Feasibility of brain age predictions from clinical T1-weighted MRIs

An individual's brain predicted age minus chronological age (brain-PAD) obtained from MRIs could become a biomarker of disease in research studies. However, brain age reports from clinical MRIs are scant despite the rich clinical information hospitals provide. Since clinical MRI protocols are meant for specific clinical purposes, performance of brain age predictions on clinical data need to be tested. We explored the feasibility of using DeepBrainNet, a deep network previously trained on research-oriented MRIs, to predict the brain ages of 840 patients who visited 15 facilities of a health system in Florida. Anticipating a strong prediction bias in our clinical sample, we characterized it to propose a covariate model in group-level regressions of brain-PAD (recommended to avoid Type I, II errors), and tested its generalizability, a requirement for meaningful brain age predictions in new single clinical cases. The best bias-related covariate model was scanner-independent and linear in age, while the best method to estimate bias-free brain ages was the inverse of a scanner-independent and quadratic in brain age function. We demonstrated the feasibility to detect sex-related differences in brain-PAD using group-level regression accounting for the selected covariate model. These differences were preserved after bias correction. The Mean-Average Error (MAE) of the predictions in independent data was ∼8 years, 2-3 years greater than reports for research-oriented MRIs using DeepBrainNet, whereas an R2 (assuming no bias) was 0.33 and 0.76 for the uncorrected and corrected brain ages, respectively. DeepBrainNet on clinical populations seems feasible, but more accurate algorithms or transfer-learning retraining is needed

Toward MR protocol-agnostic, unbiased brain age predicted from clinical-grade MRIs

The difference between the estimated brain age and the chronological age ('brain-PAD') could become a clinical biomarker. However, most brain age models were developed for research-grade high-resolution T1-weighted MRIs, limiting their applicability to clinical-grade MRIs from various protocols. We adopted a dual-transfer learning strategy to develop a model agnostic to modality, resolution, or slice orientation. We retrained a convolutional neural network (CNN) using 6281 clinical MRIs from 1559 patients, among 7 modalities and 8 scanner models. The CNN was trained to estimate brain age from synthetic research-grade magnetization-prepared rapid gradient-echo MRIs (MPRAGEs) generated by a 'super-resolution' method. The model failed with T2-weighted Gradient-Echo MRIs. The mean absolute error (MAE) was 5.86-8.59 years across the other modalities, still higher than for research-grade MRIs, but comparable between actual and synthetic MPRAGEs for some modalities. We modeled the "regression bias" in brain age, for its correction is crucial for providing unbiased summary statistics of brain age or for personalized brain age-based biomarkers. The bias model was generalizable as its correction eliminated any correlation between brain-PAD and chronological age in new samples. Brain-PAD was reliable across modalities. We demonstrate the feasibility of brain age predictions from arbitrary clinical-grade MRIs, thereby contributing to personalized medicine

Crustal structure below Popocat\'epetl Volcano (Mexico) from analysis of Rayleigh waves

An array of ten broadband stations was installed on the Popocat\'epetl volcano (Mexico) for five months between October 2002 and February 2003. 26 regional and teleseismic earthquakes were selected and filtered in the frequency time domain to extract the fundamental mode of the Rayleigh wave. The average dispersion curve was obtained in two steps. Firstly, phase velocities were measured in the period range [2-50] s from the phase difference between pairs of stations, using Wiener filtering. Secondly, the average dispersion curve was calculated by combining observations from all events in order to reduce diffraction effects. The inversion of the mean phase velocity yielded a crustal model for the volcano which is consistent with previous models of the Mexican Volcanic Belt. The overall crustal structure beneath Popocat\'epetl is therefore not different from the surrounding area, and the velocities in the lower crust are confirmed to be relatively low. Lateral variations of the structure were also investigated by dividing the network into four parts and by applying the same procedure to each sub-array. No well-defined anomalies appeared for the two sub-arrays for which it was possible to measure a dispersion curve. However, dispersion curves associated with individual events reveal important diffraction for 6 s to 12 s periods which could correspond to strong lateral variations at 5 to 10 km depth

Total and high molecular weight adiponectin have similar utility for the identification of insulin resistance

<p>Abstract</p> <p>Background</p> <p>Insulin resistance (IR) and related metabolic disturbances are characterized by low levels of adiponectin. High molecular weight adiponectin (HMWA) is considered the active form of adiponectin and a better marker of IR than total adiponectin. The objective of this study is to compare the utility of total adiponectin, HMWA and the HMWA/total adiponectin index (S_Aindex) for the identification of IR and related metabolic conditions.</p> <p>Methods</p> <p>A cross-sectional analysis was performed in a group of ambulatory subjects, aged 20 to 70 years, in Mexico City. Areas under the receiver operator characteristic (ROC) curve for total, HMWA and the S_Aindex were plotted for the identification of metabolic disturbances. Sensitivity and specificity, positive and negative predictive values, and accuracy for the identification of IR were calculated.</p> <p>Results</p> <p>The study included 101 men and 168 women. The areas under the ROC curve for total and HMWA for the identification of IR (0.664 <it>vs</it>. 0.669, <it>P </it>= 0.74), obesity (0.592 <it>vs</it>. 0.610, <it>P </it>= 0.32), hypertriglyceridemia (0.661 <it>vs</it>. 0.671, <it>P </it>= 0.50) and hypoalphalipoproteinemia (0.624 <it>vs</it>. 0.633, <it>P </it>= 0.58) were similar. A total adiponectin level of 8.03 μg/ml was associated with a sensitivity of 57.6%, a specificity of 65.9%, a positive predictive value of 50.0%, a negative predictive value of 72.4%, and an accuracy of 62.7% for the diagnosis of IR. The corresponding figures for a HMWA value of 4.25 μg/dl were 59.6%, 67.1%, 51.8%, 73.7% and 64.2%.</p> <p>The area under the ROC curve of the S_Aindex for the identification of IR was 0.622 [95% CI 0.554-0.691], obesity 0.613 [95% CI 0.536-0.689], hypertriglyceridemia 0.616 [95% CI 0.549-0.683], and hypoalphalipoproteinemia 0.606 [95% CI 0.535-0.677].</p> <p>Conclusions</p> <p>Total adiponectin, HMWA and the S_Aindex had similar utility for the identification of IR and metabolic disturbances.</p

Synthesis and evaluation of AlgNa-g-poly(QCL-co-HEMA) hydrogels as platform for chondrocyte proliferation and controlled release of betamethasone

Hydrogels obtained from combining different polymers are an interesting strategy for developing controlled release system platforms and tissue engineering scaffolds. In this study, the applicability of sodium alginate-g-(QCL-co-HEMA) hydrogels for these biomedical applications was evaluated. Hydrogels were synthesized by free-radical polymerization using a different concentration of the components. The hydrogels were characterized by Fourier transform-infrared spectroscopy, scanning electron microscopy, and a swelling degree. Betamethasone release as well as the in vitro cytocompatibility with chondrocytes and fibroblast cells were also evaluated. Scanning electron microscopy confirmed the porous surface morphology of the hydrogels in all cases. The swelling percent was determined at a different pH and was observed to be pH-sensitive. The controlled release behavior of betamethasone from the matrices was investigated in PBS media (pH = 7.4) and the drug was released in a controlled manner for up to 8 h. Human chondrocytes and fibroblasts were cultured on the hydrogels. The MTS assay showed that almost all hydrogels are cytocompatibles and an increase of proliferation in both cell types after one week of incubation was observed by the Live/Dead(R) assay. These results demonstrate that these hydrogels are attractive materials for pharmaceutical and biomedical applications due to their characteristics, their release kinetics, and biocompatibility.Oncologic Imagin

Real-Time Visualization and Quantitation of Vascular Permeability In Vivo: Implications for Drug Delivery

The leaky, heterogeneous vasculature of human tumors prevents the even distribution of systemic drugs within cancer tissues. However, techniques for studying vascular delivery systems in vivo often require complex mammalian models and time-consuming, surgical protocols. The developing chicken embryo is a well-established model for human cancer that is easily accessible for tumor imaging. To assess this model for the in vivo analysis of tumor permeability, human tumors were grown on the chorioallantoic membrane (CAM), a thin vascular membrane which overlays the growing chick embryo. The real-time movement of small fluorescent dextrans through the tumor vasculature and surrounding tissues were used to measure vascular leak within tumor xenografts. Dextran extravasation within tumor sites was selectively enhanced an interleukin-2 (IL-2) peptide fragment or vascular endothelial growth factor (VEGF). VEGF treatment increased vascular leak in the tumor core relative to surrounding normal tissue and increased doxorubicin uptake in human tumor xenografts. This new system easily visualizes vascular permeability changes in vivo and suggests that vascular permeability may be manipulated to improve chemotherapeutic targeting to tumors

Factors associated with postprandial lipemia and apolipoprotein A-V levels in individuals with familial combined hyperlipidemia

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