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Valproic acid is an anticonvulsant, which is also widely used for treating psychiatric disorders. Some clinical trials have demonstrated benefits of valproic acid augmentation therapy in schizophrenia. Interindividual variability in valproic acid dose and serum concentration may reflect functional consequences of genetic polymorphisms in genes encoding drug-metabolizing enzymes. The aim of this study was to determine the relationship between serum concentrations of valproic acid and single nucleotide polymorphisms of the cytochrome P450 (CYP) 2C19 gene in patients with schizophrenia. All patients had been receiving fixed dose of valproic acid for at least 2 weeks. The daily doses were 0.5–1.5 g. No other drugs except olanzapine were coadministered. Serum concentrations of valproic acid were measured using the ultra-high performance liquid chromatography method with mass-spectrometric detection. The CYP2C19 (CYP2C19*2 G681A rs4244285 and CYP2C19*3 G636A rs4986893) genotypes were identified by real-time PCR analyses. The mean concentration/dose ratios of valproic acid were significantly higher in patients with CYP2C19 *1/*2 genotype (P CYP2C19 *2/*3 genotype (P CYP2C12 *1/*1 genotype. The mean concentration/dose ratios of valproic acid were significantly higher in patients with 1 (P P CYP2C19 than in those without mutated alleles. And the post hoc analysis revealed that the result has acceptable statistical (power (1 – β) = 0.8486 at type I level of 0.05) to support the observed significant associations for CYP2C19 SNPs and serum C/D ratios of valproic acid. The findings of this study suggest that the genetic polymorphisms of CYP2C19 significantly affect the steady-state serum concentrations of valproic acid in Chinese Han population. The determination of the CYP2C19 genotypes may be useful for dosing adjustment in schizophrenia patients on valproic acid therapy.

The Autonomous Air Combat technique has been a lasting research topic for decades. However, no complete solutions seem to have appeared because of the highly dynamic and complex nature of the Autonomous Air Combat problem. In devising the Autonomous Air Combat solutions, we follow similar methodologies in the robotics community, and divide the overall scheme into two folds: the perception of other (enemy/friendly) aircraft, and the guidance/control for own aircraft. While the perception in the first fold serves as a foundation, this paper is mainly focused on the second one. Based on our survey, a review of own aircraft guidance/control in the (primarily one-to-one) Autonomous Air Combat solutions is presented. We divide different Autonomous Air Combat solutions into three groups, i.e. mathematics-based, knowledge-encoded, and learning-driven. In each group, we present the representative methods first; problem definition, solution, and a brief overview of the historical development are illustrated. We also comment on both weakness and strengths for each group/method. We point out certain technical paths/challenges that need to be addressed in the future Autonomous Air Combat development, i.e. to abstract and emulate the human pilot experiences, and to develop the online learning capabilites. Inspired by the state-of-art techniques in other similar fields (robotics, autonomous driving), we also propose potential solutions, i.e. traditional approaches enhanced by the novel data-driven technique. Via this paper, we hope to deliver an in-depth analysis of past experiences and potential challenges/solutions for the Autonomous Air Combat technique. We also advocate referring to the approaches/techniques that are utilized in other similar fields in devising the Autonomous Air Combat solutions.

CTCS-3 with ATO system uses bidirectional digital communication for onboard Automatic Train Protection (ATP) and Automatic Train Operation (ATO) and wayside devices to transmit train control and status information in High-Speed Railway (HSR). However, the inevitable transmission delay and packet loss in GSM-R and GPRS wireless communications in CTCS-3 systems will cause unplanned service braking or degraded operation, which would seriously affect the operation performance. In this paper, we quantitatively analyze the impact of wireless communication packet delay and loss on the tracking time and total energy consumption of CTCS-3 with ATO system under moving block. A state space model for CTCS-3 with ATO system under wireless packet delay and loss is established, and reinforcement learning control scheme based on wireless transmissions parameter adaption is proposed to improve the train control performances. Simulation results show that the proposed method can significantly improve the punctuality and operation efficiency in CTCS-3 with ATO systems compared to existing methods.

A significant portion of world population still fails to brush teeth daily. As a result, the majority of the global adult population is afflicted with chronic gingivitis, and if it is left untreated, some of them will eventually suffer from periodontitis., Most adults experience episodes of gingivitis, which can progress to the irreversible, chronic state of periodontitis, yet roles of plaque in gingivitis onset and progression to periodontitis remain elusive. Here, we longitudinally profiled the plaque metagenome, the plaque metabolome, and salivary cytokines in 40 adults who transited from naturally occurring gingivitis (NG) to healthy gingivae (baseline) and then to experimental gingivitis (EG). During EG, rapid and consistent alterations in plaque microbiota, metabolites, and salivary cytokines emerged as early as 24 to 72 h after oral-hygiene pause, defining an asymptomatic suboptimal health (SoH) stage of the gingivae. SoH features a swift, full activation of 11 salivary cytokines but a steep synergetic decrease of plaque-derived betaine and Rothia spp., suggesting an anti-gum inflammation mechanism by health-promoting symbionts. Global, cross-cohort meta-analysis revealed, at SoH, a greatly elevated microbiome-based periodontitis index driven by its convergence of both taxonomical and functional profiles toward the periodontitis microbiome. Finally, post-SoH gingivitis development accelerates oral microbiota aging by over 1 year within 28 days, with Rothia spp. depletion and Porphyromonas gingivalis elevation as hallmarks. Thus, the microbiome-defined, transient gum SoH stage is a crucial link among gingivitis, periodontitis, and aging.

Introduction Patients with atrophic gastritis (AG) or gastric intestinal metaplasia (GIM) have elevated risk of gastric adenocarcinoma. Endoscopic screening and surveillance have been implemented in high incidence countries. The study aimed to evaluate the accuracy of a deep convolutional neural network (CNN) for simultaneous recognition of AG and GIM. Methods Archived endoscopic white light images with corresponding gastric biopsies were collected from 14 hospitals located in different regions of China. Corresponding images by anatomic sites containing AG, GIM, and chronic non-AG were categorized using pathology reports. The participants were randomly assigned (8:1:1) to the training cohort for developing the CNN model (TResNet), the validation cohort for fine-tuning, and the test cohort for evaluating the diagnostic accuracy. The area under the curve (AUC), sensitivity, specificity, and accuracy with 95% confidence interval (CI) were calculated. Results A total of 7,037 endoscopic images from 2,741 participants were used to develop the CNN for recognition of AG and/or GIM. The AUC for recognizing AG was 0.98 (95% CI 0.97-0.99) with sensitivity, specificity, and accuracy of 96.2% (95% CI 94.2%-97.6%), 96.4% (95% CI 94.8%-97.9%), and 96.4% (95% CI 94.4%-97.8%), respectively. The AUC for recognizing GIM was 0.99 (95% CI 0.98-1.00) with sensitivity, specificity, and accuracy of 97.9% (95% CI 96.2%-98.9%), 97.5% (95% CI 95.8%-98.6%), and 97.6% (95% CI 95.8%-98.6%), respectively. Discussion CNN using endoscopic white light images achieved high diagnostic accuracy in recognizing AG and GIM.

Most adults experience episodes of gingivitis, which can progress to the irreversible, chronic state of periodontitis. However the mechanistic roles of plaque in gingivitis onset and progression to periodontitis remain elusive. Here, we integrated the longitudinal multi-omics data from plaque metagenome, metabolome and salivary cytokines in 40 adults who transit from naturally-occurring gingivitis (NG), to healthy gingivae (baseline) and then to experimental gingivitis (EG). During EG, rapid and consistent alterations in plaque microbiota, metabolites and salivary cytokines emerged as early as 24-72 hours after pause of oral hygiene, defining an asymptomatic ‘sub-optimal health’ (SoH) stage. SoH also features a steep and synergetic decrease of plaque-derived betaine and Rothia spp., suggesting an anti-gum-inflammation mechanism by health-promoting microbial residents. Global, cross-cohort meta-analysis revealed a high Microbiome-based Periodontitis Index at SoH state, due to its convergent taxonomical and functional profiles towards those of periodontitis. In contrast, caries SoH features a microbial signature very distinct from caries. Thus SoH is a universal state of polymicrobial inflammations with disease-specific features, which is key to maintaining a disease-preventive plaque.

In view of the wide variety of special equipment in coal mines, the complexity of equipment, the small number of equipment sets, and the wide international market, the long distance, the different policies of various countries, leading to low service efficiency, different service quality, and high service costs. Taking the regionalization, localization and individualization as the idea, it adopts a point-multifaceted management organization form, combined with the actual situation of different markets, to form an overall management and control, and a regional independent after-sales service system. It solves the contradiction between the Space and time, quality and cost of equipment after-sales service in the process of internationalization, and achieves the goal of high efficiency, high quality and low cost indicators of after-sales service. It is the key for enterprises to go global, stand firm in the market, and achieve steady profitability by establishment of an international wide-area after-sales service system for coal mine special equipment.

Objectives Application of artificial intelligence in gastrointestinal endoscopy is increasing. The aim of the study was to examine the accuracy of convolutional neural network (CNN) using endoscopic images for evaluating Helicobacter pylori (H. pylori) infection. Methods Patients who received upper endoscopy and gastric biopsies at Sir Run Run Shaw Hospital (January 2015-June 2015) were retrospectively searched. A novel Computer-Aided Decision Support System that incorporates CNN model (ResNet-50) based on endoscopic gastric images was developed to evaluate for H. pylori infection. Diagnostic accuracy was evaluated in an independent validation cohort. H. pylori infection was defined by the presence of H. pylori on immunohistochemistry testing on gastric biopsies and/or a positive 13C-urea breath test. Results Of 1,959 patients, 1,507 (77%) including 847 (56%) with H. pylori infection (11,729 gastric images) were assigned to the derivation cohort, and 452 (23%) including 310 (69%) with H. pylori infection (3,755 images) were assigned to the validation cohort. The area under the curve for a single gastric image was 0.93 (95% confidence interval [CI] 0.92-0.94) with sensitivity, specificity, and accuracy of 81.4% (95% CI 79.8%-82.9%), 90.1% (95% CI 88.4%-91.7%), and 84.5% (95% CI 83.3%-85.7%), respectively, using an optimal cutoff value of 0.3. Area under the curve for multiple gastric images (8.3 ± 3.3) per patient was 0.97 (95% CI 0.96-0.99) with sensitivity, specificity, and accuracy of 91.6% (95% CI 88.0%-94.4%), 98.6% (95% CI 95.0%-99.8%), and 93.8% (95% CI 91.2%-95.8%), respectively, using an optimal cutoff value of 0.4. Discussion In this pilot study, CNN using multiple archived gastric images achieved high diagnostic accuracy for the evaluation of H. pylori infection.

The starting and safety protection system is an important part ofthe explosion-proof diesel engine, and there are malfunctions in the explosion-proof diesel engine, such as difficulty in starting and failure in protection. As a gas working medium, compressed air is safe, reliable, and advantageous in acquisition and storage. Therefore, analyzing the starting principle and safety protection requirements of explosion-proof diesel engines and studying the correlation between the two systems, a set of starting and safety protection systemsusing compressed air as the working medium is designed in this paper. Moreover, the performance requirements of the main components in the system are studied, analyzing and calculating the operating parameters in the system, so that the design plan can be optimized. The problems appearing instarting and safety protection of explosion-proof diesel engines are solved through this system.

This paper aimed to compare the mode of action of a stannous fluoride-containing toothpaste with a conventional sodium fluoride-containing toothpaste on anti-biofilm properties.A three-species biofilm model that consists of Streptococcus mutans, Streptococcus sanguinis and Porphyromonas gingivalis was established to compare the anti-biofilm properties of a stannous fluoride-containing toothpaste (CPH), a conventional sodium fluoride-containing toothpaste (CCP) and a negative control (PBS). The 48h biofilms were subjected to two-minute episodes of treatment with test agents twice a day for 5 consecutive days. Crystal violet staining and XTT assays were used to evaluate the biomass and viability of the treated biofilm. Live/dead staining and bacteria/extracellular polysaccharides (EPS) double-staining were used to visualize the biofilm structure and to quantify microbial/extracellular components of the treated biofilms. Species-specific fluorescent in situ hybridization and quantitative polymerase chain reaction (qPCR) were used to analyze microbial composition of the biofilms after treatment.The biomass and viability of the biofilms were significantly reduced after CPH toothpaste treatment. The inhibitory effect was further confirmed by the live/dead staining. The EPS amounts of the three-species biofilm were significantly reduced by CCP and CPH treatments, and CPH toothpaste demonstrated significant inhibition on EPS production. More importantly, CPH toothpaste significantly suppressed S. mutans and P. gingvalis, and enriched S. sanguinis in the three-species biofilm. In all experiments CPH had a significantly greater effect than CCP (p0.05) and CCP had a greater effect than PBS (p0.05).Stannous fluoride-containing toothpaste not only showed better inhibitory effect against oral microbial biofilm, but was also able to modulate microbial composition within multi-species biofilm compared with conventional sodium fluoride-containing toothpaste.

MiSH, which is based on the skin microbiome, can quantitatively assess pediatric skin health across cohorts from distinct countries over large geographic distances. Moreover, the index can identify a risk-prone skin state and compare treatment effect in children, suggesting applications in diagnosis and patient stratification., A quantitative and objective indicator for skin health via the microbiome is of great interest for personalized skin care, but differences among skin sites and across human populations can make this goal challenging. A three-city (two Chinese and one American) comparison of skin microbiota from atopic dermatitis (AD) and healthy pediatric cohorts revealed that, although city has the greatest effect size (the skin microbiome can predict the originated city with near 100% accuracy), a microbial index of skin health (MiSH) based on 25 bacterial genera can diagnose AD with 83 to ∼95% accuracy within each city and 86.4% accuracy across cities (area under the concentration-time curve [AUC], 0.90). Moreover, nonlesional skin sites across the bodies of AD-active children (which include shank, arm, popliteal fossa, elbow, antecubital fossa, knee, neck, and axilla) harbor a distinct but lesional state-like microbiome that features relative enrichment of Staphylococcus aureus over healthy individuals, confirming the extension of microbiome dysbiosis across body surface in AD patients. Intriguingly, pretreatment MiSH classifies children with identical AD clinical symptoms into two host types with distinct microbial diversity and treatment effects of corticosteroid therapy. These findings suggest that MiSH has the potential to diagnose AD, assess risk-prone state of skin, and predict treatment response in children across human populations. IMPORTANCE MiSH, which is based on the skin microbiome, can quantitatively assess pediatric skin health across cohorts from distinct countries over large geographic distances. Moreover, the index can identify a risk-prone skin state and compare treatment effect in children, suggesting applications in diagnosis and patient stratification.

Background It acknowledged that skin care is an important part of atopic dermatitis therapy. However, clinical evidences are limited for the best bathing practices, especially the skin health performance of cleansing products on children's atopic dermatitis skin. Methods A randomised controlled clinical study was conducted in China among 4- to 18-year-old children with mild-to-moderate atopic dermatitis to evaluate the skin health effect of three cleansing systems (a mild synthetic bar, an ultra-mild body wash with lipids, and an ultra-mild body wash with lipids and zinc pyrithione) by measuring SCORing of Atopic Dermatitis (SCORAD), consumption of topical corticosteroid and the characteristics of microbiome. Results Increased Staphylococcus aureus abundance and decreased microbial diversity were observed in atopic dermatitis lesion sites compared with healthy control sites. After 4 weeks of treatment, all three treatments showed clinically important improvement from baseline in SCORAD. Four-week corticosteroid consumption was significantly lower for the two body wash groups than the bar group. A significant decrease in S. aureus abundance and increase in microbial diversity were observed in the lesion sites for the two body wash formulas, while the microbial diversity was statistically insignificant for the mild cleansing bar group. However, there were no incremental benefits provided by the body wash formulas based on the assessment of SCORAD. Conclusions These results demonstrated the safety and efficacy of using the investigational body wash formulas with lipids in reducing the needs for corticosteroid and improving the healthy composition of skin microbiome vs. the mild synthetic bar soap.

Gastroscopy plays an important role in the diagnosis of gastric disease. In this paper, we develop an image panoramic system to assist endoscopists in improving lesion surveillance and reducing many of the tedious operations associated with gastroscopy. The constructed panoramic view has two categories: 1) the local view broadens the endoscopist's field of view in real time. Combining with the original gastroscopic video, this mosaicking view enables the endoscopist to diagnose the lesion comprehensively; 2) the global view constructs a large-area panoramic scene of the internal gastric surface, which can be used for intraoperative surgical navigation and postoperative scene review. Due to the irregular texture and inconsistent reflection of the gastric internal surface, common registration methods cannot accurately stitch this surface. Thereby, a six degree of freedom position tracking endoscope is devised to accommodate for the accumulated mosaicking error and provide efficient mosaicking results. For the global view, a dual-cube constraint model and a Bundle Adjustment algorithm are incorporated to deal with the mosaicking error caused by the irregular inflation and nonrigid deformation of the stomach. Moreover, texture blending and frame selection schemes are developed to make the mosaicking results feasible in real-clinical applications. The experimental results demonstrate that our system performs with a speed of 7.12 frames/s in a standard computer environment, and the mosaicking mean error is 0.43 mm for local panoramic view and 3.71 mm for global panoramic view.

Objective: Acute coronary syndrome (ACS), as a common and severe cardiovascular disease, is a leading cause of death and the principal cause of serious long-term disability globally. Clinical risk prediction of ACS is important for early intervention and treatment. Existing ACS risk scoring models are based mainly on a small set of hand-picked risk factors and often dichotomize predictive variables to simplify the score calculation. Methods: This study develops a regularized stacked denoising autoencoder (SDAE) model to stratify clinical risks of ACS patients from a large volume of electronic health records (EHR). To capture characteristics of patients at similar risk levels, and preserve the discriminating information across different risk levels, two constraints are added on SDAE to make the reconstructed feature representations contain more risk information of patients, which contribute to a better clinical risk prediction result. Results: We validate our approach on a real clinical dataset consisting of 3464 ACS patient samples. The performance of our approach for predicting ACS risk remains robust and reaches 0.868 and 0.73 in terms of both AUC and accuracy, respectively. Conclusions: The obtained results show that the proposed approach achieves a competitive performance compared to state-of-the-art models in dealing with the clinical risk prediction problem. In addition, our approach can extract informative risk factors of ACS via a reconstructive learning strategy. Some of these extracted risk factors are not only consistent with existing medical domain knowledge, but also contain suggestive hypotheses that could be validated by further investigations in the medical domain.

In the present paper a band pass microwave filter with spoof surface plasmon polaritions (SPPs) structure is designed and simulated using FDTD method. The filter is composed of four sections, where in the third section, parallel and symmetrically arranged corrugated metallic strip is the spoof SPPs transmission line, in which, periodically arranged rectangular slot is designed to fulfill the spoof SPPs effect. In the fourth section, the spoof SPPs lines are coupled with each other to realize the transmission zero in the up stop band range. The transmission and reflection properties of the spoof SPPs filter in microwave frequency region are elaborately investigated by FDTD method. Through adjusting the geometrical dimensions of the plasmonic coupling structure as well as the rectangular slots structure, the bandwidth and suppression characteristics of the filter can be precisely controlled and the filter has great resistant ability to space electromagnetic interference.

Biopsy is a traditional endoscopic surveillance of premalignant gastric lesions, and endoscopic tattooing is used for marking the biopsy's location. However, the tattooing has several disadvantages. For example, the procedure is an invasive operation and may not be durable due to the diffusion. Moreover, it is procedurally cumbersome with an associated risk of technical failure. In this study, a computer aided endoscopic navigation system (CAEN system) was developed for a non-invasive biopsy procedure. The CAEN system consists of a new, designed six degree of freedom (6-DOF) tracking endoscope device and a computer simulated work station. During the procedure, the endoscopist uses the tip of the tracking endoscope to touch the lesion. Then, the lesion's location is recorded in the work station, which then guides the endoscopist in retargeting the lesions in the follow-ups. The clinical experimental results demonstrate that the accuracy at the angularis is 5.2 ± 2.8 mm, at the antral lesser curvature is 7.2 ± 2.0 mm, at the antral greater curvature is 6.3 ± 3.1 mm, at the antral posterior wall is 8.2 ± 1.6 mm, and at the antral anterior wall is 7.9 ± 1.3 mm. The mean accuracy is 7.5 mm, and the P-value is 0.023, which is likely suitable for clinical practice. Furthermore, the proposed CAEN system requires less procedural time than the tattooing.

Railway signalling system is a safety-critical system to ensure railway safety and its development cost is huge. It is of great economic value to apply the generic signalling systems in different environments through configuration of different application data. In this paper, a new method to configure the application data completely and accurately is illustrated; in particular, a technique called automatic generation technology is introduced to automatically configure the functional logic of safety-critical systems, i.e. computer-based interlocking CBI system and automatic train protection ATP system. All of the application data are collected from the workflow among various departments through the enterprise system ES. Some application data are represented by models employing automatic generation technology, and the functional logic is then obtained through analysis using these models. A configuration platform based on the ES is developed in which both the efficiency and accuracy of the application data configuration are significantly improved. In addition, it is capable of reducing human errors to a maximal extent.

The long-term reliability of ultralow-k (ULK) and copper/barrier metal, especially for time-dependent dielectric breakdown (TDDB) and electro-migration (EM), in Cu/ULK interconnects is rapidly becoming one of the most critical challenges for technology qualification as continuous advanced VLSI technology scaling. To explore the root cause to improve reliability, ULK deposition process and barrier metal process were studied. Increasing flow rate of the Si-based precursor or spacing between shower head to wafer stage was found to help dielectric breakdown voltage improvement for ULK material. Enhancing the ratio of Si-CH3/Si-O, which enables to improve the damage resistance, is considered as the main reason. As a result, TDDB enables to be improved significantly by >1000 times with comparable RC delay at a high flow rate of Si-based precursor. Meanwhile, improvement of the quality of the initial barrier film between barrier metal and ULK is found to improve EM lifetime at advanced generation when the thickness of barrier metal need to be reduced gradually as technology node continuous scaling.

Plaque-induced gingivitis can be alleviated by various treatment regimens. To probe the impacts of various anti-gingivitis treatments on plaque microflora, here a double blinded, randomized controlled trial of 91 adults with moderate gingivitis was designed with two anti-gingivitis regimens: the brush-alone treatment and the brush-plus-rinse treatment. In the later group, more reduction in both Plaque Index (TMQHI) and Gingival Index (mean MGI) at Day 3, Day 11 and Day 27 was evident, and more dramatic changes were found between baseline and other time points for both supragingival plaque microbiota structure and salivary metabonomic profiles. A comparison of plaque microbiota changes was also performed between these two treatments and a third dataset where 50 subjects received regimen of dental scaling. Only Actinobaculum, TM7 and Leptotrichia were consistently reduced by all the three treatments, whereas the different microbial signatures of the three treatments during gingivitis relieve indicate distinct mechanisms of action. Our study suggests that microbiota based signatures can serve as a valuable approach for understanding and potentially comparing the modes of action for clinical treatments and oral-care products in the future.

Accurate and fast fusion and display of real-time images of anatomy and associated data is critical for effective use in image guided procedures, including image guided cardiac catheter ablation. We have developed a piecewise patch-to-model matching method, a modification of the contractive projection point technique, for accurate and rapid matching between an intra-operative cardiac surface patch and a pre-operative cardiac surface model. Our method addresses the problems of fusing multi-modality images and using non-rigid deformation between a surface patch and a surface model. A projection lookup table, K-nearest neighborhood search, and a final iteration of point-to-projection are used to reliably find the surface correspondence. Experimental results demonstrate that the method is fast, accurate and robust for real-time matching of intra-operative surface patches to pre-operative 3D surface models of the left atrium.

Minimally Invasive Surgery (MIS) has offered great benefits to the patients for reducing patient trauma and recovery time. However, traditional MIS still has some challenges due to the loss of 3D vision and the narrow field of view provided by the endoscope. In this paper, we propose a method to reconstruct real 3D model of gastric internal surface based on gastroscopic image sequences, which can supply a significant navigation for surgeons during MIS procedure. This method utilizes a novel six-degree of freedom (6-DOF) tracking sensor to record endoscope’s real-time position information, and Structure from Motion (SFM) theory is adopted to generate 3D gastric internal surface model. The system is experimented on simulated gastric model. The 3D depth accuracy is estimated at 9.8 mm, which is suitable for clinic practice. Theoretically, this system can be applied to MIS not only on stomach but also on other organs.

Tattooing and Argon plasma coagulation (APC) are used for gastroscopic biopsy traditionally. To overcome the invasive issues of tattooing and APC, we proposed an image-guided gastroscopic biopsy system (IGGBS) to guide endoscopist in retargeting previous biopsy sites in the follow-ups non-invasively. In this paper, a model merging method is proposed to improve the IGGBS’s accuracy. The method reconstructs local realistic model based on gastroscopic image sequences during procedure, then the local model is merged with the pre-operative model in real-time. As a consequence, the merging model is used in IGGBS to navigate endoscopist to retarget biopsy sites, which provides the endoscopist with a confident 3D region around the endoscope camera site and a measure of the reconstruction precision. As the experimental result shows, the root mean square target registration error of IGGBS using merging model is 9.5 mm, which is close to the conventional biopsy tattooing method (about 1cm).

Natural Orifice Transluminal Endoscopic Surgery (NOTES) is widely used for clinical diagnoses. However, NOTES has two main problems: difficulties brought by endoscope’s flexibility and narrow view of endoscope. Image-guided system is helpful to deal with these problems. In our previous work, a computer aided endoscopic navigation system (CAEN) was developed for gastroscopic lesion surveillance. In this paper, 3D model and panoramic view are incorporated into CAEN with three improvements: selection of reference and tracking features; perspective projection for constructing local and global panoramic view; 3D surface modeling using structure from motion. The system is evaluated from three clinic applications: broadening the view, non-invasive retargeting, and overall lesion locations. The evaluation results show that the mean accuracy of broadening the view is 0.43 mm, the mean accuracy of non-invasive retargeting is 7.5 mm, and the mean accuracy for overall lesion diagnosis is 3.71 ± 0.35 mm.

Image registration is an essential technology for image guided diagnosis. However, in gastroscopic environment, it is still a challenging work due to the ambiguous and noisy endoscopic images. In this paper, we propose an iterative image registration method, homographic triangle and epipolar constraint registration, based on the homographic hypothesis. The method starts with establishing initial matching point pairs between gastroscopic image sequences and clustering them by Delaunay triangulation; normalized cross correlation is then introduced to validate the homographic assumptions of the matching triangles; after that, the inscribed circle’s center point of an unmatched triangle is registered by the epipolar constraint; finally, each unmatched triangles is divided into three sub-triangles according to its vertexes and inscribed circle center point for next HTECR iteration. Clinical data experimental results show a promising performance with this method.

Endoscopic tattoo with India ink injection for surveillance of premalignant gastric lesions is technically cumbersome and may not be durable. The aim of the study is to evaluate the accuracy of a novel, computer-simulated biopsy marking system (CSBMS) developed for the endoscopic marking of gastric lesions. Twenty-five patients with history of gastric intestinal metaplasia received both CSBMS-guided marking and India ink injection in five points in the stomach at index endoscopy. A second endoscopy was performed at three months. Primary outcome was accuracy of CSBMS (distance between CSBMS probe-guided site and tattoo site measured by CSBMS). The mean accuracy of CSBMS at angularis was5.3±2.2 mm, antral lesser curvature5.7±1.4 mm, antral greater curvature6.1±1.1 mm, antral anterior wall6.9±1.6 mm, and antral posterior wall6.9±1.6 mm. CSBMS (2.3±0.9versus12.5±4.6seconds;P=0.02) required less procedure time compared to endoscopic tattooing. No adverse events were encountered. CSBMS accurately identified previously marked gastric sites by endoscopic tattooing within 1 cm on follow-up endoscopy.

Gastric precancerous diseases (GPD) may deteriorate into early gastric cancer if misdiagnosed, so it is important to help doctors recognize GPD accurately and quickly. In this paper, we realize the classification of 3-class GPD, namely, polyp, erosion, and ulcer using convolutional neural networks (CNN) with a concise model called the Gastric Precancerous Disease Network (GPDNet). GPDNet introduces fire modules from SqueezeNet to reduce the model size and parameters about 10 times while improving speed for quick classification. To maintain classification accuracy with fewer parameters, we propose an innovative method called iterative reinforced learning (IRL). After training GPDNet from scratch, we apply IRL to fine-tune the parameters whose values are close to 0, and then we take the modified model as a pretrained model for the next training. The result shows that IRL can improve the accuracy about 9% after 6 iterations. The final classification accuracy of our GPDNet was 88.90%, which is promising for clinical GPD recognition.

Gastroscopic examination is one of the most common methods for gastric disease diagnosis. In this paper, a multitarget tracking approach is proposed to assist endoscopists in identifying lesions under gastroscopy. This approach analyzes numerous preobserved gastroscopic images and constructs a gastroscopic image graph. In this way, the deformation registration between gastroscopic images is regarded as a graph search problem. During the procedure, the endoscopist marks suspicious lesions on the screen and the graph is utilized to locate and display the lesions in the appropriate frames based on the calculated registration model. Compared to traditional gastroscopic lesion surveillance methods (e.g., tattooing or probe-based optical biopsy), this approach is noninvasive and does not require additional instruments. In order to assess and quantify the performance, this approach was applied to stomach phantom data andin vivodata. The clinical experimental results demonstrated that the accuracy at angularis, antral, and stomach body was 6.3 ± 2.4 mm, 7.6 ± 3.1 mm, and 7.9 ± 1.6 mm, respectively. The mean accuracy was 7.31 mm, average targeting time was 56 ms, and thePvalue was 0.032, which makes it an attractive candidate for clinical practice. Furthermore, this approach provides a significant reference for endoscopic target tracking of other soft tissue organs.

The lack of 3D vision and proper depth perception associated with traditional endoscopy significantly limits the quality of the diagnostic examinations and therapy delivery. To address this challenge, we propose a technique to reconstruct a 3D model of the visualized scene from a sequence of spatially-encoded endoscopic video frames. The method is based on the structure from motion approach adopted from computer vision, and uses both the intrinsic camera parameters, as well as the tracking transforms associated with each acquired video frame to calculate the global coordinates of the features in the video, and generate a true size 3D model of the imaged scene. We conducted a series of phantom experiments to evaluate the robustness of the proposed method and the accuracy of a generated 3D scene, which yielded 1.7±0.9 mm reconstruction error. We also demonstrated the application of the proposed method using patient-specific endoscopic video image samples acquired during an in vivo gastroscopy procedure.

Image registration is a key component of computer assistance in image guided surgery, and it is a challenging topic in endoscopic environments. In this study, we present a method for image registration named Homographic Patch Feature Transform (HPFT) to match gastroscopic images. HPFT can be used for tracking lesions and augmenting reality applications during gastroscopy. Furthermore, an overall evaluation scheme is proposed to validate the precision, robustness and uniformity of the registration results, which provides a standard for rejection of false matching pairs from corresponding results. Finally, HPFT is applied for processing in vivo gastroscopic data. The experimental results show that HPFT has stable performance in gastroscopic applications.

On the basis of traditional image-based diagnostic, there have been many research results shown that the comparative analysis would be more comprehensive, intuitive and targeted. In actual clinical environment, the comparison of medical imaging data on the clinician workstations is inefficient and cumbersome due to the limited support of an integrated way for presenting these data, and this leads to the emergence of the integrated visualization of these data. With the large amount of medical imaging data distributed in achieve servers, the integrated visualization on traditional clinician workstations often lead to poor user interaction. Based on the relatively mature framework of traditional clinician workstations, this paper has located the bottlenecks of data transmission and data parsing. In addition, it provides several optimization schemas against these bottlenecks, such as Streaming concept, multi-core programming and an optimization based on Intel IPP, to enhance the user interaction for the integrated visualization of imaging data. This optimized framework has been applied to many hospitals and proven to meet the clinical requirements.

Background Microbial communities inhabiting human mouth are associated with oral health and disease. Previous studies have indicated the general prevalence of adult gingivitis in China to be high. The aim of this study was to characterize in depth the oral microbiota of Chinese adults with or without gingivitis, by defining the microbial phylogenetic diversity and community-structure using highly paralleled pyrosequencing. Methods Six non-smoking Chinese, three with and three without gingivitis (age range 21-39 years, 4 females and 2 males) were enrolled in the present cross-sectional study. Gingival parameters of inflammation and bleeding on probing were characterized by a clinician using the Mazza Gingival Index (MGI). Plaque (sampled separately from four different oral sites) and salivary samples were obtained from each subject. Sequences and relative abundance of the bacterial 16 S rDNA PCR-amplicons were determined via pyrosequencing that produced 400 bp-long reads. The sequence data were analyzed via a computational pipeline customized for human oral microbiome analyses. Furthermore, the relative abundances of selected microbial groups were validated using quantitative PCR. Results The oral microbiomes from gingivitis and healthy subjects could be distinguished based on the distinct community structures of plaque microbiomes, but not the salivary microbiomes. Contributions of community members to community structure divergence were statistically accessed at the phylum, genus and species-like levels. Eight predominant taxa were found associated with gingivitis: TM7, Leptotrichia, Selenomonas, Streptococcus, Veillonella, Prevotella, Lautropia, and Haemophilus. Furthermore, 98 species-level OTUs were identified to be gingivitis-associated, which provided microbial features of gingivitis at a species resolution. Finally, for the two selected genera Streptococcus and Fusobacterium, Real-Time PCR based quantification of relative bacterial abundance validated the pyrosequencing-based results. Conclusions This methods study suggests that oral samples from this patient population of gingivitis can be characterized via plaque microbiome by pyrosequencing the 16 S rDNA genes. Further studies that characterize serial samples from subjects (longitudinal study design) with a larger population size may provide insight into the temporal and ecological features of oral microbial communities in clinically-defined states of gingivitis.

Endoscopists currently rely on an invasive biopsy tattooing method to identify previously biopsied sites. In order to better guide endoscopists to find the biopsy positions in follow-ups, we proposed a non-invasive image guided biopsy marking system for gastroscopy. Using an electromagnetic tracking device, the position of the gastroscope relative to the stomach was acquired and displayed in the guidance interface. The biopsy positions were recorded in computer for the use of guidance in follow-ups. The accuracy of the system was evaluated by both phantom experiments and in vivo experiments. The average target registration errors on the test animal and the volunteer are 13.4 mm and 11.2 mm respectively. Although the positioning error is slightly larger than current biopsy tattooing method, it satisfies the need for guidance. In the near future, we will validate the system by measuring how much it saves examination time.

In this paper, we propose a computer simulated biopsy marking (CSBM) system for gastroscopy physicians. The purpose of the study is to solve two problems: how to mark suspicious areas for follow-ups without hurting stomach, and how to cut down time spent on gastroscopy. By constructing a three-dimensional (3D) virtual stomach model and using a tracking device, the position of gastroscope is shown in multi-view: in triplanar views, in global stomach model views, and in virtual gastroscopy view. In this way, physicians are guided to overcome disorientation so that the time spent on gastroscopy is cut down. By using a tracking device, the positions of suspicious areas are marked virtually in the 3D virtual stomach model. In this way, it will not hurt patients' stomach.