Miracle-dz/UniFAR-FTUs huggingface dataset:
Serum neurofilament light in familial Alzheimer disease

Objectives: To investigate whether serum neurofilament light (NfL) concentration is increased in familial Alzheimer disease (FAD), both pre and post symptom onset, and whether it is associated with markers of disease stage and severity. Methods: We recruited 48 individuals from families with PSEN1 or APP mutations to a cross-sectional study: 18 had symptomatic Alzheimer disease (AD) and 30 were asymptomatic but at 50% risk of carrying a mutation. Serum NfL was measured using an ultrasensitive immunoassay on the single molecule array (Simoa) platform. Cognitive testing and MRI were performed; 33 participants had serial MRI, allowing calculation of atrophy rates. Genetic testing established mutation status. A generalized least squares regression model was used to compare serum NfL among symptomatic mutation carriers, presymptomatic carriers, and noncarriers, adjusting for age and sex. Spearman coefficients assessed associations between serum NfL and (1) estimated years to/from symptom onset (EYO), (2) cognitive measures, and (3) MRI measures of atrophy. Results: Nineteen of the asymptomatic participants were mutation carriers (mean EYO −9.6); 11 were noncarriers. Compared with noncarriers, serum NfL concentration was higher in both symptomatic (p < 0.0001) and presymptomatic mutation carriers (p = 0.007). Across all mutation carriers, serum NfL correlated with EYO (ρ = 0.81, p < 0.0001) and multiple cognitive and imaging measures, including Mini-Mental State Examination (ρ = −0.62, p = 0.0001), Clinical Dementia Rating Scale sum of boxes (ρ = 0.79, p < 0.0001), baseline brain volume (ρ = −0.62, p = 0.0002), and whole-brain atrophy rate (ρ = 0.53, p = 0.01). Conclusions: Serum NfL concentration is increased in FAD prior to symptom onset and correlates with measures of disease stage and severity. Serum NfL may thus be a feasible biomarker of early AD-related neurodegeneration.
Place categorization through object classification

This paper proposes a novel methodology for place categorization in mobile robots based on the presence of objects. In order to achieve such categorization, the robot is equipped with an RGB-D sensor. For a given time interval the sensor's measurements are combined with robot's localization data and reconstruct the 3D scene from the respective pointclouds. Afterwards, the method searches for dominant planes which are the most probable locations for finding objects. Given those planes, this work seeks and discriminates objects. The recognized objects, form a distribution which is given as input to a Naive Bayesian classifier in order to categorize the place.
Elucidating Pro-Inflammatory Cytokine Responses after Traumatic Brain Injury in a Human Stem Cell Model

Abstract Cytokine mediated inflammation likely plays an important role in secondary pathology after traumatic brain injury (TBI). The aim of this study was to elucidate secondary cytokine responses in an in vitro enriched (>80%) human stem cell-derived neuronal model. We exposed neuronal cultures to pre-determined and clinically relevant pathophysiological levels of tumor necrosis factor-α (TNF), interleukin-6 (IL-6) and interleukin-1β (IL-1β), shown to be present in the inflammatory aftermath of TBI. Data from this reductionist human model were then compared with our in vivo data. Human embryonic stem cell (hESC)-derived neurons were exposed to recombinant TNF (1–10,000 pg/mL), IL-1β (1–10,000 pg/mL), and IL-6 (0.1–1000 ng/mL). After 1, 24, and 72 h, culture supernatant was sampled and analyzed using a human cytokine/chemokine 42-plex Milliplex kit on the Luminex platform. The culture secretome revealed both a dose- and/or time-dependent release of cytokines. The IL-6 and TNF exposure each resulted in significantly increased levels of >10 cytokines over time, while IL-1β increased the level of C-X-C motif chemokine 10 (CXCL10/IP10) alone. Importantly, these patterns are consistent with our in vivo (human) TBI data, thus validating our human stem cell-derived neuronal platform as a clinically useful reductionist model. Our data cumulatively suggest that IL-6 and TNF have direct actions, while the action of IL-1β on human neurons likely occurs indirectly through inflammatory cells. The hESC-derived neurons provide a valuable platform to model cytokine mediated inflammation and can provide important insights into the mechanisms of neuroinflammation after TBI.
Host Antimicrobial Peptides: The Promise of New Treatment Strategies against Tuberculosis

Tuberculosis (TB) continues to be a devastating infectious disease and remerges as a global health emergency due to an alarming rise of antimicrobial resistance to its treatment. Despite of the serious effort that has been applied to develop effective antitubercular chemotherapies, the potential of antimicrobial peptides (AMPs) remains underexploited. A large amount of literature is now accessible on the AMP mechanisms of action against a diversity of pathogens; nevertheless, research on their activity on mycobacteria is still scarce. In particular, there is an urgent need to integrate all available interdisciplinary strategies to eradicate extensively drug-resistant Mycobacterium tuberculosis strains. In this context, we should not underestimate our endogenous antimicrobial proteins and peptides as ancient players of the human host defense system. We are confident that novel antibiotics based on human AMPs displaying a rapid and multifaceted mechanism, with reduced toxicity, should significantly contribute to reverse the tide of antimycobacterial drug resistance. In this review, we have provided an up to date perspective of the current research on AMPs to be applied in the fight against TB. A better understanding on the mechanisms of action of human endogenous peptides should ensure the basis for the best guided design of novel antitubercular chemotherapeutics.
Mining Consumers' Most Adaptive Products by Efficient Clustering Algorithm

Use clustering methods to discover the individual consumer's most adaptive products, which can support to make better decisions of marketing service. First, oriented from the consumer's transactional data that we will mine and targeted by finding some consumer's most adaptive products, we present a simple and efficient cluster algorithm to put the most similar data into the same group. Then we can find the mined consumer's most adaptive products from the cluster. Moreover, we propose a Boolean algorithm to improve the performance of the previous.
Testing causal effects in observational survival data using propensity score matching design

Time‐to‐event data are very common in observational studies. Unlike randomized experiments, observational studies suffer from both observed and unobserved confounding biases. To adjust for observed confounding in survival analysis, the commonly used methods are the Cox proportional hazards (PH) model, the weighted logrank test, and the inverse probability of treatment weighted Cox PH model. These methods do not rely on fully parametric models, but their practical performances are highly influenced by the validity of the PH assumption. Also, there are few methods addressing the hidden bias in causal survival analysis. We propose a strategy to test for survival function differences based on the matching design and explore sensitivity of the P‐values to assumptions about unmeasured confounding. Specifically, we apply the paired Prentice‐Wilcoxon (PPW) test or the modified PPW test to the propensity score matched data. Simulation studies show that the PPW‐type test has higher power in situations when the PH assumption fails. For potential hidden bias, we develop a sensitivity analysis based on the matched pairs to assess the robustness of our finding, following Rosenbaum's idea for nonsurvival data. For a real data illustration, we apply our method to an observational cohort of chronic liver disease patients from a Mayo Clinic study. The PPW test based on observed data initially shows evidence of a significant treatment effect. But this finding is not robust, as the sensitivity analysis reveals that the P‐value becomes nonsignificant if there exists an unmeasured confounder with a small impact.
Light Microscopy Digital Imaging

This unit presents an overview of digital imaging hardware used in light microscopy. CMOS, CCD, and EMCCDs are the primary sensors used. The strengths and weaknesses of each define the primary applications for these sensors. Sensor architecture and formats are also reviewed. Color camera design strategies and sensor window cleaning are also described in the unit. Curr. Protocol. Cytom. 46:2.3. 1‐2.3. 10. © 2008 by John Wiley & Sons, Inc.
Classification of Visit-to-Visit Blood Pressure Variability: A Machine Learning Approach for Data Clustering on Systolic Blood Pressure Intervention Trial (SPRINT)

Background: Blood pressure variability (BPV) is associated with the cardiovascular disease. However, there is no standard risk stratification method to evaluate BPV. Our study aims to cluster BPV into three levels, namely, low, medium and high levels, by a machine learning approach. Methods: The Systolic Blood Pressure Intervention Trial (SPRINT) dataset, which includes patients with hypertension or at risk of cardiovascular diseases, was obtained from a clinical data sharing platform. In the clinical trial, participants with systolic blood pressure (SBP) of at least 130 mmHg and an increased cardiovascular risk were randomized to receive intensive treatment (targeting SBP below 120 mmHg) or standard treatment (targeting SBP below 140 mmHg), and blood pressure (BP) were measured and recorded during the follow-up periods. Visit-to-visit BPV was measured by the deviation between the observed records and the personalized BP trends, and two-dimensional clustering on SBP and diastolic BP were applied. Different curve fitting techniques (linear regression and cubic regression) and clustering methods (K-means and Agglomerative Clustering) were attempted and compared with each other. Results: With 8,092 participants and a median follow-up of 3.26 years, linear regression was a simple and reliable method to capture the BP trend. K-means model showed stable data clustering results. Intensive treatment showed to be effective for participants with a high level of BPV. Conclusion: Machine learning can be used for data clustering on BPV.
Pleiotropic phenotypes caused by genetic ablation of the receiver module of the Agrobacterium tumefaciens VirA protein

The VirA protein of Agrobacterium tumefaciens is a transmembrane sensory kinase that phosphorylates the VirG response regulator in response to chemical signals released from plant wound sites. VirA contains both a two-component kinase module and, at its carboxyl terminus, a receiver module. We previously provided evidence that this receiver module inhibited the activity of the kinase module and that inhibition might be neutralized by phosphorylation. In this report, we provide additional evidence for this model by showing that overexpressing the receiver module in trans can restore low-level basal activity to a VirA mutant protein lacking the receiver module. We also show that ablation of the receiver module restores activity to the inactive VirA (delta324-413) mutant, which has a deletion within a region designated the linker module. This indicates that deletion of the linker module does not denature the kinase module, but rather locks the kinase into a phenotypically inactive conformation, and that this inactivity requires the receiver module. These data provide genetic evidence that the kinase and receiver modules of VirA attain their native conformations autonomously. The receiver module also restricts the variety of phenolic compounds that have stimulatory activity, since removal of this module causes otherwise nonstimulatory phenolic compounds such as 4-hydroxyacetophenone to stimulate vir gene expression.
Optimal antithrombotic treatment in patients with atrial fibrillation and coronary stents: an update

Purpose of review The optimal antithrombotic therapy in patients with atrial fibrillation undergoing percutaneous coronary intervention (PCI) is still debated. This review is an update of a previous review and aims to summarize new published data regarding the management of this group of atrial fibrillation patients. Recent findings Recent data report an underuse of oral anticoagulation in patients with atrial fibrillation undergoing PCI while indicated. However, tools for risk assessment and thus better guidance for decision-making are lacking, especially for elderly atrial fibrillation patients. New evidence suggests that the combination of oral anticoagulation and clopidogrel without aspirin may improve clinical outcomes in comparison with triple therapy; however, there is little data regarding the role of non-vitamin K oral anticoagulants and newer P2Y12 inhibitors in these regimens. Summary Despite accumulating data on the assessment of bleeding and thrombotic risk, the management of elderly atrial fibrillation patients, new treatment regimens, and the role of more potent antithrombotic agents, the optimal antithrombotic therapy for patients with atrial fibrillation after PCI is still unclear. In the meantime, careful assessment of both thrombotic and bleeding risk and individualized decision-making are paramount to ensure the best patient outcomes.
Is specialization an evolutionary dead end? Testing for differences in speciation, extinction and trait transition rates across diverse phylogenies of specialists and generalists

Specialization has often been claimed to be an evolutionary dead end, with specialist lineages having a reduced capacity to persist or diversify. In a phylogenetic comparative framework, an evolutionary dead end may be detectable from the phylogenetic distribution of specialists, if specialists rarely give rise to large, diverse clades. Previous phylogenetic studies of the influence of specialization on macroevolutionary processes have demonstrated a range of patterns, including examples where specialists have both higher and lower diversification rates than generalists, as well as examples where the rates of evolutionary transitions from generalists to specialists are higher, lower or equal to transitions from specialists to generalists. Here, we wish to ask whether these varied answers are due to the differences in macroevolutionary processes in different clades, or partly due to differences in methodology. We analysed ten phylogenies containing multiple independent origins of specialization and quantified the phylogenetic distribution of specialists by applying a common set of metrics to all datasets. We compared the tip branch lengths of specialists to generalists, the size of specialist clades arising from each evolutionary origin of a specialized trait and whether specialists tend to be clustered or scattered on phylogenies. For each of these measures, we compared the observed values to expectations under null models of trait evolution and expected outcomes under alternative macroevolutionary scenarios. We found that specialization is sometimes an evolutionary dead end: in two of the ten case studies (pollinator‐specific plants and host‐specific flies), specialization is associated with a reduced rate of diversification or trait persistence. However, in the majority of studies, we could not distinguish the observed phylogenetic distribution of specialists from null models in which specialization has no effect on diversification or trait persistence.
Acculturative stress as a moderator for international student drinking behaviors and alcohol use consequences

ABSTRACT Drinking behaviors and alcohol use consequences can have a major effect on well-being in college student populations. Little research has addressed how the unique acculturative stress experiences of international students may affect their alcohol use and consequences. This study examined acculturative stress as a moderator of the relationship between international student drinking behaviors and alcohol use consequences. Data were collected from 175 international students and analyzed using hierarchal regression analysis to assess the moderating effect of acculturative stress. Acculturative stress moderated the relationship between alcohol use and related consequences such that the relationship was stronger among those with higher levels of acculturative stress. Efforts to alleviate acculturative stress experiences of this population may help decrease alcohol use consequences.
Isolates of Lactobacillus plantarum and L. reuteri display greater antiproliferative and antipathogenic activity than other Lactobacillus isolates

Purpose. Lactic acid bacteria (LAB) have been associated with many beneficial effects in human digestive physiology. The aim of this study was to evaluate such effect, including attachment, antiproliferation and anti‐pathogenic/antibacterial/antimicrobial properties of LAB isolated from healthy humans. Methodology. Thirteen isolates, obtained from fecal samples of healthy individuals, were identified by phenotypic and molecular methods. Human colon adenocarcinoma cell line HT‐29 and the cell proliferation kit II (XTT) assay were used for examination of the Lactobacillus adherence and antiproliferative activity, respectively. In addition, the inhibitory effect of Lactobacillus isolates against pathogenic bacteria was examined. Results. Out of 13 Lactobacillus isolates, 5 (38 %) isolates were non‐adhesive, 4 (31 %) were adhesive and 4 (31 %) were strongly adhesive. Amongst the isolated lactobacilli, L. reuteri showed the highest degree of inhibitory effect against the attachment of the enteropathogens. The XTT assay showed that 3 different isolates had the strongest antiproliferative activity with the maximum effect observed by L. plantarum isolates. Conclusion. Our results described that different Lactobacillus species isolated from normal fecal samples had different degrees of antiproliferative and anti‐pathogenic/antibacterial/antimicrobial activities. However, no isolates showed all of the examined properties concurrently, suggestive that a combination of Lactobacillus species is needed for an active biological defense system.
A novel anthropomorphic flow phantom for the quantitative evaluation of prostate DCE-MRI acquisition techniques

A novel anthropomorphic flow phantom device has been developed, which can be used for quantitatively assessing the ability of magnetic resonance imaging (MRI) scanners to accurately measure signal/concentration time-intensity curves (CTCs) associated with dynamic contrast-enhanced (DCE) MRI. Modelling of the complex pharmacokinetics of contrast agents as they perfuse through the tumour capillary network has shown great promise for cancer diagnosis and therapy monitoring. However, clinical adoption has been hindered by methodological problems, resulting in a lack of consensus regarding the most appropriate acquisition and modelling methodology to use and a consequent wide discrepancy in published data. A heretofore overlooked source of such discrepancy may arise from measurement errors of tumour CTCs deriving from the imaging pulse sequence itself, while the effects on the fidelity of CTC measurement of using rapidly-accelerated sequences such as parallel imaging and compressed sensing remain unknown. The present work aimed to investigate these features by developing a test device in which ‘ground truth’ CTCs were generated and presented to the MRI scanner for measurement, thereby allowing for an assessment of the DCE-MRI protocol to accurately measure this curve shape. The device comprised a four-pump flow system wherein CTCs derived from prior patient prostate data were produced in measurement chambers placed within the imaged volume. The ground truth was determined as the mean of repeat measurements using an MRI-independent, custom-built optical imaging system. In DCE-MRI experiments, significant discrepancies between the ground truth and measured CTCs were found for both tumorous and healthy tissue-mimicking curve shapes. Pharmacokinetic modelling revealed errors in measured Ktrans, ve and kep values of up to 42%, 31%, and 50% respectively, following a simple variation of the parallel imaging factor and number of signal averages in the acquisition protocol. The device allows for the quantitative assessment and standardisation of DCE-MRI protocols (both existing and emerging).
Traumatic Stress Symptoms of Women Exposed to Different Forms of Childhood Victimization and Intimate Partner Violence

Interviews of women with (n = 193) and without (n = 170) recent exposure to intimate partner violence (IPV) were used to examine how IPV and past exposure to child abuse influence self-reports of posttraumatic stress disorder (PTSD) symptoms. The measurement of IPV included assessing psychological, physical, escalated physical, and sexual abuse. Women’s retrospective accounts of childhood victimization included reports of physical abuse, sexual abuse, and witnessing domestic violence growing up. Each form of adult IPV showed an independent association with PTSD symptoms, as did each form of childhood victimization. In regression models including child and adult abuse together, adult IPV and childhood sexual abuse were related to PTSD symptoms, and adult IPV mediated the association between childhood physical abuse and adult PTSD. Tests of the interactions between childhood and adulthood victimization on PTSD symptoms were not significant. Findings are discussed within the context of a life-course perspective of trauma.
Distinct quantitative computed tomography emphysema patterns are associated with physiology and function in smokers.

RATIONALE Emphysema occurs in distinct pathologic patterns, but little is known about the epidemiologic associations of these patterns. Standard quantitative measures of emphysema from computed tomography (CT) do not distinguish between distinct patterns of parenchymal destruction. OBJECTIVES To study the epidemiologic associations of distinct emphysema patterns with measures of lung-related physiology, function, and health care use in smokers. METHODS Using a local histogram-based assessment of lung density, we quantified distinct patterns of low attenuation in 9,313 smokers in the COPDGene Study. To determine if such patterns provide novel insights into chronic obstructive pulmonary disease epidemiology, we tested for their association with measures of physiology, function, and health care use. MEASUREMENTS AND MAIN RESULTS Compared with percentage of low-attenuation area less than -950 Hounsfield units (%LAA-950), local histogram-based measures of distinct CT low-attenuation patterns are more predictive of measures of lung function, dyspnea, quality of life, and health care use. These patterns are strongly associated with a wide array of measures of respiratory physiology and function, and most of these associations remain highly significant (P < 0.005) after adjusting for %LAA-950. In smokers without evidence of chronic obstructive pulmonary disease, the mild centrilobular disease pattern is associated with lower FEV1 and worse functional status (P < 0.005). CONCLUSIONS Measures of distinct CT emphysema patterns provide novel information about the relationship between emphysema and key measures of physiology, physical function, and health care use. Measures of mild emphysema in smokers with preserved lung function can be extracted from CT scans and are significantly associated with functional measures.