Microsurgical and laser ablation analysis of leaf positioning and dorsoventral patterning in tomato

Leaves are arranged according to regular patterns, a phenomenon referred to as phyllotaxis. Important determinants of phyllotaxis are the divergence angle between successive leaves, and the size of the leaves relative to the shoot axis. Young leaf primordia are thought to provide positional information to the meristem, thereby influencing the positioning of new primordia and hence the divergence angle. On the contrary, the meristem signals to the primordia to establish their dorsoventral polarity, which is a prerequisite for the formation of a leaf blade. These concepts originate from classical microsurgical studies carried out between the 1920s and the 1970s. Even though these techniques have been abandoned in favor of genetic analysis, the resulting insights remain a cornerstone of plant developmental biology. Here, we employ new microsurgical techniques to reassess and extend the classical studies on phyllotaxis and leaf polarity. Previous experiments have indicated that the isolation of an incipient primordium by a tangential incision caused a change of divergence angle between the two subsequent primordia, indicating that pre-existing primordia influence further phyllotaxis. Here.. we repeat these experiments and compare them with the results of laser ablation of incipient primordia. Furthermore. we explore to what extent the different pre-existing primordia influence the size and position of new organs. and hence phyllotaxis. We propose that the two youngest primordia (P-1 and P-2) are sufficient for the approximate positioning of the incipient primordium (I-1), and therefore for the perpetuation of the generative spiral, whereas the direct contact neighbours of I-1 (P-2 and P-3) control its delimitation and hence its exact size and position. Finally. we report L I specific cell ablation experiments suggesting that the meristem L-1 layer is essential for the dorsoventral patterning of leaf primordia.

Targeting class IA PI3K isoforms selectively impairs cell growth, survival, and migration in glioblastoma.

The phosphoinositide 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway is frequently activated in human cancer and plays a crucial role in glioblastoma biology. We were interested in gaining further insight into the potential of targeting PI3K isoforms as a novel anti-tumor approach in glioblastoma. Consistent expression of the PI3K catalytic isoform PI3K p110α was detected in a panel of glioblastoma patient samples. In contrast, PI3K p110β expression was only rarely detected in glioblastoma patient samples. The expression of a module comprising the epidermal growth factor receptor (EGFR)/PI3K p110α/phosphorylated ribosomal S6 protein (p-S6) was correlated with shorter patient survival. Inhibition of PI3K p110α activity impaired the anchorage-dependent growth of glioblastoma cells and induced tumor regression in vivo. Inhibition of PI3K p110α or PI3K p110β also led to impaired anchorage-independent growth, a decreased migratory capacity of glioblastoma cells, and reduced the activation of the Akt/mTOR pathway. These effects were selective, because targeting of PI3K p110δ did not result in a comparable impairment of glioblastoma tumorigenic properties. Together, our data reveal that drugs targeting PI3K p110α can reduce growth in a subset of glioblastoma tumors characterized by the expression of EGFR/PI3K p110α/p-S6.

MicroRNA miR-199a-5p regulates smooth muscle cell proliferation and morphology by targeting Wnt2 signaling pathway

MicroRNA miR-199a-5p impairs tight junction formation leading to increased urothelial permeability in bladder pain syndrome. Now using transcriptome analysis in urothelial TEU-2 cells we implicate it in the regulation of cell cycle, cytoskeleton remodeling, TGF and Wnt signaling pathways. MiR-199a-5p is highly expressed in the smooth muscle layer of the bladder and we altered its levels in bladder smooth muscle cells (SMC) to validate the pathway analysis. Inhibition of miR-199a-5p with antimiR increased SMC proliferation, reduced cell size and up-regulated miR-199a-5p targets, including Wnt2. Overexpression of Wnt2 protein or treating SMCs with recombinant Wnt2 closely mimicked the miR-199a-5p inhibition, whereas down-regulation of Wnt2 in antimiR-expressing SMCs with shRNA restored cell phenotype and proliferation rates. Overexpression of miR-199a-5p in the bladder SMCs significantly increased cell size and up-regulated SM22, SM alpha-actin and SM myosin heavy chain mRNA and protein levels. These changes, as well as increased expression of ACTG2, TGFB1I1, and CDKN1A were mediated by up-regulation of smooth muscle-specific transcriptional activator myocardin at mRNA and protein levels. Myocardin-related transcription factor (MRTF-A) downstream targets Id3 and MYL9 were also induced. Up-regulation of myocardin was accompanied by down-regulation of Wnt-dependent inhibitory Kruppel-like transcription factor 4 (KLF4) in miR-199a-5p overexpressing cells. In contrast, KLF4 was induced in antimiR-expressing cells following the activation of Wnt2 signaling, leading to repression of myocardin-dependent genes. MiR-199a-5p plays a critical role in the Wnt2-mediated regulation of proliferative and differentiation processes in the smooth muscle and may behave as a key modulator of smooth muscle hypertrophy, relevant for organ remodeling.

miR-125b controls apoptosis and temozolomide resistance by targeting TNFAIP3 and NKIRAS2 in glioblastomas.

Diffusely infiltrating gliomas are among the most prognostically discouraging neoplasia in human. Temozolomide (TMZ) in combination with radiotherapy is currently used for the treatment of glioblastoma (GBM) patients, but less than half of the patients respond to therapy and chemoresistance develops rapidly. Epigenetic silencing of the O(6)-methylguanine-DNA methyltransferase (MGMT) has been associated with longer survival in GBM patients treated with TMZ, but nuclear factor κB (NF-κB)-mediated survival signaling and TP53 mutations contribute significantly to TMZ resistance. Enhanced NF-κB is in part owing to downregulation of negative regulators of NF-κB activity, including Tumor necrosis factor alpha-induced protein 3 (TNFAIP3) and NF-κB inhibitor interacting RAS-like 2 (NKIRAS2). Here we provide a novel mechanism independent of TP53 and MGMT by which oncogenic miR-125b confers TMZ resistance by targeting TNFAIP3 and NKIRAS2. GBM cells overexpressing miR-125b showed increased NF-κB activity and upregulation of anti-apoptotic and cell cycle genes. This was significantly associated with resistance of GBM cells to TNFα- and TNF-related inducing ligand-induced apoptosis as well as resistance to TMZ. Conversely, overexpression of anti-miR-125b resulted in cell cycle arrest, increased apoptosis and increased sensitivity to TMZ, indicating that endogenous miR-125b is sufficient to control these processes. GBM cells overexpressing TNFAIP3 and NKIRAS2 were refractory to miR-125b-induced apoptosis resistance as well as TMZ resistance, indicating that both genes are relevant targets of miR-125b. In GBM tissues, high miR-125b expression was significantly correlated with nuclear NF-κB confirming that miR-125b is implicated in NF-κB signaling. Most remarkably, miR-125b overexpression was clearly associated with shorter overall survival of patients treated with TMZ, suggesting that this microRNA is an important predictor of response to therapy.

Lipid droplet and early autophagosomal membrane targeting of Atg2A and Atg14L in human tumor cells.

Autophagy is a lysosomal bulk degradation pathway for cytoplasmic cargo, such as long-lived proteins, lipids, and organelles. Induced upon nutrient starvation, autophagic degradation is accomplished by the concerted actions of autophagy-related (ATG) proteins. Here we demonstrate that two ATGs, human Atg2A and Atg14L, colocalize at cytoplasmic lipid droplets (LDs) and are functionally involved in controlling the number and size of LDs in human tumor cell lines. We show that Atg2A is targeted to cytoplasmic ADRP-positive LDs that migrate bidirectionally along microtubules. The LD localization of Atg2A was found to be independent of the autophagic status. Further, Atg2A colocalized with Atg14L under nutrient-rich conditions when autophagy was not induced. Upon nutrient starvation and dependent on phosphatidylinositol 3-phosphate [PtdIns(3)P] generation, both Atg2A and Atg14L were also specifically targeted to endoplasmic reticulum-associated early autophagosomal membranes, marked by the PtdIns(3)P effectors double-FYVE containing protein 1 (DFCP1) and WD-repeat protein interacting with phosphoinositides 1 (WIPI-1), both of which function at the onset of autophagy. These data provide evidence for additional roles of Atg2A and Atg14L in the formation of early autophagosomal membranes and also in lipid metabolism.

Direct in vitro and in vivo comparison of 161Tb and 177Lu using a tumour-targeting folate conjugate

Purpose The radiolanthanide 161Tb (T 1/2 = 6.90 days, Eβ− av = 154 keV) was recently proposed as a potential alternative to 177Lu (T 1/2 = 6.71 days, Eβ− av = 134 keV) due to similar physical decay characteristics but additional conversion and Auger electrons that may enhance the therapeutic efficacy. The goal of this study was to compare 161Tb and 177Lu in vitro and in vivo using a tumour-targeted DOTA-folate conjugate (cm09). Methods 161Tb-cm09 and 177Lu-cm09 were tested in vitro on folate receptor (FR)-positive KB and IGROV-1 cancer cells using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) viability assay. In vivo 161Tb-cm09 and 177Lu-cm09 (10 MBq, 0.5 nmol) were investigated in two different tumour mouse models with regard to the biodistribution, the possibility for single photon emission computed tomography (SPECT) imaging and the antitumour efficacy. Potentially undesired side effects were monitored over 6 months by determination of plasma parameters and examination of kidney function with quantitative SPECT using 99mTc-dimercaptosuccinic acid (DMSA). Results To obtain half-maximal inhibition of tumour cell viability a 4.5-fold (KB) and 1.7-fold (IGROV-1) lower radioactivity concentration was required for 161Tb-cm09 (IC50 ~0.014 MBq/ml and ~2.53 MBq/ml) compared to 177Lu-cm09 (IC50 ~0.063 MBq/ml and ~4.52 MBq/ml). SPECT imaging visualized tumours of mice with both radioconjugates. However, in therapy studies 161Tb-cm09 reduced tumour growth more efficiently than 177Lu-cm09. These findings were in line with the higher absorbed tumour dose for 161Tb-cm09 (3.3 Gy/MBq) compared to 177Lu-cm09 (2.4 Gy/MBq). None of the monitored parameters indicated signs of impaired kidney function over the whole time period of investigation after injection of the radiofolates. Conclusion Compared to 177Lu-cm09 we demonstrated equal imaging features for 161Tb-cm09 but an increased therapeutic efficacy for 161Tb-cm09 in both tumour cell lines in vitro and in vivo. Further preclinical studies using other tumour-targeting radioconjugates are clearly necessary to draw final conclusions about the future clinical perspectives of 161Tb.

[DOTA]Somatostatin-14 analogs and their (111)In-radioligands: effects of decreasing ring-size on sst1-5 profile, stability and tumor targeting.

Multiple somatostatin receptor (sst)-subtype expression has been manifested in several human tumors. Hence, the availability of radiopeptides retaining the full pansomatostatin profile of the native hormone (SS14) is expected to increase the sensitivity and broaden the clinical indications of currently applied sst2-preferring cyclic octapeptide radioligands, like OctreoScan(®) ([(111)In-DTPA]octreotide). On the other hand, SS14 has been excluded from clinical use due to its rapid in vivo degradation. We herein present a small library of seven novel cyclic SS14-mimics carrying at their N-terminus the universal chelator DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) for stable binding of medically useful radiometals, like (111)In. By decreasing the number of amino acids composing the ring in their structure from 12 up to 6 AA, we induced important changes in key-biological parameters in vitro and in vivo. In particular, we observed unexpected changes and even total loss of sst1-5-affinity (6AA-ring), as well as weaker sst2-internalization efficacy as the ring size decreased. In contrast, in vivo stability increased with decreasing ring size, reaching its maximum in the 6AA-ring analogs. Interestingly, only the 12AA- and 9AA-ring members of this series showed sst2-specific uptake in AR4-2J tumors in mice revealing the prominent role of ring size on the biological response of tested SS14-derived radioligands.

Alginate-coated chitosan nanogels differentially modulate class-A and class-B CpG-ODN targeting of dendritic cells and intracellular delivery.

UNLABELLED CpG-oligodeoxynucleotides (CpG-ODNs) interact with dendritic cells (DCs), but evidence is less clear for CpG-ODN admixed with or incorporated into vaccine delivery vehicles. We loaded alginate-coated chitosan-nanogels (Ng) with class-A or class-B CpG-ODN, and compared with the same CpG-ODNs free or admixed with empty Ng. Experiments were performed on both porcine and human blood DC subpopulations. Encapsulation of class-A CpG-ODN (loading into Ng) strongly reduced the CpG-ODN uptake and intracellular trafficking in the cytosol; this was associated with a marked deficiency in IFN-α induction. In contrast, encapsulation of class-B CpG-ODN increased its uptake and did not influence consistently intracellular trafficking into the nucleus. The choice of CpG-ODN class as adjuvant is thus critical in terms of how it will behave with nanoparticulate vaccine delivery vehicles. The latter can have distinctive modulatory influences on the CpG-ODN, which would require definition for different CpG-ODN and delivery vehicles prior to vaccine formulation. FROM THE CLINICAL EDITOR This basic science study investigates the role of class-A and class-B CpG-oligodeoxynucleotides loaded into alginate-coated chitosan nanogels, demonstrating differential effects between the two classes as related to the use of these nanoformulations as vaccine delivery vehicles.

Volumetric analysis of lung nodules in computed tomography (CT): comparison of two different segmentation algorithm softwares and two different reconstruction filters on automated volume calculation.

BACKGROUND A precise detection of volume change allows for better estimating the biological behavior of the lung nodules. Postprocessing tools with automated detection, segmentation, and volumetric analysis of lung nodules may expedite radiological processes and give additional confidence to the radiologists. PURPOSE To compare two different postprocessing software algorithms (LMS Lung, Median Technologies; LungCARE®, Siemens) in CT volumetric measurement and to analyze the effect of soft (B30) and hard reconstruction filter (B70) on automated volume measurement. MATERIAL AND METHODS Between January 2010 and April 2010, 45 patients with a total of 113 pulmonary nodules were included. The CT exam was performed on a 64-row multidetector CT scanner (Somatom Sensation, Siemens, Erlangen, Germany) with the following parameters: collimation, 24x1.2 mm; pitch, 1.15; voltage, 120 kVp; reference tube current-time, 100 mAs. Automated volumetric measurement of each lung nodule was performed with the two different postprocessing algorithms based on two reconstruction filters (B30 and B70). The average relative volume measurement difference (VME%) and the limits of agreement between two methods were used for comparison. RESULTS At soft reconstruction filters the LMS system produced mean nodule volumes that were 34.1% (P < 0.0001) larger than those by LungCARE® system. The VME% was 42.2% with a limit of agreement between -53.9% and 138.4%.The volume measurement with soft filters (B30) was significantly larger than with hard filters (B70); 11.2% for LMS and 1.6% for LungCARE®, respectively (both with P < 0.05). LMS measured greater volumes with both filters, 13.6% for soft and 3.8% for hard filters, respectively (P < 0.01 and P > 0.05). CONCLUSION There is a substantial inter-software (LMS/LungCARE®) as well as intra-software variability (B30/B70) in lung nodule volume measurement; therefore, it is mandatory to use the same equipment with the same reconstruction filter for the follow-up of lung nodule volume.

3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification

In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.

Localization and Segmentation of 3D Intervertebral Discs in MR Images by Data Driven Estimation

This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.

A complete-pelvis segmentation framework for image-free total hip arthroplasty (THA): methodology and clinical study

Background Complete-pelvis segmentation in antero-posterior pelvic radiographs is required to create a patient-specific three-dimensional pelvis model for surgical planning and postoperative assessment in image-free navigation of total hip arthroplasty. Methods A fast and robust framework for accurately segmenting the complete pelvis is presented, consisting of two consecutive modules. In the first module, a three-stage method was developed to delineate the left hemipelvis based on statistical appearance and shape models. To handle complex pelvic structures, anatomy-specific information processing techniques were employed. As the input to the second module, the delineated left hemi-pelvis was then reflected about an estimated symmetry line of the radiograph to initialize the right hemi-pelvis segmentation. The right hemi-pelvis was segmented by the same three-stage method, Results Two experiments conducted on respectively 143 and 40 AP radiographs demonstrated a mean segmentation accuracy of 1.61±0.68 mm. A clinical study to investigate the postoperative assessment of acetabular cup orientations based on the proposed framework revealed an average accuracy of 1.2°±0.9° and 1.6°±1.4° for anteversion and inclination, respectively. Delineation of each radiograph costs less than one minute. Conclusions Despite further validation needed, the preliminary results implied the underlying clinical applicability of the proposed framework for image-free THA.