Miracle-dz/UniFAR-FTUs huggingface dataset:
TRFBA: an algorithm to integrate genome‐scale metabolic and transcriptional regulatory networks with incorporation of expression data

Motivation: Integration of different biological networks and data‐types has been a major challenge in systems biology. The present study introduces the transcriptional regulated flux balance analysis (TRFBA) algorithm that integrates transcriptional regulatory and metabolic models using a set of expression data for various perturbations. Results: TRFBA considers the expression levels of genes as a new continuous variable and introduces two new linear constraints. The first constraint limits the rate of reaction(s) supported by a metabolic gene using a constant parameter (C) that converts the expression levels to the upper bounds of the reactions. Considering the concept of constraint‐based modeling, the second set of constraints correlates the expression level of each target gene with that of its regulating genes. A set of constraints and binary variables was also added to prevent the second set of constraints from overlapping. TRFBA was implemented on Escherichia coli and Saccharomyces cerevisiae models to estimate growth rates under various environmental and genetic perturbations. The error sensitivity to the algorithm parameter was evaluated to find the best value of C. The results indicate a significant improvement in the quantitative prediction of growth in comparison with previously presented algorithms. The robustness of the algorithm to change in the expression data and the regulatory network was tested to evaluate the effect of noisy and incomplete data. Furthermore, the use of added constraints for perturbations without their gene expression profile demonstrates that these constraints can be applied to improve the growth prediction of FBA. Availability and Implementation: TRFBA is implemented in Matlab software and requires COBRA toolbox. Source code is freely available at http://sbme.modares.ac.ir. Contact: motamedian@modares.ac.ir Supplementary information: Supplementary data are available at Bioinformatics online.
Using eHealth Technologies: Interests, Preferences, and Concerns of Older Adults

Background The Internet and eHealth technologies represent new opportunities for managing health. Age, sex, socioeconomic status, and current technology use are some of the known factors that influence individuals’ uptake of eHealth; however, relatively little is known about facilitators and barriers to eHealth uptake specific to older adults, particularly as they relate to their experiences in accessing health care. Objective The aim of our study was to explore the interests, preferences, and concerns of older adults in using the Internet and eHealth technologies for managing their health in relation to their experiences with the current health care system. Methods Two focus groups (n=15) were conducted with adults aged 50+ years. Pragmatic thematic analysis using an inductive approach was conducted to identify the interests, preferences, and concerns of using the Internet and eHealth technologies. Results Five themes emerged that include (1) Difficulty in identifying credible and relevant sources of information on the Web; (2) Ownership, access, and responsibility for medical information; (3) Peer communication and support; (4) Opportunities to enhance health care interactions; and (5) Privacy concerns. These findings support the potential value older adults perceive in eHealth technologies, particularly in their ability to provide access to personal health information and facilitate communication between providers and peers living with similar conditions. However, in order to foster acceptance, these technologies will need to provide personal and general health information that is secure, readily accessible, and easily understood. Conclusions Older adults have diverse needs and preferences that, in part, are driven by their experiences and frustrations with the health care system. Results can help inform the design and implementation of technologies to address gaps in care and access to health information for older adults with chronic conditions who may benefit the most from this approach.
A review of current sleep screening applications for smartphones

Sleep disorders are a common problem and contribute to a wide range of healthcare issues. The societal and financial costs of sleep disorders are enormous. Sleep-related disorders are often diagnosed with an overnight sleep test called a polysomnogram, or sleep study involving the measurement of brain activity through the electroencephalogram. Other parameters monitored include oxygen saturation, respiratory effort, cardiac activity (through the electrocardiogram), as well as video recording, sound and movement activity. Monitoring can be costly and removes the patients from their normal sleeping environment, preventing repeated unbiased studies. The recent increase in adoption of smartphones, with high quality on-board sensors has led to the proliferation of many sleep screening applications running on the phone. However, with the exception of simple questionnaires, no existing sleep-related application available for smartphones is based on scientific evidence. This paper reviews the existing smartphone applications landscape used in the field of sleep disorders and proposes possible advances to improve screening approaches.
Classification of rainfall radar images using the scattering transform

The main objective of this paper is to classify rainfall radar images by using the scattering transform, which gives us a translation invariant representation of the images and preserves high-frequency information useful to encode important morphological aspects of the meteorological phenomena under study. To demonstrate the usefulness of the approach, a classification framework is considered, where the images are to be classified into 4 morphological classes: light rain, shower, unorganised storm and organised storm. Experiments show that the benefits of the scattering are threefold: 1) it provides complementary information with respect to more traditional features computed over the distribution of the rainfall intensities, 2) it provides strong invariance to deformations, 3) second order coefficients of the scattering transform nicely encodes spatial distribution of rain intensity.
Incorporation of the number of positive lymph nodes leads to better prognostic discrimination of node-positive early stage cervical cancer

To determine the prognostic value of the number of positive lymph nodes (LNs) in cervical cancer and further stratify patients with positive LNs into multiple risk groups based on analysis of Surveillance Epidemiology and End Results (SEER) program. Patients with cervical cancer who undergo hysterectomy and had pathologically-confirmed positive LNs after lymphadenectomy were identified using the SEER database (1988-2012). Kaplan–Meier survival methods and Cox proportional hazards regression were performed. We included 2,222 patients with the median number of removed LNs and positive LNs was 22 and 2, respectively. Multivariable Cox analysis showed patients with > 2 positive LNs had poorer cause-specific survival (CSS) (hazard ratio [HR] 1.631, 95% confidence interval [CI] 1.382–1.926, P < 0.001) and overall survival (OS) (HR 1.570, 95% CI 1.346–1.832, P < 0.001) than patients with 1–2 positive LNs. Five-year CSS and OS were 78.9% vs. 65.5% (P < 0.001) and 76.7% vs. 62.7% (P < 0.001) for 1–2 positive LNs and > 2 positive LNs, respectively. The number of positive LNs had prognostic value in cervical squamous cell carcinoma or adenosquamous carcinoma, but not in cervical adenocarcinoma. The number of positive LNs is an independent risk factor for CSS and OS in cervical cancer. This new category might be helpful in better prognostic discrimination of node-positive early stage cervical cancer after hysterectomy.
TRAFIC: fiber tract classification using deep learning

We present TRAFIC, a fully automated tool for the labeling and classification of brain fiber tracts. TRAFIC classifies new fibers using a neural network trained using shape features computed from previously traced and manually corrected fiber tracts. It is independent from a DTI Atlas as it is applied to already traced fibers. This work is motivated by medical applications where the process of extracting fibers from a DTI atlas, or classifying fibers manually is time consuming and requires knowledge about brain anatomy. With this new approach we were able to classify traced fiber tracts obtaining encouraging results. In this report we will present in detail the methods used and the results achieved with our approach.
GeneSeqToFamily: a Galaxy workflow to find gene families based on the Ensembl Compara GeneTrees pipeline

Background Gene duplication is a major factor contributing to evolutionary novelty, and the contraction or expansion of gene families has often been associated with morphological, physiological and environmental adaptations. The study of homologous genes helps us to understand the evolution of gene families. It plays a vital role in finding ancestral gene duplication events as well as identifying genes that have diverged from a common ancestor under positive selection. There are various tools available, such as MSOAR, OrthoMCL and HomoloGene, to identify gene families and visualise syntenic information between species, providing an overview of syntenic regions evolution at the family level. Unfortunately, none of them provide information about structural changes within genes, such as the conservation of ancestral exon boundaries amongst multiple genomes. The Ensembl GeneTrees computational pipeline generates gene trees based on coding sequences and provides details about exon conservation, and is used in the Ensembl Compara project to discover gene families. Findings A certain amount of expertise is required to configure and run the Ensembl Compara GeneTrees pipeline via command line. Therefore, we have converted the command line Ensembl Compara GeneTrees pipeline into a Galaxy workflow, called GeneSeqToFamily, and provided additional functionality. This workflow uses existing tools from the Galaxy ToolShed, as well as providing additional wrappers and tools that are required to run the workflow. Conclusions GeneSeqToFamily represents the Ensembl Compara pipeline as a set of interconnected Galaxy tools, so they can be run interactively within the Galaxy’s user-friendly workflow environment while still providing the flexibility to tailor the analysis by changing configurations and tools if necessary. Additional tools allow users to subsequently visualise gene families, produced using the workflow, using the Aequatus.js interactive tool, which has been developed as part of the Aequatus software project.
PU.1 serves a critical role in the innate defense against Aspergillus fumigatus via dendritic cell-associated C-type lectin receptor-1 and toll-like receptors-2 and 4 in THP-1-derived macrophages

Aspergillus fumigatus (A. fumigatus) is one of the most common fungal pathogens of invasive pulmonary aspergillosis (IPA), which may be life threatening in immunocompromised individuals. The dendritic cell-associated C-type lectin receptor (Dectin-1), toll-like receptor (TLR)-2 and TLR-4 are major pattern recognition receptors in alveolar macrophages that recognize A. fumigatus components. The PU.1 transcription factor is known to be important for the transcriptional control of these three receptors in mature macrophages. The present study investigated whether alterations of PU.1 expression may affect the innate defense against A. fumigatus in the human monocyte THP-1 cell line. THP-1-derived macrophages were transduced with PU.1 adenoviral vectors and transfected with PU.1 small interfering RNA, and the mRNA and protein expression levels of Dectin-1, TLR-2 and TLR-4 were measured. In addition, the levels of tumor necrosis factor (TNF)-α and interleukin (IL)-1β were ascertained, and fungal phagocytosis and killing were assessed. The results demonstrated that overexpression of PU.1 by recombinant adenoviral vectors resulted in a significant upregulation of Dectin-1, TLR-2 and TLR-4 at the transcriptional and translational levels. In response to A. fumigatus stimulation, PU.1 overexpression increased TNF-α and IL-1β production. In addition, Dectin-1, TLR-2 and TLR-4 upregulation may have enhanced the phagocytosis and killing ability of THP-1-derived macrophages. As expected, silencing of PU.1 led to downregulation of Dectin-1, TLR-2, TLR-4 and the expression of pro-inflammatory cytokines, as well as decreased phagocytosis and the killing ability of THP1-derived macrophages. In conclusion, the results indicate that PU.1 may be a critical factor for the innate defense against A. fumigatus, and may therefore be a potential target for the prophylaxis and treatment of IPA.
VirtualFriendship : Hiding interactions on Online Social Networks Anonymous Submission

The enormous popularity of Online Social Networks (OSNs) dramatically changed the way people communicate and interact with each other. Unfortunately, the centralized control employed by OSN providers, such as Facebook, have negative impacts as it leads to privacy concerns. In fact, OSN providers can directly access a big amount of information about users and infer further information when using data mining techniques (e.g., about the on line interactions among two users). In this paper we propose VirtualFriendship, i.e., a collaborative solution that allows OSN users to browse each others’ “profile” and to exchange messages in the OSN, while the end-peers of the interactions remain anonymous with respect to the OSN provider. We demonstrate by a proof of knowledge implementation (VF-App) the feasibility of our solution. Furthermore, our analysis and thorough set of experiments also show that the overhead introduced by our solution is very limited, and we believe negligible from a user perspective.
Survey Email Scheduling and Monitoring in eRCTs (SESAMe): A Digital Tool to Improve Data Collection in Randomized Controlled Clinical Trials

Background Electronic questionnaires can ease data collection in randomized controlled trials (RCTs) in clinical practice. We found no existing software that could automate the sending of emails to participants enrolled into an RCT at different study participant inclusion time points. Objective Our aim was to develop suitable software to facilitate data collection in an ongoing multicenter RCT of low back pain (the Acuback study). For the Acuback study, we determined that we would need to send a total of 5130 emails to 270 patients recruited at different centers and at 19 different time points. Methods The first version of the software was tested in a pilot study in November 2013 but was unable to deliver multiuser or Web-based access. We resolved these shortcomings in the next version, which we tested on the Web in February 2014. Our new version was able to schedule and send the required emails in the full-scale Acuback trial that started in March 2014. The system architecture evolved through an iterative, inductive process between the project study leader and the software programmer. The program was tested and updated when errors occurred. To evaluate the development of the software, we used a logbook, a research assistant dialogue, and Acuback trial participant queries. Results We have developed a Web-based app, Survey Email Scheduling and Monitoring in eRCTs (SESAMe), that monitors responses in electronic surveys and sends reminders by emails or text messages (short message service, SMS) to participants. The overall response rate for the 19 surveys in the Acuback study increased from 76.4% (655/857) before we introduced reminders to 93.11% (1149/1234) after the new function (P<.001). Further development will aim at securing encryption and data storage. Conclusions The SESAMe software facilitates consecutive patient data collection in RCTs and can be used to increase response rates and quality of research, both in general practice and in other clinical trial settings.
Evaluation of cefazolin antimicrobial prophylaxis during cardiac surgery with cardiopulmonary bypass

Objectives Although clinical practice guidelines recommend standard cefazolin antimicrobial prophylaxis (AP) dosing for cardiac surgery, limited data exist as to whether adequate concentrations are achieved in this patient population. The goal of our study was to characterize intraoperative cefazolin concentrations particularly at wound closure with regards to maintaining target cefazolin closure concentrations ≥40 mg/L. Methods Adults undergoing cardiac surgery with cardiopulmonary bypass (CPB) and receiving cefazolin AP according to protocol were studied. Blood samples were collected after the preoperative cefazolin dose, prior to intraoperative cefazolin doses and at wound closure. Intraoperative trough and closure concentrations were characterized and evaluated against a target threshold of ≥ 40 mg/L (≥8 mg/L unbound, assuming 80% protein binding). Results Fifty-five subjects (64.9 ± 10.4 years, 89.7 ± 16.5 kg, CLCR >50 mL/min/72 kg) completed the study. Total cefazolin concentrations were <40 mg/L in 40% (12 of 30) of intraoperative trough samples and 9.8% (5 of 51) of closure samples. Below-target concentrations at some time during surgery were documented in 30.9% (17 of 55) of subjects. In multivariate analyses, lower body weight (P = 0.027) and shorter duration of surgery (P = 0.045) were significant predictors of closure concentrations <40 mg/L. A total cefazolin exposure (preoperative and intraoperative doses) of ≥ 7.6 mg/kgdosing weight for every hour of surgery (intermittent dosing) was required to achieve target closure concentrations. Conclusions The standard cefazolin AP regimen was not reliable in maintaining target closure concentrations ≥40 mg/L in patients with normal renal function undergoing elective cardiac surgery with CPB. The findings supported a cefazolin AP regimen consisting of at least 2 g preoperatively and every 3 h during surgery.
Association of BRM promoter polymorphisms and esophageal adenocarcinoma outcome

Purpose Brahma (BRM) is a critical catalytic subunit of the SWI/SNF chromatin remodeling complex; expression of BRM is commonly lost in various cancer types. BRM promoter polymorphisms (BRM-741; BRM-1321) are associated with loss of BRM expression, and with cancer risk/survival. We evaluated these two polymorphisms in the overall survival (OS) of esophageal adenocarcinoma (EAC) patients. Results Of 270 patients, 37% were stage IV. Minor allele frequencies were 47−49%; 15% were double-homozygotes. When compared to the wild-type genotype, the homozygous variant of BRM-741 carried an adjusted OS hazard ratio (aHR) of 1.64 (95% CI:1.1−2.4); for BRM-1321, the aHR was 2.09 (95% CI:1.4−3.0). Compared to the double wild-type, carrying homozygous variants of both promoter polymorphisms (double-homozygote) yielded an aHR of 2.21 (95% CI:1.4−3.6). Directions/magnitudes of associations were similar in subsets by age, gender, smoking status, use of platinum agents, and disease stage, and for progression-free survival. Materials and Methods In a cohort of EAC patients of all stages (84% male; median age of 64 years), two BRM polymorphisms were genotyped. Cox proportional hazards models, adjusted for known prognostic variables, estimated the association of polymorphisms with OS. Conclusions BRM polymorphisms were associated with OS in EAC in this study. Validation studies are warranted.
IndeCut evaluates performance of network motif discovery algorithms

Genomic networks represent a complex map of molecular interactions which are descriptive of the biological processes occurring in living cells. Identifying the small over-represented circuitry patterns in these networks helps generate hypotheses about the functional basis of such complex processes. Network motif discovery is a systematic way of achieving this goal. However, a reliable network motif discovery outcome requires generating random background networks which are the result of a uniform and independent graph sampling method. To date, there has been no sound practical method to numerically evaluate whether any network motif discovery algorithm performs as intended—thus it was not possible to assess the validity of resulting network motifs. In this work, we present IndeCut, the first and only method that allows characterization of network motif finding algorithm performance on any network of interest. We demonstrate that it is critical to use IndeCut prior to running any network motif finder for two reasons. First, IndeCut estimates the minimally required number of samples that each network motif discovery tool needs in order to produce an outcome that is both reproducible and accurate. Second, IndeCut allows users to choose the most accurate network motif discovery tool for their network of interest among many available options. IndeCut is an open source software package and is available at https://github.com/megrawlab/IndeCut.
Night-to-Night Sleep Variability in Older Adults With Chronic Insomnia: Mediators and Moderators in a Randomized Controlled Trial of Brief Behavioral Therapy (BBT-I).

STUDY OBJECTIVES Sleep variability is a clinically significant variable in understanding and treating insomnia in older adults. The current study examined changes in sleep variability in the course of brief behavioral therapy for insomnia (BBT-I) in older adults who had chronic insomnia. Additionally, the current study examined the mediating mechanisms underlying reductions of sleep variability and the moderating effects of baseline sleep variability on treatment responsiveness. METHODS Sixty-two elderly participants were randomly assigned to either BBT-I or self-monitoring and attention control (SMAC). Sleep was assessed by sleep diaries and actigraphy from baseline to posttreatment and at 3-month follow-up. Mixed models were used to examine changes in sleep variability (within-person standard deviations of weekly sleep parameters) and the hypothesized mediation and moderation effects. RESULTS Variabilities in sleep diary-assessed sleep onset latency (SOL) and actigraphy-assessed total sleep time (TST) significantly decreased in BBT-I compared to SMAC (Pseudo R2 = .12, .27; P = .018, .008). These effects were mediated by reductions in bedtime and wake time variability and time in bed. Significant time × group × baseline sleep variability interactions on sleep outcomes indicated that participants who had higher baseline sleep variability were more responsive to BBT-I; their actigraphy-assessed TST, SOL, and sleep efficiency improved to a greater degree (Pseudo R2 = .15 to .66; P < .001 to .044). CONCLUSIONS BBT-I is effective in reducing sleep variability in older adults who have chronic insomnia. Increased consistency in bedtime and wake time and decreased time in bed mediate reductions of sleep variability. Baseline sleep variability may serve as a marker of high treatment responsiveness to BBT-I. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov, Identifier: NCT02967185.
Bridging the Gap Between Software and Hardware Designers Using High-Level Synthesis

Modern Systems-on-Chip (SoC) architectures and CPU+FPGA computing platforms are moving towards heterogeneous systems featuring an increasing number of hardware accelerators. These specialized components can deliver energy-efficient high performance, but their design from high-level specifications is usually very complex. Therefore, it is crucial to understand how to design and optimize such components to implement the desired functionality. This paper discusses the challenges between software programmers and hardware designers, focusing on the state-of-the-art methods based on high-level synthesis (HLS). It also highlights the future research lines for simplifying the creation of complex accelerator-based architectures.