A real-world clinicopathological model for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer.

Purpose: This study aimed to develop and validate a clinicopathological model to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients and identify key prognostic factors. Methods: This retrospective study analyzed data from 279 breast cancer patients who received NAC at Zhejiang Provincial People's Hospital from 2011 to 2021. Additionally, an external validation dataset, comprising 50 patients from Lanxi People's Hospital and Second Affiliated Hospital, Zhejiang University School of Medicine from 2022 to 2023 was utilized for model verification. A multivariate logistic regression model was established incorporating clinical, ultrasound features, circulating tumor cells (CTCs), and pathology variables at baseline and post-NAC. Model performance for predicting pCR was evaluated. Prognostic factors were identified using survival analysis. Results: In the 279 patients enrolled, a pathologic complete response (pCR) rate of 27.96% (78 out of 279) was achieved. The predictive model incorporated independent predictors such as stromal tumor-infiltrating lymphocyte (sTIL) levels, Ki-67 expression, molecular subtype, and ultrasound echo features. The model demonstrated strong predictive accuracy for pCR (C-statistics/AUC 0.874), especially in human epidermal growth factor receptor 2 (HER2)-enriched (C-statistics/AUC 0.878) and triple-negative (C-statistics/AUC 0.870) subtypes, and the model performed well in external validation data set (C-statistics/AUC 0.836). Incorporating circulating tumor cell (CTC) changes post-NAC and tumor size changes further improved predictive performance (C-statistics/AUC 0.945) in the CTC detection subgroup. Key prognostic factors included tumor size >5cm, lymph node metastasis, sTIL levels, estrogen receptor (ER) status and pCR. Despite varied pCR rates, overall prognosis after standard systemic therapy was consistent across molecular subtypes. Conclusion: The developed predictive model showcases robust performance in forecasting pCR in NAC-treated breast cancer patients, marking a step toward more personalized therapeutic strategies in breast cancer.

Neoadjuvant chemotherapy-induced remodeling of human hormonal receptor-positive breast cancer revealed by single-cell RNA sequencing.

Hormone receptor-positive breast cancer (HR+ BC) is known to be relatively insensitive to chemotherapy, and since chemotherapy has remained the major neoadjuvant therapy for HR+ BC, the undetermined mechanism of chemoresistance and how chemotherapy reshapes the immune microenvironment need to be explored by high-throughput technology. By using single-cell RNA sequencing and multiplexed immunofluorescence staining analysis of HR+ BC samples (paired pre- and post-neoadjuvant chemotherapy (NAC)), the levels of previously unrecognized immune cell subsets, including CD8+ T cells with pronounced expression of T-cell development (LMNA) and cytotoxicity (FGFBP2) markers, CD4+ T cells characterized by proliferation marker (ATP1B3) expression and macrophages characterized by CD52 expression, were found to be increased post-NAC, which were predictive of chemosensitivity and their antitumor function was also validated with in vitro experiments. In terms of immune checkpoint expression of CD8+ T cells, we found their changes were inconsistent post-NAC, that LAG3, VSIR were decreased, and PDCD1, HAVCR2, CTLA4, KLRC1 and BTLA were increased. In addition, we have identified novel genomic and transcriptional patterns of chemoresistant cancer cells, both innate and acquired, and have confirmed their prognostic value with TCGA cohorts. By shedding light on the ecosystem of HR+ BC reshaped by chemotherapy, our results uncover valuable candidates for predicting chemosensitivity and overcoming chemoresistance in HR+ BC.

Stemness signature and targeted therapeutic drugs identification for Triple Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer and carries the worst prognosis, characterized by the lack of progesterone, estrogen, and HER2 gene expression. This study aimed to analyze cancer stemness-related gene signature to determine patients' risk stratification and prognosis feature with TNBC. Here one-class logistic regression (OCLR) algorithm was applied to compute the stemness index of TNBC patients. Cox and LASSO regression analysis was performed on stemness-index related genes to establish 16 genes-based prognostic signature, and their predictive performance was verified in TCGA and METABERIC merged data cohort. We diagnosed the expression level of prognostic genes signature in the tumor immune microenvironment, analyzed the TNBC scRNA-seq GSE176078 dataset, and further validated the expression level of prognostic genes using the HPA database. Finally, the small molecular compounds targeted at the anti-tumor effect of predictive genes were screened by molecular docking; this novel stemness-based prognostic genes signature study could facilitate the prognosis of patients with TNBC and thus provide a feasible therapeutic target for TNBC.

Seasonal changes driving shifts in microbial community assembly and species coexistence in an urban river.

Microbial communities play a vital role in urban river biogeochemical cycles. However, the seasonal variations in microbial community characteristics, particularly phylogenetic group-based community assembly and species coexistence, have not been extensively investigated. Here, we systematically explored the microbiome characteristics and assembly mechanisms of urban rivers in different seasons using 16S rRNA gene sequencing and multivariate statistical methods. The results indicated that the microbial community presented significant temporal heterogeneity in different seasons, and the diversity decreased from spring to winter. The phylogenetic group-based microbial community assembly was governed by dispersal limitation and drift in spring, summer, and autumn but was structured by homogeneous selection in winter. Moreover, the main functions of nitrification, denitrification, and methanol oxidation were susceptible to dispersal limitation and drift processes, whereas sulfate respiration and aromatic compound degradation were controlled by dispersal limitation and homogeneous selection. Network analyses indicated that network complexity decreased and then increased with seasonal changes, while network stability showed the opposite trend, suggesting that higher complexity and diversity reduced community stability. Temperature was determined to be the primary driver of microbial community structure and assembly processes in different seasons based on canonical correspondence analysis and linear regression analysis. In conclusion, seasonal variation drives the dynamics of microbial community assembly and species coexistence patterns in urban rivers. This study provides new insights into the generation and maintenance of microbial community diversity in urban rivers under seasonal change conditions.

Chemotherapy-induced exosomal circBACH1 promotes breast cancer resistance and stemness via miR-217/G3BP2 signaling pathway.

BACKGROUND: Chemoresistance involves metastasis and aggressiveness of breast cancer (BC). Chemotherapy-elicited exosomes have been reported to be associated with drug resistance and pro-metastatic capacity of BC cells. Non-coding RNAs (ncRNAs) are enriched in exosomes, which participated in generation, progression, and resistance of BC. However, the mechanism underlying the chemoresistance and metastasis in BC cells mediated by the BC-derived exosomal ncRNAs remained to be elucidated. METHODS: The effects of PTX-induced exosomal circBACH1 on BC cell function were assessed using RNA Binding Protein Immunoprecipitation (RIP), dual luciferase reporter gene, tube formation, CCK-8, and Western Blot assays. The circBACH1 and miR-217 expression levels were detected using quantitative real-time PCR (RT-qPCR) and Immunohistochemistry (IHC) assays in BC tissues and precancerous tissues of BC patients. RESULTS: CircBACH1 expression was increased in paclitaxel-treated BC-derived exosomes (PTX-EXO) and BC tissue. PTX-EXO was shown to promote PTX-resistance and angiogenesis through upregulation circBACH1. Downregulation of circBACH1 improved PTX-sensitiveness by suppressing the cell viability, stemness, migration, and angiogenesis of BC cells. Moreover, we found that miR-217 interacted with circBACH1 and targeted GTPase-activating SH3 domain-binding protein 2 (G3BP2) in BC cells. CircBACH1 combined miR-217 cotransfection suppressed the expression of G3BP2 proteins compared with circBACH1 treatment in MCF-7 cells. In addition, downregulation of G3BP2 suppressed BC cell migration. CONCLUSIONS: These results demonstrated that PTX-induced exosomal circBACH1 promoted stemness and migration of BC cells by sponging miR-217 to upregulate the expression of G3BP2, which provided a new therapeutic target for PTX-resistance and progression of BC via circBACH1/miR-217/G3BP2 axis.

Mutant p53 leads to low-grade IFN-I-induced inflammation and impairs cGAS-STING signalling in mice.

Type I interferons (IFN-Is) are a class of proinflammatory cytokines produced in response to viruses and environmental stimulations, resulting in chronic inflammation and even carcinogenesis. However, the connection between IFN-I and p53 mutation is poorly understood. Here, we investigated IFN-I status in the context of mutant p53 (p53N236S , p53S). We observed significant cytosolic double-stranded DNA (dsDNA) derived from nuclear heterochromatin in p53S cells, along with an increased expression of IFN-stimulated genes. Further study revealed that p53S promoted cyclic GMP-AMP synthase (cGAS) and IFN-regulatory factor 9 (IRF9) expression, thus activating the IFN-I pathway. However, p53S/S mice were more susceptible to herpes simplex virus 1 infection, and the cGAS-stimulator of IFN genes (STING) pathway showed a decline trend in p53S cells in response to poly(dA:dT) accompanied with decreased IFN-ß and IFN-stimulated genes, whereas the IRF9 increased in response to IFN-ß stimulation. Our results illustrated the p53S mutation leads to low-grade IFN-I-induced inflammation via consistent low activation of the cGAS-STING-IFN-I axis, and STAT1-IRF9 pathway, therefore, impairs the protective cGAS-STING signalling and IFN-I response encountered with exogenous DNA attack. These results suggested the dual molecular mechanisms of p53S mutation in inflammation regulation. Our results could be helping in further understanding of mutant p53 function in chronic inflammation and provide information for developing new therapeutic strategies for chronic inflammatory diseases or cancer.

MRI/PAI Dual-modal Imaging-guided Precise Tracking of Bone Marrow-derived Mesenchymal Stem Cells Labeled with Nanoparticles for Treating Liver Cirrhosis.

Background and Aims: Stem cell transplantation is a potential treatment option for liver cirrhosis (LC). Accurately and noninvasively monitoring the distribution, migration, and prognosis of transplanted stem cells using imaging methods is important for in-depth study of the treatment mechanisms. Our study aimed to develop Au-Fe3O4 silica nanoparticles (NPs) as tracking nanoplatforms for dual-modal stem cell imaging. Methods: Au-Fe3O4 silica NPs were synthesized by seed-mediated growth method and co-precipitation. The efficiency and cytotoxicity of the NPs-labeled bone marrow-derived mesenchymal stem cells (BM-MSCs) were evaluated by Cell Counting Kit-8 assays, ICP-MS, phenotypic characterization, and histological staining. The biodistribution of labeled BM-MSCs injected through different routes (the hepatic artery or tail vein) into rats with LC was detected by magnetic resonance imaging (MRI), photoacoustic imaging (PAI), and Prussian blue staining. Results: Synthesized Au-Fe3O4 silica NPs consisted of a core (star-shaped Au NPs) and an outside silica layer doped with Fe3O4 NPs. After 24 h coincubation with 2.0 OD concentration of NPs, the viability of BM-MSCs was 77.91%±5.86% and the uptake of Au and Fe were (22.65±1.82) µg/mL and (234.03±11.47) µg/mL, respectively. The surface markers of labeled BM-MSCs unchanged significantly. Labeled BM-MSCs have osteogenic and adipogenic differentiation potential. Post injection in vivo, rat livers were hypointense on MRI and hyperintense on PAI. Prussian blue staining showed that more labeled BM-MSCs accumulated in the liver of the hepatic artery group. The severity of LC of the rats in the hepatic artery group was significantly alleviated. Conclusions: Au-Fe3O4 silica NPs were suitable MRI/PAI dual-modal imaging nanoplatforms for stem cell tracking in regenerative medicine. Transhepatic arterial infusion of BM-MSCs was the optimal route for the treatment of LC.

Genetic architecture of inducible and constitutive metabolic profile related to drought resistance in qingke (Tibetan hulless barley).

Qingke (Tibetan hulless barley, Hordeum vulgare L. var. nudum) is the primary food crop on the Tibet Plateau, the long-term drought and other harsh environments makes qingke an important resource for the study of abiotic resistance. Here, we evaluated the drought sensitivity of 246 qingke varieties. Genome-wide association studies (GWAS) found that root-specific expressed gene CYP84 may be involved in the regulation of drought resistance. Based on widely targeted metabolic profiling, we identified 2,769 metabolites in qingke leaves, of which 302 were significantly changed in response to drought stress, including 4-aminobutyric acid (GABA), proline, sucrose and raffinose. Unexpectedly, these drought-induced metabolites changed more violently in drought-sensitive qingkes, while the constitutive metabolites that had little response to drought stress, such as C-glycosylflavonoids and some amino acids, accumulated excessively in drought-resistant qingkes. Combined with metabolite-based genome-wide association study (mGWAS), a total of 1,006 metabolites under optimal condition and 1,031 metabolites under mild drought stress had significant associated loci. As a marker metabolite induced by drought stress, raffinose was significantly associated with two conservatively adjacent α-galactosidase genes, qRT-PCR suggests that these two genes may jointly regulate the raffinose content in qingke. Besides, as constituent metabolites with stable differences between drought-sensitive and drought-resistant qingkes, a class of C-glycosylflavonoids are simultaneously regulated by a UDP-glucosyltransferase gene. Overall, we performed GWAS for sensitivity and widely targeted metabolites during drought stress in qingke for the first time, which provides new insights into the response mechanism of plant drought stress and drought resistance breeding.

Integrating Single-cell RNA-seq to construct a Neutrophil prognostic model for predicting immune responses in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most widely distributed tumor in the world, and its immunotherapy is not practical. Neutrophil is one of a tumor's most abundant immune cell groups. This research aimed to investigate the complex communication network in the immune microenvironment (TIME) of NSCLC tumors to clarify the interaction between immune cells and tumors and establish a prognostic risk model that can predict immune response and prognosis of patients by analyzing the characteristics of Neutrophil differentiation. Integrated Single-cell RNA sequencing (scRNA-seq) data from NSCLC samples and Bulk RNA-seq were used for analysis. Twenty-eight main cell clusters were identified, and their interactions were clarified. Next, four subsets of Neutrophils with different differentiation states were found, closely related to immune regulation and metabolic pathways. Based on the ratio of four housekeeping genes (ACTB, GAPDH, TFRC, TUBB), six Neutrophil differentiation-related genes (NDRGs) prognostic risk models, including MS4A7, CXCR2, CSRNP1, RETN, CD177, and LUCAT1, were constructed by Elastic Net and Multivariate Cox regression, and patients' total survival time and immunotherapy response were successfully predicted and validated in three large cohorts. Finally, the causes of the unfavorable prognosis of NSCLC caused by six prognostic genes were explored, and the small molecular compounds targeted at the anti-tumor effect of prognostic genes were screened. This study clarifies the TIME regulation network in NSCLC and emphasizes the critical role of NDRGs in predicting the prognosis of patients with NSCLC and their potential response to immunotherapy, thus providing a promising therapeutic target for NSCLC.

Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model.

Breast cancer is one of the most common tumors in women. Despite various treatments, the survival of patients with advanced breast cancer is still disappointing. Furthermore, finding an effective individualized treatment for different kinds of patients is a thorny problem. Patient-derived tumor-like cell clusters were reported to be used for personalized drug testing in cancer therapy and had a prediction accuracy of 93%. However, there is still a lack of case reports about its application in the individualized treatment of breast cancer patients. Here, we described four cases of individualized treatment for advanced breast cancer using the patient-derived tumor-like cell cluster model (PTC model). In these four cases, the PTC model showed a good predictive effect. The tumor size was reduced significantly or even disappeared completely through clinical, radiological, or pathological evaluation with the help of the PTC model for selecting an individualized therapy regimen. Furthermore, the drug sensitivity test results of the PTC model were consistent with pathological molecular typing and the actual clinical drug resistance of the patients. In summary, our case report first evaluated the application value of the PTC model in advanced breast cancer, and the PTC model might be used as an efficient tool for drug resistance screening and for selecting a better personalized treatment, although further study is needed to prove the validity and stability of the PTC model in drug screening.

Integrative metabolomic and transcriptomic analyses reveal the mechanisms of Tibetan hulless barley grain coloration.

Cereal grains accumulate anthocyanin during developmental process. The anthocyanin content increases at grain filling stages to develop grain coloration in cereals. However, anthocyanin biosynthesis responsible for grain coloring and its regulatory mechanisms controlled by structural and functional genes remain unclear. Therefore, this study aimed to explore the global map of metabolic changes linked to grain coloration of Tibetan hulless barley (qingke) using an integrative metabolome and transcriptome approach. Grains from three colored qingke cultivars at different developmental stages were considered for molecular and metabolic investigations. A total of 120 differentially accumulated metabolites (DAMs) and 8,327 differentially expressed genes (DEGs) were filtered. DEGs were mainly enriched in the phenylpropanoid and flavonoid pathways. The transcript levels of anthocyanin biosynthesis genes (PAL, C4H, 4CL, CHS, FLS, F3H, F3'H, DFR, ANS, GT, OMT, and MAT) significantly upregulate in colored qingke compared to the non-colored variety. During grain development and maturation, the strong correlation of HvMYC2 expression with anthocyanin contents and anthocyanin biosynthesis genes suggested it as a critical gene in anthocyanin accumulation. Further results confirmed that HvMYC2 could be activated by HvMYB and be a positive regulator of UV-B and cold tolerance in qingke. In addition, verification based on enzymatic assays indicated that six key modifier enzymes could catalyze glycosylation, malonylation, and methylation of anthocyanins, thereby dissecting the major anthocyanin modification pathway in colored qingke. Overall, our study provides global insight into anthocyanin accumulation and the mechanism underlying grain coloration in qingke.

Bioinformatics Analysis and Structure of Gastric Cancer Prognosis Model Based on Lipid Metabolism and Immune Microenvironment.

OBJECTIVES: The reprogramming of lipid metabolism is a new trait of cancers. However, the role of lipid metabolism in the tumor immune microenvironment (TIME) and the prognosis of gastric cancer remains unclear. METHODS: Consensus clustering was applied to identify novel subgroups. ESTIMATE, TIMER, and MCPcounter algorithms were used to determine the TIME of the subgroups. The underlying mechanisms were elucidated using functional analysis. The prognostic model was established using the LASSO algorithm and multivariate Cox regression analysis. RESULTS: Three molecular subgroups with significantly different survival were identified. The subgroup with relatively low lipid metabolic expression had a lower immune score and immune cells. The differentially expressed genes (DEGs) were concentrated in immune biological processes and cell migration via GO and KEGG analyses. GSEA analysis showed that the subgroups were mainly enriched in arachidonic acid metabolism. Gastric cancer survival can be predicted using risk models based on lipid metabolism genes. CONCLUSIONS: The TIME of gastric cancer patients is related to the expression of lipid metabolism genes and could be used to predict cancer prognosis accurately.

The Value of the Stemness Index in Ovarian Cancer Prognosis.

Ovarian cancer (OC) is one of the most common gynecological malignancies. It is associated with a difficult diagnosis and poor prognosis. Our study aimed to analyze tumor stemness to determine the prognosis feature of patients with OC. At this job, we selected the gene expression and the clinical profiles of patients with OC in the TCGA database. We calculated the stemness index of each patient using the one-class logistic regression (OCLR) algorithm and performed correlation analysis with immune infiltration. We used consensus clustering methods to classify OC patients into different stemness subtypes and compared the differences in immune infiltration between them. Finally, we established a prognostic signature by Cox and LASSO regression analysis. We found a significant negative correlation between a high stemness index and immune score. Pathway analysis indicated that the differentially expressed genes (DEGs) from the low- and high-mRNAsi groups were enriched in multiple functions and pathways, such as protein digestion and absorption, the PI3K-Akt signaling pathway, and the TGF-ß signaling pathway. By consensus cluster analysis, patients with OC were split into two stemness subtypes, with subtype II having a better prognosis and higher immune infiltration. Furthermore, we identified 11 key genes to construct the prognostic signature for patients with OC. Among these genes, the expression levels of nine, including SFRP2, MFAP4, CCDC80, COL16A1, DUSP1, VSTM2L, TGFBI, PXDN, and GAS1, were increased in the high-risk group. The analysis of the KM and ROC curves indicated that this prognostic signature had a great survival prediction ability and could independently predict the prognosis for patients with OC. We established a stemness index-related risk prognostic module for OC, which has prognostic-independent capabilities and is expected to improve the diagnosis and treatment of patients with OC.

Elucidating the anti-aging mechanism of Si Jun Zi Tang by integrating network pharmacology and experimental validation in vivo.

Si Jun Zi Tang (SJZT) is a classic Traditional Chinese Medicine (TCM) prescription used to treat aging-related diseases. However, the potential molecular mechanisms of the anti-aging effects of the bioactive compounds and their targets remain elusive. In this study, we combined network pharmacology and molecular docking with in vivo experiments to elucidate the anti-aging molecular mechanism of SJZT. A series of network pharmacology strategies were used to predict potential targets and therapeutic mechanisms of SJZT, including compound screening, pathway enrichment analysis and molecular docking studies. Based on the network pharmacology predictions and observation of outward signs of aging, the expression levels of selected genes and proteins and possible key targets were subsequently validated and analysed using qRT-PCR and immunoblotting. Using a data mining approach, 235 effective targets of SJZT and aging were obtained. AKT1, STAT3, JUN, MAPK3, TP53, MAPK1, TNF, RELA, MAPK14 and IL6 were identified as core genes in the Protein-Protein Interaction Networks (PPI) analysis. The results of the effective target Gene Ontology (Go) functional enrichment analysis suggested that SJZT may be involved aging and antiapoptotic biological processes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that the anti-aging mechanism of SJZT may be associated with the PI3K-AKT and P38 MAPK signalling pathways. Molecular docking analysis suggested that kaempferol and quercetin could fit in the binding pockets of the core targets. In addition, SJZT alleviated the aging symptoms of mice such as osteoporosis and hair loss. In conclusion, the anti-aging effect of SJZT was associated with the inhibition of the PI3K-AKT and P38 MAPK signalling pathways, and these findings were consistent with the network pharmacology prediction.

Clinical significance and mechanism of long noncoding RNA HAGLROS in triple negative breast cancer.

PURPOSE: Triple Negative Breast Cancer (TNBC) is the malignant tumor with the fastest progression rate in breast cancer. LncRNAs are widely involved in various biological characteristics of tumor. The purpose of this study was to mine LncRNAs that can be used to diagnose and evaluate the prognosis of TNBC. METHODS: Base on TCGA dataset, we used three R language packages to analyze the differentially expressed (DE) lncRNAs in TNBC. Survival analysis and ROC curve analysis were conducted to estimate the potential diagnostic and prognostic value of LncRNAs for TNBC. Furthermore, CCK-8 and Transwell assays were used to assess the effects of LncRNA on MDA-MB-231 cells proliferation and migration. Additionally, targets mRNAs of candidate LncRNA were predicted by co-expression analysis and multiple target gene prediction databases, then KEGG pathway and GO analysis were conducted using DAVID online tool. RESULTS: 6165 DERNAs and 1258 DElncRNAs were obtained. 40 LncRNAs were significantly correlated with the survival time of TNBC patients. Among them, HAGLROS has the highest HR value. ROC curve analysis also showed that HAGLROS had high sensitivity and specificity. Further in vitro experiments showed that downregulation of HAGLROS inhibited the proliferation and migration of MDA-MB-231 cells. Moreover, by conducting bioinformatics analysis, we found that these target genes of HAGLROS were involved in regulating five signaling pathways. Mechanistic investigations demonstrated that HAGLROS might regulate the expression of PAX5 through miR-330-5p, the effects of miR-330-5p in MDA-MB-231 cells were also analyzed. CONCLUSION: Our results showed that HAGLROS was significantly overexpressed in TNBC, and high HAGLROS expression predicted poor overall survival. Downregulation of HAGLROS could inhibite the proliferation and migration of MDA-MB-231 cell by regulating PAX5 expression through miR-330-5p.

Effect of laparoscopic surgery for colorectal cancer with N. O. S. E. on recovery and prognosis of patients.

OBJECTIVE: To investigate the effect of laparoscopic surgery in colorectal cancer (CRC) patients with natural orifice specimen extraction (NOSE) on the recovery and quality of life (QOL) of patients. MATERIAL AND METHODS: Ninety-two eligible patients were randomly assigned into two groups: the traditional laparoscopy group (L group, n = 46) and the laparoscopic transanal specimen extraction group (NL group, n = 46). General data, surgery-related indicators, postoperative recovery, and prognosis were compared and analyzed between the two groups. RESULTS: A total of 46 patients in each group were enrolled in this study. The general data and surgery-related indicators were comparable between the two groups (all p > .05). There were no significant differences in the time of first flatus, bleeding, obstruction, constipation, and infectious complications between the two groups (all p > .05). The differences in the incidence of postoperative diarrhea, pain degree, and satisfaction on the aesthetics of the abdominal wall showed significant differences (χ2 = 6.133, p = .013; χ2 = 12.116, p = .017; χ2 = 13.463, p = .004). The postoperative follow-up time was 3-53 months. There were no significant differences in the postoperative hospital stay, medical costs, hospital readmission rate, incidence of incisional hernia, overall survival, disease-free survival, and QOL between the two groups (all p > .05). Conclusion: Laparoscopic surgery with NOSE for eligible patients with CRC was a feasible choice.

Drought Resistance in Qingke Involves a Reprogramming of the Phenylpropanoid Pathway and UDP-Glucosyltransferase Regulation of Abiotic Stress Tolerance Targeting Flavonoid Biosynthesis.

Tibetan hulless barley (qingke) is an important food crop in the Tibetan plateau. However, it often suffers from drought stress resulting in reduction of food production because of the extreme plateau environment. To elucidate the molecular mechanisms underlying the drought resistance of qingke, the transcriptomic and metabolomic responses of drought-sensitive (D) and drought-resistant (XL) accessions were characterized in experiments with a time course design. The phenylpropanoid pathway was reprogrammed by downregulating the lignin pathway and increasing the biosynthesis of flavonoids and anthocyanins, and this regulation improved plant tolerance for drought stress. Besides, flavonoid glycosides have induced accumulation of metabolites that participated in drought stress resistance. HVUL7H11410 exhibited the activity of wide-spectrum glucosyltransferase and mediated flavonoid glycosylation to enhance drought stress resistance. Overall, the findings provide insights into the regulatory mechanism underlying drought stress tolerance associated with metabolic reprogramming. Furthermore, the flavonoid-enriched qingke is more tolerant to drought stress and can be used as a functional food to benefit human health.

A novel three-long noncoding RNA risk score system for the prognostic prediction of triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) is characterized by fast tumor increase, rapid recurrence and natural metastasis. We aimed to identify a genetic signature for predicting the prognosis of TNBC. Materials & methods: We conducted a weighted correlation network analysis of datasets from the Gene Expression Omnibus. Multivariate Cox regression was used to construct a risk score model. Results: The multi-factor risk scoring model was meaningfully associated with the prognosis of patients with TBNC. The predictive power of the model was demonstrated by the time-dependent receiver operating characteristic curve and Kaplan-Meier curve, and verified using a validation set. Conclusion: We established a long noncoding RNA-based model for the prognostic prediction of TNBC.

Quantitative Proteome Profiling Provides Insight into the Proteins Associated with ß-Glucan Accumulation in Hull-less Barley Grains.

The hull-less barley (Qingke) is widely planted as a staple food crop in the Tibetan area, China, and the grains contains high content of ß-glucan (BG). The mechanisms of BG synthesis and accumulation in qingke has not been studied at the protein level. This study characterized the proteins associated with BG synthesis and accumulation during qingke seed development. The proteome profiles of qingke seeds taken at 20, 30, and 40 days after flowering were compared using the TMT-based quantitative proteomics. A total of 4283 proteins were identified, with 759 being differentially expressed (DEPs) throughout seed development. Comparisons of protein expression pattern, functions, and pathway enrichment tests highlight cell wall modification, carbon and energy metabolism, polysaccharide metabolism, post-transcriptional modifications, and vesicular transport as critical biological processes related to qingke BG accumulation. Furthermore, induction of starch synthase, starch branching enzyme, pectin acetyl esterases, beta-glucosidases, beta-amylases, 1,4-beta-xylan, xyloglucan, α-amylase inhibitors, and glycosyltransferases underpinned BG synthesis. The results also indicated that the proteins involved in glycolytic, gluconeogenesis, and glyoxylate bypass pathways provided energy and reducing power for BG storage. Parallel reaction monitoring (PRM) and quantitative real-time PCR (qPCR) analyses confirmed the expression profile of the proteins obtained by TMT-based proteomics. The current results provided an insight into the mechanisms of BG synthesis and accumulation during qingke seed development.