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  • 1
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    Online Resource
    AICAR Induces Apoptosis and Inhibits Migration and Invasion in Prostate Cancer Cells Through an AMPK/mTOR-Dependent Pathway
    MDPI AG ; 2019
    In:  International Journal of Molecular Sciences Vol. 20, No. 7 ( 2019-04-03), p. 1647-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 20, No. 7 ( 2019-04-03), p. 1647-
    Abstract: Current clinical challenges of prostate cancer management are to restrict tumor growth and prohibit metastasis. AICAR (5-aminoimidazole-4-carbox-amide-1-β-d-ribofuranoside), an AMP-activated protein kinase (AMPK) agonist, has demonstrated antitumor activities for several types of cancers. However, the activity of AICAR on the cell growth and metastasis of prostate cancer has not been extensively studied. Herein we examine the effects of AICAR on the cell growth and metastasis of prostate cancer cells. Cell growth was performed by MTT assay and soft agar assay; cell apoptosis was examined by Annexin V/propidium iodide (PI) staining and poly ADP ribose polymerase (PARP) cleavage western blot, while cell migration and invasion were evaluated by wound-healing assay and transwell assay respectively. Epithelial–mesenchymal transition (EMT)-related protein expression and AMPK/mTOR-dependent signaling axis were analyzed by western blot. In addition, we also tested the effect of AICAR on the chemosensitivity to docetaxel using MTT assay. Our results indicated that AICAR inhibits cell growth in prostate cancer cells, but not in non-cancerous prostate cells. In addition, our results demonstrated that AICAR induces apoptosis, attenuates transforming growth factor (TGF)-β-induced cell migration, invasion and EMT-related protein expression, and enhances the chemosensitivity to docetaxel in prostate cancer cells through regulating the AMPK/mTOR-dependent pathway. These findings support AICAR as a potential therapeutic agent for the treatment of prostate cancer.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms20071647
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 2
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    An Artificial Intelligence-Based Alarm Strategy Facilitates Management of Acute Myocardial Infarction
    MDPI AG ; 2021
    In:  Journal of Personalized Medicine Vol. 11, No. 11 ( 2021-11-04), p. 1149-
    Details
    In: Journal of Personalized Medicine, MDPI AG, Vol. 11, No. 11 ( 2021-11-04), p. 1149-
    Abstract: (1) Background: While an artificial intelligence (AI)-based, cardiologist-level, deep-learning model for detecting acute myocardial infarction (AMI), based on a 12-lead electrocardiogram (ECG), has been established to have extraordinary capabilities, its real-world performance and clinical applications are currently unknown. (2) Methods and Results: To set up an artificial intelligence-based alarm strategy (AI-S) for detecting AMI, we assembled a strategy development cohort including 25,002 visits from August 2019 to April 2020 and a prospective validation cohort including 14,296 visits from May to August 2020 at an emergency department. The components of AI-S consisted of chest pain symptoms, a 12-lead ECG, and high-sensitivity troponin I. The primary endpoint was to assess the performance of AI-S in the prospective validation cohort by evaluating F-measure, precision, and recall. The secondary endpoint was to evaluate the impact on door-to-balloon (DtoB) time before and after AI-S implementation in STEMI patients treated with primary percutaneous coronary intervention (PPCI). Patients with STEMI were alerted precisely by AI-S (F-measure = 0.932, precision of 93.2%, recall of 93.2%). Strikingly, in comparison with pre-AI-S (N = 57) and post-AI-S (N = 32) implantation in STEMI protocol, the median ECG-to-cardiac catheterization laboratory activation (EtoCCLA) time was significantly reduced from 6.0 (IQR, 5.0–8.0 min) to 4.0 min (IQR, 3.0–5.0 min) (p 〈 0.01). The median DtoB time was shortened from 69 (IQR, 61.0–82.0 min) to 61 min (IQR, 56.8–73.2 min) (p = 0.037). (3) Conclusions: AI-S offers front-line physicians a timely and reliable diagnostic decision-support system, thereby significantly reducing EtoCCLA and DtoB time, and facilitating the PPCI process. Nevertheless, large-scale, multi-institute, prospective, or randomized control studies are necessary to further confirm its real-world performance.
    Type of Medium: Online Resource
    ISSN: 2075-4426
    URL: Article
    DOI: 10.3390/jpm11111149
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2662248-8
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  • 3
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    Artificial Intelligence-Enabled Electrocardiography Predicts Left Ventricular Dysfunction and Future Cardiovascular Outcomes: A Retrospective Analysis
    MDPI AG ; 2022
    In:  Journal of Personalized Medicine Vol. 12, No. 3 ( 2022-03-13), p. 455-
    Details
    In: Journal of Personalized Medicine, MDPI AG, Vol. 12, No. 3 ( 2022-03-13), p. 455-
    Abstract: BACKGROUND: The ejection fraction (EF) provides critical information about heart failure (HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for cardiac electrophysiological activities that has been used to detect patients with low EF based on a deep learning model (DLM) trained via large amounts of data. However, no studies have widely investigated its clinical impacts. OBJECTIVE: This study developed a DLM to estimate EF via ECG (ECG-EF). We further investigated the relationship between ECG-EF and echo-based EF (ECHO-EF) and explored their contributions to future cardiovascular adverse events. METHODS: There were 57,206 ECGs with corresponding echocardiograms used to train our DLM. We compared a series of training strategies and selected the best DLM. The architecture of the DLM was based on ECG12Net, developed previously. Next, 10,762 ECGs were used for validation, and another 20,629 ECGs were employed to conduct the accuracy test. The changes between ECG-EF and ECHO-EF were evaluated. The primary follow-up adverse events included future ECHO-EF changes and major adverse cardiovascular events (MACEs). RESULTS: The sex-/age-matching strategy-trained DLM achieved the best area under the curve (AUC) of 0.9472 with a sensitivity of 86.9% and specificity of 89.6% in the follow-up cohort, with a correlation of 0.603 and a mean absolute error of 7.436. In patients with accurate prediction (initial difference 〈 10%), the change traces of ECG-EF and ECHO-EF were more consistent (R-square = 0.351) than in all patients (R-square = 0.115). Patients with lower ECG-EF (≤35%) exhibited a greater risk of cardiovascular (CV) complications, delayed ECHO-EF recovery, and earlier ECHO-EF deterioration than patients with normal ECG-EF ( 〉 50%). Importantly, ECG-EF demonstrated an independent impact on MACEs and all CV adverse outcomes, with better prediction of CV outcomes than ECHO-EF. CONCLUSIONS: The ECG-EF could be used to initially screen asymptomatic left ventricular dysfunction (LVD) and it could also independently contribute to the predictions of future CV adverse events. Although further large-scale studies are warranted, DLM-based ECG-EF could serve as a promising diagnostic supportive and management-guided tool for CV disease prediction and the care of patients with LVD.
    Type of Medium: Online Resource
    ISSN: 2075-4426
    URL: Article
    DOI: 10.3390/jpm12030455
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662248-8
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  • 4
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    Online Resource
    Protective Effect of Piplartine against LPS-Induced Sepsis through Attenuating the MAPKs/NF-κB Signaling Pathway and NLRP3 Inflammasome Activation
    MDPI AG ; 2021
    In:  Pharmaceuticals Vol. 14, No. 6 ( 2021-06-18), p. 588-
    Details
    In: Pharmaceuticals, MDPI AG, Vol. 14, No. 6 ( 2021-06-18), p. 588-
    Abstract: Piplartine (or Piperlongumine) is a natural alkaloid isolated from Piper longum L., which has been proposed to exhibit various biological properties such as anti-inflammatory effects; however, the effect of piplartine on sepsis has not been examined. This study was performed to examine the anti-inflammatory activities of piplartine in vitro, ex vivo and in vivo using murine J774A.1 macrophage cell line, peritoneal macrophages, bone marrow-derived macrophages and an animal sepsis model. The results demonstrated that piplartine suppresses iNOS and COX-2 expression, reduces PGE2, TNF-α and IL-6 production, decreases the phosphorylation of MAPKs and NF-κB and attenuates NF-κB activity by LPS-activated macrophages. Piplartine also inhibits IL-1β production and suppresses NLRP3 inflammasome activation by LPS/ATP- and LPS/nigericin-activated macrophages. Moreover, piplartine reduces the production of nitric oxide (NO) and TNF-α, IL-6 and IL-1β, decreases LPS-induced tissue damage, attenuates infiltration of inflammatory cells and enhances the survival rate. Collectively, these results demonstrate piplartine exhibits anti-inflammatory activities in LPS-induced inflammation and sepsis and suggest that piplartine might have benefits for sepsis treatment.
    Type of Medium: Online Resource
    ISSN: 1424-8247
    URL: Article
    DOI: 10.3390/ph14060588
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2193542-7
    SSG: 15,3
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  • 5
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    Mycotoxin Zearalenone Attenuates Innate Immune Responses and Suppresses NLRP3 Inflammasome Activation in LPS-Activated Macrophages
    MDPI AG ; 2021
    In:  Toxins Vol. 13, No. 9 ( 2021-08-25), p. 593-
    Details
    In: Toxins, MDPI AG, Vol. 13, No. 9 ( 2021-08-25), p. 593-
    Abstract: Zearalenone (ZEA) is a mycotoxin that has several adverse effects on most mammalian species. However, the effects of ZEA on macrophage-mediated innate immunity during infection have not been examined. In the present study, bacterial lipopolysaccharides (LPS) were used to induce the activation of macrophages and evaluate the effects of ZEA on the inflammatory responses and inflammation-associated signaling pathways. The experimental results indicated that ZEA suppressed LPS-activated inflammatory responses by macrophages including attenuating the production of proinflammatory mediators (nitric oxide (NO) and prostaglandin E2 (PGE2)), decreased the secretion of proinflammatory cytokines (tumor necrosis factor (TNF)-α, interleukin (IL)-1β and IL-6), inhibited the activation of c-Jun amino-terminal kinase (JNK), p38 and nuclear factor-κB (NF-κB) signaling pathways, and repressed the nucleotide-binding and oligomerization domain (NOD)-, leucine-rich repeat (LRR)- and pyrin domain-containing protein 3 (NLRP3) inflammasome activation. These results indicated that mycotoxin ZEA attenuates macrophage-mediated innate immunity upon LPS stimulation, suggesting that the intake of mycotoxin ZEA-contaminated food might result in decreasing innate immunity, which has a higher risk of adverse effects during infection.
    Type of Medium: Online Resource
    ISSN: 2072-6651
    URL: Article
    DOI: 10.3390/toxins13090593
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2518395-3
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  • 6
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    The Application of Projection Word Embeddings on Medical Records Scoring System
    MDPI AG ; 2021
    In:  Healthcare Vol. 9, No. 10 ( 2021-09-29), p. 1298-
    Details
    In: Healthcare, MDPI AG, Vol. 9, No. 10 ( 2021-09-29), p. 1298-
    Abstract: Medical records scoring is important in a health care system. Artificial intelligence (AI) with projection word embeddings has been validated in its performance disease coding tasks, which maintain the vocabulary diversity of open internet databases and the medical terminology understanding of electronic health records (EHRs). We considered that an AI-enhanced system might be also applied to automatically score medical records. This study aimed to develop a series of deep learning models (DLMs) and validated their performance in medical records scoring task. We also analyzed the practical value of the best model. We used the admission medical records from the Tri-Services General Hospital during January 2016 to May 2020, which were scored by our visiting staffs with different levels from different departments. The medical records were scored ranged 0 to 10. All samples were divided into a training set (n = 74,959) and testing set (n = 152,730) based on time, which were used to train and validate the DLMs, respectively. The mean absolute error (MAE) was used to evaluate each DLM performance. In original AI medical record scoring, the predicted score by BERT architecture is closer to the actual reviewer score than the projection word embedding and LSTM architecture. The original MAE is 0.84 ± 0.27 using the BERT model, and the MAE is 1.00 ± 0.32 using the LSTM model. Linear mixed model can be used to improve the model performance, and the adjusted predicted score was closer compared to the original score. However, the project word embedding with the LSTM model (0.66 ± 0.39) provided better performance compared to BERT (0.70 ± 0.33) after linear mixed model enhancement (p 〈 0.001). In addition to comparing different architectures to score the medical records, this study further uses a mixed linear model to successfully adjust the AI medical record score to make it closer to the actual physician’s score.
    Type of Medium: Online Resource
    ISSN: 2227-9032
    URL: Article
    DOI: 10.3390/healthcare9101298
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2721009-1
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  • 7
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    Comparison of Dental Surface Image Registration and Fiducial Marker Registration: An In Vivo Accuracy Study of Static Computer-Assisted Implant Surgery
    MDPI AG ; 2021
    In:  Journal of Clinical Medicine Vol. 10, No. 18 ( 2021-09-16), p. 4183-
    Details
    In: Journal of Clinical Medicine, MDPI AG, Vol. 10, No. 18 ( 2021-09-16), p. 4183-
    Abstract: This study compared the accuracy of static computer-assisted implant surgery (sCAIS) planned through dental surface image registration and fiducial marker registration. Stone models of 30 patients were converted into digital dental casts by using a desktop scanner. Cone-beam computed tomography (CBCT) was performed and superimposed to the digital dental casts with two methods: matching the dental surface images or matching the fiducial markers on a stereolithographic radiographic template. Following the implant planning, stereolithographic surgical guides were fabricated, and 56 fully guided implants were inserted by the same doctor. Deviations between planned and inserted implants were measured and compared using postoperative CBCT images. After adjustment for other potential influencing factors, compared with the fiducial marker registration group, significantly larger mean lateral deviations were noted in the dental surface registration group at both the implant platform and apex (p = 0.0188 and 0.0371, respectively). However, the mean lateral deviations for the dental surface registration (0.83 ± 0.51 mm at implant platform and 1.24 ± 0.68 mm at implant apex) were comparable to the literature. In conclusion, our findings indicate that although sCAIS planned using dental surface image registration was not statistically as accurate as that using fiducial marker registration, its accuracy was satisfactory for clinical use.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    URL: Article
    DOI: 10.3390/jcm10184183
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2662592-1
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  • 8
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    Geopolymer Technologies for Stabilization of Basic Oxygen Furnace Slags and Sustainable Application as Construction Materials
    MDPI AG ; 2020
    In:  Sustainability Vol. 12, No. 12 ( 2020-06-18), p. 5002-
    Details
    In: Sustainability, MDPI AG, Vol. 12, No. 12 ( 2020-06-18), p. 5002-
    Abstract: The basic oxygen furnace slag is a major waste by-product generated from steel-producing plants. It possesses excellent characteristics and can be used as a natural aggregate. Chemically, the basic oxygen furnace slag encloses free CaO and free MgO, which is the main reason for the expansion crisis since these free oxides of alkaline earth metals react with water to form their hydroxide yields. The objective of the present research study is to stabilize the basic oxygen furnace slag by using innovative geopolymer technology, as their matrix contains a vast quantity of free silicon, which can react with free CaO and free MgO to form stable silicate compounds resulting in the prevention of the basic oxygen furnace slag expansion predicament. Lab-scale and ready-mixed plant pilot-scale experimental findings revealed that the compressive strength of fine basic oxygen furnace slag-based geopolymer mortar can achieve a compressive strength of 30–40 MPa after 28 days, and increased compressive strength, as well as the expansion, can be controlled less than 0.5% after ASTM C151 autoclave testing. Several pilot-scale cubic meters basic oxygen furnace slag-based geopolymer concrete blocks were developed in a ready-mixed plant. The compressive strength and autoclave expansion test results demonstrated that geopolymer technology does not merely stabilize the basic oxygen furnace slag production issue totally, but also turns the slags into value-added products.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su12125002
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2518383-7
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  • 9
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    Prognostic Value of CD1B in Localised Prostate Cancer
    MDPI AG ; 2019
    In:  International Journal of Environmental Research and Public Health Vol. 16, No. 23 ( 2019-11-27), p. 4723-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 16, No. 23 ( 2019-11-27), p. 4723-
    Abstract: Cluster of differentiation (CD) antigens are cell surface markers used to differentiate haematopoietic cell types. These antigens are present in various malignancies and are reportedly linked to patient prognosis; however, they have not been implemented as prostate cancer progression markers. Here, we aimed to assess the impact of genetic variation in haematopoietic cell CD markers on clinical outcomes in patients with prostate cancer. An association study of 458 patients with prostate cancer was conducted to identify single-nucleotide polymorphisms in 11 candidate CD marker genes associated with biochemical recurrence (BCR) after radical prostatectomy. Identified predictors were further evaluated in an additional cohort of 185 patients. Joint population analyses showed that CD1B rs3181082 is associated with BCR (adjusted hazard ratio 1.42, 95% confidence interval 1.09–1.85, p = 0.010). In addition, rs3181082 overlapped with predicted transcriptional regulatory elements and affected CD1B expression. Furthermore, low CD1B expression correlated with poorer BCR-free survival. Our results indicated that CD1B rs3181082 confers prostate cancer progression and may help improve clinical prognostic stratification.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph16234723
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2175195-X
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  • 10
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    The Impact on the Clinical Prognosis of Low Serum Selenium Level in Patients with Severe Trauma: Systematic Review and Meta-Analysis
    MDPI AG ; 2022
    In:  Nutrients Vol. 14, No. 6 ( 2022-03-18), p. 1295-
    Details
    In: Nutrients, MDPI AG, Vol. 14, No. 6 ( 2022-03-18), p. 1295-
    Abstract: This study was designed to examine the most up-to-date evidence about how low plasma selenium (Se) concentration affects clinical outcomes, such as mortality, infectious complications, and length of ICU or hospital stay, in patients with major trauma. We searched three databases (MEDLINE, EMBASE, and Web of Science) with the following keywords: “injury”, “trauma”, “selenium”, and “trace element”. Only records written in English published between 1990 and 2021 were included for analysis. Four studies were eligible for meta-analyses. The results of the meta-analysis showed that a low serum selenium level did not exert a negative effect on the mortality rate (OR 1.07, 95% CI: 0.32, 3.61, p = 0.91, heterogeneity, I2 = 44%). Regarding the incidence of infectious complications, there was no statistically significant deficit after analyses of the four studies (OR 1.61, 95% CI: 0.64, 4.07, p = 0.31, heterogeneity, I2 = 70%). There were no differences in the days spent in the ICU (difference in means (MD) 1.53, 95% CI: −2.15, 5.22, p = 0.41, heterogeneity, I2 = 67%) or the hospital length of stay (MD 6.49, 95% CI: −4.05, 17.02, p = 0.23, heterogeneity, I2 = 58%) in patients with low serum Se concentration. A low serum selenium level after trauma is not uncommon. However, it does not negatively affect mortality and infection rate. It also does not increase the overall length of ICU and hospital stays.
    Type of Medium: Online Resource
    ISSN: 2072-6643
    URL: Article
    DOI: 10.3390/nu14061295
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518386-2
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