2019 novel coronavirus (2019-nCoV) is widespread in China and other countries. The target of 2019-nCoV and severe acute respiratory syndrome coronavirus (SARS-CoV) is angiotensin-converting enzyme 2 (ACE2) positive cells. ACE2 is present in the salivary gland duct epithelium, and thus it could be the target of 2019-nCoV and SARS-CoV. SARS-CoV-related animal model experiments show that it can infect the epithelial cells on the salivary gland duct in Chinese rhesus macaques by targeting ACE2. Clinical studies confirmed that 2019-nCoV and SARS-CoV could be detected in saliva of human patients. We hypothesize that the infection of 2019-nCoV and SARS-CoV will lead to inflammatory pathological lesions in patients' target organs, and possibly inflammatory lesions in salivary glands. 2019-nCoV may cause acute sialoadenitis in the acute phase of infection. After the acute phase, chronic sialoadenitis may be caused by fibrosis repairment. Although there was no direct evidence to prove this, the available indirect evidence indicates a high probability of our hypothesis.

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is primarily transmitted through droplets. All human tissues with the angiotensin‐converting enzyme 2 (ACE2) and transmembrane protease serines 2 (TRMPRSS2) are potential targets of SARS‐CoV‐2. The role of saliva in SARS‐CoV‐2 transmission remains obscure. In this study, we attempted to reveal ACE2 and TRMPRSS2 protein expression in human parotid, submandibular, and sublingual glands (three major salivary glands). Then, the binding function of spike protein to ACE2 in three major salivary glands was detected. The expression of ACE2 and TMPRSS2 in human saliva from parotid glands were both examined. Exogenous recombined ACE2 and TMPRSS2 anchoring and fusing to oral mucosal epithelial cells in vitro were also unraveled. ACE2 and TMPRSS2 were found mainly to be expressed in the cytomembrane and cytoplasm of epithelial cells in the serous acinus cells in parotid and submandibular glands. Our research also discovered that the spike protein of SARS‐CoV‐2 binds to ACE2 in salivary glands in vitro. Furthermore, exogenous ACE2 and TMPRSS2 can anchor and fuse to oral mucosa in vitro. Thus, the expression of ACE2 and TMPRSS2 in human saliva might have implications for SARS‐CoV‐2 infection.

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Background Endoplasmic reticulum (ER) stress has been found to foster the escape of cancer cells from immune surveillance and upregulate PD-L1 expression. However, the underlying mechanisms are unknown. Methods While analyzing the protein levels using immunofluorescence and Western blotting, the RNA levels were measured using qRT-PCR. Ten injection of exosomes into six-week-old nude mice was made through the tail vein once every other day in total. Results The expression of certain ER stress markers such as PERK (PKR-like endoplasmic reticulum kinase), ATF6 (activating transcription factor 6), and GRP78 (glucose-regulated protein 78), was found to be upregulated in the oral squamous cell carcinoma (OSCC) tissues and related to poor overall survival. There is a positive relationship between the extent of ER stress-related proteins and a cluster of PD-L1 expression and macrophage infiltration among the OSCC tissues. Further, incubation with exosomes derived from ER-stressed HN4 cells (Exo-ER) was found to upregulate PD-L1 extents in macrophages in vitro and in vivo, and macrophage polarization toward the M2 subtype was promoted by upregulating PD-L1. Conclusions ER stress causes OSCC cells to secrete exosomal PD-L1 and upregulates PD-L1 expression in macrophages to drive M2 macrophage polarization. The delineation of a new exosome-modulated mechanism was made for OSCC–macrophage crosstalk driving tumor development and to be examined for its therapeutic use. Graphical abstract Exosomal PD-L1 secreted by ER-stressed OSCC cells promoted M2 macrophage polarization.

Certain high-risk factors related to the death of COVID-19 have been reported, however, there were few studies on a death prediction model. This study was conducted to delineate the clinical characteristics of patients with coronavirus disease 2019 (covid-19) of different degree and establish a death prediction model. In this multi-centered, retrospective, observational study, we enrolled 523 COVID-19 cases discharged before February 20, 2020 in Henan Province, China, compared clinical data, screened for high-risk fatal factors, built a death prediction model and validated the model in 429 mild cases, six fatal cases discharged after February 16, 2020 from Henan and 14 cases from Wuhan. Out of the 523 cases, 429 were mild, 78 severe survivors, 16 non-survivors. The non-survivors with median age 71 were older and had more comorbidities than the mild and severe survivors. Non-survivors had a relatively delay in hospitalization, with higher white blood cell count, neutrophil percentage, D-dimer, LDH, BNP, and PCT levels and lower proportion of eosinophils, lymphocytes and albumin. Discriminative models were constructed by using random forest with 16 non-survivors and 78 severe survivors. Age was the leading risk factors for poor prognosis, with AUC of 0.907 (95% CI 0.831-0.983). Mixed model constructed with combination of age, demographics, symptoms, and laboratory findings at admission had better performance (p = 0.021) with a generalized AUC of 0.9852 (95% CI 0.961-1). We chose 0.441 as death prediction threshold (with 0.85 sensitivity and 0.987 specificity) and validated the model in 429 mild cases, six fatal cases discharged after February 16, 2020 from Henan and 14 cases from Wuhan successfully. Mixed model can accurately predict clinical outcomes of COVID-19 patients.