This paper aims at three aspects closely related to each other: first, it presents the state of the art in the area of thinning methodologies, by giving descriptions of general ideas of the most significant algorithms with a comparison between them. Secondly, it proposes a new thinning algorithm that presents interesting properties in terms of processing quality and algorithm clarity, enriched with examples. Thirdly, the work considers parallelization issues for intrinsically sequential algorithms of thinning. The main advantage of the suggested algorithm is its universality, which makes it useful and versatile for a variety of applications.

Insulin resistance and hyperandrogenemia observed in polycystic ovary syndrome (PCOS) are associated with metabolic disturbances and could be connected with body composition pattern. To date, several studies defining the parameters of body composition using dual energy X-ray absorptiometry (DXA) method in the group of PCOS patients have been published, however, without the analysis in different phenotypes. The aim of the present study was to investigate the relationships between serum androgens concentration, insulin resistance and distribution of fat mass using DXA method in various PCOS phenotypes according to the Rotterdam criteria. We examined 146 women: 34 (38%) had PCOS phenotype A, 20 (23%) phenotype B, 20 (23%) phenotype C and 15 (16%) phenotype D (with mean age of each phenotype 25 years), and 57 control subjects (mean age of 25.5 years). Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated. Serum concentrations of testosterone, androstenedione and dehydroepiandrosterone sulfate (DHEA-S) were assessed and free androgen index (FAI) was calculated. In phenotypes A, B and C, we observed higher FAI in comparison to the control group (all p < 0.01). Serum concentrations of androstenedione and DHEA-S were higher in phenotypes A and C in comparison to the control group (all p < 0.01). However, only in phenotype A we found higher visceral adipose tissue (VAT) mass and android/gynoid ratio (A/G ratio) in comparison to the control group (all p < 0.01). In phenotype A, we observed connection of VAT with FAI (r = 0.58, p < 0.01). Accordingly, A/G ratio was related with FAI in all phenotypes (all p < 0.05). Additionally, in phenotype C, A/G ratio was related to serum concentrations of DHEA-S and androstenedione (r = 0.46, p = 0.03; r = 0.53, p = 0.01, respectively). We also found connections of HOMA-IR with VAT and A/G ratio in all phenotypes (all p < 0.05). Women with phenotype A had higher amount of VAT and A/G ratio in comparison to the control group. Serum concentration of androgens and insulin resistance are connected with VAT and A/G ratio in normoandrogenic and hyperandrogenic PCOS phenotypes.

Objective: Women with polycystic ovary syndrome (PCOS) are characterized by insulin resistance and higher prevalence of obesity. Serum ferritin is increased in obesity and is associated with insulin resistance. The aim of the present study was to evaluate the relationships between serum ferritin concentration with insulin resistance and body composition estimated by dual-energy X-ray absorptiometry (DXA) in PCOS women in comparison to the control group. Patients and Methods: One hundred four women were enrolled to the study−65 women with PCOS and 39 women matched for age and BMI as a control group. Serum ferritin concentration and oral glucose tolerance test (OGTT) were performed. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated. DXA was performed to estimate fat, fat-free mass, and visceral adipose tissue (VAT). Results: Women with PCOS have higher serum concentration of ferritin (p = 0.002), insulin at baseline (p = 0.03), at 60 min of OGTT (p = 0.01), at 120 min of OGTT (p = 0.004), HOMA-IR (p = 0.03), and VAT (p = 0.0001) in comparison to the control group. We observed a relationship of serum ferritin with insulin concentration at baseline (r = 0.25, p = 0.04) and at 120 min of OGTT (r = 0.31, p = 0.01) and with HOMA-IR (r = 0.30, p = 0.01) in the PCOS group. We noticed an association between serum ferritin concentration and VAT (r = 0.42, p = 0.001), trunk fat mass (r = 0.25, p = 0.04), and android fat mass (r = 0.25, p = 0.04) in the PCOS group. Multiple regression analysis revealed that ferritin (p = 0.02, β = 0.17), insulin at baseline (p = 0.001, β = 0.30), glucose at the 120 min of OGTT (p = 0.007, β = 0.26), and triglycerides (p = 0.001, β = 0.33) were independent predictors of VAT amount in PCOS women. Conclusions: Elevated serum ferritin concentration is connected with insulin resistance as well as with DXA-estimated VAT, android, and trunk fat mass in PCOS women, and could be a marker of metabolic dysfunction.

Women with polycystic ovary syndrome (PCOS) are at an increased risk of developing insulin resistance and abdominal obesity in the state of an improper diet balance. Leptin is a peptide considered to be a satiety hormone that plays an important role in the long-term energy balance, whereas ghrelin is a hormone that controls short-term appetite regulation and is considered a hunger hormone. The aim of the present study was to assess the relationship between serum leptin and ghrelin concentrations and the dietary macronutrient content in PCOS women. We examined 73 subjects: 39 women diagnosed with PCOS by the Rotterdam criteria and 34 healthy controls, matched by the body mass index. The subjects completed a consecutive three-day dietary diary to identify the macronutrient and micronutrient intake. Serum concentrations of leptin and total ghrelin were measured and homeostasis model assessment of insulin resistance (HOMA-IR) was calculated. The studied groups did not differ significantly in terms of the intake of macronutrients (proteins, fats, and carbohydrates) and serum concentrations of ghrelin and leptin (all p > 0.05). In the PCOS group, the serum leptin concentration positively correlated with the intake of total fat (r = 0.36, p = 0.02), total cholesterol (r = −0.36, p = 0.02), saturated fatty acids (r = 0.43, p < 0.01), and monounsaturated fatty acids (MUFA) (r = 0.37, p = 0.02), whereas the serum ghrelin concentration correlated in an inverse manner with the intake of total fat (r = −0.37, p = 0.02), MUFA (r = −0.37, p = 0.02), polyunsaturated fatty acids (r = −0.34, p = 0.03), and long chain polyunsaturated fatty acids (r = −0.38, p = 0.02). In this group, we also found a negative association of HOMA-IR with serum ghrelin levels (r = −0.4, p = 0.03) and a positive relationship with the serum leptin concentration (r = 0.5, p < 0.01) and relationships between HOMA-IR and total dietary fat (r = 0.38, p = 0.03) and MUFA (r = 0.35, p = 0.04) intake. In PCOS women, dietary components such as the total fat and type of dietary fat and HOMA-IR are positively connected to serum leptin concentrations and negatively connected to serum ghrelin concentrations, which may influence the energy balance.

Objective: It has been shown that women with polycystic ovary syndrome (PCOS), as well as Hashimoto's thyroiditis (HT), are characterized by increased incidence of infertility. Serum anti-Müllerian hormone (AMH), which reflects ovarian reserve, is elevated in PCOS women and is decreased in women with HT. The Rotterdam criteria recognize four clinical PCOS phenotypes, i.e., phenotypes A, B, C, and D. The aim of the present study was to investigate the relation between serum concentrations of thyroid peroxidase antibodies (TPOAbs) and ovarian reserve in different PCOS phenotypes. Patients and methods: We examined 141 women with PCOS [phenotype A was diagnosed in 67 (47.5%) women, phenotype B in 30 (21.3%), phenotype C in 28 (19.9%), and phenotype D in 16 (11.3%)] and 88 control subjects of similar age; all women were euthyroid. Serum concentrations of AMH, thyroid-stimulating hormone (TSH), thyroid hormones, and TPOAbs were assessed. Results: We observed positive serum TPOAbs in 21.9% women with PCOS and in 23.9% controls (p = 0.07). We did not find differences in the frequency of detection of positive serum TPOAbs between phenotypes A, B, and C and the control group (p > 0.05). We did not observe a difference in AMH levels between TPOAbs-positive and TPOAbs-negative women, both in the control group and the PCOS women (all p > 0.05). However, serum AMH concentration was markedly higher in the whole PCOS group (p < 0.01) and in phenotype A (p < 0.01) vs. controls when the serum concentration of TPOAbs was negative. In the groups with positive serum levels of TPOAbs, serum concentration of AMH did not differ between PCOS phenotypes and controls (p = 0.23). Additionally, we observed that serum AMH concentration was related to the level of TPOAbs in the PCOS group (r = −0.4, p = 0.02). Conclusions: The frequency of serum detection of positive TPOAbs did not differ between PCOS phenotypes with clinical/biochemical hyperandrogenism and the control Adamska et al. AMH and TPOAbs in PCOS Phenotypes group. The observation of the difference in serum AMH between the PCOS and control groups only in TPOAbs negative women together with the inverse relation of TPOAbs with serum AMH only in the PCOS group might suggest that ovarian reserve is influenced by TPOAbs in PCOS.