Mesenchymal stem cells (MSCs) can sense and convert mechanical stimuli signals into a chemical response. Integrins are involved in the mechanotransduction from inside to outside and from outside to inside, and ultimately affect the fate of MSCs responding to different mechanical signals. Different integrins participate in different signaling pathways to regulate MSCs multi-differentiation. In this review, we summarize the latest advances in the effects of mechanical signals on the differentiation of MSCs, the importance of integrins in mechanotransduction, the relationship between integrin heterodimers and different mechanical signals, and the interaction among mechanical signals. We put forward our views on the prospect and challenges of developing mechanical biology in tissue engineering and regenerative medicine. Graphical abstract

Toll-like receptors (TLRs) are key sensors that recognize the pathogen-associated molecular patterns (PAMPs) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to activate innate immune response to clear the invading virus. However, dysregulated immune responses may elicit the overproduction of proinflammatory cytokines and chemokines, resulting in the enhancement of immune-mediated pathology. Therefore, a proper understanding of the interaction between SARS-CoV-2 and TLR-induced immune responses is very important for the development of effective preventive and therapeutic strategies. In this review, we discuss the recognition of SARS-CoV-2 components by TLRs and the downstream signaling pathways that are activated, as well as the dual role of TLRs in regulating antiviral effects and excessive inflammatory responses in patients with coronavirus disease 2019 (COVID-19). In addition, this article describes recent progress in the development of TLR immunomodulators including the agonists and antagonists, as vaccine adjuvants or agents used to treat hyperinflammatory responses during SARS-CoV-2 infection.

A large number of studies have shown that patients with Coronavirus disease 2019 (COVID-19) have different degrees of liver injury. However, the mechanisms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) invasion into the liver are still not fully understood. This review mainly summarizes the recently published works on the abnormal liver biochemical indicators and the mechanism of viral invasion with liver injury in COVID-19 patients. Generally, SARS-CoV-2 infection of the liver was caused by blood circulation or retrograde infection of digestive tract, which led to the liver injury through direct cytopathic effect induced by virus or immunopathological effect caused by excessive inflammation. Besides these, hypoxia, endothelial injury and drug-induced jury were also the main reasons of liver injury in COVID-19 patients. In the liver function indicators, elevated alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, gamma-glutamyl transpeptidase, and lactate dehydrogenase levels with reduced albumin levels were observed in COVID-19 patients.

To explore the diagnostic models of Crohn’s disease (CD), Intestinal tuberculosis (ITB) and the differential diagnostic model between CD and ITB by analyzing serum proteome profiles. Serum proteome profiles from 30 CD patients, 21 ITB patients and 30 healthy controls (HCs) were analyzed by using weak cationic magnetic beads combined with MALDI-TOF-MS technique to detect the differentially expressed proteins of serum samples. Three groups were made and compared accordingly: group of CD patients and HCs, group of ITB patients and HCs, group of CD patients and ITB patients. Wilcoxon rank sum test was used to screen the ten most differentiated protein peaks (P < 0.05). Genetic algorithm combining with support vector machine (SVM) was utilized to establish the optimal diagnostic models for CD, ITB and the optimal differential diagnostic model between CD and ITB. The predictive effects of these models were evaluated by Leave one out (LOO) cross validation method. There were 236 protein peaks differently expressed between group of CD patients and HCs, 305 protein peaks differently expressed between group of ITB patients and HCs, 332 protein peaks differently expressed between group of CD patients and ITB patients. Ten most differentially expressed peaks were screened out between three groups respectively (P < 0.05) to establish diagnostic models and differential diagnostic model. A diagnostic model comprising of four protein peaks (M/Z 4964, 3029, 2833, 2900) can well distinguish CD patients and HCs, with a specificity and sensitivity of 96.7% and 96.7% respectively. A diagnostic model comprising four protein peaks (M/Z 3030, 2105, 2545, 4210) can well distinguish ITB patients and HCs, with a specificity and sensitivity of 93.3% and 95.2% respectively. A differential diagnostic model comprising three potential biomarkers protein peaks (M/Z 4267, 4223, 1541) can well distinguish CD patients and ITB patients, with a specificity and sensitivity of 76.2% and 80.0% respectively. Among the eleven protein peaks from the diagnostic models and differential diagnostic model, two have been successfully purified and identified, Those two peaks were M/Z 2900 from the diagnostic model between CD and HCs and M/Z 1541 from the differential diagnostic model between CD and ITB. M/Z 2900 was identified as appetite peptide, M/Z 1541 was identified as Lysyl oxidase-like 2 (LOXL-2). The differently expressed protein peaks analyzed by serum proteome with weak cationic magnetic beads combined MALDI-TOF-MS technique can effectively distinguish CD patients and HCs, ITB patients and HCs, CD patients and ITB patients. The diagnostic model between CD patients and HCs consisting of four protein peaks (M/Z 4964, 3029, 2833, 2900), the diagnostic model between ITB patients and HCs comprising four protein peaks (M/Z 3030, 2105, 2545, 4210) and the differential diagnostic model between CD patients and ITB patients comprising three protein peaks (M/Z 4267, 4223, 1541) had high specificity and sensitivity and can contribute to diagnoses of CD, ITB and the differential diagnosis between CD and ITB. Two proteins from the diagnostic model of CD and the differential diagnostic model between CD and ITB were identified. Further experiments are required using a larger cohort of samples.

Background: Clinical recovery does not mean full recovery. It is necessary to explore the aftereffects of COVID‐19 in patients and compare the laboratory features of COVID‐19 and other viral pneumonias in the recovery stages.Methods: Forty‐seven cases of COVID‐19 and 45 cases of other viral pneumonias (control) were included in this study. The laboratory parameters were compared between COVID‐19 and control patients as well as severe and moderate COVID‐19 patients from the clinical recovery stage to the 4 weeks postdischarge recovery stage.Results: A higher RDW‐CV level and neutrophil percentage and lower levels of total proteins, lymphocytes, eosinophils, and MCH were found in COVID‐19 patients compared with those in controls from the clinical recovery to the postdischarge recovery stages. Further analysis showed that decreases in lymphocytes, total proteins, and SOD and elevations in neutrophils, FDP, CRP, and ESR were more common in severe than moderate cases of COVID‐19 during hospitalization; however, differences in these indicators, except total proteins, were not observed in the postdischarge recovery stages. Additionally, only 76.9% of COVID‐19 patients were positive for IgG antibodies against SARS‐CoV‐2 in the convalescence stage, and one patient that was negative for specific IgG was reinfected.Conclusions: This study demonstrated that patients recovering from COVID‐19 might need better care than that patients with other viral pneumonias due to the possibility of having poor immunity and nutritional conditions. These findings provide new insights to improve the understanding of COVID‐19 and improve care for patients affected by these kinds of pandemics in the future.