas9 variants. Base and prime editing platforms demonstrated superior single-nucleotide correction potential, while lipid-based delivery systems outperformed viral methods in safety and efficiency. In therapeutic contexts, CRISPR demonstrated significant efficacy in correcting mutations in sickle cell anemia and cystic fibrosis, and in enhancing CAR-T cell function in hematologic malignancies. Safety profiles across trials showed a low incidence of severe adverse events, supporting the clinical viability of the technology.The findings underscore the transformative potential of CRISPR-Cas9 in modern medicine, while also emphasizing the need for continued attention to ethical, regulatory, and long-term safety concerns. With advancements in precision tools, delivery strategies, and interdisciplinary integration, CRISPR is poised to transition from experimental innovation to a cornerstone of personalized therapeutics.
Copyright (c) 2024 Usama Raza, Sumaiya Sundus (Author) https://creativecommons.org/licenses/by/4.0
EXPLORING THE ROLE OF ARTIFICIAL INTELLIGENCE IN AGRICULTURE
Artificial Intelligence (AI) is redefining the landscape of modern agriculture by offering innovative solutions to long-standing challenges such as low productivity, environmental stress, and inefficient resource utilization. As the global population continues to rise and arable land becomes scarcer, the integration of AI has emerged as a critical strategy to ensure food security, sustainability, and precision in agricultural practices. This study investigates the application of AI technologies in key agricultural domains including crop management, livestock monitoring, and supply chain optimization. A mixed-methods approach was employed, combining empirical data analysis, predictive modeling, and real-world case studies. The methodology involved developing AI models based on satellite imagery, sensor data, and time-series analytics to evaluate yield prediction, pest detection, and logistics planning. The results demonstrate that AI models significantly improve accuracy in crop yield forecasting, optimize irrigation and fertilization practices, and enable early detection of livestock diseases through wearable sensor data. Furthermore, AI-driven supply chain models were effective in reducing post-harvest losses and improving routing efficiency, leading to measurable gains in productivity and resource savings.The findings suggest that AI not only enhances operational efficiency but also contributes to environmental sustainability by reducing chemical input and water usage. However, the study also highlights challenges such as technological accessibility, data governance, and farmer training that must be addressed for equitable adoption. In conclusion, the integration of AI in agriculture presents transformative potential, provided it is supported by inclusive policy frameworks and capacity-building initiatives to ensure its benefits reach all stakeholders across the agricultural ecosystem.
HYBRID APPROACHES TO ZOO INFECTIOUS DISEASE SURVEILLANCE
Surveillance of infectious diseases in zoos is rather significant in the aspect of maintaining animal health, safeguarding human health, and biodiversity conservation. In this paper, the author proposes an integrative surveillance, which would employ behavioural monitoring, quantitative physiologic data and diagnostic screening on 180 of the zoo animals, including giraffes, lions, chimps and penguins. The data was presented in the form of nine elaborated tables and twelve complex figures. The findings indicated that chimpanzees and penguins were found to possess the most unusual behaviours and they could detect pathogens such as Salmonella, E. coli, and Influenza. A. Giraffes were least variable in physiological measurements whereas behaviour and temperature in lions varied a bit. Line and bar graphs were used to indicate the changes in body temperatures as well as the number of time that the species were observed and pie charts indicated the prevalence of particular infections. Findings indicated that the links between the behavioural problems and pathogen alarms were significant according to scatter plots and hybrid visualizations. This system combined a number of components to identify health threats in a proactive time and to optimize the intervention windows through monitoring of things in real-time and prioritizing the risks. Analysis reveals that hybrid surveillance is an evolutionary and expandable method of performing zoo epidemiology. It deploys the smart technologies and work processes in other sectors to bridge the linkages between animal health and ecological surveillance. This data promotes mixed surveillance methods in zoological networks to be used as a component of an expanded health effort, One Health.
Copyright (c) 2023 Aftab Ahmed1, Mukhtar Ahmad (Author) https://creativecommons.org/licenses/by/4.0
PHOTOBIOLOGY AND BIOCHEMISTRY IN LIGHT-MEDIATED CELL REGULATION
Light functions as both an energy source and a regulatory signal, shaping fundamental processes in cells across plants, microbes, and animals. This study investigated the interplay between photobiology and biochemistry in light-mediated cell regulation by employing a mixed-methods experimental framework that combined biochemical assays, spectroscopic analyses, gene expression profiling, and computational modeling. The results revealed that distinct wavelengths activate specific photoreceptors, leading to cascades of biochemical responses including redox transformations, phosphorylation events, and transcriptional regulation. Blue light was shown to modulate circadian clock genes through cryptochrome activity, red and far-red light activated phytochrome-controlled transcription factors influencing growth and development, while near-infrared light enhanced mitochondrial activity by stimulating cytochrome c oxidase, thereby increasing ATP production. Quantitative data across nine tables highlighted variations in enzyme kinetics, chromophore distribution, and reactive oxygen species generation, while twelve figures—including line plots, heatmaps, radar charts, and three-dimensional surface models—visualized the diversity of photoreceptor responses and biochemical outputs. The findings underscore that light-mediated regulation is an evolutionarily conserved mechanism that integrates photoreceptor signaling with cellular biochemistry to optimize survival and adaptation. Importantly, the results have broad translational implications: optogenetics exploits engineered light-sensitive proteins to regulate neuronal activity, photodynamic therapy leverages light-activated molecules for targeted medical treatment, and synthetic biology applications utilize light-responsive circuits to reprogram cellular functions. This research therefore demonstrates that the convergence of photobiology and biochemistry offers both mechanistic insight into cellular regulation and practical opportunities for innovation in medicine, agriculture, and biotechnology.
Copyright (c) 2023 Hammad Ur Rehman, Muhammad Waqar Ali (Author) https://creativecommons.org/licenses/by/4.0
ETHNOBOTANY AND PHARMACOGNOSY IN DRUG DISCOVERY
This paper examined the role of ethnobotanical knowledge and the pharmacognostic assessment in drug discovery of medicinal plants. The traditional healers’ interviews and field investigations revealed that there exist 45 different plant species commonly used in the indigenous medicine as a means of infections, inflammation and abnormal metabolism. The phytochemical analysis proved the presence of alkaloids, flavonoids, terpenoids, phenolic compounds, part of which had a high antibacterial and antioxidant in vitro. Identities of the compounds were confirmed by using HPLC, GC-MS and NMR techniques, and in silico pharmacokinetic studies indicated that a number of the phytoconstituents had good drug-likeness and bioavailability profiles. The in vivo tests reaffirmed even more that these bioactives can be employed as medications with some extracts capable of acting as equally effectively as conventional medicines. This ethnobotanical-pharmacognostic synthesis demonstrates the potential utility of traditional medicines that prove to be very useful in drawing new drugs and advocates the application of the potential of ethnopharmacological knowledge to synthesize new drugs in the long-term scale.
Copyright (c) 2023 Saad Abdullah, Usama Raza (Author) https://creativecommons.org/licenses/by/4.0
Developmental Genetics and Morphogenesis in Organ-on-Chip Models
The paper examines the usefulness of organ-on-chip (OoC) technologies in terms of what they can do in modeling developmental biology and morphogenesis in controlled microenvironments. Our biomimetic microfluidic system is capable of recreating significant steps during early stages of human tissue development through integration of CRISPR-guided gene tagging, manipulation of morphogen gradients in real-time and imaging. We were able to genetically modify human induced pluripotent stem cells (hiPSCs) in such a way that when in contact with a specific kind of markers, they would light up. We then applied the microfluidic chips made of PDMS to manage their differentiation in space. We obtained nine experimental situations of quantitative data. Changes in genes expression, morphogen distribution, cell growth and differentiation results were contained in this data. The findings indicated that the conditions were very different, and they differed significantly in developmental outcomes. As demonstrated in the scenario of better morphogen gradients, the resultant differentiation scores were 20-percent better and the correlation between gene expression and morphogen concentration (r > 0.8) was much more robust. Imaging combined with histological analysis revealed that morphological and molecular patterns of zonation were accurate and regional fidelity exceeded 85 percent. Scatter plots, violin plots, KDE overlays, and hybrid box-strip graphs were all similar wherein there were 12 intricate visualizations that were consistent with all experimental metrics. Particularly, paired regression diagrams and feature-wise correlations showed that genetic, chemical, and phenotypic variables could be expected to have predictable and modifiable relationships. These findings will validify that OoC platforms can be used to perform high-resolution, manipulable modeling of human development processes, thus this method is reproducible and scalable in terms of investigating morphogenetic events in vitro. This technology is integrated with microscale engineering, transcriptome profiling, and mathematical modeling to develop a versatile platform of basic research in developmental biology as well as practical applications, like modeling diseases and regenerative medicine.
Copyright (c) 2023 Abdul Waheed Shah, Ezza Fatima (Author) https://creativecommons.org/licenses/by/4.0
CROSS-SPECIES VARIATION IN ZOO ANIMAL PHARMACOLOGY
This paper examined the response of zoo animals that belong to various species to drugs by integrating pharmacokinetic modelling with behavioural tests based on multiple classes of medicinal drugs. Serious review of veterinary data assisted in the selection of the species and drugs, and it was scaled allometrically to modify the dose schedule. Blood samples in set partition were taken following controlled drug delivery and exponential functions of plasma concentration were simulated by taking exponential decay functions. Concurrently, behavioural observations were recorded in order to obtain qualitative indicators of drug effects. Quantitative analysis revealed that significant differences existed in pharmacokinetic values including, clearance rate, maximum plasma concentration, and elimination half-life, across species. Also behavioural studies indicated that various animals possessed variable forms of sedation, activity fluctuation, and alteration in the social interaction. Not all these trends could be associated with changes in pharmacokinetics. Mixed-effects model revealed that the kind of species determined a major factor in the distribution of drugs and responsiveness. This indicates the significance of a personalised dosing technique. The overall methodological approach allowed the robust comparison of species to be made, and this aspect also served to enhance veterinarian assistance to the animals in zoos. These findings illustrate the relevance of applying a species-specific pharmacological tool in zoological medication to enhance effectiveness of interventions as well as the wellbeing of animals.
Copyright (c) 2023 Imdad Ullah Khan, Syed Muhammad Ali Ramish (Author) https://creativecommons.org/licenses/by/4.0
ASSESSING THE IMPACT OF ENVIRONMENTAL POLLUTANTS ON PUBLIC HEALTH: AN EPIDEMIOLOGICAL STUDY OF URBAN POPULATIONS IN SOUTH ASIA
Environmental pollution poses one of the most significant threats to global public health, with its effects being especially severe in rapidly urbanizing regions such as South Asia. Urban centers like Delhi, Karachi, Dhaka, and Lahore are facing escalating levels of air, water, and soil contamination, which disproportionately affect socioeconomically disadvantaged populations.This study adopts an epidemiological approach to evaluate the relationship between environmental pollutants and public health outcomes across major South Asian cities. Data were collected on pollutant concentrations, disease prevalence, and socioeconomic variables, followed by stratified analysis to calculate relative risk and exposure differentials. Both quantitative data modeling and visual analytics were employed to interpret pollution-health dynamics and socio-spatial disparities.Results demonstrate strong associations between pollutant exposure and a spectrum of health conditions, including respiratory and cardiovascular diseases, neurodevelopmental impairments, and mental health issues. Low-income populations and urban slum dwellers were found to be at significantly higher risk due to their proximity to high-pollution zones and lack of access to clean resources and healthcare.The study concludes that environmental pollution is not only an ecological or infrastructural concern but a pressing public health emergency. Effective mitigation requires a multisectoral response, incorporating regulatory reforms, health system strengthening, climate-resilient infrastructure, and inclusive urban planning. Without timely intervention, pollution-related morbidity and mortality will continue to escalate, undermining regional health equity and sustainable development goals. This research provides critical insights for policymakers, urban planners, and public health officials aiming to reduce environmental health burdens and protect vulnerable populations across the South Asian region.
Copyright (c) 2023 Muska Hayat, Shahzad Rafiq (Author) https://creativecommons.org/licenses/by/4.0
THE IMPACT OF LIFESTYLE CHOICES ON PUBLIC HEALTH: AN EVIDENCE-BASED APPROACH
Non-communicable diseases (NCDs) such as cardiovascular conditions, diabetes, and obesity have emerged as leading global health threats, driven largely by modifiable lifestyle behaviors. In Pakistan, the growing burden of NCDs is exacerbated by rapid urbanization, dietary shifts, physical inactivity, and rising tobacco and alcohol consumption.This study adopts an evidence-based public health approach to investigate the impact of lifestyle choices on NCD prevalence across diverse demographic groups in Pakistan. The methodology combines descriptive statistical analysis, comparative risk assessment, and visual analytics to examine associations between behavioral factors and chronic disease outcomes.Findings reveal that high caloric intake, processed food consumption, and inadequate physical activity are strongly correlated with increased rates of obesity, hypertension, and type 2 diabetes. Smoking remains disproportionately high among males and adolescents, while alcohol-related complications—though culturally stigmatized—pose significant health risks in underregulated areas. Mental health conditions were also found to co-occur with physical inactivity and poor diet. The analysis further demonstrates that structured public health campaigns have a positive, though limited, effect in promoting behavior change.These insights underscore the urgent need for comprehensive lifestyle-focused health policies in Pakistan. The study concludes that integrating adaptive technologies such as explainable and agentic artificial intelligence (AI) can strengthen personalized risk prediction, enhance campaign efficacy, and promote long-term behavioral compliance. Targeted interventions, supported by cross-sectoral collaboration and digital health innovation, are essential for reversing the rising trend of NCDs and improving national health outcomes.
Copyright (c) 2023 Aftab Ahmed, Aftab Ahmed (Author) https://creativecommons.org/licenses/by/4.0
EXPLORING THE FUTURE OF MEDICAL DEVICES: INNOVATIONS IN HEALTHCARE TECHNOLOGY
The global healthcare landscape is rapidly evolving due to breakthroughs in medical device technology, particularly with the integration of Artificial Intelligence (AI), wearable sensors, and robotic systems. These innovations are reshaping clinical diagnostics, surgical procedures, and patient monitoring, leading to more personalized and efficient care delivery. This study explores the advancement and implementation of AI-powered diagnostic tools, wearable health monitoring devices, and robotic systems in both surgical and rehabilitative settings. The research utilizes performance metrics and predictive evaluations to compare device categories across urban and rural deployment scenarios, assessing diagnostic accuracy, usage trends, and recovery outcomes.The results reveal that AI-integrated diagnostic devices consistently outperform traditional methods in accuracy, while wearable devices enable continuous real-time monitoring that enhances patient engagement and chronic disease management. Robotic systems, particularly in surgical and rehabilitation contexts, demonstrate reduced complication rates, faster recovery times, and greater procedural precision. The study also highlights the benefits of hybrid systems that combine AI analytics with robotic functionalities, yielding superior clinical outcomes across diverse patient groups.In conclusion, the convergence of AI, robotics, and wearable technologies presents a transformative opportunity for modern healthcare systems. While challenges such as cost, regulatory compliance, and ethical considerations persist, the potential for these intelligent medical devices to revolutionize diagnosis, treatment, and patient outcomes is profound. Strategic integration and policy support will be key in ensuring equitable adoption and maximizing their global healthcare impact.
Copyright (c) 2023 Ranya Mohammed Elmagzoub (Author) https://creativecommons.org/licenses/by/4.0
ADVANCEMENTS IN GENETICALLY MODIFIED CROPS: IMPLICATIONS FOR GLOBAL FOOD SECURITY
The accelerating global population growth and the adverse effects of climate change have placed immense pressure on agricultural systems, intensifying concerns over food security, particularly in vulnerable and developing regions. In this context, Genetically Modified (GM) crops have emerged as a transformative innovation, offering improved resistance to pests and environmental stressors, enhanced nutritional content, and significantly increased crop yields.This study comprehensively examines the scientific advancements in GM crop technology, emphasizing gene editing, trait selection, and regulatory evaluations. A multi-trait analytical framework was adopted to assess comparative yield performance, pest resistance, and water-use efficiency between GM and conventional crops across 20 crop varieties.The results indicate that GM crops consistently outperformed their non-GM counterparts, demonstrating higher productivity, improved resistance to pests, and superior adaptability to drought and salinity conditions. Furthermore, GM crops exhibited more efficient input utilization, lower pesticide dependence, and enhanced nutritional benefits, particularly in biofortified varieties like Golden Rice.Despite these advantages, challenges remain. Socio-economic inequalities, limited accessibility for smallholder farmers, and concerns over ecological impacts such as biodiversity loss and gene flow necessitate robust and transparent regulatory oversight. Intellectual property rights and seed-saving restrictions further complicate equitable adoption in low-income regions.This research concludes that while GM crops are not without controversy, their scientifically validated benefits position them as a critical component of future global food strategies. However, their implementation must be guided by inclusive policy frameworks, public engagement, and equitable technology transfer mechanisms. A balanced, evidence-based approach is essential to ensure that GM technologies contribute to sustainable agriculture and global food security in a safe, ethical, and socially just manner.
Copyright (c) 2023 Abdul Ghaffar (Author) https://creativecommons.org/licenses/by/4.0
THE ROLE OF WOMEN IN AGRICULTURAL DEVELOPMENT
The agricultural sector serves as a foundational pillar of many developing economies, with women playing a critical yet often underrecognized role in food production, resource stewardship, and rural livelihood sustainability. Despite accounting for a significant proportion of the agricultural workforce, women frequently face structural barriers such as unequal land rights, restricted access to credit and training, and exclusion from decision-making processes.This study employed a mixed-method approach combining regional data analysis, productivity assessments, and empowerment metrics to evaluate the contribution and constraints of women in agricultural development. The methodology integrated comparative labor force data, land access surveys, yield evaluations, and participation in empowerment programs to generate a comprehensive profile of gender disparities and progress indicators.Results demonstrate that women contribute up to 70% of the agricultural labor force in some regions yet consistently face a 20–30% productivity gap compared to male counterparts, primarily due to lack of access to inputs, training, and markets. Empowerment interventions—such as cooperative participation, microfinance access, and agricultural training—were associated with measurable increases in yield, income, and participation in market-oriented activities. Regional variations revealed that Sub-Saharan Africa and South Asia experience both the highest labor reliance on women and the most acute gender disparities in land and financial resource distribution.The findings underscore the need for policy frameworks that explicitly address gender inequities in agriculture through legal reforms, inclusive training programs, and financial inclusion strategies. Empowering women not only enhances individual productivity but also promotes household food security, rural development, and broader economic resilience. The study concludes that recognizing and integrating women’s contributions is essential to achieving sustainable agricultural growth and global food security.
Copyright (c) 2023 Muneeba, Ayesha Irum (Author) https://creativecommons.org/licenses/by/4.0