Redox-Detecting Deep Learning for Mechanism Discernment in Cyclic Voltammograms of Multiple Redox Events.

In electrochemical analysis, mechanism assignment is fundamental to understanding the chemistry of a system. The detection and classification of electrochemical mechanisms in cyclic voltammetry set the foundation for subsequent quantitative evaluation and practical application, but are often based on relatively subjective visual analyses. Deep-learning (DL) techniques provide an alternative, automated means that can support experimentalists in mechanism assignment.

A subtype specific probe for targeted magnetic resonance imaging of M2 tumor-associated macrophages in brain tumors.

Pro-tumoral M2 tumor-associated macrophages (TAMs) play a critical role in the tumor immune microenvironment (TIME), making them an important therapeutic target for cancer treatment. Approaches for imaging and monitoring M2 TAMs, as well as tracking their changes in response to tumor progression or treatment are highly sought-after but remain underdeveloped. Here, we report an M2-targeted magnetic resonance imaging (MRI) probe based on sub-5 nm ultrafine iron oxide nanoparticles (uIONP), featuring an anti-biofouling coating to prevent non-specific macrophage uptake and an M2-specific peptide ligand (M2pep) for active targeting of M2 TAMs.

Seeing through "brain fog": neuroimaging assessment and imaging biomarkers for cancer-related cognitive impairments.

Advances in cancer diagnosis and treatment have substantially improved patient outcomes and survival in recent years. However, up to 75% of cancer patients and survivors, including those with non-central nervous system (non-CNS) cancers, suffer from "brain fog" or impairments in cognitive functions such as attention, memory, learning, and decision-making. While we recognize the impact of cancer-related cognitive impairment (CRCI), we have not fully investigated and understood the causes, mechanisms and interplays of various involving factors.

CryoSTAR: leveraging structural priors and constraints for cryo-EM heterogeneous reconstruction.

Resolving conformational heterogeneity in cryogenic electron microscopy datasets remains an important challenge in structural biology. Previous methods have often been restricted to working exclusively on volumetric densities, neglecting the potential of incorporating any preexisting structural knowledge as prior or constraints. Here we present cryoSTAR, which harnesses atomic model information as structural regularization to elucidate such heterogeneity.

Challenges of COVID-19 Case Forecasting in the US, 2020-2021.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org).

Hemodynamic property incorporated brain tumor segmentation by deep learning and density-based analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI).

Background: Magnetic resonance imaging (MRI) is a primary non-invasive imaging modality for tumor segmentation, leveraging its exceptional soft tissue contrast and high resolution. Current segmentation methods typically focus on structural MRI, such as T-weighted post-contrast-enhanced or fluid-attenuated inversion recovery (FLAIR) sequences. However, these methods overlook the blood perfusion and hemodynamic properties of tumors, readily derived from dynamic susceptibility contrast (DSC) enhanced MRI.

Autonomous closed-loop mechanistic investigation of molecular electrochemistry via automation.

Electrochemical research often requires stringent combinations of experimental parameters that are demanding to manually locate. Recent advances in automated instrumentation and machine-learning algorithms unlock the possibility for accelerated studies of electrochemical fundamentals via high-throughput, online decision-making. Here we report an autonomous electrochemical platform that implements an adaptive, closed-loop workflow for mechanistic investigation of molecular electrochemistry.

PhyGCN: Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning.

Hypergraphs are powerful tools for modeling complex interactions across various domains, including biomedicine. However, learning meaningful node representations from hypergraphs remains a challenge. Existing supervised methods often lack generalizability, thereby limiting their real-world applications.

Genetic impacts on nigral iron deposition in Parkinson's disease: A preliminary quantitative susceptibility mapping study.

Background: Dysfunction of iron metabolism, especially in substantia nigra (SN), is widely acknowledged in Parkinson's disease (PD), but the genetic influence on iron deposition remains largely unknown. Thus, in this study, we aimed to investigate potential genetic impacts on iron deposition in PD.

Methods: Seventy-four subjects, including 38 patients with PD and 36 age-matched normal controls, participated in this study.

Electrochemical Mechanistic Analysis from Cyclic Voltammograms Based on Deep Learning.

For decades, employing cyclic voltammetry for mechanistic investigation has demanded manual inspection of voltammograms. Here, we report a deep-learning-based algorithm that automatically analyzes cyclic voltammograms and designates a probable electrochemical mechanism among five of the most common ones in homogeneous molecular electrochemistry. The reported algorithm will aid researchers' mechanistic analyses, utilize otherwise elusive features in voltammograms, and experimentally observe the gradual mechanism transitions encountered in electrochemistry.

The protective role of cigarette smoking against Parkinson's disease via moderation of the interaction between iron deposition in the nigrostriatal pathway and clinical symptoms.

Background: Although cigarette smoking is a risk factor for multiple disorders, it has long been thought to protect against Parkinson's disease (PD). Quantitative susceptibility mapping (QSM) is a novel magnetic resonance imaging (MRI)-based technique for assessing iron accumulation that has been widely applied in PD studies. This study aimed to investigate how cigarette smoking affects clinical performance of PD using quantified iron deposition as a proxy for PD pathology.

Normalization effect of levodopa on hierarchical brain function in Parkinson's disease.

Hierarchical brain organization, in which the rich club and diverse club situate in core position, is critical for global information integration in the human brain network. Parkinson's disease (PD), a common movement disorder, has been conceptualized as a network disorder. Levodopa is an effective treatment for PD.

A multiple-tissue-specific magnetic resonance imaging model for diagnosing Parkinson's disease: a brain radiomics study.

Brain radiomics can reflect the characteristics of brain pathophysiology. However, the value of T1-weighted images, quantitative susceptibility mapping, and R2* mapping in the diagnosis of Parkinson's disease (PD) was underestimated in previous studies. In this prospective study to establish a model for PD diagnosis based on brain imaging information, we collected high-resolution T1-weighted images, R2* mapping, and quantitative susceptibility imaging data from 171 patients with PD and 179 healthy controls recruited from August 2014 to August 2019.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.

Cholinergic relevant functional reactivity is associated with dopamine responsiveness of tremor in Parkinson's disease.

Tremor in Parkinson's disease (PD) has distinct responsiveness to dopamine, which is supposed not be exclusively related to dopamine deficiency but has a close relationship with cholinergic system. This phenomenon indicates that cholinergic system may be an important regulatory for distinct dopamine responsiveness of parkinsonian tremor. Through investigating the alterations of cholinergic and dopaminergic network during levodopa administration, we aimed at exploring the mechanisms of differed dopamine responsiveness of parkinsonian tremor.

Case Report: Five Adult Cases of H3K27-Altered Diffuse Midline Glioma in the Spinal Cord.

Background: Diffuse midline glioma with H3K27-altered (DMG-H3K27a) is a novel tumor entity of the pediatric-type diffuse high-grade tumor in the latest WHO CNS 5. It mostly affects children and is only rarely found in adults. The tumor has a high level of aggressiveness, with a rapid progression and bad prognosis.

Dopamine depletion and subcortical dysfunction disrupt cortical synchronization and metastability affecting cognitive function in Parkinson's disease.

Parkinson's disease (PD) is primarily characterized by the loss of dopaminergic cells and atrophy in subcortical regions. However, the impact of these pathological changes on large-scale dynamic integration and segregation of the cortex are not well understood. In this study, we investigated the effect of subcortical dysfunction on cortical dynamics and cognition in PD.

Locus coeruleus degeneration is associated with disorganized functional topology in Parkinson's disease.

Degeneration of the locus coeruleus (LC) is recognized as a critical hallmark of Parkinson's disease (PD). Recent studies have reported that noradrenaline produced from the LC has critical effects on brain functional organization. However, it is unknown if LC degeneration in PD contributes to cognitive/motor manifestations through modulating brain functional organization.

Symptomology following mRNA vaccination against SARS-CoV-2.

Despite demonstrated efficacy of vaccines against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative agent of coronavirus disease-2019 (COVID-19), widespread hesitancy to vaccination persists. Improved knowledge regarding frequency, severity, and duration of vaccine-associated symptoms may help reduce hesitancy. In this prospective observational study, we studied 1032 healthcare workers who received both doses of the Pfizer-BioNTech SARS-CoV-2 mRNA vaccine and completed post-vaccine symptom surveys both after dose 1 and after dose 2.

Locus Coeruleus Degeneration Correlated with Levodopa Resistance in Parkinson's Disease: A Retrospective Analysis.

Background: The widely divergent responsiveness of Parkinson's disease (PD) patients to levodopa is an important clinical issue because of its relationship with quality of life and disease prognosis. Preliminary animal experiments have suggested that degeneration of the locus coeruleus (LC) attenuates the efficacy of levodopa treatment.

Objective: To explore the relationship between LC degeneration and levodopa responsiveness in PD patients in vivo.

Progressive microstructural alterations in subcortical nuclei in Parkinson's disease: A diffusion magnetic resonance imaging study.

Objectives: To explore the microstructural alterations in subcortical nuclei in Parkinson's disease (PD) at different stages with diffusion kurtosis imaging (DKI) and tensor imaging and to test the performance of diffusion metrics in identifying PD.

Methods: 108 PD patients (64 patients in early-stage PD group (EPD) and 44 patients in moderate-late-stage PD group (MLPD)) and 64 healthy controls (HC) were included. Tensor and kurtosis metrics in the subcortical nuclei were compared.

Serum Ceruloplasmin Depletion is Associated With Magnetic Resonance Evidence of Widespread Accumulation of Brain Iron in Parkinson's Disease.

Background: Excessive iron accumulation is one of the main pathogeneses of Parkinson's disease (PD). Ceruloplasmin plays an important role in keeping the iron homoeostasis.

Purpose: To explore the association between serum ceruloplasmin depletion and subcortical iron distribution in PD.

Longitudinal Macro/Microstructural Alterations of Different Callosal Subsections in Parkinson's Disease Using Connectivity-Based Parcellation.

Background: The corpus callosum (CC) is an important feature of Parkinson's disease (PD) not only in motor but also in non-motor functions. However, CC is not a homogeneous component, and the damage of specific subsection may contribute to corresponding clinical deficit.

Objective: The objective of the study is to investigate the structural alterations of different callosal subsections cross-sectionally and longitudinally in PD and evaluate their relationships to clinical performance.

COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support.

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed.