Fusobacterium nucleatum infection modulates the transcriptome and epigenome of HCT116 colorectal cancer cells in an oxygen-dependent manner.

Fusobacterium nucleatum, a gram-negative oral bacterium, has been consistently validated as a strong contributor to the progression of several types of cancer, including colorectal (CRC) and pancreatic cancer. While previous in vitro studies have shown that intracellular F. nucleatum enhances malignant phenotypes such as cell migration, the dependence of this regulation on features of the tumor microenvironment (TME) such as oxygen levels are wholly uncharacterized. Here we examine the influence of hypoxia in facilitating F. nucleatum invasion and its effects on host responses focusing on changes in the global epigenome and transcriptome. Using a multiomic approach, we analyze epigenomic alterations of H3K27ac and global transcriptomic alterations sustained within a hypoxia and normoxia conditioned CRC cell line HCT116 at 24 h following initial infection with F. nucleatum. Our findings reveal that intracellular F. nucleatum activates signaling pathways and biological processes in host cells similar to those induced upon hypoxia conditioning in the absence of infection. Furthermore, we show that a hypoxic TME favors F. nucleatum invasion and persistence and therefore infection under hypoxia may amplify malignant transformation by exacerbating the effects induced by hypoxia alone. These results motivate future studies to investigate host-microbe interactions in tumor tissue relevant conditions that more accurately define parameters for targeted cancer therapies.

Recyclable Polymer Composites with a Wrinkled Core-Shell Structure for Highly Efficient EMI Shielding and Low Reflection.

Green electromagnetic interference (EMI) shielding materials not only require high shielding effectiveness (SE) and low reflection but also need to be recyclable after damage; however, it is challenging to strike a balance in practice. Here, a polyacrylamide (PAM) composite composed of numerous chemically cross-linked PAM@carbon nanotube (cPAM@CNT) core-shell particles featuring rich wrinkled microstructures was prepared using an adsorption-drying-shrinking strategy. The wrinkled microstructures enable the incident electromagnetic waves (EMWs) to undergo attenuation within the composites, achieving an average EMI SE of 67.5 dB in the X band. Due to the hygroscopicity of hydrophobically associated PAM (hPAM, an adhesive for cPAM@CNTs core-shell particles), the average EMI SE of the composites further increased to 83.2 dB after exposure to 91% relative humidity for 24 h, with only a 2.7 dB low reflection. Additionally, the composites also demonstrated excellent Joule heating, photothermal performance, and recyclability, which exhibit substantial promise for advanced EMI shielding applications.

Exploring the molecular mechanism of sepsis-associated encephalopathy by integrated analysis of multiple datasets.

BACKGROUND: We aim to deal with the Hub-genes and signalling pathways connected with Sepsis-associated encephalopathy (SAE). METHODS: The raw datasets were acquired from the Gene Expression Omnibus (GEO) database (GSE198861 and GSE167610). R software filtered the differentially expressed genes (DEGs) for hub genes exploited for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Hub genes were identified from the intersection of DEGs via protein-protein interaction (PPI) network. And the single-cell dataset (GSE101901) was used to authenticate where the hub genes express in hippocampus cells. Cell-cell interaction analysis and Gene Set Variation Analysis (GSVA) analysis of the whole transcriptome validated the interactions between hippocampal cells. RESULTS: A total of 161 DEGs were revealed in GSE198861 and GSE167610 datasets. Biological function analysis showed that the DEGs were primarily involved in the phagosome pathway and significantly enriched. The PPI network extracted 10 Hub genes. The M2 Macrophage cell decreased significantly during the acute period, and the hub gene may play a role in this biological process. The hippocampal variation pathway was associated with the MAPK signaling pathway. CONCLUSION: Hub genes (Pecam1, Cdh5, Fcgr, C1qa, Vwf, Vegfa, C1qb, C1qc, Fcgr4 and Fcgr2b) may paticipate in the biological process of SAE.

Correlation of distribution characteristics and dynamic changes of gut microbiota with the efficacy of immunotherapy in EGFR-mutated non-small cell lung cancer.

BACKGROUND: The effects of gut microbiota and metabolites on the responses to immune checkpoint inhibitors (ICIs) in advanced epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLC) have been studied. However, their effects on EGFR-mutated (EGFR +) NSCLC remain unknown. METHODS: We prospectively recorded the clinicopathological characteristics of patients with advanced EGFR + NSCLC and assessed potential associations between the use of antibiotics or probiotics and immunotherapy efficacy. Fecal samples were collected at baseline, early on-treatment, response and progression status and were subjected to metagenomic next-generation sequencing and ultra-high-performance liquid chromatography-mass spectrometry analyses to assess the effects of gut microbiota and metabolites on immunotherapy efficacy. RESULTS: The clinical data of 74 advanced EGFR + NSCLC patients were complete and 18 patients' fecal samples were dynamically collected. Patients that used antibiotics had shorter progression-free survival (PFS) (mPFS, 4.8 vs. 6.7 months; P = 0.037); probiotics had no impact on PFS. Two dynamic types of gut microbiota during immunotherapy were identified: one type showed the lowest relative abundance at the response time point, whereas the other type showed the highest abundance at the response time point. Metabolomics revealed significant differences in metabolites distribution between responders and non-responders. Deoxycholic acid, glycerol, and quinolinic acid were enriched in responders, whereas L-citrulline was enriched in non-responders. There was a significant correlation between gut microbiota and metabolites. CONCLUSIONS: The use of antibiotics weakens immunotherapy efficacy in patients with advanced EGFR + NSCLC. The distribution characteristics and dynamic changes of gut microbiota and metabolites may indicate the efficacy of immunotherapy in advanced EGFR + NSCLC.

Efficacy and safety of perioperative therapy for locally resectable gastric cancer: A network meta-analysis of randomized clinical trials.

BACKGROUND: Gastric cancer (GC) is the fifth most commonly diagnosed malignancy worldwide, with over 1 million new cases per year, and the third leading cause of cancer-related death. AIM: To determine the optimal perioperative treatment regimen for patients with locally resectable GC. METHODS: A comprehensive literature search was conducted, focusing on phase II/III randomized controlled trials (RCTs) assessing perioperative chemotherapy and chemoradiotherapy in treating locally resectable GC. The R0 resection rate, overall survival (OS), disease-free survival (DFS), and incidence of grade 3 or higher nonsurgical severe adverse events (SAEs) associated with various perioperative regimens were analyzed. A Bayesian network meta-analysis was performed to compare treatment regimens and rank their efficacy. RESULTS: Thirty RCTs involving 8346 patients were included in this study. Neoadjuvant XELOX plus neoadjuvant radiotherapy and neoadjuvant CF were found to significantly improve the R0 resection rate compared with surgery alone, and the former had the highest probability of being the most effective option in this context. Neoadjuvant plus adjuvant FLOT was associated with the highest probability of being the best regimen for improving OS. Owing to limited data, no definitive ranking could be determined for DFS. Considering nonsurgical SAEs, FLO has emerged as the safest treatment regimen. CONCLUSION: This study provides valuable insights for clinicians when selecting perioperative treatment regimens for patients with locally resectable GC. Further studies are required to validate these findings.

Projection domain decomposition denoising algorithm based on low rank and similarity-based regularization.

BACKGROUND: Projection Domain Decomposition (PDD) is a dual energy reconstruction method which implements the decomposition process before image reconstruction. The advantage of PDD is that it can alleviate beam hardening artifacts and metal artifacts effectively as energy spectra estimation is considered in PDD. However, noise amplification occurs during the decomposition process, which significantly impacts the accuracy of effective atomic number and electron density. Therefore, effective noise reduction techniques are required in PDD. OBJECTIVE: This study aims to develop a new algorithm capable of minimizing noise while simultaneously preserving edges and fine details. METHODS: In this study, a denoising algorithm based on low rank and similarity-based regularization (LRSBR) is presented. This algorithm incorporates the low-rank characteristic of tensors into similarity-based regularization (SBR) framework. This method effectively addresses the issue of instability in edge pixels within the SBR algorithm and enhances the structural consistency of dual-energy images. RESULTS: A series of simulation and practical experiments were conducted on a dual-layer dual-energy CT system. Experiments demonstrate that the proposed method outperforms exiting noise removal methods in Peak Signal-to-noise Ratio (PSNR), Root Mean Square Error (RMSE), and Structural Similarity (SSIM). Meanwhile, there has been a notable enhancement in the visual quality of CT images. CONCLUSIONS: The proposed algorithm has a significantly improved noise reduction compared to other competing approach in dual-energy CT. Meanwhile, the LRSBR method exhibits outstanding performance in preserving edges and fine structures, making it practical for PDD applications.

Redoxhigh phenotype mediated by KEAP1/STK11/SMARCA4/NRF2 mutations diminishes tissue-resident memory CD8+ T cells and attenuates the efficacy of immunotherapy in lung adenocarcinoma.

Metabolism reprogramming within the tumor microenvironment (TME) can have a profound impact on immune cells. Identifying the association between metabolic phenotypes and immune cells in lung adenocarcinoma (LUAD) may reveal mechanisms of resistance to immune checkpoint inhibitors (ICIs). Metabolic phenotypes were classified by expression of metabolic genes. Somatic mutations and transcriptomic features were compared across the different metabolic phenotypes. The metabolic phenotype of LUAD is predominantly determined by reductase-oxidative activity and is divided into two categories: redoxhigh LUAD and redoxlow LUAD. Genetically, redoxhigh LUAD is mainly driven by mutations in KEAP1, STK11, NRF2, or SMARCA4. These mutations are more prevalent in redoxhigh LUAD (72.5%) compared to redoxlow LUAD (17.4%), whereas EGFR mutations are more common in redoxlow LUAD (19.0% vs. 0.7%). Single-cell RNA profiling of pre-treatment and post-treatment samples from patients receiving neoadjuvant chemoimmunotherapy revealed that tissue-resident memory CD8+ T cells are responders to ICIs. However, these cells are significantly reduced in redoxhigh LUAD. The redoxhigh phenotype is primarily attributed to tumor cells and is positively associated with mTORC1 signaling. LUAD with the redoxhigh phenotype demonstrates a lower response rate (39.1% vs. 70.8%, p = 0.001), shorter progression-free survival (3.3 vs. 14.6 months, p = 0.004), and overall survival (12.1 vs. 31.2 months, p = 0.022) when treated with ICIs. The redoxhigh phenotype in LUAD is predominantly driven by mutations in KEAP1, STK11, NRF2, and SMARCA4. This phenotype diminishes the number of tissue-resident memory CD8+ T cells and attenuates the efficacy of ICIs.

Analysis and prediction of interactions between transmembrane and non-transmembrane proteins.

BACKGROUND: Most of the important biological mechanisms and functions of transmembrane proteins (TMPs) are realized through their interactions with non-transmembrane proteins(nonTMPs). The interactions between TMPs and nonTMPs in cells play vital roles in intracellular signaling, energy metabolism, investigating membrane-crossing mechanisms, correlations between disease and drugs. RESULTS: Despite the importance of TMP-nonTMP interactions, the study of them remains in the wet experimental stage, lacking specific and comprehensive studies in the field of bioinformatics. To fill this gap, we performed a comprehensive statistical analysis of known TMP-nonTMP interactions and constructed a deep learning-based predictor to identify potential interactions. The statistical analysis describes known TMP-nonTMP interactions from various perspectives, such as distributions of species and protein families, enrichment of GO and KEGG pathways, as well as hub proteins and subnetwork modules in the PPI network. The predictor implemented by an end-to-end deep learning model can identify potential interactions from protein primary sequence information. The experimental results over the independent validation demonstrated considerable prediction performance with an MCC of 0.541. CONCLUSIONS: To our knowledge, we were the first to focus on TMP-nonTMP interactions. We comprehensively analyzed them using bioinformatics methods and predicted them via deep learning-based solely on their sequence. This research completes a key link in the protein network, benefits the understanding of protein functions, and helps in pathogenesis studies of diseases and associated drug development.

A cross-disease, pleiotropy-driven approach for therapeutic target prioritization and evaluation.

Cross-disease genome-wide association studies (GWASs) unveil pleiotropic loci, mostly situated within the non-coding genome, each of which exerts pleiotropic effects across multiple diseases. However, the challenge "W-H-W" (namely, whether, how, and in which specific diseases pleiotropy can inform clinical therapeutics) calls for effective and integrative approaches and tools. We here introduce a pleiotropy-driven approach specifically designed for therapeutic target prioritization and evaluation from cross-disease GWAS summary data, with its validity demonstrated through applications to two systems of disorders (neuropsychiatric and inflammatory). We illustrate its improved performance in recovering clinical proof-of-concept therapeutic targets. Importantly, it identifies specific diseases where pleiotropy informs clinical therapeutics. Furthermore, we illustrate its versatility in accomplishing advanced tasks, including pathway crosstalk identification and downstream crosstalk-based analyses. To conclude, our integrated solution helps bridge the gap between pleiotropy studies and therapeutics discovery.

Rational treatment options for T1/2N0M0 squamous cell carcinoma of the anal canal: a population-based study combined with external validation.

BACKGROUND: Treatment options for T1/2N0M0 anal squamous cell carcinoma include chemotherapy, radiotherapy, chemoradiotherapy, and local excision, although the optimal treatment method has not been determined. METHODS: The National Cancer Institute Surveillance, Epidemiology and Results database was used to search and screen 1465 patients with cT1/2N0M0 anal squamous cell carcinoma who were clinically diagnosed between 2004 and 2016. Survival analysis was performed using the Kaplan-Meier method and log-rank test. Cox proportional hazards regression analysis was performed to screen independent prognostic factors and build a nomogram survival prediction model. According to the risk score, patients were divided into low, medium, and high risk groups using X-tile software. RESULTS: Age, sex, grade and cT stage were identified as independent prognostic factors for cT1/2N0M0 anal squamous cell carcinoma and were included in the nomogram to construct a prediction model. The C-index of the model was 0.770 [95% confidence interval (CI), 0.693-0.856], which was higher than the C-index of T stage 0.565 (95% CI, 0.550-0.612). Low-risk patients benefited from local resection, moderate-risk patients benefited from radiotherapy, and high-risk patients benefited from radiotherapy or chemoradiotherapy. This was confirmed using external validation data from the center. CONCLUSION: The nomogram developed in this study effectively and comprehensively evaluated the prognosis of patients with cT1/2N0M0 squamous cell carcinoma of the anal canal. Local excision is recommended for low risk patients, radiotherapy for moderate-risk patients, and radiotherapy or chemoradiotherapy for high-risk patients.

Removal of antibiotics by four microalgae-based systems for swine wastewater treatment under different phytohormone treatment.

This study examined the removal of typical antibiotics from simulated swine wastewater. Microalgae-bacteria/fungi symbioses were constructed using Chlorella ellipsoidea, endophytic bacteria (S395-2), and Clonostachys rosea as biomaterials. The growth, photosynthetic performance, and removal of three types of antibiotics (tetracyclines, sulfonamides, and quinolones) induced by four phytohormones were analyzed in each system. The results showed that all four phytohormones effectively improved the tolerance of symbiotic strains against antibiotic stress; strigolactones (GR24) achieved the best performance. At 10-9 M, GR24 achieved the best removal of antibiotics by C. elliptica + S395-2 + C. rosea symbiosis. The average removals of tetracycline, sulfonamide, and quinolone by this system reached 96.2-99.4 %, 75.2-81.1 %, and 66.8-69.9 %, respectively. The results of this study help to develop appropriate bio enhancement strategies as well as design and operate algal-bacterial-fungal symbiotic processes for the treatment of antibiotics-containing wastewater.

Antipsychotic-induced epigenomic reorganization in frontal cortex of individuals with schizophrenia.

Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here, we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n=58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time on the impact of age and antipsychotic treatment on chromatin organization.

Multiple salary comparisons, distributive justice, and employee withdrawal.

Salary comparison has well-established implications for employees' attitudes and behaviors at work. Yet how employees process information about simultaneous comparisons, particularly when internal and external comparison information is incongruent, remains controversial. In this article, we draw from the model of dispositional attribution and equity theory to predict how the incongruence of internal and external salary comparisons affects perceptions of distributive justice and subsequent employee withdrawal behavior. We hypothesized that the effect of salary comparisons on perceived distributive justice follows a hierarchically restrictive schema in which a lower salary in comparison to a referent has a greater effect than a higher salary. This further affects employee withdrawal (neglect, turnover intention, and voluntary turnover). We also propose that the effects of salary comparisons are bounded by employees' zero-sum construal of success. Three studies were conducted to test our hypotheses: a quasi-experimental study and two time-lagged field studies. Consistent with our hypotheses, we observed that, when comparison information was incongruent, underpayment compared with others more strongly affected perceived distributive justice than overpayment did. The subsequent impact on perceived distributive justice was negatively related to employee withdrawal. As expected, the effect of incongruent salary comparison information was stronger for employees with lower zero-sum construal of success. The theoretical and practical implications of these findings are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Quality of AI-Generated Dental Caries Multiple Choice Questions: A Comparative Analysis of ChatGPT and Google Bard Language Models.

Statement of problem: AI technology presents a variety of benefits and challenges for educators. Purpose: To investigate whether ChatGPT and Google Bard (now is named Gemini) are valuable resources for generating multiple-choice questions for educators of dental caries. Material and methods: A book on dental caries was used. Sixteen paragraphs were extracted by an expert consultant based on applicability and potential for developing multiple-choice questions. ChatGPT and Bard language models were used to produce multiple-choice questions based on this input, and 64 questions were generated. Three dental specialists assessed the relevance, accuracy, and complexity of the generated questions. The questions were qualitatively evaluated using cognitive learning objectives and item writing flaws. Paired sample t-tests and two-way analysis of variance (ANOVA) were used to compare the generated multiple-choice questions and answers between ChatGPT and Bard. Results: There were no significant differences between the questions generated by ChatGPT and Bard. Moreover, the analysis of variance found no significant differences in question quality. Bard-generated questions tended to have higher cognitive levels than those of ChatGPT. Format error was predominant in ChatGPT-generated questions. Finally, Bard exhibited more absolute terms than ChatGPT. Conclusions: ChatGPT and Bard could generate questions related to dental caries, mainly at the cognitive level of knowledge and comprehension. Clinical significance: Language models are crucial for generating subject-specific questions used in quizzes, tests, and education. By using these models, educators can save time and focus on lesson preparation and student engagement instead of solely focusing on assessment creation. Additionally, language models are adept at generating numerous questions, making them particularly valuable for large-scale exams. However, educators must carefully review and adapt the questions to ensure they align with their learning goals.

Sequencing and Analysis of the Complete Mitochondrial Genome of Lentipes ikeae.

We sequenced and analyzed the complete mitochondrial genome of Lentipes ikeae and explored the phylogenetic relationships among Sicydiinae based on mitochondrial genome sequences. The complete mitochondrial genome sequence of L. ikeae was determined using the Illumina HiSeq X Ten sequencing platform, and the gene structural characteristics and base composition were analyzed. Based on the mitochondrial genome sequences of 28 Sicydiinae species published in GenBank and mitochondrial protein-coding genes (PCGs), Acanthogobius flavimanus (Gobionellinae) was selected as an outgroup to construct phylogenetic trees of Sicydiinae using the maximum likelihood and Bayesian inference methods. The mitochondrial genome of L. ikeae (GenBank number: OP764680) has a total length of 16,498 bp and encodes 13 PCGs, 22 transfer RNA genes, two ribosomal RNA genes, and a D-loop (control) region. Gene rearrangement is not observed. The mitochondrial genome of L. ikeae exhibits an AT preference, with AT skew > 0 and GC skew < 0 across the entire genome. The phylogenetic relationships of Sicydiinae based on 13 mitochondrial PCG sequences are Sicydium + (Stiphodon + (Sicyopus + Lentipes)) + Sicyopterus, indicating that Sicydium, Sicyopterus, Lentipes, and Stiphodon are all monophyletic groups.

Can Media Literacy Intervention Improve Fake News Credibility Assessment? A Meta-Analysis.

Fake news impacts individuals' behavior and decision-making while also disrupting political processes, perceptions of medical advice, and societal trends. Improving individuals' ability to accurately assess fake news can reduce its harmful effects. However, previous research on media literacy interventions designed for improving fake news credibility assessments has yielded inconsistent results. We systematically collected 33 independent studies and performed a meta-analysis to examine the effects of media literacy interventions on assessing fake news credibility (n = 36,256). The results showed that media literacy interventions significantly improved fake news credibility assessments (Hedges' g = 0.53, 95% confidence interval [0.29-0.78], p < 0.001). Gaming interventions were the most effective intervention form. Conversely, the intervention channel, outcome measurement, and subject characteristics (age, gender, and country development level) did not influence the intervention effects.

Epigenomic tomography for probing spatially defined chromatin state in the brain.

Spatially resolved epigenomic profiling is critical for understanding biology in the mammalian brain. Single-cell spatial epigenomic assays were developed recently for this purpose, but they remain costly and labor intensive for examining brain tissues across substantial dimensions and surveying a collection of brain samples. Here, we demonstrate an approach, epigenomic tomography, that maps spatial epigenomes of mouse brain at the scale of centimeters. We individually profiled neuronal and glial fractions of mouse neocortex slices with 0.5 mm thickness. Tri-methylation of histone 3 at lysine 27 (H3K27me3) or acetylation of histone 3 at lysine 27 (H3K27ac) features across these slices were grouped into clusters based on their spatial variation patterns to form epigenomic brain maps. As a proof of principle, our approach reveals striking dynamics in the frontal cortex due to kainic-acid-induced seizure, linked with transmembrane ion transporters, exocytosis of synaptic vesicles, and secretion of neurotransmitters. Epigenomic tomography provides a powerful and cost-effective tool for characterizing brain disorders based on the spatial epigenome.

Ecosystem service tradeoff and synergistic relationship in the Yellow River Delta High-Efficiency Eco-Economic Zone.

Exploring the tradeoff and synergy relationship among ecosystem services in the Yellow River Delta High-Efficiency Eco-Economic Zone is of great practical significance for regional ecosystem service function zoning and high-quality development. Using the InVEST model, spatial auto-correlation and trade-off synergism (ESTD) model, we analyzed the spatial and temporal variations of five ecosystem services (habitat quality, carbon storage, soil conservation, water conservation, and water purification), as well as their trade-off and synergistic relationships at the township scale from 2000 to 2020. The results showed that habitat quality, carbon storage, and nitrogen and phosphorus output decreased as a whole from 2000 to 2020, and soil conservation and water purification increased. Habitat quality showed a distribution pattern of high in the north and low in the south, and carbon sto-rage, nitrogen and phosphorus output, soil conservation and water purification showed a pattern of low in the north and high in the south. During the study period, synergistic relationships among the five ecosystem services were predominant in both time cross-section and time period, but there were still differences, with synergistic relationships mainly between carbon storage and other services in time cross-section, and between habitat quality and other ser-vices in time period. Our results can provide theoretical guidance and practical reference for the enhancement of ecosystem services and the zoning of ecosystem functions, as well as basic support for the optimization of spatial patterns of national territory.

Plasma Cell-Free Adenomatous Polyposis Coli Gene Promoter Methylation as a Prognostic Biomarker for Hepatocellular Carcinoma.

INTRODUCTION: Hepatocellular carcinoma (HCC) is a leading cause of cancer death worldwide. Lack of biomarkers for follow-up after treatment is a clinical challenge. DNA methylation has been proposed to be a potential biomarker in HCC. However, there is still lacking of evidence of its clinical use. This study aims to evaluate the value of using plasma Adenomatous Polyposis Coli promoter methylation level (APC-MET) as a potential biomarker in HCC treatment. METHOD: A total of 96 patients with HCC at BCLC stage B underwent local tumor ablation treatment were prospectively included in this study. APC-MET was examined from the plasma of each patient before and 1 months after treatment. The prediction value of APC-MET for survival outcome and disease status after treatment were analyzed, and adjusted with alpha-fetoprotein and protein induced by vitamin K absence-II using cox regression analysis. RESULTS: Univariate cox regression analysis showed preoperative APC-MET >0 (HR, 2.9, 95% CI 1.05－8.05, p=0.041) and postoperative APC-MET >0 (HR, 3.47, 95% CI 1.16－10.4, p=0.026) were both predictors of death, and preoperative APC-MET >0 was a predictor of disease progression after treatment (HR, 2.04, 95% CI 1.21－3.44, p=0.007). In multivariate models, pre-op APC-MET >0 was a significant predictor of disease progression after adjusting with other two traditional biomarkers (HR, 1.82, 95% CI 1.05－3.17, p=0.034). CONCLUSIONS: Hypermethylation of APC promoter appears to be a potential biomarker that could predict patient survival and disease progression outcome in patients with intermediate stage HCC after local ablation treatment.

Photoinduced Selective B-H Activation of nido-Carboranes.

The development of new synthetic methods for B-H bond activation has been an important research area in boron cluster chemistry, which may provide opportunities to broaden the application scope of boron clusters. Herein, we present a new reaction strategy for the direct site-selective B-H functionalization of nido-carboranes initiated by photoinduced cage activation via a noncovalent cage···π interaction. As a result, the nido-carborane cage radical is generated through a single electron transfer from the 3D nido-carborane cage to a 2D photocatalyst upon irradiation with green light. The resulting transient nido-carborane cage radical could be directly probed by an advanced time-resolved EPR technique. In air, the subsequent transformations of the active nido-carborane cage radical have led to efficient and selective B-N, B-S, and B-Se couplings in the presence of N-heterocycles, imines, thioethers, thioamides, and selenium ethers. This protocol also facilitates both the late-stage modification of drugs and the synthesis of nido-carborane-based drug candidates for boron neutron capture therapy (BNCT).