Absence and hypoplasia of the mental foramen detected in CBCT images: a case report

The mental foramen (MF) is an important anatomic landmark of the mandible, through which the mental nerve and blood vessels emerge. The importance of MF in dental practice is especially related to dental implants placement and other surgical procedures in the region. It is fundamental to be careful in order to avoid nerve and vessels injury during procedures. Anatomic variations of the MF can be found, such as occurrence of multiple foramina and unusual location. In very rare occasions, the absence of MF can be detected. The observation of this variation is not always possible using only conventional radiographs. The modern imaging resource cone beam computed tomography (CBCT) allows an accurate three-dimensional assessment of MF, as well as the identification of its variations. The aim of this article is to report MF absence and hypoplasia detected in CBCT images of a 27-year-old daughter and her 63-year-old mother, both from Brazil. Despite the MF anatomic variations, they presented no sensorial disturbance in the regions supplied by the mental nerve.

MART-1 peptide vaccination plus IMP321 (LAG-3Ig fusion protein) in patients receiving autologous PBMCs after lymphodepletion: results of a Phase I trial.

BACKGROUND: Immunotherapy offers a promising novel approach for the treatment of cancer and both adoptive T-cell transfer and immune modulation lead to regression of advanced melanoma. However, the potential synergy between these two strategies remains unclear. METHODS: We investigated in 12 patients with advanced stage IV melanoma the effect of multiple MART-1 analog peptide vaccinations with (n = 6) or without (n = 6) IMP321 (LAG-3Ig fusion protein) as an adjuvant in combination with lymphodepleting chemotherapy and adoptive transfer of autologous PBMCs at day (D) 0 (Trial registration No: NCT00324623). All patients were selected on the basis of ex vivo detectable MART-1-specific CD8 T-cell responses and immunized at D0, 8, 15, 22, 28, 52, and 74 post-reinfusion. RESULTS: After immunization, a significant expansion of MART-1-specific CD8 T cells was measured in 83% (n = 5/6) and 17% (n = 1/6) of patients from the IMP321 and control groups, respectively (P < 0.02). Compared to the control group, the mean fold increase of MART-1-specific CD8 T cells in the IMP321 group was respectively >2-, >4- and >6-fold higher at D15, D30 and D60 (P < 0.02). Long-lasting MART-1-specific CD8 T-cell responses were significantly associated with IMP321 (P < 0.02). At the peak of the response, MART-1-specific CD8 T cells contained higher proportions of effector (CCR7⁻ CD45RA⁺/⁻) cells in the IMP321 group (P < 0.02) and showed no sign of exhaustion (i.e. were mostly PD1⁻CD160⁻TIM3⁻LAG3⁻2B4⁺/⁻). Moreover, IMP321 was associated with a significantly reduced expansion of regulatory T cells (P < 0.04); consistently, we observed a negative correlation between the relative expansion of MART-1-specific CD8 T cells and of regulatory T cells. Finally, although there were no confirmed responses as per RECIST criteria, a transient, 30-day partial response was observed in a patient from the IMP321 group. CONCLUSIONS: Vaccination with IMP321 as an adjuvant in combination with lymphodepleting chemotherapy and adoptive transfer of autologous PBMCs induced more robust and durable cellular antitumor immune responses, supporting further development of IMP321 as an adjuvant for future immunotherapeutic strategies.

Role of the V-ATPase in regulation of the vacuolar fission-fusion equilibrium.

Like numerous other eukaryotic organelles, the vacuole of the yeast Saccharomyces cerevisiae undergoes coordinated cycles of membrane fission and fusion in the course of the cell cycle and in adaptation to environmental conditions. Organelle fission and fusion processes must be balanced to ensure organelle integrity. Coordination of vacuole fission and fusion depends on the interactions of vacuolar SNARE proteins and the dynamin-like GTPase Vps1p. Here, we identify a novel factor that impinges on the fusion-fission equilibrium: the vacuolar H(+)-ATPase (V-ATPase) performs two distinct roles in vacuole fission and fusion. Fusion requires the physical presence of the membrane sector of the vacuolar H(+)-ATPase sector, but not its pump activity. Vacuole fission, in contrast, depends on proton translocation by the V-ATPase. Eliminating proton pumping by the V-ATPase either pharmacologically or by conditional or constitutive V-ATPase mutations blocked salt-induced vacuole fragmentation in vivo. In living cells, fission defects are epistatic to fusion defects. Therefore, mutants lacking the V-ATPase display large single vacuoles instead of multiple smaller vacuoles, the phenotype that is generally seen in mutants having defects only in vacuolar fusion. Its dual involvement in vacuole fission and fusion suggests the V-ATPase as a potential regulator of vacuolar morphology and membrane dynamics.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

A Quantitative method for the characterization of lytic metastases of the bone from radiographic images

The aim of our study was to assess the diagnostic usefulness of the gray level parameters to distinguish osteolytic lesions using radiological images. Materials and Methods: A retrospective study was carried out. A total of 76 skeletal radiographs of osteolytic metastases and 67 radiographs of multiple myeloma were used. The cases were classified into nonflat (MM1 and OL1) and flat bones (MM2 and OL2). These radiological images were analyzed by using a computerized method. The parameters calculated were mean, standard deviation, and coefficient of variation (MGL, SDGL, and CVGL) based on gray level histogram analysis of a region-of-interest.Diagnostic utility was quantified bymeasurement of parameters on osteolyticmetastases andmultiplemyeloma, yielding quantification of area under the receiver operating characteristic (ROC) curve (AUC). Results: Flat bone groups (MM2 and OL2) showed significant differences in mean values of MGL ( = 0.048) and SDGL ( = 0.003). Their corresponding values of AUC were 0.758 for MGL and 0.883 for SDGL in flat bones. In nonflat bones these gray level parameters do not show diagnostic ability. Conclusion: The gray level parametersMGL and SDGL show a good discriminatory diagnostic ability to distinguish between multiple myeloma and lytic metastases in flat bones.

Automatic segmentation and classification of human intestinal parasites from microscopy images

Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

Improved Localization of Implanted Subdural Electrode Contacts on MRI Using an Elastic Image Fusion Algorithm in Invasive EEG Recording

BACKGROUND: Accurate projection of implanted subdural electrode contacts in presurgical evaluation of pharmacoresistant epilepsy cases by invasive EEG is highly relevant. Linear fusion of CT and MRI images may display the contacts in the wrong position due to brain shift effects. OBJECTIVE: A retrospective study in five patients with pharmacoresistant epilepsy was performed to evaluate whether an elastic image fusion algorithm can provide a more accurate projection of the electrode contacts on the pre-implantation MRI as compared to linear fusion. METHODS: An automated elastic image fusion algorithm (AEF), a guided elastic image fusion algorithm (GEF), and a standard linear fusion algorithm (LF) were used on preoperative MRI and post-implantation CT scans. Vertical correction of virtual contact positions, total virtual contact shift, corrections of midline shift and brain shifts due to pneumencephalus were measured. RESULTS: Both AEF and GEF worked well with all 5 cases. An average midline shift of 1.7mm (SD 1.25) was corrected to 0.4mm (SD 0.8) after AEF and to 0.0mm (SD 0) after GEF. Median virtual distances between contacts and cortical surface were corrected by a significant amount, from 2.3mm after LF to 0.0mm after AEF and GEF (p<.001). Mean total relative corrections of 3.1 mm (SD 1.85) after AEF and 3.0mm (SD 1.77) after GEF were achieved. The tested version of GEF did not achieve a satisfying virtual correction of pneumencephalus. CONCLUSION: The technique provided a clear improvement in fusion of pre- and post-implantation scans, although the accuracy is difficult to evaluate.

SNARE-fusion mediated insertion of membrane proteins into native and artificial membranes

Membrane proteins carry out functions such as nutrient uptake, ATP synthesis or transmembrane signal transduction. An increasing number of reports indicate that cellular processes are underpinned by regulated interactions between these proteins. Consequently, functional studies of these networks at a molecular level require co-reconstitution of the interacting components. Here, we report a SNARE protein-based method for incorporation of multiple membrane proteins into artificial membrane vesicles of well-defined composition, and for delivery of large water-soluble substrates into these vesicles. The approach is used for in vitro reconstruction of a fully functional bacterial respiratory chain from purified components. Furthermore, the method is used for functional incorporation of the entire F1F0 ATP synthase complex into native bacterial membranes from which this component had been genetically removed. The novel methodology offers a tool to investigate complex interaction networks between membrane-bound proteins at a molecular level, which is expected to generate functional insights into key cellular functions.

SNARE-fusion mediated inserton of membrane proteins into native and artificial membranes

Membrane proteins carry out functions such as nutrient uptake, ATP synthesis or transmembrane signal transduction. An increasing number of reports indicate that cellular processes are underpinned by regulated interactions between these proteins. Consequently, functional studies of these networks at a molecular level require co-reconstitution of the interacting components. Here, we report a SNARE-protein based method for incorporation of multiple membrane proteins into membranes, and for delivery of large water-soluble substrates into closed membrane vesicles. The approach is used for in vitro reconstruction of a fully functional bacterial respiratory chain from purified components. Furthermore, the method is used for functional incorporation of the entire F1F0-ATP synthase complex into native bacterial membranes from which this component had been genetically removed. The novel methodology offers a tool to investigate complex interaction networks between membrane-bound proteins at a molecular level, which is expected to generate functional insights into key cellular functions.

Quantification of Mitral Regurgitation with Multiple Jets: In Vitro Comparison of Two-dimensional PISA techniques

Purpose: Traditionally, the proximal isovelocity surface area (PISA) is based on the assumption of a single hemisphere (hemispheric PISA), but this technique has not been validated for the quantification of mitral regurgitation (MR) with multiple jets. Methods: The left heart simulator was actuated by a pulsatile pump at various stroke amplitudes. The regurgitant volume (Rvol) passing through the mitral valve phantoms with single and double regurgitant orifices of varying size and interspace was quantified by a flowmeter as reference technique. Color Doppler 3-D full-volumes were obtained, and Rvol were derived from 2-D PISA surfaces on the basis of hemispheric and hemicylindric assumption with one base (partial hemicylindric PISA) or 2 bases (total hemicylindric PISA). Results: 72 regurgitant volumes (Rvol range: 8 to 76 ml/beat) were obtained. Hemispheric PISA Rvol correlated well with reference Rvol by one orifice (R²=0.97; bias -2.7±3.2ml), but less by ≥ one orifice (R²=0.89). When a fusion of two PISAs occured, addition of two hemispheric PISA overestimated Rvol (bias 9.1±12.2ml, fig.1), and single hemispheric PISA underestimated Rvol (bias -12.4±4.9ml). If an integrated approach was used (hemispheric in single orifice, total hemicylindric in two non-fused PISAs and partial hemicylindric in two fused PISAs), the correlation was R²=0.95, bias -1.6±5.6ml (fig.2). In the ROC analysis, the cutoff to detect ≥ moderate-to-severe Rvol (≥45ml) was 42ml (AUC 0.99, sens. 100%, spec. 93%). Conclusions: In MR with two regurgitant jets, the 2-D hemicylindric assumption of the PISA offers a better quantification of Rvol than the hemispheric assumption. Quantification of MR using 2-D PISA requires an integrated approach that considers number of regurgitant orifices and fusion of the PISAs.

Spatial database of canopy plant densities created from satellite images over Galapagos in 2011, with intent to manage invasive species

Mapping is an important tool for the management of plant invasions. If landscapes are mapped in an appropriate way, results can help managers decide when and where to prioritize their efforts. We mapped vegetation with the aim of providing key information for managers on the extent, density and rates of spread of multiple invasive species across the landscape. Our case study focused on an area of Galapagos National Park that is faced with the challenge of managing multiple plant invasions. We used satellite imagery to produce a spatially-explicit database of plant species densities in the canopy, finding that 92% of the humid highlands had some degree of invasion and 41% of the canopy was comprised of invasive plants. We also calculated the rate of spread of eight invasive species using known introduction dates, finding that species with the most limited dispersal ability had the slowest spread rates while those able to disperse long distances had a range of spread rates. Our results on spread rate fall at the lower end of the range of published spread rates of invasive plants. This is probably because most studies are based on the entire geographic extent, whereas our estimates took plant density into account. A spatial database of plant species densities, such as the one developed in our case study, can be used by managers to decide where to apply management actions and thereby help curtail the spread of current plant invasions. For example, it can be used to identify sites containing several invasive plant species, to find the density of a particular species across the landscape or to locate where native species make up the majority of the canopy. Similar databases could be developed elsewhere to help inform the management of multiple plant invasions over the landscape.

Multisensor data fusion for accurate modelling of mobile objects

In the last decade, multi-sensor data fusion has become a broadly demanded discipline to achieve advanced solutions that can be applied in many real world situations, either civil or military. In Defence,accurate detection of all target objects is fundamental to maintaining situational awareness, to locating threats in the battlefield and to identifying and protecting strategically own forces. Civil applications, such as traffic monitoring, have similar requirements in terms of object detection and reliable identification of incidents in order to ensure safety of road users. Thanks to the appropriate data fusion technique, we can give these systems the power to exploit automatically all relevant information from multiple sources to face for instance mission needs or assess daily supervision operations. This paper focuses on its application to active vehicle monitoring in a particular area of high density traffic, and how it is redirecting the research activities being carried out in the computer vision, signal processing and machine learning fields for improving the effectiveness of detection and tracking in ground surveillance scenarios in general. Specifically, our system proposes fusion of data at a feature level which is extracted from a video camera and a laser scanner. In addition, a stochastic-based tracking which introduces some particle filters into the model to deal with uncertainty due to occlusions and improve the previous detection output is presented in this paper. It has been shown that this computer vision tracker contributes to detect objects even under poor visual information. Finally, in the same way that humans are able to analyze both temporal and spatial relations among items in the scene to associate them a meaning, once the targets objects have been correctly detected and tracked, it is desired that machines can provide a trustworthy description of what is happening in the scene under surveillance. Accomplishing so ambitious task requires a machine learning-based hierarchic architecture able to extract and analyse behaviours at different abstraction levels. A real experimental testbed has been implemented for the evaluation of the proposed modular system. Such scenario is a closed circuit where real traffic situations can be simulated. First results have shown the strength of the proposed system.

Echo-delay resolution in sonar images of the big brown bat, Eptesicus fuscus

Echolocating big brown bats (Eptesicus fuscus) broadcast ultrasonic frequency-modulated (FM) biosonar sounds (20–100 kHz frequencies; 10–50 μs periods) and perceive target range from echo delay. Knowing the acuity for delay resolution is essential to understand how bats process echoes because they perceive target shape and texture from the delay separation of multiple reflections. Bats can separately perceive the delays of two concurrent electronically generated echoes arriving as little as 2 μs apart, thus resolving reflecting points as close together as 0.3 mm in range (two-point threshold). This two-point resolution is roughly five times smaller than the shortest periods in the bat’s sounds. Because the bat’s broadcasts are 2,000–4,500 μs long, the echoes themselves overlap and interfere with each other, to merge together into a single sound whose spectrum is shaped by their mutual interference depending on the size of the time separation. To separately perceive the delays of overlapping echoes, the bat has to recover information about their very small delay separation that was transferred into the spectrum when the two echoes interfered with each other, thus explicitly reconstructing the range profile of targets from the echo spectrum. However, the bat’s 2-μs resolution limit is so short that the available spectral cues are extremely limited. Resolution of delay seems overly sharp just for interception of flying insects, which suggests that the bat’s biosonar images are of higher quality to suit a wider variety of orientation tasks, and that biosonar echo processing is correspondingly more sophisticated than has been suspected.

Indexing and integrating multiple features for WWW images

In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index image's multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partition's center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images have similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the dimensionality curse existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms image's text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partition's center. Such BS representations are small in size and fast for comparison since only bit operation are involved. By comparing common bits existing in two BSs, most of irrelevant images can be immediately filtered. To effectively integrate multi-features, we also investigated the following evidence combination techniques-Certainty Factor, Dempster Shafer Theory, Compound Probability, and Linear Combination. Our extensive experiment showed that single one-dimensional index on multi-features improves multi-indices on multi-features greatly. Our LBS method outperforms sequential scan on high dimensional space by an order of magnitude. And Certainty Factor and Dempster Shafer Theory perform best in combining multiple similarities from corresponding multiple features.

Evaluation of a method for fusing LIDAR data and multispectral images for building detection

In this paper, we describe the evaluation of a method for building detection by the Dempster-Shafer fusion of LIDAR data and multispectral images. For that purpose, ground truth was digitised for two test sites with quite different characteristics. Using these data sets, the heuristic model for the probability mass assignments of the method is validated, and rules for the tuning of the parameters of this model are discussed. Further we evaluate the contributions of the individual cues used in the classification process to the quality of the classification results. Our results show the degree to which the overall correctness of the results can be improved by fusing LIDAR data with multispectral images.