Organic-Inorganic Hybrid Perovskite Ferroelectric Nanosheets Synthesized by a Room-Temperature Antisolvent Method.

Over the past years, the application potential of ferroelectric nanomaterials with unique physical properties for modern electronics is highlighted to a large extent. However, it is relatively challenging to fabricate inorganic ferroelectric nanomaterials, which is a process depending on a vacuum atmosphere at high temperatures. As significant complements to inorganic ferroelectric nanomaterials, the nanomaterials of molecular ferroelectrics are rarely reported. Here a low-cost room-temperature antisolvent method is used to synthesize free-standing 2D organic-inorganic hybrid perovskite (OIHP) ferroelectric nanosheets (NSs), that is, (CHA)2PbBr4 NSs (CHA = cyclohexylammonium), with an average lateral size of 357.59 nm and a thickness ranging from 10 to 70 nm. This method shows high repeatability and produces NSs with excellent crystallinity. Moreover, ferroelectric domains in single NSs can be clearly visualized and manipulated using piezoresponse force microscopy (PFM). The domain switching and PFM-switching spectroscopy indicate the robust in-plane ferroelectricity of the NSs. This work not only introduces a feasible, low-cost, and scalable method for preparing molecular ferroelectric NSs but also promotes the research on molecular ferroelectric nanomaterials.

Volume-Confined Fabrication of Large-Scale Single-Crystalline Molecular Ferroelectric Thin Films and Their Applications in 2D Materials.

With outstanding advantages of chemical synthesis, structural diversity, and mechanical flexibility, molecular ferroelectrics have attracted increasing attention, demonstrating themselves as promising candidates for next-generation wearable electronics and flexible devices in the film form. However, it remains a challenge to grow high-quality thin films of molecular ferroelectrics. To address the above issue, a volume-confined method is utilized to achieve ultrasmooth single-crystal molecular ferroelectric thin films at the sub-centimeter scale, with the thickness controlled in the range of 100-1000 nm. More importantly, the preparation method is applicable to most molecular ferroelectrics and has no dependency on substrates, showing excellent reproducibility and universality. To demonstrate the application potential, two-dimensional (2D) transitional metal dichalcogenide semiconductor/molecular ferroelectric heterostructures are prepared and investigated by optical spectroscopic method, proving the possibility of integrating molecular ferroelectrics with 2D layered materials. These results may unlock the potential for preparing and developing high-performance devices based on molecular ferroelectric thin films.

Revealing the Polarizations of Molecular Ferroelectrics via SHG Polarimetry at the Nanoscale.

Multifarious molecular ferroelectrics with multipolar axial characteristics have emerged in recent years, enriching the scenarios for energy harvesting, sensing, and information processing. The increased polar axes have enhanced the urgency of distinguishing different polarization states in material design, mechanism exploration, etc. However, conventional methods hardly meet the requirements of in situ, fast, microscale, contactless, and nondestructive features due to their inherent limitations. Herein, SHG polarimetry is introduced to probe the multioriented polarizations on a nanosized multiaxial molecular ferroelectric, i.e., TMCM-CdCl3 nanoplates, as an example. Combined with the analysis of the second-order susceptibility tensor, SHG polarimetry could serve as an effective method to detect the polarization orders and domain distributions of molecular ferroelectrics. Profiting from the full-optical feature, SHG polarimetry can even be performed on samples covered by transparent mediums, 2D materials, or thin metal electrodes. Our research might spark further fundamental studies and expand the application boundaries of next-generation ferroelectric materials.

Rational Design of Molecular Ferroelectrics with Negatively Charged Domain Walls.

Ferroelectric domains and domain walls are unique characteristics of ferroelectric materials. Among them, charged domain walls (CDWs) are a special kind of peculiar microstructure that highly improve conductivity, piezoelectricity, and photovoltaic efficiency. Thus, CDWs are believed to be the key to ferroelectrics' future application in fields of energy, sensing, information storage, and so forth. Studies on CDWs are one of the most attractive directions in conventional inorganic ferroelectric ceramics. However, in newly emerged molecular ferroelectrics, which have advantages such as lightweight, easy preparation, simple film fabrication, mechanical flexibility, and biocompatibility, CDWs are rarely observed due to the lack of free charges. In inorganic ferroelectrics, doping is a traditional method to induce free charges, but for molecular ferroelectrics fabricated by solution processes, doping usually causes phase separation or phase transition, which destabilizes or removes ferroelectricity. To realize stable CDWs in molecular systems, we designed and synthesized an n-type molecular ferroelectric, 1-adamantanammonium hydroiodate. In this compound, negative charges are induced by defects in the I- vacancy, and CDWs can be achieved. Nanometer-scale CDWs that are stable at temperatures as high as 373 K can be "written" precisely by an electrically biased metal tip. More importantly, this is the first time that the charge diffusion of CDWs at variable temperatures has been investigated in molecular ferroelectrics. This work provides a new design strategy for n-type molecular ferroelectrics and may shed light on their future applications in flexible electronics, microsensors, and so forth.

CD86 Molecule Might Be a Novel Immune-Related Prognostic Biomarker for Patients With Bladder Cancer by Bioinformatics and Experimental Assays.

As one of the most common malignancies in the urinary system, bladder cancer (BC) occupies a high mortality and recurrence rate. BC carries an ominous prognosis. Thus, we aimed to identify a novel immune-related prognostic biomarker and therapeutic target for immunotherapy in the present study. We first constructed a co-expression network based on immune-related genes (IRGs). Two key modules showed high association with the clinical feature interested us most were further identified. Forty-five IRGs were screened out and regarded as hub genes in the co-expression network. We further constructed a protein-protein interaction (PPI) network, and five independent methods were used for hub gene identification. Three hub genes were identified in the present study. CD86 molecule (CD86) was screened out by performing overall survival (OS) analysis. Subsequent analyses by using some bioinformatics and experimental assays confirmed that CD86 was an immune-related prognostic biomarker, which might be a novel target for immunotherapy in BC. A small molecule drug named suloctidil was also identified, which showed potential for BC treatment.

Construction and Validation of an Autophagy-Related Prognostic Signature and a Nomogram for Bladder Cancer.

OBJECTIVE: Bladder cancer (BC) is one of the top ten cancers endangering human health but we still lack accurate tools for BC patients' risk stratification. This study aimed to develop an autophagy-related signature that could predict the prognosis of BC. In order to provide clinical doctors with a visual tool that could precisely predict the survival probability of BC patients, we also attempted to establish a nomogram based on the risk signature. METHODS: We screened out autophagy-related genes (ARGs) combining weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) in BC. Based on the screened ARGs, we performed survival analysis and Cox regression analysis to identify potential prognostic biomarkers. A risk signature based on the prognostic ARGs by multivariate Cox regression analysis was established, which was validated by using seven datasets. To provide clinical doctors with a useful tool for survival possibility prediction, a nomogram assessed by the ARG-based signature and clinicopathological features was constructed, verified using four independent datasets. RESULTS: Three prognostic biomarkers including BOC (P = 0.008, HR = 1.104), FGF7(P = 0.030, HR = 1.066), and MAP1A (P = 0.001, HR = 1.173) were identified and validated. An autophagy-related risk signature was established and validated. This signature could act as an independent prognostic feature in patients with BC (P = 0.047, HR = 1.419). We then constructed two nomograms with and without ARG-based signature and subsequent analysis indicated that the nomogram with ARG signature showed high accuracy for overall survival probability prediction of patients with BC (C-index = 0.732, AUC = 0.816). These results proved that the ARG signature improved the clinical net benefit of the standard model based on clinicopathological features (age, pathologic stage). CONCLUSIONS: Three ARGs were identified as prognosis biomarkers in BC. An ARG-based signature was established for the first time, showing strong potential for prognosis prediction in BC. This signature was proven to improve the clinical net benefit of the standard model. A nomogram was established using this signature, which could lead to more effective prognosis prediction for BC patients.

GNRH1 and LTB4R might be novel immune-related prognostic biomarkers in clear cell renal cell carcinoma (ccRCC).

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) occupied most of renal cell carcinoma (RCC), which associated with poor prognosis. The purpose of this study is to screen novel and prognostic biomarkers for patients with ccRCC. METHODS AND RESULTS: Firstly, Gene Expression Omnibus database was used to collect microarray data for weighted gene co-expression network construction. Gene modules related to prognosis which interest us most were picked out. 90 hub genes were further chosen in the key modules, two of which including gonadotropin releasing hormone 1 (GNRH1) and leukotriene B4 receptor (LTB4R) were screened and validated as immune-related prognostic biomarkers. Based on several public databases and ccRCC tissues collected by ourselves, we performed survival analysis, spearman correlation analysis, receiver operating characteristic (ROC) analysis, quantitative real-time PCR (qRT-PCR), western blotting, immunofluorescence (IF) and immunohistochemistry (IHC) staining for the validation of immune-related prognostic biomarkers. We further explored the relationship between immune-related prognostic biomarker expressions and immunocytes. Finally, gene set enrichment analysis (GSEA) demonstrated that the two immune-related prognostic biomarkers were significantly correlated with cell cycle. CONCLUSIONS: Generally speaking, the present study has identified two novel prognostic biomarkers for patients with ccRCC, which showed strong correlation with prognosis of patients with ccRCC, could further be used as potential prognostic biomarkers in ccRCC.

Complement C7 (C7), a Potential Tumor Suppressor, Is an Immune-Related Prognostic Biomarker in Prostate Cancer (PC).

Objectives: Prostate cancer (PC) is the second most frequent tumor in men, which has a high recurrence rate and poor prognosis. Therefore, this study aimed to identify novel prognostic biomarkers and therapeutic targets for immunotherapy and small molecule drugs for PC treatment. Materials and Methods: The Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm was applied to calculate immune scores and stromal scores of TCGA-PRAD data. Differentially expressed genes (DEGs) were identified using R package "limma." GO, KEGG, and DO analyses were performed to analyze DEGs. Overall survival and disease-free survival analyses were conducted for hub gene identification. To validate the hub gene at the mRNA and protein expression levels, genetic alterations were measured, and CCLE and Cox regression analyses were performed. Connectivity map (CMap) analysis and GSEA were performed for drug exploration and function analysis, respectively. Results: Immune scores ranged from -1795.98 to 2339.39, and stomal scores ranged from -1877.60 to 1659.96. In total, 45 tumor microenvironment (TME)-related DEGs were identified, of which Complement C7 (C7) was selected and validated as a hub gene. CMap analysis identified six small molecule drugs as potential agents for PC treatment. Further analysis demonstrated that C7 expression was significantly correlated with clinical T, pathological N, and immune infiltration level. Conclusions: In conclusion, of the 45 TME-related DEGs, C7 was shown to correlate with PC prognosis in patients, indicating it as a novel prognostic biomarker and immunotherapy target in PC. Additionally, six small molecule drugs showed strong therapeutic potential for PC treatment.

Identification of transforming growth factor beta induced (TGFBI) as an immune-related prognostic factor in clear cell renal cell carcinoma (ccRCC).

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among kidney cancer, which has poor prognosis. The aim of this study was to screen out novel prognostic biomarkers and therapeutic targets for immunotherapy, and some novel molecule drugs for ccRCC treatment. Immune scores ranged from -1109.36 to 2920.81 and stromal scores ranged from -1530.11 to 1955.39 were firstly calculated by applying ESTIMATE algorithm. Then 17 DEGs associated with immune score and stromal score were further identified. 6 candidate hub genes were screened out by performing overall survival (OS) and disease-free survival analyses based on TCGA-KIRC data, one of which including TGFBI was further regarded as hub gene associated with prognosis by calculating the R2 (R2 = 0.011, P = 0.018) and AUC (AUC = 0.874). The prognostic value of TGFBI was validated by performing OS, CSS, and PFS analyses based on GSE29609 and E-MTAB-3267. CMap analysis suggested that 3 molecule drugs might be novel choice for ccRCC treatment. Further analysis demonstrated that CNVs of TGFBI was associated with OS of patients with ccRCC. TGFBI expression was also correlated with histologic grade, pathologic stage, and immune infiltration level, significantly. TGFBI was the most relevant gene with OS among the candidate hub genes, which might be novel DNA methylation biomarkers for ccRCC. In conclusion, our findings indicated that TGFBI was correlated with prognosis of patients with ccRCC, which might be novel prognostic biomarkers, and targets for immunotherapy in ccRCC. Three small molecule drugs were also identified, which showed strong potential for ccRCC treatment.

Systematic analysis of gene expression and molecular interactions in cardiac and non-cardiac gastric carcinomas.

BACKGROUND/AIMS: : This study aims to comparing the gene expression profiles and molecular interactions among gastric cardiac adenocarcinomas (GCA), gastric noncardiac adenocarcinomas (GNCA) and their adjacent normal tissues. METHODOLOGY: Gene expression profile of GSE29272 was downloaded from Gene expression omnibus. Differentially expressed genes (DEGs) were identified at the cut-off of p-value ≤ 0.01. Gene ontology (GO) enrichment analysis was further performed for the DEGs, and then the binding sites of the transcriptional factors and the specific protein-protein interactions were analyzed. RESULTS: Total 1024 DEGs were screened, including 741 up-regulated genes and 283 down-regulated genes. VSNL1 (visinin-like protein-1) is expressed relatively higher in the GNCA and could be its molecular biomarker, as KRT14 (cytokeratin 14) in the GCA. GO analysis showed that the analogous cancer-relevant factors network appears in these two cancer subgroups. The DEGs in the GCA tend to be bound by SPIB and ZNF354C. FN1 lies in the center of the protein-protein interaction networks of the two cancer subgroups. CONCLUSIONS: We found out the RNA expression level of the two gastric cancers varied greatly from the normal tissues while gene expression profile of them were very similar, however, the different biomarker and transcriptional factors indicate the differences of two mechanisms.

Effects of insulin resistance on left ventricular hypertrophy in patients with CKD stage 1-3.

BACKGROUND: Left ventricular hypertrophy (LVH) existed in patients with early stage chronic kidney disease (CKD). But whether insulin resistance (IR) exists in these patients and has some definite relationship with LVH, is unknown. METHODS: Homeostatic model method was used for detecting homeostasis model assessment of insulin resistance (HOMA-IR) in 336 subjects including 286 patients with early stage CKD and 50 control subjects, and HOMA-IR and other clinical data in all subjects were obtained based on standard methods. Then, the relationship between LVH, IR and other relevant clinical data were analyzed. RESULTS: IR and LVH existed in early stage CKD patients. The prevalence of LVH in patients with IR was significantly higher than those without, and patients with LVH had a higher prevalence of IR than those without. The patients with IR or LVH had lower levels of e-GFR, hemoglobin (Hb) and total cholesterol, while higher levels of blood urea nitrogen (BUN), serum creatinine (Scr), intact parathyroid hormone (iPTH), CRP and systolic blood pressure (SBP). HOMA-IR had positive correlations with left ventricular mass index (LVMI). HOMA-IR and LVMI had positive correlations with BUN, Scr, iPTH and CRP, but negative with e-GFR and Hb. Multiple linear stepwise regression analysis showed that e-GFR, FINS, Hb and SBP enter the regression equation. Binary unconditional logistic regression analysis indicated that the main risk factors for LVH were CKD and IR (P < 0.05, respectively). CONCLUSION: Both IR and LVH existed in early stage CKD patients and were more severe with the development of CKD. IR had a significant correlation with LVH. Furthermore, decline of e-GFR, hypertension and anemia were also associated with both IR and LVH and may have some effects in the mechanism of IR on the development of LVH.