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Frustrated mixed-spin ladders: Evidence for a bond-order wave phase between rung-singlet and Haldane phases
No full textIn frustrated spin ladders, the interplay of frustration and correlations leads to the familiar Haldane (H) and rung-singlet (RS) phases. The nature of the transition between these two phases is still under debate. In this paper we tackle this issue using tools of quantum information theory. We consider frustrated mixed-spin-(1, 1/2) ladders with antiferromagnetic leg, rung and diagonal couplings, and calculate various quantities, such as the entanglement entropy (EE), the Schmidt gap, and the level degeneracy of the entanglement spectrum (ES). We use two numerical techniques, the infinite time-evolving block decimation (iTEBD) and the density matrix renormalization group (DMRG). We demonstrate that there exists an intermediate phase in which the ES levels do not exhibit the characteristic degeneracies of the H and RS phases. To understand the underlying physics in this phase, we investigate short-range spin correlations along legs, rungs and diagonals and show that in this intermediate phase long-wavelength modulations occur, akin to bond-order waves
Machine Learning Accelerated PDE Backstepping Observers
No full textState estimation is important for a variety of tasks, from forecasting to substituting for unmeasured states in feedback controllers. Performing real-time state estimation for PDEs using provably and rapidly converging observers, such as those based on PDE backstepping, is computationally expensive and in many cases prohibitive. We propose a framework for accelerating PDE observer computations using learning-based approaches that are much faster while maintaining accuracy. In particular, we employ the recently-developed Fourier Neural Operator (FNO) to learn the functional mapping from the initial observer state and boundary measurements to the state estimate. By employing backstepping observer gains for previously-designed observers with particular convergence rate guarantees, we provide numerical experiments that evaluate the increased computational efficiency gained with FNO. We consider the state estimation for three benchmark PDE examples motivated by applications: first, for a reaction-diffusion (parabolic) PDE whose state is estimated with an exponential rate of convergence; second, for a parabolic PDE with exact prescribed-time estimation;and, third, for a pair of coupled first-order hyperbolic PDEs that modeling traffic flow density and velocity. The ML-accelerated observers trained on simulation data sets for these PDEs achieves up to three orders of magnitude improvement in computational speed compared to classical methods. This demonstrates the attractiveness of the ML-accelerated observers for real-time state estimation and control
Chasing Convex Bodies and Functions with Black-Box Advice
No full textWe consider the problem of convex function chasing with black-box advice, where an online decision-maker aims to minimize the total cost of making and switching between decisions in a normed vector space, aided by black-box advice such as the decisions of a machine-learned algorithm. The decision-maker seeks cost comparable to the advice when it performs well, known as consistency, while also ensuring worst-case robustness even when the advice is adversarial. We first consider the common paradigm of algorithms that switch between the decisions of the advice and a competitive algorithm, showing that no algorithm in this class can improve upon 3-consistency while staying robust. We then propose two novel algorithms that bypass this limitation by exploiting the problem's convexity. The first, INTERP, achieves (√2̅ + ϵ)-consistency and 2̅(C/ϵ²)-robustness for any ϵ > 0, where C is the competitive ratio of an algorithm for convex function chasing or a subclass thereof. The second, BDINTERP, achieves (1 + ϵ)-consistency and O(CD/ϵ)-robustness when the problem has bounded diameter D. Further, we show that BDINTERP achieves near-optimal consistency-robustness trade-off for the special case where cost functions are α-polyhedral
Physiological adaptation of sulfate reducing bacteria in syntrophic partnership with anaerobic methanotrophic archaea
No full textSulfate-coupled anaerobic oxidation of methane (AOM) is performed by multicellular consortia of anaerobic methanotrophic archaea (ANME) in obligate syntrophic partnership with sulfate-reducing bacteria (SRB). Diverse ANME and SRB clades co-associate but the physiological basis for their adaptation and diversification is not well understood. In this work, we explore the metabolic adaptation of four syntrophic SRB clades (HotSeep-1, Seep-SRB2, Seep-SRB1a and Seep-SRB1g) from a phylogenomics perspective, tracing the evolution of conserved proteins in the syntrophic SRB clades, and comparing the genomes of syntrophic SRB to their nearest evolutionary neighbors in the phylum Desulfobacterota. We note several examples of gain, loss or biochemical adaptation of proteins within pathways involved in extracellular electron transfer, electron transport chain, nutrient sharing, biofilm formation and cell adhesion. We demonstrate that the metabolic adaptations in each of these syntrophic clades are unique, suggesting that they have independently evolved, converging to a syntrophic partnership with ANME. Within the clades we also investigated the specialization of different syntrophic SRB species to partnerships with different ANME clades, using metagenomic sequences obtained from ANME and SRB partners in individual consortia after fluorescent-sorting of cell aggregates from anaerobic sediments. In one instance of metabolic adaptation to different partnerships, we show that Seep-SRB1a partners of ANME-2c appear to lack nutritional auxotrophies, while the related Seep-SRB1a partners of a different methanotrophic archaeal lineage, ANME-2a, are missing the cobalamin synthesis pathway, suggesting that the Seep-SRB1a partners of ANME-2a may have a nutritional dependence on its partner. Together, our paired genomic analysis of AOM consortia highlights the specific adaptation and diversification of syntrophic SRB clades linked to their associated ANME lineages
Runx factors launch T-cell and innate lymphoid programs via direct and gene network-based mechanisms
No full textRunx factors are essential for lineage specification of various hematopoietic cells, including T lymphocytes. However, they regulate context-specific genes and occupy distinct genomic regions in different cell types. Here, we show that dynamic Runx binding shifts in early T-cell development are mostly not restricted by local chromatin state but regulated by Runx dosage and functional partners. Runx co-factors compete to recruit a limited pool of Runx factors in early T-progenitors, and a modest increase in Runx protein availability at pre-commitment stages causes premature Runx occupancy at post-commitment binding sites. This results in striking T-lineage developmental acceleration by selectively activating T-identity and innate lymphoid cell programs. These are collectively regulated by Runx together with other, Runx-induced transcription factors that co-occupy Runx target genes and propagate gene network changes
Hormone-induced enhancer assembly requires an optimal level of hormone receptor multivalent interactions
No full textTranscription factors (TFs) activate enhancers to drive cell-specific gene programs in response to signals, but our understanding of enhancer assembly during signaling events is incomplete. Here, we show that Androgen Receptor (AR), a steroid hormone-regulated transcription factor, forms condensates through multivalent interactions in response to androgen signaling to orchestrate enhancer assembly. We demonstrate that the intrinsically disordered N-terminal domain (NTD) of AR drives 1,6-Hexanediol-sensitive condensate formation and that NTD deletion or aromatic residue mutation reduces AR self-association and abolishes AR transcriptional activity. AR NTD can be substituted by intrinsically disordered regions (IDRs) from selective proteins for AR condensation capacity and transactivation function. Surprisingly, strengthened AR condensation capacity caused by extending the polyQ tract within AR NTD also leads to impaired transcriptional activity without affecting AR binding on enhancers. Furthermore, either NTD deletion or polyQ extension reduces heterotypic multivalent interactions between AR and other enhancer components. These results suggest the importance of an optimal level of AR condensation in mediating AR-AR homotypic and AR-cofactor heterotypic interactions to regulate enhancer assembly in response to signals. Our study supports the notion that alteration of the fine-tuned multivalent IDR-IDR interactions might underlie AR-related human pathologies, thereby providing novel molecular insights for potential therapeutic strategies to treat prostate cancer and other AR-involved diseases by targeting AR multivalent interactions
CRISPR Mediated Transactivation in the Human Disease Vector Aedes aegypti
No full textAs a major insect vector of multiple arboviruses, Aedes aegypti poses a significant global health and economic burden. A number of genetic engineering tools have been exploited to understand its biology with the goal of reducing its impact. For example, current tools have focused on knocking-down RNA transcripts, inducing loss-of-function mutations or expressing exogenous DNA. However, methods for transactivating endogenous genes have not been developed. To fill this void, here we developed a CRISPR activation (CRISPRa) system in Ae. aegypti to transactivate target gene expression. Gene expression is activated through pairing a catalytically-inactive (‘dead’) Cas9 (dCas9) with a highly-active tripartite activator, VP64-p65-Rta (VPR) and synthetic guide RNA (sgRNA) complementary to a user defined target-gene promoter region. As a proof of concept, we demonstrate that engineered Ae. aegypti mosquitoes harboring a binary CRISPRa system can be used to effectively overexpress two developmental genes, even-skipped (eve) and hedgehog (hh), resulting in observable morphological phenotypes. We also used this system to overexpress the positive transcriptional regulator of the Toll immune pathway known as AaRel1, which resulted in a significant suppression of dengue virus serotype 2 (DENV2). This system provides a versatile tool for research pathways not previously possible in Ae. aegypti, such as programmed overexpression of endogenous genes, and may lead to the development of innovative vector control tools
A confinable female-lethal population suppression system in the malaria vector, Anopheles gambiae
No full textMalaria is among the world’s deadliest diseases, predominantly affecting sub-Saharan Africa, and killing over half a million people annually. Controlling the principal vector, the mosquito Anopheles gambiae, as well as other anophelines, is among the most effective methods to control disease spread. Here we develop an innovative genetic population suppression system termed Ifegenia (Inherited Female Elimination by Genetically Encoded Nucleases to Interrupt Alleles) in this deadly vector. In this bicomponent CRISPR-based approach, we disrupt a female-essential gene, femaleless (fle), demonstrating complete genetic sexing via heritable daughter gynecide. Moreover, we show that Ifegenia males remain reproductively viable, and can load both fle mutations and CRISPR machinery to induce fle mutations in subsequent generations, resulting in sustained population suppression. Through modeling, we demonstrate that iterative releases of non-biting Ifegenia males can act as an effective, confinable, controllable, and safe population suppression and elimination system
Timeline of changes in spike conformational dynamics in emergent SARS-CoV-2 variants reveal progressive stabilization of trimer stalk and enhanced NTD dynamics
No full textSARS-CoV-2 emergent variants are characterized by increased transmissibility and each show multiple mutations predominantly localized to the spike (S) protein. Here, amide hydrogen/deuterium exchange mass spectrometry has been applied to track correlative changes in S dynamics from multiple SARS-CoV-2 variants. Our results highlight large differences across variants at two loci with impacts on S dynamics and stability. A significant enhancement in stabilization first occurred with the emergence of D614G S followed by smaller, progressive stabilization in Omicron BA.1 S traced through Alpha S and Delta S variants. Stabilization preceded progressive enhancement in dynamics in the N-terminal domain, wherein Omicron BA.1 S showed the largest magnitude increases relative to other preceding variants. Changes in stabilization and dynamics resulting from specific S mutations detail the evolutionary trajectory of S protein in emerging variants. These carry major implications for SARS-CoV-2 viral fitness and offer new insights into variant-specific therapeutic development
Multi-channel intra-cortical micro-stimulation yields quick reaction times and evokes natural somatosensations in a human participant
No full textSomatosensory brain-machine-interfaces (BMIs) can create naturalistic sensations by modulating activity of neural populations in the brain. By utilizing different spatial or temporal patterns of intra-cortical micro-stimulation (ICMS) in primary sensory cortex (S1), human patients suffering somatosensory loss can experience both cutaneous and proprioceptive sensory feedback. As evidenced by motor deficits in deafferented patients, rapid somatosensory feedback is critical for dexterous motor ability, in part because visual feedback is much slower than naturally occurring somatosensory input. However, somatosensory BMI studies typically report significantly longer cognitive processing latencies for cortical electrical stimulation than for naturally occurring somatosensations or visual sensations.
In this study, we show that multi-channel electrical stimulation patterns elicit naturalistic somatosensory percepts in a human tetraplegic participant. Crucially, somatosensations evoked by multi-channel ICMS are cognitively processed at comparable latencies to naturally evoked sensations and significantly faster than visual sensations, as measured via a simple reaction time test. Further investigation demonstrated multi-channel stimulation could significantly reduce minimum amplitude detection thresholds and such reductions in charge density resulted in more frequent “natural” sensation descriptors reported by the human participant. Multi-channel ICMS patterns also evoked percepts with highly stable somatotopic locations. While some single-channel ICMS patterns evoked sensations 20-80% of the time, most multi-channel patterns could evoke sensations with 100% repeatability, an important step in demonstrating BCI device reliability. These improvements are all significant advances towards state-of-the-art sensory BMIs. The addition of such low-latency artificial sensory feedback to motor BMIs is expected to improve movement accuracy and increase embodiment for human users