BLiSS: Bootstrapped Linear Shape Space

Morphable models are fundamental to numerous human-centered processes as they offer a simple yet expressive shape space. Creating such morphable models, however, is both tedious and expensive. The main challenge is establishing dense correspondences across raw scans that capture sufficient shape variation. This is often addressed using a mix of significant manual intervention and nonrigid registration. We observe that creating a shape space and solving for dense correspondence are tightly coupled - while dense correspondence is needed to build shape spaces, an expressive shape space provides a reduced dimensional space to regularize the search. We introduce BLiSS, a method to solve both progressively. Starting from a small set of manually registered scans to bootstrap the process, we enrich the shape space and then use that to get new unregistered scans into correspondence automatically. The critical component of BLiSS is a non-linear deformation model that captures details missed by the low-dimensional shape space, thus allowing progressive enrichment of the space

Targeting Aldehyde Dehydrogenases to Eliminate Cancer Stem Cells in Gynecologic Malignancies

Gynecologic cancers cause over 600,000 deaths annually in women worldwide. The development of chemoresistance after initial rounds of chemotherapy contributes to tumor relapse and death due to gynecologic malignancies. In this regard, cancer stem cells (CSCs), a subpopulation of stem cells with the ability to undergo self-renewal and clonal evolution, play a key role in tumor progression and drug resistance. Aldehyde dehydrogenases (ALDH) are a group of enzymes shown to be robust CSC markers in gynecologic and other malignancies. These enzymes also play functional roles in CSCs, including detoxification of aldehydes, scavenging of reactive oxygen species (ROS), and retinoic acid (RA) signaling, making ALDH an attractive therapeutic target in various clinical scenarios. In this review, we discuss the critical roles of the ALDH in driving stemness in different gynecologic malignancies. We review inhibitors of ALDH, both general and isoform-specific, which have been used to target CSCs in gynecologic cancers. Many of these inhibitors have been shown to be effective in preclinical models of gynecologic malignancies, supporting further development in the clinic. Furthermore, ALDH inhibitors, including 673A and CM037, synergize with chemotherapy to reduce tumor growth. Thus, ALDH-targeted therapies hold promise for improving patient outcomes in gynecologic malignancies

A perceptual glitch in serial perception generates temporal distortions

Precisely estimating event timing is essential for survival, yet temporal distortions are ubiquitous in our daily sensory experience. Here, we tested whether the relative position, duration, and distance in time of two sequentially-organized events—standard S, with constant duration, and comparison C, with duration varying trial-by-trial—are causal factors in generating temporal distortions. We found that temporal distortions emerge when the first event is shorter than the second event. Importantly, a significant interaction suggests that a longer inter-stimulus interval (ISI) helps to counteract such serial distortion effect only when the constant S is in the first position, but not if the unpredictable C is in the first position. These results imply the existence of a perceptual bias in perceiving ordered event durations, mechanistically contributing to distortion in time perception. We simulated our behavioral results with a Bayesian model and replicated the finding that participants disproportionately expand first-position dynamic (unpredictable) short events. Our results clarify the mechanisms generating time distortions by identifying a hitherto unknown duration-dependent encoding inefficiency in human serial temporal perception, something akin to a strong prior that can be overridden for highly predictable sensory events but unfolds for unpredictable ones

A perceptual glitch in serial perception generates temporal distortions

Precisely estimating event timing is essential for survival, yet temporal distortions are ubiquitous in our daily sensory experience. Here, we tested whether the relative position, duration, and distance in time of two sequentially-organized events—standard S, with constant duration, and comparison C, with duration varying trial-by-trial—are causal factors in generating temporal distortions. We found that temporal distortions emerge when the first event is shorter than the second event. Importantly, a significant interaction suggests that a longer inter-stimulus interval (ISI) helps to counteract such serial distortion effect only when the constant S is in the first position, but not if the unpredictable C is in the first position. These results imply the existence of a perceptual bias in perceiving ordered event durations, mechanistically contributing to distortion in time perception. We simulated our behavioral results with a Bayesian model and replicated the finding that participants disproportionately expand first-position dynamic (unpredictable) short events. Our results clarify the mechanisms generating time distortions by identifying a hitherto unknown duration-dependent encoding inefficiency in human serial temporal perception, something akin to a strong prior that can be overridden for highly predictable sensory events but unfolds for unpredictable ones

Machine-Learned Closure of URANS for Stably Stratified Turbulence: Connecting Physical Timescales & Data Hyperparameters of Deep Time-Series Models

We develop time-series machine learning (ML) methods for closure modeling of the Unsteady Reynolds Averaged Navier Stokes (URANS) equations applied to stably stratified turbulence (SST). SST is strongly affected by fine balances between forces and becomes more anisotropic in time for decaying cases. Moreover, there is a limited understanding of the physical phenomena described by some of the terms in the URANS equations. Rather than attempting to model each term separately, it is attractive to explore the capability of machine learning to model groups of terms, i.e., to directly model the force balances. We consider decaying SST which are homogeneous and stably stratified by a uniform density gradient, enabling dimensionality reduction. We consider two time-series ML models: Long Short-Term Memory (LSTM) and Neural Ordinary Differential Equation (NODE). Both models perform accurately and are numerically stable in a posteriori tests. Furthermore, we explore the data requirements of the ML models by extracting physically relevant timescales of the complex system. We find that the ratio of the timescales of the minimum information required by the ML models to accurately capture the dynamics of the SST corresponds to the Reynolds number of the flow. The current framework provides the backbone to explore the capability of such models to capture the dynamics of higher-dimensional complex SST flows

Withania somnifera Root Extract Enhances Chemotherapy through ‘Priming’

Withania somnifera extracts are known for their anti-cancerous, anti-inflammatory and antioxidative properties. One of their mechanisms of actions is to modulate mitochondrial function through increasing oxidative stress. Recently ‘priming’ has been suggested as a potential mechanism for enhancing cancer cell death. In this study we demonstrate that ‘priming’, in HT-29 colon cells, with W. somnifera root extract increased the potency of the chemotherapeutic agent cisplatin. We have also showed the W. somnifera root extract enhanced mitochondrial dysfunction and that the underlying mechanism of ‘priming’ was selectively through increased ROS. Moreover, we showed that this effect was not seen in non-cancerous cells

Variation in the provision and practice of implant-based breast reconstruction in the UK: Results from the iBRA national practice questionnaire

Introduction: The introduction of biological and synthetic meshes has revolutionised the practice of implant-based breast reconstruction (IBBR) but evidence for effectiveness is lacking. The iBRA (implant Breast Reconstruction evAluation) study is a national trainee-led project that aims to explore the practice and outcomes of IBBR to inform the design of a future trial. We report the results of the iBRA National Practice Questionnaire (NPQ) which aimed to comprehensively describe the provision and practice of IBBR across the UK. Methods: A questionnaire investigating local practice and service provision of IBBR developed by the iBRA Steering Group was completed by trainee and consultant leads at breast and plastic surgical units across the UK. Summary data for each survey item were calculated and variation between centres and overall provision of care examined. Results: 81 units within 79 NHS-hospitals completed the questionnaire. Units offered a range of reconstructive techniques, with IBBR accounting for 70% (IQR:50–80%) of participating units' immediate procedures. Units on average were staffed by 2.5 breast surgeons (IQR:2.0–3.0) and 2.0 plastic surgeons (IQR:1.0–3.0) performing 35 IBBR cases per year (IQR:20-50). Variation was demonstrated in the provision of novel different techniques for IBBR especially the use of biological (n = 62) and synthetic (n = 25) meshes and in patient selection for these procedures. Conclusions: The iBRA-NPQ has demonstrated marked variation in the provision and practice of IBBR in the UK. The prospective audit phase of the iBRA study will determine the safety and effectiveness of different approaches to IBBR and allow evidence-based best practice to be explored

Selective Cholinergic Depletion in Medial Septum Leads to Impaired Long Term Potentiation and Glutamatergic Synaptic Currents in the Hippocampus

Cholinergic depletion in the medial septum (MS) is associated with impaired hippocampal-dependent learning and memory. Here we investigated whether long term potentiation (LTP) and synaptic currents, mediated by alpha-amino-3-hydroxy-5-methyl-isoxazole-4-propionate (AMPA) and N-methyl-D-aspartate (NMDA) receptors in the CA1 hippocampal region, are affected following cholinergic lesions of the MS. Stereotaxic intra-medioseptal infusions of a selective immunotoxin, 192-saporin, against cholinergic neurons or sterile saline were made in adult rats. Four days after infusions, hippocampal slices were made and LTP, whole cell, and single channel (AMPA or NMDA receptor) currents were recorded. Results demonstrated impairment in the induction and expression of LTP in lesioned rats. Lesioned rats also showed decreases in synaptic currents from CA1 pyramidal cells and synaptosomal single channels of AMPA and NMDA receptors. Our results suggest that MS cholinergic afferents modulate LTP and glutamatergic currents in the CA1 region of the hippocampus, providing a potential synaptic mechanism for the learning and memory deficits observed in the rodent model of selective MS cholinergic lesioning