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Nonalcoholic fatty liver disease (NAFLD) is a highly prevalent disease without any approved treatment to-date despite intensive research efforts by researchers and pharmaceutical industry. Fibroblast growth factor (FGF)-21 has been gaining increasing attention as a possible contributing factor and thus therapeutic target for obesity-related metabolic disorders, including NAFLD, mainly due to its effects on lipid and carbohydrate metabolism. Most animal and human observational studies have shown higher FGF-21 concentrations in NAFLD than non-NAFLD, implying that FGF-21 may be increased to counteract hepatic steatosis and inflammation. However, although Mendelian Randomization studies have revealed that variations of FGF-21 levels within the physiological range may have effects in hyperlipidemia and possibly nonalcoholic steatohepatitis, they also indicate that FGF-21, in physiological concentrations, may fail to reverse NAFLD and may not be able to control obesity and other diseases, indicating a state of FGF-21 resistance or insensitivity that could not respond to administration of FGF-21 in supraphysiological concentrations. Interventional studies with FGF-21 analogs (eg, pegbelfermin, efruxifermin, BOS-580) in humans have provided some favorable results in Phase 1 and Phase 2 studies. However, the definite effect of FGF-21 on NAFLD may be clarified after the completion of the ongoing clinical trials with paired liver biopsies and histological endpoints. The aim of this review is to critically summarize experimental and clinical data of FGF-21 in NAFLD, in an attempt to highlight existing knowledge and areas of uncertainty, and subsequently, to focus on the potential therapeutic effects of FGF-21 and its analogs in NAFLD.

Introduction: The ongoing severe acute respiratory syndrome (SARS)-CoV-2 pandemic has expanded globally. The aim of the current study is to investigate the knowledge, attitudes, and practices (KAP) of health care professionals in Greece towards SARS-CoV-2. Methods: From 10–25 February 2020, 500 health care workers were approached. Knowledge, attitudes, and practices towards SARS-CoV-2 were assessed via a personal interview questionnaire. For knowledge, each correct answer was given 1 point; attitudes, or concerns aimed at prevention of SARS-CoV-2 infection, and practices, or behaviors towards performing preventive practices, were assigned 1 point each. Points were summed and a score for each category was calculated. Results: A total of 461 health care workers returned the questionnaire and were included in the analysis (mean age ± SD: 44.2 ± 10.78 years, 74% females). The majority were nurses (47.5%), followed by physicians (30.5%) and paramedics (19%). The majority of subjects (88.28%) had a good level of knowledge (knowledge score equal to 4, or more). The majority of participants (71%) agreed with the temporary traveling restrictions ban. The uptake of a future vaccine against SARS-CoV-2 was estimated at 43%. Knowledge score was significantly associated with both attitudes score (p = 0.011) and practices score (p < 0.001), indicating that subjects with a high knowledge score demonstrated a more positive perception on preventive measures and would practice more preventive measures. Attitudes score was significantly associated with practices score (p = 0.009) indicating that subjects with a higher attitudes score are more likely to perform practices towards the prevention of SARS-CoV-2 transmission. Conclusion: There is a high level of knowledge concerning SARS-CoV-2 pandemic among Greek health care workers and this is significantly associated with positive attitudes and practices towards preventive health measures. The high level of knowledge of health professionals about SARS-CoV-2 may have contributed considerably to the successful management of the pandemic in Greece. Tailored educational campaigns aiming to increase the proportion of health care workers willing to accept a potential SARS-CoV-2 vaccine could be of paramount importance in future proactive vaccine educational campaigns.

Aims/hypothesis Clinical data regarding circulating leptin levels in patients with non-alcoholic fatty liver disease (NAFLD) are conflicting. The purpose of this meta-analysis was to compare leptin levels between the following groups: patients with biopsy-proven NAFLD vs controls; simple steatosis (SS) patients vs controls; non-alcoholic steatohepatitis (NASH) patients vs controls and NASH patients vs SS patients. Methods We performed a systematic search in PubMed, Scopus and the Cochrane Library. We analysed 33 studies, published between 1999 and 2014, including 2,612 individuals (775 controls and 1,837 NAFLD patients). Results Higher circulating leptin levels were observed in NAFLD patients vs controls (standardised mean difference [SMD] 0.640; 95% CI 0.422, 0.858), SS patients vs controls (SMD 0.358; 95% CI 0.043, 0.673), NASH patients vs controls (SMD 0.617; 95% CI 0.403, 0.832) and NASH patients vs SS patients (SMD 0.209; 95% CI 0.023, 0.395). These results remained essentially unchanged after excluding studies involving paediatric or adolescent populations and/or individuals undergoing bariatric surgery. There was moderate-to-severe heterogeneity among studies in all comparisons, but no significant publication bias was detected. Meta-regression analysis demonstrated that BMI was inversely associated with leptin SMD and accounted for 26.5% ( p  = 0.014) and 32.7% ( p  = 0.021) of the between-study variance in the comparison between NASH patients and controls and NAFLD patients and controls, respectively. However, when bariatric studies were excluded, BMI did not significantly explain the between-study variance. Conclusions/interpretation Circulating leptin levels were higher in patients with NAFLD than in controls. Higher levels of circulating leptin were associated with increased severity of NAFLD, and the association remained significant after the exclusion of studies involving paediatric or adolescent populations and morbidly obese individuals subjected to bariatric surgery.

Key messageHeight–diameter models were developed specifically for Pinus nigra Arn., an important commercially species extending in the Mediterranean and central Europe region. The accuracy of the proposed models is expected to substantially improve the tree volume and total biomass estimations.Three types of nonlinear height–diameter models, simple, generalized mixed effects and fixed, were evaluated against independent data from even-aged black pine (Pinus nigra Arn.) natural stands located in Olympus National Park in Greece in an effort to accurately predict total tree height (h). A total of 3442 pairs of height–diameter data were collected from 66 randomly selected non-permanent plots. Using the diameter at breast height (d) as independent variable, a number of simple nonlinear mixed-effects models were fitted to select the most appropriate for further analysis. Continuously, basic stand parameters were added as predictors, so as to develop a generalized (h–d) model with increased applicability prospects. At that stage, a mixed-effects modeling approach was applied to improve height predictability based on the reduction of the Root Mean Squared Error (RMSE). The analysis showed that the inclusion of dominant height and dominant diameter as predictors improved the accuracy of the Chapman–Richards model. Moreover, the random components within the nonlinear (h–d) model explained a great part of the height variation, which was not possible to explain previously. The mixed-effects modeling approach provides an adequate framework for predicting the black pine tree height accurately, which could save intensive fieldwork.

Sustainable forest management should be pursued in all public forests of the EU countries, as this constitutes a legal requirement within the frame of the FOREST EUROPE policy. However, the forest management sustainability assessment process is a complex task, mainly because it involves integration of multiple environmental, socio-economic and institutional impacts at different spatial scales of different forest management policies, which are considered for implementation at any forest location. Moreover, the conflicts and interests of the various stakeholders related to the forest resources should be included in the assessment process. Much of the on-going research, therefore, focuses on the development of tools that can facilitate the integration of the different type of forest resource impacts and conflicts towards achievement of forest management sustainability. This paper presents a multi-criteria approach, which combined spatial analysis, Geographic Information Systems (GIS), the Analytic Hierarchy Process (AHP), spatially referenced impact indicator models for pairwise comparisons, the fuzzy extent analysis, fuzzy preference programming and the ideal solution concept in order to assess the performance of forest management sustainability at regional level. The combined multi-criteria approach was successfully implemented to the forests of Eastern Macedonia and Thrace Region in northern Greece through the operation of the National Forest Governance Council. Seven forest management policies were subjected to sustainability assessment and an Overall Forest Sustainability Performance Index (OFSPI) was calculated for each one of them. The final ranking of the forest management policies was based on their OFSPI values. Furthermore, sensitivity analysis was conducted to explore robustness of the final solution.

Perovskite solar cells (PSCs) have already achieved comparable performance to industrially established silicon technologies. However, high performance and stability must be also be achieved at large area and low cost to be truly commercially viable. The fully printable triple-mesoscopic carbon perovskite solar cell (mCPSC) has demonstrated unprecedented stability and can be produced at low capital cost with inexpensive materials. These devices are inherently scalable, and large-area modules have already been fabricated using low-cost screen printing. As a uniquely stable, scalable and low-cost architecture, mCPSC research has advanced significantly in recent years. This review provides a detailed overview of advancements in the materials and processing of each individual stack layer as well as in-depth coverage of work on perovskite formulations, with the view of highlighting potential areas for future research. Long term stability studies will also be discussed, to emphasise the impressive achievements of mCPSCs for both indoor and outdoor applications.

In the current study, a novel approach combining quantile regression with nonlinear mixed-effects (QR-NLME) modeling was applied to predict the maximum crown width (cwmax) of three economically important forest species—the European beech (Fagus sylvatica L.), the black pine (Pinus nigra Arn.), and the Calabrian pine (Pinus brutia Ten.) at tree level. A power QR-NLME model was fitted first to a dataset including 1414 European beech trees obtained from 29 randomly distributed sample plots, 770 black pine trees from 25 sample plots, and 1880 Calabrian pine trees from 41 sample plots in Greece, to predict the cwmax at tree level. Additionally, a nonlinear mixed-effects model (NLME) was fitted to the same dataset to predict the average crown width at tree level for all species. In the second stage, the crown competition factor (CCF) was estimated based on the population average response of the cwmax predictions. The proposed approach presented sound results when compared with the outcomes of relevant models from other regions fitted to open-grown tree data, and therefore, it can be well implemented on clustered data structures, in cases of absence of open-grown tree data.

The Greek fir ( Abies cephalonica Loudon), is a significant species in Greece of high ecological and economic value. However, despite its high importance, a notable lack of allometric models regarding its basic dendrometric attributes at tree level can be observed. The current study aimed to fill this knowledge gap. Based on a sample of 2873 well-documented fir trees from 47 sample plots in Parnassos Mt., in central Greece, nonlinear mixed-effects allometric models for the prediction of total height, crown width, height to live crown, and maximum crown width have been developed. The proposed models presented reasonable predictive performance, explaining 60% to 87% of the tree attributes variance in all cases, yielding modest prediction errors, while satisfying all the statistical assumptions in terms of fitting. The inclusion of statistically significant stand-level covariates improved the model's ability to explain a specific systematic variation in the response tree variables. The proposed models provided detailed information on tree crown characteristics, constituting valuable tools in a wider frame of sustainable forest management, as they can be linked with a range of forest models and products, offering insights into the complex interactions among tree attributes.