The role of head computed tomography in equine practice

This retrospective study describes the computed tomography (CT) findings in 59 horses presented with diseases of the head over 8 years that underwent CT examination of this region, including dental or sinonasal diseases (Group A) (n = 42), osseous and/or articular diseases (Group B) (n = 11) and soft tissue diseases (Group C) (n = 6). For Group A, radiographic and CT findings comparison was possible. Computed tomography had higher sensitivity (100%) and specificity (96.7%) than radiography in diagnosing dental disease. Compared to CT, radiographic identification of sinus involvement was less sensitive, particularly for ventral conchal and sphenopalatine sinuses and presented an overall sensitivity of 43.5 and 16.7%, respectively. In Group B CT allowed identification of a higher number of bone fragments and fractures in the maxillary, lacrimal, sphenoidal, temporal and zygomatic bones not identified radiographically. Accurate identification of CT changes in the temporomandibular joint and temporohyoid articulation was also possible. Group C included both intra‐ and extra‐cranial disease, retrobulbar masses being the most representative pathology (n = 3). In this group, CT was considered the gold standard for detection of periorbital diseases. We conclude that CT is an imaging technique with high diagnostic value for evaluating the equine head, yielding additional information over multiple radiographic views, which may alter the outcome of the case. Additionally, this paper reports several conditions not previously described using CT.     

Variation in pathogenicity among the three subspecies of Phytophthora alni on detached leaves,twigs and branches of Alnus glutinosa

Pathogenicity tests were carried out on leaves, twigs and branches of Alnus glutinosa using several isolates of Phytophthora alni ssp. alni, P. alni ssp. multiformis and P. alni ssp. uniformis in vitro. Healthy fresh leaves were collected from disease‐free areas and inoculated with mycelium on agar discs or by dipping in zoospore suspensions. In addition, twigs and branches were collected from both disease‐free and disease‐affected areas, inoculated with mycelium on agar discs and incubated at four temperatures (15, 20, 25, 30°C). All subspecies tested were pathogenic but with varied level of virulence. In inoculation tests on foliage, wounding was a key factor in causing infections: lesions on inoculated wounded leaves were larger than on non‐wounded leaves. In the twig and branch inoculation tests, no differences in virulence were observed among the P. alni subspecies in terms of sampling locations, but lesions differed in size according to incubation temperature, with the largest lesions occurring on tissues incubated at 25°C. The work is the first to report foliar necrosis caused by P. alni on A. glutinosa. P. alni ssp. uniformis was the least virulent of the subspecies in branch inoculations. These findings demonstrate that various tissues of A. glutinosa could act as sources of pathogen inoculum and may disseminate alder Phytophthora in natural ecosystems.     

Characterization of protein fractions from Bt-transgenic and non-transgenic maize varieties using perfusion and monolithic RP-HPLC. Maize differentiation by multivariate analysis

Protein fractions from transgenic Bt and non-transgenic maize varieties, extracted by the Osborne solvent fraction procedure, were characterized for the first time by perfusion and monolithic RP-HPLC in very short analysis times. Albumins and globulins from different transgenic Bt maizes as well as from their non-transgenic isogenic varieties were eluted in four peaks using perfusion RP-HPLC, whereas prolamins and glutelins were separated in seven peaks. Monolithic RP-HPLC enabled the separation of maize proteins in a large number of peaks showing 6 and 10 main peaks for albumins and globulins, respectively. Prolamins migrated at retention times higher than 5 min as seven peaks, whereas glutelins were separated in three main peaks appearing at retention times higher than 6.0 min. Moreover, chromatograms of the whole protein extracts showed 8 and 11 components for perfusion and monolithic RP-HPLC, respectively. A comparison of the chromatograms of the whole protein extracts relative to transgenic and non-transgenic varieties evidenced quantitative differences on the percentages of area, mainly for peaks 2 and 3 by perfusion RP-HPLC and for peaks 3 and 7 by monolithic RP-HPLC. A discriminant analysis based on these proteic profiles was carried out to classify and predict transgenic Bt maize lines, achieving 100% correct classification using perfusion RP-HPLC.