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Ecologists require spatially explicit data to relate structure to function. To date, heavy reliance has been placed on obtaining such data from remote-sensing instruments mounted on spacecraft or manned aircraft, although the spatial and temporal resolutions of the data are often not suited to local-scale ecological investigations. Recent technological innovations have led to an upsurge in the availability of unmanned aerial vehicles (UAVs) - aircraft remotely operated from the ground - and there are now many lightweight UAVs on offer at reasonable costs. Flying low and slow, UAVs offer ecologists new opportunities for scale-appropriate measurements of ecological phenomena. Equipped with capable sensors, UAVs can deliver fine spatial resolution data at temporal resolutions defined by the end user. Recent innovations in UAV platform design have been accompanied by improvements in navigation and the miniaturization of measurement technologies, allowing the study of individual organisms and their spatiotemporal dynamics at close range.

CRISPR offers new hope for many patients and promises to transform the way we think of future therapies. Ensuring safety of CRISPR therapeutics is a top priority for clinical translation and specific recommendations have been recently released by the FDA. Rapid progress in the preclinical and clinical development of CRISPR therapeutics leverages years of experience with gene therapy successes and failures. Adverse events due to immunogenicity have been a major setback that has impacted the field of gene therapy. As several in vivo CRISPR clinical trials make progress, the challenge of immunogenicity remains a significant roadblock to the clinical availability and utility of CRISPR therapeutics. In this review, we examine what is currently known about the immunogenicity of CRISPR therapeutics and discuss several considerations to mitigate immunogenicity for the design of safe and clinically translatable CRISPR therapeutics.

Based on a consensus conference of experts in the evolution and ecology of cancer, this article proposes a framework for classifying tumours that includes four evolutionary and ecological processes: neoplastic cell diversity and changes over time in that diversity, hazards to cell survival and available resources. Neoplasms change over time through a process of cell-level evolution, driven by genetic and epigenetic alterations. However, the ecology of the microenvironment of a neoplastic cell determines which changes provide adaptive benefits. There is widespread recognition of the importance of these evolutionary and ecological processes in cancer, but to date, no system has been proposed for drawing clinically relevant distinctions between how different tumours are evolving. On the basis of a consensus conference of experts in the fields of cancer evolution and cancer ecology, we propose a framework for classifying tumours that is based on four relevant components. These are the diversity of neoplastic cells (intratumoural heterogeneity) and changes over time in that diversity, which make up an evolutionary index (Evo-index), as well as the hazards to neoplastic cell survival and the resources available to neoplastic cells, which make up an ecological index (Eco-index). We review evidence demonstrating the importance of each of these factors and describe multiple methods that can be used to measure them. Development of this classification system holds promise for enabling clinicians to personalize optimal interventions based on the evolvability of the patient's tumour. The Evo- and Eco-indices provide a common lexicon for communicating about how neoplasms change in response to interventions, with potential implications for clinical trials, personalized medicine and basic cancer research.

The world of late seems oversaturated with stories about drones. These suddenly pervasive machines straddle a divide in geography, being simultaneously an important tool for proximal sensing in physical geography and technology with military origins that human geographers have critically engaged. This paper, a collaboration between a physical and a human geographer, is an exploration of the epistemological nexus that a critical drone methodology offers the discipline, and which we suggest provides a new opportunity for collaborative human/physical geography. Drawing on our own research with drones and that of others, we demonstrate how recent scholarship on vertical geographies and longstanding remote‐sensing frameworks are challenged by drone methodologies where social, environmental and technological concerns are entangled with the politics of access to proximal airspace and, in doing so, define a new conceptual atmospheric zone within the Earth's atmospheric boundary layer – the “Nephosphere” – where drone experimentation occurs. We argue that engagement with non‐military uses of drones is crucial for the discipline, now that we are entering an uncertain aerial future that will be replete with flying robots, and suggest drones are reconfiguring geographic imaginations. In short, we call on geographers to participate actively in the shaping of new drone methodologies where the values and perils of the technology can be critically debated from the starting point of the experiential, rather than the speculative.

Tension transmitted between neighboring cells can exert profound effects on cell proliferation, differentiation, and tissue organization. Exactly how intercellular mechanical tension is sensed at the molecular level is unknown. One attractive hypothesis is that a linkage between the cell-cell adhesion molecule E-cadherin, its binding partners α- and β-catenin, and actin filaments may act as a tension sensor. However, how this linkage is established at the molecular level is not known. Buckley et al. used optical tweezers to determine how mechanical load influences interactions of the cadherin/catenin complex with single actin filaments. The data support a model in which force shifts the interaction from a force-independent, weakly bound state to a highly force-sensitive, strongly bound state. The findings may explain how cells maintain tissue integrity while still being able to move and change shape. Science , this issue p. 10.1126/science.1254211 A protein complex involved in cell adhesion forms a two-state catch bond with the cytoskeleton under mechanical load. Linkage between the adherens junction (AJ) and the actin cytoskeleton is required for tissue development and homeostasis. In vivo findings indicated that the AJ proteins E-cadherin, β-catenin, and the filamentous (F)–actin binding protein αE-catenin form a minimal cadherin-catenin complex that binds directly to F-actin. Biochemical studies challenged this model because the purified cadherin-catenin complex does not bind F-actin in solution. Here, we reconciled this difference. Using an optical trap–based assay, we showed that the minimal cadherin-catenin complex formed stable bonds with an actin filament under force. Bond dissociation kinetics can be explained by a catch-bond model in which force shifts the bond from a weakly to a strongly bound state. These results may explain how the cadherin-catenin complex transduces mechanical forces at cell-cell junctions.

The CRISPR-Cas9 system has raised hopes for developing personalized gene therapies for complex diseases. Its application for genetic and epigenetic therapies in humans raises concerns over immunogenicity of the bacterially derived Cas9 protein. Here we detect antibodies to Streptococcus pyogenes Cas9 (SpCas9) in at least 5% of 143 healthy individuals. We also report pre-existing human CD8+T cell immunity in the majority of healthy individuals screened. We identify two immunodominant SpCas9 T cell epitopes for HLA-A*02:01 using an enhanced prediction algorithm that incorporates T cell receptor contact residue hydrophobicity and HLA binding and evaluated them by T cell assays using healthy donor PBMCs. In a proof-of-principle study, we demonstrate that Cas9 protein can be modified to eliminate immunodominant epitopes through targeted mutation while preserving its function and specificity. Our study highlights the problem of pre-existing immunity against CRISPR-associated nucleases and offers a potential solution to mitigate the T cell immune response. Possible immunogenicity of the Cas9 protein raises concerns about therapeutic applications. Here the authors identify pre-existing CD8+T-cell immunity in healthy individuals and in response modify Cas9 to remove the immunodominant epitopes.

Cellular mechanisms underlying the development of left–right asymmetry in tissues and embryos remain obscure. Here, the development of a chiral pattern of actomyosin was revealed by studying actin cytoskeleton self-organization in cells with isotropic circular shape. A radially symmetrical system of actin bundles consisting of α-actinin-enriched radial fibres (RFs) and myosin-IIA-enriched transverse fibres (TFs) evolved spontaneously into the chiral system as a result of the unidirectional tilting of all RFs, which was accompanied by a tangential shift in the retrograde movement of TFs. We showed that myosin-IIA-dependent contractile stresses within TFs drive their movement along RFs, which grow centripetally in a formin-dependent fashion. The handedness of the chiral pattern was shown to be regulated by α-actinin-1. Computational modelling demonstrated that the dynamics of the RF–TF system can explain the pattern transition from radial to chiral. Thus, actin cytoskeleton self-organization provides built-in machinery that potentially allows cells to develop left–right asymmetry. Bershadsky and colleagues show that cells confined to circular adhesive patterns exhibit defined and dynamic self-assembly of their actin cytoskeleton into a chiral pattern with defined handedness, potentially informing left–right cell asymmetry.

Despite the availability of major histocompatibility complex (MHC)-binding peptide prediction algorithms, the development of T-cell vaccines against pathogen and tumor antigens remains challenged by inefficient identification of immunogenic epitopes. CD8⁺ T cells must distinguish immunogenic epitopes from nonimmunogenic self peptides to respond effectively against an antigen without endangering the viability of the host. Because this discrimination is fundamental to our understanding of immune recognition and critical for rational vaccine design, we interrogated the biochemical properties of 9,888 MHC class I peptides. We identified a strong bias toward hydrophobic amino acids at T-cell receptor contact residues within immunogenic epitopes of MHC allomorphs, which permitted us to develop and train a hydrophobicity-based artificial neural network (ANN-Hydro) to predict immunogenic epitopes. The immunogenicity model was validated in a blinded in vivo overlapping epitope discovery study of 364 peptides from three HIV-1 Gag protein variants. Applying the ANN-Hydro model on existing peptide-MHC algorithms consistently reduced the number of candidate peptides across multiple antigens and may provide a correlate with immunodominance. Hydrophobicity of TCR contact residues is a hallmark of immunogenic epitopes and marks a step toward eliminating the need for empirical epitope testing for vaccine development.

Background Cancer immunotherapy with immune checkpoint blockade (CKB) is now standard of care for multiple cancers. The clinical response to CKB is associated with T cell immunity targeting cancer-induced mutations that generate novel HLA-binding epitopes (neoepitopes). Methods Here, we developed a rapid bioinformatics pipeline and filtering strategy, EpitopeHunter, to identify and prioritize clinically relevant neoepitopes from the landscape of somatic mutations. We used the pipeline to determine the frequency of neoepitopes from the TCGA dataset of invasive breast cancers. We predicted HLA class I-binding neoepitopes for 870 breast cancer samples and filtered the neoepitopes based on tumor transcript abundance. Results We found that the total mutational burden (TMB) was highest for triple-negative breast cancer, TNBC, (median = 63 mutations, range: 2–765); followed by HER-2(+) (median = 39 mutations, range: 1–1206); and lowest for ER/PR(+)HER-2(−) (median = 32 mutations, range: 1–2860). 40% of the nonsynonymous mutations led to the generation of predicted neoepitopes. The neoepitope load (NEL) is highly correlated with the mutational burden (R 2  = 0.86). Conclusions Only half (51%) of the predicted neoepitopes are expressed at the RNA level (FPKM≥2), indicating the importance of assessing whether neoepitopes are transcribed. However, of all patients, 93% have at least one expressed predicted neoepitope, indicating that most breast cancer patients have the potential for neo-epitope targeted immunotherapy.

AbstractObjectiveTo estimate population health outcomes with delayed second dose versus standard schedule of SARS-CoV-2 mRNA vaccination.DesignSimulation agent based modeling study.SettingSimulated population based on real world US county.ParticipantsThe simulation included 100 000 agents, with a representative distribution of demographics and occupations. Networks of contacts were established to simulate potentially infectious interactions though occupation, household, and random interactions.InterventionsSimulation of standard covid-19 vaccination versus delayed second dose vaccination prioritizing the first dose. The simulation runs were replicated 10 times. Sensitivity analyses included first dose vaccine efficacy of 50%, 60%, 70%, 80%, and 90% after day 12 post-vaccination; vaccination rate of 0.1%, 0.3%, and 1% of population per day; assuming the vaccine prevents only symptoms but not asymptomatic spread (that is, non-sterilizing vaccine); and an alternative vaccination strategy that implements delayed second dose for people under 65 years of age, but not until all those above this age have been vaccinated.Main outcome measuresCumulative covid-19 mortality, cumulative SARS-CoV-2 infections, and cumulative hospital admissions due to covid-19 over 180 days.ResultsOver all simulation replications, the median cumulative mortality per 100 000 for standard dosing versus delayed second dose was 226 v 179, 233 v 207, and 235 v 236 for 90%, 80%, and 70% first dose efficacy, respectively. The delayed second dose strategy was optimal for vaccine efficacies at or above 80% and vaccination rates at or below 0.3% of the population per day, under both sterilizing and non-sterilizing vaccine assumptions, resulting in absolute cumulative mortality reductions between 26 and 47 per 100 000. The delayed second dose strategy for people under 65 performed consistently well under all vaccination rates tested.ConclusionsA delayed second dose vaccination strategy, at least for people aged under 65, could result in reduced cumulative mortality under certain conditions.