Search Results (115)

Background/Objectives: Obesity is closely associated with gut microbiota dysbiosis, intestinal barrier dysfunction, and impaired glucose and lipid metabolism. However, single probiotic or prebiotic interventions often yield only limited metabolic improvements. This study aimed to evaluate the effects of a synbiotic formulation comprising Lacto-N-tetraose (LNT) and Bifidobacterium animalis subsp. lactis MN-Gup (MN-Gup) in a high-fat diet (HFD)-induced obese mouse model. Methods: In this study, an HFD-induced obese mouse model was used to investigate whether the synbiotic formulation of LNT and MN-Gup could ameliorate obesity-related metabolic dysregulation, intestinal barrier dysfunction, and gut microbiota imbalance. Mice were treated with LNT alone, MN-Gup alone, or the synbiotic at different doses. Serum biochemical parameters, glucose tolerance, lipid profiles, liver histopathology, intestinal barrier markers, gut microbiota composition, short-chain fatty acid (SCFA) levels were analyzed. Results: High-dose synbiotic intervention significantly outperformed single-component treatments in reducing weight gain, improving glucose tolerance and lipid profiles, and attenuating hepatic lipid accumulation and injury in mice. These metabolic changes were accompanied by improved markers of intestinal barrier integrity and modulation of gut microbiota composition, characterized by the enrichment of beneficial genera (e.g., Akkermansia, Leuconostoc, and Alistipes) alongside a reduction in obesity-associated taxa (including Desulfovibrionaceae_unclassified, Colidextribacter, Helicobacter, Erysipelatoclostridium, Peptococcaceae_unclassified, and Firmicutes_unclassified). Spearman correlation analysis revealed associative links between microbial alterations and host metabolic markers. Conclusions: Collectively, these findings suggest that the synbiotic formulation comprising high-dose LNT and MN-Gup offers potential benefits for managing high-fat diet-induced metabolic dysregulation in mice. Full article

Ionizing radiation has been an important tool in medical diagnosis and treatment. While the use of radiation for diagnostic purposes has been successful, clinicians are wary of the possible negative effects radiation may have on the patient. According to the linear no-threshold model, all levels of radiation are considered harmful and there is no safe threshold. However, some studies suggest there may instead be a hormetic response at lower doses typically defined as exposure below 100 mGy, and that low doses may be beneficial as a possible immunomodulatory therapeutic. Therefore, it is increasingly important to understand the effects of exposure to low doses of radiation. The lung is frequently exposed to radiation from both environmental and medical sources. The effects of low doses of radon, the most heavily studied public radiation exposure source, are still contested, as well as the potential risk from medical X-ray imaging and computed tomography exposures during diagnostic procedures. In order to appropriately evaluate the potential risks and benefits of a low-dose exposure, it is necessary to understand the mechanism(s) of action, particularly the role of DNA damage, reactive oxygen species, inflammation and immune response. Here, we review the mechanistic evidence of low-dose radiation exposure effects on the lung in the current literature and discuss the implications of these results on the validity of the LNT model as well as potential hormetic or adaptive responses. Full article

Ionizing radiation (IR) exerts complex, dose-dependent biphasic effects on the central nervous system (CNS). This review systematically elucidates the mechanisms underlying the impact of high- and low-dose radiation on neurocognitive function. High-dose radiation (HDR) triggers severe DNA damage, oxidative stress, and neuroinflammatory cascades, leading to neuronal dysfunction, suppression of neurogenesis, and failure of neural circuit reorganization, ultimately resulting in persistent cognitive decline. In contrast, low-dose radiation (LDR) exhibits a unique dual nature: within certain thresholds, it can activate endogenous protective pathways—including DNA repair and antioxidant defenses—thereby promoting neural plasticity and network homeostasis and demonstrating adaptive responses and neuroprotective potential. The research paradigm is shifting from the traditional linear no-threshold (LNT) model towards a dynamic homeostasis model. Future research should prioritize the development of neuroprotective strategies during radiotherapy for high-dose exposure, optimize irradiation modalities, and develop novel radioprotective agents to improve patient outcomes. For LDR, it is crucial to delineate its biological effects and explore its potential for intervening in neurodegenerative diseases. This review aims to provide an integrated theoretical framework for understanding the dose-dependent biphasic regulation of radiation on neurocognition and to outline future directions for developing related protective and therapeutic strategies. Full article

Background/Objectives: This study systematically analyzed the concentration dynamics of human milk oligosaccharides (HMOs) and the distribution characteristics of secretory (Se) and Lewis (Le) phenotypes in China. Methods: A total of 1462 breast milk samples were collected from lactating mothers in six major regions of China, including Changchun, Lanzhou, Chengdu, Tianjin, Guangzhou, and Shanghai. We quantified 17 major HMOs by high-performance anion exchange chromatography-pulsed amperometric detection (HPAEC-PAD), and Se/Le phenotypes were determined to evaluate regional differences and distribution patterns. Results: Total HMO concentration in breast milk showed a significant downward trend within 200 days postpartum and stabilized after 200 to 400 days. Fucosylated HMOs accounted for the highest proportion $60.0–83.0\%$, among which 2′-FL had the largest concentration $903.4–2832.7 \mathrm{m}\mathrm{g}/\mathrm{L}$; acetylated HMOs $8.4–17.6\%$ and sialylated HMOs $8.2–25.3\%$ accounted for relatively lower proportions. This study further divided breast milk into four phenotypes based on HMO characteristics: 72.49% of the samples were Se+/Le+, 6.145% were Se+/Le−, 20.12% were Se−/Le+, and 1.24% were double negative (Se−/Le−). Se+ and Le+ phenotypes accounted for 78.7% and 92.6% of the total population, respectively. The total concentration of HMOs in breast milk of different phenotypes was significantly different, with the average total HMO concentration of Se+/Le+ breast milk being the highest (8342 mg/L), while that of Se−/Le− breast milk being the lowest (4532 mg/L). Se+ phenotype was associated with higher levels of fucosylated HMOs, including 2′-fucosyllactose (2′-FL) and lacto-N-fucopentaose I (LNFP I), and lower levels of lacto-N-tetraose (LNT) and sialyl-lacto-N-tetraose b (LST b) compared to other phenotypes. Most HMOs reached their highest concentrations during the colostrum (CM) and transitional milk (TM) stages, followed by a progressive decline with lactation, with phenotype-specific variations evident across all HMOs. Notably, certain HMOs, such as 3-FL, 3′-SL, DFL, and LNDFH II, exhibited distinct temporal patterns. Conclusions: This study revealed the Se/Le phenotype distribution and dynamic characteristics of HMOs in the Chinese mother-infant population, offering a valuable reference for global breast milk composition databases and infant nutrition research. Full article

Although the composition of hearth gas in a blast furnace is still composed of CO, H₂, and N₂, after injecting shale gas, which replaces some pulverized coal, the proportion of CO, H₂, and N₂ in the hearth gas will change with the introduction of H₂. Further, the reduction process of vanadium-titanium magnetite sinter (VTMS) will be significantly impacted. Hence, the energy–mass balance and replacement ratio model was used to calculate the composition of hearth gas under different injection conditions using production data from a VTM blast furnace in the Panxi area of China. In order to investigate how shale gas injection affects the reduction process, the weight loss rates of VTMS under various reduction atmospheres were obtained through a series of thermogravimetric experiments. Additionally, X-ray diffraction (XRD) analysis was performed on select reduced samples to determine the alterations in sinter phases before and after the reaction. The impact of shale gas injection on the reduction process of VTMS was analyzed by phase transformation and kinetic analysis. The results of the research show that the reduction process of VTMS is improved with the increase in shale gas injection. Using the ln-ln analytical method, the linear relationship between ln(−ln(1 − α)) and lnt under different cases was found. The reaction mechanism of VTMS under shale gas injection circumstances is characterized by random nucleation, which is subsequently followed by growth. The integration formula associated with its dynamic function is G(α) = [−ln(1 − α)]^3/4. Full article

A series of PTT-b-PTMG copolyesters was synthesized via direct esterification followed by melt polycondensation using purified terephthalic acid (PTA), bio-based 1,3-propanediol (PDO), and poly(tetramethylene glycol) (PTMG) of varying molecular weights (650–3000 g/mol). The resulting materials were comprehensively characterized in terms of chemical structure, molecular weight, thermal behavior, phase morphology, crystalline architecture, and mechanical performance using a range of analytical techniques: Fourier-transform infrared spectroscopy (FTIR), ¹H-NMR, gel permeation chromatography (GPC), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), wide-angle X-ray scattering (WAXS), small-angle X-ray scattering (SAXS), dynamic mechanical thermal analysis (DMA), tensile testing, and other standard physical methods. FTIR, ¹H-NMR, and GPC data confirmed the successful incorporation of both PTT-hard and PTMG-soft segments into the copolymer backbone. As the PTMG molecular weight increased, the average sequence length of the PTT-hard segments (L_n,T) also increased, leading to higher melting (T_m) and crystallization (T_c) temperatures, albeit with a slight reduction in overall crystallinity. DMA results indicated enhanced microphase separation between hard and soft domains with increasing PTMG molecular weight. WAXS and SAXS analyses further revealed that the crystalline structure and long-range ordering were strongly dependent on the copolymer composition and block architecture. Mechanical testing showed that tensile strength at break remained relatively constant across the series, while Young’s modulus increased significantly with higher PTMG molecular weight—concurrently accompanied by a decrease in elongation at break. Furthermore, the elastic deformability and recovery behavior of PTT-b-PTMG block copolymers were evaluated through cyclic tensile testing. TGA confirmed that all copolyesters exhibited excellent thermal stability. This study demonstrates that the physical and mechanical properties of bio-based PTT-b-PTMG elastomers can be effectively tailored by adjusting the molecular weight of the PTMG-soft segment, offering valuable insights for the rational design of sustainable thermoplastic elastomers with tunable performance. Full article

Cadmium exposure has been associated with shortened telomeres, alterations in DNA methylation patterns, and increased mortality. However, the role of DNA methylation in mediating the relationship between cadmium and telomere dynamics is still unclear. Additionally, it is unknow how telomere dynamics and DNA methylation alterations may affect the association between cadmium exposure and mortality outcomes. We utilized data from 8716 National Health and Nutrition Examination Survey (NHANES) participants aged 18 and above, collected between 1999 and 2002, and linked these to mortality outcomes from the National Center for Health Statistics (NCHS) through 2019. In the final model, ln-blood cadmium was significantly and inversely associated with ln-T/S ratio (β = −0.043, 95% CI: −0.059 to −0.027, p < 0.001), while ln-Horvath DNAmTL was strongly and positively associated with ln-T/S ratio (β = 1.782, 95% CI: 1.467 to 2.097, p < 0.001). Moreover, ln-blood cadmium also showed a significant inverse association with ln-Horvath DNAmTL (β = −0.010, 95% CI: −0.014 to −0.006, p < 0.001). Structural equation modeling showed that the association between cadmium and T/S ratio was mediated by Horvath DNAmTL, with a total effect of −0.044, a direct effect of −0.027, and an indirect effect of −0.017. Furthermore, stratified analyses revealed that a 1-unit increase in ln-blood cadmium was associated with higher all-cause mortality, with hazard ratios (HR) of 1.47 for participants with T/S ratio below the median and 1.41 for those above. Similar patterns were observed for cardiovascular (HR = 1.68 vs. 1.30) and cancer mortality (HR = 1.75 vs. 1.42). For Horvath DNAmTL, the association was significant only for all-cause mortality (HR = 1.36 vs. 1.31). However, no significant interactions were detected. In conclusion, our findings suggest that Horvath DNAmTL is associated with the relationship between cadmium and telomere length, suggesting a potential DNA methylation pathway that warrants further longitudinal investigation. Individuals with lower T/S ratios or Horvath DNAmTL appear to be more susceptible to cadmium-related mortality. Further research is necessary to confirm these results. Full article

Arsenic, a naturally occurring metalloid, poses a significant global public health threat due to widespread environmental contamination. Despite its well-documented carcinogenicity, critical gaps remain in understanding the health impacts of chronic low-level airborne exposure and the multi-modal mechanisms driving inorganic arsenic toxicity. This narrative review synthesizes recent molecular research and population health data to explain how airborne inorganic arsenic causes harm through multiple biological pathways. Key novel insights include (1) a comprehensive analysis of inorganic arsenic-induced oxidative stress and epigenetic dysregulation, revealing transgenerational effects via germline epigenetic markers; (2) a critical evaluation of the linear no-threshold (LNT) model, demonstrating its overestimation of low-dose risks by 2–3× compared to threshold-based evidence; and (3) descriptions of mechanistic links between inorganic arsenic speciation, organ-specific pathologies (e.g., neurodevelopmental impairments, cardiovascular diseases), and pollution mitigation strategies. This study connects molecular mechanisms with public health strategies to improve arsenic risk assessment. It focuses on how inorganic arsenic alters gene regulation (epigenetics) and combines exposure from multiple sources, while also clarifying uncertainties about low-dose effects and refining safety standards. Full article

Nitrogen is an essential nutrient for the growth and development of maize (Zea mays L.), and soil nitrogen deficiency is an important factor limiting maize yield. Although excessive application of nitrogen fertilizer can increase yield, it can also cause environmental problems. Therefore, screening low-nitrogen-tolerant (LNT) germplasm resources and analyzing their genetic mechanisms are of great significance for the development of efficient and environmentally friendly agriculture. In this study, 201 maize inbred lines were used as materials. Two levels of low nitrogen (LN) (0.05 mmol/L, N1) and normal nitrogen (4 mmol/L, N2) were set up. Phenotypic indicators such as seedling length, root length and biomass were measured, and they were classified into LNT type (18 samples), nitrogen-sensitive (NS) type (27 samples) and intermediate type (156 samples). A total of 47 significant SNP loci were detected through a genome-wide association study (GWAS), and 36 candidate genes were predicted. Transcriptome sequencing (RNA-seq) analysis revealed that the differentially expressed genes (753 upregulated and 620 downregulated) in LNT materials under low nitrogen stress (LNS) were significantly fewer than those in NS materials (2436 upregulated and 2228 downregulated). Further analysis using WGCNA identified a total of eight co-expression modules. Among them, the red module was significantly correlated with root length and underground fresh weight under LN conditions (r = 0.75), and three key genes for stress response (Zm00001d005264, Zm00001d053931, Zm00001d044292) were screened out. Combined with GWAS, RNA-seq and qRT-PCR verification, eight candidate genes closely related to LNT at the seedling stage of maize were finally determined, involving biological processes such as stress response, nitrogen metabolism and substance formation. This study initially revealed the molecular mechanism of maize tolerance to LN through multi-omics analysis, providing a theoretical basis and genetic resources for breeding new nitrogen-efficient maize varieties. Full article

Intestinal inflammation involves barrier impairment, immune hyperactivation, and oxidative stress imbalance. Bioactive polysaccharides universally alleviate inflammation via anti-inflammatory, antioxidant, and microbiota-modulating effects, yet exhibit distinct core mechanisms. Elucidating these differences is vital for targeted polysaccharide applications. This research examines distinct regulatory pathways through which diverse bioactive polysaccharides mitigate lipopolysaccharide-triggered intestinal inflammation in male Kunming (KM) mice. This experiment employed Lentinula edodes polysaccharide (LNT), Auricularia auricula polysaccharide (AAP), Cordyceps militaris polysaccharide (CMP), Lycium barbarum polysaccharide (LBP), and Brassica rapa polysaccharide (BRP). The expression levels of biomarkers associated with the TLR4 signaling pathway, oxidative stress, and intestinal barrier function were quantified, along with comprehensive gut microbiota profiling. The results showed that all five polysaccharides alleviated inflammatory responses in mice by inhibiting inflammatory cytokine release, reducing oxidative damage, and modulating gut microbiota, but their modes of action differed: LBP significantly suppressed the TLR-4/MyD88 signaling pathway and its downstream pro-inflammatory cytokine expression, thereby blocking inflammatory signal transduction and reducing oxidative damage; LNT and CMP enhanced the body’s antioxidant capacity by increasing antioxidant enzyme activities and decreasing malondialdehyde (MDA) levels; AAP and BRP enriched Akkermansia (Akk.) within the Verrucomicrobia (Ver.) phylum, upregulating tight junction protein expression to strengthen the intestinal mucosal barrier and indirectly reduce oxidative damage. This research demonstrates that different polysaccharides alleviate inflammation through multi-target synergistic mechanisms: LBP primarily inhibits inflammatory pathways; AAP and BRP focus on intestinal barrier protection and microbiota modulation; and LNT and CMP exert effects via antioxidant enzyme activation. These data support designing polysaccharide blends that leverage complementary inflammatory modulation mechanisms. Full article

This study investigates the mechanical behavior and deformation mechanisms of Fe-30Mn-0.05C (30Mn0.05C) and Fe-34Mn-0.7C (34Mn0.7C) steels at room temperature (RT) and liquid nitrogen temperature (LNT). The 30Mn0.05C sample exhibited a significant enhancement in both strength and ductility at LNT, achieving a total elongation of 85%. In contrast, the 34Mn0.7C sample demonstrated superior ductility (90%) at RT, with a marginal reduction in plasticity but a remarkable increase in strength (>1100 MPa) at LNT. Compared to the 30Mn0.05C, the 34Mn0.7C, characterized by higher carbon content, displayed more pronounced dynamic strain aging (DSA) effects. Additionally, a greater density of deformation twins was activated at LNT, revealing a strong correlation between deformation twinning and DSA effects. This interplay accounts for the simultaneous strength improvement and ductility reduction observed in the 34Mn0.7C at LNT. Furthermore, the 34Mn0.7C sample exhibited a significantly refined grain structure after rolling, contributing to a substantial strength increase (approaching 1500 MPa) at the expense of ductility. This trade-off can be attributed to the pre-introduction of a higher density of dislocations and deformation twins during rolling, which facilitated strengthening but limited further plastic deformation. Full article

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer. Extensive efforts have been made to utilize radiomics from computed tomography (CT) imaging to predict tumor immune microenvironment (TIME) measurements. This study proposes a Green Learning (GL) framework for approximating tissue-based biomarkers from CT scans, focusing on the PD-L1 expression and CD68 tumor-associated macrophages (TAMs) in ccRCC. Our approach includes radiomic feature extraction, redundancy removal, and supervised feature selection through a discriminant feature test (DFT), a relevant feature test (RFT), and least-squares normal transform (LNT) for robust feature generation. For the PD-L1 expression in 52 ccRCC patients, treated as a regression problem, our GL model achieved a 5-fold cross-validated mean squared error (MSE) of 0.0041 and a Mean Absolute Error (MAE) of 0.0346. For the TAM population (CD68+/PanCK+), analyzed in 78 ccRCC patients as a binary classification task (at a 0.4 threshold), the model reached a 10-fold cross-validated Area Under the Receiver Operating Characteristic (AUROC) of 0.85 (95% CI [0.76, 0.93]) using 10 LNT-derived features, improving upon the previous benchmark of 0.81. This study demonstrates the potential of GL in radiomic analyses, offering a scalable, efficient, and interpretable framework for the non-invasive approximation of key biomarkers. Full article

Autonomous vehicles are one of the key components of smart mobility that leverage innovative technology to navigate and operate safely in urban environments. Traffic light detection systems, as a key part of autonomous vehicles, play a key role in navigation during challenging traffic scenarios. Nighttime driving poses significant challenges for autonomous vehicle navigation, particularly in regard to the accuracy of traffic lights detection (TLD) systems. Existing TLD methodologies frequently encounter difficulties under low-light conditions due to factors such as variable illumination, occlusion, and the presence of distracting light sources. Moreover, most of the recent works only focused on daytime scenarios, often overlooking the significantly increased risk and complexity associated with nighttime driving. To address these critical issues, this paper introduces a novel approach for nighttime traffic light detection using the LNT-YOLO model, which is based on the YOLOv7-tiny framework. LNT-YOLO incorporates enhancements specifically designed to improve the detection of small and poorly illuminated traffic signals. Low-level feature information is utilized to extract the small-object features that have been missing because of the structure of the pyramid structure in the YOLOv7-tiny neck component. A novel SEAM attention module is proposed to refine the features that represent both the spatial and channel information by leveraging the features from the Simple Attention Module (SimAM) and Efficient Channel Attention (ECA) mechanism. The HSM-EIoU loss function is also proposed to accurately detect a small traffic light by amplifying the loss for hard-sample objects. In response to the limited availability of datasets for nighttime traffic light detection, this paper also presents the TN-TLD dataset. This newly curated dataset comprises carefully annotated images from real-world nighttime driving scenarios, featuring both circular and arrow traffic signals. Experimental results demonstrate that the proposed model achieves high accuracy in recognizing traffic lights in the TN-TLD dataset and in the publicly available LISA dataset. The LNT-YOLO model outperforms the original YOLOv7-tiny model and other state-of-the-art object detection models in mAP performance by 13.7% to 26.2% on the TN-TLD dataset and by 9.5% to 24.5% on the LISA dataset. These results underscore the model’s feasibility and robustness compared to other state-of-the-art object detection models. The source code and dataset will be available through the GitHub repository. Full article

The enhancement of gel properties in chicken myofibrillar proteins (MPs) is a crucial objective in meat processing. In this experiment, we systematically investigated the effects of lentinan (LNT) on MP gel formation ability and three-dimensional network structure features through multi-scale structural characterization and molecular interactions analysis and elucidated the molecular pathways of their molecular actions in regulating gel properties. The addition of LNT (0–2%, w/v) significantly enhanced the water-holding capacity (WHC), textural, and rheological properties of LNT-MPs. As the concentration of LNT increased, the hydrophobic and electrostatic interactions became more pronounced. Conversely, the contribution from disulfide bonds exhibited an inverse relationship, with hydrogen bonds demonstrating the least impact. Subsequently, the α-helix content decreased from 23.75% to 22.64%, and the β-fold content increased from 28.03% to 29.22%, suggesting that the protein aggregates reorganized to form larger aggregates, which contributed to forming a more stable network structure of gels. This investigation establishes LNT’s capacity to modify the gelation mechanisms of MPs. These outcomes offer crucial insights for implementing fungal polysaccharides in processed meat product development. Full article

The aim of this study was to evaluate the effects of lentinan (LNT) on the quality of colostrum produced by perinatal dairy cows and the health status of their newborn calves. A total of 40 expectant Holstein cows, matched for parity and expected date of delivery, were selected and randomly divided into four groups: a control group fed a total mixed diet (TMR); a low LNT group (10 g/d, LLNT); a medium LNT group (20 g/d, MLNT); and a high LNT group (40 g/d, HLNT). The study commenced 21 days prior to parturition and continued for three weeks. Colostrum was collected from the cows immediately after delivery and subsequently fed to the newborn calves. The results indicated that colostrum milk protein production and IgG production in the MLNT group were significantly increased (p < 0.05). Following colostrum gavage, serum SOD and IgG in both the MLNT and HLNT groups showed significant increases (p < 0.05), while MDA and IL-1β levels were significantly decreased (p < 0.05). Moreover, calves in the MLNT and HLNT groups experienced lower incidences of diarrhea, pneumonia, and overall morbidity compared to those in the control group. In conclusion, LNT enhanced the quality of colostrum in perinatal cows and contributed to the health of newborn calves through colostrum. This study offers new research avenues for improving the health of newborn calves and provides a theoretical foundation for the development of LNT as a novel feed additive. Full article