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Currently, the copolymer of dopamine (DA) and pyrrole (PY) via chemical and electrochemical oxidation usually requires additional oxidants, and lacks flexibility in regulating the size and morphology, thereby limiting the broad applications of DA‐PY copolymer in biomedicine. Herein, the semiquinone radicals produced by the self‐oxidation of DA is ingeniously utilized as the oxidant to initiate the following copolymerization with PY, and a series of quinone‐rich polydopamine‐pyrrole copolymers (PDAm‐nPY) with significantly enhanced absorption in near‐infrared (NIR) region without any additional oxidant assistance is obtained. Moreover, the morphology and size of PDAm‐nPY can be regulated by changing the concentration of DA and PY, thereby optimizing nanoscale PDA0.05‐0.15PY particles (≈ 150 nm) with excellent NIR absorption and surface modification activity are successfully synthesized. Such PDA0.05‐0.15PY particles show effective photoacoustic (PA) imaging and photothermal therapy (PTT) against 4T1 tumors in vivo. Furthermore, other catechol derivatives can also copolymerize with PY under the same conditions. This work by fully utilizing the semiquinone radical active intermediates produced through the self‐oxidation of DA reduces the dependence on external oxidants in the synthesis of composite materials and predigests the preparation procedure, which provides a novel, simple, and green strategy for the synthesis of other newly catechol‐based functional copolymers. [ABSTRACT FROM AUTHOR]

Lysosome, the digestive organelle in eukaryotic cells, plays an important role in the degradation and recirculation of cellular products as well as in maintaining the stability of cellular metabolic microenvironment. Surface‐enhanced Raman scattering (SERS) is a molecular fingerprint technology with high detection sensitivity and photostability, suited for revealing various intracellular molecular information by inducing endocytosis of SERS‐active nanoparticles. However, it remains challenging to selectively extract the molecular information of specific organelles (e.g., lysosomes) from a high‐dimensional spectral set. Herein, we proposed a novel paradigm by combining label‐free SERS spectroscopy with confocal fluorescence imaging to investigate the digestion behavior of lysosomes in cells. The structural similarity algorithm was innovatively introduced and exhibited its effectiveness in screening out the wavenumbers in the SERS spectral set with high correlation with the metabolic behaviors of lysosomes. With comprehensive experiments on HeLa single cells, we captured the intracellular macromolecular digestion phenomenon and discovered the changing pattern of cellular SERS spectra after starvation‐induced autophagy, and analyzed the molecular information within the lysosomes in three‐dimensional space. [ABSTRACT FROM AUTHOR]

Single‐atom and vacancy‐engineered photocatalysts have shown their remarkable strengths in improving carrier transfer dynamics, yet constructing the integration of single atoms and vacancies as the active site is still challenging. Herein, an icing‐assisted photochemical strategy has been employed to anchor Pd single atoms in Zn vacancies on CdxZn1−xS nanorods to form a Pd–S4 tetrahedron coordination structure, enabling exceptional photocatalytic water splitting performance in the absence of any sacrificial agents. Under visible light irradiation, the H2 evolution rate of Pd/Cd0.1Zn0.9S reaches 608.2 μmol g−1 h−1, which is around 229, 6.7, 6.1, and 2 times to that of ZnS, Cd0.1Zn0.9S, Pd/ZnS, and Pd NPs/Cd0.1Zn0.9S, respectively. Detailed experimental and theoretical analyses confirm that Pd–S hybridized electronic states and Pd single atoms are beneficial for enhancing the charge separation/transfer, accelerating the formation of H* and the release of H2. [ABSTRACT FROM AUTHOR]

The electrocatalytic synthesis of C–N coupling compounds from CO2 and nitrogenous species not only offers an effective avenue to achieve carbon neutrality and reduce environmental pollution, but also establishes a route to synthesize valuable chemicals, such as urea, amide, and amine. This innovative approach expands the application range and product categories beyond simple carbonaceous species in electrocatalytic CO2 reduction, which is becoming a rapidly advancing field. This review summarizes the research progress in electrocatalytic urea synthesis, using N2, NO2−, and NO3− as nitrogenous species, and explores emerging trends in the electrosynthesis of amide and amine from CO2 and nitrogen species. Additionally, the future opportunities in this field are highlighted, including electrosynthesis of amino acids and other compounds containing C–N bonds, anodic C–N coupling reactions beyond water oxidation, and the catalytic mechanism of corresponding reactions. This critical review also captures the insights aimed at accelerating the development of electrochemical C–N coupling reactions, confirming the superiority of this electrochemical method over the traditional techniques. [ABSTRACT FROM AUTHOR]

In order to address the greenhouse effect and achieve the artificial carbon cycle, the electrocatalytic reduction reactions offer an effective approach for converting carbon dioxide (CO2) into valuable chemicals. In addition to the rational design of catalyst structure to improve the high selective conversion of CO2, exploring the influence of environmental conditions on the reaction path and product types is one of the keys to realizing the high selective conversion of CO2. In this review, we illustrate the important influence of changes in environmental conditions on the effectiveness of electrocatalytic carbon dioxide reduction reaction (CO2RR) technology from the design of the reactor, the selection of the electrolyte, and the setting of the reaction conditions (pressure, temperature, etc.). Through in‐depth understanding and optimization of these factors, the efficiency and selectivity of the CO2RR can be further improved to promote the development of CO2 conversion technology. [ABSTRACT FROM AUTHOR]

Electrochemical C–C and C–N coupling reactions with the conversion of abundant and inexpensive small molecules, such as CO2 and nitrogen‐containing species, are considered a promising route for increasing the value of CO2 reduction products. The development of high‐performance catalysts is the key to the both electrocatalytic reactions. In this review, we present a systematic summary of the reaction systems for electrocatalytic CO2 reduction, along with the coupling mechanisms of C–C and C–N bonds over outstanding electrocatalytic materials recently developed. The key intermediate species and reaction pathways related to the coupling as well as the catalyst‐structure relationship will be also discussed, aiming to provide insights and guidance for designing efficient CO2 reduction systems. [ABSTRACT FROM AUTHOR]

Surface‐enhanced Raman spectroscopy (SERS), well acknowledged as a fingerprinting and sensitive analytical technique, has exerted high applicational value in a broad range of fields including biomedicine, environmental protection, food safety among the others. In the endless pursuit of ever‐sensitive, robust, and comprehensive sensing and imaging, advancements keep emerging in the whole pipeline of SERS, from the design of SERS substrates and reporter molecules, synthetic route planning, instrument refinement, to data preprocessing and analysis methods. Artificial intelligence (AI), which is created to imitate and eventually exceed human behaviors, has exhibited its power in learning high‐level representations and recognizing complicated patterns with exceptional automaticity. Therefore, facing up with the intertwining influential factors and explosive data size, AI has been increasingly leveraged in all the above‐mentioned aspects in SERS, presenting elite efficiency in accelerating systematic optimization and deepening understanding about the fundamental physics and spectral data, which far transcends human labors and conventional computations. In this review, the recent progresses in SERS are summarized through the integration of AI, and new insights of the challenges and perspectives are provided in aim to better gear SERS toward the fast track. [ABSTRACT FROM AUTHOR]

Geomagnetic storms induce ionospheric disturbances, affecting short‐wave radio communication systems. Accurate ionospheric total electron content (TEC) prediction is vital for accurately describing the short‐wave radio environment of the ionosphere. We use the Multi‐Step Auxiliary Prediction (MSAP) model, a deep learning algorithm, to forecast TEC during geomagnetic storms. The MSAP model integrates Bi‐LSTM networks, an auxiliary model, and convolutional processes for spatiotemporal modeling. Our validation shows the MSAP model outperforms the IRI‐2016 model in predicting global TEC for the next 6 days in the test set. We assess its performance during 116 geomagnetic storm events, considering storm intensity, solar activity, month, and Universal Time (UT). The MSAP model exhibits a weak correlation with storm intensity and a strong correlation with solar activity. Monthly variation displays similar strong correlations in root mean square error (RMSE) and R2 for both models. For UT variation, the other metrics exhibit a weak correlation with the number of Global Navigation Satellite System stations, except for the RMSE of the MSAP and IRI‐2016 models. Plain Language Summary: Total electron content (TEC) is an important parameter to describe the ionosphere. The prediction of TEC is crucial for short‐wave communication systems. Geomagnetic storms disturb the ionosphere, thereby affecting the prediction of TEC. In this paper, the existing multi‐step auxiliary prediction model is used to predict the TEC during geomagnetic storms. Using the International Reference Ionosphere‐2016 model as the reference, the storm‐time performance and time‐varying characteristics of Multi‐Step Auxiliary Prediction (MSAP) are studied. It is found that the MSAP model captures variations with solar activity, month, and Universal Time during geomagnetic storms. Key Points: The MSAP model can predict total electron content (TEC) with high accuracy and stabilityThe MSAP model perform differently in different phases of geomagnetic storms [ABSTRACT FROM AUTHOR]

The diverse bacterial populations within the symbiotic microbiota play a pivotal role in both health and disease. Microbiota modulates critical aspects of tumor biology including cell proliferation, invasion, and metastasis. This regulation occurs through mechanisms like enhancing genomic damage, hindering gene repair, activating aberrant cell signaling pathways, influencing tumor cell metabolism, promoting revascularization, and remodeling the tumor immune microenvironment. These microbiota‐mediated effects significantly impact overall survival and the recurrence of tumors after surgery by affecting the efficacy of chemoradiotherapy. Moreover, leveraging the microbiota for the development of biovectors, probiotics, prebiotics, and synbiotics, in addition to utilizing antibiotics, dietary adjustments, defensins, oncolytic virotherapy, and fecal microbiota transplantation, offers promising alternatives for cancer treatment. Nonetheless, due to the extensive and diverse nature of the microbiota, along with tumor heterogeneity, the molecular mechanisms underlying the role of microbiota in cancer remain a subject of intense debate. In this context, we refocus on various cancers, delving into the molecular signaling pathways associated with the microbiota and its derivatives, the reshaping of the tumor microenvironmental matrix, and the impact on tolerance to tumor treatments such as chemotherapy and radiotherapy. This exploration aims to shed light on novel perspectives and potential applications in the field. [ABSTRACT FROM AUTHOR]

Reliable short‐time prediction of thermospheric mass density along the satellite orbit is always essential but challenging for the operation of Low‐Earth orbit satellites. In this paper, three machine‐learning prediction algorithms are investigated, including the Bidirectional Long Short‐Term Memory, the Transformer, and the Light Gradient Boosting Machine (LightGBM) ensemble model of the above models. We use satellite data from CHAMP, GOCE, and SWARM‐C to evaluate the robustness and accuracy of different density variations. The comparison demonstrates that all models achieve compelling predictions and are much better than NRLMSISE‐00. The LightGBM ensemble model (LE‐model) consistently outperforms others in accuracy and stability. Furthermore, when the obtained density data from the newly launched satellites are limited, the trained LE‐model can provide a valid prediction for the new satellite orbit by transfer learning. This study offers a promising insight into the short‐time prediction of thermospheric mass density using ensemble‐transfer learning and may be advantageous to future research on space whether. Plain Language Summary: Low‐Earth orbit (LEO) satellites play an important role in many aspects, such as navigation, aerospace, military industry, and so on. The LEO satellites suffer atmospheric drag caused by thermospheric mass density. Therefore, we present three different machine‐learning algorithms to achieve a robust short‐time prediction for thermospheric mass density. All models can provide effective results from testing with three satellite data, and the ensemble model always outperforms others. Then, when the obtained density data from the newly launched satellites are very limited, the pre‐trained ensemble model is also useful for the new satellite orbit by transfer learning. We offer a good insight into the short‐time prediction of thermospheric mass density and assistance for aerospace digitization and intellectualization. Key Points: Based on three different machine‐learning algorithms, we present a robust short‐time prediction for thermospheric mass densityWe evaluate the model performances using data from CHAMP, GOCE, and SWARM‐C with NRLMSISE‐00 as the referenceThe LightGBM ensemble model of Bidirectional Long Short‐Term Memory and Transformer outperforms others and can provide reliable transfer predictions for new satellites [ABSTRACT FROM AUTHOR]

The density in the D region is hard to observe on a large scale, because the density in this region is too low. In addition to solar radiation changes with a sinusoidal period of 24 hr, the energetic electron precipitation (EEP) is the major source for the ionospheric D region. In this study, we utilized observations from NOAA/MetOp satellites to derive the electron density profile from 60 to 150 km under the influence of EEP. It seems that the derived electron profile is roughly consistent with the observed one. Additionally, using above derived method of low ionospheric (D and E regions) electron profile based on the observations of NOAA/MetOp satellites, the actions of EEP on global ionosphere under different level of geomagnetic activity are analyzed. We find that EEP has a significant impact on the electron density in the altitude range from 60 to 90 km in the L ∼ 4.5–8 and MLT ∼ 9–14 regions, particularly during strong geomagnetic activity. A peak in Total Electron Content (TEC) was observed at MLT ∼ 11–12 and L ∼ 5.5–6, exhibiting an enhancement approximately 19.96 times higher than that observed during quiet periods. However, the effects of EEP decrease as altitude increases. The TEC enhancement at altitudes from 90 to 120 km during strong geomagnetic activity is like that at 60–90 km, but only about 2.08 times higher than that during quiet periods. In addition, only a weak increase is detected around midnight at altitudes from 120 to 150 km. Key Points: The electron density profile from 60 to 150 km under the influence of energetic electron precipitation (EEP) is derivedEEP has a significant impact on the electron density for the ranges from 60 to 90 km, particularly in L ∼ 4.5–8 and MLT ∼ 9‐14The effect of EEP is very weak on the electron density while the altitude is more than 120 km [ABSTRACT FROM AUTHOR]

Electrocatalytic CO2 reduction reaction (CO2RR) in membrane electrode assembly (MEA) systems is a promising technology. Gaseous CO2 can be directly transported to the cathode catalyst layer, leading to enhanced reaction rate. Meanwhile, there is no liquid electrolyte between the cathode and the anode, which can help to improve the energy efficiency of the whole system. The remarkable progress achieved recently points out the way to realize industrially relevant performance. In this review, we focus on the principles in MEA for CO2RR, focusing on gas diffusion electrodes and ion exchange membranes. Furthermore, anode processes beyond the oxidation of water are considered. Besides, the voltage distribution is scrutinized to identify the specific losses related to the individual components. We also summarize the progress on the generation of different reduced products together with the corresponding catalysts. Finally, the challenges and opportunities are highlighted for future research. [ABSTRACT FROM AUTHOR]

Background: Previous studies had explored the diagnostic or prognostic value of NRP-1/CD304 in blastic plasmacytoid dendritic cell neoplasm (BPDCN), acute myeloid leukemia (AML), and B-cell acute lymphoblastic leukemia (B-ALL), whereas the expression and application value of NRP-1/CD304 in other common hematological diseases have not been reported. Methods: Bone marrow samples from 297 newly diagnosed patients with various hematological diseases were collected to detect the expression of NRP-1/CD304 by flow cytometry (FCM). The diagnostic efficacy of NRP-1/CD304-positive diseases was analyzed by receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC) was compared. Results: In the research cohort, the total positive rate of NRP-1/CD304 was 14.81% (44/297), mainly distributed in BPDCN (100%, 6/6), B-ALL (48.61%, 35/72), and AML (4.48%, 3/67), with statistically significant differences (p < 0.01). Other diseases, such as T-cell acute lymphoblastic leukemia (T-ALL), B-cell non-Hodgkin lymphoma (B-NHL), T/NK-cell lymphoma and plasma cell neoplasms, did not express NRP-1/CD304. The AUC of NRP-1/CD304 was 0.936 (95% CI 0.898-0.973), 0.723 (95% CI 0.646-0.801), and 0.435 (95% CI 0.435) in BPDCN, B-ALL and AML, respectively. Besides, CD304 was commonly expressed in B-ALL with BCR-ABL1 gene rearrangement (p = 0.000), and CD304 expression was positively correlated with CD34 co-expression (p = 0.009) and CD10 co-expression (p = 0.007). Conclusions: NRP-1/CD304 is only expressed in BPDCN, B-ALL and AML, but not in other common hematological diseases. This indicates that NRP-1/CD304 has no obvious diagnostic and follow-up study value in hematological diseases other than BPDCN, B-ALL, and AML. [ABSTRACT FROM AUTHOR]

Magnetosonic (MS) waves can either be discrete or continuous in the time‐frequency spectrogram. Through the observation from Van Allen Probe‐A spacecraft, the global distribution of discrete and continuous spectrum MS waves in the region L ∼ 3–6 is determined. According to our research, the continuous spectrum MS waves are greater in amplitude than discrete spectrum MS waves. Also, the impact of changes in geomagnetic activity on continuous spectrum MS waves is much more significant than discrete spectrum MS waves. Besides, it is also demonstrated that the strong discrete spectrum MS waves have a peak wave amplitude of ∼60 pT and an occurrence rate of ∼50% at the noon sector outside the plasmapause. In comparison, the strong continuous spectrum MS waves have a peak wave amplitude of ∼300 pT and an occurrence rate of ∼60% at the postnoon sector inside the plasmapause. Plain Language Summary: Magnetosonic (MS) waves are usually assumed as the continuous spectrum in the frequency band in line with the quasi‐linear diffusion theory. However, discrete spectrum structures are also observable. Therefore, systematical statistics are generated in the occurrence rate and spatial distribution of discrete and continuous spectrum MS waves with the data from Van Allen Probe‐A spacecraft between January 2014 and December 2017. The study reveals the difference between discrete and continuous spectrum MS waves on the spatial distribution and the occurrence rate, which leads to the conclusion that the changes in geomagnetic activity have a more significant impact on the generation of continuous spectrum MS waves. Key Points: Out of the total magnetosonic (MS) waves observed, 32,474 (48.7%) were discrete spectrum MS waves, while 33,380 (50.1%) were continuous spectrum MS wavesThe wave amplitude of continuous spectrum MS waves is substantially greater compared to discrete spectrum MS wavesThe occurrence rates and wave amplitude of continuous spectrum MS waves are closely associated with AE* effects inside the plasmapause [ABSTRACT FROM AUTHOR]

Electrochemical carbon dioxide reduction reaction (CO2RR) using clean electric energy provides a sustainable route to generate highly‐valuable chemicals and fuels, which is beneficial for realizing the carbon‐neutral cycle. Up to now, achieving a narrow product distribution and highly targeted product selectivity over Cu‐based electrocatalysts is still a big challenge. Herein, sulfur modification on different crystal planes of cuprous oxide (Cu2O) is demonstrated, results in an improvement for formate generation to different degrees. Experimental results and density functional theory (DFT) calculations reveal that sulfur species modified on the surface of Cu2O (100) facet effectively lower the formation energy of key intermediate *OCOH for formate generation compared with Cu2O (111) facet. As a consequence, the modification of p‐Block elements over Cu‐based electrocatalysts is an effective strategy to optimize the adsorption energy of key intermediate during CO2RR, leading to a highly selective product. [ABSTRACT FROM AUTHOR]

Aims: Cerebral venous thrombosis (CVT) is a major cause of stroke in young and middle-aged adults. This study aimed to evaluate the prevalence of post-CVT employability decline and identify factors associated with unemployment. Methods: We identified patients first diagnosed with acute/subacute CVT at Xuanwu Hospital, Capital Medical University (January 2018 to June 2021) and invited all survivors to a clinical 6-months follow-up visit after onset. Baseline data were collected from all patients at admission. A modified Rankin Scale (mRS) and employment status were used to assess functional outcomes. Multivariate logistic regression was used to identify independent factors associated with unemployment. Results: A total of 303 CVT patients were eligible for this study, 131 (42.23%) patients could not return to work 6-month after discharge. After adjusting for age and sex in multivariate analysis, motor deficits, aphasia, mental disorders, CVT recurrence, National Institutes of Health Stroke Scale (NIHSS) score at admission, and mRS 0–2 at 6-month follow-up were independently associated with employment after CVT. Among 263 patients whose mRS showed a favorable outcome, 102 patients were unable to return to their previous work and the risk factors for impaired ability to return to work were aphasia and CVT recurrence. Conclusions: Impaired employability after CVT was associated with motor deficits, aphasia, mental status disorders, and NIHSS score at admission. Even if they recover from CVT without physical disability, patients with a good functional prognosis have a higher risk of employment failure due to their higher rates of aphasia and CVT recurrence. [ABSTRACT FROM AUTHOR]

The energetic electron precipitation (EEP) plays important role in the magnetosphere‐ionosphere‐thermosphere system. It can lead to the decrease of ring current energy densities, the enhancement of electron density in the lower ionosphere, and the destruction of the ozone layer. In the study, using the Energetic Electron Precipitation flux Deep Neural Networks (EPFN) model, the global dynamic evolution of EEP is reconstructed. It suggests that the model can better capture the variation of global EEP during geomagnetic activity. With that, the morphological evolution of EEP and associated potential mechanisms during different phases of geomagnetic storm are analyzed based on the EPFN model. The model provides a good way to understand the loss processes of ring current electrons during geomagnetic storm. Plain Language Summary: Energetic electron precipitations (EEPs) play significant roles in both the dynamic processes of magnetosphere and ionosphere. It is one of the major mechanisms of energetic particles loss in the magnetosphere. Furthermore, the intense precipitation can significantly alter the ionospheric properties, especially in the D and E regions. In the study, using the deep learning technology, the global dynamic evolution of EEP is reconstructed. Based on the reconstructed model, the evolution of EEP during geomagnetic storm is studied. It is helpful to understand the dynamic process in both magnetosphere and ionosphere. Key Points: The model of global dynamic evolution of energetic electron precipitation (EEP) is reconstructedThe model can well capture the variation of global EEP during geomagnetic activityThe evolution of EEP and associated potential mechanisms during different phases are analyzed [ABSTRACT FROM AUTHOR]

With oceanic reverberation and a large amount of data being the main sources of interference for underwater acoustic target detection, it is difficult to obtain a more robust detection performance by relying on the traditional constant false alarm rate (CFAR) detection method. An adaptive sonar CFAR detection method based on a back propagation (BP) neural network is proposed. The method combines the artificial intelligence algorithm and the traditional detection algorithm, and uses the classification ability of the algorithm to select the detection algorithm, which can effectively improve the adaptation ability of the algorithm and the environment and the false alarm control ability. The method combines the artificial intelligence algorithm and the traditional detection algorithm, and uses the classification ability of the algorithm to select the detection algorithm, which can effectively improve the adaptation ability of the algorithm and the environment and the false alarm control ability. This method uses a BP neural network to train the target echo signal to complete the clutter background classification and establish the clutter background recognition classification set. According to the output result of each classification, the best CFAR detector is selected from four CA/SO/GO/OS‐CFAR detectors to detect the target. The simulation results show the detection performance of the proposed method in a uniform environment, a multi‐target environment, and a clutter edge environment. The results show that the environment adaptability is strong for different clutter backgrounds, which further improves the control ability of false alarms under a non‐uniform background. [ABSTRACT FROM AUTHOR]

Plasmaspheric hiss waves make great significance on the loss of electrons in the Earth's radiation belts. The prediction and reconstruction for global evolution plasmaspheric hiss are critical to investigate the dynamic process of radiation belt. In this study, the realistic variation model of plasmaspheric waves is established based on deep learning technology. Using Light Gradient Boosting Machine and Permutation Importance methods, we first select optimal indices and corresponding historical time series associated with variation of plasmaspheric hiss waves. Then the geomagnetic indices in corresponding time series are considered as input of deep neural network model, and the samples of plasmaspheric hiss waves observed from Van Allen Probe A are utilized for training and validation. The result indicates that the model can roughly reproduce the variation of integrated hiss wave amplitude during geomagnetic storm. Based on the model, we analyze the global evolution of hiss waves during a geomagnetic storm event. In addition, we find that the prediction performance has been greatly improved with the addition of in situ density as an auxiliary input parameter, it provides a new idea of establishing higher accuracy model with auxiliary input of other characteristic parameters. Plain Language Summary: Plasmaspheric hiss waves are electromagnetic waves observed in the inner magnetosphere. It plays a vital role in dynamic evolution of the Earth's radiation belts. In previous research, few models can exhibit the realistic global evolution of plasmaspheric hiss using traditional method. In this study, using deep learning technology, we establish the realistic variation model of plasmaspheric hiss amplitude. The result indicates that the model can roughly reproduce the variation of integrated hiss wave amplitude during geomagnetic storm. Therefore, the result of this study will be significantly helpful to establish the models of magnetosphere and space weather forecasting. Key Points: The model for global evolution of plasmaspheric hiss amplitude is reconstructed based on deep learning technologyWith the addition of in situ density as an auxiliary input parameter, the prediction performance has been greatly improvedThe hiss waves exhibit different evolutionary characteristics during different phase of geomagnetic storm [ABSTRACT FROM AUTHOR]

BACKGROUND: Rare sugars have become promising 'sugar alternatives' because of their low calories and unique physiological functions. Among the family of rare sugars, d‐allulose is one of the sugars attracting interest. Ketose 3‐epimerases (KEase), including d‐tagatose 3‐epimerase (DTEase) and d‐allulose 3‐epimerase (DAEase), are mainly used for d‐allulose production. RESULTS: In this study, a putative xylose isomerase from Caballeronia insecticola was characterized and identified as a novel DAEase. Caballeronia insecticola DAEase displayed prominent enzymatic properties, and 150 g L−1d‐allulose was produced from 500 g L−1d‐fructose in 45 min with a conversion rate of 30% and high productivity of 200 g L−1 h−1. Furthermore, DAEase was employed in a phosphorylation–dephosphorylation cascade reaction, which significantly increased the conversion rate of d‐allulose. Under optimized conditions, the conversion rate of d‐allulose was approximately 100% when the concentration of d‐fructose was 50 mmol L−1. CONCLUSION: This research described a very beneficial and facile approach for d‐allulose production based on C. insecticola DAEase. © 2022 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The Constellation Observing System for Meteorology, Ionosphere, and Climate radio occultation S4 indices measurements are used to investigate the global structure and seasonal variations of tidal components in the sporadic-E (Es) layer. The diurnal tidal amplitude in the Es layer intensity and occurrence rate shows a wave-4 longitudinal structure, which is due to the diurnal tidal components of zonal wave numbers s = −3 (eastward, DE3). The wave-4 longitudinal pattern is also observed in the semidiurnal tide during spring and winter, which mostly results from the combination of semidiurnal components of zonal wave numbers s = −2 (eastward, SE2), s = 2 (westward, SW2). In addition, the semidiurnal tidal amplitude in Es layers presents obvious seasonal variability, and it dominates in the northern hemisphere during spring and summer and in the southern hemisphere during autumn and winter. Furthermore, the total semidiurnal tidal amplitude in Es layers in the northern hemisphere is greater than that in the southern hemisphere. Another important finding is that the diurnal tidal pattern at the lower altitude (below 102 km) Es layer is different from that of the higher altitude (above 102 km) Es layer and is also different from that of wind, which supports that the wind shear theory is inapplicable for the Es layer formation at low altitude proposed by many researchers. [ABSTRACT FROM AUTHOR]

To eliminate the usage of traditional fossil fuels, the concept of renewable energy sources to synthesize organic products has been increasingly accepted to achieve peak carbon emission and eventually carbon neutrality. Conversion of solar energy into chemical energy is considered one of the promising and sustainable paradigms to synthesize green chemicals with minimized negative environmental influence. Constructing a suitable semiconductor structure with proper energy‐level alignments is an essential prerequisite to improving photocatalytic efficiency. Herein, a series of 0D/2D CdS/CdIn2S4 composites are synthesized by two‐step procedures, which can improve the separation rate of photoinduced carriers and enhance the photocatalytic homocoupling oxidation of benzylamine to highly value‐added N‐benzylidenebenzylamine efficiency. As a result, the optimized 5wt% CdS/CdIn2S4 composite exhibits the highest benzylidenebenzylamine yield of 164.2 μmol under visible light irradiation for 1 h, which is ≈1.8 and 1.6 times than those of undecorated CdS and CdIn2S4. The synergistic effect between 0D CdS and 2D CdIn2S4 is comprehensively characterized, and the faster spatial separation and migration of photogenerated electron‐hole pairs contributed to the improved photocatalytic performance. This work can open up insight into construing 0D/2D heterojunctions for efficient photocatalytic organic synthesis in an economically viable and environment‐friendly way. [ABSTRACT FROM AUTHOR]

Formate production from direct CO2 electrolysis is economically appealing yet challenging in activity, selectivity, and stability. Herein, sulfur and silver dual‐decorated indium quasi‐core–shell structures with compressive or tensile strain are rationally designed for efficiently electrocatalyzing CO2 to formate. The introduction of Ag and S increases the current density, Faradaic efficiency, and operational stability of formate both in H‐cell and flow cell systems. As a result, the optimized Ag‐In‐S bimetallic catalysts exhibit the FEHCOO− of ≈94.0% with a JHCOO− of more than −560.0 mA cm−2 at ≈−0.951 VRHE in the flow cell system, which far surpasses the undecorated In catalyst. The experimental and theoretical calculations provide a deeper understanding of the role of the interfacial strain between In or In4Ag9 shell and AgIn2 core in boosting the electrocatalytic CO2 reduction efficiency, in which the formation energy of *OCHO intermediate decreases and the charge transfer rate is accelerated by interface strain. [ABSTRACT FROM AUTHOR]

Poly(ethylene oxide) (PEO) is an appealing matrix for solid polymer electrolytes (SPEs) due to its superior lithium salt dissolution ability. However, while such PEO‐based SPEs generally exhibit high crystallinity at room temperatures (∼30 °C), which severely hinders the application of SPEs. In this work, a Polymer‐In‐Salt solid electrolyte with a three‐dimensional frame structure was designed and fabricated with PVDF membrane as the frame and PEO‐in‐LiTFSI as a filler (PPIS). PPIS exhibits high ionic conductivity of 4.5×10−5 S m−1 and lithium transference number of 0.53 at room temperature with a wide electrochemical window beyond 5.5 V. Meanwhile, it exhibits excellent interfacial stability which can effectively suppress the growth of lithium dendrite. The assembled LFP/PPIS/Li solid‐state battery exhibits excellent rate performance and cycling stability at 30 °C and 60 °C. In addition, LFP/PPIS/Li pouch cell displays significant safety and functional flexibility. [ABSTRACT FROM AUTHOR]

The anticoagulant application is an effective treatment modality for cardiovascular diseases such as coronary heart disease, unstable angina pectoris, and myocardial infarction. In this study, the antithrombotic effect of recombinant neorudin (EPRhirudin, EH) was evaluated using a canine model of coronary artery thrombosis. A canine model with platelet thrombosis in the left circumferent branch of the coronary artery was designed using Folt's method, and the anti-thrombus activity of EH was investigated. Femoral administration of EH intravenously had a significant dosedependent inhibitory effect on canine coronary artery thrombosis and the effective rates were 66.7% (p < .05), 83.3% (p < .05), and 100% (p < .01) after injection of 0.3, 1.0, and 3.0 mg/kg EH, respectively. Furthermore, EH demonstrated lower bleeding, with shorter bleeding time and less bleeding loss than low molecular weight heparin (LMWH). Under the similar effect intensity of EH and LMWH (85 IU/kg), the bleeding time of the EH group at 30 min was shorter, and the blood loss at 30–120 min was less than that of LMWH (p < .05 and p < .05– .001, respectively). EH had a significant dose-dependent inhibitory effect in the dose range of 0.3–3.0 mg/kg on the coronary artery thrombosis and lower bleeding side effects than LMWH with a similar antithrombosis effect. [ABSTRACT FROM AUTHOR]

Background and Objective: Hypoglycemia induced by direct‐acting antiviral agents (DAAs) for chronic hepatitis C virus (HCV) infection is a rare but potentially life‐threatening adverse reaction, which led to warnings by competent authorities. We therefore aimed to examine the hypoglycemic safety signal for DAAs. Methods: Reports to the US Food and Drug Administration Adverse Event Reporting System (FAERS) from 1 October 2012 to 31 March 2020 were analyzed. The Medical Dictionary for Regulatory Activities was used to identify hypoglycemia cases. A case by non‐case disproportionality approach was used whereby reporting odds ratio (ROR) with 95% confidence intervals (CI) were calculated. Results: In HCV infection with diabetes patients, the cumulative frequency of hypoglycemic ADRs was 21.85/1000 for reports involving DAAs versus 13.50/1000 for reports involving other medications; For DAAs as a class drug, a nearly double increased reporting odds for hypoglycemia was observed (ROR: 1.63, 95% CI: 1.11–2.41). However, in DAAs subgroup analysis, only telaprevir (ROR: 1.66, 95% CI: 1.01–2.74) and elbasvir/grazoprevir (ROR: 2.25, 95% CI: 1.05–4.83) were associated with increased reporting risk of hypoglycemia during corresponding marketing period; when combined with insulins and sulfonylureas, DAAs were associated with increased reporting risk for hypoglycemia (ROR: 1.98, 95% CI: 1.36–2.88; ROR: 1.62, 95% CI: 1.06–2.48), but concomitant biguanides, dipeptidyl peptidase IV (DPP‐4) inhibitors or glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) were not significant. Conclusions: This study supports the current recommendation for cautious about hypoglycemic risk relating to the use of DAAs. Treatment with DAAs and antidabetic agents (especially insulins and sulfonylureas) will increase hypoglycemia reporting risk. Physicians and pharmacists should be aware of this risk when prescribing DAAs for patients suffering from diabetes, advanced age or liver decompensation. [ABSTRACT FROM AUTHOR]

The accurate prediction of ionospheric Total Electron Content (TEC) is important for global navigation satellite systems (GNSS), satellite communications and other space communications applications. In this study, a prediction model of global IGS‐TEC maps are established based on testing several different long short‐term memory (LSTM) network (LSTM)‐based algorithms to explore a direction that can effectively alleviate the increasing error with prediction time. We find that a Multi‐step auxiliary algorithm based prediction model performs best. It can effectively predict the global ionospheric IGS‐TEC in the next 6 days (the mean absolute deviation (MAD) and root mean square error (RMSE) are 2.485 and 3.511 TECU, respectively) compared to the IRI (the MAD and RMSE are 4.248 and 5.593 TECU). The analyses of four geomagnetic storm events are completely separate from the time range of the training set, so as to further validate the performance of the model. The International Reference Ionosphere model is used as a reference for the performance of our predictive model, and a rotated persistence is estimated by time‐shift algorithm of IGS‐TEC. The result suggests that the Multi‐step auxiliary prediction model has a good generalization performance and can have a relatively good stability and low error during a geomagnetic storm and quiet time. Plain Language Summary: The prediction of global Total Electron Content map is very important for the accuracy of global navigation satellite systems based global positioning system, satellite communications and other space communications applications. As is well known to all, the prediction accuracy usually decrease significantly with the increasing of the prediction time. In order to solve this issue, four different long short‐term memory‐based algorithms are tested to explore a direction that can effectively alleviate the increasing error with prediction time. The result shows that Multi‐step auxiliary prediction model can effectively alleviate the increasing error with prediction time. Moreover, it has a good generalization performance and can have a relatively good stability and low error during a geomagnetic storm. Key Points: Multi‐step auxiliary predictionmodel can effectively alleviate the increasing error with prediction timeMulti‐step auxiliary prediction model can predict international global navigation satellite systems service‐total electron content (TEC) map of next 6 days, and the mean absolute deviation and root mean square error are 2.485 and 3.511 TECU, respectivelyMulti‐step auxiliary prediction model has a good generalization performance and low error during a geomagnetic storm [ABSTRACT FROM AUTHOR]

Post‐partum ovarian cycle arrest is the main factor affecting yak reproductive efficiency. There are few reports regarding the molecular regulatory mechanism of post‐partum oestrus at transcriptome and proteome levels in yaks. Our previous studies focussed on the ovaries of yaks with post‐partum ovarian cycle arrest and post‐partum oestrus yaks. In this study, RNA sequencing transcriptomic study was combined with quantitative proteomic analyses to identify post‐partum ovarian cycle‐related genes and proteins. Consequently, 1,149 genes and 24 proteins were found to be up‐ or downregulated during post‐partum oestrus. The analysis of differentially regulated genes identified three gene or protein pairs that were synchronously upregulated and no gene or protein pairs that were synchronously downregulated, suggesting that these upregulated genes may regulate the post‐partum ovarian cycle. The functional classification of these differentially expressed genes and proteins indicated their connection with the oocyte meiosis, the oestrogen signalling pathway, the progesterone‐mediated oocyte maturation and the gonadotrophin‐releasing hormone (GnRH) signalling pathway. In this study, a total of six genes and two proteins involved in the oocyte meiosis, the oestrogen signalling pathway, the progesterone‐mediated oocyte maturation and the GnRH signalling pathway were identified. The CSNK1A1, M91_09723, M91_11326, M91_21439, M91_19073, SHC2, Atf6b, M91_03062, HSPCA and calmodulin could regulate oestrus, respectively, in the post‐partum so as to control the anoestrus status. [ABSTRACT FROM AUTHOR]

By using Qujing very high frequency radar (25.6°N, 103.7°E, magnetic latitude 16.1°N, magnetic longitude 177.0°E), daytime F region echoes were reported at equatorial ionization anomaly crest on 26 June 2020. Radar interferometry experiment was performed during the observation period. The observed results show that the spatial distributions of daytime F region echo pattern were about 150 km, 200 km, and 180 km in the zonal, meridional, and height extents, respectively. In addition, we observed a remarkable eastward drift of F region echoes with a mean velocity of about 50 m/s. To investigate the possible generation mechanism of daytime F region echoes, simultaneous occurrences of ionospheric disturbance and atmospheric gravity wave activities were presented by combining with the observations of ionosonde, global position system stations and FY-4A satellite. The existence of gravity wave from the deep convective activities in the lower atmosphere was confirmed by using FY-4A satellite measurements. The gravity wave signatures were also observed in the time series of virtual height deviations of sporadic E (dhES) and total electron content near the region where the F region echoes. We surmise that ionospheric disturbance in the F region could be excited during atmospheric gravity wave activities. Then the large-scale ionospheric disturbance could further evolve into small-scale irregularity producing radar echoes through the non-linear cascade process. [ABSTRACT FROM AUTHOR]

Nitrate (NO3−) as a common pollutant of groundwater causes drinking water safety problems and seriously endangers people's health. Electrochemical reduction of nitrate to ammonia under ambient condition is a green and significant route to reduce the concentration of NO3− and produce ammonia (NH3), known as a complement to the Haber–Bosch reaction. Currently, noble‐metal electrocatalysts are often used in electrochemical reduction of NO3−, but high cost and scarcity limited their application. Herein, three‐dimensional (3D) flower‐like zinc cobaltite (ZnCo2O4) electrocatalyst was developed to convert nitrate into ammonia at room temperature. The NH3 yield rate could reach up to around 2100 μg mg−1 h−1 at a potential of −0.6 V vs. reversible hydrogen electrode (RHE), which was around 2.0 times higher than that of pristine Co3O4. In addition, the NH3 faradaic efficiency of ZnCo2O4 electrocatalyst could reach around 95.4 % at potential of −0.4 V vs. RHE with good structural and morphological stability, which surpassed most reported non‐noble metal‐based electrocatalysts. Further studies concluded that the improved activity of electrocatalytic NO3− reduction was ascribed to the existence of abundant active sites and the charge transfer from Co atoms to Zn atoms after Zn doping. Importantly, this work opens a new path for the development of Co‐based materials as electrocatalysts for reducing nitrate to ammonia. [ABSTRACT FROM AUTHOR]

High energy electrons in planetary radiation belts are a major threat to satellites and communications in deep space applications. In order to predict the variations of energetic electron fluxes for different energy channels, we proposed a new ensemble machine leaning model for differential electron flux from 30 keV to 4 MeV in the Earth's radiation belts based on the RBSP‐A observation data from March 2013 to December 2017. The deep neural network (DNN), the convolutional neural network (CNN), the combination of CNN and DNN (CNN&DNN), the linear regression (LR), and the light gradient boosting machine (LightGBM) are among the machine learning models chosen. We carefully compared the electron flux predictions for 20 energy levels and all five models can present valid short‐time flux forecasts. The DNN model has the poorest result. The LR model is good for short‐term forecasting but not so good for long‐term forecasting. The LightGBM ensemble model is highly stable, and it has always outperformed other independent models in terms of forecast accuracy. Then the comparison by adding AE and SYM‐H indexes is given and the influence of geomagnetic activity conditions can be negligible for this short‐time prediction. Furthermore, we applied these five models on Saturn and finally got very similar prediction results. Our results will be significantly useful in instrument designs and system control of future scientific satellites in deep space explorations. Plain Language Summary: With the development of AI hardware technology, it can be predicted that those smart chips will soon be applied to various observation instruments carried by space exploration satellites. However, based on the requirements of energy limits and physical dimensions in satellites, the smart chips used in the instruments can not have very powerful computing power, which may not be effective for current long‐time space weather predictions with many large‐scale parameters. In the present study, we present a short‐time electron flux forecast in planetary radiation belts whose experiments only consider the historical flux data and local parameters. We used five different machine learning models to give the short‐time prediction of the electron differential fluxes for all 20 energy levels from tens of keV to several MeV based on RBSP‐A observations. We also verified this ensemble model on the electron flux forecast near Saturn's equatorial plane by using CASSINI/MIMI data. Our work give a new insight in the space weather applications based on machine learning, which will be critical for practical applications to the instrument designs and system operations of new scientific satellites in the space radiation environment. Key Points: We present a short‐time prediction of the electron flux in the planetary radiation belt based on five different machine learning methodsWe compared the electron flux predictions from 30 keV to 4 MeV and all five models can present valid short‐time flux forecastsFurther experiments on Saturn also show the validation of the ensemble model [ABSTRACT FROM AUTHOR]

Solid‐state zinc (Zn) batteries offer a new candidate for emerging applications sensitive to volume, safety and cost. However, current solid polymeric or ceramic electrolyte structures remain poorly conductive for the divalent Zn2+, especially at room temperature. Constructing a heterogeneous interface which allows Zn2+ percolation is a viable option, but this is rarely involved in multivalent systems. Herein, we construct a solid Zn2+‐ion conductor by inducing crystallization of tailored eutectic liquids formed by organic Zn salts and bipolar ligands. High‐entropy eutectic‐networks weaken the ion‐association and form interfacial Zn2+‐percolated channels on the nucleator surfaces, resulting in a solid crystal with exceptional selectivity for Zn2+ transport (tZn2+ =0.64) and appreciable Zn2+ conductivity (σZn2+ =3.78×10−5 S cm−1 at 30 °C, over 2 orders of magnitude higher than conventional polymers), and finally enabling practical ambient‐temperature Zn/V2O5 metal solid cells. This design principle leveraged by the eutectic solidification affords new insights on the multivalent solid electrochemistry suffering from slow ion migration. [ABSTRACT FROM AUTHOR]

Oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) play significant role on the practical applications of water splitting for producing clean fuel. Although some low‐cost metal oxides are active on catalyzing OER and HER, the instinct drawback of sluggish charges carriers transfer mobility decrease the reactions kinetic and hinder their application. To overcome the issue, CoV oxide is successfully built‐up with a CoOV structure to eliminate energy barrier during carriers transfer by the spin‐flip hopping process, which can be coated on various substrate to stimulate OER and HER. Moreover, the V "bridge" between CoO bonds stimulates the OER through more effective lattice oxygen oxidation mechanism, which can directly format OO bond in more effective pathway. The protocol could be spread on rational design of such OER electrocatalysts on various electrode to lower‐cost water splitting. [ABSTRACT FROM AUTHOR]

Electrochemically reducing carbon dioxide (CO2RR) to ethylene is one of the most promising strategies to reduce carbon dioxide emissions and simultaneously produce high value‐added chemicals. However, the lack of catalysts with excellent activity and stability limits the large‐scale application of this technology. In this work, a graphitic carbon nitride (g‐C3N4)‐supported Cu2O composite was fabricated, which exhibited a 32.2 % faradaic efficiency of C2H4 with a partial current density of −4.3 mA cm−2 at −1.1 V vs. reversible hydrogen electrode in 0.1 m KHCO3 electrolyte. The introduction of g‐C3N4 support not only enhanced the uniform dispersion of Cu2O nanocubes, but also stabilized the important *CO intermediates. Moreover, the g‐C3N4 itself had a good activity of reducing CO2 to form *CO, which enriched the key intermediates of C−C coupling around cuprous oxide. The findings highlight the importance of the g‐C3N4 support, a unique two‐dimensional material, including not only the strong CO2 adsorption and activation capacity but also its synergistic effect with the cuprous oxide in CO2RR selectivity. [ABSTRACT FROM AUTHOR]

We investigate the ionospheric responses to the 2014-2015 sudden stratospheric warming (SSW) event in winter and summer hemisphere by using ionosondes distributed in Equatorial Ionization Anomaly (EIA) crests. Daily mean value of foF2 at each station shows obvious semimonthly lunar tide (~14.5-day period) modulation from lower to higher latitude in both hemispheres during SSW period. Besides, lunar tide modulation in summer hemisphere is later than that in winter hemisphere, which can be explained by the planetary wave penetrating across the equator from winter to summer hemisphere. In addition, lunar semidiurnal tide extracted from foF2 presents evident enhancement after warming onset. Our results demonstrate the quasi 16-day periodic oscillations in F region of EIA crests are caused by the enhanced lunar tide in dynamo wind of mesosphere and lower thermosphere region, which is due to the disturbances in the zonal mean wind distribution in connection with SSW. [ABSTRACT FROM AUTHOR]

This study proposed a new type of diffuser which can not only accelerate the wind approaching the turbine before wind velocity reaches the rated velocity, but also reduces the wind drag on the diffuser when wind velocity is overrated one. A passive adaptive flexible flange constructed of two flexible cantilevered plates is developed for the diffuser. The flow distribution around the diffuser equipped with a flexible flange, as well as the wind drag on the diffuser, varies with the deformation of the flexible flange under the wind drag. Wind tunnel experiments and numerical analysis are conducted to study the flow distribution around the diffuser and the corresponding wind drag on it at different wind velocities. Experimental results reveal that the drag reduction rate of the diffuser with the passive adaptive flexible flange is 17.9% at the velocity of 20 m/s. Numerical results overall match well with the experimental measurement, such as velocity and pressure distributions, although the simulated values are slightly lower than the experimental ones. [ABSTRACT FROM AUTHOR]

Electrochemical conversion of CO2 into valuable products by utilizing renewable electricity is a thriving research field. For electrochemical reduction of CO2 to CO, uniform sponge‐like porous Ag nanocubes (SPC‐Ag) integrated on carbon paper are prepared by using an electrochemically driven method. The SPC‐Ag has a 3 D porous structure and a large specific surface area, which affords abundant active sites for the CO2 reduction reaction (CO2RR), as well as reducing impedance to accelerate the CO2RR kinetics. This distinctive organization affords SPC‐Ag with outstanding electrocatalytic performance for CO2 reduction to CO. High faradaic efficiency (>90 %) and large partial current density for CO with excellent durability are observed in a wide potential window, with a maximum value of 93 % at −0.9 V versus reversible hydrogen electrode. [ABSTRACT FROM AUTHOR]

BACKGROUND: Transbronchial needle aspiration (TBNA) of peripheral lung nodules can be difficult with conventional devices due to their limited flexibility. A promising new technology for accessing these lesions is the PeriView FLEX TBNA device, which has a flexible spiral-grooved needle. The present study reports the unique cytologic features, diagnostic value, and potential pitfalls of PeriView FLEX TBNA specimens. METHODS: This study retrospectively evaluates 113 consecutive cases of lung nodules sampled using the PeriView FLEX device with radial endobronchial ultrasound guidance. RESULTS: PeriView FLEX specimens were satisfactory for evaluation in 111 of 113 cases (98%). A diagnosis of malignancy was made on 64 specimens (57%), with 100% specificity and 70% sensitivity for malignancy. In 4 cases, the PeriView FLEX sample was the only specimen from bronchoscopy that was diagnostic of malignancy. Of the 64 PeriView FLEX specimens with malignant cells, 58 (91%) were adequate for immunohistochemistry and 44 (69%) were adequate for molecular genetic testing. Potential pitfalls were largely ameliorated through education regarding the unique features of PeriView FLEX samples, such as the expected abundance of anthracotic pigment and the paucity of lymphocytes. CONCLUSIONS: TBNA using the PeriView FLEX device to sample pulmonary nodules contributed to the diagnostic value of bronchoscopy and tended to provide sufficient tissue for ancillary studies. Many of the possible pitfalls may be avoided through consideration of the unique cytologic features associated with this novel sampling method. [ABSTRACT FROM AUTHOR]

Ultraflexible neural probe is an ideal tool for brain research, which can reduce the mechanical interfacial mismatch between electrodes and brain tissue and can thus reduce the tissue's inflammation and extend the electrodes' service life. However, the low stiffness of ultraflexible neural probe makes it susceptible to bending and buckling during insertion into brain. Here, a simple yet robust design of removable insertion shuttle consisting of a steel needle with a dissolvable spheroid micropost is reported for ultraflexible neural probe implantation. The dissolvable spheroid micropost of insertion shuttle is fabricated by the simple dip‐coating process based on the competition and balance between the surface tension and gravity. A temporary engaging mechanism enabled by the micropost engaged into the via hole on the tip of ultraflexible neural probe is adopted to enable an easy and quick implantation. Experimental studies reveal the fundamental aspects of the design of removable insertion shuttle and the operation of implantation. In vivo implantation of ultraflexible neural probes into rat's brain illustrates the unusual capabilities of removable insertion shuttle with the accurate positioning of probe at desired depth and the stable chronic brain electrophysiological recording, which show great potential in both basic neuroscience and clinical applications. [ABSTRACT FROM AUTHOR]

Irinotecan (CPT‐11) is a cytotoxic drug that has wide applicability and usage in cancer treatment. Despite its success, patients suffer dose‐dependent diarrhea, limiting the drug's efficacy. No effective therapy is available for this unmet medical need. The bacterial β‐glucuronidase (β‐GUS) plays pivotal role in CPT‐11‐induced diarrhea (CID) via activating the non‐toxic SN‐38G to toxic SN‐38 inside intestine. By using structural‐based virtual screening, three old drugs (N‐Desmethylclozapine, Aspartame, and Gemifloxacin) were firstly identified as selective bacterial β‐GUS inhibitors. The IC50 values of the compounds in the enzyme‐based and cell‐based assays range from 0.0389 to 3.6040 and 0.0105 to 5.3730 μM, respectively. The compounds also showed good selectivity against mammalian β‐GUS and no significant cytotoxicity in bacteria. Molecular docking and molecular dynamics simulations were performed to further investigate the binding modes of compounds with bacterial β‐GUS. Binding free energy decomposition revealed that the compounds formed strong interactions with E413 in catalytic trail from primary monomer and F365′ on the bacterial loop from the other monomer of bacterial β‐GUS, explaining the selectivity against mammalian β‐GUS. The old drugs identified here may be used as bacterial β‐GUS inhibitors for CID or other bacterial β‐GUS‐related disorders. [ABSTRACT FROM AUTHOR]

Summary: Aims: To investigate the critical role of Tim‐3 in the polarization of microglia in intracerebral hemorrhage (ICH)‐induced secondary brain injury (SBI). Methods: An in vivo ICH model was established by autologous whole blood injection into the right basal ganglia in rats. The primary cultured microglia were treated with oxygen‐hemoglobin (OxyHb) to mimic ICH in vitro. In this experiment, specific siRNA for Tim‐3 and recombinant human TIM‐3 were exploited both in vivo and in vitro. Results: Tim‐3 was increased in the brain after ICH, which mainly distributed in microglia, but not neurons and astrocytes. However, the blockade of Tim‐3 by siRNA markedly reduced secretion of inflammatory factors, neuronal degeneration, neuronal cell death, and brain edema. Meanwhile, downregulation of Tim‐3 promoted the transformation of microglia phenotype from M1 to M2 after ICH. Furthermore, upregulation of Tim‐3 can increase the interaction between Tim‐3 and Galectin‐9 (Gal‐9) and activate Toll‐like receptor 4 (TLR‐4) pathway after ICH. Increasing the expression of Tim‐3 may be related to the activation of HIF‐1α. Conclusion: Tim‐3 may be an important link between neuroinflammation and microglia polarization through Tim‐3/Gal‐9 and TLR‐4 signaling pathways which induced SBI after ICH. [ABSTRACT FROM AUTHOR]

A novel xylanase from the filamentous fungus Aspergillus flavus was purified and characterized as the β‐1, 4‐endoxylanase (designed as AfXynB) with a molecular mass (32.2 kDa), which is different from all of the previously reported xylanases from the same strain. AfXynB was optimally active at pH 7.5 and 55 °C, respectively. It was stable up to 50 °C within range of pH 4.0–9.5, and displayed an excellent tolerance to various cations, reagents, and proteases. AfXynB showed specific activity toward beechwood xylan but no detected activity toward CMC and pNP‐β‐D‐xylopyranoside. The xylanase is a typical endo‐xylanase; it could hydrolyze beechwood xylan to only yield xylobiose (X2) and xylopentaose (X5). Actually, this may be the first report for the endo‐xylanases that displayed such a unique hydrolytic property. These findings in the present study have great implications for its future applications of the novel xylanase. [ABSTRACT FROM AUTHOR]

Observations with a global coverage are very important for space physics research and space weather monitoring. However, due to the technical limitations, it would be very expensive or even impossible to achieve a seamless global coverage even with advanced observational devices. It would be useful to fill missing data gaps to create a global map from the available data, but up until now this has been very challenging. Fortunately, the deep learning method, a recent breakthrough in artificial intelligence, may provide an effective way to solve this problem by making full use of data from reliable observations. In this paper, a promising deep learning algorithm, deep convolutional generative adversarial network (DCGAN), is investigated to fill the missing data of total electron content (TEC) map images. The direct use of DCGAN fails to fill missing data for the completion of TEC maps because there are always missing TEC data in some regions, such as oceans, where the features vary with time and geophysical conditions. Thus, no useful information can be utilized by DCGAN to achieve a meaningful image completion. In order to overcome this shortcoming of the original DCGAN method, a novel regularized DCGAN (R‐DCGAN) is proposed by adding an extra discriminator and some widely used reference TEC maps from the International Global Navigation Satellite Systems Service Ionosphere Working Group. The proposed R‐DCGAN method generates satisfactory ionospheric peak structures at different times and geomagnetic conditions, which demonstrate its effectiveness on filling the missing data in TEC maps. The proposed R‐DCGAN framework can be readily extended to a broad application in other fields of space sciences, particularly for addressing the missing observation data issues. Plain Language Summary: This paper proposes an improved deep learning algorithm, regularized deep convolutional generative adversarial network (R‐DCGAN), for the image completion of total electron content (TEC) maps. The traditional DCGAN (which is a very popular and powerful deep learning algorithm for image completion, such as human face images) needs the training data to be completed observations. Since there is lack of distinct features in the missing data part of the training data that can be utilized by DCGAN to fill these missing values, DCGAN fails to directly learn the observation with data missing. In order to overcome the shortcoming of the original DCGAN method, an improved algorithm, R‐DCGAN, is proposed to fulfill missing data completion for the Massachusetts Institute of Technology‐TEC maps. The R‐DCGAN is designed from DCGAN, with an extra discriminator and the reference TECs. The R‐DCGAN produces satisfactory ionospheric peak structures at different times and geomagnetic conditions, and the results demonstrate that the deep learning algorithm is promising to fill the missing data. Key Points: This study proposes an improved deep learning algorithm to deal with common missing observation data issuesThe result generated by the algorithm can show satisfactory ionospheric peak structures at different times and geomagnetic conditionsThe traditional DCGAN fails to directly learn the observation with data missing; in order to overcome this, DCGAN extended to a broader application [ABSTRACT FROM AUTHOR]

A partial internal mixing (PIM) treatment of black carbon (BC), organic carbon (OC), and sulphate was examined, and the core-shell model was used to represent the internally mixed aerosols with BC as the core and sulphate or OC as the shell. The influences of PIM treatment on the effective radiative forcing due to aerosol–radiative interaction (ERFari) and global temperature were examined and compared to those of external mixing (EM) treatment using an aerosol-climate online coupled model of BCC_AGCM2.0_CUACE/Aero. Radiative forcing due to aerosol–radiation interaction (RFari) of the anthropogenic aerosols since the preindustrial era was -0.34 W m-2 for EM and -0.23 W m-2 for PIM, respectively. The global annual mean ERFari of anthropogenic aerosols since the preindustrial era was -0.42 W m-2 for EM and -0.34 W m-2 for PIM, respectively. The change in global annual mean surface temperature increased accordingly from -0.18K in the EM case to -0.125K in the PIM case.Well geographic consistence between the change in low-level cloud amount and the change in temperature can be found. The atmospheric temperature in the troposphere was markedly less reduced in the PIM case than in the EM case. The RFari/ERFari for 50% and 100% were -0.11/-0.07 and 0.13/0.14 W m-2, respectively. RFari, ERFari, and surface temperature changed approximately linearly with the internal mixing proportion. [ABSTRACT FROM AUTHOR]

Objectives This study aimed to evaluate the roles of autophagy and endoplasmic reticulum ( ER) stress in intracerebral hemorrhage ( ICH)-induced secondary brain injury ( SBI) in rats. Methods Autophagy inducer (rapamycin) and inhibitor (3-methyladenine), as well as ER stress activator (tunicamycin, TM) and inhibitor (tauroursodeoxycholic acid, TUDCA), were used. Bafilomycin A1, an inhibitor of autophagosome-lysosome fusion, was used to assess autophagic flux. Results Autophagy and ER stress were enhanced in the week after ICH. At 6 hours after ICH, autophagy was excessive, while the autophagic flux was damaged at 72 hours and return to be intact at 7 days after ICH. At 6 hours after ICH, ER stress induction by TM could enhance autophagy and lead to caspase 12-mediated apoptosis and neuronal degeneration, which was further aggravated by autophagy induction. At 7 days after ICH, ER stress inhibition by TUDCA still could suppress ICH-induced SBI. And, the effects of TUDCA were enhanced by autophagy induction. Conclusions At 6 hours after ICH, excessive autophagy may participate in ER stress-induced brain injury; at 7 days after ICH, autophagy could enhance the protection of ER stress inhibitor possibly via clearing up the cell rubbish generated due to the early-stage damaged autophagic flux. [ABSTRACT FROM AUTHOR]

Acne is one of the most common skin disorders, and its occurrence is closely related to many factors, including sebum secretion, hormone levels, bacterial infection, and inflammatory reactions. Among these, changes in sebum secretion are believed to be one important factor of acne. Increased sebum secretion can induce acne occurrence, and increasing evidence indicates sebum component changes are also strongly related to acne occurrence. Recently, developments in lipidomics have provided effective lipid analysis methods. These can help elucidate the effects of different types of sebum on acne occurrence and provide a theoretical basis for research on the mechanisms of acne pathogenesis and treatment. [ABSTRACT FROM AUTHOR]