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  1. Article ; Online: Anti-interferon-γ autoantibody-associated immunodeficiency.

    Shih, Han-Po / Ding, Jing-Ya / Yeh, Chun-Fu / Chi, Chih-Yu / Ku, Cheng-Lung

    Current opinion in immunology

    2021  Volume 72, Page(s) 206–214

    Abstract: Anticytokine autoantibodies are an emerging disease etiology, through the disturbance of physiological functions of cognate cytokines. Anti-interferon (IFN)-γ autoantibodies (AIGAs) were first identified in patients with severe mycobacterial infections, ... ...

    Abstract Anticytokine autoantibodies are an emerging disease etiology, through the disturbance of physiological functions of cognate cytokines. Anti-interferon (IFN)-γ autoantibodies (AIGAs) were first identified in patients with severe mycobacterial infections, and were considered to be an autoimmune phenocopy of inborn genetic errors of the IL-12/IFN-γ axis. More than 600 reported cases, most originating from Southeast Asia, have been diagnosed over the last decade. Specific HLA class II molecules are associated with these autoantibodies, which provide a genetic basis for the high prevalence of this immunodeficiency syndrome in certain ethnic groups. Salmonellosis and herpes zoster reactivation are observed in more than half the patients with AIGAs. Moreover, AIGAs have been shown to underlie severe Taralomyce marneffei infection in HIV-negative patients. AIGAs may, thus, be considered a new form of late-onset immunodeficiency conferring a predisposition not only to severe mycobacterial, but also to some bacterial and fungal infections.
    MeSH term(s) Animals ; Autoantibodies/immunology ; Autoimmune Diseases/immunology ; Autoimmunity ; Biomarkers ; Disease Susceptibility/immunology ; Humans ; Immunologic Deficiency Syndromes/diagnosis ; Immunologic Deficiency Syndromes/etiology ; Immunologic Deficiency Syndromes/metabolism ; Interferon-gamma/immunology
    Chemical Substances Autoantibodies ; Biomarkers ; Interferon-gamma (82115-62-6)
    Language English
    Publishing date 2021-06-25
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Review
    ZDB-ID 1035767-1
    ISSN 1879-0372 ; 0952-7915
    ISSN (online) 1879-0372
    ISSN 0952-7915
    DOI 10.1016/j.coi.2021.05.007
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  2. Article: Comparison of the accuracy of neutrophil CD64, procalcitonin, and C-reactive protein for sepsis identification: a systematic review and meta-analysis.

    Yeh, Chun-Fu / Wu, Chin-Chieh / Liu, Su-Hsun / Chen, Kuan-Fu

    Annals of intensive care

    2019  Volume 9, Issue 1, Page(s) 5

    Abstract: Background: Neutrophil CD64 is widely described as an accurate biomarker for the diagnosis of infection in patients with septic syndrome. We performed a systematic review and meta-analysis to evaluate the diagnostic accuracy of neutrophil CD64, ... ...

    Abstract Background: Neutrophil CD64 is widely described as an accurate biomarker for the diagnosis of infection in patients with septic syndrome. We performed a systematic review and meta-analysis to evaluate the diagnostic accuracy of neutrophil CD64, comparing it with C-reactive protein (CRP) and procalcitonin (PCT) for the diagnosis of infection in adult patients with septic syndrome, based on sepsis-2 criteria. We searched the PubMed and Embase databases and Google Scholar. Original studies reporting the performance of neutrophil CD64 for sepsis diagnosis in adult patients were retained. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and hierarchical summary receiver operating characteristic (SROC) curve were calculated.
    Results: We included 14 studies (2471 patients) from 2006 to 2017 in the meta-analysis. The pooled sensitivity and specificity of neutrophil CD64 for diagnosing infection in adult patients with septic syndrome were 0.87 (95% CI 0.80-0.92) and 0.89 (95% CI 0.82-0.93), respectively. The area under the SROC curve and the DOR were 0.94 (95% CI 0.92-0.96) and 53 (95% CI 22-128), respectively. There was significant heterogeneity between the studies included. Subgroup analyses showed that this heterogeneity was due to differences in sample size and the proportions of patients with sepsis included in the studies. Six studies (927 patients) compared neutrophil CD64 and CRP determinations, and six studies (744 patients) compared neutrophil CD64 and PCT determinations. The area under the SROC curve was larger for neutrophil CD64 than for CRP (0.89 [95% CI 0.87-0.92] vs. 0.84 [95% CI 0.80-0.88], P < 0.05) or PCT (0.89 [95% CI 0.84-0.95] vs. 0.84 [95% CI 0.79-0.89], P < 0.05).
    Conclusions: In adult patients with septic syndrome, neutrophil CD64 levels are an excellent biomarker with moderate accuracy outperforming both CRP and PCT determinations.
    Language English
    Publishing date 2019-01-08
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2617094-2
    ISSN 2110-5820
    ISSN 2110-5820
    DOI 10.1186/s13613-018-0479-2
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  3. Article ; Online: Diagnostic accuracy of clinical signs and symptoms of COVID-19: A systematic review and meta-analysis to investigate the different estimates in a different stage of the pandemic outbreak.

    Chen, Kuan-Fu / Feng, Tsai-Wei / Wu, Chin-Chieh / Yunusa, Ismaeel / Liu, Su-Hsun / Yeh, Chun-Fu / Han, Shih-Tsung / Mao, Chih-Yang / Harika, Dasari / Rothman, Richard / Pekosz, Andrew

    Journal of global health

    2023  Volume 13, Page(s) 6026

    Abstract: Background: The coronavirus (COVID-19) pandemic caused enormous adverse socioeconomic impacts worldwide. Evidence suggests that the diagnostic accuracy of clinical features of COVID-19 may vary among different populations.: Methods: We conducted a ... ...

    Abstract Background: The coronavirus (COVID-19) pandemic caused enormous adverse socioeconomic impacts worldwide. Evidence suggests that the diagnostic accuracy of clinical features of COVID-19 may vary among different populations.
    Methods: We conducted a systematic review and meta-analysis of studies from PubMed, Embase, Cochrane Library, Google Scholar, and the WHO Global Health Library for studies evaluating the accuracy of clinical features to predict and prognosticate COVID-19. We used the National Institutes of Health Quality Assessment Tool to evaluate the risk of bias, and the random-effects approach to obtain pooled prevalence, sensitivity, specificity, and likelihood ratios.
    Results: Among the 189 included studies (53 659 patients), fever, cough, diarrhoea, dyspnoea, and fatigue were the most reported predictors. In the later stage of the pandemic, the sensitivity in predicting COVID-19 of fever and cough decreased, while the sensitivity of other symptoms, including sputum production, sore throat, myalgia, fatigue, dyspnoea, headache, and diarrhoea, increased. A combination of fever, cough, fatigue, hypertension, and diabetes mellitus increases the odds of having a COVID-19 diagnosis in patients with a positive test (positive likelihood ratio (PLR) = 3.06)) and decreases the odds in those with a negative test (negative likelihood ratio (NLR) = 0.59)). A combination of fever, cough, sputum production, myalgia, fatigue, and dyspnea had a PLR = 10.44 and an NLR = 0.16 in predicting severe COVID-19. Further updating the umbrella review (1092 studies, including 3 342 969 patients) revealed the different prevalence of symptoms in different stages of the pandemic.
    Conclusions: Understanding the possible different distributions of predictors is essential for screening for potential COVID-19 infection and severe outcomes. Understanding that the prevalence of symptoms may change with time is important to developing a prediction model.
    MeSH term(s) United States ; Humans ; COVID-19/diagnosis ; COVID-19/epidemiology ; SARS-CoV-2 ; Myalgia ; Cough ; Pandemics ; COVID-19 Testing ; Dyspnea ; Fatigue
    Language English
    Publishing date 2023-07-14
    Publishing country Scotland
    Document type Meta-Analysis ; Systematic Review ; Journal Article
    ZDB-ID 2741629-X
    ISSN 2047-2986 ; 2047-2986
    ISSN (online) 2047-2986
    ISSN 2047-2986
    DOI 10.7189/jogh.13.06026
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  4. Article: Development and Feasibility of a Kinect-Based Constraint-Induced Therapy Program in the Home Setting for Children With Unilateral Cerebral Palsy.

    Chen, Hao-Ling / Lin, Szu-Yu / Yeh, Chun-Fu / Chen, Ren-Yu / Tang, Hsien-Hui / Ruan, Shanq-Jang / Wang, Tien-Ni

    Frontiers in bioengineering and biotechnology

    2021  Volume 9, Page(s) 755506

    Abstract: Introduction: ...

    Abstract Introduction:
    Language English
    Publishing date 2021-10-26
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2719493-0
    ISSN 2296-4185
    ISSN 2296-4185
    DOI 10.3389/fbioe.2021.755506
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  5. Article: Determining Carina and Clavicular Distance-Dependent Positioning of Endotracheal Tube in Critically Ill Patients: An Artificial Intelligence-Based Approach.

    Tsai, Lung-Wen / Yuan, Kuo-Ching / Hou, Sen-Kuang / Wu, Wei-Lin / Hsu, Chen-Hao / Liu, Tyng-Luh / Lee, Kuang-Min / Li, Chiao-Hsuan / Chen, Hann-Chyun / Tu, Ethan / Dubey, Rajni / Yeh, Chun-Fu / Chen, Ray-Jade

    Biology

    2022  Volume 11, Issue 4

    Abstract: Early and accurate prediction of endotracheal tube (ETT) location is pivotal for critically ill patients. Automatic and timely detection of faulty ETT locations from chest X-ray images may avert patients' morbidity and mortality. Therefore, we designed ... ...

    Abstract Early and accurate prediction of endotracheal tube (ETT) location is pivotal for critically ill patients. Automatic and timely detection of faulty ETT locations from chest X-ray images may avert patients' morbidity and mortality. Therefore, we designed convolutional neural network (CNN)-based algorithms to evaluate ETT position appropriateness relative to four detected key points, including tracheal tube end, carina, and left/right clavicular heads on chest radiographs. We estimated distances from the tube end to tracheal carina and the midpoint of clavicular heads. A DenseNet121 encoder transformed images into embedding features, and a CNN-based decoder generated the probability distributions. Based on four sets of tube-to-carina distance-dependent parameters (i.e., (i) 30-70 mm, (ii) 30-60 mm, (iii) 20-60 mm, and (iv) 20-55 mm), corresponding models were generated, and their accuracy was evaluated through the predicted L1 distance to ground-truth coordinates. Based on tube-to-carina and tube-to-clavicle distances, the highest sensitivity, and specificity of 92.85% and 84.62% respectively, were revealed for 20-55 mm. This implies that tube-to-carina distance between 20 and 55 mm is optimal for an AI-based key point appropriateness detection system and is empirically comparable to physicians' consensus.
    Language English
    Publishing date 2022-03-23
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2661517-4
    ISSN 2079-7737
    ISSN 2079-7737
    DOI 10.3390/biology11040490
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  6. Article ; Online: Postural control during standing reach in children with Down syndrome.

    Chen, Hao-Ling / Yeh, Chun-Fu / Howe, Tsu-Hsin

    Research in developmental disabilities

    2015  Volume 38, Page(s) 345–351

    Abstract: The purpose of the present study was to investigate the dynamic postural control of children with Down syndrome (DS). Specifically, we compared postural control and goal-directed reaching performance between children with DS and typically developing ... ...

    Abstract The purpose of the present study was to investigate the dynamic postural control of children with Down syndrome (DS). Specifically, we compared postural control and goal-directed reaching performance between children with DS and typically developing children during standing reach. Standing reach performance was analyzed in three main phases using the kinematic and kinetic data collected from a force plate and a motion capture system. Fourteen children with DS, age and gender matched with fourteen typically developing children, were recruited for this study. The results showed that the demand of the standing reach task affected both dynamic postural control and reaching performance in children with DS, especially in the condition of beyond arm's length reaching. More postural adjustment strategies were recruited when reaching distance was beyond arm's length. Children with DS tended to use inefficient and conservative strategies for postural stability and reaching. That is, children with DS perform standing reach with increased reaction and execution time and decreased amplitudes of center of pressure displacements. Standing reach resembled functional balance that is required in daily activities. It is suggested to be considered as a part of strength and balance training program with graded task difficulty.
    MeSH term(s) Arm ; Biomechanical Phenomena ; Case-Control Studies ; Child ; Down Syndrome/complications ; Down Syndrome/physiopathology ; Female ; Humans ; Male ; Movement/physiology ; Postural Balance/physiology ; Sensation Disorders/complications ; Sensation Disorders/physiopathology
    Language English
    Publishing date 2015-03
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 639175-8
    ISSN 1873-3379 ; 0891-4222
    ISSN (online) 1873-3379
    ISSN 0891-4222
    DOI 10.1016/j.ridd.2014.12.024
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    In stock of ZB MED Cologne/Königswinter

    Zs.B 2592: Show issues Location:
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  7. Article ; Online: Effect of surface-modified collagen on the adhesion, biocompatibility and differentiation of bone marrow stromal cells in poly(lactide-co-glycolide)/chitosan scaffolds.

    Kuo, Yung-Chih / Yeh, Chun-Fu

    Colloids and surfaces. B, Biointerfaces

    2011  Volume 82, Issue 2, Page(s) 624–631

    Abstract: The material-driven differentiation of bone marrow stromal cells (BMSCs) is a critical issue in regeneration medicine. In this study, we showed the differentiation of BMSCs in 3-D scaffolds consisting of collagen, poly(lactide-co-glycolide) (PLGA) and ... ...

    Abstract The material-driven differentiation of bone marrow stromal cells (BMSCs) is a critical issue in regeneration medicine. In this study, we showed the differentiation of BMSCs in 3-D scaffolds consisting of collagen, poly(lactide-co-glycolide) (PLGA) and chitosan. The results revealed that the collagen-grafted PLGA/chitosan scaffolds yielded little cytotoxicity to BMSCs. The scaffold containing type I collagen of 640μg/mL was about 1.2 times the cell adhesion efficiency of the corresponding unmodified scaffold. In addition, the modification of type I collagen with the density of 640μg/mL increased about 1.3 times the cell viability and 1.2 times the biodegradation, respectively. The differentiation of BMSCs in PLGA/chitosan scaffolds produced osteoblasts with mineral deposition on the substrate. Moreover, the surface collagen promoted the formation of mineralized tissue and reduced the amount of phenotypic BMSCs in the constructs. However, the induction with neuron growth factor (NGF) inhibited osteogenesis and guided the differentiation of BMSCs towards neurons in the constructs. Therefore, the combination of collagen-functionalized PLGA/chitosan scaffolds, NGF and BMSCs can be promising in neural tissue engineering.
    MeSH term(s) Animals ; Biocompatible Materials/chemistry ; Bone Marrow Cells/cytology ; Cell Adhesion ; Cell Differentiation ; Chitosan/chemistry ; Collagen/chemistry ; Lactic Acid/chemistry ; Male ; Nerve Growth Factor/metabolism ; Neurons/metabolism ; Osteoblasts/cytology ; Osteogenesis ; Polyglycolic Acid/chemistry ; Rats ; Rats, Sprague-Dawley ; Stromal Cells/cytology ; Surface Properties ; Tissue Engineering/methods
    Chemical Substances Biocompatible Materials ; polylactic acid-polyglycolic acid copolymer ; Polyglycolic Acid (26009-03-0) ; Lactic Acid (33X04XA5AT) ; Collagen (9007-34-5) ; Chitosan (9012-76-4) ; Nerve Growth Factor (9061-61-4)
    Language English
    Publishing date 2011-02-01
    Publishing country Netherlands
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1500523-9
    ISSN 1873-4367 ; 0927-7765
    ISSN (online) 1873-4367
    ISSN 0927-7765
    DOI 10.1016/j.colsurfb.2010.10.032
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  8. Book ; Online: AnyMAL

    Moon, Seungwhan / Madotto, Andrea / Lin, Zhaojiang / Nagarajan, Tushar / Smith, Matt / Jain, Shashank / Yeh, Chun-Fu / Murugesan, Prakash / Heidari, Peyman / Liu, Yue / Srinet, Kavya / Damavandi, Babak / Kumar, Anuj

    An Efficient and Scalable Any-Modality Augmented Language Model

    2023  

    Abstract: We present Any-Modality Augmented Language Model (AnyMAL), a unified model that reasons over diverse input modality signals (i.e. text, image, video, audio, IMU motion sensor), and generates textual responses. AnyMAL inherits the powerful text-based ... ...

    Abstract We present Any-Modality Augmented Language Model (AnyMAL), a unified model that reasons over diverse input modality signals (i.e. text, image, video, audio, IMU motion sensor), and generates textual responses. AnyMAL inherits the powerful text-based reasoning abilities of the state-of-the-art LLMs including LLaMA-2 (70B), and converts modality-specific signals to the joint textual space through a pre-trained aligner module. To further strengthen the multimodal LLM's capabilities, we fine-tune the model with a multimodal instruction set manually collected to cover diverse topics and tasks beyond simple QAs. We conduct comprehensive empirical analysis comprising both human and automatic evaluations, and demonstrate state-of-the-art performance on various multimodal tasks.
    Keywords Computer Science - Machine Learning ; Computer Science - Computation and Language ; Computer Science - Computer Vision and Pattern Recognition
    Publishing date 2023-09-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Necessity of Local Modification for Deep Learning Algorithms to Predict Diabetic Retinopathy.

    Tsai, Ching-Yao / Chen, Chueh-Tan / Chen, Guan-An / Yeh, Chun-Fu / Kuo, Chin-Tzu / Hsiao, Ya-Chuan / Hu, Hsiao-Yun / Tsai, I-Lun / Wang, Ching-Hui / Chen, Jian-Ren / Huang, Su-Chen / Lu, Tzu-Chieh / Woung, Lin-Chung

    International journal of environmental research and public health

    2022  Volume 19, Issue 3

    Abstract: Deep learning (DL) algorithms are used to diagnose diabetic retinopathy (DR). However, most of these algorithms have been trained using global data or data from patients of a single region. Using different model architectures (e.g., Inception-v3, ... ...

    Abstract Deep learning (DL) algorithms are used to diagnose diabetic retinopathy (DR). However, most of these algorithms have been trained using global data or data from patients of a single region. Using different model architectures (e.g., Inception-v3, ResNet101, and DenseNet121), we assessed the necessity of modifying the algorithms for universal society screening. We used the open-source dataset from the Kaggle Diabetic Retinopathy Detection competition to develop a model for the detection of DR severity. We used a local dataset from Taipei City Hospital to verify the necessity of model localization and validated the three aforementioned models with local datasets. The experimental results revealed that Inception-v3 outperformed ResNet101 and DenseNet121 with a foreign global dataset, whereas DenseNet121 outperformed Inception-v3 and ResNet101 with the local dataset. The quadratic weighted kappa score (κ) was used to evaluate the model performance. All models had 5-8% higher
    MeSH term(s) Algorithms ; Artificial Intelligence ; Deep Learning ; Diabetes Mellitus ; Diabetic Retinopathy/diagnosis ; Humans ; Ophthalmologists
    Language English
    Publishing date 2022-01-21
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2175195-X
    ISSN 1660-4601 ; 1661-7827
    ISSN (online) 1660-4601
    ISSN 1661-7827
    DOI 10.3390/ijerph19031204
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  10. Article ; Online: Derivation of a clinical prediction rule for bloodstream infection mortality of patients visiting the emergency department based on predisposition, infection, response, and organ dysfunction concept.

    Yeh, Chun-Fu / Chen, Kuan-Fu / Ye, Jung-Jr / Huang, Ching-Tai

    Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi

    2014  Volume 47, Issue 6, Page(s) 469–477

    Abstract: Background/purpose: Bloodstream infection (BSI) is a serious infection with a high mortality. We aimed to construct a predictive scoring system to stratify the severity of patients with BSI visiting the emergency department (ED).: Methods: We ... ...

    Abstract Background/purpose: Bloodstream infection (BSI) is a serious infection with a high mortality. We aimed to construct a predictive scoring system to stratify the severity of patients with BSI visiting the emergency department (ED).
    Methods: We conducted a retrospective cohort study consisting of patients who visited the ED of a tertiary hospital with documented BSI in 2010. The potential predictors of mortality were obtained via chart review. Multivariate logistic regression was utilized to identify predictors of mortality. Penalized maximum likelihood estimation (PMLE) was applied for score development.
    Results: There were 1063 patients with bacteremia included, with an overall 28-day mortality rate of 13.2% (n = 140). In multiple logistic regression with penalization, the independent predictors of death were "predisposition": malignancy (β-coefficient, 0.65; +2 points); "infection": Staphylococcus aureus (S. aureus) bacteremia (0.69; +2 points), pneumonia (1.32; +4 points), and bacteremia with an unknown focus (0.70; +2 points); "response": body temperature <36 °C (1.17; +3 points), band form >5% (1.00; +3 points), and red blood cell distribution width (RDW) >15% (0.63; +2 points); and "organ dysfunction": pulse oximeter oxygen saturation <90% (0.72; +2 points) and creatinine >2 mg/dL (0.69; +2 points). The area under receiver operating characteristic curve (AUROC) for the model was 0.881 [95% confidence interval (CI), 0.848-0.913], with a better performance than the Pitt bacteremia score (AUROC: 0.750; 95% CI 0.699-0.800, p < 0.001). The patients were stratified into four risk groups: (1) low, 0-3 points, mortality rate: 1.5%; (2) moderate, 4-6 points, mortality rate: 10.5%; (3) high, 7-8 points, mortality rate: 28.6%; and (4) very high, ≥ 9 points, mortality rate: 65.5%.
    Conclusion: The new scoring system for bacteremia could facilitate the prediction of the risk of 28-day mortality for patients visiting the ED with BSI.
    MeSH term(s) Aged ; Cohort Studies ; Decision Support Techniques ; Emergency Service, Hospital ; Female ; Humans ; Male ; Middle Aged ; Prognosis ; Retrospective Studies ; Sepsis/diagnosis ; Sepsis/mortality ; Sepsis/pathology ; Survival Analysis ; Tertiary Care Centers
    Language English
    Publishing date 2014-12
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1497590-7
    ISSN 1995-9133 ; 1684-1182 ; 0253-2662
    ISSN (online) 1995-9133
    ISSN 1684-1182 ; 0253-2662
    DOI 10.1016/j.jmii.2013.06.012
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