Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

Glucocorticoid-induced tumor necrosis factor receptor expression in patients with cervical human papillomavirus infection

Introduction The progression of human papillomavirus (HPV) infection in the anogenital tract has been associated with the involvement of cells with regulatory properties. Evidence has shown that glucocorticoid-induced tumor necrosis factor receptor (GITR) is an important surface molecule for the characterization of these cells and proposes that GITR ligand may constitute a rational treatment for many cancer types. We aimed to detect the presence of GITR and CD25 in cervical stroma cells with and without pathological changes or HPV infection to better understand the immune response in the infected tissue microenvironment. Methods We subjected 49 paraffin-embedded cervical tissue samples to HPV DNA detection and histopathological analysis, and subsequently immunohistochemistry to detect GITR and CD25 in lymphocytes. Results We observed that 76.9% of all samples with high GITR expression were HPV-positive regardless of histopathological findings. High GITR expression (77.8%) was predominant in samples with ≥1,000 RLU/PCB. Of the HPV-positive samples negative for intraepithelial lesion and malignancy, 62.5% had high GITR expression. High GITR expression was observed in both carcinoma and high-grade squamous intraepithelial lesion (HSIL) samples (p = 0.16). CD25 was present in great quantities in all samples. Conclusions The predominance of high GITR expression in samples with high viral load that were classified as HSIL and carcinoma suggests that GITR+ cells can exhibit regulatory properties and may contribute to the progression of HPV-induced cervical neoplasia, emphasizing the importance of GITR as a potential target for immune therapy of cervical cancer and as a disease evolution biomarker.

Immune reconstitution inflammatory syndrome in HIV and sporotrichosis coinfection: report of two cases and review of the literature

We report 2 cases of patients with immune reconstitution inflammatory syndrome (IRIS) associated with cutaneous disseminated sporotrichosis and human immunodeficiency virus (HIV) coinfection. The patients received specific treatment for sporotrichosis. However, after 4 and 5 weeks from the beginning of antiretroviral therapy, both patients experienced clinical exacerbation of skin lesions despite increased T CD4+ cells (T cells cluster of differentiation 4 positive) count and decreased viral load. Despite this exacerbation, subsequent mycological examination after systemic corticosteroid administration did not reveal fungal growth. Accordingly, they were diagnosed with IRIS. However, the sudden withdrawal of the corticosteroids resulted in the recurrence of IRIS symptoms. No serious adverse effects could be attributed to prednisone. We recommend corticosteroid treatment for mild-to-moderate cases of IRIS in sporotrichosis and HIV coinfection with close follow-up.

New delivery systems for amphotericin B applied to the improvement of leishmaniasis treatment

Leishmaniasis is one of the six major tropical diseases targeted by the World Health Organization. It is a life-threatening disease of medical, social and economic importance in endemic areas. No vaccine is yet available for human use, and chemotherapy presents several problems. Pentavalent antimonials have been the drugs of choice to treat the disease for more than six decades; however, they exhibit high toxicity and are not indicated for children, for pregnant or breastfeeding women or for chronically ill patients. Amphotericin B (AmpB) is a second-line drug, and although it has been increasingly used to treat visceral leishmaniasis (VL), its clinical use has been hampered due to its high toxicity. This review focuses on the development and in vivo usage of new delivery systems for AmpB that aim to decrease its toxicity without altering its therapeutic efficacy. These new formulations, when adjusted with regard to their production costs, may be considered new drug delivery systems that promise to improve the treatment of leishmaniasis, by reducing the side effects and the number of doses while permitting a satisfactory cost-benefit ratio.

The absence of the human platelet antigen polymorphism effect on fibrosis progression in human immunodeficiency virus-1/hepatitis C virus coinfected patients

AbstractINTRODUCTION:Hepatic fibrosis progression in patients with chronic hepatitis C virus infections has been associated with viral and host factors, including genetic polymorphisms. Human platelet antigen polymorphisms are associated with the rapid development of fibrosis in HCV-monoinfected patients. This study aimed to determine whether such an association exists in human immunodeficiency virus-1/hepatitis C virus-coinfected patients.METHODS:Genomic deoxyribonucleic acid from 36 human immunodeficiency virus-1/hepatitis C virus-coinfected patients was genotyped to determine the presence of human platelet antigens-1, -3, or -5 polymorphisms. Fibrosis progression was evaluated using the Metavir scoring system, and the patients were assigned to two groups, namely, G1 that comprised patients with F1, portal fibrosis without septa, or F2, few septa (n = 23) and G2 that comprised patients with F3, numerous septa, or F4, cirrhosis (n = 13). Fisher's exact test was utilized to determine possible associations between the human platelet antigen polymorphisms and fibrosis progression.RESULTS:There were no deviations from the Hardy-Weinberg equilibrium in the human platelet antigen systems evaluated. Statistically significant differences were not observed between G1 and G2 with respect to the distributions of the allelic and genotypic frequencies of the human platelet antigen systems.CONCLUSION:The greater stimulation of hepatic stellate cells by the human immunodeficiency virus and, consequently, the increased expression of transforming growth factor beta can offset the effect of human platelet antigen polymorphism on the progression of fibrosis in patients coinfected with the human immunodeficiency virus-1 and the hepatitis C virus.

Human herpesvirus 8 (HHV-8) and the etiopathogenesis of Kaposi's sarcoma

OBJECTIVE: To review the current literature on human herpesvirus 8 with particular attention to the aspects related to the etiopathogenesis of Kaposi's sarcoma. MATERIALS AND METHODS: The authors searched original research and review articles on specific aspects of human herpesvirus 8 infection, including virology, epidemiology, transmission, diagnosis, natural history, therapy, and Kaposi's sarcoma etiopathogenesis. The relevant material was evaluated and reviewed. RESULTS: Human herpesvirus 8 is a recently discovered DNA virus that is present throughout the world but with major geographic variation. In the Western world, the virus, transmitted mainly by means of sexual contact, is strongly associated with Kaposi's sarcoma and body cavity-based lymphoma and more controversially with multiple myeloma and other non-proliferative disorders. There is no specific effective treatment, but HIV protease inhibitors may play an indirect role in the clearance of human herpesvirus 8 DNA from peripheral blood mononuclear cells of HIV-infected patients. Human herpesvirus 8 DNA is present in saliva, but there are as yet no documented cases of nosocomial transmission to health care workers. The prevalence of human herpesvirus 8 among health care workers is probably similar to that in the general population. CONCLUSION: Human herpesvirus 8 appears to be, at least in Western Europe and United States, restricted to a population at risk of developing Kaposi's sarcoma. Human herpesvirus 8 certainly has the means to overcome cellular control and immune responses and thus predispose carriers to malignancy, particularly Kaposi's sarcoma. The wide diffusion of Human herpesvirus 8 in classic Kaposi's sarcoma areas appears to represent an important factor in the high incidence of the disease. However, additional co-factors are likely to play a role in the development of Kaposi's sarcoma.

Development of human central nervous system 3D in vitro models for preclinical research

Neurological disorders are a major concern in modern societies, with increasing prevalence mainly related with the higher life expectancy. Most of the current available therapeutic options can only control and ameliorate the patients’ symptoms, often be-coming refractory over time. Therapeutic breakthroughs and advances have been hampered by the lack of accurate central nervous system (CNS) models. The develop-ment of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of novel therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmentally, anatomically and physiologically) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity). The in vitro recapitulation of CNS phenotypic and functional features requires the implementation of advanced culture strategies that enable to mimic the in vivo struc-tural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. This thesis aimed at the development of novel human 3D in vitro CNS models by integrat-ing agitation-based culture systems and a wide array of characterization tools. Neural differentiation of hNSC as 3D neurospheres was explored in Chapter 2. Here, it was demonstrated that human midbrain-derived neural progenitor cells from fetal origin (hmNPC) can generate complex tissue-like structures containing functional dopaminergic neurons, as well as astrocytes and oligodendrocytes. Chapter 3 focused on the development of cellular characterization assays for cell aggregates based on light-sheet fluorescence imaging systems, which resulted in increased spatial resolu-tion both for fixed samples or live imaging. The applicability of the developed human 3D cell model for preclinical research was explored in Chapter 4, evaluating the poten-tial of a viral vector candidate for gene therapy. The efficacy and safety of helper-dependent CAV-2 (hd-CAV-2) for gene delivery in human neurons was evaluated, demonstrating increased neuronal tropism, efficient transgene expression and minimal toxicity. The potential of human 3D in vitro CNS models to mimic brain functions was further addressed in Chapter 5. Exploring the use of 13C-labeled substrates and Nucle-ar Magnetic Resonance (NMR) spectroscopy tools, neural metabolic signatures were evaluated showing lineage-specific metabolic specialization and establishment of neu-ron-astrocytic shuttles upon differentiation. Chapter 6 focused on transferring the knowledge and strategies described in the previous chapters for the implementation of a scalable and robust process for the 3D differentiation of hNSC derived from human induced pluripotent stem cells (hiPSC). Here, software-controlled perfusion stirred-tank bioreactors were used as technological system to sustain cell aggregation and dif-ferentiation. The work developed in this thesis provides practical and versatile new in vitro ap-proaches to model the human brain. Furthermore, the culture strategies described herein can be further extended to other sources of neural phenotypes, including pa-tient-derived hiPSC. The combination of this 3D culture strategy with the implemented characterization methods represents a powerful complementary tool applicable in the drug discovery, toxicology and disease modeling.

The human eye as human-machine interface

Eye tracking as an interface to operate a computer is under research for a while and new systems are still being developed nowadays that provide some encouragement to those bound to illnesses that incapacitates them to use any other form of interaction with a computer. Although using computer vision processing and a camera, these systems are usually based on head mount technology being considered a contact type system. This paper describes the implementation of a human-computer interface based on a fully non-contact eye tracking vision system in order to allow people with tetraplegia to interface with a computer. As an assistive technology, a graphical user interface with special features was developed including a virtual keyboard to allow user communication, fast access to pre-stored phrases and multimedia and even internet browsing. This system was developed with the focus on low cost, user friendly functionality and user independency and autonomy.

Automatic visual detection of human behavior: a review from 2000 to 2014

Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Filamentous fungi in free water and biofilms from Brazilian drinking water systems

In some regions of Brazil, especially where the water is scarce, drinking water is stored in water storage tanks. This practice gives the consumer the guarantee of available water. The water storage conditions such as the exposure to hot weather when the tanks are on rooftops allow the development of microorganisms and microbial biofilms which can deteriorate the water quality and increase the risk to human health [1,2]. This study describes the filamentous fungi (FF) detected in free water and biofilms in drinking water storage tanks in Recife - Pernambuco, Brazil. Five sampling times in triplicate were performed at two distinct points. Colony-forming units (CFU) of FF fungi were determined with 0.45 µm filtration membranes using peptone glucose rose Bengal agar (PGRBA). From the 30 samples analysed a total of 1136 CFU were obtained. The water biofilms were collected from samplers consisting of polyethylene coupons, previously installed in the reservoirs. These coupons were transferred to PGRBA plates and incubated using with the same conditions described for free FF. For the in situ detection of FF in biofilms the Calcofluor White staining technique was used. This procedure demonstrated FF forming biofilms on the surfaces of the coupons. Brazilian legislation does not define limits for FF in drinking water. However considering the potential risk of fungal contamination, the data obtained in this study will contribute to developing future quantitative and qualitative parameters for the presence of fungi in drinking water distribution systems in Brazil. [1] HageskaL, G, Lima, N, Skaar, I. The study of fungi in drinking water. Mycological Research, 113, 2009, 165-172. [2] Skaar I, Hageskal G. Fungi in Drinking Water. In.: Paterson RRM, Lima N. (Eds.) Molecular Biology of Food and Water Borne Mycotoxigenic and Mycotic Fungi. CRC Press, Taylor & Francis Group, Boca Raton, 2015, 597-606.

Human and murine clonal CD8+ T cell expansions arise during tuberculosis because of TCR selection

The immune system can recognize virtually any antigen, yet T cell responses against several pathogens, including Mycobacterium tuberculosis, are restricted to a limited number of immunodominant epitopes. The host factors that affect immunodominance are incompletely understood. Whether immunodominant epitopes elicit protective CD8+ T cell responses or instead act as decoys to subvert immunity and allow pathogens to establish chronic infection is unknown. Here we show that anatomically distinct human granulomas contain clonally expanded CD8+ T cells with overlapping T cell receptor (TCR) repertoires. Similarly, the murine CD8+ T cell response against M. tuberculosis is dominated by TB10.44-11-specific T cells with extreme TCRß bias. Using a retro genic model of TB10.44-11-specific CD8+ Tcells, we show that TCR dominance can arise because of competition between clonotypes driven by differences in affinity. Finally, we demonstrate that TB10.4-specific CD8+ T cells mediate protection against tuberculosis, which requires interferon-? production and TAP1-dependent antigen presentation in vivo. Our study of how immunodominance, biased TCR repertoires, and protection are inter-related, provides a new way to measure the quality of T cell immunity, which if applied to vaccine evaluation, could enhance our understanding of how to elicit protective T cell immunity.