Rapid unleashing of macrophage efferocytic capacity via transcriptional pause release.

During development, inflammation or tissue injury, macrophages may successively engulf and process multiple apoptotic corpses via efferocytosis to achieve tissue homeostasis1. How macrophages may rapidly adapt their transcription to achieve continuous corpse uptake is incompletely understood. Transcriptional pause/release is an evolutionarily conserved mechanism, in which RNA polymerase (Pol) II initiates transcription for 20-60 nucleotides, is paused for minutes to hours and is then released to make full-length mRNA2. Here we show that macrophages, within minutes of corpse encounter, use transcriptional pause/release to unleash a rapid transcriptional response. For human and mouse macrophages, the Pol II pause/release was required for continuous efferocytosis in vitro and in vivo. Interestingly, blocking Pol II pause/release did not impede Fc receptor-mediated phagocytosis, yeast uptake or bacterial phagocytosis. Integration of data from three genomic approaches-precision nuclear run-on sequencing, RNA sequencing, and assay for transposase-accessible chromatin using sequencing (ATAC-seq)-on efferocytic macrophages at different time points revealed that Pol II pause/release controls expression of select transcription factors and downstream target genes. Mechanistic studies on transcription factor EGR3, prominently regulated by pause/release, uncovered EGR3-related reprogramming of other macrophage genes involved in cytoskeleton and corpse processing. Using lysosomal probes and a new genetic fluorescent reporter, we identify a role for pause/release in phagosome acidification during efferocytosis. Furthermore, microglia from egr3-deficient zebrafish embryos displayed reduced phagocytosis of apoptotic neurons and fewer maturing phagosomes, supporting defective corpse processing. Collectively, these data indicate that macrophages use Pol II pause/release as a mechanism to rapidly alter their transcriptional programs for efficient processing of the ingested apoptotic corpses and for successive efferocytosis.

CD22 blockade restores homeostatic microglial phagocytosis in ageing brains.

Microglia maintain homeostasis in the central nervous system through phagocytic clearance of protein aggregates and cellular debris. This function deteriorates during ageing and neurodegenerative disease, concomitant with cognitive decline. However, the mechanisms of impaired microglial homeostatic function and the cognitive effects of restoring this function remain unknown. We combined CRISPR-Cas9 knockout screens with RNA sequencing analysis to discover age-related genetic modifiers of microglial phagocytosis. These screens identified CD22, a canonical B cell receptor, as a negative regulator of phagocytosis that is upregulated on aged microglia. CD22 mediates the anti-phagocytic effect of α2,6-linked sialic acid, and inhibition of CD22 promotes the clearance of myelin debris, amyloid-ß oligomers and α-synuclein fibrils in vivo. Long-term central nervous system delivery of an antibody that blocks CD22 function reprograms microglia towards a homeostatic transcriptional state and improves cognitive function in aged mice. These findings elucidate a mechanism of age-related microglial impairment and a strategy to restore homeostasis in the ageing brain.

Temporal learning analytics to explore traces of self-regulated learning behaviors and their associations with learning performance, cognitive load, and student engagement in an asynchronous online course.

Self-regulated learning (SRL) plays a critical role in asynchronous online courses. In recent years, attention has been focused on identifying student subgroups with different patterns of online SRL behaviors and comparing their learning performance. However, there is limited research leveraging traces of SRL behaviors to detect student subgroups and examine the subgroup differences in cognitive load and student engagement. The current study tracked the engagement of 101 graduate students with SRL-enabling tools integrated into an asynchronous online course. According to the recorded SRL behaviors, this study identified two distinct student subgroups, using sequence analysis and cluster analysis: high SRL (H-SRL) and low SRL (L-SRL) groups. The H-SRL group showed lower extraneous cognitive load and higher learning performance, germane cognitive load, and cognitive engagement than the L-SRL group did. Additionally, this study articulated and compared temporal patterns of online SRL behaviors between the student subgroups combining lag sequential analysis and epistemic network analysis. The results revealed that both groups followed three phases of self-regulation but performed off-task behaviors. Additionally, the H-SRL group preferred activating mastery learning goals to improve ethical knowledge, whereas the L-SRL group preferred choosing performance-avoidance learning goals to pass the unit tests. The H-SRL group invested more in time management and notetaking, whereas the L-SRL group engaged more in surface learning approaches. This study offers researchers both theoretical and methodological insights. Additionally, our research findings help inform practitioners about how to design and deploy personalized SRL interventions in asynchronous online courses.

Cerebrospinal fluid regulates skull bone marrow niches via direct access through dural channels.

It remains unclear how immune cells from skull bone marrow niches are recruited to the meninges. Here we report that cerebrospinal fluid (CSF) accesses skull bone marrow via dura-skull channels, and CSF proteins signal onto diverse cell types within the niches. After spinal cord injury, CSF-borne cues promote myelopoiesis and egress of myeloid cells into meninges. This reveals a mechanism of CNS-to-bone-marrow communication via CSF that regulates CNS immune responses.

The CD22-IGF2R interaction is a therapeutic target for microglial lysosome dysfunction in Niemann-Pick type C.

Lysosome dysfunction is a shared feature of rare lysosomal storage diseases and common age-related neurodegenerative diseases. Microglia, the brain-resident macrophages, are particularly vulnerable to lysosome dysfunction because of the phagocytic stress of clearing dying neurons, myelin, and debris. CD22 is a negative regulator of microglial homeostasis in the aging mouse brain, and soluble CD22 (sCD22) is increased in the cerebrospinal fluid of patients with Niemann-Pick type C disease (NPC). However, the role of CD22 in the human brain remains unknown. In contrast to previous findings in mice, here, we show that CD22 is expressed by oligodendrocytes in the human brain and binds to sialic acid­dependent ligands on microglia. Using unbiased genetic and proteomic screens, we identify insulin-like growth factor 2 receptor (IGF2R) as the binding partner of sCD22 on human myeloid cells. Targeted truncation of IGF2R revealed that sCD22 docks near critical mannose 6-phosphate­binding domains, where it disrupts lysosomal protein trafficking. Interfering with the sCD22-IGF2R interaction using CD22 blocking antibodies ameliorated lysosome dysfunction in human NPC1 mutant induced pluripotent stem cell­derived microglia-like cells without harming oligodendrocytes in vitro. These findings reinforce the differences between mouse and human microglia and provide a candidate microglia-directed immunotherapeutic to treat NPC.

Ontology-based structured cosine similarity in document summarization: with applications to mobile audio-based knowledge management.

Development of algorithms for automated text categorization in massive text document sets is an important research area of data mining and knowledge discovery. Most of the text-clustering methods were grounded in the term-based measurement of distance or similarity, ignoring the structure of the documents. In this paper, we present a novel method named structured cosine similarity (SCS) that furnishes document clustering with a new way of modeling on document summarization, considering the structure of the documents so as to improve the performance of document clustering in terms of quality, stability, and efficiency. This study was motivated by the problem of clustering speech documents (of no rich document features) attained from the wireless experience oral sharing conducted by mobile workforce of enterprises, fulfilling audio-based knowledge management. In other words, this problem aims to facilitate knowledge acquisition and sharing by speech. The evaluations also show fairly promising results on our method of structured cosine similarity.

GPS sensor-based mobile learning for English: an exploratory study on self-efficacy, self-regulation and student achievement.

This study investigated the effects of self-efficacy and self-regulation on student achievement in a context-aware learning environment. Particularly, an innovative global positioning system (GPS) sensor-based mobile learning system was used to facilitate English learning of different plants on campus. A total of 41 university students participated in the study, divided into high and low groups of self-efficacy and self-regulation. The findings showed that both self-regulation and self-efficacy were significant predictors of learning achievement in the mobile context-aware learning (MCL) context. Moreover, while the GPS-based MCL learning session had positive effects on learning achievement, no significant increase in self-regulation or self-efficacy was found in either the high or the low group, supposedly due to the short duration of the activity. The participants found the system easy to use and useful, but they also raised critical concerns that can inform future improvements. We hope this exploratory study can serve as a starting point from which more interactive, user-friendly GPS sensor-based learning systems will be generated and more areas of application will be further explored to foster self-regulated, self-motivated ubiquitous learning of mobile learners.

Phylogenetic networks: modeling, reconstructibility, and accuracy.

Phylogenetic networks model the evolutionary history of sets of organisms when events such as hybrid speciation and horizontal gene transfer occur. In spite of their widely acknowledged importance in evolutionary biology, phylogenetic networks have so far been studied mostly for specific data sets. We present a general definition of phylogenetic networks in terms of directed acyclic graphs (DAGs) and a set of conditions. Further, we distinguish between model networks and reconstructible ones and characterize the effect of extinction and taxon sampling on the reconstructibility of the network. Simulation studies are a standard technique for assessing the performance of phylogenetic methods. A main step in such studies entails quantifying the topological error between the model and inferred phylogenies. While many measures of tree topological accuracy have been proposed, none exist for phylogenetic networks. Previously, we proposed the first such measure, which applied only to a restricted class of networks. In this paper, we extend that measure to apply to all networks, and prove that it is a metric on the space of phylogenetic networks. Our results allow for the systematic study of existing network methods, and for the design of new accurate ones.

Online teaching tool simplifies faculty use of multimedia and improves student interest and knowledge in science.

Digital technologies can improve student interest and knowledge in science. However, researching the vast number of websites devoted to science education and integrating them into undergraduate curricula is time-consuming. We developed an Adobe ColdFusion- and Adobe Flash-based system for simplifying the construction, use, and delivery of electronic educational materials in science. The Online Multimedia Teaching Tool (OMTT) in Neuroscience was constructed from a ColdFusion-based online interface, which reduced the need for programming skills and the time for curriculum development. The OMTT in Neuroscience was used by faculty to enhance their lectures in existing curricula. Students had unlimited online access to encourage user-centered exploration. We found the OMTT was rapidly adapted by multiple professors, and its use by undergraduate students was consistent with the interpretation that the OMTT improved performance on exams and increased interest in the field of neuroscience.

The accuracy of fast phylogenetic methods for large datasets.

Whole-genome phylogenetic studies require various sources of phylogenetic signals to produce an accurate picture of the evolutionary history of a group of genomes. In particular, sequence-based reconstruction will play an important role, especially in resolving more recent events. But using sequences at the level of whole genomes means working with very large amounts of data--large numbers of sequences--as well as large phylogenetic distances, so that reconstruction methods must be both fast and robust as well as accurate. We study the accuracy, convergence rate, and speed of several fast reconstruction methods: neighbor-joining, Weighbor (a weighted version of neighbor-joining), greedy parsimony, and a new phylogenetic reconstruction method based on disk-covering and parsimony search (DCM-NJ + MP). Our study uses extensive simulations based on random birth-death trees, with controlled deviations from ultrametricity. We find that Weighbor, thanks to its sophisticated handling of probabilities, outperforms other methods for short sequences, while our new method is the best choice for sequence lengths above 100. For very large sequence lengths, all four methods have similar accuracy, so that the speed of neighbor-joining and greedy parsimony makes them the two methods of choice.

Towards the development of computational tools for evaluating phylogenetic network reconstruction methods.

We report on a suite of algorithms and techniques that together provide a simulation flow for studying the topological accuracy of methods for reconstructing phylogenetic networks. We implemented those algorithms and techniques and used three phylogenetic reconstruction methods for a case study of our tools. We present the results of our experimental studies in analyzing the relative performance of these methods. Our results indicate that our simulator and our proposed measure of accuracy, the latter an extension of the widely used Robinson-Foulds measure, offer a robust platform for the evaluation of network reconstruction algorithms.

Novel synthetic polyamines are effective in the treatment of experimental microsporidiosis, an opportunistic AIDS-associated infection.

Microsporidia are eukaryotic obligate intracellular protists that are emerging pathogens in immunocompromised hosts, such as patients with AIDS or patients who have undergone organ transplantation. We have demonstrated in vitro and in vivo that synthetic polyamine analogs are effective antimicrosporidial agents with a broad therapeutic window. CD8-knockout mice or nude mice infected with the microsporidian Encephalitozoon cuniculi were cured when they were treated with four different novel polyamine analogs at doses ranging from 1.25 to 5 mg/kg of body weight/day for a total of 10 days. Cured animals demonstrated no evidence of parasitemia by either PCR or histologic staining of tissues 30 days after untreated control animals died.