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1.
Nanoscale ; 16(7): 3641-3649, 2024 Feb 15.
Article in English | MEDLINE | ID: mdl-38276985

ABSTRACT

Upconverting nanoparticles (UCNPs) have found widespread applications in biophotonics and energy harvesting due to their unique non-linear optical properties arising from energy transfer upconversion (ETU) mechanisms. However, accurately characterising the power density-dependent efficiency of UCNPs using the internal quantum yield (iQY) is challenging due to the lack of methods that account for excitation beam-profile distortions. This limitation hinders the engineering of optimal UCNPs for diverse applications. To address this, this work present a novel beam profile compensation strategy based on a general analytical rate-equations model, enabling the evaluation of iQY for ETU processes of arbitrary order, such as ETU2, ETU3, and beyond. The method was applied to characterise the ETU2 and ETU3 processes corresponding to the main emission peaks (474 nm, 650 nm, and 804 nm) of a Yb-Tm codoped core-shell ß-UCNP. Through this approach, the transition power density points (which delimit the distinct non-linear regimes of the upconversion luminescence (UCL)), and the saturation iQY values (which are reached at high excitation power densities above the transition points) were determined. The ETU2 process exhibits a single transition power density point, denoted as ρ2, while the ETU3 processes involve two transition points, ρ2 and ρ3. By compensating for the beam profile, we evaluate the iQY of individual lines across a wide dynamic range of excitation power densities (up to 105 W cm-2), encompassing both non-linear and linear regimes of UCL. This study introduces a valuable approach for accurately characterising the iQY of UCNPs, facilitating a deeper understanding of the upconversion and its performance. By addressing excitation beam-profile distortions, this method provides a comprehensive and reliable assessment of the power density-dependent iQY. The results highlight the applicability and effectiveness of this beam profile compensation strategy, which can be employed for a wide range of UCNPs. This advancement opens new avenues for the tailored design and application of UCNPs in various fields, especially for biophotonics.

2.
Nanoscale Adv ; 5(12): 3279-3286, 2023 Jun 13.
Article in English | MEDLINE | ID: mdl-37325538

ABSTRACT

The quantum yield (QY) evaluation of upconverting nanoparticles (UCNPs) is an essential step in the characterisation of such materials. The QY of UCNPs is governed by competing mechanisms of populating and depopulating the electronic energy levels involved in the upconversion (UC), namely linear decay rates and energy transfer rates. As a consequence, at low excitation, the QY excitation power density (ρ) dependence obeys the power law ρn-1, where n represents the number of absorbed photons required for the emission of a single upconverted photon and determines the order of the energy transfer upconversion (ETU) process. At high power densities, the QY transits to a saturation level independent of the ETU process and the number of excitation photons, as a result of an anomalous power density dependence present in UCNPs. Despite the importance of this non-linear process for several applications (e.g., living tissue imaging and super-resolution-microscopy), little has been reported in the literature regarding theoretical studies to describe the UC QY, especially for ETUs with order higher than two. Therefore, this work presents a simple general analytical model, which introduces the concept of the transition power density points and QY saturation to characterise the QY of an arbitrary ETU process. The transition power density points determine where the power density dependence of the QY and the UC luminescence changes. The results provided in this paper from fitting the model to experimental QY data of a Yb-Tm codoped ß-UCNP for 804 nm and 474 nm emissions (ETU2 and ETU3 processes, respectively) exemplify the application of the model. The common transition points found for both processes were compared to each other showing strong agreement with theory, as well as, compared to previous reports when possible.

3.
Nanoscale ; 14(6): 2230-2237, 2022 Feb 10.
Article in English | MEDLINE | ID: mdl-35080228

ABSTRACT

The presented work uses a discrete strategy of beam profile compensation to evaluate the local internal quantum yield (iQY) of upconverting nanoparticles (UCNPs) at the pixel level of the beam profile using a compact CMOS camera. The two-photon process of upconversion with a central emission peak at 804 nm was studied for a ß-phase core-shell Tm-codoped UCNP under 976 nm excitation. At the balancing power density point, ρb, found to be 44 ± 3 W cm-2, the iQY, ηb, was obtained as 2.3 ± 0.1%. Combining the power density dynamic range provided by the pixel depth of the camera with the dynamic range achieved using two distinct beam profiles to excite the UCNPs, the iQY was evaluated throughout a range of 104 in the iQY scale (from 0.0003% to 4.6%) and 106 in power densities of excitation (from 0.003 W cm-2 to 1050 W cm-2). To the best of our knowledge, these are the lowest values ever obtained as QY results have never been reported under 0.02% or at excitation power densities below 0.01 W cm-2.

4.
Acta Neurol Scand ; 128(4): 235-40, 2013 Oct.
Article in English | MEDLINE | ID: mdl-23464981

ABSTRACT

BACKGROUND: Studies suggest that N-terminal-pro-brain natriuretic peptide (NT-proBNP) can be a biomarker of cardioembolic stroke. However, the best time to measure it after stroke is unknown. We studied the time course of NT-proBNP in patients with ischemic stroke. METHODS: Consecutive acute ischemic stroke patients were admitted over 10 months to a Stroke Unit. Stroke type was classified according to TOAST. Blood samples were drawn within 24, 48, and 72 hours after stroke. Friedman test was used to compare NT-proBNP values across the 3 times in all, cardioembolic and non-cardioembolic stroke patients. Post hoc analysis with Wilcoxon signed-rank tests was conducted with a Bonferroni correction. Mann-Whitney test was used to compare median values of NT-proBNP between cardioembolic and non-cardioembolic stroke patients. ROC curves were drawn to determine NT-proBNP accuracy to diagnose cardioembolic stroke at 24, 48, and 72 hours after stroke onset. RESULTS: One hundred and one patients were included (29 cardioembolic) with a mean age of 64.5±12.3 years. NT-proBNP values for cardioembolic stroke were significantly higher (P < 0.001) than for non-cardioembolic stroke in the 3 time points. NT-proBNP was highest in the first 24-48 h after ischemic stroke and decreased significantly 72 h after stroke onset. The area under the curve for the three time points was similar. CONCLUSION: NT-proBNP levels were highest in the first 2 days after ischemic stroke and declined significantly thereafter. However, the area under the curve for the three time points was similar. The first 72 hours after ischemic stroke have a similar diagnostic accuracy to diagnose cardioembolic stroke.


Subject(s)
Brain Ischemia/blood , Natriuretic Peptide, Brain/blood , Peptide Fragments/blood , Stroke/blood , Adult , Aged , Aged, 80 and over , Area Under Curve , Brain/diagnostic imaging , Brain/pathology , Brain Ischemia/complications , Female , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Observation , Prospective Studies , ROC Curve , Radiography , Statistics, Nonparametric , Stroke/etiology , Stroke/pathology , Time Factors , Tomography Scanners, X-Ray Computed
5.
Acta Med Port ; 10(11): 771-5, 1997 Nov.
Article in Portuguese | MEDLINE | ID: mdl-9549108

ABSTRACT

The application of computer science to the practice of laboratory medicine, one of the medical informatics fields, brings a complete revolution in laboratory work and the clinical pathologists profile. The authors explain the methodology for the implementation of such a system, in a perspective of quality assurance, defining the goals, objectives, customer requirements and analysis of the benefits they achieve. Finally the authors explain the future perspectives.


Subject(s)
Clinical Laboratory Information Systems , Forecasting , Humans , Quality Assurance, Health Care
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