Publications by authors named "Aneysis D Gonzalez-Suarez"

Background: The surgical methods used to resect sacral tumors are extensive and require maneuvering through complex anatomical systems such as the pelvic organs and sacral nerve roots. These procedures may result in complications and adverse patient outcomes. The technology integrating 3D reconstruction models in the field of spine surgery is rapidly evolving, and these challenging cases present a unique opportunity to leverage this technology's capability for enhanced patient outcomes.

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Despite the growing diversity of the U.S. population, racial and ethnic minorities remain underrepresented in healthcare professions, perpetuating health disparities.

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Background: Nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly prescribed for postoperative pain management after spinal fusion surgeries, but their potential impact on fusion outcomes and wound healing remains controversial.

Objective: To use a national database and consistent selection criteria to compare the postoperative outcomes of patients who first received NSAIDs ≤ 72 hours, 72 hours to 90 days, and 90 days to 1 year after posterior lumbar fusion (PLF) surgery, to those who never received NSAIDs within the first year of surgery.

Methods: Using the Merative Marketscan Research Databases, we analyzed PLF patients aged 18 to 90 years who underwent either single- and multilevel fusions.

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Longitudinal physical activity monitoring is a novel and promising objective outcome measure for patients with degenerative spine disorder (DSD) that currently lacks established standards for data collection and interpretation. Here, we monitored 100 patients with DSD with the Apple Watch to establish the optimal duration and pattern of step count monitoring needed to estimate their weekly physical activity before their elective surgery. Participants were predominantly female (65.

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Objective: In the digital age, patients turn to online sources for lumbar spine fusion information, necessitating a careful study of large language models (LLMs) like chat generative pre-trained transformer (ChatGPT) for patient education.

Methods: Our study aims to assess the response quality of Open AI (artificial intelligence)'s ChatGPT 3.5 and Google's Bard to patient questions on lumbar spine fusion surgery.

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Article Synopsis
  • The study investigates how machine learning models, particularly Gradient Boosting Machine (GBM), can better predict readmission rates after posterior cervical fusion (PCF) compared to traditional logistic regression (LR).
  • Using data from 4,130 patients who underwent PCF, it was found that patient discharge status and comorbidities significantly influenced readmission predictions.
  • The GBM model outperformed the LR model in accuracy and also projected greater cost savings, suggesting that machine learning can provide more effective tools for predicting patient readmissions in healthcare.
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Study Design/setting: Prospective cohort study.

Objective: To use a commercial wearable device to measure real-life, continuous physical activity in patients with CS and to establish age-adjusted and sex-adjusted standardized scores.

Summary Of Background Data: Patients with cervical spondylosis (CS) often present with pain or neurologic deficits that result in functional limitations and inactivity.

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Neurons integrate excitatory and inhibitory signals to produce their outputs, but the role of input timing in this integration remains poorly understood. Motion detection is a paradigmatic example of this integration, since theories of motion detection rely on different delays in visual signals. These delays allow circuits to compare scenes at different times to calculate the direction and speed of motion.

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Excitatory Amino Acid Transporters (EAATs) are plasma membrane proteins responsible for maintenance of low extracellular concentrations of glutamate in the CNS. Dysfunction in their activity is implicated in various neurological disorders. Glutamate transport by EAATs occurs through the movement of the central transport domain relative to the scaffold domain in the EAAT membrane protein.

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Previous work has characterized how walking coordinate the movements of individual limbs (DeAngelis et al., 2019). To understand the circuit basis of this coordination, one must characterize how sensory feedback from each limb affects walking behavior.

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In visual systems, neurons adapt both to the mean light level and to the range of light levels, or the contrast. Contrast adaptation has been studied extensively, but it remains unclear how it is distributed among neurons in connected circuits, and how early adaptation affects subsequent computations. Here, we investigated temporal contrast adaptation in neurons across Drosophila's visual motion circuitry.

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Today, we understand peptide transmitters to be signaling molecules that modulate neural activity. However, in 1982 little was known about neuropeptides and their role in neural communication. The influential 1982 paper by Jan and Jan reported definitive evidence that a presynaptically released neuropeptide evokes postsynaptic responses in an identified cholinergic synapse, thereby fueling a new era in neuroscience.

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Excitatory amino acid transporters (EAATs) are secondary active transporters of L-glutamate and L- or D-aspartate. These carriers also mediate a thermodynamically uncoupled anion conductance that is gated by Na and substrate binding. The activation of the anion channel by binding of Na alone, however, has only been demonstrated for mammalian EAAC1 (EAAT3) and EAAT4.

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Advances in structure-function analyses and computational biology have enabled a deeper understanding of how excitatory amino acid transporters (EAATs) mediate chloride permeation and substrate transport. However, the mechanism of structural coupling between these functions remains to be established. Using a combination of molecular modeling, substituted cysteine accessibility, electrophysiology and glutamate uptake assays, we identified a chloride-channeling conformer, S, transiently accessible as EAAT1 reconfigures from substrate/ion-loaded into a substrate-releasing conformer.

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