Search Results (4,861)

The rapid advancement of large language models (LLMs) has significantly transformed the development and deployment of generative AI chatbots across various domains. This systematic literature review (SLR) analyzes 39 primary studies published between 2020 and 2025 to explore how these models are utilized, the sectors in which they are deployed, and the broader trends shaping their use. The findings reveal that models such as GPT-3.5, GPT-4, and LLaMA variants have been widely adopted, with applications spanning education, healthcare, business services, and beyond. As adoption increases, research continues to emphasize the need for more adaptable, context-aware, and responsible chatbot systems. The insights from this review aim to guide the effective integration of LLM-based chatbots, highlighting best practices such as domain-specific fine-tuning, retrieval-augmented generation (RAG), and multi-modal interaction design. This review maps the current landscape of LLM-based chatbot development, explores the sectors and primary use cases in each domain, analyzes the types of generative AI models used in chatbot applications, and synthesizes the reported limitations and future directions to guide effective strategies for their design and deployment across domains. Full article

Suicidality is a complex multifactorial phenomenon strongly associated with major depression and other psychiatric disorders. Building on evidence implicating the Major Histocompatibility Complex (MHC) in modulating the immune and inflammatory processes characterizing psychiatric disorders, we hypothesized that specific HLA-DQB1 and HLA-DRB1 variants may contribute to an increased genetic susceptibility to suicidal behavior. Human Leucocyte Antigen (HLA) typing by sequence-specific primers (PCR-SSP) was performed on a sample of 196 individuals, including 70 non-lethal suicide attempters, 28 cases of completed suicide, and matched controls. The *HLA-DQB1 02/06 (RR 1.60, CI95% 1.22–2.09, p = 0.03 *) and *HLA-DRB1 11/15 (RR 1.70, CI95% 1.3–2.24, p = 0.04 *) genotypes and the HLA-DRB115~DQB103 haplotype (RR 1.58, CI95% 1.22–2.04, p = 0.03 *) were found to favor suicidal behavior. Psychosocial determinants associated with an increased suicidal risk were bereavement of close relatives (linked with HLA-DQB1*02), memory dysfunction (HLA-DQB1*06), disillusionment (HLA-DRB1*07 and HLA-DRB1*15), and self-harm (HLA-DRB1*15). Our findings support the contributory role of HLA polymorphisms in shaping susceptibility to suicidal behavior. Full article

Varaždin County is rich in mineral resources, attracting considerable investor interest in opening new exploration areas and expanding existing exploitation fields. Since the economic value of mineral resources changes with market conditions, continuous professional assessment is required. Although the proposed methodological framework is broadly applicable to mineral resource management, this case study focuses on the exploitation of construction sand and gravel deposits in Varaždin County. In this way, it addresses the sustainability challenges characteristic of quarry operations rather than large-scale mining projects. The objective of this study was to develop and test a new method for quantifying sustainability indicators in the mineral resource management (spatial, resource-related, environmental, economic, and social sustainability—I_PREGS) and for calculating an aggregated composite index (AK_I) using a pilot project for construction sand and gravel. The research establishes a cause–effect relationship between quantified indicators (I_PREGS) and the newly established aggregated composite index (AK_I). Methodologically, the study applied multivariate analysis to questionnaire data, enabling the selection, weighting, and aggregation of indicators and the design of a conceptual framework for AK_I calculation. The resulting methodology provides an instrument for monitoring and improving sustainable mineral resource management, supporting the objectives of the circular economy. The findings highlight the potential of the AK_I to reduce systemic inefficiencies, guide policy development, and offer a transparent mechanism for assessing both implementation and effectiveness. This significantly improves the current state and strengthens the basis for evidence-based economic policy-making. The case study in Varaždin County further demonstrated that the AK_I not only reproduces administrative decisions with high consistency but also clarifies how applicants should proceed in cases of partial acceptance and how policymakers can interpret conflicting outcomes across different index variants. Full article

The deployment of autonomous robots is critical for advancing sustainable agriculture, but their effectiveness hinges on visual perception systems that can reliably operate in natural, real-world environments. Selecting an appropriate vision model for these robots requires a practical evaluation that extends beyond standard accuracy metrics to include critical deployment factors such as computational efficiency, energy consumption, and robustness to environmental disturbances. To address this need, this study presents a deployment-oriented benchmark of state-of-the-art You Look Only Once (YOLO)-based models for orange detection and segmentation. Following a systematic process, the selected models were evaluated on a unified public dataset, annotated to rigorously assess real-world challenges. Performance was compared across five key dimensions: (i) identification accurac, (ii) robustness, (iii) model complexity, (iv) execution time, and (v) energy consump-tion. The results show that the YOLOv5 variants achieved the most accurate detection and segmentation. Notably, YOLO11-based models demonstrated strong and consistent results under all disturbance levels, highlighting their robustness. Lightweight architectures proved well-suited for resource-constrained operations. Interestingly, custom models did not consistently outperform their baselines, while nanoscale models showed demonstra-ble potential for meeting real-time and energy-efficient requirements. These findings offer valuable, evidence-based guidelines for the vision systems of precision agriculture robots. Full article

Modeling stock returns and option pricing in the presence of jumps remains a central challenge in financial economics. This paper employs a novel score-driven GARCH-jump model to analyze SSE (Shanghai Stock Exchange) 50 ETF returns and option pricing. The main findings are as follows. First, we use 50 ETF spot returns to estimate conditional volatility and jump intensity, and find that the SDSDJ (score-driven separate dynamic jumps) model significantly outperforms conventional GARCH-jump models in model fitting. Second, we evaluate both in-sample and out-of-sample pricing performance using data from 50 ETF options, and find that the SDSDJ model achieves the lowest in-sample pricing error among all benchmarks, while its simplified variant—the SDJ (score-driven jumps) model—delivers the most accurate out-of-sample results. Third, the superior pricing performance of both models is robust across different levels of moneyness and DTM (days-to-maturity). Full article

High-grade gliomas (HGGs) are aggressive brain tumors with limited treatment options and poor survival outcomes. Variants including isocitrate dehydrogenase (IDH)-wildtype, IDH-mutant, and histone 3 lysine to methionine substitution (H3K27M)-mutant subtypes demonstrate considerable tumor heterogeneity at the genetic, cellular, and microenvironmental levels. This presents a major barrier to the development of reliable models that recapitulate tumor heterogeneity, allowing for the development of effective therapies. Glioma tumor organoids (GTOs) have emerged as a promising model, offering a balance between biological relevance and practical scalability for precision medicine. In this study, we present a refined methodology for generating three-dimensional, multiregional, patient-derived GTOs across a spectrum of glioma subtypes (including primary and recurrent tumors) while preserving the transcriptomic and phenotypic heterogeneity of their source tumors. We demonstrate the feasibility of a high-throughput drug-screening platform to nominate multi-drug regimens, finding marked variability in drug response, not only between patients and tumor types, but also across regions within the tumor. These findings underscore the critical impact of spatial heterogeneity on therapeutic sensitivity and suggest that multiregional sampling is critical for adequate glioma model development and drug discovery. Finally, regional differential drug responses suggest that multi-agent drug therapy may provide better comprehensive oncologic control and highlight the potential of multiregional GTOs as a clinically actionable tool for personalized treatment strategies in HGG. Full article

The mechanical properties of dental implants are critical for their durability. The purpose of this study was to determine the maximum force required to induce full pull-out of a titanium implant from the bone and to characterize the mechanical behavior during this process. First, pull-out tests were performed on monolithic implants embedded in bovine ribs and foam blocks that mimic the mechanical parameters of human bone, allowing a quantitative evaluation of implant–bone interface strength and a comparison of geometric variants. Second, the extraction process was recreated in a three dimensional finite element model incorporating nonlinear interface contact and parameterization, enabling the reproduction of load–displacement curves; the results obtained showed good agreement with the experiment. Third, the fracture surfaces were observed macroscopically and by scanning electron microscopy/energy dispersive spectroscopy. The results demonstrated significant distinctions in the forces required to extract implants with varying thread geometries, clearly indicating the impact of implant design on their mechanical stability. The presented FEM-based methodology provides a reliable tool to study mechanical interactions at the implant–bone interface. The findings obtained can improve our understanding of implant behavior in biological systems and provide a basis for further optimization of their design. Full article

Traditional teaching methods are often far from aligning with professional practice demands. Team-Based Learning (TBL), a variant of Problem-Based Learning, may foster motivation, autonomy, and deeper knowledge acquisition, especially in those educative contexts linked to practical knowledge. The objective of the present research was to explore the impact of a TBL program with digital support on Sport Sciences students’ psychological and learning outcomes. A quasi-experimental design with pre- and post-tests was applied to 68 fourth-year students (mean age = 21.45 ± 1.57 years). The intervention spanned 12 weeks, where the students had to solve specific case studies linked to the theoretical content of the subject and its applicability. Variables measured included motivational climate, satisfaction of basic psychological needs, intrinsic motivation, transversal competences, and academic performance. Significant improvements were observed in task- and ego-oriented climate, autonomy, competence, relatedness, knowledge scores, and competence in scientific searches and academic dissemination (p < 0.05). No significant changes were found in intrinsic motivation or audiovisual material competence. Sex influenced several outcomes, while project marks and prior transversal skills did not. TBL combined with digital tools enhanced learning outcomes and key psychological needs, though intrinsic motivation remained unchanged. Findings highlight the value of active methodologies in higher education, while underscoring the need for long-term, broader studies. Full article

Background: High-grade serous ovarian cancer (HGSC) is the most common and aggressive subtype of ovarian cancer. Despite initial response to platinum-based chemotherapy, most patients relapse. Cytoreductive surgery at relapse has been shown to improve survival in selected patients, but the biological mechanisms underlying recurrence and resistance remain unclear. This study aimed to investigate whether the mutational profile of HGSC changes from diagnosis to relapse, and to evaluate treatment patterns and survival outcomes in a cohort undergoing cytoreductive surgery. Methods: Sixteen patients with HGSC who underwent cytoreductive surgery at both diagnosis and relapse were included. Matched tumor tissue samples (n = 32) were collected and sequenced using a 501-gene cancer panel. Only pathogenic or likely pathogenic variants were registered. Clinical data, treatment history, and survival outcomes were obtained from medical records, with a median follow-up of 63 months. Results: All patients harbored pathogenic or likely pathogenic mutations, most frequently in TP53 (88%) and BRCA1/2 (38%). The mutational landscape was largely stable, with 15 of 16 patients (94%) showing no mutational changes between diagnosis and relapse. One patient acquired a NOTCH2 mutation at relapse. Complete resection was achieved in 88% of relapse surgeries. Median time to first relapse was 32 months, and overall survival was prolonged, with 87.5% of patients alive at last follow-up. BRCA mutated patients showed longer time to relapse, and overall follow-up compared to BRCA wild-type cases. Conclusions: The somatic mutational profile of HGSC remains remarkably stable from diagnosis to relapse. Clinically, this stability suggests that repeat mutational sequencing at relapse is unlikely to yield new actionable findings and may have limited value in guiding treatment decisions. Instead, resistance mechanisms likely arise from epigenetic or non-genetic changes, underscoring the need for future research in these areas and the continued importance of optimal surgical management in selected patients. Full article

Plant height is a key agronomic trait influencing both seed production and yield in hybrid rice. In the elite japonica hybrid ‘Shenyou 26’, optimal plant height differences between the restorer line (‘Shenhui 26’) and the male sterile line (‘Shen 9A’) are critical for efficient pollination. In this study, we dissected the genetic basis of plant height variation using a doubled haploid (DH) population derived from ‘Shenyou 26’. Multi-environment phenotyping and QTL mapping identified seven QTLs associated with plant height, among which qPH1.1 and qPH9.1 were validated. qPH1.1 co-localized with the semi-dwarf gene SD1, and ‘Shen 9A’ carries a rare SD1-EQH allele that potentially confers reduced height relative to the SD1-EQ allele in ‘Shenhui 26’. qPH9.1 also contributed significantly to plant height variation, with the Shenhui26 allele increasing plant height in backcross validation. These findings indicate that plant height variation in ‘Shenyou 26’ is controlled by multiple loci, including SD1 allelic variants and other complementary QTLs, providing valuable resources for fine-tuning plant architecture in rice breeding. Full article

Open-weight generative large language models (LLMs) can be freely downloaded and modified. Yet, little empirical evidence exists on how these models are systematically altered and redistributed. This study provides a large-scale empirical analysis of safety-modified open-weight LLMs, drawing on 8608 model repositories and evaluating 20 representative modified models on unsafe prompts designed to elicit, for example, election disinformation, criminal instruction, and regulatory evasion. This study demonstrates that modified models exhibit substantially higher compliance: while an average of unmodified models complied with only 19.2% of unsafe requests, modified variants complied at an average rate of 80.0%. Modification effectiveness was independent of model size, with smaller, 14-billion-parameter variants sometimes matching or exceeding the compliance levels of 70B parameter versions. The ecosystem is highly concentrated yet structurally decentralized; for example, the top 5% of providers account for over 60% of downloads and the top 20 for nearly 86%. Moreover, more than half of the identified models use GGUF packaging, optimized for consumer hardware, and 4-bit quantization methods proliferate widely, though full-precision and lossless 16-bit models remain the most downloaded. These findings demonstrate how locally deployable, modified LLMs represent a paradigm shift for Internet safety governance, calling for new regulatory approaches suited to decentralized AI. Full article

Background and objectives: Warfarin is a commonly used anticoagulant with a narrow therapeutic index that requires a precise dose to achieve efficacy and safety. Genetic variations in the CYP2C9 and VKORC1 genes significantly contribute to individual responses to warfarin, influencing both drug metabolism and pharmacodynamics. The current study aims to investigate the frequency of CYP2C9 and VKORC1 variant genotypes and determine the appropriate warfarin dosage for patients in Saudi Arabia. Materials and Methods: Blood samples were collected from 100 Saudi patients undergoing treatment with warfarin. DNA was extracted and purified from the whole blood, and variants in the CYP2C9 and VKORC1 genes were analyzed using multiplex PCR techniques. Results: The analysis revealed that the VKORC1 GG genotype was the most common, at 54%, followed by GA at 30%, and the AA at 16%. For CYP2C9, the *1/*1 genotype predominated at 71%, whereas the *1/*2 genotype was found in 14%, the *1/*3 genotype was found in 11%, and the *2/*3 genotype was found in in 2%, being less frequently observed. Patients with VKORC1 GG required significantly higher warfarin doses than those with GA and AA genotypes. Similarly, CYP2C9 *1/*1 patients required higher doses than those with *1/*3 and *2/*3 variants. No significant differences in INR levels across genotypes were found, indicating that while genetic variations influence dosing, they do not significantly alter the therapeutic INR range. Conclusions: The findings indicate that genetic variations influence drug metabolism and response in the Saudi population, aligned with global studies. Such tailored approaches could enhance treatment efficacy and reduce adverse effects, underscoring the role of pharmacogenomics in patient care and optimizing warfarin therapy in unique genetic populations. Full article

Inflammatory bowel disease (IBD), comprising Crohn’s disease (CD) and ulcerative colitis (UC), arises from complex genetic and environmental interactions. Here, we integrate genome-wide association study (GWAS) meta-analyses with tissue-specific expression data from GTEx to map the polygenic architecture of IBD and its systemic implications. We identified 69 genome-wide significant single-nucleotide polymorphisms (SNPs) across 26 genes shared by CD and UC, revealing an almost equal partition of subtype-specific (50.7%) and shared (49.3%) risk variants. IL23R exhibited the highest allelic heterogeneity—three UC-specific, one CD-specific, and three shared SNPs—while ATG16L1′s four CD-specific variants underscored autophagy’s pivotal role in CD. Chromosomal mapping revealed distinct regulatory hotspots: UC-only loci on chromosomes 1 and 6, CD-only loci on chromosomes 10 and 16, and shared loci on chromosomes 7 and 19. Pathway enrichment emphasized IL-23/IL-17, Th17 differentiation, NF-κB, and JAK–STAT signaling as central to IBD pathogenesis. GTEx analyses showed uniformly high expression of IBD genes in gastrointestinal tissues, but pronounced heterogeneity across brain regions, including the cerebellum, frontal cortex, and hippocampus. This neuro-expression, together with enrichment of neurotrophin and neurodegeneration pathways and a nearly two-fold gene overlap with autism spectrum disorder, schizophrenia, and depression (FDR < 0.05), provides integrative evidence for gut–brain axis involvement in IBD. These findings consolidate prior work while extending perspectives on systemic disease implications. This study consolidates and systematizes dispersed genetic and transcriptomic findings into a unified reference framework. Our results highlight recurrent immune-regulatory and neuro-inflammatory pathways shared between gut and brain, offering a resource to guide future mechanistic, clinical, and translational investigations in IBD and related disorders. Full article

Background: Antibody-dependent cellular cytotoxicity (ADCC) is an immune response where antibodies bind to target cells and activate effector cells through Fcγ receptors, ultimately leading to the destruction of the target cells. Methods: This study examined the ADCC activities of charge variants of a therapeutic IgG₁, MAB1, using an internally developed reporter gene assay. In this assay, the proprietary target was expressed on DiFi cells, while FcγRIIIa was expressed on Jurkat effector cells. Results: The results revealed that different charge variants had varying levels of ADCC activity, with variants containing C-terminal lysine residues showing enhanced activity. The charge variants arose from modifications such as the presence of sialic acid at the glycan moiety, deamidation, and C-terminal lysine truncation, including K2 (two C-terminal lysine residues), K1 (one C-terminal lysine residue), and K0 (no C-terminal lysine residues) variants. Notably, the K1 and K2 variants demonstrated higher ADCC activity compared to the K0 and acidic variants. However, the observed increase was attributed not to the lysine residue itself, but rather to the MAN5 glycan associated with the lysine-containing variants. Conclusion: These findings challenge previous assumptions about the role of C-terminal lysine in ADCC, suggesting a shift in understanding the functional significance of charge variants and emphasizing the critical influence of glycan composition in therapeutic antibody efficacy. Full article

The Alpine salamander (Salamandra atra) is a cold-adapted amphibian with low dispersal capacity, endemic to the Alps and Dinarides. Isolated populations at the range’s margins are especially vulnerable to habitat fragmentation and genetic erosion. We investigated the population genetic structure of S. atra in the Koralpe, a biogeographically important mountain range in southeastern Austria. Using mitochondrial DNA, we found that the Koralpe population harbors unique genetic variants not shared with other known populations. Strong genetic differentiation and low connectivity among Koralpe subpopulations, inferred from microsatellites, indicate long-term isolation, likely caused by unsuitable intervening habitats and the species’ limited dispersal capacity. Although the estimated effective population size (Ne = 245) is moderate and no severe genetic bottlenecks were detected, subpopulation sizes are likely small. These findings highlight the conservation value of this peripheral population and support its recognition as a distinct management unit. In situ protection, improved landscape connectivity, and continued (genetic) monitoring are essential for the population’s long-term survival. Given its unique genetic signature and pronounced structuring, targeted conservation measures are critical—especially under increasing pressure from climate change and habitat degradation. Preserving this isolated lineage will contribute to local biodiversity and help safeguard the evolutionary potential of S. atra as a whole. Full article