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Changes in neurovascular coupling are associated with both Alzheimer's disease and vascular dementia in later life, but this may be confounded by cerebrovascular risk. We hypothesized that hemodynamic latency would be associated with reduced cognitive functioning across the lifespan, holding constant demographic and cerebrovascular risk. In 387 adults aged 18-85 (mean = 48.82), dynamic causal modeling was used to estimate the hemodynamic response function in the left and right V1 and V3-ventral regions of the visual cortex in response to a simple checkerboard block design stimulus with minimal cognitive demands. The hemodynamic latency (transit time) in the visual cortex was used to predict general cognitive ability (Full-Scale IQ), controlling for demographic variables (age, race, education, socioeconomic status) and cerebrovascular risk factors (hypertension, alcohol use, smoking, high cholesterol, BMI, type 2 diabetes, cardiac disorders). Increased hemodynamic latency in the visual cortex predicted reduced cognitive function (p

BackgroundTo characterize acoustic features of an infant's cry and use machine learning to provide an objective measurement of behavioral state in a cry-translator. To apply the cry-translation algorithm to colic hypothesizing that these cries sound painful.MethodsAssessment of 1000 cries in a mobile app (ChatterBabyTM). Training a cry-translation algorithm by evaluating >6000 acoustic features to predict whether infant cry was due to a pain (vaccinations, ear-piercings), fussy, or hunger states. Using the algorithm to predict the behavioral state of infants with reported colic.ResultsThe cry-translation algorithm was 90.7% accurate for identifying pain cries, and achieved 71.5% accuracy in discriminating cries from fussiness, hunger, or pain. The ChatterBaby cry-translation algorithm overwhelmingly predicted that colic cries were most likely from pain, compared to fussy and hungry states. Colic cries had average pain ratings of 73%, significantly greater than the pain measurements found in fussiness and hunger (p

BackgroundCentralized and federated models for sharing data in research networks currently exist. To build multivariate data analysis for centralized networks, transfer of patient-level data to a central computation resource is necessary. The authors implemented distributed multivariate models for federated networks in which patient-level data is kept at each site and data exchange policies are managed in a study-centric manner.ObjectiveThe objective was to implement infrastructure that supports the functionality of some existing research networks (e.g., cohort discovery, workflow management, and estimation of multivariate analytic models on centralized data) while adding additional important new features, such as algorithms for distributed iterative multivariate models, a graphical interface for multivariate model specification, synchronous and asynchronous response to network queries, investigator-initiated studies, and study-based control of staff, protocols, and data sharing policies.Materials and methodsBased on the requirements gathered from statisticians, administrators, and investigators from multiple institutions, the authors developed infrastructure and tools to support multisite comparative effectiveness studies using web services for multivariate statistical estimation in the SCANNER federated network.ResultsThe authors implemented massively parallel (map-reduce) computation methods and a new policy management system to enable each study initiated by network participants to define the ways in which data may be processed, managed, queried, and shared. The authors illustrated the use of these systems among institutions with highly different policies and operating under different state laws.Discussion and conclusionFederated research networks need not limit distributed query functionality to count queries, cohort discovery, or independently estimated analytic models. Multivariate analyses can be efficiently and securely conducted without patient-level data transport, allowing institutions with strict local data storage requirements to participate in sophisticated analyses based on federated research networks.

This article describes the patient-centered Scalable National Network for Effectiveness Research (pSCANNER), which is part of the recently formed PCORnet, a national network composed of learning healthcare systems and patient-powered research networks funded by the Patient Centered Outcomes Research Institute (PCORI). It is designed to be a stakeholder-governed federated network that uses a distributed architecture to integrate data from three existing networks covering over 21 million patients in all 50 states: (1) VA Informatics and Computing Infrastructure (VINCI), with data from Veteran Health Administration's 151 inpatient and 909 ambulatory care and community-based outpatient clinics; (2) the University of California Research exchange (UC-ReX) network, with data from UC Davis, Irvine, Los Angeles, San Francisco, and San Diego; and (3) SCANNER, a consortium of UCSD, Tennessee VA, and three federally qualified health systems in the Los Angeles area supplemented with claims and health information exchange data, led by the University of Southern California. Initial use cases will focus on three conditions: (1) congestive heart failure; (2) Kawasaki disease; (3) obesity. Stakeholders, such as patients, clinicians, and health service researchers, will be engaged to prioritize research questions to be answered through the network. We will use a privacy-preserving distributed computation model with synchronous and asynchronous modes. The distributed system will be based on a common data model that allows the construction and evaluation of distributed multivariate models for a variety of statistical analyses.

Gun violence (GV) and safety is a contentious topic in the United States, despite increasing morbidity and mortality among children and adolescents. It is important for physicians to take a role in preventing future GV. This article aims to present several methods that physicians can use to prevent GV in their own communities, ranging from implementation of large-scale intervention programs to simple screenings and anticipatory guidance. As the problem of GV persists, it is important for physicians to use their role to identify individuals who are at high-risk and advocate for changes that will benefit their future health. [ABSTRACT FROM AUTHOR]

The most common extra-alveolar sites for miniscrew placement are the infrazygomatic crest region (IZC) and mandibular buccal shelf region (MBS). The aim of the study is to determine the amount of distalization achieved with IZC and MBS mini screws, and if it has any correlation with the growth pattern. Pre-treatment scan (T1) and post-distalization (T3) scans of 30 patients were taken in whom en masse distalization with either IZC or MBS mini screws or both was achieved. T1 and T2 scans were then superimposed on OrthoAnalyzer software using landmark reference points on maxilla and mandible and assessed for the amount of distalization. The following statistical tests were conducted: Kappa statistics to assess the intra-observer reliability, Descriptive statistics for the amount of distalization by both IZC and buccal shelf mini screws, and its correlation with varying growth patterns and gender. The mean distalization achieved with IZC anchorage was 3.491 ± 0.471 mm and the mean distalization achieved with buccal shelf mini screw anchorage was 4.412 ± 0.904 mm. A weak negative correlation between growth pattern and amount of distalization was observed (r=-0.379; p=0.007). The present study suggests that both infrazygomatic and buccal shelf anchorage for arch distalization in borderline surgical class II and III cases are effective modalities. It also suggests that the skeletal facial pattern may favorably influence the amount of distalization in hypodivergent facial type, especially with MBS anchorage. [ABSTRACT FROM AUTHOR]

This research aimed to develop the phenytoin-loaded bionanosuspension by utilising the novel biopolymer from Juglans regia andreduce the long-term treatment cost of epilepsy and increase the efficiency of therapy. A novel biopolymer with remarkable inbuilt properties was isolated and used in the development of a nano capsulated dispersed system. The diverse proportions of phenytoin and biopolymer with different ratios 1:2, 1:3, 1:4, 1:5 and 1:8 were taken for the planning of details PJNC1-PJNC5. The bionanosuspension was assessed for dispersibility, pH, % entrapment efficiency, stability study and in vitro drug discharge. The formulation PJNC2 with 1:3 drug biopolymer proportion showed significant outcomes for various assessments with t50% of 16.51 h and r² estimation of 0.9884. PJNC2 showed 92.07%±2.5 drug delivery in 36h and was stable. The bionanosuspension was found to be stable and safe for the delivery of nanosized phenytoin utilising the biopolymer having a remarkable stabiliser cum retardant property. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is an age‐related neurodegenerative disorder affecting nearly 50 million individuals worldwide. Besides aging, various comorbidities can increase the risk of AD, such as asthma. However, the molecular mechanism(s) underlying this asthma‐associated AD exacerbation is unknown. This study was designed to explore the effects of house dust mite‐induced asthma on AD‐related brain changes using the AppNL‐G‐F transgenic mouse model. Method: Male and female C57BL/6 wild type and AppNL‐G‐F mice (8‐9 months old) were exposed to either saline or house dust mite (dose: 833µg/kg in saline) every alternate day for 16 weeks. Mice were sacrificed at the end of the experiment and broncho‐alveolar lavage fluid (BALF), lungs, blood, and brains were collected. BALF was analyzed for immune cell markers, inflammatory mediators, and LDH activity. Lung sections were stained with Alcian blue and Masson's Trichrome to examine mucus and collagen production, respectively. The serum was analyzed for cytokine levels. Brain sections were immunostained for Aβ, GFAP, and collagen‐4. Finally, frozen hippocampi and cortices were used to perform Aβ ELISAs and cytokine arrays, respectively. Result: Dust‐mite exposure increased inflammatory cells, cytokine levels, and LDH activity in the BALF and increased the mucus and collagen production in the lungs from both sexes and genotypes, suggesting induction of a severe asthma‐like condition. This correlated with increased levels of serum cytokines in all dust‐mite‐exposed groups. In agreement with this peripheral change, hippocampi from asthma‐induced male and female AppNL‐G‐F mice demonstrated elevated Aβ plaque load and increased soluble Aβ 1‐40/42 and insoluble Aβ 1‐40 levels. Dust‐mite exposure also increased astrogliosis in both sexes of AppNL‐G‐F mice, as indicated by GFAP immunoreactivity. Additionally, dust‐mite exposure‐induced asthma elevated cortical levels of several cytokines in both sexes and genotypes. Finally, dust‐mite exposed groups also showed a disturbed BBB integrity in the hippocampus of AppNL‐G‐F mice, as indicated by decreased collagen‐4 immunoreactivity. Conclusion: Dust‐mite exposure induced a severe asthma‐like condition that exacerbated Aβ pathology, astrogliosis, cytokine changes, and disturbed BBB integrity in the brains of male and female AppNL‐G‐F mice. Defining the mechanisms of secondary effects of asthma on the brain may provide a novel therapeutic approach for both asthma and AD. [ABSTRACT FROM AUTHOR]

This study was undertaken to evaluate if there are differences between visual estimation of blood loss (EBL) and quantitative blood loss (QBL) for maternal outcomes related to obstetrical hemorrhage. This retrospective study compared EBL (n = 500) to QBL (n = 501) for outcomes of length of stay, readmission within 30 days of discharge, percent receiving blood transfusions, time between delivery to receiving blood transfusion, and postpartum hemoglobin level. The QBL group had a significantly lower mean length of stay than the EBL group (2.6 vs 3.2 days, P < 0.001). Multivariate linear regression analysis adjusting for relevant covariates had a similar finding of lower length of stay for QBL vs EBL (B = −0.13, SE = 0.01, P < 0.001). Readmission within 30 days, blood transfusion, time to transfusion since delivery, and postpartum hemoglobin did not significantly differ between the QBL and EBL groups. We recommend that clinicians adopt QBL over EBL as standard practice since QBL is associated with lower length of stay and does not negatively impact other clinical outcomes. [ABSTRACT FROM AUTHOR]