Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single ...Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.展开更多
It is difficult to improve both energy consumption and detection accuracy simultaneously,and even to obtain the trade-off between them,when detecting and tracking moving targets,especially for Underwater Wireless Sens...It is difficult to improve both energy consumption and detection accuracy simultaneously,and even to obtain the trade-off between them,when detecting and tracking moving targets,especially for Underwater Wireless Sensor Networks(UWSNs).To this end,this paper investigates the relationship between the Degree of Target Change(DoTC)and the detection period,as well as the impact of individual nodes.A Hierarchical Detection and Tracking Approach(HDTA)is proposed.Firstly,the network detection period is determined according to DoTC,which reflects the variation of target motion.Secondly,during the network detection period,each detection node calculates its own node detection period based on the detection mutual information.Taking DoTC as pheromone,an ant colony algorithm is proposed to adaptively adjust the network detection period.The simulation results show that the proposed HDTA with the optimizations of network level and node level significantly improves the detection accuracy by 25%and the network energy consumption by 10%simultaneously,compared to the traditional adaptive period detection schemes.展开更多
The cure rate for chronic neurodegenerative diseases remains low,creating an urgent need for improved intervention methods.Recent studies have shown that enhancing mitochondrial function can mitigate the effects of th...The cure rate for chronic neurodegenerative diseases remains low,creating an urgent need for improved intervention methods.Recent studies have shown that enhancing mitochondrial function can mitigate the effects of these diseases.This paper comprehensively reviews the relationship between mitochondrial dysfunction and chronic neurodegenerative diseases,aiming to uncover the potential use of targeted mitochondrial interventions as viable therapeutic options.We detail five targeted mitochondrial intervention strategies for chronic neurodegenerative diseases that act by promoting mitophagy,inhibiting mitochondrial fission,enhancing mitochondrial biogenesis,applying mitochondria-targeting antioxidants,and transplanting mitochondria.Each method has unique advantages and potential limitations,making them suitable for various therapeutic situations.Therapies that promote mitophagy or inhibit mitochondrial fission could be particularly effective in slowing disease progression,especially in the early stages.In contrast,those that enhance mitochondrial biogenesis and apply mitochondria-targeting antioxidants may offer great benefits during the middle stages of the disease by improving cellular antioxidant capacity and energy metabolism.Mitochondrial transplantation,while still experimental,holds great promise for restoring the function of damaged cells.Future research should focus on exploring the mechanisms and effects of these intervention strategies,particularly regarding their safety and efficacy in clinical settings.Additionally,the development of innovative mitochondria-targeting approaches,such as gene editing and nanotechnology,may provide new solutions for treating chronic neurodegenerative diseases.Implementing combined therapeutic strategies that integrate multiple intervention methods could also enhance treatment outcomes.展开更多
An experimental and finite element simulation investigation are conducted to study the deformation patterns of steel targets during the penetration process of tungsten alloy long rods,as well as the influence of stren...An experimental and finite element simulation investigation are conducted to study the deformation patterns of steel targets during the penetration process of tungsten alloy long rods,as well as the influence of strength of the target on the deformation patterns.The experimental results revealed slight mass loss in the first layer of the steel target during the transient entrance phase,with an extremely negligible loss in target mass during the quasi-steady penetration phase.The results of macro-analysis,micro-analysis and simulation show that the eroded target material migrated towards the periphery of the crater,causing an increase in the target's thickness,remained within the target,instead of flowing out of the crater.Therefore,the process of long rods penetrating the metal target is considered as a process of backward extrusion.By combining the backward extrusion theory with energy conservation,a penetration depth model for long rods penetrating a metal target,taking into account both the diameter of the crater and the friction coefficient between the rod and the target,has been established.Although the model is not yet perfect,it innovatively applies the principles of solid mechanics to the study of long rod penetration.Additionally,it takes into account the friction coefficient between the rod and the target during the penetration process.Therefore,this model provides a new research direction for future studies on long rod penetration.展开更多
In radar automatic target recognition(RATR),the high-resolution range profile(HRRP)has garnered considerable attention owing to its minimal computational demands.However,radar HRRP target recognition still faces numer...In radar automatic target recognition(RATR),the high-resolution range profile(HRRP)has garnered considerable attention owing to its minimal computational demands.However,radar HRRP target recognition still faces numerous challenges,primarily due to substantial variations in the amplitude and distribution of HRRP scattering points because of slight azimuthal changes.To alleviate the effect of aspect sensitivity,a novel multi-frame attention network(MFA-Net)comprising a range deformable convolution module(RDCM),multi-frame attention module(MFAM),and global-local Transformer module(GLTM)is proposed.The RDCM is designed to adaptively learn the distance of scattering center migration.Subsequently,the MFAM extracts consistent features across different frames to alleviate the influence of power fluctuation.Finally,the GLTM allocates attention between global and local fea-tures.The feasibility and effectiveness of the proposed method are validated through simulation and experimental datasets,and the recognition rate is enhanced by more than 3%compared to the state-of-the-art methods.展开更多
Infrared small-target detection has important applications in many fields due to its high penetration capability and detection distance.This study introduces a detector called“YOLO-SDLUWD”which is based on the YOLOv...Infrared small-target detection has important applications in many fields due to its high penetration capability and detection distance.This study introduces a detector called“YOLO-SDLUWD”which is based on the YOLOv7 network,for small target detection in complex infrared backgrounds.The“SDLUWD”refers to the combination of the Spatial Depth layer followed Convolutional layer structure(SD-Conv)and a Linear Up-sampling fusion Path Aggregation Feature Pyramid Network(LU-PAFPN)and a training strategy based on the normalized Gaussian Wasserstein Distance loss(WD-loss)function.“YOLO-SDLUWD”aims to reduce detection accuracy when the maximum pooling downsampling layer in the backbone network loses important feature information,support the interaction and fusion of high-dimensional and low-dimensional feature information,and overcome the false alarm predictions induced by noise in small target images.The detector achieved a mAP@0.5 of 90.4%and mAP@0.5:0.95 of 48.5%on IRIS-AG,an increase of 9%-11%over YOLOv7-tiny,outperforming other state-of-the-art target detectors in terms of accuracy and speed.展开更多
With the application of hypervelocity weapons in warfare,comprehensively evaluating their destructive effects is of particular interest for protective engineering.Existing studies mostly focused on the depth of penetr...With the application of hypervelocity weapons in warfare,comprehensively evaluating their destructive effects is of particular interest for protective engineering.Existing studies mostly focused on the depth of penetration by hypervelocity projectile,while investigation on stress waves associated with hypervelocity penetration was very limited.To clarify the generation and propagation of stress waves in concrete targets induced by hypervelocity projectile penetration,in the present study,six spherical projectile penetration tests on concrete targets were firstly conducted with projectile velocity ranged from 1875 m/s to 3940 m/s,in which the stress waves were carefully measured by the PVDF transducers.Then corresponding numerical models were developed and validated,and based on the validated numerical model the mechanisms of generation and propagation of stress waves were clarified.It was found that the stress waves observed during hypervelocity penetration are generated by the continuous interactions of projectile and target during penetration,and have unique characteristics such as the directionality and the"two peaks"phenomenon when compared with the stress waves generated by charge explosion.Finally,the effects of projectile velocity,projectile material,and target strength on the stress waves below the penetration depth we re numerically investigated,and two important indexes for evaluating the stress waves by hypervelocity penetration were proposed.展开更多
Background:Building upon our previous work that developed a folate receptor-mediated,euphaorbia factor L1-loaded PLGA microsphere system integrating active and magnetic targeting for theranostics,further investigation...Background:Building upon our previous work that developed a folate receptor-mediated,euphaorbia factor L1-loaded PLGA microsphere system integrating active and magnetic targeting for theranostics,further investigation into its in vivo pharmacokinetics and tissue distribution is warranted despite its demonstrated biocompatibility and safety.Methods:A UPLC-MS/MS method was established to determine the concentration of euphorbia sterol in rat plasma and mouse tissue homogenates,healthy male SD rats and KM mice were administered in groups,drug concentrations at different time points were determined,pharmacokinetic parameters were analyzed by DAS software,and data were processed by SAS software.Results:The proposed method met the requirements of biological sample detection.The plasma pharmacokinetics of rats showed that the drug concentration in the microsphere group was lower than that in the injection group,and the parameters such as mean residence time(MRT(0–t)),half-life(T1/2z)and apparent volume of distribution(Vz)were significantly different from those in the solution group.The distribution of mouse tissues showed that the drug concentrations in the liver and lung tissues of the microsphere preparation group were higher than those in the injection group,and the drug concentrations in the lung and liver tissues were more distributed.Conclusion:The targeted drug delivery system changed the pharmacokinetic behavior and tissue distribution of euphorbia sterol,slowed down plasma elimination,prolonged the half-life,and improved the targeting of drugs in lung and liver tissues and the magnetic targeting effect of lungs.展开更多
Multiple UAVs cooperative target search has been widely used in various environments,such as emergency rescue and traffic monitoring.However,uncertain communication network among UAVs exhibits unstable links and rapid...Multiple UAVs cooperative target search has been widely used in various environments,such as emergency rescue and traffic monitoring.However,uncertain communication network among UAVs exhibits unstable links and rapid topological fluctuations due to mission complexity and unpredictable environmental states.This limitation hinders timely information sharing and insightful path decisions for UAVs,resulting in inefficient or even failed collaborative search.Aiming at this issue,this paper proposes a multi-UAV cooperative search strategy by developing a real-time trajectory decision that incorporates autonomous connectivity to reinforce multi-UAV collaboration and achieve search acceleration in uncertain search environments.Specifically,an autonomous connectivity strategy based on node cognitive information and network states is introduced to enable effective message transmission and adapt to the dynamic network environment.Based on the fused information,we formalize the trajectory planning as a multiobjective optimization problem by jointly considering search performance and UAV energy harnessing.A multi-agent deep reinforcement learning based algorithm is proposed to solve it,where the reward-guided real-time path is determined to achieve an energyefficient search.Finally,extensive experimental results show that the proposed algorithm outperforms existing works in terms of average search rate and coverage rate with reduced energy consumption under uncertain search environments.展开更多
Infrared images typically exhibit diverse backgrounds,each potentially containing noise and target-like interference elements.In complex backgrounds,infrared small targets are prone to be submerged by background noise...Infrared images typically exhibit diverse backgrounds,each potentially containing noise and target-like interference elements.In complex backgrounds,infrared small targets are prone to be submerged by background noise due to their low pixel proportion and limited available features,leading to detection failure.To address this problem,this paper proposes an Attention Shift-Invariant Cross-Evolutionary Feature Fusion Network(ASCFNet)tailored for the detection of infrared weak and small targets.The network architecture first designs a Multidimensional Lightweight Pixel-level Attention Module(MLPA),which alleviates the issue of small-target feature suppression during deep network propagation by combining channel reshaping,multi-scale parallel subnet architectures,and local cross-channel interactions.Then,a Multidimensional Shift-Invariant Recall Module(MSIR)is designed to ensure the network remains unaffected by minor input perturbations when processing infrared images,through focusing on the model’s shift invariance.Subsequently,a Cross-Evolutionary Feature Fusion structure(CEFF)is designed to allow flexible and efficient integration of multidimensional feature information from different network hierarchies,thereby achieving complementarity and enhancement among features.Experimental results on three public datasets,SIRST,NUDT-SIRST,and IRST640,demonstrate that our proposed network outperforms advanced algorithms in the field.Specifically,on the NUDT-SIRST dataset,the mAP50,mAP50-95,and metrics reached 99.26%,85.22%,and 99.31%,respectively.Visual evaluations of detection results in diverse scenarios indicate that our algorithm exhibits an increased detection rate and reduced false alarm rate.Our method balances accuracy and real-time performance,and achieves efficient and stable detection of infrared weak and small targets.展开更多
Elevated lipoprotein(a)[Lp(a)]is a major independent risk factor for atheroscle-rotic cardiovascular disease(ASCVD),with limited response to traditional lipid-lowering therapies.Lepodisiran,a novel N-acetylgalactosami...Elevated lipoprotein(a)[Lp(a)]is a major independent risk factor for atheroscle-rotic cardiovascular disease(ASCVD),with limited response to traditional lipid-lowering therapies.Lepodisiran,a novel N-acetylgalactosamine-conjugated small interfering RNA,targets hepatic LPA message RNA to reduce apolipoprotein(a)production.Early-phase trials demonstrated>90%sustained Lp(a)reduction with excellent safety and tolerability.The phase 2 ALPACA trial confirmed dura-ble effects lasting up to one year after biannual dosing.Compared to other thera-pies,lepodisiran offers longer duration,high efficacy,and minimal side effects.Ongoing phase 3 studies aim to determine its impact on cardiovascular outcomes,potentially establishing a new standard in precise ASCVD risk management.展开更多
Underwater target detection in forward-looking sonar(FLS)images is a challenging but promising endeavor.The existing neural-based methods yield notable progress but there remains room for improvement due to overlookin...Underwater target detection in forward-looking sonar(FLS)images is a challenging but promising endeavor.The existing neural-based methods yield notable progress but there remains room for improvement due to overlooking the unique characteristics of underwater environments.Considering the problems of low imaging resolution,complex background environment,and large changes in target imaging of underwater sonar images,this paper specifically designs a sonar images target detection Network based on Progressive sensitivity capture,named ProNet.It progressively captures the sensitive regions in the current image where potential effective targets may exist.Guided by this basic idea,the primary technical innovation of this paper is the introduction of a foundational module structure for constructing a sonar target detection backbone network.This structure employs a multi-subspace mixed convolution module that initially maps sonar images into different subspaces and extracts local contextual features using varying convolutional receptive fields within these heterogeneous subspaces.Subsequently,a Scale-aware aggregation module effectively aggregates the heterogeneous features extracted from different subspaces.Finally,the multi-scale attention structure further enhances the relational perception of the aggregated features.We evaluated ProNet on three FLS datasets of varying scenes,and experimental results indicate that ProNet outperforms the current state-of-the-art sonar image and general target detectors.展开更多
This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters wh...This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters while achieving multi-objective cooperative control for target fencing,network connectivity preservation,collision avoidance,and communication efficiency optimization.Firstly,a differential state observer is constructed to obtain the target's unmeasurable states.Secondly,leveraging swarm selforganization principles,a geometric-constraint-free distributed fencing controller is designed by integrating potential field methods with consensus theory.The controller dynamically adjusts inter-UAV distances via single potential function,enabling coordinated optimization of persistent network connectivity and collision-free motion during target fencing.Thirdly,a dual-threshold ETC mechanism based on velocity consensus deviation and fencing error is proposed,which can be triggered based on task features to dynamically adjust the communication frequency,significantly reduce the communication burden and exclude Zeno behavior.Theoretical analysis demonstrates the stability of closed-loop systems.Multi-scenario simulations show that the proposed method can achieve robust fencing under target maneuverability,partial UAV failures,and communication disturbances.展开更多
Between 2016 and 2024,the Chinese government incorporated several innovative drugs into the National Reimbursement Drug List(NRDL)through price negotiations.These negotiations led to significant price reductions,which...Between 2016 and 2024,the Chinese government incorporated several innovative drugs into the National Reimbursement Drug List(NRDL)through price negotiations.These negotiations led to significant price reductions,which in turn stimulated an increase in sales.This study aimed to assess the impact of this policy on the pricing,utilization,and overall expenditure of targeted lung cancer therapies included in the NRDL.Using an interrupted time series analysis of procurement data from 698 healthcare institutions,the study evaluated both immediate and long-term effects.In terms of immediate effects,price negotiations resulted in a significant decline in the defined daily dose cost(DDDc)for all targeted therapies(P<0.05).Regarding long-term trends,a significant shift was observed only in the pricing trajectory of Gefitinib,Icotinib,and Ensartinib(P<0.05).In terms of immediate effects on drug utilization,all targeted medicines experienced a substantial increase in volume(P<0.05),except for Gefitinib and Icotinib.Over the long term,the usage of all targeted therapies exhibited a significant upward trend(P<0.05).With respect to expenditure,the immediate impact of NRDL inclusion resulted in a significant increase in spending on Afatinib,Crizotinib,Osimertinib,Alectinib,and Ensartinib(P<0.05).Over time,total spending on targeted medicines showed a significant increase(P<0.05),except for Erlotinib.Overall,NRDL price negotiations successfully reduced the economic burden on lung cancer patients,improving both accessibility and affordability of targeted therapies in China.展开更多
Antitumor nanomedicines are usually decorated with ligands to achieve multiple functions,such as targeting delivery,tissue penetration and enhanced cellular uptake.However,a single ligand with multiple functions is ge...Antitumor nanomedicines are usually decorated with ligands to achieve multiple functions,such as targeting delivery,tissue penetration and enhanced cellular uptake.However,a single ligand with multiple functions is generally preferred for use in practice.Herein,a versatile peptide,(HE)_(10)G_(5)R_(6)GDK(HE-RK),was engineered by integrating several motifs into a single sequence,including a masking segment(HE),a flexible linker(G_(5)),and a tumor-penetrating head(RK)which comprised a cell-penetrating peptide(R_(6))and a C-end Rule peptide(RGDK).The RK moiety in HE-RK was sequentially activated following the gradual charge reversal of HE to facilitate the accumulation of its cargos in deep tumor tissue and the cytosol of cancer cells.Moreover,in our study,polymer micelles conjugated with the HE-RK peptide(PM-HE-RK)showed superior cellular internalization at pH 6.5 compared to pH 7.4 in vitro,as well as extended blood circulation time and improved tumor targeting and penetration in vivo.Furthermore,the paclitaxel-loaded micelles(PTX/PM-HERK)demonstrated considerable antitumor efficacy,with an 81.48%tumor inhibition rate in the 4T1 mouse model.Overall,the construction of this all-in-one multisegment peptide presents a synergistic and complementary approach to advancing multifunctional peptide ligand design.展开更多
Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum sca...Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum scarcity,collaborative spectrum sharing is considered for hybrid satellite-terrestrial networks(HSTNs)in this paper.With only slowly-varying large-scale channel state information(CSI),joint power and channel allocation is implemented for terrestrial mobile terminals(MTs)which share the same frequency band with the satellite MTs oppor-tunistically.Specially,strict quality service assurance is adopted for terrestrial MTs under the constraint of leakage interference to satellite MTs.With the tar-get of maximizing both the number of served terres-trial MTs and the average sum transmission rate,a double-target spectrum sharing problem is formulated.To solve the complicated mixed integer programming(MIP)problem efficiently,user-centric channel pools are introduced.Simulations demonstrate that the proposed spectrum sharing scheme could achieve a significant performance gain for the HSTN.展开更多
We propose an all-optical,single-laser-pulse scheme for generating a dense relativistic strongly magnetized electron-positron pair plasma.The scheme involves the interaction of an extremely intense(I■10^(24) W/cm^(2)...We propose an all-optical,single-laser-pulse scheme for generating a dense relativistic strongly magnetized electron-positron pair plasma.The scheme involves the interaction of an extremely intense(I■10^(24) W/cm^(2))circularly polarized laser pulse with a solid-density target containing a conical cavity.Through full-scale three-dimensional particle-in-cell simulations that account for quantum electrodynamic effects,it is shown that this interaction results in two significant outcomes:first,the generation of quasi-static magnetic fields reaching tens of gigagauss,and,second,the production of large quantities of electron-positron pairs(up to 10^(13))via the Breit-Wheeler process.The e^(-)e^(+)plasma becomes trapped in the magnetic field and remains confined in a small volume for hundreds of femtoseconds,far exceeding the laser timescale.The dependence of pair plasma parameters,as well as the efficiency of plasma production and confinement,is discussed in relation to the properties of the laser pulse and the target.Realizing this scheme experimentally would enable the investigation of physical processes relevant to extreme astrophysical environments.展开更多
Traditional Chinese medicine(TCM),especially the plant-based,represents complex chemical system containing various primary and secondary metabolites.These botanical metabolites are structurally diversified and exhibit...Traditional Chinese medicine(TCM),especially the plant-based,represents complex chemical system containing various primary and secondary metabolites.These botanical metabolites are structurally diversified and exhibit significant difference in the acidity,alkalinity,molecular weight,polarity,and content,etc,which thus poses great challenges in assessing the quality of TCM[1].展开更多
[Objectives]This study was conducted to explore the curative effect of Qingfei Ditan decoction combined with targeted drug penetration therapy of traditional Chinese medicine on severe mycoplasma pneumonia in children...[Objectives]This study was conducted to explore the curative effect of Qingfei Ditan decoction combined with targeted drug penetration therapy of traditional Chinese medicine on severe mycoplasma pneumonia in children.[Methods]Based on the retrospective study method,children with severe mycoplasma pneumonia admitted to the Children s Hospital of Soochow University from April 2023 to October 2023 were selected,and divided into a treatment group including 56 cases and a control group including 145 cases.The curative effect and adverse reactions of the two groups were compared.[Results]The total effective rate of the treatment group was higher than that of the control group,and the disappearance time of cough and lung rales was shorter than that of the control group,and the incidence of adverse reactions was lower,showing statistical significance(P<0.05).However,defervescence time and bronchoscope flushing rate showed no significant difference(P>0.05).[Conclusions]Qingfei Ditan Decoction combined with targeted drug penetration therapy of traditional Chinese medicine has a significant effect on severe mycoplasma pneumonia in children,and can reduce the side effects of drugs.It is a safe and efficient combination treatment scheme of traditional Chinese medicine.展开更多
Background:Stomach cancer(SC)is one of the most lethal malignancies worldwide due to late-stage diagnosis and limited treatment.The transcriptomic,epigenomic,and proteomic,etc.,omics datasets generated by high-through...Background:Stomach cancer(SC)is one of the most lethal malignancies worldwide due to late-stage diagnosis and limited treatment.The transcriptomic,epigenomic,and proteomic,etc.,omics datasets generated by high-throughput sequencing technology have become prominent in biomedical research,and they reveal molecular aspects of cancer diagnosis and therapy.Despite the development of advanced sequencing technology,the presence of high-dimensionality in multi-omics data makes it challenging to interpret the data.Methods:In this study,we introduce RankXLAN,an explainable ensemble-based multi-omics framework that integrates feature selection(FS),ensemble learning,bioinformatics,and in-silico validation for robust biomarker detection,potential therapeutic drug-repurposing candidates’identification,and classification of SC.To enhance the interpretability of the model,we incorporated explainable artificial intelligence(SHapley Additive exPlanations analysis),as well as accuracy,precision,F1-score,recall,cross-validation,specificity,likelihood ratio(LR)+,LR−,and Youden index results.Results:The experimental results showed that the top four FS algorithms achieved improved results when applied to the ensemble learning classification model.The proposed ensemble model produced an area under the curve(AUC)score of 0.994 for gene expression,0.97 for methylation,and 0.96 for miRNA expression data.Through the integration of bioinformatics and ML approach of the transcriptomic and epigenomic multi-omics dataset,we identified potential marker genes,namely,UBE2D2,HPCAL4,IGHA1,DPT,and FN3K.In-silico molecular docking revealed a strong binding affinity between ANKRD13C and the FDA-approved drug Everolimus(binding affinity−10.1 kcal/mol),identifying ANKRD13C as a potential therapeutic drug-repurposing target for SC.Conclusion:The proposed framework RankXLAN outperforms other existing frameworks for serum biomarker identification,therapeutic target identification,and SC classification with multi-omics datasets.展开更多
文摘Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.
文摘It is difficult to improve both energy consumption and detection accuracy simultaneously,and even to obtain the trade-off between them,when detecting and tracking moving targets,especially for Underwater Wireless Sensor Networks(UWSNs).To this end,this paper investigates the relationship between the Degree of Target Change(DoTC)and the detection period,as well as the impact of individual nodes.A Hierarchical Detection and Tracking Approach(HDTA)is proposed.Firstly,the network detection period is determined according to DoTC,which reflects the variation of target motion.Secondly,during the network detection period,each detection node calculates its own node detection period based on the detection mutual information.Taking DoTC as pheromone,an ant colony algorithm is proposed to adaptively adjust the network detection period.The simulation results show that the proposed HDTA with the optimizations of network level and node level significantly improves the detection accuracy by 25%and the network energy consumption by 10%simultaneously,compared to the traditional adaptive period detection schemes.
基金partly supported by the Yan’an University Qin Chuanyuan“Scientist+Engineer”Team Special Fund,No.2023KXJ-012(to YL)Yan’an University Transformation of Scientific and Technological Achievements Fund,No.2023CGZH-001(to YL)+2 种基金College Students Innovation and Entrepreneurship Training Program,Nos.D2023158,202410719056(to XS,JM)Yan’an University Production and Cultivation Project,No.CXY202001(to YL)Kweichow Moutai Hospital Research and Talent Development Fund Project,No.MTyk2022-25(to XO)。
文摘The cure rate for chronic neurodegenerative diseases remains low,creating an urgent need for improved intervention methods.Recent studies have shown that enhancing mitochondrial function can mitigate the effects of these diseases.This paper comprehensively reviews the relationship between mitochondrial dysfunction and chronic neurodegenerative diseases,aiming to uncover the potential use of targeted mitochondrial interventions as viable therapeutic options.We detail five targeted mitochondrial intervention strategies for chronic neurodegenerative diseases that act by promoting mitophagy,inhibiting mitochondrial fission,enhancing mitochondrial biogenesis,applying mitochondria-targeting antioxidants,and transplanting mitochondria.Each method has unique advantages and potential limitations,making them suitable for various therapeutic situations.Therapies that promote mitophagy or inhibit mitochondrial fission could be particularly effective in slowing disease progression,especially in the early stages.In contrast,those that enhance mitochondrial biogenesis and apply mitochondria-targeting antioxidants may offer great benefits during the middle stages of the disease by improving cellular antioxidant capacity and energy metabolism.Mitochondrial transplantation,while still experimental,holds great promise for restoring the function of damaged cells.Future research should focus on exploring the mechanisms and effects of these intervention strategies,particularly regarding their safety and efficacy in clinical settings.Additionally,the development of innovative mitochondria-targeting approaches,such as gene editing and nanotechnology,may provide new solutions for treating chronic neurodegenerative diseases.Implementing combined therapeutic strategies that integrate multiple intervention methods could also enhance treatment outcomes.
基金supported by the National Natural Science Foundation of China(Grant Nos.12102201,U2341244).
文摘An experimental and finite element simulation investigation are conducted to study the deformation patterns of steel targets during the penetration process of tungsten alloy long rods,as well as the influence of strength of the target on the deformation patterns.The experimental results revealed slight mass loss in the first layer of the steel target during the transient entrance phase,with an extremely negligible loss in target mass during the quasi-steady penetration phase.The results of macro-analysis,micro-analysis and simulation show that the eroded target material migrated towards the periphery of the crater,causing an increase in the target's thickness,remained within the target,instead of flowing out of the crater.Therefore,the process of long rods penetrating the metal target is considered as a process of backward extrusion.By combining the backward extrusion theory with energy conservation,a penetration depth model for long rods penetrating a metal target,taking into account both the diameter of the crater and the friction coefficient between the rod and the target,has been established.Although the model is not yet perfect,it innovatively applies the principles of solid mechanics to the study of long rod penetration.Additionally,it takes into account the friction coefficient between the rod and the target during the penetration process.Therefore,this model provides a new research direction for future studies on long rod penetration.
基金The National Natural Science Foundation of China(No.62388102)the Natural Science Foundation of Shandong Province(No.ZR2021MF134).
文摘In radar automatic target recognition(RATR),the high-resolution range profile(HRRP)has garnered considerable attention owing to its minimal computational demands.However,radar HRRP target recognition still faces numerous challenges,primarily due to substantial variations in the amplitude and distribution of HRRP scattering points because of slight azimuthal changes.To alleviate the effect of aspect sensitivity,a novel multi-frame attention network(MFA-Net)comprising a range deformable convolution module(RDCM),multi-frame attention module(MFAM),and global-local Transformer module(GLTM)is proposed.The RDCM is designed to adaptively learn the distance of scattering center migration.Subsequently,the MFAM extracts consistent features across different frames to alleviate the influence of power fluctuation.Finally,the GLTM allocates attention between global and local fea-tures.The feasibility and effectiveness of the proposed method are validated through simulation and experimental datasets,and the recognition rate is enhanced by more than 3%compared to the state-of-the-art methods.
基金supported by the National Key R&D Program“Development and Application Verification of Underwater Intelligent Defect Detection Robot System for Large Hydropower Station Dams”(Project No.2022YFB4703400)sub-topic 4“Research on Intelligent Identification and Diagnosis of Dam Defects and Fine Inspection Equipment and Technology of Hydropower Stations”(Project No.2022YFB4703404)supported in part by the National Natural Science Foundation of China under Grant 62371181in part by the Changzhou Science and Technology International Cooperation Program under Grant CZ20230029。
文摘Infrared small-target detection has important applications in many fields due to its high penetration capability and detection distance.This study introduces a detector called“YOLO-SDLUWD”which is based on the YOLOv7 network,for small target detection in complex infrared backgrounds.The“SDLUWD”refers to the combination of the Spatial Depth layer followed Convolutional layer structure(SD-Conv)and a Linear Up-sampling fusion Path Aggregation Feature Pyramid Network(LU-PAFPN)and a training strategy based on the normalized Gaussian Wasserstein Distance loss(WD-loss)function.“YOLO-SDLUWD”aims to reduce detection accuracy when the maximum pooling downsampling layer in the backbone network loses important feature information,support the interaction and fusion of high-dimensional and low-dimensional feature information,and overcome the false alarm predictions induced by noise in small target images.The detector achieved a mAP@0.5 of 90.4%and mAP@0.5:0.95 of 48.5%on IRIS-AG,an increase of 9%-11%over YOLOv7-tiny,outperforming other state-of-the-art target detectors in terms of accuracy and speed.
基金supported by the National Natural Science Foundation of China(Grant Nos.52178515 and 12472399)。
文摘With the application of hypervelocity weapons in warfare,comprehensively evaluating their destructive effects is of particular interest for protective engineering.Existing studies mostly focused on the depth of penetration by hypervelocity projectile,while investigation on stress waves associated with hypervelocity penetration was very limited.To clarify the generation and propagation of stress waves in concrete targets induced by hypervelocity projectile penetration,in the present study,six spherical projectile penetration tests on concrete targets were firstly conducted with projectile velocity ranged from 1875 m/s to 3940 m/s,in which the stress waves were carefully measured by the PVDF transducers.Then corresponding numerical models were developed and validated,and based on the validated numerical model the mechanisms of generation and propagation of stress waves were clarified.It was found that the stress waves observed during hypervelocity penetration are generated by the continuous interactions of projectile and target during penetration,and have unique characteristics such as the directionality and the"two peaks"phenomenon when compared with the stress waves generated by charge explosion.Finally,the effects of projectile velocity,projectile material,and target strength on the stress waves below the penetration depth we re numerically investigated,and two important indexes for evaluating the stress waves by hypervelocity penetration were proposed.
基金sponsored by the Fundamental Research Funds forthe Central Universities(No.2024-JYB-JBZD-047)High Level Key Discipline Construction of Traditional Chinese Medicine(zyyzdxk-2023272).
文摘Background:Building upon our previous work that developed a folate receptor-mediated,euphaorbia factor L1-loaded PLGA microsphere system integrating active and magnetic targeting for theranostics,further investigation into its in vivo pharmacokinetics and tissue distribution is warranted despite its demonstrated biocompatibility and safety.Methods:A UPLC-MS/MS method was established to determine the concentration of euphorbia sterol in rat plasma and mouse tissue homogenates,healthy male SD rats and KM mice were administered in groups,drug concentrations at different time points were determined,pharmacokinetic parameters were analyzed by DAS software,and data were processed by SAS software.Results:The proposed method met the requirements of biological sample detection.The plasma pharmacokinetics of rats showed that the drug concentration in the microsphere group was lower than that in the injection group,and the parameters such as mean residence time(MRT(0–t)),half-life(T1/2z)and apparent volume of distribution(Vz)were significantly different from those in the solution group.The distribution of mouse tissues showed that the drug concentrations in the liver and lung tissues of the microsphere preparation group were higher than those in the injection group,and the drug concentrations in the lung and liver tissues were more distributed.Conclusion:The targeted drug delivery system changed the pharmacokinetic behavior and tissue distribution of euphorbia sterol,slowed down plasma elimination,prolonged the half-life,and improved the targeting of drugs in lung and liver tissues and the magnetic targeting effect of lungs.
基金supported by National Natural Science Foundation of China(No.62202449 and No.62472410)National Key Research and Development Program of China(2021YFB2900102)。
文摘Multiple UAVs cooperative target search has been widely used in various environments,such as emergency rescue and traffic monitoring.However,uncertain communication network among UAVs exhibits unstable links and rapid topological fluctuations due to mission complexity and unpredictable environmental states.This limitation hinders timely information sharing and insightful path decisions for UAVs,resulting in inefficient or even failed collaborative search.Aiming at this issue,this paper proposes a multi-UAV cooperative search strategy by developing a real-time trajectory decision that incorporates autonomous connectivity to reinforce multi-UAV collaboration and achieve search acceleration in uncertain search environments.Specifically,an autonomous connectivity strategy based on node cognitive information and network states is introduced to enable effective message transmission and adapt to the dynamic network environment.Based on the fused information,we formalize the trajectory planning as a multiobjective optimization problem by jointly considering search performance and UAV energy harnessing.A multi-agent deep reinforcement learning based algorithm is proposed to solve it,where the reward-guided real-time path is determined to achieve an energyefficient search.Finally,extensive experimental results show that the proposed algorithm outperforms existing works in terms of average search rate and coverage rate with reduced energy consumption under uncertain search environments.
基金supported in part by the National Natural Science Foundation of China under Grant 62271302the Shanghai Municipal Natural Science Foundation under Grant 20ZR1423500.
文摘Infrared images typically exhibit diverse backgrounds,each potentially containing noise and target-like interference elements.In complex backgrounds,infrared small targets are prone to be submerged by background noise due to their low pixel proportion and limited available features,leading to detection failure.To address this problem,this paper proposes an Attention Shift-Invariant Cross-Evolutionary Feature Fusion Network(ASCFNet)tailored for the detection of infrared weak and small targets.The network architecture first designs a Multidimensional Lightweight Pixel-level Attention Module(MLPA),which alleviates the issue of small-target feature suppression during deep network propagation by combining channel reshaping,multi-scale parallel subnet architectures,and local cross-channel interactions.Then,a Multidimensional Shift-Invariant Recall Module(MSIR)is designed to ensure the network remains unaffected by minor input perturbations when processing infrared images,through focusing on the model’s shift invariance.Subsequently,a Cross-Evolutionary Feature Fusion structure(CEFF)is designed to allow flexible and efficient integration of multidimensional feature information from different network hierarchies,thereby achieving complementarity and enhancement among features.Experimental results on three public datasets,SIRST,NUDT-SIRST,and IRST640,demonstrate that our proposed network outperforms advanced algorithms in the field.Specifically,on the NUDT-SIRST dataset,the mAP50,mAP50-95,and metrics reached 99.26%,85.22%,and 99.31%,respectively.Visual evaluations of detection results in diverse scenarios indicate that our algorithm exhibits an increased detection rate and reduced false alarm rate.Our method balances accuracy and real-time performance,and achieves efficient and stable detection of infrared weak and small targets.
文摘Elevated lipoprotein(a)[Lp(a)]is a major independent risk factor for atheroscle-rotic cardiovascular disease(ASCVD),with limited response to traditional lipid-lowering therapies.Lepodisiran,a novel N-acetylgalactosamine-conjugated small interfering RNA,targets hepatic LPA message RNA to reduce apolipoprotein(a)production.Early-phase trials demonstrated>90%sustained Lp(a)reduction with excellent safety and tolerability.The phase 2 ALPACA trial confirmed dura-ble effects lasting up to one year after biannual dosing.Compared to other thera-pies,lepodisiran offers longer duration,high efficacy,and minimal side effects.Ongoing phase 3 studies aim to determine its impact on cardiovascular outcomes,potentially establishing a new standard in precise ASCVD risk management.
基金supported in part by Youth Innovation Promotion Association,Chinese Academy of Sciences under Grant 2022022in part by South China Sea Nova project of Hainan Province under Grant NHXXRCXM202340in part by the Scientific Research Foundation Project of Hainan Acoustics Laboratory under grant ZKNZ2024001.
文摘Underwater target detection in forward-looking sonar(FLS)images is a challenging but promising endeavor.The existing neural-based methods yield notable progress but there remains room for improvement due to overlooking the unique characteristics of underwater environments.Considering the problems of low imaging resolution,complex background environment,and large changes in target imaging of underwater sonar images,this paper specifically designs a sonar images target detection Network based on Progressive sensitivity capture,named ProNet.It progressively captures the sensitive regions in the current image where potential effective targets may exist.Guided by this basic idea,the primary technical innovation of this paper is the introduction of a foundational module structure for constructing a sonar target detection backbone network.This structure employs a multi-subspace mixed convolution module that initially maps sonar images into different subspaces and extracts local contextual features using varying convolutional receptive fields within these heterogeneous subspaces.Subsequently,a Scale-aware aggregation module effectively aggregates the heterogeneous features extracted from different subspaces.Finally,the multi-scale attention structure further enhances the relational perception of the aggregated features.We evaluated ProNet on three FLS datasets of varying scenes,and experimental results indicate that ProNet outperforms the current state-of-the-art sonar image and general target detectors.
文摘This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters while achieving multi-objective cooperative control for target fencing,network connectivity preservation,collision avoidance,and communication efficiency optimization.Firstly,a differential state observer is constructed to obtain the target's unmeasurable states.Secondly,leveraging swarm selforganization principles,a geometric-constraint-free distributed fencing controller is designed by integrating potential field methods with consensus theory.The controller dynamically adjusts inter-UAV distances via single potential function,enabling coordinated optimization of persistent network connectivity and collision-free motion during target fencing.Thirdly,a dual-threshold ETC mechanism based on velocity consensus deviation and fencing error is proposed,which can be triggered based on task features to dynamically adjust the communication frequency,significantly reduce the communication burden and exclude Zeno behavior.Theoretical analysis demonstrates the stability of closed-loop systems.Multi-scenario simulations show that the proposed method can achieve robust fencing under target maneuverability,partial UAV failures,and communication disturbances.
基金Research on Innovative Method of Drug Rational Use Supervision Decision Based on Big Data of Medical Insurance(Grant No.82273899)。
文摘Between 2016 and 2024,the Chinese government incorporated several innovative drugs into the National Reimbursement Drug List(NRDL)through price negotiations.These negotiations led to significant price reductions,which in turn stimulated an increase in sales.This study aimed to assess the impact of this policy on the pricing,utilization,and overall expenditure of targeted lung cancer therapies included in the NRDL.Using an interrupted time series analysis of procurement data from 698 healthcare institutions,the study evaluated both immediate and long-term effects.In terms of immediate effects,price negotiations resulted in a significant decline in the defined daily dose cost(DDDc)for all targeted therapies(P<0.05).Regarding long-term trends,a significant shift was observed only in the pricing trajectory of Gefitinib,Icotinib,and Ensartinib(P<0.05).In terms of immediate effects on drug utilization,all targeted medicines experienced a substantial increase in volume(P<0.05),except for Gefitinib and Icotinib.Over the long term,the usage of all targeted therapies exhibited a significant upward trend(P<0.05).With respect to expenditure,the immediate impact of NRDL inclusion resulted in a significant increase in spending on Afatinib,Crizotinib,Osimertinib,Alectinib,and Ensartinib(P<0.05).Over time,total spending on targeted medicines showed a significant increase(P<0.05),except for Erlotinib.Overall,NRDL price negotiations successfully reduced the economic burden on lung cancer patients,improving both accessibility and affordability of targeted therapies in China.
基金funded by the National Natural Science Foundation of China(22478438,32401048,and 82273882)the Science Fund for Distinguished Young Scholars of Jiangsu Province(BK20240098)the Special Research Fund from the State Key Laboratory of Natural Medicines at China Pharmaceutical University(SKLNMZZ2024JS19).
文摘Antitumor nanomedicines are usually decorated with ligands to achieve multiple functions,such as targeting delivery,tissue penetration and enhanced cellular uptake.However,a single ligand with multiple functions is generally preferred for use in practice.Herein,a versatile peptide,(HE)_(10)G_(5)R_(6)GDK(HE-RK),was engineered by integrating several motifs into a single sequence,including a masking segment(HE),a flexible linker(G_(5)),and a tumor-penetrating head(RK)which comprised a cell-penetrating peptide(R_(6))and a C-end Rule peptide(RGDK).The RK moiety in HE-RK was sequentially activated following the gradual charge reversal of HE to facilitate the accumulation of its cargos in deep tumor tissue and the cytosol of cancer cells.Moreover,in our study,polymer micelles conjugated with the HE-RK peptide(PM-HE-RK)showed superior cellular internalization at pH 6.5 compared to pH 7.4 in vitro,as well as extended blood circulation time and improved tumor targeting and penetration in vivo.Furthermore,the paclitaxel-loaded micelles(PTX/PM-HERK)demonstrated considerable antitumor efficacy,with an 81.48%tumor inhibition rate in the 4T1 mouse model.Overall,the construction of this all-in-one multisegment peptide presents a synergistic and complementary approach to advancing multifunctional peptide ligand design.
基金supported in part by the National Natural Science Foundation of China under Grant 62425110 and Grant U22A2002in part by the National Key Research and Development Program of China under Grant 2020YFA0711301+2 种基金in part by the Leading Project of Minzu University of China under Grant 2023QNYL23in part by the Key Research and Development Project of Nantong(Special Project for Prospective Technology Innovation)under Grant GZ2024002in part by the Suzhou Science and Technology Project,and in part by the FAW Jiefang Automotive Co.,Ltd.
文摘Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum scarcity,collaborative spectrum sharing is considered for hybrid satellite-terrestrial networks(HSTNs)in this paper.With only slowly-varying large-scale channel state information(CSI),joint power and channel allocation is implemented for terrestrial mobile terminals(MTs)which share the same frequency band with the satellite MTs oppor-tunistically.Specially,strict quality service assurance is adopted for terrestrial MTs under the constraint of leakage interference to satellite MTs.With the tar-get of maximizing both the number of served terres-trial MTs and the average sum transmission rate,a double-target spectrum sharing problem is formulated.To solve the complicated mixed integer programming(MIP)problem efficiently,user-centric channel pools are introduced.Simulations demonstrate that the proposed spectrum sharing scheme could achieve a significant performance gain for the HSTN.
基金supported by BMBF-Project No.05P24PF1DFG Project No.PU 213/6-3.
文摘We propose an all-optical,single-laser-pulse scheme for generating a dense relativistic strongly magnetized electron-positron pair plasma.The scheme involves the interaction of an extremely intense(I■10^(24) W/cm^(2))circularly polarized laser pulse with a solid-density target containing a conical cavity.Through full-scale three-dimensional particle-in-cell simulations that account for quantum electrodynamic effects,it is shown that this interaction results in two significant outcomes:first,the generation of quasi-static magnetic fields reaching tens of gigagauss,and,second,the production of large quantities of electron-positron pairs(up to 10^(13))via the Breit-Wheeler process.The e^(-)e^(+)plasma becomes trapped in the magnetic field and remains confined in a small volume for hundreds of femtoseconds,far exceeding the laser timescale.The dependence of pair plasma parameters,as well as the efficiency of plasma production and confinement,is discussed in relation to the properties of the laser pulse and the target.Realizing this scheme experimentally would enable the investigation of physical processes relevant to extreme astrophysical environments.
文摘Traditional Chinese medicine(TCM),especially the plant-based,represents complex chemical system containing various primary and secondary metabolites.These botanical metabolites are structurally diversified and exhibit significant difference in the acidity,alkalinity,molecular weight,polarity,and content,etc,which thus poses great challenges in assessing the quality of TCM[1].
基金Supported by Key project of National Key R&D Program of China in 2022(2022YFC2502700).
文摘[Objectives]This study was conducted to explore the curative effect of Qingfei Ditan decoction combined with targeted drug penetration therapy of traditional Chinese medicine on severe mycoplasma pneumonia in children.[Methods]Based on the retrospective study method,children with severe mycoplasma pneumonia admitted to the Children s Hospital of Soochow University from April 2023 to October 2023 were selected,and divided into a treatment group including 56 cases and a control group including 145 cases.The curative effect and adverse reactions of the two groups were compared.[Results]The total effective rate of the treatment group was higher than that of the control group,and the disappearance time of cough and lung rales was shorter than that of the control group,and the incidence of adverse reactions was lower,showing statistical significance(P<0.05).However,defervescence time and bronchoscope flushing rate showed no significant difference(P>0.05).[Conclusions]Qingfei Ditan Decoction combined with targeted drug penetration therapy of traditional Chinese medicine has a significant effect on severe mycoplasma pneumonia in children,and can reduce the side effects of drugs.It is a safe and efficient combination treatment scheme of traditional Chinese medicine.
基金the Deanship of Research and Graduate Studies at King Khalid University,KSA,for funding this work through the Large Research Project under grant number RGP2/164/46.
文摘Background:Stomach cancer(SC)is one of the most lethal malignancies worldwide due to late-stage diagnosis and limited treatment.The transcriptomic,epigenomic,and proteomic,etc.,omics datasets generated by high-throughput sequencing technology have become prominent in biomedical research,and they reveal molecular aspects of cancer diagnosis and therapy.Despite the development of advanced sequencing technology,the presence of high-dimensionality in multi-omics data makes it challenging to interpret the data.Methods:In this study,we introduce RankXLAN,an explainable ensemble-based multi-omics framework that integrates feature selection(FS),ensemble learning,bioinformatics,and in-silico validation for robust biomarker detection,potential therapeutic drug-repurposing candidates’identification,and classification of SC.To enhance the interpretability of the model,we incorporated explainable artificial intelligence(SHapley Additive exPlanations analysis),as well as accuracy,precision,F1-score,recall,cross-validation,specificity,likelihood ratio(LR)+,LR−,and Youden index results.Results:The experimental results showed that the top four FS algorithms achieved improved results when applied to the ensemble learning classification model.The proposed ensemble model produced an area under the curve(AUC)score of 0.994 for gene expression,0.97 for methylation,and 0.96 for miRNA expression data.Through the integration of bioinformatics and ML approach of the transcriptomic and epigenomic multi-omics dataset,we identified potential marker genes,namely,UBE2D2,HPCAL4,IGHA1,DPT,and FN3K.In-silico molecular docking revealed a strong binding affinity between ANKRD13C and the FDA-approved drug Everolimus(binding affinity−10.1 kcal/mol),identifying ANKRD13C as a potential therapeutic drug-repurposing target for SC.Conclusion:The proposed framework RankXLAN outperforms other existing frameworks for serum biomarker identification,therapeutic target identification,and SC classification with multi-omics datasets.
