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Background/objectives: The Recaller app was developed to help individuals record their food intakes. This pilot study evaluated the usability of this new food picture application (app), which operates on a smartphone with an embedded camera and Internet capability., Subjects/methods: Adults aged 19 to 28 years (23 males and 22 females) were assigned to use the Recaller app on six designated, nonconsecutive days in order to capture an image of each meal and snack before and after eating. The images were automatically time-stamped and uploaded by the app to the Recaller website. A trained nutritionist administered a 24-hour dietary recall interview 1 day after food images were taken. Participants' opinions of the Recaller app and its usability were determined by a follow-up survey. As an evaluation indicator of usability, the number of images taken was analyzed and multivariate Poisson regression used to model the factors determining the number of images sent., Results: A total of 3,315 food images were uploaded throughout the study period. The median number of images taken per day was nine for males and 13 for females. The survey showed that the Recaller app was easy to use, and 50% of the participants would consider using the app daily. Predictors of a higher number of images were as follows: greater interval (hours) between the first and last food images sent, weekend, and female., Conclusions: The results of this pilot study provide valuable information for understanding the usability of the Recaller smartphone food picture app as well as other similarly designed apps. This study provides a model for assisting nutrition educators in their collection of food intake information by using tools available on smartphones. This innovative approach has the potential to improve recall of foods eaten and monitoring of dietary intake in nutritional studies.

Genetic variation on the non-recombining portion of the Y chromosome contains information about the ancestry of male lineages. Because of their low rate of mutation, single nucleotide polymorphisms (SNPs) are the markers of choice for unambiguously classifying Y chromosomes into related sets of lineages known as haplogroups, which tend to show geographic structure in many parts of the world. However, performing the large number of SNP genotyping tests needed to properly infer haplogroup status is expensive and time consuming. A novel alternative for assigning a sampled Y chromosome to a haplogroup is presented here. We show that by applying modern machine-learning algorithms we can infer with high accuracy the proper Y chromosome haplogroup of a sample by scoring a relatively small number of Y-linked short tandem repeats (STRs). Learning is based on a diverse ground-truth data set comprising pairs of SNP test results (haplogroup) and corresponding STR scores. We apply several independent machine-learning methods in tandem to learn formal classification functions. The result is an integrated high-throughput analysis system that automatically classifies large numbers of samples into haplogroups in a cost-effective and accurate manner.

Dysregulation of epigenetic control is an important participant in carcinogenesis. The PML/RAR alpha translocation in acute promyelocytic leukemia (APL) is an example where the resultant fusion protein recruits histone deacetylase complexes to target genes resulting in their inappropriate transcriptional repression. All-trans-retinoic acid (ATRA) acts as a ligand that relieves this repression and produces an epigenetic transcriptional reprogramming of the cancer cell. CpG island microarrays were used to analyze the DNA methylation and histone acetylation state of the human APL cell line NB4 before and after differentiation with ATRA as well as normal peripheral blood mononuclear cells (PBMC). Over 70 CpG islands within 1 kb of transcription start of a known gene are aberrantly methylated in NB4 cells compared with PBMC; however, no changes in cytosine methylation were detected following ATRA-induced differentiation. With respect to histone H4 acetylation, over 100 single-copy CpG islands within 1 kb of transcription start of a known human gene became hyperacetylated following ATRA-induced differentiation. One CpG island was aberrantly methylated in NB4 cells, but became hyperacetylated and was induced following ATRA treatment and was associated with the HoxA1 gene, suggesting it may be a target gene of ATRA in APL. In addition to single-copy sequences, a selective increase in acetylation was detected in satellite DNA when compared with other high-copy sequences, such as Alu or rDNA. In summary, ATRA stimulates complex epigenomic changes during leukemic cell differentiation, and monitoring these changes may help to identify new targets of epigenetic dysfunction.