Single-case experimental designs: Reflections on conduct and analysis

In this editorial discussion we reflect on the issues addressed by, and arising from, the papers in this Special Issue on Single Case Experimental Design (SCED) study methodology. We identify areas of consensus and disagreement regarding the conduct and analysis of SCED studies. Despite the long history of application of SCEDs in studies of interventions in clinical and educational settings, the field is still developing. There is an emerging consensus on methodological quality criteria for many aspects of SCEDs, but disagreement on what are the most appropriate methods of SCED data analysis. Our aim is to stimulate this ongoing debate and highlight issues requiring further attention from applied researchers and methodologists. In addition we offer tentative criteria to support decision making in relation to selection of analytical techniques in SCED studies. Finally, we stress that large-scale interdisciplinary collaborations, such as the current Special Issue, are necessary if SCEDs are going to play a significant role in the development of the evidence base for clinical practice

Single case experimental designs: Introduction to a special Issue of Neuropsychological Rehabilitation

This paper introduces the Special Issue of Neuropsychological Rehabilitation on Single Case Experimental Design (SCED) methodology. SCED studies have a long history of use in evaluating behavioural and psychological interventions, but in recent years there has been a resurgence of interest in SCED methodology, driven in part by the development of standards for conducting and reporting SCED studies. Although there is consensus on some aspects of SCED methodology, the question of how SCED data should be analysed remains unresolved. This Special Issues includes two papers discussing aspects of conducting SCED studies, five papers illustrating use of SCED methodology in clinical practice, and nine papers that present different methods of SCED data analysis. A final Discussion paper summarises points of agreement, highlights areas where further clarity is needed, and ends with a set of resources that will assist researchers conduct and analyse SCED studies

Diversity of microbial eukaryotes along the West Antarctic Peninsula in austral spring

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Grattepanche, J.-D., Jeffrey, W., Gast, R., & Sanders, R. Diversity of microbial eukaryotes along the West Antarctic Peninsula in austral spring. Frontiers in Microbiology, 13, (2022): 844856, https://doi.org/10.3389/fmicb.2022.844856.During a cruise from October to November 2019, along the West Antarctic Peninsula, between 64.32 and 68.37°S, we assessed the diversity and composition of the active microbial eukaryotic community within three size fractions: micro- (> 20 μm), nano- (20–5 μm), and pico-size fractions (5–0.2 μm). The communities and the environmental parameters displayed latitudinal gradients, and we observed a strong similarity in the microbial eukaryotic communities as well as the environmental parameters between the sub-surface and the deep chlorophyll maximum (DCM) depths. Chlorophyll concentrations were low, and the mixed layer was shallow for most of the 17 stations sampled. The richness of the microplankton was higher in Marguerite Bay (our southernmost stations), compared to more northern stations, while the diversity for the nano- and pico-plankton was relatively stable across latitude. The microplankton communities were dominated by autotrophs, mostly diatoms, while mixotrophs (phototrophs-consuming bacteria and kleptoplastidic ciliates, mostly alveolates, and cryptophytes) were the most abundant and active members of the nano- and picoplankton communities. While phototrophy was the dominant trophic mode, heterotrophy (mixotrophy, phagotrophy, and parasitism) tended to increase southward. The samples from Marguerite Bay showed a distinct community with a high diversity of nanoplankton predators, including spirotrich ciliates, and dinoflagellates, while cryptophytes were observed elsewhere. Some lineages were significantly related—either positively or negatively—to ice coverage (e.g., positive for Pelagophyceae, negative for Spirotrichea) and temperature (e.g., positive for Cryptophyceae, negative for Spirotrichea). This suggests that climate changes will have a strong impact on the microbial eukaryotic community.This work was supported by the National Science Foundation (Grant Nos. ANT 1744767 to RS, ANT 1744663 to RG, and ANT 1744638 to WJ). This research was based, in part, upon sequencing conducted using the Rhode Island Genomics and Sequencing Center, which was supported in part by the National Science Foundation (MRI Grant No. DBI-0215393 and EPSCoR Grant Nos. 0554548 and EPS-1004057), the US Department of Agriculture (Grant Nos. 2002-34438-12688 and 2003-34438-13111), and the University of Rhode Island. This research includes calculations carried out on Temple University HPC resources supported in part by the National Science Foundation through major research instrumentation (Grant No. 1625061) and by the US Army Research Laboratory under (Contract No. W911NF-16-2-0189)

Acanthamoeba genotype T4 from the UK and Iran and isolation of the T2 genotype from clinical isolates

The majority of the keratitis-causing Acanthamoeba isolates are genotype T4. In an attempt to determine whether predominance of T4 isolates in Acanthamoeba keratitis is due to greater virulence or greater prevalence of this genotype, Acanthamoeba genotypes were determined for 13 keratitis isolates and 12 environmental isolates from Iran. Among 13 clinical isolates, eight (61.5 %) belonged to T4, two (15.3 %) belonged to T3 and three (23 %) belonged to the T2 genotype. In contrast, the majority of 12 environmental isolates tested in the present study belonged to T2 (7/12, 58.3 %), followed by 4/12 T4 isolates (33.3 %). In addition, the genotypes of six new Acanthamoeba isolates from UK keratitis cases were determined. Of these, five (83.3 %) belonged to T4 and one was T3 (16.6 %), supporting the expected high frequency of T4 in Acanthamoeba keratitis. In total, the genotypes of 24 Acanthamoeba keratitis isolates from the UK and Iran were determined. Of these, 17 belonged to T4 (70.8 %), three belonged to T2 (12.5 %), three belonged to T3 (12.5 %) and one belonged to T11 (4.1 %), confirming that T4 is the predominant genotype (S2 = 4.167; P = 0.0412) in Acanthamoeba keratitis

Brief comments on Jackiw-Teitelboim gravity coupled to Liouville theory

Jackiw-Teitelboim gravity with non-vanishing cosmological constant coupled to Liouville theory is considered as a non-critical string on $d$ dimensional flat spacetime. It is discussed how the presence of cosmological constant yields additional constraints on the parameter space of the theory, even when the conformal anomaly is independent of the cosmological constant. Such constraints agree with the necessary conditions for the tachyon field to be a primary --prelogarithmic-- operator of the worldsheet conformal field theory. Thus, the linearized tachyon field equation allows to impose the diagonal condition for the interaction term. We analyze the neutralization of the Liouville mode induced by the coupling to the Jackiw-Teitelboim Lagrangian. The free field prescription leads to obtain explicit expressions for three-point correlation functions for the case of vanishing cosmological constant in terms of a product of Shapiro-Virasoro integrals. This is a consequence of the mentioned neutralization effect.Comment: 14 pages, no figures. v2 References added. To be published in Classical and Quantum Gravity. v3 typos correcte

The Single-Case Reporting Guideline In BEhavioural Interventions (SCRIBE) 2016 statement

We developed a reporting guideline to provide authors with guidance about what should be reported when writing a paper for publication in a scientific journal using a particular type of research design: the single-case experimental design. This report describes the methods used to develop the Single-Case Reporting guideline In BEhavioural interventions (SCRIBE) 2016. As a result of 2 online surveys and a 2-day meeting of experts, the SCRIBE 2016 checklist was developed, which is a set of 26 items that authors need to address when writing about single-case research. This article complements the more detailed SCRIBE 2016 Explanation and Elaboration article (Tate et al., 2016) that provides a rationale for each of the items and examples of adequate reporting from the literature. Both these resources will assist authors to prepare reports of single-case research with clarity, completeness, accuracy, and transparency. They will also provide journal reviewers and editors with a practical checklist against which such reports may be critically evaluated. We recommend that the SCRIBE 2016 is used by authors preparing manuscripts describing single-case research for publication, as well as journal reviewers and editors who are evaluating such manuscripts.Funding for the SCRIBE project was provided by the Lifetime Care and Support Authority of New South Wales, Australia. The funding body was not involved in the conduct, interpretation or writing of this work. We acknowledge the contribution of the responders to the Delphi surveys, as well as administrative assistance provided by Kali Godbee and Donna Wakim at the SCRIBE consensus meeting. Lyndsey Nickels was funded by an Australian Research Council Future Fellowship (FT120100102) and Australian Research Council Centre of Excellence in Cognition and Its Disorders (CE110001021). For further discussion on this topic, please visit the Archives of Scientific Psychology online public forum at http://arcblog.apa.org. (Lifetime Care and Support Authority of New South Wales, Australia; FT120100102 - Australian Research Council Future Fellowship; CE110001021 - Australian Research Council Centre of Excellence in Cognition and Its Disorders)Published versio

Probabilistic Bisimulation: Naturally on Distributions

In contrast to the usual understanding of probabilistic systems as stochastic processes, recently these systems have also been regarded as transformers of probabilities. In this paper, we give a natural definition of strong bisimulation for probabilistic systems corresponding to this view that treats probability distributions as first-class citizens. Our definition applies in the same way to discrete systems as well as to systems with uncountable state and action spaces. Several examples demonstrate that our definition refines the understanding of behavioural equivalences of probabilistic systems. In particular, it solves a long-standing open problem concerning the representation of memoryless continuous time by memory-full continuous time. Finally, we give algorithms for computing this bisimulation not only for finite but also for classes of uncountably infinite systems

Impact of the Gut Microbiota on Atorvastatin Mediated Effects on Blood Lipids

Background and aims: The mechanisms of interindividual variation of lipid regulation by statins, such as the low-density lipoprotein cholesterol (LDL) lowering effects, are not fully understood yet. Here, we used a gut microbiota depleted mouse model to investigate the relation between the gut microbiota and the regulatory property of atorvastatin on blood lipids. Methods: Mice (C57BL/6) with intact gut microbiota or antibiotic induced abiotic mice (ABS) were put on standard chow diet (SCD) or high fat diet (HFD) for six weeks. Atorvastatin (10 mg/kg body weight/day) or a control vehicle were applied per gavage for the last four weeks of dietary treatment. Blood lipids including total cholesterol, very low-density lipoprotein, low-density lipoprotein, high-density lipoprotein and sphingolipids were measured to probe microbiota-dependent effects of atorvastatin. The expression of genes involved in hepatic and intestinal cholesterol metabolism was analyzed with qRT-PCR. The alteration of the microbiota profile was examined using 16S rRNA qPCR in mice with intact gut microbiota. Results: HFD feeding significantly increased total blood cholesterol and LDL levels, as compared to SCD in both mice with intact and depleted gut microbiota. The cholesterol lowering effect of atorvastatin was significantly attenuated in mice with depleted gut microbiota. Moreover, we observed a global shift in the abundance of several sphingolipids upon atorvastatin treatment which was absent in gut microbiota depleted mice. The regulatory effect of atorvastatin on the expression of distinct hepatic and intestinal cholesterol-regulating genes, including Ldlr, Srebp2 and Npc1l1 was altered upon depletion of gut microbiota. In response to HFD feeding, the relative abundance of the bacterial phyla Bacteroidetes decreased, while the abundance of Firmicutes increased. The altered ratio between Firmicutes to Bacteroidetes was partly reversed in HFD fed mice treated with atorvastatin. Conclusions: Our findings support a regulatory impact of atorvastatin on the gut microbial profile and, in turn, demonstrate a crucial role of the gut microbiome for atorvastatin-related effects on blood lipids. These results provide novel insights into potential microbiota-dependent mechanisms of lipid regulation by statins, which may account for variable response to statin treatment