Epidermal three-dimensional (3D) topography/quantification has not been completely characterized yet. The recently developed line-field confocal optical coherence tomography (LC-OCT) provides real-time, high-resolution, in-vivo 3D imaging of the skin. This pilot study aimed at quantifying epidermal metrics (epidermal thicknesses, dermal-epidermal junction [DEJ] undulation and keratinocyte number/shape/size) using 3D LC-OCT. For each study participant (8 female, skintype-II, younger/older volunteers), seven body sites were imaged with LC-OCT. Epidermal metrics were calculated by segmentations and measurements assisted by artificial intelligence (AI) when appropriate. Thicknesses of epidermis/SC, DEJ undulation and keratinocyte nuclei volume varied across body sites. Evidence of keratinocyte maturation was observed in vivo: keratinocyte nuclei being small/spherical near the DEJ and flatter/elliptical near the skin surface. Skin microanatomy can be quantified by combining LC-OCT and AI.This technology could be highly relevant to understand aging processes and conditions linked to epidermal disorders. Future clinical/research applications are to be expected in this scenario.
In vitro cellular models are promising tools for studying normal and pathological conditions. One of their important applications is the development of genetically engineered biosensor systems to investigate, in real time, the processes occurring in living cells. At present, there are fluorescence, protein-based, sensory systems for detecting various substances in living cells (for example, hydrogen peroxide, ATP, Ca2+ etc.,) or for detecting processes such as endoplasmic reticulum stress. Such systems help to study the mechanisms underlying the pathogenic processes and diseases and to screen for potential therapeutic compounds. It is also necessary to develop new tools for the processing and analysis of obtained microimages. Here, we present our web-application CellCountCV for automation of microscopic cell images analysis, which is based on fully convolutional deep neural networks. This approach can efficiently deal with non-convex overlapping objects, that are virtually inseparable with conventional image processing methods. The cell counts predicted with CellCountCV were very close to expert estimates (the average error rate was < 4%). CellCountCV was used to analyze large series of microscopic images obtained in experimental studies and it was able to demonstrate endoplasmic reticulum stress development and to catch the dose-dependent effect of tunicamycin.
IntroductionWaiting rooms in general practitioners' (GP) surgeries are a potentially useful site for spreading educational messages about health behaviors. We aimed to evaluate the impact of posters displayed in GPs' waiting rooms on the number of donors attending the blood donation drives in the Aube Department of France. The secondary objective was to identify self-reported factors that incited people to give blood among donors who did and donors who did not see the posters.MethodsObservational, multicenter, prospective study, from 1 June to 31 December 2021. Six blood donation centers in the Aube Department were selected. All GPs located within a 15 km radius around each center were invited to participate by hanging posters advertising blood drives in their waiting rooms. The number of blood donations per hour was measured before and during the campaign. Factors prompting people to give blood were evaluated by questionnaires completed by persons attending the blood drives.Results33 GPs participated. The number of donations per hour was lower in the year in which the posters were displayed (2021) compared to the previous year (12 vs. 15). A total of 1,469 questionnaires were completed by blood donors: 729 reported having seen the posters, and 740 reported not having seen the posters. Those who claimed to have seen the posters were more likely than those who claimed not to have seen the posters to respond that in parallel, they had been prompted to give blood via online publicity (7.5 vs. 3.9%, adjusted Odds ratio [aOR] 1.75, 95% confidence interval [CI] 1.12–2.82, p = 0.02). They also more often reported that they had been prompted to donate by television advertisements (8.0 vs. 4.2%, aOR 1.74, 95%CI 1.10–2.76, p = 0.02). Overall, 68% of all respondents indicated that posters in the GP's waiting room would incite them to give blood more often.ConclusionThe number of blood donations per hour was lower during the year in which posters were displayed. Questionnaire data from donors suggests that promoting blood donation via posters in GPs' waiting rooms could have a positive effect: 68% of donors claimed that posters would incite them to give blood.
The in vitro cellular models are promising tools for studying normal and pathological conditions. One of their important applications is the development of genetically engineered biosensor systems to investigate the processes occurring in living cells in real time. Today, there are fluorescence protein based sensory systems for detecting various substances in living cells (for example, hydrogen peroxide, ATP, Ca 2+ etc.) or for detecting processes such as endoplasmic reticulum stress. Such systems help to study mechanisms underlying the pathogenic processes and diseases and for screening potential therapeutic compounds. It is also necessary to develop new tools for processing and analysis of obtained microimages. Here we present our web-application CellCountCV for automation of microscopy cell images analysis which is based on fully-convolutional deep neural networks. This approach can efficiently deal with non-convex overlapping objects, that are virtually inseparable with conventional image processing methods. The cell counts predicted with CellCountCV were very close to expert estimates (the average error rate was < 4%). CellCountCV was used to analyse large series of microscopy images obtained in experimental studies and it was able to demonstrate the endoplasmic reticulum stress development and to catch the dose-dependent effect of tunicamycin.
New data released by the American Society of Plastic Surgeons shows that breast augmentation was the number one surgical procedure for body enhancement in 2018, with 313,735 procedures, up 4 percent from 2017. 1 The prosthesis is often placed beneath the pectoralis major muscle to decrease the capsular contracture rate, noticeable upper pole rippling, and an abrupt transition overlying the implant. However, one of the drawbacks of submuscular placement is that the muscle must be transected along its inferior and medial borders to allow the implant to rest beneath the breast mound and to provide good
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