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This study aimed to generate the health state classification system (HCS) of a condition-specific preference-based measure to capture the health-related quality of life (HRQoL) of patients with myasthenia gravis (MG) from the 15-item Myasthenia Gravis Quality of Life Scale (MG-QoL15r). An HCS was derived from the MG-QoL15r in a large sample of 1739 patients with MG based on psychometric analysis, including factor analysis, item response theory analysis, and discussions with experts. Reliability, construct and convergent validity, and item fit of the HCS were further assessed using another sample. The HCS has six dimensions: social activity, hobbies and fun activities, meeting family needs, work performance, mobility, and emotion, and it demonstrates good internal consistency reliability. The unidimensionality of the HCS was confirmed using confirmatory factor analysis. Satisfied convergent validity was supported by a significant association with the 12-item Short Form Survey (SF-12). Based on a solid process of development and consultations with clinical professionals and patients, a valid MG-specific preference-based measure, MGQoL-6D, was developed. Further research will estimate the local preference weight to support the MG-related cost–utility analysis. A new condition-specific health state classification system (HCS) named Myasthenia gravis Quality of Life Scale (MGQoL-6D) is proposed. MGQoL-6D classifies MG health states as a combination of six dimensions with three response levels. The dimensions of the HCS are social activity, hobbies and fun activity, family needs, work performance, mobility, and emotion. The HCS and the upcoming value set of the MGQoL-6D could support the cost-effectiveness analysis of MG-related clinical and rehabilitated interventions. [ABSTRACT FROM AUTHOR]

To evaluate the psychometric properties of the Chinese Fear of Cancer Recurrence Inventory (FCRI-C) in follicular lymphoma (FL) survivors. A nationwide cross-sectional study was conducted online between July and September 2020. The following psychometric properties of the FCRI-C were evaluated: construct, convergent, and discriminant validity, and reliability. Item variance was assessed using differential item functioning (DIF). A short version of the FCRI-C was developed using a two-parameter item response theory (IRT) model. The patterns of response scale, item fit, and item information were assessed. The receiver operating characteristic (ROC) curve was used to determine the clinical cut-off point for the FCRI-C. A total of 326 FL survivors completed the questionnaire. The confirmatory factor analysis supported the bi-factor structure of the FCRI-C. The IRT analysis confirmed a 10-item short version of the FCRI-C. Satisfactory convergent and discriminant validity were underpinned by a priori hypotheses. Cronbach's alpha of 0.95 and intraclass correlation coefficient of 0.82 indicated good internal consistency and test–retest reliability. The ROC curve determined a cut-off point of 83 and 20 for the full and short versions, respectively. The FCRI-C used to measure and screen the levels of FCR in Chinese FL survivors was found to be valid and reliable. The Chinese Fear of Cancer Recurrence Inventory (FCRI-C) is a reliable and valid measure to evaluate the fear of cancer recurrence (FCR) in follicular lymphoma survivors. The short version of the FCRI-C provides a rapid screening tool for the clinical detection of FCR in patients. The cut-off point of the FCRI-C could differentiate patients between "high" and "low" levels of FCR in clinical practice. [ABSTRACT FROM AUTHOR]

Scribble annotations have recently become popular in video salient object detection. Previous methods only focus on utilizing shallow feature consistency for more integral predictions. However, there is potential for consistency between cross-frame deep features to be used to help regularize saliency predictions better. Besides, we have observed that leveraging saliency predictions as pseudo-supervision signals yields notable improvements in extracting both intra-frame and cross-frame deep features. This, in turn, leads to more precise and detailed object structural information. Thus, we propose a cross-frame feature-saliency mutual reinforcing training process to assist scribble annotations for integral video saliency predictions. Specifically, we design a cross-frame feature regularization head, which leverages intra-frame and cross-frame deep feature consistency to regularize saliency predictions as auxiliary supervision. Then, to help obtain more accurate feature consistency, we design a cross-frame saliency regularization head, where predicted saliency values are used as pseudo-supervision signals to acquire better feature consistency. In this way, our cross-frame feature and saliency regularization heads can benefit from each other to help the network learn more accurately. Extensive experiments show that our method can achieve better performances than the previous best methods. The project is available at https://github.com/muchengxue0911/CFMR. • A mutual reinforcing process is proposed to learn comprehensive object structure. • Intra-/cross-frame feature consistency is deployed to supervise saliency predictions. • Predicted saliency values are used to help build a more accurate feature consistency. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma is a common and highly lethal tumour. The tumour microenvironment (TME) plays an important role in the progression and metastasis of hepatocellular carcinoma (HCC). A cell death mechanism, termed NETosis, has been found to play an important role in the TME of HCC. This review article focuses on the role of NETosis in the TME of HCC, a novel form of cell death in which neutrophils capture and kill microorganisms by releasing a type of DNA meshwork fibres called "NETs". This process is associated with neutrophil activation, local inflammation and cytokines. The study suggests that NETs play a multifaceted role in the development and metastasis of HCC. The article also discusses the role of NETs in tumour proliferation and metastasis, epithelial-mesenchymal transition (EMT), and surgical stress. In addition, the article discusses the interaction of NETosis with other immune cells in the TME and related therapeutic strategies. A deeper understanding of NETosis can help us better understand the complexity of the immune system and provide a new therapeutic basis for the treatment and prevention of HCC. In conclusion, NETosis is important in the TME of liver. NETs have been shown to contribute to the progression and metastasis of liver cancer. The interaction between NETosis and immune cells in the TME, as well as related therapies, are important areas of research. • The uniqueness of the liver tumour microenvironment is analysed. • Introduction to the process of Netosis. • Mechanisms of tumour invasion facilitated by Neutrophil Extracellular Traps. • Extracellular Traps interact with immune cells, affecting liver cancer progression. • Targeted therapy for Neutrophil Extracellular Traps. [ABSTRACT FROM AUTHOR]

Summary: Objective: To evaluate the effectiveness of a 9‐month school‐based adapted physical activity (APA) program for reducing weight among adolescents with intellectual disability (ID). Methods: In this randomized controlled trial, adolescents with ID, aged 12–18 years, who were overweight/or with obesity were randomly assigned into intervention and control groups. The APA intervention consisted of aerobic and resistance exercises with an overall moderate intensity and was delivered at a frequency of two sessions per week for 9 months. Changes in body mass index (BMI, primary outcome) and changes in BMIz, weight, percent body fat, waist circumference and waist‐to‐height ratio (secondary outcomes) were examined using general linear models. Results: In total 61 subjects (39 in the intervention and 22 in the control) completed the study and were included in the analyses. At 9 months, the intervention group exhibited a reduced BMI of −0.66 kg/m2 (95% CI −1.06 to −0.25 kg/m2, p = 0.002), while a significant increase in BMI was observed in the control group. A significant post‐intervention between‐group difference in change in BMI (−1.31 kg/m2 [95% CI −1.99 to −0.63], p < 0.01) was found in favour of the intervention group. Similar results were also observed for all secondary outcomes. Conclusions: This study provides evidence that a 9‐month APA intervention induced clinically meaningful effects on weight loss in adolescents with ID. [ABSTRACT FROM AUTHOR]

Video object segmentation, aiming to segment the foreground objects given the annotation of the first frame, has been attracting increasing attentions. Many state-of-the-art approaches have achieved great performance by relying on online model updating or mask-propagation techniques. However, most online models require high computational cost due to model fine-tuning during inference. Most mask-propagation based models are faster but with relatively low performance due to failure to adapt to object appearance variation. In this paper, we are aiming to design a new model to make a good balance between speed and performance. We propose a model, called NPMCA-net, which directly localizes foreground objects based on mask-propagation and non-local technique by matching pixels in reference and target frames. Since we bring in information of both first and previous frames, our network is robust to large object appearance variation, and can better adapt to occlusions. Extensive experiments show that our approach can achieve a new state-of-the-art performance with a fast speed at the same time (86.5% IoU on DAVIS-2016 and 72.2% IoU on DAVIS-2017, with speed of 0.11s per frame) under the same level comparison. Source code is available at https://github.com/siyueyu/NPMCA-net. • NPMCA-net strikes a good balance between accuracy and running speed. • Our method aggregates multi-frame information with high level interpretability. • Our methods achieves new state-of-the-art performances on reported datasets. [ABSTRACT FROM AUTHOR]

Background: Regular participation in moderate-to-vigorous physical activity (MVPA) is related to decreased risk of morbidity and mortality. Among working populations, lack of MVPA may also be a risk factor for absenteeism and presenteeism. Both traditional workplace-based and web-based interventions have been suggested as being effective in promoting participation MVPA, health-related outcomes, and work-related productivity. However, several challenges limit their application in real world contexts. A 'blended' intervention approach combining the two intervention strategies is proposed to overcome these limitations. The proposed intervention aims to utilize the blended approach to increase participation in MVPA, health-related outcomes, and work productivity among inactive workers.Methods: The study will comprise of a three-group cluster randomized controlled trial (cluster-RCT), comprising a three-month actual intervention and a nine-month behavioral follow-up period. The three groups will be: a web-based intervention group, a blended intervention group combining the web-based components with face-to-face workshops and posters, and a control group. Physically inactive office employees (N = 495) from 33 companies (i.e., clusters) will be recruited and randomly assigned to the three groups by cluster randomization. The intervention mapping (IM) framework will be used for selecting and applying effective health behavioral theories and behavioral change techniques (BCTs) to the development, implementation and assessment of the intervention, which will be personally tailored. The primary outcome variable will be objectively-measured MVPA using an accelerometer. Secondary outcomes will consist of indices of health including adiposity, blood pressure, blood sugar, blood lipids, self-reported depression, anxiety, stress, health-related quality of life and work-related variables including absenteeism and presenteeism.Discussion: The proposed study adopts a robust blended intervention approach that is expected to overcome challenges in applying workplace-based and web-based interventions separately and yield larger effects in promoting MVPA participation, health-related outcomes and work productivity. Improvements in work productivity outcomes will be of particular interest to employers. If more effective, the new blended intervention has the potential to be implemented on a larger scale to benefit workplace populations.Trial Registration: The trial is prospectively registered at the ClinicalTrials.gov PRS (Trial ID: NCT04391270; Date of First Posted: May 18, 2020). [ABSTRACT FROM AUTHOR]

• We propose a weight-guided class complementing framework to mitigate the gradient shift issue caused by unsampled classes in long-tailed scenario, including a slot-based class complementing strategy and a weight-guided feature mining loss. • We further introduce a weight refining scheme at the end of training process, which can remove the bias term in our weight-guided class complementing framework caused by long-tailed distribution. • Our plug-and-play weight-guided class complementing framework can be easily implemented to different existing approaches, achieving significant improvement on various benchmarks with new state-of-the-art performances. Real-world data are often long-tailed distributed and have plenty classes. This characteristic leads to a significant performance drop for various models. One reason behind that is the gradient shift caused by unsampled classes in each training iteration. In this paper, we propose a W eight- G uided C lass C omplementing framework to address this issue. Specifically, this framework first complements the unsampled classes in each training iteration by using a dynamic updated data slot. Then, considering the over-fitting issue caused by class complementing, we utilize the classifier weights as learned knowledge and encourage the model to discover more class specific characteristics. Finally, we design a weight refining scheme to deal with the long-tailed bias existing in classifier weights. Experimental results show that our framework can be implemented upon different existing approaches effectively, achieving consistent improvements on various benchmarks with new state-of-the-art performances. Codes will be released. [ABSTRACT FROM AUTHOR]

Objective To identify predictors for lupus low disease activity state (LLDAS), early-achieved LLDAS and long-term disease activity, and to refine a prognostic stratification tool for use in active SLE patients. Method A total of 245 active SLE patients were enrolled, followed up quarterly from 2014 to 2016. LLDAS-50 was defined as the maintenance of LLDAS for ≥50% of the observed time. LLDAS at 3 months after cohort entry (LLDAS-3mo) was considered an early-achieved LLDAS. Multivariate analysis was performed to identify predictors for LLDAS, early-achieved LLDAS and long-term disease activity. Based on the factors associated with LLDAS, a prognostic stratification tool for LLDAS was established. Results The 2-year probability of achieving LLDAS was 62.9% (154/245). Multivariate analysis-determined renal involvement, haematological involvement and hypocomplementaemia were negative predictors for achieving LLDAS and LLDAS-50. In multivariate logistic analysis, antiphospholipid antibodies positivity, hypocomplementaemia, renal involvement and haematological involvement were identified as negative predictors for achieving LLDAS-3mo. LLDAS-3mo (P  < 0.0001; risk ratio: 47.694; 95% CI: 13.776, 165.127) was a strong predictor for LLDAS-50. The probability of achieving LLDAS, LLDAS-50 and LLDAS-3mo were 88.9% (32/36), 69.4% (25/36) and 41.7% (15/36) in the low-risk group, 65% (65/100), 51.0% (51/100) and 32.0% (32/100) in intermediate-risk group, and 52.8% (57/108), 27.8% (30/108) and 13.0% (14/108) in high-risk group respectively. Significant differences (P  < 0.0001) were observed in the LLDAS Kaplan–Meier estimates for the three risk groups based on the identified risk factors. Conclusion Renal involvement, haematological involvement and hypocomplementaemia were negative predictors of LLDAS achievement and maintenance. LLDAS-3mo was a positive predictor for the long-term sustainment of LLDAS. [ABSTRACT FROM AUTHOR]

Background: Poor health‐related physical fitness (HRPF) and overweight and obesity are common health problems for children with intellectual disability. This study aimed to review existing lifestyle intervention studies, and identify effective strategies for this population. Methods: A systematic search was undertaken in three databases. The random‐effects model was used to pool the weighted results by inverse variance methods, and the I2 statistic was applied to assess heterogeneity among the included studies. Results: Most of the identified interventions (27/29) adopted physical activity (PA). For obesity‐related outcomes, the results showed no significant effect of PA studies on reducing obesity. For HRPF outcomes, significant effects were found on 6‐min walk distance (51.86 m, 95% CI [16.49, 87.22], p <.05). Conclusions: PA is the predominant intervention component adopted and may contribute to improving cardiopulmonary fitness; but the lack of research limits our ability to draw any confirmed conclusion on obesity‐related outcomes and other HRPF outcomes. [ABSTRACT FROM AUTHOR]

Image-text matching aims to bridge vision and language so as to match the instance of one modality with the instance of another modality. Recent years have seen considerable progress in the research area by exploring local alignment between image regions and sentence words. However, there are still open questions regarding how to learn modality-invariant feature embeddings and effectively utilize hard negatives in the training set to infer more accurate matching scores. In this paper, we introduce a new approach called Image-Text Modality Contrastive Learning (abbreviated as ITContrast) for image-text matching. Our method addresses these challenges by leveraging a pre-trained vision-language model, OSCAR, which is firstly fine-tuned to obtain visual and textual features. We also introduce a hard negative synthesis module, which capitalizes on the difficulty of negative samples. This module profiles negative samples within a mini-match and generates representative embeddings that reflect their hardness in relation to the anchor sample. A novel cost function is designed to comprehensively integrate the information from positives, negatives and synthesized hard negatives. Extensive experiments on the MS COCO and Flickr30K datasets demonstrate that our approach is effective for image-text matching. [ABSTRACT FROM AUTHOR]

Purpose: The association of chronic lymphocytic leukemia (CLL) with health-related quality of life (HRQoL) is rarely studied globally. This study evaluated the psychometric properties of the EORTC-Chronic Lymphocytic Leukaemia (CLL17 [phase III]) module, a newly developed assessment on CLL patients' HRQoL, among Chinese CLL patients.Methods: The Chinese CLL17, comprised of three subscales (symptom burden [SB], physical condition [PC] and worries/fears [WF]), was provided by the developer team through EORTC. A cross-sectional online survey was conducted to collect data. The classical traditional theory (CTT) and the item response theory (IRT) were used to evaluate the psychometric properties of CLL17. Internal consistency reliability was determined by the Cronbach's alpha and item-total correlation. Dimensionality was verified through confirmatory factor analysis (CFA). Convergent validity was also assessed. The generalized partial credit model was used for the IRT. The difficulty, discrimination, item fit, and differential item functioning (DIF) were calculated to assess the instrument's psychometric properties.Results: In all, 318 patients, aged between 26 and 82 years, completed the questionnaire. A good level of internal reliability was achieved (Cronbach's alpha = 0.92). The item-total correlation coefficient ranged from 0.46 to 0.72. There was a mid-to-high correlation between CLL17 and domains of EQ-5D and QLQ-C30. The IRT model showed a satisfactory homogeneity, item fit and good discrimination of items, except for item 4, 6 and 16 (< 1.0). low information provided by item 16 and 17. SB and PC provided more information with theta > 0, whereas WF provided more information with theta < 0. Item 17 perform inconsistently for respondents from different age groups (DIF).Conclusion: The EORTC-CLL17 Chinese version shows acceptable reliability and validity, making it a valuable instrument to evaluate the impact on the HRQoL of Chinese CLL patients. [ABSTRACT FROM AUTHOR]

Background: Myasthenia gravis (MG), a chronic neuromuscular disorder, can adversely affect patients' health-related quality of life (HRQoL), especially in women. The study aimed to evaluate the difference in HRQoL of women and men MG patients and explore the factors that mediate the relationship between gender and HRQoL.Methods: A cross-sectional study was conducted among 1815 patients with MG in China. The revised 15-item MG quality of life scale (MG-QOL15r) was used to access patients' HRQoL in overall, physical, social and emotional domains. Socio-demographic information, diagnosis and treatment history, comorbidities, social support, active lifestyle and the MG activities of daily living scale (MG-ADL) were recorded and compared between women and men using the Student's t-test and Pearson's Chi-square test. Multivariable regression analyses were conducted to identify independent contributors to HRQoL, especially those affecting different gender.Results: On average, female patients with MG reported a lower MG-QOL15r score than the males (44.49 ± 29.10 vs 49.32 ± 29.18). The association between gender and patients' HRQoL interacted with the number of comorbidities across the overall, physical and social domains of patients. As the number of comorbidities increased, the scores of HRQoL decreased and it was faster among females than the males (p < 0.05). Moreover, unemployment, exacerbation of the disease, and active lifestyle contributed to the patients' HRQoL across all domains. Unemployment (β = - 4.99 [95%CI, - 7.80 to - 2.18], p < 0.001) and exacerbations (β = - 8.49 [95%CI, - 11.43 to - 5.54], p < 0.001) were correlated with poorer HRQoL; while an active lifestyle had a positive impact on HRQoL (β = 0.28 [95%CI, 0.16 to 0.40], p < 0.001).Conclusions: The results indicate that the HRQoL of women MG patients was lower than that of men. The relationship between gender and HRQoL is modulated by the number of comorbidities. Thus, to improve the HRQoL of women MG patients, symptomatic treatments might not be enough, their comorbid conditions should be considered as well. Additionally, employment status, MG exacerbations, and an active lifestyle have been found as determining factors of the patients' HRQoL, which suggests future interventions should cope with these factors to improve their quality of life. [ABSTRACT FROM AUTHOR]