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Multiferroic materials have great potential in non-volatile devices for low-power and ultra-high density information storage, owing to their unique characteristic of coexisting ferroelectric and ferromagnetic orders. The effective manipulation of their intrinsic anisotropy makes it promising to control multiple degrees of the storage “medium”. Here, we have discovered intriguing in-plane electrical and magnetic anisotropies in van der Waals (vdW) multiferroic CuCrP 2 S 6 . The uniaxial anisotropies of current rectifications, magnetic properties and magnon modes are demonstrated and manipulated by electric direction/polarity, temperature variation and magnetic field. More important, we have discovered the spin-flop transition corresponding to specific resonance modes, and determined the anisotropy parameters by consistent model fittings and theoretical calculations. Our work provides in-depth investigation and quantitative analysis of electrical and magnetic anisotropies with the same easy axis in vdW multiferroics, which will stimulate potential device applications of artificial bionic synapses, multi-terminal spintronic chips and magnetoelectric devices. Manipulating electrical and magnetic anisotropies will stimulate multi-terminal device applications. Here, the authors discover axis dependence of current rectifications, magnetic properties and magnon modes in van der Waals multiferroic CuCrP 2 S 6 .

Abstract Gliomas are the most common primary neuroepithelial tumors of the central nervous system in adults, of which glioblastoma is the deadliest subtype. Apart from the intrinsically indestructible characteristics of glioma (stem) cells, accumulating evidence suggests that the tumor microenvironment also plays a vital role in the refractoriness of glioblastoma. The primary functions of platelets are to stop bleeding and regulate thrombosis under physiological conditions. Furthermore, platelets are also active elements that participate in a variety of processes of tumor development, including tumor growth, invasion, and chemoresistance. Glioma cells recruit and activate resting platelets to become tumor-educated platelets (TEPs), which in turn can promote the proliferation, invasion, stemness, and chemoresistance of glioma cells. TEPs can be used to obtain genetic information about gliomas, which is helpful for early diagnosis and monitoring of therapeutic effects. Platelet membranes are intriguing biomimetic materials for developing efficacious drug carriers to enhance antiglioma activity. Herein, we review the recent research referring to the contribution of platelets to the malignant characteristics of gliomas and focusing on the molecular mechanisms mediating the interaction between TEPs and glioma (stem) cells, as well as present the challenges and opportunities in targeting platelets for glioma therapy.

Abdominal aortic aneurysm (AAA) is the full thickness dilation of the abdominal aorta. However, few effective medical therapies are available. Thus, elucidating the molecular mechanism of AAA pathogenesis and exploring the potential molecular target of medical therapies for AAA is of vital importance. Three expression datasets (GSE7084, GSE47472 and GSE57691) were downloaded from the Gene Expression Omnibus (GEO). These datasets were merged and then normalized using the \"sva\" R package. Differential expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) were conducted. We compared the co-expression patterns between AAA and normal conditions, and hub genes of each functional module were identified. DEGs were mapped to co-expression network under AAA condition and a DEG co-expression network was generated. Crucial genes were identified using molecular complex detection (MCODE) (a plugin in Cytoscape). In our study, 6 and 10 gene modules were detected for the AAA and normal conditions, respectively, while 143 DEGs were screened. Compared to the normal condition, genes associated with immune response, inflammation and muscle contraction were clustered in three gene modules respectively under the AAA condition; the hub genes of the three modules were MAP4K1, NFIB and HPK1, respectively. A DEG co-expression network with 102 nodes and 303 edges was identified, and a hub gene cluster with 10 genes from the DEG co-expression network was detected. YIPF6, RABGAP1, ANKRD6, GPD1L, PGRMC2, HIGD1A, GMDS, MGP, SLC25A4 and FAM129A were in the cluster. The expression levels of these 10 genes showed potential diagnostic value. Based on WGCNA, we detected 6 modules under the AAA condition and 10 modules in the normal condition. Hub genes of each module and hub gene clusters of the DEG co-expression network were identified. These genes may act as potential targets for medical therapy and diagnostic biomarkers. Further studies are needed to elucidate the detailed biological function of these genes in the pathogenesis of AAA.

Background: Retinoid-binding proteins (RBPs) regulate retinoid metabolism and signaling, but their roles across human cancers remain incompletely defined. Methods: We conducted a comprehensive analysis using bioinformatics tools and experimental validations, examining RBP expression profiles across cancer types based on data from The Cancer Genome Atlas (TCGA). We employed survival analysis using the Kaplan–Meier method and utilized single-cell RNA sequencing (scRNA-seq) to investigate the roles of RBP4 and RBP7 in the tumor microenvironment. Results: Our analysis revealed significant downregulation of RBPs in multiple cancers, with RBP4 and RBP7 showing notable expression variations linked to tumor stages and grades. Cox analysis identified RBP4 as a protective gene in kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), and mesothelioma (MESO), while RBP7 exhibited protective effects in breast cancer (BRCA) and uveal melanoma (UVM). Conclusions: This pan-cancer and single-cell integrative analysis highlights the complex roles of RBPs in cancer progression and their potential as prognostic biomarkers, particularly RBP4 and RBP7 in breast cancer. These findings warrant further investigation into the functional mechanisms of RBPs, which may provide valuable strategies for therapeutic interventions.

As ancient cities are spaces that represent the development of civilization, it is worth exploring and studying their characteristics and conceptions of land use. In this regard, the focus has turned to the issue of how to achieve the efficient mining of massive urban remote sensing data through human–computer collaboration. In this paper, a new intelligent method of analyzing urban land use characteristics and their cultural significance is proposed; it is feasible, effective, accurate, manageable, and portable. The method is based on a geographic information system (GIS) and a specific algorithm. The city plan was calibrated with the help of satellite remote sensing images and sites. By constructing the “urban element area acquisition and analysis model”, various operations for areas in the city plan were realized, including an area value calculation, land use structure calculation, area modulus analysis, area ratio analysis between areas, and determination of the cultural significance of numbers and ratios. Taking the Sui and Tang dynasties capital city of Chang’an as an example, we found the existence of a set of urban planning techniques through area modulus (standard area units) for the first time; it took the market area as the modulus A and the area of Daxing Palace as the expanded modulus 2A, made the area of important areas in the city an integer multiplied by the modulus value (for example, the overall scope of the city is 100A, the rectangular urban area is 90A, and the small city area is 10A), and made the key values and numerical ratios have a cultural significance (such as 4.5, 5.5, 10, 25, 30, 100, 12:10, 1.618:1, 9:5, 45:1, 2:1), reflecting the planning and design concept of the capital city, into which the ancient Chinese deliberately integrated “number, shape and meaning”. In addition, we carried out supplementary verification with the Roman city of Timgad and the Japanese city of Heijo-kyo, discovering that they also have design methods for area planning. We believe that land use planning can better meet the practical needs of urban resource distribution. Compared with urban form design, it might have chronological precedence. By setting the area modulus and the modulus value of each area, the grid-shaped city achieves the rational distribution of land and the establishment of order in an efficient way, and this thought and operation method greatly contributed to the advancement of ancient civilizations.

Multiple artificial intelligence systems have been created to facilitate accurate and prompt histopathological diagnosis of tumors using hematoxylin-eosin-stained slides. We aimed to investigate whether weakly supervised deep learning can aid in glioma diagnosis. We analyzed 472 whole slide images (WSIs) from 226 patients in West China Hospital (WCH) and 1604 WSIs from 880 patients in The Cancer Genome Atlas (TCGA). We utilized the OpenSlide library to load WSIs, segmented them into small patches using the DeepZoom module, and then normalized the color using the Reinhard method. A weakly supervised deep learning model was developed using ResNet-50 combined with an attention mechanism. We investigated the performance of the model by calculating area under the curve (AUC) in a ten-fold cross-validation setting. Heatmap visualizations showed the prediction mechanism of the model. The results were promising, with high AUC values for differentiating grades of astrocytomas, oligodendrogliomas, all gliomas, and glioma types in the TCGA dataset (0.9419, 0.8659, 0.9904, and 0.9298, respectively), and in the WCH cohort (0.9048, 0.7423, 0.9510, and 0.7098, respectively). The model demonstrated a strong ability to infer IDH status in the TCGA dataset (AUC = 0.9488). The weakly supervised deep learning model proved to be an effective and reliable tool for neuropathological diagnosis, making it an attractive auxiliary tool.

Colorectal cancer (CRC) ranks among the leading causes of cancer‐related dea ths worldwide, and the rising incidence and mortality of CRC underscores the urgent need for better understanding and management strategies. Icaritin (ICA) is the metabolites of icariin, a natural flavonoid glycoside compound derived from the stems and leaves of Epimedium. It has broad spectrum antitumor activity and inhibits the proliferation, migration, and invasion of CRC cells, and causes S phase cell cycle arrest. It exerts its antitumor effects against CRC through repressing autophagy to promote CRC cell apoptosis via interfering the HSP90‐TXNDC9 interactions. The safety and efficacy of ICA are also affirmed in a mouse xenograft model. Additionally, to test whether ICA exerts synergistic effects with low‐temperature photothermal therapy (LTPTT), a novel nanodrug delivery system, employing SiO2 nanocarriers, is designed aiming to load ICA with photothermal materials polydopamine (PDA), and folic acid (FA). This SiO2/Ica‐PDA‐FA multifunctional nanocomposite actively targets tumor tissues through the high affinity of FA for cancer cells. Once internalized, the acidic intracellular environment triggers the controlled release of ICA, inhibiting HSP90‐TXNDC9 interactions. By LTPTT and ICA drug therapy under near‐infrared illumination, a dual synergistic antitumor effect is achieved, holding promise for enhancing therapeutic outcomes in CRC treatment. Icaritin demonstrates broad antitumor effects by inhibiting colorectal cancer (CRC) cell proliferation, migration, invasion, and causing cell cycle arrest. It induces apoptosis by repressing autophagic flux through disrupting HSP90‐TXNDC9 interactions. Proven safe and effective in mouse models, icaritin is also integrated with low‐temperature photothermal therapy using SiO₂/PDA/FA nanocarriers for targeted, synergistic CRC treatment under near‐infrared light.

Numerous cancer types present the aberrant TANK-binding kinase 1 (TBK1) expression, which plays an important role in driving inflammation and innate immunity. However, the prognostic role of TBK1 and its relationship with immune cell infiltration in hepatocellular carcinoma (HCC) remain unclear. The expression and prognostic value of TBK1 was analyzed by Tumor Immune Estimation Resource (TIMER), Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and further confirmed in the present cohort of patients with HCC. The association between TBK1 and HCC immune infiltrates, and its potential mechanism were investigated analyses of the Tumor Immune Estimation Resource, tumor-immune system interactions database (TISIDB), CIBERSORT, STRING, and Metascape. The effect of TBK1 on immune infiltrates and the therapeutic value of targeting TBK1 were further investigated in a HCC mouse model by treatment with a TBK1 antagonist. The level of TBK1 expression in HCC was higher than that measured in normal tissues, and associated with poorer overall survival (GEPIA: hazard ratio [HR]=1.80, =0.038; Kaplan-Meier plotter: HR=1.87, <0.001; CPTAC: HR=2.23, =0.007; Our cohort: HR=2.92, =0.002). In addition, high TBK1 expression was found in HCC with advanced TNM stage and identified as an independent poor prognostic factor for overall survival among patients with HCC. In terms of immune infiltration, tumor tissues from HCC patients with high TBK1 expression had a low proportion of CD8 T cells, and TBK1 expression did not show prognostic value in HCC patients with enriched CD8+ T cells. Furthermore, TBK1 expression was positively correlated with the markers of T cell exhaustion and immunosuppressive cells in the HCC microenvironment. Mechanistically, the promotion of HCC immunosuppression by TBK1 was involved in the regulation of inflammatory cytokines. experiments revealed that treatment with a TBK1 antagonist delayed HCC growth by increasing the number of tumor-infiltrating CD8+ T cells. The up-regulated expression of TBK1 may be useful in predicting poor prognosis of patients with HCC. In addition, TBK1, which promotes the HCC immunosuppressive microenvironment, may be a potential immunotherapeutic target for patients with HCC.

Idiopathic normal pressure hydrocephalus (iNPH) affects mainly aged populations. The gradual shortening of telomere length (TL) is one of the hallmarks of aging. Whereas the genetic contribution of TL to the iNPH is incompletely understood. We aimed to investigate the causal relationship between TL and iNPH through the Mendelian randomization (MR) analysis. We respectively obtained 186 qualified single nucleotide polymorphisms (SNPs) of TL and 20 eligible SNPs of iNPH for MR analysis. The result of MR analysis showed that genetically predicted longer TL was significantly associated with a reduced odd of iNPH (odds ratio [OR] = 0.634 95% Confidence interval [CI] 0.447–0.899, p  = 0.011). The causal association remained consistent in multivariable MR (OR = 0.530 95% CI 0.327–0.860, p  = 0.010). However, there was no evidence that the iNPH was causally associated with the TL (OR = 1.000 95% CI 0.996–1.004, p  = 0.955). Our study reveals a potential genetic contribution of TL to the etiology of iNPH, that is a genetically predicted increased TL might be associated with a reduced risk of iNPH.

Background Several works suggest the importance of autophagy during esophageal carcinoma development. The aim of the study is to construct a scoring system according to the expression profiles of major autophagy-related genes (ARGs) among esophageal carcinoma cases. Methods The Cancer Genome Atlas was employed to obtain the esophageal carcinoma data. Thereafter, the online database Oncolnc ( http://www.oncolnc.org/ ) was employed to verify the accuracy of our results. According to our results, the included ARGs were related to overall survival (OS). Results We detected the expression patterns of ARG within esophageal carcinoma and normal esophageal tissues. In addition, we identified the autophagy related gene set, including 14 genes displaying remarkable significance in predicting the esophageal carcinoma prognosis. The cox regression results showed that, 7 ARGs (including TBK1, ATG5, HSP90AB1, VAMP7, DNAJB1, GABARAPL2, and MAP2K7) were screened to calculate the ARGs scores. Typically, patients with higher ARGs scores were associated with poorer OS. Moreover, the receiver operating characteristic (ROC) curve analysis suggested that, ARGs accurately distinguished the healthy people from esophageal carcinoma patients, with the area under curve (AUC) value of > 0.6. Conclusion A scoring system is constructed in this study based on the main ARGs, which accurately predicts the outcomes for esophageal carcinoma.