Multicomponent nanodevices based on molecular and nanocrystal moieties

Nanoscience is an emerging and fast-growing field of science with the aim of manipulating nanometric objects with dimension below 100 nm. Top down approach is currently used to build these type of architectures (e.g microchips). The miniaturization process cannot proceed indefinitely due to physical and technical limitations. Those limits are focusing the interest on the bottom-up approach and construction of nano-objects starting from “nano-bricks” like atoms, molecules or nanocrystals. Unlike atoms, molecules can be “fully programmable” and represent the best choice to build up nanostructures. In the past twenty years many examples of functional nano-devices able to perform simple actions have been reported. Nanocrystals which are often considered simply nanostructured materials, can be active part in the development of those nano-devices, in combination with functional molecules. The object of this dissertation is the photophysical and photochemical investigation of nano-objects bearing molecules and semiconductor nanocrystals (QDs) as components. The first part focuses on the characterization of a bistable rotaxane. This study, in collaboration with the group of Prof. J.F. Stoddart (Northwestern University, Evanston, Illinois, USA) who made the synthesis of the compounds, shows the ability of this artificial machine to operate as bistable molecular-level memory under kinetic control. The second part concerns the study of the surface properties of luminescent semiconductor nanocrystals (QDs) and in particular the effect of acid and base on the spectroscopical properties of those nanoparticles. In this section is also reported the work carried out in the laboratory of Prof H. Mattoussi (Florida State University, Tallahassee, Florida, USA), where I developed a novel method for the surface decoration of QDs with lipoic acid-based ligands involving the photoreduction of the di-thiolane moiety.

Photoactive Carbon Nanostructures: From Multicomponent Arrays To Nanomaterials

Carbon has a unique ability to shape networks of differently hybridized atoms that can generate various allotropes and may also exist as nanoscale materials. The emergence of carbon nanostructures initially occured through the serendipitous discovery of fullerenes and then through experimental advances which led to carbon nanotubes, nanohorns and graphene. The structural diversity of carbon nanoscopic allotropes and their unique and unprecedentend properties, give rise to countless applications and have been intensively exploited in nanotechnology, since they may address the need to create smarter optoelectronic devices, smaller in size and with better performance. The versatile properties of carbon nanomaterials are reflected in the multidisciplinary character of my doctoral research where, in particular, I take advantage of the opportunities offered by fullerenes and carbon nanotubes in constructing novel functional materials. In this work, carbon nanostructures are incorporated in novel photoactive functional systems constructed through different types of interactions – covalent bonds, ion-pairing or self-assembly. The variety of properties exhibited by carbon nanostructures is successfully explored by assigning them a different role in a specific array: fullerenes are employed as electron or energy acceptors, whereas carbon nanotubes behave like optically inert scaffolds for luminescent materials or nanoscale substrates in sonication-induced self-assembly. All the presented systems serve as a testbed for exploring the properties of carbon nanostructures in multicomponent arrays, which may be advantageous for the production of new photovoltaic or optoelectronic devices, as well as in the design and control of self-assembly processes.

Predicting CMS datasets popularity with machine learning

In CMS è stato lanciato un progetto di Data Analytics e, all’interno di esso, un’attività specifica pilota che mira a sfruttare tecniche di Machine Learning per predire la popolarità dei dataset di CMS. Si tratta di un’osservabile molto delicata, la cui eventuale predizione premetterebbe a CMS di costruire modelli di data placement più intelligenti, ampie ottimizzazioni nell’uso dello storage a tutti i livelli Tiers, e formerebbe la base per l’introduzione di un solito sistema di data management dinamico e adattivo. Questa tesi descrive il lavoro fatto sfruttando un nuovo prototipo pilota chiamato DCAFPilot, interamente scritto in python, per affrontare questa sfida.

Predicting adverse events in children with fever and chemotherapy-induced neutropenia: the prospective multicenter SPOG 2003 FN study

PURPOSE To develop a score predicting the risk of adverse events (AEs) in pediatric patients with cancer who experience fever and neutropenia (FN) and to evaluate its performance. PATIENTS AND METHODS Pediatric patients with cancer presenting with FN induced by nonmyeloablative chemotherapy were observed in a prospective multicenter study. A score predicting the risk of future AEs (ie, serious medical complication, microbiologically defined infection, radiologically confirmed pneumonia) was developed from a multivariate mixed logistic regression model. Its cross-validated predictive performance was compared with that of published risk prediction rules. Results An AE was reported in 122 (29%) of 423 FN episodes. In 57 episodes (13%), the first AE was known only after reassessment after 8 to 24 hours of inpatient management. Predicting AE at reassessment was better than prediction at presentation with FN. A differential leukocyte count did not increase the predictive performance. The score predicting future AE in 358 episodes without known AE at reassessment used the following four variables: preceding chemotherapy more intensive than acute lymphoblastic leukemia maintenance (weight = 4), hemoglobin > or = 90 g/L (weight = 5), leukocyte count less than 0.3 G/L (weight = 3), and platelet count less than 50 G/L (weight = 3). A score (sum of weights) > or = 9 predicted future AEs. The cross-validated performance of this score exceeded the performance of published risk prediction rules. At an overall sensitivity of 92%, 35% of the episodes were classified as low risk, with a specificity of 45% and a negative predictive value of 93%. CONCLUSION This score, based on four routinely accessible characteristics, accurately identifies pediatric patients with cancer with FN at risk for AEs after reassessment.

Predicting and monitoring cancer treatment response with diffusion-weighted MRI

An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, nonimage based clinical outcome metrics include morphology, clinical, and laboratory parameters, however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pretreatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response.

Change over time in posttraumatic stress caused by myocardial infarction and predicting variables

The traumatic experience of a heart attack may evolve into symptoms of posttraumatic stress disorder, which can be diagnosed at the earliest 1 month after myocardial infarction (MI). While several predictors of posttraumatic stress in the first year after MI have been described, we particularly sought to identify longer-term predictors and predictors of change in posttraumatic stress over time.

Pressure-cornea-vascular index (PCVI) for predicting disease progression in normal tension glaucoma

It has been shown that the pressure-to-cornea index (PCI), which estimates the relative effects of intraocular pressure (IOP) and central corneal thickness (CCT), may differentiate between glaucoma and non-glaucoma states. The authors investigated the utility of the pressure-cornea-vascular index (PCVI) in predicting field-progression in patients with normal tension glaucoma (NTG).

Predicting the pathogen of diabetic toe osteomyelitis by two consecutive ulcer cultures with bone contact

In this study, we investigate the accuracy of two consecutive ulcer cultures with bone contact compared to bone biopsy for the diagnosis of diabetic toe osteomyelitis. The same nurse and orthopaedic surgeon obtained all samples: sample A-1: bone contact swabbing through the ulcer; sample A-2: a second culture swabbing from the bone surface within 24 h; sample B: surgical bone biopsy in the operating theatre. The kappa statistic measure between samples A-1 and A-2 (bone contact swabs) indicated 82.35% agreement. The sensitivity, specificity, positive and negative predictive values of the two samples A compared to B were 96%, 79%, 92% and 88%, respectively, for the causative pathogen. These results were similar with prior antibiotic treatment, discordant bone surface swabs or with monomicrobial infections. As a conclusion, two consecutive diabetic toe cultures with bone contact accurately predict the pathogen of diabetic toe osteomyelitis in 90% of cases.

Factors predicting protracted improvement after pallidal DBS for primary dystonia: the role of age and disease duration

In many patients, optimal results after pallidal deep brain stimulation (DBS) for primary dystonia may appear over several months, possibly beyond 1 year after implant. In order to elucidate the factors predicting such protracted clinical effect, we retrospectively reviewed the clinical records of 44 patients with primary dystonia and bilateral pallidal DBS implants. Patients with fixed skeletal deformities, as well as those with a history of prior ablative procedures, were excluded. The Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS) scores at baseline, 1 and 3 years after DBS were used to evaluate clinical outcome. All subjects showed a significant improvement after DBS implants (mean BFMDRS improvement of 74.9% at 1 year and 82.6% at 3 years). Disease duration (DD, median 15 years, range 2-42) and age at surgery (AS, median 31 years, range 10-59) showed a significant negative correlation with DBS outcome at 1 and 3 years. A partition analysis, using DD and AS, clustered subjects into three groups: (1) younger subjects with shorter DD (n = 19, AS < 27, DD ? 17); (2) older subjects with shorter DD (n = 8, DD ? 17, AS ? 27); (3) older subjects with longer DD (n = 17, DD > 17, AS ? 27). Younger patients with short DD benefitted more and faster than older patients, who however continued to improve 10% on average 1 year after DBS implants. Our data suggest that subjects with short DD may expect to achieve a better general outcome than those with longer DD and that AS may influence the time necessary to achieve maximal clinical response.

Predicting the transition from acute to persistent low back pain

BACKGROUND: Most people experience low back pain (LBP) at least once in their lifetime. Only a minority of them go on to develop persistent LBP. However, the socioeconomic costs of persistent LBP significantly exceed the costs of the initial acute LBP episode. AIMS: To identify factors that influence the progression of acute LBP to the persistent state at an early stage. METHODS: Prospective inception cohort study of patients attending a health practitioner for their first episode of acute LBP or recurrent LBP after a pain free period of at least 6 months. Patients were assessed at baseline addressing occupational and psychological factors as well as pain, disability, quality of life and physical activity and followed up at 3, 6, 12 weeks and 6 months. Variables were combined to the three indices 'working condition', 'depression and maladaptive cognitions' and 'pain and quality of life'. RESULTS: The index 'depression and maladaptive cognitions' was found to be a significant baseline predictor for persistent LBP up to 6 months (OR 5.1; 95% CI: 1.04-25.1). Overall predictive accuracy of the model was 81%. CONCLUSIONS: In this study of patients with acute LBP in a primary care setting psychological factors at baseline correlated with a progression to persistent LBP up to 6 months. The benefit of including factors such as 'depression and maladaptive cognition' in screening tools is that these factors can be addressed in primary and secondary prevention.

Predicting the transition from acute to persistent low back pain

BACKGROUND: Most people experience low back pain (LBP) at least once in their lifetime. Only a minority of them go on to develop persistent LBP. However, the socioeconomic costs of persistent LBP significantly exceed the costs of the initial acute LBP episode. AIMS: To identify factors that influence the progression of acute LBP to the persistent state at an early stage. METHODS: Prospective inception cohort study of patients attending a health practitioner for their first episode of acute LBP or recurrent LBP after a pain free period of at least 6 months. Patients were assessed at baseline addressing occupational and psychological factors as well as pain, disability, quality of life and physical activity and followed up at 3, 6, 12 weeks and 6 months. Variables were combined to the three indices 'working condition', 'depression and maladaptive cognitions' and 'pain and quality of life'. RESULTS: The index 'depression and maladaptive cognitions' was found to be a significant baseline predictor for persistent LBP up to 6 months (OR 5.1; 95% CI: 1.04-25.1). Overall predictive accuracy of the model was 81%. CONCLUSIONS: In this study of patients with acute LBP in a primary care setting psychological factors at baseline correlated with a progression to persistent LBP up to 6 months. The benefit of including factors such as 'depression and maladaptive cognition' in screening tools is that these factors can be addressed in primary and secondary prevention.