What the biological cell, organ, or barrier actually "sees" when interacting with a nanoparticle dispersed in a biological medium likely matters more than the bare material properties of the particle itself. Typically the bare surface of the particle is covered by several biomolecules, including a select group of proteins drawn from the biological medium. Here, we apply several different methodologies, in a time-resolved manner, to follow the lifetime of such biomolecular "coronas" both in situ and isolated from the excess plasma. We find that such particle-biomolecule complexes can be physically isolated from the surrounding medium and studied in some detail, without altering their structure. For several nanomaterial types, we find that blood plasma-derived coronas are sufficiently long-lived that they, rather than the nanomaterial surface, are likely to be what the cell sees. From fundamental science to regulatory safety, current efforts to classify the biological impacts of nanomaterials (currently according to bare material type and bare surface properties) may be assisted by the methodology and understanding reported here.
Anthropomorphism is a far-reaching phenomenon that incorporates ideas from social psychology, cognitive psychology, developmental psychology, and the neurosciences. Although commonly considered to be a relatively universal phenomenon with only limited importance in modern industrialized societies-more cute than critical-our research suggests precisely the opposite. In particular, we provide a measure of stable individual differences in anthropomorphism that predicts three important consequences for everyday life. This research demonstrates that individual differences in anthropomorphism predict the degree of moral care and concern afforded to an agent, the amount of responsibility and trust placed on an agent, and the extent to which an agent serves as a source of social influence on the self. These consequences have implications for disciplines outside of psychology including human-computer interaction, business (marketing and finance), and law. Concluding discussion addresses how understanding anthropomorphism not only informs the burgeoning study of nonpersons, but how it informs classic issues underlying person perception as well.
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We present a technique for adding global context to deep convolutional networks for semantic segmentation. The approach is simple, using the average feature for a layer to augment the features at each location. In addition, we study several idiosyncrasies of training, significantly increasing the performance of baseline networks (e.g. from FCN). When we add our proposed global feature, and a technique for learning normalization parameters, accuracy increases consistently even over our improved versions of the baselines. Our proposed approach, ParseNet, achieves state-of-the-art performance on SiftFlow and PASCAL-Context with small additional computational cost over baselines, and near current state-of-the-art performance on PASCAL VOC 2012 semantic segmentation with a simple approach. Code is available at https://github.com/weiliu89/caffe/tree/fcn .
Despite the remarkable thermochemical accuracy of Kohn–Sham density-functional theories with gradient corrections for exchange-correlation [see, for example, A. D. Becke, J. Chem. Phys. 96, 2155 (1992)], we believe that further improvements are unlikely unless exact-exchange information is considered. Arguments to support this view are presented, and a semiempirical exchange-correlation functional containing local-spin-density, gradient, and exact-exchange terms is tested on 56 atomization energies, 42 ionization potentials, 8 proton affinities, and 10 total atomic energies of first- and second-row systems. This functional performs significantly better than previous functionals with gradient corrections only, and fits experimental atomization energies with an impressively small average absolute deviation of 2.4 kcal/mol.
T HE HISTOLOGIC categorization of lymphoma has been a source of frustration for many years for both clinicians and pathologists.In the last 10 years, much new information has become available about the lymphomas, resulting in recognition of new entities and refinement of previously recognized disease categories, raising the question of whether it is time for a new lymphoma classification.In this paper we report the result of an international review of lymphomas, which we hope may clarify some of the confusion surrounding this topic.This review was conducted at a meeting of 19 hematopathologists with particular interest and experience in lymphomas (the International Lymphoma Study Group) in Berlin, Germany, in April 1993.At previous meetings in Europe and the United States, we had come to believe that, despite the variety of classification schemes used, many hematopathologists appeared to agree on a rather large number of distinct lymphoma entities that they recognize and diagnose in daily practice.We believed that we could provide a useful service to both pathologists and clinicians struggling with the classification of lymphomas by attempting to arrive at a consensus regarding the categories of lymphoid neoplasia that can be reliably recognized at present.What emerged from this meeting was, first, that each of us had independently evolved ways of viewing these diseases that were essentially identical.Surprisingly, there was little divergence between European and US participants.Second, it was evident that, while many of these lymphoma entities are recognized in the Kiel Classification,"6 the Lukes-Collins Classification,' and the Working Formulation,* they often go by different names in different publications and may have variable criteria for diagno~is.~Furthermore, we found that many of us had doubts about both the practical feasibility and the scientific validity of distinguishing certain subtypes in these systems.We also found that while some lymphoma categories are easy to recognize, others are disturbingly prone to subjective variability.This feature of lymphoma diagnosis has not been emphasized in previous schemes for classification, which imply that all categories are equally easy for the pathologist to recognize.Ideally lymphomas, like most other tumors, should be classified according to their presumed normal counterpart, to the extent possible.This should provide the best information about disease biology, natural history, and response to treatment.However, despite extensive study, the definition of lymphoid compartments in humans and movement of cells between these compartments still contains many uncertainties.Furthermore, there are difficulties in defining the full extent of the neoplastic clone in individual cases of lymphoma, and some well-defined lymphoma types lack obvious normal counterparts.Consequently, although differentiation schemes provide useful conceptual frameworks for
Eutectic mixtures of urea and a range of quaternary ammonium salts are liquid at ambient temperatures and have interesting solvent properties.
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This article addresses potential effects on reflexivity of researcher’s social position (e.g. gender, age, race, immigration status, sexual orientation), personal experiences, and political and professional beliefs. Because reflexivity is a major strategy for quality control in qualitative research, understanding how it may be impacted by the characteristics and experiences of the researcher is of paramount importance. Benefits and challenges to reflexivity under three types of researcher’s position are discussed and illustrated by means of case examples: (1) reflexivity when researcher shares the experience of study participants, (2) reflexivity when researcher moves from the position of an outsider to the position of an insider in the course of the study, and (3) reflexivity when researcher has no personal familiarity or experience with what is being studied. Strategies are offered for harvesting the benefits of researcher’s familiarity with the subject and for curbing its potentially negative effects. Directions for future research are suggested.
When looking at a scene, observers feel that they see its entire structure in great detail and can immediately notice any changes in it However, when brief blank fields are placed between alternating displays of an original and a modified scene, a striking failure of perception is induced Identification of changes becomes extremely difficult, even when changes are large and made repeatedly Identification is much faster when a verbal cue is provided showing that poor visibility is not the cause of this difficulty Identification is also faster for objects considered to be important in the scene These results support the idea that observers never form a complete, detailed representation of their surroundings In addition, the results indicate that attention is required to perceive change, and that in the absence of localized motion signals attention is guided on the basis of high-level interest
Acknowledgments 1. What Is It Like to be a Monkey? 2. Social Behavior 3. Social Knowledge 4. Vocal Communication 5. What the Vocalizations of Monkeys Mean 6. Summarizing the Mental Representations of Vocalizations and Social Relationships 7. Deception 8. Attribution 9. Social and Nonsocial Intelligence 10. How Monkeys See the World Appendix References Index
Multicentric Castleman's disease (MCD) is an atypical lymphoproliferative disorder defined using clinical and pathologic criteria. A characteristic of the MCD is a close association with Kaposi's sarcoma (KS), which occurs during the clinical course of most human immunodeficiency virus (HIV)-associated MCD cases and also, but less frequently, in HIV-negative patients. Recently, sequences of a putative new Herpesvirus (KSHV) have been isolated and further detected in almost all the acquired immunodeficiency syndrome (AIDS) KS and in most of the non-AIDS KS samples. In this study, we searched for these Herpesvirus-like sequences in MCD samples of 31 patients. KSHV sequences were detected in 14 of 14 cases of HIV-associated MCD, including 5 cases without detectable KS. Moreover, KSHV was detected in 7 of 17 MCD cases in HIV-negative patients, including 1 case associated with a cutaneous KS. In 34 non-MCD reactive lymph nodes (follicular and/or interfollicular hyperplasia) in HIV-negative patients, KSHV was detected in only 1 case. In 1 HIV-negative case of MCD, KSHV was found in both the lymph node and peripheral blood samples. These data suggest that KSHV could play a role in the pathogenesis of MCD, especially in HIV-infected patients.
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The immune reactivity of allogeneic lymphocytes plays a major role in the control of leukemia after bone marrow transplantation. In patients with recurrent leukemia after marrow transplantation, chimerism and tolerance provide ideal conditions for adoptive immunotherapy with donor lymphocytes. We studied the effect of donor lymphocyte transfusions on acute and chronic leukemia in relapse after bone marrow transplantation. One hundred thirty-five patients with chronic myeloid leukemia (CML) (N = 84), acute myeloid leukemia (AML) (N = 23), acute lymphoblastic leukemia (ALL) (N = 22), myelodysplastic syndrome (MDS) (N = 5), and polycythemia vera with osteomyelofibrosis (PCV) (N = 1) were treated with transfusions of donor lymphocytes. Patients were monitored for response of leukemia, including in CML, the use of the polymerase chain reaction for bcr/abl mRNA transcripts and for the occurrence of graft-versus-host disease (GVHD) and myelosuppression. Complete remissions were induced by donor lymphocyte transfusions in 54 patients with CML (73%) and in the patient with PCV; complete remissions were also induced in five patients (29%) with AML and a patient with MDS. In contrast, ALL did not respond to adoptive immunotherapy with donor lymphocyte transfusions. Remissions were durable in patients treated for CML in chronic phase (probability of remission: 87% at 3 years). Lymphocyte transfusions were also given to 18 patients with ALL, AML, MDS, and transformed phase CML who were in remission after chemotherapy. These remissions were not durable. Fifty-two patients (41%) developed GVHD of grade 2 or more, and 41 patients (34%) showed signs of myelosuppression. Seventeen patients died without leukemia, 14 patients with GVHD and/or myelosuppression. Donor lymphocyte transfusions exert strong effects against myeloid forms of leukemia and induce durable remissions in CML.
The gap between research and practice is well documented. We address one of the underlying reasons for this gap: the assumption that effectiveness research naturally and logically follows from successful efficacy research. These 2 research traditions have evolved different methods and values; consequently, there are inherent differences between the characteristics of a successful efficacy intervention versus those of an effectiveness one. Moderating factors that limit robustness across settings, populations, and intervention staff need to be addressed in efficacy studies, as well as in effectiveness trials. Greater attention needs to be paid to documenting intervention reach, adoption, implementation, and maintenance. Recommendations are offered to help close the gap between efficacy and effectiveness research and to guide evaluation and possible adoption of new programs.
OBJECTIVE: Statistical models, such as linear or logistic regression or survival analysis, are frequently used as a means to answer scientific questions in psychosomatic research. Many who use these techniques, however, apparently fail to appreciate fully the problem of overfitting, ie, capitalizing on the idiosyncrasies of the sample at hand. Overfitted models will fail to replicate in future samples, thus creating considerable uncertainty about the scientific merit of the finding. The present article is a nontechnical discussion of the concept of overfitting and is intended to be accessible to readers with varying levels of statistical expertise. The notion of overfitting is presented in terms of asking too much from the available data. Given a certain number of observations in a data set, there is an upper limit to the complexity of the model that can be derived with any acceptable degree of uncertainty. Complexity arises as a function of the number of degrees of freedom expended (the number of predictors including complex terms such as interactions and nonlinear terms) against the same data set during any stage of the data analysis. Theoretical and empirical evidence--with a special focus on the results of computer simulation studies--is presented to demonstrate the practical consequences of overfitting with respect to scientific inference. Three common practices--automated variable selection, pretesting of candidate predictors, and dichotomization of continuous variables--are shown to pose a considerable risk for spurious findings in models. The dilemma between overfitting and exploring candidate confounders is also discussed. Alternative means of guarding against overfitting are discussed, including variable aggregation and the fixing of coefficients a priori. Techniques that account and correct for complexity, including shrinkage and penalization, also are introduced.
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Recognizing fine-grained categories (e.g., bird species) is difficult due to the challenges of discriminative region localization and fine-grained feature learning. Existing approaches predominantly solve these challenges independently, while neglecting the fact that region detection and fine-grained feature learning are mutually correlated and thus can reinforce each other. In this paper, we propose a novel recurrent attention convolutional neural network (RA-CNN) which recursively learns discriminative region attention and region-based feature representation at multiple scales in a mutual reinforced way. The learning at each scale consists of a classification sub-network and an attention proposal sub-network (APN). The APN starts from full images, and iteratively generates region attention from coarse to fine by taking previous prediction as a reference, while the finer scale network takes as input an amplified attended region from previous scale in a recurrent way. The proposed RA-CNN is optimized by an intra-scale classification loss and an inter-scale ranking loss, to mutually learn accurate region attention and fine-grained representation. RA-CNN does not need bounding box/part annotations and can be trained end-to-end. We conduct comprehensive experiments and show that RA-CNN achieves the best performance in three fine-grained tasks, with relative accuracy gains of 3.3%, 3.7%, 3.8%, on CUB Birds, Stanford Dogs and Stanford Cars, respectively.
DIOPATHIC thrombocytopenic purpura (ITP, also I known as primary immune thrombocytopenic purpura) is a hematologic disorder for which appropriate diagnostic and treatment strategies are uncertain. In 1994, the American Society of Hematology (ASH) established a panel to produce explicitly developed practice guidelines for the diagnosis and management of ITP. “Explicitly developed,” evidencebased practice guidelines, which are being issued increasingly by medical specialty societies, combine a critical appraisal of scientific evidence with practice recommendations that state clearly to what extent the guidelines are based either on published scientific evidence or opinion (eg, clinical experience).I4 More details about the clinical practice guideline movement are provided elsewhere.’.’ This report begins with a brief summary of the panel’s recommendations, followed by a more detailed analysis of its methodology, the findings of the comprehensive literature review, and a full presentation of the recommendations. The report concludes with recommendations for future research. As explained later, the recommendations are based on the panel’s opinion, derived from a systematic scoring methodology. (Only recommendations receiving scores of 1 .O to 3.0 or 7.0 to 9.0, as defined later in the text, are cited in this summary.)