Hua Zhang

Accurate prediction of prognosis and risk stratification in patients with laryngeal cancer can inform appropriate treatment decision-making. This study aims to develop a multi-channel deep learning radiomics model based on contrast-enhanced computed tomography (CECT) for predicting postoperative overall survival (OS) in patients. A total of 272 patients with laryngeal cancer were retrospectively recruited from two hospitals between January 2016 and July 2021. Specifically, 156 patients were enrolled from Center 1 as the training cohort, and 116 patients from Center 2 as the external test cohort. Two imaging signatures, reflecting phenotypes of the radiomics and multi-channel deep learning features, were constructed using pretreatment venous-phase CECT images. Feature selection involved reproducibility evaluation, Spearman correlation coefficient, and least absolute shrinkage and selection operator (LASSO) regression. Ten machine learning algorithms were employed to construct the signatures. An integrated Deep Learning Radiomics Nomogram (DLRN) was subsequently developed to predict OS. Predictive performance was evaluated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Kaplan–Meier survival curves derived from the DLRN were used for patient risk stratification, and subgroup analyses were conducted to validate the model’s robustness. The DLRN demonstrated satisfactory prognostic performance for laryngeal cancer. In the external test cohort, the 1-, 2-, and 3-year AUC values were 0.74, 0.75, and 0.80, respectively, and achieved a C-index of 0.73, outperforming individual models. Calibration curves and DCA indicated excellent calibration and the highest clinical net benefit. Subgroup analyses confirmed consistent DLRN performance across clinical stages, age groups, and surgical modalities. The proposed multi-channel deep learning radiomics model showed promising performance for predicting OS in laryngeal cancer patients. This approach may support individualized risk stratification and assist clinical decision-making in patients with laryngeal carcinoma.

Atherosclerosis is a primary cause of cardiovascular and cerebrovascular diseases, with the unpredictable rupture of vulnerable atherosclerotic plaques enriched with lipid-laden macrophages being able to lead to heart attacks and strokes. Activating macrophage autophagy presents itself as a promising strategy for preventing vulnerable plaque formation and reducing the risk of rupture. In this study, we have developed a novel metal-free nanozyme (HCN@DS) that integrates the functions of multimodal imaging-guided therapy for atherosclerosis. HCN@DS has demonstrated high macrophage-targeting abilities due to its affinity toward scavenger receptor A (SR-A), along with excellent photoacoustic and photothermal imaging capabilities for guiding the precise treatment. It combines mild photothermal effects with moderate reactive oxygen species (ROS) generation to treat atherosclerosis. This controlled approach activates autophagy in atherosclerotic macrophages, inhibiting foam cell formation by reducing the uptake of oxidized low-density lipoproteins (oxLDL) and promoting efferocytosis and cholesterol efflux in macrophages. Additionally, it prevents plaque rupture by inhibiting apoptosis and inflammation within the plaque. Therefore, this metal-free nanozyme holds great potential for reducing the risk of atherosclerosis due to its high biosafety, excellent targeting ability, dual-modality imaging capability, and appropriate modulation of autophagy.

Mycoplasma pneumoniae (MP) is one of the most common causes of community-acquired pneumonia in children. Most children have fever. In 2021, we found that the proportion of children without fever increased. The aim of this study is to summarize the differences in the clinical characteristics of children with MP pneumonia who are febrile or not, and to raise awareness of children who are not febrile. Demographic information of the children was collected on admission. Clinical manifestations during the course of the disease and the first laboratory, imaging, and pulmonary function tests before discharge were recorded and compared. From August to December, a total of 542 people were included in the study. We found that older children were more likely to have fever. Inflammatory indicators including procalcitonin (P = 0.030), C-reaction protein (P < 0.001), erythrocyte sedimentation rate (P < 0.001), ferritin (P = 0.040) and the rate of atelectasis (P = 0.049) of febrile children were higher in febrile children. However, the elevated lactate dehydrogenase and pulmonary function impairment (P all > 0.05), especially the small airway function impairment, are no lower in afebrile children than in febrile children. The fever rate is lower in younger children, but wheezing is more common. In afebrile children, the impairment of organ and lung function was no less than in febrile children. Therefore, attention should also be paid to children who are not febrile.

Since the ideal image is difficult to be stripped from the actual sampling, this study aims to address and test a shared noise which as the knowledge and is included in the signal applying to the sampled projection to generate high qualified X-ray imaging by reducing the artifacts in computed tomography (CT). Combined with the randomness of the noise, the prereconstruction of the original projection is performed first, and then the forward projection which contains the equivalent noise in the image is obtained. Based on the slice updating, the forward and reconstruction processing is employed again. By means of threshold setting, multiple forward projections are accumulated, whereas the noise upon them will be reduced by averaging process. The noise is suppressed, and the expected information emerges, simultaneously. Study results show effective results, and the proposed method is practical and attractive as a preferred solution to CT artifacts suppression. It provides reliable guarantee for the CT inspection of internal and external dimensions.