Biology subjects

Hou, M.

Publications and source records attributed to Hou, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Different hippocampal subfield volumes predict source memory performance and general cognitive ability in an adult lifespan sample

Modest positive associations between episodic memory performance and whole hippocampal and hippocampal subfield volumes have been reported in numerous prior studies. A smaller number of studies have reported associations between hippocampal volume and performance on tests of non-mnemonic cognition. The present study examined whether these associations were evident in a lifespan sample of cognitively healthy adults. Of particular interest was whether any identified associations were sensitive to age, and whether associations between subfield volumes and mnemonic and non-mnemonic performance were subfield dependent. We acquired high-resolution T1- and T2-weighted structural images from 163 adults (18-87 years of age). Participants also undertook a comprehensive neuropsychological test battery and an in-scanner test of source memory. Principal components analysis was employed to reduce the neuropsychological test scores to 5 cognitive components. Two components reflected memory performance while the other three reflected different aspects of non-mnemonic cognition. Hippocampal subfields (Cornu Ammonis (CA)1, CA2-3, dentate gyrus (DG) and subiculum) were segmented and measured with the Automated Segmentation of Hippocampus Subfields (ASHS) package. Source memory performance was selectively associated across participants with CA2-3 volume. By contrast, both mnemonic and non-mnemonic component scores derived from the test battery were associated exclusively with the volume of the DG. All associations were age-invariant. The findings indicate that different cognitive domains can be dissociated by virtue of their associations with different hippocampal subfields. Of importance, these associations appear to be life-long and hence are unlikely to reflect individual differences in age-related decline in structural integrity.

neuroscience↗

bioRxiv2026

MG2Act: A Mechanism-Inspired Sequential Attention Framework for Molecular Glue Degradation Prediction

Molecular glue degraders act by inducing productive proximity between an E3 ligase and a substrate protein. For most characterized degradative glues, a small molecule first engages the E3, conditions its substrate-recognition surface, and only then enables recruitment of a compatible neo-substrate. This directionality is rarely encoded explicitly in computational models, which typically fuse molecule, E3 and target representations simultaneously. We present MG2Act, a structure-independent framework that translates this two-step logic into sequential cross-attention, using CRBN-mediated degradation as the most data-rich representative system. Starting from a curated continuous-valued benchmark of 1,207 pairs across 47 targets, a refined subset of 1,159 pairs was selected to train MG2Act after excluding rare targets. On identical processed data, MG2Act consistently outperforms machine learning baselines, robustly generalizes under strict redundancy-filtering, and responds coherently to mechanism-based perturbations. Prospective screening and zero-shot target-conditioned prioritization identified nanomolar degraders of IKZF1, CK1 and CDK4, including the non-classical IMiD-core CDK4 degrader SWC-202.

bioinformatics↗

bioRxiv2026

Targeting folate-dependent purine synthesis sensitizes melanoma cells to immune attack through suppressing glycolysis

Cytotoxic T lymphocytes (CTLs) play a central role in antitumor immunity; however, metabolic reprogramming within the tumor microenvironment often compromises their effector function, making metabolic targeting crucial for the improvement of T cell function. Folate-dependent purine synthesis, a core pathway sustaining the nucleotide pool, is highly activated in tumors, yet its role in regulating tumor immune sensitivity remains unclear. Here, by establishing a co-culture system of melanoma cells and human T Cell Receptor (TCR)-engineered T cells, we systematically evaluated the effects of folate-dependent purine synthesis inhibitors on tumor cell response to CD8+ T cell cytotoxicity. We found that inhibition of key enzymes such as methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) and glycinamide ribonucleotide transformylase (GART) markedly enhanced tumor cell sensitivity to T cell killing, an effect also observed with exogenous nucleoside supplementation. Mechanistically, inhibition of folate-dependent purine synthesis suppresses glycolysis by downregulating critical glycolytic enzymes, thereby reducing lactate production. Reduction in lactate further weakens lactylation and stability of the immune checkpoint protein PD-L1. In parallel, impaired purine synthesis disrupts uridine metabolism, blocks ribose salvage, and distally influences glycolysis. Collectively, our study identified the folate-dependent purine synthesis - glycolysis axis as key regulator of tumor immune response and highlights metabolic targeting as a promising strategy to improve cancer immunotherapy.

cancer biology↗

bioRxiv2026

Ciz1 safeguards Drosophila wing development by suppressing oxidative stress

Cell proliferation and fate specification are fundamental processes that ensure the generation of organs with proper size and patterning. Oxidative stress caused by accumulation of reactive oxygen species (ROS) can lead to cell cycle arrest, senescence, cell death and cell fate misspecification, thereby impairing normal development and contributing to many pathological processes. In this study, we identify Drosophila Ciz1 as a critical factor that safeguards epithelial homeostasis and development by preventing oxidative stress. Knockdown of Ciz1 in the Drosophila wing imaginal disc, an epithelial tissue that serves as the larval precursor of the adult wing, results in a small wing phenotype accompanied by thickened and ectopic veins. We further demonstrate that reduced Ciz1 expression leads to accumulation of donut-shaped mitochondria and elevated ROS levels. The increased oxidative stress subsequently suppresses proliferation via activation of JNK and promotes excessive vein formation by upregulating Rhomboid, a positive regulator of EGFR signaling. Interestingly, although Ciz1 is a zinc finger protein that predominantly localizes to the nucleus, neither its zinc finger motifs nor its nuclear localization is required for suppression of oxidative stress. Instead, the prion-like domain in its N-terminal part is essential for this activity. Our work identifies Ciz1 as an important factor in preventing oxidative stress and maintaining epithelial homeostasis.

Developmental Biology↗

bioRxiv2026

Engineering Cybergenetic Cell-Based Therapies

Adaptive, closed-loop control of cellular behavior is essential for next-generation therapies, yet most current treatments operate in an open-loop manner and lack robustness to patient variability and disease dynamics. Here, we establish a controltheoretic platform for rational engineering of closed-loop cell-based therapies that achieve precise and robust regulation. First, we introduce multi-dimensional nullgram profiling, a high-throughput approach that enables quantitative prediction and design of advanced genetic controllers in human cells across circuit topologies and parameter regimes in a single experiment. To evaluate dynamic therapeutic behavior, we next develop Cyberpatient-in-the-loop, an optogenetic digital twin platform that interfaces engineered mammalian cells with computational disease models, enabling systematic testing of closed-loop performance under realistic perturbations. Finally, we leverage these approaches to implement integral feedback cell therapies that sense inflammatory signals and autonomously regulate cytokine levels in primary immune cell cultures. Together, these results establish a general paradigm for engineering cellbased control systems and provide a foundation for next-generation cell therapies.

synthetic biology↗

bioRxiv2025

Cross-sectional association study from NHANES between some dietary supplements and anti-HAV antibodies

Background/Objectivesdietary supplements intake is known for its importance in preserving immune system and immune response but we need to estimate if there were direct cross-sectional association between some dietary supplements use 24-hours and anti-HAV antibodies or not. Methodsdata merged from three NHANES three cycles along (2013-2018) were analyzed, representing 29.400 participants across all ages. The data collected were subjected to a logistic regression analysis to assess the relationship between the reported frequency of infections and dietary nutrients consumed including minerals and some vitamins. Resultsthe results in overall verified no significant association between investigated dietary supplements use 24-hours and anti-HAV antibodies. However, vitamin D (p = 0.004) showed a significant positive association. Conclusionsthere were true direct association revealed of vitamin D on anti-HAV antibodies.

immunology↗

bioRxiv2025

Retrieval-related eye movements are predictive of memory precision

Eye movements are predictive of successful episodic memory encoding and retrieval, but it is unclear whether they reflect the precision of retrieved memory content. Here, we examined relationships between eye fixations, memory precision and fMRI BOLD activity. At study, participants were presented with object images, each placed at a random location on an invisible circle. At test, both studied and new images were presented. Participants were instructed to make a covert recognition memory judgment to each image, recall and then signal its studied location, guessing if necessary. Simultaneous fMRI and eye-tracking data were acquired during the test phase. For correctly recognized images, the trial-wise angular distance between the studied and reported locations was fitted to a two-component mixture model. Based on the model-derived parameters, correctly recognized images were categorized as those associated with successful location retrieval (location hits) or guesses. Location hits were further divided into high- and low precision trials. At retrieval, fixations predicted both successful retrieval and the precision of the retrieved location memory. Additionally, across-trial fixation patterns were more similar for location hits than for guesses, and for high- than for low-precision trials. The association between retrieval success and eye fixation precision was evident across almost the entire recall phase, whereas memory precision effects emerged around 1-1.5s after image onset. Fixation precision and fixation pattern similarity each predicted trial-wise memory precision independently of hippocampal BOLD activity, which also predicted precision. These findings suggest that eye fixations during retrieval track the fidelity of mnemonic content.

neuroscience↗

bioRxiv2025

ProSiteHunter: A unified framework for sequence-based prediction of protein-nucleic acid and protein-protein binding sites

Accurate prediction of protein binding sites is essential for elucidating protein function, understanding molecular interaction mechanisms, and facilitating drug design. However, existing sequence-based approaches are often designed for specific binding-site types and therefore lack generality, whereas structure-based methods typically rely on high-quality structural models, limiting their applicability. Here, we introduce ProSiteHunter, a unified sequence-based framework for protein binding-site prediction, which integrates a fine-tuned protein language model (SiteT5) with a multi-source feature-fusion network that incorporates evolutionary, geometric, and statistical features, while employing bidirectional semantics, local associations, and global dependencies for comprehensive binding-site characterization. The method was systematically evaluated on diverse binding sites prediction tasks, where ProSiteHunter achieved a 39.1% average improvement in PRAUC for protein-DNA/RNA/protein tasks and a 7.4% PRAUC enhancement on the particularly challenging antibody-antigen task over state-of-the-art methods. Moreover, ProSiteHunter is capable of identifying local flexible sites that complement AlphaFold3 predictions and improving the accuracy of antibody-antigen interaction prediction. These results highlight ProSiteHunter as an efficient and unified approach for accurate and robust prediction of diverse protein binding sites.

bioinformatics↗

bioRxiv2025

Genomic Evidence for Males of Exceptional Reproductive Output (ERO) in Apes and Humans

It is widely suspected that a small percentage of males have exceptional reproductive output (ERO) but progeny numbers of males are rarely measurable, even in humans. If we define the variance ratio of reproductive-output in males and females as = VM/VF, the ERO hypothesis would predict >>1. Since autosomal, X, and Y chromosomes are found in males 1/2, 1/3, and 100% of the time, their DNA diversities can inform about . For example, autosomal and Y-linked diversities are governed, respectively, by (VM+VF)/2 and VM. When comparing the chromosomal diversities, appears to be near 20 for chimpanzees and orangutans, and 1-10 for gorillas. The exception is bonobos with < 1. In humans, the extensive genomic data are coupled to a theory, developed herein, that can filter out selection influences on Y-linked diversities. Hence, the estimation of is rigorous, yielding values near or above 20, depending on the population. When >10, the presence of ERO males is very likely. These analyses can be applied more generally to species with XY sex determination.

evolutionary biology↗

bioRxiv2025

fMRI BOLD signals in the left angular gyrus and hippocampus are associated with memory precision

Prior functional magnetic resonance (fMRI) studies examining the neural correlates of retrieval success and precision have reported inconsistent results. Here, we examined the neural correlates of success and precision in a test of memory for spatial location. The present study extended prior findings by employing an experimental design that minimized temporal overlap between mnemonic and visuomotor processing. At study, participants viewed a series of object images, each placed at a randomly selected location on an imaginary circle. At test, studied images were intermixed with new images and presented to the participants. The requirement was to make a covert recognition memory judgment to each image and to attempt to recall its studied location, guessing if necessary. A cue signaling the requirement to make a location memory judgment was presented 4 seconds after image onset. Memory precision was quantified as the angular difference between the studied location and the location selected by the participant. In an analysis that combined the data from the present study and a closely similar prior study, we replicated prior reports that fMRI BOLD activity in the left angular gyrus (AG) and the hippocampus tracks memory precision on a trial-wise basis. Linear mixed effects modeling indicated that the activity in the two regions explained independent sources of variability in these judgments. In addition, multivoxel pattern similarity analysis revealed robust evidence for an item-level reinstatement effect (as indexed by encoding-retrieval overlap) in the left AG that was restricted to items associated with high precision judgments. These findings suggest that the hippocampus and the left AG play non-redundant roles in the retrieval and behavioral expression of high precision episodic memories.

neuroscience↗

bioRxiv2025

A Single-cell and Spatially Resolved Cell Atlas of Human Esophageal Squamous Cell Carcinoma

Tumor heterogeneity and the suppressive microenvironment are key challenges that limit the effectiveness of cancer treatment. In this study, we systematically elucidated the molecular characteristics and mechanisms underlying the suppressive immune microenvironment via a combination of single-cell RNA sequencing, spatial transcriptomics, and metabolomics for a series of human esophageal squamous cell carcinoma (ESCC) and matched nontumor tissues. We found that COL17A1+ epithelial cells presented greater malignancy, characterized by triglyceride (TG) and phosphocholine (PC) accumulation. We also identified a tumor-specific POSTN+ fibroblast subgroup. We found a unique epithelial-fibroblast niche with low infiltration of effector immune cells and substantial enrichment of lipids, composed of POSTN+ fibroblasts and COL17A1+ epithelial cells, where their crosstalk contributed to tumor progression. We confirmed that the INHBA/TP63 axis plays a key role in mediating the regulation of COL17A1+ tumor cells by POSTN+ fibroblasts. Our findings provided new insights into the characteristics of the tumor microenvironment and the crosstalk between tumor and fibroblasts, offering valuable multiomics data resources for elucidating tumor progression mechanisms.

genomics↗

bioRxiv2025

MultiSAAI: Sequence-informed Antibody-Antigen Interactions Prediction using Multi-scale Deep Learning

MotivationAntibodies possess high specificity toward target antigens, making them critical for therapeutic applications. However, experimental screening of antibody-antigen interactions is labor-intensive and costly. Existing structure-based computational methods often face significant challenges in modeling the dynamic conformational flexibility that governs antibody-antigen interactions, which limits their ability to accurately identify binding. Therefore, there is an urgent need for accurate and efficient sequence-based prediction method to accelerate antibody discovery and reduce experimental burden. ResultsWe propose MultiSAAI, a sequence-informed framework that models antibody-antigen interactions by explicitly accounting for the distinct roles of antibody heavy and light chains in antigen binding. MultiSAAI integrates language model embeddings, physicochemical properties, geometric constraints, and residue substitutability to characterize antibody-antigen interactions across multiple scales, employing a multi-scale network architecture that simultaneously evaluates global residue-pair compatibility and local amino acid fitness at the binding interface. Furthermore, the incorporation of site-specific information and biologically grounded binding principles allows the model to more closely reflect the actual mechanisms of interactions. Benchmark results demonstrate that MultiSAAI achieves AUROC scores of 0.757 on the generic antibody-antigen interactions dataset and 0.946 on the SARS-CoV-2 dataset, outperforming existing methods such as A2binder and AbAgIntPre. Finally, large-scale preliminary antibody screening further validates the potential of MultiSAAI for high-throughput therapeutic antibody discovery.

bioinformatics↗

bioRxiv2025

Synthesizing human-specific spike-in standards for RNA-seq experiments and assessing their technical performance

Using spike-in standards for RNA-seq experiments is critical to evaluate technical bias introduced during sample preparation, sequencing and analysis. Although some external RNA spike-in standards have been developed, species-specific spike-in standard was not reported yet. Here we developed the human-specific spike-in standards with 65 controls. We first extracted human endogenous RNAs with various lengths and GC contents, introduced random mutations approximately every 75 bp in each RNA, and then synthesized these RNAs as spike-in RNAs. After that, four mixtures of these spike-in RNAs covering a 220 dynamic range were obtained. To ensure the accuracy of RNA concentration, two rounds of ddPCR were conducted for each spike-in RNA and the intraclass correlation coefficient between two ddPCRs ranged from 0.9954 to 0.9971 after removing the two spike-in RNAs with the largest concentration difference. Furthermore, we showed that the sequencing error profiles were distinct between platforms and the library preparation procedures were related with the discrepancies in spike-in RNA read percent, transcript abundance, sequence coverage distribution, and differential gene expression. In addition, two regression models of sequence coverage were built based on RNA second structure and GC content, and 86.62%-91.78% of the variation can be explained. Our study demonstrates the technical performance of the human-specific spike-in standards for RNA-seq experiments and illustrates the biases across different libraries, platforms, and laboratories.

bioinformatics↗

bioRxiv2025

High-accuracy protein complex structure modeling based on sequence-derived structure complementarity

In living organisms, proteins perform key functions required for life activities by interacting to form complexes. Determining the protein complex structure is crucial for understanding and mastering biological functions. Although AlphaFold2 has made a revolutionary breakthrough in predicting protein monomeric structures, accurately capturing inter-chain interaction signals and modeling the structures of protein complexes remain a formidable challenge. In this work, we report DeepSCFold, a pipeline for improving protein complex structure modeling. DeepSCFold uses sequence-based deep learning models to predict protein-protein structural similarity and interaction probability, providing a foundation for identifying interaction partners and constructing deep paired multiple-sequence alignments (MSAs) for protein complex structure prediction. Benchmark results show that DeepSCFold significantly increases the accuracy of protein complex structure prediction compared with state-of-the-art methods. For multimer targets from CASP15, DeepSCFold achieves an improvement of 11.6% and 10.3% in TM-score compared to AlphaFold-Multimer and AlphaFold3, respectively. Furthermore, when applied to antibody-antigen complexes from the SAbDab database, DeepSCFold enhances the prediction success rate for antibody-antigen binding interfaces by 24.7% and 12.4% over AlphaFold-Multimer and AlphaFold3, respectively. These results demonstrate that DeepSCFold effectively captures intrinsic and conserved protein-protein interaction patterns through sequence-derived structure-aware information, rather than relying solely on sequence-level co-evolutionary signals.

bioinformatics↗

bioRxiv2024

DeepAssembly2: A Web Server for Protein Complex Structure Assembly Based on Domain-Domain Interactions

Proteins often perform biological functions by forming complexes, thereby accurately predicting the structure of protein complexes is crucial to understanding and mastering their functions, as well as facilitating drug discovery. Protein monomeric structure prediction has made a breakthrough in recent years, but the accurate prediction of complex structure remains a challenge. In this work, we present DeepAssembly2, a web server for automatically assembling protein complex structure based on domain-domain interactions. First, the features are constructed according to the input complex sequence and monomeric structures, then these features are used to predict the inter-chain residue distance through a deep learning model, and finally, the complex structure is assembled under the guidance of inter-chain residue distances. Compared with the previously developed version, DeepAssembly2 is trained on a newly constructed inter-chain domain-domain interaction dataset. Meanwhile, several important features have been added, such as Interface Residue Propensity and Ultrafast Shape Recognition. In addition, we introduced the inter-chain residue distance from the AlphaFold-Multimer model to further improve the accuracy. Finally, we also integrate our recently developed model quality assessment method to select the output models. The performance of DeepAssembly2 is significantly improved compared with the previous version, providing a solution for large protein complex structure modeling through divide-and-conquer assembly strategy, and is expected to provide new insights and an effective tool for drug development, vaccine design, etc. The web server of DeepAssembly2 is freely available at http://zhanglab-bioinf.com/DeepAssembly/.

bioinformatics↗

bioRxiv2024

Aberrant TSC-Rheb axis in Oxytocin receptor+ cells mediate stress-induced anxiety

Stress is a major risk for the onset of several maladaptive processes including pathological anxiety, a diffuse state of heightened apprehension over anticipated threats1. Pathological anxiety is prevalent in up to 59% of patients with Tuberous Sclerosis complex (TSC)2, a neurodevelopmental disorder (NDD) caused by loss-of-function mutations in genes for Tuberin (Tsc2) and/or Hamartin (Tsc1) that together comprise the eponymous protein complex. Here, we generated cell type-specific heterozygous knockout of Tsc2 in cells expressing oxytocin receptor (OTRCs) to model pathological anxiety-like behaviors observed in TSC patient population. The stress of prolonged social isolation induces a sustained negative affective state that precipitates behavioral avoidance, often by aberrant oxytocin signaling in the limbic forebrain3,4. In response to social isolation, there were striking sex differences in stress susceptibility in conditional heterozygote mice when encountering situations of approach-avoidance conflict. Socially isolated male mutants exhibited behavioral avoidance in anxiogenic environments and sought more social interaction for buffering of stress. In contrast, female mutants developed resilience during social isolation and approached anxiogenic environments, while devaluing social interaction. Systemic and medial prefrontal cortex (mPFC)-specific inhibition of downstream effector of TSC, the integrated stress response (ISR), rescued behavioral approach toward anxiogenic environments and conspecifics in male and female mutant mice respectively. Further, we found that Tsc2 deletion in OTRCs leads to OTR-signaling elicited network suppression, i.e., hypofrontality, in male mPFC, which is relieved by inhibiting the ISR. Our findings present evidence in support of a sexually dimorphic role of prefrontal OTRCs in regulating emotional responses in anxiogenic environments, which goes awry in TSC. Our work has broader implications for developing effective treatments for subtypes of anxiety disorders that are characterized by cell-autonomous ISR and prefrontal network suppression.

neuroscience↗

bioRxiv2024

Neural correlates of retrieval success and precision: an fMRI study

Prior studies examining the neural mechanisms underlying retrieval success and precision have yielded inconsistent results. Here, their neural correlates were examined using a memory task that assessed precision for spatial location. A sample of healthy young adults underwent fMRI scanning during a single study-test cycle. At study, participants viewed a series of object images, each placed at a randomly selected location on an imaginary circle. At test, studied images were intermixed with new images and presented to the participants. The requirement was to move a cursor to the location of the studied image, guessing if necessary. Participants then signaled whether the presented image as having been studied. Memory precision was quantified as the angle between the studied location and the location selected by the participant. A precision effect was evident in the left angular gyrus, where BOLD activity covaried across trials with location accuracy. Multi-voxel pattern analysis also revealed a significant item-level reinstatement effect for high-precision trials. There was no evidence of a retrieval success effect in the angular gyrus. BOLD activity in the hippocampus was insensitive to both success and precision. These findings are partially consistent with prior evidence that success and precision are dissociable features of memory retrieval.

neuroscience↗

bioRxiv2024

NK Cell Exhaustion in Wilson's Disease Revealed by Single-cell RNA Sequencing Predicts the Prognosis of Cholecystitis

Metabolic abnormalities associated with liver disease have a significant impact on the risk and prognosis of cholecystitis. However, the underlying mechanism is complicated and remains to be elucidated. In particular, the effect of metabolic abnormalities on the progression of cholecystitis through the regulation of immune cell function is poorly understood. In this study, we investigated this issue using Wilsons disease (WD) as a model. Wilsons disease is a genetic disorder characterized by impaired mitochondrial function and abnormal copper metabolism. Our retrospective clinical study of over 600 patients with WD found that they have a significantly higher incidence of cholecystitis and a poorer prognosis. The immune cell landscape in the hepatic mesenchymal stromal microenvironment of WD patients was shown using single-cell RNA. A major change is the constitution and function of the innate immune system, including enhanced antigen presentation process, activation of the immune response, and activation of lymphocytes. The proportion of mononuclear phagocytes and natural killer (NK) cells is increased, and the primary characteristic and function of macrophage, Kupffer cell, neutrophil, and NK cell are altered. Exhaustion of NK cell is the fundamental factor, supported by an increase in the expression of the inhibitory receptors KLRC1 and TIGIT and a decrease in the expression of cytotoxic molecules. Clinical tissue and blood samples verified increased KLRC1+ and TIGIT+ NK cells and decreased IFN{gamma}+ NK cells in WD. Further bioinformatic analysis has confirmed a positive correlation between NK cell exhaustion and poor prognosis in cholecystitis and other inflammatory diseases. The study demonstrated abnormal function of liver mesenchymal immune cells triggered by specific metabolic dysfunction in WD, with a focus on the correlation between NK cell exhaustion and poor healing of cholecystitis. Our findings highlight the immune cell dysfunction due to metabolic changes in hepatocytes and provide new insights into the improvement of inflammatory diseases by assessing immune cell function.

immunology↗