Search results for: genetic programming

Authors: Salam N. Abdo, Orien L. Tulp, George P. Einstein

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The purpose of this exploratory study was to gather the insights into psoriasis etiology, treatment, and patient experience, for developing psoriasis and psoriatic arthritis diagnostic test. Data collection methods consisted of a comprehensive meta-analysis of relevant studies and psoriasis patient survey. Established meta-analysis guidelines were used for the selection and qualitative comparative analysis of psoriasis and psoriatic arthritis research studies. Only studies that clearly discussed psoriasis etiology, treatment, and patient experience were reviewed and analyzed, to establish a qualitative data base for the study. Using the insights gained from meta-analysis, an existing psoriasis patient survey was modified and administered to collect additional data as well as triangulate the results. The hypothesis is that specific types of psoriatic disease have specific etiology and pathophysiologic pattern. The following etiology categories were identified: bacterial, environmental/microbial, genetic, immune, infectious, trauma/stress, and viral. Additional results, obtained from meta-analysis and confirmed by patient survey, were the common age of onset (early to mid-20s) and type of psoriasis (plaque; mild; symmetrical; scalp, chest, and extremities, specifically elbows and knees). Almost 70% of patients reported no prescription drug use due to severe side effects and prohibitive cost. These results will guide the development of psoriasis and psoriatic arthritis diagnostic test. The significant number of medical publications classified psoriatic arthritis disease as inflammatory of an unknown etiology. Thus numerous meta-analyses struggle to report any meaningful conclusions since no definitive results have been reported to date. Therefore, return to the basics is an essential step to any future meaningful results. To date, medical literature supports the fact that psoriatic disease in its current classification could be misidentifying subcategories, which in turn hinders the success of studies conducted to date. Moreover, there has been an enormous commercial support to pursue various immune-modulation therapies, thus following a narrow hypothesis/mechanism of action that is yet to yield resolution of disease state. Recurrence and complications may be considered unacceptable in a significant number of these studies. The aim of the ongoing study is to focus on a narrow subgroup of patient population, as identified by this exploratory study via meta-analysis and patient survey, and conduct an exhaustive work up, aiming at mechanism of action and causality before proposing a cure or therapeutic modality. Remission in psoriasis has been achieved and documented in medical literature, such as immune-modulation, phototherapy, various over-the-counter agents, including salts and tar. However, there is no psoriasis and psoriatic arthritis diagnostic test to date, to guide the diagnosis and treatment of this debilitating and, thus far, incurable disease. Because psoriasis affects approximately 2% of population, the results of this study may affect the treatment and improve the quality of life of a significant number of psoriasis patients, potentially millions of patients in the United States alone and many more millions worldwide.

Keywords: biologics, early diagnosis, etiology, immune disease, immune modulation therapy, inflammation skin disorder, phototherapy, plaque psoriasis, psoriasis, psoriasis classification, psoriasis disease marker, psoriasis diagnostic test, psoriasis marker, psoriasis mechanism of action, psoriasis treatment, psoriatic arthritis, psoriatic disease, psoriatic disease marker, psoriatic patient experience, psoriatic patient quality of life, remission, salt therapy, targeted immune therapy

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Authors: C. Bel, J. Nevado, F. Ciceri, M. Ropacki, T. Hoffmann, P. Lapunzina, C. Buesa

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Background: The Phelan-McDermid syndrome (PMS) is a genetic disorder caused by the deletion of the terminal region of chromosome 22 or mutation of the SHANK3 gene. Shank3 disruption in mice leads to dysfunction of synaptic transmission, which can be restored by epigenetic regulation with both Lysine Specific Demethylase 1 (LSD1) inhibitors. PMS subjects result in a variable degree of intellectual disability, delay or absence of speech, autistic spectrum disorders symptoms, low muscle tone, motor delays and epilepsy. Vafidemstat is an LSD1 inhibitor in Phase II clinical development with a well-established and favorable safety profile, and data supporting the restoration of memory and cognition defects as well as reduction of agitation and aggression in several animal models and clinical studies. Therefore, vafidemstat has the potential to become a first-in-class precision medicine approach to treat PMS patients. Aims: The goal of this research is to perform an observational trial to psychometrically characterize individuals carrying deletions in SHANK3 and build a foundation for subsequent precision psychiatry clinical trials with vafidemstat. Methodology: This study is characterizing the clinical profile of 20 to 40 subjects, > 16-year-old, with genotypically confirmed PMS diagnosis. Subjects will complete a battery of neuropsychological scales, including the Repetitive Behavior Questionnaire (RBQ), Vineland Adaptive Behavior Scales, Escala de Observación para el Diagnostico del Autismo (Autism Diagnostic Observational Scale) (ADOS)-2, the Battelle Developmental Inventory and the Behavior Problems Inventory (BPI). Results: By March 2021, 19 patients have been enrolled. Unsupervised hierarchical clustering of the results obtained so far identifies 3 groups of patients, characterized by different profiles of cognitive and behavioral scores. The first cluster is characterized by low Battelle age, high ADOS and low Vineland, RBQ and BPI scores. Low Vineland, RBQ and BPI scores are also detected in the second cluster, which in contrast has high Battelle age and low ADOS scores. The third cluster is somewhat in the middle for the Battelle, Vineland and ADOS scores while displaying the highest levels of aggression (high BPI) and repeated behaviors (high RBQ). In line with the observation that female patients are generally affected by milder forms of autistic symptoms, no male patients are present in the second cluster. Dividing the results by gender highlights that male patients in the third cluster are characterized by a higher frequency of aggression, whereas female patients from the same cluster display a tendency toward higher repetitive behavior. Finally, statistically significant differences in deletion sizes are detected comparing the three clusters (also after correcting for gender), and deletion size appears to be positively correlated with ADOS and negatively correlated with Vineland A and C scores. No correlation is detected between deletion size and the BPI and RBQ scores. Conclusions: Precision medicine may open a new way to understand and treat Central Nervous System disorders. Epigenetic dysregulation has been proposed to be an important mechanism in the pathogenesis of schizophrenia and autism. Vafidemstat holds exciting therapeutic potential in PMS, and this study will provide data regarding the optimal endpoints for a future clinical study to explore vafidemstat ability to treat shank3-associated psychiatric disorders.

Keywords: autism, epigenetics, LSD1, personalized medicine

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Authors: Tim Crocker-Buque, Sandra Mounier-Jack, Natasha Howard

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Background: Due to both the increasing scale and speed of urbanisation, urban areas in low and middle-income countries (LMICs) host increasingly large populations of under-immunized children, with the additional associated risks of rapid disease transmission in high-density living environments. Multiple interdependent factors are associated with these coverage disparities in urban areas and most evidence comes from relatively few countries, e.g., predominantly India, Kenya, Nigeria, and some from Pakistan, Iran, and Brazil. This study aimed to identify, describe, and assess the main tools used to measure or improve coverage of immunisation services in poor urban areas. Methods: Authors used a qualitative review design, including academic and non-academic literature, to identify tools used to improve coverage of public health interventions in urban areas. Authors selected and extracted sources that provided good examples of specific tools, or categories of tools, used in a context relevant to urban immunization. Diagnostic (e.g., for data collection, analysis, and insight generation) and programme tools (e.g., for investigating or improving ongoing programmes) and interventions (e.g., multi-component or stand-alone with evidence) were selected for inclusion to provide a range of type and availability of relevant tools. These were then prioritised using a decision-analysis framework and a tool selection guide for programme managers developed. Results: Authors reviewed tools used in urban immunisation contexts and tools designed for (i) non-immunization and/or non-health interventions in urban areas, and (ii) immunisation in rural contexts that had relevance for urban areas (e.g., Reaching every District/Child/ Zone). Many approaches combined several tools and methods, which authors categorised as diagnostic, programme, and intervention. The most common diagnostic tools were cross-sectional surveys, key informant interviews, focus group discussions, secondary analysis of routine data, and geographical mapping of outcomes, resources, and services. Programme tools involved multiple stages of data collection, analysis, insight generation, and intervention planning and included guidance documents from WHO (World Health Organisation), UNICEF (United Nations Children's Fund), USAID (United States Agency for International Development), and governments, and articles reporting on diagnostics, interventions, and/or evaluations to improve urban immunisation. Interventions involved service improvement, education, reminder/recall, incentives, outreach, mass-media, or were multi-component. The main gaps in existing tools were an assessment of macro/policy-level factors, exploration of effective immunization communication channels, and measuring in/out-migration. The proposed framework uses a problem tree approach to suggest tools to address five common challenges (i.e. identifying populations, understanding communities, issues with service access and use, improving services, improving coverage) based on context and available data. Conclusion: This study identified many tools relevant to evaluating urban LMIC immunisation programmes, including significant crossover between tools. This was encouraging in terms of supporting the identification of common areas, but problematic as data volumes, instructions, and activities could overwhelm managers and tools are not always suitably applied to suitable contexts. Further research is needed on how best to combine tools and methods to suit local contexts. Authors’ initial framework can be tested and developed further.

Keywords: health equity, immunisation, low and middle-income countries, poverty, urban health

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Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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Authors: Hosein Maghsoudi

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Rheumatois arthritis (RA) is progressive inflammatory autoimmune diseases that primarily affect the joints, characterized by synovial hyperplasia and inflammatory cell infiltration, deformed and painful joints, which can lead tissue destruction, functional disability systemic complications, and early dead and socioeconomic costs. The cause of rheumatoid arthritis is unknown, but genetic and environmental factors are contributory and the prognosis is guarded. However, advances in understanding the pathogenesis of the disease have fostered the development of new therapeutics, with improved outcomes. The current treatment strategy, which reflects this progress, is to initiate aggressive therapy soon after diagnosis and to escalate the therapy, guided by an assessment of disease activity, in pursuit of clinical remission. The pathobiology of RA is multifaceted and involves T cells, B cells, fibroblast-like synoviocyte (FLSc) and the complex interaction of many pro-inflammatory cytokine. Novel biologic agents that target tumor necrosis or interlukin (IL)-1 and Il-6, in addition T- and B-cells inhibitors, have resulted in favorable clinical outcomes in patients with RA. Despite this, at least 30% of RA patients are résistance to available therapies, suggesting novel mediators should be identified that can target other disease-specific pathway or cell lineage. Among the inflammatory cell population that might participated in RA pathogenesis, FLSc are crucial in initiaing and driving RA in concert of cartilage and bone by secreting metalloproteinase (MMPs) into the synovial fluid and by direct invasion into extracellular matrix (ECM), further exacerbating joint damage. Invasion of fibroblast-like synoviocytes (FLSc) is critical in the pathogenesis of rheumatoid-arthritis. The metalloproteinase (MMPs) and activator of Toll-like receptor 4 (TLR4)/nuclear factor- κB pthway play a critical role in RA-FLS invasion induced by lipopolysaccharide (LPS). The present study aimed to explore the anti-invasion activity of Glycyrrhizic Acid as a pharmacologically safe phytochemical agent with potent anti-inflammatory properties on IL-1beta and TNF-alpha signalling pathways in Bovine fibroblast-like synoviocyte ex- vitro, on LPS-stimulated bovine FLS migration and invasion as well as MMP expression and explored the upstream signal transduction. Results showed that Glycyrrhizic Acid suppressed LPS-stimulated bovine FLS migration and invasion by inhibition MMP-9 expression and activity. In addition our results revealed that Glycyrrhizic Acid inhibited the transcriptional activity of MMP-9 by suppression the nbinding activity of NF- κB in the MMP-9 promoter pathway. The extract of licorice (Glycyrrhiza glabra L.) has been widely used for many centuries in the traditional Chinese medicine as native anti-allergic agent. Glycyrrhizin (GL), a triterpenoidsaponin, extracted from the roots of licorice is the most effective compound for inflammation and allergic diseases in human body. The biological and pharmacological studies revealed that GL possesses many pharmacological effects, such as anti-inflammatory, anti-viral and liver protective effects, and the biological effects, such as induction of cytokines (interferon-γ and IL-12), chemokines as well as extrathymic T and anti-type 2 T cells. GL is known in the traditional Chinese medicine for its anti-inflammatory effect, which is originally described by Finney in 1959. The mechanism of the GL-induced anti-inflammatory effect is based on different pathways of the GL-induced selective inhibition of the prostaglandin E2 production, the CK-II- mediated activation of both GL-binding lipoxygenas (gbLOX; 17) and PLA2, an anti-thrombin action of GL and production of the reactive oxygen species (ROS; GL exerts liver protection properties by inhibiting PLA2 or by the hydroxyl radical trapping action, leading to the lowering of serum alanine and aspartate transaminase levels. The present study was undertaken to examine the possible mechanism of anti-inflammatory properties GL on IL-1beta and TNF-alpha signalling pathways in bovine fibroblast-like synoviocyte ex-vivo, on LPS-stimulated bovine FLS migration and invasion as well as MMP expression and explored the upstream signal transduction. Our results clearly showed that treatment of bovine fibroblast-like synoviocyte with GL suppressed LPS-induced cell migration and invasion. Furthermore, it revealed that GL inhibited the transcription activity of MMP-9 by suppressing the binding activity of NF-κB in the MM-9 promoter. MMP-9 is an important ECM-degrading enzyme and overexpression of MMPs in important of RA-FLSs. LPS can stimulate bovine FLS to secret MMPs, and this induction is regulated at the transcription and translational levels. In this study, LPS treatment of bovine FLS caused an increase in MMP-2 and MMP-9 levels. The increase in MMP-9 expression and secretion was inhibited by ex- vitro. Furthermore, these effects were mimicked by MMP-9 siRNA. These result therefore indicate the the inhibition of LPS-induced bovine FLS invasion by GL occurs primarily by inhibiting MMP-9 expression and activity. Next we analyzed the functional significance of NF-κB transcription of MMP-9 activation in Bovine FLSs. Results from EMSA showed that GL suppressed LPS-induced NF-κB binding to the MMP-9 promotor, as NF-κB regulates transcriptional activation of multiple inflammatory cytokines, we predicted that GL might target NF-κB to suppress MMP-9 transcription by LPS. Myeloid differentiation-factor 88 (MyD88) and TIR-domain containing adaptor protein (TIRAP) are critical proteins in the LPS-induced NF-κB and apoptotic signaling pathways, GL inhibited the expression of TLR4 and MYD88. These results demonstrated that GL suppress LPS-induced MMP-9 expression through the inhibition of the induced TLR4/NFκB signaling pathway. Taken together, our results provide evidence that GL exerts anti-inflammatory effects by inhibition LPS-induced bovine FLSs migration and invasion, and the mechanisms may involve the suppression of TLR4/NFκB –mediated MMP-9 expression. Although further work is needed to clarify the complicated mechanism of GL-induced anti-invasion of bovine FLSs, GL might be used as a further anti-invasion drug with therapeutic efficacy in the treatment of immune-mediated inflammatory disease such as RA.

Keywords: glycyrrhizic acid, bovine fibroblast-like synoviocyte, tlr4/nf-κb, metalloproteinase-9

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