Wearable Sensors to Monitor Physical Activity in Heart Failure Clinical Trials: State-of-the-Art Review.

BACKGROUND: Estimation of the effects that drugs or other interventions have on patients' symptoms and functions is crucial in heart failure trials. Traditional symptoms and functions clinical outcome assessments have important limitations. Actigraphy may help to overcome these limitations due to its objective nature and the potential for continuous recording of data. However, actigraphy is not currently accepted as clinically relevant by key stakeholders. METHODS AND RESULTS: In this state-of-the-art study, the key aspects to consider when implementing actigraphy in heart failure trials are discussed. They include which actigraphy-derived measures should be considered, how to build endpoints using them, how to measure and analyze them, and how to handle the patients' and sites' logistics of integrating devices into trials. A comprehensive recommendation based on the current evidence is provided. CONCLUSION: Actigraphy is technically feasible in clinical trials involving heart failure, but successful implementation and use to demonstrate clinically important differences in physical functioning with drug or other interventions require careful consideration of many design choices.

Leveraging intracellular ALDH1A1 activity for selective cancer stem-like cell labeling and targeted treatment via in vivo click reaction.

Inhibition of overexpressed enzymes is among the most promising approaches for targeted cancer treatment. However, many cancer-expressed enzymes are "nonlethal," in that the inhibition of the enzymes' activity is insufficient to kill cancer cells. Conventional antibody-based therapeutics can mediate efficient treatment by targeting extracellular nonlethal targets but can hardly target intracellular enzymes. Herein, we report a cancer targeting and treatment strategy to utilize intracellular nonlethal enzymes through a combination of selective cancer stem-like cell (CSC) labeling and Click chemistry-mediated drug delivery. A de novo designed compound, AAMCHO [N-(3,4,6-triacetyl- N-azidoacetylmannosamine)-cis-2-ethyl-3-formylacrylamideglycoside], selectively labeled cancer CSCs in vitro and in vivo through enzymatic oxidation by intracellular aldehyde dehydrogenase 1A1. Notably, azide labeling is more efficient in identifying tumorigenic cell populations than endogenous markers such as CD44. A dibenzocyclooctyne (DBCO)-toxin conjugate, DBCO-MMAE (Monomethylauristatin E), could next target the labeled CSCs in vivo via bioorthogonal Click reaction to achieve excellent anticancer efficacy against a series of tumor models, including orthotopic xenograft, drug-resistant tumor, and lung metastasis with low toxicity. A 5/7 complete remission was observed after single-cycle treatment of an advanced triple-negative breast cancer xenograft (~500 mm3).

Accurate Step Count with Generalized and Personalized Deep Learning on Accelerometer Data.

Physical activity (PA) is globally recognized as a pillar of general health. Step count, as one measure of PA, is a well known predictor of long-term morbidity and mortality. Despite its popularity in consumer devices, a lack of methodological standards and clinical validation remains a major impediment to step count being accepted as a valid clinical endpoint. Previous works have mainly focused on device-specific step-count algorithms and often employ sensor modalities that may not be widely available. This may limit step-count suitability in clinical scenarios. In this paper, we trained neural network models on publicly available data and tested on an independent cohort using two approaches: generalization and personalization. Specifically, we trained neural networks on accelerometer signals from one device and either directly applied them or adapted them individually to accelerometer data obtained from a separate subject cohort wearing multiple distinct devices. The best models exhibited highly accurate step-count estimates for both the generalization (96-99%) and personalization (98-99%) approaches. The results demonstrate that it is possible to develop device-agnostic, accelerometer-only algorithms that provide highly accurate step counts, positioning step count as a reliable mobility endpoint and a strong candidate for clinical validation.

Cross-fixation interactions of orientations suggest high-to-low-level decoding in visual working memory.

Sensory encoding (how stimuli evoke sensory responses) is known to progress from low- to high-level features. Decoding (how responses lead to perception) is less understood but is often assumed to follow the same hierarchy. Accordingly, orientation decoding must occur in low-level areas such as V1, without cross-fixation interactions. However, a study, Ding, Cueva, Tsodyks, and Qian (2017), provided evidence against the assumption and proposed that visual decoding may often follow a high-to-low-level hierarchy in working memory, where higher-to-lower-level constraints introduce interactions among lower-level features. If two orientations on opposite sides of the fixation are both task relevant and enter working memory, then they should interact with each other. We indeed found the predicted cross-fixation interactions (repulsion and correlation) between orientations. Control experiments and analyses ruled out alternative explanations such as reporting bias and adaptation across trials on the same side of the fixation. Moreover, we explained the data using a retrospective high-to-low-level Bayesian decoding framework.

Categorical judgments do not modify sensory representations in working memory.

Categorical judgments can systematically bias the perceptual interpretation of stimulus features. However, it remained unclear whether categorical judgments directly modify working memory representations or, alternatively, generate these biases via an inference process down-stream from working memory. To address this question we ran two novel psychophysical experiments in which human subjects had to reverse their categorical judgments about a stimulus feature, if incorrect, before providing an estimate of the feature. If categorical judgments indeed directly altered sensory representations in working memory, subjects' estimates should reflect some aspects of their initial (incorrect) categorical judgment in those trials. We found no traces of the initial categorical judgment. Rather, subjects seemed to be able to flexibly switch their categorical judgment if needed and use the correct corresponding categorical prior to properly perform feature inference. A cross-validated model comparison also revealed that feedback may lead to selective memory recall such that only memory samples that are consistent with the categorical judgment are accepted for the inference process. Our results suggest that categorical judgments do not modify sensory information in working memory but rather act as top-down expectations in the subsequent sensory recall and inference process.

Versatile Target-Guided Screen for Discovering Bidirectional Transcription Inhibitors of a Trinucleotide Repeat Disease.

Myotonic dystrophy type 1 originates from d(CTG·CAG) repeats that undergo aberrant expansion during normal processing because the d(CTG) repeat forms stable hairpin structures. Bidirectional transcription of d(CTG·CAG) yields two RNA transcripts that undergo repeat-associated non-ATG (RAN) translation to form homopolymeric proteins. Thus, both the r(CUG) transcript and the r(CAG) transcript are known to be toxic. We report a pairwise fragment-based, target-guided approach to screen for proximity-induced click dimers formed on the nucleic acid template. This screen uses an azide/alkyne clickable fragment library of nucleic acid-binding ligands incubated in parallel, pairwise reactions as an alternative to our previously reported one-pot screening method. MALDI-TOF mass spectroscopy was used to detect template assisted click products. Hit compounds inhibited the in vitro transcription of d(CTG·CAG)90 bidirectionally with IC50 values in the low micromolar range. This approach may be broadly applicable to other trinucleotide repeat diseases and in targeting other disease-associated nucleic acid sequences.

Expanded DNA and RNA Trinucleotide Repeats in Myotonic Dystrophy Type 1 Select Their Own Multitarget, Sequence-Selective Inhibitors.

There are few methods available for the rapid discovery of multitarget drugs. Herein, we describe the template-assisted, target-guided discovery of small molecules that recognize d(CTG) in the expanded d(CTG·CAG) sequence and its r(CUG) transcript that cause myotonic dystrophy type 1. A positive cross-selection was performed using a small library of 30 monomeric alkyne- and azide-containing ligands capable of producing >5000 possible di- and trimeric click products. The monomers were incubated with d(CTG)16 or r(CUG)16 under physiological conditions, and both sequences showed selectivity in the proximity-accelerated azide-alkyne [3+2] cycloaddition click reaction. The limited number of click products formed in both selections and the even smaller number of common products suggests that this method is a useful tool for the discovery of single-target and multitarget lead therapeutic agents.

Benefits of commitment in hierarchical inference.

Humans have the tendency to commit to a single interpretation of what has caused some observed evidence rather than considering all possible alternatives. This tendency can explain various forms of biases in cognition and perception. However, committing to a single high-level interpretation seems short-sighted and irrational, and thus it is unclear why humans are motivated to use such strategy. In a first step toward answering this question, we systematically quantified how this strategy affects estimation accuracy at the feature level in the context of 2 common hierarchical inference tasks, category-based perception and causal cue combination. Using model simulations, we demonstrate that although estimation accuracy is generally impaired when conditioned on only a single high-level interpretation, the reduction is not uniform across the entire feature range. Compared with a full inference strategy that considers all high-level interpretations, accuracy is only worse for feature values relatively close to the decision boundaries but is better everywhere else. That is, for feature values for which an observer has a reasonably high chance of being correct about the high-level interpretation of the feature, a full commitment to that particular interpretation is advantageous. We also show that conditioning on an preceding high-level interpretation provides an effective mechanism for partially protecting the evidence from corruption with late noise in the inference process (e.g., during retention in and recall from working memory). Our results suggest that a top-down inference strategy that solely relies on the most likely high-level interpretation can be favorable with regard to late noise and more holistic performance metrics. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Intrinsically cell-penetrating multivalent and multitargeting ligands for myotonic dystrophy type 1.

Developing highly active, multivalent ligands as therapeutic agents is challenging because of delivery issues, limited cell permeability, and toxicity. Here, we report intrinsically cell-penetrating multivalent ligands that target the trinucleotide repeat DNA and RNA in myotonic dystrophy type 1 (DM1), interrupting the disease progression in two ways. The oligomeric ligands are designed based on the repetitive structure of the target with recognition moieties alternating with bisamidinium groove binders to provide an amphiphilic and polycationic structure, mimicking cell-penetrating peptides. Multiple biological studies suggested the success of our multivalency strategy. The designed oligomers maintained cell permeability and exhibited no apparent toxicity both in cells and in mice at working concentrations. Furthermore, the oligomers showed important activities in DM1 cells and in a DM1 liver mouse model, reducing or eliminating prominent DM1 features. Phenotypic recovery of the climbing defect in adult DM1 Drosophila was also observed. This design strategy should be applicable to other repeat expansion diseases and more generally to DNA/RNA-targeted therapeutics.

Post-decision biases reveal a self-consistency principle in perceptual inference.

Making a categorical judgment can systematically bias our subsequent perception of the world. We show that these biases are well explained by a self-consistent Bayesian observer whose perceptual inference process is causally conditioned on the preceding choice. We quantitatively validated the model and its key assumptions with a targeted set of three psychophysical experiments, focusing on a task sequence where subjects first had to make a categorical orientation judgment before estimating the actual orientation of a visual stimulus. Subjects exhibited a high degree of consistency between categorical judgment and estimate, which is difficult to reconcile with alternative models in the face of late, memory related noise. The observed bias patterns resemble the well-known changes in subjective preferences associated with cognitive dissonance, which suggests that the brain's inference processes may be governed by a universal self-consistency constraint that avoids entertaining 'dissonant' interpretations of the evidence.

A Potent Inhibitor of Protein Sequestration by Expanded Triplet (CUG) Repeats that Shows Phenotypic Improvements in a Drosophila Model of Myotonic Dystrophy.

Myotonic dystrophy is the most common form of adult-onset muscular dystrophy, originating in a CTG repeat expansion in the DMPK gene. The expanded CUG transcript sequesters MBNL1, a key regulator of alternative splicing, leading to the misregulation of numerous pre-mRNAs. We report an RNA-targeted agent as a possible lead compound for the treatment of myotonic dystrophy type 1 (DM1) that reveals both the promise and challenges for this type of small-molecule approach. The agent is a potent inhibitor of the MBNL1-rCUG complex with an inhibition constant (Ki ) of 25±8 nm, and is also relatively nontoxic to HeLa cells, able to dissolve nuclear foci, and correct the insulin receptor splicing defect in DM1 model cells. Moreover, treatment with this compound improves two separate disease phenotypes in a Drosophila model of DM1: adult external eye degeneration and larval crawling defect. However, the compound has a relatively low maximum tolerated dose in mice, and its cell uptake may be limited, providing insight into directions for future development.

Rationally designed small molecules that target both the DNA and RNA causing myotonic dystrophy type 1.

Single-agent, single-target therapeutic approaches are often limited by a complex disease pathobiology. We report rationally designed, multi-target agents for myotonic dystrophy type 1 (DM1). DM1 originates in an abnormal expansion of CTG repeats (CTG(exp)) in the DMPK gene. The resultant expanded CUG transcript (CUG(exp)) identified as a toxic agent sequesters important proteins, such as muscleblind-like proteins (MBNL), undergoes repeat-associated non-ATG (RAN) translation, and potentially causes microRNA dysregulation. We report rationally designed small molecules that target the DM1 pathobiology in vitro in three distinct ways by acting simultaneously as transcription inhibitors, by inhibiting aberrant protein binding to the toxic RNA, and by acting as RNase mimics to degrade the toxic RNA. In vitro, the agents are shown to (1) bind CTG(exp) and inhibit formation of the CUG(exp) transcript, (2) bind CUG(exp) and inhibit sequestration of MBNL1, and (3) cleave CUG(exp) in an RNase-like manner. The most potent compounds are capable of reducing the levels of CUG(exp) in DM1 model cells, and one reverses two separate CUG(exp)-induced phenotypes in a DM1 Drosophila model.

Assessment of oxygen saturation in retinal vessels of normal subjects and diabetic patients with and without retinopathy using Flow Oximetry System.

PURPOSE: To assess oxygen saturation (StO2) in retinal vessels of normal subjects and diabetic patients with and without retinopathy using the modified version of the Flow Oximetry System (FOS) and a novel assessment software. METHODS: The FOS and novel assessment software were used to determine StO2 levels in arteries and veins located between 1 and 2 mm from the margin of the optic disc and in the macular area. RESULTS: Eighteen normal subjects, 15 diabetics without diabetic retinopathy (DM no DR), and 11 with non-proliferative diabetic retinopathy (NPDR) were included in final analysis. The mean [± standard deviation (SD)] StO2 in retinal arteries was 96.9%±3.8% in normal subjects; 97.4%±3.7% in DM no DR; and 98.4%±2.0% in NPDR. The mean venous StO2 was 57.5%±6.8% in normal subjects; 57.4%±7.5% in DM no DR; and 51.8%±6.8% in NPDR. The mean arterial and venous StO2 across the three groups were not statistically different (P=0.498 and P=0.071, respectively). The arterio-venous differences between the three study groups, however, were found to be statistically significant (P=0.015). Pairwise comparisons have demonstrated significant differences when comparing the A-V difference in the NPDR group to either normal subjects (P=0.02) or diabetic patients without DR (P=0.04). CONCLUSIONS: The arterio-venous difference was greater, and statistically significant, in patients with NPDR when compared to normal subjects and to patients with diabetes and no retinopathy. The mean venous StO2 was lower, but not statistically significant, in NPDR compared with diabetics without retinopathy and with normal subjects.

Targeting toxic RNAs that cause myotonic dystrophy type 1 (DM1) with a bisamidinium inhibitor.

A working hypothesis for the pathogenesis of myotonic dystrophy type 1 (DM1) involves the aberrant sequestration of an alternative splicing regulator, MBNL1, by expanded CUG repeats, r(CUG)(exp). It has been suggested that a reversal of the myotonia and potentially other symptoms of the DM1 disease can be achieved by inhibiting the toxic MBNL1-r(CUG)(exp) interaction. Using rational design, we discovered an RNA-groove binding inhibitor (ligand 3) that contains two triaminotriazine units connected by a bisamidinium linker. Ligand 3 binds r(CUG)12 with a low micromolar affinity (K(d) = 8 ± 2 µM) and disrupts the MBNL1-r(CUG)12 interaction in vitro (K(i) = 8 ± 2 µM). In addition, ligand 3 is cell and nucleus permeable, exhibits negligible toxicity to mammalian cells, dissolves MBNL1-r(CUG)(exp) ribonuclear foci, and restores misregulated splicing of IR and cTNT in a DM1 cell culture model. Importantly, suppression of r(CUG)(exp) RNA-induced toxicity in a DM1 Drosophila model was observed after treatment with ligand 3. These results suggest ligand 3 as a lead for the treatment of DM1.

Developing bivalent ligands to target CUG triplet repeats, the causative agent of myotonic dystrophy type 1.

An expanded CUG repeat transcript (CUG(exp)) is the causative agent of myotonic dystrophy type 1 (DM1) by sequestering muscleblind-like 1 protein (MBNL1), a regulator of alternative splicing. On the basis of a ligand (1) that was previously reported to be active in an in vitro assay, we present the synthesis of a small library containing 10 dimeric ligands (4-13) that differ in length, composition, and attachment point of the linking chain. The oligoamino linkers gave a greater gain in affinity for CUG RNA and were more effective when compared to oligoether linkers. The most potent in vitro ligand (9) was shown to be aqueous-soluble and both cell- and nucleus-permeable, displaying almost complete dispersion of MBNL1 ribonuclear foci in a DM1 cell model. Direct evidence for the bioactivity of 9 was observed in its ability to disperse ribonuclear foci in individual live DM1 model cells using time-lapse confocal fluorescence microscopy.

Three-dimensional phantoms for curvature correction in spatial frequency domain imaging.

The sensitivity to surface profile of non-contact optical imaging, such as spatial frequency domain imaging, may lead to incorrect measurements of optical properties and consequently erroneous extrapolation of physiological parameters of interest. Previous correction methods have focused on calibration-based, model-based, and computation-based approached. We propose an experimental method to correct the effect of surface profile on spectral images. Three-dimensional (3D) phantoms were built with acrylonitrile butadiene styrene (ABS) plastic using an accurate 3D imaging and an emergent 3D printing technique. In this study, our method was utilized for the correction of optical properties (absorption coefficient µ(a) and reduced scattering coefficient µ(s)') of objects obtained with a spatial frequency domain imaging system. The correction method was verified on three objects with simple to complex shapes. Incorrect optical properties due to surface with minimum 4 mm variation in height and 80 degree in slope were detected and improved, particularly for the absorption coefficients. The 3D phantom-based correction method is applicable for a wide range of purposes. The advantages and drawbacks of the 3D phantom-based correction methods are discussed in details.

Microfluidics based phantoms of superficial vascular network.

Several new bio-photonic techniques aim to measure flow in the human vasculature non-destructively. Some of these tools, such as laser speckle imaging or Doppler optical coherence tomography, are now reaching the clinical stage. Therefore appropriate calibration and validation techniques dedicated to these particular measurements are therefore of paramount importance. In this paper we introduce a fast prototyping technique based on laser micromachining for the fabrication of dynamic flow phantoms. Micro-channels smaller than 20 µm in width can be formed in a variety of materials such as epoxies, plastics, and household tape. Vasculature geometries can be easily and quickly modified to accommodate a particular experimental scenario.

Parameter discretization in two-dimensional continuous wavelet transform for fast fringe pattern analysis.

The two-dimensional continuous wavelet transform (2D-CWT) technique provides robust processing for digital fringe pattern analysis. To cope with the problem of long computation time, a concept called the cover map is introduced to speed up the 2D-CWT analysis. The cover map is constructed by discretizing the continuous dilation and rotation parameters. The discretized parameters help substantially reduce the processing time without affecting the analysis accuracy. The theories are presented and the validity and effectiveness of the proposed concept are demonstrated by computer simulation and real experiment.

Accuracy enhancement of digital image correlation with B-spline interpolation.

The interpolation algorithm plays an essential role in the digital image correlation (DIC) technique for shape, deformation, and motion measurements with subpixel accuracies. At the present, little effort has been made to improve the interpolation methods used in DIC. In this Letter, a family of recursive interpolation schemes based on B-spline representation and its inverse gradient weighting version is employed to enhance the accuracy of DIC analysis. Theories are introduced, and simulation results are presented to illustrate the effectiveness of the method as compared with the common bicubic interpolation.

Two-dimensional continuous wavelet transform for phase determination of complex interferograms.

A robust two-dimensional continuous wavelet transform (2D-CWT) technique for interferogram analysis is presented. To cope with the phase determination ambiguity issue encountered in the analysis of complex interferograms, a phase determination rule is proposed according to the phase distribution continuity, and a frequency-guided scheme is employed to obtain the correct phase distribution following a conventional 2D-CWT analysis. The theories are given in details, and the validity of the proposed technique is verified by computer simulation and real experiments.