Development of a CT-Based comprehensive model combining clinical, radiomics with deep learning for differentiating pulmonary metastases from noncalcified pulmonary hamartomas, a retrospective cohort study.

BACKGROUND: Clinical differentiation between pulmonary metastases and noncalcified pulmonary hamartomas (NCPH) often presents challenges, leading to potential misdiagnosis. However, the efficacy of a comprehensive model that integrates clinical features, radiomics, and deep learning (CRDL) for differential diagnosis of these two diseases remains uncertain. OBJECTIVE: This study evaluated the diagnostic efficacy of a Clinical Features, Radiomics, and Deep Learning (CRDL) model in differentiating pulmonary metastases from noncalcified pulmonary hamartomas (NCPH). METHODS: We retrospectively analyzed the clinical and imaging data of 256 patients from Hospital A and 85 patients from Hospital B, who were pathologically confirmed pulmonary hamartomas or pulmonary metastases after thoracic surgery. Employing Python 3.7 software suites, we extracted radiomic features and deep learning attributes from patient datasets. The cohort was divided into training set, internal validation set, and external validation set. The diagnostic performance of the constructed models was evaluated using receiver operating characteristic (ROC) curve analysis to determine their effectiveness in differentiating between pulmonary metastases and NCPH. RESULTS: Clinical features such as white blood cell count (WBC), platelet count (PLT), history of cancer, carcinoembryonic antigen (CEA) level, tumor marker status, lesion margin characteristics (smooth or blurred) and maximum diameter were found to have diagnostic value in differentiating between the two diseases. In the domains of radiomics and deep learning. Of the 1,130 radiomics features and 512 deep learning features, 24 and 7, respectively, were selected for model development. The area under the ROC curve (AUC) values for the four groups were 0.980, 0.979, 0.999, and 0.985 in the training set, 0.947, 0.816, 0.934, and 0.952 in the internal validation set, and 0.890, 0.904, 0.923, and 0.938 in the external validation set. This demonstrated that the CRDL model showed the greatest efficacy. CONCLUSIONS: The comprehensive model incorporating clinical features, radiomics, and deep learning shows promise for aiding in the differentiation between pulmonary metastases and hamartomas.

Study of flexural strength of concrete containing mineral admixtures based on machine learning.

In this paper, the prediction of flexural strength was investigated using machine learning methods for concrete containing supplementary cementitious materials such as silica fume. First, based on a database of suitable characteristic parameters, the flexural strength prediction was carried out using linear (LR) model, random forest (RF) model, and extreme gradient boosting (XGB) model. Subsequently, the influence of each input parameter on the flexural strength was analyzed using the SHAP model based on the optimal prediction model. The results showed that LR, RF, and XGB enhanced the accuracy of forecasting sequentially. Among the characteristic parameters, the most significant effect on the flexural strength of concrete is the water-binder ratio, and the water-binder ratio shows a negative correlation with flexural strength. The effect of maintenance age on flexural strength is second only to the water-binder ratio, and it shows a positive trend. When the amount of fly ash is less than 40% and the amount of slag or silica fume is less than 30%, the correlation between the amount of supplementary cementitious materials and flexural strength fluctuates and a positive peak in flexural strength is observed. However, at a dosage greater than the above, the supplementary cementitious materials all reduce flexural strength. The interaction interval and the degree of interaction between the supplementary cementitious materials and the cement content also differ in predicting flexural strength.

Identification and Validation of a Metabolism-Related Prognostic Signature Associated with M2 Macrophage Infiltration in Gastric Cancer.

High levels of M2 macrophage infiltration invariably contribute to poor cancer prognosis and can be manipulated by metabolic reprogramming in the tumor microenvironment. However, the metabolism-related genes (MRGs) affecting M2 macrophage infiltration and their clinical implications are not fully understood. In this study, we identified 173 MRGs associated with M2 macrophage infiltration in cases of gastric cancer (GC) using the TCGA and GEO databases. Twelve MRGs were eventually adopted as the prognostic signature to develop a risk model. In the high-risk group, the patients showed poorer survival outcomes than patients in the low-risk group. Additionally, the patients in the high-risk group were less sensitive to certain drugs, such as 5-Fluorouracil, Oxaliplatin, and Cisplatin. Risk scores were positively correlated with the infiltration of multiple immune cells, including CD8+ T cells and M2 macrophages. Furthermore, a difference was observed in the expression and distribution between the 12 signature genes in the tumor microenvironment through single-cell sequencing analysis. In vitro experiments proved that the M2 polarization of macrophages was suppressed by Sorcin-knockdown GC cells, thereby hindering the proliferation and migration of GC cells. These findings provide a valuable prognostic signature for evaluating clinical outcomes and corresponding treatment options and identifying potential targets for GC treatment.

Self-Powered Flexible Ultraviolet Photodetectors Based on CuI/a-ZTO Heterojunction Processed at Room Temperature.

For traditional wide-bandgap semiconductor materials, a high-temperature process is unavoidable for improving crystallization quality, so the substrate of the device is greatly limited. In this work, zinc-tin oxide (a-ZTO) amorphous oxide processed by the pulsed laser deposition method was utilized as the n-type layer, which exhibits considerable electron mobility and optical transparency, and can be deposited at room temperature. At the same time, by combining p-type CuI grown by the thermal evaporation method, a vertically structured ultraviolet photodetector based on CuI/ZTO heterojunction was obtained. The detector demonstrates self-powered properties, with an on-off ratio exceeding 104, and rapid response with a rise time of 2.36 ms and a fall time of 1.49 ms. Also, the photodetector shows long-term stability with 92% retention after 5000 s cyclic lighting and maintains reproducible response in frequency dependence measurement. Furthermore, the flexible photodetector on poly(ethylene terephthalate) (PET) substrates was constructed, exhibiting fast response and durability in the bending state. This is the first time that the heterostructure based on CuI has been applied in the flexible photodetector. The excellent results indicate that the combination of amorphous oxide and CuI has the potential for ultraviolet photodetectors, and will broaden the application range of high-performance flexible/transparent optoelectronic devices in the future.

Empowering biologists to decode omics data: the Genekitr R package and web server.

BACKGROUND: A variety of high-throughput analyses, such as transcriptome, proteome, and metabolome analysis, have been developed, producing unprecedented amounts of omics data. These studies generate large gene lists, of which the biological significance shall be deeply understood. However, manually interpreting these lists is difficult, especially for non-bioinformatics-savvy scientists. RESULTS: We developed an R package and a corresponding web server-Genekitr, to assist biologists in exploring large gene sets. Genekitr comprises four modules: gene information retrieval, ID (identifier) conversion, enrichment analysis and publication-ready plotting. Currently, the information retrieval module can retrieve information on up to 23 attributes for genes of 317 organisms. The ID conversion module assists in ID-mapping of genes, probes, proteins, and aliases. The enrichment analysis module organizes 315 gene set libraries in different biological contexts by over-representation analysis and gene set enrichment analysis. The plotting module performs customizable and high-quality illustrations that can be used directly in presentations or publications. CONCLUSIONS: This web server tool will make bioinformatics more accessible to scientists who might not have programming expertise, allowing them to perform bioinformatics tasks without coding.

Transcription factor AP2 enhances malignancy of non-small cell lung cancer through upregulation of USP22 gene expression.

BACKGROUND: Ubiquitin-specific protease 22 (USP22), a putative cancer stem cell marker, is frequently upregulated in cancers, and USP22 overexpression is associated with aggressive growth, metastasis, and therapy resistance in various human cancers including lung cancer. However, USP22 gene amplification seldom occurs, and the mechanism underlying USP22 upregulation in human cancers remains largely unknown. METHODS: A luciferase reporter driven by a promoter region of USP22 gene was selectively constructed to screen against a customized siRNA library targeting 89 selected transcription factors to identify potential transcription factors (TFs) that regulate USP22 expression in human non-small cell lung cancers (NSCLC). Association of identified TFs with USP22 and potential role of the TFs were validated and explored in NSCLC by biological assays and immunohistochemistry analysis. RESULTS: Luciferase reporter assays revealed that SP1 and activating transcription factor 3 (ATF3) inhibit USP22 transcription, while transcription factor AP-2 Alpha/Beta (TFAP2A/2B) and c-Myc promote USP22 transcription. Binding site-directed mutagenesis and chromosome immunoprecipitation (ChIP) assays validated AP2α and AP2ß are novel TFs of USP22. Furthermore, overexpression of AP2A and AP2B significantly upregulates USP22 expression, and its target: Cyclin D1, concurrently enhances the proliferation, migration, and invasion of NSCLC A549 and H1299 cells in a partially USP22-dependent manner. Moreover, AP2 protein level correlated with USP22 protein in human NSCLC tissues. CONCLUSION: Our findings indicate AP2α and AP2ß are important transcription factors driving USP22 gene expression to promote the progression of NSCLC, and further support USP22 as a potential biomarker and therapeutic target for lung cancer. Video Abstract.

Identification and Validation of Novel Immune-Related Alternative Splicing Signatures as a Prognostic Model for Colon Cancer.

Background: Individual immune-related alternative splicing (AS) events have been found to be significant in immune regulation and cancer prognosis. However, a comprehensive analysis of AS events in cancer cells based on immune-related genes (IRGs) has not been performed, and its clinical value is unknown. Methods: Colon cancer cases with AS data were obtained from TCGA, and then, we identified overall survival-related AS events (OS-ASEs) based on IRGs by univariate analyses. Using Lasso regression, multivariate Cox regression, Kaplan-Meier analysis and nomograms, we constructed an AS risk model based on the calculated risk score. Furthermore, associations of the risk score with clinical and immune features were confirmed through the Wilcoxon rank sum test, association analysis, etc. Finally, by qRT-PCR, cell coculture and CCK-8 analyses, we validated the significance of OS-ASEs in colon cancer cell lines and clinical samples. Results: A total of 3,119 immune-related AS events and 183 OS-ASEs were identified, and 9 OS-ASEs were ultimately used to construct a comprehensive risk model for colon cancer patients. Low-risk patients had better OS and DFS rates than high risk patients. Furthermore, a high risk score corresponded to high numbers of multiple tumour-infiltrating immune cells and high expression of HLA-D region genes and immune checkpoint genes. Notably, we identified for the first time that anti-PD-L1 or anti-CTLA-4 antibodies may decrease the OS of specific colon cancer patients in the low-risk group. Additionally, the in vitro experiment validated that CD46-9652-ES and PSMC5-43011-ES are positively correlated with the infiltration of immune cells and promote the growth of colon cancer cells. CD46-9652-ES can contribute to T cell-mediated tumour cell killing. PSMC5-43011-ES was observed to induce M2 polarization of macrophages. Conclusions: This study identified and validated immune-related prognostic AS signatures that can be used as a novel AS prognostic model and provide a novel understanding of the relationship between the immune microenvironment and clinical outcomes.

Liquid biopsy at the frontier of detection, prognosis and progression monitoring in colorectal cancer.

Colorectal cancer (CRC) is one of the most common cancers worldwide and a leading cause of carcinogenic death. To date, surgical resection is regarded as the gold standard by the operator for clinical decisions. Because conventional tissue biopsy is invasive and only a small sample can sometimes be obtained, it is unable to represent the heterogeneity of tumor or dynamically monitor tumor progression. Therefore, there is an urgent need to find a new minimally invasive or noninvasive diagnostic strategy to detect CRC at an early stage and monitor CRC recurrence. Over the past years, a new diagnostic concept called "liquid biopsy" has gained much attention. Liquid biopsy is noninvasive, allowing repeated analysis and real-time monitoring of tumor recurrence, metastasis or therapeutic responses. With the advanced development of new molecular techniques in CRC, circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes, and tumor-educated platelet (TEP) detection have achieved interesting and inspiring results as the most prominent liquid biopsy markers. In this review, we focused on some clinical applications of CTCs, ctDNA, exosomes and TEPs and discuss promising future applications to solve unmet clinical needs in CRC patients.

CircMYH9 drives colorectal cancer growth by regulating serine metabolism and redox homeostasis in a p53-dependent manner.

BACKGROUND: Circular RNAs (circRNAs) play important roles in cancer progression and metabolism regulation. Serine/glycine metabolism supports the growth of cancer cells by contributing to their anabolic demands and epigenome as well as by regulating their redox state. However, the role of circRNA in the regulation of serine/glycine metabolism has not been well elucidated. METHODS: Microarray analysis was used to screen differentially expressed novel circRNAs. qRT-PCR and FISH were utilized to analyzed the expression of circMYH9. CCK8, colony formation and FACS were used to analyze proliferation of colorectal cancer (CRC) cells. Xenograft experiments were used to analyze tumor growth in vivo. RNA-sequencing, immunoblot and LC-MS were used to identify the downstream metabolic pathway of circMYH9. ChIRP, Mass Spectrometry, RIP and RNA pulldown were utilized to test the interaction between circMYH9, hnRNPA2B1 and p53 pre-mRNA. ChIP-qPCR was used to analyze the binding sites of HIF-1α. Chemically-induced CRC mice were generated to evaluate the role of circMYH9 in tumorigenesis. RESULTS: We identified an intron-derived circRNA, circMYH9, which was significantly upregulated in CRC tissues. A higher circMYH9 level correlated with shorter relapse-free survival and overall survival of CRC patients. CircMYH9 promoted serine/glycine metabolism, the NAD + /NADH ratio, and glutathione recycling and inhibited reactive oxygen species (ROS) in a p53-dependent manner, impacting tumour growth. Mechanistically, circMYH9 destabilized the pre-mRNA of p53 by recruiting hnRNPA2B1 in the nucleus. hnRNPA2B1 bound to N6-methyladenosine sites on the 3' untranslated region of p53 pre-mRNA and maintained its stability. Moreover, a lack of amino acids led to an elevated level of ROS, resulting in increased HIF1α, which promoted circMYH9 expression by binding to the promoter region. Furthermore, in vivo AAV9-mediated transfection of circMYH9 could drive chemically-induced carcinogenesis by suppressing p53 in mice. CONCLUSIONS: The overexpression of circMYH9 promotes CRC proliferation though modulating serine/glycine metabolism and redox homeostasis in a p53-dependent manner, and targeting circMYH9 and its pathway may be an effective strategy for the treatment of CRC.

Noncoding RNAs regulate alternative splicing in Cancer.

AS (alternative splicing) is a fundamental process by which a gene can generate multiple distinct mRNA transcripts to increase protein diversity. Defects in AS influence the occurrence and development of many diseases, including cancers, and are frequently found to participate in various aspects of cancer biology, such as promoting invasion, metastasis, apoptosis resistance and drug resistance. NcRNAs (noncoding RNAs) are an abundant class of RNAs that do not encode proteins. NcRNAs include miRNAs (microRNAs), lncRNAs (long noncoding RNAs), circRNAs (circular RNAs) and snRNAs (small nuclear RNAs) and have been proven to act as regulatory molecules that mediate cancer processes through AS. NcRNAs can directly or indirectly influence a plethora of molecular targets to regulate cis-acting elements, trans-acting factors, or pre-mRNA transcription at multiple levels, affecting the AS process and generating alternatively spliced isoforms. Consequently, ncRNA-mediated AS outcomes affect multiple cellular signaling pathways that promote or suppress cancer progression. In this review, we summarize the current mechanisms by which ncRNAs regulate AS in cancers and discuss their potential clinical applications as biomarkers and therapeutic targets.

EZH2 overexpression dampens tumor-suppressive signals via an EGR1 silencer to drive breast tumorigenesis.

The mechanism underlying EZH2 overexpression in breast cancer and its involvement in tumorigenesis remain poorly understood. In this study, we developed an approach to systematically identify the trans-acting factors regulating the EZH2 expression, and identified more than 20 such factors. We revealed reciprocal regulation of early growth response 1 (EGR1) and EZH2: EGR1 activates the expression of EZH2, and EZH2 represses EGR1 expression. Using CRISPR-mediated genome/epigenome editing, we demonstrated that EHZ2 represses EGR1 expression through a silencer downstream of the EGR1 gene. Deletion of the EGR1 silencer resulted in reduced cell growth, invasion, tumorigenicity of breast cancer cells, and extensive changes in gene expression, such as upregulation of GADD45, DDIT3, and RND1; and downregulation of genes encoding cholesterol biosynthesis pathway enzymes. We hypothesize that EZH2/PRC2 acts as a "brake" for EGR1 expression by targeting the EGR1 silencer, and EZH2 overexpression dampens tumor-suppressive signals mediated by EGR1 to drive breast tumorigenesis.