•A Machine Learning model highlighted plans with expected low gamma passing rate•Complexity and expected gamma were monitored prospectively with Lean Six Sigma.•A Poka Yoke system automatically ...identified plans at risk of failure each day.•Plans considered at risk underwent measurement and were re-optimized if necessary.•Among 1722 volumetric modulated plans, 9 out of 29 at risk were actual failures.
Radiotherapy plans with excessive complexity exhibit higher uncertainties and worse patient-specific quality assurance (PSQA) results, while the workload of measurement-based PSQA can impact the efficiency of the radiotherapy workflow. Machine Learning (ML) and Lean Six Sigma, a process optimization method, were implemented to adopt a targeted PSQA approach, aiming to reduce workload, risk of failures, and monitor complexity.
Lean Six Sigma was applied using DMAIC (define, measure, analyze, improve, and control) steps. Ten complexity metrics were computed for 69,811 volumetric modulated arc therapy (VMAT) arcs from 28,612 plans delivered in our Institute (2013–2021). Outlier complexities were defined as >95th-percentile of the historical distributions, stratified by treatment. An ML model was trained to predict the gamma passing rate (GPR-3 %/1mm) of an arc given its complexity. A decision support system was developed to monitor the complexity and expected GPR. Plans at risk of PSQA failure, either extremely complex or with average GPR <90 %, were identified. The tool’s impact was assessed after nine months of clinical use.
Among 1,722 VMAT plans monitored prospectively, 29 (1.7 %) were found at risk of failure. Planners reacted by performing PSQA measurement and re-optimizing the plan. Occurrences of outlier complexities remained stable within 5 %. The expected GPR increased from a median of 97.4 % to 98.2 % (Mann-Whitney p < 0.05) due to plan re-optimization.
ML and Lean Six Sigma have been implemented in clinical practice enabling a targeted measurement-based PSQA approach for plans at risk of failure to improve overall quality and patient safety.
Smart Agriculture (SA) is an evolution of Precision Farming (PF). It has technological basis very close to the paradigms of Industry 4.0 (Ind-4.0), so that it is also often referred to as Agriculture ...4.0. After the proposal of a brief historical examination that provides a conceptual frame to the above terms, the common aspects of SA and Ind-4.0 are analyzed. These are primarily to be found in the cognitive approaches of Knowledge Management 4.0 (KM4.0, the actual theoretical basis of Ind-4.0), which underlines the need to use Integrated Information Systems (IIS) to manage all the activity areas of any production system. Based upon an infological approach, "raw data" becomes "information" only when useful to (or actually used in) a decision-making process. Thus, an IIS must be always designed according to such a view, and KM4.0 conditions the way of collecting and processing data on farms, together with the "information precision" by which the production system is managed. Such precision needs, on their turn, depend on the hierarchical level and the "Macrodomain of Prevailing Interest" (MPI) related to each decision, where the latter identifies a predominant viewpoint through which a system can be analyzed according to a prevailing purpose. Four main MPIs are here proposed: (1) physical and chemical, (2) biological and ecological, (3) productive and hierarchical, and (4) economic and social. In each MPI, the quality of the knowledge depends on the cognitive level and the maturity of the methodological approaches there achieved. The reliability of information tends to decrease from the first to the fourth MPI; lower the reliability, larger the tolerance margins that a measurement systems must ensure. Some practical examples are then discussed, taking into account some IIS-monitoring solutions of increasing complexity in relation to information integration needs and related data fusion approaches. The analysis concludes with the proposal of new operational indications for the verification and certification of the reliability of the information on the entire decision-making chain.
The HIV-1 matrix protein p17 (p17) is a pleiotropic molecule impacting on different cell types. Its interaction with many cellular proteins underlines the importance of the viral protein as a major ...determinant of human specific adaptation. We previously showed the proangiogenic capability of p17. Here, by integrating functional analysis and receptor binding, we identify a functional epitope that displays molecular mimicry with human erythropoietin (EPO) and promotes angiogenesis through common beta chain receptor (βCR) activation. The functional EPO-like epitope was found to be present in the matrix protein of HIV-1 ancestors SIV originated in chimpanzees (SIVcpz) and gorillas (SIVgor) but not in that of HIV-2 and its ancestor SIVsmm from sooty mangabeys. According to biological data, evolution of the EPO-like epitope showed a clear differentiation between HIV-1/SIVcpz-gor and HIV-2/SIVsmm branches, thus highlighting this epitope on p17 as a divergent signature discriminating HIV-1 and HIV-2 ancestors. P17 is known to enhance HIV-1 replication. Similarly to other βCR ligands, p17 is capable of attracting and activating HIV-1 target cells and promoting a proinflammatory microenvironment. Thus, it is tempting to speculate that acquisition of an epitope on the matrix proteins of HIV-1 ancestors capable of triggering βCR may have represented a critical step to enhance viral aggressiveness and early human-to-human SIVcpz/gor dissemination. The hypothesis that the p17/βCR interaction and βCR abnormal stimulation may also play a role in sustaining chronic activation and inflammation, thus marking the difference between HIV-1 and HIV-2 in term of pathogenicity, needs further investigation.
The treatment of cystic fibrosis (CF) patients homozygous for the
mutation with Orkambi
, a combination of a corrector (lumacaftor) and a potentiator (ivacaftor) of the mutated CFTR protein, resulted ...in some amelioration of the respiratory function. However, a great variability in the clinical response was also observed. The aim of this study was to evaluate the response to Orkambi
in a small cohort of F508del/F508del patients (
= 14) in terms of clinical and laboratory parameters, including ex vivo CFTR activity in mononuclear cells (MNCs), during a 12-month treatment. Patients responded with an increase in percent predicted forced expiratory volume in 1 s (FEV
%) and body mass index (BMI) as well as with a decrease in white blood cell (WBC) total counts and serum C-reactive protein (CRP) levels, although not significantly. Sweat chloride and CFTR-dependent chloride efflux were found to decrease and increase, respectively, as compared with pre-therapy values. CFTR and BMI showed a statistically significant correlation during Orkambi
treatment. Clustering analysis showed that CFTR, BMI, sweat chloride, FEV
%, and WBC were strongly associated. These data support the notion that CFTR-dependent chloride efflux in MNCs should be investigated as a sensitive outcome measure of Orkambi
treatment in CF patients.
Of-Pis1 is a potent piscidin antimicrobial peptide (AMP), recently isolated from rock bream (Oplegnathus fasciatus). This rich in histidines and glycines 24-amino acid peptide displays high and broad ...antimicrobial activity and no significant hemolytic toxicity against human erythrocytes, suggesting low toxicity. To better understand the mechanism of action of Of-Pis1 and its potential selectivity, using NMR and CD spectroscopies, we studied the interaction with eukaryotic and procaryotic membranes and membrane models. Anionic sodium dodecyl sulfate (SDS) and lipopolysaccharide (LPS) micelles were used to mimic procaryotic membranes, while zwitterionic dodecyl phosphocholine (DPC) was used as eukaryotic membrane surrogate. In an aqueous environment, Of-Pis1 adopts a flexible random coil conformation. In DPC and SDS instead, the N-terminal region of Of-Pis1 forms an amphipathic α-helix with the non-polar face in close contact with the micelles. Slower solvent exchange and higher pKas of the histidine residues in SDS than in DPC suggest that Of-Pis1 interacts more tightly with SDS. Of-Pis1 also binds tightly and structurally perturbs LPS micelles. Of-Pis1 interacts with both Escherichia coli and mammalian cell membranes, but only in the presence of Escherichia coli membranes it populates the helical conformation. Furthermore, ligand-based NMR experiments support a tighter and more specific interaction with bacterial than with eukaryotic membranes. Overall, these data clearly show the selective interaction of this broadly active AMP with bacterial over eukaryotic membranes. The conformational information is discussed in terms of Of-Pis1 amino acid sequence and composition to provide insights useful to design more potent and selective AMPs.
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•Of-Pis1 is a piscidin peptide found in from rock bream.•It displays high and broad antimicrobial activity and potential low toxicity.•Of-Pis1 forms an amphipathic helix in its N-terminal region in membrane models.•Of-Pis1 selectively interacts with bacterial over eukaryotic membranes.•His and Gly residues at the right positions in the sequence provide for selectivity.
Generated by a hierarchical and multiscale self-assembling phenomenon, peptide-based hydrogels (HGs) are soft materials useful for a variety of applications. Short and ultra-short peptides are ...intriguing building blocks for hydrogel fabrication. These matrices can also be obtained by mixing low-molecular-weight peptides with other chemical entities (e.g., polymers, other peptides). The combination of two or more constituents opens the door to the development of hybrid systems with tunable mechanical properties and unexpected biofunctionalities or morphologies. For this scope, the formulation, the multiscale analysis, and the supramolecular characterization of novel hybrid peptide-polymer hydrogels are herein described. The proposed matrices contain the Fmoc-FF (N
-fluorenylmethyloxycarbonyl diphenylalanine) hydrogelator at a concentration of 0.5 wt% (5.0 mg/mL) and a diacrylate α-/ω-substituted polyethylene-glycol derivative (PEGDA). Two PEGDA derivatives, PEGDA 1 and PEGDA2 (mean molecular weights of 575 and 250 Da, respectively), are mixed with Fmoc-FF at different ratios (Fmoc-FF/PEGDA at 1/1, 1/2, 1/5, 1/10 mol/mol). All the multicomponent hybrid peptide-polymer hydrogels are scrutinized with a large panel of analytical techniques (including proton relaxometry, FTIR, WAXS, rheometry, and scanning electronic microscopy). The matrices were found to be able to generate mechanical responses in the 2-8 kPa range, producing a panel of tunable materials with the same chemical composition. The release of a model drug (Naphthol Yellow S) is reported too. The tunable features, the different topologies, and the versatility of the proposed materials open the door to the development of tools for different applicative areas, including diagnostics, liquid biopsies and responsive materials. The incorporation of a diacrylate function also suggests the possible development of interpenetrating networks upon cross-linking reactions. All the collected data allow a mutual comparison between the different matrices, thus confirming the significance of the hybrid peptide/polymer-based methodology as a strategy for the design of innovative materials.
Each application of Precision Agriculture or Forestry should be supported by a technological platform able to perform, in an integrated way, the following data-information cycle functions: 1) data ...collection; 2) data processing; 3) data analysis and evaluation; 4) use of information. In accordance to this view, information are data that are usefully used in a decision making process or within a reporting protocol destined to users external to the enterprise (certification tasks). In order to manage the platform in a complete and efficient manner an adequate information system is needed. Firstly, the paper shows a classification of the possible monitoring solutions based on the different enterprise typologies, highlighting the main technological and interpretative requirements. Secondly, some case studies related to the application of operational monitoring in orchards and forestry are introduced, mainly focusing on some peculiar aspects of the algorithms developed for the implementation of the inference engines.
Multicomponent hydrogels (HGs) based on ultrashort aromatic peptides have been exploited as biocompatible matrices for tissue engineering applications, the delivery of therapeutic and diagnostic ...agents, and the development of biosensors. Due to its capability to gel under physiological conditions of pH and ionic strength, the low molecular-weight Fmoc-FF (Nα-fluorenylmethoxycarbonyl-diphenylalanine) homodimer is one of the most studied hydrogelators. The introduction into the Fmoc-FF hydrogel of additional molecules like protein, organic compounds, or other peptide sequences often allows the generation of novel hydrogels with improved mechanical and functional properties. In this perspective, here we studied a library of novel multicomponent Fmoc-FF based hydrogels doped with different amounts of the tripeptide Fmoc-FFX (in which X= Cys, Ser, or Thr). The insertion of these tripeptides allows to obtain hydrogels functionalized with thiol or alcohol groups that can be used for their chemical post-derivatization with bioactive molecules of interest like diagnostic or biosensing agents. These novel multicomponent hydrogels share a similar peptide organization in their supramolecular matrix. The hydrogels’ biocompatibility, and their propensity to support adhesion, proliferation, and even cell differentiation, assessed in vitro on fibroblast cell lines, allows us to conclude that the hybrid hydrogels are not toxic and can potentially act as a scaffold and support for cell culture growth.
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