A comparison of different optical instruments and machine learning techniques to identify sprouting activity in potatoes during storage

The quality of potato tubers is dependent on several attributes been maintained at appropriate levels during storage. One of these attributes is sprouting activity that is initiated from meristematic regions of the tubers (eyes). Sprouting activity is a major problem that contributes to reduced shelf life and elevated sugar content, which affects the marketability of seed tubers as well as fried products. This study compared the capabilities of three different optical systems (1: visible/near-infrared (Vis/NIR) interactance spectroscopy, 2: Vis/NIR hyperspectral imaging, 3: NIR transmittance) and machine learning methods to detect sprouting activity in potatoes based on the primordial leaf count (LC). The study was conducted on Frito Lay 1879 and Russet Norkotah cultivars stored at different temperatures and classification models were developed that considered both cultivars combined and classified the tubers as having either high or low sprouting activity. Measurements were performed on whole tubers and sliced samples to see the effect this would have on identifying sprouting activity. Sequential forward selection was applied for wavelength selection and the classification was carried out using K-nearest neighbor, partial least squares discriminant analysis, and soft independent modeling class analogy. The highest classification accuracy values obtained by the hyperspectral imaging system and was 87.5% and 90% for sliced and whole samples, respectively. Data fusion did not show classification improvement for whole tubers, whereas a 7.5% classification accuracy increase was illustrated for sliced samples. By investigating different optical techniques and machine learning methods, this study provides a first step toward developing a handheld optical device for early detection of sprouting activity, enabling advanced aid potato storage management

Contribution of Hepatic Cytochrome P450 3A4 Metabolic Activity to the Phenomenon of Clopidogrel Resistance

Background— Interindividual variability of platelet inhibition after aspirin or clopidogrel administration has been described. Additionally, aspirin resistance and clopidogrel resistance occur in some individuals. Because the prodrug clopidogrel is activated by hepatic cytochrome P450 (CYP) 3A4, we hypothesized that interindividual variability in clopidogrel efficacy might be related to interindividual differences in CYP3A4 metabolic activity. Methods and Results— Platelet aggregation was measured before and after clopidogrel treatment in 32 patients undergoing coronary artery stent implantation and in 35 healthy volunteers. The erythromycin breath test was used to measure CYP3A4 activity in vivo in 25 of the healthy volunteers. Individual platelet aggregation was studied in 10 healthy volunteers after the coadministration of clopidogrel and rifampin (a CYP3A4 inducer). Clopidogrel nonresponders, low responders, and responders were defined by a relative inhibition of adenosine diphosphate (20 μmol/L)–induced platelet aggregation of less than 10%, 10% to 29%, and ≥30%, respectively. Among patients, 22% were clopidogrel nonresponders, 32% were low responders, and 47% were responders. Among volunteers, 16% were nonresponders, 12% were low responders, and 72% were responders. Percent platelet aggregation after clopidogrel inversely correlated with CYP3A4 activity (r=−0.6, P=0.003). Improved platelet inhibition in volunteers resistant to clopidogrel was observed with the coadministration of clopidogrel and rifampin. Conclusions— Clopidogrel administration results in interindividual variability in platelet inhibition, which correlates with CYP3A4 metabolic activity. Measurement of antiplatelet drug efficacy with a point-of-care device and alternative antithrombotic strategies for aspirin or clopidogrel nonresponders and low responders could reduce the incidence of thrombotic events that continue to occur despite oral antiplatelet therapy

Atorvastatin reduces the ability of clopidogrel to inhibit platelet aggregation: A new drug-drug interaction

Background— We observed that the prodrug clopidogrel was less effective in inhibiting platelet aggregation with coadministration of atorvastatin during point-of-care platelet function testing. Because atorvastatin is metabolized by cytochrome P450 (CYP) 3A4, we hypothesized that clopidogrel might be activated by CYP3A4. Methods and Results— Platelet aggregation was measured in 44 patients undergoing coronary artery stent implantation treated with clopidogrel or clopidogrel plus pravastatin or atorvastatin, and in 27 volunteers treated with clopidogrel and either erythromycin or troleandomycin, CYP3A4 inhibitors, or rifampin, a CYP3A4 inducer. Atorvastatin, but not pravastatin, attenuated the antiplatelet activity of clopidogrel in a dose-dependent manner. Percent platelet aggregation was 34±23, 58±15 (P=0.027), 74±10 (P=0.002), and 89±7 (P=0.001) in the presence of clopidogrel and 0, 10, 20, and 40 mg of atorvastatin, respectively. Erythromycin attenuated platelet aggregation inhibition (55±12 versus 42±12% platelet aggregation; P=0.002), as did troleandomycin (78±18 versus 45±18% platelet aggregation; P less than 0.0003), whereas rifampin enhanced platelet aggregation inhibition (33±18 versus 56±20% platelet aggregation, P=0.001). Conclusions— CYP3A4 activates clopidogrel. Atorvastatin, another CYP3A4 substrate, competitively inhibits this activation. Use of a statin not metabolized by CYP3A4 and point-of-care platelet function testing may be warranted in patients treated with clopidogrel

Proatherogenic Oxidized Low-Density Lipoprotein/β2-Glycoprotein I Complexes in Arterial and Venous Disease

OxLDL/β2GPI complexes have been implicated in the initiation and progression of atherosclerosis and associated with disease severity and adverse outcomes. We investigate the significance of anti-oxLDL/β2GPI antibodies and oxLDL/β2GPI complexes in patients with arterial and idiopathic venous disease. A cohort of 61 arterial disease patients, 32 idiopathic venous disease patients, and 53 healthy controls was studied. Because statins influence oxLDL/β2GPI, these complexes were analyzed on subjects not taking statins. Arterial and venous groups expressed higher levels of IgG anti-oxLDL/β2GPI antibodies than controls without any other significant clinical association. OxLDL/β2GPI complexes were significantly elevated in arterial (0.69 U/mL, P=0.004) and venous disease (0.54 U/mL, P=0.025) than controls (0.39 U/mL). Among arterial diseases, oxLDL/β2GPI was 0.85 U/mL for carotid artery disease, 0.72 U/mL for peripheral artery disease, and 0.52 U/mL for abdominal aortic aneurysm. There was a significant association with male gender, age, hypertension, and history of thrombosis. Subjects with oxLDL/β2GPI above the median (0.25 U/mL) were more likely to have arterial (OR 4.5, P=0.004) or venous disease (OR 4.1, P=0.008). Multivariate regression indicated that males (P=0.021), high cholesterol (P=0.011), and carotid disease (P=0.023) were significant predictors of oxLDL/β2GPI. The coexistence of oxLDL/β2GPI in arterial and venous disease may suggest a common oxidative mechanism that independently predicts carotid artery disease

Whole Blood Platelet function Assay on the /CHOR

The role of platelets as the initial defense against insult to the vasculature is well established. Moreover, platelets are now recognized as having a critical role in the acute care settings of cardiopulmonary bypass (CPB) procedures and cardiac catheterization. In the environment of CPB, both platelet count and function have been demonstrated as being markedly compromised during and following the procedure. Unfortunately, current assays that are used to evaluate the parameters of platelet count and function are limited in regard to their utility in a near patient format. Here, we describe a practical, rapid, and user-friendly whole blood platelet function assay that has been developed for the ICHOR™ point-of-care hematology analyzer. This analyzer is capable of performing an eight parameter blood profile including platelet count. In comparable studies, platelet aggregation in whole blood demonstrated good correlation (for ADP the values were n=14, r2=0.81, p=0.0001; for collagen, n=10, r2=0.93, p=0.0001; for ristocetin, n=10, r2=0.89, p=0.0001; and for epinephrine, n=10, r2=0.81, p=0.0003) with traditional platelet-rich aggregometry, which uses increased light transmission as an indication of platelet aggregation. Furthermore, early feasibility studies in CPB patients demonstrated both decreased platelet count and a marked reduction in platelet function peri-procedurally. This new assay of platelet function is extremely suitable for the clinical environment with rapid turnaround time and provides a full hematology profile to enhance transfusion decisions

Direct measurements of thermal vacancies in BCC 4 He

X-ray lattice parameters of bcc 4 He crystals in contact with superfluid 4 He were measured with 300 ppm accuracy in the temperature range 1.494–1.711 K, corresponding to solid molar volumes between 20.88 and 21.09 cm 3 . Thermal vacancy concentrations in the solid at melting were estimated from a comparison of these lattice parameters with bulk solid molar volumes from the literature. Independently, temperature-dependent x-ray lattice parameter measurements on a bcc sample, held at constant macroscopic volume from 1.700 to 1.735 K, were referenced to the same solid sample (at 20.90 cm 3 ) in the hcp phase near 0.8 K, where thermal vacancy content is small. The value of the free energy of formation for vacancies in bcc 4 He obtained from these measurements is f =9±1 K. The relationship between this value and indirect inferences about vacancy formation from ion mobility and NMR experiments is discussed. Comparisons are made between vacancy properties in bcc 4 He and in the more extensively studied bcc phase of 3 He. There are many parallels between the two systems. But a puzzling apparent difference between the vacancy relaxation energies in the two solids is pointed out.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44960/1/10909_2004_Article_BF00710349.pd