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Pyruvate dehydrogenase E1 subunit beta (PDHB) is located in mitochondria and catalyzes the conversion of glucose-derived acetyl-CoA. The detailed roles of PDHB in human cancers is unclear. Here, through comprehensive bioinformatics analysis, we found that PDHB was aberrantly expressed in multiple human cancers and is associated with patients' clinical stage. The abnormal expression of PDHB was related to the prognostic values of cancers, such as kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP). The Wanderer database with clinical data from Cancer Genome Atlas (TCGA) showed a significant correlation between PDHB expression and the pathologic stage of KIRP patients. We also evaluated the mutation profiles of PDHB in pan-cancer, and showed its roles on the patients’ prognosis. At last, from several immunity algorithms, we demonstrated that the expression of PDHB was correlated with the infiltration of various immune cells in pan-cancer. Moreover, the aberrant PDHB had effects on the response to immune checkpoint inhibitors in cancer patients, such as anti-PD-1. Taken together, our study demonstrated the prognostic values of PDHB in pan-cancers. PDHB may be a potential molecular marker to predicting the immune response in cancer patients.

Ferroptosis is a novel type of cell death associated with iron accumulation and excessive lipid peroxidation. Elucidating the underlying molecular mechanisms of ferroptosis is intensively related to the development and treatment of multiple diseases, including musculoskeletal disorders. Moreover, in vitro and in vivo studies have shown the importance of oxidative stress in musculoskeletal conditions such as osteoporosis, osteoarthritis, rheumatoid arthritis, and osteosarcoma. Ferroptosis-derived clinical management of musculoskeletal diseases offers tremendous and attractive opportunities. Notably, ferroptosis agonists have been proven to enhance the sensitivity of osteosarcoma cells to conventional therapeutic strategies. In this review, we have mainly focused on the implications of ferroptosis regulation in the pathophysiology and therapeutic response of musculoskeletal disorders. Understanding roles of ferroptosis for controlling musculoskeletal diseases might provide directions for ferroptosis-driven therapies, which could be promising for the development of novel therapeutic strategies.

Objective: To optimize the extraction process of total flavonoids of Tetrastigma hemsleyanum Diels et Gilg, compare the yield of total flavonoids of Tetrastigma hemsleyanum Diels et Gilg from different origins, and use fingerprint combined with chemical pattern recognition to make a comprehensive evaluation of the quality of Tetrastigma hemsleyanum Diels et Gilg. Methods: Based on the single-factor experiments, the extraction process of total flavonoids of Tetrastigma hemsleyanum Diels et Gilg was optimized by the Box-Behnken method with the total flavonoids yield of Tetrastigma hemsleyanum Diels et Gilg as the evaluation index. Under the optimal extraction process, the total flavonoids yield of Tetrastigma hemsleyanum Diels et Gilg from different origins was determined. Basing on establishing the HPLC fingerprint of Tetrastigma hemsleyanum Diels et Gilg, the quality of Tetrastigma hemsleyanum Diels et Gilg from different origins were evaluated by similarity evaluation, cluster analysis, and principal component analysis. Results: The optimum extraction process for the total flavonoids of Trifolium was determined to be extraction time 65 min, extraction temperature 83 ℃, solid-to-liquid ratio 1:30 g·mL−1, ethanol concentration 60%, and the total flavonoids yield was 37.89 mg·g−1 under this condition. The total flavonoids yield of Tetrastigma hemsleyanum Diels et Gilg from different origins varied greatly, among which the total flavonoids content of Tetrastigma hemsleyanum Diels et Gilg from Yunnan Chuxiong, Fujian Fuzhou and Guizhou Qianxinan was higher. The HPLC fingerprints of the total flavonoids of Tetrastigma hemsleyanum Diels et Gilg from 9 different origins were established, and a total of 11 common peaks were identified, with similarities of 0.770~0.961. The results of cluster analysis and principal component analysis were consistent, and the samples of Tetrastigma hemsleyanum Diels et Gilg from different origins could be classified into 4 categories. The principal component analysis showed that the cumulative variance contribution of the first three principal components was 84.92%, and the three factors were selected for the comprehensive evaluation. Based on the comprehensive evaluation scores, it was found that the quality of Tetrastigma hemsleyanum Diels et Gilg from Zhejiang Taizhou was the best, followed by Yunnan Chuxion, and Guangdong Qingyuan was the worst. Conclusion: The results of this study would provide a reference for the quality evaluation of the quality of Tetrastigma hemsleyanum Diels et Gilg from different origins, and provide technical support for the regulation of Tetrastigma hemsleyanum Diels et Gilg sales market and subsequent resource development.

Abstract Background Desmoplastic small round cell tumor (DSRCT) is a sporadic, highly malignant tumor with a poor prognosis. The abdomen and pelvis have been reported as the primary localization sites. However, to the best of our knowledge, there are few reports on primary DSRCT in the submandibular gland. Case presentation We report a case of a 26-year-old Chinese man with a mass in the right submandibular gland. Imaging studies showed a hypoechoic mass in the right submandibular region. Intraoperative pathology revealed that the tumor tissue was composed of small round tumor cells and a dense desmoplastic stroma. On immunostaining, the tumor cells showed markers of epithelial, mesenchymal, myogenic, and neural differentiation. The EWSR1 gene rearrangement was detected by fluorescence in situ hybridization. Based on the overall morphological features and immunohistochemical findings, a final diagnosis of DSRCT was made. The patient was treated with comprehensive anti-tumor therapy mainly based on radiotherapy and chemotherapy. Conclusions DSRCT is an uncommon malignant neoplasm with rare submandibular gland involvement. In this report, we have described a case of DSRCT in the submandibular gland and reviewed the literature on DSRCT over the past 5 years. Considering the importance of differential diagnosis between DSRCT, especially with rare extra-peritoneal involvement, and small round blue cell tumors, a full recognition of the clinicopathological features will help to better diagnose this neoplasm.

With the rapid growth of trajectory big data, there is a need for more efficient methods to extract, analyze, and visualize these data. However, existing research on trajectory big data visualization mainly focuses on displaying trajectories for a specific period or showing spatial distribution characteristics of trajectory points in a single time slice using clustering, filtering, and other techniques. Therefore, this paper proposes a vector field visualization model for trajectory big data, aiming to effectively represent the inherent movement trends in the data and provide a more intuitive visualization of urban traffic congestion trends. The model utilizes the motion information of vehicles to create a travel vector grid and employs WebGL technology for vector field visualization rendering. The vector field effects are effectively displayed by generating many particles and simulating their movements. Furthermore, this research also designs and implements congestion trend point identification and hotspot congestion analysis, thus validating the practicality and effectiveness of trajectory big data vector field visualization. The results indicate that compared to traditional visualization methods, the vector field visualization method can demonstrate the direction and density changes in traffic flow and predict future traffic congestion. This work provides valuable data references and decision support for urban traffic management and planning.

The fashion industry has a critical need for fashion compatibility. Modeling compatibility is a challenging task that involves extracting (in)compatible features of pairs, obtaining compatible relationships between matching items, and applying them to personalized recommendation tasks. Measuring compatibility is a complex and subjective concept in general. The complexity is reflected in the fact that relationships between fashion items are determined by multiple matching rules, such as color, shape, and material. Each personal aesthetic style and fashion preference differs, adding subjectivity to the compatibility concept. As a result, personalized factors must be considered. Previous works mainly utilize a convolutional neural network to measure compatibility by extracting general features, but they ignore fine-grained compatibility features and only model overall compatibility. We propose a novel neural network framework called the Attention-based Personalized Compatibility Embedding Network (PCE-Net). It comprises two components: attention-based compatibility embedding modeling and attention-based personal preference modeling. In the second part, we utilize matrix factorization and content-based features to obtain user preferences. Both pieces are jointly trained using the BPR framework in an end-to-end method. Extensive experiments on the IQON3000 dataset demonstrate that PCE-Net significantly outperforms most baseline methods.

Artificial intelligence (AI) is a general term that refers to the use of a machine to imitate intelligent behavior for performing complex tasks with minimal human intervention, such as machine learning; this technology is revolutionizing and reshaping medicine. AI has considerable potential to perfect health-care systems in areas such as diagnostics, risk analysis, health information administration, lifestyle supervision, and virtual health assistance. In terms of immunotherapy, AI has been applied to the prediction of immunotherapy responses based on immune signatures, medical imaging and histological analysis. These features could also be highly useful in the management of cancer immunotherapy given their ever-increasing performance in improving diagnostic accuracy, optimizing treatment planning, predicting outcomes of care and reducing human resource costs. In this review, we present the details of AI and the current progression and state of the art in employing AI for cancer immunotherapy. Furthermore, we discuss the challenges, opportunities and corresponding strategies in applying the technology for widespread clinical deployment. Finally, we summarize the impact of AI on cancer immunotherapy and provide our perspectives about underlying applications of AI in the future.

Abstract Alterations of mitogen-activated protein kinase kinase 1 (MEK1) are commonly associated with tumorigenesis, and MEK1 is thought to be a suitable targeted therapy for various cancers. However, abnormal MEK1 alterations and their relevant clinical implications are unknown. Our research comprehensively analyzed the MEK1 alteration spectrum and provided novel insight for targeted therapies. There were 7694 samples covering 32 types of cancer from The Cancer Genome Atlas (TCGA) database. They were used to conduct an integrative analysis of MEK1 expression, alterations, functional impacts and clinical significance. There was a dramatic difference in the alteration frequency and distribution and clinical implications in 32 types of cancer from the TCGA. Skin cutaneous melanoma (SKCM) has the most alterations and has therapeutic targets located in the protein kinase domain, and the growing expression of SKCM is positively related to patient prognosis. MEK1 expression in lung adenocarcinoma (LUAD), kidney renal papillary cell carcinoma (KIRP), esophageal carcinoma (ESCA) and liver hepatocellular carcinoma (LIHC) is decreased, which is associated with better prognosis, while MEK1 expression in thymoma (THYM), stomach adenocarcinoma (STAD), kidney renal clear cell carcinoma (KIRC), testicular germ cell tumors (TGCTs) and head and neck squamous cell carcinoma (HNSC) is increased, which is associated with better prognosis. Mesothelioma (MESO) has the second highest alterations but has no therapy targets. This study provided a great and detailed interpretation of MEK1 expression, alterations and clinical implications in 32 types of cancer and reminded us to fill the gap in MEK1 research from a new perspective.

Marine environmental change directly affects bivalve growth and survival. Exoskeleton formation, the main energy dissipation in the physiological metabolism, typically reflects the body growth of the bivalve. However, how bivalves regulate the biomineralization of the exoskeleton under environmental stressors is not yet clear. Long non-coding RNA regulates various life processes through complex mechanisms in vertebrates and invertebrates. In this research, we cloned the complete sequence of a mantle-specific expressed long non-coding RNA (designated as LncMPEG1) from a pearl oyster, Pinctada fucata martensii. A quantitative real-time PCR analysis showed that LncMPEG1 expression was significantly high in early umbo larvae and juveniles, which would be the critical periods of shell development. LncMPEG1 was identified in the outer epithelium of the middle fold from the mantle edge, mantle pallial, and mantle center by using in situ hybridization. Additionally, the expression of LncMPEG1 was stimulated by shell damage, alien invasion, heat and cold temperature stress, and hypoxia stress. In the mantle, a decreased in LncMPEG1 expression was detected by RNA interference, which can cause the irregular growth of crystals on the inner surface of the prismatic layer and nacre in the shells. Therefore, we propose that LncMPEG1 could be a key regulator in biomineralization and responds to environmental stress in the mantle .

Background: Emerging studies have shown the important roles of long noncoding RNAs (lncRNAs) in the occurrence and development of liver cancer. However, the exosome-related lncRNA signature in liver cancer remains to be clarified.Methods: We obtained 371 tumor specimens and 50 normal tissues from the TCGA database. These samples were randomly divided into the training queue and verification queue. The exosome-related lncRNA risk model was verified by correlation analysis, Lasso regression analysis, and Cox regression analysis. The differences in the immune microenvironment in the two risk groups were obtained by analyzing the infiltration of different immune cells.Results: Five exosome-related lncRNAs associated (MKLN1-AS, TMCC1-AS1, AL031985.3, LINC01138, AC099850.3) with a poor prognosis were identified and used to construct the signature. Receiver operating curve (ROC) and survival curves were used to confirm the predictive ability of this signature. Based on multivariate regression analysis in the training cohort (HR: 3.033, 95% CI: 1.762–5.220) and validation cohort (HR: 1.998, 95% CI: 1.065–3.751), the risk score was found to be an independent risk factor for patient prognosis. Subsequently, a nomogram was constructed to predict the 1-, 3-, 5-years survival rates of liver cancer patients. Moreover, this signature was also related to overexpressed immune checkpoints (PD-1, B7-H3, VSIR, PD-L1, LAG3, TIGIT and CTLA4).Conclusion: Our study showed that exosome-related lncRNAs and the corresponding nomogram could be used as a better index to predict the outcome and immune regulation of liver cancer patients. This signature might provide a new idea for the immunotherapy of liver cancer in the future.

Lipoic acid synthetase (LIAS) has been demonstrated to play a crucial role in the progression of cancer. Exploring the underlying mechanisms and biological functions of LIAS could have potential therapeutic guidance for cancer treatment. Our study has explored the expression levels and prognostic values of LIAS in pan-cancer through several bioinformatics platforms, including TIMER2.0, Gene Expression Profiling Interactive Analysis, version 2 (GEPIA2.0), and Human Protein Atlas (HPA). We found that a high LIAS expression was related to the good prognosis in patients with kidney renal clear cell carcinoma (KIRC), rectum adenocarcinoma (READ), breast cancer, and ovarian cancer. Inversely, a high LIAS expression showed unfavorable prognosis in lung cancer patients. In addition, the genetic alteration, methylation levels, and immune analysis of LIAS in pan-cancer have been evaluated. To elucidate the underlying molecular mechanism of LIAS, we conduct the single-cell sequencing to implicate that LIAS expression was related to hypoxia, angiogenesis, and DNA repair. Thus, these comprehensive pan-cancer analyses have conveyed that LIAS could be potentially significant in the progression of various cancers. Moreover, the LIAS expression could predict the efficacy of immunotherapy in cancer patients.

Pyroptosis is a cell death pathway that plays a significant role in lung adenocarcinoma (LUAD). Also, studies regarding the correlation between the expression of long non-coding RNAs (lncRNAs) and the mechanism of LUAD has aroused concern around the world. The purpose of this paper is to explore the underlying relationship of differentially expressed lncRNAs and pyroptosis-related genes. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression were applied to construct a prognostic risk score model from the TCGA database. A pyroptosis-related five-lncRNA signature (CRNDE, HHLA3, MIR193BHG, LINC00941, LINC01843) was considered to be correlated to the prognosis and immune response of LUAD patients. In addition, the cytological experiments revealed that aberrantly expressed HHLA3 displayed a proliferation promotion role in LUAD cells A549 and H460. Next, the forest and nomogram plots have shown this lncRNA signature could be served as an independent prognostic factor for LUAD. The ROC curves further identified the prognostic value of the five-lncRNA signature. The infiltration of immune cells, such as T cells CD8, T cells CD4 memory resting, T cells CD4 memory activated and M0 macrophages were greatly different between the high-risk group and the low-risk group. It implicated that the signature is significantly effective in immunotherapy of LUAD patients. This study has supplied a novel pyroptosis-related lncRNA signature and provided a predictive model for prognosis and immune response of LUAD patients.

The primary or acquired resistance to anti-VEGF inhibitors remains a common problem in cancer treatment. Therefore, identifying potential biomarkers enables a better understanding of the precise mechanism. Through the GEO database, three profiles associated with bevacizumab (BV) resistance to ovarian cancer, glioma, and non-small-cell lung carcinoma, respectively, were collected for the screening process, and two genes were found. A-kinase anchor protein 12 (AKAP12), one of these two genes, correlates with tumorigenesis of some cancers. However, the role of AKAP12 in pan-cancer remains poorly defined. The present study first systematically analyzed the association of AKAP12 with anti-VEGF inhibitors’ sensitivity, clinical prognosis, DNA methylation, protein phosphorylation, and immune cell infiltration across various cancers via bioinformatic tools. We found that AKAP12 was upregulated in anti-VEGF therapy-resistant cancers, including ovarian cancer (OV), glioblastoma (GBM), lung cancer, and colorectal cancer (CRC). A high AKAP12 expression revealed dismal prognoses in OV, GBM, and CRC patients receiving anti-VEGF inhibitors. Moreover, AKAP12 expression was negatively correlated with cancer sensitivity towards anti-VEGF therapy. Clinical prognosis analysis showed that AKAP12 expression predicted worse prognoses of various cancer types encompassing colon adenocarcinoma (COAD), OV, GBM, and lung squamous cell carcinoma (LUSC). Gene mutation status may be a critical cause for the involvement of AKAP12 in resistance. Furthermore, lower expression of AKAP12 was detected in nearly all cancer types, and hypermethylation may explain its decreased expression. A decreased phosphorylation of T1760 was observed in breast cancer, clear-cell renal cell carcinoma, and lung adenocarcinoma. For the immunologic significance, AKAP12 was positively related to the abundance of pro-tumor cancer-associated fibroblasts (CAFs) in various types of cancer. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis suggested that “cell junction organization” and “MAPK pathway” participated in the effect of AKAP12. Importantly, we discovered that AKAP12 expression was greatly associated with metastasis of lung adenocarcinoma as well as differential and angiogenesis of retinoblastoma through investigating the single-cell sequencing data. Our study showed that the dual role of AKAP12 in various cancers and AKAP12 could serve as a biomarker of anti-VEGF resistance in OV, GBM, LUSC, and COAD.

Lung cancer remains the leading cause of malignant mortality worldwide. Hence, the discovery of novel targets that can improve therapeutic effects in lung cancer patients is an urgent need. In this study, we screened differentially expressed genes using isobaric tags for relative and absolute quantitation (iTRAQ) analysis and datasets from the cancer genome atlas database, and found that nuclear division cycle 80 (NDC80) might act as a novel prognostic indicator of lung cancer. The expression of NDC80 was significantly increased in lung cancer tissues, as compared to normal tissues, and high expression levels of NDC80 were correlated with unfavorable survival rates. Furthermore, an in vitro analysis showed that the stable knockdown of NDC80 decreased the cell viability and increased therapeutic sensitivity in two lung cancer cell lines, A549-IRR and H1246-IRR. Moreover, gene set enrichment analysis results showed that NDC80 was enriched in autophagy-related pathways. The downregulation of NDC80 inhibited the formation of autophagosomes, and reduced the expression of autophagy-related proteins such as LC3II, Beclin-1, and p62 in lung cancer cells. To further clarify the role of NDC80 as a downstream regulator of autophagy, we validated autophagic mediators through iTRAQ analysis and real-time polymerase chain reaction arrays. Autophagy-related protein7 (ATG7) was observed to be downregulated after the knockdown of NDC80 in lung cancer cells. Immunohistochemistry assay results revealed that both NDC80 and ATG7 were upregulated in an array of lung adenocarcinoma samples, compared to normal tissues, and the expression of NDC80 was identified to be positively associated with the levels of ATG7. Our findings suggest that NDC80 promotes the development of lung cancer by regulating autophagy, and might serve as a potential target for increasing the therapeutic sensitivity of lung cancer.

Background Pre-hospitalisation, hospitalisation and post-hospitalisation factors may significantly affect depression, anxiety and post-traumatic growth (PTG) among COVID-19 survivors. Objective Our study investigated depression, anxiety and PTG and their correlates among COVID-19 survivors. Method A cross-sectional telephone survey recruited 199 COVID-19 patients (Mean age = 42.7; 53.3% females) at six-month follow-up after hospital discharge in five Chinese cities (i.e. Wuhan, Shenzhen, Zhuhai, Dongguan and Nanning). Their demographic information, clinical records and experiences during (e.g. severity of covid-19 symptoms, treatment and exposure to other patients’ suffering) and after hospitalisation (e.g. perceived impact of covid-19, somatic symptoms after hospitalisation), and psychosocial factors (e.g. perceived discrimination, self-stigma, affiliate stigma, resilience and social support) were investigated. Depressive and anxiety symptoms were measured by the Patient Health Questionnaire (PHQ-9) and the Generalised anxiety disorder (GAD-7) scale, respectively. PTG was examined by the Post-traumatic Growth Inventory (PTGI) instrument. Results The proportion of depressive symptoms

Background As a highly infectious disease with human-to-human transmission characteristics, COVID-19 has caused panic in the general public. Those who have recovered from COVID-19 may experience discrimination and internalized stigma. They may be more likely to worry about social interaction and develop social anxiety. Objectives This study investigated the associations among hospitalization factors, social/interpersonal factors, personal factors, and social anxiety to reveal the mechanism of social anxiety in COVID-19 survivors. Methods A cross-sectional, multicenter telephone survey was conducted from July to September 2020 in five Chinese cities (i.e. Wuhan, Nanning, Shenzhen, Zhuhai, and Dongguan); adult COVID-19 survivors were recruited 6 months after they were discharged from the hospital. Linear regressions and path analysis based on the minority stress model were conducted to test the relationships among hospitalization, social/interpersonal factors, personal factors, and social anxiety. Results The response rate was 74.5% (N = 199, 55.3% females). Linear regression analyses showed that various hospitalization, social/interpersonal, and personal factors were statistically significantly associated with social anxiety. Path analysis showed that the proposed model fit the data well (χ2(df) = 3.196(3), p = .362, CFI = .999, NNFI = .996, RMSEA = .018). Internalized stigma fully mediated the association between perceived discrimination/social support and social anxiety, while it partially mediated the association between perceived affiliate stigma and social anxiety. Conclusions The results suggest that social/interpersonal and personal factors have a stronger association with social anxiety than hospitalization factors and highlight the importance of internalized stigma in understanding the mechanisms of these relationships. Clinical psychologists can refer to these modifiable psychosocial factors to develop efficient interventions for mental health promotion.

B-Raf proto-oncogene serine/threonine-protein kinase (BRAF) is frequently altered in multiple cancer types, and BRAF V600 mutations act as a prime target for precision therapy. Although emerging evidence has investigated the role of BRAF, the comprehensive profiling of BRAF expression, alteration and clinical implications across various cancer types has not been reported. In this study, we used the TCGA dataset, covering 10,967 tumor samples across 32 cancer types, to analyze BRAF abnormal expression, DNA methylation, alterations (mutations and amplification/deletion), and their associations with patient survival. The results showed that BRAF expression, alteration frequency, mutation site distribution, and DNA methylation patterns varied tremendously among different cancer types. The expression of BRAF was found higher in PCPG and CHOL, and lower in TGCT and UCS compared to normal tissues. In terms of pathological stages, BRAF expression was significantly differentially expressed in COAD, KIRC, LUSC, and OV. The methylation levels of BRAF were significantly lower in LUSC, HNSC, and UCEC compared to normal tissue. The expression of BRAF and downstream gene (ETS2) was negatively correlated with methylation levels in various cancers. The overall somatic mutation frequency of BRAF was 7.7% for all cancer samples. Most fusion transcripts were found in THCA and SKCM with distinct fusion patterns. The majority of BRAF mutations were oncogenic and mainly distributed in the Pkinase_Tyr domain of THCA, SKCM, COADREAD, and LUAD. The BRAF mutations were divided into five levels according to the clinical targeted therapy implication. The results showed level 1 was mainly distributed in SKCM, COADREAD, and LUAD, while level 3B in THCA. The overall BRAF CNV frequency was about 42.7%, most of which was gain (75.9%), common in GBM, TGCT, and KIRP. In addition, the forest plot showed that increased BRAF expression was associated with poor patient overall survival in LIHC, OV, and UCEC. Taken together, this study provided a novel insight into the full alteration spectrum of BRAF and its implications for treatment and prognosis.

Lane detection is a crucial task in the field of autonomous driving, as it enables vehicles to safely navigate on the road by interpreting the high-level semantics of traffic signs. Unfortunately, lane detection is a challenging problem due to factors such as low-light conditions, occlusions, and lane line blurring. These factors increase the perplexity and indeterminacy of the lane features, making them hard to distinguish and segment. To tackle these challenges, we propose a method called low-light enhancement fast lane detection (LLFLD) that integrates the automatic low-light scene enhancement network (ALLE) with the lane detection network to improve lane detection performance under low-light conditions. Specifically, we first utilize the ALLE network to enhance the input image’s brightness and contrast while reducing excessive noise and color distortion. Then, we introduce symmetric feature flipping module (SFFM) and channel fusion self-attention mechanism (CFSAT) to the model, which refine the low-level features and utilize more abundant global contextual information, respectively. Moreover, we devise a novel structural loss function that leverages the inherent prior geometric constraints of lanes to optimize the detection results. We evaluate our method on the CULane dataset, a public benchmark for lane detection in various lighting conditions. Our experiments show that our approach surpasses other state of the arts in both daytime and nighttime settings, especially in low-light scenarios.

The tumor microenvironment (TME) plays an important part in the initiation and development of clear cell renal cell carcinoma (ccRCC). However, an understanding of the immune infiltration in TME is still unknown. Our study aims to explore the correlation between the TME and the clinical features, as well as the prognosis of ccRCC. In the present study, ESTIMATE and CIBERSORT computational methods were applied to calculate the proportion of tumor-infiltrating immune cells (TICs) and the amount of immune and stromal fractions in the ccRCC form The Cancer Genome Atlas (TCGA) database. Then, we sought to find out those immune cell types and genes which may play a significant role and validated them in the GEO database. Furthermore, an immunohistochemical analysis of our external validation dataset was used to detect SAA1 and PDL1 expression in the ccRCC cancer tissues and corresponding normal tissues. Statistical analysis was performed to study the relationship between SAA1 and clinical characteristics, as well as PDL1 expression. Furthermore, a ccRCC cell model with SAA1 knockdown was constructed, which was used for cell proliferation and the migration test. The intersection analysis of the univariate COX and PPI analysis were performed to imply Serum Amyloid A1 (SAA1) as a predictive factor. The expression of SAA1 was significantly negatively correlated to OS and positively correlated to the clinical TMN stage system. The genes in the high-expression SAA1 group were basically enriched in immune-related activities. The proportion of mast cells resting was negatively correlated with SAA1 expression, indicating that SAA1 may be involved in the maintenance of the immune status for the TME. Moreover, the PDL1 expression was positively related to the SAA1 expression and negatively correlated with the patients’ prognosis. Further experiments revealed that the knockdown of SAA1 inhibited ccRCC development through suppressing cell proliferation and migration. SAA1 may be a novel marker for the prognosis prediction of ccRCC patients and may play a vital role in the TME by mast cell resting and PDL1 expression. SAA1 has the potential to become a therapeutic target and indicator for immune target therapy in ccRCC treatment.

Background and Objectives: Calcium-binding protein 39-like (CAB39L) has been reported to be downregulated and possessed diagnostic and prognostic values in several types of cancer. However, the clinical value and mechanism of CAB39L in kidney renal clear cell carcinoma (KIRC) remain unclear. Materials and Methods: Bioinformatics analysis was conducted using different databases including TCGA, UALCAN, GEPIA, LinkedOmics, STRING, and TIMER. One-way variance analysis and t-test were chosen to investigate the statistical differences of CAB39L expression in KIRC tissues with different clinical characteristics. The receiver operating characteristic (ROC) curve was chosen to assess the discriminatory capacity of CAB39L. Kaplan–Meier curves were employed for assessing the influence of CAB39L on the progression-free survival (PFS), disease-specific survival (DSS), and overall survival (OS) of KIRC patients. The independent prognostic significance of clinical parameters for OS such as CAB39L expression in KIRC patients was estimated by Cox analysis. A series of in vitro functional experiments and Western blot (WB) and immunohistochemistry (IHC) were used to validate the relative protein expression and function of CAB39L. Results: The mRNA and protein levels of CAB39L were relatively downregulated in KIRC samples. Meanwhile, hypermethylation of the CAB39L promoter region was possibly associated with its low expression in KIRC. The ROC curve showed that the mRNA expression of CAB39L had a strong diagnostic value for both early and late KIRC. Kaplan–Meier survival curves indicated that a higher mRNA level of CAB39L predicted good PFS, DSS, and OS. The mRNA expression of CAB39L was an independent prognostic factor (hazard ratio = 0.6, p = 0.034) identified by multivariate Cox regression analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis exhibited that CAB39L was mainly associated with substance and energy metabolism. Finally, overexpression of CAB39L impaired the proliferation and metastasis of KIRC cells in vitro. Conclusions: CAB39L possesses prognostic and diagnostic capacity in KIRC.

DNA polymerase delta 1 catalytic subunit (POLD1) plays a vital role in genomic copy with high fidelity and DNA damage repair processes. However, the prognostic value of POLD1 and its relationship with tumor immunity in clear cell renal cell carcinoma (ccRCC) remains to be further explored. Transcriptional data sets and clinical information were obtained from the TCGA, ICGC, and GEO databases. Differentially expressed genes (DEGs) were derived from the comparison between the low and high POLD1 expression groups in the TCGA–KIRC cohort. KEGG and gene ontology (GO) analyses were performed for those DEGs to explore the potential influence of POLD1 on the biological behaviors of ccRCC. The prognostic clinical value and mutational characteristics of patients were described and analyzed according to the POLD1 expression levels. TIMER and TISIDB databases were utilized to comprehensively investigate the potential relevance between the POLD1 levels and the status of the immune cells, as well as the tumor infiltration of immune cells. In addition, RT-qPCR, Western blot, immunohistochemistry and several functional and animal experiments were performed for clinical, in vitro and in vivo validation. POLD1 was highly expressed in a variety of tumors including ccRCC, and further verified in a validation cohort of 60 ccRCC samples and in vitro cell line experiments. POLD1 expression levels in the ccRCC samples were associated with various clinical characteristics including pathologic tumor stage and histologic grade. ccRCC patients with high POLD1 expression have poor clinical outcomes and exhibit a higher rate of somatic mutations than those with low POLD1 expression. Cox regression analysis also showed that POLD1 could act as a potential independent prognostic biomarker. The DEGs associated with POLD1 were significantly enriched in the immunity-related pathways. Moreover, further immune infiltration analysis indicated that high POLD1 expression was associated with high NK CD56bright cells, Treg cells, and myeloid-derived suppressor cells’ (MDSCs) infiltration scores, as well as their marker gene sets of immune cell status. Meanwhile, POLD1 exhibited resistance to various drugs when highly expressed. Finally, the knockdown of POLD1 inhibited the proliferation and migration, and promoted the apoptosis of ccRCC cells in vitro and in vivo, as well as influenced the activation of oncogenic signaling. Our current study demonstrated that POLD1 is a potential prognostic biomarker for ccRCC patients. It might create a tumor immunosuppressive microenvironment and inhibit the susceptibility to ferroptosis leading to a poor prognosis.

Background: The different pharmacological effects of drugs in different people can be explained by the polymorphisms of drug metabolism-related genes. Emerging studies have realized the importance of drug metabolism-related genes in the treatment and prognosis of cancers, including ovarian cancer (OV). In this study, using comprehensive bioinformatics and western blot, we identified that the drug metabolism-related gene, ADH1B, was significantly down-regulated in OV cells and tissues. The patients with a high level of ADH1B presented a good prognosis. We also found a negative correlation between ADH1B expression and the activity of chemotherapeutic agents, such as cyclophosphamide. In addition, positive correlations were observed between ADH1B expression and multiple immune checkpoints, including LAG3 and HAVCR2. The immune infiltration analysis further indicated that aberrantly expressed ADH1B might have important roles in regulating the infiltration of macrophages and neutrophils in OV tissues. Then, the co-expression analysis was conducted and the top three enriched KEGG pathways were spliceosome, RNA transport, and DNA replication. In conclusion, the drug metabolism-related gene ADH1B and its interactive network play an essential role in the immune regulation and therapeutic response and maybe identified as promising therapeutic targets for OV patients.

Pyroptosis, characterized as an inflammasome-mediated cell death pathway, may be participated in tumorigenesis and progression. However, the underlying molecular function and mechanism of pyroptosis in BRCA remain unclear. In our study, we aimed to develop a prognostic signature in BRCA based on pyroptosis-associated genes. Data was downloaded from TCGA database, and then we screened 760 female BRCA samples and 104 normal breast tissues as the training set. Seven pyroptosis-related genes (CASP9, GPX4, IL18, NLRC4, SCAF11, TIRAP, and TNF) were identified as the pyroptosis-related prognostic model for BRCA using LASSO Cox regression. We subsequently tested the prognostic value of pyroptosis-associated gene signature in a validation set, GSE 20685. Time-dependent receiver operating characteristic analysis demonstrated the credible predictive capacity of this pyroptosis-associated gene signature. The area under the curves were 0.806 at 3 years, 0.787 at 5 years, 0.775 at 8 years, and 0.793 at 10 years in the training set, and 0.824 at 5 years, 0.808 at 8 years, and 0.790 at 10 years in the validation set. Furthermore, there are currently few data on SCAF11 regulating pyroptosis. To clarify this issue, we performed integrative bioinformatics and experimental analysis. Knocking down SCAF11 possessed an anti-cancer effect in terms of inhibiting cell viability and suppressing colony-formation in in-vitro functional assays. Meanwhile, the biological functions of SCAF11 in BRCA were further validated with several algorithms, such as Xiantao tool, LinkedOmics, GEPIA2, and TISIDB. These findings indicated that the expression of SCAF11 was significantly correlated with diverse tumor-infiltrating lymphocytes (TILs), including T central memory cell (Tcm), and type 2 T helper cell (Th2), etc. Functional enrichment analysis suggested that co-expression genes of SCAF11 primarily participated in inflammation and immune-related signaling pathways, such as oxidative phosphorylation, antimicrobial humoral response, and immunoglobulin complex. Moreover, SCAF11 expression was positively correlated with several immune checkpoints, including PD-L1, B7H3, and PDCD1LG2. Taken together, this study uncovered that pyroptosis-associated gene signature might be applied as an effective independent predictor in patients with BRCA. The pyroptosis-related gene SCAF11 might play potential roles in the regulation of immune microenvironment in BRCA.

Human action recognition has drawn significant attention because of its importance in computer vision-based applications. Action recognition based on skeleton sequences has rapidly advanced in the last decade. Conventional deep learning-based approaches are based on extracting skeleton sequences through convolutional operations. Most of these architectures are implemented by learning spatial and temporal features through multiple streams. These studies have enlightened the action recognition endeavor from various algorithmic angles. However, three common issues are observed: (1) The models are usually complicated; therefore, they have a correspondingly higher computational complexity. (2) For supervised learning models, the reliance on labels during training is always a drawback. (3) Implementing large models is not beneficial to real-time applications. To address the above issues, in this paper, we propose a multi-layer perceptron (MLP)-based self-supervised learning framework with a contrastive learning loss function (ConMLP). ConMLP does not require a massive computational setup; it can effectively reduce the consumption of computational resources. Compared with supervised learning frameworks, ConMLP is friendly to the huge amount of unlabeled training data. In addition, it has low requirements for system configuration and is more conducive to being embedded in real-world applications. Extensive experiments show that ConMLP achieves the top one inference result of 96.9% on the NTU RGB+D dataset. This accuracy is higher than the state-of-the-art self-supervised learning method. Meanwhile, ConMLP is also evaluated in a supervised learning manner, which has achieved comparable performance to the state of the art of recognition accuracy.

Pharmacotherapeutics is the prevention and treatment of ailments, whether disorders or diseases, with medication [...]

Primary urethral adenocarcinoma in females is an extremely rare malignancy with unclear origin and only a few retrospective cases have been reported. The controversy continues to exist over the origin of primary urethral adenocarcinoma from periurethral glands (which include the Skene’s glands), urethritis glandularis or intestinal metaplasia. Herein, we report one case of a 49-year-old female with distal urethral adenocarcinoma who presented with obstructive voiding. Abdominal and pelvic CT scans and chest radiology were unremarkable. Biopsy of the mass confirmed urethral adenocarcinoma. The patient underwent partial ureterectomy and was disease-free at the 2-years follow-up period. We also present another extremely rare case of primary urethral adenocarcinoma with mucinous features in a 58-year-old female who initially complained of external urethral orifice itching with painless urethral bleeding and was treated with local excision. The patient has not received any neoadjuvant or adjuvant therapy, and experienced tumor recurrence, inguinal lymph nodes metastasis, and even local iliopsoas metastasis during over 10-years follow-up. In conclusion, our current study emphasizes the importance of imaging studies and biopsy in making an accurate preoperative diagnosis of this rare disease, and further highlights the role of multimodal therapy. A combination of radiotherapy, chemotherapy and surgery is recommended for the optimal local and distant disease control. Moreover, better medical compliance and regular follow-up are required in these patients.

Abstract In the era of the rapid development of cancer immunotherapy, there is a high level of interest in the application of cell-released small vesicles that stimulate the immune system. As cell-derived nanovesicles, exosomes show great promise in cancer immunotherapy because of their immunogenicity and molecular transfer function. The cargoes carried on exosomes have been recently identified with improved technological advances and play functional roles in the regulation of immune responses. In particular, exosomes derived from tumor cells and immune cells exhibit unique composition profiles that are directly involved in anticancer immunotherapy. More importantly, exosomes can deliver their cargoes to targeted cells and thus influence the phenotype and immune-regulation functions of targeted cells. Accumulating evidence over the last decade has further revealed that exosomes can participate in multiple cellular processes contributing to cancer development and therapeutic effects, showing the dual characteristics of promoting and suppressing cancer. The potential of exosomes in the field of cancer immunotherapy is huge, and exosomes may become the most effective cancer vaccines, as well as targeted antigen/drug carriers. Understanding how exosomes can be utilized in immune therapy is important for controlling cancer progression; additionally, exosomes have implications for diagnostics and the development of novel therapeutic strategies. This review discusses the role of exosomes in immunotherapy as carriers to stimulate an anti-cancer immune response and as predictive markers for immune activation; furthermore, it summarizes the mechanism and clinical application prospects of exosome-based immunotherapy in human cancer.

The AlkB family of Fe (II) and α-ketoglutarate-dependent dioxygenases works by removing alkyl substituents from alkylation-damaged nucleic acid bases through oxidative dealkylation, subsequently affecting tumor progression and patient prognosis. However, the specific roles of the AlkB family in Glioblastoma remain to be elucidated. By taking advantage of the abundant bioinformatics databases, such as GEPIA2, cBioPortal and TIMER, we performed a comprehensive analysis of the AlkB family in GBM, and managed to identify the significant prognostic hallmarks and therapeutic targets within this family. We found that the expression levels of ALKBH2 and ALKBH8 were significantly up-regulated in GBM compared with normal tissues. Meanwhile, the patients with high levels of ALKBH2 and ALKBH8 possessed significant poor overall survival (OS). In addition, the results suggested that the biological function of the AlkB family was closely related to DNA damage repair, cell metabolism, cell proliferation and tumor immune infiltration in GBM. Furthermore, the high expression of ALKBH8 in GBM was verified by immunohistochemistry. Taken together, this study could provide meaningful information about the aberrant AlkB family associated with GBM initiation and progression, and help clinicians precisely predict patient survival and select alternative therapeutic drugs.

Chemoresistance, especially temozolomide (TMZ) resistance, is a major clinical challenge in the treatment of glioblastoma (GBM). Exploring the mechanisms of TMZ resistance could help us identify effective therapies. Adenosine deaminases acting on RNA (ADARs) are very important in RNA modification through regulating the A-to-I RNA editing. Recent studies have shown that ADARs regulate multiple neurotransmitter receptors, which have been linked with the occurrence and progress of GBM. Here, data from several bioinformatics databases demonstrated that adenosine deaminase RNA specific B1 (ADARB1), also named ADAR2, was upregulated in both GBM tissues and cells, and had the prognostic value in GBM patients. Moreover, ADARB1 was found to be involved in AKT-mediated TMZ resistance in GBM cells. The KEGG analysis of ADARB1-associated co-expressed genes showed that ADARB1 was potentially involved in the mitochondrial respiratory chain complex. TISIDB and GEPIA databases were further used to analyze the role of ADARB1 in tumor-immune system interactions in GBM. These findings deepened our understanding of the function of ADARB1 in tumorigenesis and therapeutic response in GBM.

Background: Colon cancer is an aggressive and heterogeneous disease associated with high morbidity and mortality. The immune system is intimately involved in tumorigenesis and can influence malignant properties at the protein, epigenetic, and even genomic levels by shaping the tumor immune microenvironment (TIM). However, immune-related molecules that can effectively predict the prognosis of colon cancer remain under exploration.Methods: A total of 606 patients from TCGA and GEO databases were employed in our study, in which 429 cases were set as the training cohort and 177 were defined as the validation cohort. The immune infiltration was evaluated by ESTIMATE, TIMER, and CIBERSORT algorithms. The risk signature was constructed by LASSO Cox regression analysis. A nomogram model was generated subsequent to the multivariate Cox proportional hazards analysis to predict 1-, 3-, and 5-year survival of patients with colon cancer.Results: Infiltrating immune cell profiling identified two colon cancer clusters (Immunity_L group and Immunity_H group). The abundances of immune cells were higher in the Immunity_H group, which indicated a better prognosis. Through further statistical analysis, we identified four genes which were highly correlated with prognosis and representative of this gene set, namely ARL4C, SERPINE1, BST2, and AXIN2. When the patients were divided into low- and high-risk groups based on their risk scores, we found that patients in the high-risk group had shorter overall survival time. Moreover, a nomogram including clinicopathologic features and the established risk signature could robustly predict 1-, 3-, and 5-year survival in patients with colon cancer.Conclusion: We identified two distinct immune patterns by analyzing clinical and transcriptomic information from colon cancer patients. A subsequently constructed immune-related gene-based prognostic model as well as a nomogram model can be used to predict the prognosis of colon cancer, thereby guiding risk stratification and treatment regimen development for colon patients.

Glioma is a highly malignant brain tumor with a poor survival rate. Novel biomarkers that act as prompt indicators of glioma are urgently needed. In this study, we identified and validated prognosis-related differentially expressed genes by datasets of glioma in the GEO and TCGA databases. Ferroptosis is a newly recognized process of cell death playing a vital role in cancer biology. Pearson correlation coefficient were used to discovery the prognosis-related genes which have the highest correlation with ferroptosis. Matrix remodeling-associated protein 8 (MXRA8) was identified as a novel prognosis indicator which may be involved in ferroptosis. The expression of MXRA8 was significantly higher in glioma compared with normal brain tissue, and increased expression of MXRA8 was associated with unfavorable survivals. Furthermore, in vitro analysis showed that knockdown of MXRA8 inhibited the cell viability in T98G and U251 cells and increased the sensitivity of glioma cells to temozolomide. We further observed that downregulation of MXRA8 elevated the levels of intracellular ferrous iron and lipid peroxidation, accompanied by upregulation of NCOA4 and suppression of FTH1. Moreover, co-expression analyses showed that GO term and KEGG pathways were mainly enriched in immunity-related pathways, such as neutrophil-related immunity, adaptive immune response, and cytokine binding. Through ssGSEA algorithm and TISIDB database, immunological analyses showed that MXRA8 was significantly correlated with various immune infiltration cells including NK cells, macrophages, and neutrophils. Meanwhile, MXRA8 was also associated with chemokines and multiple immunoinhibitory molecules, such as TGF-β1, IL-10, PD-L1, and CTLA4. We also found that MXRA8 was positively associated with immune infiltration score, and patients with higher immune score underwent worse overall survivals. Moreover, IHC staining indicated a highly positive correlation of MXRA8 with a macrophage marker CSF1R. The co-cultured models of glioma cells and M2 macrophages showed MXRA8 knockdown glioma cells alleviated the infiltration of M2 macrophage, while the reduced M2 macrophage infiltration generated by MXRA8 could be rescued by Fer-1 treatment. These results suggest that MXRA8 promotes glioma progression and highlight the pivotal role of MXRA8 in ferroptosis and immune microenvironment of glioma. Therefore, MXRA8 may serve as a novel prognostic marker and therapeutic target for glioma.

The 7th member of the Late Triassic Yanchang Formation is the most important Mesozoic source rocks and shale oil reservoir in the Ordos Basin. The hydrocarbon potential and organic matter enrichment mechanism of this organic-rich member are questioned because of the high heterogeneity of continental sediments. In particular, the lack of drilling in the Chang 73 sub-member of the western Ordos Basin (central Tianhuan Depression) hinders this understanding and the progress of shale oil exploration in this region. In this study, 87 samples were collected from the well DP1 in the Tianhuan Depression, western Ordos Basin, and analyzed for sedimentology and geochemistry to unravel the paleoenvironment, paleo-productivity, and hydrocarbon potential of the Chang 73 sub-member. The results show that the Chang 73 shale is characterized by ultra-high organic matter abundance (up to 10.60%), type II kerogen, and good hydrocarbon generation potential. An intermediate chemical weathering intensity suggests that this set of organic-rich shale was deposited in a warm and humid paleoclimate setting. Extreme organic matter enrichment in study area may be attributed to ultra-high productivity (hypereutrophic lake), superimposed terrigenous organic matter input, and transgression, rather than volcanism and anoxic bottom water. This model is different from those of Chang 73 interval with higher organic matter content in the central and southern parts of the Ordos Basin. Therefore, this study proposes that the Chang 73 shale in the central Tianhuan Depression is not a good target layer for shale oil exploration and that the favorable area may be located in an undisturbed deep lake with higher organic matter abundance (e.g., southwestern Ordos Basin).

COVID-19 survivors who had acute respiratory symptoms might experience prolonged post-traumatic stress disorder (PTSD) due to further rehabilitation, somatic symptoms and related distress. The conservation of resource (COR) theory is a well-developed theory to understand how people develop PTSD symptoms in traumatic events. The current study aimed to examine the potential factors of PTSD symptoms and interrelationships among this factors among COVID-19 survivors based on the COR theory. This cross-sectional telephone survey enrolled 199 COVID-19 patients (Mean age = 42.7; 53.3% females) 6 months after their hospital discharge in five Chinese cities (i.e., Wuhan, Shenzhen, Zhuhai, Dongguan, and Nanning). The results showed that 7% of participants were classified as having probable PTSD. The significant potential factors relating to PTSD symptoms included socio-demographic status, hospitalization experiences, post-hospitalization experiences, and psychological status. Besides, the proposed statistical mediation model based on the COR framework showed good model fit, χ2(df) = 17.286 (5), p = 0.004, CFI = 0.962, NNFI = 0.951, RMSEA = 0.077. Perceived resource loss/gain fully mediated the association between exposure to other patients' suffering during hospitalization and PTSD symptoms, and partially mediated the relationships from somatic symptoms/perceived impact of being infected with COVID-19 after discharge to PTSD symptoms. On the other hand, resilience was a full mediator in the relationship from ICU experience to PTSD symptoms and a partial mediator in the relationship from perceived impact to PTSD symptoms. The results provide preliminary support on applying the COR theory to understand the factors of PTSD symptoms among COVID-19 survivors. Interventions to reduce PTSD symptoms in this population can be developed based on the modifiable psychosocial mediators.

Background: Pyroptosis is a newly recognized form of cell death. Emerging evidence has suggested the crucial role of long non-coding RNAs (lncRNAs) in the tumorigenesis and progression of ovarian cancer (OC). However, there is still poor understanding of pyroptosis-related lncRNAs in OC.Methods: The TCGA database was accessed for gene expression and clinical data of 377 patients with OC. Two cohorts for training and validation were established by random allocation. Correlation analysis and Cox regression analysis were performed to identify pyroptosis-related lncRNAs and construct a risk model.Results: Six pyroptosis-related lncRNAs were included in the final signature with unfavorable survival data. Subsequent ROC curves showed promising predictive value of patient prognosis. Further multivariate regression analyses confirmed the signature as an independent risk factor in the training (HR: 2.242, 95% CI: 1.598–3.145) and validation (HR: 1.884, 95% CI: 1.204–2.95) cohorts. A signature-based nomogram was also established with a C-index of.684 (95% CI: 0.662–0.705). Involvement of the identified signature in multiple immune-related pathways was revealed by functional analysis. Moreover, the signature was also associated with higher expression of three immune checkpoints (PD-1, B7-H3, and VSIR), suggesting the potential of the signature as an indicator for OC immunotherapies.Conclusion: This study suggests that the identified pyroptosis-related lncRNA signature and signature-based nomogram may serve as methods for risk stratification of OC. The signature is also associated with the tumor immune microenvironment, potentially providing an indicator for patient selection of immunotherapy in OC.

Exosomes, the small extracellular vesicles, are released by multiple cell types, including tumor cells, and represent a novel avenue for intercellular communication via transferring diverse biomolecules. Recently, microRNAs (miRNAs) were demonstrated to be enclosed in exosomes and therefore was protected from degradation. Such exosomal miRNAs can be transmitted to recipient cells where they could regulate multiple cancer-associated biological processes. Accumulative evidence suggests that exosomal miRNAs serve essential roles in modifying the glioma immune microenvironment and potentially affecting the malignant behaviors and therapeutic responses. As exosomal miRNAs are detectable in almost all kinds of biofluids and correlated with clinicopathological characteristics of glioma, they might be served as promising biomarkers for gliomas. We reviewed the novel findings regarding the biological functions of exosomal miRNAs during glioma pathogenesis and immune regulation. Furthermore, we elaborated on their potential clinical applications as biomarkers in glioma diagnosis, prognosis and treatment response prediction. Finally, we summarized the accessible databases that can be employed for exosome-associated miRNAs identification and functional exploration of cancers, including glioma.

Background: Ovarian cancer (OV) is one of the common malignant tumors and has a poor prognosis. Chromobox (CBX) family proteins are critical components of epigenetic regulation complexes that repress target genes transcriptionally via chromatin modification. Some studies have investigated the function specifications among several CBXs members in multiple cancer types, however, little is known about the functions and prognostic roles of distinct CBXs family proteins in ovarian cancer.Methods: In this study, several bioinformatics databases and in vitro experiments were used to analyze the expression profiles, prognostic values, and therapeutic potential of the CBXs family (CBX1-8) in ovarian cancer.Results: It was found that higher expression of CBX3/8 and lower expression of CBX1/6/7 were detected in OV tissues. CBX2/4/5/8 were significantly correlated with individual cancer stages of OV. The expression of CBX1/2/3 were all significantly associated with worse overall survival (OS) and progression-free survival (PFS) for OV patients, whereas the expression of other five CBXs members showed either irrelevant (CBX5 and CBX8) or inconsistent (CBX4, CBX6, and CBX7) results for both OS and PFS in OV. These results showed that only CBX3 had consistent results in expression and prognosis. Further cell experiments also showed that CBX3 promoted the proliferation of ovarian cancer cells. CBX3 was highly expressed in chemoresistant OV tissues. These results indicated that CBX3 was the most likely prognostic indicator and new therapeutic target in OV. Furthermore, gene enrichment analysis suggests that the CBXs family was primarily involved in mast cell activation and mast cell mediated immunity. Individual CBXs members were associated with varying degrees of the infiltration of immune cells, especially B cells. Finally, a high genetic alteration rate of CBXs family (39%) was observed in OV. The low methylation status of CBX3/8 in OV may be associated with their high expression levels.Conclusions: Taken together, these findings exhibited the pivotal value of CBXs family members (especially CBX3) in the prognosis and chemoresistance of ovarian cancer. Our results may provide new insight to explore new prognostic biomarkers and therapeutic targets for ovarian cancer.

Abstract Extrachromosomal circular DNA was recently found to be particularly abundant in multiple human cancer cells, although its frequency varies among different tumor types. Elevated levels of extrachromosomal circular DNA have been considered an effective biomarker of cancer pathogenesis. Multiple reports have demonstrated that the amplification of oncogenes and therapeutic resistance genes located on extrachromosomal DNA is a frequent event that drives intratumoral genetic heterogeneity and provides a potential evolutionary advantage. This review highlights the current understanding of the extrachromosomal circular DNA present in the tissues and circulation of patients with advanced cancers and provides a detailed discussion of their substantial roles in tumor regulation. Confirming the presence of cancer-related extrachromosomal circular DNA would provide a putative testing strategy for the precision diagnosis and treatment of human malignancies in clinical practice.

Abstract Background Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulopathy worldwide. However, the molecular events underlying IgAN remain to be fully elucidated. This study aimed to identify novel biomarkers of IgAN through bioinformatics analysis and elucidate the possible molecular mechanism. Methods Based on the microarray datasets GSE93798 and GSE37460 downloaded from the Gene Expression Omnibus database, the differentially expressed genes (DEGs) between IgAN samples and normal controls were identified. Using the DEGs, we further performed a series of functional enrichment analyses. Protein–protein interaction (PPI) networks of the DEGs were constructed using the STRING online search tool and were visualized using Cytoscape. Next, hub genes were identified and the most important module among the DEGs, Biological Networks Gene Ontology tool (BiNGO), was used to elucidate the molecular mechanism of IgAN. Results In total, 148 DEGs were identified, comprising 53 upregulated genes and 95 downregulated genes. Gene Ontology (GO) analysis indicated that the DEGs for IgAN were mainly enriched in extracellular exosome, region and space, fibroblast growth factor stimulus, inflammatory response, and innate immunity. Module analysis showed that genes in the top 1 significant module of the PPI network were mainly associated with innate immune response, integrin-mediated signaling pathway and inflammatory response. The top 10 hub genes were constructed in the PPI network, which could well distinguish the IgAN and control group in monocyte and tissue samples. We finally identified the integrin subunit beta 2 (ITGB2) and Fc fragment of IgE receptor Ig (FCER1G) genes that may play important roles in the development of IgAN. Conclusions We identified key genes along with the pathways that were most closely related to IgAN initiation and progression. Our results provide a more detailed molecular mechanism for the development of IgAN and novel candidate gene targets of IgAN.

To remove the adsorbed reagent of copper–lead mixed concentrate in bulk flotation, this study investigates the removal effect of sodium sulfide (SS) through micro-flotation, adsorption tests, equilibrium speciation analysis, electrochemical analysis, and first-principle density functional theory (DFT) calculations. Micro-flotation tests demonstrate that chalcopyrite and galena recovery remarkably decline by 50% and 70%, respectively, because of SS addition in a mineral–butyl xanthate (BX) flotation system. Meanwhile, adsorption tests reveal that with the addition of SS, the adsorption density of BX onto the surfaces of chalcopyrite and galena decrease to 0.0008 and 0.001 mg/g, respectively. These findings indicate that BX on the mineral surface almost completely desorbs. Electrochemical tests further show that in the BX–mineral system, combined with the oxidation peak, BX and mineral react to form CuX2/PbX2. After adding sodium sulfide, the above peak does not appear, indicating that BX does not react with minerals because of the effect of SS. The first-principle calculations based on the DFT further reveals the competitive adsorption mechanism between SS and BX on chalcopyrite (001) and galena (100) surface, thereby demonstrating the significant performance of SS as a removing reagent.

With the development of computer vision and mobile computing, assistive navigation for people with visual impairment arouses the attention of research communities. As two key challenges of assistive navigation, “Where am I?” and “What are the surroundings?” are still to be resolved by taking advantage of visual information. In this paper, we leverage the prevailing compact network as the backbone to build a unified network featuring two branches that implement scene description and scene recognition separately. Based on the unified network, the proposed pipeline performs scene recognition and visual localization simultaneously in the scenario of assistive navigation. The visual localization pipeline involves image retrieval and sequence matching. In the experiments, different configurations of the proposed pipeline are tested on public datasets to search for the optimal parameters. Moreover, on the real-world datasets captured by the wearable assistive device, the proposed assistive navigation pipeline is proved to achieve satisfactory performance. On the challenging dataset, the top-5 precision of scene recognition is more than 80%, and the visual localization precision is over 60% under a recall of 60%. The related codes and datasets are open-source online at https://github.com/chengricky/ScenePlaceRecognition.

Ovarian cancer (OC) is typically diagnosed at an advanced stage and poses a significant challenge to treatment and recovery. Rencently, Adenosine deaminase RNA-specific B1 (ADARB1), an adenosine-to-inosine (A-to-I) RNA-editing enzyme, has been found to play an essential role in the development of cancer. However, the specific function of ADARB1 in ovarian cancer is still not fully understood. Here, we investigated the effects of ADARB1 on OC biology. By conducting bioinformatics analyses of several public databases, we found significantly decreased ADARB1 expression in OC cells and tissues. Moreover, RT-PCR and western blot showed lower ADARB1 expression in OVCAR3, HO8910pm and A2780 OC cells compared to human normal ovarian epithelial cell IOSE. Cell proliferation assay and clone formation assay showed that overexpression of ADARB1 (ADARB1-OE) inhibited the proliferation of tumor cells. Wound healing and transwell assay indicated that ADARB1-OE could suppress OC cell invasion and metastasis. Kaplan-Meier methods revealed that the patients with low level of ADARB1 displayed poor prognosis. TISIDB databases were further used to analyze the roles of ADARB1 in tumor-immune system interactions in OC patients. Furthermore, ADARB1-OE down-regulated the expression of phosphorylated AKT. Combination of ADARB1-OE and AKT inhibitor MK2206 exerted stronger cell growth inhibition. Thus, our investigation demonstrated that low levels of ADARB1 might be a potential target in the tumorigenesis and prognostic evaluation of OC patients.

Background Understanding factors associated with post-discharge sleep quality among COVID-19 survivors is important for intervention development. Aims This study investigated sleep quality and its correlates among COVID-19 patients 6 months after their most recent hospital discharge. Method Healthcare providers at hospitals located in five different Chinese cities contacted adult COVID-19 patients discharged between 1 February and 30 March 2020. A total of 199 eligible patients provided verbal informed consent and completed the interview. Using score on the single-item Sleep Quality Scale as the dependent variable, multiple linear regression models were fitted. Results Among all participants, 10.1% reported terrible or poor sleep quality, and 26.6% reported fair sleep quality, 26.1% reported worse sleep quality when comparing their current status with the time before COVID-19, and 33.7% were bothered by a sleeping disorder in the past 2 weeks. After adjusting for significant background characteristics, factors associated with sleep quality included witnessing the suffering (adjusted B = −1.15, 95% CI = −1.70, −0.33) or death (adjusted B = −1.55, 95% CI = −2.62, −0.49) of other COVID-19 patients during hospital stay, depressive symptoms (adjusted B = −0.26, 95% CI = −0.31, −0.20), anxiety symptoms (adjusted B = −0.25, 95% CI = −0.33, −0.17), post-traumatic stress disorders (adjusted B = −0.16, 95% CI = −0.22, −0.10) and social support (adjusted B = 0.07, 95% CI = 0.04, 0.10). Conclusions COVID-19 survivors reported poor sleep quality. Interventions and support services to improve sleep quality should be provided to COVID-19 survivors during their hospital stay and after hospital discharge.

Ferroptosis, a distinct type of regulated cell death, has been reported to be involved in the tumorigenesis of liver hepatocellular carcinoma (LIHC). However, the precise functions and potential mechanisms of ferroptosis in LIHC were still poorly understood. Herein, we investigated the biological roles of ferroptosis-related gene STEAP3 in LIHC. STEAP3 was previously proved to serve a key regulator in ferroptosis via mediating the iron metabolism. Comprehensive bioinformatics from several databases revealed that STEAP3 was significantly downregulated in LIHC tissues and exhibited the favorable prognostic significance in LIHC patients. The downregulated STEAP3 was further confirmed in two LIHC cells Huh7 and MHCC97H using real-time PCR and western blot. And STEAP3 overexpression significantly inhibited the cell proliferation in Huh7 and MHCC97H cells. In addition, clinical data identified the relationship between STEAP3 expression and several clinicopathological parameters of LIHC patients, including histologic grade, alpha fetal protein (AFP) concentration, etc. Receiver operation characteristic (ROC) curve revealed STEAP3 as a potential diagnostic biomarker for LIHC patients. Moreover, the co-expression network of STEAP3 was explored to gain a better insight into its underlying signaling pathways. Finally, aberrant STEAP3 might participate in varieties of immune-associated signatures in LIHC pathogenesis, including immunostimulators, immunoinhibitors, chemokines, and chemokine receptors. Taken together, these findings could enhance our knowledge regarding the inhibitory roles and underlying biological significance of STEAP3 in LIHC tumorigenesis.

Alantolactone (ALT) is a natural compound extracted from Chinese traditional medicine Inula helenium L. with therapeutic potential in the treatment of various diseases. Recently, in vitro and in vivo studies have indicated cytotoxic effects of ALT on various cancers, including liver cancer, colorectal cancer, breast cancer, etc. The inhibitory effects of ALT depend on several cancer-associated signaling pathways and abnormal regulatory factors in cancer cells. Moreover, emerging studies have reported several promising strategies to enhance the oral bioavailability of ALT, such as combining ALT with other herbs and using ALT-entrapped nanostructured carriers. In this review, studies on the anti-tumor roles of ALT are mainly summarized, and the underlying molecular mechanisms of ALT exerting anticancer effects on cells investigated in animal-based studies are also discussed.

Exosomes are nanovesicles secreted into biofluids by various cell types and have been implicated in different physiological and pathological processes. Interestingly, a plethora of studies emphasized the mediating role of exosomes in the bidirectional communication between donor and recipient cells. Among the various cargoes of exosomes, long non-coding RNAs (lncRNAs) have been identified as crucial regulators between cancer cells and immune cells in the tumor microenvironment (TME) that can interfere with innate and adaptive immune responses to affect the therapeutic efficiency. Recently, a few major studies have focused on the exosomal lncRNA-mediated interaction between cancer cells and immune cells infiltrated into TME. Nevertheless, a dearth of studies pertains to the immune regulating role of exosomal lncRNAs in cancer and is still in the early stages. Comprehensive mechanisms of exosomal lncRNAs in tumor immunity are not well understood. Herein, we provide an overview of the immunomodulatory function of exosomal lncRNAs in cancer and treatment resistance. In addition, we also summarize the potential therapeutic strategies toward exosomal lncRNAs in TME.

Metastatic bone diseases are common in the advanced stage of numerous cancers, but rarely reported to be secondary from penile cancer. To date, there are only 9 cases of skeletal metastasis from penile cancer reported in literature worldwide. Herein, we report a rare case of the femoral neck metastasis secondary from penile carcinoma in a 35-year-old Chinese male. Based on the case study and more importantly, the literature review, we attempted to identify the clinical features of the metastatic bone diseases secondary from penile cancer.