The 2019 coronavirus disease (COVID-19) is a highly contagious and deadly disease. The elderly people are often accompanied by chronic inflammation and immunodeficiency, showing a frail state. The strength, endurance, and physiological function of the elderly are significantly decreased, and the ability to deal with stress response is weakened. They are the high-risk group that suffering from COVID-19, and rapidly developing to critical illness. Several recent studies suggest that the incidence rate of COVID-19 in elderly patients with frailty is high. Early assessment, detection, and effective intervention of frailty in COVID-19 patients are conducive to significantly improve the quality of life and improve prognosis. However, there are insufficient understanding and standards for the current evaluation methods, pathogenesis and intervention measures for COVID-19 combined with frailty. This study reviews the progress of the research on the potential pathogenesis, evaluation methods and intervention measures of the elderly COVID-19 patients with frailty, which provides a reference for scientific and reasonable comprehensive diagnosis and treatment in clinical.

Background: Malnutrition and comorbidity are two common geriatric syndromes. The pathology of pneumonia is multifactorial, making its diagnosis and management a great challenge. Hospital-acquired pneumonia (HAP) and community-acquired pneumonia (CAP) are two main types of pneumonia. However, the effect of geriatric syndromes on pneumonia and its prognosis have not been clearly explored.Methods: We collected the relevant electronic data of inpatients aged over 65 years and diagnosed with pneumonia in the Geriatrics Department Building of the First Affiliated Hospital with Nanjing Medical University between December 2018 and December 2019, and further divided them into HAP group and CAP group. The correlations of age, age-adjusted Charlson Comorbidity Index (aCCI), basic diseases and nutritional indexes (i.e., albumin, electrolyte, hemoglobin) with pneumonia and prognosis were analyzed. We analyzed the associations between infection prognosis/infection level and age, nutritional status, aCCI and underlying diseases, using linear regression model. The box plot was applied to present infection outcome, and the nomogram was built for predicting infection outcomes. We utilized the heat map to show the associations between nutritional status and infection level/outcome in all infected patients, HAP, and CAP.Results: The final study comprised samples of 669 pneumonia patients divided into HAP group (n = 517) and CAP group (n = 152). In all patients, the infection outcome was negatively correlated with age (P = 0.013). The level of albumin was negatively correlated with infection prognosis in all patients (P = 0.03), and negatively correlated with neutrophil count and CRP (P = 0.008, P < 0.001). ACCI was positively correlated with CRP (P = 0.003). The prognosis was negatively associated with age and albumin level. In the patients with basic dementia/Alzheimer's disease and chronic obstructive pulmonary disease/asthma, the prognosis was worse.Conclusion: There was a correlation between poor nutritional status-related indexes and inflammatory indexes. A poor nutritional status might predict a high risk of pneumonia in elderly adults. Advanced age and comorbidities were risk factors for the occurrence and poor prognosis of pneumonia. Therefore, comorbidities should be well-treated in the elderly with pneumonia.

SH3 and multiple ankyrin repeat domains 1 (SHANK1) is a scaffold protein, plays an important role in the normal function of neuron system. It has recently been shown to be a potential oncogene. In the present study, we report that the expression of SHANK1 is upregulated in non-small cell lung cancer (NSCLC), and is correlated with clinic pathological characteristics of NSCLC. Moreover, SHANK1 overexpression enhances the proliferation, migration and invasion of NSCLC cells. Mouse cell-derived xenograft model also confirmed the effects of SHANK1 on tumor growth in vivo. Furthermore, we found that SHANK1 increases the protein degradation of Klotho (KL), an important tumor suppressor, through ubiquitination-dependent pathway. In particular, we report discovery of KL as a SHANK1-interacting protein that acts as a new substate of the E3 ubiquitin ligase MDM2. SHANK1 can form a complex with KL and MDM2 and enhance the interaction between KL and MDM2. Our findings reveal an important oncogenic role and mechanism of SHANK1, suggesting SHANK1 can be a potential therapeutic target in NSCLC.

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Lung cancer has one of the highest morbidity and mortality rates in the world. Frailty is common in many countries and is a major cause of premature functional decline and premature death in older adults, and may affect the treatment and prognosis of lung cancer patients. To investigate the predictive value of frailty at diagnosis on all-cause mortality in lung cancer patients, this study retrospectively collected and analysed clinical information on lung cancer patients from 2015–2018. A total of 1667 patients with primary lung cancer were finally included in this study. The median follow-up time of patients was 650 (493, 1001.5) days. A total of 297(17.8%) patients had FI-LAB(the frailty index based on laboratory test) status of frail at the moment of diagnosis and the all-cause mortality rate for all patients was 61.1% (1018/1667). In a univariate model, we found a higher total all-cause mortality risk in frail patients (frail vs. robust, HR(hazard ratio) = 1.616, 95% CI(confidence interval) = 1.349,1.936), after balancing other variables combined into model 1 to model 6. The results were analyzed visually using ROC(Receiver operating characteristic) curves with nomogram and the AUC values ranged from 0.866–0.874. The final inclusion of age, TNM stage, CCI(Charlson comorbidity index) score, surgery history and chemotherapy into a multifactorial model balanced the predictive power of frailty grading on all-cause mortality. The study showed that for lung cancer patients, the higher the level of frailty at diagnosis, the higher the risk of all-cause mortality. In the context of widespread electronic medical records in hospitals, it is convenient and feasible to use FI-LAB to assess the prognosis of lung cancer patients.