ABSTRACT

The Electronic Medical Record (EMR) provides an opportunity to manage patient care efficiently and accurately. This includes clinical decision support tools for the timely identification of adverse events or acute illnesses preceded by deterioration. This paper presents a machine learning-driven tool developed using real-time EMR data for identifying patients at high risk of reaching critical conditions that may demand immediate interventions. This tool provides a pre-emptive solution that can help busy clinicians to prioritize their efforts while evaluating the individual patient risk of deterioration. The tool also provides visualized explanation of the main contributing factors to its decisions, which can guide the choice of intervention. When applied to a test cohort of 18,648 patient records, the tool achieved 100% sensitivity for prediction windows 2–8 h in advance for patients that were identified at 95%, 85% and 70% risk of deterioration.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disease with a variety of symptoms such as post-exertional malaise, fatigue, and pain, but where aetiology and pathogenesis are unknown. An increasing number of studies have implicated the involvement of the immune system in ME/CFS. Furthermore, a hereditary component is suggested by the reported increased risk for disease in relatives, and genetic association studies are being performed to identify potential risk variants. We recently reported an association with the immunologically important human leucocyte antigen (HLA) genes HLA-C and HLA-DQB1 in ME/CFS. Furthermore, a genome-wide genetic association study in 42 ME/CFS patients reported significant association signals with two variants in the T cell receptor alpha (TRA) locus (P value <5 × 10−8). As the T cell receptors interact with the HLA molecules, we aimed to replicate the previously reported findings in the TRA locus using a large Norwegian ME/CFS cohort (409 cases and 810 controls) and data from the UK biobank (2105 cases and 4786 controls). We investigated numerous SNPs in the TRA locus, including the two previously ME/CFS-associated variants, rs11157573 and rs17255510. No associations were observed in the Norwegian cohort, and there was no significant association with the two previously reported SNPs in any of the cohorts. However, other SNPs showed signs of association (P value <0.05) in the UK Biobank cohort and meta-analyses of Norwegian and UK biobank cohorts, but none survived correction for multiple testing. Hence, our research did not identify any reliable associations with variants in the TRA locus.

In this article, authors attempt to provoke the need of renewed understanding and researching related to the mythologization of the Balkans in Postmodern period. In the midpoint of this article is postmodern critic of international experts for legitimacy in ‘new state democracy’ (for example Bosnia and Herzegovina). Authors will try to make distinction between what is reality on the ground and what is the desirable model of Bosnia and Herzegovina for Europe. Regardless of various processes that are ongoing in Bosnia and Herzegovina, it is not possible to move away from mythological narratives and concepts

The purpose of this article is to introduce to the literature a new extension of the Simple WISP method adapted for utilizing the triangular fuzzy numbers. This extension is proposed to allow the use of the Simple WISP method for addressing decision-making problems related to uncertainties and inaccuracies, as well as for solving problems related to predictions. In addition, this article also discusses the use of linguistic variables to collect the attitudes of the respondents, as well as their transformation into appropriate triangular fuzzy numbers. The article discusses the use of two defuzzification procedures. The first normalization procedure is easy to use, while the second procedure uses the advantages that the application of asymmetric fuzzy numbers gives in terms of analysis. The usability of the proposed extension is presented through two examples.

Background and Objectives Very poor outcome despite IV thrombolysis (IVT) and mechanical thrombectomy (MT) occurs in approximately 1 of 4 patients with ischemic stroke and is associated with a high logistic and economic burden. We aimed to develop and validate a multivariable prognostic model to identify futile recanalization therapies (FRTs) in patients undergoing those therapies. Methods Patients from a prospectively collected observational registry of a single academic stroke center treated with MT and/or IVT were included. The data set was split into a training (N = 1,808, 80%) and internal validation (N = 453, 20%) cohort. We used gradient boosted decision tree machine learning models after k-nearest neighbor imputation of 32 variables available at admission to predict FRT defined as modified Rankin scale 5–6 at 3 months. We report feature importance, ability for discrimination, calibration, and decision curve analysis. Results A total of 2,261 patients with a median (interquartile range) age of 75 years (64–83 years), 46% female, median NIH Stroke Scale 9 (4–17), 34% IVT alone, 41% MT alone, and 25% bridging were included. Overall, 539 (24%) had FRT, more often in MT alone (34%) as compared with IVT alone (11%). Feature importance identified clinical variables (stroke severity, age, active cancer, prestroke disability), laboratory values (glucose, C-reactive protein, creatinine), imaging biomarkers (white matter hyperintensities), and onset-to-admission time as the most important predictors. The final model was discriminatory for predicting 3-month FRT (area under the curve 0.87, 95% CI 0.87–0.88) and had good calibration (Brier 0.12, 0.11–0.12). Overall performance was moderate (F1-score 0.63 ± 0.004), and decision curve analyses suggested higher mean net benefit at lower thresholds of treatment (up to 0.8). Conclusions This FRT prediction model can help inform shared decision making and identify the most relevant features in the emergency setting. Although it might be particularly useful in low resource healthcare settings, incorporation of further multifaceted variables is necessary to further increase the predictive performance.

Peste des petits ruminants (PPR) is an acute disease of small ruminants caused by a morbillivirus. Clinical observation of the disease in the field revealed that several species of small ruminants are affected to varying degrees. This difference in disease-related effects could depend either on the host or on the virulence of the virus strain. A previous study highlighted the difference in virulence between two strains of PPRV used to infect Saanen goats. For this breed, PPRV Morocco 2008 strain (MA08) was highly virulent while PPRV Côte d’Ivoire 1989 (IC89) strain induced mild disease. Experimental studies generally based on healthy and young animals do not permit exploration of the natural variability of the host susceptibility to PPRV. Therefore, building on the previous study on Saanen goats, the current study focussed on this breed of goat and used commercially available animals with an unknown history of infection with other pathogens. Results confirmed the previous disease pattern for PPRV IC89 and MA08 strains. Viral RNA detection, macroscopic and histological lesions were stronger for the highly virulent MA08 strain. We show here for the first time that viral RNA can be detected in the tissues of vaccinated animals. Viral RNA was also detected for the first time in serum samples, which is in agreement with the role of circulating immune cells in transporting the virus into host target organs. Thus, this study provides insight into the pathogenesis of strains of different virulence of PPRV and will help to better understand the onset of the disease.

In recent years, it has been shown that gastrointestinal microflora has a substantial impact on the development of a large number of chronic diseases. The imbalance in the number or type of microbes in the gastrointestinal tract can lead to diseases and conditions, including autism spectrum disorder, celiac disease, Crohn’s disease, diabetes, and small bowel cancers. This can occur as a result of genetics, alcohol, tobacco, chemotherapeutics, cytostatics, as well as antibiotic overuse. Due to this, essential taxa can be lost, and the host’s metabolism can be severely affected. A less known condition called small intestine bacterial overgrowth (SIBO) can be seen in patients who suffer from hypochlorhydria and small intestine cancers. It is characterized as a state in which the bacterial population in the small intestine exceeds 105–106 organisms/mL. The latest examination methods such as double-balloon enteroscopy and wireless capsule endoscopy have the potential to increase the accuracy and precision of diagnosis and provide better patient care. This review paper aims to summarize the effect of the gastrointestinal environment on chronic disease severity and the development of cancers.

BACKGROUND: Stenosis of the carotid arteries, as a consequence of atherosclerosis is the most common cause of cerebrovascular insult (CVI). Severe (>70%) contralateral stenosis or occlusion (SCSO) of the carotid artery may represent an additional pre-operative risk factor  for neurologic incidents.             AIM: The aim of this study was to confirm and compare early perioperative results (0-30 days) of carotid endarterectomy (CEA) in patients with and without SCSO.                 PATIENT AND METHODS: In our retrospective-prospective study, we analysed the results of 273 CEA, divided into two groups based on the presence of significant contralateral stenosis or occlusion (non-SCSO and SCSO groups)             RESULTS: 273 CEA’s were performed, divided into two groups: SCSO groups 40 (14.7%) and non-SCSO group 233 (85.3%). Between the two groups, a statistically significant difference between patients was found (54.1% compared to 87.5%; p<0.0005), CEA with patch angioplasty (25.3% compared to 52.5%; p=0.001),  and CEA with the use of a shunt (3.9% compared to 35%; p<0.0005) in favour of the SCSO group. There was no statistically significant difference (SCSO was not identified as a risk factor) for any type of stroke or mortality. Logistically regression confirmed SCSO to be an independent predictor of 30-day mortality (OR 21.58; 95% CI  1.27-36.3; p= 0.033) and any type of stroke or mortality (OR 9.27; 95% CI  1.61-53.22; p= 0.012). SCSO was not a predictor of any type of stroke within 30 days. Predictors of any type of stroke was dyslipidemia (OR 0.12, 95% CI  0.02-0.76; p= 0.024).             CONCLUSIONS: There was no statistically significant difference in the incidence of early (30 day) perioperative complications between the analysed groups. The percentage of perioperative complications remains within the accepted parameters, and thus, SCSO should not be qualified as a significant risk factor for CEA. We are of the opinion that CEA remains a safe and acceptable options for patients with SCSO, and SCSO should not be a reason for preferential use of carotid stenting.

A graph is locally irregular if the degrees of the end-vertices of every edge are distinct. An edge coloring of a graph G is locally irregular if every color induces a locally irregular subgraph of G. A colorable graph G is any graph which admits a locally irregular edge coloring. The locally irregular chromatic index X'irr(G) of a colorable graph G is the smallest number of colors required by a locally irregular edge coloring of G. The Local Irregularity Conjecture claims that all colorable graphs require at most 3 colors for a locally irregular edge coloring. Recently, it has been observed that the conjecture does not hold for the bow-tie graph B, since B is colorable and requires at least 4 colors for a locally irregular edge coloring. Since B is a cactus graph and all non-colorable graphs are also cacti, this seems to be a relevant class of graphs for the Local Irregularity Conjecture. In this paper we establish that X'irr(G)<= 4 for all colorable cactus graphs.

With a modified version of the Wells-Riley model, we simulated the size distribution and dynamics of five airborne viruses (measles, influenza, SARS-CoV-2, human rhinovirus, and adenovirus) emitted from a speaking person in a typical residential setting over a relative humidity (RH) range of 20–80% and air temperature of 20–25 °C. Besides the size transformation of virus-containing droplets due to evaporation, respiratory absorption, and then removal by gravitational settling, the modified model also considered the removal mechanism by ventilation. The trend and magnitude of RH impact depended on the respiratory virus. For rhinovirus and adenovirus humidifying the indoor air from 20/30 to 50% will be increasing the relative infection risk, however, this relative infection risk increase will be negligible for rhinovirus and weak for adenovirus. Humidification will have a potential benefit in decreasing the infection risk only for influenza when there is a large infection risk decrease for humidifying from 20 to 50%. Regardless of the dry solution composition, humidification will overall increase the infection risk via long-range airborne transmission of SARS-CoV-2. Compared to humidification at a constant ventilation rate, increasing the ventilation rate to moderate levels 0.5 → 2.0 h−1 will have a more beneficial infection risk decrease for all viruses except for influenza. Increasing the ventilation rate from low values of 0.5 h−1 to higher levels of 6 h−1 will have a dominating effect on reducing the infection risk regardless of virus type.

This paper explores the possibilities of applying physics-informed neural networks (PINNs) in topology optimization (TO) by introducing a fully self-supervised TO framework based on PINNs. This framework solves the forward elasticity problem by the deep energy method (DEM). Instead of training a separate neural network to update the density distribution, we leverage the fact that the compliance minimization problem is self-adjoint to express the element sensitivity directly in terms of the displacement field from the DEM model. Thus, no additional neural network is needed for the inverse problem. The method of moving asymptotes is used as the optimizer for updating density distribution. The implementation of Neumann, Dirichlet, and periodic boundary conditions is described in the context of the DEM model. Three numerical examples are presented to demonstrate framework capabilities: (i) compliance minimization in 2D under different geometries and loading, (ii) compliance minimization in 3D, and (iii) maximization of homogenized shear modulus to design 2D metamaterial unit cells. The results show that the optimized designs from the DEM-based framework are very comparable to those generated by the finite element method and shed light on a new way of integrating PINN-based simulation methods into classical computational mechanics problems.

Climate variables including temperature, rainfall intensity, rainfall acidity, and lithological properties are among the most important factors affecting rock weathering. However, the relative contribution of these four factors on rock weathering, especially on chemical weathering, is still unclear. In this study, we carried out a series of weathering-leaching rainfall simulations on four types of badland sediments under controlled conditions of two levels of temperature, rainfall intensity, and rainfall acidity based on the real field data from representative weather scenarios. The main objectives are 1) to explore the progressive change of sample surface and leachate characteristics and 2) to reveal the independent effects of temperature, rainfall intensity, rainfall acidity, and lithology and their relative contribution as well, on both mechanical and chemical weathering. Qualitative analysis on crack development and fragmentation of sample surface and quantitative analysis on the leachate volume, pH, electrical conductivity, and total cation and anion releases of sample leachate together demonstrated that for the investigated sediments, under the conditions of temperature, intensity, and acidity of rain that can be achieved in nature, high drying temperature obviously increases mechanical disintegration by promoting the rate and magnitude of moisture variations (wetting–drying alterations), while high rainfall intensity and acid rain have no obvious effect. Impact and importance of the drying process caused by high temperature between wetting events need more attention, rather than high rainfall intensity. Low temperature, high rainfall intensity, and acid rain contributing more hydrogen ions required for cation exchanges, rock type with more soluble minerals, all promote chemical weathering, and the influence of climatic and lithological factors on chemical weathering decreases in the following order: mineral composition> rainfall intensity > temperature > rainfall acidity. Climatic variations on temperature can modify weathering processes and in that way conditioned hydro-geomorphological processes in badland areas. Such changes should be considered for direct and indirect implications on badland dynamics.

Thiopurines remain recommended as maintenance therapy in patients with inflammatory bowel disease (IBD). Despite their widespread use, long‐term effectiveness data are sparse and safety is an increasingly debated topic which thwarts proper delineation in the current IBD treatment algorithm.