Alzheimer’s disease (AD) is accompanied by β-amyloid (Aβ), neurofibrillary tangles, and neuron cell death, and is one of the most commonly occurring diseases among the elderly. The pathology of AD is complex, involving Aβ overproduction and accumulation, tau hyperphosphorylation, and neuronal loss. In addition, chronic cerebral hypoperfusion (CCH) is ubiquitous in the AD patients and plans a pivotal role in triggering and exacerbating the pathophysiological progress of AD. The goal of this study was to investigate the neuroprotective properties of berberine (BBR) and the underlying mechanism. During the study, BBR was administrated to treat the triple-transgenic mouse model of Alzheimer’s disease (3×Tg AD). To thoroughly evaluate the effects of the BBR administration, multiple manners were utilized, for instance, 3D arterial spin labeling technique, Morris water maze assay, immunofluorescence staining, TUNEL assay, laser speckle contrast imaging, western blotting, etc. The results showed that BBR ameliorated cognitive deficits in 3×Tg AD mice, reduced the Aβ accumulation, inhibited the apoptosis of neurons, promoted the formation of microvessels in the mouse brain by enhancing brain CD31, VEGF, N-cadherin, Ang-1. The new vessels promoted by BBR were observed to have a complete structure and perfect function, which in turn promoted the recovery of cerebral blood flow (CBF). In general, berberine is effective to 3×Tg AD mice, has a neuroprotective effect, and is a candidate drug for the multi-target prevention and treatment of AD.

Cardiac arrest is a global health concern with consistently high mortality. It is also a common condition seen in the intensive care unit (ICU). We aimed to investigate the importance of albumin level on admission, which is a widely available and simple test, to predict in-hospital mortality in cardiac arrest patients. The retrospective study collected data from the eICU Collaborative Research Database. It contains data from 171 hospitals, 276 ICU wards, and 4,529 patients who were treated for cardiac arrest from 2014 to 2015. We analyzed the patients’ laboratory results and vital signs during the first 24 hours after admission to the ICU. The primary outcome was in-hospital mortality, and the secondary outcome was the length of ICU stay among survivors. In total, 2,414 patients were eligible. After adjusting for severity scores, including the Acute Physiology and Chronic Health Evaluation (APACHE) IV and Sequential Organ Failure Assessment (SOFA) scores, serum albumin was found to be a protective factor for survival (odds ratio of mortality: 0635, 95% confidence interval: 0.458-0.734, P<0.001). Among patients who survived until discharge, those with hypoalbuminemia had a long duration of stay in the ICU (P=0.005). The higher albumin level at admission to the ICU was associated with lower mortality in patients with cardiac arrest.

This study aims to develop a machine learning-based model for predicting mortality risk in patients with epilepsy admitted to the intensive care unit (ICU), providing clinicians with an accurate prognostic tool to guide individualized treatment. We collected clinical data from clinical databases (MIMIC IV and eICU-CRD) of epilepsy patients 24 h after ICU admission. The clinical characteristics of ICU patients with epilepsy were carefully feature selected and processed. MIMIC IV as the training set and eICU-CRD database as the test set. Six models were developed and validated, and the best LightGBM model was selected by performance comparison and analysed for interpretability. The final cohort comprised 429 patients for training and 1217 for testing. The training set exhibited a 90-day mortality rate of 9.32 %, and the test set had an in-hospital 90-day mortality rate of 4.10 %. Utilizing the LightGBM model, we achieved an AUC of 0.956 in the training set. External validation demonstrated promising results with accuracy of 0.898, precision of 0.975, AUC of 0.781, F1 score of 0.945, highlighting the model's potential for guiding clinical decision-making. Significant factors influencing model performance included the severity of illness, as measured by the OASIS score, and clinical parameters like heart rate and body temperature. This study introduces a machine learning-based approach to predict mortality risk in ICU epilepsy patients, offering a valuable tool for clinicians to identify high-risk individuals and devise personalized treatment strategies, thus improving patient prognosis and treatment outcomes.

Objective: This study evaluated the efficacy and safety of adjunctive clobazam (CLB) in Chinese patients with drug-resistant epilepsy (DRE). Methods: We retrospectively included 121 DRE patients receiving adjunctive CLB at the Epilepsy Center of the Seventh Affiliated Hospital of Sun Yat-sen University (Jan 2023-May 2025). Patients were followed at 1, 3, 6, 9, and 12 months or longer. Data collected included epilepsy etiology, seizure type, frequency, treatment duration, dosage, and adverse events. Response was defined as ≥50% reduction in seizure frequency from baseline. Results: A total of 121 patients were included (age at medication use 32.4 ± 13.5 years; mean three prior failed antiseizure medications; mean follow-up 12 months). Seizure types were focal (18.2%), generalized (7.4%), and both (74.4%). At first follow-up, 51.2% achieved ≥50% seizure reduction and 39.7% were seizure freedom; at last follow-up, 85.9% responded and 51.6% were seizure freedom. Response rates increased over time (all p < 0.001). Adults had higher response ( p = 0.046) and seizure freedom rates ( p = 0.041) than children. Concomitant oxcarbazepine (OXC) was associated with increased seizure freedom ( p = 0.03), whereas valproate (VPA) was associated with low response rate ( p = 0.013) but not with seizure freedom. Age at medication (OR = 1.032, p = 0.035), CLB dosage (OR = 1.093, p = 0.004), and OXC co-therapy (OR = 2.311, p = 0.04) were independent predictors of seizure freedom. Most common adverse events were somnolence/mental fatigue (9.9%) and hypersomnia (5%). Conclusion: Adjunctive CLB significantly reduced seizures in DRE with sustained efficacy. Higher dosage, longer treatment duration, and concomitant OXC use were associated with improved outcomes. CLB showed favorable efficacy, wide applicability, and acceptable safety.