Steam explosion-assisted grinding improves the functional properties and antioxidant activity of Java tea-leaf powders (Clerodendranthus spicatus).

BACKGROUND: Java tea is widely consumed and has multiple health effects. This study established a steam explosion (SE) pretreatment method to prepare Java tea-leaf powders. The physicochemical, functional properties, phenolic extraction, and antioxidant activity of Java tea-leaf powders produced by simple and SE-assisted milling methods were investigated. RESULTS: In comparison with simple milling, SE pretreatment broke the cell wall effectively and reduced the particle size of Java tea-leaf powders. Steam explosion-treated powders showed higher values for sensory signals, bulk and tap density, and for the water solubility index. After SE treatment, the adsorption capacities to glucose, soybean oil, and cholesterol of leaf powders were increased by up to 55, 95, and 80% respectively. The extracts from SE-treated powders also showed higher total polyphenol content and antioxidant activity. CONCLUSION: Steam explosion treatment is helpful for the improvement of functional properties and antioxidant activity, which can benefit the development and application of Java tea-leaf powders. © 2024 Society of Chemical Industry.

Novel ethylenediamine-ß-cyclodextrin grafted membranes for the chiral separation of mandelic acid and its derivatives.

In the present study, flat cellulose acetate ultrafiltration membranes were prepared first by nonsolvent induced phase separation method. Then chiral membranes for separating the enantiomers were prepared by grafting the ultrafiltration membranes using ethylenediamine-ß-cyclodextrin as the chiral selector and epichlorohydrin as the spacer arm. The pure water permeability of the ultrafiltration membrane was around 115 L·m-2·h-1·bar-1. The properties of the chiral membranes were characterized using infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). The chiral membrane performance in enantiomer separation was evaluated with racemates, such as mandelic acid (MA), 2-chloromandelic acid (2-ClMA), 4-chloromandelic acid (4-ClMA), and methyl mandelate (MM). The influence of feed concentration on the separation efficiency was also investigated. The results indicated that the enantiomeric excess percentages (e.e%) of the racemic mixtures for these four chiral compounds were up to 31.8%, 25.4%, 17.8%, and 32.6%, respectively. The binding free energy of the chiral selector with the (S)-enantiomer calculated by molecular dynamics simulations was stronger than that with the (R)-enantiomer, which was consistent with the experimental results (higher concentration of (R)-enantiomer in the permeate). This supports the affinity absorption-separation mechanism.

Engineered Bacterial Biomimetic Vesicles Reprogram Tumor-Associated Macrophages and Remodel Tumor Microenvironment to Promote Innate and Adaptive Antitumor Immune Responses.

Tumor-associated macrophages (TAMs) are among the most abundant infiltrating leukocytes in the tumor microenvironment (TME). Reprogramming TAMs from protumor M2 to antitumor M1 phenotype is a promising strategy for remodeling the TME and promoting antitumor immunity; however, the development of an efficient strategy remains challenging. Here, a genetically modified bacterial biomimetic vesicle (BBV) with IFN-γ exposed on the surface in a nanoassembling membrane pore structure was constructed. The engineered IFN-γ BBV featured a nanoscale structure of protein and lipid vesicle, the existence of rich pattern-associated molecular patterns (PAMPs), and the costimulation of introduced IFN-γ molecules. In vitro, IFN-γ BBV reprogrammed M2 macrophages to M1, possibly through NF-κB and JAK-STAT signaling pathways, releasing nitric oxide (NO) and inflammatory cytokines IL-1ß, IL-6, and TNF-α and increasing the expression of IL-12 and iNOS. In tumor-bearing mice, IFN-γ BBV demonstrated a targeted enrichment in tumors and successfully reprogrammed TAMs into the M1 phenotype; notably, the response of antigen-specific cytotoxic T lymphocyte (CTL) in TME was promoted while the immunosuppressive myeloid-derived suppressor cell (MDSC) was suppressed. The tumor growth was found to be significantly inhibited in both a TC-1 tumor and a CT26 tumor. It was indicated that the antitumor effects of IFN-γ BBV were macrophage-dependent. Further, the modulation of TME by IFN-γ BBV produced synergistic effects against tumor growth and metastasis with an immune checkpoint inhibitor in an orthotopic 4T1 breast cancer model which was insensitive to anti-PD-1 mAb alone. In conclusion, IFN-γ-modified BBV demonstrated a strong capability of efficiently targeting tumor and tuning a cold tumor hot through reprogramming TAMs, providing a potent approach for tumor immunotherapy.

De-Epithelialized Viable Tracheal Allotransplantation Without Immunosuppressants: 5-Year Follow-Up.

OBJECTIVE: Tracheal transplantation could be a better option for patients with long segmental laryngotracheal stenosis or defects, but the need for immunosuppressants limits its widespread use due to the antigenicity of the tracheal epithelium. Chemically treated or cryopreserved nonviable tracheal allografts have no immunogenicity but lead to necrosis and stenosis in long-term outcomes. The present report describes the 5-year outcomes of de-epithelialized viable tracheal allotransplantation without immunosuppressants in a patient with severe laryngotracheal stenosis. METHODS: The recipient was a 47-year-old female with relapsing polychondritis affecting the larynx and cervical trachea and producing a 5 cm long stenosis that could not be repaired using resection and anastomosis. A tracheal allograft was obtained from a 45-year-old male donor and treated with a combination of 3% sodium dodecyl sulfate (SDS) and organ preservation solution for 138 hours. The allograft was revascularized by heterotopical implantation in the infrahyoid muscles of the recipient for 3 months and then transplantation to the laryngotracheal defect with a split-thickness skin graft sutured to the lumen and a silicon T-tube. No immunosuppressants were used postoperatively. RESULTS: The allograft was de-epithelialized, and most of the cartilage rings remained viable after the treatment. The allograft was revascularized, viable, and mechanically stable after 3 months of heterotopic implantation. No apparent signs of rejection or destruction were observed. The T-tube was removed, and the internal lining of the allograft was repopulated 4 months after orthotopic transplantation, despite the skin graft necrotizing at 2 weeks. Endoscopy and computed tomography showed a patent airway 5 years after orthotopic transplantation. The patient was able to resume her usual quality of life. CONCLUSION: The present study demonstrates that transplantation of the de-epithelialized viable tracheal allograft without immunosuppressants is safe and promising for patients with long laryngotracheal stenosis or defects, especially for those with malignant tumor resections.

Physical properties, phenolic profile and antioxidant capacity of Java tea (Clerodendranthus spicatus) stems as affected by steam explosion treatment.

Java tea (Clerodendranthus spicatus) has been favored for its various health benefits and abundance of phenolic substances. Steam explosion (SE) treatment was performed in the pretreatment of Java tea stems and the physical properties, phenolic profile and antioxidant capacity were investigated. Extraction kinetics study showed that the phenolics yields of Java tea stems treated at 2.4 MPa for 10 min reached the maximum in 40 min, which was approximately 3 times the yields of raw stems in 180 min. The antioxidant activities of the extracts of Java tea stems were also significantly increased after SE treatment (P < 0.05). In addition, 19 phenolics were detected in Java tea stems by HPLC/QTOF-MS/MS, and rosmarinic acid was found to be hydrolyzed to danshensu during the SE process. SE could be an efficient pretreatment technology to improve the extraction rates of phenolics and conversions of their high-value hydrolyzed products, which could facilitate further research of Java tea products.

Fabrication and characterization of a novel zein/pectin/pumpkin seed oil Pickering emulsion and the effects of myricetin on oxidation stability.

In this study, zein/pectin/pumpkin seed oil (PSO) Pickering emulsions (ZPPEs) were fabricated loading with myricetin (MYT), and the quality control methods of oxidation stability were innovatively investigated. The microstructure and particle properties of zein-pectin particles were determined. The zein to pectin ratio of 5:3 and oil phase fraction (φ = 50 %) turned out as the most optimal conditions for the stabilization of myricetin-loaded ZPPEs. The expected oil-in-water emulsion-type structure was confirmed by confocal laser scanning microscopy (CLSM). The internal 3D structure of Pickering emulsions (Lugol's solution improved the water-phase contrast) was imaged by micro-computed tomography (Micro-CT) for the first time. Results showed a sponge like structure of water phase in emulsion with 42 µm as mean droplet size. Light-induced oxidation was evaluated with the PetroOxy method and malondialdehyde (MDA) assays. Encapsuling ZPPEs with MYT could prevent the light induced oxidation, especially, loading of MYT at the core of the emulsion. The analysis of Electronic nose (E-nose) was used to analyze the odor before and after UV-induced oxidation, and showed a good discrimination. This study provided a new approach to prepare ZPPEs with high oxidation stability. Micro-CT, PetroOxy and E-nose could be new methods for characterization and quality assessment of Pickering emulsions.

Single-cell transcriptome analysis indicates fatty acid metabolism-mediated metastasis and immunosuppression in male breast cancer.

Male breast cancer (MBC) is a rare but aggressive malignancy with cellular and immunological characteristics that remain unclear. Here, we perform transcriptomic analysis for 111,038 single cells from tumor tissues of six MBC and thirteen female breast cancer (FBC) patients. We find that that MBC has significantly lower infiltration of T cells relative to FBC. Metastasis-related programs are more active in cancer cells from MBC. The activated fatty acid metabolism involved with FASN is related to cancer cell metastasis and low immune infiltration of MBC. T cells in MBC show activation of p38 MAPK and lipid oxidation pathways, indicating a dysfunctional state. In contrast, T cells in FBC exhibit higher expression of cytotoxic markers and immune activation pathways mediated by immune-modulatory cytokines. Moreover, we identify the inhibitory interactions between cancer cells and T cells in MBC. Our study provides important information for understanding the tumor immunology and metabolism of MBC.

Learning how to detect: A deep reinforcement learning method for whole-slide melanoma histopathology images.

Cutaneous melanoma represents one of the most life-threatening malignancies. Histopathological image analysis serves as a vital tool for early melanoma detection. Deep neural network (DNN) models are frequently employed to aid pathologists in enhancing the efficiency and accuracy of diagnoses. However, due to the paucity of well-annotated, high-resolution, whole-slide histopathology image (WSI) datasets, WSIs are typically fragmented into numerous patches during the model training and testing stages. This process disregards the inherent interconnectedness among patches, potentially impeding the models' performance. Additionally, the presence of excess, non-contributing patches extends processing times and introduces substantial computational burdens. To mitigate these issues, we draw inspiration from the clinical decision-making processes of dermatopathologists to propose an innovative, weakly supervised deep reinforcement learning framework, titled Fast medical decision-making in melanoma histopathology images (FastMDP-RL). This framework expedites model inference by reducing the number of irrelevant patches identified within WSIs. FastMDP-RL integrates two DNN-based agents: the search agent (SeAgent) and the decision agent (DeAgent). The SeAgent initiates actions, steered by the image features observed in the current viewing field at various magnifications. Simultaneously, the DeAgent provides labeling probabilities for each patch. We utilize multi-instance learning (MIL) to construct a teacher-guided model (MILTG), serving a dual purpose: rewarding the SeAgent and guiding the DeAgent. Our evaluations were conducted using two melanoma datasets: the publicly accessible TCIA-CM dataset and the proprietary MELSC dataset. Our experimental findings affirm FastMDP-RL's ability to expedite inference and accurately predict WSIs, even in the absence of pixel-level annotations. Moreover, our research investigates the WSI-based interactive environment, encompassing the design of agents, state and reward functions, and feature extractors suitable for melanoma tissue images. This investigation offers valuable insights and references for researchers engaged in related studies. The code is available at: https://github.com/titizheng/FastMDP-RL.

Gut microbiome-mediated glucose and lipid metabolism mechanism of star apple leaf polyphenol-enriched fraction on metabolic syndrome in diabetic mice.

BACKGROUND: Diabetes is a kind of metabolic syndrome (MetS) that seriously threatens human health globally. The leaf of star apple (Chrysophyllum cainito L.) is an incompletely explored folk medicine on diabetes. And, the effects and mechanisms on diabetes complicated glycolipid metabolism disorders are unknown till now. PURPOSE: This study aimed to investigate the constituents of star apple leaf polyphenol enriched-fraction (SAP), and elucidate their treatment effects and mechanism on diabetes and accompanied other MetS. METHODS: The components of SAP were tentatively identified by HPLC-Q-TOF-MS/MS. The antioxidant activity was determined by the scavenging of free radicals and hypoglycemic activities by inhibition of α-glucosidase in vitro. HepG2 cells were used for evaluating the alleviation effects of SAP on lipid accumulation. Streptozotocin and high-fat diet induced diabetic mice were grouped to evaluate the effects of different dosages of SAP. 16S rRNA was conducted to analysis gut microbiome-mediated glucose and lipid metabolism mechanism. RESULTS: It showed that myricitrin was one of the main active constituents of SAP. SAP not only showed low IC50 on -glucosidase (24.427± 0.626 µg/mL), OH·(3.680± 0.054 µg/mL) and ABTS· (9.155±0.234 µg/mL), but significantly induced the lipid accumulation in HepG2 cells (p < 0.05). SAP at 200 mg/kg·day significantly decreased the blood glucose, insulin and oral glucose tolerance test value (p < 0.05). The insulin resistance indexes and oxidative stress were alleviated after administration. SAP not only attenuated hepatic lipid deposition, but also reversed the hepatic glycogen storage. 16S rRNA sequencing results revealed that the interaction between SAP and gut microbiota led to the positive regulation of beneficial bacteria including Akkermansia, Unspecified S24_7, Alistipes and Unspecified_Ruminococcaceae, which might be one of the mechanisms of SAP on MetS. CONCLUSION: For the first time, this study explored the regulation effect of star apple leaf polyphenols on the hepatic glycolipid metabolism and studied the underlying mechanism from the view of gut microbiota. These findings indicated that SAP possesses great potential to serve as a complementary medicine for diabetes and associated MetS. It provided scientific evidence for folk complementary medicine on the treatment of diabetes-complicated multiple metabolic disorders.

Structural Characterization, Cytotoxicity, and the Antifungal Mechanism of a Novel Peptide Extracted from Garlic (Allium sativa L.).

Garlic (Allium sativa L.) is a traditional plant with antimicrobial activity. This study aimed to discover new antifungal peptides from garlic, identify their structure, and explore the antimicrobial mechanism. Peptides were separated by chromatography and identified by MALDI-TOF analysis. Structure and conformation were characterized by CD spectrum and NMR analysis. Mechanism studies were conducted by SEM, membrane depolarization, and transcriptomic analysis. The cytotoxicity to mammalian cells as well as drug resistance development ability were also evaluated. A novel antifungal peptide named NpRS with nine amino acids (RSLNLLMFR) was obtained. It was a kind of cationic peptide with a α-helix as the dominant conformation. NOESY correlation revealed a cyclization in the molecule. The peptide significantly inhibited the growth of Candida albicans. The mechanism study indicated that membrane destruction and the interference of ribosome-related pathways might be the main mechanisms of antifungal effects. In addition, the resistance gene CDR1 for azole was down-regulated and the drug resistance was hardly developed in 21 days by the serial passage study. The present study identified a novel antifungal garlic peptide with low toxicity and provided new mechanism information for the peptide at the gene expression level to counter drug resistance.

Characterization of the Physical Chemistry Properties of Iron-Tailing-Based Ceramsite.

In order to deal with the problems of resource waste and environmental pollution caused by solid waste, iron tailings (mainly SiO2, Al2O3 and Fe2O3) were used as the main raw material to create a type of lightweight and high-strength ceramsite. Iron tailings, dolomite (industrial grade, purity 98%) and a small amount of clay were combined in a N2 atmosphere at 1150 °C. X-ray fluorescence spectrometry (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and a themogravimetric analysis (TGA) were performed and the specific surface area was analyzed to determine the strength and adsorption of the ceramsite. The results of the XRF showed that SiO2, CaO and Al2O3 were the main components of the ceramsite, with MgO and Fe2O3 also included. The results of the XRD and SEM-EDS showed that the ceramsite contained several kinds of minerals and was mainly composed of akermanite, gehlenite and diopside, and that the morphology of the internal structure of the ceramsite was mainly massive and contained a small number of particles. The ceramsite could be used in engineering practice to improve the mechanical properties of materials and meet the requirements of actual engineering for the strength of materials. The results of the specific surface area analysis showed that the inner structure of the ceramsite was compact and that there were no large voids. The voids were mainly medium and large, with a high stability and strong adsorption ability. The TGA results showed that the quality of the ceramsite samples will continue to increase within a certain range. According to the XRD experimental results and experimental conditions, it was speculated that in the part of the ore phase containing Al, Mg or Ca in the ceramsite, the elements underwent relatively complex chemical reactions with each other, resulting in the formation of an ore phase with a higher molecular weight. This research provides the basis of characterization and analysis for the preparation of high-adsorption ceramsite from iron tailings and promotes the high-value utilization of iron tailings for waste pollution control.

Gender- and age-specific associations of childhood maltreatment with peripheral serum inflammatory cytokines in middle school students.

Background: The impact of childhood maltreatment on multiple inflammatory cytokines among middle school students remains to be elucidated. This study aimed to examine the associations of different types of childhood maltreatment with peripheral serum inflammatory cytokines (interleukin-10, interleukin-1ß, interleukin-6, interleukin-8, and tumor necrosis factor-α) in middle school students, and to explore the differences in these associations between boys and girls and between late (≥15 and<20 years) and early (≥11 and <15 years) adolescence. Methods: A total of 1122 students were recruited from a boarding middle school. Each participant was asked to respond to a detailed questionnaire on childhood maltreatment, from whom one blood sample was drawn via venous blood. Results: In the overall sample there was no association between childhood maltreatment and peripheral serum inflammatory cytokines; (2) emotional abuse was significantly correlated with IL-1ß only in girls (B = -0.16; 95% CI, -0.28~-0.03; p = 0.06); (3) in late adolescence, emotional abuse, emotional neglect, and childhood maltreatment had marked link with IL-8 (B = 0.39; 95%CI, 0.16~0.63; p = 0.01; B =0.20; 95% CI, 0.04~0.37; p = 0.08; B = 0.50; 95% CI, 0.18~0.82; p = 0.01, respectively). Conclusion: These findings also strengthened an inference regarding the effects of childhood maltreatment on inflammation of students in late adolescence.

Biochemical Composition, Antioxidant Activity and Antiproliferative Effects of Different Processed Garlic Products.

Garlic (Allium sativum L.) is a type of agricultural product that is widely used as a food spice, herb and traditional medicine. White garlic (WG) can be processed into several kinds of products, such as green garlic (GG), Laba garlic (LAG) and black garlic (BG), which have multiple health effects. In this study, GC-MS (gas chromatography-mass spectrometry), DPPH (1,1'-diphenyl-2-propionyl hydrazide) radical scavenging, hydroxyl radical scavenging and MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) in vitro assays were used to compare the composition, antioxidant and antiproliferation effects of different processed garlic extracts. The relationship between the constituents and the bioactivities was analyzed using the principal components analysis (PCA) and heatmap analysis. BG showed the highest antioxidant activity (IC50 = 0.63 ± 0.02 mg/mL) in DPPH radical assays and the highest antioxidant activity (IC50 = 0.80 ± 0.01 mg/mL) by hydroxyl radical assay. Moreover, GC-MS results showed that 12 organosulfur compounds were detected in the extracts of four garlic products, and allyl methyl trisulfide showed a positive relation with the anticancer activity on SMMC-7721 cells (hepatocellular carcinoma cells). The results suggested that the processing of garlic had a significant influence on the constituents and antioxidant effects and that GG, LAG and BG might be better candidates for the related functional food products compared to WG.

Clinical value of O-RADS combined with serum CA125 and HE4 for the diagnosis of ovarian tumours.

BACKGROUND: Ovarian tumors (OTs) are common gynecological tumors in women. It is very important to correctly distinguish benign and malignant OTs. PURPOSE: To assess the diagnostic performance of the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) and evaluate the clinical value of O-RADS combined with serum carbohydrate antigen 125 (CA125) and human epididymis protein 4 (HE4) in differentiating benign from malignant OTs. MATERIAL AND METHODS: A retrospective analysis was performed on 431 cases including pathology and clinical data. The receiver operating characteristic (ROC) curve was drawn, and sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. RESULTS: In premenopausal women, O-RADS and O-RADS combined with serum CA125 and HE4 showed sensitivity at 92.2% and 94.8%, specificity at 91.8% and 93.4%, and accuracy at 91.9% and 93.8%, respectively. In postmenopausal women, the sensitivity of O-RADS, O-RADS combined with serum CA125 and HE4 was 94.8% and 95.8%, specificity was 83.9% and 93.6%, and accuracy was 90.5% and 95.6%, respectively. The sensitivity, specificity, and accuracy of O-RADS combined with CA125 and HE4 in premenopausal and postmenopausal women were higher than that of O-RADS (P<0.05). CONCLUSION: O-RADS has high diagnostic performance in OTs. When O-RADS is combined with CA125 and HE4 in the diagnosis of OTs, the sensitivity and specificity are improved, which is helpful to improve the diagnostic efficiency of OTs and has high clinical application value.

MSINGB: A Novel Computational Method Based on NGBoost for Identifying Microsatellite Instability Status from Tumor Mutation Annotation Data.

Microsatellite instability (MSI), a vital mutator phenotype caused by DNA mismatch repair deficiency, is frequently observed in several tumors. MSI is recognized as a critical molecular biomarker for diagnosis, prognosis, and therapeutic selection in several cancers. Identifying MSI status for current gold standard methods based on experimental analysis is laborious, time-consuming, and costly. Although several computational methods based on machine learning have been proposed to identify MSI status, we need to further understand which machine learning model would favor identification for MSI and which feature subset is strongly related to MSI. On this basis, more effective machine learning-based methods can be developed to improve the performance of MSI status identification. In this work, we present MSINGB, an NGBoost-based method for identifying MSI status from tumor somatic mutation annotation data. MSINGB first evaluates the prediction performance of 11 popular machine learning algorithms and 9 deep learning models to identify MSI. Among 20 models, NGBoost, a novel natural gradient boosting method, achieves the overall best performance. MSINGB then introduces two feature selection strategies to find the compact feature subset, which is strongly related to MSI, and employs the SHAP approach to interpreting how selected features impact the model prediction. MSINGB achieves a better prediction performance on both the tenfold cross-validation test and independent test compared with state-of-the-art methods.

A dynamic-static combination model based on radiomics features for prostate cancer using multiparametric MRI.

Objective. To propose a new dynamic multiparametric magnetic resonance imaging (mpMRI) radiomics method for the detection of prostate cancer (PCa), and establish a combined model using dynamic and static radiomics features based on this method.Approach. A total of 166 patients (82 PCa patients and 84 non-PCa patients) were enrolled in the study, and 31 872 mpMRI images were performed in a radiomics workflow. The whole prostate segmentation and traditional static radiomics features extraction were performed on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI,bvalue of 10, 50, 100, 150, 200, 400, 600, 800, 1000, 1500 s mm-2respectively), apparent diffusion coefficient (ADC), and T2-weighted imaging (T2WI) sequences respectively. Through the building of eachb-value DWI model and the analysis of the static key radiomics features, three types of dynamic features called standard discrete (SD), parameter (P) and relative change rate (RCR) were constructed. And the b-value parameters used to construct dynamic features were divided into three groups ('Df_', 'Db_' and 'Da_'): the front part (10-200 s mm-2), the back part (400-1500 s mm-2), and all (10-1500 s mm-2) of theb-values set, respectively. Afterwards, the dynamic mpMRI model and combined model construction were constructed, and the PCa discrimination performance of each model was evaluated.Main results.The models based on dynamic features showed good potential for PCa identification. Where, the results of Db_SD, Da_P and Db_P models were encouraging (test cohort AUCs: 90.78%, 87.60%, 86.3%), which was better than the commonly used ADC model (AUC of ADC was 75.48%). Among the combined models, the models using static features of T2WI and dynamic features performed the best. The AUC of Db_SD + T2WI, Db_P + T2WI and Db_RCR + T2WI model was 92.90%, 91.29% and 81.46%.Significance.The dynamic-static combination model based on dynamic mpMRI radiomics method has a good effect on the identification of PCa. This method has broad application prospects in PCa individual diagnosis management.

Relationship between family support, serum lipid knowledge and quality of life in Chinese breast cancer women with adjuvant endocrine therapy.

BACKGROUND: Serum lipid management is an important health management goal for breast cancer patients with endocrine therapy, and serum lipid knowledge is a substantial factor influencing patients' serum lipid management behavior. The aim of this study was to explore the relationship between family support, serum lipid knowledge and quality of life in breast cancer women with endocrine therapy. METHODS: Through convenience sampling, 301 women who had been treated in the First Affiliated Hospital of China Medical University and Liaoning Cancer Hospital were selected to fill in the questionnaire of knowledge-attitude-practice (KAP) on serum lipids, family support questionnaire (FSQ), and the functional assessment of cancer therapy-breast cancer (FACT-B). Pearson correlation coefficient was used to analyze the correlation between the three. Multiple linear regression model was used to analyze the influencing factors of quality of life in breast cancer patients with endocrine therapy. RESULTS: The average score of KAP on serum lipids was 42.62 ± 7.333, the average score of family support was 12.55 ± 2.390, and the average score of quality of life was 97.13 ± 21.347, all above the medium level. Family support of breast cancer women with endocrine therapy was positively correlated with serum lipid knowledge and quality of life. Disease stage, family support, and serum lipid knowledge were the influencing factors of quality of life of breast cancer women with endocrine therapy. CONCLUSION: Good family support is associated with better serum lipid knowledge in breast cancer women with endocrine therapy. Therefore, interventions that aim to improve the level of family support may be one way to improve the knowledge level of serum lipid, prevent cardiovascular and cerebrovascular diseases, and improve the quality of life.

Comprehensive bioinformatics analysis confirms RBMS3 as the central candidate biological target for ovarian cancer.

Ovarian cancer (OC) is one of the most lethal malignancies in the female reproductive system. To find genes related to cancer progression targeting specific biological factors for targeted therapy, bioinformatics technology has been widely used. To screen the prognostic gene markers of OC by bioinformatics and explore their potential molecular biological mechanisms. Two data sets related to OC, GSE54388, and GSE119056, were rooted in the open comprehensive gene expression database (GEO). To correct the background of the data, standardize and screen differentially expressed genes (DEGs) using the R software limma package. The selected DEGs were enriched by Gene Ontology (GO) and through DAVID online database. Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway analysis and protein-protein interaction network (PPI-network) map were constructed by STRING online database and Cytoscape software. Combined with the TCGA database, univariate and multivariate COX regression were used to screen prognostic genes. QRT-PCR was used to verify DEGs in clinical tissue samples. Eventually, the function of RBMS3 on the viability, migration, invasion, and apoptosis of OC cells was tested through functional experiments in vitro. 352 common DEGs were screened from GSE54388 and GSE119056 data sets. Survival analysis showed that MEIS2, TSTA3, CNTN1, RBMS3, and TRA2A were considered to be connected with the prognosis of OC. We discover that the expression level of RBMS3 was positively connected with the overall survival (OS) rate of sufferers with OC. The level of RBMS3 in OC tissues was markedly lower than that in neighboring structures and the outcomes of the GEPIA database were consistent with those of the qRT-PCR experiment. Through gene transfection technology it was found that overexpression of RBMS3 in OC cells substantially suppressed the vitality, migration, and invasion of OC cells and raised the rates of apoptosis in the OC cells. In this experiment, we distinguish 5 genes that may participate in the prognosis of OC and showed the key genes and pathways related to OC. It is speculated that RBMS3, a tumor suppressor gene, can be applied as a potential biological marker for the treatment of OC, gene expression summary, and prognosis.

Sinigrin Impedes the Breast Cancer Cell Growth through the Inhibition of PI3K/AKT/mTOR Phosphorylation-Mediated Cell Cycle Arrest.

Breast carcinoma, one of the most lethal variants of carcinogenesis, significantly diagnosed type of cancer amongst the female population. Sinigrin, also known as glucosinolate, is found in the seeds of Brassica nigra and shown to enhance various cancer cells potentially. Nevertheless, the mechanistic explanation of sinigrin (SGN)-mediated breast cancer growth and augmentation is still to be investigated. Therefore, we contended in this study that SGN impedes PI3K/AKT/mTOR phosphorylation-mediated cell cycle arrest in MCF-7 cells. SGN (20 M) was implemented to treat MCF-7 cells for 24 and 48 hours of incubation. A significant increase in cytotoxicity, reactive oxygen species (ROS) generation, cell cycle arrest, mitochondrion membrane alteration, lipid peroxidation, and antioxidant depletion was found in MCF-7 cells. The PI3K/AKT/mTOR events are crucial pathways that participate in survival, proliferation, and cell cycle regulation. Inhibition of PI3K/AKT/mTOR expression thought to be novel approach for alleviating breast cancer growth. We noticed that SGN inhibits PI3K, AKT, and mTOR phosphorylation, resulting in the downregulation of proliferative and cell cycle regulatory proteins, such as cyclin-Dl, PCNA, CDK4, and CDK6. SGN also causes apoptosis in MCF-7 cells by increasing nuclear fragmentation and by inducing pro-apoptotic gene expression. As a result, SGN inhibits breast cancer growth by impeding PI3K/AKT/mTOR phosphorylation-mediated cell cycle arrest in MCF-7 cells.

Discovery of a Highly Potent and Selective Dual PROTAC Degrader of CDK12 and CDK13.

Selective degradation of the cyclin-dependent kinases 12 and 13 (CDK12/13) presents a novel therapeutic opportunity for triple-negative breast cancer (TNBC), but there is still a lack of dual CDK12/13 degraders. Here, we report the discovery of the first series of highly potent and selective dual CDK12/13 degraders by employing the proteolysis-targeting chimera (PROTAC) technology. The optimal compound 7f effectively degraded CDK12 and CDK13 with DC50 values of 2.2 and 2.1 nM, respectively, in MDA-MB-231 breast cancer cells. Global proteomic profiling demonstrated the target selectivity of 7f. In vitro, 7f suppressed expression of core DNA damage response (DDR) genes in a time- and dose-dependent manner. Further, 7f markedly inhibited proliferation of multiple TNBC cell lines including MFM223, with an IC50 value of 47 nM. Importantly, 7f displayed a significantly improved antiproliferative activity compared to the structurally similar inhibitor 4, suggesting the potential advantage of a CDK12/13 degrader for TNBC targeted therapy.