As of March 24, 2020, novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been responsible for 379,661 infection cases with 16,428 deaths globally, and the number is still increasing rapidly. Herein, we present four critically ill patients with SARS-CoV-2 infection who received supportive care and convalescent plasma. Although all four patients (including a pregnant woman) recovered from SARS-CoV-2 infection eventually, randomized trials are needed to eliminate the effect of other treatments and investigate the safety and efficacy of convalescent plasma therapy.

Anormal pulmonary function and residual CT abnormalities in rehabilitating COVID-19 patients after discharge To the editor , We read with great interest an article recently published in the Journal of Infection, in which, the authors followed up the pulmonary function and chest CT changes in two critically ill patients with COVID-19. 1 The two patients' distinct outcomes that seems be related with age, the young case recovered without abnormalities on chest CT and lung function tests, while the older case had residual radiological changes and impaired lung function during the follow-up period. Recent evidences have suggested that lung is the most affected organ by COVID-19. 2 Persistent impairment of pulmonary function ranging from months to even years after discharge has been reported in other coronavirus infections, such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). 3-6 However, post-discharge imaging or lung functional data are scarce for COVID-19 survivors. Hence, we aimed to report the pulmonary function and chest CT changes in these patients with different severities. Laboratory confirmed COVID-19 patients were enrolled from March 26 to May 1, 2020 from a designated hospital of Hubei province. According to the newest COVID-19 guidelines released by the National Health Commission of China, the disease severities were classified as mild, moderate, severe and critical illness. 7 The criteria for discharge were as follows: 7 (1) normal temperature lasting longer than three days, (2) resolved respiratory symptoms, (3) substantially improved acute exudative lesions on chest CT images, and (4) a series of two repetitive negative reverse transcription-polymerase chain reaction test results, separated by at least one day. The pulmonary function test (XEEK portable PFT X1, Xiamen, China) was performed following the American Thoracic Society/European Respiratory Society (ATS-ERS) guidelines on COVID-19 patients after discharge. The chest CT closest to the data of the pulmonary function test was reviewed independently by two cardiothoracic radiologists, who blinded to the clinical information. Final decisions were reached by consensus. This study was approved by the ethics committee of The First Affiliated Hospital of Jinan University, and written informed consent was obtained from all patients. We performed lung function test on 18 COVID-19 patients after discharge, which included 12 cases of moderate illness, five cases of severe illness and one case of critical illness. The mean age of the patients was 50.7 ± 12.1 (range, 28-67 years) and 10 were male. Only four patients (22.2%) had one or more underlying disease, such as hypertension, diabetes, and hypothyroidism. No patients had chronic lung diseases. There were no significant differences between the non-severe and severe groups in regard

Background: Distant metastasis is the primary cause of treatment failure in locoregionally advanced nasopharyngeal carcinoma (LANPC). Purpose: To develop a model to evaluate distant metastasis-free survival (DMFS) in LANPC and to explore the value of additional chemotherapy to concurrent chemoradiotherapy (CCRT) for different risk groups. Study Type: Retrospective. Population: In all, 233 patients with biopsy-confirmed nasopharyngeal carcinoma (NPC) from two hospitals. Field Strength: 1.5T and 3T. Sequence: Axial T 2-weighted (T 2-w) and contrast-enhanced T 1-weighted (CET 1-w) images. Assessment: Deep learning was used to build a model based on MRI images (including axial T 2-w and CET 1-w images) and clinical variables. Hospital 1 patients were randomly divided into training (n = 169) and validation (n = 19) cohorts; Hospital 2 patients were assigned to a testing cohort (n = 45). LANPC patients were divided into low-and high-risk groups according to their DMFS (P < 0.05). Kaplan-Meier survival analysis was performed to compare the DMFS of different risk groups and subgroup analysis was performed to compare patients treated with CCRT alone and treated with additional chemotherapy to CCRT in different risk groups, respectively. Statistical Tests: Univariate analysis was performed to identify significant clinical variables. The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the model performance. Results: Our deep-learning model integrating the deep-learning signature, node (N) stage (from TNM staging), plasma Epstein-Barr virus (EBV)-DNA, and treatment regimens yielded an AUC of 0.796 (95% confidence interval [CI]: 0.729-0.863), 0.795 (95% CI: 0.540-1.000), and 0.808 (95% CI: 0.654-0.962) in the training, internal validation, and external testing cohorts, respectively. Low-risk patients treated with CCRT alone had longer DMFS than patients treated with additional chemotherapy to CCRT (P < 0.05).

Cancer remains a leading cause of death worldwide and total number of cases globally is increasing. Novel treatment strategies are therefore desperately required for radical treatment of cancers and long survival of patients. A new technology using high pulsed electric field has emerged from military application into biology and medicine by applying nsPEF as a means to inhibit cancer. However, molecular mechanisms of nsPEF on tumors or cancers are still unclear. In this paper, we found that nsPEF had extensive biological effects in cancers, and clarified its possible molecular mechanisms in vitro and in vivo. It could not only induce cell apoptosis via dependent-mitochondria intrinsic apoptosis pathway that was triggered by imbalance of anti- or pro-apoptosis Bcl-2 family proteins, but also inhibit cell proliferation through repressing NF-κB signaling pathway to reduce expressions of cyclin proteins. Moreover, nsPEF could also inactivate metastasis and invasion in cancer cells by suppressing Wnt/β-Catenin signaling pathway to down-regulating expressions of VEGF and MMPs family proteins. More importantly, nsPEF could function safely and effectively as an anti-cancer therapy through inducing tumor cell apoptosis, destroying tumor microenvironment, and depressing angiogenesis in tumor tissue in vivo. These findings may provide a creative and effective therapeutic strategy for cancers.

Background: Microvascular invasion (MVI) is a critical prognostic factor of hepatocellular carcinoma (HCC). However, it could only be obtained by postoperative histological examination. Purpose: To develop an end-to-end deep-learning models based on MRI images for preoperative prediction of MVI in HCC patients who underwent surgical resection. Study type: Retrospective. Population: Two hundred and thirty-seven patients with histologically confirmed HCC. Field strength: 1.5 T and 3.0 T. Sequence: Axial T 2 -weighted (T 2 -w) with turbo spin echo sequence, T 2 -Spectral Presaturation with Inversion Recovery (T 2 -SPIR), and dynamic contrast-enhanced (DCE) imaging with fat suppressed enhanced T 1 high-resolution isotropic volume examination. Assessment: The patients were randomly divided into training (N = 158) and validation (N = 79) sets. Data augmentation by random rotation was performed on the training set and the sample size increased to 1940 for each MR sequence. A three-dimensional convolutional neural network (3D CNN) was used to develop four deep-learning models, including three single-layer models based on single-sequence, and fusion model combining three sequences. MVI status was obtained from the postoperative pathology reports. Statistical Tests: The dice similarity coefficient (DSC) and Hausdorff distance (HD) were applied to assess the similarity and reproducibility between the manual segmentations of tumor from two radiologists. Receiver operating characteristic curve analysis was used to evaluate model performance. MVI was identified in 92 (38.8%) patients. Good reproducibility with interobserver DSCs of 0.90, 0.89, and 0.89 and HDs of 4.09, 3.67, and 3.60 was observed for PVP, T 2 WI, and T 2 -SPIR, respectively. The fusion model achieved an area under the curve (AUC) of 0.81, sensitivity of 69%, and specificity of 79% in the training set and 0.72, sensitivity of 55%, and specificity of 81% in the validation set. Data Conclusion: 3D CNN model may serve as a noninvasive tool to predict MVI in HCC, whereas its accuracy needs to be enhanced with larger cohort. Level of Evidence: 3 Technical Efficacy: Stage 2

The non-classical human leukocyte antigens (HLA)-E, HLA-G, and HLA-F have been shown to modulate immune responses. We examined whether non-classical HLA polymorphisms are associated with hepatitis B virus (HBV) infection and hepatocellular carcinoma (HCC). Fifteen Single-nucleotide polymorphisms (SNPs) in these non-classical class I alleles were investigated by ligase detection reaction. A fragment of 650 bp located in the 3' untranslated region of HLA-G was investigated. Four SNPs (rs17875380, rs41557518, rs114465251, and rs115492845) were associated with altered susceptibility to HBV or HCC, and HLA-F*01:04, HLA-G*01:05N, and HLA-E*01:01 were associated with hepatitis B or hepatitis B complicated with HCC. Six of 16 designated HLA-E, -G, and -F haplotypes were associated with risk of hepatitis B or HCC. Our study provides healthy reference and detailed analyses of non-classical HLA class Ι polymorphisms that provide insight into immune mechanisms involved in susceptibility to hepatitis B and HCC.

Purpose To quantify the severity of 2019 novel coronavirus disease (COVID-19) on chest CT and to determine its relationship with laboratory parameters. Methods Patients with real-time fluorescence polymerase chain reaction (RT-PCR)-confirmed COVID-19 between January 01 and February 18, 2020, were included in this study. Laboratory parameters were retrospectively collected from medical records. Severity of lung changes on chest CT of early, progressive, peak, and absorption stages was scored according to the percentage of lung involvement (5 lobes, scores 1-5 for each lobe, range 0-20). Relationship between CT scores and laboratory parameters was evaluated by the Spearman rank correlation. The Bonferroni correction adjusted significance level was at 0.05/4 = 0.0125. Results A total of 84 patients (mean age, 47.8 ± 12.0 years [standard deviation]; age range, 24-80 years) were evaluated. The patients underwent a total of 339 chest CT scans with a median interval of 4 days (interquartile range, 3-5 days). Median chest CT scores peaked at 4 days after the beginning of treatment and then declined. CT score of the early stage was correlated with neutrophil count (r = 0.531, P = 0.011). CT score of the progressive stage was correlated with neutrophil count (r = 0.502, P < 0.001), white blood cell count (r = 0.414, P = 0.001), C-reactive protein (r = 0.511, P < 0.001), procalcitonin (r = 0.423, P = 0.004), and lactose dehydrogenase (r = 0.369, P = 0.010). However, CT scores of the peak and absorption stages were not correlated with any parameter (P > 0.0125). No sex difference occurred regarding CT score (P > 0.05). Conclusion Severity of lung abnormalities quantified on chest CT might correlate with laboratory parameters in the early and progressive stages. However, larger cohort studies are necessary.

Background Hyperprogressive disease (HPD) is a new progressive pattern in patients with advanced hepatocellular carcinoma (HCC) treated with programmed cell death 1 (PD-1) inhibitors. We aimed to investigate risk factors associated with HPD in advanced HCC patients undergoing anti-PD-1 therapy. Methods A total of 69 patients treated with anti-PD-1 therapy between March 2017 and January 2020 were included. HPD was determined according to the time to treatment failure, tumour growth rate, and tumour growth rate ratio. Univariate and multivariate analyses were performed to identify clinical variables significantly associated with HPD. A risk model was constructed based on clinical variables with prognostic significance for HPD. Findings Overall, 10 (14·49%) had HPD. Haemoglobin level, portal vein tumour thrombus, and Child-Pugh score were significantly associated with HPD. The risk model had an area under the curve of 0·931 (95% confidence interval, 0·844–1·000). Patients with HPD had a significantly shorter overall survival (OS) than that of the patients with non-HPD ( p < 0·001). However, there was no significant difference in OS between PD (progressive disease) patients with and without HPD ( p = 0·05). Interpretation We identified three clinical variables as risk factors for HPD, providing an opportunity to aid the pre-treatment evaluation of the risk of HPD in patients treated with immunotherapy. Funding This study was funded by the National Natural Science Foundation of China (81571664, 81871323, and 81801665); National Natural Science Foundation of Guangdong Province (2018B030311024); Scientific Research General Project of Guangzhou Science Technology and Innovation Commission (201707010,328); and China Postdoctoral Science Foundation (2016M600145).