Automated region growing-based segmentation for trabecular bone structure in fresh-frozen human wrist specimens.

Bone strength depends on both mineral content and bone structure. Measurements of bone microstructure on specimens can be performed by micro-CT. In vivo measurements are reliably performed by high-resolution peripheral computed tomography (HR-pQCT) using dedicated software. In previous studies from our research group, trabecular bone properties on CT data of defatted specimens from many different CT devices have been analyzed using an Automated Region Growing (ARG) algorithm-based code, showing strong correlations to micro-CT.The aim of the study was to validate the possibility of segmenting and measuring trabecular bone structure from clinical CT data of fresh-frozen human wrist specimens. Data from micro-CT was used as reference. The hypothesis was that the ARG-based in-house built software could be used for such measurements.HR-pQCT image data at two resolutions (61 and 82 µm isotropic voxels) from 23 fresh-frozen human forearms were analyzed. Correlations to micro-CT were strong, varying from 0.72 to 0.99 for all parameters except trabecular termini and nodes. The bone volume fraction had correlations varying from 0.95 to 0.98 but was overestimated compared to micro-CT, especially at the lower resolution. Trabecular separation and spacing were the most stable parameters with correlations at 0.80-0.97 and mean values in the same range as micro-CT.Results from this in vitro study show that an ARG-based software could be used for segmenting and measuring 3D trabecular bone structure from clinical CT data of fresh-frozen human wrist specimens using micro-CT data as reference. Over-and underestimation of several of the bone structure parameters must however be taken into account.

Analysis of the Rheological Properties of Natural Hydraulic Lime-Based Suspensions for Sustainable Construction and Heritage Conservation.

Natural hydraulic lime (NHL)-based binders play a crucial role in preserving cultural heritage structures, ensuring integrity and longevity. Beyond traditional uses, these binders exhibit potential for integration into both non-structural and structural components, being compatible with innovative manufacturing processes such as digital fabrication. Meticulously designed grouts, with applicability in their fresh and hardened states, are essential for heritage stability. This study explores the relationships between mineral additions, chemical admixtures, and lime for grout formulations, aiming to advance our understanding and inform the optimization of materials for heritage restoration. Key questions include the influence of natural volcanic pozzolan (NVP) and metakaolin (MK) on rheology and the impact of varying ratios of superplasticizer on NHL-based grout's rheological behavior. This systematic evaluation of rheological parameters aims to innovate mix designs, expanding NHL-based binders' applicability in construction and science. Our hypotheses suggest that well-designed lime grout formulations, incorporating NVP and MK, can enhance rheological properties, addressing challenges in sustainable construction and heritage conservation. This research provides valuable insights for optimizing lime-based materials, fostering advancements in heritage restoration, and promoting wider NHL-based binder adoption in diverse construction applications.

Asymmetry in Cortical Thickness of the Heschl's Gyrus in Unilateral Ear Canal Atresia.

HYPOTHESIS: Unilateral congenital conductive hearing impairment in ear canal atresia leads to atrophy of the gray matter of the contralateral primary auditory cortex or changes in asymmetry pattern if left untreated in childhood. BACKGROUND: Unilateral ear canal atresia with associated severe conductive hearing loss results in deteriorated sound localization and difficulties in understanding of speech in a noisy environment. Cortical atrophy in the Heschl's gyrus has been reported in acquired sensorineural hearing loss but has not been studied in unilateral conductive hearing loss. METHODS: We obtained T1w and T2w FLAIR MRI data from 17 subjects with unilateral congenital ear canal atresia and 17 matched controls. Gray matter volume and thickness were measured in the Heschl's gyrus using Freesurfer. RESULTS: In unilateral congenital ear canal atresia, Heschl's gyrus exhibited cortical thickness asymmetry (right thicker than left, corrected p = 0.0012, mean difference 0.25 mm), while controls had symmetric findings. Gray matter volume and total thickness did not differ from controls with normal hearing. CONCLUSION: We observed cortical thickness asymmetry in congenital unilateral ear canal atresia but no evidence of contralateral cortex atrophy. Further research is needed to understand the implications of this asymmetry on central auditory processing deficits.

Randomized iterative spherical-deconvolution informed tractogram filtering.

Tractography has become an indispensable part of brain connectivity studies. However, it is currently facing problems with reliability. In particular, a substantial amount of nerve fiber reconstructions (streamlines) in tractograms produced by state-of-the-art tractography methods are anatomically implausible. To address this problem, tractogram filtering methods have been developed to remove faulty connections in a postprocessing step. This study takes a closer look at one such method, Spherical-deconvolution Informed Filtering of Tractograms (SIFT), which uses a global optimization approach to improve the agreement between the remaining streamlines after filtering and the underlying diffusion magnetic resonance imaging data. SIFT is not suitable for judging the compliance of individual streamlines with the acquired data since its results depend on the size and composition of the surrounding tractogram. To tackle this problem, we propose applying SIFT to randomly selected tractogram subsets in order to retrieve multiple assessments for each streamline. This approach makes it possible to identify streamlines with very consistent filtering results, which were used as pseudo-ground truths for training classifiers. The trained classifier is able to distinguish the obtained groups of complying and non-complying streamlines with the acquired data with an accuracy above 80%.

Fast three-dimensional image generation for healthy brain aging using diffeomorphic registration.

Predicting brain aging can help in the early detection and prognosis of neurodegenerative diseases. Longitudinal cohorts of healthy subjects scanned through magnetic resonance imaging (MRI) have been essential to understand the structural brain changes due to aging. However, these cohorts suffer from missing data due to logistic issues in the recruitment of subjects. This paper proposes a methodology for filling up missing data in longitudinal cohorts with anatomically plausible images that capture the subject-specific aging process. The proposed methodology is developed within the framework of diffeomorphic registration. First, two novel modules are introduced within Synthmorph, a fast, state-of-the-art deep learning-based diffeomorphic registration method, to simulate the aging process between the first and last available MRI scan for each subject in three-dimensional (3D). The use of image registration also makes the generated images plausible by construction. Second, we used six image similarity measurements to rearrange the generated images to the specific age range. Finally, we estimated the age of every generated image by using the assumption of linear brain decay in healthy subjects. The methodology was evaluated on 2662 T1-weighted MRI scans from 796 healthy participants from 3 different longitudinal cohorts: Alzheimer's Disease Neuroimaging Initiative, Open Access Series of Imaging Studies-3, and Group of Neuropsychological Studies of the Canary Islands (GENIC). In total, we generated 7548 images to simulate the access of a scan per subject every 6 months in these cohorts. We evaluated the quality of the synthetic images using six quantitative measurements and a qualitative assessment by an experienced neuroradiologist with state-of-the-art results. The assumption of linear brain decay was accurate in these cohorts (R2  ∈ [.924, .940]). The experimental results show that the proposed methodology can produce anatomically plausible aging predictions that can be used to enhance longitudinal datasets. Compared to deep learning-based generative methods, diffeomorphic registration is more likely to preserve the anatomy of the different structures of the brain, which makes it more appropriate for its use in clinical applications. The proposed methodology is able to efficiently simulate anatomically plausible 3D MRI scans of brain aging of healthy subjects from two images scanned at two different time points.

A deep learning model for brain age prediction using minimally preprocessed T1w images as input.

Introduction: In the last few years, several models trying to calculate the biological brain age have been proposed based on structural magnetic resonance imaging scans (T1-weighted MRIs, T1w) using multivariate methods and machine learning. We developed and validated a convolutional neural network (CNN)-based biological brain age prediction model that uses one T1w MRI preprocessing step when applying the model to external datasets to simplify implementation and increase accessibility in research settings. Our model only requires rigid image registration to the MNI space, which is an advantage compared to previous methods that require more preprocessing steps, such as feature extraction. Methods: We used a multicohort dataset of cognitively healthy individuals (age range = 32.0-95.7 years) comprising 17,296 MRIs for training and evaluation. We compared our model using hold-out (CNN1) and cross-validation (CNN2-4) approaches. To verify generalisability, we used two external datasets with different populations and MRI scan characteristics to evaluate the model. To demonstrate its usability, we included the external dataset's images in the cross-validation training (CNN3). To ensure that our model used only the brain signal on the image, we also predicted brain age using skull-stripped images (CNN4). Results: The trained models achieved a mean absolute error of 2.99, 2.67, 2.67, and 3.08 years for CNN1-4, respectively. The model's performance in the external dataset was in the typical range of mean absolute error (MAE) found in the literature for testing sets. Adding the external dataset to the training set (CNN3), overall, MAE is unaffected, but individual cohort MAE improves (5.63-2.25 years). Salience maps of predictions reveal that periventricular, temporal, and insular regions are the most important for age prediction. Discussion: We provide indicators for using biological (predicted) brain age as a metric for age correction in neuroimaging studies as an alternative to the traditional chronological age. In conclusion, using different approaches, our CNN-based model showed good performance using one T1w brain MRI preprocessing step. The proposed CNN model is made publicly available for the research community to be easily implemented and used to study ageing and age-related disorders.

Comprendiendo las reglas emocionales en el trabajo docente: un estudio con profesoras de enseñanza básica / Understanding emotional rules in the teaching profession: a study with female elementary school teachers

El objetivo del estudio fue identificar y caracterizar las reglas emocionales que profesoras de enseñanza básica perciben en su trabajo. Desde un enfoque cualitativo se realizaron entrevistas en profundidad y episódicas a cuatro profesoras. Logrando identificar cuatro reglas emocionales docentes: las docentes deben sentir pasión por su trabajo, deben mantener equilibrio emocional en su trabajo, deben vincularse afectivamente con sus estudiantes y deben regular entre entregar cariño y poner límites en la relación con ellos. Se reconocieron cuatro características: las reglas emocionales son implícitas; se definen en base a principios personales y principios profesionales; el incumplimiento de estas genera reflexiones autocriticas en las docentes y se reconocen formas de control externo para su cumplimiento. Se discute cómo las reglas identificadas concuerdan con la literatura, se despliegan fundamentalmente en la relación con los estudiantes y sus formas de control podrían estar influenciadas por las políticas de rendición de cuentas. (AU)

The objective of the study was to identify and characterize the emotional rules that female elementary school teachers perceive in their work. From a qualitative approach, in-depth and episodic interviews were conducted with four female teachers. Four emotional rules were identified: teachers must feel passion for their work; they must maintain emotional balance in their work; they must bond affectively with their students; they must regulate between giving affection and setting limits in their relationship with them. Four characteristics were recognized: the emotional rules are implicit; they are defined on the basis of personal and professional principles; non-compliance with these rules generates self-critical reflections in the teachers and forms of external control for their compliance are recognized. It is discussed how the rules identified are consistent with the literature; these rules are fundamentally deployed in the relationship with students and their forms of control could be influenced by accountability policies. (AU)

Driver Take-Over Behaviour Study Based on Gaze Focalization and Vehicle Data in CARLA Simulator.

Autonomous vehicles are the near future of the automobile industry. However, until they reach Level 5, humans and cars will share this intermediate future. Therefore, studying the transition between autonomous and manual modes is a fascinating topic. Automated vehicles may still need to occasionally hand the control to drivers due to technology limitations and legal requirements. This paper presents a study of driver behaviour in the transition between autonomous and manual modes using a CARLA simulator. To our knowledge, this is the first take-over study with transitions conducted on this simulator. For this purpose, we obtain driver gaze focalization and fuse it with the road's semantic segmentation to track to where and when the user is paying attention, besides the actuators' reaction-time measurements provided in the literature. To track gaze focalization in a non-intrusive and inexpensive way, we use a method based on a camera developed in previous works. We devised it with the OpenFace 2.0 toolkit and a NARMAX calibration method. It transforms the face parameters extracted by the toolkit into the point where the user is looking on the simulator scene. The study was carried out by different users using our simulator, which is composed of three screens, a steering wheel and pedals. We distributed this proposal in two different computer systems due to the computational cost of the simulator based on the CARLA simulator. The robot operating system (ROS) framework is in charge of the communication of both systems to provide portability and flexibility to the proposal. Results of the transition analysis are provided using state-of-the-art metrics and a novel driver situation-awareness metric for 20 users in two different scenarios.

Reinforcement Learning-Based Autonomous Driving at Intersections in CARLA Simulator.

Intersections are considered one of the most complex scenarios in a self-driving framework due to the uncertainty in the behaviors of surrounding vehicles and the different types of scenarios that can be found. To deal with this problem, we provide a Deep Reinforcement Learning approach for intersection handling, which is combined with Curriculum Learning to improve the training process. The state space is defined by two vectors, containing adversaries and ego vehicle information. We define a features extractor module and an actor-critic approach combined with Curriculum Learning techniques, adding complexity to the environment by increasing the number of vehicles. In order to address a complete autonomous driving system, a hybrid architecture is proposed. The operative level generates the driving commands, the strategy level defines the trajectory and the tactical level executes the high-level decisions. This high-level decision system is the main goal of this research. To address realistic experiments, we set up three scenarios: intersections with traffic lights, intersections with traffic signs and uncontrolled intersections. The results of this paper show that a Proximal Policy Optimization algorithm can infer ego vehicle-desired behavior for different intersection scenarios based only on the behavior of adversarial vehicles.

Automatic segmentation of the core of the acoustic radiation in humans.

Introduction: Acoustic radiation is one of the most important white matter fiber bundles of the human auditory system. However, segmenting the acoustic radiation is challenging due to its small size and proximity to several larger fiber bundles. TractSeg is a method that uses a neural network to segment some of the major fiber bundles in the brain. This study aims to train TractSeg to segment the core of acoustic radiation. Methods: We propose a methodology to automatically extract the acoustic radiation from human connectome data, which is both of high quality and high resolution. The segmentation masks generated by TractSeg of nearby fiber bundles are used to steer the generation of valid streamlines through tractography. Only streamlines connecting the Heschl's gyrus and the medial geniculate nucleus were considered. These streamlines are then used to create masks of the core of the acoustic radiation that is used to train the neural network of TractSeg. The trained network is used to automatically segment the acoustic radiation from unseen images. Results: The trained neural network successfully extracted anatomically plausible masks of the core of the acoustic radiation in human connectome data. We also applied the method to a dataset of 17 patients with unilateral congenital ear canal atresia and 17 age- and gender-paired controls acquired in a clinical setting. The method was able to extract 53/68 acoustic radiation in the dataset acquired with clinical settings. In 14/68 cases, the method generated fragments of the acoustic radiation and completely failed in a single case. The performance of the method on patients and controls was similar. Discussion: In most cases, it is possible to segment the core of the acoustic radiations even in images acquired with clinical settings in a few seconds using a pre-trained neural network.

Photon-counting detector CT and energy-integrating detector CT for trabecular bone microstructure analysis of cubic specimens from human radius.

BACKGROUND: As bone microstructure is known to impact bone strength, the aim of this in vitro study was to evaluate if the emerging photon-counting detector computed tomography (PCD-CT) technique may be used for measurements of trabecular bone structures like thickness, separation, nodes, spacing and bone volume fraction. METHODS: Fourteen cubic sections of human radius were scanned with two multislice CT devices, one PCD-CT and one energy-integrating detector CT (EID-CT), using micro-CT as a reference standard. The protocols for PCD-CT and EID-CT were those recommended for inner- and middle-ear structures, although at higher mAs values: PCD-CT at 450 mAs and EID-CT at 600 (dose equivalent to PCD-CT) and 1000 mAs. Average measurements of the five bone parameters as well as dispersion measurements of thickness, separation and spacing were calculated using a three-dimensional automated region growing (ARG) algorithm. Spearman correlations with micro-CT were computed. RESULTS: Correlations with micro-CT, for PCD-CT and EID-CT, ranged from 0.64 to 0.98 for all parameters except for dispersion of thickness, which did not show a significant correlation (p = 0.078 to 0.892). PCD-CT had seven of the eight parameters with correlations ρ > 0.7 and three ρ > 0.9. The dose-equivalent EID-CT instead had four parameters with correlations ρ > 0.7 and only one ρ > 0.9. CONCLUSIONS: In this in vitro study of radius specimens, strong correlations were found between trabecular bone structure parameters computed from PCD-CT data when compared to micro-CT. This suggests that PCD-CT might be useful for analysing bone microstructure in the peripheral human skeleton.

Spherical Convolutional Neural Networks for Survival Rate Prediction in Cancer Patients.

Objective: Survival Rate Prediction (SRP) is a valuable tool to assist in the clinical diagnosis and treatment planning of lung cancer patients. In recent years, deep learning (DL) based methods have shown great potential in medical image processing in general and SRP in particular. This study proposes a fully-automated method for SRP from computed tomography (CT) images, which combines an automatic segmentation of the tumor and a DL-based method for extracting rotational-invariant features. Methods: In the first stage, the tumor is segmented from the CT image of the lungs. Here, we use a deep-learning-based method that entails a variational autoencoder to provide more information to a U-Net segmentation model. Next, the 3D volumetric image of the tumor is projected onto 2D spherical maps. These spherical maps serve as inputs for a spherical convolutional neural network that approximates the log risk for a generalized Cox proportional hazard model. Results: The proposed method is compared with 17 baseline methods that combine different feature sets and prediction models using three publicly-available datasets: Lung1 (n=422), Lung3 (n=89), and H&N1 (n=136). We observed comparable C-index scores compared to the best-performing baseline methods in a 5-fold cross-validation on Lung1 (0.59 ± 0.03 vs. 0.62 ± 0.04). In comparison, it slightly outperforms all methods in inter-data set evaluation (0.64 vs. 0.63). The best-performing method from the first experiment reduced its performance to 0.61 and 0.62 for Lung3 and H&N1, respectively. Discussion: The experiments suggest that the performance of spherical features is comparable with previous approaches, but they generalize better when applied to unseen datasets. That might imply that orientation-independent shape features are relevant for SRP. The performance of the proposed method was very similar, using manual and automatic segmentation methods. This makes the proposed model useful in cases where expert annotations are not available or difficult to obtain.

Rheological Properties of Different Graphene Nanomaterials in Biological Media.

Carbon nanomaterials have received increased attention in the last few years due to their potential applications in several areas. In medicine, for example, these nanomaterials could be used as contrast agents, drug transporters, and tissue regenerators or in gene therapy. This makes it necessary to know the behavior of carbon nanomaterials in biological media to assure good fluidity and the absence of deleterious effects on human health. In this work, the rheological characterization of different graphene nanomaterials in fetal bovine serum and other fluids, such as bovine serum albumin and water, is studied using rotational and microfluidic chip rheometry. Graphene oxide, graphene nanoplatelets, and expanded graphene oxide at concentrations between 1 and 3 mg/mL and temperatures in the 25-40 °C range were used. The suspensions were also characterized by transmission and scanning electron microscopy and atomic force microscopy, and the results show a high tendency to aggregation and reveals that there is a protein-nanomaterial interaction. Although rotational rheometry is customarily used, it cannot provide reliable measurements in low viscosity samples, showing an apparent shear thickening, whereas capillary viscometers need transparent samples; therefore, microfluidic technology appears to be a suitable method to measure low viscosity, non-transparent Newtonian fluids, as it is able to determine small variations in viscosity. No significant changes in viscosity are found within the solid concentration range studied but it decreases between 1.1 and 0.6 mPa·s when the temperature raises from 25 to 40 °C.

Probabilistic Assessment of the Dynamic Viscosity of Self-Compacting Steel-Fiber Reinforced Concrete through a Micromechanical Model.

This article develops a probabilistic approach to a micromechanical model to calculate the dynamic viscosity in self-compacting steel-fiber reinforced concrete (SCSFRC), which implies a paradigm shift in the approach of the deterministic models used. It builds on a previous work by the authors in which Bayesian analysis is applied to rheological micromechanical models in cement paste, self-compacting mortar, and self-compacting concrete. As a consequence of the varied characteristics of the particles in these suspensions (in terms of materials, shapes, size distributions, etc.), as well as their random nature, it seems appropriate to study these systems with probabilistic models. The Bayesian analysis, thorough Markov Chain Monte Carlo and Gibbs Sampling methods, allows the conversion of parametric-deterministic models into parametric-probabilistic models, which results in enrichment in engineering and science. The incorporation of steel fibers requires a new term in the model to account for their effect on the dynamic viscosity of SCSFRC, and this new term is also treated here with the Bayesian approach. The paper uses an extensive collection of experimental data to obtain the probability density functions of the parameters for assessing the dynamic viscosity in SCSFRC. The results obtained with these parameters' distributions are much better than those calculated with the theoretical values of the parameters, which indicates that Bayesian methods are appropriated to respond to questions in complex systems with complex models.

Vascularized Bone Grafting for the Treatment of Capitate Avascular Necrosis.

Avascular necrosis (AVN) of the capitate bone is a rare condition and it can be related to major trauma or idiopathy. Different treatments are available including soft tissue interposition and intercarpal arthrodesis including lunocapitate, scaphocapitate, four corner, and carpometacarpal fusions. Other surgical options are resection of the proximal pole and revascularization procedures. The main purpose of this article is to present two cases of AVN of the capitate treated with a revascularization procedure using the 4th-5th extensor compartment artery (4th-5th ECA). Two female patients with capitate AVN are reported with an average age of 30.5 years. Both cases were classified as type-I according to Milliez classification. The major complaint in each case was wrist pain that increased during activity. In both cases there was no history of trauma, smoking, diabetes, or hematologic diseases. Both patients had a diminished range of motion, grip, and strength. The definitive diagnosis was made with magnetic resonance imaging. Both patients underwent treatment revascularization of the capitate using a vascularized bone graft based on the 4th-5th ECA. At average follow-up of 12 months, each patient had improved with regards to pain and had increased grip strength. The literature does not describe a specific algorithm treatment for capitate AVN. We recommend revascularization of the capitate using the 4th-5th ECA in type-I Milliez classification in young patients without signs of carpal collapse.

Predicting the trabecular bone apparent stiffness tensor with spherical convolutional neural networks.

The apparent stiffness tensor is relevant for characterizing trabecular bone quality. Previous studies have used morphology-stiffness relationships for estimating the apparent stiffness tensor. In this paper, we propose to train spherical convolutional neural networks (SphCNNs) to estimate this tensor. Information of the edges, trabecular thickness, and spacing are summarized in functions on the unitary sphere used as inputs for the SphCNNs. The concomitant dimensionality reduction makes it possible to train neural networks on relatively small datasets. The predicted tensors were compared to the stiffness tensors computed by using the micro-finite element method (µFE), which was considered as the gold standard, and models based on fourth-order fabric tensors. Combining edges and trabecular thickness yields significant improvements in the accuracy compared to the methods based on fourth-order fabric tensors. From the results, SphCNNs are promising for replacing the more expensive µFE stiffness estimations.

Colloidal Processing of Y0.08Zr0.92O2/La0.80Sr0.20MnO3 Semi-Cells Using a Sr-Doped Lanthanum Manganite Synthesized by a Citrate Route.

In this paper, the interface between yttria stabilized zirconia (Y0.08Zr0.92O2, YSZ) electrolyte and Sr-doped lanthanum manganite (La0.80Sr0.20MnO3, LSM) cathode for solid oxide fuel cells (SOFCs) is studied. For such a purpose, the combination of a suitable synthesis route for obtaining fine powders and simple aqueous colloidal shaping routes is proposed. The synthesis of nanosized particles of La0.80Sr0.20MnO3 by a citrate route and their full characterization, including the colloidal stability and the densification and phase development determined by X-ray diffraction and electron microscopy at different temperatures, is reported. In a second step, YSZ tapes were obtained by aqueous tape casting and used as substrates for the preparation of LSM coatings by dip-coating using aqueous slurries. YSZ tapes were used either in the green state or after a pre-sintering treatment. Co-sintering at 1350 °C led to a sharp interface with excellent adhesion, also achieved when coating pre-sintered tapes. In both cases, the substrates are dense and the coatings are porous, with thicknesses of 85 and 60 µm for green and pre-sintered tapes, respectively. No diffusion of Zr and Y occurs at the LSM layer, but some diffusion of La and Mn towards the YSZ layer takes place.

Prevalencia de disfunción sexual en gestantes en control prenatal en una institución hospitalaria en Rionegro, Colombia, 2020-2021 / Prevalence of sexual dysfunction among pregnant women attending prenatal care at a hospital in Rionegro, Colombia, 2020-2021

RESUMEN Objetivo: Describir la prevalencia de la disfunción sexual en un grupo de mujeres gestantes y hacer una exploración de posibles factores asociados a la disfunción sexual en estas mujeres. Materiales y métodos: Estudio descriptivo y trasversal en mujeres gestantes cuyas edades son de 15 años o más, con actividad sexual en la gestación, que asistieron al control prenatal en el Hospital San Juan de Dios de Rionegro entre los meses de enero y marzo del 2021. Se excluyeron pacientes con limitaciones o discapacidad cognitiva, o clasificadas con trastorno mental según la Organización Mundial de la Salud (OMS), gestantes con patologías crónicas, placentarias, ovulares, hemorrágicas e infecciosas, y las pacientes cuya gestación fue resultado de violencia sexual. Se aplicó el cuestionario Índice de Función Sexual Femenina (FSFI), se midieron variables sociodemográficas y de salud sexual y reproductiva. Los resultados se expresan en frecuencias absolutas y relativas para las variables cualitativas y medianas, y rangos intercuartílicos para las variables cuantitativas. Resultados: La mediana de edad fue de 27,5 años (RIC: 21,3-31,0); de edad gestacional 28,5 semanas (RIC: 21,3-34,8). Tras la aplicación del FSFI, 37 mujeres (37,7%) tuvieron disfunción sexual (puntaje < 26,5). La mediana del puntaje de las participantes sin disfunción sexual fue de 29,4 (RIC 26,8-32), mientras que por el lado de las que tienen disfunción sexual fue de 22,3 (RIC 20-24). La media del puntaje para cada dominio fue: deseo: 3,6 (RIC: 3,0-4,2); excitación: 4,5 (RIC: 3,6-5,1); lubricación: 4,8 (RIC: 3,9-5,4); orgasmo: 4,4 (RIC: 3,6-5,2); dolor: 4,4 (RIC: 3,6-6,0); y satisfacción: 5,4 (RIC: 4,8-6,0). Fueron factores protectores no tener hijos ni cesáreas previas. La ausencia de compañero y menor edad estuvieron asociados a disfunción sexual. Conclusión: La disfunción sexual se presenta en por lo menos un tercio de las gestantes, especialmente en el tercer trimestre. En la práctica clínica diaria se hace necesario abordar la disfunción sexual, ya que se puede contribuir desde el abordaje de la educación a un problema que puede afectar las relaciones de pareja y la calidad de vida. Es fundamental generar nuevas investigaciones que incluyan la evaluación de la efectividad y seguridad de estrategias educativas en este grupo poblacional con disfunción sexual.

ABSTRACT Objective: To describe the prevalence of sexual dysfunction in a group of pregnant women, and to explore potential factors associated with this condition in this population. Material and methods: Descriptive cross-sectional study in pregnant women 15 years of age and older, sexually active during gestation, receiving prenatal care at the San Juan de Dios Hospital in Rionegro between January and March, 2021. The exclusion criteria were patients with disabilities or cognitive impairment, or classified as having a mental disorder according to the World Health Organization (WHO); pregnant women with chronic, placental, ovulation, hemorrhagic or infectious conditions; and patients whose pregnancy was the result of sexual assault. The Female Sexual Function Index (FSFI) questionnaire was applied, and sociodemographic and sexual and reproductive health variables were measured. Results are expressed as absolute and relative frequencies for qualitative variables, and as medians and interquartile ranges for quantitative variables. Results: The mean age in years was 27.5 (IQR: 21.331.0) and the mean gestational age was 28.5 weeks (IQR: 21.3-34.8). After administering the FSFI, it was found that 37 women (37.7%) had sexual dysfunction (score < 26.5). The median scores for the participants without sexual dysfunction and those with sexual dysfunction were 29.4 (IQR 26.8-32) and 22.3 (IQR 20-24), respectively. The mean scores for each domain were: desire 3.6 (IQR: 3.0-4.2); arousal 4.5 (IQR: 3.65.1); lubrication 4.8 (IQR: 3.9-5.4); orgasm 4.4 (IQR: 3.6-5.2); pain 4.4 (IQR: 3.6-6.0); and satisfaction 5.4 (IQR: 4.8-6.0). The total score (p<0.05) was better in older women and those with one or more children. Conclusion: Sexual dysfunction occurs at least in one-third of pregnant women, especially during the third trimester. Sexual dysfunction should be considered in daily clinical practice, given that approaching the topic from an education perspective can help reduce a problem that affects the couple and quality of life. It is critical to undertake additional research that includes assessment of the effectiveness and safety of educational strategies in this population with sexual dysfunction.

Evolutionary drivers of the hump-shaped latitudinal gradient of benthic polychaete species richness along the Southeastern Pacific coast.

Latitudinal diversity gradients (LDG) and their explanatory factors are among the most challenging topics in macroecology and biogeography. Despite of its apparent generality, a growing body of evidence shows that 'anomalous' LDG (i.e., inverse or hump-shaped trends) are common among marine organisms along the Southeastern Pacific (SEP) coast. Here, we evaluate the shape of the LDG of marine benthic polychaetes and its underlying causes using a dataset of 643 species inhabiting the continental shelf (<200 m depth), using latitudinal bands with a spatial resolution of 0.5°, along the SEP (3-56° S). The explanatory value of six oceanographic (Sea Surface Temperature (SST), SST range, salinity, salinity range, primary productivity and shelf area), and one macroecological proxy (median latitudinal range of species) were assessed using a random forest model. The taxonomic structure was used to estimate the degree of niche conservatism of predictor variables and to estimate latitudinal trends in phylogenetic diversity, based on three indices (phylogenetic richness (PDSES), mean pairwise distance (MPDSES), and variation of pairwise distances (VPD)). The LDG exhibits a hump-shaped trend, with a maximum peak of species richness at ca. 42° S, declining towards northern and southern areas of SEP. The latitudinal pattern was also evident in local samples controlled by sampling effort. The random forest model had a high accuracy (pseudo-r2 = 0.95) and showed that the LDG could be explained by four variables (median latitudinal range, SST, salinity, and SST range), yet the functional relationship between species richness and these predictors was variable. A significant degree of phylogenetic conservatism was detected for the median latitudinal range and SST. PDSES increased toward the southern region, whereas VPD showed the opposite trend, both statistically significant. MPDSES has the same trend as PDSES, but it is not significant. Our results reinforce the idea that the south Chile fjord area, particularly the Chiloé region, was likely the evolutionary source of new species of marine polychaetes along SEP, creating a hotspot of diversity. Therefore, in the same way as the canonical LDG shows a decline in diversity while moving away from the tropics; on this case the decline occurs while moving away from Chiloé Island. These results, coupled with a strong phylogenetic signal of the main predictor variables suggest that processes operating mainly at evolutionary timescales govern the LDG.

Extraction optimization and structural characterization of pectin from persimmon fruit (Diospyros kaki Thunb. var. Rojo brillante).

In this work we have efficiently extracted and characterized pectin from different tissues of astringent (AS) and non-astringent (NAS) persimmon fruits (peel, pulp, whole fruit) for the first time. The highest pectin extraction (≥7.2%) was carried out at 80 °C, 120 min with 1.5% sodium citrate in peel of both AS and NAS persimmon samples. All persimmon pectins showed a molecular weight and galacturonic acid content upper than 328 kDa and 78%, respectively, indicating their suitability as food ingredient. Pectin extracted from AS pulp and peel tissues exhibited an enriched structure in rhamnose and arabinose, whereas the opposite behavior was observed in NAS persimmon whole fruit samples. Remarkably, both pulp tissues (AS and NAS) presented the highest levels of glucose and mannose, non-pectic carbohydrates. In addition, techno-functional assessment (zeta potential, particle size, apparent viscosity, gelation) showed the suitability of the persimmon pectins for a broad range of industrial applications.