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The pooled sensitivity was 0.885 (95% CI 0.818-0.929), and the pooled specificity was 0.811 (95% CI 0.667-0.902). The pooled AUC was 906.

Our meta-analysis showed that CT-based radiomics feature models can successfully differentiate COVID-19 from other viral pneumonias.

A total of 10,300 patients were involved in this meta-analysis. The radiomics quality score ranged from 13 to 16 (maximum score 36). The pooled sensitivity was 0.885 (95% CI 0.818-0.929), and the pooled specificity was 0.811 (95% CI 0.667-0.902). The pooled AUC was 906. Conclusion Our meta-analysis showed that CT-based radiomics feature models can successfully differentiate COVID-19 from other viral pneumonias.The rapid progress in the development of surface plasmon resonance-based immunosensing platforms offers wide application possibilities in medical diagnostics as a label-free alternative to enzyme immunoassays. The early diagnosis of diseases or metabolic changes through the detection of biomarkers in body fluids requires methods characterized by a very good sensitivity and selectivity. In the case of the SPR technique, as well as other surface-sensitive detection strategies, the quality of the transducer-immunoreceptor interphase is crucial for maintaining the analytical reliability of an assay. In this work, an overview of general approaches to the design of functional SPR-immunoassays is presented. It covers both immunosensors, the design of which utilizes well-known and often commercially available substrates, as well as the latest solutions developed in-house. Various approaches employing chemical and passive binding, affinity-based antibody immobilization, and the introduction of nanomaterial-based surfaces are discussed. The essence of their influence on the improvement of the main analytical parameters of a given immunosensor is explained. Particular attention is paid to solutions compatible with the latest trends in the development of label-free immunosensors, such as platforms dedicated to real-time monitoring in a quasi-continuous mode, the use of in situ-generated receptor layers (elimination of the regeneration step), and biosensors using recombinant and labelled protein receptors.Laboratory tests are performed to make effective clinical decisions. However, inappropriate laboratory test ordering hampers patient care and increases financial burden for healthcare. An automated laboratory test recommendation system can provide rapid and appropriate test selection, potentially improving the workflow to help physicians spend more time treating patients. The main objective of this study was to develop a deep learning-based automated system to recommend appropriate laboratory tests. A retrospective data collection was performed at the National Health Insurance database between 1 January 2013, and 31 December 2013. We included all prescriptions that had at least one laboratory test. A total of 1,463,837 prescriptions from 530,050 unique patients was included in our study. Of these patients, 296,541 were women (55.95%), the range of age was between 1 and 107 years. The deep learning (DL) model achieved a higher area under the receiver operating characteristics curve (AUROC micro = 0.98, and AUROC macro = 0.94). The findings of this study show that the DL model can accurately and efficiently identify laboratory tests. This model can be integrated into existing workflows to reduce under- and over-utilization problems.Sorafenib, a multi-kinase inhibitor, is the first-line treatment for advanced hepatocellular carcinoma (HCC) patients. click here However, this drug only provides a short improvement of patients' overall survival, and drug resistance is commonly developed. Thus, the identification of resistant factor(s) or biomarker(s) is needed to develop more efficient therapeutic strategies. Long, non-coding RNAs (lncRNAs) have recently been viewed as attractive cancer biomarkers and drive many important cancer phenotypes. A lncRNA, ZFAS1 (ZNFX1 antisense RNA 1) has been found to promote HCC metastasis. This study found that sorafenib induced ZFAS1 expression specifically in sorafenib-resistant HCC cells. Although ZFAS1 knockdown did not restore the sensitivity of HCC cells to sorafenib, its expression may act as a resistant biomarker for sorafenib therapy. Bioinformatics analysis predicted that sorafenib tended to induce pathways related to endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) in sorafenib-resistant HCC cells. In vitro experimental evidence suggested that sorafenib induced protein kinase RNA-like ER kinase (PERK)/activating transcription factor 4 (ATF4)-dependent ZFAS1 expression, and sorafenib resistance could be overcome by PERK/ATF inhibitors. Therefore, PERK/ATF4/ZFAS1 signaling axis might be an attractive therapeutic and prognostic biomarker for sorafenib therapy in HCC.The COVID-19 pandemic, which began in Wuhan (Hubei, China), has been ongoing for about a year and a half. An unprecedented number of people around the world have been infected with SARS-CoV-2, the etiological agent of COVID-19. Despite the fact that the mortality rate for COVID-19 is relatively low, the total number of deaths has currently already reached more than three million and continues to increase due to high incidence. Since the beginning of the pandemic, a large number of sequences have been obtained and many genetic variants have been identified. Some of them bear significant mutations that affect biological properties of the virus. These genetic variants, currently Variants of Concern (VoC), include the so-called United Kingdom variant (20I/501Y), the Brazilian variant (20J/501Y.V3), and the South African variant (20H/501Y.V2). We describe here a novel SARS-CoV-2 variant with distinct spike protein mutations, first obtained at the end of January 2021 in northwest Russia. Therefore, it is necessary to pay attention to the dynamics of its spread among patients with COVID-19, as well as to study in detail its biological properties.Exposure of oocytes to specific amino acids during in vitro fertilisation (IVF) improves preimplantation embryo development. Embryos fertilised in medium with proline and its homologue pipecolic acid showed increased blastocyst formation and inner cell mass cell numbers compared to embryos fertilised in medium containing no amino acids, betaine, glycine, or histidine. The beneficial effect of proline was prevented by the addition of excess betaine, glycine, and histidine, indicating competitive inhibition of transport-mediated uptake. Expression of transporters of proline in oocytes was investigated by measuring the rate of uptake of radiolabelled proline in the presence of unlabelled amino acids. Three transporters were identified, one that was sodium-dependent, PROT (SLC6A7), and two others that were sodium-independent, PAT1 (SLC36A1) and PAT2 (SLC36A2). Immunofluorescent staining showed localisation of PROT in intracellular vesicles and limited expression in the plasma membrane, while PAT1 and PAT2 were both expressed in the plasma membrane.