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The establishment and maintenance of protected areas (PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting protected areas based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences, as well as real-time comparison of the selected areas that result from such different priorities. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between species protection and ecosystem integrity. Outputs indicate that decision makers frequently face trade-offs among conflicting objectives. Nevertheless, we show that transparent decision-support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.
Establishing and maintaining protected areas (PAs) is a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting PAs based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences as well as real-time comparison of the outcome. Applying the tool across 1,346 terrestrial PAs, we demonstrate that decision makers frequently face trade-offs among conflicting objectives, e.g., between species protection and ecosystem integrity. Nevertheless, we show that transparent decision support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.
Dendritic spines are crucial for excitatory synaptic transmission as the size of a spine head correlates with the strength of its synapse. The distribution of spine head sizes follows a lognormal-like distribution with more small spines than large ones. We analysed the impact of synaptic activity and plasticity on the spine size distribution in adult-born hippocampal granule cells from rats with induced homo- and heterosynaptic long-term plasticity in vivo and CA1 pyramidal cells from Munc-13-1-Munc13-2 knockout mice with completely blocked synaptic transmission. Neither induction of extrinsic synaptic plasticity nor the blockage of presynaptic activity degrades the lognormal-like distribution but changes its mean, variance and skewness. The skewed distribution develops early in the life of the neuron. Our findings and their computational modelling support the idea that intrinsic synaptic plasticity is sufficient for the generation, while a combination of intrinsic and extrinsic synaptic plasticity maintains lognormal like distribution of spines.
Oral e-Poster Presentations - Booth 3: Spine 2 (Tumors), September 26, 2023, 4:10 PM - 4:50 PM
Background: Spinal metastasis remains a persistent and oftentimes urgent challenge in the neurosurgical operating room. We aim to understand metastatic spread to the spinal bone on a molecular level in endothelial cells and tumor cells to facilitate improved therapeutic approaches and diagnostics.
Methods: We established a murine syngeneic spinal bone metastasis model. In vivo dissemination was first evaluated using fluorescent beads, followed by murine cancer cell lines (B16, LLC1). We investigated short-term seeding and long-term growth to identify correlations between seeding and tumor formation. EphrinB2-Eph4 interaction has been described as a crucial mediator of spinal bone metastasis. Transient (pharmacological) and permanent (genetical) ephrinB2-Eph4 interventions were performed.
Results: Dissemination of microbeads to distinct spinal segments depended on segment and particle size. Disseminated tumor cells on the contrary showed less frequent arrest in the bone and equal distribution among segments. EphrinB2 intervention changed the dissemination behavior towards the lumbar segment. Interestingly, only transient intervention retained this distribution, permanent ephrinB2 depletion on endothelial cells (efnb2iΔEC) resulted in equal dispersion of metastases. Histological staining revealed a reduction of Endomucin (Emcn) positive structures in combination with a reduction of Type H (Emcn high/CD31 high) endothelial cells in naïve efnb2iΔEC animals. In tumor tissue, these Type H endothelial cells were unaffected. However, an increase in CD31-expressing endothelial cells was observed under endothelial ephrinB2 depletion. These CD31-expressing endothelial cells have been recently described as Type E (Emcn low/CD31 high) and implicated in angiogenesis and osteogenesis.
Conclusions: We here describe a subpopulation of endothelial cells in efnb2iΔEC mice that seems to resemble pro-angiogenic and possibly pro-adhesive type E endothelial cells. Based on these finding we propose a compensatory pro-angiogenic mechanism in efnb2iΔEC mice that is highjacking pre-existing developmental pathways, which is critical for late-stage spinal metastatic growth independent of the initial seeding and extravasation of metastatic cells.
Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability
(2023)
Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.
Results on the transverse spherocity dependence of light-flavor particle production (π, K, p, ϕ, K∗0, K0S, Λ, Ξ) at midrapidity in high-multiplicity pp collisions at s√=13 TeV were obtained with the ALICE apparatus. The transverse spherocity estimator (SpT=1O) categorizes events by their azimuthal topology. Utilizing narrow selections on SpT=1O, it is possible to contrast particle production in collisions dominated by many soft initial interactions with that observed in collisions dominated by one or more hard scatterings. Results are reported for two multiplicity estimators covering different pseudorapidity regions. The SpT=1O estimator is found to effectively constrain the hardness of the events when the midrapidity (|η|<0.8) estimator is used. The production rates of strange particles are found to be slightly higher for soft isotropic topologies, and severely suppressed in hard jet-like topologies. These effects are more pronounced for hadrons with larger mass and strangeness content, and observed when the topological selection is done within a narrow multiplicity interval. This demonstrates that an important aspect of the universal scaling of strangeness enhancement with final-state multiplicity is that high-multiplicity collisions are dominated by soft, isotropic processes. On the contrary, strangeness production in events with jet-like processes is significantly reduced. The results presented in this article are compared with several QCD-inspired Monte Carlo event generators. Models that incorporate a two-component phenomenology, either through mechanisms accounting for string density, or thermal production, are able to describe the observed strangeness enhancement as a function of SpT=1O.
Measurements of charged-particle production in pp, p−Pb, and Pb−Pb collisions in the toward, away, and transverse regions with the ALICE detector are discussed. These regions are defined event-by-event relative to the azimuthal direction of the charged trigger particle, which is the reconstructed particle with the largest transverse momentum (ptrigT) in the range 8<ptrigT<15 GeV/c. The toward and away regions contain the primary and recoil jets, respectively; both regions are accompanied by the underlying event (UE). In contrast, the transverse region perpendicular to the direction of the trigger particle is dominated by the so-called UE dynamics, and includes also contributions from initial- and final-state radiation. The relative transverse activity classifier, RT=NTch/⟨NTch⟩, is used to group events according to their UE activity, where NTch is the charged-particle multiplicity per event in the transverse region and ⟨NTch⟩ is the mean value over the whole analysed sample. The energy dependence of the RT distributions in pp collisions at s√=2.76, 5.02, 7, and 13 TeV is reported, exploring the Koba-Nielsen-Olesen (KNO) scaling properties of the multiplicity distributions. The first measurements of charged-particle pT spectra as a function of RT in the three azimuthal regions in pp, p−Pb, and Pb−Pb collisions at sNN−−−√=5.02 TeV are also reported. Data are compared with predictions obtained from the event generators PYTHIA 8 and EPOS LHC. This set of measurements is expected to contribute to the understanding of the origin of collective-like effects in small collision systems (pp and p−Pb).
The ALICE Collaboration reports the measurement of semi-inclusive distributions of charged-particle jets recoiling from a high transverse momentum (high pT) hadron trigger in proton−proton and central Pb−Pb collisions at sNN−−−√=5.02 TeV. A data-driven statistical method is used to mitigate the large uncorrelated background in central Pb−Pb collisions. Recoil jet distributions are reported for jet resolution parameter R=0.2, 0.4, and 0.5 in the range 7<pT,jet<140 GeV/c and trigger−recoil jet azimuthal separation π/2<Δφ<π. The measurements exhibit a marked medium-induced jet yield enhancement at low pT and at large azimuthal deviation from Δφ∼π. The enhancement is characterized by its dependence on Δφ, which has a slope that differs from zero by 4.7σ. Comparisons to model calculations incorporating different formulations of jet quenching are reported. These comparisons indicate that the observed yield enhancement arises from the response of the QGP medium to jet propagation.
The first measurement of the e+e− pair production at midrapidity and low invariant mass in central Pb−Pb collisions at sNN−−−√=5.02 TeV at the LHC is presented. The yield of e+e− pairs is compared with a cocktail of expected hadronic decay contributions in the invariant mass (mee) and pair transverse momentum (pT,ee) ranges mee<3.5 GeV/c2 and pT,ee<8 GeV/c. For 0.18<mee<0.5 GeV/c2 the ratio of data to the cocktail of hadronic contributions without ρ mesons amounts to 1.42±0.12 (stat.)±0.17 (syst.)±0.12 (cocktail) and 1.44±0.12 (stat.)±0.17 (syst.)+0.17−0.21 (cocktail), including or not including medium effects in the estimation of the heavy-flavor background, respectively. It is consistent with predictions from two different models for an additional contribution of thermal e+e− pairs from the hadronic and partonic phases. In the intermediate-mass range (1.2<mee<2.6 GeV/c2), the pair transverse impact parameter of the e+e− pairs (DCAee) is used for the first time in Pb−Pb collisions to separate displaced dielectrons from heavy-flavor hadron decays from a possible (thermal) contribution produced at the interaction point. The data are consistent with a suppression of e+e− pairs from cc¯¯ and an additional prompt component. Finally, the first direct-photon measurement in the 10% most central Pb−Pb collisions at sNN−−−√=5.02 TeV is reported via the study of virtual direct photons in the transverse momentum range 1<pT<5 GeV/c. A model including prompt photons, as well as photons from the pre-equilibrium and fluid-dynamic phases, can reproduce the result, while being at the upper edge of the data uncertainties.
Long- and short-range correlations for pairs of charged particles are studied via two-particle angular correlations in pp collisions at s√=13 TeV and p−Pb collisions at sNN−−−√=5.02 TeV. The correlation functions are measured as a function of relative azimuthal angle Δφ and pseudorapidity separation Δη for pairs of primary charged particles within the pseudorapidity interval |η|<0.9 and the transverse-momentum interval 1<pT<4 GeV/c. Flow coefficients are extracted for the long-range correlations (1.6<|Δη|<1.8) in various high-multiplicity event classes using the low-multiplicity template fit method. The method is used to subtract the enhanced yield of away-side jet fragments in high-multiplicity events. These results show decreasing flow signals toward lower multiplicity events. Furthermore, the flow coefficients for events with hard probes, such as jets or leading particles, do not exhibit any significant changes compared to those obtained from high-multiplicity events without any specific event selection criteria. The results are compared with hydrodynamic-model calculations, and it is found that a better understanding of the initial conditions is necessary to describe the results, particularly for low-multiplicity events.