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José Fafetine Luis Neves Peter N. Thompson Janusz T. Paweska Victor P. M. G. Rutten J. A. W. Coetzer 《PLoS neglected tropical diseases》2013,7(2)
Rift Valley fever (RVF) is endemic in most parts of Africa and has also been reported to occur in the Arabian Peninsula. It is responsible for significant morbidity and mortality, particularly in livestock, but also in humans. During the last two decades several outbreaks of RVF have been reported in countries in Southern Africa. In contrast to other countries, no clinical disease has been reported in Mozambique during this period. In a serological study conducted in 2007 in five districts of Zambézia Province, Mozambique, of a total of 654 small ruminants sampled (277 sheep and 377 goats), 35.8% of sheep sera and 21.2% of goat sera were positive for RVF virus (RVFV) antibodies in a virus neutralization test (VN) and in an IgG enzyme-linked immunosorbent assay (ELISA). In 2010, a cross-sectional survey was conducted in 313 sheep and 449 goats in two districts of the same province. This study revealed an overall seropositivity rate of 9.2% in sheep and 11.6% in goat and an increased likelihood of being seropositive in older animals (OR = 7.3; p<0.001) using an IgG ELISA. 29 out of 240 animals assessed for RVF specific IgM by ELISA were positive, suggesting recent exposure to RVFV. However, a longitudinal study carried out between September 2010 and April 2011 in a cohort of 125 of these animals (74 sheep and 51 goats) failed to demonstrate seroconversion. The results of the study indicate that RVFV circulates sub-clinically in domestic small ruminants in Zambézia Province. 相似文献
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Waterbird populations were censused each January from 1991 to 1999 at Lakes Naivasha, Elmenteita and Nakuru and from 1992 at Lake Bogoria. These shallow lakes in the Kenyan Rift Valley fluctuate greatly in water level and alkalinity. All but Naivasha are usually saline; Nakuru and Elmenteita at times support fish, while Bogoria is fishless. A standardized logarithmic index of relative abundance (value 1.0 for the mean) was calculated for each major waterbird group at each lake, and for Naivasha, Elmenteita and Nakuru combined (combined lakes). Its variance was used to compare levels of variation within and across lakes. For the combined lakes, there was high variance in large piscivores (whether combined or separated into groups), grebes, rallids and flamingos. There was low variance in Palaearctic waders (combined or separated into groups), ibises and spoonbills and birds of prey. However, the lakes generally showed idiosyncratic patterns of variation across the different groups. Variance in the indices for birds of prey and kingfishers were consistently low (max. 0.036 and 0.042, respectively), but no group had consistently high variance across all sites. The variance for all birds (other than flamingos) combined was low (0.018 – 0.085) and similar across all lakes and for combined lakes (0.018). For the combined lakes, the variance for flamingos was five times higher than for all other birds (p<0.05), though the two variances were almost equal for Bogoria. Flamingos were the most variable at Naivasha (variance 0.281) followed by Elmenteita (0.177), Nakuru (0.101) and Bogoria (0.024, and significantly lower than all the rest, p<0.05). This was opposite in order to the mean numbers of flamingos recorded at each site. Large piscivores were relatively stable at Naivasha (variance 0.005) but much more variable at Elmenteita (0.199) and Nakuru (0.269). Patterns of variation within lakes were correlated for some groups, such as waders at Naivasha and large piscivores at Nakuru. These correlations could be related to local ecological conditions. However, there were few large correlations across sites, and these were mainly direct. There was, therefore, no evidence that a fixed population of waterbirds was distributing itself across sites according to conditions. Each lake thus seems to represent and independent entity, while the waterbirds they host evidently move much more widely afield than this portion of the Rift Valley. 相似文献
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Recent surveys in South Africa have demonstrated that disordered eating is equally common among black and white female students. Self-report measures have been used in these surveys to establish levels of disordered eating. One study in Tanzania, where a two-stage design was implemented, showed that upon interview the majority of participants did not present with disordered eating. The absence of two-stage studies in South Africa brings into question some of the findings from these surveys. In the present study, we surveyed a sample of black and white high school students in South Africa to establish the prevalence of disordered eating. In the second phase of this study, we attempted to interview those black students from one particular school who scored high on the eating disorder measures. This process proved both challenging and elucidating. While a significant number of young black females endorsed eating disorder symptoms on self-report, interviews with some participants showed that self-starvation and related symptoms had a different meaning from what we would typically expect from someone with an eating disorder. Consequently, this study highlights the need to revisit the methods typically employed in cross-cultural research in eating disorders. Careful consideration of a variety of cultural factors that may alter the meaning of standard measures is called for. 相似文献
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Genevie M. Ntshoe Johanna M. McAnerney Brett N. Archer Sheilagh B. Smit Bernice N. Harris Stefano Tempia Mirriam Mashele Beverley Singh Juno Thomas Ayanda Cengimbo Lucille H. Blumberg Adrian Puren Jocelyn Moyes Johann van den Heever Barry D. Schoub Cheryl Cohen 《PloS one》2013,8(2)
Background
Since 1995, measles vaccination at nine and 18 months has been routine in South Africa; however, coverage seldom reached >95%. We describe the epidemiology of laboratory-confirmed measles case-patients and assess the impact of the nationwide mass vaccination campaign during the 2009 to 2011 measles outbreak in South Africa.Methods
Serum specimens collected from patients with suspected-measles were tested for measles-specific IgM antibodies using an enzyme-linked immunosorbent assay and genotypes of a subset were determined. To estimate the impact of the nationwide mass vaccination campaign, we compared incidence in the seven months pre- (1 September 2009–11 April 2010) and seven months post-vaccination campaign (24 May 2010–31 December 2010) periods in seven provinces of South Africa.Results
A total of 18,431 laboratory-confirmed measles case-patients were reported from all nine provinces of South Africa (cumulative incidence 37 per 100,000 population). The highest cumulative incidence per 100,000 population was in children aged <1 year (603), distributed as follows: <6 months (302/100,000), 6 to 8 months (1083/100,000) and 9 to 11 months (724/100,000). Forty eight percent of case-patients were ≥5 years (cumulative incidence 54/100,000). Cumulative incidence decreased with increasing age to 2/100,000 in persons ≥40 years. A single strain of measles virus (genotype B3) circulated throughout the outbreak. Prior to the vaccination campaign, cumulative incidence in the targeted vs. non-targeted age group was 5.9-fold higher, decreasing to 1.7 fold following the campaign (P<0.001) and an estimated 1,380 laboratory-confirmed measles case-patients were prevented.Conclusion
We observed a reduction in measles incidence following the nationwide mass vaccination campaign even though it was conducted approximately one year after the outbreak started. A booster dose at school entry may be of value given the high incidence in persons >5 years. 相似文献14.
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The composition and annual cycle of the zooplankton of two Ethiopian Rift Valley soda lakes is described. Lake Langano has a conductivity of 1 400 to 1800 µS cm–1 and a permanent mineral turbidity. Lake Abiata is more concentrated (conductivity 19 000 to 23 000 µS cm–1) and more alkaline but less turbid; it is characterised by dense phytoplankton blooms, mainly cyanophytes.The zooplankton assemblage is typically tropical, with relatively few species of Cladocera and Copepoda. There was a marked difference in zooplankton between the two lakes, Lake Abiata showing much higher concentrations and greater wet season/ dry season differences. The species composition was also different. Lake Abiata lacked Cladocera, and calanoid copepods occurred only during the wet season with lower conductivities. These two phenomena were attributed to high sodium bicarbonate concentration and to dense cyanophyte blooms. Eleven species of rotifers occurred in Lake Abiata, including six Brachionus spp. but B. rubens was the only rotifer found in Lake Langano. The seasonal variation of the zooplankton is discussed in relation to seasonal fluctuations in conductivity and Chl a concentration. 相似文献
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The purpose of this table is to provide the community with a citable record of publications of ongoing genome sequencing projects that have led to a publication in the scientific literature. While our goal is to make the list complete, there is no guarantee that we may have omitted one or more publications appearing in this time frame. Readers and authors who wish to have publications added to subsequent versions of this list are invited to provide the bibliographic data for such references to the SIGS editorial office.
- Phylum Crenarchaeota
- Thermoproteus tenax, strain Kra1, DSM 2078T sequence accession FN869859 [1]
- Phylum Euryarchaeota
- Haloarcula hispanica CGMCC 1.2049, sequence accession CP002921 (chromosome I), CP002922 (chromosome II), and CP002923 (plasmid pHH400) [2]
- Methanococcus maripaludis, strain X1 (unculturable) sequence accession CP002913 [3]
- Phylum Proteobacteria
- Acinetobacter baumannii strain 1656-2, sequence accession CP001921 [4]
- Arcobacter butzleri strain ED-1, sequence accession AP012047, AP012048, and AP012049 [5]
- Brucella suis strain 1330, sequence accession CP002997 and CP002998 [6]
- Campylobacter fetus subsp. venerealis NCTC 10354, sequence accession AFGH01000000 [7]
- “Chromobacterium sp.” strain C-61, sequence accession CAEE01000001 to CAEE01001118 [8]
- Cronobacter sakazakii strain E899, sequence accession AFMO00000000 [9]
- “Desulfovibrio sp.” strain A2, sequence accession AGFG01000000 [10]
- “Erythrobacter sp.” strain NAP1, sequence accession NZ_AAMW00000000 [11]
- Escherichia coli strain XH140A, sequence accession AFVX01000000 [12]
- Escherichia coli strain XH001, sequence accession AFYG01000000 [13]
- Haemophilus haemolyticus strain M19107, sequence accession AFQN00000000 [14]
- Haemophilus haemolyticus strain M19501, sequence accession AFQO00000000 [14]
- Haemophilus haemolyticus strain M21127, sequence accession AFQP00000000 [14]
- Haemophilus haemolyticus strain M21621, sequence accession AFQQ00000000 [14]
- Haemophilus haemolyticus strain M21639, sequence accession AFQR00000000 [14]
- Idiomarina sp.” strain A28L, sequence accession AFPO01000001 to AFPO01000028 [15]
- Ketogulonicigenium vulgare” strain WSH-001, sequence accession CP002018 (chromosome), CP002019 (plasmid pKVU_100), and CP002020 (plasmid pKVU_200) [16]
- Methylobacter tundripaludum strain SV96, sequence accession AEGW00000000 [17]
- Pseudogulbenkiania sp.” strain NH8B, sequence accession AP012224 [18]
- Pseudomonas aeruginosa NCGM1179, sequence accession DF126593 through DF126613 [19]
- Pseudomonas putida strain B001, sequence accession CAED01000001 to CAEE01000262 [20]
- Pseudomonas putida strain B6-2, sequence accession AGCS01000000 [21]
- Pseudomonas stutzeri CGMCC 1.1803, sequence accession CP002881 [22]
- Ralstonia solanacearum phylotype IB, strain Y45, sequence accession AFWL01000000 [23]
- Rheinheimera sp.” strain A13L, sequence accession AFHI01000001 through AFHI01000072 [24]
- Sphingobium yanoikuyae strain XLDN2-5, sequence accession AFXE01000000 [25]
- Vibrio cholerae strain Amazonia, sequence accession AFSV01000000 [26]
- Phylum Firmicutes
- Bacillus coagulans strain XZL4, sequence accession AFWM01000000 [27]
- Bacillus megaterium strain WSH-002, sequence accession CP003017 (chromosome), plasmids CP003018 (plasmid pBME_100), CP003019 (plasmid pBME_200), and CP003020 (plasmid pBME_300) [28]
- Bacillus pumilus strain S-1, sequence accession AGBY00000000 [29]
- “Desulfosporosinus sp.” strain OT, sequence accession AGAF01000000 [30]
- Lentibacillus jeotgali strain Grbi, sequence accession AGAV01000000 [31]
- Leuconostoc carnosum KCTC 3525, sequence accession BACM01000000 [32]
- Listeria ivanovii subsp. ivanovii strain PAM 55, sequence accession FR687253 [33]
- Paenibacillus riograndensis strain SBR5, sequence accession AGBD01000000 [34]
- Sporolactobacillus inulinus strain CASD, sequence accession AFVQ00000000 [35]
- Streptococcus pseudopneumoniae strain IS7493, sequence accession CP002925 and CP002926 [36]
- Streptococcus salivarius strain 57.I, sequence accession CP002888 and CP002889 [37]
- Streptococcus salivarius strain M18, sequence accession AGBV01000000 [38]
- Streptococcus suis SS12, sequence accession CP002640 [39]
- Streptococcus suis D9, sequence accession CP002641 [39]
- Streptococcus suis D12, sequence accession CP002644 [39]
- Streptococcus suis ST1, sequence accession CP002651 [39]
- Weissella thailandensis strain fsh4-2, sequence accession HE575133 through HE575182 [40]
- Phylum Tenericutes
- Mycoplasma anatis strain 1340, sequence accession AFVJ00000000 [41]
- Mycoplasma capricolum subsp. capripneumoniae strain M1601, sequence accession AENG01000000 [42]
- Mycoplasma putrefaciens Type strain KS1, sequence accession CP003021 [43]
- Corynebacterium pseudotuberculosis strain PAT10, sequence accession CP002924 [44]
- Phylum Actinobacteria
- Bifidobacterium animalis subsp. lactis strain BLC1, sequence accession CP003039 [45]
- Bifidobacterium breve strain DPC 6330, sequence accession AFXX01000000 [46]
- Brachybacterium squillarum strain M-6-3, sequence accession AGBX01000000 [47]
- “Citricoccus sp.” strain CH26A, sequence accession AFXQ01000000 [48]
- Corynebacterium glutamicum strain S9114, sequence accession AFYA01000000 [49]
- Dietzia alimentaria strain 72, sequence accession AGFF01000000 [50]
- Mycobacterium colombiense CECT 3035, sequence accession AFVW00000000 [51]
- Mycobacterium tuberculosis NCGM2209, sequence accession DF126614 and DF126615 [52]
- Rhodococcus erythropolis strain XP, sequence accession AGCF01000000 [53]
- Serinicoccus profundi MCCC 1A05965T, sequence accession AFYF00000000 [54]
- Phylum Spirochaetes
- Leptospira interrogans, sequence accession CP001221 (CI), CP001222 (CII) [55]
- Phylum Bacteroidetes
- Bacteroides faecis Type strain MAJ27T, sequence accession AGDG01000000 [56]
- Bizionia argentinensis, Type strain JUB59T sequence accession AFXZ01000000 [57]
- Flavobacterium branchiophilum strain FL-15, sequence accession FQ859183 [58]
- “Flavobacteriaceae” strain S85, sequence accession AFPK00000000 [59]
- Phylum Thermotogae
- “Thermotoga sp.” strain RQ2, sequence accession CP000969 [60]
Non-Bacterial genomes
- Aspergillus kawachii IFO 4308, sequence accession DF126447 through DF126592, BACL01000001 through BACL01001641, AP012272 [61]
- Cajanus cajan pigeonpea, sequence accession PRJNA72815 [62]
- Coxsackievirus A22, sequence accession JN542510 [63]
- Gordonia phage GRU1, sequence accession JF923797 [64]
- Gordonia phage GTE5, sequence accession JF923796 [64]
- Heterocephalus glaber naked mole rat, sequence accession AFSB00000000, AFSB01000000 [65]
- Human Adenovirus Prototype 17, sequence accession HQ910407 [66]
- Macaca mulatta lasiota rhesus macaque, sequence accession AEHL00000000 [67]
- Macaca mulatta mulatta rhesus macaque, sequence accession AEHK00000000 [67]
- Porcine epidemic diarrhea virus, sequence accession JN547228 [68]
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