Neurological disorders including neurodegenerative diseases,brain tumors,and stroke are the second leading cause of death and the greatest cause of disability worldwide.However,it remains challenging to achieve effect...Neurological disorders including neurodegenerative diseases,brain tumors,and stroke are the second leading cause of death and the greatest cause of disability worldwide.However,it remains challenging to achieve effective drug delivery to the central nervous system for treatments of neurological diseases due to the blood-brain barrier(BBB).The function of the BBB is regulated by the physiological interactions between various types of cells in the neurovascular unit(NVU).In the NVU,the brain vasculature of the BBB is surrounded by brain pericytes,brain astrocytes,neurons,and microglia(Figure 1).Moreover,the NVU at the levels of arteries and veins includes contractile smooth muscle cells(Schaeffer and Iadecola,2021).展开更多
Reducing the use of animal models in drug development and safety assessment has long been supported by the U.S.Food and Drug Administration(FDA).The report by Royal Society for the Prevention of Cruelty to Animals ind...Reducing the use of animal models in drug development and safety assessment has long been supported by the U.S.Food and Drug Administration(FDA).The report by Royal Society for the Prevention of Cruelty to Animals indicates that in 2020,experiments involved the use of over 100 million animals,with the United States leading the list by utilizing 20 million animals.Beyond ethical considerations associated with animal testing and the costs in terms of time and money,animal models are not always effective in predicting human reactions to drug exposure.While animal testing has been the traditional method for assessing the safety and efficacy of drugs.展开更多
This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design co...This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design considerations,such as biological constraints,energy sourcing,and wireless communication,are discussed in achieving the desired performance of the devices and enhanced interface with human tissues.In addition,we review the recent achievements in materials used for developing implantable systems,emphasizing their importance in achieving multi-functionalities,biocompatibility,and hemocompatibility.The wireless,batteryless devices offer minimally invasive device insertion to the body,enabling portable health monitoring and advanced disease diagnosis.Lastly,we summarize the most recent practical applications of advanced implantable devices for human health care,highlighting their potential for immediate commercialization and clinical uses.展开更多
Optical coherence tomography(OCT)is a new intravascular imaging technique with high resolution and could provide accurate morphological information for plaques in coronary arteries.However,its segmentation is still co...Optical coherence tomography(OCT)is a new intravascular imaging technique with high resolution and could provide accurate morphological information for plaques in coronary arteries.However,its segmentation is still commonly performed manually by experts which is time-consuming.The aim of this study was to develop automatic techniques to characterize plaque components and quantify plaque cap thickness using 3 machine learning methods including convolutional neural network(CNN)with U-Net architecture,CNN with Fully convolutional DenseNet(FC-DenseNet)architecture and support vector machine(SVM).In vivo OCT and intravascular ultrasound(IVUS)images were acquired from two patients at Emory University with informed consent obtained.Eighteen OCT image slices which included lipid core and with acceptable image quality were selected for our study.Manual segmentation from imaging experts was used as the gold standard for model training and validation.Since OCT has limited penetration,virtual histology IVUS was combined with OCT data to improve reliability.A 3-fold cross-validation method was used for model training and validation.The overall tissue classification accuracy for the 18 slices studied(total classification database sample size was 8580096 pixels)was 96.36%and 92.72%for U-Net and FC-DenseNet,respectively.The best average prediction accuracy for lipid was 91.29%based on SVM,compared to 82.84%and 78.91%from U-Net and FC-DenseNet,respectively.The overall average accuracy(Acc)differentiating lipid and fibrous tissue were 95.58%,92.33%and 81.84%for U-Net,FC-DenseNet and SVM,respectively.The average errors of U-Net,FC-DenseNet and SVM from the 18 slices for cap thickness quantification were 8.83%,10.71%and 15.85%.The average relative errors of minimum cap thickness from 18 slices of U-Net,FC-DenseNet and SVM were 17.46%,13.06%and 22.20%,respectively.To conclude,CNN-based segmentation methods can better characterize plaque compositions and quantify plaque cap thickness on OCT images and are more likely to be used in the clinical arena.Large-scale studies are needed to further develop the methods and validate our findings.展开更多
Objective and Impact Statement.We present a fully automated hematological analysis framework based on single-channel(single-wavelength),label-free deep-ultraviolet(UV)microscopy that serves as a fast,cost-effective al...Objective and Impact Statement.We present a fully automated hematological analysis framework based on single-channel(single-wavelength),label-free deep-ultraviolet(UV)microscopy that serves as a fast,cost-effective alternative to conventional hematology analyzers.Introduction.Hematological analysis is essential for the diagnosis and monitoring of several diseases but requires complex systems operated by trained personnel,costly chemical reagents,and lengthy protocols.Label-free techniques eliminate the need for staining or additional preprocessing and can lead to faster analysis and a simpler workflow.In this work,we leverage the unique capabilities of deep-UV microscopy as a label-free,molecular imaging technique to develop a deep learning-based pipeline that enables virtual staining,segmentation,classification,and counting of white blood cells(WBCs)in single-channel images of peripheral blood smears.Methods.We train independent deep networks to virtually stain and segment grayscale images of smears.The segmented images are then used to train a classifier to yield a quantitative five-part WBC differential.Results.Our virtual staining scheme accurately recapitulates the appearance of cells under conventional Giemsa staining,the gold standard in hematology.The trained cellular and nuclear segmentation networks achieve high accuracy,and the classifier can achieve a quantitative five-part differential on unseen test data.Conclusion.This proposed automated hematology analysis framework could greatly simplify and improve current complete blood count and blood smear analysis and lead to the development of a simple,fast,and low-cost,point-of-care hematology analyzer.展开更多
Background Current bottleneck of patient-specific coronary plaque model construction is the resolution of in vivo medical imaging.The threshold of cap thickness of vulnerable coronary plaques is 65 microns,while the r...Background Current bottleneck of patient-specific coronary plaque model construction is the resolution of in vivo medical imaging.The threshold of cap thickness of vulnerable coronary plaques is 65 microns,while the resolution of in vivo coronary intravascular ultrasound(IVUS)images is 150-200 microns,which is not enough to identify vulnerable plaques with thin caps and construct accurate biomechanical plaque models.Optical coherence tomography(OCT)with a 15-20μm resolution has the capacity to identify thin fibrous cap.IVUS and OCT images could complement each other and provide for more accurate plaque morphology,especially,fibrous cap thickness measurements.A modeling approach combining IVUS and OCT was introduced in our previous publication for cap thickness quantification and more accurate cap stress/strain calculations.In this paper,patient baseline and follow-up IVUS and OCT data were acquired and multimodality image-based Fluidstructure interaction(FSI)models combining 3D IVUS,OCT,angiography were constructed to better quantify human coronary atherosclerotic plaque morphology and plaque stress/strain conditions and investigate the relationship of plaque vulnerability and morphological and mechanical factors.Methods Baseline and 10-Month follow-up in vivo IVUS and OCT coronary plaque data were acquired from one patient with informed consent obtained.Co-registration and segmentation of baseline and follow-up IVUS and OCT images were performed for modeling use.Baseline and follow-up 3D FSI models based on IVUS and OCT were constructed to simulate the mechanical factors which integrating plaque morphology were employed to predict plaque vulnerability.These 3D models were solved by ADINA(ADINA R&D,Watertown,MA,USA).The quantitative indices of cap thickness,lipid percentage were classified according to histological literatures and denoted as Cap Index and Lipid Index.Cap Index,Lipid Index and Morphological Plaque Vulnerability Index(MPVI)were chosen to quantify plaque vulnerability,respectively.Random forest(RF)which was based 13 extracted features including morphological and mechanical factors was used for plaque vulnerability classification and prediction.Over sampling scheme and a 5-fold crossvalidation procedure was employed in all 45 slices for training and testing sets.Single and all different combinations of morphological and mechanical risk factors were used for plaque progression prediction.Results When Cap Index was used as the measurement,minimum cap thickness(MCT)was the best single predictor which area under curve(AUC)is 0.782 0;the combination of MCT,critical plaque wall strain(CPWSn),critical wall shear stress(CWSS)and cap wall shear stress(CapWSS)was the best predictor with ACU=0.868 6.When Lipid Index was used as the measurement,the lipid percentage(LP)was the best single predictor which AUC value is 0.857 8;the combination of Mean cap thickness(MeanCT),LP,CWSS and cap plaque wall stress(CapPWS)and was the best predictor with ACU=0.9821.When MPVI was used as the measurement,MCT was the best single predictor which AUC value is 0.782 9;the combination of MCT,LP,plaque area(PA),CPWSn and CapWSS was the best predictor with ACU=0.872 9.Conclusions Combinations of morphological and mechanical risk factors had higher prediction accuracy,compared to the prediction of single factors and other combination of morphological factors.展开更多
Background Cardiovascular diseases are closely associated with atherosclerotic plaque development and rupture.Traditional medical imaging techniques such as magnetic resonance imaging(MRI)and intravascular ultrasound(...Background Cardiovascular diseases are closely associated with atherosclerotic plaque development and rupture.Traditional medical imaging techniques such as magnetic resonance imaging(MRI)and intravascular ultrasound(IVUS)were unable to identify vulnerable plaques due to their limited resolution.Fortunately,optical coherence tomography(OCT)is an advanced intravascular imaging technique developed in recent years which has high resolution approximately 10 microns and could provide more accurate morphology of coronary plaque.In particular,it has the ability to identify plaques with fibrous cap thickness<65μm,an accepted threshold value for vulnerable plaques.However,segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective.To overcome time consumption,several methodologies have been proposed for automatic segmentation of OCT images but most of these methods were still limited by intricate image preprocessing and expensive computation.In this research,two automatic segmentation methods for intracoronary OCT image based on support vector machine(SVM)and convolutional neural network(CNN)were performed to identify the plaque region and characterize plaque components.Methods In vivo IVUS and OCT coronary plaque data from 5 patients were acquired at Emory University with patient’s consent obtained.OCT were obtained from ILUMIEN OPTIS System(St.Jude,Minnesota,MN).The OCT catheter was traversed to the segment of interest and the catheter pullback was limited at a rate of 20 mm/sec.Following the OCT image acquisition,the IVUS catheter was traversed distally though the artery to the same coronary segment(Volcano Therapeutics,Rancho Cordova)and the catheter pullback speed was at a standard rate of 0.5 mm/sec.Seventy-seven matched IVUS and OCT slices with good image quality and lipid cores were selected for our segmentation study.Manual OCT segmentation was performed by experts and used as gold standard in the automatic segmentations.VH-IVUS was used as references and guide by the experts in the manual segmentation process.Three plaque component tissue classes were identified from OCT images in this work:lipid tissue(LT),fibrous tissue(FT)and background(BG).Procedures using two machine learning methods(CNN and SVM)were developed to segment OCT images,respectively.For CNN method,the U-Net architecture was selected due to its good performance in very different biomedical segmentation and very few annotated images.For SVM method,local binary patterns(LBPs),gray level co-occurrence matrices(GLCMs)which contains contrast,correlation,energy and homogeneity,entropy and mean value were calculated as features and assembled to feed SVM classifier.The accuracies of two segmentation methods were evaluated and compared using the OCT dataset.Segmentation accuracy is defined as the ratio of the number of pixels correctly classified over the total number of pixels.Results The overall classification accuracy based CNN method reached 95.8%,and the accuracies for LT,FT and BG were 86.8%,83.4%,and 98.2%,respectively.The overall classification accuracy based SVM was 71.9%,and per-class accuracy for LT,FT and BG was 75.4%,78.3%,and67.0%,respectively.Conclusions The two methods proposed can automatically identify plaque region and characterize plaque compositions for OCT images and potentially reduce the time spent by doctors in segmenting and evaluating coronary plaque OCT images.CNN provided better segmentation accuracies compared to those achieved by SVM.展开更多
Implantable vascular devices are widely used in clinical treatments for various vascular diseases. However, current approved clinical implantable vascular devices generally have high failure rates primarily due to the...Implantable vascular devices are widely used in clinical treatments for various vascular diseases. However, current approved clinical implantable vascular devices generally have high failure rates primarily due to their surface lacking inherent functional endothelium. Here, inspired by the pathological mechanisms of vascular device failure and physiological functions of native endothelium, we developed a new generation of bioactive parylene (poly(p-xylylene))-based conformal coating to address these challenges of the vascular devices. This coating used a polyethylene glycol (PEG) linker to introduce an endothelial progenitor cell (EPC) specific binding ligand LXW7 (cGRGDdvc) onto the vascular devices for preventing platelet adhesion and selectively capturing endogenous EPCs. Also, we confirmed the long-term stability and function of this coating in human serum. Using two vascular disease-related large animal models, a porcine carotid artery interposition model and a porcine carotid artery-jugular vein arteriovenous graft model, we demonstrated that this coating enabled rapid generation of self-renewable “living” endothelium on the blood contacting surface of the expanded polytetrafluoroethylene (ePTFE) grafts after implantation. We expect this easy-to-apply conformal coating will present a promising avenue to engineer surface properties of “off-the-shelf” implantable vascular devices for long-lasting performance in the clinical settings.展开更多
CONSPECTUS:As a metal that can occur in nature in the elemental form,copper(Cu)has been used by humans since ca.8000 BC.With most properties matching those of Ag and Au,Cu has played a more significant role in commerc...CONSPECTUS:As a metal that can occur in nature in the elemental form,copper(Cu)has been used by humans since ca.8000 BC.With most properties matching those of Ag and Au,Cu has played a more significant role in commercial applications owing to its much higher(the 25th among all elements)abundance in Earth’s crust and thus more affordable price.In addition to its common use as a conductor of heat and electricity,it is a constituent of various metal alloys for hardware,coins,strain gauges,and thermocouples.展开更多
Noble-metal nanocrystals enclosed by high-index facets are of growing interest due to their enhanced catalytic performance in a variety of reactions.Herein,we report the deterministic synthesis of Pd nanocrystals enca...Noble-metal nanocrystals enclosed by high-index facets are of growing interest due to their enhanced catalytic performance in a variety of reactions.Herein,we report the deterministic synthesis of Pd nanocrystals encased by high-index facets by controlling the rate of deposition(V_(deposition))relative to that of surface diffusion(V_(diffusion)).For octahedral seeds with truncated corners,a reduction rate(and thus deposition rate)faster than that of surface diffusion(i.e.,V_(deposition)/V_(diffusion)>1)led to the formation of concave trisoctahedra(TOH)with high-index facets.When the reduction was slowed down,in contrast,surface diffusion dominated the growth pathway.In the case of V_(deposition)/V_(diffusion)≈1,truncated octahedra with enlarged sizes were produced.When the reduction rate was between these two extremes,we obtained concave tetrahexahedra(THH)without or with truncation.Similar growth patterns were also observed for the cuboctahedral seeds.When the Pd octahedra,concave TOH,and concave THH were tested for electrocatalyzing the formic acid oxidation(FAO)reaction,those with high-index facets were advantageous over the conventional Pd octahedra enclosed by{111}facets.This work not only contributes to the understanding of surface diffusion and its role in nanocrystal growth but also offers a general protocol for the synthesis of nanocrystals enclosed by high-index facets.展开更多
We report a rationally designed one-pot method for the facile synthesis of Pd concave nanocubes in an aqueous solution at room temperature by manipulating the reduction kinetics through the selection of a proper combi...We report a rationally designed one-pot method for the facile synthesis of Pd concave nanocubes in an aqueous solution at room temperature by manipulating the reduction kinetics through the selection of a proper combination of a salt precursor (PdBr4^2-) and reductant (sodium ascorbate). Our kinetic analysis demonstrates that, through this selection, the nucleation and growth of Pd nanocrystals could be effectively separated into two kinetic regimes involving distinctive reduction pathways: i) solution reduction for the initial formation of single-crystal seeds and ii) surface reduction for the formation of concave nanocrystals via autocatalytic growth from the single-crystal seeds. The suppressed surface diffusion at room temperature, when coupled with the capping effect of bromide ions, ultimately leads to the formation of concave nanocubes with an asymmetric shape and high-index facets, whose synthesis would otherwise require multiple steps and the use of elevated temperatures.展开更多
Dear Editor,Dysfunctional vascular endothelial cells(ECs)contribute to the pathophysiology of several cardiovascular diseases,such as atherosclerosis and its life-threatening complications.1 Gene therapy can be a valu...Dear Editor,Dysfunctional vascular endothelial cells(ECs)contribute to the pathophysiology of several cardiovascular diseases,such as atherosclerosis and its life-threatening complications.1 Gene therapy can be a valuable approach to modulate endothelial cell function for the prevention of atherosclerosis.However,there is still a lack of method for transgene expression in vascular endothelium.2 Herein,an effective and specific strategy was established for noninvasive spatial control of transgene expression into the target region of the mouse artery without systemic spillover using an ultrasound and microbubble(MB)guided adenoassociated viral vector(UMGAAV)(Supplementary Fig.S1).To the best of our knowledge,this is the first report on noninvasive spatial control of transgene expression in arterial endothelium in vivo.展开更多
To develop and characterize a novel cell culture method for the generation of undifferentiated and differentiated human mesenchymal stem cell 3D structures,we utilized the RWV system with a gelatin-based scaffold.3...To develop and characterize a novel cell culture method for the generation of undifferentiated and differentiated human mesenchymal stem cell 3D structures,we utilized the RWV system with a gelatin-based scaffold.3×10^(6) cells generated homogeneous spheroids and maximum spheroid loading was accomplished after 3 days of culture.Spheroids cultured in undifferentiated spheroids of 3 and 10 days retained expression of CD44,without expression of differentiation markers.Spheroids cultured in adipogenic and osteogenic differentiation media exhibited oil red O staining and von Kossa staining,respectively.Further characterization of osteogenic lineage,showed that 10 day spheroids exhibited stronger calcification than any other experimental group corresponding with significant expression of vitamin D receptor,alkaline phosphatase,and ERp60.In conclusion this study describes a novel RWV culture method that allowed efficacious engineering of undifferentiated human mesenchymal stem cell spheroids and rapid osteogenic differentiation.The use of gelatin scaffolds holds promise to design implantable stem cell tissue of various sizes and shapes for future regenerative treatment.展开更多
Objective and Impact Statement.Identifying benign mimics of prostatic adenocarcinoma remains a significant diagnostic challenge.In this work,we developed an approach based on label-free,high-resolution molecular imagi...Objective and Impact Statement.Identifying benign mimics of prostatic adenocarcinoma remains a significant diagnostic challenge.In this work,we developed an approach based on label-free,high-resolution molecular imaging with multispectral deep ultraviolet(UV)microscopy which identifies important prostate tissue components,including basal cells.This work has significant implications towards improving the pathologic assessment and diagnosis of prostate cancer.Introduction.One of the most important indicators of prostate cancer is the absence of basal cells in glands and ducts.However,identifying basal cells using hematoxylin and eosin(H&E)stains,which is the standard of care,can be difficult in a subset of cases.In such situations,pathologists often resort to immunohistochemical(IHC)stains for a definitive diagnosis.However,IHC is expensive and time-consuming and requires more tissue sections which may not be available.In addition,IHC is subject to false-negative or false-positive stains which can potentially lead to an incorrect diagnosis.Methods.We leverage the rich molecular information of label-free multispectral deep UV microscopy to uniquely identify basal cells,luminal cells,and inflammatory cells.The method applies an unsupervised geometrical representation of principal component analysis to separate the various components of prostate tissue leading to multiple image representations of the molecular information.Results.Our results show that this method accurately and efficiently identifies benign and malignant glands with high fidelity,free of any staining procedures,based on the presence or absence of basal cells.We further use the molecular information to directly generate a high-resolution virtual IHC stain that clearly identifies basal cells,even in cases where IHC stains fail.Conclusion.Our simple,low-cost,and label-free deep UV method has the potential to improve and facilitate prostate cancer diagnosis by enabling robust identification of basal cells and other important prostate tissue components.展开更多
Achieving localization with molecular precision has been of great interest for extending fluorescence microscopy to nanoscopy.MINFLUX pioneers this transition through point spread function(PSF)engineering,yet its perf...Achieving localization with molecular precision has been of great interest for extending fluorescence microscopy to nanoscopy.MINFLUX pioneers this transition through point spread function(PSF)engineering,yet its performance is primarily limited by the signal-to-background ratio.Here we demonstrate theoretically that two-photon MINFLUX(2p-MINFLUX)could double its localization precision through PSF engineering by nonlinear effect.Cramér-Rao Bound(CRB)is studied as the maximum localization precision,and CRB of two-photon MINFLUX is halved compared to single-photon MINFLUX(1p-MINFLUX)in all three dimensions.Meanwhile,in order to achieve same localization precision with 1p-MINFLUX,2p-MINFLUX requires only 1/4 of fluorescence photons.Exploiting simultaneous two-photon excitation of multiple fluorophore species,2p-MINFLUX may have the potential for registration-free nanoscopy and multicolor tracking.展开更多
Laser-activated perfluorocarb on n anodroplets are an emerging class of phase-cha nge, dual-c ontrast age nts that can be utilized in ultraso und and photoacoustic imaging. Through the ability to differe ntiate subpop...Laser-activated perfluorocarb on n anodroplets are an emerging class of phase-cha nge, dual-c ontrast age nts that can be utilized in ultraso und and photoacoustic imaging. Through the ability to differe ntiate subpopulations of nano droplets via laser activatio n at differe nt wavelengths of n ear-infrared light, optically-triggered color-coded perfluorocarb on nano droplets prese nt themselves as an attractive tool for multiplexed ultrasound and photoacoustic imaging. In particular, laser-activated droplets can be used to provide quantitative spatiotemporal information regarding distinct biological targets, allowing for their potential use in a wide range of diagnostic and therapeutic applications. In the work prese nted, laser-activated color-coded perfluorocarb on nan odroplets are syn thesized to selectively resp ond to laser irradiati on at corresp on ding wavele ngths. The dyn amic ultraso und and photoacoustic signals produced by laser-activated perfluorocarbon nano droplets are evaluated in situ prior to implementation in a murine model. In vivo, these particles are used to distinguish unique particle trafficking mechanisms and are show n to provide ultraso und and photoacoustic contrast for up to 72 hours within lymphatics. Overall, the con ducted studies show that laser-activated color-coded perfluorocarbo n nano droplets are a promising agent for multiplexed ultraso und and photoacoustic imaging.展开更多
基金supported by a 2-Year Research Grant of Pusan National University(to SIA).
文摘Neurological disorders including neurodegenerative diseases,brain tumors,and stroke are the second leading cause of death and the greatest cause of disability worldwide.However,it remains challenging to achieve effective drug delivery to the central nervous system for treatments of neurological diseases due to the blood-brain barrier(BBB).The function of the BBB is regulated by the physiological interactions between various types of cells in the neurovascular unit(NVU).In the NVU,the brain vasculature of the BBB is surrounded by brain pericytes,brain astrocytes,neurons,and microglia(Figure 1).Moreover,the NVU at the levels of arteries and veins includes contractile smooth muscle cells(Schaeffer and Iadecola,2021).
文摘Reducing the use of animal models in drug development and safety assessment has long been supported by the U.S.Food and Drug Administration(FDA).The report by Royal Society for the Prevention of Cruelty to Animals indicates that in 2020,experiments involved the use of over 100 million animals,with the United States leading the list by utilizing 20 million animals.Beyond ethical considerations associated with animal testing and the costs in terms of time and money,animal models are not always effective in predicting human reactions to drug exposure.While animal testing has been the traditional method for assessing the safety and efficacy of drugs.
基金the NSF CCSS-2152638 and the IEN Center Grant from the Institute for Electronics and Nanotechnology at Georgia Tech.
文摘This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design considerations,such as biological constraints,energy sourcing,and wireless communication,are discussed in achieving the desired performance of the devices and enhanced interface with human tissues.In addition,we review the recent achievements in materials used for developing implantable systems,emphasizing their importance in achieving multi-functionalities,biocompatibility,and hemocompatibility.The wireless,batteryless devices offer minimally invasive device insertion to the body,enabling portable health monitoring and advanced disease diagnosis.Lastly,we summarize the most recent practical applications of advanced implantable devices for human health care,highlighting their potential for immediate commercialization and clinical uses.
基金supported in part by National Sciences Foundation of China grants 11972117 and 11672001 and a Jiangsu Province Science and Technology Agency grant BE2016785.
文摘Optical coherence tomography(OCT)is a new intravascular imaging technique with high resolution and could provide accurate morphological information for plaques in coronary arteries.However,its segmentation is still commonly performed manually by experts which is time-consuming.The aim of this study was to develop automatic techniques to characterize plaque components and quantify plaque cap thickness using 3 machine learning methods including convolutional neural network(CNN)with U-Net architecture,CNN with Fully convolutional DenseNet(FC-DenseNet)architecture and support vector machine(SVM).In vivo OCT and intravascular ultrasound(IVUS)images were acquired from two patients at Emory University with informed consent obtained.Eighteen OCT image slices which included lipid core and with acceptable image quality were selected for our study.Manual segmentation from imaging experts was used as the gold standard for model training and validation.Since OCT has limited penetration,virtual histology IVUS was combined with OCT data to improve reliability.A 3-fold cross-validation method was used for model training and validation.The overall tissue classification accuracy for the 18 slices studied(total classification database sample size was 8580096 pixels)was 96.36%and 92.72%for U-Net and FC-DenseNet,respectively.The best average prediction accuracy for lipid was 91.29%based on SVM,compared to 82.84%and 78.91%from U-Net and FC-DenseNet,respectively.The overall average accuracy(Acc)differentiating lipid and fibrous tissue were 95.58%,92.33%and 81.84%for U-Net,FC-DenseNet and SVM,respectively.The average errors of U-Net,FC-DenseNet and SVM from the 18 slices for cap thickness quantification were 8.83%,10.71%and 15.85%.The average relative errors of minimum cap thickness from 18 slices of U-Net,FC-DenseNet and SVM were 17.46%,13.06%and 22.20%,respectively.To conclude,CNN-based segmentation methods can better characterize plaque compositions and quantify plaque cap thickness on OCT images and are more likely to be used in the clinical arena.Large-scale studies are needed to further develop the methods and validate our findings.
基金support for this work by the Massner Lane Family FoundationBurroughs Wellcome Fund (CASI BWF 1014540)+1 种基金National Science Foundation (NSF CBET CAREER 1752011)the Donaldson Charitable Trust Research Synergy Fund Award。
文摘Objective and Impact Statement.We present a fully automated hematological analysis framework based on single-channel(single-wavelength),label-free deep-ultraviolet(UV)microscopy that serves as a fast,cost-effective alternative to conventional hematology analyzers.Introduction.Hematological analysis is essential for the diagnosis and monitoring of several diseases but requires complex systems operated by trained personnel,costly chemical reagents,and lengthy protocols.Label-free techniques eliminate the need for staining or additional preprocessing and can lead to faster analysis and a simpler workflow.In this work,we leverage the unique capabilities of deep-UV microscopy as a label-free,molecular imaging technique to develop a deep learning-based pipeline that enables virtual staining,segmentation,classification,and counting of white blood cells(WBCs)in single-channel images of peripheral blood smears.Methods.We train independent deep networks to virtually stain and segment grayscale images of smears.The segmented images are then used to train a classifier to yield a quantitative five-part WBC differential.Results.Our virtual staining scheme accurately recapitulates the appearance of cells under conventional Giemsa staining,the gold standard in hematology.The trained cellular and nuclear segmentation networks achieve high accuracy,and the classifier can achieve a quantitative five-part differential on unseen test data.Conclusion.This proposed automated hematology analysis framework could greatly simplify and improve current complete blood count and blood smear analysis and lead to the development of a simple,fast,and low-cost,point-of-care hematology analyzer.
基金supported in part by a Jiangsu Province Science and Technology Agency grant ( BE2016785)
文摘Background Current bottleneck of patient-specific coronary plaque model construction is the resolution of in vivo medical imaging.The threshold of cap thickness of vulnerable coronary plaques is 65 microns,while the resolution of in vivo coronary intravascular ultrasound(IVUS)images is 150-200 microns,which is not enough to identify vulnerable plaques with thin caps and construct accurate biomechanical plaque models.Optical coherence tomography(OCT)with a 15-20μm resolution has the capacity to identify thin fibrous cap.IVUS and OCT images could complement each other and provide for more accurate plaque morphology,especially,fibrous cap thickness measurements.A modeling approach combining IVUS and OCT was introduced in our previous publication for cap thickness quantification and more accurate cap stress/strain calculations.In this paper,patient baseline and follow-up IVUS and OCT data were acquired and multimodality image-based Fluidstructure interaction(FSI)models combining 3D IVUS,OCT,angiography were constructed to better quantify human coronary atherosclerotic plaque morphology and plaque stress/strain conditions and investigate the relationship of plaque vulnerability and morphological and mechanical factors.Methods Baseline and 10-Month follow-up in vivo IVUS and OCT coronary plaque data were acquired from one patient with informed consent obtained.Co-registration and segmentation of baseline and follow-up IVUS and OCT images were performed for modeling use.Baseline and follow-up 3D FSI models based on IVUS and OCT were constructed to simulate the mechanical factors which integrating plaque morphology were employed to predict plaque vulnerability.These 3D models were solved by ADINA(ADINA R&D,Watertown,MA,USA).The quantitative indices of cap thickness,lipid percentage were classified according to histological literatures and denoted as Cap Index and Lipid Index.Cap Index,Lipid Index and Morphological Plaque Vulnerability Index(MPVI)were chosen to quantify plaque vulnerability,respectively.Random forest(RF)which was based 13 extracted features including morphological and mechanical factors was used for plaque vulnerability classification and prediction.Over sampling scheme and a 5-fold crossvalidation procedure was employed in all 45 slices for training and testing sets.Single and all different combinations of morphological and mechanical risk factors were used for plaque progression prediction.Results When Cap Index was used as the measurement,minimum cap thickness(MCT)was the best single predictor which area under curve(AUC)is 0.782 0;the combination of MCT,critical plaque wall strain(CPWSn),critical wall shear stress(CWSS)and cap wall shear stress(CapWSS)was the best predictor with ACU=0.868 6.When Lipid Index was used as the measurement,the lipid percentage(LP)was the best single predictor which AUC value is 0.857 8;the combination of Mean cap thickness(MeanCT),LP,CWSS and cap plaque wall stress(CapPWS)and was the best predictor with ACU=0.9821.When MPVI was used as the measurement,MCT was the best single predictor which AUC value is 0.782 9;the combination of MCT,LP,plaque area(PA),CPWSn and CapWSS was the best predictor with ACU=0.872 9.Conclusions Combinations of morphological and mechanical risk factors had higher prediction accuracy,compared to the prediction of single factors and other combination of morphological factors.
基金supported in part by National Sciences Foundation of China grant ( 11672001)Jiangsu Province Science and Technology Agency grant ( BE2016785)
文摘Background Cardiovascular diseases are closely associated with atherosclerotic plaque development and rupture.Traditional medical imaging techniques such as magnetic resonance imaging(MRI)and intravascular ultrasound(IVUS)were unable to identify vulnerable plaques due to their limited resolution.Fortunately,optical coherence tomography(OCT)is an advanced intravascular imaging technique developed in recent years which has high resolution approximately 10 microns and could provide more accurate morphology of coronary plaque.In particular,it has the ability to identify plaques with fibrous cap thickness<65μm,an accepted threshold value for vulnerable plaques.However,segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective.To overcome time consumption,several methodologies have been proposed for automatic segmentation of OCT images but most of these methods were still limited by intricate image preprocessing and expensive computation.In this research,two automatic segmentation methods for intracoronary OCT image based on support vector machine(SVM)and convolutional neural network(CNN)were performed to identify the plaque region and characterize plaque components.Methods In vivo IVUS and OCT coronary plaque data from 5 patients were acquired at Emory University with patient’s consent obtained.OCT were obtained from ILUMIEN OPTIS System(St.Jude,Minnesota,MN).The OCT catheter was traversed to the segment of interest and the catheter pullback was limited at a rate of 20 mm/sec.Following the OCT image acquisition,the IVUS catheter was traversed distally though the artery to the same coronary segment(Volcano Therapeutics,Rancho Cordova)and the catheter pullback speed was at a standard rate of 0.5 mm/sec.Seventy-seven matched IVUS and OCT slices with good image quality and lipid cores were selected for our segmentation study.Manual OCT segmentation was performed by experts and used as gold standard in the automatic segmentations.VH-IVUS was used as references and guide by the experts in the manual segmentation process.Three plaque component tissue classes were identified from OCT images in this work:lipid tissue(LT),fibrous tissue(FT)and background(BG).Procedures using two machine learning methods(CNN and SVM)were developed to segment OCT images,respectively.For CNN method,the U-Net architecture was selected due to its good performance in very different biomedical segmentation and very few annotated images.For SVM method,local binary patterns(LBPs),gray level co-occurrence matrices(GLCMs)which contains contrast,correlation,energy and homogeneity,entropy and mean value were calculated as features and assembled to feed SVM classifier.The accuracies of two segmentation methods were evaluated and compared using the OCT dataset.Segmentation accuracy is defined as the ratio of the number of pixels correctly classified over the total number of pixels.Results The overall classification accuracy based CNN method reached 95.8%,and the accuracies for LT,FT and BG were 86.8%,83.4%,and 98.2%,respectively.The overall classification accuracy based SVM was 71.9%,and per-class accuracy for LT,FT and BG was 75.4%,78.3%,and67.0%,respectively.Conclusions The two methods proposed can automatically identify plaque region and characterize plaque compositions for OCT images and potentially reduce the time spent by doctors in segmenting and evaluating coronary plaque OCT images.CNN provided better segmentation accuracies compared to those achieved by SVM.
基金supported by the UC Davis School of Medicine Dean’s Fellowship award,the Science Translation and Innovative Research(STAIR)grant offered by UC Davis Venture Catalyst,the National Heart,Lung,And Blood Institute under Award Number T32 HL086350 and U54HL 119893 through UC BRAID Center for Accelerated Innovation Technology Grant,and California Institute for Regenerative Medicine(CIRM)grant(TRAN3-13332).The authors would also like to thank the Combinatorial Chemistry Shared Resource at University of California Davis for assistance with design and synthesis of peptides and their derivativesUtilization of this Shared Resource was supported by the UC Davis Comprehensive Cancer Center Support Grant awarded by the National Cancer Institute(P30CA093373).
文摘Implantable vascular devices are widely used in clinical treatments for various vascular diseases. However, current approved clinical implantable vascular devices generally have high failure rates primarily due to their surface lacking inherent functional endothelium. Here, inspired by the pathological mechanisms of vascular device failure and physiological functions of native endothelium, we developed a new generation of bioactive parylene (poly(p-xylylene))-based conformal coating to address these challenges of the vascular devices. This coating used a polyethylene glycol (PEG) linker to introduce an endothelial progenitor cell (EPC) specific binding ligand LXW7 (cGRGDdvc) onto the vascular devices for preventing platelet adhesion and selectively capturing endogenous EPCs. Also, we confirmed the long-term stability and function of this coating in human serum. Using two vascular disease-related large animal models, a porcine carotid artery interposition model and a porcine carotid artery-jugular vein arteriovenous graft model, we demonstrated that this coating enabled rapid generation of self-renewable “living” endothelium on the blood contacting surface of the expanded polytetrafluoroethylene (ePTFE) grafts after implantation. We expect this easy-to-apply conformal coating will present a promising avenue to engineer surface properties of “off-the-shelf” implantable vascular devices for long-lasting performance in the clinical settings.
基金supported in part by the NSF(CHE-1804970,DMR-1505400,DMR-1506018,DMR-0804088,DMR-1104614,DMR-1215034)the NIH(R01,CA138527)+1 种基金the Department of Energy-Basic Energy Sciences,Division of Chemical Sciences(DE-FG02-05ER15731)startup funds from the Georgia Institute of Technology.We thank our collaborators for their invaluable contributions to these studies.
文摘CONSPECTUS:As a metal that can occur in nature in the elemental form,copper(Cu)has been used by humans since ca.8000 BC.With most properties matching those of Ag and Au,Cu has played a more significant role in commercial applications owing to its much higher(the 25th among all elements)abundance in Earth’s crust and thus more affordable price.In addition to its common use as a conductor of heat and electricity,it is a constituent of various metal alloys for hardware,coins,strain gauges,and thermocouples.
基金the NSF(CBET-2219546)and startup funds from the Georgia Institute of Technology.
文摘Noble-metal nanocrystals enclosed by high-index facets are of growing interest due to their enhanced catalytic performance in a variety of reactions.Herein,we report the deterministic synthesis of Pd nanocrystals encased by high-index facets by controlling the rate of deposition(V_(deposition))relative to that of surface diffusion(V_(diffusion)).For octahedral seeds with truncated corners,a reduction rate(and thus deposition rate)faster than that of surface diffusion(i.e.,V_(deposition)/V_(diffusion)>1)led to the formation of concave trisoctahedra(TOH)with high-index facets.When the reduction was slowed down,in contrast,surface diffusion dominated the growth pathway.In the case of V_(deposition)/V_(diffusion)≈1,truncated octahedra with enlarged sizes were produced.When the reduction rate was between these two extremes,we obtained concave tetrahexahedra(THH)without or with truncation.Similar growth patterns were also observed for the cuboctahedral seeds.When the Pd octahedra,concave TOH,and concave THH were tested for electrocatalyzing the formic acid oxidation(FAO)reaction,those with high-index facets were advantageous over the conventional Pd octahedra enclosed by{111}facets.This work not only contributes to the understanding of surface diffusion and its role in nanocrystal growth but also offers a general protocol for the synthesis of nanocrystals enclosed by high-index facets.
基金This work is supported by the National Institutes of Health (ROODE022796 to S.N.) and National Science Foundation (DMR- 0955811 to J.E.C. and PHY-0848797 to J.E.C. and D.T.K.).
基金partially supported by the NSF CAREER Award CBET-1540898Baodong Liu was partially supported by IHEP-CAS Scientific Research Foundation 2013IHEPYJRC801
文摘We report a rationally designed one-pot method for the facile synthesis of Pd concave nanocubes in an aqueous solution at room temperature by manipulating the reduction kinetics through the selection of a proper combination of a salt precursor (PdBr4^2-) and reductant (sodium ascorbate). Our kinetic analysis demonstrates that, through this selection, the nucleation and growth of Pd nanocrystals could be effectively separated into two kinetic regimes involving distinctive reduction pathways: i) solution reduction for the initial formation of single-crystal seeds and ii) surface reduction for the formation of concave nanocrystals via autocatalytic growth from the single-crystal seeds. The suppressed surface diffusion at room temperature, when coupled with the capping effect of bromide ions, ultimately leads to the formation of concave nanocubes with an asymmetric shape and high-index facets, whose synthesis would otherwise require multiple steps and the use of elevated temperatures.
基金supported by the National Natural Science Foundation of China(No.81930047 to Z.D.No.82102062 to R.L.)the Project funded by the China Postdoctoral Science Foundation(2020TQ0008 to R.L.)。
文摘Dear Editor,Dysfunctional vascular endothelial cells(ECs)contribute to the pathophysiology of several cardiovascular diseases,such as atherosclerosis and its life-threatening complications.1 Gene therapy can be a valuable approach to modulate endothelial cell function for the prevention of atherosclerosis.However,there is still a lack of method for transgene expression in vascular endothelium.2 Herein,an effective and specific strategy was established for noninvasive spatial control of transgene expression into the target region of the mouse artery without systemic spillover using an ultrasound and microbubble(MB)guided adenoassociated viral vector(UMGAAV)(Supplementary Fig.S1).To the best of our knowledge,this is the first report on noninvasive spatial control of transgene expression in arterial endothelium in vivo.
基金We thank Dr.Carlos Abramowsky and Carla Shoffeit from the Department of Pediatric Pathology at Children’s Healthcare of Atlanta for their help in tissue preparation and staining.This grant was supported by PO-1 CA-098912,NIH/RCMI G12 RR03059-21A1NIH/NCHD,NIH/NCI 1 U54 CA118623。
文摘To develop and characterize a novel cell culture method for the generation of undifferentiated and differentiated human mesenchymal stem cell 3D structures,we utilized the RWV system with a gelatin-based scaffold.3×10^(6) cells generated homogeneous spheroids and maximum spheroid loading was accomplished after 3 days of culture.Spheroids cultured in undifferentiated spheroids of 3 and 10 days retained expression of CD44,without expression of differentiation markers.Spheroids cultured in adipogenic and osteogenic differentiation media exhibited oil red O staining and von Kossa staining,respectively.Further characterization of osteogenic lineage,showed that 10 day spheroids exhibited stronger calcification than any other experimental group corresponding with significant expression of vitamin D receptor,alkaline phosphatase,and ERp60.In conclusion this study describes a novel RWV culture method that allowed efficacious engineering of undifferentiated human mesenchymal stem cell spheroids and rapid osteogenic differentiation.The use of gelatin scaffolds holds promise to design implantable stem cell tissue of various sizes and shapes for future regenerative treatment.
基金the Burroughs Wellcome Fund (CASI BWF 1014540)National Science Foundation (NSF CBET CAREER 1752011)Wallace H.Coulter Department of Biomedical Engineering at Emory University and the Georgia Institute of Technology.
文摘Objective and Impact Statement.Identifying benign mimics of prostatic adenocarcinoma remains a significant diagnostic challenge.In this work,we developed an approach based on label-free,high-resolution molecular imaging with multispectral deep ultraviolet(UV)microscopy which identifies important prostate tissue components,including basal cells.This work has significant implications towards improving the pathologic assessment and diagnosis of prostate cancer.Introduction.One of the most important indicators of prostate cancer is the absence of basal cells in glands and ducts.However,identifying basal cells using hematoxylin and eosin(H&E)stains,which is the standard of care,can be difficult in a subset of cases.In such situations,pathologists often resort to immunohistochemical(IHC)stains for a definitive diagnosis.However,IHC is expensive and time-consuming and requires more tissue sections which may not be available.In addition,IHC is subject to false-negative or false-positive stains which can potentially lead to an incorrect diagnosis.Methods.We leverage the rich molecular information of label-free multispectral deep UV microscopy to uniquely identify basal cells,luminal cells,and inflammatory cells.The method applies an unsupervised geometrical representation of principal component analysis to separate the various components of prostate tissue leading to multiple image representations of the molecular information.Results.Our results show that this method accurately and efficiently identifies benign and malignant glands with high fidelity,free of any staining procedures,based on the presence or absence of basal cells.We further use the molecular information to directly generate a high-resolution virtual IHC stain that clearly identifies basal cells,even in cases where IHC stains fail.Conclusion.Our simple,low-cost,and label-free deep UV method has the potential to improve and facilitate prostate cancer diagnosis by enabling robust identification of basal cells and other important prostate tissue components.
基金Beijing Natural Science Foundation(JQ18019)National Natural Science Foundation of China(62025501,31971376,61729501)+1 种基金State Key Research Development Program of China(2017YFC0110202)Shenzhen Science and Technology Program(KQTD20170810110913065)。
文摘Achieving localization with molecular precision has been of great interest for extending fluorescence microscopy to nanoscopy.MINFLUX pioneers this transition through point spread function(PSF)engineering,yet its performance is primarily limited by the signal-to-background ratio.Here we demonstrate theoretically that two-photon MINFLUX(2p-MINFLUX)could double its localization precision through PSF engineering by nonlinear effect.Cramér-Rao Bound(CRB)is studied as the maximum localization precision,and CRB of two-photon MINFLUX is halved compared to single-photon MINFLUX(1p-MINFLUX)in all three dimensions.Meanwhile,in order to achieve same localization precision with 1p-MINFLUX,2p-MINFLUX requires only 1/4 of fluorescence photons.Exploiting simultaneous two-photon excitation of multiple fluorophore species,2p-MINFLUX may have the potential for registration-free nanoscopy and multicolor tracking.
基金D. Y. S. acknowledges fellowship funding from the National Institutes of Health (No. T32 EB007507) and the National Science Foundation Graduate Research Fellowship ProgramK. A. H. acknowledges fellowship funding from the National Institutes of Health (No. T32 EB007507)+1 种基金S. K. Y. acknowledges fellowship funding from the National Institutes of Health (No. F30 CA216939)The work was supported in part by the National Institutes of Health under Grants CAI5859& EB008101 and CAI49740 as well as the Breast Cancer Research Foundation Grant (No. BCRF-17-043).
文摘Laser-activated perfluorocarb on n anodroplets are an emerging class of phase-cha nge, dual-c ontrast age nts that can be utilized in ultraso und and photoacoustic imaging. Through the ability to differe ntiate subpopulations of nano droplets via laser activatio n at differe nt wavelengths of n ear-infrared light, optically-triggered color-coded perfluorocarb on nano droplets prese nt themselves as an attractive tool for multiplexed ultrasound and photoacoustic imaging. In particular, laser-activated droplets can be used to provide quantitative spatiotemporal information regarding distinct biological targets, allowing for their potential use in a wide range of diagnostic and therapeutic applications. In the work prese nted, laser-activated color-coded perfluorocarb on nan odroplets are syn thesized to selectively resp ond to laser irradiati on at corresp on ding wavele ngths. The dyn amic ultraso und and photoacoustic signals produced by laser-activated perfluorocarbon nano droplets are evaluated in situ prior to implementation in a murine model. In vivo, these particles are used to distinguish unique particle trafficking mechanisms and are show n to provide ultraso und and photoacoustic contrast for up to 72 hours within lymphatics. Overall, the con ducted studies show that laser-activated color-coded perfluorocarbo n nano droplets are a promising agent for multiplexed ultraso und and photoacoustic imaging.