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  1. Article ; Online: Reply.

    Wang, Jen-Chun / Tsai, Shih-Hung

    Journal of vascular surgery

    2020  Volume 71, Issue 3, Page(s) 1074

    MeSH term(s) Aortic Aneurysm ; Humans ; Intracranial Aneurysm
    Language English
    Publishing date 2020-02-23
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 605700-7
    ISSN 1097-6809 ; 0741-5214
    ISSN (online) 1097-6809
    ISSN 0741-5214
    DOI 10.1016/j.jvs.2019.11.022
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1933: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (1.OG)
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  2. Article ; Online: Female With Progressive Exertional Dyspnea.

    Xiong, Xing-Bang / Su, Yu-Te / Ke, Hung-Yen / Tsai, Shih-Hung / Lai, Jiun-Ji

    Annals of emergency medicine

    2022  Volume 79, Issue 6, Page(s) 527–539

    MeSH term(s) Dyspnea/etiology ; Female ; Humans
    Language English
    Publishing date 2022-05-13
    Publishing country United States
    Document type Journal Article
    ZDB-ID 603080-4
    ISSN 1097-6760 ; 0196-0644
    ISSN (online) 1097-6760
    ISSN 0196-0644
    DOI 10.1016/j.annemergmed.2021.11.011
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    Zs.A 1344: Show issues Location:
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  3. Article ; Online: Hyperuricemia exacerbates abdominal aortic aneurysm formation through the URAT1/ERK/MMP-9 signaling pathway.

    Wang, Jen-Chun / Tsai, Shih-Hung / Tsai, Hsiao-Ya / Lin, Shing-Jong / Huang, Po-Hsun

    BMC cardiovascular disorders

    2023  Volume 23, Issue 1, Page(s) 55

    Abstract: Objective: Previous studies have revealed associations between hyperuricemia and microvascular diseases, but the association between hyperuricemia and abdominal aortic aneurysm (AAA) remains unclear. The aim of this study was to elucidate the ... ...

    Abstract Objective: Previous studies have revealed associations between hyperuricemia and microvascular diseases, but the association between hyperuricemia and abdominal aortic aneurysm (AAA) remains unclear. The aim of this study was to elucidate the pathogenesis and prove the relationship between AAA and hyperuricemia.
    Methods: A retrospective study was performed to validate the growth rates of AAA in humans with different serum uric acid levels. A murine model of angiotensin II-induced AAA was used to assess the effects of hyperuricemia on AAA growth in vivo, and human aortic smooth muscle cells (HASMCs) were used to study the pathways involved in these effects in vitro.
    Results: We analyzed data from 107 AAA patients and found that patients with serum uric acid levels above 9 mg/dl had higher AAA growth rates than patients with serum uric acid levels between 4 and 7.9 mg/dl. In vivo, induction of hyperuricemia increased the incidence of AAA formation and the abdominal aortic diameter in mice. The hyperuricemic mice exhibited higher levels of urate transporter 1 (URAT1) expression, phospho-extracellular signal-regulated kinase (p-ERK)1/2 expression, reactive oxygen species (ROS) levels and matrix metalloproteinase (MMP)-9 expression in the abdominal aorta than the control mice. Soluble uric acid increased the expression of URAT1, p-ERK1/2, and MMP-9 and the levels of ROS in HASMCs in vitro.
    Conclusions: We have provided human evidence that hyperuricemia exacerbates AAA formation. In addition, our murine experimental evidence suggests that hyperuricemia exacerbates AAA formation and reveals that the URAT1/ERK1/2/ROS/MMP-9 pathway is among the pathways activated by uric acid in HASMCs.
    MeSH term(s) Humans ; Mice ; Animals ; MAP Kinase Signaling System ; Uric Acid ; Matrix Metalloproteinase 9/metabolism ; Hyperuricemia/complications ; Hyperuricemia/diagnosis ; Reactive Oxygen Species/metabolism ; Retrospective Studies ; Aortic Aneurysm, Abdominal/metabolism ; Aorta, Abdominal ; Signal Transduction ; Disease Models, Animal ; Angiotensin II/metabolism
    Chemical Substances Uric Acid (268B43MJ25) ; Matrix Metalloproteinase 9 (EC 3.4.24.35) ; Reactive Oxygen Species ; Angiotensin II (11128-99-7)
    Language English
    Publishing date 2023-01-30
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2059859-2
    ISSN 1471-2261 ; 1471-2261
    ISSN (online) 1471-2261
    ISSN 1471-2261
    DOI 10.1186/s12872-022-03012-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Analyzing Monthly Blood Test Data to Forecast 30-Day Hospital Readmissions among Maintenance Hemodialysis Patients.

    Tsai, Cheng-Han / Shih, Dong-Her / Tu, Jue-Hong / Wu, Ting-Wei / Tsai, Ming-Guei / Shih, Ming-Hung

    Journal of clinical medicine

    2024  Volume 13, Issue 8

    Abstract: ... ...

    Abstract Background
    Language English
    Publishing date 2024-04-15
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662592-1
    ISSN 2077-0383
    ISSN 2077-0383
    DOI 10.3390/jcm13082283
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  5. Article: An acoustic detection dataset of birds (Aves) in montane forests using a deep learning approach.

    Wu, Shih-Hung / Ko, Jerome Chie-Jen / Lin, Ruey-Shing / Tsai, Wen-Ling / Chang, Hsueh-Wen

    Biodiversity data journal

    2023  Volume 11, Page(s) e97811

    Abstract: Background: Long-term monitoring is needed to understand the statuses and trends of wildlife communities in montane forests, such as those in Yushan National Park (YSNP), Taiwan. Integrating passive acoustic monitoring (PAM) with an automated sound ... ...

    Abstract Background: Long-term monitoring is needed to understand the statuses and trends of wildlife communities in montane forests, such as those in Yushan National Park (YSNP), Taiwan. Integrating passive acoustic monitoring (PAM) with an automated sound identifier, a long-term biodiversity monitoring project containing six PAM stations, was launched in YSNP in January 2020 and is currently ongoing. SILIC, an automated wildlife sound identification model, was used to extract sounds and species information from the recordings collected. Animal vocal activity can reflect their breeding status, behaviour, population, movement and distribution, which may be affected by factors, such as habitat loss, climate change and human activity. This massive amount of wildlife vocalisation dataset can provide essential information for the National Park's headquarters on resource management and decision-making. It can also be valuable for those studying the effects of climate change on animal distribution and behaviour at a regional or global scale.
    New information: To our best knowledge, this is the first open-access dataset with species occurrence data extracted from sounds in soundscape recordings by artificial intelligence. We obtained seven bird species for the first release, with more bird species and other taxa, such as mammals and frogs, to be updated annually. Raw recordings containing over 1.7 million one-minute recordings collected between the years 2020 and 2021 were analysed and SILIC identified 6,243,820 vocalisations of seven bird species in 439,275 recordings. The automatic detection had a precision of 0.95 and the recall ranged from 0.48 to 0.80. In terms of the balance between precision and recall, we prioritised increasing precision over recall in order to minimise false positive detections. In this dataset, we summarised the count of vocalisations detected per sound class per recording which resulted in 802,670 occurrence records. Unlike data from traditional human observation methods, the number of observations in the Darwin Core "organismQuantity" column refers to the number of vocalisations detected for a specific bird species and cannot be directly linked to the number of individuals.We expect our dataset will be able to help fill the data gaps of fine-scale avian temporal activity patterns in montane forests and contribute to studies concerning the impacts of climate change on montane forest ecosystems on regional or global scales.
    Language English
    Publishing date 2023-02-24
    Publishing country Bulgaria
    Document type Journal Article
    ZDB-ID 2736709-5
    ISSN 1314-2828
    ISSN 1314-2828
    DOI 10.3897/BDJ.11.e97811
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Man With Odynophagia.

    Su, Yu-Te / Tsai, Shih-Hung / Chen, Sy-Jou / Li, Ling-Yuan

    Annals of emergency medicine

    2021  Volume 77, Issue 6, Page(s) e115–e116

    MeSH term(s) Animals ; Deglutition Disorders/diagnostic imaging ; Diagnosis, Differential ; Esophagus/injuries ; Fishes ; Foreign Bodies/diagnostic imaging ; Humans ; Male ; Middle Aged ; Tomography, X-Ray Computed
    Language English
    Publishing date 2021-05-25
    Publishing country United States
    Document type Case Reports ; Journal Article
    ZDB-ID 603080-4
    ISSN 1097-6760 ; 0196-0644
    ISSN (online) 1097-6760
    ISSN 0196-0644
    DOI 10.1016/j.annemergmed.2020.12.011
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1344: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (1.OG)
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  7. Article: Distinct promotor methylation at tumor suppressive genes in ovarian cancer stromal progenitor cells and ovarian cancer and its clinical implication.

    Ho, Chih-Ming / Yen, Ting-Lin / Chien, Tsai-Yen / Huang, Shih-Hung

    American journal of cancer research

    2022  Volume 12, Issue 11, Page(s) 5325–5341

    Abstract: Aberrant CpG-island methylation affects ovarian cancer progression. The promotor methylation changes at tumor suppressive genes in ovarian cancer stromal progenitor cells (OCSPCs) and epithelial ovarian cancer (EOC) tissues and their clinical implication ...

    Abstract Aberrant CpG-island methylation affects ovarian cancer progression. The promotor methylation changes at tumor suppressive genes in ovarian cancer stromal progenitor cells (OCSPCs) and epithelial ovarian cancer (EOC) tissues and their clinical implication remains unexplored. We systemically analyzed the promoter methylation status of 40 tumor suppressor genes (TSGs) associated with cancer in paired epithelial-like and mesenchymal-like OCSPCs and ovarian cancer cells by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA). The effect of DNA methylation on gene expression was confirmed using qRT-PCR. The differential frequencies of TSGs' promoter methylation among matched epithelial-like or mesenchymal-like OCSPCs from tissues and ascites and ovarian cancer tissues were further validated in cancer tissues and correlated with clinicopathological features and survival outcomes of patients. According to the promoter methylation frequencies of the 40 TSGs, promoters of RASSF1A were the only significantly hypomethylated in epithelial-like OCSPCs from tissues than those from ascites and bulk tumor cells (0% vs 38% vs 45%, P=0.039 by Fisher's exact test). The most frequencies at promotor hypermethylation of TSGs in mesenchymal-like OCSPCs from ascites which processed aggressiveness were CDKN2B (73%) followed by CCND2 (45%) and RASSF1A (45%). Forty-three percent (47/110) of RASSF1A and 45% of CCND2 were validated as a frequently hypermethylated gene in an independent set of 110 EOC tissues in contrast to none (0/60) and 12% (10/60) of benign ovarian cysts (both P<0.001). Functional experiments revealed overexpression of CCND2 or CDKN2B in MSc-OCSPCs decreases EMT, invasion, and spheroid formation in EOC, and abolishes DNMT1 and COL6A3 expression. However, for the expected 5-year overall survival (OS) for patients with methylated RASSF1A, CCND2, and CDKN2B, only RASSF1A was significantly worse than those without methylated RASSF1A (56% vs 80%, p=0.022). Taken together, overexpression of CCND2 and CDKN2B decreased the aggressiveness of mesenchymal-like OCSPCs from ascites which may represent a potential therapeutic target for EOC. Promotor hypomethylation at RASSF1A in OCSPCs from EOC tissues and changes to hypermethylation of EOC and OCSPCs from ascites could predict poor survival outcomes for EOC patients compared to without those changes of CCND2 and CDKN2B.
    Language English
    Publishing date 2022-11-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2589522-9
    ISSN 2156-6976
    ISSN 2156-6976
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Syndiotactic Poly(4-methyl-1-pentene)-Based Stereoregular Diblock Copolymers: Synthesis and Self-Assembly Studies.

    Sung, Yu-Chuan / Huang, Pei-Sun / Huang, Shih-Hung / Chiang, Yeo-Wan / Tsai, Jing-Cherng

    Polymers

    2022  Volume 14, Issue 22

    Abstract: Syndiotactic poly(4-methyl-1-pentene) (sP4M1P)-based stereoregular diblock copolymers, namely sP4M1P- ...

    Abstract Syndiotactic poly(4-methyl-1-pentene) (sP4M1P)-based stereoregular diblock copolymers, namely sP4M1P-
    Language English
    Publishing date 2022-11-09
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527146-5
    ISSN 2073-4360 ; 2073-4360
    ISSN (online) 2073-4360
    ISSN 2073-4360
    DOI 10.3390/polym14224815
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  9. Article ; Online: Man With Left Abdominal Pain.

    Pai, Feng-Cheng / Tsai, Shih-Hung / Wang, Jen-Chun

    Annals of emergency medicine

    2020  Volume 76, Issue 1, Page(s) 106–110

    MeSH term(s) Abdominal Injuries/complications ; Abdominal Injuries/diagnostic imaging ; Abdominal Injuries/surgery ; Abdominal Pain/diagnostic imaging ; Abdominal Pain/etiology ; Abdominal Pain/surgery ; Accidental Falls ; Aged ; Aneurysm, False/diagnostic imaging ; Aneurysm, False/physiopathology ; Aneurysm, False/surgery ; Aortic Aneurysm, Abdominal/diagnostic imaging ; Aortic Aneurysm, Abdominal/physiopathology ; Aortic Aneurysm, Abdominal/surgery ; Blood Vessel Prosthesis Implantation ; Computed Tomography Angiography ; Femoral Artery ; Humans ; Male ; Point-of-Care Systems ; Treatment Outcome ; Ultrasonography ; Wounds, Nonpenetrating/complications ; Wounds, Nonpenetrating/diagnostic imaging ; Wounds, Nonpenetrating/physiopathology ; Wounds, Nonpenetrating/surgery
    Language English
    Publishing date 2020-07-15
    Publishing country United States
    Document type Case Reports ; Journal Article
    ZDB-ID 603080-4
    ISSN 1097-6760 ; 0196-0644
    ISSN (online) 1097-6760
    ISSN 0196-0644
    DOI 10.1016/j.annemergmed.2020.02.008
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  10. Article: Development and Validation of an Artificial Intelligence Electrocardiogram Recommendation System in the Emergency Department.

    Tsai, Dung-Jang / Tsai, Shih-Hung / Chiang, Hui-Hsun / Lee, Chia-Cheng / Chen, Sy-Jou

    Journal of personalized medicine

    2022  Volume 12, Issue 5

    Abstract: The machine learning-assisted electrocardiogram (ECG) is increasingly recognized for its unprecedented capabilities in diagnosing and predicting cardiovascular diseases. Identifying the need for ECG examination early in emergency department (ED) triage ... ...

    Abstract The machine learning-assisted electrocardiogram (ECG) is increasingly recognized for its unprecedented capabilities in diagnosing and predicting cardiovascular diseases. Identifying the need for ECG examination early in emergency department (ED) triage is key to timely artificial intelligence-assisted analysis. We used machine learning to develop and validate a clinical decision support tool to predict ED triage patients' need for ECG. Data from 301,658 ED visits from August 2017 to November 2020 in a tertiary hospital were divided into a development cohort, validation cohort, and two test cohorts that included admissions before and during the COVID-19 pandemic. Models were developed using logistic regression, decision tree, random forest, and XGBoost methods. Their areas under the receiver operating characteristic curves (AUCs), positive predictive values (PPVs), and negative predictive values (NPVs) were compared and validated. In the validation cohort, the AUCs were 0.887 for the XGBoost model, 0.885 for the logistic regression model, 0.878 for the random forest model, and 0.845 for the decision tree model. The XGBoost model was selected for subsequent application. In test cohort 1, the AUC was 0.891, with sensitivity of 0.812, specificity of 0.814, PPV of 0.708 and NPV of 0.886. In test cohort 2, the AUC was 0.885, with sensitivity of 0.816, specificity of 0.812, PPV of 0.659, and NPV of 0.908. In the cumulative incidence analysis, patients not receiving an ECG yet positively predicted by the model had significantly higher probability of receiving the examination within 48 h compared with those negatively predicted by the model. A machine learning model based on triage datasets was developed to predict ECG acquisition with high accuracy. The ECG recommendation can effectively predict whether patients presenting at ED triage will require an ECG, prompting subsequent analysis and decision-making in the ED.
    Language English
    Publishing date 2022-04-27
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662248-8
    ISSN 2075-4426
    ISSN 2075-4426
    DOI 10.3390/jpm12050700
    Database MEDical Literature Analysis and Retrieval System OnLINE

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