Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Integration of a Texting Tool to Keep Patients’ Family Members Updated During Hospitalization: Clinicians’ Perspectives

An important gap in the literature is how clinicians feel about patient-centered technologies and how clinicians experience patient-centered technologies in their workflows. Our goal was to identify clinician users’ perspectives on facilitators (pros) and barriers (cons) to using 1 digital texting innovation to promote family centered care during patients’ hospitalizations. This qualitative study was conducted at a tertiary care center in Houston, consisting of 7 hospitals (1 academic hospital and 6 community hospitals), involving analyzation of 3 focus groups of 18 physicians, 5 advanced practice providers, and 10 nurse directors and managers, as well as a content analysis of 156 real-time alerts signaling family dissatisfaction on the nursing unit/floor. Thematic analysis methods were used. We selected these participants by attending their regularly scheduled service-line meetings. Clinician feedback from focus groups resulted in 3 themes as facilitators: (a) texting platforms must be integrated within the electronic medical record; (b) texting reduces outgoing phone calls; (c) texting reduces incoming family phone calls. Clinician feedback resulted in 3 themes as barriers: (a) best practice alerts can be disruptive; (b) real-time alerts can create hopelessness; and (c) scale-up is challenging. The analyzation of facilitators (pros) and barriers (cons) pertains only to the clinician's feedback. We also analyzed real-time alerts signaling family dissatisfaction (defined as “service recovery escalation” throughout this manuscript). The most common selection for the source of family dissatisfaction, as reflected through the real-time alerts was, “I haven’t heard from physicians enough,” appearing in 52 out of 156 alerts (33%). The second most common selection for the source of dissatisfaction was “perceived inconsistent or incomplete information provided by team members,” which was selected in 48 cases (31%). Our findings indicate that clinicians value inpatient texting, not only for its ability to quickly relay updates to multiple family members with 1 click, but also because, when used intentionally and meaningfully, texting decreases family phone calls.
Efficient Knocking Out of the Organophosphorus Insecticides Degradation Gene opdB in Cupriavidus nantongensis X1T via CRISPR/Cas9 with Red System

Cupriavidus nantongensis X1T is a type strain of the genus Cupriavidus, that can degrade eight kinds of organophosphorus insecticides (OPs). Conventional genetic manipulations in Cupriavidus species are time-consuming, difficult, and hard to control. The clustered regularly interspaced short palindromic repeat (CRISPR)/associated protein 9 (Cas9) system has emerged as a powerful tool for genome editing applied in prokaryotes and eukaryotes due to its simplicity, efficiency, and accuracy. Here, we combined CRISPR/Cas9 with the Red system to perform seamless genetic manipulation in the X1T strain. Two plasmids, pACasN and pDCRH were constructed. The pACasN plasmid contained Cas9 nuclease and Red recombinase, and the pDCRH plasmid contained the dual single-guide RNA (sgRNA) of organophosphorus hydrolase (OpdB) in the X1T strain. For gene editing, two plasmids were transferred to the X1T strain and a mutant strain in which genetic recombination had taken place, resulting in the targeted deletion of opdB. The incidence of homologous recombination was over 30%. Biodegradation experiments suggested that the opdB gene was responsible for the catabolism of organophosphorus insecticides. This study was the first to use the CRISPR/Cas9 system for gene targeting in the genus Cupriavidus, and it furthered our understanding of the process of degradation of organophosphorus insecticides in the X1T strain.
A Sinusoidal Signal Generator Using a Delta-Sigma Modulated Look-Up Table and Analysis of Dither

Sinusoidal signal generators (SSG) are increasingly required for on-chip integration in impedance measurement architectures for bio-sensing and chemical sensing applications. For digital SSG architectures, there are inherent trade-offs among circuit area, power, and linearity. In this brief, we present a new approach that encodes a delta-sigma-modulated look-up table <inline-formula> <tex-math notation="LaTeX">$(\Delta \Sigma \text{M}$ </tex-math></inline-formula>-LUT) to decrease digital circuit size and power while maintaining high linearity. In addition, we present a method for analyzing the combined periodicity of the modulator and the LUT for adding dither to further improve performance. The approach is demonstrated using a 5-bit, 2 <inline-formula> <tex-math notation="LaTeX">$^{\mathrm{ nd}}$ </tex-math></inline-formula>-order <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma \text{M}$ </tex-math></inline-formula>-LUT controlling a digital <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> modulated SSG, where it enables a significant decrease in digital circuit area and power compared to state-of-the-art designs while achieving 64.6 dBc SFDR and 0.074% THD.
The impact of misspecification of nuisance parameters on test for homogeneity in zero-inflated Poisson model: A simulation study

Abstract Most of the existing methodologies for evaluating heterogeneity in zero-inflated Poisson (ZIP) models are often assuming that the Poisson mean is a function of nuisance parameters. However, these nuisance parameters can be misspecified when performing these methodologies, the validity and the power of the test may be affected. In this article, we primarily focus on investigating the impact of misspecification on the performance of score test for homogeneity in ZIP models. Through an intensive simulation study, we find that: 1) under misspecification, the limiting distribution of the score test statistic under the null no longer follows a distribution. A parametric bootstrap methodology is suggested to use to find the true null limiting distribution of the score test statistic; 2) the power of the test decreases as the number of covariates in the Poisson mean increases. The test with a constant Poisson mean has the highest power, even compared to the test with a well-specified mean. At last, simulation results are applied to the Wuhan Inpatient Care Insurance data which contain excess zeros.
Vegetable‐enriched bread: Pilot and feasibility study of measurement of changes in skin carotenoid concentrations by reflection spectroscopy as a biomarker of vegetable intake

Abstract Globally, bread is a staple food and thus a promising vehicle for the delivery of nutrients from vegetables including carotenoids. The aim of this pilot/feasibility, pre–post experimental study was to measure skin (Veggie Meter™) and plasma carotenoid concentrations 1 week before (week −1), immediately prior to (week 0), and after (week 2) 14 days of daily consumption of 200 g pumpkin‐ and sweetcorn‐enriched bread (VB). At each measurement point, total vegetable and fruit intake and specific carotenoid‐rich foods were assessed by questionnaire. Participants (n = 10, 8 males, 2 females) were aged between 19 and 39 years and weighed 90 ± 20 kg. Vegetable and fruit intake was low and less than one serving/day of foods containing carotenoids. Prior to the intervention, measures of carotenoid‐containing foods and skin or plasma carotenoids were not different when measured a week apart. Consumption of the VB did not result in statistically significant changes in either the skin or plasma carotenoid measurements. Plasma carotenoid concentrations and the carotenoid reflection scores had a large and positive (r = .845, 95% CI 0.697, 0.924) association. The relationship between the number of servings of carotenoid‐rich foods with the plasma carotenoid and carotenoid reflection scores was positive and of moderate strength. In conclusion, carotenoid status was not measurably changed with the consumption of 200 g VB each day for 2 weeks. Subjective carotenoid‐rich food intake was positively associated with objective biomarkers of carotenoids. The Veggie meter™ has the potential to provide portable measurement of circulating carotenoids and be indicative of intake of carotenoid‐rich foods.
YouTubers vs. VTubers: Persuasiveness of human and virtual presenters in promotional videos

With the recent advances in motion tracking technologies and three-dimensional computer graphics software, communication through avatars has become increasingly popular. Can avatars be sufficiently persuasive, when compared to traditional forms of interpersonal communication? What factors contribute to the persuasiveness of virtual influencers? Existing literature has studied the differences in persuasiveness between human and virtual speakers extensively, particularly in education. However, few studies have been conducted on product promotion. Therefore, in this study, we investigated the characteristics of persuasiveness for humans and virtual influencers, as well as the differences between them in this regard in a more modern and practical situation: product introduction videos used in influencer marketing. Specifically, we recruited participants to watch product introduction videos on YouTube, presented by either humans or avatars. The videos were similar, except for the appearance of the presenter. Before and after watching the videos, the participants were asked to complete a questionnaire about their willingness to purchase the products and the characteristics of presenters' persuasiveness. The results show that although promotion via avatars can increase the participants' willingness to purchase, human influencers were more persuasive. However, the virtual YouTubers (VTubers) were more persuasive in certain product domains. VTubers who can change their appearance to match the product domain have potential for future applications. We also attempted to construct a model of persuasiveness in this pragmatic context based on Dyson's persuasiveness rating scale and the overall impression of the video. The degree of persuasiveness was found to be related to the presenters' likability, whether the presenter was a human or an avatar, the degree of familiarity between the presenter and the audience, the presenters' trustworthiness, and the quality as well as the entertainment level of the video. This model may be helpful for running successful promotions on YouTube. Our findings verify that avatars can be fairly persuasive in some situations, including promotional videos. These findings contribute to the future development of communication through avatars.
Heterogeneous pattern of gene expression driven by TTN mutation is involved in the construction of a prognosis model of lung squamous cell carcinoma

Objective To investigate the impact that TTN mutation had on the gene heterogeneity expression and prognosis in patients with lung adenocarcinoma. Methods In this study, the Cancer Genome Atlas (TCGA) dataset was used to analyze the TTN mutations in lung adenocarcinoma. Lung adenocarcinoma data was collected from the TCGA database, clinical information of patients was analyzed, and bioinformatics statistical methods were applied for mutation analysis and prognosis survival analysis. The results were verified using the GEO dataset. Results The incidence of TTN mutations in lung adenocarcinoma was found to be 73%, and it was related to the prognosis of lung adenocarcinoma. Ten genes were screened with significant contributions to prognosis. A prognosis model was constructed and verified by LASSO COX analysis in the TCGA and GEO datasets based on these ten beneficial factors. The independent prognostic factor H2BC9 for TTN mutation-driven gene heterogeneity expression was screened through multi-factor COX regression analysis. Conclusion Our data showed that the gene heterogeneity expression, which was driven by TTN mutations, prolonged the survival of lung adenocarcinoma patients and provided valuable clues for the prognosis of TTN gene mutations in lung adenocarcinoma.
Should I Travel by Metro? Analyzing the Service Quality Perception of Elderly and Physically Disabled Passengers in Delhi, India

Transit officials worldwide continuously learn from passenger perception surveys to improve service quality and enhance transit ridership. However, many elderly and physically disabled (E&PD) passengers are transit users with special needs whose service requirements have received insufficient attention in the past. In fact, providing satisfactory transit services to E&PD passengers is often a critical challenge for transit officials, since a theory of interrelations among service factors is not yet established from E&PD passengers’ perspectives. Therefore, the present study aims to establish interrelations among service quality factors and identify service improvements for E&PD passengers using satisfaction data from 254 E&PD passengers of Delhi Metro. For this purpose, this study has employed an integrated Bayesian networks and partial least squares path modeling approach. The obtained results have shown some remarkable and meaningful interpretations. For instance, a one-unit increase in satisfaction with the “safety & security” factor would induce a 68% increase in their satisfaction with overall service quality. Besides, importance–performance map analysis showed that Delhi Metro must consider “safety and security,”“passenger ease,” and “seamless connectivity” as high-priority areas needing improvements to promote E&PD-friendly transit services. Overall, the findings of this study suggest several policy measures that would enrich the service quality and achieve universal design standards in metro rail transit systems.
The nonlinear model of runoff forecast based on wavelet decomposition

A great deal of information is included in runoff time series.From the point of view of frequency,the information can be sorted into low frequency and high frequency items by wavelet decomposition.The stepwise regression algorithm and the Volterra filter based on group method of data handling(GMDH) are used to forecast them respectively.The results are integrated to forecast the runoff.At last the example of application shows that this model is of high accuracy.
EMP1 as a Potential Biomarker in Liver Fibrosis: A Bioinformatics Analysis

Liver fibrosis is a wound-healing response to chronic injury, which may result in cirrhosis and liver failure. Studies have been carried on the mechanisms and pathogenesis of liver fibrosis. However, the potential cell-specific expressed marker genes involved in fibrotic processes remain unknown. In this study, we combined a publicly accessible single-cell transcriptome of human liver with microarray datasets to evaluate the cell-specific expression patterns of differentially expressed genes in the liver. We noticed that EMP1 (epithelial membrane protein 1) is significantly active not only in CCl4 (carbon tetrachloride)-treated mouse liver fibrosis but also in BDL (bile duct ligation)-induced liver fibrosis and even in human fibrotic liver tissues such as alcoholic hepatitis, NASH (nonalcoholic steatohepatitis), and advanced stage liver fibrosis. Furthermore, we demonstrated that EMP1 is a specific fibrotic gene expressed in HSCs (hepatic stellate cells) and endothelial cells using the Protein Atlas single-cell transcriptome RNA-sequencing clustering. Its expression was significantly elevated in fibrotic HSCs or CCl4 and NASH-induced fibroblasts. Previous research revealed that EMP1 plays a role in proliferation, migration, metastasis, and tumorigeneses in different cancers via a variety of mechanisms. Because HSC activation and proliferation are two important steps following liver injury, it would be interesting to investigate the role of EMP1 in these processes. All of this information suggested that EMP1 could be used as a novel fibrotic liver marker and a possible target in the future.
Characterization of Mediastinal Bulky Lymphomas with FDG-PET-Based Radiomics and Machine Learning Techniques

Simple Summary This manuscript aims to address the diagnostic challenges of mediastinal bulky lymphomas with the baseline value of 18F-FDG PET/CT metabolic, volumetric and texture parameters, also relying on machine learning techniques, in patients with grey zone lymphoma, primary diffuse large B-cell lymphoma of the mediastinum and classical Hodgkin lymphoma. Different types of histology demonstrated several baseline 18F-FDG PET/CT radiomics parameters that were significantly different from one another, suggesting the possibility of identifying potential histological heterogeneity and aggressive transformation. Moreover, using radiomics-based imaging biomarkers, machine learning techniques offer a solution for separating not completely disjoint histological types. To date, the gold standard for diagnosis is biopsy, but machine learning methods could be combined with radiomics to build a histological representation of mediastinal bulky masses that is able to successfully identify different types of lymphomas. Finally, this preliminary study supports the potential of metabolic texture analyses as future imaging biomarkers, with a growing role in clinical diagnosis. Abstract Background: This study tested the diagnostic value of 18F-FDG PET/CT (FDG-PET) volumetric and texture parameters in the histological differentiation of mediastinal bulky disease due to classical Hodgkin lymphoma (cHL), primary mediastinal B-cell lymphoma (PMBCL) and grey zone lymphoma (GZL), using machine learning techniques. Methods: We reviewed 80 cHL, 29 PMBCL and 8 GZL adult patients with mediastinal bulky disease and histopathological diagnoses who underwent FDG-PET pre-treatment. Volumetric and radiomic parameters were measured using FDG-PET both for bulky lesions (BL) and for all lesions (AL) using LIFEx software (threshold SUV ≥ 2.5). Binary and multiclass classifications were performed with various machine learning techniques fed by a relevant subset of radiomic features. Results: The analysis showed significant differences between the lymphoma groups in terms of SUVmax, SUVmean, MTV, TLG and several textural features of both first- and second-order grey level. Among machine learning classifiers, the tree-based ensembles achieved the best performance both for binary and multiclass classifications in histological differentiation. Conclusions: Our results support the value of metabolic heterogeneity as an imaging biomarker, and the use of radiomic features for early characterization of mediastinal bulky lymphoma.
Objectively-Assessed Ultraviolet Radiation Exposure and Sunburn Occurrence

Ultraviolet radiation (UVR) exposure is the primary modifiable risk factor for melanoma. Wearable UVR sensors provide a means of quantifying UVR exposure objectively and with a lower burden than self-report measures used in most research. The purpose of this study was to evaluate the relationship between detected UVR exposure and reported sunburn occurrence. In this study, a UVR monitoring device was worn by 97 parent–child dyads during waking hours for 14 days to measure instantaneous and accumulated UVR exposure. The results showed that the participants’ total UVR exposure was associated with reported sunburn after adjusting for Fitzpatrick skin type and geographic location. It was observed that one standard erythemal dose (SED) increase in the participants’ daily total UVR exposure was associated with reported sunburn (an odds ratio (OR) of 1.26 with a 95% CI of 1.13 and 1.41, and p < 0.001 for parents and an OR of 1.28 with a 95% CI of 1.12 and 1.47, and p < 0.001 for children). A one-SED increase in the participants’ UVR exposure from 10 am to 4 pm was also associated with reported sunburn (an OR of 1.31 with a 95% CI of 1.15 and 1.49, and p < 0.001 for parents and an OR of 1.33 with a 95% CI of 1.12 and 1.59, and p = 0.001 for children). We found that elevated UVR exposure recordings measured by the UVR sensor were associated with reported sunburn occurrence. Future directions for wearable UVR sensors may include their use as an intervention tool to support in-the-moment sunburn prevention.
Analytical approach to performance analysis for channel subject to shadowing and fading

In this paper a unified analytical approach to performance analyses in a gamma-shadowed Nakagami-m fading channel is presented. Specifically, a lognormal probability density function (PDF) of shadowing is approximated by a gamma PDF. The approximation is based on the moment matching method. The accuracy of the approximation is examined. A mathematical framework is developed for deriving key statistical parameters such as the PDFs, as well as performance metrics including outage probability and average bit-error rate of different noncoherent digital modulation schemes. These formulas are validated by specialising the general results to some particular cases whose solutions are known and by means of comparing our graphically presented results (based on the closed-form expressions) with corresponding known results evaluated by numerical techniques. In this way, one can conclude that presented results are reliable for lognormal shadowing spread <9 dB (note that, the shadowing spread actually observed in macrocells has a typical value that lies between 4 and 9 dB). The final results are remarkably simple and can serve as a quick way of assessing performance. In addition, presented analytical expressions are suitable for asymptotic analyses, which is a significant feature for both theoretical and practical aspects of their applications.
CORAL Models for Drug-Induced Nephrotoxicity

Drug-induced nephrotoxicity is a major cause of kidney dysfunction with potentially fatal consequences. The poor prediction of clinical responses based on preclinical research hampers the development of new pharmaceuticals. This emphasises the need for new methods for earlier and more accurate diagnosis to avoid drug-induced kidney injuries. Computational predictions of drug-induced nephrotoxicity are an attractive approach to facilitate such an assessment and such models could serve as robust and reliable replacements for animal testing. To provide the chemical information for computational prediction, we used the convenient and common SMILES format. We examined several versions of so-called optimal SMILES-based descriptors. We obtained the highest statistical values, considering the specificity, sensitivity and accuracy of the prediction, by applying recently suggested atoms pairs proportions vectors and the index of ideality of correlation, which is a special statistical measure of the predictive potential. Implementation of this tool in the drug development process might lead to safer drugs in the future.