The SLICE-3D dataset: 400,000 skin lesion image crops extracted from 3D TBP for skin cancer detection.

AI image classification algorithms have shown promising results when applied to skin cancer detection. Most public skin cancer image datasets are comprised of dermoscopic photos and are limited by selection bias, lack of standardization, and lend themselves to development of algorithms that can only be used by skilled clinicians. The SLICE-3D ("Skin Lesion Image Crops Extracted from 3D TBP") dataset described here addresses those concerns and contains images of over 400,000 distinct skin lesions from seven dermatologic centers from around the world.

A protocol for annotation of total body photography for machine learning to analyze skin phenotype and lesion classification.

Introduction: Artificial Intelligence (AI) has proven effective in classifying skin cancers using dermoscopy images. In experimental settings, algorithms have outperformed expert dermatologists in classifying melanoma and keratinocyte cancers. However, clinical application is limited when algorithms are presented with 'untrained' or out-of-distribution lesion categories, often misclassifying benign lesions as malignant, or misclassifying malignant lesions as benign.

Validating the Reliability and Clinical Relevance of a Nasolabial Fold Photonumeric Scale.

Background: The use of tissue fillers to treat age-related deepening of the nasolabial fold (NLF) has increased and become the standard clinical approach, creating a need for evidence-based, objective evaluation for pre- and post-procedure assessment of the NLF.

Methods: A 5-point rating scale was developed to assess the NLF, specifically the presence of depression and shadowing. Live validation of the scale was performed with a total of 73 participants representing the full range of NLF severities.

Phenotypic and genotypic survey of antibiotic resistance in isolates from dairy farms in Uruguay.

is an important zoonotic pathogen that is frequently identified in dairy farming systems. An increase in antibiotic resistance has led to inadequate results of treatments, with impacts on animal and human health. Here, the phenotypic and genotypic susceptibility patterns of isolates from dairy cattle and dairy farm environments were evaluated and compared.

3D Whole-body skin imaging for automated melanoma detection.

Background: Existing artificial intelligence for melanoma detection has relied on analysing images of lesions of clinical interest, which may lead to missed melanomas. Tools analysing the entire skin surface are lacking.

Objectives: To determine if melanoma can be distinguished from other skin lesions using data from automated analysis of 3D-images.

Listeria innocua isolated from diseased ruminants harbour minor virulence genes of L. monocytogenes.

Listeriosis is one of the most common nervous diseases in ruminants, and is caused almost exclusively by the Gram-positive bacterium, Listeria monocytogenes. However, there are few reports of listeriosis associated with L. innocua, which is genetically closely related to L.

A New Model to Simulate Human Facial Appearance, Accurately, and Realistically, across Age and Ethnicity.

Background: The human population is aging globally, and there is significant, growing interest in modeling and simulating facial appearance.

Methods: The authors describe a new means to model and simulate aging in facial images, using an approach based entirely on 3D whole-face data collected from 1250 female subjects, across 5 ethnicities, ages 10-80.

Results: Three models were built, each describing changes with age within each ethnic group, namely shape, color, and topography.

Development and qualification of a machine learning algorithm for automated hair counting.

Objective: Determining the amount of hair on the scalp has always been an important metric of patient satisfaction for hair growth and hair retention technologies. While simple in concept, this measurement is a difficult, resource intensive task for the dermatologist and the research scientist. Specifically, counting and measuring hair in phototrichogram images is very time consuming and labour intensive.

Reproducible Naevus Counts Using 3D Total Body Photography and Convolutional Neural Networks.

Background: The number of naevi on a person is the strongest risk factor for melanoma; however, naevus counting is highly variable due to lack of consistent methodology and lack of inter-rater agreement. Machine learning has been shown to be a valuable tool for image classification in dermatology.

Objectives: To test whether automated, reproducible naevus counts are possible through the combination of convolutional neural networks (CNN) and three-dimensional (3D) total body imaging.

Salmonella enterica Serovars Dublin and Enteritidis Comparative Proteomics Reveals Differential Expression of Proteins Involved in Stress Resistance, Virulence, and Anaerobic Metabolism.

The Enteritidis and Dublin serovars of are phylogenetically closely related yet differ significantly in host range and virulence. Enteritidis is a broad-host-range serovar that commonly causes self-limited gastroenteritis in humans, whereas Dublin is a cattle-adapted serovar that can infect humans, often resulting in invasive extraintestinal disease. The mechanism underlying the higher invasiveness of Dublin remains undetermined.

Does Shiga Toxin-Producing and Contribute Significantly to the Burden of Antimicrobial Resistance in Uruguay?

Shiga toxin-producing (STEC) and are worldwide recognized zoonotic pathogens. Recent reports have emerged about the circulation of antimicrobial-resistant STEC and isolates. To assess the frequency of antimicrobial resistance and related genes in these pathogens, we studied 45 STEC and 50 isolates locally recovered from different sources.

Publisher Correction: Comparative genomics of Salmonella enterica serovar Enteritidis ST-11 isolated in Uruguay reveals lineages associated with particular epidemiological traits.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Comparative genomics of Salmonella enterica serovar Enteritidis ST-11 isolated in Uruguay reveals lineages associated with particular epidemiological traits.

Salmonella enterica serovar Enteritidis is a major cause of foodborne disease in Uruguay since 1995. We used a genomic approach to study a set of isolates from different sources and years. Whole genome phylogeny showed that most of the strains are distributed in two major lineages (E1 and E2), both belonging to MLST sequence type 11 the major ST among serovar Enteritidis.

Urban metagenomics uncover antibiotic resistance reservoirs in coastal beach and sewage waters.

Background: Microbial communities present in environmental waters constitute a reservoir for antibiotic-resistant pathogens that impact human health. For this reason, a diverse variety of water environments are being analyzed using metagenomics to uncover public health threats. However, the composition of these communities along the coastal environment of a whole city, where sewage and beach waters are mixed, is poorly understood.

Draft Genome Sequences of Two Multidrug-Resistant Salmonella enterica Serovar Typhimurium Clinical Isolates from Uruguay.

Multidrug-resistant Salmonella enterica isolates are an increasing problem worldwide; nevertheless, the mechanisms responsible for such resistance are rarely well defined. Multidrug-resistant S. enterica serovar Typhimurium isolates ST3224 and ST827 were collected from two patients.

First Release of the Bacterial Biobank of the Urban Environment (BBUE).

Metagenomics is providing a broad overview of bacterial functional diversity; however, culturing and biobanking are still essential for microbiology. Here, we present the Bacterial Biobank of the Urban Environment (BBUE), a sizable culture collection for long-term storage and characterization of the microbiota associated with urban environments relevant for public health.

A novel prophage identified in strains from Salmonella enterica serovar Enteritidis is a phylogenetic signature of the lineage ST-1974.

Salmonella enterica serovar Enteritidis is a major agent of foodborne diseases worldwide. In Uruguay, this serovar was almost negligible until the mid 1990s but since then it has become the most prevalent. Previously, we characterized a collection of strains isolated from 1988 to 2005 and found that the two oldest strains were the most genetically divergent.

A Naturally Occurring Deletion in FliE from Salmonella enterica Serovar Dublin Results in an Aflagellate Phenotype and Defective Proinflammatory Properties.

serovar Dublin is adapted to cattle but is able to infect humans with high invasiveness. An acute inflammatory response at the intestine helps to prevent dissemination to systemic sites. Flagella contribute to this response by providing motility and FliC-mediated signaling through pattern recognition receptors.

Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification.

Recent research has helped to cultivate growing awareness that machine-learning systems fueled by big data can create or exacerbate troubling disparities in society. Much of this research comes from outside of the practicing data science community, leaving its members with little concrete guidance to proactively address these concerns. This article introduces issues of discrimination to the data science community on its own terms.

Effects of intrinsic aging and photodamage on skin dyspigmentation: an explorative study.

Photoaging is associated with increasing pigmentary heterogeneity and darkening of skin color. However, little is known about age-related changes in skin pigmentation on sun-protected areas. The aim of this explorative study was to measure skin color and dyspigmentation using image processing and to evaluate the reliability of these parameters.

Quantifying dyspigmentation in facial skin ageing: an explorative study.

Objective: The skin melanin system is affected by ageing, resulting in dyspigmentation with associated clinical and psychosocial consequences. In dark skinned phenotypes, broad evidence is available, whereas little is known about pigmentary changes in fair-skinned Caucasians. The objective of this study was to investigate age-related changes in facial pigmentation and dyspigmentation in subjects of skin phototypes II-III and to develop and test parameters for quantifying dyspigmentation.