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This study was conducted to investigate the relationship between different cornstarch levels in tilapia diet and immune function. All test fish were fed with three cornstarch levels: low-cornstarch (0, LS), medium-cornstarch (18%, MS) and high-cornstarch (36%, HS) diets. Three hundred and sixty fish (initial mean body weight 31.73 ± 1.36 g) were randomly allocated into twelve water-circulated tanks, and thirty fish per tank. Compared with the low and medium cornstarch diets, the results of growth showed that the high cornstarch diet significantly decreased the FBW, WGR, and SGR, and increased the FCR of tilapia ( P  < 0.05). The high cornstarch diet significantly decreased the content of crude protein and increased the content of crude lipid in whole body composition ( P  < 0.05). Moreover, the VSI and CF in HS diet were significantly higher than those of LS diet ( P  < 0.05). The results of blood biochemical index exhibited that the HS diet significantly increased the content of blood glucose, and liver/muscle glycogen ( P  < 0.05). The results of antioxidant experiments demonstrated that the content of SOD and T-AOC in MS diet were significantly higher than those of HS diet ( P  < 0.05). Meanwhile, the content of MDA in MS diet was significantly lower than that of HS diet ( P  < 0.05). The results of immune index test showed that the lysozyme activities in the serum, liver, and gill, and the phagocytic activity and index in MS diet were significantly higher than those of HS diet ( P  < 0.05). The challenge assay results revealed that the mortality rate of HS diet was higher than those of LS and MS diets, but the difference was not significant ( P  > 0.05). In conclusion, the overall results suggested that the 36% cornstarch diet reduced not only the growth performance, but also body immunity. Under this experimental condition, GIFT tilapia could tolerate 18% cornstarch, but not 36% cornstarch.

The purpose of this study was to evaluate the effects of nonstarch polysaccharide (NSP) hydrolase (primarily xylanase and β‐glucanase), present in plant protein‐based diets, on growth, nutrient digestibility, and protease/amylase activity of Yellow River carp, Cyprinus carpio var.. Six hundred fish were randomly allocated to four groups in five replicates and fed diets with different NSP enzyme levels (0, 0.025, 0.05, and 0.1%) for 56 days. The addition of 0.05 and 0.1% NSP enzymes to diets significantly improved the specific growth and protein efficiency rates and reduced the feed intake and feed conversion rates (p < .05). The apparent digestibility of dry matter, crude protein, energy, crude fiber, crude ash, and some amino acids was also significantly improved with 0.05 and 0.1% NSP enzymes (p < .05). The protease activity of hepatopancreas in fish fed the diet with 0.1% NSP enzymes was significantly higher than that of the control diet (p < .05). For four sample‐collecting time points, except for 5 hr after feeding, the protease activity in the middle‐rear intestine of the 0.025% enzyme group was significantly higher than that of the control group (p < .05). Addition of 0.025 or 0.05% NSP enzymes did not affect hepatopancreas amylase activity but increased the amylase activity of the front and middle‐rear intestines to a certain extent. However, a high dose of NSP enzymes (0.1%) inhibited hepatopancreas amylase activity. Determination of the effects of NSP enzymes on growth, nutrient digestibility, and endogenous enzyme activity indicated that the addition of 0.05% NSP enzymes in diets is optimal for Yellow River carp.

The factors influencing dormancy release in lily bulbs strongly affect commercialization success, but the mechanism of dormancy release is still unclear. Magnetic resonance imaging （MRI） can detect changes in morphology and water status in a living plant bulb and aid in investigating release factors. To evaluate whether MRI could be used to detect intra-bulb metabolic changes during the dormant period in Oriental Lilies （Lilium ＇Sorbonne＇）, a series of MRI and sugar concentration measurements were performed weekly on bulbs stored for 11 weeks at 4°C. The image quality of intra-bulb structure obtained using T 1-weighted imaging was superior to that obtained using T 2 -weighted imaging and had a higher signal-to-noise ratio （0.97±0.01）. Magnetization transfer ratio values for the bud and basal plate declined during the first eight weeks of cold storage （P0.05）, and were well correlated with concentration of soluble sugar in the bud （R 2 =0.95） and basal plate （R 2 =0.93）. Thus, MRI can serve as a valuable tool for observation and analysis of dynamic morphological and metabolic changes in vivo during dormancy release. This information is potentially useful as a guide in the improvement of horticultural product quality.

Crush syndrome (CS) is a life-threatening illness in traffic accidents and earthquakes. Crush syndrome-induced acute kidney injury (CS-AKI) is considered to be mainly due to myoglobin (Mb) circulation and deposition after skeletal muscle ruptures and releases. Macrophages are the primary immune cells that fight foreign substances and play critical roles in regulating the body’s natural immune response. However, what effect does myoglobin have on macrophages and the mechanisms involved in the CS-AKI remain unclear. This study aims to look into how myoglobin affects macrophages of the CS-AKI model. C57BL/6 mice were used to construct the CS-AKI model by digital crush platform. Biochemical analysis and renal histology confirmed the successful establishment of the CS-AKI mouse model. Ferrous myoglobin was used to treat Raw264.7 macrophages to mimic the CS-AKI cell model in vitro. The macrophage polarization toward M1 type and activation of RIG-I as myoglobin sensor were verified by real-time quantitative PCR (qPCR), Western blotting (WB), and immunofluorescence (IF). Macrophage pyroptosis was observed under light microscopy. The interaction between RIG-I and caspase1 was subsequently explored by co-immunoprecipitation (Co-IP) and IF. Small interfering RNA (siRIG-I) and pyroptosis inhibitor dimethyl fumarate (DMF) were used to verify the role of macrophage polarization and pyroptosis in CS-AKI. In the kidney tissue of CS-AKI mice, macrophage infiltration and M1 type were found. We also detected that in the cell model of CS-AKI in vitro, ferrous myoglobin treatment promoted macrophages polarization to M1. Meanwhile, we observed pyroptosis, and myoglobin activated the RIG-I/Caspase1/GSDMD signaling pathway. In addition, pyroptosis inhibitor DMF not only alleviated kidney injury of CS-AKI mice but also inhibited macrophage polarization to M1 phenotype and pyroptosis via the RIG-I/Caspase1/GSDMD signaling pathway. Our research found that myoglobin promotes macrophage polarization to M1 type and pyroptosis via the RIG-I/Caspase1/GSDMD signaling pathway in CS-AKI.

Background In the past few decades, researchers have made promising progress, including the development of immune checkpoint inhibitors (ICIs) in the therapy of bladder cancer (BLCA). Existing studies mainly focus on single immune checkpoint inhibitors but lack relevant studies on the gene expression profiles of multiple immune checkpoints. Methods RNA-sequencing profiling data and clinical information of BLCA patients and normal human bladder samples were acquired from the Cancer Genome Atlas and Gene Expression Omnibus databases and analyzed to identify different expression profiles of immune checkpoint genes (ICGs) after consensus clustering analysis. Based on the 526 intersecting differentially expressed genes, the LASSO Cox regression analysis was utilized to construct the ICG signature. Results According to the expression of ICGs, BLCA patients were divided into three subtypes with different phenotypic and mechanistic characteristics. Furthermore, the developed ICG signature were independent predictors of outcome in BLCA patients, and was correlated with the immune infiltration, the expression of ICGs and chemotherapeutic effect. Conclusions This study systematically and comprehensively analyzed the expression profile of immune checkpoint genes, and established the ICG signature to investigate the differences in ICGs expression and tumor immune microenvironment, which will help risk stratification and accelerate precision medicine. Finally, we identified KRT23 as the most critical model gene, and highlighted KRT23 as a potential target to enhance immunotherapy against BLCA.

Soil salinization has become a major obstacle to global agricultural sustainability. While microbial inoculants show promise for remediation, the functional coordination between Trichoderma and PGPR in saline alkali rhizospheres requires systematic investigation. Pot studies demonstrated that while individual inoculations of Trichoderma longibrachiatum (M) or Bacillus aryabhattai (A2) moderately improved rice growth and soil properties, their co-inoculation (A2 + M) synergistically enhanced stress tolerance and nutrient availability—increasing available nitrogen (AN +28.02%), phosphorus (AP +11.55%), and potassium (AK +8.26%) more than either strain alone, while more effectively mitigating salinity (EC −5.54%) and alkalinity (pH −0.13 units). High-throughput sequencing further revealed that the A2 + M treatment reshaped the rhizosphere microbiome, uniquely enriching beneficial taxa (e.g., Actinomycetota [+9.68%], Ascomycota [+50.58%], Chytridiomycota [+152.43%]), and plant-growth-promoting genera (e.g., Sphingomonas, Trichoderma), while drastically reducing saline-alkali-adapted Basidiomycota (−87.96%). Further analysis identified soil organic matter (SOM), AN, and AP as key drivers for the enrichment of Chytridiomycota and Actinomycetota, whereas pH and EC showed positive correlations with Mortierellomycota, Aphelidiomycota, unclassified_k__Fungi, and Basidiomycota. Collectively, the co-inoculation of Trichoderma and PGPR strains enhanced soil microbiome structure and mitigated saline alkali stress in rice seedlings. These findings demonstrate the potential of microbial consortia as an effective bio-strategy for saline alkali soil amelioration.

Background Isopsoralen (IPRN), one of the active ingredients of Psoralea corylifolia Linn, has anti-inflammatory properties. We attempted to investigate the inhibitory effects of IPRN on rheumatoid arthritis (RA) and characterize its potential mechanism. Methods RA fibroblast-like synoviocytes (FLSs) and mice with collagen-induced arthritis (CIA) were used as in vitro and in vivo models to analyze the antiarthritic effect of IPRN. Histological analysis of the inflamed joints from mice with CIA was performed using microcomputed tomography (micro-CT) and hematoxylin-eosin (HE) staining. RNA sequencing (RNA-Seq), network pharmacology analysis, molecular docking, drug affinity responsive target stability (DARTS) assay, and cellular thermal shift assay (CETSA) were performed to evaluate the targets of IPRN. Results IPRN ameliorated the inflammatory phenotype of RA FLSs by inhibiting their cytokine production, migration, invasion, and proangiogenic ability. IPRN also significantly reduced the severity of CIA in mice by decreasing paw thickness, arthritis score, bone damage, and serum inflammatory cytokine levels. A mechanistic study demonstrated that macrophage migration inhibitory factor (MIF), a key protein in the inflammatory process, was the specific target by which IPRN exerted its anti-inflammatory effects in RA FLSs. Conclusion Our study demonstrates the antiarthritic effect of IPRN, which suggests the therapeutic potential of IPRN in RA.

Urban agglomerations are the main form of China’s future promotion of new urbanization development. Nevertheless, their accelerated expansion and development are increasingly threatening the security of regional ecosystems. The identification and optimization of ecological safety patterns (ESPs) is the fundamental spatial way to guarantee the ecological safety of urban circles and realize the sustainable development of the socio-economic and ecological environment. Nevertheless, from the perspective of urban green, low-carbon, and ecological restoration, regional safety evaluation still lacks a complete framework integrating ecological elements and social and natural indicators. Moreover, the evaluation method of ESPs also has a lack of judgment on the long-term change dynamics of regional landscape ecological risks and ecosystem service values. Thus, we proposed a new regional ecological security evaluation system based on ecosystem service value (ESV) and landscape ecological risk (LER), using the Wuhan urban agglomeration (WUA) as the research object. This study analyzed LER and ESV’s spatial and temporal changes over nearly 40 years from 1980 to 2020. LER and LSV were used as ecological elements combined with natural and human-social elements to jointly model the resistance surface of the landscape pattern. Applying the minimum cumulative resistance model (MCR), we identified green ecological corridors, constructed the ESPs of WUA, and proposed optimization measures. Our results show that: (1) The proportion of higher- and high-ecological-risk areas in WUA has decreased from 19.30% to 13.51% over the past 40 years. Over time, a “low–high–low” hierarchical distribution characteristic centered on Wuhan city was gradually formed in the east, south, and north; the total value of ecosystem services increased from CNY1110.998 billion to CNY1160.698 billion. The ESV was higher in the northeastern, southern, and central parts of the area. (2) This study selected 30 ecological source areas with a total area of about 14,374 km2 and constructed and identified 24 ecological corridors and 42 ecological nodes, forming a multi-level ecological network optimization pattern with intertwined points, lines, and surfaces, increasing the connectivity of the ecological network and improving the ecological security level of the study area to a large extent, which is of great significance to promote the ecological priority and green-rise strategy of WUA and the high-quality development path of the green ecological shelter.

Background Knowledge of the urinary microbiome (urobiome) in diabetic kidney disease (DKD) remains limited. The most commonly used 16S rRNA sequencing technique can only provide bacterial identification at the genus level. As a novel technique, 2bRAD sequencing for microbiome (2bRAD-M) can be used to identify the low-biomass microbiome at the species level. In this study, we used 2bRAD-M to compare the urobiome composition of patients with DKD at different stages with healthy individuals and those with type 2 diabetes mellitus (T2DM), with the expectation that we would find discriminative species correlated with DKD. Method Healthy controls, patients with DKD with microalbuminuria (DKD1 group) or macroalbuminuria (DKD2 group), and patients with T2DM were recruited (n = 20 for each group). The first-morning urine was collected for 2bRAD-M testing. The albumin-to-creatinine ratio (ACR) was also measured with urine samples. Serum samples were collected for detecting clinical indicators. The microbial diversity and composition based on abundance were calculated. Differential bacteria for different groups were identified. Besides, the correlation between discriminative bacteria and clinical indices was also analyzed. Results Urobiome diversity was significantly reduced in the DKD groups. In the DKD1 group, was the dominant genus, followed by Pseudomonas_E , whereas in the DKD2 group, Pseudomonas_E became the dominant genus and Escherichia was notably reduced. Both Bifidobacterium and Streptococcus , which were the top genera in the control group, were substantially decreased in the DKD groups. The discriminative species for DKD1 included Escherichia coli and Acinetobacter johnsonii , while for DKD2, Pseudomonas_E oleovorans , Enterococcus faecalis , and Morganella morganii were identified. Pseudomonas_E , Enterococcus and Morganella showed a strong correlation with renal function indicators and urinary protein levels. Conclusion The urobiome diversity and composition in patients with DKD were markedly different from those in healthy individuals and T2DM patients. These findings provide valuable insights into the onset and progression of DKD, driven by changes in the urinary bacterial community structure.

Transition-state (TS) characterization underpins reaction modeling but conventional DFT is costly. Machine-learning interatomic potentials (MLIPs) promise quantum-level accuracy at lower cost, yet, lacking large-scale Hessian data, most are pretrained only on energies and forces, limiting TS optimization. We present HORM, the largest quantum-chemistry Hessian dataset for reactive systems: 1.84 million matrices at the ω B97x/6-31G(d) level. To exploit second-order information efficiently, we propose Hessian-informed training with stochastic row sampling, which controls the computational overhead of incorporating Hessians. Across diverse MLIP architectures and force-learning schemes, HORM yields up to 63% lower Hessian mean absolute error and up to 200× improvement in TS-search efficiency versus counterparts trained without Hessians. HORM thus fills critical data and methodological gaps, enabling more accurate, robust reactive MLIPs and scalable exploration of reaction networks.