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Introduction: Center‐based rehabilitation is limited by COVID‐19 infectivity and social distancing policy. We hypothesized that discharged patients benefit from 8‐week home‐based tele‐rehabilitation (tele‐PR) using mobile phones and low‐cost instruments. Methods: The TERCOV (Tele‐rehabilitation in COVID‐19 survivors) is an investigator‐initiated, prospective, multi‐center, real‐world study. After proper assessment, 186 discharge patients received tele‐PR by smartphone, including breathing exercise, respiratory muscle training, aerobic exercise, and resistance training. Physicians, physiotherapists, and nurses provided guidance through smartphone applications. The primary outcome was six‐minute walk distance (6MWD). The secondary outcomes included hand grip, short physical performance battery, maximal inspiratory pressure, maximal expiratory pressure, self‐rating anxiety/depression scale (SAS/SDS), 36‐item short‐form health survey (SF‐36) and international physical activity questionnaire. Results: Dyspnea subgroups were more functionally impaired. After tele‐PR, improvements were observed in exercise capacity(∆6MWD: 16.80 m, 95% CI 1.18–32.42, p < 0.0001), limb muscle function (∆SPPB 0.25 points, 95% CI 0.05–0.46), respiratory muscle strength (∆MIP 16.50 cm H2O, 95% CI 9.22–23.78, p < 0.0001; ∆MEP: 12.09 cm H2O, 95% CI 3.48–20.70, p = 0.0002), health‐related quality of life (∆SF‐36 49.85, 95% CI: 21.01–78.69, p < 0.0001), physical activity(∆HEPA 13.01%, p = 0.0029). Anxiety reduced in patients with mMRC ≥ 2 (∆SAS = −4.19 points, CI −8.16 to −0.22, p = 0.03). Greater change was seen in dyspnea patients. Implications on Physiotherapy Practice: Supervised/semi‐supervised tele‐PR is a promising option during the pandemic. Patients with Dyspnea benefit more. [ABSTRACT FROM AUTHOR]

Objective: To determine which early‐stage variables best predicted the deterioration of coronavirus disease 2019 (COVID‐19) among community‐isolated people infected with severe acute respiratory syndrome coronavirus 2 and to test the performance of prediction using only inexpensive‐to‐measure variables. Methods: Medical records of 3145 people isolated in two Fangcang shelter hospitals (large‐scale community isolation centers) from February to March 2020 were accessed. Two complementary methods—machine learning algorithms and competing risk survival analyses—were used to test potential predictors, including age, gender, severity upon admission, symptoms (general symptoms, respiratory symptoms, and gastrointestinal symptoms), computed tomography (CT) signs, and comorbid chronic diseases. All variables were measured upon (or shortly after) admission. The outcome was deterioration versus recovery of COVID‐19. Results: More than a quarter of the 3145 people did not present any symptoms, while one‐third ended isolation due to deterioration. Machine learning models identified moderate severity upon admission, old age, and CT ground‐glass opacity as the most important predictors of deterioration. Removing CT signs did not degrade the performance of models. Competing risk models identified age ≥ 35 years, male gender, moderate severity upon admission, cough, expectoration, CT patchy opacity, CT consolidation, comorbid diabetes, and comorbid cardiovascular or cerebrovascular diseases as significant predictors of deterioration, while a stuffy or runny nose as a predictor of recovery. Conclusions: Early‐stage prediction of COVID‐19 deterioration can be made with inexpensive‐to‐measure variables, such as demographic characteristics, severity upon admission, observable symptoms, and self‐reported comorbid diseases, among asymptomatic people and mildly to moderately symptomatic patients. [ABSTRACT FROM AUTHOR]

Objectives: To explore the diagnostic value of radiomics in differentiating between lung adenocarcinomas appearing as ground‐glass opacity nodules (GGO) with high‐ and low Ki‐67 expression levels. Materials and Methods: From January 2018 to January 2021, patients with pulmonary GGO who received lung resection were evaluated for potential enrollment. The included GGOs were then randomly divided into a training cohort and a validation cohort with a ratio of 7:3. Logistic regression (LR), decision tree (DT), support vector machines (SVM), and adaboost (AB) were applied for radiomic model construction. Area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the established models. Results: Seven hundred and sixty‐nine patients with 769 GGOs were included in this study. Two hundred and forty‐five GGOs were confirmed to be of high Ki‐67 labeling index (LI). In the training cohort, gender, age, spiculation sign, pleural indentation sign, bubble sign, and maximum 2D diameter of the nodule were found to be significantly different between high‐ and low Ki‐67 LI groups (p < 0.05), and spiculation sign and maximum 2D diameter of the nodule were further confirmed to be risk factors for Ki‐67 LI. The radiomic model established using SVM exhibited an AUC of 0.731 in the validation cohort, which was higher than that of the clinical‐radiographic model (AUC = 0.675). Moreover, radiomic model combining both intra‐ and peri‐nodular features showed better diagnostic efficacy than using intra‐nodular features alone (AUC = 0.731 and 0.720, respectively). Conclusions: The established radiomic model exhibited good diagnostic efficacy in differentiating between lung adenocarcinoma GGOs with high and low Ki‐67 LI, which was higher than the clinical‐radiographic model. Peri‐nodular radiomic features showed added benefits to the radiomic model. As a novel noninvasive method, radiomics have the potential to be applied in the preliminary classification of Ki‐67 expression level in lung adenocarcinoma GGOs. [ABSTRACT FROM AUTHOR]

The poor outcomes in advanced non‐small‐cell lung cancer (NSCLC) necessitate new treatments. Recent studies emphasize anisomycin as a promising anti‐cancer drug candidate. In this work, we systematically investigated the efficacy of anisomycin alone and its combination with the standard‐of‐care drugs in NSCLC. We showed that anisomycin inhibited growth, migration, and survival in NSCLC cells regardless of genetic mutation status, and to a greater extent than in normal lung epithelial cells. Isobologram analysis showed that the combination of anisomycin with cisplatin, paclitaxel, or gefitinib was synergistic in NSCLC but not normal lung cells. We further demonstrated that anisomycin inhibited NSCLC growth in mice. The combination of anisomycin with cisplatin was more effective than cisplatin alone and completely arrested NSCLC growth throughout the whole duration of treatment. JNK and p38 MAPK were not required for anisomycin's action. In contrast, anisomycin inhibits PI3K/Akt/mTOR pathway. Overexpression of constitutively active Akt reversed the pro‐apoptotic effect of anisomycin. Our work demonstrates the selective anti‐NSCLC activity of anisomycin via suppressing PI3K/Akt/mTOR. Our findings provide preclinical evidence to initialize the clinical trial of using anisomycin to sensitize NSCLC to current therapy. [ABSTRACT FROM AUTHOR]

In December 2019, coronavirus disease 2019 (COVID‐19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), emerged in Wuhan, China, and has spread globally. However, the transmission route of SARS‐CoV‐2 has not been fully understood. In this study, we aimed to investigate SARS‐CoV‐2 shedding in the excreta of COVID‐19 patients. Electronical medical records, including demographics, clinical characteristics, laboratory and radiological findings of enrolled patients were extracted and analyzed. Pharyngeal swab, stool, and urine specimens were collected and tested for SARS‐CoV‐2 RNA by real‐time reverse transcription polymerase chain reaction. Viral shedding at multiple time points in specimens was recorded, and its correlation analyzed with clinical manifestations and the severity of illness. A total of 42 laboratory‐confirmed patients were enrolled, 8 (19.05%) of whom had gastrointestinal symptoms. A total of 28 (66.67%) patients tested positive for SARS‐CoV‐2 RNA in stool specimens, and this was not associated with the presence of gastrointestinal symptoms and the severity of illness. Among them, 18 (64.29%) patients remained positive for viral RNA in the feces after the pharyngeal swabs turned negative. The duration of viral shedding from the feces after negative conversion in pharyngeal swabs was 7 (6‐10) days, regardless of COVID‐19 severity. The demographics, clinical characteristics, laboratory and radiologic findings did not differ between patients who tested positive and negative for SARS‐CoV‐2 RNA in the feces. Viral RNA was not detectable in urine specimens from 10 patients. Our results demonstrated the presence of SARS‐CoV‐2 RNA in the feces of COVID‐19 patients and suggested the possibility of SARS‐CoV‐2 transmission via the fecal‐oral route. Research Highlights: Two thirds of COVID‐19 patients tested positive for SARS‐CoV‐2 RNA in stool specimens.The presence of SARS‐CoV‐2 RNA in the feces of COVID‐19 patients was not associated with gastrointestinal symptoms and the severity of illness.More than 60% patients remained positive for viral RNA in feces after pharyngeal swabs turned negative.The duration of viral shedding from feces after negative conversion in pharyngeal swabs was 7 (6‐10) days, regardless of COVID‐19 severity.Fecal‐oral route may serve as an alternative transmission route for SARS‐CoV‐2. [ABSTRACT FROM AUTHOR]

Abstract: Idiopathic pulmonary fibrosis (IPF) is a genetic heterogeneous disease with high mortality and poor prognosis. However, a large fraction of genetic cause remains unexplained, especially in sporadic IPF (∼80% IPF). By systemically reviewing related literature and potential pathogenic pathways, 92 potentially IPF‐related genes were selected and sequenced in genomic DNAs from 253 sporadic IPF patients and 125 matched health controls using targeted massively parallel next‐generation sequencing. The identified risk variants were confirmed by Sanger sequencing. We identified two pathogenic and 10 loss‐of‐function (LOF) candidate variants, accounting for 4.74% (12 out of 253) of all the IPF cases. In burden tests, rare missense variants in three genes (CSF3R, DSP, and LAMA3) were identified that have a statistically significant relationship with IPF. Four common SNPs (rs3737002, rs2296160, rs1800470, and rs35705950) were observed to be statistically associated with increased risk of IPF. In the cumulative risk model, high risk subjects had 3.47‐fold (95%CI: 2.07–5.81, P = 2.34 × 10−6) risk of developing IPF compared with low risk subjects. We drafted a comprehensive map of genetic risks (including both rare and common candidate variants) in patients with IPF, which could provide insights to help in understanding mechanisms, providing genetic diagnosis, and predicting risk for IPF. [ABSTRACT FROM AUTHOR]