943 resultados para In silico screening
Resumo:
Background The evaluation of the elderly’s ability to manage medication through the use of a validated tool can be a significant step in identifying inabilities and needs, with the objective of increasing their self-care skills, and promoting successful aging. Aim of the review To identify studies assessing the elderly’s functional ability to manage their own medication. Method For the search strategy, the PICO method was used: P—Population(elderly), I—Instruments (tools for assessing medication management ability), C—Context (community) and O—Outcomes (functional ability to manage medication). Thefinal search query was run in MEDLINE/PubMed,CINAHL Plus, ISI Web of Science and Scopus. The whole process was developed according to the PRISMA statement. Results The search retrieved 8051 records. In each screening stage, the selection criteria were applied to eliminate records where at least one of the exclusion criteria was verified. At the end of this selection, we obtained a total of 18 papers (17 studies). The results allow the conclusion to be drawn that studies use several different instruments, most of them not validated. The authors agree that medication management abilities decrease as cognitive impairment increases, even if a lot of studies assess only the physical dimension. DRUGS was the instrument most often used. Conclusion Older adults’ ability to manage their medication should be assessed using tools specifically built and validate for the purpose. DRUGS (which uses the real regimen taken by the elderly) was the most widely used assessment instrument in the screened studies.
Resumo:
The topic of this thesis is the DFT computational study of the mechanisms for the synthesis of chiral 3,4,5-trisubstituted piperidines and 2,6-disubstituted morpholines. The goal of this synthesis is to use, the same substrate containing two electrophilic sites: an α,β-unsaturated ester and a ketone, which evolve according to the nucleophile used (cyanide, phenyl sulfide) through different addition and cyclization reactions. A quaternary ammonium salt is used as a catalyst for these reactions, which leads to a diastereoisomeric excess both for the reactions of morpholine and piperidine products. Studies in silico of the pathways of these reactions explain the chemoselection and diasteroselection deriving from the two nucleophiles used. In this case of piperidine products, it was also possible to validate the hypothesis of a concerted nucleophilic addition mechanism on the α,β-unsaturated site and cyclization due to an intramolecular Michael addition.
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Le fratture fragili del collo del femore rappresentano un grave problema sociosanitario, in via di aggravamento a causa dell’aumento dell’età media e dell’aspettativa di vita. Il verificarsi di tale evento dipende da più fattori: la frequenza con la quale si verificano cadute, la gravità delle stesse e lo stato di salute del paziente, in particolare la resistenza meccanica delle sue ossa e il suo grado di controllo neuro-motorio. Negli ultimi anni gli strumenti di analisi e stima della resistenza meccanica del femore basati su modelli agli elementi finiti hanno raggiunto un tale livello di maturità da prospettarne l’utilizzo nel contesto di “in silico trials”, ovvero la simulazione virtuale di sperimentazioni cliniche e precliniche. In questo studio si è sviluppato un modello stocastico in grado di simulare la sperimentazione clinica di nuovi trattamenti per l’osteoporosi. Questo comprende più sotto modelli in grado di simulare il processo di invecchiamento, determinare stocasticamente le cadute che si verificano in una certa popolazione in un determinato orizzonte temporale e l’entità delle forze che agiscono sul grande trocantere. In particolare, le cadute sono state generate a partire da una distribuzione di Poisson e le forze sono state stimate attraverso un modello stocastico multiscala. La tesi si è concentrata su aspetti metodologici e procedurali, nell’ottica di sviluppare un modello che permettesse agevolmente la variazione dei parametri associati alla caduta, dotato di buone robustezza ed applicabilità. È stato verificato come la discretizzazione nel dominio del tempo del rimodellamento osseo non influisca significativamente nella determinazione delle fratture; inoltre, il modello si è dimostrato capace di fornire risultati stabili in modo computazionalmente efficiente. La validazione dei risultati del modello, invece, ha dato risultati non soddisfacenti, per cui sarà necessario procedere in futuro a un’attenta calibrazione dei parametri del modello.
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The fast development of Information Communication Technologies (ICT) offers new opportunities to realize future smart cities. To understand, manage and forecast the city's behavior, it is necessary the analysis of different kinds of data from the most varied dataset acquisition systems. The aim of this research activity in the framework of Data Science and Complex Systems Physics is to provide stakeholders with new knowledge tools to improve the sustainability of mobility demand in future cities. Under this perspective, the governance of mobility demand generated by large tourist flows is becoming a vital issue for the quality of life in Italian cities' historical centers, which will worsen in the next future due to the continuous globalization process. Another critical theme is sustainable mobility, which aims to reduce private transportation means in the cities and improve multimodal mobility. We analyze the statistical properties of urban mobility of Venice, Rimini, and Bologna by using different datasets provided by companies and local authorities. We develop algorithms and tools for cartography extraction, trips reconstruction, multimodality classification, and mobility simulation. We show the existence of characteristic mobility paths and statistical properties depending on transport means and user's kinds. Finally, we use our results to model and simulate the overall behavior of the cars moving in the Emilia Romagna Region and the pedestrians moving in Venice with software able to replicate in silico the demand for mobility and its dynamic.
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In questo lavoro di tesi vengono prese in esame le principali anomalie cerebrali fetali a carico del complesso anteriore, formato dal cavo del setto pellucido e dai corni frontali dei ventricoli laterali. Si è poi concentrata l’attenzione sull’oloprosencefalia e sull’obliterazione del cavo del setto pellucido, analizzando i casi che sono stati riferiti c/o la U.O. di Ostetricia e Medicina dell’Età Prenatale del Policlinico di S. Orsola – IRCCS. L’oloprosencefalia racchiude in sé uno spettro di anomalie cerebrali caratterizzate da un difetto di formazione della linea mediana con forme variabili di fusione degli emisferi cerebrali. Le forme alobari mostrano una distorsione della anatomia cerebrale, con un singolo ventricolo e sono spesso associate ad anomalie extracerebrali e del cariotipo. Nelle forme semilobari e lobari il setto pellucido è generalmente assente nei piani assiali, con corni frontali fusi ed ipoplasici, ma queste caratteristiche possono essere di difficile interpretazione ad un esame di screening. Le anomalie facciali sono invece più sfuggenti. L’obliterazione del cavo del setto consiste in un suo aspetto ecogeno, normalmente disteso da fluido; è ritenuta una variante della norma, ma queste conclusioni sono basate su casistiche limitate. Anche in questo caso abbiamo riportato l’eventuale presenza di anomalie associate ed abbiamo poi rivalutato questi bambini mediante una visita specialistica presso la U.O. di Neuropsichiatria Infantile. Nella nostra esperienza di 16 casi, la neurosonografia è stata in grado di definire la presenza o meno di anomalie cerebrali associate (1 caso di cisti interemisferiche e corpo calloso disgenetico) al pari della risonanza magnetica. Nei casi apparentemente isolati, in circa il 20% tale reperto è stato transitorio nel corso della gravidanza e non sono state riportate anomalie del cariotipo. Tutte le visite di follow up eseguite nel contesto dello studio (risultati parziali di 7/15 bambini) hanno dimostrato uno sviluppo nella norma per l’età del bambino.
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Around 5 million women give birth each year in Europe and, while breastfeeding, the majority of them may need to take medications, either occasionally or continuously. Unfortunately, there is often scarce evidence of trustworthy information about how a specific molecule might affect the physiology of lactation. This is the reason that brought a European public-private partnership to fund the development of a reliable platform to provide women and health-care professionals a helpful instrument to reduce uncertainty about the effects of medication used during breastfeeding. On April 1st 2019, the ConcePTION project (Grant Agreement n°821520) started to develop such envisaged platform. The 3rd Work Package was in charge of the validation of in vitro, in vivo and in silico lactation models. Between the numerous species currently used in preclinical studies, pigs’ similarities with humans’ anatomy, physiology and genomics make them extremely useful as translational models, when proper veterinary expertise is applied. The ASA team from the University of Bologna, went first to characterize the translational lactation model using the swine species, chosen upon literature review. The aim of this work was to lay the foundations of a porcine lactation model that could be suitable for application within pharmaceutical tests, to study drug transfer through milk prior approval and commercialization. The obtained results highlighted both strengths and critical points of the study design, allowing a significant improvement in the knowledge of pharmacokinetic physiology in lactating mammals. Lastly, this project allowed the assessment of microbial changes in gut resident bacteria of newborns through an innovative in vitro colonic model. Indeed, even if there were no evident adverse effects determined by drug residues in milk, possible alterations in the delicate microbial ecology of newborns’ gastrointestinal tract was considered pivotal, giving its possible impact on the individual health and growth.
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Cancer is a challenging disease that involves multiple types of biological interactions in different time and space scales. Often computational modelling has been facing problems that, in the current technology level, is impracticable to represent in a single space-time continuum. To handle this sort of problems, complex orchestrations of multiscale models is frequently done. PRIMAGE is a large EU project that aims to support personalized childhood cancer diagnosis and prognosis. The goal is to do so predicting the growth of the solid tumour using multiscale in-silico technologies. The project proposes an open cloud-based platform to support decision making in the clinical management of paediatric cancers. The orchestration of predictive models is in general complex and would require a software framework that support and facilitate such task. The present work, proposes the development of an updated framework, referred herein as the VPH-HFv3, as a part of the PRIMAGE project. This framework, a complete re-writing with respect to the previous versions, aims to orchestrate several models, which are in concurrent development, using an architecture as simple as possible, easy to maintain and with high reusability. This sort of problem generally requires unfeasible execution times. To overcome this problem was developed a strategy of particularisation, which maps the upper-scale model results into a smaller number and homogenisation which does the inverse way and analysed the accuracy of this approach.
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The study of the spectroscopic phenomena in organic solids, in combination with other techniques, is an effective tool for the understanding of the structural properties of materials based on these compounds. This Ph.D. work was dedicated to the spectroscopic investigation of some relevant processes occurring in organic molecular crystals, with the goal of expanding the knowledge on the relationship between structure, dynamics and photoreactivity of these systems. Vibrational spectroscopy has been the technique of choice, always in combination with X-ray diffraction structural studies and often the support of computational methods. The vibrational study of the molecular solid state reaches its full potential when it includes the low-wavenumber region of the lattice-phonon modes, which probe the weak intermolecular interactions and are the fingerprints of the lattice itself. Microscopy is an invaluable addition in the investigation of processes that take place in the micro-meter scale of the crystal micro-domains. In chemical and phase transitions, as well as in polymorph screening and identification, the combination of Raman microscopy and lattice-phonon detection has provided useful information. Research on the fascinating class of single-crystal-to-single-crystal photoreactions, has shown how the homogeneous mechanism of these transformations can be identified by lattice-phonon microscopy, in agreement with the continuous evolution of their XRD patterns. On describing the behavior of the photodimerization mechanism of vitamin K3, the focus was instead on the influence of its polymorphism in governing the product isomerism. Polymorphism is the additional degree of freedom of molecular functional materials, and by advancing in its control and properties, functionalities can be promoted for useful applications. Its investigation focused on thin-film phases, widely employed in organic electronics. The ambiguities in phase identification often emerging by other experimental methods were successfully solved by vibrational measurements.
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In silico methods, such as musculoskeletal modelling, may aid the selection of the optimal surgical treatment for highly complex pathologies such as scoliosis. Many musculoskeletal models use a generic, simplified representation of the intervertebral joints, which are fundamental to the flexibility of the spine. Therefore, to model and simulate the spine, a suitable representation of the intervertebral joint is crucial. The aim of this PhD was to characterise specimen-specific models of the intervertebral joint for multi-body models from experimental datasets. First, the project investigated the characterisation of a specimen-specific lumped parameter model of the intervertebral joint from an experimental dataset of a four-vertebra lumbar spine segment. Specimen-specific stiffnesses were determined with an optimisation method. The sensitivity of the parameters to the joint pose was investigate. Results showed the stiffnesses and predicted motions were highly depended on both the joint pose. Following the first study, the method was reapplied to another dataset that included six complete lumbar spine segments under three different loading conditions. Specimen-specific uniform stiffnesses across joint levels and level-dependent stiffnesses were calculated by optimisation. Specimen-specific stiffness show high inter-specimen variability and were also specific to the loading condition. Level-dependent stiffnesses are necessary for accurate kinematic predictions and should be determined independently of one another. Secondly, a framework to create subject-specific musculoskeletal models of individuals with severe scoliosis was developed. This resulted in a robust codified pipeline for creating subject-specific, severely scoliotic spine models from CT data. In conclusion, this thesis showed that specimen-specific intervertebral joint stiffnesses were highly sensitive to joint pose definition and the importance of level-dependent optimisation. Further, an open-source codified pipeline to create patient-specific scoliotic spine models from CT data was released. These studies and this pipeline can facilitate the specimen-specific characterisation of the scoliotic intervertebral joint and its incorporation into scoliotic musculoskeletal spine models.
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Osteoporosis is one of the major causes of mortality among the elderly. Nowadays, areal bone mineral density (aBMD) is used as diagnostic criteria for osteoporosis; however, this is a moderate predictor of the femur fracture risk and does not capture the effect of some anatomical and physiological properties on the bone strength estimation. Data from past research suggest that most fragility femur fractures occur in patients with aBMD values outside the pathological range. Subject-specific finite element models derived from computed tomography data are considered better tools to non-invasively assess hip fracture risk. In particular, the Bologna Biomechanical Computed Tomography (BBCT) is an In Silico methodology that uses a subject specific FE model to predict bone strength. Different studies demonstrated that the modeling pipeline can increase predictive accuracy of osteoporosis detection and assess the efficacy of new antiresorptive drugs. However, one critical aspect that must be properly addressed before using the technology in the clinical practice, is the assessment of the model credibility. The aim of this study was to define and perform verification and uncertainty quantification analyses on the BBCT methodology following the risk-based credibility assessment framework recently proposed in the VV-40 standard. The analyses focused on the main verification tests used in computational solid mechanics: force and moment equilibrium check, mesh convergence analyses, mesh quality metrics study, evaluation of the uncertainties associated to the definition of the boundary conditions and material properties mapping. Results of these analyses showed that the FE model is correctly implemented and solved. The operation that mostly affect the model results is the material properties mapping step. This work represents an important step that, together with the ongoing clinical validation activities, will contribute to demonstrate the credibility of the BBCT methodology.
Resumo:
The purpose of my internship, carried out during my Erasmus period at the Complutense University of Madrid, was focused on the formulation of ionogels and hydrogels for the obtainment of films with high lignin content, and on their characterization measuring their antibacterial properties. For biomass formulation I used lignocellulosic biomass (Pinus Radiata) as raw material and ionic liquid as solvent. The two ionic liquids proposed were: 1-ethyl-3-methylimidazoliumdimethylphosphate [Emim][DMP] and 1-ethyl-3-methylimidazoliumdiethylphosphate [Emim][DEP]. The two-starting cellulose-rich solids were obtained from Pinus radiata wood that had been submitted to an organosolv process, to reduce its lignin content to fifteen (ORG15) and twenty per cent (ORG20). Having two ionic liquids and two solids available, the first phase of the project was devoted to the screening of both solids in both ionic liquids. Through this, it was possible to identify that only the [Emim][DMP] ionic liquid fulfils the purpose. It was also possible to discard the cellulose-rich solid ORG20 because its dissolution in the ionic liquid was not possible (after the time fixed) and, additionally, a Pinus radiata cellulose-rich solid bleached with hydrogen peroxide and containing ten per cent of lignin (ORG10B) was included in the screening. After screening, a total of five ionogels were subsequently formulated: two gels were formulated with the starting raw material ORG15 (with 1% and 1.75% cellulose, respectively) and three with ORG10B (with 1%, 1.75% and 3% cellulose, respectively). Five hydrogels were obtained from the ionogels. Rheological tests were performed on each ionogel and hydrogel. Finally, films were formulated from hydrogels and they were analysed by antibacterial testing to see if they could be applied as food packaging. In addition, antioxidant and properties such as opacity and transparency were also studied.
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La colonna vertebrale è uno dei principali siti per lo sviluppo delle metastasi ossee. Esse modificano le proprietà meccaniche della vertebra indebolendo la struttura e inducendo l’instabilità spinale. La medicina in silico e i modelli agli elementi finiti (FE) hanno trovato spazio nello studio del comportamento meccanico delle vertebre, permettendo una valutazione delle loro proprietà meccaniche anche in presenza di metastasi. In questo studio ho validato i campi di spostamento predetti da modelli microFE di vertebre umane, con e senza metastasi, rispetto agli spostamenti misurati mediante Digital Volume Correlation (DVC). Sono stati utilizzati 4 provini da donatore umano, ognuno composto da una vertebra sana e da una vertebra con metastasi litica. Per ogni vertebra è stato sviluppato un modello microFE omogeneo, lineare e isotropo basato su sequenze di immagini ad alta risoluzione ottenute con microCT (voxel size = 39 μm). Sono state imposte come condizioni al contorno gli spostamenti ottenuti con la DVC nelle fette prossimali e distali di ogni vertebra. I modelli microFE hanno mostrato buone capacità predittive degli spostamenti interni sia per le vertebre di controllo che per quelle metastatiche. Per range di spostamento superiori a 100 μm, il valore di R2 è risultato compreso tra 0.70 e 0.99 e il valore di RMSE% tra 1.01% e 21.88%. Dalle analisi dei campi di deformazione predetti dai modelli microFE sono state evidenziate regioni a maggior deformazione nelle vertebre metastatiche, in particolare in prossimità delle lesioni. Questi risultati sono in accordo con le misure sperimentali effettuate con la DVC. Si può assumere quindi che il modello microFE lineare omogeneo isotropo in campo elastico produca risultati attendibili sia per le vertebre sane sia per le vertebre metastatiche. La procedura di validazione implementata potrebbe essere utilizzata per approfondire lo studio delle proprietà meccaniche delle lesioni blastiche.
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Artificial Intelligence (AI) has substantially influenced numerous disciplines in recent years. Biology, chemistry, and bioinformatics are among them, with significant advances in protein structure prediction, paratope prediction, protein-protein interactions (PPIs), and antibody-antigen interactions. Understanding PPIs is critical since they are responsible for practically everything living and have several uses in vaccines, cancer, immunology, and inflammatory illnesses. Machine Learning (ML) offers enormous potential for effectively simulating antibody-antigen interactions and improving in-silico optimization of therapeutic antibodies for desired features, including binding activity, stability, and low immunogenicity. This research looks at the use of AI algorithms to better understand antibody-antigen interactions, and it further expands and explains several difficulties encountered in the field. Furthermore, we contribute by presenting a method that outperforms existing state-of-the-art strategies in paratope prediction from sequence data.