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Jiefeng Huang,1– 3,&ast; Lida Chen,4,&ast; Xiuling Li,1– 3,&ast; Menglan Chen,1– 3 Ting Lin,1– 3 Gongping Chen1– 3 1Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Fujian Medical University, Fujian Medical University, Fuzhou, People’s Republic of China; 2Institute of Respiratory Disease, Fujian Medical University, Fujian Medical University, Fuzhou, People’s Republic of China; 3Department of Respiratory and Critical Care Medicine, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People’s Republic of China; 4Department of Respiratory and Critical Care Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Xiangcheng, Zhangzhou, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Gongping Chen, Tel/Fax +86591-87981697, Email cgp2389@126.comAim: Emerging evidence has revealed that obstructive sleep apnea (OSA) is an independent risk factor for the development of a variety of adverse metabolic disease states. In this study, we evaluated the association between OSA severity and metabolic dysfunction-associated fatty liver disease (MAFLD) among Asian populations.Materials and Methods: This was a cross-sectional, single-center study. The study cohort consisted of patients undergoing polysomnography and abdominal ultrasonography. Logistic regression analysis was used to evaluate the independent risk factors of MAFLD in patients with OSA.Results: A total of 1065 patients (277 non-MAFLD and 788 MAFLD) were included in the study. The prevalence of MAFLD in non-OSA, mild-moderate OSA, and severe OSA patients was 58.16%, 72.41%, and 78.0%, respectively (p < 0.001). We identified significant differences in body mass index (BMI), apnea-hypopnea index (AHI), oxygen desaturation index (ODI), and lowest O2 saturation (LaSO2) between non-MAFLD and MAFLD patients (all p < 0.001). After adjusting for confounding variables, we used multivariate regression analysis to show that BMI, ODI, and triglyceride (TG) levels independently predicted the occurrence of MAFLD (odds ratio [OR] = 1.234, p < 0.001; OR = 1.022, p = 0.013; OR = 1.384, p = 0.001, respectively). Moreover, stratified analysis according to BMI indicated that TG levels were the predominant risk factor for MAFLD in a group of patients with a BMI < 23 kg/m2, while BMI, ODI, TG levels, and total cholesterol (TC) were the major risk factors for MAFLD in a group of patients with a BMI ≥ 23 kg/m2 (all p < 0.05).Conclusion: OSA-associated chronic intermittent hypoxia was independently associated with the risk of MAFLD, especially in OSA patients with a BMI ≥ 23 kg/m2, suggesting that oxidative stress might play an important role in the pathogenesis of MAFLD in patients with OSA.Keywords: obstructive sleep apnea, chronic intermittent hypoxia, metabolic dysfunction-associated fatty liver disease, obesity

The coronavirus disease 2019 (COVID‐19) has evolved into a pandemic rapidly. Most of the literature show that the elevated liver enzymes in COVID‐19 are of little clinical significance. Lower albumin level is seen in severe COVID‐19 and is not parallel to the changes in alanine aminotransferase and aspartate aminotransferase levels. We aimed to explore the impact of hypoalbuminemia in COVID‐19. This retrospective cohort study included adult patients with confirmed COVID‐19. The relationship between hypoalbuminemia and death was studied using binary logistic analysis. A total of 299 adult patients were included, 160 (53.5%) were males and the average age was 53.4 ± 16.7 years. The median time from the onset of illness to admission was 3 days (interquartile ranges, 2‐5). Approximately one‐third of the patients had comorbidities. Hypoalbuminemia (

The fusion of infrared and visible images is difficult because of their different modalities. Current fusion methods are difficult to maintain both complementary information and good visual effects, such as methods of region discrimination based on visual saliency and methods based on total variation (TV). Among them, methods of region discrimination based on visual saliency for fusion have better complementary information but poor visual consistency, while methods based on total variation for fusion have good visual consistency, but there is no proper regularization to ensure sufficient selection and fusion of complementary information. In this paper, an improved infrared and visible image fusion method via visual saliency and fractional-order total variation is proposed. First, the infrared and visible images are fused through the saliency map to obtain a fused image, and then the fused image and an selected original image are fused by the fractional-order total variation to obtain the final fused image. In this paper, visual saliency map-based fusion makes the fused image contain as much complementary information as possible from the source image, while fractional-order total variation-based fusion makes the fused image have better visual effects. Compared with the state-of-the-art image fusion algorithm, the experimental results show that the proposed method is more competitive in retaining image texture details and having visual effects.

Background: Hypoxia in obstructive sleep apnea (OSA) patients during sleep may have an effect on bone metabolism. Few data regarding evaluation of bone metabolism in young individuals diagnosed with OSA. In this study, we aim to identify the association between bone mineral density and OSA in young men (≤40 years old of age). Methods: Consecutive male subjects who underwent polysomnography were enrolled. Serum calcium, 25-hydroxyvitamin-D3, β-isomerized form C-terminal telopeptide of type I collagen, osteocalcin and procollagen type 1 N-propeptide were measured in all participants, and bone mineral density (BMD) at lumbar spine (L1-L4), femoral neck and hip total were determined by dual energy X-ray absorption (DXA). Results: The population consisted of 85 subjects (mean age 35.53 years). The BMD at lumbar spine (L1-L4) in moderate OSA patients was higher than control and severe OSA group significantly (p=0.036). After adjustment for confounding factors, stepwise multiple linear regression analyses showed LaSO2 (β = 0.340, p = 0.008) as an independent explanatory variable for Lumbar L1–L4 BMD, LaSO2 (β =0.304, p = 0.037), BMI (β = 0.393, p = 0.008) for femur neck BMD and BMI (β = 0.720, p = 0.002) for hip total BMD. Conclusion: Our finding indicates that there is a relationship between OSA and bone metabolism in younger men, suggesting OSA-related hypoxia was a protective factor for BMD, especially in moderate OSA group (10≤ AHI

Breast tumor segmentation is one of the key steps that helps us characterize and localize tumor regions. However, variable tumor morphology, blurred boundary, and similar intensity distributions bring challenges for accurate segmentation of breast tumors. Recently, many U-net variants have been proposed and widely used for breast tumors segmentation. However, these architectures suffer from two limitations: (1) Ignoring the characterize ability of the benchmark networks, and (2) Introducing extra complex operations increases the difficulty of understanding and reproducing the network. To alleviate these challenges, this paper proposes a simple yet powerful nested U-net (NU-net) for accurate segmentation of breast tumors. The key idea is to utilize U-Nets with different depths and shared weights to achieve robust characterization of breast tumors. NU-net mainly has the following advantages: (1) Improving network adaptability and robustness to breast tumors with different scales, (2) This method is easy to reproduce and execute, and (3) The extra operations increase network parameters without significantly increasing computational cost. Extensive experimental results with twelve state-of-the-art segmentation methods on three public breast ultrasound datasets demonstrate that NU-net has more competitive segmentation performance on breast tumors. Furthermore, the robustness of NU-net is further illustrated on the segmentation of renal ultrasound images. The source code is publicly available on https://github.com/CGPzy/NU-net.

ObjectiveTo evaluate the necessity of Covid-19 vaccination in children aged < 12 y by comparing the clinical characteristics between unvaccinated children aged < 12 y and vaccinated patients aged ≥ 12y during the Delta surge (B.1.617.2) in Putian, Fujian, China.MethodsA total of 226 patients with SARS-Cov-2 Delta variant (B.1.167.2; confirmed by Real-time PCR positivity and sequencing) were enrolled from Sep 10th to Oct 20th, 2021, including 77 unvaccinated children (aged < 12y) and 149 people aged ≥ 12y, mostly vaccinated. The transmission route was explored and the clinical data of two groups were compared; The effect factors for the time of the nucleic acid negativization (NAN) were examined by R statistical analysis.ResultsThe Delta surge in Putian spread from children in schools to factories, mostly through family contact. Compared with those aged ≥ 12y, patients aged < 12y accounted for 34.07% of the total and showed milder fever, less cough and fatigue; they reported higher peripheral blood lymphocyte counts [1.84 (1.32, 2.71)×10^9/L vs. 1.31 (0.94, 1.85)×10^9/L; pppppp=0.13).ConclusionUnvaccinated children may be an important link in the transmission of SARS-CoV-2 delta variant (B1.617.2), which indicated an urgent need of vaccination for this particular population.

ObjectiveTo evaluate the necessity of Covid-19 vaccination in children aged < 12 y by comparing the clinical characteristics in unvaccinated children aged < 12 y with vaccinated patients aged ≥ 12y during the Delta surge (B.1.617.2) in Putian, Fujian, China.MethodsA total of 226 patients with SARS-Cov-2 Delta variant (B.1.167.2; confirmed by Realtime PCR positive and sequencing) were enrolled from Sep 10th to Oct 20th, 2021, including 77 unvaccinated children (aged < 12y) and 149 people aged ≥ 12y, mostly vaccinated. The transmission route was explored and the clinical data of two groups were compared; the effect factors for the time of the nucleic acid negativization (NAN) were examined by R statistical analysis.ResultsThe Delta surge in Putian spread from children in schools to factories, mostly through family contact. Compared with those aged ≥ 12y, patients aged < 12y accounted for 34.07% of the total and showed milder fever, less cough and fatigue; they reported higher peripheral blood lymphocyte counts [1.84(1.32,2.71)×10^9/L vs. 1.31(0.94,1.85)×10^9/L; pp< 0.05]. Upon admission, their COVID19 antibodies (IgM and IgG) and IgG in convalescence were lower [0.13(0.00,0.09) vs. 0.12(0.03,0.41), pp pp=0.13).ConclusionChildren aged < 12y may be critical hidden spreaders, which indicates an urgent need of vaccination for this particular population.

Due to the influence of kidney morphology, heterogeneous structure and image quality, segmenting kidney in ultrasound images is challenging. To alleviate this challenge, we proposed a novel deep neural network architecture, namely Multi-branch Aware Network (MBANet), to segment kidney accurately and robustly. MBANet mainly consists of multi-scale feature pyramid (MSFP), multi-branch encoders (MBE) and master decoder. The design of MSFP can make the network more accessible to different kinds of class details at different scales. The information exchange between MBE can reduce the loss of feature information and improve the segmentation accuracy of the network. In addition, we designed a multi-scale fusion block (MFBlock) in the MBE to further extract and fuse more refined multi-scale image information. In order to further improve the robustness of MBANet, this paper also designed a step-by-step training mechanism. We validated the proposed approach and compared to several state-of-the-art approaches on the same kidney ultrasound datasets using six quantitative metrics. The results of our method on the six indicators of pixel accuracy (PA), intersection over union (IoU), precision, recall, specificity and F1-score (F1) are 98.83%, 92.38%, 97.10%, 95.03%, 99.46% and 0.9601, respectively. Compared with the comparison method, the average values on the six indicators are improved by about 2%. The evaluation results and segmentation results demonstrate that the proposed approach achieves the best overall performance on kidney ultrasound images segmentation.

Introduction The key transformed T cell transcription factor recombination activation gene protein 2 (RAG2) is regulated during inflammation to allow for the acquisition of effector T cells functions. The present study was designed to investigate whether stress signals elicited by leonurine (LEO) could lead to the degradation of RAG2 through v-akt murine thymoma viral oncogene homolog (AKT) signaling in lung fibrosis. Methods A total of 120 female mice were randomly divided into five groups (Group I–V): Normal group, bleomycin (BLM), BLM+LEO 50 mg/kg/d, BLM+LEO 100 mg/kg/d, and BLM+LEO 50 mg/kg/d+LY294002. Hematoxylin-eosin, Masson’s, and terminal deoxynucleotidyl transferase dUTP nick-end labeling staining were performed to observe the pathomorphological changes. The expression of CD3+, TGF-β, RAG2, and Bcl proteins was examined by immunodetection, while that of E-cadherin (ECAD), AKT, TGF-β1, alpha-actin-2, Bax, and RAG2 was detected by Western blot analysis. Results The level of T lymphocytes was reduced sharply in LEO-treated mice as compared to the other groups. The AKT signal was greatly inhibited in the BLM group and activated with LEO treatment on day 14. In addition, RAG2 was attenuated by LEO on day 14 and day 28. LY294002 could reverse the expression of AKT and RAG2 on day 28. Remarkably, the low dose of LEO has a greater protective efficacy as compared to the high-dose LEO group in terms of pulmonary fibrosis, T cell inactivation, and apoptosis in alveolar cells. Conclusion The results of the present study suggested that LEO has a protective effect on lung fibrosis with possible mechanisms of attenuating apoptosis and inflammation via the upregulation of the AKT signal in transformed T cells by suppressing the expression and activity of RAG2.

Endoscopic stone segmentation is of great significance in the comprehensive diagnosis and surgical planning of ureteroscopic lithotripsy. Due to the quality problems of endoscopic imaging, such as artifact, highlight, reflection, contrast imbalance and blur, it is a great challenge to segment kidney stone fragments of different shapes. In this study, the improved U-Net model was used to extract the kidney stone fragment area at the pixel level, and its contour information could be accurately obtained. The VGG16 network with strong portability is used as the encoder of U-Net model to extract the semantic information of multiple feature layers, and the up-sampling is realized by using transposal convolution to gradually restore the segmentation details. In the experiment, DCE Loss combining Dice Loss and Cross Entropy Loss is adopted as the Loss function of the model. The experimental results show that the improved U-Net model has higher accuracy for stone segmentation from endoscopic images, with the MPA, MIoU and F1 score of 96.44%, 97.62% and 97.03% respectively. The F1 score of the modified model is 2.25% higher than that of Deeplabv3 + model, and 14.24% higher than that of standard U-Net model.

The three-dimensional porous structure is a common scene in the field of medical surgery. However, the imaging resolution of the endoscope is low, and its scene has weak texture features and high noise, which leads it difficult for traditional algorithms to segment the porous structure. In this study, a new approach for efficient segmentation of intrarenal porous areas in endoscopic images is put forward. The proposed method first classifies the images into deep and shallow groups based on the statistical vectors derived from the color feature histogram. Then for each group, the improved U-Net learning strategy is used to extract the intrarenal porous areas at the pixel level, and its segmentation results could be accurately obtained. The effectiveness and accuracy of this work are evaluated on the data of the ureteroscopic holmium laser lithotripsy.

Background COVID-19 pandemic has forced physicians to quickly determine the patient’s condition and choose treatment strategies. This study aimed to build and validate a simple tool that can quickly predict the deterioration and survival of COVID-19 patients. Methods A total of 351 COVID-19 patients admitted to the Third People’s Hospital of Yichang between 9 January to 25 March 2020 were retrospectively analyzed. Patients were randomly grouped into training (n = 246) or a validation (n = 105) dataset. Risk factors associated with deterioration were identified using univariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression. The factors were then incorporated into the nomogram. Kaplan-Meier analysis was used to compare the survival of patients between the low- and high-risk groups divided by the cut-off point. Results The least absolute shrinkage and selection operator (LASSO) regression was used to construct the nomogram via four parameters (white blood cells, C-reactive protein, lymphocyte≥0.8 × 109/L, and lactate dehydrogenase ≥400 U/L). The nomogram showed good discriminative performance with the area under the receiver operating characteristic (AUROC) of 0.945 (95% confidence interval: 0.91–0.98), and good calibration (P = 0.539). Besides, the nomogram showed good discrimination performance and good calibration in the validation and total cohorts (AUROC = 0.979 and AUROC = 0.954, respectively). Decision curve analysis demonstrated that the model had clinical application value. Kaplan-Meier analysis illustrated that low-risk patients had a significantly higher 8-week survival rate than those in the high-risk group (100% vs 71.41% and P Conclusion A simple-to-use nomogram with excellent performance in predicting deterioration risk and survival of COVID-19 patients was developed and validated. However, it is necessary to verify this nomogram using a large-scale multicenter study.

Jia-Xin Shen,1 Ze-Hao Zhuang,1 Qiao-Xian Zhang,2 Jiao-Feng Huang,3 Gong-Ping Chen,4 Ying-Ying Fang,5 Ai-Guo Cheng6 1Endoscopy Center, First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China; 2Nursing Department, First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China; 3Department of Liver Research Center, First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China; 4Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China; 5Department of Tuberculosis, Third People’s Hospital of Yichang, Yichang, People’s Republic of China; 6Department of Critical Care, Third People’s Hospital of Yichang, Yichang, People’s Republic of ChinaCorrespondence: Ze-Hao ZhuangEndoscopy Center, First Affiliated Hospital of Fujian Medical University, 20, Chazhong Road, Taijiang District, Fuzhou, 350005, Fujian Province, People’s Republic of ChinaTel +86-131-7803-2412Fax +89-59187981370Email zhuang203@yeah.netPurpose: COVID-19 is a new infectious disease with global spread. The aim of the present study was to explore possible risk factors and evaluate prognosis in COVID-19 with liver injury.Methods: A retrospective study was conducted on 356 COVID-19 patients in the Third People’s Hospital of Yichang, Hubei, China. Clinical characteristics and laboratory tests between patients with and without liver injury were compared, while risk factors of COVID-19–related liver injury were analyzed. Univariate and multivariate Cox regression analyses were conducted to identify risk factors of in-hospital death.Results: Of the patients with liver injury, severe and critical types of COVID-19 comprised 12.43% and 14.69%, respectively, higher than in patients without liver injury (both P< 0.05). CRP and male sex were independent risk factors for for patients with liver injury, while decreased lymphocyte count (HR 0.024, 95% CI 0.001– 0.821) and elevated monocytes (HR 1.951, 95% CI 1.040– 3.662) and CRP (HR 1.028, 95% CI 1.010– 1.045) were independent risk factors of prognosis of death in COVID-19 patients with liver injury.Conclusion: Liver injury is a common complication in severe COVID-19 patients. Male sex and elevated CRP were independent risk factors in COVID-19 complicated by liver damage. Liver damage with increased CRP and monocyte count and decreased lymphocyte count may imply a poor prognosis.Keywords: COVID-19, liver injury, risk factors, prognosis