The c-Rel Subunit of NF-κB Regulates Epidermal Homeostasis and Promotes Skin Fibrosis in Mice

The five subunits of transcription factor NF-κB have distinct biological functions. NF-κB signaling is important for skin homeostasis and aging, but the contribution of individual subunits to normal skin biology and disease is unclear. Immunohistochemical analysis of the p50 and c-Rel subunits within lesional psoriatic and systemic sclerosis skin revealed abnormal epidermal expression patterns, compared with healthy skin, but RelA distribution was unaltered. The skin of Nfkb1−/− and c-Rel−/− mice is structurally normal, but epidermal thickness and proliferation are significantly reduced, compared with wild-type mice. We show that the primary defect in both Nfkb1−/− and c-Rel−/− mice is within keratinocytes that display reduced proliferation both in vitro and in vivo. However, both genotypes can respond to proliferative stress, with 12-O-tetradecanoylphorbol-13-acetate–induced epidermal hyperproliferation and closure rates of full-thickness skin wounds being equivalent to those of wild-type controls. In a model of bleomycin-induced skin fibrosis, Nfkb1−/− and c-Rel−/− mice displayed opposite phenotypes, with c-Rel−/− mice being protected and Nfkb1−/− developing more fibrosis than wild-type mice. Taken together, our data reveal a role for p50 and c-Rel in regulating epidermal proliferation and homeostasis and a profibrogenic role for c-Rel in the skin, and identify a link between epidermal c-Rel expression and systemic sclerosis. Modulating the actions of these subunits could be beneficial for treating hyperproliferative or fibrogenic diseases of the skin

Importance of Duration, Duty-Cycling and Thresholds for the Implementation of Ultraviolet C in Marine Biofouling Control

The introduction of a surface into the marine environment begins a process known as biofouling, which increases the weight and hydrodynamic drag of the fouled structure. This process is detrimental to maritime vessels and costs the industry ∼$150B in fuel and maintenance spending annually. Preventing the settlement of fouling organisms mitigates these issues and limits the spread of non-indigenous species (NIS). This is primarily achieved via antifouling paints. Ultraviolet light is a sterilization method used in water purification, food storage packaging, and within medical fields. Ultraviolet C (UV-C) radiation interacts with DNA to prevent growth, proliferation, and survival of bacteria, and biofilm formation. Recent progress in microelectronics technology has advanced the range of commercially available light-emitting diodes (LEDs) to include the UV wavelengths, and the reduced size and cost has allowed their integration into previously inaccessible locales. This study builds on recent progress in integrating UV-C LEDs into UV-lucent silicone tiles for fouling control. The operational cycle needed to prevent growth of Navicula incerta cells was determined. Constant irradiance at a peak of 5.77 μW/cm2 resulted in a significant reduction in diatoms within 2 h, and a 2 log and 3 log reduction after 48 h and 5 days, respectively. Duty cycling (pulsing) in all variations from 50 to 2.5%, indicated significant reductions in cell densities, and the lowest cycle could effectively reduce biofouling growth and increase the longevity of the LEDs for up to 45.6 years. Irradiance and exposure were altered over a set duration and indicated a restriction in growth between 0.01–0.82 J/cm2 and an increased mortality at irradiances > 2.65 J/cm2, suggesting an effective antifouling threshold between these dosages. The effective dosage for 1 log reduction in fouling was estimated to be 25 J/cm2 but varied according to irradiance delivery method. Effective dosage for a 1 log reduction between experimental methods was variable indicating that UV treatment of N. incerta departed from the Bunsen-Roscoe reciprocity law expectancy. The variation in densities at similar dosages could be explained with further investigation of DNA repair mechanisms. In conclusion, UV-B/C use was effective at all irradiances, including as low as 0.01 J/cm2, and holds considerable promise for marine biofouling control

Human and computational models of atopic dermatitis:A review and perspectives by an expert panel of the International Eczema Council

Atopic dermatitis (AD) is a prevalent disease worldwide and is associated with systemic comorbidities representing a significant burden on patients, their families, and society. Therapeutic options for AD remain limited, in part because of a lack of well-characterized animal models. There has been increasing interest in developing experimental approaches to study the pathogenesis of human AD in vivo, in vitro, and in silico to better define pathophysiologic mechanisms and identify novel therapeutic targets and biomarkers that predict therapeutic response. This review critically appraises a range of models, including genetic mutations relevant to AD, experimental challenge of human skin in vivo, tissue culture models, integration of “omics” data sets, and development of predictive computational models. Although no one individual model recapitulates the complex AD pathophysiology, our review highlights insights gained into key elements of cutaneous biology, molecular pathways, and therapeutic target identification through each approach. Recent developments in computational analysis, including application of machine learning and a systems approach to data integration and predictive modeling, highlight the applicability of these methods to AD subclassification (endotyping), therapy development, and precision medicine. Such predictive modeling will highlight knowledge gaps, further inform refinement of biological models, and support new experimental and systems approaches to AD

Using Real-World Data to Guide Ustekinumab Dosing Strategies for Psoriasis: A Prospective Pharmacokinetic-Pharmacodynamic Study.

Variation in response to biologic therapy for inflammatory diseases, such as psoriasis, is partly driven by variation in drug exposure. Real-world psoriasis data were used to develop a pharmacokinetic/pharmacodynamic (PK/PD) model for the first-line therapeutic antibody ustekinumab. The impact of differing dosing strategies on response was explored. Data were collected from a UK prospective multicenter observational cohort (491 patients on ustekinumab monotherapy, drug levels, and anti-drug antibody measurements on 797 serum samples, 1,590 measurements of Psoriasis Area Severity Index (PASI)). Ustekinumab PKs were described with a linear one-compartment model. A maximum effect (Emax ) model inhibited progression of psoriatic skin lesions in the turnover PD mechanism describing PASI evolution while on treatment. A mixture model on half-maximal effective concentration identified a potential nonresponder group, with simulations suggesting that, in future, the model could be incorporated into a Bayesian therapeutic drug monitoring "dashboard" to individualize dosing and improve treatment outcomes

Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning

Growing interest in food quality and traceability by regulators as well as consumers demands advances in more rapid, versatile and cost-effective analytical methods. Milk, as most food matrices, is a heterogeneous mixture composed of metabolites, lipids and proteins. One of the major challenges is to have simultaneous, quantitative detection (profiling) of this panel of biomolecules to gather valuable information for assessing food quality, traceability and safety. Here, for milk analysis, atmospheric pressure (AP) matrix-assisted laser desorption/ionization (MALDI) employing homogenous liquid sample droplets was used on a Q-TOF mass analyzer. This method has the capability to produce multiply charged proteinaceous ions as well as highly informative profiles of singly charged lipids/metabolites. In two examples, this method is coupled with user-friendly machine-learning software. First, rapid speciation of milk (cow, goat, sheep and camel) is demonstrated with 100% classification accuracy. Second, the detection of cow milk as adulterant in goat milk is shown at concentrations as low as 5% with 92.5% sensitivity and 94.5% specificity

Persistence and Effectiveness of Non-Biologic Systemic Therapies for Moderate-Severe Psoriasis in Adults: a Systematic Review

BACKGROUND: The persistence and effectiveness of systemic therapies for moderate-to-severe psoriasis in current clinical practice are poorly characterized. OBJECTIVES: To systematically review observational studies investigating the persistence and effectiveness of acitretin, ciclosporin, fumaric acid esters (FAE) and methotrexate, involving at least 100 adult patients with moderate-to-severe psoriasis, exposed to therapy for ≥ 3 months. METHODS: MEDLINE, Embase, the Cochrane Library and PubMed were searched from 1 January 2007 to 1 November 2017 for observational studies reporting on persistence (therapy duration or the proportion of patients discontinuing therapy during follow-up) or effectiveness [improvements in Psoriasis Area and Severity Index (PASI) or Physician's Global Assessment (PGA)]. This review was registered with PROSPERO, number CRD42018099771. RESULTS: Of 411 identified studies, eight involving 4624 patients with psoriasis were included. Variations in the definitions and analyses of persistence and effectiveness outcomes prevented a meta-analysis from being conducted. One prospective multicentre study reported drug survival probabilities of 23% (ciclosporin), 42% (acitretin) and 50% (methotrexate) at 1 year. Effectiveness outcomes were not reported for either acitretin or ciclosporin. The persistence and effectiveness of FAE and methotrexate were better characterized, but mean discontinuation times ranged from 28 to 50 months for FAE and 7·7 to 22·3 months for methotrexate. At 12 months of follow-up, three studies reported that 76% (FAE), 53% (methotrexate) and 59% (methotrexate) of patients achieved ≥ 75% reduction in PASI, and one reported that 76% of FAE-exposed patients achieved a markedly improved or clear PGA. CONCLUSIONS: The comparative persistence and effectiveness of acitretin, ciclosporin, FAE and methotrexate in real-world clinical practice in the past decade cannot be well described due to the inconsistency of the methods used

Differential Drug Survival of Biologic Therapies for the Treatment of Psoriasis: A Prospective Observational Cohort Study from the British Association of Dermatologists Biologic Interventions Register (BADBIR)

Drug survival reflects a drug’s effectiveness, safety, and tolerability. We assessed the drug survival of biologics used to treat psoriasis in a prospective national pharmacovigilance cohort (British Association of Dermatologists Biologic Interventions Register (BADBIR)). The survival rates of the first course of biologics for 3,523 biologic-naive patients with chronic plaque psoriasis were compared using survival analysis techniques and predictors of discontinuation analyzed using a multivariate Cox proportional hazards model. Data for patients on adalimumab (n=1,879), etanercept (n=1,098), infliximab (n=96), and ustekinumab (n=450) were available. The overall survival rate in the first year was 77%, falling to 53% in the third year. Multivariate analysis showed that female gender (hazard ratio (HR) 1.22; 95% confidence interval (CI): 1.09–1.37), being a current smoker (HR 1.19; 95% CI: 1.03–1.38), and a higher baseline dermatology life quality index (HR 1.01; 95% CI: 1.00–1.02) were predictors of discontinuation. Presence of psoriatic arthritis (HR 0.82; 95% CI: 0.71–0.96) was a predictor for drug survival. As compared with adalimumab, patients on etanercept (HR 1.63; 95% CI: 1.45–1.84) or infliximab (HR 1.56; 95% CI: 1.16–2.09) were more likely to discontinue therapy, whereas patients on ustekinumab were more likely to persist (HR 0.48; 95% CI: 0.37–0.62). After accounting for relevant covariates, ustekinumab had the highest first-course drug survival. The results of this study will aid clinical decision making when choosing biologic therapy for psoriasis patients

LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics

Large-scale population screening for early and accurate detection of disease is a key objective for future diagnostics. Ideally, diagnostic tests that achieve this goal are also cost-effective, fast and easily adaptable to new diseases with the potential of multiplexing. Mass spectrometry (MS), particularly MALDI MS profiling, has been explored for many years in disease diagnostics, most successfully in clinical microbiology but less in early detection of diseases. Here, we present liquid atmospheric pressure (LAP)-MALDI MS profiling as a rapid, large-scale and cost-effective analysis platform for multiplexing disease analysis. Using this new platform, two different types of tests exemplify its potential in early disease diagnosis and response to therapy. First, it is shown that LAP-MALDI MS profiling detects bovine mastitis two days before its clinical manifestation with a sensitivity of up to 70% and a specificity of up to 100%. This highly accurate, pre-symptomatic detection is demonstrated by using a large set of milk samples collected weekly over six months from approximately 500 dairy cows. Second, the potential of LAP-MALDI MS in antimicrobial resistance (AMR) detection is shown by employing the same mass spectrometric setup and similarly simple sample preparation as for the early detection of mastitis