The twenty-first century has already recorded more than ten major epidemics or pandemics of viral disease, including the devastating COVID-19. Novel effective antivirals with broad-spectrum coverage are urgently needed. Herein, we reported a novel broad-spectrum antiviral compound PAC5. Oral administration of PAC5 eliminated HBV cccDNA and reduced the large antigen load in distinct mouse models of HBV infection. Strikingly, oral administration of PAC5 in a hamster model of SARS-CoV-2 omicron (BA.1) infection significantly decreases viral loads and attenuates lung inflammation. Mechanistically, PAC5 binds to a pocket near Asp49 in the RNA recognition motif of hnRNPA2B1. PAC5-bound hnRNPA2B1 is extensively activated and translocated to the cytoplasm where it initiates the TBK1-IRF3 pathway, leading to the production of type I IFNs with antiviral activity. Our results indicate that PAC5 is a novel small-molecule agonist of hnRNPA2B1, which may have a role in dealing with emerging infectious diseases now and in the future.
Animals ; Mice ; Antiviral Agents/pharmacology* ; COVID-19 ; Hepatitis B virus ; Interferon Type I/metabolism* ; SARS-CoV-2/drug effects* ; Heterogeneous-Nuclear Ribonucleoprotein Group A-B/antagonists & inhibitors*

OBJECTIVE: To analyze the distribution characteristics of emerging and reemerging Oncomelania hupensis snails after the criteria for transmission control of schistosomiasis were achieved in China, so as to provide insights into assessment of schistosomiasis transmission risk and formulation of snail control strategies during the elimination phase. METHODS: O. hupensis survey data in China from 2015 to 2021 were collected from the National Schistosomiasis Pevention and Control Information Management System, and the distribution characteristics of emerging and reemerging O. hupensis snails were descriptively analyzed. RESULTS: Emerging and reemerging O. hupensis snails were identified in China each year from 2015 to 2021, with relatively larger areas with emerging and reemerging O. hupensis snail habitats in 2016 and 2021, and relatively higher numbers of counties (districts) where emerging and reemerging O. hupensis snails were detected in 2016 and 2021. A total of 4 586.30 hm² of emerging O. hupensis snail habitats were found in 10 schistosomiasis-endemic provinces of China (except Fujian and Yunnan Provinces) from 2015 to 2021, with 96.80% in Anhui, Hunan and Hubei provinces, where marshland and lake endemic foci were predominant. A total of 21 023.90 hm² of reemerging O. hupensis snail habitats were found in 12 schistosomiasis-endemic provinces of China from 2015 to 2021, with 97.67% in six provinces of Hubei, Sichuan, Jiangxi, Jiangsu, Yunnan and Anhui, where marshland and lake and hilly endemic regions were predominant. Emerging snail habitats were found in 15.08% of all schistosomiasisendemic counties (districts) in China from 2015 to 2021, and 78.75% of all emerging snail habitats were identified in 11 schistosomiasis-endemic counties (districts), with the largest area of emerging snail habitats found in Lixian County, Hunan Province (645.00 hm²). Reemerging snail habitats were found in 47.67% of all schistosomiasis-endemic counties (districts) in China from 2015 to 2021, and 43.29% of all reemerging snail habitats were identified in 11 schistosomiasis-endemic counties (districts), with the largest area of reemerging snail habitats found in Weishan Li and Hui Autonomous County of Hunan Province (1 579.70 hm²). CONCLUSIONS Emerging and reemerging O. hupensis snails were identified in China each year from 2015 to 2021, with much larger areas of reemerging snail habitats than emerging snail habitats, and larger numbers of schistosomiasis-endemic provinces and counties (districts) with reemerging snails were found that those of provinces and counties (districts) with emerging snails. Specific snail control interventions are required tailored to the causes of emerging and reemerging snail habitats. Both emergence and reemergence of O. hupensis snails should be paid attention to in marshland and lake endemic areas, and Guangxi Zhuang Autonomous Region, Shanghai Municipality and Zhejiang Province where schistosomiasis had been eliminated, and reemergence of O. hupensis snails should be given a high priority in hilly areas. In addition, monitoring of O. hupensis snails should be reinforced in snail-free areas after flooding.
Humans ; China/epidemiology* ; Schistosomiasis/prevention & control* ; Cities ; Ecosystem ; Lakes

Objective: To investigate the clinicopathological characteristics of plurihormonal PIT1-lineage pituitary neuroendocrine tumors. Methods: Forty-eight plurihormonal PIT1-lineage tumors were collected between January 2018 and April 2022 from the pathological database of Sanbo Brain Hospital, Capital Medical University. The related clinical and imaging data were retrieved. H&E, immunohistochemical and special stains were performed. Results: Out of the 48 plurihormonal PIT1-lineage tumors included, 13 cases were mature PIT1-lineage tumors and 35 cases were immature PIT1-lineage tumors. There were some obvious clinicopathological differences between the two groups. Clinically, the mature plurihormonal PIT1-lineage tumor mostly had endocrine symptoms due to increased hormone production, while a small number of immature PIT1-lineage tumors had endocrine symptoms accompanied by low-level increased serum pituitary hormone; patients with the immature PIT1-lineage tumors were younger than the mature PIT1-lineage tumors; the immature PIT1-lineage tumors were larger in size and more likely invasive in imaging. Histopathologically, the mature PIT1-lineage tumors were composed of large eosinophilic cells with high proportion of growth hormone expression, while the immature PIT1-lineage tumors consisted of chromophobe cells with a relatively higher expression of prolactin; the mature PIT1-lineage tumors had consistently diffuse cytoplasmic positive staining for keratin, while the immature PIT1-lineage tumors had various expression for keratin; the immature PIT1-lineage tumors showed more mitotic figures and higher Ki-67 proliferation index; in addition, 25.0% (12/48) of PIT1-positive plurihormonal tumors showed abnormal positive staining for gonadotropin hormones. There was no significant difference in the progression-free survival between the two groups (P=0.648) by Kaplan-Meier analysis. Conclusions: Plurihormonal PIT1-lineage tumor belongs to a rare type of PIT1-lineage pituitary neuroendocrine tumors, most of which are of immature lineage. Clinically increased symptoms owing to pituitary hormone secretion, histopathologically increased number of eosinophilic tumor cells with high proportion of growth hormone expression, diffusely cytoplasmic keratin staining and low proliferative activity can help differentiate the mature plurihormonal PIT1-lineage tumors from the immature PIT1-lineage tumors. The immature PIT1-lineage tumors have more complicated clinicopathological characteristics.
Humans ; Neuroendocrine Tumors ; Pituitary Neoplasms/pathology* ; Pituitary Hormones ; Growth Hormone/metabolism* ; Keratins

Objective: To investigate the clinicopathological characteristics of occupational lung diseases, to reduce the missed diagnoses and misdiagnoses of the diseases and to help standardize the diagnosis and treatment of these patients. Methods: A total of 4 813 lung biopsy specimens (including 1 935 consultation cases) collected at the Department of Pathology, Nanjing Drum Tower Hospital, Nanjing, China from January 1st, 2017 to December 31th, 2019 were retrospectively analyzed. Among them, 126 cases of occupational lung diseases were confirmed with clinical-radiological-pathological diagnosis. Special staining, PCR and scanning electron microscopy were also used to rule out the major differential diagnoses. Results: The 126 patients with occupational lung diseases included 102 males and 24 females. All of them had a history of exposure to occupational risk factor(s). Morphologically, 68.3% (86/126) of the cases mainly showed pulmonary fibrotic nodules, dust plaque formation or carbon end deposition in pulmonary parenchyma. 16.7% (21/126) of the cases mainly showed welding smoke particle deposition in the alveolar cavity and lung interstitium while 15.1% (19/126) of the cases showed granulomas with fibrous tissue hyperplasia, alveolar protein deposition or giant cell interstitial pneumonia. The qualitative and semi-quantitative analyses of residual dust components in the lung under scanning electron microscope were helpful for the diagnosis of welder's pneumoconiosis and hard metal lung disease. Conclusions: The morphological characteristics of lung biopsy tissue are important reference basis for the clinicopathological diagnosis and differential diagnosis of occupational lung diseases. Recognizing the characteristic morphology and proper use of auxiliary examination are the key to an accurate diagnosis of occupational lung diseases on biopsy specimens.
Male ; Female ; Humans ; Retrospective Studies ; Pneumoconiosis/pathology* ; Lung/pathology* ; Dust ; Pneumonia, Viral/pathology* ; Biopsy

Technical Specifications for Occupational Health Surveillance (GBZ 188-2014) is an important basis for judging suspected occupational diseases and occupational contraindications. There are crossing over or overlap between occupational contraindications and diagnostic criteria of poisoning damage. Occupational contraindications have different meanings with the degree and range of common diseases or symptoms and the frequency of physical examination during employment conflicts with the current standard. Based on the practice of occupational health examination in a large population, the present study analyzed relevant articles and put forward some suggestions for revision, in combination with clinical medicine, occupational health standards, and diagnostic standards of occupational diseases. The modification could provide a reference for the revision of Technical Specifications for Occupational Health Surveillance and the practice of occupational health examination.
Humans ; Occupational Health ; Occupational Diseases ; Occupational Health Services ; Workplace ; Reference Standards ; Occupational Medicine

Fatty acids (FA) are widely used as feed stocks for the production of cosmetics, personal hygiene products, lubricants and biofuels. Ogataea polymorpha is considered as an ideal chassis for bio-manufacturing, due to its outstanding characteristics such as methylotroph, thermal-tolerance and wide substrate spectrum. In this study, we harnessed O. polymorpha for overproduction of fatty acids by engineering its fatty acid metabolism and optimizing the fermentation process. The engineered strain produced 1.86 g/L FAs under the optimized shake-flask conditions (37℃, pH 6.4, a C/N ratio of 120 and an OD₆₀₀ of seed culture of 6-8). The fed-batch fermentation process was further optimized by using a dissolved oxygen (DO) control strategy. The C/N ratio of initial medium was 17.5, and the glucose medium with a C/N ratio of 120 was fed when the DO was higher than 30%. This operation resulted in a titer of 18.0 g/L FA, indicating the potential of using O. polymorpha as an efficient cell factory for the production of FA.
Culture Media ; Fatty Acids ; Fermentation ; Metabolic Engineering ; Saccharomycetales/metabolism*

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

Oligodontia is the congenital absence of six or more teeth and comprises the more severe forms of tooth agenesis. Many genes have been implicated in the etiology of tooth agenesis, which is highly variable in its clinical presentation. The purpose of this study was to identify associations between genetic mutations and clinical features of oligodontia patients. An online systematic search of papers published from January 1992 to June 2021 identified 381 oligodontia cases meeting the eligibility criteria of causative gene mutation, phenotype description, and radiographic records. Additionally, ten families with oligodontia were recruited and their genetic etiologies were determined by whole-exome sequence analyses. We identified a novel mutation in WNT10A (c.99_105dup) and eight previously reported mutations in WNT10A (c.433 G > A; c.682 T > A; c.318 C > G; c.511.C > T; c.321 C > A), EDAR (c.581 C > T), and LRP6 (c.1003 C > T, c.2747 G > T). Collectively, 20 different causative genes were implicated among those 393 cases with oligodontia. For each causative gene, the mean number of missing teeth per case and the frequency of teeth missing at each position were calculated. Genotype-phenotype correlation analysis indicated that molars agenesis is more likely linked to PAX9 mutations, mandibular first premolar agenesis is least associated with PAX9 mutations. Mandibular incisors and maxillary lateral incisor agenesis are most closely linked to EDA mutations.
Humans ; Phenotype ; Wnt Proteins

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.