To determine the contribution of posterior corneal astigmatism to total corneal astigmatism and the error in estimating total corneal astigmatism from anterior corneal measurements only using a ...dual-Scheimpflug analyzer.
Cullen Eye Institute, Baylor College of Medicine, Houston, Texas, USA.
Case series.
Total corneal astigmatism was calculated using ray tracing, corneal astigmatism from simulated keratometry, anterior corneal astigmatism, and posterior corneal astigmatism, and the changes with age were analyzed. Vector analysis was used to assess the error produced by estimating total corneal astigmatism from anterior corneal measurements only.
The study analyzed 715 corneas of 435 consecutive patients. The mean magnitude of posterior corneal astigmatism was -0.30 diopter (D). The steep corneal meridian was aligned vertically (60 to 120 degrees) in 51.9% of eyes for the anterior surface and in 86.6% for the posterior surface. With increasing age, the steep anterior corneal meridian tended to change from vertical to horizontal, while the steep posterior corneal meridian did not change. The magnitudes of anterior and posterior corneal astigmatism were correlated when the steeper anterior meridian was aligned vertically but not when it was aligned horizontally. Anterior corneal measurements underestimated total corneal astigmatism by 0.22 @ 180 and exceeded 0.50 D in 5% of eyes.
Ignoring posterior corneal astigmatism may yield incorrect estimation of total corneal astigmatism. Selecting toric intraocular lenses based on anterior corneal measurements could lead to overcorrection in eyes that have with-the-rule astigmatism and undercorrection in eyes that have against-the-rule astigmatism.
The authors received research support from Ziemer Group. In addition, Dr. Koch has a financial interest with Alcon Laboratories, Inc., Abbott Medical Optics, Inc., Calhoun Vision, Inc., NuLens, and Optimedica Corp.
Recent insights into the bioactivation and signaling actions of inorganic, dietary nitrate and nitrite now suggest a critical role for the microbiome in the development of cardiac and pulmonary ...vascular diseases. Once thought to be the inert, end-products of endothelial-derived nitric oxide (NO) heme-oxidation, nitrate and nitrite are now considered major sources of exogenous NO that exhibit enhanced vasoactive signaling activity under conditions of hypoxia and stress. The bioavailability of nitrate and nitrite depend on the enzymatic reduction of nitrate to nitrite by a unique set of bacterial nitrate reductase enzymes possessed by specific bacterial populations in the mammalian mouth and gut. The pathogenesis of pulmonary hypertension (PH), obesity, hypertension and CVD are linked to defects in NO signaling, suggesting a role for commensal oral bacteria to shape the development of PH through the formation of nitrite, NO and other bioactive nitrogen oxides. Oral supplementation with inorganic nitrate or nitrate-containing foods exert pleiotropic, beneficial vascular effects in the setting of inflammation, endothelial dysfunction, ischemia-reperfusion injury and in pre-clinical models of PH, while traditional high-nitrate dietary patterns are associated with beneficial outcomes in hypertension, obesity and CVD. These observations highlight the potential of the microbiome in the development of novel nitrate- and nitrite-based therapeutics for PH, CVD and their risk factors.
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•The microbiome may influence pulmonary hypertension via nitrogen oxide signaling.•Oral microbiota are necessary for nitrate reduction to vasoactive nitrogen oxides.•Dietary nitrate and nitrite are major sources of exogenous nitrogen oxides.•Dietary nitrate in vegetables exerts pleiotropic, beneficial nitrogen oxide effects.•Diet and probiotic therapy can alter beneficial nitrate and fatty acid metabolism.
Purpose To compare the accuracy of the Barrett True-K formula with other methods available on the American Society of Cataract and Refractive Surgery (ASCRS) post-refractive surgery intraocular lens ...(IOL) power calculator for the prediction of IOL power after previous myopic laser in situ keratomileusis (LASIK) or photorefractive keratectomy (PRK). Setting Cullen Eye Institute, Baylor College of Medicine, Houston, Texas, and private practice, Mesa, Arizona, USA. Design Retrospective case series. Methods The accuracy of the Barrett True-K formula was compared with the Adjusted Atlas (4.0 mm zone), Masket, modified-Masket, Wang-Koch-Maloney, Shammas, and Haigis-L methods to calculate IOL power. A separate analysis of 2 no-history methods (Shammas and Haigis-L) was performed and compared with the Barrett True-K no-history option. Results Eighty-eight eyes were available for analysis. The Barrett True-K formula had a significantly smaller median absolute refraction prediction error than all other formulas except the Masket, smaller variances compared with the Wang-Koch-Maloney, Shammas, and Haigis-L, and a greater percentage of eyes within ±0.50 diopter (D) of predicted error in refraction compared with the Adjusted Atlas, Masket, and modified Masket methods (all P < .05). In eyes with no historical data, the Barrett True-K no-history formula had a significantly smaller median absolute refraction prediction error and a greater percentage of eyes within ±0.50 D of the predicted error in refraction than the Shammas and the Haigis-L formulas (both P < .05). Conclusion The Barrett True-K formula was either equal to or better than alternative methods available on the ASCRS online calculator for predicting IOL power in eyes with previous myopic LASIK or PRK. Financial Disclosures Dr. Barrett has licensed the Barrett True-K formula to Haag-Streit. Dr. Hill is a paid consultant to Haag-Streit and Alcon Surgical, Inc. None of the other authors has a financial or proprietary interest in any material or method mentioned.
To compare the accuracy of total keratometry (TK) and standard keratometry (K) from a swept-source optical coherence tomography biometer for intraocular lens (IOL) power calculation in eyes with ...previous corneal refractive surgery.
Cullen Eye Institute, Baylor College of Medicine, Houston, Texas, USA.
Retrospective case series.
The differences between the TK and K and their association with K were assessed. For IOL power calculation, combinations of 1) K with Haigis, Haigis-L, and Barrett True-K, and 2) TK with Haigis (Haigis-TK) were used. The mean absolute error (MAE) and the percentages of eyes within prediction errors of ± 0.50 diopters (D), ± 1.00 D, and ± 2.00 D were calculated.
The study comprised 129 eyes. For Haigis, Haigis-L, Barrett True-K, and Haigis-TK, respectively, the MAEs were 0.72 D, 0.61 D, 0.54 D, and 0.50 D in the myopic laser in situ keratomileusis (LASIK)/photorefractive keratectomy (PRK) group, and 0.74 D, 0.68 D, 0.71 D, and 0.70 D in hyperopic LASIK/PRK group. For the radial keratotomy (RK) eyes, the MAEs were 0.66 D, 0.71 D, and 0.72 D for the Haigis, Barrett True-K, and Haigis-TK formulas, respectively. In the myopic LASIK/PRK group, the Barrett True-K and Haigis-TK produced significantly lower MAEs than did Haigis (P < .05). In the hyperopic LASIK/PRK and RK groups, there were no significant differences between the formulas in MAEs and percentages of eyes within the above prediction errors.
The performance of the combination of Haigis and TK in refractive prediction was comparable with Haigis-L and Barrett True-K in eyes with previous corneal refractive surgery.
Aggrecan in Cardiovascular Development and Disease Koch, Christopher D.; Lee, Chan Mi; Apte, Suneel S.
Journal of Histochemistry & Cytochemistry,
11/2020, Letnik:
68, Številka:
11
Book Review, Journal Article
Recenzirano
Odprti dostop
Aggrecan is a large proteoglycan that forms giant hydrated aggregates with hyaluronan in the extracellular matrix (ECM). The extraordinary resistance of these aggregates to compression explains their ...abundance in articular cartilage of joints where they ensure adequate load-bearing. In the brain, they provide mechanical buffering and contribute to formation of perineuronal nets, which regulate synaptic plasticity. Aggrecan is also present in cardiac jelly, developing heart valves, and blood vessels during cardiovascular development. Whereas aggrecan is essential for skeletal development, its function in the developing cardiovascular system remains to be fully elucidated. An excess of aggrecan was demonstrated in cardiovascular tissues in aortic aneurysms, atherosclerosis, vascular re-stenosis after injury, and varicose veins. It is a product of vascular smooth muscle and is likely to be an important component of pericellular matrix, where its levels are regulated by proteases. Aggrecan can contribute to specific biophysical and regulatory properties of cardiovascular ECM via the diverse interactions of its domains, and its accumulation is likely to have a significant role in developmental and disease pathways. Here, the established biological functions of aggrecan, its cardiovascular associations, and potential roles in cardiovascular development and disease are discussed.
We find a strong tendency for positive returns during the overnight period followed by reversals during the trading day. This behavior is driven by an opening price that is high relative to intraday ...prices. It is concentrated among stocks that have recently attracted the attention of retail investors, it is more pronounced for stocks that are difficult to value and costly to arbitrage, and it is greater during periods of high overall retail investor sentiment. The additional implicit transaction costs for retail traders who buy high-attention stocks near the open frequently exceed the effective half spread.
Recent thinning of glaciers over the Himalayas (sometimes referred to as the third polar region) have raised concern on future water supplies since these glaciers supply water to large river systems ...that support millions of people inhabiting the surrounding areas. Black carbon (BC) aerosols, released from incomplete combustion, have been increasingly implicated as causing large changes in the hydrology and radiative forcing over Asia and its deposition on snow is thought to increase snow melt. In India BC emissions from biofuel combustion is highly prevalent and compared to other regions, BC aerosol amounts are high. Here, we quantify the impact of BC aerosols on snow cover and precipitation from 1990 to 2010 over the Indian subcontinental region using two different BC emission inventories. New estimates indicate that Indian BC emissions from coal and biofuel are large and transport is expected to expand rapidly in coming years. We show that over the Himalayas, from 1990 to 2000, simulated snow/ice cover decreases by ~0.9% due to aerosols. The contribution of the enhanced Indian BC to this decline is ~36%, similar to that simulated for 2000 to 2010. Spatial patterns of modeled changes in snow cover and precipitation are similar to observations (from 1990 to 2000), and are mainly obtained with the newer BC estimates.
This study presents the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations related to desert dust aerosols, ...their direct radiative effect, and their impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposition. Additional comparisons to Angström exponent (AE), coarse mode AOD and dust surface concentrations are included to extend the assessment of model performance and to identify common biases present in models. These data comprise a benchmark dataset that is proposed for model inspection and future dust model development. There are large differences among the global models that simulate the dust cycle and its impact on climate. In general, models simulate the climatology of vertically integrated parameters (AOD and AE) within a factor of two whereas the total deposition and surface concentration are reproduced within a factor of 10. In addition, smaller mean normalized bias and root mean square errors are obtained for the climatology of AOD and AE than for total deposition and surface concentration. Characteristics of the datasets used and their uncertainties may influence these differences. Large uncertainties still exist with respect to the deposition fluxes in the southern oceans. Further measurements and model studies are necessary to assess the general model performance to reproduce dust deposition in ocean regions sensible to iron contributions. Models overestimate the wet deposition in regions dominated by dry deposition. They generally simulate more realistic surface concentration at stations downwind of the main sources than at remote ones. Most models simulate the gradient in AOD and AE between the different dusty regions. However the seasonality and magnitude of both variables is better simulated at African stations than Middle East ones. The models simulate the offshore transport of West Africa throughout the year but they overestimate the AOD and they transport too fine particles. The models also reproduce the dust transport across the Atlantic in the summer in terms of both AOD and AE but not so well in winter-spring nor the southward displacement of the dust cloud that is responsible of the dust transport into South America. Based on the dependency of AOD on aerosol burden and size distribution we use model bias with respect to AOD and AE to infer the bias of the dust emissions in Africa and the Middle East. According to this analysis we suggest that a range of possible emissions for North Africa is 400 to 2200 Tg yr−1 and in the Middle East 26 to 526 Tg yr−1.
Purpose To evaluate and compare the accuracy of 2 toric intraocular lens (IOL) calculators with or without a new regression formula. Setting Ein-Tal Eye Center, Tel-Aviv, Israel, and the Lions Eye ...Institute, Nedlands, Western Australia, Australia. Design Retrospective case series. Methods A new regression formula (Abulafia-Koch) was developed to calculate the estimated total corneal astigmatism based on standard keratometry measurements. The error in the predicted residual astigmatism was calculated by the Alcon and Holladay toric IOL calculators with and without adjustments by the Abulafia-Koch formula. These results were compared with those of the Barrett toric calculator. Results Data from 78 eyes were evaluated to validate the Abulafia-Koch formula. The centroid errors in predicted residual astigmatism were against-the-rule with the Alcon (0.55 diopter D) and Holladay (0.54 D) toric calculators and decreased to 0.05 D ( P < .001 x -axis, P = .776 y -axis) and 0.04 D ( P < .001 x -axis, P = .726 y -axis) with adjustments by the Abulafia-Koch formula. The Alcon and the Holladay toric calculators had a higher proportion of eyes within ±0.50 D of the predicted residual astigmatism with the Abulafia-Koch formula (76.9% and 78.2%, respectively) than without it (both 30.8%). There were no significant differences between the results of the Abulafia-Koch-modified Alcon and the Holladay toric calculators and those of the Barrett toric calculator. Conclusion Adjustment of commercial toric IOL calculators by the Abulafia-Koch formula significantly improved the prediction of postoperative astigmatic outcome. Financial Disclosure Dr. Abulafia received a speaker's fee from Haag-Streit AG. Dr. Barrett has licensed the Barrett Toric Calculator to Haag-Streit AG. Dr. Koch is a consultant to Alcon Laboratories, Inc., Abbott Medical Optics, Inc., and Revision Optics, Inc. Dr. Hill is a paid consultant to Haag-Streit AG and Alcon Laboratories, Inc. None of the other authors has a financial or proprietary interest in any material or method mentioned.
To evaluate the impact of posterior corneal astigmatism on outcomes with toric intraocular lenses (IOLs).
Cullen Eye Institute, Baylor College of Medicine, Houston, Texas, USA.
Case series.
Corneal ...astigmatism was measured using 5 devices before and 3 weeks after cataract surgery. Toric IOL alignment was recorded at surgery and at the slitlamp 3 weeks postoperatively. The actual corneal astigmatism was calculated based on refractive astigmatism 3 weeks postoperatively and the effective toric power calculated with the Holladay 2 formula. The prediction error was calculated as the difference between the astigmatism measured by each device and the actual corneal astigmatism. Vector analysis was used in all calculations.
With the IOLMaster, Lenstar, Atlas, manual keratometer, and Galilei (combined Placido-dual Scheimpflug analyzer), the mean prediction errors (D) were, respectively, 0.59 @ 89.7, 0.48 @ 91.2, 0.51 @ 78.7, 0.62 @ 97.2, and 0.57 @ 93.9 for with-the-rule (WTR) astigmatism (60 to 120 degrees), and 0.17 @ 86.2, 0.23 @ 77.7, 0.23 @ 91.4, 0.41 @ 58.4, and 0.12 @ 7.3 for against-the-rule (ATR) astigmatism (0 to 30 degrees and 150 to 180 degrees). In the WTR eyes, there were significant WTR prediction errors (0.5 to 0.6 diopters D) by all devices. In ATR eyes, WTR prediction errors were 0.2 to 0.3 D by all devices except the Placido-dual Scheimpflug analyzer (all P<.05 with Bonferroni correction).
Corneal astigmatism was overestimated in WTR by all devices and underestimated in ATR by all except the Placido-dual Scheimpflug analyzer. A new toric IOL nomogram is proposed.
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