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Winter is an important season for many limnological processes, which can range from biogeochemical transformations to ecological interactions. Interest in the structure and function of lake ecosystems under ice is on the rise. Although limnologists working at polar latitudes have a long history of winter work, the required knowledge to successfully sample under winter conditions is not widely available and relatively few limnologists receive formal training. In particular, the deployment and operation of equipment in below 0 degrees C temperatures pose considerable logistical and methodological challenges, as do the safety risks of sampling during the ice-covered period. Here, we consolidate information on winter lake sampling and describe effective methods to measure physical, chemical, and biological variables in and under ice. We describe variation in snow and ice conditions and discuss implications for sampling logistics and safety. We outline commonly encountered methodological challenges and make recommendations for best practices to maximize safety and efficiency when sampling through ice or deploying instruments in ice-covered lakes. Application of such practices over a broad range of ice-covered lakes will contribute to a better understanding of the factors that regulate lakes during winter and how winter conditions affect the subsequent ice-free period.
We present two case studies that demonstrate how a common evaluation methodology can be used to assess the reliability of regional climate model simulations from different fields of research. In Case I, we focused on the agricultural yield loss risk for maize in Northeastern Brazil during a drought linked to an El-Nino event. In Case II, the present-day regional climatic conditions in Europe for a 10-year period are simulated. To comprehensively evaluate the model results for both kinds of investigations, we developed a general methodology. On its basis, we elaborated and implemented modules to assess the quality of model results using both advanced visualization techniques and statistical algorithms. Besides univariate approaches for individual near-surface parameters, we used multivariate statistics to investigate multiple near-surface parameters of interest together. For the latter case, we defined generalized quality measures to quantify the model's accuracy. Furthermore, we elaborated a diagnosis tool applicable for atmospheric variables to assess the model's accuracy in representing the physical processes above the surface under various aspects. By means of this evaluation approach, it could be demonstrated in Case Study I that the accuracy of the applied regional climate model resides at the same level as that we found for another regional model and a global model. Excessive precipitation during the rainy season in coastal regions could be identified as a major contribution leading to this result. In Case Study II, we also identified the accuracy of the investigated mean characteristics for near- surface temperature and precipitation to be comparable to another regional model. In this case, an artificial modulation of the used initial and boundary data during preprocessing could be identified as the major source of error in the simulation. Altogether, the achieved results for the presented investigations indicate the potential of our methodology to be applied as a common test bed to different fields of research in regional climate modeling
Childhood adversity plays an important role for development of major depressive disorder (MDD). There are differences in subcortical brain structures between patients with MDD and healthy controls, but the specific impact of childhood adversity on such structures in MDD remains unclear. Thus, aim of the present study was to investigate whether childhood adversity is associated with subcortical volumes and how it interacts with a diagnosis of MDD and sex. Within the ENIGMA-MDD network, nine university partner sites, which assessed childhood adversity and magnetic resonance imaging in patients with MDD and controls, took part in the current joint mega-analysis. In this largest effort world-wide to identify subcortical brain structure differences related to childhood adversity, 3036 participants were analyzed for subcortical brain volumes using FreeSurfer. A significant interaction was evident between childhood adversity, MDD diagnosis, sex, and region. Increased exposure to childhood adversity was associated with smaller caudate volumes in females independent of MDD. All subcategories of childhood adversity were negatively associated with caudate volumes in females - in particular emotional neglect and physical neglect (independently from age, ICV, imaging site and MDD diagnosis). There was no interaction effect between childhood adversity and MDD diagnosis on subcortical brain volumes. Childhood adversity is one of the contributors to brain structural abnormalities. It is associated with subcortical brain abnormalities that are relevant to psychiatric disorders such as depression. (C) 2016 Published by Elsevier Ltd.
Bone pathology is frequent in stressed individuals. A comprehensive examination of mechanisms linking life stress, depression and disturbed bone homeostasis is missing. In this translational study, mice exposed to early life stress (MSUS) were examined for bone microarchitecture (μCT), metabolism (qPCR/ELISA), and neuronal stress mediator expression (qPCR) and compared with a sample of depressive patients with or without early life stress by analyzing bone mineral density (BMD) (DXA) and metabolic changes in serum (osteocalcin, PINP, CTX-I). MSUS mice showed a significant decrease in NGF, NPYR1, VIPR1 and TACR1 expression, higher innervation density in bone, and increased serum levels of CTX-I, suggesting a milieu in favor of catabolic bone turnover. MSUS mice had a significantly lower body weight compared to control mice, and this caused minor effects on bone microarchitecture. Depressive patients with experiences of childhood neglect also showed a catabolic pattern. A significant reduction in BMD was observed in depressive patients with childhood abuse and stressful life events during childhood. Therefore, future studies on prevention and treatment strategies for both mental and bone disease should consider early life stress as a risk factor for bone pathologies.
Bone pathology is frequent in stressed individuals. A comprehensive examination of mechanisms linking life stress, depression and disturbed bone homeostasis is missing. In this translational study, mice exposed to early life stress (MSUS) were examined for bone microarchitecture (μCT), metabolism (qPCR/ELISA), and neuronal stress mediator expression (qPCR) and compared with a sample of depressive patients with or without early life stress by analyzing bone mineral density (BMD) (DXA) and metabolic changes in serum (osteocalcin, PINP, CTX-I). MSUS mice showed a significant decrease in NGF, NPYR1, VIPR1 and TACR1 expression, higher innervation density in bone, and increased serum levels of CTX-I, suggesting a milieu in favor of catabolic bone turnover. MSUS mice had a significantly lower body weight compared to control mice, and this caused minor effects on bone microarchitecture. Depressive patients with experiences of childhood neglect also showed a catabolic pattern. A significant reduction in BMD was observed in depressive patients with childhood abuse and stressful life events during childhood. Therefore, future studies on prevention and treatment strategies for both mental and bone disease should consider early life stress as a risk factor for bone pathologies.
Background
The metabolic syndrome (MetS) is a risk cluster for a number of secondary diseases. The implementation of prevention programs requires early detection of individuals at risk. However, access to health care providers is limited in structurally weak regions. Brandenburg, a rural federal state in Germany, has an especially high MetS prevalence and disease burden. This study aims to validate and test the feasibility of a setup for mobile diagnostics of MetS and its secondary diseases, to evaluate the MetS prevalence and its association with moderating factors in Brandenburg and to identify new ways of early prevention, while establishing a “Mobile Brandenburg Cohort” to reveal new causes and risk factors for MetS.
Methods
In a pilot study, setups for mobile diagnostics of MetS and secondary diseases will be developed and validated. A van will be equipped as an examination room using point-of-care blood analyzers and by mobilizing standard methods. In study part A, these mobile diagnostic units will be placed at different locations in Brandenburg to locally recruit 5000 participants aged 40-70 years. They will be examined for MetS and advice on nutrition and physical activity will be provided. Questionnaires will be used to evaluate sociodemographics, stress perception, and physical activity. In study part B, participants with MetS, but without known secondary diseases, will receive a detailed mobile medical examination, including MetS diagnostics, medical history, clinical examinations, and instrumental diagnostics for internal, cardiovascular, musculoskeletal, and cognitive disorders. Participants will receive advice on nutrition and an exercise program will be demonstrated on site. People unable to participate in these mobile examinations will be interviewed by telephone. If necessary, participants will be referred to general practitioners for further diagnosis.
Discussion
The mobile diagnostics approach enables early detection of individuals at risk, and their targeted referral to local health care providers. Evaluation of the MetS prevalence, its relation to risk-increasing factors, and the “Mobile Brandenburg Cohort” create a unique database for further longitudinal studies on the implementation of home-based prevention programs to reduce mortality, especially in rural regions.
Trial registration
German Clinical Trials Register, DRKS00022764; registered 07 October 2020—retrospectively registered.
The valorization of coffee wastes through modification to activated carbon has been considered as a low-cost adsorbent with prospective to compete with commercial carbons. So far, very few studies have referred to the valorization of coffee parchment into activated carbon. Moreover, low-cost and efficient activation methods need to be more investigated. The aim of this work was to prepare activated carbon from spent coffee grounds and parchment, and to assess their adsorption performance. The co-calcination processing with calcium carbonate was used to prepare the activated carbons, and their adsorption capacity for organic acids, phenolic compounds and proteins was evaluated. Both spent coffee grounds and parchment showed yields after the calcination and washing treatments of around 9.0%. The adsorption of lactic acid was found to be optimal at pH 2. The maximum adsorption capacity of lactic acid with standard commercial granular activated carbon was 73.78 mg/g, while the values of 32.33 and 14.73 mg/g were registered for the parchment and spent coffee grounds activated carbons, respectively. The Langmuir isotherm showed that lactic acid was adsorbed as a monolayer and distributed homogeneously on the surface. Around 50% of total phenols and protein content from coffee wastewater were adsorbed after treatment with the prepared activated carbons, while 44, 43, and up to 84% of hydrophobic compounds were removed using parchment, spent coffee grounds and commercial activated carbon, respectively; the adsorption efficiencies of hydrophilic compounds ranged between 13 and 48%. Finally, these results illustrate the potential valorization of coffee by-products parchment and spent coffee grounds into activated carbon and their use as low-cost adsorbent for the removal of organic compounds from aqueous solutions.
The valorization of coffee wastes through modification to activated carbon has been considered as a low-cost adsorbent with prospective to compete with commercial carbons. So far, very few studies have referred to the valorization of coffee parchment into activated carbon. Moreover, low-cost and efficient activation methods need to be more investigated. The aim of this work was to prepare activated carbon from spent coffee grounds and parchment, and to assess their adsorption performance. The co-calcination processing with calcium carbonate was used to prepare the activated carbons, and their adsorption capacity for organic acids, phenolic compounds and proteins was evaluated. Both spent coffee grounds and parchment showed yields after the calcination and washing treatments of around 9.0%. The adsorption of lactic acid was found to be optimal at pH 2. The maximum adsorption capacity of lactic acid with standard commercial granular activated carbon was 73.78 mg/g, while the values of 32.33 and 14.73 mg/g were registered for the parchment and spent coffee grounds activated carbons, respectively. The Langmuir isotherm showed that lactic acid was adsorbed as a monolayer and distributed homogeneously on the surface. Around 50% of total phenols and protein content from coffee wastewater were adsorbed after treatment with the prepared activated carbons, while 44, 43, and up to 84% of hydrophobic compounds were removed using parchment, spent coffee grounds and commercial activated carbon, respectively; the adsorption efficiencies of hydrophilic compounds ranged between 13 and 48%. Finally, these results illustrate the potential valorization of coffee by-products parchment and spent coffee grounds into activated carbon and their use as low-cost adsorbent for the removal of organic compounds from aqueous solutions.