A Food Recognition System for Diabetic Patients based on an Optimized Bag of Features Model

Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5,000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10,000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Atomistic simulations of 2D bicomponent self-assembly: from molecular recognition to self-healing

Supramolecular two-dimensional engineering epitomizes the design of complex molecular architectures through recognition events in multicomponent self-assembly. Despite being the subject of in-depth experimental studies, such articulated phenomena have not been yet elucidated in time and space with atomic precision. Here we use atomistic molecular dynamics to simulate the recognition of complementary hydrogen-bonding modules forming 2D porous networks on graphite. We describe the transition path from the melt to the crystalline hexagonal phase and show that self-assembly proceeds through a series of intermediate states featuring a plethora of polygonal types. Finally, we design a novel bicomponent system possessing kinetically improved self-healing ability in silico, thus demonstrating that a priori engineering of 2D self-assembly is possible.

Pathogen recognition by the long pentraxin PTX3

Innate immunity represents the first line of defence against pathogens and plays key roles in activation and orientation of the adaptive immune response. The innate immune system comprises both a cellular and a humoral arm. Components of the humoral arm include soluble pattern recognition molecules (PRMs) that recognise pathogen-associated molecular patterns (PAMPs) and initiate the immune response in coordination with the cellular arm, therefore acting as functional ancestors of antibodies. The long pentraxin PTX3 is a prototypic soluble PRM that is produced at sites of infection and inflammation by both somatic and immune cells. Gene targeting of this evolutionarily conserved protein has revealed a nonredundant role in resistance to selected pathogens. Moreover, PTX3 exerts important functions at the cross-road between innate immunity, inflammation, and female fertility. Here, we review the studies on PTX3, with emphasis on pathogen recognition and cross-talk with other components of the innate immune system.

The therapeutic potential of the humoral pattern recognition molecule PTX3 in chronic lung infection caused by Pseudomonas aeruginosa

Chronic lung infections by Pseudomonas aeruginosa strains are a major cause of morbidity and mortality in cystic fibrosis (CF) patients. Although there is no clear evidence for a primary defect in the immune system of CF patients, the host is generally unable to clear P. aeruginosa from the airways. PTX3 is a soluble pattern recognition receptor that plays nonredundant roles in the innate immune response to fungi, bacteria, and viruses. In particular, PTX3 deficiency is associated with increased susceptibility to P. aeruginosa lung infection. To address the potential therapeutic effect of PTX3 in P. aeruginosa lung infection, we established persistent and progressive infections in mice with the RP73 clinical strain RP73 isolated from a CF patient and treated them with recombinant human PTX3. The results indicated that PTX3 has a potential therapeutic effect in P. aeruginosa chronic lung infection by reducing lung colonization, proinflammatory cytokine levels (CXCL1, CXCL2, CCL2, and IL-1β), and leukocyte recruitment in the airways. In models of acute infections and in in vitro assays, the prophagocytic effect of PTX3 was maintained in C1q-deficient mice and was lost in C3- and Fc common γ-chain-deficient mice, suggesting that facilitated recognition and phagocytosis of pathogens through the interplay between complement and FcγRs are involved in the therapeutic effect mediated by PTX3. These data suggested that PTX3 is a potential therapeutic tool in chronic P. aeruginosa lung infections, such as those seen in CF patients.

The intracellular Ig fold: a robust protein scaffold for the engineering of molecular recognition

Protein scaffolds that support molecular recognition have multiple applications in biotechnology. Thus, protein frames with robust structural cores but adaptable surface loops are in continued demand. Recently, notable progress has been made in the characterization of Ig domains of intracellular origin--in particular, modular components of the titin myofilament. These Ig belong to the I(intermediate)-type, are remarkably stable, highly soluble and undemanding to produce in the cytoplasm of Escherichia coli. Using the Z1 domain from titin as representative, we show that the I-Ig fold tolerates the drastic diversification of its CD loop, constituting an effective peptide display system. We examine the stability of CD-loop-grafted Z1-peptide chimeras using differential scanning fluorimetry, Fourier transform infrared spectroscopy and nuclear magnetic resonance and demonstrate that the introduction of bioreactive affinity binders in this position does not compromise the structural integrity of the domain. Further, the binding efficiency of the exogenous peptide sequences in Z1 is analyzed using pull-down assays and isothermal titration calorimetry. We show that an internally grafted, affinity FLAG tag is functional within the context of the fold, interacting with the anti-FLAG M2 antibody in solution and in affinity gel. Together, these data reveal the potential of the intracellular Ig scaffold for targeted functionalization.

A Novel Implantable Hearing System with Direct Acoustic Cochlear Stimulation

A new implantable hearing system, the direct acoustic cochlear stimulator (DACS) is presented. This system is based on the principle of a power-driven stapes prosthesis and intended for the treatment of severe mixed hearing loss due to advanced otosclerosis. It consists of an implantable electromagnetic transducer, which transfers acoustic energy directly to the inner ear, and an audio processor worn externally behind the implanted ear. The device is implanted using a specially developed retromeatal microsurgical approach. After removal of the stapes, a conventional stapes prosthesis is attached to the transducer and placed in the oval window to allow direct acoustical coupling to the perilymph of the inner ear. In order to restore the natural sound transmission of the ossicular chain, a second stapes prosthesis is placed in parallel to the first one into the oval window and attached to the patient's own incus, as in a conventional stapedectomy. Four patients were implanted with an investigational DACS device. The hearing threshold of the implanted ears before implantation ranged from 78 to 101 dB (air conduction, pure tone average, 0.5-4 kHz) with air-bone gaps of 33-44 dB in the same frequency range. Postoperatively, substantial improvements in sound field thresholds, speech intelligibility as well as in the subjective assessment of everyday situations were found in all patients. Two years after the implantations, monosyllabic word recognition scores in quiet at 75 dB improved by 45-100 percent points when using the DACS. Furthermore, hearing thresholds were already improved by the second stapes prosthesis alone by 14-28 dB (pure tone average 0.5-4 kHz, DACS switched off). No device-related serious medical complications occurred and all patients have continued to use their device on a daily basis for over 2 years. Copyright (c) 2008 S. Karger AG, Basel.

Virtual reality ultrasound imaging of the normal and abnormal fetal central nervous system

OBJECTIVES: In fetal ultrasound imaging, teaching and experience are of paramount importance to improve prenatal detection rates of fetal abnormalities. Yet both aspects depend on exposure to normal and, in particular, abnormal 'specimens'. We aimed to generate a number of simple virtual reality (VR) objects of the fetal central nervous system for use as educational tools. METHODS: We applied a recently proposed algorithm for the generation of fetal VR object movies to the normal and abnormal fetal brain and spine. Interactive VR object movies were generated from ultrasound volume data from normal fetuses and fetuses with typical brain or spine anomalies. Pathognomonic still images from all object movies were selected and annotated to enable recognition of these features in the object movies. RESULTS: Forty-six virtual reality object movies from 22 fetuses (two with normal and 20 with abnormal brains) were generated in an interactive display format (QuickTime) and key images were annotated. The resulting .mov files are available for download from the website of this journal. CONCLUSIONS: VR object movies can be generated from educational ultrasound volume datasets, and may prove useful for teaching and learning normal and abnormal fetal anatomy.

Evaluating retraining rules for semi-supervised learning in neural network based cursive word recognition

Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, including the generation of the ground truth, is tedious and costly. One way of reducing the high cost of labeled training data acquisition is to exploit unlabeled data, which can be gathered easily. Making use of both labeled and unlabeled data is known as semi-supervised learning. One of the most general versions of semi-supervised learning is self-training, where a recognizer iteratively retrains itself on its own output on new, unlabeled data. In this paper we propose to apply semi-supervised learning, and in particular self-training, to the problem of cursive, handwritten word recognition. The special focus of the paper is on retraining rules that define what data are actually being used in the retraining phase. In a series of experiments it is shown that the performance of a neural network based recognizer can be significantly improved through the use of unlabeled data and self-training if appropriate retraining rules are applied.

Sweet's syndrome involoving the musculoskeletal system during treatment of promyelocytic leukemia with all-trans retinoic acid

Induction therapy of promyelocytic leukemia with all-trans retinoic acid is a standard therapy despite significant side-effects. The most important, the "retinoic acid syndrome", consists of a hyperinflammatory reaction with capillary leakage (edema, pleural, and pericardial effusion), infiltration of myeloid cells into internal organs and systemic signs of inflammation. We describe here two cases of another hyperinflammatory reaction during all-trans retinoic acid therapy, the Sweet's syndrome, consisting of infiltrates of the skin and internal organs by neutrophilic granulocytes. Fever, painful erythematous cutaneous plaques, prominent musculoskeletal involvement (myositis, fasciitis), a sterile pulmonary infiltration and intercurrent proteinuria characterized the clinical course of all-trans retinoic acid-associated Sweet's syndrome. Treatment with glucocorticoids led to resolution of the syndrome within 48 h. Three other cases of all-trans retinoic acid-associated Sweet's syndrome without involvement of internal organs, prominent on our cases, were published previously. Recognition of ATRA-associated Sweet's syndrome is of practical importance.