A multi-center cross-sectional investigation of the diagnosis and treatment of breast cancer with synchronous ipsilateral supraclavicular lymph node metastases based on the CSBrs-009

Background The diagnosis and management of breast cancer with ipsilateral supraclavicular lymph node metastases currently lack any applicable criteria or guidelines (ISLM), and diagnostic and treatment strategies are varied by medical centers. This study aimed to determine the current status of the diagnosis and treatment of breast cancer with ISLM among Chinese patients. Methods Data from 30 hospitals on ISLM breast cancer patients between January 1, 2018, and December 31, 2018, were systematically analyzed for the detection rate, clinicopathological characteristics, diagnosis and treatment strategies of breast cancer with ISLM among Chinese patients. Results A total of 26,723 women presented with breast cancer in 30 hospitals over the study period. A total of 127 ISLM breast cancer patients were finally enrolled. Synchronous ISLM without distant metastases was present in 0.48% of cases. The diagnosis of patients with 86.6% of ISLM was based on ultrasound examinations. The proportion of ISLM diagnosed by fine-needle aspiration biopsy (FNA) or core-needle biopsy (CNB) before surgery was 16.5% and 37.0%, respectively. Moreover, 45.7% of the ISLM patients had no pathological evidence. Regarding treatment strategies, 69.3% of ISLM patients received neoadjuvant chemotherapy (NAC) for more than 4 cycles, while 15.7% of patients did not receive NAC. 86.6% of ISLM patients underwent a mastectomy, and breast-conserving surgery was performed in 3.9% of ISLM patients. Moreover, 41.7% of ISLM patients received supraclavicular lymph node dissection (SCLD), while 47.2% were not treated with SCLD. Conclusions The overall detection rate of breast cancer in patients with ISLM is low in China and varies widely between hospitals. There is no consensus on the optimal diagnosis and treatment of patients with ISLM breast cancer (AU)

Prevalence and incidence of heart failure among community in China during a three-year follow-up.

BACKGROUND: Epidemiological surveys on heart failure (HF) in Chinese community are relatively lacking. This study aimed to estimate the prevalence and incidence of HF among community residents in southern China. METHODS: Baseline data of this prospective study was collected from 2015 to 2017 among 12,013 permanent residents aged ≥ 35 years in Guangzhou, China. The same survey process was carried out for individuals aged ≥ 65 years after a three-year follow-up. RESULTS: The overall prevalence of HF in community residents aged ≥ 35 years was 1.06%. Male had significantly higher risk of HF prevalence [odds ratio (OR) = 1.50, P = 0.027]. The gender-adjusted risk of HF was 1.48 times higher per 10 years aging. HF prevalence was statistically associated with atrial fibrillation, valvular heart disease, hypertension and chronic obstructive pulmonary disease after adjusting for age and gender (OR = 8.30, 5.17, 1.11, 2.28, respectively; all P < 0.05). HF incidence in individuals aged ≥ 65 years were 847 per 100,000 person-years. Baseline atrial fibrillation, valvular heart disease, and diabetes mellitus were risk factors for HF incidence for individuals aged ≥ 65 years adjusting for age and gender (OR = 5.05, 3.99, 2.11, respectively; all P < 0.05). Besides, residents with new-onset atrial fibrillation and myocardial infarction were at significantly higher risk of progression to HF (OR = 14.41, 8.54, respectively; all P < 0.05). CONCLUSIONS: Both pre-existing and new-onset cardiovascular diseases were associated with HF incidence in southern China. Management of related cardiovascular diseases may be helpful to reduce the incidence of HF.

Improvement of catalytic activity of sorbose dehydrogenase for deoxynivalenol degradation by rational design.

Deoxynivalenol (DON) is the most frequently contaminated mycotoxin in food and feed worldwide, causing significant economic losses and health risks. Physical and chemical detoxification methods are widely used, but they cannot efficiently and specifically remove DON. In the study, the combination of bioinformatics screening and experimental verification confirmed that sorbose dehydrogenase (SDH) can effectively convert DON to 3-keto-DON and a substance that removes four hydrogen atoms for DON. Through rational design, the Vmax of the mutants F103L and F103A were increased by 5 and 23 times, respectively. Furthermore, we identified catalytic sites W218 and D281. SDH and its mutants have broad application conditions, including temperature ranges of 10-45 °C and pH levels of 4-9. Additionally, the half-lives of F103A at 90 °C (processing temperature) and 30 °C (storage temperature) were 60.1 min and 100.5 d, respectively. These results suggest that F103A has significant potential in the detoxification application of DON.

Identification and characterization of a new variation in DPM2 gene in two Chinese siblings with mild intellectual impairment.

Introduction: Congenital disorders of glycosylation (CDGs) are a genetically heterogeneous group of metabolic disorders caused by abnormal protein or lpid glycosylation. DPM2 is one subunit of a heterotrimeric complex for dolichol-phosphatemannose synthase (DPMS), a key enzyme in glycosylation, and only four patients with DPM2-CDG have been reported. Methods: Whole-exome sequencing (WES) was performed in a Chinese family having two siblings with a mild form of DPM2-CDG with developmental delay, mild intellectual disability, hypotonia, and increased serum creatine kinase. Sanger sequencing was used to validate the variants identified in the siblings and their parents. In vitro functional study was performed. Results: A homozygous mutation, c.197G>A (p.Gly66Glu) in exon 4 of DPM2 (NM_003863) was identified by whole exome sequencing (WES). In vitro functional analysis demonstrated that this variant increased the expression level of DPM2 protein and western blot revealed a significant decrease in ICAM1, a universal biomarker for hypoglycosylation in patients with CDG, suggesting abnormal N-linked glycosylation. We also reviewed the 4 previously reported patients carrying homozygous or compound heterozygous variants of DMP2 gene, and found that patients with variants within the region encoding the first domain had more severe clinical symptoms than those with variants within the second domain. However, the actual genotype-phenotype relationship needs more study. Discussion: Overall, our study broadens the variant spectrum of DPM2 gene, attempts to explain the different phenotypes in patients with different DPM2 variants, and emphasizes the need of further functional studies to understand the underlying pathophysiology of the phenotypic heterogeneity.

Cementum protein 1 gene-modified adipose-derived mesenchymal stem cell sheets enhance periodontal regeneration in osteoporosis rat.

BACKGROUND AND OBJECTIVES: Osteoporosis (OP) and periodontitis are both diseases with excessive bone resorption, and the number of patients who suffer from these diseases is expected to increase. OP has been identified as a risk factor that accelerates the pathological process of periodontitis. Achieving effective and safe periodontal regeneration in OP patients is a meaningful challenge. This study aimed to assess the efficacy and biosecurity of human cementum protein 1 (hCEMP1) gene-modified cell sheets for periodontal fenestration defect regeneration in an OP rat model. MATERIALS AND METHODS: Rat adipose-derived mesenchymal stem cells (rADSCs) were isolated from Sprague-Dawley rats. After primary culture, rADSCs were subjected to cell surface analysis and multi-differentiation assay. And rADSCs were transduced with hCEMP1 by lentiviral vector, and hCEMP1 gene-modified cell sheets were generated. The expression of hCEMP1 was evaluated by reverse transcription polymerase chain reaction and immunocytochemistry staining, and transduced cell proliferation was evaluated by Cell Counting Kit-8. The hCEMP1 gene-modified cell sheet structure was detected by histological analysis and scanning electron microscopy. Osteogenic and cementogenic-associated gene expression was evaluated by real-time quantitative polymerase chain reaction. In addition, an OP rat periodontal fenestration defect model was used to evaluate the regeneration effect of hCEMP1 gene-modified rADSC sheets. The efficacy was assessed with microcomputed tomography and histology, and the biosecurity of gene-modified cell sheets was evaluated by histological analysis of the spleen, liver, kidney and lung. RESULTS: The rADSCs showed a phenotype of mesenchymal stem cells and possessed multi-differentiation capacity. The gene and protein expression of hCEMP1 through lentiviral transduction was confirmed, and there was no significant effect on rADSC proliferation. Overexpression of hCEMP1 upregulated osteogenic and cementogenic-related genes such as runt-related transcription factor 2, bone morphogenetic protein 2, secreted phosphoprotein 1 and cementum attachment protein in the gene-modified cell sheets. The fenestration lesions in OP rats treated with hCEMP1 gene-modified cell sheets exhibited complete bone bridging, cementum and periodontal ligament formation. Furthermore, histological sections of the spleen, liver, kidney and lung showed no evident pathological damage. CONCLUSION: This pilot study demonstrates that hCEMP1 gene-modified rADSC sheets have a marked ability to enhance periodontal regeneration in OP rats. Thus, this approach may represent an effective and safe strategy for periodontal disease patients with OP.

Early diagnosis of coronary microvascular dysfunction by myocardial contrast stress echocardiography.

Coronary microvascular dysfunction (CMD) is one of the basic mechanisms of myocardial ischemia. Myocardial contrast echocardiography (MCE) is a bedside technique that utilises microbubbles which remain entirely within the intravascular space and denotes the status of microvascular perfusion within that region. Some pilot studies suggested that MCE may be used to diagnose CMD, but without further validation. This study is aimed to investigate the diagnostic performance of MCE for the evaluation of CMD. MCE was performed at rest and during adenosine triphosphate stress. ECG triggered real-time frames were acquired in the apical 4-chamber, 3-chamber, 2-chamber, and long-axis imaging planes. These images were imported into Narnar for further processing. Eighty-two participants with suspicion of coronary disease and absence of significant epicardial lesions were prospectively investigated. Thermodilution was used as the gold standard to diagnose CMD. CMD was present in 23 (28%) patients. Myocardial blood flow reserve (MBF) was assessed using MCE. CMD was defined as MBF reserve < 2. The MCE method had a high sensitivity (88.1%) and specificity (95.7%) in the diagnosis of CMD. There was strong agreement with thermodilution (Kappa coefficient was 0.727; 95% CI: 0.57-0.88, p < 0.001). However, the correlation coefficient (r = 0.376; p < 0.001) was not high.

ROS-induced lipid peroxidation modulates cell death outcome: mechanisms behind apoptosis, autophagy, and ferroptosis.

Reactive oxygen species (ROS) mediate lipid peroxidation and produce 4-hydroxynonenal and other related products, which play an important role in the process of cell death, including apoptosis, autophagy, and ferroptosis. Lipid peroxidation of phospholipid bilayers can promote mitochondrial apoptosis, endoplasmic reticulum stress, and other complex molecular signaling pathways to regulate apoptosis. Lipid peroxidation and its products also act at different stages of autophagy, affecting the formation of autophagosomes and the recruitment of downstream proteins. In addition, we discuss the important role of ROS and lipid peroxides in ferroptosis and the regulatory role of nuclear factor erythroid 2-related factor 2 in ferroptosis under a background of oxidation. Finally, from the perspectives of promotion, inhibition, transformation, and common upstream molecules, we summarized the crosstalk among apoptosis, autophagy, and ferroptosis in the context of ROS. Our review discusses the role of ROS and lipid peroxidation in apoptosis, autophagy, and ferroptosis and their possible crosstalk mechanisms, so as to provide new insights and directions for the study of diseases related to pathological cell death. This review also has referential significance for studying the exact mechanism of ferroptosis mediated by lipid peroxidation.

Machine learning of spectra-property relationship for imperfect and small chemistry data.

Machine learning (ML) is causing profound changes to chemical research through its powerful statistical and mathematical methodological capabilities. However, the nature of chemistry experiments often sets very high hurdles to collect high-quality data that are deficiency free, contradicting the need of ML to learn from big data. Even worse, the black-box nature of most ML methods requires more abundant data to ensure good transferability. Herein, we combine physics-based spectral descriptors with a symbolic regression method to establish interpretable spectra-property relationship. Using the machine-learned mathematical formulas, we have predicted the adsorption energy and charge transfer of the CO-adsorbed Cu-based MOF systems from their infrared and Raman spectra. The explicit prediction models are robust, allowing them to be transferrable to small and low-quality dataset containing partial errors. Surprisingly, they can be used to identify and clean error data, which are common data scenarios in real experiments. Such robust learning protocol will significantly enhance the applicability of machine-learned spectroscopy for chemical science.

Erasable Domain Wall Current-Dominated Resistive Switching in BiFeO3 Devices with an Oxide-Metal Interface.

Electric transport in the charged domain wall (CDW) region has emerged as a promising phenomenon for the development of next-generation ferro-resistive memory with ultrahigh data storage density. However, accurately measuring the conductivity of CDWs induced by polarization reversal remains challenging due to the polarization modulation of the Schottky barrier at the thin film-electrode interface, which could partially contribute to the collected "on" current of the device. Here, we propose carefully selecting an electrode that can suppress the effect of interfacial barrier modulation induced by polarization reversal, allowing the collected current mainly from the conductive CDWs. The experiment was conducted on epitaxial BiFeO3(001) thin-film devices with vertical and horizontal geometries. Piezo-response force microscopy scanning showed the local polarization experienced 180° rotation to form CDWs under the vertical electric field. However, devices with SrRuO3 epitaxial top electrodes still exhibit an interfacial barrier-dominated diode behavior, with the "on" current proportional to the electrode area. To identify the CDW current, more interfacial defects were introduced by the deposition of Pt top electrodes, which significantly enhanced charge injection for the compensation of the reversed polarization driven by the electric field, leading to the suppressed polarization modulation of the Schottky barrier height. It was observed that the current flow through Pt electrodes is significantly lower compared to that of SRO electrodes and appears to be primarily influenced by the electrode perimeter instead of the electrode area, indicating CDW-dominated conduction behavior in these devices. Planar nanodevices were further fabricated to support the quantitative investigation of the Pt electrode size-dependent "on" current with a linear fit of the current magnitude versus the CDW cross-sectional area. This work constitutes an essential part of understanding the role of the CDW current in ferro-resistive memory devices.

Machine Learning Descriptors for Data-Driven Catalysis Study.

Traditional trial-and-error experiments and theoretical simulations have difficulty optimizing catalytic processes and developing new, better-performing catalysts. Machine learning (ML) provides a promising approach for accelerating catalysis research due to its powerful learning and predictive abilities. The selection of appropriate input features (descriptors) plays a decisive role in improving the predictive accuracy of ML models and uncovering the key factors that influence catalytic activity and selectivity. This review introduces tactics for the utilization and extraction of catalytic descriptors in ML-assisted experimental and theoretical research. In addition to the effectiveness and advantages of various descriptors, their limitations are also discussed. Highlighted are both 1) newly developed spectral descriptors for catalytic performance prediction and 2) a novel research paradigm combining computational and experimental ML models through suitable intermediate descriptors. Current challenges and future perspectives on the application of descriptors and ML techniques to catalysis are also presented.

A Survey of Myopia Correction Pattern of Children and Parent's Attitudes in China.

SIGNIFICANCE: This survey provides information about Chinese children's myopia correction status and parents' attitudes toward myopia correction. PURPOSE: Under the background of a guideline of appropriate techniques for the prevention and control of children's myopia, this study aimed to investigate the current myopia correction pattern of children and parents' attitudes. METHODS: Two self-administered questionnaires were distributed to 684 children with myopia corrections and 450 parents (384 mothers and 66 fathers) to explore children's myopia correction patterns and parental attitudes. The questionnaire investigated the pattern of children's myopia correction, prescribing of children's myopia correction, the incidence of high myopia, parental attitudes towards various myopia corrections methods, and preferred initial age for contact lens usage. RESULTS: Single-vision spectacles (n = 600, 88.2 ± 7.4%) are widely used in China due to their comfort and affordability. More than 80% of children use single-vision spectacles prescribed by ophthalmologists and opticians. Children who used single-vision spectacles at an earlier age had more incidence of high myopia (18.4 ± 4.2%) than those who used single-vision spectacles at a later age (0.7 ± 0.9%). Effective myopia control was the primary reason parents preferred to choose different optical corrections, followed by safety, convenience, clarity, affordability, comfort, and other reasons. The survey indicated that 52.4% of parents whose children used orthokeratology lenses would have preferred safe and convenient options if available. Additionally, 50% of the parents preferred delaying their children's use of orthokeratology lenses and other contact lenses to an older age. CONCLUSIONS: Single-vision spectacles are still a popular option to correct myopia in children. There was a demonstrated increase in myopia in children who used single spectacles at an earlier age. Parents' attitudes were important factors for selecting myopia corrections in children.

Decoupling Analysis of O2 Adsorption on Metal-N-C Single-Atom Catalysts via Data-Driven Descriptors.

The adsorption energy of adsorbed molecules on single-atom catalysts is a key indicator of the catalytic activity of the catalysts. Developing a generic and interpretable structure-property prediction model from numerous influencing factors is a challenging task. In this work, we constructed a machine learning (ML) model from first-principles calculations of the adsorption energy data of O2 on Ni(II), Co(II), Cu(II), Fe(II), Fe(III), and Mn(II) single-atom catalysts supported on 15 different N-C substrates under various spin states. A mathematic formula is proposed to predict the adsorption energy by a novel data-driven descriptor derived from physically meaningful factors such as geometric distances and atomic charges. This data-driven descriptor is relevant to only the geometrical configuration of the adsorbate, while the parameters in the linear formulas contain only substrate-specific information. This ML model with the ability to decouple variables will greatly advance the understanding of metal-N-C single-atom catalysts and help in the design of new substrates to modulate catalytic activity.

Deep learning segmentation of the tear fluid reservoir under the sclera lens in optical coherence tomography images.

The tear fluid reservoir (TFR) under the sclera lens is a unique characteristic providing optical neutralization of any aberrations from corneal irregularities. Anterior segment optical coherence tomography (AS-OCT) has become an important imaging modality for sclera lens fitting and visual rehabilitation therapy in both optometry and ophthalmology. Herein, we aimed to investigate whether deep learning can be used to segment the TFR from healthy and keratoconus eyes, with irregular corneal surfaces, in OCT images. Using AS-OCT, a dataset of 31850 images from 52 healthy and 46 keratoconus eyes, during sclera lens wear, was obtained and labeled with our previously developed algorithm of semi-automatic segmentation. A custom-improved U-shape network architecture with a full-range multi-scale feature-enhanced module (FMFE-Unet) was designed and trained. A hybrid loss function was designed to focus training on the TFR, to tackle the class imbalance problem. The experiments on our database showed an IoU, precision, specificity, and recall of 0.9426, 0.9678, 0.9965, and 0.9731, respectively. Furthermore, FMFE-Unet was found to outperform the other two state-of-the-art methods and ablation models, suggesting its strength in segmenting the TFR under the sclera lens depicted on OCT images. The application of deep learning for TFR segmentation in OCT images provides a powerful tool to assess changes in the dynamic tear film under the sclera lens, improving the efficiency and accuracy of lens fitting, and thus supporting the promotion of sclera lenses in clinical practice.

Association between CORIN promoter methylation and stroke: Results from two independent samples of Chinese adults.

Objective: As the physical activator of natriuretic peptides, corin has been associated with stroke, but the underlying mechanism is not very clear. Here, we examined whether the CORIN promoter's methylation, an epigenetic DNA modification, was associated with the risk of stroke in two independent samples. Methods: A total of 1771 participants including 853 stroke cases and 918 healthy controls were included as a discovery sample and 2,498 community members with 10 years of follow-up were included as a replication sample. DNA methylation of the CORIN promoter was quantified by target bisulfite sequencing in both samples. We first examined the single CpG association, followed by a gene-based analysis of the joint association between multiple CpG methylation and stroke, adjusting for conventional risk factors. Results: The single CpG association analysis found that hypermethylation at all of the 9 CpG sites assayed was significantly associated with lower odds of prevalent stroke in the discovery sample (all p < 0.05), and three of them located at Chr4:47840038 (HR = 0.74, p = 0.015), Chr4:47839941 (HR = 0.80, p = 0.047), and Chr4:47839933 (HR = 0.82, p = 0.050) were also significantly associated with incident stroke in the replication sample. The gene-based association analysis found that DNA methylation of the 9 CpG sites at the CORIN promoter was jointly associated with stroke in both samples (all p < 0.05). Conclusion: DNA methylation levels of the CORIN gene promoter were lower in stroke patients and predicted a higher risk of incident stroke in Chinese adults. The underlying causality warranted further investigation.

The diagnostic performance of AccuFFRangio for evaluating coronary artery stenosis under different computational conditions.

Background: A computational method (AccuFFrangio) based on invasive coronary angiography (ICA) and computational fluid dynamics (CFD) to calculate fractional flow reserve (FFR) without a pressure wire has been devised to clarify the physiological significance of coronary stenosis. This study aimed to evaluate the diagnostic performance of AccuFFRangio computation under different boundary conditions and vessel reconstruction approaches. Methods: Consecutive patients with stable angina pectoris who underwent ICA and FFR assessment from 2 centers were analyzed retrospectively. Using wire-based FFR as the reference standard, the diagnostic performances of AccuFFRangio and its variations were evaluated and compared. The calculation of AccuFFRangio involves several key boundary conditions, including patient-specific aortic pressure, contrast flow velocity derived from the thrombolysis in myocardial infarction (TIMI) frame count method, and vessel reconstruction based on 2 angiographic views. We considered the following 3 variations: (I) a fixed aortic pressure [fixed pressure AccuFFRangio (pAccuFFRangio)], (II) an empirical hyperemic velocity [fixed velocity AccuFFRangio (vAccuFFRangio)], and (III) vessel reconstruction using a single angiographic view [single view AccuFFRangio (sAccuFFRangio)]. Results: A total of 230 patients with 230 vessels were included in the final analysis. The accuracy for standard AccuFFRangio, pAccuFFRangio, vAccuFFRangio, and sAccuFFRangio was 93.91%, 86.52%, 81.74%, and 83.48%, respectively; the sensitivity was 90.74%, 51.85%, 83.33%, and 46.30%, respectively; the specificity was 94.89%, 97.16%, 81.25%, and 94.89%, respectively; and the area under the receiver operating characteristic curve was 0.971, 0.928, 0.892, and 0.870, respectively. Conclusions: The comparison suggested that the overall performance of the standard AccuFFRangio was superior to other variations and had the highest accuracy among all the cases.

Automatic interictal epileptiform discharge (IED) detection based on convolutional neural network (CNN).

Clinical diagnosis of epilepsy significantly relies on identifying interictal epileptiform discharge (IED) in electroencephalogram (EEG). IED is generally interpreted manually, and the related process is very time-consuming. Meanwhile, the process is expert-biased, which can easily lead to missed diagnosis and misdiagnosis. In recent years, with the development of deep learning, related algorithms have been used in automatic EEG analysis, but there are still few attempts in IED detection. This study uses the currently most popular convolutional neural network (CNN) framework for EEG analysis for automatic IED detection. The research topic is transferred into a 4-labels classification problem. The algorithm is validated on the long-term EEG of 11 pediatric patients with epilepsy. The computational results confirm that the CNN-based model can obtain high classification accuracy, up to 87%. The study may provide a reference for the future application of deep learning in automatic IED detection.

Promoting Oxygen Reduction Reaction by Inducing Out-of-plane Polarization in Metal Phthalocyanine Catalyst.

Metal phthalocyanine (MPc) materials with well-defined MN4 moiety offers a platform for catalyzing oxygen reduction reaction (ORR), while their practical performances are often limited by the insufficient O2 adsorption due to the planar MN4 nature. Here, we proposed a design (called as Gr-MG -O-MP Pc) that the metal of MPc (MP ) is axially coordinated to a single metal atom in graphene (Gr-MG ) through a bridge-bonded oxygen atom (O), introducing effective out-of-plane polarization to promote O2 adsorption on MPc. Manipulating the out-of-plane polarization charge by varying types of MP and MG (MP = Fe/Co/Ni, MG = Ti/V/Cr/Mn/Fe/Co/Ni) in the axial coordination zone of -MG -O-MP - were examined by density functional theory simulations. Among them, the catalyst of Gr-V-O-FePc stands out with the highest calculated O2 adsorption energy, which was synthesized successfully and verified by systemic X-ray absorption spectroscopy measurements. Importantly, it delivered a remarkable ORR performance with half-wave potential of 0.925 V (versus RHE) and kinetic current density of 26.7 mA cm-2 . This thus demonstrates a new and simple way to pursue high catalytic performance by inducing out-of-plane polarization in catalysts. This article is protected by copyright. All rights reserved.

Promoting Oxygen Reduction Reaction on Carbon-based Materials by Selective Hydrogen Bonding.

Electrochemical oxygen reduction reaction (ORR) is fundamental for many energy conversion and storage devices. Selective tuning of *OOH/*OH adsorption energy to break the intrinsic scaling limitation (ΔG*OOH = ΔG*OH + 3.2 eV) is effective in optimizing the ORR limiting potential (UL), which however, is practically challengeable to be achieved by constructing a particular catalyst. Herein, using first-principles calculations, we elucidated how to rationally plant an additional *OH that can selectively interact with the ORR intermediate of *OOH via hydrogen bonding, while not affecting the *OH intermediate. Guided by the design principle, we successfully tailored a series of novel carbon-based catalysts, with merits of low-cost, long-lasting, synthesis feasibility, exhibiting a high UL (1.06 V). Our proposed strategy comes up with a new linear scaling relationship of ΔG*OOH = ΔG*OH + 2.84 eV. This approach offers a great possibility for the rational design of efficient catalysts for ORR and other chemical reactions.

Ultrahigh Effective Diffusion in Oxide by Engineering the Interfacial Transporter Channels.

Mass storage and removal in solids always play a vital role in technological applications such as modern batteries and neuronal computations. However, they were kinetically limited by the slow diffusional process in the lattice, which made it challenging to fabricate applicable conductors with high electronic and ionic conductivities at room temperature. Here, we proposed an acid solution/WO3/ITO sandwich structure and achieved ultrafast H transport in the WO3 layer by interfacial job-sharing diffusion, which means the spatially separated transport of the H+ and e- in different layers. From the color change of WO3, the effective diffusion coefficient (Deff) was estimated, dramatically increasing ≤106 times and overwhelming values from previous reports. The experiments and simulations also revealed the universality of extending this approach to other atoms and oxides, which could stimulate systematic studies of ultrafast mixed conductors in the future.

Myopia prevention and control in children: a systematic review and network meta-analysis.

OBJECTIVES: To analyse and compare the efficacy of different interventions for myopia prevention and control in children. METHODS: We searched CNKI, VIP, Wan-Fang, CBM, Chinese Clinical Registry, PubMed, The Cochrane Library, Web of Science, Embase and ClinicalTrials.gov from inception to July 2022. We selected randomized controlled trials (RCTs) that included interventions to slow myopia progression in children. The main outcomes included mean annual change in axial length (AL) (millimetres/year) and in refraction (R) (dioptres/year). RESULTS: A total of 80 RCTs (27103 eyes) were included. In comparison with control, orthokeratology (AL, -0.36 [-0.53, -0.20], P < 0.05; R, 0.56 [0.34, 0.77], P < 0.05), 1%Atropine (AL, -0.39 [-0.65, -0.13], P < 0.05; R, 0.54 [0.31, 0.77], P < 0.05), 0.01%Atropine + orthokeratology (AL, -0.47 [-0.80, -0.14], P < 0.05; R, 0.81 [0.43, 1.20], P < 0.05) could significantly slow the progression of myopia; in addition, progressive multi-focal spectacle lenses (PMSL) (0.42, [0.06, 0.79], P < 0.05), bifocal soft contact lenses (0.40, [0.03, 0.77], P < 0.05), 0.5%Atropine (0.67 [0.25, 1.10], P < 0.05), 0.1%Atropine (0.42 [0.15, 0.71], P < 0.05), 0.05%Atropine (0.57 [0.28, 0.86], P < 0.05), 0.01%Atropine (0.33 [0.15, 0.52], P < 0.05), 1%Atropine + bifocal spectacle lenses (BSL) (1.30 [0.54, 2.00], P < 0.05), 1%Atropine + PMSL (0.66 [0.23, 1.10], P < 0.05), 0.01%Atropine + single vision spectacle lenses (SVSL) (0.70 [0.23, 1.10], P < 0.05), 0.01%Atropine + orthokeratology (0.81 [0.43, 1.20], P < 0.05), BSL + Massage (0.85 [0.22, 1.50], P < 0.05), SVSL + Red light (0.59 [0.06, 0.79], P < 0.05) showed significant slowing effect on the increase in R. CONCLUSIONS: This network meta-analysis suggests that the combined measures were most effective in AL and R, followed by Atropine.