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  • 1
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    Online Resource
    The Current Status and Future Prospects of KAGRA, the Large-Scale Cryogenic Gravitational Wave Telescope Built in the Kamioka Underground
    MDPI AG ; 2022
    In:  Galaxies Vol. 10, No. 3 ( 2022-04-26), p. 63-
    Details
    In: Galaxies, MDPI AG, Vol. 10, No. 3 ( 2022-04-26), p. 63-
    Abstract: KAGRA is a gravitational-wave (GW) detector constructed in Japan with two unique key features: It was constructed underground, and the test-mass mirrors are cooled to cryogenic temperatures. These features are not included in other kilometer-scale detectors but will be adopted in future detectors such as the Einstein Telescope. KAGRA performed its first joint observation run with GEO600 in 2020. In this observation, the sensitivity of KAGRA to GWs was inferior to that of other kilometer-scale detectors such as LIGO and Virgo. However, further upgrades to the detector are ongoing to reach the sensitivity for detecting GWs in the next observation run, which is scheduled for 2022. In this article, the current situation, sensitivity, and future perspectives are reviewed.
    Type of Medium: Online Resource
    ISSN: 2075-4434
    URL: Article
    DOI: 10.3390/galaxies10030063
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2691049-4
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  • 2
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    Peri-Implant Marginal Bone Changes around Dental Implants with Platform-Switched and Platform-Matched Abutments: A Retrospective 5-Year Radiographic Evaluation
    MDPI AG ; 2022
    In:  Journal of Personalized Medicine Vol. 12, No. 8 ( 2022-07-27), p. 1226-
    Details
    In: Journal of Personalized Medicine, MDPI AG, Vol. 12, No. 8 ( 2022-07-27), p. 1226-
    Abstract: Preserving the marginal bone level (MBL) is essential for the long-term success of dental implant therapy, and bone remodeling around dental implants is considered to vary with time. Numerous studies comparing the platform-switching (PS) and platform-matching (PM) dental implants have indicated that PS dental implants showed a lesser reduction for the MBL, and the majority of them had a relatively short period. This study aimed to evaluate vertical and horizontal bone defects by using digital periapical radiographs to examine the changes in MBL around PM and PS dental implants over 5 years after functional loading. The vertical MBL (vMBL) was measured from the implant–abutment junction to the first bone-to-implant contact. The horizontal MBL (hMBL) was measured from the implant–abutment junction to the bone crest. All data were presented as means ± standard errors. Paired and independent t-tests with Welch’s correction were used to analyze the data. A total of 61 dental implants in 38 patients after 5 years of functional loading were evaluated. Over time, PS dental implants were more likely to gain bone; by contrast, PM dental implants were more likely to lose bone during the observation time. Changes in vMBL for PS dental implants were significantly less than those for PM dental implants at 1-year (p = 0.045), 3-year (p = 0.021), and 5-year (p = 0.010) loading. Likewise, changes in hMBL for PS dental implants were significantly smaller than in those for PM dental implants at 3-year (p = 0.021) and 5-year (p = 0.006) loading; however, the changes were minimal in both approaches. PS dental implants had a significant increment in the percentage of bone integration, whereas that for PM dental implants dropped over time, with no significance. In PS dental implants that occlude with natural teeth, vertical and horizontal bone gain was observed, and it was significant at 3 years (p = 0.023). A significant horizontal bone gain was observed in the opposing natural teeth at 3-year (p = 0.002) and 5-year loading (p = 0.002). The PS concept appears to preserve more MBL around dental implants by stabilizing the vMBL and hMBL over a 5-year period. A minimal marginal bone change was detected in both concepts. The opposing natural teeth at PS dental implants showed a favorable effect on marginal bone tissues.
    Type of Medium: Online Resource
    ISSN: 2075-4426
    URL: Article
    DOI: 10.3390/jpm12081226
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662248-8
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  • 3
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    Effects of Pitavastatin, Atorvastatin, and Rosuvastatin on the Risk of New-Onset Diabetes Mellitus: A Single-Center Cohort Study
    MDPI AG ; 2020
    In:  Biomedicines Vol. 8, No. 11 ( 2020-11-13), p. 499-
    Details
    In: Biomedicines, MDPI AG, Vol. 8, No. 11 ( 2020-11-13), p. 499-
    Abstract: Statins constitute the mainstay treatment for atherosclerotic cardiovascular disease, which is associated with the risk of new-onset diabetes mellitus (NODM). However, the effects of individual statins on the risk of NODM remain unclear. We recruited 48,941 patients taking one of the three interested statins in a tertiary hospital between 2006 and 2018. Among them, 8337 non-diabetic patients taking moderate-intensity statins (2 mg/day pitavastatin, 10 mg/day atorvastatin, and 10 mg/day rosuvastatin) were included. The pitavastatin group had a higher probability of being NODM-free than the atorvastatin and rosuvastatin groups during the 4-year follow-up (log-rank test: p = 0.038). A subgroup analysis revealed that rosuvastatin had a significantly higher risk of NODM than pitavastatin among patients with coronary artery disease (CAD) (adjusted HR [aHR] , 1.47, 95% confidence interval [CI], 1.05–2.05, p = 0.025), hypertension (aHR, 1.26, 95% CI, 1.00–1.59, p = 0.047), or chronic obstructive pulmonary disease (COPD) (aHR, 1.74, 95% CI, 1.02–2.94, p = 0.04). We concluded that compared with rosuvastatin, reduced diabetogenic effects of pitavastatin were observed among patients treated with moderate-intensity statin who had hypertension, COPD, or CAD. Additional studies are required to prove the effects of different statins on the risk of NODM.
    Type of Medium: Online Resource
    ISSN: 2227-9059
    URL: Article
    DOI: 10.3390/biomedicines8110499
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2720867-9
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  • 4
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    Associations of Warfarin Use with Risks of Ischemic Cerebrovascular Events and Major Bleeding in Patients with Hyperthyroidism-Related Atrial Fibrillation
    MDPI AG ; 2022
    In:  Biomedicines Vol. 10, No. 11 ( 2022-10-22), p. 2670-
    Details
    In: Biomedicines, MDPI AG, Vol. 10, No. 11 ( 2022-10-22), p. 2670-
    Abstract: The use of oral anticoagulants for patients with new-onset hyperthyroidism-related atrial fibrillation (AF) is controversial. We aimed to evaluate the clinical benefits of warfarin therapy in this population. This retrospective cohort study used a data-cut of Taiwan Health and Welfare Database between 2000 and 2016. We compared warfarin users and nonusers among AF patients with hyperthyroidism. We used 1:2 propensity score matching to balance covariates and Cox regression model to calculate hazard ratios (HRs). The primary outcome was risk of ischemic stroke/transient ischemic attack (TIA), and the secondary outcome was major bleeding. After propensity score matching, we defined 90 and 168 hyperthyroidism-related AF patients with mean (SD) age of 59.9 ± 13.5 and 59.2 ± 14.6 in the warfarin-treated group and untreated group separately. The mean (SD) CHA2DS2-VASc scores for the two groups were 2.1 ± 1.6 and 1.8 ± 1.5, respectively. Patients with hyperthyroidism-related AF receiving warfarin had no significant risk of ischemic stroke/TIA (adjusted HR: 1.16, 95% confidence interval [CI]: 0.52–2.56, p = 0.717) compared to nonusers. There was a comparable risk of major bleeding between those receiving warfarin or not (adjusted HR: 0.91, 95% CI: 0.56–1.47, p = 0.702). The active-comparator design also demonstrated that warfarin use had no significant association with the risk of stroke/TIA versus aspirin use (adjusted HR: 2.43; 95% CI: 0.68–8.70). In conclusion, anticoagulation therapy did not have a statistically significant benefit on ischemic stroke/TIA nor risk of bleeding, among patients with new-onset hyperthyroidism-related AF under a low CHA2DS2-VASc score, by comparing those without use.
    Type of Medium: Online Resource
    ISSN: 2227-9059
    URL: Article
    DOI: 10.3390/biomedicines10112670
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2720867-9
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  • 5
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    Detecting Digoxin Toxicity by Artificial Intelligence-Assisted Electrocardiography
    MDPI AG ; 2021
    In:  International Journal of Environmental Research and Public Health Vol. 18, No. 7 ( 2021-04-06), p. 3839-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 18, No. 7 ( 2021-04-06), p. 3839-
    Abstract: Although digoxin is important in heart rate control, the utilization of digoxin is declining due to its narrow therapeutic window. Misdiagnosis or delayed diagnosis of digoxin toxicity is common due to the lack of awareness and the time-consuming laboratory work that is involved. Electrocardiography (ECG) may be able to detect potential digoxin toxicity based on characteristic presentations. Our study attempted to develop a deep learning model to detect digoxin toxicity based on ECG manifestations. This study included 61 ECGs from patients with digoxin toxicity and 177,066 ECGs from patients in the emergency room from November 2011 to February 2019. The deep learning algorithm was trained using approximately 80% of ECGs. The other 20% of ECGs were used to validate the performance of the Artificial Intelligence (AI) system and to conduct a human-machine competition. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to evaluate the performance of ECG interpretation between humans and our deep learning system. The AUCs of our deep learning system for identifying digoxin toxicity were 0.912 and 0.929 in the validation cohort and the human-machine competition, respectively, which reached 84.6% of sensitivity and 94.6% of specificity. Interestingly, the deep learning system using only lead I (AUC = 0.960) was not worse than using complete 12 leads (0.912). Stratified analysis showed that our deep learning system was more applicable to patients with heart failure (HF) and without atrial fibrillation (AF) than those without HF and with AF. Our ECG-based deep learning system provides a high-accuracy, economical, rapid, and accessible way to detect digoxin toxicity, which can be applied as a promising decision supportive system for diagnosing digoxin toxicity in clinical practice.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph18073839
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2175195-X
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  • 6
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    TLR4-Activated MAPK-IL-6 Axis Regulates Vascular Smooth Muscle Cell Function
    MDPI AG ; 2016
    In:  International Journal of Molecular Sciences Vol. 17, No. 9 ( 2016-08-24), p. 1394-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 17, No. 9 ( 2016-08-24), p. 1394-
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms17091394
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 7
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    Therapeutic Effects of Live Lactobacillus plantarum GKD7 in a Rat Model of Knee Osteoarthritis
    MDPI AG ; 2022
    In:  Nutrients Vol. 14, No. 15 ( 2022-08-01), p. 3170-
    Details
    In: Nutrients, MDPI AG, Vol. 14, No. 15 ( 2022-08-01), p. 3170-
    Abstract: Osteoarthritis (OA) is a painful, progressive chronic inflammatory disease marked by cartilage destruction. Certain synovial inflammatory cytokines, such as IL-1β and TNF-α, promote OA inflammation and pain. Lactobacillus spp. is a well-known probiotic with anti-inflammatory, analgesic, antioxidant, and antiosteoporotic properties. This study evaluated the therapeutic effects of a live L. plantarum strain (GKD7) in the anterior cruciate ligament transection (ACLT)-induced OA rat model. The results show that oral administration of live L. plantarum GKD7 improved weight-bearing asymmetry after ACLT surgery. Moreover, micro-computed tomography images and histopathological analysis show that oral live L. plantarum GKD7 improved subchondral bone architecture, protected articular cartilage against ACLT-induced damage, and reduced synovial inflammation. L. plantarum GKD7 also reduced IL-1β and TNF-α production in OA cartilage and synovium. Thus, orally administered live L. plantarum GKD7 appears to effectively slow the progression of OA.
    Type of Medium: Online Resource
    ISSN: 2072-6643
    URL: Article
    DOI: 10.3390/nu14153170
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518386-2
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  • 8
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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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  • 9
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    A Genetic Hyper-Heuristic for an Order Scheduling Problem with Two Scenario-Dependent Parameters in a Parallel-Machine Environment
    MDPI AG ; 2022
    In:  Mathematics Vol. 10, No. 21 ( 2022-11-06), p. 4146-
    Details
    In: Mathematics, MDPI AG, Vol. 10, No. 21 ( 2022-11-06), p. 4146-
    Abstract: Studies on the customer order scheduling problem have been attracting increasing attention. Most current approaches consider that either component processing times for customer orders on each machine are constant or all customer orders are available at the outset of production planning. However, these assumptions do not hold in real-world applications. Uncertainty may be caused by multiple issues including a machine breakdown, the working environment changing, and workers’ instability. On the basis of these factors, we introduced a parallel-machine customer order scheduling problem with two scenario-dependent component processing times, due dates, and ready times. The objective was to identify an appropriate and robust schedule for minimizing the maximum of the sum of weighted numbers of tardy orders among the considered scenarios. To solve this difficult problem, we derived a few dominant properties and a lower bound for determining an optimal solution. Subsequently, we considered three variants of Moore’s algorithm, a genetic algorithm, and a genetic-algorithm-based hyper-heuristic that incorporated the proposed seven low-level heuristics to solve this problem. Finally, the performances of all proposed algorithms were evaluated.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math10214146
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704244-3
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  • 10
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    Artificial Intelligence-Enabled Electrocardiogram Estimates Left Atrium Enlargement as a Predictor of Future Cardiovascular Disease
    MDPI AG ; 2022
    In:  Journal of Personalized Medicine Vol. 12, No. 2 ( 2022-02-19), p. 315-
    Details
    In: Journal of Personalized Medicine, MDPI AG, Vol. 12, No. 2 ( 2022-02-19), p. 315-
    Abstract: Background: Left atrium enlargement (LAE) can be used as a predictor of future cardiovascular diseases, including hypertension (HTN) and atrial fibrillation (Afib). Typical electrocardiogram (ECG) changes have been reported in patients with LAE. This study developed a deep learning model (DLM)-enabled ECG system to identify patients with LAE. Method: Patients who had ECG records with corresponding echocardiography (ECHO) were included. There were 101,077 ECGs, 20,510 ECGs, 7611 ECGs, and 11,753 ECGs in the development, tuning, internal validation, and external validation sets, respectively. We evaluated the performance of a DLM-enabled ECG for diagnosing LAE and explored the prognostic value of ECG-LAE for new-onset HTN, new-onset stroke (STK), new-onset mitral regurgitation (MR), and new-onset Afib. Results: The DLM-enabled ECG achieved AUCs of 0.8127/0.8176 for diagnosing mild LAE, 0.8587/0.8688 for diagnosing moderate LAE, and 0.8899/0.8990 for diagnosing severe LAE in the internal/external validation sets. Notably, ECG-LAE had higher prognostic value compared to ECHO-LAE, which had C-indices of 0.711/0.714 compared to 0.695/0.692 for new-onset HTN, 0.676/0.688 compared to 0.663/0.677 for new-onset STK, 0.696/0.695 compared to 0.676/0.673 for new-onset MR, and 0.800/0.806 compared to 0.786/0.760 for new-onset Afib in internal/external validation sets, respectively. Conclusions: A DLM-enabled ECG could be considered as a LAE screening tool and provide better prognostic information for related cardiovascular diseases.
    Type of Medium: Online Resource
    ISSN: 2075-4426
    URL: Article
    DOI: 10.3390/jpm12020315
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662248-8
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