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Liver tumor segmentation (LiTS) is of primary importance in diagnosis and treatment of hepatocellular carcinoma. Known automated LiTS methods could not yield satisfactory results for clinical use since they were hard to model flexible tumor shapes and locations. In clinical practice, radiologists usually estimate tumor shape and size by a Response Evaluation Criteria in Solid Tumor (RECIST) mark. Inspired by this, in this paper, we explore a deep learning (DL) based interactive LiTS method, which incorporates guidance from user-provided RECIST marks. Our method takes a three-step framework to predict liver tumor boundaries. Under this architecture, we develop a RECIST mark propagation network (RMP-Net) to estimate RECIST-like marks in off-RECIST slices. We also devise a context-guided boundary-sensitive network (CGBS-Net) to distill tumors' contextual and boundary information from corresponding RECIST(-like) marks, and then predict tumor maps. To further refine the segmentation results, we process the tumor maps using a 3D conditional random field (CRF) algorithm and a morphology hole-filling operation. Verified on two clinical contrast-enhanced abdomen computed tomography (CT) image datasets, our proposed approach can produce promising segmentation results, and outperforms the state-of-the-art interactive segmentation methods.

Exploring efficient and robust antibacterial materials is crucially important for human health and ecological security. Compared with intrinsically antibacterial materials, materials modified with antibacterial agents either by chemical or physical modification can simultaneously maintain basic functions and antibacterial properties. In particular, physical modification with antiseptic sprays is quite suitable for large-size objects in our daily life but restricted by high volatility of the antibacterial agents or poor adhesion strength between the antibacterial agents and the targeted objects. In this paper, we report a poly(ionic liquid) (PIL-Cn)-based efficient and robust antiseptic spray that exhibits long-term antibacterial properties against both Gram-positive and Gram-negative bacteria on diverse substrates, including glass, PE, and cotton. It is believed that this work will provide an alternative for current antiseptic sprays for usage in our daily life and hospitals.

Repairing tooth defects with dental resin composites is currently the most commonly used method due to their tooth-colored esthetics and photocuring properties. However, the higher than desirable failure rate and moderate service life are the biggest challenges the composites currently face. Secondary caries is one of the most common reasons leading to repair failure. Therefore, many attempts have been carried out on the development of a new generation of antimicrobial and therapeutic dental polymer composite materials to inhibit dental caries and prolong the lifespan of restorations. These new antimicrobial materials can inhibit the formation of biofilms, reduce acid production from bacteria and the occurrence of secondary caries. These results are encouraging and open the doors to future clinical studies on the therapeutic value of antimicrobial dental resin-based restoratives. However, antimicrobial resins still face challenges such as biocompatibility, drug resistance and uncontrolled release of antimicrobial agents. In the future, we should focus on the development of more efficient, durable and smart antimicrobial dental resins. This article focuses on the most recent 5 years of research, reviews the current antimicrobial strategies of composite resins, and introduces representative antimicrobial agents and their antimicrobial mechanisms.

Background The symptoms of cool-temperature-induced chlorosis (CTIC) are widely existed in higher plants. Although many studies have shown that the genetic mechanism of CTIC is generally controlled by recessive genes in model plants, the dominant inheritance of albinism has not been reported thus far. Here, two CTIC mutants, Red Kamome and White Kamome, were utilized to analyse the inheritance of the albino trait in ornamental kale. The objective of this investigation is to fine-map the target locus and identify the most likely candidate genes for albinism. Results Genetic analysis revealed that the albinism in the inner leaves of ornamental kale followed semi-dominant inheritance and was controlled by a single locus in two segregating populations. BSR-seq in combination with linkage analysis was employed to fine-map the causal gene, named AK (Albino Kale), to an approximate 60 kb interval on chromosome C03. Transcriptome data from two extreme pools indicated that the differentially expressed gene of Bol015404, which encodes a cytochrome P450 protein, was the candidate gene. The Bol015404 gene was demonstrated to be upregulated in the albino leaves of ornamental kale by qPCR. Additionally, the critical temperature for the albinism was determined between 10 °C and 16 °C by gradient test. Conclusions Using two independent segregating populations, the albino mutants were shown to be controlled by one semi-dominant gene, AK, in ornamental kale. The Bol015404 gene was co-segregated with albinism phenotypes, suggesting this unknown function P450 gene as the most likely candidate gene. The albino trait appeared caused by the low temperatures rather than photoperiod. Our results lay a solid foundation on the genetic control of albinism in ornamental kale.

The oral cavity harbors complex microbial communities, which leads to biomaterial-associated infections (BAI) during dental and orthopedic treatments. Conventional antibiotic treatments have met great challenges recently due to the increasing emergency of drug-resistant bacteria. To tackle this clinical issue, antibacterial surface treatments, containing surface modification and coatings, of dental and orthopedic materials have become an area of intensive interest now. Among various antibacterial agents used in surface treatments, metallic agents possess unique properties, mainly including broad-spectrum antibacterial properties, low potential to develop bacterial resistance, relative biocompatibility, and chemical stability. Therefore, this review mainly focuses on underlying antibacterial applications and the mechanisms of metallic agents in dentistry and orthopedics. An overview of the present review indicates that much work remains to be done to deepen the understanding of antibacterial mechanisms and potential side-effects of metallic agents.

Objectives The long-term outcomes of patients with systemic lupus erythematosus (SLE)-related protein-losing enter-opathy (PLE) are unclear. This study was aimed to investigate the clinical characteristics and long-term outcomes of patients with SLE-related PLE. Methods This retrospective cohort study enrolled 58 patients with SLE-related PLE who were admitted to our center from January 2000 to June 2016. The patients’ baseline characteristics and follow-up data were analyzed, and the prognostic outcomes were survival and disease flares. The prognoses were analyzed using Kaplan-Meier curves, log-rank tests, and Cox regression models. Factors with values of P Results Two-thirds of patients had intestinal symptoms, and 77.6% of patients had concomitant organ/system involvement, including serositis (77.6%), lupus nephritis (57.6%), neuropsychiatric lupus (10.3%), and hematological disorders (22.4%). Common abnormalities in the laboratory test results were hypocomplementemia (87.9%), anti-Sjögren syndrome antigen A antibodies (51.7%), and high total cholesterol levels (62.1%). Five flares were recorded in 47 patients. The 1-, 3-, and 5-year survival rates were 93.6%, 91.3%, and 88.4%, respectively. Infection was the cause of death in 60% of patients. High 24-hour urine protein level was an independent risk factor associated with death (P = 0.012). Severe hypoalbuminemia ( Conclusions Infection causes most of the deaths in patients with SLE-related PLE. High 24-hour urine protein level is an independent risk factor associated with death, and severe hypoalbuminemia is a predictor of disease flares.

This study presents a retrospective study aimed to analyze the facial features at each stage of surgical-orthodontic treatment for skeletal class III malocclusion, and predict the changes in the lips after treatment. There were 49 skeletal class III malocclusion patients treated with bimaxillary surgery and orthodontic treatment enrolled in this study. Lateral cephalograms were obtained before treatment (T0), 1 month before surgery (T1), 1 month after surgery (T2), and after debonding (T3) for cephalometric measurements. After the measurement of the required variables, paired t-test, Pearson’s correlation analysis, and multiple linear regression were performed using SPSS 19.0. The main factors associated with changes in the upper lip included ΔUIE-V, ΔA-V, ΔU1A-V, and ΔL1A-V, and those associated with changes in the lower lip included ΔLIE-V, ΔL1A-V, ΔB-V, ΔPog-V, and Δfacial angle. The predicted regression equation for the horizontal change in the upper lip was represented as ΔUL-vertical reference line (VRL) = 9.430 + 0.779 (ΔUIE-VRL) − 0.542(VULT) (P < 0.05) with a mean error of 1.04 mm; the corresponding equation for the lower lip was ΔLL-VRL = −1.670 + 0.530 (ΔB-VRL) + 0.360 (Ls-E) + 0.393 (ΔLIE-VRL) (P < 0.05), with a mean error of 1.51 mm. This study explored the relationship between orthognathic surgery and changes in the lips and obtained the predictive equations of lip position after treatment by using multiple linear regression, which likely offers a reference for prediction of soft tissue changes before surgical-orthodontic treatment in patients with skeletal class III malocclusion. The findings can help dentists to rapidly predict the lip changes after surgical-orthodontic treatment in patients with skeletal class III malocclusion. The study has been registered with the Chinese Clinical Trial Registration (No: ChiCTR1800017694).

Backgroud To analyze the morphological changes of the anterior alveolar bone after the retraction of incisors in premolar extraction cases and the relationship between incisor retraction and remodeling of the alveolar base represented by points A and B displacements. Methods Pre- (T0) and post-treatment (T1) lateral cephalograms of 308 subjects in the maxilla and 154 subjects in the mandible who underwent the orthodontic treatment with extraction of 2 premolars in upper or lower arches were included. Alveolar bone width and height in both the maxillary and mandible incisor area were measured at T0 and T1 respectively. By superimposing the T0 and T1 cephalometric tracings, changes of points A and B, and the movement of the incisors were also measured. Then the correlation between incisor movement and the displacements of points A and B was analyzed. Results The alveolar bone width (ABW) showed a significant decrease in both maxilla and mandible (P P > 0.05). The alveolar bone height (ABH) showed a significant increase in the labial side of maxilla and a significant decrease in the lingual side of maxilla and mandible. A strong positive correlation was verified between incisor movement and position changes of points A and B in both horizontal and vertical directions. Conclusions Anterior alveolar bone width and height generally decreased after orthodontic treatment. Incisor retraction led to significant position changes of points A and B. The decrease of anterior alveolar bone due to significant incisor retraction should be taken into account in treatment planning.

This study determined the flare status of SLE patients in a single-center Chinese cohort and identified the predictors of flare in this underreported Asian population. The patients were recruited from April 2009 to February 2010 at the Peking Union Medical College Hospital (PUMCH), and then followed up regularly at our clinic until December 2015. Flare was defined as an increase in SLEDAI-2K to ≥ 4 points from the previous visit, or appearing of a new SLE manifestation or worsening of a preexisting clinical or hematological manifestation (not included in SLEDAI-2K) that results in restarting or increasing corticosteroids or immunosuppressant. Baseline and follow-up data were collected, and some of them were used as variables in survival analysis for time-to-flare outcome with Kaplan-Meier survival analysis and log-rank tests. Potential predictors with significant differences were further included in a multivariate Cox regression model for confounders adjustment and hazard ratio (HR) calculation. A total of 254 patients were finally included in our analysis. Yearly flare proportion rate was 13.0-15.7%. Renal, hematologic, and neurologic were the most frequently involved organs. Multivariate analysis confirmed onset age up to 18 years (HR 2.14, 95% CI 1.09-4.19) as a flare predictor. Organ damage at entry also showed an association trend with flare (HR = 1.693, 95% CI 0.943 ~ 3.041, p = 0.078). Chinese SLE patients showed a higher prevalence for disease flare compared with other ethnics. Future studies should be designed for figuring out the prediction role of fluctuation of anti-dsDNA antibody for disease flare.

Objective: To provide real-world data and summarize current clinical evidence on the efficacy and safety of sirolimus in active systemic lupus erythematosus (SLE) patients. Methods: This was a prospective real-world clinical study. Included SLE patients should have Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) ⩾ 2. They were treated with sirolimus and followed up regularly. The SLEDAI-2K, Physician Global Assessment (PGA), serological activity indices, and remission of organ manifestations were evaluated. We also performed a meta-analysis to integrate current evidence of sirolimus in SLE. Results: A total of 49 patients were included in the final analysis. After treatment, the SLEDAI-2K (6.2 ± 3.1 versus 4.0 ± 3.4, p = 0.001) decreased significantly, and the prednisone dosage was tapered successfully (9.9 ± 8.8 mg/day versus 5.9 ± 4.0 mg/day, p = 0.002). Serological activity indices also improved [complement 3 (C3): 0.690 ± 0.209 g/l versus 0.884 ± 0.219 g/l, p Conclusion: Sirolimus might be effective and tolerated in SLE. The role of sirolimus in LN requires further study.

In this work, we aim at classifying emphysema in computed tomography (CT) images of lungs. Most previous works are limited to extracting low-level features or mid-level features without enough high-level information. Moreover, these approaches do not take the characteristics (scales) of different emphysema into account, which are crucial for feature extraction. In contrast to previous works, we propose a novel deep learning method based on multiscale deep convolutional neural networks. There are three contributions for this paper. First, we propose to use a base residual network with 20 layers to extract more high-level information. To the best of our knowledge, this is the first deep learning method for classification of emphysema. Second, we incorporate multi-scale information into our deep neural networks so as to take full consideration of the characteristics of different emphysema. Finally, we established a high-quality emphysema dataset which contains 91 high-resolution computed tomography (HRCT) volumes, annotated manually by two experienced radiologists and checked by one experienced chest radiologist. A 92.68% classification accuracy is achieved on this dataset. The results show that (1) the multi-scale method is highly effective in comparison to the single scale setting; (2) the proposed approach is superior to the state-of-the-art techniques.

In this paper, we present a novel image representation approach for classifying emphysema in computed tomography (CT) images of the lung. Our proposed method extends rotation invariant uniform local binary pattern (RIULBP) and local ternary pattern (LTP), which are extensively used in a variety of computer vision applications, into rotation invariant uniform local ternary pattern (RIULTP) with a human perception principle: Weber's law. In addition, by integrating the upper pattern and the lower pattern of the Weber-based RIULTP (WRIULTP), we further put forward the joint Weber-based rotation invariant uniform local ternary pattern (JWRIULTP), which allows for a much richer representation and also takes the comprehensive information of the image into account. The proposed methods are tested on the Outex database (texture database) and the Bruijne and S⊘rensen database (emphysema database). The results show the superiority of the proposed approaches to the state-of-the-art techniques for emphysema classification including rotation invariant local binary pattern (RILBP) and texton-based approach.

The cell membrane characters including membrane Youngs modulus, membrane tension, mechanosensitivity of ion channel et al are important biomarkers in the living cell reseach. These properties have significance in perceptual system mediating by mechanical stimuli like sense touch or pain et al. However, knowledges based on cell membrane characters have been limited due to that there are no efficient research tools. In this paper, a cellular physiological information detect system integrating path-clamp technique and nanorobot technique has been developed which can be used to detect both physiological and physical signals on the cell simultaneously with supplying ultra-micro mechanical stimuli. This system contains a home-designed planar patch clamp module, a nanorobot based on the atomic force microscope (AFM) module and a microfluidic module. With this comprehensive system, an experiment to synchronously track the voltage-induced membrane Youngs modulus changes were proposed on the mouse neuroblastoma cell line (Neuro-2a). The experimental results show that the membrane gets softer when the clamping voltage goes up. Finally, a theoretical derivation was deduced to explain the experimental phenomenon.

This paper introduces a simple method for selective and sensitive detection of black powder by adding chlorinated hydrocarbons in the drift gas instead of changing the structure of conventional ion mobility spectrometer (IMS). The function of chloride modifiers was to substitute Cl−(H2O)n for O 2 − ( H 2 O ) n in the drift region so as to avoid the overlap between O 2 − ( H 2 O ) n and sulfur ion peaks. Among CH2Cl2, CHCl3 and CCl4, CCl4 was chosen as the modifier due to the best peak-to-peak resolution and stability towards the fluctuation of modifier concentration. With 1.4 ppm CCl4 as the modifier, the minimum detectable quantity of 0.1 ng for sulfur was achieved. Moreover, this method showed the ability for detection of common explosives at sub-nanogram level, such as black powder (BP), ammonium nitrate fuel oil (ANFO), 2,4,6-trinitrotoluene (TNT), and pentaerythritol tetranitrate (PETN). In summary, this method requiring no configuration modification has high sensitivity and selectivity, and consumes trace amount of modifier. And these characteristics make it easy to be adopted in current deployed IMS to detect black powder explosives.