Production of succinate with two CO2 fixation reactions from fatty acids in Cupriavidus necator H16.

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.

TG2 participates in pulmonary vascular remodelling by regulating the senescence of pulmonary artery smooth muscle cells.

Pulmonary hypertension (PH) is a severe cardiovascular disease characterised by pulmonary vascular remodelling. The pivotal role of cellular senescence in vascular remodelling has been acknowledged. Transglutaminase type 2 (TG2), a calcium-dependent enzyme, is intricately linked to both cellular senescence and PH. However, the precise mechanisms underlying the involvement of TG2 in PH remain unclear. In this study, we explored the expression of TG2 and the cellular senescence marker p16INK4a in the pulmonary vasculature of mice with PH induced by hypoxia combined with SU5416. Our findings revealed upregulation of both TG2 and p16INK4a expression in the pulmonary vasculature of PH mice. Additionally, a notable increase in TG2 expression was observed in senescent pulmonary artery smooth muscle cells (PASMC). To delve deeper, we employed proteomic sequencing to reveal seven genes associated with cellular senescence, with a subsequent focus on MAPK14. Our investigation revealed that TG2 regulates senescence in PASMC by modulating the phosphorylation levels of MAPK14. Additionally, in the context of hypoxia combined with SU5416, our observations revealed a noteworthy reduction in both pulmonary vascular remodelling and senescent manifestations in smooth muscle-specific TG2 knockout mice compared with their wild-type counterparts. In summary, our findings indicate that TG2 deficiency lowers the senescence levels of PASMC by inhibiting the activity of MAPK14. This inhibition of senescence in the pulmonary vasculature of PH mice helps to decelerate the progression of pulmonary vascular remodelling and consequently hinders the onset and development of PH.

A Protein-Adsorbent Hydrogel with Tunable Stiffness for Tissue Culture Demonstrates Matrix-Dependent Stiffness Responses.

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, we present a novel hydrophobic hydrogel system 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, we show 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, we reveal that stiffness mediated differentiation of dermal fibroblasts into myofibroblasts is modulated by the substrate ECM. Our material system demonstrates remarkable simplicity and flexibility to tune ECM coatings and substrate stiffness and study their effects on cell function.

Optimization strategies for CO2 biological fixation.

Global sustainable development faces a significant challenge in effectively utilizing CO2. Meanwhile, CO2 biological fixation offers a promising solution. CO2 has the highest oxidation state (+4 valence state), whereas typical multi­carbon chemicals have lower valence states. The Gibbs free energy (ΔG) changes of CO2 reductive reactions are generally positive and this renders it necessary to input different forms of energy. Although biological carbon fixation processes are friendly to operate, the thermodynamic obstacles must be overcome. To make this reaction occur favorably and efficiently, diverse strategies to enhance CO2 biological fixation efficiency have been proposed by numerous researchers. This article reviews recent advances in optimizing CO2 biological fixation and intends to provide new insights into achieving efficient biological utilization of CO2. It first outlines the thermodynamic characteristics of diverse carbon fixation reactions and proposes optimization directions for CO2 biological fixation. A comprehensive overview of the catalytic mechanisms, optimization strategies, and challenges encountered by common carbon-fixing enzymes is then provided. Subsequently, potential routes for improving the efficiency of biological carbon fixation are discussed, including the ATP supply, reducing power supply, energy supply, reactor design, and carbon enrichment system modules. In addition, effective artificial carbon fixation pathways were summarized and analyzed. Finally, prospects are made for the research direction of continuously improving the efficiency of biological carbon fixation.

The immune response-related genomic alterations in patients with malignant melanoma.

Immune checkpoint inhibitors (ICIs) significantly improve the survival outcomes of patients with advanced melanoma. However, response varies among from patient to patient and predictive biomarkers are urgently needed. We integrated mutational profiles from next-generation sequencing (NGS) data and clinicopathologic characteristics of melanoma patients to investigate whether tumor genomic profiling contribute to clinical benefit of ICIs treatment. The majority of genes identified with high mutation frequency have all been reported as well-known immunotherapy-related genes. Thirty-five patients (43.2%) had at least 1 BRAF/RAS/NF1 mutation. The other 46 (56.8%) melanomas without BRAF/RAS/NF1 mutation were classified as Triple-WT. We identified mutational signature 6 (known as associated with defective DNA mismatch repair) among cases in this cohort. Compared to patients with PD-L1 expression (TPS < 1%), patients with PD-L1 expression (TPS ≥ 1%) had significantly higher median progression-free survival (mPFS), but no significantly higher durable clinical benefit (DCB) rate. In contrast, FAT1, ATM, BRCA2, LRP1B, and PBRM1 mutations only occurred frequently in patients with DCB, irrespective of PD-L1 expression status. Our study explored molecular signatures of melanoma patients who respond to ICIs treatment and identified a series of mutated genes that might serve as predictive biomarker for ICIs responses in melanoma.

Nonlinear relationship between untraditional lipid parameters and the risk of prediabetes: a large retrospective study based on Chinese adults.

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.

Knowledge relation rank enhanced heterogeneous learning interaction modeling for neural graph forgetting knowledge tracing.

Knowledge tracing models have gained prominence in educational data mining, with applications like the Self-Attention Knowledge Tracing model, which captures the exercise-knowledge relationship. However, conventional knowledge tracing models focus solely on static question-knowledge and knowledge-knowledge relationships, treating them with equal significance. This simplistic approach often succumbs to subjective labeling bias and lacks the depth to capture nuanced exercise-knowledge connections. In this study, we propose a novel knowledge tracing model called Knowledge Relation Rank Enhanced Heterogeneous Learning Interaction Modeling for Neural Graph Forgetting Knowledge Tracing. Our model mitigates the impact of subjective labeling by fine-tuning the skill relation matrix and Q-matrix. Additionally, we employ Graph Convolutional Networks (GCNs) to capture intricate interactions between students, exercises, and skills. Specifically, the Knowledge Relation Importance Rank Calibration method is employed to generate the skill relation matrix and Q-matrix. These calibrated matrices, alongside heterogeneous interactions, serve as input for the GCN to compute exercise and skill embeddings. Subsequently, exercise embeddings, skill embeddings, item difficulty, and contingency tables collectively contribute to an exercise relation matrix, which is then fed into an attention mechanism for predictions. Experimental evaluations on two publicly available educational datasets demonstrate the superiority of our proposed model over baseline models, evidenced by enhanced performance across three evaluation metrics.

Inducing an LCST in hydrophilic polysaccharides via engineered macromolecular hydrophobicity.

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.

Upregulation of the key biomarker kinesin family member 20A (KIF20A) is associated with pulmonary artery hypertension.

OBJECTIVE: Pulmonary artery hypertension (PAH) is a complex, fatal disease with limited treatments. This study aimed to investigate possible key targets in PAH through bioinformatics. METHODS: GSE144274 were obtained from Gene Expression Omnibus (GEO) database. Then, differentially expressed genes (DEGs) between idiopathic pulmonary hypertension (IPAH) and healthy subjects were identified and analyzed. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed, and a protein-protein interaction (PPI) network was constructed using STRING. The hub genes were identified by MCODE method. The expression levels of hub genes were validated in vitro and in vivo models. Finally, the ROC analysis was performed based on the level of hub genes in clinical plasma samples. RESULTS: A total of 363 DEGs were identified. GO analysis on these DEGs were mainly enriched in cell division, inflammatory response, among others. In the KEGG pathways analysis, DEGs mainly involved in cytokine-cytokine receptor interaction, rheumatoid arthritis, and IL-17 signaling pathways were enriched. The DEGs were analyzed with the STRING for PPI network analysis, and 62 hub genes were identified by MCODE. Finally, 6 central genes, KIF18B, SPC25, DLGAP5, KIF20A, CEP55 and ANLN, were screened out due to their novelty role in PAH. The expression of KIF20A was validated to be significantly upregulated both in the lung tissue of hypoxia-induced pulmonary hypertension (HPH) mice and proliferative PASMCs. Additionally, KIF20A levels is evelated in PAH plasma and the area under the curve (AUC) to identify PAH was 0.8591 for KIF20A. CONCLUSION: The level of KIF20A elevates during the progression of PAH, which suggestes it could be a potential diagnostic and therapeutic target for the PAH.

Wearable cardiorespiratory monitoring with stretchable elastomer optical fiber.

This work presents a stretchable elastomer optical fiber sensor incorporated into a belt for respiratory rate (RR) and heart rate (HR) monitoring. Different materials and shapes of prototypes designed were tested in terms of performance and the best choice was identified. The optimal sensor was tested by 10 volunteers to evaluate the performance. The proposed elastomer optical fiber sensor can achieve simultaneous measurement of RR and HR in different body positions, and also ballistocardiography (BCG) signal measurement in the lying position. The sensor has good accuracy and stability, with maximum errors of 1 bpm and 3 bpm for RR and HR, respectively, and average weighted mean absolute percentage error (MAPE) of 5.25% and root mean square error (RMSE) of 1.28 bpm. Moreover, the results of the Bland-Altman method showed good agreement of the sensor with manual counting of RR and with electrocardiogram (ECG) measurements of HR.

Visceral adiposity index is positively associated with fasting plasma glucose: a cross-sectional study from National Health and Nutrition Examination Survey 2017-2020.

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<0.69), Q2 (0.69 ≤ VAI < 1.18), Q3 (1.18 ≤ VAI < 2.02) and Q4 (VAI ≥ 2.02). FPG significantly increased with the increasing VAI quartile. Multiple linear regression analysis showed VAI was independently positively associated with FPG after adjusting confounding factors. As a continuous variable, an increase of one unit in VAI was correlated with 0.52 mmol/L (95% CI: 0.41-0.63, p < 0.0001) higher FPG level. As a categorical variable, 4th VAI quartile group was related to 0.71 mmol/L (95% CI: 0.47-0.95, p < 0.001) higher FPG level compared with 1st VAI group. GAM and smooth curve fitting analysis identified the non-linear relationship between VAI and FPG, and 4.02 was identified as the inflection point using two-piecewise linear regression. The positive association between VAI and FPG existed when VAI was lower (ß = 0.73, p < 0.0001) and higher than 4.02 (ß = 0.23, p = 0.0063). ROC analysis indicated VAI has a good predictive value for FPG elevation (AUC = 0.7169, 95% CI: 0.6948-0.7389), and the best threshold of VAI was 1.4315. CONCLUSION: VAI was an independently risk indicator for FPG, and VAI was nonlinearly positively associated with FPG. VAI had a good predictive value for elevated FPG. VAI might become a useful indicator for risk assessment and treatment of hyperglycemia in clinical practice.

Fibrinogen-to-Albumin Ratio Predicts Postcontrast Acute Kidney Injury in Patients with Non-ST Elevation Acute Coronary Syndrome after Implantation of Drug-Eluting Stents.

Background: Postcontrast acute kidney injury (PC-AKI) is an adverse reaction to iodinated contrast agents. In this study, we investigated the use of fibrinogen-to-albumin ratio (FAR) as a novel inflammatory marker to track the development and progression of PC-AKI in patients with non-ST elevation acute coronary syndrome (NSTE-ACS) after the implantation of drug-eluting stents (DESs). Methods: A total of 872 patients with NSTE-ACS were enrolled in this study. PC-AKI was identified when serum creatinine (SCr) levels increased >26.5 mol/L (0.3 mg/dL) or was 1.5 times the baseline level within 48-72 h of exposure to an iodinated contrast agent. The effects of different variables on PC-AKI were evaluated using univariate regression analysis. Multivariate logistic regression analysis was used to determine the independent predictors of PC-AKI. The predictive value of FAR was assessed by estimating the area under the receiver operating characteristic (ROC) curve. Results: In total, 114 (13.1%) patients developed PC-AKI. The patients with PC-AKI had lower albumin levels (40.5 ± 3.4 vs. 39.0 ± 3.5, P < 0.001), higher fibrinogen levels (3.7 ± 0.6 vs. 4.1 ± 0.5, P < 0.001), and higher FAR levels (9.2 ± 1.7 vs. 10.5 ± 1.7, P < 0.001) than those with non-PC-AKI. There were no significant differences in the preoperative SCr levels between the two groups. After adjusting for confounding factors, FAR was found to be an independent predictor of PC-AKI (OR = 1.478, 95% CI = 1.298-1.684, P < 0.001). ROC analysis revealed that for PC-AKI prediction, the area under the curve for FAR was 0.702. The optimum cut-off value of FAR was 10.0, with a sensitivity of 64.9% and a specificity of 69.8%. Moreover, FAR had a higher predictive value for PC-AKI than the Mehran score (0.702 vs. 0.645). Conclusion: Our study showed that elevated preoperative FAR was closely associated with the development of PC-AKI in patients with NSTE-ACS after implantation of DESs. Therefore, it may be worth monitoring FAR as a guide for using preventive measures to avoid the development of PC-AKI.

Salinity fluctuation influences the toxicity of 1-octyl-3-methylimidazolium chloride ([C8mim]Cl) to a marine diatom Phaeodactylum tricornutum.

In this work, a marine diatom (Phaeodactylum tricornutum) was exposed to 1-octyl-3-methylimidazolium chloride ([C8mim]Cl) for 96 h at three different salinities (25, 35, and 45 ‰) for investigating their interactive effects. Results showed that values of EC10 and EC50 at 96 h of exposure were 0.29, 1.06, 2.01 µg L-1 and 7.21, 7.71, 7.25 mg L-1 when the salinities were 25, 35, and 45 ‰, respectively, meaning that salinity fluctuation affected the toxicity of [C8mim]Cl to this diatom. Changes in chlorophyll a contents and chlorophyll fluorescence parameters suggested that [C8mim]Cl and salinity fluctuation had a significant interactive effect on the algal photosynthesis. In addition, soluble protein content and activities of antioxidant enzymes in algal cells changed significantly. Increased malondialdehyde contents indicated that the combined stresses could induce excessive production of reactive oxygen species leading to oxidative damage to the algal cells.

Target Nuclear Factor Erythroid 2-Related Factor 2 in Pulmonary Hypertension: Molecular Insight into Application.

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a key transcription factor involved in maintaining redox balance and activates the expression of downstream antioxidant enzymes. Nrf2 has received wide attention considering its crucial role in oxidative and electrophilic stress. Large amounts of studies have demonstrated the protective role of Nrf2 activation in various pulmonary hypertension (pH) models. Additionally, various kinds of natural phytochemicals acting as Nrf2 activators prevent the development of pH and provide a novel and promising therapeutic insight for the treatment of pH. In the current review, we give a brief introduction of Nrf2 and focus on the role and mechanism of Nrf2 in the pathophysiology of pH and then review the relevant research of Nrf2 agonists in pH in both experimental research and clinical trials.

Elevated TyG Index Predicts Incidence of Contrast-Induced Nephropathy: A Retrospective Cohort Study in NSTE-ACS Patients Implanted With DESs.

Background: Triglyceride-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). Methods: A 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. Results: The 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<0.001). TyG index was significantly correlated with increased risk of CIN after adjusting for confounding factors irrespective of diabetes mellitus status and exhibited a J-shaped non-linear association. Subgroup analysis showed a significant gender difference in the relationship between TyG index and CIN. Receiver operating characteristic (ROC) curve analysis indicated that the risk assessment performance of TyG index was superior compared with other single metabolic indexes. Addition of TyG index to the baseline model increased the area under the curve from 0.713 (0.672-0.754) to 0.742 (0.702-0.782) and caused a reclassification improvement of 0.120 (0.092-0.149). Conclusion: The findings from the present study show that a high TyG index is significantly and independently associated with incidence of CIN in NSTE-ACS patients firstly implanted with DESs. Routine preoperative assessment of TyG index can alleviate CIN and TyG index provides a potential target for intervention in prevention of CIN.

Treatment of Mode Coupling in Step-Index Multimode Microstructured Polymer Optical Fibers by the Langevin Equation.

By solving the Langevin equation, mode coupling in a multimode step-index microstructured polymer optical fibers (SI mPOF) with a solid core was investigated. The numerical integration of the Langevin equation was based on the computer-simulated Langevin force. The numerical solution of the Langevin equation corresponded to the previously reported theoretical data. We demonstrated that by solving the Langevin equation (stochastic differential equation), one can successfully treat a mode coupling in multimode SI mPOF as a stochastic process, since it is caused by its intrinsic random perturbations. Thus, the Langevin equation allowed for a stochastic mathematical description of mode coupling in SI mPOF. Regarding the efficiency and execution speed, the Langevin equation was more favorable than the power flow equation. Such knowledge is useful for the use of multimode SI mPOFs for potential sensing and communication applications.

Directing Cholangiocyte Morphogenesis in Natural Biomaterial Scaffolds.

Patients with Alagille syndrome carry monogenic mutations in the Notch signaling pathway and face complications such as jaundice and cholestasis. Given the presence of intrahepatic ductopenia in these patients, Notch2 receptor signaling is implicated in driving normal biliary development and downstream branching morphogenesis. As a result, in vitro model systems of liver epithelium are needed to further mechanistic insight of biliary tissue assembly. Here, primary human intrahepatic cholangiocytes as a candidate population for such a platform are systematically evaluated, and conditions that direct their branching morphogenesis are described. It is found that extracellular matrix presentation, coupled with mitogen stimulation, promotes biliary branching in a Notch-dependent manner. These results demonstrate the utility of using 3D scaffolds for mechanistic investigation of cholangiocyte branching and provide a gateway to integrate biliary architecture in additional in vitro models of liver tissue.