Hongjun Zhen’s scientific contributions

Background Alzheimer's disease (AD) has a major negative impact on people's quality of life, life, and health. More research is needed to determine the relationship between age and the pathologic products associated with AD. Meanwhile, the construction of an early diagnostic model of AD, which is mainly characterized by pathological products, is very important for the diagnosis and treatment of AD. Method We collected clinical study data from September 2005 to August 2024 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Using correlation analysis method like cor function, we analyzed the pathology products (t-Tau, p-Tau, and Aβ proteins), age, gender, and Minimum Mental State Examination (MMSE) scores in the ADNI data. Next, we investigated the relationship between pathologic products and age in the AD and non-AD groups using linear regression. Ultimately, we used these features to build a diagnostic model for AD. Results A total of 1,255 individuals were included in the study (mean [SD] age, 73.27 [7.26] years; 691male [55.1%]; 564 female [44.9%]). The results of the correlation analysis showed that the correlations between pathologic products and age were, in descending order, Tau (Corr=0.75), p-Tau (Corr=0.71), and Aβ (Corr=0.54). In the AD group, t-Tau protein showed a tendency to decrease with age, but it was not statistically significant. p-Tau protein levels similarly decreased with age and its decrease was statistically significant. In contrast to Tau protein, in the AD group, Aβ levels increased progressively with age. In the non-AD group, the trend of pathologic product levels with age was consistently opposite to that of the AD group. We finally screened the optimal AD diagnostic model (AUC=0.959) based on the results of correlation analysis and by using the Xgboost algorithm and SVM algorithm. Conclusion In a novel finding, we observed that Tau protein and Aβ had opposite trends with age in both the AD and non-AD groups. The linear regression curves of the AD and non-AD groups had completely opposite trends. Through a machine learning approach, we constructed an AD diagnostic model with excellent performance based on the selected features.

Research has long centered on the pathophysiology of pain. The Transient Receiver Potential (TRP) protein family is well known for its function in the pathophysiology of pain, and extensive study has been done in this area. One of the significant mechanisms of pain etiology and analgesia that lacks a systematic synthesis and review is the ERK/CREB (Extracellular Signal-Regulated Kinase/CAMP Response Element Binding Protein) pathway. The ERK/CREB pathway-targeting analgesics may also cause a variety of adverse effects that call for specialized medical care. In this review, we systematically compiled the mechanism of the ERK/CREB pathway in the process of pain and analgesia, as well as the potential adverse effects on the nervous system brought on by the inhibition of the ERK/CREB pathway in analgesic drugs, and we suggested the corresponding solutions.