Psoriasis and Gut Microbiome—Current State of Art

Psoriasis is a chronic, immune-mediated inflammatory disease that affects around 125 million people worldwide. Several studies concerning the gut microbiota composition and its role in disease pathogenesis recently demonstrated significant alterations among psoriatic patients. Certain parameters such as Firmicutes/Bacteroidetes ratio or Psoriasis Microbiome Index were developed in order to distinguish between psoriatic and healthy individuals. The “leaky gut syndrome” and bacterial translocation is considered by some authors as a triggering factor for the onset of the disease, as it promotes chronic systemic inflammation. The alterations were also found to resemble those in inflammatory bowel diseases, obesity and certain cardiovascular diseases. Microbiota dysbiosis, depletion in SCFAs production, increased amount of produced TMAO, dysregulation of the pathways affecting the balance between lymphocytes populations seem to be the most significant findings concerning gut physiology in psoriatic patients. The gut microbiota may serve as a potential response-to-treatment biomarker in certain cases of biological treatment. Oral probiotics administration as well as fecal microbial transplantation were most reported in bringing health benefits to psoriatic patients. However, the issue of psoriatic bacterial gut composition, its role and healing potential needs further investigation. Here we reviewed the literature on the current state of the relationship between psoriasis and gut microbiome.     

Manual dexterity of older Mexican American adults: a cross-sectional pilot experimental investigation

This paper reports results from an experimental pilot study performed to quantify the manual dexterity of older Mexican American adults. The Purdue pegboard test, a two-arm coordination test, and a hand-tool dexterity test were used in this study. To enable cross-sectional comparisons of manual dexterity measures of older Mexican American adults with young Mexican American adults, these tests were administered to 18 older Mexican American adults aged 63–85 (mean age: 71.3 years, SD: 7.0 years), recruited from senior recreation centers in El Paso, and eighteen young adults aged 21–32 (mean age: 25.6 years, SD: 3.8 years) recruited from the student body at the University of Texas at El Paso. For the Purdue pegboard test, the number of pegs placed in 30 s using the preferred hand, the non-preferred hand, and both hands were first individually monitored. Then, scores on an assembly task using the Purdue pegboard were obtained. For the two-arm coordination test, participants were required to trace a star pattern with a stylus using both hands. The time for task completion and the number of errors made during task performance were monitored. For the hand-tool dexterity test, participants were required to use common hand tools and remove nuts and bolts from one side of a wooden upright, and to assemble nuts and bolts in the corresponding holes on the other side of the upright. The time taken for task completion was recorded. Since modified Levene's test showed equality of variances, two sample t-tests, comparing the mean responses of older adults with the mean responses of young adults for each individual test, were conducted. Results indicate that responses for the older adults were statistically significant different (p<0.001) from young adults for all Purdue pegboard tasks. On the average, older adults performed significantly slower (p<0.001) than young adults on the two-arm coordination test, and committed more errors before task completion (p<0.05). Older adults also took longer to complete the hand-tool dexterity task compared to their younger counterparts (p<0.05). In addition to the t-tests, manual dexterity performance measures from older adults were regressed with age to determine the cross-sectional age effects on manual dexterity measures. Results indicate that all Purdue pegboard performance measures were significantly affected by age (p<0.05). The time to complete the two-arm coordination test was significantly linearly related to age (p<0.05). However, the number of errors committed by older adults in the performance of the two-arm coordination test was not significantly linearly related to age. Time to complete the hand-tool dexterity was also significantly linearly related to age (p<0.05). Accommodating age-related changes in manual dexterity is important for job design in industry, especially in industries employing older adults requiring significant assembly and hand-tool use.

Relevance to industry

Given the aging of the industrial workforce, it is important to understand how manual dexterity is affected by age, so that jobs requiring significant manual dexterity for task initiation, task performance and task completion are designed to fit older adult dexterity levels.     

Experimental design to evaluate properties of electrospun fibers of zein/poly (ethylene oxide) for biomaterial applications

The production of polymer fibers from the combination of zein and PEO might have great potential in the field of biomaterial. Zein/PEO fibers were obtained in this work through solution electrospinning. An experimental design, 2^4-1, was used for evaluating the influences of PEO content in the blend, distance from the needle tip to the collector, applied electric voltage and solution flow for average fiber diameter and relative-yield process. Beyond this, the relationship between PEO content in the blend and the fiber properties were evaluated through FTIR, DSC, TG, tensile tests, and cytotoxic tests. The factor that exerts the greatest effect on the average fiber diameter response was the electrical voltage. The increase in PEO content in the blend decreased the thermal stability and increased the degree of the fibers' crystallinity. The mechanical tests showed that fibers with higher elongation were obtained at richer PEO blends. The fibers presented cytocompatible characteristics.     

When a Tritrophic Interaction Goes Wrong to the Third Level: Xanthoxylin From Trees Causes the Honeybee Larval Mortality in Colonies Affected by the River Disease

The “River Disease” (RD), a disorder impacting honeybee colonies located close to waterways with abundant riparian vegetation (including Sebastiania schottiana, Euphorbiaceae), kills newly hatched larvae. Forager bees from RD-affected colonies collect honeydew excretions from Epormenis cestri (Hemiptera: Flatidae), a planthopper feeding on trees of S. schottiana. First-instar honeybee larvae fed with this honeydew died. Thus, we postulated that the nectars of RD-affected colonies had a natural toxin coming from either E. cestri or S. schottiana. An untargeted metabolomics characterization of fresh nectars extracts from colonies with and without RD allowed to pinpoint xanthoxylin as one of the chemicals present in higher amounts in nectar from RD-affected colonies than in nectars from healthy colonies. Besides, xanthoxylin was also found in the aerial parts of S. schottiana and the honeydew excreted by E. cestri feeding on this tree. A larva feeding assay where xanthoxylin-enriched diets were offered to 1^st instar larvae showed that larvae died in the same proportion as larvae did when offered enriched diets with nectars from RD-colonies. These findings demonstrate that a xenobiotic can mimic the RD syndrome in honeybee larvae and provide evidence of an interspecific flow of xanthoxylin among three trophic levels. Further, our results give information that can be considered when implementing measures to control this honeybee disease.

     

Engineered Multifunctional Albumin‐Decorated Porous Silicon Nanoparticles for FcRn Translocation of Insulin

The last decade has seen remarkable advances in the development of drug delivery systems as alternative to parenteral injection‐based delivery of insulin. Neonatal Fc receptor (FcRn)‐mediated transcytosis has been recently proposed as a strategy to increase the transport of drugs across the intestinal epithelium. FcRn‐targeted nanoparticles (NPs) could hijack the FcRn transcytotic pathway and cross the epithelial cell layer. In this study, a novel nanoparticulate system for insulin delivery based on porous silicon NPs is proposed. After surface conjugation with albumin and loading with insulin, the NPs are encapsulated into a pH‐responsive polymeric particle by nanoprecipitation. The developed NP formulation shows controlled size and homogeneous size distribution. Transmission electron microscopy (TEM) images show successful encapsulation of the NPs into pH‐sensitive polymeric particles. No insulin release is detected at acidic conditions, but a controlled release profile is observed at intestinal pH. Toxicity studies show high compatibility of the NPs with intestinal cells. In vitro insulin permeation across the intestinal epithelium shows approximately fivefold increase when insulin is loaded into FcRn‐targeted NPs. Overall, these FcRn‐targeted NPs offer a toolbox in the development of targeted therapies for oral delivery of insulin.     

Ontology-driven web-based semantic similarity

Estimation of the degree of semantic similarity/distance between concepts is a very common problem in research areas such as natural language processing, knowledge acquisition, information retrieval or data mining. In the past, many similarity measures have been proposed, exploiting explicit knowledge—such as the structure of a taxonomy—or implicit knowledge—such as information distribution. In the former case, taxonomies and/or ontologies are used to introduce additional semantics; in the latter case, frequencies of term appearances in a corpus are considered. Classical measures based on those premises suffer from some problems: in the first case, their excessive dependency of the taxonomical/ontological structure; in the second case, the lack of semantics of a pure statistical analysis of occurrences and/or the ambiguity of estimating concept statistical distribution from term appearances. Measures based on Information Content (IC) of taxonomical concepts combine both approaches. However, they heavily depend on a properly pre-tagged and disambiguated corpus according to the ontological entities in order to compute accurate concept appearance probabilities. This limits the applicability of those measures to other ontologies –like specific domain ontologies- and massive corpus –like the Web-. In this paper, several of the presented issues are analyzed. Modifications of classical similarity measures are also proposed. They are based on a contextualized and scalable version of IC computation in the Web by exploiting taxonomical knowledge. The goal is to avoid the measures’ dependency on the corpus pre-processing to achieve reliable results and minimize language ambiguity. Our proposals are able to outperform classical approaches when using the Web for estimating concept probabilities.     

Robust probabilistic planning with ilao

In probabilistic planning problems which are usually modeled as Markov Decision Processes (MDPs), it is often difficult, or impossible, to obtain an accurate estimate of the state transition probabilities. This limitation can be overcome by modeling these problems as Markov Decision Processes with imprecise probabilities (MDP-IPs). Robust LAO* and Robust LRTDP are efficient algorithms for solving a special class of MDP-IPs where the probabilities lie in a given interval, known as Bounded-Parameter Stochastic-Shortest Path MDP (BSSP-MDP). However, they do not make clear what assumptions must be made to find a robust solution (the best policy under the worst model). In this paper, we propose a new efficient algorithm for BSSP-MDPs, called Robust ILAO* which has a better performance than Robust LAO* and Robust LRTDP, considered the-state-of-the art of robust probabilistic planning. We also define the assumptions required to ensure a robust solution and prove that Robust ILAO* algorithm converges to optimal values if the initial value of all states is admissible.     

Gene expression changes in a transgenic mouse model overexpressing human wildtype and mutant torsinA

Primary torsion dystonia is an autosomal-dominantly inherited, neurodevelopmental movement disorder caused by a GAG deletion (ΔGAG) in the DYT1 gene, encoding torsinA. This mutation is responsible for approximately 70% of cases of early-onset primary torsion dystonia. The function of wildtype torsinA is still unknown, and it is unsolved how the deletion in the DYT1 gene contributes to the development of the disease. To better understand the molecular processes involved in torsinA pathology, we used genome-wide oligonucleotide microarrays to characterize gene expression patterns in the striatum of mouse models overexpressing the human wildtype and mutant torsinA. By this approach we were able to detect gene expression changes that seem to be specific for torsinA pathology. We found an impact of torsinA, independent from genotype, on vesicle trafficking, exocytosis, and neurotransmitter release in our mouse model. In addition, we were able to identify several new pathways and processes involved in the development of the nervous system that are affected by wildtype and mutant torsinA. Furthermore, we have striking evidence from our gene expression data that glutamate receptor mediated synaptic plasticity in the striatum is the affected underlying cellular process for impaired motor learning in human ΔGAG torsinA transgenic mice.