ABSTRACT
Gyrokinetic simulations of the fishbone instability in DIII-D tokamak plasmas find that self-generated zonal flows can dominate the nonlinear saturation by preventing coherent structures from persisting or drifting in the energetic particle phase space when the mode frequency down-chirps. Results from the simulation with zonal flows agree quantitatively, for the first time, with experimental measurements of the fishbone saturation amplitude and energetic particle transport. Moreover, the fishbone-induced zonal flows are likely responsible for the formation of an internal transport barrier that was observed after fishbone bursts in this DIII-D experiment. Finally, gyrokinetic simulations of a related ITER baseline scenario show that the fishbone induces insignificant energetic particle redistribution and may enable high performance scenarios in ITER burning plasma experiments.
ABSTRACT
Objective: To evaluate the efficacy of 0.05% cyclosporine A eye drops combined with vitamin A palmitate eye gel in the treatment of dry eye associated with meibomian gland dysfunction (MGD). Methods: A single-center, prospective, randomized, parallel controlled trial design was used to include patients diagnosed with MGD-associated dry eye. The patients were randomly divided into three groups and administered with medications binocularly for 12 weeks. The CsA+VA group was given 0.05% cyclosporine A eye drops twice a day and vitamin A palmitate eye gel three times a day. The CsA+HA group was given 0.05% cyclosporine A eye drops twice a day and 0.1% sodium hyaluronate eye drops three times a day. The HA group was given 0.1% sodium hyaluronate eye drops 3 times a day. The OSDI score, tear meniscus height, fluorescein tear break-up time, Schirmer â test (without anesthesia), tear film lipid layer thickness, meibomian gland morphology and function examination, and corneal fluorescein sodium staining score were evaluated at baseline, 4, 8, and 12 weeks after the initiation of the treatment, respectively. Results: A total of 120 patients with MGD-related dry eye met the enrollment criteria, but 10 patients were lost to follow-up; 110 patients were finally included for observation, including 36 patients in the CsA+VA group, 38 in the CsA+HA group and 36 in the HA group. The OSDI score, tear meniscus height, fluorescein tear break-up time and meibomian gland secretion of the 3 groups were significantly improved. At the 12th week of the treatment, the differences of the CsA+VA group [25.45±15.11, (0.30±0.13) mm, (3.72±1.40) s, (5.03±2.52) points] and the CsA+HA group [26.98±16.89, (0.27±0.10) mm, (4.34±1.76) s, (5.11±2.39) points] from the HA group [24.57±11.26, (0.24±0.06) mm, (3.18±1.11) s, (9.11±3.34) points] were statistically significant (P<0.05). Compared with the CsA+HA group [(68.39±26.66) nm], the tear film lipid layer thickness in the CsA+VA group [(72.61±23.65) nm] was significantly increased (P<0.05). In the CsA+VA group, the meibomian gland secretion characters and discharge capacity among patients with severe abnormalities [(6.28±2.59) and (5.89±2.77) points at the 12th week of treatment], moderate abnormalities [(4.27±2.02) and (4.64±2.02) points at the 12th week of treatment] and mild abnormalities [(2.80±0.84) and (2.60±0.55) points at the 12th week of treatment] were significantly different (P<0.05). Conclusion: 0.05% cyclosporine A combined with vitamin A palmitate can significantly improve the symptoms and signs of patients with MGD-related dry eye, especially the tear film lipid layer thickness and the meibomian gland secretion characters and discharge capacity in severe cases.
Subject(s)
Diterpenes , Dry Eye Syndromes , Meibomian Gland Dysfunction , Retinyl Esters , Humans , Cyclosporine/therapeutic use , Prospective Studies , Hyaluronic Acid , Meibomian Glands , Tears , Dry Eye Syndromes/diagnosis , Ophthalmic Solutions/therapeutic use , Lipids , Fluoresceins/therapeutic useABSTRACT
OBJECTIVE: To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation (VA-ECMO). METHODS: We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January, 2015 and January, 2022 using a convenience sampling method. The patients were divided into a derivation cohort (201 cases) and a validation cohort (101 cases). Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients, based on which a risk prediction model was established in the form of a nomogram. The receiver operator characteristic (ROC) curve, calibration curve and clinical decision curve were used to evaluate the discrimination ability, calibration and clinical validity of this model. RESULTS: The in-hospital mortality risk prediction model was established based the risk factors including hypertension (OR=3.694, 95% CI: 1.582-8.621), continuous renal replacement therapy (OR=9.661, 95%CI: 4.103-22.745), elevated Na2 + level (OR=1.048, 95% CI: 1.003-1.095) and increased hemoglobin level (OR=0.987, 95% CI: 0.977-0.998). In the derivation cohort, the area under the ROC curve (AUC) of this model was 0.829 (95% CI: 0.770-0.889), greater than those of the 4 single factors (all AUC < 0.800), APACHE II Score (AUC=0.777, 95% CI: 0.714-0.840) and the SOFA Score (AUC=0.721, 95% CI: 0.647-0.796). The results of internal validation showed that the AUC of the model was 0.774 (95% CI: 0.679-0.869), and the goodness of fit test showed a good fitting of this model (χ2=4.629, P>0.05). CONCLUSION: The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation, calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system, and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.
Subject(s)
Extracorporeal Membrane Oxygenation , Humans , Retrospective Studies , Hospital Mortality , Extracorporeal Membrane Oxygenation/methods , Case-Control Studies , Prognosis , ROC CurveABSTRACT
The increasing application of virtual surgical planning (VSP) in orthognathic surgery implies a critical need for accurate prediction of facial and skeletal shapes. The craniofacial relationship in patients with dentofacial deformities is still not understood, and transformations between facial and skeletal shapes remain a challenging task due to intricate anatomical structures and nonlinear relationships between the facial soft tissue and bones. In this study, a novel bidirectional 3-dimensional (3D) deep learning framework, named P2P-ConvGC, was developed and validated based on a large-scale data set for accurate subject-specific transformations between facial and skeletal shapes. Specifically, the 2-stage point-sampling strategy was used to generate multiple nonoverlapping point subsets to represent high-resolution facial and skeletal shapes. Facial and skeletal point subsets were separately input into the prediction system to predict the corresponding skeletal and facial point subsets via the skeletal prediction subnetwork and facial prediction subnetwork. For quantitative evaluation, the accuracy was calculated with shape errors and landmark errors between the predicted skeleton or face with corresponding ground truths. The shape error was calculated by comparing the predicted point sets with the ground truths, with P2P-ConvGC outperforming existing state-of-the-art algorithms including P2P-Net, P2P-ASNL, and P2P-Conv. The total landmark errors (Euclidean distances of craniomaxillofacial landmarks) of P2P-ConvGC in the upper skull, mandible, and facial soft tissues were 1.964 ± 0.904 mm, 2.398 ± 1.174 mm, and 2.226 ± 0.774 mm, respectively. Furthermore, the clinical feasibility of the bidirectional model was validated using a clinical cohort. The result demonstrated its prediction ability with average surface deviation errors of 0.895 ± 0.175 mm for facial prediction and 0.906 ± 0.082 mm for skeletal prediction. To conclude, our proposed model achieved good performance on the subject-specific prediction of facial and skeletal shapes and showed clinical application potential in postoperative facial prediction and VSP for orthognathic surgery.