Biology subjects

Qian, Y.

Publications and source records attributed to Qian, Y..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

A brain-to-text framework of decoding natural tonal sentences

Speech brain-computer interfaces (BCIs) directly translate brain activity into speech sound and text, yet decoding tonal languages like Mandarin Chinese poses a significant, unexplored challenge. Despite successful cases in non-tonal languages, the complexities of Mandarin, with its distinct syllabic structures and pivotal lexical information conveyed through tonal nuances, present challenges in BCI decoding. Here we designed a brain-to-text framework to decode Mandarin tonal sentences from invasive neural recordings. Our modular approach dissects speech onset, base syllables, and lexical tones, integrating them with contextual information through Bayesian likelihood and the Viterbi decoder. The results demonstrate accurate tone and syllable decoding under variances in continuous naturalistic speech production, surpassing previous intracranial Mandarin tonal syllable decoders in decoding accuracy. We also verified the robustness of our decoding framework and showed that the model hyperparameters can be generalized across participants of varied gender, age, education backgrounds, pronunciation behaviors, and coverage of electrodes. Our pilot study shed lights on the feasibility of more generalizable brain-to-text decoding of natural tonal sentences from patients with high heterogeneities.

neuroscience↗

bioRxiv2024

Commonly used software tools produce conflicting and overly-optimistic AUPRC values

The precision-recall curve (PRC) and the area under it (AUPRC) are useful for quantifying classification performance. They are commonly used in situations with imbalanced classes, such as cancer diagnosis and cell type annotation. We evaluated 10 popular tools for plotting PRC and computing AUPRC, which were collectively used in >3,000 published studies. We found the AUPRC values computed by the tools rank classifiers differently and some tools produce overly-optimistic results.

bioinformatics↗

bioRxiv2023

Camel milk affects serum metabolites by modulating the intestinal microflora

Gut microbes play a vital role in human health and are influenced by numerous factors including diet, genetics, and environment. (Fermented) Camel milk, which is abundant in nutrients and lacks allergenic proteins, has been consumed for its edible and medicinal properties for centuries. Research on camel milks impact on gut microbiota and host metabolism is still limited. The results found that sour camel milk contained various beneficial bacteria such as Lactobacillus helveticus, Acinetobacter lwoffii, Eubacterium coprostanoligenes group, Lachnospiraceae, which could be transported to the recipients intestines by diet. This study specified that the transportation of microbiome happened both intra- and inter-species and played a principal role in the formation of progeny gut microflora. An investigation on type 2 diabetic rats revealed that the composition of gut microflora and serum metabolites of those fed with high-dose camel whey was closer to that of the normal. Eubacterium limnetica, which can reduce the risk of diseases by producing MtcB protein, was found in the gut microflora of the ones taking camel milk. These results evidenced the high potential of camel milk as a functional food.

microbiology↗

bioRxiv2023

Specific and comprehensive genetic targeting reveals brain-wide distribution and synaptic input patterns of GABAergic axo-axonic interneurons

Axo-axonic cells (AACs), also called chandelier cells (ChCs) in the cerebral cortex, are the most distinctive type of GABAergic interneurons described in the neocortex, hippocampus, and basolateral amygdala (BLA). AACs selectively innervate glutamatergic projection neurons (PNs) at their axon initial segment (AIS), thus may exert decisive control over PN spiking and regulate PN functional ensembles. However, the brain-wide distribution, synaptic connectivity, and circuit function of AACs remains poorly understood, largely due to the lack of specific and reliable experimental tools. Here, we have established an intersectional genetic strategy that achieves specific and comprehensive targeting of AACs throughout the mouse brain based on their lineage (Nkx2.1) and molecular (Unc5b, Pthlh) markers. We discovered that AACs are deployed across essentially all the pallium-derived brain structures, including not only the dorsal pallium-derived neocortex and medial pallium-derived hippocampal formation, but also the lateral pallium-derived claustrum-insular complex, and the ventral pallium-derived extended amygdaloid complex and olfactory centers. AACs are also abundant in anterior olfactory nucleus, taenia tecta and lateral septum. AACs show characteristic variations in density across neocortical areas and layers and across subregions of the hippocampal formation. Neocortical AACs comprise multiple laminar subtypes with distinct dendritic and axonal arborization patterns. Retrograde monosynaptic tracing from AACs across neocortical, hippocampal and BLA regions reveal shared as well as distinct patterns of synaptic input. Specific and comprehensive targeting of AACs facilitates the study of their developmental genetic program and circuit function across brain structures, providing a ground truth platform for understanding the conservation and variation of a bona fide cell type across brain regions and species.

neuroscience↗

bioRxiv2023

Cortical network and projection neuron types that articulate serial order in a skilled motor behavior

The coordination of forelimb and orofacial movements to compose an ethological reach-to-consume behavior likely involves neural communication across brain regions. Leveraging wide-field imaging and photo-inhibition to survey across the cortex, we identified a cortical network and a high-order motor area (MOs-c), which coordinate action progression in a mouse reach-and-withdraw-to-drink (RWD) behavior. Electrophysiology and photo-inhibition across multiple projection neuron types within the MOs-c revealed differential contributions of pyramidal tract and corticothalamic (CTMOs) output channels to action progression and hand-mouth coordination. Notably, CTMOs display sustained firing throughout RWD sequence and selectively enhance RWD-relevant activity in postsynaptic thalamus neurons, which also contribute to action coordination. CTMOs receive converging monosynaptic inputs from forelimb and orofacial sensorimotor areas and are reciprocally connected to thalamic neurons, which project back to the cortical network. Therefore, motor cortex corticothalamic channel may selectively amplify the thalamic integration of cortical and subcortical sensorimotor streams to coordinate a skilled motor sequence.

neuroscience↗

bioRxiv2023

Thymically imprinted differential responsivity of naive CD4 T cells to IL2 results in a heterogeneity of both Treg induction and subsequent effector functioning

Thymic selection predisposes naive T cells to particular outcomes when challenged later with cognate antigen, whether the antigen is self or foreign. This suggests that there is an inherent heterogeneity of functioning among T cells within the naive population (both CD4 and CD8s), and that each T cell, as part of its thymic development, is given a certain programming which will affect its eventual fate decisions. In this project, we looked at the primary effects of this thymic imprinting on the conversion of naive CD4 T cells into Tregs. Further, using an induced-Treg-reporter system, we exam the impact of thymic imprinted heterogeneity on effector functionality and identity stability. We report that naive T cell differential responsivity to cytokines leads to the observed difference in Treg induction, and that the Tregs induced from T cells of different self-affinities maintain a heterogeneity of effector function and identity.

immunology↗

bioRxiv2023

The Bias of Using Cross-Validation in Genomic Predictions and Its Correction

Cross-validation (CV) is a widely used technique in statistical learning for model evaluation and selection. Meanwhile, various of statistical learning methods, such as Generalized Least Square (GLS), Linear Mixed-Effects Models (LMM), and regularization methods are commonly used in genomic predictions, a field that utilizes DNA polymorphisms to predict phenotypic traits. However, due to high dimensionality, relatively small sample sizes, and data sparsity in genomic data, CV in these scenarios may lead to an underestimation of the generalization error. In this work, we analyzed the bias of CV in eight methods: Ordinary Least Square (OLS), GLS, LMM, Lasso, Ridge, elastic-net (ENET), and two hybrid methods: one combining GLS with Ridge regularization (GLS+Ridge), and the other combining LMM with Ridge regularization (LMM+Ridge). Leveraging genomics data from the 1,000 Genomes Project and simulated phenotypes, our investigation revealed the presence of bias in all these methods. To address this bias, we adapted a variance-structure method known as Cross-Validation Correction (CVc). This approach aims to rectify the cross-validation error by providing a more accurate estimate of the generalization error. To quantify the performance of our adapted CVc towards all these methods, we applied the trained model to an independently generated dataset, which served as a gold standard for validating the models and calculating the generalization error. The outcomes show that, by leveraging CVc, we corrected the CV bias for most of the methods mentioned above, with two exceptions that are unrectifiable methods: ENET and Lasso. Our work revealed the substantial bias in the use of CV in genomics, a phenomenon under-appreciated by the field of statistical genomics and medicine. Additionally, we demonstrated that bias-corrected models may be formed by adapting CVc, although more work is needed to cover the full spectrum.

bioinformatics↗

bioRxiv2023

Genomic locus of lncRNA-Gm26793 forms an inter-chromosomal molecular lock with Cubn to ensure proper stem cell differentiation and mouse embryogenesis

Inter-chromosomal interactions play a crucial role in 3D genome organization, yet the organizational principles and functional significances remain elusive. In general, long non-coding RNA (lncRNA) loci and transcripts are frequently associated with transcriptional programs modulated by long-range chromatin interactions. Here, we identified a novel lncRNA named Gm26793, which is abundantly distributed in the primitive streak and mesodermal cells of E7.5 mouse gastrula. Through genetic ablation of Gm26793, we observed a preferential responsiveness to primitive endoderm lineage during stem cell differentiation, as well as enhanced occurrence of transient and degenerative state cells in early mouse embryos when the cell fate segregates between epiblast and primitive endoderm. Mechanistically, we revealed the genomic locus of Gm26793, rather than the lncRNA transcript or adjacent gene governs the cell fate preference towards primitive endoderm. Concretely, Gm26793 locus (Chr 7) forms an inter-chromosomal molecular lock with Cubn (Chr 2), restraining the expression of Cubn and maintaining a natural epigenetic landscape, thus ensuring the proper lineage specification in vitro and in vivo. In order to reinforce this lock, CTCF and cohesin complex serves as a ring to fasten the inter-chromosomal contact. Overall, our study provides a clear paradigm that inter-chromosomal interaction collaborates with architectural factors to stabilize nuclear conformation and guarantee faithful gene expression during stem cell differentiation and mammalian embryogenesis.

developmental biology↗

bioRxiv2023

Discovering optimal kinetic pathways for self-assembly using automatic differentiation

During self-assembly of macromolecules ranging from ribosomes to viral capsids, the formation of long-lived intermediates or kinetic traps can dramatically reduce yield of the functional products. Understanding biological mechanisms for avoiding traps and efficiently assembling is essential for designing synthetic assembly systems, but learning optimal solutions requires numerical searches in high-dimensional parameter spaces. Here, we exploit powerful automatic differentiation algorithms commonly employed by deep learning frameworks to optimize physical models of reversible self-assembly, discovering diverse solutions in the space of rate constants for 3-7 subunit complexes. We define two biologically-inspired protocols that prevent kinetic trapping through either internal design of subunit binding kinetics or external design of subunit titration in time. Our third protocol acts to recycle intermediates, mimicking energy-consuming enzymes. Preventative solutions via interface design are the most efficient and scale better with more subunits, but external control via titration or recycling are effective even for poorly evolved binding kinetics. Whilst all protocols can produce good solutions, diverse subunits always helps; these complexes access more efficient solutions when following external control protocols, and are simpler to design for internal control, as molecular interfaces do not need modification during assembly given sufficient variation in dimerization rates. Our results identify universal scaling in the cost of kinetic trapping, and provide multiple strategies for eliminating trapping and maximizing assembly yield across large parameter spaces. SIGNIFICANCEMacromolecular complexes are frequently composed of diverse subunits. While evolution may favor repeated subunits and symmetry, we show how diversity in subunits generates an expansive parameter space that naturally improves the expressivity of self-assembly, much like a deeper neural network. By using automatic differentiation algorithms commonly used in deep learning, we searched these parameter spaces to identify classes of kinetic protocols that mimic biological solutions for productive self-assembly. Our results reveal how high-yield complexes that easily become kinetically trapped in incomplete intermediates can instead be steered by internal design of rate constants or external and active control of subunits to efficiently assemble, exploiting nonequilibrium control of these ubiquitous dynamical systems.

biophysics↗

bioRxiv2023

Estrogen prevents age-dependent beige adipogenesis failure through NAMPT-controlled ER stress pathway

Thermogenic beige adipocytes are recognized as potential therapeutic targets for combating metabolic diseases. However, the metabolic advantages they offer are compromised with aging. Here, we show that treating mice with estrogen (E2), a hormone that decreases with age, to mice can counteract the aging- related decline in beige adipocyte formation when subjected to cold, while concurrently enhancing energy expenditure and improving glucose tolerance. Mechanistically, we find that nicotinamide phosphoribosyltranferase (NAMPT) plays a pivotal role in facilitating the formation of E2-induced beige adipocytes, which subsequently suppresses the onset of age-related ER stress. Furthermore, we found that targeting NAMPT signaling, either genetically or pharmacologically, can restore the formation of beige adipocytes by increasing the number of perivascular adipocyte progenitor cells. Conversely, the absence of NAMPT signaling prevents this process. In conclusion, our findings shed light on the mechanisms governing the age-dependent impairment of beige adipocyte formation and underscore the E2-NAMPT controlled ER stress as a key regulator of this process. HighlightsO_LIEstrogen restores beige adipocyte failure along with improved energy metabolism in old mice. C_LIO_LIEstrogen enhances the thermogenic gene program by mitigating age-induced ER stress. C_LIO_LIEstrogen enhances the beige adipogenesis derived from SMA+ APCs. C_LIO_LIInhibiting the NAMPT signaling pathway abolishes estrogen-promoted beige adipogenesis. C_LI

physiology↗

bioRxiv2023

Identification and functional analysis of extrachromosomal circular DNA in plasma extracellular vesicles of liver failure patients

Withdrawal statementThe authors have withdrawn their manuscript owing to having identified certain issues with the current representation of the data in the manuscript after performing further analyses of the bioinformatics data from their eccDNA sequencing results. Therefore, the authors do not wish this work to be cited as reference for the project. A revised and corrected version will be submitted in the future. If you have any questions, please contact the corresponding authors.

genomics↗

bioRxiv2023

An expression-directed linear mixed model (edLMM) discovering low-effect genetic variants

Detecting genetic variants with low effect sizes using a moderate sample size is difficult, hindering downstream efforts to learn pathology and estimating heritability. In this work, by utilizing informative weights learned from training genetically predicted gene expression models, we formed an alternative approach to estimate the polygenic term in a linear mixed model (LMM). Our LMM estimates the genetic background by incorporating their relevance to gene expression. Our protocol, expression-directed linear mixed model (edLMM), enables the discovery of subtle signals of low-effect variants using moderate sample size. By applying edLMM to cohorts of around 5,000 individuals with either binary (WTCCC) or quantitative (NFBC1966) traits, we demonstrated its power gain at the low-effect end of the genetic etiology spectrum. In aggregate, the additional low-effect variants detected by edLMM substantially improved estimation of missing heritability. edLMM moves precision medicine forward by accurately detecting the contribution of low-effect genetic variants to human diseases.

genetics↗

bioRxiv2023

Pixel-wise programmability enables dynamic high-SNR cameras for high-speed microscopy

High-speed wide-field fluorescence microscopy has the potential to capture biological processes with exceptional spatiotemporal resolution. However, conventional cameras suffer from low signal-to-noise ratio at high frame rates, limiting their ability to detect faint fluorescent events. Here, we introduce an image sensor where each pixel has individually programmable sampling speed and phase, so that pixels can be arranged to simultaneously sample at high speed with a high signal-to-noise ratio. In high-speed voltage imaging experiments, our image sensor significantly increases the output signal-to-noise ratio compared to a low-noise scientific CMOS camera ([~]2-3 folds). This signal-to-noise ratio gain enables the detection of weak neuronal action potentials and subthreshold activities missed by the standard scientific CMOS cameras. Our camera with flexible pixel exposure configurations offers versatile sampling strategies to improve signal quality in various experimental conditions.

neuroscience↗

bioRxiv2023

The Notch-Pdgfr beta axis suppresses brown adipocyte progenitor differentiation in early postnatal mice

De novo brown adipogenesis holds potential in combating the epidemics of obesity and diabetes. However, the identity of brown adipocyte progenitor cells (APCs) and their regulation have not been extensively studied. Here through in vivo lineage tracing, we observed that PDGFR{beta}+ pericytes give rise to developmental brown adipocytes, but not to those in adult homeostasis. In contrast, TBX18+ pericytes contribute to brown adipogenesis throughout both developmental and adult stages, though in a depot-specific manner. Mechanistically, Notch inhibition in PDGFR{beta}+ pericytes promotes brown adipogenesis through the downregulation of PDGFR{beta}. Furthermore, inhibition of Notch signaling in PDGFR{beta}+ pericytes mitigates HFHS (high-fat, high-sucrose) induced glucose and metabolic impairment in both developmental and adult stages. Collectively, these findings show that the Notch/PDGFR{beta} axis negatively regulates developmental brown adipogenesis, and its repression promotes brown adipose tissue expansion and improves metabolic health. HighlightsO_LIPDGFR{beta}+ pericytes act as an essential developmental brown APC. C_LIO_LITBX18+ pericytes contribute to brown adipogenesis in a depot-specific manner. C_LIO_LIInhibiting Notch-Pdgfr{beta} axis promotes brown APC adipogenesis. C_LIO_LIEnhanced postnatal brown adipogenesis improves metabolic health in adult stage. C_LI

developmental biology↗

bioRxiv2023

Building subtraction operators and controllers via molecular sequestration

We show how subtraction can be performed via a simple chemical reaction network that includes molecular sequestration. The network computes the difference between the production rate parameters of the two mutually sequestering species. We benefit from introducing a simple change of variables, that facilitates the derivation of an approximate solution for the differential equations modeling the chemical reaction network, under a time scale separation assumption that is valid when the sequestration rate parameter is sufficiently fast. Our main result is that we provide simple expressions confirming that temporal subtraction occurs when the inputs are constant or time varying. Through simulations, we discuss two sequestration-based architectures for feedback control in light of the subtraction operations they perform.

synthetic biology↗

bioRxiv2023

Time, Space and Single-Cell Resolved Molecular Trajectory of Cell Populations and the Laterality of the Body Plan at Gastrulation

Understanding of the molecular drivers of lineage diversification and tissue patterning during primary germ layer development requires in-depth knowledge of the dynamic molecular trajectories of cell lineages across a series of developmental stages of gastrulation1-7. Through computational modeling, we constructed at single-cell resolution a spatio-temporal compendium of the molecular trajectories of germ-layer derivatives in gastrula-stage mouse embryos. This molecular atlas infers the developmental trajectories of single-cell populations and the molecular network activity underpinning the specification and differentiation of the germ-layer lineages. Analysis of the heterogeneity of cellular composition of cell populations at defined positions in the epiblast revealed progressive diversification of cell types, mirroring the process of lineage allocation during gastrulation. A novel observation is the difference in the contribution of cells on contralateral sides of the epiblast to mesoderm derivatives of the early organogenesis embryo, and the enhanced BMP signaling activity in right-side mesoderm of E7.5 embryo. Perturbation of BMP signaling activity at late gastrulation led to randomization of left-right (L-R) molecular asymmetry in the lateral mesoderm of early-somite-stage embryo. Our findings indicate the asymmetric BMP activity during gastrulation may be critical for the symmetry breaking process associated with specification of L-R body asymmetry ahead of the acquisition of functionality of the L-R organizer.

developmental biology↗

bioRxiv2023

Temporal control by co-factors prevents kinetic trapping in retroviral Gag lattice assembly

For retroviruses like HIV to proliferate, they must form virions shaped by the self-assembly of Gag polyproteins into a rigid lattice. This immature Gag lattice has been structurally characterized and reconstituted in vitro, revealing the sensitivity of lattice assembly to multiple co-factors. Due to this sensitivity, the energetic criterion for forming stable lattices is unknown, as are their corresponding rates. Here, we use a reaction-diffusion model designed from the cryo-ET structure of the immature Gag lattice to map a phase diagram of assembly outcomes controlled by experimentally constrained rates and free energies, over experimentally relevant timescales. We find that productive assembly of complete lattices in bulk solution is extraordinarily difficult due to the large size of this [~]3700 monomer complex. Multiple Gag lattices nucleate before growth can complete, resulting in loss of free monomers and frequent kinetic trapping. We therefore derive a time-dependent protocol to titrate or activate the Gag monomers slowly within the solution volume, mimicking the biological roles of co-factors. This general strategy works remarkably well, yielding productive growth of self-assembled lattices for multiple interaction strengths and binding rates. By comparing to the in vitro assembly kinetics, we can estimate bounds on rates of Gag binding to Gag and the cellular co-factor IP6. Our results show that Gag binding to IP6 can provide the additional time-delay necessary to support smooth growth of the immature lattice with relatively fast assembly kinetics, mostly avoiding kinetic traps. Our work provides a foundation for predicting and disrupting formation of the immature Gag lattice via targeting specific protein- protein binding interactions.

biophysics↗

bioRxiv2022

Cdkn2a regulates beige fat maintenance through BECN1-mediated autophagy

A potential therapeutic target to curb the obesity and diabetes epidemic is thermogenic beige adipocytes. However, beige adipocytes quickly transition into white adipocytes upon removing stimuli. Here, we define the critical role of Cdkn2a as a molecular pedal for the beige-to-white transition. Beige adipocytes lacking Cdkn2a exhibit prolonged lifespan, and mice are more resistant to diet-induced obesity, along with enhanced energy expenditure and improved glucose tolerance. Mechanistic studies demonstrate that Cdkn2a promotes the expression and activity of BECN1 by directly binding to its mRNA and its negative regulator BCL2L1, activating autophagy and accelerating the beige-to-white transition. Notably, reactivating autophagy by pharmacological or genetic methods abolishes beige adipocyte maintenance induced by Cdkn2a-ablation. Furthermore, hyperactive BECN1 alone significantly accelerates the beige-to-white transition. Collectively, these findings show that Cdkn2a-mediated autophagy serves as a brake system for beige adipocyte maintenance and is a highly promising target for anti-obesity and anti-diabetes therapy. HighlightsO_LICdkn2a ablation promotes beige fat maintenance and ameliorates diet-induced obesity C_LIO_LILoss of Cdkn2a retains beige adipocytes by inhibiting BECN1-mediated autophagy C_LIO_LICdkn2a modulates BECN1 by binding to its mRNA and its inhibitor BCL2L1, respectively C_LIO_LIHyperactive BECN1 is sufficient to accelerate the beige-to-white transition C_LI

cell biology↗