THE ROLE OF HLA TYPING IN RHEUMATIC DISEASES

Association between HLA-DR4 and rheumatoid arthritis (RA) has been known for 4 decades, and amino acid sites within HLA-DRB1 (11/13, 71, 74) are highly associated with RA. HLA is not useful for diagnosis or prognosis, but it may help predict severe and erosive disease. Since 90% of patients with ankylosing spondylitis (AS) and 50-70% of other spondyloarthritis (SpA) patients are HLA-B*27 positive, HLA is a stronghold of diagnostic algorithms. Genetic predisposition to juvenile idiopathic arthritis (JIA) is mainly due to HLA class II, and to a lesser extent to HLA class I. Although HLA plays a role in rheumatic disorders, its clinical relevance is not homogeneous. When classical biomarkers are lacking or in complex cases, HLA typing may provide support for the management of patients

RKIP Suppresses Breast Cancer Metastasis to the Bone by Regulating Stroma-Associated Genes

In the past decade cancer research has recognized the importance of tumorstroma interactions for the progression of primary tumors to an aggressive and invasive phenotype and for colonization of new organs in the context of metastasis. The dialogue between tumor cells and the surrounding stroma is a complex and dynamic phenomenon, as many cell types and soluble factors are involved. While the function of many of the players involved in this cross talk have been studied, the regulatory mechanisms and signaling pathways that control their expression haven't been investigated in depth. By using a novel, interdisciplinary approach applied to the mechanism of action of the metastasis suppressor, Raf kinase inhibitory protein (RKIP), we identified a signaling pathway that suppresses invasion and metastasis through regulation of stroma-associated genes. Conceptually, the approach we developed uses a master regulator and expression arrays from breast cancer patients to formulate hypotheses based on clinical data. Experimental validation is followed by further bioinformatic analysis to establish the clinical significance of discoveries. Using RKIP as an example we show here that this multi-step approach can be used to identify gene regulatory mechanisms that affect tumor-stroma interactions that in turn influence metastasis to the bone or other organs

Report on the Verification of the Performance of Bt11, MIR162, MIR604 and GA21 Event-specific PCR-based Methods Applied to DNA Extracted from Stack Maize Bt11 x MIR162 x MIR604 x GA21

An application was submitted by Syngenta Crop Protection AG to request the authorisation of genetically modified Bt11 x MIR162 x MIR604 x GA21 maize (resistant to lepidopteran and coleopteran pests, able to utilise mannose as the only primary carbon source and tolerant to glufosinate ammonium and glyphosate) and all sub-combinations of the individual events as present in the segregating progeny, for food and feed uses, and import and processing, in accordance with articles 5 and 17 of Regulation (EC) N° 1829/2003 GM Food and GM Feed. The unique identifier assigned to Bt11 x MIR162 x MIR604 x GA21 maize is SYN-BTØ11-1x YN-IR162-4xSYN-IR6Ø4-5xMON-ØØØ21-9. The genetically modified maize line Bt11 x MIR162 x MIR604 x GA21 maize has been obtained by conventional crossing of four genetically modified maize events: Bt11, MIR162, MIR604, and GA21 without any new genetic modification. The EU-RL GMFF has previously validated individually, and declared fit for purpose, the detection methods for the single events Bt11, MIR162, MIR604 and GA21 (see http://gmo-crl.jrc.ec.europa.eu/StatusOfDossiers.aspx). In line with the approach defined by the ENGL (http://gmo-crl.jrc.ec.europa.eu/doc/Min_Perf_Requirements_Analytical_methods.pdf) the EU-RL GMFF therefore has carried out only an in-house verification of the performance of each validated method when applied to DNA extracted from Bt11 x MIR162 x MIR604 x GA21. The hereby reported the in-house verification study lead to the conclusion that the individual methods meet the ENGL criteria also when applied to DNA extracted from the GM maize stack Bt11 x MIR162 x MIR604 x GA21JRC.I.3-Molecular Biology and Genomic

Textura de rellenos de galletitas: efecto de los ingredientes principales

Debido a la creciente demanda por parte de los consumidores de alimentos listos para el consumo, con buenas propiedades tanto nutricionales como organolépticas, la industria alimentaria tiende cada vez más al desarrollo de alimentos compuestos, con porciones secas, crujientes y rellenos suaves de diverso origen, composición y textura, como por ejemplo las galletitas rellenas. En Argentina, el consumo de galletitas es de aproximadamente 7,5 kg./hab./año, y se estima que el 15% del consumo nacional corresponde a galletitas dulces rellenas y obleas. Debido a esto, resulta de interés determinar las características y las propiedades que imparten los ingredientes comunmente utilizados en la industria alimentaria para la elaboración de rellenos de galletitas dulces. Este trabajo se centró en el estudio del efecto de los ingredientes principales de rellenos de galletitas sobre la adhesividad, la cohesividad, el tiempo de relajación y la firmeza. Las propiedades de textura se determinaron empleando un texturómetro TA.XT2i (Stable Micro Systems Ltd., Inglaterra).Facultad de IngenieríaCentro de Investigación y Desarrollo en Criotecnología de Alimento

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals.Approach. EEG recordings of 17 healthy controls (HCs), 56 subjective cognitive decline (SCD) and 45 mild cognitive impairment (MCI) subjects were acquired at resting state. After preprocessing, we selected sections corresponding to eyes-closed condition. Five different datasets were created by extracting delta, theta, alpha, beta and delta-to-theta frequency bands using bandpass filters. To classify SCDvsMCI and HCvsSCDvsMCI, we propose a framework based on the transformer architecture, which uses multi-head attention to focus on the most relevant parts of the input signals. We trained and validated the model on each dataset with a leave-one-subject-out cross-validation approach, splitting the signals into 10 s epochs. Subjects were assigned to the same class as the majority of their epochs. Classification performances of the transformer were assessed for both epochs and subjects and compared with other DL models.Main results. Results showed that the delta dataset allowed our model to achieve the best performances for the discrimination of SCD and MCI, reaching an Area Under the ROC Curve (AUC) of 0.807, while the highest results for the HCvsSCDvsMCI classification were obtained on alpha and theta with a micro-AUC higher than 0.74.Significance. We demonstrated that DL approaches can support the adoption of non-invasive and economic techniques as EEG to stratify patients in the clinical population at risk for AD. This result was achieved since the attention mechanism was able to learn temporal dependencies of the signal, focusing on the most discriminative patterns, achieving state-of-the-art results by using a deep model of reduced complexity. Our results were consistent with clinical evidence that changes in brain activity are progressive when considering early stages of AD

Cultivation of Gongolaria barbata (Fucales, Phaeophyceae) with a seaweed‐derived biostimulant in order to improve photophysiological fitness and promote fertility to advance the restoration of marine macroalgal forests

As a result of several anthropogenic factors, Cystoseira sensu lato forests have declined or become regionally extinct in many coastal regions of the Mediterranean. Given the low natural recovery of lost populations, research efforts have been encouraged to develop sustainable and efficient restoration of macroalgal forests on a large scale. By promoting growth and fertility of collected thallus branches under controlled laboratory conditions, the availability of seedlings for restoration could be ensured without jeopardizing natural populations. Here we investigated the effect of a commercial algal biostimulant (AlgatronCifo®) on the photophysiology, growth and fertility of Gongolaria barbata (Stackhouse) Kuntze (Fucales, Phaeophyceae). In a factorial laboratory experiment, two different temperatures (10 oC and 14 °C) and two culture media [i.e. seawater (SW) and Algatron (AT)] were tested. The photosynthetic performance of G. barbata doubled after three weeks of culture with AT, while it decreased by 25% when cultivated in SW. The highest photosynthetic performance and growth were achieved at 14oC with AT, where fertile receptacles also developed, followed by seedling settlements. The thalli cultured in AT had similar or better photosynthetic performance than the initial control thalli. AT-cultured thalli had a greater ability to quench energy via photochemical pathways (qP) than those from the SW, which on the contrary, had higher levels of non-photochemical responses (qN, NPQmax). This limited photosynthetic performance was probably linked to the higher P-limitation experienced under that treatment. The algal biostimulant enhanced the physiological performance and induced fertility of G. barbata, demonstrating its valorization potential and setting a new path for improved restoration applications

Drug-Induced Urolithiasis in Pediatric Patients

Drug-induced nephrolithiasis is a rare condition in children. The involved drugs may be divided into two different categories according to the mechanism involved in calculi formation. The first one includes poorly soluble drugs that favor the crystallization and calculi formation. The second category includes drugs that enhance calculi formation through their metabolic effects. The diagnosis of these specific calculi depends on a detailed medical history, associated comorbidities and the patient's history of drug consumption. There are several risk factors associated with drug-induced stones, such as high dose of consumed drugs and long duration of treatment. Moreover, there are some specific risk factors, including urinary pH and the amount of fluid consumed by children. There are limited data regarding pediatric lithogenic drugs, and hence, our aim was to perform a comprehensive review of the literature to summarize these drugs and identify the possible mechanisms involved in calculi formation and discuss the management and preventive measures for these calculi

The Status of Coastal Benthic Ecosystems in the Mediterranean Sea: Evidence From Ecological Indicators

The Mediterranean Sea is subject to multiple human pressures increasingly threatening its unique biodiversity. Spatially explicit information on the ecological status of marine ecosystems is therefore key to an effective maritime spatial planning and management, and to help the achievement of environmental targets. Here, we summarized scientific data on the ecological status of a selection of marine ecosystems based on a set of ecological indicators in more than 700 sites of the Mediterranean Sea. For Posidonia oceanica seagrass beds, rocky intertidal fringe, and coastal soft bottoms, more than 70% of investigated sites exhibited good to high ecological conditions. In contrast, about two-thirds of sites for subtidal rocky reefs were classified to be in moderate to bad conditions, stressing the need for prioritizing conservation initiatives on these productive and diverse environments. Very little quantitative information was available for the southern Mediterranean Sea, thus monitoring programs and assessments in this area are essential for a representative assessment of the health of marine coastal ecosystems in the whole basin. This overview represents a first step to implement a baseline that, through georeferenced data on ecological status, could help identifying information gaps, directing future research priorities, and supporting improvements to spatial models of expected cumulative impacts on marine ecosystems

Digital twin reference model development to prevent operators' risk in process plants

In the literature, many applications of Digital Twin methodologies in the manufacturing, construction and oil and gas sectors have been proposed, but there is still no reference model specifically developed for risk control and prevention. In this context, this work develops a Digital Twin reference model in order to define conceptual guidelines to support the implementation of Digital Twin for risk prediction and prevention. The reference model proposed in this paper is made up of four main layers (Process industry physical space, Communication system, Digital Twin and User space), while the implementation steps of the reference model have been divided into five phases (Development of the risk assessment plan, Development of the communication and control system, Development of Digital Twin tools, Tools integration in a Digital Twin perspective and models and Platform validation). During the design and implementation phases of a Digital Twin, different criticalities must be taken into consideration concerning the need for deterministic transactions, a large number of pervasive devices, and standardization issues. Practical implications of the proposed reference model regard the possibility to detect, identify and develop corrective actions that can affect the safety of operators, the reduction of maintenance and operating costs, and more general improvements of the company business by intervening both in strictly technological and organizational terms