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It is well established that increased programmed cell death protein 1 (PD-1)+C-X-C chemokine receptor type 5 (CXCR5)- CD4+T cells are found in patients with rheumatoid arthritis (RA). T cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT) is a co-inhibitory receptor that is expressed on T cells. However, the expression patterns and immunomodulatory roles of TIGIT on PD1+CXCR5-CD4+T cells in RA are poorly understood. Patients with RA were recruited and their clinical characteristics were recorded. The expression level of TIGIT on PD-1+CXCR5-CD4+T cells was examined using flow cytometry. Subsequently, the correlation between various parameters of TIGIT+PD-1+CXCR5-CD4+T cells [percentage of the cells, mean fluorescence intensity (MFI) of PD-1 and TIGIT in the cells] in patients with RA and clinical data, including autoantibodies, inflammatory indicators and RA activity, were analyzed. In addition, the risk factors of RA were assessed using univariate and multivariate regression analyses. The percentages of TIGIT+CXCR5-CD4+T, PD-1+CXCR5-CD4+T, TIGIT+PD-1+CXCR5-CD4+T, TIGIT-PD-1+CXCR5-CD4+T cells, the MFI of PD-1 in these cells and the MFI of TIGIT in TIGIT+PD-1+CXCR5-CD4+T cells were revealed to be significantly increased in patients with RA compared with those in healthy individuals. The parameters of TIGIT+PD-1+CXCR5-CD4+T cells (percentage and/or MFI of PD-1) in patients with RA were found to be associated with the levels of anti-cyclic citrullinated peptide antibodies, rheumatoid factor and inflammatory markers, such as lymphocyte count, lymphocyte percentage, neutrophil percentage, lymphocyte-to-monocyte ratio, neutrophil-to-lymphocyte ratio, systemic immune inflammation index, derived neutrophil-to-lymphocyte ratio, erythrocyte sedimentation rate and C-reactive protein. In addition, the MFI of PD-1 in TIGIT+PD-1+CXCR5-CD4+T cells was associated with a disease activity score of 28 and the patient visual analogue scale. Multivariate logistic regression analysis demonstrated that the percentage of TIGIT+PD-1+CXCR5-CD4+T cells and the MFI of PD-1 in TIGIT+PD-1+CXCR5-CD4+T cells were risk factors for RA. The present study suggests that the increase in TIGIT+PD-1+CXCR5-CD4+T cells is associated with the production of autoantibodies and RA activity and may serve a role in RA pathogenesis.
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This study has focused on determining the association of m6A methyltransferase [methyltransferase-like 3 (METTL3), methyltransferase-like 14 (METTL14), and Wilms tumor 1-associating protein (WTAP)], demethylase [fat mass and obesity-associated protein (FTO) and alkylation repair homolog protein 5 (ALKBH5)], RNA-binding proteins [YT521-B homology domains 2 (YTHDF2)], and ankylosing spondylitis (AS). A total of 154 specimens, containing 79 patients with new-onset AS and 75 healthy controls (HCs), participated in the study. The mRNA expressions of these m6A methyltransferase, demethylase, and RNA-binding protein in peripheral blood mononuclear cells (PBMCs) were detected by quantitative real-time PCR (qRT-PCR). The data showed that the mRNA expressions of YTHDF2 and ALKBH5 in PBMC from patients with new-onset AS were significantly decreased, and there was a positive correlation between RNA-binding proteins (YTHDF2) and demethylase (ALKBH5) in patients with new-onset AS. Logistic regression analysis demonstrated that the expression of YTHDF2 mRNA in PBMC is a risk factor of AS. Receiver operating characteristic (ROC) analysis of the area under the curve (AUC) for mRNA YTHDF2 in new-onset AS and HC was 0.692, with a cutoff value of <0.8724, a sensitivity of 67%, and a specificity of 63%. Moreover, we constructed a novel predictive model based on a combination of mRNA YTHDF2 and systemic immune-inflammation index (SII) for AS diagnosis (AUC = 0.865, sensitivity = 79.45%, specificity = 84.00%), and the predictive model correlated with the activity and severity of AS. This study indicates that the mRNA expression of YTHDF2 in PBMC may be involved in AS pathogenesis and a predictive model based on a combination of mRNA YTHDF2 and SII acts as a marker for diagnosis and progression of diseases.
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This study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, to mitigate feature ambiguity in bone fracture detection on radiographs of various body parts. A total of 9040 radiographic studies were extracted. These images were classified into several body part types including 1651 hand, 1302 wrist, 406 elbow, 696 shoulder, 1580 pelvic, 948 knee, 1180 ankle, and 1277 foot images. Instance segmentation was annotated by radiologists. The ResNext-101+FPN was employed as the baseline network structure and the FAMO model for processing. The proposed FAMO model and other ablative models were tested on a test set of 20% total radiographs in a balanced body part distribution. To the per-fracture extent, an AP (average precision) analysis was performed. For per-image and per-case, the sensitivity, specificity, and AUC (area under the receiver operating characteristic curve) were analyzed. At the per-fracture level, the controlled experiment set the baseline AP to 76.8% (95% CI: 76.1%, 77.4%), and the major experiment using FAMO as a preprocessor improved the AP to 77.4% (95% CI: 76.6%, 78.2%). At the per-image level, the sensitivity, specificity, and AUC were 61.9% (95% CI: 58.7%, 65.0%), 91.5% (95% CI: 89.5%, 93.3%), and 74.9% (95% CI: 74.1%, 75.7%), respectively, for the controlled experiment, and 64.5% (95% CI: 61.3%, 67.5%), 92.9% (95% CI: 91.0%, 94.5%), and 77.5% (95% CI: 76.5%, 78.5%), respectively, for the experiment with FAMO. At the per-case level, the sensitivity, specificity, and AUC were 74.9% (95% CI: 70.6%, 78.7%), 91.7%% (95% CI: 88.8%, 93.9%), and 85.7% (95% CI: 84.8%, 86.5%), respectively, for the controlled experiment, and 77.5% (95% CI: 73.3%, 81.1%), 93.4% (95% CI: 90.7%, 95.4%), and 86.5% (95% CI: 85.6%, 87.4%), respectively, for the experiment with FAMO. In conclusion, in bone fracture detection, FAMO is an effective preprocessor to enhance model performance by mitigating feature ambiguity in the network.
Assuntos
Fraturas Ósseas/diagnóstico por imagem , Redes Neurais de Computação , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Área Sob a Curva , Cotovelo/diagnóstico por imagem , Humanos , Curva ROC , Ombro/diagnóstico por imagem , Punho/diagnóstico por imagem , Raios XRESUMO
Life cycle assessment methodology was used to quantify the environmental impacts and resource use of milk production on the North China Plain, the largest milk production area in China. Variation in environmental burden caused by cow productivity was evaluated, as well as scenario analysis of the effects of improvement practices. The results indicated that the average environmental impact potential and resource use for producing 1kg of fat and protein corrected milk was 1.34kgCO2eq., 9.27gPO43-eq., 19.5gSO2eq., 4.91MJ, 1.83m2 and 266L for global warming potential (GWP), eutrophication potential (EP), acidification potential (AP), non-renewable energy use (NREU), land use (LU) and blue water use (BWU; i.e. water withdrawal), respectively. Feed production was a significant determinant of GWP, NREU, LU and BWU, while AP and EP were mainly affected by manure management. Scenario analysis showed that reducing use of concentrates and substituting with alfalfa hay decreased GWP, EP, AP, NREU and LU (by 1.0%-5.5%), but caused a significant increase of BWU (by 17.2%). Using imported soybean instead of locally-grown soybean decreased LU by 2.6%, but significantly increased GWP and NREU by 20% and 6.9%, respectively. There was no single perfect manure management system, with variable effects from different management practices. The environmental burden shifting observed in this study illustrates the importance of assessing a wide range of impact categories instead of single or limited indicators for formulating environmental policies, and the necessity of combining multiple measures to decrease the environmental burden. For the North China Plain, improving milking cow productivity and herd structure (i.e. increased proportion of milking cows), combining various manure management systems, and encouraging dairy farmers to return manure to nearby crop lands are promising measures to decrease multiple environmental impacts.
Assuntos
Indústria de Laticínios , Meio Ambiente , Aquecimento Global , Animais , Bovinos , China , Feminino , Esterco , LeiteRESUMO
Stable Pickering emulsions were prepared using only graphene oxide (GO) as a stabilizer, and the effects of the type of oil, the sonication time, the GO concentration, the oil/water ratio, and the pH value on the stability, type, and morphology of these emulsions were investigated. In addition, the effects of salt and the extent of GO reduction on emulsion formation and stability were studied and discussed. The average droplet size decreased with sonication time and with GO concentration, and the emulsions tended to achieve good stability at intermediate oil/water ratios and at low pH values. In all solvents, the emulsions were of the oil-in-water type, but interestingly, some water-in-oil-in-water (w/o/w) multiple emulsion droplets were also observed with low GO concentrations, low pH values, high oil/water ratios, high salt concentrations, or moderately reduced GO in the benzyl chloride-water system. A Pickering emulsion stabilized by Ag/GO was also prepared, and its catalytic performance for the reduction of 4-nitrophenol was investigated. This research paves the way for the fabrication of graphene-based functional materials with novel nanostructures and microstructures.