Ginsenoside Rk3 Regulates Tryptophan Metabolism along the Brain-Gut Axis by Targeting Tryptophan Hydroxylase and Remodeling the Intestinal Microenvironment to Alleviate Depressive-Like Behavior in Mice.

Depression is a neuropsychiatric disease that significantly impacts the physical and mental health of >300 million people worldwide and places a major burden on society. Ginsenosides are the main active ingredient in ginseng and have been proven to have various pharmacological effects on the nervous system. Herein, we investigated the antidepressant effect of ginsenoside Rk3 and its underlying mechanism in a murine model of depression. Rk3 significantly improved depression-like behavior in mice, ameliorated the disturbance of the hypothalamus-pituitary-adrenal axis, and alleviated neuronal damage in the hippocampus and prefrontal cortex of mice. Additionally, Rk3 improved the abnormal metabolism of tryptophan in brain tissue by targeting tryptophan hydroxylase, thereby reducing neuronal apoptosis and synaptic structural damage in the mouse hippocampus and prefrontal cortex. Furthermore, Rk3 reshaped the composition of the gut microbiota of mice and regulated intestinal tryptophan metabolism, which alleviated intestinal barrier damage. Thus, this study provides valuable insights into the role of Rk3 in the tryptophan metabolic cycle along the brain-gut axis, suggesting that Rk3 may have the potential for treating depression.

Expression of Multicopy Tandem Recombinant Ginseng Hexapeptide in Bacillus subtilis and the Evaluation of Antiaging Activity.

Ginseng oligopeptides are naturally occurring small-molecule peptides extracted from ginseng that exhibit positive effects on health and longevity. However, the current industrial production of ginseng oligopeptides primarily relies on plant extraction and chemical synthesis. In this study, we proposed a novel genetic engineering approach to produce active ginseng peptides through multicopy tandem insertion (5 and 15 times). The recombinant ginseng peptides were successfully produced from engineered Bacillus subtilis with an increasing yield from 356.55 to 2900 mg/L as the repeats multiple. Additionally, an oxidative stress-induced aging model caused by H2O2 was established to evaluate whether the recombinant ginseng peptides, without enzymatic hydrolysis into individual peptides, also have positive effects on antiaging. The results demonstrated that all two kinds of recombinant ginseng peptides could also delay cellular aging through various mechanisms, such as inhibiting cell cycle arrest, suppressing the expression of pro-inflammatory factors, and enhancing cellular antioxidant capacity.

Ginsenoside Rk1 induces autophagy-dependent apoptosis in hepatocellular carcinoma by AMPK/mTOR signaling pathway.

Hepatocellular carcinoma (HCC) is the third most lethal cancer in the world. Recent studies have shown that suppression of autophagy plays an important role in the development of HCC. Ginsenoside Rk1 is a protopanaxadiol saponin isolated from ginseng and has a significant anti-tumor effect, but its role and mechanism in HCC are still unclear. In this study, a mouse liver cancer model induced by diethylnitrosamine and carbon tetrachloride (DEN + CCl4) was employed to investigate the inhibitory effect of Rk1 on HCC. The results demonstrate that ginsenoside Rk1 effectively inhibits liver injury, liver fibrosis, and cirrhosis during HCC progression. Transcriptome data analysis of mouse liver tissue reveals that ginsenoside Rk1 significantly regulates the AMPK/mTOR signaling pathway, autophagy pathway, and apoptosis pathway. Subsequent studies show that ginsenoside Rk1 induces AMPK protein activation, upregulates the expression of autophagy marker LC3-II protein to promote autophagy, and then downregulates the expression of Bcl2 protein to trigger a caspase cascade reaction, activating AMPK/mTOR-induced toxic autophagy to promote cells death. Importantly, co-treatment of ginsenoside Rk1 with autophagy inhibitors can inhibit apoptosis of HCC cells, once again demonstrating the ability of ginsenoside Rk1 to promote autophagy-dependent apoptosis. In conclusion, our study demonstrates that ginsenoside Rk1 inhibits the development of primary HCC by activating toxic autophagy to promote apoptosis through the AMPK/mTOR pathway. These findings confirm that ginsenoside Rk1 is a promising new strategy for the treatment of HCC.

Machine Learning Model Based on the Neutrophil-to-Eosinophil Ratio Predicts the Recurrence of Hepatocellular Carcinoma After Surgery.

Background: Circulating eosinophils are associated with tumor development. An eosinophil-related index, the neutrophil to eosinophil ratio (NER), can be used to predict the prognosis of patients with tumors. However, there is still a lack of efficient prognostic biomarkers for HCC. In this study, we aimed to investigate the predictive value of the NER and develop an optimal machine learning model for the recurrence of HCC patients. Patients and methods: A retrospective collection of 562 patients who underwent hepatectomy with a pathologic diagnosis of HCC was performed. The relationship between NER and progression-free survival (PFS) was investigated. We developed a new machine learning framework with 10 machine learning algorithms and their 101 combinations to select the best model for predicting recurrence after hepatectomy. The performance of the model was assessed by the area under the curve (AUC) of characteristics and calibration curves, and clinical utility was evaluated by decision curve analysis (DCA). Results: Kaplan‒Meier curves showed that the PFS in the low NER group was significantly better than that in the high NER group. Multivariate Cox regression analysis showed that NER was an independent risk factor for recurrence after surgery. The random survival forests (RSF) model was selected as the best model that had good predictive efficacy and outperformed the TNM, BCLC, and CNLC staging systems. Conclusion: The NER has good predictive value for postoperative recurrence in patients with hepatocellular carcinoma. Machine learning model based on NER can be used for accurate predictions.

"Percentage" and "size" of residual viable tumor in lymph node, the performance in estimating pathologic response of lymph node in non-small cell lung cancer treated with neoadjuvant chemoimmunotherapy.

There is no universally accepted method for evaluating lymph node metastasis (LNM) in non-small cell lung cancer (NSCLC) after neoadjuvant chemoimmunotherapy. Different protocols recommend evaluating the percentage of residual viable tumor (RVT%) and metastatic tumor size (MTS). Our aim was to determine the prognostic significance of RVT% and MTS, and identify the more effective parameter for pathological evaluating LNM. Two independent cohorts were collected (derivation, n = 84; external validation, n = 42). All patients exhibited metastatic cancer or treatment response in lymph nodes post-surgery. In the derivation cohort, we assessed the mean and largest values of MTS and RVT% in LNM, estimating their optimal cutoffs for event-free survival (EFS) using maximally selected rank statistics. Validation was subsequently conducted in the external validation cohort. The quality of prognostic factors was evaluated using the Area Under Curve (AUC). A positive association was identified between RVT% and MTS, but an absolute association could not be conclusively established. In the derivation cohort, neither the largest MTS (cutoff = 6 mm, p = 0.28), largest RVT% (cutoff = 75%, p = 0.23), nor mean RVT% (cutoff = 55%, p = 0.06) were associated with EFS. However, mean MTS (cutoff = 4.5 mm) in lymph nodes was statistically associated with EFS (p = 0.018), validated by the external cohort (p = 0.017). The prognostic value of MTS exceeded that of ypN staging in both cohorts, as evidenced by higher AUC values. The mean value of MTS can effectively serve as a parameter for the pathological evaluation of lymph nodes, with a threshold of 4.5 mm, closely linked to EFS. Its prognostic value outperforms that of ypN staging.

Performance of the digital cell morphology analyzer MC-100i in a multicenter study in tertiary hospitals in China.

BACKGROUND: This study investigated the performance of the MC-100i, a pre-commercial digital morphology analyzer utilizing a convolutional neural network algorithm, in a multicentric setting involving up to 11 tertiary hospitals in China. METHODS: Blood smears were analyzed by MC-100i, verified by morphologists, and manually differentiated. The classification performance on WBCs and RBCs was evaluated by comparing the classification results using different methods. The PLT and PLT clump counting performance was also assessed. The total assay time including hands-on time was evaluated. RESULTS: The agreements between pre- and post-classification were high for normal WBCs (κ > 0.96) and lower for overall abnormal WBCs (κ = 0.90). The post-classification results correlated well with manual differentials for both normal and abnormal WBCs (r > 0.93), except for basophils (r = 0.8480) and atypical lymphocytes (r = 0.8211). The clinical sensitivity and specificity of each RBC abnormality after verification were above 90 % using microscopy reviews as the reference. The PLTs counted by the MC-100i before and after verification correlated well with those measured by the PLT-O mode (r = 0.98). Moreover, PLT clumps were successfully classified by the analyzer in EDTA-dependent pseudothrombocytopenia blood samples. CONCLUSIONS: The MC-100i is an accurate and reliable digital cell morphology analyzer, offering another intelligent option for hematology laboratories.

Predictive value of hepatitis B serological indicators for mortality among cancer survivors and validation in a gastric cancer cohort.

Hepatitis B virus (HBV) infection has gradually been considered to associate with cancer development and progression. This study aimed to explore the associations of serological indicators of HBV infection with mortality risk among cancer survivors and further validated using a gastric cancer (GC) cohort from China, where HBV infection is endemic. National Center for Health Statistics' National Health and Nutrition Examination Survey (NHANES) data were used in this study. Individuals with positive results of hepatitis B core antigen (anti-HBc) were considered to have current or past HBV infection. Serological indicators were positive only for hepatitis B surface antibodies (anti-HBs), indicating vaccine-induced immunity, whereas negativity for all serologic indicators was considered to indicate the absence of HBV infection and immunity to HBV. The GC cohort included patients from the First Hospital of Jilin University, China. The median follow-up time of the NHANES was 10 years; during the follow-up, 1505 deaths occurred. The results revealed that anti-HBs-positive cancer survivors had a 39% reduced risk of mortality (hazard ratio [HR] 0.61, 95% confidence interval [CI] 0.44-0.85). Men and individuals aged <65 years old with past exposure to HBV had higher mortality risk (HR 1.52, 95% CI 1.09-2.13; HR 2.07, 95% CI 1.13-3.83). In this GC cohort, individuals who were only anti-HBs-positive showed a reduced risk of mortality (HR 0.77, 95% CI 0.62-0.95). Thus, anti-HBs positivity was a significant factor of decreased mortality among cancer survivors. More rigorous surveillance is necessary for cancer survivors with anti-HBc positivity, particularly men, and younger individuals.