Search Results (19,113)

In recent years, an increasing amount of research has investigated the impact of chronic inflammation on the development and progression of both neurological and psychiatric disorders, including epilepsy, depression, schizophrenia, and bipolar disorder. Moreover, growing attention is being paid to how inflammatory processes contribute to disease mechanisms, influence symptom severity, and interact with pharmacological treatments in these conditions. Changes in the levels of inflammatory biomarkers, such as cytokines and C-reactive protein, may signal the early stages of neurological disorder development. Furthermore, specific biomarker profiles have been identified for individual diseases, and chronic treatment may affect their blood levels. Over the last two decades, significant progress in the study of inflammatory biomarkers in psychiatric disorders and epilepsy has been achieved, demonstrating an association between biomarkers with symptoms, a potential prognostic role, and possible use in personalising therapy. Furthermore, widely used methods for biomarker evaluation, such as immunoenzymatic assays and flow cytometry, remain essential tools for current research. Despite numerous indications of the importance of inflammation in psychiatry and neurology, the available studies are characterised by considerable heterogeneity in terms of both population selection and methodology. Based on the available data, inflammatory biomarkers represent a promising diagnostic and therapeutic tool for epilepsy and psychiatric disorders. Although existing studies suggest a correlation between inflammation and the symptoms of various disorders, inconsistent results highlight the need for further research to enable wider implementation of these findings in psychiatric and epilepsy practice. Advancing knowledge of inflammatory biomarkers is essential for improving treatment outcomes and promoting the development of targeted interventions. Full article

In order to reduce the environmental burden associated with Cordyceps militaris residue, we conducted a study to explore the feasibility of Cordyceps militaris residue as a silage additive. The experimental treatments included distilled sterile water control (CK), Lactiplantibacillus plantarum (LP, 1 × 10⁵ cfu/g), Cordyceps militaris residue (CM, 4% of fresh matter), and their combination (LP + CM). A total of 48 samples (4 treatments × 4 storage periods × 3 replicates) were prepared for the analysis of fermentation quality, chemical composition, microbial population, and bacterial community composition at days 2, 7, 28, and 45 of ensiling. Results showed that compared with the control, the CM and LP + CM treatments increased the lactic acid bacteria number and lactic acid content (p < 0.05), and a decrease in pH value and NH₃-N content was observed (p < 0.05). The bacterial diversity in the CM group was higher and lower than that in the CK group in the early and late stages of fermentation, respectively, and maintained a higher relative abundance of Lactococcus on day 7. Lactobacillus remained the predominant bacterial community at the end of fermentation. Random forest analysis indicated that Lactobacillus was a key determinant of the pH, lactic acid, and acetic acid levels. Consequently, the addition of Cordyceps militaris residue alone, or combined with Lactiplantibacillus plantarum, improved the quality of alfalfa silage by increasing lactic acid and lowering NH₃-N, providing a new approach for its development and utilization. Full article

Soldiers are likely to suffer an injury and require rehabilitation at some stage of their career. Load carriage, whilst a fundamental requirement, is also a source of injury risk. To optimize the rehabilitation of soldiers and prepare them for a full return to operational duty, load carriage requirements need to be considered throughout their rehabilitation pathway. In addition, injury risks associated with load carriage need to be considered to inform mitigation of reinjury. During the initial injury treatment stage, loss of key fitness elements associated with load carriage performance, being aerobic fitness and relative strength, need to be minimized. Any losses of these same elements of fitness then need to be considered in the overall reconditioning stage. Finally, with injury being a predictor of future load carriage injury, the conditioning stage must move beyond general occupational conditioning to include load carriage-specific conditioning to make the soldier physically resilient against future injury and confident of their capability. By synthesizing evidence from the latest research in load carriage, this narrative review provides pragmatic considerations and guidelines for optimizing soldier load carriage capability following injury. Full article

Background: Perioperative factors significantly impact oncologic outcomes after radical cystectomy (RC) for bladder cancer. This study aimed to identify key perioperative predictors for overall (OS) and progression-free survival (PFS) and to develop a prognostic nomogram for the identification of high-risk patients adapted to the clinical routines and standard of care of our country. Methods: We retrospectively analyzed 121 patients undergoing RC (2014–2024). Data on patient demographics, comorbidities, tumor pathology, neoadjuvant treatments, extensive intraoperative factors, and postoperative events were assessed using COX models. A prognostic nomogram for 3-year OS was constructed. Results: Median follow-up was 44.33 months. Significant predictors for worse OS included lymphovascular invasion (LVI) (HR 2.22), higher T stage (HR 8.75), N+ status (HR 1.10), and intraoperative complications (HR 3.04). Similar predictors were noted for PFS. The developed nomogram incorporated T-, N-stages, sex, grade, intraoperative complications and early (12 months) recurrence, and was able to significantly identify patients with a higher mortality risk (p < 0.001) with a C-index of 0.74. Conclusions: Our nomogram for mortality prediction of BC patients offers a promising tool for individualized risk stratification. Further studies are required for its external validation. Full article

Cannabis sativa L. is a high-value medicinal crop whose nutritional requirements and fertilization strategies remain poorly defined, particularly in relation to cannabinoid production. This study evaluated the effects of inorganic fertilization (N, P, and K) on biomass accumulation, nutrient uptake and balance, and cannabinoid content in Cannabis sativa L. A high-cannabidiol (CBD) cultivar was propagated from ex vitro cuttings and grown in 10 L pots with commercial substrate. Treatments included a non-fertilized control and increasing doses of N (0–10 g plant⁻¹), P (0–6 g plant⁻¹), and K (0–10 g plant⁻¹), with higher P and K doses applied during the reproductive stage. Biomass production peaked at 5 g N, 2 g P, and 3 g K plant⁻¹, yielding 41.9% more than the control. Fertilized plants showed harvest indexes of 31–42%. Additional P and K during the reproductive stage did not enhance inflorescence biomass and CBD content. Tissue nutrient concentrations increased with fertilization. Inflorescences had maximum N and P levels at 5 g N and 2 g P plant⁻¹, while leaves accumulated more K at 7.5 g K plant⁻¹. CBD content increased and THC (%) decreased progressively with nutrient supply. High nutrient doses, however, led to nutritional imbalances and plant health issues. Nutrient balance analysis showed differential macronutrient extraction by treatment. These findings highlight the importance of optimized fertilization strategies to enhance both biomass and cannabinoid production in high-CBD cannabis cultivars. Full article

This study investigated the effects of light intensity regulation on yield and energy efficiency during potato pre-basic seed propagation in plant factories. Using virus-free ‘Favorita’ potato seedlings as experimental material, gradient light intensities (200, 300, and 400 μmol·m²·s⁻¹) were applied at four developmental stages: the seedling stage (SS), tuber formation stage (TFS), tuber growth stage (TGS), and harvest stage (HS), to explore the physiological mechanisms of stage-specific light intensity regulation and energy utilization efficiency. The results revealed that: (1) The per-plant tuber yield of the high yield group reached 72.91 g (T59 treatment), representing a 25% increase compared to the medium yield group and a 168% increase compared to the low yield group. Additionally, the high yield group exhibited superior leaf area, photosynthetic rate, and accumulation of sucrose and starch. (2) The impact of light intensity on tuber development exhibited stage specificity: low light intensity (200 μmol·m⁻²·s⁻¹) during TFS promoted early tuber initiation, while a high light intensity (400 μmol·m⁻²·s⁻¹) enhanced tuber formation efficiency. Increasing the light intensity during TGS facilitated the accumulation of sucrose and starch in tubers. (3) Energy use efficiency (EUE) increased significantly with yield, with the high yield group reaching 3.2 g MJ⁻¹, representing 52% and 88% improvements over the medium yield (2.1 g MJ⁻¹) and low yield (1.7 g MJ⁻¹) groups, respectively. A “stage-specific precision light supplementation” strategy was proposed, involving moderate light reduction (200 μmol·m⁻²·s⁻¹) during TFS and light enhancement (300 μmol·m⁻²·s⁻¹) during TGS to coordinate source-sink relationships and optimize carbohydrate metabolism. This study provides a theoretical basis for efficient potato production in plant factories. Full article

Fractures occur frequently in daily life, and before a surgeon implements treatment, the plan needs to be based on the radiologist’s imaging diagnosis of the X-ray. Despite progress in deep learning–based fracture detection, existing methods (e.g., two-stage detectors) face challenges such as small target leakage and sensitivity to background interference in complex medical images. To address these issues, this paper proposes the ASC-YOLO model, which employs the Scale-Sensitive Feature Fusion (SSFF) module to enhance multi-scale information extraction through cross-layer feature interaction. In addition, an Adaptive Decoupled Detection Head (AsDDet) is introduced to decouple the classification and regression tasks of the detection head, thereby improving the localization accuracy of small fracture regions and suppressing background noise. Experiments on a large fracture radiograph dataset, GRAZPEDWRI-DX, demonstrate that ASC-YOLO achieves 61% mAP@50, representing an 8% improvement over the baseline YOLO model (mAP@53%). It attains 95% mAP@50 for the fracture category and 97% mAP@50 for the metal category. Furthermore, the model was evaluated on a tumor dataset to verify its generalization capability. The proposed framework provides reliable technical support for accurate fracture screening, which is expected to reduce missed diagnoses and optimize treatment. Full article

This paper presents the results of a survey of the designed biological wastewater treatment facilities of an enterprise specializing in the production of rubber products. The aim of the study was to assess the efficiency of wastewater treatment systems under the conditions of a salvo discharge of industrial effluents that differ in composition from domestic wastewater. The analysis covered the parameters of water supply, water disposal, and wastewater characteristics at various stages of treatment. Three samples were taken: after washing the premises (WW1), at the inlet to the treatment facility (WW2), and at the outlet after treatment (WW3). Experimental assessment of the purification efficiency for key pollutants showed a high degree of removal of surfactants (91.2%), oil products (84.4%), and COD (63.4%). However, phosphorus–phosphate turned out to be significantly higher than the norm—2.32 mg/L with an acceptable level of 0.2 mg/L—which corresponds to an excess of 11.6 times. A low degree of ammonium nitrogen removal was also revealed—62%. Calculations showed a critically high ratio of COD/BOD5 = 5.1 with the recommended <2.6, which indicates a small share of biodegradable substances and the need to implement physical and chemical treatment methods. The absence of the characteristic smell of household wastewater and the presence of black inorganic sediment confirm the toxicity of emerging pollutants for activated sludge. It is concluded that the installed biological treatment system cannot cope with the salvo loads of industrial wastewater. Optimization measures are proposed: preliminary local treatment, dosed feed, and a separate treatment system. Full article

Background: Tuberculosis (TB) remains a major global health challenge, including in Thailand, where both asymptomatic and symptomatic cases sustain transmission. The disease burden increases treatment complexity and mortality, requiring integrated care and coordinated policies. Methods: We developed a deterministic compartmental model to examine the transmission dynamics of TB in Thailand, incorporating both latent and active stages of infection, as well as vaccination coverage. The model was calibrated using national TB incidence data, and sensitivity analysis revealed that the TB transmission rate was the most influential parameter affecting the basic reproduction number (R₀). We evaluated the impact of several intervention strategies, including increased treatment coverage for latent and active TB infections and improved vaccination rates. Results: Our analysis indicates that among the single interventions, scaling up effective treatment for latent TB infections produced the greatest reduction in asymptomatic and symptomatic cases, while enhanced treatment for active TB cases was second most effective for reducing both asymptomatic and symptomatic cases. Importantly, our results indicate that combining multiple interventions yields significantly greater reductions in overall TB incidence than any single approach alone. Our findings suggest that a modest investment in integrated TB control can substantially reduce TB transmission and disease burden in Thailand. However, complete eradication of TB would require a comprehensive and sustained investment to achieve near-universal coverage of both preventive and curative strategies. Conclusions: TB remains a significant public health threat in Thailand. Targeted interventions and integrated strategies are key to reducing disease burden and improving treatment outcomes. Full article

Background: Surgical resection remains central to the curative treatment of locally advanced gastric cancer (GC), yet global variability persists in defining resectability, particularly in complex scenarios such as multivisceral invasion, positive peritoneal cytology (CY1), or oligometastatic disease. The Intercontinental Criteria of Resectability for Gastric Cancer (ICRGC) project was developed to address this gap by combining expert surgical input with artificial intelligence (AI)-based reasoning. Methods: A two-stage prospective survey was conducted during the 2024 European Gastric Cancer Association (EGCA) meeting. Fifty-eight surgical oncologists completed a 36-item questionnaire on resectability, strategy, and quality metrics. Subsequently, they reviewed AI-generated responses based on current clinical guidelines and completed a second round. Concordance between human and AI responses was classified as full, partial, or discordant, and changes in surgeon opinions were statistically analyzed. Results: Substantial agreement was observed in evidence-based domains. Seventy-nine percent of surgeons agreed with AI on distinguishing technical from oncological resectability. In cT4b cases, 61% supported restricting multivisceral resection to high-volume centers. Similar alignment was found in CY1 (54%) and N3 nodal disease (63%). Partial concordance appeared in areas requiring individualized judgment, such as peritonectomy or bulky-N disease. After AI exposure, surgeon responses shifted toward guideline-consistent decisions, including increased support for cytoreductive surgery only when CC0/1 was achievable and stricter classification of R2 resections as unresectable. Following AI exposure, 27.1% of surgeons changed at least one answer in alignment with AI recommendations, with statistically significant shifts observed in items related to surgical margin definition (p = 0.015), anatomical resection criteria (p < 0.05), and hospital stay benchmarks (p = 0.031). Conclusions: The ICRGC study demonstrates that AI-driven consensus modeling can replicate expert reasoning in complex surgical oncology and serve as a catalyst for harmonizing global practice. These findings suggest that AI-supported consensus modeling may complement expert surgical reasoning and promote greater consistency in decision-making, particularly in controversial or ambiguous cases. Full article

Cement manufacturing is the second largest anthropogenic source of Hg emissions in the environment. Therefore, the establishment of analytical methodologies that can be utilized in the determination of Hg concentration from cement raw materials and cement is of great importance. The total Hg and Hg thermospecies in cement raw materials and cements were determined by thermal desorption techniques with a Zeeman Hg analyzer. No chemical pre-treatment of samples is required for this technique prior to analysis. An optimum single-stage temperature program was applied to determine total Hg at an optimum heating rate of approximately 5 °C s⁻¹ while Hg thermospecies were determined over four stages at an optimum heating rate of approximately 0.2 °C s⁻¹ per stage from ambient temperature to 720 °C. Total mercury concentrations in cement raw materials ranged between 2.19 ng g⁻¹ and 395 ng g⁻¹, while in cement, concentrations ranged between 1.32 ng g⁻¹ and 31.0 ng g⁻¹. The highest Hg contents were found in dust return (580 ng g⁻¹ and 679 ng g⁻¹). Hg thermospecies determination showed that cement raw materials and cements contain one Hg thermospecies that is released at 20–180 °C while dust return contained one to four Hg thermospecies that could be released at 20–180 °C, 180–360 °C, 360–540 °C, and/or 540–720 °C, thus indicating that new Hg compounds are formed during cement production. Full article

Introduction: Healthcare service utilisation for type 2 diabetes (T2D) is suboptimal among people from culturally and linguistically diverse (CALD) backgrounds. Synthesised evidence on drivers influencing their healthcare access and utilisation across the continuum of care (CoC) is scarce. This review synthesised drivers of accessing and utilising healthcare services across the CoC for T2D from the perspectives of people from CALD backgrounds and their healthcare service providers (HSPs). Methods: Five databases (Scopus, PubMed, Web of Science, CINAHL, and PsycINFO) were searched from inception to November 2023. This review was prospectively registered with PROSPERO (ID: CRD42023491560). The McGill Mixed Methods Appraisal Tool (MMAT) was used to assess the quality of articles included in this systematic review. Studies were included if they were primary research involving people from CALD backgrounds and/or their HSPs, and reported data related to access to and utilisation of services across the CoC. The CoC framework was used to conduct a guided thematic analysis for qualitative findings and narrative synthesis was used to summarise quantitative findings. Results: Thirty-five studies were included: 31 qualitative, 3 quantitative, and 1 mixed-method. Psychosocial (e.g., fear of treatment) and sociocultural barriers (e.g., stigma) were reportedly encountered at diagnosis and initiation of treatment. Language and cultural barriers were expressed by most people with T2D and their HSPs, especially at the monitoring and adherence stages of the CoC. Trusted relationships with HSPs and the cultural competency of the HSPs were facilitators of continued monitoring and adherence and long-term care and management. No barriers or facilitators were identified for decision-making to enter the healthcare systems, screening, and first point of contact aspects of the CoC from the perspectives of either patients or HSPs. Conclusions: Although included articles were heavily skewed towards qualitative studies, the synthesised evidence on factors influencing access to and utilisation of healthcare services for T2D can inform policymaking by highlighting pathways to improved use of healthcare services among these groups. Full article

Technological innovation in immersive virtual reality is fostering the development of novel psychotherapeutic interventions in mental health, particularly benefiting populations with limited access to specialized services. This pilot study explores the feasibility, tolerability, and therapeutic potential of an immersive virtual reality-based psychotherapeutic intervention for adolescents and young people with eating disorders in a rural setting. A quasi-experimental pre-test/post-test design was used, with a control group (n = 5) and an experimental group (n = 5), applying weekly immersive virtual reality sessions focused on body perception and food exposure. Preliminary results showed good acceptance and a low incidence of cybersickness. However, a reduction in anxiety levels was observed in the experimental group after immersive virtual reality exposure, particularly in trait anxiety, suggesting a potential effect of the intervention on emotional regulation. While these changes were not statistically significant, the direction and magnitude of the effect warrant further investigation. Changes in body mass index were also noted during the intervention. The remotely guided sessions, conducted via fifth-generation mobile network connectivity, demonstrated technical feasibility and encouraging clinical outcomes, even in geographically isolated or underserved areas. These findings support the use of immersive VR as a complementary tool in the early stages of treatment for eating disorders, contributing to improved body perception and emotional self-regulation. This work not only reinforces the applicability of immersive technology in real-world clinical practice but also opens new avenues for the development of personalized, accessible, and emotionally meaningful interventions in child and adolescent mental health. Full article

Non-small-cell lung cancer (NSCLC) is a widespread and aggressive form of cancer, and in cases of its occurrence, accurate diagnosis and precise staging play a crucial role in determining treatment and estimating prognosis. Flexible bronchoscopy (FB) is a minimally invasive method used to assess the local and regional extent of the disease. FB facilitates the identification of endobronchial lesions and the collection of biopsy samples for histopathological diagnosis. It also enables the evaluation of regional lymph node involvement via advanced techniques such as endobronchial ultrasound with fine-needle aspiration (EBUS-TBNA). This method has high sensitivity and specificity, reducing the need for more invasive interventions like mediastinoscopy. The integration of endobronchial ultrasound (EBUS) has revolutionized NSCLC staging by providing detailed images and guiding biopsies of suspicious lymph nodes. Additionally, FB is valuable in staging the extent of primary tumor growth, providing critical information about the invasion of adjacent structures. In conclusion, FB, supported by advanced technologies, is important for the staging of NSCLC, improving medical practice and patient prognosis. Full article

Background: Circulating tumor DNA (ctDNA), shed into bodily fluids by cancer cells through apoptosis, necrosis, or active secretion, is currently used in the field of genomic investigation in clinical settings, primarily for advanced stages of non-small-cell lung cancer (NSCLC). However, its potential role in guiding the multi-omic approach to early-stage NSCLC is emerging as a promising area of investigation. Efforts are being made to integrate the genomics not only in surgery, but also in the definition of long-term prognosis after surgical or radiotherapy and for the prediction of recurrence. Methods: An extensive literature search was conducted on PubMed, covering publications from 2000 to 2024. Using the advanced search tool, titles and abstracts were filtered based on the following keywords: ctDNA, early stage, NSCLC. From this search, 20 studies that fulfilled all inclusion criteria were selected for analysis in this review. Results: This review highlights the growing body of evidence supporting the potential clinical use of ctDNA as a genomic biomarker in managing early-stage NSCLC. Baseline ctDNA levels offer valuable information about tumor molecular biology and histological characteristics. Beyond its prognostic value before treatment, liquid biopsy has proven useful for tracking minimal residual disease and forecasting recurrence following curative interventions such as surgery or radiotherapy. Future adjuvant treatment decisions may increasingly rely on predictive models that incorporate liquid biopsy findings alongside other clinical factors. Conclusions: The potential use of this analyte introduces new opportunities for the integration of genomic data in treatment, as well as relapse monitoring with more accurate and innovative than traditional methods, particularly in patients with early-stage NSCLC Full article