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Amon Miha - One of the best experts on this subject based on the ideXlab platform.
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Prilagodljivo ocenjevanje morfoloških lastnosti dolgih ambulantnih elektrokardiogramov z uporabo ortogonalnih transformacij
2017Co-Authors: Amon MihaAbstract:Nezanesljiv opis prehodnih morfoloških sprememb segmenta ST v dolgotrajnih ambulantnih elektokardiografskih (EKG) posnetkih in nezanesljivo razlikovanje med prehodnimi ishemičnimi ter neishemičnimi spremembami morfologij segmenta ST sta še vedno šibkejši lastnosti današnjih sistemov za vizualno ali avtomatsko odkrivanje epizod prehodne ishemije. Tradicionalna metoda ocenjevanja prehodnih sprememb morfologije segmenta ST, ki temelji na merjenju nivoja segmenta ST v zgolj eni sami statični referenčni točki, ni dovolj natančna metoda, ne le zaradi številnih motenj, ki so prisotne v signalih EKG, ta metoda namreč ne zajame morfologije celotnega segmenta ST. Posebna težava, ki do sedaj še ni bil ustrezno rešena, je tudi spremenljiva dolžina posameznih segmentov in valov znotraj posameznih srčnih utripov zaradi spreminjajoče se srčne frekvence. Klinično pomembni segmenti in valovi signala EKG lahko tako ob spremenjeni srčni frekvenci nastopijo v znatno spremenjeni časovni dolžini. Dogaja se, da so opazovane značilnosti segmentov in valov klinično ekvivalentne, ocena njihove morfologije pa je zaradi spremenjene srčne frekvence bistveno različna. Obstoječe metode za izločanje morfoloških značilk segmenta ST niso prilagodljive glede na spreminjajočo se srčno frekvenco in posledično na spreminjajočo se dolžino segmenta ST. Razvili smo novo, robustno, proti motnjam odporno metodo za opisovanje prehodnih sprememb morfologij segmenta ST in novo metodo za klasifikacijo prehodnih ishemičnih ter neishemičnih epizod segmenta ST, ki temeljita na ortogonalnih transformacijah, ki se dinamično prilagajajo spreminjajoči se srčni frekvenci. V ta namen smo razvili nov algoritem, ki s prevzorčenjem in linearno interpolacijo vhodnih vektorjev vzorcev (segmenti ST) dinamično prilagaja njihovo dolžino glede na višino trenutne srčne frekvence in jih transformira v vektorje vzorcev enotne dolžine. Algoritem temelji na Bazettovi formuli, ki je namenjena ocenjevanju dolžine intervala depolarizacije in repolarizacije srčnih ventriklov glede na trenutno srčno frekvenco in na nekaj ekspertno določenih položajih prilagodljive referenčne točke merjenja nivoja segmenta ST v odvisnosti od nekaterih izbranih vrednosti srčne frekvence. Z namenom prilagodljivega in proti motnjam odpornega zajemanja in ocenjevanja morfoloških lastnosti dolgotrajnih posnetkov EKG smo z uporabo robustnega postopka izgradnje kovariančne matrike, ki se tudi dinamično prilagaja spreminjajoči se dolžini vhodnih vektorjev vzorcev, razvili nove bazne funkcije ortogonalne transformacije Karhunena in Loèva (KLT) za segment ST ter novo ortogonalno transformacijo za segment ST na osnovi Legendrovih polinomov (LPT), ki se prav tako dinamično prilagaja spreminjajoči se dolžini vhodnih vektorjev vzorcev zaradi spreminjajoče se srčne frekvence. Transformaciji KLT in LPT dajeta konsistentne medsebojno primerljive ocene spremembmorfologij segmenta ST ne glede na spremembe v srčni frekvenci. Pridobljene časovne vrste vektorjev morfoloških značilk obeh transformacij omogočajo tudi nadaljnjoekspertno analizo in avtomatsko detekcijo ter klasifikacijo prehodnih epizod segmentaST. Razvita metoda opisovanja omogoča dolgotrajno reprezentacijo in karakterizacijoprehodnih sprememb morfologij segmenta ST na osnovi časovnih vrst vektorjev diagnostičnih in morfoloških značilk. V delu predstavljamo študijo zmogljivosti nove metode za reprezentacijo in karakterizacijo prehodnih sprememb morfologij ishemičnih in neishemičnih epizod segmenta ST z uporabo transformacije KLT ali LPT. Prve tri bazne funkcije transformacije LPT (konstanta, linearna funkcija in kvadratna funkcija) ustrezajo klinično pomembnim kategorijam morfologij, ki se pojavljajo pri prehodnih spremembah morfologije segmenta ST ob srčni ishemiji (elevacija ali depresija,nagib in ukrivljanje). Transformacija LPT tako omogoča edinstven neposreden vpogled v posamezne kategorije sprememb morfologij segmenta ST v časovnem prostoru le preko spremljanja časovnih vrst vektorjev morfoloških značilk. Izdelane nove časovne vrste vektorjev morfoloških značilk transformacij KLT in LPT smo objavili tudi v okviru mednarodne referenčne podatkovne baze LTST DB (Long-Term ST Database)dolgotrajnih posnetkov EKG, ki je prosto dostopna na spletnem portalu PhysioNet. Razvita metoda klasifikacije prehodnih ishemičnih in neishemičnih epizod segmenta ST temelji na uporabi samo vektorjev morfoloških značilk transformacije KLT aliLPT in ne uporablja drugih vektorjev diagnostičnih značilk signala EKG. Druge prednosti razvite metode pred drugimi obstoječimi metodami so še: nižja občutljivost na motnje, za vsak srčni utrip je potrebna le stabilna referenčna točka za ta utrip, točnegazačetka segmenta ST za vsak srčni utrip ni treba detektirati, prav tako informacija očasu začetka prehodne epizode ni potrebna. V delu predstavljamo študijo vrednotenja zmogljivosti klasifikacije ekspertno označenih prehodnih ishemičnih in neishemičnih epizod posnetkov podatkovne baze LTST DB z uporabo novih vektorjev morfoloških značilk transformacij KLT ali LPT ter z uporabo nekaterih izbranih standardnih klasifikatorjev. Najvišja dosežena klasifikacijska točnost, ob uporabi klasifikatorja k najbližjihsosedov, kNN (k = 3), dobljena z desetkratnim prečnim preverjanjem in desetimi ponovitvami, je na osnovi KLT 91% in na osnovi LPT 90%, kar je primerljivo in boljše odobjavljenih zmogljivosti sorodnih študij. Prilagodljivi ortogonalni transformaciji KLT in LPT prinašata nove možnosti zaučinkovitejšo ekspertno diagnostiko in avtomatsko analizo. Transformacija KLT daje višje rezultate zmogljivosti klasifikacije med prehodnimi ishemičnimi in neishemičnimi epizodami segmenta ST ter nakazuje razvoj novih in zmogljivejših avtomatskih sistemov.Transformacija LPT daje boljše rezultate opisovanja prehodnih sprememb morfologijsegmenta ST in nakazuje možnosti razvoja novih kliničnih diagnostičnih kriterijev zadiagnosticiranje prehodne ishemije.The unreliable delineation of transient Morphologic changes of ST segments in long-term ambulatory electrocardiogram (ECG) records and the unreliable differentiation between transient ischaemic and non-ischaemic ST segment morphologies are still the major weakness of modern systems for the visual or automatic detection of transient ischaemic episodes. The traditional method for assessing transient changes of ST segment morphologies, which is based on the ST segment level measurement in a single static reference point, is not a sufficiently precise technique, not only due to frequent noises present in the ECG signals, but also because this method does not acquire the morphology of an entire ST segment. A particular problem that has not been suitably resolved as of yet is the variable length of individual segments and waves of individual heartbeats due to variable heart rates. Clinically important segments and waves of the ECG signal can therefore appear in significantly modified time lengths due to changed heart rates.What occurs is that the observed characteristics of segments and waves are clinically equivalent, but the assessment of their morphology is significantly different due to a changed heart rate.The existing methods for ST segment morphology Feature extraction are not adaptive with regard to variable heart rates and consequently to variable ST segment lengths. We have developed a new, robust, noise-resistant method for the delineation of transientST segment morphology changes, and a new method for the classification of transient ischaemic and non-ischaemic ST segment episodes, which are based on a foundation of orthogonal transformations that dynamically adapt to the variable heart rate.For this purpose, we have developed a new algorithm which dynamically by resampling and the linear interpolation of the input pattern vectors (ST segments) adapts their length with regard to the value of instantaneous heart rate, and transforms them into pattern vectors with a constant length.The algorithm is based on Bazett’s formula, which is used for estimating the length of the interval of depolarization and repolarization of heart ventricles according to instantaneous heart rate, and on a few expertly determined positions of adaptive reference point of measurement of the ST segment level with regard to several selected values of heart rate.With the aim of establishing an adaptive and noise-resistant extraction and estimation of MorphologicFeatures of long-term ECG records, we have developed new basis functions of the Karhunen-Loève orthogonal Transformation (KLT) for the ST segment using a robust covariancematrix construction procedure, which also dynamically adapts to the variable lengthof the input pattern vectors, and a new orthogonal transformation for the ST segment on the basis of the Legendre polynomials (LPT), which also dynamically adapts to the variable length of the input pattern vectors due to variable heart rates.The KLT and LPT transformations yield consistent mutually comparable estimations of the ST segment morphology changes regardless of the changes in heart rate. The obtained morphology Feature-vector time series of both transformations further enable expert analysis and the automatic detection and classification of transient ST segment episodes. The developed delineation method enables a long-term representation and characterization of transient ST segment morphology changes on the basis of diagnostic and Morphologic Feature-vector time series. We present a performance study of the new method for the representation and characterization of transient ischaemic and non-ischaemic ST segment morphology changes using the KLT and LPT transformations.The first three basis functions of the LPT transformation (constant, linear function, and quadratic function) correspond to clinically important morphology categories thatoccur during transient ST segment morphology changes of heart ischaemia (elevation ordepression, slope, and scooping). The LPT transformation thus enables a unique direct insight into the individual time domain categories of the ST segment morphology changes via monitoring only the Morphologic Feature-vector time series.We have published the new derived KLT and LPT transformation-based Morphologic Feature-vector time series in the scope of the international reference database LTST DB (Long-Term ST Database) of long-term ECG records, which is freely available on the Physionet website. The method developed for the classification of transient ischaemic and non-ischaemic ST segment episodes is based on the use of the KLT or LPT transformation morphology Feature vectors only and does not use other diagnostic Feature vectors of the ECG signal.The other advantages of the developed method over the other existing methods are:lower sensitivity to noise, only a stable fiducial point is needed for each heartbeat, there is no need to detect the precise beginning of ST segment for each heartbeat, while the information on the start time of a transient episode is also not needed.In our work we present a study on the performance evaluation of classification of expert-annotated transient ischaemic and non-ischaemic episodes from LTST DB database recordsusing new Morphologic Feature vectors of the KLT and LPT transformation, and using a few selected standard classifiers.The highest classification accuracy achieved, using the k Nearest Neighbors classifier, kNN (k = 3), obtained by ten-fold cross-validation and ten repetitions, was 91% based on the KLT and 90% based on the LPT, which is comparable and better than the published performances from related studies. The adaptive KLT and LPT orthogonal transformations open new possibilities for a more efficient expert diagnosis and automated analysis. The KLT transformation yields higher results in classification performance between transient ischaemic and non-ischaemic ST segment episodes and indicates the development of new and more powerful automated systems.The LPT transformation yields better results in the delineation of transient ST segment morphology changes and indicates opportunities for the development of new clinical diagnostic criteria for diagnosing transient ischaemia
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Prilagodljivo ocenjevanje morfoloških lastnosti dolgih ambulantnih elektrokardiogramov z uporabo ortogonalnih transformacij
2017Co-Authors: Amon MihaAbstract:The unreliable delineation of transient Morphologic changes of ST segments in long-term ambulatory electrocardiogram (ECG) records and the unreliable differentiation between transient ischaemic and non-ischaemic ST segment morphologies are still the major weakness of modern systems for the visual or automatic detection of transient ischaemic episodes. The traditional method for assessing transient changes of ST segment morphologies, which is based on the ST segment level measurement in a single static reference point, is not a sufficiently precise technique, not only due to frequent noises present in the ECG signals, but also because this method does not acquire the morphology of an entire ST segment. A particular problem that has not been suitably resolved as of yet is the variable length of individual segments and waves of individual heartbeats due to variable heart rates. Clinically important segments and waves of the ECG signal can therefore appear in significantly modified time lengths due to changed heart rates.What occurs is that the observed characteristics of segments and waves are clinically equivalent, but the assessment of their morphology is significantly different due to a changed heart rate.The existing methods for ST segment morphology Feature extraction are not adaptive with regard to variable heart rates and consequently to variable ST segment lengths. We have developed a new, robust, noise-resistant method for the delineation of transientST segment morphology changes, and a new method for the classification of transient ischaemic and non-ischaemic ST segment episodes, which are based on a foundation of orthogonal transformations that dynamically adapt to the variable heart rate.For this purpose, we have developed a new algorithm which dynamically by resampling and the linear interpolation of the input pattern vectors (ST segments) adapts their length with regard to the value of instantaneous heart rate, and transforms them into pattern vectors with a constant length.The algorithm is based on Bazett’s formula, which is used for estimating the length of the interval of depolarization and repolarization of heart ventricles according to instantaneous heart rate, and on a few expertly determined positions of adaptive reference point of measurement of the ST segment level with regard to several selected values of heart rate.With the aim of establishing an adaptive and noise-resistant extraction and estimation of MorphologicFeatures of long-term ECG records, we have developed new basis functions of the Karhunen-Loève orthogonal Transformation (KLT) for the ST segment using a robust covariancematrix construction procedure, which also dynamically adapts to the variable lengthof the input pattern vectors, and a new orthogonal transformation for the ST segment on the basis of the Legendre polynomials (LPT), which also dynamically adapts to the variable length of the input pattern vectors due to variable heart rates.The KLT and LPT transformations yield consistent mutually comparable estimations of the ST segment morphology changes regardless of the changes in heart rate. The obtained morphology Feature-vector time series of both transformations further enable expert analysis and the automatic detection and classification of transient ST segment episodes. The developed delineation method enables a long-term representation and characterization of transient ST segment morphology changes on the basis of diagnostic and Morphologic Feature-vector time series. We present a performance study of the new method for the representation and characterization of transient ischaemic and non-ischaemic ST segment morphology changes using the KLT and LPT transformations.The first three basis functions of the LPT transformation (constant, linear function, and quadratic function) correspond to clinically important morphology categories thatoccur during transient ST segment morphology changes of heart ischaemia (elevation ordepression, slope, and scooping). The LPT transformation thus enables a unique direct insight into the individual time domain categories of the ST segment morphology changes via monitoring only the Morphologic Feature-vector time series.We have published the new derived KLT and LPT transformation-based Morphologic Feature-vector time series in the scope of the international reference database LTST DB (Long-Term ST Database) of long-term ECG records, which is freely available on the Physionet website. The method developed for the classification of transient ischaemic and non-ischaemic ST segment episodes is based on the use of the KLT or LPT transformation morphology Feature vectors only and does not use other diagnostic Feature vectors of the ECG signal.The other advantages of the developed method over the other existing methods are:lower sensitivity to noise, only a stable fiducial point is needed for each heartbeat, there is no need to detect the precise beginning of ST segment for each heartbeat, while the information on the start time of a transient episode is also not needed.In our work we present a study on the performance evaluation of classification of expert-annotated transient ischaemic and non-ischaemic episodes from LTST DB database recordsusing new Morphologic Feature vectors of the KLT and LPT transformation, and using a few selected standard classifiers.The highest classification accuracy achieved, using the k Nearest Neighbors classifier, kNN (k = 3), obtained by ten-fold cross-validation and ten repetitions, was 91% based on the KLT and 90% based on the LPT, which is comparable and better than the published performances from related studies. The adaptive KLT and LPT orthogonal transformations open new possibilities for a more efficient expert diagnosis and automated analysis. The KLT transformation yields higher results in classification performance between transient ischaemic and non-ischaemic ST segment episodes and indicates the development of new and more powerful automated systems.The LPT transformation yields better results in the delineation of transient ST segment morphology changes and indicates opportunities for the development of new clinical diagnostic criteria for diagnosing transient ischaemia
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Robust estimation of Morphologic Features and shape representation of electrocardiograms using orthogonal transforms
2011Co-Authors: Amon MihaAbstract:An important task in the field of electrocardiogram (ECG) signal processing is the development of effective discrete transforms, which can extract useful clinical information from source signals and represent it as Morphologic Feature vector time series. Such time series are then suitable for further machine processing as well as for visual diagnostic procedures by cardiologists. We have tested and enhanced the existing Karhunen and Loève transform (KLT) Feature vector space based noise detection algorithm. The algorithm is robust and uses the skipped mean value as an estimator. We have generated new KLT base functions for the ST electrocardiogram segment with all 86 24-hour records of the international reference ECG database LTST DB (Long-Term ST Database) as a learning set. New covariance matrices are robust and based on the kernel-approximation method. In addition, a new transform was developed, based on the Legendre polynomials (LPT) which are visually similar to typical Morphologic changes of the ST segment during myocardial ischemia. The later provides a direct insight into the transient morphology change type from the Feature vector space. The noise detection algorithm and both transforms were used for generation of new ST segment Feature vector time series for all LTST DB records. We have studied and compared characteristics of both transforms in terms of residual error distribution and characterized new Feature vector time series behavior in the neighborhood of transient ischemic and false non-ischemic ST segment episodes. Using the new Feature vector time series of both transforms and the existing LTST DB diagnostic parameter time series (heart-rate, ST segment level) we have characterized ischemic (deviation, sloping, scooping) and non-ischemic (shift of T-wave into the ST segment) ST segment morphology changes at the level of single heart beats as well as at the level of transient episodes (episode beginnings and extremes) with the motivation of evaluating the LPT transform as a new approach to effective ischemic and non-ischemic physiologic process differentiation. New graphical tools for ECG data visualizations and Morphologic Feature vector time series characterization, algorithms and software for base functions generation, KLT and LPT transform Feature vector time series derivation and several other functions as the residual errors, statistical analyses, time series manipulations etc. were also developed for this work. New Feature vector time series and the associated residual errors were added to the LTST DB database which is freely available on the Physionet servers
Junjie Wang - One of the best experts on this subject based on the ideXlab platform.
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125i seeds radiation induces paraptosis like cell death via pi3k akt signaling pathway in hct116 cells
BioMed Research International, 2016Co-Authors: Hao Wang, Yong Zhao, Junjie WangAbstract:125I seeds brachytherapy implantation has been extensively performed in unresectable and rerecurrent rectal carcinoma. Many studies on the cancer-killing activity of 125I seeds radiation mainly focused on its ability to trigger apoptosis, which is the most well-known and dominant type of cell death induced by radiation. However our results showed some unique Morphological Features such as cell swelling, cytoplasmic vacuolation, and plasma membrane integrity, which is obviously different to apoptosis. In this study, clonogenic proliferation was carried out to assay survival fraction. Transmission electron microscopy was used to analyze ultrastructural and evaluate Morphologic Feature of HCT116 cells after exposure to 125I seeds radiation. Immunofluorescence analysis was used to detect the origin of cytoplasmic vacuoles. Flow cytometry analysis was employed to detect the size and granularity of HCT116 cells. Western blot was performed to measure the protein level of AIP1, caspase-3, AKT, p-Akt (Thr308), p-Akt (Ser473), and β-actin. We found that 125I seeds radiation activated PI3K/AKT signaling pathway and could trigger paraptosis-like cell death. Moreover, inhibitor of PI3K/AKT signaling pathway could inhibit paraptosis-like cell death induced by 125I seeds radiation. Our data suggest that 125I seeds radiation can induce paraptosis-like cell death via PI3K/AKT signaling pathway.
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125I Seeds Radiation Induces Paraptosis-Like Cell Death via PI3K/AKT Signaling Pathway in HCT116 Cells
Hindawi Limited, 2016Co-Authors: Hao Wang, Yong Zhao, Junjie WangAbstract:125I seeds brachytherapy implantation has been extensively performed in unresectable and rerecurrent rectal carcinoma. Many studies on the cancer-killing activity of 125I seeds radiation mainly focused on its ability to trigger apoptosis, which is the most well-known and dominant type of cell death induced by radiation. However our results showed some unique Morphological Features such as cell swelling, cytoplasmic vacuolation, and plasma membrane integrity, which is obviously different to apoptosis. In this study, clonogenic proliferation was carried out to assay survival fraction. Transmission electron microscopy was used to analyze ultrastructural and evaluate Morphologic Feature of HCT116 cells after exposure to 125I seeds radiation. Immunofluorescence analysis was used to detect the origin of cytoplasmic vacuoles. Flow cytometry analysis was employed to detect the size and granularity of HCT116 cells. Western blot was performed to measure the protein level of AIP1, caspase-3, AKT, p-Akt (Thr308), p-Akt (Ser473), and β-actin. We found that 125I seeds radiation activated PI3K/AKT signaling pathway and could trigger paraptosis-like cell death. Moreover, inhibitor of PI3K/AKT signaling pathway could inhibit paraptosis-like cell death induced by 125I seeds radiation. Our data suggest that 125I seeds radiation can induce paraptosis-like cell death via PI3K/AKT signaling pathway
Takaaki Suzuki - One of the best experts on this subject based on the ideXlab platform.
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clinical and Morphologic Features of perimembranous ventricular septal defect with overriding of the aorta the so called eisenmenger ventricular septal defect a study making comparisons with tetralogy of fallot and perimembranous ventricular defect without aortic overriding
Cardiology in The Young, 2000Co-Authors: Toyoki Fukuda, Takaaki SuzukiAbstract:Abstract The aim of our study was to elucidate the clinical and Morphologic Features of those perimembranous ventricular septal defects which extend between the ventricular outlets, particularly when found in association with anterior deviation of the muscular outlet septum and overriding of the aorta--the so called Eisenmenger ventricular septal defect. From 1990 through 1998, we have undertaken surgical correction in 203 patients with perimembranous ventricular septal defect. Of these, 15 patients had the Eisenmenger ventricular septal defect. We conducted retrospective analyses of the clinical records, catheterization data, and angiocardiographic and echocardiographic finding of these patients. Comparative studies were then made with the patients having tetralogy of Fallot, and those with simple perimembranous ventricular septal defects without overriding of the aorta. In the patients with the Eisenmenger ventricular septal defect, the extent of anterior deviation of the outlet septum was comparable with that seen in tetralogy of Fallot, but there was less rightward displacement of the aortic valvar orifice. In contrast to earlier investigators, however, we found evidence of progressive narrowing of the subpulmonary infundibulum in those with the Eisenmenger defect. These Morphological Features were reflected in the clinical Features, since all patients showed evidence of increased pulmonary flow and congestive heart failure in early infancy, but with two-thirds of them subsequently developing right-to-left shunting. We conclude, therefore, that the Eisenmenger ventricular septal defect is a discrete cardiac abnormality in which the Morphologic substrate of anterior deviation of the outlet septum gives rise to a potential for progressive narrowing of the subpulmonary infundibulum. Surgical management, therefore, needs to take account of such narrowing as an additional cardinal Morphologic Feature.
Hao Wang - One of the best experts on this subject based on the ideXlab platform.
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125i seeds radiation induces paraptosis like cell death via pi3k akt signaling pathway in hct116 cells
BioMed Research International, 2016Co-Authors: Hao Wang, Yong Zhao, Junjie WangAbstract:125I seeds brachytherapy implantation has been extensively performed in unresectable and rerecurrent rectal carcinoma. Many studies on the cancer-killing activity of 125I seeds radiation mainly focused on its ability to trigger apoptosis, which is the most well-known and dominant type of cell death induced by radiation. However our results showed some unique Morphological Features such as cell swelling, cytoplasmic vacuolation, and plasma membrane integrity, which is obviously different to apoptosis. In this study, clonogenic proliferation was carried out to assay survival fraction. Transmission electron microscopy was used to analyze ultrastructural and evaluate Morphologic Feature of HCT116 cells after exposure to 125I seeds radiation. Immunofluorescence analysis was used to detect the origin of cytoplasmic vacuoles. Flow cytometry analysis was employed to detect the size and granularity of HCT116 cells. Western blot was performed to measure the protein level of AIP1, caspase-3, AKT, p-Akt (Thr308), p-Akt (Ser473), and β-actin. We found that 125I seeds radiation activated PI3K/AKT signaling pathway and could trigger paraptosis-like cell death. Moreover, inhibitor of PI3K/AKT signaling pathway could inhibit paraptosis-like cell death induced by 125I seeds radiation. Our data suggest that 125I seeds radiation can induce paraptosis-like cell death via PI3K/AKT signaling pathway.
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125I Seeds Radiation Induces Paraptosis-Like Cell Death via PI3K/AKT Signaling Pathway in HCT116 Cells
Hindawi Limited, 2016Co-Authors: Hao Wang, Yong Zhao, Junjie WangAbstract:125I seeds brachytherapy implantation has been extensively performed in unresectable and rerecurrent rectal carcinoma. Many studies on the cancer-killing activity of 125I seeds radiation mainly focused on its ability to trigger apoptosis, which is the most well-known and dominant type of cell death induced by radiation. However our results showed some unique Morphological Features such as cell swelling, cytoplasmic vacuolation, and plasma membrane integrity, which is obviously different to apoptosis. In this study, clonogenic proliferation was carried out to assay survival fraction. Transmission electron microscopy was used to analyze ultrastructural and evaluate Morphologic Feature of HCT116 cells after exposure to 125I seeds radiation. Immunofluorescence analysis was used to detect the origin of cytoplasmic vacuoles. Flow cytometry analysis was employed to detect the size and granularity of HCT116 cells. Western blot was performed to measure the protein level of AIP1, caspase-3, AKT, p-Akt (Thr308), p-Akt (Ser473), and β-actin. We found that 125I seeds radiation activated PI3K/AKT signaling pathway and could trigger paraptosis-like cell death. Moreover, inhibitor of PI3K/AKT signaling pathway could inhibit paraptosis-like cell death induced by 125I seeds radiation. Our data suggest that 125I seeds radiation can induce paraptosis-like cell death via PI3K/AKT signaling pathway
Ali Guermazi - One of the best experts on this subject based on the ideXlab platform.
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what comes first multitissue involvement leading to radiographic osteoarthritis magnetic resonance imaging based trajectory analysis over four years in the osteoarthritis initiative
Arthritis & Rheumatism, 2015Co-Authors: Frank W Roemer, David J Hunter, C K Kwoh, Robert M Boudreau, M J Hannon, F Eckstein, T Fujii, Ali GuermaziAbstract:Objective To assess whether the presence of structural osteoarthritis (OA) Features over as many as 4 years prior to incident radiographic OA increases the risk of radiographic OA in a nested, case–control design. Methods We studied 355 knees from the Osteoarthritis Initiative cohort that developed radiographic OA before the 48-month visit. They were matched one-to-one by sex, age, and contralateral knee radiographic status with a control knee. Magnetic resonance images (MRIs) were read for bone marrow lesions (BMLs), cartilage damage, meniscal damage (including tears and extrusion), Hoffa synovitis, and effusion synovitis. Conditional logistic regression was applied to assess the risk of radiographic OA with regard to the presence of BMLs (score ≥2), cartilage lesions (score ≥1.1), meniscal damage (any) and extrusion of ≥3 mm ± (score ≥2), and Hoffa and effusion synovitis (any). Time points were defined as incident radiographic OA visit (P0), 1 year prior to the detection of radiographic OA (P −1), 2 years prior to the detection of radiographic OA (P −2), etc. Results The presence of Hoffa synovitis (hazard ratio [HR] 1.76 [95% confidence interval (95% CI) 1.18–2.64]), effusion synovitis (HR 1.81 [95% CI 1.18–2.78]), and medial meniscal damage (HR 1.83 [95% CI 1.17–2.89]) at P −2 predicted radiographic OA incidence. At P −1, all Features but meniscal extrusion predicted radiographic OA, with highest odds for medial BMLs (HR 6.50 [95% CI 2.27–18.62]) and effusion synovitis (HR 2.50 [95% CI 1.76–3.54]). The findings at P −3 and P −4 did not reach statistical significance. Conclusion Our findings indicate that the presence of specific structural Features of MRI-detected joint damage 2 years prior to incident radiographic OA increases the risk of incident radiographic OA. However, 1 year prior to radiographic OA, the presence of almost any abnormal Morphologic Feature increases the risk of radiographic OA in the subsequent year.