Prepulse inhibition predicts spatial working memory performance in the inbred Roman high- and low-avoidance rats and in genetically heterogeneous NIH-HS rats: relevance for studying pre-attentive and cognitive anomalies in schizophrenia

Animal models of schizophrenia-relevant symptoms are increasingly important for progress in our understanding of the neurobiological basis of the disorder and for discovering novel and more specific treatments. Prepulse inhibition (PPI) and working memory, which are impaired in schizophrenic patients, are among the symptoms/processes modeled in those animal analogues. We have evaluated whether a genetically-selected rat model, the Roman high-avoidance inbred strain (RHA-I), displays PPI deficits as compared with its Roman low-avoidance (RLA-I) counterpart and the genetically heterogeneous NIH-HS rat stock. We have investigated whether PPI deficits predict spatial working memory impairments (in the Morris water maze; MWM) in these three rat types (Experiment 1), as well as in a separate sample of NIH-HS rats stratified according to their extreme (High, Medium, Low) PPI scores (Experiment 2). The results from Exp. 1 show that RHA-I rats display PPI and spatial working memory deficits compared to both RLA-I and NIH-HS rats. Likewise, in Exp. 2, “Low-PPI” NIH-HS rats present significantly impaired working memory with respect to “Medium-PPI” and “High-PPI” NIH-HS subgroups. Further support to these results comes from correlational, factorial and multiple regression analyses, which reveal that PPI is positively associated with spatial working memory performance. Conversely, cued learning in the MWM was not associated with PPI.Thus, using genetically-selected and genetically heterogeneous rats, the present study shows, for the first time, that PPI is a positive predictor of performance in a spatial working memory task. These results may have translational value for schizophrenia symptom research in humans, as they suggest that either by psychogenetic selection or by focusing on extreme PPI scores from a genetically heterogeneous rat stock, it is possible to detect a useful (perhaps “at risk”) phenotype to study cognitive anomalies linked to schizophrenia

Geographical inequalities in energy poverty in a Mediterranean city : Using small-area Bayesian spatial models

Altres ajuts: Ministerio de Economía y Competitividad; European Union, European Regional Development Fund (FEDER); CIBER Epidemiología Salud Pública (CIBERESP), sub-program "Energy Poverty and Health"; Fondo Social Europeo.Energy poverty (EP) is becoming an increasingly important problem in the urban contexts of southern Europe. In Barcelona, EP indicators are higher than those of the European Union and are strongly associated with poor health status and high use of health services and medication, becoming a major public health problem. EP is unevenly distributed in the population of Barcelona, according to axes of social stratification. However, its geographic distribution at the small-area level remains unknown because it cannot be directly estimated with the available information sources and commonly used methods. Therefore, the aim of this study was to analyze geographical inequalities in EP in Barcelona by estimating reliable small-area EP indicators and a composite indicator (index). We used a novel method that allowed us to obtain 6 EP indicators for the 73 Barcelona neighborhoods and an EP index from a principal component analysis of these indicators. We found major geographical inequalities in the distribution of EP in Barcelona. Many neighborhoods had significantly higher EP than the city average, and these areas made up 3 well-defined spatial clusters. Therefore, the estimated small-area indicators and index allowed identification of the most affected neighborhoods. These results indicate the need to prioritize these areas for local interventions to alleviate EP, and could also be used for policy making

Modelling viral encephalitis caused by herpes simplex virus 1 infection in cerebral organoids

Herpes simplex encephalitis is a life-threatening disease of the central nervous system caused by herpes simplex viruses (HSVs). Following standard of care with antiviral acyclovir treatment, most patients still experience various neurological sequelae. Here we characterize HSV-1 infection of human brain organoids by combining single-cell RNA sequencing, electrophysiology and immunostaining. We observed strong perturbations of tissue integrity, neuronal function and cellular transcriptomes. Under acyclovir treatment viral replication was stopped, but did not prevent HSV-1-driven defects such as damage of neuronal processes and neuroepithelium. Unbiased analysis of pathways deregulated upon infection revealed tumour necrosis factor activation as a potential causal factor. Combination of anti-inflammatory drugs such as necrostatin-1 or bardoxolone methyl with antiviral treatment prevented the damages caused by infection, indicating that tuning the inflammatory response in acute infection may improve current therapeutic strategies

Neurodegeneration in human brain organoids infected with herpes simplex virus type 1

Herpes simplex virus type 1 (HSV-1) infection of the nervous system may lead to brain damage, including neurodegeneration. However, lack of suitable experimental models hinders understanding molecular mechanisms and cell-type-specific responses triggered by HSV-1. Here, we infected human brain organoids with HSV-1. Known features of HSV-1 infection such as alteration of neuronal electrophysiology and induction of antisense transcription were confirmed. Full-length mRNA-sequencing revealed aberrant 3’ end formation and poly(A)-tail lengthening. Single-cell RNA-seq and spatial transcriptomics uncovered changes in the cellular composition of the infected organoids caused by viral replication and dysregulation of molecular pathways in cell-type specific manner. Furthermore, hallmarks of early neurodegeneration were observed, namely extracellular matrix disruption, STMN2 and TARDBP/TDP43 downregulation, and upregulation of the AD-related non-coding RNA BC200/BCYRN1. These hallmarks were weaker/absent when infecting with a mutant HSV-1 control. Together, our data indicate that brain organoids serve as a powerful model to study mechanisms of HSV-1-driven neurodegeneration

Spatio-temporal, optogenetic control of gene expression in organoids

Organoids derived from stem cells become increasingly important to study human development and to model disease. However, methods are needed to control and study spatio-temporal patterns of gene expression in organoids. To this aim, we combined optogenetics and gene perturbation technologies to activate or knock-down RNA of target genes, at single-cell resolution and in programmable spatio-temporal patterns. To illustrate the usefulness of our approach, we locally activated Sonic Hedgehog (SHH) signaling in an organoid model for human neurodevelopment. High-resolution spatial transcriptomic and single-cell analyses showed that this local induction was sufficient to generate stereotypically patterned organoids in three dimensions and revealed new insights into SHH's contribution to gene regulation in neurodevelopment. With this study, we propose optogenetic perturbations in combination with spatial transcriptomics as a powerful technology to reprogram and study cell fates and tissue patterning in organoids

Neoadjuvant Metformin Added to Systemic Therapy Decreases the Proliferative Capacity of Residual Breast Cancer

The proliferative capacity of residual breast cancer (BC) disease indicates the existence of partial treatment resistance and higher probability of tumor recurrence. We explored the therapeutic potential of adding neoadjuvant metformin as an innovative strategy to decrease the proliferative potential of residual BC cells in patients failing to achieve pathological complete response (pCR) after pre-operative therapy. We performed a prospective analysis involving the intention-to-treat population of the (Metformin and Trastuzumab in Neoadjuvancy) METTEN study, a randomized multicenter phase II trial of women with primary, non-metastatic (human epidermal growth factor receptor 2) HER2-positive BC evaluating the efficacy, tolerability, and safety of oral metformin (850 mg twice-daily) for 24 weeks combined with anthracycline/taxane-based chemotherapy and trastuzumab (arm A) or equivalent regimen without metformin (arm B), before surgery. We centrally evaluated the proliferation marker Ki67 on sequential core biopsies using visual assessment (VA) and an (Food and Drug Administration) FDA-cleared automated digital image analysis (ADIA) algorithm. ADIA-based pre-operative values of high Ki67 (>= 20%), but not those from VA, significantly predicted the occurrence of pCR in both arms irrespective of the hormone receptor status (p = 0.024 and 0.120, respectively). Changes in Ki67 in residual tumors of non-pCR patients were significantly higher in the metformin-containing arm (p = 0.025), with half of all patients exhibiting high Ki67 at baseline moving into the low-Ki67 (<20%) category after neoadjuvant treatment. By contrast, no statistically significant changes in Ki67 occurred in residual tumors of the control treatment arm (p = 0.293). There is an urgent need for innovative therapeutic strategies aiming to provide the protective effects of decreasing Ki67 after neoadjuvant treatment even if pCR is not achieved. Metformin would be evaluated as a safe candidate to decrease the aggressiveness of residual disease after neoadjuvant (pre-operative) systemic therapy of BC patients

Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests

Tropical forests face increasing climate risk1,2, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, Ψ50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk3–5, little is known about how these vary across Earth’s largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters Ψ50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both Ψ50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth–mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon6,7, with strong implications for the Amazon carbon sink

Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests

Funding: Data collection was largely funded by the UK Natural Environment Research Council (NERC) project TREMOR (NE/N004655/1) to D.G., E.G. and O.P., with further funds from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001) to J.V.T. and a University of Leeds Climate Research Bursary Fund to J.V.T. D.G., E.G. and O.P. acknowledge further support from a NERC-funded consortium award (ARBOLES, NE/S011811/1). This paper is an outcome of J.V.T.’s doctoral thesis, which was sponsored by CAPES (GDE 99999.001293/2015-00). J.V.T. was previously supported by the NERC-funded ARBOLES project (NE/S011811/1) and is supported at present by the Swedish Research Council Vetenskapsrådet (grant no. 2019-03758 to R.M.). E.G., O.P. and D.G. acknowledge support from NERC-funded BIORED grant (NE/N012542/1). O.P. acknowledges support from an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award. R.S.O. was supported by a CNPq productivity scholarship, the São Paulo Research Foundation (FAPESP-Microsoft 11/52072-0) and the US Department of Energy, project GoAmazon (FAPESP 2013/50531-2). M.M. acknowledges support from MINECO FUN2FUN (CGL2013-46808-R) and DRESS (CGL2017-89149-C2-1-R). C.S.-M., F.B.V. and P.R.L.B. were financed by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001). C.S.-M. received a scholarship from the Brazilian National Council for Scientific and Technological Development (CNPq 140353/2017-8) and CAPES (science without borders 88881.135316/2016-01). Y.M. acknowledges the Gordon and Betty Moore Foundation and ERC Advanced Investigator Grant (GEM-TRAITS, 321131) for supporting the Global Ecosystems Monitoring (GEM) network (gem.tropicalforests.ox.ac.uk), within which some of the field sites (KEN, TAM and ALP) are nested. The authors thank Brazil–USA Collaborative Research GoAmazon DOE-FAPESP-FAPEAM (FAPESP 2013/50533-5 to L.A.) and National Science Foundation (award DEB-1753973 to L. Alves). They thank Serrapilheira Serra-1709-18983 (to M.H.) and CNPq-PELD/POPA-441443/2016-8 (to L.G.) (P.I. Albertina Lima). They thank all the colleagues and grants mentioned elsewhere [8,36] that established, identified and measured the Amazon forest plots in the RAINFOR network analysed here. The authors particularly thank J. Lyod, S. Almeida, F. Brown, B. Vicenti, N. Silva and L. Alves. This work is an outcome approved Research Project no. 19 from ForestPlots.net, a collaborative initiative developed at the University of Leeds that unites researchers and the monitoring of their permanent plots from the world’s tropical forests [61]. The authros thank A. Levesley, K. Melgaço Ladvocat and G. Pickavance for ForestPlots.net management. They thank Y. Wang and J. Baker, respectively, for their help with the map and with the climatic data. The authors acknowledge the invaluable help of M. Brum for kindly providing the comparison of vulnerability curves based on PAD and on PLC shown in this manuscript. They thank J. Martinez-Vilalta for his comments on an early version of this manuscript. The authors also thank V. Hilares and the Asociación para la Investigación y Desarrollo Integral (AIDER, Puerto Maldonado, Peru); V. Saldaña and Instituto de Investigaciones de la Amazonía Peruana (IIAP) for local field campaign support in Peru; E. Chavez and Noel Kempff Natural History Museum for local field campaign support in Bolivia; ICMBio, INPA/NAPPA/LBA COOMFLONA (Cooperativa mista da Flona Tapajós) and T. I. Bragança-Marituba for the research support.Tropical forests face increasing climate risk1,2, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, Ψ50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk3-5, little is known about how these vary across Earth's largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters Ψ50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both Ψ50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth-mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon6,7, with strong implications for the Amazon carbon sink.Publisher PDFPeer reviewe

Bone histology provides insights into the life history mechanisms underlying dwarfing in hipparionins

Size shifts may be a by-product of alterations in life history traits driven by natural selection. Although this approach has been proposed for islands, it has not yet been explored in continental faunas. The trends towards size decrease experienced by some hipparionins constitute a good case study for the application of a life history framework to understand the size shifts on the continent. Here, we analysed bone microstructure to reconstruct the growth of some different-sized hipparionins from Greece and Spain. The two dwarfed lineages studied show different growth strategies. The Greek hipparions ceased growth early at a small size thus advancing maturity, whilst the slower-growing Spanish hipparion matured later at a small size. Based on predictive life history models, we suggest that high adult mortality was the likely selective force behind early maturity and associated size decrease in the Greek lineage. Conversely, we infer that resource limitation accompanied by high juvenile mortality triggered decrease in growth rate and a relative late maturity in the Spanish lineage. Our results provide evidence that different selective pressures can precipitate different changes in life history that lead to similar size shifts

Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: The pan-Amazonian HT dataset (Ψ 50, Ψ dry and HSM50) and branch wood density per species per site, as well as forest dynamic and climate data per plot presented in this study are available as a ForestPlots.net data package at https://forestplots.net/data-packages/Tavares-et-al-2023. Basal area weighted mean LMA is shown in Supplementary Table 2. Species stem wood density data were obtained from Global Wood Density database65,66. Species WDA data were extracted from ref. 45.Code availability: The codes to recreate the main analyses and the main figures presented in this study are available as a ForestPlots.net data package at https://forestplots.net/data-packages/Tavares-et-al-2023.Tropical forests face increasing climate risk, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, Ψ 50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk, little is known about how these vary across Earth’s largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters Ψ 50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both Ψ 50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth–mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon, with strong implications for the Amazon carbon sink