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
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
Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,ta...Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,tau is not an easy target because it dynamically interacts with microtubules and other cellular components,which presents a challenge for tau-targeted drugs.New cellular models could aid the development of mechanism-based tau-targeted therapies.展开更多
Accurate time delay estimation of target echo signals is a critical component of underwater target localization.In active sonar systems,echo signal processing is vulnerable to the effects of reverberation and noise in...Accurate time delay estimation of target echo signals is a critical component of underwater target localization.In active sonar systems,echo signal processing is vulnerable to the effects of reverberation and noise in the maritime environment.This paper proposes a novel method for estimating target time delay using multi-bright spot echoes,assuming the target’s size and depth are known.Aiming to effectively enhance the extraction of geometric features from the target echoes and mitigate the impact of reverberation and noise,the proposed approach employs the fractional order Fourier transform-frequency sliced wavelet transform to extract multi-bright spot echoes.Using the highlighting model theory and the target size information,an observation matrix is constructed to represent multi-angle incident signals and obtain the theoretical scattered echo signals from different angles.Aiming to accurately estimate the target’s time delay,waveform similarity coefficients and mean square error values between the theoretical return signals and received signals are computed across various incident angles and time delays.Simulation results show that,compared to the conventional matched filter,the proposed algorithm reduces the relative error by 65.9%-91.5%at a signal-to noise ratio of-25 dB,and by 66.7%-88.9%at a signal-to-reverberation ratio of−10 dB.This algorithm provides a new approach for the precise localization of submerged targets in shallow water environments.展开更多
Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes...Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites,neglecting multilevel pathological analysis of the overall nervous system and target organs.This has led to restrictions on current therapeutic approaches.In this paper,we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective,covering the central nervous system,peripheral nervous system,and target organs.After peripheral nerve injury,the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves;changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord.The nerve will undergo axonal regeneration,activation of Schwann cells,inflammatory response,and vascular system regeneration at the injury site.Corresponding damage to target organs can occur,including skeletal muscle atrophy and sensory receptor disruption.We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury.The main current treatments are conducted passively and include physical factor rehabilitation,pharmacological treatments,cell-based therapies,and physical exercise.However,most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system-peripheral nervous system-target organ pathway.Therefore,we should further explore multilevel treatment options that produce effective,long-lasting results,perhaps requiring a combination of passive(traditional)and active(novel)treatment methods to stimulate rehabilitation at the central-peripheral-target organ levels to achieve better functional recovery.展开更多
Regulated cell death is a form of cell death that is actively controlled by biomolecules.Several studies have shown that regulated cell death plays a key role after spinal cord injury.Pyroptosis and ferroptosis are ne...Regulated cell death is a form of cell death that is actively controlled by biomolecules.Several studies have shown that regulated cell death plays a key role after spinal cord injury.Pyroptosis and ferroptosis are newly discovered types of regulated cell deaths that have been shown to exacerbate inflammation and lead to cell death in damaged spinal cords.Autophagy,a complex form of cell death that is interconnected with various regulated cell death mechanisms,has garnered significant attention in the study of spinal cord injury.This injury triggers not only cell death but also cellular survival responses.Multiple signaling pathways play pivotal roles in influencing the processes of both deterioration and repair in spinal cord injury by regulating pyroptosis,ferroptosis,and autophagy.Therefore,this review aims to comprehensively examine the mechanisms underlying regulated cell deaths,the signaling pathways that modulate these mechanisms,and the potential therapeutic targets for spinal cord injury.Our analysis suggests that targeting the common regulatory signaling pathways of different regulated cell deaths could be a promising strategy to promote cell survival and enhance the repair of spinal cord injury.Moreover,a holistic approach that incorporates multiple regulated cell deaths and their regulatory pathways presents a promising multi-target therapeutic strategy for the management of spinal cord injury.展开更多
The application of deep learning for target detection in aerial images captured by Unmanned Aerial Vehicles(UAV)has emerged as a prominent research focus.Due to the considerable distance between UAVs and the photograp...The application of deep learning for target detection in aerial images captured by Unmanned Aerial Vehicles(UAV)has emerged as a prominent research focus.Due to the considerable distance between UAVs and the photographed objects,coupled with complex shooting environments,existing models often struggle to achieve accurate real-time target detection.In this paper,a You Only Look Once v8(YOLOv8)model is modified from four aspects:the detection head,the up-sampling module,the feature extraction module,and the parameter optimization of positive sample screening,and the YOLO-S3DT model is proposed to improve the performance of the model for detecting small targets in aerial images.Experimental results show that all detection indexes of the proposed model are significantly improved without increasing the number of model parameters and with the limited growth of computation.Moreover,this model also has the best performance compared to other detecting models,demonstrating its advancement within this category of tasks.展开更多
Natural products(NPs)have historically been a fundamental source for drug discovery.Yet the complex nature of NPs presents substantial challenges in pinpointing bioactive constituents,and corresponding targets.In the ...Natural products(NPs)have historically been a fundamental source for drug discovery.Yet the complex nature of NPs presents substantial challenges in pinpointing bioactive constituents,and corresponding targets.In the present study,an innovative natural product virtual screening-interaction-phenotype(NP-VIP)strategy that integrates virtual screening,chemical proteomics,and metabolomics to identify and validate the bioactive targets of NPs.This approach reduces false positive results and enhances the efficiency of target identification.Salvia miltiorrhiza(SM),a herb with recognized therapeutic potential against ischemic stroke(IS),was used to illustrate the workflow.Utilizing virtual screening,chemical proteomics,and metabolomics,potential therapeutic targets for SM in the IS treatment were identified,totaling 29,100,and 78,respectively.Further analysis via the NP-VIP strategy highlighted five high-confidence targets,including poly[ADP-ribose]polymerase 1(PARP1),signal transducer and activator of transcription 3(STAT3),amyloid precursor protein(APP),glutamate-ammonia ligase(GLUL),and glutamate decarboxylase 67(GAD67).These targets were subsequently validated and found to play critical roles in the neuroprotective effects of SM.The study not only underscores the importance of SM in treating IS but also sets a precedent for NP research,proposing a comprehensive approach that could be adapted for broader pharmacological explorations.展开更多
The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aer...The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles(QUAVs).This scheme mainly consists of predefinedtime estimators and fixed-time tracking controllers,with a hybrid Laplacian matrix describing the communication among these QUAVs.At the first layer,we devise predefined time estimators for leading and following QUAVs,enabling accurate estimation of desired information.In the second layer,we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator faults.Fixedtime translational tracking controllers are then proposed,and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking controllers.We employ an exact tracking differentiator to handle variables that are challenging to differentiate directly.The paper includes a demonstration of the control system stability through mathematical proof,as well as the presentation of simulation results and comparative simulations.展开更多
Chronic atrophic gastritis(CAG)is an important stage of precancerous lesions of gastric cancer.Effective treatment and regulation of CAG are essential to prevent its progression to malignancy.Traditional Chinese medic...Chronic atrophic gastritis(CAG)is an important stage of precancerous lesions of gastric cancer.Effective treatment and regulation of CAG are essential to prevent its progression to malignancy.Traditional Chinese medicine(TCM)has shown multi-targeted efficacy in CAG treatment,with advantages in enhancing gastric mucosal barrier defense,improving microcirculation,modulating inflammatory and immune responses,and promoting lesion healing,etc.Clinical studies and meta-analyses indicate that TCM provides significant benefits,with specific Chinese herbal compounds and monomers demonstrating protective effects on the gastric mucosa through mechanisms including anti-inflammation,antioxidation,and regulation of cellular proliferation and apoptosis,etc.Finally,it is pointed out that the efficacy of TCM in the treatment of CAG requires standardized research and unified standards,and constantly clarifies and improves the evaluation criteria of each dimension of gastric mucosal barrier function.展开更多
Peripheral immunity forms the foundation of tumor immunity,while tumor immunity represents a more refined adaptation of peripheral immune responses.The tumor microenvironment(TME),a localized niche surrounding tumor c...Peripheral immunity forms the foundation of tumor immunity,while tumor immunity represents a more refined adaptation of peripheral immune responses.The tumor microenvironment(TME),a localized niche surrounding tumor cells,is inherently immunosuppressive(1,2).Effective tumor therapy necessitates the dismantling of this microenvironment,aiming to eradicate tumors from the host system.展开更多
Pancreatic cancer remains one of the most challenging malignancies to treat,with a poor prognosis and limited therapeutic options.Despite the success of immunotherapy and targeted therapies for other cancers,these app...Pancreatic cancer remains one of the most challenging malignancies to treat,with a poor prognosis and limited therapeutic options.Despite the success of immunotherapy and targeted therapies for other cancers,these approaches have not yet transformed the treatment landscape for pancreatic cancer.The unique tumor microenvironment(TME)of pancreatic cancer,characterized by dense fibrotic stroma and immunosuppressive myeloid cells,poses significant barriers to effective immunotherapy.Current research highlights the need for an in-depth understanding of the TME and the development of strategies to overcome its immunosuppressive properties.Recent studies have explored various immunotherapeutic approaches,including immune checkpoint inhibitors,cancer vaccines,and adoptive cell therapies,some of which have shown promising results in preclinical and early clinical trials.Furthermore,combining immunotherapy with traditional treatments,such as chemotherapy and radiotherapy,has shown potential for enhancing antitumor efficacy,although targeted therapies for pancreatic cancer are still in their early stages and are being investigated for their ability to disrupt specific molecular pathways involved in tumor growth and survival.This review provides a comprehensive overview of the advances in immunotherapy and targeted therapies for pancreatic cancer,discussing the current state of research,clinical outcomes,and future directions for improving patient prognosis.展开更多
An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyram...An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.展开更多
Acute pancreatitis(AP)is a common but potentially devastating disease characterized at onset patho-physiologically by premature activation of digestive enzymes within the pancreas.Despite an abundance of preclinical r...Acute pancreatitis(AP)is a common but potentially devastating disease characterized at onset patho-physiologically by premature activation of digestive enzymes within the pancreas.Despite an abundance of preclinical research and,until recently,a series of disappointing clinical trials,no specific disease mod-ifying pharmacological treatment has yet been approved for this condition.Recent novel approaches to understanding the molecular pathogenesis of AP provide us with renewed optimism for translational drug discovery.Although digestive enzyme activation is the hallmark of AP,a critical mechanism that initiates AP is intracellular calcium(Ca2+)overload in pancreatic parenchymal cells,which triggers mitochondrial dysfunction,endoplasmic reticulum(ER)stress,and impairs autophagic flux.These processes are piv-otal to the disease and present a range of drug targets,associated with the inflammatory responses that drive local and systemic inflammation in AP.Progress in translation has now been made,targeting the ORAI channel with the inhibitor zegocractin(Auxora)to reduce pancreatic injury and inflammatory re-sponses in human AP.Herein we evaluated potential drug targets for the early treatment of AP,focused on intra-acinar mechanisms of injury central to the onset and severity of AP.Our analysis highlights the opportunities and progress in translating these molecular insights into clinical therapies.展开更多
Genotyping by target sequencing(GBTS)integrates the advantages of silicon-based technology(high stability and reliability)and genotyping by sequencing(high flexibility and cost-effectiveness).However,GBTS panels are n...Genotyping by target sequencing(GBTS)integrates the advantages of silicon-based technology(high stability and reliability)and genotyping by sequencing(high flexibility and cost-effectiveness).However,GBTS panels are not currently available in pigs.In this study,based on GBTS technology,we first developed a 50K panel,including 52,000 single-nucleotide polymorphisms(SNPs),in pigs,designated GBTS50K.A total of 6,032 individuals of Large White,Landrace,and Duroc pigs from 10 breeding farms were used to assess the newly developed GBTS50K.Our results showed that GBTS50K obtained a high genotyping ability,the SNP and individual call rates of GBTS50K were 0.997–0.998,and the average consistency rate and genotyping correlation coefficient were 0.997 and 0.993,respectively,in replicate samples.We also evaluated the efficiencies of GBTS50K in the application of population genetic structure analysis,selection signature detection,genome-wide association studies(GWAS),genotyped imputation,genetic selection(GS),etc.The results indicate that GBTS50K is plausible and powerful in genetic analysis and molecular breeding.For example,GBTS50K could gain higher accuracies than the current popular GGP-Porcine bead chip in genomic selection on 2 important traits of backfat thickness at 100 kg and days to 100 kg in pigs.Particularly,due to the multiple SNPs(mSNPs),GBTS50K generated 100K qualified SNPs without increasing genotyping cost,and our results showed that the haplotype-based method can further improve the accuracies of genomic selection on growth and reproduction traits by 2 to 6%.Our study showed that GBTS50K could be a powerful tool for underlying genetic architecture and molecular breeding in pigs,and it is also helpful for developing SNP panels for other farm animals.展开更多
Metal complexes hold significant promise in tumor diagnosis and treatment.However,their potential applications in photodynamic therapy(PDT)are hindered by issues such as poor photostability,low yield of reactive oxyge...Metal complexes hold significant promise in tumor diagnosis and treatment.However,their potential applications in photodynamic therapy(PDT)are hindered by issues such as poor photostability,low yield of reactive oxygen species(ROS),and aggregation-induced ROS quenching.To address these challenges,we present a molecular self-assembly strategy utilizing aggregation-induced emission(AIE)conjugates for metal complexes.As a proof of concept,we synthesized a mitochondrial-targeting cyclometalated Ir(Ⅲ)photosensitizer Ir-TPE.This approach significantly enhances the photodynamic effect while mitigating the dark toxicity associated with AIE groups.Ir-TPE readily self-assembles into nanoaggregates in aqueous solution,leading to a significant production of ROS upon light irradiation.Photoirradiated Ir-TPE triggers multiple modes of death by excessively accumulating ROS in the mitochondria,resulting in mitochondrial DNA damage.This damage can lead to ferroptosis and autophagy,two forms of cell death that are highly cytotoxic to cancer cells.The aggregation-enhanced photodynamic effect of Ir-TPE significantly enhances the production of ROS,leading to a more pronounced cytotoxic effect.In vitro and in vivo experiments demonstrate this aggregation-enhanced PDT approach achieves effective in situ tumor eradication.This study not only addresses the limitations of metal complexes in terms of low ROS production due to aggregation but also highlights the potential of this strategy for enhancing ROS production in PDT.展开更多
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
Unmanned aerial vehicle(UAV)imagery poses significant challenges for object detection due to extreme scale variations,high-density small targets(68%in VisDrone dataset),and complex backgrounds.While YOLO-series models...Unmanned aerial vehicle(UAV)imagery poses significant challenges for object detection due to extreme scale variations,high-density small targets(68%in VisDrone dataset),and complex backgrounds.While YOLO-series models achieve speed-accuracy trade-offs via fixed convolution kernels and manual feature fusion,their rigid architectures struggle with multi-scale adaptability,as exemplified by YOLOv8n’s 36.4%mAP and 13.9%small-object AP on VisDrone2019.This paper presents YOLO-LE,a lightweight framework addressing these limitations through three novel designs:(1)We introduce the C2f-Dy and LDown modules to enhance the backbone’s sensitivity to small-object features while reducing backbone parameters,thereby improving model efficiency.(2)An adaptive feature fusion module is designed to dynamically integrate multi-scale feature maps,optimizing the neck structure,reducing neck complexity,and enhancing overall model performance.(3)We replace the original loss function with a distributed focal loss and incorporate a lightweight self-attention mechanism to improve small-object recognition and bounding box regression accuracy.Experimental results demonstrate that YOLO-LE achieves 39.9%mAP@0.5 on VisDrone2019,representing a 9.6%improvement over YOLOv8n,while maintaining 8.5 GFLOPs computational efficiency.This provides an efficient solution for UAV object detection in complex scenarios.展开更多
This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and car...This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and carbon-neutrality pathways that align with China's national conditions,rather than following the idealized path toward the 1.5℃target by initially relying on extensive negative-emission technologies such as direct air carbon capture and storage(DACCS).This work suggests that pursuing a 1.5℃target is increasingly less feasible for China,as it would potentially incur 3–4 times the cost of pursuing the 2℃target.With China being likely to achieve a peak in its emissions around 2028,at about 12.8 billion tonnes of anthropogenic carbon dioxide(CO_(2)),and become carbon neutral,projected global warming levels may be less severe after the 2050s than previously estimated.This could reduce the risk potential of climate tipping points and extreme events,especially considering that the other two major carbon emitters in the world(Europe and North America)have already passed their carbon peaks.While natural carbon sinks will contribute to China's carbon neutrality efforts,they are not expected to be decisive in the transition stages.This research also addresses the growing focus on climate overshoot,tipping points,extreme events,loss and damage,and methane reductions in international climate cooperation,emphasizing the need to balance these issues with China's development,security,and fairness considerations.China's pursuit of carbon neutrality will have significant implications for global emissions scenarios,warming levels,and extreme event projections,as well as for climate change hotspots of international concern,such as climate tipping points,the climate crisis,and the notion that the world has moved from a warming to a boiling era.Possible research recommendations for global emissions scenarios based on China's 2℃target pathway are also summarized.展开更多
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.
文摘Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,tau is not an easy target because it dynamically interacts with microtubules and other cellular components,which presents a challenge for tau-targeted drugs.New cellular models could aid the development of mechanism-based tau-targeted therapies.
基金Supported by the State Key Laboratory of Acoustics and Marine Information Chinese Academy of Sciences(SKL A202507).
文摘Accurate time delay estimation of target echo signals is a critical component of underwater target localization.In active sonar systems,echo signal processing is vulnerable to the effects of reverberation and noise in the maritime environment.This paper proposes a novel method for estimating target time delay using multi-bright spot echoes,assuming the target’s size and depth are known.Aiming to effectively enhance the extraction of geometric features from the target echoes and mitigate the impact of reverberation and noise,the proposed approach employs the fractional order Fourier transform-frequency sliced wavelet transform to extract multi-bright spot echoes.Using the highlighting model theory and the target size information,an observation matrix is constructed to represent multi-angle incident signals and obtain the theoretical scattered echo signals from different angles.Aiming to accurately estimate the target’s time delay,waveform similarity coefficients and mean square error values between the theoretical return signals and received signals are computed across various incident angles and time delays.Simulation results show that,compared to the conventional matched filter,the proposed algorithm reduces the relative error by 65.9%-91.5%at a signal-to noise ratio of-25 dB,and by 66.7%-88.9%at a signal-to-reverberation ratio of−10 dB.This algorithm provides a new approach for the precise localization of submerged targets in shallow water environments.
基金supported by grants from the Natural Science Foundation of Tianjin(General Program),Nos.23JCYBJC01390(to RL),22JCYBJC00220(to XC),and 22JCYBJC00210(to QL).
文摘Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites,neglecting multilevel pathological analysis of the overall nervous system and target organs.This has led to restrictions on current therapeutic approaches.In this paper,we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective,covering the central nervous system,peripheral nervous system,and target organs.After peripheral nerve injury,the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves;changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord.The nerve will undergo axonal regeneration,activation of Schwann cells,inflammatory response,and vascular system regeneration at the injury site.Corresponding damage to target organs can occur,including skeletal muscle atrophy and sensory receptor disruption.We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury.The main current treatments are conducted passively and include physical factor rehabilitation,pharmacological treatments,cell-based therapies,and physical exercise.However,most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system-peripheral nervous system-target organ pathway.Therefore,we should further explore multilevel treatment options that produce effective,long-lasting results,perhaps requiring a combination of passive(traditional)and active(novel)treatment methods to stimulate rehabilitation at the central-peripheral-target organ levels to achieve better functional recovery.
基金supported by the Natural Science Foundation of Fujian Province,No.2021J02035(to WX).
文摘Regulated cell death is a form of cell death that is actively controlled by biomolecules.Several studies have shown that regulated cell death plays a key role after spinal cord injury.Pyroptosis and ferroptosis are newly discovered types of regulated cell deaths that have been shown to exacerbate inflammation and lead to cell death in damaged spinal cords.Autophagy,a complex form of cell death that is interconnected with various regulated cell death mechanisms,has garnered significant attention in the study of spinal cord injury.This injury triggers not only cell death but also cellular survival responses.Multiple signaling pathways play pivotal roles in influencing the processes of both deterioration and repair in spinal cord injury by regulating pyroptosis,ferroptosis,and autophagy.Therefore,this review aims to comprehensively examine the mechanisms underlying regulated cell deaths,the signaling pathways that modulate these mechanisms,and the potential therapeutic targets for spinal cord injury.Our analysis suggests that targeting the common regulatory signaling pathways of different regulated cell deaths could be a promising strategy to promote cell survival and enhance the repair of spinal cord injury.Moreover,a holistic approach that incorporates multiple regulated cell deaths and their regulatory pathways presents a promising multi-target therapeutic strategy for the management of spinal cord injury.
文摘The application of deep learning for target detection in aerial images captured by Unmanned Aerial Vehicles(UAV)has emerged as a prominent research focus.Due to the considerable distance between UAVs and the photographed objects,coupled with complex shooting environments,existing models often struggle to achieve accurate real-time target detection.In this paper,a You Only Look Once v8(YOLOv8)model is modified from four aspects:the detection head,the up-sampling module,the feature extraction module,and the parameter optimization of positive sample screening,and the YOLO-S3DT model is proposed to improve the performance of the model for detecting small targets in aerial images.Experimental results show that all detection indexes of the proposed model are significantly improved without increasing the number of model parameters and with the limited growth of computation.Moreover,this model also has the best performance compared to other detecting models,demonstrating its advancement within this category of tasks.
基金supported by the National Natural Science Foundations of China(Grant No.:82204584)Liaoning Provincial Science and Technology Projects,China(Project No.:2021JH1/10400055).
文摘Natural products(NPs)have historically been a fundamental source for drug discovery.Yet the complex nature of NPs presents substantial challenges in pinpointing bioactive constituents,and corresponding targets.In the present study,an innovative natural product virtual screening-interaction-phenotype(NP-VIP)strategy that integrates virtual screening,chemical proteomics,and metabolomics to identify and validate the bioactive targets of NPs.This approach reduces false positive results and enhances the efficiency of target identification.Salvia miltiorrhiza(SM),a herb with recognized therapeutic potential against ischemic stroke(IS),was used to illustrate the workflow.Utilizing virtual screening,chemical proteomics,and metabolomics,potential therapeutic targets for SM in the IS treatment were identified,totaling 29,100,and 78,respectively.Further analysis via the NP-VIP strategy highlighted five high-confidence targets,including poly[ADP-ribose]polymerase 1(PARP1),signal transducer and activator of transcription 3(STAT3),amyloid precursor protein(APP),glutamate-ammonia ligase(GLUL),and glutamate decarboxylase 67(GAD67).These targets were subsequently validated and found to play critical roles in the neuroprotective effects of SM.The study not only underscores the importance of SM in treating IS but also sets a precedent for NP research,proposing a comprehensive approach that could be adapted for broader pharmacological explorations.
基金supported by Natural Science Basic Research Plan in Shaanxi Province of China(No.2023-JC-QN-0733)Guangdong Basic and Applied Basic Research Foundation,China(No.2022A1515110753)+2 种基金China Postdoctoral Science Foundation(No.2022M722583)China Industry-UniversityResearch Innovation Foundation(No.2022IT188)National Key Laboratory of Air-based Information Perception and Fusion and the Aeronautic Science Foundation of China(No.20220001068001)。
文摘The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles(QUAVs).This scheme mainly consists of predefinedtime estimators and fixed-time tracking controllers,with a hybrid Laplacian matrix describing the communication among these QUAVs.At the first layer,we devise predefined time estimators for leading and following QUAVs,enabling accurate estimation of desired information.In the second layer,we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator faults.Fixedtime translational tracking controllers are then proposed,and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking controllers.We employ an exact tracking differentiator to handle variables that are challenging to differentiate directly.The paper includes a demonstration of the control system stability through mathematical proof,as well as the presentation of simulation results and comparative simulations.
基金Supported by the Scientific and Technological Innovation Project of China Academy of Chinese Medical Sciences,No.CI2021A00806High Level Chinese Medical Hospital Promotion Project,No.HLCMHPP2023086the Fundamental Research Funds for the Central Public Welfare Research Institutes,No.ZZ17-XRZ-041.
文摘Chronic atrophic gastritis(CAG)is an important stage of precancerous lesions of gastric cancer.Effective treatment and regulation of CAG are essential to prevent its progression to malignancy.Traditional Chinese medicine(TCM)has shown multi-targeted efficacy in CAG treatment,with advantages in enhancing gastric mucosal barrier defense,improving microcirculation,modulating inflammatory and immune responses,and promoting lesion healing,etc.Clinical studies and meta-analyses indicate that TCM provides significant benefits,with specific Chinese herbal compounds and monomers demonstrating protective effects on the gastric mucosa through mechanisms including anti-inflammation,antioxidation,and regulation of cellular proliferation and apoptosis,etc.Finally,it is pointed out that the efficacy of TCM in the treatment of CAG requires standardized research and unified standards,and constantly clarifies and improves the evaluation criteria of each dimension of gastric mucosal barrier function.
文摘Peripheral immunity forms the foundation of tumor immunity,while tumor immunity represents a more refined adaptation of peripheral immune responses.The tumor microenvironment(TME),a localized niche surrounding tumor cells,is inherently immunosuppressive(1,2).Effective tumor therapy necessitates the dismantling of this microenvironment,aiming to eradicate tumors from the host system.
文摘Pancreatic cancer remains one of the most challenging malignancies to treat,with a poor prognosis and limited therapeutic options.Despite the success of immunotherapy and targeted therapies for other cancers,these approaches have not yet transformed the treatment landscape for pancreatic cancer.The unique tumor microenvironment(TME)of pancreatic cancer,characterized by dense fibrotic stroma and immunosuppressive myeloid cells,poses significant barriers to effective immunotherapy.Current research highlights the need for an in-depth understanding of the TME and the development of strategies to overcome its immunosuppressive properties.Recent studies have explored various immunotherapeutic approaches,including immune checkpoint inhibitors,cancer vaccines,and adoptive cell therapies,some of which have shown promising results in preclinical and early clinical trials.Furthermore,combining immunotherapy with traditional treatments,such as chemotherapy and radiotherapy,has shown potential for enhancing antitumor efficacy,although targeted therapies for pancreatic cancer are still in their early stages and are being investigated for their ability to disrupt specific molecular pathways involved in tumor growth and survival.This review provides a comprehensive overview of the advances in immunotherapy and targeted therapies for pancreatic cancer,discussing the current state of research,clinical outcomes,and future directions for improving patient prognosis.
基金supported by the National Natural Science Foundation of China(No.62241109)the Tianjin Science and Technology Commissioner Project(No.20YDTPJC01110)。
文摘An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.
基金supported by grants from the National Nat-ural Science Foundation of China(82122010 and 82070659)the National High Level Hospital Clinical Research Funding(2022-PUMCH-E-003)+1 种基金the CAMS Innovation Fund for Medical Science(2022-I2M-1-004)an NIHR Senior Investigator Award。
文摘Acute pancreatitis(AP)is a common but potentially devastating disease characterized at onset patho-physiologically by premature activation of digestive enzymes within the pancreas.Despite an abundance of preclinical research and,until recently,a series of disappointing clinical trials,no specific disease mod-ifying pharmacological treatment has yet been approved for this condition.Recent novel approaches to understanding the molecular pathogenesis of AP provide us with renewed optimism for translational drug discovery.Although digestive enzyme activation is the hallmark of AP,a critical mechanism that initiates AP is intracellular calcium(Ca2+)overload in pancreatic parenchymal cells,which triggers mitochondrial dysfunction,endoplasmic reticulum(ER)stress,and impairs autophagic flux.These processes are piv-otal to the disease and present a range of drug targets,associated with the inflammatory responses that drive local and systemic inflammation in AP.Progress in translation has now been made,targeting the ORAI channel with the inhibitor zegocractin(Auxora)to reduce pancreatic injury and inflammatory re-sponses in human AP.Herein we evaluated potential drug targets for the early treatment of AP,focused on intra-acinar mechanisms of injury central to the onset and severity of AP.Our analysis highlights the opportunities and progress in translating these molecular insights into clinical therapies.
基金supported by the grants from the Key R&D Program of Shandong Province,China(2022LZGC003)the China Agriculture Research System of MOF and MARA(CARS-35)+1 种基金the National Key Research and Development Project of China(2019YFE0106800)the 2115 Talent Development Program of China Agricultural University。
文摘Genotyping by target sequencing(GBTS)integrates the advantages of silicon-based technology(high stability and reliability)and genotyping by sequencing(high flexibility and cost-effectiveness).However,GBTS panels are not currently available in pigs.In this study,based on GBTS technology,we first developed a 50K panel,including 52,000 single-nucleotide polymorphisms(SNPs),in pigs,designated GBTS50K.A total of 6,032 individuals of Large White,Landrace,and Duroc pigs from 10 breeding farms were used to assess the newly developed GBTS50K.Our results showed that GBTS50K obtained a high genotyping ability,the SNP and individual call rates of GBTS50K were 0.997–0.998,and the average consistency rate and genotyping correlation coefficient were 0.997 and 0.993,respectively,in replicate samples.We also evaluated the efficiencies of GBTS50K in the application of population genetic structure analysis,selection signature detection,genome-wide association studies(GWAS),genotyped imputation,genetic selection(GS),etc.The results indicate that GBTS50K is plausible and powerful in genetic analysis and molecular breeding.For example,GBTS50K could gain higher accuracies than the current popular GGP-Porcine bead chip in genomic selection on 2 important traits of backfat thickness at 100 kg and days to 100 kg in pigs.Particularly,due to the multiple SNPs(mSNPs),GBTS50K generated 100K qualified SNPs without increasing genotyping cost,and our results showed that the haplotype-based method can further improve the accuracies of genomic selection on growth and reproduction traits by 2 to 6%.Our study showed that GBTS50K could be a powerful tool for underlying genetic architecture and molecular breeding in pigs,and it is also helpful for developing SNP panels for other farm animals.
基金support from the National Natural Science Foundation of China(Nos.22277056,21977052)the Distinguished Young Scholars of Jiangsu Province(No.BK20230006)+2 种基金the Natural Science Foundation of Jiangsu Province(Nos.BK20230977,BK20231090)the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(No.23KJB150020)the Jiangsu Excellent Postdoctoral Program(No.2022ZB758)。
文摘Metal complexes hold significant promise in tumor diagnosis and treatment.However,their potential applications in photodynamic therapy(PDT)are hindered by issues such as poor photostability,low yield of reactive oxygen species(ROS),and aggregation-induced ROS quenching.To address these challenges,we present a molecular self-assembly strategy utilizing aggregation-induced emission(AIE)conjugates for metal complexes.As a proof of concept,we synthesized a mitochondrial-targeting cyclometalated Ir(Ⅲ)photosensitizer Ir-TPE.This approach significantly enhances the photodynamic effect while mitigating the dark toxicity associated with AIE groups.Ir-TPE readily self-assembles into nanoaggregates in aqueous solution,leading to a significant production of ROS upon light irradiation.Photoirradiated Ir-TPE triggers multiple modes of death by excessively accumulating ROS in the mitochondria,resulting in mitochondrial DNA damage.This damage can lead to ferroptosis and autophagy,two forms of cell death that are highly cytotoxic to cancer cells.The aggregation-enhanced photodynamic effect of Ir-TPE significantly enhances the production of ROS,leading to a more pronounced cytotoxic effect.In vitro and in vivo experiments demonstrate this aggregation-enhanced PDT approach achieves effective in situ tumor eradication.This study not only addresses the limitations of metal complexes in terms of low ROS production due to aggregation but also highlights the potential of this strategy for enhancing ROS production in PDT.
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Unmanned aerial vehicle(UAV)imagery poses significant challenges for object detection due to extreme scale variations,high-density small targets(68%in VisDrone dataset),and complex backgrounds.While YOLO-series models achieve speed-accuracy trade-offs via fixed convolution kernels and manual feature fusion,their rigid architectures struggle with multi-scale adaptability,as exemplified by YOLOv8n’s 36.4%mAP and 13.9%small-object AP on VisDrone2019.This paper presents YOLO-LE,a lightweight framework addressing these limitations through three novel designs:(1)We introduce the C2f-Dy and LDown modules to enhance the backbone’s sensitivity to small-object features while reducing backbone parameters,thereby improving model efficiency.(2)An adaptive feature fusion module is designed to dynamically integrate multi-scale feature maps,optimizing the neck structure,reducing neck complexity,and enhancing overall model performance.(3)We replace the original loss function with a distributed focal loss and incorporate a lightweight self-attention mechanism to improve small-object recognition and bounding box regression accuracy.Experimental results demonstrate that YOLO-LE achieves 39.9%mAP@0.5 on VisDrone2019,representing a 9.6%improvement over YOLOv8n,while maintaining 8.5 GFLOPs computational efficiency.This provides an efficient solution for UAV object detection in complex scenarios.
基金supported by the top-level design of the National Natural Science Foundation of China(NSFC)Major Project“Realization of optimal carbon neutral pathway and coupling of multi-scale interaction patterns of natural-social systems in China”(42341202)the Basic Scientific Research Fund of the Chinese Academy of Meteorological Sciences(2021Z014)。
文摘This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and carbon-neutrality pathways that align with China's national conditions,rather than following the idealized path toward the 1.5℃target by initially relying on extensive negative-emission technologies such as direct air carbon capture and storage(DACCS).This work suggests that pursuing a 1.5℃target is increasingly less feasible for China,as it would potentially incur 3–4 times the cost of pursuing the 2℃target.With China being likely to achieve a peak in its emissions around 2028,at about 12.8 billion tonnes of anthropogenic carbon dioxide(CO_(2)),and become carbon neutral,projected global warming levels may be less severe after the 2050s than previously estimated.This could reduce the risk potential of climate tipping points and extreme events,especially considering that the other two major carbon emitters in the world(Europe and North America)have already passed their carbon peaks.While natural carbon sinks will contribute to China's carbon neutrality efforts,they are not expected to be decisive in the transition stages.This research also addresses the growing focus on climate overshoot,tipping points,extreme events,loss and damage,and methane reductions in international climate cooperation,emphasizing the need to balance these issues with China's development,security,and fairness considerations.China's pursuit of carbon neutrality will have significant implications for global emissions scenarios,warming levels,and extreme event projections,as well as for climate change hotspots of international concern,such as climate tipping points,the climate crisis,and the notion that the world has moved from a warming to a boiling era.Possible research recommendations for global emissions scenarios based on China's 2℃target pathway are also summarized.
