A mouse protozoan boosts antigen-specific mucosal IgA responses in a specific lipid metabolism- and signaling-dependent manner.

IgA antibodies play an important role in mucosal immunity. However, there is still no effective way to consistently boost mucosal IgA responses, and the factors influencing these responses are not fully understood. We observed that colonization with the murine intestinal symbiotic protozoan Tritrichomonas musculis (T.mu) boosted antigen-specific mucosal IgA responses in wild-type C57BL/6 mice. This enhancement was attributed to the accumulation of free arachidonic acid (ARA) in the intestinal lumen, which served as a signal to stimulate the production of antigen-specific mucosal IgA. When ARA was prevented from undergoing its downstream metabolic transformation using the 5-lipoxygenase inhibitor zileuton or by blocking its downstream biological signaling through genetic deletion of the Leukotriene B4 receptor 1 (Blt1), the T.mu-mediated enhancement of antigen-specific mucosal IgA production was suppressed. Moreover, both T.mu transfer and dietary supplementation of ARA augmented the efficacy of an oral vaccine against Salmonella infection, with this effect being dependent on Blt1. Our findings elucidate a tripartite circuit linking nutrients from the diet or intestinal microbiota, host lipid metabolism, and the mucosal humoral immune response.

Lifestyle deterioration linked to elevated inflammatory cytokines over a two-month follow-up.

Healthy lifestyle reduces the risk of inflammation-related diseases. This study assessed how lifestyle changes affect inflammatory cytokines over 2 months. Involving 179 apparently healthy participants recruited from community, collecting data on lifestyles (smoking, alcohol, BMI, daily activity, sleep, diet) and measured inflammatory cytokines (TNF-α, IL-1ß, IL-17A, CRP, IL-8, IL-18, IFN-γ) plus pepsinogens (PG I, PG II) at the baseline and 2-month follow-up. The combined adverse lifestyle score is the sum of scores across six lifestyles, with higher scores indicating more adverse lifestyle factors. Use multiple linear regression and mixed linear models to analyze the relationship between the changes in lifestyle and inflammatory cytokines (follow-up values minus baseline values). For every 1-point increase in combined adverse lifestyle score, IL-17A increased by 0.98 (95% CI 0.23, 1.73) pg/mL, IFN-γ increased by 1.79 (95% CI 0.39, 3.18) pg/mL. Decreased changes in daily activity were associated with higher IL-17A (ß = 1.83, 95% CI 0.53, 3.13) and IFN-γ (ß = 2.59, 95% CI 0.9, 4.98). Excluding daily activity, changes in combined adverse lifestyle scores were not associated with changes in inflammatory cytokines. Lifestyle improvements at 2-month intervals may reduce TNF-α, IL-17A and IFN-γ, with daily activity making the greatest contribution.

Distribution and provenance analysis of polycyclic aromatic hydrocarbons in surface sediments of the East China Sea.

A total of 32 surface sediment samples were collected from the East China Sea (ECS) to investigate the distribution of polycyclic aromatic hydrocarbons (PAHs) in the surface sediments and evaluate their sources. The content of PAHs in the ECS surface sediments ranged from 2.3 ng/g to 57.8 ng/g. The source analysis revealed that the combustion of such fuels as petroleum is the main contribution source of PAHs in the ECS surface sediments, and oil spill is another important contribution source. The study also showed that the content of PAHs in the ECS surface sediments is low and does not cause adverse ecological risks.

Effects of modification methods on the structural characteristics and functional properties of dietary fiber from cucumber.

Cucumbers produce by-products such as cucumber pomace during processing and most of them are discarded without being utilized. To effectively utilize the waste, cucumber pomace is used to extract both insoluble and soluble dietary fibers (DFs) using compound enzyme method (ME), High pressure processing assisted ME (HPP-ME), and dynamic high-pressure microfluidization-assisted ME (DHPM-ME). The results showed that DHPM-ME improved the extraction rate of soluble DFs most effectively, increasing it from 1.74 % to 4.08 %. The modified DFs exhibited enhanced hydration properties and functional properties after HPP-ME- and DHPM-ME-mediated auxiliary treatment. Additionally, the modified DFs exhibited improved thermal stability, increased absorption peaks in the infrared spectra, decreased crystallinity, improved glucose and cholesterol adsorption ability, and delayed glucose adsorption. The cucumber pomace-derived modified DFs can be used as a functional food additive in bakery, meat, dairy products, and beverages, and their effective use can further enhance the economic benefits.

Linking clinical trial participants to their U.S. real-world data through tokenization: A practical guide.

In drug development, the use of real-world data (RWD) has augmented our understanding of patients' health care experiences and the effects of treatments beyond clinical trials. Although electronic health record (EHR) data integration at clinical trial sites is a widely adopted practice, primarily for recruitment and data capture, a challenge to data utility is the fragmentation of health data across different sources. Linking RWD sources to each other and to trial data -- while preserving patient privacy through tokenization -- aids in filling evidence gaps with outcome data and facilitates the generalization of effects from controlled trial environments to real-world settings. This paper describes the applications of RWD linkage and how they benefit both clinical development and real-world decision-making. Trial benefits include improving interpretability and generalizability (e.g., by remediating missing data or losses to follow-up), extending follow-up beyond trial closeout, and characterizing the applicability of trial results to under-represented groups. The operational aspects of linking trial data to RWD are addressed, emphasizing the importance of using privacy-preserving record linking systems with established metrics of accuracy and precision, managing consent, and providing the necessary training and resources at trial sites to inform participants about providing access to their RWD through data linkage.

Multi-echo three-dimensional (3D) Dixon sequence combined with disodium gadolinium for risk stratification of advanced fibrosis in metabolic dysfunction-associated steatotic liver disease.

Background: The hepatic steatosis and fibrosis related to metabolic dysfunction-associated steatotic liver disease (MASLD) are important factors in the progression. The Multi echo three-dimensional (3D) Dixon sequence can obtain a single breath hold scan for a fat fraction map and an R2* map. The R2* value is usually used to evaluate iron deposition. Whether the change in R2* value is related to liver fibrosis after injection of gadolinium disulfide (Gd) should be noted. This study evaluates the value of enhanced magnetic relaxation time in the risk stratification of liver fibrosis by analyzing the changes in R2* before and after Gd enhancement, and explores the potential application of Multi echo 3D Dixon sequence in one-stop evaluation of MASLD. Methods: This retrospective study included 138 MASLD patients who underwent Gadolinum ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) magnetic resonance imaging (MRI) examination in The First Affiliated Hospital of Chongqing Medical University from June 2020 to December 2021. Finally, 90 subjects were divided into moderate and high-risk fibrosis group and low-risk fibrosis group by two-step assessment of liver fibrosis. Multi-echo 3D chemical shift imaging sequence (Q-Dixon) sequences and gradient-echo T1WI (Vibe-Dixon) sequence were performed during the non-enhanced phase and hepatobiliary phase, respectively, and then the signal-intensity enhancement (SE) and magnetic relaxation-time enhancement (RE) values were calculated. The interobserver correlation coefficient was used to evaluate the consistency between observers. Univariate t-test was used to analyze the differences in RE and SE of liver fibrosis among different risk levels. Delong analysis was performed on receiver operating characteristic (ROC) curve to evaluate the difference in diagnostic efficacy between RE and SE in differentiating the risk level of liver fibrosis. Results: Among the 90 patients, 55 (61.1%) belonged to the low-risk group and 35 (38.9%) belonged to the medium-to-high-risk group. The average RE and SE values were 1.23±0.15 and 1.57±0.23 in the low-risk group and 0.99±0.09 and 1.38±0.21 in both the medium-to-high-risk group (P<0.01). The ROC curve showed that the area under the curve (AUC) value of RE was 0.922, with a corresponding optimal threshold of 0.713, sensitivity of 0.852, and specificity of 0.861. The AUC value of SE was 0.724, with a corresponding optimal threshold of 0.352, sensitivity of 0.519, and specificity of 0.833. The AUC difference between RE and SE for the predictive value of different risk assessments was 0.198, and the 95% confidence interval of the difference was 0.084-0.312. The Delong test showed that the difference was significant (P<0.01). Conclusions: Magnetic RE had high effectiveness for distinguishing between liver-fibrosis risk levels. The combination of the Q-Dixon sequence and Gd-EOB-DTPA has the potential of one-stop evaluation of MASLD.

Serum PCSK9 is a novel serological biomarker for the diagnosis and prognosis of pancreatic cancer.

Background: Although CA19-9 is an essential blood biomarker of pancreatic cancer (PC), its sensitivity and specificity are limited for early detection. Methods: We analyzed the serum proprotein convertase subtilisin/kexin type 9 (sPCSK9) in PC patients, benign disease groups (BDG), and healthy controls (HC) by ELISA. Results: Consistently, sPCSK9 was considerably lower in PC patients than in HC (Z = -2.546, P < 0.05), and sPCSK9 in PC patients was statistically significantly higher than in BDG (Z = -5.457, P < 0.001). sPCSK9 was linked to the invasion of lymph nodes (χ2 = 6.846, P < 0.01). According to ROC curves, combining sPCSK9 with CA19-9 could potentially enhance the diagnostic capability of CA19-9 in early-stage PC patients. Furthermore, the low sPCSK9 group (n = 41) exhibited statistically significantly prolonged overall survival compared to the high sPCSK9 group (n = 15), with median survival times of 27 months (95% CI [17.59-36.41]) and 11 months (95% CI [7.21-14.79]), respectively (P = 0.022). Conclusion: The diagnostic performance of CA19-9 for early-stage PC patients could be improved by combining sPCSK9 with CA19-9. Moreover, the higher sPCSK9 group has a significantly shorter overall survival rate.

Flexible Temperature Sensor with High Reproducibility and Wireless Closed-Loop System for Decoupled Multimodal Health Monitoring and Personalized Thermoregulation.

Temperature and pulse waves are two fundamental indicators of body health. Specifically, thermoresistive flexible temperature sensors are one of the most applied sensors. However, they suffer from poor reproducibility of resistivity; and decoupling temperature from pressure/strain is still challenging. Besides, autonomous thermoregulation by wearable sensory systems is in high demand, but conventional commercial apparatuses are cumbersome and not suitable for long-term portable use. Here, a material-design strategy is developed to overcome the problem of poor reproducibility of resistivity by tuning the thermal expansion coefficient to nearly zero, precluding the detriment caused by shape expansion/shrinkage with temperature variation and achieving high reproducibility. The strategy also obtains more reliable sensitivity and higher stability, and the designed thermoresistive fiber has strain-insensitive sensing performance and fast response/recovery time. A smart textile woven by the thermoresistive fiber can decouple temperature and pulse without crosstalk; and a flexible wireless closed-loop system comprising the smart textile, a heating textile, a flexible diminutive control patch, and a smartphone is designed and constructed to monitor health status in real-time and autonomously regulate body temperature. This work offers a new route to circumvent temperature-sensitive effects for flexible sensors and new insights for personalized thermoregulation.

Application of spatial omics in gastric cancer.

Gastric cancer (GC), a globally prevalent and lethal malignancy, continues to be a key research focus. However, due to its considerable heterogeneity and complex pathogenesis, the treatment and diagnosis of gastric cancer still face significant challenges. With the rapid development of spatial omics technology, which provides insights into the spatial information within tumor tissues, it has emerged as a significant tool in gastric cancer research. This technology affords new insights into the pathology and molecular biology of gastric cancer for scientists. This review discusses recent advances in spatial omics technology for gastric cancer research, highlighting its applications in the tumor microenvironment (TME), tumor heterogeneity, tumor genesis and development mechanisms, and the identification of potential biomarkers and therapeutic targets. Moreover, this article highlights spatial omics' potential in precision medicine and summarizes existing challenges and future directions. It anticipates spatial omics' continuing impact on gastric cancer research, aiming to improve diagnostic and therapeutic approaches for patients. With this review, we aim to offer a comprehensive overview to scientists and clinicians in gastric cancer research, motivating further exploration and utilization of spatial omics technology. Our goal is to improve patient outcomes, including survival rates and quality of life.

Postoperative adjuvant immunotherapy and molecular targeted therapy for patients of hepatocellular carcinoma with portal vein tumor thrombus after hepatectomy: a propensity score matching study.

Background: Portal vein tumor thrombus (PVTT) is a major risk factor of recurrence of hepatocellular carcinoma (HCC) after hepatectomy. Whether postoperative adjuvant immunotherapy and molecular targeted therapy (I-O and MTT) is effective in reducing the risk of recurrence of HCC with minimal portal invasion after hepatectomy and improving prognosis is unknown. Methods: We collected the data of HCC with Vp1 or Vp2 PVTT patients who underwent hepatectomy at our center between January 2019 and June 2022 from the hospital database. We utilized propensity score matching (PSM) to establish a 1:1 match between the postoperative group treated with I-O and MTT and the postoperative group without I-O and MTT. To compare the recurrence-free survival (RFS) and overall survival (OS) between the two groups, we employed the Kaplan-Meier method. Additionally, we conducted Cox regression analysis to identify the prognostic factors that influence patient prognosis. To account for different high-risk factors, subgroup analyses were carried out. Results: Among the 189 patients included in the study, 42 patients received postoperative adjuvant I-O and MTT. After PSM, the 1, 2-years RFS were 59.2%, 21.3% respectively in the I-O and MTT group and 40.8%, 9.6% respectively in the non-I-O and MTT group. The median RFS was 13.2 months for the I-O and MTT group better than 7.0 months for the non-I-O and MTT group (P = 0.028). 1, 2-years OS were 89.8%, 65.8% respectively in the I-O and MTT group and 42.4%, 27.7% respectively in the non-I-O and MTT group. The median OS was 23.5 months for the I-O and MTT group better than 17.2 months for the non-I-O and MTT group (P = 0.027). Multivariate analysis showed that postoperative adjuvant I-O and MTT was a prognostic protective factor associated with OS and RFS. The most frequent AE observed in this study was pruritus, and rare AEs included decreased platelet, hypothyroidism, proteinuria, myocarditis and hypoadrenocorticism. The incidence of GRADE ≥3 AE with no deaths recorded. Conclusion: The study suggested that postoperative adjuvant I-O and MTT strategy was beneficial to improve the prognosis of HCC patients with PVTT patients, while the therapy was safe and reliable.

Diiron Complexes with Rigid and Conjugated S-to-S Bridges for Electrocatalytic Reduction of CO2.

Electroreduction of CO2 to value-added low-carbon chemicals is a promising way for carbon neutrality and CO2 utilization. It was found that the diiron complex [(µ-bdt)Fe2(CO)6] (bdt = benzene-1,2-dithiolate) has high catalytic activity for electrocatalytic CO2 reduction. To further study the effect of the S-to-S bridge on the catalytic performances of diiron complexes for electrochemical CO2 reduction, four diiron complexes 1-4 with different rigid and conjugated S-to-S bridges were either selected or designed. The electrocatalytic studies showed that under optimal conditions, 2 with a 2,3-naphthalenedithiolato bridge exhibited the lowest catalytic onset potential (Eonset = -1.75 V vs Fc+/0), while 4 with a diphenyl-1,2-vinylidene bridge displayed the highest catalytic activity (TOFmax = 295 s-1), which is 1.5 times that of [(µ-bdt)Fe2(CO)6]. The controlled potential electrolysis experiments of 4 in 0.1 M MeOH/MeCN at -2.35 V vs Fc+/0 gave a total faradaic yield close to 100%, with selectivities of 77%, 9%, and 14% for HCOOH, CO, and H2, respectively. The mechanism for CO2 reduction was studied using density functional theory, IR spectroelectrochemistry, and electrochemical methods. The results indicate that modifying the structure of the S-to-S bridge is an effective strategy to improve the catalytic performance of diiron complexes for electrocatalytic CO2 reduction.

LC/MS-Based Untargeted Lipidomics Reveals Lipid Signatures of Sarcopenia.

Sarcopenia, a multifactorial systemic disorder, has attracted extensive attention, yet its pathogenesis is not fully understood, partly due to limited research on the relationship between lipid metabolism abnormalities and sarcopenia. Lipidomics offers the possibility to explore this relationship. Our research utilized LC/MS-based nontargeted lipidomics to investigate the lipid profile changes as-sociated with sarcopenia, aiming to enhance understanding of its underlying mechanisms. The study included 40 sarcopenia patients and 40 control subjects matched 1:1 by sex and age. Plasma lipids were detected and quantified, with differential lipids identified through univariate and mul-tivariate statistical analyses. A weighted correlation network analysis (WGCNA) and MetaboAna-lyst were used to identify lipid modules related to the clinical traits of sarcopenia patients and to conduct pathway analysis, respectively. A total of 34 lipid subclasses and 1446 lipid molecules were detected. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified 80 differen-tial lipid molecules, including 38 phospholipids. Network analysis revealed that the brown module (encompassing phosphatidylglycerol (PG) lipids) and the yellow module (containing phosphati-dylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM) lipids) were closely associated with the clinical traits such as maximum grip strength and skeletal muscle mass (SMI). Pathway analysis highlighted the potential role of the glycerophospholipid metabolic pathway in lipid me-tabolism within the context of sarcopenia. These findings suggest a correlation between sarcopenia and lipid metabolism disturbances, providing valuable insights into the disease's underlying mechanisms and indicating potential avenues for further investigation.

Loss of histone deubiquitinase Bap1 triggers anti-tumor immunity.

PURPOSE: Immunotherapy using PD-L1 blockade is effective in only a small group of cancer patients, and resistance is common. This emphasizes the importance of understanding the mechanisms of cancer immune evasion and resistance. METHODS: A genome-scale CRISPR-Cas9 screen identified Bap1 as a regulator of PD-L1 expression. To measure tumor size and survival, tumor cells were subcutaneously injected into both syngeneic WT mice and immunocompromised mice. The phenotypic and transcriptional characteristics of Bap1-deleted tumors were examined using flow cytometry, RNA-seq, and CUT&Tag-seq analysis. RESULTS: We found that loss of histone deubiquitinase Bap1 in cancer cells activates a cDC1-CD8+ T cell-dependent anti-tumor immunity. The absence of Bap1 leads to an increase in genes associated with anti-tumor immune response and a decrease in genes related to immune evasion. As a result, the tumor microenvironment becomes inflamed, with more cDC1 cells and effector CD8+ T cells, but fewer neutrophils and regulatory T cells. We also found that the elimination of Bap1-deleted tumors depends on the tumor MHCI molecule and Fas-mediated CD8+ T cell cytotoxicity. Our analysis of TCGA data further supports these findings, showing a reverse correlation between BAP1 expression and mRNA signatures of activated DCs and T-cell cytotoxicity in various human cancers. CONCLUSION: The histone deubiquitinase Bap1 could be used as a biomarker for tumor stratification and as a potential therapeutic target for cancer immunotherapies.

Adaptive self-supervised learning for sequential recommendation.

Sequential recommendation typically utilizes deep neural networks to mine rich information in interaction sequences. However, existing methods often face the issue of insufficient interaction data. To alleviate the sparsity issue, self-supervised learning is introduced into sequential recommendation. Despite its effectiveness, we argue that current self-supervised learning-based (i.e., SSL-based) sequential recommendation models have the following limitations: (1) using only a single self-supervised learning method, either contrastive self-supervised learning or generative self-supervised learning. (2) employing a simple data augmentation strategy in either the graph structure domain or the node feature domain. We believe that they have not fully utilized the capabilities of both self-supervised methods and have not sufficiently explored the advantages of combining graph augmentation schemes. As a result, they often fail to learn better item representations. In light of this, we propose a novel multi-task sequential recommendation framework named Adaptive Self-supervised Learning for sequential Recommendation (ASLRec). Specifically, our framework combines contrastive and generative self-supervised learning methods adaptively, simultaneously applying different perturbations at both the graph topology and node feature levels. This approach constructs diverse augmented graph views and employs multiple loss functions (including contrastive loss, generative loss, mask loss, and prediction loss) for joint training. By encompassing the capabilities of various methods, our model learns item representations across different augmented graph views to achieve better performance and effectively mitigate interaction noise and sparsity. In addition, we add a small proportion of random uniform noise to item representations, making the item representations more uniform and mitigating the inherent popularity bias in interaction records. We conduct extensive experiments on three publicly available benchmark datasets to evaluate our model. The results demonstrate that our approach achieves state-of-the-art performance compared to 14 other competitive methods: the hit rate (HR) improved by over 14.39%, and the normalized discounted cumulative gain (NDCG) increased by over 18.67%.

Functional connectome gradient predicts clinical symptoms of chronic insomnia disorder.

Insomnia is the second most prevalent psychiatric disorder worldwide, but the understanding of the pathophysiology of insomnia remains fragmented. In this study, we calculated the connectome gradient in 50 chronic insomnia disorder (CID) patients and 38 healthy controls (HC) to assess changes due to insomnia and utilized these gradients in a connectome-based predictive modeling (CPM) to predict clinical symptoms associated with insomnia. The results suggested that insomnia led to significant alterations in the functional gradients of some brain areas. Specifically, the gradient scores in the middle frontal gyrus, superior anterior cingulate gyrus, and right nucleus accumbens were significantly higher in the CID patients than in the HC group, whereas the scores in the middle occipital gyrus, right fusiform gyrus, and right postcentral gyrus were significantly lower than in the HC group. Further correlation analysis revealed that the right middle frontal gyrus is positively correlated with the self-rating anxiety scale (r=0.3702). Additionally, the prediction model built with functional gradients could well predict the sleep quality (r=0.5858), anxiety (r=0.6150), and depression (r=0.4022) levels of insomnia patients. This offers an objective depiction of the clinical diagnosis of insomnia, yielding a beneficial impact on the identification of effective biomarkers and the comprehension of insomnia.

ZC3H13-Mediated m6A Modification Ameliorates Acute Myocardial Infarction through Preventing Inflammation, Oxidative Stress and Ferroptosis by Targeting lncRNA93358.

BACKGROUND: Acute myocardial infarction (AMI) is a life-threatening event that is associated with RNA modification and programmed cell death (PCD). This study attempted to investigate the impacts of zinc finger CCCH domain-containing protein 13 (ZC3H13)-mediated N6-methyladenosine (m6A) on ferroptosis in AMI. METHODS: The infarcted areas and cardiac function were evaluated, and the expression level of ZC3H13 was measured in AMI rats that were induced by isoproterenol. Meanwhile, oxygen glucose deprivation (OGD) in vitro model was induced to investigate the alterations on inflammation, oxidative stress and ferroptosis. The m6A modification site of lncRNA93358 modified by ZC3H13 was predicted using bioinformatics, and the interaction between ZC3H13 and lncRNA93358 was verified using the dual-luciferase reporter assays. ZC3H13 was overexpressed and lncRNA93358 was silenced to study their regulatory role in cell death, inflammation, oxidative stress and ferroptosis in AMI. RESULTS: Significant decreased expression of ZC3H13 was observed in AMI rats, with impaired cardiac function, enhanced inflammation and oxidative stress. ZC3H13 targeted the modification site GGACC of lncRNA93358 and downregulated lncRNA93358. Silencing lncRNA93358 inhibited cell death, reduced the levels of inflammatory cytokines tumor necrosis factor (TNF)-α, interleukin (IL)-6 and IL-1ß, suppressed oxidative stress-related indicators (lactate dehydrogenase (LDH), reactive oxygen species (ROS), glutathione (GSH) and malondialdehyde (MDA), as well as downregulated ferroptosis-related acyl-CoA synthetase long chain family member 4 (ACSL4), prostaglandin-endoperoxide synthase 2 (PTGS2) and glutathione peroxidase 4 (GPX4). The effect of silencing lncRNA93358 was further enhanced by overexpression of ZC3H13. CONCLUSION: This study reveals the ZC3H13-mediated epigenetic RNA modification targeting lncRNA93358 and suggests that ZC3H13 overexpression may be a promising approach for AMI treatment.

Exact test and exact confidence interval for the Cox model.

The Cox proportional hazards model is commonly used to analyze time-to-event data in clinical trials. Standard inference procedures for the Cox model are based on asymptotic approximations and may perform poorly when there are few events in one or both treatment groups, as may be the case when the event of interest is rare or when the experimental treatment is highly efficacious. In this article, we propose an exact test of equivalence and efficacy under a proportional hazard model with treatment effect as the only fixed effect, together with an exact confidence interval that is obtained by inverting the exact test. The proposed test is based on a conditional error method originally proposed for sample size reestimation problems. In the present context, the conditional error method is used to combine information from a sequence of hypergeometric distributions, one at each observed event time. The proposed procedures are evaluated in simulation studies and illustrated using real data from an HIV prevention trial. A companion R package "ExactCox" is available for download on CRAN.

An adaptive cycle resilience perspective to understand the regime shifts of social-ecological system interactions over the past two millennia in the Tarim River Basin.

Socio-ecological systems (SESs) in arid regions have experienced multiple transformations throughout history due to human activities and natural forces. However, few studies have used the resilience cycle model to explain the resilience status and determinants of SESs over the past two millennia. This study proposes the adaptive cycle resilience (ACR) perspective to investigate regime shifts of socio-ecological system interactions in the Tarim River Basin (TRB) over the past two millennia. An ACR framework combining a piecewise linear regression model (PLR), ACR theory, and physical resilience models has been built to assess and quantify socio-ecological system resilience. Key indicators such as climate variability, settlement numbers, war frequency, glacier accumulation, and oasis area changes are identified and quantified to evaluate SESs adaptability and transformability. Glacier accumulation serves as a proxy for long-term climate change, while oasis area changes reflect the direct impact of human activities and environmental feedback on ecosystem productivity. Population and war indicators provide insights into social system stability and the impact of conflicts on SESs dynamics. The findings reveal that the 7th century and 1850s are critical points of regime shifts in the ACR. 200s BC-350s AD and 700s AD-900s AD are in the forward loop (r-K) period of the ACR. 350s AD-700s AD and 900s AD-1850s AD are the adaptive resilience backward loop (Ω-α) phase. Assessing the historical socio-ecological system resilience and identifying key transition points can inform proactive measures to mitigate potential regime shifts. Combining historical data with resilience theory provides a deep understanding of the ACR of SESs and their driving factors. This enriches the theoretical understanding of SESs and offers a robust case study for future resilience assessments and scenario analyses in arid regions.