The appearance of one's skin reflects a person's general health and is one of the main indicators of human age. 1 As skin ages, it tends to become uneven in color, roughened, lax, and wrinkled due to intrinsic and extrinsic factors (eg, photodamage). A major feature of aged skin is fragmentation of the dermal collagen matrix. Fragmentation results from the actions of specific enzymes (matrix metalloproteinases) and impairs the structural integrity of the dermis. Fibroblasts that produce and organize the collagen matrix cannot attach to fragmented collagen. Loss of attachment prevents fibroblasts from receiving mechanical information from their support, and they collapse. 2 Stretch is critical for normal balanced production of collagen and collagen-degrading enzymes. In aged skin, collapsed fibroblasts produce low levels of collagen and high levels of collagen-degrading enzymes. This imbalance advances the aging process in a selfperpetuating, never-ending deleterious cycle. 2 Many different materials, energy-based devices, and techniques have been shown to offer good results in facial rejuvenation. 3 Ablative techniques are still considered the most effective methods for improving photodamaged skin, but are associated with a prolonged recovery time and high risk of side effects. 4 The CO 2 and Er:YAG (2940 nm) wavelengths are ablative wavelengths used for many different applications including facial skin resurfacing.Ablative lasers vaporize the epidermis and part of the dermis, leaving a zone of thermal injury responsible for collagen shrinkage and remodeling. [5][6][7] Post-procedure, the epidermis has to heal, requiring at least some recovery time. Non-invasive and minimally/non-ablative methods without downtime are therefore gaining popularity in modern dermatological laser therapy. Recently, a non-ablative mode of
Уральский федеральный университет имени первого Президента России Б.Н. Ельцина, г. Екатеринбург, Россия проГноЗироВаниЕ покаЗаТЕлЕЙ конкУрЕнТоСпоСоБноСТи крУпнЫХ проиЗВодСТВЕннЫХ комплЕкСоВ Аннотация. В статье на основе анализа существующих подходов к оценке и прогнозированию конкурентоспособности предприятий и производственных комплексов предложен оригинальный авторский методический инструментарий к проведению такой оценки и прогнозированию показателей конкурентоспособности производственных комплексов. В основу оценки конкурентоспособности производственных комплексов положена методика, комплексно учитывающая различные стороны деятельности исследуемого ПК на основе сравнительного анализа с ведущими конкурентами в разрезе двух крупных направлений: текущей конкурентоспособности и конкурентного потенциала производственного комплекса. В рамках указанных направлений сформирована блочная структура показателей конкурентоспособности производственного комплекса, включающая следующие блоки показателей: для оценки текущей конкурентоспособности-операционной эффективности и положения на рынке, конкурентоспособности основных видов продукции, состояния и эффективности функционирования производственно-технологической базы, эффективность функционирования кадров и кадровой политики, качества организации и управления деятельностью, инвестиционной и инновационной активности, рисков, связанных с деятельностью производственного комплекса; для оценки конкурентного потенциала-потенциала использования производственной мощности, рыночного потенциала, соответствия кадровой квалификации персонала требованиям научно-технического прогресса. По каждому блоку разработаны состав отдельных показателей конкурентоспособности, их базовые (эталонные) значения, подходы и алгоритмы к определению (расчету) показателей. В основу прогнозирования показателей конкурентоспособности производственных комплексов положен сценарный подход, опирающийся на сценарные условия развития экономики страны и ключевых рынков сбыта продукции рассматриваемых производственных комплексов. Сформирован пошаговый алгоритм построения прогноза значений бизнес-показа-881
AIM: to assess the diagnostic accuracy of the main dermatoscopic signs and algorithms used to diagnose skin melanoma. MATERIALS AND METHODS: To assess the diagnostic effectiveness of the performed dermatoscopy in detecting skin melanoma, the main dermatoscopic signs that occur in this disease were identified: atypical pigment network, atypical globules, asymmetry of pigmentation and structure, asymmetric stripes, asymmetric zones of hyperpigmentation (spots), blue-white (white-blue) veil, graininess, scar-like foci of depigmentation, white shiny stripes, negative pigment network. The study was carried out based on the analysis of 34 archival dermatoscopic images of melanocytic skin lesions with a morphologically verified diagnosis (11 melanomas and 23 melanocytic nevi). In addition, a comparison was made of the indicators of the diagnostic efficiency of two main dermatoscopic algorithms used in the diagnosis of skin melanoma: the algorithm by 3 signs and by 7 signs. For this, 186 archived dermatoscopic images of melanocytic skin lesions were analyzed. All patients included in the study were examined and treated at the clinic for skin and venereal diseases in the period from 2015 to 2019. The study was carried out using a HEINE DELTA 20 Plus dermatoscope in immersion mode and in cross-polarization. RESULTS: The following dermatoscopic features had the highest diagnostic efficiency for the diagnosis of skin melanoma: blue-white veil (86.8%), asymmetry of pigmentation and structure (82.6%), and white shiny stripes (72.8%). The diagnostic efficiency of the 3 signs algorithm was 93.0%, the 7 signs algorithm 90.5%. CONCLUSION: Diagnostic algorithms for confirming melanoma can be successfully used by both general practitioners and medical specialists (dermatologists, oncologists). In this case, it is preferable to use the three signs algorithm at the initial admission of patients as a screening option, and the seven-signs algorithm by experienced specialists in the field of dermatoscopy to confirm the diagnosis (4 figures, 3 tables, bibliography: 11 refs).
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