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Jun Yan,1– 3,* Zhongsong Man,3,* Qian Lu,1 Kuansheng Ma2 1Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Institute for Precision Medicine, Tsinghua University, Beijing, People’s Republic of China; 2The Institute of Hepatobiliary Surgery, The First Hospital Affiliated of Army Medical University, Chongqing, People’s Republic of China; 3Center of Hepatobiliary Pancreatic Disease, Xuzhou Central Hospital, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Kuansheng MaThe Institute of Hepatobiliary Surgery, The First Hospital Affiliated of Army Medical University, Chongqing, People’s Republic of ChinaEmail makuansheng@vip.sina.comQian LuBeijing Tsinghua Changgung Hospital, School of Clinical Medicine, Institute for Precision Medicine, Tsinghua University, Beijing, People’s Republic of ChinaEmail luqian01971@tsinghua.edu.cnObjective: To evaluate the survival outcomes of combined liver resection (LR) and radiofrequency ablation (RFA) on multi-focal hepatocellular carcinoma (HCC) in patients with Barcelona clinic liver cancer (BCLC) stage B.Methods: A total of 210 cases of HCC were included in this study. In 42 cases, patients were treated with combination therapy using LR and RFA (LRCRFA). In 84 cases, patients underwent transarterial chemoembolization (TACE), and in another 84 cases, patients underwent LR; both the TACE and LR groups served as controls. It both categorized as BCLC stage B for LRCRFA and TACE groups but as BCLC stage A for LR group.Results: The overall survival (OS) rate of the LRCRFA group was significantly higher than that of the TACE group (P< 0.001) but was not significantly different when compared with the LR group (P=0.544). The disease-free survival (DFS) rate of the LRCRFA group was significantly lower than that of the LR group (P=0.029). Patients with ≤ 4 tumors or those with ≤ 5 tumors no larger than 6 cm in diameter experienced better long-term outcomes than other patients in the same LRCRFA group. The OS rates and DFS rates were not significantly different from those of patients in the LR group (P> 0.05). Having more than 2 existing tumors was an independent risk factor for OS rate.Conclusion: Combination therapy using LR and RFA can more effectively improve the prognosis of these patients than TACE. Patients with BCLC stage B HCC with ≤ 4 tumors or ≤ 5 tumors smaller than 6 cm in diameter are the ideal candidates for the application of LRCRFA.Keywords: hepatocellular carcinoma, surgical resection, radiofrequency ablation, transarterial chemoembolization, survival, Barcelona clinic liver cancer stage

Abstract Abnormal angiogenesis is a key process associated with ischaemic retinopathies such as diabetic retinopathy, for which the underlying pathological mechanisms are still poorly understood. Here, we confirm that angiogenic factor 1 with a G patch and FHA domain (AGGF1) is elevated in the diabetics and induces retinal angiogenesis. Mechanistic investigations demonstrate that HIF-1α directly regulates AGGF1 expression. AGGF1 upregulates the expression of cell cycle proteins by increasing the binding of tumour necrosis factor ligand superfamily member 12 (TNFSF12) to fibroblast -growth -factor-inducible 14 (FN14, TNFRSF12A). Furthermore, targeting AGGF1 attenuates pathological neovascularisation in ischaemic retinopathy. Additionally, we discover that sodium-glucose cotransporter 2 inhibitors (SGLT2i) could inhibit the AGGF1 signalling pathway early to achieve therapeutic effects. Overall, we elucidate the mechanism underlying pathological retinal angiogenesis involved in endothelial AGGF1-dependent events and highlight a therapy for the effective treatment of ischaemic retinopathy.

Partial differential equations (PDEs) have a wide range of applications in physics and computational science. Solving PDEs numerically is usually done by first meshing the solution region with finite difference method (FDM) and then using iterative methods to obtain an approximation of the exact solution on these meshes, hence decades of research to design iterators with fast convergence properties. With the renaissance of neural networks, many scholars have considered using deep learning to speed up solving PDEs, however, these methods leave poor theoretical guarantees or sub-convergence. We build our iterator on top of the existing standard hand-crafted iterative solvers. At the operational level, for each iteration, we use a deep convolutional network to modify the current iterative result based on the historical iterative results as a way to achieve faster convergence. At the theoretical level, due to the introduced historical iterative results, our iterator is a new iterative format: Unfixed Bias Iterator. We provide sufficient theoretical guarantees and theoretically prove that our iterator can obtain correct results with convergence, as well as a better generalization. Finally, experimental results show that our iterator has a convergence speed far beyond that of other iterators and exhibits strong generalization ability.

Abstract Background The autophagy–lysosome is intricately linked to the development of gout. At present, the diagnosis and monitoring of gout are mainly invasive tests, which cannot predict the occurrence of gout in the acute phase, and bring new pain to patients. This study focuses on the changes of lysosome-related proteins in urinary exosomes of patients with acute gout attack to explore the potential noninvasive biomarkers clinical application value. Methods Urine samples were collected from the subject and exosomes were extracted. To explore the differentially expressed proteins in urinary exosomes among acute gout patients (AD group), intermittent gout patients (ID group) and normal controls (NC group) by DIA mass spectrometry. Urinary exosomal lysosome associated proteins were analyzed and receiver operating characteristic (ROC) curves of differentially expressed proteins were drawn to evaluate their clinical value in monitoring acute gout attack. Results A total of 1896 proteins were detected between AD group and ID group, of which 121 proteins were differentially expressed (FC > 1.5 and p

Abstract Background Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and acts as a major contributor to cardiovascular diseases. Advancements in lipidomics and metabolomics have unveiled the complex role of fatty acid metabolism (FAM) in both healthy and pathological states. However, the specific roles of fatty acid metabolism-related genes (FAMGs) in shaping therapeutic approaches, especially in AS, remain largely unexplored and are a subject of ongoing research. Methods This study employed advanced bioinformatics techniques to identify and validate FAMGs associated with AS. We conducted differential expression analysis on a select list of 49 candidate FAMGs. GSEA and GSVA were utilized to elucidate the potential biological roles and pathways of these FAMGs. Subsequently, Lasso regression and SVM-RFE were applied to identify key hub genes and assess the diagnostic efficacy of seven FAMGs in distinguishing AS. The study also explored the correlation between these hub FAMGs and clinical features of AS. Validation of the expression levels of the seven FAMGs was performed using datasets GSE43292 and GSE9820. Results The study pinpointed seven FAMGs with a close association to AS: ACSBG2, ELOVL4, ACSL3, CPT2, ALDH2, HSD17B10, and CPT1B. Analysis of their biological functions underscored their significant involvement in critical processes such as fatty acid metabolism, small molecule catabolism, and nucleoside bisphosphate metabolism. The diagnostic potential of these seven FAMGs in AS differentiation showed promising results. Conclusions This research has successfully identified seven key FAMGs implicated in AS, offering novel insights into the pathophysiology of the disease. These findings not only contribute to our understanding of AS but also present potential biomarkers for the disease, opening avenues for more effective monitoring and progression tracking of AS.

Chrysanthemum morifolium Ramat. is an important industrial crop with a high medicinal value, whose capitulum consists of ray and disc florets containing numerous bioactive components, such as flavonoids and phenolic acids. However, the distribution and accumulations of the bioactive metabolites in florets of Chrysanthemum morifolium were unclear. Herein, the ray and disc florets of Chrysanthemum morifolium were separated for comparing the bioactive metabolites. The contents of phenolic compounds and antioxidant activities were significantly different between the two florets. The metabolomic analysis identified 203 and 241 differential metabolites between ray and disc florets at two flowering stages. The derivatives of quercetin, isorhamnetin, tricin, and caffeoylquinic acid were enriched in the disc florets, while apigenin, kaempferol, acacetin, and their glycosides mainly accumulated in the ray florets. Besides, the results of transcriptome and qRT-PCR suggested that the F3H, F3′H, and FLS genes highly expressed in disc florets, while the FNS gene was well expressed in ray florets, which explained the different distribution of phenolic compounds between ray and disc florets. Furthermore, the expression of CmCYC2 genes was found to be significantly related to the distribution of flavones by correlation analysis. It was proved by the luciferase reporter assay that CmCYC2a and CmCYC2d factors could bind and activate the CmFNS promoter to regulate the flavones biosynthesis in ray florets. These results revealed the significant difference of metabolite contents and gene expression profile between ray and disc floret in Chrysanthemum morifolium and demonstrated that the quality of Chrysanthemum morifolium ‘Hangju’ was closely relevant to its flower morphology.

Abstract Sepsis, characterized as a systemic inflammatory response triggered by pathogen invasion, represents a continuum that may progress from mild systemic infection to severe sepsis, potentially culminating in septic shock and multiple organ dysfunction syndrome. A pivotal element in the pathogenesis and progression of sepsis involves the significant disruption of oncological metabolic networks, where cells within the pathological milieu exhibit metabolic functions that diverge from their healthy counterparts. Among these, purine metabolism plays a crucial role in nucleic acid synthesis. However, the contribution of Purine Metabolism Genes (PMGs) to the defense mechanisms against sepsis remains inadequately explored. Leveraging bioinformatics, this study aimed to identify and substantiate potential PMGs implicated in sepsis. The approach encompassed a differential expression analysis across a pool of 75 candidate PMGs. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were employed to assess the biological significance and pathways associated with these genes. Additionally, Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) methodologies were implemented to identify key hub genes and evaluate the diagnostic potential of nine selected PMGs in sepsis identification. The study also examined the correlation between these hub PMGs and related genes, with validation conducted through expression level analysis using the GSE13904 and GSE65682 datasets. The study identified twelve PMGs correlated with sepsis, namely AK9, ENTPD3, NUDT16, GMPR2, PKM, RRM2B, POLR2J, POLE3, ADCY3, ADCY4, ADSSL1, and AMPD1. Functional analysis revealed their involvement in critical processes such as purine nucleotide and ribose phosphate metabolism. The diagnostic capability of these PMGs to effectively differentiate sepsis cases underscored their potential as biomarkers. This research elucidates twelve PMGs associated with sepsis, providing valuable insights into novel biomarkers for this condition and facilitating the monitoring of its progression. These findings highlight the significance of purine metabolism in sepsis pathogenesis and open avenues for further investigation into therapeutic targets.

Hydrogels can improve the delivery of mesenchymal stromal cells (MSCs) by providing crucial biophysical cues that mimic the extracellular matrix. The differentiation of MSCs is dependent on biophysical cues like stiffness and viscoelasticity, yet conventional hydrogels cannot be dynamically altered after fabrication and implantation to actively direct differentiation. We developed a composite hydrogel, consisting of type I collagen and phase-shift emulsion, where osteogenic differentiation of MSCs can be non-invasively modulated using ultrasound. When exposed to ultrasound, the emulsion within the hydrogel was non-thermally vaporized into bubbles, which locally compacted and stiffened the collagen matrix surrounding each bubble. Bubble growth and matrix compaction were correlated, with collagen regions proximal (i.e., ≤ ∼60 μm) to the bubble displaying a 2.5-fold increase in Young's modulus compared to distal regions (i.e., > ∼60 μm). The viability and proliferation of MSCs, which were encapsulated within the composite hydrogel, were not impacted by bubble formation. In vitro and in vivo studies revealed encapsulated MSCs exhibited significantly elevated levels of RUNX2 and osteocalcin, markers of osteogenic differentiation, in collagen regions proximal to the bubble compared to distal regions. Additionally, alkaline phosphatase activity and calcium deposition were enhanced adjacent to the bubble. An opposite trend was observed for CD90, a marker of MSC stemness. Following subcutaneous implantation, bubbles persisted in the hydrogels for two weeks, which led to localized collagen alignment and increases in nuclear asymmetry. These results are a significant step toward controlling the 3D differentiation of MSCs in a non-invasive and on-demand manner.

Abstract Crohn’s disease (CD) is a chronic inflammatory bowel condition, and colon adenocarcinoma (COAD), as one of the most prevalent malignant tumors of the digestive tract, has been indicated by research to have a close association with CD. This study employs bioinformatics techniques to uncover the potential molecular links between CD and COAD. In this study, two data series related to CD were identified from the Gene Expression Omnibus (GEO) database under specific criteria, and relevant COAD gene data were obtained from The Cancer Genome Atlas (TCGA). Weighted Gene Co-expression Network Analysis (WGCNA), differentially expressed genes (DEGs), and protein-protein interaction (PPI) network analysis were conducted. A diagnostic model was established using machine learning. The accuracy of the diagnosis was validated using methods such as the construction of Receiver Operating Characteristic (ROC) curves and nomograms. Gene Set Enrichment Analysis (GSEA) was also employed to enrich the relevant pathways and biological processes. This study identified three genes through machine learning selection: DPEP1, MMP3, and MMP13. The ROC curves demonstrated that the machine learning model constructed with these three genes has a high level of accuracy, confirming their potential as biomarkers. Furthermore, GSEA elucidated that the pathways associated with these three key genes are closely related to cytokines and other factors. This study has identified key biomarker genes for CD and COAD: DPEP1, MMP3, and MMP13, providing additional molecular mechanism associations between the two diseases. It also offers more connections and pathways for reference regarding the progression of CD to COAD.

This study aimed to investigate the effects of curcumin on the expression of antioxidation-related genes in the liver and jejunum and caecum microorganisms of rabbits. A total of 160 IRA rabbits with similar body weight were randomised assigned to 4 groups. The control group received a basal diet, while the experimental groups were given diets supplemented with 50, 100, and 150 g/t curcumin, respectively. The pre-test period spanned 7 days, followed by a 21-day test period. Results revealed a significant upregulation of nuclear factor erythroid-2 related factor 2 (Nrf2) mRNA in the liver and jejunum due to curcumin (p

To develop a potential refractory for preparing Nb–Si alloy, the Nb–16Si (at.%) alloy was melted using BaZrO3 and BaZrO3/Y2O3 dual-phase crucibles through vacuum induction melting (VIM). The interfacial behavior of BaZrO3 and BaZrO3/Y2O3 dual-phase refractories against Nb–16Si alloy melts was investigated by utilizing scanning electron microscopy with energy dispersive spectroscopy (SEM/EDS) and X-ray diffraction (XRD). The results show that the improved performance of the BaZrO3/Y₂O₃ crucible can be attributed to Y replacing Zr in BaZrO3, forming a BaZr1-xYxO₃ solid solution. The Gibbs free energy of BaZr1-xYxO₃ is lower than that of BaZrO3, indicating higher thermodynamic stability. Furthermore, Y2O3 acted as a barrier, isolating BaZrO3 from the Nb–16Si melts. The dissolution of BaZrO3 was the primary mechanism of crucible erosion. The thickness of erosion layer of BaZrO3 crucible caused by Nb–16Si melts was about 186 μm, while the erosion layer of BaZrO3/Y2O3 dual-phase crucible was negligible, resulting in alloy ingots with significantly lower contamination. The BaZrO3/Y2O3 dual-phase refractory exhibited superior high-temperature stability to Nb–16Si melts compared with BaZrO3.

Abstract Background White rot fungi produce various reactive oxygen species and ligninolytic enzymes for lignocellulose deconstruction. However, their interactions during the deconstruction of lignocellulosic structural barriers for efficient enzymatic saccharification remain unclear. Results Herein, the extracellular enzyme activities and secretomic analysis revealed the sequential expression of hydroxyl radical (⋅OH) and manganese peroxidases (MnPs) for lignocellulose deconstruction by the white rot fungus Irpex lacteus. Subsequently, in vitro functional studies found that ⋅OH possessed the ability to disrupt the smooth surface structure of corn stover, resulting in increased enzymatic saccharification and cellulose accessibility. Purified recombinant MnPs from I. lacteus were able to cleave the β-O-4 bond in phenolic and non-phenolic lignin model dimers without the help of any mediators. Furthermore, the sequential pretreatment of corn stover with ⋅OH and MnP exhibited significant synergistic effects, increasing enzymatic saccharification and cellulose accessibility by 2.9-fold and 1.8-fold, respectively. Conclusions These results proved for the first time the synergistic effects of ⋅OH and MnP pretreatment in improving the enzymatic saccharification and cellulose accessibility of corn stover. These findings also demonstrated the potential application of ⋅OH and MnP pretreatment for the efficient enzymatic saccharification of corn stover. Graphical Abstract

Abstract Background The impact of diabetes on the risk of Alzheimer’s disease remains uncertain. This study aimed to explore this issue from multiple perspectives by using the Mendelian randomization (MR) approach. Methods Instrumental variables for predicting six diabetic traits (including insulin and blood glucose), eight metabolic risk factors for diabetes (including total cholesterol and blood pressure), and seven diabetic genes were extracted from their summary data. These data were derived from multiple European cohorts and included 31,684 to 810,865 subjects respectively. The two-sample MR, multivariate MR, and summary-data-based Mendelian randomization (SMR) methods were employed to determine the associations of these traits or genes with the risk of Alzheimer’s disease. Results The two-sample MR showed that elevated fasting insulin and total cholesterol levels were associated with an increased risk of dementia in Alzheimer’s disease (P = 0.022, P = 0.041). Elevated systolic and diastolic blood pressure levels were associated with a decreased risk of dementia in Alzheimer’s disease (P = 0.036, P = 0.025). The multivariate MR reported that adjusting for telomere length (a well-established biomarker of aging) did not change these findings (P

Abstract The root system plays a crucial role in water and nutrient absorption, making it a significant factor affected by nitrogen (N) availability in the soil. However, the intricate dynamics and distribution patterns of cotton (Gossypium hirsutum L.) root density and N nutrient under varying N supplies in Southern Xinjiang, China, have not been thoroughly understood. A two-year experiment (2021 and 2022) was conducted to determine the effects of five N rates (0, 150, 225, 300, and 450 kg N ha−1) on the root system, shoot growth, N uptake and distribution, and cotton yield. Compared to the N0 treatment (0 kg N ha−1), the application of N fertilizer at a rate of 300 kg N ha−1 resulted in consistent and higher seed cotton yields of 5875 kg ha−1 and 6815 kg ha−1 in 2021 and 2022, respectively. This N fertilization also led to a significant improvement in dry matter weight and N uptake by 32.4% and 53.7%, respectively. Furthermore, applying N fertilizer at a rate of 225 kg N ha−1 significantly increased root length density (RLD), root surface density (RSD), and root volume density (RVD) by 49.6–113.3%, 29.1–95.1%, and 42.2–64.4%, respectively, compared to the treatment without N fertilization (0 kg N ha−1). Notably, the roots in the 0–20 cm soil layers exhibited a stronger response to N fertilization compared to the roots distributed in the 20–40 cm soil layers. The root morphology parameters (RLD, RSD, and RVD) at specific soil depths (0–10 cm in the seedling stage, 10–25 cm in the bud stage, and 20–40 cm in the peak boll stage) were significantly associated with N uptake and seed cotton yield. Optimizing nitrogen fertilizer supply within the range of 225–300 kg N ha−1 can enhance root foraging, thereby promoting the interaction between roots and shoots and ultimately improving cotton production in arid areas.

Abstract Pampus argenteus is a highly commercial marine fish whose population is declining sharply. Here, we generated a female P. argenteus genome, spanning 536.33 Mb with contig N50 of 1.79 Mb; 24070 genes (99.50% of 24,182) were functionally annotated. To improve quality of it, we assembled a 553.79 Mb genome of male fish with contig N50 of 24.75 Mb through HiFi and ultra-long ONT sequence technologies; 550.82 Mb were anchored onto 24 gap-free chromosomes; 22,892 genes (98.1% of 23,346) were functionally annotated; the QV value was 51.55 with 98.9% of BUSCO and 99.39% coverage of Illumina reads. Finally, we compared this genome with previous published one, revealing 37,301 SVs. 52.82 Mb and 18.05 Mb SDs were characterized in our and published assemblies, respectively, and 48.96 Mb PURs were constructed. Thus, this genome assembly exhibits excellent completeness, continuity and accuracy comparing to the published one, which can be current preferred reference genome. Overall, these works help aquaculture and wild resources recovery of P. argenteus and provide a valuable genetic resource for study.

Abstract The placenta, a temporary but essential organ for gestational support, undergoes intricate morphological and functional transformations throughout gestation. However, the spatiotemporal patterns of gene expression underlying placentation remain poorly understood. Utilizing Stereo-seq, we constructed a Mouse Placentation Spatiotemporal Transcriptomic Atlas (MPSTA) spanning from embryonic day (E) 7.5 to E14.5, which includes the transcriptomes of large trophoblast cells that were not captured in previous single-cell atlases. We defined four distinct strata of the ectoplacental cone, an early heterogeneous trophectoderm structure, and elucidated the spatial trajectory of trophoblast differentiation during early postimplantation stages before E9.5. Focusing on the labyrinth region, the interface of nutrient exchange in the mouse placenta, our spatiotemporal ligand–receptor interaction analysis unveiled pivotal modulators essential for trophoblast development and placental angiogenesis. We also found that paternally expressed genes are exclusively enriched in the placenta rather than in the decidual regions, including a cluster of genes enriched in endothelial cells that may function in placental angiogenesis. At the invasion front, we identified interface-specific transcription factor regulons, such as Atf3, Jun, Junb, Stat6, Mxd1, Maff, Fos, and Irf7, involved in gestational maintenance. Additionally, we revealed that maternal high-fat diet exposure preferentially affects this interface, exacerbating inflammatory responses and disrupting angiogenic homeostasis. Collectively, our findings furnish a comprehensive, spatially resolved atlas that offers valuable insights and benchmarks for future explorations into placental morphogenesis and pathology.

Abstract Due to simultaneous horizontal and vertical displacement during vertical evacuation, the consequences of stampede congestion accidents can be more severe. Generally, pedestrians trigger a synchronization mechanism at some point during the vertical evacuation process. This synchronization behavior helps prevent stampede congestion and improves evacuation efficiency. This paper designs a well-controlled single-file vertical evacuation experiment. After the experiment, the video footage is imported into the TRACKER system to extract the coordinates of pedestrian step movements, after which the experimental data undergo calculations and visual analysis. The research findings indicate the following: Firstly, when the crowd coordinates trigger the synchronization mechanism, this behavior remains stable as long as pedestrian speed and direction are unchanged; Secondly, the variation in footstep speed over time is not directly related to the footstep synchronization rate of the crowd; Lastly, this study calculated the characteristic density value most likely to trigger the synchronization mechanism during vertical evacuation. This research deepens our understanding of crowd dynamics, reveals the characteristics of pedestrian movement during vertical evacuation, and proposes evacuation guidance strategies based on these features.

Abstract This study presents an approach that integrates compressed sensing technology with two-dimensional hyperchaotic coupled Fourier oscillator systems (2D-HCFOS) to address the challenge of slow encryption speeds in agricultural unmanned aerial vehicles (UAVs). The primary challenge in enhancing encryption speed lies in the limited capacity inherent in traditional chaotic-based systems and the computational complexity of their processes. The 2D-HCFOS utilizes a complex two-dimensional hybrid chaotic system, which significantly enhances the security of agricultural UAV image data. Notably, the image encryption process is performed on a personal computer connected to the drone, ensuring efficient processing. By integrating advanced Fourier series and nonlinear coupled oscillators, the model surpasses existing chaotic-based methods, improving both the pseudo-randomness and robustness of encryption. Additionally, incorporating Bonouille functions into the discrete cosine transform (DCT) domain results in a sparser measurement matrix, which is essential for efficient encryption on personal computers. The effectiveness of 2D-HCFOS in securely encrypting agricultural drone images has been rigorously validated through simulations and analytical evaluations using sophisticated row, rotation, and matrix encryption techniques. The improved security performance is further verified by comparative analysis. Compared with other models, the Lyapunov index of 2D-HCFOS is 15.1039, and the sample entropy is 2.4987, indicating that it possesses superior chaotic performance and encryption reliability.

Previous studies have discussed the association between serum metabolism and lactation performance among Sanhe and Holstein cows of different parities and found that the metabolic profiles of these two breeds vary differently with parity. Since the rumen is the central organ for nutrient absorption and production transformation in dairy cows, it remains unknown whether the differences observed under the same dietary conditions are related to the structure of the rumen microbiome. This study measured the apparent digestibility and rumen fermentation parameters of Sanhe cows (S1/S2/S3/S4) and Holstein cows (H1/H2/H3/H4) across four parities and generated a comprehensive rumen microbiome dataset using high-throughput sequencing technology. Significant differences in dry matter digestibility (p = 0.001) and ammonia nitrogen (p = 0.024) were observed among the S groups, with higher trends of various VFA contents in S1 (0.05 , Neocallimastix, and Piromyces were more abundant in S1, H1, and H2, and pathways such as autophagy-animal, plant-pathogen interaction, and endocytosis were significantly enriched in these parities. Multiparous Sanhe cows had higher abundances of ATP-binding cassette transporters pathways. Additionally, CAZymes such as GH84 and GH37 were significantly associated with differential physiological indicators and milk traits. In conclusion, this study reveals the complex relationship between rumen microbiota and metabolic characteristics in Sanhe and Holstein cows of different parities, indicating that changes in the structure of the rumen microbiome may be key factors affecting lactation performance and metabolic differences in dairy cows.

BackgroundCardiorespiratory health issues often intersect. This study explored the relationship between lung health and the recently updated Cardiovascular Health Measure (Life’s Essential 8).MethodsData from the 2007–2018 National Health and Nutrition Examination Survey (NHANES) were analyzed. Three cohorts were included: lung disease in the Main cohort (N = 9,772), lung function in the Spirometry sub-cohort (N = 3,896), and respiratory symptoms in the Respiratory Symptoms sub-cohort (Age > 40) (N = 3,449). LE8 scores were used as both continuous and categorical variables (0–49, 50–79, 80–100). Weighted multivariate regression analyses examined the correlations between LE8 and lung health, and weighted restricted cubic spline (RCS) regression analyzed potential non-linear relationships. Subgroup analysis was conducted to verify stability.ResultsOverall lung health was better in the high LE8 group than in the low LE8 group. In the fully adjusted model, the high LE8 group had significantly lower odds of asthma (OR = 0.42; 95% CI = 0.29, 0.59) and chronic bronchitis (OR = 0.27; 95% CI = 0.15, 0.49) compared to the low LE8 group. Regarding lung function, each 10-point increase in LE8 was associated with an increase of 50 ml in FEV1 (Beta = 50; 95% CI = 32, 67) and 56 ml in FVC (Beta = 56; 95% CI = 32, 79). Among middle-aged and older adults (age > 40), the high LE8 group had significantly lower odds of respiratory symptoms, including cough (OR = 0.23; 95% CI = 0.12, 0.46), phlegm (OR = 0.42; 95% CI = 0.19, 0.90), and wheezing (OR = 0.29; 95% CI = 0.15, 0.54). RCS analyses demonstrated a non-linear negative correlation between LE8 and cough, sputum, and wheeze. Subgroup and sensitivity analysis suggested stability.ConclusionLife’s Essential 8 (LE8) scores are positively associated with lung health in the US population. These findings provide a valuable reference for maintaining overall cardiorespiratory health.

IntroductionThere are few studies on the effect of rumen fluid transplantation on the fecal flora of yaks. Yak fecal flora is closely related to their health. This study aimed to evaluate the effects of rumen fluid transplantation on growth performance and fecal flora indicators.MethodsTwenty 6-month healthy male yaks (weight: 57.20 ± 7.80 kg) were selected from grazing yaks in an alpine meadow pasture at an altitude of approximately 3,400 m. They were then transferred to a farm and randomly divided into a control group (CON; n = 10) and a rumen fluid transplantation group (RT; n = 10). Separate single-pen rearing was performed in two pens using the same rearing environment and feeding method, and all yaks were earmarked for identification. In addition, 10 yaks that had been adapted to stall fattening feed in 1 month were selected as the rumen fluid donor group to provide fresh rumen fluid. Ruminal fluid transplantation trials were conducted on the 1st, 3rd, and 5th weeks. Overall, 1 L of ruminal fluid was transplanted to each yak in the RT and CON groups. The formal trial then began with both groups fed the same diet. After this, yak feed intake was recorded daily; yaks were weighed on days 1, 30, and 60 of the formal trial; and yak feces were collected directly from the ground on days 1, 4, 7, 14, 30, and 60 to compare the microbial composition of the feces using 16S rRNA sequencing data.ResultsThe results showed that rumen fluid transplantation significantly increased the alpha diversity of fecal microflora (P < 0.05), and on day 30 of the experiment, both the operational taxonomic unit (OTU) and Shannon index were significantly higher in the RT group than the CON group (P < 0.05). In the principal coordinate analysis (PCoA) plot, the intestinal flora of the RT group was significantly different (P < 0.05) on days 1–7 but not significantly different after day 14. In contrast, the intestinal flora of the CON group was significantly different (P < 0.05) on days 1–14 but not significantly different after day 30. Compared with the CON group, the relative abundance of Firmicutes in the RT group was significantly lower on days 1, 4, 7, and 14 (P < 0.05); the relative abundance of Bacteroidetes in the RT group was significantly higher on days 1, 4, 14, and 30 and significantly lower on day 7 (P < 0.05); the relative abundance of Tenericutes in the RT group was significantly higher on day 30 (P < 0.05); the relative abundance of Actinobacteria in the RT group was significantly higher on day 60 (P < 0.05); the relative abundance of Ruminococcaceae_UCG-005 in the RT group was significantly lower on days 4, 7, 14, and 60 (P < 0.05); the relative abundance of Unidentified in the RT group was significantly higher on days 1, 4, and 7 days (P < 0.05); and the relative abundance of Rikenellaceae_RC9_gut_group, Bacteroides, and Christensenellaceae_R-7_group in the RT group was significantly higher on day 1 (P < 0.05). Moreover, Actinobacteria was positively correlated with ADG and negatively correlated with DMI; Tenericutes was positively correlated with weight and negatively correlated with F/G. Metabolism of terpenes and polyketones, metabolism of other amino acids, and energy metabolism were higher in the RT group than in the CON group. LEfSe analysis showed that 32 species were more abundant in the RT group and 11 in the CON group. In conclusion, our findings suggest that rumen fluid transplantation improved the stability of the intestinal tract of yaks, improved the immunity of yaks, and reduced the occurrence of intestinal diseases; rumen fluid transplantation remodeled the structure of the intestinal flora, shortened the time of remodeling the intestinal flora of yaks during the transition period, and accelerated yak adaptation to digest housed rations, reducing the DMI. The findings of this study provide new insights into yak microbial community transplantation and a reference for improving feed efficiency in the yak industry.

ObjectiveGlucose metabolism is the main way in which cells obtain energy during exercise and plays an important role in exercise. The purpose of this study was to explore the changes in the expression of glucose metabolism-related proteins in urine after running, and finally applied to the monitoring of running training.MethodsUrine samples were collected before and after running, and urine proteomics information was collected to explore the expression of proteins in the urine using LC-MS/MS in DDA mode and DIA mode. Receiver operating characteristic (ROC) curve was drawn to evaluate the value of target proteins in monitoring running training.ResultsA total of 140 proteins were identified using LC-MS/MS in DDA mode, of which 49 urine proteins showed increased expression after running. KEGG analysis revealed that glucose metabolism-related proteins are mainly concentrated in glycolysis. There were six glycolysis-related proteins, among which urine proteins PKM, TPI1, ENO1 and LDHB were significantly increased after running (P < 0.05). This changes in urine proteins PKM, TPI1, ENO1 and LDHB were further verified by the results of LC-MS/MS in DIA mode. The concentrations of the urine proteins TPI1, ENO1 and LDHB showed a significant linear relationship with PKM. ROC curve analysis showed that PKM, TPI1, ENO1 and LDHB proteins in urine had good monitoring values for running training.ConclusionThe expression of glycolysis-related proteins PKM, TPI1, ENO1 and LDHB in urine was significantly increased after running, which may be applied to the monitoring of running training.

IntroductionAstragali Radix is the dried root of Astragalus mongoliae or Astragalus membranaceus, a leguminous plant. Since ancient times, Astragali Radix has been widely used in Chinese traditional Chinese medicine. As people become more health-conscious, the market demand for Astragali Radix grows and its popularity is increasing in the international market. As an important medicinal plant, the growth of Astragali Radix is strongly influenced by environmental conditions. In order to meet the market demand for high quality Astragali Radix herbs, it is necessary to search and find areas suitable for the growth of Astragali Radix.MethodsIn this study, we assessed the potential impacts of climate change on the distribution of the Chinese medicinal plant Astragali Radix using the maximum entropy (MaxEnt) model in combination with a geographic information system(GIS). Distribution data and environmental variables were analyzed to predict suitable areas for Astragali Radix under the SSP126, SSP245 and SSP585 scenario for current and future (2041-2060, 2061-2080, 2081-2100). Jackknife is used to assess the importance of environmental variables, and environmental variables with a model contribution greater than 5% were considered to be the main drivers.ResultsThe results showed that the current area of suitable area for Astragali Radix is 188.41 km2, and the three climate scenarios show an increasing trend in the future, with a maximum of 212.70 km2. North China has always been the main suitable area, while the area of suitable area in Southwest China is decreasing, and Xinjiang will be developed as a new suitable area in the future. Annual precipitation (41.6%), elevation (15.9%), topsoil calcium carbonate (14.8%), annual mean temperature (8.3%), precipitation seasonality (8%) and topsoil pH (6%) contributed more to the model and were the main environmental influences on the distribution of Astragali Radix. In addition, the centroids of the suitable areas shifted northward under all three climate scenarios, indicating a migratory response to global warming.DiscussionOur study found that suitable area of Astragali Radix has been expanding for most of the time in each period of the three climate scenarios compared with the current situation. In the future, humans can focus on enhancing the cultivation techniques of Astragali Radix in these suitable areas. This study provide a scientific basis for the development of planting strategies and spatial distribution management of Astragali Radix. It helps to optimize the selection of planting areas and resource conservation of Chinese herbs.

Climate change is expected to increase the frequency and severity of climate extremes, which will negatively impact crop production. As one of the main food and feed crops, maize is also vulnerable to extreme climate events. In order to accurately and comprehensively assess the future climate risk to maize, it is urgent to project and evaluate the stress of extreme climate related maize production under future climate scenarios. In this study, we comprehensively evaluated the spatio-temporal changes in the frequency and intensity of six extreme climate indices (ECIs) across China’s maize harvest region by using a multi-model ensemble method, and examined the capability of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to capture these variations. We found that the Independence Weight Mean (IWM) ensemble results calculated by multiple Global Climate Models (GCMs) with bias correction could better reproduce each ECI. The results indicated that heat stress for maize showed consistent increase trends under four future climate scenarios in the 21st century. The intensity and frequency of the three extreme temperature indices in 2080s were significantly higher than these in 2040s, and in the high emission scenario were significantly higher than these in the low emission scenario. The three extreme precipitation indices changed slightly in the future, but the spatial changes were more significant. Therefore, with the uncertainty of climate change and the differences of climate characteristics in different regions, the optimization of specific management measures should be considered in combination with the specific conditions of future local climate change.

Maize growth parameters are key pieces of information describing the growth, development and yield of plants, and they are of great significance for high quality and high yield maize breeding. Plants counting, row spacing, and plant spacing are closely related to maize sowing quality and yield. Plant height is closely related to maize photosynthetic rate and biomass. The main problem with measuring phenotypic parameters during the maize seedling stage is that maize plants are small, making it difficult to segment maize plant point clouds from ground point clouds, and there is a lack of automatic methods for measuring growth parameters. A point cloud intensity segmentation and improved Euclidean clustering method for single plant segmentation was proposed based on terrestrial laser scanning (TLS) technical, and an automatic measuring method of growth parameters of maize seedling stage was realized. First, TLS was used to scan maize plants at two planting densities at V1 (first leaf is fully expanded) and V2 (second leaf is fully expanded) stages. Second, the segmentation based on point cloud intensity method and the improved Euclidean clustering single plant segmentation method were used to achieve the segmentation of a single maize plant. Finally, the automatic measurement of maize plants counting, row spacing, plant spacing, and plant height were realized. When plants counting of maize, the percentage error was lower than 1.70%. In the measurement of row spacing, plant spacing and plant height of maize plants, the mean absolute percentage error (MAPE) were lower than 1.50%, 5.50% and 3.10%, respectively. These results demonstrate that the point cloud intensity segmentation and growth parameters measurement method is feasible for maize V1 and V2 stages and different planting densities. The automatic measurement values of the number of maize plants, row spacing, plant spacing and plant height has high measurement accuracy and small error. This study provides a rapid, automatic and accurate measurement method for researchers to measure maize growth parameters.

Histotripsy is the first noninvasive, non-ionizing, and non-thermal ablation technique that mechanically fractionates target tissue into acellular homogenate via controlled acoustic cavitation. Histotripsy has been evaluated for various preclinical applications requiring noninvasive tissue removal including cancer, brain surgery, blood clot and hematoma liquefaction, and correction of neonatal congenital heart defects. Promising preclinical results including local tumor suppression, improved survival outcomes, local and systemic anti-tumor immune responses, and histotripsy-induced abscopal effects have been reported in various animal tumor models. Histotripsy is also being investigated in veterinary patients with spontaneously arising tumors. Research is underway to combine histotripsy with immunotherapy and chemotherapy to improve therapeutic outcomes. In addition to preclinical cancer research, human clinical trials are ongoing for the treatment of liver tumors and renal tumors. Histotripsy has been recently approved by the FDA for noninvasive treatment of liver tumors. This review highlights key learnings from in vivo shock-scattering histotripsy, intrinsic threshold histotripsy, and boiling histotripsy cancer studies treating cancers of different anatomic locations and discusses the major considerations in planning in vivo histotripsy studies regarding instrumentation, tumor model, study design, treatment dose, and post-treatment tumor monitoring.

Hemolysis is associated with thrombosis and vascular dysfunction, which are the pathological components of many diseases. Hemolytic products, including hemoglobin and hemin, activate platelets (PLT). Despite its activation, the effect of hemolysis on platelet clearance remains unclear, It is critical to maintain a normal platelet count and ensure that circulating platelets are functionally viable. In this study, we used hemin, a degradation product of hemoglobin, as a potent agonist to treat platelets and simulate changes in vivo in mice. Hemin treatment induced activation and morphological changes in platelets, including an increase in intracellular Ca2+ levels, phosphatidylserine (PS) exposure, and cytoskeletal rearrangement. Fewer hemin-treated platelets were cleared by macrophages in the liver after transfusion than untreated platelets. Hemin bound to glycoprotein Ibα (GPIbα), the surface receptor in hemin-induced platelet activation and aggregation. Furthermore, hemin decreased GPIbα desialylation, as evidenced by reduced Ricinus communis agglutinin I (RCA- I) binding, which likely extended the lifetime of such platelets in vivo. These data provided new insight into the mechanisms of GPIbα-mediated platelet activation and clearance in hemolytic disease.

By using multi⁃scales method,the first primary resonance of the human arm and vibration mechanical coupling system under random narrow⁃band excitation was analyzed,and the two⁃degree⁃of⁃freedom nonlinear dynamic equation of the arm system was established.The first primary resonance amplitude frequency response equation and Ito stochastic differential equation of the system were solved in turn.In order to study the distribution law of variables under random vibration,the approximate expressions of the expectation and mean square value of the first primary resonance random mean square response were calculated using the moment estimation method.The influence of the parameters of the human arm system on the primary resonance was obtained through numerical analysis.The results show that the mean square response curves of the first primary resonance have the same topological structure as their amplitude⁃frequency response curves,and the mean square value of the primary resonance amplitudes and the resonance region increase with the increase of the amplitude of the external excitation,while the increase of the system damping will reduce the mean square value and the resonance region.The change of nonlinear stiffness coefficient has little effect on the system.

Aiming at the problems such as lack of specific algorithms for process implementation, using public keys in most of the solutions, low efficiency in dealing with large-scale data sets, and lack of applicability, a unilateral shuffling protocol was proposed, and on this basis, a shuffling protocol based on additive secret sharing was designed. The share conversion algorithm was constructed through the casual transfer protocol, and the shuffling was completed without exposing the original data set. The shuffling task was decomposed into multiple sub-tasks by the Benes arrangement network, which improved the efficiency of large-scale data sets. Finally, through the additive secret sharing, the shuffling shares were safely distributed to the participants. The correctness of the proposed shuffling protocol was analyzed strictly, and its security property was evaluated by using an ideal-reality simulation paradigm. Compared with the existing literature, the proposed protocol can meet the current security standards in security, and has high efficiency in processing large-scale data sets. It improves the applicability of the protocol and further promotes its application in the current environment.

Abstract This study explores the association between LE8 scores and mortality risks among individuals diagnosed with cardiovascular disease (CVD). Utilizing data from the NHANES conducted between 2005 and 2018, survey-weighted multivariable Cox proportional hazards regression models were utilized. Life’s Essential 8 (LE8) scores dose–response associations were assessed using restricted cubic spline regression. Sub-analyses were performed for different categories of CVD. The study consisted of 2164 participants diagnosed with CVD, ranging in age from 20 to 80 years (weighted mean [SE] age, 61.47 [0.34] years; The average total LE8 was 64.97 [0.54]. 499 participants experienced mortality, with 350 deaths attributed to CVD. After accounting for potential covariates, LE8 score was found to be associated with a decreased both all-cause mortality (OR 0.34, CI 0.22–0.51) and CVD mortality (OR 0.40, CI 0.23–0.68). A survey-weighted multivariable Cox model with restricted cubic splines identified the lowest all-cause mortality (P

Abstract Clarification of the cytotoxic function of T cells is crucial for understanding human immune responses and immunotherapy procedures. Here, we report a high-throughput Bessel oblique plane microscopy (HBOPM) platform capable of 3D live imaging and phenotyping of chimeric antigen receptor (CAR)-modified T-cell cytotoxicity against cancer cells. The HBOPM platform has the following characteristics: an isotropic subcellular resolution of 320 nm, large-scale scouting over 400 interacting cell pairs, long-term observation across 5 hours, and quantitative analysis of the Terabyte-scale 3D, multichannel, time-lapse image datasets. Using this advanced microscopy platform, several key subcellular events in CAR-T cells are captured and comprehensively analyzed; these events include the instantaneous formation of immune synapses and the sustained changes in the microtubing morphology. Furthermore, we identify the actin retrograde flow speed, the actin depletion coefficient, the microtubule polarization and the contact area of the CAR-T/target cell conjugates as essential parameters strongly correlated with CAR-T-cell cytotoxic function. Our approach will be useful for establishing criteria for quantifying T-cell function in individual patients for all T-cell-based immunotherapies.