Objective Detection of Newborn Infant Acute Procedural Pain Using EEG and Machine Learning Algorithms.

Observer-dependent infant pain scales have limitations including discontinuous assessments and the lack of healthcare professionals' availability. We hypothesized that applying agnostic machine learning approaches to neonatal electroencephalographic (EEG) analysis may reveal features of the infant response to acute pain. EEG was recorded from 30 neonates undergoing acutely painful procedures (18 males, 34.

Multiple pathways to the evolution of positive assortment in aggregative multicellularity.

The evolutionary transition to multicellularity requires shifting the primary unit of selection from cells to multicellular collectives. How this occurs in aggregative organisms remains poorly understood. Clonal development provides a direct path to multicellular adaptation through genetic identity between cells, but aggregative organisms face a constraint: selection on collective-level traits cannot drive adaptation without positive genetic assortment.

Feasibility of assessing cognitive impairment via distributed camera network and privacy-preserving edge computing.

Introduction: Mild cognitive impairment (MCI) involves cognitive decline beyond normal age and education expectations. It correlates with decreased socialization and increased aimless motion. We aim to automate detection of these behaviors for improved longitudinal monitoring.

CSF proteomics reveals changes in myelin and synaptic biology after Spectris treatment.

Introduction: Brain steady-state gamma oscillations evoked using a non-invasive medical device (Spectris) have shown potential clinical benefits in patients with mild-moderate Alzheimer's disease (AD), including reduced functional and cognitive decline, reduced brain volume and myelin loss, and increased brain functional connectivity. We analyzed changes in cerebrospinal fluid (CSF) proteins after Spectris treatment in mild cognitive impairment (MCI) and their relationship to established biological pathways implicated in AD.

Methods: Unbiased proteomic analysis of CSF samples from participants with amyloid-positive MCI ( = 10) was conducted from the FLICKER (NCT03543878) clinical trial.

The Shift to Over-the-Counter Diagnostic Testing After RADx: Clinical, Regulatory, and Societal Implications.

The National Institutes of Health's Rapid Acceleration of Diagnostics (RADx) program answered the call to accelerate the development of point-of-care (POC) and over-the-counter (OTC) COVID-19 tests. The widespread availability and access to self-tests has increased the public's familiarity and acceptance of at-home diagnostics. This paper examines the current state of OTC diagnostic testing, discusses potential applications of OTC testing, and highlights the implications of widespread OTC testing for clinical medicine.

Intracellular Biomacromolecule Delivery by Stimuli-Responsive Protein Vesicles Loaded by Hydrophobic Ion Pairing.

Proteins can perform ideal therapeutic functions. However, their large size and significant surface hydrophilicity and charge prohibit them from reaching intracellular targets. These chemical features also render them poorly encapsulated by nanoparticles used for intracellular delivery.

Insights into the electronic, magnetic structure, and photocatalytic activity of YCuMnO double perovskite.

This research aims to develop YCuMnO double perovskite, using a citrate auto combustion method, to be used as a photocatalyst for the degradation of organic dyes and antibiotics. XRD and Raman characterization revealed the synthesis of pure-phase YCuMnO double perovskite. The X-ray photoelectron spectroscopy results show the presence of +4 and +2 oxidation states of Mn and Cu ions.

MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models.

The recent prevalence of publicly accessible, large medical imaging datasets has led to a proliferation of artificial intelligence (AI) models for cardiovascular image classification and analysis. At the same time, the potentially significant impacts of these models have motivated the development of a range of explainable AI (XAI) methods that aim to explain model predictions given certain image inputs. However, many of these methods are not developed or evaluated with domain experts, and explanations are not contextualized in terms of medical expertise or domain knowledge.

Automatic medical imaging segmentation via self-supervising large-scale convolutional neural networks.

Purpose: This study aims to develop a robust, large-scale deep learning model for medical image segmentation, leveraging self-supervised learning to overcome the limitations of supervised learning and data variability in clinical settings.

Methods And Materials: We curated a substantial multi-center CT dataset for self-supervised pre-training using masked image modeling with sparse submanifold convolution. We designed a series of Sparse Submanifold U-Nets (SS-UNets) of varying sizes and performed self-supervised pre-training.

Embed systemic equity throughout industrial ecology applications: How to address machine learning unfairness and bias.

Recent calls have been made for equity tools and frameworks to be integrated throughout the research and design life cycle -from conception to implementation-with an emphasis on reducing inequity in artificial intelligence (AI) and machine learning (ML) applications. Simply stating that equity should be integrated throughout, however, leaves much to be desired as industrial ecology (IE) researchers, practitioners, and decision-makers attempt to employ equitable practices. In this forum piece, we use a critical review approach to explain how socioecological inequities emerge in ML applications across their life cycle stages by leveraging the food system.

CF-Functionalized Side Chains in Nonfullerene Acceptors Promote Electrostatic Interactions for Highly Efficient Organic Solar Cells.

The advent of next-generation nonfullerene acceptors (NFAs) has propelled major advances in organic solar cells (OSCs). Here we report an NFA design incorporating CF-terminated side chains having varying -(CH)-CF linker lengths ( = 1, 2, and 3) which introduce new intermolecular interactions, hence strong modulation of the photovoltaic response. We report a systematic comparison and contrast characterization of this NFA series with a comprehensive set of chemical/physical techniques versus the heavily studied third-generation NFA, Y6, revealing distinctive and beneficial properties of this new NFA series.

Carbon Mineralization in Fractured Mafic and Ultramafic Rocks: A Review.

Mineral carbon storage in mafic and ultramafic rock masses has the potential to be an effective and permanent mechanism to reduce anthropogenic CO. Several successful pilot-scale projects have been carried out in basaltic rock (e.g.

Single immunization with an influenza hemagglutinin nanoparticle-based vaccine elicits durable protective immunity.

Vaccination is the most effective strategy to combat influenza. Ideally, potent and persistent vaccine effects would be induced with a single vaccine dose. Here, we designed a virus-like particle (VLP)-based vaccine presenting multiple copies of the influenza hemagglutinin (HA) from A/Puerto Rico/8/1934 (PR8HA-VLP) and examined its immunogenicity and protective efficacy in ferrets.

A transcriptome atlas of zygotic and somatic embryogenesis in Norway spruce.

Somatic embryogenesis (SE) is a powerful model system for studying embryo development and an important method for scaling up availability of elite and climate-adapted genetic material of Norway spruce (Picea abies L. Karst). However, there are several steps during the development of the somatic embryo (Sem) that are suboptimal compared to zygotic embryo (Zem) development.

Ecometrics demonstrates that the functional dental traits of carnivoran communities are filtered by climate.

Terrestrial carnivorans, with their diverse diets and unique adaptations such as the carnassial tooth, offer insights into the connections between functional traits and the climatic and environmental conditions they inhabit. They shed light on functional trait-environment relationships at the highest trophic levels across a broad range of environmental conditions. In this study, we evaluate the relationship between relative blade length (RBL) of the lower carnassial tooth, a key dietary adaptation among terrestrial carnivorans for slicing and grinding food items, and climate.

PPARγ/ETV2 axis regulates endothelial-to-mesenchymal transition in pulmonary hypertension.

Endothelial-to-mesenchymal transition (EndoMT) plays an important role in pulmonary hypertension (PH) but the molecular mechanisms regulating EndoMT remain to be defined. We demonstrate that the axis of the transcription factors PPARγ (Peroxisome Proliferator-Activated Receptor gamma) and ETV2 (ETS variant 2) play important roles in the pathogenesis of PH. Decreased levels of the expression of PPARγ and ETV2 along with reduced endothelial and increased EndoMT markers are consistently observed in lungs and pulmonary artery endothelial cells (PAECs) of idiopathic pulmonary arterial hypertension patients, in hypoxia-exposed mouse lungs, human PAECs, and in induced-EndoMT cells.

A resource of identified and annotated lincRNAs expressed during somatic embryogenesis development in Norway spruce.

Long non-coding RNAs (lncRNAs) have emerged as important regulators of many biological processes, although their regulatory roles remain poorly characterized in woody plants, especially in gymnosperms. A major challenge of working with lncRNAs is to assign functional annotations, since they have a low coding potential and low cross-species conservation. We utilised an existing RNA-Sequencing resource and performed short RNA sequencing of somatic embryogenesis developmental stages in Norway spruce (Picea abies L.

Thermodynamic limits of the depolymerization of poly(olefin)s using mechanochemistry.

Mechanochemistry is a promising approach for chemical recycling of commodity plastics, and in some cases depolymerization to the monomer(s) has been reported. However, while poly(olefin)s comprise the largest share of global commodity plastics, mechanochemical depolymerization of these polymers in standard laboratory-scale ball mill reactors suffers from slow rates. In this work, the observed reactivities of poly(styrene), poly(ethylene) and poly(propylene) are rationalized on the basis of thermodynamic limitations of their depolymerization by depropagation of free radical intermediates.

A physics-aware neural network for protein-ligand interactions with quantum chemical accuracy.

Quantifying intermolecular interactions with quantum chemistry (QC) is useful for many chemical problems, including understanding the nature of protein-ligand interactions. Unfortunately, QC computations on protein-ligand systems are too computationally expensive for most use cases. The flourishing field of machine-learned (ML) potentials is a promising solution, but it is limited by an inability to easily capture long range, non-local interactions.

Dual exposure-by-polygenic score interactions highlight disparities across social groups in the proportion needed to benefit.

The transferability of polygenic scores across population groups is a major concern with respect to the equitable clinical implementation of genomic medicine. Since genetic associations are identified relative to the population mean, inevitably differences in disease or trait prevalence among social strata influence the relationship between PGS and risk. Here we quantify the magnitude of PGS-by-Exposure (PGSxE) interactions for seven human diseases (coronary artery disease, type 2 diabetes, obesity thresholded to body mass index and to waist-to-hip ratio, inflammatory bowel disease, chronic kidney disease, and asthma) and pairs of 75 exposures in the White-British subset of the UK Biobank study (n=408,801).

Building Digital Twins for Cardiovascular Health: From Principles to Clinical Impact.

The past several decades have seen rapid advances in diagnosis and treatment of cardiovascular diseases and stroke, enabled by technological breakthroughs in imaging, genomics, and physiological monitoring, coupled with therapeutic interventions. We now face the challenge of how to (1) rapidly process large, complex multimodal and multiscale medical measurements; (2) map all available data streams to the trajectories of disease states over the patient's lifetime; and (3) apply this information for optimal clinical interventions and outcomes. Here we review new advances that may address these challenges using digital twin technology to fulfill the promise of personalized cardiovascular medical practice.

Tolerability of a piezoelectric microneedle electroporator in human subjects.

Electroporation, or the use of electric pulses to facilitate the intracellular delivery of DNA, RNA, and other molecules, is a well-established technique, that has been demonstrated to significantly augment the immunogenicity of DNA/mRNA vaccines and therapeutics. However, the clinical translation of traditional electroporators has been limited due to high costs, large size, complex user operation, and poor tolerability in humans due to nerve stimulation. In prior work, we introduced ePatch: an ultra-low-cost, handheld, battery-free electroporator employing a piezoelectric pulser coupled with a microneedle electrode array that showed enhanced immunogenic responses to an intradermal SARS-CoV-2 DNA vaccine in mice.

Feasibility of engineered for use as a microbiome-based topical drug delivery platform.

Non-adherence to medication is a major challenge in healthcare that results in worsened treatment outcomes for patients. Reducing the frequency of required administrations could improve adherence but is challenging for topical drug delivery due to the generally short residence time of topical formulations on the skin. In this study, we sought to determine the feasibility of developing a microbiome-based, long-acting, topical delivery platform using for drug production and delivery on the skin, which was assessed using green fluorescent protein as a model heterologous protein for delivery.

Viscoelastic blood coagulation testing system enabled by a non-contact triboelectric angle sensor.

Thromboelastography (TEG) remains a convenient and effective viscoelastic blood coagulation testing device for guiding blood component transfusion and assessing the risk of thrombosis. Here, a TEG enabled by a non-contact triboelectric angle sensor (NTAS) with a small size (∼7 cm) is developed for assessing the blood coagulation system. With the assistance of a superelastic torsion wire structure, the NTAS-TEG realizes the detection of blood viscoelasticity.

Deep-learning enabled smart insole system aiming for multifunctional foot-healthcare applications.

Real-time foot pressure monitoring using wearable smart systems, with comprehensive foot health monitoring and analysis, can enhance quality of life and prevent foot-related diseases. However, traditional smart insole solutions that rely on basic data analysis methods of manual feature extraction are limited to real-time plantar pressure mapping and gait analysis, failing to meet the diverse needs of users for comprehensive foot healthcare. To address this, we propose a deep learning-enabled smart insole system comprising a plantar pressure sensing insole, portable circuit board, deep learning and data analysis blocks, and software interface.