Machine learning for the early prediction of acute respiratory distress syndrome (ARDS) in patients with sepsis in the ICU based on clinical data.

Background: Acute respiratory distress syndrome (ARDS) is a fatal outcome of severe sepsis. Machine learning models are helpful for accurately predicting ARDS in patients with sepsis at an early stage. Objective: We aim to develop a machine-learning model for predicting ARDS in patients with sepsis in the intensive care unit (ICU). Methods: The initial clinical data of patients with sepsis admitted to the hospital (including population characteristics, clinical diagnosis, complications, and laboratory tests) were used to predict ARDS, and screen out the crucial variables. After comparing eight different algorithms, namely, XG boost, logistic regression, light GBM, random forest, GaussianNB, complement NB, support vector machine (SVM), and K nearest neighbors (KNN), rebuilding a prediction model with the best one. When remodeling with the best algorithm, 10% was randomly selected to test, and the remaining was trained for cross-validation. Using the area under the curve (AUC), sensitivity, accuracy, specificity, positive and negative predictive value, F1 score, kappa value, and clinical decision curve to evaluate the model's performance. Eventually, the application in the model illustrated by the SHAP package. Results: Ten critical features were screened utilizing the lasso method, namely, PaO2/PAO2, A-aDO2, PO2(T), CRP, gender, PO2, RDW, MCH, SG, and chlorine. The prior ranking of variables demonstrated that PaO2/PAO2 was the most significant variable. Among the eight algorithms, the performance of the Gaussian NB algorithm was significantly better than that of the others. After remodeling with the best algorithm, the AUC in the training and validation sets were 0.777 and 0.770, respectively, and the algorithm performed well in the test set (AUC = 0.781, accuracy = 78.6%, sensitivity = 82.4%, F1 score = 0.824). A comparison of the overlap factors with those of previous models revealed that the model we developed performs better. Conclusion: Sepsis-associated ARDS can be accurately predicted early via a machine learning model based on existing clinical data. These findings are helpful for accurate identification and improvement of the prognosis in patients with sepsis-associated ARDS.

Transformation of chlorobenzene by Mn(III) generated in MnO2/organic acid systems.

Chlorobenzene (CB) is a prevalent organic contaminant in water and soil environments. It presents high chemical stability and is resistant to both oxidation and reduction. In this study, we showed that CB was substantially removed by soluble Mn(III) produced during the reductive dissolution of colloidal MnO2 by naturally-occurring organic acids such as formate (FOR), oxalate (OX), and citrate (CIT). The removal rate was dependent on the physicochemical properties of organic acids. With strong electron-donating and coordination ability, OX and CIT promoted MnO2 dissolution and Mn(III) generation compared to FOR, but had adverse effects on the stability and reactivity of Mn(III). As a result, CB removal followed the order: MnO2/CIT > MnO2/FOR > MnO2/OX. Analysis of the transformation products showed that Mn(III) complexes acted as strong electrophiles, attacking the ortho/para carbons of the benzene ring and transforming CB to chlorophenols via an electrophilic substitution mechanism. The theoretical foundation of this proposed reaction mechanism was supplemented by quantum mechanical calculations. Together, the findings of this study provide new insights into the transformation of CB in natural environments and hold the potential to offer a novel strategy for the development of manganese oxide/ligand systems for CB elimination.

Classification of superficial suspected lymph nodes: non-invasive radiomic model based on multiphase contrast-enhanced ultrasound for therapeutic options of lymphadenopathy.

Background: Accurate determination of the types of lymphadenopathy is of great importance in disease diagnosis and treatment and is usually confirmed by pathological findings. Radiomics is a non-invasive tool that can extract quantitative information from medical images. Our study was designed to develop a non-invasive radiomic approach based on multiphase contrast-enhanced ultrasound (CEUS) images for the classification of different types of lymphadenopathy. Methods: A total of 426 patients with superficial suspected lymph nodes (LNs) from three centres were grouped into a training cohort (n=190), an internal testing cohort (n=127), and an external testing cohort (n=109). The radiomic features were extracted from the prevascular phase, vascular phase, and postvascular phase of the CEUS images. Model 1 (the conventional feature model), model 2 (the multiphase radiomics model), and model 3 (the combined feature model) were established for lymphadenopathy classification. The area under the curve (AUC) and confusion matrix were used to evaluate the performance of the three models. The usefulness of the models was assessed in different threshold probabilities by decision curve analysis. Results: There were 139 patients (32.6%) with benign LNs, 110 patients (25.8%) with lymphoma, and 177 patients (41.5%) with metastatic LNs in our population. Finally, twenty features were selected to construct the radiomics models for these three types of lymphadenopathy. Model 2 integrating multiphase images of the CEUS yielded the AUCs of 0.838, 0.739, and 0.733 in the training cohort, internal testing cohort, and external testing cohort, respectively. After the combination of conventional features and radiomic features, the AUCs of model 3 improved to 0.943, 0.823 and 0.785 in the training cohort, internal testing cohort, and external testing cohort. Besides, model 3 had an accuracy of 81.05%, sensitivity of 80%, and specificity of 90.43% in the training cohort. Model performance was further confirmed in the internal testing cohort and external testing cohort. Conclusions: We constructed a combined feature model using a series of CEUS images for the classification of the lymphadenopathies. For patients with superficial suspected LNs, this model can help clinicians make a decision on the LN type noninvasively and choose appropriate treatments.

Will changes in charging and gasoline prices affect electric vehicle sales? Evidence from China.

Electric vehicles and gasoline vehicles are substitutes for each other, and the cost of fuel is an important factor when consumers are faced with choices. Understanding the influence of changes in gasoline prices and charging prices on electric vehicle sales is of reference significance for promoting electric vehicles in the private sector. This paper uses data covering 212 prefecture-level cities from January, 2020, to August, 2022, for analysis, and the results show that different income groups have different sensitivities to the difference in oil and electricity prices. Additionally, changes in gasoline prices and charging prices will significantly affect electric vehicle sales in low-income and middle-income cities, electric vehicle sales in high-income cities will not be affected. Compared with nonpilot cities, residents of pilot cities are more sensitive to fuel price changes, indicating that the policy basis has a certain positive effect on the promotion of electric vehicles. It is recommended to consider the income status of regional residents when formulating policies for the use of electric vehicles. At the same time, publicity efforts should be increased to highlight the gap between the cost of fuel vehicles and electric vehicles.

Ideal serum non-ceruloplasmin bound copper prediction for long-term treated patients with Wilson disease: a nomogram model.

Purpose: This study aimed to explore the factors associated with the optimal serum non-ceruloplasmin bound copper (NCBC) level and develop a flexible predictive model to guide lifelong therapy in Wilson disease (WD) and delay disease progression. Methods: We retrospectively collected clinical data from 144 patients hospitalized in the Encephalopathy Center of the first affiliated hospital of Anhui University of Chinese Medicine between May 2012 and April 2023. Independent variables were selected using variate COX and LASSO regressions, followed by multivariate COX regression analysis. A predictive nomogram was constructed and validated using the concordance index (C-index), calibration curves, and clinical decision curve analysis, of which nomogram pictures were utilized for model visualization. Results: A total of 61 (42.36%) patients were included, with an average treatment duration of 55.0 (range, 28.0, 97.0) months. Multivariate regression analysis identified several independent risk factors for serum NCBC level, including age of diagnosis, clinical classification, laminin liver stiffness measurement, and copper to zinc ratio in 24-h urinary excretion. The C-index indicated moderate discriminative ability (48 months: 0.829, 60 months: 0.811, and 72 months: 0.819). The calibration curves showed good consistency and calibration; clinical decision curve analysis demonstrated clinically beneficial threshold probabilities at different time intervals. Conclusion: The predictive nomogram model can predict serum NCBC level; consequently, we recommend its use in clinical practice to delay disease progression and improve the clinical prognosis of WD.

Cauchy combination omnibus test for normality.

Testing whether data are from a normal distribution is a traditional problem and is of great concern for data analyses. The normality is the premise of many statistical methods, such as t-test, Hotelling T2 test and ANOVA. There are numerous tests in the literature and the commonly used ones are Anderson-Darling test, Shapiro-Wilk test and Jarque-Bera test. Each test has its own advantageous points since they are developed for specific patterns and there is no method that consistently performs optimally in all situations. Since the data distribution of practical problems can be complex and diverse, we propose a Cauchy Combination Omnibus Test (CCOT) that is robust and valid in most data cases. We also give some theoretical results to analyze the good properties of CCOT. Two obvious advantages of CCOT are that not only does CCOT have a display expression for calculating statistical significance, but extensive simulation results show its robustness regardless of the shape of distribution the data comes from. Applications to South African Heart Disease and Neonatal Hearing Impairment data further illustrate its practicability.

Screening properties of trend tests in genetic association studies.

In genome-wide association study, extracting disease-associated genetic variants among millions of single nucleotide polymorphisms is of great importance. When the response is a binary variable, the Cochran-Armitage trend tests and associated MAX test are among the most widely used methods for association analysis. However, the theoretical guarantees for applying these methods to variable screening have not been built. To fill this gap, we propose screening procedures based on adjusted versions of these methods and prove their sure screening properties and ranking consistency properties. Extensive simulations are conducted to compare the performances of different screening procedures and demonstrate the robustness and efficiency of MAX test-based screening procedure. A case study on a dataset of type 1 diabetes further verifies their effectiveness.

Interlayer-Confined NiFe Dual Atoms within MoS2 Electrocatalyst for Ultra-Efficient Acidic Overall Water Splitting.

Confining dual atoms (DAs) within the van der Waals gap of 2D layered materials is expected to expedite the kinetic and energetic strength in catalytic process, yet is a huge challenge in atomic-scale precise assembling DAs within two adjacent layers in the 2D limit. Here, an ingenious approach is proposed to assemble DAs of Ni and Fe into the interlayer of MoS2 . While inheriting the exceptional merits of diatomic species, this interlayer-confined structure arms itself with confinement effect, displaying the more favorable adsorption strength on the confined metal active center and higher catalytic activity towards acidic water splitting, as verified by intensive research efforts of theoretical calculations and experimental measurements. Moreover, the interlayer-confined structure also renders metal DAs a protective shelter to survive in harsh acidic environment. The findings embodied the confinement effects at the atom level, and interlayer-confined assembling of multiple species highlights a general pathway to advance interlayer-confined DAs catalysts within various 2D materials.

The preoperative triglyceride-glucose index has a positive effect on predicting the risk of short-term restenosis after carotid artery stenting: a retrospective cohort study.

Background: Increasing evidence suggests that insulin resistance is linked to cardiovascular disease and atherosclerosis. The triglyceride-glucose (TyG) index has proven to be a convincing marker to quantitatively evaluate insulin resistance. However, there is no relevant information about the relationship between the TyG index and restenosis after carotid artery stenting. Methods: A total of 218 patients were enrolled. Carotid ultrasound and computed tomography angiography were used to evaluate in-stent restenosis. A Kaplan-Meier analysis and Cox regression method were performed to analyze the correlation between TyG index and restenosis. Schoenfeld residuals were used to determine the proportional-hazards assumption. A restricted cubic spline method was used to model and visualize the dose-response relationship between the TyG index and the risk of in-stent restenosis. Subgroup analysis was also performed. Results: Thirty-one participants (14.2%) developed restenosis. The preoperative TyG index had a time-varying effect on restenosis. Within 29 months post-surgery, an increasing preoperative TyG index was linked to a significant increased risk of restenosis (hazard ratio: 4.347; 95% confidence interval 1.886-10.023). However, after 29 months, the effect was decreased, although not statistically significant. The subgroup analysis showed that the hazard ratios tended to be higher in the age ≤ 71 years subgroup (p < 0.001) and participants with hypertension (p < 0.001). Conclusion: The preoperative TyG index was significantly associated with the risk of short-term restenosis after CAS within 29 months post-surgery. The TyG index may be employed to stratify patients based on their risk of restenosis after carotid artery stenting.

Novel Zr-Doped Thiostannate Spinning Fiber (Fiber-KZrTS) for Highly Efficient and Renewable Recovery of Cesium and Strontium from Geothermal Water.

The efficient and renewable recovery of cesium and strontium by absorption from a new type of geothermal water liquid mineral resource is highly desirable but still challenging. In this work, a new Zr-doped layered potassium thiostannate adsorbent (KZrTS) was first synthesized and used for Cs+ and Sr2+ green and efficient adsorption. It was found that KZrTS had very fast adsorption kinetics toward both Cs+ and Sr2+ with an equilibrium reached within 1 min, and the theoretical maximum adsorption capacities for Cs+ and Sr2+ were 402.84 and 84.88 mg/g, respectively. Moreover, to solve the loss problem of the engineering application of the powdered adsorbent KZrTS, KZrTS was uniformly coated with polysulfone by wet spinning technology to form micrometer-level filament-like absorbents (Fiber-KZrTS), whose adsorption equilibrium rates and capacities toward Cs+ and Sr2+ are almost the same as that of powder. Furthermore, Fiber-KZrTS showed excellent reusability, and the adsorption performance remained virtually unchanged after 20 cycles. Therefore, Fiber-KZrTS has potential application for green and efficient cesium and strontium recovery from geothermal water.

MiRNA-200b level in peripheral blood predicts renal interstitial injury in patients with diabetic nephropathy.

Background: To uncover the diagnostic potential of peripheral blood microRNA-200b (miRNA-200b) in renal interstitial injury in diabetic nephropathy (DN) patients. Methods: A total of 50 diabetes subjects, 50 mild DN subjects, 50 moderate-severe DN subjects and 50 healthy subjects were included. Peripheral blood level of miRNA-200b in every subject was detected by reverse transcriptase-polymerase chain reaction (RT-PCR). Serum levels of renal function indicators were determined by enzyme-linked immunosorbent assay (ELISA). Meanwhile, relative levels of fibrosis damage indicators were examined by chemiluminescent immunoassay. Diagnostic potentials of miRNA200b in diabetes, mild DN and moderate-severe DN were assessed by depicting receiver operating characteristic (ROC) curves. Results: Peripheral blood level of miRNA-200b was higher in DN subjects than diabetes subjects without vascular complications, especially moderate-severe DN patients. Peripheral blood level of miRNA-200b in DN subjects was negatively correlated to relative levels of serum creatinine, urinary nitrogen, cystatin, TGF-b, CIV and PCIII. ROC curves demonstrated diagnostic potentials of miRNA-200b in mild and moderate-severe DN. Conclusions: Peripheral blood level of miRNA-200b is closely linked to the degree of renal interstitial injury in DN patients. MiRNA-200b may be a vital indicator in predicting the development of DN.

A bibliometric analysis of the application of imaging in sleep in neurodegenerative disease.

Objective: The purpose of this study was to examine the current state of the application of imaging in sleep research in degenerative disease, as well as hotspots and trends. Materials and methods: A search was conducted on the Web of Science Core Collection (WoSCC) between 1 September 2012, and 31 August 2022 for literature related to sleep imaging. This study analyzed 7,679 articles published in this field over the past 10 years, using CiteSpace to analyze tendencies, countries, institutions, authors, and hotspots. Results: There were 7,679 articles on the application of imaging to sleep research published by 566 institutions located in 135 countries in 1,428 journals; the number of articles was increasing on a yearly basis. According to keyword analysis, the research direction of the application of imaging in sleep research focused on the effects of degenerative diseases on sleep, such as Parkinson's disease, Alzheimer's disease, and small vessel disease. A literature evaluation found that Parkinson's disease, insomnia, sleep quality, and rapid eye movement sleep behavior disorder were the top research trends in this field. Conclusion: A growing body of research has focused on sleep disorders caused by degenerative diseases. In the application of imaging to sleep research, magnetic resonance functional brain imaging represents a reliable research method. In the future, more aging-related diseases may be the subject of sleep-related research, and imaging could provide convenient and reliable evidence in this respect.

Calf muscle pump tensing as a novel maneuver to improve the diagnostic performance of detecting patent foramen ovale during transesophageal echocardiography.

Objective: The Valsalva maneuver is the most sensitive provocative maneuver for patent foramen ovale detection. However, nearly half of patients are unable to perform the Valsalva maneuver well. The aim of this study was to investigate the mechanism of action of calf muscle pump tensing (TENSE) as a novel patent foramen ovale (PFO) provocative maneuver and to evaluate the diagnostic value for PFO and the effect on right-to-left shunt volume compared with the Valsalva maneuver. Methods: This study prospectively investigated 171 patients who were highly suspected to have PFO clinically. Five patients with atrial septal defects newly diagnosed on transesophageal echocardiography (TEE) were excluded. 166 patients were injected with agitated saline under three provocative maneuvers: Valsalva maneuver, TENSE, and Valsalva + TENSE combined maneuver. The patients were divided into the effective Valsalva group (n = 93) and ineffective Valsalva group (n = 73) according to whether they could perform an effective Valsalva maneuver. TENSE consisted of the straightening of both lower limbs, and when the right atrium was filled with microbubbles, the patient performed instantaneous ankle dorsiflexion movements while maintaining dorsiflexion for 3-5 s. Results: Overall, the PFO detection rate of the Valsalva + TENSE combined maneuver (78 [50.1%]) was significantly higher than that of the Valsalva maneuver (51 [30.7%]) and TENSE maneuver (57 [34.3%]) (P < 0.001). In the patients who were able to perform an effective Valsalva maneuver, the PFO detection rate by TENSE was not significantly different from that by the Valsalva maneuver (Valsalva 37/93 [39.8%] vs. TENSE 31/93 [33.3%], P > 0.05), while for the patients who performed an ineffective Valsalva maneuver, the PFO detection rate by the TENSE maneuver was higher than that by the Valsalva maneuver (TENSE 26/73 [35.6%] vs. Valsalva14/73[19.2%], P = 0.017). Conclusion: TENSE is a simple and effective provocative maneuver in the diagnosis of PFO using TEE and can assist the Valsalva maneuver. For patients who cannot perform an effective Valsalva maneuver, TENSE can be an alternative to the Valsalva maneuver to some extent.

Divided-and-combined omnibus test for genetic association analysis with high-dimensional data.

Advances in biologic technology enable researchers to obtain a huge amount of genetic and genomic data, whose dimensions are often quite high on both phenotypes and variants. Testing their association with multiple phenotypes has been a hot topic in recent years. Traditional single phenotype multiple variant analysis has to be adjusted for multiple testing and thus suffers from substantial power loss due to ignorance of correlation across phenotypes. Similarity-based method, which uses the trace of product of two similarity matrices as a test statistic, has emerged as a useful tool to handle this problem. However, it loses power when the correlation strength within multiple phenotypes is middle or strong, for some signals represented by the eigenvalues of phenotypic similarity matrix are masked by others. We propose a divided-and-combined omnibus test to handle this drawback of the similarity-based method. Based on the divided-and-combined strategy, we first divide signals into two groups in a series of cut points according to eigenvalues of the phenotypic similarity matrix and combine analysis results via the Cauchy-combined method to reach a final statistic. Extensive simulations and application to a pig data demonstrate that the proposed statistic is much more powerful and robust than the original test under most of the considered scenarios, and sometimes the power increase can be more than 0.6. Divided-and-combined omnibus test facilitates genetic association analysis with high-dimensional data and achieves much higher power than the existing similarity based method. In fact, divided-and-combined omnibus test can be used whenever the association analysis between two multivariate variables needs to be conducted.

Atomic Magnetic Heating Effect Enhanced Hydrogen Evolution Reaction of Gd@MoS2 Single-Atom Catalysts.

Atomic heating on single atoms (SAs) to maximize the catalytic efficiency of each active site would be a fascinating solution to break the bottleneck for the performance improvement of single-atom catalysts (SACs) but highly challenging task. Here, based on the Gd@MoS2 SACs synthesized by a facile laser molecular beam epitaxy method, high-frequency alternating magnetic field (AMF) technology is employed to induce atomic magnetic heating on Gd SAs that is meanwhile demonstrated to be the catalytic active center. Significant improvement in catalytic kinetics under AMF excitation (3.9 mT) is achieved, yielding a remarkable enhancement of hydrogen evolution reaction magnetothermal-current by ≈924%. Through theoretical calculations and spin-related electrochemical experiments, such promotion in catalyst activity can be attributed to spin flip (or canting) in Gd SAs leading to the atomic magnetic heating effect on catalytic active center. Together with the embodied high stability, the implement of AMF to the SAs field is demonstrated in this work, and the precisely atomic magnetic heating on specific SAs offers unprecedented thinking for further improvement of SACs performance in the future.

LncRNA TCF7 contributes to high glucose-induced damage in human podocytes by up-regulating SEMA3A via sponging miR-16-5p.

AIMS/INTRODUCTION: Long non-coding RNAs (lncRNAs) exert essential functions in the pathogenesis of diabetic nephropathy (DN). LncRNA T-cell factor 7 (TCF7) and semaphorin-3A (SEMA3A) have been found to be involved in the progression of diabetic nephropathy. However, whether the effect of TCF7 on the pathogenesis of diabetic nephropathy is mediated by SEMA3A remains unclear. MATERIALS AND METHODS: TCF7, miR-16-5p, and SEMA3A were quantified by a qRT-PCR or immunoblotting method. A CCK-8 assay gauged the cell viability. Measurement of cell apoptosis was done using flow cytometry. RNA immunoprecipitation (RIP), dual-luciferase reporter, and RNA pull-down assays were utilized to assay the targeted interactions among the variables. RESULTS: The TCF7 and SEMA3A levels were elevated in serum from patients with diabetic nephropathy. TCF7 silencing or SEMA3A depletion ameliorated high glucose (HG)-induced podocyte injury. Moreover, TCF7 silencing protected against HG-induced podocyte injury by down-regulating SEMA3A. TCF7 targeted miR-16-5p, and miR-16-5p targeted SEMA3A. Furthermore, TCF7 affected the expression of SEMA3A by competing specifically for shared miR-16-5p. CONCLUSIONS: These findings suggested that TCF7 silencing attenuated high glucose-induced podocyte damage partially through the miR-16-5p/SEMA3A regulation cascade.

Ferulic acid relieved ulcerative colitis by inhibiting the TXNIP/NLRP3 pathway in rats.

Ulcerative colitis (UC) is a disorder of the bowel that is characterized by a chronic inflammatory response. The traditional Chinese herbal medicine ferulic acid (FA) is known for its antioxidant, antiapoptotic, and antiinflammatory properties. However, its role in UC is still unclear. Thus, the current study was conducted to investigate the role of FA in UC. Rats were treated with 2,4,6-triabrobenzene sulfonic acid to induce UC and subjected to FA. Human intestinal microvascular endothelial cells (HIMECs) were treated with tumor necrosis factor-α (TNF-α) and pretreated with FA. Pathological changes in colonic tissues were visualized via hematoxylin-eosin staining. Enzyme linked immunosorbent assay was conducted to detect interleukin (IL)-6, IL-12, and IL-1ß levels. Cell morphology was visualized by using a microscope, and viability was detected by using MTT. The percentage of apoptosis was detected via flow cytometry. Western blot analysis was performed to detect the expression of the apoptosis-related proteins thioredoxin-interacting protein (TXNIP) and NOD-like receptor pyrin domain-containing 3 (NLRP3). In vivo FA administration alleviated intestinal injury in UC rats and inhibited inflammatory factor levels (IL-6, IL-12, and IL-1ß), apoptosis-related protein expression (caspase-1 and caspase-3) and the TXNIP/NLRP3 signaling pathway. In vitro, TNF-α treatment reduced HIMEC viability, increased cell apoptosis and inflammatory factor levels and activated the TXNIP/NLRP3 signaling pathway. However, FA treatment restored the viability of HIMECs, reduced TNF-α-induced cell apoptosis and inflammation and inhibited the TXNIP/NLRP3 signaling pathway. Furthermore, with increasing FA concentration, the effects were stronger. In summary, FA inhibits the inflammatory injury of endothelial cells in ulcerative colitis or alleviates TNF-α-induced HIMEC injury by inhibiting the TXNIP/NLRP3 signaling pathway.

Efficient removal of RR2 dye by electro- Ce(III) process with its elegant arts and attractive charm in performance, energy consumption and mechanism.

Reactive red 2 (RR2) azo dye wastewater poses a serious hazard to the water environment health, so using a novel and efficient Electro- Ce(III) (E- Ce(III)) process takes on a critical significance in treating RR2 dye wastewater. In this study, the effects of a variety of single-factor conditions on RR2 removal efficiency were evaluated in depth. The results indicated that the optimal experimental conditions are as reaction temperature of 25 °C, Na2SO4 concentration of 25 mM, Ce(III) concentration of 0.3 mM, pH of 4.0, and current density of 40.0 mA/cm2. When the RR2 dye wastewater was treated for 40 min under the optimal experimental conditions, a high removal rate of 99.8% for RR2 was obtained. It is suggested that the background ion PO43- in the dye wastewater inhibits the E-Ce (III) process, whereas Cl- facilitates this process. Moreover, the yield of Ce(IV) increases with the increase of the current density. At the current density of 40.0 mA/cm2, a reasonable energy consumption of 3.85 kW h/gTOC for the process was obtained after the 3-h treatment. The effects of different degradation processes (including Direct Electrooxidation (DEO), single Ce(III), and E-Ce (III)) on RR2 removal efficiency and TOC change were compared. The types of oxidizing substances in the E-Ce (III) process were detected, and the mechanism of RR2 oxidative degradation in the E-Ce (III) process was summarized. The result suggests that the E-Ce (III) process has low power consumption. Meanwhile, in the E-Ce (III) process, free reactive Ce(IV) with strong oxidation is continuously generated, RR2 can be efficiently degraded. And the continuous cycle transformation between Ce(III) and Ce(IV) maintains the strong oxidation of the process. The contribution of free reactive Ce(IV) and DEO to RR2 degradation was obtained as 58.8% and 39.8%, respectively. The combined effect of Ce(IV) and DEO played a major role in the E-Ce (III) process, while ·OH exhibited a relatively weak effect (nearly 1.4%). RR2 was comprised of 13 major intermediates, and the biodegradability of wastewater was improved significantly after treatment, thus facilitating the further mineralization and biodegradation of the products. The E- Ce(III) process is novel, efficient, and environment-friendly, and has a large market application space, suggesting that it can be applied as an efficient, economic, and sustainable water treatment process.

Alternating Magnetic Field Induced Magnetic Heating in Ferromagnetic Cobalt Single-Atom Catalysts for Efficient Oxygen Evolution Reaction.

Alternating magnetic field (AMF) is a promising methodology for further improving magnetic single-atom catalyst (SAC) activity toward oxygen evolution reaction (OER). Herein, the anchoring of Co single atoms on MoS2 support (Co@MoS2), leading to the appearance of in-plane room-temperature ferromagnetic properties, is favorable for the parallel spin arrangement of oxygen atoms when a magnetic field is applied. Moreover, field-assisted electrocatalytic experiments confirmed that the spin direction of Co@MoS2 is changing with the applied magnetic field. On this basis, under AMF, the active sites in ferromagnetic Co@MoS2 were heated by exploiting the magnetic heating generated from spin polarization flip of these SACs to further expedite OER efficiency, with overpotential at 10 mA cm-2 reduced from 317 mV to 250 mV. This work introduces a feasible and efficient approach to enhance the OER performance of Co@MoS2 by AMF, shedding some light on the further development of magnetic SACs for energy conversion.

Multifunctional Silk Fibroin Methacryloyl Microneedle for Diabetic Wound Healing.

Diabetic wound is one of the common complications in diabetic patients, which exhibits chronic, hard-to-heal characteristics. The healing process of wounds is impaired by several factors, including excessive oxidative stress, blocked angiogenesis, and bacterial infection. The therapeutic effects of traditional microneedle patches remain not satisfactory, due to their difficulty simultaneously targeting multiple targets to treat diabetic wounds. As such, there is an urgent need to develop a multifunctional microneedle (MN) patch for promoting the healing of diabetic wounds. A multifunctional MN patch with antioxidant, proangiogenesis, and antibacterial capacities was fabricated to target the pathogenesis of diabetic wounds. Silk fibroin methacryloyl, which has excellent biocompatibility, stable mechanical properties, and well processability, and is selected as the base material for multifunctional MN patches. Prussian blue nanozymes (PBNs) and vascular endothelial growth factor (VEGF) are encapsulated in tips of MN patches, Polymyxin is encapsulated in base layers of MN patches. Based on synergic properties of these components, multifunctional MN patches exhibit excellent biocompatibility, drug-sustained release, proangiogenesis, antioxidant, and antibacterial properties. The developed multifunctional MN patches accelerate diabetic wound healing, providing a potential therapeutic approach.