Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing sensitivity and specificity of screening mammography in the United States and Denmark

Delivery of screening mammography differs substantially between the United States (US) and Denmark. We evaluated whether there are differences in screening sensitivity and specificity. We included screens from women screened at age 50–69 years during 1996–2008/2009 in the US Breast Cancer Surveillance Consortium (BCSC) (n = 2,872,791), and from two population‐based mammography screening programs in Denmark (Copenhagen, n = 148,156 and Funen, n = 275,553). Women were followed‐up for 1 year. For initial screens, recall rate was significantly higher in BCSC (17.6%) than in Copenhagen (4.3%) and Funen (3.1%). Sensitivity was fairly similar in BCSC (91.8%) and Copenhagen (90.5%) and Funen (92.5%). At subsequent screens, recall rates were 8.8%, 1.8% and 1.4% in BCSC, Copenhagen and Funen, respectively. The BCSC sensitivity (82.3%) was lower compared with that in Copenhagen (88.9%) and Funen (86.9%), but when stratified by time since last screen, the sensitivity was similar. For both initial and subsequent screenings, the specificity of screening in BCSC (83.2% and 91.6%) was significantly lower than that in Copenhagen (96.6% and 98.8%) and Funen (97.9% and 99.2%). By taking time since last screen into account, it was found that American and Danish women had the same probability of having their asymptomatic cancers detected at screening. However, the majority of women free of asymptomatic cancers experienced more harms in terms of false‐positive findings in the US than in Denmark.
Is Feature Selection Secure against Training Data Poisoning?

Learning in adversarial settings is becoming an important task for application domains where attackers may inject malicious data into the training set to subvert normal operation of data-driven technologies. Feature selection has been widely used in machine learning for security applications to improve generalization and computational efficiency, although it is not clear whether its use may be beneficial or even counterproductive when training data are poisoned by intelligent attackers. In this work, we shed light on this issue by providing a framework to investigate the robustness of popular feature selection methods, including LASSO, ridge regression and the elastic net. Our results on malware detection show that feature selection methods can be significantly compromised under attack (we can reduce LASSO to almost random choices of feature sets by careful insertion of less than 5% poisoned training samples), highlighting the need for specific countermeasures.
Tracing Equilibrium in Dynamic Markets via Distributed Adaptation

Competitive equilibrium is a central concept in economics with numerous applications beyond markets, such as scheduling, fair allocation of goods, or bandwidth distribution in networks. Computation of competitive equilibria has received a significant amount of interest in algorithmic game theory, mainly for the prominent case of Fisher markets. Natural and decentralized processes like tatonnement and proportional response dynamics (PRD) converge quickly towards equilibrium in large classes of Fisher markets. Almost all of the literature assumes that the market is a static environment and that the parameters of agents and goods do not change over time. In contrast, many large real-world markets are subject to frequent and dynamic changes. In this paper, we provide the first provable performance guarantees of discrete-time tatonnement and PRD in markets that are subject to perturbation over time. We analyze the prominent class of Fisher markets with CES utilities and quantify the impact of changes in supplies of goods, budgets of agents, and utility functions of agents on the convergence of tatonnement to market equilibrium. Since the equilibrium becomes a dynamic object and will rarely be reached, our analysis provides bounds expressing the distance to equilibrium that will be maintained via tatonnement and PRD updates. Our results indicate that in many cases, tatonnement and PRD follow the equilibrium rather closely and quickly recover conditions of approximate market clearing. Our approach can be generalized to analyzing a general class of Lyapunov dynamical systems with changing system parameters, which might be of independent interest.
Genome‐wide linkage scan of nonsyndromic orofacial clefting in 91 families of central European origin

Orofacial clefts are among the most common of all congenital disorders. Nonsyndromic cases of cleft lip with or without cleft palate (NSCL/P) and cleft palate only (NSCPO) are considered to have a multifactorial etiology which involves both genetic and environmental factors. We present the results of a genome‐wide linkage scan in 91 families of central European descent with nonsyndromic orofacial clefts (NSC). The sample included 74 NSCL/P families, 15 NSCPO families, and 2 mixed families (a total of 217 affected and 230 unaffected individuals were genotyped). We genotyped 542 microsatellite markers (average intermarker distance = 6.9 cM). Multipoint nonparametric linkage analysis was performed using Allegro 2.0f. In addition to the factors investigated in previous genome‐wide linkage analyses, we searched for sex‐specific susceptibility loci, loci demonstrating parental imprinting and loci that are shared by NSCL/P and NSCPO. Several genomic regions likely to contain susceptibility loci for NSC were identified at the level of nominal significance. Some of these overlap with regions identified in previous studies. Suggestive evidence of linkage was obtained for the loci 4q21‐q26 and 1p31‐p21, with the chromosome 1 locus showing a male‐specific genetic effect. Our study has identified promising chromosomal regions for the identification of NSC‐associated genes, and demonstrates the importance of performing detailed statistical analyses which take into account complex genetic mechanisms such as sex‐specific effects and genomic imprinting. Further research in large patient samples is necessary to identify factors common to NSCL/P and NSCPO. © 2009 Wiley‐Liss, Inc.
Physiologic effects of an ambulatory ventilation system in chronic obstructive pulmonary disease.

RATIONALE Exercise intolerance limits the ability of patients with chronic obstructive pulmonary disease (COPD) to perform daily living activities. Noninvasive ventilation reduces dyspnea and improves exercise performance, but current systems are unsuitable for ambulatory use. OBJECTIVES In patients with COPD experiencing exercise-induced desaturation, we evaluated improvements in exercise tolerance facilitated by a wearable, 1-lb, noninvasive open ventilation (NIOV) system featuring a nasal pillow interface during constant work rate (CWR) cycle ergometer exercise and associated effects on dyspnea, respiratory muscle activation, and pulmonary gas exchange efficiency. METHODS Fifteen men with COPD (FEV₁ = 32.2 ± 12.0% predicted; FEV₁/FVC = 31.6 ± 7.1%; exercise oxygen saturation as measured by pulse oximetry [Spo₂] = 86.5 ± 2.9%) participated. After incremental testing establishing peak work rate, subjects completed three visits in which they performed CWR exercise to tolerance at 80% peak work rate: (1) unencumbered breathing room air, (2) using NIOV+compressed air, (3) using NIOV+compressed O₂, or (4) using O₂ via nasal cannula. Assessments included exercise duration, surface inspiratory muscle EMG, Spo₂, transcutaneous Pco₂, and Borg dyspnea scores. MEASUREMENTS AND MAIN RESULTS Exercise endurance was 17.6 ± 5.7 minutes using NIOV+O₂, greatly prolonged compared with unencumbered (5.6 ± 1.9 min), nasal O₂ (11.4 ± 6.8 min), and NIOV+Air (6.3 ± 4.1 min). Isotime Spo₂ was higher and intercostal, scalene, and diaphragmatic EMG activity was reduced using NIOV+O₂ compared with unencumbered, nasal O₂, and NIOV+Air, signifying respiratory muscle unloading. Isotime dyspnea reduction correlated with isotime EMG reduction (r = 0.42, P = 0.0053). There were no significant differences in isotime VD/VT or transcutaneous Pco₂ among treatments. CONCLUSIONS NIOV+O₂ yielded substantial exercise endurance improvements accompanied by respiratory muscle unloading and dyspnea reductions in patients with severe hypoxemic COPD.
Clinical and pathologic findings in hereditary spastic paraparesis with spastin mutation

This case is extremely important because it is the first to demonstrate the pathologic basis for dementia in SPG4-linked HSP. The findings reported in the article suggest a distinct pathologic process not seen in other dementing conditions. Earlier neuropsychological evidence of a unique dementing process in a large Irish family with HSP linked to SPG4 2 supports this thesis. We differ from the authors in their interpretation of the data on the frequency of dementia in SPG4-linked HSP. They suggest that very few SPG4 families manifest this syndrome. Like many clinical phenomena, this disorder will only be found if one looks for it using appropriate clinical tools, including psychometric testing. We contend that cognitive impairment is an intrinsic feature of all families with SPG4-linked HSP. This can be demonstrated by using age-, sex-, and education-matched controls, and is evident from age 40 in such studies using the Cambridge Cognitive Examination (CAMCOG). After age 60 years, the CAMCOG scores for subjects with SPG4-linked HSP drops below 80 (the threshold for dementia), and after 70 years of age, patients show strikingly evident dementia with behavioral changes. 4 This is clear in the study by White et al., 1 as they mention that the index patient, as well as his sister and his mother, had memory impairment after age 70 years, according to reports of other family members. The reason that this dementia has been so infrequently reported is because HSP is a rare disorder, and affected patients, who are often in wheelchairs, are protected by caregivers and not exposed to the usual challenges of new situations. In addition, neurologists have not systematically looked for this disorder. We would suggest that using the appropriate cognitive tests, deficits may be detected at least in the seventh decade of life. Perhaps a collaborative study between American and European clinicians with access to these families would be worthwhile.
Adjunctive brivaracetam in adults with uncontrolled focal epilepsy: Results from a double‐blind, randomized, placebo‐controlled trial

Brivaracetam (BRV) is a novel high‐affinity synaptic vesicle protein 2A ligand in clinical development for the treatment of epilepsy. This phase III study (N01252; NCT00490035) evaluated the efficacy and safety/tolerability of BRV (20, 50, and 100 mg/day) compared with placebo (PBO) in patients aged 16–70 years with uncontrolled focal seizures with/without secondary generalization, despite treatment with one to two concomitant antiepileptic drugs at a stable and optimal dosage.
Efficacy of Plasma Rich in Growth Factors for the Treatment of Dry Eye

Purpose: To evaluate the efficacy of plasma rich in growth factors (PRGF) for the treatment of moderate/severe dry eye. Methods: PRGF treatment was administered to 16 patients who had moderate/severe dry eye diagnosed and who had not responded previously to other standard treatments. We quantified several growth factors present in the PRGF of each patient and obtained quantitative registers of the symptoms (modified score dry eye questionnaire), both before and after PRGF treatment. We also performed impression cytology to determine the degree of squamous metaplasia before and after PRGF treatment. Results: PRGF treatment was associated with a statistically significant improvement in score dry eye questionnaire values (P < 0.001). Results from impression cytology corroborated this improvement, but the reduction in the degree of squamous metaplasia was not statistically significant. In 75% of patients treated with PRGF, no further treatments were required, whereas in the remaining 25% other ocular treatments could be reduced. Conclusions: PRGF led to symptom improvement in patients with moderate/severe dry eye. Surprisingly, the symptoms recorded in the dry eye questionnaire do not always agree with the degree of squamous metaplasia measured by impression cytology.
Can Psychiatrists and Neurologists Predict Their Patients' Participation Preferences?

There is evidence that an optimal match of patients' participation preferences improves health outcomes. Since it is unknown whether psychiatrists and neurologists can predict their patients' participation preferences we performed a cross-sectional survey involving N = 101 inpatients with schizophrenia/schizoaffective disorder and N = 102 inpatients with multiple sclerosis. Both patients and their physicians in charge were surveyed with respect to the patients' participation preferences, using the Autonomy Preference Index and a global estimate. Most patients wished to participate in medical decision making. Doctors performed poorly when predicting their individual patients' participation preferences and tended to overestimate their patients' participation preferences. A longer duration of the hospital stay did not improve the accuracy of doctors' estimates. Thus, neurologists and psychiatrists fail at predicting their patients' participation preferences accurately, which might challenge patients' treatment satisfaction. More attention in the consultation should be paid to patients' preferences.
Optimizing Experimental Design for Comparing Models of Brain Function

This article presents the first attempt to formalize the optimization of experimental design with the aim of comparing models of brain function based on neuroimaging data. We demonstrate our approach in the context of Dynamic Causal Modelling (DCM), which relates experimental manipulations to observed network dynamics (via hidden neuronal states) and provides an inference framework for selecting among candidate models. Here, we show how to optimize the sensitivity of model selection by choosing among experimental designs according to their respective model selection accuracy. Using Bayesian decision theory, we (i) derive the Laplace-Chernoff risk for model selection, (ii) disclose its relationship with classical design optimality criteria and (iii) assess its sensitivity to basic modelling assumptions. We then evaluate the approach when identifying brain networks using DCM. Monte-Carlo simulations and empirical analyses of fMRI data from a simple bimanual motor task in humans serve to demonstrate the relationship between network identification and the optimal experimental design. For example, we show that deciding whether there is a feedback connection requires shorter epoch durations, relative to asking whether there is experimentally induced change in a connection that is known to be present. Finally, we discuss limitations and potential extensions of this work.
Prevalence of the Novel Torque Teno Sus Virus Species k2b from Pigs in the United States and Lack of Association with Post‐Weaning Multisystemic Wasting Syndrome or Mulberry Heart Disease

The family Anelloviridae includes a number of viruses infecting humans (Torque teno viruses, TTV) and other animals including swine (Torque teno sus viruses, TTSuV). Two genetically distinct TTSuV species have been identified from swine thus far (TTSuV1 and TTSuVk2), although their definitive association with disease remains debatable. In 2012, a novel TTSuV species was identified from commercial swine serum and classified in the genus Kappatorquevirus as TTSuVk2b. The other Kappatorquevirus species, TTSuVk2a, has been associated with post-weaning multisystemic wasting syndrome (PMWS) when coinfected with porcine circovirus type 2 (PCV2). Therefore, in this study, we initially amplified a portion of TTSuVk2b ORF1 and, subsequently, assessed the molecular prevalence of the virus in pigs in the United States. A total of 127 serum and 115 tissue samples were obtained from pigs with PMWS or mulberry heart disease (MHD) in six states and tested by PCR for the presence of TTSuVk2b DNA. Approximately 27.6% of the serum and 21.7% of tissue samples tested positive for TTSuVk2b DNA, and the positive products were confirmed by sequencing. However, we did not detect a correlation between TTSuVk2b infection and PMWS or MHD. The near full-length genomic sequence of US TTSuVk2b was determined, and sequence analysis revealed that the US TTSuVk2b isolates were 95% identical to the TTSuVk2b isolate from Spain, with most of the variations clustering in ORF1. We conclude that the novel TTSuVk2b species is present in pigs in the United States and its potential association with a disease warrants further investigation.
Antidote to cannabinoid intoxication: the CB1 receptor inverse agonist, AM251, reverses hypothermic effects of the CB1 receptor agonist, CB‐13, in mice

Cannabis is a recreational drug leading to intoxication, following stimulation of cannabinoid CB1 receptors. However, more recently, herbs mixed with synthetic cannabinoids sometimes known as ‘Spice’ and ‘Black Mamba’ have been increasingly used, and their high CB1 receptor affinity has led not only to marked intoxication but also life‐threatening complications and an increasing number of deaths. Although many studies have indicated that prophylactic treatment with CB1 receptor antagonists can block cannabimimetic effects in animals and humans, the aim of this study was to determine whether CB1 receptor antagonism could reverse physical cannabimimetic effects.
Effect of Using Regression on Class Confidence Scores in Sentiment Analysis of Twitter Data

In this study, we aim to test our hypothesis that confidence scores of sentiment values of tweets aid in classification of sentiment. We used several feature sets consisting of lexical features, emoticons, features based on sentiment scores and combination of lexical and sentiment features. Since our dataset includes confidence scores of real numbers in [0-1] range, we employ regression analysis on each class of sentiments. We determine the class label of a tweet by looking at the maximum of the confidence scores assigned to it by these regressors. We test the results against classification results obtained by converting the confidence scores into discrete labels. Thus, the strength of sentiment is ignored. Our expectation was that taking the strength of sentiment into consideration would improve the classification results. Contrary to our expectations, our results indicate that using classification on discrete class labels and ignoring sentiment strength perform similar to using regression on continuous confidence scores.
Fast and Accurate Estimation of Quality of Results in High-Level Synthesis with Machine Learning

While high-level synthesis (HLS) offers sophisticated techniques to optimize designs for area and performance, HLS-estimated resource usage and timing often deviate significantly from actual quality of results (QoR) achieved by FPGA-targeted designs. Inaccurate HLS estimates prevent designers from performing meaningful design space exploration without resorting to the time-consuming downstream implementation process. To address this challenge, we first build a large collection of C-to-FPGA results from a diverse set of realistic HLS applications and identify relevant features from HLS reports for estimating post-implementation metrics. We then leverage these features and data to train and compare a number of promising machine learning models to effectively and efficiently bridge the accuracy gap. Experiments demonstrate that our proposed approach is able to dramatically reduce the estimation errors for different families of FPGA devices. By extracting domain-specific insights from our experiments, we explore the implications of our models and predictive influence of various features for enabling fast and accurate QoR estimation in HLS. We have released our dataset to springboard future efforts in this area.
Association between TGFBR1 Polymorphisms and Cancer Risk: A Meta-Analysis of 35 Case-Control Studies

Background Numerous epidemiological studies have evaluated the association between TGFBR1 polymorphisms and the risk of cancer, however, the results remain inconclusive. To derive a more precise estimation of the relation, we conducted a comprehensive meta-analysis of all available case-control studies relating the TGFBR1*6A and IVS7+24G>A polymorphisms of the TGFBR1 gene to the risk of cancer. Methods Eligible studies were identified by search of electronic databases. Overall and subgroup analyses were performed. Odds ratio (OR) and 95% confidence interval (CI) were applied to assess the associations between TGFBR1*6A and IVS7+24G>A polymorphisms and cancer risk. Results A total of 35 studies were identified, 32 with 19,767 cases and 18,516 controls for TGFBR1*6A polymorphism and 12 with 4,195 cases and 4,383 controls for IVS7+24G>A polymorphism. For TGFBR1*6A, significantly elevated cancer risk was found in all genetic models (dominant OR = 1.11, 95% CI = 1.04∼1.18; recessive: OR = 1.36, 95% CI = 1.11∼1.66; additive: OR = 1.13, 95% CI = 1.05∼1.20). In subgroup analysis based on cancer type, increased cancer risk was found in ovarian and breast cancer. For IVS7+24G>A, significant correlation with overall cancer risk (dominant: OR = 1.39, 95% CI = 1.15∼1.67; recessive: OR = 2.23, 95% CI = 1.26∼3.92; additive: OR = 1.43, 95% CI = 1.14∼1.80) was found, especially in Asian population. In the subgroup analysis stratified by cancer type, significant association was found in breast and colorectal cancer. Conclusions Our investigations demonstrate that TGFBR1*6A and IVS7+24G>A polymorphisms of TGFBR1 are associated with the susceptibility of cancer, and further functional research should be performed to explain the inconsistent results in different ethnicities and cancer types.
Compiler techniques for high performance sequentially consistent java programs

The rise of Java, C#, and other explicitly parallel languages has increased the importance of compiling for different software memory models. This paper describes co-operating escape, thread structure, and delay set analyses that enable high performance for sequentially consistent programs.We compare the performance of a set of Java programs compiled for sequential consistency (SC) with the performance of the same programs compiled for weak consistency. For SC, we observe a slowdown of 10% on average for an architecture based on the Intel Xeon processor, and 26% on average for an architecture based on the IBM Power3.
Children’s Allocation of Study Time during the Solution of Raven’s Progressive Matrices

The acuity of reasoning on Raven’s Progressive Matrices is strongly influenced by strategic determinants. Building on metamemory studies that highlight the influence of study-time allocation on memory development, we investigated children’s allocation of study time while solving these matrices. A total of 170 children aged 6–12 years completed a computerized short-form version of the standard matrices featuring items selected to represent a broad range of difficulties. Beyond analyzing changes in mean latencies and performances with age, we used generalized additive mixed models to explore within-participant variability in response times as a function of both item complexity and overall individual efficiency. Results revealed that individual differences in performances were significantly associated with children’s adaptive modulation of response times. Mediation analysis further indicated that response-time modulation contributed to age-related changes in performance. Taking account of study-time allocation in reasoning tasks may open up new avenues for the study of reasoning development and the assessment of intellectual functioning.
A pathologist's odyssey.

I am honored to write the prefatory chapter for the inaugural volume of the Annual Review of Pathology: Mechanisms of Disease. This publishing venture signals that pathology takes its rightful place alongside the other biomedical sciences. I thought it may be of interest to some to delineate how a circuitous path led me into a career in experimental pathology and to give some of the flavor of a past era in experimental approaches. Thus, my title.