Smart hydrogels based on semi-interpenetrating polymeric networks of collagen-polyurethane-alginate for soft/hard tissue healing,drug delivery devices,and anticancer therapies

In this work, hydrogels based on semi-interpenetrating polymeric networks (semi-IPN) based on collagen-polyurethane-alginate were studied physicochemically and from different approaches for biomedical application. It was determined that the matrices in the hydrogel state are crosslinked by the formation of urea and amide bonds between the biopolymer chains and the polyurethane crosslinker. The increment in alginate content (0–40 wt%) significantly increases the swelling capacity, generating semi-crystalline granular structures with improved storage modulus and resistance to thermal, hydrolytic, and proteolytic degradation. The in vitro bioactivity results indicated that the composition of these novel hydrogels stimulates the metabolic activity of monocytes and fibroblasts, benefiting their proliferation; while in cancer cell lines, it was determined that the composition of these biomaterials decreases the metabolic activity of breast cancer cells after 48 h of stimulation, and for colon cancer cells their metabolic activity decreases after 72 h of contact for the hydrogel with 40 wt% alginate. The matrices show a behavior of multidose release of ketorolac, and a higher concentration of analgesic is released in the semi-IPN matrix. The inhibition capacity of Escherichia coli is higher if the polysaccharide concentration is low (10 wt%). The in vitro wound closure test (scratch test) results indicate that the hydrogel with 20 wt% alginate shows an improvement in wound closure at 15 days of contact. Finally, the bioactivity of mineralization was evaluated to demonstrate that these hydrogels can induce the formation of carbonated apatite on their surface. The engineered hydrogels show biomedical multifunctionality and they could be applied in soft and hard tissue healing strategies, anticancer therapies, and drug release devices.     

Selection of synthetic proteins to modulate the human frataxin function

Frataxin is a kinetic activator of the mitochondrial supercomplex for iron-sulfur cluster assembly. Low frataxin expression or a decrease in its functionality results in Friedreich's Ataxia (FRDA). With the aim of creating new molecular tools to study this metabolic pathway, and ultimately, to explore new therapeutic strategies, we have investigated the possibility of obtaining small proteins exhibiting a high affinity for frataxin. In this study, we applied the ribosome display approach, using human frataxin as the target. We focused on Affi_224, one of the proteins that we were able to select after five rounds of selection. We have studied the interaction between both proteins and discussed some applications of this specific molecular tutor, concerning the modulation of the supercomplex activity. Affi_224 and frataxin showed a K_D value in the nanomolar range, as judged by surface plasmon resonance analysis. Most likely, it binds to the frataxin acidic ridge, as suggested by the analysis of chemical shift perturbations (nuclear magnetic resonance) and computational simulations. Affi_224 was able to increase Cys NFS1 desulfurase activation exerted by the FRDA frataxin variant G130V. Importantly, Affi_224 interacts with frataxin in a human cellular model. Our results suggest quaternary addition may be a new tool to modulate frataxin function in vivo. Nevertheless, more functional experiments under physiological conditions should be carried out to evaluate Affi_224 effectiveness in FRDA cell models.     

Neo-tropical felid activity patterns in relation to potential prey and intraguild competitors in the Calakmul Biosphere Reserve,Mexico

Predator behaviors influence, and are influenced by, prey and competitor behaviors. Jaguars (Panthera onca), pumas (Puma concolor), and ocelots (Leopardus pardalis) coexist throughout their geographic range as the three largest predators in a multi-predator community across diverse environments. This study tested for non-random segregation and overlap in the activity patterns of these felids and their shared prey in the southern buffer zone of the Calakmul Biosphere Reserve, in southern Mexico, using camera traps during February to August 2019. We detected little temporal segregation between the nocturnal activities of jaguars, pumas, and ocelots, although pumas were more active closer to dawn. Jaguars had low activity overlap with species likely to be common prey, whereas ocelots had high overlap with their potential prey. Pumas displayed finer-scale similarities in activity with species likely to be common prey. In an understudied area of conservation importance, this study shows that temporal segregation is an unlikely mechanism of coexistence. Further research should incorporate spatio-temporal avoidance and dietary differences to improve our understanding of the mechanisms that drive coexistence between generalist species in a diverse assemblage of threatened felids. Abstract in Spanish is available with online material.     

Population structure of mud flounder Paralichthys orbignyanus from the south-western Atlantic Ocean

The mud flounder Paralichthys orbignyanus (Pleuronectiformes, Paralichthyidae) inhabits shallow waters of low salinities and mud bottoms in the temperate marine coastal regions of the Bonaerensean Ecoregion of the Argentinean Biogeographic Province in the south-western Atlantic Ocean. Specimens of P. orbignyanus were collected from Lagoa dos Patos (LDP) (southern Brazil), Mar Chiquita (MCH) and Marisol (MAR) both located in Buenos Aires (Argentina), and San Antonio Oeste (SAO) in the San Matías Gulf, Rio Negro (Argentina). A fragment of the mitochondrial DNA of the Control Region and seven microsatellite loci were characterized. In the Control Region, P. orbignyanus showed high variability, low nucleotide diversity, mild population expansion and a coalescence time of 35,000 years before the present. Flounders provided evidence of a genetic structure between the sampling sites LDP, MCH, MAR vs. SAO. On the other hand, P. orbignyanus displayed a lower to moderate contemporary genetic structure among all samples except between LDP and MCH. With no evidence of isolation by distance, this analysis supports a model of limited gene flow that is likely to be associated with a consistent larvae retention in all sampling sites. In addition, the present connectivity is ascribed to a lower migration process from SAO in the San Matías Gulf congruent with the prevailing littoral drift.     

Gene-rich plastid genomes of two parasitic red algal species,Laurencia australis and L. verruciformis (Rhodomelaceae,Ceramiales), and a taxonomic revision of Janczewskia

Parasitic red algae are an interesting system for investigating the genetic changes that occur in parasites. These parasites have evolved independently multiple times within the red algae. The functional loss of plastid genomes can be investigated in these multiple independent examples, and fine-scale patterns may be discerned. The only plastid genomes from red algal parasites known so far are highly reduced and missing almost all photosynthetic genes. Our study assembled and annotated plastid genomes from the parasites Janczewskia tasmanica and its two Laurencia host species (Laurencia elata and one unidentified Laurencia sp. A25) from Australia and Janczewskia verruciformis, its host species (Laurencia catarinensis), and the closest known free-living relative (Laurencia obtusa) from the Canary Islands (Spain). For the first time we show parasitic red algal plastid genomes that are similar in size and gene content to free-living host species without any gene loss or genome reduction. The only exception was two pseudogenes (moeB and ycf46) found in the plastid genome of both isolates of J. tasmanica, indicating potential for future loss of these genes. Further comparative analyses with the three highly reduced plastid genomes showed possible gene loss patterns, in which photosynthetic gene categories were lost followed by other gene categories. Phylogenetic analyses did not confirm monophyly of Janczewskia, and the genus was subsumed into Laurencia. Further investigations will determine if any convergent small-scale patterns of gene loss exist in parasitic red algae and how these are applicable to other parasitic systems.     

Same species,different population dynamics: Spatio-temporal differences of Undaria pinnatifida (Ochrophyta,Phaeophyceae) in the intertidal of North Patagonia,Argentina

Population dynamics can be influenced by physical and biological factors, particularly in stressful environments. Introduced species usually have great physiological plasticity, resulting in populations with different traits. Undaria pinnatifida, a macroalga originally described from northeast Asia, was introduced in Northern Patagonia, Argentina (San Matías Gulf) around 2010. To describe the spatio-temporal variability in population structure and morphometry of U. pinnatifida, we conducted monthly field samplings for 2 years at the intertidal area of two contrasting sites in the San Matías Gulf. Individuals of U. pinnatifida were classified by developmental stage, and their morpho-gravimetric variables were measured. In both intertidal sites juveniles were found in higher proportion during austral autumn and grew and matured during the autumn-winter months (from May onwards), and individuals senesced during early austral summer (December and January). Conversely, density and biomass were largely different between sites, and individuals showed slight morphological variability between sites. Environmental (e.g., nutrient concentration, available substrate) and biological factors (e.g., facilitation, competition) may explain the observed differences. Since there is not a macroalga with U. pinnatifida morphometrical characteristics in the intertidal environments of San Matías Gulf, studying this recent introduction gives us a better understanding of its potential ecological effects.     

Molecular magnetic materials from polyoxometalates

The significance of polyoxometalates in the field of molecular magnetism is discussed. We show that this kind of inorganic complexes provides remarkable examples for the study of the exchange interactions in clusters. On the other hand, we examine the possibility of using these metal oxide anions as magnetic components of molecular materials containing organic tetrathiafulvalenes as electron donor molecules.     

Enhancing estimation methods for integrating probability and nonprobability survey samples with machine-learning techniques. An application to a Survey on the impact of the COVID-19 pandemic in Spain

Web surveys have replaced Face-to-Face and computer assisted telephone interviewing (CATI) as the main mode of data collection in most countries. This trend was reinforced as a consequence of COVID-19 pandemic-related restrictions. However, this mode still faces significant limitations in obtaining probability-based samples of the general population. For this reason, most web surveys rely on nonprobability survey designs. Whereas probability-based designs continue to be the gold standard in survey sampling, nonprobability web surveys may still prove useful in some situations. For instance, when small subpopulations are the group under study and probability sampling is unlikely to meet sample size requirements, complementing a small probability sample with a larger nonprobability one may improve the efficiency of the estimates. Nonprobability samples may also be designed as a mean for compensating for known biases in probability-based web survey samples by purposely targeting respondent profiles that tend to be underrepresented in these surveys. This is the case in the Survey on the impact of the COVID-19 pandemic in Spain (ESPACOV) that motivates this paper. In this paper, we propose a methodology for combining probability and nonprobability web-based survey samples with the help of machine-learning techniques. We then assess the efficiency of the resulting estimates by comparing them with other strategies that have been used before. Our simulation study and the application of the proposed estimation method to the second wave of the ESPACOV Survey allow us to conclude that this is the best option for reducing the biases observed in our data.     

A mechanistic spatio-temporal modeling of COVID-19 data

Understanding the evolution of an epidemic is essential to implement timely and efficient preventive measures. The availability of epidemiological data at a fine spatio-temporal scale is both novel and highly useful in this regard. Indeed, having geocoded data at the case level opens the door to analyze the spread of the disease on an individual basis, allowing the detection of specific outbreaks or, in general, of some interactions between cases that are not observable if aggregated data are used. Point processes are the natural tool to perform such analyses. We analyze a spatio-temporal point pattern of Coronavirus disease 2019 (COVID-19) cases detected in Valencia (Spain) during the first 11 months (February 2020 to January 2021) of the pandemic. In particular, we propose a mechanistic spatio-temporal model for the first-order intensity function of the point process. This model includes separate estimates of the overall temporal and spatial intensities of the model and a spatio-temporal interaction term. For the latter, while similar studies have considered different forms of this term solely based on the physical distances between the events, we have also incorporated mobility data to better capture the characteristics of human populations. The results suggest that there has only been a mild level of spatio-temporal interaction between cases in the study area, which to a large extent corresponds to people living in the same residential location. Extending our proposed model to larger areas could help us gain knowledge on the propagation of COVID-19 across cities with high mobility levels.