Unraveling the rapid progression of non-target lesions: risk factors and the therapeutic potential of PCSK9 inhibitors in post-PCI patients.

BACKGROUND: Rapid progression of non-target lesions (NTLs) leads to a high incidence of NTL related cardiac events post-PCI, which accounting half of the recurrent cardiac events. It is important to identify the risk factors and establish an accurate clinical prediction model for the rapid progression of NTLs post-PCI. PCSK9 inhibitors lower LDL-c levels significantly, also show the anti-inflammation effect, and may have the potential to reduce the rapid progression of NTLs post-PCI. We tried to test this hypothesis and explore the potential mechanisms. METHODS: This retrospective study included 1250 patients who underwent the first PCI and underwent repeat coronary angiography for recurrence of chest pain within 24 months. General characteristics, laboratory tests and inflammatory factors(IL-10, IL-6, IL-8, IL-1ß, sIL-2R, and TNF-α) were collected. Machine learning (LASSO regression) was mainly employed to select the important characteristic risk factors for the rapid progression of NTLs post-PCI and build prediction models. Finally, mediator analysis was employed to explore the potential mechanisms by which PCSK9 inhibitors reduce the rapid progression of NTLs post-PCI. RESULTS: There were more diabetes, less beta-blockers and PCSK9 inhibitors application, higher HbA1c, LDL-c, ApoB, TG, TC, uric acid, hs-CRP, TNF-α, IL-6, IL-8, and sIL-2R in NTL progressed group. LDL-c, hs-CRP, IL-8, and sIL-2R were characteristic risk factors for the rapid progression of NTLs post-PCI, combining LDL-c, hs-CRP, IL-8, and sIL-2R builds the optimal model for predicting the rapid progression of NTLs post-PCI (AUC = 0.632). LDL-c had a clear and incomplete mediating effect (95% CI, mediating effect: 51.56%) in the reduction of the progression of NTLs by PCSK9 inhibitors, and there was a possible mediating effect of IL-8 (90% CI), and sIL-2R (90% CI). CONCLUSIONS: LDL-c, hs-CRP, IL-8, and sIL-2R may be the key characteristic risk factors for the rapid progression of NTLs post-PCI, and combining these parameters might predict the rapid progression of NTLs post-PCI. The application of PCSK9 inhibitors had a negative correlation with the rapid progression of NTLs. In addition to the significant LDL-c-lowering, PCSK9 inhibitors may reduce the rapid progression of NTLs by reducing local inflammation of plaque. TRIAL REGISTRATION: ChiCTR2200058529; Date of registration: 2022-04-10.

Biomarkers related to m6A and succinic acid metabolism in papillary thyroid carcinoma.

BACKGROUND: Studies have shown that m6A modification is related to the occurrence and development of papillary thyroid carcinoma (PTC). The disorder of succinic acid metabolism is associated with the occurrence and development of various tumors. However, there are few studies based on m6A and succinate metabolism-related genes (SMRGs) in PTC. METHODS: The TCGA-Thyroid carcinoma (THCA), GSE33630, 1159 SMRGs, and 23 m6A regulatory factors were collected from the online databases. Subsequently, the differentially expressed genes (DEGs) were selected between PTC (Tumor) and Normal samples. The overlapping genes among the DEGs, m6A, and SMRGs were applied to screen the biomarkers. Using the 3 machine-learning algorithms, the biomarkers were determined based on the overlapping genes. Next, the biomarkers were evaluated by the ROC curve and expression analysis in TCGA-THCA and GSE33630. Then, the overall survival (OS) differences were compared between the high-and low-expression biomarkers. Finally, immune infiltration analysis, molecular regulatory network, and drug prediction were performed based on the biomarkers. RESULTS: In TCGA-THCA, there were 2800 DEGs between and Normal samples, and then 7 overlapping genes were obtained. Importantly, ADK, TNFRSF10B, CYP7B1, FGFR2, and CPQ were determined as biomarkers with excellent diagnostic efficiency (AUC > 0.7). In PTC samples, ADK and TNFRSF10B were high-expressed while CYP7B1, FGFR2, and CPQ were low-expressed. Especially, the high-expression groups of ADK had a better prognosis, while the high-expression groups of CYP7B1, FGFR2, and CPQ had a worse prognosis. Afterward, immune infiltration analysis found that 16 immune cells had infiltration differences between the Tumor and Normal samples. Finally, transcription factor SP1 could regulate CYP7B1 and TNFRSF10B. Moreover, Navitoclax was a potential drug for PTC patients. CONCLUSION: Overall, we described 5 biomarkers associated with adverse prognosis of PTC, including ADK, TNFRSF10B, CYP7B1, FGFR2, and CPQ. All these biomarkers were involved in succinate metabolism and m6A modification of RNA. This set of biomarkers should be explored further for their diagnostic value in PTC. Investigations into the mechanistic role of alteration of succinate metabolism and m6A modification of RNA pathways in the pathophysiology of PTC are warranted.

WDR77 in Pan-Cancer: Revealing expression patterns, genetic insights, and functional roles across diverse tumor types, with a spotlight on colorectal cancer.

OBJECTIVE: Despite its involvement in regulating various cellular functions, the expression and role of WD repeat-containing protein 77 (WDR77) in cancer remain elusive. This study aims to explore the expression and potential roles of WDR77 across multiple cancers, with a particular focus on its relevance in colorectal cancer (CRC). METHODS: We obtained WDR77 RNA-seq data, mutations, CNVs, and DNA methylation data from the TCGA, GTEx, and GEO databases to investigate its expression patterns and prognostic value. Additionally, we examined the correlation between WDR77 expression and somatic mutations, copy number variations, DNA methylation, and mRNA modifications. We utilized GSVA, GSEA algorithms, and CRISPR KO data from the Dependency Map database to explore WDR77's potential biological functions. The association between WDR77 and the tumor immune microenvironment was investigated using ESTIMATE and IOBR algorithms. Finally, we assessed WDR77 expression in CRC and its impact on cell proliferation through qRT-PCR, Western blotting, immunohistochemistry, CCK8, colony formation, and EdU assays. RESULTS: WDR77 was upregulated in various tumors and correlated with poor patient prognosis. Its high expression positively correlated with pathways related to cell proliferation and negatively correlated with immune-related pathways. In CRC, WDR77 expression was associated with specific clinical features, genomic alterations, and immune microenvironment characteristics. Experimental validation confirmed upregulated WDR77 expression in CRC tissues and cells, with WDR77 knockdown significantly inhibiting CRC cell proliferation. CONCLUSION: WDR77 holds potential as an oncogene and biological marker in various cancers, particularly CRC.

Identification of PPARG as key gene to link coronary atherosclerosis disease and rheumatoid arthritis via microarray data analysis.

BACKGROUND: Inflammation is the common pathogenesis of coronary atherosclerosis disease (CAD) and rheumatoid arthritis (RA). Although it is established that RA increases the risk of CAD, the underlining mechanism remained indefinite. This study seeks to explore the molecular mechanisms of RA linked CAD and identify potential target gene for early prediction of CAD in RA patients. MATERIALS AND METHODS: The study utilized five raw datasets: GSE55235, GSE55457, GSE12021 for RA patients, and GSE42148 and GSE20680 for CAD patients. Gene Set Enrichment Analysis (GSEA) was used to investigate common signaling pathways associated with RA and CAD. Then, weighted gene co-expression network analysis (WGCNA) was performed on RA and CAD training datasets to identify gene modules related to single-sample GSEA (ssGSEA) scores. Overlapping module genes and differentially expressed genes (DEGs) were considered as co-susceptible genes for both diseases. Three hub genes were screened using a protein-protein interaction (PPI) network analysis via Cytoscape plug-ins. The signaling pathways, immune infiltration, and transcription factors associated with these hub genes were analyzed to explore the underlying mechanism connecting both diseases. Immunohistochemistry and qRT-PCR were conducted to validate the expression of the key candidate gene, PPARG, in macrophages of synovial tissue and arterial walls from RA and CAD patients. RESULTS: The study found that Fc-gamma receptor-mediated endocytosis is a common signaling pathway for both RA and CAD. A total of 25 genes were screened by WGCNA and DEGs, which are involved in inflammation-related ligand-receptor interactions, cytoskeleton, and endocytosis signaling pathways. The principal component analysis(PCA) and support vector machine (SVM) and receiver-operator characteristic (ROC) analysis demonstrate that 25 DEGs can effectively distinguish RA and CAD groups from normal groups. Three hub genes TUBB2A, FKBP5, and PPARG were further identified by the Cytoscape software. Both FKBP5 and PPARG were downregulated in synovial tissue of RA and upregulated in the peripheral blood of CAD patients and differential mRNAexpreesion between normal and disease groups in both diseases were validated by qRT-PCR.Association of PPARG with monocyte was demonstrated across both training and validation datasets in CAD. PPARG expression is observed in control synovial epithelial cells and foamy macrophages of arterial walls, but was decreased in synovial epithelium of RA patients. Its expression in foamy macrophages of atherosclerotic vascular walls exhibits a positive correlation (r = 0.6276, p = 0.0002) with CD68. CONCLUSION: Our findings suggest that PPARG may serve as a potentially predictive marker for CAD in RA patients, which provides new insights into the molecular mechanism underling RA linked CAD.

Exploring the prebiotic potential of hydrolyzed fucoidan fermented in vitro with human fecal inocula: Impact on microbiota and metabolome.

Fucoidan is widely applied in food and pharmaceutical industry for the promising bioactivities. Low-molecular weight hydrolyzed fucoidan has gained attention for its beneficial health effects. Here, the modulation on microbiome and metabolome features of fucoidan and its acidolyzed derivatives (HMAF, 1.5-20 kDa; LMAF, <1.5 kDa) were investigated through human fecal cultures. Fucose is the main monosaccharide component in fucoidan and LMAF, while HMAF contains abundant glucuronic acid. LMAF fermentation resulted in the highest production of short-chain fatty acids, with acetate and propionate reaching maximum levels of 13.46 mmol/L and 11.57 mmol/L, respectively. Conversely, HMAF exhibited a maximum butyrate production of 9.28 mmol/L. Both fucoidan and acidolyzed derivatives decreased the abundance of Escherichia-Shigella and Klebsiella in human fecal cultures. Fucoidan and HMAF prefer to improve the abundance of Bacteroides. However, LMAF showed positive influence on Bifidobacterium, Lactobacillus, and Megamonas. Untargeted metabolome indicated that fucoidan and its derivatives mainly altered the metabolic level of lipids, indole, and their derivatives, with fucoidan and HMAF promoting higher level of indole-3-propionic acid and indole-3-carboxaldehyde compared to LMAF. Considering the chemical structural differences, this study suggested that hydrolyzed fucoidan can provide potential therapeutic applications for targeted regulation of microbial communities.

Experimental prognostic model integrating N6-methyladenosine-related programmed cell death genes in colorectal cancer.

Colorectal cancer (CRC) intricacies, involving dysregulated cellular processes and programmed cell death (PCD), are explored in the context of N6-methyladenosine (m6A) RNA modification. Utilizing the TCGA-COADREAD/CRC cohort, 854 m6A-related PCD genes are identified, forming the basis for a robust 10-gene risk model (CDRS) established through LASSO Cox regression. qPCR experiments using CRC cell lines and fresh tissues was performed for validation. The CDRS served as an independent risk factor for CRC and showed significant associations with clinical features, molecular subtypes, and overall survival in multiple datasets. Moreover, CDRS surpasses other predictors, unveiling distinct genomic profiles, pathway activations, and associations with the tumor microenvironment. Notably, CDRS exhibits predictive potential for drug sensitivity, presenting a novel paradigm for CRC risk stratification and personalized treatment avenues.

Expression and Prognostic Value of m6A RNA Methylation-Related Genes in Thyroid Cancer.

Background: N6-methyladenosine (m6A) methylation modification is involved in tumorigenesis and progression and can affect various stages of RNA processing. We aimed to determine m6A methylation modifications on a transcriptome-wide scale in thyroid cancer. Methods: RNA samples from cancerous tissues and adjacent tissues extracted from patients with papillary thyroid carcinoma (PTC) from Hangzhou First People's Hospital, Zhejiang, China from January 2019 to January 2020 were used for m6A-sequencing. The biological function of differentially expressed genes (DEGs) was analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Correlation analysis between the results of transcriptome sequencing and m6A-sequencing was also performed. The key m6A immune-related genes were downloaded from Immport. LASSO regression was performed on the resulting genes to establish a prognostic risk model, which was verified by multivariate Cox proportional hazards regression analyses, receiver operating characteristic (ROC) curves and Kaplan-Meier survival analysis. Results: An increase in m6A content in the total RNA of PTC was observed. A total of 123 genes with significant differential expression and differential methylation sites in thyroid cancer were selected, related to protein digestion and absorption, linoleic acid metabolism, legionellosis and alpha-linolenic acid metabolism. Seven genes (GDNF, EBI3, CCL2, BMP5, TGFB2, CGB3 and RLN2) were found to be predictive of PTC. Conclusion: We analyzed the expression, enrichment pathways and functions of m6A methylation-related genes in the whole transcriptome of thyroid cancer and provided a prognostic risk model for thyroid cancer patients.

Ultrasound-based Radiomics for Predicting Metastasis in the Lymph Nodes Posterior to the Right Recurrent Laryngeal Nerve in Patients with Papillary Thyroid Cancer.

BACKGROUND: Dissection of the lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLNs) in papillary thyroid cancer (PTC) remains controversial. OBJECTIVE: This study aimed to determine the capability of ultrasonography (US)-based radiomics for presurgical prediction of metastasis in LN-prRLNs in PTC. METHODS: Patients were retrospectively enrolled and pathologically confirmed as LN-prRLN metastasis with PTC after surgery. Radiomic analysis based on preoperative US images with manual segmentation of targets was used to develop a radiomics model. US features described in ACR TI-RADS were collected to construct a clinical model. The Radiomics model, a combined model integrating radiomics and clinical model, was also developed for the presurgical prediction of metastasis in LN-prRLNs. RESULTS: A total of 570 patients, including 488 patients with non-LN-prRLN metastasis and 82 with LN-prRLN metastasis, were assessed. The 15 topperforming features finally remained significant for constructing the radiomics model. The combined model showed that US measured tumor size (OR: 1.036, P = 0.044), US suspected lateral lymph node metastasis (OR: 2.247, P = 0.009), multifocality (OR: 1.920, P = 0.021), Delphian lymph node metastasis (DLNM) (OR: 2.300, P = 0.039), VIa compartment metastasis (OR: 5.357, P = 0.000), the radiomics score (OR: 1.003, P = 0.001) were significant risk factors for predicting LN-prRLN metastasis. The combined model achieved a higher AUC of 0.849 than that of the clinical model (AUC: 0.759) and radiomics model (AUC: 0.826). CONCLUSION: The US-based radiomics combined model can more effectively predict LN-prRLN metastasis in PTCs patients preoperatively. This approach had the potential to assist surgeons indecision-making regarding LN-prRLN dissection.

Integrative evaluation and experimental validation of the immune-modulating potential of dysregulated extracellular matrix genes in high-grade serous ovarian cancer prognosis.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is a challenging malignancy characterized by complex interactions between tumor cells and the surrounding microenvironment. Understanding the immune landscape of HGSOC, particularly the role of the extracellular matrix (ECM), is crucial for improving prognosis and guiding therapeutic interventions. METHODS AND RESULTS: Using univariate Cox regression analysis, we identified 71 ECM genes associated with prognosis in seven HGSOC populations. The ECMscore signature, consisting of 14 genes, was validated using Cox proportional hazards regression with a lasso penalty. Cox regression analyses demonstrated that ECMscore is an excellent indicator for prognostic classification in prevalent malignancies, including HGSOC. Moreover, patients with higher ECMscores exhibited more active stromal and carcinogenic activation pathways, including apical surface signaling, Notch signaling, apical junctions, Wnt signaling, epithelial-mesenchymal transition, TGF-beta signaling, and angiogenesis. In contrast, patients with relatively low ECMscores showed more active immune-related pathways, such as interferon alpha response, interferon-gamma response, and inflammatory response. The relationship between the ECMscore and genomic anomalies was further examined. Additionally, the correlation between ECMscore and immune microenvironment components and signals in HGSOC was examined in greater detail. Moreover, the expression of MGP, COL8A2, and PAPPA and its correlation with FAP were validated using qRT-PCR on samples from HGSOC. The utility of ECMscore in predicting the prospective clinical success of immunotherapy and its potential in guiding the selection of chemotherapeutic agents were also explored. Similar results were obtained from pan-cancer research. CONCLUSION: The comprehensive evaluation of the ECM may help identify immune activation and assist patients in HGSOC and even pan-cancer in receiving proper therapy.

Response of Salmonella enterica serovar Typhimurium to alginate oligosaccharides fermented with fecal inoculum: integrated transcriptomic and metabolomic analyses.

Alginate oligosaccharides (AOS), extracted from marine brown algae, are a common functional feed additive; however, it remains unclear whether they modulate the gut microbiota and microbial metabolites. The response of Salmonella enterica serovar Typhimurium, a common poultry pathogen, to AOS fermented with chicken fecal inocula was investigated using metabolomic and transcriptomic analyses. Single-strain cultivation tests showed that AOS did not directly inhibit the growth of S. Typhimurium. However, when AOS were fermented by chicken fecal microbiota, the supernatant of fermented AOS (F-AOS) exhibited remarkable antibacterial activity against S. Typhimurium, decreasing the abundance ratio of S. Typhimurium in the fecal microbiota from 18.94 to 2.94%. Transcriptomic analyses showed that the 855 differentially expressed genes induced by F-AOS were mainly enriched in porphyrin and chlorophyll metabolism, oxidative phosphorylation, and Salmonella infection-related pathways. RT-qPCR confirmed that F-AOS downregulated key genes involved in flagellar assembly and the type III secretory system of S. Typhimurium, indicating metabolites in F-AOS can influence the growth and metabolism of S. Typhimurium. Metabolomic analyses showed that 205 microbial metabolites were significantly altered in F-AOS. Among them, the increase in indolelactic acid and 3-indolepropionic acid levels were further confirmed using HPLC. This study provides a new perspective for the application of AOS as a feed additive against pathogenic intestinal bacteria. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-023-00176-z.

Structural characterization of a novel fucosylated trisaccharide prepared from bacterial exopolysaccharides and evaluation of its prebiotic activity.

Fucosylated oligosaccharides have promising prospects in various fields. In this study, a fucosylated trisaccharide (GFG) was separated from the acidolysis products of exopolysaccharides from Clavibacter michiganensis M1. Structural characterization demonstrated that GFG consists of glucose, galactose, and fucose, with a molecular weight of 488 Da. Nuclear magnetic resonance analysis showed that it has a different structure than that of 2'-fucosyllactose (2'-FL), even though they have the same monosaccharide composition. In vitro prebiotic experiments were conducted to evaluate the differences in the utilization of three selected carbohydrates by fourteen bacterial strains. In comparison with 2'-FL, GFG could be utilized by more beneficial bacteria, leading to generate more short-chain fatty acids. Moreover, GFG could not promote the proliferation of Escherichia coli. This work describes a novel fucosylated oligosaccharide and its preparation method, and the obtained trisaccharide may serve as a promising candidate for fucosylated human milk oligosaccharides.

Machine learning-based integration develops an immune-related risk model for predicting prognosis of high-grade serous ovarian cancer and providing therapeutic strategies.

Background: High-grade serous ovarian cancer (HGSOC) is a highly lethal gynecological cancer that requires accurate prognostic models and personalized treatment strategies. The tumor microenvironment (TME) is crucial for disease progression and treatment. Machine learning-based integration is a powerful tool for identifying predictive biomarkers and developing prognostic models. Hence, an immune-related risk model developed using machine learning-based integration could improve prognostic prediction and guide personalized treatment for HGSOC. Methods: During the bioinformatic study in HGSOC, we performed (i) consensus clustering to identify immune subtypes based on signatures of immune and stromal cells, (ii) differentially expressed genes and univariate Cox regression analysis to derive TME- and prognosis-related genes, (iii) machine learning-based procedures constructed by ten independent machine learning algorithms to screen and construct a TME-related risk score (TMErisk), and (iv) evaluation of the effect of TMErisk on the deconstruction of TME, indication of genomic instability, and guidance of immunotherapy and chemotherapy. Results: We identified two different immune microenvironment phenotypes and a robust and clinically practicable prognostic scoring system. TMErisk demonstrated superior performance over most clinical features and other published signatures in predicting HGSOC prognosis across cohorts. The low TMErisk group with a notably favorable prognosis was characterized by BRCA1 mutation, activation of immunity, and a better immune response. Conversely, the high TMErisk group was significantly associated with C-X-C motif chemokine ligands deletion and carcinogenic activation pathways. Additionally, low TMErisk group patients were more responsive to eleven candidate agents. Conclusion: Our study developed a novel immune-related risk model that predicts the prognosis of ovarian cancer patients using machine learning-based integration. Additionally, the study not only depicts the diversity of cell components in the TME of HGSOC but also guides the development of potential therapeutic techniques for addressing tumor immunosuppression and enhancing the response to cancer therapy.

Deciphering comprehensive features of tumor microenvironment controlled by chromatin regulators to predict prognosis and guide therapies in uterine corpus endometrial carcinoma.

Background: Dysregulation of chromatin regulators (CRs) can perturb the tumor immune microenvironment, but the underlying mechanism remains unclear. We focused on uterine corpus endometrial carcinoma (UCEC) and used gene expression data from TCGA-UCEC to investigate this mechanism. Methods: We used weighted gene co-expression network analysis (WGCNA) and consensus clustering algorithm to classify UCEC patients into Cluster_L and Cluster_H. TME-associated CRs were identified using WGCNA and differential gene expression analysis. A CR risk score (CRRS) was constructed using univariate Cox and LASSO-Cox regression analyses. A nomogram was developed based on CRRS and clinicopathologic factors to predict patients' prognosis. Results: Lower CRRS was associated with lower grade, more benign molecular subtypes, and improved survival. Patients with low CRRS showed abundant immune infiltration, a higher mutation burden, fewer CNVs, and better response to immunotherapy. Moreover, low CRRS patients were more sensitive to 24 chemotherapeutic agents. Conclusion: A comprehensive assessment of CRRS could identify immune activation and improve the efficacy of UCEC treatments.

Butyrogenic effect of galactosyl and mannosyl carbohydrates and their regulation on piglet intestinal microbiota.

Diarrhea is a global problem that causes economic losses in the pig industry. There is a growing attention on finding new alternatives to antibiotics to solve this problem. Hence, this study aimed to compare the prebiotic activity of low-molecular-weight hydrolyzed guar gum (GMPS) with commercial manno-oligosaccharide (MOS) and galacto-oligosaccharide (GOS). We further identified their combined effects along with probiotic Clostridium butyricum on regulating the intestinal microbiota of diarrheal piglet by in vitro fermentation. All the tested non-digestible carbohydrates (NDCs) showed favorable short-chain fatty acid-producing activity, and GOS and GMPS showed the highest production of lactate and butyrate, respectively. After 48 h of fermentation, the greatest enhancement in the abundance of Clostridium sensu stricto 1 was observed with the combination of GMPS and C. butyricum. Notably, all the selected NDCs significantly decreased the abundances of pathogenic bacteria genera Escherichia-Shigella and Fusobacterium and reduced the production of potentially toxic metabolites, including ammonia nitrogen, indole, and skatole. These findings demonstrated that by associating with the chemical structure, GMPS exhibited butyrogenic effects in stimulating the proliferation of C. butyricum. Thus, our results provided a theoretical foundation for further application of galactosyl and mannosyl NDCs in the livestock industry. KEY POINTS: • Galactosyl and mannosyl NDCs showed selective prebiotic effects. • GMPS, GOS, and MOS reduced pathogenic bacteria and toxic metabolites production. • GMPS specifically enhanced the Clostridium sensu stricto 1 and butyrate production.

Fucoxanthin from marine microalgae: A promising bioactive compound for industrial production and food application.

Fucoxanthin attracts increasing attentions due to its potential health benefits, which has been exploited in several food commodities. However, fucoxanthin available for industrial application is mainly derived from macroalgae, and is not yet sufficiently cost-effective compared with microalgae. This review focuses on the strategies to improve fucoxanthin productivity and approaches to reduce downstream costs in microalgal production. Here we comprehensively and critically discuss ways and methods to increase the cell growth rate and fucoxanthin content of marine microalgae, including strain screening, condition optimization, design of culture mode, metabolic and genetic engineering, and scale-up production of fucoxanthin. The approaches in downstream processes provide promising alternatives for fucoxanthin production from marine microalgae. Besides, this review summarizes fucoxanthin improvements in solubility and bioavailability by delivery system of emulsion, nanoparticle, and hydrogel, and discusses fucoxanthin metabolism with gut microbes. Fucoxanthin production from marine microalgae possesses numerous advantages in environmental sustainability and final profits to meet incremental global market demands of fucoxanthin. Strategies of adaptive evolution, multi-stage cultivation, and bioreactor improvements have tremendous potentials to improve economic viability of the production. Moreover, fucoxanthin is promising as the microbiota-targeted ingredient, and nanoparticles can protect fucoxanthin from external environmental factors for improving the solubility and bioavailability.

A comprehensive analysis focusing on cuproptosis to investigate its clinical and biological relevance in uterine corpus endometrial carcinoma and its potential in indicating prognosis.

Cuproptosis, a novel copper-dependent cell death involving mitochondrial respiration, is distinct from other known death mechanisms, which inspires us to study further in uterine corpus endometrial carcinoma (UCEC). Herein, leveraging comprehensive data from TCGA-UCEC, we conducted transcriptional and genetic analyses of 13 recently identified cuproptosis genes. We discovered severe genetic instability of cuproptosis genes, extensive positive correlations among those genes with each other at the mRNA level, and their involvement in oncogenic pathways in UCEC samples. Next, WGCNA was performed to identify a potential module regulating cuproptosis, in which the hub genes, in addition to 13 cuproptosis genes, were drawn to construct a scoring system termed Cu. Score. Furthermore, its clinical and biological relevance and tumor immune landscape, genetic alterations, as well as predicted sensitivity of chemotherapy drugs in different Cu. Score subgroups had been discussed extensively and in detail. Additionally, univariate Cox and LASSO regression were performed to identify 13 cuproptosis-related prognostic genes to establish a prognostic signature, the Risk. Score. Integrating the Risk. Score and clinical parameters, we established a nomogram with excellent performance to predict the 1-/3-/5-year survival probabilities of UCEC patients. To conclude, we conducted a comprehensive analysis encompassing cuproptosis and developed a cuproptosis scoring system and a prognostic prediction model for UCEC, which may offer help with individualized assessment and treatment for UCEC patients from the perspective of a novel death mechanism.

Amelioration of hydrolyzed guar gum on high-fat diet-induced obesity: Integrated hepatic transcriptome and metabolome.

Hydrolyzed guar gum has gained attention as an anti-obesity agent; however, few studies have focused on its role in amelioration of hepatic-associated metabolic processes. Here, the anti-obesity effect of low molecular weight hydrolyzed guar gum (GMLP, 1-10 kDa) on high-fat diet (HFD)-fed C57BL/6 J mice was investigated via transcriptome and metabolome in liver. GMLP reduced body weight gain and hepatic lipid accumulation dose-dependently, regulated blood lipid levels, and improved liver damage in HFD-fed mice. Integrated transcriptome and metabolome indicated that GMLP mainly altered lipid metabolism pathways (glycerophospholipid metabolism, glycerolipid metabolism, and fatty acid degradation), reduced disease biomarkers of ethyl glucuronide and neopterin, and increased levels of choline, flavin adenine dinucleotide, and pantetheine metabolites. Real-time quantitative PCR showed that GMLP downregulated key genes involved in de novo lipogenesis and triacylglycerol synthesis, while promoting fatty acid oxidation and choline synthesis. This study provides a theoretical basis for GMLP treatment in future clinical applications.

Deciphering the immune landscape dominated by cancer-associated fibroblasts to investigate their potential in indicating prognosis and guiding therapeutic regimens in high grade serous ovarian carcinoma.

Limited immunotherapeutic effect in high-grade serous ovarian carcinoma (HGSOC) propels exploration of the mechanics behind this resistance, which may be partly elucidated by investigating characters of cancer-associated fibroblasts (CAFs), a significant population in HGSOC involved in shaping tumor immune microenvironment. Herein, leveraging gene expression data of HGSOC samples from The Cancer Genome Atlas and Gene Expression Omnibus datasets, we suggested that CAFs detrimentally affected the outcomes of HGSOC patients. Subsequently, we performed weighted gene co-expression network analysis (WGCNA) to identify a CAFs-related module and screened out seven hub genes from this module, all of which were positively correlated with the infiltration of immunosuppressive macrophages. As one of the hub genes, the expression of fibrillin 1 (FBN1) and its relevance to CD206 were further verified by immunohistochemistry staining in HGSOC samples. Meanwhile, we extracted genes that correlated well with CAF signatures to construct a CAFscore. The capacity of the CAFscore as an independent prognostic factor was validated by Cox regression analyses, and its relevance to components as well as signals in the tumor immune microenvironment was also investigated. Under the evaluation by the CAFscore, HGSOC patients with relatively high CAFscore had worse outcomes, activated mesenchymal signaling pathways, and immune checkpoint blockade (ICB) resistance signatures, which was consistent with the fact that non-responders in anti-PD-1 treatment cohorts tended to have higher CAFscore. Besides, the possibility of CAFscore to guide the selection of sensitive chemotherapeutic agents was explored. In conclusion, individualized assessment of the CAFscore could uncover the extent of stroma activation and immunosuppression and inform therapeutic strategies to improve the benefit of therapies.