FREDA: A Web Application for the Processing, Analysis, and Visualization of Fourier-Transform Mass Spectrometry Data.

Rationale: The high-resolution measurement capability of Fourier-transform mass spectrometry (FT-MS) has made it a necessity for exploring the molecular composition of complex organic mixtures, like soil, plant, aquatic, and petroleum samples. This demand has driven a need for informatics tools to explore and analyze FT-MS data in a robust and reproducible manner.

Methods: FREDA is an interactive web application developed to enable spectrometrists to format, process, and explore their FT-MS data without the need for statistical programming expertise.

Forgiveness and Religiosity Among Nurses: A Correlational Descriptive Study.

The purpose of the study was to explore how nurses' religious beliefs affect their ability to forgive themselves and others. A descriptive correlational study was conducted. The data were collected using an online survey via Qualtrics using three validated tools Enright Forgiveness Inventory - 30 (to measure forgiveness of others), Enright Self-Forgiveness Inventory (to measure forgiveness of self), and Duke University Religious Index (to measure religiosity).

Identifying Sample Provenance From SEM/EDS Automated Particle Analysis via Few-Shot Learning Coupled With Similarity Graph Clustering.

Automated particle analysis (APA) provides a vast amount of compositional data via energy-dispersive X-ray spectroscopy along with size and shape data via scanning electron microscopy for individual particles in a sample. In many instances, APA data are leveraged to support identification of the source of a sample based on the detection of particles of a specific composition. Often, the particles that provide context make up a minuscule portion of the sample.

Self-Reported Religiosity and Spirituality of Registered Nurses in Virginia.

The professional nurse cares for an increasingly diverse population, varying in ethnicity, culture, and faith beliefs that influence health and wellness. The moral obligation of the nurse to provide individualized, holistic care of clients includes spiritual care. Supported by the Agape Model of Nursing, nurses should understand their personal religiosity and its impact on the care they provide.

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images.

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process.

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images.

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process.

Evaluating Stage Motion for Automated Electron Microscopy.

Precise control is an essential and elusive quality of emerging self-driving transmission electron microscopes (TEMs). It is widely understood these instruments must be capable of performing rapid, high-volume, and arbitrary movements for practical self-driving operation. However, stage movements are difficult to automate at scale, owing to mechanical instability, hysteresis, and thermal drift.

Emotional and Psychological Effects of the COVID-19 Pandemic on Nursing Students.

The COVID-19 pandemic impacted the mental health and educational experiences of nursing students in undergraduate and graduate programs. A larger mixed-methods study aimed to understand how COVID-19 impacted personal lives and learning experiences of students across all programs levels. This article reports on qualitative data obtained from focus groups organized by student program level.

Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.

Purpose: Hepatic steatosis (fatty liver disease) affects 25% of the world's population, particularly people with HIV (PWH). Pharmacoepidemiologic studies to identify medications associated with steatosis have not been conducted because methods to evaluate liver fat within digitized images have not been developed. We determined the accuracy of a deep learning algorithm (automatic liver attenuation region-of-interest-based measurement [ALARM]) to identify steatosis within clinically obtained noncontrast abdominal CT images compared to manual radiologist review and evaluated its performance by HIV status.

Nursing Education's Dynamic History: Challenging, Creative, and Courageous.

Professional nursing education has changed through the decades, from experiential training governed by religious sisters to formal education on theory and research for practice. Numerous types of nursing programs have been developed to meet professional and healthcare needs, and the popularity of different programs has varied over time. The purpose of this article is to explore the history of nursing education and the challenges the 21st century presents to nurse educators and clinicians.

Classifying metal-binding sites with neural networks.

To advance our ability to predict impacts of the protein scaffold on catalysis, robust classification schemes to define features of proteins that will influence reactivity are needed. One of these features is a protein's metal-binding ability, as metals are critical to catalytic conversion by metalloenzymes. As a step toward realizing this goal, we used convolutional neural networks (CNNs) to enable the classification of a metal cofactor binding pocket within a protein scaffold.

Facilitation of Forgiveness: Impact on Health and Well-being.

Although the practice of forgiveness is encouraged, the healing properties of this virtue by health care professionals are often overlooked. Forgiveness is the voluntary, conscious decision to abandon negative feelings toward another who has caused hurt and replacing those feelings with unconditional love and compassion. It is not about forgetting the hurt or ignoring the pain; it is an actual transformation of the heart.

Impact of COVID-19 on Nursing Students: Factors Associated with PTSD Risk.

The COVID-19 pandemic rapidly transformed nursing education, creating multiple stressors for students. The researchers in this study examined how undergraduate and graduate nursing students at a faith-based university perceived the impact of COVID-19. A multiple linear regression model explored the effect of 17 variables on the Impact of Events Scale-Revised (IES-R) scores.

An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analytics.

Artificial intelligence (AI) promises to reshape scientific inquiry and enable breakthrough discoveries in areas such as energy storage, quantum computing, and biomedicine. Scanning transmission electron microscopy (STEM), a cornerstone of the study of chemical and materials systems, stands to benefit greatly from AI-driven automation. However, present barriers to low-level instrument control, as well as generalizable and interpretable feature detection, make truly automated microscopy impractical.

Increased Dephospho-uncarboxylated Matrix Gla-Protein Is Associated With Lower Axial Skeletal Muscle Mass in Patients With Hypertension.

Background: Matrix Gla-protein (MGP) is a well-established inhibitor of vascular calcification that is activated by vitamin K-dependent carboxylation. In the setting of vitamin K2 deficiency, dephospho-uncarboxylated MGP (dpucMGP) levels increase, and have been associated with large artery stiffening. Vitamin K2 is also a mitochondrial electron carrier in muscle, but the relationship of vitamin K2 deficiency and dpucMGP with muscle mass is not well understood.

Integration of Infant Metabolite, Genetic, and Islet Autoimmunity Signatures to Predict Type 1 Diabetes by Age 6 Years.

Context: Biomarkers that can accurately predict risk of type 1 diabetes (T1D) in genetically predisposed children can facilitate interventions to delay or prevent the disease.

Objective: This work aimed to determine if a combination of genetic, immunologic, and metabolic features, measured at infancy, can be used to predict the likelihood that a child will develop T1D by age 6 years.

Methods: Newborns with human leukocyte antigen (HLA) typing were enrolled in the prospective birth cohort of The Environmental Determinants of Diabetes in the Young (TEDDY).

A Veteran-Centric Web-Based Decision Aid for Lung Cancer Screening: Usability Analysis.

Background: Web-based tools developed to facilitate a shared decision-making (SDM) process may facilitate the implementation of lung cancer screening (LCS), an evidence-based intervention to improve cancer outcomes. Veterans have specific risk factors and shared experiences that affect the benefits and potential harms of LCS and thus may value a veteran-centric LCS decision tool (LCSDecTool).

Objective: This study aims to conduct usability testing of an LCSDecTool designed for veterans receiving care at a Veteran Affairs medical center.

The Efficacy of a Forgiveness Bibliotherapy: A Randomized Controlled Trial with Nursing Students.

The need for forgiveness education for nursing self-care and forgiveness facilitation has risen. Therefore, the present pilot study tested the efficacy of an 8-week forgiveness bibliotherapy with a small number of undergraduate nursing students. Matched pairs of nursing students were randomly assigned to either the experimental group or no-contact control group.

Predictive Ability of Pressure-Corrected Arterial Stiffness Indices: Comparison of Pulse Wave Velocity, Cardio-Ankle Vascular Index (CAVI), and CAVI0.

Background: Pulse wave velocity (PWV) is blood pressure (BP) dependent, leading to the development of the BP-corrected metrics cardio-ankle vascular index (CAVI) and CAVI0. We aimed to assess risk prediction by heart-to-ankle PWV (haPWV), CAVI, and CAVI0 in a US population.

Methods: We included 154 subjects (94.

Reducing the Negative Impact of Social Distancing Through Intentional Connectedness.

Social distancing during the COVID-19 pandemic resulted in both positive and negative effects. Nursing education was significantly impacted by the necessity of remote learning and absence of clinical experiences. The purpose of this article is to discuss how intentionality in social connectedness can combat the negative impact of social distancing in nursing education.

Impact of Chronic Obstructive Pulmonary Disease in Heart Failure With Preserved Ejection Fraction.

COPD often coexists with HFpEF, but its impact on cardiovascular structure and function in HFpEF is incompletely understood. We aimed to compare cardiovascular phenotypes in patients with Chronic Obstructive Pulmonary Disease (COPD), Heart Failure with Preserved Ejection Fraction (HFpEF), or both. We studied 159 subjects with COPD alone (n = 48), HFpEF alone (n = 79) and HFpEF + COPD (n = 32).

Neonatal low-density granulocytes internalize and kill bacteria but suppress monocyte function using extracellular DNA.

Low-density granulocytes (LDGs) are found abundantly in neonatal blood; however, there is limited mechanistic understanding of LDG interactions with bacteria and innate immune cells during acute infection. We aimed to determine how human neonatal LDGs may influence control of the bacterial burden at sites of infection, both individually and in the presence of mononuclear phagocytes. LDGs from human umbilical cord blood do phagocytose O1:K1:H7 and traffic bacteria into acidic compartments.

When Is a Harm a Harm? Discordance between Patient and Medical Experts' Evaluation of Lung Cancer Screening Attributes.

Background: A shared decision-making (SDM) process for lung cancer screening (LCS) includes a discussion between clinicians and patients about benefits and potential harms. Expert-driven taxonomies consider mortality reduction a benefit and consider false-positives, incidental findings, overdiagnosis, overtreatment, radiation exposure, and direct and indirect costs of LCS as potential harms.

Objective: To explore whether patients conceptualize the attributes of LCS differently from expert-driven taxonomies.