Modified Damus-Kaye-Stansel/Dor Procedure for a Newborn With Severe Left Ventricular Aneurysm

Congenital left ventricular aneurysm (CVA) is a rare cardiac malformation. The prognosis is variable, depending on such factors as the size in comparison to the ventricular cavity, signs of heart failure, arrhythmia and so on. Most infants and young children with large aneurysm showed poor clinical outcomes. Here, we report the case of patient who was prenatally diagnosed with a large CVA, who had severe left ventricular dysfunction at 21 weeks' gestation for which she successfully underwent a modified Damus-Kaye-Stansel/Dor procedure

Prediction of Individual Propofol Requirements based on Preoperative EEG Signals

The patient must be given an adequate amount of propofol for safe surgery since overcapacity and low capacity cause accidents. However, the sensitivity of propofol varies from patient to patient, making it very difficult to determine the propofol requirements for anesthesia. This paper aims to propose a neurophysiological predictor of propofol requirements based on the preoperative electroencephalogram (EEG). We exploited the canonical correlation analysis that infers the amount of information on the propofol requirements. The results showed that the preoperative EEG included the factor that could explain the propofol requirements. Specifically, the frontal and posterior regions had crucial information on the propofol requirements. Moreover, there was a significantly different power in the frontal and posterior regions between baseline and unconsciousness periods, unlike the alpha power in the central region. These findings showed the potential that preoperative EEG could predict the propofol requirements.Comment: 5 pages, 1 figure, 1 tabl

Chiral magnetoresistance in Pt/Co/Pt zigzag wires

The Rashba effect leads to a chiral precession of the spins of moving electrons while the Dzyaloshinskii-Moriya interaction (DMI) generates preference towards a chiral profile of local spins. We predict that the exchange interaction between these two spin systems results in a 'chiral' magnetoresistance depending on the chirality of the local spin texture. We observe this magnetoresistance by measuring the domain wall (DW) resistance in a uniquely designed Pt/Co/Pt zigzag wire, and by changing the chirality of the DW with applying an in-plane magnetic field. A chirality-dependent DW resistance is found, and a quantitative analysis shows a good agreement with a theory based on the Rashba model. Moreover, the DW resistance measurement allows us to independently determine the strength of the Rashba effect and the DMI simultaneously, and the result implies a possible correlation between the Rashba effect, the DMI, and the symmetric Heisenberg exchange

Critical heat flux enhancement in flow boiling of Al 2O 3 and SiC nanofluids under low pressure and low flow conditions

Critical heat flux (CHF) is the thermal limit of a phenomenon in which a phase change occurs during heating (such as bubbles forming on a metal surface used to heat water), which suddenly decreases the heat transfer efficiency, thus causing localized overheating of the heating surface. The enhancement of CHF can increase the safety margins and allow operation at higher heat fluxes; thus, it can increase the economy. A very interesting characteristic of nanofluids is their ability to significantly enhance the CHF. Nanofluids are nanotechnology-based colloidal dispersions engineered through the stable suspension of nanoparticles. All experiments were performed in round tubes with an inner diameter of 0.01041 m and a length of 0.5 m under low pressure and low flow (LPLF) conditions at a fixed inlet temperature using water, 0.01 vol.% Al2O3/water nanofluid, and SiC/water nanofluid. It was found that the CHF of the nanofluids was enhanced and the CHF of the SiC/water nanofluid was more enhanced than that of the Al2O3/water nanofluid.close6

Catalpol Modulates Lifespan via DAF-16/FOXO and SKN-1/Nrf2 Activation in

Catalpol is an effective component of rehmannia root and known to possess various pharmacological properties. The present study was aimed at investigating the potential effects of catalpol on the lifespan and stress tolerance using C. elegans model system. Herein, catalpol showed potent lifespan extension of wild-type nematode under normal culture condition. In addition, survival rate of catalpol-fed nematodes was significantly elevated compared to untreated control under heat and oxidative stress but not under hyperosmolality conditions. We also found that elevated antioxidant enzyme activities and expressions of stress resistance proteins were attributed to catalpol-mediated increased stress tolerance of nematode. We further investigated whether catalpol’s longevity effect is related to aging-related factors including reproduction, food intake, and growth. Interestingly, catalpol exposure could attenuate pharyngeal pumping rate, indicating that catalpol may induce dietary restriction of nematode. Moreover, locomotory ability of aged nematode was significantly improved by catalpol treatment, while lipofuscin levels were attenuated, suggesting that catalpol may affect age-associated changes of nematode. Our mechanistic studies revealed that mek-1, daf-2, age-1, daf-16, and skn-1 are involved in catalpol-mediated longevity. These results indicate that catalpol extends lifespan and increases stress tolerance of C. elegans via DAF-16/FOXO and SKN-1/Nrf activation dependent on insulin/IGF signaling and JNK signaling

Effects of exercise on obesity-induced mitochondrial dysfunction in skeletal muscle

Obesity is known to induce inhibition of glucose uptake, reduction of lipid metabolism, and progressive loss of skeletal muscle function, which are all as- sociated with mitochondrial dysfunction in skeletal muscle. Mitochondria are dy- namic organelles that regulate cellular metabolism and bioenergetics, including ATP production via oxidative phosphorylation. Due to these critical roles of mitochon- dria, mitochondrial dysfunction results in various diseases such as obesity and type 2 diabetes. Obesity is associated with impairment of mitochondrial function (e.g., decrease in O2 respiration and increase in oxidative stress) in skeletal muscle. The bal- ance between mitochondrial fusion and fission is critical to maintain mitochondrial homeostasis in skeletal muscle. Obesity impairs mitochondrial dynamics, leading to an unbalance between fusion and fission by favorably shifting fission or reducing fusion proteins. Mitophagy is the catabolic process of damaged or unnecessary mito- chondria. Obesity reduces mitochondrial biogenesis in skeletal muscle and increases accumulation of dysfunctional cellular organelles, suggesting that mitophagy does not work properly in obesity. Mitochondrial dysfunction and oxidative stress are reported to trigger apoptosis, and mitochondrial apoptosis is induced by obesity in skeletal muscle. It is well known that exercise is the most effective intervention to protect against obesity. Although the cellular and molecular mechanisms by which exercise protects against obesity-induced mitochondrial dysfunction in skeletal mus- cle are not clearly elucidated, exercise training attenuates mitochondrial dysfunction, allows mitochondria to maintain the balance between mitochondrial dynamics and mitophagy, and reduces apoptotic signaling in obese skeletal muscle

Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression:Prediction Model Development Study

BACKGROUND: Mood disorder has emerged as a serious concern for public health; in particular, bipolar disorder has a less favorable prognosis than depression. Although prompt recognition of depression conversion to bipolar disorder is needed, early prediction is challenging due to overlapping symptoms. Recently, there have been attempts to develop a prediction model by using federated learning. Federated learning in medical fields is a method for training multi-institutional machine learning models without patient-level data sharing. OBJECTIVE: This study aims to develop and validate a federated, differentially private multi-institutional bipolar transition prediction model. METHODS: This retrospective study enrolled patients diagnosed with the first depressive episode at 5 tertiary hospitals in South Korea. We developed models for predicting bipolar transition by using data from 17,631 patients in 4 institutions. Further, we used data from 4541 patients for external validation from 1 institution. We created standardized pipelines to extract large-scale clinical features from the 4 institutions without any code modification. Moreover, we performed feature selection in a federated environment for computational efficiency and applied differential privacy to gradient updates. Finally, we compared the federated and the 4 local models developed with each hospital's data on internal and external validation data sets. RESULTS: In the internal data set, 279 out of 17,631 patients showed bipolar disorder transition. In the external data set, 39 out of 4541 patients showed bipolar disorder transition. The average performance of the federated model in the internal test (area under the curve [AUC] 0.726) and external validation (AUC 0.719) data sets was higher than that of the other locally developed models (AUC 0.642-0.707 and AUC 0.642-0.699, respectively). In the federated model, classifications were driven by several predictors such as the Charlson index (low scores were associated with bipolar transition, which may be due to younger age), severe depression, anxiolytics, young age, and visiting months (the bipolar transition was associated with seasonality, especially during the spring and summer months). CONCLUSIONS: We developed and validated a differentially private federated model by using distributed multi-institutional psychiatric data with standardized pipelines in a real-world environment. The federated model performed better than models using local data only.</p