Layer 6 corticothalamic neurons induce high gamma oscillations through cortico-cortical and cortico-thalamo-cortical pathways.

Layer 6 corticothalamic (L6CT) neurons project to both cortex and thalamus, inducing multiple effects including the modulation of cortical and thalamic firing, and the emergence of high gamma oscillations in the cortical local field potential (LFP). We hypothesize that the high gamma oscillations driven by L6CT neuron activation reflect the dynamic engagement of intracortical and cortico-thalamo-cortical circuits. To test this, we optogenetically activated L6CT neurons in NTSR1-cre mice (both male and female) expressing channelrhodopsin-2 in L6CT neurons.

AI-informed retinal biomarkers predict 10-year risk of onset of multiple hematological malignancies.

Background: Early detection of hematological malignancies improves long-term survival but remains a critical challenge due to heterogeneity in clinical presentation. Chronic inflammation is a key driver in hematologic cancers and is known to induce compensatory microvascular changes. High-resolution, non-invasive retinal imaging can allow the quantification of microvascular changes for the early detection of hematological malignancies.

Association between correlated effective neural drive and electromechanical fluctuations during co-contraction: Insights from MU discharges and interference EMG.

This study investigated the correlation between the strength of correlated effective neural drive (END) to the antagonistic muscles and the fluctuations in neural/electrical and mechanical output around the joint during steady co-contraction, and whether the correlated END strength estimated from conventional surface EMG is correlated with that determined from motor unit (MU) discharges. Fourteen young male participants performed isometric steady co-contractions with their medial gastrocnemius and tibialis anterior muscles at 10% of maximal EMG while sitting. Correlated END strength was quantified as the maximum value of the cross-correlation function between the conventional surface EMG signals and between MU discharges decomposed from high-density surface EMG of each muscle.

33 Unresolved Questions in Nanoscience and Nanotechnology.

Significant advances in science and engineering often emerge at the intersections of disciplines. Nanoscience and nanotechnology are inherently interdisciplinary, uniting researchers from chemistry, physics, biology, medicine, materials science, and engineering. This convergence has fostered novel ways of thinking and enabled the development of materials, tools, and technologies that have transformed both basic and applied research, as well as how we address critical societal challenges.

Mechanosensing Pathways in the Progression of Pulmonary Fibrosis.

Fibrotic diseases are characterized by the excess production of extracellular matrix components that leads to changes in tissue mechanics and function. Mechanosensing altered during the onset of pulmonary fibrosis is hypothesized to form a positive-feedback loop that contributes to the progression of the disease. However, the exact mechanism(s) leading to fibrotic tissue remodeling as opposed to homeostatic tissue remodeling remains unknown.

Development of a microneedle patch for delivery of mRNA-lipid nanoparticles.

mRNA delivered by microneedle patch (MNP) can enable painless delivery, reduced need for healthcare expertise, and improved thermostability. In this study, we investigated formulation and manufacturing approaches for developing MNPs that deliver mRNA-loaded lipid nanoparticles (LNPs) encoding luciferase as a reporter protein during MNP fabrication and storage, including mRNA-LNP concentration, formulation, pH, excipients, and backing material. MNPs were assessed for mRNA-LNP size, encapsulation efficiency, and protein expression in vitro and in vivo.

Sustained Benefit of Short-Term Levodopa Treatment on Inner Retinal Function in Patients With Diabetes.

Purpose: This study investigated the long-term progression of oscillatory potential (OP) implicit times (ITs) in individuals with preclinical diabetic retinopathy (DR) with and without levodopa (L-DOPA) treatment by quantifying functional and structural retinal changes.

Methods: Participants from the Motz et al. (2020) study were re-evaluated after 5 years, including individuals with diabetes mellitus (DM) who received L-DOPA treatment for 2 weeks (the DM + L-DOPA group; n = 14), those who did not (the DM group; n = 6), and non-diabetic healthy controls (the control group; n = 37).

Dynamic DNA superstructures with emergent functions.

DNA nanotechnology enables the precise construction of intricate nanoscale structures. Over the past two decades, significant progress has been made in incorporating dynamic functionalities into these nanostructures. Concurrently, innovative strategies have emerged for their self-assembly and surface patterning into larger, more complex architectures.

Multi-centre Investigation of Cardiac Diffusion Tensor Imaging in Healthy Volunteers by SCMR Cardiac Diffusion Special Interest Group NETwork (SIGNET).

Background: Cardiac diffusion tensor imaging (cDTI) is an emerging technique for microstructural characterization of the heart and has shown clinical potential in a range of cardiomyopathies. However, there is substantial variation reported for in vivo cDTI results across the literature, and sensitivity of cDTI to differences in imaging sites, scanners, acquisition protocols and post-processing methods remains incompletely understood.

Methods: SIGNET is a prospective multi-centre, observational study in travelling and non-travelling healthy volunteers.

Oxygen-tunable endothelialized microvascular chip to assess hypoxia-reperfusion in sickle cell disease.

A better understanding of hypoxia reperfusion (H/R) injury is needed to gain deeper insight into the mechanisms driving sickle cell disease (SCD) pathophysiology. Existing and models have yet to fully explain H/R, which is typically associated with harmful inflammatory processes but has also been linked to a protective effect ameliorating subsequent severe vaso-occlusion. To address this need, we developed a novel microfluidic platform that includes three-dimensional endothelial-lined microchannels within an oxygen-tunable environment.

Advancing cell therapies with artificial intelligence and synthetic biology.

Artificial intelligence provides an exciting avenue to improve approaches in cell therapies by learning and predicting dynamic gene expression patterns from large datasets of stem cell differentiation. The integration of synthetic biology provides genetic tools that mimic the spatial and temporal expression patterns during differentiation, enhancing the potential to significantly improve differentiation outcomes and further our understanding of the mechanisms involved during cell fate decisions.

A case series of cerebrovascular abnormalities in Townes sickle cell mice visualized with magnetic resonance imaging and angiography.

Arterial complications in sickle cell disease (SCD), including stenoses and occlusions, are critical contributors to stroke. Townes SCD mice exhibit neurocognitive deficits and micro-vasculopathy, however stenoses and occlusions that could be causal to ischemic strokes have not yet been confirmed, which has led to challenges whether murine pathology reflects human pathology for strokes due to SCD. In our longitudinal study using label-free magnetic resonance angiography (MRA) to image carotid arteries in Townes SCD mice as they aged from 1 to 7 months, we identified multiple stenoses and occlusions consistent with abnormalities seen in individuals with SCD and stroke complications.

Fundus Photograph-Derived Computational Features Predict Risk of Cardiovascular Events in the Chronic Renal Insufficiency Cohort Clinical Observational Study.

Background: Patients with CKD face an elevated but variable risk of cardiovascular (CV) disease. Retinal imaging in CKD provides a non-invasive opportunity for CV risk stratification through microvascular analysis. The objective of this study was to evaluate retinal vascular features extracted via computer vision and machine learning approaches for CV risk and their added value over established risk calculators in CKD patients.

Spatial morphoproteomic features predict disease states from tissue architectures.

Understanding how immune cells organize within tissue microenvironments is essential for interpreting disease responses in spatial proteomics data. We introduce SNOWFLAKE, a graph neural network pipeline that integrates single-cell protein expression and morphological features to predict disease status from lymphoid follicles. Using a pediatric COVID-19 dataset, SNOWFLAKE outperformed conventional machine learning and deep learning approaches in classifying infection status.

Sparse learned kernels for interpretable and efficient medical time series processing.

Rapid, reliable and accurate interpretation of medical time series signals is crucial for high-stakes clinical decision-making. Deep learning methods offered unprecedented performance in medical signal processing but at a cost: they were compute intensive and lacked interpretability. We propose sparse mixture of learned kernels (SMoLK), an interpretable architecture for medical time series processing.

A deep learning derived prostate zonal volume-based biomarker from T2-weighted MRI to distinguish between prostate cancer and benign prostatic hyperplasia.

Background: Benign prostatic hyperplasia (BPH) and prostate cancer (PCa) share overlapping characteristics on magnetic resonance imaging (MRI), confounding the diagnosis and detection of PCa. There is thus a clinical need to accurately differentiate BPH-Only from BPH-PCa to prevent overdiagnosis and unnecessary biopsies. Although BPH and PCa may share overlapping features, they are distinct clinical entities.

Charting the path in rodent functional neuroimaging.

Driven by a period of accelerated progress and recent technical breakthroughs, whole-brain functional neuroimaging in rodents offers exciting new possibilities for addressing basic questions about brain function and its alterations. In response to lessons learned from the human neuroimaging community, leading scientists and researchers in the field convened to address existing barriers and outline ambitious goals for the future. This article captures these discussions, highlighting a shared vision to advance rodent functional neuroimaging into an era of increased impact.

The effects of locus coeruleus optogenetic stimulation on global spatiotemporal patterns in rats.

Whole-brain intrinsic activity as detected by resting-state fMRI can besummarized by three primary spatiotemporal patterns. These patterns have beenshown to change with different brain states, especially arousal. Thenoradrenergic locus coeruleus (LC) is a key node in arousal circuits and hasextensive projections throughout the brain, giving it neuromodulatory influenceover the coordinated activity of structurally separated regions.

Fabla: A voice-based ecological assessment method for securely collecting spoken responses to researcher questions.

This article reports on the validation of Fabla, a researcher-developed and university-hosted smartphone app that facilitates naturalistic and secure collection of participants' spoken responses to researcher questions. Fabla was developed to meet the need for tools that (a) collect longitudinal qualitative data and (b) capture speech biomarkers from participants' natural environments. This study put Fabla to its first empirical test using a repeated-measures experimental design in which participants (n = 87) completed a 1-week voice daily diary via the Fabla app, and an identical 1-week text-entry daily diary administered via Qualtrics, with diary method order counterbalanced and randomized.

Sensory neurostimulation promotes stress resilience with frequency-specificity.

Chronic stress is a major risk factor for neuropsychiatric disorders, acting via increased neuroinflammation and disrupted synaptic plasticity. While non-invasive visual or audiovisual neurostimulation (AV flicker) at 40Hz has been shown to modulate brain immune signaling and improve cognitive performance in mouse models of Alzheimer's disease, its effects in the context of stress remain unknown. Here we show that AV flicker protects against stress-induced behavioral, microglial, astrocytic, and synaptic changes in a sex- and frequency-specific manner.

Benchmarking the Impact of Anatomical Segmentation on In Vivo Magnetic Resonance Spectroscopy.

Purpose: Estimation of metabolite concentrations in brain magnetic resonance spectroscopy (MRS) requires correction for differences in tissue water content, relaxation properties, and the proportions of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). Accurate knowledge of the relative proportions of these tissue classes within the volume of interest is therefore essential for reliable quantification. Commonly used brain segmentation tools differ in their algorithms, priors, and implementation, potentially introducing variability in MRS-derived concentration estimates.

The effect of mRNA-lipid nanoparticle composition on stability during microneedle patch manufacturing.

Messenger RNA (mRNA) encapsulated in lipid nanoparticles (LNPs) is a potent technology with broad applications. Microneedle patches (MNPs) can enhance the accessibility of mRNA-LNPs for vaccination or therapeutic applications. We evaluated the effects of LNP composition on the stability of mRNA-LNPs before and after MNP manufacturing, as assessed by changes in mRNA-LNP size, encapsulation efficiency, and protein expression in vitro and in vivo.