The edge cloud: A holistic view of communication, computation and caching

The evolution of communication networks shows a clear shift of focus from just improving the communications aspects to enabling new important services, from Industry 4.0 to automated driving, virtual/augmented reality, Internet of Things (IoT), and so on. This trend is evident in the roadmap planned for the deployment of the fifth generation (5G) communication networks. This ambitious goal requires a paradigm shift towards a vision that looks at communication, computation and caching (3C) resources as three components of a single holistic system. The further step is to bring these 3C resources closer to the mobile user, at the edge of the network, to enable very low latency and high reliability services. The scope of this chapter is to show that signal processing techniques can play a key role in this new vision. In particular, we motivate the joint optimization of 3C resources. Then we show how graph-based representations can play a key role in building effective learning methods and devising innovative resource allocation techniques.Comment: to appear in the book "Cooperative and Graph Signal Pocessing: Principles and Applications", P. Djuric and C. Richard Eds., Academic Press, Elsevier, 201

Ultrafiltration Fibers like Bioreactors

A polysulfone ultrafiltration membrane with pectinase physically immobilized on it by a dynamic formation method was used to examine the potential of these reactive membranes in applications involving solutions containing pectin. The effect of various operational parameters such as: pH of enzyme and pectin solutions, NaCl, retentate flow rate, and enzyme (Ce) and substrate (Cp) concentrations on the production of reducing compounds expressed as galacturonic acid (Ca), was investigated. It was found that the maximum Ca values were obtained when: (i) enzyme solution to immobilize, without NaCl, had pH values between 4.2 and 4.6 and enzyme concentration from 5.0 to 7.5 mg/mL; (ii) pectin solution had initial pH values between 4.2 and 5.0 and a concentration of 3 mg/mL; and (iii) retentate flow rate was 0.025 L/minFil: Carrin, Maria Elena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Ceci, Liliana Noemí. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Lozano, Jorge Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentin

Graph-based learning under perturbations via total least-squares

Graphs are pervasive in different fields unveiling complex relationships between data. Two major graph-based learning tasks are topology identification and inference of signals over graphs. Among the possible models to explain data interdependencies, structural equation models (SEMs) accommodate a gamut of applications involving topology identification. Obtaining conventional SEMs though requires measurements across nodes. On the other hand, typical signal inference approaches “blindly trust” a given nominal topology. In practice however, signal or topology perturbations may be present in both tasks, due to model mismatch, outliers, outages or adversarial behavior. To cope with such perturbations, this work introduces a regularized total least-squares (TLS) approach and iterative algorithms with convergence guarantees to solve both tasks. Further generalizations are also considered relying on structured and/or weighted TLS when extra prior information on the perturbation is available. Analyses with simulated and real data corroborate the effectiveness of the novel TLS-based approaches

Impact of segmentation and discretization on radiomic features in 68Ga-DOTA-TOC PET/CT images of neuroendocrine tumor

OBJECTIVE: To identify the impact of segmentation methods and intensity discretization on radiomic features (RFs) extraction from 68Ga-DOTA-TOC PET images in patients with neuroendocrine tumors.METHODS: Forty-nine patients were retrospectively analyzed. Tumor contouring was performed manually by four different operators and with a semi-automatic edge-based segmentation (SAEB) algorithm. Three SUVmax fixed thresholds (20, 30, 40%) were applied. Fifty-one RFs were extracted applying two different intensity rescale factors for gray-level discretization: one absolute (AR60 = SUV from 0 to 60) and one relative (RR = min-max of the VOI SUV). Dice similarity coefficient (DSC) was calculated to quantify segmentation agreement between different segmentation methods. The impact of segmentation and discretization on RFs was assessed by intra-class correlation coefficients (ICC) and the coefficient of variance (COVL). The RFs' correlation with volume and SUVmax was analyzed by calculating Pearson's correlation coefficients.RESULTS: DSC mean value was 0.75 ± 0.11 (0.45-0.92) between SAEB and operators and 0.78 ± 0.09 (0.36-0.97), among the four manual segmentations. The study showed high robustness (ICC >0.9): (a) in 64.7% of RFs for segmentation methods using AR60, improved by applying SUVmax threshold of 40% (86.5%); (b) in 50.9% of RFs for different SUVmax thresholds using AR60; and (c) in 37% of RFs for discretization settings using different segmentation methods. Several RFs were not correlated with volume and SUVmax.CONCLUSIONS: RFs robustness to manual segmentation resulted higher in NET 68Ga-DOTA-TOC images compared to 18F-FDG PET/CT images. Forty percent SUVmax thresholds yield superior RFs stability among operators, however leading to a possible loss of biological information. SAEB segmentation appears to be an optimal alternative to manual segmentation, but further validations are needed. Finally, discretization settings highly impacted on RFs robustness and should always be stated

Gerstmann-Sträussler-Scheinker disease amyloid protein polymerizes according to the "dock-and-lock" model.

Prion protein (PrP) amyloid formation is a central feature of genetic and acquired prion diseases such as Gerstmann-Sträussler-Scheinker disease (GSS) and variant Creutzfeldt-Jakob disease. Themajor component of GSS amyloid is a PrP fragment spanning residues ∼82-146, which when synthesized as a peptide, readily forms fibrils featuring GSS amyloid. The present study employed surface plasmon resonance (SPR) to characterize the binding events underlying PrP82-146 oligomerization at the first stages of fibrillization, according to evidence suggesting a pathogenic role of prefibrillar oligomers rather than mature amyloid fibrils. We followed in real time the binding reactions occurring during short term (seconds) addition of PrP82-146 small oligomers (1-5-mers, flowing species) onto soluble prefibrillar PrP82-146 aggregates immobilized on the sensor surface. SPR data confirmed very efficient aggregation/elongation, consistent with the hypothesis of nucleation-dependent polymerization process. Much lower binding was observed when PrP82-146 flowed onto the scrambled sequence of PrP82-146 or onto prefibrillar Aβ42 aggregates. As previously found with Aβ40, SPR data could be adequately fitted by equations modeling the "dock-and-lock" mechanism, in which the "locking" step is due to sequential conformational changes, each increasing the affinity of the monomerfor the fibril until a condition of irreversible binding is reached. However, these conformational changes (i.e. the locking steps) appear to be faster and easier with PrP82-146 than with Aβ40. Such differences suggest that PrP82-146 has a greater propensity to polymerize and greater stability of the aggregates. © 2006 by The American Society for Biochemistry and Molecular Biology, Inc

18F-FDG Pet Parameters and Radiomics Features Analysis in Advanced Nsclc Treated with Immunotherapy as Predictors of Therapy Response and Survival

Objectives: (1.1) to evaluate the association between baseline 18F-FDG PET/CT semi-quantitative parameters of the primary lesion with progression free survival (PFS), overall survival (OS) and response to immunotherapy, in advanced non-small cell lung carcinoma (NSCLC) patients eligible for immunotherapy; (1.2) to evaluate the application of radiomics analysis of the primary lesion to identify features predictive of response to immunotherapy; (1.3) to evaluate if tumor burden assessed by 18F-FDG PET/CT (N and M factors) is associated with PFS and OS. Materials and Methods: we retrospectively analyzed clinical records of advanced NCSLC patients (stage IIIb/c or stage IV) candidate to immunotherapy who performed 18F-FDG PET/CT before treatment to stage the disease. Fifty-seven (57) patients were included in the analysis (F:M 17:40; median age = 69 years old). Notably, 38/57 of patients had adenocarcinoma (AC), 10/57 squamous cell carcinoma (SCC) and 9/57 were not otherwise specified (NOS). Overall, 47.4% patients were stage IVA, 42.1% IVB and 8.8% IIIB. Immunotherapy was performed as front-line therapy in 42/57 patients and as second line therapy after chemotherapy platinum-based in 15/57. The median follow up after starting immunotherapy was 10 months (range: 1.5–68.6). Therapy response was assessed by RECIST 1.1 criteria (CT evaluation every 4 cycles of therapy) in 48/57 patients or when not feasible by clinical and laboratory data (fast disease progression or worsening of patient clinical condition in nine patients). Radiomics analysis was performed by applying regions of interest (ROIs) of the primary tumor delineated manually by two operators and semi-automatically applying a threshold at 40% of SUVmax. Results: (1.1) metabolic tumor volume (MTV) (p = 0.028) and total lesion glycolysis (TLG) (p = 0.035) were significantly associated with progressive vs. non-progressive disease status. Patients with higher values of MTV and TLG had higher probability of disease progression, compared to those patients presenting with lower values. SUVmax did not show correlation with PD status, PFS and OS. MTV (p = 0.027) and TLG (p = 0.022) also resulted in being significantly different among PR, SD and PD groups, while SUVmax was confirmed to not be associated with response to therapy (p = 0.427). (1.2) We observed the association of several radiomics features with PD status. Namely, patients with high tumor volume, TLG and heterogeneity expressed by “skewness” and “kurtosis” had a higher probability of failing immunotherapy. (1.3) M status at 18F-FDG PET/CT was significantly associated with PFS (p = 0.002) and OS (p = 0.049). No significant associations were observed for N status. Conclusions: 18F-FDG PET/CT performed before the start of immunotherapy might be an important prognostic tool able to predict the disease progression and response to immunotherapy in patients with advanced NSCLC, since MTV, TLG and radiomics features (volume and heterogeneity) are associated with disease progression

The oral and gut microbiota: beyond a short communication

Introduction. The current treatment and prevention of oral disorders, dental caries, periodontal and gum diseases, follow a very non-specific control of plaque as the main causative factor. The main therapeutically approach is carried out on the sole perspective to keep the levels of oral bacteria in an acceptable range compatible with one-way vision of oral-mouth health, as something completely separated from a systemic microbial homeostasis (dysbiosis) concomitant present in the gut. A sealed compartmental view which sees separate and incommunicable responses to a specific condition without considering the presence of interacting confounding factors can negatively influence the diagnosis a diseases and of course its progression. A general non-specific antimicrobial with more general antiplaque therapy based mainly on oral care products together with surgery interventions represent at the moment the only mechanical responses in treating oral diseases. Material and method. The present paper is a narrative review concening interractions between oral and gut microbiota, with a focus on the interdisciplinary approach in antimicrobial treatment. Pubmed, Cochrane Library database were used for searching engines. Key words used were as follows: "inflammatory bowel syndrome (IBS)", "ulcerative colitis", "oral dysbiosis", "gut dysbiosis", "probiotics", "periodontitis". Results and discussions. Literature research showed that there are few issues to be discussed the ever increasing resistance to antibiotics, the high consumption of industrial food and sugars and their negatively effect on gut and oral microbiota. There is a need to highlight and develop a novel philosophical approach in the treatments for oral diseases that will necessarily involve non-conventional antimicrobial solutions. Such approaches should preferably reduce the consumption of both intestinal and oral microbiota, that are intimately connected and host approximately well over 1000 different species of bacteria at 108–109 bacteria per mL of mucous and saliva. Preventive approaches based upon the restoration of the microbial ecological balance, rather than elimination of the disease associated species, have been proposed. Conclusions. Having both oral-gut microbiota screened is an essential moment that influence the healthy immune modulatory and regenerative capacity of the body and, the new proposed formula integrates a wider screen on the patients where oral condition is strictly evaluated together with gut screen; therefore any proposed treatment will be inevitably sustained by the use of prebiotics and probiotics to promote health-associated bacterial growth. Keywords: inflammatory bowel syndrome (IBS), ulcerative colitis, oral dysbiosis, gut dysbiosis, probiotics, periodontitis

Essential oils utility implications in symptomatic Burning Mouth Syndrome

Introduction. Burning mouth syndrome (BMS) is a clinical condition characterized by the presence of chronic pain in absence of clinically visible lesions of the oral mucosa. The etiology is uncertain and the therapeutic strategies still controversial. The objective of this prospective study is to analyze the efficacy of essential oils-based mouthwashes in the therapy of BMS. Material and method. This study included 16 patients affected by BMS who were treated with essential oils-based mouthwashes and glucose solution on alternated days for 30 days. Symptomatology was evaluated after 15, 30 and 90 days. Results and discussions. A the end of the treatment, most of the patients (67%) referred an improvement of symptoms up to complete remission in 90 days. Conclusions. Based on this study, essential oils-based mouthwashes could represent a valid aid in the treatment of BMS. Further studies are necessary in order to identify effective and standardized therapeutic protocols. Keywords: Burning Mouth Syndrome; oral rinse; essential oils; therapeutic strategies

Biostimulation with low-level laser therapy and its effects on soft and hard tissue regeneration. Literature review

Objective. Low-Level Laser Therapy encourages the healing process, reduces inflammation and pain. The aim of this study is to identify the impact of Low-Level Laser Therapy on tissue regeneration with special attention to hard tissues and to compare the effect of several wave lengths in the proliferation and differentiation of cells. Methods. The keywords used were “bone regeneration”, “laser therapy”, “photobiomodulation” OR “bio-stimulation”, “Low-Level Laser therapy” OR “LLLT”, “osteoblast proliferation” AND “differentiation”. Results. The bio-stimulation with Low-Level Laser Therapy also seems to interfere with the osseous integration of implants, by increasing its adherence on the bone-implant surfaces. Evidence has shown that Low-Level Laser Therapy influences the cellular proliferation and differentiation. Conclusions. Low-Level Laser Therapy is a promising therapy in the field of regeneration, but further studies are needed in order to define the standard protocol

Advancing microbiome research with machine learning : key findings from the ML4Microbiome COST action

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory 'omics' features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices