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Wang et al. demonstrate that a mAb specific for the human microglial receptor TREM2 induces microglia proliferation, ameliorates Aβ-induced pathology in a mouse model of Alzheimer’s disease, and can be given safely in a first-in-human phase I clinical trial., TREM2 is a receptor for lipids expressed in microglia. The R47H variant of human TREM2 impairs ligand binding and increases Alzheimer’s disease (AD) risk. In mouse models of amyloid β (Aβ) accumulation, defective TREM2 function affects microglial response to Aβ plaques, exacerbating tissue damage, whereas TREM2 overexpression attenuates pathology. Thus, AD may benefit from TREM2 activation. Here, we examined the impact of an anti-human TREM2 agonistic mAb, AL002c, in a mouse AD model expressing either the common variant (CV) or the R47H variant of TREM2. Single-cell RNA-seq of microglia after acute systemic administration of AL002c showed induction of proliferation in both CV- and R47H-transgenic mice. Prolonged administration of AL002c reduced filamentous plaques and neurite dystrophy, impacted behavior, and tempered microglial inflammatory response. We further showed that a variant of AL002c is safe and well tolerated in a first-in-human phase I clinical trial and engages TREM2 based on cerebrospinal fluid biomarkers. We conclude that AL002 is a promising candidate for AD therapy., Graphical Abstract

Attribute-based access control (ABAC) is a general access control model that subsumes numerous earlier access control models. Its increasing popularity stems from the intuitive generic structure of granting permissions based on application and domain attributes of users, subjects, objects, and other entities in the system. Multiple formal and informal languages have been developed to express policies in terms of such attributes. The utility of ABAC policy languages is potentially undermined without a properly formalized underlying model. The high-level structure in a majority of ABAC models consists of sets of tokens and sets of sets, expressions that demand that the reader unpack multiple levels of sets and tokens to determine what things mean. The resulting reduced readability potentially endangers correct expression, reduces maintainability, and impedes validation. These problems could be magnified in models that employ nonuniform representations of actions and their governing policies. We propose to avoid these magnified problems by recasting the high-level structure of ABAC models in a logical formalism that treats all actions (by users and others) uniformly and that keeps existing policy languages in place by interpreting their attributes in terms of the restructured model. In comparison to existing ABAC models, use of a logical language for model formalization, including hierarchies of types of entities and attributes, promises improved expressiveness in specifying the relationships between and requirements on application and domain attributes. A logical modeling language also potentially improves flexibility in representing relationships as attributes to support some widely used policy languages. Consistency and intelligibility are improved by using uniform means for representing different types of controlled actions---such as regular access control actions, administrative actions, and user logins---and their governing policies. Logical languages also provide a well-defined denotational semantics supported by numerous formal inference and verification tools.

Data standards are a powerful, real-world tool for enterprise interoperability, yet there exists no well-grounded methodology for selecting among alternative standards approaches. We focus on a specific sub-problem within a community's data sharing challenge and identify four major standards-based approaches to that task. We present characteristics of a data sharing community that one should consider in selecting a standards approach--such as relative power, motivation level, and technical sophistication of different participants--and illustrate with real-world examples. These characteristics and other factors are then analyzed to develop decision rules for selecting among the four approaches. Independent of the data exchange problem, we suggest two general practices in choosing a standards approach: (1) vertical decomposition of interoperability issues, in order to define a narrow, formal, tractable problem, and (2) option-exclusion rules, as they are much simpler than stating optimal-choice rules.

One vexing issue in biomedical research is the failure of many therapies to translate from success in animal models to effective treatment of human disease. One significant difference between the animal models and the human disease is the age of the subject. Cancer, stroke and Alzheimer's occur mainly in humans beyond the 75% mean survival age, while most mouse models use juvenile or young adult animals. Here we compare two mouse models of amyloid deposition, the Tg2576 APP model and the more aggressive APP+PS1 model in which a mutant presenilin1 gene is overexpressed with Tg2576. Middle-aged APP+PS1 mice and aged APP mice have similar degrees of amyloid pathology with a few differences that may partially explain some of the differences between the two age cohorts. The first study evaluated production of microhemorrhage by a monoclonal anti-Aβ antibody. We found that in spite of greater amyloid clearance in middle-aged APP+PS1 mice than aged APP mice, the microhemorrhage only developed in old animals. This argues that preclinical studies of immunotherapy in young or middle-aged mice may not predict this potential liability in clinical trials. A second study evaluated the infiltration of systemically injected GFP labeled monocytes into the CNS. Here we find that infiltration is greater in aged mice than middle-aged mice, in spite of greater total Aß staining in the middle-aged animals. We conclude that preclinical studies should be conducted in aged animal models as well as young mice to better prepare for unintended consequences in the human trial.

We examine how the biomedical informatics (BMI) community, especially consortia that share data and applications, can take advantage of a new resource called “cloud computing”. Clouds generally offer resources on demand. In most clouds, charges are pay per use, based on large farms of inexpensive, dedicated servers, sometimes supporting parallel computing. Substantial economies of scale potentially yield costs much lower than dedicated laboratory systems or even institutional data centers. Overall, even with conservative assumptions, for applications that are not I/O intensive and do not demand a fully mature environment, the numbers suggested that clouds can sometimes provide major improvements, and should be seriously considered for BMI. Methodologically, it was very advantageous to formulate analyses in terms of component technologies; focusing on these specifics enabled us to bypass the cacophony of alternative definitions (e.g., exactly what does a cloud include) and to analyze alternatives that employ some of the component technologies (e.g., an institution’s data center). Relative analyses were another great simplifier. Rather than listing the absolute strengths and weaknesses of cloud-based systems (e.g., for security or data preservation), we focus on the changes from a particular starting point, e.g., individual lab systems. We often find a rough parity (in principle), but one needs to examine individual acquisitions—is a loosely managed lab moving to a well managed cloud, or a tightly managed hospital data center moving to a poorly safeguarded cloud?

Background and purpose: Calcitonin gene-related peptide (CGRP) receptor antagonists effectively abort migraine headache and inhibit neurogenic vasodilatation in humans as well as rat models. Monoclonal antibodies typically have long half-lives, and we investigated whether or not function-blocking CGRP antibodies would inhibit neurogenic vasodilatation with a long duration of action and therefore be a possible approach to preventive therapy of migraine. During chronic treatment with anti-CGRP antibodies, we measured cardiovascular function, which might be a safety concern of CGRP inhibition.

Most recent schema matching systems assemble multiple components, each employing a particular matching technique. The domain user mustthen tune the system: select the right component to be executed and correctly adjust their numerous “knobs” (e.g., thresholds, formula coefficients). Tuning is skill and time intensive, but (as we show) without it the matching accuracy is significantly inferior. We describe eTuner, an approach to automatically tune schema matching systems. Given a schema S, we match S against synthetic schemas, for which the ground truth mapping is known, and find a tuning that demonstrably improves the performance of matching S against real schemas. To efficiently search the huge space of tuning configurations, eTuner works sequentially, starting with tuning the lowest level components. To increase the applicability of eTuner, we develop methods to tune a broad range of matching components. While the tuning process is completely automatic, eTuner can also exploit user assistance (whenever available) to further improve the tuning quality. We employed eTuner to tune four recently developed matching systems on several real-world domains. The results show that eTuner produced tuned matching systems that achieve higher accuracy than using the systems with currently possible tuning methods.

Pain and cachexia are two of the most debilitating aspects of rheumatoid arthritis. Despite that, the mechanisms by which they are mediated are not well understood. We provide evidence that nerve growth factor (NGF), a secreted regulatory protein that controls neuronal survival during development, is a key mediator of pain and weight loss in auto-immune arthritis. Function blocking antibodies to NGF completely reverse established pain in rats with fully developed arthritis despite continuing joint destruction and inflammation. Likewise, these antibodies reverse weight loss while not having any effect on levels of the pro-cachectic agent tumor necrosis factor (TNF). Taken together, these findings argue that pathological joint pain and joint destruction are mechanistically independent processes and that NGF regulates an alternative cachexia pathway that is independent or downstream of TNF.

For meaningful information exchange or integration, providers and consumers need compatible semantics between source and target systems. It is widely recognized that achieving this semantic integration is very costly. Nearly all the published research concerns how system integrators can discover and exploit semantic knowledge in order to better share data among the systems they already have. This research is very important, but to make the greatest impact, we must go beyond after-the-fact semantic integration among existing systems, to actively guiding semantic choices in new ontologies and systems - e.g., what concepts should be used as descriptive vocabularies for existing data, or as definitions for newly built systems. The goal is to ease data sharing for both new and old systems, to ensure that needed data is actually collected, and to maximize over time the business value of an enterprise's information systems.

The role of microglia in the removal of amyloid deposits after systemically administered anti-Abeta antibodies remains unclear. In the current study, we injected Tg2576 APP transgenic mice weekly with an anti-Abeta antibody for 1, 2, or 3 months such that all mice were 22 months at the end of the study. In mice immunized for 3 months, we found an improvement in alternation performance in the Y maze. Histologically, we were able to detect mouse IgG bound to congophilic amyloid deposits in those mice treated with the anti-Abeta antibody but not in those treated with a control antibody. We found that Fcgamma receptor expression on microglia was increased after 1 month of treatment, whereas CD45 was increased after 2 months of treatment. Associated with these microglial changes was a reduction in both diffuse and compact amyloid deposits after 2 months of treatment. Interestingly, the microglia markers were reduced to control levels after 3 months of treatment, whereas amyloid levels remained reduced. Serum Abeta levels and anti-Abeta antibody levels were elevated to similar levels at all three survival times in mice given anti-Abeta injections rather than control antibody injections. These data show that the antibody is able to enter the brain and bind to the amyloid deposits, likely opsonizing the Abeta and resulting in Fcgamma receptor-mediated phagocytosis. Together with our earlier work, our data argue that all proposed mechanisms of anti-Abeta antibody-mediated amyloid removal can be simultaneously active.

Current big data ecosystems lack a principled approach to metadata management. This impedes large organizations' ability to share data and data preparation and analysis code, to integrate data, and to ensure that analytic code makes compatible assumptions with the data it uses. This use-case paper describes the challenges and an in-progress effort to address them. We present a real application example, discuss requirements for "big metadata" drawn from that example as well as other U.S. government analytic applications, and briefly describe an effort to adapt an existing open source metadata manager to support the needs of big data ecosystems.

The MITRE Corporation provides technical assistance, system engineering, and acquisition support to large organizations, especially U.S. Government agencies. We help our customers to plan complex systems based on emerging technologies, and to implement systems based on commercial-off-the-shelf products. In MITRE's research program, instead of emphasizing concerns of DBMS or CASE vendors, our research emphasizes the issues of organizations who need to use such products. For example, we favor areas where we can build over commercial products, rather than changing their internals.Data management at MITRE goes beyond research, to include technology transition, system engineering, product evaluation, prototypes, tutorials, advice on customers' strategic directions, and participation in standards efforts. We use prototyping to illustrate potential improvements in customer systems, to understand vendors' capabilities, or both. There are close connections with efforts in object management, real-time systems, reengineering, artificial intelligence, and security.This paper emphasizes the research efforts, grouped into five major themes: information integration, security and privacy, active and responsive systems, metrics, and digital libraries. For each theme, we list the major questions being explored, and identify projects and contacts for further information.

Systemic administration of anti-amyloid-beta (Abeta) antibodies results in reduced parenchymal amyloid but increased vascular amyloid and microhemorrhage in amyloid precursor protein (APP) transgenic mice. Here, we evaluate the effects of reducing effector interactions of the antibody via deglycosylation. Mice aged 20 months were treated weekly for 4 months and tested behaviorally before they were killed. APP transgenic mice receiving either anti-Abeta (2H6) or deglycosylated anti-Abeta (de-2H6) showed significant improvement in radial arm water maze performance compared with mice receiving a control antibody. Both groups receiving anti-Abeta antibodies showed significant reductions in total Abeta immunochemistry and Congo red. Significantly fewer vascular amyloid deposits and microhemorrhages were observed in mice administered the de-2H6 antibody compared with those receiving unmodified 2H6 antibody. Deglycosylated anti-Abeta antibodies may be preferable to unmodified IgG because they retain the cognition-enhancing and amyloid-reducing properties of anti-Abeta immunotherapy, while greatly attenuating the increased vascular amyloid deposition and microhemorrhage observed with unmodified IgG.

Background Antibodies against the Aß peptide clear Aß deposits when injected intracranially. Deglycosylated antibodies have reduced effector functions compared to their intact counterparts, potentially avoiding immune activation. Methods Deglycosylated or intact C-terminal specific high affinity anti-Aβ antibody (2H6) were intracranially injected into the right frontal cortex and hippocampus of amyloid precursor protein (APP) transgenic mice. The untreated left hemisphere was used to normalize for the extent of amyloid deposition present in each mouse. Control transgenic mice were injected with an antibody against a drosophila-specific protein (amnesiac). Tissues were examined for brain amyloid deposition and microglial responses 3 days after the injection. Results The deglycosylated 2H6 antibody had lower affinity for several murine Fcγ receptors and human complement than intact 2H6 without a change in affinity for Aß. Immunohistochemistry for Aβ and thioflavine-S staining revealed that both diffuse and compact deposits were reduced by both antibodies. In animals treated with the intact 2H6 antibody, a significant increase in Fcγ-receptor II/III immunostaining was observed compared to animals treated with the control IgG antibody. No increase in Fcγ-receptor II/III was found with the deglycosylated 2H6 antibody. Immunostaining for the microglial activation marker CD45 demonstrated a similar trend. Conclusion These findings suggest that the deglycosylated 2H6 is capable of removing both compact and diffuse plaques without activating microglia. Thus, antibodies with reduced effector functions may clear amyloid without concomitant immune activation when tested as immunotherapy for Alzheimer's disease.

We consider pragmatic issues in applying constraint-based theories (such as that developed for data exchange) to a variety of problems. We identify disconnects between theoreticians and tool developers, and propose principles for creating problem units that are appropriate for tools. Our Downstream Principle then explains why automated schema mapping is a prerequisite to transitioning schemamatching prototypes. Next, we compare concerns, strengths, and weaknesses of database and AI approaches to data exchange. Finally, we discuss how constrained update by business processes is a central difficulty in maintaining n-tier applications, and compare the challenges with data exchange and conventional view update

A key aspect of any data integration endeavor is establishing a transformation that translates instances of one or more source schemata into instances of a target schema. This schema integration task must be tackled regardless of the integration architecture or mapping formalism. In this paper we provide a task model for schema integration. We use this breakdown to motivate a workbench for schema integration in which multiple tools share a common knowledge repository. In particular, the workbench facilitates the interoperation of research prototypes for schema matching (which automatically identify likely semantic correspondences) with commercial schema mapping tools (which help produce instance-level transformations). Currently, each of these tools provides its own ad hoc representation of schemata and mappings; combining these tools requires aligning these representations. The workbench provides a common representation so that these tools can more rapidly be combined.

Nerve growth factor (NGF) was identified originally as a survival factor for sensory and sympathetic neurons in the developing nervous system. In adults, NGF is not required for survival but it has a crucial role in the generation of pain and hyperalgesia in several acute and chronic pain states. The expression of NGF is high in injured and inflamed tissues, and activation of the NGF receptor tyrosine kinase trkA on nociceptive neurons triggers and potentiates pain signalling by multiple mechanisms. Inhibition of NGF function and signalling blocks pain sensation as effectively as cyclooxygenase inhibitors and opiates in rodent models of pain. Several pharmaceutical companies have active drug-discovery and development programs that are based on a variety of approaches to antagonise NGF, including NGF 'capture', blocking the binding of NGF to trkA and inhibiting trkA signalling. NGF antagonism is expected to be a highly effective therapeutic approach in many pain states, and to be free of the adverse effects of traditional analgesic drugs.

Access-control mechanisms in distributed systems can differ greatly. For example , a data warehouse materializes a separate database; the underlying source administrators then grant full privileges on their contributed data to the warehouse administrator, trusting that he will grant appropriate privileges on the warehouse data. On the other hand, federated database researchers have source and federation administrators collaborating to specify the rights of federation users. Research papers have proposed access-control models specifically for federations, distributed-object systems, XML systems, etc.

Privileges in standard SQL are unconditional, forcing the grantor to trust the recipient’s discretion completely. We propose an extension to the SQL grant/revoke security model that allows a grantor to impose limitations on how the received privilege may be used. This extension also has a non-traditional implication for view security. Although our examples are from DBMSs, most results apply to arbitrary sets of privileges, in non-database software.

We show how a wide variety of role-based access control policies may be formally specified in the stratified subset of clause form logic. We then show how these formal specifications may be automatically translated into a small subset of SQL to be used to seamlessly protect an SQL database from unauthorized read and update requests made by authenticated users. We demonstrate the power of our approach by showing how a variety of access control policies can be represented.

The database and document worlds have traditionally had different approaches to security. Databases provide access controls on structured data, while document security interrogates the outgoing information, based on document markings and actual contents. For the emerging world in which many documents are generated from structured data (and vice versa), the separation can cause failure, implementation-dependence, inconsistency, and wasted effort. After comparing approaches and mechanisms in the two areas, we identify issues in security administration and implementation in military and medical applications. We then present elements of a unifying model.

Security administration is harder in databases that have multiple layers of derived data, such as federations, warehouses, or systems with many views. Meta-data (e.g., security requirements) expressed at each layer must be visible and understood at the other layer. We describe several use cases in which layers negotiate to reconcile their business requirements. The sources must grant enough privileges for the derived layer to support the applications; the derived layer must enforce enough restrictions so that the sources’ concerns are met; and the relationship between the privileges at source and derived layer must be visible and auditable.

The application development lifecycle is undergoing several grand unifications that, together, will rescue conceptual modeling from the wilderness. At the same time, advances in data warehouses and middleware are removing some of the software barriers to large, multi-organizational databases, creating new data administration challenges. The increasing scale and complexity of our systems identify new "grand challenges" to data administration research; we discuss two of these, in some detail: the administration of multi-tier schema, and exploiting legacy or "foreign" data during the development of new application schemas. We illustrate these issues with examples taken from the United States Department of Defense (DOD).

Determining attribute correspondences is a difficult, time-consuming, knowledge-intensive part of database integration. We report on experiences with tools that identified candidate correspondences, as a step in a large scale effort to improve communication among Air Force systems. First, we describe a new method that was both simple and surprisingly successful: Data dictionary and catalog information were dumped to unformatted text; then off-the-shelf information retrieval software estimated string similarity, generated candidate matches, and provided the interface. The second method used a different set of clues, such as statistics on database populations, to compute separate similarity metrics (using neural network techniques). We report on substantial use of the first tool, and then report some limited initial experiments that examine the two techniques’ accuracy, consistency and complementarity.

Anti-Aβ immunotherapy in transgenic mice reduces both diffuse and compact amyloid deposits, improves memory function and clears early-stage phospho-tau aggregates. As most Alzheimer disease cases occur well past midlife, the current study examined adoptive transfer of anti-Aβ antibodies to 19- and 23-month old APP-transgenic mice. We investigated the effects of weekly anti-Aβ antibody treatment on radial-arm water-maze performance, parenchymal and vascular amyloid loads, and the presence of microhemorrhage in the brain. 19-month-old mice were treated for 1, 2 or 3 months while 23-month-old mice were treated for 5 months. Only the 23-month-old mice were subject to radial-arm water-maze testing. After 3 months of weekly injections, this passive immunization protocol completely reversed learning and memory deficits in these mice, a benefit that was undiminished after 5 months of treatment. Dramatic reductions of diffuse Aβ immunostaining and parenchymal Congophilic amyloid deposits were observed after five months, indicating that even well-established amyloid deposits are susceptible to immunotherapy. However, cerebral amyloid angiopathy increased substantially with immunotherapy, and some deposits were associated with microhemorrhage. Reanalysis of results collected from an earlier time-course study demonstrated that these increases in vascular deposits were dependent on the duration of immunotherapy. The cognitive benefits of passive immunotherapy persist in spite of the presence of vascular amyloid and small hemorrhages. These data suggest that clinical trials evaluating such treatments will require precautions to minimize potential adverse events associated with microhemorrhage.

The HiPAC (High Performance ACtive database system) project addresses two critical problems in time-constrained data management: the handling of timing constraints in databases, and the avoidance of wasteful polling through the use of situation-action rules that are an integral part of the database and are monitored by DBMS's condition monitor. A rich knowledge model provides the necessary primitives for definition of timing constraints, situation-action rules, and precipitating events. The execution model allows various coupling modes between transactions, situation evaluations and actions, and provides the framework for correct concurrent execution of transactions and triggered actions. Different approaches to scheduling of time-constrained tasks and transactions are explored and an architecture is being designed with special emphasis on the interaction of the time-constrained, active DBMS and the operating system. Performance models are developed to evaluate the various design alternatives.