Prognostic value of clinicopathological characteristics in patients with pancreatic cancer

Background： The purpose of this study was to analyze the effects of all clinical characteristics on the overall survival time, in order to provide a basis for determining the prognostic factor of patients with pancreatic cancer. Methods： A total of 103 pancreatic cancer patients were admitted to the Department of Radiotherapy and Chemotherapy of the Ruijin Hospital, Shanghai Jiaotong University School of Medicine, between January 2002 and December 2012. There were 68 men and 35 women; the median age was 62 years. Diagnoses of pancreatic cancer in all patients were confirmed by histopathology, cytology, or clinical diagnosis. The Kaplan-Meier method was performed to calculate the overall survival rate. The log-rank method was used to examine the univariate analysis. The Cox regression model was performed for multivariate analysis. Results： The median survival time was 293 days, the 1-, 2-, and 3-year survival rates were 27.18%, 5.83%, and 1.94%, respectively. Cox regression analysis revealed that age （P=0.015）, Karnofsky performance status （PS） （P=0.002）, surgical types （P〈0.001）, and platelet counts （P〈0.001） were independent prognostic factors affecting the overall survival of patients with pancreatic cancer. Conclusions＂ Pancreatic cancer had a poor prognosis, the general physical condition, age, the availability of radical surgery, and platelet counts were factors influencing the overall survival of patients with pancreatic cancer.

Energy enhanced tissue texture in spectral computed tomography for lesion classification

Tissue texture reflects the spatial distribution of contrasts of image voxel gray levels,i.e.,the tissue heterogeneity,and has been recognized as important biomarkers in various clinical tasks.Spectral computed tomography(CT)is believed to be able to enrich tissue texture by providing different voxel contrast images using different X-ray energies.Therefore,this paper aims to address two related issues for clinical usage of spectral CT,especially the photon counting CT(PCCT):(1)texture enhancement by spectral CT image reconstruction,and(2)spectral energy enriched tissue texture for improved lesion classification.For issue(1),we recently proposed a tissue-specific texture prior in addition to low rank prior for the individual energy-channel low-count image reconstruction problems in PCCT under the Bayesian theory.Reconstruction results showed the proposed method outperforms existing methods of total variation(TV),low-rank TV and tensor dictionary learning in terms of not only preserving texture features but also suppressing image noise.For issue(2),this paper will investigate three models to incorporate the enriched texture by PCCT in accordance with three types of inputs:one is the spectral images,another is the cooccurrence matrices(CMs)extracted from the spectral images,and the third one is the Haralick features(HF)extracted from the CMs.Studies were performed on simulated photon counting data by introducing attenuationenergy response curve to the traditional CT images from energy integration detectors.Classification results showed the spectral CT enriched texture model can improve the area under the receiver operating characteristic curve(AUC)score by 7.3%,0.42%and 3.0%for the spectral images,CMs and HFs respectively on the five-energy spectral data over the original single energy data only.The CM-and HF-inputs can achieve the best AUC of 0.934 and 0.927.This texture themed study shows the insight that incorporating clinical important prior information,e.g.,tissue texture in this paper,into the medical imaging,such as the upstream image reconstruction,the downstream diagnosis,and so on,can benefit the clinical tasks.

Vector textures derived from higher order derivative domains for classification of colorectal polyps

Textures have become widely adopted as an essential tool for lesion detection and classification through analysis of the lesion heterogeneities.In this study,higher order derivative images are being employed to combat the challenge of the poor contrast across similar tissue types among certain imaging modalities.To make good use of the derivative information,a novel concept of vector texture is firstly introduced to construct and extract several types of polyp descriptors.Two widely used differential operators,i.e.,the gradient operator and Hessian operator,are utilized to generate the first and second order derivative images.These derivative volumetric images are used to produce two angle-based and two vectorbased(including both angle and magnitude)textures.Next,a vector-based co-occurrence matrix is proposed to extract texture features which are fed to a random forest classifier to perform polyp classifications.To evaluate the performance of our method,experiments are implemented over a private colorectal polyp dataset obtained from computed tomographic colonography.We compare our method with four existing state-of-the-art methods and find that our method can outperform those competing methods over 4%-13%evaluated by the area under the receiver operating characteristics curves.

Multi-scale characterizations of colon polyps via computed tomographic colonography

Texture features have played an essential role in the field of medical imaging for computer-aided diagnosis.The gray-level co-occurrence matrix(GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications.This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor.In this study,we first introduce a new parameter-stride,to explore the definition of GLCM.Then we propose three multi-scaling GLCM models according to its three parameters,(1)learning model by multiple displacements,(2)learning model by multiple strides(LMS),and(3)learning model by multiple angles.These models increase the texture information by introducing more texture patterns and mitigate direction sparsity and dense sampling problems presented in the traditional Haralick model.To further analyze the three parameters,we test the three models by performing classification on a dataset of 63 large polyp masses obtained from computed tomography colonoscopy consisting of 32 adenocarcinomas and 31 benign adenomas.Finally,the proposed methods are compared to several typical GLCM-texture descriptors and one deep learning model.LMS obtains the highest performance and enhances the prediction power to 0.9450 with standard deviation 0.0285 by area under the curve of receiver operating characteristics score which is a significant improvement.

Longitudinal non-vascular transport pathways originating from acupuncture points in extremities visualised in human body

A subcutaneous transport pathway in humans has been previously visualised by injection of a paramagnetic tracer into the specific region of skin.In the current study,we further investigated the behaviours of imaging tracers in the transport pathways using imaging techniques.Three types of imaging tracers,including Gd-DTPA,iodised oil,and fluorescein sodium,were hypodermically injected into different acupuncture points of healthy volunteers to visualise the transport pathways by magnetic resonance imaging(MRI),X-ray,CT,and a digital fluorescein camera.Several longitudinal transport pathways in the arms and feet,which represent venous vessels and subcutaneous transport pathways(STPs) without well-defined boundaries,were visualised by MRI.Among the visualised veins,the partial walls of a few veins were enhanced by Gd-DTPA.The fluorescent images further indicated that STPs likely represent boundless pathways.The findings in this study suggested that specific anatomical structures within the subcutaneous tissues or the partial walls of certain veins werenot vascular conduits but rather represented unique transport pathways in humans that warrant extensive future studies.

Facile preparation of organometallic perovskite films and high-efficiency solar cells using solid-state chemistry

The power conversion efficiency of organometallic perovskite-based solar cells has skyrocketed in recent years. Intensive efforts have been made to prepare high-quality perovskite films tailored to various device configurations. Planar heterojunction devices have achieved record efficiencies; however, the preparation of perovskite films for planar junction devices requires the use of expensive vacuum facilities and/or the fine control of experimental conditions. Here, we demonstrate a facile preparation of perovskite films using solid-state chemistry. Solid-state precursor thin films of CHBNH3I and PbI2 are brought into contact with each other and allowed to react via thermally accelerated diffusion. The resulting perovskite film displays good optical absorption and a smooth morphology. Solar cells based on these films show an average efficiency of 8.7% and a maximum efficiency of 10%. The solid-state synthesis of organometallic perovskite can also be carried out on flexible plastic substrates. Using this method on a PET/ITO substrate produces devices with an efficiency of 3.2%. Unlike existing synthetic methods for organometallic perovskite films, the solid-state reaction method does not require the use of orthogonal solvents or careful adjustment of reaction conditions, and thus shows good potential for mass production in the future.

Insights into the Functionalization of the Methylsalicyclic Moiety during the Biosynthesis of Chlorothricin by Comparative Kinetic Assays of the Activities of Two KAS Ⅲ-like Acyltransferases

Summary of main observation and conclusion Chlorothricin (CHL),an archetypal member of the family of spirotetronate antibiotics,possesses a tetronate-containing pentacyclic aglycone that is conjugated with a modified methylsalicyclic acid (MSA) moiety through a disaccharide linkage.MSA is a polyketide product assembled by the iterative type Ⅰ polyketide synthase ChlB1.incorporation of this pharmaceutically important moiety into CHL relies on the activities of two distinct β-Ketoacyl-ACP synthase Ⅲ(KAS Ⅲ)-Iike acyltransferases,ChlB3 and ChlB6,which function together to coordinate the transfer of MSA through ChlB2,a discrete acyl carrier protein (ACP).During the maturation of CHL,MSA needs to be further functionalized by C2-O-methylation and C5-chlorination;however,timing of this functionalization process remains poorly understood.In this study,we report comparative kinetic assays of the activities of the two KAS Ⅲ-like acyltransferases ChlB3 and ChlB6 using substrates that vary in substitution extent and ACP carrier.ChlB3 prefers to transfer the immediately assembled 6-methyI-MSA moiety from ChlB1-ACP to the discrete ACP ChlB2,from which this moiety is preferred to be transferred directly onto the molecule desmethylsalicyl-CHL prior to C2-O-methylation and C5-chlorination.Consequently,MSA functionalization appears to occur at the molecule level rather than at the covalently tethered protein level,i.e.,ChlB1-ACP or ChlB2.Both ChlB3 and ChlB6 are flexible in substrate tolerance,holding promise for CHL engineering-based structural diversity by using variable MSA moiety.

An Efficient One-pot Three-component Process for Synthesis of Perfluoroalkylated Quinolizines

A facile multi-component process for the synthesis of perfluoroalkylated quinolizine derivatives was achieved using various arylidenemalononitriles, pyridine, and methyl perfluoroalk-2-ynoates as starting materials. Moderate yields were obtained under mild condition. The structures of perfluoroalkylated quinolizine derivatives were char- acterized by means of IH NMR, 13C NMR, 19F NMR, IR, LRMS and HRMS. Furthermore, the reaction mechanism was proposed.