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Increasing evidences indicate that the gut microbiota is involved in the development and therapy of gastrointestinal and hepatic disease. Imbalance of gut microbiota occurs in the early stages of diseases, and maintaining the balance of the gut microbiota provides a new strategy for the treatment of diseases. It has been reported that Parabacteroides distasonis is associated with multiple diseases. As the next‐generation probiotics, several studies have demonstrated its positive regulation on the gastrointestinal and hepatic disease, including inflammatory bowel disease, colorectal cancer, hepatic fibrosis, and fatty liver. The function of P. distasonis and its metabolites mainly affect host immune system, intestinal barrier function, and metabolic networks. Manipulation of P. distasonis with natural components lead to the protective effect on enterohepatic disease. In this review, the metabolic pathways regulated by P. distasonis are summarized to illustrate its active metabolites and their impact on host metabolism, the role and action mechanism in gastrointestinal and hepatic disease are discussed. More importantly, the natural components can be used to manipulate P. distasonis as treatment strategies, and the challenges and perspectives of P. distasonis in clinical applications are discussed. [ABSTRACT FROM AUTHOR]

Pickled tea is an anaerobically fermented tea common in Thailand, Myanmar and Yunnan minority areas. γ-aminobutyric acid (GABA) is non-protein amino acid with multiple bioactives, which can be easily produced under anaerobic conditions. During the processing of pickled tea, controlling the process parameters is effective for the production of GABA-rich products; however, the precise parameters remain to be clarified. In the present study, the fresh leaves of Camellia sinensis (L.) Kuntze (C. sinensis) 'FudingDabai', C. sinensis 'MabianLv No. 1', C. sinensis 'Wuniuzao' and C. sinensis 'Fuxuan No. 9' were used as raw materials to process GABA-rich pickled tea. Single-factor and orthogonal experiments were conducted to determine the best tea cultivars and optimize the best processing parameters via comparing the content of GABA, tea polyphenols (TPs) and other biochemical components of GABA-rich pickled tea. The results of the signal-factor experiment showed that the fresh leaves of C. sinensis 'MabianLv No. 1' had the highest GABA content of 2.61 mg·g−1 after treatment with vacuum for 6 h; therefore, C. sinensis 'MabianLv No. 1' was selected as the raw material for the subsequent experiments. Orthogonal experiments showed that the highest GABA content of 2.53 mg·g−1 was found in the pickled tea with 8 h of vacuum treatment, 20 min of rolling after microwave fixing, 20 min of spreading and 20 d of anaerobic fermentation at room temperature. Further, the sensory evaluation showed that it possesses a strong sour taste with a slight sweetness and a light yellow color and better comprehensive quality. This indicates that these parameters are optimal for the processing of GABA-rich pickled tea. This study will provide scientific basis for the subsequent production of high GABA tea. [ABSTRACT FROM AUTHOR]

Impatiens uliginosa is a native and potential water body-restoring ornamental plant. In this study, RNA-Seq technology was used to analyze the transcriptome of its floral organs. Candidate genes related to flower color changes under copper stress were investigated through transcriptome screening, and the intrinsic mechanism of the effects of different concentrations of copper on I. uliginosa was revealed at the molecular level. The main findings were as follows: (1) Transcriptome sequencing analysis was performed on the flower organs of I. uliginosa treated with different concentrations of copper (0 mg·L−1, 10 mg·L−1, and 20 mg·L−1). A total of 70,319 transcripts and 39,949 unigenes were obtained. An analysis of differentially expressed genes revealed structural genes including GT, ANS, CHI, and PAL; transcription factors including MYB and WD40; and transport factors including GST and ABC. (2) The gene expression levels of flower color changed in the flowering period of I. uliginosa at different copper concentrations. The expression levels of IuGT and IuGST genes in I. uliginosa were significantly different under different concentrations of copper treatments. Their expression levels were the highest at a copper concentration of 0 mg·L−1 and the lowest at 20 mg·L−1. In summary, the low expression of IuGT and IuGST genes was more conducive to the formation of white flowers of I. uliginosa. [ABSTRACT FROM AUTHOR]

Objective: To examine factors longitudinally associated with cervical cancer screening uptake among rural Chinese women, guided by protection motivation theory (PMT).Methods: A large sample of women (n = 2408, aged 35-65 years old) was randomly selected from a rural county in China in 2015 and followed up for 2 years. Data for demographic factors, knowledge of cervical cancer screening, screening outcome, and six PMT constructs measured at the baseline in 2015 were used to predict cervical cancer screening participation at the follow-up in 2017 using structural equation model method.Results: Among the 2408 women at the baseline, 1879 (78.03%) participated in the screening services at the follow-up. In addition to significant direct effect of age, social status and baseline screening outcome, and three (perceived severity, fear arousal and response efficacy) of the six PMT subconstructs, four variables (age, social status, knowledge of cervical cancer screening, and baseline screening outcome) at the baseline were indirectly associated with screening participation, mediated by the three significant PMT subconstructs.Conclusions: Findings of this study indicate that the rate of participating in cervical cancer screening for rural women needs to be further improved. In addition to the commonly reported influential factors, PMT subconstructs play important roles in encouraging rural women in China to participate in cervical cancer screening. These longitudinal findings provided data much needed for future research to develop evidence-based intervention programs to enhance cervical cancer screening among rural women in China. [ABSTRACT FROM AUTHOR]

Antimicrobial peptides (AMPs) have recently been exploited to fabricate anti-infective medical devices due to their biocompatibility and ability to combat multidrug-resistant bacteria. Modern medical devices should be thoroughly sterilised before use to avoid cross-infection and disease transmission, consequently it is essential to evaluate whether AMPs withstand the sterilisation process or not. In this study, the effect of radiation sterilisation on the structure and properties of AMPs was explored. Fourteen AMPs formed from different monomers with different topologies were synthesised by ring-opening polymerisation of N-carboxyanhydrides. The results of solubility testing showed that the star-shaped AMPs changed from water-soluble to water-insoluble after irradiation, while the solubility of linear AMPs remained unchanged. Matrix-assisted laser desorption/ionisation time of flight mass spectrometry showed that the molecular weight of the linear AMPs underwent minimal changes after irradiation. The results of minimum inhibitory concentration assay also illustrated that radiation sterilisation had little effect on the antibacterial properties of the linear AMPs. Therefore, radiation sterilisation may be a feasible method for the sterilisation of AMPs, which have promising commercial applications in medical devices.

We developed a reliable and repeatable process to create hyper-realistic, kidney phantoms with tunable image visibility under ultrasound (US) and CT imaging modalities. A methodology was defined to create phantoms that could be produced for renal biopsy evaluation. The final complex kidney phantom was devised containing critical structures of a kidney: kidney cortex, medulla, and ureter. Simultaneously, some lesions were integrated into the phantom to mimic the presence of tumors during biopsy. The phantoms were created and scanned by ultrasound and CT scanners to verify the visibility of the complex internal structures and to observe the interactions between material properties. The result was a successful advancement in knowledge of materials with ideal acoustic and impedance properties to replicate human organs for the field of image-guided interventions.

Kidney biopsies are currently performed using preoperative imaging to identify the lesion of interest and intraoperative imaging used to guide the biopsy needle to the tissue of interest. Often, these are not the same modalities forcing the physician to perform a mental cross-modality fusion of the preoperative and intraoperative scans. This limits the accuracy and reproducibility of the biopsy procedure. In this study, we developed an augmented reality system to display holographic representations of lesions superimposed on a phantom. This system allows the integration of preoperative CT scans with intraoperative ultrasound scans to better determine the lesion's real-time location. An automated deformable registration algorithm was used to increase the accuracy of the holographic lesion locations, and a magnetic tracking system was developed to provide guidance for the biopsy procedure. Our method achieved a targeting accuracy of 2.9 ± 1.5 mm in a renal phantom study.

This study demonstrates that a variant of a Siamese neural network architecture is more effective at classifying high-dimensional radiomic features (extracted from T2 MRI images) than traditional models, such as a Support Vector Machine or Discriminant Analysis. Ninety-nine female patients, between the ages of 20 and 48, were imaged with T2 MRI. Using biopsy pathology, the patients were separated into two groups: those with breast cancer (N=55) and those with GLM (N=44). Lesions were segmented by a trained radiologist and the ROIs were used for radiomic feature extraction. The radiomic features include 536 published features from Aerts et al. , along with 20 features recurrent quantification analysis features. A Student T-Test was used to select features found to be statistically significant between the two patient groups. These features were then used to train a Siamese neural network. The label given to test features was the label of whichever class the test features with the highest percentile similarity within the training group. Within the two highest-dimensional feature sets, the Siamese network produced an AUC of 0.853 and 0.894, respectively. This is compared to best non-Siamese model, Discriminant Analysis, which produced an AUC of 0.823 and 0.836 for the two respective feature sets. However, when it came to the lower-dimensional recurrent features and the top-20 most significant features from Aerts et al. , the Siamese network performed on-par or worse than the competing models. The proposed Siamese neural network architecture can outperform competing other models in high-dimensional, low-sample size spaces with regards to tabular data.

Segmentation of the prostate in magnetic resonance (MR) images has many applications in image-guided treatment planning and procedures such as biopsy and focal therapy. However, manual delineation of the prostate boundary is a time-consuming task with high inter-observer variation. In this study, we proposed a semiautomated, three-dimensional (3D) prostate segmentation technique for T2-weighted MR images based on shape and texture analysis. The prostate gland shape is usually globular with a smoothly curved surface that could be accurately modeled and reconstructed if the locations of a limited number of well-distributed surface points are known. For a training image set, we used an inter-subject correspondence between the prostate surface points to model the prostate shape variation based on a statistical point distribution modeling. We also studied the local texture difference between prostate and non-prostate tissues close to the prostate surface. To segment a new image, we used the learned prostate shape and texture characteristics to search for the prostate border close to an initially estimated prostate surface. We used 23 MR images for training, and 14 images for testing the algorithm performance. We compared the results to two sets of experts' manual reference segmentations. The measured mean ± standard deviation of error values for the whole gland were 1.4 ± 0.4 mm, 8.5 ± 2.0 mm, and 86 ± 3% in terms of mean absolute distance (MAD), Hausdorff distance (HDist), and Dice similarity coefficient (DSC). The average measured differences between the two experts on the same datasets were 1.5 mm (MAD), 9.0 mm (HDist), and 83% (DSC). The proposed algorithm illustrated a fast, accurate, and robust performance for 3D prostate segmentation. The accuracy of the algorithm is within the inter-expert variability observed in manual segmentation and comparable to the best performance results reported in the literature.

Breast cancer in young women is commonly aggressive, in part because the proportion of high-grade, triple-negative (TN) tumor is too high. There are certain limitations in the detection of biopsies or surgical specimens which only select part of tumor sample tissue and ignore the possible heterogeneity of tumors. In clinical practice, MRI is used for the diagnosis of breast cancer. MRI-based radiomics is a developing approach that may provide not only the diagnostic value for breast cancer but also the predictive or prognostic associations between the images and biological characteristics. In this work, we used radiomics methods to analyze MR images of breast cancer in 53 young women, and correlated the radiomics data with molecular subtypes. The results indicated a significant difference between TN type and non-TN type of breast cancer in young women on the radiomics features based on T2-weighted MR images. This may be helpful for the identification of TN type and guiding the therapeutic strategies.

Thermo-, pH-, and electrochemical-sensitive cellulose graft copolymers, hydroxypropyl cellulose-g-poly(4-vinylpyridine)-Os(bipyridine) (HPC-g-P4VP-Os(bpy)), were synthesized and characterized. The electrochemical properties of the resulting material were investigated via cyclic voltammetry by coating the graft copolymers on the platinized carbon electrode. The results indicated that the electrochemical properties of the graft copolymer modified electrode were responsive to the pH values of the electrolyte solution. The reversible transformation between the active and inactive state originated from the changes in the architecture of the HPC-g-P4VP-Os(bpy) graft copolymer at different pH values. At high pH (e.g., above the pK(a) of P4VP), the chains of P4VP collapsed, and the electrochemical activity of the electrode was reduced. With immobilization of glucose oxidase (GOx) on the graft copolymer decorated electrode, a biosensor for glucose detection was prepared. The current of the biosensor depended on the glucose concentration in the detected solution and increased with the successive addition of glucose.