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In recent years, spectrum sharing has emerged as a viable solution to satisfy the increased demand for spectrum resources owing to increased spectral usage. A cognitive spectrum sharing radar system implementing dynamic spectrum access (DSA) has been developed to address this need. To enhance DSA performance, we propose a method to optimize the time-division duplexing (TDD) mode of a 4G/LTE channel. This technique will cue the cognitive radar to anticipate times of low primary user transmission in allocated spectral bands, thereby allowing the radar channel to opportunistically access and utilize these bands. This TDD mode identification (ID) approach implements two simple machine learning algorithms. The data for classification are extracted from the LTE resource grid in the form of spectrograms. Fisher's linear discriminant algorithm and two iterations of K-nearest neighbor are used to perform the classification. The use of a majority vote step and optimization of the feature space size greatly increase the model efficacy. The model is successful while using only a small training dataset and is able to classify the TDD mode of a channel using only 10 ms of collected data. The overall classification rate achieved is 95%, with nearly 100% for frequency division duplexing band ID.

Tissue regeneration and maintenance rely on coordinated stem cell behaviours. This orchestration can be impaired by oncogenic mutations leading to cancer. However, it is largely unclear how oncogenes perturb stem cells’ orchestration to disrupt tissue. Here we used intravital imaging to investigate the mechanisms by which oncogenic Krasmutation causes tissue disruption in the hair follicle. Through longitudinally tracking hair follicles in live mice, we found that KrasG12D, a mutation that can lead to squamous cell carcinoma, induces epithelial tissue deformation in a spatiotemporally specific manner, linked with abnormal cell division and migration. Using a reporter mouse capture real-time ERK signal dynamics at the single-cell level, we discovered that KrasG12D, but not a closely related mutation HrasG12V, converts ERK signal in stem cells from pulsatile to sustained. Finally, we demonstrated that interrupting sustained ERK signal reverts KrasG12D-induced tissue deformation through modulating specific features of cell migration and division.

Marine protected area (MPAs) networks can buffer marine ecosystems from the impacts of climate change by allowing species to redistribute as conditions change and by reducing other stressors. There are, however, few examples where climate change has been considered in MPA network design. In this paper, we assess how climate change considerations were integrated into the design of a newly released MPA network in the Northern Shelf Bioregion in British Columbia, Canada, and then evaluate the resulting network against projected physical and biogeochemical changes and biological responses. We found that representation, replication, and size and spacing recommendations integrated into the design phase were met in most cases. Furthermore, despite varying degrees of projected changes in temperature, dissolved oxygen, and aragonite saturation across the MPA network, suitable habitat for demersal fish species is projected to remain in the network despite some redistribution among sites. We also found that mid-depth MPAs are particularly important for persistence, as fish are projected to move deeper to avoid warming in shallower areas. Our results highlight that a representative MPA network with adequate replication, that incorporates areas of varying climate change trajectory, should buffer against the impacts of climate change.

Following successful treatment in which problem behavior is reduced, it may reemerge as a function of changes in contextual stimuli or the worsening of reinforcement conditions for an alternative response. Although understudied, preliminary research suggests that simultaneouschanges in contextual stimuli and reinforcement conditions may represent particularly exigent treatment challenges that create the condition for additive or superadditive relapse. The purpose of the present review was to systematically examine the relapse literature involving simultaneous changes in contextual stimuli and reinforcement conditions in relapse tests and experimental preparations arranged to evaluate their effect on response recovery. We identified 16 empirical articles spanning 27 experiments. Although all experiments included at least one condition that experienced a change in contextual stimuli and worsening of alternative reinforcement conditions, only two experiments included the comparison conditions needed to precisely evaluate additive and superadditive relapse. Our findings establish the preclinical generality of relapse effects associated with simultaneous changes to reinforcement conditions and contextual stimuli across a range of subjects, schedule arrangements, response topographies, reinforcers, and types of contextual changes. We make several recommendations for future research based on our findings from this nascent and clinically relevant subdomain of the relapse literature.

Wide consensus exists on the notion that low muscle mass is a predictor of negative health‐related events, such as disability, morbidity, and mortality. Indeed, the European Working Group on Sarcopenia in Older People 2 had identified muscle mass as the key component to confirm the diagnosis of sarcopenia. However, the lack of normative values for muscle mass across ages hampers the practical assessment of this important parameter. The aim of the present study was to produce cross‐sectional centile and normative values for calf circumference (a surrogate estimation of muscle mass) across a wide spectrum of ages using a large and unselected sample of community‐dwellers enrolled in the Longevity Check‐up 7+ (Lookup 7+) project. This is a cross‐sectional study using the data of Lookup 7+ project, an ongoing study started in June 2015 and conducted in unconventional settings (i.e., exhibitions, malls, and health promotion campaigns). Candidate participants were considered eligible for enrolment if they were at least 45 years of age and provided written informed consent. Calf circumference was measured using an inextensible but flexible plastic tape in a sitting position with the knee and ankle at a right angle and the feet resting on the floor. Normative values for calf circumference from ages 45 to 80 + years were generated. A total of 11 814 participants were enrolled from 1 June 2015 to 30 September 2022. The mean age of participants included in the analyses was 61.8 years (standard deviation; 10.2 years; range: 45–98 years), and 6686 (57%) were women. Normative values for calf circumference were obtained for men and women, stratified by age groups. Accordingly, a calf circumference tape, with colour bands that demarcate the centiles range into which the patient falls, was created and validated. Our study established age‐ and gender‐specific centile reference values for calf circumference. The calf circumference tape can be used to easily interpret the assessment in every‐day practice for the early detection of individuals with or at risk of sarcopenia and malnutrition.

Optimum allocation of bandwidth and carrier frequency in a network of distributed radar nodes is an important non-trivial research problem. In this paper, we propose both model- and deep learning-based joint bandwidth and carrier frequency allocation algorithms for a network consisting of a central coordinator and distributed radar nodes, each operating in a monostatic mode. With an objective of enabling poor performing radar nodes, that observe low target signal-to-noise-interference ratio (SINR) values, benefit from distributed collaboration, we propose model-based max-min approach, in which we maximize the minimum of the SINRs observed by all nodes, under total bandwidth and individual node's range resolution (RR) constraints. This optimization is non-convex, but we solve it efficiently utilizing an explicit relationship between bandwidth and carrier frequencies, and the fact that each node's SINR is a monotonically decreasing function of bandwidth and carrier frequency allocated to the node. We propose two iterative optimization methods that employ successive convex approximation with a) semidefinite programming (SDP) and b) geometric programming (GP) problem formulations. Computer simulations show the performance of the proposed methods under different RR requirements, which significantly outperform the equal bandwidth allocation (EBWA) method and enable poor performing nodes to enhance their individual SINRs significantly. The solutions of this model-based optimization and target locations are then used, respectively, as labels and input, to train a bidirectional long short-term memory (LSTM) network. The trained network can significantly reduce the online run-time complexity of the bandwidth and carrier frequency allocation in distributed radar networks.

In safety-critical applications, microcontrollers have to be tested to satisfy strict quality and performance constraints. It has been demonstrated that on-chip ring oscillators can be used as speed monitors to reliably predict the performances. However, any machine-learning (ML) model is likely to be inaccurate if trained on an inadequate dataset, and labeling data for training is quite a costly process. In this article, we present a methodology based on active learning to select the best samples to be included in the training set, significantly reducing the time and cost required. Moreover, since different speed measurements are available, we designed a multilabel technique to take advantage of their correlations. Experimental results demonstrate that the approach halves the training-set size, with respect to a random-labeling, while it increases the predictive accuracy, with respect to standard single-label ML models.

A key component of cognitive radar is the ability to generalize or achieve consistent performance across a range of sensing environments, since aspects of the physical scene may vary over time. This presents a challenge for learning-based waveform selection approaches, since transmission policies that are effective in one scene may be highly suboptimal in another. We address this problem by strategically biasing a learning algorithm by exploiting high-level structure across tracking instances, referred to as Meta-Learning. In this work, we develop an online Meta-Learning approach for waveform-agile tracking. This approach uses information gained from previous target tracks to speed up and enhance learning in new tracking instances. This results in sample-efficient learning across a class of finite-state target channels by exploiting inherent similarity across tracking scenes, attributed to common physical elements such as target type or clutter statistics. We formulate the online waveform selection problem within the framework of Bayesian learning and provide prior-dependent performance bounds for the Meta-Learning problem using probability approximately correct Bayes theory. We present a computationally feasible metaposterior sampling algorithm and study the performance in a simulation study consisting of diverse scenes. Finally, we examine the potential performance benefits and practical challenges associated with online Meta-Learning for waveform-agile tracking.

Background : Nutritional status is a critical factor throughout COVID-19 disease course. Malnutrition is associated with poor outcomes in hospitalized COVID-19 patients. Aim : To assess the prevalence of malnutrition and identify its associated factors in COVID-19 survivors. Methods: Study cohort included 1230 COVID-19 survivors aged 18–86 attending a post-COVID-19 outpatient service. Data on clinical parameters, anthropometry, acute COVID-19 symptoms, lifestyle habits were collected through a comprehensive medical assessment. Malnutrition was assessed according to Global Leadership Initiative on Malnutrition (GLIM) criteria. Results : Prevalence of malnutrition was 22% at 4–5 months after acute disease. Participants who were not hospitalized during acute COVID-19 showed a higher frequency of malnutrition compared to those who needed hospitalization (26% versus 19%, p < 0.01). Malnutrition was found in 25% COVID-19 survivors over 65 years of age compared to 21% younger participants (p < 0.01). After multivariable adjustment, the likelihood of being malnourished increased progressively and independently with advancing age (Odds ratio [OR] 1.02; 95% CI 1.01–1.03) and in male participants (OR 5.56; 95% CI 3.53–8.74). Malnutrition was associated with loss of appetite (OR 2.50; 95% CI 1.73–3.62), and dysgeusia (OR 4.05; 95% CI 2.30–7.21) during acute COVID-19. Discussion : In the present investigation we showed that malnutrition was highly prevalent in a large cohort of COVID-19 survivors at 4–5 months from acute illness. Conclusions : Our findings highlight the need to implement comprehensive nutritional assessment and therapy as an integral part of care for COVID-19 patients.

The concept of metacognition has been proposed and applied to radar system analysis to enhance the classical cognitive radar paradigm. Metacognition allows a cognitive radar to have self-awareness about its cognitive processes. To accurately compare various cognitive processes and select the best under the operational scenario, a performability metric capable of comparing system performance over various scales and units is proposed and analyzed. This correspondence expands previous work on radar operational reliability to provide a metareliability metric for a metacognitive tracking radar. The approach is tested and validated on a radar that tracks a target performing a composite maneuver involving constant velocity, constant turn, and constant acceleration.

Healthy skin is a mosaic of wild-type and mutant clones1,2. Although injury can cooperate with mutated Ras family proteins to promote tumorigenesis3–12, the consequences in genetically mosaic skin are unknown. Here we show that after injury, wild-type cells suppress aberrant growth induced by oncogenic Ras. HrasG12V/+and KrasG12D/+cells outcompete wild-type cells in uninjured, mosaic tissue but their expansion is prevented after injury owing to an increase in the fraction of proliferating wild-type cells. Mechanistically, we show that, unlike HrasG12V/+cells, wild-type cells respond to autocrine and paracrine secretion of EGFR ligands, and this differential activation of the EGFR pathway explains the competitive switch during injury repair. Inhibition of EGFR signalling via drug or genetic approaches diminishes the proportion of dividing wild-type cells after injury, leading to the expansion of HrasG12V/+cells. Increased proliferation of wild-type cells via constitutive loss of the cell cycle inhibitor p21 counteracts the expansion of HrasG12V/+cells even in the absence of injury. Thus, injury has a role in switching the competitive balance between oncogenic and wild-type cells in genetically mosaic skin.

ABSTRACTTo determine whether Corallina chilensisis a distinct species or a variety (i.e. C. officinalisvar. chilensis) of the generitype of Corallina, molecular phylogenetic analyses were performed using psbA, COI-5P, rbcL, or some combination of these gene regions from 75 voucher specimens representing Corallinacollections from around the world. Names were applied by comparing these DNA sequences with sequences obtained from type specimens, including a 263 bp rbcL sequence from an isotype of C. chilensiscollected by Darwin (C. Darwin 2151) from Valparaiso, Chile. DNA sequences from the C. chilensisisotype matched unnamed coralline DNA sequences from British Columbia, Canada, and previously published DNA sequences from the northeast and southeast Pacific. The clade containing the isotype of C. chilensiswas distinct from C. officinalisspecimens in phylogenetic analyses. Although morphologically variable, fronds of C. chilensisfrom British Columbia populations matched Kützing’s original description of C. officinalisvar. chilensis. These data support the conclusion that C. chilensisis a distinct species, not a variety of C. officinalis, and is distributed in both hemispheres. While this study strongly supported C. chilensisas a distinct species, phylogenetic relationships among Corallinaspecies remain elusive because individual gene trees are not congruent.

Frequency scanning (FScan) is an innovative acquisition mode for synthetic aperture radar (SAR) systems. The method is based on the frequency-dependent beam pointing capabilities of phased array antennas, artificially increased via the combined use of true time delays and phase shifters within the array antenna. By this, typical limitations of conventional SAR systems in terms of achievable swath width and azimuth resolution can be mitigated, and so a wide swath can be imaged maintaining a fine azimuthal resolution. In the first part of the article, we introduce the theoretical concept, which is necessary to evaluate the reduced echo window length (EWL) with respect to equivalent stripmap data and the implications for the transmit pulse characterization. An FScan sensor flying in a TerraSAR-X-like orbit is shown to be capable of imaging an 80-km wide swath with 1-m azimuth resolution. The resulting time–frequency properties of the recorded raw data make the traditional SAR data compression algorithms such as block-adaptive quantization (BAQ) highly inefficient in this case. Therefore, the second part of the article investigates dedicated quantization methods for efficient data volume reduction in FScan systems. Different solutions are investigated and evaluated through simulations. Various transformations of the raw data have been exploited to optimize the encoding process, including deramping, fast Fourier transform (FFT), and blockwise approaches. Compared with standard BAQ in the time domain, the suggested data compression methods significantly improve the resulting signal-to-quantization noise ratio, allowing for the reduction in the overall data volume by about 60% for the considered system scenario, while maintaining robustness in the presence of inhomogeneous scene characteristics at the cost of a modest complexity increase for its on-board implementation.

Recent research suggests that early egg introduction during infancy may help to prevent egg allergy development. However, the infant egg consumption frequency that is sufficient to induce this immune tolerance remains uncertain.

This work addresses the coexistence problem for radar networks. Specifically, we model a network of cooperative, independent, and non-communicating radar nodes which must share resources within the network as well as with non-cooperative nearby emitters. We approach this problem using online Machine Learning (ML) techniques. Online learning approaches are specifically preferred due to the sequential nature of the problem. For this task we specifically select the multi-player multi-armed bandit (MMAB) model, where each radar node in a network makes independent selections of center frequency and waveform with the same goal of improving tracking performance for the network as a whole. For accurate tracking, each radar node communicates observations to a fusion center on set intervals. The fusion center has knowledge of the radar node placement, but cannot communicate to the individual nodes fast enough for waveform control. Each independent and identical node must choose one of many waveforms to transmit in each Pulse Repetition Interval (PRI) while avoiding collisions with other nodes and interference from the environment. The goal for the network as a whole is to minimize target tracking error, which relies on obtaining high SINR in each time step. Our contributions include a mathematical description of the MMAB framework adapted to the radar network scenario. We conclude with a simulation study of several different network configurations. Experimental results show that iterative, online learning using MMAB outperforms the more traditional sense-and-avoid (SAA) and fixed-allocation approaches.

Online selection of optimal waveforms for target tracking with active sensors has long been a problem of interest. Many conventional solutions utilize an estimation-theoretic interpretation, in which a waveform-specific Cramér–Rao lower bound on measurement error is used to select the optimal waveform for each tracking step. However, this approach is only valid in the high SNR regime, and requires a rather restrictive set of assumptions regarding the target motion and measurement models. Furthermore, due to computational concerns, many traditional approaches are limited to near-term, or myopic, optimization, even though radar scenes exhibit strong temporal correlation. More recently, reinforcement learning has been proposed for waveform selection, in which the problem is framed as a Markov decision process, allowing for long-term planning. However, a major limitation of reinforcement learning is that the memory length of the underlying Markov process is often unknown for realistic target and channel dynamics, and a more general framework is desirable. This work develops a universal sequential waveform selection scheme which asymptotically achieves Bellman optimality in any radar scene, which can be modeled as a $U{\text{th}}$-order Markov process for a finite, but unknown, integer $U$. Our approach is based on well-established tools from the field of universal source coding, where a stationary source is parsed into variable length phrases in order to build a context-tree, which is used as a probabilistic model for the scene’s behavior. We show that an algorithm based on a multialphabet version of the context-tree weighting method can be used to optimally solve a broad class of waveform-agile tracking problems while making minimal assumptions about the environment’s behavior.

In this article, a statistical model of human motion as observed by a network of radar sensors is presented where knowledge on the position and heading of the target provides information on the observation conditions of each sensor node. Sequences of motions are estimated from measurements of instantaneous Doppler frequency, which captures informative micromotions exhibited by the human target. A closed-form Bayesian estimation algorithm is presented that jointly estimates the state of the target and its exhibited motion class which are described by a hidden Markov model. To correct errors in the estimated motion class distribution introduced by faulty modeling assumptions, calibration of the probability distribution and measurement likelihood is performed by isotonic regression. It is shown, by modeling sensor observation conditions and by isotonic calibration of the measurement likelihood that a cognitive resource management system is able to increase classification accuracy by 5${\%}$–10${\%}$ while utilizing sensor resources in accordance with defined mission objectives.

Ephrin receptors and their membrane-localized ligands induce bidirectional signaling and facilitate tumor-stroma interactions. Blocking the EphB4-EphrinB2 pathway, which can be accomplished by soluble EphB4 conjugated to human serum albumin (sEphB4-HSA), promotes cell death in preclinical models of aggressive prostate cancer. We hypothesized that targeting the EphB4-EphrinB2 pathway may serve as a therapeutic target in the treatment of metastatic castration resistant prostate cancer (mCRPC).

Severe clinical pictures and sequelae of COVID‐19 disease are immune mediated and characterized by a ‘cytokine storm’. Skeletal muscle has emerged as a potent regulator of immune system function. The aim of the present study is to define the prevalence of sarcopenia among COVID‐19 survivors and the negative impact of sarcopenia on the post‐acute COVID‐19 syndrome and its related risk factors. A total of 541 subjects recovered from COVID‐19 disease were enrolled in the Gemelli Against COVID‐19 Post‐Acute Care between April 2020 and February 2021. They underwent a multidisciplinary clinical evaluation and muscle strength and physical performance assessment. Mean age was 53.1 years (SD 15.2, range from 18 to 86 years), and 274 (51%) were women. The prevalence of sarcopenia was 19.5%, and it was higher in patients with a longer hospital stay and lower in patients who were more physically active and had higher levels of serum albumin. Patients with sarcopenia had a higher number of persistent symptoms than non‐sarcopenic patients (3.8 ± 2.9 vs. 3.2 ± 2.8, respectively; P= 0.06), in particular fatigue, dyspnoea, and joint pain. Sarcopenia identified according to the EWGSOP2 criteria is high in patients recovered from COVID‐19 acute illness, particularly in those who had experienced the worst clinical picture reporting the persistence of fatigue and dyspnoea. Our data suggest that sarcopenia, through the persistence of inflammation, could be the biological substrate of long COVID‐19 syndrome. Physical activity, especially if associated with adequate nutrition, seems to be an important protective factor.

Countercontrol is a Skinnerian operant concept that posits that an individual’s attempts to exert control over another person’s behavior may evoke a countercontrolling response from the person being controlled that functions to avoid or escape the potentially aversive conditions generated by the controller. Despite Skinner’s historical concerns regarding the detrimental effects of countercontrol in terms of hindering optimal societal growth and cultural evolution, the concept has not been widely applied within behavior analysis. Drawing from recent developments in rule-governed behavior and relational frame theory, this article seeks to explicate countercontrol from a contemporary behavior analytic perspective and presents several modern-day societal applications. In particular, a relational frame theory account of rule-governed behavior is used as a framework to elucidate the behavioral processes by which rule-following occurs (or fails to occur) in the context of countercontrol. Implications of a renewed focus on countercontrol for understanding pressing societal issues are also discussed.

Climate change is causing decreases in pH and dissolved oxygen (DO) in coastal ecosystems. Canopy‐forming giant kelp can locally increase DO and pH through photosynthesis, with the most pronounced effect expected in surface waters where the bulk of kelp biomass resides. However, limited observations are available from waters in canopies and measurements at depth show limited potential of giant kelp to ameliorate chemical conditions. We quantified spatiotemporal variability of surface biogeochemistry and assessed the role of biological and physical drivers in pH and DO modification at two locations differing in hydrodynamics inside and outside of two kelp forests in Monterey Bay, California in summer 2019. pH, DO, dissolved inorganic carbon (DIC), and temperature were measured at and near the surface, in conjunction with physical parameters (currents and pressure), nutrients, and metrics of phytoplankton and kelp biological processes. DO and pH were highest, with lower DIC, at the surface inside kelp forests. However, differences inside vs. outside of kelp forests were small (DO 6–8%, pH 0.05 higher in kelp). The kelp forest with lower significant wave height and slower currents had greater modification of surface biogeochemistry as indicated by larger diel variation and slightly higher mean DO and pH, despite lower kelp growth rates. Differences between kelp forests and offshore areas were not driven by nutrients or phytoplankton. Although kelp had clear effects on biogeochemistry, which were modulated by hydrodynamics, the small magnitude and spatial extent of the effect limits the potential of kelp forests to mitigate acidification and hypoxia.

Supplemental Digital Content is available in the text.

It is well known that people read very little in Italy and that CEPELL, a centre for books and reading, has as its mission the promotion of reading. One of the tools to bring children closer to reading is the PCTO, the training courses for orientation and training, with the realization of final objectives of acquisition of targeted computer skills (Information Literacy), of learning the main notions for the online bibliographic and cataloging research, basic knowledge of library services and promotion of reading using the school library as a basis. At the G.B. Vico di Napoli two paths have been created that have guided seven classes towards the achievement of these objectives. The training courses were carried out partly in the presence and partly remotely with the collaboration of external experts and internal tutors. [ABSTRACT FROM AUTHOR]

ABSTRACTThis study made use of differential reinforcement and shaping to increase the variety of food items accepted by two boys with autism. In the first phase, three new food items were introduced to the participants and the acceptance response to the food was systematically increased. Food items were introduced in a multiple baseline design. In the second phase, the children started to eat more than one type of food item per meal by means of a changing criterion design. The procedure was implemented by the parents and carried out in the home environment of each child. At the end of the experiment, three other food items were defined for each child and parents were asked to follow the procedure learned without author’s supervision. The results showed that the two participants started accepting food, expanded the number of food items consumed and that parents learned to introduce new foods into their children’s diets.

Large eukaryotes support diverse communities of microbes on their surface—epibiota—that profoundly influence their biology. Alternate factors known to structure complex patterns of microbial diversity—host evolutionary history and ecology, environmental conditions and stochasticity—do not act independently and it is challenging to disentangle their relative effects. Here, we surveyed the epibiota from 38 sympatric seaweed species that span diverse clades and have convergent morphology, which strongly influences seaweed ecology. Host identity explains most of the variation in epibiont communities and deeper host phylogenetic relationships (e.g., genus level) explain a small but significant portion of epibiont community variation. Strikingly, epibiota community composition is significantly influenced by host morphology and epibiota richness increases with morphological complexity of the seaweed host. This effect is robust after controlling for phylogenetic non-independence and is strongest for crustose seaweeds. We experimentally validated the effect of host morphology by quantifying bacterial community assembly on latex sheets cut to resemble three seaweed morphologies. The patterns match those observed in our field survey. Thus, biodiversity increases with habitat complexity in host-associated microbial communities, mirroring patterns observed in animal communities. We suggest that host morphology and structural complexity are underexplored mechanisms structuring microbial communities.

Large eukaryotes support diverse communities of microbes on their surface—epibiota—that profoundly influence their biology. Alternate factors known to structure complex patterns of microbial diversity—host evolutionary history and ecology, environmental conditions and stochasticity—do not act independently and it is challenging to disentangle their relative effects. Here, we surveyed the epibiota from 38 sympatric seaweed species that span diverse clades and have convergent morphology, which strongly influences seaweed ecology. Host identity explains most of the variation in epibiont communities and deeper host phylogenetic relationships (e.g., genus level) explain a small but significant portion of epibiont community variation. Strikingly, epibiota community composition is significantly influenced by host morphology and epibiota richness increases with morphological complexity of the seaweed host. This effect is robust after controlling for phylogenetic non-independence and is strongest for crustose seaweeds. We experimentally validated the effect of host morphology by quantifying bacterial community assembly on latex sheets cut to resemble three seaweed morphologies. The patterns match those observed in our field survey. Thus, biodiversity increases with habitat complexity in host-associated microbial communities, mirroring patterns observed in animal communities. We suggest that host morphology and structural complexity are underexplored mechanisms structuring microbial communities.

Organs consist of multiple cell types that ensure proper architecture and function. How different cell types coexist and interact to maintain their homeostasis in vivo remains elusive. The skin epidermis comprises mostly epithelial cells, but also harbours Langerhans cells (LCs) and dendritic epidermal T cells (DETCs). Whether and how distributions of LCs and DETCs are regulated during homeostasis is unclear. Here, by tracking individual cells in the skin of live adult mice over time, we show that LCs and DETCs actively maintain a non-random spatial distribution despite continuous turnover of neighbouring basal epithelial cells. Moreover, the density of epithelial cells regulates the composition of LCs and DETCs in the epidermis. Finally, LCs require the GTPase Rac1 to maintain their positional stability, density and tiling pattern reminiscent of neuronal self-avoidance. We propose that these cellular mechanisms provide the epidermis with an optimal response to environmental insults.

The severity of heart disease varies widely among patients with transthyretin-related cardiac amyloidosis (ATTR-CA) at presentation, and availability of tools able to predict prognosis is essential for clinical and research purposes. Currently, two biomarker-based staging systems are available. The aim of this study was to compare their predictive performance.

Physical function decreases with aging, which may result in adverse outcomes (eg, disability, loss of independence, institutionalization, death). Physical function impairment is a common trait of frailty and sarcopenia. These two conditions, albeit highly common, have not yet received a unique operational definition, which has impeded their implementation in standard practice. Here, we introduce a conceptual model in which sarcopenia is proposed as the biological substrate and the pathway whereby the consequences of physical frailty develop. This conceptualization may open new venues for the design of interventions against physical frailty and promote the translation of findings to the clinical arena.

Cataract surgery is the most frequently performed surgical procedure in the elderly in Western countries and patients’ expectations for postoperative outcomes are very high.Dry eye disease (DED) is a common multifactorial symptomatic disease of the ocular surface with a complex etiopathogenesis and a prevalence significantly increasing with age.Cataract surgery and DED have a complex relationship, which needs to be acknowledged, understood, and properly managed, as suggested by daily clinical experience and growing scientific evidence. The surgical procedure can have a relevant impact on the tear film and the ocular surface, and it can, usually transiently, induce or exacerbate DED symptoms. Moreover, preoperative DED can affect surgical refractive outcomes, while postoperative DED symptoms can significantly worsen patients reported outcomes and satisfaction.At the end of this narrative review summarizing the evidence on this topic, the “Dry Eye and Cataract Surgery” subcommittee of the DROPS workshop formulated some recommendations for ocular surface and DED management pre-, intra-, and post-cataract surgery.

Graft-versus-host disease (GVHD) is a major cause of morbidity and mortality in allogeneic hematopoietic stem cell transplantation (alloSCT). By static microscopy, cutaneous GVHD lesions contain a mix of T cells and myeloid cells. We used 2-photon intravital microscopy to investigate the dynamics of CD4+and CD8+T cells and donor dendritic cells (DCs) in cutaneous GVHD lesions in an MHC-matched, multiple minor histocompatibility antigen-mismatched (miHA) model. The majority of CD4 and CD8 cells were stationary, and few cells entered and stopped or were stopped and left the imaged volumes. CD8 cells made TCR:MHCI-dependent interactions with CD11c+cells, as measured by the durations that CD8 cells contacted MHCI+vs MHCI−DCs. The acute deletion of Langerin+CD103+DCs, which were relatively rare, did not affect CD8 cell motility and DC contact times, indicating that Langerin−CD103−DCs provide stop signals to CD8 cells. CD4 cells, in contrast, had similar contact durations with MHCII+and MHCII−DCs. However, CD4 motility rapidly increased after the infusion of an MHCII-blocking antibody, indicating that TCR signaling actively suppressed CD4 movements. Many CD4 cells still were stationary after anti-MHCII antibody infusion, suggesting CD4 cell heterogeneity within the lesion. These data support a model of local GVHD maintenance within target tissues.

Graft-versus-host disease (GVHD) is a major cause of morbidity and mortality in allogeneic hematopoietic stem cell transplantation (alloSCT). By static microscopy, cutaneous GVHD lesions contain a mix of T cells and myeloid cells. We used 2-photon intravital microscopy to investigate the dynamics of CD4+ and CD8+ T cells and donor dendritic cells (DCs) in cutaneous GVHD lesions in an MHC-matched, multiple minor histocompatibility antigen-mismatched (miHA) model. The majority of CD4 and CD8 cells were stationary, and few cells entered and stopped or were stopped and left the imaged volumes. CD8 cells made TCR:MHCI-dependent interactions with CD11c+ cells, as measured by the durations that CD8 cells contacted MHCI+ vs MHCI− DCs. The acute deletion of Langerin+CD103+ DCs, which were relatively rare, did not affect CD8 cell motility and DC contact times, indicating that Langerin−CD103− DCs provide stop signals to CD8 cells. CD4 cells, in contrast, had similar contact durations with MHCII+ and MHCII− DCs. However, CD4 motility rapidly increased after the infusion of an MHCII-blocking antibody, indicating that TCR signaling actively suppressed CD4 movements. Many CD4 cells still were stationary after anti-MHCII antibody infusion, suggesting CD4 cell heterogeneity within the lesion. These data support a model of local GVHD maintenance within target tissues.

AbstractIntegrated modeling (IM) of present experiments and future tokamak reactors requires the provision of computational resources and numerical tools capable of simulating multiscale spatial phenomena as well as fast transient events and relatively slow plasma evolution within a reasonably short computational time. Recent progress in the implementation of the new computational resources for fusion applications in Europe based on modern supercomputer technologies (supercomputer MARCONI-FUSION), in the optimization and speedup of the EU fusion-related first-principle codes, and in the development of a basis for physics codes/modules integration into a centrally maintained suite of IM tools achieved within the EUROfusion Consortium is presented. Physics phenomena that can now be reasonably modelled in various areas (core turbulence and magnetic reconnection, edge and scrape-off layer physics, radio-frequency heating and current drive, magnetohydrodynamic model, reflectometry simulations) following successful code optimizations and parallelization are briefly described. Development activities in support to IM are summarized. They include support to (1) the local deployment of the IM infrastructure and access to experimental data at various host sites, (2) the management of releases for sophisticated IM workflows involving a large number of components, and (3) the performance optimization of complex IM workflows.

Cardiomyopathies (CM) are a heterogeneous group of muscle heart diseases, divided into 3 main categories (dilated, hypertrophic, and restrictive). In addition to these subgroups, athlete’s heart and hypertensive cardiopathy are both the result of heart adaptation to increased loading conditions, making it possible to include them in the CM group. Right heart involvement is clear in some CM as arrhythmogenic CM, carcinoid syndrome, and endomyocardial fibrosis, whereas in others, like hypertrophic or dilated CM, it is known that the right heart has a prognostic impact but less clear is its pathogenic role.

Sarcopenia, the progressive and generalized loss of skeletal muscle mass and strength/function associated with aging, increases the risk of a vast array of adverse health outcomes, including falls, morbidity, loss of independence, disability, and mortality. As such, sarcopenia poses a huge socioeconomic burden in developed countries. The development and implementation of effective interventions against sarcopenia are therefore a public health priority. A preliminary, fundamental step in such a process entails the agreement of researchers, healthcare professionals and policymakers around a unique operational definition of sarcopenia. This will facilitate the framing of a clear clinical entity to be incorporated in standard practice, the understanding of the underlying pathophysiology, and the identification of biological targets for drug development.

Cytoplasmic long non-coding RNAs have been shown to act at many different levels to control post-transcriptional gene expression, although their role in translational control is poorly understood. Here, we show that lnc-31, a non-coding RNA required for myoblast proliferation, promotes ROCK1 protein synthesis by stabilizing its translational activator, YB-1. We find that lnc-31binds to the Rock1mRNA as well as to the YB-1 protein and that translational activation requires physical interaction between the two RNA species. These results suggest a localized effect of YB-1 stabilization on the Rock1mRNA. ROCK1 upregulation by lnc-31, in proliferative conditions, correlates well with the differentiation-repressing activity of ROCK1. We also show that, upon induction of differentiation, the downregulation of lnc-31, in conjunction with miR-152 targeting of Rock1, establishes a regulatory loop that reinforces ROCK1 repression and promotes myogenesis.

The ability of stem cells to build and replenish tissues depends on support from their niche. Although niche architecture varies across organs, its functional importance is unclear. During hair follicle growth, multipotent epithelial progenitors build hair via crosstalk with their remodeling fibroblast niche, the dermal papilla, providing a powerful model to functionally interrogate niche architecture. Through mouse intravital imaging, we show that dermal papilla fibroblasts remodel individually and collectively to form a morphologically polarized, structurally robust niche. Asymmetric TGF-β signaling precedes morphological niche polarity, and loss of TGF-β signaling in dermal papilla fibroblasts leads them to progressively lose their stereotypic architecture, instead surrounding the epithelium. The reorganized niche induces the redistribution of multipotent progenitors but nevertheless supports their proliferation and differentiation. However, the differentiated lineages and hairs produced by progenitors are shorter. Overall, our results reveal that niche architecture optimizes organ efficiency but is not absolutely essential for organ function.