Primary Omental Torsion in an Old Woman: Imaging Techniques Can Prevent Unnecessary Surgical Interventions

Torsion and/or infarction of the greater omentum are rare but well-recognized clinical situations which present as an acute abdomen. The etiology is unknown and speculative. In most cases, the pathology is right sided and clinical presentation consists of an acute or subacute flank pain with mild peritonism usually evoking appendicitis or cholecystitis. Nevertheless, knowledge concerning these two problems can help the surgeon in proper diagnosis and treatment. Since the first report on primary torsion by Eitel in 1899, a few hundred more have been reported and some collective reviews published to date. Recently, ultra sonography and computed tomography have proved to provide sufficiently typical, consistent, and well-recognizable features to avoid unnecessary surgery. In this study, we will present a case diagnosed as primary omental torsion based on computed tomography, which underwent successful conservative management

Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems

Smart buildings are increasingly using Internet of Things (IoT)-based wireless sensing systems to reduce their energy consumption and environmental impact. As a result of their compact size and ability to sense, measure, and compute all electrical properties, Internet of Things devices have become increasingly important in our society. A major contribution of this study is the development of a comprehensive IoT-based framework for smart city energy management, incorporating multiple components of IoT architecture and framework. An IoT framework for intelligent energy management applications that employ intelligent analysis is an essential system component that collects and stores information. Additionally, it serves as a platform for the development of applications by other companies. Furthermore, we have studied intelligent energy management solutions based on intelligent mechanisms. The depletion of energy resources and the increase in energy demand have led to an increase in energy consumption and building maintenance. The data collected is used to monitor, control, and enhance the efficiency of the system

Tuning the physicochemical, structural, and antimicrobial attributes of whey-based poly (L-Lactic Acid) (PLLA) films by Chitosan Nanoparticles

Recently, the research and innovation to produce raw materials from microbial processes has gained much attention due to their economic and environmental impacts. Lactic acid is a very important microbial product due to its wide application in the food, pharmaceutical, cosmetic, and chemical industries. In the current study, poly (L-lactic acid) (PLLA) was produced by the ring opening polymerization (ROP) technique of L-lactic acid recovered from whey fermentation, and was used for the production of nanocomposites films reinforced with chitosan nanoparticles (CNPs) (average diameter ca. 100–200 nm). Three different CNPs concentrations, namely 1, 3, and 5% w/w, were tested, and their influence on the physical, mechanical, thermal, antibacterial and structural attributes of PLLA film was assessed. The results showed that the addition of CNPs up to 3% caused a significant improvement in water vapor permeability, appearance, tensile strength and elongation at break. The antibacterial properties of nanocomposites followed a dose-depended pattern as a result of CNPs addition. Therefore, the best inhibitory effects on Escherichia coli and Staphylococcus aureus was made by the addition of 5% of CNPs and lower dosages slightly affected the growth of pathogens or didn\u27t cause any inhibitory effects (in 1% of CNPs). It can be concluded that the incorporation of CNPs into the PLLA matrix allows to improve the structural, thermal, physical, mechanical and antibacterial properties of the polymer, generating promising systems for food packaging and biomedical applications

Physicochemical, thermal and rheological properties of pectin extracted from sugar beet pulp using subcritical water extraction process

The objective of this study was to characterize the properties of pectin extracted from sugar beet pulp using subcritical water (SWE) as compared to conventional extraction (CE). The research involved advanced modeling using response surface methodology and optimization of operational parameters. The optimal conditions for maximum yield of pectin for SWE and CE methods were determined by the central composite design. The optimum conditions of CE were the temperature of 90 °C, time of 240 min, pH of 1, and pectin recovery yield of 20.8%. The optimal SWE conditions were liquid-to-solid (L/S) ratio of 30% (v/w) at temperature of 130 °C for 20 min, which resulted in a comparable yield of 20.7%. The effect of obtained pectins on viscoamylograph pasting and DSC thermal parameters of corn starch was evaluated. The contents of galacturonic acid, degree of methylation, acetylation, and ferulic acid content were higher in the pectin extracted by SWE, while the molecular weight was lower. Similar chemical groups were characterized by FTIR in both SWE and CE pectins. Color attributes of both pectins were similar. Solutions of pectins at lower concentrations displayed nearly Newtonian behavior. The addition of both pectins to corn starch decreased pasting and DSC gelatinization parameters, but increased ΔH. The results offered a promising scalable approach to convert the beet waste to pectin as a value-added product using SWE with improved pectin properties.Axencia Galega de Innovación | Ref. IN607A2019 / 0

Antiphospholipid antibodies and COVID-19 mortality and thrombotic events; A systematic review and meta-analysis

Introduction:Among various proposed pathologic mechanisms during the coronavirus disease 2019 (COVID-19) pandemic, overproduction of autoantibodies is not widely studied. Antiphospholipid antibodies (aPLs) are target proteins that have affinity toward charged phospholipids. APLs are thought to have pro-thrombotic potentials that increase during thromboembolism. The present systematic review and meta-analysis aimed to evaluate the relationship between serum aPLs level and COVID-19 mortality, severity, and thrombotic events.Methods: This systematic review and meta-analysis was conducted on all open access published articles in Medline, Scopus and Google Scholar. Studies evaluating individuals over the age of 18 years who were diagnosed with COVID-19 and had positive aPLs; and provided data on mortality or thrombotic events were included. Results: Of the initially identified 512 articles, 22 studies (overall 1462 patients) were finally included in the analysis. The prevalence of positive aPLs was 48.1%. Among the 372 patients with positive aPLs, 156 patients (41.9%) had severe COVID-19 that indicated a significant relationship between COVID-19 severity and aPLs positivity (p<0.05). The prevalence of thrombotic events in aPLs positive patients was 26.3% that indicated a significant relationship between aPLs positivity and the development of thrombotic events (p=0.03). APLs positivity was related to anytime mortality in COVID-19 patients (p=0.01).Conclusion: The present review demonstrated that aPLs are linked to COVID-19 severity and thrombotic events but not short-term mortality. Further studies with longer follow up periods are warranted

Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

Background The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. Methods We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. Findings In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. Interpretation The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively. Funding The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38)

On the role of topographic amplification in seismic slope instabilities

Surface wave generation due to body wave propagation near ground surface has been discussed in the literature. This phenomenon, typically occurring in topographic changing areas, along with its interaction with body waves (SV), decreases precision of formulas for evaluation of slope displacement. This significant fact caused the researchers not only to investigate the combined surface and SV waves motion pattern, but also to consider its effect on structures built on the slopes. In order to reveal the phenomenon, several finite element numerical studies have been performed by ABAQUS programme. Besides, two physical model slopes simulating the landslide occurrence have been constructed and tested by shaking table device. The results of induced and calculated accelerations obtained by two approaches have been compared and Rayleigh wave generation has been proved. Furthermore, the slope displacements have been calculated by various empirical methods and the results were compared with numerical ones. The results proved that in order to increase the precision of empirical formulas for displacement prediction, surface wave effect should be taken into account. Finally, a concept of “effective depth of surficial amplification” is introduced and its effect on dynamic slope stability is analysed

EXTENSION OF MCDM METHOD FOR SUPPLIER SELECTION PROBLEM WITH INTERVAL NUMBERS BASED ON OBJECTIVE WEIGHTING

Selecting the most appropriate supplier is considered to be the main primary concern in supply chain because the producers spend most of their time on supplying the raw materials and spare parts. Moreover a lion’s share of cost is allocated to buying goods and services. During the past years there were many methods to evaluate and select the suppliers but traditional models of supplier selection were based on quantitative data and they paid less attention to qualitative and imprecise data. In this paper a compromise solution of interval VIKOR is presented to develop a method for evaluating and selecting the appropriate suppliers. On the other hand, the objective weights based on Shannon entropy which is fitted with imprecise data are used to eliminate the mental error caused by subjective judgment. At the end a numerical example is presented to demonstrate the application of proposed method in selecting the suppliers

Identification of novel putative alleles related to important agronomic traits of wheat using robust strategies in GWAS

Abstract Principal component analysis (PCA) is widely used in various genetics studies. In this study, the role of classical PCA (cPCA) and robust PCA (rPCA) was evaluated explicitly in genome-wide association studies (GWAS). We evaluated 294 wheat genotypes under well-watered and rain-fed, focusing on spike traits. First, we showed that some phenotypic and genotypic observations could be outliers based on cPCA and different rPCA algorithms (Proj, Grid, Hubert, and Locantore). Hubert’s method provided a better approach to identifying outliers, which helped to understand the nature of these samples. These outliers led to the deviation of the heritability of traits from the actual value. Then, we performed GWAS with 36,000 single nucleotide polymorphisms (SNPs) based on the traditional approach and two robust strategies. In the conventional approach and using the first three components of cPCA as population structure, 184 and 139 marker-trait associations (MTAs) were identified for five traits in well-watered and rain-fed environments, respectively. In the first robust strategy and when rPCA was used as population structure in GWAS, we observed that the Hubert and Grid methods identified new MTAs, especially for yield and spike weight on chromosomes 7A and 6B. In the second strategy, we followed the classical and robust principal component-based GWAS, where the first two PCs obtained from phenotypic variables were used instead of traits. In the recent strategy, despite the similarity between the methods, some new MTAs were identified that can be considered pleiotropic. Hubert's method provided a better linear combination of traits because it had the most MTAs in common with the traditional approach. Newly identified SNPs, including rs19833 (5B) and rs48316 (2B), were annotated with important genes with vital biological processes and molecular functions. The approaches presented in this study can reduce the misleading GWAS results caused by the adverse effect of outlier observations

Nitrate Removal from Contaminated Waters by Using Anion Exchanger Phragmites Australis Nanoparticles

The efficiency of modified Phragmites australis nanoparticles for nitrate removal from aqueous solution in batch and continuous conditions was studied. The effect of different operating conditions such as pH, the amount of adsorbent, and initial nitrate concentration were surveyed. Our results showed that, pH 6 could provide better condition for nitrate removal. The increase in the nitrate concentration from 5 to 120mg L-1 reduced the efficiency from 90% to 67%. Kinetics and isotherm data revealed that the nitrate adsorption successfully can be described by pseudo-second order kinetic model (R2 =1) and Longmuir isotherm (R2 =0.99), respectively. At the continuous-flow mode, column were operated at 0.98 L hr-1 and 2.27 L hr-1 with initial nitrate concentration of 15, 50 and 120 mg L-1. At the above mentioned conditions, the adsorption capacities were 13.4, 28.5 and 36.5 mg g -1 at 0.98 L hr-1 and 25.2, 60.9 and 74.3 mg g-1 at 2.27 L hr-1,  respectively