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OBJECTIVEA posterior dynamic deformity correction (PDDC) system was used to correct adolescent idiopathic scoliosis (AIS) without fusion. The preliminary outcomes of bridging only 3–4 discs in patients with variable curve severity have previously been reported. This paper examines a subgroup of patients with the authors’ proposed current indications for this device who were also treated with a longer construct.METHODSInclusion criteria included a single AIS structural curve between 40° and 60°, curve flexibility ≤ 30°, PDDC spanning 5–6 levels, and minimum 2-year follow-up. A retrospective review was conducted and demographic and radiographic data were recorded. A successful outcome was defined as a curve magnitude of ≤ 30° at final follow-up. Any serious adverse events and reoperations were recorded.RESULTSTwenty-two patients who met the inclusion criteria were operated on with the PDDC in 5 medical centers. There were 19 girls and 3 boys, aged 13–17 years, with Risser grades ≥ 2. Thirteen had Lenke type 1 curves and 9 had type 5 curves. The mean preoperative curve was 47° (range 40°–55°). At a minimum of 2 years’ follow-up, the mean major curve measured 25° (46% correction, p < 0.05). In 18 (82%) of 22 patients, the mean final Cobb angle measured ≤ 30° (range 15°–30°). Trunk shift was corrected by 1.5 cm (range 0.4–4.3 cm). The mean minor curve was reduced from 27° to 17° at final follow-up (35% correction, p < 0.05). For Lenke type 1 patterns, the mean 2D thoracic kyphosis was 24° preoperatively versus 27° at final follow-up (p < 0.05), and for Lenke type 5 curves, mean lumbar lordosis was 47° preoperatively versus 42° at final follow-up (p < 0.05). The mean preoperative Scoliosis Research Society-22 questionnaire score improved from 2.74 ± 0.3 at baseline to 4.31 ± 0.4 at 2 years after surgery (p < 0.0001). The mean preoperative self-image score and satisfaction scores improved from preoperative values, while other domain scores did not change significantly. Four patients (18%) underwent revision surgery because of nut loosening (n = 2), pedicle screw backup (n = 1), and ratchet malfunction (n = 1).CONCLUSIONSIn AIS patients with a single flexible major curve up to 60°, the fusionless PDDC device achieved a satisfactory result as 82% had residual curves ≤ 30°. These findings suggest that the PDDC device may serve as an alternative to spinal fusion in select patients.

Crawling is a common locomotion mechanism in soft robots and nonskeletal animals. In this work we propose modeling soft-robotic legged locomotion by approximating it with an equivalent articulated robot with elastic joints. For concreteness we study the inchworm crawling of our soft robot with two bending actuators, via an articulated three-link model. The solution of statically indeterminate systems with stick-slip contact transitions requires for a novel hybrid-quasistatic analysis. Then, we utilize our analysis to investigate the influence of phase-shifted harmonic inputs on performance of crawling gaits, including sensitivity analysis to friction uncertainties and energetic cost of transport. We achieve optimal values of gait parameters. Finally, we fabricate and test a fluid-driven soft robot. The experiments display good agreement with the theoretical analysis, proving that our simple model correctly captures and explains the fundamental principles of inchworm crawling and can be applied to other soft-robotic legged robots.

A leading concept in soft robotics actuation, as well as in microfluidics applications such as valves in lab-on-a-chip devices, is applying pressurized flow in cavities embedded within elastic bodies. Generating complex deformation patterns typically requires control of several inputs, which greatly complicates the system's operation. In this work, we present a novel method for single-input control of a serial chain of bi-stable elastic chambers connected by thin tubes. Controlling a single flow rate at the chain's inlet, we induce an irreversible sequence of transitions that can reach any desired state combination of all bi-stable elements. Mathematical formulation and analysis of the system's dynamics reveal that these transitions are enabled thanks to bi-stability combined with pressure lag induced by viscous resistance. The results are demonstrated via numerical simulations combined with experiments for chains of up to 5 chambers, using water-diluted glycerol as the injected fluid. The proposed technique has a promising potential for development of sophisticated soft actuators with minimalistic control., Supplementary document will be added soon

Viscous flows in hyperelastic chambers are relevant to many biological phenomena such as inhalation into the lung's acinar region, and medical applications such as the inflation of a small chamber in minimally invasive procedures. In this work, we analytically study the viscous flow and elastic deformation created due to inflation of such spherical chambers from one or two inlets. Our investigation considers the shell's constitutive hyperelastic law coupled with the flow dynamics inside the chamber. For the case of a narrow tube filling a larger chamber, the pressure within the chamber involves a large spatially uniform part, and a small-order correction. We derive a closed-form expression for the inflation dynamics, accounting for the effect of elastic bistability. Interestingly, the obtained pressure distribution shows that the maximal pressure on the chamber's surface is greater than the pressure at the entrance to the chamber. The calculated series solution of the velocity and pressure fields during inflation is verified by using a fully coupled finite element scheme, resulting in excellent agreement. Our results allow the estimation of the chamber's viscous resistance at different pressures, thus enabling us to model the process of inflation and deflation.

Many organisms sense light using rhodopsins, photoreceptive proteins containing a retinal chromophore. Here we report the discovery, structure and biophysical characterization of bestrhodopsins, a microbial rhodopsin subfamily from marine unicellular algae, in which one rhodopsin domain of eight transmembrane helices or, more often, two such domains in tandem, are C-terminally fused to a bestrophin channel. Cryo-EM analysis of a rhodopsin-rhodopsin-bestrophin fusion revealed that it forms a pentameric megacomplex (~700 kDa) with five rhodopsin pseudodimers surrounding the channel in the center. Bestrhodopsins are metastable and undergo photoconversion between red- and green-absorbing or green- and UVA-absorbing forms in the different variants. The retinal chromophore, in a unique binding pocket, photoisomerizes from all-trans to 11-cis form. Heterologously expressed bestrhodopsin behaves as a light-modulated anion channel.

Swimming micro-organisms such as flagellated bacteria and sperm cells have fascinating locomotion capabilities. Inspired by their natural motion, there is an ongoing effort to develop artificial robotic nano-swimmers for potential in-body biomedical applications. A leading method for actuation of nano-swimmers is by applying a time-varying external magnetic field. Such systems have rich and nonlinear dynamics that calls for simple fundamental models. A previous work studied forward motion of a simple two-link model with passive elastic joint, assuming small-amplitude planar oscillations of the magnetic field about a constant direction. In this work, we found that there exists a faster, backward motion of the swimmer with very rich dynamics. By relaxing the small-amplitude assumption, we analyze the multiplicity of periodic solutions, as well as their bifurcations, symmetry breaking, and stability transitions. We have also found that the net displacement and/or mean swimming speed are maximized for optimal choices of various parameters. Asymptotic calculations are performed for the bifurcation condition and the swimmer's mean speed. The results may enable significantly improving the design aspects of magnetically-actuated robotic microswimmer., Comment: version 3, revised and resubmitted for review as journal publication

International audience; Optogenetic techniques have been developed to allow control over the activity of selected cells within a highly heterogeneous tissue, using a combination of genetic engineering and light. Optogenetics employs natural and engineered photoreceptors, mostly of microbial origin, to be genetically introduced into the cells of interest. As a result, cells that are naturally light-insensitive can be made photosensitive and addressable by illumination and precisely controllable in time and space. The selectivity of expression and subcellular targeting in the host is enabled by applying control elements such as promoters, enhancers and specific targeting sequences to the employed photoreceptor-encoding DNA. This powerful approach allows precise characterization and manipulation of cellular functions and has motivated the development of advanced optical methods for patterned photostimulation. Optogenetics has revolutionized neuroscience during the past 15 years and is primed to have a similar impact in other fields, including cardiology, cell biology and plant sciences. In this Primer, we describe the principles of optogenetics, review the most commonly used optogenetic tools, illumination approaches and scientific applications and discuss the possibilities and limitations associated with optogenetic manipulations across a wide variety of optical techniques, cells, circuits and organisms.

Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics’ agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, in this article we review an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion article, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed and provide an outlook for the future directions., This report was edited by Anna Devor and Darcy Peterka. Cover design by Kıvılcım Kılıç. A.D. was supported by the U.S. National Institutes of Health (NIH) grants R01MH111359, R01DA050159, and U19NS123717. A.N. was supported by NIH grants R01NS108034, U19NS112959, and U19NS123719. D.A.B. was supported by NIH grant R01NS108472. M.G.H. is currently the ERANet Chair (NCBio) at i3S Porto funded by the European Commission (H2020-WIDESPREAD-2018-2020-6; NCBio; 951923). R.A.S. is a Wellcome Principal Research Fellow (203048, 224499) and his microscopy development is co-funded by the NIH Brain initiative (U01NS113273). Fi.P., and Fe.P. acknowledge funding from the European Research Council under the European Union's Horizon 2020 Research and Innovation Program under Grant Agreement No. 677683. M.D.V. and Fe.P. acknowledge funding from the European Union's Horizon 2020 Research and Innovation Program under Grant Agreement No. 828972. Fi.P., M.D.V., Fe.P, O.Y., V.E., and T.C. acknowledge that this project has received funding from the European Union's Horizon 2020 Research and Innovation Program under Grant Agreement No. 101016787. Fe.P., B.L.S., and M.D.V. were funded by NIH Grant No. 1UF1NS108177-01. O.Y. and V. E. were supported by H2020-RIA (DEEPER 101016787) and the ERC (PrefrontalMap 819496). L.V.W. acknowledges funding support by NIH grants R01 NS102213, U01 NS099717, and U01 EB029823. S.L.S. was supported by NIH grants R01NS091335, R01NS121919 and National Science Foundation (NSF) grant 1934288. R.E.C, and Y.N. were supported by Japan Society for the Promotion of Science (JSPS) KAKENHI grant 19H05633. V.J.S. was supported by NIH grants NS094681, EB029747, and EY031469. S.N.S. acknowledges funding from the NIH Ruth L. Kirschstein National Research Service Award (F31 NS115421). P.R.D. acknowledges funding from the NIH Ruth L. Kirschstein National Research Service Award (F31 NS118949). T.A. and T.L. acknowledge funding from the University of Minnesota Medical School (AIRP) and the National Ataxia Foundation. F.V. was supported by NIH grants R01NS117756 and R01NS121219. U.H. was supported by NIH Brain Initiative grants R01NS120832, U01NS099709, and NSF NeuroNex Technology Hub 1707352. G.Y. was supported by NIH grants R01 GM124038 and R01 NS102586. L. T. was funded by NIH grant R21EY030016. I.C. was supported by European Union's Horizon 2020 Research and Innovation Framework Program under Grant Agreement No. 654148 (Laserlab-Europe); European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2) and No. 945539 (Human Brain Project SGA3); General Hospital Corporation Center of the NIH under Award No. U01 MH117023; Italian Ministry for Education in the framework of Euro-Bioimaging Italian Node (ESFRI research infrastructure); "Fondazione CR Firenze" (private foundation). T. Č., H. U., and P. O. were supported by the European Union's H2020-RIA (DEEPER, Grant Agreement No. 101016787), European Research Council (724530), and MEYS (CZ.02.1.01/ 0.0/ 0.0/ 15_003/0000476). S.S. was supported by NIH grants U19NS107464, R01NS109885 and UF1NS107680. V.E and R.S were supported by the European Research Council (ERC-2019-AdG 885090, HOLOVIS). N.J. was supported by NIH grant U01NS118300. A.V. was supported by the National Institute of Neurological Disorders and Stroke of the NIH under Award Nos. 5U01NS103488, 1RF1NS113251, and 1RF1NS110501, and the Kavli Foundation. D. S. P. was supported by NIH grants 5U19NS104649, 5U01NS113273, 9R44MH117430. Y. Z. was supported by NIH Director's New Innovator Award DP2 OD025926-01 and the Kaufman Foundation. A. S. A holds a Career Award at the Scientific Interface from Burroughs Wellcome Fund and acknowledges funding from the Searle Scholar Program and NIH New innovator award 1DP2MH129956. E. M. R. L. was supported by NIH grants R01MH111424 and U01NS094358. E. W. M. acknowledges support from NIH (R01NS098088) and NSF (NeuroNex 1707350).

Optogenetic actuators enable highly precise spatiotemporal interrogation of biological processes at levels ranging from the subcellular to cells, circuits and behaving organisms. Although their application in neuroscience has traditionally focused on the control of spiking activity at the somatodendritic level, the scope of optogenetic modulators for direct manipulation of presynaptic functions is growing. Presynaptically localized opsins combined with light stimulation at the terminals allow light-mediated neurotransmitter release, presynaptic inhibition, induction of synaptic plasticity and specific manipulation of individual components of the presynaptic machinery. Here, we describe presynaptic applications of optogenetic tools in the context of the unique cell biology of axonal terminals, discuss their potential shortcomings and outline future directions for this rapidly developing research area.

Animal vocal communication is a broad and multi-disciplinary field of research. Studying various aspects of communication can provide key elements for understanding animal behavior, evolution, and cognition. Given the large amount of acoustic data accumulated from automated recorders, for which manual annotation and analysis is impractical, there is a growing need to develop algorithms and automatic methods for analyzing and identifying animal sounds. In this study we developed an automatic detection and analysis system based on audio signal processing algorithms and deep learning that is capable of processing and analyzing large volumes of data without human bias. We selected the White Spectacled Bulbul (

IL-13 is a central mediator of asthma1–3. Here, we used genome-wide approaches to characterize genes and regulatory elements modulated by IL-13 and other asthma-associated cytokines in airway epithelial cells and showed how they can be used for therapeutic purposes. Using bulk and single cell RNA-seq, we found distinctive responses to IL-13, IL-17, and interferons in human bronchial epithelial basal, ciliated, and secretory cells. H3K27ac ChIP-seq revealed that IL-13 had widespread effects on regulatory elements. Detailed characterization of an enhancer of SPDEF, a transcription factor required for pathologic mucin production, revealed that STAT6 and KLF5 binding sites cooperate to drive IL-13-dependent transcription selectively in secretory cells. Using this enhancer to drive CRISPRi and knockdown either SPDEF or the mucin MUC5AC showed the potential use of this approach for asthma therapeutics. This work identifies numerous genes and regulatory elements involved in cell type-selective cytokine responses and showcases their use for therapeutic purposes.

Perceptual learning, defined as long-lasting changes in the ability to extract information from the environment, occurs following either brief exposure or prolonged practice. Whether these two types of experience yield qualitatively distinct patterns of learning is not clear. We used a time-compressed speech task to assess perceptual learning following either rapid exposure or additional training. We report that both experiences yielded robust and long-lasting learning. Individual differences in rapid learning explained unique variance in performance in independent speech tasks (natural-fast speech and speech-in-noise) with no additional contribution for training-induced learning (Experiment 1). Finally, it seems that similar factors influence the specificity of the two types of learning (Experiment 1 and 2). We suggest that rapid learning is key for understanding the role of perceptual learning in speech recognition under adverse conditions while longer learning could serve to strengthen and stabilize learning.

Sixty young males enrolled in an introductory course in psychology rated themselves on a series of 7-step, bipolar, adjectival scales. Afterwards they observed a young man perform a simple mechanical task, performed the same task and then rated the young man and themselves again. It was found that when the subjects perceived the young man as personally warm, they projected onto him attributes, which, they believed, characterized them. When the young man was perceived as warm and/or competent in the mechanical task, the subjects viewed themselves as more similar to him than in the absence of these perceptions. The results were interpreted as supporting Kagan's theory of identification. (Author)

Physical exercise is known to augment brain functioning, improving memory and cognition. However, while some of the physiological effects of physical activity on the brain are known, little is known about its effects on the neural code. Using calcium imaging in freely behaving mice, we study how voluntary exercise affects the quality and long-term stability of hippocampal place codes. We find that running accelerates the emergence of a more informative spatial code in novel environments and increases code stability over days and weeks. Paradoxically, although runners demonstrated an overall more stable place code than their sedentary peers, their place code changed faster when controlling for code quality level. A model-based simulation shows that the combination of improved code quality and faster representational drift in runners, but neither of these effects alone, could account for our results. Thus, exercise may enhance hippocampal function via a more informative and dynamic place code.

Perceptual learning for speech, defined as long-lasting changes in speech recognition following exposure or practice occurs under many challenging listening conditions. However, this learning is also highly specific to the conditions in which it occurred, such that its function in adult speech recognition is not clear. We used a time-compressed speech task to assess learning following either brief exposure (rapid learning) or additional training (training-induced learning). Both types of learning were robust and long-lasting. Individual differences in rapid learning explained unique variance in recognizing natural-fast speech and speech-in-noise with no additional contribution for training-induced learning (Experiment 1). Rapid learning was stimulus specific (Experiment 2), as in previous studies on training-induced learning. We suggest that rapid learning is key for understanding the role of perceptual learning in online speech recognition whereas longer training could provide additional opportunities to consolidate and stabilize learning.

Cancer diagnosis using cell-free DNA (cfDNA) has potential to improve treatment and survival but has several technical limitations. Here, we show that tumor-associated mutations create neomers, DNA sequences 13-17 nucleotides in length that are predominantly absent from genomes of healthy individuals, that can accurately detect cancer, including early stages, and distinguish subtypes and features. Using a neomer-based classifier, we show that we can distinguish twenty-one different tumor-types with higher accuracy than state-of-the-art methods. Refinement of this classifier using a handcrafted set of kmers identified additional cancer features with greater precision. Generation and analysis of 451 cfDNA whole-genome sequences demonstrates that neomers can precisely detect lung and ovarian cancer with an area under the curve (AUC) of 0.93 and 0.89, respectively. In particular, for early stages, we show that neomers can detect lung cancer with an AUC of 0.94 and ovarian cancer, which lacks an early detection test, with an AUC of 0.93. Finally, testing over 9,000 sequences with either promoter or massively parallel reporter assays, we show that neomers can identify cancer-associated mutations that alter regulatory activity. Combined, our results identify a novel, sensitive, specific and simple diagnostic tool that can also identify novel cancer-associated mutations in gene regulatory elements.