Development and testing of a sedation protocol for Neocaridina davidi.

Neocaridina davidi, a small freshwater shrimp native to Asia, specifically China, Japan, Korea, and Vietnam, possesses remarkable resistance to poor water quality and offers various advantages over other invertebrate species to examine crucial issues in neuroscience and other related areas. These advantages include robustness, ease of maintenance, and transparency, making them useful for in vivo studies with optical imaging techniques. Despite its suitability for research purposes, particularly in the fields of imaging and fluorescent techniques, the lack of attention given to this species has resulted in the absence of a robust and replicable sedation protocol for immobilization and safe manipulation. Consequently, researchers face challenges in performing experimental procedures while minimizing harm to this specimen. In this study, we have developed and evaluated a simple sedation protocol specifically designed for Neocaridina davidi, assessing its effectiveness using light microscopy and image processing.

Correlation-informed ordered dictionary learning for imaging in complex media.

We propose a method for imaging in scattering media when large and diverse datasets are available. It has two steps. Using a dictionary learning algorithm the first step estimates the true Green's function vectors as columns in an unordered sensing matrix. The array data comes from many sparse sets of sources whose location and strength are not known to us. In the second step, the columns of the estimated sensing matrix are ordered for imaging using the multidimensional scaling algorithm with connectivity information derived from cross-correlations of its columns, as in time reversal. For these two steps to work together, we need data from large arrays of receivers so the columns of the sensing matrix are incoherent for the first step, as well as from sub-arrays so that they are coherent enough to obtain connectivity needed in the second step. Through simulation experiments, we show that the proposed method is able to provide images in complex media whose resolution is that of a homogeneous medium.

The Noise Collector for sparse recovery in high dimensions.

The ability to detect sparse signals from noisy, high-dimensional data is a top priority in modern science and engineering. It is well known that a sparse solution of the linear system [Formula: see text] can be found efficiently with an [Formula: see text]-norm minimization approach if the data are noiseless. However, detection of the signal from data corrupted by noise is still a challenging problem as the solution depends, in general, on a regularization parameter with optimal value that is not easy to choose. We propose an efficient approach that does not require any parameter estimation. We introduce a no-phantom weight τ and the Noise Collector matrix C and solve an augmented system [Formula: see text], where e is the noise. We show that the [Formula: see text]-norm minimal solution of this system has zero false discovery rate for any level of noise, with probability that tends to one as the dimension of [Formula: see text] increases to infinity. We obtain exact support recovery if the noise is not too large and develop a fast Noise Collector algorithm, which makes the computational cost of solving the augmented system comparable with that of the original one. We demonstrate the effectiveness of the method in applications to passive array imaging.

[Validity and reliability of the satisfaction scale for outpatient care users in Peru]. / Validez y confiabilidad de la escala de satisfacción de los usuarios de consulta médica ambulatoria en Perú.

OBJECTIVES.: To assess the psychometric properties of a scale to measure the satisfaction of individuals seeking services at outpatient clinics (ESCOMA) in public healthcare centers in Peru. MATERIALS AND METHODS.: We carried out a study based on a dataset from Questionnaire 1 of the National Health Users Satisfaction Survey (ENSUSALUD) 2016. ENSUSALUD applied an initial scale of 19 items constructed based on bibliographic review, expert judgment and a pilot study. We first performed an exploratory factor analysis (EFA) in two random subsamples to assess the scale's internal structure. We then developed a confirmatory factor analysis (CFA) using robust maximum likelihood estimation. Lastly, we analyzed measurement invariance and assessed reliability using McDonald's Omega Coefficient (ω). RESULTS: : We randomly divided 13,814 observations into two subsamples for the EFA. Based on this analysis, we selected a best-fitting CFA model, which comprised three factors and 18 items. We found acceptable goodness-of-fit indices for the CFA (CFI = 0.945, TLI = 0.937, SRMR = 0.036). The three resulting factors were a) administrative processes, b) infrastructure and c) medical care. We found strong invariance for age, sex, educational level and area of residence, and partial invariance for type of institution. All reliability coefficients indicated adequate fit (0.86<ω<0.92). CONCLUSIONS.: The ESCOMA demonstrates validity, reliability, and measurement invariance at different levels of care in a nationally representative Peruvian sample.

OBJETIVOS.: Evaluar las propiedades psicométricas de la escala para medir la satisfacción de los usuarios de consulta médica ambulatoria (ESCOMA) en Instituciones Prestadoras de Servicios de Salud (IPRESS) del sistema de salud peruano (SSP). MATERIALES Y MÉTODOS.: Llevamos a cabo un estudio de tipo instrumental con los datos del Cuestionario 1 de la Encuesta Nacional de Satisfacción de Usuarios de Salud (ENSUSALUD) del 2016; en la cual se administró una escala inicial de 19 ítems construidos por revisión bibliográfica, juicio de expertos y estudio piloto. Realizamos un análisis factorial exploratorio (AFE) para valorar la estructura interna de la escala y luego un análisis factorial confirmatorio (AFC) mediante el método de estimación de máxima verosimilitud robusta. Finalmente, desarrollamos análisis de invarianza de medición y evaluamos la confiabilidad con el coeficiente omega de McDonald. RESULTADOS.: Analizamos 13 814 observaciones en dos submuestras aleatorias para el AFE con lo cual definimos un modelo de tres dimensiones con 18 ítems. En el AFC encontramos índices de bondad de ajuste aceptables (CFI=0,945; TLI=0,937; SRMR=0,036). Las dimensiones resultantes fueron: procesos administrativos, infraestructura y atención médica. Evidenciamos invarianza fuerte para la edad, sexo, nivel educativo y región, e invarianza parcial para el tipo de institución (Ministerio de Salud, Seguro Social, Fuerzas Armadas y Policiales, y Clínicas Privadas). Todos los coeficientes de confiabilidad fueron adecuados (0,86<ω<0,92). CONCLUSIONES.: La ESCOMA presenta evidencia de validez y confiabilidad a nivel estructural y de invarianza de medición a diferentes niveles de atención y a nivel nacional en Perú.

Validez y confiabilidad de la escala de satisfacción de los usuarios de consulta médica ambulatoria en Perú / Validity and reliability of the satisfaction scale for outpatient care users in Peru

RESUMEN Objetivos. Evaluar las propiedades psicométricas de la escala para medir la satisfacción de los usuarios de consulta médica ambulatoria (ESCOMA) en Instituciones Prestadoras de Servicios de Salud (IPRESS) del sistema de salud peruano (SSP). Materiales y Métodos. Llevamos a cabo un estudio de tipo instrumental con los datos del Cuestionario 1 de la Encuesta Nacional de Satisfacción de Usuarios de Salud (ENSUSALUD) del 2016; en la cual se administró una escala inicial de 19 ítems construidos por revisión bibliográfica, juicio de expertos y estudio piloto. Realizamos un análisis factorial exploratorio (AFE) para valorar la estructura interna de la escala y luego un análisis factorial confirmatorio (AFC) mediante el método de estimación de máxima verosimilitud robusta. Finalmente, desarrollamos análisis de invarianza de medición y evaluamos la confiabilidad con el coeficiente omega de McDonald. Resultados. Analizamos 13 814 observaciones en dos submuestras aleatorias para el AFE con lo cual definimos un modelo de tres dimensiones con 18 ítems. En el AFC encontramos índices de bondad de ajuste aceptables (CFI=0,945; TLI=0,937; SRMR=0,036). Las dimensiones resultantes fueron: procesos administrativos, infraestructura y atención médica. Evidenciamos invarianza fuerte para la edad, sexo, nivel educativo y región, e invarianza parcial para el tipo de institución (Ministerio de Salud, Seguro Social, Fuerzas Armadas y Policiales, y Clínicas Privadas). Todos los coeficientes de confiabilidad fueron adecuados (0,86<ω<0,92). Conclusiones. La ESCOMA presenta evidencia de validez y confiabilidad a nivel estructural y de invarianza de medición a diferentes niveles de atención y a nivel nacional en Perú.

ABSTRACT Objectives. To assess the psychometric properties of a scale to measure the satisfaction of individuals seeking services at outpatient clinics (ESCOMA) in public healthcare centers in Peru. Materials and Methods. We carried out a study based on a dataset from Questionnaire 1 of the National Health Users Satisfaction Survey (ENSUSALUD) 2016. ENSUSALUD applied an initial scale of 19 items constructed based on bibliographic review, expert judgment and a pilot study. We first performed an exploratory factor analysis (EFA) in two random subsamples to assess the scale's internal structure. We then developed a confirmatory factor analysis (CFA) using robust maximum likelihood estimation. Lastly, we analyzed measurement invariance and assessed reliability using McDonald's Omega Coefficient (ω). Results : We randomly divided 13,814 observations into two subsamples for the EFA. Based on this analysis, we selected a best-fitting CFA model, which comprised three factors and 18 items. We found acceptable goodness-of-fit indices for the CFA (CFI = 0.945, TLI = 0.937, SRMR = 0.036). The three resulting factors were a) administrative processes, b) infrastructure and c) medical care. We found strong invariance for age, sex, educational level and area of residence, and partial invariance for type of institution. All reliability coefficients indicated adequate fit (0.86<ω<0.92). Conclusions. The ESCOMA demonstrates validity, reliability, and measurement invariance at different levels of care in a nationally representative Peruvian sample.

A secondary analysis examining the concordance of self-perception of weight and actual measurement of body fat percentage: The CRONICAS Cohort Study.

BACKGROUND: Individuals' self-perceptions of weight often differ from objective measurements of body fat. This study aimed to 1) measure agreement between self-perceptions of weight and objective measurement of body fat by bioelectric impedance analysis (BIA) among Peruvian adults; and 2) quantify the association between body fat and a) baseline self-perceptions of weight and b) whether a participant underestimated their weight status. METHODS: Longitudinal data from the CRONICAS Cohort Study of 3181 Peruvian adults aged 35-years and older were used. BIA measurements of body fat were categorized across four nominal descriptions: low weight, normal, overweight, and obese. Kappa statistics were estimated to compare BIA measurements with baseline self-perceptions of weight. To quantify the association between body fat over time with both baseline self-perceptions of weight and underestimation of weight status, random effects models, controlling for socioeconomic and demographic covariates, were employed. RESULTS: Of the 3181 participants, 1111 (34.9%) were overweight and 649 (20.4%) were obese at baseline. Agreement between self-perceived and BIA weight status was found among 43.1% of participants, while 49.9% underestimated and 6.9% overestimated their weight status. Weighted kappa statistics ranged from 0.20 to 0.31 across settings, suggesting poor agreement. Compared to perceiving oneself as normal, perceiving oneself as underweight, overweight, or obese was associated with - 4.1 (p < 0.001), + 5.2 (p < 0.001), and + 8.1 (p < 0.001) body fat percentage points, respectively. Underestimating one's weight status was associated with having 2.4 (p < 0.001) body fat percentage points more than those not underestimating only after adjusting for demographic and socioeconomic covariates. CONCLUSIONS: Half of study participants were overweight or obese. There was poor agreement between self-perceptions of weight with BIA measurements of body fat, indicating that individuals often believe they weigh less than they actually do. Underestimating one's weight status was associated with having more body fat percentage points, but was only statistically significant after adjusting for demographic and socioeconomic characteristics. Further research should be conducted to investigate how self-perceptions of weight can support clinical and public health interventions to curb the obesity epidemic.

Quantitative subsurface imaging in strongly scattering media.

We present a method to obtain quantitatively accurate images of small obstacles or inhomogeneities situated near the surface of a strongly scattering medium. The method uses time-resolved measurements of backscattered light to form the images. Using the asymptotic solution of the radiative transfer equation for this problem, we determine that the key information content in measurements is modeled by a diffusion approximation that is valid for small source-detector distances, and shallow penetration depths. We simplify this model further by linearizing the effect of the inhomogeneities about the known background optical properties using the Born approximation. The resulting model is used in a two-stage imaging algorithm. First, the spatial location of the inhomogeneities are determined using a modification of the multiple signal classification (MUSIC) method. Using those results, we then determine the quantitative values of the inhomogeneities through a least-squares approximation. We find that this two-stage method is most effective for reconstructing a sequence of one-dimensional images along the penetration depth corresponding to null source-detector separations rather than simultaneously using measurements over several source-detector distances. This method is limited to penetration depths and distances between boundary measurements on the order of the scattering mean-free path.

Addressing post-stroke care in rural areas with Peru as a case study. Placing emphasis on evidence-based pragmatism.

Stroke is a major cause of death and disability, with most of its burden now affecting low- and middle-income countries (LMIC). People in rural areas of LMIC who have a stroke receive very little acute stroke care and local healthcare workers and family caregivers in these regions lack the necessary knowledge to assist them. Intriguingly, a recent rapid growth in cell-phone use and digital technology in rural areas has not yet been appropriately exploited for health care training and delivery purposes. What should be done in rural areas, at the community setting-level, where access to healthcare is limited remains a challenge. We review the evidence on improving post-stroke outcomes including lowering the risks of functional disability, stroke recurrence, and mortality, and propose some approaches, to target post-stroke care and rehabilitation, noting key challenges in designing suitable interventions and emphasizing the advantages mHealth and communication technologies can offer. In the article, we present the prevailing stroke care situation and technological opportunities in rural Peru as a case study. As such, by addressing major limitations in rural healthcare systems, we investigate the potential of task-shifting complemented with technology to utilize and strengthen both community-based informal caregivers and community healthcare workers.

Combining diffuse optical tomography and spectroscopy to detect and characterize lesions in two-layered tissues.

We combine diffuse optical tomography for detecting and localizing an inhomogeneity in a two-layered tissue and diffuse optical spectroscopy (DOS) for characterizing the spectrum of that inhomogeneity. For detecting and localizing an inhomogeneity, we reduce the number of unknowns substantially by seeking only the location and size of the inhomogeneity. Then, we seek to recover an unknown specific tumor component of that inhomogeneity from spectral data. In doing so, we develop a method for distinguishing between healthy and tumorous lesions. We demonstrate the utility of this theory with numerical simulations.

Fluorescence lifetime imaging from time resolved measurements using a shape-based approach.

We present a novel fluorescent tomography algorithm to estimate the spatial distribution of fluorophores and the fluorescence lifetimes from surface time resolved measurements. The algorithm is a hybridization of the level set technique for recovering the distributions of distinct fluorescent markers with a gradient method for estimating their lifetimes. This imaging method offers several advantages compared to more traditional pixel-based techniques as, for example, well defined boundaries and a better resolution of the images. The numerical experiments show that our imaging method gives rise to accurate reconstructions in the presence of data noise and fluorescence background even for complicated fluorophore distributions in several-centimiter-thick biological tissue.

Microwave imaging for early breast cancer detection using a shape-based strategy.

In this paper, we propose and analyze a novel shape reconstruction technique for the early detection of breast cancer from microwave data, which is based on a level-set technique. The shape-based approach offers several advantages compared to more traditional pixel-based approaches when targeting the reconstruction of key characteristics of a hidden tumor such as its correct size, shape, and static permittivity value. In addition to these key characteristics of hidden tumors, we aim at estimating the correct interfaces between fatty and fibroglandular tissue in the breast and their internal permittivity profiles. The level set strategy (which is an implicit representation of the shapes) frees us from topological restrictions when reconstructing an a priori arbitrary number of tumors and the often quite complicated interfaces between fatty and fibroglandular regions. The presented strategy is able to detect and, in most cases, characterize tumors whose sizes (diameters) are much smaller than the wavelengths of the electromagnetic waves that are used for illuminating the breast. We present numerical results for a 2-D model with two distinct tissue types (fatty and fibroglandular) in the interior of the breast (in addition to a possible tumor and the surrounding skin). Our results demonstrate the performance and potential of our scheme in various simulated but realistic situations.

Reconstructing a thin absorbing obstacle in a half-space of tissue.

We solve direct and inverse obstacle-scattering problems in a half-space composed of a uniform absorbing and scattering medium. Scattering is sharply forward-peaked, so we use the modified Fokker-Planck approximation to the radiative transport equation. The obstacle is an absorbing inhomogeneity that is thin with respect to depth. Using the first Born approximation, we derive a method to recover the depth and shape of the absorbing obstacle. This method requires only plane-wave illumination at two incidence angles and a detector with a fixed numerical aperture. First we recover the depth of the obstacle through solution of a simple nonlinear least-squares problem. Using that depth, we compute a point-spread function explicitly. We use that point-spread function in a standard deconvolution algorithm to reconstruct the shape of the obstacle. Numerical results show the utility of this method even in the presence of measurement noise.

Light transport in two-layer tissues.

We study theoretically light backscattered by tissues using the radiative transport equation. In particular we consider a two-layered medium in which a finite slab is situated on top of a half space. We solve the one-dimensional problem in which a plane wave is incident normally on the top layer and is the only source of light. The solution to this problem is obtained formally by imposing continuity between the solutions for the upper and lower layers. However, we are interested solely in probing the top layer. Assuming that the optical properties in the lower layer are known, we remove it from the problem yielding a finite slab problem by prescribing an alternate boundary condition. This boundary condition is derived using the theory of Green's functions and is exact. Hence, one needs only to solve the transport equation in a finite slab using this alternate boundary condition. We derive an asymptotic solution for the case when the slab is optically thin. We extend these results to the three-dimensional problem using Fourier transforms. These results are validated by comparisons with numerical solutions for the entire two-layered problem.

Beam propagation in sharply peaked forward scattering media.

We calculate the radiance of a light beam propagating in a uniformly scattering and absorbing slab and determine the point-spread function. We do this by solving numerically the governing radiative transport equation by use of plane-wave mode expansions. When scattering is sharply peaked in the forward direction and it becomes difficult to solve the radiative transport equation, we replace it with either the Fokker-Planck or the Leakeas-Larsen equation. We also solve these equations by using plane-wave mode expansions. Numerical results show that these two equations agree with the radiative transport equation for large anisotropy factors. The agreement improves as the optical thickness increases.

Backscattering of beams by forward-peaked scattering media.

For a beam impinging on a scattering medium the diffusion approximation to the radiative transport equation is not valid for analyzing the radiance near the source, especially if the medium scatters strongly with a sharp forward peak. To analyze the radiance, we use the Fokker-Planck approximation to the radiative transport equation. Numerical results show a backscattered ring appearing around the beam center. It also appears in Monte Carlo simulations of the radiative transport equation. This ring is manifested from successive near-forward scattering events, so it requires a directional description. Therefore the diffusion approximation cannot predict this ring.

Backscattering of circularly polarized pulses.

Using numerical simulations of vector radiative transport, we examine time-resolved backscattering of circularly polarized plane waves normally incident upon a slab containing a random distribution of latex spheres in water. For large spheres the effect of polarization memory occurs a short time after first-order scattering and before depolarization. It is the result of successive near-forward-scattering events that maintain the incident wave's helicity. For moderately large scatterers it exhibits a simple dependence on the anisotropy factor. For larger spheres or those with higher refractive indices, it also depends on complicated angular and polarization characteristics of backscattering given by Mie theory.