WD-1D-VGG19-FEA: An Efficient Wood Defect Elastic Modulus Predictive Model.

As a mature non-destructive testing technology, near-infrared (NIR) spectroscopy can effectively identify and distinguish the structural characteristics of wood. The Wood Defect One-Dimensional Visual Geometry Group 19-Finite Element Analysis (WD-1D-VGG19-FEA) algorithm is used in this study. 1D-VGG19 classifies the near-infrared spectroscopy data to determine the knot area, fiber deviation area, transition area, and net wood area of the solid wood board surface and generates a two-dimensional image of the board surface through inversion. Then, the nonlinear three-dimensional model of wood with defects was established by using the inverse image, and the finite element analysis was carried out to predict the elastic modulus of wood. In the experiment, 270 points were selected from each of the four regions of the wood, totaling 1080 sets of near-infrared data, and the 1D-VGG19 model was used for classification. The results showed that the identification accuracy of the knot area was 95.1%, the fiber deviation area was 92.7%, the transition area was 90.2%, the net wood area was 100%, and the average accuracy was 94.5%. The error range of the elastic modulus prediction of the three-dimensional model established by the VGG19 classification model in the finite element analysis is between 2% and 10%, the root mean square error (RMSE) is about 598. 2, and the coefficient of determination (R2) is 0. 91. This study shows that the combination of the VGG19 algorithm and finite element analysis can accurately describe the nonlinear defect morphology of wood, thus establishing a more accurate prediction model of wood mechanical properties to maximize the use of wood mechanical properties.

Conquering Limitations: Exploring the Factors that Drive Successful Agrobacterium-Mediated Genetic Transformation of Recalcitrant Plant Species.

Agrobacterium-mediated transformation is a preferred method for genetic engineering and genome editing of plants due to its numerous advantages, although not all species exhibit transformability. Genetic engineering and plant genome editing methods are technically challenging in recalcitrant crop plants. Factors affecting the poor rate of transformation in such species include host genotype, Agrobacterium genotype, type of explant, physiological condition of the explant, vector, selectable marker, inoculation method, chemical additives, antioxidative compounds, transformation-enhancing compounds, medium formulation, optimization of culture conditions, and pre-treatments. This review provides novel insights into the key factors involved in gene transfer facilitated by Agrobacterium and proposes potential solutions to overcome existing barriers to transformation in recalcitrant species, thereby contributing to improvement programs for these species. This review introduces the key factors that impact the effectiveness of a molecular breeding program using Agrobacterium-mediated transformation, specifically focusing on recalcitrant plant species.

Prostate cancer cancer-associated fibroblasts with stable markers post-androgen deprivation therapy associated with tumor progression and castration resistant prostate cancer.

The specificity and clinical relevance of cancer-associated fibroblasts (CAFs) in prostate cancer (PCa), as well as the effect of androgen deprivation therapy (ADT) on CAFs, remain to be fully elucidated. Using cell lineage diversity and weighted gene co-expression network analysis (WGCNA), we pinpointed a unique CAF signature exclusive to PCa. The specificity of this CAF signature was validated through single-cell RNA sequencing (scRNA-seq), cell line RNA sequencing, and immunohistochemistry. This signature associates CAFs with tumor progression, elevated Gleason scores, and the emergence of castration resistant prostate cancer (CRPC). Using scRNA-seq on collected samples, we demonstrated that the CAF-specific signature is not altered by ADT, maintaining its peak signal output. Identifying a PCa-specific CAF signature and observing signaling changes in CAFs after ADT lay essential groundwork for further PCa studies.

Prediction of Prognosis and Response to Androgen Deprivation Therapy in Intermediate to High-Risk Prostate Cancer Using 18F-FDG PET/CT Radiomics.

RATIONALE AND OBJECTIVES: This study aims to predict intermediate to high-risk prostate cancer (PCa) prognosis based on 18-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) radiomics. Additionally, subgroup analysis will be performed on the androgen deprivation therapy (ADT) group and the metastatic PCa group. MATERIALS AND METHODS: In the retrospective analysis of 104 intermediate to high-risk PCa patients who underwent 18F-FDG PET/CT prior to treatment. The data set was divided into a training set (n = 72) and a testing set (n = 32). Two different PET/CT models were constructed using multivariate logistic regression with cross-validation: radiomics model A and an alternative ensemble learning-based model B. The superior model was then selected to develop a radiomics nomogram. Separate models were also developed for the ADT and metastatic PCa subgroups. RESULTS: Model A, which integrates eight radiomics features showed excellent performance with an area under curve (AUC) of 0.844 in the training set and 0.804 in the testing set. The radiomics nomogram incorporating the radiomics score (radscore) from model A and the tumor-to-liver ratio (TLR) showed good prognostic accuracy in the testing set with an AUC of 0.827. In the subgroup analyses for endocrine therapy and metastatic cancer, the PET/CT radiomics model showed AUCs of 0.845 and 0.807 respectively, suggesting its potential effectiveness. CONCLUSION: The study establishes the utility of the 18F-FDG PET/CT radiomics nomogram in predicting the prognosis of intermediate to high-risk PCa patients, indicating its potential for clinical application.

Predictive markers for infections after extracorporeal shockwave lithotripsy in patients with kidney stone based on a large prospective cohort.

OBJECTIVE: Infections in patients with kidney stones after extracorporeal shockwave lithotripsy (SWL) is a common clinical issue. However, the associated factors are unclear. Therefore, we aim to develop and validate a predictive model for infections after SWL in patients with kidney stone. METHODS: Between June 2020 and May 2022, consecutive kidney stone patients were enrolled. Of them, 553 patients comprised the development cohort. One hundred sixty-five patients comprised the validation cohort. The data were prospectively collected. The stepwise selection was applied using the likelihood ratio test with Akaike's information criterion as the stopping rule; A predictive model was constructed through multivariate logistic regression. The performance was evaluated regarding discrimination, calibration, and clinical usefulness. RESULTS: Predictors of infections after SWL in treating kidney stones included older age (OR = 1.026, p = 0.041), female (OR = 2.066, p = 0.039), higher BMI (OR = 1.072, p = 0.039), lower stone density (OR = 0.995, p < 0.001), and higher grade of hydronephrosis (OR = 5.148, p < 0.001). For the validation cohort, the model showed good discrimination with an area under the receiver operating characteristic curve of 0.839 (95% CI 0.736, 0.941) and good calibration. Decision curve analysis demonstrated that the model was also clinically useful. CONCLUSION: This study indicated that age, gender, BMI, stone density, and hydronephrosis grade were significant predictors of infections after SWL in treating kidney stones. It provided evidence in optimizing prevention and perioperative treatment strategies to reduce the risk of infection after SWL.

The mediating role of renewable energy, sectoral output and economic growth on greenhouse gas emissions: African regional perspective.

Global greenhouse gas emissions are increasing when they should be progressively reducing, given worldwide concerted emissions mitigation efforts and protocols. To effectively tackle emissions to foster a sustainable climate, the situation's complexity needs a sector- and region-specific approach, not a one-stop analysis. We must first understand where the emissions originate-which sectors contribute the most to them. This study employs a panel multiregional framework with advanced econometric techniques accounting for cross-sectional dependence and heterogeneous slope coefficients to analyse GHG emissions (CO2 and CH4), sectoral output, economic growth and renewable energy dynamics across African regions from 2010 to 2019. The empirical findings are as follows: First, regional impacts of the economic sectors vary substantially, reflecting technological and socioeconomic differences leading to heterogeneous environmental patterns in the short and long term. Second, the estimated EKC turning points are uniformly lower, indicating slower environmental impact growth with sectoral development in African regions. Third, trade and urbanization are critical drivers of emissions in most regions and economic sectors, with a more pervasive impact on CO2 emissions than CH4 emissions. Finally, sectoral output imposes differential indirect CO2 and CH4 emissions effects via renewable energy, with East African manufacturing exhibiting the most significant emissions-reduction impact. Disaggregated, regional, and sectoral-specific strategies are recommended for designing green development pathways policies.

Diagnostic value of methylated branched chain amino acid transaminase 1/IKAROS family zinc finger 1 for colorectal cancer.

BACKGROUND: The diagnostic value of combined methylated branched chain amino acid transaminase 1 (BCAT1)/IKAROS family zinc finger 1 (IKZF1) in plasma for colorectal cancer (CRC) has been explored since 2015. Recently, several related studies have published their results and showed its diagnostic efficacy. AIM: To analyze the diagnostic value of methylated BCAT1/IKZF1 in plasma for screening and postoperative follow-up of CRC. METHODS: The candidate studies were identified by searching the PubMed, Embase, Cochrane Library, CNKI, and Wanfang databases from May 31, 2003 to June 1, 2023. Sensitivity, specificity, and diagnostic accuracy were calculated by merging ratios or means. RESULTS: Twelve eligible studies were included in the analysis, involving 6561 participants. The sensitivity of methylated BCAT1/IKZF1 in plasma for CRC diagnosis was 60% [95% confidence interval (CI) 53-67] and specificity was 92% (95%CI: 90-94). The positive and negative likelihood ratios were 8.0 (95%CI: 5.8-11.0) and 0.43 (95%CI: 0.36-0.52), respectively. Diagnostic odds ratio was 19 (95%CI: 11-30) and area under the curve was 0.88 (95%CI: 0.85-0.91). The sensitivity and specificity for CRC screening were 64% (95%CI: 59-69) and 92% (95%CI: 91-93), respectively. The sensitivity and specificity for recurrence detection during follow-up were 54% (95%CI: 42-67) and 93% (95%CI: 88-96), respectively. CONCLUSION: The detection of methylated BCAT1/IKZF1 in plasma, as a non-invasive detection method of circulating tumor DNA, has potential CRC diagnosis, but the clinical application prospect needs to be further explored.

A New Nomogram for Predicting 30-Day In-Hospital Mortality Rate of Acute Cholangitis Patients in the Intensive Care Unit.

Purpose: Acute cholangitis (AC) is a widespread acute inflammatory disease and the main cause of septic shock, which has a high death rate in hospitals. At present, the prediction models for short-term mortality of AC patients are still not ideal. We aimed at developing a new model that could forecast the short-term mortality rate of AC patients. Methods: Data were extracted from the Medical Information Mart for Intensive Care IV version 2.0 (MIMIC-IV v2.0). There were a total of 506 cases of AC patients that were included. Patients were given a 7 : 3 split between the training set and the validation set after being randomly assigned to one of the groups. Multivariate logistic regression was used to create an AC patient predictive nomogram for 30-day mortality. The overall efficacy of the model is evaluated using the area under the receiver operating characteristic curve (AUC), the calibration curve, the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), and a decision curve analysis (DCA). Results: Out of 506 patients, 14.0% (71 patients) died. The training cohort had 354 patients, and the validation cohort had 152 patients. GCS, SPO2, albumin, AST/ALT, glucose, potassium, PTT, and peripheral vascular disease were the independent risk factors according to the multivariate analysis results. The newly established nomogram had better prediction performance than other common scoring systems (such as SOFA, OASIS, and SAPS II). For two cohorts, the calibration curve demonstrated coherence between the nomogram and the ideal observation (P > 0.05). The clinical utility of the nomogram in both sets was revealed by decision curve analysis. Conclusion: The novel prognostic model was effective in forecasting the 30-day mortality rate for acute cholangitis patients.

Blood-based liquid biopsy: insights into early detection, prediction, and treatment monitoring of bladder cancer.

Bladder cancer (BC) is a clinical challenge worldwide with late clinical presentation, poor prognosis, and low survival rates. Traditional cystoscopy and tissue biopsy are routine methods for the diagnosis, prognosis, and monitoring of BC. However, due to the heterogeneity and limitations of tumors, such as aggressiveness, high cost, and limited applicability of longitudinal surveillance, the identification of tumor markers has attracted significant attention in BC. Over the past decade, liquid biopsies (e.g., blood) have proven to be highly efficient methods for the discovery of BC biomarkers. This noninvasive sampling method is used to analyze unique tumor components released into the peripheral circulation and allows serial sampling and longitudinal monitoring of tumor progression. Several liquid biopsy biomarkers are being extensively studied and have shown promising results in clinical applications of BC, including early detection, detection of microscopic residual disease, prediction of recurrence, and response to therapy. Therefore, in this review, we aim to provide an update on various novel blood-based liquid biopsy markers and review the advantages and current limitations of liquid biopsy in BC therapy. The role of blood-based circulating tumor cells, circulating tumor DNA, cell-free RNA, exosomes, metabolomics, and proteomics in diagnosis, prognosis, and treatment monitoring, and their applicability to the personalized management of BC, are highlighted.

Development of a Novel Nomogram Incorporating Red Blood Cell Distribution Width-Albumin Ratio for the Prediction of 30-day Mortality in Acute Pancreatitis Patients.

Purpose: The available nomograms used to predict acute pancreatitis (AP) are not comprehensive. We sought to investigate the effect of red blood cell distribution width (RDW)-albumin ratio (RA) on prognosis of patients with AP and develop a new nomogram to identify AP patients at high risk for mortality. Methods: We used data from the Medical Information Mart for Intensive Care IV version 2.0 (MIMIC-IV v2.0). A total of 487 patients with acute pancreatitis were included. Patients enrolled in the study were randomly assigned to the training set and validation set at a 7 : 3 ratio. According to the 30-day mortality rate, the data were divided into a survival group and a death group. Multivariate logistic regression was used to establish a prognostic nomogram for predicting the 30-day mortality in AP patients. The area under the receiver operating characteristic curve (AUC), calibration curve, the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), and a decision curve analysis (DCA) are used to verify the overall performance of the model. Results: Among 487 patients, 54 patients died (11.1%). 338 patients were assigned to the training cohort and 149 were assigned to the validation cohort. The multivariate analysis results showed that RA, age, heart rate, temperature, AST/ALT, BUN, hemoglobin, potassium, and bilirubin were independent risk factors. The prediction performance of the newly established nomogram was better than those of other common scoring systems (including SOFA, OASIS, and APSIII). The nomogram suggests that RA (OR = 1.706, 95% CI: 1.367-2.185) is the most significant laboratory test indicator influencing prognosis. Conclusion: The new nomogram incorporating RA performed well in predicting AP short-term mortality. A prospective study with a larger sample is needed to validate our findings.

Immune status for monitoring and treatment of bladder cancer.

The high recurrence rate of non-muscle invasive bladder cancer (BC) and poor prognosis of advanced BC are therapeutic challenges that need to be solved. Bacillus Calmette-Guerin (BCG) perfusion was the pioneer immunotherapy for early BC, and the discovery of immune checkpoint inhibitors has created a new chapter in the treatment of advanced BC. The benefit of immunotherapy is highly anticipated, but its effectiveness still needs to be improved. In this review, we collated and analysed the currently available information and explored the mechaisms by which the internal immune imbalance of BC leads to tumour progression. The relationship between immunity and progression and the prognosis of BC has been explored through tests using body fluids such as blood and urine. These analytical tests have attempted to identify specific immuyne cells and cytokines to predict treatment outcomes and recurrence. The diversity and proportion of immune and matrix cells in BC determine the heterogeneity and immune status of tumours. The role and classification of immune cells have also been redefined, e.g., CD4 cells having recognised cytotoxicity in BC. Type 2 immunity, including that mediated by M2 macrophages, Th2 cells, and interleukin (IL)-13, plays an important role in the recurrence and progression of BC. Pathological fibrosis, activated by type 2 immunity and cancer cells, enhances the rate of cancer progression and irreversibility. Elucidating the immune status of BC and clarifying the mechanisms of action of different cells in the tumour microenvironment is the research direction to be explored in the future.

Pan-cancer Landscape of the RUNX Protein Family Reveals their Potential as Carcinogenic Biomarkers and the Mechanisms Underlying their Action.

Background: The RUNX family of transcription factors plays an important regulatory role in tumor development. Although the importance of RUNX in certain cancer types is well known, the pan-cancer landscape remains unclear. Materials and Methods: Data from The Cancer Genome Atlas (TCGA) provides a pan-cancer overview of the RUNX genes. Hence, herein, we performed a pan-cancer analysis of abnormal RUNX expression and deciphered the potential regulatory mechanism. Specifically, we used TCGA multi-omics data combined with multiple online tools to analyze transcripts, genetic alterations, DNA methylation, clinical prognoses, miRNA networks, and potential target genes. Results: RUNX genes are consistently overexpressed in esophageal, gastric, pancreatic, and pan-renal cancers. The total protein expression of RUNX1 in lung adenocarcinoma, kidney renal clear cell carcinoma (KIRC), and uterine corpus endometrial carcinoma (UCEC) is consistent with the mRNA expression results. Moreover, increased phosphorylation on the T14 and T18 residues of RUNX1 may represent potential pathogenic factors. The RUNX genes are significantly associated with survival in pan-renal cancer, brain lower-grade glioma, and uveal melanoma. Meanwhile, various mutations and posttranscriptional changes, including the RUNX1 D96 mutation in invasive breast carcinoma, the co-occurrence of RUNX gene mutations in UCEC, and methylation changes in the RUNX2 promoter in KIRC, may be associated with cancer development. Finally, analysis of epigenetic regulator co-expression, miRNA networks, and target genes revealed the carcinogenicity, abnormal expression, and direct regulation of RUNX genes. Conclusions: We successfully analyzed the pan-cancer abnormal expression and prognostic value of RUNX genes, thereby providing potential biomarkers for various cancers. Further, mutations revealed via genetic alteration analysis may serve as a basis for personalized patient therapies.

Combining 18F-FDG PET and Gd-EOB-DTPA-enhanced MRI for staging liver fibrosis.

AIM: To evaluate the diagnostic performance of combining 18F-2-fluoro-2-D-deoxyglucose-positron emission tomography (18F-FDG PET) and gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) for liver fibrosis staging. MATERIALS AND METHODS: Male New Zealand white rabbits (n = 48) were treated with carbon tetrachloride (CCl4) to induce liver fibrosis, while control group rabbits (n = 8) received normal saline. The liver tissues of rabbits were histopathologically examined (classified according to the METAVIR classification system) for liver fibrosis staging and real-time polymerase chain reaction (RT-PCR) was used to ensure diagnostic accuracy. Integrated PET/MRI was performed. The mean standardised uptake value (SUVmean) and relative enhancement (RE) were evaluated for different liver fibrosis stages using a Mann-Whitney U test. The performance of PET/MRI was evaluated by using the receiver operating characteristic curve (ROC) and the area under the ROC curve (AUC). KEY FINDINGS: In total, 10, 16, and 8 rabbits classified into no fibrosis (F0), mild fibrosis (F1-2), and severe fibrosis (F3-4) categories, respectively. There were significant differences in SUVmean and RE between F0 and F3-4 and between F1-2 and F3-4 (p < 0.01), but no significance between F0 and F1-2 (p > 0.5). Combined SUVmean and RE performed well in staging liver fibrosis, with AUC of 0.8 for F0 or greater, 0.744 for F0 or F1-2, 0.945 for F1-2 or F3-4, and 0.962 for F3-4. SIGNIFICANCE: Combining SUVmean and RE provides high accuracy for grading liver fibrosis, especially in the differentiation between F1-2 and F3-4. 18F-FDG and Gd-EOB-DTPA-enhanced PET/MRI could be a non-invasive diagnostic method to guide the selection of clinical treatment options.

Cancer-associated fibroblasts and the related Runt-related transcription factor 2 (RUNX2) promote bladder cancer progression.

Bladder urothelial cancer (BLCA) has a high incidence worldwide. Cancer-associated fibroblasts (CAFs) in the tumor microenvironment are gradually recognized to play an important role in the occurrence and progression of cancer. However, the research on BLCA CAFs is still in its infancy, and the CAFs related genes are still unclear. We used the identified BLCA-specific CAFs gene signature in our previous work to calculate the CAFs infiltration score of the sample. Furthermore, we used data from multiple public databases to prove that CAFs high infiltration is associated with tumor progression and poor prognosis. In order to select the powerful genes in BLCA that are related to CAFs infiltration and affect prognosis, we chose transcription factors as the research object, and finally defined RUNX2 as the candidate gene for functional verification. In the immunohistochemical images, tissues with higher RUNX2 expression also had deeper staining of CAFs markers. We used public databases and collected specimens to prove that RUNX2 is overexpressed at the mRNA and protein levels in BLCA tissues. Through functional enrichment analysis, RUNX2 is mainly related to epithelialmesenchymal transition and extracellular matrix. Finally, we knocked down RUNX2 in vitro and observed a significant decrease in the metastasis and proliferation ability. In conclusion, high infiltration of CAFs is associated with tumor progression and poor prognosis in BLCA. RUNX2 is a transcription factor related to CAFs, which is overexpressed in bladder cancer and affects the prognosis. RUNX2 is a potential marker relating CAFs and therapy target in BLCA.

Weighted gene co-expression network analysis can sort cancer-associated fibroblast-specific markers promoting bladder cancer progression.

The role of cancer-associated fibroblasts (CAFs) has been thoroughly investigated in tumour microenvironments but not in bladder urothelial carcinoma (BLCA). The cell fraction of CAFs gradually increased with BLCA progression. Weighted gene co-expression network analysis (WGCNA) revealed a specific gene expression module of CAFs that are relevant to cancer progression and survival status. Fifteen key genes of the module were consistent with a fibroblast signature in single-cell RNA sequencing, functionally related to the extracellular matrix, and significant in survival analysis and tumour staging. A comparison of the luminal-infiltrated versus luminal-papillary subtypes and fibroblast versus urothelial carcinoma cell lines and immunohistochemical data analysis demonstrated that the key genes were specifically expressed in CAFs. Moreover, these genes are highly correlated with previously reported CAF markers. In summary, CAFs play a major role in the progression of BLCA, and the 15 key genes act as BLCA-specific CAF markers and can predict CAF changes. WGCNA can, therefore, be used to sort CAF-specific gene set in cancer tissues.

Agrobacterium-delivered VirE2 interacts with host nucleoporin CG1 to facilitate the nuclear import of VirE2-coated T complex.

Agrobacterium tumefaciens is the causal agent of crown gall disease. The bacterium is capable of transferring a segment of single-stranded DNA (ssDNA) into recipient cells during the transformation process, and it has been widely used as a genetic modification tool for plants and nonplant organisms. Transferred DNA (T-DNA) has been proposed to be escorted by two virulence proteins, VirD2 and VirE2, as a nucleoprotein complex (T-complex) that targets the host nucleus. However, it is not clear how such a proposed large DNA-protein complex is delivered through the host nuclear pore in a natural setting. Here, we studied the natural nuclear import of the Agrobacterium-delivered ssDNA-binding protein VirE2 inside plant cells by using a split-GFP approach with a newly constructed T-DNA-free strain. Our results demonstrate that VirE2 is targeted into the host nucleus in a VirD2- and T-DNA-dependent manner. In contrast with VirD2 that binds to plant importin α for nuclear import, VirE2 directly interacts with the host nuclear pore complex component nucleoporin CG1 to facilitate its nuclear uptake and the transformation process. Our data suggest a cooperative nuclear import model in which T-DNA is guided to the host nuclear pore by VirD2 and passes through the pore with the assistance of interactions between VirE2 and host nucleoporin CG1. We hypothesize that this large linear nucleoprotein complex (T-complex) is targeted to the nucleus by a "head" guide from the VirD2-importin interaction and into the nucleus by a lateral assistance from the VirE2-nucleoporin interaction.

Agrobacterium VirE3 Uses Its Two Tandem Domains at the C-Terminus to Retain Its Companion VirE2 on the Cytoplasmic Side of the Host Plasma Membrane.

Agrobacterium tumefaciens is the causal agent of crown gall disease in nature; in the laboratory the bacterium is widely used for plant genetic modification. The bacterium delivers a single-stranded transferred DNA (T-DNA) and a group of crucial virulence proteins into host cells. A putative T-complex is formed inside host cells that is composed of T-DNA and virulence proteins VirD2 and VirE2, which protect the foreign DNA from degradation and guide its way into the host nucleus. However, little is known about how the T-complex is assembled inside host cells. We combined the split-GFP and split-sfCherry labeling systems to study the interaction of Agrobacterium-delivered VirE2 and VirE3 in host cells. Our results indicated that VirE2 co-localized with VirE3 on the cytoplasmic side of the host cellular membrane upon the delivery. We identified and characterized two tandem domains at the VirE3 C-terminus that interacted with VirE2 in vitro. Deletion of these two domains abolished the VirE2 accumulation on the host plasma membrane and affected the transformation. Furthermore, the two VirE2-interacting domains of VirE3 exhibited different affinities with VirE2. Collectively, this study demonstrates that the anchorage protein VirE3 uses the two tandem VirE2-interacting domains to facilitate VirE2 protection for T-DNA at the cytoplasmic side of the host cell entrance.

Nickel-Mediated Trifluoromethylation of Phenol Derivatives by Aryl C-O Bond Activation.

The increasing pharmaceutical importance of trifluoromethylarenes has stimulated the development of more efficient trifluoromethylation reactions. Tremendous efforts have focused on copper- and palladium-mediated/catalyzed trifluoromethylation of aryl halides. In contrast, no general method exists for the conversion of widely available inert electrophiles, such as phenol derivatives, into the corresponding trifluoromethylated arenes. Reported herein is a practical nickel-mediated trifluoromethylation of phenol derivatives with readily available trimethyl(trifluoromethyl)silane (TMSCF3 ). The strategy relies on PMe3 -promoted oxidative addition and transmetalation, and CCl3 CN-induced reductive elimination. The broad utility of this transformation has been demonstrated through the direct incorporation of trifluoromethyl into aromatic and heteroaromatic systems, including biorelevant compounds.

Identification of a Gene Signature for Renal Cell Carcinoma-Associated Fibroblasts Mediating Cancer Progression and Affecting Prognosis.

Background: Cancer-associated fibroblasts (CAFs) are mainly involved in cancer progression and treatment failure. However, the specific signature of CAFs and their related clinicopathological parameters in renal cell carcinoma (RCC) remain unclear. Here, methods to recognize gene signatures were employed to roughly assess the infiltration of CAFs in RCC, based on the data from The Cancer Genome Atlas (TCGA). Weighted Gene Coexpression Network Analysis (WGCNA) was used to cluster transcriptomes and correlate with CAFs to identify the gene signature. Single-cell and cell line sequencing data were used to verify the expression specificity of the gene signature in CAFs. The gene signature was used to evaluate the infiltration of CAFs in each sample, and the clinical significance of each key gene in the gene signature and CAFs was analyzed. We observed that the CAF infiltration was higher in kidney cancer and advanced tumor stage and grade than in normal tissues. The seven key genes of the CAF gene signature identified using WGCNA showed high expression of CAF-related characteristics in the cell clustering landscape and fibroblast cell lines; these genes were found to be associated with extracellular matrix function, collagen synthesis, cell surface interaction, and adhesion. The high CAF infiltration and the key genes were verified from the TCGA and Gene Expression Omnibus data related to the advanced grade, advanced stage, and poor prognosis of RCC. In summary, our findings indicate that the clinically significant gene signature may serve as a potential biomarker of CAFs in RCC, and the infiltration of CAFs is associated with the pathological grade, stage, and prognosis of RCC.