Image1_A novel lactate metabolism-related signature predicts prognosis and tumor immune microenvironment of breast cancer.JPEG

Background: Lactate, an intermediate product of glycolysis, has become an essential regulator of tumor maintenance, development, and metastasis. Lactate can drive tumors by changing the microenvironment of tumor cells. Because of lactate’s important role in cancer, we aim to find a novel prognostic signature based on lactate metabolism-related genes (LMRGs) of breast cancer (BC).Methods: RNA-sequencing data and clinical information of BC were enrolled from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We obtained LMRGs from the Molecular Signature Database v7.4 and articles, and then we compared candidate genes with TCGA data to get differential genes. Univariate analysis and most minor absolute shrinkage and selector operator (LASSO) Cox regression were employed to filter prognostic genes. A novel lactate metabolism-related risk signature was constructed using a multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analyses and Kaplan–Meier analyses in TCGA and GEO cohorts. Then, we further investigated in depth the function of the model’s immune microenvironment.Results: We constructed a 3-LMRG-based risk signature. Kaplan–Meier curves confirmed that high-risk score subgroups had a worse prognosis in TCGA and GEO cohorts. Then a nomogram to predict the probability of survival for BC was constructed. We also performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function analysis. The function analysis showed that the lactate metabolism-related signature was significantly related to immune response. A significant correlation was observed between prognostic LMRGs and tumor mutation burden, checkpoints, and immune cell infiltration. An mRNA–miRNA network was built to identify an miR-203a-3p/LDHD/LYRM7 regulatory axis in BC.Conclusion: In conclusion, we constructed a novel 3-LMRG signature and nomogram that can be used to predict the prognosis of BC patients. In addition, the signature is closely related to the immune microenvironment, which may provide new insight into future anticancer therapies.</p

Table3_A novel lactate metabolism-related signature predicts prognosis and tumor immune microenvironment of breast cancer.DOCX

Background: Lactate, an intermediate product of glycolysis, has become an essential regulator of tumor maintenance, development, and metastasis. Lactate can drive tumors by changing the microenvironment of tumor cells. Because of lactate’s important role in cancer, we aim to find a novel prognostic signature based on lactate metabolism-related genes (LMRGs) of breast cancer (BC).Methods: RNA-sequencing data and clinical information of BC were enrolled from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We obtained LMRGs from the Molecular Signature Database v7.4 and articles, and then we compared candidate genes with TCGA data to get differential genes. Univariate analysis and most minor absolute shrinkage and selector operator (LASSO) Cox regression were employed to filter prognostic genes. A novel lactate metabolism-related risk signature was constructed using a multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analyses and Kaplan–Meier analyses in TCGA and GEO cohorts. Then, we further investigated in depth the function of the model’s immune microenvironment.Results: We constructed a 3-LMRG-based risk signature. Kaplan–Meier curves confirmed that high-risk score subgroups had a worse prognosis in TCGA and GEO cohorts. Then a nomogram to predict the probability of survival for BC was constructed. We also performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function analysis. The function analysis showed that the lactate metabolism-related signature was significantly related to immune response. A significant correlation was observed between prognostic LMRGs and tumor mutation burden, checkpoints, and immune cell infiltration. An mRNA–miRNA network was built to identify an miR-203a-3p/LDHD/LYRM7 regulatory axis in BC.Conclusion: In conclusion, we constructed a novel 3-LMRG signature and nomogram that can be used to predict the prognosis of BC patients. In addition, the signature is closely related to the immune microenvironment, which may provide new insight into future anticancer therapies.</p

Table1_A novel lactate metabolism-related signature predicts prognosis and tumor immune microenvironment of breast cancer.DOCX

Background: Lactate, an intermediate product of glycolysis, has become an essential regulator of tumor maintenance, development, and metastasis. Lactate can drive tumors by changing the microenvironment of tumor cells. Because of lactate’s important role in cancer, we aim to find a novel prognostic signature based on lactate metabolism-related genes (LMRGs) of breast cancer (BC).Methods: RNA-sequencing data and clinical information of BC were enrolled from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We obtained LMRGs from the Molecular Signature Database v7.4 and articles, and then we compared candidate genes with TCGA data to get differential genes. Univariate analysis and most minor absolute shrinkage and selector operator (LASSO) Cox regression were employed to filter prognostic genes. A novel lactate metabolism-related risk signature was constructed using a multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analyses and Kaplan–Meier analyses in TCGA and GEO cohorts. Then, we further investigated in depth the function of the model’s immune microenvironment.Results: We constructed a 3-LMRG-based risk signature. Kaplan–Meier curves confirmed that high-risk score subgroups had a worse prognosis in TCGA and GEO cohorts. Then a nomogram to predict the probability of survival for BC was constructed. We also performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function analysis. The function analysis showed that the lactate metabolism-related signature was significantly related to immune response. A significant correlation was observed between prognostic LMRGs and tumor mutation burden, checkpoints, and immune cell infiltration. An mRNA–miRNA network was built to identify an miR-203a-3p/LDHD/LYRM7 regulatory axis in BC.Conclusion: In conclusion, we constructed a novel 3-LMRG signature and nomogram that can be used to predict the prognosis of BC patients. In addition, the signature is closely related to the immune microenvironment, which may provide new insight into future anticancer therapies.</p

Table2_A novel lactate metabolism-related signature predicts prognosis and tumor immune microenvironment of breast cancer.DOCX

Background: Lactate, an intermediate product of glycolysis, has become an essential regulator of tumor maintenance, development, and metastasis. Lactate can drive tumors by changing the microenvironment of tumor cells. Because of lactate’s important role in cancer, we aim to find a novel prognostic signature based on lactate metabolism-related genes (LMRGs) of breast cancer (BC).Methods: RNA-sequencing data and clinical information of BC were enrolled from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We obtained LMRGs from the Molecular Signature Database v7.4 and articles, and then we compared candidate genes with TCGA data to get differential genes. Univariate analysis and most minor absolute shrinkage and selector operator (LASSO) Cox regression were employed to filter prognostic genes. A novel lactate metabolism-related risk signature was constructed using a multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analyses and Kaplan–Meier analyses in TCGA and GEO cohorts. Then, we further investigated in depth the function of the model’s immune microenvironment.Results: We constructed a 3-LMRG-based risk signature. Kaplan–Meier curves confirmed that high-risk score subgroups had a worse prognosis in TCGA and GEO cohorts. Then a nomogram to predict the probability of survival for BC was constructed. We also performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function analysis. The function analysis showed that the lactate metabolism-related signature was significantly related to immune response. A significant correlation was observed between prognostic LMRGs and tumor mutation burden, checkpoints, and immune cell infiltration. An mRNA–miRNA network was built to identify an miR-203a-3p/LDHD/LYRM7 regulatory axis in BC.Conclusion: In conclusion, we constructed a novel 3-LMRG signature and nomogram that can be used to predict the prognosis of BC patients. In addition, the signature is closely related to the immune microenvironment, which may provide new insight into future anticancer therapies.</p

Facile Synthesis of Schlumbergera Bridgesii-Like Nanostructured Co₃O₄@MnO₂ as High Performance Electrode Materials for Supercapacitors

Tailored nanoarchitecture design is of great significance for the performance of supercapacitors, especially for heterostructure composites. Herein, we report a facile two-step hydrothermal strategy to prepare Co3O4@MnO2 nanocomposites, where the well-aligned Co3O4 nanograss array is capable of loading numerous and uniformly vertical MnO2 nanosheets that present an open structure of a nanoflower pattern. The microstructure of the nanograsses and nanoflower can be regulated by adjusting the hydrothermal process. The optimized Co3O4@MnO2 displays a Schlumbergera bridgesii-like nanostructure with a maximum specific capacitance of 5038.19 F g–1 as well as excellent capacity retention of as high as 97.48% after undergoing 5000 cycles at 10 A g–1. The assembled symmetric supercapacitor also exhibits a high energy density of 1467.23 Wh kg–1 and a maximum power density of 5500.07 W kg–1. This work provides a tunable strategy for the fabrication of heterostructure nanostructured composite for supercapacitor

Additional file 1 of Radiation impacts gene redundancy and biofilm regulation of cryoconite microbiomes in Northern Hemisphere glaciers

Additional file 1. Dataset Table 1–4

Descriptive statistics and correlation of PSG sleep characteristics with RCSQ items.

Descriptive statistics and correlation of PSG sleep characteristics with RCSQ items.</p

Univariate analysis of sleep quality based on RCSQ total score.

Univariate analysis of sleep quality based on RCSQ total score.</p

Two undescribed paradol-related specialized metabolites from <i>Aframomum melegueta</i>

Aframomum melegueta seeds are widely used as a spice in Africa. Two undescribed paradol-related compounds, (S)−9-hydroxy-[6]-paradol (1) and (9S)−3,9-dihydroxydihydro-[6]-paradol (2) together with eight reported constituents (3-10) were isolated and characterised from the methanol extract of A. melegueta seeds. Structure elucidation of these metabolites was achieved by means of NMR and mass spectroscopic data analyses. The absolute configuration of undescribed compounds (1 and 2) was determined using the modified Mosher’s method.</p

Crystallographic and DFT studies on host-guest complexes consisting of zinc bisporphyrinates and 1-phenylethylamine

We have investigated the chirality transfer from 1-phenylethylamine to a 5-amino-1,3-phthalic acid diamide-linked zinc bisporphyrinate through crystallographic and DFT studies. When the hosts were mixed with optically pure 1-phenylethylamine, CD showed moderate signals in the Soret band region. Single crystals of the corresponding 1:1 and 1:2 host-guest complexes were obtained. We present the first crystallographic structure of a 1:2 host-guest complex consisting of a bisporphyrin host and chiral monoamine guests. The structure reveals that the host-guest interactions are different for two guest molecules. The first guest is involved in a hydrogen bond and π-π interactions, while the second one is only involved in π-π interactions, which has not been observed in previous studies. The corresponding chirality transfer mechanism was also rationalized by DFT calculations. </p