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Background Extracellular matrix (ECM) is remodeled during carcinogenesis. An abundant constituent of ECM is collagen. Type I collagen is secreted by fibroblasts, is important for tumor growth and epithelial‐mesenchymal transition, and may also be secreted by cancer cells. However, the role and function of cancer‐derived Type I collagen in the tumor microenvironment remains unclear. Methods We used immunohistochemistry and Western blot to detect Type I collagen expression in non‐small cell lung cancer (NSCLC) and esophageal squamous cell carcinoma (ESCC) cell lines, respectively. We assessed the migration and adhesion capability of these cells in vivo by inhibiting Type I collagen in tumors. Relevant data were extracted from a large cohort study of The Cancer Genome Atlas to analyze messenger RNA levels. Protein expression of Type I collagen was further determined in tumor tissues of patients using tissue microarray. Results Cancer cell lines secreted Type I collagen. The molecular weight of cancer‐derived Type I collagen was different from that secreted by cancer‐associated fibroblasts and normal fibroblasts. Expression levels of COL1A1 and COL1A2 (subtypes of Type I collagen) messenger RNA in NSCLC and ESCC tumors were higher than in normal tissues, but were not associated with tumor node metastasis stages. Low expression of Type I collagen was significantly associated with poor overall survival and cancer cell differentiation. Conclusion NSCLC and ESCC cells could produce Type I collagen endogenously, revealing the potential functions of Type I collagen in cancer development. Cancer‐derived Type I collagen was associated with overall survival and cancer cell differentiation.

A real-time comparative measurement method is proposed to enhance the measurement accuracy of Raman shifts. Several experimental configurations are presented and demonstrated. The error sources in Raman shifts are also analyzed. The method is tested on a Raman spectrometer by measuring a sample of monocrystalline silicon and a sample of polystyrene. Experimental results indicate that the accuracy limit of the method is 0.07 cm–1. The measurement uncertainty of the Raman shift of the silicon is 0.2 cm–1 (k = 2), and the measurement uncertainty of the polystyrene is also improved. It is shown that the real-time comparative measurement method can remarkably enhance the measurement accuracy of Raman shift, and it applies to Raman spectrometers regardless of whether their exact laser wavelengths are known or not.

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Confocal Raman microscope (CRM) is one of the most powerful analytical instruments. The lateral spatial resolution is one of the key parameters for evaluating its imaging performance. In this paper, a novel knife-edge method is proposed for measuring the lateral resolution of CRMs. A virtual knife-edge phantom is developed by coating a thin layer of chromium pattern on a piece of polished monocrystalline silicon. It can avoid the edge-enhancement effect in conventional knife-edge methods. The edge spread function (ESF) and resolution of a commercial CRM at different configurations are measured to test the performance of the phantom, whose lateral resolution is from 0.8~8 micrometers. The Fermi function is used to fit the experimental data of the ESF and calculate the lateral resolution. Different types of phantoms are also developed and tested for comparison study. It is proved by experimental results that the virtual knife-edge method can be used to measure the ESF and resolution of CRMs and shows better performance than conventional methods.

Malware is at root of most of cyber-attacks, which has led to billions of dollars in damage every year. Most malware, especially Advanced Persistent Threat (APT) malware make use of Domain Name System (DNS) to control compromised machines and steal sensitive information. Therefore, several security products identified malware infection by combining machine learning technology with DNS data. However, the existing detection approaches cannot simultaneously identify both malicious domain names and infected hosts. To solve the problem, this work proposed a co-clustering based detection approach without labeled data, which integrates active DNS data with graph inference. According to active DNS data, a host-domain graph was generated in the first. Then partial domain nodes were labeled under the aid of blacklist, popular domain list, and Alexa ranking. At last, semi-supervised co-clustering was used to discover potential malicious domains and malware-infected hosts in the monitored network. This work implemented experiments in a network of hundreds of internal hosts that access 145 malware domains. Experimental results showed that the proposed detection approach was able to identify malware domains with up to 97.2% true positives. This work also compared and analyzed the results using different cluster calculating formulas with two different bipartite edge weights. Results showed that clustering with maximum and minimum edge weights has a better tolerance to different distance calculation methods.

Minimally invasive surgery (MIS) is a specialized surgical technique, the minimally invasive surgery compared to traditional surgery, not only can reduce the patient's pain, more can make the patients recover more quickly. But because the minimally invasive surgery is very complex, so the doctors need a lot of training to guarantee the realization of the surgery. In previous studies, we have developed a virtual reality training system. Based on CT image reconstruction of 3-d vessel model, we designed a 3 d model of the catheter. In order to provide the surgeon to meet the need of training sense of touch, we studied the force feedback and the collision detection algorithm. We design a system that contains three kinds of force: force feedback viscous force, friction force and impact force. Catheter force and viscous force between blood; Friction between the catheters means the power of the body and blood vessels; Catheter tip is the collision force between force and vessel. Then we develop a fast collision detection algorithm based on AABB bounding box (Axis Aligned) method. In this way, we can reduce the collision detection time, training in real time. Finally, we designed a few columns based on Phantom a control experiment. We also the contact force between the catheter and the blood vessels do the detailed analysis, combined with local collision detection algorithm to calculate the contact force and feedback to the operator through the Phantom handles.

Nasopharyngeal carcinoma is an EB-virus associated malignancy which is highly prevalent in Southeast Asia. If diagnosed early, the 5 year disease-free survival rate is about 90%. However, most patients have already developed local or regional invasion when diagnosed, which results in poor prognosis. So it is essential to develop biomarkers to screen high risk individuals or diagnose the disease at early stages. As nasopharyngeal carcinoma is closely related to EBV infection and microRNAs encoded by BART region (BamHI A Rightward Transcripts) is abundant in NPC, we propose to identify biomarkers from those BART microRNAs. To quantify the copy number of microRNAs in serum samples, we used Taqman Probe-based qPCR. After adding Spiked-in Control (Mixture of Cel-39,Cel-54, Cel-238) to each 100ul serum sample, we extracted total RNA and reverse transcribed microRNA into cDNA with corresponding Taqman primers. Meanwhile, microRNA mimics with known copy number were serial diluted and reverse transcribed along with the samples. qPCR was performed to quantify the level of microRNAs in these samples with diluted cDNA and Taqman Probe. All data was normalized by Spiked-in controls and exact copy number of each microRNA was calculated through the standard curve generated by the serial diluted microRNA mimics. Here, we screened 17 BART microRNAs in discovery stage and found BART 2-5p as a candidate biomarker. In training cohort consisting of 266 patients with nasopharyngeal carcinoma and controls from Hong Kong, the sensitivity, specificity and AUC is 93.2%, 89.8%,0.976 respectively. The results are similar in validation cohort 1 constituted by 376 patients and controls from Guang Zhou. To evaluate the ability of BART 2-5p to distinguish preclinical NPC patients from healthy high risk individuals, we established a nested case-control study with serum samples prospectively collected from 10 NPC patients at least one year prior to their clinical diagnosis and 92 matched healthy high risk controls from a screening scheme conducted in South China. The sensitivity and specificity is 90.0% and 31.5%. Taken together, EBV microRNA BART2-5p is a promising biomarker to improve NPC diagnosis and target preclinical patients more precisely than serologic test. Citation Format: Chen Jiang, Lei Li, Li Jiangchao, Shang-hang Xie, Su-mei Cao, Xin-yuan Guan. Circulating EBV microRNA BART2-5p helps to diagnose nasopharyngeal carcinoma &lt screen for high risk individuals precisely [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 722. doi:10.1158/1538-7445.AM2017-722