理论研究Cu@C_(2)N催化剂表面上水分子对电催化CO_(2)还原反应机理的影响

电催化CO_(2)还原反应(CO_(2)RR)的反应途径涉及多个质子-电子对转移,在水溶剂条件下,质子的来源是水分子,考虑水分子对质子-电子对的转移机制十分必要。本研究提出水辅助氢穿梭模型,与常用的以氢原子作为氢源的直接加氢模型对比,研究水分子在CO_(2)RR中对质子-电子对转移的影响。采用密度泛函理论,系统地研究了铜原子嵌入C_(2)N单层催化剂(Cu@C_(2)N)和石墨烯作为衬底的Cu@C_(2)N/石墨烯复合催化剂(Cu@C_(2)N/G)表面上不同加氢模型的CO_(2)RR反应机理。在水辅助氢穿梭模型中,氢原子与水分子结合形成水合质子,水合质子将自身的氢原子转移到催化剂表面的反应物上形成反应中间体,增强了中间体与催化剂之间的相互作用。此外,在Cu@C_(2)N/G催化剂中,石墨烯将电子转移到表面的Cu@C_(2)N上,提高了催化剂的CO_(2)RR催化活性。进一步,计算了Cu@C_(2)N和Cu@C_(2)N/G催化剂上CO_(2)RR和析氢反应的极限电位,讨论催化剂的活性和选择性。结果表明CO_(2)在低电位下容易生成HCOOH,施加高电位时可以生成CO、CH3OH和CH4并伴随着H2的生成。

Highly Efficient Aligned Ion‑Conducting Network and Interface Chemistries for Depolarized All‑Solid‑State Lithium Metal Batteries

Improving the long-term cycling stability and energy density of all-solid-state lithium(Li)-metal batteries(ASSLMBs)at room temperature is a severe challenge because of the notorious solid–solid interfacial contact loss and sluggish ion transport.Solid electrolytes are generally studied as two-dimensional(2D)structures with planar interfaces,showing limited interfacial contact and further resulting in unstable Li/electrolyte and cathode/electrolyte interfaces.Herein,three-dimensional(3D)architecturally designed composite solid electrolytes are developed with independently controlled structural factors using 3D printing processing and post-curing treatment.Multiple-type electrolyte films with vertical-aligned micro-pillar(p-3DSE)and spiral(s-3DSE)structures are rationally designed and developed,which can be employed for both Li metal anode and cathode in terms of accelerating the Li+transport within electrodes and reinforcing the interfacial adhesion.The printed p-3DSE delivers robust long-term cycle life of up to 2600 cycles and a high critical current density of 1.92 mA cm^(−2).The optimized electrolyte structure could lead to ASSLMBs with a superior full-cell areal capacity of 2.75 mAh cm^(−2)(LFP)and 3.92 mAh cm^(−2)(NCM811).This unique design provides enhancements for both anode and cathode electrodes,thereby alleviating interfacial degradation induced by dendrite growth and contact loss.The approach in this study opens a new design strategy for advanced composite solid polymer electrolytes in ASSLMBs operating under high rates/capacities and room temperature.

热风干燥和冷冻干燥对西洋参外观、显微特征和人参皂苷含量影响的比较研究

目的:比较热风干燥的西洋参和冷冻干燥的西洋参之间的差异,并提供改进西洋参质量的更好干燥方法。方法:在本研究中,我们使用CR-410色差计和扫描电子显微镜(scanning electron microscopy,SEM)比较了热风干燥的西洋参和冷冻干燥的西洋参的外观特征。此外,使用UPLC-QE-Orbitrap-MS/MS和高效液相色谱法(high performance liquid chromatography,HPLC)对热风干燥的西洋参和冷冻干燥的西洋参中的人参皂苷进行定性和定量测定。结果:研究结果表明,与热风干燥方法相比,冷冻干燥不仅在外观上具有明显优势,而且具有更高的生物活性成分。结论:冷冻干燥有利于保留西洋参中的人参皂苷,并有助于保持这种功能性食品的生物活性效果。

Single-cell profiling of the pig cecum at various developmental stages

The gastrointestinal tract is essential for food digestion,nutrient absorption,waste elimination,and microbial defense.Single-cell transcriptome profiling of the intestinal tract has greatly enriched our understanding of cellular diversity,functional heterogeneity,and their importance in intestinal tract development and disease.Although such profiling has been extensively conducted in humans and mice,the single-cell gene expression landscape of the pig cecum remains unexplored.Here,single-cell RNA sequencing was performed on 45572 cells obtained from seven cecal samples in pigs at four different developmental stages(days(D)30,42,150,and 730).Analysis revealed 12 major cell types and 38 subtypes,as well as their distinctive genes,transcription factors,and regulons,many of which were conserved in humans.An increase in the relative proportions of CD8^(+)T and Granzyme A(low expression)natural killer T cells(GZMA^(low)NKT)cells and a decrease in the relative proportions of epithelial stem cells,Tregs,RHEX^(+)T cells,and plasmacytoid dendritic cells(pDCs)were noted across the developmental stages.Moreover,the post-weaning period exhibited an up-regulation in mitochondrial genes,COX2 and ND2,as well as genes involved in immune activation in multiple cell types.Cell-cell crosstalk analysis indicated that IBP6^(+)fibroblasts were the main signal senders at D30,whereas IBP6^(−)fibroblasts assumed this role at the other stages.NKT cells established interactions with epithelial cells and IBP6^(+)fibroblasts in the D730 cecum through mediation of GZMA-F2RL1/F2RL2 pairs.This study provides valuable insights into cellular heterogeneity and function in the pig cecum at different development stages.

Pig H3K4me3,H3K27ac,and gene expression profiles reveal reproductive tissue-specific activity of transposable elements

Regulatory sequences and transposable elements(TEs)account for a large proportion of the genomic sequences of species;however,their roles in gene transcription,especially tissue-specific expression,remain largely unknown.Pigs serve as an excellent animal model for studying genomic sequence biology due to the extensive diversity among their wild and domesticated populations.Here,we conducted an integrated analysis using H3K27ac ChIP-seq,H3K4me3 ChIP-seq,and RNA-seq data from 10 different tissues of seven fetuses and eight closely related adult pigs.We aimed to annotate the regulatory elements and TEs to elucidate their associations with histone modifications and mRNA expression across different tissues and developmental stages.Based on correlation analysis between mRNA expression and H3K27ac and H3K4me3 peak activity,results indicated that H3K27ac exhibited stronger associations with gene expression than H3K4me3.Furthermore,1.45%of TEs overlapped with either the H3K27ac or H3K4me3 peaks,with the majority displaying tissue-specific activity.Notably,a TE subfamily(LTR4C_SS),containing binding motifs for SIX1 and SIX4,showed specific enrichment in the H3K27ac peaks of the adult and fetal ovaries.RNA-seq analysis also revealed widespread expression of TEs in the exons or promoters of genes,including 4688 TE-containing transcripts with distinct development stage-specific and tissue-specific expression.Of note,1967 TE-containing transcripts were enriched in the testes.We identified a long terminal repeat(LTR),MLT1F1,acting as a testis-specific alternative promoter in SRPK2(a cell cycle-related protein kinase)in our pig dataset.This element was also conserved in humans and mice,suggesting either an ancient integration of TEs in genes specifically expressed in the testes or parallel evolutionary patterns.Collectively,our findings demonstrate that TEs are deeply embedded in the genome and exhibit important tissue-specific biological functions,particularly in the reproductive organs.

Ambient-Condition Strategy for Production of Hollow Ga_(2)O_(3)@rGO Crystalline Nanostructures Toward Efficient Lithium Storage

Crystallineγ-Ga_(2)O_(3)@rGO core-shell nanostructures are synthesized in gram scale,which are accomplished by a facile sonochemical strategy under ambient condition.They are composed of uniformγ-Ga_(2)O_(3)nanospheres encapsulated by reduced graphene oxide(rGO)nanolayers,and their formation is mainly attributed to the existed opposite zeta potential between the Ga_(2)O_(3)and rGO.The as-constructed lithium-ion batteries(LIBs)based on as-fabricatedγ-Ga_(2)O_(3)@rGO nanostructures deliver an initial discharge capacity of 1000 mAh g^(-1)at 100 mA g^(-1)and reversible capacity of 600 mAh g^(-1)under 500 mA g^(-1)after 1000 cycles,respectively,which are remarkably higher than those of pristineγ-Ga_(2)O_(3)with a much reduced lifetime of 100 cycles and much lower capacity.Ex situ XRD and XPS analyses demonstrate that the reversible LIBs storage is dominant by a conversion reaction and alloying mechanism,where the discharged product of liquid metal Ga exhibits self-healing ability,thus preventing the destroy of electrodes.Additionally,the rGO shell could act robustly as conductive network of the electrode for significantly improved conductivity,endowing the efficient Li storage behaviors.This work might provide some insight on mass production of advanced electrode materials under mild condition for energy storage and conversion applications.

Effect of sequential nursing care combined with communication intervention on visual recovery and pain after cataract ultrasound emulsification

BACKGROUND Cataracts are a common ophthalmic disease and postoperative vision recovery is crucial to patient quality of life.Rational and efficient care models play an impor-tant role in promoting vision recovery.AIM To evaluate the clinical effectiveness of procedural nursing care combined with communication intervention in vision recovery after cataract ultrasound emulsi-fication.METHODS A randomized controlled study was conducted on 100 patients with cataracts who underwent ultrasound emulsification surgery.They were randomly assigned to an experimental group or a control group.The experimental group received procedural nursing combined with Connect,Introduce,Communicate,Ask,Respond,Exit(CICARE)communication intervention,whereas the control group received conventional nursing.The effectiveness of the nursing model was assessed by comparing differences in vision recovery,pain scores,and mental health status between the two groups.RESULTS It was found that over time the visual acuity of patients in both groups gradually recovered and patients in the experimental group had lower pain scores and superior mental health status than the control group(P<0.05).CONCLUSION Procedural nursing combined with CICARE communication intervention has positive effects on vision recovery in patients after cataract ultrasound emulsification.

Sub-Homogeneous Peridynamic Model for Fracture and Failure Analysis of Roadway Surrounding Rock

The surrounding rock of roadways exhibits intricate characteristics of discontinuity and heterogeneity.To address these complexities,this study employs non-local Peridynamics(PD)theory and reconstructs the kernel function to represent accurately the spatial decline of long-range force.Additionally,modifications to the traditional bondbased PD model are made.By considering the micro-structure of coal-rock materials within a uniform discrete model,heterogeneity characterized by bond random pre-breaking is introduced.This approach facilitates the proposal of a novel model capable of handling the random distribution characteristics of material heterogeneity,rendering the PD model suitable for analyzing the deformation and failure of heterogeneous layered coal-rock mass structures.The established numerical model and simulation method,termed the sub-homogeneous PD model,not only incorporates the support effect but also captures accurately the random heterogeneous micro-structure of roadway surrounding rock.The simulation results obtained using this model show good agreement with field measurements from the Fucun coal mine,effectively validating the model’s capability in accurately reproducing the deformation and failure mode of surrounding rock under bolt-supported(anchor cable).The proposed subhomogeneous PD model presents a valuable and effective simulation tool for studying the deformation and failure of roadway surrounding rock in coal mines,offering new insights and potential advancements.

Simulation of Corrosion-Induced Cracking of Reinforced Concrete Based on Fracture Phase Field Method

Accurate simulation of the cracking process caused by rust expansion of reinforced concrete(RC)structures plays an intuitive role in revealing the corrosion-induced failure mechanism.Considering the quasi-brittle fracture of concrete,the fracture phase field driven by the compressive-shear term is constructed and added to the traditional brittle fracture phase field model.The rationality of the proposed model is verified by a mixed fracture example under a shear displacement load.Then,the extended fracture phase model is applied to simulate the corrosion-induced cracking process of RC.The cracking patterns caused by non-uniform corrosion expansion are discussed for RC specimens with homogeneous macroscopically or heterogeneous with different polygonal aggregate distributions at the mesoscopic scale.Then,the effects of the protective layer on the crack propagation trajectory and cracking resistance are investigated,illustrating that the cracking angle and cracking resistance increase with the increase of the protective layer thickness,consistent with the experimental observation.Finally,the corrosion-induced cracking process of concrete specimens with large and small spacing rebars is simulated,and the interaction of multiple corrosion cracking is easily influenced by the reinforcement spacing,which increases with the decrease of the steel bar interval.These conclusions play an important role in the design of engineering anti-corrosion measures.The fracture phase field model can provide strong support for the life assessment of RC structures.

Recent advances in fabricating high-performance triboelectric nanogenerators via modulating surface charge density

Triboelectric nanogenerators(TENGs),a type of promising micro/nano energy source,have been arousing tremendous research interest since their inception and have been the subject of many striking developments,including defining the fundamental physical mechanisms,expanding applications in mechanical to electric power conversion and self-powered sensors,etc.TENGs with a superior surface charge density at the interfaces of the electrodes and dielectrics are found to be crucial to the enhancement of the performance of the devices.Here,an overview of recent advances,including material optimization,circuit design,and strategy conjunction,in developing TENGs through surface charge enhancement is presented.In these topics,different strategies are retrospected in terms of charge transport and trapping mechanisms,technical merits,and limitations.Additionally,the current challenges in high-performance TENG research and the perspectives in this field are discussed.

Electrospun carbon nanofiber-supported V_(2)O_(3) with enriched oxygen vacancies as a free-standing high-rate anode for an all-vanadium-based full battery

Synergistic regulation of hierarchical nanostructures and defect engineering is effective in accelerating electron and ion transport for metal oxide electrodes.Herein,carbon nanofiber-supported V_(2)O_(3) with enriched oxygen vacancies(OV-V_(2)O_(3)@CNF)was fabricated using the facile electrospinning method,followed by thermal reduction.Differing from the traditional particles embedded within carbon nanofibers or irregularly distributed between carbon nanofibers,the free-standing OV-V_(2)O_(3)@CNF allows for V_(2)O_(3) nanosheets to grow vertically on one-dimensional(1D)carbon nanofibers,enabling abundant active sites,shortened ion diffusion pathway,continuous electron transport,and robust structural stability.Meanwhile,density functional theory calculations confirmed that the oxygen vacancies can promote intrinsic electron conductivity and reduce ion diffusion energy barrier.Consequently,the OV-V_(2)O_(3)@CNF anode delivers a large reversible capacity of 812 mAh g^(-1) at 0.1 A g^(-1),superior rate capability(405 mAh g^(-1) at 5 A g^(-1)),and long cycle life(378 mAh g^(-1) at 5 A g^(-1) after 1000 cycles).Moreover,an all-vanadium full battery(V2O5//OV-V_(2)O_(3)@CNF)was assembled using an OV-V_(2)O_(3)@CNF anode and a V2O5 cathode,which outputs a working voltage of 2.5 V with high energy density and power density,suggesting promising practical application.This work offers fresh perspectives on constructing hierarchical 1D nanofiber electrodes by combining defect engineering and electrospinning technology.

Wind farms increase land surface temperature and reduce vegetation productivity in the Inner Mongolia

Wind power has been developing rapidly as a key measure to mitigate human-driven global warming.The under-standing of the development and impacts of wind farms on local climate and vegetation is of great importance for their rational use but is still limited.In this study,we combined remote sensing and on-site investigations to identify wind farm locations in Inner Mongolia and performed landscape pattern analyses using Fragstats.We explored the impacts of wind farms on land surface temperature(LST)and vegetation net primary productivity(NPP)between 1990 and 2020 by contrasting these metrics in wind farms with those in non-wind farm areas.The results showed that the area of wind farms increased rapidly from 1.2 km2 in 1990 to 10,755 km2 in 2020.Spatially,wind farms are mainly clustered in three aggregation areas in the center.Further,wind farms increased nighttime LST,with a mean value of 0.23℃,but had minor impacts on the daytime LST.Moreover,wind farms caused a decline in NPP,especially over forest areas,with an average reduction of 12.37 GC/m^(2).Given the impact of wind farms on LST and NPP,we suggest that the development of wind farms should fully consider their direct and potential impacts.This study provides scientific guidance on the spatial pattern of future wind farms.

A GAN-EfficientNet-Based Traceability Method for Malicious Code Variant Families

Due to the diversity and unpredictability of changes in malicious code,studying the traceability of variant families remains challenging.In this paper,we propose a GAN-EfficientNetV2-based method for tracing families of malicious code variants.This method leverages the similarity in layouts and textures between images of malicious code variants from the same source and their original family of malicious code images.The method includes a lightweight classifier and a simulator.The classifier utilizes the enhanced EfficientNetV2 to categorize malicious code images and can be easily deployed on mobile,embedded,and other devices.The simulator utilizes an enhanced generative adversarial network to simulate different variants of malicious code and generates datasets to validate the model’s performance.This process helps identify model vulnerabilities and security risks,facilitating model enhancement and development.The classifier achieves 98.61%and 97.59%accuracy on the MMCC dataset and Malevis dataset,respectively.The simulator’s generated image of malicious code variants has an FID value of 155.44 and an IS value of 1.72±0.42.The classifier’s accuracy for tracing the family of malicious code variants is as high as 90.29%,surpassing that of mainstream neural network models.This meets the current demand for high generalization and anti-obfuscation abilities in malicious code classification models due to the rapid evolution of malicious code.

Lightweight Malicious Code Classification Method Based on Improved Squeeze Net

With the growth of the Internet,more and more business is being done online,for example,online offices,online education and so on.While this makes people’s lives more convenient,it also increases the risk of the network being attacked by malicious code.Therefore,it is important to identify malicious codes on computer systems efficiently.However,most of the existing malicious code detection methods have two problems:(1)The ability of the model to extract features is weak,resulting in poor model performance.(2)The large scale of model data leads to difficulties deploying on devices with limited resources.Therefore,this paper proposes a lightweight malicious code identification model Lightweight Malicious Code Classification Method Based on Improved SqueezeNet(LCMISNet).In this paper,the MFire lightweight feature extraction module is constructed by proposing a feature slicing module and a multi-size depthwise separable convolution module.The feature slicing module reduces the number of parameters by grouping features.The multi-size depthwise separable convolution module reduces the number of parameters and enhances the feature extraction capability by replacing the standard convolution with depthwise separable convolution with different convolution kernel sizes.In addition,this paper also proposes a feature splicing module to connect the MFire lightweight feature extraction module based on the feature reuse and constructs the lightweight model LCMISNet.The malicious code recognition accuracy of LCMISNet on the BIG 2015 dataset and the Malimg dataset reaches 98.90% and 99.58%,respectively.It proves that LCMISNet has a powerful malicious code recognition performance.In addition,compared with other network models,LCMISNet has better performance,and a lower number of parameters and computations.

Development of a nomogram for predicting liver transplantation prognosis in hepatocellular carcinoma

BACKGROUND At present,liver transplantation(LT)is one of the best treatments for hepatocellular carcinoma(HCC).Accurately predicting the survival status after LT can significantly improve the survival rate after LT,and ensure the best way to make rational use of liver organs.AIM To develop a model for predicting prognosis after LT in patients with HCC.METHODS Clinical data and follow-up information of 160 patients with HCC who underwent LT were collected and evaluated.The expression levels of alphafetoprotein(AFP),des-gamma-carboxy prothrombin,Golgi protein 73,cytokeratin-18 epitopes M30 and M65 were measured using a fully automated chemiluminescence analyzer.The best cutoff value of biomarkers was determined using the Youden index.Cox regression analysis was used to identify the independent risk factors.A forest model was constructed using the random forest method.We evaluated the accuracy of the nomogram using the area under the curve,using the calibration curve to assess consistency.A decision curve analysis(DCA)was used to evaluate the clinical utility of the nomograms.RESULTS The total tumor diameter(TTD),vascular invasion(VI),AFP,and cytokeratin-18 epitopes M30(CK18-M30)were identified as important risk factors for outcome after LT.The nomogram had a higher predictive accuracy than the Milan,University of California,San Francisco,and Hangzhou criteria.The calibration curve analyses indicated a good fit.The survival and recurrence-free survival(RFS)of high-risk groups were significantly lower than those of low-and middle-risk groups(P<0.001).The DCA shows that the model has better clinical practicability.CONCLUSION The study developed a predictive nomogram based on TTD,VI,AFP,and CK18-M30 that could accurately predict overall survival and RFS after LT.It can screen for patients with better postoperative prognosis,and improve longterm survival for LT patients.

Revealing the Promoting Eff ect of CeO_(2)on the Cu/ZnO Catalyst for Methanol Steam Reforming

Cu-based catalysts have been extensively used in methanol steam reforming(MSR)reactions because of their low cost and high effi ciency.ZnO is often used in commercial Cu-based catalysts as both a structural and an electronic promoter to stabilize metal Cu nanoparticles and modify metal–support interfaces.Still,the further addition of chemical promoters is essential to further enhance the MSR reaction performance of the Cu/ZnO catalyst.In this work,CeO_(2)-doped Cu/ZnO catalysts were prepared using the coprecipitation method,and the eff ects of CeO_(2)on Cu-based catalysts were systematically investigated.Doping with appropriate CeO_(2)amounts could stabilize small Cu nanoparticles through a strong interaction between CeO_(2)and Cu,leading to the formation of more Cu+–ZnO x interfacial sites.However,higher CeO_(2)contents resulted in the formation of larger Cu nanoparticles and an excess of Cu+–CeO x interfacial sites.Consequently,the Cu/5CeO_(2)/ZnO catalyst with maximal Cu–ZnO interfaces exhibited the highest H 2 production rate of 94.6 mmolH2/(gcat·h),which was 1.5 and 10.2 times higher than those of Cu/ZnO and Cu/CeO_(2),respectively.

A Coupled Thermomechanical Crack Propagation Behavior of Brittle Materials by Peridynamic Differential Operator

This study proposes a comprehensive,coupled thermomechanical model that replaces local spatial derivatives in classical differential thermomechanical equations with nonlocal integral forms derived from the peridynamic differential operator(PDDO),eliminating the need for calibration procedures.The model employs a multi-rate explicit time integration scheme to handle varying time scales in multi-physics systems.Through simulations conducted on granite and ceramic materials,this model demonstrates its effectiveness.It successfully simulates thermal damage behavior in granite arising from incompatible mineral expansion and accurately calculates thermal crack propagation in ceramic slabs during quenching.To account for material heterogeneity,the model utilizes the Shuffle algorithm andWeibull distribution,yielding results that align with numerical simulations and experimental observations.This coupled thermomechanical model shows great promise for analyzing intricate thermomechanical phenomena in brittle materials.

QBIoT:A Quantum Blockchain Framework for IoT with an Improved Proof-of-Authority Consensus Algorithm and a Public-Key Quantum Signature

The Internet of Things(IoT)is a network system that connects physical devices through the Internet,allowing them to interact.Nowadays,IoT has become an integral part of our lives,offering convenience and smart functionality.However,the growing number of IoT devices has brought about a corresponding increase in cybersecurity threats,such as device vulnerabilities,data privacy concerns,and network susceptibilities.Integrating blockchain technology with IoT has proven to be a promising approach to enhance IoT security.Nevertheless,the emergence of quantum computing poses a significant challenge to the security of traditional classical cryptography used in blockchain,potentially exposing it to quantum cyber-attacks.To support the growth of the IoT industry,mitigate quantum threats,and safeguard IoT data,this study proposes a robust blockchain solution for IoT that incorporates both classical and post-quantum security measures.Firstly,we present the Quantum-Enhanced Blockchain Architecture for IoT(QBIoT)to ensure secure data sharing and integrity protection.Secondly,we propose an improved Proof of Authority consensus algorithm called“Proof of Authority with Random Election”(PoARE),implemented within QBIoT for leader selection and new block creation.Thirdly,we develop a publickey quantum signature protocol for transaction verification in the blockchain.Finally,a comprehensive security analysis of QBIoT demonstrates its resilience against cyber threats from both classical and quantum adversaries.In summary,this research introduces an innovative quantum-enhanced blockchain solution to address quantum security concernswithin the realmof IoT.The proposedQBIoT framework contributes to the ongoing development of quantum blockchain technology and offers valuable insights for future research on IoT security.

Development of a diagnostic nomogram for alpha-fetoproteinnegative hepatocellular carcinoma based on serological biomarkers

BACKGROUND Hepatocellular carcinoma(HCC)is the third leading cause of cancer-related death worldwide.Serum biomarkers play an important role in the early diagnosis and prognosis of HCC.Because a certain percentage of HCC patients are negative for alpha-fetoprotein(AFP),the diagnosis of AFP-negative HCC is essential to improve the detection rate of HCC.AIM To establish an effective model for diagnosing AFP-negative HCC based on serum tumour biomarkers.METHODS A total of 180 HCC patients were enrolled in this study.The expression levels of GP73,des-γ-carboxyprothrombin(DCP),CK18-M65,and CK18-M30 were detected by a fully automated chemiluminescence analyser.The variables were selected by logistic regression analysis.Several models were constructed using stepwise backward logistic regression.The performance of the models was compared using the C statistic,integrated discrimination improvement,net reclassification improvement,and calibration curves.The clinical utility of the nomogram was assessed using decision curve analysis(DCA).RESULTS The results showed that the expression levels of GP73,DCP,CK18-M65,and CK18-M30 were significantly greater in AFP-negative HCC patients than in healthy controls(P<0.001).Multivariate logistic regression analysis revealed that GP73,DCP,and CK18-M65 were independent factors for diagnosing AFP-negative HCC.By comparing the diagnostic performance of multiple models,we included GP73 and CK18-M65 as the model variables,and the model had good discrimination ability(area under the curve=0.946)and good goodness of fit.The DCA curves indicated the good clinical utility of the nomogram.CONCLUSION Our study identified GP73 and CK18-M65 as serum biomarkers with certain application value in the diagnosis of AFP-negative HCC.The diagnostic nomogram based on CK18-M65 combined with GP73 demonstrated good performance and effectively identified high-risk groups of patients with HCC.

Sinomenine increases osteogenesis in mice with ovariectomyinduced bone loss by modulating autophagy

BACKGROUND A decreased autophagic capacity of bone marrow mesenchymal stromal cells(BMSCs)has been suggested to be an important cause of decreased osteogenic differentiation.A pharmacological increase in autophagy of BMSCs is a potential therapeutic option to increase osteoblast viability and ameliorate osteoporosis.AIM To explore the effects of sinomenine(SIN)on the osteogenic differentiation of BMSCs and the underlying mechanisms.METHODS For in vitro experiments,BMSCs were extracted from sham-treated mice and ovariectomized mice,and the levels of autophagy markers and osteogenic differentiation were examined after treatment with the appropriate concen-trations of SIN and the autophagy inhibitor 3-methyladenine.In vivo,the therapeutic effect of SIN was verified by establishing an ovariectomy-induced mouse model and by morphological and histological assays of the mouse femur.RESULTS SIN reduced the levels of AKT and mammalian target of the rapamycin(mTOR)phosphorylation in the phosphatidylinositol 3-kinase(PI3K)/AKT/mTOR signaling pathway,inhibited mTOR activity,and increased autophagy ability of BMSCs,thereby promoting the osteogenic differentiation of BMSCs and effectively alleviating bone loss in ovariectomized mice in vivo.CONCLUSION The Chinese medicine SIN has potential for the treatment of various types of osteoporosis,bone homeostasis disorders,and autophagy-related diseases.