Abstract: Controlled experimental evolution during antibiotic treatment can help to explain the processes leading to antibiotic resistance in bacteria. Recently, intermittent antibiotic exposures have been shown to lead rapidly to the evolution of tolerance—that is, the ability to survive under treatment without developing resistance. However, whether tolerance delays or promotes the eventual emergence of resistance is unclear. Here we used in vitro evolution experiments to explore this question. We found that in all cases, tolerance preceded resistance. A mathematical population-genetics model showed how tolerance boosts the chances for resistance mutations to spread in the population. Thus, tolerance mutations pave the way for the rapid subsequent evolution of resistance. Preventing the evolution of tolerance may offer a new strategy for delaying the emergence of resistance.

Abstract: Purpose To provide guidance regarding the practical assessment and management of vulnerabilities in older patients undergoing chemotherapy. Methods An Expert Panel was convened to develop clinical practice guideline recommendations based on a systematic review of the medical literature. Results A total of 68 studies met eligibility criteria and form the evidentiary basis for the recommendations. Recommendations In patients ≥ 65 years receiving chemotherapy, geriatric assessment (GA) should be used to identify vulnerabilities that are not routinely captured in oncology assessments. Evidence supports, at a minimum, assessment of function, comorbidity, falls, depression, cognition, and nutrition. The Panel recommends instrumental activities of daily living to assess for function, a thorough history or validated tool to assess comorbidity, a single question for falls, the Geriatric Depression Scale to screen for depression, the Mini-Cog or the Blessed Orientation-Memory-Concentration test to screen for cognitive impairment, and an assessment of unintentional weight loss to evaluate nutrition. Either the CARG (Cancer and Aging Research Group) or CRASH (Chemotherapy Risk Assessment Scale for High-Age Patients) tools are recommended to obtain estimates of chemotherapy toxicity risk; the Geriatric-8 or Vulnerable Elders Survey-13 can help to predict mortality. Clinicians should use a validated tool listed at ePrognosis to estimate noncancer-based life expectancy ≥ 4 years. GA results should be applied to develop an integrated and individualized plan that informs cancer management and to identify nononcologic problems amenable to intervention. Collaborating with caregivers is essential to implementing GA-guided interventions. The Panel suggests that clinicians take into account GA results when recommending chemotherapy and that the information be provided to patients and caregivers to guide treatment decision making. Clinicians should implement targeted, GA-guided interventions to manage nononcologic problems. Additional information is available at www.asco.org/supportive-care-guidelines .

Abstract: Processing of materials by ultrashort laser pulses has evolved significantly over the last decade and is starting to reveal its scientific, technological and industrial potential. In ultrafast laser manufacturing, optical energy of tightly focused femtosecond or picosecond laser pulses can be delivered to precisely defined positions in the bulk of materials via two-/multi-photon excitation on a timescale much faster than thermal energy exchange between photoexcited electrons and lattice ions. Control of photo-ionization and thermal processes with the highest precision, inducing local photomodification in sub-100-nm-sized regions has been achieved. State-of-the-art ultrashort laser processing techniques exploit high 0.1–1 μm spatial resolution and almost unrestricted three-dimensional structuring capability. Adjustable pulse duration, spatiotemporal chirp, phase front tilt and polarization allow control of photomodification via uniquely wide parameter space. Mature opto-electrical/mechanical technologies have enabled laser processing speeds approaching meters-per-second, leading to a fast lab-to-fab transfer. The key aspects and latest achievements are reviewed with an emphasis on the fundamental relation between spatial resolution and total fabrication throughput. Emerging biomedical applications implementing micrometer feature precision over centimeter-scale scaffolds and photonic wire bonding in telecommunications are highlighted.

Abstract: Interacting quantum systems are expected to thermalize, but in some situations in the presence of disorder they can exist in localized states instead. This many-body localization is studied experimentally in a small system with programmable disorder. When a system thermalizes it loses all memory of its initial conditions. Even within a closed quantum system, subsystems usually thermalize using the rest of the system as a heat bath. Exceptions to quantum thermalization have been observed, but typically require inherent symmetries1,2 or noninteracting particles in the presence of static disorder3,4,5,6. However, for strong interactions and high excitation energy there are cases, known as many-body localization (MBL), where disordered quantum systems can fail to thermalize7,8,9,10. We experimentally generate MBL states by applying an Ising Hamiltonian with long-range interactions and programmable random disorder to ten spins initialized far from equilibrium. Using experimental and numerical methods we observe the essential signatures of MBL: initial-state memory retention, Poissonian distributed energy level spacings, and evidence of long-time entanglement growth. Our platform can be scaled to more spins, where a detailed modelling of MBL becomes impossible.

Abstract: Recent research has shown that using spectral–spatial information can considerably improve the performance of hyperspectral image (HSI) classification. HSI data is typically presented in the format of 3D cubes. Thus, 3D spatial filtering naturally offers a simple and effective method for simultaneously extracting the spectral–spatial features within such images. In this paper, a 3D convolutional neural network (3D-CNN) framework is proposed for accurate HSI classification. The proposed method views the HSI cube data altogether without relying on any preprocessing or post-processing, extracting the deep spectral–spatial-combined features effectively. In addition, it requires fewer parameters than other deep learning-based methods. Thus, the model is lighter, less likely to over-fit, and easier to train. For comparison and validation, we test the proposed method along with three other deep learning-based HSI classification methods—namely, stacked autoencoder (SAE), deep brief network (DBN), and 2D-CNN-based methods—on three real-world HSI datasets captured by different sensors. Experimental results demonstrate that our 3D-CNN-based method outperforms these state-of-the-art methods and sets a new record.

Abstract: Fine roots acquire essential soil resources and mediate biogeochemical cycling in terrestrial ecosystems. Estimates of carbon and nutrient allocation to build and maintain these structures remain uncertain because of the challenges of consistently measuring and interpreting fine-root systems. Traditionally, fine roots have been defined as all roots 2mm in diameter, yet it is now recognized that this approach fails to capture the diversity of form and function observed among fine-root orders. Here, we demonstrate how order-based and functional classification frameworks improve our understanding of dynamic root processes in ecosystems dominated by perennial plants. In these frameworks, fine roots are either separated into individual root orders or functionally defined into a shorter-lived absorptive pool and a longer-lived transport fine-root pool. Using these frameworks, we estimate that fine-root production and turnover represent 22% of terrestrial net primary production globally - a c. 30% reduction from previous estimates assuming a single fine-root pool. Future work developing tools to rapidly differentiate functional fine-root classes, explicit incorporation of mycorrhizal fungi into fine-root studies, and wider adoption of a two-pool approach to model fine roots provide opportunities to better understand below-ground processes in the terrestrial biosphere.

Abstract: Importance Evidence about the efficacy of laparoscopic resection of rectal cancer is incomplete, particularly for patients with more advanced-stage disease. Objective To determine whether laparoscopic resection is noninferior to open resection, as determined by gross pathologic and histologic evaluation of the resected proctectomy specimen. Design, setting, and participants A multicenter, balanced, noninferiority, randomized trial enrolled patients between October 2008 and September 2013. The trial was conducted by credentialed surgeons from 35 institutions in the United States and Canada. A total of 486 patients with clinical stage II or III rectal cancer within 12 cm of the anal verge were randomized after completion of neoadjuvant therapy to laparoscopic or open resection. Interventions Standard laparoscopic and open approaches were performed by the credentialed surgeons. Main outcomes and measures The primary outcome assessing efficacy was a composite of circumferential radial margin greater than 1 mm, distal margin without tumor, and completeness of total mesorectal excision. A 6% noninferiority margin was chosen according to clinical relevance estimation. Results Two hundred forty patients with laparoscopic resection and 222 with open resection were evaluable for analysis of the 486 enrolled. Successful resection occurred in 81.7% of laparoscopic resection cases (95% CI, 76.8%-86.6%) and 86.9% of open resection cases (95% CI, 82.5%-91.4%) and did not support noninferiority (difference, -5.3%; 1-sided 95% CI, -10.8% to ∞; P for noninferiority = .41). Patients underwent low anterior resection (76.7%) or abdominoperineal resection (23.3%). Conversion to open resection occurred in 11.3% of patients. Operative time was significantly longer for laparoscopic resection (mean, 266.2 vs 220.6 minutes; mean difference, 45.5 minutes; 95% CI, 27.7-63.4; P Conclusions and relevance Among patients with stage II or III rectal cancer, the use of laparoscopic resection compared with open resection failed to meet the criterion for noninferiority for pathologic outcomes. Pending clinical oncologic outcomes, the findings do not support the use of laparoscopic resection in these patients. Trial registration clinicaltrials.gov Identifier: NCT00726622.

Abstract: Microglia, the resident myeloid cells of the central nervous system, play important roles in life-long brain maintenance and in pathology. Despite their crucial role, their regulatory dynamics during brain development have not been fully elucidated. Genome-wide chromatin and expression profiling coupled with single-cell transcriptomic analysis throughout development reveal that microglia undergo three temporal developmental stages in synchrony with the brain: early, pre-, and adult microglia, which are under distinct regulatory circuits. Knockout of the adult microglia transcription factor MafB and environmental perturbations, such as those affecting the microbiome or prenatal immune activation, led to disruption of developmental genes and immune response pathways. Together, our work identifies a stepwise developmental program of microglia integrating immune response pathways that may be associated with several neurodevelopmental disorders.

Abstract: Plant-associated microorganisms have been shown to critically affect host physiology and performance, suggesting that evolution and ecology of plants and animals can only be understood in a holobiont (host and its associated organisms) context. Host-associated microbial community structures are affected by abiotic and host factors, and increased attention is given to the role of the microbiome in interactions such as pathogen inhibition. However, little is known about how these factors act on the microbial community, and especially what role microbe-microbe interaction dynamics play. We have begun to address this knowledge gap for phyllosphere microbiomes of plants by simultaneously studying three major groups of Arabidopsis thaliana symbionts (bacteria, fungi and oomycetes) using a systems biology approach. We evaluated multiple potential factors of microbial community control: we sampled various wild A. thaliana populations at different times, performed field plantings with different host genotypes, and implemented successive host colonization experiments under lab conditions where abiotic factors, host genotype, and pathogen colonization was manipulated. Our results indicate that both abiotic factors and host genotype interact to affect plant colonization by all three groups of microbes. Considering microbe-microbe interactions, however, uncovered a network of interkingdom interactions with significant contributions to community structure. As in other scale-free networks, a small number of taxa, which we call microbial "hubs," are strongly interconnected and have a severe effect on communities. By documenting these microbe-microbe interactions, we uncover an important mechanism explaining how abiotic factors and host genotypic signatures control microbial communities. In short, they act directly on "hub" microbes, which, via microbe-microbe interactions, transmit the effects to the microbial community. We analyzed two "hub" microbes (the obligate biotrophic oomycete pathogen Albugo and the basidiomycete yeast fungus Dioszegia) more closely. Albugo had strong effects on epiphytic and endophytic bacterial colonization. Specifically, alpha diversity decreased and beta diversity stabilized in the presence of Albugo infection, whereas they otherwise varied between plants. Dioszegia, on the other hand, provided evidence for direct hub interaction with phyllosphere bacteria. The identification of microbial "hubs" and their importance in phyllosphere microbiome structuring has crucial implications for plant-pathogen and microbe-microbe research and opens new entry points for ecosystem management and future targeted biocontrol. The revelation that effects can cascade through communities via "hub" microbes is important to understand community structure perturbations in parallel fields including human microbiomes and bioprocesses. In particular, parallels to human microbiome "keystone" pathogens and microbes open new avenues of interdisciplinary research that promise to better our understanding of functions of host-associated microbiomes.

Abstract: Open3D is an open-source library that supports rapid development of software that deals with 3D data The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python The backend is highly optimized and is set up for parallelization Open3D was developed from a clean slate with a small and carefully considered set of dependencies It can be set up on different platforms and compiled from source with minimal effort The code is clean, consistently styled, and maintained via a clear code review mechanism Open3D has been used in a number of published research projects and is actively deployed in the cloud We welcome contributions from the open-source community

Abstract: Intel’s Software Guard Extensions (SGX) is a set of extensions to the Intel architecture that aims to provide integrity and confidentiality guarantees to securitysensitive computation performed on a computer where all the privileged software (kernel, hypervisor, etc) is potentially malicious. This paper analyzes Intel SGX, based on the 3 papers [14, 78, 137] that introduced it, on the Intel Software Developer’s Manual [100] (which supersedes the SGX manuals [94, 98]), on an ISCA 2015 tutorial [102], and on two patents [108, 136]. We use the papers, reference manuals, and tutorial as primary data sources, and only draw on the patents to fill in missing information. This paper’s contributions are a summary of the Intel-specific architectural and micro-architectural details needed to understand SGX, a detailed and structured presentation of the publicly available information on SGX, a series of intelligent guesses about some important but undocumented aspects of SGX, and an analysis of SGX’s security properties.

Abstract: We present Deep Graph Infomax (DGI), a general approach for learning node representations within graph-structured data in an unsupervised manner. DGI relies on maximizing mutual information between patch representations and corresponding high-level summaries of graphs---both derived using established graph convolutional network architectures. The learnt patch representations summarize subgraphs centered around nodes of interest, and can thus be reused for downstream node-wise learning tasks. In contrast to most prior approaches to unsupervised learning with GCNs, DGI does not rely on random walk objectives, and is readily applicable to both transductive and inductive learning setups. We demonstrate competitive performance on a variety of node classification benchmarks, which at times even exceeds the performance of supervised learning.

Abstract: Objectives To develop and validate an international set of classification criteria for primary Sjogren's syndrome (SS) using guidelines from the American College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR) These criteria were developed for use in individuals with signs and/or symptoms suggestive of SS Methods We assigned preliminary importance weights to a consensus list of candidate criteria items, using multi-criteria decision analysis We tested and adapted the resulting draft criteria using existing cohort data on primary SS cases and non-SS controls, with case/non-case status derived from expert clinical judgement We then validated the performance of the classification criteria in a separate cohort of patients Results The final classification criteria are based on the weighted sum of five items: anti-SSA/Ro antibody positivity and focal lymphocytic sialadenitis with a focus score of ≥1 foci/4 mm2, each scoring 3; an abnormal Ocular Staining Score of ≥5 (or van Bijsterveld score of ≥4), a Schirmer's test result of ≤5 mm/5 min and an unstimulated salivary flow rate of ≤01 mL/min, each scoring 1 Individuals with signs and/or symptoms suggestive of SS who have a total score of ≥4 for the above items meet the criteria for primary SS Sensitivity and specificity against clinician-expert—derived case/non-case status in the final validation cohort were high, that is, 96% (95% CI92% to 98%) and 95% (95% CI 92% to 97%), respectively Conclusion Using methodology consistent with other recent ACR/EULAR-approved classification criteria, we developed a single set of data-driven consensus classification criteria for primary SS, which performed well in validation analyses and are well suited as criteria for enrolment in clinical trials

Abstract: The MYC oncogene encodes a transcription factor, MYC, whose broad effects make its precise oncogenic role enigmatically elusive. The evidence to date suggests that MYC triggers selective gene expression amplification to promote cell growth and proliferation. Through its targets, MYC coordinates nutrient acquisition to produce ATP and key cellular building blocks that increase cell mass and trigger DNA replication and cell division. In cancer, genetic and epigenetic derangements silence checkpoints and unleash MYC9s cell growth– and proliferation-promoting metabolic activities. Unbridled growth in response to deregulated MYC expression creates dependence on MYC-driven metabolic pathways, such that reliance on specific metabolic enzymes provides novel targets for cancer therapy. Significance: MYC9s expression and activity are tightly regulated in normal cells by multiple mechanisms, including a dependence upon growth factor stimulation and replete nutrient status. In cancer, genetic deregulation of MYC expression and loss of checkpoint components, such as TP53, permit MYC to drive malignant transformation. However, because of the reliance of MYC-driven cancers on specific metabolic pathways, synthetic lethal interactions between MYC overexpression and specific enzyme inhibitors provide novel cancer therapeutic opportunities. Cancer Discov; 5(10); 1024–39. ©2015 AACR.

Abstract: Long-distance movements of animals are an important driver of population spatial dynamics and determine the extent of overlap with area-focused human activities, such as fishing. Despite global concerns of declining shark populations, a major limitation in assessments of population trends or spatial management options is the lack of information on their long-term migratory behaviour. For a large marine predator, the tiger shark Galeocerdo cuvier, we show from individuals satellitetracked for multiple years (up to 1101 days) that adult males undertake annually repeated, roundtrip migrations of over 7,500 km in the northwest Atlantic. Notably, these migrations occurred between the highly disparate ecosystems of Caribbean coral reef regions in winter and high latitude oceanic areas in summer, with strong, repeated philopatry to specific overwintering insular habitat. Partial migration also occurred, with smaller, immature individuals displaying reduced migration propensity. Foraging may be a putative motivation for these oceanic migrations, with summer behaviour showing higher path tortuosity at the oceanic range extremes. The predictable migratory patterns and use of highly divergent ecosystems shown by male tiger sharks appear broadly similar to migrations seen in birds, reptiles and mammals, and highlight opportunities for dynamic spatial management and conservation measures of highly mobile sharks.

Abstract: Adult stem cells (SCs) are essential for tissue maintenance and regeneration yet are susceptible to senescence during aging. We demonstrate the importance of the amount of the oxidized form of cellular nicotinamide adenine dinucleotide (NAD(+)) and its effect on mitochondrial activity as a pivotal switch to modulate muscle SC (MuSC) senescence. Treatment with the NAD(+) precursor nicotinamide riboside (NR) induced the mitochondrial unfolded protein response and synthesis of prohibitin proteins, and this rejuvenated MuSCs in aged mice. NR also prevented MuSC senescence in the mdx (C57BL/10ScSn-Dmd(mdx)/J) mouse model of muscular dystrophy. We furthermore demonstrate that NR delays senescence of neural SCs and melanocyte SCs and increases mouse life span. Strategies that conserve cellular NAD(+) may reprogram dysfunctional SCs and improve life span in mammals.

Abstract: Objectives United States government scientists estimate that COVID-19 may kill tens of thousands of Americans. Many of the pre-existing conditions that increase the risk of death in those with COVID-19 are the same diseases that are affected by long-term exposure to air pollution. We investigated whether long-term average exposure to fine particulate matter (PM2.5) is associated with an increased risk of COVID-19 death in the United States. Design A nationwide, cross-sectional study using county-level data. Data sources COVID-19 death counts were collected for more than 3,000 counties in the United States (representing 98% of the population) up to April 22, 2020 from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center. Main outcome measures We fit negative binomial mixed models using county-level COVID-19 deaths as the outcome and county-level long-term average of PM2.5 as the exposure. In the main analysis, we adjusted by 20 potential confounding factors including population size, age distribution, population density, time since the beginning of the outbreak, time since state’s issuance of stay-at-home order, hospital beds, number of individuals tested, weather, and socioeconomic and behavioral variables such as obesity and smoking. We included a random intercept by state to account for potential correlation in counties within the same state. We conducted more than 68 additional sensitivity analyses. Results We found that an increase of only 1 μg/m3 in PM2.5 is associated with an 8% increase in the COVID-19 death rate (95% confidence interval [CI]: 2%, 15%). The results were statistically significant and robust to secondary and sensitivity analyses. Conclusions A small increase in long-term exposure to PM2.5 leads to a large increase in the COVID-19 death rate. Despite the inherent limitations of the ecological study design, our results underscore the importance of continuing to enforce existing air pollution regulations to protect human health both during and after the COVID-19 crisis. The data and code are publicly available so our analyses can be updated routinely. Summary Box What is already known on this topic Long-term exposure to PM2.5 is linked to many of the comorbidities that have been associated with poor prognosis and death in COVID-19 patients, including cardiovascular and lung disease. PM2.5 exposure is associated with increased risk of severe outcomes in patients with certain infectious respiratory diseases, including influenza, pneumonia, and SARS. Air pollution exposure is known to cause inflammation and cellular damage, and evidence suggests that it may suppress early immune response to infection. What this study adds This is the first nationwide study of the relationship between historical exposure to air pollution exposure and COVID-19 death rate, relying on data from more than 3,000 counties in the United States. The results suggest that long-term exposure to PM2.5 is associated with higher COVID-19 mortality rates, after adjustment for a wide range of socioeconomic, demographic, weather, behavioral, epidemic stage, and healthcare-related confounders. This study relies entirely on publicly available data and fully reproducible, public code to facilitate continued investigation of these relationships by the broader scientific community as the COVID-19 outbreak evolves and more data become available. A small increase in long-term PM2.5 exposure was associated with a substantial increase in the county’s COVID-19 mortality rate up to April 22, 2020.

Abstract: AimsTo determine whether the Joint European Societies guidelines on cardiovascular prevention are being followed in everyday clinical practice of secondary prevention and to describe the lifestyle,...

Abstract: Gastric cancer remains one of the most common and deadly cancers worldwide, especially among older males. Based on GLOBOCAN 2018 data, stomach cancer is the 5th most common neoplasm and the 3rd most deadly cancer, with an estimated 783,000 deaths in 2018. Gastric cancer incidence and mortality are highly variable by region and highly dependent on diet and Helicobacter pylori infection. While strides in preventing and treating H. pylori infection have decreased the overall incidence of gastric cancer, they have also contributed to an increase in the incidence of cardia gastric cancer, a rare subtype of the neoplasm that has grown 7-fold in the past decades. A better understanding of the etiology and risk factors of the disease can help reach a consensus in approaching H. pylori infection. Dietary modification, smoking cessation, and exercise hold promise in preventing gastric cancer, while genetic testing is enabling earlier diagnosis and thus greater survival.

Abstract: Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing 10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

Abstract: Federated learning is a recent advance in privacy protection. In this context, a trusted curator aggregates parameters optimized in decentralized fashion by multiple clients. The resulting model is then distributed back to all clients, ultimately converging to a joint representative model without explicitly having to share the data. However, the protocol is vulnerable to differential attacks, which could originate from any party contributing during federated optimization. In such an attack, a client's contribution during training and information about their data set is revealed through analyzing the distributed model. We tackle this problem and propose an algorithm for client sided differential privacy preserving federated optimization. The aim is to hide clients' contributions during training, balancing the trade-off between privacy loss and model performance. Empirical studies suggest that given a sufficiently large number of participating clients, our proposed procedure can maintain client-level differential privacy at only a minor cost in model performance.

Abstract: We demonstrate the rational design and construction of sandwich-like ZnIn2S4–In2O3 hierarchical tubular heterostructures by growing ZnIn2S4 nanosheets on both inner and outer surfaces of In2O3 microtubes as photocatalysts for efficient CO2 photoreduction. The unique design integrates In2O3 and ZnIn2S4 into hierarchical one-dimensional (1D) open architectures with double-heterojunction shells and ultrathin two-dimensional (2D) nanosheet subunits. This design accelerates the separation and transfer of photogenerated charges, offers large surface area for CO2 adsorption, and exposes abundant active sites for surface catalysis. Benefiting from the structural and compositional merits, the optimized ZnIn2S4–In2O3 photocatalyst exhibits outstanding performance for reductive CO2 deoxygenation with considerable CO generation rate (3075 μmol h–1 g–1) and high stability.

Abstract: We present NewsQA, a challenging machine comprehension dataset of over 100,000 human-generated question-answer pairs. Crowdworkers supply questions and answers based on a set of over 10,000 news articles from CNN, with answers consisting of spans of text in the articles. We collect this dataset through a four-stage process designed to solicit exploratory questions that require reasoning. Analysis confirms that NewsQA demands abilities beyond simple word matching and recognizing textual entailment. We measure human performance on the dataset and compare it to several strong neural models. The performance gap between humans and machines (13.3% F1) indicates that significant progress can be made on NewsQA through future research. The dataset is freely available online.

Abstract: and death of firms, we lack even crude answers to the following basic questions regarding the dynamic processes governing an industry's structure. What are the quantitative effects of various factors on the rates of entry and exit? How well can the growth of firms be represented by Gibrat's law of proportionate effect? What have been the effects of successful innovations on a firm's growth rate? What determines the amount of mobility within an industry's size structure?' This paper provides some tentative answers to these questions. First, it constructs some simple models to estimate the effects of an industry's capital requirements, profitability, and other such factors on its entry and exit rates. Second, it investigates how well Gibrat's law of proportionate effect can represent the growth of firms in each of the industries for which we have appropriate data. Although this law has played a prominent role in models designed to explain the size distribution of firms, it has been tested only a few times against data for very large firms. Third, we estimate the difference in growth rate between firms that carried out significant innovations and other firms of comparable initial size. The results help to measure the importance of successful innovation as a cause of interfirm differences in growth rates, and they shed new light on the rewards for such innovations. Fourth, the paper presents and tests a simple model to explain interindustry and * The author is associate professor of economics at Carnegie Institute of Technology. This paper, a preliminary version of which was read at the August 1961 meetings of the Econometric Society, will be reprinted as a Cowles Foundation Paper. The work on which it is based is part

Abstract: This work provides a systematic review of the literature from January 2003 to April 2014 pertaining to the incidence, pathophysiology, diagnosis, and treatment of osteonecrosis of the jaw (ONJ), and offers recommendations for its management based on multidisciplinary international consensus. ONJ is associated with oncology-dose parenteral antiresorptive therapy of bisphosphonates (BP) and denosumab (Dmab). The incidence of ONJ is greatest in the oncology patient population (1% to 15%), where high doses of these medications are used at frequent intervals. In the osteoporosis patient population, the incidence of ONJ is estimated at 0.001% to 0.01%, marginally higher than the incidence in the general population (<0.001%). New insights into the pathophysiology of ONJ include antiresorptive effects of BPs and Dmab, effects of BPs on gamma delta T-cells and on monocyte and macrophage function, as well as the role of local bacterial infection, inflammation, and necrosis. Advances in imaging include the use of cone beam computerized tomography assessing cortical and cancellous architecture with lower radiation exposure, magnetic resonance imaging, bone scanning, and positron emission tomography, although plain films often suffice. Other risk factors for ONJ include glucocorticoid use, maxillary or mandibular bone surgery, poor oral hygiene, chronic inflammation, diabetes mellitus, ill-fitting dentures, as well as other drugs, including antiangiogenic agents. Prevention strategies for ONJ include elimination or stabilization of oral disease prior to initiation of antiresorptive agents, as well as maintenance of good oral hygiene. In those patients at high risk for the development of ONJ, including cancer patients receiving high-dose BP or Dmab therapy, consideration should be given to withholding antiresorptive therapy following extensive oral surgery until the surgical site heals with mature mucosal coverage. Management of ONJ is based on the stage of the disease, size of the lesions, and the presence of contributing drug therapy and comorbidity. Conservative therapy includes topical antibiotic oral rinses and systemic antibiotic therapy. Localized surgical debridement is indicated in advanced nonresponsive disease and has been successful. Early data have suggested enhanced osseous wound healing with teriparatide in those without contraindications for its use. Experimental therapy includes bone marrow stem cell intralesional transplantation, low-level laser therapy, local platelet-derived growth factor application, hyperbaric oxygen, and tissue grafting.

Abstract: Unsupervised learning with generative models has the potential of discovering rich representations of 3D scenes. While geometric deep learning has explored 3D-structure-aware representations of scene geometry, these models typically require explicit 3D supervision. Emerging neural scene representations can be trained only with posed 2D images, but existing methods ignore the three-dimensional structure of scenes. We propose Scene Representation Networks (SRNs), a continuous, 3D-structure-aware scene representation that encodes both geometry and appearance. SRNs represent scenes as continuous functions that map world coordinates to a feature representation of local scene properties. By formulating the image formation as a differentiable ray-marching algorithm, SRNs can be trained end-to-end from only 2D images and their camera poses, without access to depth or shape. This formulation naturally generalizes across scenes, learning powerful geometry and appearance priors in the process. We demonstrate the potential of SRNs by evaluating them for novel view synthesis, few-shot reconstruction, joint shape and appearance interpolation, and unsupervised discovery of a non-rigid face model.

Abstract: Our understanding of the role of myeloid-derived suppressor cells (MDSCs) in cancer is becoming increasingly complex. In addition to their eponymous role in suppressing immune responses, they directly support tumor growth, differentiation, and metastasis in a number of ways that are only now beginning to be appreciated. It is because of this increasingly complex role that these cells may become an important factor in the treatment of human cancer. In this Review, we discuss the most pertinent and controversial issues of MDSC biology and their role in promoting cancer progression and highlight how these cells may be used in the clinic, both as prognostic factors and as therapeutic targets.