Inorganic-Organic Dual-Ligand-Regulated Photocatalysis of CdS@ZnxCd1-xS@ZnS Quantum Dots for Lignin Valorization.

In a dual-functional lignin valorization system, a harmonious oxidation and reduction rate is a prerequisite for high photocatalytic performance. Herein, an efficient and facile ligand manipulating strategy to balance the redox reaction process is exploited via decorating the surface of the CdS@ZnxCd1-xS@ZnS gradient-alloyed quantum dots with both inorganic ligands of hexafluorophosphate (PF6-) and organic ligands of mercaptopropionic acid (MPA). Inorganic ion ligands in this system provide a promotion for intermediator reduction reactions. By optimizing the ligand composition on the quantum dot surface, we achieve precise control over the extent of oxidation and reduction, enabling selective modification of reaction products; that is, the conversion rate of 2-phenoxy-1-phenylethanol reached 99%. Surface engineering by regulating the ligand type demonstrates that PF6- and thiocyanate (SCN-) inorganic ion ligands contribute significantly toward electron transfer, while MPA ligands have beneficial effects on the hole-transfer procedure, which is predominantly dependent on their steric hindrance, electrostatic action, and passivation effect. The present study offers insights into the development of efficient quantum dot photocatalysts for dual-functional biomass valorization through ligand design.

Grating-based x-ray dark-field CT for lung cancer diagnosis in mice.

BACKGROUND: The low absorption of x-rays in lung tissue and the poor resolution of conventional computed tomography (CT) limits its use to detect lung disease. However, x-ray dark-field imaging can sense the scattered x-rays deflected by the structures being imaged. This technique can facilitate the detection of small alveolar lesions that would be difficult to detect with conventional CT. Therefore, it may provide an alternative imaging modality to diagnose lung disease at an early stage. METHODS: Eight mice were inoculated with lung cancers simultaneously. Each time two mice were scanned using a grating-based dark-field CT on days 4, 8, 12, and 16 after the introduction of the cancer cells. The detectability index was calculated between nodules and healthy parenchyma for both attenuation and dark-field modalities. High-resolution micro-CT and pathological examinations were used to crosscheck and validate our results. Paired t-test was used for comparing the ability of dark-field and attenuation modalities in pulmonary nodule detection. RESULTS: The nodules were shown as a signal decrease in the dark-field modality and a signal increase in the attenuation modality. The number of nodules increased from day 8 to day 16, indicating disease progression. The detectability indices of dark-field modality were higher than those of attenuation modality (p = 0.025). CONCLUSIONS: Compared with the standard attenuation CT, the dark-field CT improved the detection of lung nodules. RELEVANCE STATEMENT: Dark-field CT has a higher detectability index than conventional attenuation CT in lung nodule detection. This technique could improve the early diagnosis of lung cancer. KEY POINTS: • Lung cancer progression was observed using x-ray dark-field CT. • Dark-field modality complements with attenuation modality in lung nodule detection. • Dark-field modality showed a detectability index higher than that attenuation in nodule detection.

Effect of intra-operative chemotherapy with 5-fluorouracil and leucovorin on the survival of patients with colorectal cancer after radical surgery: a retrospective cohort study.

BACKGROUND: The effect of intra-operative chemotherapy (IOC) on the long-term survival of patients with colorectal cancer (CRC) remains unclear. In this study, we evaluated the independent effect of intra-operative infusion of 5-fluorouracil in combination with calcium folinate on the survival of CRC patients following radical resection. METHODS: 1820 patients were recruited, and 1263 received IOC and 557 did not. Clinical and demographic data were collected, including overall survival (OS), clinicopathological features, and treatment strategies. Risk factors for IOC-related deaths were identified using multivariate Cox proportional hazards models. A regression model was developed to analyze the independent effects of IOC. RESULTS: Proportional hazard regression analysis showed that IOC (hazard ratio [HR]=0.53, 95% confidence intervals [CI] [0.43, 0.65], P  < 0.001) was a protective factor for the survival of patients. The mean overall survival time in IOC group was 82.50 (95% CI [80.52, 84.49]) months, and 71.21 (95% CI [67.92, 74.50]) months in non-IOC group. The OS in IOC-treated patients were significantly higher than non-IOC-treated patients ( P  < 0.001, log-rank test). Further analysis revealed that IOC decreased the risk of death in patients with CRC in a non-adjusted model (HR=0.53, 95% CI [0.43, 0.65], P  < 0.001), model 2 (adjusted for age and gender, HR=0.52, 95% CI [0.43, 0.64], P  < 0.001), and model 3 (adjusted for all factors, 95% CI 0.71 [0.55, 0.90], P  = 0.006). The subgroup analysis showed that the HR for the effect of IOC on survival was lower in patients with stage II (HR = 0.46, 95% CI [0.31, 0.67]) or III disease (HR=0.59, 95% CI [0.45, 0.76]), regardless of pre-operative radiotherapy (HR=0.55, 95% CI [0.45, 0.68]) or pre-operative chemotherapy (HR=0.54, 95% CI [0.44, 0.66]). CONCLUSIONS: IOC is an independent factor that influences the survival of CRC patients. It improved the OS of patients with stages II and III CRC after radical surgery. TRIAL REGISTRATION: chictr.org.cn, ChiCTR 2100043775.

Nomogram for benign anastomotic stricture after surgery for rectal cancer.

BACKGROUND: Benign anastomotic stricture remains among the most prevalent complications following surgery for rectal cancer. OBJECTIVE: This study is aimed at identifying risk factors of anastomotic stricture as well as generating an effective nomogram for the stricture. METHODS: Design: This is a retrospective study. SETTING: This study was conducted from January 2015 to December 2019 in a single tertiary center for rectal cancer. PATIENTS: A total of 117 rectal cancer patients after surgery without recurrence were enrolled in this study, of which 39 with anastomotic stricture and 78 without stricture. MAIN OUTCOME MEASURES: Their clinical and pathological data were collected. Multiple logistic regression analysis was conducted to identify risk factors for anastomotic stricture and to generate the nomogram prediction model. RESULTS: Multivariate analysis of the primary cohort led to the identification of LCA (left colic artery) preservation (OR, 0.074; P = 0.0015), protective stoma (OR, 5.353; P = 0.012), anastomotic leakage (OR, 12.027; P = 0.005), and anastomotic distance (OR, 7.578; P = 0.012) as independent risk factors for anastomotic stricture. The following predictive model was derived: Logit (anastomotic stricture) = 0.074∗ LCA + 5.353∗ Protective stoma +12.027∗ Anastomotic leakage + 7.578∗ Anastomotic distance. Assessment of the predictive model revealed that the area under the curve (AUC) was 0.871, while the cutoff value was 15.444 with a sensitivity of 64.1% and a specificity of 94.8%. LIMITATIONS: The main limitation is the research design of a retrospective and case-controlled study with a small sample size from a single center. CONCLUSIONS: LCA preservation, protective stoma, anastomotic leakage, and anastomotic distance may affect the occurrence of anastomotic stricture following surgery for rectal cancer. The nomogram model generated in the present study can be valuable in the prediction of anastomotic stricture. This study has been registered at the Chinese Clinical Trial Registry (http://www.chictr.org.cn/, ChiCTR 2100043775).

Enhancing photoelectrochemical CO2 reduction with silicon photonic crystals.

The effectiveness of silicon (Si) and silicon-based materials in catalyzing photoelectrochemistry (PEC) CO2 reduction is limited by poor visible light absorption. In this study, we prepared two-dimensional (2D) silicon-based photonic crystals (SiPCs) with circular dielectric pillars arranged in a square array to amplify the absorption of light within the wavelength of approximately 450 nm. By investigating five sets of n + p SiPCs with varying dielectric pillar sizes and periodicity while maintaining consistent filling ratios, our findings showed improved photocurrent densities and a notable shift in product selectivity towards CH4 (around 25% Faradaic Efficiency). Additionally, we integrated platinum nanoparticles, which further enhanced the photocurrent without impacting the enhanced light absorption effect of SiPCs. These results not only validate the crucial role of SiPCs in enhancing light absorption and improving PEC performance but also suggest a promising approach towards efficient and selective PEC CO2 reduction.

Carbon Quantum Dots Bridged TiO2/CdIn2S4 toward Photocatalytic Upgrading of Polycyclic Aromatic Hydrocarbons to Benzaldehyde.

Conversion of hazardous compounds to value-added chemicals using clean energy possesses massive industrial interest. This applies especially to the hazardous compounds that are frequently released in daily life. In this work, a S-scheme photocatalyst is optimized by rational loading of carbon quantum dots (CQDs) during the synthetic process. As a bridge, the presence of CQDs between TiO2 and CdIn2S4 improves the electron extraction from TiO2 and supports the charge transport in S-scheme. Thanks to this, the TiO2/CQDs/CdIn2S4 presents outstanding photoactivity in converting the polycyclic aromatic hydrocarbons (PAHs) released by cigarette to value-added benzaldehyde. The optimized photocatalyst performs 87.79% conversion rate and 72.76% selectivity in 1 h reaction under a simulated solar source, as confirmed by FT-IR and GC-MS. A combination of experiments and theoretical calculations are conducted to demonstrate the role of CQDs in TiO2/CQDs/CdIn2S4 toward photocatalysis.

Iterative signal retrieval for X-ray grating interferometry with dual-shot.

BACKGROUND: X-ray grating interferometry normally requires multiple steps and exposures, causing a prolonged imaging time. There is motivation to use fewer steps to reduce scanning time and complexity, while keeping fidelity of the retrieved signals. OBJECTIVE: We propose an iterative signal retrieval method, extracting attenuation, dark field contrast (DFC), and differential phase contrast (DPC) signals from two X-ray exposures. METHODS: Two shots were captured at G2 grating positions with difference of 1/4 grating period. The algorithm consists of two stages. At the first stage, amplitude of sample phase stepping curve retrieved by virtual phase stepping (VPS) method, visibility and local phase of background phase stepping curve are used to limit the results to the proximity of the ground truth. After the second stage, three high-quality parameters, amplitude, visibility, and local phase, are retrieved through finetuning, and three signals are calculated. Simulated and real-sample experiments were conducted to validate this method. RESULTS: We used standard phase stepping result as benchmark and calculated structural similarity (SSIM) and peak signal-to-noise ratio (PSNR) between benchmark and parameters retrieved by our dual-shot method and virtual phase stepping (VPS) method. For both simulated and real-sample experiments, the SSIM and PSNR value of dual-shot method are higher than those of VPS method. For real-sample method, we also conducted a three-step PS, and the SSIM and PSNR value of dual-shot method are slightly lower than those of three-step PS. CONCLUSION: Using our dual-shot method demonstrates higher performance than other single-shot method in retrieving high-quality signals, and it also reduces radiation dose and time.

MYL2 as a potential predictive biomarker for rhabdomyosarcoma.

ABSTRACT: Rhabdomyosarcoma (RMS) is a common malignant soft tissue sarcoma, which is the third most common soft tissue sarcoma after malignant fibrohistoma and liposarcoma. The discovery of potential postbiomarkers could lead to early and more effective treatment measures to reduce the mortality of RMS. The discovery of biomarker is expected to be the direction of targeted therapy, providing a new direction for the precise treatment of RMS.Gene Expression Omnibus database was used to download the tow gene profiles, GSE28511 and GSE135517. GEO2R was applied to identify differently expressed genes (DEGs) between RMS and normal group. Database for Annotation, Visualization and Integrated Discovery and Metascape can perform the enrichment analysis for the DEGs. Protein-protein interaction network was constructed, and the hub genes was identified by the Cytoscape. Expression and overall survival analysis of hub genes were performed.A total of 15 common DEGs were screened between RMS and normal tissues. The enrichment analysis here showed that the DEGs mainly enriched in the muscle filament sliding, myofibril, protein complex, sarcomere, myosin complex, nuclear chromosome, and tight junction. The 6 hub genes (DNA Topoisomerase II Alpha, Insulin Like Growth Factor 2, HIST1H4C, Cardiomyopathy Associated 5, Myosin Light Chain 2 [MYL2], Myosin Heavy Chain 2) were identified. Compared with the normal tissues, MYL2 were down-regulated in the RMS tissues. RMS patients with low expression level of MYL2 had poorer overall survival times than those with high expression levels (P < .05).In summary, lower expression of MYL2 was 1 prediction for poor prognosis of RMS. MYL2 is hope to be the target of therapy, which leads to more effective treatment and reduces the mortality rate of RMS.

Bioinformatics analysis and verification of gene targets for renal clear cell carcinoma.

BACKGROUND: It is estimated that there are 338,000 new renal-cell carcinoma releases every year in the world. Renal cell carcinoma (RCC) is a heterogeneous tumor, of which more than 70% is clear cell renal cell carcinoma (ccRCC). It is estimated that about 30% of new renal-cell carcinoma patients have metastases at the time of diagnosis. However, the pathogenesis of renal clear cell carcinoma has not been elucidated. Therefore, it is necessary to further study the pathogenesis of ccRCC. METHODS: Two expression profiling datasets (GSE68417, GSE71963) were downloaded from the GEO database. Differentially expressed genes (DEGs) between ccRCC and normal tissue samples were identified by GEO2R. Functional enrichment analysis was made by the DAVID tool. Protein-protein interaction (PPI) network was constructed. The hub genes were excavated. The clustering analysis of expression level of hub genes was performed by UCSC (University of California Santa Cruz) Xena database. The hub gene on overall survival rate (OS) in patients with ccRCC was performed by Kaplan-Meier Plotter. Finally, we used the ccRCC renal tissue samples to verify the hub genes. RESULTS: 1182 common DEGs between the two datasets were identified. The results of GO and KEGG analysis revealed that variations in were predominantly enriched in intracellular signaling cascade, oxidation reduction, intrinsic to membrane, integral to membrane, nucleoside binding, purine nucleoside binding, pathways in cancer, focal adhesion, cell adhesion molecules. 10 hub genes ITGAX, CD86, LY86, TLR2, TYROBP, FCGR2A, FCGR2B, PTPRC, ITGB2, ITGAM were identified. FCGR2B and TYROBP were negatively correlated with the overall survival rate in patients with ccRCC (P < 0.05). RT-qPCR analysis showed that the relative expression levels of CD86, FCGR2A, FCGR2B, TYROBP, LY86, and TLR2 were significantly higher in ccRCC samples, compared with the adjacent renal tissue groups. CONCLUSIONS: In summary, bioinformatics technology could be a useful tool to predict the progression of ccRCC. In addition, there are DEGs between ccRCC tumor tissue and normal renal tissue, and these DEGs might be considered as biomarkers for ccRCC.

Identification of Autophagy-Related Genes and Small-Molecule Drugs in Esophageal Carcinoma.

BACKGROUND Esophageal carcinoma (ESCA) is associated with a poor prognosis and high mortality rate. Autophagy plays important roles in promoting or suppressing tumor cell survival at different stages of cancer development. However, the roles of autophagy-related genes (ARGs) during ESCA progression and in patient prognosis remain unclear. Accordingly, in this study, we aimed to identify the relationships of ARGs with ESCA progression and patient prognosis. MATERIAL AND METHODS Clinicopathological information for patients with ESCA was downloaded from The Cancer Genome Atlas (TCGA) database. Transcriptome expression profiles were downloaded from TCGA and GTEx databases, and ARGs were downloaded from the Human Autophagy Database. We investigated the functions of ARGs by bioinformatics analysis. Moreover, statistical analysis of these genes was performed to identify independent prognostic markers. RESULTS Differentially expressed genes between normal and tumor tissues were detected and identified. GO and KEGG analyses of differentially expressed ARGs were performed. Moreover, we derived a risk signature based on the identified independent prognostic markers. The identified genes also could predict the clinicopathological features of ESCA. CONCLUSIONS ARGs were key participants in the tumorigenesis and development of ESCA. Our findings may be useful for developing improved therapeutic approaches for ESCA.

5-aza-2'-deoxycytidine (DAC) treatment induces the MAGE-A10 expression and improves the cytotoxicity of MAGE-A10-specific CTLs in lung cancer cells.

BACKGROUND: MAGE-A10 is a subtype of the Melanoma-associated antigen A (MAGE-A), a class of tumor antigens that are extensively expressed in various histological types of tumors and represents an attractive target for tumor immunotherapy. Epigenetic-modifying drugs can enhance the expression of tumor antigens and improve the cytotoxicity of antigen-specific T cells. 5-aza-2'-deoxycytidine (DAC), a DNA methyltransferase inhibitor (DNMTI) considered an epigenetic-modifying drug, could enhance the expression of MAGE-A10 in cancer cells. METHODS: Human lung cancer cell lines (H1975 and A549) and primary lung cancer cells (L228, L329 and L419) were used. 5-aza-2'-deoxycytidine was used to induce the expression of MAGE-A10 in tumor cells. MAGE-A10 antigenic peptide (sequence: SLLKFLAKV) was used to induce differentiation of MAGE-A10-specific cytotoxic T lymphocytes (CTLs). Interferon-γ release assay was used to detect the capacity of MAGE-A10 peptide to induce CTLs. Cell Counting Kit-8 (CCK-8) analysis was performed to detect the cytotoxicity of MAGE-A10-specific CTLs. Real-time PCR and western blot analysis was used to detect the mRNA and protein levels, respectively. Immunohistochemistry was performed to detect the protein expression in cancer and adjacent normal tissue. Kaplan-Meier plotter online database was used to analyze the overall survival (OS), post-progression survival (PPS), and first progression (FP). RESULTS: The lysis rate of MAGE-A10-specific CTLs in L419 and H1975 were found to be 65.9% and 80.5%, respectively. Both L419 and H1975 showed significantly higher lysis rate in group 1 than in group 3 (6.7, 26.7%), group 2 (0, 0%) and group 4 (0, 0%) (P=0.0003, P≤0.0001, P≤0.0001, respectively). Online data mining using Kaplan-Meier plotter suggested that high expression of MAGE-A10 was significantly and negatively associated with OS (Plogrank =2.1e-05) and PPS (Plogrank =0.0057), and FP (Plogrank =3.2e-12). CONCLUSIONS: High-level expression of MAGE-A10 improved the anti-tumor immune cytotoxicity of MAGE-A10-specific CTLs in lung cancer cell lines and primary lung cancer cells. However, MAGE-A10 gene expression was negatively associated with prognosis according to the survival analysis. Thus, we hypothesize that high-level of MAGE-A10 expression in vivo may inhibit the differentiation of MAGE-A10-specific CTLs.

Identification of an individualized autophagy prognostic index in clear cell renal cell carcinoma patients.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer. ccRCC arises from the proximal tubular epithelium and is associated with high mortality. Autophagy may either promote or suppress tumor cell survival at different stages of cancer development. It is essential to investigate the association between autophagy-related genes (ARGs) and prognosis in ccRCC patients. We used datasets obtained from The Cancer Genome Atlas (TCGA) database to identify the expression level of ARGs in ccRCC patients. Functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using Metascape database. Hub genes were identified by Cytoscape software. We constructed a Cox proportional hazard regression model to identify hub genes that are significantly associated with overall survival (OS) in ccRCC patients. Subsequently, a prognostic index (PI) was calculated and ccRCC patients were stratified into high-risk and low-risk groups based on a median PI value. Our study detected several altered ARGs in ccRCC, which could be a useful prognostic tool in ccRCC patients.

Screening and Identification of Key Biomarkers in Pancreatic Cancer: Evidence from Bioinformatic Analysis.

Pancreatic cancer (PC) whose mortality is comparable to morbidity is a highly fatal disease. Early approaches of diagnosis and treatment for PC are quite limited, so it is of great urgency to figure out the exact tumorigenesis and development mechanism of PC. To identify the related molecular markers of pancreatic oncogenesis, we downloaded three microarray datasets (GSE63111, GSE101448, and GSE107610) from Gene Expression Omnibus (GEO) database. The common differentially expressed genes (DEGs) among them were identified, and the corresponding function enrichment analyses were accomplished. The protein-protein interaction network was conducted by Search Tool for the Retrieval of Interacting Genes (STRING), and the corresponding module analysis was accomplished by Cytoscape. There were 55 DEGs found in total. The molecular function and biological processes (BP) of these DEGs mainly include cytokinesis, mitotic nuclear division, cell division, cell proliferation, microtubule-based movement, and mineral absorption. Among the 55 DEGs, 14 hub genes were further confirmed and it was concluded that they mainly function in mitotic cytokinesis, microtubule-based movement, mitotic chromosome condensation, and mitotic spindle assembly from the BP analysis. The survival analysis showed that all the 14 hub genes, especially nucleolar and spindle associated protein 1 and abnormal spindle microtubule assembly, may involve in the tumorigenesis and development of PC. And they might be used as new biomarkers for auxiliary diagnosis and potential targets for immunotherapy of PC.

Identification of Key Biomarkers and Potential Molecular Mechanisms in Oral Squamous Cell Carcinoma by Bioinformatics Analysis.

The aim of this study was to explore the key genes, microRNA (miRNA), and the pathogenesis of oral squamous cell carcinoma (OSCC) at the molecular level through the analysis of bioinformatics, which could provide a theoretical basis for the screening of drug targets. Data of OSCC were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified via GEO2R analysis. Next, protein-protein interaction (PPI) network of DEGs was constructed through Search Tool for the Retrieval of Interacting Gene and visualized via Cytoscape, whereas the hub genes were screened out with Cytoscape. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by Database for Annotation, Visualization and Integrated Discovery. The miRNA, which might regulate hub genes, were screened out with TargetScan and GO and KEGG analysis of miRNA was performed by DNA Intelligent Analysis-miRPath. Survival analyses of DEGs were conducted via the Kaplan-Meier plotter. Finally, the relationships between gene products and tumors were analyzed by Comparative Toxicogenomics Database. A total of 121 differential genes were identified. One hundred thirty-five GO terms and 56 pathways were obtained, which were mainly related to PI3K-Akt signals pathway, FoxO signaling pathway, Wnt signaling pathway, cell cycle, p53 signaling pathway, cellular senescence, and other pathways; 10 genes were identified as hub genes through modules analyses in the PPI network. Finally, a survival analysis of 10 hub genes was conducted, which showed that the low expression of matrix metalloproteinase (MMP)1, MMP3, and C-X-C motif chemokine ligand (CXCL)1 and the high expression of CXCL9 and CXCL10 resulted in a significantly poor 5-year overall survival rate in patients with OSCC. In this study, the DEGs of OSCC was analyzed, which assists us in a systematic understanding of the pathogenicity underlying occurrence and development of OSCC. The MMP1, MMP3, CXCL1, CXCL9, and CXCL10 genes might be used as potential targets to improve diagnosis and as immunotherapy biomarkers for OSCC.

Identification of Key Biomarkers and Potential Molecular Mechanisms in Renal Cell Carcinoma by Bioinformatics Analysis.

Renal cell carcinoma (RCC) is the most common form of kidney cancer, caused by renal epithelial cells. RCC remains to be a challenging public health problem worldwide. Metastases that are resistant to radiotherapy and chemotherapy are the major cause of death from cancer. However, the underlying molecular mechanism regulating the metastasis of RCC is poorly known. Publicly available databases of RCC were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using GEO2R analysis, whereas the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by Gene Set Enrichment Analysis (GSEA) and Metascape. Protein-protein interaction (PPI) network of DEGs was analyzed by STRING online database, and Cytoscape software was used for visualizing PPI network. Survival analysis of hub genes was conducted using GEPIA online database. The expression levels of hub genes were investigated from The Human Protein Atlas online database and GEPIA online database. Finally, the comparative toxicogenomics database (CTD; http://ctdbase.org) was used to identify hub genes associated with tumor or metastasis. We identified 229 DEGs comprising 135 downregulated genes and 94 upregulated genes. Functional analysis revealed that these DEGs were associates with cell recognition, regulation of immune, negative regulation of adaptive immune response, and other functions. And these DEGs mainly related to P53 signaling pathway, cytokine-cytokine receptor interaction, Natural killer cell mediated cytotoxicity, and other pathways are involved. Ten genes were identified as hub genes through module analyses in the PPI network. Finally, survival analysis of 10 hub genes was conducted, which showed that the MMP2 (matrix metallo peptidase 2), DCN, COL4A1, CASR (calcium sensing receptor), GPR4 (G protein-coupled receptor 4), UTS2 (urotensin 2), and LDLR (low density lipoprotein receptor) genes were significant for survival. In this study, the DEGs between RCC and metastatic RCC were analyzed, which assist us in systematically understanding the pathogeny underlying metastasis of RCC. The MMP2, DCN, COL4A1, CASR, GPR4, UTS2, and LDLR genes might be used as potential targets to improve diagnosis and immunotherapy biomarkers for RCC.

Spatial Navigation and the Central Complex: Sensory Acquisition, Orientation, and Motor Control.

Cockroaches are scavengers that forage through dark, maze-like environments. Like other foraging animals, for instance rats, they must continually asses their situation to keep track of targets and negotiate barriers. While navigating a complex environment, all animals need to integrate sensory information in order to produce appropriate motor commands. The integrated sensory cues can be used to provide the animal with an environmental and contextual reference frame for the behavior. To successfully reach a goal location, navigational cues continuously derived from sensory inputs have to be utilized in the spatial guidance of motor commands. The sensory processes, contextual and spatial mechanisms, and motor outputs contributing to navigation have been heavily studied in rats. In contrast, many insect studies focused on the sensory and/or motor components of navigation, and our knowledge of the abstract representation of environmental context and spatial information in the insect brain is relatively limited. Recent reports from several laboratories have explored the role of the central complex (CX), a sensorimotor region of the insect brain, in navigational processes by recording the activity of CX neurons in freely-moving insects and in more constrained, experimenter-controlled situations. The results of these studies indicate that the CX participates in processing the temporal and spatial components of sensory cues, and utilizes these cues in creating an internal representation of orientation and context, while also directing motor control. Although these studies led to a better understanding of the CX's role in insect navigation, there are still major voids in the literature regarding the underlying mechanisms and brain regions involved in spatial navigation. The main goal of this review is to place the above listed findings in the wider context of animal navigation by providing an overview of the neural mechanisms of navigation in rats and summarizing and comparing our current knowledge on the CX's role in insect navigation to these processes. By doing so, we aimed to highlight some of the missing puzzle pieces in insect navigation and provide a different perspective for future directions.

Central-complex control of movement in the freely walking cockroach.

To navigate in the world, an animal's brain must produce commands to move, change direction, and negotiate obstacles. In the insect brain, the central complex integrates multiple forms of sensory information and guides locomotion during behaviors such as foraging, climbing over barriers, and navigating to memorized locations. These roles suggest that the central complex influences motor commands, directing the appropriate movement within the current context. Such commands are ultimately carried out by the limbs and must therefore interact with pattern generators and reflex circuits that coordinate them. Recent studies have described how neurons of the central complex encode sensory information: neurons subdivide the space around the animal, encoding the direction or orientation of stimuli used in navigation. Does a similar central-complex code directing movement exist, and if so, how does it effect changes in the control of limbs? Recording from central-complex neurons in freely walking cockroaches (Blaberus discoidalis), we identified classes of movement-predictive cells selective for slow or fast forward walking, left or right turns, or combinations of forward and turning speeds. Stimulation through recording wires produced consistent trajectories of forward walking or turning in these animals, and those that elicited turns also altered an inter-joint reflex to a pattern resembling spontaneous turning. When an animal transitioned to climbing over an obstacle, the encoding of movement in this new context changed for a subset of cells. These results indicate that encoding of movement in the central complex participates in motor control by a distributed, flexible code targeting limb reflex circuits.

Extracellular wire tetrode recording in brain of freely walking insects.

Increasing interest in the role of brain activity in insect motor control requires that we be able to monitor neural activity while insects perform natural behavior. We previously developed a technique for implanting tetrode wires into the central complex of cockroach brains that allowed us to record activity from multiple neurons simultaneously while a tethered cockroach turned or altered walking speed. While a major advance, tethered preparations provide access to limited behaviors and often lack feedback processes that occur in freely moving animals. We now present a modified version of that technique that allows us to record from the central complex of freely moving cockroaches as they walk in an arena and deal with barriers by turning, climbing or tunneling. Coupled with high speed video and cluster cutting, we can now relate brain activity to various parameters of the movement of freely behaving insects.

Neural activity in the central complex of the cockroach brain is linked to turning behaviors.

An animal moving through complex terrain must consider sensory cues around it and alter its movements accordingly. In the arthropod brain, the central complex (CC) receives highly preprocessed sensory information and sends outputs to premotor regions, suggesting that it may play a role in the central control of oriented locomotion. We performed tetrode recordings within the CC in cockroaches walking on an air-suspended ball to examine the role of the CC in turning behaviors. When a rod was placed near the cockroach's head, the cockroach touched the rod repeatedly with one or both antennae before locomotion was initiated. Some CC units responded to self-generated antennal contact with the object, but at lower levels compared with externally imposed antennal stimulation. The neural activity of other CC units responded to locomotion. We found that some CC units showed discrete firing fields corresponding to specific locomotion states. We also found that changes in firing rate of some CC units preceded changes in turning speed in one direction but not the other. Furthermore, such biased units were located in the side of the brain ipsilateral to the direction of the turning speed they could predict. Moreover, electrical stimulation of the CC elicited or modified locomotion, and the direction of some evoked locomotion could be predicted by the response property of locomotion-predictive units near the stimulation site. Therefore, our results suggest that, at the population level, asymmetrical activity in the CC precedes and influences turning behavior.

Deciding which way to go: how do insects alter movements to negotiate barriers?

Animals must routinely deal with barriers as they move through their natural environment. These challenges require directed changes in leg movements and posture performed in the context of ever changing internal and external conditions. In particular, cockroaches use a combination of tactile and visual information to evaluate objects in their path in order to effectively guide their movements in complex terrain. When encountering a large block, the insect uses its antennae to evaluate the object's height then rears upward accordingly before climbing. A shelf presents a choice between climbing and tunneling that depends on how the antennae strike the shelf; tapping from above yields climbing, while tapping from below causes tunneling. However, ambient light conditions detected by the ocelli can bias that decision. Similarly, in a T-maze turning is determined by antennal contact but influenced by visual cues. These multi-sensory behaviors led us to look at the central complex as a center for sensori-motor integration within the insect brain. Visual and antennal tactile cues are processed within the central complex and, in tethered preparations, several central complex units changed firing rates in tandem with or prior to altered step frequency or turning, while stimulation through the implanted electrodes evoked these same behavioral changes. To further test for a central complex role in these decisions, we examined behavioral effects of brain lesions. Electrolytic lesions in restricted regions of the central complex generated site specific behavioral deficits. Similar changes were also found in reversible effects of procaine injections in the brain. Finally, we are examining these kinds of decisions made in a large arena that more closely matches the conditions under which cockroaches forage. Overall, our studies suggest that CC circuits may indeed influence the descending commands associated with navigational decisions, thereby making them more context dependent.