Optical moiré bound states in the continuum.

Trapping electromagnetic waves within the radiation continuum holds significant implications in the field of optical science and technology. Photonic bound states in the continuum (BICs) present a distinctive approach for achieving this functionality, offering potential applications in laser systems, sensing technologies, and other domains. However, the simultaneous achievement of high Q-factors, flat-band dispersions, and wide-angle responses in photonic BICs has not yet been reported, thereby impeding their practical performance due to laser direction deviation or sample disorder. Here, we theoretically demonstrate the construction of moiré BICs in one-dimensional photonic crystal (PhC) slabs, where high-Q resonances in the entire moiré flat band are achieved. Specifically, we numerically validate that the radiation loss of moiré BICs can be eliminated by aligning multiple topological polarization charges with all diffraction channels, enabling the strong suppression of far-field radiation from the entire moiré band. This leads to a slow decay of Q-factors away from moiré BICs in the momentum space. Moreover, it is found that Q-factors of the moiré flat band can still maintain at a high level with structural disorder. In experiments, we fabricate the designed 1D moiré PhC slab and observe both high-Q resonances and a slow decrease of Q-factors for moiré flat-band Bloch modes. Our findings hold promising implications for designing highly efficient optical devices with wide-angle responses and introduce a novel avenue for exploring BICs in moiré superlattices.

High-Active Surface of Centimeter-Scale ß-In2S3 for Attomolar-Level Hg2+ Sensing.

Recognition layer materials play a crucial role in the functionality of chemical sensors. Although advancements in two-dimensional (2D) materials have promoted sensor development, the controlled fabrication of large-scale recognition layers with highly active sites remains crucial for enhancing sensor sensitivity, especially for trace detection applications. Herein, we propose a strategy for the controlled preparation of centimeter-scale non-layered ultrathin ß-In2S3 materials with tailored high-active sites to design ultrasensitive Hg2+ sensors. Our results reveal that the highly active sites of non-layered ß-In2S3 materials are pivotal for achieving superior sensing performance. Selective detection of Hg2+ at the 1 aM level is achieved via selective Hg-S bonding. Additionally, we evaluate that this sensor exhibits excellent performance in detecting Hg2+ in the tap water matrix. This work provides a proof-of-concept for utilizing non-layered 2D films in high-performance sensors and highlights their potential for diverse analyte sensing applications.

Poly(ether imide) Film Doped with Protonated Tetra(aniline) Molecules for Efficiently Enhancing the Capacitive Energy Storage Performance.

The polymer dielectric spacer plays a key role in the performance of film capacitors. However, currently, commercial polymer dielectric films generally have low relative dielectric constants (<4) and low capacitive energy storage densities (<3 J cm-3). Here, we report the use of protonated tetra(aniline) (TANI) molecules with a length of 1.3 nm to improve the energy storage performance of poly(ether imide) (PEI) films. With only a small content of TANI doping, i.e., 0.7 wt %, both the dielectric constant and energy storage density of PEI film can be significantly improved, while the dielectric loss remains as low as that of pure PEI. A maximum energy density of 9.4 J cm-3 is achieved. To manifest the efficacy of protonated TANI, polyaniline and deprotonated TANI are also prepared and used as dopants in PEI. The PANI filler can also increase the dielectric constant, while the dielectric loss is increased as well. The deprotonated TANI doped in PEI has no influence on both the dielectric constant and energy density, implying that the protonated amino groups of TANI molecules are responsible for the enhanced dielectric constant of the PEI/TANI composite. The correlation between protonation of TANI dopants and dielectric properties is discussed in detail.

Heterostructured n-ZnO@p-CuO nanosheets filled in a polymer matrix for enhanced electrostatic energy storage performance.

Metallized film capacitors use plastic films as the dielectric spacer, and these polymer films generally have low dielectric constants. To boost the electrostatic energy storage density of a film capacitor, advanced high-k films with high electrical breakdown strength and low dielectric loss are highly desired. Herein, polymer nanocomposite films were made by filling ZnO@CuO nanosheets into poly(vinylidene fluoride-co-hexafluoropropylene) [P(VDF-HFP)]. The n-type ZnO nanosheets are synthesized in an aqueous solution. Through a calcination process, thin layers of p-type CuO are coated over the ZnO nanosheets. Compared to pure P(VDF-HFP) and ZnO/P(VDF-HFP) films, the ZnO@CuO/P(VDF-HFP) films exhibit higher dielectric constant and higher breakdown strength. The optimal content of ZnO@CuO nanosheet in the polymer matrix is determined to be 3 wt%, which leads to a dielectric constant of 15.6 at 1 kHz and the highest energy density of 5.6 J cm-3. The efficacy of ZnO@CuO nanosheets in enhancing the dielectric performance of the polymer nanocomposite is elucidated in detail. This research provides a scalable and low-cost strategy to produce polymer nanocomposite films with high capacitive energy storage performance.

Large-Scale Synthesis of High-Loading Single Metallic Atom Catalysts by a Metal Coordination Route.

Single atom catalyst (SAC) is one of the most efficient and versatile catalysts with well-defined active sites. However, its facile and large-scale preparation, the prerequisite of industrial applications, has been very challenging. This dilemma originates from the Gibbs-Thomson effect, which renders it rather difficult to achieve high single atom loading (< 3 mol%). Further, most synthesizing procedures are quite complex, resulting in significant mass loss and thus low yields. Herein, a novel metal coordination route is developed to address these issues simultaneously, which is realized owing to the rapid complexation between ligands (e.g., biuret) and metal ions in aqueous solutions and subsequent in situ polymerization of the formed complexes to yield SACs. The whole preparation process involves only one heating step operated in air without any special protecting atmospheres, showing general applicability for diverse transition metals. Take Cu SAC for an example, a record yield of up to 3.565 kg in one pot and an ultrahigh metal loading 16.03 mol% on carbon nitride (Cu/CN) are approached. The as-prepared SACs are demonstrated to possess high activity, outstanding selectivity, and robust cyclicity for CO2 photoreduction to HCOOH. This research explores a robust route toward cost-effective, massive production of SACs for potential industrial applications.

Reversal of tamoxifen resistance by artemisinin in ER+ breast cancer: bioinformatics analysis and experimental validation.

Breast cancer is the leading cause of cancer-related deaths in women worldwide, with Hormone Receptor (HR)+ being the predominant subtype. Tamoxifen (TAM) serves as the primary treatment for HR+ breast cancer. However, drug resistance often leads to recurrence, underscoring the need to develop new therapies to enhance patient quality of life and reduce recurrence rates. Artemisinin (ART) has demonstrated efficacy in inhibiting the growth of drug-resistant cells, positioning art as a viable option for counteracting endocrine resistance. This study explored the interaction between artemisinin and tamoxifen through a combined approach of bioinformatics analysis and experimental validation. Five characterized genes (ar, cdkn1a, erbb2, esr1, hsp90aa1) and seven drug-disease crossover genes (cyp2e1, rorc, mapk10, glp1r, egfr, pgr, mgll) were identified using WGCNA crossover analysis. Subsequent functional enrichment analyses were conducted. Our findings confirm a significant correlation between key cluster gene expression and immune cell infiltration in tamoxifen-resistant and -sensitized patients. scRNA-seq analysis revealed high expression of key cluster genes in epithelial cells, suggesting artemisinin's specific impact on tumor cells in estrogen receptor (ER)-positive BC tissues. Molecular target docking and in vitro experiments with artemisinin on LCC9 cells demonstrated a reversal effect in reducing migratory and drug resistance of drug-resistant cells by modulating relevant drug resistance genes. These results indicate that artemisinin could potentially reverse tamoxifen resistance in ER-positive breast cancer.

Topologically Protected Quantum Logic Gates with Valley-Hall Photonic Crystals.

Topological photonics provide a promising way to realize more robust optical devices against some defects and environmental perturbations. Quantum logic gates are fundamental units of quantum computers, which are widely used in future quantum information processing. Thus, constructing robust universal quantum logic gates is an important way forward to practical quantum computing. However, the most important problem to be solved is how to construct the quantum-logic-gate-required 2 × 2 beam splitter with topological protection. Here, the experimental realization of the topologically protected contradirectional coupler is reported, which can be employed to realize the quantum logic gates, including control-NOT and Hadamard gates, on the silicon photonic platform. These quantum gates not only have high experimental fidelities but also exhibit a certain degree of tolerances against certain types of defects. This work paves the way for the development of practical optical quantum computations and signal processing.

Hyperbolic photonic topological insulators.

Topological photonics provides a new degree of freedom to robustly control electromagnetic fields. To date, most of established topological states in photonics have been employed in Euclidean space. Motivated by unique properties of hyperbolic lattices, which are regular tessellations in non-Euclidean space with a constant negative curvature, the boundary-dominated hyperbolic topological states have been proposed. However, limited by highly crowded boundary resonators and complicated site couplings, the hyperbolic topological insulator has only been experimentally constructed in electric circuits. How to achieve hyperbolic photonic topological insulators is still an open question. Here, we report the experimental realization of hyperbolic photonic topological insulators using coupled ring resonators on silicon chips. Boundary-dominated one-way edge states with pseudospin-dependent propagation directions have been observed. Furthermore, the robustness of edge states in hyperbolic photonic topological insulators is also verified. Our findings have potential applications in the field of designing high-efficient topological photonic devices with enhanced boundary responses.

Non-Abelian Topological Bound States in the Continuum.

Bound states in the continuum (BICs), which are spatially localized states with energies lying in the continuum of extended modes, have been widely investigated in both quantum and classical systems. Recently, the combination of topological band theory with BICs has led to the creation of topological BICs that exhibit extraordinary robustness against disorder. However, the previously proposed topological BICs are only limited in systems with Abelian gauge fields. Whether non-Abelian gauge fields can induce topological BICs and how to experimentally explore these phenomena remains unresolved. Here, we report the theoretical and experimental realization of non-Abelian topological BICs, which are generated by the interplay between two inseparable pseudospins and can coexist in each pseudospin subspace. This unique characteristic necessitates non-Abelian couplings that lack any Abelian counterparts. Furthermore, the non-Abelian couplings can also offer a new avenue for constructing topological subspace-induced BICs at bulk dislocations. Those exotic phenomena are observed by non-Abelian topolectrical circuits. Our results establish the connection between topological BICs and non-Abelian gauge fields, and serve as the catalyst for future investigations on non-Abelian topological BICs across different platforms.

An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer.

Background: Ovarian cancer (OC) has the highest mortality rate among gynecological malignancies. Current treatment options are limited and ineffective, prompting the discovery of reliable biomarkers. Exosome lncRNAs, carrying genetic information, are promising new markers. Previous studies only focused on exosome-related genes and employed the Lasso algorithm to construct prediction models, which are not robust. Methods: 420 OC patients from the TCGA datasets were divided into training and validation datasets. The GSE102037 dataset was used for external validation. LncRNAs associated with exosome-related genes were selected using Pearson analysis. Univariate COX regression analysis was used to filter prognosis-related lncRNAs. The overlapping lncRNAs were identified as candidate lncRNAs for machine learning. Based on 10 machine learning algorithms and 117 algorithm combinations, the optimal predictor combinations were selected according to the C index. The exosome-related LncRNA Signature (ERLS) model was constructed using multivariate COX regression. Based on the median risk score of the training datasets, the patients were divided into high- and low-risk groups. Kaplan-Meier survival analysis, the time-dependent ROC, immune cell infiltration, immunotherapy response, and immune checkpoints were analyzed. Results: 64 lncRNAs were subjected to a machine-learning process. Based on the stepCox (forward) combined Ridge algorithm, 20 lncRNA were selected to construct the ERLS model. Kaplan-Meier survival analysis showed that the high-risk group had a lower survival rate. The area under the curve (AUC) in predicting OS at 1, 3, and 5 years were 0.758, 0.816, and 0.827 in the entire TCGA cohort. xCell and ssGSEA analysis showed that the low-risk group had higher immune cell infiltration, which may contribute to the activation of cytolytic activity, inflammation promotion, and T-cell co-stimulation pathways. The low-risk group had higher expression levels of PDL1, CTLA4, and higher TMB. The ERLS model can predict response to anti-PD1 and anti-CTLA4 therapy. Patients with low expression of PDL1 or high expression of CTLA4 and low ERLS exhibited significantly better survival prospects, whereas patients with high ERLS and low levels of PDL1 or CTLA4 exhibited the poorest outcomes. Conclusion: Our study constructed an ERLS model that can predict prognostic risk and immunotherapy response, optimizing clinical management for OC patients.

CRP, IL-1α, IL-1ß, and IL-6 levels and the risk of breast cancer: a two-sample Mendelian randomization study.

Epidemiological studies have reported a positive association between chronic inflammation and cancer risk. However, the causal association between chronic inflammation and breast cancer (BC) risk remains unclear. Here, we performed a Mendelian randomization study to investigate the etiological role of chronic inflammation in BC risk. We acquired data regarding C-reactive protein (CRP), interleukin (IL)-1a, IL-1b, and IL-6 expression and BC related to single nucleotide polymorphisms (SNPs) from two larger consortia (the genome-wide association studies and the Breast Cancer Association Consortium). Next, we conducted the two-sample Mendelian randomization study to investigate the relationship of the abovementioned inflammatory factors with the incidence of BC. We found that genetically predicted CRP, IL-6, and IL-1a levels did not increase BC incidence (odds ratio (OR)CRP 1.06, 95% confidence interval (CI) 0.98-1.12, P = 0.2059, ORIL-6 1.05, 95% CI 0.95-1.16, P = 0.3297 and ORIL-1a 1.01, 95% CI 0.99-1.03, P = 0.2167). However, in subgroup analysis, genetically predicted IL-1b levels increased ER + BC incidence (OR 1.15, 95% CI 1.03-1.27, P = 0.0088). Our study suggested that genetically predicted IL-1b levels were found to increase ER + BC susceptibility. However, due to the support of only one SNP, heterogeneity and pleiotropy tests cannot be performed, which deserves further research.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels the heterogeneity of cancer-associated fibroblasts in TNBC.

BACKGROUND: The treatment of triple-negative breast cancer (TNBC) is one of the main focuses and key difficulties because of its heterogeneity, and the source of this heterogeneity is unclear. METHODS: Single-cell RNA (scRNA) and transcriptomics data of TNBC and normal breast samples were retrieved from Gene Expression Omnibus (GEO) database and TCGA-BRCA database. These cells were clustered using the t-SNE and UMAP method, and the marker genes for each cluster were found. We annotated the clusters using the published literature, CellMarker database and "SingleR" R package. RESULTS: A total of 1535 cells and 21785 genes from 6 TNBC patients and 2068 cells and 15868 genes from 3 normal breast tissues were used for downstream analyses. The scRNA data were divided into 14 clusters labeled into 8 cell types, including epithelial cells, immunocytes, CAFs/fibroblasts and etc. In the TNBC samples, CAFs were divided into three clusters and labelled as prCAFs, myCAFs and emCAFs, and the marker genes were DCN, FAP and RGS5, respectively. The prCAF subgroup is functionally characterized by promoting proliferation and multi drug resistance; myCAF subgroup is involved in constituting the extracellular matrix and collagen production, matrix composition and collagen production, and the emCAF functionally characterized by energy metabolism. CONCLUSIONS: TNBC has inter- and intra-tumor heterogeneity, and CAF is one of the sources of this heterogeneity. CD74, SASH3, CD2, TAGAP and CCR7 served as significant marker genes with prognostic and therapeutic value.

Severe mental illness and the risk of breast cancer: A two-sample, two-step multivariable Mendelian randomization study.

BACKGROUND: Based on epidemiological reports, severe mental illness (SMI) and breast cancer (BC) risk are linked positively. However, it is susceptible to clinical confounding factors, such as smoking, alcohol consumption, etc. Here, we performed a two-sample, two-step multivariable Mendelian randomization (MR) research to explore how the SMI etiologically influences BC risk and to quantify mediating effects of known modifiable risk factors. METHODS: Data concerning the single nucleotide polymorphism (SNP)-associated with schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), and BC were obtained from two large consortia: the Breast Cancer Association Consortium (BCAC) and the Psychiatric Genomics Consortium (PGC). Then, the correlations of the previous SMI with the BC prevalence and the potential impact of mediators were explored through the two-sample and two-step MR analyses. RESULTS: In two-sample MR, schizophrenia increased BC incidence (odds ratio (OR) 1.06, 95% confidence interval (CI) 1.02-1.10, P = 0.001). In subgroup analysis, schizophrenia increased ER+ BC (OR 1.06, 95% CI 1.03-1.10, P = 0.0009) and ER-BC (OR 1.06, 95% CI 1.01-1.11, P = 0.0123) incidences. Neither MDD nor BD elevated the BC risk. In two-step MR, smoking explained 11.29% of the schizophrenia-all BC risk association. CONCLUSIONS: Our study indicates that schizophrenia increases susceptibility to breast cancer, with smoking playing a certain mediating role. Therefore, BC screening and smoking should be incorporated into the health management of individuals with schizophrenia.

Non-Abelian Inverse Anderson Transitions.

Inverse Anderson transitions, where the flat-band localization is destroyed by disorder, have been wildly investigated in quantum and classical systems in the presence of Abelian gauge fields. Here, we report the first investigation on inverse Anderson transitions in the system with non-Abelian gauge fields. It is found that pseudospin-dependent localized and delocalized eigenstates coexist in the disordered non-Abelian Aharonov-Bohm cage, making inverse Anderson transitions depend on the relative phase of two internal pseudospins. Such an exotic phenomenon induced by the interplay between non-Abelian gauge fields and disorder has no Abelian analogy. Furthermore, we theoretically design and experimentally fabricate non-Abelian Aharonov-Bohm topolectrical circuits to observe the non-Abelian inverse Anderson transition. Through the direct measurements of frequency-dependent impedance responses and voltage dynamics, the pseudospin-dependent non-Abelian inverse Anderson transitions are observed. Our results establish the connection between inverse Anderson transitions and non-Abelian gauge fields, and thus comprise a new insight on the fundamental aspects of localization in disordered non-Abelian flat-band systems.

Effect of ERCC1 polymorphisms on the response to platinum-based chemotherapy: A systematic review and meta-analysis based on Asian population.

BACKGROUND: Platinum-based chemotherapy is one of the most common treatments for many cancers; however, the effect of chemotherapy varies from individual to individual. Excision repair cross complementation group 1 (ERCC1) is widely recognized as a key gene regulating nucleotide excision repair (NER) and is closely associated with platinum response. Many studies have yielded conflicting results regarding whether ERCC1 polymorphisms can affect the response to platinum and overall survival (OS). Therefore, it is necessary to perform a meta-analysis of patients with specific races and cancer types. METHODS: Eight databases (EMBASE, PubMed, Cochrane Library, Chinese National Knowledge Infrastructure, Scopus, VIP, China Biology Medicine disc and Wanfang databases) were searched. Results were expressed in terms of odds ratios (ORs), hazard ratios (HRs) and 95% CIs. RESULTS: In this study, rs11615, rs2298881 and rs3212986 SNPs were studied. In the comparison between CT and TT on the response to platinum, esophageal cancer [I2 = 0%, OR = 6.18, 95% CI(1.89,20.23), P = 0.003] and ovarian cancer [I2 = 0%, OR = 4.94, 95% CI(2.21,11.04), P<0.001] showed that the rs11615 CT genotype predicted a better response. In the comparison between CC and TT, ovarian cancer [I2 = 48.0%, OR = 6.15, 95% CI (2.56,14.29), P<0.001] indicated that the CC genotype predicted a better response. In the meta-analysis of OS, the CC genotype was related to longer OS than TT in ovarian cancer [TT vs CC: I2 = 57.7%, HR = 1.71, 95% CI (1.18, 2.49), P<0.001]. CONCLUSION: The ERCC1 rs11615 polymorphism was related to the response to platinum and OS, but the correlation is based on specific cancer types in the Asian population.

Super-compact universal quantum logic gates with inverse-designed elements.

Integrated quantum photonic circuit is a promising platform for the realization of quantum information processing in the future. To achieve the large-scale quantum photonic circuits, the applied quantum logic gates should be as small as possible for the high-density integration on chips. Here, we report the implementation of super-compact universal quantum logic gates on silicon chips by the method of inverse design. In particular, the fabricated controlled-NOT gate and Hadamard gate are both nearly a vacuum wavelength, being the smallest optical quantum gates reported up to now. We further design the quantum circuit by cascading these fundamental gates to perform arbitrary quantum processing, where the corresponding size is about several orders smaller than that of previous quantum photonic circuits. Our study paves the way for the realization of large-scale quantum photonic chips with integrated sources and can have important applications in the field of quantum information processes.

Macrophages Phenotype Regulated by IL-6 Are Associated with the Prognosis of Platinum-Resistant Serous Ovarian Cancer: Integrated Analysis of Clinical Trial and Omics.

Background: The treatment of platinum-resistant recurrent ovarian cancer (PROC) is a clinical challenge and a hot topic. Tumor microenvironment (TME) as a key factor promoting ovarian cancer progression. Macrophage is a component of TME, and it has been reported that macrophage phenotype is related to the development of PROC. However, the mechanism underlying macrophage polarization and whether macrophage phenotype can be used as a prognostic indicator of PROC remains unclear. Methods: We used ESTIMATE to calculate the number of immune and stromal components in high-grade serous ovarian cancer (HGSOC) cases from The Cancer Genome Atlas database. The differential expression genes (DEGs) were analyzed via protein-protein interaction network, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analysis to reveal major pathways of DEGs. CD80 was selected for survival analysis. IL-6 was selected for gene set enrichment analysis (GSEA). A subsequent cohort study was performed to confirm the correlation of IL-6 expression with macrophage phenotype in peripheral blood and to explore the clinical utility of macrophage phenotype for the prognosis of PROC patients. Results: A total of 993 intersecting genes were identified as candidates for further survival analysis. Further analysis revealed that CD80 expression was positively correlated with the survival of HGSOC patients. The results of GO and KEGG analysis suggested that macrophage polarization could be regulated via chemokine pathway and cytokine-cytokine receptor interaction. GSEA showed that the genes were mainly enriched in IL-6-STAT-3. Correlation analysis for the proportion of tumor infiltration macrophages revealed that M2 was correlated with IL-6. The results of a cohort study demonstrated that the regulation of macrophage phenotype by IL-6 is bidirectional. The high M1% was a protective factor for progression-free survival. Conclusion: Thus, the macrophage phenotype is a prognostic indicator in PROC patients, possibly via a hyperactive IL-6-related pathway, providing an additional clue for the therapeutic intervention of PROC.

Comprehensive analysis of a cuproptosis-related ceRNA network implicates a potential endocrine therapy resistance mechanism in ER-positive breast cancer.

BACKGROUND: While adjuvant endocrine therapy (ET) may decrease the mortality rate of estrogen receptor-positive (ER+) breast cancer (BC), the likelihood of relapse and metastasis due to ET resistance remains high. Cuproptosis is a recently discovered regulated cell death (RCD), whose role in tumors has yet to be elucidated. Thus, there is a need to study its specific regulatory mechanism in resistance to ET in BC, to identify novel therapeutic targets. METHODS: The prognostic cuproptosis-related genes (CRGs) in ER+ BC were filtered by undergoing Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses in TCGA-BRCA, and a CRGs risk signature was constructed using the correlation coefficient. Immune infiltration analysis, immune function analysis, tumor microenvironment (TME) analysis, immune checkpoint analysis, immunotherapy response analysis, drug sensitivity analysis, and pathway activation analysis were carried out among the high- and low-risk groups in turn. The central CRG of cuproptosis in ER+ BC resistance to ET was acquired through the intersection of protein interaction network (PPI) analysis, genes differentially expressed (DEGs) between human BC cells LCC9 and MCF-7 (GSE159968), and CRGs with prognostic significance in TCGA-BRCA ER+ BC. The miRNAs upstream of the core CRGs were predicted based on the intersection of 4 databases, miRDB, RNA22, miRWalk, and RNAlnter. Candidate miRNAs consisted of the intersection of predicted miRNAs and miRNAs differentially expressed in the LCC9 and MCF-7 cell lines (GSE159979). Candidate lncRNAs were the intersection of the differential lncRNAs from the LCC9 and MCF-7 cell lines and the survival-related lncRNAs obtained from a univariate Cox regression analysis. Pearson's correlation analysis was performed between mRNA-miRNA, miRNA-lncRNA, and mRNA-lncRNA expression separately. RESULTS: We constructed A risk signature of 4-CRGs to predict the prognosis of ER+ BC in TCGA-BRCA, a risk score = DLD*0.378 + DBT*0.201 + DLAT*0.380 + ATP7A*0.447 was used as the definition of the formula. There were significant differences between the high- and low-risk groups based on the risk score of 4-CRGs in aspects of immune infiltration, immune function, expression levels of immune checkpoint genes, and signaling pathways. DLD was determined to be the central CRG of cuproptosis in ER+ BC resistance to ET through the intersection of the PPI network analysis, DEGs between LCC9 and MCF-7 and 4-CRGs. Two miRNAs hsa-miR-370-3p and hsa-miR-432-5p were found taking DLD mRNA as a target, and the lncRNA C6orf99 has been hypothesized to be a competitive endogenous RNA that regulates DLD mRNA expression by sponging off hsa-miR-370-3p and hsa-miR-432-5p. CONCLUSION: This study built a prognostic model based on genes related to cuproptosis in ER+ BC. We considered DLD to be the core gene associated with resistance to ET in ER+ BC via copper metabolism. The search for promising therapeutic targets led to the establishment of a cuproptosis-related ceRNA network C6orf99/hsa-miR-370-3p and hsa-miR-432-5p/DLD.

Non-Hermitian Topolectrical Circuit Sensor with High Sensitivity.

Electronic sensors play important roles in various applications, such as industry and environmental monitoring, biomedical sample ingredient analysis, wireless networks and so on. However, the sensitivity and robustness of current schemes are often limited by the low quality-factors of resonators and fabrication disorders. Hence, exploring new mechanisms of the electronic sensor with a high-level sensitivity and a strong robustness is of great significance. Here, a new way to design electronic sensors with superior performances based on exotic properties of non-Hermitian topological physics is proposed. Owing to the extreme boundary-sensitivity of non-Hermitian topological zero modes, the frequency shift induced by boundary perturbations can show an exponential growth trend with respect to the size of non-Hermitian topolectrical circuit sensors. Moreover, such an exponential growth sensitivity is also robust against disorders of circuit elements. Using designed non-Hermitian topolectrical circuit sensors, the ultrasensitive identification of the distance, rotation angle, and liquid level is further experimentally verified with the designed capacitive devices. The proposed non-Hermitian topolectrical circuit sensors can possess a wide range of applications in ultrasensitive environmental monitoring and show an exciting prospect for next-generation sensing technologies.

Remote Sensing Image of The Landsat 8-9 Compressive Sensing via Non-Local Low-Rank Regularization with the Laplace Function.

Utilizing low-rank prior data in compressed sensing (CS) schemes for Landsat 8-9 remote sensing images (RSIs) has recently received widespread attention. Nevertheless, most CS algorithms focus on the sparsity of an RSI and ignore its low-rank (LR) nature. Therefore, this paper proposes a new CS reconstruction algorithm for Landsat 8-9 remote sensing images based on a non-local optimization framework (NLOF) that is combined with non-convex Laplace functions (NCLF) used for the low-rank approximation (LAA). Since the developed algorithm is based on an approximate low-rank model of the Laplace function, it can adaptively assign different weights to different singular values. Moreover, exploiting the structural sparsity (SS) and low-rank (LR) between the image patches enables the restored image to obtain better CS reconstruction results of Landsat 8-9 RSI than the existing models. For the proposed scheme, first, a CS reconstruction model is proposed using the non-local low-rank regularization (NLLRR) and variational framework. Then, the image patch grouping and Laplace function are used as regularization/penalty terms to constrain the CS reconstruction model. Finally, to effectively solve the rank minimization problem, the alternating direction multiplier method (ADMM) is used to solve the model. Extensive numerical experimental results demonstrate that the non-local variational framework (NLVF) combined with the low-rank approximate regularization (LRAR) method of non-convex Laplace function (NCLF) can obtain better reconstruction results than the more advanced image CS reconstruction algorithms. At the same time, the model preserves the details of Landsat 8-9 RSIs and the boundaries of the transition areas.