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Accurate prediction of fine particulate matter (PM2.5) concentration is crucial for improving environmental conditions and effectively controlling air pollution. However, some existing studies could ignore the nonlinearity and spatial correlation of time series data observed from stations, and it is difficult to avoid the redundancy between features during feature selection. To further improve the accuracy, this study proposes a hybrid model based on empirical mode decomposition (EMD), minimal-redundancy-maximal-relevance (mRMR), and geographically weighted neural network (GWNN) for hourly PM2.5 concentration prediction, named EMD-mRMR-GWNN. Firstly, the original PM2.5 concentration sequence with distinct nonlinearity and non-stationarity is decomposed into multiple intrinsic mode functions (IMFs) and a residual component using EMD. IMFs are further classified and reconstructed into high-frequency and low-frequency components using the one-sample t-test. Secondly, the optimal feature subset is selected from high-frequency and low-frequency components with mRMR for the prediction model, thus holding the correlation between features and the target variable and reducing the redundancy among features. Thirdly, the residual component is predicted with the simple moving average (SMA) due to its strong trend and autocorrelation, and GWNN is used to predict the high-frequency and low-frequency components. The final prediction of the PM2.5 concentration value is calculated by an artificial neural network (ANN) composed of the predictive values of each component. PM2.5 concentration prediction experiments in three representational cities, such as Beijing, Wuhan, and Kunming were carried out. The proposed model achieved high accuracy with a coefficient of determination greater than 0.92 in forecasting PM2.5 concentration for the next 1 h. We compared this model with four baseline models in forecasting PM2.5 concentration for the next few hours and found it performed the best in PM2.5 concentration prediction. The experimental results indicated the proposed model can improve prediction accuracy. [ABSTRACT FROM AUTHOR]

At the end of 2019 Wuhan witnessed an outbreak of "atypical pneumonia" that later developed into a global pandemic. Metagenomic sequencing rapidly revealed the causative agent of this outbreak to be a novel coronavirus denoted SARS-CoV-2. To provide a snapshot of the pathogens in pneumonia-associated respiratory samples from Wuhan prior to the emergence of SARS-CoV-2, we collected bronchoalveolar lavage fluid samples from 408 patients presenting with pneumonia and acute respiratory infections at the Central Hospital of Wuhan between 2016 and 2017. Unbiased total RNA sequencing was performed to reveal their "total infectome", including viruses, bacteria and fungi. We identified 35 pathogen species, comprising 13 RNA viruses, 3 DNA viruses, 16 bacteria and 3 fungi, often at high abundance and including multiple co-infections (13.5%). SARS-CoV-2 was not present. These data depict a stable core infectome comprising common respiratory pathogens such as rhinoviruses and influenza viruses, an atypical respiratory virus (EV-D68), and a single case of a sporadic zoonotic pathogen–Chlamydia psittaci. Samples from patients experiencing respiratory disease on average had higher pathogen abundance than healthy controls. Phylogenetic analyses of individual pathogens revealed multiple origins and global transmission histories, highlighting the connectedness of the Wuhan population. This study provides a comprehensive overview of the pathogens associated with acute respiratory infections and pneumonia, which were more diverse and complex than obtained using targeted PCR or qPCR approaches. These data also suggest that SARS-CoV-2 or closely related viruses were absent from Wuhan in 2016–2017. Author summary: Acute respiratory infections and pneumonia are a significant public health concern on a global scale. This was brought sharply into focus by the emergence of COVID-19 at the end of 2019 in Wuhan, China. Far less is known, however, about the total "infectomes" associated with respiratory infection and pneumonia: that is, all the viruses, bacteria and fungi that might be associated with these important human diseases. Herein, we describe total infectomes in bronchoalveolar lavage fluid samples taken from 408 patients presenting with pneumonia and acute respiratory infection in a single hospital in Wuhan between 2016 and 2017. From these samples we identified 35 pathogen species, comprising 13 RNA viruses, 3 DNA viruses, 16 bacteria and 3 fungi, often at high abundance and including multiple co-infections. We found no evidence for SARS-CoV-2. These data reveal a stable core infectome comprising common respiratory pathogens as well as their history of global transmission. [ABSTRACT FROM AUTHOR]

Over the last several decades, no emerging virus has had a profound impact on the world as the SARS-CoV-2 that emerged at the end of 2019 has done. To know where severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated from and how it jumped into human population, we immediately started a surveillance investigation in wild mammals in and around Wuhan when we determined the agent. Herein, coronaviruses were screened in the lung, liver, and intestinal tissue samples from fifteen raccoon dogs, seven Siberian weasels, three hog badgers, and three Reeves's muntjacs collected in Wuhan and 334 bats collected around Wuhan. Consequently, eight alphacoronaviruses were identified in raccoon dogs, while nine betacoronaviruses were found in bats. Notably, the newly discovered alphacoronaviruses shared a high whole-genome sequence similarity (97.9 per cent) with the canine coronavirus (CCoV) strain 2020/7 sampled from domestic dog in the UK. Some betacoronaviruses identified here were closely related to previously known bat SARS-CoV-related viruses sampled from Hubei province and its neighbors, while the remaining betacoronaviruses exhibited a close evolutionary relationship with SARS-CoV-related bat viruses in the RdRp gene tree and clustered together with SARS-CoV-2-related bat coronaviruses in the M, N and S gene trees, but with relatively low similarity. Additionally, these newly discovered betacoronaviruses seem unlikely to bind angiotensin-converting enzyme 2 because of the deletions in the two key regions of their receptor-binding motifs. Finally, we did not find SARS-CoV-2 or its progenitor virus in these animal samples. Due to the high circulation of CCoVs in raccoon dogs in Wuhan, more scientific efforts are warranted to better understand their diversity and evolution in China and the possibility of a potential human agent. [ABSTRACT FROM AUTHOR]

Background: As of June 1, 2020, coronavirus disease 2019 (COVID-19) has caused more than 6,000,000 infected persons and 360,000 deaths globally. Previous studies revealed pregnant women with COVID-19 had similar clinical manifestations to nonpregnant women. However, little is known about the outcome of neonates born to infected women.Methods and Findings: In this retrospective study, we studied 29 pregnant women with COVID-19 infection delivered in 2 designated general hospitals in Wuhan, China between January 30 and March 10, 2020, and 30 neonates (1 set of twins). Maternal demographic characteristics, delivery course, symptoms, and laboratory tests from hospital records were extracted. Neonates were hospitalized if they had symptoms (5 cases) or their guardians agreed to a hospitalized quarantine (13 cases), whereas symptom-free neonates also could be discharged after birth and followed up through telephone (12 cases). For hospitalized neonates, laboratory test results and chest X-ray or computed tomography (CT) were extracted from hospital records. The presence of antibody of SARS-CoV-2 was assessed in the serum of 4 neonates. Among 29 pregnant COVID-19-infected women (13 confirmed and 16 clinical diagnosed), the majority had higher education (56.6%), half were employed (51.7%), and their mean age was 29 years. Fourteen women experienced mild symptoms including fever (8), cough (9), shortness of breath (3), diarrhea (2), vomiting (1), and 15 were symptom-free. Eleven of 29 women had pregnancy complications, and 27 elected to have a cesarean section delivery. Of 30 neonates, 18 were admitted to Wuhan Children's Hospital for quarantine and care, whereas the other 12 neonates discharged after birth without any symptoms and had normal follow-up. Five hospitalized neonates were diagnosed as COVID-19 infection (2 confirmed and 3 suspected). In addition, 12 of 13 other hospitalized neonates presented with radiological features for pneumonia through X-ray or CT screening, 1 with occasional cough and the others without associated symptoms. SARS-CoV-2 specific serum immunoglobulin M (IgM) and immunoglobulin G (IgG) were measured in 4 neonates and 2 were positive. The limited sample size limited statistical comparison between groups.Conclusions: In this study, we observed COVID-19 or radiological features of pneumonia in some, but not all, neonates born to women with COVID-19 infection. These findings suggest that intrauterine or intrapartum transmission is possible and warrants clinical caution and further investigation.Trial Registration: Chinese Clinical Trial Registry, ChiCTR2000031954 (Maternal and Perinatal Outcomes of Women with coronavirus disease 2019 (COVID-19): a multicenter retrospective cohort study). [ABSTRACT FROM AUTHOR]

A continuing outbreak of pneumonia associated with the 2019 novel coronavirus (2019-nCoV) was initially described in Wuhan, China in December 2019. Weak and elderly individuals, and those with chronic diseases such as hematological malignancies are prone to develop severe pneumonia. The humoral immunity of patients with multiple myeloma is prevalently low, and their inferior immunity further deteriorates during chemotherapy. For patients with onco-hematological malignancies infected with 2019-nCoV during the first chemotherapy cycle, the clinical treatment experience is lacking. The present study is a report of a 61-year-old patient newly diagnosed with multiple myeloma in the key 2019-nCoV outbreak area, who suffered severe 2019-nCoV pneumonia during the first chemotherapy cycle. The present case report demonstrated that a rapidly progressive and severe form of pneumonia was a specific clinical feature of COVID-19, especially in immunocompromised patients with cancer. The treatment strategy combining timely suspending chemotherapy, early intervention using intravenous immunoglobulin, interferon α inhalation and oral antiviral drugs was effective. Therefore, in the pandemic environment, it is strongly recommend that the risk of 2019-nCoV infection is assessed prior to chemotherapy. [ABSTRACT FROM AUTHOR]

Background: With the widespread outbreak of novel coronavirus diseases 2019(COVID-19), more and more death cases were reported, however, limited data are available for the patients who died. We aimed to explore the clinical characteristics of deaths with COVID-19 pneumonia.Methods: We abstracted and analyzed epidemiological, demographic, clinical, and laboratory data from 83 death cases with COVID-19 pneumonia in East Hospital of Wuhan University Renmin Hospital, between January 26, 2020, and February 28, 2020.Results: Of the 83 deaths, none was the medical staff. The mean age was 71.8 years (SD 13.2; range, 34-97 years) and 53(63.9%) were male. The median from onset to admission was 10 days (IQR 7-14: range, 2-43 days), to death was 17 days (IQR 14-21: range, 6-54 days). Most deaths (66[80%]) had underlying comorbid diseases, the most of which was hypertension [47(57%)]. The main initial symptoms of these 83 deaths were shortness of breath(98.8%), fever(94%), and myalgia or fatigue(90.4%). Laboratory analyses showed the lymphocytopenia in 69(83%) deaths, hypoalbuminemia in 77(93%) deaths, the elevation of lactate dehydrogenase in 79(95%) deaths, procalcitonin in 69(83%) deaths and C-reactive protein in 79(95%) deaths. All 83 patients received antiviral treatment, 81(97.6%) deaths received antibiotic therapy, 54(65.1%) deaths received glucocorticoid therapy, and 20(24.1%) patients received invasive mechanical ventilation.Conclusion: Most of the deaths with COVID-19 pneumonia were elderly patients with underlying comorbid diseases, especially those over 70 years of age. The time of death after the onset of the disease was mostly 15-21 days. More care should be given to the elderly in further prevention and control strategies of COVID-19. [ABSTRACT FROM AUTHOR]