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A high-affinity monoclonal antibody (mAb) has been prepared and separately a gold nanoparticle (AuNP)-based and a near-infrared (NIR) fluorescence-based lateral flow immunoassay (LFA) developed for determination of 5-hydroxyflunixin residue in raw milk. BTK pathway inhibitor The AuNP and IRDye® 800CW were used to label anti-5-hydroxyflunixin mAb to form the AuNP-mAb and NIR dye-mAb conjugates, respectively. Quantitative determination of 5-hydroxyflunixin was achieved by imaging the optical or fluorescence intensity of the AuNP-mAb and NIR dye-mAb captured on the test line. As a result, the detection limits of the AuNP-based LFA and NIR dye-based LFA were 0.82 and 0.073 ng/mL in raw milk, respectively. The considerable improvement on assay sensitivity of the NIR-based LFA can be attributed to the lower background and less antibody consumption per test than that of the AuNP-based LFA. The spiking experiment by the NIR-based LFA yielded 85.7-112.6% recovery with a relative standard deviation below 14%, indicating that it has satisfactory assay accuracy and precision. Furthermore, the analytical results of actual samples by the NIR dye-based LFA were consistent with that by instrumental analysis. Therefore, these results demonstrated that the NIR dye is an ideal alternative label to the conventional AuNP for the development of LFA for veterinary drugs in animal-origin food. Graphical abstract.To compare the left ventricular (LV) phase dyssynchrony parameters obtained from Tc-99m Sestamibi SPECT (GSPECT) and F-18 FDG PET(GPET), as well as the prognostic values in patients with ischemic cardiomyopathy (ICM). Consecutive ICM patients referred for myocardial viability assessment were retrospectively evaluated and were followed-up for 21 ± 5 months. Phase parameter from both GSPECT and GPET were analyzed by QGS software, including histogram bandwidth (BW), standard deviation (SD) and entropy. Independent predictor for cardiac death was analyzed by Cox regression analysis. The estimated cardiac survival curve was analyzed by and was compared with the log-rank test. Eight-eight (mean age 56 ± 10, male 94%, LVEFSPECT23 ± 10%) ICM patients were included for analysis. Moderate correlations were observed for BW (r = 0.65; p 0.05). Entropy measured by GSPECT was the predictor for cardiac death (p = 0.037) while QRS duration was not. The cardiac survival of patients with a high entropy (≥ 59%) was significantly lower than that of patients with low entropy ( less then 59%) (p less then 0.05). GSPECT and GPET-derived phase parameters were not interchangeable in ICM patients. Patients with LV dyssynchrony measured by gated SPECT were associated with a worse outcome.Introduction Dementia with Lewy bodies (DLB) is the third most common type of dementia after Alzheimer’s disease (AD) and vascular dementia. Treatment is targeted at specific disease manifestations/symptoms. While donepezil is approved for the treatment of DLB in Japan, to date no other treatment has been approved for this indication anywhere in the world. Notwithstanding, many of the medications that are approved for AD are widely used in the treatment of DLB with varying degrees of success. Consequently, clinical evidence is limited, and there is a need to understand the comparative efficacy and safety of currently used therapies for DLB. The aim of this study was to conduct a network meta-analysis (NMA) to evaluate the outcomes of the available treatment options based on currently used trial endpoints. Methods Using data from a previously published systematic review, we conducted an NMA to investigate the efficacy and safety of treatments in patients with DLB. Networks were based on change from baseline of for patients with DLB. Further comparative trials are required to improve understanding of the true difference between existing and potential future treatment options.Introduction The inherent sensitivity of metabolomics allows the detection of subtle alterations in biological pathways, making it a powerful tool to study biomarkers and the mechanisms that underlie cancer. Objectives The purpose of this work was to characterize the urinary metabolic profile of prostate cancer (PCa) patients and cancer-free controls to obtain a holistic coverage of PCa metabolome. Methods Two groups of samples, a training set (n = 41 PCa and n = 42 controls) and an external validation set (n = 18 PCa and n = 18 controls) were analyzed using a dual analytical platform, namely gas chromatography-mass spectrometry (GC-MS) and proton nuclear magnetic resonance spectroscopy (1H NMR). Results The multivariate analysis models revealed a good discrimination between cases and controls with an AUC higher than 0.8, a sensitivity ranging from 67 to 89%, a specificity ranging from 74 to 89% and an accuracy from 73 to 86%, considering the training and external validation sets. A total of 28 metabolites (15 from GC-MS and 13 from 1H NMR) accounted for the separation. These discriminant metabolites are involved in 14 biochemical pathways, indicating that PCa is highly linked to dysregulation of metabolic pathways associated with amino acids and energetic metabolism. Conclusion These findings confirmed the complementary information provided by GC-MS and 1H NMR, enabling a more comprehensive picture of the altered metabolites, underlying pathways and deepening the understanding of PCa development and progression.Background Several studies have demonstrated a significant benefit of neuromuscular facial training in the rehabilitation of patients with facial palsy. However, printed instructions for home training are often not of optimum quality and associated with low adherence to therapy. Professional guidance, e.g., by occupational therapists, is regarded as being of high quality, but is associated with a high cost burden, particularly in chronic forms of disease. Objective The idea to develop a smartphone app for facial training arose from the above-described situation. The aim was to provide structured exercises for the mimic muscles in the sense of neuromuscular training with visual feedback via the front camera of the device. Materials and methods A native app architecture in iOS was chosen to implement the graphical and content-related concept. In the Apple Xcode (Apple, Cupertino, California, US) development environment, the app’s code was written in the Swift programming language (Apple) and the graphical user interface was created.