Hidden diversity of moss mites (Acari: Oribatida) unveiled with ecological and genetic approach

Moss mites (Acari: Oribatida) are microscopic (0.1–1 mm) soil-dwelling arachnids that function as soil decomposers. The oribatids are among the most numerous soil animals with abundances reaching up to 200,000 specimens and 50 species per one square meter of soil. Despite their ubiquitous and abundant existence, they are classified as a poorly known animal group, both in Finland and elsewhere. In this thesis I study the diversity of oribatids in a previously undocumented microhabitat, red wood ant nest mounds (of the Formica rufa group), and the special characteristics of that habitat. In addition, I study whether forest clear felling detrimentally affects the physical properties of ant nests and the oribatid fauna inhabiting those nests. Using DNA-based methods, I also investigate species richness, phylogeny, and species boundaries within the genus Phthiracarus Perty 1841. First, I compared the community composition of oribatids between ant (Formica polyctena) nest mounds and the surrounding soil. The study revealed that equally abundant fauna inhabited the two habitats, but the community composition differed; these two habitats were predominantly inhabited by different species. Second, I compared the community composition of oribatids between the parts of an ant mound. I found that, as was presumed, the oribatids predominantly inhabited the surface layer of mounds, which was also observed to host the highest moisture. This study revealed that the distribution of oribatids is moisture-related within ant mounds. These results revealed that ants and their nest mounds providing optimal conditions for decomposer fauna are important factors in maintaining oribatid diversity in the forest landscape. The next study investigated how the physical properties of ant nests (those of F. aquilonia) change due to forest clear felling by comparing mounds located in mature spruce forest and its clear fells. The study showed that the surface layer of mounds was significantly drier in clear fells than in undisturbed forest, and due to the dryness, the mounds were also relatively cooler as they lose thermal capacity on clear fells. Next, I studied whether these carry-over effects have an impact on the oribatid communities inhabiting the ant nests. The study revealed that the species richness was lower in clear fell mounds, but there were no clear changes in the total abundance or community composition of oribatids. Morphology-based identification of these minute animals is difficult due to the phenotypic variation of species. Therefore, using molecular systematic methods I investigated the species delineation of the genus Phthiracarus among nine species. Despite the challenges in obtaining DNA sequences, the DNA-based analysis (using markers COI, 28S D3, ITSS) showed that five species formed clear entities (clades), while the other four species were split into two haplotypes, indicating cryptic diversity. These results highlight that the actual species diversity may be higher than previously known. Hence, the results reveal a need to develop further the DNA-based taxonomic methods for oribatids. This thesis provides novel information about the diversity, ecology, and habitat selection of oribatid mites in a distinct habitat: wood ant nest mounds. Using systematic sampling and a species-specific approach I showed that ant mounds are central factors in maintaining the oribatid diversity in forests. Moreover, the ant mounds are inhabited by a large variety of other invertebrates, and hence these microhabitats form diversity hotspots in the forest landscape. Thus, the red wood ant colonies should be taken into consideration when making conservation decisions. The red wood ant species are still viable (to use the IUCN category) in the boreal forest of Finland, but in many other European countries they are classified as near-threatened species. Hence, conservation of these distinct habitats is of great value. Appropriate identification of organisms (taxonomy, systematics) is a cornerstone in the studies focusing on biodiversity research. For this purpose, DNA taxonomy may provide a fast and precise tool in characterizing species, especially in the case of microscopic organisms that are otherwise challenging to identify. This thesis provided the first DNA reference library for the genus Phthiracarus, revealing possible cryptic diversity, but also highlighting the need for developing new laboratory protocols for the future studies of this poorly known animal group

Anesthesia and Sedation

Anxiety control and patient comfort are integral components of everyday oral and maxillofacial surgery (OMFS) practice. Moderate sedation, deep sedation (DS), and general anesthesia (GA) have been successfully administered by and in the offices of oral and maxillofacial surgeons (OMSs) and their anesthesia teams for more than 50 years. The goal of moderate sedation, DS, or GA in the OMFS office is to establish an environment in which patients are comfortable and cooperative while allowing the surgeon to safely perform the operation. This requires meticulous care in which the practitioner balances the depth of sedation and level of responsiveness while maintaining a patent airway, proper and adequate ventilation, and optimal cardiovascular hemodynamics. The record of safety among OMSs with this form of outpatient anesthesia is exemplary. The impressive morbidity and mortality statistics support the concept that the OMFS anesthesia team model is a safe, efficient, and cost‐effective model for office‐based ambulatory surgical‐anesthesia care. Safe anesthesia practice depends on various items, including goals of anesthesia, selecting the proper patient, anesthetic technique utilized, drug regimen selection, monitoring, anesthetic team (staff and anesthesia provider) training, and the team\u27s preparedness to handle unanticipated complications and medical/anesthetic emergencies

Assessing Human Error Against a Benchmark of Perfection

An increasing number of domains are providing us with detailed trace data on human decisions in settings where we can evaluate the quality of these decisions via an algorithm. Motivated by this development, an emerging line of work has begun to consider whether we can characterize and predict the kinds of decisions where people are likely to make errors. To investigate what a general framework for human error prediction might look like, we focus on a model system with a rich history in the behavioral sciences: the decisions made by chess players as they select moves in a game. We carry out our analysis at a large scale, employing datasets with several million recorded games, and using chess tablebases to acquire a form of ground truth for a subset of chess positions that have been completely solved by computers but remain challenging even for the best players in the world. We organize our analysis around three categories of features that we argue are present in most settings where the analysis of human error is applicable: the skill of the decision-maker, the time available to make the decision, and the inherent difficulty of the decision. We identify rich structure in all three of these categories of features, and find strong evidence that in our domain, features describing the inherent difficulty of an instance are significantly more powerful than features based on skill or time.Comment: KDD 2016; 10 page

Intralake heterogeneity of thermal responses to climate change: a study of large northern hemisphere lakes

Lake surface water temperature (LSWT) measurements from various sources illustrate that lakes are warming in response to climate change. Most previous studies of geographical distributions of lake warming have tended to utilize data with limited spatial resolution of LSWTs, including single-point time series. Spatially resolved LSWT time-series are now available from satellite observations and some studies have investigated previously the intra-lake warming patterns in specific lakes (e.g., North American Great Lakes). However, across-lake comparisons of intra-lake warming differences have not yet been investigated at a large, across-continental scale, thus limiting our understanding of how intra-lake warming patterns differ more broadly. In this study, we analyze up to 20 years of satellite data from 19 lakes situated across the Northern Hemisphere, to investigate how LSWT changes vary across different lake surfaces. We find considerable intra-lake variability in warming trends across many lakes. The deepest areas of large lakes are characterized by a later onset of thermal stratification, a shorter stratified warming season and exhibit longer correlation timescales of LSWT anomalies. We show that deep areas of large lakes across the Northern Hemisphere as a result tend to display higher rates of warming of summer LSWT, arising from a greater temporal persistence in deep areas of the temperature anomalies associated with an earlier onset of thermal stratification. Utilization of single-point LSWT trends to represent changes in large lakes therefore suppresses important aspects of lake responses to climate change, whereas spatially resolved LSWT measurements can be exploited to provide more comprehensive understanding

Lateralization of face processing in the human brain

Are visual face processing mechanisms the same in the left and right cerebral hemispheres? The possibility of such ‘duplicated processing’ seems puzzling in terms of neural resource usage, and we currently lack a precise characterization of the lateral differences in face processing. To address this need, we have undertaken a three-pronged approach. Using functional magnetic resonance imaging, we assessed cortical sensitivity to facial semblance, the modulatory effects of context and temporal response dynamics. Results on all three fronts revealed systematic hemispheric differences. We found that: (i) activation patterns in the left fusiform gyrus correlate with image-level face-semblance, while those in the right correlate with categorical face/non-face judgements. (ii) Context exerts significant excitatory/inhibitory influence in the left, but has limited effect on the right. (iii) Face-selectivity persists in the right even after activity on the left has returned to baseline. These results provide important clues regarding the functional architecture of face processing, suggesting that the left hemisphere is involved in processing ‘low-level’ face semblance, and perhaps is a precursor to categorical ‘deep’ analyses on the right.John Merck FundSimons FoundationJames S. McDonnell FoundationNational Eye Institute (NIH, grant number R21-EY015521

Multiple marker mapping of quantitative trait loci of Finnish dairy cattle by regression

vo

Comparative Efficacy of Video and Text Instructional Modalities for an Oral Surgery Technique among Dental Students

Purpose: To gauge the efficacy of video media in pre-doctoral oral and maxillofacial surgery education and compare it to traditional text-based learning materials. Methods: Twenty novice dental students were randomly divided into two groups to place an Erich arch bar to the maxillary dentition of a dentoform. Group A was given a 10 minute video instruction while Group B was given 10 minutes to review written text instruction. All participants were given 45 minutes to place the arch bar on a dentoform while being recorded. This session concluded with a survey of student perceptions using the SEEQ. The students then alternated instructional modalities and again evaluated using the SEEQ. Two double-blinded clinical OMS faculty evaluated the recordings in accordance with the standards detailed in the ABPAS. Results: The difference in the post-instructional skill scores of Group A and Group B students was deemed not significant (p = 0.46). Overall, the students expressed significant preference for the video modality compared to the textual modality. The difference of the scores in each preference category between the video and text modalities were all found to be significant with p-values well below 0.05. Conclusion: Educators must remain cognizant towards the benefits of new technology and continue to explore newer, potentially more efficacious modalities such as interactive teaching materials. These benefits may be utilized to help increase student engagement and increase long-term retention of the material. It is imperative to understand the limits of each method and balance them strategically to offer comprehensive healthcare training

A Match in Time Saves Nine: Deterministic Online Matching With Delays

We consider the problem of online Min-cost Perfect Matching with Delays (MPMD) introduced by Emek et al. (STOC 2016). In this problem, an even number of requests appear in a metric space at different times and the goal of an online algorithm is to match them in pairs. In contrast to traditional online matching problems, in MPMD all requests appear online and an algorithm can match any pair of requests, but such decision may be delayed (e.g., to find a better match). The cost is the sum of matching distances and the introduced delays. We present the first deterministic online algorithm for this problem. Its competitive ratio is $O(m^{\log_2 5.5})$ $= O(m^{2.46})$, where $2 m$ is the number of requests. This is polynomial in the number of metric space points if all requests are given at different points. In particular, the bound does not depend on other parameters of the metric, such as its aspect ratio. Unlike previous (randomized) solutions for the MPMD problem, our algorithm does not need to know the metric space in advance

RepViz: A replicate-driven R tool for visualizing genomic regions

Objective: Visualization of sequencing data is an integral part of genomic data analysis. Although there are several tools to visualize sequencing data on genomic regions, they do not ofer user-friendly ways to view simultaneously diferent groups of replicates. To address this need, we developed a tool that allows efcient viewing of both intraand intergroup variation of sequencing counts on a genomic region, as well as their comparison to the output of user selected analysis methods, such as peak calling. Results: We present an R package RepViz for replicate-driven visualization of genomic regions. With ChIP-seq and ATAC-seq data we demonstrate its potential to aid visual inspection involved in the evaluation of normalization, outlier behavior, detected features from diferential peak calling analysis, and combined analysis of multiple data types. RepViz is readily available on Bioconductor (https://www.bioconductor.org/packages/devel/bioc/html/RepViz.html) and on Github (https://github.com/elolab/RepViz).</p

Dirichlet process mixture models for single-cell RNA-seq clustering

Clustering of cells based on gene expression is one of the major steps in single-cell RNA-sequencing (scRNA-seq) data analysis. One key challenge in cluster analysis is the unknown number of clusters and, for this issue, there is still no comprehensive solution. To enhance the process of defining meaningful cluster resolution, we compare Bayesian latent Dirichlet allocation (LDA) method to its non-parametric counterpart, hierarchical Dirichlet process (HDP) in the context of clustering scRNA-seq data. A potential main advantage of HDP is that it does not require the number of clusters as an input parameter from the user. While LDA has been used in single-cell data analysis, it has not been compared in detail with HDP. Here, we compare the cell clustering performance of LDA and HDP using four scRNA-seq datasets (immune cells, kidney, pancreas and decidua/placenta), with a specific focus on cluster numbers. Using both intrinsic (DB-index) and extrinsic (ARI) cluster quality measures, we show that the performance of LDA and HDP is dataset dependent. We describe a case where HDP produced a more appropriate clustering compared to the best performer from a series of LDA clusterings with different numbers of clusters. However, we also observed cases where the best performing LDA cluster numbers appropriately capture the main biological features while HDP tended to inflate the number of clusters. Overall, our study highlights the importance of carefully assessing the number of clusters when analyzing scRNA-seq data.</p