Search Results (359)

Soil salinization is considered a major abiotic stress limiting the sustainable development of agriculture globally. Utilizing plant growth-promoting rhizobacteria (PGPR) to enhance crop tolerance under saline–alkali stress constitutes a sustainable and promising strategy. This study focuses on Enterobacter cloacae strain DJ, isolated from the rhizosphere of Leymus chinensis in saline–alkali soil. This study aims to investigate the role of gamma-aminobutyric acid (GABA)metabolism in regulating the saline–alkali adaptation of strain DJ and its growth-promoting effects on maize under such stress. The results indicated that under saline–alkali conditions, strain DJ upregulated genes associated with GABA metabolism, energizing ion transport and motility. Furthermore, the extracellular GABA concentration in the culture medium of strain DJ rose from 4.04 μmol L⁻¹ at 4 h to 11.65 μmol L⁻¹ at 12 h, followed by a decline to 7.00 μmol L⁻¹ at 24 h, suggesting that GABA potentially promotes cellular growth and physiological activities. Exogenous GABA further enhanced the ion transport capacity, motility, and biomass of strain DJ, confirming the contribution of GABA to improving its saline–alkali adaptability. In maize, strain DJ improved germination (by 7–10%) and seedling growth under saline–alkali conditions, as evidenced by increases in primary radicle length (+2.8 cm), shoot height (+2 cm), and fibrous root number (+4). It upregulated root expression of GAT1 (threefold), GABA-T (1.3-fold), and SSADH (1.5-fold), and increased antioxidant enzyme activities (SOD/POD: 1.5-fold; CAT: 1.8-fold). These findings demonstrate that strain DJ enhances the antioxidant capacity of maize through a GABA-mediated pathway and supports energy metabolism for improving tolerance under saline–alkali conditions. Full article

The intracellular accumulation of amyloid beta 42 (iAβ42) has been proposed as an early pathological indicator of familial Alzheimer’s disease (FAD). DJ-1 is a multifunctional protein sensitive to oxidative stress (OS) that has been associated with neurodegeneration; however, its role in iAβ42 pathology is unclear. In this study, we examined whether oxidized (sulfonic) DJ-1 (Cys¹⁰⁶-SO₃H) drives iAβ42 accumulation using postmortem brain samples and in vitro 3D iPSC-derived cerebral organoids (COs) or 2D induced pluripotent stem cells (iPSC)-derived ChLNs (cholinergic-like neurons) models from a PSEN1 E280A patient and a healthy volunteer (as a control sample). Post-mortem analyses of the temporal and frontal cortices and hippocampus from FAD PSEN1 E280A patients revealed strong intracellular co-localization of sulfonic DJ-1 and iAβ42, which was absent in control samples. To validate these findings, we generated COs from an iPSC PSEN1 E280A FAD patient and a healthy donor. In these organoids, we observed the co-localization of oxidized DJ-1 and Aβ42 in the absence of extracellular fibrils or plaques, as confirmed by BTA-1 staining. To further support these observations, 2D iPSC PSEN1 E280A-derived ChLNs cultures showed that intracellular Aβ42 accumulates progressively in direct correlation with increasing DJ-1 oxidation, as demonstrated by immunofluorescence microscopy and Western blotting analysis. These results indicate that DJ-1 oxidation accompanies the earliest intracellular stages of Aβ42 pathology. Furthermore, complementary in silico molecular docking analysis revealed a higher affinity between Aβ42 and oxidized sulfonic DJ-1 (DJ-1 Cys¹⁰⁶-SO₃H) compared to sulfenic (DJ-1 Cys¹⁰⁶-SOH) or sulfinic acid (DJ-1 Cys¹⁰⁶-SO₂H) forms. Likewise, ELISA tests and seeding assays confirmed that oxidized DJ-1 binds to and decelerates Aβ42 aggregation kinetics. Together, our results identify DJ-1 oxidation as a critical molecular event in the accumulation of iAβ42 in FAD. These findings suggest that oxidized DJ-1 represents not only a potential early biomarker of intracellular pathology but also a pharmacological target. Preventing the oxidation of DJ-1 or its pathological aggregation could provide new biomarkers and therapeutic strategies for reducing the intracellular accumulation of Aβ42 and neurodegeneration in FAD. Full article

Paddy soils are important contributors to agricultural greenhouse gas emissions, particularly methane, and soil amendments may regulate methane production by altering soil physicochemical properties and microbial methane cycling. However, the effects of different amendment types on methane emissions from anaerobic paddy soils remain uncertain. In this study, an anaerobic microcosm experiment was conducted to evaluate the effect of microbial inoculants, biochar, humic acid, and montmorillonite on CH₄ and CO₂ emissions from paddy soil. Changes in acetate concentration, pH, electrical conductivity, microbial community structure, and methane cycling functional genes were further analyzed to explore the underlying mechanisms. The results showed that microbial inoculants had stronger effects on CH₄ emissions than the other amendments, but their effects were contrasting. The Chabeijian (CB) inoculant significantly increased methane emissions by 100.8%, whereas the Duojun-360 (DJ) inoculant reduced cumulative methane by 57.1%. The stimulation of CH₄ emissions under Chabeijian was associated with enhanced acetate turnover, enrichment of methanogenic taxa including Methanosarcina, Methanobacterium, Methanocella, and Methanosaeta, and a 48.7% increase in mcrA abundance. In contrast, Duojun 360 markedly increased soil electrical conductivity, reduced methanogen abundance, decreased mcrA abundance by 26.9%, and lowered the mcrA/pmoA ratio, indicating a shift away from methane production. Although both inoculants increased methanotroph abundance and pmoA abundance, methane production remained the dominant factor controlling net CH₄ emissions. These findings may provide preliminary mechanistic support for the targeted selection of soil amendments to mitigate CH₄ emissions in rice cultivation by regulating soil properties, methanogenic communities, and the balance between methane production and oxidation. Full article

Objective: To examine lower-body stretch–shortening cycle (SSC) indicators across chronological age categories and playing positions in elite male youth soccer players. Methods: In a cross-sectional design, 984 male players from Slovakia (U15–U19) completed Squat Jumps (SJ), Countermovement Jumps (CMJ), and Drop Jumps (DJ) using the OptoJump photocell system. Outcomes included Eccentric Utilization Ratio (EUR), Reactive Strength Index (RSI), DJ Ground Contact Time (DJ GCT), and Jump Heights (JH). Differences were tested using factorial ANCOVA (age category × playing position) adjusted for height and weight, followed by Tukey-adjusted post hoc comparisons (p < 0.05). Results: Significant age-category main effects were observed for DJ RSI, DJ JH, CMJ JH, SJ JH, and DJ GCT. The largest effects were for DJ JH, CMJ JH, and SJ JH (ηp² = 0.096–0.112), whereas the DJ GCT effect was statistically significant but small (ηp² = 0.013). EUR showed no significant differences across age categories (p = 0.586). Positional differences were limited overall and mainly evident in selected U19 outcomes, particularly jump-height variables and DJ GCT. Conclusions: Lower-body SSC performance increased across chronological age categories, with the largest separation in jump-height and reactive strength outcomes. These differences likely reflect a combination of maturation, training exposure, and selection rather than chronological age alone. EUR remained stable across age categories and playing positions, although the JH-based ratio has limited sensitivity in the present test configuration. Positional separation emerged mainly at U19, supporting broad SSC development across earlier youth categories and position-sensitive interpretation in the oldest cohort. Full article

This study presents a data-driven framework to predict and optimize the quality of date juice (DJ) produced from two commercially important Saudi cultivars (Sukkary and Khlass) using physicochemical and processing variables as model inputs. A total of 1600 experimental runs were performed by systematically varying initial fruit moisture content, extraction temperature (20, 40, 60, and 80 °C), mixing velocity (10, 20, 30, 40, and 50% of maximum speed), and date-to-water ratios (1:1, 1.5, 2, 2.5, and 3 w/w). The produced juices were characterized at 25 °C for water activity, moisture content, density, pH, total soluble solids (°Brix), turbidity, viscosity, hydroxymethylfurfural (HMF), browning index, extraction time, electrical energy consumption, and an integrated Quality Index (Qi). A feed-forward artificial neural network (ANN; 7–15–1) with a hyperbolic tangent transfer function was developed and validated using normalized datasets, and its performance was benchmarked against multiple linear regression (MLR). The ANN consistently outperformed MLR for Qi prediction, achieving higher coefficients of determination and lower error indices across training, testing, and validation, indicating strong generalization and minimal overfitting. Sensitivity analysis highlighted total soluble solids, moisture content, and HMF as the most influential predictors of Qi. Optimal juice quality (Qi ≥ 0.91) was repeatedly achieved under moderate thermal conditions (≈60 °C), with 40% mixing velocity and a 1:2.5 date-to-water ratio, providing a practical operating window for producing juice at the target °Brix while limiting thermal quality deterioration. Overall, the proposed ANN-based model provides an actionable decision-support tool for process optimization and quality standardization, supporting the transition of date-juice manufacturing toward Industry 4.0 through data-driven monitoring and adaptive control strategies. Full article

Building upon our previous aerodynamic characterizations of skewed jets, this study extends the investigation to systematically evaluate their thermal performance. Turbulent air jets are produced by unilaterally supplying coolant and forcing it through a series of concave perforated blockages having varying relative inner diameters (D_in/D_j = 3.0, 4.0 and 5.0) or relative thicknesses (t/D_j = 0.5, 2.0, 4.0, 6.0 and 8.0), with the jet diameter and Reynolds number fixed at D_j = 21 mm and Re_j = 20,000, respectively. The results demonstrate that the skewed jets exhibit pronounced asymmetric velocity profiles in both the x-z and y-z planes. Unlike the Gaussian distributions characteristic of conventional axisymmetric jets, these profiles manifest as distinctly skewed or saddle-shaped topologies. This topological distortion is exacerbated by reducing either D_in/D_j or t/D_j, albeit through fundamentally different mechanisms: the former only leads to jet deflection from the geometric axis, with the deflection angle increasing non-linearly from α = 4°, 5° to 12°; whilst the latter induces asymmetric internal flow development and exit momentum redistribution. The thermal performance of these jets on an iso-flux target flat plate, characterized by Nusselt number distributions at different jet-to-target spacings (H/D_j = 0 to 8.0), is shown to significantly differ from conventional axisymmetric jets. Full article

Deep coalbed methane reservoirs are characterized by complex geological conditions, strong heterogeneity, and significant variations in in situ stress, posing challenges for accurate three-dimensional in situ stress prediction. To address the issues of strong dependence on rock mechanical parameters in traditional physical models, as well as the lack of physical constraints and poor generalization capability under small-sample conditions in purely data-driven methods, this paper proposes a LightGBM prediction model that integrates physical information and data clustering. A total of 1289 fracturing clusters in the DJ block are selected as the research objects. First, the K-means algorithm is used to divide the reservoir into three categories to reduce the impact of heterogeneity. Then, a LightGBM model is constructed for each category, and physical constraints based on Huang’s model and stress–gravity equilibrium are incorporated into the loss function to ensure that the prediction results conform to mechanical laws. Taking the fracturing clusters in Category I as an example, the proposed model achieves an MAPE of 2.78% and an R² of 0.89 on the test set. Comparative experiments show that the proposed model outperforms BP neural networks, random forests, and Transformers in prediction accuracy. Ablation experiments verify the independent contributions and synergistic effects of the clustering module and the physical information constraints. Transfer experiments demonstrate that the model has good applicability to blocks with similar geological conditions. This study provides an effective method for predicting in situ stress in deep coalbed methane reservoirs, balancing accuracy and physical interpretability. Full article

This study investigated the effects of freeze–thaw cycles on unreinforced and basalt fiber-reinforced lunar regolith simulant (LRS) geopolymer. Specimens were subjected to 0, 3, 6, and 10 freeze–thaw cycles. Compressive strength, flexural strength, elastic modulus, peak strain, and failure mode were measured. Damage degree and gain ratio were used to evaluate fiber reinforcement. Results showed that the unreinforced LRS geopolymer exhibited considerable fluctuation in compressive strength during freeze–thaw cycles. Its compressive strength first increased, then decreased; its flexural strength continuously declined; and its elastic modulus and peak strain showed opposite trends, with typical brittle failure. In contrast, basalt fiber-reinforced LRS geopolymer demonstrated superior frost resistance. Its compressive strength increased continuously with freeze–thaw cycles, reaching 23.5% after 10 cycles. Its flexural strength decreased but stabilized, with a damage level of only 16.0% after 10 cycles, significantly lower than that of the unreinforced group (26.1%). Its elastic modulus increased continuously while peak strain decreased gradually, with failure exhibiting some ductile characteristics. Gain ratio analysis showed compressive and flexural strength gain ratios of 1.92 and 1.69, respectively, after 10 cycles, indicating significant reinforcement. Among three classical constitutive models (Guo Zhenhai, Saenz L.P., and Carreira D.J.), the Guo Zhenhai model provided the best fit for stress–strain curves of both geopolymer types under all freeze–thaw conditions, making it the recommended constitutive model. This study provides theoretical support for LRS geopolymer applications in extreme environments such as the lunar surface. Full article

Gas content is a key parameter for coalbed methane (CBM) resource evaluation and production potential assessment. The accurate prediction of gas content in deep coal reservoirs is more challenging than in shallow reservoirs because both adsorbed gas and free gas must be considered. In this study, continuous logging data from the deep No. 8 coal seam in the Daning–Jixian block were integrated with measured gas content-related parameters to construct a quantitative logging interpretation framework for deep CBM reservoirs. First, the relationships between logging parameters and Langmuir volume, Langmuir pressure, porosity, and water saturation were analyzed. Then, multiple linear regression models were established to predict these key intermediate parameters, which were subsequently used to calculate adsorbed gas, free gas, and total gas content. The model was further applied to the DJ 52 well area for spatial prediction. The results show that the total gas content ranges from 24.49 to 32.90 cm³/g. The high-gas-content area is mainly located in the north-central part of the study area, whereas the southern part shows relatively lower gas content, partly due to the influence of coal seam thickness and reservoir property heterogeneity. The proposed method provides an interpretable and practical approach for deep CBM gas content evaluation using logging data. Full article

This study investigated interlimb asymmetries in lower limb performance using both vertical and horizontal jump tests in elite young basketball players. Specifically, it aimed to determine whether (1) unilateral jump performance and (2) the magnitude of interlimb asymmetry differed across maturity groups, whether (3) limb dominance influences performance, and whether (4) asymmetry direction is consistent across tests. One hundred elite male basketball players (U13 to U19) were categorised into three maturational stages: Pre-PHV (n = 19), Circa-PHV (n = 29), and Post-PHV (n = 52). Each athlete performed the following unilateral tests with both the dominant and non-dominant leg: single-leg hop, triple hop for distance, 6 m timed hop, single-leg countermovement jump (SL-CMJ), and single-leg drop jump (SL-DJ) from a 30 cm box. The Bilateral Strength Asymmetry (BSA) index was computed for each test. All tests showed significant differences between Pre-PHV and Circa-PHV groups (p < 0.001), whereas only the 6 m timed hop differed between Circa-PHV and Post-PHV (p < 0.01). BSA did not differ significantly across maturation stages in any test, except for the single-leg hop. Agreement in asymmetry direction between test pairs was slight to fair (kappa ≤ 0.29). BSA values remained largely stable across maturational stages, suggesting that interlimb asymmetries are established before PHV, likely during childhood. Limb dominance did not affect jump performance, and asymmetry direction varied between tests, confirming they are not interchangeable. Full article

Background: Sprint performance, including acceleration, maximal velocity and deceleration, is crucial for athletic success in field and court-based sports; however, deceleration remains understudied despite its role in change of direction (COD) and match performance. Methods: This study addressed this gap by comparing eccentric metrics from countermovement jumps (CMJ), drop jumps (DJ) and the Nordic hamstring exercise (NHE) to 30 m sprint and deceleration ability in 28 university athletes (Age: 20 ± 1 years; Mass: 68 ± 9 kg; Height:166 ± 6 cm). Correlations were analysed with Pearson’s r for normal data and Spearman’s r for non-normal data. Results: Significant negative correlations were found between the CMJ and DJ heights and the modified reactive strength index (RSI_MOD), as well as the reactive strength index (RSI) with sprint time (r = −0.54 to −0.83, p < 0.05), while positive correlations were obtained with sprint velocity (r = 0.57 to 0.83, p < 0.05). The eccentric mean forces from CMJs and DJs were positively correlated with sprint time and deceleration momentum (r = 0.62 to 0.84, p < 0.05). However, there were no significant correlations between NHE eccentric force and any sprint or deceleration metrics. The CMJ and DJ heights, RSI and eccentric mean forces strongly predicted sprint time, velocity, and momentum, but not deceleration performance, highlighting the role of explosive power and reactive strength. The NHE eccentric force had no significant relationships with sprint or deceleration metrics. Conclusions: These results highlight that CMJ and DJ are effective predictors of sprint performance, while deceleration efficiency may rely on other biomechanical factors. Full article

Cystathionine β-synthase (CBS) deficiency causes classical homocystinuria with severe hyperhomocysteinemia (HHcy) that is inadequately controlled by current therapies. We tested whether liver-targeted CBS gene therapy provides durable biochemical and phenotypic rescue. Using a Cre-inducible adult mouse model of whole-body CBS loss, a single intravenous dose of AAV-DJ-hCBS (3 × 10¹² or 3 × 10¹³ vg/kg) was administered, and the animals were followed for 12 months. Vector biodistribution showed ~100-fold hepatic enrichment over the kidney and spleen. Both doses rapidly normalized plasma homocysteine (<8 µM), maintaining correction throughout the study while preventing alopecia, weight loss, and loss of adiposity. Liver histology showed resolution of inflammation, and only 2 of 19 mice developed anti-hCBS antibodies. Liver proteomics (3998 proteins quantified) revealed CBS deficiency-associated suppression of tRNA aminoacylation and dysregulation of lipid and carbon metabolism with an HNF4A transcriptional signature, all normalized by therapy. Liver metabolomics demonstrated accumulation of S-adenosylmethionine and S-adenosylhomocysteine and disruption of phosphatidylcholine synthesis, also corrected by treatment. Plasma metabolomics revealed systemic disturbances fully normalized by hepatic CBS restoration. These findings identify the liver as the central metabolic control point in CBS deficiency and support liver-targeted gene therapy as a durable corrective strategy. Full article

This study presents the results of a Proof of Concept developed within the framework of the Amygdala Project, aimed at exploring the relationship between electronic music and emotional well-being among young people with and without a diagnosis of adjustment disorders (anxiety, depression, and distress). The fieldwork was conducted during the live concert of DJ Steve Aoki (Cosquín Rock 2024, Valladolid), combining psychophysiological measurements using Sociograph technology, self-reported questionnaires, and performative and contextual analyses. The results reveal significant differences between the two groups: participants with a diagnosis exhibited a more constant and profound emotional connection, interpreting the experience as a form of “emotional escape” and an opportunity for affective regulation; whereas those without a diagnosis experienced more fluctuating levels of attention and perceived the event primarily as entertainment. The triangulation of biometric, observational, and narrative data suggests that electronic music in collective contexts may operate as a tool for emotional containment and transformation, fostering group cohesion and reducing psychological distress. These findings open new avenues for interdisciplinary research into the biosocial effects of contemporary music and its potential in the design of cultural and educational strategies to promote psychological well-being among young people. Full article

Oxidative stress-induced RPE cell death is a major cause of AMD pathogenesis. However, the exact modes of oxidative stress-driven retinal death remain elusive. To address this knowledge gap, we investigated the role of DJ-1, an antioxidant protein we previously characterized in the retina, in cell death regulation. Specifically, we analyzed cell death pathways in the retinas of DJ-1 knockout (KO) mice, with or without sodium iodate (NaIO₃) injection. We quantified MAPK signaling protein activation by Western blot. The distribution of the cell death executioners, activated caspase 3, and pMLKL, was investigated. The effects of caspase and necroptosis inhibitors in mice previously injected with NaIO₃ were determined. Significant increases in JNK1/2 activation and FOXO1 levels were detected in RPE lysates when DJ-1 KO mice were injected with 10 mg/kg NaIO₃. The immunoreactivity of active caspase-3 and pMLKL was stronger in the retinas of DJ-1 KO compared with C57BL mice. These immunoreactivities further increased in the degenerating outer retina post NaIO₃ injection and were stronger in the retina of DJ-1 KO compared with C57BL mice at both doses of NaIO₃. ZVAD treatment rescued retinal degeneration to varying degrees in DJ-1 KO mice. However, necrostatin (Nec-1) alleviated retinal degeneration in both DJ-1 KO and C57BL mice, suggesting that apoptosis is a major cell death modality in the absence of DJ-1. Overall, oxidative stress-induced RPE and retinal cell death involve activation of both apoptosis and necroptosis in the absence of DJ-1. Full article

A highly selective and sensitive compact immunosensing strategy was developed for the determination of DJ-1, a potential biomarker of Parkinson’s disease, one of the leading neurodegenerative disorders, using a portable potentiostat. Initially, screen-printed carbon electrodes (SPCEs) were modified with gold nanoparticles (AuNPs), followed by functionalization with 4-mercapto-1-butanol (MOH). Subsequently, the AuNPs-doped and hydroxyl-functionalized electrodes were treated with 3-glycidoxypropyltrimethoxysilane (GPTMS) to facilitate immobilization of anti-DJ-1 antibodies. Immobilization steps were monitored using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) performed on a bench potentiostat, while the entire analytical performance of the developed biosensor system and its response in artificial cerebrospinal fluid (aCSF) were evaluated by monitoring cathodic current changes with a portable electrochemical reader. The resulting biorecognition element enabled the detection of DJ-1 within the concentration range of 0.001 to 0.3 ng/mL, based on cathodic current changes, achieving a limit of detection as low as 0.00059 ng/mL. Surface morphology and elemental composition alterations were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and energy-dispersive X-ray spectroscopy (EDX). A notable advantage of this GPTMS@AuNPs-based biosensor system is its prolonged storage stability and its capability to accurately quantify DJ-1 in artificial cerebrospinal fluid samples, with recovery rates ranging from 98.66% to 123.3%. Full article