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The Caenorhabditis Intervention Testing Program (CITP) is an NIH-funded research consortium of investigators who conduct analyses at three independent sites to identify chemical interventions that reproducibly promote health and lifespan in a robust manner. The founding principle of the CITP is that compounds with positive effects across a genetically diverse panel of Caenorhabditis species and strains are likely engaging conserved biochemical pathways to exert their effects. As such, interventions that are broadly efficacious might be considered prominent compounds for translation for pre-clinical research and human clinical applications. Here, we report results generated using a recently streamlined pipeline approach for the evaluation of the effects of chemical compounds on lifespan and health. We studied five compounds previously shown to extend C. elegans lifespan or thought to promote mammalian health: 17α-estradiol, acarbose, green tea extract, nordihydroguaiaretic acid, and rapamycin. We found that green tea extract and nordihydroguaiaretic acid extend Caenorhabditis lifespan in a species-specific manner. Additionally, these two antioxidants conferred assay-specific effects in some studies—for example, decreasing survival for certain genetic backgrounds in manual survival assays in contrast with extended lifespan as assayed using automated C. elegans Lifespan Machines. We also observed that GTE and NDGA impact on older adult mobility capacity is dependent on genetic background, and that GTE reduces oxidative stress resistance in some Caenorhabditis strains. Overall, our analysis of the five compounds supports the general idea that genetic background and assay type can influence lifespan and health effects of compounds, and underscores that lifespan and health can be uncoupled by chemical interventions. [ABSTRACT FROM AUTHOR]

Alzheimer’s disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) β-amyloid (Aβ), total Tau, and phosphorylated Tau (pTau) providing the most sensitive and specific biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the complex changes in AD brain beyond amyloid (A) and Tau (T) pathologies. Here, we report a selected reaction monitoring mass spectrometry (SRM-MS) method with isotopically labeled standards for relative protein quantification in CSF. Biomarker positive (AT+) and negative (AT−) CSF pools were used as quality controls (QCs) to assess assay precision. We detected 62 peptides (51 proteins) with an average coefficient of variation (CV) of ~13% across 30 QCs and 133 controls (cognitively normal, AT−), 127 asymptomatic (cognitively normal, AT+) and 130 symptomatic AD (cognitively impaired, AT+). Proteins that could distinguish AT+ from AT− individuals included SMOC1, GDA, 14-3-3 proteins, and those involved in glycolysis. Proteins that could distinguish cognitive impairment were mainly neuronal proteins (VGF, NPTX2, NPTXR, and SCG2). This demonstrates the utility of SRM-MS to quantify CSF protein biomarkers across stages of AD. [ABSTRACT FROM AUTHOR]

Negative correlations in the sequential evolution of interspike intervals (ISIs) are a signature of memory in neuronal spike-trains. They provide coding benefits including firing-rate stabilization, improved detectability of weak sensory signals, and enhanced transmission of information by improving signal-to-noise ratio. Primary electrosensory afferent spike-trains in weakly electric fish fall into two categories based on the pattern of ISI correlations: non-bursting units have negative correlations which remain negative but decay to zero with increasing lags (Type I ISI correlations), and bursting units have oscillatory (alternating sign) correlation which damp to zero with increasing lags (Type II ISI correlations). Here, we predict and match observed ISI correlations in these afferents using a stochastic dynamic threshold model. We determine the ISI correlation function as a function of an arbitrary discrete noise correlation function R k , where k is a multiple of the mean ISI. The function permits forward and inverse calculations of the correlation function. Both types of correlation functions can be generated by adding colored noise to the spike threshold with Type I correlations generated with slow noise and Type II correlations generated with fast noise. A first-order autoregressive (AR) process with a single parameter is sufficient to predict and accurately match both types of afferent ISI correlation functions, with the type being determined by the sign of the AR parameter. The predicted and experimentally observed correlations are in geometric progression. The theory predicts that the limiting sum of ISI correlations is - 0.5 yielding a perfect DC-block in the power spectrum of the spike train. Observed ISI correlations from afferents have a limiting sum that is slightly larger at - 0.475 ± 0.04 ( mean ± s.d. ). We conclude that the underlying process for generating ISIs may be a simple combination of low-order AR and moving average processes and discuss the results from the perspective of optimal coding. [ABSTRACT FROM AUTHOR]

Rigorous comparisons of human and machine learning algorithm performance on the same task help to support accurate claims about algorithm success rates and advances understanding of their performance relative to that of human performers. In turn, these comparisons are critical for supporting advances in artificial intelligence. However, the machine learning community has lacked a standardized, consensus framework for performing the evaluations of human performance necessary for comparison. We demonstrate common pitfalls in a designing the human performance evaluation and propose a framework for the evaluation of human performance, illustrating guiding principles for a successful comparison. These principles are first, to design the human evaluation with an understanding of the differences between human and algorithm cognition; second, to match trials between human participants and the algorithm evaluation, and third, to employ best practices for psychology research studies, such as the collection and analysis of supplementary and subjective data and adhering to ethical review protocols. We demonstrate our framework's utility for designing a study to evaluate human performance on a one-shot learning task. Adoption of this common framework may provide a standard approach to evaluate algorithm performance and aid in the reproducibility of comparisons between human and machine learning algorithm performance. [ABSTRACT FROM AUTHOR]

Insect neural systems are a promising source of inspiration for new navigation algorithms, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral and neural imaging experiments as well as the mapping of detailed connectivity of neural structures. General mechanisms for learning orientation in the central complex (CX) of Drosophila have been investigated previously; however, it is unclear how these underlying mechanisms extend to cases where there is translation through an environment (beyond only rotation), which is critical for navigation in robotic systems. Here, we develop a CX neural connectivity-constrained model that performs sensor fusion, as well as unsupervised learning of visual features for path integration; we demonstrate the viability of this circuit for use in robotic systems in simulated and physical environments. Furthermore, we propose a theoretical understanding of how distributed online unsupervised network weight modification can be leveraged for learning in a trajectory through an environment by minimizing orientation estimation error. Overall, our results may enable a new class of CX-derived low power robotic navigation algorithms and lead to testable predictions to inform future neuroscience experiments. [ABSTRACT FROM AUTHOR]

Mass spectrometry (MS)-based proteomics is a powerful tool to explore pathogenic changes of a disease in an unbiased manner and has been used extensively in Alzheimer disease (AD) research. Here, by performing a meta-analysis of high-quality proteomic studies, we address which pathological changes are observed consistently and therefore most likely are of great importance for AD pathogenesis. We retrieved datasets, comprising a total of 21,588 distinct proteins identified across 857 postmortem human samples, from ten studies using labeled or label-free MS approaches. Our meta-analysis findings showed significant alterations of 757 and 1,195 proteins in AD in the labeled and label-free datasets, respectively. Only 33 proteins, some of which were associated with synaptic signaling, had the same directional change across the individual studies. However, despite alterations in individual proteins being different between the labeled and the label-free datasets, several pathways related to synaptic signaling, oxidative phosphorylation, immune response and extracellular matrix were commonly dysregulated in AD. These pathways represent robust changes in the human AD brain and warrant further investigation. [ABSTRACT FROM AUTHOR]

Recent advances in neuroscience have enabled the exploration of brain structure at the level of individual synaptic connections. These connectomics datasets continue to grow in size and complexity; methods to search for and identify interesting graph patterns offer a promising approach to quickly reduce data dimensionality and enable discovery. These graphs are often too large to be analyzed manually, presenting significant barriers to searching for structure and testing hypotheses. We combine graph database and analysis libraries with an easy-to-use neuroscience grammar suitable for rapidly constructing queries and searching for subgraphs and patterns of interest. Our approach abstracts many of the computer science and graph theory challenges associated with nanoscale brain network analysis and allows scientists to quickly conduct research at scale. We demonstrate the utility of these tools by searching for motifs on simulated data and real public connectomics datasets, and we share simple and complex structures relevant to the neuroscience community. We contextualize our findings and provide case studies and software to motivate future neuroscience exploration. [ABSTRACT FROM AUTHOR]

We examine the economic factors that lead to the formation of multilateral environmental agreements, focusing on the likelihood a pair of countries enters into an agreement as well as the number of agreements they share using a near universe of agreements. Two countries are more likely to have an agreement and have more of them if they are economically larger and of similar economic size, closer in distance, have a preferential trade agreement, and trade more. Results are strongest for agreements involving a small number of countries, consistent with a hypothesis that agreements are formed to manage common pool resources. [ABSTRACT FROM AUTHOR]

We recover the value of curb appeal in residential housing by using photos obtained from Google Street View, a deep learning classification algorithm and a variety of hedonic controls. We show that own property curb appeal is worth about twice that of an across the street neighbor. Together, neighbor and own property curb appeal together may account for up to 7% of a house's sale price. The curb appeal premium is more pronounced during times of housing market weakness and greater in neighborhoods with high average curb appeal. Results are robust to a variety of spatial controls and curb appeal specifications. [ABSTRACT FROM AUTHOR]

The goal of the Caenorhabditis Intervention Testing Program is to identify robust and reproducible pro-longevity interventions that are efficacious across genetically diverse cohorts in the Caenorhabditis genus. The project design features multiple experimental replicates collected by three different laboratories. Our initial effort employed fully manual survival assays. With an interest in increasing throughput, we explored automation with flatbed scanner-based Automated Lifespan Machines (ALMs). We used ALMs to measure survivorship of 22 Caenorhabditis strains spanning three species. Additionally, we tested five chemicals that we previously found extended lifespan in manual assays. Overall, we found similar sources of variation among trials for the ALM and our previous manual assays, verifying reproducibility of outcome. Survival assessment was generally consistent between the manual and the ALM assays, although we did observe radically contrasting results for certain compound interventions. We found that particular lifespan outcome differences could be attributed to protocol elements such as enhanced light exposure of specific compounds in the ALM, underscoring that differences in technical details can influence outcomes and therefore interpretation. Overall, we demonstrate that the ALMs effectively reproduce a large, conventionally scored dataset from a diverse test set, independently validating ALMs as a robust and reproducible approach toward aging-intervention screening. [ABSTRACT FROM AUTHOR]

The developmental pathways of broadly neutralizing antibodies (bNAbs) against HIV are of great importance for the design of immunogens that can elicit protective responses. Here we show the maturation features of the HIV-neutralizing anti-V1V2 VRC26 lineage by simultaneously sequencing the exon together with the downstream intron of VRC26 members. Using the mutational landscapes of both segments and the selection-free nature of the intron region, we identify multiple events of amino acid mutational convergence in the complementarity-determining region 3 (CDR3) of VRC26 members, and determine potential intermediates with diverse CDR3s to a late stage bNAb from 2 years prior to its isolation. Moreover, we functionally characterize the earliest neutralizing intermediates with critical CDR3 mutations, with some emerging only 14 weeks after initial lineage detection and containing only ~6% V gene mutations. Our results thus underscore the utility of analyzing exons and introns simultaneously for studying antibody maturation and repertoire selection. [ABSTRACT FROM AUTHOR]

This paper analyzes information exchange in a model of transnational pollution control in which countries use private information in independently determining their domestic environmental policies. We show that countries may not always have an incentive to exchange their private information. However, for a sufficiently high degree of predictability of domestic environmental policy processes, the expected welfare from sharing information is greater than the expected welfare from keeping it private. The minimum degree of policy predictability for which information sharing occurs increases with the level of environmental risk. Intuitively, information exchange can help mitigate the perception of global uncertainty (both political and scientific) that surrounds transnational environmental problems and potentially improve welfare if policymaking processes are sufficiently aligned with evidence-based approaches (predictable). [ABSTRACT FROM AUTHOR]

Medical imaging analysis depends on the reproducibility of complex computation. Linux containers enable the abstraction, installation, and configuration of environments so that software can be both distributed in self-contained images and used repeatably by tool consumers. While several initiatives in neuroimaging have adopted approaches for creating and sharing more reliable scientific methods and findings, Linux containers are not yet mainstream in clinical settings. We explore related technologies and their efficacy in this setting, highlight important shortcomings, demonstrate a simple use-case, and endorse the use of Linux containers for medical image analysis. [ABSTRACT FROM AUTHOR]

As a result, in the Introduction, "In some cases, when algorithm performance is compared against that of human participants, researchers make exciting claims that the ML algorithm exceeds human performance (e.g., SP 7 sp )." now reads: "In some cases, when algorithm performance is compared against that of human participants, researchers make exciting claims that the ML algorithm exceeds human performance." "For example, they may not report how many human participants were tested or the level of expertise that the human performers have in completing the task (e.g., SP 7 sp )." now reads: "For example, they may not report how many human participants were tested or the level of expertise that the human performers have in completing the task (e.g., SP 8, 9 sp ).". [Extracted from the article]

A comprehensive study of the silicon nanowire growth process has been carried out. Silicon nanowires were grown by plasma-assisted-vapor-solid method using tin as a catalyst. We have focused on the evolution of the silicon nanowire density, morphology, and crystallinity. For the first time, the initial growth stage, which determines the nanowire (NW) density and growth direction, has been observed step by step. We provide direct evidence of the merging of Sn catalyst droplets and the formation of Si nanowires during the first 10 s of growth. We found that the density of Sn droplets decreases from ~9000 Sn droplets/μm to 2000 droplets/μm after just 10 s of growth. Moreover, the long and straight nanowire density decreases from 170/μm after 2 min of growth to less than 10/μm after 90 min. This strong reduction in nanowire density is accompanied by an evolution of their morphology from cylindrical to conical, then to bend conical, and finally, to a bend inverted conical shape. Moreover, the changes in the crystalline structure of nanowires are from (i) monocrystalline to (ii) monocrystalline core/defective crystalline shell and then to (iii) monocrystalline core/defective crystalline shell/amorphous shell. The evolutions of NW properties have been explained in detail. [ABSTRACT FROM AUTHOR]

Sensory neurons code information about stimuli in their sequence of action potentials (spikes). Intuitively, the spikes should represent stimuli with high fidelity. However, generating and propagating spikes is a metabolically expensive process. It is therefore likely that neural codes have been selected to balance energy expenditure against encoding error. Our recently proposed optimal, energy-constrained neural coder (Jones et al. Frontiers in Computational Neuroscience, 9, 61 ) postulates that neurons time spikes to minimize the trade-off between stimulus reconstruction error and expended energy by adjusting the spike threshold using a simple dynamic threshold. Here, we show that this proposed coding scheme is related to existing coding schemes, such as rate and temporal codes. We derive an instantaneous rate coder and show that the spike-rate depends on the signal and its derivative. In the limit of high spike rates the spike train maximizes fidelity given an energy constraint (average spike-rate), and the predicted interspike intervals are identical to those generated by our existing optimal coding neuron. The instantaneous rate coder is shown to closely match the spike-rates recorded from P-type primary afferents in weakly electric fish. In particular, the coder is a predictor of the peristimulus time histogram (PSTH). When tested against in vitro cortical pyramidal neuron recordings, the instantaneous spike-rate approximates DC step inputs, matching both the average spike-rate and the time-to-first-spike (a simple temporal code). Overall, the instantaneous rate coder relates optimal, energy-constrained encoding to the concepts of rate-coding and temporal-coding, suggesting a possible unifying principle of neural encoding of sensory signals. [ABSTRACT FROM AUTHOR]

Syncope is a common problem in children and adolescents. Usually vasovagal in etiology, this benign problem often results in considerable testing and expense. We sought to define the current practice, practice variation, and resource utilization as well as evaluate a screening strategy for syncope at an academic tertiary care center. We reviewed the medical records of all patients age 8 to 19 years who presented with syncope between January 1994 and January 2012 and collected data regarding demographics, history, physical examination, and diagnostic tests. Practice variation was evaluated based on provider experience and subspecialty. The sensitivity and specificity of history, physical examination, and electrocardiogram (ECG) to identify a cardiac cause for syncope were calculated. Of the 617 patients studied, a cardiac cause for syncope was found in 15 (2 %). A screening strategy consisting of history, physical examination, and ECG was 100 % sensitive and 55 % specific for diagnosing a cardiac cause for syncope. Despite having a negative screen, 314 (54 %) patients had a total of 334 additional tests at an average charge of $983/patient. Although practice variation existed, it was not explained by provider experience or electrophysiology training. Factors associated with increased testing included greater number of clinic visits and increased frequency of events, whereas those associated with decreased testing included increased number of syncopal episodes and history of psychiatric medication use. A more standardized approach to syncope is needed to decrease resource use and cost while maintaining quality of care. [ABSTRACT FROM AUTHOR]

Submarine groundwater discharge (SGD) has become increasingly recognized as an important source of freshwater and nutrients to coastal waters worldwide. Although groundwater nutrients have been found to cause algal blooms in many temperate coastal waters, little is known about the biological response to these nutrients in the tropics. On the leeward coast of Hawaii Island, SGD is the dominant freshwater and nutrient source to coastal waters. Kiholo Bay, HI and Kaloko-Honokohau National Historical Park, HI are two nearshore regions with well-documented SGD with high nutrient concentrations; however, little is known about how biological processes within the surface waters respond to these inputs. This study examined how potential gross primary production (pGPP), respiration (RESP), and potential metabolism (pMET) within surface waters differed inside and outside of groundwater plumes at these two sites and between wet and dry seasons. pGPP and RESP were both significantly higher within groundwater plumes, suggesting that SGD stimulated these biological processes; however, RESP responded to a much greater extent than pGPP, resulting in heterotrophic surface waters. RESP also varied seasonally, with greater rates during the dry season compared to the wet one; pGPP did not vary seasonally. Autotrophic conditions were found within groundwater plumes at Kiholo Bay, while heterotrophic conditions were found within them at Kaloko-Honokohau and were greater during the dry season. Overall, our results show that coastal biological processes respond to SGD and that their responses vary over short spatial and temporal scales. [ABSTRACT FROM AUTHOR]

The radial junction (RJ) architecture has proven beneficial for the design of a new generation of high performance thin film photovoltaics. We herein carry out a comprehensive modeling of the light in-coupling, propagation and absorption profile within RJ thin film cells based on an accurate set of material properties extracted from spectroscopic ellipsometry measurements. This has enabled us to understand and evaluate the impact of varying several key parameters on the light harvesting in radially formed thin film solar cells. We found that the resonance mode absorption and antenna-like light in-coupling behavior in the RJ cell cavity can lead to a unique absorption distribution in the absorber that is very different from the situation expected in a planar thin film cell, and that has to be taken into account in the design of high performance RJ thin film solar cells. When compared to the experimental EQE response of real RJ solar cells, this modeling also provides an insightful and powerful tool to resolve the wavelength-dependent contributions arising from individual RJ units and/or from strong light trapping due to the presence of the RJ cell array. [ABSTRACT FROM AUTHOR]

Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-022-05798-4, published online 25 February 2022 The original version of this Article contained an error in the spelling of the author Grace M. Hwang, which was incorrectly given as Grace Hwang. These authors contributed equally: Brian S. Robinson and Raphael Norman-Tenazas. [Extracted from the article]

The article offers the authors' insight on the paper "Are bird populations in tropical and subtropical forests of South America affected by climate change?," by M. Nores that was published in a 2009 issue of "Climatic Change." The authors say that the bird data underestimates the current number of birds in South American forests. They add that the methods used are unacceptable in the field of modern ornithology and the paper lacks insight on the possible climate change effects on birds in the forests.

The trigeminal nerve responds to a variety of nociceptive stimuli, including many chemicals that activate the olfactory system at lower concentrations. However, the mechanisms by which specific odorants activate the trigeminal nerve are largely undetermined. We used an integrative approach to determine whether TRPA1 channels were the target of eight olfactory stimuli known to activate the trigeminal nerve. In a mammalian cell line stably expressing the human TRPA1 channel, we observed significant increases in intracellular calcium levels upon application of α-terpineol, amyl acetate, benzaldehyde, and toluene. Notably, these responses were greatly reduced when these chemicals were applied in conjunction with the TRPA1 inhibitor HC-030031. To determine whether TRPA1 is required for detecting these odorants as irritants in vivo, we evaluated physiological and behavioral responses to these stimuli in mice lacking the TRPA1 channel. A decline in respiration was seen in wild-type but not TRPA1 knockout mice upon exposure to α-terpineol, benzaldehyde, and toluene. Furthermore, we observed either attenuated or absent avoidance behaviors in TRPA1 knockout mice compared to wild-type mice when exposed to α-terpineol, amyl acetate, and benzaldehyde. Our results show that TRPA1 is a molecular target for four different odorants-α-terpineol, amyl acetate, benzaldehyde, and toluene. Additionally, this study suggests that TRPA1 is required for detection of α-terpineol, benzaldehyde, and toluene as trigeminal irritants. However, TRPA1 is likely only one of multiple trigeminal receptors detecting amyl acetate. [ABSTRACT FROM AUTHOR]

Immunocytokines (IC), consisting of tumor-specific monoclonal antibodies fused to the immunostimulatory cytokine interleukin 2 (IL2), exert significant antitumor effects in several murine tumor models. We investigated whether intratumoral (IT) administration of IC provided enhanced antitumor effects against subcutaneous tumors. Three unique ICs (huKS-IL2, hu14.18-IL2, and GcT84.66-IL2) were administered systemically or IT to evaluate their antitumor effects against tumors expressing the appropriate IC-targeted tumor antigens. The effect of IT injection of the primary tumor on a distant tumor was also evaluated. Here, we show that IT injection of IC resulted in enhanced antitumor effects against B16-KSA melanoma, NXS2 neuroblastoma, and human M21 melanoma xenografts when compared to intravenous (IV) IC injection. Resolution of both primary and distant subcutaneous tumors and a tumor-specific memory response were demonstrated following IT treatment in immunocompetent mice bearing NXS2 tumors. The IT effect of huKS-IL2 IC was antigen-specific, enhanced compared to IL2 alone, and dose-dependent. Hu14.18-IL2 also showed greater IT effects than IL2 alone. The antitumor effect of IT IC did not always require T cells since IT IC induced antitumor effects against tumors in both SCID and nude mice. Localization studies using radiolabeled 111In-GcT84.66-IL2 IC confirmed that IT injection resulted in a higher concentration of IC at the tumor site than IV administration. In conclusion, we suggest that IT IC is more effective than IV administration against palpable tumors. Further testing is required to determine how to potentially incorporate IT administration of IC into an antitumor regimen that optimizes local and systemic anticancer therapy. [ABSTRACT FROM AUTHOR]

In situ transmission electron microscopy is used to study dissolution of liquid single-phase Pb/Bi inclusions attached to a grain boundary in an alloy of Al99.29Pb0.65Bi0.06 at temperatures of 343, 370, and 389 °C, respectively. The initial size of the inclusions was smaller than 60 nm. Dissolution of the inclusions was observed until their complete disappearance. Digitized video recordings of the process of dissolution were used to obtain the dependence of the inclusion size with time. The kinetics of the dissolution of the grain boundary inclusions can be described with a model where it is assumed that grain-boundary diffusion of Pb and Bi is the controlling mechanism. The high value (2.3 eV) of the apparent activation enthalpy of dissolution indicates that the process is likely governed by the large negative enthalpies of solubility of Pb and Bi in Al. [ABSTRACT FROM AUTHOR]

Cu–Co–Fe alloys undercooled below a certain temperature display demixing of the liquid, followed by coagulation before dendritic solidification. In this article high temperature phase equilibria in Cu–Co–Fe samples have been precisely determined by DSC. Special attention has been paid to the liquid–liquid phase separation and on its effect on the formation of microstructures. The measured transformation temperatures have also been used to update the description of the ternary phase diagram. [ABSTRACT FROM AUTHOR]

Free-standing nanostructures such as suspended carbon nanotubes, graphene layers, III-V nanorod photonic crystals and three-dimensional structures have recently attracted attention because they could form the basis of devices with unique electronic, optoelectronic and electromechanical characteristics. Here we report the growth by molecular beam epitaxy of free-standing nanoplates of InAs that are close to being atomically plane. The structural and transport properties of these semiconducting nanoplates have been examined with scanning electron microscopy, transmission electron microscopy, X-ray diffraction and low-temperature electron transport measurements. The carrier density of the nanoplates can be reduced to zero by applying a voltage to a nearby gate electrode, creating a new type of suspended quantum well that can be used to explore low-dimensional electron transport. The electronic and optical properties of such systems also make them potentially attractive for photovoltaic and sensing applications. [ABSTRACT FROM AUTHOR]

Survivin attenuates apoptosis by inhibiting cleavage of some cell proteins by activated caspase-3. We recently discovered strong up-regulation of survivin, primarily in astrocytes and a sub-set of neurons, after traumatic brain injury (TBI) in rats. In this study we characterized co-expression of survivin with activated caspase-3 and downstream DNA fragmentation (TUNEL) in astrocytes and neurons after TBI. Western blot analysis revealed significant time-dependent increases in active caspase-3 between 5 and 14 days post-injury. No difference was observed between the proportion of survivin-positive and survivin-negative cells labeled with active caspase-3 at 5 or 7 days post-injury, as indicated by dual fluorescent immunostaining. Labeling of survivin-negative cells with TUNEL was, however, significantly greater than for survivin-positive cells, suggesting that expression of survivin may attenuate DNA cleavage and progression of apoptosis. A higher proportion of astrocytes than neurons accumulated active caspase-3. In contrast, co-localization with TUNEL was significantly higher for neurons than for astrocytes. These data suggest that survivin expression may attenuate DNA cleavage and cell death, and that this mechanism operates in a cell type-specific manner after TBI. [ABSTRACT FROM AUTHOR]

This paper considers distributed clustering of high-dimensional heterogeneous data using a distributed principal component analysis (PCA) technique called the collective PCA. It presents the collective PCA technique, which can be used independent of the clustering application. It shows a way to integrate the Collective PCA with a given off-the-shelf clustering algorithm in order to develop a distributed clustering technique. It also presents experimental results using different test data sets including an application for web mining. [ABSTRACT FROM AUTHOR]

This paper presents the design and performance analysis of a predictor-based scheduling algorithm for optical wavelength division multiplexed (WDM) networks. WDM technology provides multiple, simultaneous and independent gigabit-per-second channels on a single fiber. A reservation-based multiple access control (MAC) protocol is considered here for a local area WDM network based on the passive star topology. The MAC protocol schedules reservation requests from the network nodes on the multiple channels. In previous work, we have presented an on-line scheduling algorithm for such a network. We have shown earlier that schedule computation time can significantly affect performance and the scheduling algorithms should be simple for better performance. In this work, we further improve system performance by using a hidden Markov chain based prediction algorithm. The objective here is to reduce the amount of time spent in computing the schedule by predicting traffic requests. Performance analysis based on discrete-event simulation, varying parameters such as number of nodes and channels is presented. The results show that the error of prediction is reasonable for most cases: more than 70% of the time, the error between actual request and predicted request is less than 20%. Network throughput is higher with the proposed prediction algorithm due to pipelining of schedule computation. [ABSTRACT FROM AUTHOR]

Neural microarchitecture is heterogeneous, varying both across and within brain regions. The consistent identification of regions of interest is one of the most critical aspects in examining neurocircuitry, as these structures serve as the vital landmarks with which to map brain pathways. Access to continuous, three-dimensional volumes that span multiple brain areas not only provides richer context for identifying such landmarks, but also enables a deeper probing of the microstructures within. Here, we describe a three-dimensional X-ray microtomography imaging dataset of a well-known and validated thalamocortical sample, encompassing a range of cortical and subcortical structures from the mouse brain. In doing so, we provide the field with access to a micron-scale anatomical imaging dataset ideal for studying heterogeneity of neural structure. Measurement(s) brain measurement Technology Type(s) micro-computed tomography Factor Type(s) brain region Sample Characteristic - Organism Mus musculus Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13005527 [ABSTRACT FROM AUTHOR]

In this work, we present new results on the plasma processing and structure of hydrogenated polymorphous silicon (pm-Si:H) thin films. pm-Si:H thin films consist of a low volume fraction of silicon nanocrystals embedded in a silicon matrix with medium range order, and they possess this morphology as a significant contribution to their growth comes from the impact on the substrate of silicon clusters and nanocrystals synthesized in the plasma. Quadrupole mass spectrometry, ion flux measurements, and material characterization by transmission electron microscopy (TEM) and atomic force microscopy all provide insight on the contribution to the growth by silicon nanocrystals during PECVD deposition. In particular, cross-section TEM measurements show for the first time that the silicon nanocrystals are uniformly distributed across the thickness of the pm-Si:H film. Moreover, parametric studies indicate that the best pm-Si:H material is obtained at the conditions after the transition between a pristine plasma and one containing nanocrystals, namely a total gas pressure around 2 Torr and a silane to hydrogen ratio between 0.05 to 0.1. From a practical point of view these conditions also correspond to the highest deposition rate achievable for a given RF power and silane flow rate. [ABSTRACT FROM AUTHOR]

The ongoing evolution of Ebolaviruses poses significant challenges to the development of immunodiagnostics for detecting emergent viral variants. There is a critical need for the discovery of monoclonal antibodies with distinct affinities and specificities for different Ebolaviruses. We developed an efficient technology for the rapid discovery of a plethora of antigen-specific monoclonal antibodies from immunized animals by mining the VH:VL paired antibody repertoire encoded by highly expanded B cells in the draining popliteal lymph node (PLN). This approach requires neither screening nor selection for antigen-binding. Specifically we show that mouse immunization with Ebola VLPs gives rise to a highly polarized antibody repertoire in CD138+ antibody-secreting cells within the PLN. All highly expanded antibody clones (7/7 distinct clones/animal) were expressed recombinantly, and shown to recognize the VLPs used for immunization. Using this approach we obtained diverse panels of antibodies including: (i) antibodies with high affinity towards GP; (ii) antibodies which bound Ebola VLP Kissidougou-C15, the strain circulating in the recent West African outbreak; (iii) non-GP binding antibodies that recognize wild type Sudan or Bundibugyo viruses that have 39% and 37% sequence divergence from Ebola virus, respectively and (iv) antibodies to the Reston virus GP for which no antibodies have been reported. [ABSTRACT FROM AUTHOR]