Background: African swine fever virus (ASFV) causes a fatal hemorrhagic disease in domestic pigs and wild boars. While live attenuated vaccines (LAVs) provide protection, their use raises safety concerns. Therefore, the aim of the present study was to identify viral B-cell antigens associated with protection and to test their potential using highly immunogenic vaccine delivery platforms. Methods: We employed a microarray of 169 ASFV proteins expressed in a cell-free prokaryotic system to identify immunodominant antigens using sera from immune pigs. Six structural proteins were selected and formulated into AP205 virus-like particles (VLPs). Additionally, replication-defective vesicular stomatitis virus (VSV)-based vaccine candidates expressing glycosylated CD2v and EP153R proteins were generated. Three groups of specific pathogen-free pigs were immunized with either VLP- or VSV-based vaccines and challenged with the virulent ASFV Georgia 2007 strain. Control groups included pigs immunized with the attenuated ASFV Estonia 2014 strain and a naïve group. Results: Most vaccine candidates induced detectable antibody responses against target ASFV proteins. However, neither VLP- nor VSV-based vaccines provided protection, as clinical scores, hematology, cytokine responses, and viremia levels were similar to those in the negative control group. In contrast, only the ASFV Estonia 2014 strain elicited a robust T-cell response and protective immunity. Conclusions: These findings highlight the challenges in identifying protective B-cell antigens of ASFV and emphasize the pivotal role of cellular immunity in mediating protection.

BACKGROUND Artificial intelligence (AI)-based algorithms are being implemented in breast screening to detect breast cancers on mammographic images. We aimed to apply an epidemiological approach to demonstrate how a cancer detection algorithm can be leveraged as an intermediate-term predictor of breast cancer (current and 4-year risk) to deliver greater risk-based personalisation in screening mammography. METHODS In this population cohort study, we used detection scores from an AI cancer detection algorithm (BRAIx AI Reader), which was calibrated using a training dataset of 397 648 women aged 40 years to 97 years from women who screened at BreastScreen Victoria, Australia between Jan 1, 2016, and Dec 31, 2017, to create a woman-specific mammography-based score for breast cancer risk, the BRAIx risk score. Subsequently, the BRAIx risk score was evaluated on an independent test dataset of women from BreastScreen Victoria, Australia, comprising a random population cohort of 96 348 women who screened from Jan 1, 2016, to Dec 31, 2017, aged 40 years to 74 years, and an independent, external dataset from woman screened at Karolinska University Hospital, Stockholm, Sweden. We applied logistic regression, using the BRAIx risk score to estimate risks of invasive breast cancers on the test dataset: (1) detected at cohort entry (n=525); and (2) for women given an all clear, diagnosed during the next 4 years either at future screens (n=790) or during intervals between screens (n=308). We also trained full multivariate risk models (logistic regression and elastic net) using the training dataset and evaluated their predictive performance on the test and external validation data, with assessment of familial aspects of the BRAIx risk score achieved with inference about causation from examining changes in regression coefficients in an innovative statistical analysis framework. FINDINGS In both Australian and Swedish test datasets, the BRAIx risk score predicted cancer detection at cohort entry and future cancer risk (all p<0·0001). The BRAIx risk score was the strongest tested explanatory factor for cancer detection at cohort entry (odds ratio 13·80 [95% CI 9·54-20·80] in Australian data; 8·89 [3·19-37·49] in Swedish data) and for intermediate-term cancer risk (2·29 [2·13-2.47] in Australian data; 2·15 [1·85-2·50] in Swedish data). We found that adding a thresholded binary version of the BRAIx risk score significantly improved model fit (p<2·2 × 10-16, Australian and Swedish data) and women with BRAIx risk scores of more than 2 were significantly at many-fold increased risk of intermediate-term cancer than women below that threshold (12·34 [7·33-20·91], Australia; 44·7 [11·9-184·9], Sweden; p<0·0001). For the top 2% of women given an all clear with the highest BRAIx risk score, the probability of a cancer diagnosis within 4 years was 9·7%. The BRAIx risk score explained 23% of why family history predicts 4-year risk (p<0·0001). After fitting the BRAIx risk score in a multivariate model, mammographic density was no longer significantly associated with breast cancer risk in the Australian test data (p>0·05) and became associated with lower risk for intermediate-term cancer in the external Swedish test dataset (0·83 [0·73-0·95]). INTERPRETATION The BRAIx risk score is a strong intermediate-term predictor of breast cancer (current to 4-year risk). Calibrating the score on a training dataset produces population-specific probabilities for calculating individual-specific risk scores for screening clients based on their mammogram images. These risk scores enable future development of personalised screening pathways to transform population breast cancer screening and save lives. Identification of women given an all clear but at very high risk, similar to those carrying BRCA1 and BRCA2 mutations, could reveal insights into both familial and non-familial causes of breast cancer. FUNDING Australian Government Medical Research Future Fund, the Ramaciotti Foundation, the National Breast Cancer Foundation, Cancer Australia, and the National Health and Medical Research Council.

In the rapidly evolving landscape of software engineering, the demand for robust and secure systems has become increasingly critical. This is especially true for self-adaptive systems due to their complexity and the dynamic environments in which they operate. To address this issue, we designed and developed the SAFT-GT toolchain that tackles the multifaceted challenges associated with ensuring both safety and security. This paper provides a comprehensive description of the toolchain's architecture and functionalities, including the Attack-Fault Trees generation and model combination approaches. We emphasize the toolchain's ability to integrate seamlessly with existing systems, allowing for enhanced safety and security analyses without requiring extensive modifications and domain knowledge. Our proposed approach can address evolving security threats, including both known vulnerabilities and emerging attack vectors that could compromise the system. As a use case for the toolchain, we integrate it into the feedback loop of self-adaptive systems. Finally, to validate the practical applicability of the toolchain, we conducted an extensive user study involving domain experts, whose insights and feedback underscore the toolchain's relevance and usability in real-world scenarios. Our findings demonstrate the toolchain's effectiveness in real-world applications while highlighting areas for future improvements. The toolchain and associated resources are available in an open-source repository to promote reproducibility and encourage further research in this field.

BACKGROUND Newborn screening (NBS) for severe combined immunodeficiency (SCID) using T cell receptor excision circles (TREC) in dried blood spots (DBS) has been implemented in the U.S. and many other regions and countries globally. The Clinical Immunology Society (CIS) and the Association of Public Health Laboratories (APHL) jointly formed the SCID Harmonization Initiative to facilitate comparison of NBS reporting practices to promote global consensus and collaboration. OBJECTIVE To assess current NBS SCID practices using a global survey and to report the findings from the Phase 1 component. METHODS An eighteen-question survey was distributed to all known SCID screening programs worldwide. Only one response per region was analyzed. Examples of international screening algorithms were also solicited and included. RESULTS A total of 200 responses were received, of which eighty responses were unique and used for further analysis. Of the 39 non-U.S. countries, 15 (38%) reported national universal screening, and 24 (62%) reported regional, pilot, or other screening. Additional questions pertained to methodology and reporting with particular emphasis on communication of the clinical urgency of an abnormal TREC result. CONCLUSIONS This global survey confirmed that the approach to NBS SCID varies widely, underscoring the need for harmonization at multiple steps, particularly for reporting and interpretation. This is the first study to capture global NBS SCID practices, and these findings provide the basis for creation of a Phase 2 consensus reporting framework, which will be developed by the same SCID Harmonization Committee that created the current study.

Background/Objectives: Heart rate variability (HRV) is a non-invasive marker of autonomic nervous system function with established prognostic value after acute coronary syndrome (ACS). The clinical relevance of temporal changes in short-term HRV remains insufficiently defined. This study evaluated short-term HRV dynamics and their association with mortality after ACS. Methods: This retrospective–prospective study included 230 patients with acute myocardial infarction. Five-minute resting ECG recordings were obtained on day 1 and day 21. Time- and frequency-domain HRV parameters were analyzed, and delta values were calculated. The primary endpoint was overall mortality. Survival was assessed using Kaplan–Meier analysis and Cox regression. Results: Patients who died during follow-up had lower HRV values on day 21 and more pronounced declines in selected parameters. In multivariable analysis, decreased ΔLF and shorter RR intervals independently predicted overall mortality. Conclusions: Short-term HRV provides a practical bedside assessment of autonomic function after ACS. Unfavorable temporal changes likely reflect persistent autonomic imbalance and may offer additional prognostic insight. Larger contemporary studies are needed to confirm these findings.

Background/Objectives: Aortic stenosis is associated with autonomic nervous system (ANS) imbalance, while diabetes mellitus is a major contributor to cardiac autonomic neuropathy. Their coexistence may result in more pronounced autonomic dysfunction not fully captured by conventional assessment. This study aimed to compare ANS function in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement (TAVR), according to diabetes status. Methods: This cross-sectional study included 74 patients with severe aortic stenosis referred for TAVR, including 21 patients with diabetes mellitus. Autonomic function was evaluated using non-invasive ECG-based analysis, incorporating short-term and 24 h Holter-derived heart rate variability (HRV), nonlinear Poincaré plot indices, and deceleration and acceleration capacity. Ambulatory blood pressure monitoring and standard clinical and echocardiographic assessment were performed. Results: Patients with diabetes mellitus demonstrated significantly lower long-term HRV parameters and reduced nonlinear Poincaré plot indices compared with non-diabetic patients, indicating altered autonomic modulation. Short-term HRV showed similar trends without statistical significance. Echocardiographic severity of aortic stenosis and left ventricular systolic function were comparable between groups. Conclusions: Autonomic dysfunction appears to be more pronounced in patients with severe aortic stenosis and diabetes mellitus, predominantly affecting parasympathetic modulation. ECG-derived autonomic parameters may offer complementary insight into ANS involvement in this population and warrant further investigation.

BACKGROUND Breast cancer is a leading cause of mortality and morbidity among females worldwide. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, we provided an updated comprehensive assessment of the epidemiological trends, disease burden, and risk factors associated with breast cancer globally, regionally, and nationally from 1990 to 2023. METHODS Breast cancer incidence, mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) were estimated by age and sex for 204 countries and territories from 1990 to 2023. Mortality estimates were generated using GBD Cause of Death Ensemble models, leveraging data from population-based cancer registration systems, vital registration systems, and verbal autopsies. Mortality-to-incidence ratios were calculated to derive both mortality and incidence estimates. Prevalence was calculated by combining incidence and modelled survival estimates. YLLs were established by multiplying age-specific deaths with the GBD standard life expectancy at the age of death. YLDs were estimated by applying disability weights to prevalence estimates. The sum of YLLs and YLDs equalled the number of DALYs. Breast cancer burden attributable to seven risk factors was examined through the comparative risk assessment framework. The GBD forecasting framework was used to forecast breast cancer incidence and mortality from 2024 to 2050. Age-standardised rates were calculated for each metric using the GBD 2023 world standard population. FINDINGS In 2023, there were an estimated 2·30 million (95% uncertainty interval [UI] 2·01 to 2·61) breast cancer incident cases, 764 000 deaths (672 000 to 854 000), and 24·1 million (21·3 to 27·5) DALYs among females globally. In the World Bank low-income group, where a low age-standardised incidence rate (ASIR) was estimated (44·2 per 100 000 person-years [31·2 to 58·4]), the age-standardised mortality rate (ASMR) was the highest (24·1 per 100 000 [16·8 to 31·9]). The highest ASIR was in the high-income group (75·7 per 100 000 [67·1 to 84·0]), and the lowest ASMR was in the upper-middle-income group (11·2 per 100 000 [10·2 to 12·3]). Between 1990 and 2023, the ASIR in the low-income group increased by 147·2% (38·1 to 271·7), compared with a 1·2% (-11·5 to 17·2) change in the high-income group. The ASMR decreased in the high-income group, changing by -29·9% (-33·6 to -25·9), but increased by 99·3% (12·5 to 202·9) in the low-income group. The increase in age-standardised DALY rates followed that of ASMRs. Risk factors such as dietary risks, tobacco use, and high fasting plasma glucose contributed to 28·3% (16·6 to 38·9) of breast cancer DALYs in 2023. The risk factors with a decrease in attributable DALYs between 1990 and 2023 were high alcohol use and tobacco. By 2050, the global incident cases of breast cancer among females were forecast to reach 3·56 million (2·29 to 4·83), with 1·37 million (0·841 to 2·02) deaths. INTERPRETATION The stable incidence and declining mortality rates of female breast cancer in high-income nations reflect success in screening, diagnosis, and treatment. In contrast, the concurrent rise in incidence and mortality in other regions signals health system deficits. Without effective interventions, many countries will fall short of the WHO Global Breast Cancer Initiative's ambitious target of achieving an annual reduction of 2·5% in age-standardised mortality rates by 2040. The mounting breast cancer burden, disproportionately affecting some of the world's most vulnerable populations, will further exacerbate health inequalities across the globe without decisive immediate action. FUNDING Gates Foundation, St Jude Children's Research Hospital.

Background Community pharmacies must balance public health obligations with economic sustainability. However, integrated methods that jointly manage medical and non-medical inventory in community pharmacies in LMICs are limited. Objective To develop and apply a dual-matrix model separating medical from non-medical products into operational control categories and introducing a High–Medium–Low profitability (HML-P) classification. Methods We conducted a retrospective, descriptive analysis of all items handled in six community pharmacies in the Republic of Srpska, Bosnia and Herzegovina, during the analyzed 2022 year (12-month period) (n = 10,541). Medical products were classified by Always Better Control (ABC) by purchase value and Fast-/Slow-/Non-moving (FSN) by dispensing frequency (predefined thresholds: >4/day = F, 1–4 = S, <1 = N) to form an ABC–FSN matrix. Non-medical products were classified by ABC and a new HML-P scheme (expert-defined Pareto cut-offs: 70%/20%/10% of cumulative gross profit) to form an ABC–HML-P matrix. Each matrix was consolidated into three control categories: I (strict), II (moderate) and III (minimal). Results Non-medical products constituted 76.4% of all items. The ABC–FSN matrix identified Im = 149 medical products for strict control, while the non-medical ABC–HML-P matrix identified Inm = 580 items for strict control and a large segment for minimal oversight (IIInm = 6218). A pronounced Pareto pattern was observed (≈10% of items accounted for 70% of spend and 70% of gross profit), alongside low daily movement (only 3.2% dispensed ≥1/day). Conclusions The proposed dual-matrix model provides a practical decision-support tool for community pharmacies. It helps prioritize availability of patient-critical medical products while supporting economic sustainability.

BACKGROUND Meningitis remains the leading infectious cause of neurological disabilities globally, disproportionately affecting children younger than 5 years and populations in the African meningitis belt. Whereas previous global estimates focused on ten pathogen categories, this study presents the most comprehensive analysis to date, assessing the meningitis burden attributable to 17 causative pathogens based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 framework. METHODS GBD is a systematic, scientific effort aimed at quantifying the comparative magnitude of health loss caused by diseases, injuries, and risk factors across age groups, sexes, and geographical locations over time. We estimated meningitis mortality using the Cause of Death Ensemble model (CODEm) and morbidity using DisMod-MR 2.1, incorporating data from vital registration, verbal autopsy, surveillance, hospital data, and systematic reviews. Aetiology-specific estimates were generated with pathogen-linked case-fatality ratios and splined binomial regression models. Risk factor attribution was based on established risk-outcome pairs and population attributable fractions. FINDINGS In 2023, there were 259 000 (95% uncertainty interval 202 000-335 000) global deaths and 2·54 million (2·20-2·93) incident cases of meningitis. Children younger than 5 years accounted for more than a third of deaths (86 600 [53 300-149 000]). Streptococcus pneumoniae, Neisseria meningitidis, non-polio enteroviruses, and other viruses were the leading causes of death, while non-polio enteroviruses caused the most cases. The four WHO-defined preventable meningitis pathogens of interest (S pneumoniae, N meningitidis, Haemophilus influenzae, and Group B streptococcus) contributed to 98 700 deaths (77 000-127 000) and 594 000 cases (514 000-686 000). Low birthweight, short gestation, and household air pollution were the top risk factors for meningitis-related mortality. INTERPRETATION Although mortality and incidence have declined significantly since 1990, progress is insufficient to meet WHO 2030 targets. Despite marked progress in reducing bacterial meningitis via global vaccination campaigns, a substantial meningitis burden persists, attributable both to common pathogens such as S pneumoniae and N meningitidis and to emerging non-bacterial pathogens such as Candida spp and drug-resistant fungi. Achieving WHO goals will require sustained investment in surveillance, vaccination, maternal screening, and health-system strengthening, especially in high-burden settings. FUNDING Gates Foundation, Wellcome Trust, and UK Department of Health and Social Care.

Abstract This study was aimed to investigate awareness of periodontitis among undergraduate students at a faculty of medicine in Bosnia and Herzegovina. This cross-sectional study was conducted among undergraduate students of the Faculty of Medicine Foca enrolled in three study programs (Medicine, Nursing, and Special Education and Rehabilitation). Knowledge and awareness of periodontitis were collected using a structured questionnaire. Approximately 58% of students had heard the term periodontitis. Higher percentage of Medicine and Nursing students identified Gum Recession, Bleeding Gums, Tooth Loss and Loose Tooth as common symptoms of periodontitis compared to Special Education and Rehabilitation students. Knowledge of risk factors for periodontitis differed between the groups, with Nursing students showing greater awareness but also incorrect recognizing of several risk factors. About one third of students answered that Diabetes Mellitus is related to periodontitis (32.4%). Significantly lower percentage of Nursing students assessed their knowledge of periodontitis as poor compared to Medicine and Special Education and Rehabilitation students. The findings revealed a lack of adequate knowledge of periodontitis across all the observed study programs. Strengthening periodontal education within undergraduate curricula is essential, particularly considering the established links between periodontal and systemic diseases.

Oxidative stress is a critical pathophysiological factor in sepsis. Ursodeoxycholic acid (UDCA), a bile acid with anti-inflammatory, antioxidant, and anti-apoptotic properties, may protect against lipopolysaccharide (LPS)-induced myocardial injury. In an experimental study, 32 male Wistar rats were randomly assigned to four groups: control, LPS, UDCA, and UDCA + LPS. UDCA was administered orally for 10 days prior to LPS-induced endotoxemia. Serum levels of high-sensitive troponin I (hsTnI), homocysteine, and oxidative stress markers were measured, and immunohistochemistry and immunofluorescence were used to assess inflammation (nuclear factor kappa B, NF-κB), apoptosis (caspase 3), and signaling pathways related to protein kinase B (Akt)/NF-κB and silent information regulator 1 (SIRT1)/nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1). UDCA pretreatment significantly reduced myocardial pathological changes, serum hsTnI, homocysteine, and total oxidative stress compared with LPS alone. It enhanced catalase (CAT) activity and glutathione (GSH) levels while lowering thiobarbituric acid reactive substances (TBARS) and nitrite concentrations in cardiac tissue. UDCA modulated cellular signaling by decreasing Akt phosphorylation and activating the SIRT1/Nrf2/HO-1 pathway. These results indicate that UDCA protects the heart from LPS-induced damage by reducing oxidative stress, inflammation, and apoptosis. UDCA modulates cellular signaling by decreasing pro-inflammatory pathways and activating anti-inflammatory pathways associated with SIRT1/Nrf2/HO-1 signaling, emphasizing its key role in myocardial protection during sepsis.

Microscopic models of the thermodynamic and transport phenomena of solids are included in the curricula of subjects dealing with these topics at all levels of education. However, a review of the research conducted shows that students of different age groups have many incorrect ideas about these phenomena. The incorrect ideas uncovered often stem from the abstract nature, complexity, and microscopic properties associated with the concepts involved. To effectively assess students’ understanding of the microscopic models of electrical and thermal conductivity of solids, a concept inventory named the METCS concept test was developed. This test encompasses a wide range of relevant concepts. Conducting the METCS test with a cohort of Croatian university students not only reaffirmed some previously acknowledged incorrect ideas but also revealed many new ones. It is important to gain insight into these ideas as this can support the development of targeted tutorials and teaching materials. These resources can help educators improve learning outcomes related to METCS concepts and ultimately promote deeper understanding among students.

Strong‐field ionization by thermal light is studied. Even though thermal light can be considered as completely classical stochastic light, it can also be treated as quantum light in the sense that it can be represented by a superposition of coherent states, similarly as has been done for the bright squeezed vacuum light, for example. Such a distribution over coherent states contains components with an intensity much higher than the average intensity of the thermal light. This increases the ionization probability by many orders of magnitude. For low intensities, in the multiphoton regime, the enhancement is by the factor of K!$K!$ , with K$K$ the multiphoton order of the process. This result is in agreement with an old experiment [Phys. Rev. Lett. 32 (1974): 265] in which a similar enhancement factor appears if a multimode laser pulse is used instead of a single‐mode pulse. It is also shown that the plateau length in high‐order above‐threshold ionization by thermal light is extended by an order of magnitude in comparison with that of coherent laser light with the same average intensity.