A Survey for Diclofop-Methyl Resistance in Italian Ryegrass from Tennessee and How To Manage Resistance in Wheat

Italian ryegrass resistance to diclofop has been documented in several countries, including the United States. The purpose of this research was to screen selected putative resistant populations of Italian ryegrass for resistance to the acetyl-CoA carboxylase (ACCase)-inhibiting herbicides diclofop and pinoxaden and the acetolactate synthase (ALS)-inhibiting herbicides imazamox, pyroxsulam, and mesosulfuron in the greenhouse and to use field experiments to develop herbicide programs for Italian ryegrass control. Resistance to diclofop was confirmed in eight populations from Tennessee. These eight populations did not show cross-resistance to pinoxaden. One additional population (R1) from Union County, North Carolina, was found to be resistant to both diclofop and pinoxaden. The level of resistance to pinoxaden of the R1 population was 15 times that of the susceptible population. No resistance was confirmed to any of the ALS-inhibiting herbicides examined in this research. Field experiments demonstrated PRE Italian ryegrass control with chlorsulfuron (71 to 94%) and flufenacet + metribuzin (84 to 96%). Italian ryegrass control with pendimethalin applied PRE or delayed preemergence (DPRE) was variable (0 to 85%). POST control of Italian ryegrass was acceptable with pinoxaden, mesosulfuron, flufenacet + metribuzin, and chlorsulfuron + flucarbazone (> 80%). Application timing and herbicide treatment had no effect on wheat yield, except for diclofop and pendimethalin treatments, in which uncontrolled Italian ryegrass reduced wheat yield.

The case of thyroid hormones: how to learn physiology by solving a detective case

Lellis-Santos C, Giannocco G, Nunes MT. The case of thyroid hormones: how to learn physiology by solving a detective case. Adv Physiol Educ 35: 219-226, 2011; doi:10.1152/advan.00135.2010.Thyroid diseases are prevalent among endocrine disorders, and careful evaluation of patients' symptoms is a very important part in their diagnosis. Developing new pedagogical strategies, such as problem-based learning (PBL), is extremely important to stimulate and encourage medical and biomedical students to learn thyroid physiology and identify the signs and symptoms of thyroid dysfunction. The present study aimed to create a new pedagogical approach to build deep knowledge about hypo-/hyperthyroidism by proposing a hands-on activity based on a detective case, using alternative materials in place of laboratory animals. After receiving a description of a criminal story involving changes in thyroid hormone economy, students collected data from clues, such as body weight, mesenteric vascularization, visceral fat, heart and thyroid size, heart rate, and thyroid-stimulating hormone serum concentration to solve the case. Nevertheless, there was one missing clue for each panel of data. Four different materials were proposed to perform the same practical lesson. Animals, pictures, small stuffed toy rats, and illustrations were all effective to promote learning, and the detective case context was considered by students as inviting and stimulating. The activity can be easily performed independently of the institution's purchasing power. The practical lesson stimulated the scientific method of data collection and organization, discussion, and review of thyroid hormone actions to solve the case. Hence, this activity provides a new strategy and alternative materials to teach without animal euthanization.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.