Imaging segmentation mechanism for rectal tumors using improved U-Net.

OBJECTIVE: In radiation therapy, cancerous region segmentation in magnetic resonance images (MRI) is a critical step. For rectal cancer, the automatic segmentation of rectal tumors from an MRI is a great challenge. There are two main shortcomings in existing deep learning-based methods that lead to incorrect segmentation: 1) there are many organs surrounding the rectum, and the shape of some organs is similar to that of rectal tumors; 2) high-level features extracted by conventional neural networks often do not contain enough high-resolution information. Therefore, an improved U-Net segmentation network based on attention mechanisms is proposed to replace the traditional U-Net network. METHODS: The overall framework of the proposed method is based on traditional U-Net. A ResNeSt module was added to extract the overall features, and a shape module was added after the encoder layer. We then combined the outputs of the shape module and the decoder to obtain the results. Moreover, the model used different types of attention mechanisms, so that the network learned information to improve segmentation accuracy. RESULTS: We validated the effectiveness of the proposed method using 3773 2D MRI datasets from 304 patients. The results showed that the proposed method achieved 0.987, 0.946, 0.897, and 0.899 for Dice, MPA, MioU, and FWIoU, respectively; these values are significantly better than those of other existing methods. CONCLUSION: Due to time savings, the proposed method can help radiologists segment rectal tumors effectively and enable them to focus on patients whose cancerous regions are difficult for the network to segment. SIGNIFICANCE: The proposed method can help doctors segment rectal tumors, thereby ensuring good diagnostic quality and accuracy.

A medical image segmentation method for rectal tumors based on multi-scale feature retention and multiple attention mechanisms.

BACKGROUND: With the continuous development of deep learning algorithms in the field of medical images, models for medical image processing based on convolutional neural networks have made great progress. Since medical images of rectal tumors are characterized by specific morphological features and complex edges that differ from natural images, achieving good segmentation results often requires a higher level of enrichment through the utilization of semantic features. PURPOSE: The efficiency of feature extraction and utilization has been improved to some extent through enhanced hardware arithmetic and deeper networks in most models. However, problems still exist with detail loss and difficulty in feature extraction, arising from the extraction of high-level semantic features in deep networks. METHODS: In this work, a novel medical image segmentation model has been proposed for Magnetic Resonance Imaging (MRI) image segmentation of rectal tumors. The model constructs a backbone architecture based on the idea of jump-connected feature fusion and solves the problems of detail feature loss and low segmentation accuracy using three novel modules: Multi-scale Feature Retention (MFR), Multi-branch Cross-channel Attention (MCA), and Coordinate Attention (CA). RESULTS: Compared with existing methods, our proposed model is able to segment the tumor region more effectively, achieving 97.4% and 94.9% in Dice and mIoU metrics, respectively, exhibiting excellent segmentation performance and computational speed. CONCLUSIONS: Our proposed model has improved the accuracy of both lesion region and tumor edge segmentation. In particular, the determination of the lesion region can help doctors identify the tumor location in clinical diagnosis, and the accurate segmentation of the tumor edge can assist doctors in judging the necessity and feasibility of surgery.

Molecular classification and tumor microenvironment characteristics in pheochromocytomas.

Pheochromocytomas (PCCs) are rare neuroendocrine tumors that originate from chromaffin cells in the adrenal gland. However, the cellular molecular characteristics and immune microenvironment of PCCs are incompletely understood. Here, we performed single-cell RNA sequencing (scRNA-seq) on 16 tissues from 4 sporadic unclassified PCC patients and 1 hereditary PCC patient with Von Hippel-Lindau (VHL) syndrome. We found that intra-tumoral heterogeneity was less extensive than the inter-individual heterogeneity of PCCs. Further, the unclassified PCC patients were divided into two types, metabolism-type (marked by NDUFA4L2 and COX4I2) and kinase-type (marked by RET and PNMT), validated by immunohistochemical staining. Trajectory analysis of tumor evolution revealed that metabolism-type PCC cells display phenotype of consistently active metabolism and increased metastasis potential, while kinase-type PCC cells showed decreased epinephrine synthesis and neuron-like phenotypes. Cell-cell communication analysis showed activation of the annexin pathway and a strong inflammation reaction in metabolism-type PCCs and activation of FGF signaling in the kinase-type PCC. Although multispectral immunofluorescence staining showed a lack of CD8+ T cell infiltration in both metabolism-type and kinase-type PCCs, only the kinase-type PCC exhibited downregulation of HLA-I molecules that possibly regulated by RET, suggesting the potential of combined therapy with kinase inhibitors and immunotherapy for kinase-type PCCs; in contrast, the application of immunotherapy to metabolism-type PCCs (with antigen presentation ability) is likely unsuitable. Our study presents a single-cell transcriptomics-based molecular classification and microenvironment characterization of PCCs, providing clues for potential therapeutic strategies to treat PCCs.

MET fusions and splicing variants is a strong adverse prognostic factor in astrocytoma, isocitrate dehydrogenase mutant.

Liu et al. describe the adverse prognostic role of MET fusions and splicing variants in astrocytoma, isocitrate dehydrogenase mutant. On this basis, MET fusions and splicing variants was suggested to be a biomarker for the diagnosis of high-grade astrocytoma, isocitrate dehydrogenase mutant.

circRNADisease v2.0: an updated resource for high-quality experimentally supported circRNA-disease associations.

circRNADisease v2.0 is an enhanced and reliable database that offers experimentally verified relationships between circular RNAs (circRNAs) and various diseases. It is accessible at http://cgga.org.cn/circRNADisease/ or http://cgga.org.cn:9091/circRNADisease/. The database currently includes 6998 circRNA-disease entries across multiple species, representing a remarkable 19.77-fold increase compared to the previous version. This expansion consists of a substantial rise in the number of circRNAs (from 330 to 4246), types of diseases (from 48 to 330) and covered species (from human only to 12 species). Furthermore, a new section has been introduced in the database, which collects information on circRNA-associated factors (genes, proteins and microRNAs), molecular mechanisms (molecular pathways), biological functions (proliferation, migration, invasion, etc.), tumor and/or cell line and/or patient-derived xenograft (PDX) details, and prognostic evidence in diseases. In addition, we identified 7 159 865 relationships between mutations and circRNAs among 30 TCGA cancer types. Due to notable enhancements and extensive data expansions, the circRNADisease 2.0 database has become an invaluable asset for both clinical practice and fundamental research. It enables researchers to develop a more comprehensive understanding of how circRNAs impact complex diseases.

Low-Temperature Vapor-Phase Growth of 2D Metal Chalcogenides.

2D metal chalcogenides (MCs) have garnered significant attention from both scientific and industrial communities due to their potential in developing next-generation functional devices. Vapor-phase deposition methods have proven highly effective in fabricating high-quality 2D MCs. Nevertheless, the conventionally high thermal budgets required for synthesizing 2D MCs pose limitations, particularly in the integration of multiple components and in specialized applications (such as flexible electronics). To overcome these challenges, it is desirable to reduce the thermal energy requirements, thus facilitating the growth of various 2D MCs at lower temperatures. Numerous endeavors have been undertaken to develop low-temperature vapor-phase growth techniques for 2D MCs, and this review aims to provide an overview of the latest advances in low-temperature vapor-phase growth of 2D MCs. Initially, the review highlights the latest progress in achieving high-quality 2D MCs through various low-temperature vapor-phase techniques, including chemical vapor deposition (CVD), metal-organic CVD, plasma-enhanced CVD, atomic layer deposition (ALD), etc. The strengths and current limitations of these methods are also evaluated. Subsequently, the review consolidates the diverse applications of 2D MCs grown at low temperatures, covering fields such as electronics, optoelectronics, flexible devices, and catalysis. Finally, current challenges and future research directions are briefly discussed, considering the most recent progress in the field.

In Situ Defect Engineering of Controllable Carrier Types in WSe2 for Homomaterial Inverters and Self-Powered Photodetectors.

WSe2 has a high mobility of electrons and holes, which is an ideal choice as active channels of electronics in extensive fields. However, carrier-type tunability of WSe2 still has enormous challenges, which are essential to overcome for practical applications. In this work, the direct growth of n-doped few-layer WSe2 is realized via in situ defect engineering. The n-doping of WSe2 is attributed to Se vacancies induced by the H2 flow purged in the cooling process. The electrical measurements based on field effect transistors demonstrate that the carrier type of WSe2 synthesized is successfully transferred from the conventional p-type to the rarely reported n-type. The electron carrier concentration is efficiently modulated by the concentration of H2 during the cooling process. Furthermore, homomaterial inverters and self-powered photodetectors are fabricated based on the doping-type-tunable WSe2. This work reveals a significant way to realize the controllable carrier type of two-dimensional (2D) materials, exhibiting great potential in future 2D electronics engineering.

Mechanistic study on the side arm effect in a palladium/Xu-Phos-catalyzed enantioselective alkoxyalkenylation of γ-hydroxyalkenes.

Recently, the asymmetric bifunctionalization of alkenes has received much attention. However, the development of enantioselective alkoxyalkenylation has posed a considerable challenge and has lagged largely behind. Herein, we report a new palladium-catalyzed enantioselective alkoxyalkenylation reaction, using a range of primary, secondary, and tertiary γ-hydroxy-alkenes with alkenyl halides. By employing newly identified Xu-Phos (Xu8 and Xu9) with a suitable side-arm adjacent to the PCy2 motif, a series of allyl-substituted tetrahydrofurans were obtained in good yields with up to 95% ee. Besides (E)-alkenyl halides, (Z)-alkenyl halide was also examined and provided the corresponding (Z)-product as a single diastereomer, supporting a stereospecific oxidative addition and reductive elimination step. Moreover, deuterium labeling and VCD experiments were employed to determine a cis-oxypalladation mechanism. DFT calculations helped us gain deeper insight into the side-arm effect on the chiral ligand. Finally, the practicability of this method is further demonstrated through a gram-scale synthesis and versatile transformations of the products.

RTAU-Net: A novel 3D rectal tumor segmentation model based on dual path fusion and attentional guidance.

BACKGROUND AND OBJECTIVE: According to the Global Cancer Statistics 2020, colorectal cancer has the third-highest diagnosis rate (10.0 %) and the second-highest mortality rate (9.4 %) among the 36 types. Rectal cancer accounts for a large proportion of colorectal cancer. The size and shape of the rectal tumor can directly affect the diagnosis and treatment by doctors. The existing rectal tumor segmentation methods are based on two-dimensional slices, which cannot analyze a patient's tumor as a whole and lose the correlation between slices of MRI image, so the practical application value is not high. METHODS: In this paper, a three-dimensional rectal tumor segmentation model is proposed. Firstly, image preprocessing is performed to reduce the effect caused by the unbalanced proportion of background region and target region, and improve the quality of the image. Secondly, a dual-path fusion network is designed to extract both global features and local detail features of rectal tumors. The network includes two encoders, a residual encoder for enhancing the spatial detail information and feature representation of the tumor and a transformer encoder for extracting global contour information of the tumor. In the decoding stage, we merge the information extracted from the dual paths and decode them. In addition, for the problem of the complex morphology and different sizes of rectal tumors, a multi-scale fusion channel attention mechanism is designed, which can capture important contextual information of different scales. Finally, visualize the 3D rectal tumor segmentation results. RESULTS: The RTAU-Net is evaluated on the data set provided by Shanxi Provincial Cancer Hospital and Xinhua Hospital. The experimental results showed that the Dice of tumor segmentation reached 0.7978 and 0.6792, respectively, which improved by 2.78 % and 7.02 % compared with suboptimal model. CONCLUSIONS: Although the morphology of rectal tumors varies, RTAU-Net can precisely localize rectal tumors and learn the contour and details of tumors, which can relieve physicians' workload and improve diagnostic accuracy.

Decision system for extent of resection in WHO grade 3 gliomas: a Chinese Glioma Genome Atlas database analysis.

BACKGROUND: Extensive surgical resection has been found to be associated with longer survival in patients with gliomas, but the interactive prognostic value of molecular pathology of the surgical resection is unclear. This study evaluated the impact of molecular pathology and clinical characteristics on the surgical benefit in WHO grade 3 IDH-mutant gliomas. METHODS: Clinical and pathological information of 246 patients with WHO grade 3 IDH-mutant gliomas were collected from the Chinese Glioma Genome Atlas database (2006-2020). The role of the extent of resection on overall survival, stratified by molecular pathology and clinical characteristics, was investigated. We then assessed prognostic factors using a univariate log-rank test and multivariate Cox proportional hazards model in the subgroups. RESULTS: The extent of resection was an independent prognostic factor in the entire cohort, even when adjusted for molecular pathology. Gross total resection was found to be associated with longer survival in all patients and in the astrocytoma group but not in the oligodendroglioma group. Compared with subtotal resections, gross total resections resulted in a longer survival time for astrocytoma patients aged ≤ 45 years. However, there was no survival benefit from total resection in patients with astrocytoma aged > 45 years. CONCLUSIONS: Extensive resection benefits only a proportion of patients with WHO grade 3 IDH-mutant gliomas. Younger patients with astrocytomas had survival benefits from extensive resection. In addition to clinical characteristics (especially age), molecular pathology impacted prognosis in patients with gliomas. Our findings provide guiding information to neurosurgeons while planning surgeries.

Preliminary Study of Whole-Genome Bisulfite Sequencing and Transcriptome Sequencing in VHL Disease-Associated ccRCC.

BACKGROUND: Von Hippel-Lindau (VHL) disease is an autosomal dominant hereditary tumor syndrome with an incidence of approximately 1/36,000. VHL disease-associated clear cell renal cell carcinoma (ccRCC) is the most common congenital RCC. Although recent advances in treating RCC have improved the long-term prognosis of patients with VHL disease, kidney cancer is still the leading cause of death in these patients. Therefore, finding new targets for diagnosing and treating VHL disease-associated ccRCC is still essential. METHODS: In this study, we collected matched tumor tissues and normal samples from 25 patients with VHL disease-associated ccRCC, diagnosed and surgically treated in the Department of Urology, Peking University First Hospital. After screening, we performed whole genome bisulfite sequencing (WGBS) on 23 pairs of tissues and RNA-seq on 6 pairs of tissues. And we also compared the VHL disease-associated ccRCC transcriptome data with the sporadic ccRCC transcriptome data from the The Cancer Genome Atlas (TCGA) public database RESULTS: We found that the methylation level of VHL disease-associated ccRCC tumor tissues was significantly lower than that of normal tissues. The tumor tissues showed a difference in the copy number of 3p loss and 5q and 7q gain compared with normal tissues. We integrated RNA-seq and WGBS data to reveal methylation candidate genes associated with VHL disease-associated ccRCC; our results showed 124 hypermethylated and downregulated genes, and 245 hypomethylated and upregulated genes. By comparing the VHL disease-associated ccRCC transcriptome data with the sporadic ccRCC transcriptome data from the TCGA public database, we found that the major pathways of differential gene enrichment differed between them. CONCLUSIONS: Our study mapped the multiomics of copy number variation, methylation and mRNA level changes in tumor and normal tissues of clear cell renal cell carcinoma with VHL syndrome, which provides a solid foundation for the mechanistic study, biomarker screening, and therapeutic target discovery of clear cell renal cell carcinoma.

Construction of a two-gene prognostic model related to ferroptosis in renal cell carcinoma.

Background: Renal cell carcinoma (RCC) is a common and aggressive tumor. A newly discovered form of programmed cell death, ferroptosis, plays an important role in tumor development and progression. However, a clear prognostic correlation between Ferroptosis-related genes (FRGs) and RCC has not yet been established. In this study, prognostic markers associated with FRGs were investigated to improve the therapeutic, diagnostic, and preventive strategies available to patients with renal cancer. Methods: The present study analyzed the predictive value of 23 FRGs in RCC through bioinformatics techniques, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) tools, Kaplan-Meier survival analysis, Cox regression modeling, tumor mutational burden (TMB), CIBERSORT, and half maximal inhibitory concentration (IC50) difference analysis. Results: We screened FRGs by differentially expressed genes (DEGs) and overall survival (OS). Four candidate genes were obtained by hybridization. Then, we constructed a two-gene prognostic signature (NCOA4 and CDKN1A) via univariate Cox regression and multivariate stepwise Cox regression, which classified RCC patients into high- and low-risk groups, and patients in the high-risk group were found to have worse OS and progression-free survival (PFS). We also found that patients with higher TNM stage, T stage, and M stage had higher risk scores than those with lower TNM stage, T stage, and M stage (P<0.05). Males had higher risk scores than females. This signature was identified as an independent prognostic indicator for RCC. These results were validated in both the test cohort and the entire cohort. In addition, we also constructed a nomogram that predicted the OS in RCC patients, the consistency index (C-index) of the nomogram was 0.731 [95% confidence interval (CI): 0.672-0.790], the areas under the receiver operating characteristic (ROC) curves (AUCs) were 0.728, 0.704, and 0.898 at 1-, 3-, and 5-year, respectively, which shows that nomogram has good prediction ability. and we also analyzed the immune status and drug sensitivity between the high- and low-risk groups. Conclusions: We constructed a prognostic model associated with ferroptosis, which may provide clinicians with a reliable predictive assessment tool and offer new perspectives for the future clinical management of RCC.

Automatic segmentation of rectal tumors from MRI using multiscale densely connected convolutional neural network based on attention mechanism.

Rectal cancer is one of the most common malignancies in the gastrointestinal tract. Currently, magnetic resonance imaging has become a vital tool in diagnosing and treating patients with rectal cancer. Notably, early diagnosis of rectal cancer can help improve patient survival rate; however, the clinical expertize of physicians is a limiting factor. Therefore, we propose an attention-based multiscale densely connected convolutional neural network based on an attention mechanism to improve the accuracy of diagnosis by automatically segmenting rectal tumors from two-dimensional (2D) magnetic resonance images (MRI) using computer-aided diagnostic techniques. First, to address the inability of U-Net (a classical segmentation network for medical images) and extract rich semantic features and the inconsistent shape and size of tumors between different patients, we replace the conventional convolutional blocks in the U-Net network with multiscale densely connected convolutional blocks. Second, to make the network focus better on global contextual information, we add central blocks with atrous convolution in the final coding layer or the last coding layer. Finally, we add a hybrid attention mechanism to each decoder module to help the model focus on the features of the rectal tumor region. We validated the effectiveness of the proposed method using 3773 2D MRI datasets from 572 patients. The sensitivity, specificity, Dice correlation coefficient, and Hausdorff distance of MRI rectal tumor segmentation were 85.47%, 86.35%, 94.71%, and 7.88 mm, respectively. The results showed that the proposed method outperforms conventional approaches. Moreover, the proposed method has better segmentation results in the rectal tumor segmentation task and can provide physicians with the second-most important clinical diagnostic opinion.

TRAF2 promotes M2-polarized tumor-associated macrophage infiltration, angiogenesis and cancer progression by inhibiting autophagy in clear cell renal cell carcinoma.

BACKGROUND: The management of advanced clear cell renal cell carcinoma (ccRCC) remains a major challenge in clinical practice, and the construction of more reliable prognostic prediction models and the further elucidation of key molecular mechanisms of tumor progression are topics in urgent need of in-depth investigation. METHODS: We used CIBERSORT to estimate the proportion of 22 tumor-infiltrating immune cell types in the TCGA-KIRC cohort. Weighted gene co-expression network analysis, least absolute shrinkage and selection operator regression analysis were used to build risk prediction models. Expression patterns and clinical significance of TRAF2 were determined through bioinformatics analysis, real-time qPCR, Western Blot, immunohistochemistry. GSEA analysis, transmission electron microscopy, 2D/3D colony formation assay, cell migration and invasion assay, and tube-formation assay were used to investigate the underlying function and mechanism of the TRAF2/M2 macrophage/autophagy axis. RESULTS: We constructed a novel prognostic prediction model based on M2 macrophage-related genes, which was identified as an accurate, independent and specific prognostic risk model for ccRCC patients. A reliable nomogram was constructed to predict 1-, 3-, and 5-year overall survival for patients with ccRCC. As one of the constituent genes of the risk model, TRAF2 was determined to be upregulated in ccRCC and associated with poor clinical prognosis. We found that TRAF2 promotes malignant progression of ccRCC by regulating macrophage polarization, migration and angiogenesis. Mechanistically, we found that TRAF2 promotes the polarization of M2 macrophages, and this chemotaxis is achieved in an autophagy-dependent pathway. Orthotopic tumor growth assay results revealed that TRAF2 plays a key role as a promotor of ccRCC growth and metastasis. CONCLUSIONS: In conclusion, this risk model is highly predictive of prognostic in ccRCC patients, which is expected to promote improved treatment evaluation and comprehensive management of ccRCC. Moreover, our findings reveal that the TRAF2/M2 macrophage/autophagy axis plays a key regulatory role in the malignant progression of ccRCC, and suggest that TRAF2 is a potential novel therapeutic target for advanced ccRCC.

Molecular and clinical characterization of PTRF in glioma via 1,022 samples.

Polymerase I and transcript release factor (PTRF) plays a role in the regulation of gene expression and the release of RNA transcripts during transcription, which have been associated with various human diseases. However, the role of PTRF in glioma remains unclear. In this study, RNA sequencing (RNA-seq) data (n = 1022 cases) and whole-exome sequencing (WES) data (n = 286 cases) were used to characterize the PTRF expression features. Gene ontology (GO) functional enrichment analysis was used to assess the biological implication of changes in PTRF expression. As a result, the expression of PTRF was associated with malignant progression in gliomas. Meanwhile, somatic mutational profiles and copy number variations (CNV) revealed the glioma subtypes classified by PTRF expression showed distinct genomic alteration. Furthermore, GO functional enrichment analysis suggested that PTRF expression was associated with cell migration and angiogenesis, particularly during an immune response. Survival analysis confirmed that a high expression of PTRF is associated with a poor prognosis. In summary, PTRF may be a valuable factor for the diagnosis and treatment target of glioma.

Genotype-phenotype correlations and clinical outcomes of patients with von Hippel-Lindau disease with large deletions.

BACKGROUND: Approximately 20%-40% of patients with von Hippel-Lindau (VHL) disease, an autosomal dominant hereditary disease, exhibit large deletions (LDs). Few studies have focused on this population. Hence, we aimed to elucidate the genotype-phenotype correlations and clinical outcomes in VHL patients with LDs. METHODS: In this retrospective study, we included 119 patients with VHL disease from 50 unrelated families in whom LDs were detected using traditional and next-generation sequencing methods. Other germline mutations were confirmed by Sanger sequencing. Genotype-phenotype correlations and survival were analysed in different groups using Kaplan-Meier and Cox regression. We also evaluated therapeutic response to tyrosine kinase inhibitor (TKI) therapy. RESULTS: The overall penetrance of patients aged <60 was 95.2%. Two VHL patients with LDs also carried CHEK2 and FLCN germline mutations. An earlier age of onset of retinal haemangioblastoma was observed in the next generation. Patients with exon 2 deletion of VHL had an earlier onset age of renal cell carcinoma and pancreatic lesions. The risk of renal cell carcinoma was lower in VHL patients with LDs and a BRK1 deletion. The group with earlier age of onset received poorer prognosis. Four of eight (50%) patients showed partial response to TKI therapy. CONCLUSION: The number of generations and the status of exon 2 could affect age of onset of VHL-related manifestations. Onset age was an independent risk factor for overall survival. TKI therapy was effective in VHL patients with LDs. Our findings would further support clinical surveillance and decision-making processes.