Depth-Dependent Compressive Equilibrium Properties of Articular Cartilage Explained by Its Composition,” Biomech.

Abstract For this study, we hypothesized that the depthdependent compressive equilibrium properties of articular cartilage are the inherent consequence of its depth-dependent composition, and not the result of depth-dependent material properties. To test this hypothesis, our recently developed fibril-reinforced poroviscoelastic swelling model was expanded to include the influence of intra-and extra-fibrillar water content, and the influence of the solid fraction on the compressive properties of the tissue. With this model, the depth-dependent compressive equilibrium properties of articular cartilage were determined, and compared with experimental data from the literature. The typical depth-dependent behavior of articular cartilage was predicted by this model. The effective aggregate modulus was highly strain-dependent. It decreased with increasing strain for low strains, and increases with increasing strain for high strains. This effect was more pronounced with increasing distance from the articular surface. The main insight from this study is that the depth-dependent material behavior of articular cartilage can be obtained from its depth-dependent composition only. This eliminates the need for the assumption that the material properties of the different constituents themselves vary with depth. Such insights are important for understanding cartilage mechanical behavior, cartilage damage mechanisms and tissue engineering studies

Impact of Mineral Dust on Nitrate, Sulfate, and Ozone in Transpacific Asian Pollution Plumes

We use a 3-D global chemical transport model (GEOS-Chem) to interpret aircraft observations of nitrate and sulfate partitioning in transpacific dust plumes during the INTEX-B campaign of April–May 2006. The model includes explicit transport of size-resolved mineral dust and its alkalinity, nitrate, and sulfate content. The observations show that particulate nitrate is primarily associated with dust, sulfate is primarily associated with ammonium, and Asian dust remains alkaline across the Pacific. This can be reproduced in the model by using a reactive uptake coefficient for $HNO_3$ on dust $(\gamma(HNO_3) \sim10^{−3})$ much lower than commonly assumed in models and possibly reflecting limitation of uptake by dust dissolution. The model overestimates gas-phase $HNO_3$ by a factor of 2–3, typical of previous model studies; we show that this cannot be corrected by uptake on dust. We find that the fraction of aerosol nitrate on dust in the model increases from ~30% in fresh Asian outflow to 80–90% over the Northeast Pacific, reflecting in part the volatilization of ammonium nitrate and the resulting transfer of nitrate to the dust. Consumption of dust alkalinity by uptake of acid gases in the model is slow relative to the lifetime of dust against deposition, so that dust does not acidify (at least not in the bulk). This limits the potential for dust iron released by acidification to become bio-available upon dust deposition. Observations in INTEX-B show no detectable ozone depletion in Asian dust plumes, consistent with the model. Uptake of $HNO_3$ by dust, suppressing its recycling to $NO_x$, reduces Asian pollution influence on US surface ozone in the model by 10–15% or up to 1 ppb.Engineering and Applied Science

Food Security Crop Price Transmission and Formation in Nigeria

The three studies in this dissertation explore the current conditions and operations of markets for seven key food security crops (cassava, cowpeas, maize, millet, rice, sorghum, and yams) in Nigeria. Chapter 2 is an empirical analysis of the current agricultural statistics system in Nigeria. A number of sources gather and report agricultural statistics for the country. Since there has not been an agricultural census implemented there for multiple decades, however, there is no objective source for data verification. Therefore, this study uses two additional types of “on the ground information” to assess if agricultural production estimates reflect growing conditions: prices and remote sensing data in the form of the normalized difference vegetation index (NDVI). The results show that existing production estimates are poorly correlated with both prices and the NDVI. Prices and the NDVI data are highly correlated, however. These findings imply that existing production estimates do not reflect growing conditions, and, therefore, are of poor quality. Chapter 3 is a comprehensive analysis of crop price transmission from global and neighbor country prices to Nigerian commercial hub and urban markets, and from commercial hubs to other urban and rural markets within the country. The results show that tradability matters for price transmission, but that tradability varies across crops and scopes of markets. Nigerian urban rice prices are highly correlated with prices on global markets and those in neighboring countries. Coarse grain prices appear disconnected from global markets, however, but move closely with those in neighboring countries. Large margins were estimated for prices of rice imported from global markets (in all regions), and for coarse grains to Southern Nigerian markets only. The existence of large margins implies that there are transactions costs and/or quality premiums that vary systematically with the world price, and/or mark-ups by traders with market power in these markets. While domestic market prices are almost always cointegrated, perfect price transmission is generally found only between commercial hubs and other urban markets. Moreover, long lags were found for price transmission across all scopes of markets, but especially between urban and rural prices in some regions. These results imply that local conditions (e.g., weather) are relatively more important than external market prices for explaining price variation in rural markets, especially in the short-run. Chapter 4 incorporates NDVI data into price formation models to estimate whether observable growing conditions explain price variation in Nigerian food security crop markets. Four issues related to use of NDVI data that exist within the literature are investigated: whether NDVI is a valid proxy for expected production, how NDVI is a proxy for seasonality, the relationship between market size and the area scope used to average NDVI values across space, and if anomalous harvest expectations can change long-run price variation and price relationships between markets. The results show that information on growing conditions is more informative for isolated than interconnected markets. Even for those local prices, however, other non-weather and non-external market price factors are relatively more important for explanation of price variation. An implication of these results is that Nigeria cannot plausibly rely solely on direct imports from global markets to meet short-run demand during future weather shock periods. Thus, storage is required to ensure stability of food security, either for imports or domestically produced surpluses acquired in non-crisis periods. Given the isolation of rural markets, local and on-farm stocks are at least as important as large facilities in commercial hubs. Improvement of village level and on-farm storage systems and elimination of other market distortions that inhibit trade between urban and rural markets would make public storage less needed. The findings on poor quality of agricultural statistics indicate a clear priority to improve agricultural data, to facilitate better planning of any food security strategies. A combination of surveys with remote sensed and crowd sourced data may improve feasibility in the funding constrained environment

The Diagnostic Value of Near-Infrared Spectroscopy to Predict Delayed Cerebral Ischemia and Unfavorable Outcome After Subarachnoid Hemorrhage

OBJECTIVE: Near-infrared spectroscopy (NIRS) is a non-invasive tool to monitor cerebral regional oxygen saturation. Impairment of microvascular circulation with subsequent cerebral hypoxia during delayed cerebral ischemia (DCI) is associated with poor functional outcome after subarachnoid hemorrhage (SAH). Therefore, NIRS could be useful to predict the risk for DCI and functional outcome. However, only limited data is available on NIRS regional cerebral tissue oxygen saturation (rSO2) distribution in SAH. The aim of this study was to compare the distribution of NIRS rSO2 values in non-traumatic SAH patients with the occurrence of DCI and functional outcome at two months. In addition, the predictive value of NIRS rSO2 was compared with the previously validated SAFIRE grade (derived from Size of the aneurysm, Age, FIsher grade, world federation of neurosurgical societies after REsuscitation).METHODS: In this study, the rSO2 distribution of patient with and without DCI after SAH are compared. The optimal cutoff points to predict DCI and outcome are assessed, and its predictive value is compared to the SAFIRE grade.RESULTS: Out of 41 patients, 12 developed DCI, and 9 had unfavorable outcome at 60 days. Prediction of DCI with NIRS had an area under the curve (AUC) of 0.77 (95%CI 0.62-0.92; p=0.0028) with an optimal cutoff point of 65% (sensitivity 1.00; specificity 0.45). Prediction of favorable outcome with NIRS had an AUC of 0.86 (95%CI 0.74-0.98; p=0.0003) with an optimal cutoff point of 63% (sensitivity 1.00; specificity 0.63). Regression analysis showed that NIRS rSO2 score is complementary to the SAFIRE grade.CONCLUSION: NIRS rSO2 monitoring in patients with SAH may improve prediction of DCI and clinical outcome after SAH.</p

The Diagnostic Value of Near-Infrared Spectroscopy to Predict Delayed Cerebral Ischemia and Unfavorable Outcome After Subarachnoid Hemorrhage

OBJECTIVE: Near-infrared spectroscopy (NIRS) is a non-invasive tool to monitor cerebral regional oxygen saturation. Impairment of microvascular circulation with subsequent cerebral hypoxia during delayed cerebral ischemia (DCI) is associated with poor functional outcome after subarachnoid hemorrhage (SAH). Therefore, NIRS could be useful to predict the risk for DCI and functional outcome. However, only limited data is available on NIRS regional cerebral tissue oxygen saturation (rSO2) distribution in SAH. The aim of this study was to compare the distribution of NIRS rSO2 values in non-traumatic SAH patients with the occurrence of DCI and functional outcome at two months. In addition, the predictive value of NIRS rSO2 was compared with the previously validated SAFIRE grade (derived from Size of the aneurysm, Age, FIsher grade, world federation of neurosurgical societies after REsuscitation).METHODS: In this study, the rSO2 distribution of patient with and without DCI after SAH are compared. The optimal cutoff points to predict DCI and outcome are assessed, and its predictive value is compared to the SAFIRE grade.RESULTS: Out of 41 patients, 12 developed DCI, and 9 had unfavorable outcome at 60 days. Prediction of DCI with NIRS had an area under the curve (AUC) of 0.77 (95%CI 0.62-0.92; p=0.0028) with an optimal cutoff point of 65% (sensitivity 1.00; specificity 0.45). Prediction of favorable outcome with NIRS had an AUC of 0.86 (95%CI 0.74-0.98; p=0.0003) with an optimal cutoff point of 63% (sensitivity 1.00; specificity 0.63). Regression analysis showed that NIRS rSO2 score is complementary to the SAFIRE grade.CONCLUSION: NIRS rSO2 monitoring in patients with SAH may improve prediction of DCI and clinical outcome after SAH.</p

The Diagnostic Value of Near-Infrared Spectroscopy to Predict Delayed Cerebral Ischemia and Unfavorable Outcome After Subarachnoid Hemorrhage

OBJECTIVE: Near-infrared spectroscopy (NIRS) is a non-invasive tool to monitor cerebral regional oxygen saturation. Impairment of microvascular circulation with subsequent cerebral hypoxia during delayed cerebral ischemia (DCI) is associated with poor functional outcome after subarachnoid hemorrhage (SAH). Therefore, NIRS could be useful to predict the risk for DCI and functional outcome. However, only limited data is available on NIRS regional cerebral tissue oxygen saturation (rSO2) distribution in SAH. The aim of this study was to compare the distribution of NIRS rSO2 values in non-traumatic SAH patients with the occurrence of DCI and functional outcome at two months. In addition, the predictive value of NIRS rSO2 was compared with the previously validated SAFIRE grade (derived from Size of the aneurysm, Age, FIsher grade, world federation of neurosurgical societies after REsuscitation).METHODS: In this study, the rSO2 distribution of patient with and without DCI after SAH are compared. The optimal cutoff points to predict DCI and outcome are assessed, and its predictive value is compared to the SAFIRE grade.RESULTS: Out of 41 patients, 12 developed DCI, and 9 had unfavorable outcome at 60 days. Prediction of DCI with NIRS had an area under the curve (AUC) of 0.77 (95%CI 0.62-0.92; p=0.0028) with an optimal cutoff point of 65% (sensitivity 1.00; specificity 0.45). Prediction of favorable outcome with NIRS had an AUC of 0.86 (95%CI 0.74-0.98; p=0.0003) with an optimal cutoff point of 63% (sensitivity 1.00; specificity 0.63). Regression analysis showed that NIRS rSO2 score is complementary to the SAFIRE grade.CONCLUSION: NIRS rSO2 monitoring in patients with SAH may improve prediction of DCI and clinical outcome after SAH.</p

The Diagnostic Value of Near-Infrared Spectroscopy to Predict Delayed Cerebral Ischemia and Unfavorable Outcome After Subarachnoid Hemorrhage

OBJECTIVE: Near-infrared spectroscopy (NIRS) is a non-invasive tool to monitor cerebral regional oxygen saturation. Impairment of microvascular circulation with subsequent cerebral hypoxia during delayed cerebral ischemia (DCI) is associated with poor functional outcome after subarachnoid hemorrhage (SAH). Therefore, NIRS could be useful to predict the risk for DCI and functional outcome. However, only limited data is available on NIRS regional cerebral tissue oxygen saturation (rSO2) distribution in SAH. The aim of this study was to compare the distribution of NIRS rSO2 values in non-traumatic SAH patients with the occurrence of DCI and functional outcome at two months. In addition, the predictive value of NIRS rSO2 was compared with the previously validated SAFIRE grade (derived from Size of the aneurysm, Age, FIsher grade, world federation of neurosurgical societies after REsuscitation).METHODS: In this study, the rSO2 distribution of patient with and without DCI after SAH are compared. The optimal cutoff points to predict DCI and outcome are assessed, and its predictive value is compared to the SAFIRE grade.RESULTS: Out of 41 patients, 12 developed DCI, and 9 had unfavorable outcome at 60 days. Prediction of DCI with NIRS had an area under the curve (AUC) of 0.77 (95%CI 0.62-0.92; p=0.0028) with an optimal cutoff point of 65% (sensitivity 1.00; specificity 0.45). Prediction of favorable outcome with NIRS had an AUC of 0.86 (95%CI 0.74-0.98; p=0.0003) with an optimal cutoff point of 63% (sensitivity 1.00; specificity 0.63). Regression analysis showed that NIRS rSO2 score is complementary to the SAFIRE grade.CONCLUSION: NIRS rSO2 monitoring in patients with SAH may improve prediction of DCI and clinical outcome after SAH.</p

The Diagnostic Value of Near-Infrared Spectroscopy to Predict Delayed Cerebral Ischemia and Unfavorable Outcome After Subarachnoid Hemorrhage

OBJECTIVE: Near-infrared spectroscopy (NIRS) is a non-invasive tool to monitor cerebral regional oxygen saturation. Impairment of microvascular circulation with subsequent cerebral hypoxia during delayed cerebral ischemia (DCI) is associated with poor functional outcome after subarachnoid hemorrhage (SAH). Therefore, NIRS could be useful to predict the risk for DCI and functional outcome. However, only limited data is available on NIRS regional cerebral tissue oxygen saturation (rSO2) distribution in SAH. The aim of this study was to compare the distribution of NIRS rSO2 values in non-traumatic SAH patients with the occurrence of DCI and functional outcome at two months. In addition, the predictive value of NIRS rSO2 was compared with the previously validated SAFIRE grade (derived from Size of the aneurysm, Age, FIsher grade, world federation of neurosurgical societies after REsuscitation).METHODS: In this study, the rSO2 distribution of patient with and without DCI after SAH are compared. The optimal cutoff points to predict DCI and outcome are assessed, and its predictive value is compared to the SAFIRE grade.RESULTS: Out of 41 patients, 12 developed DCI, and 9 had unfavorable outcome at 60 days. Prediction of DCI with NIRS had an area under the curve (AUC) of 0.77 (95%CI 0.62-0.92; p=0.0028) with an optimal cutoff point of 65% (sensitivity 1.00; specificity 0.45). Prediction of favorable outcome with NIRS had an AUC of 0.86 (95%CI 0.74-0.98; p=0.0003) with an optimal cutoff point of 63% (sensitivity 1.00; specificity 0.63). Regression analysis showed that NIRS rSO2 score is complementary to the SAFIRE grade.CONCLUSION: NIRS rSO2 monitoring in patients with SAH may improve prediction of DCI and clinical outcome after SAH.</p