Should Steroid Therapy Be Necessarily Needed for Autoimmune Pancreatitis Patients with Lesion Resected due to Misdiagnosed or Suspected Malignancy?

To explore whether steroid therapy should be needed for autoimmune pancreatitis patients after operation, eight AIP patients receiving operation were enrolled in this study from January 2007 to July 2013. All patients underwent liver function, CA19-9, and contrast-enhanced CT and/or MRI. Tests of IgG and IgG4 were performed in some patients. Tests of serum TB/DB, γ-GT, and γ-globulin were undergone during the perioperative period. Six cases receiving resection were pathologically confirmed as AIP patients and two were confirmed by intraoperative biopsy. For seven patients, TB/DB level was transiently elevated 1 day or 4 days after operation but dropped below preoperative levels or to normal levels 7 days after operation, and serum γ-GT level presented a downward trend. Serum γ-globulin level exhibited a downward trend among six AIP patients after resection, while an upward trend was found in another two AIP patients receiving internal drainage. Steroid therapy was not given to all six AIP patients until two of them showed new lines of evidence of residual or extrapancreatic AIP lesion after operation, while another two cases without resection received steroid medication. Steroid therapy might not be recommended unless there are new lines of evidence of residual extrapancreatic AIP lesions after resection

Proteomics analysis of serum protein profiling in pancreatic cancer patients by DIGE: up-regulation of mannose-binding lectin 2 and myosin light chain kinase 2

<p>Abstract</p> <p>Background</p> <p>Pancreatic cancer has significant morbidity and mortality worldwide. Good prognosis relies on an early diagnosis. The purpose of this study was to develop techniques for identifying cancer biomarkers in the serum of patients with pancreatic cancer.</p> <p>Methods</p> <p>Serum samples from five individuals with pancreatic cancer and five individuals without cancer were compared. Highly abundant serum proteins were depleted by immuno-affinity column. Differential protein analysis was performed using 2-dimensional differential in-gel electrophoresis (2D-DIGE).</p> <p>Results</p> <p>Among these protein spots, we found that 16 protein spots were differently expressed between the two mixtures; 8 of these were up-regulated and 8 were down-regulated in cancer. Mass spectrometry and database searching allowed the identification of the proteins corresponding to the gel spots. Up-regulation of mannose-binding lectin 2 and myosin light chain kinase 2, which have not previously been implicated in pancreatic cancer, were observed. In an independent series of serum samples from 16 patients with pancreatic cancer and 16 non-cancer-bearing controls, increased levels of mannose-binding lectin 2 and myosin light chain kinase 2 were confirmed by western blot.</p> <p>Conclusions</p> <p>These results suggest that affinity column enrichment and DIGE can be used to identify proteins differentially expressed in serum from pancreatic cancer patients. These two proteins 'mannose-binding lectin 2 and myosin light chain kinase 2' might be potential biomarkers for the diagnosis of the pancreatic cancer.</p

Image Segmentation based on Multi-region Multi-scale Local Binar Fitting and Kullback-Leibler Divergence

The inhomogeneity of intensity and the noise of image are the two major obstacles to accurate image segmentation by region-based level set models. To provide a more general solution to these challenges and address the difficulty of image segmentation methods to handle an arbitrary number of regions, we propose a region-based multi-phase level set method, which is based on the multi-scale local binary fitting (MLBF) and the Kullback–Leibler (KL) divergence, called KL–MMLBF. We first apply the multi-scale theory and multi-phase level set framework to the local binary fitting model to build the multi-region multi-scale local binary fitting (MMLBF). Then the energy term measured by KL divergence between regions to be segmented is incorporated into the energy function of MMLBF. KL–MMLBF utilizes the between-cluster distance and the adaptive kernel function selection strategy to formulate the energy function. Being more robust to the initial location of the contour than the classical segmentation models, KL–MMLBF can deal with blurry boundaries and noise problems. The results of experiments on synthetic and medical images have shown that KL–MMLBF can improve the effectiveness of segmentation while ensuring the accuracy by accelerating this minimization of this energy function and the model has achieved better segmentation results in terms of both accuracy and efficiency to analyze the multi-region image

Chinese construction firms in reform

Since the economic reforms that began 20 years ago, and especially with the enterprise reforms in recent years, ownership of Chinese construction firms has evolved from traditional state and collective ownership towards a mixed economy characterised by diversified ownership forms. Based on a questionnaire survey and personal interviews with individuals from firms representing four types of ownership, it has been determined that the majority of Chinese construction firms have already embraced commercial objectives and behaviour patterns similar to those of typical firms in developed market economies. Nevertheless, despite the important progress that the reforms have made, this study indicated that various construction firms during this transition are suffering serious difficulties caused by the former planned system and underdeveloped market mechanisms. Unfair practices were found to be quite serious in the construction market. Major problems stem from clients' abnormal behaviour in forcing the price down, asking contractors to finance a project wholly or partially during its construction, and delays in payment; these actions have caused severe financial difficulties to Chinese firms and seriously disrupted the normal order of market stability.China, Chinese construction firms, reform, firm objective, firm behaviour, ownership form,

Research on the Model of a Navigation and Positioning Algorithm for Agricultural Machinery Based on the IABC-BP Network

Improving the positioning accuracy and stability of a single BDS/INS sensor system in agricultural machinery is important for expanding the application scenarios of agricultural machinery. This paper proposes a navigation and positioning model based on an improved bee-colony-algorithm-optimized BP network (the IABC-BP model). The main aspect of this work involves introducing adaptive coefficients and speed adjustment coefficients that obey Gaussian distribution to ensure the balance between the rate of convergence, group flexibility, and searchability in the search process. The implicit adaptive layer formula of the BP network is proposed, and the BDS/INS navigation and positioning model for agricultural machinery is established using the IABC algorithm and the Kalman filter. Simulation tests and analyses of real-world application scenarios were conducted on the model, and the results showed that, compared with the original model, the performance of the model improved by 90.65%, 84.11%, and 25.96%, indicating that the proposed model has high accuracy and effectiveness. In the information fusion and compensation correction mode, the algorithm processes errors such as longitude and latitude within the target range and can achieve reliable navigation and positioning accuracy in a short period. At the same time, the model has good stability and generalization ability, and can be applied to other navigation scenarios in the future to expand its application scope

Combined test of serum CgA and NSE improved the power of prognosis prediction of NF-pNETs

Purpose: Chromogranin A (CgA) and neuron-specific enolase (NSE) are important markers for neuroendocrine tumors; however, the clinical value of combining these markers has not been well studied. In this study, we investigated the utility of each marker individually and in combination for patients with nonfunctional pancreatic neuroendocrine tumors (NF-pNETs). Patients and Methods: In this study, NF-pNET patients and controls were recruited from December 2011 to March 2016; 784 serum samples from peripheral vein were collected. The clinical characteristics and biomarker values of all the individuals were recorded and analyzed. Tumor burdens were calculated by CT/MRI scan. Receiver-operating characteristic curves were constructed to assess the diagnostic predictive values; sensitivity and specificity were calculated to determine the cut-off value. Therapeutic responses reflected on the changes of the biomarkers’ concentration were assessed by the RECIST criterion. Clinical relations between the prognosis and the biomarker values were also analyzed. Statistical significance was defined as P value less than 0.05. Results: Among the 167 NF-pNETs patients, 82 were males (49.1%) and the mean age was 50.0 (17.4). The mean CgA values of G1, G2 and G3 NF-pNENs were 75, 121 and 134 μg/L (P < 0.05), respectively. In NF-pNETs, CgA correlated with the WHO tumor grade (WHO G1 vs G2, P < 0.05); the linear regression relationships were found between the tumor burdens (both in pancreas and liver) and CgA concentration (P < 0.001); changes in CgA and NSE concentrations also reflect treatment response (P < 0.001). Conclusion: CgA and NSE are important diagnostic and follow-up markers in patients with NF-pNETs. The combined monitoring of CgA and NSE possesses more accuracy than individual values of CgA and NSE at predicting prognosis and disease progression

Clinical relevance of different WHO grade 3 pancreatic neuroendocrine neoplasms based on morphology

Purpose: Emerging evidence suggests G3 pancreatic neuroendocrine neoplasms (pNENs) present heterogeneous morphology and biology. The 2017 WHO classification has introduced a new category of well-differentiated pancreatic neuroendocrine tumors (WD-pNETs) G3, compared with poorly differentiated pancreatic neuroendocrine carcinomas (PD-pNECs) G3. We aim to analysis the demographics and outcomes of patients with resectable 2017 WHO G3 pNENs to facilitate the distinction between two entities. Methods: The multi-institutional retrospective cohort involving 57 surgically treated patients affected by 2017 WHO G3 pNENs were morphologically identified and clinically analyzed. Patients having WD-pNETs G3 and those having PD-pNECs G3 were compared. Results: Thirty patients had WD-pNETs and 27 patients had PD-pNECs. The distributions of Ki-67 and mitotic count in patients with PD-pNECs or WD-pNETs showed remarkable disparities. ROC indicated cut-off value of Ki-67 was 45. PD-pNECs were more common in patients with elevated Ki-67 and mitotic count, advanced AJCC TNM stage, vascular invasion, regional lymph-node metastases, elevated NSE and decreased CgA levels compared with WD-pNETs (P < 0.05). The association between 2017 WHO G3 grade and TTR was statistically significant (P < 0.05). Univariate analysis indicated OS rates were associated with morphologic differentiation (WD-pNETs vs PD-pNECs), Ki-67, TNM staging, synchronous distant metastases, initial treatments, vascular invasion, regional lymph nodes metastases, mitotic count and age (P < 0.05). Multivariate analyses illustrated Ki-67, differentiation, TNM staging and vascular invasion were independent predictors (P < 0.05). Conclusions: PD-pNECs G3 presented malignant biological behavior and dismal outcome compared with WD-pNETs G3. These findings challenge 2010 WHO classification and suggest the categorization can be improved by refined tumor grading