Effect of bariatric surgery on metabolism in diabetes and obesity comorbidity: Insight from recent research.

Obesity is a prevalent cause of diabetes mellitus (DM) and is a serious danger to human health. Type 2 DM (T2DM) mostly occurs along with obesity. Foodborne obesity-induced DM is caused by an excessive long-term diet and surplus energy. Bariatric surgery can improve the symptoms of T2DM in some obese patients. But different types of bariatric surgery may have different effects. There are some models built by researchers to discuss the surgical procedures' effects on metabolism in diabetes animal models and diabetes patients. It is high time to conclude all this effects and recommend procedures that can better improve metabolism.

Relationship between indices of insulin resistance and incident type 2 diabetes mellitus in Chinese adults.

BACKGROUND: Insulin resistance (IR) is a pivotal pathogenesis characteristic of type 2 diabetes mellitus (T2DM). The current study aimed to explore the association between triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-c), triglyceride-glucose (TyG), and triglyceride glucose-body mass index (TyG-BMI), and T2DM incidence. METHODS: A total of 116,855 Chinese adults aged over 20 without diabetes were included. Multivariate Cox regression analysis and restricted cubic spine were utilized to investigate the association between IR indicators and T2DM. The T2DM risk across different quartiles of IR parameters was compared using Kaplan-Meier curves. The receiver operating characteristic analysis was used to investigate the predictive potential of each IR indicator for future T2DM. RESULTS: A total of 2685 participants developed T2DM during a median follow-up of 2.98 years. The adjusted hazard ratios (HR) of incident T2DM were 1.177, 2.766, and 1.1018 for TG/HDL-c, TyG, and TyG-BMI, respectively. There were significant increasing trends of T2DM across the quartiles of TG/HDL-c, TyG, and TyG-BMI. The HRs of new-onset T2DM in the highest quartiles versus the lowest quartile of TG/HDL-c, TyG, and TyG-BMI were 3.298, 8.402, and 8.468. RCS revealed the nonlinear relationship between IR and T2DM risk. The correlations between IR and T2DM were more pronounced in subjects aged <40. TyG-BMI had the highest predictive value for incident T2DM (AUC = 0.774), with a cut-off value of 213.289. CONCLUSION: TG/HDL-c, TyG, and TyG-BMI index were all significantly positively associated with higher risk for future T2DM. Baseline TyG-BMI level had high predictive value for the identification of T2DM.

Identifying metabolic dysfunction-associated steatotic liver disease in patients with hypertension and pre-hypertension: An interpretable machine learning approach.

Objective: Metabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most prevalent liver diseases and is associated with pre-hypertension and hypertension. Our research aims to develop interpretable machine learning (ML) models to accurately identify MASLD in hypertensive and pre-hypertensive populations. Methods: The dataset for 4722 hypertensive and pre-hypertensive patients is from subjects in the NAGALA study. Six ML models, including the decision tree, K-nearest neighbor, gradient boosting, naive Bayes, support vector machine, and random forest (RF) models, were used in this study. The optimal model was constructed according to the performances of models evaluated by K-fold cross-validation (k = 5), the area under the receiver operating characteristic curve (AUC), average precision (AP), accuracy, sensitivity, specificity, and F1. Shapley additive explanation (SHAP) values were employed for both global and local interpretation of the model results. Results: The prevalence of MASLD in hypertensive and pre-hypertensive patients was 44.3% (362 cases) and 28.3% (1107 cases), respectively. The RF model outperformed the other five models with an AUC of 0.889, AP of 0.800, accuracy of 0.819, sensitivity of 0.816, specificity of 0.821, and F1 of 0.729. According to the SHAP analysis, the top five important features were alanine aminotransferase, body mass index, waist circumference, high-density lipoprotein cholesterol, and total cholesterol. Further analysis of the feature selection in the RF model revealed that incorporating all features leads to optimal model performance. Conclusions: ML algorithms, especially RF algorithm, improve the accuracy of MASLD identification, and the global and local interpretation of the RF model results enables us to intuitively understand how various features affect the chances of MASLD in patients with hypertension and pre-hypertension.

Native Approach to Controlled-Z Gates in Inductively Coupled Fluxonium Qubits.

The fluxonium qubits have emerged as a promising platform for gate-based quantum information processing. However, their extraordinary protection against charge fluctuations comes at a cost: when coupled capacitively, the qubit-qubit interactions are restricted to XX interactions. Consequently, effective ZZ or XZ interactions are only constructed either by temporarily populating higher-energy states, or by exploiting perturbative effects under microwave driving. Instead, we propose and demonstrate an inductive coupling scheme, which offers a wide selection of native qubit-qubit interactions for fluxonium. In particular, we leverage a built-in, flux-controlled ZZ interaction to perform qubit entanglement. To combat the increased flux-noise-induced dephasing away from the flux-insensitive position, we use a continuous version of the dynamical decoupling scheme to perform noise filtering. Combining these, we demonstrate a 20 ns controlled-z gate with a mean fidelity of 99.53%. More than confirming the efficacy of our gate scheme, this high-fidelity result also reveals a promising but rarely explored parameter space uniquely suitable for gate operations between fluxonium qubits.

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.

Prediction of M3 B4 -type MBenes as Promising Catalysts for CO2 Capture and Reduction.

The rational design of novel catalysts with high activity and selectivity for carbon dioxide reduction reaction (CO2 RR) is highly desired. In this work, we have extensive investigations on the properties of two-dimensional transition metal borides (MBenes) to achieve efficient CO2 capture and reduction through first-principles calculations. The results show that all the investigated M3 B4 -type MBene exhibit remarkable CO2 capture and activation abilities, which proved to be derived from the lone pair of electrons on the MBene surface. Then, we emphasize that the investigated MBenes can further selectively reduce activated CO2 to CH4 . Moreover, a new linear scaling relationship of the adsorption energies of potential-determining intermediates (*OCH2 O and *HOCH2 O) versus ΔG(*OCHO) has been established, where the CO2 RR limiting potentials on MBenes are determined by the different fitting slopes of ΔG(*OCH2 O) and ΔG(*HOCHO), allowing significantly lower limiting potentials to be achieved compared to transition metals. Especially, two promising CO2 RR catalysts (Mo3 B4 and Cr3 B4 MBene) exist quite low limiting potentials of -0.48 V and -0.66 V, as well as competitive selectivity concerning hydrogen evolution reactions have been identified. Our research results make future advances in CO2 capture by MBenes easier and exploit the applications of Mo3 B4 and Cr3 B4 MBenes as novel CO2 RR catalysts.

Carbon doped hexagonal boron nitride as an efficient metal-free catalyst for NO capture and reduction.

The electrochemical NO reduction reaction (NORR) towards NH3 is considered a promising strategy to cope with both NO removal and NH3 production. Currently, the research on NORR electrocatalysts mainly focuses on metal-based catalysts, while metal-free catalysts are quite scarce. In this work, we have systematically investigated the properties of pristine and C/O doped h-BN for efficient NO capture and reduction. Our results reveal that the basal plane of pristine h-BN is inert to the adsorption of NO, while doping C or O can significantly enhance the NO capture abilities of h-BN. Then, we highlight that C-doped h-BN exhibits excellent NORR catalytic performance with a relatively low limiting potential of -0.28 V. Further analysis shows that the suitable adsorption strength of NO on the C-doped h-BN surface is the prime reason for its excellent NO reduction activity, which is shown to be due to appropriate electronic interactions between the active site and NO. Last but not least, the catalytic selectivity of h-BN towards the NORR is confirmed by inhibiting the competing hydrogen evolution reaction. Our findings not only provide deeper insight into the essential effect of element doping on the catalytic activities of h-BN, but also propose general design principles for high-performance metal-free NORR electrocatalysts.

Breaking linear scaling relations by strain engineering on MXene for boosting N2 electroreduction.

The development of N2 reduction reaction (NRR) electrocatalysts with excellent activity and selectivity is of great significance, but adsorption-energy linear scaling relations between reaction intermediates severely hamper the realization of this aspiration. Here, we propose an elegant strain engineering strategy to break the linear relations in NRR to promote catalytic activity and selectivity. Our results show that the N-N bond lengths of adsorbed N2 with side-on and end-on configurations exhibit opposite variations under strains, which is illuminated by establishing two different N2 activation mechanisms of "P-P" (Pull-Pull) and "E-E" (Electron-Electron). Then, we highlight that strain engineering can break the linear scaling relations in NRR, selectively optimizing the adsorption of key NH2NH2** and NH2* intermediates to realize a lower limiting potential (UL). Particularly, the catalytic activity-selectivity trade-off of NRR on MXene can be circumvented, resulting in a low UL of -0.25 V and high Faraday efficiency (FE), which is further elucidated to originate from the strain-modulated electronic structures. Last but not least, the catalytic sustainability of MXene under strain has been guaranteed. This work not only provides fundamental insights into the strain effect on catalysis but also pioneers a new avenue toward the rational design of superior NRR catalysts.

Identification of hub genes based on integrated analysis of single-cell and microarray transcriptome in patients with pulmonary arterial hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a devastating chronic cardiopulmonary disease without an effective therapeutic approach. The underlying molecular mechanism of PAH remains largely unexplored at single-cell resolution. METHODS: Single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database (GSE210248) was included and analyzed comprehensively. Additionally, microarray transcriptome data including 15 lung tissue from PAH patients and 11 normal samples (GSE113439) was also obtained. Seurat R package was applied to process scRNA-seq data. Uniform manifold approximation and projection (UMAP) was utilized for dimensionality reduction and cluster identification, and the SingleR package was performed for cell annotation. FindAllMarkers analysis and ClusterProfiler package were applied to identify differentially expressed genes (DEGs) for each cluster in GSE210248 and GSE113439, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) were used for functional enrichment analysis of DEGs. Microenvironment Cell Populations counter (MCP counter) was applied to evaluate the immune cell infiltration. STRING was used to construct a protein-protein interaction (PPI) network of DEGs, followed by hub genes selection through Cytoscape software and Veen Diagram. RESULTS: Nineteen thousand five hundred seventy-six cells from 3 donors and 21,896 cells from 3 PAH patients remained for subsequent analysis after filtration. A total of 42 cell clusters were identified through UMAP and annotated by the SingleR package. 10 cell clusters with the top 10 cell amounts were selected for consequent analysis. Compared with the control group, the proportion of adipocytes and fibroblasts was significantly reduced, while CD8+ T cells and macrophages were notably increased in the PAH group. MCP counter revealed decreased distribution of CD8+ T cells, cytotoxic lymphocytes, and NK cells, as well as increased infiltration of monocytic lineage in PAH lung samples. Among 997 DEGs in GSE113439, module 1 with 68 critical genes was screened out through the MCODE plug-in in Cytoscape software. The top 20 DEGs in each cluster of GSE210248 were filtered out by the Cytohubba plug-in using the MCC method. Eventually, WDR43 and GNL2 were found significantly increased in PAH and identified as the hub genes after overlapping these DEGs from GSE210248 and GSE113439. CONCLUSION: WDR43 and GNL2 might provide novel insight into revealing the new molecular mechanisms and potential therapeutic targets for PAH.

Fasting blood glucose predicts high risk of in-stent restenosis in patients undergoing primary percutaneous coronary intervention: a cohort study.

Objectives. Studies have shown that fasting blood glucose (FBG) is closely associated with poor prognosis in patients with coronary heart disease (CHD) after percutaneous coronary intervention (PCI), but its association with in-stent restenosis (ISR) is still unclear. Therefore, this study was to explore the association between FBG with ISR in patients with CHD after PCI. Design. In this cohort study, we included 531 patients with CHD who underwent PCI. Logistic regression, receiver operating characteristic (ROC), subgroup analysis and restricted cubic spline (RCS) were used to assess the association between FBG with ISR. Results. A total of 124 (23.4%) patients had ISR. Patients with higher levels of FBG had higher incidence of ISR compared to those with lower levels of FBG (p = 0.002). In multivariable logistic regression analyses, higher levels of FBG remained strongly associated with higher risk of ISR (as a categorical variable, OR: 1.89, 95% CI: 1.21-2.94, p = 0.005; as a continuous variable, OR: 1.12, 95% CI: 1.03-1.23, p = 0.011). ROC analysis also showed that FBG might be associated with the occurrence of ISR (AUC = 0.577, 95% CI: 0.52-0.64, p = 0.013). Subgroup analyses showed the association of FBG with ISR was also stable in several subgroups (< 60 years or ≥ 60 years, male, with or without smoking, without diabetes and without hypertension). And RCS analysis showed that FBG was linearly and positively associated with the risk of ISR. Conclusions. Higher levels of FBG were closely associated with higher risk of ISR in patients with CHD after PCI.

Condensation-assembly synthesis of three-dimensionally porous boron nitride for effective oil removal.

A template-free pyrolysis route has been developed using condensation-assembly precursors made of trimethoxyboroxane (TMB) and melamine (M) to cater the requirements of an industrial real-world environment. The precursors contain abundant B-N bonds and exhibit a high level of interconnectivity, resulting in 3D-PBN with enhanced mechanical properties and the ability to be easily customized in terms of shape. Moreover, 3D-PBN demonstrates rapid adsorption kinetics and excellent reusability, efficiently removing up to 270% of its own weight of fuel within 30 s and being readily regenerated through simple calcination. Even after undergoing 50 cycles, the mechanical properties remain at a remarkable 80%, while the adsorption performance exceed 95%. Furthermore, a comprehensive analysis of thermal behavior from precursor to 3D-PBN has been conducted, leading to the proposal of a molecular-scale evolution process comprising four major steps. This understanding enables us to control the phase reaction and regulate the composition of the products, which is crucial for determining the characteristics of the final product.

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.

Boron nitride aerogels incorporated with metal nanoparticles: Multifunctional platforms for iodine capture and detection.

Radioactive iodine vapors produced by nuclear fission can pose a significant risk to human health and the environment. Effective monitoring of iodine vapor leakage, capture and storage of radioactive iodine vapor are of great importance for the safety of the nuclear industry. Herein, we report a novel structure-function integrated solid iodine vapor adsorbent based on metal-modified boron nitride (BN) aerogel. Metal-modified BN aerogels incorporated with Cu/Ag nanoparticles (named as BN-Cu and BN-Ag, respectively) are successfully prepared by a metal-induced, ultrasonic-assisted, and in-situ transformation method. The metal-modified BN aerogels show improved mechanical properties in both of the maximum stress and residual deformation. Remarkably, due to the greatly enhanced "host-guest" and "guest-guest" effects by the introduction of metal nanoparticles, the BN-Cu and BN-Ag aerogels exhibit record-breaking iodine vapor adsorption capacities among inorganic adsorbents (1739.8 and 2234.13 wt% respectively), which are even higher than that of most organic adsorbents. Furthermore, an integrated iodine adsorption detection device based on metal-modified aerogels is constructed to realize real-time detection of the electrical properties of aerogels during iodine adsorption. This work provides a foundation for the development of BN aerogels as multifunctional platforms for effective iodine capture and detection. It also introduces new ideas for the use of structural-functional integrated materials in the prevention and control of radioactive iodine pollution.

Establishing theoretical landscapes for identifying basal plane active sites in MBene toward multifunctional HER, OER, and ORR catalysts.

Exploring multifunctional electrocatalysts to realize efficient hydrogen evolution reaction (HER), oxygen evolution reaction (OER), and oxygen reduction reaction (ORR) is urgently desired for developing novel renewable energy storage and conversion technologies. However, integrating these three merits in one single catalyst remains a big challenge due to the difficulty in balancing the adsorption strengths of multiple reaction intermediates. Herein, through first-principles calculations, we systematically investigated the electrocatalytic activity of M2B2, M3B4, and M4B6 type MBenes (M = Cr, Mn, Fe, Co, and Ni) for multifunctional HER, OER, and ORR. The results indicate that most of the investigated MBenes show outstanding catalytic activity for HER with hydrogen adsorption Gibbs free energy close to the optimal value (0 eV). Thereinto, Ni2B2 and Co3B4 MBenes can be promising multifunctional HER/OER/ORR electrocatalysts, and Fe3B4 MBene is expected to be a promising bifunctional electrocatalyst for HER/ORR. Especially, Ni2B2 MBene is even better than the benchmark RuO2 catalyst with ultralow low overpotentials of 0.26 and 0.30 V for OER and ORR, respectively. Then, we proposed that the overpotentials of OER/ORR can be well described by the varied ΔGOH* on MBene, which has been further illuminated through the d-band center and charge transfer analysis. Importantly, new scaling relations between the adsorption energies of OOH* and O* on MBenes have been established, where ΔGOOH* and ΔGO* possess different slopes versus ΔGOH*, allowing the significantly lower overpotentials of OER and ORR to be achieved. This work provides not only promising multifunctional HER/OER/ORR electrocatalysts but also new scaling relations to achieve the rational design of MBene-based electrocatalysts.

De Ritis Ratio is Associated with Contrast-Associated Acute Kidney Injury Prediction and Long-Term Clinical Outcomes in Patients Undergoing Emergency Percutaneous Coronary Intervention.

Contrast-associated acute kidney injury (CA-AKI) is a familiar complication following percutaneous coronary intervention (PCI). The present study evaluated the predictive value of the De Ritis ratio for CA-AKI and its association with long-term clinical outcomes in patients undergoing emergency PCI. Overall, 546 patients were included in this study. The De Ritis ratio was calculated by aspartate aminotransferase/alanine aminotransferase activity. The De Ritis ratios in the CA-AKI patients were significantly higher than the non-CA-AKI patients [3.74 (2.32, 4.90) vs 1.61 (1.02, 2.53); P < .001]. The De Ritis ratio was an independent risk factor for CA-AKI [odds ratio, 2.243; 95% confidence interval (CI), 1.823-2.759; P < .001]. The area under the ROC curve was .813 (95% CI, .763-.862; P < .001), and the sensitivity and specificity were 67.0% and 82.4%, respectively, when the optimum cut-off value was 2.97. Furthermore, patients in the high De Ritis ratio group (≥1.76) had a significantly greater incidence of primary endpoints [26.7% (73/273) vs 13.2% (36/273); P < .001], and the high De Ritis ratio was an independent predictor for primary endpoints (hazard ratio, 1.888, 95% CI, 1.235-2.887; P = .003). In conclusion, the De Ritis Ratio is associated with CA-AKI prediction and long-term clinical outcomes in patients undergoing emergency PCI.

Association Between Inflammatory Biomarkers and Contrast-induced Acute Kidney Injury in ACS Patients Undergoing Percutaneous Coronary Intervention: A Cross-sectional Study.

The present study aimed to evaluate the predictive role of inflammatory biomarkers in the development of contrast-induced acute kidney injury (CI-AKI) in acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI). The inflammatory biomarkers assessed were: platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), neutrophil-to-lymphocyte*platelet ratio (NLPR), systemic inflammatory index (SII), and systemic inflammation response index (SIRI). Overall, 950 patients undergoing PCI were enrolled. The frequency of CI-AKI was 15.2% (n = 144). The levels of NLR, MLR, NLPR, SII, and SIRI were higher in the CI-AKI group than in the Non-CI-AKI group (P < .05). The addition of NLR ≥2.96, dNLR ≥2.08, NLPR ≥.012, SII ≥558.04, and SIRI ≥1.13 to the Mehran score model significantly increased the area under the curve (P < .05). Multivariable logistic regression analyses indicated that inflammatory biomarkers were significantly associated with CI-AKI, including NLR ≥2.96 (OR = 1.588, P = .017), dNLR ≥2.08 (OR = 1.686, P = .007), SII ≥558.04 (OR = 1.521, P = .030), and SIRI ≥1.13 (OR = 1.601, P = .017). Therefore, inflammation is associated with the development of CI-AKI, and preoperative hematological inflammatory markers could predict the risk of CI-AKI in ACS patients undergoing PCI.

Boron Nitride Microspheres via Pyrolysis of Polymerized Precursors.

Microspheric BN materials have high application potential because they have better fluidity and dispersion ability to endow hexagonal boron nitride (h-BN) ceramics and h-BN/polymer composites with highly desired performance. In this work, a novel synthetic route to the BN microspheres has been developed by means of a controllable pyrolysis of polymerized spherical precursors. The precursor formation mechanism is proposed to be the F-127-induced self-assembling polymerization of a boric acid-melamine-formaldehyde (MF) colloid. It is found that ammonia-annealing of an air-pyrolysis (700 °C) intermediate causes higher BN phase transformation within final BN microspheres with more uniform diameter distribution compared to those of direct ammonia-pyrolysis of spherical precursors at the same temperatures of 1100 and 1500 °C. After ammonia-annealing and ammonia-pyrolyzed treatment at 1100 and 1500 °C, the obtained BN microspheres have a low specific surface area (SSA) property, but replacing part of melamine with dicyandiamide could increase their SSAs to more than 1000 m2/g. We believe that this new microspherical BN preparation with more facile and controllable operation would be well suited for industrialization.

Predicting cerebral white matter lesions based on the platelet-to-white blood cell ratio in hypertensive patients.

Hypertension is a common chronic disease affecting many people. White matter lesions (WMLs) are one of the imaging features of cerebrovascular disease. Predicting the possibility of developing syncretic WMLs in patients with hypertension may contribute to the early identification of serious clinical conditions. This study aims to build a model to identify patients who suffered from moderate-to-severe WMLs by using recognized WMLs risk factors including age and history of diabetes and a new factor named platelet-to-white blood cell ratio (PWR). A total of 237 patients were included in this study. The Affiliated ZhongDa Hospital of Southeast University Research Ethics Committee approved this study (Ethics No. 2019ZDSYLL189-P01). We developed a nomogram to predict the risk of syncretic WMLs in patients with hypertension using the above factors. Higher total scores on the nomogram indicated a higher risk of syncretic WMLs. This means older age, smaller PWR, and patients suffering from diabetes contributed to a greater chance for the patient to suffer from syncretic WMLs. We used a decision analysis curve(DCA) to determine the net benefit of the prediction model. The DCA we constructed showed that using our model to decide whether patients suffered from syncretic WMLs or not was better than assuming they all suffered from syncretic WMLs or all WMLs-free. As a result, the area under the curve of our model was 0.787. By integrating PWR, history of diabetes, and age, we could estimate integrated WMLs in hypertensive patients. This study provides a potential tool to identify cerebrovascular disease in patients with hypertension.

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.