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Cai, Q.

Publications and source records attributed to Cai, Q..

At least 37 records · Page 2Linked to original sources

Single-cell transcriptome sequencing for opening the blood-brain barrier through specific mode electroacupuncture stimulation

BackgroundThe blood-brain barrier (BBB) interferes with the treatment of central nervous system disorders owing to the complexity of its structure and restrictive function. Thus, it is challenging to develop central nervous system drug delivery strategies. Specific mode electroacupuncture (EA) stimulation can effectively open the BBB in rats. MethodsHere, we used single-cell RNA sequencing (scRNA-seq) to comprehensively map the cell population in the Sprague-Dawley rat cerebral cortex. ResultsWe identified 23 cell subsets and eight types of cells in the brain by cell annotation. scRNA-seq revealed transcriptional changes in the cerebral cortex under EA. ConclusionsOur findings offer valuable insights into the molecular and cellular modifications in the brain resulting from EA intervention and serve as a resource for drug delivery across healthy and diseased states. Innovative approaches to enhance BBB opening will lead to more effective therapeutic plans and enhanced drug delivery.

neuroscience↗

Development of a replication-defective MPXV platform for fundamental and therapeutic research

The recent global outbreaks of mpox highlight the urgent need for both fundamental research and antiviral development. However, studying monkeypox virus (MPXV), with its large and complex genome, remains challenging due to the requirement for high-containment facilities. Here, we describe a novel strategy for de novo assembly of MPXV clade IIb genomes in bacterial artificial chromosomes using transformation-associated recombination cloning. Leveraging CRISPR-Cas9 and Lambda Red recombination, we engineered replication-defective MPXV particles with dual deletions of OPG96 (M2R) and OPG158 (A32.5L)--genes essential for virion assembly, that are capable of recapitulating key stages of the viral life cycle. Our work demonstrates the utility of replication-defective MPXV particles as a reliable platform for high-throughput antiviral discovery, offering significant advantages for both fundamental virology studies and therapeutic development against orthopoxviruses.

microbiology↗

Population-specific brain charts reveal Chinese-Western differences in neurodevelopmental trajectories

Human brain charts provide unprecedented opportunities for decoding neurodevelopmental milestones and establishing clinical benchmarks for precision brain medicine 1-7. However, current lifespan brain charts are primarily derived from European and North American cohorts, with Asian populations severely underrepresented. Here, we present the first population-specific brain charts for China, developed through the Chinese Lifespan Brain Mapping Consortium (Phase I) using neuroimaging data from 43,037 participants (aged 0-100 years) across 384 sites nationwide. We establish the lifespan normative trajectories for 296 structural brain phenotypes, encompassing global, subcortical, and cortical measures. Cross-population comparisons with Western brain charts (based on data from 56,339 participants aged 0-100 years) reveal distinct neurodevelopmental patterns in the Chinese population, including prolonged cortical and subcortical maturation, accelerated cerebellar growth, and earlier development of sensorimotor regions relative to paralimbic regions. Crucially, these Chinese-specific charts outperform Western-derived models in predicting healthy brain phenotypes and detecting pathological deviations in Chinese clinical cohorts. These findings highlight the urgent need for diverse, population-representative brain charts to advance equitable precision neuroscience and improve clinical validity across populations.

neuroscience↗

SCARF: Single Cell ATAC-seq and RNA-seq Foundation model

Recent advances in single-cell multi-omics have provided unprecedented insights into gene regulation by jointly profiling transcriptomic (scRNA-seq) and chromatin accessibility (scATAC-seq) landscapes. However, the inherent heterogeneity and high dimensionality of these multimodal data present significant challenges for effective integration and downstream analysis. Foundation models have demonstrated strong representation learning capabilities for scRNA-seq or scATAC-seq data. So far, however, no model has been specifically developed for the integrative analysis of these two modalities. Here, we introduce SCARF, a single cell ATAC-seq and RNA-seq foundation model. SCARF is pre-trained on X-Omics, the largest curated collection of single-cell multi-omics data to date, comprising over 2.7 million cells across multiple tissues and species. The model utilizes a Mamba architecture for efficiently capturing long-context relationships between genes and between accessible regions. Modality-specific and shared features are learned by the model through self-supervised learning and contrastive learning, respectively. SCARF achieves state-of-the-art performance on multiple downstream tasks, including cell representation, cell matching, and cross-omics translation. Furthermore, SCARF enables few-shot cell type annotation, demonstrating strong generalizability across previously unseen datasets. These results highlight the power of foundation models for advancing integrative analysis of single cell multi-omics data, with broad applications in important tasks including cellular characterization, gene or genomic perturbation analysis, and regulation network analysis.

bioinformatics↗

Phase separation of Polycomb-like (PCL) proteins drive PRC2 complex condensates to regulate gene expression

Polycomb group (PcG) proteins function as two major multicomponent protein complexes: Polycomb repressive complex 1 (PRC1) and 2 (PRC2) to repress key developmental genes and maintain epigenetic memory of cell identity during development. Phase-separation has long been implicated in PRC1 mediated gene silencing, but it is still unclear whether PRC2 also utilize a similar mechanism to regulate gene expression. Here we report that Polycomb-like (PCL) proteins, PRC2 accessory factors, can phase-separate in vitro and generate dynamic puncta in vivo. Biochemical and cellular analyses reveal that PCL proteins (hereafter referred to as PCLs) have intramolecular interaction between N- and C-terminal domains, which make PCLs into more compact conformations. The intramolecular interaction not only controls the size of the PCLs phase separation droplets, but also affects the chromatin association of PRC2. Finally, we show that CpG islands, key DNA regulatory elements in mammalian promoters, disrupt the N-C intramolecular interaction of PCLs to expose their middle intrinsically disordered regions (IDRs), which in turn trigger PCLs driven PRC2 condensates formation. Together, this study provides a new perspective on the regulation of PRC2 by PCLs, implicating PCLs read CpG islands to fine-tune their oligomerization to overcome the threshold for PRC2 recruitment to corresponding genomic loci via multivalent interaction with CpG islands chromatin.

biochemistry↗

Autonomous learning of pathologists' cancer grading rules

Deep learning reveals that tissue morphology contains rich pathophysiological information beyond human understanding. However, approaches to convert these spatially distributed signals into subcellular insights informing disease mechanisms are lacking. We introduce Delta-Marches, an interpretability-first approach that nominates distinguishing morphological features rather than explaining existing models' decisions. Delta-Marches simulates idealized morphological changes between classes by coupling latent-space traversals with generative AI. Comparing each image to its class-shifted counterpart allows feature extractors to infer the most affected aspects, reducing sample-to-sample variability and resolving transformations at subcellular resolution. Prototyped in renal carcinoma grading, Delta-Marches generates realistic grade transitions and pinpoints tumor-cell nuclear phenotypes as key determinants. It also reveals reduced vasculature with increasing grade, a known pattern absent from standard rubrics. Applied to dysplastic progression in colorectal tissue, it recovers glandular remodeling and goblet-cell loss, generalizing across tissue types and scales. These results show Delta-Marches parses complex image phenotypes and catalyzes hypothesis generation.

bioinformatics↗

Effect Of Perinatal Perfluorinated Compounds (PFASs) Exposure On Behavior Of SD Rats

Perfluorinated compounds (PFASs) are persistent environmental pollutants recognized for their bioaccumulation and potential neurotoxic effects, particularly in relation to attention deficit hyperactivity disorder (ADHD). This study investigated the effects of perinatal PFAS exposure on Sprague-Dawley (SD) rats, with a focus on behavioral outcomes and dopamine metabolism in the prefrontal cortex (PFC). Pregnant rats were administered PFASs at concentrations of 1 mg/L, 3 mg/L, and 10 mg/L through drinking water during gestation and lactation, with a control group included for comparison. The offspring were subjected to behavioral assessments, including open field, marble burying, and jump tests, to evaluate locomotor activity, attention, and impulsivity. Neurochemical analyses were conducted to measure the expression of tyrosine hydroxylase (TH), aromatic L-amino acid decarboxylase (DDC), and dopamine receptor D1 (Drd1) in the PFC using Western blotting and quantitative PCR (qPCR). The results indicated that high-dose PFAS exposure (10 mg/L) resulted in hyperactivity, attention deficits, and impulsive behavior (p < 0.05), along with decreased TH and DDC expression and altered Drd1 levels, suggesting disrupted dopamine metabolism. These findings imply that perinatal PFAS exposure leads to behavioral abnormalities and disruptions in dopamine-related processes.

animal behavior and cognition↗

Unraveling the Neurocognitive Mechanisms of Delayed Punishment in Second- and Third-Party Contexts

Second-party punishment (SPP) and third-party punishment (TPP) are essential in regulating social behavior and maintaining social norms, yet the effectiveness may wane when punishment is delayed. Currently, the decision-making and neural mechanisms underlying SPP and TPP under temporal delays remain largely unexplored. This study investigated both SPP and TPP punishment decisions with time-delay (immediate vs. delayed) using a hypothetical criminal scenario assessment task with fMRI. Results showed increased activity in the bilateral precuneus and left temporoparietal junction (TPJ) and stronger left TPJ-dorsolateral prefrontal cortex (dlPFC) connectivity in SPP compared to TPP. Interestingly, third-parties imposed more severe punishment in delayed conditions than in immediate ones, accompanied by enhanced neural activity in dorsomedial prefrontal cortex (dmPFC), left TPJ, ventrolateral prefrontal cortex (vlPFC), ventromedial prefrontal cortex (vmPFC), and caudate nucleus. This delay effect was evident only in misdemeanor and felony cases, with no differences in capital offenses, suggesting a moderating effect of criminal severity. In contrast, SPP showed no significant changes in punishment or neural response across immediate and delayed conditions. Multivariate pattern analysis further indicated that dmPFC, TPJ, vlPFC, vmPFC and caudate function together to encode punishment severity in TPP contexts, a pattern not observed in SPP. These findings underscore distinct decision-making mechanisms between SPP and TPP under temporal delays, with implications for understanding justice-related processing in the human brain under time constraints. Significance statementWithin the justice system, punishing norm violators is often hindered when they flee, resulting in delayed punishments. However, little is known about how second-party (SPP) and third-party (TPP) implement punishment with time delays. The current study investigated this using real criminal scenarios with time delays under fMRI scanning. We found that third parties imposed more severe punishment on defendants in delayed conditions than in immediate ones, reflected by enhanced neural activity in the dorsomedial prefrontal cortex, left temporoparietal junction, ventrolateral prefrontal cortex, ventromedial prefrontal cortex, and caudate nucleus. In contrast, no significant differences were observed in second-party punishment. We also found a moderating effect of criminal severity: the difference between immediate and delayed sanctions by third-parties was present in misdemeanor and felony cases but not in capital offenses. These results shed light on the decision-making mechanisms of SPP and TPP in contexts involving temporal delay, which may have deep impact in different disciplines, e.g., social science, cognitive neuroscience and legal system.

neuroscience↗

Leopard Cats Occupied Human Settlements in China for 3,500 years before the Arrival of Domestic cats in 600-900 CE around the Tang Dynasty

The earliest cats in human settlements in China were not domestic cats (Felis catus), but native leopard cats (Prionailurus bengalensis). To trace when and how domestic cats arrived in East Asia, we analyzed 22 feline bones from 14 sites across China spanning 5,000 years. Nuclear and mitochondrial genomes revealed that leopard cats began occupying anthropogenic scenes around 5,400 years ago and last appeared in 150 CE. Following several centuries gap of archeological feline remains, the first known domestic cat (706-883 CE) in China was identified in Shaanxi during the Tang Dynasty. Genomic analysis suggested a white or partially white coat and a link to a contemporaneous domestic cat from Kazakhstan, indicating a likely dispersal route via the Silk Road. The two felids once independently occupied ancient anthropogenic environments in China but followed divergent paths and reached different destinations in human-animal interactions.

evolutionary biology↗

Zmap: an intelligent region-allocation method to map single-cell into spatial data

Integration of single-cell and spatial transcriptome represents as a fundamental strategy to enhance spatial data quality. However, existing methods for mapping single-cell data to spatial coordinates struggle with large-scale datasets comprising millions of cells. Here, we introduce Zmap, an intelligent region-allocation method inspired by the region-of-interest (ROI) concept from image processing. By using gradient descent, Zmap allocates cells to structured spatial regions that matching the most significant biological information, optimizing the integration of data and improving speed and accuracy. Zmap excels in integrating data even in the presence of various sequencing artifacts, such as cell segmentation errors and imbalanced cell-type representations. Zmap outperforms state-of-the-art methods by 10 to 1000 times in speed, and it is the only approach capable of integrating datasets containing millions of cells in a single run. As a result, Zmap uncovers originally hidden gene expression patterns in the brain section, offers new insights into organogenesis and tumor microenvironments, all with exceptional efficiency and accuracy.

bioinformatics↗

YX0798 Is a Highly Potent, Selective, and Orally Effective CDK9 Inhibitor for Treating Aggressive Lymphoma

Non-genetic transcription evolution has been increasingly explored and recognized to drive tumor cell progression and therapeutic resistance. As the regulation hub of transcription machinery, cyclin-dependent kinase 9 (CDK9) is the gatekeeper of RNA polymerase II (Pol II) transcription, and CDK9 dysfunction results in transcriptomic reprogramming and tumor cell progression. We recently reported that the HSP90-MYC-CDK9 network drives therapeutic resistance in mantle cell lymphoma (MCL) through transcriptomic reprogramming. We also showed that targeting CDK9 by AZD4573 and enitociclib is a safe and effective treatment in preclinical MCL models, supporting CDK9 as a valid therapeutic target for MCL. However, current CDK9 inhibitors (CDK9i) under therapeutic development have room for improvement due to limited target selectivity and oral bioavailability. To this end, YX0798 was discovered to be a novel CDK9i through structural optimization. YX0798 demonstrated remarkable target selectivity and high affinity in binding to CDK9. Furthermore, YX0798 showed good oral bioavailability. YX0798, when administrated orally (5 mg/kg, daily), led to an efficacious anti-tumor activity in vivo and showed the potency in overcoming therapeutic resistance. Mechanistically, YX0798 downregulated the short-lived oncoprotein c-MYC and pro-survival protein MCL-1 as a common mechanism of CDK9 inhibition. Moreover, YX0798 disrupted the cell cycle and resulted in transcriptomic reprogramming, eventually leading to cell death. Together, these data demonstrate that YX0798 has oral bioavailability, exquisite selectivity, and anti-tumor potency that results from driving transcription reprogramming towards tumor cell killing. KEY POINTSO_LIYX0798 showed high selectivity, target binding affinity, and anti-tumor efficacy in overcoming resistance to various therapies. C_LIO_LIYX0798 had good oral pharmacokinetics and anti-tumor effects that resulted from transcription reprogramming towards tumor cell killing. C_LI

cancer biology↗

The Arabidopsis amino acid transporter UmamiT20 confers susceptibility to B. cinerea

O_LIInduction of SWEET sugar transporters by bacterial pathogens via transcription activator-like (TAL) effectors is necessary for successful blight infection of rice, cassava and cotton, - likely providing sugars for bacterial propagation. C_LIO_LIHere, we show that infection of Arabidopsis by the necrotrophic fungus Botrytis cinerea causes increased accumulation of amino acid transporter UmamiT20 mRNA in leaves. UmamiT20 protein accumulates in leaf veins surrounding the lesions after infection. Consistent with a role during infection, umamiT20 knock-out mutants were less susceptible to B. cinerea. C_LIO_LIFunctional assays demonstrate that UmamiT20 mediates amino acid transport of a wide range of amino acid substrates. C_LIO_LIPathogen-induced UmamiT20 mRNA and protein accumulation support the hypothesis that transporter-mediated pathogen susceptibility is not unique to SWEETs in bacterial blight of rice but also for a necrotrophic fungus and implicate nutrients other than sucrose, i.e., amino acids, in nutrition or nutrient signaling related to immunity. We hypothesize that stacking of mutations in different types of susceptibility-related nutrient carriers to interfere with access to several nutrients may enable engineering robust pathogen resistance in a wide range of plant-pathogen systems. C_LI Lay AbstractPathogens infect plants to gain access to their nutrient resources, enabling the pathogens to cause disease and reproduce efficiently. Here we find that an amino acid transporter constitutes a susceptibility factor for the fungal pathogen B. cinerea.

plant biology↗

Deep-learning and analytical models give distinct results for the brain structure-function relationship in health and in psychosis

Understanding the intricate relationship between brain structure and function is a cornerstone challenge in neuroscience, critical for deciphering the mechanisms that underlie healthy and pathological brain function. In this work, we present a comprehensive framework for mapping structural connectivity measured via diffusion-MRI to resting-state functional connectivity measured via magnetoencephalography, utilizing a deep-learning model based on a Graph Multi-Head Attention AutoEncoder. We compare the results to those from an analytical model that utilizes shortest-path-length and search-information communication mechanisms. The deep-learning model outperformed the analytical model in predicting functional connectivity in healthy participants at the individual level, achieving mean correlation coefficients higher than 0.8 in the alpha and beta frequency bands. Our results imply that human brain structural connectivity and electrophysiological functional connectivity are tightly coupled. The two models suggested distinct structure-function coupling in people with psychosis compared to healthy participants (p < 2 x 10-4 for the deep-learning model, p < 3 x 10-3 in the delta band for the analytical model). Importantly, the alterations in the structure-function relationship were much more pronounced than any structure-specific or function-specific alterations observed in the psychosis participants. The findings demonstrate that analytical algorithms effectively model communication between brain areas in psychosis patients within the delta and theta bands, whereas more sophisticated models are necessary to capture the dynamics in the alpha and beta band.

neuroscience↗

Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing

Characterizing DNA methylation patterns is important for addressing key questions in evolutionary biology, geroscience, and medical genomics. While costs are decreasing, whole-genome DNA methylation profiling remains prohibitively expensive for most population-scale studies, creating a need for cost-effective, reduced representation approaches (i.e., assays that rely on microarrays, enzyme digests, or sequence capture to target a subset of the genome). Most common whole genome and reduced representation techniques rely on bisulfite conversion, which can damage DNA resulting in DNA loss and sequencing biases. Enzymatic methyl sequencing (EM-seq) was recently proposed to overcome these issues, but thorough benchmarking of EM-seq combined with cost-effective, reduced representation strategies has not yet been performed. To do so, we optimized Targeted Methylation Sequencing protocol (TMS)--which profiles [~]4 million CpG sites--for miniaturization, flexibility, and multispecies use at a cost of [~]$80. First, we tested modifications to increase throughput and reduce cost, including increasing multiplexing, decreasing DNA input, and using enzymatic rather than mechanical fragmentation to prepare DNA. Second, we compared our optimized TMS protocol to commonly used techniques, specifically the Infinium MethylationEPIC BeadChip (n=55 paired samples) and whole genome bisulfite sequencing (n=6 paired samples). In both cases, we found strong agreement between technologies (R{superscript 2} = 0.97 and 0.99, respectively). Third, we tested the optimized TMS protocol in three non-human primate species (rhesus macaques, geladas, and capuchins). We captured a high percentage (mean=77.1%) of targeted CpG sites and produced methylation level estimates that agreed with those generated from reduced representation bisulfite sequencing (R{superscript 2} = 0.98). Finally, we applied our protocol to profile age-associated DNA methylation variation in two subsistence-level populations--the Tsimane of lowland Bolivia and the Orang Asli of Peninsular Malaysia--and found age-methylation patterns that were strikingly similar to those reported in high income cohorts, despite known differences in age-health relationships between lifestyle contexts. Altogether, our optimized TMS protocol will enable cost-effective, population-scale studies of genome-wide DNA methylation levels across human and non-human primate species.

genomics↗

Spatial Heterogeneity of Climate Fluctuations Shapes Ecological Processes and Community Dynamics in Riverine Invertebrates Across a Landscape

The environment and its variability exhibit spatial heterogeneity in influencing ecological processes and community dynamics across landscapes. However, the mechanisms remain unexplored. This study investigates relative significance of temporal ecological processes that shape invertebrate community dynamics across 15 rivers in the European Iberian Peninsula over 21 years. Spatial asymmetry in community dynamics was driven by a combination of temporal deterministic and stochastic processes (i.e., environmental filtering and temporal distance within the same locations, respectively). It is noteworthy that the relative importance of deterministic versus stochastic processes diminishes with increasing elevation. The analysis of community dynamics in diverse landscapes offers a foundation for anticipating and mitigating the consequences of prospective environmental transformation on biodiversity, thereby directing efficacious conservation strategies.

ecology↗

A comprehensive analysis of the potential biological functions and prognostic values of SREBF1 for multiple cancer types including colorectal cancer

As an important molecule involved in lipid metabolism, Sterol Regulatory Element-Binding Protein 1 (SREBF1) plays a critical role in governing cellular lipid synthesis and uptake. However, a comprehensive understanding of the biological significance of SREBF1 in pan-cancer remains elusive. In this study, we aimed to comprehensively analyze the functional characteristics of SREBF1 in human cancers, including colorectal cancer (CRC). Our study utilized various databases and tools such as TCGA, GEO, TIMER2.0, GEPIA2.0, UALCAN, and the Human Protein Atlas to examine SREBF1 expression, genetic alterations, immune infiltration, single-cell sequencing, survival analysis, and gene enrichment. The results revealed that the expression of SREBF1 exhibited significant variations across different cancer types, and was closely associated with patient prognosis and immune infiltration. Moreover, the gene function assays indicated SREBF1 significantly affect cell growth and migration. Overall, the findings suggest that SREBF1 could serve as a potential prognostic biomarker and a novel therapeutic target in different cancer types.

cancer biology↗

On the discovered Cancer Driving Nucleotides (CDNs)-Distributions across genes, cancer types and patients

A central goal of cancer genomics is to identify, in each patient, all the cancer driving mutations. Among them, point mutations are referred to as Cancer Driving Nucleotides (CDNs), which recur in cancers. The companion study shows that the probability of i recurrent hits in n patients would decrease exponentially with i; hence, any mutation with i [&ge;] 3 hits in the TCGA database is a high-probability CDN. This study characterizes the 50[~]150 CDNs identifiable for each cancer type of TCGA (while anticipating 10 times more undiscovered ones) as follows: i) CDNs tend to code for amino acids of divergent chemical properties. ii) At the genic level, far more CDNs (>5-fold) fall on non-canonical than canonical cancer driving genes (CDGs). Most undiscovered CDNs are expected to be on unknown CDGs. iii) CDNs tend to be more widely shared among cancer types than canonical CDGs, mainly because of the higher resolution at the nucleotide than the whole-gene level. iv) Most important, among the 50[~]100 coding region mutations carried by a cancer patient, 5[~]8 CDNs are expected but only 0[~]2 CDNs have been identified at present. This low level of identification has hampered functional test and gene targeted therapy. We show that, by expanding the sample size to 105, most CDNs can be identified. Full CDN identification will then facilitate the design of patient-specific targeting against multiple CDN-harboring genes.

evolutionary biology↗

Genetic regulation of lncRNA expression in the whole human brain

Long non-coding RNAs (lncRNAs) play a key role in the human brain, and genetic variants regulate their expression. Herein, the expression quantitative trait loci (eQTL) of lncRNAs encompassing ten brain regions from 134 individuals was analyzed, and novel variants influencing lncRNA expression (eSNPs) and the respective affected lncRNAs (elncRNAs) were identified. The eSNPs are proximate to their corresponding elncRNAs, enriched in the non-coding genome, and have a high minor allele frequency. The elncRNAs exhibit a high-level and complex pattern of expression. The genetic regulation is more tissue-specific for lncRNAs than for protein-coding genes, with notable differences between cerebrum and cerebellum. However, it shows relatively similar patterns across the cortex regions. Furthermore, we observed a significant enrichment of eSNPs among variants associated with neurological disorders, especially insomnia, and identified insomnia-related lncRNAs involved in immune response functions. Moreover, the present study offers an improved tool for lncRNA quantification, a novel approach for lncRNA function analysis, and a database of lncRNA expression regulation in the human brain. These findings and resources will advance the research on non-coding gene expression regulation in neuroscience.

bioinformatics↗