MicroRNA profiling reveals marker of motor neuron disease in ALS models

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder marked by the loss of motor neurons (MNs) in the brain and spinal cord, leading to fatally debilitating weakness. Because this disease predominantly affects MNs, we aimed to characterize the distinct expression profile of that cell type to elucidate underlying disease mechanisms and to identify novel targets that inform on MN health during ALS disease time course. microRNAs (miRNAs) are short, noncoding RNAs that can shape the expression profile of a cell and thus often exhibit cell-type-enriched expression. To determine MN-enriched miRNA expression, we used Cre recombinase-dependent miRNA tagging and affinity purification in mice. By defining thein vivomiRNA expression of MNs, all neurons, astrocytes, and microglia, we then focused on MN-enriched miRNAs via a comparative analysis and found that they may functionally distinguish MNs postnatally from other spinal neurons. Characterizing the levels of the MN-enriched miRNAs in CSF harvested from ALS models of MN disease demonstrated that one miRNA (miR-218) tracked with MN loss and was responsive to an ALS therapy in rodent models. Therefore, we have used cellular expression profiling tools to define the distinct miRNA expression of MNs, which is likely to enrich future studies of MN disease. This approach enabled the development of a novel, drug-responsive marker of MN disease in ALS rodents.SIGNIFICANCE STATEMENTAmyotrophic lateral sclerosis (ALS) is a neurodegenerative disease in which motor neurons (MNs) in the brain and spinal cord are selectively lost. To develop tools to aid in our understanding of the distinct expression profiles of MNs and, ultimately, to monitor MN disease progression, we identified small regulatory microRNAs (miRNAs) that were highly enriched or exclusive in MNs. The signal for one of these MN-enriched miRNAs is detectable in spinal tap biofluid from an ALS rat model, where its levels change as disease progresses, suggesting that it may be a clinically useful marker of disease status. Furthermore, rats treated with ALS therapy have restored expression of this MN RNA marker, making it an MN-specific and drug-responsive marker for ALS rodents.</jats:p

Effectiveness of Denitrifying Bioreactors on Water Pollutant Reduction from Agricultural Areas

HighlightsDenitrifying woodchip bioreactors treat nitrate-N in a variety of applications and geographies.This review focuses on subsurface drainage bioreactors and bed-style designs (including in-ditch).Monitoring and reporting recommendations are provided to advance bioreactor science and engineering. Denitrifying bioreactors enhance the natural process of denitrification in a practical way to treat nitrate-nitrogen (N) in a variety of N-laden water matrices. The design and construction of bioreactors for treatment of subsurface drainage in the U.S. is guided by USDA-NRCS Conservation Practice Standard 605. This review consolidates the state of the science for denitrifying bioreactors using case studies from across the globe with an emphasis on full-size bioreactor nitrate-N removal and cost-effectiveness. The focus is on bed-style bioreactors (including in-ditch modifications), although there is mention of denitrifying walls, which broaden the applicability of bioreactor technology in some areas. Subsurface drainage denitrifying bioreactors have been assessed as removing 20% to 40% of annual nitrate-N loss in the Midwest, and an evaluation across the peer-reviewed literature published over the past three years showed that bioreactors around the world have been generally consistent with that (N load reduction median: 46%; mean ±SD: 40% ±26%; n = 15). Reported N removal rates were on the order of 5.1 g N m-3 d-1 (median; mean ±SD: 7.2 ±9.6 g N m-3 d-1; n = 27). Subsurface drainage bioreactor installation costs have ranged from less than $5,000 to$27,000, with estimated cost efficiencies ranging from less than $2.50 kg-1 N year-1 to roughly$20 kg-1 N year-1 (although they can be as high as $48 kg-1 N year-1). A suggested monitoring setup is described primarily for the context of conservation practitioners and watershed groups for assessing annual nitrate-N load removal performance of subsurface drainage denitrifying bioreactors. Recommended minimum reporting measures for assessing and comparing annual N removal performance include: bioreactor dimensions and installation date; fill media size, porosity, and type; nitrate-N concentrations and water temperatures; bioreactor flow treatment details; basic drainage system and bioreactor design characteristics; and N removal rate and efficiency

Topology of the C-Terminal Tail of HIV-1 gp41: Differential Exposure of the Kennedy Epitope on Cell and Viral Membranes

The C-terminal tail (CTT) of the HIV-1 gp41 envelope (Env) protein is increasingly recognized as an important determinant of Env structure and functional properties, including fusogenicity and antigenicity. While the CTT has been commonly referred to as the “intracytoplasmic domain” based on the assumption of an exclusive localization inside the membrane lipid bilayer, early antigenicity studies and recent biochemical analyses have produced a credible case for surface exposure of specific CTT sequences, including the classical “Kennedy epitope” (KE) of gp41, leading to an alternative model of gp41 topology with multiple membrane-spanning domains. The current study was designed to test these conflicting models of CTT topology by characterizing the exposure of native CTT sequences and substituted VSV-G epitope tags in cell- and virion-associated Env to reference monoclonal antibodies (MAbs). Surface staining and FACS analysis of intact, Env-expressing cells demonstrated that the KE is accessible to binding by MAbs directed to both an inserted VSV-G epitope tag and the native KE sequence. Importantly, the VSV-G tag was only reactive when inserted into the KE; no reactivity was observed in cells expressing Env with the VSV-G tag inserted into the LLP2 domain. In contrast to cell-surface expressed Env, no binding of KE-directed MAbs was observed to Env on the surface of intact virions using either immune precipitation or surface plasmon resonance spectroscopy. These data indicate apparently distinct CTT topologies for virion- and cell-associated Env species and add to the case for a reconsideration of CTT topology that is more complex than currently envisioned

Optics and Quantum Electronics

Contains table of contents for Section 3, reports on twenty-one research projects and a list of publications and meeting papers.Joint Services Electronics Program Contract DAAL03-92-C-0001U.S. Air Force - Office of Scientific Research Contract F49620-91-C-0091Charles S. Draper Laboratories Contract DL-H-441692MIT Lincoln LaboratoryNational Science Foundation Grant ECS 90-12787Fujitsu LaboratoriesU.S. Navy - Office of Naval Research Grant N00014-92-J-1302National Center for Integrated Photonic TechnologyNational Science Foundation Grant ECS 85-52701U.S. Navy - Office of Naval Research (MFEL) Grant N00014-91-C-0084U.S. Navy - Office of Naval Research (MFEL) Grant N00014-91-J-1956National Institutes of Health Grant R01-GM35459-08U.S. Air Force - Office of Scientific Research Grant F49620-93-1-0301MIT Lincoln Laboratory Contract BX-5098Electric Power Research Institute Contract RP3170-2

Optics and Quantum Electronics

Contains table of contents for Section 3 and reports on twenty research projects.Charles S. Draper Laboratories Contract DL-H-467138Joint Services Electronics Program Contract DAAL03-92-C-0001Joint Services Electronics Program Grant DAAH04-95-1-0038U.S. Air Force - Office of Scientific Research Contract F49620-91-C-0091MIT Lincoln LaboratoryNational Science Foundation Grant ECS 90-12787Fujitsu LaboratoriesNational Center for Integrated PhotonicsHoneywell Technology CenterU.S. Navy - Office of Naval Research (MFEL) Contract N00014-94-1-0717U.S. Navy - Office of Naval Research (MFEL) Grant N00014-91-J-1956National Institutes of Health Grant NIH-5-R01-GM35459-09U.S. Air Force - Office of Scientific Research Grant F49620-93-1-0301MIT Lincoln Laboratory Contract BX-5098Electric Power Research Institute Contract RP3170-25ENEC

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

Cognitive Decision Theory: Developing Models of Real-World Decision Behavior

For 300 years, the areas of economics, statistics, and probability theory, have held the decision sciences captive with the likes of Bernoulli, Laplace, Von Neumann, Savage and others, developing normative or rational models of decision making. A weakness of this approach, however, is that it disregards the cognitive capabilities of the agent and only considers the environment in which behavior takes place. In contrast, cognitive scientists have often failed to recognize that the processes they&apos;re trying to model take place in an uncertain world involving serious consequences. Thus, cognition in the real world needs to confront decisionmaking topics. In this symposium, we survey several recent examples of the emerging field we call Cognitive Decision Theory -a branch of decision theory in which models of judgment and decision making are built from principles of cognition rather than axioms of rationality. As the talks in the symposium illustrate, the application of cognitive models to understanding judgment and decision making addresses the weaknesses of both cognitive and decision science. On the one hand, models of decision making become more plausible with the realization that the cognitive system places constraints on the types of processes (or heuristics) that are assumed to guide actual decision behavior. On the other hand, models of cognition are challenged to reconceptualize how their laboratory-derivations can be scaled up to account for cognition in the real world. Diagnostic Hypothesis Generation &amp; Human Judgment Michael Dougherty* &amp; Rick Thomas Inductive inference is a fundamental component of everyday reasoning, both by lay people and by professionals. Indeed, hypothesis generation processes occur in any task that involves taking &quot;data&quot; and formulating possible explanations of that data, including clinicians&apos; generation of diagnoses on the basis of symptoms (e.g., The Adaptive Decision Maker: Selecting Strategies According to the Environment Jörg Rieskamp How do people make probabilistic inferences, such as inferring which of two patients needs more urgent treatment? Bayesian models have been proposed as normative benchmarks for such tasks. However, it has been demonstrated that for many real-world inference tasks, simple heuristics can perform astonishingly well and sometimes even outperform Bayesian models. If people behave adaptively, it can be predicted that they will select simple heuristics in environments where the heuristics outperform cognitively more demanding strategies. To describe the adaptive process of strategy selection, a computational model will be proposed that specifies how people select strategies. The strategy selection learning theory predicts a strategy selection process on the basis of reinforcement learning. The theory was supported in several experimental studies and makes better predictions than alternative accounts. 3