Age-Associated Lipidome Changes in Metaphase II Mouse Oocytes

The quality of mammalian oocytes declines with age, which negatively affects fertilization and developmental potential. The aging process often accompanies damages to macromolecules such as proteins, DNA, and lipids. To investigate if aged oocytes display an altered lipidome compared to young oocytes, we performed a global lipidomic analysis between oocytes from 4-week-old and 42 to 50-week-old mice. Increased oxidative stress is often considered as one of the main causes of cellular aging. Thus, we set up a group of 4-week-old oocytes treated with hydrogen peroxide (H₂O₂), a commonly used oxidative stressor, to compare if similar lipid species are altered between aged and oxidative-stressed oocytes. Between young and aged oocytes, we identified 26 decreased and 6 increased lipids in aged oocytes; and between young and H₂O₂-treated oocytes, we identified 35 decreased and 26 increased lipids in H₂O₂-treated oocytes. The decreased lipid species in these two comparisons were overlapped, whereas the increased lipid species were distinct. Multiple phospholipid classes, phosphatidic acid (PA), phosphatidylinositol (PI), phosphatidylserine (PS), and lysophosphatidylserine (LPS) significantly decreased both in H₂O₂-treated and aged oocytes, suggesting that the integrity of plasma membrane is similarly affected under these conditions. In contrast, a dramatic increase in diacylglycerol (DG) was only noted in H₂O₂-treated oocytes, indicating that the acute effect of H₂O₂-caused oxidative stress is distinct from aging-associated lipidome alteration. In H₂O₂-treated oocytes, the expression of lysophosphatidylcholine acyltransferase 1 increased along with increases in phosphatidylcholine. Overall, our data reveal that several classes of phospholipids are affected in aged oocytes, suggesting that the integrity of plasma membrane is associated with maintaining fertilization and developmental potential of mouse oocytes.     

The Largest Known Survival Analysis of Patients with Brain Metastasis from Thyroid Cancer Based on Prognostic Groups

PurposeTo analyze the clinical features and prognostic factors associated with the survival of patients with a very rare occurrence of brain metastasis (BM) from differentiated thyroid cancer (DTC).ResultsThe median age at BM was 63 years, and the median time from initial thyroid cancer diagnosis to BM was 3.8 years. The median survival and the 1-year actuarial survival rate after BM were 8.8 months and 47%, respectively. According to univariate and multivariate analyses, four good prognostic factors (GPFs) were identified including age ≤ 60 years, PS ≤ ECOG 2, ≤ 3 BM sites, and without extracranial metastasis prior to BM. Three prognostic groups were designed based on age and number of remaining GPFs: patients ≤ 60 years of age with at least 2 GPFs (Group A) had the most favorable prognosis with a median survival of 32.8 months; patients ≤ 60 years of age with fewer than 2 GPFs and those > 60 years of age with at least 2 GPFs (Group B) had an intermediate prognosis with a median survival of 9.4 months; and patients > 60 years of age with fewer than 2 GPFs (Group C) had the least favorable prognosis with a median survival of 1.5 months.ConclusionsThe survival of patients with BM form DTC differed among the prognostic groups based on the total number of good prognostic factors.     

Simple Scoring System and Artificial Neural Network for Knee Osteoarthritis Risk Prediction: A Cross-Sectional Study

Background

Knee osteoarthritis (OA) is the most common joint disease of adults worldwide. Since the treatments for advanced radiographic knee OA are limited, clinicians face a significant challenge of identifying patients who are at high risk of OA in a timely and appropriate way. Therefore, we developed a simple self-assessment scoring system and an improved artificial neural network (ANN) model for knee OA.

Methods

The Fifth Korea National Health and Nutrition Examination Surveys (KNHANES V-1) data were used to develop a scoring system and ANN for radiographic knee OA. A logistic regression analysis was used to determine the predictors of the scoring system. The ANN was constructed using 1777 participants and validated internally on 888 participants in the KNHANES V-1. The predictors of the scoring system were selected as the inputs of the ANN. External validation was performed using 4731 participants in the Osteoarthritis Initiative (OAI). Area under the curve (AUC) of the receiver operating characteristic was calculated to compare the prediction models.

Results

The scoring system and ANN were built using the independent predictors including sex, age, body mass index, educational status, hypertension, moderate physical activity, and knee pain. In the internal validation, both scoring system and ANN predicted radiographic knee OA (AUC 0.73 versus 0.81, p<0.001) and symptomatic knee OA (AUC 0.88 versus 0.94, p<0.001) with good discriminative ability. In the external validation, both scoring system and ANN showed lower discriminative ability in predicting radiographic knee OA (AUC 0.62 versus 0.67, p<0.001) and symptomatic knee OA (AUC 0.70 versus 0.76, p<0.001).

Conclusions

The self-assessment scoring system may be useful for identifying the adults at high risk for knee OA. The performance of the scoring system is improved significantly by the ANN. We provided an ANN calculator to simply predict the knee OA risk.     

Characterization of Ternary Protein Systems In?Vivo with Tricolor Heterospecies Partition Analysis

Tools and assays that characterize protein-protein interactions are of fundamental importance to biology, because protein assemblies play a critical role in the control and regulation of nearly every cellular process. The availability of fluorescent proteins has facilitated the direct and real-time observation of protein-protein interactions inside living cells, but existing methods are mostly limited to binary interactions between two proteins. Because of the scarcity of techniques capable of identifying ternary interactions, we developed tricolor heterospecies partition analysis. The technique is based on brightness analysis of fluorescence fluctuations from three fluorescent proteins that serve as protein labels. We identified three fluorescent proteins suitable for tricolor brightness experiments. In addition, we developed the theory of identifying interactions in a ternary protein system using tricolor heterospecies partition analysis. The theory was verified by experiments on well-characterized protein systems. A graphical representation of the heterospecies partition data was introduced to visualize interactions in ternary protein systems. Lastly, we performed fluorescence fluctuation experiments on cells expressing a coactivator and two nuclear receptors and applied heterospecies partition analysis to explore the interactions of this ternary protein system.     

Retraction Note to: Enhancement of the catalytic activity of ferulic acid decarboxylase from Enterobacter sp. Px6-4 through random and site-directed mutagenesis

Applied Microbiology and Biotechnology -