Search Results (1,037)

A comprehensive metabolic profiling of Catharanthus roseus (L.) G. Don was performed using tandem mass spectrometry, along with an evaluation of the biological activities of its various solvent extracts. Among these, the methanolic leaf extract exhibited mild radical scavenging activity, low to moderate antimicrobial activity, and limited cytotoxicity in both the brine shrimp lethality assay and MTT assay against HeLa and A549 cell lines. High-performance liquid chromatography–electrospray ionization–high-resolution tandem mass spectrometry (HPLC-ESI-HRMS/MS) analysis led to the annotation of 34 metabolites, primarily alkaloids. These included 23 indole alkaloids, two fatty acids, two pentacyclic triterpenoids, one amino acid, four porphyrin derivatives, one glyceride, and one chlorin derivative. Notably, two metabolites—2,3-dihydroxypropyl 9,12,15-octadecatrienoate and (10S)-hydroxypheophorbide A—were identified for the first time in C. roseus. Furthermore, Global Natural Products Social Molecular Networking (GNPS) analysis revealed 18 additional metabolites, including epoxypheophorbide A, 11,12-dehydroursolic acid lactone, and 20-isocatharanthine. These findings highlight the diverse secondary metabolite profile of C. roseus and support its potential as a source of bioactive compounds for therapeutic development. Full article

The convergence of artificial intelligence (AI) and nanomedicine has transformed cancer vaccine development, particularly in optimizing RNA-loaded lipid nanoparticles (LNPs). Stability and targeted delivery are major obstacles to the clinical translation of promising RNA-LNP vaccines for cancer immunotherapy. This systematic review analyzes the AI’s impact on LNP engineering through machine learning-driven predictive models, generative adversarial networks (GANs) for novel lipid design, and neural network-enhanced biodistribution prediction. AI reduces the therapeutic development timeline through accelerated virtual screening of millions of lipid combinations, compared to conventional high-throughput screening. Furthermore, AI-optimized LNPs demonstrate improved tumor targeting. GAN-generated lipids show structural novelty while maintaining higher encapsulation efficiency; graph neural networks predict RNA-LNP binding affinity with high accuracy vs. experimental data; digital twins reduce lyophilization optimization from years to months; and federated learning models enable multi-institutional data sharing. We propose a framework to address key technical challenges: training data quality (min. 15,000 lipid structures), model interpretability (SHAP > 0.65), and regulatory compliance (21CFR Part 11). AI integration reduces manufacturing costs and makes personalized cancer vaccine affordable. Future directions need to prioritize quantum machine learning for stability prediction and edge computing for real-time formulation modifications. Full article

Historic cities across the globe have experienced profound changes in their spatial and functional characteristics over time, and the historic core of Patan, Nepal, is no exception. The area surrounding Patan Durbar Square was designated as a UNESCO World Heritage Site in 1979. Between 2003 and 2007, the Kathmandu Valley was placed on UNESCO’s List of World Heritage in Danger, largely due to various factors, including the rapid and unsympathetic transformation of its buffer zone. This study focuses on the Nagbahal neighborhood, a culturally significant locality within this buffer area, to explore a community-rooted and sustainable approach to conservation. Employing a mixed-methods research design, the study integrates qualitative and quantitative data gathered through interviews and surveys of native residents. It investigates the drivers and impacts of changes in the function, ownership, and physical form of traditional residential buildings, and assesses whether these changes align with principles of sustainable heritage conservation—social, cultural, economic, and environmental. While challenges persist, including the proliferation of reinforced concrete structures and limited enforcement of heritage policies, the findings reveal that Nagbahal remains resilient due to strong local traditions, active religious institutions, and cohesive social practices. The study offers transferable lessons for sustainable conservation in living heritage buffer zones globally. Full article

This work explores zinc oxide nanoparticle (ZnO NP) synthesis utilizing leaf extract of the Gaultheria fragrantissima plant that are useful in medicine, environmental remediation, and cosmetics due to their antibacterial activity, photocatalytic efficiency, and UV-blocking characteristics. Traditional synthesis methods involve energy-intensive procedures and hazardous chemicals, posing environmental and human health risks. To overcome these limitations, this research focuses on utilizing G. fragrantissima, rich in bioactive compounds such as phenolics and flavonoids, with the methyl salicylate previously reported in the literature for this species, which helps reduce and stabilize NPs. ZnO NPs were characterized through X-ray diffraction (XRD), UV–visible spectroscopy, Fourier transform infrared (FTIR) spectroscopy, field emission scanning electron microscopy (FESEM), and energy-dispersive spectroscopy (EDS). The ZnO NPs were found to have a well-defined crystalline structure, with their average crystallite size measured at around 8.26 nm. ZnO NPs exhibited moderate antimicrobial activity against selected microbial strains. These findings underscore the potential of G. fragrantissima-mediated synthesis as an environmentally sustainable and efficient method for producing ZnO NPs with multifunctional applications. This study provides a greener alternative to conventional synthesis approaches, demonstrating a method that is both eco-friendly and capable of yielding NPss with desirable properties. Full article

The water regime in Pakistan’s northern region has experienced significant changes regarding hydrological extremes like floods because of climate change. Coupling hydrological models with remote sensing data can be valuable for flow simulation in data-scarce regions. This study focused on simulating the snow- and glacier-melt runoff using the snowmelt runoff model (SRM) in the Gilgit and Kachura River Basins of the upper Indus basin (UIB). The SRM was applied by coupling it with in situ and improved cloud-free MODIS snow and glacier composite satellite data (MOYDGL06) to simulate the flow under current and future climate scenarios. The SRM showed significant results: the Nash–Sutcliffe coefficient (NSE) for the calibration and validation period was between 0.93 and 0.97, and the difference in volume (between the simulated and observed flow) was in the range of −1.5 to 2.8% for both catchments. The flow tends to increase by 0.3–10.8% for both regions (with a higher increase in Gilgit) under mid- and late-21st-century climate scenarios. The Gilgit Basin’s higher hydrological sensitivity to climate change, compared to the Kachura Basin, stems from its lower mean elevation, seasonal snow dominance, and greater temperature-induced melt exposure. This study concludes that the simple temperature-based models, such as the SRM, coupled with improved satellite snow cover data, are reliable in simulating the current and future flows from the data-scarce mountainous catchments of Pakistan. The outcomes are valuable and can be used to anticipate and lessen any threat of flooding to the local community and the environment under the changing climate. This study may support flood assessment and mapping models in future flood risk reduction plans. Full article

A Sanskrit manuscript of the Prajñāpāramitā or Perfection of Wisdom in eight thousand verses, now in the Cambridge University Library, Add.1643, is one of the most ambitiously designed South Asian manuscripts from the eleventh century, with the highest number of painted panels known among the dated manuscripts from medieval South Asia until 1400 CE. Thanks to the unique occurrence of a caption written next to each painted panel, it is possible to identify most images in this manuscript as representing those of famous pilgrimage sites or auspicious images of specific locales. The iconographic program transforms Add.1643 into a portable device containing famous pilgrimage sites of the Buddhist world known to the makers and users of the manuscript in eleventh-century Nepal. It is one compact colorful package of a book, which can be opened and experienced in its unfolding three-dimensional space, like a virtual or imagined pilgrimage. Building on the recent research focusing on early medieval Buddhist sites across Monsoon Asia and analyzing the representational potentials and ontological values of painting, this essay demonstrates how this early eleventh-century Nepalese manuscript (Add.1643) and its visual program document and remember the knowledge of maritime travels and the transregional and intraregional activities of people and ideas moving across Monsoon Asia. Despite being made in the Kathmandu Valley with a considerable physical distance from the actual sea routes, the sites remembered in the manuscript open a possibility to connect the dots of human movement beyond the known networks and routes of “world systems”. Full article

Some of the most intense thunderstorms and extreme weather events on Earth occur in the Hindu Kush Himalaya (HKH) region of Southern Asia. The need to provide end users, stakeholders, and decision makers with accurate forecasts and alerts of extreme weather is critical. To that end, a cutting edge weather modeling framework coined the High Impact Weather Assessment Toolkit (HIWAT) was created through the National Aeronautics and Space Administration (NASA) SERVIR Applied Sciences Team (AST) effort, which consists of a suite of varied numerical weather prediction (NWP) model runs to provide probabilities of straight-line damaging winds, hail, frequent lightning, and intense rainfall as part of a daily 54 h forecast tool. The HIWAT system was first deployed in 2018, and the recently released model archive hosted by the Global Hydrometeorology Resource Center (GHRC) Distributed Active Archive Center (DAAC) provides daily model outputs for the years of 2018–2022. With a nested modeling domain covering Nepal, Bangladesh, Bhutan, and Northeast India, the HIWAT archive spans the critical pre-monsoon and monsoon months of March–October when severe weather and flooding are most frequent. As part of NASA’s Transformation To Open Science (TOPS), this data archive is freely available to practitioners and researchers. Full article

In 2023, the VAS international working group on Buerger’s Disease (BD) recommended two diagnostic criteria based on a prior Delphi study: “definitive” and “suspected”. The “definitive” criteria are history of smoking, typical angiography, and typical histopathological features. All three features are mandatory to confirm a “definitive” diagnosis of BD. The conundrum is—what features should be considered typical of BD angiography? According to this review, segmental occlusion of infrapopliteal arteries, corkscrew collaterals that appear to continue the occluded arterial segment (Martorell’s sign) or bypass the segmental occlusion, absence of atherosclerotic plaque or aneurysm could differentiate BD from ASO. Hence, for “typical” BD angiography, these manifestations should certainly be considered. However, data for differentiating angiography patterns of BD from the small- and medium-sized vasculitis including Behcet’s disease, scleroderma, hepatitis associated vasculitis, and anti-phospholipid syndrome are limited. Further studies for investigating the angiography pattern in BD patients in early and late presentation of BD, particularly in the patients with long-term follow up, are highly recommended. Full article

Forest fires in the Hindu Kush Himalaya (HKH) region are increasing in frequency and severity, driven by climate variability, prolonged dry periods, and human activity. Nepal, a critical part of the HKH, recorded over 22,700 forest fire events in the past decade, with fire incidence nearly doubling in 2023. Despite this growing threat, operational early warning systems remain limited. This study presents Nepal’s first high-resolution early fire risk outlook system, developed by adopting the Canadian Fire Weather Index (FWI) using meteorological forecasts from the High-Impact Weather Assessment Toolkit (HIWAT). The system generates daily and two-day forecasts using a fully automated Python-based workflow and publishes results as Web Map Services (WMS). Model validation against MODIS, VIIRS, and ground fire records for 2023 showed that over 80% of fires occurred in zones classified as Moderate to Very High risk. Spatiotemporal analysis confirmed fire seasonality, with peaks in mid-April and over 65% of fires occurring in forested areas. The system’s integration of satellite data and high-resolution forecasts improves the spatial and temporal accuracy of fire danger predictions. This research presents a novel, scalable, and operational framework tailored for data-scarce and topographically complex regions. Its transferability holds substantial potential for strengthening anticipatory fire management and climate adaptation strategies across the HKH and beyond. Full article

This study assesses habitat suitability and identifies conservation priority areas for the endangered Marco Polo sheep throughout Khunjerab National Park (Pakistan) and Tashkurgan Natural Reserve (China). We analyzed species occurrence records against environmental variables (elevation, slope, climate, land cover) using MaxEnt modeling. Model performance was validated through AUC-ROC analysis and response curves, generating spatial predictions of suitable habitats to inform conservation strategies. Spatial predictions were generated to map potential distribution zones, aiding conservation planning for this endangered species. The model’s predictive performance was evaluated using the Area Under the Curve (AUC) of the Receiver Operating Characteristic curve, yielding an AUC of 0.919, indicating strong discriminatory capability. Elevation (43.9%), slope (25.9%), and September precipitation (15.9%) emerged as the most influential environmental predictors, collectively contributing 85.7% to the model. The total percentage contribution and permutation significance values were 98.6% and 77.8%, respectively. Jackknife analysis identified elevation (bio-1), slope (bio-7), hillshade (bio-2), and the maximum July temperature (bio-9) as the most significant factors influencing the distribution of Marco Polo sheep, Conversely, variables such as viewshade (bio-14), land cover (bio-3), and precipitation in August (bio-4) contributed a minimal gain, suggesting that they had little impact on accurately predicting species distribution. The habitat suitability map reveals varying conditions across the study area, with the highest suitability (yellow zones) found in the northern and western regions, particularly along the Wakhan Corridor ridgelines. The southern regions, including Khunjerab Pass, show predominantly low suitability, marked by purple zones, suggesting poor habitat conditions. The eastern region displays moderate to low suitability, with fragmented patches of green and yellow, indicating seasonal habitats. The survival of transboundary Marco Polo sheep remains at risk due to poaching activities and habitat destruction and border fence barriers. This study recommends scientific approaches to habitat restoration together with improved China–Pakistan cooperation in order to establish sustainable migratory patterns for this iconic species. Full article

The elongated tortoise (Indotestudo elongata), a Critically Endangered (CR) species, faces numerous threats across its range. Yet, the ecological and anthropogenic factors affecting its conservation in fragmented habitats remain poorly understood. This study integrated field surveys and community questionnaires to assess the distribution drivers and local perceptions, such as attitudes, knowledge, conservation practices, and perceived threats, in the Jalthal Forest, one of the last remnants of suitable habitat for the elongated tortoise in eastern Nepal. Using ArcMap, we established 138 randomly selected grids (500 m × 500 m) to evaluate the environmental covariates of tortoise occurrence and anthropogenic pressures. Generalized linear models revealed that tortoise occurrence was negatively associated with dense ground cover (β = −3.50, p = 0.017) and human disturbance (β = −8.11, p = 0.019). Surveys of local residents from community forest user groups (n = 236 respondents) indicated strong local support for tortoise conservation (69% willing to protect the species). Despite this, the respondents identified persistent threats, including hunting for bushmeat and traditional medicine (74%), habitat degradation (65%), and forest fires. While 60% of the respondents recognized the threatened species status, significant knowledge gaps regarding that status and ongoing illegal exploitation persisted. These findings underscore the need for targeted habitat management, reduced anthropogenic pressures, and community-led initiatives to align local attitudes with conservation actions. This study provides critical baseline data for conserving the elongated tortoise in human-modified landscapes and emphasizes the necessity of integrated ecological and socio-cultural strategies for its long-term survival. Full article

Dengue has been a serious public health concern in Nepal since the past few years, with concurrent big outbreaks occurring in 2022–2024. This cross-sectional study was conducted among febrile patients visiting hospitals in Mahottari district in southern Nepal. A total of 2141 dengue-suspected patients were investigated by routine laboratory assays and serological and molecular techniques, including real-time quantitative polymerase chain reaction (RT-qPCR). Among them, 455 (21.3%) were confirmed as dengue cases. The majority of dengue cases (435, 95.6%) had a primary dengue infection. The total bilirubin level was significantly higher in secondary dengue infection than in primary (p = 0.032). The major dengue virus (DENV) serotypes responsible for this outbreak were DENV-1 (45.5%) and DENV-2 (40.9%), while 13.6% patients had DENV-3 infection. DENV-3 infection showed a significantly higher viral load (median: 7.71 Log₁₀ copies/mL; range: 6.48–7.94) compared to DENV-1 (6.72 Log₁₀ copies/mL; 5.49–7.17) and DENV-2 (4.76 Log₁₀ copies/mL; 2.32–6.96). Adult patients exhibited a significantly higher viral load than children (p = 0.035). NS1- and IgM-positive as well as admitted patients had a higher viral load (p < 0.05). Co-circulation of multiple serotypes (DENV-1, -2, -3) was confirmed with the first introduction of DENV-1 and DENV-3 in Mahottari and surrounding areas in the 2023 outbreak. Identification of the circulating DENV serotypes is crucial to understanding the epidemiological trend and dynamics of population immunity. These findings underscore the need of nation-wide integrated surveillance, including genomic data generation, in Nepal for disease control, prevention, and potential vaccine implication. Full article

Introduction: Pediatric prosthetic knee joints must be appropriately scaled from adult designs to ensure proper gait biomechanics. However, direct dimensional scaling without considering the biomechanical implications may lead to functional discrepancies. This study aimed to evaluate whether using a linear scaling factor can effectively adapt a knee for pediatric use. The study assessed whether such an approach yields a viable pediatric prosthetic knee joint by applying a fixed scaling factor and analyzing the resultant knee geometry. Methods: The linear scaling factor was determined based on the pylon tube diameter, a key constraint in compact pediatric knee design. Given a pediatric pylon diameter of 22 mm, the length of the tibial link was set to 22 mm, yielding a scaling factor of 0.6875 when compared to the adult-sized knee. This scaling factor was used to determine the dimensions of the pediatric four-bar (scaled) knee joint. Static geometric analysis was conducted using GeoGebra^® to model the lower-body segment lengths. The knee joint’s performance was evaluated based on stance and swing phase parameters. These metrics were compared between the scaled knee and a commercial pediatric knee. Results: The geometric analysis revealed that while using the linear scaling factor maintained proportional relationships, certain biomechanical parameters deviated from the expected pediatric norms. The scaled knee achieved a toe clearance of 13.5 mm compared to 19.7 mm in the commercial design and demonstrated a swing-phase heel clearance of 11.6 mm versus 13.3 mm, maintaining negative x/y ratios at heel contact and showing significant stability in push-off moments, while the stance flexion angle remained within an acceptable range. The heel contact and push-off ratios (x/y) were found to be comparable, with the scaled model achieving values of −1.21 and −0.59, respectively. The stance flexion angle measured 10.6°, closely aligning with the commercial reference. Conclusions: Using a linear scaling factor provides a straightforward method for adapting adult prosthetic knee designs to pediatric use. However, deviations in key biomechanical parameters indicate that further experimental study may be required to validate the applicability of the scaled knee joint for pediatric users. Future work should explore dynamic simulations and experimental validations to refine the design further and ensure optimal gait performance. Full article

The Internet of Things (IoT) has enabled the development of various applications for energy, exploiting unprecedented data collection, multi-stage data processing, enhanced awareness, and control of the physical environment. In this context, the availability of tools for efficient development is paramount. This paper explores and validates the use of a generic, flexible, open-source measurement-oriented data collection framework for the energy field, namely Measurify, in the Internet of Things (IoT) context. Based on a literature analysis, we have spotted three domains (namely, vehicular batteries, low voltage (LV) test feeder, and home energy-management system) and defined for each one of them an application (namely: range prediction, power flow analysis, and appliance scheduling), to verify the impact given by the use of the proposed IoT framework. We modeled each one of them with Measurify, mapping the energy field items into the abstract resources provided by the framework. From our experience in the three applications, we highlight the generality of Measurify, with straightforward modeling capabilities and rapid deployment time. We thus argue for the importance for practitioners of using powerful big data management development tools to improve efficiency and effectiveness in the life-cycle of IoT applications, also in the energy domain. Full article

Elsholtzia blanda (Benth.) Benth. (EBB) is a traditional plant in Nepal with bioactive properties, including antioxidant, cytotoxic, and antitumor activities. In this study, a methanol EBB extract was tested to evaluate the anti-inflammatory effect against lipopolysaccharide (LPS)-induced microglial (BV2) cells. EBB effectively suppressed LPS-induced nitric oxide production and inhibited the secretion of proinflammatory cytokines such as tumor necrosis factor-alpha (TNF-α) and interleukin (IL)-6. In LPS-stimulated BV2 cells, EBB significantly inhibited inducible nitric oxide synthase (iNOS), TNF-α, IL-6, IL-1β, IL-8, IL-18, and IL-10 mRNA expression in a concentration-dependent manner. In particular, EBB significantly reduced the protein expression of iNOS and cyclooxygenase-2, which were upregulated by LPS. Further, EBB could alleviate the inflammatory response in microglia by suppressing the phosphorylation of mitogen-activated protein kinases. EBB also attenuated LPS-induced reactive oxygen species (ROS) in BV2 cells. In addition, EBB enhanced heme oxygenase-1 (HO-1) protein and mRNA expression. The present results show that an EBB extract could effectively suppress the neuroinflammatory response induced by LPS in BV2 cells. Accordingly, an EBB extract is a promising preventive agent against diseases involving neuroinflammatory responses. Full article