Aging and the Spectral Properties of Brain Hemodynamics.

Cerebral glucose metabolism (CMRGlc) systematically decreases with advancing age. We sought to identify correlates of decreased CMRGlc in the spectral properties of fMRI signals imaged in the task-free state. We analyzed lifespan resting-state fMRI data acquired in 455 healthy adults (ages 18-87 years) and cerebral metabolic data acquired in a separate cohort of 94 healthy adults (ages 25-45 years, 65-85 years).

Perioperative Antibiotic Choice Does Not Affect Wound Complications in the Operative Treatment of Ankle Fractures.

Background and aims Ankle injuries are one of the most common lower extremity traumas reported, with nearly half needing surgical intervention. For those who undergo surgical treatment, surgical site infection (SSI) is not a rare complication. Cefazolin is the recommended preoperative surgical chemoprophylaxis for surgical site infection.

Individual-level metabolic connectivity from dynamic [F]FDG PET reveals glioma-induced impairments in brain architecture and offers novel insights beyond the SUVR clinical standard.

Purpose: This study evaluates the potential of within-individual Metabolic Connectivity (wi-MC), from dynamic [F]FDG PET data, based on the Euclidean Similarity method. This approach leverages the biological information of the tracer's full temporal dynamics, enabling the direct extraction of individual metabolic connectomes. Specifically, the proposed framework, applied to glioma pathology, seeks to assess sensitivity to metabolic dysfunctions in the whole brain, while simultaneously providing further insights into the pathophysiological mechanisms regulating glioma progression.

The brain's "dark energy" puzzle : [F]FDG uptake, delivery and phosphorylation, and their coupling with resting-state brain activity.

The brain's resting-state energy consumption is expected to be mainly driven by spontaneous activity. In our previous work, we extracted a wide range of features from resting-state fMRI (rs-fMRI), and used them to predict [F]FDG PET SUVR as a proxy of glucose metabolism. Here, we expanded upon our previous effort by estimating [F]FDG kinetic parameters according to Sokoloff's model, i.

Hyperglycemia selectively increases cerebral non-oxidative glucose consumption without affecting blood flow.

Multiple studies have shown that hyperglycemia increases the cerebral metabolic rate of glucose (CMRglc) in subcortical white matter. This observation remains unexplained. Using positron emission tomography (PET) and euinsulinaemic glucose clamps, we found, for the first time, that acute hyperglycemia increases non-oxidative CMRglc (i.

Smoking and alcohol by HPV status in head and neck cancer: a Mendelian randomization study.

HPV-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) are recognized as distinct entities. There remains uncertainty surrounding the causal effects of smoking and alcohol on the development of these two cancer types. Here we perform multivariable Mendelian randomization (MR) to evaluate the causal effects of smoking and alcohol on the risk of HPV-positive and HPV-negative HNSCC in 3431 cases and 3469 controls.

Complexity organization of resting-state functional-MRI networks.

Entropy measures are increasingly being used to analyze the structure of neural activity observed by functional magnetic resonance imaging (fMRI), with resting-state networks (RSNs) being of interest for their reproducible descriptions of the brain's functional architecture. Temporal correlations have shown a dichotomy among these networks: those that engage with the environment, known as extrinsic, which include the visual and sensorimotor networks; and those associated with executive control and self-referencing, known as intrinsic, which include the default mode network and the frontoparietal control network. While these inter-voxel temporal correlations enable the assessment of synchrony among the components of individual networks, entropic measures introduce an intra-voxel assessment that quantifies signal features encoded within each blood oxygen level-dependent (BOLD) time series.

The role of dupilumab in the treatment of eosinophilic esophagitis.

Dupilumab has been approved to treat a variety of atopic disorders and was the first US FDA-approved medication for the treatment of eosinophilic esophagitis (EoE), initially approved in May 2022, with expansion in use to patients as young as 1 year of age weighing at least 15 kg in January 2024. It is a fully human monoclonal antibody that inhibits both IL-4 and IL-13 signaling, suppressing TH2-mediated proinflammatory cytokines, chemokines and IgE implicated in EoE pathogenesis. Phase II and III trials in EoE have demonstrated histologic, endoscopic and symptomatic improvement in disease activity with an overall favorable safety profile.

Clinical Predictors of Cisplatin Chemoradiation-Induced Ototoxicity in HPV-Positive Oropharyngeal Squamous Cell Carcinoma: A Case-Control Study.

Background: Cisplatin-based chemoradiation is a standard treatment for many patients with human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC), an etiologically distinct subset of head and neck cancer. Although associated with good long-term survival, clinical risk factors for ototoxicity have been understudied in this population. This study aimed to evaluate clinical predictors associated with ototoxicity in HPV-positive OPSCC patients treated with cisplatin chemoradiation.

Multi-Tracer Studies of Brain Oxygen and Glucose Metabolism Using a Time-of-Flight Positron Emission Tomography - Computed Tomography Scanner.

The authors have developed a paradigm using positron emission tomography (PET) with multiple radiopharmaceutical tracers that combines measurements of cerebral metabolic rate of glucose (CMRGlc), cerebral metabolic rate of oxygen (CMRO2), cerebral blood flow (CBF), and cerebral blood volume (CBV), culminating in estimates of brain aerobic glycolysis (AG). These in vivo estimates of oxidative and non-oxidative glucose metabolism are pertinent to the study of the human brain in health and disease. The latest positron emission tomography-computed tomography (PET-CT) scanners provide time-of-flight (TOF) imaging and critical improvements in spatial resolution and reduction of artifacts.

Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.

Purpose: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care.

Data-driven decomposition and staging of flortaucipir uptake in Alzheimer's disease.

Introduction: Previous approaches pursuing in vivo staging of tau pathology in Alzheimer's disease (AD) have typically relied on neuropathologically defined criteria. In using predefined systems, these studies may miss spatial deposition patterns which are informative of disease progression.

Methods: We selected discovery (n = 418) and replication (n = 132) cohorts with flortaucipir imaging.

Impact of molecular symmetry on crystallization pathways in highly supersaturated KHPO solutions.

Solute structure and its evolution in supersaturated aqueous solutions are key clues to understand Ostwald's step rule. Here, we measure the structural evolution of solute molecules in highly supersaturated solutions of KHPO (KDP) and NHHPO (ADP) using a combination of electrostatic levitation and synchrotron X-ray scattering. The measurement reveals the existence of a solution-solution transition in KDP solution, caused by changing molecular symmetries and structural evolution of the solution with supersaturation.

The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity?

Brain glucose metabolism, which can be investigated at the macroscale level with [F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown.

The Impact of Screening for Perioperative ICU Admission in Geriatric Hip Fracture Patients: A Retrospective Analysis.

Background: Hip fracture patients are a subset of trauma patients with high peri-operative mortality. To mitigate the mortality risk, the use of predictive scoring systems (e.g.

Patterns of Glucose Metabolism in [ F]FDG PET Indicate Regional Variability and Neurodegeneration in the Progression of Alzheimer's Dementia.

Unlabelled: In disorders of cognitive impairment, such as Alzheimer's disease, neurodegeneration is the final common pathway of disease progression. Modulating, reversing, or preventing disease progression is a clinical imperative most likely to succeed following accurate and explanatory understanding of neurodegeneration, requiring enhanced consistency with quantitative measurements and expanded interpretability of complex data. The on-going study of neurodegeneration has robustly demonstrated the advantages of accumulating large amounts of clinical data that include neuroimaging, motiving multi-center studies such as the Alzheimer's Disease Neuroimaging Initiative (ADNI).

Glioblastoma induces whole-brain spectral change in resting state fMRI: Associations with clinical comorbidities and overall survival.

Glioblastoma, a highly aggressive form of brain tumor, is a brain-wide disease. We evaluated the impact of tumor burden on whole brain resting-state functional magnetic resonance imaging (rs-fMRI) activity. Specifically, we analyzed rs-fMRI signals in the temporal frequency domain in terms of the power-law exponent and fractional amplitude of low-frequency fluctuations (fALFF).

A new framework for metabolic connectivity mapping using bolus [F]FDG PET and kinetic modeling.

Metabolic connectivity (MC) has been previously proposed as the covariation of static [F]FDG PET images across participants, i.e., MC (ai-MC).

Structural gray matter alterations in glioblastoma and high-grade glioma-A potential biomarker of survival.

Background: Patients with glioblastoma (GBM) and high-grade glioma (HGG, World Health Organization [WHO] grade IV glioma) have a poor prognosis. Consequently, there is an unmet clinical need for accessible and noninvasively acquired predictive biomarkers of overall survival in patients. This study evaluated morphological changes in the brain separated from the tumor invasion site (ie, contralateral hemisphere).

Murine model for chronic rhinosinusitis: an interventional study.

Background: Chronic rhinosinusitis (CRS) is a complex inflammatory disease of the sinonasal tract. To understand this disease entity and develop targeted treatments, a reproducible animal model is paramount.

Aims/objectives: To optimize a murine model of eosinophilic CRS by establishing benchmark histological markers and validate its fidelity in evaluating intranasal treatments.

Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learning.

Objective: Resting-state functional MRI (RS-fMRI) enables the mapping of function within the brain and is emerging as an efficient tool for the presurgical evaluation of eloquent cortex. Models capable of reliable and precise mapping of resting-state networks (RSNs) with a reduced scanning time would lead to improved patient comfort while reducing the cost per scan. The aims of the present study were to develop a deep 3D convolutional neural network (3DCNN) capable of voxel-wise mapping of language (LAN) and motor (MOT) RSNs with minimal quantities of RS-fMRI data.