S evere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus that causes coronavirus disease 2019 in human beings, has caused a serious public health issue. 1 Attention to pancreatic injury is lacking, which may impact patients' prognosis. In this study, we explored the expression and distribution of angiotensin-converting enzyme 2 (ACE2), the receptor of SARS-CoV-2, in the pancreas. Combined with clinical data, we showed that pancreatic injury can occur in some COVID-19 patients. MethodsA public database was used to explore the expression and distribution of ACE2 in normal pancreases. We also retrospectively analyzed patients diagnosed with COVID-19 from January 1, 2020, to February 15, 2020, in Wuhan Tongji Hospital and Wuhan Jin Yin-tan Hospital. We collected hospital admission data, laboratory tests, and imaging tests from clinical electronic medical records. Severe COVID-19 was defined when patients had 1 of the following criteria: (1) shortness of breath and respiratory frequency !30/min; (2) finger pulse oximeter oxygen saturation at rest of 93% or less; or (3) oxygenation index of 300 mm Hg or less. More details about clinical data and public data set analysis are described in the Supplementary Methods.

SUMMARY Genetic screening identifies the atypical tetraspanin TM4SF1 as a strong mediator of metastatic reactivation of breast cancer. Intriguingly, TM4SF1 couples the collagen receptor tyrosine kinase DDR1 to the cortical adaptor syntenin 2 and, hence, to PKCα. The latter kinase phosphorylates and activates JAK2, leading to the activation of STAT3. This non-canonical mechanism of signaling induces the expression of SOX2 and NANOG, sustains the manifestation of cancer stem cell traits, and drives metastatic reactivation in the lung, bone, and brain. Bioinformatic analyses and pathological studies corroborate the clinical relevance of these findings. We conclude that non-canonical DDR1 signaling enables breast cancer cells to exploit the ubiquitous interstitial matrix component collagen I to undergo metastatic reactivation in multiple target organs.

The ongoing outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) started in the end of 2019 in China has triggered a global public health crisis. Previous studies have shown that SARS-CoV-2 infects cells by binding angiotensin-converting enzyme 2 (ACE2), which is the same as SARS-CoV. The expression and distribution of ACE2 in the pancreas are unknown. At the same time, the injury of pancreas after SARS-CoV-2 infection has not been concerned. Here, we collected public datasets (bulk RNA-seq and single-cell RNA-seq) to indicate the expression and the distribution of ACE2 in pancreas (in both exocrine glands and islets). And further, clinical data including mild and severe patients with COVID-19 demonstrated there existed mild pancreatitis. In the 67 severe cases, 11 patients (16.41%) showed elevated levels of both amylase and lipase, and 5 patients (7.46%) showed imaging alterations. Only one patient (1.85%) showed elevated levels of both amylase and lipase in 54 mild cases, without imaging changes. Our study revealed the phenomenon and possible cause of mild pancreatic injury in patients with COVID-19. This suggests that pancreatitis after SARS-CoV-2 infection should also be paid attention in clinical work.

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Soybean is an important crop providing edible oil and protein source. Soybean oil and protein contents are quantitatively inherited and significantly affected by environmental factors. In this study, meta-analysis was conducted based on soybean physical maps to integrate quantitative trait loci (QTLs) from multiple experiments in different environments. Meta-QTLs for seed oil, fatty acid composition, and protein were identified. Of them, 11 meta-QTLs were located on hot regions for both seed oil and protein. Next, we selected 4 chromosome segment substitution lines with different seed oil and protein contents to characterize their 3 years of phenotype selection in the field. Using strand-specific RNA-sequencing analysis, we profile the time-course transcriptome patterns of soybean seeds at early maturity, middle maturity, and dry seed stages. Pairwise comparison and K-means clustering analysis revealed 7,482 differentially expressed genes and 45 expression patterns clusters. Weighted gene coexpression network analysis uncovered 46 modules of gene expression patterns. The 2 most significant coexpression networks were visualized, and 7 hub genes were identified that were involved in soybean oil and seed storage protein accumulation processes. Our results provided a transcriptome dataset for soybean seed development, and the candidate hub genes represent a foundation for further research.

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