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STEP: Stochastic Traversability Evaluation and Planning for Risk-Aware Off-road Navigation; Results from the DARPA Subterranean Challenge
No full textAlthough autonomy has gained widespread usage in structured and controlled environments, robotic autonomy in unknown and off-road terrain remains a difficult problem. Extreme, off-road, and unstructured environments such as undeveloped wilderness, caves, rubble, and other post-disaster sites pose unique and challenging problems for autonomous navigation. Based on our participation in the DARPA Subterranean Challenge, we propose an approach to improve autonomous traversal of robots in subterranean environments that are perceptually degraded and completely unknown through a traversability and planning framework called STEP (Stochastic Traversability Evaluation and Planning). We present 1) rapid uncertainty-aware mapping and traversability evaluation, 2) tail risk assessment using the Conditional Value-at-Risk (CVaR), 3) efficient risk and constraint-aware kinodynamic motion planning using sequential quadratic programming-based (SQP) model predictive control (MPC), 4) fast recovery behaviors to account for unexpected scenarios that may cause failure, and 5) risk-based gait adaptation for quadrupedal robots. We illustrate and validate extensive results from our experiments on wheeled and legged robotic platforms in field studies at the Valentine Cave, CA (cave environment), Kentucky Underground, KY (mine environment), and Louisville Mega Cavern, KY (final competition site for the DARPA Subterranean Challenge with tunnel, urban, and cave environments)
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning
No full textWe study a multi-agent reinforcement learning (MARL) problem where the agents interact over a given network. The goal of the agents is to cooperatively maximize the average of their entropy-regularized long-term rewards. To overcome the curse of dimensionality and to reduce communication, we propose a Localized Policy Iteration (LPI) algorithm that provably learns a near-globally-optimal policy using only local information. In particular, we show that, despite restricting each agent's attention to only its κ-hop neighborhood, the agents are able to learn a policy with an optimality gap that decays polynomially in κ. In addition, we show the finite-sample convergence of LPI to the global optimal policy, which explicitly captures the trade-off between optimality and computational complexity in choosing κ. Numerical simulations demonstrate the effectiveness of LPI
Dynamical states of self-organized waves in a giant single-celled organism feeding on light
No full textLiving systems often appear to act upon potential outcomes, exhibiting anticipatory behavior. Here we studyCaulerpa brachypus, a marine green alga consisting of differentiated organs resembling leaves, stems and roots. While an individual can exceed a meter in size, it is a single multinucleated giant cell. Our experimental work reveals self-organized waves of greenness — chloroplasts — that propagate throughout the alga and anticipate the day-night light cycle. Using dynamical systems analysis we show that these waves are coupled to a self-sustained oscillator, and demonstrate their entrainment to light. Under constant conditions we find that light intensity affects the natural period and can drive transition to temporal disorder. We find also that the rate of development of organs, and their shape and size, depend on light intensity and its temporal distribution. The findings suggest the waves and their environmental control as a link among biological oscillators, metabolism and morphogenesis
Maternal hormones engage a dormant monomorphic aggression circuit, leading to the introduction of an innate behavior in adulthood in females
No full textAggression - a sexually dimorphic behavior, is prevalent in males and typically absent in virgin females. Following parturition, however, the transient expression of aggression in adult females ensures the pups’ defense from predators and infanticide. While maternal hormones are known to elicit nursing, whether they play a role in the expression of maternal aggression remains unknown. Here we show that a molecularly defined subset of ventral premammillary (PMvᴰᴬᵀ) neurons, instrumental for intermale aggression, switch into a hyperexcitable state during lactation. We identify that the maternal hormones prolactin and oxytocin excite these cells, an effect mediated through T-type Ca²⁺ channels. Optogenetic manipulation or genetic ablation of PMvᴰᴬᵀ neurons profoundly affects maternal aggression, while activation of these neurons impairs the expression of non-aggression-related behaviors. This work identifies a monomorphic neural substrate that incorporates hormonal cues to enable the transient expression of a dormant behavioral program in adult females
Engineered Antiviral Sensor Targets Infected Mosquitoes
No full textEscalating vector disease burdens pose significant global health risks, so innovative tools for targeting mosquitoes are critical. We engineered an antiviral strategy termed REAPER (vRNA Expression Activates Poisonous Effector Ribonuclease) that leverages the programmable RNA-targeting capabilities of CRISPR Cas13 and its potent collateral activity. Akin to a stealthy Trojan Horse hiding in stealth awaiting the presence of its enemy, REAPER remains concealed within the mosquito until an infectious blood meal is up taken. Upon target viral RNA infection, REAPER activates, triggering programmed destruction of its target arbovirus such as chikungunya. Consequently, Cas13 mediated RNA targeting significantly reduces viral replication and its promiscuous collateral activity can even kill infected mosquitoes. This innovative REAPER technology adds to an arsenal of effective molecular genetic tools to combat mosquito virus transmission
Mutant NPM1 Hijacks Transcriptional Hubs to Maintain Pathogenic Gene Programs in Acute Myeloid Leukemia
No full textNucleophosmin (NPM1) is a ubiquitously expressed nucleolar protein with a wide range of biological functions. In 30% of acute myeloid leukemia (AML), the terminal exon of NPM1 is often found mutated, resulting in the addition of a nuclear export signal and a shift of the protein to the cytoplasm (NPM1c). AMLs carrying this mutation have aberrant expression of the HOXA/B genes, whose overexpression leads to leukemogenic transformation. Here, for the first time, we comprehensively prove that NPM1c binds to a subset of active gene promoters in NPM1c AMLs, including well-known leukemia-driving genes—HOXA/B cluster genes and MEIS1. NPM1c sustains the active transcription of key target genes by orchestrating a transcription hub and maintains the active chromatin landscape by inhibiting the activity of histone deacetylases. Together, these findings reveal the neomorphic function of NPM1c as a transcriptional amplifier for leukemic gene expression and open up new paradigms for therapeutic intervention. Significance: NPM1 mutation is the most common mutation in AML, yet the mechanism of how the mutant protein results in AML remains unclear. Here, for the first time, we prove mutant NPM1 directly binds to active chromatin regions and hijacks the transcription of AML-driving genes
DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model
No full textMotivation: Folding during transcription can have an important influence on the structure and function of RNA molecules, as regions closer to the 5' end can fold into metastable structures before potentially stronger interactions with the 3' end become available. Thermodynamic RNA folding models are not suitable to predict structures that result from cotranscriptional folding, as they can only calculate properties of the equilibrium distribution. Other software packages that simulate the kinetic process of RNA folding during transcription exist, but they are mostly applicable for short sequences.
Results: We present a new algorithm that tracks changes to the RNA secondary structure ensemble during transcription. At every transcription step, new representative local minima are identified, a neighborhood relation is defined and transition rates are estimated for kinetic simulations. After every simulation, a part of the ensemble is removed and the remainder is used to search for new representative structures. The presented algorithm is deterministic (up to numeric instabilities of simulations), fast (in comparison with existing methods), and it is capable of folding RNAs much longer than 200 nucleotides.
Availability and implementation: This software is open-source and available at https://github.com/ViennaRNA/drtransformer.
Supplementary information: Supplementary data are available at Bioinformatics online
CD4 binding site immunogens elicit heterologous anti–HIV-1 neutralizing antibodies in transgenic and wild-type animals
No full textPassive transfer of broadly neutralizing anti–HIV-1 antibodies (bNAbs) protects against infection, and therefore, eliciting bNAbs by vaccination is a major goal of HIV-1 vaccine efforts. bNAbs that target the CD4 binding site (CD4bs) on HIV-1 Env are among the most broadly active, but to date, responses elicited against this epitope in vaccinated animals have lacked potency and breadth. We hypothesized that CD4bs bNAbs resembling the antibody IOMA might be easier to elicit than other CD4bs antibodies that exhibit higher somatic mutation rates, a difficult-to-achieve mechanism to accommodate Env’s N276
gp120
N-glycan, and rare five-residue light chain complementarity-determining region 3. As an initial test of this idea, we developed IOMA germline–targeting Env immunogens and evaluated a sequential immunization regimen in transgenic mice expressing germline-reverted IOMA. These mice developed CD4bs epitope–specific responses with heterologous neutralization, and cloned antibodies overcame neutralization roadblocks, including accommodating the N276_(gp120) glycan, with some neutralizing selected HIV-1 strains more potently than IOMA. The immunization regimen also elicited CD4bs-specific responses in mice containing polyclonal antibody repertoires as well as rabbits and rhesus macaques. Thus, germline targeting of IOMA-class antibody precursors represents a potential vaccine strategy to induce CD4bs bNAbs
Photogenerated Ni(I)–Bipyridine Halide Complexes: Structure-Function Relationships for Competitive C(sp²)–Cl Oxidative Addition and Dimerization Reactivity Pathways
No full textWe report the facile photochemical generation of a library of Ni(I)–bpy halide complexes (Ni(I)(ᴿbpy)X (R = t-Bu, H, MeOOC; X = Cl, Br, I) and benchmark their relative reactivity toward competitive oxidative addition and off-cycle dimerization pathways. Structure-function relationships between ligand set and reactivity are developed, with a particular emphasis on rationalizing previously uncharacterized ligand-controlled reactivity toward high energy and challenging C(sp²)–Cl bonds. Through a dual Hammett and computational analysis, the mechanism of the formal oxidative addition is found to proceed through an SNAr-type pathway, consisting of a nucleophilic two-electron transfer between the Ni(I) 3d(z²) orbital and the C_(aryl)–Cl σ* orbital, which contrasts the mechanism previously observed for activation of weaker C(sp²)–Br/I bonds. The bpy substituent provides a strong influence on reactivity, ultimately determining whether oxidative addition or dimerization even occur. Here we elucidate the origin of this substituent influence as arising from perturbations to the effective nuclear charge (Zeff) of the Ni(I) center. Electron donation to the metal decreases Zeff, which leads to a significant destabilization of the entire 3d orbital manifold. Decreasing the 3d(z²) electron binding energies leads to a powerful two-electron donor to activate strong C(sp²)–Cl bonds. These changes also prove to have an analogous effect on dimerization, with decreases in Zeff leading to more rapid dimerization. Ligand-induced modulation of Zeff and the 3d(z²) orbital energy is thus a tunable target by which the reactivity of Ni(I) complexes can be altered, providing a direct route to stimulate reactivity with even stronger C–X bonds and potentially unveiling new ways to accomplish Ni-mediated photocatalytic cycles
Continuous Multiplexed Phage Genome Editing Using Recombitrons
No full textBacteriophages, which naturally shape bacterial communities, can be co-opted as a biological technology to help eliminate pathogenic bacteria from our bodies and food supply. Phage genome editing is a critical tool to engineer more effective phage technologies. However, editing phage genomes has traditionally been a low efficiency process that requires laborious screening, counter selection, or in vitro construction of modified genomes. These requirements impose limitations on the type and throughput of phage modifications, which in turn limit our knowledge and potential for innovation. Here, we present a scalable approach for engineering phage genomes using recombitrons: modified bacterial retrons that generate recombineering donor DNA paired with single stranded binding and annealing proteins to integrate those donors into phage genomes. This system can efficiently create genome modifications in multiple phages without the need for counterselection. Moreover, the process is continuous, with edits accumulating in the phage genome the longer the phage is cultured with the host, and multiplexable, with different editing hosts contributing distinct mutations along the genome of a phage in a mixed culture. In lambda phage, as an example, recombitrons yield single-base substitutions at up to 99% efficiency and up to 5 distinct mutations installed on a single phage genome, all without counterselection and only a few hours of hands-on time