Prediction model of measurement errors in current transformers based on deep learning.

The long-term monitoring stability of electronic current transformers is crucial for accurately obtaining the current signal of the power grid. However, it is difficult to accurately distinguish between the fluctuation of non-stationary random signals on the primary side of the power grid and the gradual error of the transformers themselves. A current transformer error prediction model, CNN-MHA-BiLSTM, based on the golden jackal optimization (GJO) algorithm, which is used to obtain the optimal parameter values, bidirectional long short-term memory (BiLSTM) network, convolutional neural networks (CNNs), and multi-head attention (MHA), is proposed to address the difficulty of measuring error evaluation. This model can be used to determine the operation of transformers and can be widely applied to assist in determining the stability of transformer operation and early faults. First, CNN is used to mine the vertical detail features of error data at a certain moment, improving the speed of error prediction. Furthermore, a cascaded network with BiLSTM as the core is constructed to extract the horizontal historical features of the error data. The GJO algorithm is used to adjust the parameters of the BiLSTM model; optimize the hidden layer nodes, training frequency, and learning rate; and integrate MHA mechanism to promote the model to pay attention to the characteristic changes of the data in order to improve the accuracy of error prediction. Finally, this method is applied to the operation data of transformer in substations, and four time periods of data are selected to verify the model effectiveness of the current transformer dataset. The analysis results of single step and multi-step examples indicate that the proposed model has significant advantages in terms of accuracy and stability in error prediction.

Associations of per- and polyfluoroalkyl substances (PFAS) and their mixture with risk of rheumatoid arthritis in the U.S. adult population.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are known environmental contaminants with immunosuppressive properties. Their connection to rheumatoid arthritis (RA), a condition influenced by the immune system, is not well studied. This research explores the association between PFAS exposure and RA prevalence. METHODS: This research utilized data from the NHANES, encompassing a sample of 10,496 adults from the 2003-2018 cycles, focusing on serum levels of several PFAS. The presence of RA was determined based on self-reports. This study used multivariable logistic regression to assess the relationship between individual PFAS and RA risk, adjusting for covariates to calculate odds ratios (ORs). The combined effects of PFAS mixtures were evaluated using BKMR, WQS regression, and quantile g-computation. Additionally, sex-specific associations were explored through stratified analysis. RESULTS: Higher serum PFOA (OR = 0.88, 95% CI: 0.79, 0.98), PFHxS (OR = 0.91, 95% CI: 0.83, 1.00), PFNA (OR = 0.87, 95% CI: 0.77, 0.98), and PFDA (OR = 0.89, 95% CI: 0.81, 0.99) concentration was related to lower odds of RA. Sex-specific analysis in single chemical models indicated the significant inverse associations were only evident in females. BKMR did not show an obvious pattern of RA estimates across PFAS mixture. The outcomes of sex-stratified quantile g-computation demonstrated that an increase in PFAS mixture was associated with a decreased odds of RA in females (OR: 0.76, 95% CI: 0.62, 0.92). We identified a significant interaction term of the WQS*sex in the 100 repeated hold out WQS analysis. Notably, a higher concentration of the PFAS mixture was significantly associated with reduced odds of RA in females (mean OR = 0.93, 95% CI: 0.88, 0.98). CONCLUSIONS: This study indicates potential sex-specific associations of exposure to various individual PFAS and their mixtures with RA. Notably, the observed inverse relationships were statistically significant in females but not in males. These findings contribute to the growing body of evidence indicating that PFAS may have immunosuppressive effects.

Broad/narrowband switchable terahertz absorber based on Dirac semimetal and strontium titanate for temperature sensing.

A broadband and narrowband switchable terahertz (THz) absorber based on a bulk Dirac semimetal (BDS) and strontium titanate (STO) is proposed. Narrowband and broadband absorption can be switched by adjusting the Fermi level of the BDS. When the Fermi level of the BDS is 100 meV, the device is an absorber with three narrowband absorption peaks. The frequencies are 0.44, 0.86, and 1.96 THz, respectively, when the temperature of STO is 250 K. By adjusting the temperature of STO from 250 to 500 K, the blue shifts of the frequencies are approximately 0.14, 0.32, and 0.60 THz, respectively. The sensitivities of the three absorption peaks are 0.56, 1.27, and 2.38 GHz/K, respectively. When the Fermi level of the BDS is adjusted from 100 to 30 meV, the device can be switched to a broadband absorber with a bandwidth of 0.70 THz. By adjusting the temperature of STO from 250 to 500 K, the central frequency shifts from 1.40 to 1.79 THz, and the bandwidth broadens from 0.70 to 0.96 THz. The sensitivity of the central frequency is 1.57 GHz/K. The absorber also has a wide range of potential applications in multifunctional tunable devices, such as temperature sensors, stealth equipment, and filters.

Neonatal stress disrupts the glymphatic system development and increases the susceptibility to Parkinson's disease in later life.

INTRODUCTION: Neonatal stress disrupts brain development and increases the risk of neurological disorders later in life. However, the impact of neonatal stress on the development of the glymphatic system and susceptibility to Parkinson's disease (PD) remains largely unknown. METHODS: Neonatal maternal deprivation (NMD) was performed on mice for 14 consecutive days to model chronic neonatal stress. Adeno-associated virus expressing A53T-α-synuclein (α-syn) was injected into the substantia nigra to establish PD model mice. Glymphatic activity was determined using in vivo magnetic resonance imaging, ex vivo fluorescence imaging and microplate assay. The transcription and expression of aquaporin-4 (AQP4) and other molecules were evaluated by qPCR, western blotting, and immunofluorescence. Animal's responses to NMD and α-syn overexpression were observed using behavioral tests. RESULTS: Glymphatic activity was impaired in adult NMD mice. AQP4 polarization and platelet-derived growth factor B (PDGF-B) signaling were reduced in the frontal cortex and hippocampus of both young and adult NMD mice. Furthermore, exogenous α-syn accumulation was increased and PD-like symptoms were aggravated in adult NMD mice. CONCLUSION: The results demonstrated that NMD could disrupt the development of the glymphatic system through PDGF-B signaling and increase the risk of PD later in life, indicating that alleviating neonatal stress could be beneficial in protecting the glymphatic system and reducing susceptibility to neurodegeneration.

Efficacy and safety of Nafamostat mesylate in patients with end-stage renal failure.

BACKGROUND: Recent studies on dialysis anticoagulation therapy in patients with renal failure have shown that Nafamostat mesylate, a broad-spectrum potent serine protease inhibitor, has strong anticoagulation and anti-fiber activity. AIM: To evaluate the efficacy and safety of Nafamostat mesylate in patients with end-stage renal failure. METHODS: Seventy-five patients with end-stage renal failure who received hemodialysis at our hospital between January 2020 and August 2021 were selected and divided into the observation group (Nafamostat mesylate for injection, n = 33) and control group (heparin sodium injection, n = 32). General patient data, indicators of clinical efficacy, dialyzer hemocoagulation parameters, coagulation function indices, and hemoglobin concentration and platelet count before and after treatment, and the occurrence of adverse reactions after treatment were compared between the two groups. RESULTS: The two groups showed no significant differences in general patient data (P > 0.05). The post-treatment effectiveness rate in the control group was lower than that in the observation group (P < 0.05). The two groups showed no significant difference in the number of patients in grade I (P > 0.05), while the number of patients in grade 0 was lower in the control group, and the number of patients in grades II and III was higher in the control group (P < 0.05). The post-treatment prothrombin time, activated partial thromboplastin time, thrombin time, and international normalized ratio values in the control group were higher than those in the observation group, while the fibrinogen level in the control group was lower than that in the observation group (P < 0.05). The two groups showed no significant difference in the platelet count and hemoglobin level before and after treatment (P > 0.05). The total number of post-treatment adverse reactions in the observation group was lower than that in the control group (P < 0.05). CONCLUSION: Treatment of patients showing end-stage renal failure with Nafamostat mesylate can significantly improve therapeutic efficacy and has high safety and clinical value.

Joint effects of prenatal exposure to air pollution and pregnancy-related anxiety on birth weight: A prospective birth cohort study in Ma'anshan, China.

BACKGROUND: A growing number of studies have shown that prenatal exposure to chemical and non-chemical stressors has effects on fetal growth. The co-exposure of both better reflects real-life exposure patterns. However, no studies have included air pollutants and pregnancy-related anxiety (PrA) as mixtures in the analysis. METHOD: Using the birth cohort study method, 576 mother-child pairs were included in the Ma'anshan Maternal and Child Health Hospital. Evaluate the exposure levels of six air pollutants during pregnancy using inverse distance weighting (IDW) based on the pregnant woman's residential address and air pollution data from monitoring stations. Prenatal anxiety levels were assessed using the PrA Questionnaire. Generalized linear regression (GLR), quantile g-computation (QgC) and bayesian kernel machine regression (BKMR) were used to assess the independent or combined effects of air pollutants and PrA on birth weight for gestational age z-score (BWz). RESULT: The results of GLR indicate that the correlation between the six air pollutants and PrA with BWz varies depending on the different stages of pregnancy and pollutants. The QgC shows that during trimester 1, when air pollutants and PrA are considered as a whole exposure, an increase of one quartile is significantly negatively correlated with BWz. The BKMR similarly indicates that during trimester 1, the combined exposure of air pollutants and PrA is moderately correlated with a decrease in BWz. CONCLUSION: Using the method of analyzing mixed exposures, we found that during pregnancy, the combined exposure of air pollutants and PrA, particularly during trimester 1, is associated with BWz decrease. This supports the view that prenatal exposure to chemical and non-chemical stressors has an impact on fetal growth.

The effects of gestational diabetes mellitus on fetal growth: is it different for low-risk and medium-high-risk pregnant women?

BACKGROUND: It has been suggested that gestational diabetes mellitus (GDM) alters the growth trajectory of a fetus and increases the risk of abnormal birth weight. In spite of this, there is still a significant debate regarding the mode and optimal timing of diagnosing this condition. Our aim was to determine fetal growth velocity and birth biometry in pregnant women with GDM at varying risk levels. METHODS: We conducted a cohort study involving 1023 pregnant women at a maternity hospital in Ma'anshan, China. All women completed an oral glucose tolerance test at 24-28 weeks' gestation. We measured fetal head circumference (HC), femoral length (FL), abdominal circumference (AC), biparietal diameter (BPD), and estimate fetal weight (EFW) by ultrasound at 17, 24, 31, and 35 weeks' gestation, respectively. RESULTS: Overall, 5115 ultrasound scans were performed. Among both low-risk and medium-high-risk pregnant women at 17-24 weeks' gestation, GDM exposure was associated with an increase in fetal growth velocity. Neonates born to women with GDM at medium-high risk had significantly larger birth weights than those born to women without GDM, while this was not observed in women at low risk. CONCLUSION: In medium-high-risk pregnant women, exposure to GDM has a greater effect on the fetus, leading to abnormal fetal growth velocity that lasts beyond week 24. It is evident from our results that the effects of GDM on fetal growth differ between medium-high-risk pregnant women and low-risk pregnant women, and therefore a different screening program based on the risk factor for GDM is warranted.

Investigation on application of filling mining technology pass through abandoned roadway of reclaimed working face.

This paper aims to analyze the roof stability when the reclaimed working face passes through abandoned roadway. The mechanical model of main roof in abandoned roadway was established for the purpose of theoretical analyses. To ensure the stability of the abandoned roadway, the strength formula of backfill body was deduced. The optimum ratios among different compositions of the filling material were determined by experiment, while the viscosity, bleeding, hydration temperature and compressive strength of filling material were also studied. Test results indicated that the optimum ratio among coal ash, lime and compound activator is 80:15:5, and the ideal water cement ratio is 0.7:1. It was also found that no bleeding occurred, the rheological behavior of slurry presented shear thinning fluid and the hydration temperature of filling body was relatively stable which is mainly maintained at 40°C. The uniaxial compressive strength of filling material with 28 and 90 days curing were 3.35 and 6.62 MPa respectively. Under a confining pressure environment, the filling material presented an obviously plastic deformation. Field test showed that the filling rate was almost 100%, when working face passed through abandoned roadway, the surface of filled body was complete and no roof collapse was triggered. Therefore, a better bonding effect was proved for the filling body.

Association of urinary heavy metal combined exposure with periodontitis among US adults from NHANES 2011-2014.

Some heavy metals are associated with periodontitis; whereas most of these associations have focused on individual metal, there are no specific studies on the effects of combined heavy metal exposure on periodontitis. We conducted an analysis on the association between urinary heavy metal exposure and periodontitis in participants aged 30 years and older using multiple logistic regression and Bayesian kernel machine regression (BKMR). This analysis was performed on data from the National Health and Nutrition Examination Survey from 2011 to 2014. The study found that using logistic regression, the 4th quartile of urinary lead and molybdenum and the 3rd quartile of urinary strontium were positively associated with periodontitis compared to the reference quartile after adjusting for covariates. Odds ratio (OR) with 95% confidence interval (CI) was 1.738 (1.069-2.826), 1.515 (1.025-2.239), and 1.498 (1.010-2.222), respectively. The 3rd and 4th quartiles of urinary cobalt were negatively associated with periodontitis, and their ORs and 95% CIs were 0.639 (0.438-0.934) and 0.571 (0.377-0.964), respectively. The BKMR model showed that urinary barium, lead, and molybdenum were positively associated with periodontitis in a range of concentrations and urinary cobalt, manganese, tin, and strontium were negatively correlated with periodontitis. Furthermore, the overall association between urinary heavy metals and periodontitis was positive. Our study provides evidence for an association between exposure to multiple urinary heavy metals and periodontitis. However, further longitudinal studies are needed to explore the specific mechanisms involved.

Effect of gaseous pollutant and greenness exposure on mortality during treatment of newly treated tuberculosis patients: a provincial population-based cohort study.

BACKGROUND: Previous studies addressing the impact of environmental factors on TB prognosis are scarce, with only some studies examining the effect of particulate pollutants on TB mortality. Moreover, few studies have evaluated the effects of multiple gaseous pollutants and greenness exposures on newly treated TB patients on a large population scale. METHODS: Through the Centers for Disease Control and Prevention, data were collected from January 1, 2015 to December 31, 2020 for newly treated TB patients in Anhui Province, China. Data on gaseous pollutants sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone were collected through the National Earth System Science Data Center of China. Normalized vegetation index data were obtained through NASA. The Cox proportional risk model was also applied to calculate the hazard ratios of SO2, NO2, CO, O3, and NDVI with 95% confidence intervals for mortality among newly treated TB patients. RESULTS: Multifactorial Cox regression analysis showed that for every 0.10 µg/m3 increase in SO2, the risk of death among newly treated TB patients increased by 13.2% (HR = 1.132, 95% CI: 1.045-1.1.225), for every 10 µg/m3 increase in NO2, the risk of death among newly treated TB patients increased by 11.4%, and for each 0.1 mg/m3 increase in CO, the risk of death among newly treated TB patients increased by 5.8%. For each 0.1 increase in NDVI 250m-buffer and 500m-buffer, the risk of death among newly treated TB patients decreased by 8.5% and 6.4%, respectively. The effect of gaseous pollutants on mortality decreased progressively with elevated greenness exposure when greenness exposure was grouped from low to high. CONCLUSION: Gaseous pollutants are a risk factor during the treatment of newly treated TB patients and greenness exposure is a protective factor. Higher greenness exposure reduces the risk of death due to exposure to gaseous pollutants.

The modification of meteorological factors on the relationship between air pollution and periodontal diseases: an exploration based on different interaction strategies.

We aimed to characterize the association between air pollutants exposure and periodontal diseases outpatient visits and to explore the interactions between ambient air pollutants and meteorological factors. The outpatient visits data of several large stomatological and general hospitals in Hefei during 2015-2020 were collected to explore the relationship between daily air pollutants exposure and periodontal diseases by combining Poisson's generalized linear model (GLMs) and distributed lag nonlinear model (DLNMs). Subgroup analysis was performed to identify the vulnerability of different populations to air pollutants exposure. The interaction between air pollutants and meteorological factors was verified in both multiplicative and additive interaction models. An interquartile range (IQR) increased in nitrogen dioxide (NO2) concentration was associated with the greatest lag-specific relative risk (RR) of gingivitis at lag 3 days (RR = 1.087, 95% CI 1.008-1.173). Fine particulate matter (PM2.5) exposure also increased the risk of periodontitis at the day of exposure (RR = 1.049, 95% CI 1.004-1.096). Elderly patients with gingivitis and periodontitis were both vulnerable to PM2.5 exposure. The interaction analyses showed that exposure to high levels of NO2 at low temperatures was related to an increased risk of gingivitis, while exposure to high levels of NO2 and PM2.5 may also increase the risk of gingivitis and periodontitis in the high-humidity environment, respectively. This study supported that NO2 and PM2.5 exposure increased the risk of gingivitis and periodontitis outpatient visits, respectively. Besides, the adverse effects of air pollutants exposure on periodontal diseases may vary depending on ambient temperature and humidity.

Identification of AKI signatures and classification patterns in ccRCC based on machine learning.

Background: Acute kidney injury can be mitigated if detected early. There are limited biomarkers for predicting acute kidney injury (AKI). In this study, we used public databases with machine learning algorithms to identify novel biomarkers to predict AKI. In addition, the interaction between AKI and clear cell renal cell carcinoma (ccRCC) remain elusive. Methods: Four public AKI datasets (GSE126805, GSE139061, GSE30718, and GSE90861) treated as discovery datasets and one (GSE43974) treated as a validation dataset were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between AKI and normal kidney tissues were identified using the R package limma. Four machine learning algorithms were used to identify the novel AKI biomarkers. The correlations between the seven biomarkers and immune cells or their components were calculated using the R package ggcor. Furthermore, two distinct ccRCC subtypes with different prognoses and immune characteristics were identified and verified using seven novel biomarkers. Results: Seven robust AKI signatures were identified using the four machine learning methods. The immune infiltration analysis revealed that the numbers of activated CD4 T cells, CD56dim natural killer cells, eosinophils, mast cells, memory B cells, natural killer T cells, neutrophils, T follicular helper cells, and type 1 T helper cells were significantly higher in the AKI cluster. The nomogram for prediction of AKI risk demonstrated satisfactory discrimination with an Area Under the Curve (AUC) of 0.919 in the training set and 0.945 in the testing set. In addition, the calibration plot demonstrated few errors between the predicted and actual values. In a separate analysis, the immune components and cellular differences between the two ccRCC subtypes based on their AKI signatures were compared. Patients in the CS1 had better overall survival, progression-free survival, drug sensitivity, and survival probability. Conclusion: Our study identified seven distinct AKI-related biomarkers based on four machine learning methods and proposed a nomogram for stratified AKI risk prediction. We also confirmed that AKI signatures were valuable for predicting ccRCC prognosis. The current work not only sheds light on the early prediction of AKI, but also provides new insights into the correlation between AKI and ccRCC.

[Acupuncture at "umbilical four-acupoints" for chronic insomnia and its comorbid symptoms].

OBJECTIVE: To observe the effects of acupuncture at "umbilical four-acupoints" on chronic insomnia and its comorbid symptoms. METHODS: A total of 120 patients with chronic insomnia were randomly divided into an observation group (60 cases, 8 cases dropped off) and a control group (60 cases, 5 cases dropped off). The patients in the observation group were treated with acupuncture at regular acupoints (Baihui [GV 20] and bilateral Shenmen [HT 7], Neiguan [PC 6], Anmian [Extra]) and "umbilical four-acupoints", while the patients in the control group were treated with acupuncture at regular acupoints. Acupuncture was given once a day, 6 times a week, for a total of 3 weeks in the two groups. The Pittsburgh sleep quality index (PSQI), insomnia severity index (ISI) scores were observed before treatment, after treatment and in follow-up of one month after treatment completion; the Beck anxiety inventory (BAI), Beck depression inventory (BDI), fatigue severity scale (FSS), and Epworth sleepiness scale (ESS) scores were observed before and after treatment; the sleep parameters of polysomnography (PSG), including sleep latency (SL), awake-up time (AT), sleep efficiency (SE) and total sleep time (TST), were observed before and after treatment using polysomnography monitor in the two groups. RESULTS: Compared with those before treatment, the PSQI and ISI scores in both groups were reduced after treatment and in follow-up (P<0.05), and the PSQI and ISI scores in the observation group were lower than those in the control group after treatment and in follow-up (P<0.05). Compared with those before treatment, the BAI, BDI, FSS and ESS scores in both groups were reduced after treatment (P<0.05), and the BAI, BDI, FSS and ESS scores in the observation group were lower than those in the control group after treatment (P<0.05). Compared with those before treatment, the SL and AT in both groups were reduced after treatment (P<0.05), while SE and TST were increased after treatment (P<0.05); after treatment, the SL and AT in the observation group were lower than those in the control group (P<0.05), while SE and TST in the observation group were higher than those in the control group (P<0.05). CONCLUSION: On the basis of regular acupoint selection, acupuncture at "umbilical four-acupoints" could improve sleep quality, alleviate the severity of insomnia, and improve the comorbid symptoms i.e. anxiety, depression, fatigue and lethargy in patients with chronic insomnia.

The Role of Self-Esteem in the Relationship Between Psychological Capital and Anxiety of Left-Behind Experience College Students During COVID-19 Pandemic: An Online Study.

Background: There is growing evidence that the COVID-19 pandemic has had a dramatic impact on public mental health. However, less attention has been paid to left-behind experience college students (LBEs). This online study aimed to investigate the relationship between psychological capital (PsyCap) and anxiety among LBEs during COVID-19 pandemic, and further analyze the mediation role of self-esteem between them. Methods: A total of 9990 students were chosen using the stratified cluster sampling method. Three self-reported questionnaires were used to assess the PsyCap, self-esteem, and anxiety, respectively. All the statistical analyses were conducted using SPSS 23.0 and R, and to further investigate the mediation effect of self-esteem in the association of PsyCap with anxiety, AMOS 23.0 was used to build a structural equation model. Results: PsyCap, self-esteem, and anxiety were significantly correlated among LBEs during the COVID-19 pandemic. PsyCap affects anxiety directly (ß = -0.22, SE = 0.051, 95% CI: -0.27, -0.17, P < 0.05). In addition, self-esteem partially mediated the relationship between PsyCap and anxiety (mediating effect value = -0.16, 95% CI: -0.20, -0.13, P < 0.05). Conclusion: During the pandemic of COVID-19, left-behind experience had a negative influence on the PsyCap and self-esteem of college students. In addition, for LBEs, self-esteem plays an important mediating role between PsyCap and anxiety. Therefore, from the perspective of PsyCap and self-esteem, schools should translate them into practical educational strategies to enhance the mental health and mitigate the anxiety levels of LBEs.

Recent advances in CRISPR-based genome editing technology and its applications in cardiovascular research.

The rapid development of genome editing technology has brought major breakthroughs in the fields of life science and medicine. In recent years, the clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing toolbox has been greatly expanded, not only with emerging CRISPR-associated protein (Cas) nucleases, but also novel applications through combination with diverse effectors. Recently, transposon-associated programmable RNA-guided genome editing systems have been uncovered, adding myriads of potential new tools to the genome editing toolbox. CRISPR-based genome editing technology has also revolutionized cardiovascular research. Here we first summarize the advances involving newly identified Cas orthologs, engineered variants and novel genome editing systems, and then discuss the applications of the CRISPR-Cas systems in precise genome editing, such as base editing and prime editing. We also highlight recent progress in cardiovascular research using CRISPR-based genome editing technologies, including the generation of genetically modified in vitro and animal models of cardiovascular diseases (CVD) as well as the applications in treating different types of CVD. Finally, the current limitations and future prospects of genome editing technologies are discussed.

Nitrogen-Neighbored Single-Cobalt Sites Enable Heterogeneous Oxidase-Type Catalysis.

The development of biomimetic catalytic systems that can imitate or even surpass natural enzymes remains an ongoing challenge, especially for bioinspired syntheses that can access non-natural reactions. Here, we show how an all-inorganic biomimetic system bearing robust nitrogen-neighbored single-cobalt site/pyridinic-N site (Co-N4/Py-N) pairs can act cooperatively as an oxidase mimic, which renders an engaged coupling of oxygen (O2) reduction with synthetically beneficial chemical transformations. By developing this broadly applicable platform, the scalable synthesis of greater than 100 industrially and pharmaceutically appealing O-silylated compounds including silanols, borasiloxanes, and silyl ethers via the unprecedented aerobic oxidation of hydrosilane under ambient conditions is demonstrated. Moreover, this heterogeneous oxidase mimic also offers the potential for expanding the catalytic scope of enzymatic synthesis. We anticipate that the strategy demonstrated here will pave a new avenue for understanding the underlying nature of redox enzymes and open up a new class of material systems for artificial biomimetics.

Interaction Between the Glymphatic System and α-Synuclein in Parkinson's Disease.

The glymphatic system contributes to the clearance of amyloid-ß from the brain and is disrupted in Alzheimer's disease. However, whether the system is involved in the removal of α-synuclein (α-syn) and whether it is suppressed in Parkinson's disease (PD) remain largely unknown. In mice receiving the intranigral injection of recombinant human α-syn, we found that the glymphatic suppression via aquaporin-4 (AQP4) gene deletion or acetazolamide treatment reduced the clearance of injected α-syn from the brain. In mice overexpressing the human A53T-α-syn, we revealed that AQP4 deficiency accelerated the accumulation of α-syn, facilitated the loss of dopaminergic neurons, and accelerated PD-like symptoms. We also found that the overexpression of A53T-α-syn reduced the expression/polarization of AQP4 and suppressed the glymphatic activity of mice. The study demonstrates a close interaction between the AQP4-mediated glymphatic system and parenchymal α-syn, indicating that restoring the glymphatic activity is a potential therapeutic target to delay PD progression.

Circulating exosomal lncRNA contributes to the pathogenesis of spinal cord injury in rats.

Exosome-derived long non-coding RNAs (lncRNAs) are extensively engaged in recovery and repair of the injured spinal cord, through different mechanisms. However, to date no study has systematically evaluated the differentially expressed lncRNAs involved in the development of spinal cord injury. Thus, the aim of this study was to identify key circulating exosome-derived lncRNAs in a rat model of spinal cord injury and investigate their potential actions. To this end, we established a rat model of spinal cord hemisection. Circulating exosomes were extracted from blood samples from spinal cord injury and control (sham) rats and further identified through Western blotting and electron microscopy. RNA was isolated from the exosomes and sequenced. The enrichment analysis demonstrated that there were distinctively different lncRNA and mRNA expression patterns between the two groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology (GO) functional analysis were performed to determine the possible involvements of upregulated and downregulated lncRNAs in various pathways and different biological processes, as well as their cellular locations and molecular functions. Furthermore, quantitative reverse transcription-polymerase chain reaction showed that the expression of five lncRNAs--ENSRN0T00000067908, XR_590093, XR_591455, XR_360081, and XR_346933--was increased, whereas the expression of XR_351404, XR_591426, XR_353833, XR_590076, and XR_590719 was decreased. Of note, these 10 lncRNAs were at the center of the lncRNA-miRNA-mRNA coexpression network, which also included 198 mRNAs and 41 miRNAs. Taken together, our findings show that several circulating exosomal lncRNAs are differentially expressed after spinal cord injury, suggesting that they may be involved in spinal cord injury pathology and pathogenesis. These lncRNAs could potentially serve as targets for the clinical diagnosis and treatment of spinal cord injury.

Theoretical investigation of borane compounds mimicking transition metals for N2 fixation and activation.

N2 fixation is very difficult because of the nonpolarity and high stability of N2. Traditionally, it is achieved by transition metal (TM) systems utilizing the back donation from the d orbitals of the TM to the antibonding π* orbitals of N2 to activate N2. This back donation is rare for main group compounds due to the lack of high-lying valence d orbitals. In the present study, we show that borane compounds with weak B-X (X = H, Si, Ge, and Sb) bonds can mimic TM systems and be used to fix and activate N2. This is achieved by the back donation from the σ bonding orbitals of the B-X bonds to the antibonding π* and σ* orbitals of N2. There is even a linear relationship between the number of B-X bonds and the binding potential energy of N2 with BR1R2R3 (R1, R2, R3 = H, CH3, SiH3, GeH3, and SbH2). Based on these findings, we designed several stable silylborane compounds that are feasible for N2 fixation and activation under mild reaction conditions, i.e., room temperature and 1 atm. In some sandwich-like complexes formed between N2 and silylborane compounds, N2 is even activated from the triple bond to double bond.

Borenium-Ion-Catalyzed C-H Borylation of Arenes.

Non-metal-catalyzed C-H borylation of arenes represents a sustainable and environment-friendly approach for the functionalization of arenes. Despite its promise as an alternative to traditional transition-metal systems, its substrate scope is generally limited to electron-rich arenes, thus hindering its application in organic synthesis. Herein, we report the development of a borenium-ion catalyst which can borylate unactivated arenes under ambient conditions with 4-chlorocatecholborane (HBcatCl) as borylation reagent. This metal-free catalytic system is suitable for the borylation of C-H bonds in sterically encumbered positions, which has been a challenging task for transition-metal systems. Additionally, this catalytic system allows para-selective one-pot borylation of phenols, which has not been achieved by using transition-metal systems. Our mechanistic investigations and computational studies support a synergistic activation of the H-BcatCl bond by the arene substrate and the borenium-ion catalyst. This generates a Wheland intermediate and a neutral hydroborane species and is followed by deprotonation of the Wheland intermediate with the hydroborane species. The latter step of C-H bond cleavage is likely the rate-limiting step.