Background: Pulmonary mucormycosis (PM) is a relatively rare but often fatal and rapidly progressive disease. Most studies of PM are case reports or case series with limited numbers of patients, and focus on immunocompromised patients. We investigated the clinical manifestations, imaging features, treatment, and outcomes of patients with PM with a focus on the difference in clinical manifestations between patients with different immune status. Methods: Clinical records, laboratory results, and computed tomography scans of 24 patients with proven or probable PM from January 2005 to December 2018 in Peking Union Medical College Hospital were retrospectively analyzed. Results: Ten female and 14 male patients were included (median age, 43.5 years; range, 13–64 years). Common presenting symptoms were fever (70.8%), cough (70.8%), sputum production (54.2%), and hemoptysis (41.7%). Radiological findings included consolidation (83.3%), ground-glass opacities (58.3%), nodules (50.0%), masses (37.5%), cavities (33.3%), mediastinal lymphadenopathy (29.2%), and halo sign (12.5%); one patient had a reversed halo sign. Seven patients (29.2%) had no obvious predisposing risk factors, and 17 (70.8%) had underlying diseases including diabetes, hematological malignancy, and use of immunosuppressants. Compared with immunocompromised patients, immunocompetent patients with PM were younger {23 [13–46] vs. 48 [17–64] years, P=0.023}, comprised a higher proportion of men (100.0% vs. 41.2%, P=0.019), had a longer disease course {34 [8–47] vs. 9 [2–102] weeks, P=0.033}, had a higher eosinophil count [0.66 (0.07–2.00) ×10⁹/L vs. 0.04 (0.00–0.23) ×10⁹/L, P=0.001], and had a lower erythrocyte sedimentation rate {12 [1–88] vs. 74 [9–140] mm/h, P=0.032}. Conclusions: PM can occur in heterogeneous patients with different immune status, and the clinical phenotype differs between immunocompetent and immunocompromised patients. Because of the lack of specific clinic and imaging manifestations, aggressive performance of invasive procedures to obtain histopathological and microbial evidence is crucial for a definitive diagnosis.

Objective: While the upregulation of cytochrome P450 family 24 subfamily A member 1 (CYP24A1) gene expression has been reported in colon cancer, its role in tumorigenesis remains largely unknown. In this study, we aimed to investigate the involvement of CYP24A1 in Wnt pathway regulation via the nuclear factor kappa B (NF-κB) pathway. Methods: The human colon cancer cell lines HCT-116 and Caco-2 were subjected to stimulation with interleukin-6 (IL-6) as well as tumor necrosis factor alpha (TNF-α), with subsequent treatment using the NF-κB pathway-specific inhibitor ammonium pyrrolidinedithiocarbamate (PDTC). Furthermore, CYP24A1 expression was subjected to knockdown via the use of small interfering RNA (siRNA). Subsequently, NF-κB pathway activation was determined by an electrophoretic mobility shift assay, and the transcriptional activity of β-catenin was determined by a dual-luciferase reporter assay. A mouse ulcerative colitis (UC)-associated carcinogenesis model was established, wherein TNF-α and the NF-κB pathway were blocked by anti-TNF-α monoclonal antibody and NF-κB antisense oligonucleotides, respectively. Then the tumor size and protein level of CYP24A1 were determined. Results: IL-6 and TNF-α upregulated CYP24A1 expression and activated the NF-κB pathway in colon cancer cells. PDTC significantly inhibited this increase in CYP24A1 expression. Additionally, knockdown of CYP24A1 expression by siRNA could partially antagonize Wnt pathway activation. Upregulated CYP24A1 expression was observed in the colonic epithelial cells of UC-associated carcinoma mouse models. Anti-TNF-α monoclonal antibody and NF-κB antisense oligonucleotides decreased the tumor size and suppressed CYP24A1 expression. Conclusion: Taken together, this study suggests that inflammatory factors may increase CYP24A1 expression via NF-κB pathway activation, which in turn stimulates Wnt signaling.

The aim of this study was to investigate the factors related to large-volume central cervical lymph node metastasis (LNM) in papillary thyroid carcinoma. A retrospective study of 340 patients with 642 papillary thyroid carcinoma nodules who underwent thyroidectomy in Peking Union Medical College Hospital between 2011 and 2015 was conducted. These nodules were divided into two groups by the number of central cervical lymph node metastases: large‐volume central cervical LNM (>5 metastatic lymph nodes, n = 129) and no central cervical LNM (n = 211). We evaluated the correlations between gender, age, chronic lymphocytic thyroiditis, thyroid ultrasonographic features, and large‐volume central cervical LNM. We found that younger age (≤40 years) (OR = 3.796, 95% CI = 2.842, 5.070), male gender (OR = 4.005, 95% CI = 2.858, 5.61), and ultrasonographic features such as tumor macroaxis size (OR = 2.985, 95% CI = 1.581, 5.633), tumor located in the isthmus (OR = 7.578, 95% CI = 4.863, 11.810), ill-defined margin (OR = 3.008, 95% CI = 1.986, 4.556), microcalcification (OR = 2.155, 95% CI = 1.585, 2.929), and abnormal cervical lymph nodes (OR = 13.753, 95% CI = 9.278, 20.385) were independent risk factors for large-volume central cervical LNM in papillary thyroid carcinoma, while chronic lymphocytic thyroiditis (OR = 0.248, 95% CI = 0.172, 0.358) was a protective factor. Younger age (≤40 years), male sex, and ultrasonographic features such as tumor macroaxis size, tumor located in the isthmus, ill-defined margin, microcalcification, and abnormal cervical lymph nodes were independent risk factors for large-volume central cervical LNM in papillary thyroid carcinoma, while chronic lymphocytic thyroiditis can be considered a protective factor. Our results provide a reference for adjusting clinical treatment approaches.

Contrast-enhanced ultrasound (CEUS) is a promising imaging modality in predicting the efficacy of neoadjuvant chemotherapy for pancreatic cancer, a tumor with high mortality. In this study, we proposed a deep-learning-based strategy for analyzing CEUS videos to predict the prognosis of pancreatic cancer neoadjuvant chemotherapy. Pre-trained convolutional neural network (CNN) models were used for binary classification of the chemotherapy as effective or ineffective, with CEUS videos collected before chemotherapy as the model input, and with the efficacy after chemotherapy as the reference standard. We proposed two deep learning models. The first CNN model used videos of ultrasound (US) and CEUS (US+CEUS), while the second CNN model only used videos of selected regions of interest (ROIs) within CEUS (CEUS-ROI). A total of 38 patients with strict restriction of clinical factors were enrolled, with 76 original CEUS videos collected. After data augmentation, 760 and 720 videos were included for the two CNN models, respectively. Seventy-six-fold and 72-fold cross-validations were performed to validate the classification performance of the two CNN models. The areas under the curve were 0.892 and 0.908 for the two models. The accuracy, recall, precision and F1 score were 0.829, 0.759, 0.786, and 0.772 for the first model. Those were 0.864, 0.930, 0.866, and 0.897 for the second model. A total of 38.2% and 40.3% of the original videos could be clearly distinguished by the deep learning models when the naked eye made an inaccurate classification. This study is the first to demonstrate the feasibility and potential of deep learning models based on pre-chemotherapy CEUS videos in predicting the efficacy of neoadjuvant chemotherapy for pancreas cancer.

Background: Pediatric community acquired pneumonia (pCAP) is a major public health and economic problem with a considerable impact on morbidity and mortality in children. Recently many studies and meta-analyses have shown promising results on the accuracy of lung ultrasonography (LU) in diagnosing pneumonia and potentially replacing chest radiography (CR) in pediatric population. However, previous studies establishing the accuracy of LU often used CR as reference standard and took into account different clinical settings all together. To make a more objective and specific analysis, we performed a systematic review and meta-analysis to compare the diagnostic accuracy of LU and CR for pCAP in the emergency department (ED) setting. Methods: A literature search of PubMed and Embase databases up to December 2018 was conducted. Pooled sensitivity, specificity, positive and negative likelihood ratio, and diagnostic odds ratio of LU and CR were calculated, and summary receiver operating characteristic (SROC) curves were drawn. Results: A total of six studies, which included 575 pCAPs from 701 patients, were finally analyzed. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratios of LU were 96.7%, 87.3%, 8.10, 0.05, 256.68, while they were 89.7%, 93.7%, 9.97, 0.12, 175.07 for CR, respectively. The area under the SROC curves in diagnosing pCAP in the ED setting were 0.99 [95% confidence interval (CI), 0.98–1.00] and 0.97 (95% CI, 0.95–1.00) for LU and CR, respectively. Conclusions: Our meta-analysis suggests that LU is an accurate tool in the diagnosis of pCAP in the ED setting with a superior sensitivity over CR.