This study aims to show that lactic fermentation by selected starters can enrich plant matrices with hydroxy- and oxo-fatty acids. The behavior of 31 lactic acid bacteria strains was investigated during the fermentation of Persian walnut, which was selected as a model growth substrate due to its inherent lipids content. The content of the following free fatty acids increased in the majority of the fermented walnut samples: linoleic, α-linolenic, palmitic, and oleic acids. The increase of diacylglycerols and, especially, monoacylglycerols levels in fermented walnuts confirmed that strain-specific bacterial lipolytic activities hydrolyzed triacylglycerols during walnut fermentation. Twelve hydroxylated or epoxidized derivatives arising from oleic, linoleic, and linolenic fatty acids, in five groups of isomeric compounds, were also identified. In addition to the better-known lactobacilli, certain strains of Weissella cibaria, Leuconostoc mesenteroides, and Enterococcus faecalis emerged for their lipolytic activities and ability to release hydroxy- and epoxy-fatty acids during walnut fermentation.
All around the world, schools and universities should re-think and update teaching to adjust to technological changes and exploit their potentialities by means of hybrid teaching (Limone, 2013). Considering teaching in presence as absolutely good and online teaching as bad and necessary only during the pandemic is ideological, reductive and wrong (Ferri, Moriggi, 2018). If properly used in an ad-hoc pedagogical approach, technology represents an opportunity for students (Bonaiuti, Dipace, 2021), who can participate in training and updating processes and better adapt to changes. The long and complex post-pandemic period should allow the experimentation of a better integration between teaching in the classroom and technologically ‘augmented’ teaching. The process of digitalisation and methodological innovation should become permanent, as suggested in Mission number 4 – Education and Research of the NPRR. This was the starting point for an explorative survey (Lucisano, Salerni, 2002) conducted with 400 students of the University of Bari in order to research their challenges and levels of satisfaction with the online courses attended in the a.a. 2020/2021. The survey shows the difficulties with distance teaching and presents an overview on possible future blended approaches.
The experience of the Covid-19 lockdown has suddenly accelerated the awareness process of the entire university faculty about the need to hybridise their teaching with digital tools (Trentin, Bocconi 2015; Perla, Scarinci, Amati 2021) transforming traditional scholarship of the Italian University in a gigantic field of experimentation of innovative practices (Perla, 2020, p. 562). This has brought out the importance of supporting the quality of university teaching through the commitment to address precise Faculty Development policies, specifically through the development of innovative experiences and the design of paths based on micro-credentials. This contribution reports some actions promoted by the University of Bari aimed at the innovation of university teaching and the results of a pilot course on micro-credentials.
13q14 deletion is the most recurrent chromosomal aberration reported in B-CLL, having a favorable prognostic significance when occurring as the sole cytogenetic alteration. However, its clinical outcome is also related to the deletion size and number of cells with the del(13)(q14) deletion. In 10% of cases, 13q14 deletion arises following a translocation event with multiple partner chromosomes, whose oncogenic impact has not been investigated so far due to the assumption of a possible role as a passenger mutation. Here, we describe a t(4;13)(q21;q14) translocation occurring in a B-CLL case from the diagnosis to spontaneous regression. FISH and SNP-array analyses revealed a heterozygous deletion at 4q21, leading to the loss of the Rho GTPase Activating Protein 24 (ARHGAP24) tumor suppressor gene, down-regulated in the patient RNA, in addition to the homozygous deletion at 13q14 involving DLEU2/miR15a/miR16-1 genes. Interestingly, targeted Next Generation Sequencing analysis of 54 genes related to B-CLL indicated no additional somatic mutation in the patient, underlining the relevance of this t(4;13)(q21;q14) aberration in the leukemogenic process. In all tested RNA samples, RT-qPCR experiments assessed the downregulation of the PCNA, MKI67, and TOP2A proliferation factor genes, and the BCL2 anti-apoptotic gene as well as the up-regulation of TP53 and CDKN1A tumor suppressors, indicating a low proliferation potential of the cells harboring the aberration. In addition, RNA-seq analyses identified four chimeric transcripts (ATG4B::PTMA, OAZ1::PTMA, ZFP36::PTMA, and PIM3::BRD1), two of which (ATG4B::PTMA and ZFP36::PTMA) failed to be detected at the remission, suggesting a possible transcriptional remodeling during the disease course. Overall, our results indicate a favorable prognostic impact of the described chromosomal aberration, as it arises a permissive molecular landscape to the spontaneous B-CLL regression in the patient, highlighting ARHGAP24 as a potentially relevant concurrent alteration to the 13q14 deletion in delineating B-CLL disease evolution.
Change Detection (CD) aims to distinguish surface changes based on bi-temporal remote sensing images. In recent years, deep neural models have made a breakthrough in CD processes. However, training a deep neural model requires a large volume of labelled training samples that are time-consuming and labour-intensive to acquire. With the aim of learning an accurate CD model with limited labelled data, we propose SENECA: a method based on a CD Siamese network, which takes advantage of both Transfer Learning (TL) and Active Learning (AL) to handle the constraint of limited supervision. More precisely, we jointly use AL and TL to adapt a CD model trained on a labelled source domain to a (related) target domain featured by restricted access to labelled data. We report results from an experimental evaluation involving five pairs of images acquired via Sentinel-2 satellites between 2015 and 2018 in various locations picked all over Asia and USA. The results show the beneficial effects of the proposed AL and TL strategies on the accuracy of the decisions made by the CD Siamese network and depict the merit of the proposed approach over competing CD baselines.
The individual and combined effect of sodium chloride and hydroxytyrosol on the colloidal properties and the chemical and physical stability of olive oil-in-water emulsions was explored by multivariate statistical analysis. Sodium chloride affected the dispersion degree of the emulsions causing an increase of droplet size and inducing flocculation phenomena; however, during storage, the presence of hydroxytyrosol, when added in combination with 2% and 5% of NaCl, retarded samples physical destabilization. A protective effect of salt on lipid hydroperoxides, over storage, was highlighted, mainly at the highest concentrations used. The analysis of volatile organic compounds allowed to identify different oxidation patterns as a consequence of NaCl addition and hydroxytyrosol; moreover, by applying a multivariate statistical approach, it was possible to highlight a positive effect of both NaCl and hydroxytyrosol over the reduction of some oxidation volatiles.
Anaemia is a global public health problem with major consequences for human health. Noninvasive methods must be investigated to determine a sick person's anaemic status or conduct screening campaigns, especially in resource-constrained areas of the earth. This study aims to prove that the colour of the sclera and scleral blood vessels extracted from digital images of the eye can be used to check the anaemic status of a person. To date, we have not found in the literature other studies that have attempted this promising approach. We propose a novel pipeline for anaemia estimation consisting of three main contributions: a sclera segmentation algorithm applied to near-taken digital photos of the eye, a vessel extraction algorithm, and a classifier to predict the anaemic status of a person vs normal controls. This study was based on the public dataset Eyes-defy-anaemia, which contains 218 eye pictures taken with a special device that removes any ambient light influence. Very interesting results have been achieved for the sclera segmentation task with good precision (88.53), recall (82.53) and F1 (84.10). The colour features and haemoglobin value appear to be well related allowing us to obtain an F2 score in the anaemia detection task of 86.4% using colour features from the whole sclera and of 83.8% using only vessels’ colour features.
Hepatitis E virus (HEV) is the etiological agent of acute viral hepatitis, a disease transmitted by the oral-faecal route. In Europe, zoonotic transmission of HEV-3 genotype is associated with the consumption of raw or slightly cooked meat of pigs and wild boars that are considered the main reservoirs. This work aims to assess the occurrence of swines' HEV RNA liver samples and rectal swabs slaughtered in Sicily using biomolecular methods. HEV-RNA was detected in 17.5 % (21/120) liver samples analyzed and in 3.7 % (3/81) rectal swabs examined. All positive samples were predicted as genotype 3 and subtype 3c (75 %). These data suggest a potential HEV transmission to humans through close contact with pig breeders, veterinarians, slaughterhouse personnel, and pork meat product consumption. Moreover, there are few scientific data evaluating the HEV spread around pigs and humans in Sicily. Therefore, further studies are necessary to correlate humans with swine serotypes and to assess the HEV presence and persistence in food and the risk during the slaughtering process. These surveys allow to clarify the role of the swine species as a potential source of infection for other domestic or wild animals and humans and to establish possible control measures throughout the food chain.
The diagnosis of mediastinal masses is challenging due to the variety of possiblepathologies , and its definitive diagnosis is mainly confirmed by histological evaluation. Sometimes some lesions may have a greater intravascular rather than mediastinal development and the collection of a biopsy sample becomes even more complex. In these cases endovascular catheter biopsy is helpful in the collection of the necessary biological material, having to adapt to the type of surface and consistency of the mass to be analyzed. Endovascular catheter biopsy was performed with a biliary forceps to sample a mediastinal mass with greater endovascular and cardiac development, with a hard and difficult to sample surface. The histological result was diagnosed with non-hodgkins lymphoma.
Background and objective: Neurodegenerative diseases are the most frequent age-related diseases. This type of disease, if not discovered in the initial stage, will compromise the quality of life of the affected subject. Thus, a timely diagnosis is of paramount importance. One of the most used tasks from neurologists to detect and determine the severity of the disease is analysing human gait. This work presents the dataset named "Beside Gait" containing timeseries of coordinates of extracted body joints of people with neurodegenerative diseases in various stages of the disease as well as control subjects. In addition, the novel Multi-Speed transformer technique will be presented and benchmarked against several other techniques making use of deep learning and Shallow Learning. The objective is to recognize subjects affected by some form of neurodegenerative disease in early stage using a computer vision technique making use of deep learning that can be integrated into a smartphone app for offline inference with the aim of promptly initiate investigations and treatment to improve the patient's quality of life. Methods: The recorded videos were processed, and the skeleton of the person in the video was extracted using pose estimation. The raw time-series coordinates of the joints extracted by the pose estimation algorithm were tested against novel deep neural network architectures and Shallow Learning techniques. In this work, the proposed Multi-Speed Transformer is benchmarked against other deep neural networks such as Temporal Convolutional Neural Networks, Transformers, as well as Shallow Learning techniques making use of feature extraction and different classifiers such as Random Forests, K Nearest Neighbours, Ada Boost, Linear and RBF SVM. The proposed Multi-Speed Transformer architecture has been developed to learn short and long-term patterns to model the various pathological gaits. Results: The Multi-Speed Transformer outperformed all other existing models reaching an accuracy of 96.9%, a sensitivity of 96.9%, a precision of 97.7%, and a specificity of 97.1% in binary classification. The accuracy in multi-class classification for detecting the presence of the disease in various stages is 71.6%, the sensitivity is 67.7%, and the specificity is 71.8%. In addition, tests have also been conducted against two other different activity recognition datasets, namely SHREC and JHMDB, in the exact same conditions. Multi-Speed Transformer has demonstrated to beat always all other tested techniques as well as the techniques reviewed in the state-of-the-art with respectively of accuracy 91.8% and 74%. Having those datasets more than two classes, specificity was not computed. Conclusions: The Multi-Speed Transformer is a valuable technique for neurodegenerative disease assessment through computer vision. In addition, the novel dataset "Beside Gait" here presented is an important starting point for future research work on automatic recognition of neurodegenerative diseases using gait analysis.
Hepatic steatosis is often a consequence of obesity. Adipose tissue is an important endocrine regulator of metabolic homeostasis in the body. In obesity, adipocytes become hypertrophic and develop an inflammatory phenotype, altering the panel of secreted adipokines. Moreover, excess fatty acids are, in part, released by adipocytes and delivered to the liver. These multiple pathways of adipose-liver crosstalk contribute to the development and progression of liver disease: TNFα induces hepatocyte dysfunction, excess of circulating fatty acids promotes hepatic steatosis and inflammation, whilst adipokines mediate and exacerbate liver injury. In this study, we investigated in vitro the effects and mechanisms of the crosstalk between adipocytes and hepatocytes, as a function of the different adipocyte status (mature vs hypertrophic) being mediated by soluble factors. We employed the conditioned medium method to test how mature and hypertrophic adipocytes distinctively affect the liver, leading to metabolic dysfunction. The media collected from adipocytes were characterized by high triglyceride content and led to lipid accumulation and fat-dependent dysfunction in hepatocytes. The present findings seem to suggest that, in addition to triglycerides, other soluble mediators, cytokines, are released by mature and hypertrophic adipocytes and influence the metabolic status of liver cells. Understanding the precise factors involved in the pathogenesis and pathophysiology of NAFLD in obesity will provide important insights into the mechanisms responsible for the metabolic complications of obesity, paving the way for new possible approaches.
The attention deserved to the recognition of qualifications (degrees) and competencies acquired elsewhere, as a means for equity and inclusion in education has progressively influenced educational research and also educational policy and decision-making. Different European countries, agreeing with the importance of valorising informal learning, have expressed the need to make learning 'beyond the classroom' visible and to assess it in a more responsive and effective way. Despite the common educational policy framework, in the European area, students with a migratory background (i.e., migrants and/or refugees) continue to struggle in accessing university paths. Given the persistent difficulties in ensuring migrants and refugees equal access to education and training opportunities, this article reports a systematic review study focused on recognition practices realized, over the last 5 years, in the European higher education context. Against the backdrop of the learning recognition debate, the results of this literature review study show a scattered landscape of local practices, sometimes, misaligned with the educational policies defined at the European level. The present study represents a useful step in reflecting on what actions are expected to be designed and implemented by higher education institutions in order to ensure a culturally responsive and equitable education for all.
Introduction Recently, accurate machine learning and deep learning approaches have been dedicated to the investigation of breast cancer invasive disease events (IDEs), such as recurrence, contralateral and second cancers. However, such approaches are poorly interpretable. Methods Thus, we designed an Explainable Artificial Intelligence (XAI) framework to investigate IDEs within a cohort of 486 breast cancer patients enrolled at IRCCS Istituto Tumori “Giovanni Paolo II” in Bari, Italy. Using Shapley values, we determined the IDE driving features according to two periods, often adopted in clinical practice, of 5 and 10 years from the first tumor diagnosis. Results Age, tumor diameter, surgery type, and multiplicity are predominant within the 5-year frame, while therapy-related features, including hormone, chemotherapy schemes and lymphovascular invasion, dominate the 10-year IDE prediction. Estrogen Receptor (ER), proliferation marker Ki67 and metastatic lymph nodes affect both frames. Discussion Thus, our framework aims at shortening the distance between AI and clinical practice
Controlling and planning the removal of invasive species are topics of outmost importance in management of natural resources because of the severe ecological damages and economic losses caused by non-native alien species. Optimal management strategies often rely on coupling population dynamics models with optimization procedures to achieve an effective allocation of limited resources for removing invasive species from hosting ecosystems. We analyse a parabolic optimal control model to simulate the best spatiotemporal strategy for the removal of the species when a budget constraint is applied. The model also predicts the species spread under the control action. We improve the capability of the model to reproduce realistic scenarios by introducing an advection term in the state equation. That allows to model the action of external forces, like currents or winds, which might bias dispersal in certain directions. The analytical properties of the model are discussed under suitable boundary conditions. As a further original contribution, we introduce a novel numerical procedure for approximating the solution reducing the computational costs in view of its implementation as a support decision tool. Then we test the approach by simulating the spread and the control of a hypothetical invasive plant in the territory of the Italian Sardinia island. To reproduce the anisotropy of the diffusion we include the effect of the altitude in the habitat suitability of the species.
Semi-natural habitats are considered fundamental for biodiversity conservation and the provision of biological control services in agroecosystems. However, crop pests that exploit different types of habitats during their life cycle might thrive in complex landscapes. Understanding how crop pests use a range of resources across the agroecosystem is fundamental to plan sustainable crop protection strategies. Here we explored the effects of local habitat type (i.e., annual crop, perennial crop, dry grassland and forest) and landscape composition (increasing cover of forest and dry grassland) on stink bug pests in Mediterranean agroecosystems. Stink bugs (Hemiptera: Pentatomoidea) are polyphagous and highly mobile organisms considered a serious threat for numerous crops worldwide. To better understand how stink bugs used different habitats, we sampled active adults and juveniles in spring and summer, and overwintering individuals in autumn and winter. Our results showed that semi-natural habitats supported more abundant stink bug populations, potentially providing alternative feeding, reproduction, and overwintering sites. Specifically, we found more active adults and juveniles in dry grasslands, while forests hosted greater numbers of overwintering individuals. Moreover, forest cover in the landscape was positively related to active stink bug abundance in all sampled habitats. Finally, we found complex landscapes rich in overall semi-natural habitats to support higher abundance of overwintering individuals in both forests and dry grasslands, while perennial crop might provide suitable overwintering sites in highly simplified landscape. These results have important implications for pest management as crop fields situated in complex landscapes might be more susceptible to pest infestation. Effective control strategies may require a landscape-based approach.
New financing in clean energy technologies plays a progressively important role in increasing energy access in Sub-Saharan Africa (SSA). This research investigates the salient social dimensions of clean electricity access with the view to identify the most suitable SSA countries for funding and implementing decentralised renewable energy systems and sheds light on the opportunities for improving social conditions through clean electrification. Our multi-dimensional analysis of social considerations culminates in the Social Clean Energy Access (Social CEA) Index. The composite indicator structure was empirically tested and improved in terms of accuracy and robustness for 35 SSA countries. The Social CEA index captures the status of social factors on health, education, economic development, gender equality, and quality of life related to electricity access. The Social CEA Index strength is assessed by exploring the synergies between electricity access and social development and its progress over time is evaluated through a dimension's breakdown approach in Ghana.
Background and aims: Proprotein Convertase Subtilisin/Kexin type 9 inhibitors (PCSK9i) are recommended in patients at high and very-high cardiovascular (CV) risk, with documented atherosclerotic CV disease (ASCVD), and for very-high risk patients with familial hypercholesterolaemia not achieving LDL-cholesterol (LDL-C) goal while receiving maximally tolerated dose of lipid-lowering therapy (LLT). However, single country real-life data, reporting the use of PCSK9i in clinical practice, are limited. Therefore, we designed AT-TARGET-IT, an Italian, multicenter, observational registry on the use of PCSK9i in clinical practice. Methods: All data were recorded at the time of the first prescription and at the latest observation preceding inclusion in the study. Results: 798 patients were enrolled. The median reduction in LDL-C levels was 64.9%. After stratification for CV risk, 63.8% achieved LDL-C target; of them, 83.3% took LLTs at PCSK9i initiation and 16.7% did not. 760 patients (95.2%) showed high adherence to therapy, 13 (1.6%) partial adherence, and 25 (3.1%) poor adherence. At 6 months, 99.7% of patients enrolled in the study remained on therapy; there were 519 and 423 patients in the study with a follow-up of at least 12 and 18 months, respectively. Persistence in these groups was 98.1% and 97.5%, respectively. Overall, 3.5% of patients discontinued therapy. No differences in efficacy, adherence, and persistence were found between alirocumab and evolocumab. Conclusions: PCSK9i are safe and effective in clinical practice, leading to very high adherence and persistence to therapy, and achievement of recommended LDL-C target in most patients, especially when used as combination therapy.
Cannabinoid type 2 receptor (CB2R) is a G-protein-coupled receptor that, together with Cannabinoid type 1 receptor (CB1R), endogenous cannabinoids and enzymes responsible for their synthesis and degradation, forms the EndoCannabinoid System (ECS). In the last decade, several studies have shown that CB2R is overexpressed in activated central nervous system (CNS) microglia cells, in disorders based on an inflammatory state, such as neurodegenerative diseases, neuropathic pain, and cancer. For this reason, the anti-inflammatory and immune-modulatory potentials of CB2R ligands are emerging as a novel therapeutic approach. The design of selective ligands is however hampered by the high sequence homology of transmembrane domains of CB1R and CB2R. Based on a recent three-arm pharmacophore hypothesis and latest CB2R crystal structures, we designed, synthesized, and evaluated a series of new N-adamantyl-anthranil amide derivatives as CB2R selective ligands. Interestingly, this new class of compounds displayed a high affinity for human CB2R along with an excellent selectivity respect to CB1R. In this respect, compounds exhibiting the best pharmacodynamic profile in terms of CB2R affinity were also evaluated for the functional behavior and molecular docking simulations provided a sound rationale by highlighting the relevance of the arm 1 substitution to prompt CB2R action. Moreover, the modulation of the pro- and anti-inflammatory cytokines production was also investigated to exert the ability of the best compounds to modulate the inflammatory cascade.
Aim: This guideline (GL) is aimed at providing a reference for the management of non-functioning, benign thyroid nodules causing local symptoms in adults outside of pregnancy. Methods: This GL has been developed following the methods described in the Manual of the National Guideline System. For each question, the panel appointed by Associazione Medici Endocrinology(AME) identified potentially relevant outcomes, which were then rated for their impact on therapeutic choices. Only outcomes classified as "critical" and "important" were considered in the systematic review of evidence and only those classified as "critical" were considered in the formulation of recommendations. Results: The present GL contains recommendations about the respective roles of surgery and minimally invasive treatments for the management of benign symptomatic thyroid nodules. We suggest hemithyroidectomy plus isthmectomy as the first-choice surgical treatment, provided that clinically significant disease is not present in the contralateral thyroid lobe. Total thyroidectomy should be considered for patients with clinically significant disease in the contralateral thyroid lobe. We suggest considering thermo-ablation as an alternative option to surgery for patients with a symptomatic, solid, benign, single, or dominant thyroid nodule. These recommendations apply to outpatients, either in primary care or when referred to specialists. Conclusion: The present GL is directed to endocrinologists, surgeons, and interventional radiologists working in hospitals, in territorial services, or private practice, general practitioners, and patients. The available data suggest that the implementation of this GL recommendations will result in the progressive reduction of surgical procedures for benign thyroid nodular disease, with a decreased number of admissions to surgical departments for non-malignant conditions and more rapid access to patients with thyroid cancer. Importantly, a reduction of indirect costs due to long-term replacement therapy and the management of surgical complications may also be speculated.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.