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Background: Pulmonary enteric adenocarcinoma (PEAC) has distinctive clinical outcomes, radiographic, pathological and molecular characteristics. The prognosis of patients with PEAC was poor. However, molecular profiles and therapeutic biomarkers of PEAC remain elusive. Methods: In the present study, the hospitalized patients with PEAC admitted to Tongji Hospital in Wuhan from January 1, 2014 to November 20, 2020 were retrospectively enrolled and followed until December 10, 2020. Comprehensive genomic profiling of tumor tissue from the PEAC patients were performed and compared with lung adenocarcinoma, colorectal cancer and metastatic colorectal carcinoma. Tumor immune microenvironment analysis were evaluated. Results: There were 10 patients with PEAC enrolled. 70% of patients were male and the median age of onset was 63 years (interquartile range, 55–72). There were six early-stage patients (Stage IA to IIB) and four stage IV patients. Molecular analysis revealed the most common gene mutations included TP53 (57%, 4/7) and KRAS (57%, 4/7) mutations. There were 40% mutations occurred in genes encoding receptor tyrosine kinases (RTKs). 100% of patients (8/8) were microsatellite stability (MSS). The median level of TMB was 6.0 (interquartile range, 4.5–7.0) mutations/Mb. Three of 10 patients showed low PD-L1 expression (tumor proportion score < 10%) and the others were PD-L1 negative. A small subset of CD8+, CD3+, CD68+ T cells were observed and were mainly distributed in the cancer stroma. Conclusion: This study demonstrated that PEAC was characterized by low-frequency RTK gene mutation, high KRAS mutation, low PD-L1 expression, low TMB, and low CD8+ T cells infiltration. [ABSTRACT FROM AUTHOR]

Metro subway systems with underground tunnels form the backbone of urban transportations and therefore, accurate monitoring and maintenance of such subway systems are extremely necessary for a hassle-free daily commutation of billions of people. Though 3-D models of tunnels are widely used for the deformation monitoring of such subway tunnels, existing model-based tunnel monitoring systems rely on coarse geometric models and hence fail to capture complete tunnel health information. We present a two-stage algorithm to create high-fidelity geometric models of tunnel lining from Terrestrial Laser Scanning (TLS) point clouds. Tunnel geometry, defined at the detailed block entity level, is constructed through a data-driven block segmentation algorithm and a model-driven assembly technique. In our approach, the 3-D tunnel block segmentation problem has been translated into a bolt and lining joint recognition problem from 2-D images unfolded from the 3-D scans. The segmented 3-D blocks are matched with a set of predefined 3-D templates from a primitive library via a constraint total least squares matching method and the matched 3-D templates are assembled to create the final watertight tunnel model. The proposed tunnel modeling method has been comprehensively evaluated on Changzhou, Nanjing, and Wuhan tunnel data sets in terms of outliers, missing data, point density, topological representation, robustness, and geometric accuracy. The experiments on Nanjing and Changzhou metro tunnels show that the geometric model fitting incurs an error of only 7 mm, which is almost consistent with a mean density of 6 mm of these two data sets. Experimental results validate the advantages and potentials of the proposed tunnel modeling method. [ABSTRACT FROM AUTHOR]

A newly identified coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), which causes the infectious coronavirus disease 2019 (COVID‐19), emerged in December 2019 in Wuhan, Hubei Province, China, and now poses a major threat to global public health. Previous studies have observed highly variable alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels in patients with COVID‐19. However, circulating levels of the cholangiocyte injury biomarker gamma‐glutamyltransferase (GGT) have yet to be reported in the existing COVID‐19 case studies. Herein, we describe the relationship between GGT levels and clinical and biochemical characteristics of patients with COVID‐19. Our study is a retrospective case series of 98 consecutive hospitalized patients with confirmed COVID‐19 at Wenzhou Central Hospital in Wenzhou, China, from January 17 to February 5, 2020. Clinical data were collected using a standardized case report form. Diagnosis of COVID‐19 was assessed by symptomatology, reverse‐transcription polymerase chain reaction (RT‐PCR), and computed tomography scan. The medical records of patients were analyzed by the research team. Of the 98 patients evaluated, elevated GGT levels were observed in 32.7%; increased C‐reactive protein (CRP) and elevated ALT and AST levels were observed in 22.5%, 13.3%, and 20.4%, respectively; and elevated alkaline phosphatase (ALP) and triglycerides (TGs) were found in 2% and 21.4%, respectively. Initially, in the 82 patients without chronic liver disease and alcohol history, age older than 40 years (P = 0.027); male sex (P = 0.0145); elevated CRP (P = 0.0366), ALT (P < 0.0001), and ALP (P = 0.0003); and increased TGs (P = 0.0002) were found to be associated with elevated GGT levels. Elevated GGT (P = 0.0086) and CRP (P = 0.0162) levels had a longer length of hospital stay. Conclusion: A sizable number of patients with COVID‐19 infection have elevated serum GGT levels. This elevation supports involvement of the liver in persons with COVID‐19. [ABSTRACT FROM AUTHOR]

Previous studies on coronavirus disease 2019 (COVID-19) have focused on populations with normal immunity, but lack data on immunocompromised populations. To evaluate the clinical features and outcomes of COVID-19 pneumonia in kidney transplant recipients. A total of 10 renal transplant recipients with laboratory-confirmed COVID-19 pneumonia were enrolled in this retrospective study. In addition, 10 of their family members diagnosed with COVID-19 pneumonia were included in the control group. Immunosuppressant reduction and low-dose methylprednisolone therapy. The clinical outcomes (the severity of pneumonia, recovery rate, time of virus shedding, and length of illness) were compared with the control group by statistical analysis. The clinical symptomatic, laboratory, and radiological characteristics of COVID-19 pneumonia in the renal transplant recipients were similar to those of severe COVID-19 pneumonia in the general population. The severity of COVID-19 pneumonia was greater in the transplant recipients than in the control group (five severe/three critical cases vs one severe case). Five patients developed transient renal allograft damage. After a longer time of virus shedding (28.4 ± 9.3 vs 12.2 ± 4.6 d in the control group) and a longer course of illness (35.3 ± 8.3 vs 18.8 ± 10.5 d in the control group), nine of the 10 transplant patients recovered successfully after treatment. One patient developed acute renal graft failure and died of progressive respiratory failure. Kidney transplant recipients had more severe COVID-19 pneumonia than the general population, but most of them recovered after a prolonged clinical course and virus shedding. Findings from this small group of cases may have important implications for the treatment of COVID-19 pneumonia in immunosuppressed populations. Immunosuppressed transplant recipients with coronavirus disease 2019 infection had more severe pneumonia, but most of them still achieved a good prognosis after appropriate treatment. Immunosuppressed renal transplant recipients with coronavirus disease 2019 infection had more severe pneumonia than the general population. Most patients could recover following a treatment regimen consisting of reduced immunosuppressant use, low-dose methylprednisolone therapy, and protection of renal graft function. [ABSTRACT FROM AUTHOR]