An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella (S.) Dublin, which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-year period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for non-infected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and post-movement measures within a 1-mo time-window may help reduce S. Dublin spread.

ABSTRACT Context: Since beginning of the coronavirus disease (COVID-19) it became clear that severe forms of this infection have primarily affected patients with chronic conditions. Aims: The aim of the study was to explore clinical and epidemiological characteristics associated with COVID 19 outcomes. Settings and Design: The retrospective observational study included 40,692 citizens of Banja Luka County, Bosnia and Herzegovina, who were confirmed as reverse transcriptase polymerase chain reaction (RT-PCR) positive on COVID-19 at a primary healthcare centre from March 2020 to September 2022. Methods and Materials: Epidemiological data were obtained from Web-Medic medical records of patients. The COVID-19 data were obtained from COVID-19 data sheets comprised of patients’ RT-PCR testing forms, surveillance forms for severe acute respiratory syndrome coronavirus-2 status, and a map of their positive and isolated contacts. Statistical Analysis Used: Differences regarding the distributions of patients between groups were analysed using the Pearson chi-square test and Mantel-Haenszel chi-square test for trends, while differences in mean values were compared using an independent sample t-test. Results: The average age of hospitalised patients was significantly higher compared to the age of non-hospitalised patients (P < 0.001). The average age of patients with lethal outcomes was nearly twice as high in comparison to patients with non-lethal outcomes (P < 0.001). Male patients had a higher hospitalization and mortality rate (P < 0.001). The highest hospitalization rate was in patients with chronic renal failure (CRF), diabetes and cardiovascular diseases (CVDs), while the death rate was the highest among patients with CRF and hearth comorbidities. Patients with fatigue and appetite loss had a higher percentage of lethal outcomes. Vaccinated patients had a significantly lower rate of lethal outcome. Conclusions: Clinical symptoms, signs and outcomes, are posing as predictive parameters for further management of COVID-19. Vaccination has an important role in the clinical outcomes of COVID-19.

Prediction of short-term mortality in patients with acute decompensation of liver cirrhosis could be improved. We aimed to develop and validate two machine learning (ML) models for predicting 28-day and 90-day mortality in patients hospitalized with acute decompensated liver cirrhosis. We trained two artificial neural network (ANN)-based ML models using a training sample of 165 out of 290 (56.9%) patients, and then tested their predictive performance against Model of End-stage Liver Disease-Sodium (MELD-Na) and MELD 3.0 scores using a different validation sample of 125 out of 290 (43.1%) patients. The area under the ROC curve (AUC) for predicting 28-day mortality for the ML model was 0.811 (95%CI: 0.714- 0.907; p < 0.001), while the AUC for the MELD-Na score was 0.577 (95%CI: 0.435–0.720; p = 0.226) and for MELD 3.0 was 0.600 (95%CI: 0.462–0.739; p = 0.117). The area under the ROC curve (AUC) for predicting 90-day mortality for the ML model was 0.839 (95%CI: 0.776- 0.884; p < 0.001), while the AUC for the MELD-Na score was 0.682 (95%CI: 0.575–0.790; p = 0.002) and for MELD 3.0 was 0.703 (95%CI: 0.590–0.816; p < 0.001). Our study demonstrates that ML-based models for predicting short-term mortality in patients with acute decompensation of liver cirrhosis perform significantly better than MELD-Na and MELD 3.0 scores in a validation cohort.

The need for a systematic approach in developing new metal-based drugs with dual anticancer-antimicrobial properties is emphasized by the vulnerability of cancer patients to bacterial infections. In this context, a novel organometallic assembly was designed, featuring ruthenium(II) coordination with p-cymene, one chlorido ligand, and a bidentate neutral Schiff base derived from 4-methoxybenzaldehyde and N,N-dimethylethylenediamine. The compound was extensively characterized in both solid-state and solution, employing single crystal X-ray diffraction, nuclear magnetic resonance, infrared, ultraviolet-visible spectroscopy, and density functional theory, alongside Hirshfeld surface analysis. The hydrolysis kinetic was thoroughly investigated, revealing the important role of the chloro-aqua equilibrium in the dynamics of binding with deoxyribonucleic acid and bovine serum albumin. Notably, the aqua species exhibited a pronounced affinity for deoxyribonucleic acid, engaging through electrostatic and hydrogen bonding interactions, while the chloro species demonstrated groove-binding properties. Interaction with albumin revealed distinct binding mechanisms. The aqua species displayed covalent binding, contrasting with the ligand-like van der Waals interactions and hydrogen bonding observed with the chloro specie. Molecular docking studies highlighted site-specific interactions with biomolecular targets. Remarkably, the compound exhibited wide spectrum moderate antimicrobial activity against Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans, coupled with low micromolar cytotoxic activity against human colorectal adenocarcinoma cells and significant activity against human leukemic monocyte lymphoma cells. The presented findings encourage further development of this compound, promising avenues for its evolution into a versatile therapeutic agent targeting both infectious diseases and cancer.

Solvents prepared from natural terpenes (menthol and thymol), as H-bond acceptors, and a series of organic acids (chain lengths of 8, 10, and 14 C atoms), as H-bond donors, were characterized and tested as reaction media for liquid–liquid extraction purposes. Due to their high hydrophobicity, they seem to be promising alternatives to conventional (nonpolar and toxic) solvents, since they possess relatively less toxic, less volatile, and consequently, more environmentally friendly characteristics. Assuming that the equilibrium is established between solvent and analyte during a ligandless procedure, it can be concluded that those nonpolar solvents can efficiently extract nonpolar analytes from the aqueous environment. Previous investigations showed a wide range of applications, including their use as solvents in extractions of metal cations, small molecules, and bioactive compounds for food and pharmaceutical applications. In this work, hydrophobic solvents based on natural terpenes, which showed chemical stability and desirable physicochemical and thermal properties, were chosen as potential reaction media in the liquid–liquid extraction (LLE) procedure for Pb(II) removal from aqueous solutions. Low viscosities and high hydrophobicities of prepared solvents were confirmed as desirable properties for their application. Extraction parameters were optimized, and chosen solvents were applied. The results showed satisfactory extraction efficiencies in simple and fast procedures, followed by low solvent consumption. The best results (98%) were obtained by the thymol-based solvent, thymol–decanoic acid (Thy-DecA) 1:1, followed by L-menthol-based solvents: menthol–octanoic acid (Men-OctA) 1:1 with 97% and menthol–decanoic acid (Men-DecA) 1:1 with 94.3% efficiency.

Diagnosing intracardiac masses poses a complex, multimodal challenge. We present the case of a 72-year-old woman with a history of rheumatic fever leading to mitral stenosis and a previous mitral valve commissurotomy who reported fatigue, weakness, and palpitations over the past three months. Echocardiography revealed a tumor (53 × 40 mm) in the enlarged left atrium, attached by a wide base to the left atrium wall, exhibiting variable densities. Computerized tomography identified a heterodense mass (53 × 46 × 37 mm) with similar attachments. Angiography showed two branches from the circumflex artery intricately associated with the mass. Despite unsuccessful embolization of the mass’ blood supply, surgical intervention including mitral valve replacement, tricuspid valve annuloplasty, and tumor removal was pursued. Pathohistological analysis confirmed the mass as a thrombus. During the postoperative follow-up, the patient presented with no complaints. Follow-up echocardiography indicated the normal function of the mechanical mitral valve prosthesis and the absence of intracardiac masses. While it remains unknown whether this neovascularization is specific to patients with severe mitral valve disease, this case highlights the diagnostic challenges of differentiating between thrombi and tumors in the context of mitral valve disease. It illustrates the critical role of multimodal imaging in elucidating the anatomical and functional relationships within the heart, thereby guiding accurate diagnosis and effective treatment.

Introduction Technical advances and the increasing role of interdisciplinary decision-making may warrant formal definitions of expertise in surgical neuro-oncology. Research question The EANS Neuro-oncology Section felt that a survey detailing the European neurosurgical perspective on the concept of expertise in surgical neuro-oncology might be helpful. Material and methods The EANS Neuro-oncology Section panel developed an online survey asking questions regarding criteria for expertise in neuro-oncological surgery and sent it to all individual EANS members. Results Our questionnaire was completed by 251 respondents (consultants: 80.1%) from 42 countries. 67.7% would accept a lifetime caseload of >200 cases and 86.7% an annual caseload of >50 as evidence of neuro-oncological surgical expertise. A majority felt that surgeons who do not treat children (56.2%), do not have experience with spinal fusion (78.1%) or peripheral nerve tumors (71.7%) may still be considered experts. Majorities believed that expertise requires the use of skull-base approaches (85.8%), intraoperative monitoring (83.4%), awake craniotomies (77.3%), and neuro-endoscopy (75.5%) as well as continuing education of at least 1/year (100.0%), a research background (80.0%) and teaching activities (78.7%), and formal interdisciplinary collaborations (e.g., tumor board: 93.0%). Academic vs. non-academic affiliation, career position, years of neurosurgical experience, country of practice, and primary clinical interest had a minor influence on the respondents’ opinions. Discussion and conclusion Opinions among neurosurgeons regarding the characteristics and features of expertise in neuro-oncology vary surprisingly little. Large majorities favoring certain thresholds and qualitative criteria suggest a consensus definition might be possible.