Bioinformatics advances in saliva diagnostics

There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva diagnostics made possible by the Saliva Ontology and SDxMart

The effect of cigarette price increase on the cigarette consumption in Taiwan: evidence from the National Health Interview Surveys on cigarette consumption

BACKGROUND: This study uses cigarette price elasticity to evaluate the effect of a new excise tax increase on cigarette consumption and to investigate responses from various types of smokers. METHODS: Our sample consisted of current smokers between 17 and 69 years old interviewed during an annual face-to-face survey conducted by Taiwan National Health Research Institutes between 2000 to 2003. We used Ordinary Least Squares (OLS) procedure to estimate double logarithmic function of cigarette demand and cigarette price elasticity. RESULTS: In 2002, after Taiwan had enacted the new tax scheme, cigarette price elasticity in Taiwan was found to be -0.5274. The new tax scheme brought about an average annual 13.27 packs/person (10.5%) reduction in cigarette consumption. Using the cigarette price elasticity estimate from -0.309 in 2003, we calculated that if the Health and Welfare Tax were increased by another NT$ 3 per pack and cigarette producers shifted this increase to the consumers, cigarette consumption would be reduced by 2.47 packs/person (2.2%). The value of the estimated cigarette price elasticity is smaller than one, meaning that the tax will not only reduce cigarette consumption but it will also generate additional tax revenues. Male smokers who had no income or who smoked light cigarettes were found to be more responsive to changes in cigarette price. CONCLUSIONS: An additional tax added to the cost of cigarettes would bring about a reduction in cigarette consumption and increased tax revenues. It would also help reduce incidents smoking-related illnesses. The additional tax revenues generated by the tax increase could be used to offset the current financial deficiency of Taiwan's National Health Insurance program and provide better public services

Demon-like Algorithmic Quantum Cooling and its Realization with Quantum Optics

The simulation of low-temperature properties of many-body systems remains one of the major challenges in theoretical and experimental quantum information science. We present, and demonstrate experimentally, a universal cooling method which is applicable to any physical system that can be simulated by a quantum computer. This method allows us to distill and eliminate hot components of quantum states, i.e., a quantum Maxwell's demon. The experimental implementation is realized with a quantum-optical network, and the results are in full agreement with theoretical predictions (with fidelity higher than 0.978). These results open a new path for simulating low-temperature properties of physical and chemical systems that are intractable with classical methods.Comment: 7 pages, 5 figures, plus supplementarity material

Two-orbital SU(N) magnetism with ultracold alkaline-earth atoms

Fermionic alkaline-earth atoms have unique properties that make them attractive candidates for the realization of novel atomic clocks and degenerate quantum gases. At the same time, they are attracting considerable theoretical attention in the context of quantum information processing. Here we demonstrate that when such atoms are loaded in optical lattices, they can be used as quantum simulators of unique many-body phenomena. In particular, we show that the decoupling of the nuclear spin from the electronic angular momentum can be used to implement many-body systems with an unprecedented degree of symmetry, characterized by the SU(N) group with N as large as 10. Moreover, the interplay of the nuclear spin with the electronic degree of freedom provided by a stable optically excited state allows for the study of spin-orbital physics. Such systems may provide valuable insights into strongly correlated physics of transition metal oxides, heavy fermion materials, and spin liquid phases.Comment: 15 pages, 10 figures. V2: extended experimental accessibility and Kondo sections in the main text (including new Fig. 5b) and in the Methods; reorganized other parts; added reference

Towards quantum computing with single atoms and optical cavities on atom chips

We report on recent developments in the integration of optical microresonators into atom chips and describe some fabrication and implementation challenges. We also review theoretical proposals for quantum computing with single atoms based on the observation of photons leaking through the cavity mirrors. The use of measurements to generate entanglement can result in simpler, more robust and scalable quantum computing architectures. Indeed, we show that quantum computing with atom-cavity systems is feasible even in the presence of relatively large spontaneous decay rates and finite photon detector efficiencies.Comment: 14 pages, 6 figure

MicroRNAs in cardiac arrhythmia: DNA sequence variation of MiR-1 and MiR-133A in long QT syndrome.

Long QT syndrome (LQTS) is a genetic cardiac condition associated with prolonged ventricular repolarization, primarily a result of perturbations in cardiac ion channels, which predisposes individuals to life-threatening arrhythmias. Using DNA screening and sequencing methods, over 700 different LQTS-causing mutations have been identified in 13 genes worldwide. Despite this, the genetic cause of 30-50% of LQTS is presently unknown. MicroRNAs (miRNAs) are small (∼ 22 nucleotides) noncoding RNAs which post-transcriptionally regulate gene expression by binding complementary sequences within messenger RNAs (mRNAs). The human genome encodes over 1800 miRNAs, which target about 60% of human genes. Consequently, miRNAs are likely to regulate many complex processes in the body, indeed aberrant expression of various miRNA species has been implicated in numerous disease states, including cardiovascular diseases. MiR-1 and MiR-133A are the most abundant miRNAs in the heart and have both been reported to regulate cardiac ion channels. We hypothesized that, as a consequence of their role in regulating cardiac ion channels, genetic variation in the genes which encode MiR-1 and MiR-133A might explain some cases of LQTS. Four miRNA genes (miR-1-1, miR-1-2, miR-133a-1 and miR-133a-2), which encode MiR-1 and MiR-133A, were sequenced in 125 LQTS probands. No genetic variants were identified in miR-1-1 or miR-133a-1; but in miR-1-2 we identified a single substitution (n.100A> G) and in miR-133a-2 we identified two substitutions (n.-19G> A and n.98C> T). None of the variants affect the mature miRNA products. Our findings indicate that sequence variants of miR-1-1, miR-1-2, miR-133a-1 and miR-133a-2 are not a cause of LQTS in this cohort

Poly-Logarithmic Side Channel Rank Estimation via Exponential Sampling

Rank estimation is an important tool for a side-channel evaluations laboratories. It allows estimating the remaining security after an attack has been performed, quantified as the time complexity and the memory consumption required to brute force the key given the leakages as probability distributions over $d$ subkeys (usually key bytes). These estimations are particularly useful where the key is not reachable with exhaustive search. We propose ESrank, the first rank estimation algorithm that enjoys provable poly-logarithmic time- and space-complexity, which also achieves excellent practical performance. Our main idea is to use exponential sampling to drastically reduce the algorithm\u27s complexity. Importantly, ESrank is simple to build from scratch, and requires no algorithmic tools beyond a sorting function. After rigorously bounding the accuracy, time and space complexities, we evaluated the performance of ESrank on a real SCA data corpus, and compared it to the currently-best histogram-based algorithm. We show that ESrank gives excellent rank estimation (with roughly a 1-bit margin between lower and upper bounds), with a performance that is on-par with the Histogram algorithm: a run-time of under 1 second on a standard laptop using 6.5 MB RAM

Diagnosis and Reporting of Follicular-Patterned Thyroid Lesions by Fine Needle Aspiration

Over the past 3 decades, fine needle aspiration (FNA) has developed as the most accurate and cost-effective initial method for guiding the clinical management of patients with thyroid nodules. Thyroid FNA specimens containing follicular-patterned lesions are the most commonly encountered and include various forms of benign thyroid nodules, follicular carcinomas, and the follicular variant of papillary thyroid carcinoma. Based primarily upon the cytoarchitectural pattern, FNA is used as a screening test for follicular-patterned lesions to identify the majority of patients with benign nodules who can be managed without surgical intervention. The terminology and reporting of thyroid FNA results have been problematic due to significant variation between laboratories, but the recent multidisciplinary NCI Thyroid FNA State of the Science Conference has provided a seven-tiered diagnostic solution. A key element of this approach is the category “atypical cells of undetermined significance” (ACUS) which is used for those aspirates which cannot be easily classified as benign, suspicious, or malignant. Lesions in this category represent approximately 3–6% of thyroid FNAs and have a risk of malignancy intermediate between the “benign” category and the “suspicious for a follicular neoplasm” category. The recommended follow-up for an ACUS diagnosis is clinical correlation and in most cases, repeat FNA sampling

Deep learning of the retina enables phenome- and genome-wide analyses of the microvasculature.

Background: The microvasculature, the smallest blood vessels in the body, has key roles in maintenance of organ health as well as tumorigenesis. The retinal fundus is a window for human in vivo non-invasive assessment of the microvasculature. Large-scale complementary machine learning-based assessment of the retinal vasculature with phenome-wide and genome-wide analyses may yield new insights into human health and disease. Methods: We utilized 97,895 retinal fundus images from 54,813 UK Biobank participants. Using convolutional neural networks to segment the retinal microvasculature, we calculated fractal dimension (FD) as a measure of vascular branching complexity, and vascular density. We associated these indices with 1,866 incident ICD-based conditions (median 10y follow-up) and 88 quantitative traits, adjusting for age, sex, smoking status, and ethnicity. Results: Low retinal vascular FD and density were significantly associated with higher risks for incident mortality, hypertension, congestive heart failure, renal failure, type 2 diabetes, sleep apnea, anemia, and multiple ocular conditions, as well as corresponding quantitative traits. Genome-wide association of vascular FD and density identified 7 and 13 novel loci respectively, which were enriched for pathways linked to angiogenesis (e.g., VEGF, PDGFR, angiopoietin, and WNT signaling pathways) and inflammation (e.g., interleukin, cytokine signaling). Conclusions: Our results indicate that the retinal vasculature may serve as a biomarker for future cardiometabolic and ocular disease and provide insights on genes and biological pathways influencing microvascular indices. Moreover, such a framework highlights how deep learning of images can quantify an interpretable phenotype for integration with electronic health records, biomarker, and genetic data to inform risk prediction and risk modification