Evaluation of LOXL1 polymorphisms in exfoliation syndrome in a Chinese population

Purpose: To evaluate the association profiles of the lysyl oxidase-like 1 (LOXL1) gene polymorphisms with exfoliation syndrome in a Chinese population. Methods: Fifty unrelated patients with exfoliation syndrome and 125 control subjects were included. Genotypes of the three single nucleotide polymorphisms (SNPs) of LOXL1 (rs1048661, rs3825942, and rs2165241) were analyzed by direct sequencing, and a case-control association study was performed. Results: The three SNPs were significantly associated with exfoliation syndrome (XFS) and exfoliation glaucoma (XFG) individually. After controlling for rs3825942 and rs2165241, the association between rs1048661 and XFS/XFG remained significant (p=3.6x10(-7)). At this SNP, the T allele and TT genotype conferred a 7.59-(95% confidence interval [CI]: 3.87-14.89, p=6.95x10(-11)) and 8.69-(95% CI: 4.15-18.20, p<1.00x10(-7)) fold increased risk to the disease. The alleles of T at rs1048661 and C at rs2165241 were found to be risk alleles in Chinese subjects, which were opposite to Caucasian individuals. The haplotypes T-G, defined by SNPs rs1048661 and rs3825942, and T-C by SNPs rs1048661 and rs2165241, were also significantly associated with the disorder. However when the genotypic or allelic frequencies of the three SNPs were compared between XFS and XFG, no significant difference was detected. Conclusions: LOXL1 is a susceptibility gene of XFS/XFG in the Chinese population, and the association is mainly attributed to SNP rs1048661. The risk alleles of rs1048661 and rs2165241 in Chinese subjects were found to be opposite to that of Caucasians. The genotypic and allelic distributions of these SNPs are similar between XFS and XFG.Biochemistry & Molecular BiologyOphthalmologySCI(E)30ARTICLE250-522349-23571

BAFF Promotes Th17 Cells and Aggravates Experimental Autoimmune Encephalomyelitis

BAFF, in addition to promoting B cell survival and differentiation, may affect T cells. The objective of this study was to determine the effect of BAFF on Th17 cell generation and its ramifications for the Th17 cell-driven disease, EAE.Th17 cells were increased in BAFF-Tg B6 (B6.BTg) mice and decreased in B6.Baff(-/-) mice. Th17 cells in B6.Baff(-/-) mice bearing a BAFF Tg (B6.Baff(-/-).BTg mice) were identical to those in B6.BTg mice, indicating that membrane BAFF is dispensable for Th17 cell generation as long as soluble BAFF is plentiful. In T + non-T cell criss-cross co-cultures, Th17 cell generation was greatest in cultures containing B6.BTg T cells and lowest in cultures containing B6.Baff(-/-) T cells, regardless of the source of non-T cells. In cultures containing only T cells, Th17 cell generation followed an identical pattern. CD4(+) cell expression of CD126 (IL-6R α chain) was increased in B6.BTg mice and decreased in B6.Baff(-/-) mice, and activation of STAT3 following stimulation with IL-6 + TGF-β was also greatest in B6.BTg cells and lowest in B6.Baff(-/-) cells. EAE was clinically and pathologically most severe in B6.BTg mice and least severe in B6.Baff(-/-) mice and correlated with MOG(35-55) peptide-induced Th17 cell responses.Collectively, these findings document a contribution of BAFF to pathogenic Th17 cell responses and suggest that BAFF antagonism may be efficacious in Th17 cell-driven diseases

Adaptive Multivariable Super-Twisting Sliding Mode Controller and Disturbance Observer Design for Hypersonic Vehicle

A multivariable super-twisting sliding mode controller and disturbance observer with gain adaptation, chattering reduction, and finite time convergence are proposed for a generic hypersonic vehicle where the boundary of aerodynamic uncertainties exists but is unknown. Firstly, an input-output linearization model is constructed for the purpose of controller design. Then, the sliding manifold is designed based on the homogeneity theory. Furthermore, an integrated adaptive multivariable super-twisting sliding mode controller and disturbance observer are designed in order to achieve the tracking for step changes in velocity and altitude. Finally, some simulation results are provided to verify the effectiveness of the proposed method

Adaptive High Order Sliding Mode Controller Design for Hypersonic Vehicle with Flexible Body Dynamics

This paper describes the design of a nonlinear robust adaptive controller for a flexible hypersonic vehicle model which is nonlinear, multivariable, and unstable, and includes uncertain parameters. Firstly, a control-oriented model is derived for controller design. Then, the model analysis is conducted for this model via input-output (I/O) linearized technique. Secondly, the sliding mode manifold is designed based on the homogeneity theory. Then, the adaptive high order sliding mode controller is designed to achieve the tracking for hypersonic vehicle where the upper bounds of the uncertainties are not known in advance. Furthermore, the stability of the system is proved via the Lyapunov theory. Finally, the Monte-Carlo simulation results on the full-order nonlinear model with aerodynamic uncertainties are provided to demonstrate the effectiveness of the proposed control strategy

A review on image reconstruction algorithms for electrical capacitance/resistance tomography

PurposeElectrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low cost, non-invasive and visualization features. There are two major difficulties in image reconstruction for ECT and ERT: the “soft-field”effect, and the ill-posedness of the inverse problem, which includes two problems: under-determined problem and the solution is not stable, i.e. is very sensitive to measurement errors and noise. This paper aims to summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide reference for further research and application.Design/methodology/approachIn the past 10 years, various image reconstruction algorithms have been developed to deal with these problems, including in the field of industrial multi-phase flow measurement and biological medical diagnosis.FindingsThis paper reviews existing image reconstruction algorithms and the new algorithms proposed by the authors for electrical capacitance tomography and electrical resistance tomography in multi-phase flow measurement and biological medical diagnosis.Originality/valueThe authors systematically summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide valuable reference for practical applications.</jats:sec

Table_1_Association between immune-related adverse events and the efficacy of PD-1 inhibitors in advanced esophageal cancer.docx

IntroductionRecent developments in immune checkpoint inhibitors (ICIs) have improved the treatment outcomes of esophageal cancer (EC); however, it may initiate immune-related adverse events (irAEs) in some patients. The ICIs’ therapeutic efficacy is associated with irAEs in patients with non-small cell lung cancer or renal cell carcinoma, although this association is unknown in EC. The purpose of this study was to explore the association between irAEs and the efficacy of programmed death 1 (PD-1) inhibitors in EC patients.Patients and methodsThis study included patients with advanced EC treated with PD-1 inhibitors. The patients were divided into two groups according to the occurrence of irAEs. Afterward, the efficacy was compared between the irAE-negative and irAE-positive groups, and we analyzed the predictive factors of irAEs and survival.ResultsOverall, 295 patients were included in this study. Baseline characteristics were balanced in the irAE-negative and irAE-positive groups. In total, 143 (48.47%) patients experienced irAEs. The most frequent irAEs were anemia (49, 16.61%), hyperthyroidism (45, 15.25%), and pneumonitis (44, 14.92%). In total, 33 (11.19%) patients had grade ≥ 3 irAEs and pneumonitis have 15 (5.08%). No grade 5 adverse events were observed. A total of 52 (17.63%) and 91 (30.85%) patients had single and multiple irAEs, respectively. Compared with patients without irAEs, those with irAEs had significantly higher objective response rate (ORR) (37.76% vs. 25.00%, p = 0.018) and disease control rate (DCR) (92.31% vs. 83.55%, p = 0.022). Univariate Cox analyses indicated the significant association between irAEs and improved median progression-free survival (PFS) (10.27 vs. 6.2 months, p 8, radiation, as well as antiangiogenic therapy were strongly associated with irAEs development (p ConclusionIn advanced EC, patients with irAEs showed markedly better efficacy in ORR, DCR, PFS, and OS compared with patients without irAEs.</p

From pixels to patient care: deep learning-enabled pathomics signature offers precise outcome predictions for immunotherapy in esophageal squamous cell cancer

Abstract Background Immunotherapy has significantly improved survival of esophageal squamous cell cancer (ESCC) patients, however the clinical benefit was limited to only a small portion of patients. This study aimed to perform a deep learning signature based on H&E-stained pathological specimens to accurately predict the clinical benefit of PD-1 inhibitors in ESCC patients. Methods ESCC patients receiving PD-1 inhibitors from Shandong Cancer Hospital were included. WSI images of H&E-stained histological specimens of included patients were collected, and randomly divided into training (70%) and validation (30%) sets. The labels of images were defined by the progression-free survival (PFS) with the interval of 4 months. The pretrained ViT model was used for patch-level model training, and all patches were projected into probabilities after linear classifier. Then the most predictive patches were passed to RNN for final patient-level prediction to construct ESCC-pathomics signature (ESCC-PS). Accuracy rate and survival analysis were performed to evaluate the performance of ViT-RNN survival model in validation cohort. Results 163 ESCC patients receiving PD-1 inhibitors were included for model training. There were 486,188 patches of 1024*1024 pixels from 324 WSI images of H&E-stained histological specimens after image pre-processing. There were 120 patients with 227 images in training cohort and 43 patients with 97 images in validation cohort, with balanced baseline characteristics between two groups. The ESCC-PS achieved an accuracy of 84.5% in the validation cohort, and could distinguish patients into three risk groups with the median PFS of 2.6, 4.5 and 12.9 months (P < 0.001). The multivariate cox analysis revealed ESCC-PS could act as an independent predictor of survival from PD-1 inhibitors (P < 0.001). A combined signature incorporating ESCC-PS and expression of PD-L1 shows significantly improved accuracy in outcome prediction of PD-1 inhibitors compared to ESCC-PS and PD-L1 anlone, with the area under curve value of 0.904, 0.924, 0.610 for 6-month PFS and C-index of 0.814, 0.806, 0.601, respectively. Conclusions The outcome supervised pathomics signature based on deep learning has the potential to enable superior prognostic stratification of ESCC patients receiving PD-1 inhibitors, which convert the images pixels to an effective and labour-saving tool to optimize clinical management of ESCC patients