Defining a Unique Gene Expression Profile in Mature and Developing Keloids.

Keloids are benign, fibroproliferative dermal tumors that typically form owing to abnormal wound healing. The current standard of care is generally ineffective and does not prevent recurrence. To characterize keloid scars and better understand the mechanism of their formation, we performed transcriptomic profiling of keloid biopsies from a total of 25 subjects of diverse racial and ethnic origins, 15 of whom provided a paired nonlesional sample, a longitudinal sample, or both. The transcriptomic signature of nonlesional skin biopsies from subjects with keloids resembled that of control skin at baseline but shifted to closely match that of keloid skin after dermal trauma. Peripheral keloid skin and rebiopsied surrounding normal skin both showed upregulation of epithelial-mesenchymal transition markers, extracellular matrix organization, and collagen genes. These keloid signatures strongly overlapped those from healthy wound healing studies, usually with greater perturbations, reinforcing our understanding of keloids as dysregulated and exuberant wound healing. In addition, 219 genes uniquely regulated in keloids but not in normal injured or uninjured skin were also identified. This study provides insights into mature and developing keloid signatures that can act as a basis for further validation and target identification in the search for transformative keloid treatments.

Analysis of multiple bacterial species and antibiotic classes reveals large variation in the association between seasonal antibiotic use and resistance.

Understanding how antibiotic use drives resistance is crucial for guiding effective strategies to limit the spread of resistance, but the use-resistance relationship across pathogens and antibiotics remains unclear. We applied sinusoidal models to evaluate the seasonal use-resistance relationship across 3 species (Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae) and 5 antibiotic classes (penicillins, macrolides, quinolones, tetracyclines, and nitrofurans) in Boston, Massachusetts. Outpatient use of all 5 classes and resistance in inpatient and outpatient isolates in 9 of 15 species-antibiotic combinations showed statistically significant amplitudes of seasonality (false discovery rate (FDR) < 0.05). While seasonal peaks in use varied by class, resistance in all 9 species-antibiotic combinations peaked in the winter and spring. The correlations between seasonal use and resistance thus varied widely, with resistance to all antibiotic classes being most positively correlated with use of the winter peaking classes (penicillins and macrolides). These findings challenge the simple model of antibiotic use independently selecting for resistance and suggest that stewardship strategies will not be equally effective across all species and antibiotics. Rather, seasonal selection for resistance across multiple antibiotic classes may be dominated by use of the most highly prescribed antibiotic classes, penicillins and macrolides.

Case-based surveillance of antimicrobial resistance with full susceptibility profiles.

Surveillance of antimicrobial resistance (AMR) is essential for clinical decision-making and for public health authorities to monitor patterns in resistance and evaluate the effectiveness of interventions and control measures. Existing AMR surveillance is typically based on reports from hospital laboratories and public health laboratories, comprising reports of pathogen frequencies and resistance frequencies among each species detected. Here we propose an improved framework for AMR surveillance, in which the unit of surveillance is patients with specific conditions, rather than biological samples of a particular type. In this 'case-based' surveillance, denominators as well as numerators will be clearly defined with clinical relevance and more comparable at the local, national and international level. In locations with sufficient resources, individual-based data on patient characteristics and full antibiotic susceptibility profiles would provide high-quality evidence for monitoring resistant pathogens of clinical importance, clinical treatment of infections and public health responses to outbreaks of infections with resistant bacteria.