HnRNPAB promotes pancreatic ductal adenocarcinoma extravasation and liver metastasis by stablizing MYC mRNA.

Heterogeneous nuclear ribonucleoprotein AB (hnRNPAB) is considered a cancer-promoting heterogeneous nuclear ribonucleoprotein in many cancers, but its function in pancreatic ductal adenocarcinoma (PDAC) is poorly understood. HnRNPAB was highly expressed in PDAC tissues compared to normal pancreatic tissues, and high expression of hnRNPAB was associated with poor overall survival and recurrence-free survival in PDAC patients. HnRNPAB promotes migration and invasion of PDAC cells in vitro. In xenograft tumor mouse models, hnRNPAB deprivation significantly attenuated liver metastasis. HnRNPAB mRNA and protein levels are positively associated with MYC in PDAC cells. Mechanistically, hnRNPAB bound to MYC mRNA and prolonged its half-life of MYC mRNA. HnRNPAB induced PDAC cells to secret CXCL8 via MYC, which promoted neutrophils recruitment and facilitated tumor cells entrancing into the hepatic parenchyma. These findings point to a novel regulatory mechanism via which hnRNPAB promotes PDAC metastasis. Implications: Hnrnpab participates in the post-transcriptional regulation of the oncogene MYC by binding and stabilizing MYC mRNA, thereby promoting liver metastasis in PDAC.

A novel optimization rainfall coupling model based on stepwise decomposition technique.

Traditional decomposition integration models decompose the original sequence into subsequences, which are then proportionally divided into training and testing periods for modeling. Decomposition may cause data aliasing, then the decomposed training period may contain part of the test period data. A more effective method of sample construction is sought in order to accurately validate the model prediction accuracy. Semi-stepwise decomposition (SSD), full stepwise decomposition (FSD), single model semi-stepwise decomposition (SMSSD), and single model full stepwise decomposition (SMFSD) techniques were used to create the samples. This study integrates Variational Mode Decomposition (VMD), African Vulture Optimization Algorithm (AVOA), and Least Squares Support Vector Machine (LSSVM) to construct a coupled rainfall prediction model. The influence of different VMD parameters α is examined, and the most suitable stepwise decomposition machine learning coupled model algorithm for various stations in the North China Plain is selected. The results reveal that SMFSD is relatively the most suitable tool for monthly precipitation forecasting in the North China Plain. Among the predictions for the five stations, the best overall performance is observed at Huairou Station (RMSE of 18.37 mm, NSE of 0.86, MRE of 107.2%) and Jingxian Station (RMSE of 24.74 mm, NSE of 0.86, MRE of 51.71%), while Hekou Station exhibits the poorest performance (RMSE of 25.11 mm, NSE of 0.75, MRE of 173.75%).

Bimodality in Ras signaling originates from processivity of the Ras activator SOS without deterministic bistability.

Ras is a small GTPase that is central to important functional decisions in diverse cell types. An important aspect of Ras signaling is its ability to exhibit bimodal or switch-like activity. We describe the total reconstitution of a receptor-mediated Ras activation-deactivation reaction catalyzed by SOS and p120-RasGAP on supported lipid membrane microarrays. The results reveal a bimodal Ras activation response, which is not a result of deterministic bistability but is rather driven by the distinct processivity of the Ras activator, SOS. Furthermore, the bimodal response is controlled by the condensation state of the scaffold protein, LAT, to which SOS is recruited. Processivity-driven bimodality leads to stochastic bursts of Ras activation even under strongly deactivating conditions. This behavior contrasts deterministic bistability and may be more resistant to pharmacological inhibition.

Electric Field Effect of the Plasma-Initiated Polymerization of Methyl Methacrylate: A Negatively Charged Long-Lived Radical.

Plasma-initiated polymerization (PIP) is generally attributed to a radical process due to its inhibiting property. However, its unique polymerization behaviors like long-lived radical and solvent effect do not comply well with the traditional radical mechanism. Herein, the PIP of methyl methacrylate (MMA) was conducted in a high-voltage DC electric field to investigate the charged nature of its radicals. Consequently, the polymerization presented a preferential distribution of polymers at the anode but not the cathode, revealing the negatively charged nature of the growing radicals. An acceleration phenomenon, accompanied by the growth in molecular weights and the reduction in molecular weight distributions (Ð), was observed at the voltages above 16 kV, suggesting the dissociation of ion pairs of growing radicals. The PIP yielded PMMA with analogous chemical and steric structures to those of PMMA from traditional radical initiation, whether in the presence or absence of the external electric field. This work offers new insights into the PIP of vinyl monomers, wherein a one-electron transfer reaction is inferred to be involved in the monomer activation.

Development of machine learning models to predict perioperative blood transfusion in hip surgery.

BACKGROUND: Allogeneic Blood transfusion is common in hip surgery but is associated with increased morbidity. Accurate prediction of transfusion risk is necessary for minimizing blood product waste and preoperative decision-making. The study aimed to develop machine learning models for predicting perioperative blood transfusion in hip surgery and identify significant risk factors. METHODS: Data of patients undergoing hip surgery between January 2013 and October 2021 in the Peking Union Medical College Hospital were collected to train and test predictive models. The primary outcome was perioperative red blood cell (RBC) transfusion within 72 h of surgery. Fourteen machine learning algorithms were established to predict blood transfusion risk incorporating patient demographic characteristics, preoperative laboratory tests, and surgical information. Discrimination, calibration, and decision curve analysis were used to evaluate machine learning models. SHapley Additive exPlanations (SHAP) was performed to interpret models. RESULTS: In this study, 2431 hip surgeries were included. The Ridge Classifier performed the best with an AUC = 0.85 (95% CI, 0.81 to 0.88) and a Brier score = 0.21. Patient-related risk factors included lower preoperative hemoglobin, American Society of Anesthesiologists (ASA) Physical Status > 2, anemia, lower preoperative fibrinogen, and lower preoperative albumin. Surgery-related risk factors included longer operation time, total hip arthroplasty, and autotransfusion. CONCLUSIONS: The machine learning model developed in this study achieved high predictive performance using available variables for perioperative blood transfusion in hip surgery. The predictors identified could be helpful for risk stratification, preoperative optimization, and outcomes improvement.

Sustained Secretion of CCL21 via an Implantable Cell Reservoir Hydrogel Enhances the Systemic Antitumor Effect of Radiotherapy.

The combination of radiotherapy (RT) and immunotherapy shows promise in improving the clinical treatment of solid tumors; however, it faces challenges of low response rates and systemic toxicity. Herein, an implantable alginate/collagen hydrogel encapsulating C-C motif ligand 21 (CCL21)-expressing dendritic cells (CCL21-DCs@gel) was developed to potentiate the systemic antitumor effects of RT. The hydrogel functioned as a suitable reservoir for in vivo culture and proliferation of CCL21-DCs, thereby enabling sustained CCL21 release. The local CCL21 gradient induced by CCL21-DCs@gel significantly enhanced the efficacy of RT in suppressing primary tumor growth and inhibiting distant metastasis across several mouse models. Furthermore, the combination of RT with CCL21-DCs@gel provided complete prophylactic protection to mice. Mechanistic investigations revealed that CCL21-DCs@gel potentiated RT by promoting tumor lymphangiogenesis and attracting immune cell infiltration into the tumor. Collectively, these results suggest that CCL21-DCs@gel is a promising adjunct to RT for effectively eradicating tumors and preventing tumor recurrence.

Proteomic, single-cell and bulk transcriptomic analysis of plasma and tumor tissues unveil core proteins in response to anti-PD-L1 immunotherapy in triple negative breast cancer.

BACKGROUND: Anti-PD-1/PD-L1 treatment has achieved durable responses in TNBC patients, whereas a fraction of them showed non-sensitivity to the treatment and the mechanism is still unclear. METHODS: Pre- and post-treatment plasma samples from triple negative breast cancer (TNBC) patients treated with immunotherapy were measured by tandem mass tag (TMT) mass spectrometry. Public proteome data of lung cancer and melanoma treated with immunotherapy were employed to validate the findings. Blood and tissue single-cell RNA sequencing (scRNA-seq) data of TNBC patients treated with or without immunotherapy were analyzed to identify the derivations of plasma proteins. RNA-seq data from IMvigor210 and other cancer types were used to validate plasma proteins in predicting response to immunotherapy. RESULTS: A random forest model constructed by FAP, LRG1, LBP and COMP could well predict the response to immunotherapy. The activation of complement cascade was observed in responders, whereas FAP and COMP showed a higher abundance in non-responders and negative correlated with the activation of complements. scRNA-seq and bulk RNA-seq analysis suggested that FAP, COMP and complements were derived from fibroblasts of tumor tissues. CONCLUSIONS: We constructe an effective plasma proteomic model in predicting response to immunotherapy, and find that FAP+ and COMP+ fibroblasts are potential targets for reversing immunotherapy resistance.

Human lung cancer-derived mesenchymal stem cells promote tumor growth and immunosuppression.

BACKGROUND: The presence of mesenchymal stem cells has been confirmed in some solid tumors where they serve as important components of the tumor microenvironment; however, their role in cancer has not been fully elucidated. The aim of this study was to investigate the functions of mesenchymal stem cells isolated from tumor tissues of patients with non-small cell lung cancer. RESULTS: Human lung cancer-derived mesenchymal stem cells displayed the typical morphology and immunophenotype of mesenchymal stem cells; they were nontumorigenic and capable of undergoing multipotent differentiation. These isolated cells remarkably enhanced tumor growth when incorporated into systems alongside tumor cells in vivo. Importantly, in the presence of mesenchymal stem cells, the ability of peripheral blood mononuclear cell-derived natural killer and activated T cells to mediate tumor cell destruction was significantly compromised. CONCLUSION: Collectively, these data support the notion that human lung cancer-derived mesenchymal stem cells protect tumor cells from immune-mediated destruction by inhibiting the antitumor activities of natural killer and T cells.

Case reports on uniparental disomy of chromosomes 6 and 3 in paternity testing.

In paternity testing, when there are Mendelian errors in the alleles between the child and the parents, a slippage mutation, or silent allele may not fully explain the phenomenon. Sometimes, it is attributed to chromosomal abnormalities, such as uniparental disomy (UPD). Here, we present the investigation of two cases of suspected UPD in paternity testing based on short tandem repeat (STR) detection (capillary electrophoresis platform). Case 1 involves a trio, where all genotypes detected on chromosome 6 in the child are homozygous and found in the father. Case 2 is a duo (mother and child), where all genotypes on chromosome 3 in the child are homozygous and not always found in the mother. At the same time, Mendelian error alleles were also observed at specific loci in these two chromosomes. Furthermore, we used the MGIEasy Signature Identification Library Prep Kit for sequencing on the massively parallel sequencing platform, which included common autosomal, X and Y chromosomes, and mitochondrial genetic markers used in forensic practice. The results showed that the genotypes of shared STRs on the two platforms were consistent, and STRs and single nucleotide polymorphisms (SNPs) on these two chromosomes were homozygous. All other genetic markers followed the laws of inheritance. A comprehensive analysis supported the parent-child relationship between the child and the alleged parent, and the observed genetic anomalies can be attributed to UPD. UPD occurrences are rare, and ignoring its presence can lead to erroneous exclusions in paternity testing, particularly when multiple loci on a chromosome exhibit homozygosity.

Expression landscape of cancer-FOXP3 and its prognostic value in pancreatic adenocarcinoma.

FOXP3, a key identifier of Treg, has also been identified in tumor cells, which is referred to as cancer-FOXP3 (c-FOXP3). Human c-FOXP3 undergoes multiple alternative splicing events, generating several isoforms, like c-FOXP3FL and c-FOXP3Δ3. Previous research on c-FOXP3 often ignore its cellular source (immune or tumor cells) and isoform expression patterns, which may obscure our understanding of its clinical significance. Our immunohistochemistry investigations which conducted across 18 tumors using validated c-FOXP3 antibodies revealed distinct expression landscapes for c-FOXP3 and its variants, with the majority of tumors exhibited a predominantly expression of c-FOXP3Δ3. In pancreatic ductal adenocarcinoma (PDAC), we further discovered a potential link between nuclear c-FOXP3Δ3 in tumor cells and poor prognosis. Overexpression of c-FOXP3Δ3 in tumor cells was associated with metastasis. This work elucidates the expression pattern of c-FOXP3 in pan-cancer and indicates its potential as a prognostic biomarker in clinical settings, offering new perspectives for its clinical application.

Oxygen Self-Supplied Perfluorocarbon-Modified Micelles for Enhanced Cancer Photodynamic Therapy and Ferroptosis.

Photodynamic therapy (PDT) and ferroptosis show significant potential in tumor treatment. However, their therapeutic efficacy is often hindered by the oxygen-deficient tumor microenvironment and the challenges associated with efficient intracellular drug delivery into tumor cells. Toward this end, this work synthesized perfluorocarbon (PFC)-modified Pluronic F127 (PFC-F127), and then exploits it as a carrier for codelivery of photosensitizer Chlorin e6 (Ce6) and the ferroptosis promoter sorafenib (Sor), yielding an oxygen self-supplying nanoplatform denoted as Ce6-Sor@PFC-F127. The PFCs on the surface of the micelle play a crucial role in efficiently solubilizing and delivering oxygen as well as increasing the hydrophobicity of the micelle surface, giving rise to enhanced endocytosis by cancer cells. The incorporation of an oxygen-carrying moiety into the micelles enhances the therapeutic impact of PDT and ferroptosis, leading to amplified endocytosis and cytotoxicity of tumor cells. Hypotonic saline technology was developed to enhance the cargo encapsulation efficiency. Notably, in a murine tumor model, Ce6-Sor@PFC-F127 effectively inhibited tumor growth through the combined use of oxygen-enhanced PDT and ferroptosis. Taken together, this work underscores the promising potential of Ce6-Sor@PFC-F127 as a multifunctional therapeutic nanoplatform for the codelivery of multiple cargos such as oxygen, photosensitizers, and ferroptosis inducers.

TSPAN8+ myofibroblastic cancer-associated fibroblasts promote chemoresistance in patients with breast cancer.

Cancer-associated fibroblasts (CAFs) are abundant stromal cells in the tumor microenvironment that promote cancer progression and relapse. However, the heterogeneity and regulatory roles of CAFs underlying chemoresistance remain largely unclear. Here, we performed a single-cell analysis using high-dimensional flow cytometry analysis and identified a distinct senescence-like tetraspanin-8 (TSPAN8)+ myofibroblastic CAF (myCAF) subset, which is correlated with therapeutic resistance and poor survival in multiple cohorts of patients with breast cancer (BC). TSPAN8+ myCAFs potentiate the stemness of the surrounding BC cells through secretion of senescence-associated secretory phenotype (SASP)-related factors IL-6 and IL-8 to counteract chemotherapy. NAD-dependent protein deacetylase sirtuin 6 (SIRT6) reduction was responsible for the senescence-like phenotype and tumor-promoting role of TSPAN8+ myCAFs. Mechanistically, TSPAN8 promoted the phosphorylation of ubiquitin E3 ligase retinoblastoma binding protein 6 (RBBP6) at Ser772 by recruiting MAPK11, thereby inducing SIRT6 protein destruction. In turn, SIRT6 down-regulation up-regulated GLS1 and PYCR1, which caused TSPAN8+ myCAFs to secrete aspartate and proline, and therefore proved a nutritional niche to support BC outgrowth. By demonstrating that TSPAN8+SIRT6low myCAFs were tightly associated with unfavorable disease outcomes, we proposed that the combined regimen of anti-TSPAN8 antibody and SIRT6 activator MDL-800 is a promising approach to overcome chemoresistance. These findings highlight that senescence contributes to CAF heterogeneity and chemoresistance and suggest that targeting TSPAN8+ myCAFs is a promising approach to circumvent chemoresistance.

Mesenchymal Stromal Cells Increase the Natural Killer Resistance of Circulating Tumor Cells via Intercellular Signaling of cGAS-STING-IFNß-HLA.

Circulating tumor cells (CTCs) shed from primary tumors must overcome the cytotoxicity of immune cells, particularly natural killer (NK) cells, to cause metastasis. The tumor microenvironment (TME) protects tumor cells from the cytotoxicity of immune cells, which is partially executed by cancer-associated mesenchymal stromal cells (MSCs). However, the mechanisms by which MSCs influence the NK resistance of CTCs remain poorly understood. This study demonstrates that MSCs enhance the NK resistance of cancer cells in a gap junction-dependent manner, thereby promoting the survival and metastatic seeding of CTCs in immunocompromised mice. Tumor cells crosstalk with MSCs through an intercellular cGAS-cGAMP-STING signaling loop, leading to increased production of interferon-ß (IFNß) by MSCs. IFNß reversely enhances the type I IFN (IFN-I) signaling in tumor cells and hence the expression of human leukocyte antigen class I (HLA-I) on the cell surface, protecting the tumor cells from NK cytotoxicity. Disruption of this loop reverses NK sensitivity in tumor cells and decreases tumor metastasis. Moreover, there are positive correlations between IFN-I signaling, HLA-I expression, and NK tolerance in human tumor samples. Thus, the NK-resistant signaling loop between tumor cells and MSCs may serve as a novel therapeutic target.

Mechanical stress induced mitochondrial dysfunction in cardiovascular diseases: Novel mechanisms and therapeutic targets.

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide. Others and our studies have shown that mechanical stresses (forces) including shear stress and cyclic stretch, occur in various pathological conditions, play significant roles in the development and progression of CVDs. Mitochondria regulate the physiological processes of cardiac and vascular cells mainly through adenosine triphosphate (ATP) production, calcium flux and redox control while promote cell death through electron transport complex (ETC) related cellular stress response. Mounting evidence reveal that mechanical stress-induced mitochondrial dysfunction plays a vital role in the pathogenesis of many CVDs including heart failure and atherosclerosis. This review summarized mitochondrial functions in cardiovascular system under physiological mechanical stress and mitochondrial dysfunction under pathological mechanical stress in CVDs (graphical abstract). The study of mitochondrial dysfunction under mechanical stress can further our understanding of the underlying mechanisms, identify potential therapeutic targets, and aid the development of novel treatments of CVDs.

Fusing Diverse Decision Rules in 3D-Radiomics for Assisting Diagnosis of Lung Adenocarcinoma.

This study aimed to develop an interpretable diagnostic model for subtyping of pulmonary adenocarcinoma, including minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), and invasive adenocarcinoma (IAC), by integrating 3D-radiomic features and clinical data. Data from multiple hospitals were collected, and 10 key features were selected from 1600 3D radiomic signatures and 11 radiological features. Diverse decision rules were extracted using ensemble learning methods (gradient boosting, random forest, and AdaBoost), fused, ranked, and selected via RuleFit and SHAP to construct a rule-based diagnostic model. The model's performance was evaluated using AUC, precision, accuracy, recall, and F1-score and compared with other models. The rule-based diagnostic model exhibited excellent performance in the training, testing, and validation cohorts, with AUC values of 0.9621, 0.9529, and 0.8953, respectively. This model outperformed counterparts relying solely on selected features and previous research models. Specifically, the AUC values for the previous research models in the three cohorts were 0.851, 0.893, and 0.836. It is noteworthy that individual models employing GBDT, random forest, and AdaBoost demonstrated AUC values of 0.9391, 0.8681, and 0.9449 in the training cohort, 0.9093, 0.8722, and 0.9363 in the testing cohort, and 0.8440, 0.8640, and 0.8750 in the validation cohort, respectively. These results highlight the superiority of the rule-based diagnostic model in the assessment of lung adenocarcinoma subtypes, while also providing insights into the performance of individual models. Integrating diverse decision rules enhanced the accuracy and interpretability of the diagnostic model for lung adenocarcinoma subtypes. This approach bridges the gap between complex predictive models and clinical utility, offering valuable support to healthcare professionals and patients.

Application of Multivariate Data Analysis on Historical Recombinant Adenovirus Zoster Vaccine Production Data for Upstream Process Improvements.

In recent years, multivariate data analysis (MVDA) has been widely used for process characterization and fault diagnosis in the biopharmaceutical industry. This study aims to investigate the feasibility of using MVDA for the development and scale-up of a perfusion process for HEK293 cell-based recombinant adenovirus zoster vaccine (Ad-HER) production. The Principal Component Analysis (PCA) results suggested comparable performance among the ATF, PATFP, and BFP perfusion systems in benchtop-scale stirred-tank bioreactor (STR). Then a Batch Evolution Model (BEM) was built using representative data from 10 L STR with a BFP system to assess the Ad-HER perfusion process performance at pilot-scale bioreactor (50 L STR and 50 L wave bioreactor). Furthermore, another BEM model and Batch Level Model (BLM) were built to monitor process parameters over time and predict the final adenovirus titer in 50 L wave bioreactor. The loading plot revealed that lactate dehydrogenase activity, viable cell diameter, and base-added during the virus production phase could be used as preliminary indicators of adenovirus yield. Finally, an adenovirus titer of 2.0±0.3×1010 IFU/mL was achieved in the 50 L wave bioreactor with BFP system, highlighting the robustness of the Ad-HER perfusion process at pilot-scale. Overall, this study emphasizes the effectiveness of MVDA as a tool for advancing the understanding of recombinant adenovirus vaccine perfusion production process development and scale-up.

Competitive and synergic evolution of the water-food-ecology system: A case study of the Beijing-Tianjin-Hebei region, China.

A vital approach to attaining sustainable development lies in the in-depth examination of both competition and synergy between these subsystems from a water-food-ecology (WFE) system perspective, while previous or existing studies have limitations in to quantitative characterize and evaluation the cooperative and competitive relationships between different systems. In this study, an evaluation indicator system is constructed from the two dimensions of resources and efficiency, and the WFE synergic development capacity (WFE-SDC) is proposed by integrating the order degree of the coupled system, enables a multidimensional and comprehensive quantitative assessment of the sustainable development of the WFE system. Then a synergic evolution model is constructed to explore the competitive and synergic evolution of the WFE system in the Beijing-Tianjin-Hebei region. The following key insights were obtained: (1) The WFE-SDC (range of 0-1) shows a fluctuating increase, indicating a shift from mild dysfunctional recession to intermediate synergic development (0.24 to 0.72). (2) Principal factors impeding WFE-SDC encompass diversion water, ecology water consumption, grain demand, reclaimed water consumption, and outbound water, both come from resource dimension, with a combined impediment degree of over 46 %, and the improvement of efficiency dimension may improve the WFE-SDC. (3) The water subsystem acts as a driving force for synergic development, fostering cooperation within the food and ecology subsystems, although they mainly operate in a competitive state. (4) Within the WFE system, Beijing, Tianjin, and Hebei exhibited mutual cooperation and significantly contributed to one another's development. Beijing has played a pivotal role in the progress of both Tianjin and Hebei. This study offers valuable insights for the formulation of policies and the application of technical approaches for the sustainable development of the WFE system in relevant regions.

Tumor Immune Infiltration and Clinical Impact of Specific BCG-Related Genes in Melanoma.

Melanoma, caused by malignant melanocytes, is known for its invasiveness and poor prognosis. Therapies are often ineffective due to their heterogeneity and resistance. Bacillus Calmette-Guérin (BCG), primarily a tuberculosis vaccine, shows potential in treating melanoma by activating immune responses. In this study, data from The Cancer Genome Atlas and the NCBI GEO database were utilized to determine pivotal differentially expressed genes (DEGs) such as DSC2, CXCR1, BOK, and CSTB, which are significantly upregulated in BCG treated blood samples and are strongly associated with the prognosis of melanoma. We employ tools like edgeR and ggplot2 for functional and pathway analysis and develop a prognostic model using LASSO Cox regression analysis to predict patient survival. A notable finding is the correlation between BCG-related genes and immune cell infiltration in melanoma, highlighting the potential of these genes as both biomarkers and therapeutic targets. Additionally, the study examines genetic alterations in these genes and their impact on the disease. This study highlights the necessity of further exploring BCG-related genes for insights into melanoma pathogenesis and treatment enhancement, suggesting that BCG's role in immune activation could offer novel therapeutic avenues in cancer treatment.

Dynamics of carbon storage driven by land use/land cover transformation in coal mining areas with a high groundwater table: A case study of Yanzhou Coal Mine, China.

Intensive anthropogenic activities have led to drastic changes in land use/land cover (LULC) and impacted the carbon storage in high-groundwater coal basins. In this paper, we conduct a case study on the Yanzhou Coalfield in Shandong Province of China. We further classify waterbodies by using the Google Earth Engine (GEE) to better investigate the process of LULC transformation and the forces driving it in four periods from 1985 to 2020 (i.e., 1985-1995, 1995-2005, 2005-2015, and 2015-2020). We modeled the spatiotemporal dynamics of carbon storage by using InVEST based on the transformation in LULC and its drivers, including mining (M), reclamation (R), urbanization and village relocation (U), and ecological restoration (E). The results indicate that carbon storage had depleted by 19.69 % (321099.06 Mg) owing to intensive transformations in LULC. The area of cropland shrank with the expansion of built-up land and waterbodies, and 56.31 % of the study area underwent transitions in land use in the study period. U was the primary driver of carbon loss while E was the leading driver of carbon gain. While the direct impact of M on carbon loss accounted for only 5.23 % of the total, it affected urbanization and led to village relocation. R led to the recovery of cropland and the reclamation of water for aquaculture, which in turn improved the efficiency of land use. However, it contributed only 2.09 % to the total increase in carbon storage. Numerous complicated and intertwined processes (211) drove the changes in carbon storage in the study area. The work here provides valuable information for decision-makers as well as people involved in reclamation and ecological restoration to better understand the link between carbon storage and the forces influencing it. The results can be used to integrate the goals of carbon sequestration into measures for land management.