Non-alcoholic steatohepatitis (NASH), an emerging global healthcare problem, has become the leading cause of liver transplantation in recent decades. No effective therapies in the clinic have been proven due to the incomplete understanding of the pathogenesis of NASH, and further studies are expected to continue to delve into the mechanisms of NASH. Extracellular vesicles (EVs), which are small lipid membrane vesicles carrying proteins, microRNAs and other molecules, have been identified to play a vital role in cell-to-cell communication and are involved in the development and progression of various diseases. In recent years, there has been increasing interest in the role of EVs in NASH. Many studies have revealed that EVs mediate important pathological processes in NASH, and the role of EVs in NASH is distinct and variable depending on their origin cells and target cells. This review outlines the emerging mechanisms of EVs in the development of NASH and the preclinical evidence related to stem cell-derived EVs as a potential therapeutic strategy for NASH. Moreover, possible strategies involving EVs as clinical diagnostic, staging and prognostic biomarkers for NASH are summarized.

Background The aim of this study is to design a deep learning (DL) model to preoperatively predict the occurrence of central lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC). Methods This research collected preoperative ultrasound (US) images and clinical factors of 611 PTMC patients. The clinical factors were analyzed using multivariate regression. Then, a DL model based on US images and clinical factors was developed to preoperatively predict CLNM. The model’s efficacy was evaluated using the receiver operating characteristic (ROC) curve, along with accuracy, sensitivity, specificity, and the F1 score. Results The multivariate analysis indicated an independent correlation factors including age ≥55 (OR = 0.309, p < 0.001), tumor diameter (OR = 2.551, p = 0.010), macrocalcifications (OR = 1.832, p = 0.002), and capsular invasion (OR = 1.977, p = 0.005). The suggested DL model utilized US images achieved an average area under the curve (AUC) of 0.65, slightly outperforming the model that employed traditional clinical factors (AUC = 0.64). Nevertheless, the model that incorporated both of them did not enhance prediction accuracy (AUC = 0.63). Conclusions The suggested approach offers a reference for the treatment and supervision of PTMC. Among three models used in this study, the deep model relied generally more on image modalities than the data modality of clinic records when making the predictions.

Preoperative chemotherapy can help to downstage cancer, while postoperative chemotherapy can potentially reduce the risk of cancer recurrence or metastasis. However, as the number of chemotherapy sessions or drug dose increases, patients may develop different degrees of drug resistance. Traditional Chinese Medicine (TCM) holds that the main cause of breast cancer formation and development is “qi stagnation and blood stasis”. Treatment can be initiated by invigorating qi and activating blood flow. Astragalus membranaceus and Panax notoginseng belong to the traditional Chinese herbs used to promote qi and blood circulation. Astragaloside IV (AST IV) and Panax notoginseng saponins (PNS) are important active ingredients of TCM with cardiovascular and cerebrovascular effects, respectively. These compounds have various functions, including tonifying qi and rising Yang, consolidating surface, reducing perspiration, benefiting water retention, reducing swelling, promoting body fluid, and nourishing blood. Through animal experiments, we found that the total compound of Astragalus notoginseng can effectively improve the inflammatory state and hypoxia state of breast cancer xenografts in nude mice, as well as reduce tumor volume. These results suggest that astragalus and Panax notoginseng compound glycosides can reverse the chemoresistance to a certain extent. The effectiveness of astragaloside and Panax notoginseng compound glycosides in reversing chemoresistance may be attributed to their active components, such as AST IV and PNS, which can regulate HIF-1α/MDR1, and improve the hypoxia of tumor cells. Therefore, this study suggests that Astragalus and Panax notoginseng compound glycosides have potential value in the treatment of chemoresistance of breast cancer.

3147 Background: Immune checkpoint inhibitors have opened a new chapter in cancer therapy, but the incidence of irAEs caused by them is high, and severe irAEs can be fatal. The current research on irAEs is almost focused on early predictions, and there is a lack of near-term predictions (the cycle before the occurrence of irAEs). Absolute eosinophil count (EO#) has been reported to be associated with immune-related pneumonia, but its association with other systemic irAEs requires further exploration. The aim of this study was to explore the near-term predictive value of neutrophil/lymphocyte (NLR), platelet/lymphocyte (PLR), and EO# for PD-1 inhibitor-induced irAEs. Methods: The data are from tumor patients who received PD-1 inhibitor therapy in our department from July 2019 to May 2021. A total of 146 cases were included, of which 56 had irAEs. The data of NLR, PLR and EO# in the cycle before the occurrence of irAEs (the median number of cycles was the second cycle) were collected, and the data of the second cycle was used as the control for patients without irAEs group. Logistic method was used to analyze the correlation between NLR, PLR and EO# and irAEs, and a predictive model was constructed. The sensitivity and specificity of the model were evaluated by ROC curve. This study was registered on Chinese Clinical Trail Registry (ChiCTR2100049849). Results: A total of 146 tumor patients were included, of which 56 developed at least one irAEs. Grade 1-2 irAEs occurred in 39 cases, grade 3-4 in 12 cases (including cardiac, liver, lung and skin toxicity), grade 5 in 2 cases(including cardiac and lung toxicity), and ungraded in 3 cases. The data of the cycle before the occurrence of irAEs were analyzed. Univariate analysis showed that NLR (odds ratio [OR], 1.4, p< 0.05) and EO# (OR, 12.6, p< 0.05) were associated with irAEs, and multivariate analysis suggested NLR (OR, 1.7, p< 0.001) and EO# (OR, 20.4, p< 0.05) were independent risk factors for irAEs. The prediction model composed of NLR, PLR and EO# had a correct rate of 76.7% (AUC = 0.752) in predicting the occurrence of irAEs in the near-term cycle, with a sensitivity of 51.8% and a specificity of 92.2%; the correct rate of predicting irAEs of grade 3 and above was as high as 91.9% (AUC = 0.778), the sensitivity was 14.3% and the specificity was 99.2%. Conclusions: The model composed of NLR, PLR and EO# may predict the occurrence of irAEs in the near-term cycle, especially the prediction of irAEs above grade 3, which can provide early warning for the occurrence of irAEs. Clinical trial information: ChiCTR2100049849.

Background: NDUFA4L2 is overexpressed in VHL-deficient cell lines and neuroblastoma. The clinical significance of NDUFA4L2 in clear cell renal cell carcinoma (ccRCC) has not been well studied. Therefore, we evaluated the prognostic value of NDUFA4L2 in ccRCC patients.Methods: In our study, NDUFA4L2 expression in 86 cases of ccRCC and adjacent normal tissues was monitored by immunohistochemistry, semi-quantitative RT-PCR, and Western blot analyses. The relationship between NDUFA4L2 expression and the clinical features of ccRCC was assessed.Results: The results showed that NDUFA4L2 protein expression was found to be higher in ccRCC tissues 81.4% (70/86) than in normal tissues 26.7% (23/86) (p=0.021). The average level of NDUFA4L2 mRNA expression was found to be 122.236.018 and 21.34 +/- 1.036 in ccRCC tissue and adjacent normal tissue (p<0.001). NDUFA4L2 expression levels were correlated with some clinical features of ccRCC. Multivariate analysis showed NDUFA4L2 expression was an independent prognostic factor for ccRCC patients.Conclusions: Our study has provided the significant clinical relevance of NDUFA4L2 in ccRCC and suggested that ccRCC patients with NDUFA4L2 overexpression may be suitable as a potential therapeutic target for ccRCC patients.