Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusion at the surface of topological insulators

We consider the dc transport properties of topological insulator surface states in the presence of uncorrelated point-like disorder, both in the classical and quantum regimes. The dc conductivity of those two-dimensional surface states depends strongly on the amplitude of the hexagonal warping of their Fermi surface. A perturbative analysis of the warping is shown to fail to describe the transport in Bi2Se3 over a broad range of experimentally available Fermi energies, and in Bi2Te3 for the higher Fermi energies. Hence we develop a fully non-perturbative description of these effects. In particular, we find that the dependence of the warping amplitude on the Fermi energy manifests itself in a strong dependence of the diffusion constant on this Fermi energy, leading to several important experimental consequences. Moreover, the combination of a strong warping with an in-plane Zeeman effect leads to an attenuation of conductance fluctuations in contrast to the situation of unwarped Dirac surface states.
Dissecting water binding sites at protein–protein interfaces: a lesson from the atomic structures in the Protein Data Bank

We dissect the protein–protein interfaces into water preservation (WP), water hydration (WH) and water dehydration (WD) sites by comparing the water-mediated hydrogen bonds (H-bond) in the bound and unbound states of the interacting subunits. Upon subunit complexation, if a H-bond between an interface water and a protein polar group is retained, we assign it as WP site; if it is lost, we assign it as WD site and if a new H-bond is created, we assign it as WH site. We find that the density of WD sites is highest followed by WH and WP sites except in antigen and (or) antibody complexes, where the density of WH sites is highest followed by WD and WP sites. Furthermore, we find that WP sites are the most conserved followed by WD and WH sites in all class of complexes except in antigen and (or) antibody complexes, where WD sites are the most conserved followed by WH and WP sites. A significant number of WP and WH sites are involved in water bridges that stabilize the subunit interactions. At WH sites, the residues involved in water bridges are significantly better conserved than the other residues. However, no such difference is observed at WP sites. Interestingly, WD sites are generally replaced with direct H-bonds upon subunit complexation. Significantly, we observe many water-mediated H-bonds remain preserved in spite of large conformational changes upon subunit complexation. These findings have implications in predicting and engineering water binding sites at protein–protein interfaces.
Structural and Functional Basis of the Fidelity of Nucleotide Selection by Flavivirus RNA-Dependent RNA Polymerases

Viral RNA-dependent RNA polymerases (RdRps) play a central role not only in viral replication, but also in the genetic evolution of viral RNAs. After binding to an RNA template and selecting 5′-triphosphate ribonucleosides, viral RdRps synthesize an RNA copy according to Watson-Crick base-pairing rules. The copy process sometimes deviates from both the base-pairing rules specified by the template and the natural ribose selectivity and, thus, the process is error-prone due to the intrinsic (in)fidelity of viral RdRps. These enzymes share a number of conserved amino-acid sequence strings, called motifs A–G, which can be defined from a structural and functional point-of-view. A co-relation is gradually emerging between mutations in these motifs and viral genome evolution or observed mutation rates. Here, we review our current knowledge on these motifs and their role on the structural and mechanistic basis of the fidelity of nucleotide selection and RNA synthesis by Flavivirus RdRps.
A Proposed Approach for Joint Modeling of the Longitudinal and Time-To-Event Data in Heterogeneous Populations: An Application to HIV/AIDS's Disease

In recent years, the joint models have been widely used for modeling the longitudinal and time-to-event data simultaneously. In this study, we proposed an approach (PA) to study the longitudinal and survival outcomes simultaneously in heterogeneous populations. PA relaxes the assumption of conditional independence (CI). We also compared PA with joint latent class model (JLCM) and separate approach (SA) for various sample sizes (150, 300, and 600) and different association parameters (0, 0.2, and 0.5). The average bias of parameters estimation (AB-PE), average SE of parameters estimation (ASE-PE), and coverage probability of the 95% confidence interval (CP) among the three approaches were compared. In most cases, when the sample sizes increased, AB-PE and ASE-PE decreased for the three approaches, and CP got closer to the nominal level of 0.95. When there was a considerable association, PA in comparison with SA and JLCM performed better in the sense that PA had the smallest AB-PE and ASE-PE for the longitudinal submodel among the three approaches for the small and moderate sample sizes. Moreover, JLCM was desirable for the none-association and the large sample size. Finally, the evaluated approaches were applied on a real HIV/AIDS dataset for validation, and the results were compared.
The Clinical Pharmacokinetics of Itraconazole: An Overview

Summary: Itraconazole (R 51211) is the prototype of a class of triazole antifungals characterized by a high lipophilicity. This property determines to a large extent the pharmacokinetics of itraconazole and differentiates it from the hydrophilic triazole antifungal fluconazole.
Speech and speaker recognition for home automation: Preliminary results

In voice controlled multi-room smart homes ASR and speaker identification systems face distance speech conditions which have a significant impact on performance. Regarding voice command recognition, this paper presents an approach which selects dynamically the best channel and adapts models to the environmental conditions. The method has been tested on data recorded with 11 elderly and visually impaired participants in a real smart home. The voice command recognition error rate was 3.2% in off-line condition and of 13.2% in online condition. For speaker identification, the performances were below very speaker dependant. However, we show a high correlation between performance and training size. The main difficulty was the too short utterance duration in comparison to state of the art studies. Moreover, speaker identification performance depends on the size of the adapting corpus and then users must record enough data before using the system.
Predictive Modeling of Hospital Readmission Rates Using Electronic Medical Record-Wide Machine Learning: A Case-Study Using Mount Sinai Heart Failure Cohort

Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneumonia remains a significant challenge for improving the outcomes and decreasing the cost of healthcare delivery in the United States. Patient readmission rates are relatively high for conditions like heart failure (HF) despite the implementation of high-quality healthcare delivery operation guidelines created by regulatory authorities. Multiple predictive models are currently available to evaluate potential 30-day readmission rates of patients. Most of these models are hypothesis driven and repetitively assess the predictive abilities of the same set of biomarkers as predictive features. In this manuscript, we discuss our attempt to develop a data-driven, electronic-medical record-wide (EMR-wide) feature selection approach and subsequent machine learning to predict readmission probabilities. We have assessed a large repertoire of variables from electronic medical records of heart failure patients in a single center. The cohort included 1,068 patients with 178 patients were readmitted within a 30-day interval (16.66% readmission rate). A total of 4,205 variables were extracted from EMR including diagnosis codes (n=1,763), medications (n=1,028), laboratory measurements (n=846), surgical procedures (n=564) and vital signs (n=4). We designed a multistep modeling strategy using the Naïve Bayes algorithm. In the first step, we created individual models to classify the cases (readmitted) and controls (non-readmitted). In the second step, features contributing to predictive risk from independent models were combined into a composite model using a correlation-based feature selection (CFS) method. All models were trained and tested using a 5-fold cross-validation method, with 70% of the cohort used for training and the remaining 30% for testing. Compared to existing predictive models for HF readmission rates (AUCs in the range of 0.6-0.7), results from our EMR-wide predictive model (AUC=0.78; Accuracy=83.19%) and phenome-wide feature selection strategies are encouraging and reveal the utility of such datadriven machine learning. Fine tuning of the model, replication using multi-center cohorts and prospective clinical trial to evaluate the clinical utility would help the adoption of the model as a clinical decision system for evaluating readmission status.
How Can the Complications of Central Vein Catheters Be Reduced?

For many end-stage renal disease (ESRD) patients, vascular access for hemodialysis (HD) is a recurring challenge. As such, current guidelines strongly recommend that all patients start HD with either an arteriovenous fistula (AVF) or arteriovenous graft (AVG), based primarily on observational evidence that patients starting HD with an AVF have superior outcomes to patients starting HD with AVG, who in turn have superior outcomes to patients that start with tunneled dialysis catheters (TDC) (1). Despite this, over 80% of patients in the United States start HD with a TDC (2). Transitioning TDC patients to an arteriovenous (AV) access, either an AVF or AVG, can be a time consuming and difficult process (3). Thus, before a patient is brought to the operative suite for AV access creation, it is important for care providers to understand how patient preferences impact the surgical decision-making process as patients consider their HD access options.
Molecular Pathology of Lung Cancer Cytology Specimens: A Concise Review.

CONTEXT - There has been a paradigm shift in the understanding of molecular pathogenesis of lung cancer. A number of oncogenic drivers have been identified in non-small cell lung carcinoma, such as the epidermal growth factor receptor ( EGFR) mutation and anaplastic lymphoma kinase ( ALK) gene rearrangement. Because of the clinical presentation at an advanced stage of disease in non-small cell lung carcinoma patients, the use of minimally invasive techniques is preferred to obtain a tumor sample for diagnosis. These techniques include image-guided biopsies and fine-needle aspirations, and frequently the cytology specimen may be the only tissue sample available for the diagnosis and molecular testing for these patients. OBJECTIVE - To review the current literature and evaluate the role of cytology specimens in lung cancer mutation testing. We reviewed the types of specimens received in the laboratory, specimen processing, the effect of preanalytic factors on downstream molecular studies, and the commonly used molecular techniques for biomarker testing in lung cancer. DATA SOURCES - PubMed and Google search engines were used to review the published literature on the topic. CONCLUSIONS - Mutation testing is feasible on a variety of cytologic specimen types and preparations. However, a thorough understanding of the cytology workflow for the processing of samples and appropriate background knowledge of the molecular tests are necessary for triaging, and optimum use of these specimens is necessary to guide patient management.
Detection of tuberculosis by automatic cough sound analysis

Objective: Globally, tuberculosis (TB) remains one of the most deadly diseases. Although several effective diagnosis methods exist, in lower income countries clinics may not be in a position to afford expensive equipment and employ the trained experts needed to interpret results. In these situations, symptoms including cough are commonly used to identify patients for testing. However, self-reported cough has suboptimal sensitivity and specificity, which may be improved by digital detection. Approach: This study investigates a simple and easily applied method for TB screening based on the automatic analysis of coughing sounds. A database of cough audio recordings was collected and used to develop statistical classifiers. Main results: These classifiers use short-term spectral information to automatically distinguish between the coughs of TB positive patients and healthy controls with an accuracy of 78% and an AUC of 0.95. When a set of five clinical measurements is available in addition to the audio, this accuracy improves to 82%. By choosing an appropriate decision threshold, the system can achieve a sensitivity of 95% at a specificity of approximately 72%. The experiments suggest that the classifiers are using some spectral information that is not perceivable by the human auditory system, and that certain frequencies are more useful for classification than others. Significance: We conclude that automatic classification of coughing sounds may represent a viable low-cost and low-complexity screening method for TB.
Sentiment Analysis for the Social Media: A Case Study for Turkish General Elections

The ideas expressed in social media are not always compliant with natural language rules, and the mood and emotion indicators are mostly highlighted by emoticons and emotion specific keywords. There are language independent emotion keywords (e.g. love, hate, good, bad), besides every language has its own particular emotion specific keywords. These keywords can be used for polarity analysis for a particular sentence. In this study, we first created a Turkish dictionary containing emotion specific keywords. Then, we used this dictionary to detect the polarity of tweets that are collected by querying political keywords right before the Turkish general election in 2015. The tweets were collected based on their relatedness with three main categories: the political leaders, ideologies, and political parties. The polarity of these tweets are analyzed in comparison with the election results.
Age Differences in Deactivation: A Link to Cognitive Control?

The network of regions shown by functional imaging studies to be deactivated by experimental tasks relative to nominally more passive baselines (task < baseline) may reflect processes engaged during the resting state or default mode. Deactivation may result when attention and resources are diverted from default-mode processes toward task processes. Aging is associated with altered patterns of deactivation which may be related to declining resources, difficulties with resource allocation, or both. These possibilities predict that greater task demand, which increases deactivation levels in younger adults, should exacerbate age-related declines in allocating resources away from the default mode. The present study investigated the magnitude and temporal properties of deactivations in young and older adults during tasks that varied in their demand for cognitive control. Two versions of a verb generation task that varied in their demand for selection among competing alternatives were compared to word reading and a fixation baseline condition. Consistent with our hypothesis, greater deactivations were found with increasing demand. Young and older adults showed equivalent deactivations in the minimal selection condition. By contrast, age differences in both the magnitude and time course of deactivation increased with selection demand: Compared to young adults', older adults' deactivation response showed less sensitivity to demand. Demand-related changes in deactivation magnitude correlated with performance changes, suggesting that individual and group differences in deactivation have functional significance.
A Meta-Analysis for the Efficacy of Hypnotherapy in Alleviating PTSD Symptoms

Abstract A systematic review and meta-analysis of the efficacy of hypnotherapy in the treatment of PTSD used literature searches to obtain 47 articles. However, only 6 were experiments testing the efficacy of hypnosis-based treatments. A fixed-effects meta-analysis was applied to postintervention assessment results and 4-week follow-ups. A large effect in favor of hypnosis-based (especially manualized abreactive hypnosis) treatment was found for the studies that reported the posttest results (d = 1.17). The temporal stability of the effect remains strong, as reflected by the 4-week follow-up assessments (d = 1.58) and also by long-term evaluations (e.g., 12 months). Hypnosis appears to be effective in alleviating PTSD symptoms.
Immune-related adverse events for anti-PD-1 and anti-PD-L1 drugs: systematic review and meta-analysis

Abstract Objective To evaluate rates of serious organ specific immune-related adverse events, general adverse events related to immune activation, and adverse events consistent with musculoskeletal problems for anti-programmed cell death 1 (PD-1) drugs overall and compared with control treatments. Design Systematic review and meta-analysis. Data sources Medline, Embase, Cochrane Library, Web of Science, and Scopus searched to 16 March 2017 and combined with data from ClinicalTrials.gov. Study selection Eligible studies included primary clinical trial data on patients with cancer with recurrent or metastatic disease. Data extraction Three independent investigators extracted data on adverse events from ClinicalTrials.gov and the published studies. Risk of bias was assessed using the Cochrane tool by three independent investigators. Results 13 relevant studies were included; adverse event data were available on ClinicalTrials.gov for eight. Studies compared nivolumab (n=6), pembrolizumab (5), or atezolizumab (2) with chemotherapy (11), targeted drugs (1), or both (1). Serious organ specific immune-related adverse events were rare, but compared with standard treatment, rates of hypothyroidism (odds ratio 7.56, 95% confidence interval 4.53 to 12.61), pneumonitis (5.37, 2.73 to 10.56), colitis (2.88, 1.30 to 6.37), and hypophysitis (3.38, 1.02 to 11.08) were increased with anti-PD-1 drugs. Of the general adverse events related to immune activation, only the rate of rash (2.34, 2.73 to 10.56) increased. Incidence of fatigue (32%) and diarrhea (19%) were high but similar to control. Reporting of adverse events consistent with musculoskeletal problems was inconsistent; rates varied but were over 20% in some studies for arthraligia and back pain. Conclusions Organ specific immune-related adverse events are uncommon with anti-PD-1 drugs but the risk is increased compared with control treatments. General adverse events related to immune activation are largely similar. Adverse events consistent with musculoskeletal problems are inconsistently reported but adverse events may be common.
Pvclust: an R package for assessing the uncertainty in hierarchical clustering

SUMMARY Pvclust is an add-on package for a statistical software R to assess the uncertainty in hierarchical cluster analysis. Pvclust can be used easily for general statistical problems, such as DNA microarray analysis, to perform the bootstrap analysis of clustering, which has been popular in phylogenetic analysis. Pvclust calculates probability values (p-values) for each cluster using bootstrap resampling techniques. Two types of p-values are available: approximately unbiased (AU) p-value and bootstrap probability (BP) value. Multiscale bootstrap resampling is used for the calculation of AU p-value, which has superiority in bias over BP value calculated by the ordinary bootstrap resampling. In addition the computation time can be enormously decreased with parallel computing option.
3D surface imaging for guidance in breast cancer radiotherapy: organs at risk

Purpose: To evaluate the variability in heart position in deep-inspiration breath-hold (DIBH) radiotherapy for breast cancer when 3D surface imaging would be used for monitoring the depth of the breath hold during treatment. Materials and Methods: Ten patients who received DIBH radiotherapy after breast-conserving surgery (BCS) were included. Retrospectively, heart-based registrations were performed for cone-beam computed tomography (CBCT) to planning CT and breast surface registrations were performed for a 3D surface (two different regions of interest [ROIs]), captured concurrently with CBCT, to planning CT. The resulting setup errors were compared with linear regression analysis and receiver operating characteristic (ROC) analysis was performed to investigate the prediction quality of 3D surface imaging for 3D heart displacement. Further, the residual setup errors (systematic [Σ] and random [σ]) of the heart were estimated relative to the surface registrations. Results: When surface imaging [ROIleft-side;ROIboth-sides] would be used for monitoring, the residual errors of the heart position are in left-right: Σ=[0.36;0.12], σ=[0.16;0.14]; cranio-caudal: Σ=[0.54;0.54], σ=[0.28;0.31]; and in anteriorposterior: Σ=[0.18;0.14], σ=[0.20;0.19] cm. Correlations between setup errors were: R2 = [0.23;0.73], [0.67;0.65], [0.65;0.73] in left-right, cranio-caudal, and anterior-posterior direction, respectively. ROC analysis resulted in an area under the ROC curve of [0.82;0.78]. Conclusion: The use of ROIboth-sides provided promising results. However, considerable variability in the heart position, particularly in CC direction, is observed when 3D surface imaging would be used for guidance in DIBH radiotherapy after BCS. Planning organ at risk volume margins should be used to take into account the heart-position variability.
Adaptive Value of Phenological Traits in Stressful Environments: Predictions Based on Seed Production and Laboratory Natural Selection

Phenological traits often show variation within and among natural populations of annual plants. Nevertheless, the adaptive value of post-anthesis traits is seldom tested. In this study, we estimated the adaptive values of pre- and post-anthesis traits in two stressful environments (water stress and interspecific competition), using the selfing annual species Arabidopsis thaliana. By estimating seed production and by performing laboratory natural selection (LNS), we assessed the strength and nature (directional, disruptive and stabilizing) of selection acting on phenological traits in A. thaliana under the two tested stress conditions, each with four intensities. Both the type of stress and its intensity affected the strength and nature of selection, as did genetic constraints among phenological traits. Under water stress, both experimental approaches demonstrated directional selection for a shorter life cycle, although bolting time imposes a genetic constraint on the length of the interval between bolting and anthesis. Under interspecific competition, results from the two experimental approaches showed discrepancies. Estimation of seed production predicted directional selection toward early pre-anthesis traits and long post-anthesis periods. In contrast, the LNS approach suggested neutrality for all phenological traits. This study opens questions on adaptation in complex natural environment where many selective pressures act simultaneously.