Miracle-dz/UniFAR-FTUs huggingface dataset:
A Data-Driven Iterative Approach for Semi-automatically Assessing the Correctness of Medication Value Sets: A Proof of Concept Based on Opioids

Abstract Background Value sets are lists of terms (e.g., opioid medication names) and their corresponding codes from standard clinical vocabularies (e.g., RxNorm) created with the intent of supporting health information exchange and research. Value sets are manually-created and often exhibit errors. Objectives The aim of the study is to develop a semi-automatic, data-centric natural language processing (NLP) method to assess medication-related value set correctness and evaluate it on a set of opioid medication value sets. Methods We developed an NLP algorithm that utilizes value sets containing mostly true positives and true negatives to learn lexical patterns associated with the true positives, and then employs these patterns to identify potential errors in unseen value sets. We evaluated the algorithm on a set of opioid medication value sets, using the recall, precision and F1-score metrics. We applied the trained model to assess the correctness of unseen opioid value sets based on recall. To replicate the application of the algorithm in real-world settings, a domain expert manually conducted error analysis to identify potential system and value set errors. Results Thirty-eight value sets were retrieved from the Value Set Authority Center, and six (two opioid, four non-opioid) were used to develop and evaluate the system. Average precision, recall, and F1-score were 0.932, 0.904, and 0.909, respectively on uncorrected value sets; and 0.958, 0.953, and 0.953, respectively after manual correction of the same value sets. On 20 unseen opioid value sets, the algorithm obtained average recall of 0.89. Error analyses revealed that the main sources of system misclassifications were differences in how opioids were coded in the value sets—while the training value sets had generic names mostly, some of the unseen value sets had new trade names and ingredients. Conclusion The proposed approach is data-centric, reusable, customizable, and not resource intensive. It may help domain experts to easily validate value sets.
Why don't all nurse practitioners precept? A comparative study

ABSTRACT Background: Preceptors are integral in nurse practitioner (NP) education. A shortage of willing preceptors limits graduations from NP programs. However, little is known about why NPs decide not to precept. Purpose: To identify the factors significantly associated with NPs' status as currently, previously, or never precepting, using the Integrated Behavioral Model as the conceptual framework. Methodology: This was a cross-sectional, comparative, descriptive study of NPs using survey methodology. Our survey was based on published surveys with items added and adapted to reflect our framework. Subscales included personal factors, primary determinants of intent to precept, and external factors. We mailed recruitment postcards, with an online survey link, to all NPs in Arkansas. Data were analyzed using bivariate and stepwise multinomial logistic regression for each subscale. Results: We obtained 261 responses. Participants who had previously and/or never precepted differed from current preceptors on multiple variables on bivariate analysis. Predictive personal factors included experience and hours worked per week. Predictive primary determinants included knowing NPs that precept, support for precepting, recognition of preceptors, and clinical expertise. Predictive external factors included space, liability, having a “gatekeeper,” NP program, importance of precepting, and number of requests. Conclusions: Different factors predict NPs who currently, previously, and have never precepted. However, frequency of requests predicted both nonprecepting groups. Various supports in the clinical setting and program factors predicted one or other nonprecepting group. Implications: Strategies should be developed to ensure all potential preceptors are recruited, increase support for precepting, and ensure educational programs meet preceptors' needs.
CalliSpheres drug-eluting beads transarterial-chemoembolization in the treatment of liver metastases from breast cancer

Abstract Breast cancer patients with liver metastases are associated with high mortality. However, no standardized treatment approach is available for these patients who have undergone chemotherapy and hormonal therapy. We aimed to assess the clinical outcomes of patients with breast cancer liver metastases (BCLM) who underwent drug-eluting beads used for transarterial-chemoembolization (DEB-TACE). We retrospectively enrolled 14 patients with 39 lesions who underwent DEB-TACE for liver metastases following mastectomy for primary breast cancer. The incidence of complications, overall survival (OS), and local tumor progression-free survival (PFS) were assessed. A total of 14 patients with 39 liver metastases were treated with DEB-TACE from July 2017 to July 2020. The objective response rates (ORR) and disease control rates (DCR) were 71.4% and 92.8% at the 3-month period and 50% and 71.4% at the 6-month period, respectively. During the follow-up period the local tumor PFS was 8.0 months. The median OS was 20.0 months (range, 8–40 months) and the 1-, 2-year OS rates were 84.4% and 47.4%, respectively. No severe complications caused by this technique were detected. DEB-TACE for BCLM was characterized as a low trauma technique, with a limited number of complications. The results indicated that this method was safe and effective for patients with BCLM and could be widely adopted as a palliative treatment in clinical practice.
Numerical simulation in the abdominal aorta and the visceral arteries with or without stenosis based on 2D PCMRI

It is important to obtain accurate boundary conditions (BCs) in hemodynamic simulations. This article aimed to improve the accuracy of BCs in computational fluid dynamics (CFD) simulation and analyze the differences in hemodynamics between healthy volunteers and patients with visceral arterial stenosis (VAS). The geometric models of seven cases were reconstructed using the magnetic resonance angiogram (MRA) or computed tomography angiogram (CTA) imaging data. The physiological flow waveforms obtained from 2D Phase Contrast Magnetic Resonance Imaging (PCMRI) were imposed on the aortic inlet and the visceral arteries' outlets. The individualized RCR values of the three‐element Windkessel model were imposed on the aortic outlet. CFD simulations were run in the open‐source software: svSolver. Two specific time points were selected to compare the hemodynamics of healthy volunteers and patients with VAS. The results suggested that blood in the stenotic visceral arteries flowed at high speed throughout the cardiac cycle. The low pressure is distributed at stenotic lesions. The wall shear stress (WSS) reached 4 Pa near stenotic locations. The low time average wall shear stress (TAWSS), high oscillatory shear index (OSI), and high relative residence time (RRT) concentrated in the abdominal aorta. Besides, the ratios of the areas with low TAWSS, high OSI, and high RRT to the computational domain were higher in patients with VAS than which in the healthy volunteers. The individualized BCs were used for hemodynamic simulations and results suggest that patients with stenosis have a higher risk of blood retention and atherosclerosis formation in the abdominal aorta.
A deep learning method for repurposing antiviral drugs against new viruses via multi-view nonnegative matrix factorization and its application to SARS-CoV-2

The outbreak of COVID-19 caused by SARS-coronavirus (CoV)-2 has made millions of deaths since 2019. Although a variety of computational methods have been proposed to repurpose drugs for treating SARS-CoV-2 infections, it is still a challenging task for new viruses, as there are no verified virus-drug associations (VDAs) between them and existing drugs. To efficiently solve the cold-start problem posed by new viruses, a novel constrained multi-view nonnegative matrix factorization (CMNMF) model is designed by jointly utilizing multiple sources of biological information. With the CMNMF model, the similarities of drugs and viruses can be preserved from their own perspectives when they are projected onto a unified latent feature space. Based on the CMNMF model, we propose a deep learning method, namely VDA-DLCMNMF, for repurposing drugs against new viruses. VDA-DLCMNMF first initializes the node representations of drugs and viruses with their corresponding latent feature vectors to avoid a random initialization and then applies graph convolutional network to optimize their representations. Given an arbitrary drug, its probability of being associated with a new virus is computed according to their representations. To evaluate the performance of VDA-DLCMNMF, we have conducted a series of experiments on three VDA datasets created for SARS-CoV-2. Experimental results demonstrate that the promising prediction accuracy of VDA-DLCMNMF. Moreover, incorporating the CMNMF model into deep learning gains new insight into the drug repurposing for SARS-CoV-2, as the results of molecular docking experiments reveal that four antiviral drugs identified by VDA-DLCMNMF have the potential ability to treat SARS-CoV-2 infections.
Serum concentration of zinc is elevated in clinically stable bipolar disorder patients

Bipolar disorder (BD) is a chronic psychiatric disorder characterized by recurrent mood episodes interspersed with euthymic periods. A growing number of studies have indicated that zinc plays an important role in coordinating immune responses, as well as being involved in synaptic transmission. In the current study, we set out to measure serum levels of zinc in a meticulously phenotyped cohort of 121 euthymic BD subjects and 30 matched controls.
Songbird subthalamic neurons project to dopaminergic midbrain and exhibit singing-related activity.

Skill learning requires motor output to be evaluated against internal performance benchmarks. In songbirds, ventral tegmental area (VTA) dopamine neurons (DA) signal performance errors important for learning, but it remains unclear which brain regions project to VTA and how these inputs may contribute to DA error signaling. Here we find that the songbird subthalamic nucleus (STN) projects to VTA and that STN micro-stimulation can excite VTA neurons. We also discover that STN receives inputs from motor cortical, auditory cortical and ventral pallidal brain regions previously implicated in song evaluation. In the first neural recordings from songbird STN, we discover that the activity of most STN neurons is associated with body movements and not singing, but a small fraction of neurons exhibits precise song timing and performance error signals. Our results place the STN in a pathway important for song learning, but not song production, and expand the territories of songbird brain potentially associated with song learning.
The Risk of Developing Coal Workers' Pneumoconiosis in German Coal Mining under Modern Mining Conditions

A complete inception cohort of 1369 German coal miners was followed up for coal workers’pneumoconiosis (CWP) development (13569 radiographs) and coal mine dust exposure (36113gravimetric dust measurements) between 1974 and 1998. Mean respirable coal mine dustconcentrations decreased from 2.5 to 1.5 mg/m
IC-compatible process for pattern transfer in deep wells for integration of RF components

An IC-compatible process for pattern transfer in deep wells and cavities for the integration of RF components is presented. After an anisotropic wet etching step used to define the optimum position of the ground plane, structures need to be patterned on the bottom of 250-400 micrometers dep etched grooves, trenches or cavities to realize wafer- through contact holes and metal patterns. Thick positive photoresist such as AZ4562 and ma-P275 are used. Modified resist spinning procedure and soft bake process resulted in a good coverage of the etched cavities, even for the deeper ones. The effect of resist thickness and spinning procedure on coating defect density and resolution loss is investigated and optimum conditions are found. A few examples of structures realized using the process described here are shown to indicate the potential and restrictions of this process. © (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
COMPARISON OF STUDENTS' AND PRACTICING ENGINEERS' KNOWLEDGE IN TRAFFIC SIGNAL ENGINEERING

by Kelvin B. Daratha, M.S. Washington State University May 2013 Chair: Shane Brown The current literature suggests that conceptual understanding, misconceptions, and the context of knowledge are important for the learning of students. Furthermore, the literature indicates a difference in the thinking between novices and experts. However, no research has been conducted to characterize the conceptual thinking of practicing engineers or to investigate practicing engineers’ misconceptions and their comparison with students. Research is needed to determine the correct context for students in the engineering classroom, which would foster an environment with greater authenticity that would mimic the engineering practice. This study used clinical interviews to extract misconceptions and contexts quotations from the interviewees, and compared the data between novice students, expert students, and practicing engineers. The results of the misconception prevalence and the context of the concepts were used to compare the knowledge of traffic signal engineering between the three cohorts. The investigation of the misconception prevalence revealed that most of the concepts did not follow the trend hypothesized by the researchers. Furthermore, the results of the misconception prevalence also revealed frequent misconceptions across the three cohorts. The investigation on the context
Changes in Choroidal Vascularity Index (CVI) in Intermediate Uveitis

Purpose To investigate the longitudinal changes in choroidal vascularity index (CVI) in eyes with active and quiescent intermediate uveitis using enhanced depth imaging optical coherence tomography (EDI-OCT). Methods EDI-OCT images of eyes with active and quiescent intermediate uveitis were retrospectively reviewed and binarized using ImageJ software. Choroidal parameters including CVI, total choroidal area (TCA), luminal area (LA), stromal area (SA), and subfoveal choroidal thickness (SCT) were measured and compared between baseline and follow-up visits among eyes with active and quiescent intermediate uveitis. Results Thirty-eight eyes from 21 patients with active intermediate uveitis and 30 eyes from 17 patients with quiescent intermediate uveitis were included. CVI in eyes with active intermediate uveitis significantly increased from baseline (66.50% ± 3.40%) with resolution of inflammation on follow-up (68.82% ± 3.90%; P < 0.001). In eyes with quiescent intermediate uveitis at baseline eyes, CVI did not significantly change after follow-up (66.34% ± 3.19% to 66.25% ± 3.13%; P = 0.850). Conclusions CVI significantly increased when active inflammation in intermediate uveitis resolved while CVI remained unchanged at follow-up in quiescent intermediate uveitis. Translational Relevance CVI may be a useful noninvasive tool to monitor treatment response in intermediate uveitis. Our findings also highlight the involvement of choroidal vasculature in uveitic eyes without any clinical evidence of choroiditis.
Multi-attribute Raman spectroscopy (MARS) for monitoring product quality attributes in formulated monoclonal antibody therapeutics

ABSTRACT Rapid release of biopharmaceutical products enables a more efficient drug manufacturing process. Multi-attribute methods that target several product quality attributes (PQAs) at one time are an essential pillar of the rapid-release strategy. The novel, high-throughput, and nondestructive multi-attribute Raman spectroscopy (MARS) method combines Raman spectroscopy, design of experiments, and multivariate data analysis (MVDA). MARS allows the measurement of multiple PQAs for formulated protein therapeutics without sample preparation from a single spectroscopic scan. Variable importance in projection analysis is used to associate the chemical and spectral basis of targeted PQAs, which assists in model interpretation and selection. This study shows the feasibility of MARS for the measurement of both protein purity-related and formulation-related PQAs; measurements of protein concentration, osmolality, and some formulation additives were achieved by a generic multiproduct model for various protein products containing the same formulation components. MARS demonstrates the potential to be a powerful methodology to improve the efficiency of biopharmaceutical development and manufacturing, as it features fast turnaround time, good robustness, less human intervention, and potential for automation.
Prelinguistic Consonant Production and the Influence of Mouthing Before and After Cochlear Implantation

Objectives: The goal of the study was to investigate prelinguistic consonant production and the influence of vocalizations that co-occurred with object mouthing on consonant production in infants with profound sensorineural hearing loss before and after cochlear implantation to advance knowledge of early speech development in infants with profound hearing loss. Design: Participants were 43 infants, 16 infants with profound sensorineural hearing loss and 27 hearing infants. In the mixed longitudinal and cross-sectional design, infants with profound hearing loss and age-matched hearing infants participated before cochlear implantation, at an average age of 9.9 mo, and/or after cochlear implantation, at an average age of 17.8 mo. Mean age at cochlear implantation for infants with profound hearing loss was 12.4 mo; mean duration of cochlear implant use at time of testing was 4.2 mo. Results: Before and after cochlear implantation, infants with profound hearing loss produced significantly fewer supraglottal consonants per consonant-vowel vocalization than hearing peers and had smaller overall consonant inventories. Before, but not after cochlear implantation, infants with profound hearing loss produced proportionally more vocalizations, supraglottal consonant-vowel vocalizations, and different supraglottal consonants in vocalizations during mouthing than did hearing infants. Conclusions: The results document consonant production before cochlear implantation in a larger group of infants with profound hearing loss than previously examined. The results also extend evidence of early delays in consonant production to infants who received cochlear implants at 12 mo of age, and show that they likely miss the potential benefits of auditory-motor feedback in vocalization-mouthing combinations that occur before they have access to sound through cochlear implants.
Anti-nociceptive and anti-inflammatory activities of the essential oil isolated from Cupressus arizonica Greene fruits

Background Cupressus arizonica Greene is a coniferous tree with great importance in fragrance and pharmaceutical industries. Essential oils from C. arizonica (EC) have shown potential antioxidant, and anti-microbial activities. This study aimed at investigating the anti-nociceptive and anti-inflammatory effects/mechanisms of EC. Methods The EC was evaluated for anti-nociceptive and anti-inflammatory activities on male Wistar rats using a formalin test and carrageenan-induced paw edema, respectively. Also, we pre-treated some of the animals with naloxone and flumazenil in the formalin test to find out the possible contributions of opioid and benzodiazepine receptors to EC anti-nociceptive effects. Finally, gas chromatography/mass spectrometry (GC/MS) analysis was used to identify the EC’s constituents. Results EC in intraperitoneal doses of 0.5 and 1 g/kg significantly decrease the nociceptive responses in both early and late phases of the formalin test. From a mechanistic point of view, flumazenil administration 20 minutes before the most effective dose of EC (1 g/kg) showed a meaningful reduction in the associated anti-nociceptive responses during the early and late phases of the formalin test. Naloxone also reduced the anti-nociceptive role of EC in the late phase. Furthermore, EC at the doses of 1, 0.5, and 0.25 g/kg significantly reduced paw edema from 0.5 hours after carrageenan injection to 4 hours. GC/MS analysis showed that isolated EC is a monoterpene-rich oil with the major presence of α-pinene (71.92%), myrcene (6.37%), δ-3-carene (4.68%), β-pinene (3.71%), and limonene (3.34%). Conclusions EC showed potent anti-nociceptive and anti-inflammatory activities with the relative involvement of opioid and benzodiazepine receptors.
lncRNA Expression-Based Risk Scoring System Can Predict Survival of Tumor-Positive Patients with Hepatocellular Carcinoma

Background: Long non-coding RNAs (lncRNAs) play critical roles in the progression of hepatocellular carcinoma (HCC). The aim of this study was to explore whether lncRNA expression profiles can predict prognosis of HCC patients with tumors. Methods: Expression of lncRNAs in HCC patients based on data in The Cancer Genome Atlas (TCGA) was examined by uni- and multivariate cox analysis to identify associations between clinical features and overall survival (OS) or recurrence-free survival (RFS). Based on our finding that both were independently associated with tumor status, we examined lncRNAs differentially expressed between patients with or without tumors. An lncRNA-based risk scoring system was developed to predict OS and RFS in tumor-positive patients, and it was assessed using uni- and multivariate cox analyses. Potential functions of the prognostic lncRNAs were explored. Results: A risk scoring system to predict OS for HCC patients with tumors was developed based on the expression of six lncRNAs (AC090921.1, AC012640.1, AL158839.1, AL356056.1, AL359853.1 and C10orf91), and a corresponding scoring system to predict RFS was developed from nine lncRNAs (AL356056.1, AL158839.1, MIR7-3HG, AL445493.2, AP000808.1, AP003354.2, PLCE1-AS1, TH2LCRR and LINC01447). Both risk scoring systems gave areas under receiver operating characteristic curves >0.7. Uni- and multivariate cox analyses showed that both risk scoring systems independently predicted survival even after adjusting for clinical factors. The lncRNAs related to OS may be involved in complement and coagulation cascades, while those related to RFS may be involved in the cell cycle. Conclusion: Risk scoring system based on these lncRNAs may be useful for predicting prognosis of tumor-positive HCC patients.
The Girls’ Leadership Academy: A Promising, Empowerment-Based Approach to the Prevention of Sexual Violence

Sexual violence (SV) is a pernicious issue that disproportionally impacts girls and women. Although few initiatives have demonstrated effectiveness in leading to reductions in SV, global health organizations have identified empowerment-based programs as a promising approach to SV prevention. The purpose of this article is to discuss the Girls Leadership Academy (GLA), a program of the Nebraska's Women's Center for Advancement, which is a “homegrown,” theoretically grounded, practice-based SV prevention program for adolescent girls. More specifically, we discuss previous research relevant to the GLA; the theoretical underpinnings of the GLA; and the history, context, and content of the GLA.