Rosetta error model for gene expression analysis

MOTIVATION: In microarray gene expression studies, the number of replicated microarrays is usually small because of cost and sample availability, resulting in unreliable variance estimation and thus unreliable statistical hypothesis tests. The unreliable variance estimation is further complicated by the fact that the technology-specific variance is intrinsically intensity-dependent. RESULTS: The Rosetta error model captures the variance-intensity relationship for various types of microarray technologies, such as single-color arrays and two-color arrays. This error model conservatively estimates intensity error and uses this value to stabilize the variance estimation. We present two commonly used error models: the intensity error-model for single-color microarrays and the ratio error model for two-color microarrays or ratios built from two single-color arrays. We present examples to demonstrate the strength of our error models in improving statistical power of microarray data analysis, particularly, in increasing expression detection sensitivity and specificity when the number of replicates is limited.     

Learning, memory, and the role of neural network architecture

The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems.     

Time to Treatment and Patient Outcomes among TB Suspects Screened by a Single Point-of-Care Xpert MTB/RIF at a Primary Care Clinic in Johannesburg,South Africa

Introduction

In December 2010, the World Health Organization recommended a single Xpert MTB/RIF assay as the initial diagnostic in people suspected of HIV-associated or drug resistant tuberculosis. Few data are available on the impact of this recommendation on patient outcomes. We describe the diagnostic follow-up, clinical characteristics and outcomes of a cohort of tuberculosis suspects screened using a single point-of-care Xpert.

Methods

Consecutive tuberculosis suspects at a primary care clinic in Johannesburg, South Africa were assessed for tuberculosis using point-of-care Xpert. Sputum smear microscopy and liquid culture were performed as reference standards. Xpert-negatives were evaluated clinically, and further assessed at the discretion of clinicians. Participants were followed for six months.

Results

From July-September 2011, 641 tuberculosis suspects were enrolled, of whom 69% were HIV-infected. Eight percent were positive by a single Xpert. Among 116 individuals diagnosed with TB, 66 (57%) were Xpert negative, of which 44 (67%) were empirical or radiological diagnoses and 22 (33%) were Xpert negative/culture-positive. The median time to tuberculosis treatment was 0 days (IQR: 0–0) for Xpert positives, 14 days (IQR: 5–35) for those diagnosed empirically, 14 days (IQR: 7–29) for radiological diagnoses, and 144 days (IQR: 28–180) for culture positives. Xpert negative tuberculosis cases were clinically similar to Xpert positives, including HIV status and CD4 count, and had similar treatment outcomes including mortality and time to antiretroviral treatment initiation.

Conclusions

In a high HIV-burden setting, a single Xpert identified less than half of those started on tuberculosis treatment, highlighting the complexity of TB diagnosis even in the Xpert era. Xpert at point-of-care resulted in same day treatment initiation in Xpert-positives, but had no impact on tuberculosis treatment outcomes or mortality.     

鼠李糖脂的表面化学和生物合成及其在垃圾堆肥中的应用展望

鼠李糖脂是生物表面活性剂中一类非常重要而应用广泛的微生物发酵产物,在环境污染修复中需求量越来越多。针对近十年来国内外对鼠李糖脂生物表面活性剂的研究,较系统地总结了其化学结构、性质、生物合成机理及产量调节方法,及大规模生产鼠李糖脂的基础研究工作,并对其在城市生活垃圾堆肥中的应用做了展望。     

Efficient Physical Embedding of Topologically Complex Information Processing Networks in Brains and Computer Circuits

Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI) computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent''s rule, which is related to the dimensionality of the circuit''s interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent''s rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks.     

Thyroid hormone excess rather than thyrotropin deficiency induces osteoporosis in hyperthyroidism

Thyrotoxicosis is an important but under recognized cause of osteoporosis. Recently, TSH deficiency, rather than thyroid hormone excess, has been suggested as the underlying cause. To investigate the molecular mechanism of osteoporosis in thyroid disease, we characterized the skeleton in mice lacking either thyroid hormone receptor alpha or beta (TRalpha(0/0), TRbeta-/-). Remarkably, in the presence of normal circulating thyroid hormone and TSH concentrations, adult TRalpha(0/0) mice had osteosclerosis accompanied by reduced osteoclastic bone resorption, whereas juveniles had delayed endochondral ossification with reduced bone mineral deposition. By contrast, adult TRbeta-/- mice with elevated TSH and thyroid hormone levels were osteoporotic with evidence of increased bone resorption, whereas juveniles had advanced ossification with increased bone mineral deposition. Analysis of T3 target gene expression revealed skeletal hypothyroidism in TRalpha(0/0) mice, but skeletal thyrotoxicosis in TRbeta-/- mice. These studies demonstrate that bone loss in thyrotoxicosis is independent of circulating TSH levels and mediated predominantly by TRalpha, thus identifying TRalpha as a novel drug target in the prevention and treatment of osteoporosis.     

Thyroid status during skeletal development determines adult bone structure and mineralization

Childhood hypothyroidism delays ossification and bone mineralization, whereas adult thyrotoxicosis causes osteoporosis. To determine how effects of thyroid hormone (T3) during development manifest in adult bone, we characterized TRalpha1(+/m)beta(+/-) mice, which express a mutant T3 receptor (TR) alpha1 with dominant-negative properties due to reduced ligand-binding affinity. Remarkably, adult TRalpha1(+/m)beta(+/-) mice had osteosclerosis with increased bone mineralization even though juveniles had delayed ossification. This phenotype was partially normalized by transient T3 treatment of juveniles and fully reversed in compound TRalpha1(+/m)beta(-/-) mutant mice due to 10-fold elevated hormone levels that allow the mutant TRalpha1 to bind T3. By contrast, deletion of TRbeta in TRalpha1(+/+)beta(-/ -) mice, which causes a 3-fold increase of hormone levels, led to osteoporosis in adults but advanced ossification in juveniles. T3-target gene analysis revealed skeletal hypothyroidism in TRalpha1(m/+)beta(+/-) mice, thyrotoxicosis in TRalpha1(+/+)beta(-/-) mice, and euthyroidism in TRalpha1(+/)beta(-/-) double mutants. Thus, TRalpha1 regulates both skeletal development and adult bone maintenance, with euthyroid status during development being essential to establish normal adult bone structure and mineralization.