After a decade of clinical use of coronary computed tomographic angiography (CCTA) to evaluate the anatomic severity of coronary artery disease, new methods of deriving functional information from CCTA have been developed. These methods utilize the anatomic information provided by CCTA in conjunction with computational fluid dynamics to calculate fractional flow reserve (FFR) values from CCTA image data sets. Computed tomography-derived FFR (CT-FFR) enables the identification of lesion-specific drop noninvasively. A three-dimensional CT-FFR modeling technique, which provides FFR values throughout the coronary tree (HeartFlow FFRCT analysis), has been validated against measured FFR and is now approved by the US Food and Drug Administration for clinical use. This technique requires off-site supercomputer analysis. More recently, a one-dimensional computational analysis technique (Siemens cFFR), which can be performed on on-site workstations, has been developed and is currently under investigation. This article reviews CT-FFR technology and clinical evidence for its use in stable patients with suspected coronary artery disease.

Although many studies have attempted to examine the consequences of Mexico-U.S. migration for Mexican immigrants' health, few have had adequate data to generate the appropriate comparisons. In this article, we use data from two waves of the Mexican Family Life Survey (MxFLS) to compare the health of current migrants from Mexico with those of earlier migrants and nonmigrants. Because the longitudinal data permit us to examine short-term changes in health status subsequent to the baseline survey for current migrants and for Mexican residents, as well as to control for the potential health selectivity of migrants, the results provide a clearer picture of the consequences of immigration for Mexican migrant health than have previous studies. Our findings demonstrate that current migrants are more likely to experience recent changes in health status-both improvements and declines-than either earlier migrants or nonmigrants. The net effect, however, is a decline in health for current migrants: compared with never migrants, the health of current migrants is much more likely to have declined in the year or two since migration and not significantly more likely to have improved. Thus, it appears that the migration process itself and/or the experiences of the immediate post-migration period detrimentally affect Mexican immigrants' health.

While many studies have established the importance of streamflow as a driver of fish population dynamics, few have examined relationships between survival of juvenile salmonids and flow-related variables in intermittent streams. With predictions for higher frequency of drought conditions due to climate change, and the associated increasing human demand for water during the dry season, understanding fish­­­–flow relationships is becoming increasingly important for the protection of sensitive aquatic species. To examine the effects of low streamflow on juvenile salmonids rearing in small intermittent streams, we estimated survival and collected environmental data in four coastal California watersheds from 2011 to 2013. We used an individual-based mark-recapture modeling approach to evaluate the influence of flow-related variables on oversummer survival of PIT-tagged juvenile Coho Salmon stocked into eight stream reaches. Survival was positively associated with streamflow magnitude, wetted volume, and dissolved oxygen, and negatively associated with days of disconnected surface flow (days of disconnection), and temperature. Days of disconnection best explained survival, though the relationship varied by geomorphic reach type. Survival was lower in alluvial reaches as compared to bedrock and clay reaches, and showed a faster rate of decline with increasing days of disconnection and drought condition. In all reaches, the onset of pool disconnection represented a turning point at which water quality, water quantity, and survival declined. For this reason, we suggest that days of disconnection (or the flow magnitude at which pools become disconnected) is a useful metric for identifying flow-impaired reaches, informing streamflow protection strategies, and prioritizing streamflow enhancement efforts designed to benefit sensitive salmonid populations in intermittent streams.

The manipulation and control of nanoscale magnetic spin textures are of rising interest as they are potential foundational units in next-generation computing paradigms. Achieving this requires a quantitative understanding of the spin texture behavior under external stimuli using in situ experiments. Lorentz transmission electron microscopy (LTEM) enables real-space imaging of spin textures at the nanoscale, but quantitative characterization of in situ data is extremely challenging. Here, we present an AI-enabled phase-retrieval method based on integrating a generative deep image prior with an image formation forward model for LTEM. Our approach uses a single out-of-focus image for phase retrieval and achieves significantly higher accuracy and robustness to noise compared to existing methods. Furthermore, our method is capable of isolating sample heterogeneities from magnetic contrast, as shown by application to simulated and experimental data. This approach allows quantitative phase reconstruction of in situ data and can also enable near real-time quantitative magnetic imaging.

Ptychography has rapidly grown in the fields of X-ray and electron imaging for its unprecedented ability to achieve nano or atomic scale resolution while simultaneously retrieving chemical or magnetic information from a sample. A ptychographic reconstruction is achieved by means of solving a complex inverse problem that imposes constraints both on the acquisition and on the analysis of the data, which typically precludes real-time imaging due to computational cost involved in solving this inverse problem. In this work we propose PtychoNN, a novel approach to solve the ptychography reconstruction problem based on deep convolutional neural networks. We demonstrate how the proposed method can be used to predict real-space structure and phase at each scan point solely from the corresponding far-field diffraction data. The presented results demonstrate how PtychoNN can effectively be used on experimental data, being able to generate high quality reconstructions of a sample up to hundreds of times faster than state-of-the-art ptychography reconstruction solutions once trained. By surpassing the typical constraints of iterative model-based methods, we can significantly relax the data acquisition sampling conditions and produce equally satisfactory reconstructions. Besides drastically accelerating acquisition and analysis, this capability can enable new imaging scenarios that were not possible before, in cases of dose sensitive, dynamic and extremely voluminous samples.

With an increasing focus on biomarkers in dementia research, illustrating the role of neuropsychological assessment in detecting mild cognitive impairment (MCI) and Alzheimer's dementia (AD) is important. This systematic review and meta-analysis, conducted in accordance with PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) standards, summarizes the sensitivity and specificity of memory measures in individuals with MCI and AD. Both meta-analytic and qualitative examination of AD versus healthy control (HC) studies (n = 47) revealed generally high sensitivity and specificity (≥ 80% for AD comparisons) for measures of immediate (sensitivity = 87%, specificity = 88%) and delayed memory (sensitivity = 89%, specificity = 89%), especially those involving word-list recall. Examination of MCI versus HC studies (n = 38) revealed generally lower diagnostic accuracy for both immediate (sensitivity = 72%, specificity = 81%) and delayed memory (sensitivity = 75%, specificity = 81%). Measures that differentiated AD from other conditions (n = 10 studies) yielded mixed results, with generally high sensitivity in the context of low or variable specificity. Results confirm that memory measures have high diagnostic accuracy for identification of AD, are promising but require further refinement for identification of MCI, and provide support for ongoing investigation of neuropsychological assessment as a cognitive biomarker of preclinical AD. Emphasizing diagnostic test accuracy statistics over null hypothesis testing in future studies will promote the ongoing use of neuropsychological tests as Alzheimer's disease research and clinical criteria increasingly rely upon cerebrospinal fluid (CSF) and neuroimaging biomarkers.

Non-neurogenic cell types, such as cortical astroglia and fibroblasts, can be directly converted into neurons by the overexpression of defined transcription factors. Normally, the cellular phenotype of such differentiated cells is remarkably stable and resists direct cell transdifferentiation. Here we show that the Ink4a/Arf (also known as Cdkn2a) locus is a developmental barrier to direct neuronal transdifferentiation induced by transcription factor overexpression. With serial passage in vitro, wild-type postnatal cortical astroglia become progressively resistant to Dlx2-induced neuronal transdifferentiation. In contrast, the neurogenic competence of Ink4a/Arf-deficient astroglia is both greatly increased and does not diminish through serial cell culture passage. Electrophysiological analysis further demonstrates the neuronal identity of cells induced from Ink4a/Arf-null astroglia, and short hairpin RNA-mediated acute knockdown of p16Ink4a and p19Arf p16(Ink4a) and p19(Arf) indicates that these gene products function postnatally as a barrier to cellular transdifferentiation. Finally, we found that mouse fibroblasts deficient for Ink4a/Arf also exhibit greatly enhanced transcription factor-induced neuronal induction. These data indicate that Ink4a/Arf is a potent barrier to direct neuronal transdifferentiation and further suggest that this locus functions normally in the progressive developmental restriction of postnatal astrocytes.

Social relationships define an individual's position in its social network, which can influence the acquisition and spread of information and behavioural variants through the population. Thus, when nuisance behaviours spread through wildlife populations, identifying central individuals may provide valuable insights for problem-species management. We studied the effects of network position on California sea lion (Zalophus californianus) discovery and foraging success at a novel foraging ground-the salmonids that aggregate at the Bonneville Dam tail-race, 235 km up the Columbia River. We found that an individual's centrality in their social network influenced discovery of the Bonneville Dam and whether they returned the next year. Foraging success once at the dam was independent of network position. Extensive lethal and non-lethal removal efforts have been implemented at Bonneville Dam and focused on reducing the number of individual sea lions at the dam. Since social relationships forged at the opening of the Columbia River influence both the discovery and return to the Bonneville Dam, efforts to increase salmon recovery may be enhanced by breaking apart social networks at the opening of the river.

Objective

To determine whether lower socioeconomic status (SES) and longer home to hospital driving time are associated with reductions in tissue plasminogen activator (tPA) administration and timeliness of the treatment.

Methods

We conducted a retrospective observational study using data from the Get With The Guidelines-Stroke Registry (GWTG-Stroke) between January 2015 and March 2017. The study included 118,683 ischemic stroke patients age ≥18 who were transported by emergency medical services to one of 1,489 US hospitals. We defined each patient's SES based on zip code median household income. We calculated the driving time between each patient's home zip code and the hospital where he or she was treated using the Google Maps Directions Application Programing Interface. The primary outcomes were tPA administration and onset-to-arrival time (OTA). Outcomes were analyzed using hierarchical multivariable logistic regression models.

Results

SES was not associated with OTA (p = 0.31) or tPA administration (p = 0.47), but was associated with the secondary outcomes of onset-to-treatment time (OTT) (p = 0.0160) and in-hospital mortality (p = 0.0037), with higher SES associated with shorter OTT and lower in-hospital mortality. Driving time was associated with tPA administration (p < 0.001) and OTA (p < 0.0001), with lower odds of tPA (0.83, 0.79-0.88) and longer OTA (1.30, 1.24-1.35) in patients with the longest vs shortest driving time quartiles. Lower SES quintiles were associated with slightly longer driving time quartiles (p = 0.0029), but there was no interaction between the SES and driving time for either OTA (p = 0.1145) or tPA (p = 0.6103).

Conclusions

Longer driving times were associated with lower odds of tPA administration and longer OTA; however, SES did not modify these associations.