The concept of a default mode of brain function arose out of a focused need to explain the appearance of activity decreases in functional neuroimaging data when the control state was passive visual fixation or eyes closed resting. The problem was particularly compelling because these activity decreases were remarkably consistent across a wide variety of task conditions. Using PET, we determined that these activity decreases did not arise from activations in the resting state. Hence, their presence implied the existence of a default mode. While the unique constellation of brain areas provoking this analysis has come to be known as the default system, all areas of the brain have a high level of organized default functional activity. Most critically, this work has called attention to the importance of intrinsic functional activity in assessing brain behavior relationships.

Is perception of the whole based on perception of its parts? There is psychological and physiological evidence for parts-based representations in the brain, and certain computational theories of object recognition rely on such representations. But little is known about how brains or computers might learn the parts of objects. Here we demonstrate an algorithm for non-negative matrix factorization that is able to learn parts of faces and semantic features of text. This is in contrast to other methods, such as principal components analysis and vector quantization, that learn holistic, not parts-based, representations. Non-negative matrix factorization is distinguished from the other methods by its use of non-negativity constraints. These constraints lead to a parts-based representation because they allow only additive, not subtractive, combinations. When non-negative matrix factorization is implemented as a neural network, parts-based representations emerge by virtue of two properties: the firing rates of neurons are never negative and synaptic strengths do not change sign.

The aim of many analyses of large databases is to draw causal inferences about the effects of actions, treatments, or interventions. Examples include the effects of various options available to a physician for treating a particular patient, the relative efficacies of various health care providers, and the consequences of implementing a new national health care policy. A complication of using large databases to achieve such aims is that their data are almost always observational rather than experimental. That is, the data in most large data sets are not based on the results of carefully conducted randomized clinical trials, but rather represent data collected through the observation of systems as they operate in normal practice without any interventions implemented by randomized assignment rules. Such data are relatively inexpensive to obtain, however, and often do represent the spectrum of medical practice better than the settings of randomized experiments. Consequently, it is sensible to try to estimate the effects of treatments from such large data sets, even if only to help design a new randomized experiment or shed light on the generalizability of results from existing randomized experiments. However, standard methods of analysis using available statistical software (such as linear or logistic regression) can be deceptive for these objectives because they provide no warnings about their propriety. Propensity score methods are more reliable tools for addressing such objectives because the assumptions needed to make their answers appropriate are more assessable and transparent to the investigator.

The factors regulating the expression of microRNAs (miRNAs), a ubiquitous family of approximately 22-nt noncoding regulatory RNAs, remain undefined. However, it is known that miRNAs are first transcribed as a largely unstructured precursor, termed a primary miRNA (pri-miRNA), which is sequentially processed in the nucleus, to give the approximately 65-nt pre-miRNA hairpin intermediate, and then in the cytoplasm, to give the mature miRNA. Here we have sought to identify the RNA polymerase responsible for miRNA transcription and to define the structure of a full-length human miRNA. We show that the pri-miRNA precursors for nine human miRNAs are both capped and polyadenylated and report the sequence of the full-length, approximately 3433-nt pri-miR-21 RNA. This pri-miR-21 gene sequence is flanked 5' by a promoter element able to transcribe heterologous mRNAs and 3' by a consensus polyadenylation sequence. Nuclear processing of pri-miRNAs was found to be efficient, thus largely preventing the nuclear export of full-length pri-miRNAs. Nevertheless, an intact miRNA stem-loop precursor located in the 3' UTR of a protein coding gene only moderately inhibited expression of the linked open reading frame, probably because the 3' truncated mRNA could still be exported and expressed. Together, these data show that human pri-miRNAs are not only structurally similar to mRNAs but can, in fact, function both as pri-miRNAs and mRNAs.

BACKGROUND

Insulin resistance appears to be the best predictor of the development of diabetes in the children of patients with type 2 diabetes, but the mechanism responsible is unknown.

METHODS

We performed hyperinsulinemic-euglycemic clamp studies in combination with infusions of [6,6-(2)H(2)]glucose in healthy, young, lean, insulin-resistant offspring of patients with type 2 diabetes and insulin-sensitive control subjects matched for age, height, weight, and physical activity to assess the sensitivity of liver and muscle to insulin. Proton ((1)H) magnetic resonance spectroscopy studies were performed to measure intramyocellular lipid and intrahepatic triglyceride content. Rates of whole-body and subcutaneous fat lipolysis were assessed by measuring the rates of [(2)H(5)]glycerol turnover in combination with microdialysis measurements of glycerol release from subcutaneous fat. We performed (31)P magnetic resonance spectroscopy studies to assess the rates of mitochondrial oxidative-phosphorylation activity in muscle.

RESULTS

The insulin-stimulated rate of glucose uptake by muscle was approximately 60 percent lower in the insulin-resistant subjects than in the insulin-sensitive control subjects (P<0.001) and was associated with an increase of approximately 80 percent in the intramyocellular lipid content (P=0.005). This increase in intramyocellular lipid content was most likely attributable to mitochondrial dysfunction, as reflected by a reduction of approximately 30 percent in mitochondrial phosphorylation (P=0.01 for the comparison with controls), since there were no significant differences in systemic or localized rates of lipolysis or plasma concentrations of tumor necrosis factor alpha, interleukin-6, resistin, or adiponectin.

CONCLUSIONS

These data support the hypothesis that insulin resistance in the skeletal muscle of insulin-resistant offspring of patients with type 2 diabetes is associated with dysregulation of intramyocellular fatty acid metabolism, possibly because of an inherited defect in mitochondrial oxidative phosphorylation.

Because depression and painful symptoms commonly occur together, we conducted a literature review to determine the prevalence of both conditions and the effects of comorbidity on diagnosis, clinical outcomes, and treatment. The prevalences of pain in depressed cohorts and depression in pain cohorts are higher than when these conditions are individually examined. The presence of pain negatively affects the recognition and treatment of depression. When pain is moderate to severe, impairs function, and/or is refractory to treatment, it is associated with more depressive symptoms and worse depression outcomes (eg, lower quality of life, decreased work function, and increased health care utilization). Similarly, depression in patients with pain is associated with more pain complaints and greater impairment. Depression and pain share biological pathways and neurotransmitters, which has implications for the treatment of both concurrently. A model that incorporates assessment and treatment of depression and pain simultaneously is necessary for improved outcomes.

Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we first derive an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection. Then, we present a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers). This allows us to select a compact set of superior features at very low cost. We perform extensive experimental comparison of our algorithm and other methods using three different classifiers (naive Bayes, support vector machine, and linear discriminate analysis) and four different data sets (handwritten digits, arrhythmia, NCI cancer cell lines, and lymphoma tissues). The results confirm that mRMR leads to promising improvement on feature selection and classification accuracy.

In addition to intracellular organelles, eukaryotic cells also contain extracellular organelles that are released, or shed, into the microenvironment. These membranous extracellular organelles include exosomes, shedding microvesicles (SMVs) and apoptotic blebs (ABs), many of which exhibit pleiotropic biological functions. Because extracellular organelle terminology is often confounding, with many preparations reported in the literature being mixtures of extracellular vesicles, there is a growing need to clarify nomenclature and to improve purification strategies in order to discriminate the biochemical and functional activities of these moieties. Exosomes are formed by the inward budding of multivesicular bodies (MVBs) and are released from the cell into the microenvironment following the fusion of MVBs with the plasma membrane (PM). In this review we focus on various strategies for purifying exosomes and discuss their biophysical and biochemical properties. An update on proteomic analysis of exosomes from various cell types and body fluids is provided and host-cell specific proteomic signatures are also discussed. Because the ectodomain of ~42% of exosomal integral membrane proteins are also found in the secretome, these vesicles provide a potential source of serum-based membrane protein biomarkers that are reflective of the host cell. ExoCarta, an exosomal protein and RNA database (http://exocarta.ludwig.edu.au), is described.

Caspase-1 activation by inflammasome scaffolds comprised of intracellular nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) and the adaptor ASC is believed to be essential for production of the pro-inflammatory cytokines interleukin (IL)-1β and IL-18 during the innate immune response. Here we show, with C57BL/6 Casp11 gene-targeted mice, that caspase-11 (also known as caspase-4) is critical for caspase-1 activation and IL-1β production in macrophages infected with Escherichia coli, Citrobacter rodentium or Vibrio cholerae. Strain 129 mice, like Casp11(-/-) mice, exhibited defects in IL-1β production and harboured a mutation in the Casp11 locus that attenuated caspase-11 expression. This finding is important because published targeting of the Casp1 gene was done using strain 129 embryonic stem cells. Casp1 and Casp11 are too close in the genome to be segregated by recombination; consequently, the published Casp1(-/-) mice lack both caspase-11 and caspase-1. Interestingly, Casp11(-/-) macrophages secreted IL-1β normally in response to ATP and monosodium urate, indicating that caspase-11 is engaged by a non-canonical inflammasome. Casp1(-/-)Casp11(129mt/129mt) macrophages expressing caspase-11 from a C57BL/6 bacterial artificial chromosome transgene failed to secrete IL-1β regardless of stimulus, confirming an essential role for caspase-1 in IL-1β production. Caspase-11 rather than caspase-1, however, was required for non-canonical inflammasome-triggered macrophage cell death, indicating that caspase-11 orchestrates both caspase-1-dependent and -independent outputs. Caspase-1 activation by non-canonical stimuli required NLRP3 and ASC, but caspase-11 processing and cell death did not, implying that there is a distinct activator of caspase-11. Lastly, loss of caspase-11 rather than caspase-1 protected mice from a lethal dose of lipopolysaccharide. These data highlight a unique pro-inflammatory role for caspase-11 in the innate immune response to clinically significant bacterial infections.

OBJECTIVE

Autism spectrum disorders (ASDs) are a group of developmental disabilities characterized by impairments in social interaction and communication and by restricted, repetitive, and stereotyped patterns of behavior. Symptoms typically are apparent before age 3 years. The complex nature of these disorders, coupled with a lack of biologic markers for diagnosis and changes in clinical definitions over time, creates challenges in monitoring the prevalence of ASDs. Accurate reporting of data is essential to understand the prevalence of ASDs in the population and can help direct research.

METHODS

2008.

METHODS

The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that estimates the prevalence of ASDs and describes other characteristics among children aged 8 years whose parents or guardians reside within 14 ADDM sites in the United States. ADDM does not rely on professional or family reporting of an existing ASD diagnosis or classification to ascertain case status. Instead, information is obtained from children's evaluation records to determine the presence of ASD symptoms at any time from birth through the end of the year when the child reaches age 8 years. ADDM focuses on children aged 8 years because a baseline study conducted by CDC demonstrated that this is the age of identified peak prevalence. A child is included as meeting the surveillance case definition for an ASD if he or she displays behaviors (as described on a comprehensive evaluation completed by a qualified professional) consistent with the American Psychiatric Association's Diagnostic and Statistical Manual-IV, Text Revision (DSM-IV-TR) diagnostic criteria for any of the following conditions: Autistic Disorder; Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS, including Atypical Autism); or Asperger Disorder. The first phase of the ADDM methodology involves screening and abstraction of comprehensive evaluations completed by professional providers at multiple data sources in the community. Multiple data sources are included, ranging from general pediatric health clinics to specialized programs for children with developmental disabilities. In addition, many ADDM sites also review and abstract records of children receiving special education services in public schools. In the second phase of the study, all abstracted evaluations are reviewed by trained clinicians to determine ASD case status. Because the case definition and surveillance methods have remained consistent across all ADDM surveillance years to date, comparisons to results for earlier surveillance years can be made. This report provides updated ASD prevalence estimates from the 2008 surveillance year, representing 14 ADDM areas in the United States. In addition to prevalence estimates, characteristics of the population of children with ASDs are described, as well as detailed comparisons of the 2008 surveillance year findings with those for the 2002 and 2006 surveillance years.

RESULTS

For 2008, the overall estimated prevalence of ASDs among the 14 ADDM sites was 11.3 per 1,000 (one in 88) children aged 8 years who were living in these communities during 2008. Overall ASD prevalence estimates varied widely across all sites (range: 4.8-21.2 per 1,000 children aged 8 years). ASD prevalence estimates also varied widely by sex and by racial/ethnic group. Approximately one in 54 boys and one in 252 girls living in the ADDM Network communities were identified as having ASDs. Comparison of 2008 findings with those for earlier surveillance years indicated an increase in estimated ASD prevalence of 23% when the 2008 data were compared with the data for 2006 (from 9.0 per 1,000 children aged 8 years in 2006 to 11.0 in 2008 for the 11 sites that provided data for both surveillance years) and an estimated increase of 78% when the 2008 data were compared with the data for 2002 (from 6.4 per 1,000 children aged 8 years in 2002 to 11.4 in 2008 for the 13 sites that provided data for both surveillance years). Because the ADDM Network sites do not make up a nationally representative sample, these combined prevalence estimates should not be generalized to the United States as a whole.

CONCLUSIONS

These data confirm that the estimated prevalence of ASDs identified in the ADDM network surveillance populations continues to increase. The extent to which these increases reflect better case ascertainment as a result of increases in awareness and access to services or true increases in prevalence of ASD symptoms is not known. ASDs continue to be an important public health concern in the United States, underscoring the need for continued resources to identify potential risk factors and to provide essential supports for persons with ASDs and their families.

CONCLUSIONS

Given substantial increases in ASD prevalence estimates over a relatively short period, overall and within various subgroups of the population, continued monitoring is needed to quantify and understand these patterns. With 5 biennial surveillance years completed in the past decade, the ADDM Network continues to monitor prevalence and characteristics of ASDs and other developmental disabilities for the 2010 surveillance year. Further work is needed to evaluate multiple factors contributing to increases in estimated ASD prevalence over time. ADDM Network investigators continue to explore these factors, with a focus on understanding disparities in the identification of ASDs among certain subgroups and on how these disparities have contributed to changes in the estimated prevalence of ASDs. CDC is partnering with other federal and private partners in a coordinated response to identify risk factors for ASDs and to meet the needs of persons with ASDs and their families.

Microbial communities are vital in the functioning of all ecosystems; however, most microorganisms are uncultivated, and their roles in natural systems are unclear. Here, using random shotgun sequencing of DNA from a natural acidophilic biofilm, we report reconstruction of near-complete genomes of Leptospirillum group II and Ferroplasma type II, and partial recovery of three other genomes. This was possible because the biofilm was dominated by a small number of species populations and the frequency of genomic rearrangements and gene insertions or deletions was relatively low. Because each sequence read came from a different individual, we could determine that single-nucleotide polymorphisms are the predominant form of heterogeneity at the strain level. The Leptospirillum group II genome had remarkably few nucleotide polymorphisms, despite the existence of low-abundance variants. The Ferroplasma type II genome seems to be a composite from three ancestral strains that have undergone homologous recombination to form a large population of mosaic genomes. Analysis of the gene complement for each organism revealed the pathways for carbon and nitrogen fixation and energy generation, and provided insights into survival strategies in an extreme environment.

Qualitative research methods could help us to improve our understanding of medicine. Rather than thinking of qualitative and quantitative strategies as incompatible, they should be seen as complementary. Although procedures for textual interpretation differ from those of statistical analysis, because of the different type of data used and questions to be answered, the underlying principles are much the same. In this article I propose relevance, validity, and reflexivity as overall standards for qualitative inquiry. I will discuss the specific challenges in relation to reflexivity, transferability, and shared assumptions of interpretation, which are met by medical researchers who do this type of research, and I will propose guidelines for qualitative inquiry.

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statistics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement recording systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The storage and reactivation of perceptual symbols operates at the level of perceptual components--not at the level of holistic perceptual experiences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a common frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspection (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and abstract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinatorially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a perceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal symbol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.

OBJECTIVE

To provide a single source for the best available estimates of the US prevalence of and number of individuals affected by arthritis overall, rheumatoid arthritis, juvenile arthritis, the spondylarthritides, systemic lupus erythematosus, systemic sclerosis, and Sjögren's syndrome. A companion article (part II) addresses additional conditions.

METHODS

The National Arthritis Data Workgroup reviewed published analyses from available national surveys, such as the National Health and Nutrition Examination Survey and the National Health Interview Survey (NHIS). For analysis of overall arthritis, we used the NHIS. Because data based on national population samples are unavailable for most specific rheumatic conditions, we derived estimates from published studies of smaller, defined populations. For specific conditions, the best available prevalence estimates were applied to the corresponding 2005 US population estimates from the Census Bureau, to estimate the number affected with each condition.

RESULTS

More than 21% of US adults (46.4 million persons) were found to have self-reported doctor-diagnosed arthritis. We estimated that rheumatoid arthritis affects 1.3 million adults (down from the estimate of 2.1 million for 1995), juvenile arthritis affects 294,000 children, spondylarthritides affect from 0.6 million to 2.4 million adults, systemic lupus erythematosus affects from 161,000 to 322,000 adults, systemic sclerosis affects 49,000 adults, and primary Sjögren's syndrome affects from 0.4 million to 3.1 million adults.

CONCLUSIONS

Arthritis and other rheumatic conditions continue to be a large and growing public health problem. Estimates for many specific rheumatic conditions rely on a few, small studies of uncertain generalizability to the US population. This report provides the best available prevalence estimates for the US, but for most specific conditions, more studies generalizable to the US or addressing understudied populations are needed.

The Prevention of Maternal Mortality Program is a collaborative effort of Columbia University's Center for Population and Family Health and multidisciplinary teams of researchers from Ghana, Nigeria and Sierra Leone. Program goals include dissemination of information to those concerned with preventing maternal deaths. This review, which presents findings from a broad body of research, is part of that activity. While there are numerous factors that contribute to maternal mortality, we focus on those that affect the interval between the onset of obstetric complication and its outcome. If prompt, adequate treatment is provided, the outcome will usually be satisfactory; therefore, the outcome is most adversely affected by delayed treatment. We examine research on the factors that: (1) delay the decision to seek care; (2) delay arrival at a health facility; and (3) delay the provision of adequate care. The literature clearly indicates that while distance and cost are major obstacles in the decision to seek care, the relationships are not simple. There is evidence that people often consider the quality of care more important than cost. These three factors--distance, cost and quality--alone do not give a full understanding of decision-making process. Their salience as obstacles is ultimately defined by illness-related factors, such as severity. Differential use of health services is also shaped by such variables as gender and socioeconomic status. Patients who make a timely decision to seek care can still experience delay, because the accessibility of health services is an acute problem in the developing world. In rural areas, a woman with an obstetric emergency may find the closest facility equipped only for basic treatments and education, and she may have no way to reach a regional center where resources exist. Finally, arriving at the facility may not lead to the immediate commencement of treatment. Shortages of qualified staff, essential drugs and supplies, coupled with administrative delays and clinical mismanagement, become documentable contributors to maternal deaths. Findings from the literature review are discussed in light of their implications for programs. Options for health programs are offered and examples of efforts to reduce maternal deaths are presented, with an emphasis on strategies to mobilize and adapt existing resources.

Glucose homeostasis depends on insulin responsiveness in target tissues, most importantly, muscle and liver. The critical initial steps in insulin action include phosphorylation of scaffolding proteins and activation of phosphatidylinositol 3-kinase. These early events lead to activation of the serine-threonine protein kinase Akt, also known as protein kinase B. We show that mice deficient in Akt2 are impaired in the ability of insulin to lower blood glucose because of defects in the action of the hormone on liver and skeletal muscle. These data establish Akt2 as an essential gene in the maintenance of normal glucose homeostasis.

Excess CO2 is generated when lactate is increased during exercise because its [H+] is buffered primarily by HCO-3 (22 ml for each meq of lactic acid). We developed a method to detect the anaerobic threshold (AT), using computerized regression analysis of the slopes of the CO2 uptake (VCO2) vs. O2 uptake (VO2) plot, which detects the beginning of the excess CO2 output generated from the buffering of [H+], termed the V-slope method. From incremental exercise tests on 10 subjects, the point of excess CO2 output (AT) predicted closely the lactate and HCO-3 thresholds. The mean gas exchange AT was found to correspond to a small increment of lactate above the mathematically defined lactate threshold [0.50 +/- 0.34 (SD) meq/l] and not to differ significantly from the estimated HCO-3 threshold. The mean VO2 at AT computed by the V-slope analysis did not differ significantly from the mean value determined by a panel of six experienced reviewers using traditional visual methods, but the AT could be more reliably determined by the V-slope method. The respiratory compensation point, detected separately by examining the minute ventilation vs. VCO2 plot, was consistently higher than the AT (2.51 +/- 0.42 vs. 1.83 +/- 0.30 l/min of VO2). This method for determining the AT has significant advantages over others that depend on regular breathing pattern and respiratory chemosensitivity.

This randomized, controlled trial assessed the efficacy of transarterial Lipiodol (Lipiodol Ultrafluide, Laboratoire Guerbet, Aulnay-Sous-Bois, France) chemoembolization in patients with unresectable hepatocellular carcinoma. From March 1996 to October 1997, 80 out of 279 Asian patients with newly diagnosed unresectable hepatocellular carcinoma fulfilled the entry criteria and randomly were assigned to treatment with chemoembolization using a variable dose of an emulsion of cisplatin in Lipiodol and gelatin-sponge particles injected through the hepatic artery (chemoembolization group, 40 patients) or symptomatic treatment (control group, 40 patients). One patient assigned to the control group secondarily was excluded because of unrecognized systemic metastasis. Chemoembolization was repeated every 2 to 3 months unless there was evidence of contraindications or progressive disease. Survival was the main end point. The chemoembolization group received a total of 192 courses of chemoembolization with a median of 4.5 (range, 1-15) courses per patient. Chemoembolization resulted in a marked tumor response, and the actuarial survival was significantly better in the chemoembolization group (1 year, 57%; 2 years, 31%; 3 years, 26%) than in the control group (1 year, 32%; 2 years, 11%; 3 years, 3%; P =.002). When adjustments for baseline variables that were prognostic on univariate analysis were made with a multivariate Cox model, the survival benefit of chemoembolization remained significant (relative risk of death, 0.49; 95% CI, 0.29-0.81; P =.006). Although death from liver failure was more frequent in patients who received chemoembolization, the liver functions of the survivors were not significantly different. In conclusion, in Asian patients with unresectable hepatocellular carcinoma, transarterial Lipiodol chemoembolization significantly improves survival and is an effective form of treatment.

OBJECTIVE

To provide a single source for the best available estimates of the national prevalence of arthritis in general and of selected musculoskeletal disorders (osteoarthritis, rheumatoid arthritis, juvenile rheumatoid arthritis, the spondylarthropathies, systemic lupus erythematosus, scleroderma, polymyalgia rheumatica/giant cell arteritis, gout, fibromyalgia, and low back pain).

METHODS

The National Arthritis Data Workgroup reviewed data from available surveys, such as the National Health and Nutrition Examination Survey series. For overall national estimates, we used surveys based on representative samples. Because data based on national population samples are unavailable for most specific musculoskeletal conditions, we derived data from various smaller survey samples from defined populations. Prevalence estimates from these surveys were linked to 1990 US Bureau of the Census population data to calculate national estimates. We also estimated the expected frequency of arthritis in the year 2020.

RESULTS

Current national estimates are provided, with important caveats regarding their interpretation, for self-reported arthritis and selected conditions. An estimated 15% (40 million) of Americans had some form of arthritis in 1995. By the year 2020, an estimated 18.2% (59.4 million) will be affected.

CONCLUSIONS

Given the limitations of the data on which they are based, this report provides the best available prevalence estimates for arthritis and other rheumatic conditions overall, and for selected musculoskeletal disorders, in the US population.

RNA interference (RNAi) is a universal and evolutionarily conserved phenomenon of post-transcriptional gene silencing by means of sequence-specific mRNA degradation, triggered by small double-stranded RNAs. Because this mechanism can be efficiently induced in vivo by expressing target-complementary short hairpin RNA (shRNA) from non-viral and viral vectors, RNAi is attractive for functional genomics and human therapeutics. Here we systematically investigate the long-term effects of sustained high-level shRNA expression in livers of adult mice. Robust shRNA expression in all the hepatocytes after intravenous infusion was achieved with an optimized shRNA delivery vector based on duplex-DNA-containing adeno-associated virus type 8 (AAV8). An evaluation of 49 distinct AAV/shRNA vectors, unique in length and sequence and directed against six targets, showed that 36 resulted in dose-dependent liver injury, with 23 ultimately causing death. Morbidity was associated with the downregulation of liver-derived microRNAs (miRNAs), indicating possible competition of the latter with shRNAs for limiting cellular factors required for the processing of various small RNAs. In vitro and in vivo shRNA transfection studies implied that one such factor, shared by the shRNA/miRNA pathways and readily saturated, is the nuclear karyopherin exportin-5. Our findings have fundamental consequences for future RNAi-based strategies in animals and humans, because controlling intracellular shRNA expression levels will be imperative. However, the risk of oversaturating endogenous small RNA pathways can be minimized by optimizing shRNA dose and sequence, as exemplified here by our report of persistent and therapeutic RNAi against human hepatitis B virus in vivo.

Vulnerable periods during the development of the nervous system are sensitive to environmental insults because they are dependent on the temporal and regional emergence of critical developmental processes (i.e., proliferation, migration, differentiation, synaptogenesis, myelination, and apoptosis). Evidence from numerous sources demonstrates that neural development extends from the embryonic period through adolescence. In general, the sequence of events is comparable among species, although the time scales are considerably different. Developmental exposure of animals or humans to numerous agents (e.g., X-ray irradiation, methylazoxymethanol, ethanol, lead, methyl mercury, or chlorpyrifos) demonstrates that interference with one or more of these developmental processes can lead to developmental neurotoxicity. Different behavioral domains (e.g., sensory, motor, and various cognitive functions) are subserved by different brain areas. Although there are important differences between the rodent and human brain, analogous structures can be identified. Moreover, the ontogeny of specific behaviors can be used to draw inferences regarding the maturation of specific brain structures or neural circuits in rodents and primates, including humans. Furthermore, various clinical disorders in humans (e.g., schizophrenia, dyslexia, epilepsy, and autism) may also be the result of interference with normal ontogeny of developmental processes in the nervous system. Of critical concern is the possibility that developmental exposure to neurotoxicants may result in an acceleration of age-related decline in function. This concern is compounded by the fact that developmental neurotoxicity that results in small effects can have a profound societal impact when amortized across the entire population and across the life span of humans.

Telomeres in most human cells shorten with each round of DNA replication, because they lack the enzyme telomerase. This is not, however, the only determinant of the rate of loss of telomeric DNA. Oxidative damage is repaired less well in telomeric DNA than elsewhere in the chromosome, and oxidative stress accelerates telomere loss, whereas antioxidants decelerate it. I suggest here that oxidative stress is an important modulator of telomere loss and that telomere-driven replicative senescence is primarily a stress response. This might have evolved to block the growth of cells that have been exposed to a high risk of mutation.

Selection against deleterious alleles maintained by mutation may cause a reduction in the amount of genetic variability at linked neutral sites. This is because a new neutral variant can only remain in a large population for a long period of time if it is maintained in gametes that are free of deleterious alleles, and hence are not destined for rapid elimination from the population by selection. Approximate formulas are derived for the reduction below classical neutral values resulting from such background selection against deleterious mutations, for the mean times to fixation and loss of new mutations, nucleotide site diversity, and number of segregating sites. These formulas apply to random-mating populations with no genetic recombination, and to populations reproducing exclusively asexually or by self-fertilization. For a given selection regime and mating system, the reduction is an exponential function of the total mutation rate to deleterious mutations for the section of the genome involved. Simulations show that the effect decreases rapidly with increasing recombination frequency or rate of outcrossing. The mean time to loss of new neutral mutations and the total number of segregating neutral sites are less sensitive to background selection than the other statistics, unless the population size is of the order of a hundred thousand or more. The stationary distribution of allele frequencies at the neutral sites is correspondingly skewed in favor of rare alleles, compared with the classical neutral result. Observed reductions in molecular variation in low recombination genomic regions of sufficiently large size, for instance in the centromere-proximal regions of Drosophila autosomes or in highly selfing plant populations, may be partly due to background selection against deleterious mutations.

In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a "research framework" because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.