Private Multiplicative Weights Beyond Linear Queries

A wide variety of fundamental data analyses in machine learning, such as linear and logistic regression, require minimizing a convex function defined by the data. Since the data may contain sensitive information about individuals, and these analyses can leak that sensitive information, it is important to be able to solve convex minimization in a privacy-preserving way. A series of recent results show how to accurately solve a single convex minimization problem in a differentially private manner. However, the same data is often analyzed repeatedly, and little is known about solving multiple convex minimization problems with differential privacy. For simpler data analyses, such as linear queries, there are remarkable differentially private algorithms such as the private multiplicative weights mechanism (Hardt and Rothblum, FOCS 2010) that accurately answer exponentially many distinct queries. In this work, we extend these results to the case of convex minimization and show how to give accurate and differentially private solutions to *exponentially many* convex minimization problems on a sensitive dataset

Private Incremental Regression

Data is continuously generated by modern data sources, and a recent challenge in machine learning has been to develop techniques that perform well in an incremental (streaming) setting. In this paper, we investigate the problem of private machine learning, where as common in practice, the data is not given at once, but rather arrives incrementally over time. We introduce the problems of private incremental ERM and private incremental regression where the general goal is to always maintain a good empirical risk minimizer for the history observed under differential privacy. Our first contribution is a generic transformation of private batch ERM mechanisms into private incremental ERM mechanisms, based on a simple idea of invoking the private batch ERM procedure at some regular time intervals. We take this construction as a baseline for comparison. We then provide two mechanisms for the private incremental regression problem. Our first mechanism is based on privately constructing a noisy incremental gradient function, which is then used in a modified projected gradient procedure at every timestep. This mechanism has an excess empirical risk of $\approx\sqrt{d}$, where $d$ is the dimensionality of the data. While from the results of [Bassily et al. 2014] this bound is tight in the worst-case, we show that certain geometric properties of the input and constraint set can be used to derive significantly better results for certain interesting regression problems.Comment: To appear in PODS 201

Dietary Tetrahydrocurcumin Reduces Renal Fibrosis and Cardiac Hypertrophy in 5/6 Nephrectomized Rats

Tetrahydrocurcumin (THC) is the principal metabolite of curcumin and has antioxidant properties. In the present investigation, the effect of THC on renal and cardiovascular outcomes was studied in rats with chronic kidney disease (CKD). CKD rats were randomized following 5/6 nephrectomy to a special diet for 9 weeks which contained 1% THC (CKD+THC group). Low-dose polyenylphosphatidylcholine was used as a lipid carrier to increase bioavailability. Endpoints included tail blood pressure, normalized heart weight, plasma and urine biochemical data, and kidney tissue analyses. CKD animals demonstrated increased proteinuria, decreased creatinine clearance, hypertension, and cardiac hypertrophy. The antioxidant proteins CuZn SOD and glutathione peroxidase were decreased in the remnant kidney, while apoptosis (caspase-3) and fibrosis (alpha-SM actin) were increased. Renal fibrosis was confirmed histologically on trichrome staining. These pathologic changes were ameliorated in the CKD+THC group with significant decrease in proteinuria, hypertension, and kidney fibrosis. THC therapy restored levels of CuZn SOD and glutathione peroxidase. Consistent with prior reports, dietary THC did not improve nuclear Nrf2 levels. In summary, dietary THC therapy improved expression of antioxidant proteins in the remnant kidney, decreased renal fibrosis and proteinuria, and ameliorated hypertension in 5/6 nephrectomized rats

Compositional Proteomics: Effects of Spatial Constraints on Protein Quantification Utilizing Isobaric Tags.

Mass spectrometry (MS) has become an accessible tool for whole proteome quantitation with the ability to characterize protein expression across thousands of proteins within a single experiment. A subset of MS quantification methods (e.g., SILAC and label-free) monitor the relative intensity of intact peptides, where thousands of measurements can be made from a single mass spectrum. An alternative approach, isobaric labeling, enables precise quantification of multiple samples simultaneously through unique and sample specific mass reporter ions. Consequently, in a single scan, the quantitative signal comes from a limited number of spectral features (≤11). The signal observed for these features is constrained by automatic gain control, forcing codependence of concurrent signals. The study of constrained outcomes primarily belongs to the field of compositional data analysis. We show experimentally that isobaric tag proteomics data are inherently compositional and highlight the implications for data analysis and interpretation. We present a new statistical model and accompanying software that improves estimation accuracy and the ability to detect changes in protein abundance. Finally, we demonstrate a unique compositional effect on proteins with infinite changes. We conclude that many infinite changes will appear small and that the magnitude of these estimates is highly dependent on experimental design

Cosmological expansion and local physics

The interplay between cosmological expansion and local attraction in a gravitationally bound system is revisited in various regimes. First, weakly gravitating Newtonian systems are considered, followed by various exact solutions describing a relativistic central object embedded in a Friedmann universe. It is shown that the ``all or nothing'' behaviour recently discovered (i.e., weakly coupled systems are comoving while strongly coupled ones resist the cosmic expansion) is limited to the de Sitter background. New exact solutions are presented which describe black holes perfectly comoving with a generic Friedmann universe. The possibility of violating cosmic censorship for a black hole approaching the Big Rip is also discussed.Comment: 17 pages, LaTeX, to appear in Phys. Rev.

EXMOTIF: efficient structured motif extraction

BACKGROUND: Extracting motifs from sequences is a mainstay of bioinformatics. We look at the problem of mining structured motifs, which allow variable length gaps between simple motif components. We propose an efficient algorithm, called EXMOTIF, that given some sequence(s), and a structured motif template, extracts all frequent structured motifs that have quorum q. Potential applications of our method include the extraction of single/composite regulatory binding sites in DNA sequences. RESULTS: EXMOTIF is efficient in terms of both time and space and is shown empirically to outperform RISO, a state-of-the-art algorithm. It is also successful in finding potential single/composite transcription factor binding sites. CONCLUSION: EXMOTIF is a useful and efficient tool in discovering structured motifs, especially in DNA sequences. The algorithm is available as open-source at:

A structural comparison of human serum transferrin and human lactoferrin

The transferrins are a family of proteins that bind free iron in the blood and bodily fluids. Serum transferrins function to deliver iron to cells via a receptor-mediated endocytotic process as well as to remove toxic free iron from the blood and to provide an anti-bacterial, low-iron environment. Lactoferrins (found in bodily secretions such as milk) are only known to have an anti-bacterial function, via their ability to tightly bind free iron even at low pH, and have no known transport function. Though these proteins keep the level of free iron low, pathogenic bacteria are able to thrive by obtaining iron from their host via expression of outer membrane proteins that can bind to and remove iron from host proteins, including both serum transferrin and lactoferrin. Furthermore, even though human serum transferrin and lactoferrin are quite similar in sequence and structure, and coordinate iron in the same manner, they differ in their affinities for iron as well as their receptor binding properties: the human transferrin receptor only binds serum transferrin, and two distinct bacterial transport systems are used to capture iron from serum transferrin and lactoferrin. Comparison of the recently solved crystal structure of iron-free human serum transferrin to that of human lactoferrin provides insight into these differences

Human PAPS Synthase Isoforms Are Dynamically Regulated Enzymes with Access to Nucleus and Cytoplasm

In higher eukaryotes, PAPS synthases are the only enzymes producing the essential sulphate-donor 3′-phospho-adenosine-5′-phosphosulphate (PAPS). Recently, PAPS synthases have been associated with several genetic diseases and retroviral infection. To improve our understanding of their pathobiological functions, we analysed the intracellular localisation of the two human PAPS synthases, PAPSS1 and PAPSS2. For both enzymes, we observed pronounced heterogeneity in their subcellular localisation. PAPSS1 was predominantly nuclear, whereas PAPSS2 localised mainly within the cytoplasm. Treatment with the nuclear export inhibitor leptomycin B had little effect on their localisation. However, a mutagenesis screen revealed an Arg-Arg motif at the kinase interface exhibiting export activity. Notably, both isoforms contain a conserved N-terminal basic Lys-Lys-Xaa-Lys motif indispensable for their nuclear localisation. This nuclear localisation signal was more efficient in PAPSS1 than in PAPSS2. The activities of the identified localisation signals were confirmed by microinjection studies. Collectively, we describe unusual localisation signals of both PAPS synthase isoforms, mobile enzymes capable of executing their function in the cytoplasm as well as in the nucleus

A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis

Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have defined DNA drivers of aggressive clinical behavior. Whole-genome and exome data from 1273 NDMM patients identified genetic factors that contribute significantly to progression free survival (PFS) and overall survival (OS) (cumulative R2 = 18.4% and 25.2%, respectively). Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R2 of 34.3% for PFS and 46.5% for OS. A high-risk subgroup was defined by recursive partitioning using either a) bi-allelic TP53 inactivation or b) amplification (≥4 copies) of CKS1B (1q21) on the background of International Staging System III, comprising 6.1% of the population (median PFS = 15.4 months; OS = 20.7 months) that was validated in an independent dataset. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches

The Impact of Local Genome Sequence on Defining Heterochromatin Domains

Characterizing how genomic sequence interacts with trans-acting regulatory factors to implement a program of gene expression in eukaryotic organisms is critical to understanding genome function. One means by which patterns of gene expression are achieved is through the differential packaging of DNA into distinct types of chromatin. While chromatin state exerts a major influence on gene expression, the extent to which cis-acting DNA sequences contribute to the specification of chromatin state remains incompletely understood. To address this, we have used a fission yeast sequence element (L5), known to be sufficient to nucleate heterochromatin, to establish de novo heterochromatin domains in the Schizosaccharomyces pombe genome. The resulting heterochromatin domains were queried for the presence of H3K9 di-methylation and Swi6p, both hallmarks of heterochromatin, and for levels of gene expression. We describe a major effect of genomic sequences in determining the size and extent of such de novo heterochromatin domains. Heterochromatin spreading is antagonized by the presence of genes, in a manner that can occur independent of strength of transcription. Increasing the dosage of Swi6p results in increased heterochromatin proximal to the L5 element, but does not result in an expansion of the heterochromatin domain, suggesting that in this context genomic effects are dominant over trans effects. Finally, we show that the ratio of Swi6p to H3K9 di-methylation is sequence-dependent and correlates with the extent of gene repression. Taken together, these data demonstrate that the sequence content of a genomic region plays a significant role in shaping its response to encroaching heterochromatin and suggest a role of DNA sequence in specifying chromatin state