Offline to Online Conversion

We consider the problem of converting offline estimators into an online predictor or estimator with small extra regret. Formally this is the problem of merging a collection of probability measures over strings of length 1,2,3,... into a single probability measure over infinite sequences. We describe various approaches and their pros and cons on various examples. As a side-result we give an elementary non-heuristic purely combinatoric derivation of Turing's famous estimator. Our main technical contribution is to determine the computational complexity of online estimators with good guarantees in general.Comment: 20 LaTeX page

Towards Continuous Subject Identification Using Wearable Devices and Deep CNNs

© 2020 IEEE. Subject identification has several applications. In transportation companies, knowing who is driving their vehicles might prevent theft or other ill-intended actions. On the other hand, privacy concerns, and the respective legislation, hinder the applicability of several traditional recognition techniques based on invasive technologies, such as video cameras. Moreover, in order to keep the driver's distractions to a minimum, this technologies must be non-disruptive, that is, they must be able to identify the subject seamlessly without them taking any action. In this context, we propose using deep learning applied to smart watch data for recognizing the person driving a vehicle based on a training set. Our proposal relies on the possibility of using transfer learning to avoid long training sessions for new drivers and to deliver a solution which can be deployed in practice. In this paper, we describe the convolutional neural network used in the solution and present results according to a real data-set collected by us, achieving accuracies ranging from 75 to 94%

Global Levels of Histone Modifications in Peripheral Blood Mononuclear Cells of Subjects with Exposure to Nickel

Background: Occupational exposure to nickel (Ni) is associated with an increased risk for lung and nasal cancers. Ni compounds exhibit weak mutagenic activity, cause gene amplification, and disrupt cellular epigenetic homeostasis. However, the Ni-induced changes in global histone modification levels have only been tested in vitro

Socioeconomic inequalities in mortality, morbidity and diabetes management for adults with type 1 diabetes: A systematic review.

AIMS: To systematically review the evidence of socioeconomic inequalities for adults with type 1 diabetes in relation to mortality, morbidity and diabetes management. METHODS: We carried out a systematic search across six relevant databases and included all studies reporting associations between socioeconomic indicators and mortality, morbidity, or diabetes management for adults with type 1 diabetes. Data extraction and quality assessment was undertaken for all included studies. A narrative synthesis was conducted. RESULTS: A total of 33 studies were identified. Twelve cohort, 19 cross sectional and 2 case control studies met the inclusion criteria. Regardless of healthcare system, low socioeconomic status was associated with poorer outcomes. Following adjustments for other risk factors, socioeconomic status was a statistically significant independent predictor of mortality in 9/10 studies and morbidity in 8/10 studies for adults with type 1 diabetes. There appeared to be an association between low socioeconomic status and some aspects of diabetes management. Although only 3 of 16 studies made adjustments for confounders and other risk factors, poor diabetes management was associated with lower socioeconomic status in 3/3 of these studies. CONCLUSIONS: Low socioeconomic status is associated with higher levels of mortality and morbidity for adults with type 1 diabetes even amongst those with access to a universal healthcare system. The association between low socioeconomic status and diabetes management requires further research given the paucity of evidence and the potential for diabetes management to mitigate the adverse effects of low socioeconomic status

Biomarkers for Clinical and Incipient Tuberculosis: Performance in a TB-Endemic Country

Simple biomarkers are required to identify TB in both HIV(-)TB(+) and HIV(+)TB(+) patients. Earlier studies have identified the M. tuberculosis Malate Synthase (MS) and MPT51 as immunodominant antigens in TB patients. One goal of these investigations was to evaluate the sensitivity and specificity of anti-MS and -MPT51 antibodies as biomarkers for TB in HIV(-)TB(+) and HIV(+)TB(+) patients from a TB-endemic setting. Earlier studies also demonstrated the presence of these biomarkers during incipient subclinical TB. If these biomarkers correlate with incipient TB, their prevalence should be higher in asymptomatic HIV(+) subjects who are at a high-risk for TB. The second goal was to compare the prevalence of these biomarkers in asymptomatic, CD4(+) T cell-matched HIV(+)TB(-) subjects from India who are at high-risk for TB with similar subjects from US who are at low-risk for TB.Anti-MS and -MPT51 antibodies were assessed in sera from 480 subjects including PPD(+) or PPD(-) healthy subjects, healthy community members, and HIV(-)TB(+) and HIV(+)TB(+) patients from India. Results demonstrate high sensitivity (approximately 80%) of detection of smear-positive HIV(-)TB(+) and HIV(+)TB(+) patients, and high specificity (>97%) with PPD(+) subjects and endemic controls. While approximately 45% of the asymptomatic HIV(+)TB(-) patients at high-risk for TB tested biomarker-positive, >97% of the HIV(+)TB(-) subjects at low risk for TB tested negative. Although the current studies are hampered by lack of knowledge of the outcome, these results provide strong support for the potential of these biomarkers to detect incipient, subclinical TB in HIV(+) subjects.These biomarkers provide high sensitivity and specificity for TB diagnosis in a TB endemic setting. Their performance is not compromised by concurrent HIV infection, site of TB and absence of pulmonary manifestations in HIV(+)TB(+) patients. Results also demonstrate the potential of these biomarkers for identifying incipient subclinical TB in HIV(+)TB(-) subjects at high-risk for TB

Different Pattern of Immunoglobulin Gene Usage by HIV-1 Compared to Non-HIV-1 Antibodies Derived from the Same Infected Subject

A biased usage of immunoglobulin (Ig) genes is observed in human anti-HIV-1 monoclonal antibodies (mAbs) resulting probably from compensation to reduced usage of the VH3 family genes, while the other alternative suggests that this bias usage is due to antigen requirements. If the antigen structure is responsible for the preferential usage of particular Ig genes, it may have certain implications for HIV vaccine development by the targeting of particular Ig gene-encoded B cell receptors to induce neutralizing anti-HIV-1 antibodies. To address this issue, we have produced HIV-1 specific and non-HIV-1 mAbs from an infected individual and analyzed the Ig gene usage. Green-fluorescence labeled virus-like particles (VLP) expressing HIV-1 envelope (Env) proteins of JRFL and BaL and control VLPs (without Env) were used to select single B cells for the production of 68 recombinant mAbs. Ten of these mAbs were HIV-1 Env specific with neutralizing activity against V3 and the CD4 binding site, as well as non-neutralizing mAbs to gp41. The remaining 58 mAbs were non-HIV-1 Env mAbs with undefined specificities. Analysis revealed that biased usage of Ig genes was restricted only to anti-HIV-1 but not to non-HIV-1 mAbs. The VH1 family genes were dominantly used, followed by VH3, VH4, and VH5 among anti-HIV-1 mAbs, while non-HIV-1 specific mAbs preferentially used VH3 family genes, followed by VH4, VH1 and VH5 families in a pattern identical to Abs derived from healthy individuals. This observation suggests that the biased usage of Ig genes by anti-HIV-1 mAbs is driven by structural requirements of the virus antigens rather than by compensation to any depletion of VH3 B cells due to autoreactive mechanisms, according to the gp120 superantigen hypothesis

Cardiac tumours in children

Cardiac tumours are benign or malignant neoplasms arising primarily in the inner lining, muscle layer, or the surrounding pericardium of the heart. They can be primary or metastatic. Primary cardiac tumours are rare in paediatric practice with a prevalence of 0.0017 to 0.28 in autopsy series. In contrast, the incidence of cardiac tumours during foetal life has been reported to be approximately 0.14%. The vast majority of primary cardiac tumours in children are benign, whilst approximately 10% are malignant. Secondary malignant tumours are 10–20 times more prevalent than primary malignant tumours. Rhabdomyoma is the most common cardiac tumour during foetal life and childhood. It accounts for more than 60% of all primary cardiac tumours. The frequency and type of cardiac tumours in adults differ from those in children with 75% being benign and 25% being malignant. Myxomas are the most common primary tumours in adults constituting 40% of benign tumours. Sarcomas make up 75% of malignant cardiac masses. Echocardiography, Computing Tomography (CT) and Magnetic Resonance Imaging (MRI) of the heart are the main non-invasive diagnostic tools. Cardiac catheterisation is seldom necessary. Tumour biopsy with histological assessment remains the gold standard for confirmation of the diagnosis. Surgical resection of primary cardiac tumours should be considered to relieve symptoms and mechanical obstruction to blood flow. The outcome of surgical resection in symptomatic, non-myxomatous benign cardiac tumours is favourable. Patients with primary cardiac malignancies may benefit from palliative surgery but this approach should not be recommended for patients with metastatic cardiac tumours. Surgery, chemotherapy and radiotherapy may prolong survival. The prognosis for malignant primary cardiac tumours is generally extremely poor

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed