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In efforts to improve regional ecosystem service functions, coordinate land development and ecological conservation, and establish a reference for optimizing land resource allocation and policy formulation to cope with climate change, it is critical to investigate the spatial distribution of land use/cover change (LUCC) and ecosystem services (ESs) under future climate change. This study proposes a framework based on the Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP), integrating the patch-generating land use simulation (PLUS) model and the integrated valuation of ecosystem services and tradeoffs (InVEST) model to analyze the spatial agglomeration of ESs, to analyze the importance of each driving factors. The results of the study show as follows: (1) the combination of CMIP6 and PLUS models can effectively simulate land use with an overall accuracy of 0.9379. (2) In spatial correlation, ESs show good clustering in all three future scenarios, with similar distribution of cold hotspots in the SSP126 and SSP245 scenarios. Hotspots are more dispersed and cold spots are shifted to the west in the SSP585 scenario. (3) GDP is an important factor in carbon storage and habitat quality, and precipitation has a greater impact on soil retention and water production. Overall, ESs can be increased by appropriately controlling population and economic development, balancing economic development and ecological protection, promoting energy transition, maintaining ecological hotspot areas, and improving cold spot areas.

Here, a BSA/anti-CEA/Pd@Pt/MoS2-Gr/GCE electrochemical immunosensor was constructed to quantitatively detect CEA. By using graphene as a growth framework, the introduction of molybdenum disulfide (MoS2) effectively solves the problem of easy accumulation of graphene during hydrothermal reduction and self-assembly. Also, it increases the specific surface area and electrochemical performance. The core-shell Pd@Pt composite metal nanoparticles with obvious concavity on the outer surface can provide larger specific surface area, higher conductivity, more catalytic active sites, better biocompatibility, and other advantages. MoS2-Gr also solves the problem of low direct loading of precious metal nanoparticles. Applying the modification materials Pd@Pt/MoS2-Gr to the electrode, the prepared elctrochemical immunosensor has a detection limit of 0.005 pg/mL for CEA and a linear range of 0.00001–100 ng/mL; meanwhile, it shows good selectivity, reproducibility, and stability that achieve effective and accurate detection of CEA.

Wicking within woven screens has attracted considerable attention due to its important role in applications concerning phase-change heat transfer and phase separation. In the present study, horizontal spreading experiments are conducted to investigate the wicking performance of woven screens by measuring the volumetric liquid intake into the screens and the liquid propagation fronts through two perpendicular high-speed cameras. Woven screens with micro (single- and multilayer)- and nano (plain, etched, and fluoridated)-porous structures are manipulated through diffusion bonding and chemical processes. The macroscopic observation indicates the substantial enhancement of the wicking capability in multilayer structures, where the interlayer microchannels could compensate for the essential deficiency of single-layer screens by providing low-resistance flow passages. Wicking capability of water is enhanced by the hydrophilic nanograsses along the wires. Furthermore, flow mechanisms within the screens are analyzed by comparisons between apparent and saturated wicking distances. In multilayer structures, the liquid spreads along the entire cross-sectional area in etched screens, while it spreads primarily along the interlayer microchannels in plain and fluoridated screens. The influence of various fluids on the wicking behavior within the woven screens is found to be fully represented by a unique parameter that captures the effects of surface tension and dynamic viscosity in the radial flow model. This work deepens the understanding of the capillary-driven flow within the woven screens with hybrid micro-/nanoporous structures and provides guidance for the design and manufacture of highly efficient wicking structures.

Background: Tumor recurrence and metastasis lead to a poor prognosis in colorectal cancer (CRC). Necroptosis is closely related to the tumor microenvironment (TME) and affects tumor recurrence and metastasis. We aimed to stratify CRC patients according to necroptosis-related long noncoding RNAs (lncRNAs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also evaluate the efficacy of immunotherapy and guide the selection of immunotherapeutic methods. Methods: A lncRNA expression profile was collected from The Cancer Genome Atlas (TCGA). Necroptosis-related lncRNAs were identified by coexpression analysis. Cox regression analysis identified a necroptosis-related lncRNA signature. Then, the value of this signature was comprehensively and multidimensionally evaluated, and its fidelity was assessed with clinical CRC data and compared with that of six other lncRNA signatures for CRC prognosis prediction. Gene set enrichment analysis (GSEA), TME analysis and prediction of the half-maximal inhibitory concentration (IC50) were also performed according to the risk score (RS) of the signature. Results: An 8-lncRNA signature significantly associated with overall survival (OS) was constructed, and its fidelity was validated with clinical CRC data. Most of the areas under the receiver operating characteristic (ROC) curve (AUCs) for 1-, 3- and 5-year OS for this signature were higher than those for the other six lncRNA signatures. OS, disease-specific survival (DSS) and the progression-free interval (PFI) were all significantly poorer in the high-risk group. The RS of the signature showed good concordance with the predicted prognosis, with AUCs for 1-, 3- and 5-year OS of 0.79, 0.81 and 0.77, respectively. Additionally, the calibration plots for this signature combined with clinical factors could effectively improve the ability to predict OS. The RS was correlated with tumor stage, lymph node metastasis and distant metastasis. Most of the enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) terms were tumor metastasis-related pathways in the high-risk group, which showed greater infiltration of immunosuppressive cells, such as cancer-associated fibroblasts (CAFs), hematopoietic stem cells and M2 macrophages, but fewer infiltrating antitumor effector immune cells, such as CD8+ T cells and regulatory T cells (Tregs). We explored additional potential immune checkpoint genes and immunotherapeutic and chemotherapeutic drugs with relatively low IC50 values. Conclusions: We identified a signature with strong fidelity that could stably predict prognosis and might be implicated in the TME and metastasis of CRC. Furthermore, additional potential immune checkpoint genes and immunotherapeutic and chemotherapeutic drugs were explored.

Organic materials are considered to have broad application prospects in energy storage systems due to their strong designability and abundant resources. Here, we report a triquinoxalinylene derivative tribenzoquinoxaline-5,10-dione (3BQ) containing high redox potential functional groups (CO and CN) and a large number of low redox potential functional groups (unsaturated carbon). This paper uses 3BQ as the cathode and anode to assemble all-organic symmetric batteries. Since 3BQ has denser active sites and a larger conjuated system than triquinoxalinylene (3Q), the 3BQ cathode has an initial capacity of 506 mA h g−1 (Ctheo = 515 mA h g−1) at 0.2C, and the capacity of 3BQ and 3Q cathodes is 210 and 107 mA h g−1 after 300 cycles at 1C. The large conjugated system and planar structure of 3BQ inhibit its dissolution in electrolytes and accelerate the charge transfer rate, resulting in good cycle stability and rate performance for batteries. The all-organic symmetric batteries assembled with pre-lithiated 3BQ and pristine 3BQ deliver an initial capacity of 483 mA h g−1 at 0.2C, a capacity of 172 mA h g−1 after 300 cycles and an energy density of 301 W h kg−1. This work provides a strategy for the development of high-performance LIBs using organic materials as the cathode and anode.

To compare natural orifice specimen extraction surgery (NOSES) and conventional laparoscopic (LAP) surgery in treating colorectal cancer. The present authors conducted a systematic search in the PubMed, EMBASE, and Cochrane databases for randomized controlled trials (RCTs), prospective nonrandomized studies, and retrospective studies up to May 2019. We used postoperative complications as the main endpoints, and used hospital stay, time to first flatus, operative time, postoperative pain, cosmetic result, wound infections, and oncological outcomes as the secondary endpoints. Subgroup analyses were conducted according to the different specimen extraction sites (transanal and transvaginal). A sensitivity analysis was carried out to evaluate the reliability of the outcomes. RevMan5.3 software was used for statistical analysis. Twelve studies (one RCT, ten retrospective studies, and one prospective nonrandomized study) involving a total of 1437 patients (NOSES group 665 patients and LAP surgery group 772 patients) were included. Meta-analysis showed that compared with LAP surgery, NOSES resulted in a shorter hospital stay (WMD = −0.79 days; 95% CI −1.17 to −0.42; P

Deep learning (DL) is rapidly finding applications in low-dose CT image denoising. While having the potential to improve the image quality (IQ) over the filtered back projection method (FBP) and produce images quickly, performance generalizability of the data-driven DL methods is not fully understood yet. The main purpose of this work is to investigate the performance generalizability of a low-dose CT image denoising neural network in data acquired under different scan conditions, particularly relating to these three parameters: reconstruction kernel, slice thickness, and dose (noise) level. A secondary goal is to identify any underlying data property associated with the CT scan settings that might help predict the generalizability of the denoising network.We select the residual encoder-decoder convolutional neural network (REDCNN) as an example of a low-dose CT image denoising technique in this work. To study how the network generalizes on the three imaging parameters, we grouped the CT volumes in the Low-Dose Grand Challenge (LDGC) data into three pairs of training datasets according to their imaging parameters, changing only one parameter in each pair. We trained REDCNN with them to obtain six denoising models. We test each denoising model on datasets of matching and mismatching parameters with respect to its training sets regarding dose, reconstruction kernel, and slice thickness, respectively, to evaluate the denoising performance changes. Denoising performances are evaluated on patient scans, simulated phantom scans, and physical phantom scans using IQ metrics including mean-squared error (MSE), contrast-dependent modulation transfer function (MTF), pixel-level noise power spectrum (pNPS), and low-contrast lesion detectability (LCD).REDCNN had larger MSE when the testing data were different from the training data in reconstruction kernel, but no significant MSE difference when varying slice thickness in the testing data. REDCNN trained with quarter-dose data had slightly worse MSE in denoising higher-dose images than that trained with mixed-dose data (17%-80%). The MTF tests showed that REDCNN trained with the two reconstruction kernels and slice thicknesses yielded images of similar image resolution. However, REDCNN trained with mixed-dose data preserved the low-contrast resolution better compared to REDCNN trained with quarter-dose data. In the pNPS test, it was found that REDCNN trained with smooth-kernel data could not remove high-frequency noise in the test data of sharp kernel, possibly because the lack of high-frequency noise in the smooth-kernel data limited the ability of the trained model in removing high-frequency noise. Finally, in the LCD test, REDCNN improved the lesion detectability over the original FBP images regardless of whether the training and testing data had matching reconstruction kernels.REDCNN is observed to be poorly generalizable between reconstruction kernels, more robust in denoising data of arbitrary dose levels when trained with mixed-dose data, and not highly sensitive to slice thickness. It is known that reconstruction kernel affects the in-plane pNPS shape of a CT image, whereas slice thickness and dose level do not, so it is possible that the generalizability performance of this CT image denoising network highly correlates to the pNPS similarity between the testing and training data.

To explore the correlation between serum iron(Fe) and the overall survival of oral cancer.Patients with oral cancer who met the inclusion criteria in the Department of Oral and Maxillofacial Surgery of the First Affiliated Hospital of Fujian Medical University from January 2010 to April 2017 were collected. The average age was(57.12±13.94) years old, including 489 males(65.46%), 258 females(34.54%) and 564 cases of squamous cell carcinoma(77.90%). Overall survival rates were calculated by Kaplan-Meier method. Survival difference was compared by log-rank test. Cox regression model was used to estimate the hazard ratio(HRs) and 95% confidence intervals(95%CIs).The distributions of serum iron level were non-normal distribution(Plt;0.001), and the serum iron level is expressed as 13.9(10.3, 17.8)μmol/L in M(P25, P75). According to X-tile, the optimal cut-off value of serum iron was 15.3 μmol/L, used as a criterion to group patients. The result showed that the mortality risk of patients with oral cancer in high serum iron level(Fegt;15.3 μmol/L) was 0.72 times of patients in lower one(Fe≤15.3 μmol/L)(95%CI 0.52-0.99). Stratified analysis suggested that serum iron was a good predictor of patients with oral cancer aged 60 years(HR=0.62, 95%CI 0.39-0.99), male(HR=0.66, 95%CI 0.44-0.98), with TNM stage I-II(HR=0.42, 95%CI 0.20-0.88) and squamous cell of pathological type(HR=0.69, 95%CI 0.49-0.97).Serum iron is closely related to the overall survival of oral cancer, patients with high serum iron have a lower risk of death.

Land use change is closely related to the terrestrial ecosystem. Studying the relationship between land use and ecosystem service carbon storage under future climate change can optimize the regional ecosystem service function and formulate sustainable social and economic development policies, which is of great significance for regional carbon emission management and climate change response. In this paper, the coupled model of SSP-RCP-PLUS-InVEST was constructed to simulate land use change under different scenarios, analyze the influence degree of driving factors on different regions, and explore the spatio-temporal evolution and spatial correlation of carbon storage, taking Central Yunnan City agglomeration as an example. The results showed that: (1) from the perspective of land use change, the overall changes in SSP126 and SSP245 scenarios were similar, and the change rates of different types were slightly different. Under the SSP585 scenario, the forest area decreased, and the urban land and cropland land expanded. (2) Under the three scenarios in the future, the decrease in total carbon storage is the most serious under the SSP245 scenario, and the decrease is the most serious under the SSP585 scenario. (3) Comparative spatial correlation: the carbon storage in the Central Yunnan urban agglomeration is generally correlated among counties, and there is no significant difference under the future scenarios, showing a high accumulation pattern in the east and low accumulation pattern in the middle. In general, reasonable planning of land spatial patterns and increasing the proportion of forest is conducive to the proportion of regional carbon sequestration capacity. The research methods can provide references for addressing climate change and territorial spatial planning.

Background The KiSS1 gene is considered a tumor suppressor in various cancers. MicroRNAs are involved in many important life processes, and their regulation of gene expression may be as important as that of transcription factors. Here, we explore the roles of miR-124-3p and miR-378-3p in colorectal cancer and their relationships with the KiSS1 gene. Methods The effects of miR-124-3p and miR-378-3p on KiSS1 protein expression were observed by transfecting colorectal cancer cells (SW-480) with miR-124-3p and miR-378-3p mimics and inhibitors. Moreover, cell proliferation, migration and invasion were evaluated by ethynyl-20-deoxyuridine and Transwell experiments. Results The KiSS1 mRNA and protein expression levels were significantly increased in mimic-transfected cells compared with those in untransfected cells, and the proliferation, migration and invasion abilities of the former were decreased; in addition, opposing results were obtained in the inhibitor and mimic groups. Conclusions In conclusion, our studies indicate that miR-124-3p and miR-378-3p upregulate the expression of KiSS1 and are associated with colorectal cancer metastasis and progression. miR-124-3p, miR-378-3p and KiSS1 may play important roles in colorectal cancer.

Polyphenols are found in free and bound forms in foods, both of which exert a wide range of pharmacological and therapeutic effects. Here, 3T3-L1 pre-adipocytes and high-fat diet (HFD)-induced mice were used to investigate the potential anti-obesity effect of b ound p henolics extracted from l otus seeds (LBP). Phenolic compounds including protocatechuic, caffeic and ellagic acids were identified in LBP. In vitro results showed LBP significantly decreased intracellular lipid accumulation; while oral administration of LBP was found to retard body weight gain and improve plasma lipid profile in HFD-induced mice. Moreover, LBP increased phosphorylation of adenosine monophosphate-activated protein kinase (AMPK) accompanied with down-regulation of adipogenic/lipogenic genes (Pparγ, C/ebpα, aP2, Srebp-1c, Acc1, Fas, Lpl) expression; and up-regulation of lipolytic genes (Hsl, Pgc-1α, Sirt1, Cpt1α) and adipokine adiponectin expression. Taken together, these observations suggested lotus seeds bound phenolics may alleviate obesity, in part by modulating the AMPK signaling pathway.

Copper-oxide raw ore has a complex composition and cannot be processed effectively by conventional, single-stage sorting methods. Based on the characteristics of copper-oxide ore, a new combined grinding–flotation–high-gradient magnetic separation–secondary grinding–leaching process has been proposed to recover copper. Test results show that the new process is very effective. Sodium sulfide was used as a vulcanizing agent in the flotation process, and butyl xanthate was used as a collector to obtain a qualified copper concentrate with a copper grade of 29.37% and a recovery rate of 32.22%. The flotation tailings were subjected to high-gradient magnetic separation to obtain magnetic concentrates and magnetic tailings, and copper was recovered by leaching from the magnetic concentrates and tailings. After secondary grinding of the magnetic concentrates, the leaching rates of copper from the magnetic concentrates and magnetic tailings were 26.85% and 26.95%, respectively. The total copper recovery was 86.02%. The new process introduces high-gradient magnetic separation, enriches refractory chrysocolla, leaches chrysocolla at 65 °C, leaches malachite from the magnetic tailings at 40 °C, and saves heating costs. Secondary grinding can reduce the leaching temperature, shorten the leaching time, and achieve a low energy consumption and effective extraction of refractory copper-oxide ore.

Emerging studies have focused on ways to treat cancers by modulating T cell activation. However, whether B cell receptor signaling in the tumor microenvironment (TME) can be harnessed for immunotherapy is unclear. Here, we report that an Asia-specific variant of human IgG1 containing a Gly396 to Arg396 substitution (hIgG1-G396R) conferred improved survival of patients with colorectal cancer (CRC). Mice with knockin of the murine functional homolog mIgG2c-G400R recapitulated the alleviated tumorigenesis and progression in murine colon carcinoma models. Immune profiling of the TME revealed broad mobilizations of IgG1+ plasma cells, CD8+ T cells, CD103+ DCs, and active tertiary lymphoid structure formation, suggesting an effective antitumor microenvironment in hIgG1-G396R CRC patients. Mechanistically, this variant potentiated tumor-associated antigen-specific (TAA-specific) plasma cell differentiation and thus antibody production. These elevated TAA-specific IgG2c antibodies in turn efficiently boosted the antibody-dependent tumor cell phagocytosis and TAA presentation to effector CD8+ T cells. Notably, adoptive transfer of TAA-specific class-switched memory B cells harboring this variant exhibited therapeutic efficacy in murine tumor models, indicating their clinical potential. All these results prompted a prospective investigation of hIgG1-G396R in patients with CRC as a biomarker for clinical prognosis and demonstrated that manipulating the functionality of IgG1+ memory B cells in tumors could improve immunotherapy outcomes.

Backgroud: Tumour recurrence and metastasis lead to poor prognosis incolon cancer(COAD). Therefore We aimed to identify a lncRNA signature through an integrative analysis of copy number variation, mutation and transcriptome data to predict prognosis and explore its internal mechanism.Methods: The lncRNA expression profile were collected fromThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). TCGA data was randomly divided 3:1 intotraining andtesting cohort. In the training, weperformed integrated analyses of three candidate lncRNA sets that correlated with prognosis, copy number variations and mutations to establish a signature through Cox regression analysis. The robustness was determined in the testing and GEO.Results: An 11-lncRNA signature that was significantly associated with prognosiswas constructed in the training (PP=0.0019, HR=3.374) and GSE17536(P=0.0076, HR=1.864). The signature is significantly related to MSI status and clinical prognostic factors. The prognostic-relatedrisk scores were significantly excellent than the other five models have been reported. Furthermore, GSEA suggested that the signature was involved in COAD development and metastasis-related pathways.Conclusions: We identifiedansignature has strong robustness and can stably predict the prognosis of COAD in different platformsand may be implicated in COAD pathogenesis and metastasis and applied clinically as a prognostic marker.

Backgroud: Tumour recurrence and metastasis lead to poor prognosis in colon cancer (COAD). Therefore We aimed to identify a lncRNA signature through an integrative analysis of copy number variation, mutation and transcriptome data to predict prognosis and explore its internal mechanism.Methods: The lncRNA expression profile were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). TCGA data was randomly divided 3:1 into training and testing cohort. In the training, we performed integrated analyses of three candidate lncRNA sets that correlated with prognosis, copy number variations and mutations to establish a signature through Cox regression analysis. The robustness was determined in the testing and GEO. Results: An 11-lncRNA signature that was significantly associated with prognosis was constructed in the training (P

The presence of B lymphocytes in tumor tertiary lymphoid structures (TLSs) is an important prognostic indicator for different types of cancers. However, whether B cell responses in the tumor microenvironment (TME) can be harnessed for immunotherapy is unclear. Here we report that a protective germline variant of human immunoglobulin heavy constant gamma 1 gene (IGHG1) containing a Gly396 to Arg396 substitution (hIgG1-G396R) confers improved survival of colorectal cancer (CRC) patients. These hIgG1-G396R homozygous CRC patients displayed elevated tumor-associated antigen (TAA)-specific IgG1 antibody production and plasma cell infiltration into tumors. In murine colon carcinoma models, mice expressing the murine functional homolog IgG2c-Gly400Arg variant (mIgG2c-G400R) also produce higher levels of tumor-specific IgG2c antibodies via enhanced plasma cell differentiation, together with alleviated tumorigenesis and progression. Mechanistically, this variant potentiates TAA-specific antibody-dependent cellular phagocytosis and antigen presentation. Comprehensive immune profiling of the TME of CRC patients revealed that hIgG1-G396R prominently promotes broad mobilization of immune cells (IgG1+ plasma cells, CD8+ T cells, CD103+ DCs) and efficient TLS formation, both key components of an anti-tumor microenvironment. Notably, adoptive transfer of tumor-primed B cells with this variant exhibited therapeutic efficacy in murine tumor models, demonstrating clinical potential. These results prompt a prospective investigation of hIgG1-G396R in CRC patients as a biomarker for clinical prognosis and demonstrate that manipulating the functionality of IgG1+ B cells in tumors could improve immunotherapy outcomes.

Magnetic field inhomogeneity estimation is important in some types of magnetic resonance imaging (MRI), including field-corrected reconstruction for fast MRI with long readout times, and chemical shift based water-fat imaging. Regularized field map estimation methods that account for phase wrapping and noise involve nonconvex cost functions that require iterative algorithms. Most existing minimization techniques were computationally or memory intensive for 3D datasets, and are designed for single-coil MRI. This article considers 3D MRI with optional consideration of coil sensitivity, and addresses the multi-echo field map estimation and water-fat imaging problem. Our efficient algorithm uses a preconditioned nonlinear conjugate gradient method based on an incomplete Cholesky factorization of the Hessian of the cost function, along with a monotonic line search. Numerical experiments show the computational advantage of the proposed algorithm over state-of-the-art methods with similar memory requirements.

Copper oxide ore has a complex composition, and a low recovery rate is often achieved via the traditional sorting method. A new combined process of flotation–high-gradient magnetic separation–leaching is proposed here to recover copper minerals. The test results showed that the flotation process was successful when using sodium sulfide as a vulcanizing agent and butyl xanthate as a collector. The flotation concentrates can be qualified with a copper grade of 29.37% and a recovery rate of 32.22%. Flotation tailings separated by high-gradient magnetic separation can yield two products, namely, magnetic separation concentrates and magnetic separation tailings, via the leaching recovery of the remaining copper minerals. However, the leaching conditions are different. The leaching rates of copper from magnetic separation concentrates and tailings are 28.44% and 26.95%, respectively. The total copper recovery is 87.61%. This new technology introduces a high-gradient magnetic separation process, which achieves the requirements of low energy consumption and high-efficiency copper recovery.

Chalcopyrite and pyrite are difficult to separate under low alkaline environment. The selective depression mechanism of pyrite by sodium dimethyl dithiocarbamate (SDD) was explored in this study. Micro-flotation test showed that when the pH was 8.5, the recovery efficiency of pyrite decreased from 80.18% to 22.17% after adding SDD, while that of chalcopyrite decreased from 96.32% to 92.79%, indicating that SDD has a good selective depression effect on pyrite. Scanning electron microscopy and energy dispersive spectrometry results showed that SDD formed a stable complex on the pyrite surface, while the surface morphology of chalcopyrite did not change. The infrared spectrum study showed that significant SDD characteristic peaks appeared on the pyrite surface, resulting in obvious chemisorption, whereas no SDD characteristic peaks appeared on the chalcopyrite surface. Local electrochemical impedance spectroscopy in-situ study showed that the impedance of the pyrite surface decreased more than that of the chalcopyrite surface after SDD was added, indicating that the adsorption degree of SDD on the pyrite surface was stronger than chalcopyrite. X-ray photoelectron spectroscopy analysis also showed that SDD was significantly adsorbed on the pyrite surface. The above results indicated that SDD could selectively depress pyrite under low alkaline environment, thus increasing the difference in surface hydrophobicity between the two and selectively depressing pyrite.

Background The aim of this study was to explore the expression levels and biological significance of TDO2 in colorectal cancer (CRC). Methods First, we explored the potential oncogenic roles of TDO2 across 33 tumors based on data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Second, we evaluated TDO2 protein expression in 55 CRC tissue samples and 30 cDNA samples by immunohistochemistry and qPCR. Third, we investigated the effect of TDO2 on CRC cells by cell proliferation, wound healing, invasion, and colony formation assays. Finally, we determined the protein that is most closely associated with TDO2 via bioinformatics analysis, enriched the key pathways, and verified them. Results The expression level of TDO2 was found to be associated with the tumor clinical stage in CRC. A high expression of TDO2 was associated with a poor outcome in CRC patients. Inhibition of TDO2 expression by RNAi in LoVo and HCT116 cell lines significantly reduced the proliferation, migration, and invasion abilities as well as colony formation abilities of cells. Further, knockdown of TDO2 expression induced inactivation of the TDO2–KYNU–AhR signaling pathway. Conclusion The results suggest that TDO2 plays an important role in the progression of CRC. Accordingly, TDO2 is a potential therapeutic target in CRC.

Background: Immune cells and stromal cells are an important part of the tumor microenvironment and significantly affect the progression of colon cancer. The purpose of this study was to elucidate the prognostic value of noncoding RNAs (lncRNAs) related to immune cell infiltration in colon cancer. Methods: Single sample gene set enrichment analysis (ssGSEA) was used to identify the subtypes of colon cancer based on the immune genomes of 29 immune signatures. Cox regression analysis identified a lncRNA signatures associated with immune infiltration. The Tumor Immune Estimation Resource database was used to analyze the relationship between gene expression and immune cell content. The lncRNA competition endogenous RNA mechanism is used to construct the lncRNA-miRNA-mRNA network. Findings: Colon cancer samples were divided into three subtypes by unsupervised cluster analysis. Univariate and multivariate Cox regression analysis identified an immune infiltration-related 5-lncRNA signature. This signature combined with clinical factors can effectively improve the predictive ability for the overall survival (OS) of colon cancer. At the same time, we found that the expression of H19 affects the content of B cells and macrophages in the microenvironment of colon cancer and affects the prognosis of colon cancer. Finally, we constructed the H19 regulatory network and further analyzed the possible mechanisms. Interpretation: The findings may help to formulate clinical strategies and understand the underlying mechanisms of H19 regulation. H19 may be a biomarker for targeted treatment of colon cancer. Funding Statement: The Natural Science Foundation of Fujian Province of China (2019J01448). Declaration of Interests: The authors declare that they have no conflicts of interest regarding this work. Ethics Approval Statement: Not required.

Growing evidence suggests that immune-related genes (IRGs) and long non-coding RNAs (lncRNAs) can serve as prognostic markers of overall survival (OS) in patients with colon cancer. This study aimed to identify an immune-related lncRNA signature for the prospective assessment of prognosis in these patients. Gene expression and clinical data of colon cancer patients were downloaded from The Cancer Genome Atlas (TCGA). Immune-related lncRNAs were identified by a correlation analysis between IRGs and lncRNAs. In total, 447 samples were divided into a training cohort (224 samples) and a testing cohort (223 samples). Univariate, lasso and multivariate Cox regression analyses identified an immune-related nine-lncRNA signature closely related to OS in colon cancer patients in the training dataset. A risk score formula involving nine immune-related lncRNAs was developed to evaluate the prognostic value of the lncRNA signature in the training dataset. Colon cancer patients with a high risk score had poorer OS than those with a low risk score. A multivariate Cox regression analysis confirmed that the immune-related nine-lncRNA signature could be an independent prognostic factor in colon cancer patients. The results were further confirmed in the testing cohort and the entire TCGA cohort. Furthermore, a gene set enrichment analysis revealed several pathways with significant enrichment in the high- and low-risk groups that may be helpful in formulating clinical strategies and understanding the underlying mechanisms. Finally, a quantitative real-time polymerase chain reaction assay found that the nine lncRNAs were significantly differentially expressed in colon cancer cell lines. The results of this study indicate that this signature has important clinical implications for improving predictive outcomes and guiding individualized treatment in colon cancer patients. These lncRNAs could be potential biomarkers affecting the prognosis of colon cancer.

The low-rank plus sparse (L+S) decomposition model enables the reconstruction of under-sampled dynamic parallel magnetic resonance imaging (MRI) data. Solving for the low-rank and the sparse components involves non-smooth composite convex optimization, and algorithms for this problem can be categorized into proximal gradient methods and variable splitting methods. This paper investigates new efficient algorithms for both schemes. While current proximal gradient techniques for the L+S model involve the classical iterative soft thresholding algorithm (ISTA), this paper considers two accelerated alternatives, one based on the fast iterative shrinkage-thresholding algorithm (FISTA), and the other with the recent proximal optimized gradient method (POGM). In the augmented Lagrangian (AL) framework, we propose an efficient variable splitting scheme based on the form of the data acquisition operator, leading to simpler computation than the conjugate gradient (CG) approach required by existing AL methods. Numerical results suggest faster convergence of the efficient implementations for both frameworks, with POGM providing the fastest convergence overall and the practical benefit of being free of algorithm tuning parameters.

Colorectal cancer (CRC) is one of the most common cancers of the digestive tract. Although numerous studies have been conducted to elucidate the cause of CRC, the exact mechanism of CRC development remains to be determined. To identify candidate genes that may be involved in CRC development and progression, the microarray datasets GSE41657, GSE77953 and GSE113513 were downloaded from the Gene Expression Omnibus database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for functional enrichment analysis of differentially expressed genes (DEGs). A protein-protein interaction network was constructed, and the hub genes were subjected to module analysis and identification using Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. A total of 142 DEGs were identified, with enriched functions and pathways in the 'cell cycle', 'cell proliferation', 'the mitotic cell cycle' and 'one-carbon metabolic process'. In addition, 10 hub genes were identified, and functional analysis indicated that these genes are mainly enriched in 'cell division', 'cell cycle' and functions associated with nucleotide binding processes. Survival analysis demonstrated that DNA topoisomerase II α, cyclin-dependent kinase 1 and CDC28 protein kinase regulatory subunit 2 may be involved in cancer invasion or recurrence. The DEGs identified in the present study may help explain the molecular mechanisms of CRC development and progression.

Fresh-cut fruits and vegetables are the main sources of foodborne illness outbreaks with implicated pathogens such as Escherichia coli O157:H7, Salmonella, and Listeria monocytogenes. This study aimed at investigating the influence of two key parameters (concentration of curcumin and illumination time) on the effects of curcumin-based photodynamic sterilization on the preservation of fresh-cut Hami melons. The results indicated that illumination with 50 &mu, mol/L curcumin for 60 min using a blue LED lamp reduced the total aerobic microorganism count by ~1.8 log CFU/g in fresh-cut Hami melons. Besides this, the effects of photodynamic sterilization on the soluble solids content, color, water content, firmness, and sensory indices of the fresh-cut Hami melons were also evaluated. Compared to the control group, photodynamic sterilization can effectively delay the browning rate and maintain the luminosity, firmness, water content, and soluble solids content of fresh-cut Hami melon. The sensory quality was indeed preserved well after 9 days of storage in a fridge. These results showed that photodynamic sterilization is an effective and promising technology to prolong the shelf life of fresh-cut Hami melons.

Tremella Fuciformis is an edible fungus with high water content and nutritional values. However, fresh T. Fuciformis can quickly lose its quality by physical damage, water loss and microbial degradation during storage. Herein, we evaluated the effects of curcumin-mediated photodynamic technology (PDT) using light-emitting diode (LED) light to preserve fresh T. Fuciformis. Changes in bacterial counts and community, physicochemical properties, and sensory attributes of curcumin-mediated PDT-treated fresh T. Fuciformis were assessed. The results indicated that treatment with 30 μmol/L curcumin and 30 min of LED light exposure could reduce bacterial counts by ~1.99 ± 0.06 log (CFU/g) in fresh T. Fuciformis upon 5 days storage. The bacterial microbiota in T. Fuciformis during storage was also altered upon PDT treatment. PDT treatment also retained the color, water content, hardness, tactility, and appearance of fresh T. Fuciformis. In conclusion, this study demonstrated that curcumin-mediated PDT could be a viable and promising non-thermal technology for preserving the quality of fresh T. Fuciformis.

The sulfidization–xanthate method is an important method for recovering smithsonite. As the sulfidization time increases, the newly formed sulfidization layer on the smithsonite surface is unstable, which causes attenuation and affects the recovery efficiency. We studied the stability of the sulfidization layer of smithsonite and the effect of ammonium chloride on the sulfidization layer by microflotation experiments, sulfur adsorption test, X-ray photoelectron spectroscopy and time-of-flight secondary mass spectrometry. Microflotation experiments results showed that ammonium-chloride addition can increase the recovery efficiency of the smithsonite by ~10%. Sulfur adsorption test results showed that after ammonium-chloride addition, more sulfur components were formed on the smithsonite surface. XPS results showed that after ammonium-chloride addition, the atomic concentration of the surface sulfur component increased from 0.09% to 2.38%. ToF-SIMS results showed that the newly formed sulfide component was more evenly distributed and the surface of the sulfide layer was smoother. The sulfur composition and sulfide layer thickness increased significantly, which increased the sulfide layer stability and improved the recovery efficiency of the smithsonite. All these details have established that the ammonium chloride has a good promoting effect on the sulfidization of smithsonite and increases the sulfidization layer stability.

In this study, the antiobesity effects of n-butanol extract of lotus seeds (LBE) were evaluated in cultured 3T3-L1 preadipocytes and in high-fat diet (HFD)-fed mice. LBE decreased lipid contents in mature 3T3-L1 cells without obvious cytotoxicity. Meanwhile, LBE supplementation also led to weight loss and improved plasma lipid profiles in HFD-fed mice. Furthermore, LBE could activate AMP-activated protein kinase (AMPK) accompanied by down-regulation of lipogenesis related genes (PPARγ, aP2, LPL, C/EBPα, FAS, SREBP-1c) and up-regulation of lipolysis genes (adiponectin and PPARα) in vitro and in vivo. Collectively, our data demonstrated LBE possesses antiadipogenic and antilipogenic activities which are, at least partially, mediated by the activation of AMPK signaling pathways.

The purpose of this study was to investigate the expression of microRNA-202 (miR-202) and its role in colorectal cancer (CRC) in vivo and in vitro. We examined the expression of miR-202 in CRC tissues by quantitative real-time PCR (qRT-PCR) assay. Lentiviral vectors were constructed to overexpress or inhibit the expression of miR-202 in the CRC cell lines HCT116 and SW480 to determine its effects on cell invasion and proliferation. We found that overexpression of miR-202 significantly inhibited the proliferation and invasion of HCT116 cells. MiRNA target gene prediction, dual luciferase assay, and western blot analysis demonstrated that miR-202 regulated ubiquitin-like with PHD and RING finger domain 1 (UHRF1) expression in both cell lines. The effect of miR-202 on cell proliferation and invasion was partially reversed by activating the expression of UHRF1. Furthermore, miR-202 induced tumor formation in HCT116 xenograft BALB/c nude mice. Mice vaccinated with miR-202-overexpressing cells had smaller tumors and lower UHRF1 expression than the control group. These results indicate the possibility that miR-202 is under-expressed in CRC tissues, and that miR-202 inhibits the proliferation and invasion of CRC via targeting UHRF1. MiR-202 is a potential therapeutic target for CRC.

In this study, we successfully apply a silicon nanowire FETs biosensor for detection of uric acid according to pH change. The pH sensing experiments of the silicon nanowire FETs shows that average sensitivity of 42mV/pH. We show that silicon nanowire FETs configured as pH sensors can be used for the quantitative detection of uric acid at concentration as low as 2.4mg/dL. The sensor shows a good linearity (R2 = 0.99) and sensitivity (60mV/mM) in the concentration range of 3-8mg/dL, with less than 300 sec response time. These results demonstrate that silicon nanowire FETs based biosensor can potentially be served as the diagnosis tool for general clinical examinations.

This paper takes the plateau mountain city: the urban agglomeration in central Yunnan as the research area, 2000-2015 as the research period, and measure and analyze the spatio-temporal differentiation of construction land expansion in the urban agglomeration based on the calculation of kernel density. Use the spatial autocorrelation model to analyze the spatial autocorrelation patterns of construction land on the 1 km × 1 km grid scale, and then use the GIS spatial analysis technique to study the local aggregation area at the p

Data sharing among different platform in smart city is a key issue on big data era. This paper focuses on the core issues of heterogeneous data switching, sharing and updating in the construction of smart city. We first review the current research status of data sharing from three aspects which including big data characteristics, technology system and big data sharing platform in smart city. The analysis shows that the current data sharing research in smart city has been only used one or two types of data, and the data utilization mode is relatively simple. The research on the data sharing technology system of heterogeneous data needs to be further development. The research of data sharing is limited to a certain field, few platforms have studied data sharing in more than two fields, and horizontal data sharing methods need some breakthrough. Our work analyzes the data requirement and data source characteristics on the smart city construction platform, analyzes the hierarchical relationship and sharing relationship of various data from different platform, and clarifies the hierarchical relationship, sequence and sharing process of data sharing among different platforms. Then the platform architecture of data sharing, switching, updating and guarantee mechanism between heterogeneous systems based on cloud computing is proposed, and the data sharing and switching technology based on cloud and big data is proposed, which provide the top-level framework reference and technical support for the realization of cross platform data sharing in smart city. Finally, the paper concludes and analyzes the key implementation technology of data sharing in depth.

Monitoring and supervision of land resources requires several spatial databases related to land use, land planning, mineral resources, etc. It also needs support via information technologies such as GIS, GNSS, RS (3S), wireless communication, and internet-of-things. At present, in view of the requirements related to the complexity and comprehensiveness of the monitoring and supervision of land resources, some application systems have been developed in China and some progress has been made. However, most of the existing systems have several weaknesses; for example, field inspection and office verification have to be carried out separately. Real-time spatial data analysis and monitoring confirmation cannot be performed, and the process is time consuming. A dynamic and integrated monitoring process has not yet been realized. In this study, a new type of land resource monitoring and supervision system (LRMSS) with 3S and mobile internet is designed and developed. The LRMSS integrates real-time data communication and the monitoring and supervision of land resources with spatial analysis. It provides a multilevel, multifaceted visual display of the monitoring processes and graphics and other information on the mobile terminal and monitoring platform. The standardized, efficient, and systematic LRMSS has been implemented and applied, which can improve the processing speed and work efficiency of the monitoring and supervision of land resources. In this study, based on location services, an unattended geospatial analysis and service model is developed by integrating 3S technologies using multisource data; thereafter, the corresponding system software, which provides the functions of integrating the data of the core database of land resources and monitoring of land resources, is developed. Meanwhile, based on the accessing mechanism of geospatial information service with the asynchronous communication protocol, the study uses the VPDN network as the main means and the BDS short message as an emergency supplement. Data security and the transmission mechanism for reliable transmission of geospatial data are both realized. The paper states the interface requirements and data standard for reporting and receiving data between databases. The results of this study can provide services for supervising and decision analysis for law enforcement supervision. It has been widely used in the department of land resource management.

We present novel numerical methods for polyline-to-point-cloud registration and their application to patient-specific modeling of deployed coronary artery stents from image data. Patient-specific coronary stent reconstruction is an important challenge in computational hemodynamics and relevant to the design and improvement of the prostheses. It is an invaluable tool in large-scale clinical trials that computationally investigate the effect of new generations of stents on hemodynamics and eventually tissue remodeling. Given a point cloud of strut positions, which can be extracted from images, our stent reconstruction method aims at finding a geometrical transformation that aligns a model of the undeployed stent to the point cloud. Mathematically, we describe the undeployed stent as a polyline, which is a piecewise linear object defined by its vertices and edges. We formulate the nonlinear registration as an optimization problem whose objective function consists of a similarity measure, quantifying the distance between the polyline and the point cloud, and a regularization functional, penalizing undesired transformations. Using projections of points onto the polyline structure, we derive novel distance measures. Our formulation supports most commonly used transformation models including very flexible nonlinear deformations. We also propose 2 regularization approaches ensuring the smoothness of the estimated nonlinear transformation. We demonstrate the potential of our methods using an academic 2D example and a real-life 3D bioabsorbable stent reconstruction problem. Our results show that the registration problem can be solved to sufficient accuracy within seconds using only a few number of Gauss-Newton iterations.

The pressure in the renal interstitium is an important factor for normal kidney function. Here we develop a computational model of the rat kidney and use it to investigate the relationship between arterial blood pressure and interstitial fluid pressure. In addition, we investigate how tissue flexibility influences this relationship. Due to the complexity of the model, the large number of parameters, and the inherent uncertainty of the experimental data, we utilize Monte Carlo sampling to study the model’s behavior under a wide range of parameter values and to compute first- and total-order sensitivity indices. Characteristically, at elevated arterial blood pressure, the model predicts cases with increased or reduced interstitial pressure. The transition between the two cases is controlled mostly by the compliance of the blood vessels located before the afferent arterioles.

Response surface methodology is used to optimize the leaching process for refractory flotation copper tailings. The proportion of the refractory combination oxide copper (chrysocolla) is 64.84%. At present, few studies have examined the leaching of chrysocolla. In this study, we examine the effects of several variables, including the amount of concentrated sulfuric acid, leaching temperature, and leaching time, on leaching efficiency. Using a response surface methodology, we develop a quadratic model relanbting all the above experimental variables with leaching efficiency. The resulting model is highly consistent with experimental data. According to the model, the factor with the greatest influence on leaching efficiency is the amount of concentrated sulfuric acid. According to the model, the optimal leaching conditions are 85 kg/t concentrated sulfuric acid, a leaching temperature of 68.51 °C, and a leaching time of 4.36 h. The actual measured leaching efficiency under these conditions is 85.86%, which is close to the value of 86.79% predicted by the model. We study the leaching processes using scanning electron microscopy (SEM) and energy dispersive spectrometry (EDS) surface scan analyses. Both methods allow us to explore the content of the main element and visually observe its distribution, allowing us to develop effective methods for treating low-grade oxide ores.

We present novel numerical methods for polyline-to-point-cloud registration and their application to patient-specific modeling of deployed coronary artery stents from image data. Patient-specific coronary stent reconstruction is an important challenge in computational hemodynamics and relevant to the design and improvement of the prostheses. It is an invaluable tool in large-scale clinical trials that computationally investigate the effect of new generations of stents on hemodynamics and eventually tissue remodeling. Given a point cloud of strut positions, which can be extracted from images, our stent reconstruction method aims at finding a geometrical transformation that aligns a model of the undeployed stent to the point cloud. Mathematically, we describe the undeployed stent as a polyline, which is a piecewise linear object defined by its vertices and edges. We formulate the nonlinear registration as an optimization problem whose objective function consists of a similarity measure, quantifying the distance between the polyline and the point cloud, and a regularization functional, penalizing undesired transformations. Using projections of points onto the polyline structure, we derive novel distance measures. Our formulation supports most commonly used transformation models including very flexible nonlinear deformations. We also propose 2 regularization approaches ensuring the smoothness of the estimated nonlinear transformation. We demonstrate the potential of our methods using an academic 2D example and a real-life 3D bioabsorbable stent reconstruction problem. Our results show that the registration problem can be solved to sufficient accuracy within seconds using only a few number of Gauss-Newton iterations.