Monitoring of Alarm Reactions of Red Deer (Cervus elaphus) in a Captive Population in Paneveggio Pale di San Martino Natural Park

Simple Summary After several years of inappropriate management, the pasture inside the enclosure for captive red deer in Paneveggio Pale di San Martino regional Park (TN, Italy) lost its nutritional value, due to the expansion of unpalatable tall grasses. Therefore, several measures to restore a suitable pasture composition were needed. The mowing activity represents a disturbance for the captive deer, which negatively affects the animals' well-being. To establish the more appropriate times/days to perform activities inside the enclosure, we observed the alarm reactions and relative intensity of animals exposed to different visual stimuli presented inside and outside the enclosure. Some differences were highlighted between the males and the nursery (females and fawns) groups. Considering the deer biology and the studied location, the best months in which it would be possible to plan activities inside the enclosure are March, April (if the snow is not present) and August. Data elaboration suggests that the best day to perform activities inside the enclosure is Wednesday because the animals showed less sensitivity to disturbances; Tuesday and Thursday may also be considered additional suitable days. The study analyzes red deer responses to disturbances during the day and different exposures to tourists, to establish the more appropriate times to carry out activities inside the Paneveggio deer enclosure. The alarm reactions of red deer were observed after presenting different types of visual stimuli inside and outside the fence, in order to answer some questions: Which stimuli produce the strongest reactions from the animals? Do animals differently react to stimuli presented outside and inside the fence? On which days and times are the animals more sensitive to disturbances? Are there different reactions between the males and females? The results suggest that the red deer adversely react to the disturbance at different degrees of intensity in relation to day, sex, tourist and where the stimuli are presented. It was observed that during the days with the highest tourist presence, the animals were particularly alarmed; discomfort accumulation produced the highest number of alarm reactions on Monday. For these reasons, it would be opportune to manage the pasture on Tuesday, Wednesday and Thursday, scheduled at specific times of day, preferably far from the estimated presence of tourists

Photoinduced chemiluminescence determination of carbamate pesticides

A liquid chromatography method with post-column photoinduced chemiluminescence (PICL) detection is proposed for the simultaneous determination of eight carbamate pesticides, namely aldicarb, butocarboxim, ethiofencarb, methomyl, methiocarb, thiodicarb, thiofanox and thiophanate-methyl. After chromatographic separation, quinine (sensitizer) was incorporated and the flow passed through an UV lamp (67 s of irradiation time) to obtain the photoproducts, which reacted with acidic Ce(IV) and provided a CL emission. The PICL method showed great selectivity for carbamate pesticides containing sulphur in their chemical structure. A solid-phase extraction process increased sensitivity (LODs ranging from 0.06 to 0.27 ng mL−1) and allowed the carbamate pesticides in surface and ground water samples to be determined, with recoveries in the range 87 110% (except for thiophanate-methyl, whose recoveries were between 60 and 75%). The intra- and inter-day precision was evaluated, with RSD ranging from 1.1 to 7.5% and from 2.6 to 12.3%, respectively. A discussion about the PICL mechanism is also included.Catalá-Icardo, M.; Meseguer-Lloret, S.; Torres-Cartas, S. (2016). Photoinduced chemiluminescence determination of carbamate pesticides. Photochemical and Photobiological Sciences. 15:626-634. doi:10.1039/c6pp00056hS62663415Santaladchaiyakit, Y., Srijaranai, S., & Burakham, R. (2012). Methodological aspects of sample preparation for the determination of carbamate residues: A review. Journal of Separation Science, 35(18), 2373-2389. doi:10.1002/jssc.201200431Pesticides in Ground and Drinking water, ed. M. Fielding, Water Pollution Research Report 27, Commission of the European Communities, Brussels, 1991Melchert, W. R., & Rocha, F. R. P. (2010). A greener and highly sensitive flow-based procedure for carbaryl determination exploiting long pathlength spectrophotometry and photochemical waste degradation. Talanta, 81(1-2), 327-333. doi:10.1016/j.talanta.2009.12.005Chu, N., & Fan, S. (2009). Sequential injection kinetic spectrophotometric determination of quaternary mixtures of carbamate pesticides in water and fruit samples using artificial neural networks for multivariate calibration. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 74(5), 1173-1181. doi:10.1016/j.saa.2009.09.030Pacioni, N. L., & Veglia, A. V. (2007). Determination of poorly fluorescent carbamate pesticides in water, bendiocarb and promecarb, using cyclodextrin nanocavities and related media. Analytica Chimica Acta, 583(1), 63-71. doi:10.1016/j.aca.2006.10.010Yang, E.-Y., & Shin, H.-S. (2013). Trace level determinations of carbamate pesticides in surface water by gas chromatography–mass spectrometry after derivatization with 9-xanthydrol. Journal of Chromatography A, 1305, 328-332. doi:10.1016/j.chroma.2013.07.055Fernández-Ramos, C., Šatínský, D., & Solich, P. (2014). New method for the determination of carbamate and pyrethroid insecticides in water samples using on-line SPE fused core column chromatography. Talanta, 129, 579-585. doi:10.1016/j.talanta.2014.06.037Wang, X., Cheng, J., Wang, X., Wu, M., & Cheng, M. (2012). Development of an improved single-drop microextraction method and its application for the analysis of carbamate and organophosphorus pesticides in water samples. The Analyst, 137(22), 5339. doi:10.1039/c2an35623fFytianos, K., Pitarakis, K., & Bobola, E. (2006). Monitoring ofN-methylcarbamate pesticides in the Pinios River (central Greece) by HPLC. International Journal of Environmental Analytical Chemistry, 86(1-2), 131-145. doi:10.1080/03067310500248171Fu, L., Liu, X., Hu, J., Zhao, X., Wang, H., & Wang, X. (2009). Application of dispersive liquid–liquid microextraction for the analysis of triazophos and carbaryl pesticides in water and fruit juice samples. Analytica Chimica Acta, 632(2), 289-295. doi:10.1016/j.aca.2008.11.020Shi, Z., Hu, J., Li, Q., Zhang, S., Liang, Y., & Zhang, H. (2014). Graphene based solid phase extraction combined with ultra high performance liquid chromatography–tandem mass spectrometry for carbamate pesticides analysis in environmental water samples. Journal of Chromatography A, 1355, 219-227. doi:10.1016/j.chroma.2014.05.085Latrous El Atrache, L., Ben Sghaier, R., Bejaoui Kefi, B., Haldys, V., Dachraoui, M., & Tortajada, J. (2013). Factorial design optimization of experimental variables in preconcentration of carbamates pesticides in water samples using solid phase extraction and liquid chromatography–electrospray-mass spectrometry determination. Talanta, 117, 392-398. doi:10.1016/j.talanta.2013.09.032Cahill, M. G., Caprioli, G., Stack, M., Vittori, S., & James, K. J. (2011). Semi-automated liquid chromatography–mass spectrometry (LC–MS/MS) method for basic pesticides in wastewater effluents. Analytical and Bioanalytical Chemistry, 400(2), 587-594. doi:10.1007/s00216-011-4781-1López-Paz, J. L., Catalá-Icardo, M., & Langa-Sánchez, A. (2014). Determination ofN-methylcarbamate pesticides using flow injection with photoinduced chemiluminescence detection. International Journal of Environmental Analytical Chemistry, 94(6), 606-617. doi:10.1080/03067319.2013.879295López-Paz, J. L., & Catalá-Icardo, M. (2011). Analysis of Pesticides by Flow Injection Coupled with Chemiluminescent Detection: A Review. Analytical Letters, 44(1-3), 146-175. doi:10.1080/00032719.2010.500788Huertas-Pérez, J. F., & García-Campaña, A. M. (2008). Determination of N-methylcarbamate pesticides in water and vegetable samples by HPLC with post-column chemiluminescence detection using the luminol reaction. Analytica Chimica Acta, 630(2), 194-204. doi:10.1016/j.aca.2008.09.047Pérez-Ruiz, T., Martínez-Lozano, C., & García, M. D. (2007). Determination of N-methylcarbamate pesticides in environmental samples by an automated solid-phase extraction and liquid chromatographic method based on post-column photolysis and chemiluminescence detection. Journal of Chromatography A, 1164(1-2), 174-180. doi:10.1016/j.chroma.2007.07.006Orejuela, E., & Silva, M. (2003). Monitoring some phenoxyl-type N-methylcarbamate pesticide residues in fruit juices using high-performance liquid chromatography with peroxyoxalate-chemiluminescence detection. Journal of Chromatography A, 1007(1-2), 197-201. doi:10.1016/s0021-9673(03)00934-8Catalá-Icardo, M., Lahuerta-Zamora, L., Torres-Cartas, S., & Meseguer-Lloret, S. (2014). Determination of organothiophosphorus pesticides in water by liquid chromatography and post-column chemiluminescence with cerium(IV). Journal of Chromatography A, 1341, 31-40. doi:10.1016/j.chroma.2014.03.024Galera, M. M., García, M. D. G., & Valverde, R. S. (2006). Determination of nine pyrethroid insecticides by high-performance liquid chromatography with post-column photoderivatization and detection based on acetonitrile chemiluminescence. Journal of Chromatography A, 1113(1-2), 191-197. doi:10.1016/j.chroma.2006.02.013Meseguer-Lloret, S., Torres-Cartas, S., Catalá-Icardo, M., & Gómez-Benito, C. (2015). Selective and Sensitive Chemiluminescence Determination of MCPB: Flow Injection and Liquid Chromatography. Applied Spectroscopy, 70(2), 312-321. doi:10.1177/0003702815620133Pesticide properties database (PPDB). University of Hertfordshire, http://sitem.herts.ac.uk/aeru/ppdb/en/index.htmPulgarín, J. A. M., Molina, A. A., & López, P. F. (2006). Automatic chemiluminescence-based determination of carbaryl in various types of matrices. Talanta, 68(3), 586-593. doi:10.1016/j.talanta.2005.04.051Waseem, A., Yaqoob, M., & Nabi, A. (2007). Flow-injection determination of carbaryl and carbofuran based on KMnO4–Na2SO3 chemiluminescence detection. Luminescence, 22(4), 349-354. doi:10.1002/bio.970Tsogas, G. Z., Giokas, D. L., Nikolakopoulos, P. G., Vlessidis, A. G., & Evmiridis, N. P. (2006). Determination of the pesticide carbaryl and its photodegradation kinetics in natural waters by flow injection–direct chemiluminescence detection. Analytica Chimica Acta, 573-574, 354-359. doi:10.1016/j.aca.2005.11.058Xie, Z., Ouyang, X., Guo, L., Lin, X., & Chen, G. (2005). Determination of carbofuran by flow-injection with chemiluminescent detection. Luminescence, 20(3), 226-230. doi:10.1002/bio.825Liu, H., Hao, Y., Ren, J., He, P., & Fang, Y. (2007). Determination of tsumacide residues in vegetable samples using a flow-injection chemiluminescence method. Luminescence, 22(4), 302-308. doi:10.1002/bio.963Amorim, C. M. P. G., Albert-García, J. R., Montenegro, M. C. B. S., Araújo, A. N., & Calatayud, J. M. (2007). Photo-induced chemiluminometric determination of Karbutilate in a continuous-flow Multicommutation assembly. Journal of Pharmaceutical and Biomedical Analysis, 43(2), 421-427. doi:10.1016/j.jpba.2006.07.006DeMarco, A. C., & Hayes, E. R. (1979). Photodegradation of thiolcarbamate herbicides. Chemosphere, 8(5), 321-326. doi:10.1016/0045-6535(79)90117-6Prevention, Pesticides and Toxic Substances (7508C) Reregistration eligibility decision. Thiophanate-methyl, Environmental Protection Agency (EPA), 2005Sanz-Asensio, J., Plaza-Medina, M., Martı́nez-Soria, M. ., & Pérez-Clavijo, M. (1999). Study of photodegradation of the pesticide ethiofencarb in aqueous and non-aqueous media, by gas chromatography–mass spectrometry. Journal of Chromatography A, 840(2), 235-247. doi:10.1016/s0021-9673(99)00219-8D. Barceló and M. C.Hennion, Techniques and instrumentation in analytical chemistry, Elsevier, Amsterdam, The Netherlands, 1997, vol. 19Capitán-Vallvey, L. (2000). Chemiluminescence determination of sodium 2-mercaptoethane sulfonate by flow injection analysis using cerium(IV) sensitized by quinine. Talanta, 51(6), 1155-1161. doi:10.1016/s0039-9140(00)00291-5NIE, L., MA, H., SUN, M., LI, X., SU, M., & LIANG, S. (2003). Direct chemiluminescence determination of cysteine in human serum using quinine–Ce(IV) system. Talanta, 59(5), 959-964. doi:10.1016/s0039-9140(02)00649-5J. R. Lakowicz , Principles of Fluorescence Spectroscopy, 3rd edn, Springer, New York, 2006Hamilton, D. J., Ambrus, Á., Dieterle, R. M., Felsot, A. S., Harris, C. A., Holland, P. T., … Wong, S.-S. (2003). Regulatory limits for pesticide residues in water (IUPAC Technical Report). Pure and Applied Chemistry, 75(8), 1123-1155. doi:10.1351/pac20037508112

Assessing learning and memory in pigs

In recent years, there has been a surge of interest in (mini) pigs (Sus scrofa) as species for cognitive research. A major reason for this is their physiological and anatomical similarity with humans. For example, pigs possess a well-developed, large brain. Assessment of the learning and memory functions of pigs is not only relevant to human research but also to animal welfare, given the nature of current farming practices and the demands they make on animal health and behavior. In this article, we review studies of pig cognition, focusing on the underlying processes and mechanisms, with a view to identifying. Our goal is to aid the selection of appropriate cognitive tasks for research into pig cognition. To this end, we formulated several basic criteria for pig cognition tests and then applied these criteria and knowledge about pig-specific sensorimotor abilities and behavior to evaluate the merits, drawbacks, and limitations of the different types of tests used to date. While behavioral studies using (mini) pigs have shown that this species can perform learning and memory tasks, and much has been learned about pig cognition, results have not been replicated or proven replicable because of the lack of validated, translational behavioral paradigms that are specially suited to tap specific aspects of pig cognition. We identified several promising types of tasks for use in studies of pig cognition, such as versatile spatial free-choice type tasks that allow the simultaneous measurement of several behavioral domains. The use of appropriate tasks will facilitate the collection of reliable and valid data on pig cognition

Expression of the transcription factor Hes3 in the mouse and human ocular surface, and in pterygium

Purpose: In this work we examined the presence of the neural stem cell biomarker Hairy and Enhancer of Split 3 (Hes3) in the anterior eye segment and in the aberrant growth condition of the conjunctiva pterygium. Further, we studied the response of Hes3 to irradiation. Materials and methods: Adult mouse and human corneoscleral junction and conjunctiva, as well as human pterygium were prepared for immunohistochemical detection of Hes3 and other markers. Total body irradiation was used to study the changes in the pattern of Hes3 expression. Results: The adult rodent and human eye as well as pterygium, contain a population of cells expressing Hes3. In the human eye, Hes3-expressing (Hes3+) cells are found predominantly in the subconjunctival space spanning over the limbus where they physically associate with blood vessels. The cytoarchitecture of Hes3 + cells is similar to those previously observed in the adult central nervous system. Furthermore, irradiation reduces the number of Hes3 + cells in the subconjunctival space. In contrast, irradiation strongly promotes the nuclear localization of Hes3 in the ciliary body epithelium. Conclusions: Our results suggest that a recently identified signal transduction pathway that regulates neural stem cells and glioblastoma cancer stem cells also operates in the ocular surface, ciliary body, and in pterygium