93 research outputs found
Morphology and ploidy level determination of Pteris vittata callus during induction and regeneration
Background: Morphological and ploidy changes of the arsenic hyperaccumulator, Chinese brake fern (Pteris vittata) callus tissue are described here to provide insight into fern life cycle biology and for possible biotechnology applications. Pteris vittata callus was studied using transmission and scanning electron microscopy, and flow cytometry.
Results: Callus induction occurred both in light and dark culture conditions from prothallus tissues, whereas rhizoid formation occurred only in dark culture conditions. Callus tissues contained two types of cells: one actively dividing and the other containing a single large vacuole undergoing exocytosis. Sporophytes regenerated from callus asynchronously form clusters of cells in a manner apparently analogous to direct organogenesis. Extracellular matrices were observed in actively-growing callus and at the base of regenerating sporophytes. Callus tissue nuclei were found to be primarily diploid at induction and throughout maintenance of cultures indicating that callus cell fate is determined at induction, which closely follows apogamous sporophyte development. Presence of a dense extracellular matrix in conjunction with sporophyte development suggests a link between the suspensor-like activity of the embryonic foot during normal fern embryo development and the suspected functions of extracellular matrices in angiosperms.
Conclusions: Further investigation could lead to a better understanding of genes involved in P. vittata embryo development and apogamous sporophyte development. The methodology could be useful for in vitro propagation of rare and valuable fern germplasm
Very bright orange fluorescent plants: endoplasmic reticulum targeting of orange fluorescent proteins as visual reporters in transgenic plants
Background
The expression of fluorescent protein (FP) genes as real-time visual markers, both transiently and stably, has revolutionized plant biotechnology. A palette of colors of FPs is now available for use, but the diversity has generally been underutilized in plant biotechnology. Because of the green and far-red autofluorescent properties of many plant tissues and the FPs themselves, red and orange FPs (RFPs, and OFPs, respectfully) appear to be the colors with maximum utility in plant biotechnology. Within the color palette OFPs have emerged as the brightest FP markers in the visible spectra. This study compares several native, near-native and modified OFPs for their “brightness” and fluorescence, therefore, their usability as marker genes in transgenic plant tissues. Results
The OFPs DsRed2, tdTomato, mOrange and pporRFP were all expressed under the control of the CaMV 35S promoter in agroinfiltration-mediated transient assays in Nicotiana benthamiana. Each of these, as well as endoplasmic reticulum (ER)-targeted versions, were stably expressed in transgenic Nicotiana tabacum and Arabidopsis thaliana. Congruent results were observed between transient and stable assays. Our results demonstrated that there are several adequate OFP genes available for plant transformation, including the new pporRFP, an unaltered tetramer from the hard coral Porites porites. When the tandem dimer tdTomato and the monomeric mOrange were targeted to the ER, dramatic, ca. 3-fold, increase in plant fluorescence was observed. Conclusions
From our empirical data, and a search of the literature, it appears that tdTomato-ER and mOrange-ER are the two highest fluorescing FPs available as reporters for transgenic plants. The pporRFP is a brightly fluorescing tetramer, but all tetramer FPs are far less bright than the ER-targeted monomers we report here
Computed tomography-based anatomic assessment overestimates local tumor recurrence in patients with mass-like consolidation after stereotactic body radiotherapy for early-stage non-small cell lung cancer.
PURPOSE: To investigate pulmonary radiologic changes after lung stereotactic body radiotherapy (SBRT), to distinguish between mass-like fibrosis and tumor recurrence.
METHODS AND MATERIALS: Eighty consecutive patients treated with 3- to 5-fraction SBRT for early-stage peripheral non-small cell lung cancer with a minimum follow-up of 12 months were reviewed. The mean biologic equivalent dose received was 150 Gy (range, 78-180 Gy). Patients were followed with serial CT imaging every 3 months. The CT appearance of consolidation was defined as diffuse or mass-like. Progressive disease on CT was defined according to Response Evaluation Criteria in Solid Tumors 1.1. Positron emission tomography (PET) CT was used as an adjunct test. Tumor recurrence was defined as a standardized uptake value equal to or greater than the pretreatment value. Biopsy was used to further assess consolidation in select patients.
RESULTS: Median follow-up was 24 months (range, 12.0-36.0 months). Abnormal mass-like consolidation was identified in 44 patients (55%), whereas diffuse consolidation was identified in 12 patients (15%), at a median time from end of treatment of 10.3 months and 11.5 months, respectively. Tumor recurrence was found in 35 of 44 patients with mass-like consolidation using CT alone. Combined with PET, 10 of the 44 patients had tumor recurrence. Tumor size (hazard ratio 1.12, P=.05) and time to consolidation (hazard ratio 0.622, P=.03) were predictors for tumor recurrence. Three consecutive increases in volume and increasing volume at 12 months after treatment in mass-like consolidation were highly specific for tumor recurrence (100% and 80%, respectively). Patients with diffuse consolidation were more likely to develop grade ≥ 2 pneumonitis (odds ratio 26.5, P=.02) than those with mass-like consolidation (odds ratio 0.42, P=.07).
CONCLUSION: Incorporating the kinetics of mass-like consolidation and PET to the current criteria for evaluating posttreatment response will increase the likelihood of correctly identifying patients with progressive disease after lung SBRT
A New System for Lung Cancer Diagnosis based on the Integration of Global and Local CT Features
© 2019 IEEE. Lung cancer leads deaths caused by cancer for both men and women worldwide, that is why creating systems for early diagnosis with machine learning algorithms and nominal user intervention is of huge importance. In this manuscript, a new system for lung nodule diagnosis, using features extracted from one computed tomography (CT) scan, is presented. This system integrates global and local features to give an implication of the nodule prior growth rate, which is the main point for diagnosis of pulmonary nodules. 3D adjustable local binary pattern and some basic geometric features are used to extract the nodule global features, and the local features are extracted using 3D convolutional neural networks (3D-CNN) because of its ability to exploit the spatial correlation of input data in an efficient way. Finally all these features are integrated using autoencoder to give a final diagnosis for the lung nodule whether benign or malignant. The system was evaluated using 727 nodules extracted from the Lung Image Database Consortium (LIDC) dataset. The proposed system diagnosis accuracy, sensitivity, and specificity were 92.20%,93.55%, and 91.20% respectively. The proposed framework demonstrated its promise as a valuable tool for lung cancer detection evidenced by its higher accuracy
A Novel CT-Based Descriptors for Precise Diagnosis of Pulmonary Nodules
© 2019 IEEE. Early diagnosis of pulmonary nodules is critical for lung cancer clinical management. In this paper, a novel framework for pulmonary nodule diagnosis, using descriptors extracted from single computed tomography (CT) scan, is introduced. This framework combines appearance and shape descriptors to give an indication of the nodule prior growth rate, which is the key point for diagnosis of lung nodules. Resolved Ambiguity Local Binary Pattern and 7th Order Markov Gibbs Random Field are developed to describe the nodule appearance without neglecting spatial information. Spherical harmonics expansion and some primitive geometric features are utilized to describe how the nodule shape is complicated. Ultimately, all descriptors are combined using denoising autoencoder to classify the nodule, whether malignant or benign. Training, testing, and parameter tuning of all framework modules are done using a set of 727 nodules extracted from the Lung Image Database Consortium (LIDC) dataset. The proposed system diagnosis accuracy, sensitivity, and specificity were 94.95%, 94.62%, 95.20% respectively, all of which show that our system has promise to reach the accepted clinical accuracy threshold
Stereotactic body radiation therapy (SBRT) of adrenal gland metastases in oligometastatic and oligoprogressive disease
BACKGROUND: Stereotactic body radiation therapy (SBRT) as a form of noninvasive treatment that is becoming increasingly used to manage cancers with adrenal gland metastases. There is a paucity of data on safety and efficacy of this modality.
The aim of the study was to evaluate the safety and efficacy of adrenal gland SBRT in oligometastatic and oligoprogressive disease.
MATERIALS AND METHODS: In this retrospective study, we performed a single-institution analysis of 26 adrenal lesions from 23 patients with oligometastatic or oligoprogressive disease treated from 2013 to 2019 with the goal of achieving durable local control. Palliative cases were excluded. Radiation dosimetry data was collected. Kaplan Meier product estimator and Cox proportional hazards regression analysis were used for statistical analysis.
RESULTS: The median dose was 36 Gy in 3 fractions (range: 24–50 Gy and 3–6 fractions) with a median biologically effective dose (BED10) of 72 (range: 40–100). 1-year local control rate was 80% and median local control was not achieved due to a low number of failures. 1- and 2-year overall survival rates were 66% and 32%. Toxicity was mild with only one case of grade 2 nausea and no grade 3–5 toxicity. Higher neutrophil to lymphocyte ratio was associated with worse overall survival and a trend toward worse progression-free survival. In addition, worse performance status and lower BED10 were associated with worse survival. No such association could be shown for primary tumor location, histology, size or stage.
CONCLUSION: Adrenal SBRT for oligometastatic or oligoprogressive disease is a safe and effective form of treatment
A Novel Autoencoder-Based Diagnostic System for Early Assessment of Lung Cancer
© 2018 IEEE. A novel framework for the classification of lung nodules using computed tomography (CT) scans is proposed in this paper. To get an accurate diagnosis of the detected lung nodules, the proposed framework integrates the following two groups of features: (i) appearance features that is modeled using higher-order Markov Gibbs random field (MGRF)-model that has the ability to describe the spatial inhomogeneities inside the lung nodule; and (ii) geometric features that describe the shape geometry of the lung nodules. The novelty of this paper is to accurately model the appearance of the detected lung nodules using a new developed 7th-order MGRF model that has the ability to model the existing spatial inhomogeneities for both small and large detected lung nodules, in addition to the integration with the extracted geometric features. Finally, a deep autoencoder (AE) classifier is fed by the above two feature groups to distinguish between the malignant and benign nodules. To evaluate the proposed framework, we used the publicly available data from the Lung Image Database Consortium (LIDC). We used a total of 727 nodules that were collected from 467 patients. The proposed system demonstrates the promise to be a valuable tool for the detection of lung cancer evidenced by achieving a nodule classification accuracy of 92.20%
A generalized deep learning-based diagnostic system for early diagnosis of various types of pulmonary nodules
© The Author(s) 2018. A novel framework for the classification of lung nodules using computed tomography scans is proposed in this article. To get an accurate diagnosis of the detected lung nodules, the proposed framework integrates the following 2 groups of features: (1) appearance features modeled using the higher order Markov Gibbs random field model that has the ability to describe the spatial inhomogeneities inside the lung nodule and (2) geometric features that describe the shape geometry of the lung nodules. The novelty of this article is to accurately model the appearance of the detected lung nodules using a new developed seventh-order Markov Gibbs random field model that has the ability to model the existing spatial inhomogeneities for both small and large detected lung nodules, in addition to the integration with the extracted geometric features. Finally, a deep autoencoder classifier is fed by the above 2 feature groups to distinguish between the malignant and benign nodules. To evaluate the proposed framework, we used the publicly available data from the Lung Image Database Consortium. We used a total of 727 nodules that were collected from 467 patients. The proposed system demonstrates the promise to be a valuable tool for the detection of lung cancer evidenced by achieving a nodule classification accuracy of 91.20%
Size matters: A comparison of T1 and T2 peripheral non–small-cell lung cancers treated with stereotactic body radiation therapy (SBRT)
ObjectiveThe purpose of this study was to compare the outcomes and local control rates of patients with peripheral T1 and T2 non–small-cell lung cancer treated with stereotactic body radiation therapy.MethodsThe records of 40 consecutive patients treated with 3- or 5-fraction lung stereotactic body radiation therapy for peripheral, clinical stage I non–small-cell lung cancer were reviewed. Stereotactic body radiation therapy was delivered at a median dose of 60 Gy. Doses to organs at risk were limited based on the Radiation Therapy Oncology Group 0236 treatment protocol. Patients were staged clinically. Median follow was 12.5 months.ResultsTwenty-seven (67%) patients and 13 (33%) patients had T1 and T2 tumors, respectively. Thirty-seven (94%) patients were medically inoperable. Nine (23%) patients had chest wall pain after stereotactic body radiation therapy. Symptomatic pneumonitis developed in 4 (10%) patients. Increasing tumor size correlated with worse local control and overall survival. The median recurrence-free survival for T1 and T2 tumors was 30.6 months (95% confidence interval [CI], 26.9–34.2) and 20.5 months (95% CI, 14.3–26.5), respectively (P = .038). Local control at 2 years was 90% and 70% in T1 and T2 tumors, respectively (P = .03). The median survival for T1 and T2 tumors was 20 months (95% CI, 20.1–31.6) and 16.7 months (95% CI, 10.8–21.2), respectively (P = .073).ConclusionsStereotactic body radiation therapy for T2 non–small-cell lung cancer has a higher local recurrence rate and trended toward a worse survival than did T1 lesions. Tumor size is an important predictor of response to stereotactic body radiation therapy and should be considered in treatment planning
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