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Liao, J.

Publications and source records attributed to Liao, J..

108 records · Page 6Linked to original sources
bioRxiv2020

An Experimental Validation of the Computer Fluid Dynamics of Normal Human Nasal Airflow Using a Precise 3-D Printing Model

Computer Fluid Dynamics (CFD) is a popular method for studying airflow of nasal cavities. However, the data of CFD studies has rarely been validated through experiments. To test the accuracy of CFD computation, we studied the consistency of the air pressure of nasal cavities in the CFD and the experiment. A proportional resin model of a normal human subjects nasal cavities was created by a 3-d printer with a precision value of 0.1mm. The pressure of 63 check points in the nasal cavities in different breathing states was measured. The experimental data was compared with the data obtained by CFD simulation. At the flow rates of 180 ml s-1 and 560 ml s-1, the pressure in all check points remained highly consistent with the CFD data. At 1100 ml s-1 flow rate, there was a significant deviation in the posterior segment of the nasal cavity during exhalation. The method used in this study to measure the pressure in the nasal cavities can be used in experimental validation of CFD data. The computational methods and the boundary conditions used in this study resulted in a high agreement between the results of the CFD simulation and the experiment. Author SummaryIn the contemporary era, Computer fluid dynamics (CFD) is the mainstream method for studying air flow. Due to the complex anatomical structure of the nasal cavity, the CFD results of the nasal flow have rarely been experimentally verified. This study provides a method to verify the methods and results of nasal CFD. We printed an accurate model of a normal persons nasal cavity with a high-precision 3D printer. In this nasal cavity model, we set 63 small holes to detect the air pressure of the places we concerned. Three different nasal flow quantity are used to represent different breathing conditions: high (1100 ml s-1), medium (560 ml s-1), and low (180 ml s-1). In medium and low nasal flow quantities, our CFD results are in good agreement with the experimental pressure values. On this basis, we analyzed the characteristics of nasal airflow in normal people. The method used in this study to measure the pressure in the nasal cavities can be used in experimental measurements of the partial resistance of the nasal cavity. With proper modification, it can be applied to the clinical practice for nasal resistance, giving more help for the design of the operation plan.

biophysics↗
bioRxiv2020

ACTB and GAPDH proteins appear at multiple positions of SDS-PAGE and may not be suitable for serving as reference genes for the protein level determination in such techniques as Western blotting

Most human genes can produce multiple protein isoforms that should appear at multiple positions of polyacrylamide gel electrophoresis (PAGE) with sodium dodecyl sulfate (SDS), but most published results of Western blotting show only one protein. We performed SDS-PAGE of proteins from several human cell lines, isolated the proteins at the 72-, 55-, 48-, 40-, and 26-kD positions, and used liquid chromatography and tandem mass spectrometry (LC-MS/MS) to determine the protein identities. Although ACTB and GAPDH are 41.7-kD and 36-kD proteins, respectively, LC-MS/MS identified peptides of ACTB and GAPDH at all of these SDS-PAGE positions, making us wonder whether they produce some unknown protein isoforms. The NCBI (National Center for Biotechnology Information, USA) database lists only one ACTB mRNA but five GAPDH mRNAs and one non-coding RNA. The five GAPDH mRNAs encode three protein isoforms, while our bioinformatic analysis identified a 17.6-kD isoform encoded by the non-coding RNA. All LC-MS/MS-identified GAPDH peptides at all positions studied are unique, but some of the identified ACTB peptides are shared by ACTC1, ACTBL2, POTEF, POTEE, POTEI, and POTEJ. ACTC1 and ACTBL2 belong to the ACT family with great similarities to ACTB in protein sequence, whereas the four POTEs are ACTB-containing chimeric genes with the C-terminus of their proteins highly similar to ACTB. These data collectively disqualify GAPDH and ACTB from serving as the reference genes for determination of the protein level in such techniques as Western blotting, a leading role these two genes have been playing for decades in the biomedical research.

molecular biology↗
bioRxiv2020

Comparative genomics reveals different population structures associated with host and geographic origin in antimicrobial-resistant Salmonella enterica

Genetic variation in a pathogen, including the causative agent of salmonellosis, Salmonella enterica, can occur as a result of eco-evolutionary forces triggered by dissimilarities of ecological niches. Here, we applied comparative genomics to study 90 antimicrobial resistant (AMR) S. enterica isolates from bovine and human hosts in New York state and Washington state to understand host- and geographic-associated population structure. Results revealed distinct presence/absence profiles of functional genes and pseudogenes (e.g., virulence genes) associated with bovine and human isolates. Notably, bovine isolates contained significantly more transposase genes but fewer transposase pseudogenes than human isolates, suggesting the occurrence of large-scale transposition in genomes of bovine and human isolates at different times. The high correlation between transposase genes and AMR genes, as well as plasmid replicons, highlights the potential role of horizontally transferred transposons in promoting adaptation to antibiotics. By contrast, a number of potentially geographic-associated single-nucleotide polymorphisms (SNPs), rather than geographic-associated genes, were identified. Interestingly, 38% of these SNPs were in genes annotated as cell surface protein-encoding genes, including some essential for antibiotic resistance and host colonization. Overall, different evolutionary forces and limited recent inter-population transmission appear to shape AMR S. enterica population structure in different hosts and geographic origins. Originality/Significance StatementSalmonella enterica, which is the causative agent of salmonellosis, poses a growing public health concern due to the emergence and spread of antimicrobial resistant (AMR) strains. The mechanisms underlying the population structure associated with different hosts and geographic origins of AMR S. enterica are underexplored due to limited genome-wide studies assessing the impact of ecological niches on genetic variations. By employing comparative genomics, our study provided insights into the genomic profiles of AMR S. enterica associated with two distinct hosts and two distant geographic locations, improving the mechanistic understanding of how bacterial population structure is shaped by different ecological niches. Our findings have broad implications for elucidating the impact of ecological and evolutionary forces on the adaptation, antimicrobial resistance, and pathogenicity of bacteria. Also, specific genetic markers we identified may help predict host or geographic origin of AMR Salmonella isolates, which could benefit the source tracking (e.g., host and geographic origins) of human disease cases and contamination events caused by AMR S. enterica.

microbiology↗
bioRxiv2019

Non-shared dispersal networks with heterogeneity promote species coexistence in hierarchical competitive metacommunities

The competition-colonization trade-off has been a classic paradigm to understand the maintenance of biodiversity in natural ecosystems. However, species-specific dispersal heterogeneities are not well integrated into our general understanding of how spatial coexistence emerges between competitors. Combining both network and metapopulation approaches, we construct a spatially explicit, patch-occupancy dynamic model for communities with hierarchically preemptive competition, to explore species coexistence in shared vs. non-shared dispersal networks with contrasting heterogeneities (including regular, random, exponential and scale-free networks). Our model shows that species with the same demography (i.e. identical colonization and extinction rates) cannot coexist stably in shared networks (i.e. the same dispersal pathways), regardless of dispersal heterogeneity. In contrast, increasing dispersal heterogeneity (even at very low levels of heterogeneity) in non-shared networks can greatly promote spatial coexistence, owing to the segregation-aggregation mechanism by which each species is restricted to self-organized clusters with a core of the most connected patches. However, these competitive patterns are largely mediated by species life-history attributes, for example, a unimodal biodiversity response to an increase of species dispersal rate emerges in non-shared heterogeneous networks, with species richness peaking at intermediate dispersal levels. Interestingly, increasing network size can foster species coexistence, leading to a monotonic increase in species-area curves. This strongly suggests that, unexpectedly, many more species can co-occur than the number of limiting resources. Overall, this modelling study, filling the gap between network structure and spatial competition, provides new insights into the coexistence mechanisms of spatial heterogeneity.

ecology↗
bioRxiv2019

Cytological abnormalities and pollen abortion in interspecific hybrids of Nicotiana

Interspecific cross breeding introduces superior agronomic traits into cultivated species; however, problematic pollen sterility occurs in the hybrids. Our previous study obtained interspecific hybrids from the cross between a cytoplasmic male sterility line of Nicotiana tabacum and Nicotiana alata, and some of the hybrids were pollen sterile. Here, we conducted an in-depth cellular study to understand the cytological mechanism of pollen abortion in these hybrids (F1-D sterile) compared with pollen development in the fertile hybrids (F1-S sterile) from the same cross. The ultrastructure observation showed that the membrane of microspore in F1-D sterile hybrid was deficient at all represented developmental stages. Chromosome behavior during meiosis was studied by carbol fuchsin staining, which indicated that cytomixis, chromosome leakage and asymmetric callose wall deposition occurred with high frequency in the microsporocyte of F1-D sterile. The results of the ultrastructure and 6-diamidino-2-phenylindole (DAPI) analyses also showed that the cytoplasm and nucleus were unstable and extruded from F1-D sterile microspore during the developmental process, leading to mature pollen grains that were vacuous and collapsed in the aperture region. In addition, delayed tapetum degradation was also detected in the anther of F1-D sterile, and might be associated with irregular sporopollenin deposition in the aperture region of F1-D sterile pollen. Genetic unbalance and cytomembrane deficiency might both be responsible for the instability of the chromosome, nuclear and cytoplasm, and resulted in pollen abortion in F1-D sterile hybrids, and irregular tapetum degradation might also be related with pollen sterility.

developmental biology↗
bioRxiv2019

Effect of antenatal tetramethylpyrazine on lung development and YAP expression in a rat model of experimental congenital diaphragmatic hernia

Tetramethylpyrazine (TMP) is a chemical compound found in extracts derived from the Chinese medicinal plant. Due to its remarkable therapeutic effects, availability, and low cost and toxicity, TMP has been used to treat cardiovascular diseases and pulmonary hypertension in China. The aim of this study was to investigate the therapeutic effects and underlying mechanism of TMP on lung development using a rat model of nitrofen-induced congenital diaphragmatic hernia (CDH). Pregnant rats were divided into three groups: control, CDH, and CDH+TMP. Nitrofen was used to induce CDH. In the CDH and CDH+TMP, Fetuses only with left diaphragmatic hernias were chosen for analysis. Lung and body weight were recorded and lung histologic evaluations, image analysis, and western blot analysis of YAP, p-YAP and LATS1 were performed after lung processing. A marked abnormal structure was observed, as evidenced by pulmonary hypoplasia and vascular remodeling, in the CDH. These abnormalities were improved in the CDH+TMP. There were significant differences between the CDH and CDH+TMP in percentage of medial wall thickness, arteriole muscularization, radial alveolar counts, AA%, and alveolar septal thickness. YAP expression was markedly increased in the CDH compared to the control, which was not affected by antenatal TMP administration. However, prenatal TMP intervention significantly increased expression of LATS1 and phosphorylation of YAP in the CDH fetuses. Our results demonstrate that antenatal TMP administration improved vascular remodeling and promoted lung development in a rat model of CDH, potentially through increasing expression of LATS1 and phosphorylation of YAP.

developmental biology↗
bioRxiv2019

Sub-species niche specialization in the oral microbiome is associated with nasopharyngeal carcinoma risk in an endemic area of southern China

Oral health and changes in the oral microbiome have been associated with both local and systemic cancer. Poor oral hygiene is a known risk factor for Nasopharyngeal Carcinoma (NPC), a virally-associated head and neck cancer endemic to southern China. We explored the relationship between NPC and the oral microbiome using 16s rRNA sequencing in a study of 499 NPC patients and 495 population-based age and sex frequency-matched controls from an endemic area of Southern China. We found a significant reduction in community richness in cases compared to controls. Differences in the overall microbial community structure between cases and controls could not be explained by other potential confounders; disease status explained 5 times more variation in the Unweighted UniFrac distance than the next most explanatory variable. In feature-based analyses, we identified a pair of co-excluding Granulicatella adiacens (G. adicans) amplicon sequence variants (ASVs) which were strongly associated with NPC status and differed by a single nucleotide. The G. adicans variant an individual carried was also associated with the overall microbial community based on beta diversity. Co-occurrence analysis suggested the two G. adicans ASVs sit at the center of two co-excluding clusters of closely related organisms. Our results suggest there are differences in the oral microbiome between NPC patients and healthy controls and these may be associated with both a loss of microbial diversity and niche specialization among closely related commensals. Importance The relationship between oral health and the risk of Nasopharyngeal Carcinoma has been previously established. However, the role of oral microbiome has not been evaluated in the disease in a large epidemiological study. This paper clearly establishes a difference in the oral microbiome between NPC patients and healthy controls which cannot be explained by other confounding factors. It furthermore identifies a pair of closely related co-excluding organisms associated with the disease, highlighting the importance of modern methods for single nucleotide resolution in 16s rRNA sequence characterization. To the best of our knowledge, this is one of the first examples of cancer-associated niche-specialization of the oral microbiome.

microbiology↗
bioRxiv2019

Identification of orthotropic material parameters for acute, necrotic, fibrotic and remodelling myocardial infarcts in the rat

Finite element (FE) models have been effectively utilized in studying biomechanical aspects of myocardial infarction (MI). Although the rat is a widely used animal model for MI, there is a lack of material parameters based on anisotropic constitutive models for rat myocardial infarcts in literature. This study aimed at employing inverse methods to identify the parameters of an orthotropic constitutive model for myocardial infarcts in the acute, necrotic, fibrotic and remodelling phases utilizing the biaxial mechanical data developed in a previous study. FE model was developed mimicking the setup of the biaxial tensile experiment. The orthotropic case of the generalized Fung constitutive model was utilized to model the material properties of the infarct. The parameters of Fung model were optimized so that the FE solution best fitted the biaxial experimental stress-strain data. A genetic algorithm was used to minimize the objective function. Fung orthotropic material parameters for different infarct stages were identified. The FE model predictions best approximated the experimental data of the 28 days infarct stage with 3.0% mean absolute percentage error. The worst approximation was for the 7 days stage with 3.6% error. This study demonstrated that the experimental biaxial stress-strain data of healing rat infarcts could be successfully approximated using inverse FE methods and genetic algorithms. The material parameters identified in this study will provide an essential platform for FE investigations of biomechanical aspects of MI and the development of therapies.

bioengineering↗
bioRxiv2019

A revised 1.6 Å structure of the GTPase domain of the Parkinson’s disease-associated protein LRRK2 provides insights into mechanisms

Leucine-rich repeat kinase 2 (LRRK2) is a large 286 kDa multi-domain protein whose mutation is a common cause of Parkinsons disease (PD). One of the common sites of familial PD-associated mutations occurs at residue Arg-1441 in the GTPase domain of LRRK2. Previously, we reported that the PD-associated mutation R1441H impairs the catalytic activity of the GTPase domain thereby traps it in a persistently \"on\" state. More recently, we reported that the GTPase domain of LRRK2 exists in a dynamic dimer-monomer equilibrium where GTP binding shifts it to the monomeric conformation while GDP binding shifts it back to the dimeric state. We also reported that all of the PD-associated mutations at Arg-1441, including R1441H, R1441C, and R1441G, impair the nucleotide-dependent dimer-monomer conformational dynamics of the GTPase domain. However, the mechanism of this nucleotide-dependent conformational dynamics and how it is impaired by the mutations at residue Arg-1441 remained unclear. Here, we report a 1.6 [A] crystal structure of the GTPase domain of LRRK2. Our structure has revealed a dynamic switch region that can be differentially regulated by GTP and GDP binding. This nucleotide-dependent regulation is impaired when residue Arg-1441 is substituted with the PD-associated mutations due to the loss of its exquisite interactions consisting of two hydrogen bonds and a {pi}-stacking interaction at the dimer interface.\n\nSignificance StatementMutations in LRRK2 are associated with familial Parkinsons disease, so understanding its mechanism of actions and how they are changed by the disease-associated mutations is important for developing therapeutic strategies. This paper describes an atomic structure of the G-domain of LRRK2 revealing that the conformational dynamics of the switch regions are potentially important for its normal function. It further shows that a disease-associated mutation could lock the G domain in a persistently active-like conformation, thus perturbing its normal function.

biochemistry↗
bioRxiv2019

Infection of Plasmodiophora brassicae changes the fungal endophyte community of tumourous stem mustard roots as revealed by high-throughput sequencing and culture-dependent methods

Diverse fungal endophytes live in plants and are shaped by some abiotic and biotic stresses. Plant disease as particular biotic stress possibly gives an impact on the communities of fungal endophytes. In this study, clubroot disease caused by an obligate biotroph protist, Plasmodiophora brassicae, was considered to analyze its influence on the fungal endophyte community using an internal transcribed spacer (ITS) through high-throughput sequencing and culture-dependent methods. The results show that the diversity of the endophyte community in the healthy roots was much higher than the clubroots. Ascomycota was the dominant group of endophytes (including Phoma, Mortierella, Penicillium, etc.) in the healthy roots while P. brassicae was the dominant taxon in the clubroots. Hierarchical clustering, principal component analysis (PCA) and principal coordinates analysis (PCoA) indicated significant differences between the endophyte communities in the healthy roots and clubroots. Linear discriminant analysis effect size (LefSe) analysis showed that the dominant genera could be regarded as potential biomarkers. The endophyte community in the healthy roots had a more complex network compared with the clubroots. Also, many plant pathogenic Fusarium were isolated from the clubroots by the culture-dependent method. The outcome of this study illustrates that P. brassicae infection may change the fungal endophyte community associated with the roots of tumourous stem mustard and facilitates the entry of soil pathogen into the roots.

microbiology↗
bioRxiv2018

Differential DNA modification of an enhancer at the IGF2 locus affects dopamine synthesis in patients with major psychosis

Dopamine dysregulation is central to the pathogenesis of diseases with major psychosis, but its molecular origins are unclear. In an epigenome-wide investigation in neurons, individuals with schizophrenia and bipolar disorder showed reduced DNA modifications at an enhancer in IGF2, which disrupted the regulation of the dopamine synthesis enzyme tyrosine hydroxylase and striatal dopamine levels in transgenic mice. Epigenetic control of this enhancer may be an important molecular determinant of psychosis.

neuroscience↗
bioRxiv2018

Animal models of chemotherapy-induced peripheral neuropathy: a machine-assisted systematic review and meta-analysis A comprehensive summary of the field to inform robust experimental design

Background and aimsChemotherapy-induced peripheral neuropathy (CIPN) can be a severely disabling side-effect of commonly used cancer chemotherapeutics, requiring cessation or dose reduction, impacting on survival and quality of life. Our aim was to conduct a systematic review and meta-analysis of research using animal models of CIPN to inform robust experimental design.\n\nMethodsWe systematically searched 5 online databases (PubMed, Web of Science, Citation Index, Biosis Previews and Embase (September 2012) to identify publications reporting in vivo CIPN modelling. Due to the number of publications and high accrual rate of new studies, we ran an updated search November 2015, using machine-learning and text mining to identify relevant studies.\n\nAll data were abstracted by two independent reviewers. For each comparison we calculated a standardised mean difference effect size then combined effects in a random effects meta- analysis. The impact of study design factors and reporting of measures to reduce the risk of bias was assessed. We ran power analysis for the most commonly reported behavioural tests.\n\nResults341 publications were included. The majority (84%) of studies reported using male animals to model CIPN; the most commonly reported strain was Sprague Dawley rat. In modelling experiments, Vincristine was associated with the greatest increase in pain-related behaviour (-3.22 SD [-3.88; -2.56], n=152, p=0). The most commonly reported outcome measure was evoked limb withdrawal to mechanical monofilaments. Pain-related complex behaviours were rarely reported. The number of animals required to obtain 80% power with a significance level of 0.05 varied substantially across behavioural tests. Overall, studies were at moderate risk of bias, with modest reporting of measures to reduce the risk of bias.\n\nConclusionsHere we provide a comprehensive summary of the field of animal models of CIPN and inform robust experimental design by highlighting measures to increase the internal and external validity of studies using animal models of CIPN. Power calculations and other factors, such as clinical relevance, should inform the choice of outcome measure in study design.

neuroscience↗
bioRxiv2018

Automation of citation screening in pre-clinical systematic reviews

BackgroundThe amount of published in vivo studies and the speed researchers are publishing them make it virtually impossible to follow the recent development in the field. Systematic review emerged as a method to summarise and analyse the studies quantitatively and critically but it is often out-of-date due to its lengthy process. MethodWe invited five machine learning and text-mining groups to build classifiers for identifying publications relevant to neuropathic pain (33814 training publications). We kept 1188 publications for the assessment of the performance of different classifiers. Two groups participated in the next stage: testing their algorithm on datasets labeled for psychosis (11777/2944) and datasets labeled for Vitamin D in multiple sclerosis (train/text: 2038/510). ResultThe performances (sensitive/specificity) of the most promising classifier built for neuropathic pain are: 95%/84%. The performance for psychosis and Vitamin D in multiple sclerosis datasets are 95%/73% and 100%/45%. ConclusionsMachine learning can significantly reduce the irrelevant publications in a systematic review, and save the scientists time and money. Classifier algorithms built for one dataset can be reapplied on another dataset in different field. We are building a machine learning service at the back of Systematic Review & Meta-analysis Facility (SyRF).

scientific communication and education↗
bioRxiv2018

The use of text-mining and machine learning algorithms in systematic reviews: reducing workload in preclinical biomedical sciences and reducing human screening error

BackgroundHere we outline a method of applying existing machine learning (ML) approaches to aid citation screening in an on-going broad and shallow systematic review of preclinical animal studies, with the aim of achieving a high performing algorithm comparable to human screening.\n\nMethodsWe applied ML approaches to a broad systematic review of animal models of depression at the citation screening stage. We tested two independently developed ML approaches which used different classification models and feature sets. We recorded the performance of the ML approaches on an unseen validation set of papers using sensitivity, specificity and accuracy. We aimed to achieve 95% sensitivity and to maximise specificity. The classification model providing the most accurate predictions was applied to the remaining unseen records in the dataset and will be used in the next stage of the preclinical biomedical sciences systematic review. We used a cross validation technique to assign ML inclusion likelihood scores to the human screened records, to identify potential errors made during the human screening process (error analysis).\n\nResultsML approaches reached 98.7% sensitivity based on learning from a training set of 5749 records, with an inclusion prevalence of 13.2%. The highest level of specificity reached was 86%. Performance was assessed on an independent validation dataset. Human errors in the training and validation sets were successfully identified using assigned the inclusion likelihood from the ML model to highlight discrepancies. Training the ML algorithm on the corrected dataset improved the specificity of the algorithm without compromising sensitivity. Error analysis correction leads to a 3% improvement in sensitivity and specificity, which increases precision and accuracy of the ML algorithm.\n\nConclusionsThis work has confirmed the performance and application of ML algorithms for screening in systematic reviews of preclinical animal studies. It has highlighted the novel use of ML algorithms to identify human error. This needs to be confirmed in other reviews, , but represents a promising approach to integrating human decisions and automation in systematic review methodology.

neuroscience↗
bioRxiv2018

Estimating the statistical performance of different approaches to meta-analysis of data from animal studies in identifying the impact of aspects of study design

BackgroundMeta-analysis is increasingly used to summarise the findings identified in systematic reviews of animal studies modelling human disease. Such reviews typically identify a large number of individually small studies, testing efficacy under a variety of conditions. This leads to substantial heterogeneity, and identifying potential sources of this heterogeneity is an important function of such analyses. However, the statistical performance of different approaches (normalised compared with standardised mean difference estimates of effect size; stratified meta-analysis compared with meta-regression) is not known.\n\nMethodsUsing data from 3116 experiments in focal cerebral ischaemia to construct a linear model predicting observed improvement in outcome contingent on 25 independent variables. We used stochastic simulation to attribute these variables to simulated studies according to their prevalence. To ascertain the ability to detect an effect of a given variable we introduced in addition this \"variable of interest\" of given prevalence and effect. To establish any impact of a latent variable on the apparent influence of the variable of interest we also introduced a \"latent confounding variable\" with given prevalence and effect, and allowed the prevalence of the variable of interest to be different in the presence and absence of the latent variable.\n\nResultsGenerally, the normalised mean difference (NMD) approach had higher statistical power than the standardised mean difference (SMD) approach. Even when the effect size and the number of studies contributing to the meta-analysis was small, there was good statistical power to detect the overall effect, with a low false positive rate. For detecting an effect of the variable of interest, stratified meta-analysis was associated with a substantial false positive rate with NMD estimates of effect size, while using an SMD estimate of effect size had very low statistical power. Univariate and multivariable meta-regression performed substantially better, with low false positive rate for both NMD and SMD approaches; power was higher for NMD than for SMD. The presence or absence of a latent confounding variables only introduced an apparent effect of the variable of interest when there was substantial asymmetry in the prevalence of the variable of interest in the presence or absence of the confounding variable.\n\nConclusionsIn meta-analysis of data from animal studies, NMD estimates of effect size should be used in preference to SMD estimates, and meta-regression should, where possible, be chosen over stratified meta-analysis. The power to detect the influence of the variable of interest depends on the effect of the variable of interest and its prevalence, but unless effects are very large adequate power is only achieved once at least 100 experiments are included in the meta-analysis.

bioinformatics↗
bioRxiv2018

Structural and functional influences of urban and rural childhoods on the medial prefrontal cortex

Global increases in urbanization have brought dramatic economic, environmental and social changes. However, less is understood about how these may influence disease-related brain mechanisms underlying epidemiological observations that urban birth and childhoods may increase the risk for neuropsychiatric disorders, including increased social stress and depression. In a genetically homogeneous Han Chinese adult population with divergent urban and rural birth and childhoods, we examined the structural and functional MRI neural correlates of childhood urbanicity, focusing on behavioral traits responding to social status threats, and polygenic risk for depression. Subjects with divergent rural and urban childhoods were similar in adult socioeconomic status and were genetically homogeneous. Urban childhoods, however, were associated with higher trait anxiety-depression. On structural MRI, urban childhoods were associated with relatively reduced medial prefrontal gray matter volumes. Functional medial prefrontal engagement under social status threat during working memory correlated with trait anxiety-depression in subjects with urban childhoods, to a significantly greater extent than in their rural counterparts, implicating an exaggerated physiological response to the threat context. Stress-associated medial prefrontal engagement also interacted with polygenic risk for depression, significantly predicting a differential response in individuals with urban but not rural childhoods. Developmental urbanicity thus differentially influenced medial prefrontal structure and function, at least in part through mechanisms associated with the neural processing of social status threat, trait anxiety, and genetic risk for depression, which may be factors in the association of urbanicity with adult psychopathology.\n\nSignificance StatementUrban living has been associated with social inequalities and stress. However, less is understood about the neural underpinnings by which these stressors affect disease risk, and in particular, genetic risk for depression. Leveraging urbanization in China, we studied adults with diverse urban and rural upbringings, who were genetically homogeneous and with similar current socioeconomic status, to isolate the effects of childhood urbanicity. At medial prefrontal cortex, a region critical for processing emotional stressors and social status, genetic risk for depression resulted in more deleterious function under stress in individuals with urban, but not rural childhoods. This implicates medial prefrontal cortexs critical role in brain development, integrating genetic mechanisms of stress and depression with the childhood environment.

neuroscience↗
bioRxiv2017

Single-cell RNA-Seq Resolves Cellular Heterogeneity and Transcriptional Dynamics during Spermatogonia Stem Cells Establishment and Differentiation

The transition of gonocytes to spermatogonia and subsequent differentiation provide the foundation of spermatogenesis. However, systematic understanding on the cellular and molecular basis of this process is still limited, mainly impeded by the asynchrony in development and the lack of stage-specific markers. Using single-cell RNA sequencing on Oct4-GFP+/KIT- cells isolated from PND5.5 mice, we dissected the cellular heterogeneity and established molecular regulations. We demonstrated that gonocyte-spermatogonial transition was characterized by gene expression change related to apoptosis, cell cycle progression, and regulation of migration processes. Pseudotime analysis reconstructed developmental dynamics of the spermatogonial populations and unraveled sequential cellular and molecular transitions. We also identified CD87 as a neonatal stem cell marker which are potentially involved in the intial establishment of SSC pool. Lastly, we uncovered an unexpected subpopulation of spermatogonia primed to differentiation within the undifferentiated compartment, which is characterized by the lack of self-renewal genes and enhanced Oct4 expression and retinoic acid signaling response. Our study thus provides a novel understanding of cellular and molecular changes during spermatogonial establishment.

developmental biology↗
bioRxiv2017

CAM: A Quality Control Pipeline For MNase-Seq Data

Nucleosome organization affects the accessibility of cis-elements to trans-acting factors. Micrococcal nuclease digestion followed by high-throughput sequencing (MNase-seq) is the most popular technology used to profile nucleosome organization on a genome-wide scale. Evaluating the data quality of MNase-seq data remains challenging, especially in mammalian. There is a strong need for a convenient and comprehensive approach to obtain dedicated quality control (QC) for MNase-seq data analysis. Here we developed CAM, which is a comprehensive QC pipeline for MNase-seq data. The CAM pipeline provides multiple informative QC measurements and nucleosome organization profiles on different potentially functional regions for given MNase-seq data. CAM also includes 268 historical MNase-seq datasets from human and mouse as a reference atlas for unbiased assessment. CAM is freely available at: http://www.tongji.edu.cn/~zhanglab/CAM

bioinformatics↗