Krusele3465
This article is part of the theme issue 'The role of the microbiome in host evolution'.In many animal hosts, microbial symbionts are housed within specialized structures known as symbiotic organs, but the evolutionary origins of these structures have rarely been investigated. Here, I adopt an evolutionary developmental (evo-devo) approach, specifically to apply knowledge of the development of symbiotic organs to gain insights into their evolutionary origins and diversification. In particular, host genetic changes associated with evolution of symbiotic organs can be inferred from studies to identify the host genes that orchestrate the development of symbiotic organs, recognizing that microbial products may also play a key role in triggering the developmental programme in some associations. These studies may also reveal whether higher animal taxonomic groups (order, class, phylum, etc.) possess a common genetic regulatory network for symbiosis that is latent in taxa lacking symbiotic organs, and activated at the origination of symbiosis in different host lineages. In this way, apparent instances of convergent evolution of symbiotic organs may be homologous in terms of a common genetic blueprint for symbiosis. Advances in genetic technologies, including reverse genetic tools and genome editing, will facilitate the application of evo-devo approaches to investigate the evolution of symbiotic organs in animals. This article is part of the theme issue 'The role of the microbiome in host evolution'.Microorganismal diversity can be explained in large part by selection imposed from both the abiotic and biotic environments, including-in the case of host-associated microbiomes-interactions with eukaryotes. As such, the diversity of host-associated microbiomes can be usefully studied across a variety of scales within a single host over time, among host genotypes within a population, between populations and among host species. A plethora of recent studies across these scales and across diverse systems are (i) exemplifying the importance of the host genetics in shaping microbiome composition; (ii) uncovering the role of the microbiome in shaping key host phenotypes; and (iii) highlighting the dynamic nature of the microbiome. They have also raised a critical question do these complex associations fit within our existing understanding of evolution and coevolution, or do these often intimate and seemingly cross-generational interactions follow novel evolutionary rules from those previously identified? Herein, we describe the known importance of (co)evolution in host-microbiome systems, placing the existing data within extant frameworks that have been developed over decades of study, and ask whether there are unique properties of host-microbiome systems that require a paradigm shift. By examining when and how selection can act on the host and its microbiome as a unit (termed, the holobiont), we find that the existing conceptual framework, which focuses on individuals, as well as interactions among individuals and groups, is generally well suited for understanding (co)evolutionary change in these intimate assemblages. This article is part of the theme issue 'The role of the microbiome in host evolution'.Community-integrated facilities provide security and care for justice-involved youth, minimizing risks, while allowing youth to build on protective factors within their community. Literature on the specific factors that determine appropriate placement in a community-integrated facility, versus a more restrictive high-security setting, is scarce. Current screening and assessment tools for youth are mostly applied after placement and mainly focus on the reoffending risk. The current paper explored which youth, who would previously have been placed in a high-security setting, could be successfully placed in a less secure community-integrated facility. Through qualitative analysis, based on the perspectives of professionals, youth and parents, the current paper identified six distinct domains to guide appropriate screening and outlines guidelines for policy and practice. These domains include motivation to comply, short and long-term perspective, current offense context, crime history, safety and support from youth's network, and mental health and intellectual abilities.
This study was performed assess the clinical outcomes of elderly patients with osteoporotic femoral neck fractures (FNFs) (AO/OTA 31B/C) treated by initial uncemented total hip arthroplasty (UTA) or cemented total hip arthroplasty (CTA).
This study involved consecutive elderly patients with osteoporotic FNFs (AO/OTA 31B/C) treated by initial UTA or CTA in our medical centre from 2010 to 2015. The primary outcomes were the Harris hip score (HHS) and the rates of revision, loosening, periprosthetic fracture, and dislocation.
In total, 224 patients were included in the final analysis (UTA, n = 114; CTA, n = 110). The mean follow-up duration was 60 months (range, 32-68 months). The mean HHS was 75.34 ± 18.82 for UTA and 80.12 ± 17.83 for CTA. Significant dissimilarities were detected in the rates of revision, loosening, and periprosthetic fracture between UTA and CTA (14.0% vs. 5.5%, 20.2% vs. Mivebresib supplier 10.0%, and 12.3% vs. 4.5%, respectively). A significant difference was also detected in the probability of revision between the two groups.
Elderly patients with osteoporotic FNFs (AO/OTA 31B/C) treated with CTA show greater improvements in functional outcomes and key orthopaedic complications than those treated with UTA.
Elderly patients with osteoporotic FNFs (AO/OTA 31B/C) treated with CTA show greater improvements in functional outcomes and key orthopaedic complications than those treated with UTA.
Currently, measurement tools to assess patient-reported outcomes for drug dependence are limited in their latent trait to adapt to the needs of individual patients while also maintaining comparability of scores across patients.
To develop an item bank for computer adaptive testing (CAT) to measure severity of drug dependence. Methods There were four phases (1) review the literature of drug dependence measurement; (2) formulate an item list to be assessed by experts; (3) pretest our item list in two substance dependence treatment centers; and (4) field-test and conduct psychometric performance analysis with the final item bank. Additionally, based on our response data, a CAT simulation was used to validate the item bank, Drug Dependence CAT (DD-CAT).
The final drug dependence item bank - with a unidimensional configuration - contained 56 items with good item-fit, high discrimination, no differential item functioning, and covered all symptoms of diagnostic criteria for drug dependence. These results revealed that the final item bank was of good quality.
