Section Arachis is the largest of nine sections in the genus Arachis and includes domesticated peanut, A. hypogaea L. Most species are diploids (x = 10) with two tetraploids and a few aneuploids. Three genome types have been recognized in this section (A, B and D), but the genomes are not well characterized and relationships of several newly described species are uncertain. To clarify genomic relationships in section Arachis, cytogenetic information and molecular data from amplified fragment length polymorphism (AFLP) and the trnT-F plastid region were used to provide an additional insight into genome composition and species relationships. Cytogenetic information supports earlier observations on genome types of A. cruziana, A. herzogii, A. kempff-mercadoi and A. kuhlmannii but was inconclusive about the genome composition of A. benensis, A. hoehnei, A. ipaensis, A. palustris, A. praecox and A. williamsii. An AFLP dendrogram resolved species into four major clusters and showed A. hypogaea grouping closely with A. ipaensis and A. williamsii. Sequence data of the trnT-F region provided genome-specific information and showed for the first time that the B and D genomes are more closely related to each other than to the A genome. Integration of information from cytogenetics and biparentally and maternally inherited genomic regions show promise in understanding genome types and relationships in Arachis.

Pistacia is an economically important genus because it contains the pistachio crop, <i>P. vera</i>, which has edible seeds of considerable commercial importance whose value has increased over the last two decades reaching an annual value of about $2 billion (harvested crop). The taxonomic relationships among its species are controversial and not well under- stood due to the fact that they have no genetic barriers. The taxonomy of this genus is revised in detail through our re- search. It includes the following taxa: Pistacia atlantica Desf., <i>P. chinensis</i> Bunge subsp. chinensis, <i>P. chinensis</i> subsp. falcata (Bess. ex Martinelli) Rech. f., <i>P. chinensis</i> subsp. integerrima (J.L. Stew. ex Brandis) Rech. f., <i>P. eurycarpa</i> Yalt., <i>P. khinjuk</i> Stocks, <i>P. lentiscus</i> L. subsp. lentiscus, <i>P. lentiscus</i> subsp. emarginata (Engl.) AL-Saghir, <i>P. mexicana</i> Humb., Bonpl., & Kunth, P. X saportae Burnat, <i>P. terebinthus</i> L., <i>P. vera</i> L., and <i>P. weinmannifolia</i> Poiss. ex Franch. The genus is divided into two sections: section Pistacia and section Lentiscella. A key to the 14 taxa that have been recognized by this study is included. The new combination <i>P. lentiscus</i> subsp. emarginata (Engl.) AL-Saghir is made, and the names <i>P. chinensis</i> subsp. integerrima (J. L. Stew. ex Brandis) Rech. F., <i>P. terebinthus</i> L., and <i>P. vera</i> L. are lectotypified

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Malaria and leishmaniasis are among the two most important health problems of many developing countries especially in the Middle East and North Africa. It is common for vector-borne infectious diseases to have similar hotspots which may be attributed to the overlapping ecological distribution of the vector. Hotspot analyses were conducted to simultaneously detect the location of local hotspots and test their statistical significance. Spatial scan statistics were used to detect and test hotspots of malaria and cutaneous leishmaniasis (CL) in Afghanistan in 2009. A multivariate negative binomial model was used to simultaneously assess the effects of environmental variables on malaria and CL. In addition to the dependency between malaria and CL disease counts, spatial and temporal information were also incorporated in the model. Results indicated that malaria and CL incidence peaked at the same periods. Two hotspots were detected for malaria and three for CL. The findings in the current study show an association between the incidence of malaria and CL in the studied areas of Afghanistan. The incidence of CL disease in a given month is linked with the incidence of malaria in the previous month. Co-existence of malaria and CL within the same geographical area was supported by this study, highlighting the presence and effects of environmental variables such as temperature and precipitation. People living in areas with malaria are at increased risk for leishmaniasis infection. Local healthcare authorities should consider the co-infection problem by recommending systematic malaria screening for all CL patients.

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