Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging.

Cardiac magnetic resonance imaging (CMR) is the gold standard for cardiac function assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However, its widespread application has been limited by the heavy resource burden of CMR interpretation. Here, to address this challenge, we developed and validated computerized CMR interpretation for screening and diagnosis of 11 types of CVD in 9,719 patients. We propose a two-stage paradigm consisting of noninvasive cine-based CVD screening followed by cine and late gadolinium enhancement-based diagnosis. The screening and diagnostic models achieved high performance (area under the curve of 0.988 ± 0.3% and 0.991 ± 0.0%, respectively) in both internal and external datasets. Furthermore, the diagnostic model outperformed cardiologists in diagnosing pulmonary arterial hypertension, demonstrating the ability of artificial intelligence-enabled CMR to detect previously unidentified CMR features. This proof-of-concept study holds the potential to substantially advance the efficiency and scalability of CMR interpretation, thereby improving CVD screening and diagnosis.

Real-time detection of acetone gas molecules at ppt levels in an air atmosphere using a partially suspended graphene surface acoustic wave skin gas sensor.

To improve the quality of modern life in the current society, low-power, highly sensitive, and reliable healthcare technology is necessary to monitor human health in real-time. In this study, we fabricated partially suspended monolayer graphene surface acoustic wave gas sensors (G-SAWs) with a love-mode wave to effectively detect ppt-level acetone gas molecules at room temperature. The sputtered SiO2 thin film on the surface of a black 36°YX-LiTaO3 (B-LT) substrate acted as a guiding layer, effectively reducing the noise and insertion loss. The G-SAWs exhibited enhanced gas response towards acetone gas molecules (800 ppt) in a real-time atmosphere. The high sensitivity of the G-SAW sensor can be attributed to the elasticity and surface roughness of the SiO2 film. In addition, the G-SAW sensor exhibited rapid response and recovery at room temperature. This study provides a potential strategy for diagnosing different stages of diabetes in the human body.

Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.

Background: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized prostate cancer. However, ADT can negatively impact quality of life and there remain no validated predictive models to guide its use. Methods: Digital pathology image and clinical data from pre-treatment prostate tissue from 5,727 patients enrolled on five phase III randomized trials treated with radiotherapy +/- ADT were used to develop and validate an artificial intelligence (AI)-derived predictive model to assess ADT benefit with the primary endpoint of distant metastasis. After the model was locked, validation was performed on NRG/RTOG 9408 (n = 1,594) that randomized men to radiotherapy +/- 4 months of ADT. Fine-Gray regression and restricted mean survival times were used to assess the interaction between treatment and predictive model and within predictive model positive and negative subgroup treatment effects. Results: In the NRG/RTOG 9408 validation cohort (14.9 years of median follow-up), ADT significantly improved time to distant metastasis (subdistribution hazard ratio [sHR] = 0.64, 95%CI [0.45-0.90], p = 0.01). The predictive model-treatment interaction was significant (p-interaction = 0.01). In predictive model positive patients (n = 543, 34%), ADT significantly reduced the risk of distant metastasis compared to radiotherapy alone (sHR = 0.34, 95%CI [0.19-0.63], p < 0.001). There were no significant differences between treatment arms in the predictive model negative subgroup (n = 1,051, 66%; sHR = 0.92, 95%CI [0.59-1.43], p = 0.71). Conclusions: Our data, derived and validated from completed randomized phase III trials, show that an AI-based predictive model was able to identify prostate cancer patients, with predominately intermediate-risk disease, who are likely to benefit from short-term ADT.

Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.

BACKGROUND: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized prostate cancer. However, ADT can negatively impact quality of life, and there remain no validated predictive models to guide its use. METHODS: We used digital pathology images from pretreatment prostate tissue and clinical data from 5727 patients enrolled in five phase 3 randomized trials, in which treatment was radiotherapy with or without ADT, as our data source to develop and validate an artificial intelligence (AI)­derived predictive patient-specific model that would determine which patients would develop the primary end point of distant metastasis. The model used baseline data to provide a binary output that a given patient will likely benefit from ADT or not. After the model was locked, validation was performed using data from NRG Oncology/Radiation Therapy Oncology Group (RTOG) 9408 (n=1594), a trial that randomly assigned men to radiotherapy plus or minus 4 months of ADT. Fine­Gray regression and restricted mean survival times were used to assess the interaction between treatment and the predictive model and within predictive model­positive, i.e., benefited from ADT, and ­negative subgroup treatment effects. RESULTS: Overall, in the NRG/RTOG 9408 validation cohort (14.9 years of median follow-up), ADT significantly improved time to distant metastasis. Of these enrolled patients, 543 (34%) were model positive, and ADT significantly reduced the risk of distant metastasis compared with radiotherapy alone. Of 1051 patients who were model negative, ADT did not provide benefit. CONCLUSIONS: Our AI-based predictive model was able to identify patients with a predominantly intermediate risk for prostate cancer likely to benefit from short-term ADT. (Supported by a grant [U10CA180822] from NRG Oncology Statistical and Data Management Center, a grant [UG1CA189867] from NCI Community Oncology Research Program, a grant [U10CA180868] from NRG Oncology Operations, and a grant [U24CA196067] from NRG Specimen Bank from the National Cancer Institute and by Artera, Inc. ClinicalTrials.gov numbers NCT00767286, NCT00002597, NCT00769548, NCT00005044, and NCT00033631.)

OPN promotes pro-inflammatory cytokine expression via ERK/JNK pathway and M1 macrophage polarization in Rosacea.

Rosacea is a chronic inflammatory dermatosis that involves dysregulation of innate and adaptive immune systems. Osteopontin (OPN) is a phosphorylated glycoprotein produced by a broad range of immune cells such as macrophages, keratinocytes, and T cells. However, the role of OPN in rosacea remains to be elucidated. In this study, it was found that OPN expression was significantly upregulated in rosacea patients and LL37-induced rosacea-like skin inflammation. Transcriptome sequencing results indicated that OPN regulated pro-inflammatory cytokines and promoted macrophage polarization towards M1 phenotype in rosacea-like skin inflammation. In vitro, it was demonstrated that intracellular OPN (iOPN) promoted LL37-induced IL1B production through ERK1/2 and JNK pathways in keratinocytes. Moreover, secreted OPN (sOPN) played an important role in keratinocyte-macrophage crosstalk. In conclusion, sOPN and iOPN were identified as key regulators of the innate immune system and played different roles in the pathogenesis of rosacea.

Comparative study on alleviating effect of kiwi berry (Actinidia arguta) polysaccharide and polyphenol extracts on constipated mice.

Kiwi berry (Actinidia arguta) is beneficial for relieving constipation, but the mechanism of easing constipation is still unknown. The alleviating effects of kiwi berry polysaccharide and polyphenol extracts on loperamide induced constipation were studied. Administration with polysaccharide extract of kiwi berry in loperamide-induced constipation mice distinctly decreased the body weight gain by 124.0%, the number and the water content of feces was decreased by 152.4% and 107.0% respectively, gastrointestinal (GI) transit rate was decreased by 39.5% and the time to the first dark stool was largen by 56.2% as compared with those in the loperamide group, respectively. The levels of excitability neurotransmitters were increased, and the inhibitory neurotransmitter was decreased in the kiwi berry extracts groups compared with the loperamide group. The levels of aquaporins were decreased to ameliorate constipation. Moreover, kiwi berry extracts can protect colon smooth muscle cells from apoptosis and help to restore colon health. Interstitial cells of Cajal (ICC) and animal experiments suggested that kiwi berry extracts can up-regulate the expression levels of stem cell factors (SCF)/c-kit protein. Kiwi berry can remodel the structure of microbial communities. All findings suggest that kiwi berry polysaccharide and polyphenol especially its polysaccharide extract, can effectively alleviate constipation induced by loperamide. Kiwi berry is a promising food supplement that can be used to relieve constipation.

Effect of bovine serum albumin on the stability and antioxidant activity of blueberry anthocyanins during processing and in vitro simulated digestion.

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.

Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset.

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 (AZ) values for malignancy classification on CBIS-DDSM for each technique. We find average AZ 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 < 0.05). These results reinforce recent findings suggesting that representation learning techniques such as BoVW and CNNs are advantageous for mammogram analysis because they do not require lesion segmentation, the quality and specific characteristics of which can vary substantially across datasets. We further observe that segmentation-dependent methods achieve performance levels on CBIS-DDSM inferior to those achieved on the original evaluation datasets reported in the literature. Each of these findings reinforces the need for standardization of datasets, segmentation techniques, and model implementations in performance assessments of automated classifiers for medical imaging.

[Study on expression and mechanism of serum differential proteins after rush immunotherapy of allergic rhinitis].

Objective:To detect the expression of differentially expressed proteins in serum of patients with allergic rhinitis who were allergic to dust mites before and after 6-day rush immunotherapy. The three differentially expressed proteins, CRP, CTHRC1 and WDR89, were detected and identified. The immunoregulatory effects and significance of these three differentially expressed proteins in rush immunotherapy of allergic rhinitis were analyzed and discussed. Method:The serum samples of 15 patients with allergic rhinitis, 15 patients with rush immunotherapy and 10 patients with healthy control group were collected. The samples were studied by isobaric tags for relative and absolute quantitation（iTRAQ） technique. The related differential proteins were determined by two-dimensional gel electrophoresis and mass spectrometry, and the rationality of the screened differential proteins was tested and verified by Cluster3.0 software and Java TreeView software. Finally, the selected CRP, CTHRC1 and WDR89 proteins were identified by enzyme-linked immunosorbent assay（ELISA）. Result:In this study, 893 proteins were detected and 53 differential proteins were identified. Compared with healthy control group, 24 proteins which was statistically significant were found in allergic rhinitis group, which were closely related to the occurrence of allergic rhinitis, including 10 up-regulated proteins and 14 down-regulated proteins. Compared with the allergic rhinitis group, patients with allergic rhinitis underwent 6 days of rush immunotherapy. There were 29 proteins whose expression of proteins with a difference of P value of less than 0.05 and 1.2 times higher, which were related to the effect after the incremental phase of rush immunotherapy was completed, of which 12 were up-regulated and 17 were down-regulated. Compared with healthy control group, the expression of up-regulated of allergic rhinitis group and the expression of down-regulated protein after 6 days of rush immunotherapy were CTHRC1, WDR89; Compared with healthy control group, AR group was down-regulated and the expression of up-regulated protein after 6 days of rush immunotherapy was CRP. CRP, CTHRC1 and WDR89 proteins were identified by enzyme linked immunosorbent assay（ELISA）, and it was found that the differential expression of CTHRC1 and WDR89 in AR and RIT was statistically significant（P<0.05）, but the differential expression of serum CRP in AR and RIT was not statistically significant（P>0.05）. Conclusion:Serum protein CTHRC1 and WDR89 are closely related to the pathogenesis of allergic rhinitis, and played a role in the regulation of rush immunotherapy, while serum protein CRP has no significant effect on AR and RIT.

Effects of lentivirus-mediated CCR3 RNA interference on the function of mast cells of allergic rhinitis in mice.

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.

The effects of ethoxyquin and Angelica sinensis extracts on lipid oxidation in fish feeds and growth, digestive and absorptive capacities and antioxidant status in juvenile red carp (Cyprinus carpio var. xingguonensis): a comparative study.

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.