Iskanje po repozitoriju

Opis: Background Vector-borne diseases are becoming increasingly important in public health. The incidence of Lyme borreliosis in Slovenia continues to rise. Therefore, screening the prevalence of Borrelia spp. in vectors and their hosts is very important. Rarely, but still, it is possible to discover new species or subtypes in a new region. Methods As part of a master’s thesis, a study group collected ticks in a coastal area of Slovenia. The ticks were incubated in an MKP medium for a possible Borrelia culture. Borrelia DNA was extracted from positive cultures. We performed classical molecular genotyping methods to complement whole genome sequencing (WGS) analysis. Results Using classical genotyping, we confirmed previously undetected Borrelia species in a Slovenian tick, Borrelia lusitanie. Using large restriction fragment polymorphisms (LRFP) with the enzyme MluI, we were able to detect a new LRFP subtype of Borrelia lusitanie, namely Mll3. Using WGS, we identified a new MLST type (ST-1154) and reconstructed five linear plasmids (lp17, lp25, lp28–8, lp54 and lp56+38) and two circular plasmids (cp26 and cp32–11+1). Conclusion Regular screening of vectors and their hosts for the presence of Borrelia pathogens is important to detect the spread of different species in new areas. When reconstructing Borrelia plasmids, it is very important to apply different assembly methods and to critically analyse the results in order to select suitable contigs for further trimming and to successfully generate a complete consensus genome of high quality from hybrid read data.
Ključne besede: Slovenia, Borrelia lusitaniae, tick, Ixodes ricinus, WGS, plasmid analysis
Objavljeno v RUP: 05.08.2025; Ogledov: 464; Prenosov: 2
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Opis: Sandflies (Diptera: Psychodidae: Phlebotominae) are important vectors of pathogens, including Leishmania parasites and phleboviruses, but their distribution and seasonal activity in Slovenia have not been sufficiently studied. This study presents a comprehensive three-year (2020–2022) surveillance programme aimed at assessing the diversity of sandfly species, their distribution, seasonal dynamics and potential role as vectors of pathogens. A total of 1,240 sandflies were collected at 43 sampling sites across Slovenia, identifying Phlebotomus papatasi, P. neglectus, P. perniciosus and P. mascittii. The highest abundance and species diversity were observed in the Mediterranean and Karst regions. Seasonal activity peaked in July, with population fluctuations influenced by climatic conditions. Molecular analyses for Leishmania parasites and phleboviruses showed no positive results, indicating a low prevalence of pathogens in the sampled populations. Predictive habitat models indicate that environmental factors, particularly temperature and precipitation, play a decisive role in the spread of sandflies. While P. mascittii has the largest ecological range, its vector competence remains uncertain. The results provide important insights into the ecology of sandflies in Slovenia and emphasize the need for continuous surveillance in the context of climate change and emerging vector-borne disease risks.
Ključne besede: sandflies, monitoring, distribution, modeling, Slovenia
Objavljeno v RUP: 04.08.2025; Ogledov: 553; Prenosov: 7
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Opis: Retrieval-Augmented Generation (RAG) systems synergize retrieval mechanisms with generative language models to enhance the accuracy and relevance of responses. However, bridging the style gap between user queries and relevant information in document text remains a persistent challenge in retrieval-augmented systems, often addressed by runtime solutions (e.g., Hypothetical Document Embeddings (HyDE)) that attempt to improve alignment but introduce extra computational overhead at query time. To address these challenges, we propose Hypothetical Prompt Embeddings (HyPE), a framework that shifts the generation of hypothetical content from query time to the indexing phase. By precomputing multiple hypothetical prompts for each data chunk and embedding the chunk in place of the prompt, HyPE transforms retrieval into a question-question matching task, bypassing the need for runtime synthetic answer generation. This approach does not introduce latency but also strengthens the alignment between queries and relevant context. Our experimental results on six common datasets show that HyPE can improve retrieval context precision by up to 42 percentage points and claim recall by up to 45 percentage points, compared to standard approaches, while remaining compatible with re-ranking, multi-vector retrieval, query decomposition, and other RAG advancements.
Ključne besede: LLM, hypothetical prompt embedding, Retrieval-Augmented Generation (RAG)
Objavljeno v RUP: 04.08.2025; Ogledov: 557; Prenosov: 4
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Opis: Purpose This study aims to identify key risk factors for sarcopenia using machine learning models, leveraging anthropomet- ric, biochemical, functional, nutritional, and genetic data. By developing predictive models, the research seeks to improve early detection, enhance diagnostic accuracy, and facilitate personalized interventions for individuals at risk of sarcopenia. Methods We analysed multimodal data from 484 older adults. Two scenarios: Set-a (including SARC–CalF, excluding SARC-F) and Set-b (including SARC-F, excluding SARC–CalF) were applied in a three-stage modeling process with progressively reduced features and optimized predictive performance using machine learning models. Key predictors were ranked using SHAP values, and model performance was evaluated using AUC, accuracy, sensitivity, and specificity. Internal validation and DeLong’s test were applied to assess robustness and statistical differences. Results The most predictive risk factors included functional measures (chair stand, gait speed), nutritional indicators (pro- tein, folate, copper, vitamin B7), clinical conditions (diabetes, comorbidities, low-density lipoprotein (LDL)), and anthro- pometric markers (body mass index (BMI), calf circumference). Genetic features also contributed to risk stratification. The best-performing model Set-b (with screening test SARC-F) achieved an AUC of 0.951 and an accuracy of 93.62%. While SARC–CalF showed higher individual feature importance, the model achieved an AUC of 0.945 and accuracy of 92.2%. Conclusions This study highlights that traditional sarcopenia screening can be enhanced by capturing complex interplay of functional, nutritional, clinical, and genetic factors, offering clinicians a more accurate and tailored tool for early detec- tion and risk stratification. Future research should focus on validating these models in larger, independent, and longitudinal cohorts to assess their predictive utility across diverse populations and over time.
Ključne besede: genetics, nutrition, risk factors, sarcopenia
Objavljeno v RUP: 23.07.2025; Ogledov: 564; Prenosov: 12
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Opis: We construct over a given bilinear multi-patch domain a novel $C^s$-smooth mixed degree and regularity isogeometric spline space, which possesses the degree $p=2s+1$ and regularity $r=s$ in a small neighborhood around the edges and vertices, and the degree~$\widetilde{p} \leq p$ with regularity $\widetilde{r} = \widetilde{p}-1 \geq r$ in all other parts of the domain. Our proposed approach relies on the technique Kapl and Vitrih (2021), which requires for the $C^s$-smooth isogeometric spline space a degree at least $p=2s+1$ on the entire multi-patch domain. Similar to Kapl and Vitrih (2021), the $C^s$-smooth mixed degree and regularity spline space is generated as the span of basis functions that correspond to the individual patches, edges and vertices of the domain. The reduction of degrees of freedom for the functions in the interior of the patches is achieved by introducing an appropriate mixed degree and regularity underlying spline space over $[0,1]^2$ to define the functions on the single patches. We further extend our construction with a few examples to the class of bilinear-like $G^8$ multi-patch parameterizations (Kapl and Vitrih (2018); Kapl and Vitrih (2021)), which enables the design of multi-patch domains having curved boundaries and interfaces. Finally, the great potential of the $C^8$-smooth mixed degree and regularity isogeometric spline space for performing isogeometric analysis is demonstrated by several numerical examples of solving two particular high order partial differential equations, namely the biharmonic and triharmonic equation, via the isogeometric Galerkin method.
Ključne besede: isogeometric analysis, Galerkin method, C^s-smoothness, mixed degree and regularity spline space, multi-patch domain
Objavljeno v RUP: 01.07.2025; Ogledov: 662; Prenosov: 4
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