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This review provides an overview of common assays used to screen for gene methylation and early biomarkers of methylation in various cancers. DNA methylation, one of the most well-studied epigenetic modifications, plays a crucial role in normal cell and tissue development. It is increasingly utilized as a biomarker for early cancer and precancerous lesion detection. In this review, we describe common methods associated with gene methylation, including bisulfite sequencing PCR (BSP), pyrosequencing technology (PYR), methylation-specific polymerase chain reaction (MS-PCR/MSP), methylation-sensitive high-resolution melting (MS-HRM), methylation sensitive single nucleotide primer extension (MS-SnuPE), Epityper, Droplet digital PCR (ddPCR), methylation-sensitive restriction enzyme (MSRE) analysis, COBRA and PacBio SMRT sequencing. Additionally, we summarize methylation markers and their sample types for early cancer screening, focusing on colorectal cancer, hepatocellular carcinoma, gastric cancer, pancreatic cancer, esophageal cancer (digestive system), lung cancer (respiratory system), breast cancer, ovarian cancer, cervical cancer (female reproductive system), bladder cancer, and prostate cancer (urinary system). Furthermore, we discuss the recent detection of methylation biomarkers in clinical samples such as blood, urine, sputum, feces, and tissues. The aim of this review is to summarize early methylation biomarkers that are expected or have already been clinically applied. For future large-scale studies or the integration of available methylome level data, the discovery of sufficiently sensitive clinical biomarkers is essential.

Objective: To explore the mechanism of Wenyang Shengji Ointment (温阳生肌膏, WYSJO) in the treatment of diabetic wounds from the perspective of network pharmacology, and to verify it by animal experiments. Methods: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and related literature were used to screen active compounds in WYSJO and their corresponding targets. GeneCards, Online Mendelian Inheritance in Man (OMIM), DrugBank, PharmGkb, and Therapeutic Target Database (TTD) databases were employed to identify the targets associated with diabetic wounds. Cytoscape 3.9.0 was used to map the active ingredients in WYSJO, which was the diabetic wound target network. Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) platform was utilized to construct protein-protein interaction (PPI) network. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed to identify signaling pathways between WYSJO and diabetic wounds. AutoDock 1.5.6 was used for molecular docking of core components in WYSJO to their targets. Eighteen rats were randomly divided into control, model, and WYSJO groups (n = 6). The model and WYSJO groups were used to prepare the model of refractory wounds in diabetes rats. The wound healing was observed on day 0, 5, 9, and 14 after treatment, and the wound tissue morphology was observed by hematoxylin-eosin (HE) staining. The expression levels of core genes were detected by quantitative real-time polymerase chain reaction (qPCR). Results: A total of 76 active compounds in WYSJO, 206 WYSJO drug targets, 3 797 diabetic wound targets, and 167 diabetic wound associated WYSJO targets were screened out through network pharmacology. With the use of WYSJO-diabetic wound target network, core targets of seven active compounds encompassing quercetin, daidzein, kaempferol, rhamnetin, rhamnocitrin, strictosamide, and diisobutyl phthalate (DIBP) in WYSJO were found. GO enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve lipopolysaccharide, bacteria-derived molecules, metal ions, foreign stimuli, chemical stress, nutrient level, hypoxia, and oxidative stress in the biological processes. KEGG enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve advanced glycation end products (AGE-RAGE), p53, interleukin (IL)-17, tumor necrosis factor (TNF), hypoxia inducible factor-1 (HIF-1), apoptosis, lipid, atherosclerosis, etc. The results of animal experiments showed that WYSJO could significantly accelerate the healing process of diabetic wounds (P < 0.05), alleviate inflammatory response, promote the growth of granulation tissues, and down-regulate the expression levels of eight core genes [histone crotonyltransferase p300 (EP300), protoc gene-oncogene c-Jun (JUN), myelocytomatosis (MYC), hypoxia inducible factor 1A (HIF1A), mitogen-activated protein kinase 14 (MAPK14), specificity protein 1 (SP1), tumor protein p53 (TP53), and estrogen receptor 1 (ESR1)] predicted by the network pharmacology (P < 0.05). Conclusion: The mechanism of WYSJO in treating diabetes wounds may be closely related to AGE-RAGE, p53, HIF-1, and other pathways. This study can provide new ideas for the pharmacological research of WYSJO, and provide a basis for its further transformation and application.

Abstract Background Liver metastasis of CRC is still the main cause of poor prognosis in patients with CRC. Previous studies have suggested that serpin family C member 1(SERPINC1) is involved in the development of a variety of tumours, but its effect on colorectal cancer progression has been poorly elucidated. Methods Based on the GEO database, this study identifies the core gene SERPINC1 associated with liver metastasis in CRC. We used transcriptomic data and immunohistochemical staining to explore the expression of SERPINC1 in normal, cancer, and liver metastases tissue from CRC patients. Clinical data obtained from our hospital were used to explore the impact of SERPINC1 on the prognosis of colon cancer patients. Mechanistically, the biological functions exerted by SERPINC1 in CRC were predicted by bioinformatics, and the results were validated by the results of the experiments in vitro. Cell lines with knockdown of SERPINC1 were performed a series assay such as trans well, CCK‐8 and colony formation assay to explore the relationship between SERPINC1 and proliferation and metastasis of CRC cells. Finally, the effect of SERPINC1 on the sensitivity of colon cancer patients to immune checkpoint therapy was evaluated. Results In CRC liver metastatic tissues, we found significantly high expression of SERPINC1. Briefly, 212 CRC cohorts showed that SERPINC1 was significantly associated with TNM stage and plasma CA19‐9 and CEA in CRC patients. Univariate and multivariate Cox demonstrated that SERPINC1 was significantly associated with 5‐year survival after radical surgery for colorectal cancer (p

Abstract Background Aberrant glycosylation, catalyzed by the specific glycosyltransferase, is one of the dominant features of cancers. Among the glycosyltransferase subfamilies, sialyltransferases (SiaTs) are an essential part which has close linkages with tumor-associated events, such as tumor growth, metastasis and angiogenesis. Considering the relationship between SiaTs and cancer, the current study attempted to establish an effective prognostic model with SiaTs-related genes (SRGs) to predict patients’ outcome and therapeutic responsiveness of bladder cancer. Methods RNA-seq data, clinical information and genomic mutation data were downloaded (TCGA-BLCA and GSE13507 datasets). The comprehensive landscape of the 20 SiaTs was analyzed, and the differentially expressed SiaTs-related genes were screened with “DESeq2” R package. ConsensusClusterPlus was applied for clustering, following with survival analysis with Kaplan–Meier curve. The overall survival related SRGs were determined with univariate Cox proportional hazards regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to generate a SRGs-related prognostic model. The predictive value was estimated with Kaplan–Meier plot and the receiver operating characteristic (ROC) curve, which was further validated with the constructed nomogram and decision curve. Results In bladder cancer tissues, 17 out of the 20 SiaTs were differentially expressed with CNV changes and somatic mutations. Two SiaTs_Clusters were determined based on the expression of the 20 SiaTs, and two gene_Clusters were identified based on the expression of differentially expressed genes between SiaTs_Clusters. The SRGs-related prognostic model was generated with 7 key genes (CD109, TEAD4, FN1, TM4SF1, CDCA7L, ATOH8 and GZMA), and the accuracy for outcome prediction was validated with ROC curve and a constructed nomogram. The SRGs-related prognostic signature could separate patients into high- and low-risk group, where the high-risk group showed poorer outcome, more abundant immune infiltration, and higher expression of immune checkpoint genes. In addition, the risk score derived from the SRGs-related prognostic model could be utilized as a predictor to evaluate the responsiveness of patients to the medical therapies. Conclusions The SRGs-related prognostic signature could potentially aid in the prediction of the survival outcome and therapy response for patients with bladder cancer, contributing to the development of personalized treatment and appropriate medical decisions.

In recent years, the poultry breeding industry has been converted into a large-scale, intensive, and intelligent production mode. The Internet of Things (IoT) is under rapid development, which promotes the development of precision livestock farming. In this study, we developed an intelligent service platform for a facility environment based on the IoT structure, utilizing the capabilities of Platform as a Service (PaaS). The platform consists of four layers, including an information perception layer, network layer, management service layer, and application layer. By using the cloud service model with a distributed network architecture, asynchronous data transmission, and a distributed file system, the platform can centrally manage multiple farm’s data. The intelligent service platform includes the following functions: displaying environmental data, water and electricity consumption, data analysis, and managing production data. Over a 500-day trial period in a live poultry house, the platform demonstrated high data integrity (>87%) and resilience against network disruptions and power outages. The data validity of each environmental element exceeded 94%, among which the validity of the temperature, humidity, and carbon dioxide concentration exceeded 99%. The overall accuracy of the dataset remained relatively high, providing a robust data foundation for further research. Key features included audio analysis, environmental monitoring, and production data management. The platform’s operational status was efficiently communicated via data statistics and email alerts, facilitating timely system recovery. The demonstrated modules included sound recognition, psychrometric charts for visual alerts, and financial analysis tools, offering versatile solutions for integrating PLF models and advanced analytics.

Low expression levels of breast cancer metastasis suppressor 1 like (BRMS1L) have been associated with the growth of cancer cells. However, the mechanisms underlying the role of BRMS1L as an antitumour transcription factor in the progression of NSCLC have not been explored. Herein, we reveal that BRMS1L plays a key role as a tumour suppressor in inhibiting NSCLC proliferation and metastasis. Mechanistically, BRMS1L overexpression results in the downregulation of glutathione peroxidase 2 (GPX2) expression and consequently causes abnormal glutathione metabolism and increased levels of reactive oxygen species (ROS) in cells, inducing oxidative stress injury and apoptosis. Furthermore, overexpression of GPX2 enhances the growth advantage and oxidative stress repair conferred by knockdown of BRMS1L. Importantly, we show that low expression of BRMS1L in NSCLC cells causes relatively high levels of antioxidant accumulation to maintain cell redox balance and renders cancer cells more sensitive to treatment with piperlongumine as an ROS inducer both in vitro and in vivo. These findings offer new insights into the role of BRMS1L as a transcriptional repressor in NSCLC and suggest that the BRMS1L expression level may be a potential biomarker for predicting the therapeutic response to small molecule ROS inducers, providing new ideas for targeted therapy.

Abstract Background and Objectives Anastomotic leakage is a serious complication following surgery for cancer of the rectum. It is not clear whether reinforcing sutures could prevent anastomotic leakage. Therefore, this study aims at evaluating the efficacy of reinforcing sutures on anastomotic leakage. Methods We searched PubMed, Embase, and the Cochrane Library databases from inception to January 31, 2023. We included studies comparing anastomosis with reinforcing sutures to anastomosis without reinforcing sutures after low anterior resection. Risk of bias was assessed by the Cochrane tool for RCTs and the Risk of Bias in Non‐Randomized Studies (ROBINS)‐I tool for observational studies. The overall quality of evidence for primary outcome was assessed using Grading of Recommendations Assessment, Development, and Evaluations methodology. Results Two RCTs (345 patients) and four observational studies (783 patients) were included. Anastomotic leakage occurred in 4.4% (24 of 548) of patients with reinforcing sutures and 11.9% (69 of 580) of patients without reinforcing sutures. Meta‐analysis showed a lower incidence of anastomotic leakage (RR, 0.41; 95% CI 0.25 to 0.66, low certainty) in patients with reinforcing sutures. Operative time (WMD, −3.66; 95% CI −18.58 to 11.25) and reoperation for anastomotic leakage (RR, 0.69; 95% CI 0.23 to 2.08) were similar between patients with reinforcing sutures and those without reinforcing sutures. Conclusions While observational data suggest that, there is a clear benefit in terms of reducing the risk of anastomotic leakage with the use of reinforcing sutures, RCT data are less clear. Further large, prospective studies are warranted to determine whether a true clinically important benefit exists with this technique.

Uterine corpus endometrial carcinoma (UCEC) is one of the most common type of gynecological malignancies. Multiple lines of evidence indicated that CXC chemokines exerted an anti-tumor immunological role in the tumor microenvironment which were critical regulators of cancer immunity. However, the relevance of CXC chemokines in the evaluation of prognosis and immune infiltration of UCEC remains to be explored. This study utilized various online databases, including TCGA, UALCAN, Kaplan-Meier Plotter, cBioPortal, TIMER2.0, TISIDB, and MethSurv to perform the analysis. Gene expression data from the TCGA-UCEC dataset indicated decreased expression of CXCL2/12 and increased expression of CXCL14/17. CXCL2/12 expression was negatively whereas CXCL14/17 expression was positively correlated with clinicopathological features of UCEC patients, including cancer stage, patients' age, weight and menopause status. Patients with higher CXCL12/14 expression corresponded with better clinical outcomes, which were not influenced by the genetic alterations. The differential expression of CXCL2/12/14/17 was not only significantly correlated with immune infiltration levels, but also the abundance of immune checkpoint inhibitors. Heatmaps of DNA methylation of CXCL2/12/14/17 were investigated, and 4 CpGs of CXCL2, 16 CpGs of CXCL12, 3 CpGs of CXCL14/17 were identified where altered methylation affected the prognosis of UCEC patients. These findings provided novel insights into the immunologic features of UCEC and might pave the way toward the prognostic evaluation and immunotherapy selection based on CXCL2/12/14/17 expression status.

Abstract Background Gastric cancer (GC) ranks second in mortality among all malignant diseases worldwide. However, the cause and molecular mechanism underlying gastric cancer are not clear. Here, we used integrated bioinformatics to identify possible key genes and reveal the pathogenesis and prognosis of gastric cancer. Methods The gene expression profiles of GSE118916, GSE79973, and GSE29272 were available from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between GC and normal gastric tissues were screened by R software and Venn diagram software. GO and KEGG pathway enrichment of DEGs was performed using the DAVID database. A protein-protein interaction (PPI) network was established by STRING and visualized using Cytoscape software. Then the influence of hub genes on expression and survival was assessed using TCGA database. Results A total of 83 DEGs were found in the three datasets, including 41 up-regulated genes and 42 down-regulated genes. These DEGs were mainly enriched in extracellular matrix organization and cell adhesion. The enriched pathways obtained in the KEGG pathway analysis were extracellular matrix (ECM)-receptor interaction and focal adhesion. A PPI network of DEGs was analyzed using the Molecular Complex Detection (MCODE) app of Cytoscape. Four genes were considered hub genes, including COL5A1, FBN1, SPARC, and LUM. Among them, LUM was found to have a significantly worse prognosis based on TCGA database. Conclusions We screened DEGs associated with GC by integrated bioinformatics analysis and found one potential biomarker that may be involved in the progress of GC. This hub gene may serve as a guide for further molecular biological experiments.

METTL3-mediated RNA N6-methyladenosine (m6A) is the most prevalent modification that participates in tumor initiation and progression via governing the expression of their target genes in cancers. However, its role in tumor cell metabolism remains poorly characterized. In this study, m6A microarray and quantitative proteomics were employed to explore the potential effect and mechanism of METTL3 on the metabolism in GC cells. Our results showed that METTL3 induced significant alterations in the protein and m6A modification profile in GC cells. Gene Ontology (GO) enrichment indicated that down-regulated proteins were significantly enriched in intracellular mitochondrial oxidative phosphorylation (OXPHOS). Moreover, the protein-protein Interaction (PPI) network analysis found that these differentially expressed proteins were significantly associated with OXPHOS. A prognostic model was subsequently constructed based on the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, and the high-risk group exhibited a worse prognosis in GC patients. Meanwhile, Gene Set Enrichment Analysis (GSEA) demonstrated significant enrichment in the energy metabolism signaling pathway. Then, combined with the results of the m6A microarray analysis, the intersection molecules of DEPs and differential methylation genes (DMGs) were significantly correlated with the molecules of OXPHOS. Besides, there were significant differences in prognosis and GSEA enrichment between the two clusters of GC patients classified according to the consensus clustering algorithm. Finally, highly expressed and highly methylated molecules regulated by METTL3 were analyzed and three (AVEN, DAZAP2, DNAJB1) genes were identified to be significantly associated with poor prognosis in GC patients. These results signified that METTL3-regulated DEPs in GC cells were significantly associated with OXPHOS. After combined with m6A microarray analysis, the results suggested that these proteins might be implicated in cell energy metabolism through m6A modifications thus influencing the prognosis of GC patients. Overall, our study revealed that METTL3 is involved in cell metabolism through an m6A-dependent mechanism in GC cells, and indicated a potential biomarker for prognostic prediction in GC.

Abnormal N6-methyladenosine (m6A) modification levels caused by METTL3 have been identified to be a critical regulator in human cancers, and its roles in the immune microenvironment and the relationship between targeted therapy and immunotherapy sensitivity in gastric cancer (GC) remain poorly understood. In this study, we assessed the transcriptome-wide m6A methylation profile after METTL3 overexpression by m6A sequencing and RNA sequencing in BGC-823 cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze the function of core targets of METTL3. Eighteen methylation core molecules were identified in GC patients by combining transcriptome and methylome sequencing. GC patients can be separated into two subtypes based on the expression of 18 methylation core molecules. Furthermore, subgroup analysis showed that patients with different subtypes had a different OS, PFS, stage, grade, and TMB. Gene set enrichment analysis (GSEA) showed that immune-related pathways were enriched among subtype A. The ESTIMATE analysis suggested that the extent of infiltration of immune cells was different in two subtypes of GC patients. Tumor Immune Dysfunction and Exclusion (TIDE) and The Cancer Immunome Atlas (TCIA) database also showed that there were significant differences in the efficacy of immunotherapy among different types of GC patients. Altogether, our results reveal that METTL3-mediated m6A methylation modification is associated with the immune microenvironment and the effects of immunotherapy in GC patients. Our findings provide novel insights for clinicians in the diagnosis and optimal treatment of GC patients.

We examined the variation in the solidification microstructure of AlSi10Mg alloy powder over a wide range of cooling rates controlled by using the fast scanning calorimetry (FSC) technique. Two exothermic peaks derived from the primary solidification of the α-Al phases and the α-Al/Si eutectic reaction were detected. These exothermic peaks became broader and shifted to lower temperatures at higher cooling rates. Focus ion beam (FIB) milling enables microstructural characterization of AlSi10Mg powder solidified at controlled cooling rates above 102 °C·s−1 in the FSC equipment. The sample solidified at 4 × 104 °C·s−1 exhibited a fine microstructure consisting of a primary α-Al phase surrounded by lamellar-shaped Si phases. The fraction of the Si phase continuously decreased with increasing cooling rate, indicating higher content of solute Si element in the α-Al phase solidified at a higher cooling rate. The secondary dendrite arm spacing (λ) of the primary α-Al phase decreased in the sample solidified at a higher cooling rate (dT/dt). The relation follows a general equation of λ = A (dT/dt)-n (A: 38.4, n: 0.33) in wide range of cooling rate (10-1 ∼ 104 °C·s−1). The results were utilized to discuss the cooling rate of Al alloys during the laser powder bed fusion (L-PBF) process.

We propose a scheme for ultra-broadband and polarization-insensitive metamaterial perfect absorber (PA) by utilizing a thin metal-insulator-metal (MIM) stack, which is comprised of an array of cross-shaped titanium resonators, a silica dielectric spacer, and an opaque titanium slab. The bandwidth of absorption (A) > 90% is up to 2100 nm, ranging from the visible to near infrared region. At the wavelength range of 400-2500 nm, this metamaterial absorber shows strong absorption of electromagnetic waves. The spectral average absorptivity reaches 93.8% and the maximal absorptivity is up to 99.8%. In addition, the simulations show that the absorption remains high over a broad range of incident angles. Additionally, we have investigated the influences of geometries, structural parameters and material features on the absorption properties. The utilization of titanium rather than the noble metals efficiently lowers the fabrication cost and enhances the thermal stability and biocompatibility, thus paving a way to numerous applications such as solar energy harvesting, imaging, infrared detection and bio-medical techniques.

Objective: m7G is a post-transcriptional modification modality, however, limited research has been conducted on its role in colon cancer. DNA damage repair (DDR) is an important factor that contributes to colon cancer development, growth and chemoresistance. This study aimed to explore whether m7G-related DNA damage repair genes may be used as biomarkers to predict the prognosis of colon cancer patients.Methods: We use non-negative matrix factorization (NMF) to type CRC patients into. Risk models were constructed using different expression genes in two clusters. We assessed the reliability of risk models with DCA curves, and a Nomogram. Meanwhile, The receiver operating characteristic and C-index curves were used to compare the predictive significance of the constructed risk models with other studies. In additional, we examined the significance of risk models on patients’ immunity microenvironment and response to immune therapy. Finally, we used a series of cellular experiments to validate the effect of model genes on the malignant progression of CRC cells.Results: Twenty-eight m7G genes were obtained from the GSEA database. Multivariate Cox and LASSO Cox regression analysis was performed and eleven m7G-related DDR genes were identified for constructing the risk model. Survival and stage of CRC patients were worser in the high-risk group than in the low-risk group for both the training and test sets. Additionally, the different immune microenvironment status of patients in the high- and low-risk groups, suggesting that patients in the low-risk group may be more sensitive to immunotherapy, particularly immune checkpoint inhibitors. Finally, we found that depletion of ATP2A1, one of the risk genes in our model, influence the biologic behaviour of CRC cells significantly.Conclusion: The m7G-related DDR genes can be used as important markers for predicting patient prognosis and immunotherapy response. Our data suggest that ATP2A1 may promote the proliferation of colon cancer cells. These findings may provide new therapeutic targets for the treatment of colon cancer.

Inflammation, nutrition, and coagulation play significant roles in cancer prognosis. Autonomic function is also actively involved in tumorigenesis. Previous studies have shown that an elevated C-reactive protein (CRP) level, a serum marker for inflammation, is associated with low heart rate variability (HRV), a common clinical tool for the assessment of autonomic function. It is yet to be investigated whether HRV links to these prognostic factors in cancer patients. Sixty-one patients who were first diagnosed with gastric cancer (GC) were enrolled in this study. Fasting blood samples were collected in the morning seven days before surgery. Blood CRP, prealbumin (PA), and fibrinogen (FIB) were used to assess the inflammation level, nutritional status, and coagulation function respectively. Five-minute resting electrocardiogram (ECG) signals were collected one day before surgical treatment. Short-term HRV time-series were extracted from ECG recordings and were analyzed using commonly-used time- and frequency-domain parameters including standard deviation of normal-to-normal intervals (SDNN), root mean square of successive heartbeat interval differences (RMSSD), very-low-frequency power (VLF), low-frequency power (LF), high-frequency power (HF), total power (TP), LF power in normalized units (LF n.u.), HF power in normalized units (HF n.u.), and ratio of LF to HF (LF/HF). After adjusted for sex, age, body mass index, alcohol consumption, history of diabetes, left ventricular ejection fraction, and hemoglobin levels, our results demonstrated negative associations of HRV with levels of CRP and FIB, while positive associations between HRV and PA level, with effect sizes of as high as 35%-52% standard deviations (SD) changes in CRP, FIB, or PA per 1-SD change in HRV parameters. Therefore, decreased HRV in patients with GC predicts increased burdens of inflammation and coagulation and perturbed nutrition, suggesting that short-term HRV measurement can potentially be a noninvasive biomarker for GC prognosis.

Multidrug resistance (MDR) is the primary cause for the failure of chemotherapy in the treatment of colon cancer. Recent research has indicated that the combination of a chemotherapeutic agent and a mitochondrial inhibitor might represent a promising strategy to help overcome MDR. However, for this approach to be clinically effective, it is important that the two drugs can be actively and simultaneously delivered into tumor cells at an optimal ratio and completely released drug within cells. To address these challenges, we designed and prepared a folate receptor-targeted and redox-responsive drug delivery system (FA-ss-P/A) that was able to co-deliver paclitaxel (PTX) and adjudin (ADD) to reverse colon cancer MDR. The PTX prodrug was obtained by conjugating PTX to dextrin via a disulfide-linkage. Then, folic acid (FA) was modified on the PTX prodrug. Finally, ADD, a mitochondrial inhibitor, was encapsulated in the PTX prodrug-formed micelles. A series of in vitro and in vivo experiments subsequently demonstrated that FA-ss-P/A can effectively reverse MDR by increasing cell uptake, inhibiting PTX efflux, and improving drug release.

In this study, we analyzed GPC family genes in colorectal cancer (CRC) and the possible mechanism of action of GPC1 in CRC. CRC patient data were extracted from The Cancer Genome Atlas, and the prognostic significance of GPC1 expression and its association with clinicopathological features were identified by Kolmogorov–Smirnov test. CRC patients with high GPC1 expression had poor overall survival compared with patients with low GPC1 expression. In vitro experiments demonstrated that knockdown of GPC1 significantly inhibited the proliferation and migration and promoted cell apoptosis in CRC cell lines. Gene Ontology analysis of differential genes indicated that GPC1 may influence the TGF-β1 signaling pathway. Additional experiments revealed that silencing GPC1 suppressed the levels of TGF-β1 and p-SMAD2 but increased the expression of SMAD2. Taken together, these findings suggest that GPC1 may function as a tumor promoter in CRC cells through promoting TGF-β signaling pathway. Our results also indicate that GPC1 may serve as a critical effector in CRC progression and a new potential target for CRC therapy.

In order to manage both the strength and ductility of Al–Si alloys additively manufactured by laser powder bed fusion (L-PBF), an attempt was made to introduce nanoscale precipitates within the α-Al (fcc) supersaturated solid solution using the L-PBF manufactured Al–12%Si alloy by artificial aging treatments. The aging treatment at 120°C improved both the tensile strength and ductility (total elongation) of the L-PBF manufactured specimen. The simultaneous strength–ductility enhancement is due to the homogeneously distributed nanoscale Si precipitates that enhanced the strain hardening. These results provide new insights for overcoming the strength-ductility trade-off in the L-PBF manufactured Al alloys.

Abstract Solitary fibrous tumor (SFT) derived from the abdominal wall is rare. We report a case of SFT in the abdominal wall. When abdominal computed tomography reveals soft‐tissue mass and analysis of preoperative needle biopsy reveals spindle cell tumor, the possibility of SFT should be considered.

Objective To develop and externally validate a prognostic nomogram to predict overall survival (OS) in patients with resectable colon cancer. Methods Data for 50,996 patients diagnosed with non-metastatic colon cancer were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were assigned randomly to the training set (n = 34,168) or validation set (n = 16,828). Independent prognostic factors were identified by multivariate Cox proportional hazards regression analysis and used to construct the nomogram. Harrell’s C-index and calibration plots were calculated using the SEER validation set. Additional external validation was performed using a Chinese dataset (n = 342). Results Harrell’s C-index of the nomogram for OS in the SEER validation set was 0.71, which was superior to that using the 7th edition of the American Joint Committee on Cancer TNM staging (0.59). Calibration plots showed consistency between actual observations and predicted 1-, 3-, and 5-year survival. Harrell’s C-index (0.72) and calibration plot showed excellent predictive accuracy in the external validation set. Conclusions We developed a nomogram to predict OS after curative resection for colon cancer. Validation using the SEER and external datasets revealed good discrimination and calibration. This nomogram may help predict individual survival in patients with colon cancer.

The recent advances in gene chip technology have led to the identification of multiple metabolism-related genes that are closely associated with colorectal cancer (CRC). Nevertheless, none of these genes could accurately diagnose or predict CRC. The prognosis of CRC has been made by previous prognostic models constructed by using multiple genes, however, the predictive function of multi-gene prognostic models using metabolic genes for the CRC prognosis remains unexplored. In this study, we used the TCGA-CRC cohort as the test dataset and the GSE39582 cohort as the experimental dataset. Firstly, we constructed a prognostic model using metabolic genes from the TCGA-CRC cohort, which were also associated with CRC prognosis. We analyzed the advantages of the prognostic model in the prognosis of CRC and its regulatory mechanism of the genes associated with the model. Secondly, the outcome of the TCGA-CRC cohort analysis was validated using the GSE39582 cohort. We found that the prognostic model can be employed as an independent prognostic risk factor for estimating the CRC survival rate. Besides, compared with traditional clinical pathology, it can precisely predict CRC prognosis as well. The high-risk group of the prognostic model showed a substantially lower survival rate as compared to the low-risk group. In addition, gene enrichment analysis of metabolic genes showed that genes in the prognostic model are enriched in metabolism and cancer-related pathways, which may explain its underlying mechanism. Our study identified a novel metabolic profile containing 11 genes for prognostic prediction of CRC. The prognostic model may unravel the imbalanced metabolic microenvironment, and it might promote the development of biomarkers for predicting treatment response and streamlining metabolic therapy in CRC.

Long non-coding RNAs (lncRNAs) are key regulators of a range of human diseases, including various cancers, with multiple previous studies having explored lncRNA dysregulation in the context of gastric cancer (GC). The present study sought to expand upon these previous results by downloading lncRNA, mRNA, and microRNA (miRNA) expression profiles derived from 180 GC tissues and 24 normal control tissues within the Cancer Genome Atlas (TCGA) database. These datasets were then interrogated to identify GC-related differentially expressed (DE) RNAs (|fold change| ≥ 2, FDR< 0.01), leading to the identification of 1946 DE lncRNAs, 123 DE miRNAs, and 3159 DE mRNAs. These results were then used to generate a putative GC-related competitive endogenous RNA (ceRNA) network composed of 131 lncRNAs, 9 miRNAs, and 78 mRNAs. Subsequent survival analyses based upon this network revealed 17 of these lncRNAs to be significantly associated with GC patient survival (P < 0.05). Further multivariable Cox regression and lasso analyses allowed for the construction of an 8-lncRNA risk score that was able to effectively predict GC patient survival with good discriminative ability. The Kaplan-Meier Plotter database further confirmed that network hub genes that were related to these 8 lncRNAs were associated with GC patient prognosis (P < 0.05). As the ceRNA network in the present study was constructed with a focus on both disease stage and differential gene expression, it represents a key resource that will offer valuable insights into the mechanistic roles of ceRNA pathways in GC development and progression.

BACKGROUND: COP9 signalosome subunit 2 (CSN2) is believed to be involved in human cancer, but its prognostic significance in colorectal cancer (CRC) has not been elucidated. PATIENTS AND METHODS: We retrospectively analyzed the expression of CSN2 andCD8+ tumor-infiltrating lymphocytes (TILs), and mismatch repair (MMR) status in 267 paraffin-embedded specimens using immunohistochemistry in a training cohort. A number of risk factors were used to form nomograms to evaluate survival, and Harrell's concordance index (C-index) was used to evaluate the predictive accuracy. Further validation was performed in an independent cohort of 238cases. RESULTS: Low CSN2 expression and a low number of CD8 + TILs were significantly associated with diminished disease-free survival (DFS) and overall survival (OS) in CRC patients, and patients with MMR-deficient CRC had enhanced DFS and OS. Moreover, the multivariate Cox analysis identified CSN2, CD8 + TILs, and MMR status as independent prognostic factors for DFS and OS. Using these three markers and four clinicopathological risk variables, two nomograms were constructed and validated for predicting DFS and OS (C-index: training cohort, 0.836 (95% CI:0.804–0.868) and 0.841 (0.808–0.874), respectively; validation cohort, 0.801 (0.760–843) and 0.843 (0.806–0.881), respectively). CONCLUSIONS: CSN2, CD8+ TILs, and MMR status were independent prognostic factors. The nomograms could be used to generate individualized predictions for DFS and OS.

Background/Aims: Polycystic ovary syndrome (PCOS), characterized by female infertility and metabolic abnormalities, is one of the most common endocrine disorders. The etiology of PCOS remains unknown. The comprehensive analysis of protein alterations in PCOS patients is meaningful for identifying diagnostic biomarkers of PCOS. Here, we explored the clinical value of serum proteins as novel biomarkers to detect PCOS with low progesterone level. Methods: A total of 43 patients with PCOS and 30 healthy women were enrolled. Protein array was used to detect the variations of serum proteins between PCOS patients and healthy women. The level of five serum proteins was further confirmed by ELISA and western blot. The human ovarian granulosa cells (KGN) was cultured to examine the underlying mechanism of PCOS. CCK8 assay and western blot were carried out to evaluate the alterations in proliferative ability, TUNEL assay and DAPI staining to detect the apoptosis of KGN cells. Results: Among the 507 proteins, we identified 76 differentially expressed serum proteins (≧1.5 fold), with 40 elevated and 36 decreased proteins. Moreover, 47 proteins were newly reported in PCOS. The alterations in the five significantly decreased proteins (EREG, inhibin βA, IDE, PDGF-D and KNG1) were further confirmed by ELISA and western blot. The level of these proteins were directly associated with the low progesterone, and the expression could be upregulated by progesterone. EREG and inhibin βA also promoted the proliferation and inhibited the apoptosis of ovarian granulosa cells. Conclusion: The study highlights that serum proteins are differentially expressed in PCOS patients and healthy women, and EREG and inhibin βA levels are upregulated by progesterone, which are correlated with ovarian functions. The study suggests that EREG and inhibin βA may be applied as novel potential biomarkers for PCOS with low progesterone level.

Wideband absorbers are desirable for optoelectronics. Nevertheless, the absorption platforms are usually with broad spectral absorption but complex structure or narrowband absorption but simple design. Herein, a new infrared broadband absorption platform formed by a titanium nanoholes array is theoretically proposed and numerically demonstrated. The full absorption width at half-maximum is about 84% and the average absorption in the whole wavelength range from 0.75 μm to 3.25 μm is also up to 80%. Optical cavity with strong optical field coupling effect has been utilized to enhance the absorption in the wideband spectrum. Moreover, in sharp contrast to the narrowband absorption for the system with noble metal, ultra-broadband absorption is achieved in the platform due to the using of titanium metal. Furthermore, the absorption features including the bandwidth and operating wavelength positions can be both manipulated via the structural parameters. Strong plasmonic resonant coupling and photonic cavity trapping via the metal and dielectric resonators are the main contributions. These findings could be interesting for the broadband absorber platform, light flow modulator, etc. Keywords: Plasmonics, Broadband absorber, Optical cavity, Titanium

Long non-coding RNAs (lncRNAs) have been shown to play important roles in many human diseases. However, their functions and mechanisms in tumorigenesis and development remain largely unknown. Here, we demonstrated that focally amplified lncRNA in epithelial cancer (FALEC) was upregulated and significantly correlated with lymph node metastasis, TNM stage in gastric cancer (GC). Further experiments revealed that FALEC knockdown significantly inhibited GC cells migration and invasion in vitro. Mechanistic investigations demonstrated that small interfering RNA-induced silencing of FALEC decreased expression of the nearby gene extracellular matrix protein 1 (ECM1) in cis. Additionally, ECM1 and FALEC expression were positively correlated, and high levels of ECM1 predicted shorter survival time in GC patients. Our results suggest that the downregulation of FALEC significantly inhibited the migration and invasion of GC cells through impairing ECM1 expression by exerting an enhancer-like function. Our work provides valuable information and a novel promising target for developing new therapeutic strategies in GC.

In this study, we systematically investigated microstructures and tensile properties of an Al–12mass%Si alloy additive-manufactured by laser powder bed fusion (LPBF) process and subsequently annealed at various temperatures. Microstructure of the as-fabricated sample was characterized by a number of melt pools consisting of α-Al phases surrounded by Si eutectic phases. Fine Si precipitates were observed in the α-Al phase in the sample annealed at 200 °C. The eutectic Si phase appears to agglutinate, resulting in a coarsened Si phase formed at high temperatures above 300 °C. The initial cellular microstructure completely disappears and a number of coarsened Si phases and plate-shaped intermetallic phases (β-AlFeSi) were formed in the sample annealed at 530 °C. However, the grain morphology of the α-Al matrix slightly changed after the annealing at high temperatures. The as-fabricated specimen showed a high strength above 400 MPa and a low ductility of below 10% in total elongation. The tensile ductility varied depending on the tensile direction. The annealed specimens exhibited a lower tensile strength and larger elongation, whereas the direction dependence of the tensile properties was less pronounced in the specimens annealed at higher temperatures. The anisotropic tensile ductility can be rationalized by preferential fractures occurred around melt pool boundaries.

Heat stress is one of the most important environmental stressors facing poultry production and welfare worldwide. The detrimental effects of heat stress on poultry range from reduced growth and egg production to impaired health. Animal vocalisations are associated with different animal responses and can be used as useful indicators of the state of animal welfare. It is already known that specific chicken vocalisations such as alarm, squawk, and gakel calls are correlated with stressful events, and therefore, could be used as stress indicators in poultry monitoring systems. In this study, we focused on developing a hen vocalisation detection method based on machine learning to assess their thermal comfort condition. For extraction of the vocalisations, nine source-filter theory related temporal and spectral features were chosen, and a support vector machine (SVM) based classifier was developed. As a result, the classification performance of the optimal SVM model was 95.1 ± 4.3% (the sensitivity parameter) and 97.6 ± 1.9% (the precision parameter). Based on the developed algorithm, the study illustrated that a significant correlation existed between specific vocalisations (alarm and squawk call) and thermal comfort indices (temperature-humidity index, THI) (alarm-THI, R = −0.414, P = 0.01; squawk-THI, R = 0.594, P = 0.01). This work represents the first step towards the further development of technology to monitor flock vocalisations with the intent of providing producers an additional tool to help them actively manage the welfare of their flock.

BACKGROUND:Endoscopic resection and gastrectomy are treatment modalities for early gastric cancer, but their relative benefits and risks are unclear. We conducted a systematic review and meta-analysis to compare endoscopic resection and gastrectomy for treating early gastric cancer. METHODS:We searched PubMed, Embase, and the Cochrane Library until April 2015 for studies comparing endoscopic resection with gastrectomy for treatment of early gastric cancer. Outcome measures were five-year overall survival (OS), length of hospital stay and postoperative morbidity. We calculated pooled hazard ratio (HR), weighted mean difference (WMD) and odds ratio (OR) using random effects models. RESULTS:Six studies comprising 1,466 patients (618 endoscopic resection and 848 gastrectomy) met inclusion criteria. Five-year OS was similar between endoscopic resection and gastrectomy (HR, 1.06; 95% CI: 0.61 to 1.83). Endoscopic resection was associated with shorter hospital stays (WMD, -6.94; 95% CI: -7.59 to -6.29) and reduced overall postoperative morbidity (OR, 0.36; 95% CI: 0.17 to 0.74). CONCLUSIONS:While five-year OS is similar between endoscopic resection and gastrectomy, endoscopic resection offers a shorter hospital stay and fewer complications than gastrectomy for treating early gastric cancer. Endoscopic resection is a reasonable treatment for early gastric cancer with a negligible risk of lymph node metastasis.

LTE deployment is being accelerated due to its improved radio access structure meeting the requirements of current and next generation of wireless networks. Its low band application presents useful aspects such as low density of base station while providing good in-building penetration. In this work, we design and develop a dual-polarized base station antenna supporting 698 MHz to 960 MHz with an azimuth-plan half-power beam width of 90° covering all mainstream LTE 700/800/900 MHz frequency bands representing the widest low frequency range being actively used in the current mobile communication industry. In the design process, rigorous algorithm based on swarm method is developed to tune the electrical performances under strict base station antenna requirements. Experimental results from pattern tests demonstrate the design analysis and the significant advantages of using swarm method in the antenna development process.