text:
An AFM-Based Nanomechanical Study of Ovarian Tissues with Pathological Conditions
Authors Ansardamavandi A, Tafazzoli-Shadpour M, Omidvar R, Nili F
Accepted for publication 2 June 2020
Published 19 June 2020 Volume 2020:15 Pages 4333—4350
Editor who approved publication: Prof. Dr. Anderson Oliveira Lobo
Arian Ansardamavandi,1 Mohammad Tafazzoli-Shadpour,1 Ramin Omidvar,2 Fatemeh Nili3
1Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran; 2Faculty of Biology, Centre for Biological Signalling Studies (BIOSS), Albert Ludwigs University Freiburg, Freiburg, Germany; 3Department of Pathology, Tehran University of Medical Sciences, Tehran, Iran
Correspondence: Mohammad Tafazzoli-Shadpour
Amirkabir University of Technology, No. 350, Hafez Ave, Valiasr Square, Tehran, Iran
Tel +98 02164542385
Email Tafazoli@aut.ac.ir
Background: Different diseases affect both mechanical and chemical features of the involved tissue, enhancing the symptoms.
Methods: In this study, using atomic force microscopy, we mechanically characterized human ovarian tissues with four distinct pathological conditions: mucinous, serous, and mature teratoma tumors, and non-tumorous endometriosis. Mechanical elasticity profiles were quantified and the resultant data were categorized using K-means clustering method, as well as fuzzy C-means, to evaluate elastic moduli of cellular and non-cellular parts of diseased tissues and compare them among four disease conditions. Samples were stained by hematoxylin–eosin staining to further study the content of different locations of tissues.
Results: Pathological state vastly influenced the mechanical properties of the ovarian tissues. Significant alterations among elastic moduli of both cellular and non-cellular parts were observed. Mature teratoma tumors commonly composed of multiple cell types and heterogeneous ECM structure showed the widest range of elasticity profile and the stiffest average elastic modulus of 14 kPa. Samples of serous tumors were the softest tissues with elastic modulus of only 400 Pa for the cellular part and 5 kPa for the ECM. Tissues of other two diseases were closer in mechanical properties as mucinous tumors were insignificantly stiffer than endometriosis in cellular part, 1300 Pa compared to 1000 Pa, with the ECM average elastic modulus of 8 kPa for both.
Conclusion: The higher incidence of carcinoma out of teratoma and serous tumors may be related to the intense alteration of mechanical features of the cellular and the ECM, serving as a potential risk factor which necessitates further investigation.
Keywords: ovarian tumors, tissue elasticity, atomic force microscopy, cellular and extra cellular matrix components
The state of health and disease among organs and tissues is defined in the cellular level. The initiation and progression of the pathological conditions are characterized by alterations in the function of biological cells, most notably due to environmental incentives. Cancer is an example that alterations in the function of cells due to mutations in cell proteins and transitions such as epithelial–mesenchymal transition cause tumor initiation, and in later stages invasion to healthy tissues through intravasation and extravasation. The function and behaviors of cancerous cells continuously change to form a new stage of cancer. Such adaptation includes physical aspects of the cell body such as mechanical properties. To invade, cancer cells need to pass through the extracellular matrix (ECM) and endothelial junctions, enter blood vessels and travel to other tissues. This requires highly deformable cells with enhanced motility. Cancer cells are known to be softer and more deformable than normal cells, and they generate higher traction forces and stronger stress fibers that enhance motility.1–3 Hence, alterations in mechanical properties of cancer cells are correlated with the biological and biochemical events in the cascade of cancer and can be used as biomarkers to distinguish cancer progress.4–6
Young's modulus of elasticity quantifies cell elasticity through the correlation between the applied force and deformation and its alterations can be used to describe the state of cell malignancy among cancer cells.6 This parameter can be estimated by nanoindentation techniques such as atomic force microscopy (AFM) through the relationship between indentation force and the intended distance,7 application of aspiration pressure on the suspended cell body and evaluation of cell deformation in micropipette aspiration technique,8 or other techniques.
AFM technique has been widely used for quantifying topography of the surface and mechanical properties of materials, as well as biological samples.9–11 A growing body of in vitro studies has mechanically characterized different cancer cell lines or cells extracted from cancerous tissues of different stages of several types of cancer.12 More recently, due to the advantage of AFM to probe very locally, mechanical characterization has been performed on sections of cancerous tissues obtained from patients to study cellular and non-cellular parts of cancerous tissue,13 indicating noticeable softening of cellular portions compared to normal tissues.14,15
Using AFM, we previously characterized layered sections of breast cancer tissues and compared them to those of normal breast tissues and distinguished differences among elastic moduli between cellular and fibrous parts of diseased and normal tissues.4 Despite a range of studies on this issue, there is still a lack of investigation on comparison of mechanical properties of cellular and fibrous parts of tumorous tissues for different types of cancer and diseases. This is especially interesting when specific tissues with different known types of tumor generation are studied such as ovarian tissue. Ovarian cancer which initiates in the ovaries, fallopian tubes, and peritoneum causes higher mortality than any other cancer of the female reproductive system mainly due to the lack of effective early screening and diagnosis.16
Alterations in mechanical properties of tissues during disease initiation and progression are mostly due to abnormal adjustments in ECM synthesis and structure,17,18 through irregular sedimentation of ECM, matrix crosslinking, or matrix degradation. Since ECM is synthesized and organized by cells, any pathological condition that affects cell behavior might influence ECM contents and structures.12,19,20 As an example, it has been shown that the ovarian tissue of patients with diseases such as polycystic ovary syndrome has higher shear modulus than healthy tissue measured by magnetic resonance elastography.21 While ECM fibers are synthesized by cells, cell behavior is mutually affected by the microenvironment due to external stimuli transferring physical signals to the cell body. In cancer progress, it has been shown that the adhesiveness of ovarian carcinoma cells directly depends on ECM components.22 In vitro studies have shown the influence of physical and structural properties of substrates on the behavior of seeded cells, as cells show better proliferation and differentiation behaviors by adapting physical properties of the substrate similar to those of ECM of the original tissue.23–25 Hence, the cell–ECM interaction and dependency necessitate study of both cell and non-cellular parts of tissues in health and disease.
In addition to cancer, it has been reported that other diseases cause changes in physical properties of cells like asthma.26 Lung parenchymal diseases lead to chemically and physically different tissues with changes in matrix stiffness leading to the altered mechanical forces on cells, which in turn may cause cellular remodeling.27 While malignant lesions of some organs such as thyroid, breast, prostate, and bladder have a stiffer microenvironment, tissues of ovarian and kidney malignant lesions tend to be softer;28,29 however, all cancerous cells are reported to be softer compared to the normal ones.30,31 Benign tumors are reported to have an average stiffness between malignant and healthy lesions.32
Ovarian tissue is a proper candidate for the study of changes in tissue and cell elasticity values related to the disease development since there are diverse types of ovarian tumors with possibly different mechanical properties depending on the disease character and progress. Hence, in this study, we examined the extent of changes on mechanical properties of cellular and non-cellular parts of diseased ovarian tissues with different types of tumors and cysts.
Depending on the cell type of origin, ovarian cystic neoplasms are grouped as epithelial tumors (mucinous and serous), germ cell tumors (mature teratoma and immature teratoma), sex cord-stromal tumors with lowest incidence, and other tumors.33 Among benign ovarian neoplasms, serous and mucinous cystadenomas and mature cystic teratoma are the most common.34,35
Ovarian mucinous and serous cystadenoma are benign tumors with different gene expressions in adhesion molecules, matrix metalloproteinases, and tumor suppressor gene (p53).36,37 With progress along different pathways, serous cystadenoma is thought to arise from a cortical inclusion cyst, but ovarian mucinous tumors, which are bigger, arise from the surface epithelium of the ovary.38,39 Teratoma is referred to germ cell tumors that are composed of several different types of tissue derived from two or three embryonic layers and comprises approximately 20% of all ovarian neoplasms. The majority of these tumors are mature cystic teratomas or dermoid cysts composed of mature elements.40,41 Endometriosis is a common gynecologic disease, in which endometrial tissue composed of endometrial stroma or endometrial-type glandular epithelium is found outside the uterus. Based on clinical findings, uterosacral ligament and ovaries are the most frequent sites of this condition.
Numerous studies have focused on the identification of ovarian tumors and their diagnostic markers;42,43 however, mechanical properties of cellular and fibrous parts of ovarian cancerous tissues have not been considered as a possible assistive biomarker to distinguish between different types of tumors or between primary ovarian carcinoma and metastatic one. Disorders or variations in the microenvironment due to disease pathogenesis and progression can affect the content and organization of cell cytoskeleton and molecular organization, resulting in altered mechanical properties.18,44,45 Hence, nano-scale evaluation of mechanical characteristics of cellular and fibrous parts of cancerous tissues can indicate the biological state of the disease both in terms of cancer type and stage of progress.
In this study, the elastic modulus of various ovarian diseased tissues including three non-malignant tumors having different origins (mucinous cystadenoma, serous cystadenoma, and mature teratoma) and one non-tumorous (endometriosis) was evaluated using AFM. The mechanical characterization was carried out by evaluating Young's modulus of elasticity of both cellular and non-cellular parts of tissues to describe the extent of change in mechanical properties on tissues caused by the state of disease. Using K-means and fuzzy C-means algorithm, the data were categorized to "naturally" distinguish between cellular and fibrous parts of tissues, as previously we applied on the breast tissue.4 A deterministic approach to label data into cellular or ECM categories aside from AFM is not possible; hence, we implemented clustering algorithms to achieve unbiased categorization. Numerical calculations were compared with pathological examinations by histopathological staining method.
Examination of ovarian tissue elasticity was performed on four different ovarian-related diseases. For each disease, samples of ovarian tissues of patients in the age range of 40–50 years old were examined with informed consent with ethical approval. The left ovarian tissues of these patients were extracted by surgery due to complications and tissue samples were provided by continuous supervision of a pathologist. The elastic moduli of different locations of tissue sections were quantified by AFM. The coordinates of indented locations were recorded during experiments. By using a mathematical calculating method, elasticity histograms were obtained and data were clustered by K-means as well as Fuzzy C-means algorithms to distinguish between elastic moduli of cellular and non-cellular zones. Accordingly, the average values of elastic moduli of cellular part and ECM were calculated. Additionally, using histopathological staining on the indented tissue samples, different parts of samples were identified. Results were compared statistically to reveal the effects of tumor-related ovarian diseases on elastic moduli of different parts of ovarian tissue. Figure 1 shows the experimental approach with a schematic representation, as well as the experimental approach for the treatment of a typical sample of mature teratoma.
Figure 1 A representation of experimental approach. (A) Schematic representation of the study. (B) AFM measurement of the mature teratoma ovarian tissue sample, the tissue was tested while adhered to a graded plate to identify the approximate location of AFM measurement with a specific dimension of (0.3 × 1 × 1.5 cm) in DMEM solution. (C) The obtained data of AFM measurements. AFM tip pushes down the tissue containing cells and ECM documenting the indentation depth (μm) versus force (nN) generated by pushing down the section. This result was used for obtaining elasticity according to the fundamental equations. (D) The image represents the sample which was prepared for histopathological staining after AFM indentation (top), and the histopathological stained section of mature teratoma (bottom).
Tissue Preparation
Samples of ovarian tissue were obtained during surgery of female subjects with different ovarian-related diseases with written informed consent of the patient, by supervision of an expert oncologist according to the procedure regarding experiments involved human subjects, approved by Ethical Committee, Cancer Research Center, Cancer Institute, Tehran University of Medical Sciences in accordance with Declaration of Helsinki,46 and published protocols.47,48 The biopsy specimens were investigated by an expert pathologist and smooth uniform samples with best features and no physical damage were chosen. For AFM tests, samples with 0.3 × 1 × 1.5 cm were carefully cut and the rest of the samples were used for pathological examinations. Test samples were examined by the pathologist and were categorized as endometriosis, mucinous cystadenoma, serous cystadenoma, and mature teratoma.
Samples were kept in DMEM solution at 4°C prior to the indentation tests which were being performed no longer than 6 hours after biopsy in order to prevent any tissue destruction.
AFM Experiment
To better locate the indentation sites for further analysis, in addition to AFM probe location, a graded transparent plate was placed under the petri dish containing samples that were pasted on them by a biocompatible glue, defining the initial location and direction of continuous indentation path.4 A Nanowizard3 atomic force microscope (JPK Instruments AG, Germany) was used in force spectroscopy mode while samples were kept in DMEM solution. Samples mounted on the stage were indented by CSC17/noAl cantilevers (MikroMasch, USA) with normal spring constant of 0.15 N/m. The cantilever spring constant was calculated with the thermal noise method.49
There is a wide range of AFM cantilevers for probing, including those with spherical and sharp tips. While due to the larger contact area, spherical tips provide more accurate estimate of elastic moduli, sharp tips provide higher spatial resolution. Since our aim was to discriminate the cellular and non-cellular parts of the tissue, low contact area was a key factor in order to ideally indent either cellular or non-cellular part in a force cycle. The higher spatial resolution of sharp probes provides the opportunity to cluster data more accurately. Since our primary interest was to investigate the relative effects of different diseases on mechanical properties of the tissue, and not the absolute values of elastic moduli, sharp tips were utilized in this study.
AFM can measure the elastic modulus of underlying tissue by two means of applying a preset force or deformation at a defined speed onto a surface. To achieve an optimized resolution, we used the force mode with a predefined force of 1.5nN applied by the cantilever for one second after lowering to the contact point of the samples as the reference position. The cantilever was returned to the initial position and the force-displacement data were recorded in both directions. At least 20 locations in each sample were probed, among each, 30 points were indented in an area of 30×30 µm. The spatial position of each indentation site was carefully located for histopathological analysis of that site. Since to some extent, the AFM results depend on the parameter sets and experimental conditions,50,51 we used the same parameters and conditions for all experiments (Table 1). Setting these parameters and selecting a low speed of the probe for a better evaluation of elastic moduli,50 a reliable comparison of elasticity values among different parts of tissue was possible.
Table 1 Representing Different AFM Features and Preset Conditions for Analyzing Elasticity of Ovarian Samples with Different Pathological Conditions
Evaluation of Young's Modulus
The difference between the deflection of the cantilever's tip (d) and the position of piezoelectric crystals (Z) defines the depth of indentation (δ) as:
where d0 and Z0 correspondingly indicate cantilever deflection and the piezoelectric position when the tip contacts tissue surface.
Based on the spring constant of the cantilever, the tip deflection is related to the applied force. Hence, the force was applied during continuous recording of the tip deflection, and the Young's elastic modulus of the indented site of the tissue was calculated using the resultant force-displacement data and application of the Hertz model, modified by the shape of cantilever tip.14,52
Parameter α represents half value of the cone angle of the tip that was 20° in this study. Parameters δ and F, respectively, show the indentation depth and the applied force, respectively. Moreover, μ indicates the Poisson ratio of the indented tissue considered to be 0.5 due to the assumption of incompressibility of soft biological tissues.53 Substituting Equation 1 in Equation 2, a linear function is derived (Equation 3) by which the slope of the line represents the Young's modulus of indented sites.54
The calculated values of Young's modulus are usually represented in histogram forms when the horizontal axis shows the calculated Young's moduli and the vertical axis indicates the frequency of occurrence (or relative frequency as the normalized value to the total frequency).55
Clustering Algorithm
The indented parts of ovarian tissues contained cellular, fibrous, and other structural features which could not be distinguished during nanoindentation. Hence, a wide range of values of elastic modulus was observed in the histogram. Since we hypothesized that elastic moduli of these parts were different for each specimen, we applied clustering algorithms to categorize data and naturally distinguish the number of clusters of data of elastic moduli. These clusters could be biologically meaningful such as cellular, fibrous, luminal ducts, etc. Hence, K-means clustering algorithm was used to classify experimental data into numbers of clusters to distinguish the elastic properties of different parts of tissue in such a way that there were maximum similarities between values of members of each cluster, while the differences between center of clusters were maximized.56 In other words, the measured data were divided into clusters such that the data within each cluster were as similar as possible, while the data in different clusters were as dissimilar as possible. Using this method, we avoided to predefine categories for elastic modulus of cellular and non-cellular parts of the diseased tissues and allowed an unbiased classification and examined whether these categories were biologically meaningful.
The result of clustering varies by change in the number of clusters; hence, a main challenge of clustering algorithm is that the number of clusters is rarely known. To overcome this problem, the K-means approach can be used accompanied by available methods to estimate the number of clusters such as statistical indexes, variance-based methods, information theory, and fit methods.57 A number of approaches utilize indexes comparing within-cluster distances with between-cluster distances to decide a criterion to select number of clusters,58 including elbow and silhouette methods. These two well-balanced methods have proved a good performance in experiments.59,60
The elbow method evaluates the clustering algorithm with stepwise increase of number of clusters from 2 and calculates the average value of each cluster and the squared sum of the distances between centroid of the cluster, and within-cluster sum of squares (WCSS) according to the number of clusters. By increase of number of clusters, the WCSS value decreases markedly until reaching a plateau which defines the optimized value of number of clusters. In silhouette method, the difference between the within-cluster tightness and separation from the rest is calculated. The largest average of the difference, over different number of clusters, indicates the best number for clustering data.57 We used both methods through MATLAB to obtain the best number of clusters, and results were considered reliable if numbers of clusters using two methods were the same.
To compare different methods of clustering, fuzzy C-means clustering tool which was performed in our previous study for clustering elastic moduli of normal and carcinoma breast tissues was also performed.4
Membership Grade
By determining the proper number of clusters using MATLAB Logic Toolbox, K-means clustering was used as a partitioning method. The function K-means divides data into k-limited clusters by returning the index of the cluster to which it allocates each observation. In comparison, the fuzzy C-means algorithm was also utilized to allocate data to clusters through calculation of membership grades which are numbers between [0,1]. After defining the number of clusters for samples of each ovarian disease, the cumulative center of the data in each cluster was calculated as the Young's modulus of samples assigned to that cluster.
Histopathologic Assessment
Samples were stained for pathological observation after mechanical characterization to compare the calculated elastic moduli with histological status of the indented sites. The samples underwent hematoxylin–eosin (H&E) staining according to the published protocols.61,62 The stained samples were investigated by the pathologist and the cellular and fibrous sites were distinguished and compared to those of indented sites.
Data were presented as mean ± standard error of the mean (SEM). At least ten samples were examined for each related ovarian tissue diseases. The number of measurements in each sample was at least 180 different points which were selected randomly. To compare elastic moduli of cellular and fibrous (ECM) locations among samples of different ovarian diseases, one-way ANOVA was performed for verification of statistical significance. Additionally, to compare samples of each disease, Bonferroni's multiple comparison test was performed. The P values for statistical significance were set to be less than 0.05.
According to the histopathological staining of biopsy samples, four different ovarian tissue-related diseases were recognized and examined. After indentation tests on different locations of samples of four ovarian diseases, elasticity histograms were plotted in logarithmic scale to better compare elastic moduli of different parts of heterogeneous tissues. Figure 2A–D shows plots of elasticity histograms of all samples of ovarian-related diseases. Results indicated marked differences among the ranges of elastic moduli described by histograms among subjects with four ovarian-related diseases. For mature teratoma, the indented sites were in the elasticity range of up to 80 kPa, at least 4-folds more than those of other groups. For samples with serous cystadenoma, Young's modulus values were less than 12 kPa, having the lowest range of elastic moduli compared to studied diseases. These results indicate that mature teratoma elasticity profile has the highest heterogeneity and the stiffest microenvironment. By the opposite trend, serous samples were the softest samples among all groups. For samples with endometriosis and mucinous cystadenoma, the ranges of obtained elastic moduli were almost similar, up to 20 kPa. However, the relative frequency of occurrence among the range of obtained elasticity was noticeably different between them. The highest frequency of elastic modulus was for 1000 Pa data for endometriosis and mucinous cystadenoma, with 30% and 20% of occurrence, respectively. Although the histogram for serous cystadenoma peaked at 500 Pa with 30% of relative frequency, the figure for mature teratoma peaked in 2000 Pa with merely 13% of occurrence, which indicates the broad and diverse elasticity profiles due to this disease (Figure 2A–D). To better compare elastic properties of ovarian tissue among four diseased conditions, the average elastic modulus of samples, regardless of indentation locations, was measured and compared among four diseased groups (Figure 2E).
Figure 2 Represents Young's modulus histogram of tissues of different ovarian diseases in logarithmic scale with a Gaussian distribution plot fitted on histograms. (A) Endometriosis, (B) mucinous cystadenoma, (C) serous cystadenoma, (D) mature teratoma, and (E) the average elastic moduli of ovarian tissues with four diseases. Measurements were carried out by atomic force microscopy in force spectroscopy mode at room temperature under physiological conditions. The significant differences in parameters of test groups were reported with the * sign (****p<0.0001).
Considering both cellular and non-cellular parts, results of average values of elastic moduli indicated that by far the stiffest tissue was mature teratoma, with the average of 14 kPa, and the softest ones were serous tumors with the average elastic modulus of 1.6 kPa (Figure 2E). The other values were 3.5 and 2.1 kPa for mucinous tumors and endometriosis, respectively (Figure 2E). Although the statistical results illustrate no significant difference between the average elasticity of serous, mucinous, and endometriosis tissues, exception is samples of mature teratoma with elastic moduli stiffer than that of others (P<0.05).
Since the elasticity histograms show variations with increased elastic modulus, the obtained data were clustered using K-means clustering algorithm. Using both elbow and silhouette methods, the optimized number of clusters was calculated and found to be three and four depending on disease conditions (Figure 3) (data not shown for silhouette method). This indicates that the obtained data does not belong to a single group, and while for the broad range of obtained elasticity in mature teratoma this number is calculated four, the stiffness variation of endometriosis, serous, mucinous should be categorized in three different regions, all indicating different parts in a tissue with a specific disease. Considering pathological examinations, we defined them as, cellular, extracellular matrix soft region (ECMs) indicating a region with a few cells with unparallel fibers of ovarian tissue, and the rigid one (ECMr) indicating fibrous part of tissue with parallel collagen fibers, consistent to previous studies.4,13 For mature teratoma, another category was defined as the highly rigid extracellular matrix (ECMhr), indicating the highly rigid parts in the microenvironment of tissue which is not observed in other ovarian studied diseases, also proving that the microenvironment of mature teratoma tumors is by far stiffer than other quantified diseases (Figure 2E). We further analyzed data and used fuzzy C-means to categorize data based on the obtained number of clusters and similar results were obtained for all clusters of data of cellular and non-cellular parts. The difference between C-means and K-means clustered data was obtained insignificant.
Figure 3 Obtaining number of clusters by elbow methods. Figure represents average within the cluster distance of elasticity profiles of indented tissues four ovarian diseases versus the clustering number. (A) Elbow method for endometriosis. (B) Elbow method for mucinous cystadenoma. (C) Elbow method for serous cystadenoma. (D) Elbow method for mature teratoma. Results were further verified by silhouette method.
According to the mathematical clustering calculation, the data which belong to the cellular parts of measured diseases were selected and plotted in a separate histogram. The elastic moduli of cells in measured tumors showed a Gaussian alternation with different peaks, depending on the disease condition. Previously published data have indicated the same order of magnitude for the elastic moduli of cells through nanoindentation.14,31 The K-means clustering centers showed 400, 1000, 1300, and 3700 Pa for cellular parts of serous, endometriosis, mucinous, and mature tumors, respectively, with the highest relative frequency in the cellular histogram parts (Figure 4A–D). The cellular part in serous cystadenoma was highly soft, with the average of 400 Pa, which was more than two and three folds softer than endometriosis and mucinous cystadenoma, respectively. The average elastic moduli of cellular parts were 1000 Pa for endometriosis and 1300 Pa for mucinous one; however, the cells in mature teratoma showed by far higher elasticity, with the average of 3700 Pa. An ANOVA statistical measurement indicated that the difference between cellular profiles in quantified diseases was statistically significant (P<0.05), with the exception of difference between endometriosis and mucinous tumors (Figure 5A).
Figure 4 Represents the cellular elasticity profiles of ovarian tissues of four different diseases measured by atomic force microscopy. (A) Endometriosis, (B) mucinous cystadenoma, (C) serous cystadenoma, (D) mature teratoma. K-means clustering was applied to categorize elasticity data. K-means clustering center 1 (kmeanC1) represents the clustering center of cellular region which significantly depends on the disease condition.
The data of elastic moduli were sorted in different partitions of cellular, soft ECM, rigid ECM, and highly rigid ECM. The extracellular matrix in mature teratoma is by far stiffer than other disorders, with elastic moduli of 17 kPa for the soft ECM components and 40 kPa and 66 kPa for rigid and highly rigid ones. Unlike the mature teratoma tissue, the average value for the softest quantified tissue, serous cystadenoma, is roughly 4 kPa for the soft ECM and 10 kPa for the rigid ECM components. For endometriosis and mucinous ovarian samples, the elastic modulus of ECM soft regions was approximately 6 kPa for both tissues. Endometriosis showed the second highest rigid ECM (ECMr) with the elastic modulus value of 18 kPa (Figure 5B and C). With combining the data of all ECM types (non-cellular parts), the average value for elastic moduli was measured 31 kPa, 8 kPa, 8 kPa, and 5 kPa for mature teratoma, endometriosis, mucinous, and serous ovarian tissues, respectively, with the significant differences between mature teratoma and other quantified diseases (P<0.05) (Figure 5D). Generally, there were unnoticeable differences in elastic moduli of both cellular and ECM components, when endometriosis tissues with mucinous tumors were compared (P>0.05), while samples of two other diseases showed significant alternations in both parts (Figure 5A–D).
The histological images of sections of ovarian samples with four diseases are shown in Figures 6 and 7 All samples show a diverse range of objects specially among the non-cellular parts. This might be the cause for categorizing elastic moduli of ECM in two or three separate categories. The cellular parts include different cells such as epithelial cells and fibroblasts. The non-cellular parts include both fibrous (mostly collagenous) and non-fibrous zones, in which the latter includes a wide range of tissues such as endometrial and sebaceous glands, adipose tissue, vessel walls, mucinous layer, and keratin layer depending on the disease. Such variety of objects define a wide range of elastic moduli, with higher moduli than that of cell body, yet lower than that of fibrous ECM. Hence, the non-cellular part represents at least two distinct ranges of elastic moduli, most likely due to fibrous and non-fibrous structures.
Figure 5 Represents the average elastic moduli of cellular and ECM parts of quantified diseases. (A) Cellular and (B–D) extracellular matrix portions. Bonferroni's multiple comparison test was performed to compare data statistically. The significant differences in parameters of test groups were reported with the *sign (*p<0.05, **p<0.01, and ****p<0.0001).
Figure 6 Histopathological examination of ovarian tissues. (A and B) Microscopic examination of hematoxylin and eosin (H&E) stained sections demonstrate endometriosis. (A) Microscopic low power examination (10×) reveals ovarian cyst lined by endometrial glands and decasualized stroma is evident. Hemosiderin laden macrophages and features of old hemorrhage are also seen. (B) High-power examination (40×) of the stromal cells shows abundant eosinophilic cytoplasm, distinct cell membrane, and round uniform nuclei consistent with progesterone hormonal effect on the underlying endometriosis. (C and D) Microscopic examination of hematoxylin and eosin (H&E) stained sections demonstrate mucinous cystadenoma. (C) Microscopic low power examination (10×) shows ovarian tissue with cystic structure, fibrotic stroma and (D) microscopic high-power examination (40×) shows a flat mucinous epithelial lining, without significant atypia compatible with mucinous cystadenoma.
Cells set the function of tissues through multiple behaviors such as migration, proliferation, synthesis, and regulation of ECM by which the dynamic state of homeostasis is met. Mutually, chemical and physical environmental stimuli influence cells through ECM and further regulate cell behaviors. The interactive process of cell-ECM signaling defines and guides biological processes in tissue level such as morphogenesis, tissue remodeling, healing, and disease development. During initiation and progression of diseases, the properties of both cell and ECM including their physical properties change. Alterations in mechanical properties of both cell bodies and ECM are due to altered structural arrangement and/or content of fibrous components which remodel cell cytoskeleton and ECM synthesis and degradation. The extent of such alterations is such that, these changes have been proposed as biomarkers of diseases, most notably in cancer.63 It has been well established that cancer cells are softer than normal cells while the ECM of cancerous tissues is stiffer, and these alterations are intensified by increased invasion.2,64 Cancerous cells are highly deformable, especially during invasion, to penetrate tissue matrix and migrate to implement intravasation and extravasation by which they pass through endothelial junctions of vessel walls and reach the bloodstream and with the same pattern penetrate to a new tissue and metastasize.65 Cancer cells also affect ECM to facilitate their migration by degradation through secretion of abnormal MMPs and synthesis and rearrangement of a new fibrous structure.66 It seems that during initiation and progress of many pathological conditions, cellular and non-cellular parts of diseased tissues undergo remodeling which causes altered mechanical properties for new biological conditions.67 Here, we examined the differences among cellular and non-cellular parts of ovarian-related tumorigenic and non-tumorigenic diseases and found significant differences among elastic moduli of those parts.
Tissues related to four non-malignant ovarian diseases, mucinous cystadenoma, serous cystadenoma, and mature teratoma, as tumorous diseases, and endometriosis, as the non-tumorous disease, had different mechanical properties both in terms of cellular and non-cellular elastic moduli depending on the disease condition. On average, samples of mature teratoma showed the stiffest microenvironment and were approximately six times stiffer than samples of serous cystadenoma (the softest) in ECM region and nearly nine folds stiffer in cellular region (Figure 5A and D). Such quantities show the wide extent of variation in mechanical properties of biological tissues in different disease conditions, as cells comply to the pathological state by remodeling their behavior which affects their structures, most likely through their cytoskeleton, as well as ECM rearrangement.68
It has been shown that some benign ovarian tumors of mucinous or serous origins can potentially be transformed to malignant state.69,70 A majority of low-grade invasive serous ovarian carcinomas coexist with ovarian tumors of micropapillary and typical types, which in turn usually coexist with serous borderline tumors.71,72 The overexpression and mutation of p53 marker, which is highly related to the carcinomas, were also detected in ovarian benign tumors.73,74 Furthermore, it has been suggested that the risk of several types of ovarian cancer increases among women with endometriosis.75 Moreover, although mature cystic teratoma hardly undergoes malignant transformation, the possibility of such incidence increases with age.76–78 Overall, the close relations between ovarian benign lesions and carcinoma incidences highlight the importance of study of benign lesion microenvironment. Our results indicated that different ovarian benign lesions have undergone significant alterations according to their pathological states, with highest variations in their ECM elasticity most probably due to cell remodeling which affects ECM synthesis and regulation. Cells of these tissues also showed different elastic properties. The high heterogeneity among cell and ECM parts of samples with different disease states indicates the high impact of pathological conditions of microenvironment on tissue mechanical properties which can assist in the understanding of development of these conditions. It might seem at first that softer benign cells produce softer ECMs; however, there is no biological evidence for this. During cancer onset and development, cancer cells undergo softening with invasion degree, while ECM becomes stiffer.65 Here, although for samples with mature teratoma both cellular and non-cellular zones are significantly stiffer than those of other samples, there is no such trend when samples of other three benign conditions are compared. In other words, the trend of stiffening of cellular parts does not match the trends among ECMr and ECMs regions of samples of endometriosis, mucinous cystadenoma, and serous cystadenoma, and their properties depend on disease conditions. Each pathological state indicates a specific structural property of cells and ECM parts to meet the requirements of that disease. Hence, since ECM changes are due to cell behaviors, there is a correlation between cellular and ECM microenvironment elasticity; however, such correlation varies among different diseases and possibly among different stages of the disease. The cystic environments of the mucinous and serous are different which may affect both cellular and ECM microenvironments. The cyst of serous contains watery fluid or occasionally thin mucinous fluid compared to that of mucinous cystadenoma which is filled with thick mucoid material.79 In this regard, the physiological conditions of serous cyst, having unilocular lesions and homogenous microenvironment with a thin regular wall may influence alternation of elasticity histograms, leading to decreasing ranges of both cellular and ECM elasticity variations. However, mucinous cysts are multilocular cystic structures, with cytoplasm containing abundant mucin materials and fibro collagenous stroma with variable cellularity. These futures lead to having both stiffer cells and ECM in mucinous tumors compared to the serous one (Figure 5A–D).80,81
Our results indicated a wide range of elastic moduli among samples of ovarian tissues shown in the elasticity histograms (Figure 2A–D). Such range of data defined elastic properties of both cellular and non-cellular regions. Since non-cellular regions are stiffer in nature than the cellular parts, we intended to divide data into categories to distinguish between cellular and non-cellular parts. This allows to obtain average values of elastic moduli of different regions and compare those among samples of several diseases. AFM technique is able to probe very locally; however, the histological evaluation is not feasible during indentation such that there is no sufficient resolution to distinguish between the individual tissue components.65,82 Hence, we used clustering algorithms that "naturally" categorize data into a suitable number of categories with the highest similarity among data of each group and the least similarity between groups without subjective intervention. The coordination of measurements during AFM for elasticity quantification was also used to investigate the nature of probed local tissue by H&E staining of examined sections (Figures 6 and 7). Previously we used Fuzzy C-means method to distinguish between elastic moduli of cellular and non-cellular zones among samples of normal and cancerous breast tissues and found that the cellular parts of cancerous tissues were significantly softer than those of healthy tissues.4 We distinguished three categories to cluster data of breast tissues. We named them as cellular region, intermediate region containing less dense ECM fibers together with ducts and lumens, and fibrous ECM region. In this study, we used two methods of K-means and fuzzy C-means in parallel with similar results in indentation data clustering, demonstrating the high similarity of these two clustering methods in our study. Similarly, here we distinguished three regions among samples of three diseases and named them as cellular part, ECM soft region (ECMs), and ECM rigid one (ECMr). For the tumorous mature teratoma samples, the non-cellular part was categorized with one more region of extra stiff fibrous zone. Similar to our previous work, variations among less fibrous part of ECM were lower compared to the denser and more fibrous parts (Figure 5B and C). When the non-cellular parts among study groups were averaged (Figure 5D), data revealed that on average, the non-cellular parts of samples of different diseases were 7 to 10 times stiffer than the cellular part (Figure 5A and D).
Teratomas may include not only the rudiments of a variety of tissues but also organs and groups of organs. In mature teratomas, derivatives of germ layers can differentiate up to very impressive and even artistic levels described as "fetus in the fetu", and mitotic activity in them is either absent or only slightly expressed.76 The most common ectodermal components in them include the skin epidermis, pilosebaceous structures, sweat glands, teeth, and neurological tissues. Mesoderm is most commonly represented by cartilage, bone, fat, and muscle (smooth and striated) tissue, and endoderm is represented by cysts lined with respiratory and intestinal epithelium, and sometimes parts of the pancreas and liver.83 In this trend, differentiation to different organs is the dominant feature of these tumors.79,84 Interestingly, it has been shown that the wide range of elasticity in these tissues can serve as a mechanical stimulation to induce differentiation potential in cells to the different target cells depending highly on the mechanical microenvironment.25,85,86 Our results also confirm this trend, as the range of elasticity histogram in mature teratoma samples was almost four times higher than those of other diseases and showed a marked mechanical heterogeneity through the tissue sections, in such that we defined three ECM related zones of different elastic moduli with natural clustering of data (Figure 3). Such broad range was also observed in cellular region among three pathological states, which is a confirmation in existence of different types of cells related to the disease condition (Figure 4A–D).
Figure 7 Histopathological examination of ovarian tissues. (A and B) Microscopic examination of hematoxylin and eosin (H&E) stained sections demonstrate serous cystadenoma. (A) Microscopic low power examination (10×) shows ovarian tissue with fibrotic stroma and multiple cystic structures. (B) Microscopic high-power examination (40×) depicts that the tissue sections were lined with flat or cuboidal ciliated epithelial cells without significant atypia compatible with serous cystadenoma. (C and D) Microscopic examination of hematoxylin and eosin (H&E) stained sections demonstrate mature teratoma. (C) Microscopic low power examination (10×) reveals ovarian cyst with keratinizing squamous epithelial lining, normal skin appendices, and hair follicle consistent with mature teratoma. (D) High-power examination (40×) reveals a mature adipose tissue (at the bottom) and sebaceous gland (left of the figure) are seen.
Endometriosis is considered as a non-tumorous ovarian disorder and we studied samples of these tissues to compare with other ovarian tumor-based diseases. Similar to tumorous ovarian tissues, these samples also showed variations in mechanical properties among cellular and ECM portions and showed different mechanical properties from tumorous ovarian tissues, particularly, their cells were significantly stiffer than serous cystadenoma cells and softer than mature teratoma cells. Both serous cystadenoma and mature teratoma have markedly higher cancer incidences than mucinous cystadenoma. Almost 90% of ovarian cancers involve epithelial cells, among which serous carcinoma cases are the most abundant with 52% of cases and mucinous carcinoma the least common with only 6% of cases.87 The very soft nature of serous carcinoma cells might contribute to a majority of cancer-related events in ovarian tissue and can be considered for therapeutic actions.88–90 The highly deformable cells can swiftly migrate through ECM, pass endothelial junctions, endure shearing forces of the blood flow, and settle in a new tissue. Accordingly, results indicated that serous carcinoma cells, with higher likelihood of becoming malignant, are significantly softer than cells of all other three ovarian diseases (P<0.05) (Figure 5A). The histological images of diseased tissues show a considerable level of fibroblasts which are also another source of cells in tissues that contribute to the elasticity of cellular part of samples. Interestingly, cancer onset and progress is accompanied by the cross-talks between cancerous epithelial cells and cancer-associated fibroblasts (CAFs) which facilitate the process of detachment from tumor, ECM degradation, and further synthesis and migration.91
It seems that among samples of ovarian tissues with four diseases, the fibrous parts of the ECM represent the higher range of elasticity (represented by ECMr in Figure 5C), while the non-fibrous parts characterize the softer elasticity range (described by ECMs in Figure 5B). Samples of mature teratoma possess dense collagenous fibrous locations which are most likely related to the stiffest ECM part of samples (represented by ECMhr). While the non-fibrous part contains a variety of tissues among all samples of different diseases, the highly diverse range of objects in the samples of mature teratoma includes even more objects such as adipose tissue, sebaceous gland, hair follicle, keratin layer, vessel wall, fibrous stroma, and dense collagen fibers. This necessitates a higher number of categories of ECM elastic modulus compared to tissues of other three diseases. Hence, using a clustering algorithm, while ECM of other ovarian diseases was naturally categorized by two groups, the ECM of mature teratoma was characterized by three categories with distinct elastic moduli.
In conclusion, tissues which undergo pathological conditions experience variation of mechanical properties among cellular and non-cellular parts. For the ovarian tissue, samples of three tumor-based diseases and one non-tumorous disease revealed marked variations among all cellular and non-cellular parts including less dense and highly dense ECM portions. It was shown that different diseases have direct effects on changing cellular microenvironment and even on the cell mechanical properties, enhancing the symptoms. Furthermore, these results also represented the ability of AFM to reveal alterations in the tissue structural properties in pathological conditions. Aside from clustering algorithms to categorize tissue content, there are other AFM-based techniques for surveying tissues to distinguish structure and morphology of the indented location that might assist in the study of diseased tissues in future studies, such as force volume imaging which simultaneously provides both morphology and elasticity data.92 Such approach is rather time-consuming and might result in sample degradation in some cases. Furthermore, it is possible to combine both force spectroscopy and contact modes to probe the 3D morphology of indented material.11 This technique also is limited in application, since the contact mode requires separate set up with a soft probe that results in rescanning the samples. Another approach which has been used is conjugating the probe tip with specific biomarkers, for molecular recognition approach. Due to high diversity of tissue structure, this application might require different biomarkers including conjugated proteins to probe all cellular and non-cellular content. The possibility of recruiting these techniques after overcoming limitations remains an interesting field of future studies. Our results may be assistive in the study of physical microenvironment of cells during onset and progress of diseases and their correlation with biological events, of particular interest in cancer. Such variations may be quantified as biomarkers in disease initiation and progression and be used in diagnostic tools and treatment strategies.
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91. Mayor R, Etienne-Manneville S. The front and rear of collective cell migration. Nat Rev Mol Cell Biol. 2016;17(2):97. doi:10.1038/nrm.2015.14
92. Krieg M, Fläschner G, Alsteens D, et al. Atomic force microscopy-based mechanobiology. Nat Rev Phys. 2019;1(1):41–57. doi:10.1038/s42254-018-0001-7


text:
O Reduto dos Dois Paus localiza-se na península do Monte Brasil, na freguesia da Sé, na cidade e concelho de Angra do Heroísmo, na costa sul da ilha Terceira, nos Açores.

Integra o conjunto defensivo da Fortaleza de São João Baptista da Ilha Terceira.

História
No contexto da instalação da Capitania Geral dos Açores, o seu estado foi assim reportado em 1767: "(…) No reducto dos dois paus tem três canhoneiras e duas peças de feiro esfuguenadas, precisa uma com o seu reparo."

Em nossos dias encontra-se em ruínas.

Bibliografia
 JÚDICE, João António. "Revistas feitas no Castello de S. João Baptista, Forte de S. Sebastião e de todos os mais fortes que tem esta Ilha Terceira" (Arquivo Nacional da Torre do Tombo. Papéis do Ministério do Reino, Maço 611). in Arquivo dos Açores, vol. V (ed. fac-similada de 1883). Ponta Delgada (Açores): Universidade dos Açores, 1981. pp. 407–418.
 MOTA, Valdemar. "Fortificação da Ilha Terceira". in Boletim do Instituto Histórico da Ilha Terceira, vol. LI-LII, 1993-1994.

Ver também
 Lista de fortificações nos Açores
 Tombo dos Fortes da Ilha Terceira

Ligações externas

Fortificações dos Açores
Angra do Heroísmo

redpajama_set_name: RedPajamaWikipedia


text:
Q: Is it possible to flow type a function that returns another function that may be curried? Let's say you have a function that returns another function, and that function that is returned may or may not be curried. Can this be flow typed? I'm guessing that the answer may be no.
Here's an example:
function getAddFn(curried) {
  if (curried === true) {
    return function add(x) {
      return function(y) {
        return x + y;
      }
    }
  }

  return function add(x, y) { return x + y };
}

const add = getAddFn(false);

add(2, 3)

For this code, flow gives the following error:
add(2, 3)
           ^ Cannot call `add` because no more than 1 argument is expected by function [1].
References:
3:     return function add(x) {
              ^ [1]

Essentially, flow is unable to determine which function style has been returned.  It's also not possible to type the variable that receives the function, e.g.:
const add: (number, number) => number = getAddFn(false);

In this case, flow complains:
13: const add: (number, number) => number = getAddFn(false);
                                            ^ Cannot assign `getAddFn(...)` to `add` because function [1] is incompatible with number [2] in the return value.
References:
4:       return function(y) {
                ^ [1]
13: const add: (number, number) => number = getAddFn(false);
                                   ^ [2]

Can anyone explain if this is possible? Or if not, clearly explain why? I can see that the problem could be related to the fact that the value of the boolean passed into getAddFn is not known until runtime.

A: While it's true that Flow doesn't know whether curried is true or false, you're hitting a much more fundamental limitation than that. In flow, a union type x : A | B doesn't mean that x is either A or B, and that Flow doesn't have enough information to distinguish them. It means that x has the type A | B. The type A | B can only be consumed in two ways:

*

*by passing it to something which can accept both an A and a B

*by passing it to something which can separate out an A from a B, such as an if statement

The distinction is subtle, but it gets clearer if you think about what the type checking algorithm is doing. First, Flow checks that the type annotation of your getAddFn is correct. The function returns number => number => number in one place, and (number, number) => number) in another. Flow thus infers the the type (number => number => number) | ((number, number) => number) for the function.
Then, Flow holds onto this type and completely forgets about the function body. This is what I mean by the distinction above; once Flow knows that a function returns a union type, it knows everything it wants to about that function, and won't revisit it. Given this and the first bullet point above, the errors hopefully start to make sense.

As an aside, hopefully one day this sort of thing will be possible if Flow ever gets proper support for intersection-typed functions. Intersection types are documented here, but there are open github issues on the fact that they don't work with functions, such as this one here. If they worked properly, then it might be possible to use them alongside Flow's literal types to implement something like this. The trick would be to overload the function's type to say that it is both a function from the literal value true to something of type number => number => number and a function from the literal value false to something of type (number, number) => number. Alas, we currently don't have the ability to do this, and it is unclear whether we ever will.

A: It seems flow doesn't like that your signature appears to be
num -> num | num -> num -> num

This means the exact type would have to be checked at runtime.

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Before I went to Lisbon, my goal in life was to live in a hotel. After going to Lisbon, my goal is to specifically live at The Lumiares or The Vintage - sister hotels that each have their own distinctive vibe and absolutely make you feel like the the most special person in all of Portugal! That really is the first thing I have to note - the staff at both hotels were unbelievable. So kind and welcoming, there are a lot of beautiful hotels in the world - but I have never come across a hotel staff who were collectively so gracious and lovely. I mean, from my Instagram Stories and Lisbon blog posts, you know that Delta just didn't send my bag to Lisbon for 2 days. Although it was stressful, I didn't have to worry about it once. The brilliant concierge at The Lumiares called after my bag until it arrived, doing everything he could to assure it would get to me. At The Vintage, they had a delightful birthday cake made for me and delivered it to my room when I was finally well enough to enjoy it. This trip could have easily been a disaster because of the bad luck that seemed to plague it, but it was my experience at both hotels that made me want to not give up and still see Lisbon - a city that has my heart 100% now!
When you're across the world and your trip is kind of falling apart, all you want it is home and that how the apartment we stayed in at The Lumiares felt - granted, a much more chic apartment than one I've ever had! Once we got over the shock of having this two bedroom two bath spacious gem all to ourselves in Lisbon, Fallon and I both decided immediately that we needed to recreate this aesthetic in our homes. Its a mix of bohemian flair colorfully coordinated with a touch of palatial elegance - which makes sense, because it is a former palace! Do you have any idea how hard it is to not immediately jump into a pristine, freshly-made bed when your off of 16 hours of traveling - especially one that looks that cozy? When we finally decompressed for the night, showered with the yummiest citrus-scented Banho goodies (the robes and towels are A1 + a waterfall showerhead is always best), and ordered in two Lumi Burgers from room service - it was finally time to test out that bed I had been thinking about all afternoon and it did NOT disappoint. I think I went on to sleep for a solid 12 hours. Although the hotel is situated in the heart of the bustling Bairro Alto, it was such a quiet and peaceful sleep. In fact, it rained our first night so I was out like a light, The apartment also had everything we would need to cook, including a stove that only heated recognized cookware - literally you can't even burn your own hand, flatware, mugs, plates, glasses, you name it. It's the perfect hotel if you prefer to do some grocery shopping and make your meals instead of eating out. Also, the mini-bar is complimentary. Do I even need to say more? Beers, wines, sodas, water - didn't I tell you this hotel will make you feel absolutely special?
On our second evening, we ventured up to the Lumi Rooftop for dinner with some insane views of Lisbon - from my beloved Alfama to the Rio Tejo. If that isn't enough, the hotel sits opposite one of Lisbon's most beautiful terraces - Miradouro de São Pedro de Alcântara. The day we went, there was a vibrant market scene with live band playing...I'm pretty sure it was Stevie Wonder. We didn't try the adorable Mercado cafe downstairs because we're room services babes, but I've never met a rooftop I didn't like. Between a bottle of Portuguese wine, Goat Cheese Pastry, Alheira (think boudin) Balls, Scarlett Shrimp Linguini, and another outstanding Lumi Burger over the course of a 3 hour meal, it was a good thing we were walking 2-4 miles every day or they would have had to roll us back to America.
The Vintage is vacation and hotel and life goals! While The Lumiares sports a bohemian airy elegance, The Vinatge is sumptuous. Sitting atop a slope that sends you down to some of the most fashionable shopping in Lisbon (I did go to Louis, but only to look!), this hotel has a charming buttery yellow exterior that houses rooms individually done in a rainbow of moody shades. The whole vibe fits perfectly with the name - there is a retro feel to the hotel from the romatically lit halls to the color palettes used for the rooms - from midnight blue to mint green to dusty pink. It's the kind of hotel you could imagine a 1960s movie star like Audrey Hepburn or Sophia Loren would frequent, closing the heavy curtains when she wanted to escape from the world or leaning over the quaint balcony when deciding to give the paparazzi a few glamorous shots.
I don't know if anything could have made me happier on this trip than a pink hotel room, and not any shade of pink - but the shade that is quickly washing out of my hair. I had rose gold hair, rose gold luggage, and not a rose gold room that was the most perfect place to wake up on my 32nd birthday. On of my favorite features of the room was that their were small floor lights that illuminated my path whether I was walking the (again stocked and complimentary!) minibar, the walk in waterfall shower, or the private bathroom with bidet. Honestly, can we get on the bidet movement in America? We deserve better. Our stay at The Vintage was topped off with a night at the spa - I can still feel the rush or warm fragrant air when you step off of the elevators and into the luxurious scene. I opted for a facial because my skin was a WRECK from dry airplane air and no luggage stress. Next time - I'm taking one of each service and just setting up for the night in the eucalyptus steam room and dry sauna. There's also a gym with 24 hour access, which looked just wonderful but climbing the 7 hills was my cardio that week. Like it's sister hotel, The Vintage has a rooftop with sweeping views of Lisbon as well and local eats that more than make up for the steep hills and endless walks in the city. Also, probably the best complimentart breakfast ever. Ripe kiwis, fresh juices, made to order eggs, cheese, Portuguese ham, and pastel de nata! With two hotels like these, who needs to come home?


text:
The Mix Masters
PASO WINEMAKERS ARE BLENDING THEIR WAY TO THE TOP
By Steve Heimoff
Paso Robles has always felt a little like comedian Rodney Dangerfield. It didn't get any respect.
Napa Valley and Sonoma County monopolized the public's fancy for fine wine. Paso, by contrast, marked the halfway point on the freeway between San Francisco and Los Angeles. Conventional wisdom ran that it was too hot for wine. The area's cowboy traditions didn't exactly burnish its reputation as chic wine country.
But things are quickly changing.
The Templeton Gap Effect
Some years ago, people began to seriously explore Paso's wide-ranging terroirs and microclimates. Granted, Paso's northern and eastern reaches tend to be ovens in the summer. But vintners increasingly took advantage of a weather effect caused by the region's notable Templeton Gap—low passageways in the coastal hills that permit cool maritime air to penetrate vineyards within its influence. Particularly in hilly western Paso Robles, these temperate areas have proven successful for more balanced, nuanced wines.
Vintners discovered something else: If they made a wine from one particular variety, it could be a little one-dimensional, with "divots"—deficiencies in aroma, color, texture or flavor. By blending in different varieties to fill in the divots, winemakers discovered they could create more complex, complete wines.
As Tablas Creek's general manager, Jason Haas, notes, "Why do we blend in a world where varietals reign supreme? Because blends are better than component pieces."
Mixing It Up for Today
A younger generation of winemakers, less encumbered by the traditions of the past, has wholeheartedly embraced the blending phenomenon. Matt Villard, the owner/winemaker at MCV, tinkers with everything from Petite Sirah and Grenache to Tannat and Petit Verdot in his "1105" red wine. "I'm a big fan of blends," he says. "You get a more interesting wine, with a broader spectrum of everything available."
Brian Brown of ONX says of his unique Zinfandel, Syrah, Tempranillo and Cabernet Sauvignon blend, "You'd never see this kind of blend anywhere outside of Paso." He feels that Paso's traditional weakness—an absence of high-end winemaking—has been turned into its strength. "A lot of winemaking elsewhere is done by convention. Even in Napa Valley [where Brown used to be winemaker at Round Pond], I don't think Cabernet Sauvignon necessarily makes the best wine. But that's what sells."
"It's no-holds barred down here when it comes to blending," observes David Galzignato, winemaker at Jada Vineyard. "The culture is more artistic and experimental than other places I've worked," which include stints at Charles Krug, Lewis and Paraduxx, all of them in Napa Valley.
More Success Brings More Talent
Success breeds success. As Paso Robles has upgraded its image in the past few years, outsider investors have noticed and moved in. As Brown puts it, "More interest from the public brings more capital in, so more folks want to invest. And talent always follows the money."
Besides the wineries referred to above, others that are producing interesting red (and sometimes white) blends from Paso Robles include The Farm Winery and Bonne Niche. As The Farm's co-owner, Wally Murray, notes, "After many decades of effort in California, I think we now have a pretty good idea of how to make good wines—and that requires blending!"
If you do visit Paso—and it's well worth a few days—you'll hear about the great restaurants that have sprung up around the old Town Square. The Old West way of life is still alive and well, but the new wine culture has arrived with culinary deliciousness. Try Villa Creek, Bistro Laurent, Buona Tavola and, a winemaker favorite, Artisan.
Kassidy Clark February 13, 2013
Briarwood in Templeton: A View Over the Vineyard
Kassidy Clark August 21, 2013
ONX Wines Dives Head-On Into "Blending Without Boundaries"

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Security posts or bollards can be used as the ultimate obstruction to secure your vehicle or an unmovable anchor point for your Caravan or Trailer MotorNuts have a great range from Maypole.
Serious protection for driveways and forecourts, simply lock the post into the ground to create a formidable barrier.Please note some Insurance Companies will offer a discount when a security post is fitted.
Ideal for securing parking spaces, driveways and forecourts,Easy surface mounted installation.
Security posts or bollards create a formidable barrier or anchor providing the ultimate protection for your caravan or vehicle on your driveway.
Simply lock the post into the ground for the ideal security for parked cars then it can be easily removed when the vehicle requires access.
For caravansand trailers, simply hitch up to the post then for additional peace of mind secure in place with a hitch lock.
Highly visual and effective, the security posts or bollards are an efficient deterrent to would be thieves and some insurance companies do provide a discount when a security post is used.


text:
Julia O'Malley-Keyes Exclusive Fine Art PrintsVOTE for the 2020 BEST OFEnter the 2020 Annual Photo Contest
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Scott Peacock Building & Remodeling
Cape Cod Home / Annual Home 2016 / Home, Garden & Design, People & Businesses
Writer: Susan Dewey
Cape & Islands Architects and Builders
Courtesy of Scott Peacock Building & Remodeling
After more than 30 years of building and remodeling homes on Cape Cod, Scott Peacock still loves what he does—and that, he says, has been the key to his success.
"I'm just so lucky to have built a business in the place that I was born. That's huge for me, and it has allowed me to raise my family here," Peacock says. "Every day is different. We're constantly being challenged with new problems, which are fun to figure out."
Growing up in his father's painting business, Peacock was immersed early on in the world of home design and construction. "At a young age, my Dad put a lot of trust in my brother, John, and me," Peacock says. "He had us running jobs while we were still in high school. We were taught how to estimate, and then we were in charge of his crews. It was a big responsibility, but I guess it came naturally to us."
When business was slow in the winter of 1980, Peacock had the opportunity to frame houses with David Brodd, a local builder. "Unfortunately for my father, after that winter I could never think of going back to painting, as I loved watching these houses go from clearing a lot, to building a framed house, in such a short period of time," he says.
Today, Peacock's wife, Amy, runs his Osterville office and his team includes five employees—some of whom have been with him for 25 years. Peacock says he and his team work closely with homeowners and architects to design what their clients are looking for. "I try to be as involved in every step of the process as I can be, from start to finish," Peacock says, whether the project is a whole house remodel, or a simple addition.
This makes the process, he explains, as painless as possible for customers. "Our whole goal is to make the home building and remodeling process a fun, rewarding experience for every single client," Peacock says.
[foogallery id="26375″]
Chef Ben's Heartwarming Holiday
Chef Ben Robinson found international fame on Bravo's reality series "Below Deck," but this week he's returned to his home…
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Land Frontiers is dedicated to helping anyone purchase rural, vacant land; regardless of their financial situation at a price that they can afford. We are a family of investors who buy rural vacant land at wholesale prices and sell at deep discounts to investors and vacation buyers. We specialize in finding land where you may want to retire, hold for investment and make profit or build your dream cabin on. There's no better feeling than owning a piece of America and we want each of our clients to be able to experience that feeling.
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text:
Types of schools in Germany
As well as being divided into Hauptschulen, Realschulen and Gymnasien offering different qualifications, German primary and secondary schools are also split between public schools and private or alternative schools (Ersatzschulen). Both private and public schools participate in Germany's streamed system of schooling and also receive funding from the federal government (Bundesregierung).
Public schools (öffentliche Schulen)
The majority of pupils in Germany (around 90%) attend state-funded public schools. Education policy in Germany is controlled by individual federal states, which means that there can be a great degree of regional variation in terms of curriculum and school types. State education authorities work together, however, to ensure that a common and comparable standard of education is achieved throughout Germany.
Private schools & Alternative schools (Ersatzschulen)
The right to establish private schools as alternatives to public schools is enshrined in the German constitution (Grundgesetz - "Basic Law"). All private schools that offer German qualifications, however, must receive approval from regional state authorities, who assess whether the school measures up to public-sector schools in terms of their educational aims, facilities and staff.
Furthermore, Ersatzschulen cannot be deemed to be encouraging the segregation of pupils according to their socioeconomic backgrounds. For this reason, private schools in Germany receive fairly generous state subsidies and tend to charge much lower tuition fees than in other countries in western Europe.
Types of private schools in Germany
There are several different types of private and alternative schools in Germany. Here is an overview of some of the most common ones:
Religious or denominational schools in Germany are founded on a specific faith such as Protestantism, Catholicism or Judaism. Attending a religious school doesn't necessarily mean you need to practice that religion, but you will be expected to observe and respect their customs.
Freie Waldorfschulen (Rudolf Steiner schools)
Following the educational philosophy of Rudolf Steiner, Freie Waldorfschulen have a long history in Germany, with the first being opened in Stuttgart in 1919. Steiner schools have a holistic approach to education that emphasises creativity and imagination to develop pupils' intellectual, artistic and practical skills.
The Montessori educational approach, based on the work of Italian educator Maria Montessori, relies on the concept that children are inherently curious and resourceful. By placing them in a supportive learning environment, the method encourages the development of children's natural abilities through discovery and play.
Free alternative schools (Freie Alternativschulen)
Partially based on concepts like the Montessori approach, free alternative schools encourage individual responsibility, varied lesson formats and mixed-age classes.
Jenaplan schools
Jenaplan schools are founded on the concepts of Peter Petersen and promote cooperation and communal living, in particular, shared responsibilities for children, teachers and parents. The Jenaplan emphasises the uniqueness of each human being and encourages learning via teaching, celebration, discussion and play.
International schools (internationale Schulen)
International schools are designed specifically so that the children of expats, who often spend long portions of their childhood abroad, can receive a consistent and coherent education. International schools offer instruction at least partially in English (many are bilingual English - German) and internationally-recognised certifications such as IGCSE and IB diplomas. For those wanting to complete higher education in Germany, there are many schools that also offer the Abitur qualification.
As they offer international qualifications, international schools sometimes fall outside of laws controlling private schools. This means they might not receive funding from the state, can charge uncapped tuition fees, and are given more freedom in terms of their curriculums. Browse through our selection of the top international schools in Germany for expats.
Homeschooling in Germany
Homeschooling is illegal in Germany, on the basis that a child's right to be well-educated and socialised outweighs the parent's desire to keep them at home. This ruling applies to non-German and German citizens alike and can be enforced with fines and prison sentences.
Primary and secondary education in Germany
The German education system explained for expats: types of schools (public & private), structure of the school system in Germany, school holidays & fees.
International schools in Germany
Looking for an international school for your expat children in Germany? Here's a list of international schools in Germany, divided by German city.
The German school system
While primary education is mixed in Germany, secondary education is streamed into academic & vocational schools: Hauptschule, Realschule & Gymnasium.
School fees in Germany
While primary and secondary schools in Germany are usually free, private schools and international schools are allowed to charge (capped) school fees.