Foxbright1561
omarker screening of male E. ulmoides flower core collections. We first evaluated the metabolite profiles and compositional variations of male E. ulmoides flowers in representative core collections before establishing possible chemotypes and significant biomarkers denoting the variations. We used genetic variations to infer the metabolite compositional variations of male E. ulmoides flower core collections instead of using the geographical origins of the germplasm resources. The newly proposed biomarkers sufficiently classified the chemotypes to be applied for germplasm resource evaluation.
Cold therapy has the disadvantage of inducing vasoconstriction in arterial and venous capillaries. The effects of carbon dioxide (CO
) hot water depend mainly on not only cutaneous vasodilation but also muscle vasodilation. We examined the effects of artificial CO
cold water immersion (CCWI) on skin oxygenation and muscle oxygenation and the immersed skin temperature.
Fifteen healthy young males participated. CO
-rich water containing CO
>1,150 ppm was prepared using a micro-bubble device. Each subject's single leg was immersed up to the knee in the CO
-rich water (20°C) for 15 min, followed by a 20-min recovery period. As a control study, a leg of the subject was immersed in cold tap-water at 20°C (CWI). The skin temperature at the lower leg under water immersion (T
-WI) and the subject's thermal sensation at the immersed and non-immersed lower legs were measured throughout the experiment. Lomeguatrib molecular weight We simultaneously measured the relative changes of local muscle oxygenation/deoxygenation compared to theperiod. The T
-WI stayed lower with the CCWI compared to the CWI, as it is associated with vasodilation by CO
.
The combination of CO2 and cold water can induce both more increased blood inflow into muscles and volume-related (total heme concentration) changes in deoxy[Hb+Mb] during the recovery period. The Tsk-WI stayed lower with the CCWI compared to the CWI, as it is associated with vasodilation by CO2.The scientific method has provided the 21st allopathic healer with many powerful and effective tools to combat disease. However, the management of technology does not equate with being a healer. The integral healer not only utilizes the power of the scientific method but also balances its application with compassionate intention and wise perspective. This article describes the characteristics of the 4 pillars of becoming an integral healer (competency, compassion, wisdom, and self-cultivation) and describes how each one of these pillars is vital to being a healer.
To investigate the retinal nerve fiber layer profile measured by optical coherence tomography and its relation to refractive error and axial length.
The Gutenberg Health Study is a population-based study in Mainz, Germany. At the five-year follow-up examination, participants underwent optical coherence tomography, objective refraction and biometry. Peripapillary retinal nerve fiber layer (pRNFL) was segmented using proprietary software. The pRNFL profiles were compared between different refraction groups and the angle between the maxima, i.e., the peaks of pRNFL thickness in the upper and lower hemisphere (angle between the maxima of pRNFL thickness [AMR]) was computed. Multivariable linear regression analysis was carried out to determine associations of pRNFL profile (AMR) including age, sex, optic disc size, and axial length in model 1 and spherical equivalent in model 2.
A total of 5387 participants were included. AMR was 145.3° ± 23.4° in right eyes and 151.8° ± 26.7° in left eyes and the pRNFL profile was significant different in the upper hemisphere. The AMR decreased with increasing axial length by -5.86°/mm (95% confidence interval [CI] [-6.44; -5.29],
< 0.001), female sex (-7.61°; 95% CI [-8.71; -6.51],
< 0.001) and increased with higher age (0.08°/year; 95% CI [0.03; 0.14],
= 0.002) and larger optic disc size (2.29°/mm
; 95% CI [1.18; 3.41],
< 0.001). In phakic eyes, AMR increased with hyperopic refractive error by 2.60°/diopters (dpt) (95% CI [2.33; 2.88],
< 0.001).
The pRNFL profiles are related to individual ocular and systemic parameters.
Biometric parameters should be considered when pRNFL profiles are interpreted in diagnostics, i.e., in glaucoma.
Biometric parameters should be considered when pRNFL profiles are interpreted in diagnostics, i.e., in glaucoma.
To quantitatively measure meibomian gland (MG) tortuosity in meibomian gland dysfunction (MGD) patients and normal controls and to observe the efficacy of evaluating MG tortuosity for the diagnosis of MGD.
This cross-sectional study enrolled 32 obstructive MGD patients and 28 normal volunteers. Clinical assessments were performed, including symptom questionnaires, tear meniscus height, tear break-up time (TBUT), corneal fluorescein staining, lid margin abnormality, MG expressibility, and meibography. The meibomian gland tortuosity and meibomian gland density were measured by VIA software.
The mean age of the patients in the MGD group was 33.28 ± 9.28 years, and that of the normal controls was 25.25 ± 11.19 years. The average tortuosity of all MGs in the MGD patients was significantly larger than in the normal controls (
0.05). We further stratified the MGD patients into symptomatic MGD and asymptomatic groups. The average tortuosity of all MGs and of the central eight MGs was significantly higher in the symptomatic MGD patients than in the asymptomatic MGD patients (
0.05). Significant linear correlations were found between MG tortuosity and the lid margin score, meiboscore, meibum expressibility score, and TBUT (
0.05). When the diagnosis of obstructive MGD was based on the tortuosity of the central eight MGs of both eyelids, the sensitivity and specificity were 100% and 100%, respectively.
MG tortuosity is an effective index to delineate MG morphology and to diagnose MGD, especially for the diagnosis of early-stage MGD.
Calculating tortuosity quantitatively may play an important role in the diagnosis of MGD.
Calculating tortuosity quantitatively may play an important role in the diagnosis of MGD.
Using a geometrically derived model and a virtual curb simulator, we quantify the degree to which a wearable device that projects a laser line onto tripping hazards in a pedestrian's path improves visual recognition for people with visual impairments (VI). We confirm this with subjects' performance on computer simulations of low contrast curbs.
We derive geometric expressions quantifying the visual cue users perceive when a single laser line is projected from their hip onto a curb. We show how the efficacy of this cue changes with the angle of the laser line relative to the subject's walking trajectory. We confirm this result with data from three subjects with VI in a simulated curb recognition task in which subjects classified computer images as an "Ascending," "Flat," or "Descending" curb.
The derived model predicts that human recognition performance depends strongly on the laser line angle and the subject data confirms this (
= 0.86
< 0.001). The laser line cue improved subject accuracy from a chance level of 33% to 95% for a simulated, one-inch, low-contrast curb at a distance of five feet.
Recognition of curbs in low light can be improved by augmenting the scene with a single laser line projected from a user's hip, if the angle of laser line is appropriately selected.
A majority of people with VI rely on their impaired residual vision for mobility, rather than a mobility aid, resulting in increased injury for this population. Enhancing residual vision could promote safety, increase independence, and reduce medical costs.
A majority of people with VI rely on their impaired residual vision for mobility, rather than a mobility aid, resulting in increased injury for this population. Enhancing residual vision could promote safety, increase independence, and reduce medical costs.
To present a fully automatic method to estimate the corneal endothelium parameters from specular microscopy images and to use it to study a one-year follow-up after ultrathin Descemet stripping automated endothelial keratoplasty.
We analyzed 383 post ultrathin Descemet stripping automated endothelial keratoplasty images from 41 eyes acquired with a Topcon SP-1P specular microscope at 1, 3, 6, and 12 months after surgery. The estimated parameters were endothelial cell density (ECD), coefficient of variation (CV), and hexagonality (HEX). Manual segmentation was performed in all images.
Our method provided an estimate for ECD, CV, and HEX in 98.4% of the images, whereas Topcon's software had a success rate of 71.5% for ECD/CV and 30.5% for HEX. For the images with estimates, the percentage error in our method was 2.5% for ECD, 5.7% for CV, and 5.7% for HEX, whereas Topcon's software provided an error of 7.5% for ECD, 17.5% for CV, and 18.3% for HEX. Our method was significantly better than Topcon's (
< 0.0001) and was not statistically significantly different from the manual assessments (
> 0.05). At month 12, the subjects presented an average ECD = 1377 ± 483 [cells/mm
], CV = 26.1 ± 5.7 [%], and HEX = 58.1 ± 7.1 [%].
The proposed method obtains reliable and accurate estimations even in challenging specular images of pathologic corneas.
CV and HEX, not currently used in the clinic owing to a lack of reliability in automatic methods, are useful biomarkers to analyze the postoperative healing process. Our accurate estimations allow now for their clinical use.
CV and HEX, not currently used in the clinic owing to a lack of reliability in automatic methods, are useful biomarkers to analyze the postoperative healing process. Our accurate estimations allow now for their clinical use.
We developed a method to automatically locate and quantify graft detachment after Descemet's membrane endothelial keratoplasty (DMEK) in anterior segment optical coherence tomography (AS-OCT) scans.
A total of 1280 AS-OCT B-scans were annotated by a DMEK expert. Using the annotations, a deep learning pipeline was developed to localize scleral spur, center the AS-OCT B-scans and segment the detached graft sections. Detachment segmentation model performance was evaluated per B-scan by comparing (1) length of detachment and (2) horizontal projection of the detached sections with the expert annotations. Horizontal projections were used to construct graft detachment maps. All final evaluations were done on a test set that was set apart during training of the models. A second DMEK expert annotated the test set to determine interrater performance.
Mean scleral spur localization error was 0.155 mm, whereas the interrater difference was 0.090 mm. The estimated graft detachment lengths were in 69% of the cases within a 10-pixel (∼150 µm) difference from the ground truth (77% for the second DMEK expert). Dice scores for the horizontal projections of all B-scans with detachments were 0.896 and 0.880 for our model and the second DMEK expert, respectively.
Our deep learning model can be used to automatically and instantly localize graft detachment in AS-OCT B-scans. Horizontal detachment projections can be determined with the same accuracy as a human DMEK expert, allowing for the construction of accurate graft detachment maps.
Automated localization and quantification of graft detachment can support DMEK research and standardize clinical decision-making.
Automated localization and quantification of graft detachment can support DMEK research and standardize clinical decision-making.
