Biology subjects

Li, J.-N.

Publications and source records attributed to Li, J.-N..

6 recordsLinked to original sources

bioRxiv2026

Causally-inspired meta-representation learning framework for predicting patient-specific clinical responses to drug combinations

Large-scale prediction and assessment of clinical patient responses (i.e., RECIST class) to drug combinations remains challenging due to scarce patient-derived data. The existing prediction methods mainly rely on cancer cell line models. However, substantial biological heterogeneity between cancer cell lines and cancer patients within same tissues, as well as the heterogeneity between one tissue and another, often limit the generalizability of these methods in clinical patients. To overcome these limitations, here we present CaMeRe, a Causally-inspired Meta-representation learning framework designed to predict patient-specific clinical Response to drug combinations. In situations where stable causal factors and domain-specific response-modulating factors are unobservable, explicit discrete domain labels are unavailable, and data is scarce, CaMeRe designed a domain-invariant causal representation learning (DICRL) model guided by the invariant information bottleneck theory and causal intervention invariance principle, and also built a meta-learning framework with bi-level domain generalization to optimize DICRL model for achieving multi-domain generalization within and across tissues. By integrating the causal representation learning and meta learning framework, CaMeRe not only exhibited robust multi-domain generalization performance across multiple clinical drug combination response datasets and PDXs drug combination response datasets and generalization scenarios, but also had better interpretability. We applied CaMeRe to predict drug-combination response scores for 3,423 patients across 542,080 drug combinations. The predicted scores were significantly associated with biomarkers of known drug combinations and enabled the prioritization of candidate drug combinations across 11 cancer types, with stronger support from literature and clinical trial evidences than random baselines. We believe that CaMeRe can be a useful tool for predicting large-scale clinical individual drug combination responses and it has broad clinical applications.

bioinformatics↗

bioRxiv2026

The Critical Role of Pdyn-Lineage Enteric Neurons in Colonic Motility and Visceral Interoception

Summary/Abstract Sensory neurons play well defined roles in the regulation of intestinal motility, digestion, and interoception, but transcriptional dissection of intrinsic and extrinsic sensory neurons innervating the intestines has been challenging because these cells share many genetic markers. However, we cross-referenced transcriptional profiles of intrinsic and extrinsic intestinal neurons and the cells that surround them and identified Pdyn, the gene encoding Prodynorphin, as a marker of putative sensory enteric neurons of the mouse intestines. In a Pdyn lineage-reporter mouse, we identified labeled cells in the myenteric and submucosal plexuses of the large intestine, in contrast to their sparse presence in the dorsal root or nodose ganglia. In dissociated cell culture, these neurons mostly display a phasic firing pattern, discharging one or two action potentials at the onset of a depolarizing current pulse, followed by a prompt cessation of firing despite continued current injection, as assessed by whole-cell patch-clamp recordings. Optogenetic activation of Pdyn-lineage neurons propels stool in ex vivo colons, and in untethered and mobile mice, optogenetic stimulation of the proximal colon induces freezing behaviors and orbital tightening, suggesting interoceptive behaviors, without significant stool output differences. Together, these findings suggest that activation of Pdyn-lineage enteric neurons regulates motility and visceral interoception.

neuroscience↗

bioRxiv2025

Central Amygdala Neuronal Ensembles Coordinate Visceral Pain and Its Affective Behaviors

Visceral pain and its affective component associated with cystitis remain poorly understood. Here, we delineate the role of central amygdala (CeA) neuronal ensembles in encoding and modulating cystitis-induced bladder pain and its affective components. Utilizing a multidisciplinary approach combining behavioral assays, optogenetic manipulations, whole-cell electrophysiology, and activity-dependent genetic labeling, we identified functionally discrete CeA subpopulations that are selectively recruited during bladder inflammation. Bidirectional optogenetic modulation of these ensembles produced opposing effects on nocifensive and anxiety-like behaviors, indicating their causal involvement. Single-nucleus RNA sequencing of FosTRAP-labeled neurons revealed distinct transcriptional signatures associated with inflammatory activation. Integrating electrophysiological and transcriptomic data, we demonstrate that cystitis drives cell type-specific adaptations in CeA circuits. These findings provide mechanistic insight and uncover a molecularly and functionally defined CeA ensemble that orchestrates the sensory and affective dimensions of visceral pain.

neuroscience↗

bioRxiv2025

Human sensory neurons exhibit cell-type-specific, pain-associated differences in intrinsic excitability and expression of SCN9A and SCN10A

Despite major advances in pain science, the approval of novel therapeutics has been slow. A major cause for the lack of new analgesics may be fundamental biological differences between humans and model organisms used in preclinical research. Large-scale transcriptional profiling efforts on human dorsal root ganglia (hDRG) have now identified at least 22 distinct neuronal subtypes; however, a significant knowledge gap exists in ascribing functional phenotypes to these diverse neuronal populations. In this study, we use Patch-seq recordings in hDRG to link electrical properties to transcriptionally defined cell types. First, through unbiased clustering of electrophysiological properties from 228 hDRG neurons, we identify three electrophysiological subtypes (E-types). Next, we show that E-types can be mapped onto specific transcriptional classes (T-types) of hDRG neurons. We find that donors pain history is associated with E-type-specific differences in electrical properties, some of which may be associated with higher expression of voltage-gated sodium channels, NaV1.7 and NaV1.8. These results highlight the importance of using multimodal profiling to better understand human sensory neuron biology and may help reveal novel therapeutic targets driving chronic pain. TeaserMapping electrical properties to transcriptional profiles of human sensory neurons offers new insights into pain neurobiology

neuroscience↗

bioRxiv2022

Oral oxycodone self-administration leads to features of opioid addiction in male and female mice

Use of prescription opioids, particularly oxycodone is an initiating factor driving the current opioid epidemic. There are several challenges with modeling oxycodone abuse. First, prescription opioids including oxycodone are orally self-administered and have different pharmacokinetics and dynamics than morphine or fentanyl which have been more commonly used in rodent research. This oral route of administration determines the pharmacokinetic profile, which then influences the establishment of drug-reinforcement associations in animals. Moreover, the pattern of intake and the environment in which addictive drugs are self-administered are critical determinants of the levels of drug intake, of behavioral sensitization, and of propensity to relapse behavior. These are all important considerations when modeling prescription opioid use, which is characterized by continuous drug access in familiar environments. Thus, to model features of prescription opioid use and the transition to abuse, we designed an oral, homecage-based oxycodone self-administration paradigm. Mice voluntarily self-administer oxycodone in this paradigm without any taste modification such as sweeteners, and the majority exhibit preference for oxycodone, escalation of intake, physical signs of dependence, and reinstatement of seeking after withdrawal. In addition, a subset of animals demonstrate drug taking that is resistant to aversive consequences. This model is therefore translationally relevant and useful for studying the neurobiological substrates of prescription opioid abuse.

neuroscience↗

bioRxiv2021

Modeling features of addiction with an oral oxycodone self-administration paradigm

Prescription opioid use is an initiating factor driving the current opioid epidemic. There are several challenges with modeling prescription opioid addiction. First, prescription opioids such as oxycodone are orally self-administered and have different pharmacokinetics and dynamics than morphine or fentanyl. This oral route of administration determines the pharmacokinetic profile, which is critical for establishing reliable drug-reinforcement associations in animals. Moreover, the pattern of intake and environment in which addictive drugs are self-administered intake are critical determinants of the levels of drug intake, sensitization and relapse behavior. This is an important consideration with prescription opioid use, which is characterized by continuous drug access in familiar environments. Thus, to model features of prescription opioid use and the transition to abuse, we present an oral oxycodone self-administration paradigm that is administered in the home cage. Mice voluntarily self-administer oxycodone in this paradigm without any taste modification such as sweeteners, and exhibit preference for oxycodone, escalation of intake, physical signs of dependence, reinstatement of seeking after withdrawal, and a subset of animals demonstrate drug taking that is resistant to aversive consequences. This model could be useful for studying the neurobiological substrates specifically relevant to prescription opioid abuse.

neuroscience↗