F Doping-Induced Multicomponent Synergistic Active Site Construction toward High-Efficiency Bifunctional Oxygen Electrocatalysis for Rechargeable Zn-Air Batteries.

The commercialization of rechargeable Zn-air batteries (ZABs) relies on the material innovation to accelerate the sluggish oxygen electrocatalysis kinetics. Due to the differentiated mechanisms of reverse processes, i.e., oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), rationally integrating dual sites for bifunctional oxygen electrocatalysis is prerequisite yet remains challenging. Herein, multicomponent synergistic active sites within highly graphitic carbon substrate are exquisitely constructed, which is accomplished by fluorine (F) modulation strategy. The incorporation of F dopants facilitates pyridinic N formation for anchoring single metal sites, thus guaranteeing the coexistence of sufficient M-Nx sites and metal nanoparticles toward bifunctional oxygen electrocatalysis. As a result, the optimal catalyst, denoted as F NH2-FeNi-800, outperforms commercial Pt/C+RuO2 with smaller gap between Ej = 10 and E1/2 (ΔE) of 0.63 V (vs 0.7 V for Pt/C+RuO2), demonstrating its superior bifunctionality. Beyond that, its superiority is validated in homemade rechargeable ZABs. ZABs assembled using F NH2-FeNi-800 as the air cathode delivers higher peak power density (123.8 mW cm-2) and long-cycle lifetime (over 660 cycles) in comparison with Pt/C@RuO2 (68.8 mW cm-2; 300 cycles). The finding not only affords a highly promising oxygen electrocatalyst, but also opens an avenue to constructing multifunctional active sites for heterogeneous catalysts.

CREB-binding protein and HIF-1α/ß-catenin to upregulate miR-322 and alleviate myocardial ischemia-reperfusion injury.

Myocardial ischemia/reperfusion injury (MIRI) is a prevalent condition associated with numerous critical clinical conditions. miR-322 has been implicated in MIRI through poorly understood mechanisms. Our preliminary analysis indicated potential interaction of CREB-binding protein (CBP), a transcriptional coactivator and acetyltransferase, with HIF-1α/ß-catenin, which might regulate miR-322 expression. We, therefore, hypothesized that CBP/HIF-1α/ß-catenin/miR-322 axis might play a role in MIRI. Rat cardiomyocytes subjected to oxygen-glucose deprivation /reperfusion (OGD/R) and Langendorff perfused heart model were used to model MIRI in vitro and in vivo, respectively. We used various techniques such as CCK-8 assay, transferase dUTP nick end labeling staining, western blotting, RT-qPCR, chromatin immunoprecipitation (ChIP), dual-luciferase assay, co-immunoprecipitation (Co-IP), hematoxylin and eosin staining, and TTC staining to assess cell viability, apoptosis, and the levels of CBP, HIF-1α, ß-catenin, miR-322, and acetylation. Our results indicate that OGD/R in cardiomyocytes decreased CBP/HIF-1α/ß-catenin/miR-322 expression, increased cell apoptosis and cytokines, and reduced cell viability. However, overexpression of CBP or miR-322 suppressed OGD/R-induced cell injury, while knockdown of HIF-1α/ß-catenin further exacerbated the damage. HIF-1α/ß-catenin bound to miR-322 promoter to promote its expression, while CBP acetylated HIF-1α/ß-catenin for stabilization. Overexpression of CBP attenuated MIRI in rats by acetylating HIF-1α/ß-catenin to stabilize their expression, resulting in stronger binding of HIF-1α/ß-catenin with the miR-322 promoter and subsequent increased miR-322 levels. Therefore, activating CBP/HIF-1α/ß-catenin/miR-322 signaling may be a potential approach to treat MIRI.

Measuring Human Auditory Evoked Fields with a Flexible Multi-Channel OPM-Based MEG System.

BACKGROUND: Magnetoencephalography (MEG) is a non-invasive imaging technique for directly measuring the external magnetic field generated from synchronously activated pyramidal neurons in the brain. The optically pumped magnetometer (OPM) is known for its less expensive, non-cryogenic, movable and user-friendly custom-design provides the potential for a change in functional neuroimaging based on MEG. METHODS: An array of OPMs covering the opposite sides of a subject's head is placed inside a magnetically shielded room (MSR) and responses evoked from the auditory cortices are measured. RESULTS: High signal-to-noise ratio auditory evoked response fields (AEFs) were detected by a wearable OPM-MEG system in a MSR, for which a flexible helmet was specially designed to minimize the sensor-to-head distance, along with a set of bi-planar coils developed for background field and gradient nulling. Neuronal current sources activated in AEF experiments were localized and the auditory cortices showed the highest activities. Performance of the hybrid optically pumped magnetometer-magnetoencephalography/electroencephalography (OPM-MEG/EEG) system was also assessed. CONCLUSIONS: The multi-channel OPM-MEG system performs well in a custom built MSR equipped with bi-planar coils and detects human AEFs with a flexible helmet. Moreover, the similarities and differences of auditory evoked potentials (AEPs) and AEFs are discussed, while the operation of OPM-MEG sensors in conjunction with EEG electrodes provides an encouraging combination for the exploration of hybrid OPM-MEG/EEG systems.

Challenges and Strategies of Anion Exchange Membranes in Hydrogen-electricity Energy Conversion Devices.

Alkaline hydrogen-electricity energy conversion technologies, involving anion exchange membrane fuel cells (AEMFCs) and anion exchange membrane water electrolyzers (AEMWEs) are more appealing than the acidic counterparts due to the elimination of precious metal catalysts. However, the physicochemical properties of anion exchange membrane (AEMs), i.e., ionic conductivity, mechanical strength, stability, etc., are inferior to that of proton exchange membranes (PEMs), thus hindering these alkaline technologies from practical employment. To promote their development, we summarize the main challenges and the corresponding strategies of AEMs for the application of AEMFCs and AEMWEs in this review. The hydroxide transportation mechanism, ion exchange capacity, hydration and microscopic morphology that are relevant to the ionic conductivity are discussed firstly. Following the ionic conductivity, another obstacle, stability of AEMs is comprehensively described in terms of alkaline stability, mechanical stability and electrochemical stability. Upon integrating into the devices, water management, carbonation effect and membrane-electrode interface that are critical to the cell performance are highlighted as well. This review is anticipated to provide insights into the AEM design for hydrogen-electric energy conversion devices, thus accelerating the widespread commercialization of these promising technologies.

Atorvastatin-induced tolerogenic dendritic cells improve cardiac remodeling by suppressing TLR-4/NF-κB activation after myocardial infarction.

OBJECTIVE: Myocardial infarction (MI) caused by ischemic cardiomyocyte necrosis induces inflammatory responses that strongly affect ventricular remodeling. Tolerogenic dendritic cells (tDCs) can suppress this effect on inflammatory responses. However, the precise role of atorvastatin-induced tDCs in ventricular remodeling after MI remains unclear. METHODS: To explore the effect of necrotic cardiomyocytes (SNC) and/or atorvastatin on DC function, the expression of CD40, CD80, CD86, and MHC-II was determined using flow cytometry. The protein levels of TLR-4/NF-κB-related molecules were evaluated using western blotting. The infarct area after MI was determined via 2,3,5-triphenyltetrazolium chloride staining. The TUNEL assay was employed to evaluate the apoptosis of cardiomyocytes in heart sections. Masson's trichrome method was used to determine the extent of fibrosis. RESULTS: Compared to the DCs co-cultured with PBS (control), cells co-cultured with Supernatant-IM or Supernatant-NH produced higher levels of inflammatory cytokines, including TNF-α, IL-1, IL-6, IL-12P40, and IL-8. This cytokine production was impaired by atorvastatin treatment. SNC treatment induced DC maturation and enhanced inflammatory cytokine secretion and oxidative stress through TLR-4/NF-κB pathway activation. Compared to that in the PBS-treated group, the left ventricular ejection fraction was significantly improved after tDC treatment. Additionally, compared to that in the PBS-treated group, tDC treatment reduced the left ventricular end-diastolic and end-systolic diameters in mice. Furthermore, treatment with tDCs improved the left ventricular systolic function, attenuated inflammatory cell infiltration, and reduced cardiomyocyte apoptosis, myocardial fibrosis, and infarct size compared to those in the control group. CONCLUSIONS: Adoptive transfer of atorvastatin-induced tDCs alleviated post-infarction cardiomyocyte apoptosis and myocardial fibrosis in association with decreased inflammatory cell infiltration and inhibited oxidative stress, likely by suppressing TLR-4/NF-κB activation after myocardial infarction.

HIF-1α-induced upregulated miR-322 forms a feedback loop by targeting Smurf2 and Smad7 to activate Smad3/ß-catenin/HIF-1α, thereby improving myocardial ischemia-reperfusion injury.

Myocardial ischemia/reperfusion injury (MIRI) is a major cause of heart failure after myocardial infarction. It has been reported that miR-322 is involved in MIRI progression, while the molecular mechanism of miR-322 in regulating MIRI progression needs to be further probed. MIRI cell model was established by oxygen-glucose deprivation/reoxygenation (OGD/R). Cell viability was assessed using MTS assay. Flow cytometry and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling staining were employed to analyze cell apoptosis. In addition, the interactions between miR-322, Smad7/Smurf2, hypoxia-inducible factor alpha (HIF-1α), and ß-catenin were verified by dual-luciferase reporter gene assay. Our results displayed that miR-322 was significantly downregulated in OGD/R-treated H9c2 cells, and its overexpression resulted in increased cell viability and reduced the apoptosis. Smurf2 and Smad7 were identified as the direct targets of miR-322. Smad7 knockdown or Smurf2 knockdown increased OGD/R-treated H9c2 cell viability and suppressed the apoptosis. Meanwhile, miR-322 mimics abolished the mitigating effect of Smad7 or Smurf2 overexpression on MIRI. In addition, the Smad3/ß-catenin pathway was identified as the downstream pathway of Smurf2/Smad7. Moreover, it was found that HIF-1α interacted with the miR-322 promoter, and ß-catenin interacted with the HIF-1α promoter to form a loop. HIF-1α-induced upregulated miR-322 activated the Smad3/ß-catenin pathway by targeting Smurf2 and Smad7 to improve MIRI; meanwhile, ß-catenin/HIF-1α formed a positive feedback loop to continuously improve MIRI.

Improving MRI-based analysis of brain structural changes in patients with hypertension via a privileged information learning algorithm.

Hypertension can lead to changes in the brain structure and function, and different blood pressure levels (2017ACC/AHA) have different effects on brain structure. It is important to analyze these changes by machine learning methods, and various characteristics can provide rich information for the analysis of these changes. However, multiple feature extraction involves complex data processing. How to make a single feature achieve the same diagnosis effect as multiple features do is worth of study. Kernel ridge regression (KRR) is a kind of machine learning method, which shows faster learning speed and generalization ability in classification tasks. In order to knowledge transfer, we use privileged information (PI) to transfer information of multiple types of feature to single feature. This allows only one feature type to be used during the test stage. In the process of feature fusion, we need to consider all the samples' attribution making the classifier better. In this work, we propose a multi-kernel KRR+ framework based on self-paced learning to analyze the changes of the brain structure in patients with different blood pressure levels. Specifically, one kind of a feature is taken as main feature, and other features are input into the multi-kernel KRR as PI. These two inputs are fed into the final KRR classifier together. In addition, a self-paced learning method is introduced into sample selecting to avoid training the classifier using samples with a large loss value firstly, which improves the generalization performance of the classifier. Experimental results show that the proposed method can make full use of the information of various features and achieve better classification performance. This shows self-paced learning based KRR can help analyze brain structure of patients with different blood pressure levels. The discriminative features may help clinicians to make judgments of hypertension degrees on brain MRI images.

Quasi-Covalently Coupled Ni-Cu Atomic Pair for Synergistic Electroreduction of CO2.

Developing highly active, selective, and stable electrocatalysts for the carbon dioxide reduction reaction (CO2RR) is crucial to establish a CO2 conversion system for industrial implementation and, therefore, to realize an artificially closed carbon loop. This can only be achieved through the rational material design based upon the knowledge of the operational active site at the molecular scale. Enlightened by theoretical screening, herein, we for the first time manipulate a novel Ni-Cu atomic pair configuration toward improved CO2RR performance. Systematic characterizations and theoretical modeling reveal that the secondary Cu metal incorporation positively shifts the Ni 3d orbital energy to the Fermi level and thus accelerates the rate-determining step, *COOH formation. In addition, the intrinsic inactivity of Cu toward the competing hydrogen evolution reaction causes a considerable reaction barrier for water dissociation on the Ni-Cu moiety. Due to these attributes, the as-developed Ni/Cu-N-C catalyst exhibits excellent catalytic activity and selectivity, with a record-high turnover frequency of 20,695 h-1 at -0.6 V (vs RHE) and a maximum Faradaic efficiency of 97.7% for CO production. Furthermore, the dynamic structure evolution monitored by operando X-ray absorption fine-structure spectroscopy unveils the interaction between the Ni center and CO2 molecules and the synergistic effect of the Ni-Cu atomic pair on CO2RR activity.

Outcomes and risk factors of perforating and non-perforating middle cerebral artery infarctions after intravenous thrombolysis.

The clinical symptoms of perforating arteries differ, and responses to intravenous thrombolytic therapy are heterogeneous. Here, we investigated the effect of intravenous thrombolytic therapy and the related factors influencing acute perforating and non-perforating middle cerebral artery infarctions. We analyzed 320 patients with acute middle cerebral artery infarction who received alteplase thrombolysis within 4.5 h of onset at two stroke centers from January 2016 to December 2019. Outcome measures included rates of a favorable functional outcome (modified Rankin Scale scores of 0-2), distribution of modified Rankin Scale scores, intracranial hemorrhage, and symptomatic cerebral hemorrhage at 14 days, with comparisons between perforating artery and non-perforating artery cerebral infarction groups. In the perforating vessel disease group, 12 cases (17.4%) of intracranial hemorrhage occurred, with symptomatic cerebral hemorrhage in three cases (4.3%); there were no significant differences between the perforating and non-perforating vessel disease groups (all P > 0.05). In the perforating vessel disease group, the only significant prognostic factor was the National Institutes of Health Stroke Scale score before thrombolysis (Exp(B) = 1.365; 95% confidence interval [CI] 1.124-1.659; P = 0.002), and the only significant risk factor for hemorrhagic transformation was previous perforator disease (Exp(B) = 0.078; P = 0.038). Regardless of whether an acute infarction is perforating or non-perforating, intravenous thrombolytic therapy can yield a favorable outcome. Therefore, intravenous thrombolysis should be actively administered to treat perforating artery infarctions with a high risk of disability.

[Multi-task motor imagery electroencephalogram classification based on adaptive time-frequency common spatial pattern combined with convolutional neural network].

The effective classification of multi-task motor imagery electroencephalogram (EEG) is helpful to achieve accurate multi-dimensional human-computer interaction, and the high frequency domain specificity between subjects can improve the classification accuracy and robustness. Therefore, this paper proposed a multi-task EEG signal classification method based on adaptive time-frequency common spatial pattern (CSP) combined with convolutional neural network (CNN). The characteristics of subjects' personalized rhythm were extracted by adaptive spectrum awareness, and the spatial characteristics were calculated by using the one-versus-rest CSP, and then the composite time-domain characteristics were characterized to construct the spatial-temporal frequency multi-level fusion features. Finally, the CNN was used to perform high-precision and high-robust four-task classification. The algorithm in this paper was verified by the self-test dataset containing 10 subjects (33 ± 3 years old, inexperienced) and the dataset of the 4th 2018 Brain-Computer Interface Competition (BCI competition Ⅳ-2a). The average accuracy of the proposed algorithm for the four-task classification reached 93.96% and 84.04%, respectively. Compared with other advanced algorithms, the average classification accuracy of the proposed algorithm was significantly improved, and the accuracy range error between subjects was significantly reduced in the public dataset. The results show that the proposed algorithm has good performance in multi-task classification, and can effectively improve the classification accuracy and robustness.

CISD1 protects against atherosclerosis by suppressing lipid accumulation and inflammation via mediating Drp1.

Atherosclerosis still remains the leading cause of morbidity and mortality worldwide, and deeper understanding of target signaling that protect from the atherosclerosis progression may provide novel therapeutic strategies. CDGSH iron-sulfur domain-containing protein 1 (CISD1) is a protein localized on the outer membrane of mitochondria, and plays key roles in regulating cell death and oxidative stress. However, its potential on atherosclerosis development and the underlying mechanisms are largely unknown. Here, in our study, we found markedly decreased CISD1 expression in lipid-laden THP1 macrophages. Notably, lentivirus (LV)-mediated CISD1 over-expression remarkably ameliorated lipid deposition in macrophages stimulated by ox-LDL. Furthermore, cellular total ROS and mitochondrial ROS generation, and impairment of mitochondrial membrane potential (MMP) were highly induced by ox-LDL in THP1 cells, while being considerably reversed upon CISD1 over-expression. Inflammatory response caused by ox-LDL was also significantly restrained in macrophages with CISD1 over-expression. Mechanistically, we found that CISD1 could interact with dynamin-related protein 1 (Drp1). Intriguingly, CISD1-improved mitochondrial dysfunction and inflammation in ox-LDL-treated macrophages were strongly abolished by Drp1 over-expression, indicating that Drp1 suppression might be necessary for CISD1 to perform its protective effects in vitro. In high fat diet (HFD)-fed apolipoprotein E-deficient (ApoE-/-) mice, tail vein injection of lentiviral vector expressing CISD1 remarkably decreased atherosclerotic lesion area, serum LDL cholesterol levels and triglyceride contents. Inflammatory response, cellular total and mitochondrial ROS production, and Drp1 expression levels in aorta tissues were also dramatically ameliorated in HFD-fed ApoE-/- mice, contributing to the inhibition of atherosclerosis in vivo. Therefore, improving CISD1 expression may be a novel therapeutic strategy for atherosclerosis treatment.

Inhibition of KIF20A by transcription factor IRF6 affects the progression of renal clear cell carcinoma.

BACKGROUND: Renal clear cell carcinoma (ccRCC) is one of the most common malignant tumors, whose incidence is increasing year by year. IRF6 plays an important role in the occurrence of tumors, although there is yet no report on its expression in ccRCC. METHODS: The expression of IRF6 and KIF20A in ccRCC was predicted by GEPIA and HAP databases. In addition, GEPIA database predicted the relationship between IRF6 and KIF20A expressions and the pathological staging, overall survival, and disease-free survival of ccRCC. The possible binding sites of IRF6 and KIF20A promoters were predicted by JASPAR database and verified by luciferase and ChIP assays. The specific effects of IRF6 on ccRCC cell proliferation, invasion and apoptosis were subsequently examined at both cellular level and animal level. RESULTS: The database predicted down-regulated IRF6 expression in renal carcinoma tissues and its correlation with poor prognosis. IRF6 overexpression inhibited cRCC cell proliferation, invasion and migration. In addition, up-regulated KIF20A expression in renal carcinoma tissues and its association with prognosis were also predicted. Interference with KIF20A inhibited the proliferation, invasion, and migration of ccRCC cells. Finally, we confirmed that KIF20A is a functional target of IRF6 and can partially reverse the effects of IRF6 on the proliferation, invasion and migration of ccRCC cells. CONCLUSION: Inhibition of KIF20A by transcription factor IRF6 affects cell proliferation, invasion and migration in renal clear cell carcinoma.

[Automatic segmentation of kidney tumor based on cascaded multiscale convolutional neural networks].

The background of abdominal computed tomography (CT) images is complex, and kidney tumors have different shapes, sizes and unclear edges. Consequently, the segmentation methods applying to the whole CT images are often unable to effectively segment the kidney tumors. To solve these problems, this paper proposes a multi-scale network based on cascaded 3D U-Net and DeepLabV3+ for kidney tumor segmentation, which uses atrous convolution feature pyramid to adaptively control receptive field. Through the fusion of high-level and low-level features, the segmented edges of large tumors and the segmentation accuracies of small tumors are effectively improved. A total of 210 CT data published by Kits2019 were used for five-fold cross validation, and 30 CT volume data collected from Suzhou Science and Technology Town Hospital were independently tested by trained segmentation models. The results of five-fold cross validation experiments showed that the Dice coefficient, sensitivity and precision were 0.796 2 ± 0.274 1, 0.824 5 ± 0.276 3, and 0.805 1 ± 0.284 0, respectively. On the external test set, the Dice coefficient, sensitivity and precision were 0.817 2 ± 0.110 0, 0.829 6 ± 0.150 7, and 0.831 8 ± 0.116 8, respectively. The results show a great improvement in the segmentation accuracy compared with other semantic segmentation methods.

Magnetic-Field-Stimulated Efficient Photocatalytic N2 Fixation over Defective BaTiO3 Perovskites.

Efficient coupling solar energy conversion and N2 fixation by photocatalysis has been shown promising potentials. However, the unsatisfied yield rate of NH3 curbs its forward application. Defective typical perovskite, BaTiO3 , shows remarkable activity under an applied magnetic field for photocatalytic N2 fixation with an NH3 yield rate exceeding 1.93 mg L-1 h-1 . Through steered surface spin states and oxygen vacancies, the electromagnetic synergistic effect between the internal electric field and an external magnetic field is stimulated. X-ray absorption spectroscopy and density functional theory calculations reveal the regulation of electronic and magnetic properties through manipulation of oxygen vacancies and inducement of Lorentz force and spin selectivity effect. The electromagnetic effect suppresses the recombination of photoexcited carriers in semiconducting nanomaterials, which acts synergistically to promote N2 adsorption and activation while facilitating fast charge separation under UV-vis irradiation.

Correlation Between Quantitative Assessment of Chest Computed Tomography (CT) Imaging and Prognosis of COVID-19 Patients.

BACKGROUND The aim of our work was to evaluate the correlation between the quantitative parameters of the peak lesion to 25% improvement time (PIT25) and the prognosis of new coronavirus pneumonia (COVID-19) patients by analyzing the changes of chest CT imaging. MATERIAL AND METHODS This retrospective analysis included 68 patients with COVID-19 in the Fifth People's Hospital of Suzhou City. Three radiologists performed a blind evaluation of 4 chest CT images that included the initial scans, the lesion peak, the lesion decreased to 25% of the peak, and the final scan. The score of chest CT lesion, the imaging characteristics of the lesion, the time of the appearance of symptoms related to the CT examination, quantitative assessment of PIT25, and the absorption of the lesion in last CT image were analyzed. Patients were divided into an obvious absorption group and a non-obvious absorption group according to the reduction of the lesion area by greater than 50% or less than 50%. RESULTS In the peak time, the most common images of CT were ground-glass opacities (94.1%), consolidation (85.3%) and reticulation (88.2%), multifocal (97.1%), center and subpleural (54.4%), subpleural distribution (45.6%), and pleural thickening (79.4%). The PIT25 with the prognosis (r=0.53, p=0.00) was significantly relevant. PIT25 was 4.3±0.7 days for the obvious absorption group and 6.8±1.4 days for the non-obvious absorption group. CONCLUSIONS The features of CT image are specific at the peak. The quantitative parameter PIT25 could be used to predict the prognosis of the patients with COVID-19, as COVID-19 patients with a shorter PIT25 have a better prognosis and vice versa.

Gut microbe-derived metabolite trimethylamine N-oxide accelerates fibroblast-myofibroblast differentiation and induces cardiac fibrosis.

BACKGROUND: Trimethylamine N-oxide (TMAO), a gut microbe-derived metabolite of dietary choline and other trimethylamine-containing nutrients, has been associated with poor prognosis in coronary heart disease. However, the role and underlying mechanisms of TMAO in the cardiac fibrosis after myocardial infarction (MI) remains unclear. METHODS: We used mouse MI models and primary cardiac fibroblasts cultures to study the role of TMAO in the heart and in cardiac fibroblasts. C57BL/6 mice were fed a control diet, high choline (1.2%) or/and DMB diet or a diet containing TMAO (0.12%) starting 3 weeks before MI. DMB, a structural analogue of choline, inhibited microbial TMA lyases and reduced the level of TMAO in mice. Cardiac function was measured 7 days after MI using echocardiography. One week post MI, myocardial tissues were collected to evaluate cardiac fibrosis, and blood samples were evaluated for TMAO levels. The expression of TGF-ß receptor, P-Smad2, α-SMA or collagen I in myocardial tissues and fibroblasts were analyzed by western blot or immunocytochemistry. RESULTS: We demonstrated that cardiac function and cardiac fibrosis were significantly deteriorated in mice fed either TMAO or high choline diets compared with the control diet, and DMB reversed the cardiac function damage of high choline diet (p < .05). Cardiomyocyte necrosis, apoptosis and macrophage infiltration after MI was significantly increased after treatment with TMAO or high choline diets. The size and migration of fibroblasts were increased after TMAO treatment compared with non-treated fibroblasts in vitro. Furthermore, TMAO increased TGF-ß receptor I expression, which promoted the phosphorylation of Smad2 and up-regulated the expression of α-SMA and collagen I. The ubiquitination of TGF-ßRI was decreased in neonatal mouse fibroblasts after TMAO treatment. TMAO also inhibited the expression of smurf2. Inhibition of TGF-ß1 receptor with the small molecule inhibitor SB431542 decreased TGF-ß receptor I expression, reduced the phosphorylation of Smad2, down-regulated TMAO-induced α-SMA and collagen I expression in cardiac fibroblasts. CONCLUSIONS: Cardiac function and cardiac fibrosis were significantly exacerbated in mice fed diets supplemented with either choline or TMAO, probably through accelerating the transformation of fibroblasts into myofibroblasts, indicating activation of TGF-ßRI/Smad2 pathway.

Engineering Energy Level of Metal Center: Ru Single-Atom Site for Efficient and Durable Oxygen Reduction Catalysis.

Emerging as a new frontier in heterogeneous catalysis, single-atom site catalysts (SSCs) have sparked enormous attention and bring about new opportunities to oxygen reduction electrocatalysis. Despite considerable progress achieved recently, most of the reported SSCs suffer from either insufficient activity or unsatisfactory stability, which severely retards their practical application. Here, we demonstrate a novel Ru-SSC with appropriate adsorption free energy of OH* (ΔGOH*) to confer excellent activity and low Fenton reactivity to maintain long-term stability. The as-developed Ru-SSC exhibits encouraging oxygen reduction reaction turnover frequency of 4.99 e- s-1 sites-1, far exceeding the state-of-the-art Fe-SSC counterpart (0.816 e- s-1 sites-1), as a result of Ru energy level regulation via spontaneous OH binding. Furthermore, Ru-SSC exhibits greatly suppressed Fenton reactivity, with restrained generation of reactive oxygen species directly observed, thus endowing the Ru-SSC with much more superior stability (only 17 mV negative shift after 20 000 cycles) than the Fe-SSC counterpart (31 mV). The practical application of Ru-SSC is further validated by its excellent activity and stability in a real fuel cell device.

Climbing the Apex of the ORR Volcano Plot via Binuclear Site Construction: Electronic and Geometric Engineering.

Great enthusiasm in single-atom catalysts (SACs) for the oxygen reduction reaction (ORR) has been aroused by the discovery of M-NX as a promising ORR catalysis center. However, the performance of SACs lags far behind that of state-of-the-art Pt due to the unsatisfactory adsorption-desorption behaviors of the reported catalytic centers. To address this issue, rational manipulation of the active site configuration toward a well-managed energy level and geometric structure is urgently desired, yet still remains a challenge. Herein, we report a novel strategy to accomplish this task through the construction of an Fe-Co dual-atom centered site. A spontaneously absorbed electron-withdrawing OH ligand was proposed to act proactively as an energy level modifier to empower easy intermediate desorption, while the triangular Fe-Co-OH coordination facilitates O-O bond scission. Benefiting from these attributes, the as-constructed FeCoN5-OH site enables an ORR onset potential and half-wave potential of up to 1.02 and 0.86 V (vs RHE), respectively, with an intrinsic activity over 20 times higher than the single-atom FeN4 site. Our finding not only opens up a novel strategy to tailor the electronic structure of an atomic site toward boosted activity but also provides new insights into the fundamental understanding of diatomic sites for ORR electrocatalysis.

Defect-Enriched Nitrogen Doped-Graphene Quantum Dots Engineered NiCo2 S4 Nanoarray as High-Efficiency Bifunctional Catalyst for Flexible Zn-Air Battery.

Flexible Zn-air batteries have recently emerged as one of the key energy storage systems of wearable/portable electronic devices, drawing enormous attention due to the high theoretical energy density, flat working voltage, low cost, and excellent safety. However, the majority of the previously reported flexible Zn-air batteries encounter problems such as sluggish oxygen reaction kinetics, inferior long-term durability, and poor flexibility induced by the rigid nature of the air cathode, all of which severely hinder their practical applications. Herein, a defect-enriched nitrogen doped-graphene quantum dots (N-GQDs) engineered 3D NiCo2 S4 nanoarray is developed by a facile chemical sulfuration and subsequent electrophoretic deposition process. The as-fabricated N-GQDs/NiCo2 S4 nanoarray grown on carbon cloth as a flexible air cathode exhibits superior electrocatalytic activities toward both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), outstanding cycle stability (200 h at 20 mA cm-2 ), and excellent mechanical flexibility (without observable decay under various bending angles). These impressive enhancements in electrocatalytic performance are mainly attributed to bifunctional active sites within the N-GQDs/NiCo2 S4 catalyst and synergistic coupling effects between N-GQDs and NiCo2 S4 . Density functional theory analysis further reveals that stronger OOH* dissociation adsorption at the interface between N-GQDs and NiCo2 S4 lowers the overpotential of both ORR and OER.

Analyzing brain structural differences associated with categories of blood pressure in adults using empirical kernel mapping-based kernel ELM.

BACKGROUND: Hypertension increases the risk of angiocardiopathy and cognitive disorder. Blood pressure has four categories: normal, elevated, hypertension stage 1 and hypertension stage 2. The quantitative analysis of hypertension helps determine disease status, prognosis assessment, guidance and management, but is not well studied in the framework of machine learning. METHODS: We proposed empirical kernel mapping-based kernel extreme learning machine plus (EKM-KELM+) classifier to discriminate different blood pressure grades in adults from structural brain MR images. ELM+ is the extended version of ELM, which integrates the additional privileged information about training samples in ELM to help train a more effective classifier. In this work, we extracted gray matter volume (GMV), white matter volume, cerebrospinal fluid volume, cortical surface area, cortical thickness from structural brain MR images, and constructed brain network features based on thickness. After feature selection and EKM, the enhanced features are obtained. Then, we select one feature type as the main feature to feed into KELM+, and the rest of the feature types are PI to assist the main feature to train 5 KELM+ classifiers. Finally, the 5 KELM+ classifiers are ensemble to predict classification result in the test stage, while PI is not used during testing. RESULTS: We evaluated the performance of the proposed EKM-KELM+ method using four grades of hypertension data (73 samples for each grade). The experimental results show that the GMV performs observably better than any other feature types with a comparatively higher classification accuracy of 77.37% (Grade 1 vs. Grade 2), 93.19% (Grade 1 vs. Grade 3), and 95.15% (Grade 1 vs. Grade 4). The most discriminative brain regions found using our method are olfactory, orbitofrontal cortex (inferior), supplementary motor area, etc. CONCLUSIONS: Using region of interest features and brain network features, EKM-KELM+ is proposed to study the most discriminative regions that have obvious structural changes in different blood pressure grades. The discriminative features that are selected using our method are consistent with the existing neuroimaging studies. Moreover, our study provides a potential approach to take effective interventions in the early period, when the blood pressure makes minor impacts on the brain structure and function.