Ubiquitin-specific protease 7 maintains c-Myc stability to support pancreatic cancer glycolysis and tumor growth.

Background: The typical pathological feature of pancreatic ductal adenocarcinoma (PDAC) is a significant increase in stromal reaction, leading to a hypoxic and poorly vascularized tumor microenvironment. Tumor cells undergo metabolic reprogramming, such as the Warburg effect, yet the underlying mechanisms are not fully understood.

Methods: Interference and overexpression experiments were conducted to analyze the in vivo and in vitro effects of USP7 on the growth and glycolysis of tumor cells.

Deep causal learning for pancreatic cancer segmentation in CT sequences.

Segmenting the irregular pancreas and inconspicuous tumor simultaneously is an essential but challenging step in diagnosing pancreatic cancer. Current deep-learning (DL) methods usually segment the pancreas or tumor independently using mixed image features, which are disrupted by surrounding complex and low-contrast background tissues. Here, we proposed a deep causal learning framework named CausegNet for pancreas and tumor co-segmentation in 3D CT sequences.

Association between cardiovascular disease and risk of female sexual dysfunction: a systematic review and meta-analysis.

Aims: Female sexual dysfunction (FSD) is a considerably underestimated condition. It has been repeatedly reported that patients with cardiovascular diseases (CVD) may suffer from an increased risk of FSD. However, there is still a lack of comprehensive and systematic evaluation of various CVD and FSD.

Multi-Dimensional Cascaded Net with Uncertain Probability Reduction for Abdominal Multi-Organ Segmentation in CT Sequences.

Background And Objective: Deep learning abdominal multi-organ segmentation provides preoperative guidance for abdominal surgery. However, due to the large volume of 3D CT sequences, the existing methods cannot balance complete semantic features and high-resolution detail information, which leads to uncertain, rough, and inaccurate segmentation, especially in small and irregular organs. In this paper, we propose a two-stage algorithm named multi-dimensional cascaded net (MDCNet) to solve the above problems and segment multi-organs in CT images, including the spleen, kidney, gallbladder, esophagus, liver, stomach, pancreas, and duodenum.

A metric learning-based method using graph neural network for pancreatic cystic neoplasm classification from CTs.

Purpose: Pancreatic cystic neoplasms (PCNs) are relatively rare neoplasms and difficult to be classified preoperatively. Ordinary deep learning methods have great potential to provide support for doctors in PCNs classification but require a quantity of labeled samples and exact segmentation of neoplasm. The proposed metric learning-based method using graph neural network (GNN) aims to overcome the limitations brought by small and imbalanced dataset and get fast and accurate PCNs classification result from computed tomography (CT) images.

Evaluating perioperative glycemic status after different types of pancreatic surgeries via continuous glucose monitoring system: a pilot study.

Background: Perioperative glycemic status after pancreatic surgery has never been described. However, it's essential for optimal perioperative glucose management and understanding the pathogenesis of new-onset diabetes mellitus (NODM) after pancreatectomy. Continuous glucose monitoring (CGM) system provides us a helpful tool for closely monitoring and studying perioperative glucose change.

Computer-aided differentiates benign from malignant IPMN and MCN with a novel feature selection algorithm.

In clinical practice, differentiating benign from malignant intraductal papillary mucinous neoplasm (IPMN) and mucinous cystic neoplasm (MCN) preoperatively is crucial for deciding future treating algorithm. However, it remains challenging as benign and malignant lesions usually show similarities in both imaging appearances and clinical indices. Therefore, a robust and accurate computer-aided diagnosis (CAD) system based on radiomics and clinical indices was proposed in this paper to solve this dilemma.

Exosome-delivered CD44v6/C1QBP complex drives pancreatic cancer liver metastasis by promoting fibrotic liver microenvironment.

Objective: Pancreatic ductal adenocarcinoma (PDAC) shows a remarkable predilection for liver metastasis. Pro-oncogenic secretome delivery and trafficking via exosomes are crucial for pre-metastatic microenvironment formation and metastasis. This study aimed to explore the underlying mechanisms of how PDAC-derived exosomes (Pex) modulate the liver microenvironment and promote metastasis.

Partial pancreatic tail preserving subtotal pancreatectomy for pancreatic cancer: Improving glycemic control and quality of life without compromising oncological outcomes.

Background: Total pancreatectomy (TP) is usually considered a therapeutic option for pancreatic cancer in which Whipple surgery and distal pancreatectomy are undesirable, but brittle diabetes and poor quality of life (QoL) remain major concerns. A subset of patients who underwent TP even died due to severe hypoglycemia. For pancreatic cancer involving the pancreatic head and proximal body but without invasion to the pancreatic tail, we performed partial pancreatic tail preserving subtotal pancreatectomy (PPTP-SP) in selected patients, in order to improve postoperative glycemic control and QoL without compromising oncological outcomes.

WD repeat-containing protein 1 maintains β-Catenin activity to promote pancreatic cancer aggressiveness.

Background: The molecular signature underlying pancreatic ductal adenocarcinoma (PDAC) progression may include key proteins affecting the malignant phenotypes. Here, we aimed to identify the proteins implicated in PDAC with different tumour-node-metastasis (TNM) stages.

Methods: Eight-plex isobaric tags coupled with two-dimensional liquid chromatography-tandem mass spectrometry were used to analyse the proteome of PDAC tissues with different TNM stages.

Controlling Nutritional Status score is superior to Prognostic Nutritional Index score in predicting survival and complications in pancreatic ductal adenocarcinoma: a Chinese propensity score matching study.

Preoperative nutritional status plays an important role in predicting postoperative outcomes. Prognostic Nutritional Index (PNI) and Controlling Nutritional Status (CONUT) are good tools to assess patients' nutritional status. They have been used in predicting outcomes in various malignancies, but few studies have focused on pancreatic adenocarcinoma (PDAC) patients.

LRG-1 promotes pancreatic cancer growth and metastasis via modulation of the EGFR/p38 signaling.

Background: The abnormal expression of leucine-rich-alpha-2-glycoprotein 1 (LRG-1) is reported to be associated with multiple malignancies, but its role in the progression of pancreatic ductal adenocarcinoma (PDAC) remains to be determined.

Methods: The expression of LRG-1 was assessed in PDAC tissues by RT-PCR, Western blot and immunohistochemistry. LRG-1-silenced or overexpressed cell lines were constructed using shRNA or LRG-1-overexpressing plasmids.

Total pancreatectomy for pancreatic malignancy with preservation of the spleen.

Background: Total pancreatectomy may be necessary to achieve margin-negative resection for pancreatic cancer. However, despite the desirability of saving the spleen, the feasibility, safety, and oncological outcomes of spleen-preserving total pancreatectomy have not been studied in patients with malignancy involving the pancreatic neck or proximal body. The aim of this study was to report the efficacy of spleen-preserving total pancreatectomy using the Warshaw technique for patients with pancreatic malignancies.

A Comprehensive Proteome Analysis of Peripheral Blood Mononuclear Cells (PBMCs) to Identify Candidate Biomarkers of Pancreatic Cancer.

Background/aim: Pancreatic cancer (PC) is currently the fourth leading cause of cancer-related mortality worldwide. Peripheral blood mononuclear cells (PBMCs) is a subpopulation of accessible and functional immune cells. Comparative analysis of the proteome of PBMCs can help us elucidate the mechanism of disease and find potential biomarkers for diagnosis.

Dynamic quantitative detection of ABC transporter family promoter methylation by MS-HRM for predicting MDR in pancreatic cancer.

The main focus of the present study was to evaluate whether ABC transporter family promoter methylation predicted multidrug resistance in gemcitabine-resistant cancer cell lines (BxPC-3/Gem and PANC-1/Gem). Using low concentrations of gemcitabine, the cell lines acquired drug resistance with different initial gemcitabine concentrations. A novel technology, methylation-sensitive high-resolution melting, was used to monitor the dynamic changes of ABC transporter family promoter methylation, including ATP binding cassette subfamily B member 1 (ABCB1), ATP binding cassette subfamily C (ABCC) and ATP binding cassette subfamily G member 2 (ABCG2) mRNA expression.

Functional engineered human cardiac patches prepared from nature's platform improve heart function after acute myocardial infarction.

With the advent of induced pluripotent stem cells and directed differentiation techniques, it is now feasible to derive individual-specific cardiac cells for human heart tissue engineering. Here we report the generation of functional engineered human cardiac patches using human induced pluripotent stem cells-derived cardiac cells and decellularized natural heart ECM as scaffolds. The engineered human cardiac patches can be tailored to any desired size and shape and exhibited normal contractile and electrical physiology in vitro.