The Effect of Intensive Implementation Support on Fidelity for Four Evidence‑Based Psychosis Treatments: A Cluster Randomized Trial

Abstract Purpose: Service providers need effective strategies to implement evidence-based practices (EBPs) with high fidelity. This study aimed to evaluate an intensive implementation support strategy to increase fidelity to EBP standards in treatment of patients with psychosis. Methods: The study used a cluster randomized design with pairwise assignment of practices within each of 39 Norwegian mental health clinics. Each site chose two of four practices for implementation: physical health care, antipsychotic medication management, family psychoeducation, illness management and recovery. One practice was assigned to the experimental condition (toolkits, clinical training, implementation facilitation, data-based feedback) and the other to the control condition (manual only). The outcome measure was fidelity to the EBP, measured at baseline and after 6, 12, and 18 months, analyzed using linear mixed models and effect sizes. Results: The increase in fidelity scores (within a range 1-5) from baseline to 18 months was significantly greater for experimental sites than for control sites for the combined four practices, with mean difference in change of 0.86 with 95% CI (0.21; 1.50), p = 0.009). Effect sizes for increase in group difference of mean fidelity scores were 2.24 for illness management and recovery, 0.68 for physical health care, 0.71 for antipsychotic medication management, and 0.27 for family psychoeducation. Most improvements occurred during the first 12 months. Conclusions: Intensive implementation strategies (toolkits, clinical training, implementation facilitation, data-based feedback) over 12 months can facilitate the implementation of EBPs for psychosis treatment. The approach may be more effective for some practices than for others. Keywords: Evidence-based practice; Fidelity scale; Implementation support; Mental health services; Psychoses. © 2021. The Author(s).publishedVersio

Biorefining of wheat straw:accounting for the distribution of mineral elements in pretreated biomass by an extended pretreatment–severity equation

BACKGROUND: Mineral elements present in lignocellulosic biomass feedstocks may accumulate in biorefinery process streams and cause technological problems, or alternatively can be reaped for value addition. A better understanding of the distribution of minerals in biomass in response to pretreatment factors is therefore important in relation to development of new biorefinery processes. The objective of the present study was to examine the levels of mineral elements in pretreated wheat straw in response to systematic variations in the hydrothermal pretreatment parameters (pH, temperature, and treatment time), and to assess whether it is possible to model mineral levels in the pretreated fiber fraction. RESULTS: Principal component analysis of the wheat straw biomass constituents, including mineral elements, showed that the recovered levels of wheat straw constituents after different hydrothermal pretreatments could be divided into two groups: 1) Phosphorus, magnesium, potassium, manganese, zinc, and calcium correlated with xylose and arabinose (that is, hemicellulose), and levels of these constituents present in the fiber fraction after pretreatment varied depending on the pretreatment-severity; and 2) Silicon, iron, copper, aluminum correlated with lignin and cellulose levels, but the levels of these constituents showed no severity-dependent trends. For the first group, an expanded pretreatment-severity equation, containing a specific factor for each constituent, accounting for variability due to pretreatment pH, was developed. Using this equation, the mineral levels could be predicted with R(2) > 0.75; for some with R(2) up to 0.96. CONCLUSION: Pretreatment conditions, especially pH, significantly influenced the levels of phosphorus, magnesium, potassium, manganese, zinc, and calcium in the resulting fiber fractions. A new expanded pretreatment-severity equation is proposed to model and predict mineral composition in pretreated wheat straw biomass

A genetically modified minipig model for Alzheimer's disease with SORL1 haploinsufficiency

The established causal genes in Alzheimer’s disease (AD), APP, PSEN1, and PSEN2, are functionally characterized using biomarkers, capturing an in vivo profile reflecting the disease’s initial preclinical phase. Mutations in SORL1, encoding the endosome recycling receptor SORLA, are found in 2%–3% of individuals with early-onset AD, and SORL1 haploinsufficiency appears to be causal for AD. To test whether SORL1 can function as an AD causal gene, we use CRISPR-Cas9-based gene editing to develop a model of SORL1 haploinsufficiency in Göttingen minipigs, taking advantage of porcine models for biomarker investigations. SORL1 haploinsufficiency in young adult minipigs is found to phenocopy the preclinical in vivo profile of AD observed with APP, PSEN1, and PSEN2, resulting in elevated levels of β-amyloid (Aβ) and tau preceding amyloid plaque formation and neurodegeneration, as observed in humans. Our study provides functional support for the theory that SORL1 haploinsufficiency leads to endosome cytopathology with biofluid hallmarks of autosomal dominant AD

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis