Depth-dependent hydration dynamics in human skin: Vehicle-controlled efficacy assessment of a functional 10% urea plus NMF moisturizer by near-infrared confocal spectroscopic imaging (KOSIM IR) and capacitance method complemented by volunteer perception.

BACKGROUND: Stratum corneum (SC) hydration is vital for the optimal maintenance and appearance of healthy skin. In this context, we evaluated the efficacy of an NMF-enriched moisturizer containing 10% urea on different aspects of SC hydration of dry skin. MATERIAL AND METHODS: In two clinical studies, the hydration efficacy of the moisturizer in comparison to its vehicle was investigated. In the first study, 42 subjects applied the moisturizer and the vehicle to one lower leg each. Thirty minutes and 24 h after this single treatment, SC hydration was measured by corneometry. Volunteers also rated skin moisturization and evaluated product properties. In the second study, 27 subjects each treated one forearm twice daily for 2 weeks with the moisturizer and the vehicle. Then, depth-resolved water-absorption spectra were measured by near-infrared confocal spectroscopic imaging (KOSIM IR). RESULTS: The moisturizer exerted a superior hydrating effect compared to the vehicle. KOSIM IR measurements show that, compared to the vehicle, the moisturizer significantly improved the water gradient in the SC from the surface to a depth of 15 µm. Moreover, the moisturizer received high acceptance ratings from the volunteers and was preferred to the vehicle. CONCLUSION: The humectants applied in the investigated moisturizer improved SC water content in total and as a function of depth. The combination of depth-resolved data (KOSIM IR) with classical corneometry provides an integrated concept in the measurement of skin hydration, rendering both methods complementary. These findings were in line with the volunteers` self-assessments of the moisturizer properties that are relevant to treatment adherence.

Improved sample preparation for MALDI-MSI of endogenous compounds in skin tissue sections and mapping of exogenous active compounds subsequent to ex-vivo skin penetration.

Localization of endogenous and exogenous compounds directly in tissue sections is a challenging task in skin research. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a powerful label-free technique that enables determination of the distribution of a large range of biomolecules directly in tissue sections. Nevertheless, its application in this field is limited in large part by the low adhesion of skin tissue sections to indium-tin oxide-coated (ITO) glass slides. For the first time corona discharge (CD) treatment was used to modify the glass slide surface for improved adhesion. Localization of endogenous cholesterol sulfate was performed directly in human skin tissue sections. A spatial resolution of approximately 30 µm was sufficient for assignment of mass signals to skin structure morphology. Furthermore, imaging of an exogenous model compound, Nile red, was performed directly in skin tissue sections after ex-vivo penetration into porcine skin, enabling determination of the pathway and depth of penetration. Finally, the ion density map of Nile red was compared with its high resolution fluorescence micrograph. This work provides new insights into the application of MALDI-MSI in skin research.

A new protocol for functional analysis of adipogenesis using reverse transfection technology and time-lapse video microscopy.

Since the worldwide increase in obesity represents a growing challenge for healthcare systems, research focusing on fat cell metabolism has become a focal point of interest. Here, we describe a small interfering RNA (siRNA)-technology-based screening method to study fat cell differentiation in human primary preadipocytes that could be further developed towards an automated middle-throughput screening procedure. First, we established optimal conditions for the reverse transfection of human primary preadipocytes demonstrating that an efficient reverse transfection of preadipocytes is technically feasible. Aligning the processes of reverse transfection and fat cell differentiation utilizing peroxisome proliferator-activated receptor gamma (PPAR gamma)-siRNA, we showed that preadipocyte differentiation was suppressed by knock-down of PPAR gamma, the key regulator of fat cell differentiation. The use of fluorescently labelled fatty acids in combination with fluorescence time-lapse microscopy over a longer period of time enabled us to quantify the PPAR gamma phenotype. Additionally, our data demonstrate that reverse transfection of human cultured preadipocytes with TIP60 (HIV-1 Tat-interacting protein 60)-siRNA lead to a TIP60 knock-down and subsequently inhibits fat cell differentiation, suggesting a role of this protein in human adipogenesis. In conclusion, we established a protocol that allows for an efficient functional and time-dependent analysis by quantitative time-lapse microscopy to identify novel adipogenesis-associated genes.

Structural investigations of human hairs by spectrally resolved ellipsometry.

Human hair is a biological layered system composed of two major layers, the cortex and the cuticle. We show spectrally resolved ellipsometry measurements of the ellipsometric parameters Psi and Delta of single human hairs. The spectra reflect the layered nature of hair and the optical anisotropy of the hair's structure. In addition, measurements on strands of human hair show a high reproducibility of the ellipsometric parameters for different hair fiber bundles from the same person. Based on the measurements, we describe a dielectric model of hair that explains the spectra in terms of the dielectric properties of the major parts of hair and their associated layer thicknesses. In addition, surface roughness effects modeled by a roughness layer with a complex refractive index given by an effective medium approach can be seen to have a significant effect on the measurements. We derive values for the parameters of the cuticle surface roughness layer of the thickness d(ACu)=273 to 360 nm and the air inclusion fA=0.6 to 5.7%.

Melanoma diagnosis by Raman spectroscopy and neural networks: structure alterations in proteins and lipids in intact cancer tissue.

Melanoma is the most aggressive skin cancer. The specificity and sensitivity of clinical diagnosis varies from around 40% to 80%. Here, we investigated whether the chemical changes in the melanoma tissue detected by Raman spectroscopy and neural networks can be used for diagnostic purposes. Near-infrared Fourier transform Raman spectra were obtained from samples of melanoma (n=22) and other skin tumors that can be clinically confused with melanoma: pigmented nevi (n=41), basal cell carcinoma (n=48), seborrheic keratoses (n=23), and normal skin (n=89). A sensitivity analysis of spectral frequencies used by a neural network was performed to determine the importance of the individual components in the Raman spectra. Visual inspection of the Raman spectra suggested that melanoma could be differentiated from pigmented nevi, basal cell carcinoma, seborrheic keratoses, and normal skin due to the decrease in the intensity of the amide I protein band around 1660 cm-1. Moreover, melanoma and basal cell carcinoma showed an increase in the intensity of the lipid-specific band peaks around 1310 cm-1 and 1330 cm-1, respectively. Band alterations used in the visual inspection were also independently identified by a neural network for melanoma diagnosis. The sensitivity and specificity for diagnosis of melanoma achieved by neural network analysis of Raman spectra were 85% and 99%, respectively. We propose that neural network analysis of near-infrared Fourier transform Raman spectra could provide a novel method for rapid, automated skin cancer diagnosis on unstained skin samples.