Nomogram established on account of Lasso-logistic regression for predicting hemorrhagic transformation in patients with acute ischemic stroke after endovascular thrombectomy.

BACKGROUND: Hemorrhagic transformation (HT) is a common and serious complication in patients with acute ischemic stroke (AIS) after endovascular thrombectomy (EVT). This study was performed to determine the predictive factors associated with HT in stroke patients with EVT and to establish and validate a nomogram that combines with independent predictors to predict the probability of HT after EVT in patients with AIS. METHODS: All patients were randomly divided into development and validation cohorts at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression was used to select the optimal factors, and multivariate logistic regression analysis was used to build a clinical prediction model. Calibration plots, decision curve analysis (DCA) and receiver operating characteristic curve (ROC) were generated to assess predictive performance. RESULTS: LASSO regression analysis showed that Alberta Stroke Program Early CT Scores (ASPECTS), international normalized ratio (INR), uric acid (UA), neutrophils (NEU) were the influencing factors for AIS with HT after EVT. A novel prognostic nomogram model was established to predict the possibility of HT with AIS after EVT. The calibration curve showed that the model had good consistency. The results of ROC analysis showed that the AUC of the prediction model established in this study for predicting HT was 0.797 in the development cohort and 0.786 in the validation cohort. CONCLUSION: This study proposes a novel and practical nomogram based on ASPECTS, INR, UA, NEU, which can well predict the probability of HT after EVT in patients with AIS.

Rational Identification of Novel Antibody-Drug Conjugate with High Bystander Killing Effect against Heterogeneous Tumors.

Bystander-killing payloads can significantly overcome the tumor heterogeneity issue and enhance the clinical potential of antibody-drug conjugates (ADC), but the rational design and identification of effective bystander warheads constrain the broader implementation of this strategy. Here, graph attention networks (GAT) are constructed for a rational bystander killing scoring model and ADC construction workflow for the first time. To generate efficient bystander-killing payloads, this model is utilized for score-directed exatecan derivatives design. Among them, Ed9, the most potent payload with satisfactory permeability and bioactivity, is further used to construct ADC. Through linker optimization and conjugation, novel ADCs are constructed that perform excellent anti-tumor efficacy and bystander-killing effect in vivo and in vitro. The optimal conjugate T-VEd9 exhibited therapeutic efficacy superior to DS-8201 against heterogeneous tumors. These results demonstrate that the effective scoring approach can pave the way for the discovery of novel ADC with promising bystander payloads to combat tumor heterogeneity.

Discovery of potent small molecule ubiquitin-specific protease 10 inhibitors with anti-hepatocellular carcinoma activity through regulating YAP expression.

High expression of ubiquitin-specific protease 10 (USP10) promote the proliferation of hepatocellular carcinoma (HCC), thus the development of USP10 inhibitors holds promise as a novel therapeutic approach for HCC treatment. However, the development of selective USP10 inhibitor is still limited. In this study, we developed a novel USP10 inhibitor for investigating the feasibility of targeting USP10 for the treatment of HCC. Due to high USP10 inhibition potency and prominent selectivity, compound D1 bearing quinolin-4(1H)-one scaffold was identified as a lead compound. Subsequent research revealed that D1 significantly inhibits cell proliferation and clone formation in HCC cells. Mechanistic insights indicated that D1 targets the ubiquitin pathway, facilitating the degradation of YAP (Yes-associated protein), thereby triggering the downregulation of p53 and its downstream protein p21. Ultimately, this cascade leads to S-phase arrest in HCC cells, followed by cell apoptosis. Collectively, our findings highlight D1 as a promising starting point for USP10-positive HCC treatment, underscoring its potential as a vital tool for unraveling the functional intricacies of USP10.

Discovery of New Phenyltetrazolium Derivatives as Ferroptosis Inhibitors for Treating Ischemic Stroke: An Example Development from Free Radical Scavengers.

Ferroptosis is a promising therapeutic target for injury-related diseases, yet diversity in ferroptosis inhibitors remains limited. In this study, initial structure optimization led us to focus on the bond dissociation enthalpy (BDE) of the N-H bond and the residency time of radical scavengers in a phospholipid bilayer, which may play an important role in ferroptosis inhibition potency. This led to the discovery of compound D1, exhibiting potent ferroptosis inhibition, high radical scavenging, and moderate membrane permeability. D1 demonstrated significant neuroprotection in an oxygen glucose deprivation/reoxygenation (OGD/R) model and reduced infarct volume in an in vivo stroke model upon intravenous treatment. Further screening based on this strategy identified NecroX-7 and Eriodictyol-7-O-glucoside as novel ferroptosis inhibitors with highly polar structural characteristics. This approach bridges the gap between free radical scavengers and ferroptosis inhibitors, providing a foundation for research and insights into novel ferroptosis inhibitor development.