Uncover spatially informed variations for single-cell spatial transcriptomics with STew.

Motivation: The recent spatial transcriptomics (ST) technologies have enabled characterization of gene expression patterns and spatial information, advancing our understanding of cell lineages within diseased tissues. Several analytical approaches have been proposed for ST data, but effectively utilizing spatial information to unveil the shared variation with gene expression remains a challenge. Results: We introduce STew, a Spatial Transcriptomic multi-viEW representation learning method, to jointly analyze spatial information and gene expression in a scalable manner, followed by a data-driven statistical framework to measure the goodness of model fit. Through benchmarking using human dorsolateral prefrontal cortex and mouse main olfactory bulb data with true manual annotations, STew achieved superior performance in both clustering accuracy and continuity of identified spatial domains compared with other methods. STew is also robust to generate consistent results insensitive to model parameters, including sparsity constraints. We next applied STew to various ST data acquired from 10× Visium, Slide-seqV2, and 10× Xenium, encompassing single-cell and multi-cellular resolution ST technologies, which revealed spatially informed cell type clusters and biologically meaningful axes. In particular, we identified a proinflammatory fibroblast spatial niche using ST data from psoriatic skins. Moreover, STew scales almost linearly with the number of spatial locations, guaranteeing its applicability to datasets with thousands of spatial locations to capture disease-relevant niches in complex tissues. Availability and implementation: Source code and the R software tool STew are available from github.com/fanzhanglab/STew.

Tracing isotopically labeled selenium nanoparticles in plants via single-particle ICP-mass spectrometry.

Agronomic biofortification using selenium nanoparticles (SeNPs) shows potential for addressing selenium deficiency but further research on SeNPs-plants interaction is required before it can be effectively used to improve nutritional quality. In this work, single-particle inductively coupled plasma-mass spectrometry (SP-ICP-MS) was used for tracing isotopically labeled SeNPs (82SeNPs) in Oryza sativa L. tissues. For this purpose, SeNPs with natural isotopic abundance and 82SeNPs were synthesized by a chemical method. The NPs characterization by transmission electron microscopy (TEM) confirmed that enriched NPs maintained the basic properties of unlabeled NPs, showing spherical shape, monodispersity, and sizes in the nano-range (82.8 ± 6.6 nm and 73.2 ± 4.4 nm for SeNPs and 82SeNPs, respectively). The use of 82SeNPs resulted in an 11-fold enhancement in the detection power for ICP-MS analysis, accompanied by an improvement in the signal-to-background ratio and a reduction of the size limits of detection from 89.9 to 39.9 nm in SP-ICP-MS analysis. This enabled 82SeNPs to be tracked in O. sativa L. plants cultivated under foliar application of 82SeNPs. Tracing studies combining SP-ICP-MS and TEM-energy-dispersive X-ray spectroscopy data confirmed the uptake of intact 82SeNPs by rice leaves, with most NPs remaining in the leaves and very few particles translocated to shoots and roots. Translocation of Se from leaves to roots and shoots was found to be lower when applied as NPs compared to selenite application. From the size distributions, as obtained by SP-ICP-MS, it can be concluded that a fraction of the 82SeNPs remained within the same size range as that of the applied NP suspension, while other fraction underwent an agglomeration process in the leaves, as confirmed by TEM images. This illustrates the potential of SP-ICP-MS analysis of isotopically enriched 82SeNPs for tracing NPs in the presence of background elements within complex plant matrices, providing important information about the uptake, accumulation, and biotransformation of SeNPs in rice plants.

Non-protein nitrogen supplementation on in vitro fermentation profile, methane production, and microbial nitrogen synthesis in a corn silage-based substrate.

Non-protein nitrogen (NPN) supplements improve animal performance in backgrounding diets. However, there is scarce information regarding the effect of different NPN sources and combinations on ruminal fermentation profile. The current study aimed to evaluate the effect of different NPN sources and their combinations on in vitro fermentation, microbial N synthesis, and methane (CH4) production in a backgrounding diet. Incubations were conducted on three separate days for 24 h using corn silage and cotton gin byproduct (70% and 30% of DM, respectively) as substrate. Treatments were control (without NPN), urea, and five different proportions of urea-biuret and nitrate (100:0, 75:25, 50:50, 25:75, and 0:100). Each treatment, except control, was formulated to be isonitrogenous and equivalent to 1% urea inclusion. Ruminal fluid was collected from two ruminally cannulated Angus crossbred steers fed ad libitum corn silage and cotton gin byproduct plus 100 g of a urea-biuret-nitrate mixture. The concentration of volatile fatty acids (VFAs) and ammonia nitrogen (NH3-N) were determined at 12 and 24 h of incubation. Final pH, in vitro dry and organic matter digestibility, total gas production, and concentration of CH4 were determined at 24 h. The supplementation of NPN increased (P < 0.05) the concentration of NH3-N at 12 and 24 h. Although NPN supplementation increased (P < 0.05) the concentration of total VFA and acetate at 12 h, treatments did not differ (P > 0.05) at 24 h. Supplementation of NPN increased (P < 0.05) the proportion of acetate at 12 and 24 h but tended to reduce (P = 0.054) the proportion of propionate only at 12 h. Digestibility and pH were not different (P > 0.05) among treatments. Increasing nitrates in the NPN supplement increased (P < 0.05) the proportion of acetate and reduced (P < 0.05) the proportion of butyrate at 12 and 24 h. The supplementation of NPN increased (P < 0.05) microbial N synthesis. Furthermore, increasing nitrate proportion in the NPN supplement increased (P < 0.05) the microbial N synthesis and efficiency of N use. Supplementation of NPN did not modify (P > 0.05) total gas or CH4 production. However, increasing nitrate proportion in the NPN supplement linearly reduced (P < 0.05) CH4 production. Supplementation of NPN increased NH3-N concentration and microbial N while increasing the inclusion of nitrate decreased the production of CH4 and increased the microbial N synthesis in a corn silage-based substrate under in vitro conditions.

Carbon-based Flame Retardants for Polymers: A Bottom-up Review.

This state-of-the-art review is geared toward elucidating the molecular understanding of the carbon-based flame-retardant mechanisms for polymers via holistic characterization combining detailed analytical assessments and computational material science. The use of carbon-based flame retardants, which include graphite, graphene, carbon nanotubes (CNTs), carbon dots (CDs), and fullerenes, in their pure and functionalized forms are initially reviewed to evaluate their flame retardancy performance and to determine their elevation of the flammability resistance on various types of polymers. The early transition metal carbides such as MXenes, regarded as next-generation carbon-based flame retardants, are discussed with respect to their superior flame retardancy and multifunctional applications. At the core of this review is the utilization of cutting-edge molecular dynamics (MD) simulations which sets a precedence of an alternative bottom-up approach to fill the knowledge gap through insights into the thermal resisting process of the carbon-based flame retardants, such as the formation of carbonaceous char and intermediate chemical reactions offered by the unique carbon bonding arrangements and microscopic in-situ architectures. Combining MD simulations with detailed experimental assessments and characterization, a more targeted development as well as a systematic material synthesis framework can be realized for the future development of advanced flame-retardant polymers.

Tooth loss and depression in Chilean participants of the National Health Survey 2016-2017: Oral and social functions mediation analysis.

BACKGROUND: Previous studies have indicated the association between poor oral health and depression in adults. This study evaluated oral and social functions contribution to the association between tooth loss and depressive symptoms in Chilean individuals. METHODS: We used data from the Chilean National Health Survey. The number of remaining teeth (≤19 versus ≥20 teeth) and anterior tooth losses were the exposure variables. Outcome was depression, measured through a self-report question and with the Composite International Diagnostic Interview - Short Form (CIDI SF). Mediating variables were determined by five questions, including problems regarding "speaking", "pain and suffering", "eating", "daily activities", and "social relationships". We performed logistic regression models adjusted by multiple confounders variables. Finally, we calculated indirect, direct effect, total effect, and the proportion mediated (PM). RESULTS: We included 5383 participants. The self-reported depression and suspected depression prevalence were 22,1 % and 14,0 % respectively. The total effect of fewer remaining teeth (≤19) on self-reported depression was 1.21 (95 % CI 1.02-1.44), and 1.09 (95 % CI 0.90-1.33) for suspected depression. All five variables of oral and social functions significantly mediated the association between tooth loss and depression. Feeling uncomfortable when speaking or eating discomfort were the most significant mediators. LIMITATIONS: The mediation analysis should be interpreted with caution due to the cross-sectional design. CONCLUSIONS: Deterioration of oral and social functions was a significant mediator in the association between tooth loss and depression, in particular feeling uncomfortable when speaking or eating. This mechanism should be considered in interventions to improve mental health.

Actuales retos diagnósticos genómicos en los Síndromes Hemofagocíticos en pediatría: reporte de caso

Introducción: La linfohistiocitosis hemofagocítica familiar (FHL) es una enfermedad del sistema autoinmune que se presenta con un síndrome inflamatorio excesivo causado por linfocitos T activados e histiocitosis. Cursa con herencia autosómica recesiva ligada al cromosoma X. Aproximadamente el 90% de los niños diagnosticados son menores de 2 años y la incidencia es de aproximadamente 0.12 por 100.000. Se puede dividir en cinco subtipos según la variante genética causante. Las variantes patogénicas más involucradas son en los genes de la perforina 1 (PRF1) y homólogo D de la proteína UNC-13 (UNC13D). Caso clínico: Se presenta el caso de un preadolescente de 11 años, con antecedente de infecciones recurrentes, quien cursa con síndrome convulsivo asociado a fiebre, peso y talla bajas para la edad, hepatomegalia y discapacidad cognitiva. En el abordaje inicial se descartan enfermedades infecciosas, inmunológicas, hematológicas, metabólicas y oncológicas. El exoma clínico para inmunodeficiencias primarias muestra una variante patogénica p.A91V homocigota en el gen de la PRF1 de herencia autosómica recesiva, resultado relacionado con linfohistiocitosis hemofagocítica familiar tipo 2 (FHL2). Discusión y conclusión: El cambio conformacional del PRF1 alterado reduce la actividad citotóxica de la proteína y provoca la enfermedad. Los pacientes portadores de defectos en el gen PRF1 son vulnerables a infecciones, enfermedades autoinmunes y tumores malignos. Con un diagnóstico definido y preciso es posible orientar las acciones en salud, pautas de seguimiento, evaluación de riesgo de heredabilidad a través de un caso índice para así encontrar otros posibles portadores, realizar un asesoramiento genético completo, implementar e iniciar tratamientos dirigidos que aminoren la morbilidad y mortalidad asociada a esta patología. Actualmente se cuenta con varios estudios en diferentes fases de investigación sobre moléculas que pueden intervenir en la historia natural de la enfermedad. (provisto por Infomedic International)

Introduction: Familial hemophagocytic lymphohistiocytosis (FHL) is a disease of the autoimmune system that presents with an excessive inflammatory syndrome caused by activated T lymphocytes and histiocytosis. It occurs with autosomal recessive inheritance linked to the chromosome X. Approximately 90% of diagnosed children are under 2 years of age and the incidence is approximately 0.12 per 100,000. It can be divided into five subtypes depending on the causative genetic variant. The most involved pathogenic variants are in the perforin 1 (PRF1) and UNC-13 protein homolog D (UNC13D) genes. Clinical case: The case of an 11-year-old preadolescent is presented, with a history of recurrent infections, who presents with convulsive syndrome associated with fever, low weight and height for age, hepatomegaly and cognitive disability. In the initial approach, infectious, immunological, hematological, metabolic and oncological diseases are ruled out. The clinical exome for primary immunodeficiencies shows a homozygous pathogenic variant p.A91V in the PRF1 gene of autosomal recessive inheritance, a result related to familial hemophagocytic lymphohistiocytosis type 2 (FHL2). Discussion and conclusion: The altered PRF1 conformational change reduces the cytotoxic activity of the protein and causes disease. Patients carrying defects in the PRF1 gene are vulnerable to infections, autoimmune diseases and malignant tumors. With a defined and precise diagnosis, it is possible to guide health actions, follow-up guidelines, evaluation of heritability risk through an index case in order to find other possible carriers, carry out complete genetic counseling, implement and initiate targeted treatments that reduce the morbidity and mortality associated with this pathology. Currently, there are several studies in different phases of research on molecules that may intervene in the natural history of the disease. (provided by Infomedic International)

Soundscape Characterization Using Autoencoders and Unsupervised Learning.

Passive acoustic monitoring (PAM) through acoustic recorder units (ARUs) shows promise in detecting early landscape changes linked to functional and structural patterns, including species richness, acoustic diversity, community interactions, and human-induced threats. However, current approaches primarily rely on supervised methods, which require prior knowledge of collected datasets. This reliance poses challenges due to the large volumes of ARU data. In this work, we propose a non-supervised framework using autoencoders to extract soundscape features. We applied this framework to a dataset from Colombian landscapes captured by 31 audiomoth recorders. Our method generates clusters based on autoencoder features and represents cluster information with prototype spectrograms using centroid features and the decoder part of the neural network. Our analysis provides valuable insights into the distribution and temporal patterns of various sound compositions within the study area. By utilizing autoencoders, we identify significant soundscape patterns characterized by recurring and intense sound types across multiple frequency ranges. This comprehensive understanding of the study area's soundscape allows us to pinpoint crucial sound sources and gain deeper insights into its acoustic environment. Our results encourage further exploration of unsupervised algorithms in soundscape analysis as a promising alternative path for understanding and monitoring environmental changes.

Determination of gas flux and animal performance test duration of growing cattle in confined conditions.

Data from three experiments was analyzed to determine the number of visits and days to assess gas flux (CH4, CO2, and O2), dry matter intake (DMI), and average daily gain (ADG) from growing animals under confined conditions. In experiment 1, 213 animals (461 ±â€…91 kg initial body weight [BW]) were fed a backgrounding diet and evaluated for 60 d. In experiment 2, 169 steers (488 ±â€…37 kg initial BW) were fed a finishing diet and assessed for 70 d. In experiment 3, 64 steers (514 ±â€…42 kg initial BW) were fed a finishing diet and evaluated for 80 d. In each experiment, animals were placed in one pen with one Greenfeed and five SmartFeeds to collect gas flux and feed intake simultaneously. Gas flux was analyzed using data from 161 animals from the three experiments with 100 visits for 2 or more min or 3 or more min. Also, metabolic heat production (MHP) was estimated using the individual gas flux. Daily DMI was calculated as the daily feed intake corrected by the dry matter concentration. ADG was computed as the slope of the regression of the shrunk BW (96% BW) throughout each of the experimental periods. The mean gas flux and MHP were estimated for increasing or decreasing 5-visit intervals starting with the first or the last 5 visits and increasing or decreasing until the full 100-visit dataset was utilized, respectively. Intervals of DMI were estimated for increasing or decreasing 5-d intervals starting with the first or the last 5 d and increasing or decreasing until the end of the experimental period, respectively. Intervals of ADG were estimated for increasing or decreasing measurement period intervals until the end of the experimental period, respectively. Pearson and Spearman correlations were computed between the maximum visits or days and each shortened visit or day interval. The minimum number of visits and days was determined when correlations with the total visits were greater than 0.95. The results indicated that the minimum number of visits needed to quantify CO2, O2, and MHP accurately was 40, while CH4 was 60. A visitation length of 2 min or more or 3 min or more did not modify the gas flux determination. Thus, based on the average daily visitation in these experiments, gas flux data could be collected for 25 d. Additionally, the required days to determine DMI was 30, while ADG could not be assessed in a shorter than 60-d period.

Graph-Based Audio Classification Using Pre-Trained Models and Graph Neural Networks.

Sound classification plays a crucial role in enhancing the interpretation, analysis, and use of acoustic data, leading to a wide range of practical applications, of which environmental sound analysis is one of the most important. In this paper, we explore the representation of audio data as graphs in the context of sound classification. We propose a methodology that leverages pre-trained audio models to extract deep features from audio files, which are then employed as node information to build graphs. Subsequently, we train various graph neural networks (GNNs), specifically graph convolutional networks (GCNs), GraphSAGE, and graph attention networks (GATs), to solve multi-class audio classification problems. Our findings underscore the effectiveness of employing graphs to represent audio data. Moreover, they highlight the competitive performance of GNNs in sound classification endeavors, with the GAT model emerging as the top performer, achieving a mean accuracy of 83% in classifying environmental sounds and 91% in identifying the land cover of a site based on its audio recording. In conclusion, this study provides novel insights into the potential of graph representation learning techniques for analyzing audio data.

Development of an Immunocapture-Based Polymeric Optical Fiber Sensor for Bacterial Detection in Water.

Conventional methods for pathogen detection in water rely on time-consuming enrichment steps followed by biochemical identification strategies, which require assay times ranging from 24 hours to a week. However, in recent years, significant efforts have been made to develop biosensing technologies enabling rapid and close-to-real-time detection of waterborne pathogens. In previous studies, we developed a plastic optical fiber (POF) immunosensor using an optoelectronic configuration consisting of a U-Shape probe connected to an LED and a photodetector. Bacterial detection was evaluated with the immunosensor immersed in a bacterial suspension in water with a known concentration. Here, we report on the sensitivity of a new optoelectronic configuration consisting of two POF U-shaped probes, one as the reference and the other as the immunosensor, for the detection of Escherichia coli. In addition, another methos of detection was tested where the sensors were calibrated in the air, before being immersed in a bacterial suspension and then read in the air. This modification improved sensor sensitivity and resulted in a faster detection time. After the immunocapture, the sensors were DAPI-stained and submitted to confocal microscopy. The histograms obtained confirmed that the responses of the immunosensors were due to the bacteria. This new sensor detected the presence of E. coli at 104 CFU/mL in less than 20 min. Currently, sub-20 min is faster than previous studies using fiber-optic based biosensors. We report on an inexpensive and faster detection technology when compared with conventional methods.

Safety attributes of Pseudomonas sp. P26, an environmental microorganism with potential application in contaminated environments.

Currently, the selection of non-pathogenic microorganisms that lack clinically relevant antimicrobial resistance is crucial to bioaugmentation strategies. Pseudomonas sp. P26 (P26) is an environmental bacterium of interest due to its ability to remove aromatic compounds from petroleum, but its safety characteristics are still unknown. The study aimed to: a) determine P26 sensitivity to antimicrobials, b) investigate the presence of quinolone and ß-lactam resistance genes, c) determine the presence of virulence factors, and d) evaluate the effect of P26 on the viability of Galleria mellonella (an invertebrate animal model). P26 antimicrobial sensitivity was determined in vitro using the Kirby-Bauer agar diffusion method and the VITEK 2 automated system (BioMerieux®). Polymerase Chain Reaction was employed for the investigation of genes associated with quinolone resistance, extended-spectrum ß-lactamases, and carbapenemases. Hemolysin and protease production was determined in human blood agar and skimmed-milk agar, respectively. In the in vivo assay, different doses of P26 were injected into Galleria mellonella larvae and their survival was monitored daily. Control larvae injected with Pseudomonas putida KT2440 (a strain considered as safe) and Pseudomonas aeruginosa PA14 (a pathogenic strain) were included. Pseudomonas sp. P26 was susceptible to most evaluated antimicrobials, except for trimethoprim-sulfamethoxazole. No epidemiologically relevant genes associated with quinolone and ß-lactam resistance were identified. Hemolysin and protease production was only evidenced in the virulent strain (PA14). Furthermore, the results obtained in the in vivo experiment demonstrated that inocula less than 108 CFU/mL of P26 and P. putida KT2440 did not significantly affect larval survival, whereas larvae injected with the lowest dose of the pathogenic strain P. aeruginosa PA14 experienced instant mortality. The results suggest that Pseudomonas sp. P26 is a safe strain for its application in environmental bioremediation processes. Additional studies will be conducted to ensure the safety of this bacterium against other organisms.

Impact of Supplementing a Backgrounding Diet with Nonprotein Nitrogen on In Vitro Methane Production, Nutrient Digestibility, and Steer Performance.

Two experiments were conducted to evaluate the effect of nonprotein nitrogen (NPN) supplementation on in vitro fermentation and animal performance using a backgrounding diet. In experiment 1, incubations were conducted on three separate days (replicates). Treatments were control (CTL, without NPN), urea (U), urea-biuret (UB), and urea-biuret-nitrate (UBN) mixtures. Except for control, treatments were isonitrogenous using 1% U inclusion as a reference. Ruminal fluid was collected from two Angus-crossbred steers fed a backgrounding diet plus 100 g of a UBN mixture for at least 35 d. The concentration of volatile fatty acids (VFA) and ammonia nitrogen (NH3-N), in vitro organic matter digestibility (IVOMD), and total gas and methane (CH4) production were determined at 24 h of incubation. In experiment 2, 72 Angus-crossbred yearling steers (303 ±â€…29 kg of body weight [BW]) were stratified by BW and randomly allocated in nine pens (eight animals/pen and three pens/treatment). Steers consumed a backgrounding diet formulated to match the diet used in the in vitro fermentation experiment. Treatments were U, UB, and UBN and were isonitrogenous using 1% U inclusion as a reference. Steers were adapted to the NPN supplementation for 17 d. Then, digestibility evaluation was performed after 13 d of full NPN supplementation for 4 d using 36 steers (12 steers/treatment). After that, steer performance was evaluated for 56 d (24 steers/treatment). In experiment 1, NPN supplementation increased the concentration of NH3-N and VFA (P < 0.01) without affecting the IVOMD (P = 0.48), total gas (P = 0.51), and CH4 production (P = 0.57). Additionally, in vitro fermentation parameters did not differ (P > 0.05) among NPN sources. In experiment 2, NPN supplementation did not change dry matter and nutrient intake (P > 0.05). However, UB and UBN showed lower (P < 0.05) nutrient digestibility than U, except for starch (P = 0.20). Dry matter intake (P = 0.28), average daily gain (P = 0.88), and gain:feed (P = 0.63) did not differ among steers receiving NPN mixtures. In conclusion, tested NPN mixtures have the potential to be included in the backgrounding diets without any apparent negative effects on animal performance and warrant further studies to evaluate other variables to fully assess the response of feeding these novel NPN mixtures.

Nonprotein nitrogen (NPN) supplements can be used as a nitrogen source for ruminants fed low-protein diets. The most common NPN source is urea, included typically at a range between 0.5% and 1% of the diet dry matter in growing beef cattle. Although other NPN sources and mixtures are available, there is scarce information regarding their use in ruminant production. Two experiments were conducted to evaluate the effect of NPN sources on in vitro fermentation and animal performance using a backgrounding diet. In experiment 1, three different incubations were performed for 24 h. Treatments were control (without NPN), urea (U), urea­biuret (UB), and urea­biuret­nitrate (UBN) mixtures. In experiment 2, 72 crossbred yearling steers were randomly assigned to one of the following treatments: U, UB, and UBN mixtures. Diets were formulated to contain the same nitrogen concentration in both experiments. In experiment 1, supplementation of NPN increased the in vitro fermentation, but there were no differences among NPN sources. In experiment 2, steers performed similarly among NPN sources. These findings suggest that NPN mixtures have the potential to be included in the backgrounding diets without detrimental effects. Further studies should evaluate other variables (e.g., fermentation dynamic and microbial protein supply) when using these novel mixtures.

Generic design principles for antibody-based tumour necrosis factor (TNF) receptor 2 (TNFR2) agonists with FcγR-independent agonism.

Background: Selective TNFR2 activation can be used to treat immune pathologies by activating and expanding regulatory T-cells (Tregs) but may also restore anti-tumour immunity by co-stimulating CD8+ T-cells. Oligomerized TNFR2-specific TNF mutants or anti-TNFR2 antibodies can activate TNFR2 but suffer either from poor production and pharmacokinetics or in the case of anti-TNFR2 antibodies typically from the need of FcγR binding to elicit maximal agonistic activity. Methods: To identify the major factor(s) determining FcγR-independent agonism of anti-TNFR2 antibodies, we systematically investigated a comprehensive panel of anti-TNFR2 antibodies and antibody-based constructs differing in the characteristics of their TNFR2 binding domains but also in the number and positioning of the latter. Results: We identified the domain architecture of the constructs as the pivotal factor enabling FcγR-independent, thus intrinsic TNFR2-agonism. Anti-TNFR2 antibody formats with either TNFR2 binding sites on opposing sites of the antibody scaffold or six or more TNFR2 binding sites in similar orientation regularly showed strong FcγR-independent agonism. The affinity of the TNFR2 binding domain and the epitope recognized in TNFR2, however, were found to be of only secondary importance for agonistic activity. Conclusion: Generic design principles enable the generation of highly active bona fide TNFR2 agonists from nearly any TNFR2-specific antibody.

Assessment of clinical impact of SARS-CoV-2 in people with type 1 diabetes: A cohort study.

OBJECTIVES: During the coronavirus 2019 pandemic, there had been more than 758 million COVID-19 cases as of February 13, 2023, and it is the main cause of death in many countries. Due to the variation in disease presentation, scientists determined that people living with type 2 diabetes mellitus were at higher risk of mortality. However, people living with type 1 diabetes have not been thoroughly studied, especially in extreme regions of developing countries. The objective of this study was to analyze the effects of SARS-CoV-2 pandemic restrictions on different variables in a cohort with type 1 diabetes. METHODS: This cohort-type study included pediatric and adult patients with type 1 diabetes at Regional Hospital Dr. Juan Noé Crevani in Arica, Chile. Biosocial and anthropometric factors, clinical history, self-care activities, and biochemical parameters were assessed and compared using analysis of variance and paired t tests between March 2020 and March 2021. RESULTS: A total of 150 patients were assessed during the SARS-CoV-2 pandemic in Arica, Chile. One year after the pandemic struck, the main causes for metabolic deterioration were a reduction of carbohydrate counting by an average of 8.67% (P = 0.000), a reduction of adherence to treatment by an average of 25% (P = 0.000), and a shift to telemedicine as a main health care service (P = 0.023); these factors raised hemoglobin A1c (HbA1c) levels by 1.81%, 1.78% and 0.075%, respectively. The participants' average body mass index (BMI) increased by 1.26 kg/m2 and HbA1c levels increased by 0.16% during the first year of the pandemic. Also, hospitalizations increased about 2% (P = 0.984), and there was a significant increase in carbohydrate and snack intake (P = 0.330 and P = 0.811, respectively). Children's linear growth decreased by a standard deviation of 0.035 (P = 0.648), and their physical activity decreased by 12.67% (P = 0.383). CONCLUSIONS: This study found that adherence to diabetes care was reduced during the pandemic owing to a variety of behavioral reasons and environmental changes (e.g., quarantines and food security). This affected this population's HbA1c levels, BMI, linear growth, and number of hospitalizations as main consequences. Telemedicine remains an important tool, but it must be reconsidered among all different age groups.

Cross-examining the influence of upwelling and seaweed quality on herbivores' feeding behavior and growth.

At the regional scale, upwelling conditions are known to influence ecosystems and communities and their primary and secondary productivity. However, the influence of upwelling on local herbivore-algae interactions is less well understood. We address this question by cross-examining herbivores and seaweeds from sites associated with upwelling and downwelling conditions along the Humboldt Current System. Specifically, we quantified the feeding and benefits attained by the black sea urchin (Tetrapygus niger) and the black sea snail (Tegula atra) while consuming a widespread kelp species (Lessonia spicata). We hypothesized that food quality drives herbivores' preference, consumption, and growth rates, regardless of the origin or "prior" conditions of the consumers. Laboratory trials measured algal consumption rates with (preference) and without a choice, and consumer's growth rates, to assess the influence of food quality (algae from upwelling vs downwelling sites) and the site of origin of the consumers. Our results showed that algal quality was a prevailing factor for both herbivores: they chose, consumed more, and grew faster on high quality (upwelling) algae. By comparison, the origin of the consumer was only significant for sea snails: those coming from an upwelling site, consumed significantly more and grew faster than those from downwelling. The bulk of our results provided strong support to our hypothesis and suggest that the high nutritional quality of algae associated with upwelling centers has a strong influence on consumers' preferences, consumption, and performance (growth). The fact that origin was found to be relevant for one of the herbivores suggests that the conditions in which species grow may dictate some of their efficiency as consumers.

Rasgos funcionales de frutos con importancia particular para los dispersores de semillas en el bosque seco tropical

Introducción: La frugivoría es un proceso ecológico determinante para la estructuración y regeneración de los bosques. En los trópicos, donde la diversidad de plantas y animales frugívoros es alta, las relaciones interespecíficas son complejas y requieren estudio. Objetivo: Identificar las especies de plantas ecológicamente importantes en dos redes de interacción, y el papel de los rasgos funcionales de los frutos en esas interacciones en un bosque seco. Métodos: Recolectamos 10 frutos por planta de 10 plantas de cada especie de interés en un bosque seco colombiano, calculamos el índice de importancia de las plantas a partir de la relevancia de aves y mamíferos frugívoros en la estructura de las redes. Esta relevancia se relaciona directamente con el potencial del animal como dispersor efectivo de semillas. Utilizamos modelos lineales generalizados para estimar el tamaño, color, estrato, y tipo de pulpa, en el índice. Resultados: Las plantas más importantes son especies de los géneros Miconia, Ficus, Cecropia, Bursera, Casearia y Trichilia, también identificadas como recursos importantes para los frugívoros de los trópicos en otros estudios. Las plantas con frutos carnosos, rojos y de menor tamaño son los mejores para dispersores de semillas. El índice de importancia de las plantas tiene alta variación; esto sugiere que un conjunto de especies frugívoras beneficiadas por cada especie de planta tiene una contribución diferenciada en procesos ecológicos derivados de la dispersión de semillas. Conclusiones: Programas de restauración para este tipo de bosque tropical seco debería incluir una variedad de plantas, incluyendo especies con frutos pequeños, rojos y carnosos.

Introduction: Frugivory is a pivotal ecological process for the structure and regeneration of forests. In the tropics, where the diversity of plants and frugivorous animals is high, interspecific relationships in the interaction networks are complex and need study. Objective: To identify ecologically important plant species in two interaction networks, and the role of functional fruit traits in those interactions in a dry forest. Methods: We collected 10 fruits per plant from 10 plants of each species of interest in a Colombian dry forest, we calculated the Plant Importance Index based on the bird and mammal frugivores relevance for network structure. This relevance is directly related to the animal's potential as effective seed dispersers. We used generalized linear models to estimate the effect of fruit size, color, stratum, and type of pulp, on the index. Results: The most important plants are species of the genera Miconia, Ficus, Cecropia, Bursera, Casearia and Trichilia, also identified as important resources for tropical frugivores in other studies. Plants with small, red, and fleshy fruits are the best for seed dispersers. The plant importance index has a high variation; this suggests that the set of frugivore species benefited by each plant species has a differential contribution to the ecological processes derived from seed dispersal. Conclusions: Restoration programs for this kind of tropical dry forest should include a variety of plants, including species with small, red, and fleshy fruits.

The role of Eudragit® as a component of hydrogel formulations for medical devices.

Over the last decade, significant progress has been made in developing hydrogels as medical devices. By physically cross-linking pharmaceutically approved polymers into three-dimensional matrices, we can ensure their biocompatibility and facilitate their seamless transition from the laboratory to clinical applications. Moreover, the reversible nature of their physical cross-links allows hydrogels to dissolve in the presence of external stimuli. Particularly, their high degree of hydration, high molecular weight, and superior flexibility of the polymer chains facilitate their interaction with complex biological barriers (e.g., mucus layer), making them ideal candidates for mucosal drug delivery. However, fine-tuning the composition of the hydrogel formulations is of great importance to optimize the performance of the medical device and its therapeutic cargo. Herein, we investigated the influence of different Eudragits® on the properties of hydrogels based on polyvinylpyrrolidone (PVP), polyvinyl alcohol (PVA), and polyethylene glycol (PEG), which were originally proposed as ocular inserts in previous reports. Our research aims to determine the effects that including different Eudragits® have on the structure and protein ocular delivery ability of various hydrogel formulations. Properties such as matrix stability, protein encapsulation, release kinetics, mucoadhesion, and biocompatibility have been analyzed in detail. Our study represents a guideline of the features that Eudragits® have to exhibit to endow hydrogels with good adhesion to the eye's conjunctiva, biocompatibility, and structural strength to cope with the ocular biointerface and allow sustained protein release. This work has important implications for the design of new hydrogel materials containing Eudragits® in their composition, particularly in mucosal drug delivery.

Hormone Receptor-Positive / HER2-Negative Early Breast Cancer High-Risk Population: An Algorithm for Optimization Systemic Adjuvant Treatment Based on 2022 Updates.

Prognostic and predictive factors for early and late distant distance recurrence risk in estrogen-receptor positive and HER2-receptor negative early breast cancer are well known, but not all these variables work equally for the prediction. The following are the most widely accepted variables for categorizing risk levels: clinic-pathologic features (tumor size, lymph node involvement, histological grade, age, menopausal status, Ki-67 expression, estrogen, and progesterone expression), primary systemic treatment response (pathologic response and/or Ki-67 downstaging), and gene expression signatures stratification. Treatment guidelines from cancer societies and collaborative groups, online predict-tools, real-world data and experts' opinion recommends different adjuvant strategies (chemotherapy, endocrine therapy, ovarian suppression, olaparib, or abemaciclib) depending on the low (< 10%), intermediate (10%-20%) or high-risk of distance recurrence at least in the first 5 years. Multiple randomized prospective trials were updated in 2022, that evidence allow us to perform a stratification of risk in pre- and postmenopausal women with estrogen-receptor positive and HER2-receptor negative early breast cancer based on a combination of clinic-pathologic features and genomic assays and guide the adjuvant systemic treatment recommendation for those with high risk.

Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review.

Focal cortical dysplasia (FCD) is a congenital brain malformation that is closely associated with epilepsy. Early and accurate diagnosis is essential for effectively treating and managing FCD. Magnetic resonance imaging (MRI)-one of the most commonly used non-invasive neuroimaging methods for evaluating the structure of the brain-is often implemented along with automatic methods to diagnose FCD. In this review, we define three categories for FCD identification based on MRI: visual, semi-automatic, and fully automatic methods. By conducting a systematic review following the PRISMA statement, we identified 65 relevant papers that have contributed to our understanding of automatic FCD identification techniques. The results of this review present a comprehensive overview of the current state-of-the-art in the field of automatic FCD identification and highlight the progress made and challenges ahead in developing reliable, efficient methods for automatic FCD diagnosis using MRI images. Future developments in this area will most likely lead to the integration of these automatic identification tools into medical image-viewing software, providing neurologists and radiologists with enhanced diagnostic capabilities. Moreover, new MRI sequences and higher-field-strength scanners will offer improved resolution and anatomical detail for precise FCD characterization. This review summarizes the current state of automatic FCD identification, thereby contributing to a deeper understanding and the advancement of FCD diagnosis and management.