Search Results (570)

Cholangiocarcinoma (CCA) is highly prevalent in the Greater Mekong sub-region, especially northeastern Thailand, where infection with the liver fluke Opisthorchis viverrini is a major etiological factor. Limited therapeutic options and the absence of reliable early diagnosis tools impede effective disease control. Atractylodes lancea (Thunb.) DC.—long used in Thai and East Asian medicine, contains atractylodin (ATD), a potent bioactive compound with anticancer potential. Here, we developed ATD-loaded poly(lactic co-glycolic acid) nanoparticles (ATD PLGA NPs) and evaluated their antitumor efficacy against CCA. The formulated nanoparticles had a mean diameter of 229.8 nm, an encapsulation efficiency of 83%, and exhibited biphasic, sustained release, reaching a cumulative release of 92% within seven days. In vitro, ATD-PLGA NPs selectively reduced the viability of CL-6 and HuCCT-1 CCA cell lines, with selectivity indices (SI) of 3.53 and 2.61, respectively, outperforming free ATD and 5-fluorouracil (5-FU). They suppressed CL-6 cell migration and invasion by up to 90% within 12 h and induced apoptosis in 83% of cells through caspase-3/7 activation. Micronucleus assays showed lower mutagenic potential than the positive control. In vivo, ATD-PLGA NPs dose-dependently inhibited tumor growth and prolonged survival in CCA-xenografted nude mice; the high-dose regimen matched or exceeded the efficacy of 5-FU. Gene expression analysis revealed significant downregulation of pro-tumorigenic factors (VEGF, MMP-9, TGF-β, TNF-α, COX-2, PGE₂, and IL-6) and upregulation of the anti-inflammatory cytokine IL-10. Collectively, these results indicate that ATD-PLGA NPs are a promising nanotherapeutic platform for targeted CCA treatment, offering improved anticancer potency, selectivity, and safety compared to conventional therapies. Full article

Agrarian women are at the forefront of rural livelihoods increasingly affected by the frequency and severity of climate change impacts. However, their household livelihood resilience (HLR) remains limited due to gender-blind policies, scarce sex-disaggregated data, and inadequate consideration of gender-specific needs in resilience-building efforts. Grounded in participatory feminist research, this study employed a multi-method qualitative approach, including semi-structured interviews and oral history narratives, with 60 women in two climate-vulnerable provinces. Data were analyzed through thematic coding, CATWOE (Customers, Actors, Transformation, Worldview, Owners, Environmental Constraints) analysis, and descriptive statistics. The findings identify nine major climate-related events disrupting livelihoods and reveal a limited understanding of HLR as a long-term, transformative concept. Adaptation strategies remain short-term and focused on immediate survival. Barriers to HLR include financial constraints, limited access to agricultural resources and technology, and entrenched gender norms restricting women’s leadership and decision-making. While local governments, women’s associations, and community networks provide some support, gaps in accessibility and adequacy persist. Participants expressed the need for financial assistance, vocational training, agricultural technologies, and stronger peer networks. Strengthening HLR among agrarian women requires gender-sensitive policies, investment in local support systems, and community-led initiatives. Empowering agrarian women as agents of change is critical for fostering resilient rural livelihoods and achieving inclusive, sustainable development. Full article

As a key tropospheric photochemical pollutant, ground-level ozone (O₃) poses significant threats to ecosystems through its strong oxidative capacity. With China’s rapid industrialization and urbanization, worsening O₃ pollution has emerged as a critical environmental concern. This study examines O₃’s impacts on forest ecosystems in Southwestern China (Yunnan, Guizhou, Sichuan, and Chongqing), which harbors crucial forest resources. We analyzed high-resolution monitoring data from over 200 stations (2019–2023), employing spatial interpolation to derive the regional maximum daily 8 h average O₃ (MDA8-O₃, ppb) and accumulated O₃ exposure over 40 ppb (AOT40) metrics. Through AOT40-based exposure–response modeling, we quantified the forest relative yield losses (RYL), economic losses (ECL) and ECL/GDP (GDP: gross domestic product) ratios in this region. Our findings reveal alarming O₃ increases across the region, with a mean annual MDA8-O₃ anomaly trend of 2.4% year⁻¹ (p < 0.05). Provincial MDA8-O₃ anomaly trends varied from 1.4% year⁻¹ (Yunnan, p = 0.059) to 4.3% year⁻¹ (Guizhou, p < 0.001). Strong correlations (r > 0.85) between annual RYL and annual MDA8-O₃ anomalies demonstrate the detrimental effects of O₃ on forest biomass. The RYL trajectory showed an initial decline during 2019–2020 and accelerated losses during 2020–2023, peaking at 13.8 ± 6.4% in 2023. Provincial variations showed a 5-year averaged RYL ranging from 7.10% (Chongqing) to 15.85% (Yunnan). O₃ exposure caused annual ECL/GDP averaging 4.44% for Southwestern China, with Yunnan suffering the most severe consequences (ECL/GDP averaging 8.20%, ECL averaging CNY 29.8 billion). These results suggest that O₃-driven forest degradation may intensify, potentially undermining the regional carbon sequestration capacity, highlighting the urgent need for policy interventions. We recommend enhanced monitoring networks and stricter control methods to address these challenges. Full article

Gastrointestinal (GI) parasitic infections in non-human primates are of growing concern due to their implications for both veterinary and public health. Long-tailed macaques (Macaca fascicularis), commonly found in peri-urban and temple environments in Southeast Asia, may act as reservoirs for zoonotic parasites, posing risks to humans and domestic animals. This study investigated the prevalence and species diversity of GI parasites in free-ranging macaques from four provinces in Northeast Thailand (Loei, Khon Kaen, Bueng Kan, and Sisaket). A cross-sectional study was conducted between April and May 2025. A total of 445 fecal samples were examined using two parasitological techniques: agar plate culture (APC) and the formalin–ethyl acetate concentration technique (FECT). The overall prevalence of parasitic infection was 86.5%, with Strongyloides sp. (65.2%) as the most prevalent helminth and Balantioides coli-like (29.5%) and Entamoeba histolytica-like (28.8%) as the predominant protozoa. Other parasites identified included helminths (Trichuris sp., Ascaris sp.) and protozoa (Blastocystis sp., Iodamoeba bütschlii, Entamoeba coli, and Chilomastix mesnili). Mixed infections were frequently observed, with both helminths and protozoa co-occurring in 37.3% of cases. The high infection rates and parasite diversity reflect substantial environmental contamination and sustained transmission cycles. These findings underscore the importance of integrated surveillance in wildlife populations and the need for One Health-based approaches to minimize zoonotic transmission risks at the human–animal–environment interface. Full article

The booming nature rubber industry has contributed to the extensive expansion of rubber plantations in the Lancang-Mekong River Basin over recent decades. To date, limited research has focused on the assessment of soil erosion caused by this expansion, resulting in a knowledge gap in the systematic and quantitative understanding of its ecological and hydrological impacts. This study evaluates soil erosion within rubber plantations and changes associated with their expansion by modifying the Revised Universal Soil Loss Equation (RUSLE) model in the middle section of the Lancang-Mekong River Basin from 2003 to 2022. The results show that: (1) rubber plantations have expanded rapidly, reaching a total area of 70.391 × 10⁴ ha; (2) over the 20-year period, soil erosion trends within rubber plantations show both slight aggravation (affecting 45.377% of the area) and slight mitigation (affecting 35.859% of the area); (3) soil erosion in rubber plantations shows a pattern of decreasing, then increasing, and then decreasing again with stand age, with the lowest erosion (0.693 t·ha⁻¹·yr⁻¹) observed in plantations aged 10–15 years and the highest (1.017 t·ha⁻¹·yr⁻¹) in those aged 15–20 years; (4) rubber plantation expansion led to a fivefold increase in soil erosion with an average soil loss of 0.148 t·ha⁻¹·yr⁻¹ in the non-expansion areas and 0.902 t·ha⁻¹·yr⁻¹ in expansion areas; and (5) slope had the most significant impact on soil erosion. Interactions between slope and other factors —especially slope and soil type (Q > 0.777)—consistently demonstrated strong explanatory power. This research provides valuable insights for the assessment and management of soil erosion in rubber plantations. Full article

In Vietnam, English proficiency is a graduation requirement and offers students great opportunities to win scholarships and employability after graduation. Universities in the Mekong Delta region (MDR) often face challenges in foresting students’ English proficiency despite continuous assistance offered. Although students have taken online supplementary courses (OSC) delivered through e-learning systems to support their English formal classes for several years, students’ successes in English tests with such supplementary courses and the predictors of this issue remain unknown. Therefore, we developed a model to predict students’ success in English final tests based on behaviors and grades in OSC using logistic regression (LR) and classification and regression tree (CART) classifiers. A total of 109 students of OSC in a target university in MDR participated in this study, and the result showed that CART (area under the curve (AUC) = 89.3%) was slightly better than LR. The outcomes of this study contribute to students’ success in English tests and the enhancement of the effectiveness of online supplementary courses for English improvements. Full article

The Mekong Delta, an important agricultural and economic hub in Vietnam, has suffered from severe water quality issues caused by both natural and anthropogenic forces. This paper aims to conduct a rational statistical approach to evaluate the current situation of surface water quality in the Mekong Delta, applying Factor Analysis (FA), Principal Component Analysis (PCA), and Agglomerative Hierarchical Clustering (AHC) to a database of 3117 samples collected by national and provincial monitoring stations. The results revealed significant contamination with organic pollutants (BOD5: 3.50–172.870 mg/L, COD: 6.493–472.984 mg/L), pesticides (e.g., DDTs: n.d to 1.227 mg/L), trace metals (As: 0.006–0.046 mg/L, Cr: n.d–1.960 mg/L), and microbial indicators (Coliforms: n.d–45,100 MPN/100 mL), often higher than the WHO drinking water threshold. PCA/AHC analysis identified the following five major pollution components: (1) organic pollution and sewage/industrial and deposited chemicals (PCA1—23.08% variance); (2) pesticide and agricultural runoff derived contamination with Hg (PCA2—15.44%); (3) microbial pollution of the water was found to correlate positively with Zn and Cu content (PCA3—8.90%); (4) salinity was found to mobilize As and Cr (PCA4—8.00%); (5) nutrient/microbial pollution presumably from agricultural and sewage inputs (PCA5—7.22%). AHC showed some spatial variability that grouped samples in urban/industrial (Cluster 1), rural/agricultural (Cluster 2), and a highly contaminated one, where water was toxic and presented with microbial and Cd contamination (Cluster 3). Levels of pesticides, Cr, and microbial pollution were higher than reported in previous Mekong Delta studies and exceeded regional trends. These results emphasize the importance of holistic water management strategies, including better wastewater treatment, pesticide control, sustainable farming, and climate-adaptive measures to reduce saltwater intrusion and safeguard drinking water quality for the Mekong Delta. Full article

Accurate and reliable short-term electricity load forecasting plays an important role in ensuring the healthy operation of the power grid and promoting sustainable socio-economic development. This research proposes a novel hybrid load probability prediction model, BiGRU-GAM-GPR, which combines a bidirectional gated recurrent unit (BiGRU), global attention mechanism (GAM), and Gaussian process regression (GPR). Firstly, BiGRU-GAM is used to predict the sequence to obtain preliminary prediction results, and then these results are input into GPR to obtain more accurate deterministic and probabilistic prediction results. To verify the effectiveness of the proposed model, a series of experiments are conducted on three real-world power load datasets. The experimental results show the following: (1) BiGRU has the optimal forecasting ability compared with the other basic models. (2) The global attention mechanism improves the model’s perception ability of the spatial features of multi-feature sequences and plays a positive role in enhancing the model’s forecasting performance. (3) The GPR model further explores the internal relationships of the data by expanding the deterministic prediction results into probabilistic results, thus improving the forecasting effect. (4) The proposed model BiGRU-GAM-GPR exhibits the best performance in both deterministic and probabilistic forecasting and has good robustness. Full article

Methane (CH₄) is a potent greenhouse gas with a significant impact on short- and medium-term climate forcing, and its atmospheric concentration has been increasing rapidly in recent decades. This study aims to analyze spatio-temporal patterns of atmospheric methane concentrations between 2019 and 2025, focusing on comparisons between regions characterized by high and low emission intensities. Level-3 XCH₄ data from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite were used, which were aggregated into seasonal and annual composites. High-emission regions, such as the Mekong Delta, Nile Delta, Eastern Uttar Pradesh and Bihar, Central Thailand, Lake Victoria Basin, and Eastern Arkansas, were contrasted with low-emission areas including Patagonia, the Mongolian Steppe, Northern Scandinavia, the Australian Outback, the Sahara Desert, and the Canadian Shield. The results show that high-emission regions exhibit substantially higher seasonal amplitude in XCH₄ concentrations, with an average seasonal variation of approximately 30.00 ppb, compared to 17.39 ppb in low-emission regions. Methane concentrations generally peaked at the end of the year (Q4) and reached their lowest levels during the first half of the year (Q1 or Q2), particularly in agriculturally dominated regions. Principal component and cluster analyses further confirmed a strong spatial differentiation between high- and low-emission regions based on both temporal trends and seasonal behavior. These findings demonstrate the potential of satellite remote sensing to monitor regional methane dynamics and highlight the need for targeted mitigation strategies in major agricultural and wetland zones. Full article

Canine distemper virus (CDV) is a highly contagious pathogen and causes a fatal systemic disease in domestic dogs and wild carnivores worldwide. Despite CDV infections being monitored globally, studies on CDV in Vietnam seem to be limited. This study, therefore, investigated the epidemiological, clinical, and molecular characteristics of CDV in the Mekong Delta (MD) region of Vietnam. A total of 6687 ocular/nasal swabs were collected from CDV-suspected dogs across seven cities/provinces. CDV infection was detected in 6.19% (414 dogs) of suspected dogs using a commercially available rapid kit, with infection associated with age, roaming status, and vaccination status. Hematological and blood biochemical analysis of CDV-infected dogs revealed anemia, leukopenia, neutrophilia, thrombocytopenia, a slight increase in aspartate aminotransferase (AST) levels, and a significant increase in blood urea nitrogen (BUN) levels. Molecular characterization of partial hemagglutinin (H) and fusion (F) genes exhibited high nucleotide and amino acid homology with the Asia-1 genotype. Phylogenetic analysis confirmed that the field sequences were clustered into the Asia-1 genotype together with the neighboring countries. These findings provide important insights into the current epidemiological, clinical, and molecular features of CDV circulating in Vietnam. Full article

The Ca Mau Peninsula (CMP), the southernmost region of the Mekong Delta, is increasingly threatened by groundwater salinization, posing severe risks to both the freshwater supply and land sustainability. This study develops a three-dimensional, density-dependent groundwater flow and salinity transport model to investigate salinization dynamics across the CMP’s complex multi-aquifer system. Unlike previous studies that largely rely on model calibration, this research introduces a novel approach by systematically deriving the spatial distribution of longitudinal dispersivity based on sediment characteristics. Moreover, detailed land use mapping is integrated to assign spatially and temporally variable Total Dissolved Solids (TDS) values to the uppermost layers, thereby enhancing the model realism in areas where monitoring data are limited. The model was utilized not only to simulate the regional salinity evolution, but also to critically evaluate conceptual hypotheses related to the mechanisms driving groundwater salinization. Results reveal a strong influence of seasonal and land use factors on salinity variability in the upper aquifers, while deeper aquifers remain largely stable, affected primarily by paleosalinity and localized pumping. This integrated modeling approach contributes to a better understanding of regional-scale groundwater salinization and highlights both the potential and the limitations of numerical modeling under data-scarce conditions. The findings provide a valuable scientific basis for adaptive water resource management in vulnerable coastal zones. Full article

Graduate employability remains a crucial challenge for higher education institutions, especially in developing economies. This study investigates the key academic and vocational factors influencing early employment outcomes among recent graduates at a public university in Vietnam’s Mekong Delta region. By leveraging predictive analytics, the research explores how data-driven approaches can enhance career readiness strategies. The analysis employed AI-driven models, particularly classification and regression trees (CARTs), using a dataset of 610 recent graduates from a public university in the Mekong Delta to predict early employability. The input factors included gender, field of study, university entrance scores, and grade point average (GPA) scores for four university years. The output factor was recent graduates’ (un)employment within six months after graduation. Among all input factors, third-year GPA, university entrance scores, and final-year academic performance are the most significant predictors of early employment. Among the tested models, CARTs achieved the highest accuracy (93.6%), offering interpretable decision rules that can inform curriculum design and career support services. This study contributes to the intersection of artificial intelligence and vocational education by providing actionable insights for universities, policymakers, and employers, supporting the alignment of education with labor market demands and improving graduate employability outcomes. Full article

Background: Vietnam has made significant strides in reducing the prevalence of HIV infection and achievements in its antiretroviral treatment program. However, the COVID-19 pandemic and financial challenges in the healthcare system have posed significant obstacles to maintaining effective HIV treatment and monitoring, particularly among vulnerable populations. This study aims to evaluate the situation of HIV drug resistance among patients who have experienced treatment failure in the Mekong Delta region and to compare data from 2019 to 2022. Methods: The study material was blood plasma samples from HIV-infected individuals with ART failure: 316 collected in 2019 and 326 collected in 2022. HIV-1 genotyping and mutation detection were performed based on an analysis of the nucleotide sequences of the Pol gene region. A total of 116 HIV-infected individuals with virological failure in 2019 and 2022 were assessed for HIV drug resistance. Results: The study revealed a high proportion of participants with viral loads exceeding 1000 copies/mL, significantly increasing from 12.0% in 2019 to 23.9% in 2022 (OR = 2.3; p = 0.0001). HIV drug resistance mutations were detected in 84.21% of cases in 2019 and 92.59% in 2022. The prevalence of concurrent resistance to NRTIs and NNRTIs was 37.5% and 30.13% in 2019 and 2022, respectively. There was a statistically significant decrease in NNRTI resistance (OR = 0.32, χ² = 5.43, p < 0.05). In contrast, multi-drug resistance to protease inhibitors rose from 18.52% to 45.21% (φ* = 0.00403, p < 0.05). Triple-class resistance was identified only in 2022 (17.81%). The most common mutations included M184I/V, D67N, K103N, Y181C, and V82A/S/T, with D67N rising significantly from 3.13% to 21.92%. The predominant subtype was CRF01_AE. Conclusion: A high prevalence of viral non-suppression and HIV drug resistance was observed among patients in the Mekong Delta region, particularly after the onset of the COVID-19 pandemic. Our study highlights the ongoing challenges that the HIV/AIDS treatment program in Vietnam must address in the post-pandemic period to sustain its success and achieve the goals of the country’s HIV prevention strategies. Full article

This study evaluates the performance of CMIP6 models in simulating drought characteristics in the Mekong region, including drought duration, intensity, and severity, using the SPI and SPEI indices. The results show that CMIP6 models are capable of accurately reproducing past drought conditions, with a high agreement between model data and actual data from ERA5. This study projects that future droughts will become more prolonged and severe which could lead to long-term agricultural and hydrological droughts tending to increase. In the SSP585 scenario, drought intensity will increase sharply in the southern and central regions by the end of the century. The SSP245 and SSP585 climate scenarios have distinct differences in drought trends, with SSP245 showing a strong drought trend, while SSP585 indicates a potential increase in precipitation. The SPEI indices show a clear improvement in wet conditions, with the highest drought variability in zone 2 and stable trends across scenarios. Ecosystems influence drought impacts and management needs. These results highlight the importance of accurately assessing drought characteristics to develop effective water resource and agricultural management measures, especially in the context of climate change. However, this study also points out some limitations, including the imperfect accuracy in future projections and the use of only SPI and SPEI indices without combining them with other indices which may reduce the comprehensiveness of drought impact assessment. This requires future studies to improve and expand to overcome the above limitations, thereby enhancing the reliability of drought forecasts and water resource management strategies. Full article

Land use and land cover (LULC) in coastal areas is critical in shaping the ecological systems, regional economy, and livelihood of indigenous communities. This study analyzes LULC changes (LULCC) in Soc Trang Province, Vietnam Mekong Delta, from 2010 to 2020 and simulates future LULC for 2030 under four scenarios: natural growth (business as usual, BAU), climate change challenges, profit optimization, and adaptation strategies. Satellite-based LULC maps and geospatial datasets were integrated into a LULC simulation model based on a Markov Chain and Cellular Automata to predict LULC in 2030 under disparate scenarios. Simultaneously, this study also estimates economic values and ecosystem service values as proxies to evaluate benefits and trade-offs between the scenarios. The research findings reveal that the critical LULCC observed during 2010–2020 are transitions from triple rice crops to double rice crops, rice–shrimp to brackish aquaculture, and expansion of perennial plantations. These transitional trends will persist at a modest rate under the BAU scenario in 2030. The climate change challenge scenario will intervene up to 24.2% of the total area, with double rice crops reaching the most extensive area compared to other scenarios, about 106,047 ha. The profit optimization scenario will affect 16.03% of the total area, focusing on aquaculture expansion to the maximum shared proportion of 34% (approximately 57,000 ha). Adaptive solutions will emphasize reducing triple rice crops while expanding double rice crops and reviving rice–shrimp to different extents depending on development pathways. Economic evaluations show a growth trend across scenarios, with maximum returns under profit optimization. Yet, ecosystem service values notably highlight ecological trade-offs, raising concerns about balancing economic benefits and ecological trade-offs in land use planning. The research findings recommend a comprehensive and multitarget approach to land use planning that integrates ecosystem services into initial assessments to balance benefits and trade-offs in coastal areas commonly affected by LULCC. By adopting well-informed and strategic land use plans that minimize ecological and social impacts, local sustainability and resilience to climate change can be significantly enhanced. Full article