Biology subjects

Nguyen, T. D.

Publications and source records attributed to Nguyen, T. D..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Characterization of dynamic patterns of human fetal to neonatal brain asymmetry with deformation-based morphometry

Despite established knowledge on the morphological and functional asymmetries in the human brain, the understanding of how brain asymmetry patterns change during late fetal to neonatal life remains incomplete. The goal of this study was to characterize the dynamic patterns of inter-hemispheric brain asymmetry over this critically important developmental stage using longitudinally acquired MRI scans. Super-resolution reconstructed T2-weighted MRI of 20 neurotypically developing participants were used, and for each participant fetal and neonatal MRI was acquired. To quantify brain morphological changes, deformation-based morphometry (DBM) on the longitudinal MRI scans was utilized. Two registration frameworks were evaluated and used in our study: (A) fetal to neonatal image registration and (B) registration through a mid-time template. Developmental changes of cerebral asymmetry were characterized as (A) the inter-hemispheric differences of the Jacobian determinant (JD) of fetal to neonatal morphometry change and the (B) time-dependent change of the JD capturing left-right differences at fetal or neonatal time points. Left-right and fetal-neonatal differences were statistically tested using multivariate linear models, corrected for participants age and sex and using threshold-free cluster enhancement. Fetal to neonatal morphometry changes demonstrated asymmetry in the temporal pole and left-right asymmetry differences between fetal and neonatal timepoints revealed temporal changes in the temporal pole, likely to go from right dominant in fetal to a bilateral morphology in neonatal timepoint. Furthermore, the analysis revealed right-dominant subcortical grey matter in neonates and three clusters of increased JD values in the left hemisphere from fetal to neonatal timepoints. While these findings provide evidence that morphological asymmetry gradually emerges during development, discrepancies between registration frameworks require careful considerations when using DBM for longitudinal data of early brain development.

neuroscience↗

bioRxiv2023

Distinguishing between- from within-site phase-amplitude coupling using antisymmetrized bispectra

Phase-amplitude coupling (PAC) is a form of cross-frequency coupling in which the amplitude of a fast oscillation is locked to the phase of a slow oscillation. PAC has been proposed as a mechanism for integrating slow large-scale networks with fast-oscillating local processes in the brain. On a signal level, PAC can be observed in single time series, reflecting local dynamics, or between two time series, potentially reflecting a functional interaction between distinct brain sites. To investigate the role of PAC as a mechanism of brain signalling, it is important to distinguish these two cases. However, when mixtures of underlying signals are observed, between-site PAC can spuriously emerge even if the true interaction is only local (within-site). This problem arises in electrophysiological recordings where mixing occurs due to volume conduction or the presence of a shared electrical reference. To address this problem, we propose to estimate PAC using the anti-symmetrized bispectrum (ASB-PAC). It has previously been shown that the cross-bispectrum can be used to measure PAC while efficiently sup-pressing Gaussian noise, and that the anti-symmetrized bispectra vanish for mixtures of independent sources. However, ASB-PAC has so far not been used to assess the presence of genuine between-site PAC. Using simulations, we here investigate the performance of different algorithms to detect PAC in a mixed signal setting as well as the performance of the same methods to distinguish genuine between-site PAC from within-site PAC. This is done in a minimal two-channel setup as well as in a more complex setting that assesses PAC on reconstructions of simulated EEG sources. We observe that bispectral PAC methods are considerably better at detecting simulated PAC in the volume conduction setting than three conventional PAC estimators. ASB-PAC achieves the highest performance in detecting genuine between-site PAC interactions while detecting the fewest spurious interactions. Using the ASB-PAC could therefore greatly facilitate the interpretation of future PAC studies when discriminating local from remote effects. We demonstrate the application of ASB-PAC on EEG data from a motor imagery experiment. Additionally, we present an upgraded version of the free ROIconnect plugin for the EEGLAB toolbox, which includes PAC and ASB-PAC metriscs based on bispectra.

neuroscience↗

bioRxiv2023

Role of Seasonal Importation and Random Genetic Drift on Selection for Drug-Resistant Genotypes of Plasmodium falciparum in High Transmission Settings

Historically Plasmodium falciparum has followed a pattern of drug resistance first appearing in low transmission settings before spreading to high transmission settings. Several features of low-transmission regions are hypothesized as explanations: higher chance of symptoms and treatment seeking, better treatment access, less within-host competition among clones, and lower rates of recombination. Here, we test whether importation of drug-resistant parasites is more likely to lead to successful emergence and establishment in low-transmission or high-transmission periods of the same epidemiological setting, using a spatial, individual-based stochastic model of malaria and drug-resistance evolution calibrated for Burkina Faso. Upon controlling for the timing of importation of drug-resistant genotypes and examination of key model variables, we found that drug-resistant genotypes imported during the low transmission season were, (1) more susceptible to stochastic extinction due to the action of random genetic drift, and (2) more likely to lead to establishment of drug resistance when parasites are able to survive early stochastic loss due to drift. This implies that rare importation events are more likely to lead to establishment if they occur during a high-transmission season, but that constant importation (e.g., neighboring countries with high levels of resistance) may produce a greater risk during low-transmission periods.

genetics↗

bioRxiv2023

Brain tissue cerebrospinal fluid fraction increases quadratically in normal aging

Background and PurposeOur objective was to apply multi-compartment T2 relaxometry in cognitively normal individuals aged 20-80 years to study the effect of aging on the parenchymal cerebrospinal fluid fraction (CSFF), a measure of the microscopic-scale CSF space. Materials and MethodsA total of 66 volunteers (age range, 22-80 years) were enrolled. Voxel-wise maps of short-T2 myelin water fraction (MWF), intermediate-T2 intra/extra-cellular water fraction (IEWF), and long-T2 CSFF were obtained using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) sequence and three-pool non-linear least squares fitting. Multiple linear regression analysis with correction for multiple comparisons was performed to study the association between age and regional MWF, IEWF, and CSFF measurements, adjusting for sex and region of interest (ROI) volume. The cerebral white matter (WM), cerebral cortex, and subcortical deep gray matter (GM) were considered as ROIs. In each model, a quadratic term for age was tested using an ANOVA test. A Spearmans correlation between the normalized lateral ventricle volume, a measure of organ-level CSF space, and the regional CSFF, a measure of tissue-level CSF space, was computed. ResultsIn the multiple regression analysis, we found a statistically significant quadratic relationship between age and regional CSFF for all three ROIs (all p-values < 0.001). A statistically significant quadratic relationship with age was also found for MWF in the deep GM (p = 0.004) and IEWF in the cortex (p = 0.012). There was a statistically significant linear relationship between age and regional IEWF in the cerebral WM (p = 0.006) and deep GM (p = 0.002). In the univariate correlation analysis, the normalized lateral ventricle volume was found to correlate moderately with the regional CSFF measurement in the cerebral WM ({rho} = 0.43, p < 0.001), cortex ({rho} = 0.43, p < 0.001), and deep GM ({rho} = 0.49, p < 0.001). ConclusionBrain tissue water residing in different water compartments shows complex changing patterns with age. Parenchymal CSFF, a biomarker of microscopic-scale CSF-like water, shows a quadratic increase in both GM and WM, starting approximately at the age of 50.

neuroscience↗

bioRxiv2022

Label-free and high-throughput removal of residual undifferentiated cells from iPSC-derived spinal-cord progenitor cells

The transplantation of spinal cord progenitor cells (SCPCs) derived from human induced pluripotent stem cells (iPSCs) has beneficial effects on treating spinal cord injury (SCI). However, the presence of residual undifferentiated iPSCs amongst their differentiated progeny poses a high risk as it can develop teratomas or other types of tumors post-transplantation. Despite the need to remove these residual undifferentiated iPSCs, no specific surface markers can identify them for subsequent removal. By profiling the size of SCPCs after a 10-day differentiation process, we found that the large-sized group contains significantly more cells expressing pluripotent markers. In this study, we employed a sized-based, label-free separation using an inertial microfluidic-based device to remove tumor-risk cells. The device can reduce the number of undifferentiated cells from an SCPC population with high throughput (i.e., > 3 million cells per minute) without affecting cell viability and functions. The sorted cells were verified with immunofluorescence staining, flow cytometry analysis, and colony culture assay. We demonstrated the capabilities of our technology to reduce the percentage of OCT4-positive cells. Our technology has great potential for the downstream processing of cell manufacturing workflow, ensuring better quality and safety of transplanted cells.

bioengineering↗

bioRxiv2022

Assessing emergence risk of double-resistant and triple-resistant genotypes of Plasmodium falciparum

Delaying and slowing antimalarial drug resistance evolution is a priority for the World Health Organization and for National Malaria Control Programs in malaria-endemic countries. Until novel therapies become available, the mainstay of antimalarial treatment will continue to be artemisinin combination therapy (ACT), with artemether-lumefantrine, artesunate-amodiaquine, and dihydroartemisinin-piperaquine the three primary therapies deployed worldwide. Deployment of ACTs can be optimized to minimize evolutionary pressure for drug resistance by deploying them as a set of co-equal multiple first-line therapies (MFT) rather than rotating therapies in and out of use. Here, we consider one potential detriment of MFT policies, namely, that the simultaneous deployment of multiple ACTs could drive the evolution of different resistance alleles concurrently and that these resistance alleles could then be brought together by recombination into double-resistant or triple-resistant parasites. Using an individual-based Plasmodium falciparum transmission model, we compare MFT and cycling policies over 20-year periods in malaria transmission settings ranging from 0.1% to 25% Plasmodium falciparum prevalence (PfPR2-10). We define a total risk measure for multi-drug resistance (MDR) by summing the area under the genotype-frequency curves (AUC) of double- and triple-resistant genotypes. When PfPR [≥] 1%, total MDR risk as measured by AUC is 4% to 90% lower under MFT policies than under cycling policies, irrespective of whether resistance is imported or emerges de novo. When PfPR = 0.1%, there is little statistical difference in MDR risk between MFT and cycling.

evolutionary biology↗

bioRxiv2022

Evaluating spatial and network properties of NMDA-dependent neuronal connectivity in mixed cortical cultures

A technique combining fluorescence imaging with Ca2+ indicators and single-cell laser scanning photostimulation of caged glutamate (LSPS) allows identification of functional connections between individual neurons in mixed cultures of rat neocortical cells as well as observation of synchronous spontaneous activity among neurons. LSPS performed on large numbers of neurons yielded maps of functional connections between neurons and allowed calculation of neuronal network parameters. LSPS also provided an indirect measure of excitability of neurons targeted for photostimulation. By repeating LSPS sessions with the same neurons, stability of connections and change in the number and strength of connections were also determined. Experiments were conducted in the presence of bicuculline to study the properties of excitatory neurotransmission. The AMPA receptor inhibitor, 6-Cyano-7-nitroquinoxaline-2,3-dione (CNQX), abolished synchronous neuronal activity but had no effect on connections mapped by LSPS. In contrast, the NMDA receptor inhibitor, 2-Amino-5-phosphono-pentanoic acid (APV), dramatically decreased the number of functional connections between neurons while also affecting synchronous spontaneous activity. Functional connections were also decreased by increasing extracellular Mg2+ concentration. These data demonstrated that LSPS mapping interrogates NMDA receptor-dependent connectivity between neurons in the network. A GluN2A-specific inhibitor, NVP-AAM077, decreased the number and strength of connections between neurons as well as neuron excitability. Conversely, the GluN2A-specific positive modulator, GNE-0723, increased these same properties. These data showed that LSPS can be used to directly study perturbations in the properties of NMDA receptor-dependent connectivity in neuronal networks. This approach should be applicable in a wide variety of in vitro and in vivo experimental preparations.

neuroscience↗

bioRxiv2022

QSMRim-Net: Imbalance-Aware Learning for Identification of Chronic Active Multiple Sclerosis Lesions on Quantitative Susceptibility Maps

Background and PurposeChronic active multiple sclerosis (MS) lesions are characterized by a paramagnetic rim at the edge of the lesion and are associated with increased disability in patients. Quantitative susceptibility mapping (QSM) is an MRI technique that is sensitive to chronic active lesions, termed rim+ lesions on the QSM. We present QSMRim-Net, a data imbalance-aware deep neural network that fuses lesion-level radiomic and convolutional image features for automated identification of rim+ lesions on QSM. MethodsQSM and T2-weighted-Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI of the brain were collected at 3T for 172 MS patients. Rim+ lesions were manually annotated by two human experts, followed by consensus from a third expert, for a total of 177 rim+ and 3986 rim negative (rim-) lesions. Our automated rim+ detection algorithm, QSMRim-Net, consists of a two-branch feature extraction network and a synthetic minority oversampling network to classify rim+ lesions. The first network branch is for image feature extraction from the QSM and T2-FLAIR, and the second network branch is a fully connected network for QSM lesion-level radiomic feature extraction. The oversampling network is designed to increase classification performance with imbalanced data. ResultsOn a lesion-level, in a five-fold cross validation framework, the proposed QSMRim-Net detected rim+ lesions with a partial area under the receiver operating characteristic curve (pROC AUC) of 0.760, where clinically relevant false positive rates of less than 0.1 were considered. The method attained an area under the precision recall curve (PR AUC) of 0.704. QSMRim-Net out-performed other state-of-the-art methods applied to the QSM on both pROC AUC and PR AUC. On a subject-level, comparing the predicted rim+ lesion count and the human expert annotated count, QSMRim-Net achieved the lowest mean square error of 0.98 and the highest correlation of 0.89 (95% CI: 0.86, 0.92). ConclusionThis study develops a novel automated deep neural network for rim+ MS lesion identification using T2-FLAIR and QSM images.

bioinformatics↗

bioRxiv2021

Massively Parallel Selection of NanoCluster Beacons

NanoCluster Beacons (NCBs) are multicolor silver nanocluster probes whose fluorescence can be activated or tuned by a proximal DNA strand called the activator. While a single-nucleotide difference in a pair of activators can lead to drastically different activation outcomes, termed the polar opposite twins (POTs), it is difficult to discover new POT-NCBs using the conventional low-throughput characterization approaches. Here we report a high-throughput selection method that takes advantage of repurposed next-generation-sequencing (NGS) chips to screen the activation fluorescence of [~]40,000 activator sequences. We find the nucleobases at positions 7-12 of the 18-nucleotide-long activator are critical to creating bright NCBs and positions 4-6 and 2-4 are hotspots to generate yellow and red POTs, respectively. Based on these findings, we propose a "zipper bag model" that explains how these hotspots lead to the creation of distinct silver cluster chromophores and contribute to the difference in chromophore chemical yields. Combining high-throughput screening with machine learning algorithms, we establish a pipeline to rationally design bright and multicolor NCBs.

bioengineering↗

bioRxiv2021

General Finite-Element Framework of the Virtual Fields Method in Nonlinear Elasticity

This paper presents a method to derive the virtual fields for identifying constitutive model parameters using the Virtual Fields Method (VFM). The VFM is an approach to identify unknown constitutive parameters using deformation fields measured across a given volume of interest. The general principle for solving identification problems with the VFM is first to derive parametric stress field, where the stress components at any point depend on the unknown constitutive parameters, across the volume of interest from the measured deformation fields. Applying the principle of virtual work to the parametric stress fields, one can write scalar equations of the unknown parameters and solve the obtained system of equations to deduce the values of unknown parameters. However, no rules have been proposed to select the virtual fields in identification problems related to nonlinear elasticity and there are multiple strategies possible that can yield different results. In this work, we propose a systematic, robust and automatic approach to reconstruct the systems of scalar equations with the VFM. This approach is well suited to finite-element implementation and can be applied to any problem provided that full-field deformation data are available across a volume of interest. We also successfully demonstrate the feasibility of the novel approach by multiple numerical examples. Potential applications of the proposed approach are numerous in biomedical engineering where imaging techniques are commonly used to observe soft tissues and where alterations of material properties are markers of diseased states. List of symbols O_TBL View this table: org.highwire.dtl.DTLVardef@1addce2org.highwire.dtl.DTLVardef@1808699org.highwire.dtl.DTLVardef@104dadeorg.highwire.dtl.DTLVardef@1bd527aorg.highwire.dtl.DTLVardef@71ef75_HPS_FORMAT_FIGEXP M_TBL C_TBL

bioengineering↗

bioRxiv2021

Pre-existing partner-drug resistance facilitates the emergence and spread of artemisinin resistance: a consensus modelling study

BackgroundArtemisinin-resistant genotypes have now emerged a minimum of five times on three continents despite recommendations that all artemisinins be deployed as artemisinin combination therapies (ACTs). Widespread resistance to the non-artemisinin partner drugs in ACTs has the potential to limit the clinical and resistance benefits provided by combination therapy. MethodsUsing a consensus modelling approach with three individual-based mathematical models of Plasmodium falciparum transmission, we evaluate the effects of pre-existing partner-drug resistance and ACT deployment on artemisinin resistance evolution. We evaluate settings where dihydroartemisinin-piperaquine (DHA-PPQ), artesunate-amodiaquine (ASAQ), or artemether-lumefantrine (AL) are deployed as first-line therapy. We use time until 0.25 artemisinin resistance allele frequency (the establishment time) as the primary outcome measure. FindingsHigher frequencies of pre-existing partner-drug resistant genotypes lead to earlier establishment of artemisinin resistance. Across all scenarios and pre-existing frequencies of partner-drug resistance explored, a 0.10 increase in partner-drug resistance frequency on average corresponded to 0.7 to 5.0 years loss of artemisinin efficacy. However, the majority of reductions in time to artemisinin establishment were observed after the first increment from 0.0 to 0.10 partner-drug resistance genotype frequency. InterpretationPartner-drug resistance in ACTs facilitates the early emergence of artemisinin resistance and is a major public health concern. Higher grade partner-drug resistance has the largest effect, with piperaquine-resistance accelerating early emergence of artemisinin-resistant alleles the most. Continued investment in molecular surveillance of partner-drug resistant genotypes to guide choice of first-line ACT is paramount. FundingBill and Melinda Gates Foundation; Wellcome Trust.

genetics↗

bioRxiv2021

Antimalarial mass drug administration in large populations and the evolution of drug resistance

Mass drug administration (MDA) with antimalarials has been shown to reduce prevalence and interrupt transmission in small populations, in populations with reliable access to antimalarial drugs, and in populations where sustained improvements in diagnosis and treatment are possible. Effective MDA eliminates drug-resistant parasites which has the long-term benefit of extending the useful therapeutic life of first-line therapies for all populations, not just the focal population where MDA was carried out. However, in order to plan elimination measures effectively, it is necessary to characterize the conditions under which failed MDA could exacerbate resistance. We use an individual-based stochastic model of Plasmodium falciparum transmission to evaluate this risk in large populations (>40K) where access to antimalarial treatments may not be uniformly high and where re-importation of drug-resistant parasites may be common. We find that drug-resistance evolution can be accelerated by MDA when all three of the following conditions are met: (1) strong genetic bottlenecking that falls short of elimination, (2) re-importation of resistant genotypes, and (3) continued selection pressure during routine case management post-MDA. Accelerated resistance levels are not immediate but follow the rebound of malaria cases post-MDA, if this is allowed to occur. Crucially, resistance is driven by the selection pressure during routine case management post-MDA and not the selection pressure exerted during the MDA itself. Second, we find that increasing treatment coverage post-MDA increases the probability of local elimination in low-transmission regions (PfPR < 2%) in scenarios with both low and high levels of drug-resistance importation. This emphasizes the importance of preparation and planning to ensure that MDA has a high probability of leading to elimination, and the necessity of supporting public health infrastructure to provide high coverage of diagnosis and treatment post-MDA.

evolutionary biology↗

bioRxiv2021

Increasing age is independently associated with higher free water in non-active MS brain - A multi-compartment analysis using FAST-T2

PurposeTo explore the relationship between the cerebral cortical perivascular space (PVS) and aging in non-active MS subjects by using the multi-echo T2 relaxometry based cerebrospinal fluid fraction (CSFF) map. MethodsMulti-echo spiral T2 data from 111 subjects with non-active multiple sclerosis (MS) were retrospectively investigated by fitting the T2 data into a three-compartment model, the three water compartments including myelin water, intra-extracellular water, and cerebrospinal fluid. Segmentation of T1w image was performed to get the region of interest (ROI) in cerebral cortical regions. The white matter lesion segmentation was conducted using a convolutional neural network (CNN) based segmentation tool. The CSFF in the ROIs were correlated with age by controlling the gender, white matter hyperintensity lesion burden, and MS disease duration. Multiple linear models were created for the analysis of aging effect on the CSFF. ResultsThe ROI analysis shows that the CSFF in the cerebral cortical regions (temporal, occipital, parietal, front, hippo, and mtl) are significantly linear increasing with age (p<0.01). The intra-extracellular water fraction (IEWF) in the ROIs are significantly linear decreasing (p<0.01). ConclusionThe multi-echo T2 based three-compartment model can be used to quantify the CSFF. The linear increase of CSF water contents in the cerebral cortical regions indicates increased perivascular space load in cortex with aging. The quantification of CSFF may provide a way to understand the glymphatic clearance function in aging and neurodegenerations. HighlightsO_LIMR T2 relaxometry is a valid method to quantify the cerebrospinal fluid fraction (CSFF) in cerebral cortical regions C_LIO_LIThe CSFF in the cerebral cortical regions are positively correlated with age by controlling the white matter lesion load in non-active MS subjects. C_LIO_LIQuantification of cerebral CSFF may reflect the perivascular space load in cortex and better interpret the disease progression in neurodegenerative disease, such as MS. C_LI

neuroscience↗

bioRxiv2020

Deep learning enables rapid and robust analysis of fluorescence lifetime imaging in photon-starved conditions

Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study the molecular states in the complex cellular environment as the lifetime readings are not biased by the fluorophore concentration or the excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termed flimGANE (fluorescence lifetime imaging based on Generative Adversarial Network Estimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is not only 258 times faster than the most popular time-domain least-square estimation (TD_LSE) method but also provide more accurate analysis in barcode identification, cellular structure visualization, Forster resonance energy transfer characterization, and metabolic state analysis. With its advantages in speed and reliability, flimGANE is particularly useful in fundamental biological research and clinical applications, where ultrafast analysis is critical.

cell biology↗

bioRxiv2019

Extensive Mammalian Germline Genome Engineering

Xenotransplantation, specifically the use of porcine organs for human transplantation, has long been sought after as an alternative for patients suffering from organ failure. However, clinical application of this approach has been impeded by two main hurdles: 1) risk of transmission of porcine endogenous retroviruses (PERVs) and 2) molecular incompatibilities between donor pigs and humans which culminate in rejection of the graft. We previously demonstrated that all 25 copies of the PERV elements in the pig genome could be inactivated and live pigs successfully generated. In this study, we improved the scale of porcine germline editing from targeting a single repetitive locus with CRISPR to engineering 13 different genes using multiple genome engineering methods. we engineered the pig genome at 42 alleles using CRISPR-Cas9 and transposon and produced PERVKO{middle dot}3KO{middle dot}9TG pigs which carry PERV inactivation, xeno-antigen KO and 9 effective human transgenes. The engineered pigs exhibit normal physiology, fertility, and germline transmission of the edited alleles. In vitro assays demonstrated that these pigs gain significant resistance to human humoral and cell mediated damage, and coagulation dysregulations, similar to that of allotransplantation. Successful creation of PERVKO{middle dot}3KO{middle dot}9TG pigs represents a significant step forward towards safe and effective porcine xenotransplantation, which also represents a synthetic biology accomplishment of engineering novel functions in a living organism. One Sentence SummaryExtensive genome engineering is applied to modify pigs for safe and immune compatible organs for human transplantation

synthetic biology↗

bioRxiv2019

The paternal and maternal genetic history of Vietnamese populations

Vietnam exhibits great cultural and linguistic diversity, yet the genetic history of Vietnamese populations remains poorly understood. Previous studies focused mostly on the majority Kinh group, and thus the genetic diversity of the many other groups has not yet been investigated. Here we analyze complete mtDNA genome sequences and 2.34 mB sequences of the male-specific portion of the Y chromosome from the Kinh and 16 minority populations, encompassing all five language families present in Vietnam. We find highly variable levels of diversity within and between groups that do not correlate with either geography or language family. In particular, the Mang and Sila have undergone recent, independent bottlenecks, while the majority group, Kinh, exhibits low levels of differentiation with other groups. The two Austronesian-speaking groups, Giarai and Ede, show a potential impact of matrilocality on their patterns of variation. Overall, we find that isolation, coupled with some limited contact involving some groups, has been the major factor influencing the genetic structure of Vietnamese populations, and that there is substantial genetic diversity that is not represented by the Kinh.

genetics↗

bioRxiv2019

Association between development of early cortical activity on amplitude-integrated EEG and 5-years neurodevelopmental outcome in the preterm infant

AimTo analyse the association between early aEEG and cognitive outcome at early school-age in very preterm infants. MethodsProspective cohort study including infants with gestational age (GA) <32.0 weeks, undergoing continuous aEEG recording during first 4 days of life. Semiquantitative and quantitative (maximum/minimum amplitude) measures were averaged over the recording period. Cognitive outcome was assessed with the Kaufman-Assessment Battery for Children at 5 years of age. Uni- and multivariate logistic regressions were calculated between aEEG parameters and normal cognitive outcome (IQ[≥]85). ResultsAmong 118 monitored preterm children, 89 were assessed at median(IQR) corrected age of 68.6 months (65.5-71.2) [48% female, median(IQR) GA 29.9(28.2,30.9) weeks, mean(SD) birth weight 1235(363) grams]. Mean(SD) IQ was 97.8(12.7). IQ<85 occurred in 21.3 %, cerebral palsy was found in 3.4%. Despite univariate associations of total maturity scores, cycling subscores, background pattern and minimum aEEG amplitude with normal cognitive outcome none of the associations remained significant after adjustment for confounders. Socioeconomic status was identified as independent predictor of neurodevelopmental outcome. ConclusionIn this cohort of very preterm infants, early short-term aEEG was not predictive of later cognitive outcome. Further research is needed to explore how aEEG could help to inform long-term prognosis in this population group. Key notesO_LIPreterm born infants are at high risk for neurodevelopmental impairment. C_LIO_LIEarly amplitude integrated electroencephalography characteristics are univariately associated with cognitive outcome at 5 years of age in preterm born children. C_LIO_LIHowever, socioeconomic factors and neonatal morbidity were stronger predictors of long-term neurodevelopmental outcome than early aEEG measures. C_LI

neuroscience↗

bioRxiv2018

An aged human heart tissue model showing age-related molecular and functional deterioration resembling the native heart

Deaths attributed to ischemic heart disease increased by 41.7% from 1990 to 2013. This is primarily due to an increase in the aged population, however, research on cardiovascular disease (CVD) has been overlooking aging, a well-documented contributor to CVD. The field heavily depends on the use of young animals due to lower costs and ready availability, despite the prominent differences between young and aged heart structure and function. Here we present the first human induced pluripotent stem cell (hiPSC)-derived cardiomyocyte (iCM)-based, in vitro aged myocardial tissue model as an alternative research platform. Within 4 months, iCMs go through accelerated senescence and show cellular characteristics of aging. Furthermore, the model tissues fabricated using these aged iCMs, with stiffness resembling that of aged human heart, show functional and pharmacological deterioration specific to aged myocardium. Our novel tissue model with age-appropriate physiology and pathology presents a promising new platform for investigating CVD or other age-related diseases.

bioengineering↗