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Found 6515 publications
Explaining the variation in sustainable development through the lens of key macroeconomic and environmental factors
Publication Name: Discover Sustainability
Publication Date: 2026-12-01
Volume: 7
Issue: 1
Page Range: Unknown
Description:
This paper investigates the role ofenvironmental and macroeconomic stabilityin achieving sustainable developmentin Pakistan from 1990 to 2022.The objective of this study is to investigate the contagion effects of both ecological and macroeconomic variables on Pakistan's sustainable development, employing the structural VAR methodology. The research addresses an important gap in the literature to jointly analyze macroeconomic stability and environmental sustainability within a unified framework for a developing economy like Pakistan. The need for this study arises from Pakistan’s dual challenges of persistent macroeconomic instability and rising environmental stress, which together threaten progress toward the Sustainable Development Goals (SDGs). Positive energy shocks are strongerth annegative shocks arising from CO2 , external debt, and inflationin explicating variation inPakistan’s sustainable development. The study finds that renewable energy consumption has the most significant long-term impact on sustainable development, accounting for 33.83% of the forecast error variance. Overall, 55.50% of sustainable development is predicted by environmental factors,14.66% by macroeconomic variables, and 29.84% by its shock. Such results lead to accepting the hypothesis that ecological and macroeconomic stability significantly affect the sustainable development of Pakistan. In the long run, renewable energy consumption has a positive impact on sustainable development, promoting energy security, supporting economic growth, and maintaining environmental stability. The results of diagnostic tests suggest that the structural VAR approach is specified correctly. This study recommends that all economic policies be designed to highlight the need for comprehensive reforms that align economic stability with environmental resilience to achieve sustainable development. In the context of Pakistan, positive shocks arising from renewable energy consumption demonstrate a stronger influence on variations in sustainable development compared to negative shocks arising from CO₂ emissions, external debt, and inflation. This highlights the central role of energy transitions in achieving sustainability.
Open Access: Yes
Sustainable closed-loop supply chain network design under uncertainty using a fuzzy multi-objective optimization framework for the battery industry
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
The study presents a sustainable closed-loop supply chain network that integrates financial, environmental, and social objectives within a context of uncertainty. A fuzzy-based modeling approach is introduced to address uncertainty in customer demand, cost parameters, and carbon emission coefficients across the sustainable closed-loop supply chain network. Two metaheuristic methods, the non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimization (MOPSO), are employed to address the problem and are compared against each other. A practical case study of a battery company is employed to validate the framework. The findings indicate that MOPSO surpasses non-dominated sorting genetic algorithm II in terms of solution quality and computational efficiency, compared with NSGA-II, the proposed MOPSO achieved a 6.3% reduction in total cost and an 8.1% decrease in CO₂ emissions, while the social index reflecting recruitment and employee security increased by 12.5%. This study contributes a sustainable closed-loop supply chain network design model for the battery industry that together optimizes economic, environmental, and social objectives amid parameter uncertainty, and offers algorithmic evaluations of optimized multi-objective metaheuristics to achieve high-quality Pareto solutions.
Open Access: Yes
Hospital Admission Classification of Cardiac Patients Utilizing Metaheuristics-Optimized Two Tier Framework
Publication Name: International Journal of Computational Intelligence Systems
Publication Date: 2026-12-01
Volume: 19
Issue: 1
Page Range: Unknown
Description:
Accurate evaluation of a cardiac patient’s risk at the point of hospital entry is critical for efficient triage and ensuring timely, suitable medical intervention. This study aims to forecast a range of clinical outcomes by leveraging admission data from a cardiac care unit, utilizing a refined and optimized machine learning approach. This research introduces a hybrid architecture that integrates convolutional neural networks (CNNs) with advanced machine learning classifiers, namely light gradient boosting machine (LightGBM) and categorical boosting (CatBoost), further enhanced through metaheuristic optimization techniques to maximize their performance. The proposed two-tiered design organizes feature extraction and final decision modeling into a coherent pipeline tailored for multi-class hospital admission classification. A comprehensive evaluation using a real-world hospital admission dataset demonstrates the framework’s effectiveness on a real-world, publicly available hospital admission dataset, supporting its utility for multi-class cardiac outcome prediction. Three experiments were conducted using publicly available datasets, where the best-performing models achieved a peak classification accuracy of 99.79%. Furthermore, explainable AI techniques were employed to interpret model predictions, offering actionable insights that can guide future data acquisition and strengthen the accurate classification of cardiac patients.
Open Access: Yes
Dual TYK2/JAK1 Inhibition by Brepocitinib Reprograms Synoviocyte Pathobiology: Mechanistic Insights Into Targeted Therapy for Rheumatoid Arthritis
Publication Name: Iranian Journal of Pharmaceutical Research
Publication Date: 2026-12-01
Volume: 25
Issue: 1
Page Range: Unknown
Description:
Background: Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by synovial hyperplasia, persistent inflammation, and joint destruction. Targeted inhibition of intracellular signaling pathways, such as JAK-STAT, has improved RA treatment outcomes, though safety and selectivity remain as concerns. Brepocitinib, a dual TYK2/JAK1 inhibitor, has shown clinical efficacy in the management of autoimmune diseases, yet its mechanistic impact on synoviocytes remains underexplored. Objectives: To investigate the molecular and functional effects of brepocitinib on MH7A and RA-FLS synoviocytes, a key effector cell type in RA pathogenesis. Methods: MH7A and RA-FLS cells were treated with brepocitinib (0.5 µM, 1 µM, and 5 µM) for 24 hours. Cell viability was assessed. Western blotting was used to examine phosphorylation of TYK2, JAK1, STAT1/3, and apoptotic markers (BAX, BCL-2, caspase-3). Quantitative PCR and ELISA were performed to evaluate mRNA and protein levels, respectively, of IL-6, TNF-α, and IFN-γ. Wound healing assays measured synoviocyte migration. Results: Brepocitinib maintained ≥ 85% cell viability across all doses, compared with ~20% viability in doxorubicin-treated controls. At 5 µM, phosphorylation of JAK1 and STAT3 was suppressed by > 80%, while TYK2 and STAT1 inhibition reached ~70%. IL-6 and TNF-α transcripts were reduced by > 80% and IFN-γ by ~70%, with corresponding decreases in secreted cytokines (IL-6: 100 pg/mL to 20 pg/mL; TNF-α: 150 pg/mL to 15 pg/mL; IFN-γ: 41 pg/mL to 11 pg/mL). Brepocitinib shifted the BAX/BCL-2 ratio fourfold in favor of apoptosis and increased cleaved caspase-3 levels to ~80% of maximal response. Functionally, it reduced wound closure from ~75% in controls to ~20% at 5 µM, confirming potent inhibition of synoviocyte migration. Conclusions: Brepocitinib exerts multi-faceted effects on RA synoviocytes by simultaneously inhibiting inflammatory signaling, suppressing cytokine expression, restoring apoptotic sensitivity, and reducing migratory potential. These findings provide mechanistic support for brepocitinib as a targeted therapeutic agent in RA.
Open Access: Yes
DOI: 10.5812/ijpr-166019
Molecular characterisation of the invasive terrestrial nemertean Geonemertes pelaensis: long and complex mitogenome and presence of NUMTs
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
The complete mitochondrial genome of the invasive terrestrial nemertean Geonemertes pelaensis Semper, 1863 (Nemertea: Prosorhochmidae) was sequenced from two specimens collected in geographically distant French overseas territories—Martinique in the Caribbean and New Caledonia in the South-West Pacific. In both specimens, the mitogenome contained 13 protein-coding genes, two rRNA genes, and 21 tRNA genes, and was unusually large, approaching 32 kb. The two genomes differed by only four single nucleotide polymorphisms and one indel. A comparison with 22 cox1 sequences available in GenBank confirmed this high level of genetic conservation, suggesting a recent introduction from related source populations. The extraordinary length of the mitogenome was largely attributable to two extended regions comprising only tRNA genes and long intergenic sequences. These results were contrasted with data from an unpublished SRA sequencing project (SRS20559370) of an unlocalized specimen identified as G. pelaensis; its reconstructed mitogenome was only 18 kb in length (14 kb shorter) and showed extensive sequence divergence. Phylogenetic analyses placed this specimen as the sister lineage to G. pelaensis, highlighting the need for further investigation of this taxon. In the Martinique specimen, several NUMTs (nuclear mitochondrial pseudogenes) were also detected, which could complicate future studies relying solely on Sanger sequencing. Sequencing additionally revealed prey DNA from the gut contents of both worms: the New Caledonian specimen had consumed an unidentified noctuid moth, while the Martinique specimen had likely fed on the invasive cockroach Periplaneta australasiae (Fabricius, 1775), itself an introduced species.
Open Access: Yes
Real-time monitoring of ammonia emissions from cereal crops using LoRaWAN-based sensing technology
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
This study presents a LoRaWAN-based IoT system developed for real-time monitoring of ammonia (NH₃) emissions in cereal crop fields. Sustainable agriculture increasingly demands on-farm greenhouse gas (GHG) tracking linked to environmental variables. IoT offers efficient real-time monitoring of soil NH₃ emissions and associated factors. Our research introduces a unique Field Monitoring Laboratory: a LoRaWAN-connected IoT system integrating soil, crop, and microclimate sensors to observe NH₃⁺, air temperature, rainfall, humidity, soil temperature, and moisture content. The system comprises a field lab, data server, and custom dashboard with analytics capabilities. NH₃ fluxes were measured in autumn-sown cereals across three growing seasons (2020–2023). Tukey’s Kramer test revealed significant (p < 0.05, p < 0.001) differences in NH₃ emissions and environmental variables between years. Highest NH₃ emissions (1.94 ppm in 2020, 1.71 ppm in 2021) coincided with elevated air (25–31 °C) and soil (21–23 °C) temperatures, and higher mean and peak rainfall (0.40–0.48 mm average; max 9–31.6 mm). Principal Component Analysis showed 65.8% variance explained by PC1 and PC2, with high loadings from temperature and soil moisture. Spearman’s correlation indicated moderate positive associations (r = 0.38–0.4, p < 0.05) of NH₃ with soil moisture at 20 cm and 40 cm of soil depth, and a weak negative correlation (r = -0.16 and − 0.17) with soil temperature at 20 cm and 40 cm. The study underscores the potential of IoT technology using calibrated gas sensors and LoRaWAN for real-time NH₃ and environmental monitoring, enabling informed decision-making in smart agriculture.
Open Access: Yes
Discovery of potential antiviral compounds and accelerating the therapeutic discovery against monkeypox virus
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
Monkeypox virus is a zoonotic virus of the genus Orthopox viruses. It can be transmitted through direct or indirect contact with animals or infected ones. Owing similarity of pathogenesis with smallpox, the same drugs can be used for both viruses, but they are not specific and only help to relieve the symptoms only. Therefore, the absence of antiviral treatment or licensed vaccine highlights an urgent need, especially due to its rapid prevalence. The study screened the library of compounds to retrieve drug-like molecules that can act against monkeypox virus. The highly virulent target gene B8R having uniport ID Q3I8J0 was chosen. Targeting B8R is substantial for global health and can align with SDG 3 and awareness of disease management. The B8R was modelled via Artificial intelligence (AI) AlphaFold method and then exposed to a library of compounds. Complementary interactions in the active site were shown by molecular docking. The Complex-1 had the greatest binding affinity (–8.4 kcal/mol), followed by Complex-2 (–8.1 kcal/mol) and Complex-3 (–7.7 kcal/mol). After 125 ns, Complex-1 reached equilibrium at 7.5 Å RMSD, according to MD simulations, exhibiting stable ligand retention and reliable interactions with crucial residues Gly135 and Lys136. Complex-3 shown intermediate protein stability (6 Å RMSD) but notable ligand fluctuation (48 Å RMSF), while Complex-2 displayed increased protein RMSD (8 Å RMSD) and delayed ligand stabilisation (16 Å RMSF). These results were corroborated by PCA analysis, which showed that Complex-1 exhibits coherent structural development whereas Complex-2 and Complex-3 show scattered and compact trajectories, respectively. Complex-1 promise for Mpox viral inhibition was highlighted by the fact that it was the most stable and dynamically favourable contender overall. The N-terminal follows the folding trend. The insilico analysis not only proposed a potent compound but also provides deep insight into the behavior of protein. The proposed potent compound against this zoonotic virus can be helpful to combat the monkeypox virus by subjecting it further towards experimental investigation.
Open Access: Yes
Regression and statistical analysis of heat transfer enhancement in water/ethylene glycol (40/60) base molybdenum carbide (Mo2C) MXene nanofluid using a transient fractional model
Publication Name: Discover Nano
Publication Date: 2026-12-01
Volume: 21
Issue: 1
Page Range: Unknown
Description:
To investigate the effects of fractional order (), nanoparticle volume fraction (), magnetic field strength (), and Brinkman permeability () on both flow and heat transfer characteristics, a detailed parametric and statistical analysis is conducted. The statistical regression analysis shows that the volume fraction of nanoparticles and temperature have a strong positive correlation (coefficient = 0.94, p = 0.021) indicating that Mo2 C MXene is an excellent heat absorption. On the other hand, the fractional parameter α has a strong negative effect on temperature field (coefficient = − 0.086, p < 0.001), which emphasizes its importance in describing the effects of thermal memory. The findings also indicate that, although MXene nanoparticles significantly increase thermal transport, an augmentation in magnetic field strength and Brinkman resistance cause a resistive Lorentz force and frictional drag, respectively, to prevent fluid flow. These results are physically informative about non-Fourier heat transfer in MXene-based nanofluids as well as offer invaluable information to developing high-performance thermal management systems and solar-energy applications.
Open Access: Yes
The effect of mixed fatigue on knee biomechanics and muscle activation during sidestep cutting in elite soccer players
Publication Name: BMC Sports Science Medicine and Rehabilitation
Publication Date: 2026-12-01
Volume: 18
Issue: 1
Page Range: Unknown
Description:
Background: Football is one of the most popular sports in the world, and it is also a sport with a high rate of injury. The study aims to investigate the effects of physical and mental mixed fatigue (PMF) on knee biomechanics during sidestep cutting maneuvers in elite male soccer players, thereby assessing the potential mechanisms underlying non-contact knee injuries. Methods: Thirty-six elite male soccer players were recruited (age: 21.61 ± 1.22 years; body mass: 75.16 ± 6.34 kg; height: 175.8 ± 3.53 cm; shoe size: 41–44 EUR). Following a targeted fatigue induction protocol, key lower limb biomechanical data were acquired during anticipated sidestep cutting maneuvers both pre- and post-PMF. Statistical analyses were performed utilizing paired sample t-tests and one-dimensional Statistical Parametric Mapping (SPM1d). Results: Following PMF, knee valgus increased at initial contact (P = 0.022). Kinetic analysis, supported by SPM1d, revealed a marked transition from an extensor-dominant to a flexor-dominant pattern in sagittal knee moments (P = 0.007), alongside elevated knee valgus moments (P = 0.039). Neuromuscularly, quadriceps and lateral gastrocnemius activation (iEMG/RMS) significantly decreased, whereas compensatory increases were observed in the hamstrings and medial gastrocnemius (all P < 0.001). Conclusion: While PMF preserved most kinematics, the statistically significant increase in knee valgus, though small in magnitude, suggests an impaired frontal-plane control that may elevate Anterior Cruciate Ligament (ACL) strain. The shift from quadriceps to hamstring dominance reflects a compensatory neuromuscular strategy. These findings emphasize the importance of incorporating cognitive load into injury-prevention programs and monitoring mental fatigue to reduce non-contact knee injury risks.
Open Access: Yes
