Browse Articles

Immunoinformatics method to design universal multi-epitope nanoparticle vaccine for TGEV S protein

Correlation between pierced earrings and the prevalence of metal allergies at Tokushima university hospital: a 15-year retrospective analysis

Research on the desalination kinetics of carbon tableting electrodes for capacitive deionization water purification

UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures

Abstract In the present study, a simple, rapid and cost-effective analytical method was developed for the simultaneous determination of three commonly prescribed cardiovascular drugs: propranolol, rosuvastatin and valsartan. The method employed artificial neural networks (ANN) to model the relation between the UV absorption spectra of the drugs and their concentrations. An experimental design of 25 samples was employed as a calibration set, and a central composite design of 20 samples was used as a validation set. The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. Validation of the developed FA-ANN models demonstrated excellent accuracy, precision and selectivity for the quantification of the target analytes as per international conference on harmonisation (ICH) guidelines. Additionally, the greenness, analytical practicality and sustainability of the developed models were assessed using the analytical greenness (AGREE), blue applicability grade index (BAGI) and the red-green-blue (RGB) tools, confirming their environmentally friendly, practical and sustainable nature. This research shed the light on the potential of ANN coupled with UV fingerprinting for the rapid and simultaneous determination of critical cardiovascular drugs posing a significant impact on pharmaceutical quality control and patient monitoring.

An integration of ensemble deep learning with hybrid optimization approaches for effective underwater object detection and classification model

Using Mg isotopes to constrain the formation temperature of dolomite

Hydro-morphodynamic numerical modeling indicates risk zones for riverbed clogging

Abstract Riverbed clogging compromises the ecological functioning of gravel-bed rivers. Physical clogging affects aquatic habitats and occurs when fine sediments infiltrate coarser substrates, reducing permeability, porosity, and oxygenation. Clogging analyses mostly rely on methods or models that assess the clogging state from field data without predictive capacity. However, predictive tools are essential to optimize habitat restoration in mountain rivers. This study evaluates a two-dimensional numerical model for simulating fine sediment infiltration and mobilization around two large wood pieces in a fully controlled morphodynamic gravel-bed channel. Field data from the morphodynamic channel, collected before and after an artificial flood, were used to calibrate the model and compare its outputs with measured sediment parameters. The model reproduces fine sediment fractions in the surface and subsurface layers, especially in a shallow, high-velocity zone that underwent substantial declogging. In contrast, fine sediment fractions increased in a deeper, slower-flowing zone. Additionally, simulated suspended sediment concentration and fine sediment fraction maps highlight how a swale saturated with fine sediment on the floodplain contributed to increased fine sediment infiltration and clogging downstream. These findings demonstrate that a robust 2d model capturing fine sediment dynamics can effectively identify clogging-prone areas in gravel-bed rivers.

Inference of a plume conduit beneath the Réunion Island from 3D migration of Ps conversions from the mantle transition zone

Abstract The Réunion hotspot is the best example of a primary plume, manifested as intraplate-volcanism, a large igneous province and a geochemical anomaly. In this study, we investigate the mantle transition zone (MTZ) structure beneath the Réunion Island using 3D-migration of P-Receiver functions, to decipher the effect of the plume on the MTZ and its architecture. Results indicate a thin MTZ in the regions surrounding the Réunion, like Madagascar and its vicinity, eastern and south-eastern sides of the Réunion, suggesting high-temperature anomalies within, caused by the plume. Interestingly, we detect a depressed 410 km discontinuity exactly beneath the Réunion hotspot and a broader depression of 660 km discontinuity within and regions in its proximity. These maiden results shed-light on the high-temperature anomalies in the mid-mantle, probably sourced from the Réunion plume and provide evidence for the Majorite-garnet phase transformation at 660 km discontinuity. We postulate that an ascending Réunion plume has initially hit the 660 km discontinuity, got horizontally spread and further progressed to the 410 km discontinuity as a columnar structure.

Magnitude and determinants of occupational exposure to blood and body fluids among physicians in a teaching hospital in northern Ethiopia

Spatio-temporal variations on alluvial fan channel width in response to grain size on the channel bed under constant upstream boundary conditions

Association between COVID-19 and the development of chronic kidney disease in patients without initial acute kidney injury

Blocking mineralocorticoid signaling with esaxerenone reduces atherosclerosis in hyperglycemic ApoE KO mice without affecting blood pressure and glycolipid metabolism

Abstract Endothelial damage mediated by mineralocorticoid receptor (MR) is an important factor in the development of atherosclerosis. Esaxerenone is a highly selective drug that can specifically block MR activity. The aim of this study is to examine whether specific blocking of mineralocorticoid signaling with esaxerenone exerts favorable effects on the progression of atherosclerosis. ApoE KO mice were used as a model of atherosclerosis. In addition to a non-diabetic model, we created a diabetic model using streptozotocin. These were divided into a control group and an esaxerenone group. Esaxerenone-containing diet was provided for 8 weeks starting at 10 weeks of age. Various metabolic markers and abdominal aortic mRNA expression were evaluated, and histological examination of the aortic arch and thoracic aorta was performed. We also used human aortic smooth muscle cells (HASMCs) to investigate the possible direct effects of esaxerenone on vascular smooth muscle cells. In diabetic mice, plaque area in the aortic arch was significantly smaller in esaxerenone group compared to control group, although there were no differences in blood pressure, serum lipid levels between the two groups. Inflammation-related genes, macrophage marker, cell adhesion factors and oxidative stress marker were all significantly lower in esaxerenone group. The studies using HASMCs have confirmed that esaxerenone has anti-inflammatory effects on vascular smooth muscle cells. Specific blocking of mineralocorticoid signaling with esaxerenone exerts favorable effects on the progression of atherosclerosis without influencing blood pressure and glycolipid metabolism.

A BiLSTM model enhanced with multi-objective arithmetic optimization for COVID-19 diagnosis from CT images

Zero-shot incremental learning using spatial-frequency feature representations

Optical fibre-based quantum random number generator: stochastic modelling and measurements

Abstract In this work, we present a study of a quantum random number generation system based on a branching path approach with spatial superposition principle, realised using fibre optics. The analysis of the experimental system was supported by the development of a stochastic model of the entropy source, which, to the best of the authors’ knowledge, has not yet been properly described. This resulted in the analytical equations for the probability of possible output quantum states depending on the initial properties of the system. Based on the presented model, the quantum efficiency and the Shannon entropy were calculated and compared with experimentally obtained values, which resulted in full agreement between these data. Additional statistical tests were performed on random numbers obtained theoretically and experimentally to confirm their high degree of randomness and their usability in cryptographic applications. The fact that the developed system is based on fibre optics allows it to operate in stable conditions with a final efficiency at the level of 15%, which provides a random number generation rate of about 8 kb/s. The developed system is used as an input to the quantum key distribution system, which has possible applications in cryptography or military and commercial secure communications.

Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers

Research on detection and location method of safflower filament picking points during the blooming period in unstructured environments

The use of Apple smartwatches to obtain vital signs readings in surgical patients

Thermodynamic modeling hexamethylenetetramine adsorption on sandstone

Optimizing thoracodorsal artery perforator flap outcomes in oncoplastic breast surgery: multidimensional assistive techniques mitigate learning curve and enhance feasibility

Abstract This study aims to evaluate the feasibility and postoperative outcomes of the thoracodorsal artery perforator (TDAP) flap in oncoplastic breast surgery (OBS), incorporating multidimensional assistive techniques. We retrospectively analyzed 14 breast cancer patients treated with TDAP flap OBS from May 2020 to August 2023. Patients were divided into two groups: Group A (first 7 cases) and Group B (last 7 cases). Preoperative perforator localization was performed using color Doppler ultrasound and handheld Doppler, with intraoperative comparisons. Blood perfusion was assessed intraoperatively with indocyanine green (ICG) fluorescence imaging and postoperatively with infrared thermal (IRT) imaging. Patient satisfaction was measured using the BREAST-Q scale. Group A had longer operation times (4.05 ± 0.61 h vs. 3.27 ± 0.31 h, P = 0.011) and longer hospitalization (9.14 ± 2.27 days vs. 7.71 ± 1.60 days, P = 0.199). No flap necrosis occurred. Preoperative and intraoperative perforator positions were consistent. ICG imaging showed good flap blood supply; edge trimming improved perfusion in two cases. IRT imaging confirmed good blood perfusion in the first 3 days post-op. BREAST-Q scores for psychological health and sexual satisfaction were lower post-op (P < 0.001), but no significant differences were found in scores for chest physical health, shoulder and back physical health, or breast satisfaction. While TDAP flap surgery involves a learning curve, it is a highly feasible technique for OBS. Multidimensional assistive technologies significantly enhance preoperative perforator localization and intraoperative flap blood perfusion monitoring, thereby improving flap survival rates and patient satisfaction.