Creating a Unified Digital Communication Strategy with Chicago Farmers Market Collective

CMFC is a group of independent farmers markets throughout Chicago that work together to get fresh produce to consumers. They need a way to digitally market their company so the message can be clearly advertised to their target market and beyond

Clues to unraveling the coral species problem: distinguishing species from geographic variation in Porites across the Pacific with molecular markers and microskeletal traits

Morphological variation in the geographically widespread coral Porites lobata can make it difficult to distinguish from other massive congeneric species. This morphological variation could be attributed to geographic variability, phenotypic plasticity, or a combination of such factors. We examined genetic and microscopic morphological variability in P. lobata samples from the Galápagos, Easter Island, Tahiti, Fiji, Rarotonga, and Australia. Panamanian P. evermanni specimens were used as a previously established distinct outgroup against which to test genetic and morphological methods of discrimination. We employed a molecular analysis of variance (AMOVA) based on ribosomal internal transcribed spacer region (ITS) sequence, principal component analysis (PCA) of skeletal landmarks, and Mantel tests to compare genetic and morphological variation. Both genetic and morphometric methods clearly distinguished P. lobata and P. evermanni, while significant genetic and morphological variance was attributed to differences among geographic regions for P. lobata. Mantel tests indicate a correlation between genetic and morphological variation for P. lobata across the Pacific. Here we highlight landmark morphometric measures that correlate well with genetic differences, showing promise for resolving species of Porites, one of the most ubiquitous yet challenging to identify architects of coral reefs

Source-Sink Estimates of Genetic Introgression Show Influence of Hatchery Strays on Wild Chum Salmon Populations in Prince William Sound, Alaska

<div><p>The extent to which stray, hatchery-reared salmon affect wild populations is much debated. Although experiments show that artificial breeding and culture influence the genetics of hatchery salmon, little is known about the interaction between hatchery and wild salmon in a natural setting. Here, we estimated historical and contemporary genetic population structures of chum salmon (<i>Oncorhynchus keta</i>) in Prince William Sound (PWS), Alaska, with 135 single nucleotide polymorphism (SNP) markers. Historical population structure was inferred from the analysis of DNA from fish scales, which had been archived since the late 1960’s for several populations in PWS. Parallel analyses with microsatellites and a test based on Hardy-Weinberg proportions showed that about 50% of the fish-scale DNA was cross-contaminated with DNA from other fish. These samples were removed from the analysis. We used a novel application of the classical source-sink model to compare SNP allele frequencies in these archived fish-scales (1964–1982) with frequencies in contemporary samples (2008–2010) and found a temporal shift toward hatchery allele frequencies in some wild populations. Other populations showed markedly less introgression, despite moderate amounts of hatchery straying. The extent of introgression may reflect similarities in spawning time and life-history traits between hatchery and wild fish, or the degree that hybrids return to a natal spawning area. The source-sink model is a powerful means of detecting low levels of introgression over several generations.</p></div

Competing models to detect DNA contamination among individuals (<i>k)</i> within a collection (<i>i</i>) across loci (<i>l</i>).

<p> Genotype index is a value assigned the apparent genotype observed during allele scoring. In uncontaminated and contaminated individuals, the probability of observing these apparent genotypes is estimated by Hardy-Weinberg expectations based on a single individual and on two individuals, respectively. See text for description.</p

Diagram of a model of genetic introgression based on the classic source-sink model of migration.

<p>Explanation of variables: <i>q_l</i> is the allele frequency at a locus in a source population and is assumed to be unchanging over <i>n</i> generations of introgression. <i>q_n,i,l</i> is the allele frequency at locus, <i>l,</i> in a wild sink population, <i>i</i> after <i>n</i> generations.</p

Chum salmon production in Prince William Sound, Alaska hatcheries.

<p>^a Last used as brood stock in 1986.</p><p>^b Includes releases at Armin F. Koernig Hatchery and Port Chalmers remote release site.</p

Neighbor-joining tree of <i>F</i>_ST between chum salmon samples from Prince William Sound, Alaska.

<p>Numbers in the tree represent bootstrap support for a node.</p

Plots of versus for 135 SNP loci in chum salmon in Prince William Sound, Alaska.

<p>Dashed line represents observed curve and solid line represents expected curve without introgression. (a) Siwash Creek, (b) Wells River (c) Beartrap Creek, (d) Constantine Creek.</p

Estimates of genetic diversity and divergence (<i>F</i>_ST) between historical (H) and contemporary (C) samples of chum salmon from Prince William Sound, Alaska.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081916#pone-0081916-t002" target="_blank">Table 2</a> for sample abbreviation. <i>F</i>_ST (below diagonal), expected heterozygosity <i>H</i>_e (diagonal in <b>bold</b>), and Probability of Fisher’s exact test over loci for selected comparisons (above diagonal) between historical (H) and contemporary (C) collections. See </p><p><i>P</i><0.001.</p

Low mortality risk but high loss to follow-up among patients in the Tanzanian national HIV care and treatment programme.

UNLABELLED: OBJECTIVE To analyse survival and retention rates of the Tanzanian care and treatment programme. METHODS: Routine patient-level data were available from 101 of 909 clinics. Kaplan-Meier probabilities of mortality and attrition after ART initiation were calculated. Mortality risks were corrected for biases from loss to follow-up using Egger's nomogram. Smoothed hazard rates showed mortality and attrition peaks. Cox regression identified factors associated with death and attrition. Median CD4 counts were calculated at 6 month intervals. RESULTS: In 88,875 adults, 18% were lost to follow up 12 months after treatment initiation, and 36% after 36 months. Cumulative mortality reached 10% by 12 months (15% after correcting for loss to follow-up) and 14% by 36 months. Mortality and attrition rates both peaked within the first six months, and were higher among males, those under 45 kg and those with CD4 counts below 50 cells/μl at ART initiation. In the first year on ART, median CD4 count increased by 126 cells/μl, with similar changes in both sexes. CONCLUSION: Earlier diagnoses through expanded HIV testing may reduce high mortality and attrition rates if combined with better patient tracing systems. Further research is needed to explore reasons for attrition