A Case of Fluorine-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Imaging of Eosinophilic Granulomatosis With Polyangiitis Combined With Non-tuberculous Mycobacterium

Fluorine-18-fluorodeoxyglucose positron emission tomography/ computed tomography (18FDG-PET/CT) has been used to diagnose vasculitis, tuberculosis and malignancy. Because PET/CT scan show hotspots during an activation of clinically suspected lesions, it is widely used for diagnosis. However, there are rare cases of PET/CT images for vasculitis combined with tuberculosis. Here we report a case of an eosinophilic granulomatosis with polyangiitis in a patient with disseminated non-tuberculosis mycobacterial infection in multiple sites mimicking metastatic malignacy and describe the associated PET/CT scan findings before and after treatment

A machine-learning approach to predict postprandial hypoglycemia

Background For an effective artificial pancreas (AP) system and an improved therapeutic intervention with continuous glucose monitoring (CGM), predicting the occurrence of hypoglycemia accurately is very important. While there have been many studies reporting successful algorithms for predicting nocturnal hypoglycemia, predicting postprandial hypoglycemia still remains a challenge due to extreme glucose fluctuations that occur around mealtimes. The goal of this study is to evaluate the feasibility of easy-to-use, computationally efficient machine-learning algorithm to predict postprandial hypoglycemia with a unique feature set. Methods We use retrospective CGM datasets of 104 people who had experienced at least one hypoglycemia alert value during a three-day CGM session. The algorithms were developed based on four machine learning models with a unique data-driven feature set: a random forest (RF), a support vector machine using a linear function or a radial basis function, a K-nearest neighbor, and a logistic regression. With 5-fold cross-subject validation, the average performance of each model was calculated to compare and contrast their individual performance. The area under a receiver operating characteristic curve (AUC) and the F1 score were used as the main criterion for evaluating the performance. Results In predicting a hypoglycemia alert value with a 30-min prediction horizon, the RF model showed the best performance with the average AUC of 0.966, the average sensitivity of 89.6%, the average specificity of 91.3%, and the average F1 score of 0.543. In addition, the RF showed the better predictive performance for postprandial hypoglycemic events than other models. Conclusion In conclusion, we showed that machine-learning algorithms have potential in predicting postprandial hypoglycemia, and the RF model could be a better candidate for the further development of postprandial hypoglycemia prediction algorithm to advance the CGM technology and the AP technology further.11Ysciescopu

Critical current densities and flux creep rates in near optimally doped BaFe2-xRuxAs2 (x≈0.7) single crystals

We present an investigation of the critical current densities Jc and flux creep rates in a near optimally doped BaFe2-xRuxAs2 (x≈0.7) single crystal by (measuring magnetization). The superconducting critical temperature is 18 K. The in-field dependences of the critical current density Jc are due to a mixed pinning scenario produced mainly by large precipitates and a less significant contribution of random disorder. Furthermore, a Maley analysis in the regime dominated by strong pinning centers (μ0H=0.1 T) is well described through a glassy exponent μ=1.9 and a collective pinning energy (U0) smaller than 100 K.Fil: Haberkorn, Nestor Fabian. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Eom, Man Jin. Pohang University of Science and Technology; Corea del SurFil: You, Jung Sang. Pohang University of Science and Technology; Corea del SurFil: Kim, Jeehoon. Pohang University of Science and Technology; Corea del SurFil: Kim, Jun Sung. Pohang University of Science and Technology; Corea del Su

Systems Biology from Virus to Humans

Natural infection and then recovery are considered to be the most effective means for hosts to build protective immunity. Thus, mimicking natural infection of pathogens, many live attenuated vaccines such as influenza virus, and yellow fever vaccine 17D were developed and have been successfully used to induce protective immunity. However, humans fail to generate long-term protective immunity to some pathogens after natural infection such as influenza virus, respiratory syncytial virus (RSV), and human immunodeficiency virus (HIV) even if they survive initial infections. Many vaccines are suboptimal since much mortality is still occurring, which is exampled by influenza and tuberculosis. It is critically important to increase our understanding on protein components of pathogens and vaccines as well as cellular and host responses to infections and vaccinations. Here, we highlight recent advances in gene transcripts and protein analysis results in the systems biology to enhance our understanding of viral pathogens, vaccines, and host cell responses

Prediction of Daytime Hypoglycemic Events Using Continuous Glucose Monitoring Data and Classification Technique

Daytime hypoglycemia should be accurately predicted to achieve normoglycemia and to avoid disastrous situations. Hypoglycemia, an abnormally low blood glucose level, is divided into daytime hypoglycemia and nocturnal hypoglycemia. Many studies of hypoglycemia prevention deal with nocturnal hypoglycemia. In this paper, we propose new predictor variables to predict daytime hypoglycemia using continuous glucose monitoring (CGM) data. We apply classification and regression tree (CART) as a prediction method. The independent variables of our prediction model are the rate of decrease from a peak and absolute level of the BG at the decision point. The evaluation results showed that our model was able to detect almost 80% of hypoglycemic events 15 min in advance, which was higher than the existing methods with similar conditions. The proposed method might achieve a real-time prediction as well as can be embedded into BG monitoring device.1

In situ-generated metal oxide catalyst during CO oxidation reaction transformed from redox-active metal-organic framework-supported palladium nanoparticles

The preparation of redox-active metal-organic framework (ra-MOF)-supported Pd nanoparticles (NPs) via the redox couple-driven method is reported, which can yield unprotected metallic NPs at room temperature within 10 min without the use of reducing agents. The Pd@ra-MOF has been exploited as a precursor of an active catalyst for CO oxidation. Under the CO oxidation reaction condition, Pd@ra-MOF is transformed into a PdOx-NiOy/C nanocomposite to generate catalytically active species in situ, and the resultant nanocatalyst shows sustainable activity through synergistic stabilization.open4

Structural studies on Helicobacter pylori ATP-dependent protease, FtsH

The crystal structures of the Helicobacter pylori FtsH ATPase domain in the nucleotide-free state and complexed with ADP have been determined

Drosophila Porin/VDAC Affects Mitochondrial Morphology

Voltage-dependent anion channel (VDAC) has been suggested to be a mediator of mitochondrial-dependent cell death induced by Ca2+ overload, oxidative stress and Bax-Bid activation. To confirm this hypothesis in vivo, we generated and characterized Drosophila VDAC (porin) mutants and found that Porin is not required for mitochondrial apoptosis, which is consistent with the previous mouse studies. We also reported a novel physiological role of Porin. Loss of porin resulted in locomotive defects and male sterility. Intriguingly, porin mutants exhibited elongated mitochondria in indirect flight muscle, whereas Porin overexpression produced fragmented mitochondria. Through genetic analysis with the components of mitochondrial fission and fusion, we found that the elongated mitochondria phenotype in porin mutants were suppressed by increased mitochondrial fission, but enhanced by increased mitochondrial fusion. Furthermore, increased mitochondrial fission by Drp1 expression suppressed the flight defects in the porin mutants. Collectively, our study showed that loss of Drosophila Porin results in mitochondrial morphological defects and suggested that the defective mitochondrial function by Porin deficiency affects the mitochondrial remodeling process