Browse Articles
Discover research articles across all indexed journals
Decoding perceptions and behavioral preferences in industrial heritage landscapes: a multi-source study of Shougang Park, Beijing
γ-Fe2O3@Prussian blue nanozyme-driven colorimetric detection of antimicrobial susceptibility in bacterial culture
Safety research on the original coal pillar area during expansion and remining of strong rockburst-prone panels in kilometer-deep coal mines
Structure aware graph community cluster pruning for efficient neural network compression in Parkinson’s disease diagnosis
Strategic sacrifice resolves fairness-induced coordination failure through emergent leadership in simulated kinship networks
Hybrid multimodal medical image fusion and secure watermarking for smart healthcare
Factors influencing acceptance of intravenous-to-oral switch (IVOS) of antibiotics among residents in China: a cross-sectional study based on the health belief model (HBM)
Random noise attenuation using dual-module attention with multi-scale kernels
Cytokine and profibrotic gene expression during tracheal stenosis development in an experimental model
Involving supernumerary teeth in “qpdb” teeth numbering system
Abstract Supernumerary teeth are extra-dentation or tooth-like structure that may be present anywhere in the oral cavity. Currently used numbering systems lack a standardized method for identifying supernumerary teeth which might result in misinterpretation and hinder effective collaboration among dental practitioners. A pre-study questionnaire was conducted on 235 dental practitioners, including dentists, interns and clinical dental students to evaluate their previous experience with supernumerary teeth and the numbering systems used to identify them. Of the respondents, only 32% reported using systems to identify supernumeraries while 68% had no experience with any of systems confirming a significant gap in standardized practice highlighting the need for development of a new numbering system. This manuscript presents a novel addition to the existing “qpdb” tooth numbering system for identification of supernumerary teeth, addressing the limitations of existing methods that fail to provide a standardized approach for identifying these extra teeth. The modification introduces the digit zero (0) placed in combination with the tooth number mesially adjacent to the supernumerary (the identifier tooth) as a designation. This approach enables more precise, consistent and communicable identification of supernumerary teeth addressing the limitations of currently available numbering systems.
An ML-augmented framework for WSN and IoT in 6G networks
Effects of environmental evaporation rate on desiccation cracking of a compacted expansive soil subjected to wetting-drying cycles
Bioprospection of Metschnikowia species as a biocontrol agent against AFB1 contamination
Local signals, systemic decline
A high-fat diet affects tumor-to-nerve signaling and promotes cachexia in mice
Design and failure envelopes for square raft and embedded block foundations under combined loading
Volcanic magma sculpts eerie domes on the sea floor
Physiological shear flow enhances pinocytosis in human platelets
Abstract Pinocytosis, the uptake of extracellular fluid, is an important yet poorly understood function of platelets. Although platelets are continuously exposed to shear flow in the circulation, the mechanism by which shear modulates pinocytosis in human platelets remains unclear. Here, we investigated the effects of physiological shear rate on platelet pinocytosis using a rotational viscometer combined with flow cytometric quantification using pHrodo dextran. Exposure to 500–1500 s -1 shear rates enhanced platelet pinocytosis and increased intracellular Ca 2+ levels measured using Fluo-4. The pharmacological inhibition of intracellular Ca 2+ signaling with prostaglandin E1 and chelation of extracellular Ca 2+ with ethylene glycol tetraacetic acid suppressed both shear-induced Ca 2+ elevation and pinocytosis, suggesting Ca 2+ dependence. Notably, shear exposure within this physiological range did not induce classical platelet activation markers, including integrin αIIbβ3 activation or P-selectin expression, suggesting that shear-induced pinocytosis occurs independently of canonical activation pathways. Under plasma-free conditions, platelet pinocytosis was markedly enhanced, even in the absence of shear, without concomitant Ca 2+ elevation, suggesting the involvement of distinct plasma-dependent regulatory mechanisms. Together, these findings demonstrate that physiological shear promotes calcium-dependent platelet pinocytosis through activation-independent pathways, and highlight shear modulation as a potential strategy for drug loading into platelets in blood cell-based drug delivery systems.
An ECG biomarker for sudden cardiac death discovered with deep learning
Abstract Sudden cardiac death is, in theory, preventable with defibrillators. But every year, many patients die without defibrillators because doctors fail to predict their risk 1 . The only predictive biomarker in wide use, cardiac left ventricular ejection fraction (LVEF), misses most sudden cardiac deaths 2 , and flags many low-risk patients for futile defibrillators that never fire 3,4 . Here we apply deep learning to a dataset linking all electrocardiograms (ECGs) in a Swedish region to death certificates. The resulting model isolates a high-risk group (2.2% of the sample) with a 7.0% annual rate of sudden cardiac death, higher than those with reduced LVEF (1.9% of the sample; 4.6% annual rate). Notably, 86.1% of the model’s high-risk patients were not flagged by LVEF. High-risk ECG patients with defibrillators implanted were 54.4% less likely to die than expected, suggesting a mortality benefit. We externally validate the model in a US health system, in which it predicts ventricular arrhythmias that cause sudden death; and a Taiwanese hospital registry, in which it specifically predicts future arrhythmic cardiac arrests. To visualize the waveform morphology ‘discovered’ by the predictive model, we pair it with a generative model of the ECG waveform. Together, they reveal a biomarker that is easily visible and robustly predicts sudden cardiac death, but has not to our knowledge been previously described. Tying the biomarker’s shape to electrophysiological first principles, we form and preliminarily test a new hypothesis on the mechanism of sudden cardiac death.