Software-aided efficient identification of the components of compound formulae and their metabolites in rats by UHPLC/IM-QTOF-MS and an in-house high-definition MS^(2) library: Sishen formula as a case

Identifying the compound formulae-related xenobiotics in bio-samples is full of challenges.Conventional strategies always exhibit the insufficiencies in overall coverage,analytical efficiency,and degree of automation,and the results highly rely on the personal knowledge and experience.The goal of this work was to establish a software-aided approach,by integrating ultra-high performance liquid chromatography/ion-mobility quadrupole time-of-flight mass spectrometry(UHPLC/IM-QTOF-MS)and in-house high-definition MS^(2) library,to enhance the identification of prototypes and metabolites of the compound formulae in vivo,taking Sishen formula(SSF)as a template.Seven different MS2 acquisition methods were compared,which demonstrated the potency of a hybrid scan approach(namely high-definition data-independent/data-dependent acquisition(HDDIDDA))in the identification precision,MS1 coverage,and MS^(2) spectra quality.The HDDIDDA data for 55 reference compounds,four component drugs,and SSF,together with the rat bio-samples(e.g.,plasma,urine,feces,liver,and kidney),were acquired.Based on the UNIFI™platform(Waters),the efficient data processing workflows were established by combining mass defect filtering(MDF)-induced classification,diagnostic product ions(DPIs),and neutral loss filtering(NLF)-dominated structural confirmation.The high-definition MS^(2) spectral libraries,dubbed in vitro-SSF and in vivo-SSF,were elaborated,enabling the efficient and automatic identification of SSF-associated xenobiotics in diverse rat bio-samples.Consequently,118 prototypes and 206 metabolites of SSF were identified,with the identification rate reaching 80.51%and 79.61%,respectively.The metabolic pathways mainly involved the oxidation,reduction,hydrolysis,sulfation,methylation,demethylation,acetylation,glucuronidation,and the combined reactions.Conclusively,the proposed strategy can drive the identification of compound formulae-related xenobiotics in vivo in an intelligent manner.

An intelligent prediction model of epidemic characters based on multi-feature

The epidemic characters of Omicron(e.g.large-scale transmission)are significantly different from the initial variants of COVID-19.The data generated by large-scale transmission is important to predict the trend of epidemic characters.However,the re-sults of current prediction models are inaccurate since they are not closely combined with the actual situation of Omicron transmission.In consequence,these inaccurate results have negative impacts on the process of the manufacturing and the service industry,for example,the production of masks and the recovery of the tourism industry.The authors have studied the epidemic characters in two ways,that is,investigation and prediction.First,a large amount of data is collected by utilising the Baidu index and conduct questionnaire survey concerning epidemic characters.Second,theβ-SEIDR model is established,where the population is classified as Susceptible,Exposed,Infected,Dead andβ-Recovered persons,to intelligently predict the epidemic characters of COVID-19.Note thatβ-Recovered persons denote that the Recovered persons may become Sus-ceptible persons with probabilityβ.The simulation results show that the model can accurately predict the epidemic characters.

Biomimetic 3D printing of composite structures with decreased cracking

The development of tissue engineering and regeneration research has created new platforms for bone transplantation.However,the preparation of scaffolds with good fiber integrity is challenging,because scaffolds prepared by traditional printing methods are prone to fiber cracking during solvent evaporation.Human skin has an excellent natural heat-management system,which helps to maintain a constant body temperature through perspiration or blood-vessel constriction.In this work,an electrohydrodynamic-jet 3D-printing method inspired by the thermal-management system of skin was developed.In this system,the evaporation of solvent in the printed fibers can be adjusted using the temperature-change rate of the substrate to prepare 3D structures with good structural integrity.To investigate the solvent evaporation and the interlayer bonding of the fibers,finite-element analysis simulations of a three-layer microscale structure were carried out.The results show that the solvent-evaporation path is from bottom to top,and the strain in the printed structure becomes smaller with a smaller temperaturechange rate.Experimental results verified the accuracy of these simulation results,and a variety of complex 3D structures with high aspect ratios were printed.Microscale cracks were reduced to the nanoscale by adjusting the temperature-change rate from 2.5 to 0.5℃s-1.Optimized process parameters were selected to prepare a tissue engineering scaffold with high integrity.It was confirmed that this printed scaffold had good biocompatibility and could be used for bone-tissue regeneration.This simple and flexible 3D-printing method can also help with the preparation of a wide range of micro-and nanostructured sensors and actuators.

Recent advances of collagen composite biomaterials for biomedical engineering:antibacterial functionalization and 3D-printed architecturalization

Collagen possesses high biocompatibility with all tissue and cell types in the body,enabling the creation of multifunc-tional composite materials for medical applications.In biomedical engineering,naturally-sourced collagen is often combined with diverse organic and inorganic bioactive components to eliminate defects and disorders in fields including orthopedics,dermatology,and more.At the same time,medical-related infection issues and the precise treatment needs of patients require collagen composite biomaterials to have antibacterial properties and customized structures.This paper reviews the antibacterial functionalization of collagen composite biomaterials in recent years,including the combination with inorganic or organic antibacterial agents,which is beneficial for preventing and con-trolling biological contamination in medical applications.Then,the existing problems and future development direc-tions for the architecturalization of collagen composite materials with 3D printing were discussed,providing guidance for personalized customization of multifunctional materials to meet the specific needs of patients in the future.

幼儿深度学习的基本特质与逻辑架构

深度学习能力是新时代发展对人提出的新要求。幼儿深度学习是指幼儿在教师的引导下,在较长的一个时段,围绕着富有挑战性的课题,全身心地积极投入,通过同伴间的合作与探究,运用高阶思维,迁移已有经验,最终解决实际问题的有意义的学习过程。幼儿深度学习表现在认知层面,强调问题解决能力的培养;表现在动机层面,强调积极情绪的激发与维持;表现在社会文化层面,强调人际互动中的沟通与支持。幼儿深度学习与浅层学习虽然在学习目标、动机、方式和结果等方面有着本质区别,但二者是对应而非对立的关系,浅层学习是深度学习的基础,深度学习是对浅层学习的提高。幼儿深度学习的过程应以问题解决为导向,以积极情绪为动力,以动手制作为依托,以同伴合作为支撑,以评价反思为主轴。

植物适应性原:治疗病毒感染后疲劳有前途的治疗分子

近年来,通过全国性的预防和控制措施,有效控制了新型冠状病毒肺炎(COVID-19)在中国的传播。然而,大量康复患者受到疲劳的困扰,无论是急性还是慢性的,以及其他严重影响生活质量的与疲劳相关的综合症。病毒感染后疲劳综合症(PVFS)是一种广泛存在的慢性神经系统疾病,缺乏明确的病因因素、确切的诊断检测方法或经批准的药物治疗、疗法或治愈方案。本研究通过文献计量学分析结果表明,神经炎症在PVFS的发展中发挥了作用。因此,本研究简要分析了COVID-19患者神经炎症发展的机制。为了寻找缓解PVFS的有效药物,我们总结了四种传统草药的适应症,并讨论了它们在改善神经疲劳方面的分子机制。研究表明,人参、刺五加、红景天和五味子在缓解PVFS方面具有益处。

某高校既有供热系统节能改造案例分析

目前我国部分北方高校既有供热系统多为自备小型燃煤锅炉,均面临烟煤锅炉拆除改造的问题。本文以济南某高校集中供热系统节能改造为例,结合实际调研数据,利用复合热源热泵技术,建立分布式能源系统替代原有的燃煤锅炉房,运用合同能源管理模式对整个校区既有能源系统进行了经济性分析。结果表明:改造方案需投入约784.5万元,每年节省的运行费用约212.19万元,运用合同能源管理运行模式,投资回收期约3.5年。

Potential Treatment of COVID-19 with Traditional Chinese Medicine: What Herbs Can Help Win the Battle with SARS-CoV-2?

Traditional Chinese medicine(TCM)has been successfully applied worldwide in the treatment of coronavirus disease 2019(COVID-19),which is caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).However,the pharmacological mechanisms underlying this success remain unclear.Hence,the aim of this review is to combine pharmacological assays based on the theory of TCM in order to elucidate the potential signaling pathways,targets,active compounds,and formulas of herbs that are involved in the TCM treatment of COVID-19,which exhibits combatting viral infections,immune regulation,and amelioration of lung injury and fibrosis.Extensive reports on target screening are elucidated using virtual prediction via docking analysis or network pharmacology based on existing data.The results of these reports indicate that an intricate regulatory mechanism is involved in the pathogenesis of COVID-19.Therefore,more pharmacological research on the natural herbs used in TCM should be conducted in order to determine the association between TCM and COVID-19 and account for the observed therapeutic effects of TCM against COVID-19.

Effect of fermented bee pollen on metabolic syndrome in high-fat diet-induced mice

Bee pollen has potential in preventing metabolic syndrome(MetS).The present study aimed to investigate the effect of yeast-fermented wall-broken bee pollen(YB)intervention on ICR mice with MetS induced with a high-fat(HF)diet.After YB intervention in mice for 16 weeks,the effect on alleviating MetS was evaluated based on MetS serum parameters,hepatic oxidant status markers and gut microbial populations.The results of animal experiment showed that YB intervention attenuated MetS.Based on multivariate statistical analysis results,YB treatment signifi cantly increased glutathione S-transferase(GST)and catalase(CAT)activities and decreased the malondialdehyde(MDA)level in the liver.Further investigation showed that YB restored the Nrf-2-Keap-1 pathway to alleviate oxidative stress.Additionally,gut microbial community analysis revealed that YB restored the increase in the Firmicutes to Bacteroidetes(F/B)ratio(6.94 for the HF group and 3.74 for HF+YB group)and improved Lactobacillus and Lactococcus abundance induced by the HF diet.Overall,YB improved function and prevented MetS by modulating the gut microbiota and alleviating oxidative stress.

The development of data acquisition and processing application system for RF ion source

As the key ion source component of nuclear fusion auxiliary heating devices, the radio frequency （RF） ion source is developed and applied gradually to offer a source plasma with the advantages of ease of control and high reliability. In addition, it easily achieves long-pulse steady-state operation. During the process of the development and testing of the RF ion source, a lot of original experimental data will be generated. Therefore, it is necessary to develop a stable and reliable computer data acquisition and processing application system for realizing the functions of data acquisition, storage, access, and real-time monitoring. In this paper, the development of a data acquisition and processing application system for the RF ion source is presented. The hardware platform is based on the PXI system and the software is programmed on the LabVIEW development environment. The key technologies that are used for the implementation of this software programming mainly include the long-pulse data acquisition technology, multi- threading processing technology, transmission control communication protocol, and the Lempel-Ziv-Oberhumer data compression algorithm. Now, this design has been tested and applied on the RF ion source. The test results show that it can work reliably and steadily. With the help of this design, the stable plasma discharge data of the RF ion source are collected, stored, accessed, and monitored in real-time. It is shown that it has a very practical application significance for the RF experiments.

Pose Robust Low-resolution Face Recognition via Coupled Kernel-based Enhanced Discriminant Analysis

Most face recognition techniques have been successful in dealing with high-resolution (HR) frontal face images. However, real-world face recognition systems are often confronted with the low-resolution (LR) face images with pose and illumination variations. This is a very challenging issue, especially under the constraint of using only a single gallery image per person. To address the problem, we propose a novel approach called coupled kernel-based enhanced discriminant analysis (CKEDA). CKEDA aims to simultaneously project the features from LR non-frontal probe images and HR frontal gallery ones into a common space where discrimination property is maximized. There are four advantages of the proposed approach: 1) by using the appropriate kernel function, the data becomes linearly separable, which is beneficial for recognition; 2) inspired by linear discriminant analysis (LDA), we integrate multiple discriminant factors into our objective function to enhance the discrimination property; 3) we use the gallery extended trick to improve the recognition performance for a single gallery image per person problem; 4) our approach can address the problem of matching LR non-frontal probe images with HR frontal gallery images, which is difficult for most existing face recognition techniques. Experimental evaluation on the multi-PIE dataset signifies highly competitive performance of our algorithm. © 2014 Chinese Association of Automation.

Preparation and Application of Biomass-based Sprayable Hydrogels

Hydrogels have three-dimensional network structures that have been widely applied owing to their high water content,excellent biocompatibility,and physicochemical properties.Compared with conventional hydrogels,sprayable hydrogels exhibit excellent temporal and spatial controllability.Biomass materials offer easy accessibility,biocompatibility,biodegradability,and other physicochemical properties that are extensively used in the formation of sprayable hydrogels.In situ formed biomass-based sprayable hydrogels are realized by chemical or physical crosslinking.Rapid spray filming,in situ drug delivery,high permeability,and flexible portability enable biomass-based sprayable hydrogels to show great potential for topical drug delivery,wound healing,and other applications.This review describes in detail the status of research on the preparation and application of biomassbased sprayable hydrogels and suggests prospects for their future development.

Modification of Cellulose by Hydrophobic Long-chain Molecules: Advances and Prospects

Cellulose,a natural polymer material with abundant natural sources,is non-toxic,renewable,and biodegradable,making it one of the most promising green materials.Its inherent hydrophilicity dramatically limits the development and application of cellulose products.Hydrophobic modification can significantly change cellulose properties and endow it with additional functions depending on the types of modifying molecules.Controlled modification of cellulose by long-chain hydrophobic molecules is challenging.Significant advances took advantage of new reaction systems and copolymerization.This paper reviews recent innovations in long-chain cellulose hydrophobic modification.A brief value-adding assessment provides a reference for green changes of cellulose to make it fit for future applications.

Prediction of lattice thermal conductivity with two-stage interpretable machine learning

Thermoelectric and thermal materials are essential in achieving carbon neutrality. However, the high cost of lattice thermal conductivity calculations and the limited applicability of classical physical models have led to the inefficient development of thermoelectric materials. In this study, we proposed a two-stage machine learning framework with physical interpretability incorporating domain knowledge to calculate high/low thermal conductivity rapidly. Specifically, crystal graph convolutional neural network(CGCNN) is constructed to predict the fundamental physical parameters related to lattice thermal conductivity. Based on the above physical parameters, an interpretable machine learning model–sure independence screening and sparsifying operator(SISSO), is trained to predict the lattice thermal conductivity. We have predicted the lattice thermal conductivity of all available materials in the open quantum materials database(OQMD)(https://www.oqmd.org/). The proposed approach guides the next step of searching for materials with ultra-high or ultralow lattice thermal conductivity and promotes the development of new thermal insulation materials and thermoelectric materials.

Tanshinone IIA protects intestinal epithelial cells from ferroptosis through the upregulation of GPX4 and SLC7A11

Background:Inflammatory bowel disease(IBD)is a chronic inflammatory disease of the gastrointestinal tract.The destruction of the intestinal epithelial barrier is one of the major pathological processes in IBD pathology.Growing evidence indicated that epithelial cell ferroptosis is linked to IBD and is considered a target process.Methods:RAS-selective lethal 3(RSL3)was used to induce ferroptosis in intestinal epithelial cell line No.6(IEC-6)cells,and cell ferroptosis and the effects of tanshinone IIA(Tan IIA)were determined by cell counting kit-8(CCK-8),reactive oxygen species(ROS)staining,Giemsa staining and transmission electron microscope(TEM).The cell viability of natural product library compounds was determined by CCK-8.The expression of ferroptosis-related genes were detected by real-time quantitative polymerase chain reaction(RT-qPCR)and western blot.Results:Treatment of IEC-6 cells results in the accumulation of ROS and typical morphological characteristics of ferroptosis.RSL3 treatment caused rapid cellular cytotoxicity which could be reversed by ferrostatin-1(Fer-1)in IEC-6 cells.Natural product library screening revealed that Tan IIA is a potent inhibitor of IEC-6 cell ferroptosis.Tan IIA could significantly protect the RSL3-induced ferroptosis of IEC-6 cells.Furthermore,the ferroptosis suppressors,glutathione peroxidase 4(GPX4),solute carrier family 7 member 11(SLC7A11),and miR-17-92 were found to be early response genes in RSL3-treated cells.Treatment of IEC-6 cells with Tan IIA resulted in upregulation of GPX4,SLC7A11,and miR-17-92.Conclusion:Our study demonstrated that Tan IIA protects IEC-6 cells from ferroptosis through the upregulation of GPX4,SLC7A11,and miR-17-92.The findings might provide a theoretical grounding for the future application of Tan IIA to treat or prevent IBD.

Lebesgues-Stieltjes Integrals of Fuzzy Stochastic Processes with Respect to Finite Variation Processes

Let be a fuzzy stochastic process and be a real valued finite variation process. We define the Lebesgue-Stieltjes integral denoted by for each by using the selection method, which is direct, nature and different from the indirect definition appearing in some references. We shall show that this kind of integral is also measurable, continuous in time t and bounded a.s. under the Hausdorff metric.

Strong coupling between localized 5f moments and itinerant quasiparticles in the ferromagnetic superconductor UGe2

The heavy fermion physics arises from the complex interplay of nearly localized 4f/5f electrons and itinerant band- like ones, yielding heavy quasiparticles with an effective mass about 100 times （or more） of the bare electrons, Recently, experimental and theoretical investigations point out a localized and delocalized dual nature in actinide compounds, where itinerant quasiparticles account for the unconventional superconductivity in the vicinity of a magnetic instability. Here we report the strong coupling between localized 5f moments and itinerant quasiparticles in the ferromagnetic superconductor UGe2. The coupling is nearly antiferromagnetic. As embedded in the ferromagnetic matrix of localized 5f moments below Tc ~ 52 K, this coupling leads to short-range dynamic correlations of heavy quasiparticles, characterized by fluctuations of magnetic clusters. Those cluster-like spins of itinerant quasiparticles show a broad hump of magnetization at Tx≈28 K, which is typical for the spin-glass freezing. Thus, our results present the direct observation of itinerant quasiparticles coexisting with localized 5f moments by conventional magnetic measurements, providing a new route into the coexistence between ferromagnetism and superconductivity in heavy fermion systems.

Psychological Intervention and Nursing Analysis of Gynecological Malignant Tumors during Chemotherapy

Objectives:To explore the clinical effect of psychological intervention and nursing during the chemotherapy of gynecological malignant tumor.Methods:120 patients with gynecologic malignancies were selected as subjects.According to the nursing method,these patients were divided into intervention group and control group,with 60 cases in each group.The patients in the control group were given routine care,and the patients in the observation group were given psychological intervention care on the basis of routine nursing.Before and after treatment,the anxiety and depression of the two groups were compared using the Self-rating Anxiety Scale(SAS)and the Self-rating Depression Scale(SDS).The satisfaction and adverse reactions of the two groups were compared.The results were statistically analyzed.Results:After nursing intervention,the anxiety and depression scores of the intervention group were lower than those of the control group(P<0.05).The incidence of nausea,vomiting and fatigue in the intervention group was significantly lower than that in the control group(P<0.01).There was no significant difference in the symptoms of diarrhea between the two groups(P>0.05).After the treatment,the satisfaction of the intervention group was significantly higher than that of the control group(P<0.05).Conclusions:During the chemotherapy of gynecological malignant tumor patients,psychological intervention nursing can alleviate the anxiety and depression of patients,improve the complications,and improve the satisfaction of patients.It is worthy of clinical application.

Shedding light on the reversible deactivation of carbon-supported single-atom catalysts in hydrogenation reaction

Carbon-supported single-atom catalysts were found to suffer reversible deactivation in catalytic hydrogenation,but the mechanism is still unclear.Herein,nitro compounds hydrogenation catalyzed by N-doped carbon-supported Co single atom(Co1/NC)was taken as a model to uncover the mechanism of the reversible deactivation phenomenon.Co1/NC exhibited moderate adsorption towards the substrate molecules(i.e.,nitro compounds or related intermediates),which could be strengthened by the confinement effect from the porous structure.Consequently,substrate molecules tend to accumulate within the pore channel,especially micropores that host Co1,making it difficult for the reactants to access the active sites and finally leading to their deactivation.The situation could be even worse when the substrate molecules possess a large size.Nevertheless,the catalytic activity of Co1/NC could be restored via a simple thermal treatment,which could remove the adsorbates within the pore channel,hence releasing active sites that were originally inaccessible to reactants.

Collagen fibril-like injectable hydrogels from self-assembled nanoparticles for promoting wound healing

Soft hydrogels are excellent candidate materials for repairing various tissue defects,yet the mechanical strength,anti-swelling properties,and biocompatibility of many soft hydrogels need to be improved.Herein,inspired by the nanostructure of collagen fibrils,we developed a strategy toward achieving a soft but tough,anti-swelling nanofibrillar hydrogel by combining the self-assembly and chemical crosslinking of nanoparticles.Specifically,the collagen fibril-like injectable hydrogel was subtly designed and fabricated by self-assembling methylacrylyl hydroxypropyl chitosan(HM)with laponite(LAP)to form nanoparticles,followed by the inter-nanoparticle bonding through photo-crosslinking.The assembly mechanism of nanoparticles was elucidated by both experimental and simulation techniques.Due to the unique structure of the crosslinked nanoparticles,the nanocomposite hydrogels exhibited low stiffness(G’<2 kPa),high compressive strength(709 kPa),and anti-swelling(swelling ratio of 1.07 in PBS)properties.Additionally,by harnessing the photo-crosslinking ability of the nanoparticles,the nanocomposite hydrogels were processed as microgels,which can be three-dimensionally(3D)printed into complex shapes.Furthermore,we demonstrated that these nanocomposite hydrogels are highly biocompatible,biodegradability,and can effectively promote fibroblast migration and accelerate blood vessel formation during wound healing.This work presents a promising approach to develop biomimetic,nanofibrillar soft hydrogels for regenerative medicine applications.