Transthyretin amyloid cardiomyopathy, an often unrecognized cause of heart failure, is now treatable with a transthyretin stabilizer. It is therefore important to identify at-risk patients who can undergo targeted testing for earlier diagnosis and treatment, prior to the development of irreversible heart failure. Here we show that a random forest machine learning model can identify potential wild-type transthyretin amyloid cardiomyopathy using medical claims data. We derive a machine learning model in 1071 cases and 1071 non-amyloid heart failure controls and validate the model in three nationally representative cohorts (9412 cases, 9412 matched controls), and a large, single-center electronic health record-based cohort (261 cases, 39393 controls). We show that the machine learning model performs well in identifying patients with cardiac amyloidosis in the derivation cohort and all four validation cohorts, thereby providing a systematic framework to increase the suspicion of transthyretin cardiac amyloidosis in patients with heart failure.

The protein kinase C (PKC) enzymes have long been established as critical for synaptic plasticity. However, it is unknown whether Ca-dependent PKC isozymes are activated in dendritic spines during plasticity and, if so, how this synaptic activity is encoded by PKC. Here, using newly developed, isozyme-specific sensors, we demonstrate that classical isozymes are activated to varying degrees and with distinct kinetics. PKCα is activated robustly and rapidly in stimulated spines and is the only isozyme required for structural plasticity. This specificity depends on a PDZ-binding motif present only in PKCα. The activation of PKCα during plasticity requires both NMDA receptor Ca flux and autocrine brain-derived neurotrophic factor (BDNF)-TrkB signaling, two pathways that differ vastly in their spatiotemporal scales of signaling. Our results suggest that, by integrating these signals, PKCα combines a measure of recent, nearby synaptic plasticity with local synaptic input, enabling complex cellular computations such as heterosynaptic facilitation of plasticity necessary for efficient hippocampus-dependent learning.

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This paper presents the results of an experimental study comparing cortical activation in the brain when generating solutions using brainstorming, morphological analysis, and TRIZ. Twelve engineering students were given the same three design tasks, respectively, using the three solution generation techniques. Students generated solutions while change in oxygenated blood along the prefrontal cortex (PFC) was measured using functional near-infrared spectroscopy. The results show that generating solutions using brainstorming, morphological analysis, and TRIZ leads to differences in cortical activation, specifically along the region of the brain associated with spatial working memory, cognitive flexibility, and abstract reasoning, called the left dorsolateral prefrontal cortex (left DLPFC). Brainstorming evokes a high average blood oxygenation level dependent (BOLD) response in the left DLPFC early during the solution generation process but this high response is not sustained. In comparison, morphological analysis and TRIZ evoke multiple high average BOLD responses across the solution generation process. Not only was the high average BOLD response sustained but the density of network coordination among brain regions across the PFC was greater for morphological analysis and TRIZ. Higher density is a proxy for higher cognitive effort. The brain regions most central to coordination also varied. During brainstorming the right hemisphere, in a region associated with memory encoding (right PFC), was most activated. During morphological analysis, the left hemisphere, the left DLPFC was most activated. During TRIZ, both the middle and left hemisphere included regions of high activation. These results indicate neuro-cognitive differences of activation patterns, cognitive effort over time, and brain regions central for coordination when using these three concept generation techniques. Future research can begin to explore neuro-cognitive differences as a result of these techniques over multiple uses and the effects of design education.

This paper presents the results of studying the brain activations of 30 engineering students when using three different design concept generation techniques: brainstorming, morphological analysis, and TRIZ. Changes in students’ brain activation in the prefrontal cortex were measured using functional near-infrared spectroscopy. The results are based on the area under the curve analysis of oxygenated hemodynamic response as well as an assessment of functional connectivity using Pearson’s correlation to compare students’ cognitive brain activations using these three different ideation techniques. The results indicate that brainstorming and morphological analysis demand more cognitive activation across the prefrontal cortex (PFC) compared to TRIZ. The highest cognitive activation when brainstorming and using morphological analysis is in the right dorsolateral PFC (DLPFC) and ventrolateral PFC. These regions are associated with divergent thinking and ill-defined problem-solving. TRIZ produces more cognitive activation in the left DLPFC. This region is associated with convergent thinking and making judgments. Morphological analysis and TRIZ also enable greater coordination (i.e., synchronized activation) between brain regions. These findings offer new evidence that structured techniques like TRIZ reduce cognitive activation, change patterns of activation and increase coordination between regions in the brain.

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BACKGROUND. Left atrial (LA) and left ventricular (LV) remodeling are associated with atrial fibrillation (AF). The prospective associations of impairment in cardiac mechanical function, as assessed by speckle-tracking echocardiography, with incident AF are less clear. METHODS. In the Cardiovascular Health Study, a community-based cohort of older adults, participants free of AF with echocardiograms of adequate quality for speckle tracking were included. We evaluated the associations of indices of cardiac mechanics (LA reservoir strain, LV longitudinal strain, and LV early diastolic strain rate) with incident AF. RESULTS. Of 4341 participants with strain imaging, participants with lower LA reservoir strain were older, had more cardiometabolic risk factors, and had lower renal function at baseline. Over a median follow-up of 10 years, 497 (11.4%) participants developed AF. Compared with the highest quartile of LA reservoir strain, the lowest quartile of LA reservoir strain was associated with higher risk of AF after covariate adjustment, including LA volume and LV longitudinal strain (Hazard Ratio [HR], 1.80; 95% CI, 1.31-2.45; P < 0.001). The association of LA reservoir strain and AF was stronger in subgroups with higher blood pressure, NT-proBNP, and LA volumes. There were no associations of LV longitudinal strain and LV early diastolic strain rate with incident AF after adjustment for LA reservoir strain. CONCLUSION. Lower LA reservoir strain was associated with incident AF, independent of LV mechanics, and with stronger associations in high-risk subgroups. These findings suggest that LA mechanical dysfunction precedes the development of AF. Therapies targeting LA mechanical dysfunction may prevent progression to AF.