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Urbanization in Ethiopia is rapidly reducing green space and biodiversity, and placing ecological stress on trees. Urban street trees (UST) can provide multiple ecosystem services, but need to cope with challenging street ecology and future climate risks. However, UST selection in Ethiopia is poor, and conventional trials and modern breeding are costly and time consuming to apply in Ethiopia. The main objective of the study was to identify potential UST species for two Ethiopian cities; Addis Ababa, and Arba Minch, by studying interspecific differences in functional traits. For the purpose, we created a database with list of 120 candidate UST gathered from multi-stakeholder workshop, literature review, and senior experts survey, and their ecological with their phenological and morphological features. Then we filtered 25 potential UST through framework analysis considering eco-morphological features of the trees. For the 25 species, we measured three types of plant functional traits: conservative traits (leaf mass per area and leaf dry matter content), acquisitive traits (leaf area, specific leaf area and leaf water content) and drought tolerance traits (leaf turgor pressure loss point, and leaf succulence index). Our results showed a strong trade-off between conservative and acquisitive traits, particularly between leaf dry matter content (LDMC) and specific leaf area (SLA) (r = −0.71), consistent with plant economic spectrum theory. Using PCA analysis, we identified three groups of potential USTs (Type I, II and III) that exhibit different adaptation strategies, consistent with Grime’s trait-based classification of universal plant adaptation strategies (CSR). Compared to species with high acquisitive traits (Type II and Type III), Type I species have high conservative and drought-tolerant traits shows better adaptation to harsh road environments, whereas Type II and Type III species may be more advantageous for urban parks and other resource-rich components of urban ecology. We also found significant variation in conservative, acquisitive and drought-tolerant traits among different species, indicating their different adaptation strategies. Our research advances the knowledge of plant adaptation in urban environments and provides a useful method for UST selection.

BackgroundNeurodevelopmental disorders (NDD), psychiatric comorbidity and cognitive deficits are commonly seen in children with obesity; however, little is known about the overlap between these conditions. This study aimed to examine the undiagnosed and diagnosed frequency of NDDs and explore its association with psychiatric conditions and general intellectual ability (IQ) in children presenting for obesity treatment.MethodsIn this observational study at two outpatient obesity clinics during 2018-2019, 80 children (8-17 years) were consecutively recruited, and screened for NDD unless already diagnosed with an NDD. A psychiatric unit evaluated children who screened positive for NDD. Diagnoses and clinical background factors were collected from medical records. IQ was assessed with the Weschler Intelligence Scales and internalizing symptoms were assessed using the Beck Youth Inventories. Associations between background factors, IQ and internalizing symptoms were explored in relation to having an NDD or not.ResultsWe found that 47/80 children had at least one NDD. Children with a diagnosed NDD before study start (n = 30) had significantly more comorbidities than children diagnosed after the study screening (n = 17) (P = .01). Greater cognitive impairment was seen in children with NDD compared with children without an NDD (P = .01). Also, 33/73 participants self-reported substantial internalizing symptoms. At follow-up, 21/79 participants, in addition to NDD, had been diagnosed with another psychiatric disorder. Ten of these were children that had been diagnosed with an NDD before study start.ConclusionThe overlap between NDD, cognitive deficits and psychiatric conditions in children with obesity is an important consideration for clinical practice. Screening for these conditions may be necessary when providing targeted interventions.

IntroductionPlanting trees in urban areas can mitigate some of the emissions generated in cities by carbon sequestration (annual uptake of CO2 through the process of photosynthesis) and carbon storage (amount of carbon stored in the tree's biomass throughout its lifespan). The aim of this study was to calculate the carbon footprint from nursery production to final establishment of different tree species grown for planting in urban parks in a northern European context.Material and methodsThe analysis included a cradle-to-gate approach and investigated the amount of carbon the adult trees needed to sequester in order to compensate for initial carbon emissions and which temporal perspectives are of concern. Greenhouse gas emissions were estimated based on an inventory of consumption of fuels, energy, materials and other production inputs during cultivation, delivery, planting and establishment of three different tree species in three different locations in Sweden. The tree species considered in the analysis (Salix alba, Quercus rubra, Pinus sylvestris) were selected due to significant differences in their growth rates. Salix alba is a competitive strategist in resource-rich habitats, and is proficient at converting these resources into vigorous growth. Pinus sylvestris is a pronounced stress strategist with good ability to handle resource-limited habitats, and invests in traits accordingly, resulting in significantly slower development. Quercus rubra has its main distribution in cool and moderately resource-rich habitats, but has relatively high stress tolerance and can be considered intermediate between the other two species in terms of growth rate.Results and discussionThe results showed that within 16 years of planting, all species in all three cities, except Pinus sylvestris planted in Umeå, compensated for initial carbon emissions, i.e. showed net absorption of CO2 after emissions from cultivation, delivery, planting and establishment of the trees had been deducted. There was a clear link between the time by which compensation of initial carbon emissions was achieved and growth rate of the different species, with the fast-growing Salix alba showing the best results. The single largest source of emissions among all activities carried out during cultivation, delivery and planting of all species, regardless of the city in which they were planted, was fuel consumption during tree planting.

The sound-evoked electrical compound potential known as auditory brainstem response (ABR) represents the firing of a heterogenous population of auditory neurons in response to sound stimuli, and is often used for clinical diagnosis based on wave amplitude and latency. However, recent ABR applications to detect human cochlear synaptopathy have led to inconsistent results, mainly due to the high variability of ABR wave-1 amplitude. Here, rather than focusing on the amplitude of ABR wave 1, we evaluated the use of ABR wave curvature to detect cochlear synaptic loss. We first compared four curvature quantification methods using simulated ABR waves, and identified that the cubic spline method using five data points produced the most accurate quantification. We next evaluated this quantification method with ABR data from an established mouse model with cochlear synaptopathy. The data clearly demonstrated that curvature measurement is more sensitive and consistent in identifying cochlear synaptic loss in mice compared to the amplitude and latency measurements. We further tested this curvature method in a different mouse model presenting with otitis media. The change in curvature profile due to middle ear infection in otitis media is different from the profile of mice with cochlear synaptopathy. Thus, our study suggests that curvature quantification can be used to address the current ABR variability issue, and may lead to additional applications in the clinic diagnosis of hearing disorders.

The COVID-19 pandemic has increased levels of uncertainty and social polarization in our societies, compromising young people's capacity to envision a positive future and maintain a meaningful sense of purpose in life. Within a positive youth development framework, the present study investigates the associations of a positive future orientation, presence of and search for meaning in life, and support for violent radicalization (VR) in a diverse sample of Canadian college students. In addition, we investigate the moderating role of future orientation in the association between presence of and search for a meaning in life and support for VR. A total of 3,100 college students in Québec (Canada) (69% female; Mage = 18.57, SDage = 1.76) completed an online survey during the second wave of the COVID-19 pandemic. Results from linear mixed-effects models indicate that a positive future orientation and a higher presence of a meaning in life were negatively and independently associated with support for VR. Search for meaning in life was not associated with support for VR. The magnitude of the negative association between presence of a meaning in life and support for VR was greater among students with a more positive future orientation. Schools and colleges are in a privileged position to implement preventive interventions to support a positive future orientation and the presence of a meaning in life among young people during these challenging and uncertain times and reduce the risk of violence related to extreme ideologies in our rapidly changing society.

Self-organized criticality has been proposed to be a universal mechanism for the emergence of scale-free dynamics in many complex systems, and possibly in the brain. While such scale-free patterns were identified experimentally in many different types of neural recordings, the biological principles behind their emergence remained unknown. Utilizing different network models and motivated by experimental observations, synaptic plasticity was proposed as a possible mechanism to self-organize brain dynamics toward a critical point. In this review, we discuss how various biologically plausible plasticity rules operating across multiple timescales are implemented in the models and how they alter the network’s dynamical state through modification of number and strength of the connections between the neurons. Some of these rules help to stabilize criticality, some need additional mechanisms to prevent divergence from the critical state. We propose that rules that are capable of bringing the network to criticality can be classified by how long the near-critical dynamics persists after their disabling. Finally, we discuss the role of self-organization and criticality in computation. Overall, the concept of criticality helps to shed light on brain function and self-organization, yet the overall dynamics of living neural networks seem to harnesses not only criticality for computation, but also deviations thereof.