Category: 3. Business

Introduction

Insomnia, characterized by difficulty falling or staying asleep, affects 12–20% of the global population, impairing mental and physical health and even increasing risks of hypertension, depression, and cardiovascular diseases.^1–3 Insomnia patients usually suffer heavy burdens, partly due to higher healthcare costs and cognitive dysfunction, and even increased risk of developing various serious diseases (eg, hypertension and cardiovascular disease)^1,2 (Figure 1). The main therapeutic strategies for insomnia are cognitive-behavioral therapy (CBT) and pharmacotherapy.^1–3 CBT is widely recognized as the first-line standard treatment for chronic insomnia, using various cognitive and behavioral techniques to correct dysfunctional beliefs and behavioral patterns that perpetuate insomnia.^4,5 CBT can significantly improve quality of sleep, offering long-term benefits, while medications (eg, benzodiazepines, melatonin receptor agonists, and orexin receptor antagonists) provide short-term relief but with dependency risks.⁴ However, the accessibility of CBT remains a challenge as it requires specially trained therapists.

Figure 1 The potential pathogenesis and harm of insomnia.

Alternative therapies like traditional herbal remedy (eg, Guipi capsule) have caught increasingly attentions due to their efficacy, affordable, and fewer side effects, although lack of convincingly scientific evidence.⁶ Herbal medicine for insomnia has a history of thousands of years.⁶ Guipi capsule is constituted of a traditional Chinese herbal formula. Its major components are same with the traditional herbal medicine Guipi tang (Chinese for Guipi tang or Japanese for kihi-to) that is a mixture of 12 herbs used to treat insomnia, forgetfulness, fatigue, poor memory or amnesia, anorexia, anemia, palpitations, and other neurological symptoms.⁷ This review will introduce the potential pathogenesis of insomnia, and the therapeutic efficacy and potential mechanisms of Guipi capsule for treating insomnia.

Potential Pathogenesis of Insomnia

Biofeedback Between Insomnia and Stomach Dysfunction

The classical theory of traditional Chinese medicine argues “if the stomach is not harmonized, one cannot lie peacefully.⁸ This theory indicates that dysfunction or imbalance of gastrointestinal system may cause insomnia. A survey study found that 68% of patients with functional dyspepsia, 71.2% of those with both functional dyspepsia and irritable bowel syndrome (IBS), and 50.2% of those with IBS alone self-reported sleep disturbances.⁹ Patients with functional gastrointestinal diseases often experience sleep problems, which may be attributed to the chronic pain stimuli they endure, such as persistent gastrointestinal discomfort leading to difficulty in falling asleep, disrupted sleep preventing them from falling back asleep, and overall reduced sleep duration. Individuals with digestive system disorders experience impaired sleep, while in turn, decreased sleep quality may exacerbate or trigger gastrointestinal symptoms, creating a vicious cycle of mutual influence. Therefore, improving sleep can alleviate digestive discomfort, and conversely, a better digestive state can benefit sleep quality.⁸

The current understanding of the pathophysiology of functional gastrointestinal diseases involves dysregulation of central autonomic function, visceral hypersensitivity, and neuroendocrine changes in response to stress.¹⁰ Some neurotransmitter systems involved in regulating these abnormalities, such as the ascending serotonergic system, cholinergic system, and noradrenergic arousal system, also play a vital role in sleep regulation, potentially contributing to sleep disturbances. Gastrointestinal functional disorders are often accompanied by imbalances in the intestinal microbiota and the production of inflammation in the body.^11,12 The gut houses a diverse community of microorganisms with intricate metabolic processes that significantly impact various aspects of human health, sleep regulation included.

Roles of Emotion in Insomnia

Insomnia frequently occurs in people struggling with mental issues. Chronic depression and anxiety often disrupt sleep, fueling a cycle of sleeplessness.¹³ In fact, depression is the most common mental health disorder accompanying insomnia, and the two are closely intertwined.^14–16 Research suggests that depression not only predicts insomnia but also worsens it—up to 90% of depressed patients experience poor quality of sleep, and nearly 58% of those with severe depression suffer from insomnia.¹⁷ Similarly, people prone to insomnia tend to have more severe depressive symptoms and difficulty regulating emotions, reinforcing a vicious cycle where each condition exacerbates the other.¹⁵ Anxiety-induced reductions in high-frequency heart rate variability, a marker of diminished parasympathetic nervous system activity, are associated with poorer sleep quality and increased sleep reactivity.^18,19 These findings align with existing evidence demonstrating anxiety’s role in amplifying sleep reactivity, which serves as a critical mechanism through which emotional disturbances like depression and anxiety impair sleep quality.

From a neurobiological perspective, heightened sleep reactivity appears to involve three interconnected systems: (1) dysfunctional cortical networks, (2) autonomic nervous system imbalance that characterized by sympathetic dominance and parasympathetic withdrawal, and (3) hyperactivity of the hypothalamic-pituitary-adrenal axis. Preliminary research indicates that individuals with high sleep reactivity typically exhibit this pattern of increased sympathetic activation coupled with reduced parasympathetic activity.²⁰

Emerging evidence suggests dopamine (DA) system dysfunction may play a key role in modulating sleep reactivity.²¹ As a critical monoamine neurotransmitter, DA not only regulates motivation, reward processing, and pleasure perception but also significantly influences sleep neurobiology – particularly through its action on ventral tegmental area and substantia nigra neurons.²² The connection between DA dysfunction and sleep disturbances appears bidirectional: disrupted DA signaling can contribute to anxiety and depression, which in turn exacerbate sleep reactivity and lead to insomnia.²³

Pharmacological Ingredients of Guipi Capsule and Its Potential Regulatory Mechanisms

Guipi capsule’s main bioactive ingredients amount to dozens of compounds, including sanjoinine A, jujuboside A, jujuboside B, and spinosyn (Table 1). Through the continuous collision of modern and traditional medicine, several studies have indicated mechanisms underlying the active pharmaceutical ingredients of Guipi for the treatment of insomnia (Figure 2).

Table 1 Bioactive Ingredients of the Guipi Capsule and Their Corresponding Effects

Figure 2 The mechanisms underlying the Guipi capsule for insomnia treatment. (A) The bioactive ingredients of Guipi capsule treat insomnia by dynamically regulating neurotransmitter. (B) The bioactive ingredients of Guipi capsule treat insomnia by anti-inflammation effects. (C) The bioactive ingredients of Guipi capsule treat insomnia by regulate organ functions and emotions. Upward arrows mean upregulate and downward arrows mean downregulate. Abbreviations: ASF, astragaloside isoflavan; ASI, astragaloside; APS, astragaloside polysaccharide; AGN, angelica sinensis extract; AO, atractylodes macrocephala oil.

The increased 5-hydroxytryptamine exerts anti-insominia Guipi capsule regulates HPA axis signaling and increases 5-HT levels.^7,24 Each of the individual compounds in Guipi decoction exerts anti-insomnia effects by distinct ways (Figure 2A). For example, Jujube seed contains complex bioactive ingredients for insomnia, including mountain sanjoinine A, Jujuboside A, jujuboside B, spinosin and other flavonoids. These active compounds can increase the levels of 5-HT in insomnia patients, while significantly reducing the levels of 5-HIAA. This effect of regulation can be comparable to the conventional anti-insomnia treatment with western medicines, and the anti-insomnia effect of Jujube seed is even more significant when it is combined with these western medicines.²⁵

Atractylodis macrocephalae oil (AO) was able to increase the levels of IL-10 and decrease the levels of TNF-α, IL-6, 5-HT.²⁶ Atractylodis macrocephalae polysaccharide increases tryptophan, 5-HT.²⁷ The aqueous extract of Atractylodis Macrocephalae (the main components of which are atractylenolide III and β-eudesmol exhibited inhibitory effects on DOI-induced head-twitch response (HTR).²⁸ After administration of Angelica sinensis volatiles in a mouse model of insomnia, prostaglandin E2 (PGE2), histamine (HIS), and 5-hydroxytryptamine (5-HT) levels returned to those observed in normal controls.²⁹ Poria triterpenoids may modulate 5-HT receptors expressed in cells, and inhibition of 5-HT-induced inward currents occurs in a concentration-dependent and reversible manner.³⁰ Flavonoids, liquiritigenin, glabridin, and licochalcone A are the most potent inhibitors of 5-HT-induced currents,³¹ liquiritin and isoliquiritin also significantly reduced the ratio of 5-HIAA/5-HT in the hippocampus and hypothalamus, and slowed down 5-HT metabolism.³² Astragaloside IV or astragalus saponin restores 5-HT, and monoamine oxidase deletion levels and normalizes Tph 2 mRNA expression to control values and improves memory deficits and it improves sleep disorders by this mechanism.³³

GABA Involves in Regulating the Sleep-Wake Cycle

The second mechanism by which Guipi capsule treats insomnia involves enhancing the expression of NR1 and Tau in the hippocampus, promoting GABA synthesis, and increasing serum GABA levels. Elevated GABA enhances Cl⁻influx into neurons, leading to membrane hyperpolarization, reduced neuronal excitability, and regulation of the sleep-wake cycle (Figure 1A).^34,35 GAT, including GAT-1, GAT-2, and GAT-3 isoforms, acts as the GABA transporter that maintains GABA homeostasis. GAT-1, mainly located on GABAergic neuron membranes, mediates GABA reuptake. The down-regulation of GAT-1 expression is considered to be a mechanism of self-protection after insomnia.³⁶ The up-regulation of GAT-1 caused by Guipi may be related to the release of the persistent state of excitation, and the compensatory expression of GAT-1 is gradually restored, which maintains the balance of the concentration of GABA in the neurons and synapses, and exerts its neuroinhibitory effect to improve the symptoms of insomnia.^37,38

As with the first mechanism, the various components of Guipi capsule each exert their anti-insomnia effects by directly or indirectly increasing GABA levels. Atractylenolide II/ III can maintain the activity of the recombinant GABA-A receptor.³⁹ Jujube seed contains a variety of effective chemical components against insomnia, including sanjoinine A, jujuboside A, spinosin and other flavonoids, which are able to mediate sedative and hypnotic functions through GABAergic and serotonergic systems,⁴⁰ jujuboside A and jujuboside B have significant effects on the expression and activation of GABA-A receptor,⁴¹ low-dose jujuboside A induced significant increases in the mRNA of α1, α5 and β2 subunits of GABA-A receptor in both 24-hour and 72-hour treatments, and increased the frequency of the opening of chloride channels, which had a calming and hypnotic effect.⁴² Jujuboside A not only regulates the expression of GABA receptor subunit mRNA, but also down-regulates the secretion of inflammatory cytokines related to the intestinal mucosal system, affects the cytokine network between nerve cells in the brain and exerts its specific sedative-hypnotic effect, which is a similar mechanism to that of melatonin.⁴³

Poria triterpenoids, a main component in Poria cocos, can regulate the content of GABA, menthionine and glutamate in the brain, as well as regulating the expression of GAD65 and GABA,⁴⁴ with sedative and anticonvulsant effects. There are also studies specifically targeting the signaling pathway to begin with, Poria cocos water-soluble polysaccharides (PCWP) inhibited the anxiety of rats induced by chronic sleep deprivation (CSD). PCWP intervention increased the levels of 5-HT, DA, norepinephrine, and γ-aminobutyric acid in the hypothalamus and inhibited TNF-α/nuclear factor, NF-κB signaling pathway.⁴⁵ Glabridin through GABA-A receptors to enhance GABA inhibition in neurons, thereby exerting sedative and hypnotic effects.⁴⁶ Isoliquiritin activates GABA-B receptors, thereby reducing voltage-gated Ca²⁺ channels and glutamate release in rat cortical nerve terminals. Additionally, it alleviates elevated levels of GABA and histamine.⁴⁷

The Roles of DA and NE Metabolism in Insomnia

Neural stem cells (NSC) were treated with astragaloside (ASI), astragaloside polysaccharide (APS) and astragaloside isoflavan (ASF), the main active ingredients of Astragalus. Quantitative RT-PCR results showed that ASI, APS and ASF could promote the expression of tyrosine hydroxylase and dopamine transporter protein mRNA specifically expressed in DA neurons. Meanwhile, Shh, Nurr1 and Ptx3 have been suggested to stimulate the formation of DA neurons.⁴⁸ Costunolide ameliorates have anti-apoptotic activity, which may be attributed to their regulatory effects on DA metabolism-related genes. Costunolide ameliorates are involved in the regulation of genes Nurr1, DAT and VMAT2 and are closely associated with ASYN-related DA metabolism.⁴⁹ Jujube seed extract can affect DA and NE levels in insomniac mice, exerting sedative and tranquilizing effects. This suggests that Jujube seed extract may ameliorate insomnia symptoms by modulating the levels of DA and NE.⁴² Liquiritin reduced dopamine levels to control levels;⁵⁰ Isoliquiritin antagonized the increase in striatal dopamine release.⁵¹ And licorice chalcone A (Lico. A), a flavonoid isolated from licorice, was demonstrated to attenuate the reduction of DA uptake and loss of tyrosine hydroxylase immunoreactivity in an in vitro model of PD induced by Isoliquiritin,⁵² as evidenced in experiments on cultured primary mesencephalic glia;⁵³ Lico. Isoliquiritin-induced reduction in DA uptake and loss of tyrosine hydroxylase-immunoreactive neurons in an in vitro model of PD.⁵² Dose-dependent neuroprotective effects of liquiritin during subacute NE depletion of nerve endings.⁵⁰ Atractylenolide I (AT-I) is a major constituent of Atractylodes macrocephala with a wide range of activities. AT-I was able to counteract the reduction in hippocampal 5-HT and NE concentrations induced by CUMS.⁵⁴

Anti-Inflammation Cytokines in Insomnia

As mentioned in the previous content, patients with insomnia have higher levels of inflammation, and inflammatory factors such as TNF-α and IL-1β can affect the neurotransmitter balance in the sleep center, leading to the occurrence of insomnia.⁵⁵ Therefore, reducing inflammation level is an effective method to treat insomnia (Figure 2B).

Flavonoids contained in Codonopsis, Astragalus, Atractylodes macrocephala, and Poria are natural compounds with anti-inflammatory properties.⁵⁶ Flavonoids can reduce the expression levels of inflammatory factors such as TNF-α and IL-1β as well as inhibit the NF-κB signaling pathway, suppressing the inflammatory response and thus improving the quality of sleep.⁵⁷ In addition to flavonoids, other medications have been shown to play an anti-inflammatory role in the treatment of insomnia by inhibiting the MAPK signaling pathway, including the ERK, JNK and p38 pathways. These pathways play an important role in the inflammatory response, and inhibiting their activity reduces the inflammatory response and improves sleep quality.⁵⁸ Specific drug efficacy is as follows, Astragaloside IV dose-dependently reduces serum levels of corticosterone, IL-6 and TNF-α.⁵⁹

Atractylodes macrocephala oil (AO) was able to increase the levels of IL-10 and decrease the levels of TNF-α, IL-6, and 5-HT.⁵⁹ AO can significantly inhibit systemic inflammation triggered by acute local stimuli, and exerts anti-inflammatory activity mainly by regulating the metabolic network disorders centered on glycine and arachidonic acid.⁶⁰ AO exerts anti-inflammatory effects by inhibiting pro-inflammatory cytokines (TNF-α, IL-1β, IL-6), inflammatory mediators (HIS, 5-HT, PGE2, NO), and inflammation-related enzymes (iNOS and COX-2), as well as promoting the production of the anti-inflammatory cytokine IL-10.⁶¹ Poria cocos extract inhibited the inflammatory response induced by chronic mild stress (UCMS) and reduced the expression of p38, NF-κB, and TNF-α in the frontal cortex.⁶²

The Roles of Organ Dysfunctions and Emotions Instability in Insomnia

In addition, Guipi capsule plays an important role in regulating the spleen, stomach, liver and kidneys (Figure 1C). Guipi capsule exhibits broad therapeutic effects across multiple systems. Clinically, it demonstrates efficacy in treating non-acidic gastroesophageal reflux disease (GERD) with mood disorders when combined with omeprazole, improving gastrointestinal motility, reducing esophageal hypersensitivity, and modulating beneficial gut bacteria.^63,64 In neuropsychiatric applications, Guipi capsule shows antidepressant effects comparable to fluoxetine but with faster onset and better safety. Clinical trials reveal significant hamilton depression scale (HAMD) score improvements as early as 1 week post-treatment (P < 0.01 vs fluoxetine), with no reported adverse reactions versus fluoxetine’s 3.33% incidence (P < 0.01).⁶⁵ Mechanistically, its active components (eg, Astragalus extracts) reduce oxidative damage by suppressing ROS production and reversing 6-OHDA-induced oxidative stress.⁶⁶ Although Guipi capsule in treating insomnia show good efficacy and relatively higher safety,⁶⁵ the results are easily influenced by potential resources of bias, including publication bias and size of patients, and designs of clinical trials, the efficacy and safety of Guipi capsule need to be more strictly demonstrated based on more and better clinical trials in future. In addition, there are some other limitations: inadequate randomization and blinding for clinical trials and methodological quality of included studies.

Guipi capsule also exerts therapeutic effects through other multiple mechanisms involving both metabolic regulation and emotional modulation. The capsule influences key amino acid metabolic pathways while also regulating intestinal flora composition and promoting short-chain fatty acid production. The capsule’s emotional regulation properties are majorly mediated by its active components like astragaloside IV (ASIV) and astragalus saponins.⁶⁷ Additionally, they have been shown to mitigate anxiety responses and inflammatory reactions induced by restraint stress.⁵⁹

Furthermore, the active ingredients in Guipi capsules exert antidepressant effects by modulating the serotonin (5-HT) system, a key neurotransmitter pathway involved in mood regulation.³³ Similarly, licorice extracts appear to enhance norepinephrine (NE) and dopamine (DA) levels in the brain, contributing to their antidepressant properties.⁵⁰ Angelica sinensis extract (AGN) has been shown to mitigate stress-induced helpless behavior in rats, likely through its influence on the central noradrenergic system and upregulation of brain-derived neurotrophic factor (BDNF).⁶⁸ Meanwhile, Hairy Angelica serrulata demonstrates vasorelaxant effects in rat thoracic aorta, mediated by calcium channel blockade and increased cGMP levels in vascular smooth muscle.⁶⁹ Cycloastragenol exhibits neuroendocrine regulatory effects, reducing serum levels of stress-related factors such as NE, aldosterone, angiotensin II, and endothelin-1.⁷⁰ Additionally, pCWP has been found to counteract anxiety behaviors induced by chronic sleep deprivation in rodent models.⁴⁵

Conclusions and Discussion

Guipi capsule, a traditional Chinese herbal remedy, has been widely used in the treatment of insomnia.⁷ As mentioned above, numerous studies have shown that Guipi capsule is effective in regulating hormones and neurotransmitters, enhancing GABAergic activity,⁷¹ DA⁴⁹ and NE⁵⁰ metabolism, anti-inflammatory effects,^59–62 as well as improving gastrointestinal function and emotional health.⁶⁵ However, there are some limitations in this review: (1) The underlying mechanisms by which Guipi capsule regulates insomnia were revealed by using the single bioactive ingredient. Therefore, research should further explore the mechanism of action of Guipi capsule in depth because Guipi capsule inevitably suffers from the problem that its efficacy varies according to individual constitution and condition like most herbal medicines. (2) We could not convincingly demonstrate efficacy and safety of Guipi capsule as limited robust and well-designed clinical trials.

Overall, the application of Guipi capsule in the treatment of insomnia is potential promising, but its therapeutic efficacy and safety is expected to be further improved through in-depth research technological innovation, and well-designed clinical trials. The combination of Chinese and Western medicine in the treatment of insomnia may provide patients with more comprehensive and effective treatment options, and promote the development of the field of insomnia treatment.

Data Sharing Statement

All of data and materials can be found in references.

Acknowledgments

X. F. was supported by the 2023 Shanghai Jiao Tong University Teaching Development Fund (CTLD23J0104).

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare no competing interests.

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Drawing on insight from the firm’s global network of partners, the analysis provides a forward look at the issues likely to demand insurers’ attention as the global risk landscape continues to shift over the next 12 months. 

Clyde & Co’s emerging risk predictions for insurers in 2026: 

• Social media addiction
• Space
• Next generation nuclear
• Sanctions
• Head office liability 
• Litigation funding

Since September 2022, the Europeana Research Community and the EuropeanaTech Community have supported a Working Group on Datasheets for Digital Cultural Heritage Datasets. The Working Group addresses a critical matter for cultural heritage institutions managing digital collections, that is, providing data reusers with the context needed for reusing data.

Specifically, the working group has focused on datasheets as a standardised publication format for documenting datasets (for example, corpora of digitised books and newspapers, bibliographic datasets, digitised artworks), with the goal to support cultural heritage institutions and other data providers to describe their data assets in a way compliant with the FAIR principles, enabling an efficient inclusion into reuse workflows. This focus has also brought forward the efforts to affirm a ‘Collection as Data’ approach in the common European data space for cultural heritage, concretely expressed by the development of the ‘Collections as Data’ workflow, in which documentation is addressed as one of the ten steps suggested for curating datasets.

After realising their datasheet template – Version 1 in September 2023, and presenting it at events across Europe, this year the Working Group members have organised a series of workshops to test and refine the template with professionals and researchers interested in digital curation across and beyond the Europeana Initiative. This series included a workshop with those working on similar initiatives in Europe (such as data envelopes at the KNAW | The Royal Netherlands Academy of Arts and Sciences) and a highly attended workshop open to the public embedded into the programme of the Europeana Aggregators’ Forum meeting in Spring.

This approach – nurtured by the spirit of the Europeana communities that are based on knowledge-sharing and bottom-up development of the cultural heritage sector – led to the release of the datasheet template – Version 2 in July 2025.

What’s new in Version 2

The new datasheet template is structured in six sections, which combine technical and ethical aspects that documentation should take into account: title, description, distribution, composition, data collection process, examples and considerations for using the data. While the core aims of the template remain the same, Version 2 brings several structural improvements. The updated version features a modular information architecture organised into three levels of depth, with a minimal set of mandatory fields. This design allows the template to better accommodate the diversity and complexity of digital heritage collections and to be used meaningfully across very different types of datasets, while clearly indicating what is known, unknown and not applicable.

In addition to these structural updates, Version 2 takes the first steps toward machine-readability, in line with the current developments around the common European data space for cultural heritage. Fields identified as mandatory within the template have been mapped to the Data Catalogue Vocabulary Application Profile for data portals in Europe (DCAT-AP), a specification for describing public sector datasets in Europe. Aligning with this standard enables discoverability in data portals and compatibility with automated workflows, while keeping the primary focus of the template on human readability and usability.

What’s next and how to get involved

The Working Group continues to refine the template, focusing on interoperability and facilitating its adoption. Current priorities include an overall alignment with DCAT-AP, and gathering new use cases, whilst developing an open-source tool to support the creation of documentation for datasets, which will be finalised and made available in open source by next year. The datasheet template – Version 2 will serve as a basis to define minimum requirements for sharing datasets through the upcoming data catalogue of the common European data space for cultural heritage.

Explore the datasheet template – Version 2, try it out in your own context, and share your feedback by writing an email to [email protected]! Your contributions will help shape the next steps in this community-driven project.

Meet the Working Group on site or online at Fantastic Futures 2025

Working Group representatives will present these updates at the Fantastic Futures 2025 conference organised by AI4LAM and hosted at the British Library on 3–5 December 2025, in a lightning talk highlighting Version 2 within a group of initiatives focusing on documenting datasets: Write it down! Fostering Responsible Reuse of Cultural Heritage Data with Interoperable Dataset Descriptions. Tickets for online attendance are now available for free – register now.

Introduction

Low back pain is a leading cause of global disability, and intervertebral disc degeneration (IVDD) is one of its most common pathological underpinnings.¹ IVDD is a progressive pathological process characterized by structural disruption and cellular dysfunction within the disc, ultimately leading to biomechanical instability and chronic inflammation.² Among the major components of the intervertebral disc, the annulus fibrosus (AF) plays a crucial role in maintaining disc integrity by providing tensile strength and enclosing the nucleus pulposus.³ During IVDD, annulus fibrosus cells (AFCs) undergo profound pathological alterations, including extracellular matrix (ECM) degradation, increased fibrosis, phenotypic transition, and inflammatory activation.⁴ These changes compromise the structural and mechanical properties of the disc, accelerate tissue breakdown, and contribute to the chronic degenerative cascade. Despite the central role of AFCs in IVDD pathogenesis, the underlying regulatory mechanisms driving their degeneration remain incompletely understood.

PANoptosis is a recently identified form of programmed cell death that simultaneously engages pyroptosis, apoptosis, and necroptosis through the assembly of the PANoptosome complex.⁵ PANoptosis is a unique, inflammatory programmed cell death pathway characterized by the concomitant activation of pyroptosis, apoptosis, and necroptosis, which cannot be fully accounted for by any of these pathways alone. Its execution is regulated by the assembly of a multifaceted protein complex termed the PANoptosome, which recruits key molecules such as ASC, RIPK3, and Caspase-8, among others. This complex serves as a molecular platform for the simultaneous activation of the three death pathways. In recent years, PANoptosis has gained increasing attention in IVDD research, as excessive cell death and inflammation are pivotal drivers of disease progression. For instance, one study demonstrated that PANoptosis occurs in nucleus pulposus cells (NPCs) and that L-BAIBA inhibits this process while promoting ECM synthesis via the AMPK/NF-κB pathway; similarly, another study showed that Kongensin A suppresses PANoptosis in NPCs by upregulating TAK1 and alleviates IVDD progression.⁶ With attention growing on PANoptosis in IVDD, current research has predominantly focused on NPCs, leaving the relationship between PANoptosis and AFCs unexplored. Our previous research demonstrated that AFCs undergo apoptosis during disc degeneration, consistent with findings reported by Jacobsen et al^7,8 Additionally, studies by Yao et al⁹ have shown that AFCs experience pyroptosis in the degenerative process. Drawing from these studies, we hypothesize that PANoptosis is likely involved in the degeneration of AFCs. However, PANoptosis has not been directly demonstrated in AFCs.

Toll-like receptor 4 (TLR4), as a key molecule connecting inflammation and cell death, has been confirmed to be involved in the pathological process of various degenerative diseases by activating downstream signaling pathways.¹⁰ Additionally, NLRP12, as a negative regulatory factor of the NLR family, plays an important role in the balance between inflammatory signal transduction and cell death.¹¹ A study found that Heme + PAMPs induce the expression of NLRP12 through the TLR2/4-IRF1-ROS axis. NLRP12 assembles the PANoptosome to activate caspase-8/RIPK3 and cleaved-Caspase-1, mediates PANoptosis and the release of inflammatory factors, and aggravates hemolysis-related tissue damage.⁵ However, in the inflammatory microenvironment of IVDD, it remains unclear whether NLRP12 serves as a key connector molecule between TLR4 and PANoptosis. While existing studies have demonstrated that TLR4 can exacerbate IVDD through inflammatory signaling, research on the impact of NLRP12 on IVDD remains notably scarce.

Based on this background, this study aims to explore for the first time the regulatory role of the TLR4 signaling pathway in PANoptosis of AFCs and clarify the mediating mechanism of NLRP12 as a key molecule. The research results will provide a new perspective for analyzing the pathogenesis of IVDD and lay a theoretical foundation for the development of intervention strategies targeting cell death pathways.

Materials and Methods

Single-Cell RNA Sequencing (scRNA-Seq) Analysis

We analyzed the publicly available single-cell RNA sequencing dataset GSE230809, which included 46,961 cells from three healthy AF samples and ten IVDD cases. Quality control was performed by filtering cells with feature counts between 300 and 8000, total RNA counts ranging from 500 to 60,000, and excluding cells with mitochondrial gene expression exceeding 20% or hemoglobin genes surpassing 10%. The data were normalized and subjected to principal component analysis (PCA) for dimensionality reduction, followed by UMAP clustering at a resolution of 0.5 to identify distinct cell populations. Cell type annotation was performed by integrating UMAP projections, hierarchical clustering, and known marker genes from existing literature. Differential gene expression analysis between healthy and IVDD groups was conducted using Seurat’s FindMarkers function. Functional enrichment analysis, including Gene Ontology (GO) and KEGG pathway analysis, was performed to elucidate biological differences, supplemented by gene set enrichment analysis (GSEA) for pathway-level comparisons. Pseudotime trajectory analysis was carried out using Monocle 2 (v2.10.1) to explore dynamic transcriptional changes across cell states. Additionally, gene set variation analysis (GSVA) was applied to evaluate pathway activity within clusters using the MSigDB c5.go.v2023.2.Hs.symbols.gmt gene set. To investigate intercellular signaling, we employed CellChat to infer ligand-receptor interactions and communication networks, focusing on pathways that exhibited significant differences between healthy and degenerated discs.

RNA Sequencing Analysis

RNA sequencing (RNA-seq) was conducted by Wuhan Metaware Biotechnology Company (Wuhan, China). Total RNA was extracted on ice using TRIzol reagent (Thermo Fisher Scientific, MA, USA). RNA concentration and purity were measured with a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific), while RNA integrity was assessed using the RNA Nano 6000 Assay Kit on the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA). Subsequently, the cDNA library was quality-checked using the same Agilent Bioanalyzer 2100 system. RNA-seq was performed on the Illumina NovaSeq platform. Raw sequencing data were processed to generate clean reads by removing adapter-containing reads, poly-N sequences, and low-quality reads. Clean reads were mapped to the reference Rattus norvegicus genome using HISAT2, followed by transcript reconstruction with StringTie. Gene expression levels were quantified as fragments per kilobase of transcript per million mapped fragments (FPKM). Differential gene expression analysis was performed using the DESeq R package (version 1.10.1). Genes were considered significantly differentially expressed if they met the thresholds of a false discovery rate (FDR) < 0.05 and |log2 fold change| ≥ 1. Finally, KOBAS software was used to perform statistical enrichment analyses of differentially expressed genes in GO terms, KEGG pathways, and GSEA.

Isolation and Culture of AFCs

Under sterile conditions, AF tissue was isolated and cut into approximately 1 mm³ fragments using ophthalmic scissors. For each isolation, AF tissues from 8 rats were pooled and digested with 0.4% type II collagenase and 0.01% type V hyaluronidase at 37 °C for 90 min. Tissue debris was removed using a 70-μm cell strainer, and the remaining suspension was centrifuged at 400 × g for 5 min. The supernatant was discarded, and the pellet was resuspended in complete medium consisting of Dulbecco’s modified Eagle medium/F-12 (Viva Cell, Shanghai, China), 10% fetal bovine serum (Gibco, NY, USA), and 1% penicillin/streptomycin (Beyotime, Shanghai, China). Cells were cultured at 37 °C in a cell incubator with 5% CO₂. The medium was replaced every 3 days, and AFCs were passaged when confluency reached 80–90%. The third generation of AFCs was used for subsequent analysis. For the in vitro IVDD model, AFCs were treated with 20 ng/mL of TNF-α (MCE, NJ, USA) for 24 hours to mimic the inflammatory microenvironment.

Western Blot Analysis

AFCs were lysed using RIPA lysis buffer (Beyotime), and protein concentrations were determined with a BCA assay kit (Solarbio, Beijing, China). Lysates were mixed with 1/5 volume of loading buffer, followed by incubation in boiling water for 10 min. Proteins were separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and subsequently transferred to PVDF membranes. These membranes were blocked with 5% skim milk for 1 h before being incubated with primary antibodies at 4°C overnight. The primary antibodies included cleaved-Caspase 1 (1:2000, Invitrogen, CA, USA, PA5-99390), cleaved-Caspase 3 (1:1000, Proteintech, IL, USA, 25128-1-AP), MLKL (1:5000, Proteintech, 66675-1-Ig), p-MLKL (1:1000, Invitrogen, MA5-32752), c-GSDMD (1:2000, abcam, UK, ab215203), and GAPDH (1:10000, Proteintech, 60004-1-Ig). After washing with TBST, the PVDF membranes were incubated with secondary antibodies for 1 h. The secondary antibodies employed were Goat Anti-Mouse IgG (H + L) HRP (1:20000, Absin, Shanghai, China) or Goat Anti-Rabbit IgG (H + L) HRP (1:20000, Absin). Target protein expression was detected using Clarity Western ECL Substrate (Bio-Rad, CA, USA) and a ChemiDoc imaging system (Bio-Rad), and analyzed with ImageJ software. All results were quantified and normalized to GAPDH.

TUNEL Staining Assay

TUNEL staining was performed to assess apoptosis in cultured AFCs. Cells were seeded on sterile glass coverslips in 6-well plates and treated as indicated. After treatment, cells were fixed with 4% paraformaldehyde for 30 minutes at room temperature, followed by permeabilization with 0.1% Triton X-100 for 10 minutes. Apoptotic cells were detected using a TUNEL apoptosis detection kit (Bio-Rad), following the manufacturer’s instructions. Briefly, the labeling reaction was carried out in a humidified chamber at 37°C for 1 hour in the dark. After washing, nuclei were counterstained with DAPI for 5 minutes. Coverslips were mounted with antifade reagent and examined using a fluorescence microscope (Olympus, Tokyo, Japan). The apoptosis index was calculated as the percentage of TUNEL-positive cells relative to the total number of nuclei.

Apoptosis Detection by Flow Cytometry

Apoptosis in AFCs was quantified using flow cytometry with Annexin V-PE/7-AAD double staining. After treatment, cells were harvested by trypsinization without EDTA, washed twice with cold PBS, and resuspended in 1× binding buffer at a concentration of 1×10⁶ cells/mL. A total of 100 μL of the cell suspension was incubated with 5 μL Annexin V-PE and 5 μL Phycoerythrin (PE) for 15 minutes at room temperature in the dark, according to the manufacturer’s instructions of the Annexin V-PE/7-AAD Apoptosis Detection Kit (Roche, IN, USA). After staining, 400 μL of binding buffer was added, and samples were immediately analyzed using a flow cytometer. At least 10,000 events were recorded per sample. Early apoptotic cells (Annexin V⁺/PE⁻) and late apoptotic or necrotic cells (Annexin V⁺/PE⁺) were quantified, and the apoptosis rate was calculated as the sum of early and late apoptotic populations.

Immunofluorescence Staining

AFCs were seeded into confocal culture dishes and treated as indicated. After treatment, cells were fixed with 4% paraformaldehyde for 20 minutes at room temperature and permeabilized with 0.1% Triton X-100 for 10 minutes. Non-specific binding was blocked with 5% BSA for 1 hour. Cells were then incubated with primary antibodies against Caspase-8 (1:100, Invitrogen, MA1-41280), RIPK3 (1:200, Invitrogen, 703750), and ASC (1:200, Invitrogen, PA5-50915) overnight at 4°C. After washing, cells were incubated with appropriate fluorophore-conjugated secondary antibodies for 1 hour at room temperature in the dark. Nuclei were counterstained with DAPI. Coverslips were mounted with antifade reagent and imaged using a fluorescence microscope. Colocalization of proteins was evaluated to assess PANoptosome formation.

Establishment of the IVDD Rat Model

Under aseptic conditions, male Sprague-Dawley rats (8 weeks old) were anesthetized by intraperitoneal injection of sodium pentobarbital (40 mg/kg). The coccygeal intervertebral discs were located via palpation and confirmed by lateral X-ray. Under fluoroscopic guidance, a 20G needle was inserted perpendicularly into the AF of the target disc to a depth of 5 mm, then rotated 360° for 30 seconds. At 4 weeks post-puncture, the intervertebral disc tissues were harvested for histological sectioning, magnetic resonance imaging (MRI), and biochemical analysis. All animal experiments were approved by the Laboratory Animal Welfare and Ethics Committee of Qinghai Provincial People’s Hospital. Twelve rats were randomly assigned to four experimental groups (n = 3 per group): Sham, IVDD, IVDD + LV-control, and IVDD + LV-shTLR4. For in vivo delivery, a total of 5 μL lentivirus (1×10⁸ TU/mL) was slowly injected into the punctured disc using a microsyringe immediately after the acupuncture procedure.

Histological Staining

Rat intervertebral discs were harvested, fixed in 4% paraformaldehyde for 48 hours, decalcified in 10% EDTA for three weeks, and embedded in paraffin. Serial sagittal sections (5 μm thick) were prepared for histological and apoptosis analyses. H&E staining was performed following standard procedures: sections were deparaffinized, rehydrated, stained with hematoxylin for 5 minutes, rinsed, counterstained with eosin for 2 minutes, dehydrated, cleared, and mounted. For Safranin O/Fast Green (SO/FG) staining, sections were stained with Fast Green for 5 minutes, rinsed in acetic acid, then stained with Safranin O for 5 minutes, followed by dehydration and mounting.

TUNEL staining was performed on paraffin sections to detect apoptotic cells in the AF region. Sections were processed using a commercial TUNEL apoptosis detection kit (Beyotime), following the manufacturer’s protocol. Briefly, sections were dewaxed, rehydrated, permeabilized with proteinase K, and incubated with TUNEL reaction mixture at 37°C for 1 hour in the dark. Nuclei were counterstained with DAPI, and apoptotic cells (TUNEL-positive) were visualized using a fluorescence microscope. Quantification was performed from three randomly selected fields per section.

X-Ray Analysis

Lateral X-ray imaging of rat tails was performed to evaluate intervertebral disc height after AF puncture and treatment. The scanning parameters were set as follows: 63 mA exposure and 35 kV penetration. Intervertebral disc height index (DHI) was calculated using ImageJ software, with changes in DHI expressed as DHI% (postoperative DHI/preoperative DHI × 100%).

Lentiviral Construction and Transduction

All lentiviral vectors, including shRNA constructs targeting TLR4 and NLRP12, as well as control vectors, were designed and synthesized by GeneChem (Shanghai, China). The target sequences for rat TLR4 and NLRP12 shRNA were as follows: shTLR4: 5’-GACCAGAAATTGCTGAGTT-3’; shNLRP12: 5’-GCAGATGAACTGGTATTAT-3’. AFCs were seeded in six-well plates and transduced with lentivirus at a multiplicity of infection (MOI) of 20 in the presence of polybrene (5 μg/mL). After 24 hours of incubation, the medium was replaced with fresh complete medium, and cells were cultured for an additional 48–72 hours prior to downstream analysis. Knockdown efficiency was confirmed by qPCR and Western blot. For in vivo delivery, lentivirus was injected directly into the AF region of rat tail discs using a microsyringe immediately after needle puncture.

Data Analysis

All experiments were performed in three biological replicates with technical triplicates. Statistical analysis was performed using GraphPad Prism 11 (Graphpad Software Inc., MA, USA). Data are expressed as mean ± SD. Two-group comparisons were analyzed using an unpaired t-test. Multiple comparisons used one-way ANOVA followed by Bonferroni’s post hoc test. p < 0.05 was considered statistically significant.

Results

scRNA-Seq Analysis Reveals Cellular Remodeling and Subtype Shifts in Degenerative AF Tissue

We analyzed the publicly available single-cell RNA-sequencing dataset GSE230809, which includes three samples of healthy AF tissue and ten samples from IVDD cases. To eliminate low-quality cells and minimize RNA contamination, we performed preprocessing and quality control on the dataset, retaining a total of 43,421 cells for downstream analysis.

Using the Seurat standard pipeline and unsupervised Uniform Manifold Approximation and Projection (UMAP) clustering, we identified distinct cell populations. Cluster annotation was based on UMAP projection, hierarchical clustering, and expression patterns of canonical markers reported in the literature (Figure 1A and C). The following AF cell subtypes were identified:

• Fibrotic-like AF cells (Fibro-AFCs): characterized by expression of COL1A1 and FBLN¹²
• Chondrocyte-like AF cells (Chon-AFCs): expressing SOX9 and ACAN¹³
• Homeostatic AF cells (Homeo-AFCs): marked by RSP29 and CCN3¹⁴
• Adhesive AF cells (Adh-AFCs): expressing MSMO1 and HMGCS1¹⁵
• Regulatory AF cells (Reg-AFCs): marked by CHI3L1 and CXCL2¹⁶

Figure 1 Single-cell RNA sequencing reveals cellular heterogeneity and functional pathways in intervertebral disc tissues. (A) UMAP visualization of 43,421 cells from the human NP tissue, dyed according to cell types. (B) Pie chart of the cell type ratio in intervertebral disc tissues. (C) Heatmap of differentially expressed genes among different AFCs subpopulations, including homo-AFCs, chon-AFCs, fibro-AFCs, and pro-AFCs. (D and E) Comparison of cell type distributions between control and disease groups. (F) GO enrichment analysis for differentially expressed genes between control and disease groups. Enriched pathways related to cell death and inflammation are highlighted with red box. (G) KEGG enrichment analysis highlight the top enriched pathways. Enriched pathways related to cell death and inflammation are highlighted with red box. (H) Expression distribution of representative marker genes across different cell clusters.

The relative proportions of each subpopulation are shown in Figure 1B, with Homeo-AFCs being the most abundant and Reg-AFCs the least represented. Figure 1C and H shows the marker genes for each cell cluster. Next, we compared the distribution and relative proportions of AF subtypes between healthy and degenerative samples (Figure 1D and E). Notably, Fibro-AFCs and Adh-AFCs were significantly increased in IVDD samples, while Chon-AFCs and Homeo-AFCs were markedly decreased. Reg-AFCs showed a slight reduction.

We subsequently performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for the healthy and IVDD groups (Figure 1F and G). GO terms enriched in the degenerative group included cell-cell adhesion via plasma membrane adhesion molecules, cell chemotaxis, myofibril assembly, cellular component assembly involved in morphogenesis, and pyroptosis. KEGG analysis revealed enrichment in cell adhesion molecules, ECM-receptor interaction, apoptosis, cAMP signaling, and NF-κB signaling pathway.

Interestingly, both GO and KEGG analyses revealed enrichment of pathways related to cell death, prompting us to hypothesize that PANoptosis, a form of programmed cell death integrating pyroptosis, apoptosis, and necroptosis, might be occurring in IVDD.

PANoptosis Activation Detected in AFCs During IVDD

PANoptosis is an inflammatory form of programmed cell death (PCD) regulated by the formation of the PANoptosome complex and triggered by specific signals. It integrates key molecular features of pyroptosis, apoptosis, and necroptosis.

To investigate whether PANoptosis occurs in IVDD, we conducted Gene Set Enrichment Analysis (GSEA) on several relevant pathways, including the NLRP1 inflammasome complex, NLRP3 inflammasome complex, apoptosis, necroptosis, and pyroptosis (Figure 2A). GSEA results revealed that PANoptosis-related gene sets were significantly downregulated in healthy samples relative to degenerative samples, indicating their upregulation in the latter. We next calculated pyroptosis, apoptosis, and necroptosis scores for each sample. All three scores were significantly elevated in the IVDD group compared to controls (Figure 2B), supporting the activation of PANoptotic signaling during disc degeneration.

Figure 2 Single-cell trajectory analysis and interaction network reveal molecular mechanisms in AFCs. (A) GSEA analysis of PANoptosis-related pathways. (B) Apoptosis, pyroptosis, and necroptosis scores across distinct cell subpopulations. (C) Pseudotime trajectory analysis of key genes (RIPK1, RIPK3, NLRP3, ASC) involved in PANoptosis. (D) Interaction network constructed by CellPhoneDB showing potential interactions between different cell clusters. (E) Cell interaction network analysis based on ligand-receptor pairs.

To further explore the cellular progression dynamics, we performed pseudotime trajectory analysis. Adh-AFCs were positioned at the early stage of the pseudotime axis, Fibro-AFCs were primarily located at the terminal end, distributed in the late stage of the trajectory, while Homeo-AFCs were evenly distributed across all pseudotime stages (Figure S1A). This suggests a potential differentiation trajectory from adhesive to fibrotic phenotypes during disease progression. To further examine the association between degeneration and PANoptosis, we analyzed the expression of PANoptosis-related genes along the pseudotime axis. Key genes such as RIPK1, RIPK3, NLRP3, and ASC were found to be markedly upregulated in late-stage AFCs (Figure 2C), implicating enhanced PANoptotic activity in these cells. Finally, we evaluated intercellular communication patterns within AF subpopulations. The IVDD group exhibited significantly increased frequency and strength of cell-cell interactions compared to the healthy group (Figure 2D and E), indicating a more active and inflammatory intercellular environment that may promote PANoptosis.

Collectively, these findings suggest that PANoptosis is likely activated in degenerative AF tissues and that late-stage AFCs may serve as a central hub for this process.

TLR4 Drives PANoptosis in AFCs

To further verify the occurrence of PANoptosis in degenerative AFCs, we treated AFCs with tumour necrosis factor-alpha (TNF-α) to simulate the degenerative inflammatory environment. Western blot analysis showed increased expression of PANoptosis-related proteins, including cleaved-Caspase-1, cleaved-Caspase-3, MLKL, phosphorylated MLKL (p-MLKL), and cleaved Gasdermin D (c-GSDMD), in TNF-α-treated cells compared to the control and DMSO groups (Figure 3A and B). This indicates that inflammation-induced degeneration of AFCs leads to activation of PANoptosis. Immunofluorescence staining revealed the formation of PANoptosome complexes, marked by colocalization of Caspase-8, RIPK3, and ASC in TNF-α-treated cells (Figure 3C). These aggregates (white arrows) provide morphological evidence of PANoptosome assembly in degenerative AFCs.

Figure 3 TLR4 Drives PANoptosis in Annulus Fibrosus Cells. (A) Western blot analysis of PANoptosis-related proteins (Caspase-1, Caspase-3, MLKL, p-MLKL, C-GSDMD) in Group Con, DMSO, and TNF-α. GAPDH serves as a loading control. (B) Quantification of relative protein levels in (A) normalized to GAPDH. (C) Immunofluorescence staining of Caspase-8, RIPK3, and ASC in Con group and TNF-α group. White arrows indicate the aggregated PANoptosome complex. (D) Heatmap of differentially expressed genes in AFCs between Con group and TNF-α group. (E) Volcano map of differentially expressed genes between Con and TNF-α groups. (F) GO analysis, KEGG analysis, and Reactome analysis of differentially expressed genes. Enriched pathways related to cell death and inflammation are highlighted with red box. (G) GSEA analysis of representative pathways (Apoptosis, Toll-like receptor signaling pathway, Activated tlr4 signaling) in AFCs. ***p < 0.001; ****p < 0.0001; ns indicates not significant.

To further investigate the molecular changes in degenerative AFCs, we performed transcriptome sequencing on TNF-α-treated and control groups. Heatmap and volcano plot exhibited the differentially expressed genes (Figure 3D and E), KEGG pathway enrichment analysis revealed significant involvement of the apoptosis pathway, while GO analysis showed enrichment in the NLRP1 inflammasome complex (Figure 3F), suggesting that TNF-α treatment triggers PANoptosis-related processes in AFCs. In addition, KEGG analysis also indicated activation of the Toll-like receptor signaling pathway, and Reactome analysis highlighted enrichment in the activated TLR4 signaling cascade. These findings imply a potential link between TLR4 activation and PANoptosis induction. To validate these results, GSEA was conducted on representative pathways, including apoptosis, Toll-like receptor signaling, and activated TLR4 signaling. The results were consistent with the enrichment analyses described above (Figure 3G), further supporting the role of TLR4 activation in promoting PANoptosis in this inflammatory model.

TLR4 Induces PANoptosis via NLRP12 Activation in AFCs

RKH acetate is a specific TLR4 inhibitor that directly binds TLR4 and blocks its downstream signaling.¹⁷ To explore the role of TLR4 in AFC PANoptosis, AFCs were treated with RKH acetate. WB showed that RKH acetate reversed the TNF-α-induced upregulation of cleaved-Caspase-1, cleaved-Caspase-3, MLKL, p-MLKL, and c-GSDMD (Figure 4A and B), indicating that inhibition of TLR4 alleviates PANoptosis in AFCs. TUNEL staining revealed an increase in apoptotic cells in the TNF-α group, which was reduced after TLR4 inhibition (Figure 4C and D). FC further confirmed that TLR4 blockade attenuated TNF-α-induced apoptosis (Figure 4E and F).

Figure 4 Continued.

Figure 4 TLR4 Induces PANoptosis via NLRP12 Activation in AFCs. (A and B) Western blot analysis and quantification of PANoptosis-related proteins (Caspase-1, Caspase-3, MLKL, p-MLKL, C-GSDMD) in AFCs treated with Con, DMSO, TNF-α and TNF-α+RKH acetate. (C) TUNEL staining detecting AFCs apoptosis in Con, DMSO, TNF-α, and TNF-α+ RKH acetate groups. Apoptotic cells appear red, and nuclei are counterstained with Hoechst (blue). Scale bar = 40 μm. (D) Statistical analysis of TUNEL-positive apoptotic AFCs in (C). (E) Representative flow cytometry scatter plots detecting AFCs apoptosis in TNF-α, and TNF-α+ RKH acetate groups. (F) Statistical analysis of apoptotic AFCs in (E) determined by flow cytometry (n=3). (G and H) Western blot analysis and quantification of PANoptosis-related proteins in AFCs treated with Con, TNF-α, TNF-α+Lv-ctrl, and TNF-α+Lv-TLR4. (I) TUNEL staining detecting AFCs apoptosis in Con, TNF-α, TNF-α+Lv-ctrl, and TNF-α+Lv-TLR4 groups. Scale bar = 40 μm. (J) Statistical analysis of TUNEL-positive apoptotic AFCs in (I). (K) Representative flow cytometry scatter plots detecting AFCs apoptosis in Con, TNF-α, TNF-α+Lv-ctrl, and TNF-α+Lv-TLR4 groups. (L) Statistical analysis of apoptotic AFCs in (K) determined by flow cytometry (n=3). (M and N) Western blot analysis and quantification of PANoptosis-related proteins in AFCs treated with Con, TEA, TEA+Lv-ctrl, and TEA+Lv-NLRP12. (O) TUNEL staining detecting AFCs apoptosis in Con, TEA, TEA+Lv-ctrl, and TEA+Lv-NLRP12 groups. Scale bar = 40 μm. (P) Statistical analysis of TUNEL-positive apoptotic AFCs in (O). (Q) Representative flow cytometry scatter plots detecting AFCs apoptosis in Con, TEA, TEA+Lv-ctrl, and TEA+Lv-NLRP12 group. (R) Statistical analysis of apoptotic AFCs in (Q) determined by flow cytometry (n=3). **p < 0.01; ***p < 0.001; ****p < 0.0001; ns indicates not significant.

To further validate the involvement of TLR4, AFCs were infected with TLR4 knockdown (KD) lentivirus. WB showed that PANoptosis-related protein levels were significantly reduced in the KD group compared to the LV-ctrl group (Figure 4G and H). Consistently, TUNEL and FC analysis demonstrated decreased apoptosis following TLR4 silencing (Figure 4I–L). These findings suggest that TLR4 promotes PANoptosis in AFCs.

Among known PANoptosome inducers, ZBP1-, AIM2-, and NLRP12-mediated complexes have been identified.¹⁸ ZBP1 and AIM2 are typically activated by viral stimuli, which are absent in the intervertebral disc environment.^19,20 Previous work by Sundaram et al demonstrated that TLR4 functions upstream of NLRP12 to promote PANoptosome assembly.⁵ Based on this, we hypothesized that TLR4 may induce PANoptosis in degenerative AFCs via NLRP12. This hypothesis was supported by our transcriptomic heatmap, which showed increased expression of NLRP12-related genes in degenerative AFCs (Figure S1B). To verify the role of NLRP12, AFCs were treated with TLR4 agonist-1 (TEA), a potent TLR4 activator, with or without NLRP12 KD. WB showed that TEA significantly upregulated PANoptosis-related proteins, consistent with our earlier findings (Figure 4M and N). Notably, NLRP12 KD markedly suppressed the TEA-induced expression of these proteins compared to the TEA and TEA+LV-ctrl groups, indicating that TLR4 promotes PANoptosis through NLRP12 in AFCs. Consistent with the WB findings, TUNEL and FC analyses showed similar trends (Figure 4O–R). These findings confirm that TLR4 induces PANoptosis in AFCs through activation of NLRP12.

Inhibition of TLR4 Ameliorates IVDD in Rat Model

To evaluate the role of TLR4 in AF degeneration in vivo, lentiviral-mediated TLR4 knockdown was performed in rat AF tissue. X-ray imaging showed that TLR4 KD significantly alleviated disc height loss induced by acupuncture compared to the LV-ctrl group (Figure 5A and E).

Figure 5 Inhibition of TLR4 Ameliorates IVDD in Rat Models. (A) X-ray images of intervertebral discs in rats subjected to different treatments. Disc heights are highlighted with red box. (B) H&E staining of intervertebral disc tissues from rats with various treatments. Scale bar = 500 μm. (C) SOFG staining of intervertebral disc tissues from rats with different treatments. Scale bar = 500 μm. (D) TUNEL staining of intervertebral disc tissues from rats under various treatments. Scale bar = 800 μm. (E) Quantitative analysis of DHI% (Disc Height Index percentage) based on X-ray results. (F) Histological score analysis of different treatments. (G) The ratio of apoptotic cells in AF tissue of rats shown by TUNEL staining. **p < 0.01; ***p < 0.001; ****p < 0.0001; ns indicates not significant.

H&E staining revealed that TLR4 KD preserved the lamellar structure of the AF and reduced NP shrinkage, resulting in improved histological scores compared to the IVDD rats with LV-ctrl (Figure 5B and F). SO/FG staining indicated that GAG content, which was reduced in the IVDD group, was restored after TLR4 knockdown (Figure 5C). TUNEL staining showed increased apoptosis in IVDD discs, which was markedly reduced following TLR4 silencing (Figure 5D and G).

Collectively, these in vivo data demonstrate that suppressing TLR4 alleviates disc degeneration, further corroborating the critical role of TLR4 in regulating AF PANoptosis during IVDD. A schematic diagram of PANoptosis induced by TLR4-NLRP12 activation in degenerative AFCs is shown in Figure 6.

Figure 6 Schematic diagram of TLR4 induces annulus fibrosus cells PANoptosis via NLRP12 in IVDD.

Discussion

In this study, we systematically explored the role of TLR4 signaling in AFCs during IVDD. scRNA-seq analysis revealed an increased proportion of fibroblast-like AFC subtypes and transcriptional enrichment of pyroptosis and apoptosis pathways in degenerative discs. Functional experiments showed that TNF-α stimulation induced activation of PANoptosis in AFCs, as evidenced by upregulation of cleaved-Caspase-1, cleaved-Caspase-3, MLKL, p-MLKL, and c-GSDMD, along with formation of PANoptosome structures. Transcriptomic analysis further identified TLR4 as a key upstream regulator, acting via NLRP12. In vivo, TLR4 knockdown mitigated disc degeneration and reduced PANoptosis in AFCs. Collectively, our findings indicate that PANoptosis occurs in degenerative AFCs, regulated by the TLR4-NLRP12 axis. To our knowledge, this is the first study to implicate PANoptosis as a relevant mode of cell death in AFCs during IVDD, providing novel insights into the degenerative process of the disc.

Recent studies have applied scRNA-seq to explore cellular heterogeneity in IVDD, with most focusing on NP samples.^21,22 These analyses have identified key immune, stromal, and degenerative cell populations involved in disc pathology. We reanalyzed the scRNA-seq dataset GSE230809, which included 3 healthy and 10 degenerative AF samples. After standard quality control and batch integration, 43,421 cells were retained for downstream analysis. Based on canonical markers reported in previous studies, we performed cell clustering and identified five distinct AFC subtypes: Fibro-AFCs, Chon-AFCs, Homeo-AFCs, Adh-AFCs, and Reg-AFCs. Among these, Fibro-AFCs were significantly enriched in IVDD samples and were closely associated with extracellular matrix remodeling and fibrosis. To further explore the biological changes in degenerative AF tissue, we performed GO and KEGG enrichment analyses using the ClusterProfiler package. GO terms enriched in the degenerative group included “cell-cell adhesion”, “myofibril assembly”, and “pyroptosis”, while KEGG analysis highlighted pathways such as apoptosis, ECM-receptor interaction, and NF-κB signaling. Notably, both analyses revealed strong enrichment in cell death-related pathways, raising the possibility that PANoptosis may be involved in the degenerative process.

To evaluate the activation of programmed cell death pathways in degenerative AFCs, we calculated apoptosis, pyroptosis, and necroptosis scores using gene set-based module scoring. All three scores were significantly elevated in the degenerative group, suggesting simultaneous activation of multiple cell death programs. To further explore the temporal dynamics of these processes, we conducted pseudotime trajectory analysis using the Monocle3 package. This method, commonly used in scRNA-seq studies, enables inference of gene expression changes along a simulated degenerative trajectory. Our analysis revealed that Adh-AFCs were positioned at early pseudotime stages, while Fibro-AFCs were predominantly enriched at later stages, indicating that PANoptosis may occur in terminally activated AFC subsets. We next evaluated the expression patterns of RIPK1, RIPK3, NLRP3, and ASC-core components of the PANoptosome.²³ RIPK1 and RIPK3 are central to necroptotic signaling and can engage in PANoptotic complexes through interactions with Caspase-8.²⁴ NLRP3, a canonical inflammasome sensor, and ASC, an adaptor protein essential for inflammasome assembly, are also critical for PANoptosis execution.^25,26 Our pseudotime analysis revealed that these genes were significantly upregulated in late-stage AFCs, further supporting the involvement of PANoptosis in degenerative progression.

To mimic the inflammatory environment observed in degenerative AF tissue, we treated AFCs with TNF-α, a pro-inflammatory cytokine previously reported to participate in disc degeneration and immune-related matrix remodeling.^27,28 Upon stimulation, WB analysis revealed increased expression of cleaved-Caspase-1, cleaved-Caspase-3, p-MLKL, and c-GSDMD, which are canonical executioner molecules of pyroptosis, apoptosis, and necroptosis, respectively.^6,29 These results confirmed the activation of PANoptosis under degenerative-like stimulation. To further assess the assembly of PANoptosomes, IF staining was performed to detect Caspase-8, RIPK3, and ASC, which have been identified as core components of the PANoptosome complex in other inflammatory or infectious contexts.⁶ Colocalization of these markers in TNF-α-treated AFCs supported the presence of functional PANoptosome aggregates, providing morphological evidence of PANoptosis. To gain insight into global transcriptomic changes induced by TNF-α, we conducted bulk RNA-seq analysis. AFCs were grouped into TNF-α-treated and control conditions. GO and KEGG enrichment analyses showed that TNF-α treatment upregulated genes involved in apoptosis, inflammasome activation, ECM-receptor interaction, and Toll-like receptor signaling, suggesting enhanced activation of inflammatory and cell death pathways. Reactome pathway analysis further highlighted enrichment in the activated TLR4 signaling cascade, implicating TLR4 as a key upstream modulator. To validate these findings, we performed GSEA on representative gene sets, including apoptosis, TLR signaling, and activated TLR4 signaling. These pathways were significantly enriched in the TNF-α-treated group, confirming that TLR4-driven signaling is a potential upstream regulator of PANoptosis in AFCs.

To confirm the upstream regulatory role of TLR4 in AFC PANoptosis, we first employed RKH acetate, a selective TLR4 inhibitor. WB, TUNEL, and flow cytometry results demonstrated that inhibition of TLR4 markedly reduced the expression of PANoptosis-related proteins and attenuated cell death in TNF-α-treated AFCs. To further validate these findings, we constructed a TLR4-knockdown lentiviral vector. Consistently, TLR4 silencing led to decreased levels of cleaved-Caspase-1, cleaved-Caspase-3, p-MLKL, and c-GSDMD, along with reduced TUNEL-positive and apoptotic cell populations. These results confirm that TLR4 contributes directly to PANoptosis induction in AFCs.

PANoptosis is executed via the formation of PANoptosomes-multiprotein complexes composed of key molecules such as ASC, RIPK3, and Caspase-8. Recent studies have defined three PANoptosome complexes with distinct sensors and regulators: ZBP1-, AIM2-, and NLRP12-mediated complexes.³⁰ ZBP1- and AIM2-associated PANoptosis are generally activated in response to viral or microbial components, which are largely absent in the IVD microenvironment.³¹ Based on this, we hypothesized that NLRP12 may be the dominant initiator of PANoptosome formation in AFCs. Transcriptomic analysis revealed that only NLRP12 was significantly upregulated in degenerative conditions, while ZBP1 and AIM2 showed no notable changes. To further evaluate the role of NLRP12, we performed rescue experiments using TEA, a potent TLR4 agonist. While TEA alone induced robust upregulation of PANoptosis-related proteins, co-treatment with NLRP12 knockdown markedly attenuated this response. Together, these data suggest that aberrant activation of the TLR4-NLRP12 axis may be a detrimental driver of AFC death and IVDD progression through PANoptosome assembly.

To validate TLR4 function in vivo, we knocked down TLR4 in a rat AF puncture model. TLR4 silencing alleviated disc height loss, preserved AF structure, and restored GAG content. TUNEL staining showed reduced apoptosis, indicating protective effects against cell death. These findings support that TLR4 contributes to IVDD progression by promoting AFC degeneration. Combined with our in vitro data, we propose that aberrant TLR4 activation induces PANoptosis via NLRP12, exacerbating disc degeneration. This pathological mechanism is summarized in Figure 6.

Although TLR4 knockdown alleviated disc degeneration in vivo, the findings were primarily based on rodent models and in vitro assays. The needle puncture model utilized in this study, while effective, induces mechanical injury in nature. It should be noted that the invasive nature of this intervention can elicit inflammatory responses.³² Human-derived AFCs and clinical tissue samples were not included, which limits the translational relevance of the conclusions. Additionally, while our data support the involvement of the TLR4-NLRP12 axis in PANoptosis, the complexity of disc degeneration may involve additional regulatory pathways not addressed in this study. In future studies, we will aim to validate these findings in human IVD tissues and further explore their therapeutic potential.

Conclusion

Our study is the first to identify the occurrence of PANoptosis and PANoptosome formation in AFCs. We demonstrated that TLR4 promotes PANoptosis in AFCs through NLRP12 activation, contributing to IVDD progression, while TLR4 knockdown alleviates disc degeneration. These findings suggest that TLR4 may serve as a potential therapeutic target for IVDD.

Data Sharing Statement

All data and materials are included in this manuscript.

Ethics Approval

The animal study protocol was approved by the Ethics Committee of Qinghai Provincial People’s Hospital (protocol code: KYLs (2024)-073, January 2024). All procedures were performed in accordance with the 3R principles (Replacement, Reduction, Refinement) to minimize animal suffering. For the scRNA-seq data analysis, since we utilized a publicly available dataset where all personally identifiable information had been anonymized by the data provider, this study was granted an exemption from ethical approval by the Ethics Committee of Qinghai Provincial People’s Hospital.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This work was supported by 2022 Kunlun Talents of Qinghai Province High-end Innovation and Entrepreneurship – Cultivate Leading Talents Project [QHKLYC-GDCXCY-2022-058] and the Health Committee Key Project in Qinghai Province [2022-wjzd-02].

Disclosure

The authors report no conflicts of interest in this work.

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East Midlands Gateway – Christopher Cook, currently Managing Director of Maersk’s India, Bangladesh & Sri Lanka Area, will take over as the new Managing Director of UK & Ireland Area with the start of the new year.

The British national joined Maersk as a trainee in 2002 and has worked over the last two decades across Africa, Europe, Middle East and India with both Damco and Maersk. Christopher Cook has spent the last 7 years in the IMEA region, initially as Managing Director in the UAE Area, successfully leading the integration and transformation of the business there. Most recently, he served as Managing Director for IBS Area where he has operationalised the long-term strategy for the Area, deepened the operational execution capability and lifted the profitability with successful growth across the portfolio.

I am very pleased to welcome Chris to our Region Europe leadership team as our new head of UK and Ireland Area. Chris is no stranger to the UK and brings a strong customer focus. He is also known for his passion about people and developing strong culture in the organisations he leads.

About Maersk

A.P. Moller – Maersk is an integrated logistics company working to connect and simplify its customers’ supply chains. As a global leader in logistics services, the company operates in more than 130 countries and employs around 100,000 people. Maersk is aiming to reach net zero GHG emissions by 2040 across the entire business with new technologies, new vessels, and reduced GHG emissions fuels*.

*Maersk defines “reduced GHG emissions fuels” as fuels with at least 65% reductions in GHG emissions on a lifecycle basis compared to fossil of 94 g CO2e/MJ.

Asian and European equities were mixed Monday with investors awaiting the release of key US data that could play a role in Federal Reserve deliberations ahead of an expected interest rate cut next week.

After November’s end-of-month rebound across world markets, confidence remains high amid speculation the US central bank could continue easing monetary policy into the new year.

That has helped overcome lingering worries about an AI-fuelled tech bubble that some observers warn could pop and lead to a painful correction.

While the odds on a third successive rate reduction on December 10 are hovering around 90 percent, traders will keep a close eye on this week’s batch of indicators to gauge the Fed’s desire to keep on cutting.

Among the reports due for release are private jobs creation, services activity and personal consumption expenditure — the Fed’s preferred gauge of inflation.

Bets on a cut surged in late November after several of the bank’s policymakers said they backed lower borrowing costs as they were more concerned about the flagging labour market than stubbornly high inflation.

That helped markets recover the losses sustained in the first half of the month, and analysts said they could be in store for an end-of-year rally.

“As the clouds of worry that cast an ominous shadow over markets through to mid-November gently dissipate, they give way to new emotions — notably the fear of not participating and the risk of underperforming benchmark targets,” said Pepperstone’s Chris Weston.

However, he warned that “risk managers remain highly astute to the landmines that could still derail the improving risk backdrop through December”.

He cited the possibility the Fed does not cut, or offers a “hawkish cut”, the Supreme Court’s possible decision on the legality of President Donald Trump’s trade tariffs, and jobs and inflation data.

Meanwhile, reports that Trump’s top economic adviser Kevin Hassett — a proponent of rate cuts — is the frontrunner to take the helm at the Fed next year added to the upbeat mood.

After last week’s healthy gains and Wall Street’s strong Thanksgiving rally, Asian equities were mixed.

Hong Kong, Shanghai, Singapore and Bangkok rose, but Sydney, Seoul, Wellington, Manila, Mumbai and Taipei dipped.

London, Frankfurt and Paris fell at the open.

Tokyo sank 1.9 percent as the yen strengthened on expectations the Bank of Japan will lift interest rates this month.

Governor Kazuo Ueda said it would “consider the pros and cons of raising the policy interest rate and make decisions as appropriate”, with Bloomberg saying traders saw a more than 60 percent chance of a move on December 19. That rose to 90 percent for a hike no later than January.

Masamichi Adachi, UBS Securities chief economist for Japan, wrote: “The BoJ is likely to hike its policy rate at the December 19 meeting. Recent remarks and reports… suggest groundwork for a rate hike is underway, with market probability exceeding 50 percent.”

But he said the yen would likely remain under pressure against the dollar, adding that Prime Minister Sanae Takaichi’s “preference for negative real rates may pressure (the) yen further”.

Oil prices surged around two percent after OPEC+ confirmed it would not hike output in the first three months of 2026, citing lower seasonal demand.

The decision comes amid uncertainty over the outlook for crude as traders look for indications of progress in Ukraine peace talks, which could lead to the return of Russian crude to markets.

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