ISSLS PRIZE IN BIOENGINEERING SCIENCE 2019: biomechanical changes in dynamic sagittal balance and lower limb compensatory strategies following realignment surgery in adult spinal deformity patients.

Study designA longitudinal cohort study.ObjectiveTo define a set of objective biomechanical metrics that are representative of adult spinal deformity (ASD) post-surgical outcomes and that may forecast post-surgical mechanical complications. Current outcomes for ASD surgical planning and post-surgical assessment are limited to static radiographic alignment and patient-reported questionnaires. Little is known about the compensatory biomechanical strategies for stabilizing sagittal balance during functional movements in ASD patients.MethodsWe collected in-clinic motion data from 15 ASD patients and 10 controls during an unassisted sit-to-stand (STS) functional maneuver. Joint motions were measured using noninvasive 3D depth mapping sensor technology. Mathematical methods were used to attain high-fidelity joint-position tracking for biomechanical modeling. This approach provided reliable measurements for biomechanical behaviors at the spine, hip, and knee. These included peak sagittal vertical axis (SVA) over the course of the STS, as well as forces and muscular moments at various joints. We compared changes in dynamic sagittal balance (DSB) metrics between pre- and post-surgery and then separately compared pre- and post-surgical data to controls.ResultsStandard radiographic and patient-reported outcomes significantly improved following realignment surgery. From the DSB biomechanical metrics, peak SVA and biomechanical loads and muscular forces on the lower lumbar spine significantly reduced following surgery (- 19 to - 30%, all p < 0.05). In addition, as SVA improved, hip moments decreased (- 28 to - 65%, all p < 0.05) and knee moments increased (+ 7 to + 28%, p < 0.05), indicating changes in lower limb compensatory strategies. After surgery, DSB data approached values from the controls, with some post-surgical metrics becoming statistically equivalent to controls.ConclusionsLongitudinal changes in DSB following successful multi-level spinal realignment indicate reduced forces on the lower lumbar spine along with altered lower limb dynamics matching that of controls. Inadequate improvement in DSB may indicate increased risk of post-surgical mechanical failure. These slides can be retrieved under Electronic Supplementary Material

Predicting Temporal Patterns In The Environment: Toward Primitive Mechanisms Of Learning, Memory, And Generalization

Across a wide range of cognitive tasks, recent experience influences subsequent behavior. For example, when individuals repeatedly perform a speeded two-alternative choice task, response latencies vary dramatically based on the immediately preceding sequence. These sequential dependencies (SDs) have been interpreted as adaptation to the statistical structure of an uncertain, changing environment (e.g., Jones & Sieck, 2003; Mozer, Kinoshita, & Shettel, 2007; Yu & Cohen, 2009), and can shed light on how individuals learn and represent structure in binary stimulus sequences. Heretofore, theories have posited that SDs arise from rapidly (exponentially) decaying memory traces of various environmental statistics (e.g., Cho et al., 2002; Yu & Cohen, 2009).

We present a series of experiments and a model that place SDs on a fundamentally different foundation. We show that: (1) decay of recent experience can follow a power function curve, not an exponential, linking the SD literature
to a rich literature on human declarative memory; (2) the simple trace-based mechanism underlying existing accounts is inadequate, but incremental memory adjustments may be explained via error correction, linking the SD literature to the rich literature on human associative learning; and (3) distinct but interacting subsystems are found in the brain that jointly predict upcoming environmental events. 

We conducted three behavioral studies with EEG recordings of individuals performing discrimination of spatial location and motion coherence. Identifying the onset of the lateralized readiness potential (LRP) in an event-related EEG analysis, we are able to decompose the total response latency into two intervals—pre and post LRP onset—and to examine SDs in stimulus and response processing separately. We find evidence for two distinct mechanisms, one reflecting incremental learning of stimulus repetition rate (i.e., the probability that successive
stimuli will match), and the other reflecting incremental learning of response baserates. The data cannot be explained by a model that assumes these rates are based on independent traces, and calls for an account in which the two rates jointly predict future stimuli via error-correction learning. 

By manipulating the autocorrelation structure of the sequences (from a positive to a negative autocorrelation, indicated on the graphs by blue and red lines, respectively), we obtained evidence for incremental learning occurring over hundreds of trials, which is parsimoniously explained by a memory with power function decay. Together, the results highlight a tension between the two broad and well established classes of trace-based memory models and learning models based on error correction. Two attempts at reconciling these approaches via modeling are discussed

Climate Variability and Local Environmental Stressors Influencing Migration in Nang Rong, Thailand

Scholars point to climate change, often in the form of more frequent and severe drought, as a potential driver of migration in the developing world, particularly in populations that rely on agriculture for their livelihoods. To date, however, there have been few large-scale, longitudinal studies that explore the relationship between climate change and migration. This study significantly extends current scholarship by evaluating distinctive effects of slow onset climate change and short-term extreme events upon different migration outcomes. Our analysis models the effect of the environment--as measured by Normalized Difference Vegetation Index (NDVI) and the occurrence of El Nino Southern Oscillation (ENSO) events—on migration out of Nang Rong. Our preliminary findings indicate that predominantly dry El Niño periods of 24 months duration lead to outmigration, while predominantly wetter La Niña periods of 12-month duration reduce outmigration. Clustered monthly patterns of annual NDVI fluctuation indicate that villagers living in pixels that exhibit early, consistently higher, and steep rising green-up are less likely to migrate out in the subsequent year

Magnetic effects on the low-T/|W| instability in differentially rotating neutron stars

Dynamical instabilities in protoneutron stars may produce gravitational waves whose observation could shed light on the physics of core-collapse supernovae. When born with sufficient differential rotation, these stars are susceptible to a shear instability (the "low-T/|W| instability"), but such rotation can also amplify magnetic fields to strengths where they have a considerable impact on the dynamics of the stellar matter. Using a new magnetohydrodynamics module for the Spectral Einstein Code, we have simulated a differentially-rotating neutron star in full 3D to study the effects of magnetic fields on this instability. Though strong toroidal fields were predicted to suppress the low-T/|W| instability, we find that they do so only in a small range of field strengths. Below 4e13 G, poloidal seed fields do not wind up fast enough to have an effect before the instability saturates, while above 5e14 G, magnetic instabilities can actually amplify a global quadrupole mode (this threshold may be even lower in reality, as small-scale magnetic instabilities remain difficult to resolve numerically). Thus, the prospects for observing gravitational waves from such systems are not in fact diminished over most of the magnetic parameter space. Additionally, we report that the detailed development of the low-T/|W| instability, including its growth rate, depends strongly on the particular numerical methods used. The high-order methods we employ suggest that growth might be considerably slower than found in some previous simulations.Comment: REVTeX 4.1, 21 pages, 18 figures, submitting to Physical Review

Electrophysiological correlates of high-level perception during spatial navigation

We studied the electrophysiological basis of object recognition by recording scalp\ud electroencephalograms while participants played a virtual-reality taxi driver game.\ud Participants searched for passengers and stores during virtual navigation in simulated\ud towns. We compared oscillatory brain activity in response to store views that were targets or\ud nontargets (during store search) or neutral (during passenger search). Even though store\ud category was solely defined by task context (rather than by sensory cues), frontal ...\ud \u

Identification of new members of the Escherichia coli K-12 MG1655 SlyA regulon.

SlyA is a member of the MarR family of bacterial transcriptional regulators. Previously, SlyA has been shown to directly regulate only two operons in Escherichia coli K-12 MG1655, fimB and hlyE (clyA). In both cases SlyA activates gene expression by antagonizing repression by the nucleoid associated protein H-NS. Here the transcript profiles of aerobic glucose-limited steady-state chemostat cultures of E. coli K-12 MG1655, slyA mutant and slyA over-expression strains are reported. The transcript profile of the slyA mutant was not significantly different to that of the parent; however, that of the slyA expression strain was significantly different from that of the vector control. Transcripts representing 27 operons were increased in abundance, whereas 3 were decreased. Of the 30 differentially regulated operons, 24 have been previously associated with sites of H-NS binding, suggesting that antagonism of H-NS repression is a common feature of SlyA-mediated transcription regulation. Direct binding of SlyA to DNA located upstream of a selection of these targets permitted the identification of new operons likely to be directly regulated by SlyA. Transcripts of four operons coding for cryptic adhesins exhibited enhanced expression and this was consistent with enhanced biofilm formation associated with the SlyA over-producing strain

Inhibition of Nonsense-Mediated mRNA Decay by Antisense Morpholino Oligonucleotides Restores Functional Expression of hERG Nonsense and Frameshift Mutations in Long-QT Syndrome

Mutations in the human ether-a-go-go-related gene (hERG) cause long-QT syndrome type 2 (LQT2). We previously described a homozygous LQT2 nonsense mutation Q1070X in which the mutant mRNA is degraded by nonsense-mediated mRNA decay (NMD) leading to a severe clinical phenotype. The degradation of the Q1070X transcript precludes the expression of truncated but functional mutant channels. In the present study, we tested the hypothesis that inhibition of NMD can restore functional expression of LQT2 mutations that are targeted by NMD. We showed that inhibition of NMD by RNA interference-mediated knockdown of UPF1 increased Q1070X mutant channel protein expression and hERG current amplitude. More importantly, we found that specific inhibition of downstream intron splicing by antisense morpholino oligonucleotides prevented NMD of the Q1070X mutant mRNA and restored the expression of functional Q1070X mutant channels. The restoration of functional expression by antisense morpholino oligonucleotides was also observed in LQT2 frameshift mutations. Our findings suggest that inhibition of NMD by antisense morpholino oligonucleotides may be a potential therapeutic approach for some LQT2 patients carrying nonsense and frameshift mutations

Gravitational waveforms for neutron star binaries from binary black hole simulations

Gravitational waves from binary neutron star (BNS) and black-hole/neutron star (BHNS) inspirals are primary sources for detection by the Advanced Laser Interferometer Gravitational-Wave Observatory. The tidal forces acting on the neutron stars induce changes in the phase evolution of the gravitational waveform, and these changes can be used to constrain the nuclear equation of state. Current methods of generating BNS and BHNS waveforms rely on either computationally challenging full 3D hydrodynamical simulations or approximate analytic solutions. We introduce a new method for computing inspiral waveforms for BNS/BHNS systems by adding the post-Newtonian (PN) tidal effects to full numerical simulations of binary black holes (BBHs), effectively replacing the non-tidal terms in the PN expansion with BBH results. Comparing a waveform generated with this method against a full hydrodynamical simulation of a BNS inspiral yields a phase difference of < 1 radian over ~ 15 orbits. The numerical phase accuracy required of BNS simulations to measure the accuracy of the method we present here is estimated as a function of the tidal deformability parameter ⋋

Psilocybin for treatment-resistant depression: fMRI-measured brain mechanisms

Psilocybin with psychological support is showing promise as a treatment model in psychiatry but its therapeutic mechanisms are poorly understood. Here, cerebral blood flow (CBF) and blood oxygen-level dependent (BOLD) resting-state functional connectivity (RSFC) were measured with functional magnetic resonance imaging (fMRI) before and after treatment with psilocybin (serotonin agonist) for treatment-resistant depression (TRD). Quality pre and post treatment fMRI data were collected from 16 of 19 patients. Decreased depressive symptoms were observed in all 19 patients at 1-week post-treatment and 47% met criteria for response at 5 weeks. Whole-brain analyses revealed post-treatment decreases in CBF in the temporal cortex, including the amygdala. Decreased amygdala CBF correlated with reduced depressive symptoms. Focusing on a priori selected circuitry for RSFC analyses, increased RSFC was observed within the default-mode network (DMN) post-treatment. Increased ventromedial prefrontal cortex-bilateral inferior lateral parietal cortex RSFC was predictive of treatment response at 5-weeks, as was decreased parahippocampal-prefrontal cortex RSFC. These data fill an important knowledge gap regarding the post-treatment brain effects of psilocybin, and are the first in depressed patients. The post-treatment brain changes are different to previously observed acute effects of psilocybin and other ‘psychedelics’ yet were related to clinical outcomes. A ‘reset’ therapeutic mechanism is proposed