Niobium-Based Oxide for Anode Materials for Lithium-Ion Batteries.

Recently, it has become imperative to develop high energy density as well as high safety lithium-ion batteries (LIBS) to meet the growing energy demand. Among the anode materials used in LIBs, the currently used commercial graphite has low capacity and is a safety hazard due to the formation of lithium dendrites during the reaction. Among the transition metal oxide (TMO) anode materials, TMO based on the intercalation reaction mechanism has a more stable structure and is less prone to volume expansion than TMO based on the conversion reaction mechanism, especially the niobium-based oxide in it has attracted much attention. Niobium-based oxides have a high operating potential to inhibit the formation of lithium dendrites and lithium deposits to ensure safety, and have stable and fast lithium ion transport channels with excellent multiplicative performance. This review summarizes the recent developments of niobium-based oxides as anode materials for lithium-ion batteries, discusses the special structure and electrochemical reaction mechanism of the materials, the synthesis methods and morphology of nanostructures, deficiencies and improvement strategies, and looks into the future developments and challenges of niobium-based oxide anode materials.

SnO2/Sn with core-shell structure Schottky heterojunctions loaded in graphene to promote electrochemical reaction kinetics and enable efficient lithium-ion storage.

The stannic oxide (SnO2) anode expands in volume during cycling causing a decrease in reversible capacity. In this work, we generated a spherical SnO2/Sn heterojunction with core-shell structure composites encapsulated by graphene (SnO2/Sn/G) in situ using a simple one-step hydrothermal and subsequent annealing process. SnO2/Sn heterojunction nanospheres dispersed in a porous graphene framework accelerate the diffusion kinetics of electrons and ions. In addition, the structure plays a key role in mitigating large volume changes and nanostructure agglomeration. As a result, SnO2/Sn/G exhibits excellent performance as an anode material for lithium-ion batteries (LIBs), maintaining a reversible specific capacity of 720.6 mA h g-1 even after 600 cycles at a current density of 0.5 A g-1.

Synthesis of heterointerfaces in NiO/SnO2 coated nitrogen-doped graphene for efficient lithium storage.

Currently, it remains a challenge to make comprehensive improvements to overcome the disadvantages of volume expansion, Li2O irreversibility and low conductivity of SnO2. Heterostructure construction has been investigated as an effective strategy to promote electron transfer and surface reaction kinetics, leading to high electrochemical performance. Herein, NiO/SnO2 heterojunction modified nitrogen doped graphene (NiO/SnO2@NG) anode materials were prepared using hydrothermal and carbonization techniques. Based on the excellent structural advantages, sufficiently small NiO/SnO2 heterojunction nanoparticles increase the interfacial density to promote Li2O decomposition, and the built-in electric field accelerates the charge transport rate to improve the conductivity. The three-dimensional porous graphene framework effectively mitigates volume expansion during cycling and stabilizes the reactive interface of electrode materials. The results show that the NiO/SnO2@NG mixture has high reversible specific capacity (938.8 mA h g-1 after 450 cycles at 0.1 A g-1), superior multiplicity performance (374.5 mA h g-1 at 3.0 A g-1) and long cycle life (685.3 mA h g-1 after 1000 cycles at 0.5 A g-1). Thus, this design of introducing NiO to form heterostructures with SnO2 is directly related to enhancing the electrochemical performance of lithium-ion batteries (LIBs).

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.

Polymorphism of neurodegeneration-related genes associated with Parkinson's disease risk.

BACKGROUND: Neurodegenerative genes are critical in neuronal loss in Parkinson's disease (PD). We performed a systematic meta-analysis including all the studies published on PD risk related to genes encoding enzymes vital for dopamine metabolism and neuron survival. METHODS: We included neurodegeneration-related genes which were divided into four groups according to their functions: main enzymes in dopamine metabolism, receptors and transporters for dopamine or other metabolites, neuroprotective factors for dopaminergic neurons, and genes associated with dopaminergic neurons survival reported in other neurological diseases. We collected original articles from PubMed, Embase, and Web of Science databases. Revman 5.3 software was used to analyze data. The allele model (AM) was used to test the effect size of the effect allele between the case group and the control group and secondary analysis using the dominant model (DM) and recessive model (RM) to analyze the contributions from heterozygote and homozygote to the allele risk. Odds ratio (OR) and 95% confidence interval (CI) were used to present the pooled results. RESULTS: We included 31 variants in 20 genes for the final pooled analysis. Consequently, SLC6A4/5-HTT HTTLPR, BDNF rs56164415, FGF20 rs1721100, PARK16 rs823128, rs823156, rs947211, APOE e2, A2M rs669, RIT2 rs12456492, MAPT intron 9 H1H2, and STH rs62063857 variants were statistically associated with PD risk while researched variants in COMT, DBH, MAO, DAT/SLC6A3, DRD2, GRIN2B, GSK3ß, ATP13A2, LINGO1, PICALM, and GRN were not related to PD risk. CONCLUSION: Several variants from neurodegeneration-related genes are associated with PD risk, which may help deepen the understanding of PD pathogenesis and improve clinical treatment strategies.

Treatment of Short Stature with Aromatase Inhibitors: A Systematic Review and Meta-Analysis.

The objective of the study is to determine the risks and benefits of treating idiopathic short stature (ISS) with aromatase inhibitors (AIs). We comprehensively searched PubMed, Embase, and the China National Knowledge Infrastructure between establishment year and January 31, 2020. Mean difference (MD)/Standardized mean differences (SMD) with 95% confidence intervals (CI) of individual studies were pooled using fixed or random effects models. Subgroup and sensitivity analyses were also performed. Publication bias was estimated using funnel plots and Egger tests. Fourteen studies including 388 participants were included. The meta-analysis results showed that AIs significantly increased final height (MD=2.46, 95% CI: 0.8-4.12) and predicted adult height (MD=0.34, 95% CI: 0.11-0.57). Changes in bone age (MD=-0.1, 95% CI: -0.86-0.66) and bone mineral density (MD=-0.05, 95% CI: -0.19-0.1) were not different between intervention and control group. AI significantly increased testosterone level (SMD=2.01, 95% CI: 0.8-3.23) and reduced estradiol level (SMD=-1.13, 95% CI: -1.87 to -0.40); The intervention and control group had no significant differences in the levels of high-density lipoprotein-cholesterol (SMD=-0.31, 95%CI: -0.68-0.06) and IGF-1 (SMD=0.7, 95% CI: -0.66-2.06) levels. Adverse events were more frequent in the intervention group than in the control group (odds ratio=3.12, 95% CI: 1.44-6.73). In conclusion, both AI monotherapy and AI combination therapy can increase predicted adult height and testosterone levels.

Quantum dot heterostructures on N-doped graphene with accelerated diffusion kinetics for stable lithium-ion storage.

The high energy density and low self-discharge rate of lithium-ion batteries make them promising for large-scale energy storage. However, the practical development of such electrochemical energy storage systems relies heavily on the development of anode materials with high multiplier capacity and stable cycle life. Here, a simple and efficient one-step hydrothermal method is used to obtain stannide heterostructures, which are loaded on N-doped graphene (SnS2/SnO2@NG) that promotes Li+ diffusion for fast charge transfer. It is demonstrated that the built-in electric field generated by the electron transfer from electron-rich SnS2 to SnO2 in the stannide heterojunction collectively provides abundant cation adsorption sites, accelerating the migration of Li+ thus improving the electrochemical reaction kinetics. Besides, the SnS2/SnO2 nanoparticles have high structural stability, and the heterojunction compressive stresses obtained from density functional theory (DFT) calculations can significantly limit the structural damage. When applied as anodes in Li+ batteries with 300 cycles at 0.5 A/g, we achieved a high reversible capacity of 892.73 mAh/g. The rational design of low-cost batteries for energy storage and conversion can benefit from the quantitative design of fast and persistent charge transfer in a stannide heterostructure.

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.

The Role of m6A RNA Methylation-Related lncRNAs in the Prognosis and Tumor Immune Microenvironment of Papillary Thyroid Carcinoma.

Emerging evidence has indicated that N6-methylandenosine (m6A) RNA methylation plays a critical role in cancer development. However, the function of m6A RNA methylation-related long noncoding RNAs (m6A-lncRNAs) in papillary thyroid carcinoma (PTC) has never been reported. This study aimed to investigate the role of m6A-lncRNAs in the prognosis and tumor microenvironment (TME) of PTC. Three subgroups (clusters 1, 2, and 3) were identified by consensus clustering of 19 prognosis-related m6A-lncRNA regulators, of which cluster 1 is preferentially related to unfavorable prognosis, lower immune scores, and distinct immune infiltrate level. A risk-score model was established based on 8 prognosis-related m6A-lncRNAs. Patients with a high-risk score showed a worse prognosis, and the ROC indicated a reliable prediction performance for patients with PTC (AUC = 0.802). As expected, the immune scores, the infiltration levels of immune cells, and ESTIMATE scores in the low-risk subgroups were notably higher (p < 0.001) when compared with those in high-risk subgroups. Furthermore, GSEA analysis revealed that tumor associated pathways, hallmarks, and biological processes were remarkably enriched in the high-risk subgroup. Further analysis indicated that the risk score and age were independent prognostic factors for PTC. An integrated nomogram was constructed that accurately predicted the survival status (AUC = 0.963). Moreover, a lncRNA-miRNA-mRNA regulated network was established based on seven prognosis-related m6A-lncRNAs. In addition, 30 clinical samples and different PTC cells were validated. This is the first study to reveal that m6A-lncRNAs plays a vital role in the prognosis and TME of PTC. To a certain degree, m6A-lncRNAs can be considered as new, promising prognostic biomarkers and treatment targets.

Does CYP2C19 polymorphisms affect neurological deterioration in stroke/TIA patients?: A systematic review and meta-analysis of prospective cohort studies.

BACKGROUND: The association between cytochrome P450 2C19 (CYP2C19) polymorphisms and neurological deterioration in stroke or transient ischemic attack (TIA) patients is not completely understood. Hence, we performed a systematic review and meta-analysis of prospective cohort studies to quantify this association. METHODS: PubMed, Cochrane Library, Excerpta Medica Database, China National Knowledge Infrastructure and WanFang databases were searched for studies published up to April 2019. Prospective cohort studies that reported an association between CYP2C19 polymorphisms and neurological deterioration in stroke/TIA patients were included. Data on risk ratio (RR) and 95% confidence intervals (CI) were extracted and pooled by the authors. Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines were followed. RESULTS: Twelve eligible studies were included. Twelve studies reported CYP2C19∗2, ∗3 loss-of-function alleles and 5 studies reported CYP2C19∗17 gain-of-function allele. Compared to non-carriers, carriers of CYP2C19∗2, ∗3 loss-of-function alleles had a significantly higher risk of neurological deterioration (RR, 1.63; 95%CI, 1.32-2.02). Conversely, carriers of CYP2C19∗17 gain-of-function allele had a significantly lower risk of neurological deterioration (RR, 0.520; 95%CI, 0.393-0.689) compared to non-carriers. CONCLUSIONS: This meta-analysis demonstrated that the carriers of CYP2C19∗2, ∗3 loss-of-function alleles have an increased risk of neurological deterioration compared to non-carriers in stroke or TIA patients. Additionally, CYP2C19∗17 gain-of-function allele can reduce the risk of neurological deterioration.

Personalized antiplatelet therapy based on clopidogrel/aspirin resistance tests in acute ischemic stroke and transient ischemic attack: Study protocol of a multi-center, single-blinded and randomized controlled trial.

BACKGROUND: Clopidogrel and aspirin are key intervention for acute ischemic stroke (AIS) and transient ischemic attack (TIA). However, with increased clinical application, many patients have shown clopidogrel resistance (CR) and/or aspirin resistance (AR) that affect antiplatelet therapy on AIS/TIA. At present, there is no research reported on personalized antiplatelet therapy guidelines for patients with CR and/or AR. Our study aims to assess the effect of personalized antiplatelet therapy based on CYP2C19 genotype and urine 11-dhTxB2 tests in patients with AIS or TIA. METHODS: This is a multi-center randomized controlled trial. Eligible patients with AIS/TIA from 14 comprehensive hospitals in Jiangxi province will be recruited after obtaining informed consent. Participants will be randomly divided into the intervention group and the control group at a ratio of 1:1. personalized antiplatelet therapy based on the CYP2C19 genotype/urine11-dhTxB2 tests will be given to the intervention group. Demographics, disease history, laboratory investigations, therapys, physiological tests, imaging reports and other clinical features will be collected. Clinical outcomes including stroke recurrence, Modified Rankin Scale (mRS) score, bleeding events and all-cause mortality will be assessed at the 1st, 3rd, 6th, and 12th-month post-discharge. DISCUSSION: Our study will conduct free antiplatelet resistance tests and personalized antiplatelet therapy for AIS/TIA patients with CR/AR, ultimately evaluating personalized therapy effectiveness through one-year follow-up. The research results will help to assess the impact of personalized antiplatelet therapy on the prognosis of stroke, thus providing reference for precise clinical treatment.