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Background: Occupational exposure to sunlight, in particular to blue light (wavelength of 380-550 nm), is a risk factor for several pathologies, including chronic retinal photochemical damage and, more specifically, age-related macular degeneration (AMD). Moreover, in addition to the effect of blue light, there is evidence about the role of near ultraviolet light (UV-A) as a risk factor for AMD since, given the wavelength, a precise "turning point" between effect and no effect is not definable., Methods and Results: This work reports the case of a woman employed in the agricultural sector from 15 to 25 years of age, with no significant occupational exposure to other risk factors for AMD, who later developed this pathology. The case is of particular interest given that she worked as a "mondina", a task involving the transplanting of young rice seedlings into water-flooded fields and manual weed control. This practice, although replaced by the introduction of pesticides, entailed the exposure to sunlight reflection on the water surface in addition to direct exposure to natural light., Conclusion: This brief case-report points out that occupational exposure to the short wavelength component of visible light and UV-A deserve further attention regarding preventive measures and the adoption of adequate personal protective equipment, in particular in productive sectors involving lengthy eye exposure to solar radiation and to the reflectance of surrounding surfaces. Furthermore, the cases of AMD and cataract should receive a complete and accurate occupational anamnesis for a more proper recognition of the possible role of occupational solar radiation exposure in the induction of the disease.

Background: Sequencing technologies are generating enormous amounts of read data, however assembly of genomes and metagenomes remain among the most challenging tasks. In this paper we study the comparison of genomes and metagenomes only based on read data, using word counts statistics called alignment-free thus not requiring reference genomes or assemblies. Quality scores produced by sequencing platforms are fundamental for various analyses, moreover future-generation sequencing platforms, will produce longer reads but with error rate around 15 %. In this context it will be fundamental to exploit quality values information within the framework of alignment-free measures., Results: In this paper we present a family of alignment-free measures, called d (q) -type, that are based on k-mer counts and quality values. These statistics can be used to compare genomes and metagenomes based on their read sets. Results show that the evolutionary relationship of genomes can be reconstructed based on the direct comparison of theirs reads sets., Conclusion: The use of quality values on average improves the classification accuracy, and its contribution increases when the reads are more noisy. Also the comparison of metagenomic microbial communities can be performed efficiently. Similar metagenomes are quickly detected, just by processing their read data, without the need of costly alignments.

Background: The data volume generated by Next-Generation Sequencing (NGS) technologies is growing at a pace that is now challenging the storage and data processing capacities of modern computer systems. In this context an important aspect is the reduction of data complexity by collapsing redundant reads in a single cluster to improve the run time, memory requirements, and quality of post-processing steps like assembly and error correction. Several alignment-free measures, based on k-mers counts, have been used to cluster reads. Quality scores produced by NGS platforms are fundamental for various analysis of NGS data like reads mapping and error detection. Moreover future-generation sequencing platforms will produce long reads but with a large number of erroneous bases (up to 15 %)., Results: In this scenario it will be fundamental to exploit quality value information within the alignment-free framework. To the best of our knowledge this is the first study that incorporates quality value information and k-mers counts, in the context of alignment-free measures, for the comparison of reads data. Based on this principles, in this paper we present a family of alignment-free measures called D (q) -type. A set of experiments on simulated and real reads data confirms that the new measures are superior to other classical alignment-free statistics, especially when erroneous reads are considered. Also results on de novo assembly and metagenomic reads classification show that the introduction of quality values improves over standard alignment-free measures. These statistics are implemented in a software called QCluster (http://www.dei.unipd.it/~ciompin/main/qcluster.html).

Background: With the advent of Next-Generation Sequencing technologies (NGS), a large amount of short read data has been generated. If a reference genome is not available, the assembly of a template sequence is usually challenging because of repeats and the short length of reads. When NGS reads cannot be mapped onto a reference genome alignment-based methods are not applicable. However it is still possible to study the evolutionary relationship of unassembled genomes based on NGS data., Results: We present a parameter-free alignment-free method, called Under2, based on variable-length patterns, for the direct comparison of sets of NGS reads. We define a similarity measure using variable-length patterns, as well as reverses and reverse-complements, along with their statistical and syntactical properties. We evaluate several alignment-free statistics on the comparison of NGS reads coming from simulated and real genomes. In almost all simulations our method Under2 outperforms all other statistics. The performance gain becomes more evident when real genomes are used., Conclusion: The new alignment-free statistic is highly successful in discriminating related genomes based on NGS reads data. In almost all experiments, it outperforms traditional alignment-free statistics that are based on fixed length patterns.