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Abstract Background Hyperuricemia is considered as an independent risk factor for acute ischemic stroke (AIS), and some AIS patients are accompanied by an increase in serum uric acid. Recent studies have highlighted the important role of gut microbiota in both hyperuricemia and AIS, but there is little available data on the relationship between gut microbiota and the pathogenesis of AIS with hyperuricemia (HAS). Methods Here we profiled the gut microbiota composition in 63 HAS patients and 269 non-HAS patients through 16s rRNA sequencing. Male rat with hyperuricemia were subjected to middle cerebral artery occlusion (MCAO) to establish HAS model and were then treated with Parabacteroides distasonis. Subsequently, the neurological deficit, pathological damages and blood-brain barrier disruption were evaluated. Moreover, the levels of ROS, inflammatory cytokines, NF-𝜿B pathway related protein, and vascular density markers were determined. Results There were significant differences of gut microbiota composition between HAS patients and non-HAS patients, and a significant decrease in the abundance of Parabacteroides in HAS patients compared to non-HAS patients. Animal experiments showed that supplementation with P. distasonis increased beneficial commensal bacteria, significantly improved neurological deficits, pathological damages and BBB disruption, as well as reduced the level of serum uric acid in HAS rats. We further demonstrated that P. distasonis treatment decreased ROS level and increased SOD2 level, thereby reducing oxidative stress. Meanwhile, P. distasonis effectively inhibited NF-𝜿B signal pathway and reduced the production of inflammatory cytokines, including TNF-α and IL-1β, alleviating the inflammatory response. Notably, P. distasonis treatment increased the levels of vascular density markers including cluster of differentiation 31 (CD31) and alpha-smooth muscle actin (α-SMA), ameliorating vascular damage in HAS rats. Conclusions Together, these findings highlighted the important role of P. distasonis in the pathogenesis of HAS, and its mechanism was involved in the regulation of gut microbiota-gut-brain axis, which implied a novel strategy against HAS.

Abstract Osteosarcoma (OS) is a highly aggressive malignant tumor with a high rate of disability and mortality rates, and dysregulated autophagy is a crucial factor in cancer. However, the molecular mechanisms that regulate autophagy in OS remain unclear. This study aimed to explore key molecules that affect autophagy in OS and their regulatory mechanisms. We found that fatty acid synthase (FASN) was significantly increased in activated autophagy models of OS and promoted OS proliferation in an autophagy-dependent manner, as detected by LC3 double-labeled fluorescence confocal microscopy, western blotting, transmission electron microscopy (TEM), and cell functional experiments. Furthermore, co-immunoprecipitation combined with mass spectrometry (Co-IP/MS), ubiquitination modification, molecular docking, and protein truncation methods were used to identify FASN-interacting proteins and analyze their effects on OS. Valosin-containing protein (VCP) enhanced the FASN stability by recruiting ubiquitin specific peptidase-2 (USP2) to remove the K48-linked ubiquitin chains from FASN; domain 2 of VCP and the amino acid sequence () of USP2 were critical for their interactions. Gain- and loss-of-function experiments showed that the inhibition of FASN or USP2 attenuated the stimulatory effect of VCP overexpression on autophagy and the malignant phenotypes of OS cells in vitro and in vivo. Notably, micro-CT indicated that VCP induced severe bone destruction in nude mice, which was abrogated by FASN or USP2 downregulation. In summary, VCP recruits USP2 to stabilize FASN by deubiquitylation, thereby activating autophagy and promoting OS progression. The identification of the VCP/USP2/FASN axis, which mediates autophagy regulation, provides important insights into the underlying mechanisms of OS and offers potential diagnostic and therapeutic strategies for patients with OS.

Abstract A multiscale regulation strategy has been demonstrated for synthetic energy storage enhancement in a tetragonal tungsten bronze structure ferroelectric. Grain refining and second-phase precipitation (perovskite phase) are introduced in the BaSrTiNb2-xTaxO9 ceramics by regulating the composition and sintering process. Disordered polarization and distribution, chemical inhomogeneity, and insulating boundary layers are achieved to provide the fundamental structural origin of the relaxation characteristic, high breakdown strength, and superior energy storage performance. Thus, an ultrahigh energy storage density of 12.2 J cm−3 with an low energy consumption was achieved at an electric field of 950 kV cm−1. This is the highest known energy storage performance in tetragonal tungsten bronze-based ferroelectric. Notably, this ceramic shows remarkable stability over frequency, temperature, and cycling electric fields. This work brings new material candidates and structure design for developing of energy storage capacitors apart from the predominant perovskite ferroelectric ceramics.

Background: Spinal cord injuries (SCIs) trigger a cascade of detrimental processes, encompassing neuroinflammation and oxidative stress (OS), ultimately leading to neuronal damage. Phillygenin (PHI), isolated from forsythia, is used in a number of biomedical applications, and is known to exhibit anti-neuroinflammation activity. In this study, we investigated the role and mechanistic ability of PHI in the activation of microglia-mediated neuroinflammation and subsequent neuronal apoptosis following SCI. Methods: A rat model of SCI was used to investigate the impact of PHI on inflammation, axonal regeneration, neuronal apoptosis, and the restoration of motor function. In vitro, neuroinflammation models were induced by stimulating microglia with lipopolysaccharide (LPS); then, we investigated the influence of PHI on pro-inflammatory mediator release in LPS-treated microglia along with the underlying mechanisms. Finally, we established a co-culture system, featuring microglia and VSC 4.1 cells, to investigate the role of PHI in the activation of microglia-mediated neuronal apoptosis. Results: In vivo, PHI significantly inhibited the inflammatory response and neuronal apoptosis while enhancing axonal regeneration and improving motor function recovery. In vitro, PHI inhibited the release of inflammation-related factors from polarized BV2 cells in a dose-dependent manner. The online Swiss Target Prediction database predicted that toll-like receptor 4 (TLR4) was the target protein for PHI. In addition, Molecular Operating Environment software was used to perform molecular docking for PHI with the TLR4 protein; this resulted in a binding energy interaction of −6.7 kcal/mol. PHI inhibited microglia-mediated neuroinflammation, the production of reactive oxygen species (ROS), and activity of the NF-κb signaling pathway. PHI also increased mitochondrial membrane potential (MMP) in VSC 4.1 neuronal cells. In BV2 cells, PHI attenuated the overexpression of TLR4-induced microglial polarization and significantly suppressed the release of inflammatory cytokines. Conclusion: PHI ameliorated SCI-induced neuroinflammation by modulating the TLR4/MYD88/NF-κB signaling pathway. PHI has the potential to be administered as a treatment for SCI and represents a novel candidate drug for addressing neuroinflammation mediated by microglial cells. The translational potential of this article: We demonstrated that PHI is a potential drug candidate for the therapeutic management of SCI with promising developmental and translational applications.

Investigating the effect of steel fiber blending schemes on the dynamic mechanical properties and damage evolution of concrete is crucial for deep-shaft construction projects. Dynamic impact tests were conducted on steel fiber concrete specimens with varying mixing schemes and grades, according to the settings of the ultra-deep shaft-lining support project of a mine in Yunnan Province. The evolution of strain fields on the specimen surfaces under impact loads was analyzed using digital image correlation techniques. The steel fiber mixing schemes were as follows: single mixing, in which 55 kg of end-hook long fibers were added per cubic meter of concrete; double mixing, which involved the addition of 15 kg of end-hook long fibers and 40 kg of short copper-plated straight fibers per cubic meter of concrete; and triple mixing, which involved the addition of 40 kg of end-hook long fibers, 5 kg of copper-plated straight medium-length fibers, and 10 kg of short copper-plated straight fibers per cubic meter of concrete. The test results indicated that the dynamic compressive strength and dissipated energy ratio of the triple-mixed steel fiber concrete specimens were greater than those of the single- and double-mixed steel fiber concrete specimens. The smaller dynamic strength of plain concrete, the more pronounced the enhancement in the dynamic strength observed in concrete specimens with a steel fiber admixture. A high-speed camera was used to record the complete failure process of the steel fiber concrete specimens. The camera revealed that the failure mode was influenced by the concrete grade and steel fiber mixing scheme. The observed failure modes included shear, splitting, and shear-splitting failures. Compared with plain concrete specimens, steel fiber concrete specimens exhibited fewer cracks, a lower percentage of reflected energy, and higher percentages of transmitted and dissipated energy under impact loading. This indicates that the steel fibers effectively inhibited crack initiation and propagation, thereby enhancing the stability of the shaft wall concrete. Non-destructive impact tests on steel fiber concrete specimens showed that the triple-mixed steel fiber scheme inhibited concrete damage under impact loading to the maximum extent. It is recommended that the lining support for the deep shaft of the mine be constructed using grade C50 concrete with steel fibers mixed with 40 kg of end-hooked long fibers, 5 kg of copper-plated straight medium-length fibers, and 10 kg of short copper-plated straight fibers per cubic meter of concrete.

Ground losses due to tunneling would induce settlement of nearby raft foundations. To study the change in behavior of the raft foundations over time due to tunnel excavation in soft clay, a series of centrifuge model tests were conducted. The results reveal that the raft stiffness has a significant influence on the development of the gap between the raft and the ground. The width of the gap beneath the flexible foundation would increase over time, leading to a further increase in tensile strain after excavation, whereas the gap for raft foundations with a large stiffness would reduce with time, causing a gradual decrease in tensile strain. The modification factor (MF) design approach is also evaluated with the test results and demonstrates that the MF design approach would underestimate the tensile strain of the flexible raft and provide a relatively conservative prediction for larger stiffnesses.

Abstract Metal implants play a significant role in orthopedics, commonly used for treating fractures, joint replacement surgeries, spinal procedures, and more. Chromium (Cr), crucial in these implants, may raises health concerns. However, the relationship between metal implants and urine Cr levels remains uncertain. We aimed to evaluate this relationship. We conducted a cross-sectional study on 1419 individuals aged 40 years or older using data from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2017 to 2020. Multivariate linear regression models and subgroup analysis were applied to assess associations between metal implants and urine Cr levels. Among the 1419 participants, 402 [28.3%] self-reported having metal objects in their bodies. After adjusting for potential confounding factors, metal implants were positively correlated with the accumulation of urine Cr (β = 0.41, 95% CI 0.04–0.77, p = 0.028). However, the positive correlation of metal implants with urine Cr was only present in females (β = 0.81, 95% CI 0.08–1.53, p = 0.029), but not in males. Our study revealed higher urine Cr levels in individuals with metal implants, with noticeable gender differences. Additionally, those with metal implants exhibited a more pronounced elevation in urine Cr levels with increasing age compared to individuals without implants.

Abstract Intangible cultural heritage is the carrier of national memory and a historical witness. Exploring the spatial distribution and chronological evolution of intangible cultural heritage is of great significance to understand the cultural integrity and historical continuity. Taking the intangible cultural heritage along the Grand Canal as an example, this study carries out spatial deconstruction based on the extent of the spread of intangible cultural heritage and reveales the aggregation pattern through spatial autocorrelation analysis. Then, the historical process and the spatial center of gravity are shown through an evolution tree model. The influencing factors are illustrated via the methods of Geodetector and qualitative analysis. The results are as follows: (1) The two ends of the canal exhibit obvious advantages in the number of intangible cultural heritage items; however, the existence of a spatial mismatch at the city–county level makes the southern endpoint occupy a dominant position. (2) Although there is a high–high aggregation pattern along the whole canal, 29.82% of the counties are distributed widely with low–low aggregation. (3) The spatial center of intangible cultural heritage items from different historical periods generally presents a changing path from north to south and returning north. (4) Intangible cultural heritage items are mainly distributed in areas with a prosperous culture, a high level of economic development, and strong policy and financial support from government. Changes in the natural environment, population migration, economic development, war disasters, and canal shipping have profound impacts over time. This study provides a new idea for the methodological advancement of spatial distribution of intangible cultural heritage, as well as studies on local cultural identity and regional consistency.

Lightweight refractory high-entropy alloy (LRHEA) is one of potential structural materials in aerospace industry for its excellent high-temperature comprehensive properties and low density. In this work, a new high-throughput method to develop LRHEAs was proposed. The equimolar HfNbTaTiZr alloy was immersed with melting pure aluminum for a given time, and a thick layer with composition gradient was obtained. Further characterizations of the layer result in relations between composition and nanohardness or Young's modulus, which facilitate the selection of the optimal composition with desired properties. Finally, three LRHEAs were designed and casted into bulk samples with arc-melting method. The alloys show superhigh Vickers hardness of 8.29–9.56 GPa and low densities of 6.27–7.08 g/cm3, showing great potentials in applications as wear-resistant materials. The high-throughput method developed here may also accelerate the development of new LRHEAs.

In order to explore the energy evolution law and damage evolution characteristics of coal and rock mass in the process of deformation and failure under different water content, the uniaxial compression test of coal and rock mass in Shuangma No.1 Coal Mine under different water content conditions was carried out. Based on the principle of energy calculation and minimum energy consumption, the energy dissipation characteristics and damage evolution mechanism of coal and rock mass under different water content were analyzed. The results show that the mechanical properties of coal and rock mass under different water content are different, and the peak strain are positive correlated with water content, compressive strength and elastic modulus are negatively correlated with water content. The higher the water content of the coal and rock mass, the smaller the elastic strain energy at the peak value and the total strain energy absorbed by the failure, and the higher the proportion of the dissipated energy to the total strain energy. The damage constitutive model based on the principle of minimum energy consumption shows that the damage threshold value gradually decreases with the increase of water content of coal and rock mass. In the dry state, the damage variables of coal and rock mass at the peak stress are 0.36 and 0.28, respectively.When the water content increases to the natural state, the damage variables of coal and rock mass at the peak stress decrease by 0.09 and 0.18, respectively.However, when the water content increases to the saturated state, the damage variables of coal and rock mass at the peak stress increase by 0.102 and 0.49, respectively, showing a trend of decreasing first and then increasing.The evolution model of damage strain energy release rate of coal rock with different water content is further established. The maximum damage strain energy release rate of low water content coal rock is significantly lower than that of dry coal rock, and the decrease is 45.61% and 31.29% respectively. With the increase of water content to saturated state, the maximum damage strain energy release rate changes gently, which is 3.08% and 8.80% respectively, indicating that the damage severity of coal rock does not increase significantly.

IntroductionNumerous studies have reported alterations in the composition of gut microbiota in patients with acute ischemic stroke (AIS), with changes becoming more pronounced as the disease progresses. However, the association between the progression of transient ischemic attack (TIA) and AIS remains unclear. This study aims to elucidate the microbial differences among TIA, AIS, and healthy controls (HC) while exploring the associations between disease progression and gut microbiota.MethodsFecal samples were collected from acute TIA patients (n = 28), AIS patients (n = 235), and healthy controls (n = 75) and analyzed using 16 s rRNA gene sequencing. We determined characteristic microbiota through linear discriminant analysis effect size and used the receiver operating characteristic (ROC) curve to assess their predictive value as diagnostic biomarkers.ResultsOur results showed significant gut microbial differences among the TIA, AIS, and HC groups. Patients with AIS exhibited higher abundances of Lactobacillus and Streptococcus, along with lower abundances of Butyricicoccaceae and Lachnospiraceae_UCG-004. Further analysis revealed that the abundance of characteristic bacteria, such as Lactobacillus and Streptococcus, was negatively correlated with HDL levels, while Lactobacillus was positively correlated with risk factors such as homocysteine (Hcy). In contrast, the abundance of Lachnospiraceae_UCG-004 was negatively correlated with both Hcy and D-dimer levels. ROC models based on the characteristic bacteria Streptococcus and Lactobacillus effectively distinguished TIA from AIS, yielding areas under the curve of 0.699 and 0.626, respectively.ConclusionWe identified distinct changes in gut bacteria associated with the progression from TIA to AIS and highlighted specific characteristic bacteria as predictive biomarkers. Overall, our findings may promote the development of microbiome-oriented diagnostic methods for the early detection of AIS.

Summary: Gut microbiota plays a crucial role in the pathogenesis of Alzheimer disease (AD). Here, we found that AD patients had significantly lower abundance of Agathobacter, which were negatively correlated with cognitive impairment. Animal experiments showed that Agathobacter rectalis (A. rectalis) supplementation increased beneficial commensal bacteria, significantly improved pathological damage, and suppressed microglial activation in APP/PS1 mice. We further demonstrated that butyric acid, a metabolite of A. rectalis, reduced microglial activation and pro-inflammatory factor production via Akt/ nuclear factor κB (NF-κB) signal pathway in vitro. Meanwhile, we revealed that A. rectalis effectively inhibited activation of microglia in the APP/PS1 mice by regulating Akt/ NF-κB pathway. This finding highlights the role of A. rectalis and its metabolite butyrate in mitigating neuroinflammation in AD by modulating the Akt/NF-κB pathway.

Abstract Seasonal variability could have an impact on the incidence and outcome of stroke. However, little is known about the correlation between seasonal variability and location of acute cerebral infarction. This study aimed to explore the relationship between onset season and the lesions distribution of acute ischemic stroke (AIS). We retrospectively analysis data from 1488 AIS patients admitted to the Second Hospital of Tianjin Medical University from 2018 to 2022. All subjects completed head magnetic resonance imaging examination (MRI) and were divided into four groups according to the onset seasons. The lesions distribution of AIS was evaluated for anterior/posterior/double circulation infarction (DCI), unilateral/bilateral infarctions, and single/multiple cerebral infarctions based on MRI. Logistic regression models were employed to assess the association of season with lesions distribution of AIS. Subgroup analysis was performed in different stroke subtypes. Of 1488 patients, 387 (26.0%) AIS occurred in spring, 425 (28.6%) in summer, 331 (22.2%) in autumn and 345 (23.2%) in winter. Multivariate logistic regression demonstrated that the winter group had 2.15 times (95% CI:1.44–3.21) risk of multiple infarctions, 2.69 times (95% CI:1.80–4.02) of bilateral infarctions and 1.54 times (95% CI:1.05–2.26) of DCI compared with summer group, respectively. Subgroup analysis showed an increased risk of multiple (p

Abstract While smoking is widely acknowledged as a risk factor for rheumatoid arthritis (RA), the connection between secondhand smoke (SHS) exposure and RA in never-smoking adults remains limited and inconsistent. This study aims to explore and quantify this association using serum cotinine levels. We conducted a cross-sectional study with 14,940 adults who self-report as never smokers, using National Health and Nutrition Examination Survey data from 1999 to 2018. Based on previous literature, SHS exposure was categorized into four groups according to serum cotinine levels. Compared to individuals in the unexposed group (serum cotinine

Abstract An electronic tongue (E-tongue) comprises a series of sensors that simulate human perception of taste and embedded artificial intelligence (AI) for data analysis and recognition. Traditional E-tongues based on electrochemical methods suffer from a bulky size and require larger sample volumes and extra power sources, limiting their applications in in vivo medical diagnosis and analytical chemistry. Inspired by the mechanics of the human tongue, triboelectric components have been incorporated into E-tongue platforms to overcome these limitations. In this study, an integrated multichannel triboelectric bioinspired E-tongue (TBIET) device was developed on a single glass slide chip to improve the device’s taste classification accuracy by utilizing numerous sensory signals. The detection capability of the TBIET was further validated using various test samples, including representative human body, environmental, and beverage samples. The TBIET achieved a remarkably high classification accuracy. For instance, chemical solutions showed 100% identification accuracy, environmental samples reached 98.3% accuracy, and four typical teas demonstrated 97.0% accuracy. Additionally, the classification accuracy of NaCl solutions with five different concentrations reached 96.9%. The innovative TBIET exhibits a remarkable capacity to detect and analyze droplets with ultrahigh sensitivity to their electrical properties. Moreover, it offers a high degree of reliability in accurately detecting and analyzing various liquid samples within a short timeframe. The development of a self-powered portable triboelectric E-tongue prototype is a notable advancement in the field and is one that can greatly enhance the feasibility of rapid on-site detection of liquid samples in various settings.

Abstract Ubiquitin-specific protease 3 (USP3) plays an important role in the progression of various tumors. However, the role of USP3 in osteosarcoma (OS) remains poorly understood. The aim of this study was to explore the biological function of USP3 in OS and the underlying molecular mechanism. We found that OS had higher USP3 expression compared with that of normal bone tissue, and high expression of USP3 was associated with poor prognosis in patients with OS. Overexpression of USP3 significantly increased OS cell proliferation, migration, and invasion. Mechanistically, USP3 led to the activation of the PI3K/AKT signaling pathway in OS by binding to EPHA2 and then reducing its protein degradation. Notably, the truncation mutant USP3-F2 (159–520) interacted with EPHA2, and amino acid 203 was found to play an important role in this process. And knockdown of EPHA2 expression reversed the pro-tumour effects of USP3-upregulating. Thus, our study indicates the USP3/EPHA2 axis may be a novel potential target for OS treatment.

AbstractPurpose To investigate the value of three-dimensional ultrasound fusion imaging (3DUS FI) technique for guiding needle placement in hepatocellular carcinoma (HCC) thermal ablation.Methods A total of 57 patients with 60 HCCs with 3DUS FI-guided thermal ablation were retrospectively included in the study. 3DUS volume data of liver were acquired preoperatively by freehand scanning with the tumor and predetermined 5 mm ablative margin automatically segmented. Plan of needle placement was made through a predetermined simulated ablation zone to ensure a 5 mm ablative margin with the coverage rate toward tumor and ablative margin. With real-time ultrasound and 3DUS fusion imaging, ablation needles were placed according to the plan. After ablation, the ablative margin was immediately evaluated by contrast-enhanced ultrasound and 3DUS fusion imaging. The rate of adequate ablative margin, complete response (CR), local tumor progression (LTP), disease-free survival (DFS), and overall survival (OS) was evaluated.Results According to postoperative contrast-enhanced CT or MR imaging, the complete response rate was 100% (60/60), and 83% of tumors (30/36) achieved adequate ablative margin (>5 mm) three-dimensionally. During the follow-up period of 6.0-42.6 months, LTP occurred in 5 lesions, with 1- and 2-year LTP rates being 7.0% and 9.4%. The 1- and 2-year DFS rates were 76.1% and 65.6%, and 1- and 2-year OS rates were 98.1% and 94.0%. No major complications or ablation-related deaths were observed in any patients.Conclusions Three-dimensional ultrasound fusion imaging technique may improve the needle placement of thermal ablation for HCC and reduce the rate of LTP.

Kiwifruit bacterial canker, caused by Pseudomonas syringae pv. actinidiae (PSA), poses a grave threat to the global kiwifruit industry. In this study, we examined the role of microRNAs (miRNAs) in kiwifruit’s response to PSA. Kiwifruit seedlings subjected to PSA treatment showed significant changes in both miRNA and gene expression compared to the control group. We identified 364 differentially expressed miRNAs (DEMs) and 7170 differentially expressed genes (DEGs). Further analysis revealed 180 miRNAs negatively regulating 641 mRNAs. Notably, two miRNAs from the miRNA482 family, miRNA-215-3p and miRNA-29-3p, were found to increase kiwifruit’s sensitivity to PSA when overexpressed. These miRNAs were linked to the regulation of NBS-LRR target genes, shedding light on their role in kiwifruit’s defence against PSA. This study offers insights into the miRNA482-NBS-LRR network as a crucial component in enhancing kiwifruit bioresistance to PSA infestation and provides promising candidate genes for further research.

Rapidly growing urbanization and industrialization drive the continued development of soil stabilization and ground improvement techniques. Rice husk ash (RHA) is widely regarded as a highly promising construction material in civil engineering due to its excellent pozzolanic properties and has garnered significant attention from researchers. This paper presents an experimental study and a micro-mechanical discussion on the role of RHA in the mechanical improvement of soil. RHA was mixed with the native soil in varying proportions, ranging from 0% to 12%. Several laboratory tests were conducted, including standard proctor compaction tests, Atterberg limit tests, freeze-thaw tests, unconfined compression tests, X-ray diffraction (XRD) analysis, and scanning electron microscopy (SEM). The results indicated that the optimal moisture content (OMC) of the soil mixture increased while the maximum dry density (MDD) decreased with higher RHA dosage. The Atterberg limits of the soil mixture exhibited a positive correlation with the RHA content. A substantial enhancement in the soil's strength, stiffness, and ductility was observed upon the incorporation of RHA. It was noted that the strength loss of the untreated samples and those with 12% RHA was 34.91% and 12.89%, respectively, following 12 freeze-thaw cycles. Furthermore, XRD test results revealed that the treated specimen had an identical mineral composition to the control specimen, with no generation of hydration products. SEM analysis also highlighted that the filling effect of RHA significantly reduced pore content and pore connectivity within the soil, accompanied by a shift in the specimen's pores from mesopores to small and micropores. The excellent thermal insulation and heat retention properties of RHA, along with its pore-refining effect, make a positive contribution to enhancing the frost resistance of the specimens. These findings contribute to guiding the effective application of RHA in civil engineering, offering eco-friendly solutions for biomass waste management, and promoting the sustainable development of construction materials.

Purpose: This study aimed to explore the expression of CX3CL1 induced by lipopolysaccharide (LPS) in oral squamous cell carcinoma (OSCC) and its impact on biological characteristics such as invasion and migration, taking the foundation for new targets for the treatment and prognosis of OSCC. Methods: This study utilized a variety of techniques, including bioinformatics, molecular biology, and cell experiments, to investigate the expression of CX3CL1 and its receptor CX3CR1 in OSCC patients’ cancer tissues or OSCC cell lines. Extracting, organizing, and analyzing the TCGA database on the expression of CX3CL1 and its receptor CX3CR1 in cancer tissues and corresponding paracancerous normal tissues of OSCC patients by bioinformatics methods. The expression of CX3CL1 in cancerous and normal tissues of OSCC patients was verified by IHC, and the changes in mRNA and protein expression of CX3CL1 and its receptor CX3CR1 in OSCC cell lines were detected before and after lipopolysaccharide LPS stimulation by RT-PCR, ELISA, and WB. Changes in cell biological behavior by overexpression of CX3CL1 in OSCC cell lines were detected by CCK-8, Transwell, scratch healing assay, and cloning assay. The effects of overexpressing cell lines on the AKT pathway and Epithelial-mesenchymal Transition (EMT)-related protein expression before and after LPS stimulation were detected by Western Blot.Results: (1) CX3CL1 and its receptor CX3CR1 were found to be downregulated in OSCC tissues of patients or OSCC cell lines. (2) After LPS stimulation, CX3CL1 gene expression increased in both OSCC cell lines, while CX3CR1 expression remained unchanged. (3) OSCC cell lines overexpressing CX3CL1 showed changes in cell biological characteristics, including decreased proliferation, invasion, migration, and stemness, which were more pronounced after LPS stimulation. (4) Overexpression of CX3CL1 in OSCC cell lines decreased EMT-related protein expression and AKT phosphorylation. On the contrary were promoted by LPS stimulation.Conclusion:CX3CL1 and CX3CR1 are downregulated in OSCC cancer tissues and cell lines compared to adjacent normal tissues and cells. LPS stimulation increases CX3CL1 expression in OSCC cell lines, suggesting that inflammation may induce CX3CL1 expression and that the CX3CL1 gene may play an important role in OSCC progression. Overexpression of CX3CL1 inhibits OSCC cell proliferation, migration, invasion, and stemness, suggesting that CX3CL1 plays a critical role in suppressing OSCC development. CX3CL1 suppresses OSCC invasion and migration by affecting EMT progression and AKT phosphorylation, and partially reverse the process that LPS causes and affects the development of OSCC.

BackgroundPainful diabetic neuropathy (PDN) is a common chronic neurological complication of diabetes mellitus. Medications are often used to relieve pain, but with significant side effects. Acupuncture is now a component of pragmatic and integrative treatment for PDN. An increasing number of relevant randomized controlled trials have been published in recent years, but a comprehensive meta-analysis has not yet been performed. The aim of this paper is to verify the effectiveness and safety of acupuncture for PDN by meta-analysis and trial sequential analysis (TSA).MethodsAll participants in this study should have had a PDN diagnosis and the trial group was treated with acupuncture. Eight databases, including EMbase, PubMed, Web of science, Cochrane Library, China Biology Medicine disc (CBM), China National Knowledge Infrastructure (CNKI), Wanfang and Chongqing VIP (CQVIP) were retrieved from inception to 5 April 2023. Meta-analysis was conducted utilizing RevMan 5.3 and Stata 15.0. TSA was performed to assess the adequacy of sample size for the outcomes.ResultsA total of 36 studies, comprising 2,739 PDN patients, were included. Among them, 1,393 patients were assigned to the trial group and 1,346 patients were treated in the control group. Outcomes covers the primary indicator Total effective rate (RR = 1.42, 95%CI [1.34, 1.52], p

Abstract Major depressive disorder (MDD) is a globally prevalent and highly disabling disease characterized by dysfunction of large-scale brain networks. Previous studies have found that static functional connectivity is not sufficient to reflect the complicated and time-varying properties of the brain. The underlying dynamic interactions between brain functional networks of MDD remain largely unknown, and it is also unclear whether neuroimaging-based dynamic properties are sufficiently robust to discriminate individuals with MDD from healthy controls since the diagnosis of MDD mainly depends on symptom-based criteria evaluated by clinical observation. Resting-state functional magnetic resonance imaging (fMRI) data of 221 MDD patients and 215 healthy controls were shared by REST-meta-MDD consortium. We investigated the spatial-temporal dynamics of MDD using co-activation pattern analysis and made individual diagnoses using support vector machine (SVM). We found that MDD patients exhibited aberrant dynamic properties (such as dwell time, occurrence rate, transition probability, and entropy of Markov trajectories) in some transient networks including subcortical network (SCN), activated default mode network (DMN), de-activated SCN-cerebellum network, a joint network, activated attention network (ATN), and de-activated DMN-ATN, where some dynamic properties were indicative of depressive symptoms. The trajectories of other networks to deactivated DMN-ATN were more accessible in MDD patients. Subgroup analyses also showed subtle dynamic changes in first-episode drug-naïve (FEDN) MDD patients. Finally, SVM achieved preferable accuracies of 84.69%, 76.77%, and 88.10% in discriminating patients with MDD, FEDN MDD, and recurrent MDD from healthy controls with their dynamic metrics. Our findings reveal that MDD is characterized by aberrant dynamic fluctuations of brain network and the feasibility of discriminating MDD patients using dynamic properties, which provide novel insights into the neural mechanism of MDD.

During the investigation of the freshwater diatoms from Tibet, a monoraphid species was observed from a hot spring near Anduo County, located on a plateau in the central portion of Tibet. This species shares the diagnostic features of Crenotia, such as the valve bent along the transapical axis, striae uniseriate to biseriate from centre to the apices and areolae with special structures located at the end of each stria. We compared the morphological characters of this new species with the others in this genus and show it to be new; it is named Crenotia tibetia sp. nov. This species has small valves with slightly protracted ends with nearly capitate apices, lanceolate axial area, central area unilaterally expanded to the margin, striae uniseriate to biseriate, but, in some valves, the striae are only uniseriate. Areolae are round small to irregular in shape and, at the end of each stria, there is a horseshoe-shaped areola present. Observations of developing valves show all the striae begin biseriate, then they become covered by silica to form uniseriate striae. Comparisons are made amongst the species in this genus and with genera assigned to the Achnanthidiaceae.

The continuous rise in atmospheric CO2 levels has led to persistent ocean acidification, which negatively impacts marine environments crucial for marine life and alters the chemical composition of seawater. This phenomenon carries significant implications for human society. Utilizing surface seawater pH data from the North Pacific spanning 1995 to 2019, this study investigates the overall and localized spatiotemporal variations in pH within the region, as well as the factors influencing these variations. Additionally, it conducts a quantitative analysis of the different influencing factors. The findings reveal a consistent downward trend in surface seawater pH in the North Pacific, decreasing from 8.073 to 8.029, with notable seasonal variations. The highest pH values are recorded in winter, followed by spring, with lower values in autumn and summer. Spatially, the pH values are higher in the northwest and lower in the southeast, with the most pronounced acidification occurring in the central and western regions, while other areas exhibit more uniform acidification levels. Spatial correlation analysis indicates that surface seawater pH in the North Pacific generally shows a negative correlation with sea surface temperature (SST), salinity (SSS), and chlorophyll-a concentration (chl a) and a positive correlation with dissolved oxygen (DO). Among these factors, SST exerts the greatest influence on seawater pH, followed by DO and SSS. The degree of acidification varies across different regions, and the dominant influencing factors differ accordingly. In the equatorial central region (A), the primary factors are chl a and SST; in the eastern regions of China and Japan (B) and the western region of Canada (C), DO and SSS are the main controlling factors. An interaction analysis of each pair of dominant factors using the geodetector shows that their respective contributions to regions A, B, and C are 70%, 90%, and 50%, respectively. Understanding the primary factors driving acidification in different regions can aid in comprehending the biological and environmental impacts of acidification in those areas and provide valuable insights for mitigating marine acidification.

In this study, a novel chemical modification was proposed to introduce carboxylate copper onto the woven carbon fiber (CF) surface, and then the modified CF/Al-2219 composites were successfully fabricated by powder metallurgy. The results showed that the chemical modification of CF improved the infiltration of Al-2219 matrix into woven CFs, thus significantly reduced the defects. The average ultimate tensile strength (UTS) of the modified CF/Al-2219 composites was improved by approximately 13.2 %, and the woven CFs were able to strengthen the composites in multiple directions. This work provides a convenient method of CF pre-treatment for the fabrication of CF/Al composites.

The Archimedes optimization algorithm (AOA) has attracted much attention for its few parameters and competitive optimization effects. However, all agents in the canonical AOA are treated in the same way, resulting in slow convergence and local optima. To solve these problems, an improved hierarchical chain-based AOA (HCAOA) is proposed in this paper. The idea of HCAOA is to deal with individuals at different levels in different ways. The optimal individual is processed by an orthogonal learning mechanism based on refraction opposition to fully learn the information on all dimensions, effectively avoiding local optima. Superior individuals are handled by an Archimedes spiral mechanism based on Levy flight, avoiding clueless random mining and improving optimization speed. For general individuals, the conventional AOA is applied to maximize its inherent exploration and exploitation abilities. Moreover, a multi-strategy boundary processing mechanism is introduced to improve population diversity. Experimental outcomes on CEC 2017 test suite show that HCAOA outperforms AOA and other advanced competitors. The competitive optimization results achieved by HCAOA on four engineering design problems also demonstrate its ability to solve practical problems.

In the present study, the Ni coatings on the surface of carbon fibers (CFs) were purposely regulated to provide the enhanced interfacial microstructure evolution and mechanical properties of CF reinforced Al–Mg matrix (CF/Al–Mg) composites. With increasing the pH value and deposition time, the coating thickness increased with the formation of island-like agglomeration as the pH value was 4.5. Based on the stable electroless plating process, different thicknesses of interconnected coatings were applied in the CF/Al–Mg composites fabricated by a semi-solid rolling process in open space. With the optimal thickness of 2.15 μm, the relative density of the composites increased from 89.7 % to 98.1 %, compared with that of the composites with the thickness of 0.54 μm due to eliminated un-infiltration defects. Simultaneously, optimized fiber dispersion and interfacial behavior were obtained, leading to effective load transfer, more energy absorption and consequently significant enhanced mechanical properties. The ultimate tensile strength (UTS) of the composites was 183 MPa with the largest improvement, which was 96.8 % higher than that of the matrix.

Abstract The present aims to investigate the mechanical characteristics and energy evolution in rock masses containing weak structural planes under conventional triaxial loading conditions. Using a fluid–solid coupling test system of coal rock, numerous conventional triaxial compression tests were performed on rock masses at various dip angles of the structural plane. The obtained empirical outcomes revealed that the deviatoric stress–strain curve of the weak structural plane rock mass with an inclination angle greater than 20° rises step-by-step. On the macro level, slip-stability occurs on the upper and lower parts of the rock mass on the weak structural plane. Then mechanism of the slip-stability phenomenon is explored by analyzing the stress level in the rock mass with various inclination angles. It is found that the energy evolution during deformation and failure reflects the damaged state of the rock. Accordingly, the concept of ‘slip dissipation energy’ is proposed, and the values of each energy are calculated. The results have a good correspondence with the deviatoric stress–strain curve. Furthermore, it was found that the energy evolution of rock mass with a weak structural plane can be primarily classified into four stages, including storage of the initial energy, slip dissipation, abrupt increase in the pre-peak dissipation energy, and sudden drop in post-peak energy. Rock masses with various levels of dip angles exhibit similar elastic strain energy and dissipation energy at the peak point, demonstrating that energy evolution is dominated by energy storage and dissipation. At the same time, a negative correlation is observed between the structural plane dip angle and the occurrence of instantaneous impact instability failure in rock masses, indicating that a greater dip angle makes the rock mass less prone to experiencing instantaneous impact instability failure. This article provides a new idea for analyzing the geological disasters caused by external disturbances.

In the practical application of wireless power transfer (WPT) technology, the identification of uncertain secondary side coil is of great significance to the interoperability of the WPT system. Whether the secondary coil can be accurately identified to realize the ideal match of the primary coil and the secondary coil is one of the keys to achieve efficient power transmission. Based on the characteristics of magnetic field image, this paper combines the convolutional neural network (CNN) to realize the recognition of the coil type, and establishes a 4-layer and 6-layer neural network respectively, and the recognition accuracy is as high as 98%. Compared with the existing visual geometry group (VGG) 16 neural network algorithm, the proposed algorithm has lower complexity and is more suitable for the WPT application field.

Abstract Manganese (Mn) is an essential trace element for almost all living organisms. In plants, Mn deficiency, which is occurs in calcareous soils or alkaline soils, severely limiting crop yields. However, the potential mechanism of Mn transport in Triticum aestivum is still obscure. Here, we found that TaNRAMP3, a member of the naturally resistant macrophage protein (NRAMP) family in Triticum aestivum, is located in the plasma membrane of protoplasts and functions as an influx transporter for Mn in yeast (Δsmf1). The expression of TaNRAMP3 was induced under Mn-deficiency conditions. Furthermore, TaNRAMP3-RNAi plants exhibited a sensitive phenotype, while transgenic plants overexpressing TaNRAMP3 showed a tolerant phenotype. In addition, TaNRAMP3 rescued the sensitive phenotype of Arabidopsis nramp1 mutant under Mn deficiency condition. In summary, our study reveals the key role of TaNRAMP3 in Mn transport in Triticum aestivum, allowing it to adapt to Mn-deficiency stress. These findings provide new insights for the cultivation of Mn-deficiency tolerant wheat varieties.

An accurate gas utilization model is essential for precisely detecting plant photosynthetic capacity. Existing equipment for measuring the plant photosynthetic rate typically considers the key parameters of mesophyll cell conductance and a photosynthetic model based on the carbon reaction process under direct light conditions. However, the light environment signals received by the plant canopy not only vary significantly in incidence angles, but the effective light intensity also differs greatly from the measured values under vertical incidence conditions. To reduce the deviation between existing photosynthetic models and the actual photosynthetic efficiency of leaves, this study employs the gas diffusion method from engineering, using the finite element approach. Based on elastic mechanics and seepage mechanics, the internal stress field control equation of tomato leaves and the two-phase flow equation under a CO2 porous medium were derived. A mathematical model of porous gas–liquid two-phase fluid-solid coupling was established, solved, and analyzed. Preliminary verification was conducted through tests. The results show that in the initial stage of CO2 entering the leaf, the gas flow velocity is higher because of the larger pressure gradient between the pore and the leaf. In this stage, the gas diffusion rate is higher. As the intake time increases, the pressure gradient gradually decreases, and the inlet velocity slows down. Consequently, the diffusion rate gradually reduces. Because of the coupling of light quantity and light direction, the gas diffusion rate significantly increases compared with the uncoupled model. Additionally, a diffusion model that does not consider fluid–solid coupling will overestimate the gas flow rate as the depth of gas entry increases. Therefore, the internal gas diffusion model must account for the effect of coupling on the diffusion rate.

Background:Radix Bupleuri, a kind of Chinese herbal medicine with great clinical use, is often confused with its adulterants, and it is difficult to identify it without certain knowledge. The existing identification methods have their own drawbacks, so a new method is needed to realize the identification of Radix Bupleuri and its adulterants.Methods: We used Micro Computed Tomography (Micro-CT) to perform tomography scans on Radix Bupleuri and its adulterants, performed data screening and data correction on the obtained DICOM images, and then applied 3D reconstruction, data augmentation, and ResNext deep learning model for the classification study.Results: The DICOM images after data screening, data correction, and 3D reconstruction can observe the differences in the microstructure of Radix Bupleuri and its adulterants, thus enabling effective classification and analysis. Meanwhile, the accuracy of classification using the ResNext model reached 75%.Conclusion: The results of this study showed that Micro-CT technology is feasible for the authentication of Radix Bupleuri. The pre-processed and 3D reconstructed tomographic images clearly show the microstructure and the difference between Radix Bupleuri and its adulterants without damaging the internal structure of the samples. This study concludes that Micro-CT technology provides important technical support for the reliable identification of Radix Bupleuri and its adulterants, which is expected to play an important role in the quality control and clinical application of herbs.

Abstract The rapid development of industrial Internet has resulted in significant changes in industrial manufacturing system architecture. In this study, a system architecture suitable for small‐scale personalized production lines is proposed. The core of this architecture is a three‐layer structure comprising the Internet layer, data layer, and field control layer. The system facilitates the transmission of user‐specific product demands from the Internet to the production line, where the production equipment achieves personalized production through motion control. This system architecture for production lines integrates industrial Internet and smart manufacturing technologies, reducing the complexity of the enterprise system architecture and enhancing the flexibility of the system compared to large‐scale personalized production systems. The effectiveness of this system architecture was validated using a flexible yogurt filling production line and lays a foundation for the transformation of industrial manufacturing from the tradition system to a personalized production.

A uniaxial compression test was conducted on sandstone specimens at various inclination angles to determine the energy evolution characteristics during deformation and damage. Based on the principle of minimum energy dissipation, an intrinsic model incorporating the damage threshold was developed to investigate the mechanical properties of sandstone at different inclination angles, and the energy damage evolution during deformation and damage. This study indicated that when the inclination angle of the structural surface remained below 40°, sandstone exhibited varying mechanical properties based on different inclination angles. The peak strain was positively correlated with the inclination angle, whereas the compressive strength and modulus of elasticity showed negative correlations. From an energy perspective, the deformation and damage of sandstone under external loading entail processes of energy input, accumulation, and dissipation. Moreover, higher inclination angles of the structural surface resulted in a smaller absorbed peak strain and a reduced proportion of dissipated energy relative to the energy input, thereby affecting the evolution of energy damage throughout the process. As the inclination angle of the structural surface increased, the absorbed total strain at the peak value decreased, whereas the proportion of the dissipated energy increased. Additionally, the damage threshold and critical value of the rock specimens increased with the inclination angle. The critical value, a composite index comprising the peak strain, compressive strength, and elastic modulus, also increased accordingly. These findings can offer a novel perspective for analyzing geological disasters triggered by fissure zones within underground rock formations.

Lysosomes are active sites to integrate cellular metabolism and signal transduction. A collection of proteins associated with the lysosome mediate these metabolic and signaling functions. Both lysosomal metabolism and lysosomal signaling have been linked to longevity regulation; however, how lysosomes adjust their protein composition to accommodate this regulation remains unclear. Using deep proteomic profiling, we systemically profiled lysosome-associated proteins linked with four different longevity mechanisms. We discovered the lysosomal recruitment of AMP-activated protein kinase and nucleoporin proteins and their requirements for longevity in response to increased lysosomal lipolysis. Through comparative proteomic analyses of lysosomes from different tissues and labeled with different markers, we further elucidated lysosomal heterogeneity across tissues as well as the increased enrichment of the Ragulator complex on Cystinosin-positive lysosomes. Together, this work uncovers lysosomal proteome heterogeneity across multiple scales and provides resources for understanding the contribution of lysosomal protein dynamics to signal transduction, organelle crosstalk, and organism longevity.

Phthalates (PEs) are widely used plasticizers in polymer products, and humans are increasingly exposed to them. This study was designed to investigate the alleviative effect of phytochemicals quercetin (Que) against male reproductive toxicity caused by the mixture of three commonly used PEs (MPEs), and further to explore the underlying mechanism. Forty-eight male SD rats were randomly and evenly divided into control group, Que group, MPEs group and MPEs+Que group (n = 12); The oral exposure doses of MPEs and Que were 450 mg/kg/d and 50 mg/kg/d, respectively. After 91 days of continuous intervention, compared with control group, the testes weight, epididymis weight, serum sex hormones, and anogenital distance were significantly decreased in MPEs group (P

BackgroundPolycystic ovarian syndrome (PCOS) is a common reproductive disorder that affects a considerable number of women worldwide. It is accompanied by irregular menstruation, hyperandrogenism, metabolic abnormalities, reproductive disorders and other clinical symptoms, which seriously endangers women’s physical and mental health. The etiology and pathogenesis of PCOS are not completely clear, but it is hypothesized that immune system may play a key role in it. However, previous studies investigating the connection between immune cells and PCOS have produced conflicting results.MethodsMendelian randomization (MR) is a powerful study design that uses genetic variants as instrumental variables to enable examination of the causal effect of an exposure on an outcome in observational data. In this study, we utilized a comprehensive two-sample MR analysis to examine the causal link between 731 immune cells and PCOS. We employed complementary MR methods, such as the inverse-variance weighted (IVW) method, and conducted sensitivity analyses to evaluate the reliability of the outcomes.ResultsFour immunophenotypes were identified to be significantly associated with PCOS risk: Memory B cell AC (IVW: OR [95%]: 1.123[1.040 to 1.213], p = 0.003), CD39+ CD4+ %CD4+ (IVW: OR [95%]: 0.869[0.784 to 0.963], p = 0.008), CD20 on CD20- CD38-(IVW: OR [95%]:1.297[1.088 to 1.546], p = 0.004), and HLA DR on CD14- CD16+ monocyte (IVW: OR [95%]:1.225[1.074 to 1.397], p = 0.003). The results of the sensitivity analyses were consistent with the main findings.ConclusionsOur MR analysis provides strong evidence supporting a causal association between immune cells and the susceptibility of PCOS. This discovery can assist in clinical decision-making regarding disease prognosis and treatment options, and also provides a new direction for drug development.

IntroductionPatients with acute ischemic stroke (AIS) with non-alcoholic fatty liver disease (NAFLD) frequently have poor prognosis. Many evidences suggested that the changes in gut microbiota may play an important role in the occurrence and development of AIS patients with NAFLD. The purpose of this study was to explore microbial characteristics in patients of AIS with NAFLD, and the correlation between gut microbiota and functional outcomes.MethodsThe patients of AIS were recruited and divided into NAFLD group and non-NAFLD group. The stool samples and clinical information were collected. 16 s rRNA sequencing was used to analyze the characteristics of gut microbiota. The patients of AIS with NAFLD were followed-up to evaluate the functional outcomes of disease. The adverse outcomes were determined by modified Rankin scale (mRS) scores at 3 months after stroke. The diagnostic performance of microbial marker in predicting adverse outcomes was assessed by recipient operating characteristic (ROC) curves.ResultsOur results showed that the composition of gut microbiota between non-NAFLD group and NAFLD group were different. The characteristic bacteria in the patients of AIS with NAFLD was that the relative abundance of Dorea, Dialister, Intestinibacter and Flavonifractor were decreased, while the relative abundance of Enorma was increased. Moreover, the characteristic microbiota was correlated with many clinical parameters, such as mRS scores, mean arterial pressure and fasting blood glucose level. In addition, ROC models based on the characteristic microbiota or the combination of characteristic microbiota with independent risk factors could distinguish functional dependence patients and functional independence patients in AIS with NAFLD (area under curve is 0.765 and 0.882 respectively).ConclusionThese findings revealed the microbial characteristics in patients of AIS with NAFLD, and further demonstrated the predictive capability of characteristic microbiota for adverse outcomes in patients of AIS with NAFLD.

Study Region: Poyang Lake, the largest freshwater lake in China, has been experiencing persistent shrinkage in recent years. Study Focus: The Poyang Lake Hydraulic Project (PLHP) was proposed to improve water resource and environment carrying capacity, its hydrological effects remain under investigation. This study combined a hydrodynamic model with geostatistical connectivity analysis, to quantify the influence of the PLHP on surface water connectivity in Poyang Lake. New Hydrological Insights for the Region: The PLHP enlarges inundated areas most in the recession period (September-November), accounting for 85% of the total increase throughout the operating period (September-March), and enhances the interconnection probability within these inundated regions. Statistical analysis reveals that the Connectivity Function (CF) in low connectivity conditions (CF

Anthocyanins are precious industrial raw materials. Purple corn is rich in anthocyanins, with large variation in their content between organs. It is imperative to find a rapid and non-destructive method to determine the anthocyanin content in purple corn. To this end, a field experiment with ten purple corn hybrids was conducted, collecting plant images using a digital camera and determining the anthocyanin content of different organ types. The average values of red (R), green (G) and blue (B) in the images were extracted. The color indices derived from RGB arithmetic operations were applied in establishing a model for estimation of the anthocyanin content. The results showed that the specific color index varied with the organ type in purple corn, i.e., ACCR for the grains, BRT for the cobs, ACCB for the husks, R for the stems, ACCB for the sheaths and BRT for the laminae, respectively. Linear models of the relationship between the color indices and anthocyanin content for different organs were established with R2 falling in the range of 0.64–0.94. The predictive accuracy of the linear models, assessed according to the NRMSE, was validated using a sample size of 2:1. The average NRMSE value was 11.68% in the grains, 13.66% in the cobs, 8.90% in the husks, 27.20% in the stems, 7.90% in the sheaths and 15.83% in the laminae, respectively, all less than 30%, indicating that the accuracy and stability of the model was trustworthy and reliable. In conclusion, this study provided a new method for rapid, non-destructive prediction of anthocyanin-rich organs in purple corn.

IntroductionH-type hypertension (HHTN) is a subtype of hypertension that tends to worsen the prognosis of acute ischemic stroke (AIS). Recent studies have highlighted the vital role of gut microbiota in both hypertension and AIS, but there is little available data on the relationship between gut microbiota and the progression of AIS patients with HHTN. In this study, we investigated the microbial signature of AIS patients with HHTN and identified characteristic bacteria as biomarkers for predicting prognosis.MethodsAIS patients with HHTN (n = 150) and without HHTN (n = 50) were enrolled. All patients received a modified Rankin Scale (mRS) assessment at 3 months after discharge. Fecal samples were collected from the participants upon admission, including 150 AIS patients with HHTN, 50 AIS patients with non-HHTN, and 90 healthy subjects with HHTN. These samples were analyzed using 16S rRNA sequencing to characterize the bacterial taxa, predict functions, and conduct correlation analysis between specific taxa and clinical features.ResultsOur results showed that the composition of the gut microbiota in HHTN patients differed significantly from that in non-HHTN patients. The abundance of the genera Bacteroides, Escherichia-Shigella, Lactobacillus, Bifidobacterium, and Prevotella in AIS patients with HHTN was significantly increased compared to AIS patients without HHTN, while the genus Streptococcus, Faecalibacterium, and Klebsiella were significantly decreased. Moreover, Bacteroides, Lactobacillus, Bifidobacterium, and Klebsiella in AIS patients with HHTN were more abundant than healthy subjects with HHTN, while Escherichia-Shigella, Blautia, and Faecalibacterium were less abundant. Moreover, the genera Butyricicoccus, Rothia, and Family_XIII_UCG-001 were negatively connected with the NIHSS score, and the genera Butyricicoccus and Rothia were observed to be negatively associated with the mRS score. The genera Butyricicoccus, Romboutsia, and Terrisporobacter were associated with a poor prognosis, whereas the increase in Butyricimonas and Odoribacter was correlated with good outcomes. Generated by eight genera and clinical indexes, the area under the curve (AUC) value of the receiver operating characteristic (ROC) curve achieved 0.739 to effectively predict the prognosis of AIS patients with HHTN.ConclusionThese findings revealed the microbial signature of AIS patients with HHTN and further provided potential microbial biomarkers for the clinical diagnosis of AIS patients with HHTN.

Directional control of the process of doughs with nutrition fortification is challenging. Thus, this study aimed to develop non-starch polysaccharides that can modify the quality of flour products. Polysaccharides were extracted from three different garlic cultivars, evaluated for physicochemical properties and used to enrich doughs for microstructure and mesoscopic characteristics analysis. We assessed the moisture distribution, texture characteristics, thermodynamic properties, dynamic viscoelastic properties, protein structure, microstructure and molecular interaction of the doughs and demonstrated a relatively high molecular weight, lower steric hindrance of molecular chains and higher cross-linking ability with the dough network in the supernatant polysaccharide from Yunnan single-clove-garlic (SGSOS) fraction. These features of SGSOS fraction improved the rheological, thermodynamic, texture characteristics, and water distribution of doughs. These findings provide information on the use of garlic polysaccharides during the processing and manufacturing of foods to enhance their processing adaptability and qualities.

IntroductionCorn is one of the world's essential crops, and the presence of corn diseases significantly affects both the yield and quality of corn. Accurate identification of corn diseases in real time is crucial to increasing crop yield and improving farmers' income. However, in real-world environments, the complexity of the background, irregularity of the disease region, large intraclass variation, and small interclass variation make it difficult for most convolutional neural network models to achieve disease recognition under such conditions. Additionally, the low accuracy of existing lightweight models forces farmers to compromise between accuracy and real-time.MethodsTo address these challenges, we propose FCA-EfficientNet. Building upon EfficientNet, the fully-convolution-based coordinate attention module allows the network to acquire spatial information through convolutional structures. This enhances the network's ability to focus on disease regions while mitigating interference from complex backgrounds. Furthermore, the adaptive fusion module is employed to fuse image information from different scales, reducing interference from the background in disease recognition. Finally, through multiple experiments, we have determined the network structure that achieves optimal performance.ResultsCompared to other widely used deep learning models, this proposed model exhibits outstanding performance in terms of accuracy, precision, recall, and F1 score. Furthermore, the model has a parameter count of 3.44M and Flops of 339.74M, which is lower than most lightweight network models. We designed and implemented a corn disease recognition application and deployed the model on an Android device with an average recognition speed of 92.88ms, which meets the user's needs.DiscussionOverall, our model can accurately identify corn diseases in realistic environments, contributing to timely and effective disease prevention and control.

IntroductionRecent studies have highlighted the vital role of gut microbiota in traumatic brain injury (TBI). Fecal microbiota transplantation (FMT) is an effective means of regulating the microbiota–gut–brain axis, while the beneficial effect and potential mechanisms of FMT against TBI remain unclear. Here, we elucidated the anti-neuroinflammatory effect and possible mechanism of FMT against TBI in mice via regulating the microbiota–gut–brain axis.MethodsThe TBI mouse model was established by heavy object falling impact and then treated with FMT. The neurological deficits, neuropathological change, synaptic damage, microglia activation, and neuroinflammatory cytokine production were assessed, and the intestinal pathological change and gut microbiota composition were also evaluated. Moreover, the population of Treg cells in the spleen was measured.ResultsOur results showed that FMT treatment significantly alleviated neurological deficits and neuropathological changes and improved synaptic damage by increasing the levels of the synaptic plasticity-related protein such as postsynaptic density protein 95 (PSD-95) and synapsin I in the TBI mice model. Moreover, FMT could inhibit the activation of microglia and reduce the production of the inflammatory cytokine TNF-α, alleviating the inflammatory response of TBI mice. Meanwhile, FMT treatment could attenuate intestinal histopathologic changes and gut microbiota dysbiosis and increase the Treg cell population in TBI mice.ConclusionThese findings elucidated that FMT treatment effectively suppressed the TBI-induced neuroinflammation via regulating the gut microbiota–gut–brain axis, and its mechanism was involved in the regulation of peripheral immune cells, which implied a novel strategy against TBI.

Accurate identification of soybean leaf disease is of utmost importance for its cultivation and fine management, as it is a critical factor contributing to the decreased quality and yield of soybean. Nevertheless, several existing studies on the identification of soybean leaf disease encounter the challenge of striking a balance between model expressiveness and practical applicability. To address such issue, we propose a well-designed two-stage feature aggregation network framework (TFANet). The main component of it is the two-stage feature aggregation (TFA) module, which is designed to achieve great feature representation capability by aggregating feature information from different convolutional layers in two stages. Meanwhile, TFA module incorporates the efficient channel attention to extract crucial disease information. Afterwards, to limit the loss of feature information and expand the receptive field, a dilated convolution-based feature fusion (DCFF) module is developed. Additionally, the InceptionC module is introduced to further achieve better performance. The experimental results demonstrated that TFANet obtained an accuracy of 98.18% and an F1 scores of 98.39%, with merely 1.18 M parameters. In comparison with some classic convolutional neural network models, TFANet showed remarkable superiority in multiple evaluation metrics. Hence, TFANet has great potential to be used in practical soybean leaf disease identification.

Objective: The spectrum and risk of cancer in relatives of BRCA1/2 pathogenic variant carriers in the Chinese population have not been established. Methods: A family history of cancer in 9903 unselected breast cancer patients was retrospectively analyzed. BRCA1/2 status was determined for all patients and relative risks (RRs) were calculated to evaluate cancer risk in relatives of the patients. Results: The incidences of breast cancer in female relatives of BRCA1 carriers, BRCA2 carriers, and non-carriers were 33.0%, 32.2%, and 7.7%, respectively. The corresponding incidences of ovarian cancer were 11.5%, 2.4%, and 0.5%, respectively. The incidences of pancreatic cancer in male relatives of BRCA1 carriers, BRCA2 carriers, and non-carriers were 1.4%, 2.7%, and 0.6%, respectively. The corresponding incidences of prostate cancer were 1.0%, 2.1%, and 0.4%, respectively. The risks of breast and ovarian cancers in female relatives of BRCA1 and BRCA2 carriers were significantly higher than female relatives of non-carriers (BRCA1: RR = 4.29, P < 0.001 and RR = 21.95, P < 0.001; BRCA2: RR = 4.19, P < 0.001 and RR = 4.65, P < 0.001, respectively). Additionally, higher risks of pancreatic and prostate cancers were noted in male relatives of BRCA2 carriers than non-carriers (RR = 4.34, P = 0.001 and RR = 4.86, P = 0.001, respectively). Conclusions: Female relatives of BRCA1 and BRCA2 carriers are at increased risk for breast and ovarian cancers, and male relatives of BRCA2 carriers are at increased risk for pancreatic and prostate cancers.

Abstract Background Medication nonadherence is a significant public health problem as it contributes to poor clinical outcomes and increased healthcare costs. Older patients with multimorbidity and polypharmacy often have low medication adherence. These patients also have a high prevalence of potentially inappropriate medication (PIM) use. Aim To explore risk factors related to medication nonadherence in older patients with multimorbidity and polypharmacy and examine the association between medication nonadherence and PIM use. Method A multicenter cross-sectional study was conducted from May to December 2019 in 16 tertiary hospitals from 12 provinces and cities in China. Data were collected from outpatients 65 years or older with multimorbidity and polypharmacy. The PIMs were evaluated using the 2019 Beers Criteria. Self-reported medication adherence was assessed using the Visual Analog Scale (VAS). Results A total of 773 outpatients were recruited. The prevalence of medication nonadherence was 31.8%. In the univariate analysis, nonadherence was significantly associated with sex, cognitive impairment, stroke, visiting the same physicians, self-administration of medication, the percentage of drug costs ≥ 10% of the medical expenses, and PIMs for the alimentary tract and metabolism. In the multivariate analysis, the results almost paralleled those of the univariate associations. Notably, the use of PIM was significantly associated with medication adherence. Conclusion Several factors that influence medication adherence were identified. Targeted interventions can be implemented to improve medication adherence, such as encouraging self-administering medications and reducing medication expenses.

There has been significant recent interest in the use of deep learning for regularizing imaging inverse problems. Most work in the area has focused on regularization imposed implicitly by convolutional neural networks (CNNs) pre-trained for image reconstruction. In this work, we follow an alternative line of work based on learning explicit regularization functionals that promote preferred solutions. We develop the Explicit Learned Deep Equilibrium Regularizer (ELDER) method for learning explicit regularization functionals that minimize a mean-squared error (MSE) metric. ELDER is based on a regularization functional parameterized by a CNN and a deep equilibrium learning (DEQ) method for training the functional to be MSE-optimal at the fixed points of the reconstruction algorithm. The explicit regularizer enables ELDER to directly inherit fundamental convergence results from optimization theory. On the other hand, DEQ training enables ELDER to improve over existing explicit regularizers without prohibitive memory complexity during training. We use ELDER to train several approaches to parameterizing explicit regularizers and test their performance on three distinct imaging inverse problems. Our results show that ELDER can greatly improve the quality of explicit regularizers compared to existing methods, and show that learning explicit regularizers does not compromise performance relative to methods based on implicit regularization.

Cardiovascular diseases are the leading causes of death globally. Their pathological mechanisms are complex and have not yet been fully clarified. With the development of epigenetics research in recent years, the epigenetic modification N6-methyladenosine (m6A) has been demonstrated to play an important role in the occurrence and development of cardiovascular diseases. Moreover, m6A methyltransferases, demethylases, and recognition proteins can regulate m6A methylation levels in the RNA, affecting various biological processes such as RNA splicing, nuclear export, protein translation, and degradation. In this paper, we focus on the biological functions of m6A and investigate its role in the biological processes of apoptosis, inflammation, oxidative stress, energy metabolism, and lipid metabolism. Furthermore, we describe the current findings on the mechanisms involving m6A in cardiovascular diseases and discuss potential drugs targeting m6A for therapy.