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Crosslinking of thermoplastics is a versatile method to create crystallizable polymer networks, which are of high interest for shape-memory actuators. Here, crosslinked poly(epsilon-caprolactone) thermosets (cPCLs) were prepared from linear starting material, whereby the amount of extractable polymer was varied. Fractions of 5-60 wt % of non-crosslinked polymer chains, which freely interpenetrate the crosslinked network, were achieved leading to differences in the resulting phase of the bulk material. This can be described as "sponge-like" with open or closed compartments depending on the amount of interpenetrating polymer. The crosslinking density and the average network chain length remained in a similar range for all network structures, while the theoretical accessible volume for reptation of the free polymer content is affected. This feature could influence or introduce new functions into the material created by thermomechanical treatment. The effect of interpenetrating PCL in cPCLs on the reversible actuation was analyzed by cyclic, uniaxial tensile tests. Here, high reversible strains of up to Delta epsilon = 24% showed the enhanced actuation performance of networks with a non-crosslinked PCL content of 30 wt % resulting from the crystal formation in the phase of the non-crosslinked PCL and co-crystallization with network structures. Additional functionalities are reprogrammability and self-healing capabilities for networks with high contents of extractable polymer enabling reusability and providing durable actuator materials.
Correction to: Knowledge bases and software support for variant interpretation in precision oncology
(2021)
EC 22536-5304
(2021)
Helium-burning hot subdwarf stars of spectral types O and B (sdO/B) are thought to be produced through various types of binary interactions. The helium-rich hot subdwarf star EC 22536-5304 was recently found to be extremely enriched in lead. Here, we show that EC 22536-5304 is a binary star with a metal-poor subdwarf F-type (sdF) companion. We performed a detailed analysis of high-resolution SALT/HRS and VLT/UVES spectra, deriving metal abundances for the hot subdwarf, as well as atmospheric parameters for both components. Because we consider the contribution of the sdF star, the derived lead abundance for the sdOB, + 6.3 +/- 0.3 dex relative to solar, is even higher than previously thought. We derive T-eff = 6210 +/- 70 K, log g = 4.64 +/- 0.10, [FE/H] = - 1.95 +/- 0.04, and [alpha/Fe] = + 0.40 +/- 0.04 for the sdF component. Radial velocity variations, although poorly sampled at present, indicate that the binary system has a long orbital period of about 457 days. This suggests that the system was likely formed through stable Roche lobe overflow (RLOF). A kinematic analysis shows that EC 22536-5304 is on an eccentric orbit around the Galactic centre. This, as well as the low metallicity and strong alpha enhancement of the sdF-type companion, indicate that EC 22536-5304 is part of the Galactic halo or metal-weak thick disc. As the first long-period hot subdwarf binary at [FE/H] less than or similar to- 1, EC 22536-5304 may help to constrain the RLOF mechanism for mass transfer from low-mass, low-metallicity red giant branch (RGB) stars to main-sequence companions.
Background: Epidemiological studies suggest that an increased red meat intake is associated with a higher risk of type 2 diabetes, whereas an increased fiber intake is associated with a lower risk. Objectives: We conducted an intervention study to investigate the effects of these nutritional factors on glucose and lipid metabolism, body-fat distribution, and liver fat content in subjects at increased risk of type 2 diabetes. Methods: This prospective, randomized, and controlled dietary intervention study was performed over 6 mo. All groups decreased their daily caloric intake by 400 kcal. The "control" group (N = 40) only had this requirement. The "no red meat" group (N = 48) in addition aimed to avoid the intake of red meat, and the "fiber" group (N = 44) increased intake of fibers to 40 g/d. Anthropometric parameters and frequently sampled oral glucose tolerance tests were performed before and after intervention. Body-fat mass and distribution, liver fat, and liver iron content were assessed by MRI and single voxel proton magnetic resonance spectroscopy. Results: Participants in all groups lost weight (mean 3.3 +/- 0.5 kg, P < 0.0001). Glucose tolerance and insulin sensitivity improved (P < 0.001), and body and visceral fat mass decreased in all groups (P < 0.001). These changes did not differ between groups. Liver fat content decreased significantly (P < 0.001) with no differences between the groups. The decrease in liver fat correlated with the decrease in ferritin during intervention (r(2) = 0.08, P = 0.0021). This association was confirmed in an independent lifestyle intervention study (Tuebingen Lifestyle Intervention Program, N = 229, P = 0.0084). Conclusions: Our data indicate that caloric restriction leads to a marked improvement in glucose metabolism and body-fat composition, including liver-fat content. The marked reduction in liver fat might be mediated via changes in ferritin levels. In the context of caloric restriction, there seems to be no additional beneficial impact of reduced red meat intake and increased fiber intake on the improvement in cardiometabolic risk parameters. This trial was registered at clinicaltrials.gov as NCT03231839.
The Low Earth Orbit (LEO) experiment Biology and Mars Experiment (BIOMEX) is an interdisciplinary and international space research project selected by ESA. The experiment will be accommodated on the space exposure facility EXPOSE-R2 on the International Space Station (ISS) and is foreseen to be launched in 2013. The prime objective of BIOMEX is to measure to what extent biomolecules, such as pigments and cellular components, are resistant to and able to maintain their stability under space and Mars-like conditions. The results of BIOMEX will be relevant for space proven biosignature definition and for building a biosignature data base (e.g. the proposed creation of an international Raman library). The library will be highly relevant for future space missions such as the search for life on Mars. The secondary scientific objective is to analyze to what extent terrestrial extremophiles are able to survive in space and to determine which interactions between biological samples and selected minerals (including terrestrial, Moon- and Mars analogs) can be observed under space and Mars-like conditions. In this context, the Moon will be an additional platform for performing similar experiments with negligible magnetic shielding and higher solar and galactic irradiation compared to LEO. Using the Moon as an additional astrobiological exposure platform to complement ongoing astrobiological LEO investigations could thus enhance the chances of detecting organic traces of life on Mars. We present a lunar lander mission with two related objectives: a lunar lander equipped with Raman and PanCam instruments which can analyze the lunar surface and survey an astrobiological exposure platform. This dual use of testing mission technology together with geo- and astrobiological analyses will significantly increase the science return, and support the human preparation objectives. It will provide knowledge about the Moon's surface itself and, in addition, monitor the stability of life-markers, such as cells, cell components and pigments, in an extraterrestrial environment with much closer radiation properties to the surface of Mars. The combination of a Raman data base of these data together with data from LEO and space simulation experiments, will lead to further progress on the analysis and interpretation of data that we will obtain from future Moon and Mars exploration missions.
Strong light-matter coupling can re-arrange the exciton energies in organic semiconductors. Here, we exploit strong coupling by embedding a fullerene-free organic solar cell (OSC) photo-active layer into an optical microcavity, leading to the formation of polariton peaks and a red-shift of the optical gap. At the same time, the open-circuit voltage of the device remains unaffected. This leads to reduced photon energy losses for the low-energy polaritons and a steepening of the absorption edge. While strong coupling reduces the optical gap, the energy of the charge-transfer state is not affected for large driving force donor-acceptor systems. Interestingly, this implies that strong coupling can be exploited in OSCs to reduce the driving force for electron transfer, without chemical or microstructural modifications of the photoactive layer. Our work demonstrates that the processes determining voltage losses in OSCs can now be tuned, and reduced to unprecedented values, simply by manipulating the device architecture.
Improving our understanding of biodiversity and ecosystem functioning and our capacity to inform ecosystem management requires an integrated framework for functional biodiversity research (FBR). However, adequate integration among empirical approaches (monitoring and experimental) and modelling has rarely been achieved in FBR. We offer an appraisal of the issues involved and chart a course towards enhanced integration. A major element of this path is the joint orientation towards the continuous refinement of a theoretical framework for FBR that links theory testing and generalization with applied research oriented towards the conservation of biodiversity and ecosystem functioning. We further emphasize existing decision-making frameworks as suitable instruments to practically merge these different aims of FBR and bring them into application. This integrated framework requires joint research planning, and should improve communication and stimulate collaboration between modellers and empiricists, thereby overcoming existing reservations and prejudices. The implementation of this integrative research agenda for FBR requires an adaptation in most national and international funding schemes in order to accommodate such joint teams and their more complex structures and data needs.
Understanding interrelations between an environment's hydrological past and its current biogeochemistry is necessary for the assessment of biogeochemical and microbial responses to changing hydrological conditions. The question how previous dry-wet events determine the contemporary microbial and biogeochemical state is addressed in this study. Therefore, sediments exposed to the atmosphere of areas with a different hydrological past within one kettle hole, i.e. (1) the predominantly inundated pond center, (2) the pond margin frequently desiccated for longer periods and (3) an intermediate zone, were incubated with the same rewetting treatment. Physicochemical and textural characteristics were related to structural microbial parameters regarding carbon and nitrogen turnover, i.e. abundance of bacteria and fungi, denitrifiers (targeted by the nirK und nirS functional genes) and nitrate ammonifiers (targeted by the nrfA functional gene). Our study reveals that, in combination with varying sediment texture, the hydrological history creates distinct microbial habitats with defined boundary conditions within the kettle hole, mainly driven by redox conditions, pH and organic matter (OM) composition. OM mineralization, as indicated by CO2-outgassing, was most efficient in exposed sediments with a less stable hydrological past. The potential for nitrogen retention via nitrate ammonification was highest in the hydrologically rather stable pond center, counteracting nitrogen loss due to denitrification. Therefore, the degree of hydrological stability is an important factor leaving a microbial and biogeochemical legacy, which determines carbon and nitrogen losses from small lentic freshwater systems in the long term run.
In aquatic ecosystems, light availability can significantly influence microbial turnover of terrestrial organic matter through associated metabolic interactions between phototrophic and heterotrophic communities. However, particularly in streams, microbial functions vary significantly with the structure of the streambed, that is the distribution and spatial arrangement of sediment grains in the streambed. It is therefore essential to elucidate how environmental factors synergistically define the microbial turnover of terrestrial organic matter in order to better understand the ecological role of photoheterotrophic interactions in stream ecosystem processes. In outdoor experimental streams, we examined how the structure of streambeds modifies the influence of light availability on microbial turnover of leaf carbon (C). Furthermore, we investigated whether the studied relationships of microbial leaf C turnover to environmental conditions are affected by flow intermittency commonly occurring in streams. We applied leaves enriched with a C-13-stable isotope tracer and combined quantitative and isotope analyses. We thereby elucidated whether treatment induced changes in C turnover were associated with altered use of leaf C within the microbial food web. Moreover, isotope analyses were combined with measurements of microbial community composition to determine whether changes in community function were associated with a change in community composition. In this study, we present evidence, that environmental factors interactively determine how phototrophs and heterotrophs contribute to leaf C turnover. Light availability promoted the utilization of leaf C within the microbial food web, which was likely associated with a promoted availability of highly bioavailable metabolites of phototrophic origin. However, our results additionally confirm that the structure of the streambed modifies light-related changes in microbial C turnover. From our observations, we conclude that the streambed structure influences the strength of photo-heterotrophic interactions by defining the spatial availability of algal metabolites in the streambed and the composition of microbial communities. Collectively, our multifactorial approach provides valuable insights into environmental controls on the functioning of stream ecosystems.
Background: Pavlovian processes are thought to play an important role in the development, maintenance and relapse of alcohol dependence, possibly by influencing and usurping ongoing thought and behavior. The influence of pavlovian stimuli on ongoing behavior is paradigmatically measured by pavlovian-to-instrumental transfer (PIT) tasks. These involve multiple stages and are complex. Whether increased PIT is involved in human alcohol dependence is uncertain. We therefore aimed to establish and validate a modified PIT paradigm that would be robust, consistent and tolerated by healthy controls as well as by patients suffering from alcohol dependence, and to explore whether alcohol dependence is associated with enhanced PIT. Methods: Thirty-two recently detoxified alcohol-dependent patients and 32 age- and gender-matched healthy controls performed a PIT task with instrumental go/no-go approach behaviors. The task involved both pavlovian stimuli associated with monetary rewards and losses, and images of drinks. Results: Both patients and healthy controls showed a robust and temporally stable PIT effect. Strengths of PIT effects to drug-related and monetary conditioned stimuli were highly correlated. Patients more frequently showed a PIT effect, and the effect was stronger in response to aversively conditioned CSs (conditioned suppression), but there was no group difference in response to appetitive CSs. Conclusion: The implementation of PIT has favorably robust properties in chronic alcohol-dependent patients and in healthy controls. It shows internal consistency between monetary and drug-related cues. The findings support an association of alcohol dependence with an increased propensity towards PIT.
Behavioral choice can be characterized along two axes. One axis distinguishes reflexive, model-free systems that slowly accumulate values through experience and a model-based system that uses knowledge to reason prospectively. The second axis distinguishes Pavlovian valuation of stimuli from instrumental valuation of actions or stimulus–action pairs. This results in four values and many possible interactions between them, with important consequences for accounts of individual variation. We here explored whether individual variation along one axis was related to individual variation along the other. Specifically, we asked whether individuals' balance between model-based and model-free learning was related to their tendency to show Pavlovian interferences with instrumental decisions. In two independent samples with a total of 243 participants, Pavlovian–instrumental transfer effects were negatively correlated with the strength of model-based reasoning in a two-step task. This suggests a potential common underlying substrate predisposing individuals to both have strong Pavlovian interference and be less model-based and provides a framework within which to interpret the observation of both effects in addiction.
Theories of decision-making and its neural substrates have long assumed the existence of two distinct and competing valuation systems, variously described as goal-directed vs. habitual, or, more recently and based on statistical arguments, as model-free vs. model-based reinforcement-learning. Though both have been shown to control choices, the cognitive abilities associated with these systems are under ongoing investigation. Here we examine the link to cognitive abilities, and find that individual differences in processing speed covary with a shift from model-free to model-based choice control in the presence of above-average working memory function. This suggests shared cognitive and neural processes; provides a bridge between literatures on intelligence and valuation; and may guide the development of process models of different valuation components. Furthermore, it provides a rationale for individual differences in the tendency to deploy valuation systems, which may be important for understanding the manifold neuropsychiatric diseases associated with malfunctions of valuation.
Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities.
In animals and humans, behavior can be influenced by irrelevant stimuli, a phenomenon called Pavlovian-to-instrumental transfer (PIT). In subjects with substance use disorder, PIT is even enhanced with functional activation in the nucleus accumbens (NAcc) and amygdala. While we observed enhanced behavioral and neural PIT effects in alcohol-dependent subjects, we here aimed to determine whether behavioral PIT is enhanced in young men with high-risk compared to low-risk drinking and subsequently related functional activation in an a-priori region of interest encompassing the NAcc and amygdala and related to polygenic risk for alcohol consumption. A representative sample of 18-year old men (n = 1937) was contacted: 445 were screened, 209 assessed: resulting in 191 valid behavioral, 139 imaging and 157 genetic datasets. None of the subjects fulfilled criteria for alcohol dependence according to the Diagnostic and Statistical Manual of Mental Disorders-IV-TextRevision (DSM-IV-TR). We measured how instrumental responding for rewards was influenced by background Pavlovian conditioned stimuli predicting action-independent rewards and losses. Behavioral PIT was enhanced in high-compared to low-risk drinkers (b = 0.09, SE = 0.03, z = 2.7, p < 0.009). Across all subjects, we observed PIT-related neural blood oxygen level-dependent (BOLD) signal in the right amygdala (t = 3.25, p(SVC) = 0.04, x = 26, y = -6, z = -12), but not in NAcc. The strength of the behavioral PIT effect was positively correlated with polygenic risk for alcohol consumption (r(s) = 0.17, p = 0.032). We conclude that behavioral PIT and polygenic risk for alcohol consumption might be a biomarker for a subclinical phenotype of risky alcohol consumption, even if no drug-related stimulus is present. The association between behavioral PIT effects and the amygdala might point to habitual processes related to out PIT task. In non-dependent young social drinkers, the amygdala rather than the NAcc is activated during PIT; possible different involvement in association with disease trajectory should be investigated in future studies.
Background:
Prejudices against minorities can be understood as habitually negative evaluations that are kept in spite of evidence to the contrary. Therefore, individuals with strong prejudices might be dominated by habitual or "automatic" reactions at the expense of more controlled reactions. Computational theories suggest individual differences in the balance between habitual/model-free and deliberative/model-based decision-making.
Methods:
127 subjects performed the two Step task and completed the blatant and subtle prejudice scale.
Results:
By using analyses of choices and reaction times in combination with computational modeling, subjects with stronger blatant prejudices showed a shift away from model-based control. There was no association between these decision-making processes and subtle prejudices.
Conclusion:
These results support the idea that blatant prejudices toward minorities are related to a relative dominance of habitual decision-making. This finding has important implications for developing interventions that target to change prejudices across societies.
BACKGROUND: Addiction is supposedly characterized by a shift from goal-directed to habitual decision making, thus facilitating automatic drug intake. The two-step task allows distinguishing between these mechanisms by computationally modeling goal-directed and habitual behavior as model-based and model-free control. In addicted patients, decision making may also strongly depend upon drug-associated expectations. Therefore, we investigated model-based versus model-free decision making and its neural correlates as well as alcohol expectancies in alcohol-dependent patients and healthy controls and assessed treatment outcome in patients. METHODS: Ninety detoxified, medication-free, alcohol-dependent patients and 96 age-and gender-matched control subjects underwent functional magnetic resonance imaging during the two-step task. Alcohol expectancies were measured with the Alcohol Expectancy Questionnaire. Over a follow-up period of 48 weeks, 37 patients remained abstinent and 53 patients relapsed as indicated by the Alcohol Timeline Followback method. RESULTS: Patients who relapsed displayed reduced medial prefrontal cortex activation during model-based decision making. Furthermore, high alcohol expectancies were associated with low model-based control in relapsers, while the opposite was observed in abstainers and healthy control subjects. However, reduced model-based control per se was not associated with subsequent relapse. CONCLUSIONS: These findings suggest that poor treatment outcome in alcohol dependence does not simply result from a shift from model-based to model-free control but is instead dependent on the interaction between high drug expectancies and low model-based decision making. Reduced model-based medial prefrontal cortex signatures in those who relapse point to a neural correlate of relapse risk. These observations suggest that therapeutic interventions should target subjective alcohol expectancies.
Importance Alcohol consumption (AC) leads to death and disability worldwide. Ongoing discussions on potential negative effects of the COVID-19 pandemic on AC need to be informed by real-world evidence.
Objective To examine whether lockdown measures are associated with AC and consumption-related temporal and psychological within-person mechanisms.
Design, Setting, and Participants This quantitative, intensive, longitudinal cohort study recruited 1743 participants from 3 sites from February 20, 2020, to February 28, 2021. Data were provided before and within the second lockdown of the COVID-19 pandemic in Germany: before lockdown (October 2 to November 1, 2020); light lockdown (November 2 to December 15, 2020); and hard lockdown (December 16, 2020, to February 28, 2021).
Main Outcomes and Measures Daily ratings of AC (main outcome) captured during 3 lockdown phases (main variable) and temporal (weekends and holidays) and psychological (social isolation and drinking intention) correlates.
Results Of the 1743 screened participants, 189 (119 [63.0%] male; median [IQR] age, 37 [27.5-52.0] years) with at least 2 alcohol use disorder (AUD) criteria according to the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) yet without the need for medically supervised alcohol withdrawal were included. These individuals provided 14 694 smartphone ratings from October 2020 through February 2021. Multilevel modeling revealed significantly higher AC (grams of alcohol per day) on weekend days vs weekdays (β = 11.39; 95% CI, 10.00-12.77; P < .001). Alcohol consumption was above the overall average on Christmas (β = 26.82; 95% CI, 21.87-31.77; P < .001) and New Year’s Eve (β = 66.88; 95% CI, 59.22-74.54; P < .001). During the hard lockdown, perceived social isolation was significantly higher (β = 0.12; 95% CI, 0.06-0.15; P < .001), but AC was significantly lower (β = −5.45; 95% CI, −8.00 to −2.90; P = .001). Independent of lockdown, intention to drink less alcohol was associated with lower AC (β = −11.10; 95% CI, −13.63 to −8.58; P < .001). Notably, differences in AC between weekend and weekdays decreased both during the hard lockdown (β = −6.14; 95% CI, −9.96 to −2.31; P = .002) and in participants with severe AUD (β = −6.26; 95% CI, −10.18 to −2.34; P = .002).
Conclusions and Relevance This 5-month cohort study found no immediate negative associations of lockdown measures with overall AC. Rather, weekend-weekday and holiday AC patterns exceeded lockdown effects. Differences in AC between weekend days and weekdays evinced that weekend drinking cycles decreased as a function of AUD severity and lockdown measures, indicating a potential mechanism of losing and regaining control. This finding suggests that temporal patterns and drinking intention constitute promising targets for prevention and intervention, even in high-risk individuals.
Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at pathology departments worldwide, creating the urgent need for scalable cancer variant annotation and molecularly informed treatment recommendations. A wealth of mainly academia-driven knowledge bases calls for software tools supporting the multi-step diagnostic process. We derive a comprehensive list of knowledge bases relevant for variant interpretation by a review of existing literature followed by a survey among medical experts from university hospitals in Germany. In addition, we review cancer variant interpretation tools, which integrate multiple knowledge bases. We categorize the knowledge bases along the diagnostic process in precision oncology and analyze programmatic access options as well as the integration of knowledge bases into software tools. The most commonly used knowledge bases provide good programmatic access options and have been integrated into a range of software tools. For the wider set of knowledge bases, access options vary across different parts of the diagnostic process. Programmatic access is limited for information regarding clinical classifications of variants and for therapy recommendations. The main issue for databases used for biological classification of pathogenic variants and pathway context information is the lack of standardized interfaces. There is no single cancer variant interpretation tool that integrates all identified knowledge bases. Specialized tools are available and need to be further developed for different steps in the diagnostic process.
Hot subdwarf stars represent a late and peculiar stage in the evolution of low-mass stars, since they are likely formed by close binary interactions. In this work, we perform a radial velocity (RV) variability study of a sample of 646 hot subdwarfs with multi-epoch radial velocities based on spectra from Sloan Digital Sky Survey (SDSS) and Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST). The atmospheric parameters and RVs were taken from the literature. For stars with archival spectra but without literature values, we determined the parameters by fitting model atmospheres. In addition, we redetermined the atmospheric parameters and RVs for all the He-enriched sdO/Bs. This broad sample allowed us to study RV-variability as a function of the location in the T-eff - log g- and T-eff - log n(He)/n(H) diagrams in a statistically significant way. We used the fraction of RV-variable stars and the distribution of the maximum RV variations Delta RVmax as diagnostics. Both indicators turned out to be quite inhomogeneous across the studied parameter ranges. A striking feature is the completely dissimilar behaviour of He-poor and He-rich hot subdwarfs. While the former have a high fraction of close binaries, almost no significant RV variations could be detected for the latter. This has led us to the conclusion that there is likely no evolutionary connection between these subtypes. On the other hand, intermediate He-rich- and extreme He-rich sdOB/Os are more likely to be related. Furthermore, we conclude that the vast majority of this population is formed via one or several binary merger channels. Hot subdwarfs with temperatures cooler than similar to 24 000 K tend to show fewer and smaller RV-variations. These objects might constitute a new subpopulation of binaries with longer periods and late-type or compact companions. The RV-variability properties of the extreme horizontal branch (EHB) and corresponding post-EHB populations of the He-poor hot subdwarfs match and confirm the predicted evolutionary connection between them. Stars found below the canonical EHB at somewhat higher surface gravities show large RV variations and a high RV variability fraction. These properties are consistent with most of them being low-mass EHB stars or progenitors of low-mass helium white dwarfs in close binaries.