International Journal of Scientific Discoveries
The International Journal of Scientific Discoveries (IJSD) is a peer-reviewed academic journal dedicated to publishing high-quality research across a wide range of scientific disciplines. The journal aims to provide a platform for groundbreaking discoveries, innovative methodologies, and advancements in various fields including but not limited to natural sciences, engineering, technology, health sciences, and environmental studies. It seeks to foster interdisciplinary collaboration and share novel insights that contribute to scientific progress and societal development. IJSD publishes original research articles, reviews, case studies, and short communications that showcase cutting-edge work and offer a forum for scientific dialogue and discovery.
ELITE PATH EDUCATIONAL ACADEMY (SMC-PRIVATE) LIMITED
ADVANCEMENTS IN QUANTUM COMPUTING: IMPLICATIONS FOR CRYPTOGRAPHY AND DATA PROTECTION IN FINANCIAL TRANSACTIONS
Quantum computing represents a paradigm shift that poses a profound threat to contemporary financial cryptographic systems. This study investigates the implications of quantum computing on classical encryption mechanisms and evaluates the effectiveness of post-quantum cryptographic solutions for securing financial transactions. Using a mixed-methods experimental approach, the study quantitatively analyzes the vulnerability of widely used cryptographic algorithms, including RSA, elliptic curve cryptography, and AES, under quantum attack models based on Shor’s and Grover’s algorithms. The results demonstrate a drastic reduction in security for asymmetric cryptographic schemes and a significant degradation in symmetric key strength, effectively halving their security margins. Qualitative risk analysis further reveals heightened exposure of financial systems to long-term data breaches, transaction manipulation, and regulatory non-compliance, particularly under “harvest-now, decrypt-later” scenarios. Post-quantum cryptographic schemes, including lattice-based and hash-based methods, are shown to provide robust resistance to quantum attacks while introducing manageable computational overhead. The findings highlight the importance of crypto-agility, hybrid cryptographic deployment, and early migration strategies to mitigate quantum-induced risks. This study concludes that the proactive adoption of quantum-safe cryptography is essential to preserving financial security, operational resilience, and trust in the emerging quantum era.
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0
ASSESSING THE IMPACT OF ZOONOTIC DISEASES ON PUBLIC HEALTH: A CASE STUDY OF EMERGING PATHOGENS IN WILDLIFE AND LIVESTOCK
Zoonotic diseases continue to pose a critical and escalating threat to global public health, driven by intensified interactions among wildlife, livestock, humans, and the environment. This study assessed the public health impact of emerging zoonotic pathogens using an integrated mixed-methods approach that combined epidemiological surveillance, quantitative modeling, and visual analytics across wildlife–livestock–human interfaces. The results revealed substantial regional variability in pathogen prevalence, with wildlife populations acting as primary reservoirs and livestock serving as amplification hosts that significantly increased human infection risk. Human incidence rates demonstrated a strong positive association with livestock prevalence, while mortality outcomes were disproportionately higher in regions with limited healthcare infrastructure and surveillance capacity. Seasonal analyses identified pronounced transmission peaks linked to environmental conditions, and occupational assessments confirmed elevated exposure risks among farmers, abattoir workers, and wildlife handlers. Antimicrobial resistance patterns further underscored the role of intensive farming and antibiotic misuse in exacerbating zoonotic threats. Economic evaluations highlighted considerable healthcare and productivity losses, emphasizing the broader socioeconomic burden of zoonotic outbreaks. Integrated risk indices and surveillance performance metrics demonstrated that regions implementing One Health-based monitoring systems exhibited improved outbreak detection and reduced disease impact. Overall, the findings underscore the necessity of adopting a unified One Health framework that integrates human, animal, and environmental health disciplines to strengthen surveillance, mitigate spillover risks, and enhance global preparedness against emerging zoonotic diseases.
EXPLORING THE ROLE OF TELEMEDICINE IN ENHANCING ACCESS TO VETERINARY SERVICES FOR RURAL AND UNDERSERVED COMMUNITIES
Telemedicine has emerged as a transformative approach in veterinary medicine, offering innovative solutions to long-standing challenges in accessing animal healthcare in rural and underserved communities. This study investigated the role of telemedicine in enhancing accessibility, efficiency, affordability, and quality of veterinary services through a mixed-methods experimental design. Quantitative results demonstrated a significant increase in veterinary consultation frequency, substantial reductions in response time, improved treatment compliance, and high levels of client satisfaction following telemedicine implementation. Economic analyses revealed notable cost savings for animal owners due to reduced travel and associated indirect expenses, while workload assessments indicated more efficient utilization of veterinary professional time. Qualitative findings further supported these outcomes, highlighting positive stakeholder perceptions regarding convenience, continuity of care, and expanded geographic reach. However, the results also identified persistent challenges, including regulatory ambiguity, digital literacy gaps, and concerns regarding diagnostic limitations in remote consultations. Overall, the findings confirm that telemedicine can effectively bridge critical gaps in veterinary service delivery when supported by appropriate technological infrastructure, training, and policy frameworks. This study contributes empirical evidence to the growing body of literature on veterinary telemedicine and underscores its potential as a sustainable strategy for improving animal health and welfare in resource-limited settings.
THE ROLE OF BIOENGINEERING IN DEVELOPING DROUGHT-RESISTANT AND DISEASE-RESISTANT CROP VARIETIES FOR SUSTAINABLE FOOD PRODUCTION
The increasing frequency and intensity of climate-induced biotic and abiotic stresses pose a significant threat to global agricultural productivity and food security. This study investigated the effectiveness of integrated biotechnological approaches in developing disease- and drought-resistant crop varieties using a mixed-method experimental framework. Genome editing, multi-omics profiling, and physiological evaluations were combined to assess stress resilience at molecular, biochemical, and agronomic levels. The results revealed that bioengineered crop lines exhibited significant upregulation of stress-responsive genes, enhanced antioxidant enzyme activities, and improved metabolic stability under drought and pathogen stress compared with conventional varieties. These molecular advantages translated into higher water-use efficiency, reduced disease severity, and sustained yield performance across increasing stress intensities. Graphical and statistical analyses further confirmed strong genotype–phenotype associations and coordinated stress-adaptive responses. Field-relevant evaluations demonstrated that engineered crops maintained superior growth, biomass allocation, and recovery capacity following stress exposure. Overall, the findings highlight the potential of advanced biotechnology to precisely manipulate key regulatory pathways governing stress tolerance, thereby enabling the development of climate-resilient crops. This study provides compelling evidence that biotechnological crop improvement is a viable and sustainable solution for enhancing agricultural productivity and resilience under changing environmental conditions.
GEOTECHNICAL ENGINEERING APPLICATIONS IN SAFE AND SUSTAINABLE INFRASTRUCTURE DEVELOPMENT FOR EARTHQUAKE-PRONE REGIONS
The severe threat to the security and sustainability of infrastructure in places with high seismic activity and complex underlying processes is earthquake. This study will look at the role of geotechnical engineering in development of safe and sustainable infrastructure that can withstand seismic hazards. The results show that the comprehensive site characterisation of geotechnical sites, with the advanced soil and foundation studies, significantly improves the prediction and mitigation of the ground failures caused by earthquakes. The findings indicate that the method of stabilising soils, seismic resistant foundation systems, and performance based geotechnical design methods are effective in stabilising structures and making them less susceptible and more robust. In addition, sustainable geotechnical principles allow minimizing the effect on the environment and maintaining high safety standards. This research concludes that geotechnical engineering is required to construct the infrastructure which can resist the earthquakes and survive a long period. It offers feasible solutions that are balanced in terms of safety, durability and sustainability in places that may experience earthquakes.
Application of Drone-Based Remote Sensing and Machine Learning for Real-Time Herd Health Surveillance and Behavioral Abnormality Detection
The integration of drone-based remote sensing with artificial intelligence presents a novel paradigm in real-time livestock health monitoring. This study employed a mixed-method experimental design incorporating both qualitative stakeholder input and quantitative data acquisition using UAVs equipped with multispectral, hyperspectral, and thermal sensors. Over 180 animals were monitored across nine batches, producing 9 detailed tables and 12 complex figures that revealed significant physiological and behavioral patterns. Machine learning models, including convolutional neural networks (CNNs) and support vector machines (SVMs), were trained to detect anomalies using features such as body temperature and motion deviation scores. Results showed that animals with temperatures exceeding 39.2°C and motion deviation scores above 6.5 were consistently identified as high-risk, achieving an anomaly detection accuracy exceeding 90%. Visualizations validated the system’s ability to differentiate between healthy and unhealthy animals in a non-invasive, automated manner. Additionally, a real-time feedback dashboard provided actionable insights to farmers and veterinarians, enabling early intervention and informed decision-making. The proposed system demonstrates strong potential for improving animal welfare, reducing economic losses, and supporting sustainable livestock management practices. This research underscores the viability of smart farming technologies and lays the foundation for future scalable applications in precision animal agriculture.
Quantitative Trait Loci (QTL) Mapping and Genomic Selection for Mastitis Resistance in Holstein-Friesian Cattle Using Whole-Genome Sequencing
Mastitis, a pervasive and economically significant disease in dairy cattle, demands an integrated diagnostic and preventative strategy due to its complex etiology involving host genetics, immune response, and microbial factors. This study employed a multi-omics and computational framework to elucidate the genomic, immunological, and microbial determinants of mastitis resistance in Holstein-Friesian cows. Through whole-genome sequencing and QTL mapping, we identified several SNPs associated with mastitis resilience. Simultaneously, cytokine profiling revealed elevated IL-1β and TNF-α levels in infected cattle, which were statistically correlated with somatic cell count (SCC) and pathogen burden. Microbiome analysis via 16S rRNA sequencing indicated reduced microbial diversity and increased prevalence of Staphylococcus aureus and E. coli in mastitis-affected milk samples. Nine detailed tables demonstrated these trends across various animal groups, and twelve figures, including hybrid plots, bar graphs, and scatter charts, visualized the intricate relationships among host immunity, microbial community structure, and genomic variations. Machine learning models—especially ensemble classifiers—exhibited strong predictive performance (accuracy > 90%) for mastitis risk assessment using integrated features. Explainable AI techniques validated model transparency and feature importance. These results underscore the utility of genomics-driven precision breeding and computational diagnostics in controlling mastitis. The study provides a scalable, reproducible methodology for enhancing mastitis resistance, contributing to improved dairy herd productivity and sustainability.
Mapping Immunosenescence Trajectories in Aging Adults Using Integrated Cytomics, Methylation Clocks, and AI-Powered Disease Risk Forecasting
Immunosenescence and inflammaging represent fundamental biological processes driving the onset of age-related diseases. This study employed a mixed-methods experimental design integrating immunological profiling, transcriptomic analysis, and qualitative clinician insights to characterize the progression of immune aging and chronic inflammation across stratified age cohorts. Quantitative data revealed a consistent decline in naïve T cells, expansion of senescent immune cells, elevated levels of inflammatory cytokines (IL-6, TNF-α), and increased mitochondrial dysfunction. Epigenetic assays indicated accelerated biological aging, with strong associations between senescence indices and disease phenotypes including neurodegeneration, cardiovascular pathology, and osteoarthritis. Regression modeling confirmed that cytokine levels and senescence scores are predictive of age-related disease risk. The results were supported by 9 comprehensive tables and 12 complex visualizations—including line, bar, scatter, pie, and hybrid plots—demonstrating age-related immune and inflammatory shifts. A detailed diagram illustrated the central role of the senescence-associated secretory phenotype (SASP) in mediating chronic inflammation and systemic dysfunction. This integrative analysis substantiates the mechanistic link between immunosenescence and age-associated morbidities and highlights potential targets for therapeutic intervention. The findings underscore the need for immunological rejuvenation strategies in geriatric medicine and provide a foundational framework for future translational research in healthy aging.
AI-Driven Pest Detection Systems: Integrating Zoological Knowledge and Agricultural Engineering
Artificial intelligence has created new opportunities to deal with the pests in the farming area accurately, and the majority of the detection system does not consider the environment. This research is a demonstration of an integrated pest detection software supported by AI that incorporates knowledge in zoology and agricultural engineering in order to make it more precise and less to understand. The UAVs captured high-resolution images of crops infected with pests, and the entomologists assigned labels to them creating some powerful dataset with more than 50 species. The idea was to test and train a ResNet50 convolutional neural network (CNN) 5-fold cross-validation. It consisted of a semantic layer of attention which linked morphological characteristics to entomological expertise. The model presented an accuracy of classification of 94.3 percent and an AUC of 0.97. The outputs were quite comprehensible and revealed characteristics which were exclusive to pests. Real-time field deployment of ground vehicles enabled by edge computing demonstrated that the system performed well in the real world scenario, in terms of its capabilities to identify things. Comments left by zoologists helped us to enhance the attention mechanisms and fill the model with whatsoever blind spots. The technology also worked in most environmental conditions, though very good at separating similar-looking pests. The multidisciplinary approach indicates how a combination of a deep learning algorithm with the specificity of biological intelligence will result in a pest detection solution capable of next-generation smart farming which can be deployed in field, scale, and explainable.
Tracking Climate-Induced Shifts in Pollinator Behavior and Their Impacts on Crop Yields
The effects of climate change are transforming the behaviours of the pollinators, and this has a domino effect on the amount of the crops that are produced globally. This study aimed at adopting a mixed-methods approach within the three distinct agro-climatic zones in tracking the shift in pollinators behavior due to the effects of climate change and quantifying the impact of these changes on crops. The experimental arrangement was the monitoring of the weather (temperature, humidity, and speed of the wind), monitoring of the digital pollinators with the use of the camera systems utilizing YOLOv5, the pollination exclusion plot and the thorough crop yield analysis in Brassica napus. The analysis revealed that during the hot weather and high winds, the frequency of the visit of pollinators experienced significant reductions and that the pollinators searched differently when it came to getting food during their peak flowering time. The count of pollinators turned out to be the significant (and positive) predictor of crop yield in regression analysis (β 1 = 0.63, p < 0.001). SEM showed an indirect impact (composition of change in pollinator behavior) of climate change on yields. Removing pollinators by excluding them in plots even reduced yields by 35 per cent when compared to the open-pollinated plots. This indicates the necessity of pollinators in helping maintain a stable food production in the face of altered environments. Additionally, the qualitative observation indicated the type of species that shifted away to specialist pollinators in territories where there is warmer weather since they could better handle the heat than generalists. These findings demonstrate the instability of pollination systems and reiterate the importance of introducing pollinator-friendly practices into climate-resilient planning of agricultural activities as soon as possible. This paper contributes much more to the ties between behavioral ecology and food security during the period of climate change.
Voice Disorders in Professional Voice Users: Identifying Early Signs and Occupational Risk Factors
This study evaluated early vocal changes and occupational risk factors in 150 professional voice users (50 teachers, 40 call-centre operators, 30 singers, 30 actors) using mixed quantitative and qualitative methods. Acoustic measures revealed that call-centre operators exhibited the highest mean jitter (1.2 ± 0.3 %) and shimmer (5.8 ± 1.2 %) and the lowest harmonic-to-noise ratio (HNR; 16.5 ± 3.1 dB), whereas singers showed the most favorable vocal profiles (jitter = 0.6 ± 0.1 %; shimmer = 3.9 ± 0.8 %; HNR = 20.3 ± 1.9 dB). Occupational exposure metrics peaked in call-centre operators (mean daily voice use = 7.2 ± 1.0 hours; background noise = 75 ± 6 dB) and were lowest among singers (5.8 ± 1.5 hours; 60 ± 4 dB). Hydration adherence ranged from 50 % (call-centre) to 80 % (singers), and regular rest‐break compliance varied from 35 % to 70 %. Pearson correlations linked increased shimmer with noise level (r = .53, p < .01) and elevated jitter with voice-use duration (r = .42, p < .05), while HNR inversely correlated with jitter (r = –.58, p < .01). A hierarchical regression model (R² = 0.45, F(7,142) = 16.5, p < .001) identified excessive phonatory load, dehydration, and insufficient rest as significant predictors of subclinical dysphonia, which affected 55 % of call-centre operators, 40 % of teachers, 35 % of actors, and 30 % of singers. Qualitative interviews underscored delayed symptom reporting due to normalization of vocal fatigue. These findings support implementing routine acoustic monitoring and targeted preventive strategies (voice rest scheduling, hydration protocols, environmental controls) to detect and mitigate early voice disorders in high-risk occupational groups.
A Controlled-Release Nano-Fertilizer System for Improving Phosphorus Uptake and Root Development in Paddy Soils
The effective management of phosphorus—a critical but often limited nutrient in paddy cultivation—is essential for sustainable rice production. This study aimed to develop and evaluate a controlled-release nano-fertilizer system using nano-hydroxyapatite encapsulated with nanochitin to enhance phosphorus uptake and root development in paddy soils. A randomized complete block design (RCBD) field experiment was conducted with three treatments: T1 (conventional phosphorus fertilizer), T2 (bulk hydroxyapatite), and T3 (nano-hydroxyapatite with nanochitin). The results demonstrated that T3 significantly improved soil phosphorus availability, microbial biomass phosphorus, and phosphorus uptake in shoot and root tissues. T3-treated plants exhibited superior root morphological traits, including increased root length and surface area, along with enhanced phosphorus use efficiency (PUE), which peaked at 74% compared to 42% and 56% in T1 and T2, respectively. Biomass yield and plant vigor were at their highest when plants were treated with nano-fertilizers, seen through their sun-seeking posture, more extended leaves and better overall color from chlorophyll. Because phosphorus was released steadily from the nano-formulation, plants used it as needed, little was lost and the environment benefited. The application of nanochitin promoted good activity of beneficial microorganisms in the rhizosphere and contributed to soil nutrition and health. All these findings suggest that controlled-release nano-fertilizers hold great potential to improve rice farming, increase what crops gain from fertilizers and keep the system sustainable. These results make it easier for farmers to try nanotechnology methods specific to their land and farming needs.
Exploring the Role of Bioactive Phytochemicals in Cancer Cell Apoptosis and Cell Cycle Arrest Mechanisms
This study investigates the mechanistic role of selected bioactive phytochemicals—curcumin, quercetin, and resveratrol—in inducing apoptosis and cell cycle arrest in human cancer cell lines, with the objective of identifying effective, low-toxicity alternatives to conventional chemotherapeutics. Using MCF-7 (breast), HCT-116 (colon), and PC-3 (prostate) cancer cells, we conducted a series of in vitro assays to assess cytotoxicity, apoptotic activity, cell cycle distribution, reactive oxygen species (ROS) generation, mitochondrial membrane potential disruption, and changes in regulatory protein expression. IC₅₀ determination revealed that curcumin exhibited the highest cytotoxic potency across all tested cell lines. Flow cytometry confirmed significant induction of early and late apoptosis, particularly in curcumin-treated groups, with HCT-116 cells showing the greatest apoptotic shift. Cell cycle analysis indicated a pronounced arrest at the G0/G1 phase, especially in MCF-7 and HCT-116 cells. Western blotting demonstrated upregulation of caspase-3 and Bax, along with downregulation of Bcl-2 and Cyclin D1, accompanied by increased p21 expression, indicating dual pro-apoptotic and anti-proliferative actions. Quantitative PCR validated these protein expression trends at the transcript level. Furthermore, DCFH-DA and JC-1 assays revealed significant ROS accumulation and mitochondrial membrane depolarization, confirming mitochondrial pathway involvement in apoptosis. Notably, curcumin led to the highest ROS generation (185%) and Δψm loss (71%) among the compounds. These findings substantiate the potential of plant-derived phytochemicals as multi-targeted agents capable of selectively inducing cancer cell death while halting proliferation. This research not only enhances mechanistic understanding of phytochemical action but also provides foundational data for advancing these compounds toward clinical translation as complementary cancer therapies.
Copyright (c) 2024 International Journal of Scientific Discoveries
Zoonotic Potential of Salmonella spp. in Raw Milk Distribution Chains in Informal Markets
The study was a cross-sectional assessment of the zoonotic potential of Salmonella spp. in the raw milk distribution channels in informal market places. We collected a total of 250 samples; 200 raw milk samples and 50 ambient swabs at dairy farms, transport system and vendor stands. Twenty-four percent of milk samples and 30 percent of ambient samples were positive to Salmonella spp. The most prevalent serovars were S. Enteritidis (41.3%) and S. Typhimurium (33.3%) based on molecular identification. Antimicrobial susceptibility test revealed that, 68.4% of the isolates were resistant to ampicillin, 60.5 percent were resistant to tetracycline, and 55.3 percent were resistant to streptomycin. Also, the isolates were categorized with 39.5 percent being multidrug-resistant (MDR). Logistic regression revealed that poor udder cleaned (OR=3.75), unclean equipment (OR=4.20), lack of cold storage (OR=2.93) and transportation delay (OR=2.15) were significantly risk factors of infections (p<0.05). Vendor tests revealed that 72 percent of them failed to meet reasonable hygiene standards and 85 percent of the consumers interviewed never boiled raw milk prior to consuming it. The rate of contamination was directly correlated to increased ambient temperatures and extended storage time. These results support the high zoonotic potential of Salmonella in uncontrolled raw milk markets and highlight the need of improved hygiene control, official oversight, and consumer awareness to mitigate the health risks to the population caused by the use of raw milk in the informal sector.
Study of Mineral and Metabolic Profiles in Cattle Affected by Post-Parturient Hemoglobinuria
One of the key metabolic disorders in dairy cows, particularly within the first weeks after calving, is post-parturient hemoglobinuria (PPH). It causes severe implications on both the animal welfare and farm economics. They compared the hematological, mineral, metabolic, hepatic, and oxidative parameters of cows with PPH (n=30) to healthy controls (n=30). Hematological analysis showed that the anemia was severe in PPH cows, with lower red blood cell count (5.34 +/- 0.57 x 10 6 /mL), hemoglobin (7.2 +/- 1.1 g/dl), and hematocrit (21.5 +/- 3.4%) compared with controls (p < 0.001). Serum mineral analysis revealed very low phosphorus concentrations (3.1 +/ - 0.5 mg/dL) and reduced concentrations of copper, selenium, iron, and zinc (p < 0.001). Metabolic assessments showed a positive state of non-esterified fatty acids (0.74 +/- 0.09 mmol/L) and B-hydroxybutyrate (1.8 +/- 0.3 mmol/L), which indicated a negative energy balance, and a significant decrease in the level of glucose. Liver function tests indicated that the levels of AST, ALT, and GGT increased significantly (p < 0.001), and this fact indicates that the liver worked under significant stress. The analysis of oxidative stress revealed that there was high malondialdehyde (3.9 +/- 0.6 nmoI/mL) and low total antioxidant capacity (0.8 +/- 0.2 mmol/L). This is an indication that oxidative damage was extensive. There was a correlation study conducted that revealed a high negative correlation between phosphorus and oxidative stress indicators (r = -0.72, p < 0.001). Phosphorus, copper, selenium, and malondialdehyde were identified as important predictors of the risk of PPH by logistic regression. The above findings highlight the multifaceted nature of PPH pathophysiology, emphasizing the role of mineral deficiencies, metabolic disturbance, and oxidative stress. Positive nutrition intervention to correct such imbalances at the early stages and monitor their progress could serve as preventive and curative mechanisms of PPH in dairy cattle.
Evaluating the Role of Traditional Knowledge in Biodiverse Farming for Enhancing Agroecosystem Resilience
This study evaluates the contribution of traditional knowledge to agroecosystem resilience within biodiverse farming systems. Drawing on mixed-method research that included field surveys, stakeholder interviews, and ecological assessments across multiple regions, the investigation aimed to identify how indigenous practices contribute to farming sustainability under environmental stress. The results reveal that traditional practices such as intercropping, use of native seeds, organic amendments, and water harvesting significantly contribute to ecological balance, soil health, and yield stability. In regions exposed to climate fluctuations and pest pressures, farms managed with traditional methods displayed greater biodiversity and more consistent productivity compared to conventional monoculture systems. Community-based knowledge-sharing practices were also instrumental in fostering collective adaptation. These outcomes highlight the value of traditional knowledge as a living, adaptive system that enhances ecological resilience while maintaining cultural integrity. The study recommends integrating such knowledge into mainstream agricultural policy and climate adaptation planning, positioning traditional farmers as co-creators of sustainable solutions.
Copyright (c) 2025 International Journal of Scientific Discoveries
The Role of Endothelial Dysfunction in Deep Vein Thrombosis: A Multi-Center Study
Deep vein thrombosis (DVT) is a multifactorial condition with significant morbidity and mortality, often resulting from a complex interplay between hemodynamic changes, coagulation abnormalities, and endothelial dysfunction. While the contributions of stasis and hypercoagulability are well established, the role of endothelial dysfunction in DVT pathogenesis remains underexplored. This multi-center study aimed to investigate the mechanistic contribution of endothelial dysfunction to DVT through comprehensive biomarker analysis and vascular assessment. A total of 412 patients with ultrasound-confirmed DVT and 200 age- and sex-matched controls were enrolled. Biomarkers of endothelial injury (circulating endothelial cells, endothelial microparticles), vasodilation (nitric oxide), inflammation (VCAM-1, IL-6, TNF-α, CRP), oxidative stress (MDA, SOD), and senescence (β-galactosidase activity, p16INK4a) were evaluated. Both non-invasive imaging and statistical analysis were used to discover what predicts DVT. Patients with DVT had much greater levels of endothelial cells, microparticles, VCAM-1 and pro-inflammatory cytokines (IL-6, TNF-α and CRP) than the controls (p < 0.001). There was clear oxidative stress since MDA levels in the DVT group were higher than in the non-DVT group. An increase in senescence markers implies that vascular aging may play a new role in triggering thrombus development. Flow-mediated dilation and the tone of the arteries were significantly lower in people with DVT, as found by functional assessments. Analysis of several factors showed that VCAM-1, IL-6, MDA and p16INK4a are powerful factors linked to DVT (p < 0.001). It is clear from these findings that dysfunction of the vascular endothelium, caused by inflammation, free radicals and aging, has a key role in developing DVT. Recognizing these biomarkers may lead to better therapies and better ways to assess disease risk in patients.
Assessment of Nutritional Deficiencies and Trace Mineral Imbalances in Calves Raised in Marginal Pastoral Regions
This study investigates the prevalence and impact of nutritional deficiencies and trace mineral imbalances in calves raised under extensive pastoral systems in marginal regions. A total of 80 pre-weaned calves from 12 smallholder farms were clinically evaluated, with blood, forage, soil, and fecal samples analyzed to determine micronutrient status, pathogen prevalence, and associated health outcomes. Biochemical analysis revealed widespread deficiencies in key trace minerals—zinc (72.4%), selenium (81.0%), copper (68.3%), and phosphorus (65.1%)—as well as fat-soluble vitamins A (69.8%) and E (83.5%). Such deficiencies were closely associated with clinical signs like rough hair coats, retarded growth, lameness and recurring diarrhea. Forage and soil samples in grazing areas proved to be deficient in vital minerals, a fact that confirms the notion that the environment is the cause of the imbalances. There was strong positive correlation of serum zinc, copper and selenium concentrations with average daily weight increase, highlighting the developmental importance of these nutrients. Trace mineral deficiencies in calves also showed gastrointestinal infections, particularly Escherichia coli (43.1%) and Cryptosporidium (34.7%), demonstrating immunosuppressive effects of trace minerals deficiencies. Such management interventions as the supplementing of minerals in the diet and the feeding of colostrum early were related to much lower rates of deficiency and disease. These findings demonstrate that selective mineral supplement and pasture improvement are urgently needed in the not very productive areas. Specific solutions to enhance the nutrition of calves during the first phases of life can significantly increase health, growth, and the productivity of the herd in the long term. It is a viable means of livestock producers in resource-constrained regions to progress sustainably.
Patterns of Sexual Dimorphism in Avian Species Along Altitudinal Gradients
Sexual dimorphism in avian species represents a key axis of evolutionary differentiation, yet its modulation by environmental gradients remains inadequately quantified. This study investigates patterns of sexual dimorphism across altitudinal gradients in 10 bird species inhabiting the Western Himalayas, integrating morphometric, ecological, and behavioral data. We conducted extensive field observations, biometric measurements, and vocal analyses across low (0–800 m), mid (801–2000 m), and high (>2000 m) elevation zones. Morphological traits—specifically wing length, body mass, and beak size—were compared between sexes using Sexual Dimorphism Indices (SDIs), ANOVA, and generalized linear models (GLMs) incorporating environmental predictors. Results demonstrated a consistent increase in dimorphism with elevation, with high-altitude populations exhibiting significantly larger trait disparities between males and females. SDI values were positively correlated with vegetation density and canopy cover, and negatively with ambient temperature. ANOVA confirmed significant altitudinal differences in wing length (F = 8.74, p = 0.021) and body mass (F = 6.95, p = 0.027). Figure-based visualizations reinforced these findings: bar plots and scatter plots highlighted male-biased dimorphism, while line plots traced trait divergence along altitudes. Notably, behavioral evidence suggested habitat partitioning by sex in some species, aligning with ecological niche specialization. These findings support the hypothesis that environmental harshness and resource structure intensify sexual trait differentiation. The study highlights elevation as a powerful ecological filter shaping the expression of dimorphic traits, with significant implications for species adaptation and conservation under climate change. This work advances our understanding of how spatial ecological heterogeneity influences evolutionary outcomes in avian sexual dimorphism.
Postmortem Histopathological Profiling of Emerging Viral Hepatitis Syndromes in Backyard Poultry
This study presents a comprehensive postmortem histopathological and molecular investigation of emerging viral hepatitis syndromes in backyard poultry, aiming to elucidate the etiology, lesion patterns, and viral associations in low-biosecurity smallholder systems.A complete necropsy, histological examination, and PCR-based detection of viruses were carried out on 60 birds (40 chickens and 20 ducks) with clinical signs of liver failure. According to gross pathological observations, the high frequency of pale liver (83.3%), hepatomegaly (66.7%), and necrotic foci (63.3%) were determined, with gross changes being more expressed in chickens than in ducks. Histopathological profiling showed that there was massive hepatic necrosis, lymphocytic infiltration, bile duct proliferation, fibrosis and formation of inclusion bodies with the highest severity rating belonging to necrosis and inclusion bodies. PCR tests detected the avian influenza virus (H 5 N 1 ) in 36.7 percent of cases, the fowl adenovirus in 30 percent of cases and the Newcastle disease virus in 20 percent of cases. In some instances, they had infections that were identical in both groups. Lesion severity index was highly associated with the virus type, birds infected with H 5 N 1 showed maximum lesion severity index ( 2.8 ), and adenoviruses infections were significantly associated with the development of inclusion bodies. Anatomical mapping of lesions revealed that lesions were more in the right and cranial lobes of the liver than in the other lobes. The gross lesions were considerably confirmed histologically and over 90 percent of pale livers were microscopically confirmed. It was easier to diagnose using special stains such as Masson Trichrome and PAS which helped fibrotic bands and viral inclusions to stand out. The findings of the study demonstrate the diagnostic usefulness of histopathology and special stains in differentiation of etiologies of viral hepatitis, particularly where resources are limited in backyard poultry. The research highlights the urgent need of enhanced surveillance, molecular diagnosis and biosecurity to handle the emerging viral hepatitis concerns in small-scale poultry systems and to minimize the associated zoonotic risks.
Public Health Strategies for Preventing Non-Communicable Diseases
Non-communicable diseases (NCDs), including cardiovascular conditions, diabetes, chronic respiratory diseases, and cancers, are now the leading cause of death globally, with low- and middle-income countries like Pakistan bearing a disproportionate burden. Despite their preventable nature, NCDs continue to rise in prevalence due to rapid urbanization, sedentary lifestyles, poor dietary habits, tobacco use, and limited healthcare access.This study adopts a comprehensive, data-driven approach to assess the effectiveness of public health strategies aimed at preventing and managing NCDs in Pakistan. The methodology involves regional analysis of behavioral risk factors, healthcare accessibility, and policy implementation, supported by visualizations and comparative tables. A combination of quantitative data, policy review, and visual analytics was used to identify trends and evaluate outcomes across diverse population groups.The results reveal that regions with stronger health policies, mobile health interventions, and awareness campaigns report significant improvements in early diagnosis and reductions in behavioral risk factors. Urban areas, while having better healthcare infrastructure, exhibit higher prevalence of lifestyle-related NCDs, whereas rural areas face challenges due to limited access and education. Mobile health tools and school-based programs demonstrate high potential in bridging these gaps.The findings underscore the importance of a multi-tiered strategy combining behavioral interventions, structural reforms, community engagement, and digital health innovations. This study recommends strengthening intersectoral collaboration, scaling up community-based education, and investing in digital platforms for preventive care. By aligning national efforts with global best practices, Pakistan can move toward achieving sustainable health outcomes and mitigating its growing NCD burden.
From Lab to Clinic: The Journey of Stem Cell Therapies in Treating Neurological Disorders
Neurological disorders such as Parkinson’s disease, Alzheimer’s, and spinal cord injury present profound therapeutic challenges due to their complex pathophysiology and limited regenerative capacity. Stem cell therapies have emerged as promising interventions capable of neural repair and functional restoration, revolutionizing the treatment landscape for neurodegenerative diseases.This study systematically explores the translational pipeline of stem cell therapies, beginning with the selection and differentiation of pluripotent and multipotent stem cells, progressing through preclinical animal models, and culminating in phased human clinical trials. Quantitative metrics including patient response scores, survival rates, and adverse event profiles were analyzed to evaluate therapeutic efficacy and safety.The results demonstrate significant improvements in functional outcomes among patients treated with iPSC- and MSC-derived interventions, with notably high survival rates and minimal severe side effects. Efficacy varied across cell types and clinical centers, with patient-specific applications yielding the most favorable results. Additionally, early-phase clinical trials revealed a strong correlation between early intervention and increased neurological recovery.This research underscores the clinical viability of stem cell therapies while acknowledging existing challenges such as immunogenicity, delivery mechanisms, and ethical concerns. The integration of nanotechnology and scaffold-based delivery is highlighted as a potential solution to improve site-specific targeting and cell survival. Moreover, ethical frameworks and global standardization are imperative for ensuring responsible deployment of these advanced therapies.In conclusion, stem cell-based interventions offer a transformative avenue for neurological treatment, demonstrating measurable therapeutic gains and paving the way for personalized, regenerative medicine in neurology. Continued interdisciplinary collaboration and innovation are essential to bridge the gap from laboratory promise to routine clinical practice.
The Impact of Invasive Species on Agriculture
Invasive species represent a growing global threat to agricultural productivity, food security, and ecosystem integrity. Their accelerated spread—fueled by international trade, climate change, and anthropogenic land-use changes—has created complex challenges for sustainable farming systems worldwide. This study examines the multifaceted impact of invasive species on agriculture, including ecological disruption, economic losses, and systemic vulnerabilities.A mixed-methods approach was employed, integrating ecological assessments, economic modeling, and a multi-tiered evaluation of invasive species control strategies. Key management frameworks analyzed included Integrated Pest Management (IPM), biological control, and sustainable chemical interventions. A conceptual methodology diagram was developed to visualize the decision-making pipeline for invasion response, incorporating risk detection, control implementation, and adaptive feedback mechanisms.The findings reveal that invasive species significantly reduce crop yields, increase reliance on chemical inputs, and degrade soil and pollinator health. Economic impacts were pronounced, with estimates of multi-billion-dollar losses across affected regions. Visual analytics further demonstrated seasonal variation in pest intensities and regional disparities in control success rates. The study also highlights trade disruptions and regulatory burdens faced by countries grappling with invasive outbreaks.This research underscores the urgent need for early detection systems, transboundary cooperation, and adaptive management protocols to mitigate the long-term threats posed by invasive species. Promoting ecosystem resilience through biodiversity conservation and policy support for sustainable practices is essential to safeguarding agricultural systems. Ultimately, integrating ecological intelligence with evidence-based control measures can enhance the resilience of food systems against the growing biological invasion crisis.
The Role of Green Engineering in Mitigating Environmental Pollution: A Comprehensive Review
Environmental pollution has turned to be a worldwide issue due to industrial development, urbanisation and exploitation of resources in unsustainable manner. The conventional engineering practices placed the economic growth over the environmental sustainability thus threatening the air, water, and soil degraded. An innovative solution to these problems has been found in green engineering. It involves the consideration of the concepts of sustainability in design/implementation, operation, and optimisation of technological systems.The research examines the effectiveness of green engineering practices to mitigate the pollution through a multidisciplinary framework dealing with the pollution prevention, energy savings, integrating renewable energy and using waste as the source of energy. We applied data driven method, a method of considering the key performance indicators of various industries and comparisons of the measures pre and post green measures. The mechanical skills of the operators were studied with advanced statistical and visualisation techniques to view the trend in performance and we quantified the environmental benefit. In the findings, it can be seen that all the sectors under investigation have achieved significant progresses in terms of curbing pollution, saving energy, and recovering resources in improved ways. It should be added that indices of air and water quality got better considerably. Meanwhile, the introduction of renewable sources of energy and circular economy resulted in visible reductions in both the quantities of carbon emissions and hazardous waste. These findings indicate that green engineering as a methodology proves effective and useful in allowing sustainability to be promoted at the systems level.Finally, green engineering does not only provide us with an opportunity to correct the situation with an environment with the help of technology, but also preconditions long-term development. In order to have it to work we should overcome such issues as money problems, gaps in policy, and public resistance. However, through proper help and innovative thinking green engineering could alter the current mode of operation in factories and could make a major impact over the health of the economy and not made into the distant future.
Advancements in Sustainable Water Treatment Technologies: Innovations and Future Directions
With the increased demand of environmentally friendly and efficient methods of treating wastewater pollutants, the world is drifting towards new methods of treatment of wastewater that are integrated and curb the shortcomings of the old systems. The conventional methods are ordinarily ineffective to eliminate emerging pollutants, apply fewer resources, or acquire environmental sustainability objectives. A combination of nanotechnology, bio-based filtration, membrane systems, advanced oxidation processes (AOPs) and artificial intelligence (AI) promise to offer a novel means of water cleaning up.A mixture of comparisons and experiments are utilized in this research, in which the performance of different treatment technologies is examined. These are hybrid membrane-biofiltration systems, nanomaterial-enhanced adsorptive media and AI-based process control units. Their approach combines lab-scale simulations with performance prediction models as well as data analytics to consider the energy-use, removal and cost-effectiveness.It was established in the results format that nanofiltration systems could remove over 95% of these contaminants and the bio-based filters could consistently eliminate the heavy metals and nitrates. AOPs worked quite well when they were accompanied by membranes in breaking down recalcitrant chemicals. Nevertheless, it is very crucial to optimize the use of energy. Very accurate predictions were made by AI-based models on the effectiveness of the system, and that is why it was possible to change it in real time, and operations in different situations become more robust.The findings reveal that the integrated treatment systems are found to be better compared to the standalone ones in being able to remove pollutants, scoring on the sustainability index and being cost-effective. These findings demonstrate the significance of this approach to the application of multiple technologies in order to achieve the Sustainable Development Goals (SDG-6), and particularly in those areas where resources are limited and fragmented.Finally, we find in our research that application of smart, hybrid and green wastewater treatment technology is feasible and even essential. The report provides a helpful asset plan regarding infrastructure development in future. It requires individuals in diverse sectors to collaborate, modifications in the regulations and massive implementation of clever treatment structures so as to safeguard the water reserves of the world.
Innovative Approaches to Wastewater Treatment: Integration of Nanotechnology and Biological Processes
The worsening state of water pollution with industrialisation and urbanisation has informed us that we must have more efficient, longer lasting and better wastewater treatment methods. The paper examines the possibility of integrating nanotechnology and the biology to create a hybrid system capable of removing more pollutants. With a complete experiment, it was arranged to determine the effectiveness of nano-bio systems in removing heavy metals, infections, organic and inorganic pollutants, and other contaminants present in various forms of environments.The overall plan resulted in the significant positive changes in the outcome of treatment. Functionalised nanoparticles such as TiO 2, ZnO, and carbon nanotubes removed over 90 per cent of the material when used in certain cases. Complex contaminants were broken down due to microbial activity that was optimised by maintaining the temperature and pH to some levels. A combination of the nano-bio reactors was able to always remove pollutants, and the highest removal rates were 94.42 and more than 90% COD removal. The kinetics of first order also indicated that the rate of degradation of contaminants is higher and research on bacterial growth indicated that nanoparticles are safe to be used at a given dose.There were 12 different graphs (such as COD reduction trends, pollutant category distributions, cost-efficiency graphs) which proved that the system performed best among others. A review of the costs and use of energy indicated that the hybrid treatment reduced the cost per m3 whilst increasing the sustainability standards. These findings demonstrate that nano-bio hybrid systems might assist in resolving some of the issues of modern wastewater processing approaches as they are more efficient, versatile, and cost-effective. The research discovers that incorporating nanoparticles in the biological treatment system is a revolutionary method of handling the wastewater in an environmentally friendly and scalable manner.
Harnessing Artificial Intelligence in Translational Research: Revolutionizing Diagnostics and Treatment
Artificial Intelligence (AI) is transforming face of translational research by providing possibility of speedy yet effective choice of decisions in both the diagnostic and therapeutic fields. Its integration into the healthcare system has contributed to the transition to a proactive, data-based therapy, at least in such domains as diagnostics, personalized medicine, and therapy optimization.This paper examines the manner in which AI has the potential to enhance the translation process through the use of a multimodal structure that usually incorporates both deep learning and machine learning models. We applied clinical data such as imaging, genetic sequencing, and electronic health records to supervised learning algorithms such as CNN, SVM, and XGBoost. The approach is devoted to transparency and interpretability based on predictive modeling, cross-validation, and SHAP.All the experiments revealed that AI models exhibited an excellent classification performance (mean classification accuracy = 96.2%), where F1-scores were above 0.94 across different clinical applications, including diagnostic imaging, locating genomic mutations, and predicting pharmacogenomic responses. Moreover, in terms of individualized treatment prescriptions, AI models showed higher accuracy rates compared to the regular protocol in predicting positive outcomes of the patients. The models were also effective even in datasets collected in multiple institutions demonstrating that they were powerful and could be applied in real-life scenarios.These findings depict that AI not only assists in the earlier detection of the problem and better prediction of outcomes but also makes treatment more precise. Nonetheless, issues of ethics, such as data privacy, algorithmic and model explainability and fairness remain highly significant to its appropriate use. The research summarizes implications that could be applied to the estimulation that AI can transform translational medicine but only through collaborating, rigorous testing, and equitable implementation into clinical practice.
Biological impacts of climate change on ecosystem functionality: an ecological perspective
Climate change has emerged as a critical driver of ecological transformation, disrupting biodiversity, ecosystem services, and the structural integrity of habitats worldwide. In ecologically sensitive regions like Pakistan, the effects are especially pronounced due to diverse climatic zones ranging from arid deserts to montane forests and coastal wetlands. This study investigates the multifaceted biological impacts of climate change on ecosystem functionality, focusing on species composition, habitat degradation, ecological processes, and adaptive strategies. A multidisciplinary methodological approach was adopted, combining literature review, regional case analysis, and ecological indicator evaluation to capture both spatial and functional shifts in biodiversity and ecosystem dynamics. The results reveal widespread species migration, habitat fragmentation, and a marked increase in the prevalence of invasive species, particularly in wetland and arid ecosystems. Climatic anomalies such as extreme heat events and altered precipitation regimes were found to reduce primary productivity, disrupt nutrient cycling, and create phenological mismatches between plants and pollinators. These disruptions have weakened trophic stability and pushed several ecosystems toward ecological thresholds. The study also highlights the growing importance of community-based conservation and ecosystem-based adaptation measures, which have shown promise in improving ecological resilience and sustaining biodiversity under climate stress. Overall, the findings underscore the urgency of integrating climate adaptation into national biodiversity and environmental policy frameworks. Strengthening local conservation capacity, restoring degraded habitats, and monitoring ecological indicators will be pivotal in safeguarding Pakistan’s ecosystems against the long-term consequences of climate change.
The Role of Regenerative Medicine in Treating Degenerative Diseases: Translational Insights
Degenerative diseases such as osteoarthritis, neurodegenerative disorders, and cardiovascular conditions represent a significant global health burden due to their progressive and often irreversible nature. Regenerative medicine offers a paradigm shift by aiming to restore, replace, or regenerate damaged tissues and organs rather than merely managing symptoms.This study explores the translational potential of regenerative approaches including stem cell therapy, tissue engineering, and gene editing. A comprehensive methodological framework was adopted, examining mechanisms of action, preclinical models, and early clinical applications. Quantitative assessments were conducted to evaluate patient response rates, recovery durations, immune rejection incidence, and cost-efficiency across various therapies.Experimental findings demonstrated that stem cell therapies yielded high clinical success rates across multiple degenerative conditions, while gene editing approaches showed precision in targeting genetic mutations. Tissue engineering techniques effectively regenerated cartilage and cardiac tissue with notable recovery times. Visualizations revealed substantial differences in biomarker correlation, treatment costs, and side-effect severity across treatment modalities.The discussion highlighted translational challenges including species variation, immune compatibility, ethical concerns in gene modification, and global disparities in regulatory frameworks. Emerging technologies like 3D bioprinting and organoid development, combined with artificial intelligence-driven personalization, are expected to bridge these gaps and improve accessibility, efficacy, and safety.In conclusion, regenerative medicine holds immense promise for transforming the therapeutic landscape of chronic degenerative diseases. However, its success will depend on interdisciplinary collaboration, regulatory harmonization, and investments in scalable and equitable solutions that can deliver personalized and durable outcomes to diverse patient populations.
The Role of Microbiomes in Human Health and Disease
The human microbiome consists of billions of bacteria that constitute a complicated ecosystem that exists in various organs of the human body. It is quite important in maintaining the health of the host and influencing the growth of disease. The current advancement of the sequencing methods has enabled full profiling of microbial communities of the belly, skin, mouth, vagina, and nose. The microbiome plays a significant role in personalized medicine because these various populations of microorganisms facilitate the regulation of the immune system, metabolism and pathogen tolerance.In our work, we compared and estimated the number, diversity, and the distribution of functional genes of microbes across the various parts of the body using a metagenomic technique. Such key variables as the Shannon and Simpson indices of diversity, Firmicutes / Bacteroidetes ratio, the levels of the short-chain fatty acids, and abundance of microbes prior to exposure to antibiotics were considered. We also examined how probiotics and categories of genes affect the functionality of the microbes.We observed that the microbial composition of body parts had very diverse compositions. The most diversity and metabolic ability were in the gut microbiome. It is also interesting to mention that the structure of the microbiota was connected with the host factors such as BMI or probiotic use. There was a considerable decrease in the number of microbes in the body due to antibiotic treatment but a rise in the number of SCFAs in the probiotic patients. This argues with the notion that altering your food can enhance the functionality of the microbes.The article demonstrates the centrality of the microbiome in diagnosis and treatment as well as the alteration of phenotype in the host. In further studies, longitudinal and multi-omics methods should be conducted to understand more on the interaction between microbes and the host and in sustaining clinical interventions on the basis of microbiome research.