8 2 35 13 5 2 57 7 Mba. Daporinad ic50 alcaliphilum 96.8 8 21 6 7 13 55 8 Mbr. millerae 97.9 2 0 4 31 5 42 9 Mbr. millerae 97.9 10 4 4 11 2 31 10 Mbr. millerae 99.8 4 1 12 0 14 31 11 Mbr. ALK assay smithii 98.1 5 9 3 4 4 25 12 Mbr. millerae 97.9 0 19 3 0 2 24 13 Msp. stadtmanae 96.4 3 3 0 2 9 17 14 Mbr. smithii 98.0 6 1 4 5 0 16 15 Apr. boonei 82.3 0 0 9 0 0 9 16 Mbr. ruminantium 96.4 3 2 1 0 1 7 17 Mbr. millerae 98.7 3 0 2 0 2 7 18 Apr. boonei 82.5 0 0 1 1 4 6 19 Mba. alcaliphilum 95.5 1 1 2 1 0 5 20 Mba. alcaliphilum 96.5 0 4 1 0 0 5 21 Mbr. olleyae 96.7 0 1 0 3 1 5 22 Msp.

stadtmanae 96.5 0 0 1 4 0 5 23 Mbr. millerae 97.2 1 0 1 2 0 4 24 Mba. alcaliphilum 96.9 1 0 0 0 3 4 25 Mbr. ruminantium 98.4 0 1 1 0 1 3 26 Mbr. ruminantium 97.7 0 2 1 0 0 3 27 Mbr. smithii 97.3 0 1 1 1 0 3 28 Apr. boonei 82.6 0 0 2 1 0 3 29 Mbr. millerae 97.3 2 0 0 0 0 2 30 Mbr. GW 572016 millerae 97.8 2 0

0 0 0 2 31 Apr. boonei 81.6 0 2 0 0 0 2 32 Mbr. ruminantium 97.5 0 1 0 1 0 2 33 Mbr. ruminantium 97.2 0 1 0 0 1 2 34 Mbr. ruminantium 95.6 0 0 1 1 0 2 35 Apr. boonei 81.7 0 0 1 0 1 2 36 Mbr. gottschalkii 96.4 0 0 0 0 2 2 37 Mbr. gottschalkii 96.7 1 0 0 0 0 1 38 Apr. boonei 80.9 0 1 0 0 0 1 39 Mbr. ruminantium 96.4 0 1 0 0 0 1 40 Mbr. ruminantium 94.8 0 1 0 0 0 1 41 Mbr. wolinii 95.8 0 1 0 0 0 1 42 Mbr. millerae 97.2 0 0 1 0 0 1 43 Mbr. ruminantium 96.8 0 0 1 0 0 1 44 Mbr. olleyae 96.7 0 0 0 1 0 1 45 Mbr. smithii 97.5 0 0 0 1 0 1 46 Mbr. millerae 96.2 0 0 0 1 0 1 47 Msp. of unique OTUs % OTU coverage Shannon Index ± 95% confidence limits LIBSHUFF Clomifene Methodc Alpaca 4 3 97.8 2.06 ± 0.15b P≤ 0.0004 Alpaca 5 5 93.5 2.12 ± 0.14b P≤ 0.0022 Alpaca 6 2 94.0 1.96 ± 0.15b P≤ 0.0001 Alpaca 8 3 95.2 1.89 ± 0.16b P≤ 0.0028 Alpaca 9 6 94.4 2.09 ± 0.17b P≤ 0.0028 Combined – 98.4 2.85 ± 0.07b – a Schloss et al.

The inherited slots can be specialized by a sub concept. For example, Destruction of Satoyama, a traditional rural landscape in Japan, inherits “a/o place of occurrence = region” from its super concept Destruction of regional environment and specializes it to “a/o place of occurrence = Satoyama.” In this way, RG7112 cost concepts can be defined during the process of ontology building through inheritance and specialization. 2. Basic structure Due to the emphasis on the problem-solving approach of SS, Problem and Countermeasure against a problem are two of the SS ontology’s top-level concepts. Also, when trying to solve a problem,

a goal or goals for countermeasures must be set, and the existing conditions and impacts of the countermeasures must be evaluated explicitly or implicitly. Post evaluation as well as prior evaluation

may result in finding a new problem. Thus, we include Goal and Evaluation in the AZD1390 manufacturer top-level concepts of the ontology. In addition, we set Domain Concept as another top-level concept. In the SS ontology, the knowledge in the domain is not organized by individual Cilengitide molecular weight fields or disciplines, such as energy, climate, population, policy, or laws. Instead, it is organized by more general concepts, such as objects, activities, situations, and attributes, on the basis of ontology engineering theory (Mizoguchi 2003, 2004a, b). In ontology engineering theory, an ontology is composed of domain-specific concepts under the upper level concepts, which are highly domain-neutral. In this way, the ontology is organized in a domain-neutral manner. Our ontology consists of five top-level concepts: Goal, Problem, Countermeasure, Evaluation, and Domain Concept. Although they are SS-specific, they are sufficiently generalized to be independent of the targeted domains. Furthermore, while concrete occurrences and activities can be the sub concepts of Domain Concept, these concepts do not depend on the context of problem-solving.

By describing the world using two types of super concepts, domain-independent and domain-dependent, we can represent any kinds of countermeasures for sustainability Dapagliflozin that we would like to show. Domain-specific knowledge seen from a specific viewpoint can be represented by combining these concepts. Also, such a conceptual system can support the generation of ideas for new concrete countermeasures that were not conceived when the system was initially designed. 3. Prototype of SS ontology Using Hozo as an application platform, we have developed a prototype of SS ontology. It is not our intention in this paper to present a fully developed SS ontology. However, we briefly explain the top-level concepts and second-level concepts with the slots, which are concepts of parts and attributes, that are used to describe them. In the current implementation, SS ontology has 562 concepts and 14 hierarchy levels. (i) Problem (a) Top- and second-level concepts.

7 0.2–2.9 2.7 1.0–7.9 3.0 1.5–6.3   2+ – – 15.9 1.5–162.7 3.2 1.0–10.6 Osteoarthritis With 1.4 0.9–2.2 1.4 0.8–2.2 1.8 1.1–2.9 Model 2               Endplate 1 2.7 0.6–12.1 1.5 0.4–5.8 1.0 0.3–2.7   2+ – – 16.7 1.8–154.0 3.0 0.9–10.1 Osteoarthritis With 1.4 0.9–2.2 1.4 0.8–2.2 1.8 1.1–2.9 Model 3               Crush 1 – – 1.1 0.2–7.4 buy Staurosporine 0.7 0.2–2.6   2+ 3.9 0.6–25.5

3.9 0.3–47.4 0.9 0.2–4.3 Osteoarthritis With 1.4 0.9–2.2 1.4 0.8–2.2 1.8 1.1–2.8 Model 4               Any 1 1.0 0.3–3.0 1.9 0.8–4.6 2.3 1.2–4.5   2+ 1.3 0.3–6.6 11.1 3.5–35.0 2.8 1.4–5.8 Osteoarthritis With 1.4 0.9–2.2 1.4 0.8–2.2 1.8 1.1–2.9 Each model was run three separate times (once each for upper, lower, and any (upper or lower) back pain) for a total of 15 separate analyses, each with covariates for age (continuous), body mass index (continuous), and AZD1152 datasheet number of painful nonspine joints (ordinal). There were four regression models; the model for Wedge deformity and osteoarthritis (Model 1) included ordinal variables for number of endplate and number of crush deformities; the model for Endplate deformity and osteoarthritis (Model 2) included ordinal variables for number of wedge and number of crush deformities; and the model for Crush deformity and osteoarthritis (Model 3) included ordinal variables for number of wedge and number of endplate

deformities. The model for Any deformity and osteoarthritis (Model 4) did not include ordinal variables enough for numbers Trichostatin A mw of other vertebral deformity types Discussion We examined the prevalence of the three types of vertebral deformity by anatomic location and the associations of number and type of vertebral deformity or osteoarthritis with back pain among women in Japan. The prevalence of vertebral deformity was higher in the midthoracic and upper lumbar spine. Wedge deformity was the most frequent

deformity type, with a predilection for the thoraco-lumbar region (T12–L3). Crush deformity was less frequent and showed no predilection for anatomical location. Significant associations with back pain were observed for wedge deformities, for vertebral deformities in general (in models that included all types) and for vertebral osteoarthritis. Our results confirm findings from other population-based studies in women that wedge was the most frequent type of deformity [6, 13], and that the prevalence of deformity was higher in midthoracic and upper lumbar vertebrae [13, 15]. This distribution is believed to be related to biomechanical factors [29, 30]. Movements such as stooping or lifting greatly increase loading on the spine, especially the midthoracic and upper lumbar vertebrae where the spine curves.

Diagnosis and treatment of chronic constipation: a European perspective. Neurogastroenterol Motil. 2011;23(8):697–710.PubMedCrossRef 8. Pare P, Ferrazzi S, Thompson WG, et al. An epidemiological survey of constipation in Canada: definitions, rates, demographics, and predictors of health care seeking. Am J Gastroenterol. 2001;96(11):3130–7.PubMedCrossRef 9. Higgins PD, Johanson JF. Epidemiology of constipation in North America:

a systematic review. Am J Gastroenterol. 2004;99(4):750–9.PubMedCrossRef 10. Choung RS, Locke GR 3rd, Schleck CD, et al. Cumulative incidence Selleck BI 2536 of chronic constipation: a population-based study 1988–2003. CB-839 Aliment Pharmacol Ther. 2007;26(11–12):1521–8.PubMedCrossRef 11. Barditch-Crovo P, Trapnell CB, Ette E, et al. The effects of rifampin and rifabutin on the pharmacokinetics and pharmacodynamics

of a combination oral contraceptive. Clin Pharmacol Ther. MEK inhibitor 1999;65(4):428–38.PubMedCrossRef 12. Bolt HM. Interactions between clinically used drugs and oral contraceptives. Environ Health Perspect. 1994;102(Suppl 9):35–8.PubMedCrossRef 13. European Medicines Agency. ICH harmonised tripartite guidelines for good clinical practice, 1996. http://​www.​emea.​europa.​eu/​pdfs/​human/​ich/​013595en.​pdf. Accessed 11 June 2012. 14. World Medical Association. Declaration of Helsinki: ethical principles for medical research involving human subjects. http://​www.​wma.​net/​en/​30publications/​10policies/​b3/​. Accessed 12 August 2009. 15. US Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research (CDER), Center for Veterinary Medicine (CVM). Guidance for industry: bioanalytical method validation, 2001. http://​www.​fda.​gov/​downloads/​Drugs/​GuidanceComplian​ceRegulatoryInfo​rmation/​Guidances/​ucm070107.​pdf. Accessed 14 December 2011. 16. Organisation for Economic Co-operation and Development. OECD principles of good laboratory practice (GLP). http://​www.​oecd.​org/​document/​63/​0,3746,en_​2649_​34377_​2346175_​1_​1_​1_​1,00.​html. Accessed 13 April 2012. 17. Hanker JP. Gastrointestinal disease and oral contraception.

Am J Obstet Gynecol. 1990;163(6 Pt 2):2204–7.PubMedCrossRef 18. Camilleri M, Van Outryve MJ, Beyens very G, et al. Clinical trial: the efficacy of open-label prucalopride treatment in patients with chronic constipation: follow-up of patients from the pivotal studies. Aliment Pharmacol Ther. 2010;32(9):1113–23.PubMedCrossRef 19. Quigley EM, Tack J, Kerstens R, et al. The efficacy and safety of oral prucalopride in female patients with chronic constipation who had failed laxative therapy (EMA-authorised population) is similar to that of the ITT population in the initial pivotal trials: pooled data analysis. Gastroenterology. 2012;142(Suppl I):S820–1. 20. De Maeyer JH, Aerssens J, Verhasselt P, et al. Alternative splicing and exon duplication generates 10 unique porcine 5-HT 4 receptor splice variants including a functional homofusion variant.

phellinicola (Röhrich et al. 2013a), which is considered comparatively rare. The additional substituent of the C-terminal Tyrol of voglmayrins 12−17 (compounds 46−51), which has tentatively been assigned as a prenyl or isoprenyl (C5H8) residue, is hypothesised to be located at the p-hydroxy group. A regiospecific O-prenylation at the 4-position of the aromatic ring has recently been demonstrated for SirD (Zou et al. 2011), a tyrosine

O-prenyltranferase (Kremer and Li 2010) catalysing the first pathway-specific step in the biosynthesis of the phytotoxin sirodesmin PL. The latter is produced by Leptosphaeria maculans (anamorph: Phoma lingam), the causal agent of blackleg of canola (Brassica napus). Recently, O-prenyltyrosine diketopiperazines have been described from Fusarium sp. and Penicillium crustosum (Guimarães et al. find more 2010). Another notable structural element, dihydroxy-Pheol was found at the C-terminus of hypocitrin-1 (compound 69). While the presence of either Pheol or Tyrol may be assumed to originate from the relaxed substrate specificity in the terminal adenylate domain of the respective peptaibol

synthetase, the direct incorporation of dihydroxy-Phe, presumably 3,4-dihydroxy-L-Phe (DOPA), is one possible biosynthetic route. Fungal tyrosinases are known to oxidise not only Tyr and various other monophenols, e.g. in the route to melanins, but also act on tyrosyl residues within peptides and proteins, leading to the formation of inter- and intra-molecular crosslinks (Selinheimo et al. 2007). Thus, Tyrol-containing peptaibols could be further RXDX-101 oxidised by tyrosinases, and even become attached to components of the fungal cell wall (Mattinen et al. 2008). Considering the sequences of all species screened, including those of H. pulvinata and H. phellinicola, a general building scheme for those SF1-peptaibiotics can be given (Table 13): Table 13 General building scheme of the sequences of Hypocrea/Trichoderma SF1-peptaibiotics

RG7420 concentration screened (Röhrich et al. 2012, 2013a, this study)   Residue 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19a 20b Ac Aib Ala Aib Ala Aib Ala Gln Aib Lxx Aib Gly Lxx Aib Pro Vxx Aib Vxx Gln Gln Pheol   (Vxx) (Ser) Ala Aib (Vxx) (Aib)   (Vxx) Aib (Ala) Ala (Vxx) (Vxx)   Lxx Tau-protein kinase (Vxx) Aib (Glu) – Lxxol     (Aib) (Ser) (Lxx) (Phe)     (Ala) (Vxx)   (Ser) (Aib)     (Aib)   (Lxx)   (Glu) (Vxxol)     (Lxx) (Vxx) (Ser) (Ala)                             (Tyrol)     (Vxx)   (Gly) (Lxx)                             (Tyr(C5H8)ol)                                         (di-OH-Pheol) Minor sequence variants are parenthesised aOne of the Gln/Glu residues is deleted in some of the truncated sequences bThe C-terminal amino alcohol is deleted in some of the truncated sequences As can be seen from above, all structural features (Röhrich et al. 2012) required for ion channel formation (Grigoriev et al.

Running costs are estimated at no more than AUD 2 per assay compared to AUD 15 for DNA sequencing. The limitations of RCA in the primary identification of resistance are acknowledged (see above). However, the technique is well-suited as an epidemiological tool for high throughput screening for commonly-encountered ERG11 SNPs to assist in the detection of potentially-resistant check details strains and to track the movement of such strains.

Further, its utility in detecting SNPs in other genes that have been linked to azole resistance click here in C. albcians such as those encoding for the transcriptional activator of CDR1 (TAC1) and the transcriptional activator Upc2 (UPC2) [32, 33] warrant consideration. Conclusion In conclusion, the sensitive and specific RCA-based assay proved to be a simple robust method for the rapid detection of ERG11 mutations and showed excellent concordance with DNA sequencing.

It has good potential as a tool for tracking specific strains and identifying markers/co-markers of azole resistance. Broader implications include application of the method in the study of oher gene mutations linked to azole resistance in C. albicans and of azole resistance in other fungi such as Aspergillus fumigatus in which ERG11 mutations are a major mechanism of resistance [34, 35]. Methods C. albicans isolates Eight fluconazole-resistant “”reference”" isolates with previously-described mutations in ERG11 MM-102 mouse (strains C438, C440, C470, C480, C507, C527, C577 and C594 provided by A. Chau, Schering-Plough Research Institute, Kenilworth, New Jersey; Table 1) [15] were used to validate the RCA assay. Two fluconazole-susceptible Dichloromethane dehalogenase isolates (strains ATCC 10231 and ATCC 90028) were purchased from the American type culture collection (ATCC; Rockville, Md). Of 46 Australian clinical C.

albicans isolates, 25 (obtained from 19 patients) were resistant, or had reduced susceptibility to fluconazole (five patients – patient 3, 6, 8, 12 and 16 had >1 isolate recovered on separate occasions) and 21 were fluconazole-susceptible (Table 2). These isolates were from the culture collection of the Clinical Mycology laboratory, Westmead Hospital, Sydney and the Mycology Unit, Women’s and Children’s Hospital, Adelaide. The experimental work was approved as part of a Centre of Clinical Research Excellence Grant awarded by the National Health and Medical Research Council of Australia (grant #264625) and approved by the Scientific Advisory Committee, Sydney West Area Health Service and the Research and Development Committee, Centre for Infectious Diseases and Microbiology Laboratory Services, Westmead Hospital. Thus, 33 isolates with reduced fluconazole susceptibility and 23 fluconazole-susceptible isolates were studied. Isolates were identified as C. albicans by standard phenotypic methods [36] and maintained on Sabouraud’s dextrose agar at 4°C until required.

Conversely, p53 status lack of any significant association with docetaxel sensitivity in the same setting. Probably, TP53 gene mutational analysis could be more informative that IHC, even if a simplistic association between TP53 gene status and taxane treatment response seem

to be unlikely given the wide and very complicated molecular pathway related to p53. References 1. Jemal A, Siegel R, Ward E, Hao Y, Xu J, Murray T, Thun MJ: Cancer statistics, 2008. CA Cancer J Clin 2008, 58:71–96.PubMedCrossRef MLN2238 manufacturer 2. Grande E, Inghelmann R, Francisci S, Verdecchia A, Micheli A, Baili P, Capocaccia R, De Angelis R: Regional estimates of breast cancer burden in Italy. Tumori 2007, 93:374–9.PubMed 3. Sledge GW, Neuberg D, Bernardo P, Ingle JN, Martino S, Rowinsky EK, Wood WC: Phase III trial of doxorubicin, paclitaxel, and the combination of doxorubicin and paclitaxel as front-line chemotherapy for metastatic breast cancer: an Intergroup trial (E1193). J Clin Oncol 2003, 21:588–592.PubMedCrossRef 4. De Laurentiis M, Cancello G, D’Agostino G, Giuliano M, Giordano A, Montagna E, Lauria R, Forestieri V, Esposito A, Silvestro L, Pennacchio R, Criscitiello C, Montanino A, Limite G, Bianco AR, De Placido S: Taxane-based combinations

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Osteoporos Int 22:391–420PubMedCrossRef 75. Copanlisib Kanis JA, Johnell O, Oden A, EPZ5676 purchase Johansson H, McCloskey E (2008) FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int 19:385–397PubMedCrossRef 76. WHO (2007) Assessment of osteoporosis at the primary health care level. WHO, Geneva. At: www.​who.​int/​chp/​topics/​rheumatic/​en/​index.​html. Accessed May 2012 77. Kanis JA, Oden A, Johnell O et al (2007) The use of clinical risk factors enhances the performance

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Given that larger proteins generally give rise to a greater number of peptides following digestion, and thus a greater number spectral counts, relative protein abundance is commonly standardized to account for protein size. Rappsilber et al. used “protein abundance index” (PAI), which represents the number

of peptides identified divided by the number of theoretically observed peptides, to quantify the relative abundance of proteins detected by MS analyses [61]. Zybailov et al. and Florens and Washburn used “normalized spectral abundance factor” (NSAF), which represents the number of spectral counts divided by protein length [62, 63]. In this study, we have quantified 2D-HPLC-MS/MS abundance profiles based on each proteins “relative abundance index” selleck products (RAI), calculated as the number of spectral counts (SpC) divided by molecular mass (Mr) of protein. While selleck chemicals llc the number of proteins detected by shotgun 2D-HPLC-MS/MS was greater than 4-plex 2D-HPLC-MS/MS, RAI values followed a similar trend, further verifying general protein abundance using both acquisition methods ( Additional file 1). However, the RIA per a given protein was lower using the 4-plex versus shotgun acquisition Proteases inhibitor method. This was expected given that the 4-plex run simultaneously measures four samples and

associated labels, thus reducing available peptide acquisition time. Due to the increased sensitivity and deeper coverage, we use the RAI data of shotgun exponential phase samples when discussing relative protein expression profiles in the text. Changes in stationary phase protein expression levels using iTRAQ 2D-HPLC-MS/MS Understanding cellular responses to pH change, end-product accumulation, and substrate limitation may aid in improving

strain growth through targeted deregulation of factors that limit growth and production of desired end-products. Comparison of expression levels of two biologically replicated iTRAQ-labelled exponential phase and stationary phase samples (tagged with reporter ions 114 & 115 and 116 & 117, respectively) was performed using 4-plex 2D-HPLC-MS/MS. Ratios of z-score values among exponential and stationary phase biological replicates (reporter ion ratios 115/114 vs 117/116) and between exponential phase vs stationary phase samples Cyclic nucleotide phosphodiesterase (reporter ion ratio 116/114 vs 117/115) are plotted in Additional file 2a and 2b, respectively, to illustrate correlation between biological replicates. While Additional file 2a shows good correlation between biological replicates (perfect correlation represented by coordinates 0,0), a number of proteins have poorer correlation between replicates. To determine the statistical significance of protein expression ratios between exponential and stationary phase samples when factoring in the deviation between biological replicates, z-scores ratios for each protein were converted into vectors, and the vector difference was calculated (see Methods).

10 Metopina perpusilla (Six)       2         Unknown 1.10 Metopina pileata CA4P mw Schmitz   1   2         Unknown 1.00 Phalacrotophora berolinensis Schmitz   15   10   21     Zoophagous 1.70 Phalacrotophora fasciata

(Fallén)   32 2 6   11     Zoophagous 1.70 Phora artifrons Schmitz   16 Temsirolimus purchase   302   84 42 86 Unknown   Phora atra (Meigen)   4 9 145     2 47 Unknown 2.35 Phora convallium Schmitz           3     Unknown 2.20 Phora dubia (Zetterstedt)   1   120   11   1 Unknown 3.00 Phora holosericea Schmitz   17   77   146 8 7 Zoophagous 2.50 Phora indivisa Schmitz           1     Unknown 3.20 Phora obscura (Zetterstedt)   7   92   366 2   Unknown 2.25 Phora penicillata Schmitz         2 41     Unknown 2.25 Phora praepandens Schmitz           3     Unknown 2.10 Phora pubipes Schmitz           1     Unknown 2.70 Phora tincta Schmitz           17     Unknown 2.25 Plectanocnema nudipes (Becker)             2   Unknown 1.80 Poloniohora bialoviensis Disney         1    

  Unknown 1.05 Pseudacteon fennicus Schmitz             3 1 Zoophagous 1.50 Pseudacteon formicarum (Verrall)   1       4     Zoophagous 1.60 Triphleba aequalis (Schmitz)       1         Saprophagous 1.60 Triphleba antricola (Schmitz)       3         Saprophagousa 1.90 Triphleba bifida Schmitz 1               Unknown selleck chemicals 2.70 Triphleba crassinervis (Strobl)         1       Unknown 1.60 Triphleba distinguenda (Strobl) 1               Necrophagous 1.70 Triphleba hyalinata (Meigen)   2   5         Saprophagous 2.20 Triphleba intermedia (Malloch)       2     1 1 Unknown 2.35 Triphleba lugubris (Meigen)   5   1 5 4     Zoophagous 2.20 Triphleba luteifemorata (Wood)   13   34   12     Necrophagous 1.70 Triphleba minuta (Fabricius)   4             Mycophagous 3-mercaptopyruvate sulfurtransferase 2.20 Triphleba nudipalpis (Schmitz)   2   1   2     Necrophagous 1.80 Triphleba opaca (Meigen) 1 21 3 26 37 18 1 2 Saprophagous 2.85 Triphleba

papillata (Wingate)       1     2 3 Saprophagous 2.90 Triphleba smithi Disney           1     Unknown 1.65 Triphleba subcompleta Schmitz 1   1           Unknown 2.50 Triphleba trinervis (Becker) 4 2   6 4 5     Unknown 2.50 Trucidophora ewardurskae (Disney)           5     Zoophagous * Woodiphora retroversa (Wood)   1             Unknown * Total number of species per site 43 79 37 93 38 123 59 52     Expected number of species—ACE 53.1 88.0 66.8 116.6 48.0 138.8 66.1 70.6     Expected number of species—Chao1 52.0 85.5 61.6 115.0 57.1 145.3 63.5 124.3     Expected number of species—Chao1 corrected 49.5 84.7 56.0 112.5 51.6 143.0 62.6 97.3     Total number of individuals per site 1458 2037 687 7113 336 3466 1117 1333     Dominant species, at least at one site of all habitat types ≥10 individuals, are shown in bold type (Lundbeck 1922; Schmitz 1938–1958; Schmitz et al. 1974–1981; Disney 1991 and references therein, Disney personal comm.