NUP85 alleviates lipid metabolism and inflammation by regulating PI3K/AKT signaling pathway in nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is one of the common causes of chronic liver disease in the world. The problem of NAFLD had become increasingly prominent. However, its pathogenesis is still indistinct. As we all know, NAFLD begins with the accumulation of triglyceride (TG), leading to fatty degeneration, inflammation and other liver tissues damage. Notably, structure of nucleoporin 85 (NUP85) is related to lipid metabolism and inflammation of liver diseases. In this study, the results of researches indicated that NUP85 played a critical role in NAFLD. Firstly, the expression level of NUP85 in methionine-choline-deficient (MCD)-induced mice increased distinctly, as well as the levels of fat disorder and inflammation. On the contrary, knockdown of NUP85 had the opposite effects. In vitro, AML-12 cells were stimulated with 2 mm free fatty acids (FFA) for 24 h. Results also proved that NUP85 significantly increased in model group, and increased lipid accumulation and inflammation level. Besides, NUP85 protein could interact with C-C motif chemokine receptor 2 (CCR2). Furthermore, when NUP85 protein expressed at an extremely low level, the expression level of CCR2 protein also decreased, accompanied with an inhibition of phosphorylation of phosphoinositol-3 kinase (PI3K)-protein kinase B (AKT) signaling pathway. What is more, trans isomer (ISRIB), a targeted inhibitor of NUP85, could alleviate NAFLD. In summary, our findings suggested that NUP85 functions as an important regulator in NAFLD through modulation of CCR2.

Unveiling the Potential of Two-Terminal Perovskite/Organic Tandem Solar Cells: Mechanisms, Status, and Challenges.

Perovskite/organic tandem solar cells (PO-TSCs) demonstrate exceptional suitability for emerging applications such as building-integrated photovoltaics, wearable devices, and greenhouse farming. By leveraging the distinctive attributes of perovskite and organic materials, which encompass expanded solar spectrum utilization, chemically benign solubility, and soft nature, PO-TSCs position themselves as ideal candidates for high-performance semi-transparent photovoltaics (ST-PVs). Despite these advantages, their development significantly lags behind other perovskite-based counterparts, such as perovskite/perovskite, perovskite/silicon, and perovskite/Cu(In, Ga)Se2. To address existing challenges and unlock the full potential of PO-TSCs, an exploration of the fundamental mechanisms governing tandem photovoltaic devices is embarked. Delving into critical aspects such as charge generation/separation, energy level alignment, and material choices becomes pivotal for optimizing PO-TSC performance. The investigation of monolithic two-terminal PO-TSCs offers insights into achievements and barriers, recognizing the competitive landscape with other TSC counterparts. Further scrutiny of perovskite absorbers and organic absorbers in TSCs reveals strategies aimed at enhancing stability and efficiency. The discussion extends to interconnection layers, elucidating their role in optimizing light transmission and balancing carrier recombination. In conclusion, a compelling outlook on the dynamic landscape of PO-TSCs is presented, highlighting the remarkable efficiency progression and signaling their potential to revolutionize solar energy harvesting technologies.

Association between genetically proxied PCSK9 inhibition and systemic lupus erythematosus risk: A mendelian randomization study.

BACKGROUND: Preclinical and epidemiological studies suggest that proprotein convertase subtilisin/kexin type 9 (PCSK9) had a potential effect on the development of SLE, but it was unclear whether a causal relationship exists. We aimed to investigate the association between genetically proxied inhibition of PCSK9 and the risk of SLE using a two-sample Mendelian randomization (MR) approach. METHODS: Single nucleotide polymorphisms (SNPs) associated with PCSK9 were extracted from pooled data obtained from the Global Lipid Genetics Consortium (GLGC) Genome-wide Association Study (GWAS) related to LDL-c levels, which was used as a proxy for PCSK9 inhibition. Pooled statistics for SLE were obtained from an independent GWAS dataset including 5201 SLE patients and 9066 controls. Inverse variance-weighted random-effects models were used to examine the association between genetically proxied inhibition of PCSK9 and the risk of SLE. MR-Egger, weighted median, weighted mode, Simple mode, and co-location analyses were used as sensitivity analyses to test the robustness of the analyses. RESULTS: Genetically proxied inhibition of PCSK9 was associated with a reduced risk of SLE (OR = 0.51, 95% CI = 0.34 to 0.77, p = .001). This finding was replicated in an earlier GLGC GWAS analysis (OR = 0.59, 95% CI = 0.40 to 0.87, p = .007). Sensitivity analysis ensured that the results were robust. Co-localization analysis did not find evidence of shared causal variation between PCSK9 and SLE. CONCLUSIONS: This Mendelian randomization study showed that PCSK9 was associated with SLE pathogenesis, and its inhibition was associated with a reduced risk of SLE. This study has offered a prospective therapeutic avenue for intervening in the progression of SLE by inhibiting PCSK9 levels.

Trend analysis and prediction of the incidence and mortality of CKD in China and the US.

BACKGROUND: Currently, limited research is available on the comparative analysis of chronic kidney disease (CKD) incidence and mortality rates between China and the United States. This study aimed to explore the trends in CKD incidence and mortality rates in both countries, as well as make some future predictions. METHODS: The data on CKD incidence and mortality in China and the US from 1990 to 2019 were derived from the 2019 Global Burden of Disease database. A Joinpoint regression model was used to analyze temporal trends in CKD incidence and mortality. An age-period-cohort model was used to assess the effects of age, period, and birth cohort on CKD risk and forecast the age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) of CKD in China and the US over the next 15 years. RESULTS: CKD incidence in China and the US showed an upward trend. Its mortality rate showed a downward trend in China but an upward one in the US. The relative risk (RR) of CKD incidence and mortality increases with age. The RR of CKD incidence in the 0-5 age group exceeds that in the 5-55 age group, and the RR for mortality surpasses that in the 5-35 age group. Over time, the RR of CKD incidence has gradually increased in China and the US. Individuals born in later birth cohorts had a lower RR of CKD incidence and mortality. The ASIR of CKD may increase in both China and the US, whereas its ASMR may decline over the next 15 years. CONCLUSION: Screening measures should be strengthened among populations at high risk of CKD; prenatal examinations of pregnant women should be emphasized to reduce CKD incidence in newborns. It is imperative to increase health education and encourage individuals to adopt healthy lifestyles.

Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia.

PURPOSE: To explore the predictive value of radiomics in predicting stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients and construct a prediction model based on clinical features and DWI-MRI radiomics features. METHODS: Univariate and multivariate logistic regression analyses were used to identify the independent clinical predictors for SAP. Pearson correlation analysis and the least absolute shrinkage and selection operator with ten-fold cross-validation were used to calculate the radiomics score for each feature and identify the predictive radiomics features for SAP. Multivariate logistic regression was used to combine the predictive radiomics features with the independent clinical predictors. The prediction performance of the SAP models was evaluated using receiver operating characteristics (ROC), calibration curves, decision curve analysis, and subgroup analyses. RESULTS: Triglycerides, the neutrophil-to-lymphocyte ratio, dysphagia, the National Institutes of Health Stroke Scale (NIHSS) score, and internal carotid artery stenosis were identified as clinically independent risk factors for SAP. The radiomics scores in patients with SAP were generally higher than in patients without SAP (P < 0. 05). There was a linear positive correlation between radiomics scores and NIHSS scores, as well as between radiomics scores and infarct volume. Infarct volume showed moderate performance in predicting the occurrence of SAP, with an AUC of 0.635. When compared with the other models, the combined prediction model achieved the best area under the ROC (AUC) in both training (AUC = 0.859, 95% CI 0.759-0.936) and validation (AUC = 0.830, 95% CI 0.758-0.896) cohorts (P < 0.05). The calibration curves and decision curve analysis further confirmed the clinical value of the nomogram. Subgroup analysis showed that this nomogram had potential generalization ability. CONCLUSION: The addition of the radiomics features to the clinical model improved the prediction of SAP in AIS patients, which verified its feasibility.

Low infrared emissivity and broadband wide-angle microwave absorption integrated bi-functional camouflage metamaterial with a hexagonal patch based metasurface superstrate.

This work proposed and demonstrated a bi-functional metamaterial to implement the multispectral camouflage in infrared and microwave bands. Aiming at integrating broadband, wide-angle and low infrared emissivity into one structure, the bi-functional structure is made up of three metasurface layers with different functions. Specifically, a metasurface superstrate based on hexagonal metallic patch was deployed to achieve a low infrared emissivity and a high transmittance of microwave simultaneously. In the framework of equivalent circuit model, the bi-functional structure was designed and optimized. A dielectric transition layer was introduced into the structure to obtain better microwave absorption performances. A sample of such structure was prepared based on optimized geometric parameters and tested. The simulated and measured results indicate that the novel hexagonal patch metasurface superstrate significantly reduces infrared emissivity and the measured emissivity of the structure is about 0.144 in 8-14µm infrared band. Meanwhile, the multilayered structure has a broadband absorption band from 2.32 GHz to 24.8 GHz with 7  mm thickness and is equipped with good angular stability under oblique incidence. In general, the method and specific design proposed in this work will benefit utilizing metasurface to implement bi-functional microwave and infrared camouflage materials with outstanding performances, which are promising for extensive applications.

Modular Toolbox as Snap Jewelry for Biomimetic Synthesis of Multifunctional Amino Acid Surfactants Inspired by Melanin.

Amino acid surfactants have gained significant importance in overcoming the limitations of conventional surfactants, notably, their low biocompatibility and biodegradability. However, the current amino acid surfactants lack multifunctional properties due to the nonreactivity of their aliphatic chains, necessitating the development of a new type of amino acid surfactant. A novel melanin-like amino acid surfactant and a biomimetic synthesis route were devised by mimicking the biosynthesis of melanin. Renewable natural polyphenol compounds with catechol moieties were utilized as building blocks for the hydrophobic group. In a proof-of-concept experiment, ethyl protocatechuate was oxidized to o-quinone and subsequently covalently linked to the amino group of lysine via Michael addition. The chemical structure was verified using liquid chromatography-tandem mass spectroscopy. The melanin-like amino acid surfactant exhibited excellent surface-active properties, with a critical micelle concentration of 1.59 mN m-1. Furthermore, it demonstrated remarkable emulsifying, foaming, solubilizing, dispersing, and wetting capabilities. Notably, it also possessed multifunctionality, including antibacterial activity, antioxidant activity, robustness, and mildness. These outstanding properties indicate significant potential for various applications. This strategy offers innovative insights and a versatile, modular toolbox for synthesizing multifunctional amino acid surfactants that mimic melanin. The approach allows for the easy interchange of o-quinone building blocks, which is akin to snap jewelry.

Spherical porous iron-nitrogen-carbon nanozymes derived from a tannin coordination framework for the preparation of L-DOPA by emulating tyrosine hydroxylase.

L-3,4-Dihydroxyphenylalanine (L-DOPA) is widely used in Parkinson's disease treatment and is therefore in high demand. Development of an efficient method for the production of L-DOPA is urgently required. Nanozymes emulating tyrosine hydroxylase have attracted enormous attention for biomimetic synthesis of L-DOPA, but suffered from heterogeneity. Herein, a spherical porous iron-nitrogen-carbon nanozyme was developed for production of L-DOPA. Tannic acid chelated with ferrous ions to form a tannin-iron coordination framework as a carbon precursor. Iron and nitrogen co-doped carbon nanospheres were assembled via an evaporation-induced self-assembly process using urea as a nitrogen source, F127 as a soft template, and formaldehyde as a crosslinker. The nanozyme was obtained after carbonization and acid etching. The nanozyme possessed a dispersive iron atom anchored in the Fe-N coordination structure as an active site to mimic the active center of tyrosine hydroxylase. The material showed spherical morphology, uniform size, high specific surface area, a mesoporous structure and easy magnetic separation. The structural properties could promote the density and accessibility of active sites and facilitate mass transport and electron transfer. The nanozyme exhibited high activity to catalyze the hydroxylation of tyrosine to L-DOPA as tyrosine hydroxylase in the presence of ascorbic acid and hydrogen peroxide. The titer of DOPA reached 1.2 mM. The nanozyme showed good reusability and comparable enzyme kinetics to tyrosine hydroxylase with a Michaelis-Menten constant of 2.3 mM. The major active species was the hydroxyl radical. Biomimetic simulation of tyrosine hydroxylase using a nanozyme with a fine structure provided a new route for the efficient production of L-DOPA.

Prediction of recurrent ischaemic stroke using radiomics data and machine learning methods in patients with acute ischaemic stroke: protocol for a multicentre, large sample, prospective observational cohort study in China.

INTRODUCTION: Stroke is a leading cause of mortality and disability worldwide. Recurrent strokes result in prolonged hospitalisation and worsened functional outcomes compared with the initial stroke. Thus, it is critical to identify patients who are at high risk of stroke recurrence. This study is positioned to develop and validate a prediction model using radiomics data and machine learning methods to identify the risk of stroke recurrence in patients with acute ischaemic stroke (AIS). METHODS AND ANALYSIS: A total of 1957 patients with AIS will be needed. Enrolment at participating hospitals will continue until the required sample size is reached, and we will recruit as many participants as possible. Multiple indicators including basic clinical data, image data, laboratory data, CYP2C19 genotype and follow-up data will be assessed at various time points during the registry, including baseline, 24 hours, 7 days, 1 month, 3 months, 6 months, 9 months and 12 months. The primary outcome was stroke recurrence. The secondary outcomes were death events, prognosis scores and adverse events. Imaging images were processed using deep learning algorithms to construct a programme capable of automatically labelling the lesion area and extracting radiomics features. The machine learning algorithms will be applied to integrate cross-scale, multidimensional data for exploratory analysis. Then, an ischaemic stroke recurrence prediction model of the best performance for patients with AIS will be established. Calibration, receiver operating characteristic and decision curve analyses will be evaluated. ETHICS AND DISSEMINATION: This study has received ethical approval from the Medical Ethics Committee of the Second Affiliated Hospital of Nanchang University (medical research review No.34/2021), and informed consent will be obtained voluntarily. The research findings will be disseminated through publication in journals and presented at conferences. TRIAL REGISTRATION NUMBER: ChiCTR2200055209.

Comparison of the Predictive Value of Inflammatory Biomarkers for the Risk of Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke.

Purpose: To investigate the predictive value of various inflammatory biomarkers in patients with acute ischemic stroke (AIS) and evaluate the relationship between stroke-associated pneumonia (SAP) and the best predictive index. Patients and Methods: We calculated the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), prognostic nutritional index (PNI), systemic inflammation response index (SIRI), systemic immune inflammation index (SII), Glasgow prognostic score (GPS), modified Glasgow prognostic score (mGPS), and prognostic index (PI). Variables were selectively included in the logistic regression analysis to explore the associations of NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI with SAP. We assessed the predictive performance of biomarkers by analyzing receiver operating characteristic (ROC) curves. We further used restricted cubic splines (RCS) to investigate the association. Next, we conducted subgroup analyses to investigate whether specific populations were more susceptible to NLR. Results: NLR, PLR, MLR, SIRI, SII, GPS, mGPS, and PI increased significantly in SAP patients, and PNI was significantly decreased. After adjustment for potential confounders, the association of inflammatory biomarkers with SAP persisted. NLR showed the most favorable discriminative performance and was an independent risk factor predicting SAP. The RCS showed an increasing nonlinear trend of SAP risk with increasing NLR. The AUC of the combined indicator of NLR and C-reactive protein (CRP) was significantly higher than those of NLR and CRP alone (DeLong test, P<0.001). Subgroup analyses suggested good generalizability of the predictive effect. Conclusion: NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI can predict the occurrence of SAP. Among the indices, the NLR was the best predictor of SAP occurrence. It can therefore be used for the early identification of SAP.

Accuracy comparison of tooth volume and mesiodistal diameter measurements for sex dimorphism based on cone-beam computed tomography: a study for the northern Chinese population.

Sex estimation based on teeth could help to narrow the scope for individual identification. According to the different teeth morphology among both genders, we plan to establish a sex estimation method for the northern Chinese population through mesiodistal diameter and teeth volume measurements and compare the accuracy of the two methods. In this study, measurements were taken from cone-beam computed tomography images collected from 142 males and 140 females aged 21-59 years. The mesiodistal diameter and volume of the left canines and the first molars in both upper and lower jaws were measured and analyzed for suitable coefficients. We selected 80% samples as the training set to set up the logistic regression formulas and 20% as the test set to obtain accuracy. The accuracy of sex estimation by mesiodistal diameter can reach 87.50%, and the volume is up to 78.57%. The measurement of mesiodistal diameter is less time-consuming. This work established and tested a method to estimate sex for the northern Chinese population. Results showed that sex estimation based on the mesiodistal diameter of teeth has higher accuracy than the method based on teeth volume.

Public exposure to broadband electromagnetic fields and its association with population density and building density: The case study of Beijing.

The gradual increase in electromagnetic field (EMF) exposure levels poses a potential threat to human health and the normal operation of electronic systems. In order to know the environmental EMF conditions, measurements were carried out on roads of about 400 km in the urban area of Beijing, China. The measurement results show that the electric field strength of about 89% of the sampling points is within 3 V/m, and the electric field strength of other sampling points is relatively high. Combined with further spectrum analysis, it was found that the electric field strength of one road section exceeded the national standard limits. In addition, to help quickly identify the general condition of the environmental EMF, a set of procedures for mining the association rules between the electric field strength and population density and building density is proposed in this paper. The final association rules show that the electric field strength is usually lower than 1.5 V/m in areas with medium or lower population density and areas with low building density; the electric field strength in areas with extremely high population density and areas with high building density is usually 1.5-4 V/m; while the electric field strength higher than 4 V/m mainly occurs in areas with extremely high population density. It is recommended to focus on strengthening the monitoring of EMF in areas with extremely high population density, and at the same time continuously pay attention to the trend of the urban EMF levels, so as to achieve early warning and treatment of relevant risks.

Real-time assay of invertase activity using isoquinolinylboronic acid as turn-on fluorescent sensor.

Invertase is the key enzyme involved in several crucial biological processes by hydrolyzing sucrose for production of glucose and fructose. Invertase plays important roles in the fields of food, pharmacy, cosmetics, biofuels, and agriculture. Detection of invertase activity is urgently necessary for scientific research and industrial processes. Herein, a continuous fluorometric method was developed for real-time detection of invertase activity. 8-Isoquinolinylboronic acid responded to fructose by formation of a fluorescent complex in turn-on manner, and served as a fluorescent sensor to selectively recognize fructose in ternary enzymatic mixture containing sucrose and glucose. The limit of detection (LOD) for fructose was 0.07 mM. Progress curve for fructose production was established by directly and continuously monitoring the fluorescence for invertase reaction with sucrose as substrate. Initial velocity was obtained to characterize invertase activity. LOD for invertase assay was 0.10 U·mL-1. Km and υmax for invertase were determined as 7.70 mM and 0.86 mM·min-1, respectively. Copper ion was demonstrated to inhibit the invertase activity with IC50 of 33.61 mM. Applicability in high-throughput screening for inhibitor was demonstrated. The proposed method allows for real-time, simple, and rapidly monitoring the invertase activity. It has a broad range of potential applications for kinetics and screening inhibitor.

Short-term efficacy and safety of personalized antiplatelet therapy for patients with acute ischaemic stroke or transient ischaemic attack: A randomized clinical trial.

AIMS: The aim of this study was to determine whether the testing strategy for clopidogrel and/or aspirin resistance using CYP2C19 genotyping or urinary 11-dhTxB2 testing has an impact on clinical outcomes. METHODS: A multicentre, randomized, controlled trial was conducted at 14 centres in China from 2019 to 2021. For the intervention group, a specific antiplatelet strategy was assigned based on the CYP2C19 genotype and 11-dhTxB2, a urinary metabolite of aspirin, and the control group received nonguided (ie, standard of care) treatment. 11-dhTXB2 is a thromboxane A2 metabolite that can help quantify the effects of resistance to aspirin in individuals after ingestion. The primary efficacy outcome was new stroke, the secondary efficacy outcome was a poor functional prognosis (a modified Rankin scale score ≥3), and the primary safety outcome was bleeding, all within the 90-day follow-up period. RESULTS: A total of 2815 patients were screened and 2663 patients were enrolled in the trial, with 1344 subjects assigned to the intervention group and 1319 subjects assigned to the control group. A total of 60.1% were carriers of the CYP2C19 loss-of-function allele (*2, *3) and 8.71% tested positive for urinary 11-dhTxB2- indicating aspirin resistance in the intervention group. The primary outcome was not different between the intervention and control groups (P = .842). A total of 200 patients (14.88%) in the intervention group and 240 patients (18.20%) in the control group had a poor functional prognosis (hazard ratio 0.77, 95% confidence interval [CI] 0.63 to 0.95, P = .012). Bleeding events occurred in 49 patients (3.65%) in the intervention group and 72 patients (5.46%) in the control group (hazard ratio 0.66, 95% CI 0.45 to 0.95, P = .025). CONCLUSIONS: Personalized antiplatelet therapy based on the CYP2C19 genotype and 11-dhTxB2 levels was associated with favourable neurological function and reduced bleeding risk in acute ischaemic stroke and transient ischaemic attack patients. The results may help support the role of CYP2C19 genotyping and urinary 11-dhTxB2 testing in the provision of precise clinical treatment.

Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics.

Purpose: This study aimed to investigate the value of a machine learning-based magnetic resonance imaging (MRI) radiomics model in predicting the risk of recurrence within 1 year following an acute ischemic stroke (AIS). Methods: The MRI and clinical data of 612 patients diagnosed with AIS at the Second Affiliated Hospital of Nanchang University from March 1, 2019, to March 5, 2021, were obtained. The patients were divided into recurrence and non-recurrence groups according to whether they had a recurrent stroke within 1 year after discharge. Randomized splitting was used to divide the data into training and validation sets using a ratio of 7:3. Two radiologists used the 3D-slicer software to label the lesions on brain diffusion-weighted (DWI) MRI sequences. Radiomics features were extracted from the annotated images using the pyradiomics software package, and the features were filtered using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Four machine learning algorithms, logistic regression (LR), Support Vector Classification (SVC), LightGBM, and Random forest (RF), were used to construct a recurrence prediction model. For each algorithm, three models were constructed based on the MRI radiomics features, clinical features, and combined MRI radiomics and clinical features. The sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were used to compare the predictive efficacy of the models. Results: Twenty features were selected from 1,037 radiomics features extracted from DWI images. The LightGBM model based on data with three different features achieved the best prediction accuracy from all 4 models in the validation set. The LightGBM model based solely on radiomics features achieved a sensitivity, specificity, and AUC of 0.65, 0.671, and 0.647, respectively, and the model based on clinical data achieved a sensitivity, specificity, and AUC of 0.7, 0.799, 0.735, respectively. The sensitivity, specificity, and AUC of the LightGBM model base on both radiomics and clinical features achieved the best performance with a sensitivity, specificity, and AUC of 0.85, 0.805, 0.789, respectively. Conclusion: The ischemic stroke recurrence prediction model based on LightGBM achieved the best prediction of recurrence within 1 year following an AIS. The combination of MRI radiomics features and clinical data improved the prediction performance of the model.

Automatic sex estimation using deep convolutional neural network based on orthopantomogram images.

Sex estimation is very important in forensic applications as part of individual identification. Morphological sex estimation methods predominantly focus on anatomical measurements. Based on the close relationship between sex chromosome genes and facial characterization, craniofacial hard tissues morphology shows sex dimorphism. In order to establish a more labor-saving, rapid, and accurate reference for sex estimation, the study investigated a deep learning network-based artificial intelligence (AI) model using orthopantomograms (OPG) to estimate sex in northern Chinese subjects. In total, 10703 OPG images were divided into training (80%), validation (10%), and test sets (10%). At the same time, different age thresholds were selected to compare the accuracy differences between adults and minors. The accuracy of sex estimation using CNN (convolutional neural network) model was higher for adults (90.97%) compared with minors (82.64%). This work demonstrated that the proposed model trained with a large dataset could be used in automatic morphological sex-related identification with favorable performance and practical significance in forensic science for adults in northern China, while also providing a reference for minors to some extent.

Reversal of the detrimental effects of social isolation on ischemic cerebral injury and stroke-associated pneumonia by inhibiting small intestinal γδ T-cell migration into the brain and lung.

Social isolation (ISO) is associated with an increased risk and poor outcomes of ischemic stroke. However, the roles and mechanisms of ISO in stroke-associated pneumonia (SAP) remain unclear. Adult male mice were single- or pair-housed with an ovariectomized female mouse and then subjected to transient middle cerebral artery occlusion. Isolated mice were treated with the natriuretic peptide receptor A antagonist A71915 or anti-gamma-delta (γδ) TCR monoclonal antibody, whereas pair-housed mice were treated with recombinant human atrial natriuretic peptide (rhANP). Subdiaphragmatic vagotomy (SDV) was performed 14 days before single- or pair-housed conditions. We found that ISO significantly worsened brain and lung injuries relative to pair housing, which was partially mediated by elevated interleukin (IL)-17A levels and the migration of small intestine-derived inflammatory γδ T-cells into the brain and lung. However, rhANP treatment or SDV could ameliorate ISO-exacerbated post-stroke brain and lung damage by reducing IL-17A levels and inhibiting the migration of inflammatory γδ T-cells into the brain and lung. Our results suggest that rhANP mitigated ISO-induced exacerbation of SAP and ischemic cerebral injury by inhibiting small intestine-derived γδ T-cell migration into the lung and brain, which could be mediated by the subdiaphragmatic vagus nerve.

Biomimetic synthesis of hydroxytyrosol from conversion of tyrosol by mimicking tyrosine hydroxylase.

Hydroxytyrosol, one of the most powerful natural antioxidants, exhibits certificated benefits for human health. In this study, a biomimetic approach to synthesize hydroxytyrosol from the hydroxylation of tyrosol was established. EDTA-Fe2+ coordination complex served as an active center to simulate tyrosine hydroxylase. H2O2 and ascorbic acid were used as oxygen donor and hydrogen donor, respectively. Hydroxy radical and singlet oxygen contributed to active species. The biomimetic system displayed analogous component, structure, and activity with TyrH. Hydroxytyrosol titer of 21.59 mM, and productivity of 9985.92 mg·L-1·h-1 was achieved with 100 mM tyrosol as substrate. The proposed approach provided efficient and convenient route to quickly produce high amount of hydroxytyrosol.

Inhibitory mechanism of scutellarein on tyrosinase by kinetics, spectroscopy and molecular simulation.

Tyrosinase plays an important role in melanin synthesis. Inhibition against tyrosinase activity has been extensively focused on for pharmaceutical, food, cosmetic, and agricultural purpose. The inhibitory mechanism of scutellarein on tyrosinase was elaborated by coupling enzyme kinetics, multi-spectroscopy and computational simulation. Scutellarein remarkably inhibited tyrosinase activity with an IC50 value of 91 µM. Scutellarein reversibly inhibited tyrosinase in a competitive manner. Fluorescence quenching validated that interaction of scutellarein with tyrosinase occurred to form a complex with a binding constant of 6.11 × 104 M-1. Thermodynamic parameters suggested that scutellarein spontaneously bound with tyrosinase via hydrogen bond and van der Waals force. Three-dimensional fluorescence spectra and circular dichroism spectra revealed that scutellarein induced an obvious conformational change in tyrosinase. Molecular docking result predicted that scutellarein mainly bound with tyrosinase via Arg268 residue. Scutellarein effectively controlled the enzymatic browning of apple slices during storage. This research could give theoretical guiding significance in various application for tyrosinase inhibitors.

Determination of monophenolase activity based on backpropagation neural network analysis of three-dimensional fluorescence spectroscopy.

Tyrosinase is pivotal for melanin formation. Measuring monophenolase activity is of great importance for both fundamental research and industrial applications. For the first time, a backpropagation (BP) artificial neural network with three-dimensional fluorescence spectroscopy was applied for the real-time determination of tyrosinase monophenolase activity. Principal component analysis (PCA) was utilized for the dimension reduction of three-dimensional fluorescence data. The four principal components served as inputs for the neural network. Network parameters were optimized using a genetic algorithm (GA). BP learning algorithm was applied to train the network model to determine tyrosine levels in a binary mixture containing tyrosine and L-DOPA without any chemical separation. The time course of tyrosine consumption by monophenolase was determined to calculate the initial velocity of the enzymatic reaction. The limit of detection of the monophenolase assay was 0.0615 U·mL-1. This combined strategy of PCA, GAs, and BP artificial neural networks for three-dimensional fluorescence spectroscopy was efficient for the real-time and in-situ determination of monophenolase activity in a cascade reaction.