Comprehensive analysis of T-cell receptor repertoires reveals antigen-driven T-cell clusters in patients with Behçet's syndrome.

T lymphocytes are the major components of adaptive immunity in Behçet's syndrome (BS) pathology. However, the precise mechanism of T-cell-induced inflammatory condition remains to be determined. We applied bulk sequencing of the T-cell receptor (TCR) ß chain in peripheral blood samples from 45 patients with BS and 10 healthy donors as controls. TCR repertoires in BS patients displayed more clonality and less diversity than in healthy donors. Male patients exhibited lower diversity metrics of TCR and had a larger proportion in the top 10 clones than females (p = 0.016). There were no TCR clonality differences in other clinical features, such as age, disease duration, organ involvement, disease severity, and activity. By "Grouping of Lymphocyte Interactions by Paratope Hotspots" (GLIPH2) for antigen prediction, we found distinct 2477 clusters of TCR-ß sequences that potentially recognize similar antigens shared between BS patients. We observed clonal T-cell expansion in BS patients. Sexual differences in TCR clonal expansion and public TCR groups deserve further study to reveal the underline T-cell-mediated immunity in BS.

Predictors of infliximab refractory intestinal Behçet's syndrome: A retrospective cohort study from the Shanghai Behçet's syndrome database.

OBJECTIVES: This retrospective cohort study aimed to find out predictors and early biomarkers of Infliximab (IFX) refractory intestinal Behçet's syndrome (intestinal BS). METHODS: We collected the baseline clinical characteristics, laboratory parameters, and concomitant therapies of intestinal BS patients treated by IFX from the Shanghai Behçet's syndrome database. After 1 year IFX therapy, intestinal BS patients with non-mucosal healing (NMH, intestinal ulcers detected by colonoscopy) and/or no clinical remission [NCR, scores of the disease activity index for intestinal Behçet's disease (DAIBD) ≥20] were defined as IFX refractory intestinal BS. Multivariate logistic regression analysis was performed to evaluate the predictors for NMH and NCR in IFX refractory intestinal BS. RESULTS: In 85 intestinal BS patients, NMH was identified in 29 (34.12%) patients, and NCR was confirmed in 20 (23.53%) patients. Erythrocyte sedimentation rate (ESR; ≥24 mm/h) and free triiodothyronine (fT3; ≤3.3pmol/L) were the independent risk factors of NMH in IFX refractory intestinal BS. Drinking alcohol and the fT3/free thyroxine ratio (fT3/fT4; ≤0.24) were independent risk factors, and thalidomide was an independent protective factor, for NCR in intestinal BS patients treated by IFX. CONCLUSION: This study may be applicable for adjusting the therapeutic strategy and sidestepping unnecessary exposure to IFX in intestinal BS patients. Routine assessments of ESR, fT3, and fT3/fT4 ratio are helpful to identify high-risk individuals of IFX refractory intestinal BS. Thalidomide is suggested to be a concomitant therapy with IFX for intestinal BS patients.

Serum uric acid could be served as an independent marker for increased risk and severity of ascending aortic dilatation in Behçet's disease patients.

OBJECTIVE: This study aimed to investigate the correlation of serum uric acid (SUA) with risk and dilatation diameter of ascending aortic dilatation (AAD) in Behçet's disease (BD) patients. METHODS: Seventeen BD patients complicated with AAD and 20 BD patients without AAD were consecutively enrolled and categorized into AAD group and control group, respectively. Ascending aortic dilatation was determined by two-dimensional doppler echocardiographic examination, and AAD was defined as a diameter of ascending aorta ≥3.8 and <4.4 cm. SUA was detected by quantitative immunoassay method. RESULTS: Ascending aortic dilatation patients presented with higher proportion of male patients (P = 0.003), hypertension occurrence (P = 0.036) and increased diameter of ascending aorta (P < 0.001) compared to controls. SUA was elevated in AAD patients compared to controls (P = 0.002), and receiver operating characteristic curve displayed that SUA presented with great predictive value for AAD risk in BD patients with area under curve (AUC) 0.821 (95% CI 0.675-0.966). Pearson's analysis also disclosed that SUA was positively correlated with ascending aortic diameter in total BD patients. However, no difference of CRP (P = 0.219) or ESR (P = 0.320) between AAD patients and controls was observed, and no correlation of CRP (R = -0.150, P = 0.377) or ESR (R = 0.067, P = 0.692) with ascending aortic diameter in total BD patients was discovered either. Further multivariate logistic regression illuminated that SUA was an independent factor predicting AAD risk in BD patients (P = 0.031). CONCLUSIONS: Serum uric acid could be served as an independent marker for increased risk and severity of AAD in BD patients.

Long-Term Outcomes and Predictors of Sustained Response in Patients with Intestinal Behcet's Disease Treated with Infliximab.

BACKGROUND: Intestinal Behcet's disease (BD) is a specific subtype of BD. Effective drug therapy for intestinal BD remains elusive. AIMS: To investigate long-term outcomes and identify predictors of sustained response in intestinal BD patients receiving infliximab (IFX) treatment. METHODS: The medical records were reviewed of patients received IFX from September 2012 to March 2016. The cumulative probabilities of sustained response were calculated using the Kaplan-Meier. Predictor factors for sustained response were accessed by receiver operating characteristic curve. RESULTS: Totally, 27 active intestinal BD patients were enrolled. Sustained responses were observed in 17 patients, after a median follow-up duration 24 months (interquartile range 9-37). The proportion of clinical remission at week 14, 30, and 52 had occurred in 84.6, 70, and 70%, respectively, with the proportion of clinical remission of 69.2, 40, and 55%. The mucosal healing (MH) rate at week 14 was 72%. Kaplan-Meier estimated patients with achievement of clinical and biological responses at week 14 or MH was likely to remain sustained clinical response. ROC curve analysis revealed CRP level (of 6.85 mg/L) at week 14 is a potential predictor for discriminating patients with sustained response from relapse, with an area under the curve values of 0.837. CONCLUSIONS: IFX is effective and safe for induction and maintenance therapy in Chinese patients with moderate-to-severe active intestinal BD. Early achievement of clinical response and mucosal healing might associate long-term response. A lower CRP level seems to be associated with a more benign clinical course.

Clinical characteristics of Behçet's syndrome in Shanghai database: Baseline data of a cross-sectional cohort study.

OBJECTIVE: Behçet's syndrome (BS) is a variant vessel vasculitis that can involve multiple organs, with highly heterogeneous clinical manifestations. This study aims to analyze baseline data of BS patients to enhance the comprehension of its clinical features. METHODS: This study included 1216 registered cases of BS patients referred to Huadong Hospital affiliated with Fudan University. Each patient was thoroughly assessed and recorded for demographic data, clinical manifestations, gastrointestinal endoscope, imaging, etc. RESULTS: Significant gender differences were observed in clinical manifestations. Pseudofolliculitis (p < .001), uveitis (p = .003), vascular (p < .001), and cardiovascular involvement (p < .001) were significantly more prevalent in male BS patients, while genital ulcers (p = .011) and erythema nodosum (p = .009) were more common among the female. Furthermore, pseudofolliculitis (44.3%, 37.4% vs. 25.0%, p < .001), pathergy test positivity (37.0%, 24.5% vs. 12.6%, p < .001), and uveitis (18.8%, 18.4% vs. 11.2%, p < .001) showed higher incidence rates in the 16-35 years age group. Vascular involvement (11.1%, 18.0% vs. 15.8%, p < .001) notably increased in the 36-50 years age group. Additionally, the ISG diagnostic criteria were more likely to be met in the 16-35 age group (OR: 2.039, 95% CI: 1.581-2.631, p < .001), whereas the ICBD criteria were less likely to be met in the 16-35 age group (OR: 0.266, 95% CI: 0.150-0.474, p < .001). CONCLUSIONS: This study provided data on the baseline of clinical features of BS in a single center, BS patients presented significant heterogeneity, showing different manifestations across various genders and age groups. This diversity might contribute to a better understanding of BS clinical features and pave the way for future multi-center studies.

Pruning Self-Attentions Into Convolutional Layers in Single Path.

Vision Transformers (ViTs) have achieved impressive performance over various computer vision tasks. However, modeling global correlations with multi-head self-attention (MSA) layers leads to two widely recognized issues: the massive computational resource consumption and the lack of intrinsic inductive bias for modeling local visual patterns. To solve both issues, we devise a simple yet effective method named Single-Path Vision Transformer pruning (SPViT), to efficiently and automatically compress the pre-trained ViTs into compact models with proper locality added. Specifically, we first propose a novel weight-sharing scheme between MSA and convolutional operations, delivering a single-path space to encode all candidate operations. In this way, we cast the operation search problem as finding which subset of parameters to use in each MSA layer, which significantly reduces the computational cost and optimization difficulty, and the convolution kernels can be well initialized using pre-trained MSA parameters. Relying on the single-path space, we introduce learnable binary gates to encode the operation choices in MSA layers. Similarly, we further employ learnable gates to encode the fine-grained MLP expansion ratios of FFN layers. In this way, our SPViT optimizes the learnable gates to automatically explore from a vast and unified search space and flexibly adjust the MSA-FFN pruning proportions for each individual dense model. We conduct extensive experiments on two representative ViTs showing that our SPViT achieves a new SOTA for pruning on ImageNet-1 k. For example, our SPViT can trim 52.0% FLOPs for DeiT-B and get an impressive 0.6% top-1 accuracy gain simultaneously.

Bridging Global Context Interactions for High-Fidelity Pluralistic Image Completion.

We introduce PICFormer, a novel framework for Pluralistic Image Completion using a transFormer based architecture, that achieves both high quality and diversity at a much faster inference speed. Our key contribution is to introduce a code-shared codebook learning using a restrictive CNN on small and non-overlapping receptive fields (RFs) for the local visible token representation. This results in a compact yet expressive discrete representation, facilitating efficient modeling of global visible context relations by the transformer. Unlike the prevailing autoregressive approaches, we proposed to sample all tokens simultaneously, leading to more than 100× faster inference speed. To enhance appearance consistency between visible and generated regions, we further propose a novel attention-aware layer (AAL), designed to better exploit distantly related high-frequency features. Through extensive experiments, we demonstrate that the efficiently learns semantically-rich discrete codes, resulting in significantly improved image quality. Moreover, our diverse image completion framework surpasses state-of-the-art methods on multiple image completion datasets. The project page is available at https://chuanxiaz.com/picformer/.

Clinical heterogeneity and five phenotypes identified in pediatric Behçet's syndrome: a cohort study from Shanghai Behçet's syndrome database.

OBJECTIVES: Behçet's syndrome (BS) is a rare disease of unknown etiology, with limited reports especially in pediatric BS. The clinical characteristics and phenotypes of pediatric BS as a highly heterogeneous variable vessel vasculitis were investigated in this study. METHODS: A cross-sectional study was conducted to compare clinical variables and descriptive characteristics of BS by age of onset and gender. Cluster analysis was then performed to identify the phenotypes of pediatric BS. RESULTS: A total of 2082 BS patients were included in this study, 1834 adults and 248 children. Compared with adult-onset BS, pediatric BS had a higher incidence of folliculitis [relative risks (RR) and 95% confidence interval (CI) 1.3 (1.0-1.5)], uveitis of the left eye [RR and 95% CI 2.3 (1.0-5.0)], intestinal ulcer complications [RR and 95% CI 2.1 (1.1-4.2)], pericarditis [RR and 95% CI 2.5 (1.0-6.2)], and psychiatric disorders [RR and 95% CI 2.8(1.0-7.9)], while the incidence of thrombocytopenia was lower [RR 0.2 (0.1-1.0)]. Among pediatric BS, females had more genital ulcers, while males were more likely to have skin lesions, panuveitis, vascular involvement, venous lesions, cardiac involvement, and aortic aneurysms. Cluster analysis classified pediatric BS into five clusters (C1-C5): C1 (n = 61, 24.6%) showed gastrointestinal (GI) involvement; C2 (n = 44, 17.7%) was the central nervous system (CNS) type where 23 cases overlapped joint involvement; in C3 (n = 35, 14.1%), all patients presented with arthritis or arthralgia; all patients in C4 (n = 29, 11.7%) manifested ocular involvement, with a few patients overlapping with GI involvement or joint damage; C5 (n = 79, 31.9%) was the mucocutaneous type, presenting both oral ulcers, genital ulcers, and skin lesions. CONCLUSIONS: The clinical features of pediatric and adult BS differ significantly. Male and female pediatric BS also have a distinct demography. Five phenotypes including GI, CNS, joint, ocular, and mucocutaneous types were identified for pediatric BS.

AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs.

Despite well-defined criteria for radiographic diagnosis of atypical femur fractures (AFFs), missed and delayed diagnosis is common. An AFF diagnostic software could provide timely AFF detection to prevent progression of incomplete or development of contralateral AFFs. In this study, we investigated the ability for an artificial intelligence (AI)-based application, using deep learning models (DLMs), particularly convolutional neural networks (CNNs), to detect AFFs from femoral radiographs. A labelled Australian dataset of pre-operative complete AFF (cAFF), incomplete AFF (iAFF), typical femoral shaft fracture (TFF), and non-fractured femoral (NFF) X-ray images in anterior-posterior view were used for training (N = 213, 49, 394, 1359, respectively). An AFFnet model was developed using a pretrained (ImageNet dataset) ResNet-50 backbone, and a novel Box Attention Guide (BAG) module to guide the model's scanning patterns to enhance its learning. All images were used to train and internally test the model using a 5-fold cross validation approach, and further validated by an external dataset. External validation of the model's performance was conducted on a Sweden dataset comprising 733 TFF and 290 AFF images. Precision, sensitivity, specificity, F1-score and AUC were measured and compared between AFFnet and a global approach with ResNet-50. Excellent diagnostic performance was recorded in both models (all AUC >0.97), however AFFnet recorded lower number of prediction errors, and improved sensitivity, F1-score and precision compared to ResNet-50 in both internal and external testing. Sensitivity in the detection of iAFF was higher for AFFnet than ResNet-50 (82 % vs 56 %). In conclusion, AFFnet achieved excellent diagnostic performance on internal and external validation, which was superior to a pre-existing model. Accurate AI-based AFF diagnostic software has the potential to improve AFF diagnosis, reduce radiologist error, and allow urgent intervention, thus improving patient outcomes.

Clinical phenotypes of adult-onset Behçet's syndrome: a comprehensive cross-sectional study in China.

Behçet's syndrome (BS) is a variant vasculitis that can involve multiple organs with inflammatory manifestations. This study aimed to provide a more comprehensive analysis of the clinical phenotypes and characteristics of BS patients. We enrolled 2792 BS patients referred from China nationwide to Huadong Hospital Affiliated to Fudan University from October 2012 to December 2022. Detailed assessments of demographic information, clinical manifestations, laboratory results, gastroscopy, and medical imaging were conducted. Cluster analysis was performed based on 13 variables to determine the clinical phenotypes, and each phenotype was characterized according to the features of BS patients. A total of 1834 BS patients were included, while 958 invalid patients were excluded. The median age at onset was 31 years (IQR, 24-40 years), and the median disease duration was 10 years (IQR, 5-15 years). Eight clusters were identified, including mucocutaneous (n = 655, 35.7%), gastrointestinal (n = 363, 19.8%), articular (n = 184, 10%), ocular (n = 223, 12.2%), cardiovascular (n = 119, 6.5%), neurological (n = 118, 6.4%), vascular (n = 114, 6.2%), and hematological phenotype (n = 58, 3.2%). Ocular (RR = 1.672 (95% CI, 1.327-2.106); P < 0.001), gastrointestinal (RR = = 1.194 (95% CI, 1.031-1.383); P = 0.018), cardiovascular (RR = = 2.582 (95% CI, 1.842-3.620); P < 0.001), and vascular (RR = = 2.288 (95% CI, 1.600-3.272); P < 0.001) involvement were more prevalent in male BS patients, while the hematological (RR = 0.528 (95% CI, 0.360-0.776); P = 0.001) involvement was more common among female patients. BS presents significant heterogeneity and gender differences. The eight phenotypes of BS patients we propose hold the potential to assist clinicians in devising more personalized treatment and follow-up strategies. Key Points • This cluster analysis divided adult-onset BS into eight clinical phenotypes. • BS demonstrates a high level of clinical heterogeneity and gender differences. • Hematologic phenotypes of BS present distinctive clinical characteristics.

PLK1-activating IFI16-STING-TBK1 pathway induces apoptosis of intestinal epithelial cells in patients with intestinal Behçet's syndrome.

Inflammatory signals from immunological cells may cause damage to intestinal epithelial cells (IECs), resulting in intestinal inflammation and tissue impairment. Interferon-γ-inducible protein 16 (IFI16) was reported to be involved in the pathogenesis of Behçet's syndrome (BS). This study aimed to investigate how inflammatory cytokines released by immunological cells and IFI16 participate in the pathogenesis of intestinal BS. RNA sequencing and real-time quantitative PCR (qPCR) showed that the positive regulation of tumor necrosis factor-α (TNF-α) production in peripheral blood mononuclear cells (PBMCs) of intestinal BS patients may be related to the upregulation of polo like kinase 1 (PLK1) in PBMCs (P = 0.012). The plasma TNF-α protein level in intestinal BS was significantly higher than in healthy controls (HCs; P = 0.009). PBMCs of intestinal BS patients and HCs were co-cultured with human normal IECs (NCM460) to explore the interaction between immunological cells and IECs. Using IFI16 knockdown, PBMC-NCM460 co-culture, TNF-α neutralizing monoclonal antibody (mAb), stimulator of interferon genes (STING) agonist 2'3'-cGAMP, and the PLK1 inhibitor SBE 13 HCL, we found that PLK1 promotes the secretion of TNF-α from PBMCs of intestinal BS patients, which causes overexpression of IFI16 and induces apoptosis of IECs via the STING-TBK1 pathway. The expressions of IFI16, TNF-α, cleaved caspase 3, phosphorylated STING (pSTING) and phosphorylated tank binding kinase 1 (pTBK1) in the intestinal ulcer tissue of BS patients were significantly higher than that of HCs (all P < 0.05). PLK1 in PBMCs of intestinal BS patients increased TNF-α secretion, inducing IEC apoptosis via activation of the IFI16-STING-TBK1 pathway. PLK1 and the IFI16-STING-TBK1 pathway may be new therapeutic targets for intestinal BS.

Deconfounded Image Captioning: A Causal Retrospect.

Dataset bias in vision-language tasks is becoming one of the main problems which hinders the progress of our community. Existing solutions lack a principled analysis about why modern image captioners easily collapse into dataset bias. In this paper, we present a novel perspective: Deconfounded Image Captioning (DIC), to find out the answer of this question, then retrospect modern neural image captioners, and finally propose a DIC framework: DICv1.0 to alleviate the negative effects brought by dataset bias. DIC is based on causal inference, whose two principles: the backdoor and front-door adjustments, help us review previous studies and design new effective models. In particular, we showcase that DICv1.0 can strengthen two prevailing captioning models and can achieve a single-model 131.1 CIDEr-D and 128.4 c40 CIDEr-D on Karpathy split and online split of the challenging MS COCO dataset, respectively. Interestingly, DICv1.0 is a natural derivation from our causal retrospect, which opens promising directions for image captioning.

FastCAT: A framework for fast routing table calculation incorporating multiple protocols.

Currently, most network outages occur because of manual configuration errors. Therefore, it is essential to verify the correctness of network configurations before deployment. Computing the network control plane is a key technology for network configuration verification. We can verify the correctness of network configurations for fault tolerance by generating routing tables, as well as connectivity. However, existing routing table calculation tools have disadvantages such as lack of user-friendliness, limited expressiveness, and slower speed of routing table generation. In this paper, we present FastCAT, a framework for computing routing tables incorporating multiple protocols. FastCAT can simulate the interaction of multiple routing protocols and quickly generate routing tables based on configuration files and topology information. The key to FastCAT's performance is that FastCAT focuses only on the final stable state of the OSPF and IS-IS protocols, disregarding the transient states during protocol convergence. For RIPv2 and BGP, FastCAT computes the current protocol routing tables based on the protocol's previous state, retaining only the most recent protocol routing tables in the latest state. Experimental evaluations have shown that FastCAT generates routing tables more quickly and accurately than the state-of-the-art routing simulation tool, in a general network of around 200 routers.

End-to-End One-Shot Human Parsing.

Previous human parsing methods are limited to parsing humans into pre-defined classes, which is inflexible for practical fashion applications that often have new fashion item classes. In this paper, we define a novel one-shot human parsing (OSHP) task that requires parsing humans into an open set of classes defined by any test example. During training, only base classes are exposed, which only overlap with part of the test-time classes. To address three main challenges in OSHP, i.e., small sizes, testing bias, and similar parts, we devise an End-to-end One-shot human Parsing Network (EOP-Net). Firstly, an end-to-end human parsing framework is proposed to parse the query image into both coarse-grained and fine-grained human classes, which embeds rich semantic information that is shared across different granularities to identify the small-sized human classes. Then, we gradually smooth the training-time static prototypes to get robust class representations. Moreover, we employ a dynamic objective to encourage the network enhancing features' representational capability in the early training phase while improving features' transferability in the late training phase. Therefore, our method can quickly adapt to the novel classes and mitigate the testing bias issue. In addition, we add a contrastive loss at the prototype level to enforce inter-class distances, thereby discriminating the similar parts. For comprehensive evaluations on the new task, we tailor three existing popular human parsing benchmarks to the OSHP task. Experiments demonstrate that EOP-Net outperforms representative one-shot segmentation models by large margins and serves as a strong baseline for further research.

Single-Path Bit Sharing for Automatic Loss-Aware Model Compression.

Network pruning and quantization are proven to be effective ways for deep model compression. To obtain a highly compact model, most methods first perform network pruning and then conduct quantization based on the pruned model. However, this strategy may ignore that the pruning and quantization would affect each other and thus performing them separately may lead to sub-optimal performance. To address this, performing pruning and quantization jointly is essential. Nevertheless, how to make a trade-off between pruning and quantization is non-trivial. Moreover, existing compression methods often rely on some pre-defined compression configurations (i.e., pruning rates or bitwidths). Some attempts have been made to search for optimal configurations, which however may take unbearable optimization cost. To address these issues, we devise a simple yet effective method named Single-path Bit Sharing (SBS) for automatic loss-aware model compression. To this end, we consider the network pruning as a special case of quantization and provide a unified view for model pruning and quantization. We then introduce a single-path model to encode all candidate compression configurations, where a high bitwidth value will be decomposed into the sum of a lowest bitwidth value and a series of re-assignment offsets. Relying on the single-path model, we introduce learnable binary gates to encode the choice of configurations and learn the binary gates and model parameters jointly. More importantly, the configuration search problem can be transformed into a subset selection problem, which helps to significantly reduce the optimization difficulty and computation cost. In this way, the compression configurations of each layer and the trade-off between pruning and quantization can be automatically determined. Extensive experiments on CIFAR-100 and ImageNet show that SBS significantly reduces computation cost while achieving promising performance. For example, our SBS compressed MobileNetV2 achieves 22.6× Bit-Operation (BOP) reduction with only 0.1% drop in the Top-1 accuracy.

Facial Action Unit Detection via Adaptive Attention and Relation.

Facial action unit (AU) detection is challenging due to the difficulty in capturing correlated information from subtle and dynamic AUs. Existing methods often resort to the localization of correlated regions of AUs, in which predefining local AU attentions by correlated facial landmarks often discards essential parts, or learning global attention maps often contains irrelevant areas. Furthermore, existing relational reasoning methods often employ common patterns for all AUs while ignoring the specific way of each AU. To tackle these limitations, we propose a novel adaptive attention and relation (AAR) framework for facial AU detection. Specifically, we propose an adaptive attention regression network to regress the global attention map of each AU under the constraint of attention predefinition and the guidance of AU detection, which is beneficial for capturing both specified dependencies by landmarks in strongly correlated regions and facial globally distributed dependencies in weakly correlated regions. Moreover, considering the diversity and dynamics of AUs, we propose an adaptive spatio-temporal graph convolutional network to simultaneously reason the independent pattern of each AU, the inter-dependencies among AUs, as well as the temporal dependencies. Extensive experiments show that our approach (i) achieves competitive performance on challenging benchmarks including BP4D, DISFA, and GFT in constrained scenarios and Aff-Wild2 in unconstrained scenarios, and (ii) can precisely learn the regional correlation distribution of each AU.

Unifying Flow, Stereo and Depth Estimation.

We present a unified formulation and model for three motion and 3D perception tasks: optical flow, rectified stereo matching and unrectified stereo depth estimation from posed images. Unlike previous specialized architectures for each specific task, we formulate all three tasks as a unified dense correspondence matching problem, which can be solved with a single model by directly comparing feature similarities. Such a formulation calls for discriminative feature representations, which we achieve using a Transformer, in particular the cross-attention mechanism. We demonstrate that cross-attention enables integration of knowledge from another image via cross-view interactions, which greatly improves the quality of the extracted features. Our unified model naturally enables cross-task transfer since the model architecture and parameters are shared across tasks. We outperform RAFT with our unified model on the challenging Sintel dataset, and our final model that uses a few additional task-specific refinement steps outperforms or compares favorably to recent state-of-the-art methods on 10 popular flow, stereo and depth datasets, while being simpler and more efficient in terms of model design and inference speed.

PCSK9 promotes T helper 1 and T helper 17 cell differentiation by activating the nuclear factor-κB pathway in ankylosing spondylitis.

OBJECTIVE: Our previous study reveals that proprotein convertase subtilisin/kexin type 9 (PCSK9) is positively related to inflammatory markers, T helper (Th)-17 cells, and treatment response in ankylosing spondylitis (AS) patients. Subsequently, this study aimed to explore the effect of PCSK9 on Th cell differentiation and its potential molecular mechanism in AS. METHODS: Serum PCSK9 was determined by enzyme-linked immunosorbent assay in 20 AS patients and 20 healthy controls (HCs). Then naïve CD4+ T cells were isolated from AS patients and infected with PCSK9 overexpression or knockdown adenovirus followed by polarization assay. Afterward, PMA (an NF-κB activator) was administrated. RESULTS: PCSK9 was increased in AS patients compared to HCs (p < .001), and it was positively related to Th1 cells (p = .050) and Th17 cells (p = .039) in AS patients. PCSK9 overexpression increased the CD4+ IFN-γ+ cells (p < .05), CD4+ IL-17A+ cells (p < .01), IFN-γ (p < .01), and IL-17A (p < .01), while it exhibited no effect on CD4+ IL-4+ cells or IL-4 (both p > .05); its knockdown displayed the opposite function on them. Moreover, PCSK9 overexpression upregulated the p-NF-κB p65/NF-κB p65 (p < .01), while it had no effect on p-ERK/ERK or p-JNK/JNK (both p > .05); its knockdown decreased p-NF-κB p65/NF-κB p65 (p < .01) and p-JNK/JNK (p < .05). Then, PMA upregulates p-NF-κB p65/NF-κB p65 (p < .001) and increased CD4+ IFN-γ+ cells, CD4+ IL-17A+ cells, IFN-γ, and IL-17A (all p < .01), also it alleviated the effect of PCSK9 knockdown on NF-κB inhibition and Th cell differentiation (all p < .01). CONCLUSION: PCSK9 enhances Th1 and Th17 cell differentiation in an NF-κB-dependent manner in AS, while further validation is necessary.

Serum PCSK9 is positively correlated with disease activity and Th17 cells, while its short-term decline during treatment reflects desirable outcomes in ankylosing spondylitis patients.

OBJECTIVE: Proprotein convertase subtilisin/kexin type 9 (PCSK9) participates in the autoimmune disease pathology by regulating T helper (Th) cell differentiation, NF-κB pathway, toll-like receptor 4, etc. This study intended to investigate the association of serum PCSK9 with disease activity, Th cells, and treatment response in ankylosing spondylitis (AS) patients. METHODS: Eighty-nine active AS patients were enrolled in this multicenter, prospective study. Serum was collected from AS patients at week (W)0, W4, W8, and W12, as well as from 20 osteoarthritis patients and 20 healthy controls after enrollment to detect PCSK9 by ELISA. Based on the ASAS40 response at W12, AS patients were classified as responders and non-responders. RESULTS: PCSK9 was increased in AS patients versus healthy controls (P < 0.001) and osteoarthritis patients (P = 0.006). In AS patients, PCSK9 was positively linked with C-reactive protein (CRP) (P = 0.003) and ASDAS-CRP (P = 0.017), but not with other clinical properties (P > 0.05). Besides, PCSK9 was negatively correlated with interleukin-4 (P = 0.034), positively associated with Th17 cells (P = 0.005) and interleukin-17A (P = 0.014), but did not relate to Th1 cells, interferon-γ, or Th2 cells (all P > 0.05). Additionally, PCSK9 was decreased from W0 to W12 in general AS patients (P < 0.001) and responders (P < 0.001) but remained unchanged in non-responders (P = 0.129). Moreover, PCSK9 was lower at W4 (P = 0.045), W8 (P = 0.008), and W12 (P = 0.004) in responders versus non-responders. Furthermore, the treatment options did not affect the PCSK9 level (P > 0.05). CONCLUSION: Serum PCSK9 is positively associated with disease activity and Th17 cells, while its short-term decline reflects desirable treatment response in AS patients.

On the selection of transmission range in underwater acoustic sensor networks.

Transmission range plays an important role in the deployment of a practical underwater acoustic sensor network (UWSN), where sensor nodes equipping with only basic functions are deployed at random locations with no particular geometrical arrangements. The selection of the transmission range directly influences the energy efficiency and the network connectivity of such a random network. In this paper, we seek analytical modeling to investigate the tradeoff between the energy efficiency and the network connectivity through the selection of the transmission range. Our formulation offers a design guideline for energy-efficient packet transmission operation given a certain network connectivity requirement.