Notes

Form of a new Platelet-Mediated Supply Method for Drug-Incorporated Nanospheres to improve Anti-Tumor Restorative Impact.
11 kcal/mol). Thus, this study provided vital information on the volatile compounds in underutilized spices associated with their health beneficial properties.
Test the feasibility of replacing 24-hour urine collection with a single voided urinary protein-creatinine ratio (UPCR) inpatients with amyloid light-chain (AL) amyloidosis.

Retrospective study examining the correlation between a 24-hour urine measurement and UPCR at various proteinuria levels using a linear regression analysis with Pearson's correlation coefficient (r). We assessed how using these 2 different measurements would alter the diagnosis, staging, and kidney response assessment in patients with AL amyloidosis.

We included 265 patients with systemic AL amyloidosis who visited the Amyloidosis Center at Boston University between July 2018-January 2020 and had proteinuria measurement by both methods on the same day.

24-hour urine collection for protein versus UPCR.

The correlation between 24-hour urine and UPCR was moderate in patients with proteinuria levels of 500-3,000 mg/day and >3,000 mg/day, with r values of 0.57 and 0.62, respectively. Replacing the 24-hour urine collection with UPCo recommend it in patients with AL amyloidosis because replacing the 24-hour urine collection with UPCR would change kidney staging and organ response in 10%-20% of patients. In addition, the correlation between the 2 modalities was moderate at best in patients with nephrotic-range proteinuria.The global pandemic of COVID-19 caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection confers great threat to public health. Human breast milk is a complex nutritional composition to nourish infants and protect them from different kinds of infectious diseases including COVID-19. Here, we identified that lactoferrin (LF), mucin1 (MUC1), and α-lactalbumin (α-LA) from human breast milk inhibit SARS-CoV-2 infection using a SARS-CoV-2 pseudovirus system and transcription and replication-competent SARS-CoV-2 virus-like-particles (trVLP). In addition, LF and MUC1 inhibited multiple steps including viral attachment, entry, and postentry replication, whereas α-LA inhibited viral attachment and entry. Importantly, LF, MUC1, and α-LA possess potent antiviral activities toward variants such as B.1.1.7 (alpha), B.1.351 (beta), P.1 (gamma), and B.1.617.1 (kappa). Taken together, our study provides evidence that human breast milk components (LF, MUC1, and α-LA) are promising antiviral and potential therapeutic candidates warranting further development for treating COVID-19.Multiple quantitative methods for single-case experimental design data have been applied to multiple-baseline, withdrawal, and reversal designs. The advanced data analytic techniques historically applied to single-case design data are primarily applicable to designs that involve clear sequential phases such as repeated measurement during baseline and treatment phases, but these techniques may not be valid for alternating treatment design (ATD) data where two or more treatments are rapidly alternated. Some recently proposed data analytic techniques applicable to ATD are reviewed. For ATDs with random assignment of condition ordering, the Edgington's randomization test is one type of inferential statistical technique that can complement descriptive data analytic techniques for comparing data paths and for assessing the consistency of effects across blocks in which different conditions are being compared. In addition, several recently developed graphical representations are presented, alongside the commonly used time series line graph. The quantitative and graphical data analytic techniques are illustrated with two previously published data sets. Apart from discussing the potential advantages provided by each of these data analytic techniques, barriers to applying them are reduced by disseminating open access software to quantify or graph data from ATDs.Functional analysis (FA) is an integral component of behavioral assessment and treatment given that clinicians design behavioral treatments based on FA results. Unfortunately, the interrater reliability of FA data interpretation by visual analysis can be inconsistent, potentially leading to ineffective treatment implementation. Hall et al. (2020) recently developed automated nonparametric statistical analysis (ANSA) to facilitate the interpretation of FA data and Kranak et al. (2021) subsequently extended and validated ANSA by applying it to unpublished clinical data. The results of both Hall et al. and Kranak et al. support ANSA as an emerging statistical supplement for interpreting FA data. In the present article, we show how ANSA can be applied to interpret FA data collected in clinical settings in multielement and pairwise designs. We provide a detailed overview of the calculations involved, how to use ANSA in practice, and recommendations for its implementation. A free web-based application is available at https//ansa.shinyapps.io/ansa/.
The online version contains supplementary material available at 10.1007/s40614-021-00290-2.
The online version contains supplementary material available at 10.1007/s40614-021-00290-2.This study investigated the power of two-level hierarchical linear modeling (HLM) to explain variability in intervention effectiveness between participants in context of single-case experimental design (SCED) research. HLM is a flexible technique that allows the inclusion of participant characteristics (e.g., age, gender, and disability types) as moderators, and as such supplements visual analysis findings. First, this study empirically investigated the power to estimate intervention and moderator effects using Monte Carlo simulation techniques. The results indicate that larger values for the true effects and the number of participants resulted in a higher power. The more moderators added to the model, the more participants needed to detect the effects with sufficient power (i.e., power ≥.80). When a model includes three moderators, at least 20 participants are required to capture the intervention effect and moderator effects with sufficient power. For that same condition, but only including one moderator, seven participants are sufficient. Specific recommendations for designing a SCED study with sufficient power to estimate intervention and moderator effects were provided. Second, this study introduced a newly developed user-friendly point and click Shiny tool, PowerSCED. This tool assists applied SCED researchers in designing a SCED study that has sufficient power to detect intervention and moderator effects. To end, the use of HLM with the inclusion of moderators was demonstrated using two previously published SCED studies in the journal School Psychology Quarterly.This special issue of Perspective on Behavior Science is a productive contribution to current advances in the use and documentation of single-case research designs. We focus in this article on major themes emphasized by the articles in this issue and suggest directions for improving professional standards focused on the design, analysis, and dissemination of single-case research.Due to the complex nature of single-case experimental design data, numerous effect measures are available to quantify and evaluate the effectiveness of an intervention. An inappropriate choice of the effect measure can result in a misrepresentation of the intervention effectiveness and this can have far-reaching implications for theory, practice, and policymaking. As guidelines for reporting appropriate justification for selecting an effect measure are missing, the first aim is to identify the relevant dimensions for effect measure selection and justification prior to data gathering. The second aim is to use these dimensions to construct a user-friendly flowchart or decision tree guiding applied researchers in this process. The use of the flowchart is illustrated in the context of a preregistered protocol. Adenosine 5′-diphosphate solubility dmso This is the first study that attempts to propose reporting guidelines to justify the effect measure choice, before collecting the data, to avoid selective reporting of the largest quantifications of an effect. A proper justification, less prone to confirmation bias, and transparent and explicit reporting can enhance the credibility of the single-case design study findings.The articles in this special section offer strategies to single-case experimental design (SCED) researchers to interpret their outcomes, communicate their results, and compare the results using common, quantitative results. Advancing quantitative methods applied to SCED data will facilitate communication with scientists and other professionals that do not typically interpret graphed data of the dependent variable. Horner and Ferron aptly note that innovative statistical procedures are improving the precision and credibility of SCED research as disseminate our findings to an increasingly diverse audience. This special section promotes the translation of these quantitative methods to encourage their adoption in research using single case experimental designs.Researchers report increasing trends in psychotropic medication use to treat problem behavior in individuals with intellectual and developmental disability, despite some controversy regarding its application and treatment efficacy. A substantial evidence base exists supporting behavioral intervention efficacy, however research evaluating separate and combined intervention (i.e., concurrent application of behavioral and psychopharmacological interventions) effects remains scarce. This article demonstrates how a series of analyses on clinical data collected during treatment (i.e., four case studies) may be used to retrospectively explore separate and combined intervention effects on severe problem behavior. First, we calculated individual effect sizes and corresponding confidence intervals. The results indicated larger problem behavior decreases may have coincided more often with behavioral intervention adjustments compared to medication adjustments. Second, a conditional rates analysis indicated surges in problem behavior did not reliably coincide with medication reductions. Spearman correlation analyses indicated a negative relationship between behavioral intervention phase progress and weekly episodes of problem behavior compared to a positive relationship between total medication dosage and weekly episodes of problem behavior. However, a nonparametric partial correlation analyses indicated individualized, complex relationships may exist among total medication dosage, behavioral intervention, and weekly episodes of problem behavior. We discuss potential clinical implications and encourage behavioral researchers and practitioners to consider applying creative analytic strategies to evaluate separate and combined intervention effects on problem behavior to further explore this extremely understudied topic.
The online version contains supplementary material available at 10.1007/s40614-020-00279-3.
The online version contains supplementary material available at 10.1007/s40614-020-00279-3.Access to raw data of graphs presented in original articles to calculate the effect size of single-case research is a challenge for researchers conducting studies such as meta-analysis. Researchers typically use data extraction software programs to extract raw data from the graphs in articles. In this study, we aimed to analyze the validity and reliability of the PlotDigitizer software program, which is widely used in literature and an alternative to other data extraction programs, on computers with different operating systems. We performed the digitization of 6.846 data points on three different computers using 15 hypothetical graphs with 20 data series and 186 graphs with 242 data series from 29 published articles to accomplish the goal. Besides, using the values we digitized, we recalculated the 23 effect sizes presented in the original articles for validity analysis. Based on our sampling, we calculated intercoder and intracoder Pearson correlation coefficients. The results showed that PlotDigitizer could be an alternative to other programs as it is free and can run on many current and outdated systems, and it is valid and reliable as it is nearly perfect.
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