Hidden Real Topology and Unusual Magnetoelectric Responses in Two-Dimensional Antiferromagnets.

Recently, the real topology has been attracting widespread interest in two dimensions (2D). Here, based on first-principles calculations and theoretical analysis, the monolayer Cr2Se2O (ML-CrSeO) is revealed as the first material example of a 2D antiferromagnetic (AFM) real Chern insulator (RCI) with topologically protected corner states. Unlike previous RCIs, it is found that the real topology of the ML-CrSeO is rooted in one certain mirror subsystem of the two spin channels, and cannot be directly obtained from all the valence bands in each spin channel as commonly believed. In particular, due to antiferromagnetism, the corner modes in ML-CrSeO exhibit strong corner-contrasted spin polarization, leading to spin-corner coupling (SCC). This SCC enables a direct connection between spin space and real space. Consequently, large and switchable net magnetization can be induced in the ML-CrSeO nanodisk by electrostatic means, such as potential step and in-plane electric field, and the corresponding magnetoelectric responses behave like a sign function, distinguished from that of the conventional multiferroic materials. This work considerably broadens the candidate range of RCI materials, and opens up a new direction for topo-spintronics and 2D AFM materials research.

Clinical prognostication and immunotherapy response prediction in esophageal squamous cell carcinoma using the DNA damage repair-associated signature.

BACKGROUND: The relationship between DNA damage repair (DDR) and cancer is intricately intertwined; however, its specific role in esophageal squamous cell carcinoma (ESCC) remains enigmatic. METHODS: Employing single-cell analysis, we delineated the functionality of DDR-related genes within the tumor microenvironment (TME). A diverse array of scoring mechanisms, including AUCell, UCell, singscore, ssgsea, and AddModuleScore, were harnessed to scrutinize the activity of DDR-related genes across different cell types. Differential pathway alterations between high-and low-DDR activity cell clusters were compared. Furthermore, leveraging multiple RNA-seq datasets, we constructed a robust DDR-associated signature (DAS), and through integrative multiomics analysis, we explored differences in prognosis, pathways, mutational landscapes, and immunotherapy predictions among distinct DAS groups. RESULTS: Notably, high-DDR activity cell subpopulations exhibited markedly enhanced cellular communication. The DAS demonstrated uniformity across multiple datasets. The low-DAS group exhibited improved prognoses, accompanied by heightened immune infiltration and elevated immune checkpoint expression. SubMap analysis of multiple immunotherapy datasets suggested that low-DAS group may experience enhanced immunotherapy responses. The "oncopredict" R package analyzed and screened sensitive drugs for different DAS groups. CONCLUSION: Through the integration of single-cell and bulk RNA-seq data, we have developed a DAS associated with prognosis and immunotherapy response. This signature holds promise for the future stratification and personalized treatment of ESCC patients in clinical settings.

Genuine Dirac Half-Metals in Two-Dimensions.

When spin-orbit coupling (SOC) is absent, all proposed half-metals with twofold degenerate nodal points at the K (or K') point in 2D materials are classified as "Dirac half-metals" owing to the way graphene is utilized in the earliest studies. Actually, each band crossing point at the K or K' point is described by a 2D Weyl Hamiltonian with definite chirality; hence, it should be a Weyl point. To the best of its knowledge, there have not yet been any reports of a genuine (i.e., fourfold degenerate) 2D Dirac point half-metal. In this work, using first-principles calculations, it proposes for the first time that the 2D d0 -type ferromagnet Mg4 N4 is a genuine 2D Dirac half-metal candidate with a fourfold degenerate Dirac point at the S high-symmetry point, intrinsic magnetism, a high Curie temperature, 100% spin polarization, topology robust under the SOC and uniaxial and biaxial strains, and spin-polarized edge states. This work can serve as a starting point for future predictions of intrinsically magnetic materials with genuine 2D Dirac points, which will aid the frontier of topo-spintronics research in 2D systems.

Quality of life after lung cancer surgery: sublobar resection versus lobectomy.

BACKGROUND: This study aimed to compare the postoperative quality of life (PQOL) between non-small-cell lung cancer (NSCLC) patients who underwent video-assisted thoracoscopic sublobar resection (subsegment, segment, or wedge) and lobectomy. Meanwhile, we developed a PQOL scale for patients with NSCLC after optimization. METHODS: Developing and evaluating the postoperative quality-of-life scale of non-small-cell lung cancer (NSCLC-PQOL) followed by the international principles for developing quality-of-life scale. Therefore, we used the NSCLC-PQOL scale to evaluate the PQOL of patients who underwent different surgeries. RESULTS: The overall PQOL of patients who underwent video-assisted thoracoscopic lobectomy and sublobar resection gradually worsened from discharge to 3 months postoperatively and progressively improved from three to 6 months postoperatively. And the sublobar resection group showed better PQOL in chest tightness, breath shortness, breathlessness, cough and expectoration than the lobectomy group, and the differences were statistically significant (P < 0.05). The final version of the NSCLC-PQOL contained three dimensions: "signs-symptoms", "psychological and psychiatric", and "social-life" dimensions. CONCLUSIONS: The sublobar resection group showed better PQOL in "chest tightness", "breath shortness", "breathlessness", "cough", and "expectoration" than the lobectomy group. Twenty-two items formed a well-behaved PQOL scale after being validated satisfactorily. The scale was a suitable rating tool for evaluating the NSCLC-PQOL of patients. TRIAL REGISTRATION: As this study was a retrospective study and not a clinical trial, we did not register this study in the Chinese Clinical Trial Registry.

CT-based radiomics model to predict spread through air space in resectable lung cancer.

BACKGROUND: Spread through air space (STAS) has been identified as a pathological pattern associated with lung cancer progression. Patients with STAS were related to a worse prognosis compared with patients without STAS. The objective of this study was to establish a radiomics model capable of forecasting STAS before surgery, which can assist surgeons in selecting the most appropriate operation type for patients with STAS. METHOD: There were 537 eligible patients retrospectively included in this study. ROI segmentation was performed manually on all CT images to identify the region of interest. From each segmented lesion, a total of 1688 features were extracted. The tumor size, maximum tumor diameters, and tumor type were also recorded. Using Spearman's correlation coefficient to calculate the correlation and redundancy of elements, and redundant features less than 0.80 were removed. In order to reduce the level of overfitting and avoid statistical biases, a dimension reduction process of the dataset was conducted to decrease the number of features. Finally, a radiomics model included 44 features was established to predict STAS. To evaluate the performance of the model, the receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated, and the accuracy of the model was verified by 10-fold cross-validation. RESULTS: The incidence of STAS was 38.2% (205/537). The tumor type, maximum tumor diameters, and consolidation tumor ratio were significantly different between STAS group and non-STAS group. The training group included 430 patients, while the test group was consisted with 107. The training group achieved an AUC of 0.825 (sensitivity, 0.875; specificity, 0.621; and accuracy, 0.749) and the test group had an AUC of 0.802 (sensitivity, 0.797; specificity,0.688; and accuracy, 0.748). The 10-fold cross-validation had an AUC of 0.834. CONCLUSION: CT-based radiomic model can predict STAS effectively, which is of great importance to guide the selection of operation types before surgery.

Real-World Effectiveness and Prognostic Factors Analysis of Stages I-III Non-Small Cell Lung Cancer Following Neoadjuvant Chemo-Immunotherapy or Neoadjuvant Chemotherapy.

PURPOSE: Immune checkpoint inhibitors (ICIs) have been successfully used in many clinical trials related to immunotherapy. This study aimed to investigate the clinical efficacy of ICIs and prognostic factors in patients with resectable non-small cell lung cancer (NSCLC) following neoadjuvant therapy in the real world. METHODS: A total of 170 consecutive patients were finally selected and divided into two groups: the preoperative chemotherapy group (n = 91) and the chemo-immunotherapy group (n = 79). The primary endpoint was disease-free survival (DFS). The secondary endpoints were pathological response, clinical response, pathological nodal disease, and ability of multivariate Cox regression analysis to predict survival. Survival was estimated using Kaplan-Meier method and compared using log-rank test. RESULTS: There was a statistically significant difference in DFS between the two groups (log-rank test, P = 0.019). Multivariate Cox regression analysis showed that maximum tumor diameter (P = 0.016), higher lymph node stage (ypN1, P = 0.016; ypN2, P <0.001), and major pathological response not achieved (non-major pathological response [MPR], P = 0.011) were independent prognostic factors for worse DFS. CONCLUSION: Neoadjuvant chemo-immunotherapy yields better effects in pathological and clinical response than chemotherapy alone, which is also associated with longer DFS in the treatment of locally advanced NSCLC. Moreover, a larger tumor specimen diameter, higher ypN staging, and non-MPR after neoadjuvant therapy were associated with worse prognosis.

Risk factors and survival analysis of arrhythmia following lung cancer surgery: a retrospective study.

BACKGROUND: Surgical treatment of lung cancer is one of the important treatments for early-stage non-small cell lung cancer (NSCLC). However, arrhythmia, especially atrial fibrillation (AF) and supraventricular arrhythmia, are quite common among patients after surgical treatment of lung cancer. The impact of postoperative arrhythmia (PA) on survival is rarely reported. Our aim was to evaluate the risk factors of PA and its impact on overall survival (OS) after lung cancer surgery. METHODS: A total of 344 patients diagnosed with NSCLC who underwent lung cancer surgery were enrolled in this study. These patients were divided into two groups based on the occurrence of PA. Univariate and multivariate logistic regression analyses were conducted to identify the risk factors of PA. The Kaplan-Meier method was applied to show the OS differences between the two groups. RESULTS: The incidence of PA was 16% (55/344). Among these 55 patients, 20 had AF, 30 had sinus tachycardia, and 5 had premature beats. A total of 332 patients underwent lung cancer radical resection. Operation type (P<0.001), preoperative abnormal ECG (P=0.032), transfusion (P=0.016), postoperative serum potassium concentration (P=0.001) and clinical stage (P<0.05) were risk factors for PA. PA (HR 2.083, 95% CI, 1.334-3.253; P=0.001), age (HR 1.543, 95% CI, 1.063-2.239; P=0.025) and mediastinal lymph node metastasis (HR 2.655, 95% CI, 1.809-3.897; P<0.001) were independent prognostic risk factors for OS by multivariate cox analysis. CONCLUSIONS: We identified PA as an independent prognostic risk factor to predict poor OS in patients who underwent lung cancer surgery and had risk factors for PA. We therefore provides guidance for PA in improving the prognosis of lung cancer patients.

A prognostic nomogram for lung adenocarcinoma based on immune-infiltrating Treg-related genes: from bench to bedside.

BACKGROUND: Accumulating evidence suggests that lymphocyte infiltration in the tumor microenvironment is positively correlated with tumorigenesis and development, while the role of Tregs (regulatory T cells) has been controversial. Therefore, we attempted to discover the possible value of Tregs for lung adenocarcinoma (LUAD). METHODS: The gene-sequencing data of LUAD were applied from three Gene Expression Omnibus (GEO) datasets-GSE10072, GSE32863 and GSE43458; the corresponding fractions of tumor-infiltrating immune cells were extracted from the CIBERSORTx portal. Weighted gene coexpression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis were conducted to identify the significant module and candidate genes related to Tregs. The role of candidate genes in LUAD was further verified using data from The Cancer Genome Atlas (TCGA) database. Finally, we constructed a nomogram model to predict the prognosis of LUAD by plotting Kaplan-Meier (K-M), receiver operating characteristic (ROC) and calibration curves, which elucidated the performance of the nomogram. RESULTS: In total, 10,047 genes in 333 samples (196 tumor and 137 normal samples) from the GEO database were included. By WGCNA and PPI analysis, we identified a significant black module and 36 candidate genes related to Treg. Next, the candidate genes were verified using TCGA data by Cox regression analysis to screen 13 hub genes that stratified LUAD patients into low- or high-risk groups. Low-risk patients showed a significantly longer overall survival (OS) than high-risk patients (3-year OS: 70.2% vs. 35.2%; 5-year OS: 36.6% vs. 0; P=1.651E-09), and the areas under the ROC curves (AUCs) showed good (3-year AUC: 0.733; 5-year AUC: 0.777). Next, we constructed a survival nomogram combining the hub genes and clinical parameters; the low-risk patients still showed a favorable prognosis compared with that of the high-risk patients (P=7.073E-13), and the AUCs were better (3-year AUC: 0.763; 5-year AUC: 0.873). CONCLUSIONS: We revealed the role of immune-infiltrating Treg-related genes in LUAD and constructed a prognostic nomogram, which may help clinicians make optimal therapeutic decisions and help patients obtain better outcomes.

Development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes.

BACKGROUND: Given that abnormal autophagy is involved in the pathogenesis of cancers, we sought to explore the potential value of autophagy-associated genes in lung adenocarcinoma (LUAD). METHODS: RNA sequencing and clinical data on tumour and normal samples were acquired from The Cancer Genome Atlas (TCGA) database and randomly assigned to training and testing groups. Differentially expressed autophagy-associated genes (AAGs) were screened. Within the training group, Cox regression and Lasso regression analyses were conducted to screen five prognostic AAGs, which were used to develop a model. Kaplan-Meier (KM) and receiver operating characteristic (ROC) curves were plotted to determine the performance of the model in both groups. Immunohistochemistry was used to demonstrate the differential expression of AAGs in tumour and normal tissues at the protein level. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to further elucidate the roles of AAGs in LUAD. RESULTS: The data from the TCGA database included 497 tumour and 54 normal samples, within which 30 differentially expressed AAGs were screened. Using Cox regression and Lasso regression analyses for the training group, 5 prognostic AAGs were identified and the prognostic model was constructed. Patients with low risk had better overall survival (OS) in the training group (3-year OS, 73.0% vs 48.0%; 5-year OS, 45.0% vs 33.8%; P = 1.305E-04) and in the testing group (3-year OS, 66.8% vs 41.2%; 5-year OS, 31.7% vs 25.8%; P = 1.027E-03). The areas under the ROC curves (AUC) were significant for both the training and testing groups (3-year AUC, 0.810 vs 0.894; 5-year AUC, 0.792 vs 0.749). CONCLUSIONS: We developed a survival model for LUAD and validated the performance of the model, which may provide superior outcomes for the patients.

[Nitrate Source Identification and Nitrification-denitrification at the Sediment-water Interface].

Identifying nitrate sources and its transformation mechanisms are important for nitrate pollution control in surface water. The columnar core sediment samples in West Lake were taken in different seasons. The transformation of nitrogen at the sediment-water interface was studied using nitrogen and oxygen isotopes, stable isotope analysis in R (SIAR) and acetylene inhibition method in the West Lake, Hangzhou. The results showed that the concentration gradient of both NO3-and NH4+ existed at the sediment-water interface. NO3- concentrations decreased from bottom water to pore water and NO3- was accumulated in sediments. NH4+ concentrations increased from bottom water to pore water and NH4+ was released from sediments. Nitrate sources in bottom water where nitrification exited were sewage (manure), soil nitrogen, chemical fertilizer and precipitation. Sewage (manure) was the major nitrogen contributor (60.8%) in summer. Particularly high δ15 N values in pore water indicated that there was strong denitrification at the sediment-water interface in West Lake. The average nitrification rate and denitrification rate at the sediment-water interface were 2.85 mmol·(m2·d)-1 and 23.51 µmol·(m2·d)-1, respectively. The sediment-water interface played a role in nitrogen removal process in aquatic environment. Seasonal and spatial variations of nitrification rates and denitrification rates were found in this study. Temperature and dissolved oxygen were the main influential factors for the transformation of nitrogen at the sediment-water interface in West Lake.