circRNADisease v2.0: an updated resource for high-quality experimentally supported circRNA-disease associations.

circRNADisease v2.0 is an enhanced and reliable database that offers experimentally verified relationships between circular RNAs (circRNAs) and various diseases. It is accessible at http://cgga.org.cn/circRNADisease/ or http://cgga.org.cn:9091/circRNADisease/. The database currently includes 6998 circRNA-disease entries across multiple species, representing a remarkable 19.77-fold increase compared to the previous version. This expansion consists of a substantial rise in the number of circRNAs (from 330 to 4246), types of diseases (from 48 to 330) and covered species (from human only to 12 species). Furthermore, a new section has been introduced in the database, which collects information on circRNA-associated factors (genes, proteins and microRNAs), molecular mechanisms (molecular pathways), biological functions (proliferation, migration, invasion, etc.), tumor and/or cell line and/or patient-derived xenograft (PDX) details, and prognostic evidence in diseases. In addition, we identified 7 159 865 relationships between mutations and circRNAs among 30 TCGA cancer types. Due to notable enhancements and extensive data expansions, the circRNADisease 2.0 database has become an invaluable asset for both clinical practice and fundamental research. It enables researchers to develop a more comprehensive understanding of how circRNAs impact complex diseases.

Lyoniresinol attenuates cerebral ischemic stroke injury in MCAO rat based on oxidative stress suppression via regulation of Akt/GSK-3ß/Nrf2 signaling.

Stroke is one of the predominant causes of death and disability. Currently, besides thrombolytic therapy, neuroprotection is also generally recognized as a promising way for stroke treatment, which would be very important for the functional recovery of stroke patients. However, it's reported that all the current available neuroprotective drugs have failed in clinical investigations of stroke treatments so far. Lyoniresinol (LNO) is a natural lignan with powerful antioxidant and cytoprotective activities. In this study, OGD/R leaded HT22 cell damage models and Middle Cerebral Artery Occlusion (MCAO) rats were used to investigate the effect of LNO on cerebral ischemic stroke injury and related mechanisms. The cell experiments revealed LNO can suppress the oxygen glucose deprivation-reoxygenation (OGD/R) induced apoptosis of HT22 cells. Subsequently, LNO can improve nerve function deficit and brain injury in MCAO rats with a higher neurological function scores and less infarct size. And the further molecular mechanisms studies suggested LNO activated the PI3K/AKT/GSK-3ß/NRF2 signaling and improved the oxidative stress in cells to inhibit the OGD/R induced apoptosis in HT22 cells. Collectively, our findings would be useflu for the further drug development of LNO as new drug for stroke and its related diseases.

OncoPDSS: an evidence-based clinical decision support system for oncology pharmacotherapy at the individual level.

BACKGROUND: Precision oncology pharmacotherapy relies on precise patient-specific alterations that impact drug responses. Due to rapid advances in clinical tumor sequencing, an urgent need exists for a clinical support tool that automatically interprets sequencing results based on a structured knowledge base of alteration events associated with clinical implications. RESULTS: Here, we introduced the Oncology Pharmacotherapy Decision Support System (OncoPDSS), a web server that systematically annotates the effects of alterations on drug responses. The platform integrates actionable evidence from several well-known resources, distills drug indications from anti-cancer drug labels, and extracts cancer clinical trial data from the ClinicalTrials.gov database. A therapy-centric classification strategy was used to identify potentially effective and non-effective pharmacotherapies from user-uploaded alterations of multi-omics based on integrative evidence. For each potentially effective therapy, clinical trials with faculty information were listed to help patients and their health care providers find the most suitable one. CONCLUSIONS: OncoPDSS can serve as both an integrative knowledge base on cancer precision medicine, as well as a clinical decision support system for cancer researchers and clinical oncologists. It receives multi-omics alterations as input and interprets them into pharmacotherapy-centered information, thus helping clinicians to make clinical pharmacotherapy decisions. The OncoPDSS web server is freely accessible at https://oncopdss.capitalbiobigdata.com .