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Objective Among patients with type 2 diabetes (T2D), the prevalence of hidden hypercortisolism (HidHyCo, formally called subclinical hypercortisolism or mild autonomous cortisol secretion) was estimated to be 2.2-12.1%. The aim of this study was to investigate whether the available literature helps to identify the characteristics of T2D patients more frequently associated with HidHyCo. Methods A meta-analysis was performed using studies that assessed both the prevalence of HidHyCo in patients with T2D and the characteristics of these patients with and without HidHyCo. The DerSimonian and Laird (DSL) and the Hartung, Knapp, Sidik and Jonkman (HKSJ) methods were utilized. Results Among the 18 available studies, 6 studies provided the necessary data. The association between HidHyCo and advanced T2D (based on the patients’ description given in each study in presence of micro/ microvascular complications, or insulin treatment plus hypertension, or hypertension treated with ≥2 drugs), hypertension, insulin treatment and dyslipidemia was reported in 5 (2184 patients), 6 (2283 patients), 3 (1440 patients), and 3 (987 patients) studies, respectively. HidHyCo was associated with advanced T2D as assessed with both DSL (odds ratio, OR, 3.47, 95% Confidence Interval, 95%CI, 2.12-5.67) and HKSJ method (OR 3.60, 95%CI 2.03-6.41) and with the prevalence of hypertension or of insulin treatment as assessed by the DSL approach (OR 1.92, 95%CI 1.05-3.50 and OR 2.29, 95%CI 1.07-4.91, respectively), but not as assessed with HKSJ method. Conclusions Patients with advanced T2D have a higher prevalence of HidHyCo. These data inform about the selection of T2D patients for HidHyCo screening.

Background: Non-occupational cases of contact dermatitis to finished wood are occasionally reported from contact with wooden jewellery, musical instruments, knife handles and wooden footwear. Two female patients, 26 and 34 years old, developed acute eczema on the wrists after they worn in the summer a kind of catholic bracelet called “memorabilia” made by single wooden chunks with over-impressed iconic religious images. Objectives: To identify the culprit photoallergen responsible for the reported adverse reactions suspected to be a compound of the wooden bracelets. Methods: Three months after the resolution of the dermatitis, patch test and photo-patch tests were performed with the S.I.D.A.P.A. (Italian Society of Allergic, Occupational and Environmental Dermatology) standard series, and with wood sawdust obtained from both bracelets and tested at 5% in pet. A thin-layer chromatogram (TLC) strip and an extract made from the bracelets were tested in both the patients as patch test and photo-patch test. The extracts of the wooden bracelets were analyzed by gas chromatography – mass spectrometry (GC-MS). Results: Patch tests and photo-patch test with standard series turned out negative. Photo-patch tests with wood sawdust in pet. 5% evidenced a positive reaction (++) in both patients. Two chemicals were detected in the wooden bracelets with GC-MS: dibutylphthalate, commonly used as plasticizer, and 8,8-dimethyl-2H,8H-benzo[1,2-b:3,4-b']dipyran-2-one, a coumarin. Patch test with TLC did not elicit positive reactions but the photo-patch test with TLC gave positive reactions in both the patients to the same invisible spot on the strips. Two coumarins (8,8-dimethyl-2H,8H-benzo[1,2-b:3,4-b']dipyran-2-one and 8,8-dimethyl-2H,8H-benzo[1,2-b:5,4-b']dipyran-2-one) were detected in the spot with GC-MS. Conclusion: Coumarins are chemicals found in many plants with a known photo-allergic potential. They are probably the main photo-allergens in religious wooden bracelets instead of quinones and psoralens hypothesized in previous reports.

Breast cancer is the most common invasive cancer in women, affecting more than 10% of women worldwide. Microscopic analysis of a biopsy remains one of the most important methods to diagnose the type of breast cancer. This requires specialized analysis by pathologists, in a task that i) is highly time- and cost-consuming and ii) often leads to nonconsensual results. The relevance and potential of automatic classification algorithms using hematoxylin-eosin stained histopathological images has already been demonstrated, but the reported results are still sub-optimal for clinical use. With the goal of advancing the state-of-the-art in automatic classification, the Grand Challenge on BreAst Cancer Histology images (BACH) was organized in conjunction with the 15th International Conference on Image Analysis and Recognition (ICIAR 2018). A large annotated dataset, composed of both microscopy and whole-slide images, was specifically compiled and made publicly available for the BACH challenge. Following a positive response from the scientific community, a total of 64 submissions, out of 677 registrations, effectively entered the competition. From the submitted algorithms it was possible to push forward the state-of-the-art in terms of accuracy (87%) in automatic classification of breast cancer with histopathological images. Convolutional neuronal networks were the most successful methodology in the BACH challenge. Detailed analysis of the collective results allowed the identification of remaining challenges in the field and recommendations for future developments. The BACH dataset remains publically available as to promote further improvements to the field of automatic classification in digital pathology., Accepted for publication at Medical Image Analysis (Elsevier). Publication licensed under the Creative Commons CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

Objectives This study evaluated the usefulness of artificial intelligence (AI) algorithms as tools in improving the accuracy of histologic classification of breast tissue. Methods Overall, 100 microscopic photographs (test A) and 152 regions of interest in whole-slide images (test B) of breast tissue were classified into 4 classes: normal, benign, carcinoma in situ (CIS), and invasive carcinoma. The accuracy of 4 pathologists and 3 pathology residents were evaluated without and with the assistance of algorithms. Results In test A, algorithm A had accuracy of 0.87, with the lowest accuracy in the benign class (0.72). The observers had average accuracy of 0.80, and most clinically relevant discordances occurred in distinguishing benign from CIS (7.1% of classifications). With the assistance of algorithm A, the observers significantly increased their average accuracy to 0.88. In test B, algorithm B had accuracy of 0.49, with the lowest accuracy in the CIS class (0.06). The observers had average accuracy of 0.86, and most clinically relevant discordances occurred in distinguishing benign from CIS (6.3% of classifications). With the assistance of algorithm B, the observers maintained their average accuracy. Conclusions AI tools can increase the classification accuracy of pathologists in the setting of breast lesions.

ContextCushing’s syndrome frequently causes mental health impairment. Data in patients with adrenal incidentaloma (AI) are lacking.ObjectiveWe aimed to evaluate psychiatric and neurocognitive functions in AI patients, in relation to the presence of subclinical hypercortisolism (SH), and the effect of adrenalectomy on mental health.DesignWe enrolled 62 AI patients (64.8 ± 8.9 years) referred to our centers. Subclinical hypercortisolism was diagnosed when cortisol after 1mg-dexamethasone suppression test was >50 nmol/L, in the absence of signs of overt hypercortisolism, in 43 patients (SH+).InterventionsThe structured clinical interview for the Diagnostic and Statistical Manual of Mental Disorders-5, and 5 psychiatric scales were performed. The Brief Assessment of Cognition in Schizophrenia (Verbal and Working Memory, Token and Symbol Task, Verbal Fluency, Tower of London) was explored in 26 patients (≤65 years).ResultsThe prevalence of psychiatric disorders was 27.4% (SH+ 30.2% vs SH- 21.1%, P = 0.45). SH+ showed a higher prevalence of middle insomnia (by the Hamilton Depression Rating Scale) compared with SH- (51% vs 22%, P = 0.039). Considering the Sheehan Disability Scale, SH+ showed a higher disability score (7 vs 3, P = 0.019), higher perceived stress (4.2 ± 1.9 vs 2.9 ± 1.9, P = 0.015), and lower perceived social support (75 vs 80, P = 0.036) than SH-. High perceived stress was independently associated with SH (odds ratio [OR] = 5.46, confidence interval 95% 1.4–21.8, P = 0.016). Interestingly, SH+ performed better in verbal fluency (49.5 ± 38.9 vs 38.9 ± 9.0, P = 0.012), symbol coding (54.1 ± 6.7 vs 42.3 ± 15.5, P = 0.013), and Tower of London (15.1 vs 10.9, P = 0.009) than SH-. In 8 operated SH+, no significant changes were found.ConclusionsSubclinical hypercortisolism may influence patients’ mental health and cognitive performances, requiring an integrated treatment.

Early diagnosis of lung cancer via computed tomography can significantly reduce the morbidity and mortality rates associated with the pathology. However, searching lung nodules is a high complexity task, which affects the success of screening programs. Whilst computer-aided detection systems can be used as second observers, they may bias radiologists and introduce significant time overheads. With this in mind, this study assesses the potential of using gaze information for integrating automatic detection systems in the clinical practice. For that purpose, 4 radiologists were asked to annotate 20 scans from a public dataset while being monitored by an eye tracker device, and an automatic lung nodule detection system was developed. Our results show that radiologists follow a similar search routine and tend to have lower fixation periods in regions where finding errors occur. The overall detection sensitivity of the specialists was $\mathbf {0.67\pm 0.07}$ , whereas the system achieved 0.69. Combining the annotations of one radiologist with the automatic system significantly improves the detection performance to similar levels of two annotators. Filtering automatic detection candidates only for low fixation regions still significantly improves the detection sensitivity without increasing the number of false-positives.

Background Effective screening for colorectal cancer can reduce mortality by early detection of tumours and colonic polyps. An altered pattern of volatile organic compounds (VOCs) in exhaled breath has been proposed as a potential non‐invasive diagnostic tool for detection of cancer. The aim of this study was to evaluate the reliability of breath‐testing for colorectal cancer screening and early diagnosis using an advanced breath sampler. Methods The exhaled breath of patients with colorectal cancer and non‐cancer controls with negative findings on colonoscopy was collected using the ReCIVA® Breath Sampler. This portable device is able to capture the alveolar breath fraction without environmental contamination. VOCs were desorbed thermally and analysed by gas chromatography–mass spectrometry. The discriminatory ability of VOCs in detecting colorectal cancer was evaluated by receiver operating characteristic (ROC) curve analysis for each VOC, followed by cross‐validation by the leave‐one‐out method, and by applying stepwise logistic regression analysis. Results The study included 83 patients with colorectal cancer and 90 non‐cancer controls. Fourteen VOCs were found to have significant discriminatory ability in detecting patients with colorectal cancer. The model with the diagnosis of cancer versus no cancer resulted in a statistically significant likelihood of discrimination of 173·45 (P, Available screening methods for colorectal cancer have poor reliability and low patient compliance. Cancer cells produce altered metabolites, which are transported in the bloodstream and released in the alveoli; these volatile organic compounds (VOCs) can be detected in exhaled breath. This study used a new‐generation breath sampler, capable of selecting the alveolar fraction of the breath and preventing environmental contamination. A pattern of 14 VOCs was able to discriminate patients with colorectal cancer from healthy controls, with a true predictive value of 93 per cent, irrespective of cancer stage. Breath test signature in colorectal cancer

Proliferative diabetic retinopathy (PDR) is an advanced diabetic retinopathy stage, characterized by neovascularization, which leads to ocular complications and severe vision loss. However, the available DR-labeled retinal image datasets have a small representation of images of the severest DR grades, and thus there is lack of PDR cases for training DR grading models. Additionally, the criteria for labelling these images in the publicly available datasets is not always clear, with some images which do not show typical PDR lesions being labeled as PDR due to the presence of photo-coagulation treatment and laser marks. This problem, together with the datasets' high class imbalance, leads to a limited variability of the samples, which the typical data augmentation and class balancing cannot fully mitigate. We propose a heuristic-based data augmentation scheme based on the synthesis of neovessel (NV)-like structures that compensates for the lack of PDR cases in DR-labeled datasets. The proposed neovessel generation algorithm relies on the general knowledge of common location and shape of these structures. NVs are generated and introduced in pre-existent retinal images which can then be used for enlarging deep neural networks' training sets. The data augmentation scheme was tested on multiple datasets, and allows to improve the model's capacity to detect NVs.

Mild hypercortisolism (mHC) is defined as an excessive cortisol secretion, without the classical manifestations of clinically overt Cushing’s syndrome. This condition increases the risk of bone fragility, neuropsychological alterations, hypertension, diabetes, cardiovascular events and mortality. At variance with Cushing’s syndrome, mHC is not rare, with it estimated to be present in up to 2% of individuals older than 60 years, with higher prevalence (up to 10%) in individuals with uncontrolled hypertension and/or diabetes or with unexplainable bone fragility. Measuring cortisol after a 1 mg overnight dexamethasone suppression test is the first-line test for searching for mHC, and the degree of cortisol suppression is associated with the presence of cortisol-related consequences and mortality. Among the additional tests used for diagnosing mHC in doubtful cases, the basal morning plasma adrenocorticotroph hormone, 24-h urinary free cortisol and/or late-night salivary cortisol could be measured, particularly in patients with possible cortisol-related complications, such as hypertension and diabetes. Surgery is considered as a possible therapeutic option in patients with munilateral adrenal incidentalomas and mHC since it improves diabetes and hypertension and reduces the fracture risk. In patients with mHC and bilateral adrenal adenomas, in whom surgery would lead to persistent hypocortisolism, and in patients refusing surgery or in whom surgery is not feasible, medical therapy is needed. Currently, promising though scarce data have been provided on the possible use of pituitary-directed agents, such as the multi-ligand somatostatin analog pasireotide or the dopamine agonist cabergoline for the—nowadays—rare patients with pituitary mHC. In the more frequently adrenal mHC, encouraging data are available for metyrapone, a steroidogenesis inhibitor acting mainly against the adrenal 11-βhydroxylase, while data on osilodrostat and levoketoconazole, other new steroidogenesis inhibitors, are still needed in patients with mHC. Finally, on the basis of promising data with mifepristone, a non-selective glucocorticoid receptor antagonist, in patients with mild cortisol hypersecretion, a randomized placebo-controlled study is ongoing for assessing the efficacy and safety of relacorilant, a selective glucocorticoid receptor antagonist, for patients with mild adrenal hypercortisolism and diabetes mellitus/impaired glucose tolerance and/or uncontrolled systolic hypertension.

We propose iW-Net, a deep learning model that allows for both automatic and interactive segmentation of lung nodules in computed tomography images. iW-Net is composed of two blocks: the first one provides an automatic segmentation and the second one allows to correct it by analyzing 2 points introduced by the user in the nodule's boundary. For this purpose, a physics inspired weight map that takes the user input into account is proposed, which is used both as a feature map and in the system's loss function. Our approach is extensively evaluated on the public LIDC-IDRI dataset, where we achieve a state-of-the-art performance of 0.55 intersection over union vs the 0.59 inter-observer agreement. Also, we show that iW-Net allows to correct the segmentation of small nodules, essential for proper patient referral decision, as well as improve the segmentation of the challenging non-solid nodules and thus may be an important tool for increasing the early diagnosis of lung cancer., Comment: Pre-print submitted to IEEE Transactions on Biomedical Engineering

Illustrating to young people the extent to which human attitudes interfere with the well-being of terrestrial and marine species has been one of the objectives of several environmental organizations such as the United Nations Environment Program, the World Commission on Environment and Development, among others. However, there is a need to make this illustration through mechanisms that facilitate the retention of attention, and the enthusiasm during this learning, hence the need to have playful elements as facilitators of this process. Among the ludic activities, the digital game has been used more and more as a means for information transition, and above all to influence and change behaviors. Making young people create digital games around marine litter with emphasis on plastic pollution and developing them by visual tools, is believed to be a much more engaging mechanism that will boost knowledge and behavior change in relation to this theme. The work focuses on developing and validating a tool to support the creation of digital games to promote environmental awareness, targeting young adults in higher education in the city of Pemba, Cabo-Delgado province, northern Mozambique.

Purpose:Classic Cushing's syndrome (CS) is a severe disease characterized by central obesity, hypertension, easy bruising, striae rubrae, buffalo hump, proximal myopathy and hypertricosis. However, several CS cases have also been reported with unusual or camouflaged manifestations. In recent years, several authors investigated the prevalence of "hidden hypercortisolism" (HidHyCo) among subjects affected with bone fragility, hypertension and type 2 diabetes mellitus (DM2). The prevalence of the HidHyCo is estimated to be much higher than that of classic CS. However, similarly to classic CS, HidHyCo is known to increase the risk of fractures, cardiovascular disease and mortality. Methods:We reviewed all published cases of unusual presentations of hypercortisolism and studies specifically assessing the HidHyCo prevalence in diabetic, osteoporotic and hypertensive patients. Results:We found 49 HidHyCo cases, in whom bone fragility, hypertension and diabetes were the presenting manifestations of an otherwise silent hypercortisolism. Amongst these cases, 34.7%, 32.7%, 6.1% and 19.0%, respectively, had bone fragility, hypertension, DM2 or hypertension plus DM2 as the sole clinical manifestations of HidHyCo. Overall, 25% of HidHyCo cases were of pituitary origin, and bone fragility was the very prevalent first manifestation among them. In population studies, it is possible to estimate that 1-4% of patients with apparent primary osteoporosis has a HidHyCo and the prevalence of this condition among diabetics ranges between 3.4 and 10%. Conclusion:These data indicate that patients with resistant or suddenly worsening hypertension or DM2 or unexplainable bone fragility should be screened for HidHyCo using the most recently approved sensitive cut-offs.

The utilization of solar energy for driving reactions in which CO2 is converted into energy-rich products is discussed in this chapter. Three approaches are considered: i. electrolysis of water by photovoltaic energy to generate hydrogen used, in turn, for the hydrogenation of CO2 to gaseous or liquid fuels; ii. use of concentrated solar power for splitting CO2 and H2O and making Syngas; iii. the direct co-processing of water and CO2 to energy-rich products under solar irradiation. The former option can be applied in the short term as both the electrolysis and CO2 conversion are well-known processes; the second needs some further improvement of both the technology for concentrating solar energy and catalysts for H2O and CO2 splitting and may be applied in the medium term; the latter will most likely be exploited in the medium–long term as new, effective and stable photocatalysts must be discovered and advanced reactors-concentrators of solar light need to be developed.

In this chapter, carbon-free perennial primary energy sources are described and the potential of relevant technologies to produce electric or thermal energy is highlighted. Solar, wind, hydro, and geothermal power are analyzed for their contribution to substitute fossil-C in coming decades.

Adrenal incidentalomas (AI) may be associated with a mild autonomous cortisol secretion (MACS) in up to one third of cases. There is growing evidence that MACS patients actually present increased risk of cardiovascular disease and higher mortality rate, driven by increased prevalence of known cardiovascular risk factors, as well as accelerated cardiovascular remodelling. Adrenalectomy seems to have cardiometabolic beneficial effects in MACS patients but their management is still a debated topic due to the lack of high-quality studies. Several studies suggested that so called “non-functioning” AI may be actually “functioning” with an associated increased cardiovascular risk. Although the individual cortisol sensitivity and peripheral activation have been recently suggested to play a role in influencing the cardiovascular risk even in apparently eucortisolemic patients, to date the degree of cortisol secretion, as mirrored by the cortisol levels after dexamethasone suppression test remains the best predictor of an increased cardiovascular risk in AI patients. However, whether or not the currently used cut-off set at 50 nmol/L for cortisol levels after dexamethasone suppression could be considered completely reliable in ruling out hypercortisolism remains unclear.

In this chapter, the use of fossil-C as source of energy (compared to other sources) and as raw material for the chemical industry is discussed. Some fundamental processes are illustrated for the production of liquid fuels from either coal or natural gas. Emissions of CO2 are quoted for several sectors. The syngas and Fischer–Tropsch processes are discussed more in detail in the Deep Insight (DI).

The substitution of fossil-C is an urgent task for both the scarcity of resources and stopping the emission of green-house gases, (GHGs) that impact the climate of our planet. The transfer to the atmosphere of heat, due to the inefficiency of conversion of chemical energy into other forms of energy, and CO2 is also causing the increase of atmospheric water vapor, a stronger and more abundant greenhouse gas than CO2: all actors (heat, CO2 and H2Ov) concur to increase the temperature of the planet. Partial substitution of fossil-C can be achieved by using biomass, but that alone cannot produce all the energy and goods necessary for our society. Carbon will still be present in our future, but the solution to our problems is integrating solar chemistry and biotechnologies for using atmospheric CO2. This chapter, after an introduction to Carbon Circular Economy-CCE and CO2 utilization in Chemical Industry, considers the various options available of using solar energy for CO2 conversion into energy vectors that may allow to continue to use the existing infrastructures in transport and every-day life. Two options are considered: (i) solar-based water splitting and use of H2 for chemo-catalytic CO2 conversion using known processes, or (ii) photo-co-processing of water and CO2 to afford energy products and chemicals without H2 generation, a most innovative technology. The state of the art is provided and barriers to overcome for a large-scale exploitation of the two options are highlighted. The contribution to fossil-C substitution that may come from integration of solar chemistry with material science and biotechnology concludes this chapter.

The potential of carbon recycling through CO2 utilization is “sized” here by merging all options discussed in previous chapters. It is interesting to note that in the medium-long term some 7–9 GtCO2/y can be avoided, and this is a very interesting news: coupled to the use of biomass and utilization of perennial energies (SWHG) will make possible the reduction of the extraction of fossil fuels to, most likely, one-third–one-fourth with respect to today. This will be a great achievement.

In this chapter, the relevance of Carbon Dioxide Utilization (CCU) to Innovation and Sustainability of the Chemical Industry and to the strategy of the Circular Economy is discussed. A number of examples are presented of processes which may convert CO2 into added-value chemicals, polymeric materials, and fuels which have each a market higher than 1 Mt/y, causing a significant reduction of CO2 emission. Only thermal processes are considered here, while solar-driven processes are discussed in Chap. 10 and the integration of Chemical Catalysis and Biotechnology is presented in Chap. 11.

Fossil-C, in the form of coal, natural gas, and oil, covers 81+% of the energy necessary to satisfy the needs of our society. The continued use of fossil-C causes the accumulation of carbon dioxide in the atmosphere. The reduction of the emission of CO2 is becoming urgent.

In this study the LCA methodology is applied in order to satisfy two goals: i) to evaluate the hot spots in site-specific production chain of biodiesel from terrestrial and micro-algae feedstock; ii) to compare quantitatively, utilizing primary data, the impacts of the first generation in respect to the third generation bio-fuels. Results show that micro-algae are neither competitive yet with traditional oil crops nor with fossil fuel. The use of renewable technologies as photovoltaics and biogas self production might increase the competitiveness of micro-algae oil. Further investigations are however necessary to optimize their production chain and to increase the added value of co-products.

Lung cancer is the deadliest type of cancer worldwide and late detection is the major factor for the low survival rate of patients. Low dose computed tomography has been suggested as a potential screening tool but manual screening is costly and time-consuming. This has fuelled the development of automatic methods for the detection, segmentation and characterisation of pulmonary nodules. In spite of promising results, the application of automatic methods to clinical routine is not straightforward and only a limited number of studies have addressed the problem in a holistic way. With the goal of advancing the state of the art, the Lung Nodule Database (LNDb) Challenge on automatic lung cancer patient management was organized. The LNDb Challenge addressed lung nodule detection, segmentation and characterization as well as prediction of patient follow-up according to the 2017 Fleischner society pulmonary nodule guidelines. 294 CT scans were thus collected retrospectively at the Centro Hospitalar e Universitrio de So Joo in Porto, Portugal and each CT was annotated by at least one radiologist. Annotations comprised nodule centroids, segmentations and subjective characterization. 58 CTs and the corresponding annotations were withheld as a separate test set. A total of 947 users registered for the challenge and 11 successful submissions for at least one of the sub-challenges were received. For patient follow-up prediction, a maximum quadratic weighted Cohen's kappa of 0.580 was obtained. In terms of nodule detection, a sensitivity below 0.4 (and 0.7) at 1 false positive per scan was obtained for nodules identified by at least one (and two) radiologist(s). For nodule segmentation, a maximum Jaccard score of 0.567 was obtained, surpassing the interobserver variability. In terms of nodule texture characterization, a maximum quadratic weighted Cohen's kappa of 0.733 was obtained, with part solid nodules being particularly challenging to classify correctly. Detailed analysis of the proposed methods and the differences in performance allow to identify the major challenges remaining and future directions - data collection, augmentation/generation and evaluation of under-represented classes, the incorporation of scan-level information for better decision-making and the development of tools and challenges with clinical-oriented goals. The LNDb Challenge and associated data remain publicly available so that future methods can be tested and benchmarked, promoting the development of new algorithms in lung cancer medical image analysis and patient follow-up recommendation.

In the present paper, we report the synthesis and characterization of both binary (Cu2O, Fe2O3, and In2O3) and ternary (Cu2O-Fe2O3 and Cu2O-In2O3) transition metal mixed-oxides that may find application as photocatalysts for solar driven CO2 conversion into energy rich species. Two different preparation techniques (High Energy Milling (HEM) and Co-Precipitation (CP)) are compared and materials properties are studied by means of a variety of characterization and analytical techniques UV-Visible Diffuse Reflectance Spectroscopy (UV-VIS DRS), X-ray Photoelectron Spectroscopy (XPS), X-Ray Diffraction (XRD), Transmission Electron Microscopy (TEM), and Energy Dispersive X-Ray spectrometry (EDX). Appropriate data elaboration methods are used to extract materials bandgap for Cu2O@Fe2O3 and Cu2O@In2O3 prepared by HEM and CP, and foresee whether the newly prepared semiconductor mixed oxides pairs are useful for application in CO2-H2O coprocessing. The experimental results show that the synthetic technique influences the photoactivity of the materials that can correctly be foreseen on the basis of bandgap experimentally derived. Of the mixed oxides prepared and described in this work, only Cu2O@In2O3 shows positive results in CO2-H2O photo-co-processing. Preliminary results show that the composition and synthetic methodologies of mixed-oxides, the reactor geometry, the way of dispersing the photocatalyst sample, play a key role in the light driven reaction of CO2&ndash, H2O. This work is a rare case of full characterization of photo-materials, using UV-Visible DRS, XPS, XRD, TEM, EDX for the surface and bulk analytical characterization. Surface composition may not be the same of the bulk composition and plays a key role in photocatalysts behavior. We show that a full material knowledge is necessary for the correct forecast of their photocatalytic behavior, inferred from experimentally determined bandgaps.

Involving students in the creation of their own games about a theme may enhance the interest toward the addressed topic, a sense of ownership and a better understanding of the value of what is learned. This paper presents the application of a Toolkit to Game Design in two Game Creation sessions with upper-secondary students. The Toolkit was developed in the context of the Gamers4Nature project and includes resources and tools designed to enhance the active participation of the youngest audience in game creation activities, while promoting environmental preservation and biodiversity conservation. The Toolkit to Game Design was used in two Game Design sessions organized with upper-secondary students (n=28). By using the Toolkit, 10 functional prototypes of digital games were created. Students enhanced the Toolkit’s ease of use, mentioned that it was an engaging approach to game creation and that its use promoted a more active way to addressed the educational content and the programming activity. Preliminary results indicate that the Toolkit can be seen as an engaging approach to game creation, able to be adopted in different upper-secondary and higher education disciplines and fields.

Background In patients with adrenal incidentalomas (AIs), there is uncertainty on how to rule out hypercortisolism. The occurrence of postsurgical (unilateral adrenalectomy) hypocortisolism (PSH) has been proposed as a proof of the presence of presurgical hypercortisolism in AI patients. The aim of this study was to define the thresholds of cortisol level after the 1 mg overnight dexamethasone suppression test (F-1mgDST), urinary free cortisol (UFC), midnight serum cortisol (MSC), and adrenocorticotropin (ACTH) to predict the absence of PSH in AI patients undergoing surgery. Methods In 60 patients who underwent AI excision, cortisol secretion was assessed by a low-dose corticotropin stimulation test or insulin tolerance test when needed. We searched for the lowest presurgical value of F-1mgDST, UFC, and MSC and the highest value for ACTH in AI patients with PSH as indexes of normal cortisol secretion. Results The lowest values of F-1mgDST, UFC, and MSC and the highest value for ACTH in PSH patients were 1.2 µg/dL (33 nmol/L), 10.4 µg/24 hours (29 nmol/24 hours), 1.2 µg/dL (33 nmol/L), and 26.9 pg/mL (6 pmol/L), respectively, but only F-1mgDST Conclusion In AI patients a F-1mgDST

Purpose. Cortisol secretion, peripheral activation and sensitivity seem to be associated with hypertension (HY), type-2 diabetes (T2D) and fragility fractures (FX) even in eucortisolemic subjects. The aim of the present study was to determine the cut-off(s) of the parameters of cortisol secretion and peripheral activation for predicting the presence of HY, T2D and FX (comorbidities). Methods. In 206 postmenopausal females (157 with ≥1 comorbidities and 49 without any), we assessed the ratio between 24-hour urinary free cortisol and cortisone (R-UFF/UFE, cortisol activation index), cortisol after 1mg-overnight-dexamethasone (F-1mgDST, cortisol secretion index), and the GC receptor N363S single-nucleotide polymorphism (N363S-SNP, cortisol sensitivity index). Results. The cut-offs for F-1mgDST and R-UFF/UFE set at 0.9 μg/dL (Area Under the Curve, AUC 0.634±0.43, p=0.005) and 0.17 (AUC 0.624±0.5, p=0.017) respectively, predicted the presence of ≥1 comorbidities. The presence of F-1mgDST >0.9 μg/dL plus R-UFF/UFE >0.17 showed 82.1% specificity for predicting the presence of ≥1 comorbidities, while the simultaneous presence of F-1mgDST ≤0.9 μg/dL and R-UFF/UFE ≤0.17 showed 88% sensitivity for predicting the absence of comorbidities. The F-1mgDST >0.9 μg/dL or R-UFF/UFE >0.17 was associated with 2.8 and 2.1 fold increased risk of having ≥1 comorbidities, respectively. The F-1mgDST ≤0.9 μg/dL plus R-UFF/UFE ≤0.17 or F-1mgDST >0.9 μg/dL plus R-UFF/UFE >0.17 was associated with 2.8 fold reduced or 4.9 fold increased risk of having ≥1 comorbidities regardless of age, BMI and N363S-SNP. Conclusions. F-1mgDST >0.9 μg/dL and R-UFF/UFE >0.17 may be used for predicting the presence of ≥1 among HY, T2D and fragility FX.

Currently, lung cancer is the most lethal in the world. In order to make screening and follow-up a little more systematic, guidelines have been proposed. Therefore, this study aimed to create a diagnostic support approach by providing a patient label based on the LUNG-RADS™ guidelines. The only input required by the system is the nodule centroid to take the region of interest for the input of the classification system. With this in mind, two deep learning networks were evaluated: a Wide Residual Network and a DenseNet. Taking into account the annotation uncertainty we proposed to use sample weights that are introduced in the loss function, allowing nodules with a high agreement in the annotation process to take a greater impact on the training error than its counterpart. The best result was achieved with the Wide Residual Network with sample weights achieving a nodule-wise LUNG-RADS™ labelling accuracy of $0.735\pm 0.003$ .

Cortisol secretion, peripheral activation, and sensitivity seem to be associated with hypertension (HY), type 2 diabetes (T2D), and fragility fractures (FX) even in eucortisolemic subjects. The aim of the present study was to determine the cutoff(s) of the parameters of cortisol secretion and peripheral activation for predicting the presence of HY, T2D, and FX (comorbidities). In 206 postmenopausal females (157 with ≥1 comorbidities and 49 without any), we assessed the ratio between 24-h urinary free cortisol and cortisone (R-UFF/UFE, cortisol activation index), cortisol after 1 mg-overnight-dexamethasone (F-1mgDST, cortisol secretion index), and the GC receptor N363S single-nucleotide polymorphism (N363S-SNP, cortisol sensitivity index). The cutoffs for F-1mgDST and R-UFF/UFE were set at 0.9 μg/dL (area under the curve, AUC 0.634 ± 0.43, p = 0.005) and 0.17 (AUC 0.624 ± 0.5, p = 0.017), respectively, predicted the presence of ≥1 comorbidities. The presence of F-1mgDST > 0.9 μg/dL plus R-UFF/UFE > 0.17 showed 82.1% specificity for predicting the presence of ≥1 comorbidities, while the simultaneous presence of F-1mgDST ≤ 0.9 μg/dL and R-UFF/UFE ≤ 0.17 showed 88% sensitivity for predicting the absence of comorbidities. The F-1mgDST > 0.9 μg/dL or R-UFF/UFE > 0.17 was associated with 2.8 and 2.1-fold increased risk of having ≥1 comorbidities, respectively. The F-1mgDST ≤ 0.9 μg/dL plus R-UFF/UFE ≤ 0.17 or F-1mgDST > 0.9 μg/dL plus R-UFF/UFE > 0.17 was associated with 2.8-fold reduced or 4.9-fold increased risk of having ≥1 comorbidities regardless of age, BMI, and N363S-SNP. F-1mgDST > 0.9 μg/dL and R-UFF/UFE > 0.17 may be used for predicting the presence of ≥1 among HY, T2D, and fragility FX.

Translating the implied meanings in utterances is one of the trickiest situations translators may confront. One example is in translating utterances that flout the maxim of quality. When a speaker flouts the maxim of quality, they are implying further information that is not represented in the utterance. Translators use various translation techniques in order to convey the meaning of the original text in the most appropriate and acceptable form in the target text. This study investigates how translation techniques may affect the quality of a translation. The approach implemented in this study is pragmatics in translation. This study belongs to the field of descriptive qualitative research with an embedded case study. For data, we look at all the utterances which may be said to be flouting the maxim of quality in the source text and its translation. Content analysis and focus group discussion were applied as the methods to collect and analyze the data. A focus group discussion was used to assess translation quality. The majority of the data was classified as accurate and acceptable, while the rest was considered less accurate and inaccurate due to the application of the translation technique amplification (addition), discursive creation and literal translation. Some data was also found to be less acceptable due to literal translation and pure borrowing.

This essay discusses a deep malaise of contemporary architecture, made more obvious by experiencing COVID-19 lockdowns for several months. Evidence-based arguments urge society to improve human health and well-being by re-considering the design of interior and exterior spaces. So far, predictions of how design will “improve” after COVID-19 just continue business-as-usual, ignoring accumulated evidence. Yet, the negative emotional experience of families cooped up during the pandemic reveals the failure of the standard approach to designing spaces. An architecture that adapts to human biology and psychology starts with the relatively new understanding of people interacting unconsciously with their environment and broadens it. A traditional design toolkit, augmented by the latest technology, can generate healing spaces as judged by their ability to enhance users’ subjective well-being. We recommend implementing specific design innovations to achieve this goal—replacing industrial-minimalism with biophilic and neuro-based design and using documented patterns that trigger feelings of happiness in users.

This paper aims at highlighting the hurdles and traps on the way back from CO2 to chemicals (or even fuels). The case of the synthesis of dialkyl carbonates is discussed, considering several synthetic conditions and comparing the relevant amount of energy necessary for product separation. The calculations show that the post-reaction separation process may share an important part of the energy consumption in the whole synthetic procedure and make, in some conditions, the reaction a strong CO2 emitter more than a CO2 consumer.

Incidentally discovered adrenal masses are very common given the increased number of imaging studies performed in recent years. We here report a clinical case of a 20-year-old woman who presented with left flank pain. Ultrasound examination revealed a contralateral adrenal mass, which was confirmed at computed tomography (CT) scan. Hormonal hypersecretion was excluded. Given the size (11 × 10 × 7 cm) and the uncertain nature of the mass, it was surgically removed and sent for pathological analyses. Conclusive diagnosis was ganglioneuroblastoma. Ganglioneuroblastoma is an uncommon malignant tumor, extremely rare in adults, particularly in females. This neoplasm is frequently localized in adrenal gland.

Lung cancer is the deadliest type of cancer worldwide and late detection is one of the major factors for the low survival rate of patients. Low dose computed tomography has been suggested as a potential early screening tool but manual screening is costly, time-consuming and prone to interobserver variability. This has fueled the development of automatic methods for the detection, segmentation and characterisation of pulmonary nodules but its application to the clinical routine is challenging. In this study, a platform for the development, deployment and testing of pulmonary nodule computer-aided strategies is presented: LNDetector. LNDetector integrates image exploration and nodule annotation tools as well as advanced nodule detection, segmentation and classification methods and gaze characterisation. Different processing modules can easily be implemented or replaced to test their efficiency in clinical environments and the use of gaze analysis allows for the development of collaborative strategies. The potential use of this platform is shown through a combination of visual search, gaze characterisation and automatic nodule detection tools for an efficient and collaborative computer-aided strategy for pulmonary nodule screening.

Diabetic Retinopathy (DR) is one of the leading causes of preventable blindness in the developed world. With the increasing number of diabetic patients there is a growing need of an automated system for DR detection. We propose Eye WeS, a method that not only detects DR in eye fundus images but also pinpoints the regions of the image that contain lesions, while being trained with image labels only. We show that it is possible to convert any pre-trained convolutional neural network into a weakly-supervised model while increasing their performance and efficiency. EyeWeS improved the results of Inception V3 from 94.9% Area Under the Receiver Operating Curve (AUC) to 95.8% AUC while maintaining only approximately 5% of the Inception V3's number of parameters. The same model is able to achieve 97.1% AUC in a cross-dataset experiment.

Lung cancer has an increasing preponderance in worldwide mortality, demanding for the development of efficient screening methods. With this in mind, a binary classification method using Lung-RADSTM guidelines to warn changes in the screening management is proposed. First, having into account the lack of public datasets for this task, the lung nodules in the LIDC-IDRI dataset were re-annotated to include a Lung-RADSTM-based referral label. Then, a wide residual network is used for automatically assessing lung nodules in 3D chest computed tomography exams. Unlike the standard malignancy prediction approaches, the proposed method avoids the need to segment and characterize lung nodules, and instead directly defines if a patient should be submitted for further lung cancer tests. The system achieves a nodule-wise accuracy of 0.87±0.02.

This paper proposes a new methodology to automatically segment and measure the volume of pulmonary nodules in lung computed tomography (CT) scans. Estimating the malignancy likelihood of a pulmonary nodule based on lesion characteristics motivated the development of an unsupervised pulmonary nodule segmentation and volume measurement as a preliminary stage for pulmonary nodule characterization. The idea is to optimally cluster a set of feature vectors composed by intensity and shape-related features in a given feature data space extracted from a pre-detected nodule. For that purpose, a metaheuristic search based on evolutionary computation is used for clustering the corresponding feature vectors. The proposed method is simple, unsupervised and is able to segment different types of nodules in terms of location and texture without the need for any manual annotation. We validate the proposed segmentation and volume measurement on the Lung Image Database Consortium and Image Database Resource Initiative – LIDC-IDRI dataset. The first dataset is a group of 705 solid and sub-solid (assessed as part-solid and non-solid) nodules located in different regions of the lungs, and the second, more challenging, is a group of 59 sub-solid nodules. The average Dice scores of 82.35% and 71.05% for the two datasets show the good performance of the segmentation proposal. Comparisons with previous state-of-the-art techniques also show acceptable and comparable segmentation results. The volumes of the segmented nodules are measured via ellipsoid approximation. The correlation and statistical significance between the measured volumes of the segmented nodules and the ground-truth are obtained by Pearson correlation coefficient value, obtaining an R-value ≥ 92.16% with a significance level of 5%.

Context Previous data suggest a possible association between type 2 diabetes (T2D) and fragility fractures (FX) with the degree of glucocorticoid suppressibility (GCS) and peripheral activation or sensitivity even in persons without hypercortisolemia. Objective To investigate whether the degree of GCS, GC sensitivity, and peripheral activation in persons without overt or mild hypercortisolism are associated with hypertension and with the number of the possible consequences of cortisol excess among patients with T2D, fragility FX, and hypertension. Design Case-control study. Setting Outpatient clinic. Patients A total of 216 postmenopausal women without hypercortisolemia (age, 50 to 80 years; 108 with hypertension); 68 and 99 patients had fragility FX and T2D, respectively Main outcome measures We assessed 24-hour urinary free cortisol (UFF), cortisone (UFE), their ratio (R-UFF/UFE), (F-1mgDST), and the GC receptor N363S single-nucleotide polymorphism (N363S-SNP). Results Hypertension was associated with F-1 mgDST [odds ratio (OR), 3.3; 95% CI, 1.5 to 7.5; P = 0.004) and R-UFF/UFE (OR, 101.7; 95% CI, 2.6 to 4004.1; P = 0.014), regardless of age, body mass index, and presence of the N363S single nucleotide polymorphism and of T2D. The progressive increase in the number of possible consequences of cortisol excess was significantly associated with F-1mgDST levels (R2 = 0.125; P = 0.04), R-UFF/UFE (R2 = 0.46; P = 0.02), and the prevalence of N363S heterozygous variant (T = 0.46; P = 0.015), after adjustment for age. Conclusions In postmenopausal women without hypercortisolemia, hypertension is associated with GCS and GC peripheral activation. The number of possible consequences of cortisol excess (among patients with hypertension, T2D, and fragility FX) is associated with GCS, GC peripheral activation, and the prevalence of the N363S heterozygous variant.

International audience; Surgical tool detection is attracting increasing attention from the medical image analysis community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surgeon at each instant. The main motivation for annotating tool usage is to design efficient solutions for surgical workflow analysis, with potential applications in report generation, surgical training and even real-time decision support. Most existing tool annotation algorithms focus on laparo-scopic surgeries. However, with 19 million interventions per year, the most common surgical procedure in the world is cataract surgery. The CATARACTS challenge was organized in 2017 to evaluate tool annotation algorithms in the specific context of cataract surgery. It relies on more than nine hours of videos, from 50 cataract surgeries, in which the presence of 21 surgical tools was manually annotated by two experts. With 14 participating teams, this challenge can be considered a success. As might be expected,-H. Conze et al. / Medical Image Analysis 52 (2019) 24-41 25 the submitted solutions are based on deep learning. This paper thoroughly evaluates these solutions: in particular, the quality of their annotations are compared to that of human interpretations. Next, lessons learnt from the differential analysis of these solutions are discussed. We expect that they will guide the design of efficient surgery monitoring tools in the near future.

The need to reduce the emission of carbon dioxide into the atmosphere is pushing toward the use of “renewable carbon”, so to avoid as much as possible burning “fossil carbon”. It would be possible to complement the natural “carbon cycle” by developing man-made industrial processes for “carbon recycling”, converting, thus, “spent carbon” as CO 2 into “working carbon”, as that present in valuable chemicals or fuels. Such practice would fall into the utilization of “renewable carbon”, as the man-made process would perfectly mimic the natural process. An order of complexity higher would be represented by the integration of biotechnology and catalysis for an effective CO 2 conversion, using selective catalysts such as enzymes, or even whole microorganisms, coupled to chemical technologies for energy supply to enzymes, using perennial sources as sun or wind or geothermal as primary energy. These days all the above approaches are under investigation with an interesting complementarity of public–private investment in research. This paper aimed at making the state of the art in CO 2 conversion and giving a perspective on the potential of such technology. Each atom of C we can recycle is an atom of fossil carbon left in the underground for next generations that will not reach the atmosphere today.

The transplantation of glucose-responsive, insulin-producing cells offers the potential for restoring glycemic control in individuals with diabetes. Pancreas transplantation and the infusion of cadaveric islets are currently implemented clinically, but these approaches are limited by the adverse effects of immunosuppressive therapy over the lifetime of the recipient and the limited supply of donor tissue. The latter concern may be addressed by recently described glucose-responsive mature beta cells that are derived from human embryonic stem cells (referred to as SC-β cells), which may represent an unlimited source of human cells for pancreas replacement therapy. Strategies to address the immunosuppression concerns include immunoisolation of insulin-producing cells with porous biomaterials that function as an immune barrier. However, clinical implementation has been challenging because of host immune responses to the implant materials. Here we report the first long-term glycemic correction of a diabetic, immunocompetent animal model using human SC-β cells. SC-β cells were encapsulated with alginate derivatives capable of mitigating foreign-body responses in vivo and implanted into the intraperitoneal space of C57BL/6J mice treated with streptozotocin, which is an animal model for chemically induced type 1 diabetes. These implants induced glycemic correction without any immunosuppression until their removal at 174 d after implantation. Human C-peptide concentrations and in vivo glucose responsiveness demonstrated therapeutically relevant glycemic control. Implants retrieved after 174 d contained viable insulin-producing cells.

Lung cancer diagnosis is made by radiologists through nodule search in chest Computed Tomography (CT) scans. This task is known to be difficult and prone to errors that can lead to late diagnosis. Although Computer-Aided Diagnostic (CAD) systems are promising tools to be used in clinical practice, experienced radiologists continue to perform better diagnosis than CADs. This paper proposes a methodology for characterizing the radiologist's gaze during nodules search in chest CT scans. The main goals are to identify regions that attract the radiologists' attention, which can then be used for improving a lung CAD system, and to create a tool to assist radiologists during the search task. For that purpose, the methodology processes the radiologists' gaze and their mouse coordinates during the nodule search. The resulting data is then processed to obtain a 3D gaze path from which relevant attention studies can be derived. To better convey the found information, a reference model of the lung that eases the communication of the location of relevant anatomical/pathological findings is also proposed. The methodology is tested on a set of 24 real-practice gazes, recorded via an Eye tracker, from 3 radiologists.

Objectives: This pilot project aimed to examine the acceptability and feasibility of a group storytelling intervention to support self-management among adults living with type 2 diabetes. Methods: Two waves of a single-arm storytelling intervention, consisting of 8 sessions at a community health centre, were delivered to 8 adults with type 2 diabetes. Diabetes educators facilitated each session, in which patients shared stories about diabetes-self-management topics of their choice. Focus groups with both patients and facilitators explored the feasibility and acceptability of the sessions. External raters assessed the fidelity of the intervention's implementation. Results: Overarching themes describe the acceptability and feasibility of the intervention: 1) the facilitation of patient self-direction, group cohesion, collective learning and support; 2) roles of facilitator educator, and peer learner; 3) the intervention's customization to patients' preferences. The sessions were delivered with high fidelity (averaging 84.4%). Conclusions: Informal group storytelling enables patients to discuss, understand and give personal meaning to the information that was exchanged, and facilitates educators' better understanding of patients' concerns and gaps in knowledge and how-to strategies that can inform their practice. The group storytelling intervention is acceptable to patients and educators and can be delivered with high fidelity. Further research into effective patient recruitment methods and evaluation of the intervention's impact on diabetes self-management is required.

Studies on genome-wide transcription patterns have shown that many genetic alterations implicated in pheochromocytoma-paraganglioma (P-PGL) syndromes cluster in a common cellular pathway leading to aberrant activation of molecular response to hypoxia in normoxic conditions (the pseudohypoxia hypothesis). Several cases of P-PGL have been reported in patients with cyanotic congenital heart disease (CCHD). Patients affected with CCHD have an increased likelihood of P-PGL compared to those affected with noncyanotic congenital heart disease. One widely supported hypothesis is that chronic hypoxia represents the determining factor supporting this increased risk. We report the case of a 23-year-old woman affected with congenital tricuspid atresia surgically by the Fontan procedure. The patient was admitted to hospital with hypertensive crisis and dyspnea. Chest computed tomography revealed, incidentally, a 6-cm mass in the left adrenal lodge. Increased levels of noradrenaline (NA) and its metabolites were detected (plasma NA 5003.7 pg/ml, n.v.µg/24 h, n.v.µg/24 h, n.v.α- and β-blockers and histopathological examination confirmed the diagnosis of pheochromocytoma (Ki-67