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Physical activity trajectories among persons of Turkish descent living in Germany — a cohort study
(2020)
Physical activity (PA) behavior is increasingly described as trajectories taking changes over a longer period into account. Little is known, however, about predictors of those trajectories among migrant populations. Therefore, the aim of the present cohort study was to describe changes of PA over six years and to explore migration-related and other predictors for different PA trajectories in adults of Turkish descent living in Berlin. At baseline (2011/2012) and after six years, sociodemographics, health behavior, and medical information were assessed. Four PA trajectories were defined using data of weekly PA from baseline and follow-up: “inactive”, “decreasing”, “increasing”, and “stable active”. Multivariable regression analyses were performed in order to determine predictors for the “stable active” trajectory, and results were presented as adjusted odds ratios (aOR) with 95% confidence intervals (95%CI). In this analysis, 197 people (60.9% women, mean age ± standard deviation 49.9 ± 12.8 years) were included. A total of 77.7% were first-generation migrants, and 50.5% had Turkish citizenship. The four PA trajectories differed regarding citizenship, preferred questionnaire language, and marital status. “Stable active” trajectory membership was predicted by educational level (high vs. low: aOR 4.20, 95%CI [1.10; 16.00]), citizenship (German or dual vs. Turkish only: 3.60 [1.20; 10.86]), preferred questionnaire language (German vs. Turkish: 3.35 [1.05; 10.66]), and BMI (overweight vs. normal weight: 0.28 [0.08; 0.99]). In our study, migration-related factors only partially predicted trajectory membership, however, persons with citizenship of their country of origin and/or with poor language skills should be particularly considered when planning PA prevention programs.
The main goal of the present study was the identification of cellular phenotypes in attention-deficit-/hyperactivity disorder (ADHD) patient-derived cellular models from carriers of rare copy number variants (CNVs) in the PARK2 locus that have been previously associated with ADHD. Human-derived fibroblasts (HDF) were cultured and human-induced pluripotent stem cells (hiPSC) were reprogrammed and differentiated into dopaminergic neuronal cells (mDANs). A series of assays in baseline condition and in different stress paradigms (nutrient deprivation, carbonyl cyanide m-chlorophenyl hydrazine (CCCP)) focusing on mitochondrial function and energy metabolism (ATP production, basal oxygen consumption rates, reactive oxygen species (ROS) abundance) were performed and changes in mitochondrial network morphology evaluated. We found changes in PARK2 CNV deletion and duplication carriers with ADHD in PARK2 gene and protein expression, ATP production and basal oxygen consumption rates compared to healthy and ADHD wildtype control cell lines, partly differing between HDF and mDANs and to some extent enhanced in stress paradigms. The generation of ROS was not influenced by the genotype. Our preliminary work suggests an energy impairment in HDF and mDAN cells of PARK2 CNV deletion and duplication carriers with ADHD. The energy impairment could be associated with the role of PARK2 dysregulation in mitochondrial dynamics.
Polyploid genomes present a challenge for cytogenetic and genomic studies, due to the high number of similar size chromosomes and the simultaneous presence of hardly distinguishable paralogous elements. The karyotype of the Siberian sturgeon (Acipenser baerii) contains around 250 chromosomes and is remarkable for the presence of paralogs from two rounds of whole-genome duplications (WGD). In this study, we applied the sterlet-derived acipenserid satDNA-based whole chromosome-specific probes to analyze the Siberian sturgeon karyotype. We demonstrate that the last genome duplication event in the Siberian sturgeon was accompanied by the simultaneous expansion of several repetitive DNA families. Some of the repetitive probes serve as good cytogenetic markers distinguishing paralogous chromosomes and detecting ancestral syntenic regions, which underwent fusions and fissions. The tendency of minisatellite specificity for chromosome size groups previously observed in the sterlet genome is also visible in the Siberian sturgeon. We provide an initial physical chromosome map of the Siberian sturgeon genome supported by molecular markers. The application of these data will facilitate genomic studies in other recent polyploid sturgeon species.
Water crises are becoming severe in recent times, further fueled by population increase and climate change. They result in complex and unsustainable water management. Spatial estimation of consumptive water use is vital for performance assessment of the irrigation system using Remote Sensing (RS). For this study, its estimation is done using the Soil Energy Balance Algorithm for Land (SEBAL) approach. Performance indicators including equity, adequacy, and reliability were worked out at various spatiotemporal scales. Moreover, optimization and sustainable use of water resources are not possible without knowing the factors mainly influencing consumptive water use of major crops. For that purpose, random forest regression modelling was employed using various sets of factors for site-specific, proximity, and cropping system. The results show that the system is underperforming both for Kharif (i.e., summer) and Rabi (i.e., winter) seasons. Performance indicators highlight poor water distribution in the system, a shortage of water supply, and unreliability. The results are relatively good for Rabi as compared to Kharif, with an overall poor situation for both seasons. Factors importance varies for different crops. Overall, distance from canal, road density, canal density, and farm approachability are the most important factors for explaining consumptive water use. Auditing of consumptive water use shows the potential for resource optimization through on-farm water management by the targeted approach. The results are based on the present situation without considering future changes in canal water supply and consumptive water use under climate change.
Tristriazolotriazines (TTTs) with a threefold alkoxyphenyl substitution were prepared and studied by DSC, polarized optical microscopy (POM) and X-ray scattering. Six pentyloxy chains are sufficient to induce liquid-crystalline behavior in these star-shaped compounds. Thermotropic properties of TTTs with varying substitution patterns and a periphery of linear chains of different lengths, branching in the chain and swallow-tails, are compared. Generally, these disks display broad and stable thermotropic mesophases, with the tangential TTT being superior to the radial isomer. The structure–property relationships of the number of alkyl chains, their position, length and structure were studied.
The plant hormone jasmonoyl-isoleucine (JA-Ile) is an important regulator of plant growth and defense in response to various biotic and abiotic stress cues. Under our experimental conditions, JA-Ile levels increased approximately seven-fold in NaCl-treated Arabidopsis thaliana roots. Although these levels were around 1000-fold lower than in wounded leaves, genes of the JA-Ile signaling pathway were induced by a factor of 100 or more. Induction was severely compromised in plants lacking the JA-Ile receptor CORONATINE INSENSITIVE 1 or enzymes required for JA-Ile biosynthesis. To explain efficient gene expression at very low JA-Ile levels, we hypothesized that salt-induced expression of the JA/JA-Ile transporter JAT1/AtABCG16 would lead to increased nuclear levels of JA-Ile. However, mutant plants with different jat1 alleles were similar to wild-type ones with respect to salt-induced gene expression. The mechanism that allows COI1-dependent gene expression at very low JA-Ile levels remains to be elucidated.
West African savannas are severely threatened with intensified land use and increasing degradation. Bees are important for terrestrial biodiversity as they provide native plant species with pollination services. However, little information is available regarding their mutualistic interactions with woody plant species. In the first network study from sub-Saharan West Africa, we investigated the effects of land-use intensity and climatic seasonality on plant–bee communities and their interaction networks. In total, we recorded 5686 interactions between 53 flowering woody plant species and 100 bee species. Bee-species richness and the number of interactions were higher in the low compared to medium and high land-use intensity sites. Bee- and plant-species richness and the number of interactions were higher in the dry compared to the rainy season. Plant–bee visitation networks were not strongly affected by land-use intensity; however, climatic seasonality had a strong effect on network architecture. Null-model corrected connectance and nestedness were higher in the dry compared to the rainy season. In addition, network specialization and null-model corrected modularity were lower in the dry compared to the rainy season. Our results suggest that in our study region, seasonal effects on mutualistic network architecture are more pronounced compared to land-use change effects. Nonetheless, the decrease in bee-species richness and the number of plant–bee interactions with an increase in land-use intensity highlights the importance of savanna conservation for maintaining bee diversity and the concomitant provision of ecosystem services.
The pathological hallmark of Parkinson's disease (PD) is the loss of neuromelanin-containing dopaminergic neurons within the substantia nigra pars compacta (SNpc). Additionally, numerous studies indicate an altered synaptic function during disease progression. To gain new insights into the molecular processes underlying the alteration of synaptic function in PD, a proteomic study was performed. Therefore, synaptosomes were isolated by density gradient centrifugation from SNpc tissue of individuals at advanced PD stages (N = 5) as well as control subjects free of pathology (N = 5) followed by mass spectrometry-based analysis. In total, 362 proteins were identified and assigned to the synaptosomal core proteome. This core proteome comprised all proteins expressed within the synapses without regard to data analysis software, gender, age, or disease. The differential analysis between control subjects and PD cases revealed that CD9 antigen was overrepresented and fourteen proteins, among them Thymidine kinase 2 (TK2), mitochondrial, 39S ribosomal protein L37, neurolysin, and Methionine-tRNA ligase (MARS2) were underrepresented in PD suggesting an alteration in mitochondrial translation within synaptosomes.
Atherosclerotic lesions are populated by cells of the innate and adaptive immune system, including CD8\(^+\) T cells. The CD8\(^+\) T cell infiltrate has recently been characterized in mouse and human atherosclerosis and revealed activated, cytotoxic, and possibly dysfunctional and exhausted cell phenotypes. In mouse models of atherosclerosis, antibody-mediated depletion of CD8\(^+\) T cells ameliorates atherosclerosis. CD8\(^+\) T cells control monopoiesis and macrophage accumulation in early atherosclerosis. In addition, CD8\(^+\) T cells exert cytotoxic functions in atherosclerotic plaques and contribute to macrophage cell death and necrotic core formation. CD8\(^+\) T cell activation may be antigen-specific, and epitopes of atherosclerosis-relevant antigens may be targets of CD8\(^+\) T cells and their cytotoxic activity. CD8\(^+\) T cell functions are tightly controlled by costimulatory and coinhibitory immune checkpoints. Subsets of regulatory CD25\(^+\)CD8\(^+\) T cells with immunosuppressive functions can inhibit atherosclerosis. Importantly, local cytotoxic CD8\(^+\) T cell responses may trigger endothelial damage and plaque erosion in acute coronary syndromes. Understanding the complex role of CD8\(^+\) T cells in atherosclerosis may pave the way for defining novel treatment approaches in atherosclerosis. In this review article, we discuss these aspects, highlighting the emerging and critical role of CD8\(^+\) T cells in atherosclerosis.
The adoptive transfer of the chimeric antigen receptor (CAR) expressing T-cells has produced unprecedented successful results in the treatment of B-cell malignancies. However, the use of this technology in other malignancies remains less effective. In the setting of solid neoplasms, CAR T-cell metabolic fitness needs to be optimal to reach the tumor and execute their cytolytic function in an environment often hostile. It is now well established that both tumor and T cell metabolisms play critical roles in controlling the immune response by conditioning the tumor microenvironment and the fate and activity of the T cells. In this review, after a brief description of the tumoral and T cell metabolic reprogramming, we summarize the latest advances and new strategies that have been developed to improve the metabolic fitness and efficacy of CAR T-cell products.
Patients affected by gastroenteropancreatic–neuroendocrine tumors (GEP–NETs) have an increased risk of developing osteopenia and osteoporosis, as several factors impact on bone metabolism in these patients. In fact, besides the direct effect of bone metastasis, bone health can be affected by hormone hypersecretion (including serotonin, cortisol, and parathyroid hormone-related protein), specific microRNAs, nutritional status (which in turn could be affected by medical and surgical treatments), and vitamin D deficiency. In patients with multiple endocrine neoplasia type 1 (MEN1), a hereditary syndrome associated with NET occurrence, bone damage may carry other consequences. Osteoporosis may negatively impact on the quality of life of these patients and can increment the cost of medical care since these patients usually live with their disease for a long time. However, recommendations suggesting screening to assess bone health in GEP–NET patients are missing. The aim of this review is to critically analyze evidence on the mechanisms that could have a potential impact on bone health in patients affected by GEP–NET, focusing on vitamin D and its role in GEP–NET, as well as on factors associated with MEN1 that could have an impact on bone homeostasis.
Osmotic adaptation and accumulation of compatible solutes is a key process for life at high osmotic pressure and elevated salt concentrations. Most important solutes that can protect cell structures and metabolic processes at high salt concentrations are glycine betaine and ectoine. The genome analysis of more than 130 phototrophic bacteria shows that biosynthesis of glycine betaine is common among marine and halophilic phototrophic Proteobacteria and their chemotrophic relatives, as well as in representatives of Pirellulaceae and Actinobacteria, but are also found in halophilic Cyanobacteria and Chloroherpeton thalassium. This ability correlates well with the successful toleration of extreme salt concentrations. Freshwater bacteria in general lack the possibilities to synthesize and often also to take up these compounds. The biosynthesis of ectoine is found in the phylogenetic lines of phototrophic Alpha- and Gammaproteobacteria, most prominent in the Halorhodospira species and a number of Rhodobacteraceae. It is also common among Streptomycetes and Bacilli. The phylogeny of glycine-sarcosine methyltransferase (GMT) and diaminobutyrate-pyruvate aminotransferase (EctB) sequences correlate well with otherwise established phylogenetic groups. Most significantly, GMT sequences of cyanobacteria form two major phylogenetic branches and the branch of Halorhodospira species is distinct from all other Ectothiorhodospiraceae. A variety of transport systems for osmolytes are present in the studied bacteria.
(1) Background: We aimed to evaluate the effect of proposed “microbiome-stabilising interventions”, i.e., breastfeeding for ≥3 months and prophylactic use of Lactobacillus acidophilus/ Bifidobacterium infantis probiotics on neurocognitive and behavioral outcomes of very-low-birthweight (VLBW) children aged 5–6 years. (2) Methods: We performed a 5-year-follow-up assessment including a strength and difficulties questionnaire (SDQ) and an intelligence quotient (IQ) assessment using the Wechsler Preschool and Primary Scale of Intelligence (WPPSI)-III test in preterm children previously enrolled in the German Neonatal Network (GNN). The analysis was restricted to children exposed to antenatal corticosteroids and postnatal antibiotics. (3) Results: 2467 primary school-aged children fulfilled the inclusion criteria. In multivariable linear regression models breastfeeding ≥3 months was associated with lower conduct disorders (B (95% confidence intervals (CI)): −0.25 (−0.47 to −0.03)) and inattention/hyperactivity (−0.46 (−0.81 to −0.10)) as measured by SDQ. Probiotic treatment during the neonatal period had no effect on SDQ scores or intelligence. (4) Conclusions: Prolonged breastfeeding of highly vulnerable infants may promote their mental health later in childhood, particularly by reducing risk for inattention/hyperactivity and conduct disorders. Future studies need to disentangle the underlying mechanisms during a critical time frame of development.
Here, we assessed whether 36 single nucleotide polymorphisms (SNPs) within the TNFSF4 and MAPKAPK2 loci influence the risk of developing invasive aspergillosis (IA). We conducted a two-stage case control study including 911 high-risk patients diagnosed with hematological malignancies that were ascertained through the aspBIOmics consortium. The meta-analysis of the discovery and replication populations revealed that carriers of the TNFSF4\(_{rs7526628T/T}\) genotype had a significantly increased risk of developing IA (p = 0.00022). We also found that carriers of the TNFSF4\(_{rs7526628T}\) allele showed decreased serum levels of TNFSF14 protein (p = 0.0027), and that their macrophages had a decreased fungicidal activity (p = 0.048). In addition, we observed that each copy of the MAPKAPK2\(_{rs12137965G}\) allele increased the risk of IA by 60% (p = 0.0017), whereas each copy of the MAPKAPK2\(_{rs17013271T}\) allele was estimated to decrease the risk of developing the disease (p = 0.0029). Mechanistically, we found that carriers of the risk MAPKAPK2\(_{rs12137965G}\) allele showed increased numbers of CD38+IgM-IgD- plasmablasts in blood (p = 0.00086), whereas those harboring two copies of the allele had decreased serum concentrations of thymic stromal lymphopoietin (p = 0.00097). Finally, we also found that carriers of the protective MAPKAPK2\(_{rs17013271T}\) allele had decreased numbers of CD27-IgM-IgD- B cells (p = 0.00087) and significantly lower numbers of CD14+ and CD14+CD16- cells (p = 0.00018 and 0.00023). Altogether, these results suggest a role of the TNFSF4 and MAPKAPK2 genes in determining IA risk.
Candida lusitaniae is a rare cause of candidemia that is known for its unique capability to rapidly acquire resistance to amphotericin B. We report the case of an adolescent with grade IV graft-vs.-host disease after hematopoietic cell transplantation who developed catheter-associated C. lusitaniae candidemia while on therapeutic doses of liposomal amphotericin B. We review the epidemiology of C. lusitaniae bloodstream infections in adult and pediatric patients, the development of resistance, and its role in breakthrough candidemia. Appropriate species identification, in vitro susceptibility testing, and source control are pivotal to optimal management of C. lusitaniae candidemia. Initial antifungal therapy may consist of an echinocandin and be guided by in vitro susceptibility and clinical response.
A new and easy polymerase chain reaction (PCR) multiplex strategy, for the identification of the most common fungal species involved in invasive fungal infections (IFI) was developed in this work. Two panels with species-specific markers were designed, the Candida Panel for the identification of Candida species, and the Filamentous Fungi Panel for the identification of Aspergillus species and Rhizopusarrhizus. The method allowed the correct identification of all targeted pathogens using extracted DNA or by colony PCR, showed no cross-reactivity with nontargeted species and allowed identification of different species in mixed infections. Sensitivity reached 10 to 1 pg of DNA and was suitable for clinical samples from sterile sites, with a sensitivity of 89% and specificity of 100%. Overall, the study showed that the new method is suitable for the identification of the ten most important fungal species involved in IFI, not only from positive blood cultures but also from clinical samples from sterile sites. The method provides a unique characteristic, of seeing the peak in the specific region of the panel with the correct fluorescence dye, that aids the ruling out of unspecific amplifications. Furthermore, the panels can be further customized, selecting markers for different species and/or resistance genes.
The early diagnosis of invasive aspergillosis (IA) relies mainly on computed tomography imaging and testing for fungal biomarkers such as galactomannan (GM). We compared an established ELISA for the detection of GM with a turbidimetric assay for detection of the panfungal biomarker β-D-glucan (BDG) for early diagnosis of IA. A total of 226 serum specimens from 47 proven and seven probable IA cases were analysed. Sensitivity was calculated for samples obtained closest to the day of IA-diagnosis (d0). Additional analyses were performed by including samples obtained during the presumed course of disease. Most IA cases involved the respiratory system (63%), and Aspergillus fumigatus was the most frequently isolated species (59%). For proven cases, sensitivity of BDG/GM analysis was 57%/40%. Including all samples dating from –6 to +1 weeks from d0 increased sensitivities to 74%/51%. Sensitivity of BDG testing was as high as or higher than GM testing for all subgroups and time intervals analysed. BDG testing was less specific (90–93%) than GM testing (99–100%). Combining BDG and GM testing resulted in sensitivity/specificity of 70%/91%. Often, BDG testing was positive before GM testing. Our study backs the use of BDG for diagnosis of suspected IA. We suggest combining BDG and GM to improve the overall sensitivity.
The neoclassical mainstream theory of economic growth does not care about the First and the Second Law of Thermodynamics. It usually considers only capital and labor as the factors that produce the wealth of modern industrial economies. If energy is taken into account as a factor of production, its economic weight, that is its output elasticity, is assigned a meager magnitude of roughly 5 percent, according to the neoclassical cost-share theorem. Because of that, neoclassical economics has the problems of the “Solow Residual”, which is the big difference between observed and computed economic growth, and of the failure to explain the economic recessions since World War 2 by the variations of the production factors. Having recalled these problems, we point out that technological constraints on factor combinations have been overlooked in the derivation of the cost-share theorem. Biophysical analyses of economic growth that disregard this theorem and mend the neoclassical deficiencies are sketched. They show that energy’s output elasticity is much larger than its cost share and elucidate the existence of bidirectional causality between energy conversion and economic growth. This helps to understand how economic crises have been triggered and overcome by supply-side and demand-side actions. Human creativity changes the state of economic systems. We discuss the challenges to it by the risks from politics and markets in conjunction with energy sources and technologies, and by the constraints that the emissions of particles and heat from entropy production impose on industrial growth in the biosphere.
Traps baited with attractive lures are increasingly used at entry-points and surrounding natural areas to intercept exotic wood-boring beetles accidentally introduced via international trade. Several trapping variables can affect the efficacy of this activity, including trap color. In this study, we tested whether species richness and abundance of jewel beetles (Buprestidae), bark and ambrosia beetles (Scolytinae), and their common predators (i.e., checkered beetles, Cleridae) can be modified using trap colors different to those currently used for surveillance of jewel beetles and bark and ambrosia beetles (i.e., green or black). We show that green and black traps are generally efficient, but also that many flower-visiting or dark-metallic colored jewel beetles and certain bark beetles are more attracted by other colors. In addition, we show that checkered beetles have color preferences similar to those of their Scolytinae preys, which limits using trap color to minimize their inadvertent removal. Overall, this study confirmed that understanding the color perception mechanisms in wood-boring beetles can lead to important improvements in trapping techniques and thereby increase the efficacy of surveillance programs.
1. Honeybees, which are among the most important pollinators globally, do not only collect pollen and nectar during foraging but may also disperse diverse microbes. Some of these can be deleterious to agricultural crops and forest trees, such as the bacterium Pantoea ananatis, an emerging pathogen in some systems. P. ananatis infections can lead to leaf blotches, die-back, bulb rot, and fruit rot. 2. We isolated P. ananatis bacteria from flowers with the aim of determining whether honeybees can sense these bacteria and if the bacteria affect behavioral responses of the bees to sugar solutions. 3. Honeybees decreased their responsiveness to different sugar solutions when these contained high concentrations of P. ananatis but were not deterred by solutions from which bacteria had been removed. This suggests that their reduced responsiveness was due to the taste of bacteria and not to the depletion of sugar in the solution or bacteria metabolites. Intriguingly, the bees appeared not to taste ecologically relevant low concentrations of bacteria. 4. Synthesis and applications. Our data suggest that honeybees may introduce P.ananatis bacteria into nectar in field-realistic densities during foraging trips and may thus affect nectar quality and plant fitness.
Trait variation in moths mirrors small-scaled ecological gradients in a tropical forest landscape
(2020)
Along environmental gradients, communities are expected to be filtered from the regional species pool by physical constraints, resource availability, and biotic interactions. This should be reflected in species trait composition. Using data on species-rich moth assemblages sampled by light traps in a lowland rainforest landscape in Costa Rica, we show that moths in two unrelated clades (Erebidae-Arctiinae; Geometridae) are much smaller-sized in oil palm plantations than in nearby old-growth forest, with intermediate values at disturbed forest sites. In old-growth forest, Arctiinae predominantly show aposematic coloration as a means of anti-predator defense, whereas this trait is much reduced in the prevalence in plantations. Similarly, participation in Müllerian mimicry rings with Hymenoptera and Lycidae beetles, respectively, is rare in plantations. Across three topographic types of old-growth forests, community-weighted means of moth traits showed little variation, but in creek forest, both types of mimicry were surprisingly rare. Our results emphasize that despite their mobility, moth assemblages are strongly shaped by local environmental conditions through the interplay of bottom–up and top–down processes. Assemblages in oil palm plantations are highly degraded not only in their biodiversity, but also in terms of trait expression.
Stroma-infiltrating immune cells, such as tumor-associated macrophages (TAM), play an important role in regulating tumor progression and chemoresistance. These effects are mostly conveyed by secreted mediators, among them several cathepsin proteases. In addition, increasing evidence suggests that stroma-infiltrating immune cells are able to induce profound metabolic changes within the tumor microenvironment. In this study, we aimed to characterize the impact of cathepsins in maintaining the TAM phenotype in more detail. For this purpose, we investigated the molecular effects of pharmacological cathepsin inhibition on the viability and polarization of human primary macrophages as well as its metabolic consequences. Pharmacological inhibition of cathepsins B, L, and S using a novel inhibitor, GB111-NH\(_2\), led to changes in cellular recycling processes characterized by an increased expression of autophagy- and lysosome-associated marker genes and reduced adenosine triphosphate (ATP) content. Decreased cathepsin activity in primary macrophages further led to distinct changes in fatty acid metabolites associated with increased expression of key modulators of fatty acid metabolism, such as fatty acid synthase (FASN) and acid ceramidase (ASAH1). The altered fatty acid profile was associated with an increased synthesis of the pro-inflammatory prostaglandin PGE\(_2\), which correlated with the upregulation of numerous NF\(_k\)B-dependent pro-inflammatory mediators, including interleukin-1 (IL-1), interleukin-6 (IL-6), C-C motif chemokine ligand 2 (CCL2), and tumor necrosis factor-alpha (TNFα). Our data indicate a novel link between cathepsin activity and metabolic reprogramming in macrophages, demonstrated by a profound impact on autophagy and fatty acid metabolism, which facilitates a pro-inflammatory micromilieu generally associated with enhanced tumor elimination. These results provide a strong rationale for therapeutic cathepsin inhibition to overcome the tumor-promoting effects of the immune-evasive tumor micromilieu.
Cardiac surgery (CSX) can be lifesaving in elderly patients (age ≥ 80 years) but may still be associated with complications and functional decline. Frailty represents a determinant to outcomes in critically ill patients, but little is known about its influence on elderly CSX-patients. This is a secondary exploratory analysis of a multi-center, prospective observational cohort study of 610 elderly patients admitted to the ICU and followed for one year to document long-term outcomes. CSX-ICU-patients (n = 49) were compared to surgical ICU patients (n = 184) with regard to demographics, frailty, and outcomes. Of all surgical patients, 102 (43%) were considered vulnerable or frail. The subdistribution hazard ratio (SHR) of time to discharge home (TTDH) for vulnerable/frail vs. fit/well patients was 0.54 (95% confidence interval (CI), 0.34, 0.86, p = 0.007). The p-value for effect modification between surgery group (CSX vs. surgical ICU patients) and Clinical Frailty Scale (CFS) group was not significant (p = 0.37) suggesting that the observed difference in the CFS effect between the CSX and surgical ICU patients is consistent with random error. A further subgroup analysis shows that among surgical ICU patients, the SHR of time to discharge home (TTDH) for vulnerable/frail vs. fit/well patients was 0.49 (95% CI, 0.29, 0.83) while the corresponding SHR for CSX patients was 0.77 (0.32–1.88). In conclusion, preoperative frailty reduced the rate of discharge to home in both surgical and CSX patients, but a larger sample of CSX patients is needed to adequately address this question in this patient group.
Laparoscopic techniques have established themselves as a major part of modern surgery. Their implementation in every surgical discipline has played a vital part in the reduction of perioperative morbidity and mortality. Precise robotic surgery, as an evolution of this, is shaping the present and future operating theatre that an anesthetist is facing. While incisions get smaller and the impact on the organism seems to dwindle, challenges for anesthetists do not lessen and could even become more demanding than in open procedures. This review focuses on the pathophysiological effects of contemporary laparoscopic and robotic procedures and summarizes anesthetic challenges and strategies for perioperative management.
Background: Macrophage Migration Inhibitory Factor (MIF) is highly elevated after cardiac surgery and impacts the postoperative inflammation. The aim of this study was to analyze whether the polymorphisms CATT\(_{5–7}\) (rs5844572/rs3063368,“-794”) and G>C single-nucleotide polymorphism (rs755622,-173) in the MIF gene promoter are related to postoperative outcome. Methods: In 1116 patients undergoing cardiac surgery, the MIF gene polymorphisms were analyzed and serum MIF was measured by ELISA in 100 patients. Results: Patients with at least one extended repeat allele (CATT\(_7\)) had a significantly higher risk of acute kidney injury (AKI) compared to others (23% vs. 13%; OR 2.01 (1.40–2.88), p = 0.0001). Carriers of CATT\(_7\) were also at higher risk of death (1.8% vs. 0.4%; OR 5.12 (0.99–33.14), p = 0.026). The GC genotype was associated with AKI (20% vs. GG/CC:13%, OR 1.71 (1.20–2.43), p = 0.003). Multivariate analyses identified CATT\(_7\) predictive for AKI (OR 2.13 (1.46–3.09), p < 0.001) and death (OR 5.58 (1.29–24.04), p = 0.021). CATT\(_7\) was associated with higher serum MIF before surgery (79.2 vs. 50.4 ng/mL, p = 0.008). Conclusion: The CATT\(_7\) allele associates with a higher risk of AKI and death after cardiac surgery, which might be related to chronically elevated serum MIF. Polymorphisms in the MIF gene may constitute a predisposition for postoperative complications and the assessment may improve risk stratification and therapeutic guidance.
In the last decade there has been tremendous effort in offering better therapeutic management strategies to patients with hematologic malignancies. These efforts have ranged from biological to clinical approaches and resulted in the rapid development of new approaches. The main “problem” that comes with the high influx of newly approved drugs, which not only influences hematologists that frequently work with these drugs but also affects other healthcare professionals that work with hematologists in patient management, including intensive care unit (ICU) physicians, is they have to keep up within their specialty and, in addition, with the side-effects that can occur when encountering hematology-specific therapies. Nonetheless, there are few people that have an in-depth understanding of a specialty outside theirs. Thus, this manuscript offers an overview of the most common side-effects caused by therapies used in hematology nowadays, or that are currently being investigated in clinical trials, with the purpose to serve as an aid to other specialties. Nevertheless, because of the high amount of information on this subject, each chapter will offer an overview of the side-effects of a drug class with each reference of the section being intended as further reading.
For machine manufacturing companies, besides the production of high quality and reliable machines, requirements have emerged to maintain machine-related aspects through digital services. The development of such services in the field of the Industrial Internet of Things (IIoT) is dealing with solutions such as effective condition monitoring and predictive maintenance. However, appropriate data sources are needed on which digital services can be technically based. As many powerful and cheap sensors have been introduced over the last years, their integration into complex machines is promising for developing digital services for various scenarios. It is apparent that for components handling recorded data of these sensors they must usually deal with large amounts of data. In particular, the labeling of raw sensor data must be furthered by a technical solution. To deal with these data handling challenges in a generic way, a sensor processing pipeline (SPP) was developed, which provides effective methods to capture, process, store, and visualize raw sensor data based on a processing chain. Based on the example of a machine manufacturing company, the SPP approach is presented in this work. For the company involved, the approach has revealed promising results.
The quest for a food secure and safe world has led to continuous effort toward improvements of global food and health systems. While the developed countries seem to have these systems stabilized, some parts of the world still face enormous challenges. Yam (Dioscorea species) is an orphan crop, widely distributed globally; and has contributed enormously to food security especially in sub-Saharan Africa because of its role in providing nutritional benefits and income. Additionally, yam has non-nutritional components called bioactive compounds, which offer numerous health benefits ranging from prevention to treatment of degenerative diseases. Pharmaceutical application of diosgenin and dioscorin, among other compounds isolated from yam, has shown more prospects recently. Despite the benefits embedded in yam, reports on the nutritional and therapeutic potentials of yam have been fragmented and the diversity within the genus has led to much confusion. An overview of the nutritional and health importance of yam will harness the crop to meet its potential towards combating hunger and malnutrition, while improving global health. This review makes a conscious attempt to provide an overview regarding the nutritional, bioactive compositions and therapeutic potentials of yam diversity. Insights on how to increase its utilization for a greater impact are elucidated.
Background: Infections are a leading cause of refugee morbidity. Recent data on the rate of airway infections and factors influencing their spread in refugee reception centers is scarce. Methods: A retrospective, cross-sectional study of de-identified medical records with a focus on respiratory infections in underage refugees was conducted at two large German refugee reception centers. Results: In total, medical data from n = 10,431 refugees over an observational period of n = 819 days was analyzed. Among pediatric patients (n = 4289), 55.3% presented at least once to the on-site medical ward with an acute respiratory infection or signs thereof. In 38.4% of pediatric consultations, acute airway infections or signs thereof were present. Airway infections spiked during colder months and were significantly more prevalent amongst preschool and resettled children. Their frequency displayed a positive correlation with the number of refugees housed at the reception centers. Conclusions: We show that respiratory infections are a leading cause for morbidity in young refugees and that their rate is influenced age, season, status, and residential density. This illustrates the need to protect refugee children from contracting airway infections which may also reduce the spread of coronavirus disease 2019 (COVID-19) during the current pandemic.
Plant transpiration is a key element in the hydrological cycle. Widely used methods for its assessment comprise sap flux techniques for whole-plant transpiration and porometry for leaf stomatal conductance. Recently emerging approaches based on surface temperatures and a wide range of machine learning techniques offer new possibilities to quantify transpiration. The focus of this study was to predict sap flux and leaf stomatal conductance based on drone-recorded and meteorological data and compare these predictions with in-situ measured transpiration. To build the prediction models, we applied classical statistical approaches and machine learning algorithms. The field work was conducted in an oil palm agroforest in lowland Sumatra. Random forest predictions yielded the highest congruence with measured sap flux (r\(^2\) = 0.87 for trees and r\(^2\) = 0.58 for palms) and confidence intervals for intercept and slope of a Passing-Bablok regression suggest interchangeability of the methods. Differences in model performance are indicated when predicting different tree species. Predictions for stomatal conductance were less congruent for all prediction methods, likely due to spatial and temporal offsets of the measurements. Overall, the applied drone and modelling scheme predicts whole-plant transpiration with high accuracy. We conclude that there is large potential in machine learning approaches for ecological applications such as predicting transpiration.
The monitoring of land cover and land use change is critical for assessing the provision of ecosystem services. One of the sources for long-term land cover change quantification is through the classification of historical and/or current maps. Little research has been done on historical maps using Object-Based Image Analysis (OBIA). This study applied an object-based classification using eCognition tool for analyzing the land cover based on historical maps in the Main river catchment, Upper Franconia, Germany. This allowed land use change analysis between the 1850s and 2015, a time span which covers the phase of industrialization of landscapes in central Europe. The results show a strong increase in urban area by 2600%, a severe loss of cropland (−24%), a moderate reduction in meadows (−4%), and a small gain in forests (+4%). The method proved useful for the application on historical maps due to the ability of the software to create semantic objects. The confusion matrix shows an overall accuracy of 82% for the automatic classification compared to manual reclassification considering all 17 sample tiles. The minimum overall accuracy was 65% for historical maps of poor quality and the maximum was 91% for very high-quality ones. Although accuracy is between high and moderate, coarse land cover patterns in the past and trends in land cover change can be analyzed. We conclude that such long-term analysis of land cover is a prerequisite for quantifying long-term changes in ecosystem services.
Forests in Germany cover around 11.4 million hectares and, thus, a share of 32% of Germany's surface area. Therefore, forests shape the character of the country's cultural landscape. Germany's forests fulfil a variety of functions for nature and society, and also play an important role in the context of climate levelling. Climate change, manifested via rising temperatures and current weather extremes, has a negative impact on the health and development of forests. Within the last five years, severe storms, extreme drought, and heat waves, and the subsequent mass reproduction of bark beetles have all seriously affected Germany’s forests. Facing the current dramatic extent of forest damage and the emerging long-term consequences, the effort to preserve forests in Germany, along with their diversity and productivity, is an indispensable task for the government. Several German ministries have and plan to initiate measures supporting forest health. Quantitative data is one means for sound decision-making to ensure the monitoring of the forest and to improve the monitoring of forest damage. In addition to existing forest monitoring systems, such as the federal forest inventory, the national crown condition survey, and the national forest soil inventory, systematic surveys of forest condition and vulnerability at the national scale can be expanded with the help of a satellite-based earth observation. In this review, we analysed and categorized all research studies published in the last 20 years that focus on the remote sensing of forests in Germany. For this study, 166 citation indexed research publications have been thoroughly analysed with respect to publication frequency, location of studies undertaken, spatial and temporal scale, coverage of the studies, satellite sensors employed, thematic foci of the studies, and overall outcomes, allowing us to identify major research and geoinformation product gaps.
Forecasting spatio-temporal dynamics on the land surface using Earth Observation data — a review
(2020)
Reliable forecasts on the impacts of global change on the land surface are vital to inform the actions of policy and decision makers to mitigate consequences and secure livelihoods. Geospatial Earth Observation (EO) data from remote sensing satellites has been collected continuously for 40 years and has the potential to facilitate the spatio-temporal forecasting of land surface dynamics. In this review we compiled 143 papers on EO-based forecasting of all aspects of the land surface published in 16 high-ranking remote sensing journals within the past decade. We analyzed the literature regarding research focus, the spatial scope of the study, the forecasting method applied, as well as the temporal and technical properties of the input data. We categorized the identified forecasting methods according to their temporal forecasting mechanism and the type of input data. Time-lagged regressions which are predominantly used for crop yield forecasting and approaches based on Markov Chains for future land use and land cover simulation are the most established methods. The use of external climate projections allows the forecasting of numerical land surface parameters up to one hundred years into the future, while auto-regressive time series modeling can account for intra-annual variances. Machine learning methods have been increasingly used in all categories and multivariate modeling that integrates multiple data sources appears to be more popular than univariate auto-regressive modeling despite the availability of continuously expanding time series data. Regardless of the method, reliable EO-based forecasting requires high-level remote sensing data products and the resulting computational demand appears to be the main reason that most forecasts are conducted only on a local scale. In the upcoming years, however, we expect this to change with further advances in the field of machine learning, the publication of new global datasets, and the further establishment of cloud computing for data processing.
Global Navigation Satellite System (GNSS) provides accurate positioning data for vehicular navigation in open outdoor environment. In an indoor environment, Light Detection and Ranging (LIDAR) Simultaneous Localization and Mapping (SLAM) establishes a two-dimensional map and provides positioning data. However, LIDAR can only provide relative positioning data and it cannot directly provide the latitude and longitude of the current position. As a consequence, GNSS/Inertial Navigation System (INS) integrated navigation could be employed in outdoors, while the indoors part makes use of INS/LIDAR integrated navigation and the corresponding switching navigation will make the indoor and outdoor positioning consistent. In addition, when the vehicle enters the garage, the GNSS signal will be blurred for a while and then disappeared. Ambiguous GNSS satellite signals will lead to the continuous distortion or overall drift of the positioning trajectory in the indoor condition. Therefore, an INS/LIDAR seamless integrated navigation algorithm and a switching algorithm based on vehicle navigation system are designed. According to the experimental data, the positioning accuracy of the INS/LIDAR navigation algorithm in the simulated environmental experiment is 50% higher than that of the Dead Reckoning (DR) algorithm. Besides, the switching algorithm developed based on the INS/LIDAR integrated navigation algorithm can achieve 80% success rate in navigation mode switching.
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by investigating aggregated classes. The increase in data with a very high spatial resolution enables investigations on a fine-grained feature level which can help us to better understand the dynamics of land surfaces by taking object dynamics into account. To extract fine-grained features and objects, the most popular deep-learning model for image analysis is commonly used: the convolutional neural network (CNN). In this review, we provide a comprehensive overview of the impact of deep learning on EO applications by reviewing 429 studies on image segmentation and object detection with CNNs. We extensively examine the spatial distribution of study sites, employed sensors, used datasets and CNN architectures, and give a thorough overview of applications in EO which used CNNs. Our main finding is that CNNs are in an advanced transition phase from computer vision to EO. Upon this, we argue that in the near future, investigations which analyze object dynamics with CNNs will have a significant impact on EO research. With a focus on EO applications in this Part II, we complete the methodological review provided in Part I.
The effect of non-personalised tips on the continued use of self-monitoring mHealth applications
(2020)
Chronic tinnitus, the perception of a phantom sound in the absence of corresponding stimulus, is a condition known to affect patients' quality of life. Recent advances in mHealth have enabled patients to maintain a ‘disease journal’ of ecologically-valid momentary assessments, improving patients' own awareness of their disease while also providing clinicians valuable data for research. In this study, we investigate the effect of non-personalised tips on patients' perception of tinnitus, and on their continued use of the application. The data collected from the study involved three groups of patients that used the app for 16 weeks. Groups A & Y were exposed to feedback from the start of the study, while group B only received tips for the second half of the study. Groups A and Y were run by different supervisors and also differed in the number of hospital visits during the study. Users of Group A and B underwent assessment at baseline, mid-study, post-study and follow-up, while users of group Y were only assessed at baseline and post-study. It is seen that the users in group B use the app for longer, and also more often during the day. The answers of the users to the Ecological Momentary Assessments are seen to form clusters where the degree to which the tinnitus distress depends on tinnitus loudness varies. Additionally, cluster-level models were able to predict new unseen data with better accuracy than a single global model. This strengthens the argument that the discovered clusters really do reflect underlying patterns in disease expression.
The exposure of humans to nano-and microplastic particles (NMPs) is an issue recognized as a potential health hazard by scientists, authorities, politics, non-governmental organizations and the general public. The concentration of NMPs in the environment is increasing concomitantly with global plastic production and the usage of plastic materials. NMPs are detectable in numerous aquatic organisms and also in human samples, therefore necessitating a risk assessment of NMPs for human health. So far, a comprehensive risk assessment of NMPs is hampered by limited availability of appropriate reference materials, analytical obstacles and a lack of definitions and standardized study designs. Most studies conducted so far used polystyrene (PS) spheres as a matter of availability, although this polymer type accounts for only about 7% of total plastic production. Differently sized particles, different concentration and incubation times, and various biological models have been used, yielding hardly comparable data sets. Crucial physico-chemical properties of NMPs such as surface (charge, polarity, chemical reactivity), supplemented additives and adsorbed chemicals have been widely excluded from studies, although in particular the surface of NMPs determines the interaction with cellular membranes. In this manuscript we give an overview about the critical parameters which should be considered when performing risk assessments of NMPs, including novel reference materials, taking into account surface modifications (e.g., reflecting weathering processes), and the possible role of NMPs as a substrate and/or carrier for (pathogenic) microbes. Moreover, we make suggestions for biological model systems to evaluate immediate toxicity, long-term effects and the potential of NMPs to cross biological barriers. We are convinced that standardized reference materials and experimental parameters along with technical innovations in (nano)-particle sampling and analytics are a prerequisite for the successful realization of conclusive human health risk assessments of NMPs.
New innovative neuropsychological tests in attention deficit hyperactivity disorder ADHD have been proposed as objective measures for diagnosis and therapy. The current study aims to investigate two different commercial continuous performance tests (CPT) in a head-to-head comparison regarding their comparability and their link with clinical parameters. The CPTs were evaluated in a clinical sample of 29 adult patients presenting in an ADHD outpatient clinic. Correlational analyses were performed between neuropsychological data, clinical rating scales, and a personality-based measure. Though inattention was found to positively correlate between the two tests (r = 0.49, p = 0.01), no association with clinical measures and inattention was found for both tests. While hyperactivity did not correlate between both tests, current ADHD symptoms were positively associated with Nesplora Aquarium's motor activity (r = 0.52 to 0.61, p < 0.05) and the Qb-Test's hyperactivity (r = 0.52 to 0.71, p < 0.05). Conclusively, the overall comparability of the tests was limited and correlation with clinical parameters was low. While our study shows some interesting correlation between clinical symptoms and sub-scales of these tests, usage in clinical practice is not recommended.
Tinnitus is a complex and heterogeneous psycho-physiological disorder responsible for causing a phantom ringing or buzzing sound albeit the absence of an external sound source. It has a direct influence on affecting the quality of life of its sufferers. Despite being around for a while, there has not been a cure for tinnitus, and the usual course of action for its treatment involves use of tinnitus retaining and sound therapy, or Cognitive Behavioral Therapy (CBT). One positive aspect about these therapies is that they can be administered face-to-face as well as delivered via internet or smartphone. Smartphones are especially helpful as they are highly personalized devices, and offer a well-established ecosystem of apps, accessible via respective marketplaces of differing mobile platforms. Note that current therapeutic treatments such as CBT have shown to be effective in suppressing the tinnitus symptoms when administered face-to-face, their effectiveness when being delivered using smartphones is not known so far. A quick search on the prominent market places of popular mobile platforms (Android and iOS) yielded roughly 250 smartphone apps offering tinnitus-related therapies and tinnitus management. As this number is expected to steadily increase due to high interest in smartphone app development, a contemporary review of such apps is crucial. In this paper, we aim to review scientific studies validating the smartphone apps, particularly to test their effectiveness in tinnitus management and treatment. We use the PRISMA guidelines for identification of studies on major scientific literature sources and delineate the outcomes of identified studies.
Amidochelocardin overcomes resistance mechanisms exerted on tetracyclines and natural chelocardin
(2020)
The reassessment of known but neglected natural compounds is a vital strategy for providing novel lead structures urgently needed to overcome antimicrobial resistance. Scaffolds with resistance-breaking properties represent the most promising candidates for a successful translation into future therapeutics. Our study focuses on chelocardin, a member of the atypical tetracyclines, and its bioengineered derivative amidochelocardin, both showing broad-spectrum antibacterial activity within the ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) panel. Further lead development of chelocardins requires extensive biological and chemical profiling to achieve favorable pharmaceutical properties and efficacy. This study shows that both molecules possess resistance-breaking properties enabling the escape from most common tetracycline resistance mechanisms. Further, we show that these compounds are potent candidates for treatment of urinary tract infections due to their in vitro activity against a large panel of multidrug-resistant uropathogenic clinical isolates. In addition, the mechanism of resistance to natural chelocardin was identified as relying on efflux processes, both in the chelocardin producer Amycolatopsis sulphurea and in the pathogen Klebsiella pneumoniae. Resistance development in Klebsiella led primarily to mutations in ramR, causing increased expression of the acrAB-tolC efflux pump. Most importantly, amidochelocardin overcomes this resistance mechanism, revealing not only the improved activity profile but also superior resistance-breaking properties of this novel antibacterial compound.
RTX-Toxins
(2020)
Smart sensors and smartphones are becoming increasingly prevalent. Both can be used to gather environmental data (e.g., noise). Importantly, these devices can be connected to each other as well as to the Internet to collect large amounts of sensor data, which leads to many new opportunities. In particular, mobile crowdsensing techniques can be used to capture phenomena of common interest. Especially valuable insights can be gained if the collected data are additionally related to the time and place of the measurements. However, many technical solutions still use monolithic backends that are not capable of processing crowdsensing data in a flexible, efficient, and scalable manner. In this work, an architectural design was conceived with the goal to manage geospatial data in challenging crowdsensing healthcare scenarios. It will be shown how the proposed approach can be used to provide users with an interactive map of environmental noise, allowing tinnitus patients and other health-conscious people to avoid locations with harmful sound levels. Technically, the shown approach combines cloud-native applications with Big Data and stream processing concepts. In general, the presented architectural design shall serve as a foundation to implement practical and scalable crowdsensing platforms for various healthcare scenarios beyond the addressed use case.
This paper is concerned with the rights of refugees. The refugee issue has been an acutely charged item on the political agenda for several years. Although the great waves of influx have flattened out, people are continually venturing into Europe. Europe’s handling of refugees has been subject to strong criticism, and the accusation that various actions contradict internationally agreed law is particularly serious. It remains a question of how to respond appropriately to the influx of people fearing for their lives. This paper examines empirically how young people from different denominations in Germany (n = 2022) and how Roman Catholics from 10 countries (n = 5363) evaluate refugee rights. It also investigates whether individual religiosity moderates the influence of denomination or national context. The results show that there are no significant differences between respondents from different denominations, but there are significant differences between respondents from different countries. However, religiosity was not found to moderate the influence of denomination or national context. These findings suggest that attitudes towards refugee rights depend more on the national context in which people live rather than on their religious affiliation or individual religiosity.
Multidrug-resistant bacteria represent one of the most important health care problems worldwide. While there are numerous drugs available for standard therapy, there are only a few compounds capable of serving as a last resort for severe infections. Therefore, approaches to control multidrug-resistant bacteria must be implemented. Here, a strategy of reactivating the established glycopeptide antibiotic vancomycin by structural modification with polycationic peptides and subsequent fatty acid conjugation to overcome the resistance of multidrug-resistant bacteria was followed. This study especially focuses on the structure–activity relationship, depending on the modification site and fatty acid chain length. The synthesized conjugates showed high antimicrobial potential on vancomycin-resistant enterococci. We were able to demonstrate that the antimicrobial activity of the vancomycin-lipopeptide conjugates depends on the chain length of the attached fatty acid. All conjugates showed good cytocompatibility in vitro and in vivo. Radiolabeling enabled the in vivo determination of pharmacokinetics in Wistar rats by molecular imaging and biodistribution studies. An improved biodistribution profile in comparison to unmodified vancomycin was observed. While vancomycin is rapidly excreted by the kidneys, the most potent conjugate shows a hepatobiliary excretion profile. In conclusion, these results demonstrate the potential of the structural modification of already established antibiotics to provide highly active compounds for tackling multidrug-resistant bacteria.
Protection and recovery of natural resource and biodiversity requires accurate monitoring at multiple scales. Airborne Laser Scanning (ALS) provides high-resolution imagery that is valuable for monitoring structural changes to vegetation, providing a reliable reference for ecological analyses and comparison purposes, especially if used in conjunction with other remote-sensing and field products. However, the potential of ALS data has not been fully exploited, due to limits in data availability and validation. To bridge this gap, the global network for airborne laser scanner data (GlobALS) has been established as a worldwide network of ALS data providers that aims at linking those interested in research and applications related to natural resources and biodiversity monitoring. The network does not collect data itself but collects metadata and facilitates networking and collaborative research amongst the end-users and data providers. This letter describes this facility, with the aim of broadening participation in GlobALS.
In China, freshwater is an increasingly scarce resource and wetlands are under great pressure. This study focuses on China's second largest freshwater lake in the middle reaches of the Yangtze River — the Dongting Lake — and its surrounding wetlands, which are declared a protected Ramsar site. The Dongting Lake area is also a research region of focus within the Sino-European Dragon Programme, aiming for the international collaboration of Earth Observation researchers. ESA's Copernicus Programme enables comprehensive monitoring with area-wide coverage, which is especially advantageous for large wetlands that are difficult to access during floods. The first year completely covered by Sentinel-1 SAR satellite data was 2016, which is used here to focus on Dongting Lake's wetland dynamics. The well-established, threshold-based approach and the high spatio-temporal resolution of Sentinel-1 imagery enabled the generation of monthly surface water maps and the analysis of the inundation frequency at a 10 m resolution. The maximum extent of the Dongting Lake derived from Sentinel-1 occurred in July 2016, at 2465 km\(^2\), indicating an extreme flood year. The minimum size of the lake was detected in October, at 1331 km\(^2\). Time series analysis reveals detailed inundation patterns and small-scale structures within the lake that were not known from previous studies. Sentinel-1 also proves to be capable of mapping the wetland management practices for Dongting Lake polders and dykes. For validation, the lake extent and inundation duration derived from the Sentinel-1 data were compared with excerpts from the Global WaterPack (frequently derived by the German Aerospace Center, DLR), high-resolution optical data, and in situ water level data, which showed very good agreement for the period studied. The mean monthly extent of the lake in 2016 from Sentinel-1 was 1798 km\(^2\), which is consistent with the Global WaterPack, deviating by only 4%. In summary, the presented analysis of the complete annual time series of the Sentinel-1 data provides information on the monthly behavior of water expansion, which is of interest and relevance to local authorities involved in water resource management tasks in the region, as well as to wetland conservationists concerned with the Ramsar site wetlands of Dongting Lake and to local researchers.
Deep learning (DL) has great influence on large parts of science and increasingly established itself as an adaptive method for new challenges in the field of Earth observation (EO). Nevertheless, the entry barriers for EO researchers are high due to the dense and rapidly developing field mainly driven by advances in computer vision (CV). To lower the barriers for researchers in EO, this review gives an overview of the evolution of DL with a focus on image segmentation and object detection in convolutional neural networks (CNN). The survey starts in 2012, when a CNN set new standards in image recognition, and lasts until late 2019. Thereby, we highlight the connections between the most important CNN architectures and cornerstones coming from CV in order to alleviate the evaluation of modern DL models. Furthermore, we briefly outline the evolution of the most popular DL frameworks and provide a summary of datasets in EO. By discussing well performing DL architectures on these datasets as well as reflecting on advances made in CV and their impact on future research in EO, we narrow the gap between the reviewed, theoretical concepts from CV and practical application in EO.