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Abstract Neutrophilia and an elevated neutrophil:lymphocyte ratio are both characteristic features of severe COVID-19 infection. However, functional neutrophil responses have been poorly investigated in this setting. We utilised a novel PMA-based stimulation assay to determine neutrophil-derived reactive oxygen species (ROS) generation in patients with severe COVID-19 infection, non-COVID related sepsis and healthy study participants. ROS production was markedly elevated in COVID-19 patients with median values ninefold higher than in healthy controls and was particularly high in patients on mechanical ventilation. ROS generation correlated strongly with neutrophil count and elevated levels were also seen in patients with non-COVID related sepsis. Relative values, adjusted for neutrophil count, were high in both groups but extreme low or high values were seen in two patients who died shortly after testing, potentially indicating a predictive value for neutrophil function. Our results show that the high levels of neutrophils observed in patients with COVID-19 and sepsis exhibit functional capacity for ROS generation. This may contribute to the clinical features of acute disease and represents a potential novel target for therapeutic intervention.

Although coasts are frequently seen as at the frontline of near-future environmental risk, there is more to the understanding of the future of coastal environments than a simple interaction between increasing hazards (particularly related to global sea level rise) and increasing exposure and vulnerability of coastal populations. The environment is both multi-hazard and regionally differentiated, and coastal populations, in what should be seen as a coupled social–ecological–physical system, are both affected by, and themselves modify, the impact of coastal dynamics. As the coupled dance between human decisions and coastal environmental change unfolds over the coming decades, transdisciplinary approaches will be required to come to better decisions on identifying and following sustainable coastal management pathways, including the promotion of innovative restoration activities. Inputs from indigenous knowledge systems and local communities will be particularly important as these stakeholders are crucial actors in the implementation of ecosystem-based mitigation and adaptation strategies.

The socioeconomics of the Anthropocene is exposing coastal regions to multiple pressures, including climate change hazards, resource degradation, urban development and inequality. Tourism is often raised as either a panacea to, or exacerbator of, such threats to ecosystems and sustainable livelihoods. To better understand the impacts of tourism on coastal areas, Scopus and Web of Science databases were searched for the top 100 cited papers on coastal tourism. Web of Science suggested ‘highly cited’ papers were also included to allow for more recent high-impact papers. Of the papers retrieved, 44 focused on the impacts of tourism. Social/cultural and environmental impacts were viewed as mostly negative, while economic impacts were viewed as mostly positive but only of actual benefit to a few. In addition, when compared with recent whole-of-sector reviews and reports it was evident that coastal tourism is increasingly a global enterprise dominated by large corporations that leverage various interests across local to transnational scales. Through this global enterprise, even the positive economic benefits identified were overshadowed by a broader system of land and property development fuelling local wealth inequity and furthering the interests of offshore beneficiaries. Only two highly cited papers discussed tourism within a broader context of integrated coastal zone management, suggesting that tourism is mostly assessed as a discrete sector within the coastal zone and peripheral to other coastal management considerations or the global tourism sector as a whole. The findings have relevance to the holistic management of coasts, coastal tourism and the achievement of sustainable development goals in a way that considers the increasing threats from coastal hazards, resource extraction and urbanisation, as well as the pervasive impacts of international business systems from local to global scales.

Whilst there is little argument that coasts are on the frontline when it comes to the impacts of near-future global environmental change, is there a need for yet another coastal journal? Emphatically ‘yes’. There is an unfilled niche here for a forum that promotes and presents cross-disciplinary research, from fundamental science to impact-orientated approaches. We wish to see a journal that informs pathways away from unsustainable practices towards more socially just and equitable futures for the world’s coastlines and their communities. We set out below some of the questions that arise when articulating this pathway, using the high-level categories in the journal’s topic map as some of the stepping stones that will be encountered along the way.

Photoacoustic imaging (PAI) takes advantage of both optical and ultrasound imaging properties to visualize optical absorption with high resolution and contrast. Photoacoustic microscopy (PAM) is usually categorized with all-optical microscopy techniques such as optical coherence tomography or confocal microscopes. Despite offering high sensitivity, novel imaging contrast, and high resolution, PAM is not generally an all-optical imaging method unlike the other microscopy techniques. One of the significant limitations of photoacoustic microscopes arises from their need to be in physical contact with the sample through a coupling media. This physical contact, coupling, or immersion of the sample is undesirable or impractical for many clinical and pre-clinical applications. This also limits the flexibility of photoacoustic techniques to be integrated with other all-optical imaging microscopes for providing complementary imaging contrast. To overcome these limitations, several non-contact photoacoustic signal detection approaches have been proposed. This paper presents a brief overview of current non-contact photoacoustic detection techniques with an emphasis on all-optical detection methods and their associated physical mechanisms.

There is a disconnect between ambition and achievement of the UN Agenda 2030 and associated Sustainable Development Goals that is especially apparent when it comes to ocean and coastal health. While scientific knowledge is critical to confront and resolve contradictions that reproduce unsustainable practices at the coast and to spark global societal change toward sustainability, it is not enough in itself to catalyze large scale behavioral change. People learn, understand and generate knowledge in different ways according to their experiences, perspectives, and culture, amongst others, which shape responses and willingness to alter behavior. Historically, there has been a strong connection between art and science, both of which share a common goal to understand and describe the world around us as well as provide avenues for communication and enquiry. This connection provides a clear avenue for engaging multiple audiences at once, evoking emotion and intuition to trigger stronger motivations for change. There is an urgent need to rupture the engrained status quo of disciplinary divisions across academia and society to generate transdisciplinary approaches to global environmental challenges. This paper describes the evolution of an art-science collaboration (Catching a Wave) designed to galvanize change in the Anthropocene era by creating discourse drivers for transformations that are more centered on society rather than the more traditional science-policy-practice nexus.

In this paper, we consider the Schwartz’s one-factor model for a storable commodity and a futures contract on that commodity. We introduce the analysis of asymptotic arbitrage in storable commodity models by proving that the futures prices process allows asymptotic exponential arbitrage with geometric decaying failure probability. Next, we find by comparison that, under some similar conditions, our result is a corresponding commodity assets (stronger) version of Föllmer and Schachermayer’s result stated in the modeling setting of geometric Ornstein-Uhlenbeck process for financial security assets.

After the dawn of the August 2007 financial crisis, banks became more aware of financial risk leading to the appearance of nonnegligible spreads between LIBOR and OIS rates and also between LIBOR of different tenors. This consequently led to the birth of multicurve models. This study establishes a new model; the multicurve cross-currency LIBOR market model (MCCCLMM). The model extends the initial LIBOR Market Model (LMM) from the single-curve cross-currency economy into the multicurve cross-currency economy. The model incorporates both the risk-free OIS rates and the risky forward LIBOR rates of two different currencies. The established model is suitable for pricing different quanto interest rate derivatives. A brief illustration is given on the application of the MCCCLMM on pricing quanto caplets and quanto floorlets using a Black-like formula derived from the MCCCLMM.

In this article, we are interested in developing an alternative estimation method of the parameters of the hybrid log-Poisson regression model. In our previous paper, we have proposed a hybrid log-Poisson regression model where we have derived the analytical expression of the fuzzy parameters. We found that the hybrid model provide better results than the classical log-Poisson regression model according to the mean square error prediction and the goodness of fit index. However, nowhere we have taken into account the optimal value of h(α-cut) which is of greatest importance in fuzzy regressions literature. In this paper, we provide an alternative estimation method of our hybrid model using a quadratic optimization program and the optimized h-value (α-cut). The expected value of fuzzy number is used as a defuzzification procedure to move from fuzzy values to crisp values. We perform the hybrid model with the alternative estimation we are suggesting on two different numerical data to predict incremental payments in loss reserving. From the mean square error prediction, we prove that the alternative estimation of the new hybrid model with an optimized h-value predicts incremental payments better than the classical log-Poisson regression model as well as the same hybrid model with analytical estimation of parameters. Hence we have optimized the outstanding loss reserves.

This article synthesizes and compares environmental governance theories. For each theory we outline its main tenets, claims, origin, and supporting literature. We then group the theories into focused versus combinatory frameworks for comparison. The analysis resonates with many types of ecosystems; however, to make it more tangible, we focus on coastal systems. First, we characterize coastal governance challenges and then later link salient research questions arising from these challenges to the theories that may be useful in answering them. Our discussion emphasizes the usefulness of having a diverse theoretical toolbox, and we argue that if governance analysts are more broadly informed about the theories available, they may more easily engage in open-minded interdisciplinary collaboration. The eight theories examined are the following: polycentricity, network governance, multilevel governance, collective action, governmentality (power / knowledge), adaptive governance, interactive governance theory (IGT), and evolutionary governance theory (EGT). Polycentricity and network governance both help examine the links or connections in governance processes. Polycentricity emphasizes structural configurations at a broader level, and network governance highlights agency and information flow within and between individuals or organizations. Collective action theory is helpful for examining community level governance, and helps analyze variables hindering or enabling self-organization and shared resource outcomes. In contrast, multilevel governance helps understand governance integration processes between localities, regions, and states across administrative, policy, or legal dimensions. Governmentality is helpful for understanding the role of discourse, power, knowledge, and narratives in governance, such as who creates them and who becomes governed by them with what effect. Adaptive governance helps analyze the links between context, change, and resilience. IGT helps examine the interdependencies between the systems being governed and the governing systems. EGT is helpful for unpacking how coevolutionary processes shape governance and the options for change.

Photoacoustic imaging (PAI) is an emerging imaging technique that bridges the gap between pure optical and acoustic techniques to provide images with optical contrast at the acoustic penetration depth. The two key components that have allowed PAI to attain high-resolution images at deeper penetration depths are the photoacoustic signal generator, which is typically implemented as a pulsed laser and the detector to receive the generated acoustic signals. Many types of acoustic sensors have been explored as a detector for the PAI including Fabry−Perot interferometers (FPIs), micro ring resonators (MRRs), piezoelectric transducers, and capacitive micromachined ultrasound transducers (CMUTs). The fabrication technique of CMUTs has given it an edge over the other detectors. First, CMUTs can be easily fabricated into given shapes and sizes to fit the design specifications. Moreover, they can be made into an array to increase the imaging speed and reduce motion artifacts. With a fabrication technique that is similar to complementary metal-oxide-semiconductor (CMOS), CMUTs can be integrated with electronics to reduce the parasitic capacitance and improve the signal to noise ratio. The numerous benefits of CMUTs have enticed researchers to develop it for various PAI purposes such as photoacoustic computed tomography (PACT) and photoacoustic endoscopy applications. For PACT applications, the main areas of research are in designing two-dimensional array, transparent, and multi-frequency CMUTs. Moving from the table top approach to endoscopes, some of the different configurations that are being investigated are phased and ring arrays. In this paper, an overview of the development of CMUTs for PAI is presented.

Abstract Background Loss of communication with loved ones and carers is one of the most isolating and debilitating effects of many neurological disorders. Assistive technology (AT) supports individuals with communication, but the acceptability of AT solutions is highly variable. In this paper a novel ear based control method of AT, the concept of ’EarSwitch’, is presented. This new approach is based on detecting ear rumbling, which is the voluntary contraction of the tensor tympani muscle (TTM), resulting in observable movement of the eardrum and a dull rumbling sound. ’EarSwitch’ has the potential to be a discreet method that can complement existing AT control methods. However, only a subset of the population can ear rumble and little is known about the ability of rumbling in populations with neurological disorders. Methods To explore the viability of the ’EarSwitch’ concept as an AT control method we conducted in-depth online surveys with (N=1853) respondents from the general population and (N=170) respondents with self-declared neurological disorders including Motor Neurone Disease (MND) and Multiple Sclerosis (MS).This is the largest ever study to explore ear rumbling and the first to explore whether rumbling is preserved among individuals with neurological disorders. In addition, we validated rumbling, and investigated usability of the ’EarSwitch’ concept as a control input, using in-person otoscopic examination with a subset of participants. Results A significant proportion of the population with neurological disorders could benefit from ’EarSwitch’ controllable AT. The upper bound prevalence of the ability to rumble without accompanying movements was 55% in the general population, 38% in the neurological population, and 20% of participants with MND (N=95) reported this ability. During the validation procedure, participants achieved high accuracy in self-reporting the ability to rumble (80%) and proved concept of using the ’EarSwitch’ method to control a basic interface. Discussion ’EarSwitch’ is a potential new AT control method control, either by itself or as a supplement to other existing methods. Results demonstrate self-reported ear rumbling is present among patients with different neurological disorders, including MND. Further research should explore how well the ability to rumble is preserved in different types and stages of neurological disorders.

Abstract Background Eukaryotic cells are highly compartmentalized by a variety of organelles that carry out specific cellular processes. The position of these organelles within the cell is elaborately regulated and vital for their function. For instance, the position of lysosomes relative to the nucleus controls their degradative capacity and is altered in pathophysiological conditions. The molecular components orchestrating the precise localization of organelles remain incompletely understood. A confounding factor in these studies is the fact that organelle positioning is surprisingly non-trivial to address e.g., perturbations that affect the localization of organelles often lead to secondary phenotypes such as changes in cell or organelle size. These phenotypes could potentially mask effects or lead to the identification of false positive hits. To uncover and test potential molecular components at scale, accurate and easy-to-use analysis tools are required that allow robust measurements of organelle positioning. Results Here, we present an analysis workflow for the faithful, robust, and quantitative analysis of organelle positioning phenotypes. Our workflow consists of an easy-to-use Fiji plugin and an R Shiny App. These tools enable users without background in image or data analysis to (1) segment single cells and nuclei and to detect organelles, (2) to measure cell size and the distance between detected organelles and the nucleus, (3) to measure intensities in the organelle channel plus one additional channel, (4) to measure radial intensity profiles of organellar markers, and (5) to plot the results in informative graphs. Using simulated data and immunofluorescent images of cells in which the function of known factors for lysosome positioning has been perturbed, we show that the workflow is robust against common problems for the accurate assessment of organelle positioning such as changes of cell shape and size, organelle size and background. Conclusions OrgaMapper is a versatile, robust, and easy-to-use automated image analysis workflow that can be utilized in microscopy-based hypothesis testing and screens. It effectively allows for the mapping of the intracellular space and enables the discovery of novel regulators of organelle positioning.

Abstract Naïve pluripotency is sustained by a self-reinforcing gene regulatory network (GRN) comprising core and naïve pluripotency-specific transcription factors (TFs). Upon exiting naïve pluripotency, embryonic stem cells (ESCs) transition through a formative post-implantation-like pluripotent state, where they acquire competence for lineage choice. However, the mechanisms underlying disengagement from the naïve GRN and initiation of the formative GRN are unclear. Here, we demonstrate that phosphorylated AKT acts as a gatekeeper that prevents nuclear localisation of FoxO TFs in naïve ESCs. PTEN-mediated reduction of AKT activity upon exit from naïve pluripotency allows nuclear entry of FoxO TFs, enforcing a cell fate transition by binding and activating formative pluripotency-specific enhancers. Indeed, FoxO TFs are necessary and sufficient for the activation of the formative pluripotency-specific GRN. Our work uncovers a pivotal role for FoxO TFs in establishing formative post-implantation pluripotency, a critical early embryonic cell fate transition.

Abstract Background The use of serious games in medical education provides a bridge between rapidly developing technology and traditional health-care teaching. Building on a promising web-based serious game for reviewing and acquiring factual knowledge in dental education, the present study investigated the benefits of a dual-player mode and various game options for enhancing knowledge gain and study motivation. Methods Before the intervention, students’ dental knowledge and game experience were assessed using a pre-knowledge test and questionnaire-based self-assessment. Students in the clinical study phase (n = 57) were stratified based on prior knowledge and gender and then randomly assigned to two groups, with two player modes: single player (SP) and dual player (DP). In the SP group, each participant played alone, whereas in the DP group, the participants played against a previously determined peer. For a period of 4 weeks, the students were able to playfully acquire knowledge from the field of operative dentistry using METIS, a serious game application with three different game options (Marathon, Sprint, and Time). After the intervention phase, both groups completed a post-knowledge test. The usability of the serious game was evaluated with a self-assessment questionnaire. Results The competitive game mode (DP mode; M = 8.92, SD = 1.85) resulted in an increase in the factual knowledge test that was a mean of 2.49 points higher than the SP mode (M = 5.89, SD = 2.19; p

Abstract Kindler syndrome (KS) is a rare genodermatosis resulting from loss-of-function mutations in FERMT1, the gene that encodes Kindlin-1. KS patients have a high propensity to develop aggressive and metastatic cutaneous squamous cell carcinoma (cSCC). Here we show in non-KS-associated patients that elevation of FERMT1 expression is increased in actinic keratoses compared to normal skin, with a further increase in cSCC supporting a pro-tumorigenic role in this population. In contrast, we show that loss of Kindlin-1 leads to increased SCC tumor growth in vivo and in 3D spheroids, which was associated with the development of a hypoxic tumor environment and increased glycolysis. The metalloproteinase Mmp13 was upregulated in Kindlin-1-depleted tumors, and increased expression of MMP13 was responsible for driving increased invasion of the Kindlin-1-depleted SCC cells. These results provide evidence that Kindlin-1 loss in SCC can promote invasion through the upregulation of MMP13, and offer novel insights into how Kindlin-1 loss leads to the development of a hypoxic environment that is permissive for tumor growth.

The overall mechanical response of a fractured rock mass is, to a large extent, affected by naturally occurring fractures that exhibit sizes from millimeters to kilometers. Thus, in analysis of underground structures, such as tunnels, it is required that the fractures’ influence on the stress and deformation state in the vicinity of the structure is taken into account. In the present work, we examine the applicability of the statistical volume element (SVE) approach to determining the apparent stiffness tensor of an equivalent continuum representation of the fractured rock, which is then used in the framework of the finite element method. The equivalent continuum properties are determined by volume-averaging the effect of individual fractures that intersect the SVE, while the fractures are represented using the “parallel plate model”. Stochastically generated discrete fracture networks are used to represent the fractures’ geometry. Presently, we solve the problem linearly for an incremental change of the stress state. An application of the concept is demonstrated on simulation of tunnel excavation.

Study objective: There is an increasing trend in myocardial infarction (MI) hospitalizations in young individuals. The prevalence of modifiable cardiovascular risk factors is high in this population. This study aims to assess the prevalence of traditional and non-traditional cardiovascular risk factors among young patients with coronary artery disease (CAD) including novel lipid and dietary biomarkers with a focus on potential gender differences. Design: The Young Heart study is a prospective, single-center pilot cohort study. Baseline data included medical history, medications, and lifestyle factors. We also collected blood samples for lipid profile, lipoprotein (a), high-sensitivity C-reactive protein (hsCRP), and trimethylamine N-oxide (TMAO). Participants: A total of 60 patients aged

IntroductionIn this study, we address the challenge of accurate time series forecasting of air passenger demand using historical market demand data from the U.S. commercial aviation industry in the 21st century. Commercial aviation is a major contributor to the U.S. economy, directly or indirectly generating ~US$1.37 trillion annually, or 5% of annual GDP, and supporting more than 10 million jobs (Airlines for America, 2024). Over 1 billion passengers flew through U.S. airports in 2023 (Bureau of Transportation Statistics, 2024a). Using multiple correlated time series inputs predicts future values of multiple interrelated time series and leverages their mutual dependencies to enhance accuracy.MethodsIn this study, we introduce a two-stage algorithm employing a deep neural network for correlated time series forecasting, addressing scenarios where multiple input variables are interrelated. This approach is designed to capture the influence that one time series can exert on another, thereby enhancing prediction accuracy by leveraging these interdependencies. In the first stage, we fit four Recurrent Neural Network (RNN) models to generate accurate univariate forecasts, each functioning as a single input-output model to predict aggregated market demand. The Gated Recurrent Unit (GRU) model was the top performer for our dataset overall. In the second stage, we apply the best fitted model (GRU Model) from Stage 1 to each individual competitor (disaggregated from the market) and then merge all input tensors using the Concatenate function.Results and discussionWe hope to contribute to the relevant body of knowledge with a deep neural network framework for forecasting market share among competitors in the U.S. commercial aviation industry, as no similar approach has been documented in the literature. Given the importance of the industry, there is potentially great value in applying sophisticated forecasting techniques to achieve accurate predictions of air passenger demand. Moreover, these techniques may have wider applications and can potentially be employed in other contexts.

Background Schizophrenia spectrum and other psychotic disorders (SSPD) are among the most debilitating of all mental disorders. While the evidence for psychosocial interventions such as cognitive behavioral therapy and peer support has significantly improved, access to these services remains limited. This paper describes a protocol for a pragmatic feasibility study of a digital mental health intervention (HoryzonsCa) that provides access to evidence-based psychosocial interventions, social networking, and clinical and peer support services through a secured, web-based platform for adults diagnosed with SSPD. Objective The objectives are: (1) Adapt and translate HoryzonsCa for implementation in English and French; (2) Develop an implementation and training strategy; (3) Assess the acceptability, safety, and demand of HoryzonsCa; (4) Assess clinical outcomes and perceived impacts; (5) Examine the experiences and process of adapting and implementing HoryzonsCa; (6) Explore the role of sociocultural and demographic factors on HoryzonsCa outcomes and implementation. Methods This feasibility study will use a single-group, pre-post, mixed-methods (QUAN–QUAL convergent) research design, with assessments at baseline and 12 weeks. The study aims to recruit 100 individuals (ages 18–50) diagnosed with SSPD from two healthcare settings in Canada. Data collection includes interview-based psychometric measures, self-reports, focus groups, and interviews with participants. The study will also collect qualitative data from moderators and the research team, and will be conducted entirely remotely. Conclusions This study has been prospectively registered and is underway. It will provide timely information on the feasibility and potential impacts of using digital mental health services for individuals with chronic mental health conditions. Trial Registration ISRCTN12561259; https://doi.org/10.1186/ISRCTN12561259 (250/max 250 words)

Abstract Background The “Virtual Semester for Medical Research Aachen” (vSEMERA) is an international, interdisciplinary, virtual education program developed for health profession students. The first edition (2021) was hosted by the Medical Faculty of RWTH Aachen University (Germany) in cooperation with Centro Universitário Christus (Brazil) and Universidad Peruana Cayetano Heredia (Peru). The primary aim of the 12-weeks program was to provide students with skills in health science research and prepare them for scientific career paths. Methods vSEMERA was built on a virtual learning platform, the “vSEMERA-Campus”, designed to foster students’ learning process and social interactions. Maximum flexibility was offered through synchronous and asynchronous teaching, enabling participants to join via any device from any part of the Globe alongside their regular studies. For the program’s first edition (September - November 2021), health profession students from Germany, Brazil, Peru, Spain, and Italy filled all 30 available spots. Satisfaction, quality of the program and courses offered, as well as perceived learning outcomes, were examined using questionnaires throughout and at the end of the program. Results The program received a rating of 4.38 out of 5 stars. While it met most expectations (4.29 out of 5), participants were unable to attend as many courses as intended (2.81 out of 5), mainly due to scheduling conflicts with the home university schedule (46%), internships (23%), and general timing issues (31%). Participants acknowledged considerable improvements in their scientific skills, English language skills, confidence in scientific project management, research career progression, and enthusiasm for a scientific career. Conclusions vSEMERA represents a promising example of an online international learning and exchange program using pedagogical and technological elements of virtual collaboration and teaching. In addition to advancing future vSEMERA editions, our results may offer insights for similar projects that address the targeted integration of scientific research education into an international, digital learning environment.

Abstract Despite its great scientific and technological importance, wall-bounded turbulence is an unresolved problem in classical physics that requires new perspectives to be tackled. One of the key strategies has been to study interactions among the energy-containing coherent structures in the flow. Such interactions are explored in this study using an explainable deep-learning method. The instantaneous velocity field obtained from a turbulent channel flow simulation is used to predict the velocity field in time through a U-net architecture. Based on the predicted flow, we assess the importance of each structure for this prediction using the game-theoretic algorithm of SHapley Additive exPlanations (SHAP). This work provides results in agreement with previous observations in the literature and extends them by revealing that the most important structures in the flow are not necessarily the ones with the highest contribution to the Reynolds shear stress. We also apply the method to an experimental database, where we can identify structures based on their importance score. This framework has the potential to shed light on numerous fundamental phenomena of wall-bounded turbulence, including novel strategies for flow control.

Old plant communities are of utmost importance for nature conservation, carbon sequestration, as well as gene pool maintenance. Shrub populations occurring in extreme environments beyond abiotic tree-lines provide diverse ecosystem services and have potential as proxy archives because they often inhabit areas with scarce and short instrumental records. We provide dendrochronological insight into one such population made up of prostrate Juniperus communis shrubs in the northern Scandinavian tundra (Norway), growing on a competition-free boulder field. We dated and provided a growth chronology of the oldest living shrub population (190 ± 148 years) from Scandinavia with the oldest individual being 683 years old. This is a conservative estimate, as shrubs in extreme environments do not form even a single row of cells in some years. The cross-dating issues of poorly growing shrubs do not fully allow to rely on climate sensitivity of the juniper population studied, although the species' potential for dendroclimatological reconstructions is generally considered high, also because the common juniper is an abundant woody species distributed globally. Old populations present an important gene source in plant recruitment, particularly in the context of the present environmental change.

Abstract The functions of cellular organelles and sub-compartments depend on their protein content, which can be characterized by spatial proteomics approaches. However, many spatial proteomics methods are limited in their ability to resolve organellar sub-compartments, profile multiple sub-compartments in parallel, and/or characterize membrane-associated proteomes. Here, we develop a cross-link assisted spatial proteomics (CLASP) strategy that addresses these shortcomings. Using human mitochondria as a model system, we show that CLASP can elucidate spatial proteomes of all mitochondrial sub-compartments and provide topological insight into the mitochondrial membrane proteome. Biochemical and imaging-based follow-up studies confirm that CLASP allows discovering mitochondria-associated proteins and revising previous protein sub-compartment localization and membrane topology data. We also validate the CLASP concept in synaptic vesicles, demonstrating its applicability to different sub-cellular compartments. This study extends the scope of cross-linking mass spectrometry beyond protein structure and interaction analysis towards spatial proteomics, and establishes a method for concomitant profiling of sub-organelle and membrane proteomes.