BACKGROUND:Osteoarthritis (OA) is an age-related degenerative joint disease for which there are no effective therapies. Although electroacupuncture (EA) has emerged as a potentially effective therapeutic intervention for OA, the underlying mechanisms are not yet fully understood. Cartilage-derived stem/progenitor cells (CSPCs) are known to play a critical role in cartilage repair; however, whether CSPCs contribute to the therapeutic effects of EA has not been well characterized. Accordingly, this study aimed to investigate the involvement of CSPCs in mediating the therapeutic efficacy of EA in OA and to explore the associated mechanisms. METHODS:CSPCs (CD44+CD90+CD45-) obtained from cartilage specimens of OA mice in EA or control groups were examined based on bulk RNA sequencing. Molecules involved in the functions of CSPCs were investigated through in vitro and in vivo experiments. The effects of fibroblast growth factor receptor 4 (FGFR4) on CSPCs proliferation induced by EA were determined via intraarticular injection of adenoviruses (AAVs) with the targeted inhibition of FGFR4 in chondrocytes of Gremlin 1-creERT mice. Immunofluorescence, immunohistochemistry, Western blot, chromatin immunoprecipitation, and luciferase reporter analyses were used for determining the associated molecular and cellular mechanisms. RESULTS:Our results indicated that EA intervention alleviated pain behaviors and cartilage degeneration in OA mice, along with upregulated proliferation of CSPCs. An EA-induced increment of FGFR4 played a protective role by inducing CSPCs proliferation. The targeted inhibition of FGFR4 in CSPCs suppressed the efficacy of EA treatment in OA mice. Mechanistically, EA intervention may promote the proliferation of CSPCs via activation of the Ca2+/phosphorylated-calmodulin-dependent protein kinase II (p-CaMKII)/signal transducer and activator of transcription 3 (STAT3) signaling pathway. Moreover, FGFR4 expression was induced via direct binding of STAT3 on the Fgfr4 promoter in CSPCs following EA intervention in OA mice. CONCLUSIONS:Our findings in this study provide valuable insights into the molecular and cellular mechanisms underlying the effects of EA on pain and cartilage degeneration in OA mice. EA may enhance CSPCs' function via the Ca2+/STAT3/FGFR4 signaling pathway in the OA mice model, providing possible novel targets for treating chronic aging-related OA diseases.

BackgroundElectroacupuncture is widely accepted to treat pain related conditions, but detailed mechanisms remain unknown.ObjectiveTo explore cortical and subcortical subnuclei involved in electroacupuncture stimulation (EAS) analgesia by observing EAS's analgesic efficacy and c-fos expression changes, providing a basis for neural circuit research and clinical transcranial magnetic stimulation (TMS) therapy.Design, setting, participants and interventionsA chronic inflammatory pain model was established using knee osteoarthritis (KOA). Bilateral Zusanli was selected for electroacupuncture intervention. Von Frey test, open field test, elevated plus maze, and tail suspension test, and immunohistochemical staining were performed.Main outcomes measuresChanges in mechanical pain threshold and pain-related emotional behaviors and distribution of c-fos positive cells in cortical and subcortical nuclei.ResultsElectroacupuncture significantly increased mechanical pain thresholds in KOA model mice. KOA modeling caused c-fos downregulation in the motor cortex, insular cortex, secondary auditory cortex, dorsal peduncular cortex, temporal association cortex, caudate putamen, lateral septal nucleus, accumbens nucleus, and the anterior cortical amygdaloid area. Electroacupuncture at Zusanli reversed these changes, upregulating c-fos in abovementioned brain regions, and additionally upregulated c-fos expression in the granular insular cortex, extended amydala.ConclusionInflammatory pain induces widespread inhibition of neuronal activity in cortical and subcortical nuclei. The core mechanisms of electroacupuncture analgesia may involve direct reversal of abnormal inhibition in the lateral septal nucleus, caudate putamen, accumbens nucleus, and the anterior cortical amygdaloid area and activation of the granular insular cortex, medial septal nucleus and the extended amygdala for pain information integration.

Mechanical allodynia, a manifestation of neuropathic pain, affects patients' well-being. Our previous research identified a spinal "allodynia gate" involving glycinergic (Gly) inhibitory and protein kinase Cγ (PKCγ) excitatory neurons. Nerve injury disrupts this circuit, leading to allodynia. However, the disinhibition mechanisms remain unclear. Here, genetically modified mouse lines were used to demonstrate that nerve injury triggers endocannabinoid (eCB) release from PKCγ neurons, activating cannabinoid receptor 1 (CB1R) bound to glycine transporter 2 (GlyT2) in Gly neurons, upregulating GlyT2 function and reducing synaptic glycine levels, thus causing circuit disinhibition. Dysfunction in this circuit enables low-threshold Aβ-primary inputs to activate PKCγ neurons, propagating signals to the nociceptive pathway. The peptide Tat-STVKIAK-KFERQ, capable of degrading GlyT2 and thus disrupting the CB1R-GlyT2 interaction, effectively prevents and alleviates nerve-injury-induced mechanical allodynia. Overall, our study systematically elucidates the organization and function of the spinal allodynia gate, developing a peptide drug targeting this gate to mitigate mechanical pain.

ABSTRACT Neuropathic pain (NP) affects 7%–10% of population, with current treatments often proving inadequate. Here we show that Na v 1.7 and Na v 1.8 form supramolecular active complexes (SMACs) with polygonal lattice structure in dorsal root ganglion (DRG) neurons of mouse models and patients with severe chronic NP. TrkB signaling facilitates the formation of Na v 1.7/Na v 1.8 SMACs. Targeting these SMACs with combined Na v 1.7 and Na v 1.8 blockers inhibits action potentials of both human and mouse pathological DRG neurons and synergistically alleviates chronic NP in spared nerve injury (SNI) and diabetic mouse models. The SMAC formation is promoted by five cytoskeletal proteins (SPTAN1, DSP, AHNAK, MPZ and PRX). Functional study demonstrates that these SMACs create a Na + potential difference to amplify sodium currents, promoting DRG neuron hyperexcitability. Moreover, knockdown of these five cytoskeletal proteins prevents action potential generation in DRG neurons and eliminates NP in SNI mice. Our findings support that SMACs can be a potential pathological hallmark and novel promising therapeutic target for severe chronic NP.

Drug detection is highly important, yet reversible and highly sensitive sensing materials are still scarce. A novel ionogel sensor material, poly(ethylene glycol) diacrylate (PEGDA)/1-butyl-3-methylimidazole tetrafluoroborate, was developed for reproducible N-methylphenylethylamine (MPEA) detection. It was fabricated by immobilizing a flowable ionic liquid within a PEGDA network via UV curing. The immobilized ions retain mobility, enabling efficient ionic conduction. Integrated on a flexible poly(ethylene naphthalate) substrate, the sensor is fully transparent and flexible, showing over 72.6% transmittance in the visible spectrum. This allows it to be discreetly attached to surfaces for concealed detection. Using non-covalent interactions, the sensor achieves reproducible MPEA detection at sub ppb levels at room temperature, with a theoretical detection limit of 317 ppt. It also exhibits high selectivity and consistency. Ionic conductivity was confirmed through current voltage tests and impedance spectroscopy, and the sensing mechanism was clarified. The device performs reliably under bending, proving suitable for dynamic environments. With a Bluetooth module for wireless transmission, the sensor shows strong potential for practical and discreet drug monitoring in real world applications.

Background: Postoperative neurocognitive disorders (PND) are frequent complications in the elderly surgical patients, with aging recognized as a major risk factor. This study aimed to identify electrophysiological markers and establish an exploratory machine learning framework for PND-related vulnerability prediction using anesthetic electroencephalography (EEG) features in aged mice. Methods: Young and aged mice underwent laparotomy under isoflurane anesthesia with EEG recording. Neurocognitive performance was quantified by 16 standardized behavioral fractions. A semi-supervised K-means algorithm, anchored on young-surgery mice, stratified aged-surgery mice into PND and non-PND clusters. EEG dynamics during anesthesia maintenance and emergence were analyzed, and machine learning models were trained to predict PND from EEG features. Results: At baseline, neurocognitive function was comparable across groups. After anesthesia/surgery, aged mice exhibited selective spatial and contextual memory impairments, with two-thirds classified as PND. During emergence, PND mice displayed elevated δ power and reduced α and β ratios. A Multi-layer Perceptron classifier showed discriminatory performance for PND classification in one evaluation setting (AUC = 0.94). Conclusions: This study identifies emergence-related EEG features associated with postoperative neurocognitive vulnerability in aged mice and provides an exploratory machine learning framework for preclinical risk stratification. These findings support further mechanistic investigation and warrant future validation in human perioperative EEG datasets.

Perioperative neurocognitive disorder (PND) is one of the most prevalent neurological complications in elderly surgical patients. Dysregulated lipid metabolism is a hallmark of aging and is strongly associated with cognitive dysfunction. This study aimed to investigate whether ω-6 polyunsaturated fatty acid (PUFA) metabolism contribute to PND and examined whether fatty acid desaturase 1 (FADS1) represents a key regulatory link between fatty acid metabolism and PND in aged mice. An anesthesia/surgery-induced cognitive dysfunction model was established via laparotomy in 18-month-old C57BL/6J mice under 1.4

Accurate quantification of structurally similar metabolites as biomarkers in biofluids has remained a longstanding challenge. Here, we report a semiconductor-organic hybrid interface (ZrS2@ZrOx-C16) with a triple-gated molecular recognition environment for high-specificity detection of lysophosphatidylcholine (16:0) (LysoPC (16:0)), which is identified as a potential biomarker associated with aging and cognitive decline. Through integrating phosphocholine-selective Zr-O-P coordination, chain-length-matched hydrophobic free-energy minimization, and a dual-resonant charge-transfer pathway, ZrS2@ZrOx-C16 affords molecular-level discrimination among lysophospholipids with nearly identical chemical structures, enabling amplified and selective quantitative Raman signals. Coupled with machine-learning extraction of Raman fingerprints, ZrS2@ZrOx-C16 achieves rapid, label-free quantification with an accuracy of R2 = 0.999 across human and mouse serum samples, allowing precise mapping of LysoPC (16:0) deficits as a biomarker and therapeutic target across aging, Alzheimer's disease, and perioperative neurocognitive impairment. This work establishes a framework for precision lipid analytics and high-selectivity metabolic sensing, enabling mechanistic insights in neurometabolic biology.

Neuropathic pain (NP) affects 7%-10% of population, with current treatments often proving inadequate. Here we show that Nav1.7 and Nav1.8 form supramolecular active complexes (SMACs) with polygonal lattice structure in dorsal root ganglion (DRG) neurons of mouse models and patients with severe chronic NP. TrkB signaling facilitates the formation of Nav1.7/Nav1.8 SMACs. Targeting these SMACs with combined Nav1.7 and Nav1.8 blockers inhibits action potentials of both human and mouse pathological DRG neurons and synergistically alleviates chronic NP in spared nerve injury (SNI) and diabetic mouse models. The SMAC formation is promoted by five cytoskeletal proteins (SPTAN1, DSP, AHNAK, MPZ and PRX). Functional study demonstrates that these SMACs create a Na+ potential difference to amplify sodium currents, promoting DRG neuron hyperexcitability. Moreover, knockdown of these five cytoskeletal proteins prevents action potential generation in DRG neurons and eliminates NP in SNI mice. Our findings support that SMACs can be a potential pathological hallmark and novel promising therapeutic target for severe chronic NP.

BackgroundAlzheimer’s disease (AD) and Mild Cognitive Impairment (MCI) pose significant societal and healthcare burden. Artificial intelligence (AI) methods have been widely applied in AD and MCI studies. We conducted a bibliometric analysis of the 100 most cited articles on AI applied to AD and MCI.MethodsWe searched the Web of Science database using keywords related to AD, MCI, and AI (e.g., “deep learning,” “machine learning,” “neural networks”). Citation counts ranked articles, and the top 100 were manually screened. Key parameters such as authors, journals, citation count, countries, institutions, and keywords were automatically extracted. We also manually extracted key information, including publication type, impact factor (IF), Journal Citation Reports (JCR) Category Quartile, AI methods, and clinical data types. Analysis and visualization were conducted using VOSviewer.ResultsAmong the 100 articles, 13 were reviews, 2 were basic research papers, and 85 were clinical studies. Seventy seven articles focused on diagnosis and prediction. MRI data was the most frequently used analysis source. Shen Dinggang, the United States, and the University of North Carolina at Chapel Hill were respectively the individual, country, and institution with the highest publication volume. Neuroimage published the most papers (n = 14), and all the top 10 journals belonged to JCR Q1. Emerging keywords included “ensemble learning,” “transfer learning,” and “structural MRI.” Support Vector Machine (SVM) was the most commonly applied AI method (n = 25), closely followed by convolutional neural network (CNN, n = 24).ConclusionWe analyzed the top 100 cited articles on AI in AD and MCI across authors, journals, countries, institutions, keywords, and AI methods. Diagnosing AD/MCI is the primary research focus, with MRI as the most studied examination. SVM and CNN are the most frequently used AI methods in these studies.

Plant-derived extracellular vesicles (PDEVs) have emerged as a promising cell-free therapeutic paradigm in regenerative medicine, particularly for managing the impaired healing associated with diabetic foot ulcers. Grounded in the need for evidence-based clinical translation, this study employed a systematic review and meta-analysis to evaluate the preclinical efficacy and safety of PDEVs in diabetic wound models. A comprehensive search across PubMed, Web of Science, and Embase through May 10, 2026, identified 20 eligible studies, which were rigorously assessed using the SYRCLE risk-of-bias tool and CAMARADES checklist. Random-effects meta-analyses were performed for wound healing rate, angiogenesis, and collagen deposition. Quantitative synthesis demonstrated that PDEVs significantly improved wound healing rate across early (SMD = 2.45, 95% CI: 1.63-3.27, p < 0.00001), mid (SMD = 1.75, 95% CI: 1.15-2.36, p < 0.00001), and late stages (SMD = 1.54, 95% CI: 0.14-2.94, p = 0.03), while markedly enhancing angiogenesis (SMD = 2.13, 95% CI: 1.35-2.91, p < 0.00001) and collagen deposition (SMD = 2.49, 95% CI: 1.83-3.15, p < 0.00001). Qualitative evidence further suggested that PDEVs improve the diabetic wound microenvironment by modulating macrophage polarization, attenuating excessive inflammation, restoring endothelial function, promoting re-epithelialization, and facilitating extracellular matrix remodeling. Sensitivity analyses generally supported the robustness of the main findings, although late-stage wound healing and several subgroup results were influenced by individual studies. No serious adverse events were reported in the subset of studies that assessed them; however, safety evaluations were incomplete across included studies and largely limited to short-term observation. Overall, PDEVs show promising preclinical potential for diabetic wound repair, but current evidence remains preliminary due to constrained sample sizes, suboptimal reporting of randomization, and unstandardized quality control. Future studies should adopt rigorous experimental designs, standardized source documentation, scalable manufacturing, potency assays, and systematic toxicological evaluation to support clinical translation.

Perioperative neurocognitive disorder (PND) is a significant neurological complication in aging perioperative patients that impacts post-operative cognition. PND is currently diagnosed through cognitive function testing, which is limited by its subjectivity and time requirements. Thus, the identification of biomarkers to assess PND onset is a priority to identify at-risk individuals and enable interventions and treatments to patient outcomes. This article synthesizes expert perspectives on brain aging and PND, presents the latest clinical evidence on PND biomarkers (imaging, electroencephalography, and molecular biomarkers), and delves into the relationship between PND and other age-related cognitive disorders. Thorough review of PND research identified several biomarkers with high sensitivity and specificity, offering a solid scientific foundation to predict and diagnose PND. These biomarkers not only enhance diagnostic accuracy for clinicians but also provide opportunities for earlier intervention and more effective treatment, potentially enhancing patient outcomes and quality of life.

Neurological injuries and diseases are a leading cause of disability worldwide, underscoring the urgent need for effective therapies. Neural regaining and enhancement therapies are seen as the most promising strategies for restoring neural function, offering hope for individuals affected by these conditions. Despite their promise, the path from animal research to clinical application is fraught with challenges. Neuroengineering, particularly through the use of biomaterials, has emerged as a key field that is paving the way for innovative solutions to these challenges. It seeks to understand and treat neurological disorders, unravel the nature of consciousness, and explore the mechanisms of memory and the brain's relationship with behavior, offering solutions for neural tissue engineering, neural interfaces and targeted drug delivery systems. These biomaterials, including both natural and synthetic types, are designed to replicate the cellular environment of the brain, thereby facilitating neural repair. This review aims to provide a comprehensive overview for biomaterials in neuroengineering, highlighting their application in neural functional regaining and enhancement across both basic research and clinical practice. It covers recent developments in biomaterial-based products, including 2D to 3D bioprinted scaffolds for cell and organoid culture, brain-on-a-chip systems, biomimetic electrodes and brain-computer interfaces. It also explores artificial synapses and neural networks, discussing their applications in modeling neural microenvironments for repair and regeneration, neural modulation and manipulation and the integration of traditional Chinese medicine. This review serves as a comprehensive guide to the role of biomaterials in advancing neuroengineering solutions, providing insights into the ongoing efforts to bridge the gap between innovation and clinical application.

ABSTRACT Introduction Cerebrospinal fluid Aβ42 has been proposed as a potential indicator for cerebral β‐amyloidosis and may be involved in the pathophysiology of delirium. Whether perioperative plasma Aβ42 alternation is associated with postoperative delirium risk among elderly patients remains unknown. Methods This was a secondary analysis of a randomized controlled trial evaluating the effects of acupuncture (intervention) compared to standard care (control) on the incidence of delirium in patients undergoing major abdominal surgery. Participants with blood samples collected were included in this cohort study. The exposure variable was the Aβ42 ratio, calculated with the plasma Aβ42 level immediately after surgery divided by the preoperative plasma Aβ42 level. The primary endpoint was the occurrence of delirium within the first 7 days following surgery or until hospital discharge, whichever happened first, evaluated using either the Confusion Assessment Method or the Confusion Assessment Method‐intensive care unit for intubated patients. Delirium severity was a secondary outcome assessed by the Memorial Delirium Assessment Scale. The logistic regression models and a restricted cubic spline were performed to examine the association between the Aβ42 ratio and delirium incidence, with receiver operating characteristic curve (ROC) analysis for diagnostic power. The mediation effects of the matrix metalloproteinase‐9 ratio were further explored by causal mediation analysis. The linear regression and generalized linear mixed models assessed the association between the Aβ42 ratio and delirium severity. Results A total of 195 patients with blood samples collected were included in the final analysis. Among them, the mean age was 70.2 ± 4.2 years; 134 were female (68.7%), and 26 (13.3%) patients experienced postoperative delirium. The plasma Aβ42 ratio was positively correlated with an increased delirium risk (adjusted odds ratio 3.21, 95% confidence interval 1.71–6.05, p < 0.001) and delirium severity, as measured by the highest postoperative Memorial Delirium Assessment Scale score (adjusted β coefficient 3.04, 95% confidence interval 0.9–5.18, p = 0.006) in the fully adjusted multivariable analysis models. The restricted cubic spline indicated a linear relationship between the plasma Aβ42 ratio and delirium incidence (p = 0.202). The ROC showed that the area under the curve for the Aβ42 ratio to predict delirium risk was 0.698 (95% CI, 0.582–0.814), with the optimal cut‐off point of 0.137. Mediation analyses showed that the Aβ42 ratio does not mediate postoperative delirium through the matrix metalloproteinase‐9 ratio (proportion: 1.3%). Conclusions This cohort study showed that a higher Aβ42 ratio was associated with an increased delirium risk and severity, and the association was linear. The plasma Aβ42 ratio might be a mini‐invasive biomarker to identify postoperative delirium.

Postpartum depression (PPD) affects maternal mental health extensively and is challenged by the lack of objective diagnostic methods. This study aimed to explore the characteristics of niacin skin flush response, a diagnostic marker for depression, in individuals with PPD and to determine its clinical potential as an adjunctive screening marker. A total of 1417 parturients was recruited in this study. Edinburgh Postnatal Depression Scale was used to screen for depression with a cut-off score ≥ 13. The Patient Health Questionnaire-9 scale was used to test the consistency of scale screening. The Chi-square test was used to compare the screening results of the two scales, and the reliability and validity of the two scales were discussed. Mann Whitney U test was used to analyze the differences in niacin-flushing between PPD and healthy controls (HC), and a ten-fold cross-validation with logistic regression was used to verify the potential of niacin-flushing to distinguish between PPD and HC. A screening model for women with PPD was established by bivariate truncation method. The results of the two depression screening scales were 12.85

Chronic itch remains a clinically challenging condition with limited therapeutic efficacy, posing a significant burden on patients' quality of life. Despite its prevalence, the underlying neural mechanisms remain poorly understood. In this study, we explored the synaptic relationships between neuropeptide Y (NPY) neurons and gastrin-releasing peptide receptor (GRPR) neurons in the spinal cord. Our findings reveal a direct synaptic connection whereby Npy neurons provide inhibitory modulation to Grpr neurons. Notably, during chronic itch, the activity of Grpr neurons was significantly elevated, coinciding with a decrease in Y1 receptor expression and a reduction in both the frequency and amplitude of inhibitory postsynaptic currents (IPSCs). These results suggest a decline in NPY/Y1R system function during chronic itch, leading to a decreased inhibitory influence of Npy neurons on Grpr neurons and subsequent disinhibition and excitation of the latter. This disinhibitory mechanism may underlie the enhanced responsiveness to mechanical and chemical itch stimuli in chronic itch patients.

Painful physical symptoms in major depressive disorder (MDD) patients lead to poor outcomes during MDD treatment. Here, we report that decreased Na+/K+-ATPase β1 subunit (NKAβ1) expression in anterior cingulate cortex glutamatergic (ACCGlu) neurons promotes ion dyshomeostasis, leading to hyperactivity of ACCGlu-insular cortex circuits in chronic stress mice. This ultimately primes allodynia. Mechanistically, we reveal that chronic stress strengthens LAMP2A-driven chaperone-mediated autophagy (CMA) and subsequently promotes the degradation of NKAβ1. We further identify NKAβ1 as a CMA substrate. Accordingly, genetically LAMP2A loss in ACCGlu neurons reverses chronic-stress-induced neuronal hyperexcitability, subsequently ameliorating allodynia. Additionally, we develop a trans-activating transcription (TAT)-LAMP2A peptide that significantly alleviates depression-induced allodynia. Taken together, our results reveal a mechanistic connection between CMA and neuronal excitability. TAT-LAMP2A peptide intervention, by disturbing CMA-dependent NKAβ1 elimination, could be a potential pharmacological treatment for depression-induced allodynia and further facilitate the efficacy of antidepressant treatment.

Pain represents a significant public health challenge with substantial clinical and economic burdens. While pharmacotherapy remains a mainstay of pain management, its utility is limited by adverse side effects and the potential for dependency. Acupuncture has shown great potential in pain management through its ability to induce analgesic effects via acupoint stimulation. However, its poor specificity and ill-defined stimulation parameters compromise therapeutic specificity and reproducibility. Herein, we developed a biomaterial-based acupoint activation strategy for pain management. Adhesive polydopamine-coated hydrogel microspheres were fabricated using microfluidic techniques for accurate attachment and activation of acupoints. Adhesive hydrogel microspheres loaded with adenosine can slowly release exogenous adenosine at the ST36 acupoint to simulate the analgesic effect of acupuncture. In vitro and in vivo studies demonstrated that single-dose administration of adhesive microspheres can effectively target acupoints, elevate mechanical pain thresholds, and provide systemic anti-inflammatory effects for up to 7 days. Overall, the proposed adhesive hydrogel microsphere system offers a new perspective on acupuncture practice and pain management.

Globally, over 300 million surgeries are performed each year, and more than 50% of surgeries involve patients aged 65 and older. Aging poses significant challenges to perioperative brain health, as the deterioration of brain structure and function increases susceptibility to postoperative neurological complications. Protecting perioperative brain health remains a worldwide clinical challenge. With senescence, the brain undergoes a progressive decline in homeostasis across various molecular, cellular, and regional functions. Anesthetics and surgical stimuli may accelerate the disruption of brain homeostasis and exacerbate age-related neurodegeneration. This review provides a framework for understanding how anesthesia and surgery can affect brain health in the aging population and contribute to postoperative neurological complications, with a particular focus on perioperative neurocognitive disorder.