Search Results (372)

Background/Objectives: Metabolic syndrome (MetS) is a multifactorial condition characterized by abdominal obesity, dyslipidemia, insulin resistance, hypertension, and chronic inflammation. As its global prevalence rises, there is increasing interest in natural, multi-targeted approaches to manage MetS. Curcuma longa Linn. (turmeric), especially its active compound curcumin, has shown therapeutic promise in preclinical studies. This systematic review and meta-analysis evaluated the effects of Curcuma longa and its derivatives on MetS-related outcomes in rodent models. Methods: A comprehensive search was conducted across six databases (PubMed, Scopus, AMED, LILACS, MDPI, and Google Scholar), yielding 47 eligible in vivo studies. Data were extracted on key metabolic, inflammatory, and oxidative stress markers and analyzed using random-effects models. Results were presented as mean differences (MD) with 95% confidence intervals (CI). Results: Meta-analysis showed that curcumin significantly reduced body weight (rats: MD = −42.10; mice: MD = −2.91), blood glucose (rats: MD = −55.59; mice: MD = −28.69), triglycerides (rats: MD = −70.17; mice: MD = −24.57), total cholesterol (rats: MD = −35.77; mice: MD = −52.61), and LDL cholesterol (rats: MD = −69.34; mice: MD = −42.93). HDL cholesterol increased significantly in rats but not in mice. Inflammatory cytokines were markedly reduced, while oxidative stress improved via decreased malondialdehyde (MDA) and elevated superoxide dismutase (SOD) and catalase (CAT) levels. Heterogeneity was moderate to high, primarily due to variations in curcumin dosage (ranging from 10 to 500 mg/kg) and treatment duration (2 to 16 weeks) across studies. Conclusions: This preclinical evidence supports Curcuma longa as a promising functional food component for preventing and managing MetS. Its multi-faceted effects warrant further clinical studies to validate its translational potential. Full article

Extrapulmonary tuberculosis (EPTB) remains diagnostically challenging due to its paucibacillary nature and variable presentation. Xpert and culture are limited in EPTB diagnosis due to sampling challenges, low sensitivity, and long turnaround times. This study evaluated the performance of the MPT64 antigen detection test for diagnosing EPTB, particularly tuberculous lymphadenitis (TBLN) and tuberculous pleuritis (TBP), in a high-TB, low-HIV setting. Conducted at Gulab-Devi Hospital, Lahore, Pakistan, this study evaluated the MPT64 test’s performance against conventional diagnostic methods, including culture, histopathology, and the Xpert MTB/RIF assay. Lymph node biopsies were collected, and cell blocks were made from aspirated pleural fluid from patients clinically presumed to have EPTB. Of 338 patients, 318 (94%) were diagnosed with EPTB. For TBLN, MPT64 demonstrated higher sensitivity (84%) than Xpert (48%); for TBP, the sensitivity was 51% versus 7%, respectively. Among histopathology-confirmed TBLN cases, MPT64 outperformed both culture and Xpert (85% vs. 58% and 47%). Due to the low number of non-TB cases, specificity could not be reliably assessed. The MPT64 test shows promise as a rapid, sensitive diagnostic tool for EPTB, particularly TBLN, in routine settings. While sensitivity is notably superior to Xpert, further studies are needed to evaluate its specificity and broader diagnostic utility. Full article

Reservoir-induced landslides threaten infrastructures and downstream communities, making continuous deformation monitoring vital. Time-series InSAR, notably the SBAS algorithm, provides high-precision surface-displacement mapping but suffers from voids due to layover/shadow effects and temporal decorrelation. Existing deep-learning approaches often operate on fixed-size patches or ignore irregular spatio-temporal dependencies, limiting their ability to recover missing pixels. With this objective, a hybrid spatio-temporal Graph Attention (ST-GAT) framework was developed and trained on SBAS-InSAR values using 24 influential features. A unified spatio-temporal graph is constructed, where each node represents a pixel at a specific acquisition time. The nodes are connected via inverse distance spatial edges to their K-nearest neighbors, and they have bidirectional temporal edges to themselves in adjacent acquisitions. The two spatial GAT layers capture terrain-driven influences, while the two temporal GAT layers model annual deformation trends. A compact MLP with per-map bias converts the fused node embeddings into normalized LOS estimates. The SBAS-InSAR results reveal LOS deformation, with 48% of missing pixels and 20% located near the Dasu dam. ST D-GAT reconstructed fully continuous spatio-temporal displacement fields, filling voids at critical sites. The model was validated and achieved an overall R² (0.907), ρ (0.947), per-map R² ≥ 0.807 with RMSE ≤ 9.99, and a ROC-AUC of 0.91. It also outperformed the six compared baseline models (IDW, KNN, RF, XGBoost, MLP, simple-NN) in both RMSE and R². By combining observed LOS values with 24 covariates in the proposed model, it delivers physically consistent gap-filling and enables continuous, high-resolution landslide monitoring in radar-challenged mountainous terrain. Full article

Extremophilic microorganisms offer an untapped potential for producing unique bioactive metabolites with therapeutic applications. In the current study, bacterial isolates were obtained from samples collected from Chamalang cave located in Kohlu District, Balochistan, Pakistan. The cave-derived isolate C1 (Rhodococcus jialingiae) exhibits prominent antibacterial activity against multidrug-resistant pathogens (MDR), including Escherichia coli, Staphylococcus aureus, and Micrococcus luteus. It also demonstrates substantial antioxidant activity, with 71% and 58.39% DPPH radical scavenging. Optimization of physicochemical conditions, such as media, pH, temperature, and nitrogen and carbon sources and concentrations substantially enhanced both biomass and metabolite yields. Optimal conditions comprise specialized media, a pH of 7, a temperature of 30 °C, peptone (1.0 g/L) as the nitrogen source, and glucose (0.5 g/L) as the carbon source. HPLC and QTOF-MS analyses uncovered numerous metabolites, including a phenolic compound, 2-[(E)-3-hydroxy-3-(4-methoxyphenyl) prop-2-enoyl]-4-methoxyphenolate, Streptolactam C, Puromycin, and a putative aromatic polyketide highlighting the C1 isolate chemical. Remarkably, one compound (C₁₄H₃₆N₇) demonstrated a special molecular profile, signifying structural novelty and warranting further characterization by techniques such as ¹H and ¹³C NMR. These findings highlight the biotechnological capacity of the C1 isolate as a source of novel antimicrobials and antioxidants, linking environmental adaptation to metabolic potential and supporting natural product discovery pipelines against antibiotic resistance. Full article

Blasting is one of the most widely used and cost-effective techniques for rock excavation and fragmentation in open-pit mining, particularly for large-scale operations. However, repeated or poorly controlled blasting can generate excessive ground vibrations that threaten slope stability by causing structural damage, fracturing of the rock mass, and potential failure. Evaluating the effects of blast-induced vibrations is essential to ensure safe and sustainable mining operations. This study investigates the impact of blasting-induced vibrations on slope stability at the Saindak Copper-Gold Open-Pit Mine in Pakistan. A comprehensive dataset was compiled, including field-monitored ground vibration measurements—specifically peak particle velocity (PPV) and key blast design parameters such as spacing (S), burden (B), stemming length (SL), maximum charge per delay (MCPD), and distance from the blast point (D). Geomechanical properties of slope-forming rock units were validated through laboratory testing. Slope stability was analyzed using pseudo-static limit equilibrium methods (LEMs) based on the Mohr–Coulomb failure criterion, employing four approaches: Fellenius, Janbu, Bishop, and Spencer. Pearson and Spearman correlation analyses quantified the influence of blasting parameters on slope behavior, and sensitivity analysis determined the cumulative distribution of slope failure and dynamic response under increasing seismic loads. FoS values were calculated for both east and west pit slopes under static and dynamic conditions. Among all methods, Spencer consistently yielded the highest FoS values. Under static conditions, FoS was 1.502 for the east slope and 1.254 for the west. Under dynamic loading, FoS declined to 1.308 and 1.102, reductions of 12.9% and 11.3%, respectively, as calculated using the Spencer method. The east slope exhibited greater stability due to its gentler angle. Correlation analysis revealed that burden had a significant negative impact (r = −0.81) on stability. Sensitivity analysis showed that stability deteriorates notably when PPV exceeds 10.9 mm/s. Although daily blasting did not critically compromise stability, the west slope showed greater vulnerability, underscoring the need for stricter control of blasting energy to mitigate vibration-induced instability and promote long-term operational sustainability. Full article

The determination of the live body weight of camels (required for their successful breeding) is a rather difficult task due to the problems with handling and restraining these animals. Therefore, the main aim of this study was to predict the ABW of eight indigenous camel (Camelus dromedarius) breeds of Pakistan (Bravhi, Kachi, Kharani, Kohi, Lassi, Makrani, Pishin, and Rodbari). Selected productive (hair production, milk yield per lactation, and lactation length) and reproductive (age of puberty, age at first breeding, gestation period, dry period, and calving interval) traits served as the predictors. Six data mining methods [classification and regression trees (CARTs), chi-square automatic interaction detector (CHAID), exhaustive CHAID (EXCHAID), multivariate adaptive regression splines (MARSs), MLP, and RBF] were applied for ABW prediction. Additionally, hierarchical cluster analysis with Euclidean distance was performed for the phenotypic characterization of the camel breeds. The highest Pearson correlation coefficient between the observed and predicted values (0.84, p < 0.05) was obtained for MLP, which was also characterized by the lowest root-mean-square error (RMSE) (20.86 kg), standard deviation ratio (SD_ratio) (0.54), mean absolute percentage error (MAPE) (2.44%), and mean absolute deviation (MAD) (16.45 kg). The most influential predictor for all the models was the camel breed. The applied methods allowed for the moderately accurate prediction of ABW (average R² equal to 65.0%) and the identification of the most important productive and reproductive traits affecting its value. However, one important limitation of the present study is its relatively small dataset, especially for training the ANN (MLP and RBF). Hence, the obtained preliminary results should be validated on larger datasets in the future. Full article

Research on energy demand is advancing, with the addition of nanomaterials in anaerobic digestion increasing stability, accelerating hydrolysis, and reducing microbial inhibition. However, further research is needed to determine the mechanisms, ideal dosages, and long-term impacts. This work used continuous stir tank reactors (CSTRs) to experimentally examine the biocompatibility of iron oxide nanoparticles (Fe₃O₄-NPs) at a concentration of 75 mg/L at various organic loading rates (OLRs) of 0.3, 0.8, and 1.3 gVS/L.d (CSTRs). The efficiency of the reactors was observed by considering various parameters, such as pH, soluble chemical oxygen demand (sCOD), TVFA formation and degradation, total solids (TS), and volatile solids (VS) removal, as well as methane (CH₄) generation. Hence, it was found that the reactor with added NPs (R1) yielded an optimum 725.9 mL/gVS of CH₄ and this was achieved at the lowest OLR of 0.3 gVS/Ld. However, another reactor (R2, without NPs), exhibited more stabilized results, ranging from 372.8 to 424.4 mL/gVS at 0.3 to 1.3 gVS/Ld of OLR, respectively. Therefore, in R1, the maximum removal of sCOD, TVFAs, and VS was achieved at 90%, 74%, and 93%, respectively, as compared to R2. Full article

This study explores the role of religion as a state-promoted tool for political assimilation in Pakistan’s border provinces of Khyber Pakhtunkhwa (KP) and Balochistan. The study is based on five phases of fieldwork (2016–2024) combined with a thematic literature review. The research explores how religious strategies were deployed to forge a unified national identity in these regions. The findings reveal significant disparities in the effectiveness of these strategies. In KP, historical factors, cultural alignment, and geopolitical influences—particularly the Afghan conflict—largely facilitated the integration of Pashtun identity into Pakistan’s broader Islamic-national framework. Tools such as madrassa networks, education reforms, religious slogans, and state-backed Islamist parties effectively promoted religious nationalism. In contrast, religious assimilation efforts in Balochistan largely failed due to entrenched ethnic nationalism, economic exclusion, and political marginalization. Attempts to expand madrassas, delegitimize nationalist leaders as “anti-Islamic,” and support religious movements have been met with resistance, deepening distrust between the Baloch population and the state. The study found that religion alone cannot sustain national cohesion, particularly in regions with longstanding grievances and systemic inequalities. This research emphasizes the limitations of top-down, coercive assimilationist policies and underscores the necessity for more inclusive approaches, such as addressing economic disparities, recognizing regional identities, and promoting political participation as essential components for building a sustainable and unified nation. The study provides critical insights for policymakers, advocating for a shift from religious assimilation to strategies that prioritize justice, equity, and cultural accommodation, particularly in KPK and Balochistan. Full article

Mining activities in Pakistan’s mineral-rich provinces threaten freshwater security through groundwater depletion, contamination, and flood-induced pollution. This study develops an Inclusive Disaster Risk Reduction (IDRR) framework integrating governance, social, environmental, and technical (GSET) dimensions to holistically assess mining-induced water hazards across Balochistan, Khyber Pakhtunkhwa, and Punjab. Using GIS-based spatial risk mapping with multi-layer hydrological modeling, we combine computational analysis and participatory validation to identify vulnerability hotspots and prioritize high-risk mines. Community workshops involving women water collectors, indigenous leaders, and local experts enhanced map accuracy by translating indigenous knowledge into spatially referenced mitigation plans and integrating gender-sensitive metrics to address gendered water access disparities. Key findings reveal severe groundwater depletion, acid mine drainage, and gendered burdens near Saindak and Cherat mines. Multi-sectoral engagements secured corporate commitments for water stewardship and policy advances in inclusive governance. The framework employs four priority-ranked risk categories (Governance-Economic 15%, Social-Community 30%, Environmental 40%, Technical-Geological 15%) derived via local stakeholder collaboration, enabling context-specific interventions. Despite data limitations, the GIS-driven methodology provides a scalable model for regions facing socio-environmental vulnerabilities. The results demonstrate how community participation directly shaped village-level water management alongside GSET analysis to craft equitable risk reduction strategies. Spatially explicit risk maps guided infrastructure upgrades and zoning regulations, advancing SDG 6 and 13 progress in Pakistan. This work underscores the value of inclusive, weighted frameworks for sustainable mining–water nexus management in Pakistan and analogous contexts. Full article

This study examines culture-led urban regeneration as a strategy for revitalizing Meezan Chowk, a historically significant yet deteriorating public space in Quetta, Pakistan. Once a central site of social and commercial exchange, the area suffered from infrastructural decline, overcrowding, and the erosion of its architectural identity. The research proposes a design intervention to restore the site’s heritage value while enhancing its functional and social relevance. A qualitative approach is adopted, incorporating surveys, focus group discussions, and site observations to assess user needs and spatial dynamics. A SWOT analysis serves as the analytical framework to identify the site’s internal strengths and weaknesses, as well as external opportunities and threats. By utilizing the Geographic Information Systems (GIS) and OpenStreetMap data, further information can enhance understanding of the site’s urban morphology. The proposed design integrates vernacular elements, such as arched facades, shaded corridors, and communal courtyards, with contemporary features, including cafes, local artisan shops, and accessible public amenities. Full article

Metabolic syndrome (MetS) is a complex condition defined by central obesity, insulin resistance, dyslipidemia, and systemic inflammation. Kefir, a fermented beverage rich in probiotics and beneficial compounds, has emerged as a functional food that may offer metabolic advantages. Nevertheless, preclinical results have been variable. This systematic review and meta-analysis aimed to assess the influence of kefir and its derived compositions on parameters associated with MetS, inflammation, and oxidative stress in rodent studies. A comprehensive literature search was conducted in PubMed, Scopus, AMED, and LILACS through June 2024. Eligible studies involving kefir interventions in rodent MetS models were included. Data extraction followed PRISMA guidelines, with the risk of bias assessed using the CAMARADES and SYRCLE tools. Meta-analyses were performed with a random effects model. Thirty-eight studies involving 1462 rodents (mice and rats) were analyzed. Kefir significantly reduced body weight gain in both mice (MD = –3.33; 95% CI: –4.89 to –1.77) and rats (MD = –41.53; 95% CI: –54.33 to –28.72). In mice, triglycerides and LDL-C levels decreased significantly; in rats, kefir lowered total cholesterol and triglycerides. Insulin levels were reduced (MD = –0.69; 95% CI: –1.16 to –0.22), suggesting improved insulin sensitivity. Several studies also reported reductions in TNF-α, IL-1β, and IL-6. Despite promising results, the high heterogeneity and methodological variability emphasize the need for standardized preclinical protocols and clinical validation. These findings support the role of kefir as a functional food for metabolic health promotion. Full article

The Mega-Sub Controlled Structure System (MSCSS) represents an innovative category of seismic-resistant super high-rise building structural systems, and exploring its damage mechanisms and identification methods is crucial. Nonetheless, the prevailing methodologies for establishing criteria for structural damage are deficient in providing a lucid and comprehensible representation of the actual damage sustained by edifices during seismic events. To address these challenges, the present study develops a finite element model of the MSCSS, conducts nonlinear time-history analyses to assess the MSCSS’s response to prolonged seismic motion records, and evaluates its damage progression. Moreover, considering the genuine damage conditions experienced by the MSCSS, damage working scenarios under seismic forces were formulated to delineate the damage patterns. A convolutional neural network recognition framework based on stacking ensemble learning is proposed for extracting damage features from the temporal response of structural systems and achieving damage classification. This framework accounts for the temporal and spatial interrelations among sensors distributed at disparate locations within the structure and addresses the issue of data imbalance arising from a limited quantity of damaged samples. The research results indicate that the proposed method achieves an accuracy of over 98% in dealing with damage in imbalanced datasets, while also demonstrating remarkable robustness. Full article

Pakistan’s marine fishing industry is crucial to the country’s economy, generating employment opportunities and foreign revenue. It produces 80% of the country’s total fish production. Otolithes ruber is a commercially important fish on the Makran coast of Pakistan, contributing significantly to the region’s croaker fisheries. This study is the first to apply three length-based approaches for assessing the stock status of O. ruber in the Makran coast: (1) TropFishR to estimate the mortality, growth parameters, and current exploitation status, reference points based on the yield per recruitment model, (2) the length-based Bayesian biomass method (LBB) to calculate stock biomass, and (3) the length-based spawning potential ratio (LBSPR) to estimate the spawning potential ratio. The length–weight relationship of Otolithes ruber was a positive allometric pattern (b = 3.28; R² = 0.94). Growth parameters for Otolithes ruber were L_∞ = 55.47 cm, K = 0.50 year⁻¹. The calculated total mortality rate (Z), natural mortality (M), and fishing mortality (F) were 2.27 year⁻¹, 0.67 year⁻¹, and 1.6 year⁻¹, respectively. The exploitation rate (E) was 0.70, indicating severe overexploitation. The current length at first capture (Lc₅₀) = 27.37 cm was lower than that at first maturity (Lm₅₀) = 30.75 cm, indicating growth overfishing. The current spawning potential ratio (8%) was lower than the optimal value (40%), indicating recruitment overfishing. The current biomass, concerning virgin biomass B/B_o, was also 8%, resulting in a 92% stock decline. We recommend reducing the exploitation pressure by limiting the commercial catch to an optimum length range of 34.5–42.2 cm and reducing fishing pressure by 40% to ensure sustainable fishery management. Full article

Introduction: The use of electrical appliances using extremely low frequency (ELF) electromagnetic fields (EMF) has increased in the past few years. These ELF MF are reported to be linked to several adverse health effects. However, only a couple of studies have been conducted on the association between risk of tumours and use of electronic devices using low frequency (LF) EMF. Methods: We studied the use of common household electrical appliances and suspected risk of tumours in a multi-hospital-based case-control study. In total, 316 patients were included in the final analysis. Results: The study results showed a below unity risk for most of the devices. A slight increased risk of tumour was observed for computer screen use OR: 1.13 (95% CI: 0.43–3.02) and use of microwave oven OR: 1.21 (95% CI: 0.36–4.04). We also had chance to investigate ELF MFs exposure association with tumour. Where we observed elevated odd ratios in individuals living near electricity transformer stations, with a statistically significant risk OR: 2.16 (95% CI: 1.30–3.59). However, the risk was below unity (OR: 0.98) in individuals residing close to powerlines. Conclusion: The current study serves as a pilot study of primary data and will be helpful in future epidemiological research studies on the topic in the region. Full article

Lentil is an important legume crop globally with an annual production of around 6.3 million tons. Pakistan stands at the 49th position producing 4668 tons of lentil from 7428 hectares with an average yield of 570 kg/ha. A lack of high-yielding varieties is one of the major reasons for low yield, resulting in an approx. 31% decrease in the cultivation area. In the present study, 649 accessions of lentil representing Pakistan, USA, and Syria were studied for yield and yield-contributing traits for three consecutive years. Accession 5930 performed best in all three years, having a seed yield (SY) of 192.84 ± 9.05 g/m² and a biological yield (BY) of 534.20 ± 25.79 g/m². Overall, SY has a significant positive association with BY, pods per plant (NP), pod weight (PW), harvest index (HI), and plant height (PH). PCA, heritability, and genetic advance also suggested these traits as effective selection indicators. A K-mean cluster analysis based on Wilks lambda highlighted that accessions with a higher SY, BY, NP, PW, and NB were grouped in Clusters III, V, and II during the first, second, and third years, respectively. During all three years, genotypes in the HI range 10.1–15% had the highest biological yield, while the HI range of >35% represented early maturing accessions with high seed yields, providing a strong basis for future selection. Fluctuation in mean temperature (22.5, 22.4 and 24.7 °C) and rainfall (518, 644.6 and 287.7 mm) during the three cropping seasons (October–April) under study had a significant impact on performance of the accessions. The better average yield was observed in the third year, which might be attributed to aforementioned temperature and rainfall differences. Despite the weather impact, 10 accessions, viz., 5930, 6057, 5865, 34709, 5542, 5884, 17794, 34693, 5888, and 5944 exhibited high yield potential in all three years and are therefore recommended for lentil improvement programs in the future. Full article