The role of miRNAs as biomarkers in heterotopic ossification

Fibrodysplasia ossificans progressiva and progressive osseous heteroplasia are genetic forms of heterotopic ossification (HO). Fibrodysplasia ossificans progressiva is caused by ACVR1 gene mutations, while progressive osseous heteroplasia is caused by GNAS gene mutations. Nongenetic HO typically occurs after trauma or surgery, with an occurrence rate of 20–60%. It can also be observed in conditions such as diffuse idiopathic skeletal hyperostosis, spinal ligament ossification, ankylosing spondylitis, and skeletal fluorosis. The exact cause of nongenetic HO is not entirely clear. More than 100 types of miRNAs have been identified as being linked to the development of HO. Some miRNAs are promising potential biomarkers for traumatic HO and ossification of the posterior longitudinal ligament. These findings further emphasize the significant role miRNAs play in the pathogenesis and progression of bone disorders. Repeated investigations into the function of a specific miRNA are infrequent and yield inconsistent results, possibly because of variable experimental conditions. It is hypothesized that miRNAs can enhance osteogenesis for the management of fractures and bone defects. However, further research is required to validate this hypothesis

Risk prediction model establishment with tri-phasic CT image features for differential diagnosis of adrenal pheochromocytomas and lipid-poor adenomas: Grouping method

ObjectivesThe purpose of this study was to establish a risk prediction model for differential diagnosis of pheochromocytomas (PCCs) from lipid-poor adenomas (LPAs) using a grouping method based on tri-phasic CT image features.MethodsIn this retrospective study, we enrolled patients that were assigned to a training set (136 PCCs and 183 LPAs) from two medical centers, along with an external independent validation set (30 PCCs and 54 LPAs) from another center. According to the attenuation values in unenhanced CT (CTu), the lesions were divided into three groups: group 1, 10 HU < CTu ≤ 25 HU; group 2, 25 HU < CTu ≤ 40 HU; and group 3, CTu > 40 HU. Quantitative and qualitative CT imaging features were calculated and evaluated. Univariate, ROC, and binary logistic regression analyses were applied to compare these features.ResultsCystic degeneration, CTu, and the peak value of enhancement in the arterial and venous phase (DEpeak) were independent risk factors for differential diagnosis of adrenal PCCs from LPAs. In all subjects (groups 1, 2, and 3), the model formula for the differentiation of PCCs was as follows: Y = -7.709 + 3.617*(cystic degeneration) + 0.175*(CTu ≥ 35.55 HU) + 0.068*(DEpeak ≥ 51.35 HU). ROC curves were drawn with an AUC of 0.95 (95% CI: 0.927–0.973) in the training set and 0.91 (95% CI: 0.860–0.929) in the external validation set.ConclusionA reliable and practical prediction model for differential diagnosis of adrenal PCCs and LPAs was established using a grouping method

LiDAR point cloud denoising for individual tree extraction based on the Noise4Denoise

The processing of LiDAR point cloud data is of critical importance in the context of forest resource surveys, as well as representing a pivotal element in the realm of forest physiological and ecological studies.Nonetheless, conventional denoising algorithms frequently exhibit deficiencies with regard to adaptability and denoising efficacy, particularly when employed in relation to disparate datasets.To address these issues, this study introduces DEN4, an unsupervised, deep learning-based point cloud denoising algorithm designed to improve the accuracy of single tree segmentation in LiDAR point clouds.DEN4 introduces a multilevel noise separation module that effectively distinguishes between signal and noise, thereby improving the signal-to-noise ratio (SNR) and reducing the error.The experimental results demonstrate that DEN4 significantly outperforms traditional denoising methods in several key metrics, including mean square error (MSE), SNR, Hausdorff distance, and structural similarity index (SSIM).In the 60 sample dataset, DEN4 achieved the best mean and standard deviation on all metrics: Specifically, the MSE mean was found to be 0.0094, with a standard deviation of 0.0008, the SNR mean was 149.1570, with a standard deviation of 0.5628, the Hausdorff mean was 0.8503, with a standard deviation of 0.0947, and the SSIM mean was 0.8399, with a standard deviation of 0.0054. For instance, in the S10 dataset, DEN4 attained a 70.2% diminution in MSE and a 37.8% augmentation in SNR in comparison with PTD.The findings demonstrate the efficacy of DEN4 in multiple forest datasets, its ability to maintain geometric integrity, and its enhanced stability without the necessity for pre-labelled data. The algorithm's superior performance and robustness in diverse forest environments underscores its potential application in single tree segmentation and forest resource management

Preparation of ZnO hybrid nanoparticles by ATRP

Zinc oxide (ZnO) is a wide bandgap semiconductor material that has attracted widespread interest as particle filler in polymer nanocomposite materials. However, its applications have been hindered by the limited dispersibility and surface-modification techniques. Herein, three distinct approaches for the synthesis of polymer-tethered ZnO hybrid materials are compared in terms of uniformity and yield of the particle-brush product: “grafting-from”, “grafting-onto”, and “grafted-copolymer template” methods. In the “grafting-from” method, pristine ZnO nanoparticles (NP) were first functionalized with atom transfer radical polymerization (ATRP) initiators followed by grafting-from process to form poly(methyl methacrylate) (PMMA) or poly(styrene-co-acrylonitrile) (PSAN) tethered polymer chains. In the “grafting-onto” method, PMMA-b-PAA (poly[acrylic acid]) and PSAN-b-PAA diblock copolymers were prepared and attached onto the surface of ZnO NPs using sonication bath. For the “grafted-copolymer template” method, PSAN-b-PtBA-Br (poly[tert-butyl acrylate]-Br) macroinitiators were crosslinked with divinylbenzene (DVB) to form PSAN-b-PtBA-PDVB core-shell star polymers. After hydrolysis to form PSAN-b-PAA-PDVB star polymers, the functional stars were used as polymer templates for the synthesis of ZnO NPs within the PAA-core of the stars. Core-shell molecular bottlebrushes with PAA-b-PS block-copolymer side chains were also used as anisotropic analogues of star template to prepared worm-like ZnO particles. Several ZnO precursors, zinc nitrite, zinc 2-ethylhexanoate, and zinc acetate were evaluated as precursors of ZnO. Conditions were identified that enable the synthesis of polymer-tethered ZnO with excellent size uniformity and dispersion characteristics using the star-template method

Clinical and radiological characteristics of pediatric COVID-19 before and after the Omicron outbreak: a multi-center study

IntroductionThe emergence of the Omicron variant has seen changes in the clinical and radiological presentations of COVID-19 in pediatric patients. We sought to compare these features between patients infected in the early phase of the pandemic and those during the Omicron outbreak.MethodsA retrospective study was conducted on 68 pediatric COVID-19 patients, of which 31 were infected with the original SARS-CoV-2 strain (original group) and 37 with the Omicron variant (Omicron group). Clinical symptoms and chest CT scans were examined to assess clinical characteristics, and the extent and severity of lung involvement.ResultsPediatric COVID-19 patients predominantly had normal or mild chest CT findings. The Omicron group demonstrated a significantly reduced CT severity score than the original group. Ground-glass opacities were the prevalent radiological findings in both sets. The Omicron group presented with fewer symptoms, had milder clinical manifestations, and recovered faster than the original group.DiscussionThe clinical and radiological characteristics of pediatric COVID-19 patients have evolved with the advent of the Omicron variant. For children displaying severe symptoms warranting CT examinations, it is crucial to weigh the implications of ionizing radiation and employ customized scanning protocols and protective measures. This research offers insights into the shifting disease spectrum, aiding in the effective diagnosis and treatment of pediatric COVID-19 patients

Guidelines for burn rehabilitation in China

Abstract Quality of life and functional recovery after burn injury is the final goal of burn care, especially as most of burn patients survive the injury due to advanced medical science. However, dysfunction, disfigurement, contractures, psychological problems and other discomforts due to burns and the consequent scars are common, and physical therapy and occupational therapy provide alternative treatments for these problems of burn patients. This guideline, organized by the Chinese Burn Association and Chinese Association of Burn Surgeons aims to emphasize the importance of team work in burn care and provide a brief introduction of the outlines of physical and occupational therapies during burn treatment, which is suitable for the current medical circumstances of China. It can be used as the start of the tools for burn rehabilitation.</jats:p