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The 2024 chikungunya virus (CHIKV) outbreak in Mansehra, Khyber Pakhtunkhwa, Pakistan, marked a significant public health event, providing a unique opportunity to investigate the genomic diversity and evolutionary dynamics of circulating strains. Using metagenomic next-generation sequencing (mNGS), we analyzed serum samples from patients presenting with acute febrile illness and joint pain, identifying 16 CHIKV-positive cases, six of which yielded near-complete genomes. Phylogenetic analysis revealed that all isolates belonged to the East/Central/South African (ECSA) genotype, closely related to strains from India (2020–2024) and China (2017). Notably, this study represents the first comprehensive whole-genome sequencing of CHIKV in Pakistan, uncovering unique mutations in structural (E1: I28V, V290I; E2: Y39H, D54E) and non-structural proteins (NSP1: I167V, M376T; NSP4: G27R, P52S, I403V), suggesting potential viral adaptations to local environmental and vector conditions. The absence of the E1-A226V mutation, associated with enhanced transmission by Aedes albopictus , highlights the need for continued genomic surveillance to monitor emerging variants. Additionally, the detection of a GB virus-C co-infection in one case underscores the utility of mNGS in identifying co-circulating pathogens. This study provides critical insights into the genomic landscape of CHIKV in Pakistan, emphasizing the importance of enhanced surveillance, diagnostics, and vector control strategies to mitigate future outbreaks. The findings underscore the necessity of regional collaboration and genomic monitoring to address the evolving threat of CHIKV in South Asia.

Premature coronary artery disease (PCAD) is a growing public health concern, especially in South Asia, where traditional risk factors fail to fully explain the increasing incidence of early-onset myocardial infarction. To explore its molecular underpinnings, we conducted a pilot study analyzing plasma proteins and lipids to identify potential biomarkers and dysregulated pathways associated with PCAD. Label-free quantitative proteomics revealed distinct molecular signatures separating PCAD patients from age- and sex-matched healthy controls. Key alterations included upregulation of GALE, immunoglobulin genes, and KIF20B, suggesting enhanced inflammatory responses and proliferative activity associated with post-myocardial infarction cellular repair. Similarly, down regulations of various proteins linked to multiple functions, such as myocardial infarction, hemoglobinopathy, complement and coagulation cascade, and fatty acid and lipoprotein transport in hepatocytes, were observed. Untargeted lipidomics further revealed significant elevations in several phosphatidylcholine species (PC 42:5, PC 40:3, and PC 42:7), highlighting disruption of highly unsaturated phospholipid metabolism. Overall, these findings indicate that PCAD is a multifactorial disorder involving metabolic, immune, and vascular dysfunction beyond conventional lipid abnormalities, underscoring the need for larger cohort studies to validate these biomarkers and uncover novel therapeutic targets.

Background/Objectives: Coronary artery disease (CAD) remains the leading cause of mortality worldwide, with South Asia bearing a disproportionately high and rising burden, particularly at younger ages. The present study aimed to investigate genetic variants associated with premature coronary artery disease (PCAD) using whole-genome sequencing (WGS). Methods: WGS was conducted on 12 people (five PCAD cases, seven matched controls) to assess feasibility and methodology for future large-scale research. High-quality genomic DNA was sequenced at a minimum read depth of 10× with a quality threshold of Q30. Variant calling with stringent quality control identified single-nucleotide polymorphisms (SNPs), followed by annotation against gnomAD for allele frequencies and ClinVar for pathogenicity. Protein-coding variants were filtered, and candidate genes were prioritized for comparative analysis between cases and controls. Results: An average of over 8.8 million SNPs per individual was identified, with comparable overall variant distributions between cases and controls. Initial analyses revealed 120 SNPs exclusively present in PCAD cases. All protein-coding variants were rare (allele frequency < 0.0001), and none were previously classified as pathogenic in ClinVar. After filtration, 87 candidate genes were prioritized. Enriched or unique variants in PCAD cases are mapped to genes involved in lipid metabolism, endothelial dysfunction, inflammatory signaling, immune regulation, thrombosis, vascular remodeling, and metabolic processes. Additional variants were identified in genes related to smooth muscle proliferation, oxidative stress, and other biological pathways. Conclusions: This WGS pilot study provides an initial overview of the genomic landscape of PCAD in a South Asian cohort, highlighting rare variants across multiple biological pathways implicated in atherosclerosis that need validation in a large-scale study.

The 2024 chikungunya virus (CHIKV) outbreak in Mansehra, Khyber Pakhtunkhwa, Pakistan, marked a significant public health event, providing a unique opportunity to investigate the genomic diversity and evolutionary dynamics of circulating strains. Using metagenomic next-generation sequencing (mNGS), we analyzed serum samples from patients presenting with acute febrile illness and joint pain, identifying 16 CHIKV-positive cases, six of which yielded near-complete genomes. Phylogenetic analysis revealed that all isolates belonged to the East/Central/South African (ECSA) genotype, closely related to strains from India (2020-2024) and China (2017). Notably, this study represents the first comprehensive whole-genome sequencing of CHIKV in Pakistan, uncovering unique mutations in structural (E1: I28V, V290I; E2: Y39H, D54E) and non-structural proteins (NSP1: I167V, M376T; NSP4: G27R, P52S, I403V), suggesting potential viral adaptations to local environmental and vector conditions. The absence of the E1-A226V mutation, associated with enhanced transmission by Aedes albopictus, highlights the need for continued genomic surveillance to monitor emerging variants. Additionally, the detection of a GB virus-C co-infection in one case underscores the utility of mNGS in identifying co-circulating pathogens. This study provides critical insights into the genomic landscape of CHIKV in Pakistan, emphasizing the importance of enhanced surveillance, diagnostics, and vector control strategies to mitigate future outbreaks. The findings underscore the necessity of regional collaboration and genomic monitoring to address the evolving threat of CHIKV in South Asia.

The 2024 chikungunya virus (CHIKV) outbreak in Mansehra, Khyber Pakhtunkhwa, Pakistan, marked a significant public health event, providing a unique opportunity to investigate the genomic diversity and evolutionary dynamics of circulating strains. Using metagenomic next-generation sequencing (mNGS), we analyzed serum samples from patients presenting with acute febrile illness and joint pain, identifying 16 CHIKV-positive cases, six of which yielded near-complete genomes. Phylogenetic analysis revealed that all isolates belonged to the East/Central/South African (ECSA) genotype, closely related to strains from India (2020-2024) and China (2017). Notably, this study represents the first comprehensive whole-genome sequencing of CHIKV in Pakistan, uncovering unique mutations in structural (E1: I28V, V290I; E2: Y39H, D54E) and non-structural proteins (NSP1: I167V, M376T; NSP4: G27R, P52S, I403V), suggesting potential viral adaptations to local environmental and vector conditions. The absence of the E1-A226V mutation, associated with enhanced transmission by Aedes albopictus, highlights the need for continued genomic surveillance to monitor emerging variants. Additionally, the detection of a GB virus-C co-infection in one case underscores the utility of mNGS in identifying co-circulating pathogens. This study provides critical insights into the genomic landscape of CHIKV in Pakistan, emphasizing the importance of enhanced surveillance, diagnostics, and vector control strategies to mitigate future outbreaks. The findings underscore the necessity of regional collaboration and genomic monitoring to address the evolving threat of CHIKV in South Asia.

In this study, we introduce an Adaptive Exponentially Weighted Moving based Coefficient of Variation (AEWMCV) control chart, designed to address situations where the process mean fluctuates over time and the standard deviation of the process changes linearly with the process mean. To enhance the efficiency and effectiveness of the control chart, we integrate the ranked set sampling method and its modified schemes, such as Simple Random Sampling, Quartile RSS, Median RSS, and Extreme RSS. The performance of the proposed AEWMCV control chart and the studied CV control charts are evaluated using the Average Run Length and Standard Deviation of Run Length metrics. Our findings reveal that the proposed control chart outperforms the existing CV control charts, especially in detecting slight to moderate changes in the process CV. To illustrate the practical applicability of the suggested control chart, we present an example demonstrating its use on a real dataset. The results highlight the superior performance of the AEWMCV control chart in accurately detecting and responding to changes in the process CV. In conclusion, our study introduces an innovative AEWMCV control chart that combines ranked set sampling and its modified schemes to enhance performance in scenarios with fluctuating process means and changing standard deviations. The proposed control chart proves to be more effective in detecting subtle variations in the process CV compared to traditional CV control charts. This research provides a valuable contribution to the field of control chart methodology, especially when dealing with challenging or costly data collection scenarios.

Amyloid fibril formation by proteins leads to variety of degenerative disorders called amyloidosis. While these disorders are topic of extensive research, effective treatments are still unavailable. Thus in present study, two anti-tuberculosis drugs, i.e., pyrazinamide (PYZ) and D-cycloserine (DCS), also known for treatment for Alzheimer's dementia, were checked for the anti-aggregation and anti-amyloidogenic ability on Aβ-42 peptide and hen egg white lysozyme. Results demonstrated that both drugs inhibit the heat induced aggregation; however, PYZ was more potent and decelerated the nucleation phase as observed from various spectroscopic and microscopic techniques. Furthermore, pre-formed amyloid fibrils incubated with these drugs also increased the PC12/SH-SY5Y cell viability as compare to the amyloid fibrils alone; however, the increase was more pronounced for PYZ as confirmed by MTT assay. Additionally, molecular docking study suggested that the greater inhibitory potential of PYZ as compare to DCS may be due to strong binding affinity and more occupancy of hydrophobic patches of HEWL, which is known to form the core of the protein fibrils.

The electronic waste generation rate is increasing drastically at a rate of 3 to 5% per year in developing countries. The aim of this study is to analyze the environmental sustainability and economic benefits of such e-waste management in the developing economies like Pakistan. The life cycle assessment (LCA) method has been employed for streamlined impact analysis of the end-of-life processing of e-waste focusing mainly on laptop computers and liquid crystal display (LCD) desktop computers in Pakistan. The method of cumulative exergy extraction from the natural environment (CEENE) has also been deployed for the relative assessment of resources’ consumption of e-waste recycling versus landfilling scenario. The determined impact scores are 1.79E + 03 kg CO 2 eq., 7.19E-07 kg CFC-11 eq., 1.02E + 03 kg 1,4-DCB, 7.13E + 01 kg 1,4-DCB, and 3.41E-03 kg Cu eq. in climate change potential , stratospheric ozone depletion, ecotoxicity potential, human noncarcinogenic potential, and mineral resource depletion impact categories, respectively. The results of CEENE analysis reveal that approximately 80% of the impact on natural resources is reduced by the efficient recycling of e-waste. The comparative assessment of respective scores for current and target material weight recovery (MWR) indicators represented that by increasing the MWR indicator by 33.8% for laptop computers and by 27.2% for LCD computers, the country will achieve an annual economic benefit of US $191.56 million. This is greatly significant for a transitional shift towards e-waste revalorization while realizing the objectives of sustainable resource consumption. Innovative improvement measures ensuring economically feasible, energy-efficient, and environment friendly waste collection, treatment, and recycling practices present an invaluable opportunity for developing countries.

The mechanical properties of concrete are the important parameters in a design code. The amount of laboratory trial batches and experiments required to produce useful design data can be decreased by using robust prediction models for the mechanical properties of concrete, which can save time and money. Portland cement is frequently substituted with metakaolin (MK) because of its technical and environmental advantages. In this study, three mechanical properties of concrete with MK, i.e., compressive strength (f′c), splitting tensile strength (fst), and flexural strength (FS) were modelled by using four machine learning (ML) techniques: gene expression programming (GEP), artificial neural network (ANN), M5P model tree algorithm, and random forest (RF). For this purpose, a comprehensive database containing detail of concrete mixture proportions and values of f′c, fst, and FS at different ages was gathered from peer-reviewed published documents. Various statistical metrics were used to compare the predictive and generalization capability of the ML techniques. The comparative study of ML techniques revealed that RF has better predictive and generalization capability as compared with GEP, ANN, and M5P model tree algorithm. Moreover, the sensitivity and parametric analysis (PA) was carried out. The PA showed that the most suitable proportions of MK as partial cement replacement were 10% for FS and 15% for both f′c and fst.

In this study, the multi-attribute utility theory model, one of the most widely utilized multi-criteria decision-making methods, is employed to analyze the relative sustainability and cleaner development mechanism (CDM) potential of a novel bioenergy project in Pakistan and four registered CDM bioenergy installations in China, India, Sri Lanka, and Thailand. Four major sustainability evaluation criteria selected for the study are technology, economy, environment, and social aspects, whereas “simple multi-attribute rating technique” (SMART) and “additive synthesis method” were utilized for the calculation of weighting factors. The most significant indicator was emission reduction, and least significant indicator was job creation with 24% and 15% respective weightages, in the sustainability scoring. Moreover, for three considered evaluation scenarios, (I) base case, (II) per kilowatt, and (III) per kilowatt hour, the bioenergy project in Pakistan has the highest comparative sustainability values of 0.735, 0.592, and 0.492 respectively. This analysis will provide an insight assistance to developing countries for establishing sustainable energy installations under CDM.