Cellular death, aging, and tissue damage trigger inflammation that leads to enzymatic and non-enzymatic lipid peroxidation of polyunsaturated fatty acids present on cellular membranes and lipoproteins. This results in the generation of highly reactive degradation products, such as malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE), that covalently modify free amino groups of proteins and lipids in their vicinity. These newly generated neoepitopes represent a unique set of damage-associated molecular patterns (DAMPs) associated with oxidative stress termed oxidation-specific epitopes (OSEs). OSEs are enriched on oxidized lipoproteins, microvesicles, and dying cells, and can trigger sterile inflammation. Therefore, prompt recognition and removal of OSEs is required to maintain the homeostatic balance. This is partially achieved by various humoral components of the innate immune system, such as natural IgM antibodies, pentraxins and complement components that not only bind OSEs but in some cases modulate their pro-inflammatory potential. Natural IgM antibodies are potent complement activators, and 30% of them recognize OSEs such as oxidized phosphocholine (OxPC-), 4-HNE-, and MDA-epitopes. Furthermore, OxPC-epitopes can bind the complement-activating pentraxin C-reactive protein, while MDA-epitopes are bound by C1q, C3a, complement factor H (CFH), and complement factor H-related proteins 1, 3, 5 (FHR-1, FHR-3, FHR-5). In addition, CFH and FHR-3 are recruited to 2-(ω-carboxyethyl)pyrrole (CEP), and full-length CFH also possesses the ability to attenuate 4-HNE-induced oxidative stress. Consequently, alterations in the innate humoral defense against OSEs predispose to the development of diseases associated with oxidative stress, as shown for the prototypical OSE, MDA-epitopes. In this mini-review, we focus on the mechanisms of the accumulation of OSEs, the pathophysiological consequences, and the interactions between different OSEs and complement components. Additionally, we will discuss the clinical potential of genetic variants in OSE-recognizing complement proteins – the OSE complotype - in the risk estimation of diseases associated with oxidative stress.

Writing is an integral part of linguistic education of deaf persons which, due to the lack of auditorysensors, has an insurmountable difficulty achieving, so this shortcoming is directly reflected in the general literacyof deaf children. Many detailed studies in the world suggest that in order to become literate, a deaf child must learnthe language of the community. Je/she must first learn the letters and learn to write. About 50% of young deafpeople after high school read and write worse than a ten-year-old hearing child. The aim of this research is toexamine the usage, reading, writing, and comprehension in deaf children of the adverbial clause of place in writtenform and to determine the statistical significance of differences between deaf and hearing children. The study wasconducted on a sample of 140 respondents. The first subsample of subjects, the experimental group consisted of 70deaf students, and the second subsample, a control group of 70 hearing students, of the same chronological age. Themeasurement instrument “Test of writing, and comprehension of an adverbial clause of place” was applied. Thefrequencies and percentages of respondents' responses to the variables were calculated. The F (Fisher) test was usedto determine the statistical significance of the differences between deaf and hearing subjects. The results showed that1.40 % of deaf children are completely successful in reading and writing priloske odredbe, and thaat 90 % of deafchildren use prislocke odredbe partially successfully. The percentage of children that do not use priloske odredbe inany form in their written communication is 8.60%. The order of use of adverbial clause of place by frequency is asfollows: "in", "on", "below", "behind", "next to", and "between". The largest number of deaf children use theadverbial clause of place "in" in their written expression, 65.70% of them. Then, the adverbial clause of place "on"51.14%, the adverbial clause of place "below" 47.14%, the adverbial clause of place "behind" 31.43%, the adverbialclause of place "beside" 30%, and the adverbial clause of place "between" 22.85%.There is a statistically significant difference between deaf and hearing children in the use of the adverbial clause ofplace at the level of statistical significance of p=0.000.

Radiology is integral to cancer care. Compared to molecular assays, imaging has its advantages. Imaging as a noninvasive tool can assess the entirety of tumor unbiased by sampling error and is routinely acquired at multiple time points in oncological practice. Imaging data can be digitally post-processed for quantitative assessment. The ever-increasing application of Artificial intelligence (AI) to clinical imaging is challenging radiology to become a discipline with competence in data science, which plays an important role in modern oncology. Beyond streamlining certain clinical tasks, the power of AI lies in its ability to reveal previously undetected or even imperceptible radiographic patterns that may be difficult to ascertain by the human sensory system. Here, we provide a narrative review of the emerging AI applications relevant to the oncological imaging spectrum and elaborate on emerging paradigms and opportunities. We envision that these technical advances will change radiology in the coming years, leading to the optimization of imaging acquisition and discovery of clinically relevant biomarkers for cancer diagnosis, staging, and treatment monitoring. Together, they pave the road for future clinical translation in precision oncology.

Background: The aim of the present randomized, crossover study was to determine the physiological and cognitive function responses while wearing a facemask during a maximal running aerobic fitness test. Methods: Fourteen healthy, nonsmoking physical education students (age = 17.5 years, height = 1.72 m, body mass = 70.4 kg) volunteered to participate in this study. They carried out a 20 m multistage fitness test (MSFT) while wearing or not a cloth facemask on two separate occasions performed in random order. The “Rating of Perceived Exertion” (RPE) and the d2 test for visual attention were administered and assessed before and immediately after the MSFT for both conditions (with or without a facemask). Results: When wearing the facemask, the participants exhibited lower maximal aerobic speed (p = 0.039), VO2max (p = 0.039), distance covered during the MSFT (p = 0.057), and concentration performance (p < 0.001), when compared with the control situation (without facemask). Moreover, they made more errors compared with the control condition (p = 0.021). The use of a cloth facemask during maximal endurance running tests (such as the MSFT) reduced VO2max, and measures of cognitive performance as assessed by the test of focused visual attention (the d2 test). This data suggests avoiding using a cloth facemask during maximal aerobic fitness tests, and before any tasks that require a high level of visual attention.

The Weibull distribution, with shape parameter $k>0$ and scale parameter $\lambda>0$, is one of the most popular parametric distributions in survival analysis with complete or censored data. Although inference of the parameters of the Weibull distribution is commonly done through maximum likelihood, it is well established that the maximum likelihood estimate of the shape parameter is inadequate due to the associated large bias when the sample size is small or the proportion of censored data is large. This manuscript demonstrates how the Bayesian information-theoretic minimum message length principle coupled with a suitable choice of weakly informative prior distributions, can be used to infer Weibull distribution parameters given complete data or data with type I censoring. Empirical experiments show that the proposed minimum message length estimate of the shape parameter is superior to the maximum likelihood estimate and appears superior to other recently proposed modified maximum likelihood estimates in terms of Kullback-Leibler risk. Lastly, we derive an extension of the proposed method to data with type II censoring.

Principal component analysis (PCA) is perhaps the most widely used method for data dimensionality reduction. A key question in PCA is deciding how many factors to retain. This manuscript describes a new approach to automatically selecting the number of principal components based on the Bayesian minimum message length method of inductive inference. We derive a new estimate of the isotropic residual variance and demonstrate that it improves on the usual maximum likelihood approach. We also discuss extending this approach to finite mixture models of principal component analyzers.

The aim of this manuscript is to introduce the Bayesian minimum message length principle of inductive inference to a general statistical audience that may not be familiar with information theoretic statistics. We describe two key minimum message length inference approaches and demonstrate how the principle can be used to develop a new Bayesian alternative to the frequentist $t$-test as well as new approaches to hypothesis testing for the correlation coefficient. Lastly, we compare the minimum message length approach to the closely related minimum description length principle and discuss similarities and differences between both approaches to inference.

In this short note, we derive a new bias adjusted maximum likelihood estimate for the shape parameter of the Weibull distribution with complete data and type I censored data. The proposed estimate of the shape parameter is significantly less biased and more efficient than the corresponding maximum likelihood estimate, while being simple to compute using existing maximum likelihood software procedures.

The Weibull distribution, with shape parameter $k>0$ and scale parameter $\lambda>0$, is one of the most popular parametric distributions in survival analysis with complete or censored data. Although inference of the parameters of the Weibull distribution is commonly done through maximum likelihood, it is well established that the maximum likelihood estimate of the shape parameter is inadequate due to the associated large bias when the sample size is small or the proportion of censored data is large. This manuscript demonstrates how the Bayesian information-theoretic minimum message length principle coupled with a suitable choice of weakly informative prior distributions, can be used to infer Weibull distribution parameters given complete data or data with type I censoring. Empirical experiments show that the proposed minimum message length estimate of the shape parameter is superior to the maximum likelihood estimate and appears superior to other recently proposed modified maximum likelihood estimates in terms of Kullback-Leibler risk. Lastly, we derive an extension of the proposed method to data with type II censoring.

The rule of law is one of the key concepts in the 21st century. The idea of the rule of law exists to the extent that there are reflections on the state and law, and a relationship between these two concepts. The aim of this paper is to show in one place the development of the idea of the rule of law through history. In this sense, the authors look at the thoughts of philosophers who have largely determined the direction of development of the idea of the rule of law. Of course, not all philosophers who have contemplated the rule of law are listed in the paper, but it nevertheless attempts to show in chronological order how the rule of law as an idea developed from Plato to its modern theorists.

Objective To establish optimised diffusion weightings (‘ b -values’) for acquisition of whole-body diffusion-weighted MRI (WB-DWI) for estimation of the apparent diffusion coefficient (ADC) in patients with metastatic melanoma (MM). Existing recommendations for WB-DWI have not been optimised for the tumour properties in MM; therefore, evaluation of acquisition parameters is essential before embarking on larger studies. Methods Retrospective clinical data and phantom experiments were used. Clinical data comprised 125 lesions from 14 examinations in 11 patients with multifocal MM, imaged before and/or after treatment with immunotherapy at a single institution. ADC estimates from these data were applied to a model to estimate the optimum b -value. A large non-diffusing phantom was used to assess eddy current–induced geometric distortion. Results Considering all tumour sites from pre- and post-treatment examinations together, metastases exhibited a large range of mean ADC values, [0.67–1.49] × 10^−3 mm^2/s, and the optimum high b -value ( b _high) for ADC estimation was 1100 (10th–90th percentile: 740–1790) s/mm^2. At higher b -values, geometric distortion increased, and longer echo times were required, leading to reduced signal. Conclusions Theoretical optimisation gave an optimum b _high of 1100 (10th–90th percentile: 740–1790) s/mm^2 for ADC estimation in MM, with the large range of optimum b -values reflecting the wide range of ADC values in these tumours. Geometric distortion and minimum echo time increase at higher b -values and are not included in the theoretical optimisation; b _high in the range 750–1100 s/mm^2 should be adopted to maintain acceptable image quality but performance should be evaluated for a specific scanner. Key Points • Theoretical optimisation gave an optimum high b-value of 1100 (10th–90th percentile: 740–1790) s/mm ^ 2 for ADC estimation in metastatic melanoma. • Considering geometric distortion and minimum echo time (TE), a b-value in the range 750–1100 s/mm ^ 2 is recommended. • Sites should evaluate the performance of specific scanners to assess the effect of geometric distortion and minimum TE.

The pandemic of COVID-19 has brought many changes in health care systems at all levels of health care. The increase in the number of cases of COVID-19 has led to overuse and misuse of antibiotics.The aim of this study was to compare the consumption of antibiotics for systemic use in outpatients in the Republic of Srpska (RS), before and during the first year of the COVID-19 pandemic, as well as the association between antibiotic consumption and the rate of incidence and mortality of COVID-19. The total consumption of the antibiotics for systemic use (J01) in outpatients in the Republic of Srpska during 2019 was 19.40 DDD/TID, with an increase to 30.80 DDD/TID in 2020.Significantly higher use of penicillin (10.58 ± 11.01 DDD/TID in 2019 vs. 17.10 ± 13.63 DDD/TID in 2020), cephalosporins (2.68 ± 1.90 DDD/TID in 2019 vs. 5.93 ± 2.77 DDD/TID in 2020) and macrolides (2.14 ± 2.22 DDD/TID in 2019 vs. 3.40 ± 3.44 DDD/TID in 2020) was observed during the pandemic period. It is necessary to improve the prescribing practice of antibiotics at the primary health care level, public awareness about rational use of antibiotics, as well as the current antibiotic stewardship programs and control their implementation.