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Article ; Online: A meta-analysis of melanoma risk in idiopathic inflammatory myopathy patients.

Luo, Rui / Xia, Dan / Yu, Siyang

2024

Abstract: Background: Idiopathic inflammatory myopathy (IIM) is a group of chronic acquired autoimmune diseases. The association between IIM and malignancies has been observed for decades. No meta-analysis has been conducted to summarize the relationship between ... ...

Title translation	Metaanalyse zum Melanomrisiko bei Patienten mit idiopathischer inflammatorischer Myopathie.
Abstract	Background: Idiopathic inflammatory myopathy (IIM) is a group of chronic acquired autoimmune diseases. The association between IIM and malignancies has been observed for decades. No meta-analysis has been conducted to summarize the relationship between IIM and melanoma. Herein, we specifically wanted to investigate whether IIM is associated with a higher incidence of melanoma. Methods: We searched both Chinese and English databases (CNKI, VIP, Wanfang, PubMed, Embase, Web of Science) for studies on IIM related to melanoma published up to October 2023. Two independent authors reviewed all literature to identify studies according to predefined selection criteria. Fixed effects models were applied to pool the risk. Publication bias was also evaluated and sensitivity analysis performed. Results: A total of 1660 articles were initially identified but only four cohort studies met the criteria. Thus, 4239 IIM patients were followed up. The pooled overall risk ratio/hazard ratio was 3.08 (95% confidence interval [CI] 0.79-5.37) and the standardized incidence ratio was 6.30 (95% CI 1.59-11.02). Conclusion: The present meta-analysis suggests that IIM patients are at a significantly higher risk of developing melanoma.
Language	English
Publishing date	2024-01-29
Publishing country	Germany
Document type	Journal Article ; Review
ZDB-ID	124985-x
ISSN	1435-1250 ; 0340-1855 ; 0301-6382
ISSN (online)	1435-1250
ISSN	0340-1855 ; 0301-6382
DOI	10.1007/s00393-024-01473-3
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Article: Glycerol Droplet Spreading on Growing Bacillus Subtilis Biofilms.

Luo, Siyang / Liu, Yanan / Luo, Hao / Jing, Guangyin

Micromachines

2023 Volume 14, Issue 3

Abstract: Bacterial biofilm is a three-dimensional matrix composed of a large number of living bacterial individuals. The strong bio-interaction between the bacteria and its self-secreted matrix environment strengthens the mechanical integrity of the biofilm and ... ...

Abstract	Bacterial biofilm is a three-dimensional matrix composed of a large number of living bacterial individuals. The strong bio-interaction between the bacteria and its self-secreted matrix environment strengthens the mechanical integrity of the biofilm and the sustainable resistance of bacteria to antibiotics. As a soft surface, the biofilm is expected to present different dynamical wetting behavior in response to shear stress, which is, however, less known. Here, the spreading of liquid droplet on
Language	English
Publishing date	2023-03-04
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2620864-7
ISSN	2072-666X
ISSN	2072-666X
DOI	10.3390/mi14030599
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Article ; Online: T-TIME: Test-Time Information Maximization Ensemble for Plug-and-Play BCIs.

Li, Siyang / Wang, Ziwei / Luo, Hanbin / Ding, Lieyun / Wu, Dongrui

IEEE transactions on bio-medical engineering

2024 Volume 71, Issue 2, Page(s) 423–432

Abstract: Objective: An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the human brain and a computer. Due to individual differences and non-stationarity of EEG signals, such BCIs usually require a subject- ... ...

Abstract	Objective: An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the human brain and a computer. Due to individual differences and non-stationarity of EEG signals, such BCIs usually require a subject-specific calibration session before each use, which is time-consuming and user-unfriendly. Transfer learning (TL) has been proposed to shorten or eliminate this calibration, but existing TL approaches mainly consider offline settings, where all unlabeled EEG trials from the new user are available. Methods: This article proposes Test-Time Information Maximization Ensemble (T-TIME) to accommodate the most challenging online TL scenario, where unlabeled EEG data from the new user arrive in a stream, and immediate classification is performed. T-TIME initializes multiple classifiers from the aligned source data. When an unlabeled test EEG trial arrives, T-TIME first predicts its labels using ensemble learning, and then updates each classifier by conditional entropy minimization and adaptive marginal distribution regularization. Our code is publicized. Results: Extensive experiments on three public motor imagery based BCI datasets demonstrated that T-TIME outperformed about 20 classical and state-of-the-art TL approaches. Significance: To our knowledge, this is the first work on test time adaptation for calibration-free EEG-based BCIs, making plug-and-play BCIs possible.
MeSH term(s)	Humans ; Algorithms ; Brain-Computer Interfaces ; Electroencephalography ; Brain ; Learning
Language	English
Publishing date	2024-01-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	160429-6
ISSN	1558-2531 ; 0018-9294
ISSN (online)	1558-2531
ISSN	0018-9294
DOI	10.1109/TBME.2023.3303289
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Article ; Online: Effective evaluations of community nursing on rehabilitation for stroke survivors: A meta-analysis.

Mi, Yuqing / Qu, Siyang / Huang, Jingwen / Yin, Yanling / Luo, Sheng / Li, Wei / Wang, Xiang

Geriatric nursing (New York, N.Y.)

2024 Volume 57, Page(s) 80–90

Abstract: Background: Long-term rehabilitation of stroke survivors is often difficult and new tools to improve quality of life should be proposed. Community nursing can be a cost-effective tool to positively impact the lives of stroke survivors. This meta- ... ...

Abstract	Background: Long-term rehabilitation of stroke survivors is often difficult and new tools to improve quality of life should be proposed. Community nursing can be a cost-effective tool to positively impact the lives of stroke survivors. This meta-analysis aimed to comprehensively evaluate the effects of community nursing on rehabilitation for stroke survivors. Methods: The Cochrane Library, PubMed, Web of Science, CINAHL Plus, Embase, PEDro, China Knowledge Resource Integrated Database (CNKI), WANFANG, and WEIPU databases were comprehensively searched from their inception to April 18, 2023. The revised Cochrane risk-of-bias tool for RCTs(RoB 2 tool) was used to assess the quality of the included studies. Meta-analysis was conducted using the Stata 12.0 software package and Review Manager v5.3 software. Results: A total of 25 randomized controlled trials with 2537 participants were included in the meta-analysis. Compared with the control group, community nursing combined with routine nursing had a significantly superior effect on the Barthel Index(BI), Fugl-Meyer(FMA), National Institutes of Health Stroke Scale(NIHSS), Self-rating Anxiety Scale(SAS), and Self-rating Depression Scale(SDS) scores for stroke survivors (BI: MD: 18.48, 95 % CI [16.87, 20.08], P < 0.00001; FMA: MD: 12.61, 95 % CI [10.44, 14.78], P < 0.00001; NIHSS: MD: -2.94, 95 % CI [-3.50, -2.37], P < 0.00001; SAS: MD: -8.19; 95 % CI: [-9.46, -6.92], P < 0.00001; SDS: MD: -6.46 95 % CI [-7.23, -5.70], P < 0.00001). Subgroup analysis demonstrated that routine nursing, health education, exercise rehabilitation nursing and psychological nursing combined with different community nursing measures were significant in rehabilitation for stroke survivors and there was no heterogeneous in the studies of each subgroup(P > 0.1, I Conclusion: This meta-analysis demonstrated that community nursing combined with routine nursing might improve activities of daily living, motor function and nerve function, and relieve anxiety and depression in stroke survivors. Overall, community nursing had a significant effect on rehabilitation of stroke survivors. However, this study still has limitations such as the overestimation effects caused by the sample size and the risk of bias caused by interventions. Future research will attempt to overcome these limitations and comprehensively assess the effect of community nursing on the rehabilitation of stroke survivors.
Language	English
Publishing date	2024-04-09
Publishing country	United States
Document type	Journal Article
ZDB-ID	632559-2
ISSN	1528-3984 ; 0197-4572
ISSN (online)	1528-3984
ISSN	0197-4572
DOI	10.1016/j.gerinurse.2024.03.004
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Article: Automatically Explaining Machine Learning Predictions on Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study.

Zeng, Siyang / Arjomandi, Mehrdad / Luo, Gang

JMIR medical informatics

2022 Volume 10, Issue 2, Page(s) e33043

Abstract: Background: Chronic obstructive pulmonary disease (COPD) is a major cause of death and places a heavy burden on health care. To optimize the allocation of precious preventive care management resources and improve the outcomes for high-risk patients with ...

Abstract	Background: Chronic obstructive pulmonary disease (COPD) is a major cause of death and places a heavy burden on health care. To optimize the allocation of precious preventive care management resources and improve the outcomes for high-risk patients with COPD, we recently built the most accurate model to date to predict severe COPD exacerbations, which need inpatient stays or emergency department visits, in the following 12 months. Our model is a machine learning model. As is the case with most machine learning models, our model does not explain its predictions, forming a barrier for clinical use. Previously, we designed a method to automatically provide rule-type explanations for machine learning predictions and suggest tailored interventions with no loss of model performance. This method has been tested before for asthma outcome prediction but not for COPD outcome prediction. Objective: This study aims to assess the generalizability of our automatic explanation method for predicting severe COPD exacerbations. Methods: The patient cohort included all patients with COPD who visited the University of Washington Medicine facilities between 2011 and 2019. In a secondary analysis of 43,576 data instances, we used our formerly developed automatic explanation method to automatically explain our model's predictions and suggest tailored interventions. Results: Our method explained the predictions for 97.1% (100/103) of the patients with COPD whom our model correctly predicted to have severe COPD exacerbations in the following 12 months and the predictions for 73.6% (134/182) of the patients with COPD who had ≥1 severe COPD exacerbation in the following 12 months. Conclusions: Our automatic explanation method worked well for predicting severe COPD exacerbations. After further improving our method, we hope to use it to facilitate future clinical use of our model. International registered report identifier (irrid): RR2-10.2196/13783.
Language	English
Publishing date	2022-02-25
Publishing country	Canada
Document type	Journal Article
ZDB-ID	2798261-0
ISSN	2291-9694
ISSN	2291-9694
DOI	10.2196/33043
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Article ; Online: Does losing money truly hurt? The shared neural bases of monetary loss and pain.

Tan, Huixin / Duan, Qin / Liu, Yihan / Qiao, Xinyu / Luo, Siyang

Human brain mapping

2022 Volume 43, Issue 10, Page(s) 3153–3163

Abstract: Both monetary loss and pain have been studied for decades, but evidence supporting the relationship between them is still lacking. We conducted a meta-analysis to explore the overlapping brain regions between monetary loss and pain, including physical ... ...

Abstract	Both monetary loss and pain have been studied for decades, but evidence supporting the relationship between them is still lacking. We conducted a meta-analysis to explore the overlapping brain regions between monetary loss and pain, including physical pain and social pain. Regardless of the type of pain experienced, activation of the anterior insula was a shared neural representation of monetary loss and pain. The network representation pattern of monetary loss was more similar to that of social pain than that of physical pain. In conclusion, our research provided evidence of the common neural correlates of monetary loss and pain.
MeSH term(s)	Brain/diagnostic imaging ; Brain/physiology ; Brain Mapping ; Humans ; Magnetic Resonance Imaging ; Pain/diagnostic imaging ; Reward
Language	English
Publishing date	2022-03-22
Publishing country	United States
Document type	Journal Article ; Meta-Analysis ; Research Support, Non-U.S. Gov't
ZDB-ID	1197207-5
ISSN	1097-0193 ; 1065-9471
ISSN (online)	1097-0193
ISSN	1065-9471
DOI	10.1002/hbm.25840
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Article: Lung volumes differentiate the predominance of emphysema

Zeng, Siyang / Luo, Gang / Lynch, David A / Bowler, Russell P / Arjomandi, Mehrdad

ERJ open research

2023 Volume 9, Issue 5

Abstract: Rationale: Lung volumes identify the "susceptible smokers" who progress to develop spirometric COPD. However, among susceptible smokers, development of spirometric COPD seems to be heterogeneous, suggesting the presence of different pathological ... ...

Abstract	Rationale: Lung volumes identify the "susceptible smokers" who progress to develop spirometric COPD. However, among susceptible smokers, development of spirometric COPD seems to be heterogeneous, suggesting the presence of different pathological mechanisms during early establishment of spirometric COPD. The objective of the present study was to determine the differential patterns of radiographic pathologies among susceptible smokers. Methods: We categorised smokers with preserved spirometry (Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 0) in the Genetic Epidemiology of COPD (COPDGene) cohort based on tertiles (low, intermediate and high) of lung volumes (either total lung capacity (TLC), functional residual capacity FRC or FRC/TLC) at baseline visit. We then examined the differential patterns of change in spirometry and the associated prevalence of computed tomography measured pathologies of emphysema and airway disease with those categories of lung volumes. Results: The pattern of spirometric change differed when participants were categorised by TLC Conclusions: Lung volumes identify distinct physiological and radiographic phenotypes in early disease among susceptible smokers and predict the rate of spirometric disease progression and the severity of symptoms in early COPD.
Language	English
Publishing date	2023-09-18
Publishing country	England
Document type	Journal Article
ZDB-ID	2827830-6
ISSN	2312-0541
ISSN	2312-0541
DOI	10.1183/23120541.00289-2023
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Book ; Online: Domain Adaptive Graph Classification

Luo, Siyang / Jiang, Ziyi / Chen, Zhenghan / Liang, Xiaoxuan

2023

Abstract: Despite the remarkable accomplishments of graph neural networks (GNNs), they typically rely on task-specific labels, posing potential challenges in terms of their acquisition. Existing work have been made to address this issue through the lens of ... ...

Abstract	Despite the remarkable accomplishments of graph neural networks (GNNs), they typically rely on task-specific labels, posing potential challenges in terms of their acquisition. Existing work have been made to address this issue through the lens of unsupervised domain adaptation, wherein labeled source graphs are utilized to enhance the learning process for target data. However, the simultaneous exploration of graph topology and reduction of domain disparities remains a substantial hurdle. In this paper, we introduce the Dual Adversarial Graph Representation Learning (DAGRL), which explore the graph topology from dual branches and mitigate domain discrepancies via dual adversarial learning. Our method encompasses a dual-pronged structure, consisting of a graph convolutional network branch and a graph kernel branch, which enables us to capture graph semantics from both implicit and explicit perspectives. Moreover, our approach incorporates adaptive perturbations into the dual branches, which align the source and target distribution to address domain discrepancies. Extensive experiments on a wild range graph classification datasets demonstrate the effectiveness of our proposed method.
Keywords	Computer Science - Machine Learning ; Computer Science - Artificial Intelligence
Subject code	006
Publishing date	2023-12-20
Publishing country	us
Document type	Book ; Online
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Article ; Online: Genetic basis of STEM occupational choice and regional economic performance

Chen Zhu / Qiran Zhao / Jianbo He / Petri Böckerman / Siyang Luo / Qihui Chen

Human Genomics, Vol 17, Iss 1, Pp 1-

a UK biobank genome-wide association study

2023 Volume 11

Abstract: Abstract Background Science, technology, engineering, and mathematics (STEM) professionals are regarded as the highly skilled labor force that fosters economic productivity, enterprise innovation, and international competitiveness of a country. This ... ...

Abstract	Abstract Background Science, technology, engineering, and mathematics (STEM) professionals are regarded as the highly skilled labor force that fosters economic productivity, enterprise innovation, and international competitiveness of a country. This study aims to understand the genetic predisposition to STEM occupations and investigate its associations with regional economic performance. We conducted a genome-wide association study on the occupational choice of STEM jobs based on a sample of 178,976 participants from the UK Biobank database. Results We identified two genetic loci significantly associated with participants’ STEM job choices: rs10048736 on chromosome 2 and rs12903858 on chromosome 15. The SNP heritability of STEM occupations was estimated to be 4.2%. We also found phenotypic and genetic evidence of assortative mating in STEM occupations. At the local authority level, we found that the average polygenic score of STEM is significantly and robustly associated with several metrics of regional economic performance. Conclusions The current study expands our knowledge of the genetic basis of occupational choice and potential regional disparities in socioeconomic developments.
Keywords	STEM ; Occupational choice ; Genome-wide association study ; Polygenic score ; Assortative mating ; Comparative economic development ; Medicine ; R ; Genetics ; QH426-470
Subject code	300
Language	English
Publishing date	2023-05-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Lung volumes differentiate the predominance of emphysema versus airway disease phenotype in early COPD

Siyang Zeng / Gang Luo / David A. Lynch / Russell P. Bowler / Mehrdad Arjomandi

ERJ Open Research, Vol 9, Iss

an observational study of the COPDGene cohort

2023 Volume 5

Abstract: Rationale Lung volumes identify the “susceptible smokers” who progress to develop spirometric COPD. However, among susceptible smokers, development of spirometric COPD seems to be heterogeneous, suggesting the presence of different pathological ... ...

Abstract	Rationale Lung volumes identify the “susceptible smokers” who progress to develop spirometric COPD. However, among susceptible smokers, development of spirometric COPD seems to be heterogeneous, suggesting the presence of different pathological mechanisms during early establishment of spirometric COPD. The objective of the present study was to determine the differential patterns of radiographic pathologies among susceptible smokers. Methods We categorised smokers with preserved spirometry (Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 0) in the Genetic Epidemiology of COPD (COPDGene) cohort based on tertiles (low, intermediate and high) of lung volumes (either total lung capacity (TLC), functional residual capacity FRC or FRC/TLC) at baseline visit. We then examined the differential patterns of change in spirometry and the associated prevalence of computed tomography measured pathologies of emphysema and airway disease with those categories of lung volumes. Results The pattern of spirometric change differed when participants were categorised by TLC versus FRC/TLC: those in the high TLC tertile showed stable forced expiratory volume in 1 s (FEV1), but enlarging forced vital capacity (FVC), while those in the high FRC/TLC tertile showed decline in both FEV1 and FVC. When participants from the high TLC and high FRC/TLC tertiles were partitioned into mutually exclusive groups, compared to those with high TLC, those with high FRC/TLC had lesser emphysema, but greater air trapping, more self-reported respiratory symptoms and exacerbation episodes and higher likelihood of progressing to more severe spirometric disease (GOLD stages 2–4 versus GOLD stage 1). Conclusions Lung volumes identify distinct physiological and radiographic phenotypes in early disease among susceptible smokers and predict the rate of spirometric disease progression and the severity of symptoms in early COPD.
Keywords	Medicine ; R
Subject code	610
Language	English
Publishing date	2023-09-01T00:00:00Z
Publisher	European Respiratory Society
Document type	Article ; Online
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