Orientation Cues-Aware Facial Relationship Representation for Head Pose Estimation via Transformer.

Head pose estimation (HPE) is an indispensable upstream task in the fields of human-machine interaction, self-driving, and attention detection. However, practical head pose applications suffer from several challenges, such as severe occlusion, low illumination, and extreme orientations. To address these challenges, we identify three cues from head images, namely, critical minority relationships, neighborhood orientation relationships, and significant facial changes. On the basis of the three cues, two key insights on head poses are revealed: 1) intra-orientation relationship and 2) cross-orientation relationship. To leverage two key insights above, a novel relationship-driven method is proposed based on the Transformer architecture, in which facial and orientation relationships can be learned. Specifically, we design several orientation tokens to explicitly encode basic orientation regions. Besides, a novel token guide multi-loss function is accordingly designed to guide the orientation tokens as they learn the desired regional similarities and relationships. Experimental results on three challenging benchmark HPE datasets show that our proposed TokenHPE achieves state-of-the-art performance. Moreover, qualitative visualizations are provided to verify the effectiveness of the token-learning methodology.

A rehabilitation robot control framework with adaptation of training tasks and robotic assistance.

Robot-assisted rehabilitation has exhibited great potential to enhance the motor function of physically and neurologically impaired patients. State-of-the-art control strategies usually allow the rehabilitation robot to track the training task trajectory along with the impaired limb, and the robotic motion can be regulated through physical human-robot interaction for comfortable support and appropriate assistance level. However, it is hardly possible, especially for patients with severe motor disabilities, to continuously exert force to guide the robot to complete the prescribed training task. Conversely, reduced task difficulty cannot facilitate stimulating patients' potential movement capabilities. Moreover, challenging more difficult tasks with minimal robotic assistance is usually ignored when subjects show improved performance. In this paper, a control framework is proposed to simultaneously adjust both the training task and robotic assistance according to the subjects' performance, which can be estimated from the users' electromyography signals. Concretely, a trajectory deformation algorithm is developed to generate smooth and compliant task motion while responding to pHRI. An assist-as-needed (ANN) controller along with a feedback gain modification algorithm is designed to promote patients' active participation according to individual performance variance on completing the training task. The proposed control framework is validated using a lower extremity rehabilitation robot through experiments. The experimental results demonstrate that the control scheme can optimize the robotic assistance to complete the subject-adaptation training task with high efficiency.

Serum TBK1 levels are correlated with inflammation, optic nerve sheath diameter and intracranial pressure in severe traumatic brain injury patients under deep sedation.

BACKGROUND: Severe traumatic brain injuries (STBIs) cause 1/3-1/2 of trauma-related deaths. Tumor necrosis factor (TNF) receptor-associated factor NF-κB activator (TANK)-binding kinase 1 (TBK1) is a biomarker associated with inflammation, while inflammation is a key promoter of the TBI process. OBJECTIVES: To investigate the clinical significance of TBK1 in STBI patients. MATERIAL AND METHODS: The present prospective observational study included a total of 95 STBI cases diagnosed from October 2019 to October 2021. The values for optic nerve sheath diameter (ONSD) were determined under deep sedation using 2-dimensional gray scale ultrasound. Intracranial pressure (ICP) was also measured. Serum levels of TBK1 and inflammatory factors such as C-reactive protein (CRP), interleukin (IL)-1ß and IL-6 were evaluated with enzyme-linked immunosorbent assay (ELISA). Clinical variables including pathological type, Glasgow Coma Scale (GCS) score, sequential organ failure assessment (SOFA) score, and Acute Physiology and Chronic Health Evaluation II (APACHE II) score were recorded. RESULTS: The levels of TBK1 in the deceased patients were remarkably lower than in the patients who survived. The IL-1ß and IL-6 were markedly elevated in deceased patients compared with survivors, and negatively correlated with serum levels of TBK1. The ONSD and ICP values were significantly higher in the deceased patients than in the patients who survived and were positively correlated with each other, while both were negatively correlated with TBK1 levels. Patients with lower TBK1 expression showed significantly lower GCS scores, higher SOFA and APACHE II scores, as well as a higher 1-month mortality rate. The Kaplan-Meier curve showed that patients with higher TBK1 levels had a higher 1-month survival rate compared with the patients with lower TBK1 levels. Only TBK1 and ONSD were independent risk factors for 1-month mortality in STBI patients. CONCLUSIONS: Lower serum TBK1 levels are associated with higher inflammatory factors, higher ONSD and ICP levels, as well as a poorer prognosis in STBI patients.

Is there an epilepsy belt of high prevalence rate in China?

Background: Epilepsy is one of the leading neurological diseases. Our study is aimed to determine whether there is a focal region of high epilepsy prevalence in China. Methods: All studies published between 1981 and 2020 investigating the prevalence of epilepsy in China were systematically reviewed. The geographical location, sample size, number of cases, urbanization rate, gross domestic product (GDP) per capita, percentage of <15 years old, and medical insurance per capita were derived and analyzed. Criteria for a provincial region of high prevalence was defined as with higher epilepsy prevalence than the average prevalence of epilepsy in China. Results: A total of 60 studies provided data on the prevalence of epilepsy in 29 of 33 provincial regions of China. The average prevalence in China was 1.68 per 1,000, and 12 provincial regions met our criteria for a region of high epilepsy prevalence and constitute an epilepsy belt ranging along the division between the second step and the third step of China. The prevalence in the epilepsy belt was 331.9 per 100,000 population compared with 125.3 per 100,000 in regions outside the belt (P < 0.05). Surprisingly, there was no significant difference in sample size, number of cases, urbanization rate, GDP per capita, percentage of <15 years old, or medical insurance per capita between the regions in and outside the epilepsy belt. Conclusions: An epilepsy belt of high prevalence exists in 12 provincial regions locating along the division between the second step and the third step of China.

Site and Mechanism of Recurrent Pontine Infarction: A Hospital-Based Follow-Up Study.

Although pontine infarction is the most common subtype of posterior circulation stroke, there has been little research focusing on recurrent pontine infarction. Our study aimed to investigate the factors associated with site and mechanism of recurrent pontine infarction. Patients with acute isolated pontine infarction were enrolled and followed up for one year. Lesion topography was determined by diffusion-weighted imaging. Mechanisms were determined based on lesion topography and other vascular, cardiologic and laboratory results. A total of 562 patients with pontine infarction were included, with 67 patients experiencing recurrence during the follow-up period. Forty-one recurrences occurred at the same site as index pontine infarction (41/67, 61.2%). Results indicated that the mechanism of index pontine infarction was significantly associated with the recurrent sites (p = 0.041, OR 2.938, 95% CI 1.044-8.268), and also with the mechanisms of recurrence (p = 0.004, OR 6.056, 95% CI 1.774-20.679). Branch atheromatous disease-induced index pontine infarction was likely to recur at the same site and with the same mechanism. Moreover, if recurrence occurred at the same site, the mechanism was probably the same as that of the index stroke (p = 0.000). Our study may help physicians treat patients with pontine infarction by predicting the site and mechanism of recurrence.

Higher Prevalence of Diabetes in Pontine Infarction than in Other Posterior Circulation Strokes.

BACKGROUND: Pontine infarction is the major subtype of posterior circulation stroke, and diabetes is more common in pontine infarction patients than in anterior circulation stroke patients. Whether the prevalence of diabetes remains homogenous within the posterior circulation stroke population is unclear. The present study is aimed at investigating the prevalence of diabetes in pontine infarction and comparing it to other subtypes of posterior circulation stroke. METHODS: We conducted a multicenter case-control study. Patients with posterior circulation stroke were screened. The subjects were divided into pontine infarction and nonpontine infarction groups. RESULTS: From November 1, 2018, to February 28, 2021, a total of 6145 stroke patients were screened and 2627 patients had posterior circulation strokes. After excluding cardioembolic stroke, as well as its other determined and undetermined causes, 1549 patients with 754 pontine infarctions were included in the analysis. The prevalence of diabetes in the pontine infarction group was higher than that in the nonpontine infarction group (42.7% vs. 31.4%, P < 0.05). After adjusting for confounding factors, diabetes was an independent risk factor for pontine infarction (OR 1.63, 95% CI 1.27-2.09, P < 0.05). For small vessel occlusion, diabetes was also more common in the pontine infarction group (43.2% vs. 30.0%, P < 0.05). Multivariate analysis also showed that diabetes was an independent risk factor for pontine infarction (OR 1.80, 95% CI 1.32-2.46, P < 0.05). CONCLUSION: In comparison with the nonpontine infarction subtype of posterior circulation stroke, patients with pontine infarction had a higher prevalence of diabetes, and diabetes was an independent risk factor for pontine infarction.

Learning From Images: A Distillation Learning Framework for Event Cameras.

Event cameras have recently drawn massive attention in the computer vision community because of their low power consumption and high response speed. These cameras produce sparse and non-uniform spatiotemporal representations of a scene. These characteristics of representations make it difficult for event-based models to extract discriminative cues (such as textures and geometric relationships). Consequently, event-based methods usually perform poorly compared to their conventional image counterparts. Considering that traditional images and event signals share considerable visual information, this paper aims to improve the feature extraction ability of event-based models by using knowledge distilled from the image domain to additionally provide explicit feature-level supervision for the learning of event data. Specifically, we propose a simple yet effective distillation learning framework, including multi-level customized knowledge distillation constraints. Our framework can significantly boost the feature extraction process for event data and is applicable to various downstream tasks. We evaluate our framework on high-level and low-level tasks, i.e., object classification and optical flow prediction. Experimental results show that our framework can effectively improve the performance of event-based models on both tasks by a large margin. Furthermore, we present a 10K dataset (CEP-DVS) for event-based object classification. This dataset consists of samples recorded under random motion trajectories that can better evaluate the motion robustness of the event-based model and is compatible with multi-modality vision tasks.

RGBD Salient Object Detection via Disentangled Cross-modal Fusion.

Depth is beneficial for salient object detection (SOD) for its additional saliency cues. Existing RGBD SOD methods focus on tailoring complicated cross-modal fusion topologies, which although achieve encouraging performance, are with a high risk of over-fitting and ambiguous in studying cross-modal complementarity. Different from these conventional approaches combining cross-modal features entirely without differentiating, we concentrate our attention on decoupling the diverse cross-modal complements to simplify the fusion process and enhance the fusion sufficiency. We argue that if cross-modal heterogeneous representations can be disentangled explicitly, the cross-modal fusion process can hold less uncertainty, while enjoying better adaptability. To this end, we design a disentangled cross-modal fusion network to expose structural and content representations from both modalities by cross-modal reconstruction. For different scenes, the disentangled representations allow the fusion module to easily identify, and incorporate desired complements for informative multi-modal fusion. Extensive experiments show the effectiveness of our designs and a large outperformance over state-of-the-art methods.

Interaction between worsening cognitive function and deteriorating functional status on depressive symptoms among Chinese community-dwelling elders.

AIM: Cognitive impairment and functional deterioration are common in later life and often co-occur with depressive symptoms (DS). This study aims to examine the individual effects and possible interaction between worsening cognitive function (CF) and deteriorating functional status (FS) on DS using large sample, longitudinal data. METHODS: Elderly people who completed the baseline survey of China Health and Retirement Longitudinal Study (CHARLS 2011) and the third wave survey (2015) were included. A multivariable logistic regression model was used to assess the individual effects. The relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP) and synergy index (SI) were calculated to evaluate the additive interaction. RESULTS: Worsening CF and deteriorating FS were associated with the increase in DS, while unchanged or improved CF and FS were associated with the decrease in DS. In addition, decreased (increased) FS led to more severe (improved) DS than decreased (increased) CF. The additive interaction between worsening CF and deteriorating FS on the increase in DS was significant. The estimates and 95% CI of the RERI, AP and SI were 0.626 (0.061, 1.190), 0.222 (0.042, 0.402) and 1.526 (1.016, 2.291) respectively. CONCLUSIONS: Both worsening CF and deteriorating FS have positive interactions with the increase in DS. It is vital to focus on DS of elderly people with worsening CF and/or FS and to adopt interventions. Geriatr Gerontol Int 2020; 20: 343-347.

Discriminative Cross-Modal Transfer Learning and Densely Cross-Level Feedback Fusion for RGB-D Salient Object Detection.

This article addresses two key issues in RGB-D salient object detection based on the convolutional neural network (CNN). 1) How to bridge the gap between the "data-hungry" nature of CNNs and the insufficient labeled training data in the depth modality? 2) How to take full advantages of the complementary information among two modalities. To solve the first problem, we model the depth-induced saliency detection as a CNN-based cross-modal transfer learning problem. Instead of directly adopting the RGB CNN as initialization, we additionally train a modality classification network (MCNet) to encourage discriminative modality-specific representations in minimizing the modality classification loss. To solve the second problem, we propose a densely cross-level feedback topology, in which the cross-modal complements are combined in each level and then densely fed back to all shallower layers for sufficient cross-level interactions. Compared to traditional two-stream frameworks, the proposed one can better explore, select, and fuse cross-modal cross-level complements. Experiments show the significant and consistent improvements of the proposed CNN framework over other state-of-the-art methods.

Temporal precedence of cognitive function and functional abilities: A latent difference score model of the Chinese community-dwelling elders.

OBJECTIVES: Little research has explored how cognitive function and activities of daily living (ADL) affect each other over time. In addition, no current finding provides a clear hint to the temporal precedence between them. The present study tries to address these limitations of prior studies by utilizing a longitudinal data and advanced statistical modeling. METHODS: This study analyzed the data from the China Health and Retirement Longitudinal Study (CHARLS), a prospective observational study performed every 2 years for a total of three waves between 2011 and 2015 using a multistage probability sampling. Cognitive function was measured on the basis of three aspects of cognitive performance. Functional abilities were assessed using six types of activities of ADL and five types of instrumental ADL (IADL). Latent difference score modeling was employed to investigate the temporal precedence between cognitive function and ADL. RESULTS: The best fitting model indicates poor cognitive function precede worsening in ADL function, whereas the current findings did not support that poor ADL predate the cognition decline or reciprocal influence hypotheses. CONCLUSIONS: The elderly with poor cognitive function may be more vulnerable to deterioration in ADL. Findings underscore the importance of early screening for cognitive function among the elderly as the key strategy to prevent further ADL impairment and keep independence.

A Multi-Mode Rehabilitation Robot With Magnetorheological Actuators Based on Human Motion Intention Estimation.

Lower extremity paralysis has become common in recent years, and robots have been developed to help patients recover from it. This paper presents such a robotic system that allows for two working modes, the robot-active mode and human-active mode. The robot is designed to be equipped with magnetorheological (MR) actuators that have the advantages of high torque, fast response, flexible controllability, low power consumption and safety guarantee. The design and characteristics of the MR actuator are introduced. In the robot-active mode, the MR actuator works as a clutch to transfer the torque to the robotic joint safely. In the human-active mode, the MR actuator functions as a brake to provide resistance to help strengthen muscles. The working mode is determined by the human motion intention, which is detected via the skin surface electromyography (EMG) signals. The human-robot interaction torques are estimated using the EMG-driven impedance model. The biomechanical analysis based on AnyBody Modeling System (AMS) is used to help optimization. Then, an adaptive control method is proposed to realize the assist-as-needed (AAN) training strategy, where the robot can switch between these two modes. Experiments are conducted to validate the proposed design.

Discontinuation and switching patterns of tumour necrosis factor inhibitors (TNFis) in TNFi-naive and TNFi-experienced patients with psoriatic arthritis: an observational study from the US-based Corrona registry.

Objective: To examine patterns of tumour necrosis factor inhibitor (TNFi) use in TNFi-naive and TNFi-experienced patients with psoriatic arthritis (PsA) in the USA. Methods: All patients aged ≥18 years with PsA enrolled in the Corrona Psoriatic Arthritis/Spondyloarthritis Registry who initiated a TNFi (index therapy) between March 2013 and January 2017 and had ≥1 follow-up visit were included. Times to and rates of discontinuation/switch of the index TNFi were compared between TNFi-naive and TNFi-experienced cohorts. Patient demographics and disease characteristics at the time of TNFi initiation (baseline) were compared between cohorts and between patients who continued versus discontinued their index TNFi by the first follow-up visit within each cohort. Results: This study included 171 TNFi-naive and 147 TNFi-experienced patients (total follow-up, 579.2 person-years). Overall, 75 of 171 TNFi-naive (43.9%) and 80 of 147 TNFi-experienced (54.4%) patients discontinued their index TNFi; 33 of 171 (19.3%) and 48 of 147 (32.7%), respectively, switched to a new biologic. TNFi-experienced patients had a shorter time to discontinuation (median, 20 vs 27 months) and were more likely to discontinue (p=0.03) or switch (p<0.01) compared with TNFi-naive patients. Among those who discontinued, 49 of 75 TNFi-naive (65.3%) and 59 of 80 TNFi-experienced (73.8%) patients discontinued by the first follow-up visit; such patients showed a trend towards higher baseline disease activity compared with those who continued. Conclusions: The results of this real-world study can help inform treatment decisions when selecting later lines of therapy for patients with PsA.

miR-15b-5p targeting amyloid precursor protein is involved in the anti-amyloid eflect of curcumin in swAPP695-HEK293 cells.

Curcumin exerts a neuroprotective effect on Alzheimer's disease; however, it is not known whether microRNAs are involved in this protective effect. This study was conducted using swAPP695-HEK293 cells as an Alzheimer's disease cell model. swAPP695-HEK293 cells were treated with 0, 0.5, 1, 2, 5, and 10 µM curcumin for 24 hours. The changes in miR-15b-5p, miR-19a-3p, miR-195-5p, miR-101-3p, miR-216b-5p, miR-16-5p and miR-185-5p expression were assessed by real-time quantitative polymerase chain reaction. The mRNA and protein levels of amyloid precursor protein, amyloid-ß40 and amyloid-ß42 were evaluated by quantitative real-time polymerase chain reaction, western blot assays and enzyme-linked immunosorbent assays. swAPP695-HEK293 cells were transfected with miR-15b-5p mimic, or treated with 1 µM curcumin 24 hours before miR-15b-5p inhibitor transfection. The effects of curcumin on amyloid precursor protein, amyloid-ß40 and amyloid-ß42 levels were evaluated by western blot assays and enzyme-linked immunosorbent assay. Luciferase assays were used to analyze the interaction between miR-15b-5p and the 3'-untranslated region of amyloid precursor protein. The results show that amyloid precursor protein and amyloid-ß expression were enhanced in swAPP695-HEK293 cells compared with HEK293 parental cells. Curcumin suppressed the expression of amyloid precursor protein and amyloid-ß and up-regulated the expression of miR-15b-5p in swAPP695-HEK293 cells. In addition, we found a negative association of miR-15b-5p expression with amyloid precursor protein and amyloid-ß levels in the curcumin-treated cells. Luciferase assays revealed that miR-15b-5p impaired the luciferase activity of the plasmid harboring the 3'-untranslated region of amyloid precursor protein. These findings indicate that curcumin down-regulates the expression of amyloid precursor protein and amyloid-ß in swAPP695-HEK293 cells, which was partially mediated by miR-15b-5p via targeting of the 3'-untranslated region of amyloid precursor protein.

Therapy with Biologic Agents After Diagnosis of Solid Malignancies: Results from the Corrona Registry.

OBJECTIVE: Guidelines suggest that rheumatoid arthritis (RA) patients with previously treated solid malignancy may be treated as patients without such history. The recommendation is based on limited evidence, and rheumatologists and patients are frequently hesitant to start or continue biologic therapy after a cancer diagnosis. The objective of this study was to describe biologic use in real-world patients with RA following a malignancy diagnosis. METHODS: RA patients enrolled in the Corrona registry and diagnosed with solid malignancy with at least 1 followup visit within 12 months after diagnosis were included in this analysis. The proportion of patients continuing or initiating biological/targeted synthetic disease-modifying antirheumatic drug (bDMARD/tsDMARD) after diagnosis was estimated. Median time to initiation of bDMARD/tsDMARD after diagnosis was calculated using the Kaplan-Meier method and the proportion initiating biologic treatment in 6-month time intervals was estimated using the life-table method. RESULTS: There were 880 patients who met inclusion criteria with 2585 person-years total followup time postdiagnosis. Of those, 367 (41.7%) were treated with bDMARD/tsDMARD within 12 months preceding malignancy, of whom 270 (30.7%) were taking such agents at first postdiagnosis visit. Forty-four (5%) switched biologic agents within 36 months and an additional 90 patients (10.2%) started a biologic. The majority of bDMARD/tsDMARD initiations during followup was a tumor necrosis factor inhibitor (TNFi; 53.5%). CONCLUSION: In real-world practice, nearly one-third of RA patients with a cancer diagnosis were treated with systemic therapy in the immediate visit after malignancy diagnosis and a considerable percentage of malignancy survivors initiated biologic therapy within 3 years. The majority of bDMARD/tsDMARD initiations post-malignancy diagnosis was a TNFi.

Three-stream Attention-aware Network for RGB-D Salient Object Detection.

Previous RGB-D fusion systems based on convolutional neural networks (CNNs) typically employ a two-stream architecture, in which RGB and depth inputs are learnt independently. The multi-modal fusion stage is typically performed by concatenating the deep features from each stream in the inference process. The traditional two-stream architecture might experience insufficient multi-modal fusion due to two following limitations: (1) The cross-modal complementarity is rarely studied in the bottom-up path, wherein we believe the crossmodal complements can be combined to learn new discriminative features to enlarge the RGB-D representation community; (2) The cross-modal channels are typically combined by undifferentiated concatenation, which appears ambiguous to select cross-modal complementary features. In this work, we address these two limitations by proposing a novel three-stream attention-aware multi-modal fusion network. In the proposed architecture, a cross-modal distillation stream, accompanying the RGB-specific and depth-specific streams, is introduced to extract new RGB-D features in each level in the bottom-up path. Furthermore, the channel-wise attention mechanism is innovatively introduced to the cross-modal cross-level fusion problem to adaptively select complementary feature maps from each modality in each level. Extensive experiments report the effectiveness of the proposed architecture and the significant improvement over state-of-theart RGB-D salient object detection methods.

Liberating carotid arteries: measuring arterial pressure through femoral artery in mice.

Researches involving arterial pressure measurements in mice have primarily relied on carotid arterial catheterization. However, in some circumstances, measuring arterial pressure through the carotid arterial impairs accuracy. This study was aimed to evaluate whether femoral artery could displace carotid artery for the blood pressure (BP) measurements in mice. Fifty-six Swiss mice (n = 14 in each group) were randomized into four groups: control, left femoral artery, right femoral artery, and union group, in which BP was measured through left carotid, left femoral, right femoral artery, and simultaneously from right femoral artery and left carotid artery, respectively. Arterial pressure was recorded for 5 min after catheterization. There was no significant difference of the success rate and mortality rate among four groups (P > 0.05), and no obvious difference (P > 0.05) of catheterization time among the first three groups. For intergroup comparison of arterial pressure, there was no significant difference (P > 0.05) of the systolic blood pressure (SBP), diastolic BP, mean arterial pressure, and pulse pressure among the first three groups. For intragroup comparison, SBP, diastolic blood pressure (DBP), mean arterial pressure (MAP) monitored from right femoral artery were similar (P > 0.05) with those from left carotid artery, with significantly positive correlation. The mean values of difference of SBP, DBP, and MAP were -1.3, 1.2, and 0.5 mmHg, respectively. Our results indicated that femoral artery catheterization could be a safe, feasible, reliable, and accuracy alternative for the direct measurement of arterial pressure in anesthesia mice.

Blind Poissonian reconstruction algorithm via curvelet regularization for an FTIR spectrometer.

An FTIR spectrometer often suffers from common problems of band overlap and Poisson noises. In this paper, we show that the issue of infrared (IR) spectrum degradation can be considered as a maximum a posterior (MAP) problem and solved by minimized a cost function that includes a likelihood term and two prior terms. In the MAP framework, the likelihood probability density function (PDF) is constructed based on the observed Poisson noise model. A fitted distribution of curvelet transform coefficient is used as spectral prior PDF, and the instrument response function (IRF) prior is described based on a Gauss-Markov function. Moreover, the split Bregman iteration method is employed to solve the resulting minimization problem, which highly reduces the computational load. As a result, the Poisson noises are perfectly removed, while the spectral structure information is well preserved. The novelty of the proposed method lies in its ability to estimate the IRF and latent spectrum in a joint framework, thus eliminating the degradation effects to a large extent. The reconstructed IR spectrum is more convenient for extracting the spectral feature and interpreting the unknown chemical or biological materials.

Delayed Treatment Acceleration in Patients with Rheumatoid Arthritis Who Have Inadequate Response to Initial Tumor Necrosis Factor Inhibitors: Data from the Corrona Registry.

BACKGROUND: The implementation of treat-to-target principles in rheumatoid arthritis (RA) has not been fully investigated in patients with inadequate response to tumor necrosis factor (TNF) inhibitor treatment. OBJECTIVES: To evaluate the prevalence of an inadequate response to initial TNF inhibitor treatment at 6 and 12 months among patients with RA in a real-world patient registry, as well as the delay in therapy adjustment and its impact on disease activity and patient-reported outcome (PRO) measures. METHODS: This analysis is based on data of patients with moderate or severe disease activity (Clinical Disease Activity Index [CDAI] score >10) who were included in the Consortium of Rheumatology Researchers of North America (Corrona) RA registry, a prospective, observational database. The patients had never received treatment with a biologic disease-modifying antirheumatic drug (DMARD) and had initiated treatment with a TNF inhibitor (adalimumab, certolizumab pegol, etanercept, golimumab, or infliximab) between October 2001 and December 2014. We evaluated treatment response (CDAI score ≤10), select PRO measures, and treatment changes at 6 months. Patients who had an inadequate response to TNF inhibitor therapy at 6 months and continued to use their initial TNF inhibitor were evaluated again at 12 months. RESULTS: This retrospective analysis included 2282 patients. At 6 months, 1732 (75.9%) of the patients continued to use their initial TNF inhibitor; of these, 803 (46.4%) patients had an inadequate response to treatment. Of the 803 patients who had an inadequate response at 6 months, 488 (60.8%) continued their initial treatment at 12 months. Of these 488 patients, 315 (64.5%) had an inadequate response at 12 months, and 173 (35.5%) had a response. Numerically greater improvements in all PRO measures were observed for patients who responded to therapy compared with patients with an inadequate response. CONCLUSIONS: In this real-world analysis of data from the Corrona RA registry, a considerable proportion of patients with RA had an inadequate response to the initial TNF inhibitor therapy at 6 and 12 months. Many patients continued to have moderate or high disease activity, without accelerating treatment (eg, addition or increase in the dose of concurrent conventional synthetic DMARDs or a TNF inhibitor), contrary to treat-to-target principles, thus remaining at risk for accumulating joint damage and disability.

Vascular endothelial growth factor aggravates cerebral ischemia and reperfusion-induced blood-brain-barrier disruption through regulating LOC102640519/HOXC13/ZO-1 signaling.

BACKGROUND/OBJECTIVE: Vascular endothelial growth factor (VEGF) has been recognized to be a potential pharmaceutical target for treating ischemic stroke, but its severe side effects hinder its widely application. Here, the present study was designed to investigate the effects of VEGF on blood-brain-barrier (BBB) disruption and the underlying mechanisms. METHODS: A mouse model of middle cerebral artery occlusion (MCAO) was constructed and treated with or without VEGF. Meanwhile, mice brain microvascular endothelial cells in co-culture with astrocytes were subjected to 1, 2 and 4 h oxygen-glucose deprivation followed by 24 h of reperfusion (OGD/R) in the absence or presence of VEGF. The mRNA and protein expression were assessed by real-time PCR and Western blotting. Fluorescence in situ hybridization (FISH) was utilized to validate LOC102640519 expression in OGD/R cell models. Chromatin Immunoprecipitation (ChIP) assay was used to confirm the regulatory mechanism of LOC102640519 to HOXC13. Interactions between HOXC13 and ZO-1 were measured by a luciferase reporter assay and RNA pull down assay. RESULTS: Our results showed that administration of VEGF significantly aggravated BBB by upregulating LOC102640519 and HOXC13 expression in vitro and vitro model of cerebral ischemia. Furthermore, LOC102640519 positively regulated the expression of HOXC13, thus negatively regulated the expression of ZO-1, Occludin and Claudin-5 in OGD/R model in the absence or presence of VEGF. CONCLUSIONS: VEGF aggravated BBB disruption after cerebral I/R-induced injury probably by increasing LOC102640519 and HOXC13 through inhibition of ZO-1, Occludin and Claudin-5.