Biology subjects

Zhang, L.

Publications and source records attributed to Zhang, L..

At least 505 records · Page 28Linked to original sources

bioRxiv2025

Pluripotent stem cell-derived NK progenitor cell therapy prevents tumour occurrence and eradicates minimal residual disease

The lack of persistence and short-term efficacy presents a major challenge for CAR-NK cell therapy. Here, we addressed this issue by developing pluripotent stem cell-derived NK lineage-committed progenitor (iNKP) cell therapy. For the first time, we generated abundant iNKP cells via an organoid culture system. The iNKP cells, engineered to express CXCR4 and chimeric antigen receptors (CAR), efficiently migrated to the bone marrow and generated CAR-iNK cells persisting in peripheral blood (PB) for over 80 days. Notably, CAR-iNKP cell therapy durably protected animals from tumour occurrence. Furthermore, a single low-dose infusion of CAR-iNKP cells following conventional chemotherapy eradicated minimal residual disease (MRD), leading to long-term complete remission. Our findings present a novel strategy to overcome the limitations of traditional CAR-NK cell therapy and offer dural breakthroughs for the prevention of tumour occurrence and relapse.

cancer biology↗

bioRxiv2025

Discovery of Expression-Governing Residues in Proteins

Understanding how amino acids influence protein expression is crucial for advancements in biotechnology and synthetic biology. In this study, we introduce Venus-TIGER, a deep learning model designed to accurately identify amino acids critical for expression. By constructing a two-dimensional matrix that links model representations to experimental fitness, Venus-TIGER achieves improved predictive accuracy and enhanced extrapolation capability. We validated our approach on both public deep mutational scanning datasets and low-throughput experimental datasets, demonstrating notable performance compared to traditional methods. Venus-TIGER exhibits robust trans-ferability in zero-shot predicting scenarios and enhanced predictive performance in few-shot learning, even with limited experimental data. This capability is particularly valuable for protein design aimed at enhancing expression, where generating large datasets can be costly and time-consuming. Additionally, we conducted a statistical analysis to identify expression-associated features, such as sequence and structural preferences, distinguishing between those linked to high and low expression. Our investigation also revealed a correlation among stability, activity and expression, providing insight into their interconnected roles and underlying mechanisms.

bioengineering↗

bioRxiv2024

Single-cell RNA sequencing analysis reveals new insights for intersex gonad initiation and early sex differentiation of goats

Polled intersex syndrome in goats severely impacts productivity and economic benefits, serving as a potential model for human reproductive defects. However, its specific molecular and cellular regulatory mechanisms remain unclear. This study combined single-cell RNA-sequencing (scRNA-seq) with tissue morphology and immunofluorescence detection to investigate the cellular heterogeneity, pseudo-time differentiation trajectory, differentially expressed genes, and regulatory networks of female, intersex, and male gonads during the 55-65 days embryonic stage of goats. The results indicated significant heterogeneity and cell fate transition in the somatic and germ cells of female, intersex, and male gonads at different developmental stages. Stromal cells may initiate female and intersexual gonad development, and epithelial cells may be the source of gonad cells in male fetuses. The abnormal expression of FOXL2, SOX9, AMH, DMRT1, RSPO1, INSL3, TCF21 and CSF1R may cause female-to-male sex reversal. The new candidate genes like PHLDB2, ZNRF3 and TEAD1 may contribute to the gender differentiation. Additionally, TREM2+ macrophages analogous to those in humans were identified in male gonads, while genes such as CSF1R and TYROBP potentially regulate macrophage immune privilege mechanisms. Early gonadal development in goats may also be regulated by circadian rhythm mechanisms similar to humans, with genes such as NR1D1, LGR4, and ATG5 involved in granulosa cell development, while genes such as ATG5, NRIP1, and FBXW11 may affect intersex trait development. In general, this study provided an important reference for exploring molecular and cellular mechanisms of intersex initiation during early embryonic development in goats and also for modelling human reproductive defects. Author summaryIn this study, we investigated the cell fate trajectory and key gene expression profile of goat fetus gonads using scRNA-seq. The analysis revealed cellular heterogeneity among normal male, normal female, and intersex gonadal somatic and germ cells, alongside their dynamic fate transitions across various developmental states. Pseudo-time trajectory analysis suggested that stromal cells might act as the initiation signal for female and intersexual gonad development, while epithelial cells could serve as the primary source of gonadal cells in male fetal goats. GO functional enrichment and KEGG analyses confirmed that abnormal expression of FOXL2, SOX9, AMH, DMRT1 and RSPO1 was linked to the emergence of intersexual gonads. Newly identified candidate genes including LRP2, PITX2, ARX, LHX9, PHLDB2, ZNRF3 and TEAD1 may contribute to sex-specific differences, while INSL3 and TCF21 could be linked to intersexual gonads. We identified TREM2+ macrophages analogous to those in humans, which could regulate immune privilege mechanisms. Circadian rhythmic changes were observed during early goat gonadal development.

developmental biology↗

bioRxiv2024

Geometry-based BERT: an experimentally validated deep learning model for molecular property prediction in drug discovery

Various deep learning based methods have significantly impacted the realm of drug discovery. The development of deep learning methods for identifying novel structural types of active compounds has become an urgent challenge. In this paper, we introduce a self-supervised representation learning framework, i.e., GEO-BERT. GEO-BERT considers the information of atoms and chemical bonds in chemical structures as the input, and integrates the positional information of the three-dimensional conformation of the molecule for training. Specifically, GEO-BERT enhances its ability to characterize molecular structures by introducing three different positional relationships: atom-atom, bond-bond, and atom-bond. By benchmarking study, GEO-BERT has demonstrated optimal performance on multiple benchmarks. We also performed prospective study to validate the GEO-BERT model, with screening for DYRK1A inhibitors as a case. Two potent and novel DYRK1A inhibitors (IC50: <1 M) were ultimately discovered at a hit rate of 10%. Taken together, we have developed the Geometry-based BERT model for molecular property prediction and proved its practical utility in early-stage drug discovery. Graphical Abstract GEO-BERT is a model pretrained on large-scale drug molecule data, while improving the accuracy of property prediction by using three-dimensional structural information within the molecule. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/630211v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1e9bc54org.highwire.dtl.DTLVardef@4b6832org.highwire.dtl.DTLVardef@a5d8eeorg.highwire.dtl.DTLVardef@44f7be_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2024

A biocatalytic platform for the production of substituted 2-quinolones and (thio)coumarins

2-quinolones are privileged scaffolds for drug discovery that are relatively rare in nature. Here, we characterise two promiscuous fungal polyketide synthases AthePKS and FerePKS, which we had previously found to produce quinolones in vitro. We challenged the enzymes with several substituted anthranilic acid derivatives, revealing their ability to produce precursors of pharmaceutically relevant quinolones. We also discovered that AthePKS and FerePKS accept other 2-substituted benzoic acids, leading to the formation of coumarin and thiocoumarin scaffolds. We applied AthePKS in an artificial enzymatic cascade towards an antimicrobial 4-methoxy-1-methyl-2-quinolone and demonstrated its in vivo feasibility by successfully expressing the pathway in Escherichia coli. Lastly, we determined the crystal structure of AthePKS, suggesting hotspots for enhancing its catalytic efficiency by enzyme engineering. Our results provide a framework for further engineering of enzymatic routes towards privileged heteroaromatic scaffolds and derivatives thereof.

biochemistry↗

bioRxiv2024

A Comprehensive Assessment of Methylation-Based Age Prediction Methods

DNA methylation (DNAm) clock is widely used to measure biological age, helping to identify key biomarkers associated with aging, infer the progression of aging, and have promise for elucidating, delaying, or even reversing aging. During the past decade, a large number of epigenetic clocks have been developed. However, they are decentralized, with applicable scopes overlapping. We benchmark 15 of these methods on 142 Illumina DNAm array datasets in five criteria and analyze the biological significance of CPGs about aging and overlapping. There are many exciting commons in models performance. We found the optimal model closely related to the numbers and characteristics of the training data. We provided a comprehensive assessment process to guide DNAm clock research at (https://dnamclock.com), the corresponding data and evaluation pipeline are freely available (https://github.comyNENUBioCompute/MethylationEvaluation), this study will aid in the development of improved tools designed to analyze increasingly large DNAm datasets.

bioinformatics↗

bioRxiv2024

Unveiling unique metabolomic and transcriptomic profiles in three Brassicaceae crops

Brassica napus, Camelina sativa and field pennycress (Thlaspi arvense), represent one highly economically valuable crop and two emerging oilseed crops of the Brassicaceae family, respectively. As sessile organisms, these crops are continuously exposed to various stresses when grown in the field. Interestingly, the responses of these three crops to different environmental stimuli vary to a great extent, but there is very limited knowledge about the molecular basis of these differential responses. In this study, we employed untargeted metabolomics to compare the metabolic profile of these crops, and examined the potentially related genes through further integration with transcriptomic analysis. Our data revealed distinctive overall metabolic profiles among these three crops, where in particular, a variety of phenylpropanoids showed differential accumulation and the corresponding putative genes expression varied significantly. The results provide a valuable resource for those studying Brassicaceae species and will provide insight into the understanding of metabolic variation among these three important oilseed crops, and provide potential targets for the future breeding of stress tolerant crops.

plant biology↗

bioRxiv2024

A molecularly defined brain circuit module for regulating the panic-like defensive state

Panic is an episode of strong defensive state, characterized by intense fear and severe physical symptoms such as elevated cardiorespiratory activities. How the brain generates panic state remains poorly understood. Here, we developed a robot-based experimental paradigm to evoke panic-like defensive state in mice. When stimulated by the robot, the mice exhibited jumping escapes and elevated cardiorespiratory activities. With this paradigm, we identified Cbln2-expressing (Cbln2+) neurons in the posterior hypothalamic nucleus (PHN) as a key neuronal population essential for the induction of panic-like defensive state. Activation of Cbln2+ PHN neurons induced behavioral and physical symptoms of panic-like defensive state. These neurons were strongly activated by noxious mechanical stimuli and encode jumping escape vigor. They were synaptically innervated by anxiety-associated brain areas and provoked panic-like defensive state via their projection to the periaqueductal gray. Together, our results reveal a molecularly defined circuit module that regulates the panic-like defensive state in mice.

neuroscience↗

bioRxiv2024

Silicon-rhodamine-enabled Identification (SeeID) for Near-Infrared Light Controlled Proximity Labeling In Vitro and In Vivo

Advancement in fluorescence imaging techniques enables the study of protein dynamics and localization with unprecedented spatiotemporal resolution. However, current imaging tools are unable to elucidate dynamic protein interactomes underlying imaging observations. In contrast, proteomics tools such as proximity labeling enable the analysis of protein interactomes at a single time point but lack information about protein dynamics. We herein developed Silicon-rhodamine-enabled Identification (SeeID) for near-infrared light controlled proximity labeling that could bridge the gap between imaging and proximity labeling. SeeID was benchmarked through characterization of various organelle-specific proteomes and the KRAS protein interactome. The fluorogenic nature of SiR allows for intracellular proximity labeling with high subcellular specificity. Leveraging SiR as both a fluorophore and a photocatalyst, we developed a protocol that allows the study of dynamic protein interactomes of Parkin during mitophagy. We discovered the association of the proteasome complex with Parkin at early time points, indicating the involvement of the ubiquitin-proteasome system for protein degradation in the early phase of mitophagy. In addition, by virtue of the deep tissue penetration of near-infrared light, we achieved spatiotemporally controlled proximity labeling in vivo across the mouse brain cortex with a labeling depth of [~]2 mm using an off-the-shelf 660 nm LED light set-up.

molecular biology↗

bioRxiv2024

Incomplete lineage sorting of segmental duplications defines the human chromosome 2 fusion site early during African great ape speciation

All great apes differ karyotypically from humans due to the fusion of chromosomes 2a and 2b, resulting in human chromosome 2. Yet, the structure, function, and evolutionary history of the genomic regions associated with this fusion remain poorly understood. Here, we analyze finished telomere-to-telomere chromosomes in great apes and macaques to show that the fusion was associated with multiple pericentric inversions, segmental duplications (SDs), and the rapid turnover of subterminal repetitive DNA. We characterized the fusion site at single-base-pair resolution and identified three distinct SDs that originated more than 5 million years ago. These three distinct SDs were differentially distributed among African great apes as a result of incomplete lineage sorting (ILS) and lineage-specific duplication. Most conspicuously, one of these SDs shares homology to a hypomethylated SD spacer sequence present in hundreds of copies in the subterminal heterochromatin of chimpanzees and bonobos. The fusion in human was accompanied by a systematic degradation of the three divergent -satellite arrays representing the ancestral centromere creating five distinct structural haplotypes in humans. CRISPR/Cas9-mediated depletion of the fusion site in human cell lines significantly alters the expression of 108 genes, indicating a potential regulatory consequence to this human-specific karyotypic change.

evolutionary biology↗

bioRxiv2024

Exploring Genetic Interactions with Rare Variants Reveals Gene Networks Susceptible to Complex Diseases

Genetic interactions play a crucial role in understanding the susceptibility and etiology of complex human diseases. However, existing methods for analyzing gene-gene interactions are often limited to common variants and may not capture the effects of rare variants. In this study, we propose a novel method called GGI-RUNNER that is specifically designed for analyzing gene-gene interactions of rare variants. GGI-RUNNER evaluates the enrichment of rare variant interaction burden in patients relative to baselines in the general population. The baselines are estimated for pairwise genes by a recursive truncated negative-binomial regression model on multiple genomic features available from public data. Intensive simulations demonstrate that GGI-RUNNER exhibits substantially higher statistical power than alternative epistasis tests and maintains reasonable type I error rates even in stratified populations. Applied to real data, GGI-RUNNER identified significant rare variant interactions associated with Alzheimers disease, Hirschsprungs disease, Ulcerative colitis and Crohns disease. Furthermore, we found that these identified genes for each trait can form interconnected networks, which may provide valuable insights into the underlying molecular mechanisms.

bioinformatics↗

bioRxiv2024

Modulating Prestimulus Alpha and Beta Power with tRNS Establishes Their Causal Role in Visual Perception

Variability in visual perception in response to consistent stimuli is a fundamental phenomenon linked to fluctuations in prestimulus low-frequency neural oscillations--particularly in the alpha (8-13 Hz) and beta (13-30 Hz) bands--typically measured by their power in electroencephalography (EEG) signals. However, the causal role of these prestimulus alpha and beta power fluctuations in visual perception remains unestablished. In this study, we investigated whether prestimulus alpha and beta power causally affect visual perception using transcranial random noise stimulation (tRNS). In a sham-controlled, single-blind, within-subject design, 29 participants performed a visual detection task while receiving occipital tRNS. Online functional near-infrared spectroscopy (fNIRS) was used to measure cortical excitability during stimulation, and offline EEG signals were collected after stimulation. Mental fatigue was incorporated as a state-dependent factor influencing tRNS effects. Our findings demonstrate that, primarily under low fatigue states, tRNS increased cortical excitability during stimulation (indicated by increased fNIRS oxyhemoglobin amplitude), decreased subsequent prestimulus EEG alpha and beta power, and consequently reduced the visual contrast threshold (VCT), indicating enhanced visual perception. Sensitivity analysis revealed that alpha oscillations contributed more significantly to visual perception than beta oscillations under low fatigue. Additionally, the state-dependent effects of tRNS may result from different sensitivities of VCT to neural oscillations across fatigue states. These results provide causal evidence linking prestimulus alpha and beta power to visual perception and underscore the importance of considering brain states in neuromodulation research. Our study advances the understanding of the neural mechanisms underlying visual perception and suggests potential therapeutic applications targeting neural oscillations. Significance statementUnderstanding why we perceive identical visual stimuli differently is a fundamental question in neuroscience. This study provides causal evidence that prestimulus alpha and beta neural oscillations directly influence visual perception, particularly under low mental fatigue state. By using tRNS alongside fNIRS and EEG recordings, we demonstrate that modulating neural excitability can alter perceptual outcomes. Our findings highlight the importance of considering brain state--such as fatigue levels--in neuromodulation research. This work advances our understanding of the neural mechanisms underlying visual perception and opens avenues for developing targeted interventions to enhance sensory processing and cognitive functions, potentially benefiting individuals with perceptual or attentional disorders.

neuroscience↗

bioRxiv2024

Within-Family GWAS does not Ameliorate the Decline in Prediction Accuracy across Populations

As polygenic prediction extends beyond the research domain to involve clinical applications, the urgency of solving the "portability problem" becomes amplified--that is, the fact that polygenic indices (PGI) constructed based on discovery analysis in one population (typically of exclusively continental European descent) predict poorly in other populations. In the present paper we test whether population differences in genetic nurture, assortative mating, or population stratification contribute to the fact that polygenic indices constructed based on GWAS results from European-descent samples predict more poorly in admixed populations with Native American and African ancestry. We do this by comparing the rates of decline in prediction accuracy of classical-GWAS-based PGIs versus within-family-based PGIs, each estimated in a population of European descent, as they are deployed in two samples of Latino Americans and African Americans. Within-family GWAS putatively eliminates the effects of parental genetic nurture, assortative mating, and population stratification; thus, we can determine whether without those confounding factors in the PGI construction, the relative prediction accuracy in the out-groups is ameliorated. Results show that relative prediction accuracy is not improved, suggesting that the differences across groups can be almost entirely explained by variation in genetic architecture (i.e. allele frequencies and short-range LD) rather than the aforementioned factors. Additional analysis of the impact of genetic architecture on the decline in prediction accuracy supports this conclusion. Future researchers should test within-family analysis at the prediction rather than the discovery stage.

genomics↗

bioRxiv2024

Effect of OASL on OXA-induced immunogenic cell death in gastric cancer via cGAS-STING pathway

This study investigates the role of 2-5 oligoadenylate synthetase-like (OASL) in Oxaliplatin (OXA)-induced immunogenic cell death (ICD) in Gastric cancer (GC) cells through the cGAS-STING signaling pathway. Knockdown of OASL enhanced ICD expression, while overexpression had the opposite effect. RNA sequencing of OASL-knockdown and control GC cells treated with OXA revealed significant enrichment of the second messenger signaling pathway (cGAMP). cGAMP could directly activate STING as a second messenger, and cGAS was a key synthetic enzyme upstream of cGAMP. Next, the role of OASL in OXA-induced ICD in GC cells was validated through the cGAS-STING signaling pathway. The Co-IP and immunofluorescence results confirmed that the OASL and cGAS proteins can bind directly. Further research validated these findings in vivo. Results show that OASL regulates OXA-induced ICD in GC cells via the cGAS-STING pathway, impacting chemosensitivity. The findings suggest new targets and strategies for improving GC therapy by modulating OASL expression to enhance OXA sensitivity through immunogenic mechanisms.

cancer biology↗

bioRxiv2024

Single-nucleus RNA sequencing of human periventricular white matter in vascular dementia

Vascular dementia (VaD) refers to a variety of dementias driven by cerebrovascular disease and is the second leading cause of dementia globally. VaD may be caused by ischemic strokes, intracerebral hemorrhage, and/or cerebral small vessel disease, commonly identified as white matter hyperintensities on MRI. The mechanisms underlying these white matter lesions in the periventricular brain are poorly understood. In this study we perform an extensive transcriptomic analysis on human postmortem periventricular white matter lesions in patients with VaD with the goal of identifying molecular pathways in the disease. We find increased cellular stress responses in astrocytes, oligodendrocytes, and oligodendrocyte precursor cells as well as transcriptional and translational repression in microglia in our dataset. We show that several genes identified by GWAS as being associated with white matter disease are differentially expressed in cells in VaD. Finally, we compare our dataset to an independent snRNAseq dataset of PVWM in VaD and a scRNAseq dataset on human iPSC-derived microglia exposed to oxygen glucose deprivation (OGD). We identify the increase of the heat shock protein response as a conserved feature of VaD across celltypes and show that this increase is not linked to OGD exposure. Overall, our study is the first to show that increased heat shock protein responses are a common feature of lesioned PVWM in VaD and may represent a potential therapeutic target.

neuroscience↗

bioRxiv2024

Prediabetes Phenotype Clusters in the Diabetes Prevention Program Study

ObjectiveThe purpose of this study was to apply clustering methods to identify and characterize prediabetes phenotypes and their relationships with treatment arm and type 2 diabetes (T2D) outcomes in the Diabetes Prevention Program (DPP), and to compare the utility of additional clustering measures in phenotype characterization and T2D risk stratification. Research Design and MethodsThis was a secondary analysis of data from a subset of participants (n=994) from the previously completed Diabetes Prevention Program trial. Unsupervised k-means clustering analysis was applied to derive the optimal number of clusters of participants based on common clinical risk factors alone or common risk factors plus more comprehensive measures of glucose tolerance and body composition. ResultsFive clusters were derived from common clinical characteristics and the addition of comprehensive measures of glucose tolerance and body composition. Within each modeling approach, participants show significantly different levels of risk factors. The clinical only model showed higher accuracy for time to T2D, however the more comprehensive models further differentiated a metabolically health overweight phenotype. For both models, the greatest differentiation in determining time to T2D was in the metformin arm of the trial. ConclusionsData driven clustering of patients with prediabetes allows for identification of prediabetes phenotypes at greater risk for disease progression and responses to risk reduction interventions. Further investigation into phenotypic differences in treatment response could enable better personalization of prediabetes and T2D prevention and treatment choices.

genomics↗

bioRxiv2024

PTTG1-Mediated Pericyte Dysfunction Drives Diabetes-Induced Microvascular Dysfunction

BackgroundPericytes are crucial for the development, stabilization, and functional regulation of microvasculature, especially in the retina. In diabetic retinopathy (DR), early loss of pericytes is a key event that drives microvascular dysfunction. Despite their critical role, the mechanisms underlying the functional heterogeneity of pericytes in DR remain poorly understood, impeding the development of effective therapeutic strategies. MethodsWe employed single-cell RNA sequencing to construct a comprehensive single- cell atlas of non-diabetic and diabetic retinas. Using bioinformatic clustering and subcluster analysis, we identified a specific pericyte subcluster associated with diabetic microvascular complications. Differential gene expression analysis and immunofluorescence validation highlighted PTTG1 as a potential key regulator of pericyte dysfunction. To investigate its functional role, we emplyed CRISPR/Cas9 and adenoviral vectors to modulate PTTG1 expression in vitro and in vivo. Combined transcriptomic and metabolomic approaches were used to explore the mechanistic pathways through which PTTG1 influences pericyte biology and vascular function. ResultsWe identified a novel pericyte subcluster characterized by elevated expression of PTTG1, which was strongly correlated with diabetic microvascular dysfunction. Silencing PTTG1 using CRISPR/Cas9 and siRNA in vitro mitigated pericyte dysfunction under high- glucose conditions. Targeted knockdown of PTTG1 using viral vectors improved retinal vascular integrity and reduced neovascularization in diabetic mice. Transcriptomic and untargeted metabolomic analyses revealed that PTTG1 knockdown reprogrammed pericyte energy metabolism by modulating glycolysis pathway genes, reducing oxidative stress, and restoring pericyte function, ultimately alleviating microvascular dysfunction in DR. ConclusionsPTTG1 plays a critical role in regulating pericyte dysfunction and maintaining vascular homeostasis in diabetic retinopathy. By modulating key metabolic pathways and pericyte phenotypes, PTTG1 represents a promising therapeutic target for treating diabetic microvascular complications. These insights offer a novel molecular framework for developing targeted therapies aimed at restoring retinal vascular health in diabetic patients.

molecular biology↗

bioRxiv2024

Temporal Configuration as a New Feature of Sound: Psychological and Neurophysiological Evidence, Cross-species Consistency and Underlying Neuronal Mechanisms

Natural sounds are defined not only by their spectral content but also by their fine temporal structure. Here we show that millisecond-scale temporal configuration--defined by the ordering of inter-click intervals (ICIs) within a click train--behaves as a distinct auditory feature, conserved across species and emerging hierarchically along the auditory pathway. Human listeners reliably discriminated click trains that shared the same average ICI but differed in temporal configuration, and these differences elicited robust mismatch negativity (MMN) responses in an oddball paradigm, indicating automatic cortical deviance detection. Awake rats showed analogous MMN-like ECoG responses to configuration changes, demonstrating cross-species generality. Neuropixels recordings along the inferior colliculus-medial geniculate body-primary auditory cortex (IC-MGB-A1) axis revealed minimal configuration sensitivity in IC, intermediate sensitivity in MGB, and strong stimulus-specific adaptation to temporal configuration in A1. Reversible cooling of auditory cortex reduced configuration sensitivity in MGB, implicating corticothalamic feedback in shaping thalamic representations. Layer-resolved analyses further showed that supragranular A1 neurons carry stronger configuration-specific adaptation than infragranular neurons. These findings identify temporal configuration as a feature-like dimension of sound and delineate a hierarchical, feedback-dependent IC-MGB-A1 circuit architecture for encoding fine temporal structure in the mammalian brain.

neuroscience↗