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Background: Image segmentation is an important part of computer-aided diagnosis (CAD), the segmentation of small ground glass opacity (GGO) pulmonary nodules is beneficial for the early detection of lung cancer. For the segmentation of small GGO pulmonary nodules, an integrated active contour model based on Markov random field energy and Bayesian probability difference (IACM_MRFEBPD) is proposed in this paper.Methods: First, the Markov random field (MRF) is constructed on the computed tomography (CT) images, then the MRF energy is calculated. The MRF energy is used to construct the region term. It can not only enhance the contrast between pulmonary nodule and the background region, but also solve the problem of intensity inhomogeneity using local spatial correlation information between neighboring pixels in the image. Second, the Gaussian mixture model is used to establish the probability model of the image, and the model parameters are estimated by the expectation maximization (EM) algorithm. So the Bayesian posterior probability difference of each pixel can be calculated. The probability difference is used to construct the boundary detection term, which is 0 at the boundary. Therefore, the blurred boundary problem can be solved. Finally, under the framework of the level set, the integrated active contour model is constructed.Results: To verify the effectiveness of the proposed method, the public data of the lung image database consortium and image database resource initiative (LIDC-IDRI) and the clinical data of the Affiliated Jiangmen Hospital of Sun Yat-sen University are used to perform experiments, and the intersection over union (IOU) score is used to evaluate the segmentation methods. Compared with other methods, the proposed method achieves the best results with the highest average IOU of 0.7444, 0.7503, and 0.7450 for LIDC-IDRI test set, clinical test set, and all test sets, respectively.Conclusions: The experiment results show that the proposed method can segment various small GGO pulmonary nodules more accurately and robustly, which is helpful for the accurate evaluation of medical imaging. [ABSTRACT FROM AUTHOR]

The flavor of Hunan fuzhuan brick tea (HFBT), as a typical post-fermented dark tea, is one of the crucial properties reflecting its quality and influenced by phytochemical components. However, the key components related to the quality of HFBT remain unclear. Thus, this study investigated the relationship between 6 sensory attributes and 56 phytochemical components of 27 HFBT, and identified key substances using multivariate statistical analysis. Results showed that the quality characteristics of HFBT can be categorized as bitter-astringency, mellow, and umami-sweet type. Among these, bitterness, astringency, and sweetness were dominant. Further, a total of 32 phytochemical components were identified as key contributors to the quality characteristic of HFBT through the partial least squares regression (PLSR) analysis and dose over threshold (Dot) factor, including 8 flavonol glycosides, 7 overall indicators, 5 phenolic acids, 5 amino acids, 4 catechin components, 2 organic acids, and 1 alkaloid. Among them, 19 phytochemical components together influence bitterness, astringency, and sweetness. In conclusion, this study provided a reference base for improving the quality of HFBT, and the subsequent experiment will further explore key components related to sourness, umami, and overall taste especially the isomerism and multivariate taste characteristics of amino acids in dark tea. [Display omitted] • The quality of Hunan fuzhuan brick tea was classified 3 types based on QDA. • The phenolics importantly contribute to the taste of Hunan fuzhuan brick tea. • Flavonol glycosides had low threshold and high astringency contribution. • Amino acids may exist as isomers in tea process, thereby affecting umami expression. [ABSTRACT FROM AUTHOR]

The present study aimed to explore the microRNA‑let‑7e (miR‑let‑7e) expression in allergic rhinitis (AR), and to investigate the underlying molecular mechanisms. miR‑let‑7e expression in the nasal mucosa of mice and patients with AR were detected. The expression levels of three inflammatory factors, including histamine, immunoglobulin E and tumor necrosis factor‑α (TNF‑α), in the blood of AR mice and in interleukin (IL)‑13‑stimulated nasal epithelial cells (NECs) were also measured. Furthermore, the target gene of miR‑let‑7e was predicted and validated using a luciferase reporter assay. The expression levels of Janus kinase 1 (JAK1) and signal transducer and activator of transcription 3 (STAT3) were detected. The results demonstrated that miR‑let‑7e was downregulated in patients and mice with AR compared with the controls. In addition, the expression levels of inflammatory factors were higher in the blood of mice with AR compared with the control group, while miR‑let‑7e overexpression inhibited these levels in AR mice and IL‑13‑stimulated NECs. Furthermore, suppressor of cytokine signaling 4 (SOCS4) was revealed as a potential target gene of miR‑let‑7e and was negatively regulated by miR‑let‑7e. Overexpression of SOCS4 abrogated the anti‑inflammatory activity of miR‑let‑7e overexpression. Finally, miR‑let‑7e overexpression activated the JAK1/STAT3 signaling pathway. In conclusion, miR‑let‑7e may serve an important role in the progression and development of AR, while overexpression of miR‑let‑7e had an anti‑inflammatory effect by targeting SOCS4, which may be achieved by activation of the JAK1/STAT3 signaling pathway. [ABSTRACT FROM AUTHOR]

Long noncoding RNA PVT1 has been reported to be dysregulated and play vital roles in a variety of cancers. However, the functions and molecular mechanisms of PVT1 in cervical cancer remain unclear. The objective of this study was to investigate the expression, clinical significance, biological roles, and underlying functional mechanisms of PVT1 in cervical cancer. Our results revealed that PVT1 is upregulated in cervical cancer tissues. Enhanced expression of PVT1 is associated with larger tumor size, advanced International Federation of Gynecology and Obstetrics stage, and poor prognosis of cervical cancer patients. Using gain-of-function and loss-of-function approaches, we demonstrated that overexpression of PVT1 promotes cervical cancer cells proliferation, cell cycle progression and migration, and depletion of PVT1 inhibits cervical cancer cell proliferation, cell cycle progression, and migration. Mechanistically, we verified that PVT1 binds to EZH2, recruits EZH2 to the miR-200b promoter, increases histone H3K27 trimethylation level on the miR-200b promoter, and inhibits miR-200b expression. Furthermore, the effects of PVT1 on cervical cell proliferation and migration depend upon silencing of miR-200b. Taken together, our findings confirmed that PVT1 functions as an oncogene in cervical cancer and indicated that PVT1 is not only an important prognostic marker, but also a potential therapy target for cervical cancer. [ABSTRACT FROM AUTHOR]

The common spatial pattern (CSP) is a very effective feature extraction method in motor imagery based brain computer interface (BCI), but its performance depends on the selection of the optimal frequency band. Although a lot of research works have been proposed to improve CSP, most of these works have the problems of large computation costs and long feature extraction time. To this end, three new feature extraction methods based on CSP and a new feature selection method based on non-convex log regularization are proposed in this paper. Firstly, EEG signals are spatially filtered by CSP, and then three new feature extraction methods are proposed. We called them CSP-wavelet, CSP-WPD and CSP-FB, respectively. For CSP-Wavelet and CSP-WPD, the discrete wavelet transform (DWT) or wavelet packet decomposition (WPD) is used to decompose the spatially filtered signals, and then the energy and standard deviation of the wavelet coefficients are extracted as features. For CSP-FB, the spatially filtered signals are filtered into multiple bands by a filter bank (FB), and then the logarithm of variances of each band are extracted as features. Secondly, a sparse optimization method regularized with a non-convex log function is proposed for the feature selection, which we called LOG, and an optimization algorithm for LOG is given. Finally, ensemble learning is used for secondary feature selection and classification model construction. Combing feature extraction and feature selection methods, a total of three new EEG decoding methods are obtained, namely CSP-Wavelet+LOG, CSP-WPD+LOG, and CSP-FB+LOG. Four public motor imagery datasets are used to verify the performance of the proposed methods. Compared to existing methods, the proposed methods achieved the highest average classification accuracy of 88.86, 83.40, 81.53, and 80.83 in datasets 1–4, respectively. The feature extraction time of CSP-FB is the shortest. The experimental results show that the proposed methods can effectively improve the classification accuracy and reduce the feature extraction time. With comprehensive consideration of classification accuracy and feature extraction time, CSP-FB+LOG has the best performance and can be used for the real-time BCI system. [ABSTRACT FROM AUTHOR]

Feature extraction and selection are important parts of motor imagery electroencephalogram (EEG) decoding and have always been the focus and difficulty of brain-computer interface (BCI) system research. In order to improve the accuracy of EEG decoding and reduce model training time, new feature extraction and selection methods are proposed in this paper. First, a new spatial-frequency feature extraction method is proposed. The original EEG signal is preprocessed, and then the common spatial pattern (CSP) is used for spatial filtering and dimensionality reduction. Finally, the filter bank method is used to decompose the spatially filtered signals into multiple frequency subbands, and the logarithmic band power feature of each frequency subband is extracted. Second, to select the subject-specific spatial-frequency features, a hybrid feature selection method based on the Fisher score and support vector machine (SVM) is proposed. The Fisher score of each feature is calculated, then a series of threshold parameters are set to generate different feature subsets, and finally, SVM and cross-validation are used to select the optimal feature subset. The effectiveness of the proposed method is validated using two sets of publicly available BCI competition data and a set of self-collected data. The total average accuracy of the three data sets achieved by the proposed method is 82.39%, which is 2.99% higher than the CSP method. The experimental results show that the proposed method has a better classification effect than the existing methods, and at the same time, feature extraction and feature selection time also have greater advantages. [ABSTRACT FROM AUTHOR]

An implantable optrode with micro-thermal detectors was designed to investigate the availability and safety of INS using high repetition rates. Optical auditory brainstem responses (oABRs) were recorded in normal-hearing guinea pigs, and the energy thresholds, pulse durations, and amplitudes evoked by the varied stimulus repetitions were analyzed. Stable oABRs could be evoked through INS even as the repetition rate of stimulation reached 19 kHz. The energy threshold of oABRs was elevated, the amplitudes decreased as pulse durations increased and repetition rates were higher, and the latencies were delayed as the pulse durations increased. The temperature variation curves on the site of stimulation significantly increased as the pulse duration increased to 400 μ s. INS elevated the temperature around the stimulus site area via thermal accumulation during radiation, especially when higher repetition stimuli were used. Our results demonstrate that high repetition infrared stimulations can safely evoke stable and available oABRs in normal-hearing guinea pigs. [ABSTRACT FROM AUTHOR]

Purpose: To investigate optimal approaches for appropriate removal of the parotid gland in the management of squamous cell carcinoma (SCC) of the external auditory canal (EAC) at different tumor stages. Methods: In total, 39 patients with SCC of EAC treated at the Second Affiliated Hospital of Nanchang University between September 2003 and April 2019 were enrolled in this study. All patients underwent lateral temporal bone resection or subtotal temporal bone resection. Total parotidectomy was performed in patients with direct parotid invasion. Superficial parotidectomy was performed in patients with parotid node metastasis and patients with advanced stages without evidence of parotid involvement. Results: The mean follow-up period was 68.7 months. Local recurrences or distant metastases occurred in five patients (12.8%). The 5-year overall survival rate was 78.4%. The 5-year survival rate was 100% in early stage (T1 and T2) patients, and 58.9 and 50.0% in patients staged III and IV, respectively. Direct parotid invasion was observed in only advanced-stage patients, while parotid node metastasis was noted in both early and advanced-stage patients preoperatively. There were no significant differences (χ2 = 0.1026; p = 0.749) between different tumor primary locations. However, soft tissue or preauricular organs became vulnerable once the anterior wall was infiltrated or eroded. Conclusion: Parotid management is important for achieving safer and wider tumor-free margins. Total parotidectomy should be mandatory for all advanced-staged (T3 and T4) patients. An optimal decision for parotid management in early stages depends on the infiltration or erosion of the anterior wall of the EAC. [ABSTRACT FROM AUTHOR]

Objective. To establish a risk prediction model of nonalcoholic fatty liver disease (NAFLD) and provide management strategies for preventing this disease. Methods. A total of 200 inpatients and physical examinees were collected from the Department of Gastroenterology and Endocrinology and Physical Examination Center. The data of physical examination, laboratory examination, and abdominal ultrasound examination were collected. All subjects were randomly divided into a training set (70%) and a verification set (30%). A random forest (RF) prediction model is constructed to predict the occurrence risk of NAFLD. The receiver operating characteristic (ROC) curve is used to verify the prediction effect of the prediction models. Results. The number of NAFLD patients was 44 out of 200 enrolled patients, and the cumulative incidence rate was 22%. The prediction models showed that BMI, TG, HDL-C, LDL-C, ALT, SUA, and MTTP mutations were independent influencing factors of NAFLD, all of which has statistical significance (P < 0.05). The area under curve (AUC) of logistic regression and the RF model was 0.940 (95% CI: 0.870~0.987) and 0.945 (95% CI: 0.899~0.994), respectively. Conclusion. This study established a prediction model of NAFLD occurrence risk based on the RF, which has a good prediction value. [ABSTRACT FROM AUTHOR]

Keywords: endolymphatic sac decompression; hearing Loss; Meniere's disease; semicircular canal occlusion; vertigo EN endolymphatic sac decompression hearing Loss Meniere's disease semicircular canal occlusion vertigo 319 322 4 02/17/22 20220301 NES 220301 Key points Triple semicircular canal occlusion is an efficient strategy for vertigo control in patients with intractable Meniere's disease. Approximately 10% of patients suffered from persistent vertigo, despite an optimal conservative treatment, are considered as intractable MD.1 To date, many methods have been attempted to treat these patients, including a variety of surgeries: selective vestibular neurotomy, labyrinthectomy and endolymphatic sac surgeries. The surgery can block the movement of endolymph in the canals to eliminate vertigo attacks induced by position changing Patients with advanced-stage MD suffered more from hearing deterioration postoperatively. [Extracted from the article]

Understanding of the surface structure of FGH96 alloy powders has implications for the subsequent evolution in sintering. The results from this work indicate that the oxide film of powder surface was composed of TiO 2 particles and homogeneous oxide layer. Two types of carbides with size of about 30–50 nm and 250 nm are founded, which can further lead to the differences in low-temperature oxidation during the atomization process, resulting in the presence of amorphous TiO 2 particles of similar size to the precipitates above them. The oxidation of the γ leads to a uniform amorphous oxide layer with a thickness of approximately 14 nm above the powder matrix. [Display omitted] • The correspondence between surface morphology and structure was established. • The M(Ti, Nb)C is precipitated on the powder surface during atomization. • Different oxidation products of powders due to the existence of precipitated phase. • Oxide film of powder surface consists of amorphous oxide layer and TiO 2 particles. [ABSTRACT FROM AUTHOR]

• Particle size had the biggest effect on non-volatile compounds in black tea infusions. • Compositions of volatile compounds were most affected by water/tea ratio. • Optimal conditions for black tea infusion: 89 °C, 6 min, 56 mL/g, and 2000 μm. • Geraniol and β-ionone could enhance the sweetness of black tea infusion. As a worldwide popular drink, black tea has always been one of the main focuses of tea studies. However, few studies have addressed the flavor profiles and related components, and most researches were based on a single factor. This study investigated the effects of multiple brewing conditions (temperature, time, water/tea ratio, and particle size) on the phytochemicals (non-volatile and volatile compounds) and sensory profiles of black tea infusions through response surface methodology. The regression models describing the brewing of detected indexes were significant (p ≤ 0.01) and reliable (R2 ≥ 0.902). The particle size led to the greatest variation of non-volatile compounds and presented negative correlations, while the water/tea ratio affected the composition of volatile compounds the most. Meanwhile, through the addition of the selected aroma compounds (geraniol and β-ionone), an enhancement of black tea infusion sweetness was observed, proved the existence of odor–taste interaction in black tea infusions. [ABSTRACT FROM AUTHOR]

Background: DNA vaccination is a convenient means of immunizing animals with recombinant parasite antigens. DNA delivery methods are believed to affect the qualitative nature of immune responses to DNA vaccines in ways that may affect their protective activity. However, relatively few studies have directly compared immune responses to plasmids encoding the same antigens after injection by different routes. Therefore, the purpose of this study was to explore the influence of the route of administration on antibody responses to plasmids encoding antigens from the filarial nematode parasite Brugia malayi. Methods: Four B. malayi genes and partial genes encoding paramyosin (BM5), heat shock protein (BMHSP-70), intermediate filament (BMIF) and a serodiagnostic antigen (BM14) were inserted in eukaryotic expression vectors (pJW4303 and pCR™3.1). BALB/c mice were immunized with individual recombinant plasmids or with a cocktail of all four plasmids by intramuscular injection (IM) or by gene gun-intradermal inoculation (GG). Antibody responses to recombinant antigens were measured by ELISA. Mean IgG1 to IgG2a antibody ratios were used as an indicator of Th1 or Th2 bias in immune responses induced with particular antigens by IM or GG immunization. The statistical significance of group differences in antibody responses was assessed by the nonparametric Kruskal-Wallis test. Results: Mice produced antibody responses to all four filarial antigens after DNA vaccination by either the IM or GG route. Antibody responses to BM5 paramyosin were strongly biased toward IgG1 with lower levels of IgG2a after GG vaccination, while IM vaccination produced dominant IgG2a antibody responses. Antibody responses were biased toward IgG1 after both IM and GG immunization with BMIF, but antibodies were biased toward IgG2a after IM and GG vaccination with BMHSP-70 and BM14. Animals injected with a mixture of four recombinant plasmid DNAs produced antibodies to all four antigens. Conclusions: Our results show that monovalent and polyvalent DNA vaccination successfully induced antibody responses to a variety of filarial antigens. However, antibody responses to different antigens varied in magnitude and with respect to isotype bias. The isotype bias of antibody responses following DNA vaccination can be affected by route of administration and by intrinsic characteristics of individual antigens. [ABSTRACT FROM AUTHOR]

Background/Aims: This study aims to investigate the effect of CD47 on the development of laryngeal squamous cell carcinoma (LSCC) and the therapeutic potential of monoclonal antibody against CD47 and its ligand SIRPα in the treatment of LSCC. Methods: We firstly detected the expressions of CD47 mRNA and protein in LSCC and para-carcinoma tissues, introduced the most efficient CD47siRNA sequence into LSCC cells by lentiviral transfection and employed three monoclonal antibodies to evaluate their anti-LSCC effects in vitro and in vivo. Results: We observed that the mRNA and protein expressions of CD47 in LSCC tissue had significant increase in LSCC tissues compared with those in para-carcinoma tissue (p < 0.05). After the treatments of three monoclonal antibodies, i.e. anti-SIRPα, anti-CD47 BRIC126, anti-CD47 B6H12.2, in rats transfected with Hep-2 cell, it has been showed that the mRNA and protein expressions of CD47 in LSCC tissue decreased, macrophage efficiency was promoted when anti-SIRPα and/or CD47siRNA were used, the amounts, viabilities and expressions of CD47 protein of tumor cell were significantly inhibited. Additionally, combined use of CD47siRNA and anti-SIRPα seemed more efficient than solo use of CD47siRNA/anti-SIRPα. Conclusion: The results suggested a critical role of CD47 in LSCC development and the promising treatment of antiCD47/SIRPα and/or CD47siRNA in LSCC. [ABSTRACT FROM AUTHOR]

EEG signals exhibit commonality and variability across subjects, sessions, and tasks. But most existing EEG studies focus on mean group effects (commonality) by averaging signals over trials and subjects. The substantial intra- and inter-subject variability of EEG have often been overlooked. The recently significant technological advances in machine learning, especially deep learning, have brought technological innovations to EEG signal application in many aspects, but there are still great challenges in cross-session, cross-task, and cross-subject EEG decoding. In this work, an EEG-based biometric competition based on a large-scale M3CV (A Multi-subject, Multi-session, and Multi-task Database for investigation of EEG Commonality and Variability) database was launched to better characterize and harness the intra- and inter-subject variability and promote the development of machine learning algorithm in this field. In the M3CV database, EEG signals were recorded from 106 subjects, of which 95 subjects repeated two sessions of the experiments on different days. The whole experiment consisted of 6 paradigms, including resting-state, transient-state sensory, steady-state sensory, cognitive oddball, motor execution, and steady-state sensory with selective attention with 14 types of EEG signals, 120000 epochs. Two learning tasks (identification and verification), performance metrics, and baseline methods were introduced in the competition. In general, the proposed M3CV dataset and the EEG-based biometric competition aim to provide the opportunity to develop advanced machine learning algorithms for achieving an in-depth understanding of the commonality and variability of EEG signals across subjects, sessions, and tasks. [ABSTRACT FROM AUTHOR]

Abstract: Commercial-scale fermentation for tobramycin manufacture is carried out with Streptomyces tenebrarius. Impurity profiling during various phases of pharmaceutical production is important for evaluating the effectiveness of a processing step and meeting regulatory requirements. High-performance anion-exchange (HPAE) chromatography with integrated pulsed amperometric detection (HPAE-IPAD) is a highly sensitive method used to assay tobramycin and to assess purity, but no prior publications demonstrated the capability of this technique to monitor purity at various stages of production at either the typical concentrations or in the typical matrices of a manufacturing process. In addition, the identities of the impurity peaks observed in commercial sources of tobramycin when assayed by using HPAE-IPAD are mainly unknown. Regulatory agencies generally require these impurities to be characterized when found above certain limits, and when present at higher levels require toxicological studies. In this paper, we analyze tobramycin samples using HPAE-IPAD at different stages of production and show the impurity profile and concentration changes through the manufacturing process. We successfully identified nearly all the impurity peaks found in commercially available tobramycin, based on known degradation pathways deduced from extreme pH forced degradation studies, which we experimentally reproduced, and based on previously known related substances found in S. tenebrarius fermentation broth. In crude and final tobramycin products, we identified the peaks for neamine, kanamycin B, nebramine, kanosamine, 2-deoxystreptamine. We tentatively identified deoxystreptamine–kanosaminide in crude and final products, and kanamycin A, carbamoyl-kanamycin B and carbamoyl-tobramycin in down stream process intermediates of a S. tenebrarius fermentation culture. Results presented in this paper support the effective use of the HPAE-IPAD method for in-process impurity profiling of tobramycin, and as a stability-indicating technique after product purification. [Copyright &y& Elsevier]