Recently, several new lipid-dependent species belonging to the genus Malassezia have been described. Some of them, such as Malassezia dermatis, Malassezia nana, and the tentatively named "Malassezia equi," have similar phenotypes and are genetically close to Malassezia sympodialis Simmons et Guého 1990. DNA characterization by D1/D2 26S rRNA gene and internal transcribed spacer (ITS)-5.8S rRNA gene sequencing analysis of lipid-dependent strains from different animal species close to M. sympodialis is described and illustrated. Phylogenetic analysis of both the D1/D2 regions of 26S rRNA gene and ITS-5.8S rRNA gene sequences showed four distinct clusters. Cluster I included isolates from different animal species (horse, pig, and lamb) and the type culture of M. sympodialis. Cluster II included isolates from horses grouping close to the "M. equi" AJ305330 sequence. Cluster III comprised isolates mainly from goats. Cluster IV contained isolates mainly from cats grouping together with the M. nana AB075224 sequence. This last cluster included isolates from healthy and external otitic ears. All of these strains had identical 26S rRNA gene and ITS regions. It is not clear whether the value of these genetic differences is for the definition of species or whether they only demonstrate genetic variation among strains from different origins within M. sympodialis, which are in the course of differentiation and probably adaptation to specific animal hosts.Malassezia species are lipophilic yeasts that are usually members of the normal mycobiota of the human skin and inhabit the skin of a variety of animal species. However, these yeasts are associated with a variety of dermatological disorders of the human skin, such as atopic dermatitis, dandruff, folliculitis, pityriasis versicolor or seborrheic dermatitis (13) and intravascular catheter-acquired infections (23). They have been implicated in different skin disorders in animals, mainly otitis externa and dermatitis (6,15).Since the genus Malassezia was created by Baillon in 1889, its taxonomy has been a matter of controversy. A few years ago, the genus was reclassified (14, 16) on the basis of studies of morphological, ultrastructural, physiological, and genetic characteristics, and seven species, which are now widely accepted, were proposed. They are the previously described Malassezia furfur, Malassezia pachydermatis, and Malassezia sympodialis and four new species, Malassezia obtusa, Malassezia globosa, Malassezia restricta, and Malassezia slooffiae.

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Objective Systemic sclerosis (SSc) is a rare debilitating autoimmune disease of the connective tissue. This study aimed to assess the recent prevalence and incidence of SSc across the world. Methods Using a systematic search strategy, PubMed/MEDLINE and EMBASE were searched to identify relevant studies published between 2006 and 2016. Two reviewers independently evaluated studies for inclusion based on inclusion/exclusion criteria and performed data extraction. The review was conducted and reported following the Preferred Reporting Items for Systematic Review and Meta‐analysis (PRISMA) statement. The pooled prevalence of SSc was calculated by meta‐analysis using a random‐effects model. Results There were 1364 references retrieved using the initial searching strategy, and 20 epidemiological publications were selected for data extraction. The identified studies reported prevalence ranging from 3.8 per 100 000 in Taiwan to 50 per 100 000 in the USA. The prevalence was 23 per 100 000 (95% CI: 16‐29 per 100 000; 18 studies) in a pooled sample of 11 574 individuals. Incidence rate of SSc ranges from 0.77 per 100 000 person‐years in the Netherlands to 5.6 per 100 000 person‐years in the USA. SSc predominates in females with higher prevalence and incidence rates. It is important to note that different methodologies were used to derive these numbers so comparisons were made with caution. Conclusion This review provides an assessment of the current estimates of disease prevalence and incidence of SSc. The epidemiological burdens of SSc vary among different regions of the world. The epidemiological data need to be interpreted with caution considering the methodological differences in deriving these estimates.

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Background: Currently there is no standard algorithm to identify whether a subject is residing in a nursing home from administrative claims. Our objective was to develop and validate an algorithm that identifies nursing home admissions at the resident-month level using the MarketScan Medicare Supplemental and Coordination of Benefit (COB) database.