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At least 37 records · Page 2

Analysis of Orthogonal Efflux and Permeation Properties of Compounds Leads to the Discovery of New Efflux Pump Inhibitors

Optimization of compound permeation into Gram-negative bacteria is one of the most challenging tasks in the development of antibacterial agents. Two permeability barriers–the passive diffusion barrier of the outer membrane (OM) and active drug efflux–act synergistically to protect cells from the antibacterial action of compounds. In Escherichia coli (E. coli) and relatives, these two barriers sieve compounds based on different physicochemical properties that are defined by their interactions with OM porins and efflux pumps, respectively. In this study, we critically tested the hypothesis that the best substrates and inhibitors of efflux pumps are compounds that can effectively permeate the OM and are available at relatively high concentrations in the periplasm. For this purpose, we filtered a large subset of the ZINC15 database of commercially available compounds for compounds containing a primary amine, a chemical feature known to facilitate the uptake through E. coli general porins. The assembled library was screened by ensemble docking to AcrA, the periplasmic component of the AcrAB-TolC efflux pump, followed by experimental testing of the top predicted binders for antibacterial activities, efflux recognition, and inhibition. In this work, we found that the filtered primary amine library is a rich source of compounds with efflux-inhibiting activities and identified efflux pump inhibitors with novel chemical scaffolds effective against E. coli AcrAB-TolC and efflux pumps of multidrug-resistant clinical isolates of Acinetobacter baumannii. However, primary amines are not required for the recognition of compounds by efflux pumps and their efflux-inhibitory activities.

60 APPLIED LIFE SCIENCES↗

Transcriptomic and Proteomic Insights into Host Immune Responses in Pediatric Severe Malarial Anemia: Dysregulation in HSP60-70-TLR2/4 Signaling and Altered Glutamine Metabolism

Severe malarial anemia (SMA, Hb < 6.0 g/dL) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission zones. This study explored the entire expressed human transcriptome in whole blood from 66 Kenyan children with non-SMA (Hb ≥ 6.0 g/dL, n = 41) and SMA (n = 25), focusing on host immune response networks. RNA-seq analysis revealed 6862 differentially expressed genes, with equally distributed up-and down-regulated genes, indicating a complex host immune response. Deconvolution analyses uncovered leukocytic immune profiles indicative of a diminished antigenic response, reduced immune priming, and polarization toward cellular repair in SMA. Weighted gene co-expression network analysis revealed that immune-regulated processes are central molecular distinctions between non-SMA and SMA. A top dysregulated immune response signaling network in SMA was the HSP60-HSP70-TLR2/4 signaling pathway, indicating altered pathogen recognition, innate immune activation, stress responses, and antigen recognition. Validation with high-throughput gene expression from a separate cohort of Kenyan children (n = 50) with varying severities of malarial anemia (n = 38 non-SMA and n = 12 SMA) confirmed the RNA-seq findings. Proteomic analyses in 35 children with matched transcript and protein abundance (n = 19 non-SMA and n = 16 SMA) confirmed dysregulation in the HSP60-HSP70-TLR2/4 signaling pathway. Additionally, glutamine transporter and glutamine synthetase genes were differentially expressed, indicating altered glutamine metabolism in SMA. This comprehensive analysis underscores complex immune dysregulation and novel pathogenic features in SMA.

Microbiology↗

Evaluating Automated Face Identity-Masking Methods with Human Perception and a Deep Convolutional Neural Network

Face de-identification (or “masking”) algorithms have been developed in response to the prevalent use of video recordings in public places. Here, we evaluated the success of face identity masking for human perceivers and a deep convolutional neural network (DCNN). Eight de-identification algorithms were applied to videos of drivers’ faces, while they actively operated a motor vehicle. These masks were pre-selected to be applicable to low-quality video and to maintain coarse information about facial actions. Humans studied high-resolution images to learn driver identities and were tested on their recognition of active drivers in low-resolution videos. Faces in the videos were either unmasked or were masked by one of the eight algorithms. When participants were tested immediately after learning (Experiment 1), all masks reduced identification, with six of eight masks reducing identification to extremely poor performance. In a second experiment, two of the most effective masks were tested after a delay of 7 or 28 days. The delay did not further reduce identification of the masked faces. In all masked conditions, participants maintained stringent decision criteria, with low confidence in recognition, further indicating the effectiveness of the masks. Next, the DCNN performed an identity-matching task between high-resolution images and masked videos—a task analogous to that done by humans. The pattern of accuracy for the DCNN mirrored some, but not all, aspects of human performance, highlighting the need to test the effectiveness of identity masking for both humans and machines. The DCNN was also tested on its ability to match identity between masked and unmasked versions of the same video, based only on the face. DCNN performance for the eight masks offers insight into the nature of the information in faces that is coded in these networks.

97 MATHEMATICS AND COMPUTING↗

“The structure of the Type III secretion system export gate with CdsO, an ATPase lever arm”

Type III protein secretion systems (T3SS) deliver effector proteins from the Gram-negative bacterial cytoplasm into a eukaryotic host cell through a syringe-like, multi-protein nanomachine. Cytosolic components of T3SS include a portion of the export apparatus, which traverses the inner membrane and features the opening of the secretion channel, and the sorting complex for substrate recognition and for providing the energetics required for protein secretion. Two components critical for efficient effector export are the export gate protein and the ATPase, which are proposed to be linked by the central stalk protein of the ATPase. We present the structure of the soluble export gate homo-nonamer, CdsV, in complex with the central stalk protein, CdsO, of its cognate ATPase, both derived from Chlamydia pneumoniae. This structure defines the interface between these essential T3S proteins and reveals that CdsO engages the periphery of the export gate that may allow the ATPase to catalyze an opening between export gate subunits to allow cargo to enter the export apparatus. We also demonstrate through structure-based mutagenesis of the homologous export gate in Pseudomonas aeruginosa that mutation of this interface disrupts effector secretion. These results provide novel insights into the molecular mechanisms governing active substrate recognition and translocation through a T3SS.

59 BASIC BIOLOGICAL SCIENCES↗

A majority of Rhodobacter sphaeroides promoters lack a crucial RNA polymerase recognition feature, enabling coordinated transcription activation

Using an in vitro transcription system with purified RNA polymerase (RNAP) to investigate rRNA synthesis in the photoheterotrophic α-proteobacterium Rhodobacter sphaeroides, we identified a surprising feature of promoters recognized by the major holoenzyme. Transcription from R. sphaeroides rRNA promoters was unexpectedly weak, correlating with absence of 7T, the very highly conserved thymine found at the last position in –10 elements of promoters in most bacterial species. Thymine substitutions for adenine at position –7 in the three rRNA promoters strongly increased intrinsic promoter activity, indicating that R. sphaeroides RNAP can utilize –7T when present. rRNA promoters were activated by purified R. sphaeroides CarD, a transcription factor found in many bacterial species but not in β- and γ-proteobacteria. Overall, CarD increased the activity of 15 of 16 native R. sphaeroides promoters tested in vitro that lacked –7T, whereas it had no effect on three of the four native promoters that contained –7T. Genome-wide bioinformatic analysis of promoters from R. sphaeroides and two other α-proteobacterial species indicated that 30 to 43% contained –7T, whereas 90 to 99% of promoters from non–α-proteobacteria contained –7T. Thus, promoters lacking –7T appear to be widespread in α-proteobacteria and may have evolved away from consensus to enable their coordinated regulation by transcription factors like CarD. We observed a strong reduction in R. sphaeroides CarD levels when cells enter stationary phase, suggesting that reduced activation by CarD may contribute to inhibition of rRNA transcription when cells enter stationary phase, the stage of growth when bacterial ribosome synthesis declines.

59 BASIC BIOLOGICAL SCIENCES↗

Mineral dissolution by dimeric complexes

Mineral dissolution is typically thought to occur by the detachment of monomeric building blocks of the crystal structure, although direct evidence is rare. Using in situ high-speed atomic force microscopy to examine step-edge retreat dynamics at high resolution, we report that the dissolution of gibbsite in alkaline solutions occurs mainly by the release of aluminate dimers, which subsequently dissociate into the monomeric species that dominate the solution. Here, the observed dissolution anisotropy is readily explained by this mechanism, which was further supported by density functional tight-binding simulations of detachment activation energies. Recognition that such polynuclear dissolution mechanisms exist may enable an improved understanding of processes regulating mineral dissolution rates in nature and industry.

atomic force microscopy↗

Basic Energy Sciences Program Update

This brochure describes updates to the BES program in FY 2019, including new awards, strategic planning activities, and recognition of BES Principal Investigators. It also describes select research highlights from the three divisions in BES.

14 SOLAR ENERGY↗

Automated recognition and characterization of solar active regions based on the SOHO/MDI images

The first results of a new method to identify and characterize the various surface structures on the sun, which may contribute to the changes in solar total and spectral irradiance, are shown. The full disk magnetograms (1024 x 1024 pixels) of the Michelson Doppler Imager (MDI) experiment onboard SOHO are analyzed. Use of a Bayesian inference scheme allows objective, uniform, automated processing of a long sequence of images. The main goal is to identify the solar magnetic features causing irradiance changes. The results presented are based on a pilot time interval of August 1996.

Pap, J. M.↗

What Sensing Tells Us: Towards a Formal Theory of Testing for Dynamical Systems

Just as actions can have indirect effects on the state of the world, so too can sensing actions have indirect effects on an agent's state of knowledge. In this paper, we investigate "what sensing actions tell us", i.e., what an agent comes to know indirectly from the outcome of a sensing action, given knowledge of its actions and state constraints that hold in the world. To this end, we propose a formalization of the notion of testing within a dialect of the situation calculus that includes knowledge and sensing actions. Realizing this formalization requires addressing the ramification problem for sensing actions. We formalize simple tests as sensing actions. Complex tests are expressed in the logic programming language Golog. We examine what it means to perform a test, and how the outcome of a test affects an agent's state of knowledge. Finally, we propose automated reasoning techniques for test generation and complex-test verification, under certain restrictions. The work presented in this paper is relevant to a number of application domains including diagnostic problem solving, natural language understanding, plan recognition, and active vision.

McIlraith, Sheila↗

The 3D Recognition, Generation, Fusion, Update and Refinement (RG4) Concept

This paper describes an active (real time) recognition strategy whereby information is inferred iteratively across several viewpoints in descent imagery. We will show how we use inverse theory within the context of parametric model generation, namely height and spectral reflection functions, to generate model assertions. Using this strategy in an active context implies that, from every viewpoint, the proposed system must refine its hypotheses taking into account the image and the effect of uncertainties as well. The proposed system employs probabilistic solutions to the problem of iteratively merging information (images) from several viewpoints. This involves feeding the posterior distribution from all previous images as a prior for the next view. Novel approaches will be developed to accelerate the inversion search using novel statistic implementations and reducing the model complexity using foveated vision. Foveated vision refers to imagery where the resolution varies across the image. In this paper, we allow the model to be foveated where the highest resolution region is called the foveation region. Typically, the images will have dynamic control of the location of the foveation region. For descent imagery in the Entry, Descent, and Landing (EDL) process, it is possible to have more than one foveation region. This research initiative is directed towards descent imagery in connection with NASA's EDL applications. Three-Dimensional Model Recognition, Generation, Fusion, Update, and Refinement (RGFUR or RG4) for height and the spectral reflection characteristics are in focus for various reasons, one of which is the prospect that their interpretation will provide for real time active vision for automated EDL.

Maluf, David A.↗

The Future of Arctic Fires: Leveraging Ongoing Activities, New Efforts, and International Cooperation

Fires in the Arctic region are gaining more attention and driving increased concern from the public, the scientific community, and policymakers. An increasing number of scientific projects, collaboration efforts, media coverage, and policy assessments have been and are being implemented and published regarding this emerging and important wildland fire phenomenon. In short, this increased activity comes from the recognition of increasing fire risk and activity close to, within, and impacting the Arctic. There is a need to integrate these numerous and expanding local, national, and international efforts to avoid redundant and overlapping efforts and to focus resources more efficiently. As a response, this report suggests short and long-term goals to respond to the growing fire risk and fire danger in the Arctic. All efforts call for more integrated international collaboration and greater recognition of the importance for Arctic communities to be collaborators and leaders.

Future↗

CholecTriplet2021: A benchmark challenge for surgical action triplet recognition

Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works recognize surgical activities at a coarse-grained level, such as phases, steps or events, leaving out fine-grained interaction details about the surgical activity; yet those are needed for more helpful AI assistance in the operating room. Recognizing surgical actions as triplets of ‹ instrument, verb, target › combination delivers more comprehensive details about the activities taking place in surgical videos. This paper presents CholecTriplet2021: an endoscopic vision challenge organized at MICCAI 2021 for the recognition of surgical action triplets in laparoscopic videos. Here, the challenge granted private access to the large-scale CholecT50 dataset, which is annotated with action triplet information. In this paper, we present the challenge setup and the assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge. Here, a total of 4 baseline methods from the challenge organizers and 19 new deep learning algorithms from the competing teams are presented to recognize surgical action triplets directly from surgical videos, achieving mean average precision (mAP) ranging from 4.2% to 38.1%. This study also analyzes the significance of the results obtained by the presented approaches, performs a thorough methodological comparison between them, in-depth result analysis, and proposes a novel ensemble method for enhanced recognition. Our analysis shows that surgical workflow analysis is not yet solved, and also highlights interesting directions for future research on fine-grained surgical activity recognition which is of utmost importance for the development of AI in surgery.

60 APPLIED LIFE SCIENCES↗

Land Processes Distributed Active Archive Center (LP DAAC) 25th Anniversary Recognition "A Model for Government Partnerships". LP DAAC "History and a Look Forward"

This presentation discusses 25 years of interactions between NASA and the USGS to manage a Land Processes Distributed Active Archive Center (LPDAAC) for the purpose of providing users access to NASA's rich collection of Earth Science data. The presentation addresses challenges, efforts and metrics on the performance.

Land Remote Sensing↗

EVA Task and 3D Pose Recognition from Video

Extravehicular Activity (EVA) has been known to involve potential risks of biomechanical stresses and injuries to crewmembers. Gathering of EVA motion patterns is necessary for risk analysis and mitigation. However, many existing techniques, such as motion capture systems, are not only cost-prohibitive but are impractical for retrospective analysis of past missions. In this work, a software tool was developed, which can estimate the 3D poses of a spacesuit from photographs or videos, without using special sensors or equipment. The tool is based on the state-of-the-art artificial intelligence and machine learning (AI/ML) system, which was trained by studying and capturing motion patterns of past and current spacesuit test data. The AI/ML tool was further enhanced using synthetically generated data, in which the suit postures, backgrounds, camera angles and illumination conditions were parametrically adjusted and rendered for training. The tool, incorporated the methodologies of Convolutional Neural Network (CNN), was trained, and tested in the cloud computing environment. The trained model was then applied on new imagery and video to extract estimated joint positions and suit outlines. The joint positions were further processed to capture activity (“digging”), pose labels (“bending”), and other useful downstream information. The model performance on new imagery and video was successfully assessed for accuracy and reliability. This AI/ML based posture recognition tool thus allows for the quantification of injury risk and task performance characterization for both current and past missions and training, which can immensely help to improve EVA task and suit design.

Kyung Han Kim↗

Structural basis of LAIR1 targeting by polymorphic Plasmodium RIFINs

RIFIN, a large family of Plasmodium variant surface antigens, plays a crucial role in malaria pathogenesis by mediating immune suppression through activation of inhibitory receptors such as LAIR1, and antibodies with LAIR1 inserts have been identified that bind infected erythrocytes through RIFIN. However, details of RIFIN-mediated LAIR1 recognition and receptor activation have been unclear. Here, we use negative-stain EM to define the architecture of LAIR1-inserted antibodies and determine crystal structures of RIFIN-variable 2 (V2) domain in complex with a LAIR1 domain. These structures reveal the LAIR1-binding region of RIFIN to be hydrophobic and membrane-distal, to exhibit extensive structural diversity, and to interact with RIFIN-V2 in a one-to-one fashion. Through structural and sequence analysis of various LAIR1 constructs, we identify essential elements of RIFIN-binding on LAIR1. Furthermore, a structure-derived LAIR1-binding sequence signature ascertained >20 LAIR1-binding RIFINs, including some from P. falciparum field strains and Plasmodium species infecting gorillas and chimpanzees.

59 BASIC BIOLOGICAL SCIENCES↗

A Structural and Molecular Approach for the Study Biomarkers

Investigation of the nucleation and growth of crystals in both abiotic and biotic systems is critical to seemingly diverse disciplines of geology, biology, environmental science, and astrobiology. While there are abundant studies devoted to the determination of the structure and composition of inorganic crystals, as well as to the development of thermodynamic and kinetic models, it is only recently that research efforts have been directed towards understanding mineralization in biological systems (i.e., biomineralization). Biomineralization refers to the processes by which living organisms form inorganic solids. Studies of the processes of biomineralization under low temperature aqueous conditions have focused primarily on magnetite forming bacteria and shell forming marine organisms. Many of the biological building materials consist of inorganic minerals (calcium carbonate, calcium phosphate, silica or iron oxide) intricately combined with organic polymers (like proteins). More recently, efforts have been undertaken to explore the nature of biological activities in ancient rocks. In the absence of well-preserved microorganisms or genetic material required for the polmerase chain reaction (PCR) method in molecular phylogenetic studies, using biominerals as biomarkers offers an alternative approach for the recognition of biogenic activity in both terrestrial and extraterrestrial environments. The primary driving force in biomineralization is the interaction between organic and inorganic phases. Thus, the investigation of the ultrastructure and the nature of reactions at the molecular level occurring at the interface between inorganic and organic phases is essential to understanding the processes leading to the nucleation and growth of crystals. It is recognized that crystal surfaces can serve as the substrate for the organization of organic molecules that lead to the formation of polymers and other complex organic molecules, and in discussions of the origins of life, is referred to as organic synthesis on mineral surfaces. Furthermore, it is suggested that the interaction between mineral surfaces and simple organic molecules resulted in the formation of amino acids, RNA, and perhaps other more complex molecules such as proteins. On the other hand, in natural systems, it is recognized that functional groups on cell walls or membranes of microorganisms serve as sites of nucleation and crystallization. The precise replication of biominerals with controlled structure, morphology, size and texture is not confined to higher organisms as it also occurs in primitive prokaryotic cells such as magnetotactic bacteria and cyanobacteria. This suggests that the principal strategies of biomineralization were established early on in the evolutionary history of organisms. It is critical, therefore, to search for common mechanisms within diverse biological systems. One such common factor is the capability for organization and self-assembly. Organic macromolecules such as proteins and lipids can aggregate and polymerize forming membranes or extracellular matrix. At the organic-inorganic interface, several factors such as lattice geometry, polarity, stereochemistry and topography may act in concert to control nucleation and growth of crystals. Although several models have been proposed that discuss the significance of these factors for biomineralization, no comprehensive experimental data are available. In contrast to crystallization in exclusively inorganic systems, the kinetics of reaction and structural relationships between organic and inorganic phases in biominerals or biomimetic material is poorly understood. For example, it is not clear if the concept of epitactic growth (geometrical matching of unit cells at the interface of a secondary crystal growing on a primary crystal) applies to organic-inorganic systems. In contrast to inorganic templates that often have a smooth and rigid surface that promotes epitactic growth, biological substrates are usually rough and result in a large degree of mismatch. It is apparent that factors controlling the reaction at the crystal-matrix interface are strongly dependent upon the nature of the substrate. Therefore, characterization of the assembled organic surface and surface structure of the inorganic phase is crucial to understanding the processes of biomineralization. The focus of our research is the investigation of the processes leading to the nucleation and growth of crystals on both natural and synthetic systems through an interdisciplinary approach that integrates molecular biology, morphology and mineralogy using advanced preparation and analytical techniques. We have studied run-products, particularly magnetite, siderite and other carbonates, that resulted from extracellular biomineralization by extremophiles isolated from a variety of extreme environments ranging from permafrost to hydrothermal vent systems. The results of this study are critical to recognizing biomarkers in terrestrial and extraterrestrial environments.

Thomas-Keprta, Kathie↗

Quantifying Operational Drivers of Multimodal Biometric Verification in Aerial Surveillance

Multimodal biometric verification is increasingly applied across operational contexts ranging from close-range security cameras and building-mounted surveillance to long-range ground sensors and unmanned aerial system (UAS) imagery. Variations in acquisition conditions—such as image resolution, viewing geometry, and motion artifacts—pose significant challenges for cross-domain algorithmic generalization. This study evaluates two independent multimodal biometric verification systems developed under the Intelligence Advanced Research Projects Activity (IARPA) Biometric Recognition and Identification at Altitude and Range (BRIAR) program, comparing performance on close-range and aerial datasets. Close-range video served as a baseline to quantify the decline in verification performance on aerial footage. The dataset included six UAS platforms, spanning small quadcopters at 10m altitude to medium-sized fixed-wing aircraft at 360m. Mixed-effects logistic regression identified image resolution (head and body pixel counts), head height, sensor characteristics, and algorithm selection as primary determinants of verification success, whereas demographic attributes and mission gait were not significant predictors. Activity type and collection site influenced performance in close-range data but had negligible impact on UAS imagery. These results clarify modality-specific strengths and limitations and highlight opportunities to enhance cross-domain biometric verification.

Peluso, Alina [ORNL] (ORCID:0000000328950406)↗

A minimal complex of KHNYN and zinc-finger antiviral protein binds and degrades single-stranded RNA

Detecting viral infection is a key role of the innate immune system. The genomes of some RNA viruses have a high CpG dinucleotide content relative to most vertebrate cell RNAs, making CpGs a molecular marker of infection. The human zinc-finger antiviral protein (ZAP) recognizes CpG, mediates clearance of the foreign CpG-rich RNA, and causes attenuation of CpG-rich RNA viruses. While ZAP binds RNA, it lacks enzymatic activity that might be responsible for RNA degradation and thus requires interacting cofactors for its function. One of these cofactors, KHNYN, has a predicted nuclease domain. Using biochemical approaches, we found that the KHNYN NYN domain is a single-stranded RNA ribonuclease that does not have sequence specificity and digests RNA with or without CpG dinucleotides equivalently in vitro. We show that unlike most KH domains, the KHNYN KH domain does not bind RNA. Indeed, a crystal structure of the KH region revealed a double-KH domain with a negatively charged surface that accounts for the lack of RNA binding. Rather, the KHNYN C-terminal domain (CTD) interacts with the ZAP RNA-binding domain (RBD) to provide target RNA specificity. We define a minimal complex composed of the ZAP RBD and the KHNYN NYN-CTD and use a fluorescence polarization assay to propose a model for how this complex interacts with a CpG dinucleotide-containing RNA. In the context of the cell, this module would represent the minimum ZAP and KHNYN domains required for CpG-recognition and ribonuclease activity essential for attenuation of viruses with clusters of CpG dinucleotides.

Yeoh, Zoe C. (ORCID:0000000226949068)↗