Automated radiotherapy treatment planning guided by GPT-4Vision.

Radiotherapy treatment planning is a time-consuming and potentially subjective process that requires the iterative adjustment of model parameters to balance multiple conflicting objectives. Recent advancements in large foundation models offer promising avenues for addressing the challenges in planning and clinical decision-making. This study introduces GPT-RadPlan, a fully automated treatment planning framework that harnesses prior radiation oncology knowledge encoded in multi-modal large language models, such as GPT-4Vision (GPT-4V) from OpenAI. GPT-RadPlan is made aware of planning protocols as context and acts as an expert human planner, capable of guiding a treatment planning process. Via in-context learning, we incorporate clinical protocols for various disease sites as prompts to enable GPT-4V to acquire treatment planning domain knowledge. The resulting GPT-RadPlan agent is integrated into our in-house inverse treatment planning system through an API. The efficacy of the automated planning system is showcased using multiple prostate and head & neck cancer cases, where we compared GPT-RadPlan results to clinical plans. In all cases, GPT-RadPlan either outperformed or matched the clinical plans, demonstrating superior target coverage and organ-at-risk sparing. Consistently satisfying the dosimetric objectives in the clinical protocol, GPT-RadPlan represents the first multimodal large language model agent that mimics the behaviors of human planners in radiation oncology clinics, achieving remarkable results in automating the treatment planning process without the need for additional training.

Adaptive fixed-time fuzzy containment control for uncertain nonlinear multiagent systems with unmeasurable states.

This paper addresses the adaptive fixed-time fuzzy containment control for uncertain nonlinear multiagent systems, where the states and nonlinear functions are not feasible for the controller design. To address the issue of unmeasurable states, a state observer is developed, and fuzzy logic systems are utilized to approximate unknown nonlinear functions. Under the framework of fixed-time Lyapunov function theory and cooperative control, an adaptive fixed-time fuzzy containment control protocol is derived via the adaptive backstepping and adding one power integrator method. The derived fixed-time containment controller can confirm that the closed-loop systems are practical fixed-time stable, which implies that all signals in the systems are bounded and all follower agents can converge to the convex hull formed by the leader agents within fixed-time in the presence of unmeasurable states and unknown nonlinear functions . Simulation examples are conducted to test the validity of the present control algorithm.

Large Language Model-Augmented Auto-Delineation of Treatment Target Volume in Radiation Therapy.

Radiation therapy (RT) is one of the most effective treatments for cancer, and its success relies on the accurate delineation of targets. However, target delineation is a comprehensive medical decision that currently relies purely on manual processes by human experts. Manual delineation is time-consuming, laborious, and subject to interobserver variations. Although the advancements in artificial intelligence (AI) techniques have significantly enhanced the auto-contouring of normal tissues, accurate delineation of RT target volumes remains a challenge. In this study, we propose a visual language model-based RT target volume auto-delineation network termed Radformer. The Radformer utilizes a hierarichal vision transformer as the backbone and incorporates large language models to extract text-rich features from clinical data. We introduce a visual language attention module (VLAM) for integrating visual and linguistic features for language-aware visual encoding (LAVE). The Radformer has been evaluated on a dataset comprising 2985 patients with head-and-neck cancer who underwent RT. Metrics, including the Dice similarity coefficient (DSC), intersection over union (IOU), and 95th percentile Hausdorff distance (HD95), were used to evaluate the performance of the model quantitatively. Our results demonstrate that the Radformer has superior segmentation performance compared to other state-of-the-art models, validating its potential for adoption in RT practice.

Role of cell metabolism in the pathophysiology of brain size-associated neurodevelopmental disorders.

Cell metabolism is a key regulator of human neocortex development and evolution. Several lines of evidence indicate that alterations in neural stem/progenitor cell (NPC) metabolism lead to abnormal brain development, particularly brain size-associated neurodevelopmental disorders, such as microcephaly. Abnormal NPC metabolism causes impaired cell proliferation and thus insufficient expansion of NPCs for neurogenesis. Therefore, the production of neurons, which is a major determinant of brain size, is decreased and the size of the brain, especially the size of the neocortex, is significantly reduced. This review discusses recent progress understanding NPC metabolism, focusing in particular on glucose metabolism, fatty acid metabolism and amino acid metabolism (e.g., glutaminolysis and serine metabolism). We provide an overview of the contributions of these metabolic pathways to brain development and evolution, as well as to the etiology of neurodevelopmental disorders. Furthermore, we discuss the advantages and disadvantages of various experimental models to study cell metabolism in the developing brain.

Optimizing cystoscopy and TURBT: enhanced imaging and artificial intelligence.

Diagnostic cystoscopy in combination with transurethral resection of the bladder tumour are the standard for the diagnosis, surgical treatment and surveillance of bladder cancer. The ability to inspect the bladder in its current form stems from a long chain of advances in imaging science and endoscopy. Despite these advances, bladder cancer recurrence and progression rates remain high after endoscopic resection. This stagnation is a result of the heterogeneity of cancer biology as well as limitations in surgical techniques and tools, as incomplete resection and provider-specific differences affect cancer persistence and early recurrence. An unmet clinical need remains for solutions that can improve tumour delineation and resection. Translational advances in enhanced cystoscopy technologies and artificial intelligence offer promising avenues to overcoming the progress plateau.

Mitochondrial endogenous substance transport-inspired nanomaterials for mitochondria-targeted gene delivery.

Mitochondrial genome (mtDNA) independent of nuclear gene is a set of double-stranded circular DNA that encodes 13 proteins, 2 ribosomal RNAs and 22 mitochondrial transfer RNAs, all of which play vital roles in functions as well as behaviors of mitochondria. Mutations in mtDNA result in various mitochondrial disorders without available cures. However, the manipulation of mtDNA via the mitochondria-targeted gene delivery faces formidable barriers, particularly owing to the mitochondrial double membrane. Given the fact that there are various transport channels on the mitochondrial membrane used to transfer a variety of endogenous substances to maintain the normal functions of mitochondria, mitochondrial endogenous substance transport-inspired nanomaterials have been proposed for mitochondria-targeted gene delivery. In this review, we summarize mitochondria-targeted gene delivery systems based on different mitochondrial endogenous substance transport pathways. These are categorized into mitochondrial steroid hormones import pathways-inspired nanomaterials, protein import pathways-inspired nanomaterials and other mitochondria-targeted gene delivery nanomaterials. We also review the applications and challenges involved in current mitochondrial gene editing systems. This review delves into the approaches of mitochondria-targeted gene delivery, providing details on the design of mitochondria-targeted delivery systems and the limitations regarding the various technologies. Despite the progress in this field is currently slow, the ongoing exploration of mitochondrial endogenous substance transport and mitochondrial biological phenomena may act as a crucial breakthrough in the targeted delivery of gene into mitochondria and even the manipulation of mtDNA.

Acetylation-dependent deubiquitinase USP26 stabilizes BAG3 to promote breast cancer progression.

Deubiquitylases (DUBs) have emerged as promising targets for cancer therapy due to their role in stabilizing substrate proteins within the ubiquitin machinery. Here, we identified ubiquitin-specific protease 26 (USP26) as an oncogene via screening prognostic DUBs in breast cancer. Through in vitro and in vivo experiments, we found that depletion of USP26 inhibited breast cancer cell proliferation and invasion, and suppressed tumor growth and metastasis in nude mice. Further investigation identified co-chaperone Bcl-2-associated athanogene 3 (BAG3) as the direct substrate of USP26, and ectopic expression of BAG3 partially reversed antitumor effect induced by USP26 knockdown. Mechanistically, the lysine acetyltransferase Tip60 targeted USP26 at K134 for acetylation, which enhanced USP26 binding affinity to BAG3, leading to BAG3 deubiquitination and increased protein stability. Importantly, we employed a structure-based virtual screening and discovered a drug-like molecule called 5813669 that targets USP26, destabilizing BAG3 and effectively mitigating tumor growth and metastasis in vivo. Clinically, high expression levels of USP26 were correlated with elevated BAG3 levels and poor prognosis in breast cancer patients. Overall, our findings highlight the critical role of USP26 in BAG3 protein stabilization and provide a promising therapeutic target for breast cancer.

Potential of Progressive and Disruptive Innovation-Driven Cost Reductions of Green Hydrogen Production.

Green hydrogen from water electrolysis is a key driver for energy and industrial decarbonization. The prediction of the future green hydrogen cost reduction is required for investment and policy-making purposes but is complicated due to a lack of data, incomplete accounting for costs, and difficulty justifying trend predictions. A new AI-assisted data-driven prediction model is developed for an in-depth analysis of the current and future levelized costs of green hydrogen, driven by both progressive and disruptive innovations. The model uses natural language processing to gather data and generate trends for the technological development of key aspects of electrolyzer technology. Through an uncertainty analysis, green hydrogen costs have been shown to likely reach the key target of <$2.5 kg-1 by 2030 via progressive innovations, and beyond this point, disruptive technological developments are required to affect significantly further decease cost. Additionally, the global distribution of green hydrogen costs has been calculated. This work creates a comprehensive analysis of the levelized cost of green hydrogen, including the important balance of plant components, both now and as electrolyzer technology develops, and offers a likely prediction for how the costs will develop over time.

Commissioning of a novel PET-Linac for biology-guided radiotherapy (BgRT).

BACKGROUND: Biology-guided radiotherapy (BgRT) is a novel radiotherapy delivery technique that utilizes the tumor itself to guide dynamic delivery of treatment dose to the tumor. The RefleXion X1 system is the first radiotherapy system developed to deliver SCINTIX® BgRT. The X1 is characterized by its split arc design, employing two 90-degree positron emission tomography (PET) arcs to guide therapeutic radiation beams in real time, currently cleared by FDA to treat bone and lung tumors. PURPOSE: This study aims to comprehensively evaluate the capabilities of the SCINTIX radiotherapy delivery system by evaluating its sensitivity to changes in PET contrast, its adaptability in the context of patient motion, and its performance across a spectrum of prescription doses. METHODS: A series of experimental scenarios, both static and dynamic, were designed to assess the SCINTIX BgRT system's performance, including an end-to-end test. These experiments involved a range of factors, including changes in PET contrast, motion, and prescription doses. Measurements were performed using a custom-made ArcCHECK insert which included a 2.2 cm spherical target and a c-shape structure that can be filled with a PET tracer with varying concentrations. Sinusoidal and cosine4 motion patterns, simulating patient breathing, was used to test the SCINTIX system's ability to deliver BgRT during motion-induced challenges. Each experiment was evaluated against specific metrics, including Activity Concentration (AC), Normalized Target Signal (NTS), and Biology Tracking Zone (BTZ) bounded dose-volume histogram (bDVH) pass rates. The accuracy of the delivered BgRT doses on ArcCHECK and EBT-XD film were evaluated using gamma 3%/2 mm and 3%/3 mm analysis. RESULTS: In static scenarios, the X1 system consistently demonstrated precision and robustness in SCINTIX dose delivery. The end-to-end delivery to the spherical target yielded good results, with AC and NTS values surpassing the critical thresholds of 5 kBq/mL and 2, respectively. Furthermore, bDVH analysis consistently confirmed 100% pass rates. These results were reaffirmed in scenarios involving changes in PET contrast, emphasizing the system's ability to adapt to varying PET avidities. Gamma analysis with 3%/2 mm (10% dose threshold) criteria consistently achieved pass rates > 91.5% for the static tests. In dynamic SCINTIX delivery scenarios, the X1 system exhibited adaptability under conditions of motion. Sinusoidal and cosine4 motion patterns resulted in 3%/3 mm gamma pass rates > 87%. Moreover, the comparison with gated stereotactic body radiotherapy (SBRT) delivery on a conventional c-arm Linac resulted in 93.9% gamma pass rates and used as comparison to evaluate the interplay effect. The 1 cm step shift tests showed low overall gamma pass rates of 60.3% in ArcCHECK measurements, while the doses in the PTV agreed with the plan with 99.9% for 3%/3 mm measured with film. CONCLUSIONS: The comprehensive evaluation of the X1 radiotherapy delivery system for SCINTIX BgRT demonstrated good agreement for the static tests. The system consistently achieved critical metrics and delivered the BgRT doses per plan. The motion tests demonstrated its ability to co-localize the dose where the PET signal is and deliver acceptable BgRT dose distributions.

Synergistic effect of mesenchymal stem cell-derived extracellular vesicle and miR-137 alleviates autism-like behaviors by modulating the NF-κB pathway.

Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder predominant in childhood. Despite existing treatments, the benefits are still limited. This study explored the effectiveness of mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) loaded with miR-137 in enhancing autism-like behaviors and mitigating neuroinflammation. Utilizing BTBR mice as an autism model, the study demonstrated that intranasal administration of MSC-miR137-EVs ameliorates autism-like behaviors and inhibits pro-inflammatory factors via the TLR4/NF-κB pathway. In vitro evaluation of LPS-activated BV2 cells revealed that MSC-miR137-EVs target the TLR4/NF-κB pathway through miR-137 inhibits proinflammatory M1 microglia. Moreover, bioinformatics analysis identified that MSC-EVs are rich in miR-146a-5p, which targets the TRAF6/NF-κB signaling pathway. In summary, the findings suggest that the integration of MSC-EVs with miR-137 may be a promising therapeutic strategy for ASD, which is worthy of clinical adoption.

Automated contouring, treatment planning, and quality assurance for VMAT craniospinal irradiation (VMAT-CSI).

Purpose: Create a comprehensive automated solution for pediatric and adult VMAT-CSI including contouring, planning, and plan check to reduce planning time and improve plan quality. Methods: Seventy-seven previously treated CSI patients (age, 2-67 years) were used for creation of an auto-contouring model to segment 25 organs at risk (OARs). The auto-contoured OARs were evaluated using the Dice Similarity Coefficient (DSC), 95% Hausdorff Distance (HD95), and a qualitative ranking by one physician and one physicist (scale: 1-acceptable, 2-minor edits, 3-major edits). The auto-planning script was developed using the Varian Eclipse Scripting API and tested with 20 patients previously treated with either low-dose VMAT-CSI (12 Gy) or high-dose VMAT-CSI (36 Gy + 18 Gy boost). Clinically relevant metrics, planning time, and blinded physician review were used to evaluate significance of differences between the auto and manual plans. Finally, the plan preparation for treatment and plan check processes were automated to improve efficiency and safety of VMAT-CSI. Results: The auto-contours achieved an average DSC of 0.71 ± 0.15, HD95 of 4.81 ± 4.68, and reviewers' ranking of 1.22 ± 0.39, indicating close to "acceptable-as-is" contours. Compared to the manual CSI plans, the auto-plans for both dose regimens achieved statistically significant reductions in body V50% and Dmean for parotids, submandibular, and thyroid glands. The variance in the dosimetric parameters decreased for the auto-plans as compared to the manual plans indicating better plan consistency. From the blinded review, the auto-plans were marked as equivalent or superior to the manual-plans 88.3% of the time. The required time for the auto-contouring and planning was consistently between 1-2 hours compared to an estimated 5-6 hours for manual contouring and planning. Conclusions: Reductions in contouring and planning time without sacrificing plan quality were obtained using the developed auto-planning process. The auto-planning scripts and documentation will be made freely available to other institutions and clinics.

Functional synergy of a human-specific and an ape-specific metabolic regulator in human neocortex development.

Metabolism has recently emerged as a major target of genes implicated in the evolutionary expansion of human neocortex. One such gene is the human-specific gene ARHGAP11B. During human neocortex development, ARHGAP11B increases the abundance of basal radial glia, key progenitors for neocortex expansion, by stimulating glutaminolysis (glutamine-to-glutamate-to-alpha-ketoglutarate) in mitochondria. Here we show that the ape-specific protein GLUD2 (glutamate dehydrogenase 2), which also operates in mitochondria and converts glutamate-to-αKG, enhances ARHGAP11B's ability to increase basal radial glia abundance. ARHGAP11B + GLUD2 double-transgenic bRG show increased production of aspartate, a metabolite essential for cell proliferation, from glutamate via alpha-ketoglutarate and the TCA cycle. Hence, during human evolution, a human-specific gene exploited the existence of another gene that emerged during ape evolution, to increase, via concerted changes in metabolism, progenitor abundance and neocortex size.

Glutamatergic neurons in the paraventricular nucleus of the hypothalamus participate in the regulation of visceral pain induced by pancreatic cancer in mice.

Background: Visceral pain induced by pancreatic cancer seriously affects patients' quality of life, and there is no effective treatment, because the mechanism of its neural circuit is unknown. Therefore, the aim of this study is to explore the main neural circuit mechanism regulating visceral pain induced by pancreatic cancer in mice. Methods: The mouse model of pancreatic cancer visceral pain was established on C57BL/6N mice by pancreatic injection of mPAKPC-luc cells. Abdominal mechanical hyperalgesia and hunch score were performed to assess visceral pain; the pseudorabies virus (PRV) was used to identify the brain regions innervating the pancreas; the c-fos co-labeling method was used to ascertain the types of activated neurons; in vitro electrophysiological patch-clamp technique was used to record the electrophysiological activity of specific neurons; the calcium imaging technique was used to determine the calcium activity of specific neurons; specific neuron destruction and chemogenetics methods were used to explore whether specific neurons were involved in visceral pain induced by pancreatic cancer. Results: The PRV injected into the pancreas was detected in the paraventricular nucleus of the hypothalamus (PVN). Immunofluorescence staining showed that the majority of c-fos were co-labeled with glutamatergic neurons in the PVN. In vitro electrophysiological results showed that the firing frequency of glutamatergic neurons in the PVN was increased. The calcium imaging results showed that the calcium activity of glutamatergic neurons in the PVN was enhanced. Both specific destruction of glutamatergic neurons and chemogenetics inhibition of glutamatergic neurons in the PVN alleviated visceral pain induced by pancreatic cancer. Conclusions: Glutamatergic neurons in the PVN participate in the regulation of visceral pain induced by pancreatic cancer in mice, providing new insights for the discovery of effective targets for the treatment of pancreatic cancer visceral pain.

Enhancing the quality of fermented plant leaves: the role of metabolite signatures and associated fungi.

Fungi play a pivotal role in fermentation processes, influencing the breakdown and transformation of metabolites. However, studies focusing on the effects of fungal-metabolite correlations on leaf fermentation quality enhancement are limited. This study investigated specific metabolites and fungi associated with high- and low-quality fermented plant leaves. Their changes were monitored over fermentation periods of 0, 8, 16, and 24 days. The results indicated that organoheterocyclic compounds, lipids, lipid-like molecules, organic nitrogen compounds, phenylpropanoids, and polyketides were predominant in high-quality samples. The fungi Saccharomyces (14.8%) and Thermoascus (4.6%) were predominantly found in these samples. These markers exhibited significant changes during the 24-day fermentation period. The critical influence of fungal community equilibrium was demonstrated by interspecies interactions (e.g., between Saccharomyces and Eurotium). A co-occurrence network analysis identified Saccharomyces as the primary contributor to high-quality samples. These markers collectively enhance the quality and sensory characteristics of the final product.

Quantifying particle concentration via AI-enhanced optical coherence tomography.

Efficient and robust quantification of the number of nanoparticles in solution is not only essential but also insufficient in nanotechnology and biomedical research. This paper proposes to use optical coherence tomography (OCT) to quantify the number of gold nanorods, which exemplify the nanoparticles with high light scattering signals. Additionally, we have developed an AI-enhanced OCT image processing to improve the accuracy and robustness of the quantification result.

Reactive Oxygen Species-Responsive Nanoparticles Toward Extracellular Matrix Normalization for Pancreatic Fibrosis Regression.

Pancreatic fibrosis (PF) is primarily characterized by aberrant production and degradation modes of extracellular matrix (ECM) components, resulting from the activation of pancreatic stellate cells (PSCs) and the pathological cross-linking of ECM mediated by lysyl oxidase (LOX) family members. The excessively deposited ECM increases matrix stiffness, and the over-accumulated reactive oxygen species (ROS) induces oxidative stress, which further stimulates the continuous activation of PSCs and advancing PF; challenging the strategy toward normalizing ECM homeostasis for the regression of PF. Herein, ROS-responsive and Vitamin A (VA) decorated micelles (named LR-SSVA) to reverse the imbalanced ECM homeostasis for ameliorating PF are designed and synthesized. Specifically, LR-SSVA selectively targets PSCs via VA, thereby effectively delivering siLOXL1 and resveratrol (RES) into the pancreas. The ROS-responsive released RES inhibits the overproduction of ECM by eliminating ROS and inactivating PSCs, meanwhile, the decreased expression of LOXL1 ameliorates the cross-linked collagen for easier degradation by collagenase which jointly normalizes ECM homeostasis and alleviates PF. This research shows that LR-SSVA is a safe and efficient ROS-response and PSC-targeted drug-delivery system for ECM normalization, which will propose an innovative and ideal platform for the reversal of PF.

AI-assisted mass spectrometry imaging with in situ image segmentation for subcellular metabolomics analysis.

Subcellular metabolomics analysis is crucial for understanding intracellular heterogeneity and accurate drug-cell interactions. Unfortunately, the ultra-small size and complex microenvironment inside the cell pose a great challenge to achieving this goal. To address this challenge, we propose an artificial intelligence-assisted subcellular mass spectrometry imaging (AI-SMSI) strategy with in situ image segmentation. Based on the nanometer-resolution MSI technique, the protonated guanine and threonine ions were respectively employed as the nucleus and cytoplasmic markers to complete image segmentation at the subcellular level, avoiding mutual interference of signals from various compartments in the cell. With advanced AI models, the metabolites within the different regions could be further integrated and profiled. Through this method, we decrypted the distinct action mechanism of isomeric drugs, doxorubicin (DOX) and epirubicin (EPI), only with a stereochemical inversion at C-4'. Within the cytoplasmic region, fifteen specific metabolites were discovered as biomarkers for distinguishing the drug action difference between DOX and EPI. Moreover, we identified that the downregulations of glutamate and aspartate in the malate-aspartate shuttle pathway may contribute to the higher paratoxicity of DOX. Our current AI-SMSI approach has promising applications for subcellular metabolomics analysis and thus opens new opportunities to further explore drug-cell specific interactions for the long-term pursuit of precision medicine.

Nanoparticles targeting mutant p53 overcome chemoresistance and tumor recurrence in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) shows high drug resistance and leads to low survival due to the high level of mutated Tumor Protein p53 (TP53). Cisplatin is a first-line treatment option for NSCLC, and the p53 mutation is a major factor in chemoresistance. We demonstrate that cisplatin chemotherapy increases the risk of TP53 mutations, further contributing to cisplatin resistance. Encouragingly, we find that the combination of cisplatin and fluvastatin can alleviate this problem. Therefore, we synthesize Fluplatin, a prodrug consisting of cisplatin and fluvastatin. Then, Fluplatin self-assembles and is further encapsulated with poly-(ethylene glycol)-phosphoethanolamine (PEG-PE), we obtain Fluplatin@PEG-PE nanoparticles (FP NPs). FP NPs can degrade mutant p53 (mutp53) and efficiently trigger endoplasmic reticulum stress (ERS). In this study, we show that FP NPs relieve the inhibition of cisplatin chemotherapy caused by mutp53, exhibiting highly effective tumor suppression and improving the poor NSCLC prognosis.

An Adaptive Radon-Transform-Based Marker Detection and Localization Method for Displacement Measurements Using Unmanned Aerial Vehicles.

UAVs have been widely used in deformation monitoring because of their high availability and flexibility. However, the quality of UAV images is affected by changing attitude and surveying environments, resulting in a low monitoring accuracy. Cross-shaped markers are used to improve the accuracy of UAV monitoring due to their distinct center contrast and absence of eccentricity. However, existing methods cannot rapidly and precisely detect these markers in UAV images. To address these problems, this paper proposes an adaptive Radon-transform-based marker detection and localization method for UAV displacement measurements, focusing on two critical detection parameters, namely, the radius of marker information acquisition and the edge width of the cross-shaped scoring template. The experimental results show that the marker detection rate is 97.2% under different combinations of flight altitudes, radius ratios of marker information acquisition, and marker sizes. Furthermore, the root mean square error of detection and localization is 0.57 pixels, significantly surpassing the performance and accuracy of other methods. We also derive the critical detection radius and appropriate parameter combinations for different heights to further improve the practicality of the method.

The Protective Effects of Ecdysterone on Cognitive Impairment through Regulating Akt/GSK-3ß/Nrf2 Signaling Pathway and Oxidative Stress in Cognitive Mice Model and Aß-Induced Cell Neurotoxicity.

BACKGROUND: Severe neurological condition like Alzheimer's disease (AD) has a significantly negative impact on families and society, wherein there is no proven cure. As one of the principal active constituents of Achyranthes bidentata Blume, ecdysterone (ECR) has demonstrated antioxidant and cognitive dysfunction improvement effects. Nonetheless, the mechanism underlying the improvement of cognitive dysfunction by ECR remains unclear. This study sought to ascertain whether ECR may allebviate cognitive impairment by reducing oxidative stress via activation of the nuclear factor erythroid-2-related factor-2 (Nrf2) antioxidant system through Akt/GSK3ß pathway. METHODS: In terms of the experimental procedure, we determined the neuroprotective benefits of ECR in vivo via a cognitive impairment model of senescence-accelerated mouse prone 8 (SAMP8), we performed procedures such as behavioral testing, biochemical assaying, Nissl and TUNEL stainings, as well as flow cytometry, immunohistochemistry and western blotting. Furthermore, we investigated the underlying mechanistic action of ECR by activating PC12 cells with ß-amyloid peptide fragment 25-35 (Aß25-35). RESULTS: In vivo studies showed that ECR effectively improved cognitive impairment in SAMP8 via enhancement of learning and memory capabilities, but decreased oxidative stress, apoptosis and neuronal damage in the hippocampus. During the in vitro study, we observed that ECR dose-dependently reduced the oxidative stress and apoptosis that were induced in PC12 cells by Aß25-35. Additionally, the use of Akt inhibitors further established the potential of ECR to control Nrf2 through activation of the Akt/GSK3ß pathway and protect the PC12 cells from Aß25-35 induced damage. CONCLUSIONS: These findings offer proof that ECR reduces cognitive impairment by triggering the Nrf2 antioxidant system via the Akt/GSK3ß pathway and offer fresh information on ECR's potential as a promising therapeutic development candidate for AD.