Ningetinib, a novel FLT3 inhibitor, overcomes secondary drug resistance in acute myeloid leukemia.

BACKGROUND: FMS-like tyrosine kinase 3 internal tandem duplication (FLT3-ITD) is a common mutation type in acute myeloid leukemia (AML) and is usually associated with poor patient prognosis. With advancements in molecular diagnostics and the development of tyrosine kinase inhibitors (TKI), the overall survival (OS) of AML patients with FLT3-ITD mutations has been prolonged to some extent, but relapse and drug resistance are still substantial challenges. Ningetinib is a novel TKI against various kinases in relation to tumour pathogenesis and is undergoing clinical trials of lung cancer. In this study, we explored the antitumor activity of ningetinib against AML with FLT3 mutations both in vivo and in vitro. METHODS: Cell proliferation assays were performed in AML cell lines and Ba/F3 cells expressing various FLT3 mutations to validate the antileukemic activity of ningetinib in vitro. Immunoblot assays were used to verify the effect of ningetinib on the FLT3 protein and downstream pathways. Molecular docking and CETSA were used to validate the interaction of ningetinib with target proteins. The survival benefit of ningetinib in vivo was assessed in Ba/F3-FLT3-ITD-, MOLM13, Ba/F3-FLT3-ITD-F691L-, MOLM13-FLT3-ITD-F691L-induced leukemia mouse models. We also used patient-derived primary cells to determine the efficacy of ningetinib. RESULTS: Ningetinib inhibited cell proliferation, blocked the cell cycle, induced apoptosis and bound FLT3 to inhibit its downstream signaling pathways, including the STAT5, AKT and ERK pathways, in FLT3-ITD AML cell lines. In the mouse models with FLT3-ITD and FLT3-ITD-F691L mutation, ningetinib showed superior anti-leukemia activity to existing clinical drugs gilteritinib and quizartinib, significantly prolongating the survival of mice. In addition, ningetinib exhibited activity against patient-derived primary cells harboring FLT3-ITD mutations. CONCLUSION: Overall, our study confirmed the therapeutic role of ningetinib in AML with FLT3-ITD mutations, providing a potential new option for clinically resistant patients.

Research on an SICM Scanning Image Resolution Enhancement Algorithm.

Scanning ion conductance microscopy (SICM) enables the non-invasive three-dimensional imaging of live cells and other structures in physiological environments. However, when imaging complex samples, SICM faces challenges such as having a low temporal resolution during slow scanning and a reduced signal-to-noise ratio during fast scanning, making it difficult to simultaneously improve both temporal and spatial resolution. To address these issues, this paper proposes an algorithm for enhancing image resolution under high-speed scanning. Firstly, scanning images are preprocessed using a median filtering algorithm to remove the salt-and-pepper noise generated during high-speed scanning. Next, the Canny edge detection algorithm is employed to extract the edges of the image targets. To avoid blurring the edges, the new edge-directed interpolation (NEDI) algorithm is then used to fill the edges, while non-edge areas are filled using bilinear interpolation, thereby enhancing the image resolution. Finally, the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) are used to analyze the imaging of articular chondrocytes. The results show that under a scanning speed of 480 nm/ms, the proposed algorithm improves the temporal resolution of imaging by 60% compared to traditional 2× resolution imaging, increases the peak signal-to-noise ratio of the scanning images by 7 dB, and achieves a structural similarity of 0.97. Therefore, the proposed algorithm effectively removes noise during high-speed scanning and improves the SICM scanning imaging resolution, thereby avoiding the reduction in temporal resolution when scanning larger resolution samples and effectively enhancing the performance of SICM scanning imaging.

Novel insight into the genetic signatures of altitude adaptation related body composition in Tibetans.

Background: The Tibetan population residing in high-altitude (HA) regions has adapted to extreme hypoxic environments. However, there is limited understanding of the genetic basis of body compositions in Tibetan population adapted to HA. Methods: We performed a genome-wide association study (GWAS) to identify genetic variants associated with HA and HA-related body composition traits. A total of 755,731 single nucleotide polymorphisms (SNPs) were genotyped using the precision medicine diversity array from 996 Tibetan college students. T-tests and Pearson correlation analysis were used to estimate the association between body compositions and altitude. The mixed linear regression identified the SNPs significantly associated with HA and HA-related body compositions. LASSO regression was used to screen for important SNPs in HA and body compositions. Results: Significant differences were observed in lean body mass (LBW), muscle mass (MM), total body water (TBW), standard weight (SBW), basal metabolic rate (BMR), total protein (TP), and total inorganic salt (Is) in different altitudes stratification. We identified three SNPs in EPAS1 (rs1562453, rs7589621 and rs7583392) that were significantly associated with HA (p < 5 × 10-7). GWAS analysis of 7 HA-related body composition traits, we identified 14 SNPs for LBM, 11 SNPs for TBW, 15 SNPs for MM, 16 SNPs for SBW, 9 SNPs for BMR, 12 SNPs for TP, and 26 SNPs for Is (p < 5.0 × 10-5). Conclusion: These findings provide insight into the genetic basis of body composition in Tibetan college students adapted to HA, and lay the foundation for further investigation into the molecular mechanisms underlying HA adaptation.

Poly(ethylene oxide)-based composite solid electrolyte for long cycle life solid-state lithium metal batteries: Improvement of interface stability through a dual mechanism.

Solid-state lithium metal batteries (SSLMBs) are promising candidates for safe and high-energy-density next-generation applications. However, harmful interfacial decomposition and uneven Li deposition lead to poor ion transport, a short cycle life, and battery failure. Herein, we propose a novel poly(ethylene oxide) (PEO)-based composite solid electrolyte (CSE) containing succinonitrile (SN) and zinc oxide (ZnO) nanoparticles (NPs), which improves interface stability through a dual mechanism. (1) By anchoring bis(trifluoromethanesulfonyl)imide (TFSI) anions to ZnO, a reliable solid electrolyte interface (SEI) later with abundant LiF can be obtained to inhibit interface decomposition. (2) The immobilization of escaping SN molecules in the SEI layer by ZnO NPs promotes the self-polymerization of SN and facilitates charge transfer through the interface. As a result, the ion conductivity of the stainless steel-symmetrical battery reaches 1.1 × 10-4 S cm-1 at room temperature, and a LiFePO4 (LFP) full battery exhibits ultrahigh stability (800 cycles) at 0.5 C. Thus, the present study provides valuable insights for the development of advanced PEO-based SSLMBs.

Association Between CYP24A1 Polymorphisms and Bladder Cancer Risk in the Chinese Han Population.

In this cohort of 217 bladder cancer patients and 484 healthy controls, we explored the association between CYP24A1 variants (rs2762934, rs1570669, rs6068816, rs2296241) and bladder cancer risk in the Chinese Han population. Utilizing the Agena MassARRAY system, we genotyped four selected CYP24A1 polymorphisms. Logistic regression revealed a significant association of rs2762934 and rs1570669 with elevated bladder cancer risk, while rs6068816 exhibited a protective effect. Bioinformatics analysis of CYP24A1 expression in normal and cancerous bladder tissues indicated higher expression in normal tissue. In conclusion, our findings highlight the potential role of CYP24A1 variants in bladder cancer susceptibility.

Towards Open Vocabulary Learning: A Survey.

In the field of visual scene understanding, deep neural networks have made impressive advancements in various core tasks like segmentation, tracking, and detection. However, most approaches operate on the close-set assumption, meaning that the model can only identify pre-defined categories that are present in the training set. Recently, open vocabulary settings were proposed due to the rapid progress of vision language pre-training. These new approaches seek to locate and recognize categories beyond the annotated label space. The open vocabulary approach is more general, practical, and effective than weakly supervised and zero-shot settings. This paper thoroughly reviews open vocabulary learning, summarizing and analyzing recent developments in the field. In particular, we begin by juxtaposing open vocabulary learning with analogous concepts such as zero-shot learning, open-set recognition, and out-of-distribution detection. Subsequently, we examine several pertinent tasks within the realms of segmentation and detection, encompassing long-tail problems, few-shot, and zero-shot settings. As a foundation for our method survey, we first elucidate the fundamental principles of detection and segmentation in close-set scenarios. Next, we examine various contexts where open vocabulary learning is employed, pinpointing recurring design elements and central themes. This is followed by a comparative analysis of recent detection and segmentation methodologies in commonly used datasets and benchmarks. Our review culminates with a synthesis of insights, challenges, and discourse on prospective research trajectories. To our knowledge, this constitutes the inaugural exhaustive literature review on open vocabulary learning.

Discovery of Pyrido[2,3-d]pyrimidin-7-one Derivatives as Highly Potent and Efficacious Ectonucleotide Pyrophosphatase/Phosphodiesterase 1 (ENPP1) Inhibitors for Cancer Treatment.

Ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) is an extracellular enzyme responsible for hydrolyzing cyclic guanosine monophosphate-adenosine monophosphate (cGAMP), the endogenous agonist for the stimulator of interferon genes (STING) pathway. Inhibition of ENPP1 can trigger STING and promote antitumor immunity, offering an attractive therapeutic target for cancer immunotherapy. Despite progress in the discovery of ENPP1 inhibitors, the diversity in chemical structures and the efficacy of the agents are far from desirable, emphasizing the demand for novel inhibitors. Herein, we describe the design, synthesis, and biological evaluation of a series of ENPP1 inhibitors based on the pyrido[2,3-d]pyrimidin-7-one scaffold. Optimization efforts led to compound 31 with significant potency in both ENPP1 inhibition and STING pathway stimulation in vitro. Notably, 31 demonstrated in vivo efficacy in a syngeneic 4T1 mouse triple negative breast cancer model. These findings provide a promising lead compound with a novel scaffold for further drug development in cancer immunotherapy.

Anoikis-related signature predicts prognosis and characterizes immune landscape of ovarian cancer.

Ovarian cancer (OV) is the most lethal gynecological malignancy worldwide, with high recurrence rates. Anoikis, a newly-acknowledged form of programmed cell death, plays an essential role in cancer progression, though studies focused on prognostic patterns of anoikis in OV are still lacking. We filtered 32 potential anoikis-related genes (ARGs) among the 6406 differentially expressed genes (DEGs) between the 180 normal controls and 376 TCGA-OV samples. Through the LASSO-Cox analysis, a 2-gene prognostic signature, namely AKT2, and DAPK1, was finally distinguished. We then demonstrated the promising prognostic value of the signature through the K-M survival analysis and time-dependent ROC curves (p-value < 0.05). Moreover, based on the signature and clinical features, we constructed and validated a nomogram model for 1-year, 3-year, and 5-year overall survival, with reliable prognostic values in both TCGA-OV training cohort (p-value < 0.001) and ICGC-OV validation cohort (p-value = 0.030). We evaluated the tumor immune landscape through the CIBERSORT algorithm, which indicated the upregulation of resting Myeloid Dendritic Cells (DCs), memory B cells, and naïve B cells and high expression of key immune checkpoint molecules (CD274 and PDCD1LG2) in the high-risk group. Interestingly, the high-risk group exhibited better sensitivity toward immunotherapy and less sensitivity toward chemotherapies, including Cisplatin and Bleomycin. Especially, based on the IHC of tissue microarrays among 125 OV patients at our institution, we reported that aberrant upregulation of DAPK1 was related to poor prognosis. Conclusively, the anoikis-related signature was a promising tool to evaluate prognosis and predict therapy responses, thus assisting decision-making in the realm of OV precision medicine.

Comprehensive machine learning-based preoperative blood features predict the prognosis for ovarian cancer.

PURPOSE: Significant advancements in improving ovarian cancer (OC) outcomes have been limited over the past decade. To predict prognosis and improve outcomes of OC, we plan to develop and validate a robust prognosis signature based on blood features. METHODS: We screened age and 33 blood features from 331 OC patients. Using ten machine learning algorithms, 88 combinations were generated, from which one was selected to construct a blood risk score (BRS) according to the highest C-index in the test dataset. RESULTS: Stepcox (both) and Enet (alpha = 0.7) performed the best in the test dataset with a C-index of 0.711. Meanwhile, the low RBS group possessed observably prolonged survival in this model. Compared to traditional prognostic-related features such as age, stage, grade, and CA125, our combined model had the highest AUC values at 3, 5, and 7 years. According to the results of the model, BRS can provide accurate predictions of OC prognosis. BRS was also capable of identifying various prognostic stratifications in different stages and grades. Importantly, developing the nomogram may improve performance by combining BRS and stage. CONCLUSION: This study provides a valuable combined machine-learning model that can be used for predicting the individualized prognosis of OC patients.

Letermovir Effectively Prevents Cytomegalovirus Infection in Patients with Aplastic Anemia After Hematopoietic Stem Cell Transplantation: A Real-World Retrospective Cohort Study.

INTRODUCTION: In this single-center retrospective cohort study, we investigated the efficacy of letermovir in preventing Cytomegalovirus (CMV) infection in patients with aplastic anemia (AA) who have undergone allogeneic hematopoietic stem cell transplantation (allo-HSCT). METHODS: Based on whether or not letermovir was used for preventing CMV infection, the patients were categorized into two groups: letermovir and control groups. The overall survival (OS) rate and cumulative incidence of CMV infection during the first 100 days after allo-HSCT were evaluated. The study included 21 matched pairs of patients, identified through propensity score matching analysis, to compare CMV infection rates, treatment efficacy, and regression. RESULTS: The incidence of CMV infection within 100 days after transplantation was significantly lower in the letermovir group than in the control group (26.5 vs. 77.4%, respectively; P < 0.001), among a total of 87 patients who underwent the transplant. In the matched cohort of 21 patients with AA, the letermovir group also showed a significantly reduced cumulative incidence of CMV infection (14.3 vs. 90.5% in the control group; P < 0.001). Compared to the control group, patients with CMV infection in the letermovir group had lower CMV-DNA load and a shorter clearance time. However, there was no significant difference in OS between both groups (P = 0.34). CONCLUSIONS: Letermovir effectively prevents CMV infection in allo-HSCT recipients with AA and demonstrates a high safety profile.

Constructing sulfur and oxygen super-coordinated main-group electrocatalysts for selective and cumulative H2O2 production.

Direct electrosynthesis of hydrogen peroxide (H2O2) via the two-electron oxygen reduction reaction presents a burgeoning alternative to the conventional energy-intensive anthraquinone process for on-site applications. Nevertheless, its adoption is currently hindered by inferior H2O2 selectivity and diminished H2O2 yield induced by consecutive H2O2 reduction or Fenton reactions. Herein, guided by theoretical calculations, we endeavor to overcome this challenge by activating a main-group Pb single-atom catalyst via a local micro-environment engineering strategy employing a sulfur and oxygen super-coordinated structure. The main-group catalyst, synthesized using a carbon dot-assisted pyrolysis technique, displays an industrial current density reaching 400 mA cm-2 and elevated accumulated H2O2 concentrations (1358 mM) with remarkable Faradaic efficiencies. Both experimental results and theoretical simulations elucidate that S and O super-coordination directs a fraction of electrons from the main-group Pb sites to the coordinated oxygen atoms, consequently optimizing the *OOH binding energy and augmenting the 2e- oxygen reduction activity. This work unveils novel avenues for mitigating the production-depletion challenge in H2O2 electrosynthesis through the rational design of main-group catalysts.

Discovery of a PROTAC degrader for METTL3-METTL14 complex.

N6-methyladenosine (m6A) methylation is the most abundant type of RNA modification that is mainly catalyzed by the METTL3-METTL14 methyltransferase complex. This complex has been linked to multiple cancers and is considered a promising therapeutic target for acute myeloid leukemia (AML). However, only a few METTL3 inhibitors targeting the catalytic activity were developed recently. Here, we present the discovery of WD6305 as the potent and selective proteolysis-targeting chimera (PROTAC) degrader of METTL3-METTL14 complex. WD6305 suppresses m6A modification and the proliferation of AML cells, and promotes apoptosis much more effectively than its parent inhibitor. WD6305 also affects a variety of signaling pathways related to the development and proliferation of AML. Collectively, our study reveals PROTAC degradation of METTL3-METTL14 complex as a potential anti-leukemic strategy and provides desirable chemical tool for further understanding METTL3-METTL14 protein functions.

Cost-effectiveness analysis of hepatitis E vaccination strategies among patients with chronic hepatitis B in China.

AIM: This study aimed to evaluate the cost-effectiveness of hepatitis E vaccination strategies in chronic hepatitis B (CHB) patients. METHODS: Based on the societal perspective, the cost-effectiveness of three hepatitis E vaccination strategies-vaccination without screening, screening-based vaccination, and no vaccination-among CHB patients was evaluated using a decision tree-Markov model, and incremental cost-effectiveness ratios (ICERs) were calculated. Values for treatment costs and health utilities were estimated from a prior investigation on disease burden, and values for transition probabilities and vaccination-related costs were obtained from previous studies and government agencies. Sensitivity analyses were undertaken for assessing model uncertainties. RESULTS: It was estimated that CHB patients superinfected with hepatitis E virus (HEV) incurred significantly longer disease course, higher economic burden, and more health loss compared to those with HEV infection alone (all p < 0.05). The ICERs of vaccination without screening and screening-based vaccination compared to no vaccination were 41,843.01 yuan/quality-adjusted life year (QALY) and 29,147.32 yuan/QALY, respectively, both lower than China's per-capita gross domestic product (GDP) in 2018. The screening-based vaccination reduced the cost and gained more QALYs than vaccination without screening. One-way sensitivity analyses revealed that vaccine price, vaccine protection rate, and decay rate of vaccine protection had the greatest impact on the cost-effectiveness analysis. Probabilistic sensitivity analyses confirmed the base-case results, and if the willingness-to-pay value reached per-capita GDP, the probability that screening-based vaccination would be cost-effective was approaching 100%. CONCLUSIONS: The disease burden in CHB patients superinfected with HEV is relatively heavy in China, and the screening-based hepatitis E vaccination strategy for CHB patients is the most cost-effective option.

Impact of missense TSBP1 variants on the susceptibility to coronary heart disease.

BACKGROUND: A genome-wide association study has recognized C6orf10-BTNL2 polymorphism in coronary artery disease. The goal of this study was to explore the potential correlation of nine missense TSBP1 variants with coronary heart disease (CHD) risk in the Chinese Han population. METHODS: Nine TSBP1 missense single nucleotide polymorphisms (SNPs) were selected for genotyping by the Agena MassARRAY platform. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to analyze the contribution of TSBP1 SNPs to CHD predisposition by logistic regression models adjusted by age, sex, drinking, and smoking. The correlation of TSBP1 variants with clinical data in CHD patients was examined by Kruskal-Wallis test. RESULTS: rs9268368-C (p = 0.039, OR = 1.18, 95 % CI: 1.01-1.38) was related to an increased risk of CHD, while rs3749966-C (p = 0.032, OR = 0.49, 95 % CI: 0.25-0.96) and rs3129941-A (p = 0.011, OR = 0.74, 95 % CI: 0.59-0.93) might be protective factors against CHD occurrence in the Chinese Han population. We also observed the effects of demographic characteristics (age, sex, alcohol consumption, and smoking) and complications (hypertension and diabetes) on the interactive association of TSBP1 polymorphisms with CHD susceptibility. rs139993810 was related to the levels of high-density lipoprotein cholesterol (HDL-C, p = 0.030). CONCLUSIONS: Our findings determined the association of TSBP1 rs9268368, rs3749966, and rs3129941 with CHD occurrence in the Chinese Han population, and highlighted the influence of demographic characteristics and complications on the interactive association of TSBP1 polymorphisms with CHD risk.

The role of SIRT3 in mediating the cognitive deficits and neuroinflammatory changes associated with a developmental animal model of schizophrenia.

The neuroinflammatory state may contribute to the pathogenesis of many mental disorders including schizophrenia. Nicotinamide adenine dinucleotide (NAD+) is an essential cofactor for activation of proteins involved in mitochondria quality control, such as Sirtuin3 (SIRT3). Our previous study has found that NAD+ supplement could rescue early life stress (ELS)-induced neuroinflammation and down-regulation of SIRT3 in adult offspring. However, it is unclear whether SIRT3 is the key to the neuroprotective effects of NAD+ supplement in this animal model of schizophrenia. The present study used 24 h maternal separation (MS) as ELS to Wistar rat pups on the postnatal day (PND) 9. Schizophrenia-like behaviors and memory impairments were detected by behavioral tests. Microglial activation, pro-inflammatory cytokine expression, and NAD+/SIRT3 expression were detected in the prefrontal cortex and hippocampus. Meanwhile, NAM (a precursor of NAD+), and the SIRT3 activator Honokiol (HNK), and the SIRT3 inhibitor 3-TYP were used as an intervention in vivo. Our results showed that ELS could induce schizophrenia-like behaviors and M1 microglial activation, NAD+ decline, lower expression of SIRT3, and increased acetylated superoxide dismutase 2 expression at the adult stage. NAD+ supplement or HNK administration could block this process and normalize the behavioral alterations of the MS animals. 3-TYP administration in the control group and the NAM-treated MS rats caused M1 microglial activation and cognitive deficits. Our results demonstrated that SIRT3 mediated the stabilizing effect of NAD+ on normalizing M1 microglial activation and behavioral phenotypes in MS rats.

Discovery of a potent and selective covalent threonine tyrosine kinase (TTK) inhibitor.

Threonine tyrosine kinase (TTK) is a critical component of the spindle assembly checkpoint and plays a pivotal role in mitosis. TTK has been identified as a potential therapeutic target for human cancers. Here, we describe our design, synthesis and evaluation of a class of covalent TTK inhibitors, exemplified by 16 (SYL1073). Compound 16 potently inhibits TTK kinase with an IC50 of 0.016 µM and displays improved selectivity in a panel of kinases. Mass spectrometry analysis reveals that 16 covalently binds to the C604 cysteine residue in the hinge region of the TTK kinase domain. Furthermore, 16 achieves strong potency in inhibiting the growth of various human cancer cell lines, outperforming its relative reversible inhibitor, and eliciting robust downstream effects. Taken together, compound 16 provides a valuable lead compound for further optimization toward the development of drug for treatment of human cancers.

CSGALNACT2 restricts ovarian cancer migration and invasion by modulating MAPK/ERK pathway through DUSP1.

PURPOSE: Ovarian cancer is one of the leading causes of cancer-related death among women. CSGALNACT2 is a vital Golgi transferase and is related to a variety of human diseases. However, its expression pattern and function in ovarian cancer remain uncertain. METHODS: The Cancer Genome Atlas and GEPIA databases were used to assess the expression of CSGALNACT2 in ovarian cancer patients. RNA-seq, qRT-PCR, and IHC were used to verify the expression of CSGALNACT2 in ovarian cancer tissues. Then, in vivo and in vitro experiments were conducted to evaluate the role of CSGALNACT2 in the progression of ovarian cancer. RNA-seq and GSEA were used to reveal the potential biological function and oncogenic pathways of CSGALNACT2. RESULTS: We demonstrated that the mRNA expression and protein level of CSGALNACT2 were significantly downregulated in ovarian cancer and ovarian cancer metastatic tissues. CSGALNACT2 can significantly inhibit the migration, invasion, and clonogenic growth of ovarian cancer in vitro and is progressively lost during ovarian cancer progression in vivo. CSGALNACT2 suppresses ovarian cancer migration and invasion via DUSP1 modulation of the MAPK/ERK pathway through RNA-seq, KEGG analysis, and Western blotting. Moreover, CSGALNACT2 expression was correlated with immune cell infiltration and had prognostic value in different immune cell-enriched or decreased ovarian cancer. In addition, patients with CSGALNACT2 downregulation are less likely to benefit from immunotherapy. CONCLUSION: As an ovarian cancer suppressor gene, CSGALNACT2 inhibits the development of ovarian cancer, and it might be used as a prognostic biomarker in patients with ovarian cancer.

Capsaicin alleviates neuronal apoptosis and schizophrenia-like behavioral abnormalities induced by early life stress.

Early life stress (ELS) is associated with the later development of schizophrenia. In the rodent model, the maternal separation (MS) stress may induce neuronal apoptosis and schizophrenia-like behavior. Although the TRPV1 agonist capsaicin (CAP) has been reported to reduce apoptosis in the central nervous system, its effect in MS models is unclear. Twenty-four hours of MS of Wistar rat pups on postnatal day (PND9) was used as an ELS. Male rats in the adult stage were the subjects of the study. CAP (1 mg/kg/day) intraperitoneal injection pretreatment was undertaken before behavioral tests for 1 week and continued during the tests. Behavioral tests included open field, novel object recognition, Barnes maze test, and pre-pulse inhibition (PPI) test. MS rats showed behavioral deficits and cognitive impairments mimicking symptoms of schizophrenia compared with controls. MS decreased the expression of TRPV1 in the frontal association cortex (FrA) and in the hippocampal CA1, CA3, and dentate gyrus (DG) regions compared with the control group resulting in the increase of pro-apoptotic proteins (BAX, Caspase3, Cleaved-Caspase3) and the decrease of anti-apoptotic proteins (Bcl-2). The number of NeuN++TUNEL+ cells increased in the MS group in the FrA, CA1, CA3, and DG compared with the control group. Neuronal and behavioral impairments of MS were reversed by treatment with CAP. Exposure to ELS may lead to increased neuronal apoptosis and impaired cognitive function with decreased TRPV1 expression in the prefrontal cortex and hippocampus in adulthood. Sustained low-dose administration of CAP improved neuronal apoptosis and cognitive function. Our results provide evidence for future clinical trials of chili peppers or CAP as dietary supplements for the reversal treatment of schizophrenia.