Stereodynamic control of nonadiabatic processes in low-energy Be+(2P) + H2 (v = 0, j = 2) collisions.

Controlling the relative arrangement of colliding molecules is crucial for determining the dynamical outcomes of chemical processes and has emerged as a hot spot of experimental research. Here, the quantum scattering calculations are conducted to investigate the stereodynamic control in collisions between Be+(2P) and H2 (v = 0, j = 2), which undergo nonadiabatic transitions to the electronic ground state. Stereodynamic preparation is achieved by controlling the initial alignment of the H2 bond axis relative to the scattering frame. For product BeH+ in the reactive process, the differential cross sections (DCSs) are significantly enhanced in the forward and sideways hemispheres when the alignment angle ß is 60°. For the product H2 in the quenching channel, the ß = 0° preparation can result in a more than one-fold increase in the DCS at a polar scattering angle of 0°. Furthermore, varying the alignment angle ß also has noteworthy effects on the rotational-state distributions of BeH+ products. Specifically, ß = 0° preparation can induce the disappearance of the bimodal distribution of rotational states at a collision energy of 0.05 eV.

LILAR, a novel long noncoding RNA regulating autophagy in the liver tissues of endotoxemic mice through a competing endogenous RNA mechanism.

Sepsis is an often-deadly complication of infection that can lead to multiple organ failure. Previous studies have demonstrated that autophagy has a protective effect on liver injury in sepsis. Here, we report a novel long noncoding RNA (lncRNA), named lipopolysaccharide (LPS)-induced liver autophagy regulator (LILAR), which was highly induced in the liver tissues of endotoxemic mice. LILAR deficiency significantly increased the susceptibility of mice to LPS. In contrast, LILAR overexpression rescued the liver injury mediated by LILAR deficiency and increased the survival of LILAR knockout mice with endotoxemia. Autophagy-related protein 13 (Atg13) is a potential downstream target gene of LILAR. LILAR deficiency notably decreased Atg13 expression and suppressed autophagy in the livers of mice challenged with LPS. A reporter gene assay showed that LILAR competitively adsorbed miR-705 to increase the expression of Atg13 in cultured cells, indicating that LILAR participates in the regulation of the autophagy in the liver tissues of endotoxemic mice through a competitive endogenous RNA mechanism. In summary, we identified a novel lncRNA, LILAR, as a hepatic autophagy regulator, which not only promotes our understanding of liver pathophysiology but also provides a potential therapeutic target and/or diagnostic biomarker for liver injury in endotoxemia.

Integrated Analyses of Single-Cell Transcriptome and Mendelian Randomization Reveal the Protective Role of Resistin in Sepsis Survival in Intensive Care Unit.

The high morbidity and mortality rates associated with sepsis highlight the challenges of finding specific remedies for this condition in the intensive care unit (ICU). This study aimed to explore the differentially expressed genes (DEGs) specific to cell types in sepsis and investigate the role of resistin in the survival of sepsis patients through Mendelian randomization (MR) analyses. We used single-cell and bulk transcriptome data to identify cell type-specific DEGs between sepsis and healthy controls. MR analyses were then conducted to investigate the causal relationships between resistin (one of the identified DEGs) levels and the survival of sepsis patients. Additionally, we utilized meQTL (methylation quantitative trait loci) to identify cytosine-phosphate-guanine (CpG) sites that may directly affect sepsis. We identified 560 cell type-specific DEGs between sepsis and healthy controls. Notably, we observed the upregulation of resistin levels in macrophages during sepsis. In bulk transcriptome, RETN is also upregulated in sepsis samples compared with healthy controls. MR analyses revealed a negative association existed between the expression of resistin, at both gene and protein levels, and the mortality or severity of sepsis patients in ICU. Moreover, there were no associations observed between resistin levels and death or organ failure due to other causes. We also identified three methylation CpG sites, located in RETN or its promoter region-cg06633066, cg22322184, and cg02346997-that directly affected both resistin protein levels and sepsis death in the ICU. Our findings suggest that resistin may provide feasible protection for sepsis patients, particularly those with severe cases, without serious side effects. Therefore, resistin could be a potential drug candidate for sepsis treatment. Additionally, we identified two CpG sites, cg06633066 and cg22322184, that were associated with RETN protein levels and sepsis death, providing novel insights into the underlying mechanisms of sepsis.

An effective approximation of Coriolis coupling in reactive scattering: application to the time-dependent wave packet calculations.

Coriolis coupling plays a crucial role in reactive scattering, but dynamics calculations including the complete Coriolis coupling significantly increase the difficulty of numerical evolution due to the corresponding expensive matrix processing. The coupled state approximation that completely ignores the off-diagonal Coriolis coupling saves computational cost significantly but its error is usually unacceptable. In this paper, an improved coupled state approximation inspired by recently published results [D. Yang, X. Hu, D. H. Zhang and D. Xie, J. Chem. Phys., 2018, 148, 084101.] of the inelastic scattering problem is extended to deal with the reactive scattering. The calculations using the time-dependent wave packet method reveal that the new method can accurately reproduce the rigorous results of the H + HD (j0 < 3) → D + H2 reaction and immensely improve the computational efficiency. Additionally, we extend the new method to the non-adiabatic Li(2p) + H2 (v0 = 0, j0 = 0, 1) → H + LiH reaction, showcasing its advantages of low computational cost and high accuracy.

Globally Accurate Gaussian Process Potential Energy Surface and Quantum Dynamics Studies on the Li(2S) + Na2 → LiNa + Na Reaction at Low Collision Energies.

The LiNa2 reactive system has recently received great attention in the experimental study of ultracold chemical reactions, but the corresponding theoretical calculations have not been carried out. Here, we report the first globally accurate ground-state LiNa2 potential energy surface (PES) using a Gaussian process model based on only 1776 actively selected high-level ab initio training points. The constructed PES had high precision and strong generalization capability. On the new PES, the quantum dynamics calculations on the Li(2S) + Na2(v = 0, j = 0) → LiNa + Na reaction were carried out in the 0.001-0.01 eV collision energy range using an improved time-dependent wave packet method. The calculated results indicate that this reaction is dominated by a complex-forming mechanism at low collision energies. The presented dynamics data provide guidance for experimental research, and the newly constructed PES could be further used for ultracold reaction dynamics calculations on this reactive system.

Identification of differentially expressed genes at the single-cell level and prognosis prediction through bulk RNA sequencing data in breast cancer.

Background: The invention and development of single-cell technologies have contributed a lot to the understanding of tumor heterogeneity. The objective of this research was to investigate the differentially expressed genes (DEGs) between normal and tumor cells at the single-cell level and explore the clinical application of these genes with bulk RNA-sequencing data in breast cancer. Methods: We collected single-cell, bulk RNA sequencing (RNA-seq) and microarray data from two public databases. Through single-cell analysis of 23,909 mammary gland cells from seven healthy donors and 33,138 tumor cells from seven breast cancer patients, cell type-specific DEGs between normal and tumor cells were identified. With these genes and the bulk RNA-seq data, we developed a prognostic signature and validated the efficacy in two independent cohorts. We also explored the differences of immune infiltration and tumor mutational burden (TMB) between the different risk groups. Results: A total of 6,175 cell-type-specific DEGs were obtained through the single-cell analysis between normal and tumor cells in breast cancer, of which 1,768 genes intersected with the bulk RNA-seq data. An 18-gene signature was constructed to assess the outcomes in breast cancer patients. The efficacy of the signature was notably prominent in two independent cohorts. The low-risk group showed higher immune infiltration and lower TMB. Among the 18 genes in the signature, 16 were also differentially expressed in the bulk RNA-seq dataset. Conclusion: Cell-type-specific DEGs between normal and tumor cells were identified through single-cell transcriptome data. The signature constructed with these DEGs could stratify patients efficiently. The signature was also closely correlated with immune infiltration and TMB. Nearly all the genes in the signature were also differentially expressed at the bulk RNA-seq level.

A neural network potential energy surface and quantum dynamics studies for the Ca+(2S) + H2 → CaH+ + H reaction.

Reactive collisions of Ca+ ions with H2 molecules play a crucial role in ultracold chemistry, quantum information and other cutting-edge fields, and have been widely studied experimentally, but the corresponding theoretical studies have not been reported due to the lack of an applicable potential energy surface (PES). Herein, a globally accurate PES of the ground-state CaH2+ is constructed using the permutation invariant polynomial neural network method based on 27 780 ab initio points calculated at the multi-reference configuration interaction level. On the new PES, the quantum time-dependent wave packet calculations are performed to study the dynamics mechanisms of the Ca+(2S) + H2(ν0 = 0, j0 = 0) → CaH+ + H reaction. The calculated results suggest that the reaction follows a direct abstraction process when the collision energy is below 5.0 eV. The dynamics results would have a great reference significance for the experimental research of this reactive system at a finer level, and further dynamics studies, such as the effects of isotope substitution and rovibrational excitations of the reactant molecule, could be carried out on this newly constructed PES.

Prognosis Prediction Through an Integrated Analysis of Single-Cell and Bulk RNA-Sequencing Data in Triple-Negative Breast Cancer.

Background: Genomic and antigenic heterogeneity pose challenges in the precise assessment of outcomes of triple-negative breast cancer (TNBC) patients. Thus, this study was designed to investigate the cardinal genes related to cell differentiation and tumor malignant grade to advance the prognosis prediction in TNBC patients through an integrated analysis of single-cell and bulk RNA-sequencing (RNA-seq) data. Methods: We collected RNA-seq and microarray data of TNBC from two public datasets. Using single-cell pseudotime analysis, differentially expressed genes (DEGs) among trajectories from 1534 cells of 6 TNBC patients were identified as the potential genes crucial for cell differentiation. Furthermore, the grade- and tumor mutational burden (TMB)-related DEGs were explored via a weighted correlation network analysis using the Molecular Taxonomy of Breast Cancer International Consortium dataset. Subsequently, we utilized the DEGs to construct a prognostic signature, which was validated using another independent dataset. Moreover, as gene set variation analysis indicated the differences in immune-related pathways between different risk groups, we explored the immune differences between the two groups. Results: A signature including 10 genes related to grade and TMB was developed to assess the outcomes of TNBC patients, and its prognostic efficacy was prominent in two cohorts. The low-risk group generally harbored lower immune infiltration compared to the high-risk group. Conclusion: Cell differentiation and grade- and TMB-related DEGs were identified using single-cell and bulk RNA-seq data. A 10-gene signature for prognosis prediction in TNBC patients was constructed, and its performance was excellent. Interestingly, the signature was found to be closely related to tumor immune infiltration, which might provide evidence for the crucial roles of immune cells in malignant initiation and progression in TNBC.

Representing globally accurate reactive potential energy surfaces with complex topography by combining Gaussian process regression and neural networks.

There has been increasing attention in using machine learning technologies, such as neural networks (NNs) and Gaussian process regression (GPR), to model multi-dimensional potential energy surfaces (PESs). A PES constructed using NNs features high accuracy and generalization capability, but a single NN cannot actively select training points as GPR does, resulting in expensive ab initio calculations as the molecular complexity increases. However, a PES constructed using GPR has a slow speed of evaluation and it is difficult to accurately describe a fast-changing potential. Herein, an efficient scheme for representing globally accurate reactive PESs with complex topography based on as few points as possible by incorporating active data selection of GPR into NN fitting is proposed. The validity of this strategy is tested using the BeH2+ system, and only 1270 points are automatically sampled. The generalization performance and speed of evaluation of the generated PES are much better than those of the GPR PES constructed using the same dataset. Moreover, an accurate NN PES is fitted by 12 122 points as a benchmark for comparison to further test the global accuracy of the PES obtained using this scheme, and the corresponding results present extremely consistent topography characteristics and calculated Be+(2S) + H2 reaction probabilities.

Identification of a pyroptosis-related prognostic signature in breast cancer.

BACKGROUND: The relationship between pyroptosis and cancer is complex. It is controversial that whether pyroptosis represses or promotes tumor development. This study aimed to explore prognostic molecular characteristics to predict the prognosis of breast cancer (BRCA) based on a comprehensive analysis of pyroptosis-related gene expression data. METHODS: RNA-sequcing data of BRCA were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Ominibus (GEO) datasets. First, pyroptosis-related differentially expressed genes (DEGs) between normal and tumor tissues were identified from the TCGA database. Based on the DEGs, 1053 BRCA patients were divided into two clusters. Second, DEGs between the two clusters were used to construct a signature by a least absolute shrinkage and selection operator (LASSO) Cox regression model, and the GEO cohort was used to validate the signature. Various statistical methods were applied to assess this gene signature. Finally, Single-sample gene set enrichment analysis (ssGSEA) was employed to compare the enrichment scores of 16 types of immune cells and 13 immune-related pathways between the low- and high-risk groups. We calculated the tumor mutational burden (TMB) of TCGA cohort and evaluated the correlations between the TMB and riskscores of the TCGA cohort. We also compared the TMB between the low- and high-risk groups. RESULTS: A total of 39 pyroptosis-related DEGs were identified from the TCGA-breast cancer dataset. A prognostic signature comprising 16 genes in the two clusters of DEGs was developed to divide patients into high-risk and low-risk groups, and its prognostic performance was excellent in two independent patient cohorts. The high-risk group generally had lower levels of immune cell infiltration and lower activity of immune pathway activity than did the low-risk group, and different risk groups revealed different proportions of immune subtypes. The TMB is higher in high-risk group compared with low-risk group. OS of low-TMB group is better than that of high-TMB group. CONCLUSION: A 16-gene signature comprising pyroptosis-related genes was constructed to assess the prognosis of breast cancer patients and its prognostic performance was excellent in two independent patient cohorts. The signature was found closely associated with the tumor immune microenvironment and the potential correlation could provide some clues for further studies. The signature was also correlated with TMB and the mechanisms are still warranted.

High expression of RNF169 is associated with poor prognosis in pancreatic adenocarcinoma by regulating tumour immune infiltration.

Background: Pancreatic adenocarcinoma (PAAD) is a highly deadly and aggressive tumour with a poor prognosis. However, the prognostic value of RNF169 and its related mechanisms in PAAD have not been elucidated. In this study, we aimed to explore prognosis-related genes, especially RNF169 in PAAD and to identify novel potential prognostic predictors of PAAD. Methods: The GEPIA and UALCAN databases were used to investigate the expression and prognostic value of RNF169 in PAAD. The correlation between RNF169 expression and immune infiltration was determined by using TIMER and TISIDB. Correlation analysis with starBase was performed to identify a potential regulatory axis of lncRNA-miRNA-RNF169. Results: The data showed that the level of RNF169 mRNA expression in PAAD tissues was higher than that in normal tissues. High RNF169 expression was correlated with poor prognosis in PAAD. In addition, analysis with the TISIDB and TIMER databases revealed that RNF169 expression was positively correlated with tumour immune infiltration in PAAD. Correlation analysis suggested that the long non-coding RNA (lncRNA) AL049555.1 and the microRNA (miRNA) hsa-miR-324-5p were involved in the expression of RNF169, composing a potential regulatory axis to control the progression of PAAD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that RNF169 plays a role in PAAD through pathways such as TNF, Hippo, JAK-STAT and Toll-like receptor signaling. Conclusion: In summary, the upregulation of RNF169 expression mediated by ncRNAs might influence immune cell infiltration in the microenvironment; thus, it can be used as a prognostic biomarker and a potential therapeutic target in PAAD.

[Microbial Community Structure of Waste Water Treatment Plants in Different Seasons].

Wastewater treatment plants (WWTPs) have different treatment effects during different seasons due to changes in water quality and temperature. To understand bacterial community structure and diversity dynamics in the WWTPs, this study employed high-throughput sequencing technology during winter and summer. A total of 60 activated sludge samples were collected in five WWTPs in Beijing with different treatment processes in summer (temperature=28℃±2℃, water temperature=24.9℃±1.1℃) and winter (temperature=0℃±3℃, water temperature=16.8℃±1.3℃). The relative abundances of dominant bacterial genera in activated sludge varied significantly between the WWTPs but microbial community structure was typically similar between different treatment units (i.e., the anaerobic tank, anoxic tank, and aerobic tank) at each WWTP. At the same time, different bacteria dominated in winter and summer, when the relative abundance of SJA-15, Ferruginibacter, and Blasocatellaceae was 6.07%, 4.50%, and 4.44% respectively, when the relative abundance of Nitrospira, Methylotenera, and RBG-13-54-9 in winter was 10.17%, 3.96%, and 3.28%, respectively. Correlation analysis showed that temperature, total nitrogen (TN), NH4+-N, total phosphorus (TP), and chemical oxygen demand (COD) were the main environmental factors affecting microbial community structure, of which temperature had the greatest effect on species composition followed by TN. Furthermore, a predictive analysis of functional enzymes indicated that the abundance of key enzymes involved in the nitrogen cycle in the activated sludge of WWTPs is higher in winter than that in summer. These results show that temperature, water quality, and treatment process affect bacterial community structure (i.e., dominance and abundance) in WWTP activated sludge.

[Value of FOXP3 Tregs predicting the effectiveness of neoadjuvant chemotherapy in patients with breast cancer].

OBJECTIVE: To explore the predictive significance of FOXP3 Tregs in patients with breast cancer on neoadjuvant chemotherapy (NACT). METHODS: A total of 78 newly diagnosed and untreated patients with invasive breast cancer were recruited for this retrospective study.FOXP3 Tregs were assessed by immunohistochemistry. The relationship between clinicopathological factors, FOXP3+ Tregs and pathological complete response (pCR) rate was analyzed. RESULTS: Among 78 patients with TAC neoadjuvant chemotherapy, the pCR rate was 19.2%. The pCR rate of patients with high expressions of FOXP3+ Tregs was significantly lower than that of those with low expressions of FOXP3+ Tregs (9.5% vs 30.5%, P = 0.023). FOXP3+ Tregs expression in breast cancer and efficacy of NACT were negatively correlated. CONCLUSION: FOXP3+ Tregs may serve as a predictor for assessing the efficacy of NACT.