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We investigated the Kondo effect of cobalt(II)-5-15-bis(4'-bromophenyl)-10,20-bis(4'-iodophenyl)porphyrin (CoTPPBr2I2) molecules on Au(111) with low-temperature scanning tunneling microscopy under ultrahigh vacuum conditions. The molecules exhibit four adsorption configurations at the top and bridge sites of the surface with different molecular orientations. The Kondo resonance shows extraordinary sensitivity to the adsorption configuration. By switching the molecule between different configurations, the Kondo temperature is varied over a wide range from ≈8 up to ≈250 K. Density functional theory calculations reveal that changes of the adsorption configuration lead to distinct variations of the hybridization between the molecule and the surface. Furthermore, we show that surface reconstruction plays a significant role for the molecular Kondo effect.
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We aimed to explore whether the genes associated with both platinum-based therapy and polyamine metabolism could predict the prognosis of LUAD. We searched for the differential expression genes (DEGs) associated with platinum-based therapy, then we interacted them with polyamine metabolism-related genes to obtain hub genes. Subsequently, we analysed the main immune cell populations in LUAD using the scRNA-seq data, and evaluated the activity of polyamine metabolism of different cell subpopulations. The DEGs between high and low activity groups were screened to identify key DEGs to establish prognostic risk score model. We further elucidated the landscape of immune cells, mutation and drug sensitivity analysis in different risk groups. Finally, we got 10 hub genes associated with both platinum-based chemotherapy and polyamine metabolism, and found that these hub genes mainly affected signalling transduction pathways. B cells and mast cells with highest polyamine metabolism activity, while NK cells were found with lowest polyamine metabolism activity based on scRNA-seq data. DEGs between high and low polyamine metabolism activity groups were identified, then 6 key genes were screened out to build risk score, which showed a good predictive power. The risk score showed a universal negative correlation with immunotherapy checkpoint genes and the cytotoxic T cells infiltration. The mutation rates of EGFR in low-risk group was significantly higher than that of high-risk group. In conclusion, we developed a risk score based on key genes associated with platinum-based therapy and polyamine metabolism, which provide a new perspective for prognosis prediction of LUAD.
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Adenocarcinoma de Pulmão , Regulação Neoplásica da Expressão Gênica , Neoplasias Pulmonares , Poliaminas , Humanos , Poliaminas/metabolismo , Prognóstico , Adenocarcinoma de Pulmão/genética , Adenocarcinoma de Pulmão/patologia , Adenocarcinoma de Pulmão/imunologia , Adenocarcinoma de Pulmão/tratamento farmacológico , Adenocarcinoma de Pulmão/metabolismo , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/imunologia , Neoplasias Pulmonares/metabolismo , Mutação , Perfilação da Expressão Gênica , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismoRESUMO
BACKGROUND: Hyperglycemia is a rapidly increasing risk factor for cancer mortality worldwide. However, the doseâresponse relationship between glucose levels and all-cause mortality in cancer survivors is still uncertain. METHODS: We enrolled 4,491 cancer survivors (weighted population 19,465,739) from the 1999-2019 National Health and Nutrition Examination Survey (NHANES). Cancer survivors were defined based on the question of whether they had ever been diagnosed with cancer by a doctor or a health professional. Hemoglobin A1c (HbA1c) was selected in this study as a stable marker of glucose level. Mortality was ascertained by linkage to National Death Index records until December 31, 2019. Cox proportional hazard, KaplanâMeier survival curves and Restricted cubic spline regression models were used to evaluate the associations between HbA1c and all-cause mortality risk in cancer survivors. RESULTS: In NHANES, after adjusting for confounders, HbA1c had an independent nonlinear association with increased all-cause mortality in cancer survivors (nonlinear P value < 0.05). The threshold value for HbA1c was 5.4%, and the HRs (95% CI) below and above the threshold value were 0.917 (0.856,0.983) and 1.026 (1.010,1.043), respectively. Similar associations were found between fasting glucose and all-cause mortality in cancer survivors, and the threshold value was 5.7 mmol/L. CONCLUSIONS: HbA1c was nonlinearly associated with all-cause mortality in cancer survivors, and the critical value of HbA1c in decreased mortality was 5.4%, suggesting optimal glucose management in cancer survivors may be a key to preventing premature death in cancer survivors.
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Glicemia , Sobreviventes de Câncer , Hemoglobinas Glicadas , Inquéritos Nutricionais , Humanos , Sobreviventes de Câncer/estatística & dados numéricos , Feminino , Masculino , Pessoa de Meia-Idade , Hemoglobinas Glicadas/análise , Glicemia/análise , Adulto , Idoso , Causas de Morte , Neoplasias/mortalidade , Neoplasias/sangue , Fatores de Risco , Hiperglicemia/mortalidade , Estados Unidos/epidemiologia , Modelos de Riscos ProporcionaisRESUMO
Drug resistance is the major difficulty in treatment of lung squamous cell carcinoma (LUSC). This study aims to explore drug response-related miRNAs (DRmiRNAs) based on multi-omics research. We identified DRmiRNAs of LUSC with a multi-omics integrated system that combines expression data of microRNA, lncRNA, mRNA, methylation levels, somatic mutations. After identifying DRmiRNAs, we screened and validated of the target mRNAs of DRmiRNAs through Targetscan and the miRDB database. Then, Real-time PCR and Western blot assays were used to estimate the expression of DRmiRNAs and target protein, and the dual-luciferase assays were used to confirm the interaction of DRmiRNAs and target mRNA. Furthermore, CCK-8 (Cell Counting Kit-8) assays were used to evaluate cell proliferation and drug sensitivity. After integrated analysis, hsa-miR-185-5p was identified as DRmiRNA based on multi-omics data. Through Targetscan and miRDB database, the possible target mRNAs were obtained and PCDHA11 was validated as a target mRNA of miR-185-5p by real-time PCR, Western blot assays and dual-luciferase assays. CCK-8 assays and clone formation assays showed that the proliferation of miR-185-5p mimics was significantly slower than that of miR-185-5p inhibitors, which means overexpression of miR-185-5p enhanced the anticancer effects of cisplatin, whereas the downregulation of miR-185-5p reduced the effects. Furthermore, the proliferation of silencing PCDHA11 was significantly slower than that of overexpression of PCDHA11, which means PCDHA11 overexpression weakened the anticancer effects of cisplatin, and silencing PCDHA11 enhanced the effects. This study demonstrated that miR-185-5p was involved in chemoresistance of LUSC cells to cisplatin partly via down-regulating PCDHA11, which may promote understanding the underlying molecular mechanisms of drug response.
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Applying 10 Hz (α-rate) sensory stimulation, not 5 Hz (θ-rate), prior to introducing novel speech-print pairs can reset the phase of θ oscillations and enhance associative learning. This rapid gain indicates coordinated mechanisms to regulate attentional/cognitive resources (α oscillations) and facilitate memory storage (θ oscillations) early in learning. The present findings may inform educational practices for children with reading difficulties.
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This study examined the cognitive-linguistic and literacy-related correlates of dyslexia in three Chinese cities and the English word reading and mathematics performances of Chinese children with dyslexia. Chinese children with/without dyslexia were measured with an equivalent test battery of literacy and mathematics in Beijing, Hong Kong, and Taipei. Univariate analysis results suggested that phonological sensitivity distinguished those with and without dyslexia across all three cities in group comparisons. In Taipei and Hong Kong, morphological awareness, delayed copying, and spelling also distinguished the groups. Logistic regression analyses demonstrated that Chinese character reading, as directly compared to Chinese word reading, also distinguished the groups particularly well. In addition, in Beijing and Hong Kong, children with dyslexia performed significantly less well in English word reading than those without dyslexia. In Hong Kong and Taipei, children with dyslexia also had difficulties in mathematics performance. Findings highlight the fundamental importance of some cognitive-linguistic skills for explaining Chinese dyslexia across cultures, the utility of recognizing the individual Chinese character as a foundational unit of analysis in Chinese across cultures, and the generalizability of the comorbidity of both English as a second language (L2) and mathematics with dyslexia in Chinese children in both Beijing and Hong Kong.
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Dislexia , Humanos , Hong Kong , Masculino , Criança , Feminino , Dislexia/fisiopatologia , Taiwan , Leitura , Pequim/epidemiologia , Comparação Transcultural , Desempenho Acadêmico/estatística & dados numéricos , Cognição/fisiologia , Povo Asiático , Alfabetização/estatística & dados numéricos , Multilinguismo , China/epidemiologiaRESUMO
PURPOSE: FSTL3 expression is altered in various types of cancer. However, the role and mechanism of action of FSTL3 in lung adenocarcinoma development and tumor immunity are unknown. We investigated the association between FSTL3 expression and clinical characteristics and immune cell infiltration in lung adenocarcinoma samples from The Cancer Genome Atlas (TCGA) and a separate validation set from our hospital. METHODS: Data on immune system infiltration, gene expression, and relevant clinical information were obtained by analyzing lung adenocarcinoma sample data from TCGA database. Using online tools like GEPIA, the correlations between FSTL3 expression and prognosis, clinical stage, survival status, and tumor-infiltrating immune cells were examined. In a validation dataset, immunohistochemistry was performed to analyze FSTL3 expression and its related clinical characteristics. RESULTS: FSTL3 expression was markedly reduced in patients with lung adenocarcinoma. N stage, pathological stage, and overall survival were significantly correlated with FSTL3 expression. According to GSEA, FSTL3 is strongly linked to signaling pathways such as DNA replication and those involved in cell cycle regulation. Examination of TCGA database and TIMER online revealed a correlation between FSTL3 and B cell, T cell, NK cell, and neutrophil levels. The prognosis of patients with lung adenocarcinoma was significantly affected by six genes (KRT6A, VEGFC, KRT14, KRT17, SNORA12, and KRT81) related to FSTL3. CONCLUSION: FSTL3 is significantly associated with the prognosis and progression of lung adenocarcinoma and the infiltration of immune cells. Thus, targeting FSTL3 and its associated genes in immunotherapy could be potentially beneficial for the treatment of lung adenocarcinoma.
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Adenocarcinoma de Pulmão , Adenocarcinoma , Neoplasias Pulmonares , Humanos , Prognóstico , Adenocarcinoma de Pulmão/genética , Adenocarcinoma/genética , Linfócitos B , Neoplasias Pulmonares/genéticaRESUMO
Problem: Chest radiography is a crucial tool for diagnosing thoracic disorders, but interpretation errors and a lack of qualified practitioners can cause delays in treatment. Aim: This study aimed to develop a reliable multi-classification artificial intelligence (AI) tool to improve the accuracy and efficiency of chest radiograph diagnosis. Methods: We developed a convolutional neural network (CNN) capable of distinguishing among 26 thoracic diagnoses. The model was trained and externally validated using 795,055 chest radiographs from 13 datasets across 4 countries. Results: The CNN model achieved an average area under the curve (AUC) of 0.961 across all 26 diagnoses in the testing set. COVID-19 detection achieved perfect accuracy (AUC 1.000, [95% confidence interval {CI}, 1.000 to 1.000]), while effusion or pleural effusion detection showed the lowest accuracy (AUC 0.8453, [95% CI, 0.8417 to 0.8489]). In external validation, the model demonstrated strong reproducibility and generalizability within the local dataset, achieving an AUC of 0.9634 for lung opacity detection (95% CI, 0.9423 to 0.9702). The CNN outperformed both radiologists and nonradiological physicians, particularly in trans-device image recognition. Even for diseases not specifically trained on, such as aortic dissection, the AI model showed considerable scalability and enhanced diagnostic accuracy for physicians of varying experience levels (all P < 0.05). Additionally, our model exhibited no gender bias (P > 0.05). Conclusion: The developed AI algorithm, now available as professional web-based software, substantively improves chest radiograph interpretation. This research advances medical imaging and offers substantial diagnostic support in clinical settings.
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Background: Natural killer (NK) cells are crucial for tumor prognosis; however, their role in non-small-cell lung cancer (NSCLC) remains unclear. The current detection methods for NSCLC are inefficient and costly. Therefore, radiomics represent a promising alternative. Methods: We analyzed the radiogenomics datasets to extract clinical, radiological, and transcriptome data. The effect of NK cells on the prognosis of NSCLC was assessed. Tumors were delineated using a 3D Slicer, and features were extracted using pyradiomics. A radiomics model was developed and validated using five-fold cross-validation. A nomogram model was constructed using the selected clinical variables and a radiomic score (RS). The CIBERSORTx database and gene set enrichment analysis were used to explore the correlations of NK cell infiltration and molecular mechanisms. Results: Higher infiltration of NK cells was correlated with better overall survival (OS) (P = 0.002). The radiomic model showed an area under the curve of 0.731, with 0.726 post-validation. The RS differed significantly between high and low infiltration of NK cells (P < 0.01). The nomogram, using RS and clinical variables, effectively predicted 3-year OS. NK cell infiltration was correlated with the ICOS and BTLA genes (P < 0.001) and macrophage M0/M2 levels. The key pathways included TNF-α signaling via NF-κB and Wnt/ß-catenin signaling. Conclusions: Our radiomic model accurately predicted NK cell infiltration in NSCLC. Combined with clinical characteristics, it can predict the prognosis of patients with NSCLC. Bioinformatic analysis revealed the gene expression and pathways underlying NK cell infiltration in NSCLC.