Lung cancer is the leading cause of cancer death, and non-small cell lung cancer (NSCLC) accounts for 85%. Immunotherapy has significantly improved the clinical prognosis of patients with NSCLC. However, because of the complexity and heterogeneousness of the tumor microenvironment, only a subset of individuals can benefit from immunotherapy. Therefore, it is necessary to explore effective predictive biomarkers for immunotherapy of NSCLC. Tertiary lymphoid structure (TLS) is an ectopic lymphoid organ that is highly similar to secondary lymphoid organs (SLO), and the presence of TLS has been found to be closely associated with a good prognosis in immunotherapy for a variety of solid tumors, including NSCLC. This article provides a review of the prognostic role of tertiary lymphoid structures in immunotherapy of NSCLC, in order to offer references for screening suitable candidates for immunotherapy of NSCLC and develop personalized and precise treatment plans.
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Humans ; Carcinoma, Non-Small-Cell Lung/pathology* ; Tertiary Lymphoid Structures/pathology* ; Lung Neoplasms/pathology* ; Prognosis ; Immunotherapy ; Tumor Microenvironment

ObjectiveTo develop and validate a predictive model to individually predict the risk of patients with stroke in the eICU Collaborative Research Database for early clinical identification and intervention. MethodIndividual patient data （200 859 cases） from a national multicenter cohort study （eICU database） were selected， and the patients with stroke in neurological diseases （9 037 cases） were selected for statistical analysis. The main outcome was hospital mortality. The Glasgow Coma scale （GCS） was used to divide all patients with stroke into stroke in meridian and stroke in viscera （GCS≤14 for stroke in viscera and GCS=15 for stroke in meridian）. The patients were then divided into a training set and a test set according to 7∶3， respectively， to evaluate the differences in hospital mortality between the two groups. The multivariate logistic regression was used to analyze the related factors affecting the prognosis of the two groups， and a predictive model was established. Receiver operator characteristic （ROC） curves were used to assess the discrimination of the predictive model. ResultThe predictive model based on 9 037 patients with stroke was established. The predictors of the stroke in meridian （4 475 cases） included pulmonary infection， mechanical ventilation， acute physiology， and chronic health status scoring system Ⅳ （APACHE Ⅳ） score. The predictors of the stroke in viscera （4 562 cases） included anticoagulation therapy （AT）， mechanical ventilation， acute physiology， and APACHE Ⅳ score. According to the predictors， the predictive models of the stroke in meridian and the stroke in viscera were constructed， respectively. The areas under the curve （AUC） of ROC of the training set and the test set of the predictive models of the stroke in meridian were 0.845 ［95% confidence interval （CI） （0.811， 0.879）］ and 0.807 ［95% CI （0.751， 0.863）］， respectively. The areas under the ROC curve of the training set and test set of the predictive models of the stroke in viscera were 0.799 ［95% CI （0.781， 0.817）］ and 0.805 ［95% CI （0.778， 0.832）］， respectively. The AUC of the predictive model of the training set and the test set were both above 0.7. ConclusionThe model established in this study can conveniently， directly， and accurately predict the hospital mortality risk of patients with stroke. Physicians and other healthcare professionals can use this predictive approach to provide early care planning and clinical interventions for patients with stroke during their hospital stay.

Carbohydrates are fundamental molecules involved in nearly all aspects of lives, such as being involved in formating the genetic and energy materials, supporting the structure of organisms, constituting invasion and host defense systems, and forming antibiotics secondary metabolites. The naturally occurring carbohydrates and their derivatives have been extensively studied as therapeutic agents for the treatment of various diseases. During 2000 to 2021, totally 54 carbohydrate-based drugs which contain carbohydrate moities as the major structural units have been approved as drugs or diagnostic agents. Here we provide a comprehensive review on the chemical structures, activities, and clinical trial results of these carbohydrate-based drugs, which are categorized by their indications into antiviral drugs, antibacterial/antiparasitic drugs, anticancer drugs, antidiabetics drugs, cardiovascular drugs, nervous system drugs, and other agents.