Search Results (3,063)

The distribution of white spots on the shell is one of the remarkable characteristics of the appearance of Portunus trituberculatus, but there have been no reports on its characteristics and genetic analysis. In this study, seven parameters of white spots were extracted based on computer vision, including white spot number (WSN), white spot area (WSA), white spot regional area (WSRA), percentage of white spot area (PWSA), percentage of white spot regional area (PWSRA), white spot number of white spot regional area (WSNRA), and white spot number of carapace area (WSNCA). Using 22 full-sib families, we estimated genetic parameters of these white spot traits and their genetic correlations with growth carapace area (CA). Results demonstrated that these parameters exhibit continuous variation, but the performance of these white spot indicators was not consistent. Based on comprehensive principal component analysis (PCA), they could be categorized into three distinct groups within the full-sib families. The heritability estimated under the animal model ranged from 0.00 to 0.35 for white spot traits and was 0.18 for CA. Most white spot traits showed low to moderate heritability. The genetic correlations among WSN, WSA, WSRA, PWSA, and CA were significantly positive, indicating that selection for one of these traits would result in the improvement of others. This study presents the first estimation of characteristics and genetic parameters of white spot traits of P. trituberculatus, providing valuable information for understanding these traits and facilitating the optimization of breeding strategies for this species. Full article

This study presents a hydrogeochemical assessment of oilfield formation waters from the Karazhanbas, Zhetybay, and Uzen oil fields in the Mangystau Region of Kazakhstan, with the aim of elucidating lithium distribution, identifying the geochemical factors controlling its accumulation, and providing a preliminary resource-oriented evaluation. The study investigated pH, total dissolved solids (TDS), ionic–salt composition, lithium (Li) concentration, and the relationships between Li, TDS, major cations, and geochemical ratios, including Ca/Li and Mg/Li. Major ions were determined using standard hydrochemical methods, while Li was analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES). The investigated waters were predominantly classified as chloride–calcium type according to their hydrochemical composition. In terms of TDS, the waters follow the sequence Uzen > Zhetybay > Karazhanbas, whereas Li concentrations follow the sequence Zhetybay > Uzen > Karazhanbas. The highest Li concentrations were detected in Zhetybay waters (1.40–1.85 mg/dm³); in Uzen waters, Li reached 1.51 mg/dm³; and in Karazhanbas waters, it ranged from 0.30 to 0.70 mg/dm³. The highest Mg/Li and (Na⁺ + K⁺)/Li ratios were characteristic of Uzen waters, indicating a more complex salt matrix. Compared with internationally reported lithium-enriched brines, the Mangystau formation waters contain relatively low Li concentrations and cannot currently be considered a commercially viable lithium source. The scientific significance of this study lies in establishing a regional hydrogeochemical baseline for oilfield formation waters and demonstrating that maximum mineralization does not necessarily correspond to the highest Li concentration. Full article

To address the potential ecological risks and environmental persistence of organosilicon-fluorine viscosity reducers in conventional silicone-fluoride drilling fluid systems, this work designs and synthesizes a non-organosilicon-fluorine, high-temperature, comb-shaped zwitterionic polymer viscosity reducer, AD-XSJ. The viscosity reducer is prepared via aqueous free-radical polymerization of acrylic acid (AA), acrylamide (AM), 2-acrylamido-2-methylpropane sulfonic acid (AMPS), and dimethyl diallyl ammonium chloride (DADMAC), and it exhibits low molecular weight, uniform molecular weight distribution, and excellent thermal stability. Analyses by FT-IR, thermogravimetry, particle size, zeta potential measurements and Electrostatic potential (ESP) demonstrate that AD-XSJ dismantles the bentonite network structure through the synergistic combination of hydrogen-bonding adsorption and electrostatic repulsion, releasing trapped free water and thereby substantially reducing viscosity and gel strength. Compared with conventional organosilicon-fluorine viscosity reducers, AD-XSJ exhibits superior viscosity reduction capability under high-solid, high-temperature, and high-salinity calcium-contamination conditions, achieving viscosity reduction rates of 33.3% and 50.0% in fluids contaminated with 10.0% NaCl and 1.0% CaCl₂, respectively. In field applications under conditions of high bentonite content and calcium contamination, the viscosity reduction rates reach 57.7% and 62.5%, accompanied by markedly improved rheological properties and an average borehole enlargement rate of only 5.7%, indicating effective shale inhibition and anti-sloughing performance. Integrating efficient viscosity reduction, dispersion stabilization, and inhibition capabilities, this viscosity reducer can replace traditional organosilicon-fluorine products, reduce potential hazards to aquatic ecosystems at the source, and holds considerable promise for engineering and environmentally conscious deployment. Full article

Chlorogenic acid (CA) exhibits robust lipid antioxidant activity within meat matrices. However, excess CA generates quinones that alter and damage porcine myofibrillar protein (MP). This study investigated the restorative effects of chitosan (CS) on MPs suffering from CA-induced oxidative damage. Three CA concentrations (0, 50, 100 μmol/g protein) and five CS dosages (0.125–1.0 g/g protein) were used to evaluate conformation, turbidity, surface hydrophobicity, solubility, emulsification, rheology, and gel properties. CA-oxidative damage to MP triggered protein unfolding, thiol depletion and aggregation, greatly lowering solubility, emulsifying capacity, viscoelasticity and water retention. CS exerted biphasic effects on turbidity, surface hydrophobicity, tertiary structure, and solubility only under severe CA-induced oxidative modification (100 μmol/g CA): low-to-medium CS aggravated adverse changes, while 1.0 g/g CS partially reversed such damage. For conformational, emulsion and gel parameters, CS consistently alleviated structural disorder caused by CA-induced oxidative damage across all treatments, with 1.0 g/g CS optimally mitigating α-helix loss and uneven emulsion droplets. Significant CA × CS interactions were detected for conformation, turbidity, surface hydrophobicity, solubility, emulsification and rheology (p < 0.001). Gel strength, water-holding capacity and water distribution exhibited non-significant interactions (p > 0.05), revealing independent additive effects of CA and CS on gel networks. Overall, high-dose CS partially ameliorates structural and functional defects of MP caused by CA-induced oxidative damage, which provides theoretical support for the combined application of polyphenols and polysaccharides in meat protein regulation. Full article

Background/Objectives: We aim to determine whether prior cataract surgery affects the intraocular pressure (IOP)-lowering effect of selective laser trabeculoplasty (SLT) in patients with primary open-angle glaucoma (POAG). Methods: This prospective interventional cohort study initially included 92 patients with POAG who were inadequately controlled or intolerant to topical therapy and were treated with SLT. Of these, 84 patients completed all scheduled visits and constituted the final analyzed dataset. Patients were divided into phakic and pseudophakic groups, with cataract surgery performed at least one year before SLT in all pseudophakic eyes. All patients underwent standardized 360-degree SLT by a single specialist. The primary outcome was IOP reduction at one year. Secondary outcomes included percentage IOP reduction and treatment success, defined as ≥20% IOP reduction. Data were analyzed using Statistica^TM 14.0.1.25 (TIBCO Software Inc., Palo Alto, CA, USA, USA). Results: Before SLT, the median IOP was 20.5 mmHg in phakic eyes and 21 mmHg in pseudophakic eyes. One year after SLT, median IOP decreased insignificantly in phakic eyes (4.0 mmHg; p = 0.262), whereas it decreased significantly in pseudophakic eyes (5.5 mmHg; p = 0.004). At one year post-SLT, an IOP reduction of ≥20% was observed in 53.6% of phakic and 72.7% of pseudophakic eyes. Pseudophakic patients were significantly older than phakic patients, as expected, because age-related senile cataract is more common in older individuals, and the groups also differed by gender distribution. This gender imbalance was coincidental and reflected the non-randomized inclusion of POAG patients according to clinical need for SLT rather than predefined matching. In unadjusted analyses, one-year IOP reduction was positively associated with age (p = 0.048), pretreatment IOP (p < 0.001), and prior cataract surgery (p = 0.047). However, after adjusting for age, gender, and baseline IOP in a multivariate sensitivity analysis, prior cataract surgery was not an independent predictor of success; only pretreatment IOP predicted a significant reduction (p = 0.031) in the analysis of 84 eyes. Conclusion: Although pseudophakic eyes showed greater unadjusted IOP reduction after SLT over one year, lens status was not an independent predictor after adjustment for potential confounders. Therefore, the observed pseudophakic advantage should be interpreted as a hypothesis-generating association warranting further research into the effect of pseudophakia on SLT response. Full article

Consolidation treatments are essential for the conservation of wall paintings affected by decohesion and disintegration phenomena. In hypogean environments, high relative humidity, limited ventilation and elevated biological risk impose particularly stringent performance requirements. Under these conditions, consolidants must ensure chemical compatibility, effective distribution within water-saturated substrates, long-term stability at high relative humidity and low toxicological impact. Calcium-based nanomaterials, especially nanolime dispersions, are widely employed as reference consolidants. However, their performance is strongly influenced by the dispersing medium, environmental conditions and substrate characteristics. This study addresses the lack of comparative assessments of currently available calcium-based consolidants by testing four products—two alcohol-based nanolimes (Nanorestore Plus^® and CaLoSil^®), one aqueous nanolime dispersion (Nanolaq^®) and a laboratory-formulated aqueous nanocalcite—applied to painted mock-ups. For the first time, the effectiveness of these treatments was investigated under both high relative humidity and water-saturated conditions through a multi-analytical approach. Colorimetric variations, water vapour permeability, water absorption and consolidant distribution within the pictorial layers were evaluated. The results provide a comparative assessment of consolidant performance as a function of the hygrometric regime of the substrate, with differentiated responses under high-humidity conditions and attenuated differences under water-saturated conditions. Overall, the effectiveness of the consolidant appeared to depend significantly on the combined influence of the dispersing medium, the imbibition state of the substrate and its chemical nature, highlighting the need for selection criteria and evaluation protocols based on simulating realistic conservation conditions. Full article

As autonomous driving moves toward large-scale deployment, controllable and efficient simulation testing has become a primary means of ensuring system safety. However, in open-world environments, existing scenario catalogs often fail to cover the full spectrum of potential traffic situations, while rare yet high-risk critical scenarios are even harder to obtain. This scarcity renders traditional random sampling and parameter-sweeping strategies ineffective for identifying unknown risks. This study addresses two core challenges: (1) incomplete scenario catalogs hindering unknown critical scenario recognition and (2) insufficient critical samples, where generated scenarios struggle to balance physical realism and edge case coverage. To tackle the first challenge, we propose an open-world recognition method integrating transformers, random forests, and extreme value theory for precise unseen sample detection. Outlier and validity filtering ensure clustering reliability, and random forest activation patterns cluster unknown samples into meaningful groups to expand the scenario catalog. Experiments show the overall F1_macro improved by 2.3 percentage points over SOTA MDENet, with its clustering accuracy surpassing iterative-AutoNovel by 6.2 percentage points. For the second challenge, we introduce a reinforcement-learning-based maneuver-level generation method. It extracts maneuver semantics from trajectories, constructs a low-dimensional parameter space, and models parameter correlations via a multivariate multimodal distribution. A dual-layer LSTM agent with a composite reward iteratively optimizes policies toward high-risk edge scenarios. The results outperformed RLBE; longitudinal and lateral reconstruction errors were reduced by 32.7% and 15.3%, respectively, while high-risk time steps and the collision rate increased by 4.3% and 5.1%, respectively. Finally, we develop a CARLA-based scenario-driven simulation framework, integrating recognized and generated scenarios into closed-loop testing on high-risk road segments. CAS failure cases validate the generated scenarios’ physical feasibility and extreme challenge. Targeted augmentation of scarce critical scenarios enriches the test library and ensures broader coverage of real-world driving conditions. Full article

Heavy metal (HM) contamination near mining operations in Kazakhstan poses a serious threat to the environment. However, data on the state of chernozem soils in this region is limited. This study assessed the bioaccumulation of HMs and translocation within the soil–sunflower (Helianthus annuus L.) system in a southern Calcic Chernozem in the Kostanay region (Northern Kazakhstan), which is located 50 km from the nearest mining facility. The content of seven HMs (Cd, Co, Cr, Cu, Ni, Pb, and Zn) and arsenic (As), as well as five macroelements (K, Ca, S, Mg, and P), was determined in 18 soil samples from the complete soil pedon (0–150 cm) and in eight anatomical parts of six sunflower plants at physiological maturity. Most metals exhibited a deficiency relative to upper continental crustal Clarke values (Clarke of Concentration (CC) < 1 for Cr, Cu, Ni, Pb, and Zn), with a moderate lithogenic anomaly for Cd (CC = 1.65–3.57) and a localized Co anomaly in the Bk horizon (56.26 mg kg⁻¹), indicating no pronounced HM contamination at the investigated agricultural site. Metal distribution exhibited strong organ specificity in sunflower plants. Cd, Cu, and Zn accumulated preferentially in the leaves, whereas Ni and Co were more concentrated in the seeds and stems, respectively. Only cadmium exceeded the threshold values for both BCF > 1 (1.01) and TF > 1 (1.47), confirming the status of sunflower as a cadmium accumulator. These results provide a preliminary reference dataset of the organ-specific distribution of heavy metals in H. annuus L. plants, which can serve as a local baseline for sunflower growth in uncontaminated southern Chernozems. This information can contribute to future environmental monitoring purposes in the region, acting as an exploratory benchmark. Full article

Maintaining effective fluid-loss control in water-based drilling fluids under coupled high-salinity, high-temperature, and high-density conditions remains a critical challenge in deep and ultra-deep drilling operations. In this study, a low-molecular-weight polymer fluid-loss additive (LM-ASQF) was synthesized via redox-initiated copolymerization of acrylamide, dimethyldiallylammonium chloride, and sodium allyl sulfonate. The synthesis route and proposed polymer structure were further illustrated to clarify the incorporation of amide, quaternary ammonium, and sulfonate functional units within the LM-ASQF molecular architecture. The polymer exhibited a controllable number-average molecular weight of 18.2–29.4 kDa with a unimodal distribution. Thermal analysis confirmed that no main-chain-dominated degradation occurred below 220 °C, indicating structural stability under high-temperature conditions. In drilling-fluid systems containing NaCl, CaCl₂, and mixed salts (0–20%), LM-ASQF maintained stable rheological properties, with apparent viscosity ranging from 26.1 to 41.6 mPa·s, while the API fluid loss was controlled within 5.8–11.2 mL. After thermal aging at 220 °C for 16 h, the API fluid loss remained below 13 mL in both freshwater and mixed-salt systems. In high-density systems (1.80–2.40 g/cm³), the drilling fluids preserved continuous rheological structures and showed no abrupt increase in filtration. Mechanistically, fluid-loss control was primarily attributed to synergistic interfacial adsorption of amide groups, hydration stabilization induced by sulfonate functionalities, and particle rearrangement-driven filter-cake densification, rather than viscosity enhancement through long-chain entanglement. This mechanism enables effective filtration control without excessive viscosity increase, thereby maintaining rheological compatibility under complex conditions. These results demonstrate that the low-molecular-weight design strategy provides a reliable approach for achieving stable fluid-loss control in water-based drilling fluids under high salinity, elevated temperature, and high-density conditions. Full article

Ensuring the long-term serviceability of nearshore breakwaters constructed on weak seabeds is important for sustainable port infrastructure. This study investigates the wave-induced dynamic response of a vibro-compaction sand-pile composite foundation used in the Jinpai Port breakwater project in Lingao, Hainan, China. A coupled wave–structure–seabed numerical model was established using FssiCAS. Four representative monitoring points were selected inside and outside the structural influence zone and at different burial depths. The displacement, effective stress, shear stress, and pore water pressure responses were analyzed by combining full-field contour distributions with local time-history results. The results show that the foundation response is strongly location-dependent. The maximum horizontal displacement follows the order D > C > A > B, with values of approximately 10.8, 7.6, 0.5, and 0.3 mm, respectively. The final settlement follows the order A > B > C > D, with values of approximately 84, 43, 31, and 19 mm, respectively. Residual pore pressure is more significant beneath the breakwater, especially at Point B. The breakwater toes, structural boundaries, shallow seabed, and improved–natural foundation transition zones are identified as stability-sensitive zones, providing guidance for targeted monitoring, local reinforcement, drainage improvement, and maintenance planning. Full article

Background/Objectives: Diabetic retinopathy (DR) is a leading cause of vision loss and is triggered by chronic inflammation and genetic predisposition. The aim of this study was to examine the connection between specific gene variations of interleukin IL-18 and IL-8 and the likelihood of developing DR, their part in the clinical severity of the condition, and their possible effect on kidney function in patients with diabetes. Methods: This study included 176 participants, 88 of whom were patients with DR and 88 of whom were healthy controls. Genotyping for IL-18 (−607 C/A, −137 G/C) was performed using allele-specific PCR, while IL-8 (−251 A/T) analysis was conducted via the PCR-restriction fragment length polymorphism (PCR-RFLP) method. A comprehensive documentation of demographic and clinical parameters was undertaken. Renal function was the subject of evaluation using the estimated glomerular filtration rate (eGFR). The statistical analyses included the independent samples t-test for continuous variables, the chi-squared test for categorical data, and binary logistic regression to assess genotype distributions. Adjusted multivariate logistic regression analysis was performed to account for potential confounding factors, and significance was determined using the Bonferroni correction (adjusted α = 0.005) for all genetic and clinical risk assessments. Results: A multivariate logistic regression analysis, adjusted for clinical variables, identified the IL-18 (−137) GC genotype (adjusted odds ratio (AOR) = 2.25, p = 0.002) and the IL-8 (−251) AT genotype (AOR = 1.98, p = 0.003) as significant independent risk factors for DR. Combined genotype analysis revealed that the IL-18/IL-8 (CA-AT) and (GC-AT) combinations were the most potent risk factors, with an adjusted odds ratio (AOR) of 3.10 (p = 0.002) for each. Additionally, specific IL-18 (CC-GC and CC-GG) haplotype combinations were identified as significant predictors of DR risk (AOR = 2.15, p = 0.004 and AOR = 0.38, p = 0.003, respectively). Exploratory subgroup analyses within the DR cohort revealed that certain genotypes, notably IL-18 (−607) CA, IL-18 (−137) GC, and IL-8 (−251) AT, remained significantly associated with the presence of vision-threatening diabetic retinopathy (VTDR) and ME following Bonferroni correction (p < 0.005). Finally, no statistically significant differences in eGFR levels were observed across the various genotype distributions (p > 0.05). Conclusions: Both IL-18 (−137 G/C) and IL-8 (−251 A/T) gene variations, and their synergistic combinations (e.g., CA-AT and GC-AT), significantly contribute to the risk and clinical severity of DR. Our adjusted multivariate analysis confirms that these variations are independent risk factors for DR, with high odds ratios observed in advanced clinical stages, such as VTDR and ME. Additionally, while hypertension, a family history of diabetes mellitus, and CAD were identified as significant clinical predictors, the lack of significant variance in eGFR across genotype distributions suggests that these genetic variations may influence DR pathology independently of gross renal impairment in our study population. In light of the observed associations, further investigation of these genetic markers in larger prospective cohorts is warranted to clarify the underlying inflammatory mechanisms and their broader clinical implications. Full article

The Curve Number (CN) remains one of the most widely applied parameters for estimating direct surface runoff. However, its conventional application based on watershed-aggregated tabulated values conceals hydrological variability in regions with contrasting soils and steep topographic gradients. A recurring limitation of distributed CN approaches is the absence of independent hydrological validation; most machine learning models are trained and evaluated against the same SCS-USDA lookup values used to construct the training target, a circular scheme that measures statistical agreement rather than physical credibility. This study develops a reproducible geospatial workflow for distributed CN estimation across continental Ecuador, combining official MAG land use, soil surface texture natural drainage, and topographic slope layers at 1:25,000 scale with a Random Forest regression model at 10 m spatial resolution. The CN reference raster was derived from official geo-pedological layers and independently validated, not against tabulated assumptions, but against observed hydrological behaviour. Field hydraulic characterization across four dominant land cover classes in the Guamote microwatershed (Chimborazo Province), combined with HEC-HMS (US Army Corps of Engineers, Davis, CA, USA) rainfall-runoff modelling over 41 years (1981–2021), confirmed a mean annual discharge of 0.1568 m³ s⁻¹ consistent with the tabulated CN assignments. To our knowledge, this is the first nationally distributed CN map with field-anchored hydrological benchmarking for an Andean country. The Random Forest model achieved an RMSE = 10.4, an R² = 0.42, and an NSE = 0.41, a performance consistent with published field-based CN estimation studies and expected given the inherent scatter of the SCS-USDA method under real-world conditions. Zonal CN comparisons confirmed a mean absolute error below 5 CN units across the Andean highland and Amazon watersheds; the Guamote watershed showed a mean ∆CN below 4 units against the field-calibrated model. Land use and surface texture emerged as the dominant CN predictors, with natural drainage providing critical discrimination in volcanic and poorly drained soil environments. The resulting 10 m national CN map offers a physically grounded, spatially explicit parameterization layer for distributed hydrological modeling and water resources planning across data-scarce Andean and tropical territories, with direct relevance for flood risk screening, irrigation planning, watershed conservation, and climate adaptation under SDG 6, SDG 11, SDG 13 and SDG 15. Full article

Lead-bearing dusts from metallurgical processes are hazardous secondary resources due to their complex composition and toxicity. At the same time, their high lead content makes them a promising feedstock for resource recovery. This study proposes an energy-efficient electrosmelting approach based on the partial substitution of sodium carbonate with calcium-rich industrial waste (sugar-industry defecate). Thermodynamic analysis and equilibrium modeling of the Pb–Sb–Fe–Na–Ca–Si–S–Cl–As system were performed in the temperature range of 200–1200 °C using Outotec HSC Chemistry. The results indicate that under equilibrium conditions approximately 90–95% of lead is concentrated in the metallic phase (~56 kg from ~60 kg in the feed), while antimony is co-recovered (~1.9–2.0 kg). The slag is dominated by calcium silicates, primarily Ca₂SiO₄, confirming the important role of CaO in slag formation and impurity fixation. Chlorine is predominantly bound as NaCl and partially as CaCl₂, while sulfur is distributed between Na₂S and Na₂SO₄. A significant portion of arsenic is predicted to be retained in the slag as calcium and sodium arsenates (Ca₃(AsO₄)₂ and Na₃AsO₄), whereas its volatilization is thermodynamically negligible under equilibrium conditions. Preliminary experimental results are generally consistent with the thermodynamic predictions and confirm the feasibility of partially replacing Na₂CO₃ with sugar-industry defecate. The proposed approach contributes to reducing the consumption of conventional fluxes and promotes the utilization of industrial waste within a circular-economy framework. Full article

Accurate and robust weed detection is a critical prerequisite for precision agriculture and site-specific weed management. However, real-world agricultural environments pose significant challenges to existing object detectors due to severe illumination variability, high inter-class similarity between crops and weeds, and the prevalence of small and occluded targets at early growth stages. To address these challenges, this paper proposes DSD-YOLOv11, a domain-adaptive and structurally refined detection framework tailored for complex field scenarios. Specifically, a physics-based data augmentation strategy is first introduced to simulate realistic illumination conditions and soil background variations, effectively broadening the training distribution without increasing model complexity. In addition, a lightweight Feature Enhancement Module (FEM) is selectively injected at the P3 detection layer, where high-resolution features are preserved. The FEM integrates a SpatialAttentionLite mechanism with a projection-based feature alignment strategy, enabling precise enhancement of fine-grained spatial cues while maintaining compatibility with pre-trained backbones. An epoch-aware alpha controller is further designed to ensure stable optimization by gradually activating the enhancement pathway during training. Extensive experiments on a real-world agricultural weed dataset demonstrate that the proposed method consistently outperforms baseline YOLOv11 models across multiple evaluation metrics. Notably, DSD-YOLOv11 achieves an absolute mAP@50 improvement of +12.73 percentage points over the native baseline without data augmentation (reaching 87.14%, where the physics-based augmentation contributes +7.94 percentage points and the FEM module contributes an additional +4.79 percentage points over the augmented YOLO11n baseline), while operating at 84.2 FPS on a desktop GPU (NVIDIA RTX 4090; NVIDIA Corporation, Santa Clara, CA, USA) and 7.2 FPS on an edge computing platform (NVIDIA Jetson Nano; NVIDIA Corporation, Santa Clara, CA, USA) with only marginal parameter increases. These results indicate that the proposed framework provides an effective and efficient solution for weed detection in unstructured agricultural environments. Full article

The non-specific lipid transfer proteins (nsLTPs) are able to bind various hydrophobic compounds and facilitate the transport of fatty acids between intracellular membranes, and nsLTPs are found in rice endosperm and embryo during seed development. However, whether nsLTPs function as lipid carriers and thereby affect lipid metabolism in rice grains remains unclear. To elucidate whether nsLTPs influence fatty acid distribution in rice, we generated OsLTP10-OE (OsLTP10 overexpression) and OsLTP10-CR (OsLTP10 CRISPR/Cas9) lines. Phenotypic and metabolic analyses indicated that OsLTP10 expression is closely associated with fatty acid (FA) profiles and grain appearance. In general, total fatty acid content in the brown rice of OsLTP10-OE was higher than that in wildtype, but OsLTP10-CR was lower than wildtype. While FA accumulation was altered in both tissues, the endosperm (milled grain) was more severely affected than the bran, with individual FAs in the milled grains of OsLTP10-OE expanding by 31.87–52.00%. Additionally, key grain quality traits were substantially altered; OsLTP10-CR lines displayed a significantly enlarged white-belly chalkiness area alongside a 19.50% reduction in amylose content, whereas OsLTP10-OE lines showed decreased chalkiness and a 7.80% increase in amylose. Overall, the fatty acid content and composition, chalkiness, brown rice size, and amylose were influenced by OsLTP10. Full article