Iron-catalyzed C-7 selective NH2 amination of indoles.

7-Aminoindoles are important synthetic intermediates to a broad range of bioactive molecules. Transition metal-catalyzed directed C-H amination is among the most straightforward route for their synthesis, whereas methods that could directly incorporate an NH2 group in a highly selective manner remains elusive. Moreover, there is still high demand for the development of earth-abundant metal catalysis for such attractive reactivity. We present here the first C-7 selective NH2 amination of indoles through a directed homolytic aromatic substitution (HAS) with iron-aminyl radical. The reaction exhibits broad substrate scope, tolerates variety of functional groups, and is readily scalable with catalyst loading down to 0.1 mol% and turnover number (TON) up to 4500.

Machine learning-based model for predicting outcomes in cerebral hemorrhage patients with leukemia.

BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) in leukemia patients progresses rapidly with high mortality. Limited data are available on imaging studies in this population. The study aims to develop prediction models for 7-day and short-term mortality risk based on the non-contrast computed tomography (NCCT) image features. METHODS: The NCCT image features of ICH in 135 leukemia patients between 2007-2023 were retrospectively extracted using manual assessment and radiomics methods. After multiple imputation of missing laboratory data, univariate logistic regression and least absolute shrinkage and selection operator (LASSO) were used for feature selection. Random forest models were built with comprehensive evaluation and ranking of feature importance. RESULT: 135 and 129 patients were included in the studies for 7-day and short-term prognostic models, respectively. The median age of all enrolled patients was 35 years, and there were 86 male patients (63.7 %). Clinical models (validation: AUC [area under the curve] = 0.78, AUPRC [area under the precision-recall curve] = 0.73; AUC = 0.84, AUPRC = 0.86), radiomics models (validation: AUC = 0.82, AUPRC = 0.78; AUC = 0.75, AUPRC = 0.77), and the combined models (validation: AUC = 0.84, AUPRC = 0.83; AUC = 0.87, AUPRC = 0.89) predicted 7-day and short-term mortality with good predictive efficacy. Clinical decision curve analysis showed that the combined models predicted 7-day and 30-day risk of death would be more beneficial than other models. Shape features contributed significantly more than semantic features in both radiomics models and combined models (93.3 %, 52.1 %, as well as 85.2 %,37.4 %, respectively) for 7-day and 30-day mortality. CONCLUSIONS: Combined models constructed based on NCCT perform well in predicting the risk of 7-day and short-term mortality in ICH patients with leukemia. Shape features extracted by radiomics are important markers for modeling the prognosis.

Characterize direct protein interactions with enrichable, cleavable and latent bioreactive unnatural amino acids.

Latent bioreactive unnatural amino acids (Uaas) have been widely used in the development of covalent drugs and identification of protein interactors, such as proteins, DNA, RNA and carbohydrates. However, it is challenging to perform high-throughput identification of Uaa cross-linking products due to the complexities of protein samples and the data analysis processes. Enrichable Uaas can effectively reduce the complexities of protein samples and simplify data analysis, but few cross-linked peptides were identified from mammalian cell samples with these Uaas. Here we develop an enrichable and multiple amino acids reactive Uaa, eFSY, and demonstrate that eFSY is MS cleavable when eFSY-Lys and eFSY-His are the cross-linking products. An identification software, AixUaa is developed to decipher eFSY mass cleavable data. We systematically identify direct interactomes of Thioredoxin 1 (Trx1) and Selenoprotein M (SELM) with eFSY and AixUaa.

Gossypol acetic acid regulates leukemia stem cells by degrading LRPPRC via inhibiting IL-6/JAK1/STAT3 signaling or resulting mitochondrial dysfunction.

BACKGROUND: Leukemia stem cells (LSCs) are found to be one of the main factors contributing to poor therapeutic effects in acute myeloid leukemia (AML), as they are protected by the bone marrow microenvironment (BMM) against conventional therapies. Gossypol acetic acid (GAA), which is extracted from the seeds of cotton plants, exerts anti-tumor roles in several types of cancer and has been reported to induce apoptosis of LSCs by inhibiting Bcl2. AIM: To investigate the exact roles of GAA in regulating LSCs under different microenvironments and the exact mechanism. METHODS: In this study, LSCs were magnetically sorted from AML cell lines and the CD34+CD38- population was obtained. The expression of leucine-rich pentatricopeptide repeat-containing protein (LRPPRC) and forkhead box M1 (FOXM1) was evaluated in LSCs, and the effects of GAA on malignancies and mitochondrial function were measured. RESULTS: LRPPRC was found to be upregulated, and GAA inhibited cell proliferation by degrading LRPPRC. GAA induced LRPPRC degradation and inhibited the activation of interleukin 6 (IL-6)/janus kinase (JAK) 1/signal transducer and activator of transcription (STAT) 3 signaling, enhancing chemosensitivity in LSCs against conventional chemotherapies, including L-Asparaginase, Dexamethasone, and cytarabine. GAA was also found to downregulate FOXM1 indirectly by regulating LRPPRC. Furthermore, GAA induced reactive oxygen species accumulation, disturbed mitochondrial homeostasis, and caused mitochondrial dysfunction. By inhibiting IL-6/JAK1/STAT3 signaling via degrading LRPPRC, GAA resulted in the elimination of LSCs. Meanwhile, GAA induced oxidative stress and subsequent cell damage by causing mitochondrial damage. CONCLUSION: Taken together, the results indicate that GAA might overcome the BMM protective effect and be considered as a novel and effective combination therapy for AML.

Single-cell and spatial transcriptome sequencing uncover a platinum-resistant cluster overexpressed TACSTD2 in high-grade serous ovarian cancer.

Purpose: Platinum-based chemotherapy is effective but limited by resistance in high-grade serous ovarian cancer (HGSOC). Single-cell RNA sequencing (scRNA-seq) can reveal tumour cell heterogeneity and subclonal differentiation. We aimed to analyze resistance mechanisms and potential targets in HGSOC using scRNA-seq. Methods: We performed 10× genomics scRNA-seq sequencing on tumour tissues from 3 platinum-sensitive and 3 platinum-resistant HGSOC patients. We analyzed cell subcluster communication networks and spatial distribution using cellchat. We performed RNA-seq analysis on TACSTD2, a representative resistance gene in the E0 subcluster, to explore its molecular mechanism. Results: Epithelial cells, characterized by distinct chemotherapy resistance traits and highest gene copy number variations, revealed a specific cisplatin-resistant cluster (E0) associated with poor prognosis. E0 exhibited malignant features related to resistance, fostering growth through communication with fibroblasts and endothelial cells. Spatially, E0 promoted fibroblasts to protect tumour cells and impede immune cells infiltration. Furthermore, TACSTD2 was identified as a representative gene of the E0 subcluster, elucidating its role in platinum resistance through the Rap1/PI3K/AKT pathway. Conclusions: Our study reveals a platinum-resistant epithelial cell subcluster E0 and its association with TACSTD2 in HGSOC, uncovers new insights and evidence for the platinum resistance mechanism, and provides new ideas and targets for the development of therapeutic strategies against TACSTD2+ epithelial cancer cells.

Metformin and statins reduce hepatocellular carcinoma risk in chronic hepatitis C patients with failed antiviral therapy.

BACKGROUND/AIMS: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. METHODS: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan's cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray's cumulative incidence and Cox subdistribution hazards models to analyze HCC development. RESULTS: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. CONCLUSION: Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Triterpene esters of cirsium setosum and their anti-inflammatory activity.

Two new triterpene fatty acid esters, 3ß-palmityloxy-12,27-cyclofriedoolean-14-en-11α-ol (1) and 3ß-palmityloxy-19α-hydroxyursane (2), together with 3ß-hydroxy-11-oxo-olean-12-enyl palmitate (3) were isolated from the potent anti-inflammatory active fraction of the petroleum ether-soluble part of Cirsium setosum ethanol extract. Compound 1 was found to be a rare 12,27-cyclopropane triterpenoid. Their structures were determined through spectral data analysis combined with literature reports. Furthermore, in vitro experiment, compounds 1-3 exhibited significant inhibitory effects on nitric oxide production in lipopolysaccharide-activated mouse RAW264.7 macrophages.

A new era of antibody discovery: an in-depth review of AI-driven approaches.

Given their high affinity and specificity for a range of macromolecules, antibodies are widely used in the treatment of autoimmune diseases, cancers, inflammatory diseases, and Alzheimer's disease (AD). Traditional experimental methods are time-consuming, expensive, and labor-intensive. Recent advances in artificial intelligence (AI) technologies provide complementary methods that can reduce the time and costs required for antibody design by minimizing failures and increasing the success rate of experimental tests. In this review, we scrutinize the plethora of AI-driven methodologies that have been deployed over the past 4 years for modeling antibody structures, predicting antibody-antigen interactions, optimizing antibody affinity, and generating novel antibody candidates. We also briefly address the challenges faced in integrating AI-based models with traditional antibody discovery pipelines and highlight the potential future directions in this burgeoning field.

Analysis of m6A-related lncRNAs for prognostic and immunotherapeutic response in hepatocellular carcinoma.

Background: RNA methylation modifications are important post-translational modifications that are regulated in an epigenetic manner. Recently, N6-methyladenosine (m6A) RNA modifications have emerged as potential epigenetic markers in tumor biology. Methods: Gene expression and clinicopathological data of LIHC were obtained from the cancer genome atlas (TCGA) database. The relationship between long non-coding RNAs (lncRNAs) and m6A-related genes was determined by gene expression analysis using Perl and R software. Co-expression network of m6A-lncRNA was constructed, and the relevant lncRNAs associated with prognosis were identified using univariate Cox regression analysis. These lncRNAs were then divided into two clusters (cluster 1 and cluster 2) to determine the differences in survival, pathoclinical parameters, and immune cell infiltration between the different lncRNA subtypes. The least absolute shrinkage and selection operator (LASSO) was carried out for regression analysis and prognostic model. The HCC patients were randomly divided into a train group and a test group. According to the median risk score of the model, HCC patients were divided into high-risk and low-risk groups. We built models using the train group and confirmed them through the test group. The m6A-lncRNAs derived from the models were analyzed for the tumor mutational burden (TMB), immune evasion and immune function using R software. AL355574.1 was identified as an important m6A-associated lncRNA and selected for further investigation. Finally, in vitro experiments were conducted to confirm the effect of AL355574.1 on the biological function of HCC and the possible biological mechanisms. Huh7 and HepG2 cells were transfected with AL355574.1 siRNA and cell proliferation ability was measured by CCK-8, EdU and colony formation assays. Wound healing and transwell assays were used to determine the cell migration capacity. The expression levels of MMP-2, MMP-9, E-cadherin, N-cadherin and Akt/mTOR phosphorylation were all determined by Western blotting. Results: The lncRNAs with significant prognostic value were classified into two subtypes by a consistent clustering analysis. We found that the clinical features, immune cell infiltration and tumor microenvironment (TME) were significantly different between the lncRNA subtypes. Our analysis revealed significant correlations between these different lncRNA subtypes and immune infiltrating and stromal cells. We created the final risk profile using LASSO regression, which notably included three lncRNAs (AL355574.1, AL158166.1, TMCC1-AS1). A prognostic signature consisting of the three lncRNAs was constructed, and the model showed excellent prognostic predictive ability. The overall survival (OS) of the low-risk cohort was significantly higher than that of the high-risk cohort in both the train and test group. Both risk score [hazard ratio (HR)=1.062; P<0.001] and stage (HR=1.647; P< 0.001) were considered independent indicators of HCC prognosis by univariate and multivariate Cox regression analysis. In Huh7 and HepG2 cells, AL355574.1 knockdown inhibited cell proliferation and migration, suppressed the protein expression levels of MMP-2, MMP-9, N-cadherin and Akt/mTOR phosphorylation, but promoted the protein expression levels of E-cadherin. Conclusions: This study established a predictive model for the OS of HCC patients, and these OS-related m6A-lncRNAs, especially AL355574.1 may play a potential role in the progression of HCC. In vitro experiments also showed that AL355574.1 could enhance the expression of MMPs and EMT through the Akt/mTOR signaling pathway, thereby affected the proliferation and migration of HCC. This provides a new perspective on the anticancer molecular mechanism of AL355574.1 in HCC.

Prediction of transformation in the histopathological growth pattern of colorectal liver metastases after chemotherapy using CT-based radiomics.

Chemotherapy alters the prognostic biomarker histopathological growth pattern (HGP) phenotype in colorectal liver metastases (CRLMs) patients. We aimed to develop a CT-based radiomics model to predict the transformation of the HGP phenotype after chemotherapy. This study included 181 patients with 298 CRLMs who underwent preoperative contrast-enhanced CT followed by partial hepatectomy between January 2007 and July 2022 at two institutions. HGPs were categorized as pure desmoplastic HGP (pdHGP) or non-pdHGP. The samples were allocated to training, internal validation, and external validation cohorts comprising 153, 65, and 29 CRLMs, respectively. Radiomics analysis was performed on pre-enhanced, arterial phase, portal venous phase (PVP), and fused images. The model was used to predict prechemotherapy HGPs in 112 CRLMs, and HGP transformation was analysed by comparing these findings with postchemotherapy HGPs determined pathologically. The prevalence of pdHGP was 19.8% (23/116) and 45.8% (70/153) in chemonaïve and postchemotherapy patients, respectively (P < 0.001). The PVP radiomics signature showed good performance in distinguishing pdHGP from non-pdHGPs (AUCs of 0.906, 0.877, and 0.805 in the training, internal validation, and external validation cohorts, respectively). The prevalence of prechemotherapy pdHGP predicted by the radiomics model was 33.0% (37/112), and the prevalence of postchemotherapy pdHGP according to the pathological analysis was 47.3% (53/112; P = 0.029). The transformation of HGP was bidirectional, with 15.2% (17/112) of CRLMs transforming from prechemotherapy pdHGP to postchemotherapy non-pdHGP and 30.4% (34/112) transforming from prechemotherapy non-pdHGP to postchemotherapy pdHGP (P = 0.005). CT-based radiomics method can be used to effectively predict the HGP transformation in chemotherapy-treated CRLM patients, thereby providing a basis for treatment decisions.

A Systematic Review and Meta-Analysis of MRI Radiomics for Predicting Microvascular Invasion in Patients with Hepatocellular Carcinoma.

BACKGROUND: The prediction power of MRI radiomics for microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) remains uncertain. OBJECTIVE: To investigate the prediction performance of MRI radiomics for MVI in HCC. METHODS: Original studies focusing on preoperative prediction performance of MRI radiomics for MVI in HCC, were systematically searched from databases of PubMed, Embase, Web of Science and Cochrane Library. Radiomics quality score (RQS) and risk of bias of involved studies were evaluated. Meta-analysis was carried out to demonstrate the value of MRI radiomics for MVI prediction in HCC. Influencing factors of the prediction performance of MRI radiomics were identified by subgroup analyses. RESULTS: 13 studies classified as type 2a or above according to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement were eligible for this systematic review and meta-analysis. The studies achieved an average RQS of 14 (ranging from 11 to 17), accounting for 38.9% of the total points. MRI radiomics achieved a pooled sensitivity of 0.82 (95%CI: 0.78 - 0.86), specificity of 0.79 (95%CI: 0.76 - 0.83) and area under the summary receiver operator characteristic curve (AUC) of 0.88 (95%CI: 0.84 - 0.91) to predict MVI in HCC. Radiomics models combined with clinical features achieved superior performances compared to models without the combination (AUC: 0.90 vs 0.85, P < 0.05). CONCLUSION: MRI radiomics has the potential for preoperative prediction of MVI in HCC. Further studies with high methodological quality should be designed to improve the reliability and reproducibility of the radiomics models for clinical application. The systematic review and meta-analysis was registered prospectively in the International Prospective Register of Systematic Reviews (No. CRD42022333822).

Systematic analysis of the role of LDHs subtype in pan-cancer demonstrates the importance of LDHD in the prognosis of hepatocellular carcinoma patients.

BACKGROUND: Lactate dehydrogenase (LDHs) is an enzyme involved in anaerobic glycolysis, including LDHA, LDHB, LDHC and LDHD. Given the regulatory role in the biological progression of certain tumors, we analyzed the role of LDHs in pan-cancers. METHODS: Cox regression, Kaplan-Meier curves, Receiver Operating Characteristic (ROC) curves, and correlation of clinical indicators in tumor patients were used to assess the prognostic significance of LDHs in pan-cancer. The TCGA, HPA, TIMER, UALCAN, TISIDB, and Cellminer databases were used to investigate the correlation between the expression of LDHs and immune subtypes, immune checkpoint genes, methylation levels, tumor mutational load, microsatellite instability, tumor-infiltrating immune cells and drug sensitivity. The cBioPortal database was also used to identify genomic abnormalities of LDHs in pan-cancer. A comprehensive assessment of the biological functions of LDHs was performed using GSEA. In vitro, HepG2 and Huh7 cells were transfected with LDHD siRNA and GFP-LDHD, the proliferation capacity of cells was examined using CCK-8, EdU, and colony formation assays; the migration and invasion of cells was detected by wound healing and transwell assays; western blotting was used to detect the levels of MMP-2, MMP-9, E-cadherin, N-cadherin and Akt phosphorylation. RESULTS: LDHs were differentially expressed in a variety of human tumor tissues. LDHs subtypes can act as pro-oncogenes or anti-oncogenes in different types of cancer and have an impact on the prognosis of patients with tumors by influencing their clinicopathological characteristics. LDHs were differentially expressed in tumor immune subtypes and molecular subtypes. In addition, LDHs expression correlated with immune checkpoint genes, tumor mutational load, and microsatellite instability. LDHD was identified to play an important role in the prognosis of HCC patients, according to a comprehensive analysis of LDHs in pan-cancer. In HepG2 and Huh7 cells, knockdown of LDHD promoted cell proliferation, migration, and invasion, promoted the protein expression levels of MMP-2, MMP-9, N-cadherin, and Akt phosphorylation, but inhibited the protein expression level of E-cadherin. In addition, LDHD overexpression showed the opposite changes. CONCLUSION: LDHs subtypes can be used as potential prognostic markers for certain cancers. Prognostic and immunotherapeutic analysis indicated that LDHD plays an important role in the prognosis of HCC patients. In vitro experiments revealed that LDHD can affect HCC proliferation, migration, and invasion by regulating MMPs expression and EMT via Akt signaling pathway, which provides a new perspective on the anti-cancer molecular mechanism of LDHD in HCC.

Prediction of macrotrabecular-massive hepatocellular carcinoma by using MR-based models and their prognostic implications.

PURPOSE: To evaluate the efficacy of MRI-based radiomics and clinical models in predicting MTM-HCC. Additionally, to investigate the ability of the radiomics model designed for MTM-HCC identification in predicting disease-free survival (DFS) in patients with HCC. METHODS: A total of 336 patients who underwent oncological resection for HCC between June 2007 and March 2021 were included. 127 patients in Cohort1 were used for MTM-HCC identification, and 209 patients in Cohort2 for prognostic analyses. Radiomics analysis was performed using volumes of interest of HCC delineated on pre-operative MRI images. Radiomics and clinical models were developed using Random Forest algorithm in Cohort1 and a radiomics probability (RP) of MTM-HCC was obtained from the radiomics model. Based on the RP, patients in Cohort2 were divided into a RAD-MTM-HCC (RAD-M) group and a RAD-non-MTM-HCC (RAD-nM) group. Univariate and multivariate Cox regression analyses were employed to identify the independent predictors for DFS of patients in Cohort2. Kaplan-Meier curves were used to compare the DFS between different groups pf patients based on the predictors. RESULTS: The radiomics model for identifying MTM-HCC showed AUCs of 0.916 (95% CI: 0.858-0.960) and 0.833 (95% CI: 0.675-0.935), and the clinical model showed AUCs of 0.760 (95% CI: 0.669-0.836) and 0.704 (95% CI: 0.532-0.843) in the respective training and validation sets. Furthermore, the radiomics biomarker RP, portal or hepatic vein tumor thrombus, irregular rim-like arterial phase hyperenhancement (IRE) and AFP were independent predictors of DFS in patients with HCC. The DFS of RAD-nM group was significantly higher than that of the RAD-M group (p < .001). CONCLUSION: MR-based clinical and radiomic models have the potential to accurately diagnose MTM-HCC. Moreover, the radiomics signature designed to identify MTM-HCC also can be used to predict prognosis in patients with HCC, realizing the diagnostic and prognostic aims at the same time.

Therapeutic effect of hydrogen and its mechanisms in kidney disease treatment.

Hydrogen is a simple, colorless, and biologically active small molecule gas that can react with reactive oxygen species. Recent research suggests that hydrogen possesses several biological effects, including antioxidant, anti-inflammatory, and anti-apoptotic effects, while exhibiting an extremely high level of safety. Hydrogen application has shown promise in treating a range of acute and chronic diseases, both benign and malignant. Importantly, an increasing number of clinical studies on hydrogen have demonstrated its efficacy and safety in treating various diseases. This review highlights the beneficial effects of hydrogen in kidney diseases, summarizes potential mechanisms by which hydrogen may act in these diseases, and proposes several promising avenues for future research.

Ultrasound-Controlled Delivery of Growth Factor-Loaded Cerasomes Combined with Polycaprolactone Scaffolds Seeded with Bone Marrow Mesenchymal Stem Cells for Biomimetic Tendon-to-Bone Interface Engineering.

Rotator cuff tear (RCT) is a prevalent shoulder injury that poses challenges for achieving continuous and functional regeneration of the tendon-to-bone interface (TBI). In this study, we controlled the delivery of growth factors (GFs) from liposomal nanohybrid cerasomes by ultrasound and implanted three-dimensional printed polycaprolactone (PCL) scaffolds modified with polydopamine loaded with bone marrow mesenchymal stem cells (BMSCs) to repair tears of the infraspinatus tendon in a lapine model. Direct suturing (control, CTL) was used as a control. The PCL/BMSC/cerasome (PBC) devices are sutured with the enthesis of the infraspinatus tendon. The cerasomes and PCL scaffolds are highly stable with excellent biocompatibility. The roles of GFs BMP2, TGFß1, and FGF2 in tissue-specific differentiation are validated. Compared with the CTL group, the PBC group had significantly greater proteoglycan deposition (P = 0.0218), collagen volume fraction (P = 0.0078), and proportions of collagen I (P = 0.0085) and collagen III (P = 0.0048). Biotin-labeled in situ hybridization revealed a high rate of survival for transplanted BMSCs. Collagen type co-staining at the TBI is consistent with multiple collagen regeneration. Our studies demonstrate the validity of biomimetic scaffolds of TBI with BMSC-seeded PCL scaffolds and GF-loaded cerasomes to enhance the treatment outcomes for RCTs.

A comparative study on ctDNA and tumor DNA mutations in lung cancer and benign cases with a high number of CTCs and CTECs.

BACKGROUND: Liquid biopsy provides a non-invasive approach that enables detecting circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) using blood specimens and theoretically benefits early finding primary tumor or monitoring treatment response as well as tumor recurrence. Despite many studies on these novel biomarkers, their clinical relevance remains controversial. This study aims to investigate the correlation between ctDNA, CTCs, and circulating tumor-derived endothelial cells (CTECs)  while also evaluating whether mutation profiling in ctDNA is consistent with that in tumor tissue from lung cancer patients. These findings will help the evaluation and utilization of these approaches in clinical practice. METHODS: 104 participants (49 with lung cancer and 31 with benign lesions) underwent CTCs and CTECs detection using integrating subtraction enrichment and immunostaining-fluorescence in situ hybridization (SE-iFISH) strategy. The circulating cell-free DNA (cfDNA) concentration was measured and the mutational profiles of ctDNA were examined by Roche AVENIO ctDNA Expanded Kit (targeted total of 77 genes) by next generation sequencing (NGS) in 28 patients (20 with lung cancer and 8 with benign lesions) with highest numbers of CTCs and CTECs. Mutation validation in matched tumor tissue DNA was then performed in 9 patients with ctDNA mutations using a customized xGen pan-solid tumor kit (targeted total of 474 genes) by NGS. RESULTS: The sensitivity and specificity of total number of CTCs and CTECs for the diagnosis of NSCLC were 67.3% and 77.6% [AUC (95%CI): 0.815 (0.722-0.907)], 83.9% and 77.4% [AUC (95%CI): 0.739 (0.618-0.860)]. The concentration of cfDNA in plasma was statistically correlated with the size of the primary tumor (r = 0.430, P = 0.022) and CYFRA 21-1 (r = 0.411, P = 0.041), but not with the numbers of CTCs and CTECs. In this study, mutations were found to be poorly consistent between ctDNA and tumor DNA (tDNA) in patients, even when numerous CTCs and CTECs were present. CONCLUSION: Detection of CTCs and CTECs could be the potential adjunct tool for the early finding of lung cancer. The cfDNA levels are associated with the tumor burden, rather than the CTCs or CTECs counts. Moreover, the poorly consistent mutations between ctDNA and tDNA require further exploration.

Exploring the Common Gene Signatures Between Myocardial Infarction-Reperfusion Injury and the Gut Microbiome Using Bioinformatics.

BACKGROUND: This bioinformatics report attempts to explore the cross-talk genes, transcription factors (TFs), and pathways related to myocardial ischemia-reperfusion injury (MIRI) as well as the gut microbiome. METHOD: The datasets GSE61592 (three MIRI and three sham samples) and GSE160516 (twelve MIRI and four sham samples) were selected in the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) identification (p < 0.05 and |log FC (fold change)| ≥1) together with functional annotation (p < 0.05) was implemented. The Cytoscape platform established the protein-protein interaction (PPI) network. Genes associated with gut microbiome disorder were extracted based on the DisGeNET database, and those associated with MIRI were overlapped. The Recursive Feature Elimination (RFE) algorithm was adopted for selecting features, and cross-talk genes were predicted by the Support Vector Machine (SVM) models. A network encompassing cross-talk genes along with the TFs was thereby established. RESULT: The MIRI datasets comprised 138 shared DEGs, with 101 showing up-regulation whereas 37 showing down-regulation. Notably, the PPI interwork for MIRI contained 2517 edges along with 1818 nodes. By using RFE and SVM methods, six feature genes with the highest prediction were identified: B2m, VCAM-1, PDIA4, Ptgds, Mlxipl, and ACADS. Among these genes, B2m and PDIA4 were most highly expressed in MIRI and the gut microbiome disorder. CONCLUSION: B2m and PDIA4 were identified to be significantly correlated with candidate cross-talk genes of MIRI with gut microbiome disorder, implying a similarity between MIRI and Gut microbiome disorder (GMD). These genes can serve as an experimental research basis for future studies.

Meniscal fibrocartilage regeneration inspired by meniscal maturational and regenerative process.

Meniscus is a complex and crucial fibrocartilaginous tissue within the knee joint. Meniscal regeneration remains to be a scientific and translational challenge. We clarified that mesenchymal stem cells (MSCs) participated in meniscal maturation and regeneration using MSC-tracing transgenic mice model. Here, inspired by meniscal natural maturational and regenerative process, we developed an effective and translational strategy to facilitate meniscal regeneration by three-dimensionally printing biomimetic meniscal scaffold combining autologous synovium transplant, which contained abundant intrinsic MSCs. We verified that this facilitated anisotropic meniscus-like tissue regeneration and protected cartilage from degeneration in large animal model. Mechanistically, the biomechanics and matrix stiffness up-regulated Piezo1 expression, facilitating concerted activation of calcineurin and NFATc1, further activated YAP-pSmad2/3-SOX9 axis, and consequently facilitated fibrochondrogenesis of MSCs during meniscal regeneration. In addition, Piezo1 induced by biomechanics and matrix stiffness up-regulated collagen cross-link enzyme expression, which catalyzed collagen cross-link and thereby enhanced mechanical properties of regenerated tissue.

Harnessing the power of exogenous factors to enhance plant resistance to aluminum toxicity; a critical review.

Aluminum (Al) is the most prevalent element in the earth crust and is toxic to plants in acidic soils. However, plants can address Al toxicity through external exclusion (which prevents Al from entering roots) and internal detoxification (which counterbalances the toxic-Al absorbed by roots). Nowadays, certain categories of exogenously added regulatory factors (EARF), such as nutritional elements, organic acids, amino acids, phytohormones, or biochar, etc. play a critical role in reducing the bioavailability/toxicity of Al in plants. Numerous studies suggest that regulating factors against Al toxicity mediate the expression of Al-responsive genes and transcription factors, thereby regulating the secretion of organic acids, alkalizing rhizosphere pH, modulating cell wall (CW) modifications, improving antioxidant defense systems, and promoting the compartmentalization of non-toxic Al within intracellular. This review primarily discusses recent and older published papers to demonstrate the basic concepts of Al phytotoxicity. Furthermore, we provide a comprehensive explanation of the crucial roles of EARF-induced responses against Al toxicity in plants. This information may serve as a foundation for improving plant resistance to Al and enhancing the growth of susceptible species in acidic soils. And this review holds significant theoretical significance for EARF to improve the quality of acidic soils cultivated land, increase crop yield and quality, and ensure food security.

Sirt6 enhances macrophage lipophagy and improves lipid metabolism disorder by regulating the Wnt1/ß-catenin pathway in atherosclerosis.

Lipid metabolism disorders are considerably involved in the pathology of atherosclerosis; nevertheless, the fundamental mechanism is still largely unclear. This research sought to examine the function of lipophagy in lipid metabolism disorder-induced atherosclerosis and its fundamental mechanisms. Previously, Sirt6 has been reported to stimulate plaque stability by promoting macrophage autophagy. However, its role in macrophage lipophagy and its relationship with Wnt1 remains to be established. In this study, ApoE-/-: Sirt6-/- and ApoE-/-: Sirt6Tg mice were used and lipid droplets were analysed via transmission electron microscopy and Bodipy 493/503 staining in vitro. Atherosclerotic plaques in ApoE-/-: Sirt6-/- mice showed greater necrotic cores and lower stability score. Reconstitution of Sirt6 in atherosclerotic mice improved lipid metabolism disorder and prevented the progression of atherosclerosis. Furthermore, macrophages with Ac-LDL intervention showed more lipid droplets and increased expression of adipophilin and PLIN2. Reconstitution of Sirt6 recruited using SNF2H suppressed Wnt1 expression and improved lipid metabolism disorder by promoting lipophagy. In addition, downregulation of Sirt6 expression in Ac-LDL-treated macrophages inhibited lipid droplet degradation and stimulated foam cell formation. Innovative discoveries in the research revealed that atherosclerosis is caused by lipid metabolism disorders due to downregulated Sirt6 expression. Thus, modulating Sirt6's function in lipid metabolism might be a useful therapeutic approach for treating atherosclerosis.