SANA - Salone Internazionale del Biologico e del Naturale. La ricerca transnazionale in agricoltura biologica: il programma “Core organic”

Within the FrameWork of SANA, Bologna, the Project FAVORDENONDE was presented as part of the Italian Partnership for CORE Organic Projects

SANA - Salone Internazionale del Biologico e del Naturale. La ricerca transnazionale in agricoltura biologica: il programma “Core organic”

Within the FrameWork of SANA, Bologna, the Project FAVORDENONDE was presented as part of the Italian Partnership for CORE Organic Projects

The use of mercury against pediculosis in the Renaissance: tha case of Ferdinand of Aragon, King of Naples (1467-1496)

Pediculosis seems to have afflicted humans since the most ancient times and lice have been found in several ancient human remains. Examination of the head hair and pubic hair of the artificial mummy of Ferdinand II of Aragon (1467-1496), King of Naples, revealed a double infestation with two different species of lice, Pediculus capitis, the head louse, and Pthirus pubis, the pubic louse. The hair samples were also positive for the presence of mercury, probably applied as an anti-pediculosis therapy. This is the first time that these parasites have been found in the hair of a king, demonstrating that even members of the wealthy classes in the Renaissance were subject to louse infestation

Nitrogen status assessment for variable rate fertilization in maize through hyperspectral imagery

This paper presents a method for mapping the nitrogen (N) status in a maize field using hyperspectral remote sensing imagery. An airborne survey was conducted with an AISA Eagle hyperspectral sensor over an experimental farm where maize (Zea mays L.) was grown with two N fertilization levels (0 and 100 kg N ha-1) in four replicates. Leaf and canopy field data were collected during the flight. The nitrogen (N) status has been estimated in this work based on the Nitrogen Nutrition Index (NNI) defined as the ratio between the leaf actual N concentration (%Na) of the crop and the minimum N content required for the maximum biomass production (critical N concentration (%Nc)) calculated through the dry mass at the time of the flight (Wflight). The inputs required to calculate the NNI (i.e. %Na and Wflight) have been estimated through regression analyses between field data and remotely sensed vegetation indices. MCARI/MTVI2 (Modified Chlorophyll Absorption Ratio Index / Modified Triangular Vegetation Index 2) showed the best performances in estimating the %Na (R2 = 0.59) and MTVI2 in estimating the Wflight (R2 = 0.80). The %Na and the Wflight were then mapped and used to compute the NNI map over the entire field. The NNI map agreed with the NNI estimated using field data through traditional destructive measurements (R2 = 0.70) confirming the potential of using remotely sensed indices to assess the crop N condition. Finally, a method to derive a pixel based variable rate N fertilization map was proposed as the difference between the actual N content and the optimal N content. We think that the proposed operational methodology is promising for precision farming since it represents an innovative attempt to derive from an aerial hyperspectral image a variable rate N fertilization map based on the actual crop N status.JRC.H.4-Monitoring Agricultural Resource

Nitrogen status assessment for variable rate fertilization in maize through hyperspectral imagery

JRC.H.4-Monitoring Agricultural Resource

An atlas of the knee joint proteins and their role in osteoarthritis defined by literature mining

[Abstract] Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of the entire joint. One of the most common locations of OA is the knee. Knee tissues have been studied using molecular strategies, generating a large amount of complex data. As one of the goals of the Rheumatic and Autoimmune Diseases initiative of the Human Proteome Project, we applied a text-mining strategy to publicly available literature to collect relevant information and generate a systematically organized overview of the proteins most closely related to the different knee components. To this end, the PubPular literature-mining software was employed to identify protein-topic relationships and extract the most frequently cited proteins associated with the different knee joint components and OA. The text-mining approach searched over eight million articles in PubMed up to November 2022. Proteins associated with the six most representative knee components (articular cartilage, subchondral bone, synovial membrane, synovial fluid, meniscus, and cruciate ligament) were retrieved and ranked by their relevance to the tissue and OA. Gene ontology analyses showed the biological functions of these proteins. This study provided a systematic and prioritized description of knee-component proteins most frequently cited as associated with OA. The study also explored the relationship of these proteins to OA and identified the processes most relevant to proper knee function and OA pathophysiology.PI19/01206; Instituto de Salud Carlos IIIPI20/00793; Instituto de Salud Carlos IIIPI20/01409; Instituto de Salud Carlos IIIPI22/01155; Instituto de Salud Carlos IIIRICORS-REIRD21/0002/0009; Instituto de Salud Carlos IIIED431E2018/03; Xunta de GaliciaIN607A2021/07; Xunta de GaliciaIN607D2020/10; Xunta de Galici

Analysis of Endogenous Peptides Released from Osteoarthritic Cartilage Unravels Novel Pathogenic Markers

Osteoarthritis (OA) is a pathology characterized by the loss of articular cartilage. In this study, we performed a peptidomic strategy to identify endogenous peptides (neopeptides) that are released from human osteoarthritic tissue, which may serve as disease markers. With this aim, secretomes of osteoarthritic and healthy articular cartilages obtained from knee and hip were analyzed by shotgun peptidomics. This discovery step led to the identification of 1175 different peptides, corresponding to 101 proteins, as products of the physiological or pathological turnover of cartilage extracellular matrix. Then, a targeted multiple reaction monitoring-mass spectrometry method was developed to quantify the panel of best marker candidates on a larger set of samples (n = 62). Statistical analyses were performed to evaluate the significance of the observed differences and the ability of the neopeptides to classify the tissue. Eight of them were differentially abundant in the media from wounded zones of OA cartilage compared with the healthy tissue (p < 0.05). Three neopeptides belonging to Clusterin and one from Cartilage Oligomeric Matrix Protein showed a disease-dependent decrease specifically in hip OA, whereas two from Prolargin (PRELP) and one from Cartilage Intermediate Layer Protein 1 were significantly increased in samples from knee OA. The release of one peptide from PRELP showed the best metrics for tissue classification (AUC = 0.834). The present study reveals specific neopeptides that are differentially released from knee or hip human osteoarthritic cartilage compared with healthy tissue. This evidences the intervention of characteristic pathogenic pathways in OA and provides a novel panel of peptidic candidates for biomarker development.Ministerio of Educación (Spain). M.C.-E. is supported by the Xunta de Galicia and the European Union (European Social Fund - ESF) through a predoctoral fellowship (IN606A-2016/012). C.R.-R. has been supported by the Miguel Servet II program from Fondo Investigacón Sanitaria-Spain (CPII15/00013

Analysis of endogenous peptides released from osteoarthritic articular cartilage unravels novel pathogenic markers

[Abstract] Osteoarthritis (OA) is a pathology characterized by the loss of articular cartilage. In this study, we performed a peptidomic strategy to identify endogenous peptides (neopeptides) that are released from human osteoarthritic tissue, which may serve as disease markers. With this aim, secretomes of osteoarthritic and healthy articular cartilages obtained from knee and hip were analyzed by shotgun peptidomics. This discovery step led to the identification of 1175 different peptides, corresponding to 101 proteins, as products of the physiological or pathological turnover of cartilage extracellular matrix. Then, a targeted multiple reaction monitoring-mass spectrometry method was developed to quantify the panel of best marker candidates on a larger set of samples (n = 62). Statistical analyses were performed to evaluate the significance of the observed differences and the ability of the neopeptides to classify the tissue. Eight of them were differentially abundant in the media from wounded zones of OA cartilage compared with the healthy tissue (p < 0.05). Three neopeptides belonging to Clusterin and one from Cartilage Oligomeric Matrix Protein showed a disease-dependent decrease specifically in hip OA, whereas two from Prolargin (PRELP) and one from Cartilage Intermediate Layer Protein 1 were significantly increased in samples from knee OA. The release of one peptide from PRELP showed the best metrics for tissue classification (AUC = 0.834). The present study reveals specific neopeptides that are differentially released from knee or hip human osteoarthritic cartilage compared with healthy tissue. This evidences the intervention of characteristic pathogenic pathways in OA and provides a novel panel of peptidic candidates for biomarker development.Instituto de Salud Carlos III; PI14/01707Instituto de Salud Carlos III; PI16/02124Instituto de Salud Carlos III; PI17/00404Instituto de Salud Carlos III; CIBER-CB06/01/0040Instituto de Salud Carlos III; DTS17/00200Instituto de Salud Carlos III; RETIC-RIER-RD16/0012/0002Instituto de Salud Carlos III; PT17/0019/001

Predictive modeling of therapeutic response to chondroitin sulfate/glucosamine hydrochloride in knee osteoarthritis

[Abstract] Background: In the present study, we explored potential protein biomarkers useful to predict the therapeutic response of knee osteoarthritis (KOA) patients treated with pharmaceutical grade Chondroitin sulfate/Glucosamine hydrochloride (CS+GH; Droglican, Bioiberica), in order to optimize therapeutic outcomes. Methods: A shotgun proteomic analysis by iTRAQ labelling and liquid chromatography–mass spectrometry (LC-MS/MS) was performed using sera from 40 patients enrolled in the Multicentre Osteoarthritis interVEntion trial with Sysadoa (MOVES). The panel of proteins potentially useful to predict KOA patient’s response was clinically validated in the whole MOVES cohort at baseline (n = 506) using commercially available enzyme-linked immunosorbent assays kits. Logistic regression models and receiver-operating-characteristics (ROC) curves were used to analyze the contribution of these proteins to our prediction models of symptomatic drug response in KOA. Results: In the discovery phase of the study, a panel of six putative predictive biomarkers of response to CS+GH (APOA2, APOA4, APOH, ITIH1, C4BPa and ORM2) were identified by shotgun proteomics. Data are available via ProteomeXchange with identifier PXD012444. In the verification phase, the panel was verified in a larger set of KOA patients (n = 262). Finally, ITIH1 and ORM2 were qualified by a blind test in the whole MOVES cohort at baseline. The combination of these biomarkers with clinical variables predict the patients’ response to CS+GH with a specificity of 79.5% and a sensitivity of 77.1%. Conclusions: Combining clinical and analytical parameters, we identified one biomarker that could accurately predict KOA patients’ response to CS+GH treatment. Its use would allow an increase in response rates and safety for the patients suffering KOA.Insituto de Salud Carlos III; PI14/01707Instituto de Salud Carlos III; PI16/02124Insituto de Salud Carlos III; PI17/00404Instituto de Salud Carlos III; DTS17/00200Instituto de Salud Carlos III; CIBER-CB06/01/0040Insituto de Salud Carlos III; RETIC-RIER-RD16/0012/000