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Abstract Background Biotransformation of CO2 into high-value-added carbon-based products is a promising process for reducing greenhouse gas emissions. To realize the green transformation of CO2, we use fatty acids as carbon source to drive CO2 fixation to produce succinate through a portion of the 3-hydroxypropionate (3HP) cycle in Cupriavidus necator H16. Results This work can achieve the production of a single succinate molecule from one acetyl-CoA molecule and two CO2 molecules. It was verified using an isotope labeling experiment utilizing NaH13CO3. This implies that 50% of the carbon atoms present in succinate are derived from CO2, resulting in a twofold increase in efficiency compared to prior methods of succinate biosynthesis that relied on the carboxylation of phosphoenolpyruvate or pyruvate. Meanwhile, using fatty acid as a carbon source has a higher theoretical yield than other feedstocks and also avoids carbon loss during acetyl-CoA and succinate production. To further optimize succinate production, different approaches including the optimization of ATP and NADPH supply, optimization of metabolic burden, and optimization of carbon sources were used. The resulting strain was capable of producing succinate to a level of 3.6 g/L, an increase of 159% from the starting strain. Conclusions This investigation established a new method for the production of succinate by the implementation of two CO2 fixation reactions and demonstrated the feasibility of ATP, NADPH, and metabolic burden regulation strategies in biological carbon fixation.

The action mechanism of blast shock wave and detonation gas in rock blasting remains unclear. This article attempts to reveal the action mechanism of blast shock wave and detonation gas through high-speed schlieren system, overpressure test system and AUTODYN numerical simulation analysis. 5 cartridges under different explosive types and charge structures were designed, and the dynamic action evolution of detonation products can be visualized from schlieren photos. The action change of blast shock wave and detonation gas in the flow field were compared under the said five conditions. The numerical simulation results were compared with the schlieren experiment results, and the detonation wave process in explosives was reversely deduced. The results showed: the blast shock wave initially expand along with the detonation gas, both propagate outwardly around the point of detonation in a spherical shape. During propagation, the blast shock wave is gradually separated from the detonation gas, and the blast shock wave propagates at a higher velocity compared with the detonation gas. In the scenarios of different charge structures, the features for which the blast shock wave is separated from the detonation gas are varied, the time of separation will shorten as the constraining effect of the cartridge shell intensifies. In the scenarios of different explosive types, the wave patterns of shock wave and detonation gas are essentially the same. However, the velocity and pressure change of shock wave and detonation wave may deviate in the course of propagation, due to different physical and mechanical parameters of explosive materials. In the presence of slot, shock wave and detonation gas will first propagate outwardly from the slot, then the flow is carried out in the other direction, and the pressure and speed in the incision direction will increase, the energy along the slot direction is concentrated and the tube wall is first damaged, resulting in the effect of directional damage. In the numerical simulation, the fluctuation pattern and schear experimental results of explosion shock wave and explosion gas are more consistent in morphology.

Abstract Hematoxylin and eosin (H&E) whole slide images provide valuable information for predicting prognostic outcomes in colorectal cancer (CRC) patients. However, extracting prognostic indicators from pathological images is challenging due to the subtle complexities of phenotypic information. We trained a weakly supervised deep learning model on data from 640 CRC patients in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial dataset and validated it using data from 522 CRC patients in the cancer genome atlas (TCGA) dataset. We created the colorectal cancer risk score (CRCRS) to assess patient prognosis, visualized the pathological phenotype of the risk score using Grad‐CAM, and employed multiomics data from the TCGA CRC cohort to investigate the potential biological mechanisms underlying the risk score. The overall survival analysis revealed that the CRCRS served as an independent prognostic indicator for both the PLCO cohort (p

While the extracellular matrix (ECM) has long been recognized for its structural contributions, anchoring cells for adhesion, providing mechanical support, and maintaining tissue integrity, recent efforts have elucidated its dynamic, reciprocal, and diverse properties on angiogenesis. The ECM modulates angiogenic signaling and mechanical transduction, influences the extent and degree of receptor activation, controls cellular behaviors, and serves as a reservoir for bioactive macromolecules. Collectively, these factors guide the formation, maturation, and stabilization of a functional vascular network. This review aims to shed light on the versatile roles of the ECM in angiogenesis, transcending its traditional functions as a mere structural material. We will explore its engagement and synergy in signaling modulation, interactions with various angiogenic factors, and highlight its importance in both health and disease. By capturing the essence of the ECM's diverse functionalities, we highlight the significance in the broader context of vascular biology, enabling the design of novel biomaterials to engineer vascularized tissues and their potential therapeutic implications.

Abstract Background Abnormal lipid metabolism poses a risk for prediabetes. However, research on lipid parameters used to predict the risk of prediabetes is scarce, and the significance of traditional and untraditional lipid parameters remains unexplored in prediabetes. This study aimed to comprehensively evaluate the association between 12 lipid parameters and prediabetes and their diagnostic value. Methods This cross-sectional study included data from 100,309 Chinese adults with normal baseline blood glucose levels. New onset of prediabetes was the outcome of concern. Untraditional lipid parameters were derived from traditional lipid parameters. Multivariate logistic regression and smooth curve fitting were used to examine the nonlinear relationship between lipid parameters and prediabetes. A two-piecewise linear regression model was used to identify the critical points of lipid parameters influencing the risk of prediabetes. The areas under the receiver operating characteristic curve estimated the predictive value of the lipid parameters. Results A total of 12,352 participants (12.31%) were newly diagnosed with prediabetes. Following adjustments for confounding covariables, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol were negatively correlated with prediabetes risk. Conversely, total cholesterol, triglyceride (TG), lipoprotein combine index (LCI), atherogenic index of plasma (AIP), non-HDL-C, atherogenic coefficient, Castelli’s index-I, remnant cholesterol (RC), and RC/HDL-C ratio displayed positive correlations. In younger adults, females, individuals with a family history of diabetes, and non-obese individuals, LCI, TG, and AIP exhibited higher predictive values for the onset of prediabetes compared to other lipid profiles. Conclusion Nonlinear associations were observed between untraditional lipid parameters and the risk of prediabetes. The predictive value of untraditional lipid parameters for prediabetes surpassed that of traditional lipid parameters, with LCI emerging as the most effective predictor for prediabetes.

Abstract Thermoresponsive polysaccharide-based materials with tunable transition temperatures regulating phase-separated microdomains offer substantial opportunities in tissue engineering and biomedical applications. To develop novel synthetic thermoresponsive polysaccharides, we employed versatile chemical routes to attach hydrophobic adducts to the backbone of hydrophilic dextran and gradually increased the hydrophobicity of the dextran chains to engineer phase separation. Conjugating methacrylate moieties to the dextran backbone yielded a continuous increase in macromolecular hydrophobicity that induced a reversible phase transition whose lower critical solution temperature can be modulated via variations in polysaccharide concentration, molecular weight, degree of methacrylation, ionic strength, surfactant, urea and Hofmeister salts. The phase separation is driven by increased hydrophobic interactions of methacrylate residues, where the addition of surfactant and urea disassociates hydrophobic interactions and eliminates phase transition. Morphological characterization of phase-separated dextran solutions via scanning electron and flow imaging microscopy revealed the formation of microdomains upon phase transition. These novel thermoresponsive dextrans exhibited promising cytocompatibility in cell culture where the phase transition exerted negligible effects on the attachment, spreading and proliferation of human dermal fibroblasts. Leveraging the conjugated methacrylate groups, we employed photo-initiated radical polymerization to generate phase-separated hydrogels with distinct microdomains. Our bottom-up approach to engineering macromolecular hydrophobicity of conventional hydrophilic, non-phase separating dextrans to induce robust phase transition and generate thermoresponsive phase-separated biomaterials will find applications in mechanobiology, tissue repair and regenerative medicine.

Abstract Background Visceral adiposity index (VAI) has been recognized as a reliable indicator for visceral adiposity. However, it remains largely unexplored on its association with fasting plasma glucose (FPG). The current study aims to explore the association between VAI and FPG using a representative dataset. Methods A cross-sectional study was carried out based on the dataset from National Health and Nutrition Examination Survey (NHANES) 2017–2020. Univariate and Multiple linear regression analysis were performed to explore the relationship between VAI and FPG. Generalized additive model (GAM) and smooth curve fitting analysis were performed to explore the nonlinear relationship between VAI and FPG. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of VAI for FPG elevation. Results A total of 4437 participants with complete data were finally included in the research. Individuals were divided into 4 quartiles according to the calculated VAI value: Q1 (VAI

Abstract Background Tissue culture is an effective method for the rapid breeding of seedlings and improving production efficiency, but explant browning is a key limiting factor of walnut tissue culture. Specifically, the polymerization of PPO-derived quinones that cause explant browning of walnut is not well understood. This study investigated explants of ‘Zanmei’ walnut shoot apices cultured in agar (A) or vermiculite (V) media, and the survival percentage, changes in phenolic content, POD and PPO activity, and JrPPO expression in explants were studied to determine the role of PPO in the browning of walnut explants. Results The results showed that the V media greatly reduced the death rate of explants, and 89.9 and 38.7% of the explants cultured in V media and A media survived, respectively. Compared with that of explants at 0 h, the PPO of explants cultured in A was highly active throughout the culture, but activity in those cultured in V remained low. The phenolic level of explants cultured in A increased significantly at 72 h but subsequently declined, and the content in the explants cultured in V increased to a high level only at 144 h. The POD in explants cultured in V showed high activity that did not cause browning. Gene expression assays showed that the expression of JrPPO1 was downregulated in explants cultured in both A and V. However, the expression of JrPPO2 was upregulated in explants cultured in A throughout the culture and upregulated in V at 144 h. JrPPO expression analyses in different tissues showed that JrPPO1 was highly expressed in stems, young leaves, mature leaves, catkins, pistils, and hulls, and JrPPO2 was highly expressed in mature leaves and pistils. Moreover, browning assays showed that both explants in A and leaf tissue exhibited high JrPPO2 activity. Conclusion The rapid increase in phenolic content caused the browning and death of explants. V media delayed the rapid accumulation of phenolic compounds in walnut explants in the short term, which significantly decreased explants mortality. The results suggest that JrPPO2 plays a key role in the oxidation of phenols in explants after branch injury.

In vitro models of the human mammary gland have struggled to mimic the 3D morphogenic processes that occur in vivo. Here the authors develop a 3D microfluidic platform of a vascularized human mammary duct that simulates diverse morphogenic transitions and paracrine crosstalk.

BackgroundTriglyceride-glucose (TyG) index is a reliable and specific biomarker for insulin resistance and is associated with renal dysfunction. The present study sought to explore the relationship between TyG index and the incidence of contrast-induced nephropathy (CIN) in non-ST elevation acute coronary syndrome (NSTE-ACS) patients implanted with drug-eluting stents (DESs).MethodsA total of 1108 participants were recruited to the study and assigned to two groups based on occurrence of CIN. TyG index was calculated as ln [fasting triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2]. Baseline characteristics and incidence of CIN were compared between the two groups. Logistic regression analysis was performed to evaluate the relationship between TyG index and CIN.ResultsThe results showed that 167 participants (15.1%) developed CIN. Subjects in the CIN group had a significantly higher TyG index compared with subjects in the non-CIN group (8.9 ± 0.7 vs. 9.3 ± 0.7, P

With the development of online educational platforms, numerous research works have focused on the knowledge tracing task, which relates to the problem of diagnosing the changing knowledge proficiency of learners. Deep-neural-network-based models are used to explore the interaction information between students and their answer logs in the current field of knowledge tracing studies. However, those models ignore the impact of previous interactions, including the exercise relation, forget factor, and student behaviors (the slipping factor and the guessing factor). Those models also do not consider the importance of the Q-matrix, which relates exercises to knowledge points. In this paper, we propose a novel relational attention knowledge tracing (RAKT) to track the students’ knowledge proficiency in exercises. Specifically, the RAKT model incorporates the students’ performance data with corresponding interaction information, such as the context of exercises and the different time intervals between exercises. The RAKT model also takes into account the students’ interaction behaviors, including the slipping factor and the guessing factor. Moreover, consider the relationship between exercise sets and knowledge sets and the relationship between different knowledge points in the same exercise. An extension model of RAKT is called the Calibrated Q-matrix relational attention knowledge tracing model (QRAKT), which was developed using a Q-matrix calibration method based on the hierarchical knowledge levels. Experiments were conducted on two public educational datasets, ASSISTment2012 and Eedi. The results of the experiments indicated that the RAKT model and the QRAKT model outperformed the four baseline models.

The increased availability of ultra-high field scanners provides an opportunity to perform fMRI at sub-millimeter spatial scales and enables in vivo probing of laminar function in the human brain. In most previous studies, the definition of cortical layers, or depths, is based on an anatomical reference image that is collected by a different acquisition sequence and exhibits different geometric distortion compared to the functional images. Here, we propose to generate the anatomical image with the fMRI acquisition technique by incorporating magnetization transfer (MT) weighted imaging. Small flip angle binomial pulse trains are used as MT preparation, with a flexible duration (several to tens of milliseconds), which can be applied before each EPI segment without constraining the acquisition length (segment or slice number). The method's feasibility was demonstrated at 7T for coverage of either a small slab or the near-whole brain at 0.8 mm isotropic resolution. Tissue contrast was found to be similar to that obtained with a state-of-art anatomical reference based on MP2RAGE. This MT-weighted EPI image allows an automatic reconstruction of the cortical surface to support laminar analysis in native fMRI space, obviating the need for distortion correction and registration.

Earlier research in cats has shown that both cerebral blood volume (CBV) and cerebral blood flow (CBF) can be used to identify layer-dependent fMRI activation with spatial specificity superior to gradient-echo blood-oxygen-level-dependent (BOLD) contrast (Jin and Kim, 2008a). CBF contrast of perfusion fMRI at ultra-high field has not been widely applied in humans to measure laminar activity due to its low sensitivity, while CBV contrast for fMRI using vascular space occupancy (VASO) has been successfully used. However, VASO can be compromised by interference of blood in-flow effects and a temporally limited acquisition window around the blood-nulling time point. Here, we proposed to use DANTE (Delay Alternating with Nutation for Tailored Excitation) pulse trains combined with 3D-EPI to acquire an integrated VASO and perfusion (VAPER) contrast. The signal origin of the VAPER contrast was theoretically evaluated with respect to its CBV and CBF contributions using a four-compartment simulation model. The feasibility of VAPER to measure layer-dependent activity was empirically investigated in human primary motor cortex at 7 ​T. We demonstrated this new tool, with its highly specified functional layer profile, robust reproducibility, and improved sensitivity, to allow investigation of layer-specific cortical functions.

With the development of smart grid and the increasing of network application within the electric power information network,electric power CDN plays an important role of network acceleration technology,traffic load balancing and network security.However,facing the rapidly changing of application requirements,electric power CDN was required to response to the application deployment quickly and possess flexible application extensibility.In addition,there are some problems on electric power CDN node expansion,such as complex operations management and low utilization rate of resources.It is necessary to reform the traditional power CDN architecture,SDN and NFV technique can support.The data control can be extracted and transmitted by SDN from the network data,so it is conducive to expand a variety of application in power CDN rapidly.And NFV can expand the CDN node capacity and schedule node resources based on the application.It can effectively reduce the capital ecpenditure,storage and power consumption.

PurposeThe principal excitatory neurotransmitter glutamate plays an important role in many central nervous system disorders. Because glutamate resides predominantly in glutamatergic neurons, its relaxation properties reflect the intracellular environment of glutamatergic neurons. This study developed an improved echo time-independent technique for measuring transverse relaxation time and demonstrated that this radio frequency (RF)-driven longitudinal steady state technique can reliably measure glutamate transverse relaxation in the frontal cortex, where structural and functional abnormalities have been associated with psychiatric symptoms.MethodBloch and Monte Carlo simulations were performed to improve and optimize the RF-driven, longitudinal, steady-state (MARzss) technique to significantly shorten scan time and increase measurement precision. Optimized four-flip angle measurements at 0°,12°, 24°, and 36° with matched repetition time were used in nine human subjects (6F, 3M; 27-49 years old) at 7 Tesla. Longitudinal and transverse relaxation rates for glutamate were measured from a 2 x 2 x 2 cm3 voxel placed in three different brain regions: gray matter-dominated medial prefrontal lobe, white matter-dominated left frontal lobe, and gray matter-dominated occipital lobe.ResultsCompared to the original MARzss technique, the scan time per voxel for measuring glutamate transverse relaxation was shortened by more than 50%. In the medial frontal, left frontal, and occipital voxels, the glutamate T2 was found to be 117.5±12.9 ms (mean ± standard deviation, n = 9), 107.3±12.1 (n = 9), and 124.4±16.6 ms (n = 8), respectively.ConclusionsThe improvements described in this study make the MARZSS technique a viable tool for reliably measuring glutamate relaxation from human subjects in a typical clinical setting. It is expected that this improved technique can be applied to characterize the intracellular environment of glutamatergic neurons in a variety of brain disorders.

Abstract Heterogeneous hydrogels with desired matrix complexity are studied for a variety of biomimetic materials. Despite the range of such microstructured materials described, few methods permit independent control over microstructure and microscale mechanics by precisely controlled, single‐step processing methods. Here, a phototriggered crosslinking methodology that traps microstructures in liquid–liquid phase‐separated solutions of a highly elastomeric resilin‐like polypeptide (RLP) and poly(ethylene glycol) (PEG) is reported. RLP‐rich domains of various diameters can be trapped in a PEG continuous phase, with the kinetics of domain maturation dependent on the degree of acrylation. The chemical composition of both hydrogel phases over time is assessed via in situ hyperspectral coherent Raman microscopy, with equilibrium concentrations consistent with the compositions derived from NMR‐measured coexistence curves. Atomic force microscopy reveals that the local mechanical properties of the two phases evolve over time, even as the bulk modulus of the material remains constant, showing that the strategy permits control of mechanical properties on micrometer length scales, of relevance in generating mechanically robust materials for a range of applications. As one example, the successful encapsulation, localization, and survival of primary cells are demonstrated and suggest the potential application of phase‐separated RLP‐PEG hydrogels in regenerative medicine applications.

Background and purposeTechniques to stratify subgroups of patients with asymptomatic carotid artery disease are urgently needed to guide decisions on optimal treatment. Reliance on estimates of % luminal stenosis has not been effective, perhaps because that approach entirely disregards potentially important information on the pathological process in the wall of the artery.MethodsSince plaque lipid is a key determinant of plaque behaviour we used a newly validated, high-sensitivity T2-mapping MR technique for a systematic survey of the quantity and distribution of plaque lipid in patients undergoing endarterectomy. Lipid percentage was quantified in 50 carotid endarterectomy patients. Lipid distribution was tested, using two imaging indices (contribution of the largest lipid deposit towards total lipid (LLD %) and a newly-developed LAI 'lipid aggregation index').ResultsThe bifurcation contained maximal lipid volume. Lipid percentage was higher in symptomatic vs. asymptomatic patients with degree of stenosis (DS ≥ 50%) and in the total cohort (P = 0.013 and P = 0.005, respectively). Both LLD % and LAI was higher in symptomatic patients (P = 0.028 and P = 0.018, respectively), suggesting that for a given plaque lipid volume, coalesced deposits were more likely to be associated with symptomatic events. There was no correlation between plaque volume or lipid content and degree of luminal stenosis measured on ultrasound duplex (r = -0.09, P = 0.53 and r = -0.05, P = 0.75), respectively. However, there was a strong correlation in lipid between left and right carotid arteries (r = 0.5, P ConclusionsPlaque lipid content and distribution is associated with symptomatic status of the carotid plaque. Importantly, plaque lipid content was not related to the degree of luminal stenosis assessed by ultrasound. Determination of plaque lipid content may prove useful for stratification of asymptomatic patients, including selection of optimal invasive treatments.

Residue solvent accessibility is closely related to the spatial arrangement and packing of residues. Predicting the solvent accessibility of a protein is an important step to understand its structure and function. In this work, we present a deep learning method to predict residue solvent accessibility, which is based on a stacked deep bidirectional recurrent neural network applied to sequence profiles. To capture more long-range sequence information, a merging operator was proposed when bidirectional information from hidden nodes was merged for outputs. Three types of merging operators were used in our improved model, with a long short-term memory network performing as a hidden computing node. The trained database was constructed from 7361 proteins extracted from the PISCES server using a cut-off of 25% sequence identity. Sequence-derived features including position-specific scoring matrix, physical properties, physicochemical characteristics, conservation score and protein coding were used to represent a residue. Using this method, predictive values of continuous relative solvent-accessible area were obtained, and then, these values were transformed into binary states with predefined thresholds. Our experimental results showed that our deep learning method improved prediction quality relative to current methods, with mean absolute error and Pearson’s correlation coefficient values of 8.8% and 74.8%, respectively, on the CB502 dataset and 8.2% and 78%, respectively, on the Manesh215 dataset.

Although tissue culture plastic has been widely employed for cell culture, the rigidity of plastic is not physiologic. Softer hydrogels used to culture cells have not been widely adopted in part because coupling chemistries are required to covalently capture extracellular matrix (ECM) proteins and support cell adhesion. To create an in vitro system with tunable stiffnesses that readily adsorbs ECM proteins for cell culture, a novel hydrophobic hydrogel system is presented via chemically converting hydroxyl residues on the dextran backbone to methacrylate groups, thereby transforming non-protein adhesive, hydrophilic dextran to highly protein adsorbent substrates. Increasing methacrylate functionality increases the hydrophobicity in the resulting hydrogels and enhances ECM protein adsorption without additional chemical reactions. These hydrophobic hydrogels permit facile and tunable modulation of substrate stiffness independent of hydrophobicity or ECM coatings. Using this approach, it is shown that substrate stiffness and ECM adsorption work together to affect cell morphology and proliferation, but the strengths of these effects vary in different cell types. Furthermore, it is revealed that stiffness-mediated differentiation of dermal fibroblasts into myofibroblasts is modulated by the substrate ECM. The material system demonstrates remarkable simplicity and flexibility to tune ECM coatings and substrate stiffness and study their effects on cell function. [ABSTRACT FROM AUTHOR]