In dentistry, panoramic X-ray images are extensively used by dentists for tooth structure analysis and disease diagnosis. However, the manual analysis of these images is time-consuming and prone to misdiagnosis or ove...In dentistry, panoramic X-ray images are extensively used by dentists for tooth structure analysis and disease diagnosis. However, the manual analysis of these images is time-consuming and prone to misdiagnosis or overlooked. While deep learning techniques have been employed to segment teeth in panoramic X-ray images, accurate segmentation of individual teeth remains an underexplored area. In this study, we propose an end-to-end deep learning method that effectively addresses this challenge by employing an improved combinatorial loss function to separate the boundaries of adjacent teeth, enabling precise segmentation of individual teeth in panoramic X-ray images. We validate the feasibility of our approach using a challenging dataset. By training our segmentation network on 115 panoramic X-ray images, we achieve an intersection over union (IoU) of 86.56% for tooth segmentation and an accuracy of 65.52% in tooth counting on 87 test set images. Experimental results demonstrate the significant improvement of our proposed method in single tooth segmentation compared to existing methods.展开更多
Jasmine(Jasminum sambac Aiton)is a well-known cultivated plant species for its fragrant flowers used in the perfume industry and cosmetics.However,the genetic basis of its floral scent is largely unknown.In this study...Jasmine(Jasminum sambac Aiton)is a well-known cultivated plant species for its fragrant flowers used in the perfume industry and cosmetics.However,the genetic basis of its floral scent is largely unknown.In this study,using PacBio,Illumina,10×Genomics and highthroughput chromosome conformation capture(Hi-C)sequencing technologies,a high-quality chromosome-level reference genome for J.sambac was obtained,exploiting a double-petal phenotype cultivar‘Shuangbanmoli’(JSSB).The results showed that the final assembled genome of JSSB is 580.33 Mb in size(contig N50=1.05 Mb;scaffold N50=45.07 Mb)with a total of 39618 predicted protein-coding genes.Our analyses revealed that the JSSB genome has undergone an ancient whole-genome duplication(WGD)event at 91.68 million years ago(Mya).It was estimated that J.sambac diverged from the lineage leading to Olea europaea and Osmanthus fragrans about 28.8 Mya.On the basis of a combination of genomic,transcriptomic and metabolomic analyses,a range of floral scent volatiles and genes were identified involved in the benzenoid/phenylpropanoid and terpenoid biosynthesis pathways.The results provide new insights into the molecular mechanism of its fragrance biosynthesis in jasmine.展开更多
BACKGROUND:Sepsis-related acute respiratory distress syndrome(ARDS)has a high mortality rate,and no effective treatment is available currently.Quercetin is a natural plant product with many pharmacological activities,...BACKGROUND:Sepsis-related acute respiratory distress syndrome(ARDS)has a high mortality rate,and no effective treatment is available currently.Quercetin is a natural plant product with many pharmacological activities,such as antioxidative,anti-apoptotic,and anti-inflammatory effects.This study aimed to elucidate the protective mechanism of quercetin against sepsis-related ARDS.METHODS:In this study,network pharmacology and in vitro experiments were used to investigate the underlying mechanisms of quercetin against sepsis-related ARDS.Core targets and signaling pathways of quercetin against sepsis-related ARDS were screened and were verified by in vitro experiments.RESULTS:A total of 4,230 targets of quercetin,360 disease targets of sepsis-related ARDS,and 211 intersection targets were obtained via database screening.Among the 211 intersection targets,interleukin-6(IL-6),tumor necrosis factor(TNF),albumin(ALB),AKT serine/threonine kinase 1(AKT1),and interleukin-1β(IL-1β)were identified as the core targets.A Gene Ontology(GO)enrichment analysis revealed 894 genes involved in the inflammatory response,apoptosis regulation,and response to hypoxia.Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis identified 106 pathways.After eliminating and generalizing,the hypoxia-inducible factor-1(HIF-1),TNF,nuclear factor-κB(NF-κB),and nucleotide-binding and oligomerization domain(NOD)-like receptor signaling pathways were identified.Molecular docking revealed that quercetin had good binding activity with the core targets.Moreover,quercetin blocked the HIF-1,TNF,NF-κB,and NODlike receptor signaling pathways in lipopolysaccharide(LPS)-induced murine alveolar macrophage(MH-S)cells.It also suppressed the inflammatory response,oxidative reactions,and cell apoptosis.CONCLUSION:Quercetin ameliorates sepsis-related ARDS by binding to its core targets and blocking the HIF-1,TNF,NF-κB,and NOD-like receptor signaling pathways to reduce inflammation,cell apoptosis,and oxidative stress.展开更多
Perovskite solar cells(PSCs) have stood out from many photovoltaic technologies due to their flexibility,cost-effectiveness and high-power conversion efficiency(PCE). Nevertheless, the further development of PSCs is g...Perovskite solar cells(PSCs) have stood out from many photovoltaic technologies due to their flexibility,cost-effectiveness and high-power conversion efficiency(PCE). Nevertheless, the further development of PSCs is greatly hindered by the trap-induced non-radiative recombination losses and poor long-term work stability. In the past decade, the huge advancements have been obtained on suppressing nonradiative recombination and enhancing device durability. Among them, the multisite ligands(MSLs) engineering plays a crucial role in precise control and directional modification of functional layers and interfaces,which contributes to markedly increased PCE and lifetimes of PSCs. In view of this, this review summarizes the advances of MSLs in PSCs. From the perspective of functional groups and chemical interaction,the modulation mechanisms of properties of different functional layers and interfaces and device performance via various MSLs are deeply investigated and revealed. Finally, the prospects for the application and development direction of MSLs in PSCs are legitimately proposed.展开更多
Chemotherapy-induced cachexia(CIC)is a debilitating condition characterized by weight loss,muscle atrophy,and anorexia[1].While peripheral mechanisms of cachexia have been extensively studied,the involvement of the ce...Chemotherapy-induced cachexia(CIC)is a debilitating condition characterized by weight loss,muscle atrophy,and anorexia[1].While peripheral mechanisms of cachexia have been extensively studied,the involvement of the central nervous system(CNS)in CIC is often overlooked.Chemotherapeutic drugs cause stress responses and inflammation,which may impact the hypothalamus and disrupt systemic energy and neuroendocrine functions.Understanding hypothalamic roles in regulating these processes can provide insights into CIC's mechanisms and aid in developing novel therapies.展开更多
Lung cancer is one of the greatest threats to human health. It is a very effective way to detect lung cancer by pathological pictures of lung cancer cells. Therefore, improving the accuracy and stability of diagnosis ...Lung cancer is one of the greatest threats to human health. It is a very effective way to detect lung cancer by pathological pictures of lung cancer cells. Therefore, improving the accuracy and stability of diagnosis is very important. In this study, we develop an automatic detection scheme for lung cancer cells based on convolutional neural networks and Swin Transformer. Microscopic images of patients’ lung cells are first segmented using a Mask R-CNN-based network, resulting in a separate image for each cell. Part of the background information is preserved by Gaussian blurring of surrounding cells, while the target cells are highlighted. The classification model based on Swin Transformer not only reduces the computation but also achieves better results than the classical CNN model, ResNet50. The final results show that the accuracy of the method proposed in this paper reaches 96.16%. Therefore, this method is helpful for the detection and classification of lung cancer cells.展开更多
文摘In dentistry, panoramic X-ray images are extensively used by dentists for tooth structure analysis and disease diagnosis. However, the manual analysis of these images is time-consuming and prone to misdiagnosis or overlooked. While deep learning techniques have been employed to segment teeth in panoramic X-ray images, accurate segmentation of individual teeth remains an underexplored area. In this study, we propose an end-to-end deep learning method that effectively addresses this challenge by employing an improved combinatorial loss function to separate the boundaries of adjacent teeth, enabling precise segmentation of individual teeth in panoramic X-ray images. We validate the feasibility of our approach using a challenging dataset. By training our segmentation network on 115 panoramic X-ray images, we achieve an intersection over union (IoU) of 86.56% for tooth segmentation and an accuracy of 65.52% in tooth counting on 87 test set images. Experimental results demonstrate the significant improvement of our proposed method in single tooth segmentation compared to existing methods.
基金financially supported by the National Natural Science Foundation of China(Grant No.31772338)the Basic Scientific Research Business Special Project of Jiangsu Academy of Agricultural Sciences(Grant No.0090756100ZX)。
文摘Jasmine(Jasminum sambac Aiton)is a well-known cultivated plant species for its fragrant flowers used in the perfume industry and cosmetics.However,the genetic basis of its floral scent is largely unknown.In this study,using PacBio,Illumina,10×Genomics and highthroughput chromosome conformation capture(Hi-C)sequencing technologies,a high-quality chromosome-level reference genome for J.sambac was obtained,exploiting a double-petal phenotype cultivar‘Shuangbanmoli’(JSSB).The results showed that the final assembled genome of JSSB is 580.33 Mb in size(contig N50=1.05 Mb;scaffold N50=45.07 Mb)with a total of 39618 predicted protein-coding genes.Our analyses revealed that the JSSB genome has undergone an ancient whole-genome duplication(WGD)event at 91.68 million years ago(Mya).It was estimated that J.sambac diverged from the lineage leading to Olea europaea and Osmanthus fragrans about 28.8 Mya.On the basis of a combination of genomic,transcriptomic and metabolomic analyses,a range of floral scent volatiles and genes were identified involved in the benzenoid/phenylpropanoid and terpenoid biosynthesis pathways.The results provide new insights into the molecular mechanism of its fragrance biosynthesis in jasmine.
基金supported by the National Natural Science Foundation of China(82172182 and 82102311)Natural Science Foundation of Jiangsu Province(BK20211136)+2 种基金China Postdoctoral Science Foundation(2018M643890 and 2020M683718)Xuzhou Science and Technology Project(KC21215 and KC22136)Development Fund Project of Affiliated Hospital of Xuzhou Medical University(XYFY202232)。
文摘BACKGROUND:Sepsis-related acute respiratory distress syndrome(ARDS)has a high mortality rate,and no effective treatment is available currently.Quercetin is a natural plant product with many pharmacological activities,such as antioxidative,anti-apoptotic,and anti-inflammatory effects.This study aimed to elucidate the protective mechanism of quercetin against sepsis-related ARDS.METHODS:In this study,network pharmacology and in vitro experiments were used to investigate the underlying mechanisms of quercetin against sepsis-related ARDS.Core targets and signaling pathways of quercetin against sepsis-related ARDS were screened and were verified by in vitro experiments.RESULTS:A total of 4,230 targets of quercetin,360 disease targets of sepsis-related ARDS,and 211 intersection targets were obtained via database screening.Among the 211 intersection targets,interleukin-6(IL-6),tumor necrosis factor(TNF),albumin(ALB),AKT serine/threonine kinase 1(AKT1),and interleukin-1β(IL-1β)were identified as the core targets.A Gene Ontology(GO)enrichment analysis revealed 894 genes involved in the inflammatory response,apoptosis regulation,and response to hypoxia.Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis identified 106 pathways.After eliminating and generalizing,the hypoxia-inducible factor-1(HIF-1),TNF,nuclear factor-κB(NF-κB),and nucleotide-binding and oligomerization domain(NOD)-like receptor signaling pathways were identified.Molecular docking revealed that quercetin had good binding activity with the core targets.Moreover,quercetin blocked the HIF-1,TNF,NF-κB,and NODlike receptor signaling pathways in lipopolysaccharide(LPS)-induced murine alveolar macrophage(MH-S)cells.It also suppressed the inflammatory response,oxidative reactions,and cell apoptosis.CONCLUSION:Quercetin ameliorates sepsis-related ARDS by binding to its core targets and blocking the HIF-1,TNF,NF-κB,and NOD-like receptor signaling pathways to reduce inflammation,cell apoptosis,and oxidative stress.
基金financially supported by the National Natural Science Foundation of China (62274018)the Xinjiang Construction Corps Key Areas of Science and Technology Research Project (2023AB029)the Key Project of Chongqing Overseas Students Returning to China Entrepreneurship and Innovation Support Plan (cx2023006)。
文摘Perovskite solar cells(PSCs) have stood out from many photovoltaic technologies due to their flexibility,cost-effectiveness and high-power conversion efficiency(PCE). Nevertheless, the further development of PSCs is greatly hindered by the trap-induced non-radiative recombination losses and poor long-term work stability. In the past decade, the huge advancements have been obtained on suppressing nonradiative recombination and enhancing device durability. Among them, the multisite ligands(MSLs) engineering plays a crucial role in precise control and directional modification of functional layers and interfaces,which contributes to markedly increased PCE and lifetimes of PSCs. In view of this, this review summarizes the advances of MSLs in PSCs. From the perspective of functional groups and chemical interaction,the modulation mechanisms of properties of different functional layers and interfaces and device performance via various MSLs are deeply investigated and revealed. Finally, the prospects for the application and development direction of MSLs in PSCs are legitimately proposed.
基金the National Key Research and Development Program of China(Grant No.:2022YFC3501700)the Key-Area Research and Development Program of Guangdong Province,China(Grant No.:2020B1111110001)the Youth Program of the National Natural Science Foundation of China(Grant No.:82003939).
文摘Chemotherapy-induced cachexia(CIC)is a debilitating condition characterized by weight loss,muscle atrophy,and anorexia[1].While peripheral mechanisms of cachexia have been extensively studied,the involvement of the central nervous system(CNS)in CIC is often overlooked.Chemotherapeutic drugs cause stress responses and inflammation,which may impact the hypothalamus and disrupt systemic energy and neuroendocrine functions.Understanding hypothalamic roles in regulating these processes can provide insights into CIC's mechanisms and aid in developing novel therapies.
文摘Lung cancer is one of the greatest threats to human health. It is a very effective way to detect lung cancer by pathological pictures of lung cancer cells. Therefore, improving the accuracy and stability of diagnosis is very important. In this study, we develop an automatic detection scheme for lung cancer cells based on convolutional neural networks and Swin Transformer. Microscopic images of patients’ lung cells are first segmented using a Mask R-CNN-based network, resulting in a separate image for each cell. Part of the background information is preserved by Gaussian blurring of surrounding cells, while the target cells are highlighted. The classification model based on Swin Transformer not only reduces the computation but also achieves better results than the classical CNN model, ResNet50. The final results show that the accuracy of the method proposed in this paper reaches 96.16%. Therefore, this method is helpful for the detection and classification of lung cancer cells.
