Image1_VitroGel-loaded human MenSCs promote endometrial regeneration and fertility restoration.JPEG

Introduction: Intrauterine adhesions (IUA), also known as Asherman's syndrome, is caused by trauma to the pregnant or non-pregnant uterus, which leads to damaged endometrial basal lining and partial or total occlusion of the uterine chambers, resulting in abnormal menstruation, infertility, or recurrent miscarriage. The essence of this syndrome is endometrial fibrosis. And there is no effective treatment for IUA to stimulate endometrial regeneration currently. Recently, menstrual blood-derived stem cells (MenSCs) have been proved to hold therapeutic promise in various diseases, such as myocardial infarction, stroke, diabetes, and liver cirrhosis.Methods: In this study, we examined the effects of MenSCs on the repair of uterine adhesions in a rat model, and more importantly, promoted such therapeutic effects via a xeno-free VitroGel MMP carrier.Results: This combined treatment reduced the expression of inflammatory factors, increased the expression of anti-inflammatory factors, restricted the area of endometrial fibrosis, diminished uterine adhesions, and partially restored fertility, showing stronger effectiveness than each component alone and almost resembling the sham group.Discussion: Our findings suggest a highly promising strategy for IUA treatment.</p

Additional file 1 of High efficacy of PD-1 inhibitor after initial failure of PD-L1 inhibitor in Relapsed/Refractory classical Hodgkin Lymphoma

Additional file 1

DataSheet_1_Artificial Intelligence-Assisted Score Analysis for Predicting the Expression of the Immunotherapy Biomarker PD-L1 in Lung Cancer.docx

Programmed cell death ligand 1 (PD-L1) is a critical biomarker for predicting the response to immunotherapy. However, traditional quantitative evaluation of PD-L1 expression using immunohistochemistry staining remains challenging for pathologists. Here we developed a deep learning (DL)-based artificial intelligence (AI) model to automatically analyze the immunohistochemical expression of PD-L1 in lung cancer patients. A total of 1,288 patients with lung cancer were included in the study. The diagnostic ability of three different AI models (M1, M2, and M3) was assessed in both PD-L1 (22C3) and PD-L1 (SP263) assays. M2 and M3 showed improved performance in the evaluation of PD-L1 expression in the PD-L1 (22C3) assay, especially at 1% cutoff. Highly accurate performance in the PD-L1 (SP263) was also achieved, with accuracy and specificity of 96.4 and 96.8% in both M2 and M3, respectively. Moreover, the diagnostic results of these three AI-assisted models were highly consistent with those from the pathologist. Similar performances of M1, M2, and M3 in the 22C3 dataset were also obtained in lung adenocarcinoma and lung squamous cell carcinoma in both sampling methods. In conclusion, these results suggest that AI-assisted diagnostic models in PD-L1 expression are a promising tool for improving the efficiency of clinical pathologists.</p

Additional file 1: of Dysregulation of miR-6868-5p/FOXM1 circuit contributes to colorectal cancer angiogenesis

Figure S1. (A) qRT-PCR analysis of the expression of indicated miRNAs in HCT8 and HCT116 cells. (B & C) Transfection efficiency was measured by qRT-PCR. *p < 0.05, **p < 0.01. Figure S2. (A) Western blot analysis of FOXM1 expression in HCT116 cells transfected with empty control vector or FOXM1 expressing plasmid. (B) HUVECswere treatedwith the CM from indicated cells, and subjected to wound healing assay. Scale bar = 20 μm. (C) Xenografted tumors were excised at week 3 post the inoculation, and the tumor weight from different groups was compared. (D) Western blot analysis of FOXM1 expression in HCT116 cells transfected with shNC, sh1 and sh2 against FOXM1. (E) HUVECs were treated with the CM from HCT116 cells transfected with indicated vectors. Cell viability of HUVECs was measured by CCK8 assay. (F) HUVECs were co-cultured with HCT116 cells transfected with indicated vectors in transwell apparatus. Migrated HUVECs were quantified after co-culture for 24 h. Scale bar = 20 μm. (G) HUVECs were treated with the CM from indicated cells, and subjected to tube formation assay. Scale bar = 20 μm. *p < 0.05, **p < 0.01. Figure S3. The bivariate relation between the mRNA levels of FOXM1 and IL-8 in CRC samples from GEO dataset was assessed by Pearson’s correlation test. Figure S4. (A) qRT-PCR analysis of pre-miR-6868 expression in HCT116 cells with FOXM1 overexpression. (B) HCT8 and HCT116 cells were treated with 5-Azd (10 μM). The miR-6868-5p levels were examined by qRT-PCR after 48 h. miR-375 was used as positive control. (C) Western blot analysis of H3K27me3 expression in HCT116 cells upon GSK126 treatment. *p < 0.05, **p < 0.01. Figure S5. (A) The bivariate relation between the EXOC7 mRNA levels and miR-6868-5p levels in CRC samples was assessed by Pearson’s correlation test. (B) qRT-PCR analysis of pre-miR-6868 and miR-6868-5p expression in cells transfected with siNC or siDrosha. (C) qRT-PCR analysis of EXOC7 expression in HCT116 cells with FOXM1 overexpression. Table S1. Number of predicted binding sites in FOXM1 3’-UTR. Table S2. Sequences of primers used for qRT-PCR in this study. Table S3. Sequences of primers used for ChIP-qPCR in this study. Table S4. Correlation between miR-6868-5p expression and TNM stage in CRC samples. (DOCX 12322 kb