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Introduction/Objective. Acute appendicitis (AA) is by far the most frequent urgent condition in abdominal surgery and numerous biomarkers may help the physician to diagnose and even predict the severity of the disease. The objective of the paper was to determine the accuracy of C-reactive protein (CRP), interleukin-6, and endotoxin level and compare it with the diagnostic value of Alvarado score (AS) in adults surgically treated for AA. Methods. Sixty-seven patients were diagnosed with AA using AS. Prior to surgery serum levels of inflammatory biomarkers were determined and together with AS were respectively compared to the results of histopathological analysis of specimens. The patients were divided into three group according to the histopathological assessment. Results. The univariate analysis revealed that the increase of CRP level by one unit increases the probability of complicated AA (CoAA) occurrence by 1% (1.00–1.02, p < 0.05). ROC curve analysis has revealed that CRP has better capacity to predict suppurative AA (SAAs)/CoAAs than catarrhal AA (CAA), with the cut-off value of 19.45. The increase of AS value by one unit produced 2.98-fold increase of the probability of CoAA occurrence (1.60–5.57, p < 0.001), while positive AS value increases the probability of CoAA occurrence 24.67 times (4.94–123.12; p < 0.001). ROC curve analysis demonstrated that AS may predict CoAAs better than CAAs/SAAs, with the cut-off value of 8.50. Conclusion. AS and CRP should be routinely used combined as powerful tools for the diagnosis and prediction of complicated AA.

Most high-mountain regions worldwide are susceptible to snow avalanches during the winter or all year round. In this study, a Universal Snow Avalanche Modeling Index is developed, suitable for determining avalanche hazard in mountain regions. The first step in the research is the collection of data in the field and their processing in geographic information systems and remote sensing. In the period 2023–2024, avalanches were mapped in the field, and later, avalanches as points in geographic information systems (GIS) were overlapped with the dominant natural conditions in the study area. The second step involves determining the main criteria (snow cover, terrain slope, and land use) and evaluating the values to obtain the Snow Avalanche Formation Index (SAFI). Thresholds obtained through field research and the formation of avalanche inventory were used to develop the SAFI index. The index is applied with the aim of identifying locations susceptible to avalanche formation (source areas). The values used for the calculation include Normalized Difference Snow Index (NDSI > 0.6), terrain slope (20–60°) and land use (pastures, meadows). The third step presents the analysis of SAFI locations with meteorological conditions (winter precipitation and winter air temperature). The fourth step is the modeling of the propagation (simulation) of other parts of the snow avalanche in the Flow-R software 2.0. The results show that 282.9 km2 of the study area (Šar Mountains, Serbia) is susceptible to snow avalanches, with the thickness of the potentially triggered layer being 50 cm. With a 5 m thick snowpack, 299.9 km2 would be susceptible. The validation using the ROC-AUC method confirms a very high predictive power (0.94). The SAFI–Flow-R approach offers snow avalanche modeling for which no avalanche inventory is available, representing an advance for all mountain areas where historical data do not exist. The results of the study can be used for land use planning, zoning vulnerable areas, and adopting adequate environmental protection measures. [ABSTRACT FROM AUTHOR]

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Copyright of Timocki Medicinski Glasnik is the property of Timocki Medicinski Glasnik and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The gut microbiota plays an important role in host metabolism, immunity, digestibility and even behaviour. Candida spec. is common resident of the gastrointestinal tract and integral part of the microbiota. The aim of the study was to evaluate if positive Candida cultures in the stool influence metabolic parameters in type 2DM patients. 46 patients with type 2 DM and oral antidiabetic treatment, were divided into a study group (S=18 patients with positive Candida sp. cultures in stool) and the control group (C= remaining 28 patients). Besides medical history and clinical examination, all patients were tested for coproculture, fasting glycaemia (FPG), HbA1C, total cholesterol (CL) triglycerides (TG), high-density lipoproteins (HDL) and low-density lipoproteins (LDL). Study group patients had a significantly higher BMI (31.41 ± 5.29 vs. 25.18 ± 3.58; p<0.001); HbA1C (9.8 % ± 1.74 vs 6.9% ± 1.89; p<0.05) as well as FPG (10.87 ± 1.35 vs 7.47 ± 1.03; p<0.01), compared to the control group. Even though the study group patients had higher TG, CL, LDL and HDL, compared to the control group, there was no statistical significance verified. Uncontrolled glucoregulation is one of the host condition which favours candida colonization and subsequent infection. This may be related to the decrease in commensal bacteria, probably as the result of yeast-bacterial competition. On the other hand, we have to keep in mindthat a significantly increased number of Candida colonies can affect the rate of digestion and absorption of carbohydrates and consequently increase the level of glycaemia in patients with diabetes. [ABSTRACT FROM AUTHOR]

Copyright of Timocki Medicinski Glasnik is the property of Timocki Medicinski Glasnik and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)