Kringmalone2343

We used area under receiver operating characteristic (ROC) curve (AUC) to evaluate the performance of the trained CNNs on a separate test set of 95 patients, using a validation set of 102 patients for finetuning. The shallow network outperformed the deep network with the best 2D slice-based AUC of 0.85 obtained by the rotation method.The prediction and detection of radiation-related caries (RRC) are crucial to manage the side effects of the head and the neck cancer (HNC) radiotherapy (RT). Despite the demands for the prediction of RRC, no study proposes and evaluates a prediction method. This study introduces a method based on artificial intelligence neural network to predict and detect either regular caries or RRC in HNC patients under RT using features extracted from panoramic radiograph. We selected fifteen HNC patients (13 men and 2 women) to analyze, retrospectively, their panoramic dental images, including 420 teeth. Two dentists manually labeled the teeth to separate healthy and teeth with either type caries. They also labeled the teeth by resistant and vulnerable, as predictive labels telling about RT aftermath caries. We extracted 105 statistical/morphological image features of the teeth using PyRadiomics. Then, we used an artificial neural network classifier (ANN), firstly, to select the best features (using maximum weights) and then label the teeth in caries and non-caries while detecting RRC, and resistant and vulnerable while predicting RRC. To evaluate the method, we calculated the confusion matrix, receiver operating characteristic (ROC), and area under curve (AUC), as well as a comparison with recent methods. The proposed method showed a sensibility to detect RRC of 98.8% (AUC = 0.9869) and to predict RRC achieved 99.2% (AUC = 0.9886). The proposed method to predict and detect RRC using neural network and PyRadiomics features showed a reliable accuracy able to perform before starting RT to decrease the side effects on susceptible teeth.Parkinson's disease (PD) is known as one of the most common degenerative disorders related to the damage of the central nervous system (CNS). This brain disorder is also characterized by the formation of Lewy bodies in the cytoplasm of the dopaminergic neurons in the substantia nigra pars compacta (SNc), which consequently leads to motor and non-motor symptoms. With regard to the growing trend in the number of cases with PD and its effects on individuals, families, and communities, immediate treatments together with diagnostic methods are required. In this respect, long non-coding ribonucleic acids (lncRNAs) represent a large class of ncRNAs with more than 200 nucleotides in length, playing key roles in some important processes including gene expression, cell differentiation, genomic imprinting, apoptosis, and cell cycle. MF-438 They are highly expressed in the CNS and previous studies have further reported that the expression profile of lncRNAs is disrupted in human diseases such as neurodegenerative disorders. Since the levels of some lncRNAs change over time in the brains of patients with PD, a number of previous studies have examined their potentials as biomarkers for this brain disorder. Therefore, the main purpose of this study was to review the advances in the related literature on lncRNAs as diagnostic, therapeutic, and prognostic biomarkers for PD.This study aims to evaluate differences in serum and fecal calprotectin in patients with HCV chronic hepatitis and COVID-19 infection and compare them to a control group. This observational study was performed between April 2020 and October 2020 in a single Internal Medicine center. We determined serum and fecal calprotectin, as well as levels of transaminases, C-reactive protein, ferritin, in 25 patients with COVID-19 infection, 30 patients with active HCV chronic infection and 38 patients with cured HCV infection. Serum levels of ALT, AST, C-reactive protein and ferritin were significantly higher in patients with COVID-19 infection (mean values of 127 IU/mL, 135 IU/mL, 123 mg/L and 1034 ng/mL, respectively) than in patients with active HCV infection (mean values of 68 IU/mL, 51 IU/mL, 17 mg/L and 528 ng/mL, respectively) or in patients with cured HCV infection (37 IU/mL, 29 IU/mL, 3.4 mg/L and 274 ng/mL, respectively). Also, serum and fecal calprotectin had increased concentrations in patients with COVID-19 (7.3 µg/mL and 394 µg/mg) versus patients with active hepatitis (2.4 µg/mL and 217 µg/mg) and patients with cured hepatitis (1.2 µg/mL and 38 µg/mg). Values were significantly higher in patients with digestive symptoms related to COVID-19. Serum and fecal calprotectin can be used as inflammatory markers in patients with active viral infections. In COVID-19, calprotectin concentrations can be correlated to the severity of disease, particularly in patients with digestive symptoms.A promising electrochemical strategy for assay of N6-methyladenosine (m6A)/N6-methyladenine (6mA) in RNA/DNA is proposed. The key of this strategy is the end-labeling of nucleic acid, which makes it possible to detect methylation level in unknown sequence. Firstly, the end of m6A-RNA or 6mA-DNA was labeled with sulfhydryl group through T4 polynucleotide kinase (T4 PNK) and then directly assembled on a gold nanoparticle-modified glassy carbon electrode (AuNPs/GCE). Secondly, methylation sites in RNA/DNA were specifically recognized by anti-m6A-antibody, and then, horseradish peroxidase-labeled goat anti-rabbit IgG (HRP-IgG) was further conjugated on the antibody. Thirdly, HRP-IgG catalyzed the hydroquinone oxidation reaction to generate amplified current signal which correlates with the amount of m6A/6mA in nucleic acid. This method showed a wide linear range from 0.0001 to 10 nM for m6A-RNA, 0.001 to 100 nM for 6mA-dsDNA, and 0.0001 to 10 nM for 6mA-ssDNA. The method was successfully applied to detection of m6A/6mA in RNA/DNA from HeLa cells and E. coli cells and validation of the decrease of m6A-RNA in HeLa cells after treatment with FTO protein.Although many etiologies have been proposed for Chiari malformation type I (CM-I), there currently is no singular known cause of CM-I pathogenesis. Advances in imaging have greatly progressed the study of CM-I. This study reviews the literature to determine if an anatomical cause for CM-I could be proposed from morphometric studies in adult CM-I patients. After conducting a literature search using relevant search terms, two authors screened abstracts for relevance. Full-length articles of primary morphometric studies published in peer-reviewed journals were included. Detailed information regarding methodology and symptomatology, craniocervical instability, syringomyelia, operative effects, and genetics were extracted. Forty-six studies met inclusion criteria, averaging 93.2 CM-I patients and 41.4 healthy controls in size. To obtain measurements, 40 studies utilized MRI and 10 utilized CT imaging, whereas 41 analyzed parameters within the posterior fossa and 20 analyzed parameters of the craniovertebral junction. The most commonly measured parameters included clivus length (n = 30), tonsillar position or descent (n = 28), McRae line length (n = 26), and supraocciput length (n = 26). While certain structural anomalies including reduced clivus length have been implicated in CM-I, there is a lack of consensus on how several other morphometric parameters may or may not contribute to its development. Heterogeneity in presentation with respect to the extent of tonsillar descent suggests alternate methods utilizing morphometric measurements that may help to identify CM-I patients and may benefit future research to better understand underlying pathophysiology and sequelae such as syringomyelia.A gold nanoparticle (AuNP)-based sensing strategy based on rapid reduction of Au(I→0) is proposed. As a proof-of-concept study, the proposed sensing principle is designed for simultaneous and colorimetric detection and discrimination of multiple proteins. In the presence of H2O2, the target proteins could reduce Au(I) (i.e. HAuCl2) to AuNPs with different sizes, shapes and dispersion/aggregation states, thus resulting in rapidly colorimetric identification of different proteins. The optical response (i.e. color) of AuNPs is found to be characteristic of a given protein. The color response patterns are characteristic for each protein and can be quantitatively differentiated by statistical techniques. The sensor array is capable of discriminating proteins at concentrations as low as 0.1 μg/mL with high accuracy. A linear relationship was observed between the total Euclidean distances and protein concentration, providing the potential for protein quantification using this sensor array. The limit of detection (LOD) for catalase (Cat) is 0.08 μg/mL. The good linear range (from 0 to 8 μg/mL) has been used for the quantitative assay of Cat. To show a potentially practical application, this method was used to detect and discriminate proteins in human urine and tear samples. Graphical abstract We report a facile gold nanoparticle (AuNP)-based sensing strategy, that is, "a rapid reduction of Au(I) to Au(0) nanoparticles with different sizes and shapes by analytes that having certain reducing capabilities, resulting in different colours." The proposed sensing principle is designed for simultaneous, colorimetric detection and discrimination of multiple proteins.As the debate about holism and reductionism in ecology has ebbed in the last twenty years, this article aims to reassess the traditional opposition between holistic and reductionist epistemologies during the development of population biology. The history of the notion of carrying capacity, the upper demographic limit of a viable population, will be analyzed as a paradigmatic case of the progressive imposition of reductionist strategies, from both an epistemological and a semantic point of view, since the middle of the twentieth century. Then, Richard Looijen's reduction of the carrying capacity concept to the niche partitioning theory will be assessed and rebuked for both empirical and logical reasons. Eventually, some recent "weak" and "hard" emergent conceptualizations of the notion of carrying capacity, in logistic map models or in coupled niche-population systems, will be presented in order to show how they call into question the nature and the use of the notion of carrying capacity as a predefined ecological limit.Our study aimed to evaluate the sensitivity of the sonication tool for the microbiological diagnosis of cardiovascular implantable electronic device infections (CIEDIs). The extracted cardiac implants of 52 patients were assessed 19 with CIEDI and 33 with elective generator replacement or revision without clinical infection. Sonication fluid culture of explanted CIEDs yielded higher numbers of microorganisms than pocket tissue or swab cultures. The sensitivity of sonication fluid culture was significantly higher than that of pocket swab and tissue culture for microbiological diagnosis of CIEDI. The microorganisms isolated most frequently via sonication of explanted CIEDs were Gram-positive cocci (70%), of which 50% was coagulase-negative Staphylococcus. Sonication fluid culture detected colonization in 36.4% of the non-infected patients. Sonication fluid culture represents a promising diagnostic strategy with increased sensitivity compared to conventional culture methods for microbiological diagnosis of cardiac devices associated with infection and colonization.