口服抗氧化剂与日光防护

紫外线照射对皮肤产生一系列急性或慢性损伤,预防紫外线损伤越来越引起公众的注意.口服防晒剂的作用不依赖于局部应用因而更加稳定,易于调控,除了可在人群中普遍应用外,还可以用于敏感人群对紫外线损伤的预防.该文就口服抗氧化剂抗紫外线的损伤作用作一综述.     

西安市高中生日光紫外线暴露和防护的知识和行为评价

目的评价西安市高中学生日光紫外线辐射的认知水平和防护行为,阐明影响紫外线辐射安全教育的因素。方法西安市4所高中的607名在校学生,完成19个题目构成的问卷调查,问卷涉及调查对象对紫外线辐射不良作用的认识程度和采取的防护行为。运用频率描述和卡方检验处理数据。结果 77.27%(469例)和70.51%(428例)的被调查者知道紫外线辐射可以引起皮肤损伤和皮肤癌,53.71%(326例)的被调查者采取防护措施,仅有7.25%(44例)的被调查者紫外线辐射安全知识是从学校教育获得。结论高中生的紫外线辐射知识水平有限,防护行为不足,应该强调紫外线知识的学校教育。     

防晒化妆品日光防护系数与使用剂量的关系

随着人们生活水平的提高,防晒化妆品已经被越来越多的人群所使用.日光防护系数(SPF)是对防晒化妆品防护效果的评价指标,在实验室中检测防晒化妆品SPF值时使用的剂量~([1])为2.0 mg/cm~2,但人们在日常生活中的使用量远低于此剂量.降低使用剂量是否会影响防晒化妆品的防护效果,影响程度有多大?我们对此进行多中心研究.     

实验室检验体内持续皮肤黑化方法测定遮光剂UV防护指数的可重复性

目前有多种方法评价遮光剂的性能，日本化妆品工业协会（JcIA）采用持续皮肤黑化（persistant pigment darkening，PPD）方法，通过检测皮肤对所有波段UVA的反应，确定UVA防护指数（UVA protection factors，UVAPF），进而检测遮光剂作用。由于使用的检测仪器不同，受试人群不同，不同实验室即使按照PPD统一操作规程，可能也会造成UVAPF检测结果差异。最近，法国欧莱雅研究院的Dominique Moyal等对PPD方法检测结果的实验室室间差异、可重复性以及皮肤类型对结果的影响进行了研究。     

上海地区非医学专业大学生对日光照射及皮肤防护认知的随机抽样调查研究

目的探讨上海地区非医学专业大学生对日光照射及皮肤防护的认知情况。方法选取非医学专业的大学生,采用问卷方法对其掌握日光紫外线照射的认识水平和日常生活中对皮肤防护工作的方法进行随机抽样调查。结果上海地区的非医学专业大学生对日光照射和防晒认知整体水平尚可,但对日光对皮肤损伤的了解欠缺,防晒行为存在一定误区。结论皮肤科专业医师需针对性加强青年人群在日光照射及皮肤防护认知水平方面的宣传和正确指导。     

免疫防护指数对防光剂评价的研究进展

紫外线可通过诱导免疫抑制细胞因子产生、减低抗原提呈细胞的功能等途径对皮肤产生免疫抑制作用,但防光剂作为一种有效而广泛的光损伤防护措施,目前对其的评价方法还主要以针对中波紫外线的急性损伤为主,尚不能准确的评价防光剂的免疫防护作用.     

上海地区常驻居民紫外线最小红斑量的影响因素分析

目的:探讨上海常驻居民最小红斑量(minimal erythema dose,MED)与年龄、性别、皮肤日光反应类型、肤色指标、个体类型角及体质指数的关系.方法 :使用GS2004多波段SPF测试日光模拟器对受试者背部进行长波紫外线(UVA)+中波紫外线(UVB)波段照射,并测定健康受试者背部MED值,并采集肤色、皮肤...     

The relation between sun protection factor and amount of suncreen applied in vivo

BACKGROUND: The declared sun protection factor (SPF) is based on the use of a sunscreen layer of 2 mg cm(-2). However, only around a quarter (0 x 5 mg cm(-2)) of this amount is applied by sunbathers. Theoretical calculations have suggested that the effective SPF is related to sunscreen quantity in an exponential way but this was not confirmed in vitro and has not been studied in vivo. OBJECTIVES: To investigate the relation between SPF and sunscreen amount in vivo. SUBJECTS AND METHODS: On the backs of 20 healthy volunteers, five areas of 34 cm(2) each were marked. One area was phototested to determine the ultraviolet (UV) sensitivity. Four areas were treated with a sunscreen SPF 4 in different amounts: 0 x 5, 1, 2 and 4 mg cm(-2). Thirty minutes after sunscreen application a phototest was conducted on each area. The effective SPF was calculated 22-26 h after irradiation using the UV dose needed to produce just perceptible erythema (minimal erythema dose) on protected and unprotected skin. RESULTS: In all areas the mean SPF was significantly different from an SPF of 1 (no protection) (P 相似文献   

The comparison of sun protection factor values with different light sources.

Sun protection factors (SPFs) were evaluated with three light sources (sunlight, a xenon arc solar simulator, and fluorescent lamps) in indoor and outdoor studies. Two types of light, UV-A+B and UV+Visible, were obtained from the solar simulator. The untanned backs of twenty-four healthy male volunteers were used as test sites. A broad spectrum sunscreen containing SPF 6, according to the manufacturer, was used. The sunscreen tested was applied at 2 mg/cm2. The actual SPF values were 4.8 with sunlight, 6.0 with UV-A+B, 4.9 with UV+Visible, and 11.8 with fluorescent lamps. There were no significant differences between the SPF values with sunlight and those with the solar simulator; the SPF value for fluorescent lamps was significantly higher. The SPF with UV-A+B of the solar simulator was similar to that with sunlight; the use of this light served to reduce pain on tested subjects. Therefore, UV-A+B from the solar simulator seems to be the most appropriate artificial light source for evaluating sunscreens.     

Rating clothing for sun protection: current status in Australia

Clothing has been promoted as a major sun protection measure for some time, yet its performance in this role has only recently been studied. The principal test methods for measuring the photoprotectiveness of clothing are: in vitro testing, in which ultraviolet transmission through a garment is measured; and in vivo testing, where protection by the garment from human skin erythema is assessed. Our research team has been studying the fabric properties and design factors involved in photoprotection by clothing so that more effective products can be developed. Fabric properties identified include: the construction and fibre type used, the stretch and hydration states, and ultraviolet-absorbing dyes and chemicals incorporated. An exciting innovation has been the use of an ultraviolet absorber which dramatically improves a garment's rating. In Australia, we are about to have the world's first standard for rating sun-protective clothing.     

Clothing reduces the sun protection factor of sunscreens

Background Individuals are recommended to wait for 20 min following sunscreen application before dressing. However, this is probably seldom done in daily life, and therefore we investigated how dressing earlier than 20 min after application affected the sun protection factor (SPF). Objectives To determine the SPF of a sunscreen applied at different amounts at 4, 8 and 20 min before dressing. Methods An organic sunscreen was used on the backs of 22 healthy volunteers. Before SPF testing, participants wore a cotton T‐shirt for 60 min after the test areas had been uncovered for 4, 8 or 20 min after sunscreen application. The SPF was also tested on unclothed skin. Results The median SPF was 11·7 (2 mg cm^?2), 5·7 (1 mg cm^?2) and 3·3 (0·5 mg cm^?2) for unclothed skin, and 8·1 (2 mg cm^?2), 4·8 (1 mg cm^?2) and 2·2 (0·5 mg cm^?2) following an interval of 8 min before dressing. The SPF was similar for time intervals of 20 and 8 min when the amount was 1 mg cm^?2 (P = 0·48) and 2 mg cm^?2 (P = 0·56). For 0·5 mg cm^?2 there was no difference between skin clothed after 20 min and unclothed skin (P = 0·19), nor between skin clothed after 4 min and after 8 min (P = 0·28). Conclusions When sunscreens are applied at amounts of 1 and 2 mg cm^?2 the time between sunscreen application and dressing can be as little as 8 min. When less sunscreen is used the SPF is insensitive to the length of time between application and dressing.     

Durability of the sun protection factor provided by dihydroxyacetone

BACKGROUND/PURPOSE: The sunless tanning agent dihydroxyacetone (DHA) is known to protect against longwave ultraviolet radiation (UVA) and visible light. Recently, our laboratory has shown that DHA in addition offers a modest sun protection factor (SPF) in humans. We conducted this study in order to investigate the durability of the SPF provided by DHA. METHODS: Ten healthy volunteers were treated with 20% DHA cream twice in three areas on the volar forearm. One, 5 and 7 days after the second application the participants were phototested with simulated sunlight in each area. Blue reflectance was used to measure the skin coloration by DHA in the test sites. RESULTS: DHA generated a significant SPF of 3.0 at day 1, 2.0 at day 5 and 1.7 at day 7 (P<0.0001). The SPF was positively correlated to the change in blue reflectance (r=0.39, P=0.034). The loss of SPF unit/day was not significantly different between the subjects (P<0.122). However, the intercepts were significantly different (P<0.0001) indicating differences in the initial SPF obtained among the subjects. CONCLUSIONS: The SPF of DHA decreases with the same loss of SPF unit/day between humans and the durability of the SPF thus depends on the initial SPF provided.     

Machine learning for the prediction of sunscreen sun protection factor and protection grade of UVA

We report a prediction model for sunscreen sun protection factor (SPF) and protection grade of ultraviolet (UV) A (PA) based on machine learning. We illustrate with real clinical test results of UV protection ability of sunscreen for SPF and PA. With approximately 2200 individual clinical results for both SPF and PA level detection, individually, we were able to see that active ingredient information can provide accurate SPF and PA prediction rates through machine learning. Furthermore, we included four new factors—presence of pigment, concentration of pigment grade titanium dioxide, type of formulation and type of product—as additional information for the prediction model and were able to see increased prediction rates as results.