With the advent of new reconstructive rhinoplasty techniques, we have the opportunity to correct a larger number of nasal deformities. Dimensional analysis using non-nasal references assists in identifying the abnormalities in a deformed nose. Analysis of 98 patients undergoing rhinoplasty plus or minus septal surgery was performed to identify the prevalent abnormalities with the help of the dimensional approach.
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http://dx.doi.org/10.1111/j.1365-2273.2004.00847.x | DOI Listing |
Vaccines (Basel)
December 2024
Clinical Laboratory Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China.
Echinococcosis is a zoonotic infectious disease that poses a significant threat to the health of individuals living in rural regions. While vaccination represents a potential strategy for disease prevention, there is currently no effective vaccine available for humans to prevent cystic echinococcosis (CE). This study aimed to design a novel multi-epitope vaccine (MEV) against Echinococcus granulosus for human use, employing immunoinformatics methods.
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December 2024
CeMOS Research and Transfer Center, Mannheim University of Applied Sciences, 68163 Mannheim, Germany.
Advancements in Raman light sheet microscopy have provided a powerful, non-invasive, marker-free method for imaging complex 3D biological structures, such as cell cultures and spheroids. By combining 3D tomograms made by Rayleigh scattering, Raman scattering, and fluorescence detection, this modality captures complementary spatial and molecular data, critical for biomedical research, histology, and drug discovery. Despite its capabilities, Raman light sheet microscopy faces inherent limitations, including low signal intensity, high noise levels, and restricted spatial resolution, which impede the visualization of fine subcellular structures.
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December 2024
Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.
Monitoring cerebral oxygenation and metabolism, using a combination of invasive and non-invasive sensors, is vital due to frequent disruptions in hemodynamic regulation across various diseases. These sensors generate continuous high-frequency data streams, including intracranial pressure (ICP) and cerebral perfusion pressure (CPP), providing real-time insights into cerebral function. Analyzing these signals is crucial for understanding complex brain processes, identifying subtle patterns, and detecting anomalies.
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December 2024
Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy.
The automatic detection of arrhythmia is of primary importance due to the huge number of victims caused worldwide by cardiovascular diseases. To this aim, several deep learning approaches have been recently proposed to automatically classify heartbeats in a small number of classes. Most of these approaches use convolutional neural networks (CNNs), exploiting some bi-dimensional representation of the ECG signal, such as spectrograms, scalograms, or similar.
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December 2024
South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China.
A data-efficient training method, namely Q-AL-GPR, is proposed for visible light positioning (VLP) systems with Gaussian process regression (GPR). The proposed method employs the methodology of active learning (AL) to progressively update the effective training dataset with data of low similarity to the existing one. A detailed explanation of the principle of the proposed methods is given.
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