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Abstract Emerging evidence suggests the dysregulation of long non-coding RNAs (lncRNAs) involved in pancreatic cancer (PC). However, the function of LINC00930 in PC has not been elaborated. In this study, we found that LINC00930 was significantly down-regulated in PC cell lines and tissues, and associated with tumor size, lymphatic metastasis, TNM stage and poor prognosis. According to the bioinformatics database, the downregulation of LINC00930 was a common event in PC associated with prognosis and EMT. Overexpression of LINC00930 inhibited the aggressive cancer phenotypes including proliferation, metastasis and epithelial-mesenchymal transition (EMT) of PC in vitro and in vivo. Bioinformatics and dual-luciferase reporter assay indicated that miR-6792-3p could directly bind to LINC00930. Additionally, the Zinc finger and BTB domain containing 16 (ZBTB16) was significantly declined in PC, which was predicted to be the downstream gene of miR-6792-3p. MiR-6792-3p mimic rescued the decreased proliferation, metastasis and EMT caused by ZBTB16 in PC cells. The LINC00930/miR-6792-3p/ZBTB16 axis was associated with the malignant progression and process of PC. The relative expression of LINC00930 was negatively correlated with the expression of miR-6792-3p and was closely linked with ZBTB16 levels in PC. LINC00930 might serve as a potential prognostic biomarker and therapeutic target for PC.

Abstract Stem cell‐derived pancreatic progenitors (SC‐PPs), as an unlimited source of SC‐derived β (SC‐β) cells, offers a robust tool for diabetes treatment in stem cell‐based transplantation, disease modeling, and drug screening. Whereas, PDX1+/NKX6.1+ PPs enhances the subsequent endocrine lineage specification and gives rise to glucose‐responsive SC‐β cells in vivo and in vitro. To identify the regulators that promote induction efficiency and cellular function maturation, single‐cell RNA‐sequencing is performed to decipher the transcriptional landscape during PPs differentiation. The comprehensive evaluation of functionality demonstrated that manipulating LINC MIR503HG using CRISPR in PP cell fate decision can improve insulin synthesis and secretion in mature SC‐β cells, without effects on liver lineage specification. Importantly, transplantation of MIR503HG−/− SC‐β cells in recipients significantly restored blood glucose homeostasis, accompanied by serum C‐peptide release and an increase in body weight. Mechanistically, by releasing CtBP1 occupying the CDH1 and HES1 promoters, the decrease in MIR503HG expression levels provided an excellent extracellular niche and appropriate Notch signaling activation for PPs following differentiation. Furthermore, this exhibited higher crucial transcription factors and mature epithelial markers in CDH1High expressed clusters. Altogether, these findings highlighted MIR503HG as an essential and exclusive PP cell fate specification regulator with promising therapeutic potential for patients with diabetes.

When the two eyes are presented with highly distinct stimuli, the resulting visual percept generally switches every few seconds between the two monocular images in an irregular fashion, giving rise to a phenomenon known as binocular rivalry. While a host of theoretical studies have explored potential mechanisms for binocular rivalry in the context of evoked model dynamics in response to simple stimuli, here we investigate binocular rivalry directly through complex stimulus reconstructions based on the activity of a two-layer neuronal network model with competing downstream pools driven by disparate monocular stimuli composed of image pixels. To estimate the dynamic percept, we derive a linear input-output mapping rooted in the non-linear network dynamics and iteratively apply compressive sensing techniques for signal recovery. Utilizing a dominance metric, we are able to identify when percept alternations occur and use data collected during each dominance period to generate a sequence of percept reconstructions. We show that despite the approximate nature of the input-output mapping and the significant reduction in neurons downstream relative to stimulus pixels, the dominant monocular image is well-encoded in the network dynamics and improvements are garnered when realistic spatial receptive field structure is incorporated into the feedforward connectivity. Our model demonstrates gamma-distributed dominance durations and well obeys Levelt's four laws for how dominance durations change with stimulus strength, agreeing with key recurring experimental observations often used to benchmark rivalry models. In light of evidence that individuals with autism exhibit relatively slow percept switching in binocular rivalry, we corroborate the ubiquitous hypothesis that autism manifests from reduced inhibition in the brain by systematically probing our model alternation rate across choices of inhibition strength. We exhibit sufficient conditions for producing binocular rivalry in the context of natural scene stimuli, opening a clearer window into the dynamic brain computations that vary with the generated percept and a potential path toward further understanding neurological disorders.

Macroscopic materials are heterogeneous, multi-elementary, and complex. No material is homogeneous or isotropic at a certain small scale. Parts of the material that differ from one another can be termed “natural chips.” At different spots on the material, the composition, structure, and properties vary slightly, and the combination of these slight differences establishes the overall material performance. This article presents a state-of-the-art review of research and applications of high-throughput statistical spatial-mapping characterization technology based on the intrinsic heterogeneity within materials. High-throughput statistical spatial-mapping uses a series of rapid characterization techniques for analysis from the macroscopic to the microscopic scale. Datasets of composition, structure, and properties at each location are obtained rapidly for practical sample sizes. Accurate positional coordinate information and references to a point-to-point correspondence are used to set up a database that contains spatial-mapping lattices. Based on material research and development design requirements, dataset spatial-mapping within required target intervals is selected from the database. Statistical analysis can be used to select a suitable design that better meets the targeted requirements. After repeated verification, genetic units that reflect the material properties are determined. By optimizing process parameters, the assembly of these genetic unit(s) is verified at the mesoscale, and quantitative correlations are established between the microscale, mesoscale, macroscale, practical sample, across-the-scale span composition, structure, and properties. The high-throughput statistical spatial-mapping characterization technology has been applied to numerous material systems, such as steels, superalloys, galvanization, and ferrosilicon alloys. This approach has guided the composition and the process optimization of various materials.

Background. Tai chi (TC) has received increased attention in stroke rehabilitation, yet services are greatly underutilized. An increasing number of systematic reviews and meta-analyses (SRs/MAs) have begun to investigate the effects of TC on balance function in stroke patients. The aim of this current study was to systematically collate, appraise, and synthesize the results of these SRs/MAs using a systematic overview. Methods. Eight databases were searched: PubMed, Cochrane Library, Embase, Web of Science, CNKI, SinoMed, Chongqing VIP, and Wanfang Data. SRs/MAs of TC on balance function in stroke patients were included. Literature selection, data extraction, and assessment of the review quality were performed by two independent reviewers. Methodological quality was assessed by the Assessing the Methodological Quality of Systematic Reviews 2 (AMSTAR-2), reporting quality by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and evidence quality by Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). Results. Nine SRs/MAs were included in this study. For methodological quality, what resulted in unsatisfactory methodological quality was noncompliance with critical item 4 (using a comprehensive literature search strategy) and critical item 7 (providing the list of excluded research literature). For reporting quality, what resulted in unsatisfactory reporting quality was inadequate reporting of Q1 (protocol and registration), Q8 (search), Q15 (risk of bias across studies), Q16 (additional analyses), Q22 (risk of bias across studies), Q23 (additional analysis), and Q27 (funding). For GRADE, the evidence quality was high in 0, moderate in 3, low in 11, and very low in 6. Risk of bias was the most common factor leading to downgrading of evidence, followed by inconsistency, imprecision, publication bias, and indirectness. Conclusions. TC may have beneficial effects on balance function in stroke survivors; however, this finding is limited by the generally low methodology, reporting quality, and evidence quality for published SRs/MAs.

BackgroundHepatocellular carcinoma (HCC) is one of the world’s most lethal malignant tumors with a poor prognosis. Growing evidence has been demonstrating that immune-related long non-coding RNAs (lncRNAs) are relevant to the tumor microenvironment (TME) and can help assess the effects of immunotherapy and evaluate one’s prognosis. This study aims to identify an immune-related lncRNA signature for the prospective assessment of the immunotherapy and prognosis in HCC.MethodWe downloaded HCC RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) project database. We first used ESTIMATE to evaluate the TME. Then, we conducted a cox regression analysis to construct a prognostic signature and the riskScore. We then applied the univariate Cox regression, multivariate Cox regression, principal components analysis (PCA), receiver operating characteristic (ROC) curve, and stratification analyses to confirm our previous assessments. Afterward, we employed a gene set enrichment analysis (GSEA) to explore the biological processes and pathways. Besides, we used CIBERSORT to estimate the abundance of tumor-infiltrating immune cells (TIICs). Furthermore, we investigated the relationship between the immune-related lncRNA signature and immune checkpoint genes. Finally, we used the quantitative real-time polymerase chain reaction (qRT-PCR) assays to demonstrate the expression of the six lncRNAs.ResultsWe identified six immune-related lncRNAs — MSC-AS1, AC145207.5, SNHG3, AL365203.2, AL031985.3, NRAV — which show the ability to stratify patients into high-risk and low-risk groups with significantly different survival rates. The univariate Cox regression, multivariate Cox regression, ROC, and stratification analyses confirmed that the immune-related six-lncRNA signature was a novel independent prognostic factor in HCC patients. The high-risk group and low-risk group illustrated contrasting distributions in PCA. The GSEA suggested that the immune-related six-lncRNA signature was involved in the immune-related biological processes and pathways. Besides, the immune-related six-lncRNA signature was associated with the infiltration of immune cells. Furthermore, it was linked with the expression of critical immune genes and could predict immunotherapy’s clinical response. Finally, the qRT-PCR demonstrated that the six lncRNAs were significantly differentially expressed in HCC cell lines and normal hepatic cell lines.ConclusionIn summary, we identified an immune-related six-lncRNA signature that can predict the outcomes, immune cell infiltration, and immunotherapy response in patients with hepatocellular carcinoma.

Abstract Background The regulatory mechanism of insulin-producing cells (IPCs) differentiation from induced pluripotent stem cells (iPSCs) in vitro is very important in the phylogenetics of pancreatic islets, the molecular pathogenesis of diabetes, and the acquisition of high-quality pancreatic β-cells derived from stem cells for cell therapy. Methods miPSCs were induced for IPCs differentiation. miRNA microarray assays were performed by using total RNA from our iPCs-derived IPCs containing undifferentiated iPSCs and iPSCs-derived IPCSs at day 4, day 14, and day 21 during step 3 to screen the differentially expressed miRNAs (DEmiRNAs) related to IPCs differentiation, and putative target genes of DEmiRNAs were predicted by bioinformatics analysis. miR-690 was selected for further research, and MPCs were transfected by miR-690-agomir to confirm whether it was involved in the regulation of IPCs differentiation in iPSCs. Quantitative Real-Time PCR (qRT-PCR), Western blotting, and immunostaining assays were performed to examine the pancreatic function of IPCs at mRNA and protein level respectively. Flow cytometry and ELISA were performed to detect differentiation efficiency and insulin content and secretion from iPSCs-derived IPCs in response to stimulation at different concentration of glucose. The targeting of the 3′-untranslated region of Sox9 by miR-690 was examined by luciferase assay. Results We found that miR-690 was expressed dynamically during IPCs differentiation according to the miRNA array results and that overexpression of miR-690 significantly impaired the maturation and insulinogenesis of IPCs derived from iPSCs both in vitro and in vivo. Bioinformatic prediction and mechanistic analysis revealed that miR-690 plays a pivotal role during the differentiation of IPCs by directly targeting the transcription factor sex-determining region Y (SRY)-box9. Furthermore, downstream experiments indicated that miR-690 is likely to act as an inactivated regulator of the Wnt signaling pathway in this process. Conclusions We discovered a previously unknown interaction between miR-690 and sox9 but also revealed a new regulatory signaling pathway of the miR-690/Sox9 axis during iPSCs-induced IPCs differentiation.

Abstract In the port transportation, the transportation vehicle is extremely easy to cause a bad condition in the transportation process due to the influence of foreign matter, and the current foreign matter detection is still carried out by manual methods. Based on this, this study is based on the automatic image recognition technology, using the binocular imaging system for video collection and analyzing the video images for foreign object recognition. We use extreme median filtering to perform image noise processing and improve the traditional Canny edge detection algorithm to obtain an improved edge detection method for Canny operator. The algorithm is used to perform image edge detection, and the image gray histogram is used to enhance the foreign object image processing. Combined with the experimental analysis, the detection method of this study has certain effects, which can be used for foreign object identification in port transportation channels and can provide theoretical reference for subsequent related research.

Cancer cells are characterized by malignant proliferation and aberrant metabolism and are thereby liable to the depletion of nutrients and accumulation of metabolic waste. To maintain cellular homeostasis, cancer cells are prone to upregulating the canonical autophagy pathway. Here, we identified paroxetine hydrochloride (Paxil) as a late autophagy inhibitor and investigated its killing effect on lung cancer cells and with a xenograft mouse model in vivo. Upregulated LC3-II and p62 expression indicated that Paxil inhibited autophagy. Acid-sensitive dyes (e.g., LysoTracker and AO staining) indicated reduced lysosomal acidity following Paxil treatment; consequently, the maturation of the pH-dependent hydroxylases (e.g., cathepsin B and D) substantially declined. Paxil also induced the fragmentation of mitochondria and further intensified ROS overproduction. Since the autophagy pathway was blocked, ROS rapidly accumulated, which activated JNK and p38 kinase. Such activity promoted the localization of Bax, which led to increased mitochondrial outer membrane permeability. The release of Cytochrome c with the loss of the membrane potential triggered a caspase cascade, ultimately leading to apoptosis. In contrast, the clearance of ROS by its scavenger, NAC, rescued Paxil-induced apoptosis accompanied by reduced p38 and JNK activation. Thus, Paxil blocked the autophagic flux and induced the mitochondria-dependent apoptosis via the ROS-MAPK pathway.

We propose a novel method to simulate soft tissue deformation for virtual surgery applications. The method considers the mechanical properties of soft tissue, such as its viscoelasticity, nonlinearity and incompressibility; its speed, stability and accuracy also meet the requirements for a surgery simulator. Modifying the traditional equation for mass spring dampers (MSD) introduces nonlinearity and viscoelasticity into the calculation of elastic force. Then, the elastic force is used in the constraint projection step for naturally reducing constraint potential. The node position is enforced by the combined spring force and constraint conservative force through Newton's second law. We conduct a comparison study of conventional MSD and position-based dynamics for our new integrating method. Our approach enables stable, fast and large step simulation by freely controlling visual effects based on nonlinearity, viscoelasticity and incompressibility. We implement a laparoscopic cholecystectomy simulator to demonstrate the practicality of our method, in which liver and gallbladder deformation can be simulated in real time. Our method is an appropriate choice for the development of real-time virtual surgery applications.

Diabetes affects millions of people worldwide, and β-cell replacement is one of the promising new strategies for treatment. Induced pluripotent stem cells (iPSCs) can differentiate into any cell type, including pancreatic β cells, providing a potential treatment for diabetes. However, the molecular mechanisms underlying the differentiation of iPSC-derived β cells have not yet been fully elucidated. Here, we generated pancreatic β-like cells from mouse iPSCs using a 3-step protocol and performed deep RNA sequencing to get a transcriptional landscape of iPSC-derived pancreatic β-like cells during the selective differentiation period. We then focused on the differentially expressed genes (DEGs) during the time course of the differentiation period, and these genes underwent Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway analysis. In addition, gene-act networks were constructed for these DEGs, and the expression of pivotal genes detected by quantitative real-time polymerase chain reaction was well correlated with RNA sequence (RNA-seq). Overall, our study provides valuable information regarding the transcriptome changes in β cells derived from iPSCs during differentiation, elucidates the biological process and pathways underlying β-cell differentiation, and promotes the identification and functional analysis of potential genes that could be used for improving functional β-cell generation from iPSCs.

Using an integral averaging method and generalized Riccati technique, by introducing a parameter β≥1, we derive new oscillation criteria for second-order partial differential equations with damping. The results are of high degree of generality and sharper than most known ones.

The acceleration of urbanization and the increasing demand for precise city planning have made the extraction of buildings and roads from remote sensing images crucial. Deep learning-based methods have propelled the progress of object extraction technology, but there are still challenges such as the missing and incomplete extraction of buildings and roads for small objects and occlusions. To address this issue, we propose a dual-path extraction network based on CNN and Transformer, combining local and global features to fully extract the semantic information of objects. To further enhance the semantic reconstruction capability of features, this paper introduces a multi-scale upsampling mechanism, thereby expanding the visual range of reconstruction. Finally, we adopt a deep supervision strategy to improve the reconstruction accuracy of objects at different resolutions. Our method has been tested on four remote sensing image datasets and has achieved excellent IoU scores on all datasets (Massachusetts Building and Roads Dataset: 76.69% and 66.41%, LRSNY and CHN6-CUG Roads Dataset: 88.96% and 61.99%). Furthermore, our method demonstrates superior performance compared to other mainstream image segmentation algorithms, fully demonstrating the effectiveness of our approach.

Automated extraction of roads from remotely sensed data come forth various usages ranging from digital twins for smart cities, intelligent transportation, urban planning, autonomous driving, to emergency management. Many studies have focused on promoting the progress of methods for automated road extraction from aerial and satellite optical images, synthetic aperture radar (SAR) images, and LiDAR point clouds. In the past 10 years, no a more comprehensive survey on this topic could be found in literature. This paper attempts to provide a comprehensive survey on road extraction methods that use 2D earth observing images and 3D LiDAR point clouds. In this review, we first present a tree-structure that separate the literature into 2D and 3D. Then, further methodologies level classification is demonstrated both in 2D and 3D. In 2D and 3D, we introduce and analyze the literature published in the last ten years. Except for the methodologies, we also review the aspects of data commonly used. Finally, this paper explores the existing challenges and future trends.

Background Pancreatic cancer is one of the most aggressive cancers, and the aggressiveness of pancreatic cancer is in part due to its intrinsic and extrinsic drug resistance characteristics, which are also associated with the acquisition of epithelial-to-mesenchymal transition (EMT). Increasing evidence suggests that EMT-type cells share many biological characteristics with cancer stem-like cells. And miR-200 has been identified as a powerful regulator of EMT. Methods Cancer Stem Cells (CSCs) of human pancreatic cancer cell line PANC-1 were processed for CD24, CD44 and ESA multi-colorstaining, and sorted out on a BD FACS Aria IImachine. RT-qPCR was performed using the miScript PCR Kit to assay the expression of miR-200 family. In order to find the role of miR-200a in the process of EMT, miR-200a mimic was transfected to CSCs. Results Pancreatic cancer cells with EMT phenotype displayed stem-like cell features characterized by the expression of cell surface markers CD24, CD44 and epithelial-specific antigen (ESA), which was associated with decreased expression of miR-200a. Moreover, overexpression of miR-200a was resulted in down-regulation of N-cadherin, ZEB1 and vimentin, but upregulation of E-cadherin. In addition, miR-200a overexpression inhibited cell migration and invasion in CSCs. Conclusion In our study, we found that miR-200a played an important role in linking the characteristics of cancer stem-like cells with EMT-like cell signatures in pancreatic cancer. Selective elimination of cancer stem-like cells by reversing the EMT phenotype to mesenchymal-toepithelial transition (MET) phenotype using novel agents would be useful for prevention and/or treatment of pancreatic cancer. [ABSTRACT FROM AUTHOR]

An efficient domino approach for the synthesis of arylated (Z)-enones or -enals through gold(I)-catalyzed reactions of enynols with furans was developed. PPh3AuNTf2was found to be an excellent catalyst to catalyze both of the Friedel−Crafts and furan/alkyne cyclization reactions in the same vessel. This method offers several advantages such as high stereoselectivities, mild reaction conditions, and easily accessible starting materials. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess the effect of intrahepatic injection of bone-derived green fluorescent protein (GFP)-transgenic murine mesenchymal stem cells (GFP-mMSCs) containing the human insulin(ins) gene in streptozotocin-induced diabetic mice. GFP-mMSCs were isolated from the bone marrow of GFP transgenic mice, expanded, and transfected with a recombinant retrovirus MSCV carrying the human insulin gene. C57BL/6J mice were made diabetic by an intraperitoneal administration of 160 mg/kg streptozotocin (STZ), followed by intrahepatic injection of transfected GFP-mMSCs. The variations in body weight and the blood glucose and serum insulin levels were determined after cell transplantation. GFP-mMSCs survival and human insulin expression in liver tissues were examined by fluorescent microscopy and immunohistochemistry. The body weight in diabetic mice that received GFP-mMSCs harboring the human insulin gene was increased by 6% within 6 weeks after treatment, and the average blood glucose levels in these animals were 10.40 ± 2.80 mmol/l (day 7) and 6.50 ± 0.89 mmol/l (day 42), respectively, while the average values of blood glucose in diabetic animals without treatment were 26.80 ± 2.49 mmol/l (day 7) and 25.40 ± 4.10 mmol/l (day 42), showing a significant difference ( p < 0.05). Moreover, secretion of human insulin of GFP-mMSCs in serum and animal liver was detected by radioimmunoassay (RIA) and immunohistochemistry (IHC). Experimental diabetes could be relieved effectively for up to 6 weeks by intrahepatic transplantation of murine mesenchymal stem cells expressing human insulin. This study implies a novel approach of gene therapy for type I diabetes. [ABSTRACT FROM AUTHOR]

Background: Natural products have numerous medicinal applications and play important roles in the biology of the organisms that accumulate them. Few methods are currently available for identifying proteins that bind to small molecules, therefore the discovery of cellular targets for natural products with pharmacological activity continues to pose a significant challenge in drug validation. Similarly, the identification of enzymes that participate in the biosynthesis or modification of natural products remains a formidable bottleneck for metabolic engineering. Flavonoids are one large group of natural products with a diverse number of functions in plants and in human health. The coupling of flavonoids to small ceramic and glass beads provides a first step in the development of high-throughput, solid-support base approaches to screen complex libraries to identify proteins that bind natural products. Results: The utilization of small glass and ceramic beads as solid supports for the coupling of small molecules was explored. Initial characterization of the beads indicated uniform and high capacity loading of amino groups. Once the beads were deemed adequate for the linking of small molecules by the coupling of NHS-fluorescein followed by microscopy, chemical hydrolysis and fluorometry, the flavonoid naringenin was modified with 1,4-dibromobutane, followed by the attachment of aminopropyltriethoxysilane. After NMR structural confirmation, the resulting 7-(4-(3- (triethoxysilyl)propylamino)butoxy) naringenin was attached to the ceramic beads. Conclusion: Our results demonstrate that ceramic and glass beads provide convenient solid supports for the efficient and facile coupling of small molecules. We succeeded in generating naringenin-coupled ceramic and glass beads. We also developed a convenient series of steps that can be applied for the solid-support coupling of other related flavonoids. The availability of solidsupport coupled naringenin opens up new opportunities for the identification of flavonoid-binding proteins. [ABSTRACT FROM AUTHOR]

Background: Pancreatic cancer is among the most lethal malignancies worldwide. In this study, we aimed to determine whether miR-573 could suppress pancreatic cancer cell proliferation, migration, and invasion by targeting E2F3. Materials and Methods: MiR-573 expression in pancreatic cancer tissues and cell lines was measured using real-time PCR. Target genes of miR-573 were screened using bioinformatics tools and confirmed using dual-luciferase reporter assay and real-time PCR. Pancreatic cancer cells were transfected using an miR-573 mimic or siRNA E2F3. Furthermore, cell proliferation, migration, and invasion were assessed using CCK-8, Edu staining, colony-forming assay, wound healing assay, and transwell assay in vitro . The in vivo effects of miR-573 were verified using tumor xenografts. Differential expression and prognostic analyses of miR-573 and E2F3 were visualized using the Kaplan‑Meier plotter and GEPIA. Results: We found that the expression of miR-573 was significantly reduced in pancreatic cancer tissues and cell lines. Overexpression of miR-573 obviously suppressed the proliferation, migration, and invasion of pancreatic cancer cells. The Dual-luciferase assay showed that miR-573 could specifically target E2F3. Furthermore, E2F3 was up-regulated in pancreatic cancer tissues and cell lines and E2F3 down-regulation inhibited the proliferation, migration, and invasion of pancreatic cancer cells. The ectopic expression of miR-573 inhibited xenograft tumor growth in vivo . Results from the Kaplan-Meier analysis and GEPIA showed that patients with a high level of miR-573 had a significantly reduced risk of death while those with a high level of E2F3 displayed significant correlation with the tumor stage and suffered worse prognosis. Conclusions: MiR-573 could suppress the proliferation, migration, and invasion of pancreatic cancer cells by targeting E2F3, thereby establishing miR-573 as a novel regulator of E2F3 and indicating its critical role in tumorigenesis, especially in pancreatic cancer., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)