Silver birch, a widely distributed deciduous tree native to Europe, is valued for its wood applications in construction, furniture making, and paper production. In Lithuania, silver birch ranks as the third most common forest-tree species, comprising 22% of the forested areas, and is an important species for tree breeding due to its potential and adaptability. This study was focused on assessing the mechanical properties of wood (sample and log hardness, wood density, dynamic modulus of elasticity (MOEdyn), static modulus of elasticity (MOE) and bending strength (MOR)) in silver birch (Betula pendula L. Roth.) trees from different half-sibling families. Two experimental plantations of the progenies of Lithuanian populations (half-sib families) of silver birch from different regions were analysed. From these plantations, four genetic families were selected for mechanical properties evaluation. The study findings revealed significant variability in various wood properties among different genetic families, although the static modulus of elasticity did not exhibit significant differences between the chosen genetic families. All measured wood properties decreased from the bottom to the top of the model trees. Wood hardness displayed a moderately negative correlation for wood density and weak correlations for MOE and MOR. Given the weak correlations between wood hardness and other wood mechanical properties, it is suggested that MOEdyn would be a more suitable trait for genetic studies. Full article

In this study, we propose coupled time-delayed fractional oscillators with dichotomous fluctuating frequencies and investigate the collective resonant behavior. Firstly, we obtain the condition of complete synchronization between the average behavior of the two oscillators. Subsequently, we derive the precise analytical expression of the output amplitude gain. Based on the analytical results, we observe the collective resonant behavior of the coupled time-delayed system and further study its dependence on various system parameters. The observed results underscore that the coupling strength, fractional order, and time delay play significant roles in controlling the collective resonant behavior by facilitating the occurrence and optimizing the intensity. Finally, numerical simulations are also conducted and verify the accuracy of the analytical results. Full article

With the increasing demand for electricity, the power grid is undergoing significant advancements. Insulators, which serve as protective devices for transmission lines in outdoor high-altitude power systems, are widely employed. However, the detection of defects in insulators captured under challenging conditions, such as rain, snow, fog, sunlight, and fast-moving drones during long-distance photography, remains a major challenge. To address this issue and improve the accuracy of defect detection, this paper presents a novel approach: the Multi-Scale Insulator Defect Detection Approach using Detection Transformer (DETR). In this study, we propose a multi-scale backbone network that effectively captures the features of small objects, enhancing the detection performance. Additionally, we introduce a self-attention upsampling (SAU) module to replace the conventional attention module, enhancing contextual information extraction and facilitating the detection of small objects. Furthermore, we introduce the insulator defect (IDIoU) loss, which mitigates the instability in the matching process caused by small defects. Extensive experiments were conducted on an insulator defect dataset to evaluate the performance of our proposed method. The results demonstrate that our approach achieves outstanding performance, particularly in detecting small defects. Compared to existing methods, our approach exhibits a remarkable 7.47% increase in the average precision, emphasizing its efficacy in insulator defect detection. The proposed method not only enhances the accuracy of defect detection, which is crucial for maintaining the reliability and safety of power transmission systems but also has broader implications for the maintenance and inspection of high-voltage power infrastructure. Full article

Proteogenomics represents a transformative intersection in nephrology, uniting genomics, transcriptomics, and proteomics to unravel the molecular intricacies of kidney diseases. This review encapsulates the methodological essence of proteogenomics and its profound implications in chronic kidney disease (CKD) research. We explore the proteogenomic pipeline, highlighting the integrated analysis of genomic, transcriptomic, and proteomic data and its pivotal role in enhancing our understanding of kidney pathologies. Through case studies, we showcase the application of proteogenomics in clear cell renal cell carcinoma (ccRCC) and Autosomal Recessive Polycystic Kidney Disease (ARPKD), emphasizing its potential in personalized treatment strategies and biomarker discovery. The review also addresses the challenges in proteogenomic analysis, including data integration complexities and bioinformatics limitations, and proposes solutions for advancing the field. Ultimately, this review underscores the prospective future of proteogenomics in nephrology, particularly in advancing personalized medicine and providing novel therapeutic insights. Full article

Magnetic resonance sounding is a geophysical method for quantitatively determining the state for groundwater storage that has gained international attention in recent years. However, the practical acquisition of magnetic resonance sounding signals, which are on the nanovolt scale, is susceptible to various types of interference, such as power-line harmonics, random noise, and spike noise. Such interference can degrade the quality of magnetic resonance sounding signals and, in severe cases, be completely drowned out by noise. This paper introduces an adaptive Gaussian filtering algorithm that is well-suited for handling intricate noise signals due to its adaptive solving characteristics and iterative sifting approach. Notably, the algorithm can process signals without relying on prior knowledge. The adaptive Gaussian filtering algorithm is applied for the envelope extraction of noisy magnetic resonance sounding signals, and the reliability and effectiveness of the method are rigorously validated. The simulation results reveal that, even under strong noise interference (with original signal-to-noise ratios ranging from −7 dB to −25 dB), the magnetic resonance sounding signal obtained after algorithmic processing is compared to the ideal signal, with 16 sets of data statistics, and the algorithm ensures an initial amplitude uncertainty within 4nV and restricts the uncertainty of the relaxation time within a 6 ms range. The signal-to-noise ratio can be boosted by up to 53 dB. The comparative assessments with classical algorithms such as empirical mode decomposition and the harmonic modeling method confirm the superior performance of the adaptive Gaussian filtering algorithm. The processing of the field data also fully proved the practical application effects of the algorithm. Full article

The hydrolysis and biotransformation of lignocellulose, i.e., biorefinery, can provide human beings with biofuels, bio-based chemicals, and materials, and is an important technology to solve the fossil energy crisis and promote global sustainable development. Biorefinery involves steps such as pretreatment, saccharification, and fermentation, and researchers have developed a variety of biorefinery strategies to optimize the process and reduce process costs in recent years. Lignocellulosic hydrolysates are platforms that connect the saccharification process and downstream fermentation. The hydrolysate composition is closely related to biomass raw materials, the pretreatment process, and the choice of biorefining strategies, and provides not only nutrients but also possible inhibitors for downstream fermentation. In this review, we summarized the effects of each stage of lignocellulosic biorefinery on nutrients and possible inhibitors, analyzed the huge differences in nutrient retention and inhibitor generation among various biorefinery strategies, and emphasized that all steps in lignocellulose biorefinery need to be considered comprehensively to achieve maximum nutrient retention and optimal control of inhibitors at low cost, to provide a reference for the development of biomass energy and chemicals. Full article

Psychological stress increases risk of gastrointestinal tract diseases. However, the mechanism behind stress-induced gastrointestinal injury is not well understood. The objective of our study is to elucidate the putative mechanism of stress-induced gastrointestinal injury and develop an intervention strategy. To achieve this, we employed the restraint stress mouse model, a well-established method to study the pathophysiological changes associated with psychological stress in mice. By orally administering gut-nonabsorbable Evans blue dye and monitoring its plasma levels, we were able to track the progression of gastrointestinal injury in live mice. Additionally, flow cytometry was utilized to assess the viability, death, and inflammatory status of splenic leukocytes, providing insights into the stress-induced impact on the innate immune system associated with stress-induced gastrointestinal injury. Our findings reveal that neutrophils represent the primary innate immune leukocyte lineage responsible for stress-induced inflammation. Splenic neutrophils exhibited elevated expression levels of the pro-inflammatory cytokine IL-1, cellular reactive oxygen species, mitochondrial burden, and cell death following stress challenge compared to other innate immune cells such as macrophages, monocytes, and dendritic cells. Regulated cell death analysis indicated that NETosis is the predominant stress-induced cell death response among other analyzed regulated cell death pathways. NETosis culminates in the formation and release of neutrophil extracellular traps, which play a crucial role in modulating inflammation by binding to pathogens. Treatment with the NETosis inhibitor GSK484 rescued stress-induced neutrophil extracellular trap release and gastrointestinal injury, highlighting the involvement of neutrophil extracellular traps in stress-induced gastrointestinal inflammation. Our results suggest that neutrophil NETosis could serve as a promising drug target for managing psychological stress-induced gastrointestinal injuries. Full article

A systematic analysis of the spatiotemporal evolution patterns and factors influencing ecological land (EL) can support the optimization of EL protection policies and ensure the stability of regional ecosystems. Based on remote sensing data, using the gravity center shift model, the landscape pattern index, and the equivalent factor method, the characteristics of EL evolution in the Beijing–Tianjin–Hebei (BTH) region from 1980 to 2020 were analyzed. A fixed-effects model was used to quantitatively explore the factors influencing EL evolution and heterogeneity analysis. The results are as follows: (1) The EL area exhibited a trend of initial decrease followed by a subsequent increase during the study period. The most significant area transfer occurred between cropland and EL, but, after the 21st century, the proportion of area transfer between construction land and EL noticeably increased. (2) The compactness and fragmentation of EL showed a certain spatiotemporal stability, but the spatial distribution of compactness and fragmentation hot and cold spots exhibited significant differences. The fragmentation hot spots mainly displayed a strip distribution, while those of compactness showed a clustered distribution. (3) Although the ecosystem service value in the BTH region demonstrated dynamic “M”-shaped changes, the distribution of hot and cold spots still exhibited spatial stability. Regulating services consistently occupied a higher proportion of the sub-service functions, while cultural services still needed further enhancement. (4) Factors influencing the evolution of areas and values demonstrated similarities. The landscape was significantly influenced by construction land, showing a non-linear “U”-shaped relationship with fragmentation. Different economic development gradients and altitudes exhibited differentiated characteristics in terms of their influencing factors. This study provides scientific support for dynamically and precisely adjusting governmental EL management policies, contributing to the sustainable development of regional socio-economics. Full article

There are significant variations in pathogenicity among different virulent strains of the Newcastle disease virus (NDV). Virulent NDV typically induces severe pathological changes and high mortality rates in infected birds, while avirulent NDV usually results in asymptomatic infection. Currently, the understanding of the specific mechanisms underlying the differences in host pathological responses and symptoms caused by various virulent NDV strains remains limited. Long non-coding RNA (lncRNA) can participate in a range of biological processes and plays a crucial role in viral infection and replication. Therefore, this study employed RNA-Seq to investigate the transcriptional profiles of chicken embryos’ visceral tissues (CEVTs) infected with either the virulent NA-1 strain or avirulent LaSota strain at 24 hpi and 36 hpi. Using bioinformatic methods, we obtained a total of 2532 lncRNAs, of which there were 52 and 85 differentially expressed lncRNAs at 24 hpi and 36 hpi, respectively. LncRNA analysis revealed that the severe pathological changes and symptoms induced by virulent NDV infection may be partially attributed to related target genes, regulated by differentially expressed lncRNAs such as MSTRG.1545.5, MSTRG.14601.6, MSTRG.7150.1, and MSTRG.4481.1. Taken together, these findings suggest that virulent NDV infection exploits the host’s metabolic resources and exerts an influence on the host’s metabolic processes, accompanied by excessive activation of the immune response. This impacts the growth and development of each system of CEVTs, breaches the blood–brain barrier, inflicts severe damage on the nervous system, and induces significant lesions. These observations may be attributed to variations in pathology. Consequently, novel insights were obtained into the intricate regulatory mechanisms governing NDV and host interactions. This will aid in unraveling the molecular mechanisms underlying both virulent and avirulent forms of NDV infection. Full article

Demand response management (DRM) plays a crucial role in the prospective development of smart grids. The precise estimation of electricity demand for individual houses is vital for optimizing the operation and planning of the power system. Accurate forecasting of the required components holds significance as it can substantially impact the final cost, mitigate risks, and support informed decision-making. In this paper, a forecasting approach employing neural networks for smart grid demand-side management is proposed. The study explores various enhanced artificial neural network (ANN) architectures for forecasting smart grid consumption. The performance of the ANN approach in predicting energy demands is evaluated through a comparison with three statistical models: a time series model, an auto-regressive model, and a hybrid model. Experimental results demonstrate the ability of the proposed neural network framework to deliver accurate and reliable energy demand forecasts. Full article

We consider the newly developed multinomial mixed-link models for a high-risk intestinal metaplasia (IM) study with DNA methylation data. Different from the traditional multinomial logistic models commonly used for categorical responses, the mixed-link models allow us to select the most appropriate link function for each category. We show that the selected multinomial mixed-link model (Model 1) using the total number of stem cell divisions (TNSC) based on DNA methylation data outperforms the traditional logistic models in terms of cross-entropy loss from ten-fold cross-validations with significant p-values $8.12\times {10}^{-4}$ and $6.94\times {10}^{-5}$. Based on our selected model, the significance of TNSC’s effect in predicting the risk of IM is justified with a p-value less than ${10}^{-6}$. We also select the most appropriate mixed-link models (Models 2 and 3) when an additional covariate, the status of gastric atrophy, is available. When the status is negative, mild, or moderate, we recommend Model 2; otherwise, we prefer Model 3. Both Models 2 and 3 can predict the risk of IM significantly better than Model 1, which justifies that the status of gastric atrophy is informative in predicting the risk of IM. Full article

Understanding the spatial and temporal patterns of forest fires, along with the key factors influencing their occurrence, and accurately forecasting these events are crucial for effective forest management. In the Central-South region of China, forest fires pose a significant threat to the ecological system, public safety, and economic stability. This study employs Geographic Information Systems (GISs) and the LightGBM (Light Gradient Boosting Machine) model to identify the determinants of forest fire incidents and develop a predictive model for the likelihood of forest fire occurrences, in addition to proposing a zoning strategy. The purpose of the study is to enhance our understanding of forest fire dynamics in the Central-South region of China and to provide actionable insights for mitigating the risks associated with such disasters. The findings reveal the following: (i) Spatially, fire incidents exhibit significant clustering and autocorrelation, highlighting areas with heightened likelihood. (ii) The Central-South Forest Fire Likelihood Prediction Model demonstrates high accuracy, reliability, and predictive capability, with performance metrics such as accuracy, precision, recall, and F1 scores exceeding 85% and AUC values above 89%, proving its effectiveness in forecasting the likelihood of forest fires and differentiating between fire scenarios. (iii) The likelihood of forest fires in the Central-South region of China varies across regions and seasons, with increased likelihood observed from March to May in specific provinces due to various factors, including weather conditions and leaf litter accumulation. Risks of localized fires are noted from June to August and from September to November in different areas, while certain regions continue to face heightened likelihood from December to February. Full article

The increase in atmospheric CO₂ concentration is a significant factor in triggering global warming. CO₂ is essential for plant photosynthesis, but excessive CO₂ can negatively impact photosynthesis and its associated physiological and biochemical processes. The tetraploid Robinia pseudoacacia L., a superior and improved variety, exhibits high tolerance to abiotic stress. In this study, we investigated the physiological and proteomic response mechanisms of the tetraploid R. pseudoacacia under high CO₂ treatment. The results of our physiological and biochemical analyses revealed that a 5% high concentration of CO₂ hindered the growth and development of the tetraploid R. pseudoacacia and caused severe damage to the leaves. Additionally, it significantly reduced photosynthetic parameters such as Pn, Gs, Tr, and Ci, as well as respiration. The levels of chlorophyll (Chl a and b) and the fluorescent parameters of chlorophyll (Fm, Fv/Fm, qP, and ETR) also significantly decreased. Conversely, the levels of ROS (H₂O₂ and O₂^·−) were significantly increased, while the activities of antioxidant enzymes (SOD, CAT, GR, and APX) were significantly decreased. Furthermore, high CO₂ induced stomatal closure by promoting the accumulation of ROS and NO in guard cells. Through a proteomic analysis, we identified a total of 1652 DAPs after high CO₂ treatment. GO functional annotation revealed that these DAPs were mainly associated with redox activity, catalytic activity, and ion binding. KEGG analysis showed an enrichment of DAPs in metabolic pathways, secondary metabolite biosynthesis, amino acid biosynthesis, and photosynthetic pathways. Overall, our study provides valuable insights into the adaptation mechanisms of the tetraploid R. pseudoacacia to high CO₂. Full article

After Hurricane Maria devastated Puerto Rico, we wanted to determine how the islanders viewed environmental organizations as part of an effort to understand the relationships between attitudes, institutions, and environmental and social justice issues. As a category 5 hurricane, Hurricane Maria was one of the strongest to hit Puerto Rico. Yet, the US mainstream media coverage of this and other environmental issues was lacking. From a total of 90 environmental organizations in Puerto Rico, we surveyed 19 that were active in the southwest of the island. We asked: (1) How do local people view environmental and social justice issues and (2) given their organizations’ efforts to deal with these issues, what are their successes? To address these questions, we developed a survey in English and Spanish and conducted personal and online interviews with 30 relevant individuals. Their most successful outcomes included: (1) educating and creating greater awareness of environmental issues; (2) introducing environmental changes into their communities; and (3) becoming and surviving as economically sustainable organizations. The results inform our understanding between environmental organizations and social and environmental justice in Puerto Rico and more broadly, because the organizations surveyed are at the center of fighting climate change and achieving environmental justice. Full article

The fruit of Choerospondias axillaris (Anacardiaceae), known as south wild jujube in China, has been consumed widely in several regions of the world to produce fruit pastille and leathers, juice, jam, and candy. A comprehensive chemical study on the fresh fruits led to the isolation and identification of 18 compounds, including 7 new (1–7) and 11 known (8–18) comprised of 5 alkenyl (cyclohexenols and cyclohexenones) derivatives (1–5), 3 benzofuran derivatives (6–8), 6 flavonoids (9–14) and 4 lignans (15–18). Their structures were elucidated by extensive spectroscopic analysis. The known lignans 15–18 were isolated from the genus Choerospondias for the first time. Most of the isolates exhibited significant inhibitory activity on α-glucosidase with IC₅₀ values from 2.26 ± 0.06 to 43.9 ± 0.96 μM. Molecular docking experiments strongly supported the potent α-glucosidase inhibitory activity. The results indicated that C. axillaris fruits could be an excellent source of functional foods that acquire potential hypoglycemic bioactive components. Full article

The emission factor method (Tier 1) recommended by the Intergovernmental Panel on Climate Change (IPCC) is commonly used to estimate greenhouse gas (GHG) emissions from livestock and poultry farms. However, the estimation accuracy may vary due to practical differences in manure management across China. The objectives of this study were to estimate the direct and indirect nitrous oxide (N₂O) emissions from dairy manure management between 1990 and 2021 in China and characterize its spatial and temporal variations following IPCC guideline Tier 2. The N₂O emission factor (EF) of dairy cow manure management systems was determined at the national level and regional level as well. The results showed that the national cumulative N₂O emission of manure management from 1990 to 2021 was 113.1million tons of CO₂ equivalent, ranging from 90.3 to 135.9 million tons with an uncertainty of ±20.2%. The annual EF was 0.021 kg N₂O-N (kg N)⁻¹ for total emissions, while it was 0.014 kg N₂O-N (kg N)⁻¹ for direct emissions. The proportions of N₂O emissions in North China, Northeast China, East China, Central and Southern China, Southwest China and Northwest China were 32.3%, 18.6%, 11.4%, 5.8%, 6.1% and 25.8%, respectively. In addition, N₂O emissions varied among farms in different scales. The respective proportions of total N₂O emissions from small-scale and large-scale farms were 64.8% and 35.2% in the past three decades. With the improvement in farm management and milk production efficiency, the N₂O emissions per unit mass of milk decreased from 0.77 × 10⁻³ kg to 0.48 × 10⁻³ kg in 1990–2021. This study may provide important insights into compiling a GHG emission inventory and developing GHG emission reduction strategies for the dairy farming system in China. Full article

With the fast development of unmanned aerial vehicles (UAVs), reliable UAV communication is becoming increasingly vital. The channel knowledge map (CKM) is a crucial bridge connecting the environment and the propagation channel that may visually depict channel characteristics. This paper presents a comprehensive scheme based on a UAV-assisted channel measurement system for constructing the CKM in real-world scenarios. Firstly, a three-dimensional (3D) CKM construction scheme for real-world scenarios is provided, which involves channel knowledge extraction, mapping, and completion. Secondly, an algorithm of channel knowledge extraction and completion is proposed. The sparse channel knowledge is extracted based on the sliding correlation and constant false alarm rate (CFAR) approaches. The 3D Kriging interpolation is used to complete the sparse channel knowledge. Finally, a UAV-assisted channel measurement system is developed and CKM measurement campaigns are conducted in campus and farmland scenarios. The path loss (PL) and root mean square delay spread (RMS-DS) are measured at different heights to determine CKMs. The measured and analyzed results show that the proposed construction scheme can effectively and accurately construct the CKMs in real-world scenarios. Full article

In this study, the design and asymmetric synthesis of a series of chiral targets of orientational chirality were conducted by taking advantage of N-sulfinylimine-assisted nucleophilic addition and modified Sonogashira catalytic coupling systems. Orientational isomers were controlled completely using alkynyl/alkynyl levers [C(sp)-C(sp) axis] with absolute configuration assignment determined by X-ray structural analysis. The key structural element of the resulting orientational chirality is uniquely characterized by remote through-space blocking. Forty examples of multi-step synthesis were performed, with modest to good yields and excellent orientational selectivity. Several chiral orientational amino targets are attached with scaffolds of natural and medicinal products, showing potential pharmaceutical and medical applications in the future. Full article

The global agricultural sector confronts significant obstacles such as population growth, climate change, and natural disasters, which negatively impact food production and pose a threat to food security. In response to these challenges, the integration of IoT and AI technologies emerges as a promising solution, facilitating data-driven decision-making, optimizing resource allocation, and enhancing monitoring and control systems in agricultural operations to address these challenges and promote sustainable farming practices. This study examines the intersection of IoT and AI in precision agriculture (PA), aiming to provide a comprehensive understanding of their combined impact and mutually reinforcing relationship. Employing a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, we explore the synergies and transformative potential of integrating IoT and AI in agricultural systems. The review also aims to identify present trends, challenges, and opportunities in utilizing IoT and AI in agricultural systems. Diverse forms of agricultural practices are scrutinized to discern the applications of IoT and AI systems. Through a critical analysis of existing literature, this study contributes to a deeper understanding of how the integration of IoT and AI technologies can revolutionize PA, resulting in improved efficiency, sustainability, and productivity in the agricultural sector. Full article

Unbonded flexible risers consist of several helical and cylindrical layers, which can undergo large bending deformation and can be installed to different configurations to adapt to harsh marine environments, and is a key equipment in transporting oil and gas resources from Ultra Deep Waters (UDWs) to offshore platforms. The helical interlayer of an unbonded flexible riser makes the structural behavior difficult to predict. In this paper, the axial tensile behavior and the axial tensile ultimate strength of an unbonded flexible riser are studied based on a typical 2.5-inch eight-layer unbonded flexible riser model, and verified through a theoretical method considering the contact between adjacent layers. First, the balance equation of separate layers is deduced by a functional principle, and then the overall theoretical model of an unbonded flexible riser is established considering the geometric relationship between adjacent layers. Then, the numerical model considering the detailed geometric properties of an unbonded flexible riser is established to simulate the axial tensile behavior. Finally, after being verified through the experimental results, the axial tensile stiffness and axial tensile strength of an unboned flexible riser considering the elasticity of the tensile armor layer are studied using the proposed two methods. Additionally, the effect of frictional coefficients is conducted. The numerical and theoretical results show good agreement with the test results, and the friction between adjacent layers would increase the axial tensile stiffness of an unbonded flexible riser. Full article

Several extensions of the basic scalar variable logistic density to the multivariate and matrix-variate cases, in the real and complex domains, are given where the extended forms end up in extended zeta functions. Several cases of multivariate and matrix-variate Bayesian procedures, in the real and complex domains, are also given. It is pointed out that there are a range of applications of Gaussian and Wishart-based matrix-variate distributions in the complex domain in multi-look data from radar and sonar. It is hoped that the distributions derived in this paper will be highly useful in such applications in physics, engineering, statistics and communication problems, because, in the real scalar case, a logistic model is seen to be more appropriate compared to a Gaussian model in many industrial applications. Hence, logistic-based multivariate and matrix-variate distributions, especially in the complex domain, are expected to perform better where Gaussian and Wishart-based distributions are currently used. Full article

Type 1 diabetes (T1D) affects gastrointestinal (GI) motility, favoring gastroparesis, constipation, and fecal incontinence, which are more prevalent in women. The mechanisms are unknown. Given the G-protein-coupled estrogen receptor’s (GPER) role in GI motility, we investigated sex-related diabetes-induced epigenetic changes in GPER. We assessed GPER mRNA and protein expression levels using qPCR and Western blot analyses, and quantified the changes in nuclear DNA methyltransferases and histone modifications (H3K4me3, H3Ac, and H3K27Ac) by ELISA kits. Targeted bisulfite and chromatin immunoprecipitation assays were used to evaluate DNA methylation and histone modifications around the GPER promoter by chromatin immunoprecipitation assays in gastric and colonic smooth muscle tissues of male and female control (CTR) and non-obese diabetic (NOD) mice. GPER expression was downregulated in NOD, with sex-dependent variations. In the gastric smooth muscle, not in colonic smooth muscle, downregulation coincided with differences in methylation ratios between regions 1 and 2 of the GPER promoter of NOD. DNA methylation was higher in NOD male colonic smooth muscle than in NOD females. H3K4me3 and H3ac enrichment decreased in NOD gastric smooth muscle. H3K4me3 levels diminished in the colonic smooth muscle of NOD. H3K27ac levels were unaffected, but enrichment decreased in NOD male gastric smooth muscle; however, it increased in the NOD male colonic smooth muscle and decreased in the female NOD colonic smooth muscle. Male NOD colonic smooth muscle exhibited decreased H3K27ac levels, not female, whereas female NOD colonic smooth muscle demonstrated diminished enrichment of H3ac at the GPER promoter, contrary to male NOD. Sex-specific epigenetic mechanisms contribute to T1D-mediated suppression of GPER expression in the GI tract. These insights advance our understanding of T1D complications and suggest promising avenues for targeted therapeutic interventions. Full article