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In pursuing cheap and effective oxygen reduction catalysts, the Fe/N/C system emerges as a promising candidate. Nevertheless, the structural transformations of starting materials into Fe- and N-doped carbon catalysts remains poorly characterized under pyrolytic conditions. Here, we explore the evolution of Fe species and track the formation of Fe-N4 site development by employing diverse in-situ diagnostic techniques. In-situ heating microscopy reveals the initial formation of FeOx nanoparticles and subsequent internal migration within the carbon matrix, which stops once FeOx is fully reduced. The migration and decomposition of nanoparticles then leads to carbon layer reconstruction. Experimental and theoretical analysis reveals size-dependent behavior of FeOx where nanoparticles below 7 nm readily release Fe atoms to form Fe-N4 while nanoparticles with sizes >10 nm tend to coalesce and impede Fe-N4 site formation. The work visualizes the pyrolysis process of Fe/N/C materials, providing theoretical guidance for the rational design of catalysts.
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To investigate the dynamic changes in hippocampal metabolism after microwave radiation using liquid chromatography in tandem with mass spectrometry/mass spectrometry (LC-MS/MS) and to identify potential biomarkers. Wistar rats were randomly assigned to a sham group and a microwave radiation group. The rats in the microwave radiation group were exposed to 2.856 GHz for 15 min for three times, with 5 min intervals. The rats in the sham group were not exposed. Transmission electron microscope revealed blurring of the synaptic cleft and postsynaptic dense thickening in hippocampal neurons after microwave radiation. Metabolomic analysis revealed 38, 24, and 39 differentially abundant metabolites at 3, 7, and 14 days after radiation, respectively, and the abundance of 9 metabolites, such as argininosuccinic acid, was continuously decreased. After microwave radiation, the abundance of metabolites such as argininosuccinic acid was successively decreased, indicating that these metabolites could be potential biomarkers for hippocampal tissue injury.
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Nail fold capillaroscopy is an important means of monitoring human health. Panoramic nail fold images improve the efficiency and accuracy of examinations. However, the acquisition of panoramic nail fold images is seldom studied and the problem manifests of few matching feature points when image stitching is used for such images. Therefore, this paper presents a method for panoramic nail fold image stitching based on vascular contour enhancement, which first solves the problem of few matching feature points by pre-processing the image with contrast-constrained adaptive histogram equalization (CLAHE), bilateral filtering (BF), and sharpening algorithms. The panoramic images of the nail fold blood vessels are then successfully stitched using the fast robust feature (SURF), fast library of approximate nearest neighbors (FLANN) and random sample agreement (RANSAC) algorithms. The experimental results show that the panoramic image stitched by this paper's algorithm has a field of view width of 7.43 mm, which improves the efficiency and accuracy of diagnosis.
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Optically pumped magnetometer magnetoencephalography (OPM-MEG) holds significant promise for clinical functional brain imaging due to its superior spatiotemporal resolution. However, effectively suppressing metallic artifacts, particularly from devices such as orthodontic braces and vagal nerve stimulators remains a major challenge, hindering the wider clinical application of wearable OPM-MEG devices. A comprehensive analysis of metal artifact characteristics from time, frequency, and time-frequency perspectives was conducted for the first time using an OPM-MEG device in clinical medicine. This study focused on patients with metal orthodontics, examining the modulation of metal artifacts by breath and head movement, the incomplete regular sub-Gaussian distribution, and the high absolute power ratio in the 0.5-8 Hz band. The existing metal artifact suppression algorithms applied to SQUID-MEG, such as fast independent component analysis (FastICA), information maximization (Infomax), and algorithms for multiple unknown signal extraction (AMUSE), exhibit limited efficacy. Consequently, this study introduced the second-order blind identification (SOBI) algorithm, which utilized multiple time delays for the component separation of OPM-MEG measurement signals. We modified the time delays of the SOBI method to improve its efficacy in separating artifact components, particularly those in the ultralow frequency range. This approach employs the frequency-domain absolute power ratio, root mean square (RMS) value, and mutual information methods to automate the artifact component screening process. The effectiveness of this method was validated through simulation experiments involving four subjects in both resting and evoked experiments. In addition, the proposed method was also validated by the actual OPM-MEG evoked experiments of three subjects. Comparative analyses were conducted against the FastICA, Infomax, and AMUSE algorithms. Evaluation metrics included normalized mean square error, normalized delta band power error, RMS error, and signal-to-noise ratio, demonstrating that the proposed method provides optimal suppression of metal artifacts. This advancement holds promise for enhancing data quality and expanding the clinical applications of OPM-MEG.
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Artefatos , Magnetoencefalografia , Humanos , Magnetoencefalografia/métodos , Magnetoencefalografia/instrumentação , Adulto , Feminino , Masculino , Algoritmos , Metais , Processamento de Sinais Assistido por Computador , Adulto Jovem , Encéfalo/fisiologiaRESUMO
Porous organic polymers (POPs) with inherent porosity, tunable pore environment, and semiconductive property are ideally suitable for application in various advanced semiconductor-related devices. However, owing to the lack of processability, POPs are usually prepared in powder forms, which limits their application in advanced devices. Herein, we demonstrate an example of information storage application of POPs with film form prepared by an electrochemical method. The growth process of the electropolymerized films in accordance with the Volmer-Weber model was proposed by observation of atomic force microscopy. Given the mechanism of the electron transfer system, we verified and mainly emphasized the importance of porosity and interfacial properties of porous polymer films for memristor. As expected, the as-fabricated memristors exhibit good performance on low turn-on voltage (0.65 ± 0.10 V), reliable data storage, and high on/off current ratio (104). This work offers inspiration for applying POPs in the form of electropolymerized films in various advanced semiconductor-related devices.
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Exploring economical, efficient, and stable electrocatalysts for the seawater hydrogen evolution reaction (HER) is highly desirable but is challenging. In this study, a Mo cation doped Ni0.85Se/MoSe2 heterostructural electrocatalyst, Mox-Ni0.85Se/MoSe2, was successfully prepared by simultaneously doping Mo cations into the Ni0.85Se lattice (Mox-Ni0.85Se) and growing atomic MoSe2 nanosheets epitaxially at the edge of the Mox-Ni0.85Se. Such an Mox-Ni0.85Se/MoSe2 catalyst requires only 110 mV to drive current densities of 10 mA cm-2 in alkaline simulated seawater, and shows almost no obvious degradation after 80 h at 20 mA cm-2. The experimental results, combined with the density functional theory calculations, reveal that the Mox-Ni0.85Se/MoSe2 heterostructure will generate an interfacial electric field to facilitate the electron transfer, thus reducing the water dissociation barrier. Significantly, the heteroatomic Mo-doping in the Ni0.85Se can regulate the local electronic configuration of the Mox-Ni0.85Se/MoSe2 heterostructure catalyst by altering the coordination environment and orbital hybridization, thereby weakening the bonding interaction between the Cl and Se/Mo. This synergistic effect for the Mox-Ni0.85Se/MoSe2 heterostructure will simultaneously enhance the catalytic activity and durability, without poisoning or corrosion of the chloride ions.
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The electrochemical reduction of oxygen via the 2e pathway is an environmentally friendly approach to the electrosynthesis of H2O2. Nevertheless, its sluggish kinetics and limited selectivity hinder its practical application. Herein, single Fe atoms anchored on graphene oxide (SA Fe/GO) with Fe-O4-C sites are developed as an efficient electrocatalyst for the electro-synthesis of H2O2. These Fe-O4-C site active centres could efficiently enhance the activity and selectivity towards 2e electrochemical oxygen reduction in an alkaline environment. The newly-developed SA Fe/GO electrocatalyst demonstrates exceptional electrochemical performance, exhibiting impressive activity with an onset potential of 0.90 and H2O2 production of 0.60 mg cm-2 h-1 at 0.4 V. Remarkably, it achieves a remarkable H2O2 selectivity of over 95.5%.
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Cation-tuning engineering has become a new frontier in altering the electronic structure of electrocatalysts, which has been employed to enhance their electrochemical performance. Significant efforts have been made to promote the electrochemical performance of transition metal-based materials during oxygen electrocatalysis and related energy devices such as Zn-air batteries. Herein, the advantages of cation-tuning engineering, including cation vacancies/defects and cation doping, in the modification of the electronic structure of transition metal oxide catalysts are discussed. Additionally, practical applications of the cation-tuning engineering strategy are reviewed in detail with a special emphasis on oxygen reduction reaction and oxygen evolution reaction. Lastly, challenges and future opportunities in this field are also proposed.
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Room-temperature sodium-sulfur (RT-Na/S) batteries possess high potential for grid-scale stationary energy storage due to their low cost and high energy density. However, the issues arising from the low S mass loading and poor cycling stability caused by the shuttle effect of polysulfides seriously limit their operating capacity and cycling capability. Herein, sulfur-doped graphene frameworks supporting atomically dispersed 2H-MoS2 and Mo1 (S@MoS2 -Mo1 /SGF) with a record high sulfur mass loading of 80.9 wt.% are synthesized as an integrated dual active sites cathode for RT-Na/S batteries. Impressively, the as-prepared S@MoS2 -Mo1 /SGF display unprecedented cyclic stability with a high initial capacity of 1017 mAh g-1 at 0.1 A g-1 and a low-capacity fading rate of 0.05% per cycle over 1000 cycles. Experimental and computational results including X-ray absorption spectroscopy, in situ synchrotron X-ray diffraction and density-functional theory calculations reveal that atomic-level Mo in this integrated dual-active-site forms a delocalized electron system, which could improve the reactivity of sulfur and reaction reversibility of S and Na, greatly alleviating the shuttle effect. The findings not only provide an effective strategy to fabricate high-performance dual-site cathodes, but also deepen the understanding of their enhancement mechanisms at an atomic level.
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OBJECTIVE: The impact of selenium (Se) on human thyroid function remains unclear, with inconsistent results from recent epidemiological studies. Moreover, the observed associations are prone to bias due to potential confounding and reverse causation. Mendelian randomization (MR) analysis facilitates the large minimization of biases produced by environmental and lifestyle influences, providing unconfounded estimates of causal effects using instrumental variables. We aim to examine the association between Se concentrations and human thyroid function using a two-sample MR analysis. DESIGN AND METHODS: Genetic instruments for Se concentrations, including toenail and blood (TAB) and blood Se concentrations, were identified from a genome-wide association study (GWAS) of blood Se (n = 5477) and toenail Se levels (n = 4162). GWAS summary statistics on thyroid phenotypes were downloaded from the ThyroidOmics consortium, including thyroid-stimulating hormone (TSH) (n = 54,288), free thyroxin (FT4) (n = 49,269), hypo (n = 53,423), and hyperthyroidism (n = 51,823). The MR study was conducted using the inverse-variance weighted (IVW) method, supplemented with the weighted median and the mode-based method. RESULTS: Genetically determined TAB Se was negatively associated with FT4 (ß = -.067; 95% confidence interval [CI] = -0.106, -0.028; p = 0.001) using the IVW analyses, as well in the additional analyses using the weighted median and weighted-mode methods. No evidence in heterogeneity, pleiotropy or outlier single-nucleotide polymorphisms was detected (all p > 0.05). Suggestive casual association between increased genetically determined TAB Se concentrations and decreased hypothyroidism risk was found by the IVW method (odds ratio [OR] = 0.847; 95% CI = 0.728, 0.985; p = 0.031). The causal effect of TAB Se on FT4 was observed in women (ß = -.076; 95% CI = -0.129, -0.024; p = 0.004). However, the influence of genetically determined higher Se concentrations on TSH levels and hyperthyroidism revealed insignificance in the primary and sensitivity analyses. CONCLUSIONS: The present MR study indicated that high Se concentration enable the decreasing of FT4 levels, and the effects of Se concentrations on FT4 remain sex-specific.
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Hipertireoidismo , Selênio , Masculino , Humanos , Feminino , Análise da Randomização Mendeliana/métodos , Estudo de Associação Genômica Ampla , Tireotropina , Polimorfismo de Nucleotídeo Único/genéticaRESUMO
In recent years, the use of machine learning to predict stock market indices has emerged as a vital concern in the FinTech domain. However, the inherent nature of point estimation in traditional supervised machine learning models leads to an almost negligible probability of achieving perfect predictions, significantly constraining the applicability of machine learning prediction models. This study employs 4 machine learning models, namely BPN, LSTM, RF, and ELM, to establish predictive models for the Taiwan biotech index during the COVID-19 period. Additionally, it integrates the Gaussian membership function MF from fuzzy theory to develop 4 hybrid fuzzy interval-based machine learning models, evaluating their predictive accuracy through empirical analysis and comparing them with conventional point estimation models. The empirical data is sourced from the financial time series of the "M1722 Listed Biotechnology and Medical Care Index" compiled by the Taiwan Economic Journal during the outbreak of the COVID-19 pandemic, aiming to understand the effectiveness of machine learning models in the face of significant disruptive factors like the pandemic. The findings demonstrate that despite the influence of COVID-19, machine learning remains effective. LSTM performs the best among the models, both in traditional mode and after fuzzy interval enhancement, followed by the ELM and RF models. The predictive results of these three models reach a certain level of accuracy and all outperform the BPN model. Fuzzy-LSTM effectively predicts at a 68% confidence level, while Fuzzy-ELM and Fuzzy-RF yield better results at a 95% confidence level. Fuzzy-BPN exhibits the lowest predictive accuracy. Overall, the fuzzy interval-based LSTM excels in time series prediction, suggesting its potential application in forecasting time series data in financial markets to enhance the efficacy of investment analysis for investors.
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Aim: Public concerns over the mental health problems of college students are rising. Previous research show that female tend to suffer more from mental health problems than males, with few studies focusing on males. This study sought to explore the association of lifestyle-related risk factors with the prevalence of mental health problems among male college students in China. Methods: The lifestyle information and mental health status of 686 male college students from Chongqing, China, were assessed in 2014, and 582 of them were followed up a year later. Participants completed a questionnaire assessing demographic and lifestyle factors which include sleep quality, computer usage, sedentariness, physical activity, smoking, current alcohol, coke, coffee, and milk tea drinking, and current tea/fried food/baked food consumption. Mental health problems were measured using the Depression Anxiety Stress Scale-21 (DASS-21). Results: Univariate analyses indicated that age, sleep latency, sleep duration, computer usage time, milk tea drinking, and fried food consumption were potential risk factors for mental health problems (p's < 0.05). Multivariate analysis further revealed that, either at baseline or during follow-up, participants with (i) more computer usage time were at a higher risk of having depression symptoms (p's < 0.05) and (ii) a higher frequency of fried food consumption were associated with a higher risk of having depression, anxiety, and stress symptoms (p's < 0.05). Additionally, the cross-lagged analysis showed that (i) computer usage time in 2014 is positively correlated with depression status (ß = 0.106, p < 0.05) but not anxiety (ß = 0.047, p > 0.05) and stress (ß = 0.019, p > 0.05) status a year later and (ii) fried food consumption in 2014 is positively correlated with depression (ß = 0.129, p < 0.01), anxiety (ß = 0.168, p < 0.001), and stress (ß = 0.113, p < 0.01) status a year later. Conclusions: Computer usage time and fried food consumption were lifestyle-related risk factors for mental health problems in male college students in Chongqing, China. These results might emphasize further preventive strategies for mental health problems, especially in male college students.
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Saúde Mental , Estudantes , Humanos , Feminino , Masculino , Estilo de Vida , Fatores de Risco , China/epidemiologiaRESUMO
Background: The association between educational attainment (EA) and offspring birth weight (BW) has been reported by several traditional epidemiological studies. However, evidence for this association tends to be mixed and confounded. This study aimed to investigate the causal association between EA of parents and offspring BW. Methods: Here, we carried out a two-sample bidirectional Mendelian randomization (MR) analysis to examine the causal association between EA of males (n = 131,695) and females (n = 162,028) and offspring BW using genetic instruments. Summary statistics of EA associated single nucleotide polymorphisms (SNPs) were extracted from a GWAS incorporating 293,723 individuals of European descent performed by the Social Science Genetic Association Consortium (SSGAC), and the effects of these SNPs on offspring BW were estimated using a GWAS meta-analysis of 86,577 participants of European descent from 25 studies. Univariable MR analyses were conducted using the inverse-variance weighted (IVW) method and four other methods. Further sensitivity analyses were carried out to test the viability of the results. Multivariable MR was used to examine the confounders between the exposure and outcome. Results: The result shows evidence that the offspring BW is positively causally affected by female EA. Each one standard deviation (SD) increase in female EA was associated with 0.24 SD higher of offspring BW (95% confidence interval [CI], 0.10 to 0.37, p < 0.001 for the IVW method). Similarly, change in offspring BW was 0.21 SD (95% CI: 0.07 to 0.34, p = 2.82 × 10-3) per one SD higher in male EA. No causal effect of BW on EA was found by any of the five methods. The causal association between female EA and offspring BW maintained after adjusting for alcoholic drinks per week and BMI. The effect of male EA on offspring BW was attenuated when we adjusted for BMI and alcoholic drinks per week using multivariable MR analysis. Conclusion: Our study indicated that female EA is positively causally associated with offspring BW. The association between male EA and offspring BW may be confounded by alcoholic drinks per week and BMI.
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Objective: To explore the differences in the clinical efficacy, complications, and safety of transurethral plasmakinetic resection of the prostate (PKRP) by the conventional approach versus the approach preserving the urethral mucosa at the prostatic apex in the treatment of benign prostatic hyperplasia (BPH). Methods: A total of 90 patients with PKRP admitted to the First Hospital of Qinhuangdao from December 2018 to March 2021 were selected and divided into a control group (conventional PKRP, n = 45) and an observation group (PKRP with preserved urethral mucosa at the prostatic apex, n = 45). The clinical efficacy, safety, and sexual function of the groups were evaluated using the patients' International Prostate Symptom Score (IPSS), quality of life (QoL), prostate volume, maximum flow rate (Qmax), post-void residual (PVR), blood loss, surgical resection efficiency, and surgical complication data. Results: The differences in the preoperative indicators, glandectomy quality, and glandectomy rate between the groups were not statistically significant (P > 0.05). However, in the observation group, the surgery time and blood loss were significantly lower compared with the control group, and the resection efficiency was significantly higher, with statistical significance (P < 0.05). In the follow-up, one month after surgery, the IPSS and QoL were lower in the observation group than in the control group, and the differences were statistically significant (P < 0.05); three months after surgery, the PVR, IPSS, QoL, and Qmax scores were similar between the groups, with no statistical significance (P > 0.05). In terms of surgical complications, the incidences of urinary incontinence and other complications after catheter extraction were significantly lower in the observation group than in the control group, and the differences between the groups were statistically significant (P < 0.05). Conclusion: Compared with conventional PKRP, PKRP with preserved urethral mucosa at the prostatic apex can lead to immediate urinary continence after catheter extraction, reduce intraoperative blood loss, and shorten the surgery time, thus improving the surgical efficiency.
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The key to breaking through the capacity limitation imposed by intercalation chemistry lies in the ability to harness more active sites that can reversibly accommodate more ions (e.g., Li+ ) and electrons within a finite space. However, excessive Li-ion insertion into the Li layer of layered cathodes results in fast performance decay due to the huge lattice change and irreversible phase transformation. In this study, an ultrahigh reversible capacity is demonstrated by a layered oxide cathode purely based on manganese. Through a wealth of characterizations, it is clarified that the presence of low-content Li2 MnO3 domains not only reduces the amount of irreversible O loss; but also regulates Mn migration in LiMnO2 domains, enabling elastic lattice with high reversibility for tetrahedral sites Li-ion storage in Li layers. This work utilizes bulk cation disorder to create stable Li-ion-storage tetrahedral sites and an elastic lattice for layered materials, with a reversible capacity of 600 mA h g-1 , demonstrated in th range 0.6-4.9 V versus Li/Li+ at 10 mA g-1 . Admittedly, discharging to 0.6 V might be too low for practical use, but this exploration is still of great importance as it conceptually demonstrates the limit of Li-ions insertion into layered oxide materials.
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Micro-Ondas , Miócitos Cardíacos , Animais , Autofagia , Micro-Ondas/efeitos adversos , Ratos , Ratos WistarRESUMO
Electrochemical oxygen reduction provides an eco-friendly synthetic route to hydrogen peroxide (H2O2), a widely used green chemical. However, the kinetically sluggish and low-selectivity oxygen reduction reaction (ORR) is a key challenge to electrochemical production of H2O2 for practical applications. Herein, we demonstrate that single cobalt atoms anchored on oxygen functionalized graphene oxide form Co-O-C@GO active centres (abbreviated as Co1@GO for simplicity) that act as an efficient and durable electrocatalyst for H2O2 production. This Co1@GO electrocatalyst shows excellent electrochemical performance in O2-saturated 0.1 M KOH, exhibiting high reactivity with an onset potential of 0.91 V and H2O2 production of 1.0 mg cm-2 h-1 while affording high selectivity of 81.4% for H2O2. Our combined experimental observations and theoretical calculations indicate that the high reactivity and selectivity of Co1@GO for H2O2 electrogeneration arises from a synergistic effect between the O-bonded single Co atoms and adjacent oxygen functional groups (C-O bonds) of the GO present in the Co-O-C active centres.
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Flexibility has become a certain trend in the development of secondary batteries to meet the requirements of wide portability and applicability. On account of their intrinsic high energy density, flexible alkali metal-chalcogen batteries are attracting increasing interest. Although great advances have been made in promoting the electrochemical performance of metal-S or metal-Se batteries, explorations on flexible chalcogen-based batteries are still limited. Extensive and rational use of soft materials for electrodes is the main bottleneck. The re-emergence of safe liquid metals (LMs), which provide an ideal combination of metallic and fluidic properties at room temperature, offers a fascinating paradigm for constructing flexible chalcogen batteries. They may provide dendrite-free anodes and restrain the dissolution of polysulfides and polyselenides for cathodes. From this perspective, we elaborate on the appealing features of LMs for the construction of flexible metal-chalcogen batteries. Recent advances on LM-based battery are discussed, covering novel liquid alkali metals as anodes and LM-sulfur hybrids as cathodes, with the focus placed on durable high-energy-density output and self-healing flexible capability. At last, perspectives are proposed on the future development of LM-based chalcogen batteries, and the viable strategies to meet the current challenges that are obstructing more practical flexible chalcogen batteries.