Surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR) are among the most common and powerful label-free refractive index-based biosensing techniques available nowadays. Focusing on LSPR sensors, their performance is highly dependent on the size, shape, and nature of the nanomaterial employed. Indeed, the tailoring of those parameters allows the development of LSPR sensors with a tunable wavelength range between the ultra-violet (UV) and near infra-red (NIR). Furthermore, dealing with LSPR along optical fiber technology, with their low attenuation coefficients at NIR, allow for the possibility to create ultra-sensitive and long-range sensing networks to be deployed in a variety of both biological and chemical sensors. This work provides a detailed review of the key science underpinning such systems as well as recent progress in the development of several LSPR-based biosensors in the NIR wavelengths, including an overview of the LSPR phenomena along recent developments in the field of nanomaterials and nanostructure development towards NIR sensing. The review ends with a consideration of key advances in terms of nanostructure characteristics for LSPR sensing and prospects for future research and advances in this field.
Kanabrocki, E. L.; Hermida, R. C.; McCormick, J. B.; Bremner, F. W.; Third, J. L.H.C.; Ryan, M.; Shirazi, P.; Nemchausky, B. A.; Scheving, L. E. Author Information
Deng et al. have recently proposed that estimates of an upper limit to the rate of spontaneous mutations and their average heterozygous effect can be obtained from the mean and variance of a given fitness trait in naturally segregating populations, provided that allele frequencies are maintained at the balance between mutation and selection. Using simulations they show that this estimation method generally has little bias and is very robust to violations of the mutation-selection balance assumption. Here I show that the particular parameters and models used in these simulations generally reduce the amount of bias that can occur with this estimation method. In particular, the assumption of a large mutation rate in the simulations always implies a low bias of estimates. In addition, the specific model of overdominance used to check the violation of the mutation-selection balance assumption is such that there is not a dramatic decline in mean fitness from overdominant mutations, again implying a low bias of estimates. The assumption of lower mutation rates and/or other models of balancing selection may imply considerably larger biases of the estimates, making the reliability of the proposed method highly questionable.
Abstract Models of nucleotide substitution are commonly used in the analysis of DNA sequences. This unit describes the use of the program MODELTEST (coupled with PAUP*) to find the best‐fit model of substitution for the sequence alignment at hand. An example data file is analyzed and the interpretation of the results is discussed. Some background theory on model selection and a discussion of the relevance of models is included at the end of the unit.
PartitionTest test suite
Previous studies established that a single daily dose of olmesartan remains effective for the entire 24 h without alteration of the day-night blood pressure (BP) pattern. On the other hand, the administration of valsartan or telmisartan at bedtime, as opposed to upon wakening, improves the sleep-time relative BP decline toward a greater dipper pattern without loss of 24 h efficacy. Yet to be determined is whether this administration-time-dependent efficacy is a class-related feature, characteristic of all angiotensin-receptor-blocker (ARB) medications. We studied 123 grade 1 and 2 hypertensive patients, 46.6+/-12.3 yrs of age, randomly assigned to receive olmesartan (20 mg/day) as a monotherapy either upon awakening or at bedtime for three months. BP was measured by ambulatory monitoring for 48 consecutive hours before and after treatment. The 24 h BP reduction was similar for both treatment times. Administration of olmesartan at bedtime, however, was significantly more efficient than morning administration in reducing the nocturnal BP mean. The sleep-time relative BP decline was slightly reduced with olmesartan ingestion upon awakening but significantly increased with ingestion at bedtime, thus reducing the prevalence of non-dipping from baseline by 48%. Olmesartan administration at bedtime, as opposed to in the morning, improved the awake/asleep BP ratio toward a greater dipper pattern without loss of 24 h efficacy. Nocturnal BP regulation was significantly better achieved with bedtime as compared to morning dosing of olmesartan. These effects are comparable to those previously reported for valsartan and telmisartan, thus suggesting that they may be class-related features of ARB medications in spite of differences in their half-life kinetics. These administration-time-dependent effects should be taken into account when prescribing ARB medications for treatment of essential hypertension.
