Wavelength-Dependent Effects of Photobiomodulation for Wound Care in Diabetic Wounds.

Photobiomodulation, showing positive effects on wound healing processes, has been performed mainly with lasers in the red/infrared spectrum. Light of shorter wavelengths can significantly influence biological systems. This study aimed to evaluate and compare the therapeutic effects of pulsed LED light of different wavelengths on wound healing in a diabetic (db/db) mouse excision wound model. LED therapy by Repuls was applied at either 470 nm (blue), 540 nm (green) or 635 nm (red), at 40 mW/cm2 each. Wound size and wound perfusion were assessed and correlated to wound temperature and light absorption in the tissue. Red and trend-wise green light positively stimulated wound healing, while blue light was ineffective. Light absorption was wavelength-dependent and was associated with significantly increased wound perfusion as measured by laser Doppler imaging. Shorter wavelengths ranging from green to blue significantly increased wound surface temperature, while red light, which penetrates deeper into tissue, led to a significant increase in core body temperature. In summary, wound treatment with pulsed red or green light resulted in improved wound healing in diabetic mice. Since impeded wound healing in diabetic patients poses an ever-increasing socio-economic problem, LED therapy may be an effective, easily applied and cost-efficient supportive treatment for diabetic wound therapy.

Correction: Wind et al. Topical Bimiralisib Shows Meaningful Cutaneous Drug Levels in Healthy Volunteers and Mycosis Fungoides Patients but No Clinical Activity in a First-in-Human, Randomized Controlled Trial. Cancers 2022, 14, 1510.

The authors wish to make the following corrections to this paper [...].

Ivermectin treatment in rosacea: How novel smartphone technology can support monitoring rosacea-associated signs and symptoms.

Rosacea lessens patients' quality of life not only by visible symptoms like erythema, papules, and pustules but also by invisible symptoms like stinging, burning, and dryness. Ivermectin 1% cream has recently been introduced as an efficient therapy for papules and pustules in rosacea patients. To investigate the potential of ivermectin 1% cream to improve rosacea-associated erythema and invisible symptoms by combining established questionnaires with the novel photography and analysis tool Scarletred®Vision. We performed an open monocentric pilot study including 25 Caucasian patients presenting with moderate to severe rosacea with erythema, less than 10 papules and/or pustules, and ≥ 15 Demodex mites/cm2 . Patients applied 1 g of ivermectin 1% cream (Soolantra®) once a day for ≥16 weeks. Skin symptoms were recorded at baseline, week 8 and ≥ week 16. Grade of erythema was determined by clinician erythema assessment (CEA) and patient self-assessment (PSA). Severity of invisible skin symptoms (stinging and/or burning, dryness, itching) were assessed by questionnaire. Erythema and skin texture were additionally quantified using Scarletred®Vision. Ivermectin 1% cream significantly reduced invisible symptoms of rosacea (stinging and/or burning, dryness: p < 0.0001; itching p < 0.001; at ≥16 weeks). Analysis with Scarletred®Vision confirmed CEA and PSA results for improvement of erythema (p < 0.0001; at ≥16 weeks) and skin roughness (p < 0.001; at ≥16 weeks). Treatment with ivermectin 1% cream is efficient in treating not only rosacea-associated papules and pustules but also erythema and invisible skin symptoms.

Sensitivity and Specificity of SARS-CoV-2 Rapid Antigen Detection Tests Using Oral, Anterior Nasal, and Nasopharyngeal Swabs: a Diagnostic Accuracy Study.

The objective of our study was to evaluate the sensitivity and specificity of rapid antigen detection tests versus those of reverse transcriptase PCR (RT-PCR) using oral, anterior nasal, and nasopharyngeal swabs. The underlying prospective, diagnostic case-control-type accuracy study included 87 hospitalized and nonhospitalized participants in a positive and a negative sample cohort between 16 March and 14 May 2021 in two hospitals in Vienna. SARS-CoV-2 infection status was confirmed by RT-PCR. Participants self-performed one oral and one anterior nasal swab for the rapid antigen test, immediately followed by two nasopharyngeal swabs for the rapid antigen test and RT-PCR by the investigator. Test results were read after 15 min, and participants completed a questionnaire in the meantime. Test parameters were calculated based on the evaluation of 87 participants. The overall sensitivity of rapid antigen detection tests versus that of RT-PCR with oral, anterior nasal, and nasopharyngeal samples was 18.18% (95% confidence interval [CI] 8.19% to 32.71%), 63.04% (95% CI 47.55% to 76.79%), and 73.33% (95% CI 58.06% to 85.4%), respectively. All sampling methods had a test specificity of 100% regardless of the cycle threshold (CT) value. Rapid antigen detection tests using self-collected anterior nasal swabs proved to be as sensitive as and more tolerable than professionally collected nasopharyngeal swabs for CT values up to 30 determined by RT-PCR. This finding illustrates the reliability of tests obtained by adequate self-collected anterior nasal specimen. Sensitivity was dependent upon the CT value for each sampling method. While the main advantage of rapid antigen detection tests is the immediate availability of results, PCR should be preferred in crucial settings wherever possible. IMPORTANCE Rapid antigen detection devices for SARS-CoV-2 represent a valuable tool for monitoring the spread of infection. However, the reliability of the tests depends largely on the test performance and the respective sampling method. Nasopharyngeal swabs mark the gold standard for sample collection in suspected respiratory tract infections but are unsuitable for widespread application, as they must be performed by medically trained personnel. With the underlying study, the head-to-head test performance and the usability of self-collected samples for SARS-CoV-2 detection using rapid antigen detection devices were evaluated. The results confirm similar sensitivity of self-collected anterior nasal swabs to that of professionally collected nasopharyngeal swabs for patients with a CT of < 30 determined by RT-PCR.

The mathematics of erythema: Development of machine learning models for artificial intelligence assisted measurement and severity scoring of radiation induced dermatitis.

Although significant advancements in computer-aided diagnostics using artificial intelligence (AI) have been made, to date, no viable method for radiation-induced skin reaction (RISR) analysis and classification is available. The objective of this single-center study was to develop machine learning and deep learning approaches using deep convolutional neural networks (CNNs) for automatic classification of RISRs according to the Common Terminology Criteria for Adverse Events (CTCAE) grading system. ScarletredⓇ Vision, a novel and state-of-the-art digital skin imaging method capable of remote monitoring and objective assessment of acute RISRs was used to convert 2D digital skin images using the CIELAB color space and conduct SEV* measurements. A set of different machine learning and deep convolutional neural network-based algorithms has been explored for the automatic classification of RISRs. A total of 2263 distinct images from 209 patients were analyzed for training and testing the machine learning and CNN algorithms. For a 2-class problem of healthy skin (grade 0) versus erythema (grade ≥ 1), all machine learning models produced an accuracy of above 70%, and the sensitivity and specificity of erythema recognition were 67-72% and 72-83%, respectively. The CNN produced a test accuracy of 74%, sensitivity of 66%, and specificity of 83% for predicting healthy and erythema cases. For the severity grade prediction of a 3-class problem (grade 0 versus 1 versus 2), the overall test accuracy was 60-67%, and the sensitivities were 56-82%, 35-59%, and 65-72%, respectively. For estimating the severity grade of each class, the CNN obtained an accuracy of 73%, 66%, and 82%, respectively. Ensemble learning combines several individual predictions to obtain a better generalization performance. Furthermore, we exploited ensemble learning by deploying a CNN model as a meta-learner. The ensemble CNN based on bagging and majority voting shows an accuracy, sensitivity and specificity of 87%, 90%, and 82% for a 2-class problem, respectively. For a 3-class problem, the ensemble CNN shows an overall accuracy of 66%, while for each grade (0, 1, and 2) accuracies were 76%, 69%, and 87%, sensitivities were 70%, 57%, and 71%, and specificities were 78%, 75%, and 95%, respectively. This study is the first to focus on erythema in radiation-dermatitis and produces benchmark results using machine learning models. The outcome of this study validates that the proposed system can act as a pre-screening and decision support tool for oncologists or patients to provide fast, reliable, and efficient assessment of erythema grading.

128 SHADES OF RED: Objective Remote Assessment of Radiation Dermatitis by Augmented Digital Skin Imaging.

The purpose of our investigation was to develop a novel and state of the art digital skin imaging method capable for remote monitoring and objective assessment of Radiation Induced Dermatitis (RID). Therefore, radiation therapy related side effects were assessed by medical experts according to Common Terminology Criteria for Adverse Events (CTCAE) grade of severity in 20 female breast cancer patients in a clinical trial over the treatment time frame of 25-28 radiation cycles, 50.0-50.4 Gy each. Furthermore the intensity of developed skin erythema was documented by using conventional spectrophotometry plus digital skin imaging. Thereby we could derive the Standardized Erythema Value (SEV), a novel objective parameter, which in contrast to single parametric L* and a* delivers a long dynamic measurement range for analyzing RID from bright to very dark skin tones. Methodical superiority of the SEV could be proven over spectrophotometer measurements in terms of a higher sensitivity and by enabling signal intensity mapping in analyzed skin images. Our thereupon-derived patent enables novel objective dermatologic eHealth applications in a broad range of medical and industrial use by opening likewise the window for augmented dermatology. The first of its kind system is now already further developed in form of the medical device product Scarletred®Vision. It is available on the market for primary usage in clinical trials and in medical routine.

Expression analysis of multiple myeloma CD138 negative progenitor cells using single molecule microarray readout.

We present a highly sensitive bioanalytical microarray assay that enables the analysis of small genomic sample material. By combining an optimized cDNA purification step with single molecule cDNA detection on the microarray, the platform has improved sensitivity compared to conventional systems, allowing amplification-free determination of expression profiles with as little as 600ng total RNA. Total RNA from cells was reverse transcribed into fluorescently labeled cDNA and purified employing a precipitation method that minimizes loss of cDNA material. The microarray was scanned on a fluorescence chip-reader with single molecule sensitivity. Using the newly developed platform we were able to analyze the RNA expression profile of a subpopulation of rare multiple myeloma CD138 negative progenitor (MM CD138(neg)) cells. The high-sensitivity microarray approach led to the identification of a set of 20 genes differentially expressed in MM CD138(neg) cells. Our work demonstrates the applicability of a straight-forward single-molecule DNA array technology to current topics of molecular and cellular cancer research, which are otherwise difficult to address due to the limited amount of sample material.

Hedgehog-EGFR cooperation response genes determine the oncogenic phenotype of basal cell carcinoma and tumour-initiating pancreatic cancer cells.

Inhibition of Hedgehog (HH)/GLI signalling in cancer is a promising therapeutic approach. Interactions between HH/GLI and other oncogenic pathways affect the strength and tumourigenicity of HH/GLI. Cooperation of HH/GLI with epidermal growth factor receptor (EGFR) signalling promotes transformation and cancer cell proliferation in vitro. However, the in vivo relevance of HH-EGFR signal integration and the critical downstream mediators are largely undefined. In this report we show that genetic and pharmacologic inhibition of EGFR signalling reduces tumour growth in mouse models of HH/GLI driven basal cell carcinoma (BCC). We describe HH-EGFR cooperation response genes including SOX2, SOX9, JUN, CXCR4 and FGF19 that are synergistically activated by HH-EGFR signal integration and required for in vivo growth of BCC cells and tumour-initiating pancreatic cancer cells. The data validate EGFR signalling as drug target in HH/GLI driven cancers and shed light on the molecular processes controlled by HH-EGFR signal cooperation, providing new therapeutic strategies based on combined targeting of HH-EGFR signalling and selected downstream target genes.

Drosophila genome-wide obesity screen reveals hedgehog as a determinant of brown versus white adipose cell fate.

Over 1 billion people are estimated to be overweight, placing them at risk for diabetes, cardiovascular disease, and cancer. We performed a systems-level genetic dissection of adiposity regulation using genome-wide RNAi screening in adult Drosophila. As a follow-up, the resulting approximately 500 candidate obesity genes were functionally classified using muscle-, oenocyte-, fat-body-, and neuronal-specific knockdown in vivo and revealed hedgehog signaling as the top-scoring fat-body-specific pathway. To extrapolate these findings into mammals, we generated fat-specific hedgehog-activation mutant mice. Intriguingly, these mice displayed near total loss of white, but not brown, fat compartments. Mechanistically, activation of hedgehog signaling irreversibly blocked differentiation of white adipocytes through direct, coordinate modulation of early adipogenic factors. These findings identify a role for hedgehog signaling in white/brown adipocyte determination and link in vivo RNAi-based scanning of the Drosophila genome to regulation of adipocyte cell fate in mammals.

Epidermal growth factor receptor signaling synergizes with Hedgehog/GLI in oncogenic transformation via activation of the MEK/ERK/JUN pathway.

Persistent activation of the Hedgehog (HH)/GLI signaling pathway has been implicated in the development of a number of human cancers. The GLI zinc finger transcription factors act at the end of the HH signaling cascade to control gene expression, and recent studies have shown that the activity of GLI proteins can be additionally modified by integration of distinct signals, such as the MEK/extracellular signal-regulated kinase (ERK) and phosphinositide-3 kinase (PI3K)/AKT pathway. However, little is known about the identity of the upstream activators of these HH/GLI interacting signaling pathways in cancer. Here, we provide evidence that integration of the HH/GLI and epidermal growth factor receptor (EGFR) pathway synergistically induces oncogenic transformation, which depends on EGFR-mediated activation of the RAS/RAF/MEK/ERK but not of the PI3K/AKT pathway. EGFR/MEK/ERK signaling induces JUN/activator protein 1 activation, which is essential for oncogenic transformation, in combination with the GLI activator forms GLI1 and GLI2. Furthermore, pharmacologic inhibition of EGFR and HH/GLI efficiently reduces growth of basal cell carcinoma (BCC) cell lines derived from mice with activated HH/GLI signaling. The results identify the synergistic integration of GLI activator function and EGFR signaling as a critical step in oncogenic transformation and provide a molecular basis for therapeutic opportunities relying on combined inhibition of the HH/GLI and EGFR/MEK/ERK/JUN pathway in BCC.

Selective modulation of Hedgehog/GLI target gene expression by epidermal growth factor signaling in human keratinocytes.

Hedgehog (HH)/GLI signaling plays a critical role in epidermal development and basal cell carcinoma. Here, we provide evidence that epidermal growth factor receptor (EGFR) signaling modulates the target gene expression profile of GLI transcription factors in epidermal cells. Using expression profiling and quantitative reverse transcriptase PCR, we identified a set of 19 genes whose transcription is synergistically induced by GLI1 and parallel EGF treatment. Promoter studies of a subset of GLI/EGF-regulated genes, including the genes encoding interleukin-1 antagonist IL1R2, Jagged 2, cyclin D1, S100A7, and S100A9, suggest convergence of EGFR and HH/GLI signaling at the level of promoters of selected direct GLI target genes. Inhibition of EGFR and MEK/ERK but not of phosphatidylinositol 3-kinase/AKT abrogated synergistic activation of GLI/EGF target genes, showing that EGFR can signal via RAF/MEK/ERK to cooperate with GLI proteins in selective target gene regulation. Coexpression of the GLI/EGF target IL1R2, EGFR, and activated ERK1/2 in human anagen hair follicles argues for a cooperative role of EGFR and HH/GLI signaling in specifying the fate of outer root sheath (ORS) cells. We also show that EGF treatment neutralizes GLI-mediated induction of epidermal stem cell marker expression and provide evidence that EGFR signaling is essential for GLI-induced cell cycle progression in epidermal cells. The results suggest that EGFR signaling modulates GLI target gene profiles which may play an important regulatory role in ORS specification, hair growth, and possibly cancer.

Overlapping and distinct transcriptional regulator properties of the GLI1 and GLI2 oncogenes.

The GLI transcription factors mediate the hedgehog signal in development and carcinogenesis. Basal cell carcinoma can be caused by overexpression of either GLI1 or GLI2. Though GLI1 and GLI2 have identical or very similar DNA binding specificities, some of their activities are overlapping, some are clearly distinct. We analyzed target gene specificities of GLI1 and constitutively active GLI2 (GLI2DeltaN) by global expression profiling in an inducible, well-characterized HaCaT keratinocyte expression system. Four hundred fifty-six genes up- or downregulated at least twofold were identified. GLI target gene profiles correlated well with the biological activities of these transcription factors in hair follicles and basal cell carcinoma. Upregulation of largely overlapping sets of target genes was effected by both factors, repression occurred predominantly in response to GLI2. Also, significant quantitative differences in response to GLI1 and GLI2DeltaN were found for a small number of activated genes. Since we have not detected a putative processed GLI2 repressor, these results point to specific but indirect target gene repression by GLI2DeltaN via preferential activation of one or more negative regulators.

Activation of the BCL2 promoter in response to Hedgehog/GLI signal transduction is predominantly mediated by GLI2.

Aberrant activation of the Hedgehog (HH)/GLI signaling pathway has been implicated in the development of basal cell carcinoma (BCC). The zinc finger transcription factors GLI1 and GLI2 are considered mediators of the HH signal in epidermal cells, although their tumorigenic nature and their relative contribution to tumorigenesis are only poorly understood. To shed light on the respective role of these transcription factors in epidermal neoplasia, we screened for genes preferentially regulated either by GLI1 or GLI2 in human epidermal cells. We show here that expression of the key antiapoptotic factor BCL2 is predominantly activated by GLI2 compared with GLI1. Detailed promoter analysis and gel shift assays identified three GLI binding sites in the human BCL2 cis-regulatory region. We found that one of these binding sites is critical for conferring GLI2-specific activation of the human BCL2 promoter and that the selective induction of BCL2 expression depends on the zinc finger DNA binding domain of GLI2. In vivo, GLI2 and BCL2 were coexpressed in the outer root sheath of hair follicles and BCC and in plasma cells that infiltrated BCC tumor islands. On the basis of the latter observation, we analyzed plasma cell-derived tumors and found strong expression of GLI2 and BCL2 in neoplastic cells of plasmacytoma patients, implicating HH/GLI signaling in the development of plasma cell-derived malignancies. The results reveal a central role for GLI2 in activating the prosurvival factor BCL2, which may represent an important mechanism in the development or maintenance of cancers associated with inappropriate HH signaling.

The zinc-finger transcription factor GLI2 antagonizes contact inhibition and differentiation of human epidermal cells.

In stratified epidermis, activation of the Hh/Gli signal transduction pathway has been implicated in the control of cell proliferation and tumorigenesis. The zinc-finger transcription factor Gli2 has been identified as critical mediator of the Hh signal at the distal end of the pathway, but the molecular mechanisms by which Gli2 regulates cell proliferation or induces epidermal malignancies such as basal cell carcinoma are still unclear. Here, we provide evidence for a role of human GLI2 in antagonizing contact inhibition and epidermal differentiation. We show by gene expression profiling that activation of the GLI2 oncogene in human keratinocytes activates the transcription of a number of genes involved in cell cycle progression such as E2F1, CCND1, CDC2 and CDC45L, while it represses genes associated with epidermal differentiation. Analysis of the proliferative effect of GLI2 revealed that GLI2 is able to induce G1-S phase progression in contact-inhibited keratinocytes. Detailed time-course experiments identified E2F1 as early transcriptional target of GLI2. Further, we show that GLI2 expression in human keratinocytes results in a marked downregulation of epidermal differentiation markers. The data suggest a role for GLI2 in Hh-induced epidermal neoplasia by opposing epithelial cell cycle arrest signals and epidermal differentiation.