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IntroductionReceptor activity-modifying proteins (RAMPs) are known to modulate the pharmacology and function of several G-protein-coupled receptors (GPCRs), including the parathyroid hormone 1 receptor (PTH1R). However, the precise effects of different RAMPs on PTH1R signalling and trafficking remain poorly understood. This study investigated the impact of RAMP2 and RAMP3 on PTH1R function using a range of PTH and PTH-related protein (PTHrP)-derived ligands.MethodsWe employed FRET imaging to assess PTH1R interactions with RAMPs. Cell surface expression of PTH1R was evaluated in the presence of RAMPs. PTH1R-mediated cAMP accumulation, β-arrestin recruitment, and calcium signalling were measured in response to various ligands. Antibody-capture scintillation proximity assays were used to examine G-protein activation patterns.ResultsPTH1R preferentially interacted with RAMP2 and, to a lesser extent, RAMP3, but not with RAMP1. RAMP3 co-expression reduced cell surface expression of PTH1R. RAMP2 significantly enhanced PTH1R-mediated signalling responses to PTH (1-34), PTHrP (1-34), PTH (1-84), and PTH (1-17) analogue ZP2307, while RAMP3 co-expression attenuated or abolished these responses. Full-length PTHrP analogues exhibited lower potency and efficacy than PTHrP (1-34) in activating PTH1R. RAMP2 increased the potency and/or efficacy of these analogues, whereas RAMP3 reduced these responses. RAMP2 differentially modulated G-protein activation by PTH1R in a ligand-dependent manner, with PTH (1-34) and PTHrP (1-34) inducing distinct patterns of G-protein subtype activation.DiscussionThese findings highlight the complex role of RAMPs in regulating PTH1R signalling and trafficking, revealing differential effects of RAMP2 and RAMP3 on receptor function. The data suggest that targeting the PTH1R/RAMP2 complex may be a promising strategy for developing novel bone anabolic therapies by leveraging biased agonism and functional selectivity. Further research using physiologically relevant models is needed to elucidate the therapeutic potential of this approach.

This study delves into the Smart Readiness Indicator (SRI), an innovative measure designed to assess and enhance the smart capabilities of buildings across Europe. Addressing the critical question, ‘How can the SRI be effectively documented, made more accessible to European citizens, continuously monitored, and financially supported to enhance its adoption and under-standing?’ This research aims to bridge the gap between the conceptual framework of SRI and its practical implementation for the benefit of European citizens. The study introduces the SRI FAQ Initiative, a pivotal effort aimed at demystifying the SRI through the compilation and dissemination of essential questions and answers. The establishment of the SRI Observatory is another significant outcome, documenting the ongoing development of SRI and providing annual out-looks for future advancements. The research employs a multifaceted methodology, incorporating field research, extensive literature reviews, stakeholder interviews, and both digital and roundtable discussions.

ABSTRACTThermal systems, including those utilising solar energy and waste heat recovery, often have a mismatch between the energy supply and demand. It is crucial to implement a form of Thermal Energy Storage (TES) to effectively utilise the energy source. This study evaluates the thermal performance of a packed bed Latent Heat Thermal Energy Storage (LHTES) unit that is incorporated with a solar flat plate collector. The results show that the time required to charge the tank is reduced by 7% when the porosity is increased from 0.49 to 0.61, and also when the flow rate is raised from 2 to 4 kg/min, the charging time decreases by 2.5%. Additionally, studies were done to investigate the performances of different kinds of paraffin (RT30, RT28HC, WAX, RT58, and P56-58), and compare the heat capacities of each TES tank which resulted in the RT58 TES tank having the highest heat capacity.Abbreviations: BC: boundary conditions; HTF: heat transfer fluid; LHS: latent heat storage; LHTES: latent heat thermal energy storage; PCM: phase change material; SHS: sensible heat storage; TES: thermal energy storage

The continuous growth of urban populations has led to the persistent problem of traffic congestion, which imposes adverse effects on quality of life, such as commute times, road safety, and the local air quality. Advancements in Internet of Things (IoT) sensor technology have contributed to a plethora of new data streams regarding traffic conditions. Therefore, the recognition and prediction of traffic congestion patterns utilizing such data have become crucial. To that end, the integration of Machine Learning (ML) algorithms can further enhance Intelligent Transportation Systems (ITS), contributing to the smart management of transportation systems and effectively tackling traffic congestion in cities. This study seeks to assess a wide range of models as potential solutions for an ML-based multi-step forecasting approach intended to improve traffic congestion prediction, particularly in areas with limited historical data. Various interpretable predictive algorithms, suitable for handling the complexity and spatiotemporal characteristics of urban traffic flow, were tested and eventually shortlisted based on their predictive performance. The forecasting approach selects the optimal model in each step to maximize the accuracy. The findings demonstrate that, in a 24 h step prediction, variating Ensemble Tree-Based (ETB) regressors like the Light Gradient Boosting Machine (LGBM) exhibit superior performances compared to traditional Deep Learning (DL) methods. Our work provides a valuable contribution to short-term traffic congestion predictions and can enable more efficient scheduling of daily urban transportation.

The scope of this study is the investigation of the thermal performance of building-integrated solar flat collectors with a uniform and multiple riser structure. The effect of dynamic operating parameters such as the environmental temperature, solar radiation, the inclination angle and further model modifications to the fluid inlet, outlet and riser are studied. Numerical calculations were carried out using Finite Element (FE) analysis. Three-dimensional transient models were developed to calculate the thermal performance of the investigated objects. The study revealed increased efficiency for the multiple-riser configuration. Under all boundary conditions, the highest fluid temperatures occur in the south orientation during autumn and winter and in the west during spring and summer. The thermal assessment comparison between the roof installed and vertical solar collectors were performed, and the differences throughout the slope angles were distinguished. The results showed that a building-integrated solar system acted as a shield barrier, and provided heat to the building structure.

Lignin constitutes the sole renewable aromatic resource found in abundance on Earth and does not call into question the ethics of diverting land from food to energy production. In view of that, the potential of lignocellulosic biomass in promoting the Circular Economy and Bioeconomy concepts in future biorefinery operations is widely acknowledged. Biorefineries can convert lignocellulosic biomass into high-value products, lessen their environmental effect, and hasten the advent of a sustainable and renewable future by incorporating cutting-edge technologies and doing thorough Life Cycle Assessment analysis. However, converting lignin into added-value products is a challenging field from technological, environmental, and economic perspectives. This work set out to determine the most critical environmental aspects expected to provide reliable evidence in support of lignin valorisation routes that enable the production of value-added products and bioenergy. Findings provide the necessary knowledge for decision-making in biorefineries aligned with the Circular Bioeconomy concept, like how decision-making relating to future biorefineries is facilitated. Highlights Environmental burdens of lignin-derived products valorisation due to complex lignin structure A limited number of LCA studies on the valorisation of lignin to added-value products Future lignin-based biorefineries development should be assessed using holistic, sustainable approaches LCA methodologies on environmental performance of promising lignin valorisation routes Controversial aspects of lignin valorisation under the Circular Bioeconomy concept Raised concerns as a result of the lignin fraction expected high demand Identified controversial environmental aspects linking lignin valorisation to adverse impacts

Abstract WDR11, a gene associated with Kallmann syndrome, is important in reproductive system development but molecular understanding of its action remains incomplete. We previously reported that Wdr11-deficient embryos exhibit defective ciliogenesis and developmental defects associated with Hedgehog (HH) signalling. Here we demonstrate that WDR11 is required for primordial germ cell (PGC) development, regulating canonical and noncanonical HH signalling in parallel. Loss of WDR11 disrupts PGC motility and proliferation driven by the cilia-independent, PTCH2/GAS1-dependent noncanonical HH pathway. WDR11 modulates the growth of somatic cells surrounding PGCs by regulating the cilia-dependent, PTCH1/BOC-dependent canonical HH pathway. We reveal that PTCH1/BOC or PTCH2/GAS1 receptor context dictates SMO localisation inside or outside of cilia, respectively, and loss of WDR11 affects the signalling responses of SMO in both situations. We show that GAS1 is induced by PTCH2-specific HH signalling, which is lost in the absence of WDR11. We also provide evidence supporting a role for WDR11 in ciliogenesis through regulation of anterograde intraflagellar transport potentially via its interaction with IFT20. Since WDR11 is a target of noncanonical SMO signalling, WDR11 represents a novel mechanism by which noncanonical and canonical HH signals communicate and cooperate.

According to the European Energy Efficiency Directive for Buildings, member states are required to develop long-term strategies to adopt more sustainable, secure, and decarbonized energy systems in buildings by 2050. In this line of approach, an optional common regime has been established to define and calculate the smart readiness of buildings and assess their ability to adapt their operation to the needs of the occupants and the network. Thus, the smart readiness indicator (SRI) emerged, which assesses technological readiness by examining the presence and evaluation of the functionality level of various smart services, aiming at energy savings, the ability of the building to respond to users’ needs, and energy flexibility. This paper focuses on examining the SRI calculation methodology’s application to an office building, which is currently being deeply renovated. Initially, there is an analysis of the SRI, its calculation methodology, and its goals. This is followed by the practical calculation part of the SRI for a typical office building located in Greece and belonging to the climate zone of southern Europe. The results indicate that the SRIs application is not a straightforward issue since parameters that need to be considered are not regulated to the same degree. On the other hand, SRI can provide a stimulus for exploiting the renovation potential of buildings, precisely by integrating the various aspects and linking those to the use of innovative technologies.

Abstract The heterogeneity in recovery outcomes for individuals with First Episode Psychosis (FEP) calls for a strong evidence base to inform practice at an individual level. Between 19–89% of young people with FEP have an incomplete recovery despite gold-standard evidence-based treatments, suggesting current service models, which adopt a ‘one-size fits all’ approach, may not be addressing the needs of many young people with psychosis. The lack of consistent terminology to define key concepts such as recovery and treatment resistance, the multidimensional nature of these concepts, and common comorbid symptoms are some of the challenges faced by the field in delineating heterogeneity in recovery outcomes. The lack of robust markers for incomplete recovery also results in potential delay in delivering prompt, and effective treatments to individuals at greatest risk. There is a clear need to adopt a stratified approach to care where interventions are targeted at subgroups of patients, and ultimately at the individual level. Novel machine learning, using large, representative data from a range of modalities, may aid in the parsing of heterogeneity, and provide greater precision and sophistication in identifying those on a pathway to incomplete recovery.

Abstract The Ciliary Adhesion (CA) complex forms in close association with the basal bodies of cilia during the early stages of ciliogenesis and is responsible for mediating complex interactions with the actin networks of multiciliated cells (MCCs). However, its precise localization with respect to basal body accessory structures and the interactions that lead to its establishment in MCCs are not well understood. Here, we studied the distribution of the CA proteins using super-resolution imaging and possible interactions with the microtubule network. The results of this study reveal that the apical CA complex forms at the distal end of the basal foot and depends on microtubules. Our data also raise the possibility that CAs may have additional roles in the regulation of the organization of the microtubule network of MCCs.

Prospective graduate students' noncognitive attributes are commonly evaluated as a part of a holistic review of their admission applications. Yet it is difficult to determine which noncognitive attributes are considered by those who evaluate graduate admissions applications and what approaches they take to measure applicants' noncognitive attributes. It is even less clear to what degree prospective graduate students understand how they are evaluated for graduate admissions and how the evaluation of their noncognitive attributes factor into admissions decisions. Drawing on surveys of graduate enrollment management (GEM) professionals and prospective graduate students in the United States, our study investigated the noncognitive attributes prospective graduate students and GEM professionals deem important to success in graduate school and the application components each group believes demonstrate those attributes. Results suggest that some alignment exists between the perspectives of prospective graduate students and GEM professionals on the noncognitive attributes most important for completing a graduate program of study. We share recommendations for improving the agreement between prospective graduate students and GEM professionals including the need for more explicit and transparent communication about how graduate admissions applications are evaluated, which is of particular importance as admissions processes forgo the consideration of applicants' race.

Purpose The aim of this review was to systematically summarize the current literature on corticospinal excitation and muscle activity in restless legs syndrome (RLS) patients during daytime and diurnal activities. Three models of muscle activation in RLS directed this review: (i) evoked neuromuscular activation; (ii) sensory reflex responsiveness; (iii) voluntary muscle activation. Methods A literature search was conducted in PubMed and Google Scholar, and 51 articles met the primary inclusion criteria. After a quality analysis, a total 13 articles were deemed of sufficient quality for data extraction. Results Three studies on evoked neuromuscular activation demonstrated increased motor excitability associated with RLS. Sensory reflex responsiveness studies in RLS patients revealed increased reflex responsiveness, indicating increased spinal excitability and a possible dysfunction in afferent inhibition. Voluntary muscle activation studies showed both diurnal muscle electromyography abnormalities and an increased circadian variation in the musculature of the lower leg in RLS patients. Conclusions Although a number of mechanisms have been evaluated increasing the understanding of RLS, few studies have evaluated RLS during daytime and diurnal muscle activity in patients with RLS. Furthermore, potential associations with the circadian rhythm have not been thoroughly investigated, nor have methodologies been combined. Future research should aim to establish differences in muscle activity of RLS patients and associate these differences with the duration and severity of symptoms. Suggestions for further studies are provided.

Background: Previous research suggests that there may be similarities in structural brain changes seen in patients with depression and psychosis compared to healthy controls. However, there is yet no systematic review collating studies comparing structural brain changes in depression and psychosis. Establishing shared and specific neuroanatomical features could aid the investigation of underlying biological processes. Aims: To identify structural neuroimaging similarities and differences between patients with depression and psychosis. Method: We searched PubMed, PsychInfo, Embase, NICE Evidence, Medline and the Cochrane Library were searched from inception to 30/06/2021 using relevant subject headings (controlled vocabularies) and search syntax. Papers were assessed for quality using the Newcastle-Ottawa Scale. Results: Five-hundred and twenty papers were retrieved, seven met inclusion criteria. In narrative collation of results, grey matter volume (GMV) reductions were found in the medial frontal gyrus (MFG), hippocampus and left-sided posterior subgenual prefrontal cortex in both psychosis and depression. GMV reductions affected more brain regions in psychosis, including in the insula and thalamus. White matter volume (WMV) decline was found in both depression and psychosis. Reduced fractional anisotropy (FA) was more commonly seen in depression. Conclusions: Our results suggest potential transdiagnostic patterns of GMV and WMV reductions in areas including the MFG, hippocampus, and left-sided posterior subgenual prefrontal cortex. These could be investigated as a future biomarker of transdiagnostic signature across mental illnesses. However, due to the limited number and poor quality of studies future research in large samples and harmonised imaging data is first needed.

Neural tube closure is a fundamental process during vertebrate embryogenesis, which leads to the formation of the central nervous system. Defective neural tube closure leads to neural tube defects which are some of the most common human birth defects. While the intrinsic morphogenetic events shaping the neuroepithelium have been studied extensively, how tissues mechanically coupled with the neural plate influence neural tube closure remains poorly understood. Here, using Xenopus laevis embryos, live imaging in combination with loss of function experiments and morphometric analysis of fixed samples we explore the reciprocal mechanical communication between the neural plate and the somitic mesoderm and its impact on tissue morphogenesis. We show that although somitic mesoderm convergent extension occurs independently from neural plate morphogenesis neural tube closure depends on somitic mesoderm morphogenesis. Specifically, impaired somitic mesoderm remodelling results in defective apical constriction within the neuroepithelium and failure of neural tube closure. Last, our data reveal that mild abnormalities in somitic mesoderm and neural plate morphogenesis have a synergistic effect during neurulation, leading to severe neural tube closure defects. Overall, our data reveal that defective morphogenesis of tissues mechanically coupled with the neural plate can not only drastically exacerbate mild neural tube defects that may arise from abnormalities within the neural tissue but can also elicit neural tube defects even when the neural plate is itself free of inherent defects.

In today’s digital age, mobile applications have become invaluable tools for enhancing accessibility and inclusivity, especially for individuals with disabilities. This study focuses on the landscape of accessibility apps designed to facilitate inclusivity for disabled individuals in buildings. By investigating current trends, strengths, weaknesses, and their impact on independence and quality of life, the research aims to shed light on the state of these apps and identify areas for future development. To achieve these objectives, a multi-faceted approach was employed, encompassing a literature review and app categorization. The study emphasizes the necessity for a common evaluation and certification framework to ensure consistency, reliability, and transparency in assessing the effectiveness of accessibility apps in the built environment. Such a framework would instill user trust, support informed decision-making, and stimulate innovation in this field. The findings of this research contribute to the advancement of inclusive design practices, serving as a valuable resource for developers, policymakers, and disabled individuals seeking effective tools to enhance accessibility. By fostering an inclusive society where disabled individuals can fully navigate and participate, this study aligns with the broader goal of creating a more inclusive and equitable world.

This article provides a thorough bibliometric analysis of significant research trends in sustainability from 1988 until now, focusing on sustainable, healthy and digital buildings and cities. It exemplifies how research emphasis has shifted from explicit ecological investigations to nature-based solutions and city greening programs, with a rising interest in the many responsibilities of urban stakeholders in attaining sustainability. Despite weak integration at the literature and author cooperation levels, the “healthy buildings and cities” topic indicates promise for multidisciplinary integration. The “digital buildings and cities” topic, on the other hand, presents a more particular concern with strong cross-cluster collaboration and significant integration possibilities. Global relevance has been demonstrated through research on “sustainable buildings and cities,” mainly in journal papers. This topic’s study clusters show remarkable synergy across management, transportation, ecology, remote sensing and environmental engineering domains. In comparison to “healthy buildings and cities” and “digital buildings and cities” topics, the study of “sustainable buildings and cities” demonstrates a deeper level of interdisciplinary integration, highlighting the significant potential for further exploration within sustainability science research. This study emphasizes the ongoing worldwide relevance of sustainability science research and identifies significant opportunities for multidisciplinary integration across the investigated subjects.

As federal strategic plans prioritize increasing diversity within the biomedical workforce, and STEM training and outreach programs seek to recruit and retain students from historically underrepresented populations, there is a need for interrogation of traditional demographic descriptors and careful consideration of best practices for obtaining demographic data. To accelerate this work, equity-focused researchers and leaders from STEM programs convened to examine approaches for measuring demographic variables. Gender, race/ethnicity, disability, and disadvantaged background were prioritized given their focus by federal funding agencies. Categories of sex minority, sexual (orientation) minority, and gender minority (SSGM) should be included in demographic measures collected by STEM programs, consistent with recommendations from White House Executive Orders and federal reports. Our manuscript offers operationalized phrasing for demographic questions and recommendations for use across student-serving programs. Inclusive demographics permit the identification of individuals who are being excluded, marginalized, or improperly aggregated, increasing capacity to address inequities in biomedical research training. As trainees do not enter training programs with equal access, accommodations, or preparation, inclusive demographic measures can welcome trainees and inform a nuanced set of program outcomes that facilitate research on intersectionality to support the recruitment and retention of underrepresented students in biomedical research.

A water quality monitoring system in hydroponics with a Total Dissolved Solid Sensor (TDS) equipped with the Arduino UNO microcontroller has been developed. The TDS SEN0244 sensor read the water sensitivity, which will display the value of the reading on the LCD. Furthermore, if the output is less than 2.30 Volts or 1000 ppm, the buzzer will sound once, and the dosing pump will rotate to automatically add nutrients A and B. The buzzer will sound twice if the output is more than 2.40 Volts or 1200 ppm. When reading the sensitivity of water (well water) with a water value of 400 ppm, the relevant results were obtained, namely, 1000 - 1200 ppm when 4 - 5 mL of the nutrient solution was added to water with a capacity of fewer than 6 liters. The appropriate value was obtained when testing the TDS sensor on several water samples. However, in the salt and soapy water samples, the voltage value reading was unstable or experienced an error. Implementing this system is expected to make it easier for the community, especially farmers, to cultivate hydroponic plants.

Abstract Negative symptoms occur frequently in individuals at clinical high risk (CHR) for psychosis and contribute to functional impairments. The aim of this study was to predict negative symptom severity in CHR after 9 months. Predictive models either included baseline negative symptoms measured with the Structured Interview for Psychosis-Risk Syndromes (SIPS-N), whole-brain gyrification, or both to forecast negative symptoms of at least moderate severity in 94 CHR. We also conducted sequential risk stratification to stratify CHR into different risk groups based on the SIPS-N and gyrification model. Additionally, we assessed the models’ ability to predict functional outcomes in CHR and their transdiagnostic generalizability to predict negative symptoms in 96 patients with recent-onset psychosis (ROP) and 97 patients with recent-onset depression (ROD). Baseline SIPS-N and gyrification predicted moderate/severe negative symptoms with significant balanced accuracies of 68 and 62%, while the combined model achieved 73% accuracy. Sequential risk stratification stratified CHR into a high (83%), medium (40–64%), and low (19%) risk group regarding their risk of having moderate/severe negative symptoms at 9 months follow-up. The baseline SIPS-N model was also able to predict social (61%), but not role functioning (59%) at above-chance accuracies, whereas the gyrification model achieved significant accuracies in predicting both social (76%) and role (74%) functioning in CHR. Finally, only the baseline SIPS-N model showed transdiagnostic generalization to ROP (63%). This study delivers a multimodal prognostic model to identify those CHR with a clinically relevant negative symptom severity and functional impairments, potentially requiring further therapeutic consideration.

The Smart Readiness Indicator (SRI) is an assessment scheme for the intelligence of buildings, which was introduced by the European Commission in the directive for the Energy Performance of Buildings in 2018. Since its introduction, many activities related to the maturation and employment of the SRI have been initiated. One of the adaptation needs of the SRI, revealed through public consultation with relevant stakeholders, is the requirement for a tailored SRI for different types of buildings. The aim of this study is to analyze possible scenarios to optimize the smartness performance, as addressed by the SRI score, in educational buildings. The subject of this study concerned campus buildings of the Kaunas University of Technology, in Lithuania. For the definition of the SRI, the calculation sheet developed by the European Commission was used. The effect of the improvements in the smartness performance of buildings on their energy efficiency was examined with the use of a whole-building, BIM-based energy assessment tool (IDA-ICE). The findings of this study revealed that despite the improvement in the automation and control levels of the building heating system, the maximum SRI values achieved deviate significantly by a high-smartness level. This study revealed the importance of services at a city level towards achieving the optimal smartness levels at a building unit level. It also delivered useful findings related to the linkage between energy and smartness performance of a building. The policy implication of the study findings also covers topics relevant to utilities management at a district level, as well as on the need for tailored SRI services catalogs for different types of buildings.

Abstract Background Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase that is overexpressed or activated in several advanced-stage solid cancers. It is known to play both kinase-dependent and -independent roles in promoting tumor progression and metastasis. Numerous inhibitors, targeting either the enzymatic or scaffolding activities of FAK have been generated, with varying degree of success. Here, we describe a novel approach to site-specifically target both kinase-dependent and -independent FAK functions at focal adhesions (FAs), the primary sites at which the kinase exerts its activity. Methods We took advantage of the well-characterized interactions between the paxillin LD motifs and the FAK FAT domain and generated a polypeptide (LD2-LD3-LD4) expected to compete with interactions with paxillin. Co-immunoprecipitation experiments were performed to examine the interaction between the LD2-LD3-LD4 polypeptide and FAK. The effects of LD2-LD3-LD4 in the localization and functions of FAK, as well as FA composition, were evaluated using quantitative immunofluorescence, cell fractionation, FA isolation and Western Blot analysis. Live cell imaging, as well as 2-D migration and cell invasion assays were used to examine the effects on FA turnover and tumor cell migration and invasion. Results Expression of the LD2-LD3-LD4 polypeptide prevents FAK localization at FAs, in a controlled and dose-dependent manner, by competing with endogenous paxillin for FAK binding. Importantly, the LD2-LD3-LD4 peptide did not otherwise affect FA composition or integrin activation. LD2-LD3-LD4 inhibited FAK-dependent downstream integrin signaling and, unlike existing inhibitors, also blocked FAK’s scaffolding functions. We further show that LD2-LD3-LD4 expression markedly reduces FA turnover and inhibits tumor cell migration and invasion. Finally, we show that dimers of a single motif, linked through a flexible linker of the proper size, are sufficient for the displacement of FAK from FAs and for inhibition of tumor cell migration. This work raises the possibility of using a synthetic peptide as an antimetastatic agent, given that effective displacement of FAK from FAs only requires dimers of a single LD motif linked by a short flexible linker. Conclusion In conclusion, these results suggest that FAK displacement from FAs is a promising new strategy to target critical processes implicated in cancer progression and metastasis. Video abstract. Graphical abstract

In this paper, we analyze the relevance of the use of the shallow water model and the Boussinesq model to simulate tsunamis generated by a landslide. In a first part, we determine if the two models are able to reproduce waves generated by a landslide. Each model has drawbacks but it seems that it is possible to use them together to improve the simulations. In a second part we try to recover the landslide displacement from the generated wave. This problem is formulated as a minimization problem and we limit the number of parameters to determine assuming that the bottom can be well described by an empirical law.

Wildlife biodiversity is essential for healthy, resilient and sustainable ecosystems. For biologists, this diversity also represents a treasure trove of genetic, molecular and developmental mechanisms that deepen our understanding of the origins and rules of life. However, the rapid decline in biodiversity reported recently foreshadows a potentially catastrophic collapse of many important ecosystems and the associated irreversible loss of many forms of life on our planet. Immediate action by conservationists of all stripes is required to avert this disaster. In this Spotlight, we draw together insights and proposals discussed at a recent workshop hosted by Revive & Restore, which gathered experts to discuss how stem cell technologies can support traditional conservation techniques and help protect animal biodiversity. We discuss reprogramming, in vitro gametogenesis, disease modelling and embryo modelling, and we highlight the prospects for leveraging stem cell technologies beyond mammalian species.