Objective:To investigate the effect of the ethanolic extract of Rosa laevigata Michx.fruit on rats with mesangial proliferative glomerulonephritis based on the NLRP3 inflammasome pathway.Methods:Thirty Wistar rats wer...Objective:To investigate the effect of the ethanolic extract of Rosa laevigata Michx.fruit on rats with mesangial proliferative glomerulonephritis based on the NLRP3 inflammasome pathway.Methods:Thirty Wistar rats were divided into three groups,a blank control group,a diabetic nephropathy(DN)model group,and an ethanolic extract intervention group,according to the random number table method,with 10 rats in each group.One day before the experiment,basic feeding was initiated for all the rats;the changes in activity and weight of each group of rats were observed and recorded after 7 d,and a rat model of renal function injury was established after 1 d.Results:Compared with the control group,the model group had significantly higher kidney/body ratio,24 h urine protein,serum creatinine(SCr),blood urea nitrogen(BUN),glomerular mesangial cell(GMC)count,and extracellular matrix(ECM)positive area ratio(P<0.05);the same indicators were significantly lower in the intervention group than in the model group(P<0.05).The NLRP3 inflammasome pathway in renal intrinsic cells was activated in the intervention group.The overactivation of NLRP3 inflammasome is known to promote interleukin(IL)-1βrelease,which was inhibited in the intervention group.Conclusion:The ethanolic extract of Rosa laevigata Michx.fruit has a protective effect on renal intrinsic cells and may be related to NLRP3 inflammasome pathway,suggesting that the fruit of Rosa laevigata Michx.has a potential role in protecting renal intrinsic cells from inflammatory damage.NLRP3 inflammasomes are involved in the development of various chronic inflammatory diseases,such as acute and chronic glomerulonephritis and renal fibrosis.展开更多
Coconut(Cocos nucifera L.),a major oil and fruit crop of the Arecaceae family,is extensively cultivated across the Asia—Pacific region.Despite its agricultural importance,genome assembly in coconut remains challengin...Coconut(Cocos nucifera L.),a major oil and fruit crop of the Arecaceae family,is extensively cultivated across the Asia—Pacific region.Despite its agricultural importance,genome assembly in coconut remains challenging due to its large genome size and high proportion of repetitive sequences.Allele-specific expression(ASE)plays a key role in regulating plant development and evolution,yet research on ASE in coconut is limited(Shao et al.,2019;Li et al.,2021;Zhang et al.,2021;Hu et al.,2022).Among phenotypic traits,fruit color is especially important as an indicator of maturity,guiding harvest timing and post-harvest processes(Kapoor et al.,2022).While prior studies have explored various coconut traits such as salt tolerance,fiber content,and plant height(Wang et al.,2021;Yang et al.,2021),investigations into ASE and fruit color remain scarce.展开更多
In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in...In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.展开更多
基金This work was supported by the Health Commission of Hebei Province under the project Chuanxiong Extract Improves Inflammatory Response in Rats with Pyelonephritis Through IL-6/STAT3 Signaling Pathway(Project Number:20231486).
文摘Objective:To investigate the effect of the ethanolic extract of Rosa laevigata Michx.fruit on rats with mesangial proliferative glomerulonephritis based on the NLRP3 inflammasome pathway.Methods:Thirty Wistar rats were divided into three groups,a blank control group,a diabetic nephropathy(DN)model group,and an ethanolic extract intervention group,according to the random number table method,with 10 rats in each group.One day before the experiment,basic feeding was initiated for all the rats;the changes in activity and weight of each group of rats were observed and recorded after 7 d,and a rat model of renal function injury was established after 1 d.Results:Compared with the control group,the model group had significantly higher kidney/body ratio,24 h urine protein,serum creatinine(SCr),blood urea nitrogen(BUN),glomerular mesangial cell(GMC)count,and extracellular matrix(ECM)positive area ratio(P<0.05);the same indicators were significantly lower in the intervention group than in the model group(P<0.05).The NLRP3 inflammasome pathway in renal intrinsic cells was activated in the intervention group.The overactivation of NLRP3 inflammasome is known to promote interleukin(IL)-1βrelease,which was inhibited in the intervention group.Conclusion:The ethanolic extract of Rosa laevigata Michx.fruit has a protective effect on renal intrinsic cells and may be related to NLRP3 inflammasome pathway,suggesting that the fruit of Rosa laevigata Michx.has a potential role in protecting renal intrinsic cells from inflammatory damage.NLRP3 inflammasomes are involved in the development of various chronic inflammatory diseases,such as acute and chronic glomerulonephritis and renal fibrosis.
基金supported by Central Public-interest Scientific Institution Basal Research Fund(CATAS-Nos.1630152023007,1630152023011,1630152023012,1630152023013)the National Natural Science Foundation of China(Grant No.32071805).
文摘Coconut(Cocos nucifera L.),a major oil and fruit crop of the Arecaceae family,is extensively cultivated across the Asia—Pacific region.Despite its agricultural importance,genome assembly in coconut remains challenging due to its large genome size and high proportion of repetitive sequences.Allele-specific expression(ASE)plays a key role in regulating plant development and evolution,yet research on ASE in coconut is limited(Shao et al.,2019;Li et al.,2021;Zhang et al.,2021;Hu et al.,2022).Among phenotypic traits,fruit color is especially important as an indicator of maturity,guiding harvest timing and post-harvest processes(Kapoor et al.,2022).While prior studies have explored various coconut traits such as salt tolerance,fiber content,and plant height(Wang et al.,2021;Yang et al.,2021),investigations into ASE and fruit color remain scarce.
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia,Grant No.KFU250098.
文摘In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.
