Ocular pharmacology

Ophthalmic diseases include both those analogous to systemic diseases (eg, inflammation, infection, neuronal degeneration) and not analogous (eg, cataract, myopia). Many anterior segment diseases are treated pharmacologically through eye drops, which have an implied therapeutic index of local therapy. Unlike oral dosage forms administered for systemic diseases, eyedrops require patients not only to adhere to treatment, but to be able to accurately perform—ie, instill drops correctly.Anatomical and physiological barriers make topical delivery to the anterior chamber challenging—in some cases more challenging than absorption through the skin, nasal passages, or gut. Treatment of the posterior segment (eg, vitreous, retina, choroid, and optic nerve) is more challenging due to additional barriers. Recently, intravitreal injections have become a standard of care with biologics for the treatment of macular degeneration and other diseases. Although the eye has esterases, hydroxylases, and transporters, it has relatively little CYP450 enzymes. Because it is challenging to obtain drug concentrations at the target site, ocular clinical pharmacokinetics, and thus pharmacokinetic‐pharmacodynamic interactions, are rarely available. Ophthalmic pharmaceuticals require consideration of solubility, physiological pH, and osmolarity, as well as sterility and stability, which in turn requires optimal pharmaceutics. Although applied locally, ocular medications may be absorbed systemically, which results in morbidity and mortality (eg, systemic hypotension, bronchospasm, and bradycardia).Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136697/1/jcph634_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136697/2/jcph634.pd

An automatic gait analysis pipeline for wearable sensors: a pilot study in Parkinson’s disease

The use of wearable sensors allows continuous recordings of physical activity from participants in free-living or at-home clinical studies. The large amount of data collected demands automatic analysis pipelines to extract gait parameters that can be used as clinical endpoints. We introduce a deep learning-based automatic pipeline for wearables that processes tri-axial accelerometry data and extracts gait events—bout segmentation, initial contact (IC), and final contact (FC)—from a single sensor located at either the lower back (near L5), shin or wrist. The gait events detected are posteriorly used for gait parameter estimation, such as step time, length, and symmetry. We report results from a leave-one-subject-out (LOSO) validation on a pilot study dataset of five participants clinically diagnosed with Parkinson’s disease (PD) and six healthy controls (HC). Participants wore sensors at three body locations and walked on a pressure-sensing walkway to obtain reference gait data. Mean absolute errors (MAE) for the IC events ranged from 22.82 to 33.09 milliseconds (msecs) for the lower back sensor while for the shin and wrist sensors, MAE ranges were 28.56–64.66 and 40.19–72.50 msecs, respectively. For the FC-event detection, MAE ranges were 29.06–48.42, 40.19–72.70 and 36.06–60.18 msecs for the lumbar, wrist and shin sensors, respectively. Intraclass correlation coefficients, ICC(2,k), between the estimated parameters and the reference data resulted in good-to-excellent agreement (ICC ≥ 0.84) for the lumbar and shin sensors, excluding the double support time (ICC = 0.37 lumbar and 0.38 shin) and swing time (ICC = 0.55 lumbar and 0.59 shin). The wrist sensor also showed good agreements, but the ICCs were lower overall than for the other two sensors. Our proposed analysis pipeline has the potential to extract up to 100 gait-related parameters, and we expect our contribution will further support developments in the fields of wearable sensors, digital health, and remote monitoring in clinical trials

Craniux: A LabVIEW-Based Modular Software Framework for Brain-Machine Interface Research

This paper presents “Craniux,” an open-access, open-source software framework for brain-machine interface (BMI) research. Developed in LabVIEW, a high-level graphical programming environment, Craniux offers both out-of-the-box functionality and a modular BMI software framework that is easily extendable. Specifically, it allows researchers to take advantage of multiple features inherent to the LabVIEW environment for on-the-fly data visualization, parallel processing, multithreading, and data saving. This paper introduces the basic features and system architecture of Craniux and describes the validation of the system under real-time BMI operation using simulated and real electrocorticographic (ECoG) signals. Our results indicate that Craniux is able to operate consistently in real time, enabling a seamless work flow to achieve brain control of cursor movement. The Craniux software framework is made available to the scientific research community to provide a LabVIEW-based BMI software platform for future BMI research and development

Communication Predicts Medication Self-Efficacy in Glaucoma Patients

Medication self-efficacy, or patients’ confidence that they can perform medication-related behaviors, is associated with better glaucoma medication adherence. Little is known about how to enhance glaucoma patients’ medication self-efficacy. Our purpose is to examine whether patient-provider communication increases glaucoma patients’ medication self-efficacy

Caveolin 1 is overexpressed and amplified in a subset of basal-like and metaplastic breast carcinomas: a morphologic, ultrastructural, immunohistochemical, and in situ hybridization analysis

The distribution and significance of caveolin 1 (CAV1) expression in different breast cell types and role in breast carcinogenesis remain poorly understood. Both tumor-suppressive and oncogenic roles have been proposed for this protein. The aims of this study were to characterize the distribution of CAV1 in normal breast, benign breast lesions, breast cancer precursors, and metaplastic breast carcinomas; to assess the prognostic significance of CAV1 expression in invasive breast carcinomas; and to define whether CAV1 gene amplification is the underlying genetic mechanism driving CAV1 overexpression in breast carcinomas. Purpose: The distribution and significance of caveolin 1 (CAV1) expression in different breast cell types and role in breast carcinogenesis remain poorly understood. Both tumor-suppressive and oncogenic roles have been proposed for this protein. The aims of this study were to characterize the distribution of CAV1 in normal breast, benign breast lesions, breast cancer precursors, and metaplastic breast carcinomas; to assess the prognostic significance of CAV1 expression in invasive breast carcinomas; and to define whether CAV1 gene amplification is the underlying genetic mechanism driving CAV1 overexpression in breast carcinomas. Experimental Design: CAV1 distribution in frozen and paraffin-embedded whole tissue sections of normal breast was evaluated using immunohistochemistry, immunofluorescence, and immunoelectron microscopy. CAV1 expression was immunohistochemically analyzed in benign lesions, breast cancer precursors, and metaplastic breast carcinomas and in a cohort of 245 invasive breast carcinomas from patients treated with surgery followed by anthracycline-based chemotherapy. In 25 cases, CAV1 gene amplification was assessed by chromogenic in situ hybridization. Results: In normal breast, CAV1 was expressed in myoepithelial cells, endothelial cells, and a subset of fibroblasts. Luminal epithelial cells showed negligible staining. CAV1 was expressed in 90% of 39 metaplastic breast carcinomas and in 9.4% of 245 invasive breast cancers. In the later cohort, CAV1 expression was significantly associated with ‘basal-like’ immunophenotype and with shorter disease-free and overall survival on univariate analysis. CAV1 gene amplification was found in 13% of cases with strong CAV1 expression. Conclusions: The concurrent CAV1 amplification and overexpression call into question its tumor-suppressive effects in basal-like breast carcinomas

Dynamics Impact Tolerance of Shuttle RCC Leading Edge Panels Using LS-DYNA

This paper describes a research program conducted to enable accurate prediction of the impact tolerance of the shuttle Orbiter leading-edge wing panels using physics-based codes such as LS-DYNA, a nonlinear, explicit transient dynamic finite element code. The shuttle leading-edge panels are constructed of Reinforced-Carbon-Carbon (RCC) composite material, which is used because of its thermal properties to protect the shuttle during reentry into the Earth's atmosphere. Accurate predictions of impact damage from insulating foam and other debris strikes that occur during launch required materials characterization of expected debris, including strain-rate effects. First, analytical models of individual foam and RCC materials were validated. Next, analytical models of foam cylinders impacting 6- in. x 6-in. RCC flat plates were developed and validated. LS-DYNA pre-test models of the RCC flat plate specimens established the impact velocity of the test for three damage levels: no-detectable damage, non-destructive evaluation (NDE) detectable damage, or visible damage such as a through crack or hole. Finally, the threshold of impact damage for RCC on representative Orbiter wing panels was predicted for both a small through crack and for NDE-detectable damage

Simultaneous measurement of gastric emptying of a soup test meal using MRI and gamma scintigraphy

Measurement of gastric emptying is of clinical value for a range of conditions. Gamma scintigraphy (GS) has an established role, but the use of magnetic resonance imaging (MRI) has recently increased. Previous comparison studies between MRI and GS showed good correlation, but were performed on separate study days. In this study, the modalities were alternated rapidly allowing direct comparison with no intra-individual variability confounds. Twelve healthy participants consumed 400 g of Technetium-99m (99mTc)-labelled soup test meal (204 kcal) and were imaged at intervals for 150 min, alternating between MRI and GS. The time to empty half of the stomach contents (T1/2) and retention rate (RR) were calculated and data correlated. The average T1/2 was similar for MRI (44 ± 6 min) and GS (35 ± 4 min) with a moderate but significant difference between the two modalities (p ≤0.004). The individual T1/2 values were measured, and MRI and GS showed a good positive correlation (r = 0.95, p ≤ 0.0001), as well as all the RRs at each time point up to 120 min. Gastric emptying was measured for the first time by MRI and GS on the same day. This may help with translating the use of this simple meal, known to elicit reliable, physiological, and pathological gastrointestinal motor, peptide, and appetite response

The Relationship between Glaucoma Medication Adherence, Eye Drop Technique, and Visual Field Defect Severity

The purpose of the study was to examine: (a) how patient adherence and eye drop technique were associated with visual field defect severity and (b) how general glaucoma adherence self-efficacy and eye drop technique self-efficacy were related to visual field defect severity