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The study was to explore the effect of the extracts of Angelica sinensis (EAs) on lipid oxidation in fish feeds compared with ethoxyquin (EQ) and the effect of dietary EAs on growth performance of carp (Cyprinus carpio var. Jian). Firstly, fish feeds were respectively added with EQ, and ethyl ether extract, ethyl acetate extract (EAE), acetone extract, ethanol extract (EE) and aqueous extract (AQE) of Angelica sinensis, except for the control. The results showed that EAs and EQ inhibited lipid oxidation in fish feeds (P < 0.05). Of all of the examined EAs, EAE showed the strongest protective effects against lipid oxidation (P < 0.05). Moreover, EAE at high concentrations showed a stronger effect on lipid oxidation compared with EQ (P < 0.05). Then, 7 experimental diets respectively supplemented with 0.0, 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 g/kg of EAE were fed to the respective treatment groups for 30 d. Four replicates were performed for each treatment group; 20 carp (mean weight: 12.10 ± 0.13 g) were in each replicate. The results indicated that dietary EAE improved the growth performance in carp (P < 0.05). The appropriate concentration of EAE for carp growth was estimated to be 3.643 g/kg diet. Thus, EAE could be used as a natural antioxidant in feeds for Jian carp. Keywords: Angelica sinensis, Extracts, Ethoxyquin, Lipid oxidation, Growth performance

The application of blueberry anthocyanins (ANs) was limited due to their low in-process stability and bioavailability. In our study, the stability and antioxidant capacity of ANs before and after adding bovine serum albumin (BSA) were examined by simulating various processing, storage (light, sucrose, and vitamin C (Vc)), and in vitro simulated digestion parameters. For this purpose, pH-differential method, high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS), peroxyl scavenging capacity assay, and cellular antioxidant assay were conducted. BSA at different concentrations, specifically at 0.15 mg/mL, inhibited the degradation of ANs and the loss of antioxidant capacity. The results suggest that BSA has a positive effect on ANs.

The reliability of machine learning models can be compromised when trained on low quality data. Many large-scale medical imaging datasets contain low quality labels extracted from sources such as medical reports. Moreover, images within a dataset may have heterogeneous quality due to artifacts and biases arising from equipment or measurement errors. Therefore, algorithms that can automatically identify low quality data are highly desired. In this study, we used data Shapley, a data valuation metric, to quantify the value of training data to the performance of a pneumonia detection algorithm in a large chest X-ray dataset. We characterized the effectiveness of data Shapley in identifying low quality versus valuable data for pneumonia detection. We found that removing training data with high Shapley values decreased the pneumonia detection performance, whereas removing data with low Shapley values improved the model performance. Furthermore, there were more mislabeled examples in low Shapley value data and more true pneumonia cases in high Shapley value data. Our results suggest that low Shapley value indicates mislabeled or poor quality images, whereas high Shapley value indicates data that are valuable for pneumonia detection. Our method can serve as a framework for using data Shapley to denoise large-scale medical imaging datasets.

Objective: To analyze the differential expression of related serum proteins was detected in patients with AR who were sensitized to dust mites pre- and 6-day post-RIT. Methods: Serum samples were collected from 15 AR, 15 6-day post-RIT and 10 healthy control patients. This analysis was performed using iTRAQ technique and was coupled with 2-dimensional gel electrophoresis and mass spectrometry. To determine the intimacy of the screened related differential proteins, a hierarchical analysis was performed with Cluster 3.0 software, and the results were visualized using Java TreeView software. Last, an ELISA was employed to validate the selected CRP, CTHRC1 and WDR89 protein expression data. Results: Compared with the healthy control group, the most upregulated protein in the AR group and the most downregulated proteins in the 6-day post-RIT group were CTHRC1 and WDR89. Compared with the healthy control group, the most downregulated protein in the AR group and the most upregulated protein of the 6-day post-RIT group was CRP. The serum protein levels of CRP, CTHRC1 and WDR89 proteins were determined by ELISA. It was found that the differential expression of CTHRC1 and WDR89 in the AR and 6-day post-RIT groups were statistically significant (P 0.05) was found in the differential expression of serum CRP in the AR and 6-day post-RIT groups. Conclusions: We found that CTHRC1 and WDR89 might be associated with the pathogenesis of AR, and they may play a regulatory role in the RIT.

The CC chemokine receptor 3 (CCR3) expressed by eosinophils, mast cells and Th2 cells is closely related to allergic diseases. The objective of this study was to explore whether silencing of CCR3 with short hairpin RNAs (shRNAs) delivered by a lentiviral vector could impact the function of mast cells in a murine model of allergic rhinitis (AR) in vivo. The murine model of allergic rhinitis (AR) inducing by ovalbumin (OVA) was constructed, and the BALB/c mice were divided into normal control group, AR group, controlshRNA treated group and lentiviral CCR3-shRNA treated group. The recombinant lentivirus vectors which express a short hairpin RNA (shRNA) targeting the CCR3 were dropped into the nasal cavity of OVA-sensitized mice before the challenges. Real-time fluorescence quantitative PCR and western blotting were performed to observe inhibitory effect of CCR3 gene. Nasal symptoms of mice and OVA-specific IgE in each group were assessed. Concentrations of histamine, tryptase and Prostaglandin D2 (PGD2) in bone marrow, peripheral blood and nasal mucosa were analyzed. Furthermore, histological analysis and electron microscopy analysis were applied to detect the histology changes of nasal mucosa and the infiltration of mast cells in nasal mucosa. The results showed that administration of CCR3shRNA could effectively inhibit the expression of the CCR3 gene in bone marrow, peripheral blood and nasal mucosa, which reduced the nasal symptoms, the level of OVA-specific IgE, the inflammatory cells and mast cells infiltration into nasal cavity, and relieved the histopathological changes of nasal mucosa. In addition, intervention of CCR3shRNA could reduce the levels of the histamine, tryptase and PGD2 in bone marrow, peripheral blood and nasal mucosa. These results suggest that inhibition of CCR3 gene expression by shRNAs lentiviral vectors can effectively attenuate migration, infiltration and degranulation of mast cells in local tissues and alleviate the inflammation of allergic rhinitis mice.

BackgroundHeterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide ASD individuals into non-overlapping (categorical) subgroups. However, continuous inter-individual variation in ASD suggests the need for a dimensional approach.MethodsA Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of ASD individuals into multiple abnormal RSFC patterns, i.e., categorical subtypes henceforth referred to as “factors”. Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 ASD individuals (age 5.2-57 years) from two multisite repositories. Posthoc analyses associated factors with symptoms and demographics.ResultsAnalyses yielded three factors with dissociable whole-brain hypo/hyper RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default network, but the directionality (hypo/hyper RSFC) differed across factors. Factor 1 was associated with core ASD symptoms, while factor 2 was associated with comorbid symptoms. Older males preferentially expressed factor 3. Factors were robust across multiple control analyses and not associated with IQ, nor head motion.ConclusionsThere exist at least three ASD factors with dissociable patterns of whole-brain RSFC, behaviors and demographics. Heterogeneous default network hypo/hyper RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms - a less appreciated domain of heterogeneity in ASD. These factors are co-expressed in ASD individuals with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.

Background Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping (categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach. Methods A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of individuals with ASD into multiple abnormal RSFC patterns, i.e., categorical subtypes, henceforth referred to as “factors.” Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 individuals with ASD (5.2–57 years of age) from two multisite repositories. Post hoc analyses associated factors with symptoms and demographics. Results Analyses yielded three factors with dissociable whole-brain hypo- and hyper–RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default mode network, but the directionality (hypo- or hyper–RSFC) differed across factors. Factor 1 was associated with core ASD symptoms. Factors 1 and 2 were associated with distinct comorbid symptoms. Older male participants preferentially expressed factor 3. Factors were robust across control analyses and were not associated with IQ or head motion. Conclusions There exist at least three ASD factors with dissociable whole-brain RSFC patterns, behaviors, and demographics. Heterogeneous default mode network hypo- and hyper–RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms—a less appreciated domain of heterogeneity in ASD. These factors are coexpressed in individuals with ASD with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.

PURPOSE: To compare machine learning methods for classifying mass lesions on mammography images that use predefined image features computed over lesion segmentations to those that leverage segmentation-free representation learning on a standard, public evaluation dataset. METHODS: We apply several classification algorithms to the public Curated Breast Imaging Subset of the Digital Database for Screening Mammography (CBIS-DDSM), in which each image contains a mass lesion. Segmentation-free representation learning techniques for classifying lesions as benign or malignant include both a Bag-of-Visual-Words (BoVW) method and a Convolutional Neural Network (CNN). We compare classification performance of these techniques to that obtained using two different segmentation-dependent approaches from the literature that rely on specific combinations of end classifiers (e.g. linear discriminant analysis, neural networks) and predefined features computed over the lesion segmentation (e.g. spiculation measure, morphological characteristics, intensity metrics). RESULTS: We report area under the receiver operating characteristic curve (A(Z)) values for malignancy classification on CBIS-DDSM for each technique. We find average A(Z) values of 0.73 for a segmentation-free BoVW method, 0.86 for a segmentation-free CNN method, 0.75 for a segmentation-dependent linear discriminant analysis of Rubber-Band Straightening Transform features, and 0.58 for a hybrid rule-based neural network classification using a small number of hand-designed features. CONCLUSIONS: We find that malignancy classification performance on the CBIS-DDSM dataset using segmentation-free BoVW features is comparable to that of the best segmentation-dependent methods we study, but also observe that a common segmentation-free CNN model substantially and significantly outperforms each of these (p

BackgroundThere is considerable interest in a dimensional transdiagnostic approach to psychiatry. Most transdiagnostic studies have derived factors based only on clinical symptoms, which might miss possible links between psychopathology, cognitive processes and personality traits. Furthermore, many psychiatric studies focus on higher-order association brain networks, thus neglecting the potential influence of huge swaths of the brain.MethodsA multivariate data-driven approach (partial least squares; PLS) was utilized to identify latent components linking a large set of clinical, cognitive and personality measures to whole-brain resting-state functional connectivity (RSFC) patterns across 224 participants. The participants were either healthy (N=110) or diagnosed with bipolar disorder (N=40), attention-deficit/hyperactivity disorder (N=37), schizophrenia (N=29) or schizoaffective disorder (N=8). In contrast to traditional case-control analyses, the diagnostic categories were not utilized in the PLS analysis, but were helpful for interpreting the components.ResultsOur analyses revealed three latent components corresponding to general psychopathology, cognitive dysfunction and impulsivity. Each component was associated with a unique whole-brain RSFC signature and shared across all participants. The components were robust across multiple control analyses and replicated using independent task functional magnetic resonance imaging data from the same participants. Strikingly, all three components featured connectivity alterations within the somatosensory-motor network, and its connectivity with subcortical structures and cortical executive networks.ConclusionsWe identified three distinct dimensions with dissociable (but overlapping) whole-brain RSFC signatures across healthy individuals and individuals with psychiatric illness, providing potential intermediate phenotypes that span across diagnostic categories. Our results suggest expanding the focus of psychiatric neuroscience beyond higher-order brain networks.

Firstly, a linoleic and linolenic acid emulsion and fish feeds were incubated with graded levels of ethoxyquin (EQ) and petroleum ether extract, ethyl acetate extract (EAE), ethanol extract and aqueous extract of Angelica sinensis. The results showed that EQ and extracts of Angelica sinensis (EAs) inhibited lipid oxidation in material above. Of all of the examined EAs, EAE showed the strongest protective effects against the lipid oxidation. Moreover, EAE at high concentrations showed a stronger inhibitory effect on lipid oxidation than that of EQ. Next, 7 experimental diets that respectively supplemented 0.0, 0.2, 0.8 and 3.2 g kg−1 of EQ and EAE were fed to 280 juvenile red carp (Cyprinus carpio var. xingguonensis) with seven treatment groups for 30 days. The results indicated that dietary EAE improved growth performance in carp. Moreover, dietary EAE increased the activities of trypsin, lipase, alpha-amylase, alkaline phosphatase, glutamate-oxaloacetate transaminase and glutamate-pyruvate transaminase (GPT) and decreased plasma ammonia content in carp. Meanwhile, dietary EAE reduced the levels of malondialdehyde and raised the activities of anti-superoxide anion, anti-hydroxyl radical, superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase and the content of reduced glutathione in the hepatopancreas and intestine of carp. However, with the exception of GPT, dietary EQ got the opposite results to dietary EAE in carp. These results revealed that dietary EAE improved the digestive, absorptive and antioxidant capacities in fish. However, dietary EQ inhibited the digestive, absorptive and antioxidant capacities in fish. So, EAE could be used as a natural antioxidant for replacing EQ in fish feeds.