Gastric Section Correlation Network for Gastric Precancerous Lesion Diagnosis.

Goal: Diagnosing the corpus-predominant gastritis index (CGI) which is an early precancerous lesion in the stomach has been shown its effectiveness in identifying high gastric cancer risk patients for preventive healthcare. However, invasive biopsies and time-consuming pathological analysis are required for the CGI diagnosis. Methods: We propose a novel gastric section correlation network (GSCNet) for the CGI diagnosis from endoscopic images of three dominant gastric sections, the antrum, body and cardia. The proposed network consists of two dominant modules including the scaling feature fusion module and section correlation module. The front one aims to extract scaling fusion features which can effectively represent the mucosa under variant viewing angles and scale changes for each gastric section. The latter one aims to apply the medical prior knowledge with three section correlation losses to model the correlations of different gastric sections for the CGI diagnosis. Results: The proposed method outperforms competing deep learning methods and achieves high testing accuracy, sensitivity, and specificity of 0.957, 0.938 and 0.962, respectively. Conclusions: The proposed method is the first method to identify high gastric cancer risk patients with CGI from endoscopic images without invasive biopsies and time-consuming pathological analysis.

Effect of short-term exposure to air pollution on hospital admission for cardiovascular disease: A time-series study in Xiangyang, China.

BACKGROUND: Data on the relationship between short-term exposure to air pollution and cardiovascular diseases (CVDs) and the potential modifying factors are limited and inconsistent. OBJECTIVE: To explore the relationship between short-term exposure to air pollution and CVD risk, and potential modification effect factors. METHOD: A time series study was conducted on 52,991 hospital admissions for CVD from 2015 to 2019 in Xiangyang City, China. Air pollution data from four national fixed monitoring stations were collected to estimate exposure level in Xiangyang City. A quasi-Poisson generalized additive model incorporating a distributed lag nonlinear model was applied to evaluate the association between air pollution and CVD risk. The potential modification effect of sex, age, and season on the above associations was also evaluated. RESULTS: CVD risk was positively associated with air pollution. Peak associations in single lag day structures were observed for particulate matter ≤10 µm in aerodynamic (PM10; RR: 1.040, 95 % CI: 0.996-1.087), PM2.5 (1.025, 1.004-1.045), nitrogen dioxide (NO2; 1.074, 1.039-1.111), and sulfur dioxide (SO2; 1.079, 1.019-1.141) at Lag 0 and ozone (O3; 1.018, 1.004-1.031) at Lag 4. In cumulative lag day structures, the highest RRs were 1.225 (1.079,1.392) for PM10 at Lag 06, 1.054 (1.013, 1.098) for PM2.5 at Lag 03, 1.200 (1.119, 1.287) for NO2 at Lag 04, and 1.135 (1.025, 1.257) for SO2 at Lag 02. Moreover, the association between air pollution and CVD risk was modified by sex and age (P < 0.05). Females and individuals aged ≤65 years were more vulnerable to NO2 and had a higher CVD risk. CONCLUSION: Short-term exposure to air pollution was positively associated with CVD risk. Moreover, sex and age could modify the effect of air pollution on CVD risk. Females and individuals aged ≤65 years had a higher NO2 exposure-induced CVD risk.

Development and Validation of a 3D Resnet Model for Prediction of Lymph Node Metastasis in Head and Neck Cancer Patients.

The accurate diagnosis and staging of lymph node metastasis (LNM) are crucial for determining the optimal treatment strategy for head and neck cancer patients. We aimed to develop a 3D Resnet model and investigate its prediction value in detecting LNM. This study enrolled 156 head and neck cancer patients and analyzed 342 lymph nodes segmented from surgical pathologic reports. The patients' clinical and pathological data related to the primary tumor site and clinical and pathology T and N stages were collected. To predict LNM, we developed a dual-pathway 3D Resnet model incorporating two Resnet models with different depths to extract features from the input data. To assess the model's performance, we compared its predictions with those of radiologists in a test dataset comprising 38 patients. The study found that the dimensions and volume of LNM + were significantly larger than those of LNM-. Specifically, the Y and Z dimensions showed the highest sensitivity of 84.6% and specificity of 72.2%, respectively, in predicting LNM + . The analysis of various variations of the proposed 3D Resnet model demonstrated that Dual-3D-Resnet models with a depth of 34 achieved the highest AUC values of 0.9294. In the validation test of 38 patients and 86 lymph nodes dataset, the 3D Resnet model outperformed both physical examination and radiologists in terms of sensitivity (80.8% compared to 50.0% and 91.7%, respectively), specificity(90.0% compared to 88.5% and 65.4%, respectively), and positive predictive value (77.8% compared to 66.7% and 55.0%, respectively) in detecting individual LNM + . These results suggest that the 3D Resnet model can be valuable for accurately identifying LNM + in head and neck cancer patients. A prospective trial is needed to evaluate further the role of the 3D Resnet model in determining LNM + in head and neck cancer patients and its impact on treatment strategies and patient outcomes.

Cross-Scale Fusion Transformer for Histopathological Image Classification.

Histopathological images provide the medical evidences to help the disease diagnosis. However, pathologists are not always available or are overloaded by work. Moreover, the variations of pathological images with respect to different organs, cell sizes and magnification factors lead to the difficulty of developing a general method to solve the histopathological image classification problems. To address these issues, we propose a novel cross-scale fusion (CSF) transformer which consists of the multiple field-of-view patch embedding module, the transformer encoders and the cross-fusion modules. Based on the proposed modules, the CSF transformer can effectively integrate patch embeddings of different field-of-views to learn cross-scale contextual correlations, which represent tissues and cells of different sizes and magnification factors, with less memory usage and computation compared with the state-of-the-art transformers. To verify the generalization ability of the CSF transformer, experiments are performed on four public datasets of different organs and magnification factors. The CSF transformer outperforms the state-of-the-art task specific methods, convolutional neural network-based methods and transformer-based methods. The source code will be available in our GitHub https://github.com/nchucvml/CSFT.

Solar ultraviolet B radiation promotes α-MSH secretion to attenuate the function of ILC2s via the pituitary-lung axis.

The immunomodulatory effects of ultraviolet B (UVB) radiation in human diseases have been described. Whether type 2 lung inflammation is directly affected by solar ultraviolet (UV) radiation is not fully understood. Here, we show a possible negative correlation between solar UVB radiation and asthmatic inflammation in humans and mice. UVB exposure to the eyes induces hypothalamus-pituitary activation and α-melanocyte-stimulating hormone (α-MSH) accumulation in the serum to suppress allergic airway inflammation by targeting group 2 innate lymphoid cells (ILC2) through the MC5R receptor in mice. The α-MSH/MC5R interaction limits ILC2 function through attenuation of JAK/STAT and NF-κB signaling. Consistently, we observe that the plasma α-MSH concentration is negatively correlated with the number and function of ILC2s in the peripheral blood mononuclear cells (PBMC) of patients with asthma. We provide insights into how solar UVB radiation-driven neuroendocrine α-MSH restricts ILC2-mediated lung inflammation and offer a possible strategy for controlling allergic diseases.

Multiple Field-of-View Based Attention Driven Network for Weakly Supervised Common Bile Duct Stone Detection.

OBJECTIVE: Common bile duct (CBD) stones caused diseases are life-threatening. Because CBD stones locate in the distal part of the CBD and have relatively small sizes, detecting CBD stones from CT scans is a challenging issue in the medical domain. METHODS AND PROCEDURES: We propose a deep learning based weakly-supervised method called multiple field-of-view based attention driven network (MFADNet) to detect CBD stones from CT scans based on image-level labels. Three dominant modules including a multiple field-of-view encoder, an attention driven decoder and a classification network are collaborated in the network. The encoder learns the feature of multi-scale contextual information while the decoder with the classification network is applied to locate the CBD stones based on spatial-channel attentions. To drive the learning of the whole network in a weakly-supervised and end-to-end trainable manner, four losses including the foreground loss, background loss, consistency loss and classification loss are proposed. RESULTS: Compared with state-of-the-art weakly-supervised methods in the experiments, the proposed method can accurately classify and locate CBD stones based on the quantitative and qualitative results. CONCLUSION: We propose a novel multiple field-of-view based attention driven network for a new medical application of CBD stone detection from CT scans while only image-levels are required to reduce the burdens of labeling and help physicians automatically diagnose CBD stones. The source code is available at https://github.com/nchucvml/MFADNet after acceptance. CLINICAL IMPACT: Our deep learning method can help physicians localize relatively small CBD stones for effectively diagnosing CBD stone caused diseases.

Video Summarization With Spatiotemporal Vision Transformer.

Video summarization aims to generate a compact summary of the original video for efficient video browsing. To provide video summaries which are consistent with the human perception and contain important content, supervised learning-based video summarization methods are proposed. These methods aim to learn important content based on continuous frame information of human-created summaries. However, simultaneously considering both of inter-frame correlations among non-adjacent frames and intra-frame attention which attracts the humans for frame importance representations are rarely discussed in recent methods. To address these issues, we propose a novel transformer-based method named spatiotemporal vision transformer (STVT) for video summarization. The STVT is composed of three dominant components including the embedded sequence module, temporal inter-frame attention (TIA) encoder, and spatial intra-frame attention (SIA) encoder. The embedded sequence module generates the embedded sequence by fusing the frame embedding, index embedding and segment class embedding to represent the frames. The temporal inter-frame correlations among non-adjacent frames are learned by the TIA encoder with the multi-head self-attention scheme. Then, the spatial intra-frame attention of each frame is learned by the SIA encoder. Finally, a multi-frame loss is computed to drive the learning of the network in an end-to-end trainable manner. By simultaneously using both inter-frame and intra-frame information, our method outperforms state-of-the-art methods in both of the SumMe and TVSum datasets. The source code of the spatiotemporal vision transformer will be available at https://github.com/nchucvml/STVT.

Respiratory microbiota and radiomics features in the stable COPD patients.

BACKGROUNDS: The respiratory microbiota and radiomics correlate with the disease severity and prognosis of chronic obstructive pulmonary disease (COPD). We aim to characterize the respiratory microbiota and radiomics features of COPD patients and explore the relationship between them. METHODS: Sputa from stable COPD patients were collected for bacterial 16 S rRNA gene sequencing and fungal Internal Transcribed Spacer (ITS) sequencing. Chest computed tomography (CT) and 3D-CT analysis were conducted for radiomics information, including the percentages of low attenuation area below - 950 Hounsfield Units (LAA%), wall thickness (WT), and intraluminal area (Ai). WT and Ai were adjusted by body surface area (BSA) to WT/[Formula: see text] and Ai/BSA, respectively. Some key pulmonary function indicators were collected, which included forced expiratory volume in one second (FEV1), forced vital capacity (FVC), diffusion lung carbon monoxide (DLco). Differences and correlations of microbiomics with radiomics and clinical indicators between different patient subgroups were assessed. RESULTS: Two bacterial clusters dominated by Streptococcus and Rothia were identified. Chao and Shannon indices were higher in the Streptococcus cluster than that in the Rothia cluster. Principal Co-ordinates Analysis (PCoA) indicated significant differences between their community structures. Higher relative abundance of Actinobacteria was detected in the Rothia cluster. Some genera were more common in the Streptococcus cluster, mainly including Leptotrichia, Oribacterium, Peptostreptococcus. Peptostreptococcus was positively correlated with DLco per unit of alveolar volume as a percentage of predicted value (DLco/VA%pred). The patients with past-year exacerbations were more in the Streptococcus cluster. Fungal analysis revealed two clusters dominated by Aspergillus and Candida. Chao and Shannon indices of the Aspergillus cluster were higher than that in the Candida cluster. PCoA showed distinct community compositions between the two clusters. Greater abundance of Cladosporium and Penicillium was found in the Aspergillus cluster. The patients of the Candida cluster had upper FEV1 and FEV1/FVC levels. In radiomics, the patients of the Rothia cluster had higher LAA% and WT/[Formula: see text] than those of the Streptococcus cluster. Haemophilus, Neisseria and Cutaneotrichosporon positively correlated with Ai/BSA, but Cladosporium negatively correlated with Ai/BSA. CONCLUSIONS: Among respiratory microbiota in stable COPD patients, Streptococcus dominance was associated with an increased risk of exacerbation, and Rothia dominance was relevant to worse emphysema and airway lesions. Peptostreptococcus, Haemophilus, Neisseria and Cutaneotrichosporon probably affected COPD progression and potentially could be disease prediction biomarkers.

ADMM-SRNet: Alternating Direction Method of Multipliers Based Sparse Representation Network for One-Class Classification.

One-class classification aims to learn one-class models from only in-class training samples. Because of lacking out-of-class samples during training, most conventional deep learning based methods suffer from the feature collapse problem. In contrast, contrastive learning based methods can learn features from only in-class samples but are hard to be end-to-end trained with one-class models. To address the aforementioned problems, we propose alternating direction method of multipliers based sparse representation network (ADMM-SRNet). ADMM-SRNet contains the heterogeneous contrastive feature (HCF) network and the sparse dictionary (SD) network. The HCF network learns in-class heterogeneous contrastive features by using contrastive learning with heterogeneous augmentations. Then, the SD network models the distributions of the in-class training samples by using dictionaries computed based on ADMM. By coupling the HCF network, SD network and the proposed loss functions, our method can effectively learn discriminative features and one-class models of the in-class training samples in an end-to-end trainable manner. Experimental results show that the proposed method outperforms state-of-the-art methods on CIFAR-10, CIFAR-100 and ImageNet-30 datasets under one-class classification settings. Code is available at https://github.com/nchucvml/ADMM-SRNet.

The effects of external diaphragmatic pacing on diaphragm function and weaning outcomes of critically ill patients with mechanical ventilation: a prospective randomized study.

Background: Diaphragmatic pacing can improve diaphragm function, which is beneficial for the prognosis of patients treated with prolonged mechanical ventilation (MV). While most previous studies have focused on the role of implanted diaphragm pacing (IDP), our study is the first to examine the effects of external diaphragmatic pacing (EDP) in mechanically ventilated patients. Specifically, the effect of EDP on diaphragm function, the success rate of weaning, the duration of MV (DMV), and the intensive care unit (ICU) length of stay (ILOS) were assessed. Methods: From September 2019 to December 2020, a total of 51 mechanically ventilated patients in the ICU of the Sun Yat-sen Memorial Hospital, Sun Yat-sen University were enrolled and randomly divided into an EDP group of 27 patients and a control group of 24 patients. The control group received routine treatment, and the EDP group received EDP treatment in addition to routine treatment. The diaphragm excursion (DE), diaphragm thickening fraction (DTF), DMV, ILOS, and average survival time were recorded to evaluate efficacy. Results: Patients treated with EDP had increased DE [exp(B) =1.86, 95% CI: 1.39 to 2.50, P<0.001] and DTF [exp(B) =1.35, 95% CI: 1.05 to 1.76, P=0.022], shortened weaning time (P=0.026) and prolonged average survival time (P<0.001) compared to patients who did not receive EDP therapy. Especially in cases with difficult weaning, the improvement of DE and DTF in the EDP treatment group was more obvious than that in the control group (P=0.013 and P=0.032). Moreover, the DTF upon attempted spontaneous breathing trial (SBT) was negatively correlated with the fraction of inspired oxygen (FiO2) [r=-0.54; 95% confidence interval (CI): -0.77 to -0.19; P=0.004], the arterial partial pressure of oxygen (PaO2) (r=-0.58; 95% CI: -0.79 to -0.25; P=0.001), the PaO2/FiO2 ratio (r=-0.52; 95% CI: -0.75 to -0.16; P=0.006), and the serum lactate concentration (Lac) (r=-0.39; 95% CI: -0.68 to 0.003; P=0.046). Conclusions: EDP treatment can effectively reduce the DMV and prolong the average survival time of mechanically ventilated patients. Trial Registration: Chinese Clinical Trial Registry ChiCTR1900024096.

Clinical and imaging findings of patients diagnosed with adenovirus-positive pneumonia during 2015-2019 in Shanghai, China.

BACKGROUND: This study was to describe the clinical characteristics, chest CT image findings, and potential role of T cells immunity in adenovirus positive pneumonia. METHODS: In this retrospective study, medical records of 53 adult Adv+ patients who were admitted to the Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, from May 2015 to August 2019 were included. The presence of adenovirus and other respiratory viruses was detected using polymerase chain reaction of throat swabs samples. Clinical features and chest computed tomography (CT) findings were compared between patients with Adv+ pneumonia and Adv+ non-pneumonia. RESULTS: The top 3 most commonly occurring symptoms in Adv+ pneumonia patients were fever (66.7%), cough (63.3%), and tachypnea (16.7%). Patients with Adv+ pneumonia showed significantly higher rates of cough and fever and longer duration of hospitalization than patients with Adv+ non-pneumonia. In the Adv+ pneumonia group, consolidation (73.3%) was the most common imaging finding on chest CT scan, and the likelihood of involvement of bilateral lobes (60%) was high. Classical conspicuous consolidation with surrounding ground-glass opacity was observed in 5 (16.6%) patients with Adv+ pneumonia. Patients with Adv+ pneumonia showed a higher inhibition of T-cell immunity than did patients with Adv+ non-pneumonia, and counts of CD3+, CD4+, and CD8+ T-cells may predict the presence of pneumonia in Adv+ patients. DISCUSSION: With regard to Adv+ pneumonia, the most frequent symptoms were cough and fever, and the most common CT pattern was consolidation; classical CT findings such as consolidation with surrounding ground-glass opacity could also be observed. Furthermore, our data indicated the incidence of abrogated cellular immunity in patients with Adv+ pneumonia.

Anabolic-androgenic steroids for patients with chronic obstructive pulmonary disease: A systematic review and meta-analysis.

Background: Testosterone deficiency is common in chronic obstructive pulmonary disease (COPD) patients. There has been a growing interest in the potential use of anabolic-androgenic steroids (AASs) in patients with COPD recently. However, whether AASs could improve their clinical outcomes remains unknown. Methods: In order to explore the efficacy of AASs in patients with COPD, systematic search of MEDLINE, Embase, the Cochrane Library and ClinicalTrials.gov for randomized controlled trials (RCTs) of AASs for COPD published before March 17, 2022 was performed. Results: Data were extracted from 8 articles involving 520 participants. The median number of participants per study was 39.5 and the mean follow up was 14.2 weeks. As compared to the control group, AASs therapy could significantly improve body weight (weighted mean difference (WMD), 1.38 kg; 95% CI, 0.79 to 1.97 kg), fat-free mass (WMD, 1.56 kg; 95% CI, 0.94 to 2.18 kg) and peak workload (WMD, 6.89W; 95% CI, 3.97 to 9.81W) of COPD patients, but no improvements in spirometry indicators and six-minute walking distances (WMD, 16.88 m; 95%, -3.27 to 37.04 m). Based on the available research data, it is uncertain whether AASs treatment could improve the quality of life of COPD patients. Conclusions: Limited published evidence indicates that AASs therapy provides clinical benefits in patients with COPD. However, longer and larger studies are needed to better clarify the efficacy of AASs and draw final conclusions.

Detection of Carbohydrate Antigen 50 Based on a Novel Miniaturized Chemiluminescence Analyzer Enables Large-Scale Cancer Early Screening in Grassroots Community.

Early screening of cancer can effectively prolong survival time and reduce cancer mortality. However, the existing health-monitoring devices can only be carried out in professional laboratories, so large-scale early cancer screening in resource-limited settings is hardly achieved. To embrace the challenge, we developed a novel chemiluminescence immunoassay (CLIA) analyzer that does not require a professional operation. Then, it was applied to detect carbohydrate antigen 50 (CA50), a non-organ-specific tumor marker for screening various cancers. As a result, the analyzer exhibited excellent performance that the total assay time was only 15 min, and the detection limit reached 0.057 U ml-1. A coefficient of variance (CV) less than 15% was well-controlled for both intra- and inter-assay precision, and the linear range was 0-500 U ml-1. More importantly, this analyzer can continuously detect 60 samples per hour without any professional paramedic. Finally, this analyzer has been applied to evaluate clinical samples and the detected results showed a good correlation with the clinical test results (correlation coefficient, 0.9958). These characteristics exactly meet large-scale and high-throughput early screening of cancer. Thus, this miniaturized analyzer for CA50 detection is promising to achieve early large-scale screening of cancer in the resource-limited grassroots community.

Effect of inhaled corticosteroids on microbiome and microbial correlations in asthma over a 9-month period.

The effect of inhaled corticosteroids (ICS) on the airway microbiome requires longitudinal research for corroboration. Asthma patients, not undergoing ICS treatment (baseline), were enrolled and prescribed ICS; all these patients were followed up with regular visits at 3 months (visit 1) and 9 months (visit 2). Induced sputum was collected, and fungal microbiota (mycobiome) and bacterial microbiota (bacteriome) were estimated using 16S rRNA and internal transcribed spacer (ITS) sequencing. Bacterial α diversity indices were not significantly different between baseline, visit 1, and visit 2. Visit 1 showed lower fungal evenness than the baseline, and visit 2 showed lower fungal diversity and evenness than the baseline. Fungal, but not bacterial, community compositions differed significantly between the baseline, visit 1, and visit 2. The most abundant bacterial phyla and genera did not differ significantly between the baseline, visit 1, and visit 2. Compared with the baseline, visit 1 showed significantly increased frequency of the fungal phylum Ascomycota and lower frequency of Basidiomycota. We found sharply decreased fungal genera Wallemia, Cladosporium, Penicillium, and Alternaria at visit 1 and visit 2 compared with the baseline, although the differences were not statistically significant. We also found the proportion of Basidiomycota was positively correlated with percentages of sputum eosinophils and neutrophils. The proportions of Saccharomyces, Wallemia, and Aplosporella were positively correlated with percentage of sputum eosinophils. Moreover, we identified distinct inter- and intra-kingdom interactions in baseline, visit 1, and visit 2. Therefore, ICS use altered the airway microbial diversity, evenness, community composition, and microbial connections.

Prevalence and associated factors of frailty among Southern Chinese Han patients on haemodialysis: a multicentre, observational cross-sectional study.

OBJECTIVES: Frailty has been extensively studied in the general population. However, there is little information on frailty among patients undergoing haemodialysis (HD) in China. This study analysed the prevalence and associated factors of frailty among Southern Chinese Han patients on HD. DESIGN: Observational cross-sectional study. SETTING: Three HD centres in Southern China. PARTICIPANTS: Three hundred patients who underwent regular HD between June 2019 and October 2019. MAIN OUTCOMES AND MEASURES: Frailty was assessed using the Tilburg indicator of frailty (TFI) questionnaire, and the psychological status of the respondents was evaluated by the Self-Rating Depression Scale (SDS) and the Self-Rating Anxiety Scale (SAS). RESULTS: Seventy-five per cent of participants were in the frailty group, and the TFI score of HD patients was 6.89±2.87, with 8.15±2.06 in the frailty group and 2.87±1.31 in the non-frailty group. Frailty patients had higher SDS and SAS scores, and were more likely to suffer depression and anxiety than non-frailty patients. Multivariate logistic regression analysis excluding depression and anxiety showed that age, Charlson Comorbidity Index (excluding end-stage renal disease), a nuclear family (compared with living alone), and albumin were independently associated with frailty (all p<0.05). In the model including depression and anxiety, age, diabetes mellitus, living as a couple (compared with living alone), a nuclear family (compared with living alone), an extended family (compared with living alone), low phosphorus, depression and anxiety were associated with frailty by multivariate logistic regression analysis (all p<0.05). CONCLUSIONS: Approximately three-quarters of patients with HD in Southern China are frail, often accompanied with depression and anxiety. Age, diabetes mellitus, family structure, phosphorus, depression and anxiety were associated with frailty.

Semantic Context-Aware Image Style Transfer.

To provide semantic image style transfer results which are consistent with human perception, transferring styles of semantic regions of the style image to their corresponding semantic regions of the content image is necessary. However, when the object categories between the content and style images are not the same, it is difficult to match semantic regions between two images for semantic image style transfer. To solve the semantic matching problem and guide the semantic image style transfer based on matched regions, we propose a novel semantic context-aware image style transfer method by performing semantic context matching followed by a hierarchical local-to-global network architecture. The semantic context matching aims to obtain the corresponding regions between the content and style images by using context correlations of different object categories. Based on the matching results, we retrieve semantic context pairs where each pair is composed of two semantically matched regions from the content and style images. To achieve semantic context-aware style transfer, a hierarchical local-to-global network architecture, which contains two sub-networks including the local context network and the global context network, is proposed. The former focuses on style transfer for each semantic context pair from the style image to the content image, and generates a local style transfer image storing the detailed style feature representations for corresponding semantic regions. The latter aims to derive the stylized image by considering the content, the style, and the intermediate local style transfer images, so that inconsistency between different corresponding semantic regions can be addressed and solved. The experimental results show that the stylized results using our method are more consistent with human perception compared with the state-of-the-art methods.

The effect of short-chain fatty acids on M2 macrophages polarization in vitro and in vivo.

Alternatively activated macrophages (M2 polarization) play an important role in asthma. Short-chain fatty acids (SCFAs) possessed immune-regulatory functions, but their effects on M2 polarization of alveolar macrophages and its underlying mechanisms are still unclear. In our study, murine alveolar macrophage MH-S cell line and human monocyte-derived macrophages were used to polarize to M2 subset with interleukin-4 (IL-4) treatment. The underlying mechanisms involved were investigated using molecule inhibitors/agonists. In vivo, female C57BL/6 mice were divided into five groups: CON group, ovalbumin (OVA) asthma group, OVA+Acetate group, OVA+Butyrate group, and OVA+Propionate group. Mice were fed with or without SCFAs (Acetate, Butyrate, Propionate) in drinking water for 20 days before developing OVA-induced asthma model. In MH-S, SCFAs inhibited IL-4-incuced protein or mRNA expressions of M2-associated genes in a dose-dependent manner. G-protein-coupled receptor 43 (GPR43) agonist 4-CMTB and histone deacetylase (HDAC) inhibitor (trichostatin A, TSA), but not GPR41 agonist AR420626 could inhibit the protein or mRNA expressions M2-associated genes. 4-CMTB, but not TSA, had no synergistic role in the inhibitory effect of SCFAs on M2 polarization. In vivo study indicated Butyrate and Propionate, but not Acetate, attenuated OVA-induced M2 polarization in the lung and airway inflammation. We also found the inhibitory effect of SCFAs on M2 polarization in human-derived macrophages. Therefore, SCFAs inhibited M2 polarization in MH-S likely through GPR43 activation and/or HDAC inhibition. Butyrate and Propionate but not Acetate could inhibit M2 polarization and airway inflammation in asthma model. SCFAs also abrogated M2 polarization in human-derived macrophages.

Thrombin cleaves IL-33 and modulates IL-33-activated allergic lung inflammation.

BACKGROUND: Organisms have orchestrated coagulation and immune systems. Although a link between inflammation and haemostasis has been reported in asthma, the interaction mechanism has not been completely elucidated. Here, we investigated the direct link between the mammalian immune and coagulation systems. METHODS: Mice were administered protease or antigens intranasally to induce airway inflammation with or without thrombin inhibitors treatment. The effects of thrombin and its inhibitors on interleukin (IL)-33 were investigated both in vivo and in vitro. Peripheral blood mononuclear cells (PBMCs) and plasma from asthma patients are collected to verify the correlation between thrombin and group 2 innate lymphocytes (ILC2s). RESULTS: Low-molecular-weight heparin (LMWH, an indirect inhibitor of thrombin) restrained both papain- and fungus-induced type 2 immune responses in mice by inhibiting IL-33 cleavage. Upon examining the potential thrombin protease consensus sites, we found that IL-33 was directly cleaved by thrombin at specific amino acids (R48 and R106) to generate a mature form of IL-33 with potent biological activity. In addition, we found that bivalirudin TFA (a direct inhibitor of thrombin) inhibited a variety of type 2 inflammatory responses, such as those in house dust mite (HDM)- and ovalbumin (OVA)-mediated pulmonary inflammation models. We found that plasma thrombin-antithrombin complex (TATc) levels in asthma patients were positively associated with the number and function of IL-33-responder group 2 innate lymphocytes (ILC2s) among peripheral blood mononuclear cells (PBMCs) from asthma patients. CONCLUSION: The data suggested that thrombin inhibitors administration could be effective in treating lung inflammation by regulating ILC2s via IL-33 maturation, indicating that targeting thrombin is a potential way to treat allergic diseases.

High-throughput sequencing reveals omnivorous and preferential diets of the rotifer Polyarthra in situ.

Knowledge of in situ diet of widespread rotifers is crucial for accurately understanding the trophic position, ecological function, and adaptability to environmental changes in aquatic ecosystems. However, it is challenging to achieve the in situ diet information due to the lack of efficient and comprehensive methods. Here, we investigated the diet composition of Polyarthra in a subtropical lake using high-throughput sequencing (HTS) of a rRNA metabarcode for Polyarthra and ambient water samples. After eliminating Polyarthra sequences, a total of 159 operational taxonomic units (OTUs) from taxa in 15 phyla were detected from Polyarthra gut content samples. Most of the OTUs belong to Chlorophyta, followed by unclassified Fungi, Chrysophyta, Dinoflagellata, Ciliophora, Bacillariophyta, Cryptophyta, Arthropoda, Cercozoa, Mollusca, Apicomplexa, Haptophyta, Amoebozoa, Chordata and other eukaryotes. Our results showed that Polyarthra mainly grazed on Chlorophyta, which may result from the high relative abundance of Chlorophyta in ambient waters. In contrast, Chrysophyceae and Synurophyceae were enriched in Polyarthra's gut, indicating that this rotifer prefers these taxa as food. Moreover, correlation analysis showed that total nitrogen, transparency, depth, Chlorophyll-a and total phosphorus were key factors for the variation of the eukaryotic community in the Polyarthra gut contents. When the concentration of nutrients in the water environment decreased, Polyarthra shifted from herbivorous feeding to more carnivorous feeding. Thus, Polyarthra is generally omnivorous but preference for Chrysophytes and Synurophytes, and it responds to the environmental changes by adopting a flexible feeding strategy. This could partly explain why the widespread rotifers have apparently wide tolerance toward spatial and environmental changes.