Single Neuroform Atlas stent: a reliable approach for treating complex wide-neck bifurcated aneurysms.

Background: Treating wide-neck bifurcated cerebral aneurysms (WNBAs) using various techniques and new devices has shown favorable outcomes. However, endovascular coiling can be technically challenging when the aneurysm neck is incorporated into the parent vessel. Furthermore, although recent research has reported favorable outcomes of Neuroform Atlas stent (NAS)-assisted coiling, broad inclusion criteria have hampered precise evaluations of their effectiveness and safety for treating complex WNBAs. Therefore, this study evaluated whether the use of a single NAS is a safe and effective approach for treating complex WNBAs. Methods: We treated 76 complex WNBAs (unruptured, n = 49; ruptured, n = 27) using single NAS-assisted coil embolization and retrospectively analyzed the clinical and angiographic outcomes. Results: In a cohort of 68 patients (mean age, 58.3 ± 11.6 years; males n = 20, 29.4%; females, n = 48, 70.6%), 76 stents were successfully delivered to the target aneurysms, yielding a technical success rate of 98.6%. Complete occlusion was evident in 59 (77.6%) of 76 aneurysms, with neck remnants found in 16 (21.1%) and partial occlusion in 1 (1.3%). Treatment-related morbidities comprised one branch occlusion and one parenchymal hemorrhage. However, no new neurological symptoms of unruptured aneurysms were evident at discharge. The outcomes of 20 of the 27 ruptured aneurysms were favorable (Glasgow Outcome Scale scores of 4 or 5) at the final follow-up assessment (mean 12.2 [6-29] months), except for one initial subarachnoid hemorrhage. Post-treatment angiography revealed complete occlusion in 89.1%, neck remnants in 7.8%, and incomplete occlusion in 3.1% of the aneurysms. Approximately 88.2% of the patients were assessed at least once by follow-up diagnostic or magnetic resonance angiography (mean, 12.5 ± 4.3 [range, 6-29] months), with five (7.8%) minor and two (3.1%) major recurrences. Conclusion: A single NAS is safe and effective for treating WNBAs incorporated into parent vessels.

Neurochemical atlas of the rabbit spinal cord.

Complex neurophysiological and morphologic experiments require suitable animal models for investigation. The rabbit is one of the most successful models for studying spinal cord functions owing to its substantial size. However, achieving precise surgical access to specific spinal regions requires a thorough understanding of the spinal cord's cytoarchitectonic structure and its spatial relationship with the vertebrae. The comprehensive anatomo-neurochemical atlases of the spinal cord are invaluable for attaining such insight. While such atlases exist for some rodents and primates, none exist for rabbits. We have developed a spinal cord atlas for rabbits to bridge this gap. Utilizing various neurochemical markers-including antibodies to NeuN, calbindin 28 kDa, parvalbumin, choline acetyltransferase, nitric oxide synthase, and non-phosphorylated heavy-chain neurofilaments (SMI-32 antibody)-we present the visualization of diverse spinal neuronal populations, various spinal cord metrics, stereotaxic maps of transverse slices for each spinal segment, and a spatial map detailing the intricate relationship between the spinal cord and the vertebrae across its entire length.

The role of clivus and atlanto-occipital lateral mass height in basilar invagination with or without atlas occipitalization.

Basilar invagination (BI) is a common deformity. This study aimed to quantitatively evaluate the height of clivus and atlanto-occipital lateral mass (LM) in patients with BI with or without atlas occipitalization (AOZ). We evaluated 166 images of patients with BI and of controls. Seventy-one participants were control subjects (group A), 68 had BI with AOZ (group B), and 27 had BI without AOZ (group C). Parameters were defined and measured for comparisons across the groups. Multiple linear regression analysis was used to test the relationship between Chamberlain's line violation (CLV) and the clivus height ratio or atlanto-occipital LM height. Based on the degree of AOZ, the lateral masses in group B were classified as follows: segmentation, incomplete AOZ, complete AOZ. From groups A to C, there was a decreasing trend in the clivus height and clivus height ratio. There was a linear negative correlation between the clivus height ratio and CLV in the three groups. Generally, the atlanto-occipital LM height followed the order of group B < group C < group A. The atlanto-occipital LM height was included only in the equations of groups B. There were no cases of atlantoaxial dislocation (AAD) in group C. There was a decreasing trend in LM height from the segmentation type to the complete AOZ type in group B. BI can be divided into three categories: AOZ causes LM height loss; Clivus height loss; Both clivus and LM height loss. The clivus height ratio was found to play a decisive role in both controls and BI group, while the atlanto-occipital LM height loss caused by AOZ could be a secondary factor in patients with BI and AOZ. AOZ may be a necessary factor for AAD in patients with congenital BI. The degree of AOZ is associated with LM height in group B.

Deciphering deep-sea chemosynthetic symbiosis by single-nucleus RNA-sequencing.

Bathymodioline mussels dominate deep-sea methane seep and hydrothermal vent habitats and obtain nutrients and energy primarily through chemosynthetic endosymbiotic bacteria in the bacteriocytes of their gill. However, the molecular mechanisms that orchestrate mussel host-symbiont interactions remain unclear. Here, we constructed a comprehensive cell atlas of the gill in the mussel Gigantidas platifrons from the South China Sea methane seeps (1100 m depth) using single-nucleus RNA-sequencing (snRNA-seq) and whole-mount in situ hybridisation. We identified 13 types of cells, including three previously unknown ones, and uncovered unknown tissue heterogeneity. Every cell type has a designated function in supporting the gill's structure and function, creating an optimal environment for chemosynthesis, and effectively acquiring nutrients from the endosymbiotic bacteria. Analysis of snRNA-seq of in situ transplanted mussels clearly showed the shifts in cell state in response to environmental oscillations. Our findings provide insight into the principles of host-symbiont interaction and the bivalves' environmental adaption mechanisms.

Remote sensing estimates of global sea surface nitrate: Methodology and validation.

Information about sea surface nitrate (SSN) concentrations is crucial for estimating oceanic new productivity and for carbon cycle studies. Due to the absence of optical properties in SSN and the intricate relationships with environmental factors affecting spatiotemporal dynamics, developing a more representative and widely applicable remote sensing inversion algorithm for SSN is challenging. Most methods for the remote estimation of SSN are based on data-driven neural networks or deep learning and lack mechanistic descriptions. Since fitting functions between the SSN and sea surface temperature (SST), mixed layer depth (MLD), and chlorophyll (Chl) content have been established for the open ocean, it is important to include the remote sensing indicator photosynthetically active radiation (PAR), which is critical in nitrate biogeochemical processes. In this study, we employed an algorithm for estimating the monthly average SSN on a global 1° by 1° resolution grid; this algorithm relies on the empirical relationship between the World Ocean Atlas 2018 (WOA18) monthly interpolated climatology of nitrate in each 1°â€¯× 1° grid and the estimated monthly SST and PAR datasets from Moderate Resolution Imaging Spectroradiometer (MODIS) and MLD from the Hybrid Coordinate Ocean Model (HYCOM). These results indicated that PAR potentially affects SSN. Furthermore, validation of the SSN model with measured nitrate data from different months and locations for the years 2018-2023 yielded a high prediction accuracy (N = 12,846, R2 = 0.93, root mean square difference (RMSE) = 3.12 µmol/L, and mean absolute error (MAE) = 2.22 µmol/L). Further independent validation and sensitivity tests demonstrated the validity of the algorithm for retrieving SSN.

COA6 promotes the oncogenesis and progression of breast cancer by oxidative phosphorylation pathway.

Mitochondrial oxidative phosphorylation (OXPHOS) has long been considered the primary energy source in breast cancer cells. Cytochrome c oxidase assembly factor 6 (COA6), which functions as a metal chaperone to transport copper to complex Ⅳ during the OXPHOS process, plays a crucial role in the carcinogenesis of lung adenocarcinoma. Nevertheless, its specific function in breast cancer is undefined. The present investigation aimed to clarify COA6's expression profile and regulatory functions in breast cancer, as well as to unveil its underlying mechanisms. Initially, our findings revealed a significant upregulation of COA6 in breast cancer, as evidenced by an analysis of the TCGA database and tissue microarrays. This upregulation correlated with tumor size and histological grade. Additionally, survival analysis revealed that elevated COA6 amounts were correlated with decreased overall survival (OS) in breast cancer. To delve deeper into the functions of COA6, both COA6-overexpressing and COA6-knockdown breast cancer cell models were established. These experiments demonstrated COA6 is pivotal in regulating cell proliferation, apoptosis, migration, and invasion, thereby promoting cancer progression in vitro. Notably, functional enrichment analysis indicated COA6 might be involved in breast cancer progression by modulating oxidative phosphorylation (OXPHOS). Collectively, this study reveals an overt tumorigenic role for COA6 in breast cancer and sheds light on its potential mechanisms, offering valuable therapeutic targets for breast cancer therapy.

Mapping stroke outcomes: A review of brain connectivity atlases.

The brain connectivity-based atlas is a promising tool for understanding neural communication pathways in the brain, gaining relevance in predicting personalized outcomes for various brain pathologies. This critical review examines the robustness of the brain connectivity-based atlas for predicting post-stroke outcomes. A comprehensive literature search was conducted from 2012 to May 2023 across PubMed, Scopus, EMBASE, EBSCOhost, and Medline databases. Twenty-one studies were screened, and through analysis of these studies, we identified 18 brain connectivity atlases employed by the studies for lesion analysis in their predictions. The brain atlases were assessed for study cohorts, connectivity measures, identified brain regions, atlas applications, and limitations. Based on the analysis of these studies, most atlases were based on diffusion tensor imaging and resting-state functional magnetic resonance imaging (MRI). Studies predicting post-stroke functional outcomes relied on the atlases for multivariate lesion analysis and region of interest identification, often employing atlases derived from young, healthy populations. Current brain connectivity-based atlases for stroke applications lack standardized methods to define and map brain connectivity across atlases and cover sensorimotor functional connectivity to a limited extent. In conclusion, this review highlights the need to develop more comprehensive, robust, and adaptable brain connectivity-based atlases specifically tailored to post-stroke populations.

Designing the Australian Cancer Atlas: visualizing geostatistical model uncertainty for multiple audiences.

OBJECTIVE: The Australian Cancer Atlas (ACA) aims to provide small-area estimates of cancer incidence and survival in Australia to help identify and address geographical health disparities. We report on the 21-month user-centered design study to visualize the data, in particular, the visualization of the estimate uncertainty for multiple audiences. MATERIALS AND METHODS: The preliminary phases included a scoping study, literature review, and target audience focus groups. Several methods were used to reach the wide target audience. The design and development stage included digital prototyping in parallel with Bayesian model development. Feedback was sought from multiple workshops, audience focus groups, and regular meetings throughout with an expert external advisory group. RESULTS: The initial scoping identified 4 target audience groups: the general public, researchers, health practitioners, and policy makers. These target groups were consulted throughout the project to ensure the developed model and uncertainty visualizations were effective for communication. In this paper, we detail ACA features and design iterations, including the 3 complementary ways in which uncertainty is communicated: the wave plot, the v-plot, and color transparency. DISCUSSION: We reflect on the methods, design iterations, decision-making process, and document lessons learned for future atlases. CONCLUSION: The ACA has been hugely successful since launching in 2018. It has received over 62 000 individual users from over 100 countries and across all target audiences. It has been replicated in other countries and the second version of the ACA was launched in May 2024. This paper provides rich documentation for future projects.

Atlas-guided brain projection tracts: From regions of interest to tractography 3D rendering.

The use of diffusion tensor imaging (DTI) has seen significant development over the last two decades, in particular with the development of the tractography of association tracts for preoperative planning of surgery. However, projection tracts are difficult to differentiate from one another and tractography studies have failed to reconstruct these ascending/descending pathways from/to the spinal cord. The present study proposes an atlas of regions of interest (ROIs) designed specifically for projection tracts tractography. Forty-nine healthy subjects were included in this prospective study. Brain DTI was acquired using the same 3 T MRI scanner, with 32 diffusion directions. Distortions were corrected using the FSL software package. ROIs were drawn using the anterior commissure (AC)-posterior commissure (PC) line on the following landmarks: the pyramid for the corticospinal tract, the medio-caudal part of the red nucleus for the rubrospinal tract, the pontine reticular nucleus for corticoreticular tract, the superior and inferior cerebellar peduncles for, respectively, the anterior and posterior spinocerebellar tract, the gracilis and cuneatus nucleus for the dorsal columns, and the ventro-posterolateral nucleus for the spinothalamic tract. Fiber tracking was performed using a deterministic algorithm using DSI Studio software. ROI coordinates, according to AC-PC line, were given for each tract. Tractography was obtained for each tract, allowing tridimensional rendering and comparison of tracking metrics between tracts. The present study reports the accurate design of specific ROIs for tractography of each projection tract. This could be a useful tool in order to differentiate projection tracts at the spinal cord level.

ITIH1 suppresses carcinogenesis in renal cell carcinoma through regulation of the NF­κB signaling pathway.

Renal cell carcinoma (RCC) is a common malignancy of the urinary system. Although traditional therapies, such as surgery assisted with chemotherapy have improved the quality of life and survival time of patients with RCC, patients with metastasis or recurrence benefit little from such therapies. At present, little is known about the underlying mechanisms of RCC, rendering treatment selection and implementation challenging. Therefore, investigating the cause and underlying mechanisms of RCC remain of importance to explore potential new avenues for its treatment. Inter-α-trypsin inhibitor heavy chain 1 (ITIH1) is an inflammation-associated gene reported to suppress the progression of liver cancer. However, its role in RCC remains poorly understood. Therefore, the present study aimed to investigate the role and mechanism of ITIH1 in RCC. Based on data obtained from The Cancer Genome Atlas database, ITIH1 expression was demonstrated to be significantly higher in tumor tissues compared with normal tissues, which was in turn negatively associated with the survival of patients with RCC. However, in RCC cells, ITIH1 was shown to be expressed at significantly lower levels compared with those in HK-2 cells. The discrepancy between tissues and cell lines might be due to the different environment of cell growth. ITIH1 knockdown in RCC cells significantly increased cell proliferation and invasion whilst significantly decreasing the apoptosis rate, compared with those in control cells (without ITIH1 knockdown). By contrast, overexpression of ITIH1 significantly inhibited cell proliferation and invasion in RCC cells. In terms of western blotting results, the phosphorylation levels of NF-κB were significantly increased following ITIH1 knockdown. The protein expression level of IκB significantly decreased whereas that of IKK, Cyclin D1, proliferating cell nuclear antigen and α-smooth muscle actin were significantly increased in ITIH1-knockdown cells, compared with those in the control cells (without ITIH1 knockdown). This suggests that the NF-κB pathway may be activated after ITIH1 knockdown. Following treatment with the NF-κB pathway inhibitor JSH-23 in combination with ITIH1 knockdown, RCC cell proliferation and invasion were significantly reduced compared with those after ITIH1 knockdown alone. In summary, results from the present study suggest that ITIH1 can serve an inhibitory role in the progression of RCC, which could potentially be inhibited through the NF-κB signaling pathway.

Immune landscape of hepatocellular carcinoma: The central role of TP53-inducible glycolysis and apoptosis regulator.

Objective: This study aims to address the substantive issue of lacking reliable prognostic biomarkers in hepatocellular carcinoma (HCC) by investigating the relationship between TP53-inducible glycolysis and apoptosis regulator (TIGAR) and HCC prognosis using The Cancer Genome Atlas database. Methods: (1) Integrated statistical analyses, including logistic regression, Wilcoxon signed-rank test, and Kruskal-Wallis test, were conducted to explore the association between TIGAR expression and clinical-pathological features of HCC. (2) The Kaplan-Meier method combined with univariate and multivariate Cox regression models underscored TIGAR as a prognostic factor in HCC. (3) Gene set enrichment analysis (GSEA) revealed key pathways associated with TIGAR, while single-sample gene set enrichment analysis (ssGSEA) determined its relevance to cancer immune infiltration. Results: (1) Elevated TIGAR expression was significantly correlated with decreased survival outcomes in HCC patients. (2) GSEA highlighted the significant link between TIGAR and humoral immunity. (3) ssGSEA revealed a positive correlation between TIGAR expression and infiltration of Th1 and Th2 cells and a negative correlation with Th17 cell infiltration. Conclusion: TIGAR, as a potential prognostic biomarker for HCC, holds significant value in immune infiltration. Understanding the role of TIGAR could contribute to improved prognostic predictions and personalized treatment strategies for HCC patients.

Histology Atlas of the Developing Mouse Respiratory System From Prenatal Day 9.0 Through Postnatal Day 30.

Respiratory diseases are one of the leading causes of death and disability around the world. Mice are commonly used as models of human respiratory disease. Phenotypic analysis of mice with spontaneous, congenital, inherited, or treatment-related respiratory tract abnormalities requires investigators to discriminate normal anatomic features of the respiratory system from those that have been altered by disease. Many publications describe individual aspects of normal respiratory tract development, primarily focusing on morphogenesis of the trachea and lung. However, a single reference providing detailed low- and high-magnification, high-resolution images of routine hematoxylin and eosin (H&E)-stained sections depicting all major structures of the entire developing murine respiratory system does not exist. The purpose of this atlas is to correct this deficiency by establishing one concise reference of high-resolution color photomicrographs from whole-slide scans of H&E-stained tissue sections. The atlas has detailed descriptions and well-annotated images of the developing mouse upper and lower respiratory tracts emphasizing embryonic days (E) 9.0 to 18.5 and major early postnatal events. The selected images illustrate the main structures and events at key developmental stages and thus should help investigators both confirm the chronological age of mouse embryos and distinguish normal morphology as well as structural (cellular and organ) abnormalities.

Development and Validation of a Carbohydrate Metabolism-Related Model for Predicting Prognosis and Immune Landscape in Hepatocellular Carcinoma Patients.

OBJECTIVE: The activities and products of carbohydrate metabolism are involved in key processes of cancer. However, its relationship with hepatocellular carcinoma (HCC) is unclear. METHODS: The cancer genome atlas (TCGA)-HCC and ICGC-LIRI-JP datasets were acquired via public databases. Differentially expressed genes (DEGs) between HCC and control samples in the TCGA-HCC dataset were identified and overlapped with 355 carbohydrate metabolism-related genes (CRGs) to obtain differentially expressed CRGs (DE-CRGs). Then, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were applied to identify risk model genes, and HCC samples were divided into high/low-risk groups according to the median risk score. Next, gene set enrichment analysis (GSEA) was performed on the risk model genes. The sensitivity of the risk model to immunotherapy and chemotherapy was also explored. RESULTS: A total of 8 risk model genes, namely, G6PD, PFKFB4, ACAT1, ALDH2, ACYP1, OGDHL, ACADS, and TKTL1, were identified. Moreover, the risk score, cancer status, age, and pathologic T stage were strongly associated with the prognosis of HCC patients. Both the stromal score and immune score had significant negative/positive correlations with the risk score, reflecting the important role of the risk model in immunotherapy sensitivity. Furthermore, the stromal and immune scores had significant negative/positive correlations with risk scores, reflecting the important role of the risk model in immunotherapy sensitivity. Eventually, we found that high-/low-risk patients were more sensitive to 102 drugs, suggesting that the risk model exhibited sensitivity to chemotherapy drugs. The results of the experiments in HCC tissue samples validated the expression of the risk model genes. CONCLUSION: Through bioinformatic analysis, we constructed a carbohydrate metabolism-related risk model for HCC, contributing to the prognosis prediction and treatment of HCC patients.

Atlas of metastatic gastric cancer links ferroptosis to disease progression and immunotherapy response.

BACKGROUND & AIMS: Metastases from gastric adenocarcinoma (GAC) lead to high morbidity and mortality. Developing innovative and effective therapies requires a comprehensive understanding of the tumor and immune biology of advanced GAC. Yet, collecting matched specimens from advanced, treatment-naïve GAC patients poses a significant challenge, limiting the scope of current research, which has predominantly focused on localized tumors. This gap hinders a deeper insight into the metastatic dynamics of GAC. METHODS: We performed in-depth single-cell transcriptome and immune profiling on 68 paired, treatment-naïve, primary-metastatic tumors to delineate alterations in cancer cells and their tumor microenvironment (TME) during metastatic progression. To validate our observations, we conducted comprehensive functional studies both in vitro and in vivo, employing cell lines, multiple PDX and novel mouse models of GAC. RESULTS: Liver and peritoneal metastases exhibited distinct properties in cancer cells and dynamics of TME phenotypes, supporting the notion that cancer cells and their local TMEs co-evolve at metastatic sites. Our study also revealed differential activation of cancer meta-programs across metastases. We observed evasion of cancer cell ferroptosis via GPX4 upregulation during GAC progression. Conditional depletion of Gpx4 or pharmacological inhibition of ferroptosis resistance significantly attenuated tumor growth and metastatic progression. Additionally, ferroptosis-resensitizing treatments augmented the efficacy of CAR T-cell therapy. CONCLUSIONS: This study represents the largest single-cell dataset of metastatic GACs to date. High-resolution mapping of the molecular and cellular dynamics of GAC metastasis has revealed a rationale for targeting ferroptosis defense in combination with CAR T-cell therapy as a novel therapeutic strategy with potential immense clinical implications.

Predictive role of oxidative stress-related genes in colon cancer: a retrospective cohort study based on The Cancer Genome Atlas.

PURPOSE: This study aimed to elucidate the predictive role of an oxidative stress-related genes (OSRGs) model in colon cancer. MATERIALS AND METHODS: First, OSRGs that were differentially expressed between tumor and normal tissues were identified using The Cancer Genome Atlas (TCGA)-(Colorectal Adenocarcinoma) COAD dataset. Then, Lasso COX regression was performed to develop an optimal prognostic model patients were stratified into high- and low-risk groups based on the expression patterns of these genes. The model's validity was confirmed through Kaplan-Meier survival curves and receiver operating characteristic curve (ROC) analysis. Additionally, enrichment analyses were performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) to uncover underlying mechanisms. RESULTS: A totally of 115 differentially expressed OSRGs were identified within the TCGA cohort, with 17 significantly linked to overall survival. These 17 genes were used to formulate a prognostic model that differentiated patients into distinct risk groups, with the high-risk group demonstrating a notably inferior overall survival rate. The risk score, when integrated with clinical and pathological data, emerged as an independent prognostic indicator of colon cancer. Further analyses revealed that the disparity in prognostic outcomes between risk groups could be attributed to the reactive oxygen species pathway and the p53 signaling pathway. CONCLUSION: A new prediction model was established based on OSRGs. CYP19A1, NOL3 and UCN were found to be highly expressed in tumor tissues and substantial clinical predictive significance. These findings offer new insights into the role of oxidative stress in colon cancer.

Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks.

BACKGROUND: Cell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation atlas to TOO detection in low depth cfDNA samples. METHODS: We constructed a tumor-specific methylation atlas (TSMA) using whole-genome bisulfite sequencing (WGBS) data from five types of tumor tissues (breast, colorectal, gastric, liver and lung cancer) and paired white blood cells (WBC). TSMA was used with a non-negative least square matrix factorization (NNLS) deconvolution algorithm to identify the abundance of tumor tissue types in a WGBS sample. We showed that TSMA worked well with tumor tissue but struggled with cfDNA samples due to the overwhelming amount of WBC-derived DNA. To construct a model for TOO, we adopted the multi-modal strategy and used as inputs the combination of deconvolution scores from TSMA with other features of cfDNA. RESULTS: Our final model comprised of a graph convolutional neural network using deconvolution scores and genome-wide methylation density features, which achieved an accuracy of 69% in a held-out validation dataset of 239 low-depth cfDNA samples. CONCLUSIONS: In conclusion, we have demonstrated that our TSMA in combination with other cfDNA features can improve TOO detection in low-depth cfDNA samples.

Identification and validation of a novel 17 coagulation-related genes signature for predicting prognostic risk in colorectal cancer.

Background: Patients with colorectal cancer commonly experience disturbances in coagulation homeostasis. Activation of the coagulation system contributes to cancer-associated thrombosis as the second risk factor for death in cancer patients. This study intended to discover coagulation-related genes and construct a risk model for colorectal cancer patients' prognosis. Methods: Coagulation-related genes were identified by searching coagulation-related pathways in the Molecular Signatures Database. Transcriptomic data and clinical data were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus datasets. Univariate Cox and backward stepwise regression were utilized to identify prognosis-related genes and construct a predictive risk model for the training cohort. Next, survival analysis determines the risk model's predictive power, correlation with clinicopathological characteristics, and nomogram. Additionally, we characterized the variances in immune cell infiltration, somatic mutations, immune checkpoint molecules, biological functions, and drug sensitivity between the high- and low-score patients. Result: Eight hundred forty-five genes were obtained by searching the theme term "coagulation" after de-duplication. After univariate regression analysis, 69 genes correlated with prognosis were obtained from the Cancer Genome Atlas dataset. A signature consisting of 17 coagulation-related genes was established through backward stepwise regression. The Kaplan-Meier curve indicated a worse prognosis for high-score patients. Time-dependent receiver operating characteristic curve analysis demonstrated high accuracy in predicting overall survival. Further, the results were validated by two independent datasets (GSE39582 and GSE17536). Combined with clinicopathological characteristics, the risk model was proven to be an independent prognostic factor to predict poor pathological status and worse prognosis. Furthermore, high-score patients had significantly higher stromal cell infiltration. Low-score patients were associated with high infiltration of resting memory CD4+ T cells, activated CD4+ T cells, and T follicular helper cells. The low-score patients exhibited increased expression of immune checkpoint genes, and this might be relevant to their better prognosis. High-score patients exhibited lower IC50 values of Paclitaxel, Rapamycin, Temozolomide, Cyclophosphamide, etc. The differential signaling pathways mainly involve the calcium signaling pathway and the neuroactive ligand-receptor interaction. Lastly, a nomogram was constructed and showed a good prediction. Conclusion: The prognostic signature of 17 coagulation-related genes had significant prognostic value for colorectal cancer patients. We expect to improve treatment modalities and benefit more patients through research on molecular features.

Analysis of methylation-driven genes for predicting the prognosis of patients with oral squamous cell carcinoma.

Background: Oral squamous cell carcinoma (OSCC) is a highly aggressive malignancy that is characterized by early distant metastasis and poor prognosis. DNA methylation plays an important role in the etiology and pathogenesis of OSCC. This study aimed to identify methylation-driven genes through bioinformatics analysis as potential biomarkers for early diagnosis and prognostic assessment of OSCC. Methods: Methylation data, RNA sequencing (RNA-seq) data and clinical prognosis information of OSCC patients were retrieved from The Cancer Genome Atlas (TCGA) database. The R packages MethylMix were employed to analyze the correlation between methylation status and corresponding gene expression in tumor and normal tissues to obtain methylation-driven genes. Univariate Cox regression analysis was developed to further screen methylation-driven genes associated with the prognosis of OSCC patients. Subsequently, multivariate Cox regression analysis was utilized to construct a linear prognostic risk prediction model. Furthermore, a combined survival analysis integrating methylation and gene expression was performed to investigate the prognostic value. Results: A total of 374 differentially expressed methylation-driven genes were identified. Seven methylation-driven genes (BST2, KRT15, ZNF134, NT5E, GSTA7P, NAPRT, and GOLPH3L) were found to be significantly associated with patient prognosis. Additionally, four methylation-driven genes (BST2, KRT15, ZNF134 and NAPRT) were used to construct a linear prognostic risk prediction model for OSCC patients. Furthermore, a combined Kaplan-Meier survival analysis revealed that three methylation-driven genes (ZKSCAN7, MFF, ZNF134) alone can be used as independent prognostic markers or drug targets. Conclusions: Our findings facilitate a better understanding of molecular mechanisms of OSCC and provide potential biomarkers of early diagnosis, precision treatment and prognosis evaluation.

Identification of a prognostic DNA repair gene signature in esophageal cancer.

Background: DNA repair plays a crucial role in the development and progression of different types of cancers. Nevertheless, little is known about the role of DNA repair-related genes (DRRGs) in esophageal cancer (EC). The present study aimed to identify a novel DRRGs prognostic signature in EC. Methods: Gene set enrichment analysis (GSEA) was performed to screen 150 genes related to DNA repair, which is the most important enrichment gene set in EC. Univariate and multivariate Cox regression analyses were used to screen DRRGs closely associated with prognosis. The difference in the expression of hub DRRGs between tumor and normal tissues was analyzed. Combined with clinical indicators (including age, gender, and tumor stage), we evaluated whether the 4-DRRGs signature was an independent prognostic factor. In addition, we evaluated the prediction accuracy using a receiver operating characteristic (ROC) curve and visualized the model's performance via a nomogram. Results: Four-DRRGs (NT5C3A, TAF9, BCAP31, and NUDT21) were selected by Cox regression analysis to establish a prognostic signature to effectively classify patients into high- and low-risk groups. The area under the curve (AUC) of the time-dependent ROC of the prognostic signature for 1- and 3-year was 0.769 and 0.720, respectively. Compared with other clinical characteristics, the risk score showed a robust ability to predict the prognosis in EC, especially in the early stage of EC. Furthermore, we constructed a nomogram to interpret the clinical application of the 4-DRRGs signature. Conclusions: In conclusion, we identified a prognostic signature based on the DRRGs for patients with EC, which can contribute independent value in identifying clinical outcomes that complement the TNM system in EC.

ATLAS: Mapping ATtention's Location And Size to probe five modes of serial and parallel search.

Conventional visual search tasks do not address attention directly and their core manipulation of 'set size' - the number of displayed items - introduces stimulus confounds that hinder interpretation. However, alternative approaches have not been widely adopted, perhaps reflecting their complexity, assumptions, or indirect attention-sampling. Here, a new procedure, the ATtention Location And Size ('ATLAS') task used probe displays to track attention's location, breadth, and guidance during search. Though most probe displays comprised six items, participants reported only the single item they judged themselves to have perceived most clearly - indexing the attention 'peak'. By sampling peaks across variable 'choice sets', the size and position of the attention window during search was profiled. These indices appeared to distinguish narrow- from broad attention, signalled attention to pairs of items where it arose and tracked evolving attention-guidance over time. ATLAS is designed to discriminate five key search modes: serial-unguided, sequential-guided, unguided attention to 'clumps' with local guidance, and broad parallel-attention with or without guidance. This initial investigation used only an example set of highly regular stimuli, but its broader potential should be investigated.