From biomolecules to bioimages: filling the gap from bench to bedside.  

Projects highlights

INCIPIT

ISTAPCA (253 views)

 INMiND (409 views)

 PRIN (468 views)

 eHealthNet (359 views)

  Ponrec (314 views)

MFAG Grant (349 views)


Links

Activities highlights
This activity is focused on developing a software procedure for automated segmentation of brain structures starting from brain CTs and/or MRs.
The software must support the manual 3D drawing or importing of a lesion ROI, excluded during segmentation.
The software applies also an atlas on the segmentation, both on the Gray Matter and the White Matter and produces an RTP structure file, with contours for each slice and for each ROI.
Optionally the software can import an RT dose DICOM file with which it calculates dose-volume histograms.
The activity is aimed to develop, test, validate and improve the software and use it on the field for research purposes.

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The family of human proteins containing a potassium channel tetramerization domain (KCTD) includes 21 members that are implicated in very important biological processes. KCTD11/REN, the best-characterized member of the family to date, is a negative regulator of the Hedgehog pathway and plays an important role in the tumorigenesis of medulloblastoma, a severe and widespread solid cancer of the childhood. Very recently it has been shown that it is involved in the ubiquitination of HDAC1 by acting, in complex with Cullin3, as an E3 ubiquitin ligase (1). The molecular and structural characterization of KCTD11 has shown that this tetrameric protein is involved in giant macromolecular complexes with its biological partners (Cul3, Rbx1, E2) (2). The development of molecules that are able to interfere with the function of this protein will likely have a relevant impact in the definition of the molecular basis of tumorigenesis. In this scenario, we have recently developed peptides, derived from the Cl3 protein, that are able to bind KCTD11 and other members of this protein family (3). Current activities are focused on the optimization of these molecules and on the characterization of structure-function relations for other members of the KCTD family.

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During the recent years, the use of small animal models in in-vivo biomedical research has been growing. This has resulted in an emerging need for dedicated small animal imaging systems that provide better spatial resolution and sensitivity. Most small animal SPECT systems have been developed based on pinhole or multi-pinhole collimation technique as reported in the literature. Few dedicated small animal systems have been designed and developed based on parallel-hole collimation system.
The IBB-CNR of Rome, in collaboration of Peking University, College of Engineering trough the Department of Biomedical Engineering (BME), develop an innovative SPECT devices which will be within of Quad-modality Molecular Imaging System for small Animal. The technology, based on advanced method, it will serve to improve the performance of the instrumentation. The devices will soon be available for preliminary testing in the laboratory and will be tested for industrial applications in Chinese market.
The contract includes a research collaboration with CNR-IBB, through the development and delivery of 10 detectors for SPECT applications, to be applied in some industrial prototypes (for their use in molecular imaging research). This agreement opens the way for greater collaboration between the CNR-IBB and the University of Peking, to develop, jointly, diagnostic equipment for clinical use and radio-guided surgery.

SSR (Super Spatial Resolution) proposed method could be applied to improve the effective spatial resolution achievable. The our results confirm that it is possible to achieve optimal spatial resolution values at different depths, useful in small object and small animal imaging.
In this analysis, we will show ours preliminary opinions and design concepts for high spatial resolution SSR-SPECT for small animal imaging. The system was extensively evaluated utilizing GATE/GEANT4 Monte Carlo simulations.
This detector will perform high photon sensitivity through:
1. A new collimator-scintillation structure optimized for discrete gamma cameras;
2. An innovative resolution method (3D-SSR) that allows increasing the spatial resolution without penalize the detection sensitivity.
The objectives/outcomes for this project are the following:
1. Designing and testing of several collimator-scintillation structure in order to evaluate imaging performance with Monte Carlo simulations;
2. Implementation of an advanced 3D image reconstruction software;
3. The building of a proof-of-concept prototype of the optimized camera to evaluate the performance;
4. Designing the final detector.

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The activity is dedicated to realization of objects able to simulate the therapeutic behavior as well as the realization of prosthetic models and health facilities.

External Actor: Huong Elena Tran, tran.elena90@gmail.com

Huong Elena Tran. Elaboration of biomedical images for 3D printing: a tool for surgical planning. Master of Science in Biomedical Engineering , Faculty of Civil and Industrial Engineering . La Sapienza University , Rome.

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Neurodegenerative diseases are widespread pathologies of large social impact that include: prion, Alzheimer and Parkinson disease, Huntington chorea and amyotrophic lateral sclerosis. The onset of these diseases is commonly associated with the accumulation of insoluble amyloid plaques in specific neuronal population. In this scenario, research activities for the prevention and the treatment of these diseases are focused on two distinct directions: (a) the enhancement of factors that promote the survival and maintenance of nerve cells and (b) the definition of the molecular processes that lead to the onset of neurodegenerative diseases. In this framework, the activities here described are focused on the analysis of structural/dynamic determinants of the function of neuroprotective proteins (neurotrophins) (1, 2) and the study of structural properties of amyloid aggregates and their toxic precursors (3, 8). Computations carried out on neurotrophins have not only provided clues on the intrinsic dynamic features of these proteins, but they have also suggested strategies for the design and the development of new compounds of potential therapeutic interest (1, 2). Furthermore, Molecular dynamics simulations have provided valuable information on the conformational preferences of amyloid-like aggregates in non-crystalline environments. Notably, these investigations are also providing clues on the genesis of oligomeric amyloid-like states and on the structural basis of their toxicity.

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This activity comprises the development, evolution and tuning of a software tool that calculate relaxation rates and proton density (QMCI images) voxelwise in the knee and wrist, provided a suitable set of MRI acquisitions, and segment the tissues of various structures. The current version, tuned for 0. 25 Tesla, segments knee studies into the following 6 compartments: Bone; Cartilage; Muscle, Fat; Fluid and Low Proton Density tissue. The software furnishes volumetric and relaxometric information of each compartment. It also highlights the relaxation rates and proton density of the cartilage in a T1-w image to better show the pathology. This model based segmentation uses relaxation rates, proton density and anatomical information. The software is configurable and can be optimized in various environmental situations as different scanner characteristics and different anatomical regions (see also Relaxometry based MRI brain segmentation).

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This activity comprises the development and tuning of a software tool that can produce digital MRI brain phantoms, which simulate relaxation rate distributions of real target studies.
Digital brain phantoms are needed to assess the performance of segmentation methods, providing a gold standard, against which compare the segmentation produced by the softwares.
The phantom is composed of 17 tissue compartment and an optional abnormal white matter compartment, simulating MS lesions.
The software has four head models, two normal volunteers and two MS models. Currently the software allow to manually specify the mean signal intensities of the compartments, orientation, position, noise and other parameters or derive them from a target study, segmented automatically by our segmentation software, optionally warping the phantom to the target study.
Four sample phantoms, one for each model, and the custom phantoms are available for download at this link.


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Aim of this activity is to develop a software tool to measure skin sliding over the bones in human hand, to take this phenomenon into account in virtual reality reconstruction, by the use of sensible gloves. The problem was solved by coregistering the MRI hand acquisitions, taking into account only some selected bones, because the hand in the various acquisitions was in different configuration. Then the movement with respect to the bones of some vaseline references was measured. The program recognizes bones, references and other structure by dimension, shape and signal intensity. Further studies are needed to optimize the acquisition, the segmentation and the measures and to extend the sliding estimation to all the phalanxes.

Click for details.
This activity comprises the development, evolution and tuning of a software tool that calculate relaxation rates and proton density (QMCI images) voxelwise in the knee and wrist, provided a suitable set of MRI acquisitions, and segment the tissues of various structures. The current version, tuned for 0. 25 Tesla, segments knee studies into the following 6 compartments: Bone; Cartilage; Muscle, Fat; Fluid and Low Proton Density tissue. The software furnishes volumetric and relaxometric information of each compartment. It also highlights the relaxation rates and proton density of the cartilage in a T1-w image to better show the pathology. This model based segmentation uses relaxation rates, proton density and anatomical information. The software is configurable and can be optimized in various environmental situations as different scanner characteristics and different anatomical regions (see also Relaxometry based MRI brain segmentation).
Development, tuning and testing of a software tool that calculates MRI relaxation rates and proton density voxel-wise (QMCI images), and segments most of the brain tissues, including multiple sclerosis lesions.
The current version, validated at 1 and 1. 5 Tesla, segments brain studies into the following 18 compartments: Gray Matter (GM); White Matter (WM); demyelinized/abnormal WM (AWM); Cerebrospinal Fluid (CSF); Globus Pallidus; Putamen; Thalamus; Caudate Nucleus; Substantia Nigra; Red Nucleus; Dentate Nucleus; Muscle, Fat; Vitreous humor; Intra-Cranial and Extra-Cranial Connective tissues; Extra-Cranial Fluid; and Low Proton Density tissue. The software produces volumetric and relaxometric information of each compartment.
This model based segmentation uses relaxation rates, proton density and anatomical information.
The software is configurable and can be optimized in various environmental situations as different scanner characteristics and different anatomical regions (see also Relaxometry based MRI limb segmentation).
A module for automatic follow-up evaluation was also developed: it aligns basal and follow-up studies with rigid coregistration (normalized mutual information based of the SPM software), cuts out tissues not common to all studies and perform volumes and rates Pearson's analisys.
Application to neurological research: Aging; Alzheimer Disease; Schizophrenia; Degenerative disorders; Partial volume effect correction for PET and SPECT.
The improvements currently in testing phase include: 3T brain studies segmentation; Receiving and Transmission MRI inhomogeneity correction (critical for 3T studies); Automatic real flip angle estimation; Registration of misaligned semi-series. Affine registration of basal and follow-up to take into account MR gradient derive; Improved anatomical and signal model for brain studies.
Planned future improvements are: Fast Spin Echo support; T1w-like 3D FFE support; Other 3D fast sequences for rates maps; Further improved anatomical and signal model for brain studies; Iterative segmentation.

Click for details.
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Brain segmentation for radiation oncology application
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Characterization of the KCTD protein family: key factors in several biological processes
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Integration of the SPECT modules to innovative Quad-modality Molecular Imaging System for Small Animal (PET / SPECT / CT/ Fluorescence device)
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Anatomical modeling and 3D printers
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Characterization of neurotoxic and neuroprotective factors by using computational methodologies
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Relaxometry based MRI limb segmentation
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Software development of digital MRI brain phantom
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Hand MRI Coregistration and segmentation
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Relaxometry based MRI limb segmentation
Cardiovascular Diseases
Hematologic Diseases
Cancer Diseases
Quantitative Imaging
Technologies and techniques in medicine
Preclinical Imaging
Other Diseases
Relaxometry based MRI brain segmentation
< 1 2 3 4 5 6 7 8 9 10 >

Papers highlights
The 20S proteasome is a barrel-shaped enzymatic assembly playing a critical role in proteome maintenance. Access of proteasome substrates to the catalytic chamber is finely regulated through gating mechanisms which involve aromatic and negatively charged residues located at the N-terminal tails of α subunits. However, despite the importance of gates in regulating proteasome function, up to now very few molecules have been shown to interfere with the equilibrium by which the catalytic channel exchanges between the open and closed states. In this light, and inspired by previous results evidencing the antiproteasome potential of cationic porphyrins, here we combine experimental (enzyme kinetics, UV stopped flow and NMR) and computational (bioinformatic analysis and docking studies) approaches to inspect proteasome inhibition by meso-tetrakis(4-N-methylpyridyl)-porphyrin (H2T4) and its two ortho- and meta-isomers. We show that in a first, fast binding event H2T4 accommodates in a pocket made of negatively charged and aromatic residues present in α1 (Asp10, Phe9), α3 (Tyr5), α5 (Asp9, Tyr8), α6 (Asp7, Tyr6) and α7 (Asp9, Tyr8) subunits thereby stabilizing the closed conformation. A second, slower binding mode involves interaction with the grooves which separate the α- from the β-rings. Of note, the proteasome inhibition by ortho- and meta-H2T4 decreases significantly if compared to the parent compound, thus underscoring the role played by spatial distribution of the four peripheral positive charges in regulating proteasome–ligand interactions. We think that our results may pave the way to further studies aimed at rationalizing the molecular basis of novel, and more sophisticated, proteasome regulatory mechanisms.

Santoro AM et al. Chemical Science, 2016; 7: 1286-1297.
Purpose: A new MRI parameter representative of active tumor burden is proposed: diffusion volume (DV), defined as the sum of all the voxels within a tumor with apparent diffusion coefficient (ADC) values within a specific range.
The aims of the study were: (a) to calculate DV on ADC maps in patients with cervical/endometrial cancer; (b) to correlate DV with histological grade (G) and risk classification; (c) to evaluate intra/inter-observer agreement of DV calculation.

Materials and methods: Fifty-three patients with endometrial (n = 28) and cervical (n = 25) cancers under-went pelvic MRI with DWI sequences. Both endometrial and cervical tumors were classified on the basis of G (G1/G2/G3) and FIGO staging (low/medium/high-risk).
A semi-automated segmentation procedure was used to calculate the DV. A freehand closed ROI out-lined the whole visible tumor on the most representative slice of ADC maps defined as the slice with the maximum diameter of the solid neoplastic component. Successively, two thresholds were generated on the basis of the mean and standard deviation (SD) of the ADC values: lower threshold (LT = “mean minus three SD”) and higher threshold (HT = “mean plus one SD”). The closed ROI was expanded in 3D, including all the contiguous voxels with ADC values in the range LT-HT × 10–3 mm2/s.
A Kruskal–Wallis test was used to assess the differences in DV among G and risk groups. Intra-/inter-observer variability for DV measurement was analyzed according to the method of Bland and Altman and the intraclass-correlation–coefficient (ICC).

Results: DV values were significantly different among G and risk groups in both endometrial (p < 0.05) and cervical cancers (p ≤ 0.01). For endometrial cancer, DV of G1 (mean ± sd: 2.81 ± 3.21 cc) neoplasms were significantly lower than G2 (9.44 ± 9.58 cc) and G3 (11.96 ± 8.0 cc) ones; moreover, DV of low risk cancers (5.23 ± 8.0 cc) were significantly lower than medium (7.28 ± 4.3 cc) and high risk (14.7 ± 9.9 cc) ones.
For cervical cancer, DV of G1 (0.31 ± 0.13 cc) neoplasms was significantly lower than G3 (40.68 ± 45.65 cc) ones; moreover, DV of low risk neoplasms (6.98 ± 8.08 cc) was significantly lower than medium (21.7 ± 17.13 cc) and high risk (62.9 ± 51.12 cc) ones and DV of medium risk neoplasms was significantly lower than high risk ones.
The intra-/inter-observer variability for DV measurement showed an excellent correlation for both cancers (ICC ≥ 0.86).

Conclusions: DV is an accurate index for the assessment of G and risk classification of cervical/endometrial cancers with low intra-/inter-observer variability.



Mainenti PP et al. Eur J Radiol, 2016 Jan; 85(1): 113-124.

Representative sagittal summed (20-50 min) PET images obtained at the level of the brainstem in a symptomatic SOD1G93A mouse (125 days old) with a clinical score of 4 (a) and in a WT SOD1 control mouse (130 days old) (b) showing higher uptake of 18F-DPA-714 in the brainstem of the symptomatic SOD1G93A mouse (white arrows) as compared with the WT SOD1 control mouse.

Representative confocal laser scanning microscopy images of double-label immunofluorescence for TSPO and microglia in the facial nucleus of a symptomatic SOD1G93A mouse (125 days old) with a CS of 4 (c) and a WT SOD1 control mouse (130 days old) (d). The images show markedly higher levels of TSPO and Iba1 immunoreactivity in the symptomatic SOD1G93A mouse compared with the WT SOD1 control mouse.


Gargiulo S et al. Eur J Nucl Med Mol Imaging, 2016 Jan 27;
Despite the widespread use of cardiotocography in foetal monitoring, the evaluation of foetal status suffers from a considerable inter and intra-observer variability. In order to overcome the main limitations of visual cardiotocographic assessment, computerised methods to analyse cardiotocographic recordings have been recently developed. In this study, a new software for automated analysis of foetal heart rate is presented. It allows an automatic procedure for measuring the most relevant parameters derivable from cardiotocographic traces. Simulated and real cardiotocographic traces were analysed to test software reliability. In artificial traces, we simulated a set number of events (accelerations, decelerations and contractions) to be recognised. In the case of real signals, instead, results of the computerised analysis were compared with the visual assessment performed by 18 expert clinicians and three performance indexes were computed to gain information about performances of the proposed software. The software showed preliminary performance we judged satisfactory in that the results matched completely the requirements, as proved by tests on artificial signals in which all simulated events were detected from the software. Performance indexes computed in comparison with obstetricians' evaluations are, on the contrary, not so satisfactory; in fact they led to obtain the following values of the statistical parameters: sensitivity equal to 93%, positive predictive value equal to 82% and accuracy equal to 77%. Very probably this arises from the high variability of trace annotation carried out by clinicians.

Romano M et al. Comput Methods Programs Biomed, 2016 Feb; 124: 121-137.
The 20S proteasome is a barrel-shaped enzymatic assembly playing a critical role in proteome maintenance. Access of proteasome substrates to the catalytic chamber is finely regulated through gating mechanisms which involve aromatic and negatively charged residues located at the N-terminal tails of α subunits. However, despite the importance of gates in regulating proteasome function, up to now very few molecules have been shown to interfere with the equilibrium by which the catalytic channel exchanges between the open and closed states. In this light, and inspired by previous results evidencing the antiproteasome potential of cationic porphyrins, here we combine experimental (enzyme kinetics, UV stopped flow and NMR) and computational (bioinformatic analysis and docking studies) approaches to inspect proteasome inhibition by meso-tetrakis(4-N-methylpyridyl)-porphyrin (H2T4) and its two ortho- and meta-isomers. We show that in a first, fast binding event H2T4 accommodates in a pocket made of negatively charged and aromatic residues present in α1 (Asp10, Phe9), α3 (Tyr5), α5 (Asp9, Tyr8), α6 (Asp7, Tyr6) and α7 (Asp9, Tyr8) subunits thereby stabilizing the closed conformation. A second, slower binding mode involves interaction with the grooves which separate the α- from the β-rings. Of note, the proteasome inhibition by ortho- and meta-H2T4 decreases significantly if compared to the parent compound, thus underscoring the role played by spatial distribution of the four peripheral positive charges in regulating proteasome–ligand interactions. We think that our results may pave the way to further studies aimed at rationalizing the molecular basis of novel, and more sophisticated, proteasome regulatory mechanisms.

Santoro AM et al. Chemical Science, 2016; 7: 1286-1297.
Purpose: A new MRI parameter representative of active tumor burden is proposed: diffusion volume (DV), defined as the sum of all the voxels within a tumor with apparent diffusion coefficient (ADC) values within a specific range.
The aims of the study were: (a) to calculate DV on ADC maps in patients with cervical/endometrial cancer; (b) to correlate DV with histological grade (G) and risk classification; (c) to evaluate intra/inter-observer agreement of DV calculation.

Materials and methods: Fifty-three patients with endometrial (n = 28) and cervical (n = 25) cancers under-went pelvic MRI with DWI sequences. Both endometrial and cervical tumors were classified on the basis of G (G1/G2/G3) and FIGO staging (low/medium/high-risk).
A semi-automated segmentation procedure was used to calculate the DV. A freehand closed ROI out-lined the whole visible tumor on the most representative slice of ADC maps defined as the slice with the maximum diameter of the solid neoplastic component. Successively, two thresholds were generated on the basis of the mean and standard deviation (SD) of the ADC values: lower threshold (LT = “mean minus three SD”) and higher threshold (HT = “mean plus one SD”). The closed ROI was expanded in 3D, including all the contiguous voxels with ADC values in the range LT-HT × 10–3 mm2/s.
A Kruskal–Wallis test was used to assess the differences in DV among G and risk groups. Intra-/inter-observer variability for DV measurement was analyzed according to the method of Bland and Altman and the intraclass-correlation–coefficient (ICC).

Results: DV values were significantly different among G and risk groups in both endometrial (p < 0.05) and cervical cancers (p ≤ 0.01). For endometrial cancer, DV of G1 (mean ± sd: 2.81 ± 3.21 cc) neoplasms were significantly lower than G2 (9.44 ± 9.58 cc) and G3 (11.96 ± 8.0 cc) ones; moreover, DV of low risk cancers (5.23 ± 8.0 cc) were significantly lower than medium (7.28 ± 4.3 cc) and high risk (14.7 ± 9.9 cc) ones.
For cervical cancer, DV of G1 (0.31 ± 0.13 cc) neoplasms was significantly lower than G3 (40.68 ± 45.65 cc) ones; moreover, DV of low risk neoplasms (6.98 ± 8.08 cc) was significantly lower than medium (21.7 ± 17.13 cc) and high risk (62.9 ± 51.12 cc) ones and DV of medium risk neoplasms was significantly lower than high risk ones.
The intra-/inter-observer variability for DV measurement showed an excellent correlation for both cancers (ICC ≥ 0.86).

Conclusions: DV is an accurate index for the assessment of G and risk classification of cervical/endometrial cancers with low intra-/inter-observer variability.



Mainenti PP et al. Eur J Radiol, 2016 Jan; 85(1): 113-124.

Representative sagittal summed (20-50 min) PET images obtained at the level of the brainstem in a symptomatic SOD1G93A mouse (125 days old) with a clinical score of 4 (a) and in a WT SOD1 control mouse (130 days old) (b) showing higher uptake of 18F-DPA-714 in the brainstem of the symptomatic SOD1G93A mouse (white arrows) as compared with the WT SOD1 control mouse.

Representative confocal laser scanning microscopy images of double-label immunofluorescence for TSPO and microglia in the facial nucleus of a symptomatic SOD1G93A mouse (125 days old) with a CS of 4 (c) and a WT SOD1 control mouse (130 days old) (d). The images show markedly higher levels of TSPO and Iba1 immunoreactivity in the symptomatic SOD1G93A mouse compared with the WT SOD1 control mouse.


Gargiulo S et al. Eur J Nucl Med Mol Imaging, 2016 Jan 27;
Despite the widespread use of cardiotocography in foetal monitoring, the evaluation of foetal status suffers from a considerable inter and intra-observer variability. In order to overcome the main limitations of visual cardiotocographic assessment, computerised methods to analyse cardiotocographic recordings have been recently developed. In this study, a new software for automated analysis of foetal heart rate is presented. It allows an automatic procedure for measuring the most relevant parameters derivable from cardiotocographic traces. Simulated and real cardiotocographic traces were analysed to test software reliability. In artificial traces, we simulated a set number of events (accelerations, decelerations and contractions) to be recognised. In the case of real signals, instead, results of the computerised analysis were compared with the visual assessment performed by 18 expert clinicians and three performance indexes were computed to gain information about performances of the proposed software. The software showed preliminary performance we judged satisfactory in that the results matched completely the requirements, as proved by tests on artificial signals in which all simulated events were detected from the software. Performance indexes computed in comparison with obstetricians' evaluations are, on the contrary, not so satisfactory; in fact they led to obtain the following values of the statistical parameters: sensitivity equal to 93%, positive predictive value equal to 82% and accuracy equal to 77%. Very probably this arises from the high variability of trace annotation carried out by clinicians.

Romano M et al. Comput Methods Programs Biomed, 2016 Feb; 124: 121-137.
The 20S proteasome is a barrel-shaped enzymatic assembly playing a critical role in proteome maintenance. Access of proteasome substrates to the catalytic chamber is finely regulated through gating mechanisms which involve aromatic and negatively charged residues located at the N-terminal tails of α subunits. However, despite the importance of gates in regulating proteasome function, up to now very few molecules have been shown to interfere with the equilibrium by which the catalytic channel exchanges between the open and closed states. In this light, and inspired by previous results evidencing the antiproteasome potential of cationic porphyrins, here we combine experimental (enzyme kinetics, UV stopped flow and NMR) and computational (bioinformatic analysis and docking studies) approaches to inspect proteasome inhibition by meso-tetrakis(4-N-methylpyridyl)-porphyrin (H2T4) and its two ortho- and meta-isomers. We show that in a first, fast binding event H2T4 accommodates in a pocket made of negatively charged and aromatic residues present in α1 (Asp10, Phe9), α3 (Tyr5), α5 (Asp9, Tyr8), α6 (Asp7, Tyr6) and α7 (Asp9, Tyr8) subunits thereby stabilizing the closed conformation. A second, slower binding mode involves interaction with the grooves which separate the α- from the β-rings. Of note, the proteasome inhibition by ortho- and meta-H2T4 decreases significantly if compared to the parent compound, thus underscoring the role played by spatial distribution of the four peripheral positive charges in regulating proteasome–ligand interactions. We think that our results may pave the way to further studies aimed at rationalizing the molecular basis of novel, and more sophisticated, proteasome regulatory mechanisms.

Santoro AM et al. Chemical Science, 2016; 7: 1286-1297.
Purpose: A new MRI parameter representative of active tumor burden is proposed: diffusion volume (DV), defined as the sum of all the voxels within a tumor with apparent diffusion coefficient (ADC) values within a specific range.
The aims of the study were: (a) to calculate DV on ADC maps in patients with cervical/endometrial cancer; (b) to correlate DV with histological grade (G) and risk classification; (c) to evaluate intra/inter-observer agreement of DV calculation.

Materials and methods: Fifty-three patients with endometrial (n = 28) and cervical (n = 25) cancers under-went pelvic MRI with DWI sequences. Both endometrial and cervical tumors were classified on the basis of G (G1/G2/G3) and FIGO staging (low/medium/high-risk).
A semi-automated segmentation procedure was used to calculate the DV. A freehand closed ROI out-lined the whole visible tumor on the most representative slice of ADC maps defined as the slice with the maximum diameter of the solid neoplastic component. Successively, two thresholds were generated on the basis of the mean and standard deviation (SD) of the ADC values: lower threshold (LT = “mean minus three SD”) and higher threshold (HT = “mean plus one SD”). The closed ROI was expanded in 3D, including all the contiguous voxels with ADC values in the range LT-HT × 10–3 mm2/s.
A Kruskal–Wallis test was used to assess the differences in DV among G and risk groups. Intra-/inter-observer variability for DV measurement was analyzed according to the method of Bland and Altman and the intraclass-correlation–coefficient (ICC).

Results: DV values were significantly different among G and risk groups in both endometrial (p < 0.05) and cervical cancers (p ≤ 0.01). For endometrial cancer, DV of G1 (mean ± sd: 2.81 ± 3.21 cc) neoplasms were significantly lower than G2 (9.44 ± 9.58 cc) and G3 (11.96 ± 8.0 cc) ones; moreover, DV of low risk cancers (5.23 ± 8.0 cc) were significantly lower than medium (7.28 ± 4.3 cc) and high risk (14.7 ± 9.9 cc) ones.
For cervical cancer, DV of G1 (0.31 ± 0.13 cc) neoplasms was significantly lower than G3 (40.68 ± 45.65 cc) ones; moreover, DV of low risk neoplasms (6.98 ± 8.08 cc) was significantly lower than medium (21.7 ± 17.13 cc) and high risk (62.9 ± 51.12 cc) ones and DV of medium risk neoplasms was significantly lower than high risk ones.
The intra-/inter-observer variability for DV measurement showed an excellent correlation for both cancers (ICC ≥ 0.86).

Conclusions: DV is an accurate index for the assessment of G and risk classification of cervical/endometrial cancers with low intra-/inter-observer variability.



Mainenti PP et al. Eur J Radiol, 2016 Jan; 85(1): 113-124.

Representative sagittal summed (20-50 min) PET images obtained at the level of the brainstem in a symptomatic SOD1G93A mouse (125 days old) with a clinical score of 4 (a) and in a WT SOD1 control mouse (130 days old) (b) showing higher uptake of 18F-DPA-714 in the brainstem of the symptomatic SOD1G93A mouse (white arrows) as compared with the WT SOD1 control mouse.

Representative confocal laser scanning microscopy images of double-label immunofluorescence for TSPO and microglia in the facial nucleus of a symptomatic SOD1G93A mouse (125 days old) with a CS of 4 (c) and a WT SOD1 control mouse (130 days old) (d). The images show markedly higher levels of TSPO and Iba1 immunoreactivity in the symptomatic SOD1G93A mouse compared with the WT SOD1 control mouse.


Gargiulo S et al. Eur J Nucl Med Mol Imaging, 2016 Jan 27;
Despite the widespread use of cardiotocography in foetal monitoring, the evaluation of foetal status suffers from a considerable inter and intra-observer variability. In order to overcome the main limitations of visual cardiotocographic assessment, computerised methods to analyse cardiotocographic recordings have been recently developed. In this study, a new software for automated analysis of foetal heart rate is presented. It allows an automatic procedure for measuring the most relevant parameters derivable from cardiotocographic traces. Simulated and real cardiotocographic traces were analysed to test software reliability. In artificial traces, we simulated a set number of events (accelerations, decelerations and contractions) to be recognised. In the case of real signals, instead, results of the computerised analysis were compared with the visual assessment performed by 18 expert clinicians and three performance indexes were computed to gain information about performances of the proposed software. The software showed preliminary performance we judged satisfactory in that the results matched completely the requirements, as proved by tests on artificial signals in which all simulated events were detected from the software. Performance indexes computed in comparison with obstetricians' evaluations are, on the contrary, not so satisfactory; in fact they led to obtain the following values of the statistical parameters: sensitivity equal to 93%, positive predictive value equal to 82% and accuracy equal to 77%. Very probably this arises from the high variability of trace annotation carried out by clinicians.

Romano M et al. Comput Methods Programs Biomed, 2016 Feb; 124: 121-137.


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