针对自动驾驶场景下,近处干扰点云误检率高、远处稀疏点云漏检率高的问题,提出了一种基于改进PointPillars的自动驾驶障碍物点云检测算法.首先,通过聚合模块和共享多层感知机(shared multi-layer perceptron,MLP)对柱体内点云进行特征编...针对自动驾驶场景下,近处干扰点云误检率高、远处稀疏点云漏检率高的问题,提出了一种基于改进PointPillars的自动驾驶障碍物点云检测算法.首先,通过聚合模块和共享多层感知机(shared multi-layer perceptron,MLP)对柱体内点云进行特征编码,采用最大池化与平均池化叠加的方法将点云的显著特征与细节特征映射为柱体特征;其次,针对算法对伪图特征关注与利用不充分的问题,引入坐标注意力(coordinate attention,CA)机制和残差连接的伪图特征提取模块(attention and residual second block,ARSB),将深层与浅层特征图进行融合,优化算法梯度,增强算法对有效目标的关注度.试验结果表明:改进算法对全局点云检测精度较高,平均精度优于PointPillars、稀疏到稠密3D目标检测器(STD)等点云目标检测算法,在汽车类别上的检测精度优势明显,检测速度较快,符合实时性要求.展开更多
Alzheimer's disease,a progressively degenerative neurological disorder,is the most common cause of dementia in the elderly.While its precise etiology remains unclear,researchers have identified diverse pathologica...Alzheimer's disease,a progressively degenerative neurological disorder,is the most common cause of dementia in the elderly.While its precise etiology remains unclear,researchers have identified diverse pathological characteristics and molecular pathways associated with its progression.Advances in scientific research have increasingly highlighted the crucial role of non-coding RNAs in the progression of Alzheimer's disease.These non-coding RNAs regulate several biological processes critical to the advancement of the disease,offering promising potential as therapeutic targets and diagnostic biomarkers.Therefore,this review aims to investigate the underlying mechanisms of Alzheimer's disease onset,with a particular focus on microRNAs,long non-coding RNAs,and circular RNAs associated with the disease.The review elucidates the potential pathogenic processes of Alzheimer's disease and provides a detailed description of the synthesis mechanisms of the three aforementioned non-coding RNAs.It comprehensively summarizes the various non-coding RNAs that have been identified to play key regulatory roles in Alzheimer's disease,as well as how these noncoding RNAs influence the disease's progression by regulating gene expression and protein functions.For example,miR-9 targets the UBE4B gene,promoting autophagy-mediated degradation of Tau protein,thereby reducing Tau accumulation and delaying Alzheimer's disease progression.Conversely,the long non-coding RNA BACE1-AS stabilizes BACE1 mRNA,promoting the generation of amyloid-βand accelerating Alzheimer's disease development.Additionally,circular RNAs play significant roles in regulating neuroinflammatory responses.By integrating insights from these regulatory mechanisms,there is potential to discover new therapeutic targets and potential biomarkers for early detection and management of Alzheimer's disease.This review aims to enhance the understanding of the relationship between Alzheimer's disease and non-coding RNAs,potentially paving the way for early detection and novel treatment strategies.展开更多
3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with m...3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with multi-scale targets,remains challenging.This paper proposes an enhanced segmentation method integrating improved PointNet++with a coverage-voted strategy.The coverage-voted strategy reduces data while preserving multi-scale target topology.The segmentation is achieved using an enhanced PointNet++algorithm with a normalization preprocessing head,resulting in a 94%accuracy for common supporting components.Ablation experiments show that the preprocessing head and coverage strategies increase segmentation accuracy by 20%and 2%,respectively,and improve Intersection over Union(IoU)for bearing plate segmentation by 58%and 20%.The accuracy of the current pretraining segmentation model may be affected by variations in surface support components,but it can be readily enhanced through re-optimization with additional labeled point cloud data.This proposed method,combined with a previously developed machine learning model that links rock bolt load and the deformation field of its bearing plate,provides a robust technique for simultaneously measuring the load of multiple rock bolts in a single laser scan.展开更多
Genomic destabilization and defective DNA repair are the most prominent features of tumour cells and are exploited by various chemotherapy drugs for cancer therapy.Long non-coding RNA(lncR-NAs)have emerged as powerful...Genomic destabilization and defective DNA repair are the most prominent features of tumour cells and are exploited by various chemotherapy drugs for cancer therapy.Long non-coding RNA(lncR-NAs)have emerged as powerful regulators of gene expression and are thus involved in diverse biological processes.Recent studies have demonstrated that several lncRNAs play critical roles in DNA repair.Nonetheless,the relationship between DNA damage-responsive lncRNAs and chemoresistance remains poorly defined.In this study,we established four different DNA damage models triggered by cisplatin(DDP),H2O2,neocarzinostatin(NCS)or ultraviolet(UV)irradiation and identified a specific upregu-lated lncRNA(lnc-DUSP6)involved in the cisplatin-induced DNA damage response.Furthermore,loss-or gain-of-function experiments confirmed that lnc-DUSP6 enhanced DNA repair and cell survival under cisplatin treatment,thus promoting cisplatin resistance.Mechanistically,an RNA immunoprecipitation(RIP)assay revealed that lnc-DUSP6 directly interacts with DUSP6(Dual Specificity Phosphatase 6),which is closely associated with cisplatin sensitivity.Additionally,overexpression of DUSP6 significantly rescued the effects of lnc-DUSP6 silencing on DNA repair and cell survival under cisplatin treatment.O-verall,our results show the effect and underlying mechanism of lnc-DUSP6 in cisplatin resistance:lnc-DUSP6 promotes cisplatin-induced DNA damage repair and cisplatin resistance by stabilizing DUSP6,which is highly clinically important for enhancing the efficacy of cisplatin for cancers.展开更多
Gastric cancer(GC)has high morbidity and mortality worldwide.Due to the absence of noticeable symptoms,diagnosing GC at an early stage is very difficult,which consequently leads to advanced GC and poor prognosis.Effec...Gastric cancer(GC)has high morbidity and mortality worldwide.Due to the absence of noticeable symptoms,diagnosing GC at an early stage is very difficult,which consequently leads to advanced GC and poor prognosis.Effective biomarkers are essential for prolonging patients’survival.Helicobacter pylori(H.pylori)infection represents the most significant risk factor for GC,with nearly all cases linked to this infection.Many non-coding RNAs(ncRNAs)are dysregulated in H.pylori-infected GC,indicating that ncRNAs may serve as biomarkers of early-stage GC.In this editorial,we discuss the study by Chen et al.Although previous studies have identified roles for miR-136 in gastric cancer proliferation,apoptosis,and invasion,none have specifically explored its relationship with H.pylori-associated gastric carcinogenesis.展开更多
A large body of evidence has highlighted the role of non-coding RNAs in neurodevelopment and neuroinflammation.This evidence has led to increasing speculation that non-coding RNAs may be involved in the pathophysiolog...A large body of evidence has highlighted the role of non-coding RNAs in neurodevelopment and neuroinflammation.This evidence has led to increasing speculation that non-coding RNAs may be involved in the pathophysiological mechanisms underlying hydrocephalus,one of the most common neurological conditions worldwide.In this review,we first outline the basic concepts and incidence of hydrocephalus along with the limitations of existing treatments for this condition.Then,we outline the definition,classification,and biological role of non-coding RNAs.Subsequently,we analyze the roles of non-coding RNAs in the formation of hydrocephalus in detail.Specifically,we have focused on the potential significance of non-coding RNAs in the pathophysiology of hydrocephalus,including glymphatic pathways,neuroinflammatory processes,and neurological dysplasia,on the basis of the existing evidence.Lastly,we review the potential of non-coding RNAs as biomarkers of hydrocephalus and for the creation of innovative treatments.展开更多
Anther is a key male reproductive organ that is essential for the plant life cycle,from the sporophyte to the gametophyte generation.To explore the isoform-level transcriptional landscape of developing anthers in maiz...Anther is a key male reproductive organ that is essential for the plant life cycle,from the sporophyte to the gametophyte generation.To explore the isoform-level transcriptional landscape of developing anthers in maize(Zea mays L.),we analyzed Iso-Seq data from anthers collected at 10 developmental stages,together with strand-specific RNA-seq,CAGE-seq,and PAS-seq data.Of the 152,026 high-confidence full-length isoforms identified,68.8%have not been described;these include 22,365 isoforms that originate from previously unannotated loci and 82,167 novel isoforms that originate from annotated protein-coding genes.Using our newly developed strategy to detect dynamic expression patterns of isoforms,we identify 13,899 differentially variable regions(DVRs);surprisingly,1275 genes contain more than two DVRs,revealing highly efficient utilization of limited genic regions.We identify 7876 long non-coding RNAs(lncRNAs)from 4098 loci,most of which were preferentially expressed during cell differentiation and meiosis.We also detected 371 long-range interactions involving intergenic lncRNAs(lincRNAs);interestingly,243 were lincRNA-gene ones,and the interacting genes were highly expressed in anthers,suggesting that many potential lncRNA regulators of key genes are required for anther development.This study provides valuable resources and fundamental information for studying the essential transcripts of key genes during anther development.展开更多
Flavonoids,abundant in the fruits,are pivotal to their growth,development,and storage.In addition,they have significant beneficial effects on human health.Consequently,research is increasingly concentrating on the reg...Flavonoids,abundant in the fruits,are pivotal to their growth,development,and storage.In addition,they have significant beneficial effects on human health.Consequently,research is increasingly concentrating on the regulatory mechanisms governing flavonoid biosynthesis in fruits.Phytohormones are involved in the regulation of flavonoid biosynthesis.The abscisic acid,ethylene,jasmonic acid,cytokinins,and brassinosteroids promote flavonoid biosynthesis,while auxin negatively regulates flavonoid biosynthesis.Subsequently,transcription factors from the MYB,bHLH,WRKY,NAC,and bZIP families are pivotal in regulating flavonoid biosynthesis.In addition,non-coding RNAs(microRNA and lncRNA)also participate in the regulation of flavonoids biosynthesis.MicroRNAs are generally believed to negatively regulate flavonoid metabolism in fruits,while lncRNAs have the opposite effect.Furthermore,the interactions between plant hormones,transcription factors,and non-coding RNAs in fruit flavonoid biosynthesis were analyzed.Ultimately,a foundational regulatory network for fruit flavonoid biosynthesis was hereby established.展开更多
The correlation between the Soil Moisture and Ocean Salinity(SMOS)L-band brightness temperature and thin sea ice thickness has been widely exploited using semi-empirical retrieval approaches based on a single-tie poin...The correlation between the Soil Moisture and Ocean Salinity(SMOS)L-band brightness temperature and thin sea ice thickness has been widely exploited using semi-empirical retrieval approaches based on a single-tie point(STP).However,due to pronounced spatial heterogeneity in seawater and sea ice properties across the Arctic,the use of an STP often leads to regionally biased.To address this limitation,this study proposes a multi-tie point(MTP)sea ice thickness retrieval method based on SMOS brightness temperature and sea ice concentration time series.Multiple seawater and sea ice tie-point values are identified through point-by-point time series analysis,quality control,and statistical hypothesis testing,allowing spatial variability in radiometric properties to be explicitly considered.The MTP-based retrieval is applied to Arctic freeze-up conditions.Validation against independent SMOS thin sea ice thickness products shows that the MTP approach yields significantly reduced bias and root mean square error compared with the conventional STP method,with statistically significant improvements confirmed by paired t-tests.While retrieval accuracy stabilizes beyond a certain number of tie points,the preprocessing cost associated with tie-point selection increases substantially.Considering both accuracy and efficiency,the MTP framework provides a practical and robust approach for large-scale Arctic thin sea ice thickness retrieval and enables improved characterization of regional freezing processes and maximum ice thickness.展开更多
Hepatocellular carcinoma(HCC)remains one of the most prevalent and lethal malignancies worldwide.Long non-coding RNAs(lncRNAs)have emerged as crucial regulators of gene expression and cancer progression,yet the functi...Hepatocellular carcinoma(HCC)remains one of the most prevalent and lethal malignancies worldwide.Long non-coding RNAs(lncRNAs)have emerged as crucial regulators of gene expression and cancer progression,yet the functional diversity of RP11-derived lncRNAs—originally mapped to bacterial artificial chromosome(BAC)clones from the Roswell Park Cancer Institute—has only recently begun to be appreciated.This mini-review aims to systematically synthesize current findings on RP11-derived lncRNAs in HCC,outlining their genomic origins,molecular mechanisms,and biological significance.We highlight their roles in metabolic reprogramming,microRNA network modulation,and tumor progression,as well as their diagnostic and prognostic value in tissue and serum-based analyses.Finally,we discuss therapeutic opportunities and propose future directions to translate RP11-derived lncRNAs into clinically actionable biomarkers and targets for precision liver cancer therapy.展开更多
The strong connection between braids and knots provides valuable insights into studying the topological state and phase classification of various physical systems.The phenomenon of non-Hermitian(NH)two-and three-band ...The strong connection between braids and knots provides valuable insights into studying the topological state and phase classification of various physical systems.The phenomenon of non-Hermitian(NH)two-and three-band braiding has received widespread attention.However,a systematic exploration and visualization of non-Abelian braiding and the associated knot transformations in four-band systems remains unexplored.Here,we propose a theoretical model of NH four-band braiding,provide its phase diagram,and establish its trivial,Abelian,and non-Abelian braiding rules.Additionally,we report on special knots,such as the Hopf and Solomon links in braided knots,and reveal that their transformations are accompanied by and mediated through exceptional points.Our work provides a detailed case for studying NH multiband braiding and knot structures in four-band systems,which could offer insights for topological photonics and analog information processing applications.展开更多
Evaluating rock mass quality using three-dimensional(3D)point clouds is crucial for discontinuity extraction and is widely applied in various industrial sectors.However,the utilization of this method in geological sur...Evaluating rock mass quality using three-dimensional(3D)point clouds is crucial for discontinuity extraction and is widely applied in various industrial sectors.However,the utilization of this method in geological surveys remains limited.Notable limitations of current research include the scarcity of validation using simple geometric shapes for discontinuity extraction methods,and the lack of studies that target both planar and linear discontinuity.To address these gaps,this study proposes a workflow for identifying discontinuity planes and traces in rock outcrops from photogrammetric 3D modeling,employing the Compass and Facets plugins in the open-source CloudCompare software.Prior to field application,the efficacy of the extraction methods was first evaluated using experimental datasets of a cube and an isosceles triangular prism generated under laboratory-controlled conditions.This validation demonstrated exceptional accuracy,with the dip and dip direction(DDD)of extracted structures consistently within±2°of the actual values.Following this rigorous laboratory validation,this methodology was applied to a more complex natural rock outcrop(Miocene–Pliocene deposits in Japan),demonstrating its applicability in realistic geological settings for identifying structures.The results showed that the dip and dip direction trends of the extracted bedding planes and faults were consistent with field measurements,achieving a time reduction of approximately 40%compared to traditional methods.In conclusion,through strictly controlled initial verification and subsequent successful application to a complex natural setting,this study confirmed that the proposed workflow can effectively and efficiently extract discontinuous geological structures from point clouds.展开更多
Automatic and accurate medical image segmentation remains a fundamental task in computer-aided diagnosis and treatment planning.Recent advances in foundation models,such as the medical-focused Segment AnythingModel(Me...Automatic and accurate medical image segmentation remains a fundamental task in computer-aided diagnosis and treatment planning.Recent advances in foundation models,such as the medical-focused Segment AnythingModel(MedSAM),have demonstrated strong performance but face challenges inmanymedical applications due to anatomical complexity and a limited domain-specific prompt.Thiswork introduces amethodology that enhances segmentation robustness and precision by automatically generating multiple informative point prompts,rather than relying on single inputs.The proposed approach randomly samples sets of spatially distributed point prompts based on image features,enabling MedSAM to better capture fine-grained anatomical structures and boundaries.During inference,probability maps are aggregated to reduce local misclassifications without additional model training.Extensive experiments on various computed tomography(CT)and magnetic resonance imaging(MRI)datasets demonstrate improvements in Dice Similarity Coefficient(DSC)and Normalized Surface Dice(NSD)metrics compared to baseline SAM and Scribble Prompt models.A semi-automatic point sampling version based on the ground truth segmentations yielded enhanced results,achieving up to 92.1%DSC and 86.6%NSD,with significant gains in delineating complex organs such as the pancreas,colon,kidney,and brain tumours.The main novelty of our method consists of effectively combining the results of multiple point prompts into the medical segmentation pipeline so that single-point prompt methods are outperformed.Overall,the proposed model offers a straightforward yet effective approach to improve medical image segmentation performance while maintaining computational efficiency.展开更多
Background:The medicinal material known as Os Draconis(Longgu)originates from fossilized remains of ancient mammals and is widely used in treating emotional and mental conditions.However,fossil resources are nonrenewa...Background:The medicinal material known as Os Draconis(Longgu)originates from fossilized remains of ancient mammals and is widely used in treating emotional and mental conditions.However,fossil resources are nonrenewable,and clinical demand is increasingly difficult to meet,leading to a proliferation of counterfeit products.During prolonged geological burial,static pressure from the surrounding strata severely compromises the microstructural integrity of osteons in Os Draconis,but Os Draconis still largely retains the structural features of mammalian bone.Methods:Using verified authentic Os Draconis samples over 10,000 years old as a baseline,this study summarizes the ultrastructural characteristics of genuine Os Draconis.Employing electron probe microanalysis and optical polarized light microscopy,we examined 28 batches of authentic Os Draconis and 31 batches of counterfeits to identify their ultrastructural differences.Key points for ultrastructural identification of Os Draconis were compiled,and a new identification approach was proposed based on these differences.Results:Authentic Os Draconis exhibited distinct ultrastructural markers:irregularly shaped osteons with traversing fissures,deformed/displaced Haversian canals,and secondary mineral infill(predominantly calcium carbonate).Counterfeits showed regular osteon arrangements,absent traversal fissures,and homogeneous hydroxyapatite composition.Lab-simulated samples lacked structural degradation features.EPMA confirmed calcium carbonate infill in fossilized Haversian canals,while elemental profiles differentiated lacunae types(void vs.mineral-packed).Conclusion:The study established ultrastructural criteria for authentic Os Draconis identification:osteon deformation,geological fissures penetrating bone units,and heterogenous mineral deposition.These features,unattainable in counterfeits or modern processed bones,provide a cost-effective,accurate identification method.This approach bridges gaps in TCM material standardization and supports quality control for clinical applications.展开更多
Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to priva...Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to privacy leaks.Federated learning provides an effective solution to data leakage by eliminating the need for data transmission,relying instead on the exchange of model parameters.However,the uneven distribution of client data can still affect the model’s ability to generalize effectively.To address these challenges,we propose a new framework for point cloud classification called Federated Dynamic Aggregation Selection Strategy-based Multi-Receptive Field Fusion Classification Framework(FDASS-MRFCF).Specifically,we tackle these challenges with two key innovations:(1)During the client local training phase,we propose a Multi-Receptive Field Fusion Classification Model(MRFCM),which captures local and global structures in point cloud data through dynamic convolution and multi-scale feature fusion,enhancing the robustness of point cloud classification.(2)In the server aggregation phase,we introduce a Federated Dynamic Aggregation Selection Strategy(FDASS),which employs a hybrid strategy to average client model parameters,skip aggregation,or reallocate local models to different clients,thereby balancing global consistency and local diversity.We evaluate our framework using the ModelNet40 and ShapeNetPart benchmarks,demonstrating its effectiveness.The proposed method is expected to significantly advance the field of point cloud classification in a secure environment.展开更多
文摘针对自动驾驶场景下,近处干扰点云误检率高、远处稀疏点云漏检率高的问题,提出了一种基于改进PointPillars的自动驾驶障碍物点云检测算法.首先,通过聚合模块和共享多层感知机(shared multi-layer perceptron,MLP)对柱体内点云进行特征编码,采用最大池化与平均池化叠加的方法将点云的显著特征与细节特征映射为柱体特征;其次,针对算法对伪图特征关注与利用不充分的问题,引入坐标注意力(coordinate attention,CA)机制和残差连接的伪图特征提取模块(attention and residual second block,ARSB),将深层与浅层特征图进行融合,优化算法梯度,增强算法对有效目标的关注度.试验结果表明:改进算法对全局点云检测精度较高,平均精度优于PointPillars、稀疏到稠密3D目标检测器(STD)等点云目标检测算法,在汽车类别上的检测精度优势明显,检测速度较快,符合实时性要求.
文摘Alzheimer's disease,a progressively degenerative neurological disorder,is the most common cause of dementia in the elderly.While its precise etiology remains unclear,researchers have identified diverse pathological characteristics and molecular pathways associated with its progression.Advances in scientific research have increasingly highlighted the crucial role of non-coding RNAs in the progression of Alzheimer's disease.These non-coding RNAs regulate several biological processes critical to the advancement of the disease,offering promising potential as therapeutic targets and diagnostic biomarkers.Therefore,this review aims to investigate the underlying mechanisms of Alzheimer's disease onset,with a particular focus on microRNAs,long non-coding RNAs,and circular RNAs associated with the disease.The review elucidates the potential pathogenic processes of Alzheimer's disease and provides a detailed description of the synthesis mechanisms of the three aforementioned non-coding RNAs.It comprehensively summarizes the various non-coding RNAs that have been identified to play key regulatory roles in Alzheimer's disease,as well as how these noncoding RNAs influence the disease's progression by regulating gene expression and protein functions.For example,miR-9 targets the UBE4B gene,promoting autophagy-mediated degradation of Tau protein,thereby reducing Tau accumulation and delaying Alzheimer's disease progression.Conversely,the long non-coding RNA BACE1-AS stabilizes BACE1 mRNA,promoting the generation of amyloid-βand accelerating Alzheimer's disease development.Additionally,circular RNAs play significant roles in regulating neuroinflammatory responses.By integrating insights from these regulatory mechanisms,there is potential to discover new therapeutic targets and potential biomarkers for early detection and management of Alzheimer's disease.This review aims to enhance the understanding of the relationship between Alzheimer's disease and non-coding RNAs,potentially paving the way for early detection and novel treatment strategies.
基金supported by the National Natural Science Foundation of China(Grant Nos.52304139,52325403)the CCTEG Coal Mining Research Institute funding(Grant No.KCYJY-2024-MS-10).
文摘3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with multi-scale targets,remains challenging.This paper proposes an enhanced segmentation method integrating improved PointNet++with a coverage-voted strategy.The coverage-voted strategy reduces data while preserving multi-scale target topology.The segmentation is achieved using an enhanced PointNet++algorithm with a normalization preprocessing head,resulting in a 94%accuracy for common supporting components.Ablation experiments show that the preprocessing head and coverage strategies increase segmentation accuracy by 20%and 2%,respectively,and improve Intersection over Union(IoU)for bearing plate segmentation by 58%and 20%.The accuracy of the current pretraining segmentation model may be affected by variations in surface support components,but it can be readily enhanced through re-optimization with additional labeled point cloud data.This proposed method,combined with a previously developed machine learning model that links rock bolt load and the deformation field of its bearing plate,provides a robust technique for simultaneously measuring the load of multiple rock bolts in a single laser scan.
基金Supported by the National Natural Science Foundation of China(No.82071571)the Natural Science Foundation of Guangdong Province(No.2021A1515010601)+3 种基金Guangdong Provincial Basic and Applied Basic Research Foundation-Dongguan Joint Fund(No.2024A1515140121)the“Climbing”Program of Guangdong Province(No.pdjh2021b0226)the Innovation and Entrepreneurship Program for College Students(No.GDMU2022038,202310571038,ZZDC002,S202510571041)Guangdong Medical University Undergraduate Innovation and Entrepreneurship Education Base Project(No.JDXM2024039,JDXM2025046)。
文摘Genomic destabilization and defective DNA repair are the most prominent features of tumour cells and are exploited by various chemotherapy drugs for cancer therapy.Long non-coding RNA(lncR-NAs)have emerged as powerful regulators of gene expression and are thus involved in diverse biological processes.Recent studies have demonstrated that several lncRNAs play critical roles in DNA repair.Nonetheless,the relationship between DNA damage-responsive lncRNAs and chemoresistance remains poorly defined.In this study,we established four different DNA damage models triggered by cisplatin(DDP),H2O2,neocarzinostatin(NCS)or ultraviolet(UV)irradiation and identified a specific upregu-lated lncRNA(lnc-DUSP6)involved in the cisplatin-induced DNA damage response.Furthermore,loss-or gain-of-function experiments confirmed that lnc-DUSP6 enhanced DNA repair and cell survival under cisplatin treatment,thus promoting cisplatin resistance.Mechanistically,an RNA immunoprecipitation(RIP)assay revealed that lnc-DUSP6 directly interacts with DUSP6(Dual Specificity Phosphatase 6),which is closely associated with cisplatin sensitivity.Additionally,overexpression of DUSP6 significantly rescued the effects of lnc-DUSP6 silencing on DNA repair and cell survival under cisplatin treatment.O-verall,our results show the effect and underlying mechanism of lnc-DUSP6 in cisplatin resistance:lnc-DUSP6 promotes cisplatin-induced DNA damage repair and cisplatin resistance by stabilizing DUSP6,which is highly clinically important for enhancing the efficacy of cisplatin for cancers.
基金Supported by The Joint Fund of Zhejiang Provincial Natural Science Foundation of China,No.LKLY25H160002.
文摘Gastric cancer(GC)has high morbidity and mortality worldwide.Due to the absence of noticeable symptoms,diagnosing GC at an early stage is very difficult,which consequently leads to advanced GC and poor prognosis.Effective biomarkers are essential for prolonging patients’survival.Helicobacter pylori(H.pylori)infection represents the most significant risk factor for GC,with nearly all cases linked to this infection.Many non-coding RNAs(ncRNAs)are dysregulated in H.pylori-infected GC,indicating that ncRNAs may serve as biomarkers of early-stage GC.In this editorial,we discuss the study by Chen et al.Although previous studies have identified roles for miR-136 in gastric cancer proliferation,apoptosis,and invasion,none have specifically explored its relationship with H.pylori-associated gastric carcinogenesis.
基金supported by the National Natural Science Foundation of China,Nos.82171347,82371362the Natural Science Foundation of Hunan Province,No.2022JJ30971the Scientific Research Project of Hunan Provincial Health Commission of China,No.202204040024(all to GX).
文摘A large body of evidence has highlighted the role of non-coding RNAs in neurodevelopment and neuroinflammation.This evidence has led to increasing speculation that non-coding RNAs may be involved in the pathophysiological mechanisms underlying hydrocephalus,one of the most common neurological conditions worldwide.In this review,we first outline the basic concepts and incidence of hydrocephalus along with the limitations of existing treatments for this condition.Then,we outline the definition,classification,and biological role of non-coding RNAs.Subsequently,we analyze the roles of non-coding RNAs in the formation of hydrocephalus in detail.Specifically,we have focused on the potential significance of non-coding RNAs in the pathophysiology of hydrocephalus,including glymphatic pathways,neuroinflammatory processes,and neurological dysplasia,on the basis of the existing evidence.Lastly,we review the potential of non-coding RNAs as biomarkers of hydrocephalus and for the creation of innovative treatments.
基金supported by the Excellent Young Scientists Fund(Category B)(32422063)the National Key Research and Development Program of China(2022YFF1003500)the Zhengzhou University Qiushi Postdoctoral Research Funding Program.For open access,the authors have applied for a Creative Commons Attribution(CC BY)license for any Author Accepted Manuscript version arising from this submission.
文摘Anther is a key male reproductive organ that is essential for the plant life cycle,from the sporophyte to the gametophyte generation.To explore the isoform-level transcriptional landscape of developing anthers in maize(Zea mays L.),we analyzed Iso-Seq data from anthers collected at 10 developmental stages,together with strand-specific RNA-seq,CAGE-seq,and PAS-seq data.Of the 152,026 high-confidence full-length isoforms identified,68.8%have not been described;these include 22,365 isoforms that originate from previously unannotated loci and 82,167 novel isoforms that originate from annotated protein-coding genes.Using our newly developed strategy to detect dynamic expression patterns of isoforms,we identify 13,899 differentially variable regions(DVRs);surprisingly,1275 genes contain more than two DVRs,revealing highly efficient utilization of limited genic regions.We identify 7876 long non-coding RNAs(lncRNAs)from 4098 loci,most of which were preferentially expressed during cell differentiation and meiosis.We also detected 371 long-range interactions involving intergenic lncRNAs(lincRNAs);interestingly,243 were lincRNA-gene ones,and the interacting genes were highly expressed in anthers,suggesting that many potential lncRNA regulators of key genes are required for anther development.This study provides valuable resources and fundamental information for studying the essential transcripts of key genes during anther development.
基金supported by the China Agricultural Research System(Grant No.CARS-09)the Central Government Guiding Local Science and Technology Development Project(Grant No.YDZX2023029)the Gansu Planning Projects on Science and Technology(Grant No.23CXNJ0013).
文摘Flavonoids,abundant in the fruits,are pivotal to their growth,development,and storage.In addition,they have significant beneficial effects on human health.Consequently,research is increasingly concentrating on the regulatory mechanisms governing flavonoid biosynthesis in fruits.Phytohormones are involved in the regulation of flavonoid biosynthesis.The abscisic acid,ethylene,jasmonic acid,cytokinins,and brassinosteroids promote flavonoid biosynthesis,while auxin negatively regulates flavonoid biosynthesis.Subsequently,transcription factors from the MYB,bHLH,WRKY,NAC,and bZIP families are pivotal in regulating flavonoid biosynthesis.In addition,non-coding RNAs(microRNA and lncRNA)also participate in the regulation of flavonoids biosynthesis.MicroRNAs are generally believed to negatively regulate flavonoid metabolism in fruits,while lncRNAs have the opposite effect.Furthermore,the interactions between plant hormones,transcription factors,and non-coding RNAs in fruit flavonoid biosynthesis were analyzed.Ultimately,a foundational regulatory network for fruit flavonoid biosynthesis was hereby established.
基金supported by the National Key Research and Development Program of China(Grant nos.2023YFC2809103,2024YFC2813505)the Fundamental Research Funds for the Central Universities(Grant nos.2042025kf0083,2042025gf0014)the Antarctic Zhongshan Ice and Space Environment National Observation and Research Station(Grant no.ZSNORS-20252702).
文摘The correlation between the Soil Moisture and Ocean Salinity(SMOS)L-band brightness temperature and thin sea ice thickness has been widely exploited using semi-empirical retrieval approaches based on a single-tie point(STP).However,due to pronounced spatial heterogeneity in seawater and sea ice properties across the Arctic,the use of an STP often leads to regionally biased.To address this limitation,this study proposes a multi-tie point(MTP)sea ice thickness retrieval method based on SMOS brightness temperature and sea ice concentration time series.Multiple seawater and sea ice tie-point values are identified through point-by-point time series analysis,quality control,and statistical hypothesis testing,allowing spatial variability in radiometric properties to be explicitly considered.The MTP-based retrieval is applied to Arctic freeze-up conditions.Validation against independent SMOS thin sea ice thickness products shows that the MTP approach yields significantly reduced bias and root mean square error compared with the conventional STP method,with statistically significant improvements confirmed by paired t-tests.While retrieval accuracy stabilizes beyond a certain number of tie points,the preprocessing cost associated with tie-point selection increases substantially.Considering both accuracy and efficiency,the MTP framework provides a practical and robust approach for large-scale Arctic thin sea ice thickness retrieval and enables improved characterization of regional freezing processes and maximum ice thickness.
基金supported by the National Research Foundation of Korea(NRF),funded by the Ministry of Science and ICT(MSIT),Republic of Korea(grant numbers:RS-2022-NR070489 and RS-2023-00210847)the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI),funded by the Ministry of Health and Welfare,Republic of Korea(grant number HR21C1003).
文摘Hepatocellular carcinoma(HCC)remains one of the most prevalent and lethal malignancies worldwide.Long non-coding RNAs(lncRNAs)have emerged as crucial regulators of gene expression and cancer progression,yet the functional diversity of RP11-derived lncRNAs—originally mapped to bacterial artificial chromosome(BAC)clones from the Roswell Park Cancer Institute—has only recently begun to be appreciated.This mini-review aims to systematically synthesize current findings on RP11-derived lncRNAs in HCC,outlining their genomic origins,molecular mechanisms,and biological significance.We highlight their roles in metabolic reprogramming,microRNA network modulation,and tumor progression,as well as their diagnostic and prognostic value in tissue and serum-based analyses.Finally,we discuss therapeutic opportunities and propose future directions to translate RP11-derived lncRNAs into clinically actionable biomarkers and targets for precision liver cancer therapy.
基金supported by the National Natural Science Foundation of China(Grant Nos.62575099,62075059,61405058)Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515011353)+2 种基金Open Project of the State Key Laboratory of Advanced Optical Communication Systems and Networks of China(Grant No.2024GZKF20)the Natural Science Foundation of Hunan Province(Grant Nos.2020JJ4161 and 2017JJ2048)Scientific Research Foundation of Hunan Provincial Education Department(Grant No.21A0013)。
文摘The strong connection between braids and knots provides valuable insights into studying the topological state and phase classification of various physical systems.The phenomenon of non-Hermitian(NH)two-and three-band braiding has received widespread attention.However,a systematic exploration and visualization of non-Abelian braiding and the associated knot transformations in four-band systems remains unexplored.Here,we propose a theoretical model of NH four-band braiding,provide its phase diagram,and establish its trivial,Abelian,and non-Abelian braiding rules.Additionally,we report on special knots,such as the Hopf and Solomon links in braided knots,and reveal that their transformations are accompanied by and mediated through exceptional points.Our work provides a detailed case for studying NH multiband braiding and knot structures in four-band systems,which could offer insights for topological photonics and analog information processing applications.
文摘Evaluating rock mass quality using three-dimensional(3D)point clouds is crucial for discontinuity extraction and is widely applied in various industrial sectors.However,the utilization of this method in geological surveys remains limited.Notable limitations of current research include the scarcity of validation using simple geometric shapes for discontinuity extraction methods,and the lack of studies that target both planar and linear discontinuity.To address these gaps,this study proposes a workflow for identifying discontinuity planes and traces in rock outcrops from photogrammetric 3D modeling,employing the Compass and Facets plugins in the open-source CloudCompare software.Prior to field application,the efficacy of the extraction methods was first evaluated using experimental datasets of a cube and an isosceles triangular prism generated under laboratory-controlled conditions.This validation demonstrated exceptional accuracy,with the dip and dip direction(DDD)of extracted structures consistently within±2°of the actual values.Following this rigorous laboratory validation,this methodology was applied to a more complex natural rock outcrop(Miocene–Pliocene deposits in Japan),demonstrating its applicability in realistic geological settings for identifying structures.The results showed that the dip and dip direction trends of the extracted bedding planes and faults were consistent with field measurements,achieving a time reduction of approximately 40%compared to traditional methods.In conclusion,through strictly controlled initial verification and subsequent successful application to a complex natural setting,this study confirmed that the proposed workflow can effectively and efficiently extract discontinuous geological structures from point clouds.
基金supported by the Autonomous Government of Andalusia(Spain)under project UMA20-FEDERJA-108also by the Ministry of Science and Innovation of Spain,grant number PID2022-136764OA-I00+1 种基金It includes funds fromthe European Regional Development Fund(ERDF),It is also partially supported by the Fundación Unicaja(PUNI-003_2023)the Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina-IBIMA Plataforma BIONAND(ATECH-25-02).
文摘Automatic and accurate medical image segmentation remains a fundamental task in computer-aided diagnosis and treatment planning.Recent advances in foundation models,such as the medical-focused Segment AnythingModel(MedSAM),have demonstrated strong performance but face challenges inmanymedical applications due to anatomical complexity and a limited domain-specific prompt.Thiswork introduces amethodology that enhances segmentation robustness and precision by automatically generating multiple informative point prompts,rather than relying on single inputs.The proposed approach randomly samples sets of spatially distributed point prompts based on image features,enabling MedSAM to better capture fine-grained anatomical structures and boundaries.During inference,probability maps are aggregated to reduce local misclassifications without additional model training.Extensive experiments on various computed tomography(CT)and magnetic resonance imaging(MRI)datasets demonstrate improvements in Dice Similarity Coefficient(DSC)and Normalized Surface Dice(NSD)metrics compared to baseline SAM and Scribble Prompt models.A semi-automatic point sampling version based on the ground truth segmentations yielded enhanced results,achieving up to 92.1%DSC and 86.6%NSD,with significant gains in delineating complex organs such as the pancreas,colon,kidney,and brain tumours.The main novelty of our method consists of effectively combining the results of multiple point prompts into the medical segmentation pipeline so that single-point prompt methods are outperformed.Overall,the proposed model offers a straightforward yet effective approach to improve medical image segmentation performance while maintaining computational efficiency.
基金supported by the Scientific and Technological Innovation Project of the China Academy of Chinese Medical Sciences(CI2021A04013)the National Natural Science Foundation of China(82204610)+1 种基金the Qihang Talent Program(L2022046)the Fundamental Research Funds for the Central Public Welfare Research Institutes(ZZ15-YQ-041 and L2021029).
文摘Background:The medicinal material known as Os Draconis(Longgu)originates from fossilized remains of ancient mammals and is widely used in treating emotional and mental conditions.However,fossil resources are nonrenewable,and clinical demand is increasingly difficult to meet,leading to a proliferation of counterfeit products.During prolonged geological burial,static pressure from the surrounding strata severely compromises the microstructural integrity of osteons in Os Draconis,but Os Draconis still largely retains the structural features of mammalian bone.Methods:Using verified authentic Os Draconis samples over 10,000 years old as a baseline,this study summarizes the ultrastructural characteristics of genuine Os Draconis.Employing electron probe microanalysis and optical polarized light microscopy,we examined 28 batches of authentic Os Draconis and 31 batches of counterfeits to identify their ultrastructural differences.Key points for ultrastructural identification of Os Draconis were compiled,and a new identification approach was proposed based on these differences.Results:Authentic Os Draconis exhibited distinct ultrastructural markers:irregularly shaped osteons with traversing fissures,deformed/displaced Haversian canals,and secondary mineral infill(predominantly calcium carbonate).Counterfeits showed regular osteon arrangements,absent traversal fissures,and homogeneous hydroxyapatite composition.Lab-simulated samples lacked structural degradation features.EPMA confirmed calcium carbonate infill in fossilized Haversian canals,while elemental profiles differentiated lacunae types(void vs.mineral-packed).Conclusion:The study established ultrastructural criteria for authentic Os Draconis identification:osteon deformation,geological fissures penetrating bone units,and heterogenous mineral deposition.These features,unattainable in counterfeits or modern processed bones,provide a cost-effective,accurate identification method.This approach bridges gaps in TCM material standardization and supports quality control for clinical applications.
基金supported in part by the National Key Research and Development Program of Chinaunder(Grant 2021YFB3101100)in part by the National Natural Science Foundation of Chinaunder(Grant 42461057),(Grant 62272123),and(Grant 42371470)+1 种基金in part by the Fundamental Research Program of Shanxi Province under(Grant 202303021212164)in part by the Postgraduate Education Innovation Program of Shanxi Province under(Grant 2024KY474).
文摘Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to privacy leaks.Federated learning provides an effective solution to data leakage by eliminating the need for data transmission,relying instead on the exchange of model parameters.However,the uneven distribution of client data can still affect the model’s ability to generalize effectively.To address these challenges,we propose a new framework for point cloud classification called Federated Dynamic Aggregation Selection Strategy-based Multi-Receptive Field Fusion Classification Framework(FDASS-MRFCF).Specifically,we tackle these challenges with two key innovations:(1)During the client local training phase,we propose a Multi-Receptive Field Fusion Classification Model(MRFCM),which captures local and global structures in point cloud data through dynamic convolution and multi-scale feature fusion,enhancing the robustness of point cloud classification.(2)In the server aggregation phase,we introduce a Federated Dynamic Aggregation Selection Strategy(FDASS),which employs a hybrid strategy to average client model parameters,skip aggregation,or reallocate local models to different clients,thereby balancing global consistency and local diversity.We evaluate our framework using the ModelNet40 and ShapeNetPart benchmarks,demonstrating its effectiveness.The proposed method is expected to significantly advance the field of point cloud classification in a secure environment.
