The evolution of flavonoid biosynthesis.

The flavonoid pathway is characteristic of land plants and a central biosynthetic component enabling life in a terrestrial environment. Flavonoids provide tolerance to both abiotic and biotic stresses and facilitate beneficial relationships, such as signalling to symbiont microorganisms, or attracting pollinators and seed dispersal agents. The biosynthetic pathway shows great diversity across species, resulting principally from repeated biosynthetic gene duplication and neofunctionalization events during evolution. Such events may reflect a selection for new flavonoid structures with novel functions that enable occupancy of varied ecological niches. However, the biochemical and genetic diversity of the pathway also likely resulted from evolution along parallel trends across land plant lineages, producing variant compounds with similar biological functions. Analyses of the wide range of whole-plant genome sequences now available, particularly for archegoniate plants, have enabled proposals on which genes were ancestral to land plants and which arose within the land plant lineages. In this review, we discuss the emerging proposals for how the flavonoid pathway may have evolved and diversified. This article is part of the theme issue 'The evolution of plant metabolism'.

The auronidin flavonoid pigments of the liverwort Marchantia polymorpha form polymers that modify cell wall properties.

Plant adaptation from aquatic to terrestrial environments required modifications to cell wall structure and function to provide tolerance to new abiotic and biotic stressors. Here, we investigate the nature and function of red auronidin pigment accumulation in the cell wall of the liverwort Marchantia polymorpha. Transgenic plants with auronidin production either constitutive or absent were analysed for their cell wall properties, including fractionation of polysaccharide and phenolic components. While small amounts of auronidin and other flavonoids were loosely associated with the cell wall, the majority of the pigments were tightly associated, similar to what is observed in angiosperms for polyphenolics such as lignin. No evidence of covalent binding to a polysaccharide component was found: we propose auronidin is present in the wall as a physically entrapped large molecular weight polymer. The results suggested auronidin is a dual function molecule that can both screen excess light and increase wall strength, hydrophobicity and resistance to enzymatic degradation by pathogens. Thus, liverworts have expanded the core phenylpropanoid toolkit that was present in the ancestor of all land plants, to deliver a lineage-specific solution to some of the environmental stresses faced from a terrestrial lifestyle.

Risk prediction models for diabetic nephropathy among type 2 diabetes patients in China: a systematic review and meta-analysis.

Objective: This study systematically reviews and meta-analyzes existing risk prediction models for diabetic kidney disease (DKD) among patients with type 2 diabetes, aiming to provide references for scholars in China to develop higher-quality risk prediction models. Methods: We searched databases including China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP Chinese Science and Technology Journal Database, Chinese Biomedical Literature Database (CBM), PubMed, Web of Science, Embase, and the Cochrane Library for studies on the construction of DKD risk prediction models among type 2 diabetes patients, up until 28 December 2023. Two researchers independently screened the literature and extracted and evaluated information according to a data extraction form and bias risk assessment tool for prediction model studies. The area under the curve (AUC) values of the models were meta-analyzed using STATA 14.0 software. Results: A total of 32 studies were included, with 31 performing internal validation and 22 reporting calibration. The incidence rate of DKD among patients with type 2 diabetes ranged from 6.0% to 62.3%. The AUC ranged from 0.713 to 0.949, indicating the prediction models have fair to excellent prediction accuracy. The overall applicability of the included studies was good; however, there was a high overall risk of bias, mainly due to the retrospective nature of most studies, unreasonable sample sizes, and studies conducted in a single center. Meta-analysis of the models yielded a combined AUC of 0.810 (95% CI: 0.780-0.840), indicating good predictive performance. Conclusion: Research on DKD risk prediction models for patients with type 2 diabetes in China is still in its initial stages, with a high overall risk of bias and a lack of clinical application. Future efforts could focus on constructing high-performance, easy-to-use prediction models based on interpretable machine learning methods and applying them in clinical settings. Registration: This systematic review and meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a recognized guideline for such research. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024498015.

DWARF27 and CAROTENOID CLEAVAGE DIOXYGENASE 7 genes regulate release, germination and growth of gemma in Marchantia polymorpha.

Strigolactones (SLs), a class of carotenoid-derived hormones, play a crucial role in flowering plants by regulating underground communication with symbiotic arbuscular mycorrhizal fungi (AM) and controlling shoot and root architecture. While the functions of core SL genes have been characterized in many plants, their roles in non-tracheophyte plants like liverworts require further investigation. In this study, we employed the model liverwort species Marchantia polymorpha, which lacks detectable SL production and orthologs of key SL biosynthetic genes, including CAROTENOID CLEAVAGE DIOXYGENASE 8 (CCD8) and MORE AXILLARY GROWTH 1 (MAX1). However, it retains some SL pathway components, including DWARF27 (D27) and CCD7. To help elucidate the function of these remaining components in M. polymorpha, knockout mutants were generated for MpD27-1, MpD27-2 and MpCCD7. Phenotypic comparisons of these mutants with the wild-type control revealed a novel role for these genes in regulating the release of gemmae from the gemma cup and the germination and growth of gemmae in the dark. Mpd27-1, Mpd27-2, and Mpccd7 mutants showed lower transcript abundance of genes involved in photosynthesis, such as EARLY LIGHT INDUCED (ELI), and stress responses such as LATE EMBRYOGENESIS ABUNDANT (LEA) but exhibited higher transcript levels of ETHYLENE RESPONSE FACTORS (ERFs) and SL and carotenoid related genes, such as TERPENE SYNTHASE (TS), CCD7 and LECITHIN-RETINAL ACYL TRANSFERASE (LRAT). Furthermore, the mutants of M. polymorpha in the SL pathway exhibited increased contents of carotenoid. This unveils a previously unrecognized role for MpD27-1, MpD27-2 and MpCCD7 in controlling release, germination, and growth of gemmae in response to varying light conditions. These discoveries enhance our comprehension of the regulatory functions of SL biosynthesis genes in non-flowering plants.

Direct evidence for the occurrence of indigenous cadmium-based nanoparticles in paddy soils.

Speciation of heavy metal-based nanoparticles (NPs) in paddy soils greatly determines their fate and potential risk towards food safety. However, quantitative understanding of such distinctive species remains challenging, because they are commonly presented at trace levels (e.g., sub parts-per-million) and extremely difficult to be fractionated in soil matrices. Herein, we propose a state-of-art non-destructive strategy for effective extraction and quantification of cadmium (Cd)-NPs - the most widespread heavy metal in paddy soils - by employing single particle inductively coupled plasma mass spectrometry (spICP-MS) and tetrasodium pyrophosphate (TSPP) as the extractant. Acceptable extraction efficiencies (64.7-80.4 %) were obtained for spiked cadmium sulfide nanoparticles (CdS-NPs). We demonstrate the presence of indigenous Cd-NPs in all six Cd-contaminated paddy soils tested, with a number concentration ranging from 2.20 × 108 to 3.18 × 109 particles/g, representing 17.0-50.4 % of the total Cd content. Furthermore, semi-spherical and irregular CdS-NPs were directly observed as an important form of the Cd-NPs in paddy soils, as characterized by transmission electron microscopy coupled with energy-dispersive X-ray spectroscopy (TEM-EDX). This research marks a significant step towards directly observing indigenous Cd-NPs at trace levels in paddy soil, offering a useful tool for quantitative understanding of the biogeochemical cycling of heavy metal-based NPs in complex matrices.

In Vitro Toxicity and Modeling Reveal Nanoplastic Effects on Marine Bivalves.

Nanoplastics (NPs) represent a growing concern for global environmental health, particularly in marine ecosystems where they predominantly accumulate. The impact of NPs on marine benthic organisms, such as bivalves, raises critical questions regarding ecological integrity and food safety. Traditional methods for assessing NP toxicity are often limited by their time-intensive nature and ethical considerations. Herein, we explore the toxicological effects of NPs on the marine bivalve Ruditapes philippinarum, employing a combination of in vitro cellular assays and advanced modeling techniques. Results indicate a range of adverse effects at the organismal level, including growth inhibition (69.5-108%), oxidative stress, lipid peroxidation, and DNA damage in bivalves, following exposure to NPs at concentrations in the range of 1.6 × 109-1.6 × 1011 particles/mL (p/mL). Interestingly, the growth inhibition predicted by models (54.7-104%), based on in vitro cellular proliferation assays, shows strong agreement with the in vivo outcomes of NP exposure. Furthermore, we establish a clear correlation between cytotoxicity observed in vitro and the toxicological responses at the organismal level. Taken together, this work suggests that the integration of computational modeling with in vitro toxicity assays can predict the detrimental effects of NPs on bivalves, offering insightful references for assessing the environmental risk assessment of NPs in marine benthic ecosystems.

Painted flowers: Eluta generates pigment patterning in Antirrhinum.

In the early 1900s, Erwin Baur established Antirrhinum majus as a model system, identifying and characterising numerous flower colour variants. This included Picturatum/Eluta, which restricts the accumulation of magenta anthocyanin pigments, forming bullseye markings on the flower face. We identified the gene underlying the Eluta locus by transposon-tagging, using an Antirrhinum line that spontaneously lost the nonsuppressive el phenotype. A candidate MYB repressor gene at this locus contained a CACTA transposable element. We subsequently identified plants where this element excised, reverting to a suppressive Eluta phenotype. El alleles inhibit expression of anthocyanin biosynthetic genes, confirming it to be a regulatory locus. The modes of action of Eluta were investigated by generating stable transgenic tobacco lines, biolistic transformation of Antirrhinum petals and promoter activation/repression assays. Eluta competes with MYB activators for promoter cis-elements, and also by titrating essential cofactors (bHLH proteins) to reduce transcription of target genes. Eluta restricts the pigmentation established by the R2R3-MYB factors, Rosea and Venosa, with the greatest repression on those parts of the petals where Eluta is most highly expressed. Baur questioned the origin of heredity units determining flower colour variation in cultivated A. majus. Our findings support introgression from wild species into cultivated varieties.

Test-retest reliability of the attention network test from the perspective of intrinsic network organization.

The attention network test (ANT), developed based on the triple-network taxonomy by Posner and colleagues, has been widely used to examine the efficacy of alerting, orienting and executive control in clinical and developmental neuroscience studies. Recent research suggests the imperfect reliability of the behavioural ANT and its variants. However, the classical ANT fMRI task's test-retest reliability has received little attention. Moreover, it remains ambiguous whether the attention-related intrinsic network components, especially the dorsal attention, ventral attention and frontoparietal network, manifest acceptable reliability. The present study approaches these issues by utilizing an openly available ANT fMRI dataset for participants with Parkinson's disease and healthy elderly. The reproducibility of group-level activations across sessions and participant groups and the test-retest reliability at the individual level were examined at the voxel, region and network levels. The intrinsic network was defined using the Yeo-Schaefer atlas. Our results reveal three critical facets: (1) the overlapping of the group-level contrast map between sessions and between participant groups was unsatisfactory; (2) the reliability of alerting, orienting and executive, defined as a contrast between conditions, was worse than estimates of specific conditions. (3) Dorsal attention, ventral attention, visual and somatomotor networks showed acceptable reliability for the congruent and incongruent conditions. Our results suggest that specific condition estimates might be used instead of the contrast map for individual or group-difference studies.

A transthyretin-like protein acts downstream of miR397 and LACCASE to regulate grain yield in rice.

Increasing grain yield is a major goal of breeders due to the rising global demand for food. We previously reported that the miR397-LACCASE (OsLAC) module regulates brassinosteroid (BR) signaling and grain yield in rice (Oryza sativa). However, the precise roles of laccase enzymes in the BR pathway remain unclear. Here, we report that OsLAC controls grain yield by preventing the turnover of TRANSTHYRETIN-LIKE (OsTTL), a negative regulator of BR signaling. Overexpressing OsTTL decreased BR sensitivity in rice, while loss-of-function of OsTTL led to enhanced BR signaling and increased grain yield. OsLAC directly binds to OsTTL and regulates its phosphorylation-mediated turnover. The phosphorylation site Ser226 of OsTTL is essential for its ubiquitination and degradation. Overexpressing the dephosphorylation-mimic form of OsTTL (OsTTLS226A) resulted in more severe defects than did overexpressing OsTTL. These findings provide insight into the role of an ancient laccase in BR signaling and suggest that the OsLAC-OsTTL module could serve as a target for improving grain yield.

CT radiomics-based model for predicting TMB and immunotherapy response in non-small cell lung cancer.

BACKGROUND: Tumor mutational burden (TMB) is one of the most significant predictive biomarkers of immunotherapy efficacy in non-small cell lung cancer (NSCLC). Radiomics allows high-throughput extraction and analysis of advanced and quantitative medical imaging features. This study develops and validates a radiomic model for predicting TMB level and the response to immunotherapy based on CT features in NSCLC. METHOD: Pre-operative chest CT images of 127 patients with NSCLC were retrospectively studied. The 3D-Slicer software was used to outline the region of interest and extract features from the CT images. Radiomics prediction model was constructed by LASSO and multiple logistic regression in a training dataset. The model was validated by receiver operating characteristic (ROC) curves and calibration curves using external datasets. Decision curve analysis was used to assess the value of the model for clinical application. RESULTS: A total of 1037 radiomic features were extracted from the CT images of NSCLC patients from TCGA. LASSO regression selected three radiomics features (Flatness, Autocorrelation and Minimum), which were associated with TMB level in NSCLC. A TMB prediction model consisting of 3 radiomic features was constructed by multiple logistic regression. The area under the curve (AUC) value in the TCGA training dataset was 0.816 (95% CI: 0.7109-0.9203) for predicting TMB level in NSCLC. The AUC value in external validation dataset I was 0.775 (95% CI: 0.5528-0.9972) for predicting TMB level in NSCLC, and the AUC value in external validation dataset II was 0.762 (95% CI: 0.5669-0.9569) for predicting the efficacy of immunotherapy in NSCLC. CONCLUSION: The model based on CT radiomic features helps to achieve cost effective improvement in TMB classification and precise immunotherapy treatment of NSCLC patients.

Surface-Charge-Driven Ferroptosis and Mitochondrial Dysfunction Is Involved in Toxicity Diversity in the Marine Bivalve Exposed to Nanoplastics.

Nanoplastics (NPs) pervade daily life, posing serious threats to marine ecosystems. Despite the crucial role that surface charge plays in NP effects, there is a substantial gap in our understanding of how surface charge influences NP toxicity. Herein, by exposing Ruditapes philippinarum (R. philippinarum) to both positively charged NPs (p-NPs) and negatively charged NPs (n-NPs) at environmentally relevant particle number levels for a duration of 35 days, we unequivocally demonstrate that both types of NPs had discernible impacts on the clams depending on their surface charge. Through transcriptomic and proteomic analyses, we unveiled the primary mechanisms behind p-NP toxicity, which stem from induced mitochondrial dysfunction and ferroptosis. In contrast, n-NPs predominantly stimulated innate immune responses, influencing salivary secretion and modulating the complement and coagulation cascades. Furthermore, in vitro tests on clam immune cells confirmed that internalized p-NPs triggered alterations in mitochondrial morphology, a decrease in membrane potential, and the initiation of ferroptosis. Conversely, n-NPs, to a certain extent, moderated the expression of genes related to immune responses, thus mitigating their adverse effects. Taken together, these findings indicate that the differential surface-charge-driven ferroptosis and mitochondrial dysfunction in clams play a critical role in the toxicity profile of NPs, providing an insightful reference for assessing the ecological toxicity associated with NPs.

MicroRNA397 promotes rice flowering by regulating the photorespiration pathway.

The precise timing of flowering plays a pivotal role in ensuring successful plant reproduction and seed production. This process is intricately governed by complex genetic networks that integrate internal and external signals. This study delved into the regulatory function of microRNA397 (miR397) and its target gene LACCASE-15 (OsLAC15) in modulating flowering traits in rice (Oryza sativa). Overexpression of miR397 led to earlier heading dates, decreased number of leaves on the main stem, and accelerated differentiation of the spikelet meristem. Conversely, overexpression of OsLAC15 resulted in delayed flowering and prolonged vegetative growth. Through biochemical and physiological assays, we uncovered that miR397-OsLAC15 had a profound impact on carbohydrate accumulation and photosynthetic assimilation, consequently enhancing the photosynthetic intensity in miR397-overexpressing rice plants. Notably, we identified that OsLAC15 is at least partially localized within the peroxisome organelle, where it regulates the photorespiration pathway. Moreover, we observed that a high CO2 concentration could rescue the late flowering phenotype in OsLAC15-overexpressing plants. These findings shed valuable insights into the regulatory mechanisms of miR397-OsLAC15 in rice flowering and provided potential strategies for developing crop varieties with early flowering and high-yield traits through genetic breeding.

Impact of facemask debris on marine diatoms: Physiology, surface properties, sinking rate, and copepod ingestion.

Discarded surgical masks have become a new source of plastic waste in seawater capable of releasing numerous micro and nano plastic fragments. However, little information is available about how this waste impacts the ecological state of marine phytoplankton. Here, we exposed two model marine diatoms (Phaeodactylum tricornutum and Thalassiosira weissflogii) to mask-released debris (MD) that is characterized by various differently-charged functional groups. Although MD could only bind loosely to diatoms, it still inhibited their growth and significantly altered cell surface physicochemical properties. At the nanoscale, MD-exposed cell walls showed enhanced roughness and modulus, besides declined electrical potential, adhesion, and proportion of oxygen-containing compounds. As a result, diatom ingestion by copepods was reduced, and the sinking rate of the carbon pool consisting of MD plus diatoms decreased as well. Our study indicated that MD effects on diatoms have the potential to slow down carbon export from surface seawater to the deep sea. Since oxidation and generation of functional groups are common during the aging process of microplastics (MPs) in nature, the interactions between the diatom cell surface and MD have important environmental significance.

Effects of nanoplastics on clam Ruditapes philippinarum at environmentally realistic concentrations: Toxicokinetics, toxicity, and gut microbiota.

Nanoplastics are ubiquitous in marine environments, understanding to what extent nanoplastics accumulate in bivalves and the adverse effects derived from their retention is imperative for evaluating the detrimental effects in the benthic ecosystem. Here, using palladium-doped polystyrene nanoplastics (139.5 nm, 43.8 mV), we quantitatively determined nanoplastic accumulation in Ruditapes philippinarum and investigated its toxic effects by combining physiological damage assessments with a toxicokinetic model and 16 S rRNA sequencing. After a 14 days exposure, significant nanoplastic accumulation was observed, up to 17.2 and 137.9 mg·kg-1 for the environmentally realistic (0.02 mg·L-1) and ecologically (2 mg·L-1) relevant groups, respectively. Ecologically relevant nanoplastic concentrations evidently attenuated the total antioxidant capacity and stimulated excessive reactive oxygen species, which elicited lipid peroxidation, apoptosis, and pathological damage. The modeled uptake (k1) and elimination (k2) rate constants (from physiologically based pharmacokinetic model) were significantly negatively correlated with short-term toxicity. Although no obvious toxic effects were found, environmentally realistic exposures notably altered the intestinal microbial community structure. This work increases our understanding of how the accumulation of nanoplastics influences their toxic effects in terms of the toxicokinetics and gut microbiota, providing further evidence of their potential environmental risks.

Nanoplastics induces oxidative stress and triggers lysosome-associated immune-defensive cell death in the earthworm Eisenia fetida.

Nanoplastics (NPs) are increasingly perceived as an emerging threat to terrestrial environments, but the adverse impacts of NPs on soil fauna and the mechanisms behind these negative outcomes remain elusive. Here, a risk assessment of NPs was conducted on model organism (earthworm) from tissue to cell. Using palladium-doped polystyrene NPs, we quantitatively measured nanoplastic accumulation in earthworm and investigated its toxic effects by combining physiological assessment with RNA-Seq transcriptomic analyses. After a 42-day exposure, earthworm accumulated up to 15.9 and 143.3 mg kg-1 of NPs for the low (0.3 mg kg-1) and high (3 mg kg-1) dose groups, respectively. NPs retention led to the decrease of antioxidant enzyme activity and the accumulation of reactive oxygen species (O2- and H2O2), which reduced growth rate by 21.3 %-50.8 % and caused pathological abnormalities. These adverse effects were enhanced by the positively charged NPs. Furthermore, we observed that irrespective of surface charge, after 2 h of exposure, NPs were gradually internalized by earthworm coelomocytes (∼0.12 µg per cell) and mainly amassed at lysosomes. Those agglomerations stimulated lysosomal membranes to lose stability and even rupture, resulting in impeded autophagy process and cellular clearance, and eventually coelomocyte death. In comparison with negatively charged nanoplastics, the positively charged NPs exerted 83 % higher cytotoxicity. Our findings provide a better understanding of how NPs posed harmful effects on soil fauna and have important implications for evaluating the ecological risk of NPs.

Nanoplastics alter ecosystem multifunctionality and may increase global warming potential.

Although the presence of nanoplastics in aquatic and terrestrial ecosystems has received increasing attention, little is known about its potential effect on ecosystem processes and functions. Here, we evaluated if differentially charged polystyrene (PS) nanoplastics (PS-NH2 and PS-SO3 H) exhibit distinct influences on microbial community structure, nitrogen removal processes (denitrification and anammox), emissions of greenhouse gases (CO2 , CH4 , and N2 O), and ecosystem multifunctionality in soils with and without earthworms through a 42-day microcosm experiment. Our results indicated that nanoplastics significantly altered soil microbial community structure and potential functions, with more pronounced effects for positively charged PS-NH2 than for negatively charged PS-SO3 H. Ecologically relevant concentration (3 g kg-1 ) of nanoplastics inhibited both soil denitrification and anammox rates, while environmentally realistic concentration (0.3 g kg-1 ) of nanoplastics decreased the denitrification rate and enhanced the anammox rate. The soil N2 O flux was always inhibited 6%-51% by both types of nanoplastics, whereas emissions of CO2 and CH4 were enhanced by nanoplastics in most cases. Significantly, although N2 O emissions were decreased by nanoplastics, the global warming potential of total greenhouse gases was increased 21%-75% by nanoplastics in soils without earthworms. Moreover, ecosystem multifunctionality was increased 4%-12% by 0.3 g kg-1 of nanoplastics but decreased 4%-11% by 3 g kg-1 of nanoplastics. Our findings provide the only evidence to date that the rapid increase in nanoplastics is altering not only ecosystem structure and processes but also ecosystem multifunctionality, and it may increase the emission of CO2 and CH4 and their global warming potential to some extent.

Automatic detection of indoor occupancy based on improved YOLOv5 model.

Indoor occupancy detection is essential for energy efficiency control and Coronavirus Disease 2019 traceability. The number and location of people can be accurately identified and determined through classroom surveillance video analysis. This information is used to manage environmental equipment such as HVAC and lighting systems to reduce energy use. However, the mainstream one-stage YOLO algorithm still uses an anchor-based mechanism and couples detection heads to predict. This results in slow model convergence and poor detection performance for densely occluded targets. Therefore, this paper proposed a novel decoupled anchor-free VariFocal loss convolutional network algorithm DFV-YOLOv5 for occupancy detection to tackle these problems. The proposed method uses the YOLOv5 algorithm as a baseline. It uses the anchor-free mechanism to reduce the number of design parameters needing heuristic tuning. Afterwards, to reduce the coupling of the model, speed up the model's convergence ability, and improve the model detection performance, the detection head is decoupled based on the YOLOv5 model. It can resolve the conflict between classification and regression tasks. In addition, we use the VariFocal loss to assign more weights to difficult data points to optimize the class imbalance problem and use the training target q to measure positive samples, treating positive and negative samples asymmetrically. The total loss function is redesigned, the L 1 loss is increased, and the ablation experiment verifies the effect of the improved loss. By applying a hybrid activation function of the sigmoid linear unit and rectified linear unit, we improved the model's nonlinear representation and reduced the model's inference time. Finally, a classroom dataset was constructed to validate the occupancy detection performance of the model. The proposed model was compared with mainstream target detection models regarding average mean precision, memory allocation, execution time, and the number of parameters on the VOC2012, CrowdHuman and self-built datasets. The experimental results show that the method significantly improves the detection accuracy and robustness, shortens the inference time, and proves the practicality of the algorithm in occupancy detection compared with the mainstream target detection model and related variants of the model.

The Split-Half Reliability and Construct Validity of the Virtual Reality-Based Path Integration Task in the Healthy Population.

OBJECTIVE: The virtual reality (VR)-based path integration task shows substantial promise in predicting dementia risk. However, the reliability and validity in healthy populations need further exploration. The present study investigates the relationship between task indicators and brain structures in a healthy population using a VR-based navigation task, particularly the entorhinal cortex (EC) and hippocampus. METHODS: Sixty healthy adults were randomly recruited to perform a VR-based path integration task, the digit span task (DST), and an MRI scan. The indicators of the VR-based path integration task were calculated, including the absolute distance error (ADE), degree of angle deviation (DAD), degree of path deviation (DPD), and return time (Time). The reliability of the above indicators was then estimated using the split-half method and Cronbach's alpha. Correlation and regression analyses were then performed to examine the associations between these indicators and age, general cognitive ability (DST), and brain structural measures. RESULTS: ADE, DAD, and DPD showed reasonable split-half reliability estimates (0.84, 0.81, and 0.72) and nice Cronbach's alpha estimates (0.90, 0.86, and 0.96). All indicators correlated with age and DST. ADE and DAD were sensitive predictors of hippocampal volume, and return time was a predictor of EC thickness. CONCLUSION: Our findings demonstrate that the VR-based path integration task exhibits good reliability and validity in the healthy population. The task indicators are age-sensitive, can capture working memory capacity, and are closely related to the integrity of individual EC and hippocampal structures.