HIPAD - A Hybrid Interior-Point Alternating Direction algorithm for knowledge-based SVM and feature selection

We consider classification tasks in the regime of scarce labeled training data in high dimensional feature space, where specific expert knowledge is also available. We propose a new hybrid optimization algorithm that solves the elastic-net support vector machine (SVM) through an alternating direction method of multipliers in the first phase, followed by an interior-point method for the classical SVM in the second phase. Both SVM formulations are adapted to knowledge incorporation. Our proposed algorithm addresses the challenges of automatic feature selection, high optimization accuracy, and algorithmic flexibility for taking advantage of prior knowledge. We demonstrate the effectiveness and efficiency of our algorithm and compare it with existing methods on a collection of synthetic and real-world data.Comment: Proceedings of 8th Learning and Intelligent OptimizatioN (LION8) Conference, 201

Nanostructured interfacial self-assembled peptide-polymer membranes for enhanced mineralization and cell adhesion

This work was supported by national funds through the Portuguese Foundation for Science and Technology (FCT) under the scope of the project PTDC/CTM-BIO/0814/2012 and by the European Regional Development Fund (ERDF) through the Operational Competitiveness Programme “COMPETE” (FCOMP-01-0124-FEDER-028491). J. Borges and R. P. Pirraco gratefully acknowledge funding support from FCT for postdoctoral (SFRH/BPD/103604/2014) and investigator (IF/00347/2015) grants, respectively. Y. Shi acknowledges China Scholarship Council for her PhD scholarship (no. 201307060020). H. S. Azevedo also acknowledges financial support from the EU-funded project “SuprHApolymers” (PCIG14-GA-2013-631871) and A. Mata acknowledges the European Research Council Starting Grant “STROFUNSCAFF” and the Marie Curie Career Integration Grant “BIOMORPH”

The diagnosis of mental disorders: the problem of reification

A pressing need for interrater reliability in the diagnosis of mental disorders emerged during the mid-twentieth century, prompted in part by the development of diverse new treatments. The Diagnostic and Statistical Manual of Mental Disorders (DSM), third edition answered this need by introducing operationalized diagnostic criteria that were field-tested for interrater reliability. Unfortunately, the focus on reliability came at a time when the scientific understanding of mental disorders was embryonic and could not yield valid disease definitions. Based on accreting problems with the current DSM-fourth edition (DSM-IV) classification, it is apparent that validity will not be achieved simply by refining criteria for existing disorders or by the addition of new disorders. Yet DSM-IV diagnostic criteria dominate thinking about mental disorders in clinical practice, research, treatment development, and law. As a result, the modernDSMsystem, intended to create a shared language, also creates epistemic blinders that impede progress toward valid diagnoses. Insights that are beginning to emerge from psychology, neuroscience, and genetics suggest possible strategies for moving forward

Fixed Effect Estimation of Large T Panel Data Models

This article reviews recent advances in fixed effect estimation of panel data models for long panels, where the number of time periods is relatively large. We focus on semiparametric models with unobserved individual and time effects, where the distribution of the outcome variable conditional on covariates and unobserved effects is specified parametrically, while the distribution of the unobserved effects is left unrestricted. Compared to existing reviews on long panels (Arellano and Hahn 2007; a section in Arellano and Bonhomme 2011) we discuss models with both individual and time effects, split-panel Jackknife bias corrections, unbalanced panels, distribution and quantile effects, and other extensions. Understanding and correcting the incidental parameter bias caused by the estimation of many fixed effects is our main focus, and the unifying theme is that the order of this bias is given by the simple formula p/n for all models discussed, with p the number of estimated parameters and n the total sample size.Comment: 40 pages, 1 tabl

Patient-Specific Prosthetic Fingers by Remote Collaboration - A Case Study

The concealment of amputation through prosthesis usage can shield an amputee from social stigma and help improve the emotional healing process especially at the early stages of hand or finger loss. However, the traditional techniques in prosthesis fabrication defy this as the patients need numerous visits to the clinics for measurements, fitting and follow-ups. This paper presents a method for constructing a prosthetic finger through online collaboration with the designer. The main input from the amputee comes from the Computer Tomography (CT) data in the region of the affected and the non-affected fingers. These data are sent over the internet and the prosthesis is constructed using visualization, computer-aided design and manufacturing tools. The finished product is then shipped to the patient. A case study with a single patient having an amputated ring finger at the proximal interphalangeal joint shows that the proposed method has a potential to address the patient's psychosocial concerns and minimize the exposure of the finger loss to the public.Comment: Open Access articl

Proceedings of the Second Annual Conference of the MidSouth Computational Biology and Bioinformatics Society

The MCBIOS 2004 conference brought together regional researchers and students in biology, computer science and bioinformatics on October 7th-9th 2004 to present their latest work. This editorial describes the conference itself and introduces the twelve peer-reviewed manuscripts accepted for publication in the Proceedings of the MCBIOS 2004 Conference. These manuscripts included new methods for analysis of high-throughput gene expression experiments, EST clustering, analysis of mass spectrometry data and genomic analysi

Inhibition of Y1 receptor signaling improves islet transplant outcome

Failure to secrete sufficient quantities of insulin is a pathological feature of type-1 and type-2 diabetes, and also reduces the success of islet cell transplantation. Here we demonstrate that Y1 receptor signaling inhibits insulin release in β-cells, and show that this can be pharmacologically exploited to boost insulin secretion. Transplanting islets with Y1 receptor deficiency accelerates the normalization of hyperglycemia in chemically induced diabetic recipient mice, which can also be achieved by short-term pharmacological blockade of Y1 receptors in transplanted mouse and human islets. Furthermore, treatment of non-obese diabetic mice with a Y1 receptor antagonist delays the onset of diabetes. Mechanistically, Y1 receptor signaling inhibits the production of cAMP in islets, which via CREB mediated pathways results in the down-regulation of several key enzymes in glycolysis and ATP production. Thus, manipulating Y1 receptor signaling in β-cells offers a unique therapeutic opportunity for correcting insulin deficiency as it occurs in the pathological state of type-1 diabetes as well as during islet transplantation.Islet transplantation is considered one of the potential treatments for T1DM but limited islet survival and their impaired function pose limitations to this approach. Here Loh et al. show that the Y1 receptor is expressed in β- cells and inhibition of its signalling, both genetic and pharmacological, improves mouse and human islet function.info:eu-repo/semantics/publishe

Responsiveness differences in outcome instruments after revision hip arthroplasty: What are the implications?

Responsiveness to change is an important psychometric property of an outcome instrument. Assessment of health-related quality of life (HRQoL) is critical to outcome assessment after total joint replacement, a surgery aimed at improving pain, function and HRQoL of the patients undergoing these procedures. In a recent study, Shi et al. examined the responsiveness to change of various subscales of two instruments, physician-administered Harris Hip Score and patient self-administered Short Form-36 (SF-36), 6 months after revision total hip arthroplasty. The responsiveness statistics for both scales were reasonable, higher for Harris Hip Score than SF-36. This is the first study to examine responsiveness of these instruments in revision THA patients in a systematic fashion

A System for the Synchronized Recording of Sonomyography, Electromyography and Joint Angle

Ultrasound and electromyography (EMG) are two of the most commonly used diagnostic tools for the assessment of muscles. Recently, many studies reported the simultaneous collection of EMG signals and ultrasound images, which were normally amplified and digitized by different devices. However, there is lack of a systematic method to synchronize them and no study has reported the effects of ultrasound gel to the EMG signal collection during the simultaneous data collection. In this paper, we introduced a new method to synchronize ultrasound B-scan images, EMG signals, joint angles and other related signals (e.g. force and velocity signals) in real-time. The B-mode ultrasound images were simultaneously captured by the PC together with the surface EMG (SEMG) and the joint angle signal. The deformations of the forearm muscles induced by wrist motions were extracted from a sequence of ultrasound images, named as Sonomyography (SMG). Preliminary experiments demonstrated that the proposed method could reliably collect the synchronized ultrasound images, SEMG signals and joint angle signals in real-time. In addition, the effect of ultrasound gel on the SEMG signals when the EMG electrodes were close to the ultrasound probe was studied. It was found that the SEMG signals were not significantly affected by the amount of the ultrasound gel. The system is being used for the study of contractions of various muscles as well as the muscle fatigue

Macrophage-Specific ApoE Gene Repair Reduces Diet-Induced Hyperlipidemia and Atherosclerosis in Hypomorphic Apoe Mice

Apolipoprotein (apo) E is best known for its ability to lower plasma cholesterol and protect against atherosclerosis. Although the liver is the major source of plasma apoE, extra-hepatic sources of apoE, including from macrophages, account for up to 10% of plasma apoE levels. This study examined the contribution of macrophage-derived apoE expression levels in diet-induced hyperlipidemia and atherosclerosis.Hypomorphic apoE (Apoe(h/h)) mice expressing wildtype mouse apoE at ∼2-5% of physiological levels in all tissues were derived by gene targeting in embryonic stem cells. Cre-mediated gene repair of the Apoe(h/h) allele in Apoe(h/h)LysM-Cre mice raised apoE expression levels by 26 fold in freshly isolated peritoneal macrophages, restoring it to 37% of levels seen in wildtype mice. Chow-fed Apoe(h/h)LysM-Cre and Apoe(h/h) mice displayed similar plasma apoE and cholesterol levels (55.53±2.90 mg/dl versus 62.70±2.77 mg/dl, n = 12). When fed a high-cholesterol diet (HCD) for 16 weeks, Apoe(h/h)LysM-Cre mice displayed a 3-fold increase in plasma apoE and a concomitant 32% decrease in plasma cholesterol when compared to Apoe(h/h) mice (602.20±22.30 mg/dl versus 888.80±24.99 mg/dl, n = 7). On HCD, Apoe(h/h)LysM-Cre mice showed increased apoE immunoreactivity in lesional macrophages and liver-associated Kupffer cells but not hepatocytes. In addition, Apoe(h/h)LysM-Cre mice developed 35% less atherosclerotic lesions in the aortic root than Apoe(h/h) mice (167×10(3)±16×10(3) µm(2) versus 259×10(3)±56×10(3) µm(2), n = 7). This difference in atherosclerosis lesions size was proportional to the observed reduction in plasma cholesterol.Macrophage-derived apoE raises plasma apoE levels in response to diet-induced hyperlipidemia and by such reduces atherosclerosis proportionally to the extent to which it lowers plasma cholesterol levels