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Aim: Sarcopenic obesity (SO) is associated with adverse outcomes in diseased patients. This study aimed to examine the prevalence and risks associated with SO, with a focus on the impact of SO on cardiovascular risk in patients with MASLD.

Materials And Methods: In this cross-sectional study, patients with MASLD were prospectively enrolled.

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Objectives: To assess the effect of patient positioning and general anesthesia on the condylar position in orthognathic surgery.

Materials And Methods: This prospective study included patients undergoing orthognathic surgery between 2019 and 2020. Four weeks prior to surgery (T0) cone-beam computed tomography (CBCT) scans and intra-oral scans (IOS) were acquired in an upright position.

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New Numerical Inversion Method to Improve the Spatial Accuracy of Elemental Imaging for LA-ICP-MS.

Anal Chem

January 2025

State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, PR China.

The elemental imaging of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) provides spatial information on elements and therefore can further investigate the growth or evolution processes of an analyte. However, the accurate determination of spatial information is limited by the decoupling between the elemental distribution and mass spectrometry signals. This phenomenon, which is more distinct when high-diffusion ablation cells are used, arises from the overlap of ablation and the transport dispersion of aerosols.

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An unprecedented global outbreak caused by the monkeypox virus (MPXV) prompted the World Health Organization to declare a public health emergency of international concern on July 23, 2022. Therapeutics and vaccines for MPXV are not widely available, necessitating further studies, particularly in drug repurposing area. To this end, the standardization of in vitro infection systems is essential.

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The development of deep learning algorithms has transformed medical image analysis, especially in brain tumor recognition. This research introduces a robust automatic microbrain tumor identification method utilizing the VGG16 deep learning model. Microscopy magnetic resonance imaging (MMRI) scans extract detailed features, providing multi-modal insights.

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