Search Results (225)

Soil-transmitted helminths (STHs) and Herpes Simplex Virus type 2 (HSV-2) are highly prevalent infections with overlapping distribution, particularly in resource-poor regions. STH/HSV-2 co-infections may impact female reproductive health. However, many aspects of STH/HSV-2 co-infections, including the role of microRNAs (miRNAs) in regulating female genital tract (FGT) immunity and their potential contribution to pathologies such as chronic inflammation, impaired mucosal defense, and reproductive tract cancers remain unclear. In this study we investigated the miRNA expression profiles in murine FGT tissues following single or co-infection with Nippostrongylus brasiliensis (Nb) and HSV-2 and explored predicted miRNA-mRNA targets and pathways. An analysis of miRNA sequencing data was conducted to determine differentially expressed (DE) miRNAs between infected FGT tissues and uninfected controls. Ingenuity Pathway Analysis was conducted to predict the immune-related target genes of the DE miRNAs and reveal enriched canonical pathways, top diseases, and biological functions. Selected representative DE miRNAs were validated using RT-qPCR. Our results showed a total of eight DE miRNAs (mmu-miR-218-5p, mmu-miR-449a-5p, mmu-miR-497a-3p, mmu-miR-144-3p, mmu-miR-33-5p, mmu-miR-451a, mmu-miR-194-5p, and mmu-miR-192-5p) in the comparison of Nb-infected versus uninfected controls; nine DE miRNAs (mmu-miR-451a, mmu-miR-449a-5p, mmu-miR-144-3p, mmu-miR-376a-3p, mmu-miR-192-5p, mmu-miR-218-5p, mmu-miR-205-3p, mmu-miR-103-3p, and mmu-miR-200b-3p) in the comparison of HSV-2-infected versus uninfected controls; and one DE miRNA (mmu-miR-199a-5p) in the comparison of Nb/HSV-2 co-infected versus uninfected controls (p-value < 0.05, |logFC| ≥ 1). Core expression analysis showed that, among other canonical pathways, the DE miRNAs and their predicted mRNA targets were involved in neutrophil degranulation, interleukin-4 and interleukin-13 signaling, natural killer cell signaling, interferon alpha/beta signaling, and ISGylation. Additionally, cancer was predicted as one of the significantly enriched diseases, particularly in the co-infected group. This is the first study to provide insights into the FGT miRNA profiles following Nb and HSV-2 single and co-infection, as well as the predicted genes and pathways they regulate, which may influence host immunity and pathology. This study highlights the role of miRNAs in regulating FGT immunity and pathology in the context of STH/HSV-2 co-infection. Full article

This study investigates how three technical factors—steering wheel tilt, torque, and cabin vibration frequency—affect driver posture. Heavy-truck drivers often suffer from musculoskeletal disorders (MSDs), mainly due to poor cabin ergonomics and prolonged postures during work. In countries like Ecuador, making major structural changes to cabin design is not feasible. These factors were identified through video analysis and surveys from drivers at two Ecuadorian trucking companies. An experimental system was developed using a simplified cabin to control these variables, while posture and muscle activity were recorded in 16 participants using motion capture, inertial sensors, and electromyography (EMG) on the upper trapezius, middle trapezius, triceps brachii, quadriceps muscle, and gastrocnemius muscle. The test protocol simulated key truck-driving tasks. Data were analyzed using ANOVA (${\displaystyle p<0.05}$), with technical factors and mass index as independent variables, and posture metrics as dependent variables. Results showed that head mass index significantly affected head abduction–adduction (${\displaystyle -}$8.12 to ${\displaystyle -}$2.18°), and spine mass index influenced spine flexion–extension (${\displaystyle -}$0.38 to 6.99°). Among technical factors, steering wheel tilt impacted trunk flexion–extension (${\displaystyle -}$13.56 to 16.99°) and arm rotation (${\displaystyle -}$31.1 to 19.7°). Steering wheel torque affected arm rotation (${\displaystyle -}$30.49 to ${\displaystyle -}$6.77°), while vibration frequency influenced forearm flexion–extension (3.76 to 16.51°). EMG signals showed little variation between muscles, likely due to the protocol’s short duration. These findings offer quantitative support for improving cabin ergonomics in low-resource settings through targeted, cost-effective design changes. Full article

As an important unconventional oil and gas resource, tight oil exploration and development is of great significance to ensure energy supply under the background of continuous growth of global energy demand. Low-porosity and low-permeability reservoirs are characterized by tight rock properties, poor physical properties, and complex pore structure, and as a result the fine calculation of logging reservoir parameters faces great challenges. In addition, the crude oil in this area has high viscosity, the formation water salinity is low, and the oil reservoir resistivity shows significant spatial variability in the horizontal direction, which further increases the difficulty of oil and water reservoir identification and affects the accuracy of oil saturation calculation. Targeting the above problems, the Nutcracker Optimization Algorithm (NOA) was used to optimize the hyperparameters of the random forest classification model, and then the optimal hyperparameters were input into the random forest model, and the conventional logging curve and oil test data were combined to identify and classify the reservoir fluids, with the final accuracy reaching 94.92%. Compared with the traditional Hingle map intersection method, the accuracy of this method is improved by 14.92%, which verifies the reliability of the model for fluid identification of low-porosity and low-permeability reservoirs in the research block and provides reference significance for the next oil test and production test layer in this block. Full article

Frequent and complex boarding operations require an effective management process for specialized tools. Traditional manual statistical analysis exhibits low efficiency, poor accuracy, and a lack of electronic records, making it difficult to meet the demands of modern aviation manufacturing. In this study, we propose an efficient and lightweight network designed for the recognition and analysis of professional tools. We employ a combination of knowledge distillation and pruning techniques to construct a compact network optimized for the target dataset and constrained deployment resources. We introduce a self-attention mechanism (SAM) for multi-scale feature fusion within the network to enhance its feature segmentation capability on the target dataset. In addition, we integrate a large language model (LLM), enhanced by retrieval-augmented generation (RAG), to analyze tool detection results, enabling the system to rapidly provide relevant information about operational tools for management personnel and facilitating intelligent monitoring and control. Experimental results on multiple benchmark datasets and professional tool datasets validate the effectiveness of our approach, demonstrating superior performance. Full article

With the advancement of integrated energy systems (IES) and the increasing penetration of variable renewable energy, IES confronts complex uncertainties that necessitate enhanced flexibility. Therefore, this study focuses on improving IES flexibility. To this end, multi-dimensional flexibility evaluation indexes for the “Source–Structure–Demand” dimensions were established, and a multi-objective optimization model considering flexibility and source–demand side uncertainties was developed. The flexibility evaluation indexes include the Grid Dependency Level (GDL) for the source side, Insufficient Flexible Resource Probability (IFRP) for the structure side, and Loss of Load Probability (LOLP) for the demand side. Moreover, considering the distinct adjustment response times and inertia of different energy flows during IES operation, thermal and electrical energy are optimized on separate time scales. Thus, the multi-objective optimization constitutes a multi-time scale, high-dimensional, non-convex nonlinear model targeting economy, flexibility, security, and low carbon emissions. This paper employs single-economy objective, single-flexibility objective, and multi-objective optimization to analyze IES configuration, operation, risk, carbon emissions, and flexibility. The results indicate that poor flexibility leads to high operational risk, while excessive pursuit of flexibility incurs high costs and destabilizes operations. By implementing this multi-objective optimization, IES flexibility is enhanced while ensuring system economic performance. It also addresses the flexibility deficiency in traditional single-economy objective optimizations. Additionally, the system increases the renewable energy absorption rate by approximately 10%. Full article

Vaginitis is a major health concern among women, with inadequate treatment potentially leading to reproductive complications. This study aimed to assess vaginitis prevalence, identify predominant pathogens, and evaluate associated risk factors among female patients at Da Nang Dermato-Venereology Hospital. A prospective study of 796 female patients undergoing physical examinations was conducted, with demographic, clinical, and microbiological data collected. Vaginitis was diagnosed in 180 (22.6%) of 796 female patients, predominantly caused by Candida spp. (66.1%) and bacterial pathogens (31.7%), with no Trichomonas vaginalis detected, and was most prevalent in women aged 20–30 years. Poor hygiene practices, including infrequent sanitary pad changes (OR = 5.01, p < 0.001) and routine vaginal douching (OR = 6.77, p < 0.001), were significantly associated with vaginitis. The Amsel criteria showed high specificity (99.1%) for bacterial vaginosis diagnosis. The absence of T. vaginalis suggests a potential shift in the epidemiology of vaginal infections. The Amsel criteria are a practical diagnostic tool in resource-limited settings. Our findings highlight the need for targeted hygiene education to reduce vaginitis prevalence in Vietnam. Full article

Background/Objectives: Ovarian and endometrial cancers present significant health burdens due to their substantial morbidity and mortality. Surgery delay is hypothesized to negatively impact patient outcomes, yet evidence remains inconsistent. This systematic review aims to comprehensively evaluate current evidence regarding the effects of treatment delay on survival and quality of life in these patients. Methods: A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, Scopus, and ClinicalTrials.gov databases, complemented by a manual screening of reference lists, with studies included up to March 2025. Two independent reviewers screened and assessed the methodological quality using the ROBINS-E tool and extracted the data from the studies. Due to substantial methodological and clinical heterogeneity, results were synthesized qualitatively through narrative synthesis. Results: Twenty-one studies met the inclusion criteria, comprising predominantly retrospective cohort analyses. Treatment delays consistently correlated with decreased survival and advanced disease stages. Among studies, optimal intervals from diagnosis to treatment were varied from 2 to 8 weeks. Patient-reported outcomes indicated heightened anxiety, increased distress, and poor satisfaction with prolonged delays. Healthcare system factors such as resource allocation, geographic disparities, and socioeconomic inequalities significantly contributed to delays. Quantitative survival metrics supported a clear negative association between treatment delays and survival, although paradoxical outcomes in select subgroups highlighted underlying complexities. Conclusions: This systematic review underscores the critical importance of minimizing delays in the treatment of ovarian and endometrial cancers to improve patient survival and psychological outcomes. Identified healthcare system barriers demand targeted policy interventions to ensure timely and equitable access to tertiary healthcare infrastructures. Future research should prioritize standardizing delay definitions to strengthen and homogenize evidence. Full article

Groundwater is a critical resource in semi-arid regions like Morocco’s Guire Basin, yet pollution and overexploitation threaten its sustainability. This study evaluates the groundwater quality of the Guire aquifer (Eastern High Atlas) using an integrated approach combining hydrochemical, isotopic (δ¹⁸O, δ²H, δ¹³C), multivariate statistical, and Geographic Information System (GIS) analyses alongside the Water Quality Index (WQI). Sixteen wells were monitored for physicochemical parameters (pH: 7–7.9; EC: 480–3004 μS/cm; BOD5: 1.03–30.5 mg/L; COD: 10.2–45.75 mg/L) and major ions, revealing widespread exceedances of Moroccan standards for Cl⁻, HCO₃⁻, Mg²⁺, Ca²⁺, and NH₄⁺. WQI classified 81% of samples as “Poor” to “Unsuitable for drinking” (WQI: 51–537), driven by elevated Cl⁻, Na⁺, and SO₄²⁻ from Triassic evaporite dissolution and NO₃⁻ (up to 45 mg/L) from agricultural runoff. Stable isotopes (δ¹⁸O: −7.73‰ to −5.08‰; δ²H: −66.14‰ to −44.20‰) indicate Atlantic-influenced recharge at 900–2200 m altitudes, with a δ¹⁸O-δ²H slope of 5.93 reflecting evaporation during infiltration. Strontium (Sr²⁺/Ca²⁺: 0.0024–0.0236) and bromide (Br/Cl: 8.47 × 10⁻⁵–9.88 × 10⁻⁴) ratios further confirm evaporitic dominance over anthropogenic contamination. This work provides actionable insights for policymakers, advocating for targeted restrictions on fertilizers, enhanced monitoring near evaporite zones, and artificial recharge initiatives. By linking geogenic/anthropogenic contamination to governance strategies, this study advances sustainable groundwater management in semi-arid regions. Full article

Carbonate geothermal reservoirs, characterized by widespread distribution, a high discharge capacity, and favorable reinjection conditions, have become a key target for geothermal resource development. However, the karst geothermal reservoir system in the Juancheng geothermal field exhibits significant heterogeneity, leading to substantial disparities in productivity among multiple geothermal wells and severely restricting efficient regional exploitation. This study systematically investigates the hydraulic characteristics and development potential of the karst geothermal reservoir in the Juancheng geothermal field using sodium fluorescein tracing experiment technology. The results reveal that the reservoir system contains multiple flow channels with distinct permeability differences. The dominant flow pathways, controlled by fault structures, exhibit an apparent velocity of up to 10.98 m/h, significantly higher than other regions in the study area. In contrast, low-permeability zones, influenced by the burial depth of the Ordovician strata, show poor connectivity due to limited karst development, with the lowest apparent velocity of only 1.03 m/h. By integrating pumping test data and tracer response characteristics, the dominant flow direction (northeast) demonstrates a stronger recharge capacity and water abundance, offering a higher development value. Conversely, the southeast low-permeability zone has weaker water production and constrained recharge conditions, resulting in a relatively limited development potential. Additionally, it is recommended that the direction of future geothermal well placement in the Juancheng geothermal field should avoid being parallel to the fault strike to prolong the thermal breakthrough arrival time. In regions with deeper Ordovician strata burial, denser well network deployment is suggested to enhance the reservoir utilization efficiency. Full article

Tuberculosis is an infectious condition caused by Mycobacterium tuberculosis, primarily targeting the pulmonary system, with the potential to disseminate to various other organs via the haematogenous pathway, ranking among the top ten causes of global mortality. Tuberculosis remains a serious public health problem worldwide. This narrative review aims to emphasise the clinical importance of the inter-relationships between nutrition, pharmacotherapy, and the most common drug–nutrient interactions in the context of tuberculosis and multi-drug-resistant tuberculosis management. Nowadays, pharmacologic approaches utilise polytherapeutic regimens that, although showing increased efficacy, prominently affect the nutritional status of patients and modify multiple metabolic pathways, thus influencing both the effectiveness of therapy and the patient outcomes. There is much evidence that antituberculosis drugs are associated with deficiencies in essential vitamins and various micronutrients, leading to serious adverse consequences. Moreover, poor nutrition exacerbates TB outcomes, and TB further exacerbates nutritional status, a vicious cycle that is particularly prevalent in low-resource environments. Nutritional support is necessary, and clinicians ought to evaluate it on a patient-by-patient basis, as empirical evidence has shown that it can improve immune recovery, decrease tuberculosis-associated morbidity, and increase adherence to therapy. However, drug–food interactions are increasingly prevalent, and patients with tuberculosis require personalised dietary and pharmacological regimens. In this context, antituberculosis treatment requires a holistic approach, based on the collaboration of the prescribing physician, pharmacist, and nutritionist, to assess the patient’s needs from a nutritional and pharmacological perspective, with the ultimate goal of decreasing mortality and improving the prognosis of patients through personalised therapies. Full article

Aberrant glycosylation is a hallmark of cancer, offering opportunities to enhance clinical decision-making and enable precise targeting of cancer cells. Nevertheless, alterations in the bladder urothelial carcinoma (BLCA) N-glycome remain poorly characterized. Here, we used in situ N-deglycosylation and mass spectrometry, revealing a marked enrichment of oligomannose-type N-glycans in non-invasive Ta tumors, which diminished with disease progression. A complementary analysis of The Cancer Genome Atlas (TCGA) transcriptomic data revealed downregulation of the key mannosidases in BLCA, suggesting a mechanistic basis for oligomannose accumulation, though this requires further validation. Then, targeted glycoproteomic profiling identified potential stage-specific carriers of oligomannoses. Exploratory functional annotation suggests stage-dependent differences among detected glycoproteins, ranging from metabolic regulation in Ta tumors to oxidative stress adaptation in muscle-invasive disease, highlighting glycosylation’s contribution to tumor progression. Furthermore, myeloperoxidase (MPO) was enriched in more aggressive stages. Spatial validation confirmed MPO overexpression in tumor-infiltrating immune cells and its correlation with oligomannose content. Importantly, high MPO expression combined with low mannosidase levels was linked to poor survival, suggesting biological relevance. This study suggests a dynamic, stage-specific N-glycome in BLCA and identifies oligomannose-bearing glycoproteins as exploratory leads for biomarker and therapeutic target discovery, providing a N-glycomic resource for further investigation towards glycan-based precision oncology. Full article

Background: Real-world data provide insights into populations underrepresented in clinical trials such as non-small-cell cancer (NSCLC) patients with brain metastases (BMs). Despite global survival improvement due to novel drug employment, their impact in resource-limited settings like Serbia remains underexplored. This study analyzes the overall survival (OS) of NSCLC patients with BMs treated in routine clinical practice, considering patient-, disease- and treatment-related factors amid restricted access to novel drugs. Methods: We retrospectively analyzed 267 NSCLC patients diagnosed with BMs from 2018 to 2022 at a single Serbian clinical center. Inclusion required histologically confirmed NSCLC, radiologically verified BMs and complete clinical data. OS was defined as the time from BM verification to death or last follow-up. Kaplan–Meier curves and Cox regression were used for survival analysis. Results: Median OS (mOS) was 5.0 months. Univariate analysis linked age < 65 years, female gender, single BM, asymptomatic BMs, ECOG PS 0–1, BM verification at diagnosis and combined systemic and local therapy to better OS. Combined therapy offered the best survival rates (mOS: 9.0 months), while best supportive care and local-only therapy both resulted in a poor mOS of 2.0 months. Immunotherapy and targeted therapy were associated with the highest mOS, outperforming chemotherapy alone (13.0 vs. 7.0 months, p < 0.001). Multivariate analysis confirmed younger age, single BM, early BM verification and combined therapy as independent predictors of improved survival. Conclusions: limited access to novel therapies remains associated with poor patient survival, highlighting the need for better global availability. Full article

The national prevalence of HIV among adults in Zimbabwe was 10.4% in 2023, while the HIV prevalence in Bulawayo Metropolitan Province was 11.7%. The country achieved the UNAIDS Fast Track goals of 95-95-95 ahead of the 2030 target, by reporting an ART coverage of 97.0% and a viral suppression rate of 95.0%. As the number of people on ART continues to grow, it is expected that the number of patients failing current first-line non-nucleoside treatment will increase. However, access to second-line treatment regimens remains very limited in resource-poor settings such as Zimbabwe. It is therefore imperative to review treatment success for persons on second-line treatment. A retrospective cohort analysis was conducted using routinely collected clinical and demographic data from 315 participants who had been on a second-line ART regimen in Bulawayo for at least six months between 2015 and 2020. Statistical analyses were conducted to identify risk factors for viral suppression using SPSS version 28. Viral suppression (68.6%) for adults was far below the target of 95%. After accounting for all other variables, baseline CD4 count (>200 c/µL) [AOR = 1.94 (1.05–3.61)], having no history of non-adherence on first-line ART [AOR = 3.88 (1.91–7.85)], drug switch within 12 months of failure [AOR = 4.13 (1.98–8.60)] and retention in care at 5 years [AOR = 6.35 (2.56–15.76)] predicted viral re-suppression. The second-line (rescue) regimen has not achieved the expected success in reversing initial viral non-suppression (due to late presentation and poor adherence), despite enhanced adherence counselling. Timely switching is effective when done within 12 months and coupled with persistent engagement in care. We recommend improved methods, such as enhanced adherence counselling for behaviour change to improve viral re-suppression rates, especially for those on with a history of poor adherence and virologic non-suppression. Full article

The mid- and long-term hydrological forecast is important for water resource management and disaster prevention. Moreover, mid- and long-term hydrological forecasts in the region with poorly observed field meteorological data are a great challenge for traditional hydrological models due to the complexity of hydrological processes. To address this challenge, a machine learning model, particularly the deep learning model (DL), provides a new tool for improving the accuracy of runoff prediction. In this study, we took the Irtysh River, one of the longest rivers in Central Asia and a well-known trans-boundary river basin with poor field meteorological observations, as an example to develop a deep learning model based on LSTM and combined with runoff decomposition by Maximal Overlap Discrete Wavelet Transform (MODWT) to process target variables for predicting monthly streamflow. We also proposed an XGBoost-SHAP (Extreme Gradient Boost-SHapley Additive Explanations) method for the identification of predictors from large-scale indices for the streamflow forecast. The results suggest that MODWT shows the robustness of runoff decomposition between the training and test period. The deep learning model combined with MODWT shows better performance than the benchmark deep learning model without MODWT illustrated by an increased NSE. The XGBoost-SHAP method well identified the nonlinear relationship between the predictors and streamflow, and the predictors determined by XGBoost-SHAP can be physically explained. Compared with the traditional mutual information method, the XGBoost-SHAP method improves the accuracy of the deep learning model for streamflow forecast. The results of this study illustrate the ability of a deep learning model for mid- and long-term streamflow forecast, and the methods we developed in this study provide an effective approach to improve the streamflow prediction in the scarcely observed catchments. Full article

Despite overall improvements in the accessibility, quality, and outcomes of care in the U.S. health care system over the last 30 years, a large proportion of marginalized racial and ethnic minority (minoritized) groups continue to suffer from worse outcomes across most domains. Many of these health disparities are driven by inequities in access to and the scope of society’s health-affirming structural resources and opportunities commonly referred to as structural drivers or social determinants of health—SDoH. Persistently health-undermining factors in the social environment and the downstream effects of these inequities on neurocognitive and biological pathways exacerbate these disparities. The consequences of these circumstances manifest as behavioral, neurohormonal, immune, and inflammatory and oxidative stress responses, as well as epigenetic changes. We propose a theoretical model of the interdependent characteristics of inequities in the SDoH driven by race-based discriminatory laws, policies, and practices that eventually culminate in poor health outcomes. This model provides a framework for developing and validating multi-level interventions designed to target root causes, thereby lessening health disparities and accelerating improved health outcomes for minoritized groups. Full article