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Background Primary progressive aphasia (PPA) diagnostic criteria underestimate the complex presentation of semantic (sv) and logopenic (lv) variants, in which symptoms partially overlap, and mixed clinical presentation (mixed-PPA) and heterogenous profile (lvPPA +) are frequent. Conceptualization of similarities and differences of these clinical conditions is still scarce. Methods Lexical, semantic, phonological, and working memory errors from nine language tasks of sixty-seven PPA were analyzed using Profile Analysis based on Multidimensional Scaling, which allowed us to create a distributed representation of patients’ linguistic performance in a shared space. Patients had been studied with [ 18 F] FDG-PET. Correlations were performed between metabolic and behavioral data. Results Patients’ profiles were distributed across a continuum. All PPA, but two, presented a lexical retrieval impairment, in terms of reduced production of verbs and nouns. svPPA patients occupied a fairly clumped space along the continuum, showing a preponderant semantic deficit, which correlated to fusiform gyrus hypometabolism, while only few presented working memory deficits. Adjacently, lvPPA + presented a semantic impairment combined with phonological deficits, which correlated with metabolism in the anterior fusiform gyrus and posterior middle temporal gyrus. Starting from the shared phonological deficit side, a large portion of the space was occupied by all lvPPA, showing a combination of phonological, lexical, and working memory deficits, with the latter correlating with posterior temporo-parietal hypometabolism. Mixed PPA did not show unique profile, distributing across the space. Discussion Different clinical PPA entities exist but overlaps are frequent. Identifying shared and unique clinical markers is critical for research and clinical practice. Further research is needed to identify the role of genetic and pathological factors in such distribution, including also higher sample size of less represented groups.

Computer-based interactive items have become prevalent in recent educational assessments. In such items, detailed human–computer interactive process, known as response process, is recorded in a log file. The recorded response processes provide great opportunities to understand individuals’ problem solving processes. However, difficulties exist in analyzing these data as they are high-dimensional sequences in a nonstandard format. This paper aims at extracting useful information from response processes. In particular, we consider an exploratory analysis that extracts latent variables from process data through a multidimensional scaling framework. A dissimilarity measure is described to quantify the discrepancy between two response processes. The proposed method is applied to both simulated data and real process data from 14 PSTRE items in PIAAC 2012. A prediction procedure is used to examine the information contained in the extracted latent variables. We find that the extracted latent variables preserve a substantial amount of information in the process and have reasonable interpretability. We also empirically prove that process data contains more information than classic binary item responses in terms of out-of-sample prediction of many variables.

This paper proposes multidimensional scaling (MDS) applied to high-throughput chromosome conformation capture (Hi-C) data on genomic interactions to visualize DNA loops. Currently, the mechanisms underlying the regulation of gene expression are poorly understood, and where and when DNA loops are formed remains undetermined. Previous studies have focused on reproducing the entire three-dimensional structure of chromatin; however, identifying DNA loops using these data is time-consuming and difficult. MDS is an unsupervised method for reconstructing the original coordinates from a distance matrix. Here, MDS was applied to high-throughput chromosome conformation capture (Hi-C) data on genomic interactions to visualize DNA loops. Hi-C data were converted to distances by taking the inverse to reproduce loops via MDS, and the missing values were set to zero. Using the converted data, MDS was applied to the log-transformed genomic coordinate distances and this process successfully reproduced the DNA loops in the given structure. Consequently, the reconstructed DNA loops revealed significantly more DNA-transcription factor interactions involved in DNA loop formation than those obtained from previously applied methods. Furthermore, the reconstructed DNA loops were significantly consistent with chromatin immunoprecipitation followed by sequencing (ChIP-seq) peak positions. In conclusion, the proposed method is an improvement over previous methods for identifying DNA loops.

Interoception refers to the sensation, interpretation, and integration of internal somatic signals. Abnormalities in self-reported interoception are prevalent features of major depressive disorder (MDD) and may affect treatment outcomes. In the present study, we investigated the psychometric properties of the revised eight-dimensional and 37-item Multidimensional Assessment of Interoceptive Awareness questionnaire (the MAIA-2) in a severely depressed sample, after translating two updated scales (Not-Distracting, Not-Worrying) into German. Specifically, we examined the measure's internal consistency reliability, sensitivity to change, and minimal important differences (MID) with a focus on patient's antidepressive responses to treatment. The study enrolled 110 participants (age: M = 46.85, SD = 11.23; female: 55.45%) undergoing hospital treatment, of whom 87 were included in the pre-post analysis. Participants completed a German translation of MAIA-2 and the Beck Depression Inventory-II (pre-/post-treatment). Internal consistency reliability was determined by Cronbach's α/McDonalds's ω, sensitivity to change was determined by effect sizes, and MIDs were determined by distribution- (0.5*SD) and anchor-based approaches (mean change method; ROC curve cut-points). Depression severity reduced over the course of treatment (Median = -65.22%), and 34.48% of patients achieved remission. Reliability was appropriate for post-treatment (range of ω: .70-.90), but questionable for two pre-treatment scales (Noticing: ω = .64; Not-Distracting: ω = .66). The eight dimensions of MAIA-2 were sensitive to change (standardized response mean: .32-.81; Cohen's effect size: .30-.92). Distribution-based MIDs (.38-.61) and anchor-based mean change MIDs (remission vs. partial response: .00-.85; partial response vs. nonresponse: .08-.88) were established on the group level. For six scales, ROC cut-points (remission: .00-1.33; response: -.20-1.00) demonstrated accurate classification to treatment response groups on the individual level. This study demonstrated the applicability of the MAIA-2 questionnaire in MDD. The updated version may have led to reliability improvements regarding the revised scales, but subthreshold reliability was evident prior to treatment. The measure's dimensions were sensitive to change. MIDs were established that corresponded with antidepressive treatment outcomes. Our findings are consistent with a growing area of research which considers somatic feelings as key contributors to mental health.

To determine the optimal soil sample size for microbial community structure analysis, DNA extraction, microbial composition analysis, and diversity assessments were performed using soil sample sizes of 0.2, 1, and 5 g. This study focused on the relationship between soil amount and DNA extraction container volume and the alteration in microbial composition at different taxonomic ranks (order, class, and phylum). Horizontal (0.2 and 1 g) and vertical (5 g) shaking were applied during DNA extraction for practical use in a small laboratory. In the case of the 5 g soil sample, DNA extraction efficiency and the value of α-diversity index fluctuated severely, possibly because of vertical shaking. Regarding the 0.2 and 1 g soil samples, the number of taxa, Shannon–Wiener index, and Bray–Curtis dissimilarity were stable and had approximately the same values at each taxonomic rank. However, non-metric multidimensional scaling showed that the microbial compositions of these two sample sizes were different. The higher relative abundance of taxa in the case of the 0.2 g soil sample might indicate that cell wall compositions differentiated the microbial community structures in these two sample sizes due to high shear stress tolerance. The soil sample size and tube volume affected the estimated microbial community structure. A soil sample size of 0.2 g would be preferable to the other sample sizes because of the possible higher shearing force for DNA extraction and lower experimental costs due to smaller amounts of consumables. When the taxonomic rank was changed from order to phylum, some minor taxa identified at the order rank were integrated into major taxa at the phylum rank. The integration affected the value of the β-diversity index; therefore, the microbial community structure analysis, reproducibility of structures, diversity assessment, and detection of minor taxa would be influenced by the taxonomic rank applied.

Mimivirus is one of the most complex and largest viruses known. The origin and evolution of Mimivirus and other giant viruses have been a subject of intense study in the last two decades. The two prevailing hypotheses on the origin of Mimivirus and other viruses are the reduction hypothesis, which posits that viruses emerged from modern unicellular organisms; whereas the virus-first hypothesis proposes viruses as relics of precellular forms of life. In this study, to gain insights into the origin of Mimivirus, we have carried out extensive phylogenetic, correlation, and multidimensional scaling analyses of the putative proteins involved in the replication of its 1.2-Mb large genome. Correlation analysis and multidimensional scaling methods were validated using bacteriophage, bacteria, archaea, and eukaryotic replication proteins before applying to Mimivirus. We show that a large fraction of mimiviral replication proteins, including polymerase B, clamp, and clamp loaders are of eukaryotic origin and are coevolving. Although phylogenetic analysis places some components along the lineages of phage and bacteria, we show that all the replication-related genes have been homogenized and are under purifying selection. Collectively our analysis supports the idea that Mimivirus originated from a complex cellular ancestor. We hypothesize that Mimivirus has largely retained complex replication machinery reminiscent of its progenitor while losing most of the other genes related to processes such as metabolism and translation.

Employees’ workplace deviant behaviors have a harmful potential for organizations in many respects. Past research has indicated that individual variables may ac for personal differences in work deviance. One of the prevalent findings is that men display direct aggression more frequently than women. Yet, most of the past studies have reported results providing information on the magnitude of a general behavioral tendency of each gender, leading to rough distinctions. Unlike the previous studies, we focused on examining profiles of the role of gender in interpersonal and organizational deviance, utilizing Profile Analysis via Multidimensional Scaling that allowed us to compare specific deviance behavior indicators between males and females d in the profiles. The current exploratory study reveals that gender differences in aggressive workplace behavior are not only those apparent in inter-personal relations but also when directed towards the organization. Moreover, the reported results point to specific behavioral profiles of men and women that could not be revealed using the mean difference analyses.

Interpreting the relationship between different taste function tests of different stimuli, such as chemical and electrical stimulation, is still poorly understood. This study aims to analyze visually as well as quantitatively how to interpret the relationship of results between taste function tests using different stimuli. Patients who underwent the whole mouth test and Electrogustometry (EGM) at a tertiary medical center between August 2018 and December 2018 were reviewed retrospectively with electronic medical records. Of the 110 patients, a total of 86 adults who self-reported that their taste function was normal through a questionnaire were enrolled. EGM measured the thresholds of the chorda tympani (CT) and glossopharyngeal nerve (GL) area of the tongue. The whole mouth test measured detection and recognition thresholds for sweet, salty, bitter, sour, and umami taste. Statistical analyses of Pearson’s, Spearman’s rank and polyserial correlation and multidimensional scaling (MDS) was performed. The EGM threshold for the average value of both CT regions and the recognition threshold of the whole mouth test were significantly correlated in sweet, salty, bitter, and sour taste (r = 0.244–0.398, P  < 0.05), and the detection threshold was correlated only significant in sweet (r = 0.360, P  = 0.007). In the MDS analysis results, the three-dimensional ( D ) solution was chosen over the 2- D solution because of the lower stress. Detection-, recognition threshold of whole mouth test and EGM thresholds of CT and GL area, those were standardized by Z-score, formed well-distinguished sections in the MDS analyses. The EGM threshold of the CT area was closer to the detection and recognition thresholds than the EGM threshold of the GL area. In general, the EGM threshold was closer to the recognition threshold than the detection threshold for each taste. Overall, visualization of the relationship of whole mouth test and EGM by MDS was in good agreement with quantitative analysis. EGM and whole mouth test seem to reflect different aspects of taste. However, when interpreting the EGM results, the EGM threshold of the CT area will show more similarity to the recognition threshold than the detection threshold for the whole mouth test.

Variations and fluctuations are characteristic features of biological systems and are also manifested in cell cultures. Here, we describe a computational pipeline for identifying the range of three-dimensional (3D) cell-aggregate sizes in which nonisometric scaling emerges in the presence of joint mass and metabolic rate fluctuations. The 3D cell-laden spheroids with size and single-cell metabolic rates described by probability density functions were randomly generated in silico. The distributions of the resulting metabolic rates of the spheroids were computed by modeling oxygen diffusion and reaction. Then, a method for estimating scaling exponents of correlated variables through statistically significant data collapse of joint probability distributions was developed. The method was used to identify a physiologically relevant range of spheroid sizes, where both nonisometric scaling and a minimum oxygen concentration (0.04 mol·m−3) is maintained. The in silico pipeline described enables the prediction of the number of experiments needed for an acceptable collapse and, thus, a consistent estimate of scaling parameters. Using the pipeline, we also show that scaling exponents may be significantly different in the presence of joint mass and metabolicrate variations typically found in cells. Our study highlights the importance of incorporating fluctuations and variability in size and metabolic rates when estimating scaling exponents. It also suggests the need for taking into account their covariations for better understanding and interpreting experimental observations both in vitro and in vivo and brings insights for the design ofmore predictive and physiologically relevant in vitro models.