Miracle-dz/UniFAR-FTUs huggingface dataset:
Multisite Delayed Feedback for Electrical Brain Stimulation

Demand-controlled deep brain stimulation (DBS) appears to be a promising approach for the treatment of Parkinson's disease (PD) as revealed by computational, pre-clinical and clinical studies. Stimulation delivery is adapted to brain activity, for example, to the amount of neuronal activity considered to be abnormal. Such a closed-loop stimulation setup might help to reduce the amount of stimulation current, thereby maintaining therapeutic efficacy. In the context of the development of stimulation techniques that aim to restore desynchronized neuronal activity on a long-term basis, specific closed-loop stimulation protocols were designed computationally. These feedback techniques, e.g., pulsatile linear delayed feedback (LDF) or pulsatile nonlinear delayed feedback (NDF), were computationally developed to counteract abnormal neuronal synchronization characteristic for PD and other neurological disorders. By design, these techniques are intrinsically demand-controlled methods, where the amplitude of the stimulation signal is reduced when the desired desynchronized regime is reached. We here introduce a novel demand-controlled stimulation method, pulsatile multisite linear delayed feedback (MLDF), by employing MLDF to modulate the pulse amplitude of high-frequency (HF) DBS, in this way aiming at a specific, MLDF-related desynchronizing impact, while maintaining safety requirements with the charge-balanced HF DBS. Previously, MLDF was computationally developed for the control of spatio-temporal synchronized patterns and cluster states in neuronal populations. Here, in a physiologically motivated model network comprising neurons from subthalamic nucleus (STN) and external globus pallidus (GPe), we compare pulsatile MLDF to pulsatile LDF for the case where the smooth feedback signals are used to modulate the amplitude of charge-balanced HF DBS and suggest a modification of pulsatile MLDF which enables a pronounced desynchronizing impact. Our results may contribute to further clinical development of closed-loop DBS techniques.
Postnatal NG2 proteoglycan–expressing progenitor cells are intrinsically multipotent and generate functional neurons

Neurogenesis is known to persist in the adult mammalian central nervous system (CNS). The identity of the cells that generate new neurons in the postnatal CNS has become a crucial but elusive issue. Using a transgenic mouse, we show that NG2 proteoglycan–positive progenitor cells that express the 2′,3′-cyclic nucleotide 3′-phosphodiesterase gene display a multipotent phenotype in vitro and generate electrically excitable neurons, as well as astrocytes and oligodendrocytes. The fast kinetics and the high rate of multipotent fate of these NG2+ progenitors in vitro reflect an intrinsic property, rather than reprogramming. We demonstrate in the hippocampus in vivo that a sizeable fraction of postnatal NG2+ progenitor cells are proliferative precursors whose progeny appears to differentiate into GABAergic neurons capable of propagating action potentials and displaying functional synaptic inputs. These data show that at least a subpopulation of postnatal NG2-expressing cells are CNS multipotent precursors that may underlie adult hippocampal neurogenesis.
CEP 1507 C arbon Emissions and Business Cycle s

Using structural Vector Autoregressions (SVARs), we estimate the response of carbon dioxide emissions to technology and policy shocks to the U.S. economy to inform the recent environmental economics literature employing dynamic stochastic general equilibrium (E-DSGE) models. Although unanticipated technology shocks can account for the positive correlation between output and emissions observed in the data, they account for less than 10 percent of variation in emissions. Government spending and monetary policy shocks are not a significant source of emissions’ variation either. By contrast, anticipated investment technology shocks account for 25 percent of such variation. We also present an E-DSGE model with emission responses to technology shocks that are consistent with the ones we estimate using SVARs. JEL classification: E32, Q58, Q54
Fine Needle Aspiration Biopsy of Salivary Gland Lesions

OBJECTIVE To assess the diagnostic value of fine needle aspiration biopsy in individual lesions of the salivary glands. STUDY DESIGN During a 16-year period (1979-1995), 841 salivary gland lesions were investigated by fine needle aspiration with cytologic examination. The lesions affected the parotid gland area in all cases except 85 and 19, respectively, in which the submandibular gland and oral cavity (more often the palate) were involved. RESULTS Approximately 3% (25/841) of the aspirates were inadequate, and in 97% of cases they represented the result of samplings performed outside our institution. The 816 diagnostic aspirates comprised 245 cases negative for tumor cells (benign cysts, inflammatory, malformed, degenerative lesions), 571 positive for tumor cells (benign; malignant; not otherwise specified [NOS]); metastatic to the salivary gland tissue; or to the intraparotid or periparotid lymph nodes). Among the 245 cases negative for tumor cells, 36 underwent surgery, and the absence of a neoplasm was histologically confirmed in all cases but one (a low grade mucoepidermoid carcinoma, underdiagnosed as a retention cyst). Among the 571 patients having a cytologic diagnosis positive for tumor cells, in 518 the lesion was removed and the tumor nature confirmed. The cytologic diagnosis of a neoplastic lesion demonstrated a good correlation with histology except in an oncocytic adenoma diagnosed as a Warthin's tumor, in a basal cell adenoma diagnosed as pleomorphic adenoma, in a low grade mucoepidermoid carcinoma of the palate diagnosed as a polymorphous low grade adenocarcinoma and in a vegetative intravascular hemangioendothelioma diagnosed as a possible malignant tumor, NOS. CONCLUSION The accuracy was 97%, the sensitivity to the presence of a tumor 98% and the specificity for absence of a neoplasm 98%. Despite the relative rarity of salivary gland tumors, if established diagnostic criteria are present and strictly observed, the great majority of the common variants of the nonneoplastic and both benign and malignant salivary gland tumors can be diagnosed with a high level of accuracy. There remains a proportion of "problem cases" due to the rarity of the lesions, and in these circumstances the uncertainty must be conveyed to the surgeon openly, leaving the diagnosis open, with a few suggested differential diagnoses.
Solving Linear SVMs with Multiple 1D Projections

We present a new methodology for solving linear Support Vector Machines (SVMs) that capitalizes on multiple 1D projections. We show that the approach approximates the optimal solution with high accuracy and comes with analytical guarantees. Our solution adapts on methodologies from random projections, exponential search, and coordinate descent. In our experimental evaluation, we compare our approach with the popular liblinear SVM library. We demonstrate a significant speedup on various benchmarks. At the same time, the new methodology provides a comparable or better approximation factor of the optimal solution and exhibits smooth convergence properties. Our results are accompanied by bounds on the time complexity and accuracy.
SpiroSmart: using a microphone to measure lung function on a mobile phone

Home spirometry is gaining acceptance in the medical community because of its ability to detect pulmonary exacerbations and improve outcomes of chronic lung ailments. However, cost and usability are significant barriers to its widespread adoption. To this end, we present SpiroSmart, a low-cost mobile phone application that performs spirometry sensing using the built-in microphone. We evaluate SpiroSmart on 52 subjects, showing that the mean error when compared to a clinical spirometer is 5.1% for common measures of lung function. Finally, we show that pulmonologists can use SpiroSmart to diagnose varying degrees of obstructive lung ailments.
Steroid Transport, Local Synthesis, and Signaling within the Brain: Roles in Neurogenesis, Neuroprotection, and Sexual Behaviors

Sex steroid hormones are synthesized from cholesterol and exert pleiotropic effects notably in the central nervous system. Pioneering studies from Baulieu and colleagues have suggested that steroids are also locally-synthesized in the brain. Such steroids, called neurosteroids, can rapidly modulate neuronal excitability and functions, brain plasticity, and behavior. Accumulating data obtained on a wide variety of species demonstrate that neurosteroidogenesis is an evolutionary conserved feature across fish, birds, and mammals. In this review, we will first document neurosteroidogenesis and steroid signaling for estrogens, progestagens, and androgens in the brain of teleost fish, birds, and mammals. We will next consider the effects of sex steroids in homeostatic and regenerative neurogenesis, in neuroprotection, and in sexual behaviors. In a last part, we will discuss the transport of steroids and lipoproteins from the periphery within the brain (and vice-versa) and document their effects on the blood-brain barrier (BBB) permeability and on neuroprotection. We will emphasize the potential interaction between lipoproteins and sex steroids, addressing the beneficial effects of steroids and lipoproteins, particularly HDL-cholesterol, against the breakdown of the BBB reported to occur during brain ischemic stroke. We will consequently highlight the potential anti-inflammatory, anti-oxidant, and neuroprotective properties of sex steroid and lipoproteins, these latest improving cholesterol and steroid ester transport within the brain after insults.
Second-Order Optimization for Non-Convex Machine Learning: An Empirical Study

While first-order optimization methods such as stochastic gradient descent (SGD) are popular in machine learning (ML), they come with well-known deficiencies, including relatively-slow convergence, sensitivity to the settings of hyper-parameters such as learning rate, stagnation at high training errors, and difficulty in escaping flat regions and saddle points. These issues are particularly acute in highly non-convex settings such as those arising in neural networks. Motivated by this, there has been recent interest in second-order methods that aim to alleviate these shortcomings by capturing curvature information. In this paper, we report detailed empirical evaluations of a class of Newton-type methods, namely sub-sampled variants of trust region (TR) and adaptive regularization with cubics (ARC) algorithms, for non-convex ML problems. In doing so, we demonstrate that these methods not only can be computationally competitive with hand-tuned SGD with momentum, obtaining comparable or better generalization performance, but also they are highly robust to hyper-parameter settings. Further, in contrast to SGD with momentum, we show that the manner in which these Newton-type methods employ curvature information allows them to seamlessly escape flat regions and saddle points.
Implications of macrophage polarization in autoimmunity

Macrophages are extremely heterogeneous and plastic cells with an important role not only in physiological conditions, but also during inflammation (both for initiation and resolution). In the early 1990s, two different phenotypes of macrophages were described: one of them called classically activated (or inflammatory) macrophages (M1) and the other alternatively activated (or wound‐healing) macrophages (M2). Currently, it is known that functional polarization of macrophages into only two groups is an over‐simplified description of macrophage heterogeneity and plasticity; indeed, it is necessary to consider a continuum of functional states. Overall, the current available data indicate that macrophage polarization is a multifactorial process in which a huge number of factors can be involved producing different activation scenarios. Once a macrophage adopts a phenotype, it still retains the ability to continue changing in response to new environmental influences. The reversibility of polarization has a critical therapeutic value, especially in diseases in which an M1/M2 imbalance plays a pathogenic role. In this review, we assess the high plasticity of macrophages and their potential to be exploited to reduce chronic/detrimental inflammation. On the whole, the evidence detailed in this review underscores macrophage polarization as a target of interest for immunotherapy.
Direct coronary stent implantation does not reduce the incidence of in-stent restenosis or major adverse cardiac events Six month results of a randomized trial

A.J.J. IJsselmuiden, P.W. Serruys, A. Scholte, F. Kiemeneij, T. Slagboom, L.R. v/d Wieken, G.J. Tangelder, G.J. Laarman Amsterdam Department of Interventional Cardiology, OLVG-Hospital, 1 Oosterparkstraat 279, 1090 HM, Amsterdam, The Netherlands Department of Interventional Cardiology, Thoraxcenter, University Hospital Dijkzigt, Rotterdam, The Netherlands Department of Physiology, Vrije Universiteit Medical Center, Amsterdam, The Netherlands
A case study in the gamification of a university-level games development course

Gamification is the application of game mechanics and player incentives to non-game environments. When designed correctly, gamification has been found to increase engagement and encourage targeted behaviours among users. This paper presents the gamification of a university course in Computer Games Development using an online learning management tool, including how this might generalize to other courses. Our goal with gamification was to improve lecture attendance, content understanding, problem solving skills and general engagement. The success of this intervention was measured using course marks, lecturer evaluations, lecture attendance, and a questionnaire; all with strongly positive results. However, this must be balanced against the costs, both monetary and time, required to successfully implement gamification.
Regional Differences in the Prevalence of Cardiovascular Disease.

BACKGROUND Cardiovascular disease continues to be the single most common cause of death and to account for the largest single portion of treatment costs in Germany. Reliable data on regional differences in the frequency of cardio - vascular disease are important for the planning of targeted care structures and preventive measures. METHODS Pooled data from the German Health Update (GEDA), a nationwide telephone health survey conducted in 2009, 2010 and 2012 (n = 62 214) were used to estimate the lifetime prevalence of major cardiovascular disease (self-reported medical diagnosis of myocardial infarction, other coronary heart disease, stroke, or congestive heart failure) in each of the German federal states. The influence of sociodemographic factors on regional prevalence differences was examined in adjusted logistic regression analyses. Prevalences were compared with mortality rates from cardiovascular disease that were obtained from cause-of-death statistics. RESULTS The lifetime prevalence of cardiovascular disease in Germany ranged from 10.0% in Baden-W¨rttemberg to 15.8% in Saxony-Anhalt. After adjustment for age, sex, socioeconomic status, and size of the communities of residence, nine of the other 15 states had significantly higher prevalences than Baden-W¨rttemberg, with odds ratios ranging from 1.26 (Hesse) to 1.55 (Saxony-Anhalt). Four of the five states that previously constituted the German Democratic Republic (East Germany) had above-average figures for prevalence and mortality. CONCLUSION There are relevant differences among the German federal states in the lifetime prevalence of major cardiovascular disease, which are only partly accounted for by differences in age and sex distribution, socioeconomic status, and community size.
An open-source model and solution method to predict co-contraction in the finger

Abstract A novel open-source biomechanical model of the index finger with an electromyography (EMG)-constrained static optimization solution method are developed with the goal of improving co-contraction estimates and providing means to assess tendon tension distribution through the finger. The Intrinsic model has four degrees of freedom and seven muscles (with a 14 component extensor mechanism). A novel plugin developed for the OpenSim modelling software applied the EMG-constrained static optimization solution method. Ten participants performed static pressing in three finger postures and five dynamic free motion tasks. Index finger 3D kinematics, force (5, 15, 30 N), and EMG (4 extrinsic muscles and first dorsal interosseous) were used in the analysis. The Intrinsic model predicted co-contraction increased by 29% during static pressing over the existing model. Further, tendon tension distribution patterns and forces, known to be essential to produce finger action, were determined by the model across all postures. The Intrinsic model and custom solution method improved co-contraction estimates to facilitate force propagation through the finger. These tools improve our interpretation of loads in the finger to develop better rehabilitation and workplace injury risk reduction strategies.
Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions

Abstract When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so‐called trend‐damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent‐based model—the adaptive anchoring model (ADAM)—to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear‐regression time series model. Moreover, ADAM outperformed autoregressive‐integrated‐moving‐average (ARIMA) and exponential‐smoothing models, while neither of these models accounts for people's responses on the average estimation task.
How are necroptosis, immune dysfunction, and motoneuron death connected in amyotrophic lateral sclerosis?

1Institute of Criminal Science and Technology, Wenzhou Police Department, Wenzhou 325000, Zhejiang, China. 2West China College of Public Health, Sichuan University, Chengdu 610041, Sichuan, China. 3Department of Pathology, Loyola University Medical Center, Maywood, IL 60153, USA. 4Research and Development Service, Hines VA Hospital, Hines, IL 60141, USA. 5Department of Pathology, The University of Chicago Medicine, Chicago, IL 60637, USA.
Unexpected evolutionary benefit to phages imparted by bacterial CRISPR-Cas9

Phages show an elevated mutation rate and remarkably rapid evolution when attacked by the bacterial CRISPR/Cas system. Bacteria and bacteriophages arm themselves with various defensive and counterdefensive mechanisms to protect their own genome and degrade the other’s. CRISPR (clustered regularly interspaced short palindromic repeat)–Cas (CRISPR-associated) is an adaptive bacterial defense mechanism that recognizes short stretches of invading phage genome and destroys it by nuclease attack. Unexpectedly, we discovered that the CRISPR-Cas system might also accelerate phage evolution. When Escherichia coli bacteria containing CRISPR-Cas9 were infected with phage T4, its cytosine hydroxymethylated and glucosylated genome was cleaved poorly by Cas9 nuclease, but the continuing CRISPR-Cas9 pressure led to rapid evolution of mutants that accumulated even by the time a single plaque was formed. The mutation frequencies are, remarkably, approximately six orders of magnitude higher than the spontaneous mutation frequency in the absence of CRISPR pressure. Our findings lead to the hypothesis that the CRISPR-Cas might be a double-edged sword, providing survival advantages to both bacteria and phages, leading to their coevolution and abundance on Earth.
Native T1 and ECV of Noninfarcted Myocardium and Outcome in Patients With Coronary Artery Disease

BACKGROUND Coronary artery disease (CAD) remains the major cause of cardiac morbidity and mortality worldwide, despite the advances in treatment with coronary revascularization and modern antiremodeling therapy. Risk strati ﬁ cation in CAD patients is primarily based on left ventricular volumes, ejection fraction (LVEF), risk scores, and the presence and extent of late gadolinium enhancement (LGE). The prognostic role of T1 mapping in noninfarcted myocardium in CAD patients has not yet been determined. OBJECTIVES This study sought to examine prognostic signi ﬁ cance of native T1 mapping of noninfarcted myocardium in patients with CAD. METHODS A prospective, observational, multicenter longitudinal study of consecutive patients undergoing routine cardiac magnetic resonance imaging with T1 mapping and LGE. The primary endpoint was all-cause mortality. Major adverse cardiocerebrovascular events (MACCE) (cardiac mortality, nonfatal acute coronary syndrome, stroke, and appropriate device discharge) are also reported.
Adaptive testing for multiple traits in a proportional odds model with applications to detect SNP‐brain network associations

There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging genetic studies. Most of existing methods treat a single trait or multiple traits as response while treating an SNP as a predictor coded under an additive inheritance mode. In this paper, we follow an earlier approach in treating an SNP as an ordinal response while treating traits as predictors in a proportional odds model (POM). In this way, it is not only easier to handle mixed types of traits, e.g., some quantitative and some binary, but it is also potentially more robust to the commonly adopted additive inheritance mode. More importantly, we develop an adaptive test in a POM so that it can maintain high power across many possible situations. Compared to the existing methods treating multiple traits as responses, e.g., in a generalized estimating equation (GEE) approach, the proposed method can be applied to a high dimensional setting where the number of phenotypes (p) can be larger than the sample size (n), in addition to a usual small P setting. The promising performance of the proposed method was demonstrated with applications to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, in which either structural MRI driven phenotypes or resting‐state functional MRI (rs‐fMRI) derived brain functional connectivity measures were used as phenotypes. The applications led to the identification of several top SNPs of biological interest. Furthermore, simulation studies showed competitive performance of the new method, especially for p>n .