bluuebunny/crossref_metadata_2025_split huggingface dataset:
Technological risks and ethical implications of using robots in long-term care
Authors: Hung Lillian , Mann Jim , Perry Jennifer , Berndt Annette , Wong Joey 
Published: June 2022

Introduction The pandemic provides a unique opportunity to examine new directions in innovative technological approaches in long-term care (LTC) homes. While robotics could enhance staff capacity to provide care, there are potential technology risks and ethical concerns involved in technology use among older people residing in communal aged care homes. This qualitative descriptive study explores the technological risks and ethical issues associated with the adoption of robots in the specific context of LTC homes. Methods The research team including patient and family partners employed purposive and snowballing methods to recruit 30 LTC participants: frontline interdisciplinary staff, operational leaders, residents and family members, and ethics experts in dementia care. Semi-structured interviews were conducted. Thematic analysis was performed to identify themes that capture empirical experiences and perspectives of a diverse group of LTC stakeholders about robotic use. Results Technological risks include safety, increased workload, privacy, cost and social justice, and human connection. The findings offer practical insights based on the LTC perspective to contribute to the robot ethics literature. We propose a list of pragmatic recommendations, focusing on six principles (ETHICS): Engagement of stakeholders, Technology benefit and risk assessment, Harm mitigation, Individual autonomy, Cultural safety and justice, Support of privacy. Conclusions There is both a growing interest as well as fear in using robotics in LTC. Practice leaders need to reflect on ethical considerations and engage relevant stakeholders in making technology decisions for everyday care.
Approaches to Safety Evaluation of Baby Wipes
Authors: Li Ning , Dey Swatee , O’Connor Robert , Abbinante-Nissen Joan , White Jeff 
Published: June 2022

Disposable baby wipes manufactured by Procter & Gamble, soft sheets bearing lotion that is balanced to maintain natural skin pH, are convenient for cleaning the diaper area and a quick cleanup on baby’s face and hands. Objective: Develop a rigorous safety assessment process to ensure that baby wipes are safe and gentle to skin. This process is built-in from the start of product research and development. Methods: A systematic, iterative approach that includes (1) exposure-based safety assessment of all raw materials for systemic and local effects, which are consistent with established risk assessment paradigms; (2) when needed, testing of finished wipes in in vitro and/or clinical studies for skin and eye irritation, contact sensitization, or mechanical effects on skin in comparison to benchmark products that have a long history of wipe safety in marketplace; (3) prospective and randomized in-use studies in babies; and (4) in-market monitoring that is an integral part of the on-going product safety assessment. Results: Individual approaches and/or their combination show mildness of the test wipes. Further, in-market monitoring is testimony to baby skin compatibility of baby wipes. Conclusion: The approaches that have been developed demonstrate the skin compatibility and/or benefits of baby wipes relative to other modes of cleaning if needed. This article describes our safety assurance program, exposure-based safety assessment, and the range of robust testing strategies and approaches that can be employed to assure the safety of baby wipes.
Evaluation of the Impact of an Education Program on Self-Reported Leadership and Management Competence Among Nurse Managers
Authors: Aqtash Salah , Alnusair Hussam , Brownie Sharon , Alnjadat Rafi , Fonbuena Mariezl , Perinchery Saleem 
Published: June 2022

Background Developing leadership and management competencies for nursing managers is critical to the effective leadership of others and driving team and organizational performance. This paper aimed to evaluate the impact of a system-wide nursing leadership quality improvement initiative in a network of four public hospitals and one specialized outpatient center in the United Arab Emirates (UAE). The initiative was designed to enhance nursing middle managers’ leadership and managerial competencies. Methods This is a quantitative evaluation following the Standards for Quality Improvement Reporting Excellence (SQUIRES) guidelines. Secondary Data analysis of a pre- and post-course self-assessment for 105 middle nursing managers who attended a nursing leadership quality improvement training program between December 2017 and April 2019. Results Following participation in this quality improvement initiative, the paired sample t-test analysis demonstrated a statistically significant difference between the pre- and post-assessments total and individual leadership domains mean scores. Conclusion Attending well-structured nursing leadership quality improvement programs positively enhances nurse managers’ professional abilities and perception of their management and leadership competencies. Leadership development programs should equip managers with the skills and tools to achieve their professional goals effectively and support their transition to becoming expert nurse leaders. Healthcare institutions’ ethical obligation is to provide them with the necessary resources and training to achieve this goal.
A macaque clonal hematopoiesis model demonstrates expansion of TET2-disrupted clones and utility for testing interventions
Authors: Shin Tae-Hoon , Zhou Yifan , Chen Shirley , Cordes Stefan , Grice Max Z. , Fan Xing , Lee Byung-Chul , Aljanahi Aisha A. , Hong So Gun , Vaughan Kelli L. , Mattison Julie A. , Kohama Steven G. , Fabre Margarete A. , Uchida Naoya , Demirci Selami , Corat Marcus A.F. , Métais Jean-Yves , Calvo Katherine R. , Buscarlet Manuel , Natanson Hannah , McGraw Kathy L. , List Alan F. , Busque Lambert , Tisdale John F. , Vassiliou George S. , Yu Kyung-Rok , Dunbar Cynthia E. 
Published: June 2022

Abstract
Individuals with age-related clonal hematopoiesis (CH) are at greater risk for hematologic malignancies and cardiovascular diseases. However, predictive preclinical animal models to recapitulate the spectrum of human CH are lacking. Through error-corrected sequencing of 56 human CH/myeloid malignancy genes, we identified natural CH driver mutations in aged rhesus macaques matching genes somatically mutated in human CH, with DNMT3A mutations being the most frequent. A CH model in young adult macaques was generated via autologous transplantation of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9–mediated gene-edited hematopoietic stem and progenitor cells (HSPCs), targeting the top human CH genes with loss-of-function (LOF) mutations. Long-term follow-up revealed reproducible and significant expansion of multiple HSPC clones with heterozygous TET2 LOF mutations, compared with minimal expansion of clones bearing other mutations. Although the blood counts of these CH macaques were normal, their bone marrows were hypercellular and myeloid-predominant. TET2-disrupted myeloid colony-forming units isolated from these animals showed a distinct hyperinflammatory gene expression profile compared with wild type. In addition, mature macrophages purified from the CH macaques showed elevated NLRP3 inflammasome activity and increased interleukin-1β (IL-1β) and IL-6 production. The model was used to test the impact of IL-6 blockage by tocilizumab, documenting a slowing of TET2-mutated expansion, suggesting that interruption of the IL-6 axis may remove the selective advantage of mutant HSPCs. These findings provide a model for examining the pathophysiology of CH and give insights into potential therapeutic interventions.
Gradient Annealing as a New Strategy to Fabricate Gradient Nanoparticle Array on Microwires
Authors: Chen Anqi , Lv You , Wu Yanyan , Zhu Yuan 
Published: June 2022

AbstractCreating gradients of nanostructure on the surface has found broad applications such as enhanced optical spectroscopy, optical storage of information, and broadband solar energy harvesting. Here, a facile strategy is presented for fabricating gradient nanoparticle arrays with tunable size. It takes a ZnO:Ga microwire as the starting material, and the Ga3+ doping gradient along the microwire is induced by the high voltage applied. Such a doping gradient facilitates the formation of a temperature gradient in a Joule heating process. And this temperature gradient produced by this technique can be as high as 800 °C/mm, which could be later used for gradient annealing of thin metal films. After annealing, the thin metal films turn to gradient nanoparticle arrays. The obtained gradient nanoparticle arrays are confirmed effective in multi-wavelength surface enhanced Raman scattering enhancement.
Early donepezil monotherapy or combination with metoprolol significantly prevents subsequent chronic heart failure in rats with reperfused myocardial infarction
Authors: Li Meihua , Zheng Can , Kawada Toru , Uemura Kazunori , Inagaki Masashi , Saku Keita , Sugimachi Masaru 
Published: June 2022

AbstractDespite the presence of clinical guidelines recommending that β-blocker treatment be initiated early after reperfused myocardial infarction (RMI), acute myocardial infarction remains a leading cause of chronic heart failure (CHF). In this study, we compared the effects of donepezil, metoprolol, and their combination on the progression of cardiac remodeling in rats with RMI. The animals were randomly assigned to untreated (UT), donepezil-treated (DT), metoprolol-treated (MT), and a combination of donepezil and metoprolol (DMT) groups. On day 8 after surgery, compared to the UT, the DT and DMT significantly improved myocardial salvage, owing to the suppression of macrophage infiltration and apoptosis. After the 10-week treatment, the DT and DMT exhibited decreased heart rate, reduced myocardial infarct size, attenuated cardiac dysfunction, and decreased plasma levels of brain natriuretic peptide and catecholamine, thereby preventing subsequent CHF. These results suggest that donepezil monotherapy or combined therapy with β-blocker may be an alternative pharmacotherapy post-RMI.
Explainable deep drug–target representations for binding affinity prediction
Authors: Monteiro Nelson R. C. , Simões Carlos J. V. , Ávila Henrique V. , Abbasi Maryam , Oliveira José L. , Arrais Joel P. 
Published: June 2022

Abstract
Background
Several computational advances have been achieved in the drug discovery field, promoting the identification of novel drug–target interactions and new leads. However, most of these methodologies have been overlooking the importance of providing explanations to the decision-making process of deep learning architectures. In this research study, we explore the reliability of convolutional neural networks (CNNs) at identifying relevant regions for binding, specifically binding sites and motifs, and the significance of the deep representations extracted by providing explanations to the model’s decisions based on the identification of the input regions that contributed the most to the prediction. We make use of an end-to-end deep learning architecture to predict binding affinity, where CNNs are exploited in their capacity to automatically identify and extract discriminating deep representations from 1D sequential and structural data.

Results
The results demonstrate the effectiveness of the deep representations extracted from CNNs in the prediction of drug–target interactions. CNNs were found to identify and extract features from regions relevant for the interaction, where the weight associated with these spots was in the range of those with the highest positive influence given by the CNNs in the prediction. The end-to-end deep learning model achieved the highest performance both in the prediction of the binding affinity and on the ability to correctly distinguish the interaction strength rank order when compared to baseline approaches.

Conclusions
This research study validates the potential applicability of an end-to-end deep learning architecture in the context of drug discovery beyond the confined space of proteins and ligands with determined 3D structure. Furthermore, it shows the reliability of the deep representations extracted from the CNNs by providing explainability to the decision-making process.
A hierarchical spike-and-slab model for pan-cancer survival using pan-omic data
Authors: Samorodnitsky Sarah , Hoadley Katherine A. , Lock Eric F. 
Published: June 2022

Abstract
Background
Pan-omics, pan-cancer analysis has advanced our understanding of the molecular heterogeneity of cancer. However, such analyses have been limited in their ability to use information from multiple sources of data (e.g., omics platforms) and multiple sample sets (e.g., cancer types) to predict clinical outcomes. We address the issue of prediction across multiple high-dimensional sources of data and sample sets by using molecular patterns identified by BIDIFAC+, a method for integrative dimension reduction of bidimensionally-linked matrices, in a Bayesian hierarchical model. Our model performs variable selection through spike-and-slab priors that borrow information across clustered data. We use this model to predict overall patient survival from the Cancer Genome Atlas with data from 29 cancer types and 4 omics sources and use simulations to characterize the performance of the hierarchical spike-and-slab prior.

Results
We found that molecular patterns shared across all or most cancers were largely not predictive of survival. However, our model selected patterns unique to subsets of cancers that differentiate clinical tumor subtypes with markedly different survival outcomes. Some of these subtypes were previously established, such as subtypes of uterine corpus endometrial carcinoma, while others may be novel, such as subtypes within a set of kidney carcinomas. Through simulations, we found that the hierarchical spike-and-slab prior performs best in terms of variable selection accuracy and predictive power when borrowing information is advantageous, but also offers competitive performance when it is not.

Conclusions
We address the issue of prediction across multiple sources of data by using results from BIDIFAC+ in a Bayesian hierarchical model for overall patient survival. By incorporating spike-and-slab priors that borrow information across cancers, we identified molecular patterns that distinguish clinical tumor subtypes within a single cancer and within a group of cancers. We also corroborate the flexibility and performance of using spike-and-slab priors as a Bayesian variable selection approach.
Benchmarking imputation methods for network inference using a novel method of synthetic scRNA-seq data generation
Authors: Lasri Ayoub , Shahrezaei Vahid , Sturrock Marc 
Published: June 2022

AbstractBackgroundSingle cell RNA-sequencing (scRNA-seq) has very rapidly become the new workhorse of modern biology providing an unprecedented global view on cellular diversity and heterogeneity. In particular, the structure of gene-gene expression correlation contains information on the underlying gene regulatory networks. However, interpretation of scRNA-seq data is challenging due to specific experimental error and biases that are unique to this kind of data including drop-out (or technical zeros).MethodsTo deal with this problem several methods for imputation of zeros for scRNA-seq have been developed. However, it is not clear how these processing steps affect inference of genetic networks from single cell data. Here, we introduce Biomodelling.jl, a tool for generation of synthetic scRNA-seq data using multiscale modelling of stochastic gene regulatory networks in growing and dividing cells.ResultsOur tool produces realistic transcription data with a known ground truth network topology that can be used to benchmark different approaches for gene regulatory network inference. Using this tool we investigate the impact of different imputation methods on the performance of several network inference algorithms.ConclusionsBiomodelling.jl provides a versatile and useful tool for future development and benchmarking of network inference approaches using scRNA-seq data.
Genetic diversity and connectivity of chemosynthetic cold seep mussels from the U.S. Atlantic margin
Authors: DeLeo Danielle M. , Morrison Cheryl L. , Sei Makiri , Salamone Veronica , Demopoulos Amanda W. J. , Quattrini Andrea M. 
Published: June 2022

Abstract
Background
Deep-sea mussels in the subfamily Bathymodiolinae have unique adaptations to colonize hydrothermal-vent and cold-seep environments throughout the world ocean. These invertebrates function as important ecosystem engineers, creating heterogeneous habitat and promoting biodiversity in the deep sea. Despite their ecological significance, efforts to assess the diversity and connectivity of this group are extremely limited. Here, we present the first genomic-scale diversity assessments of the recently discovered bathymodioline cold-seep communities along the U.S. Atlantic margin, dominated by Gigantidas childressi and Bathymodiolus heckerae.

Results
A Restriction-site Associated DNA Sequencing (RADSeq) approach was used on 177 bathymodiolines to examine genetic diversity and population structure within and between seep sites. Assessments of genetic differentiation using single-nucleotide polymorphism (SNP) data revealed high gene flow among sites, with the shallower and more northern sites serving as source populations for deeper occurring G. childressi. No evidence was found for genetic diversification across depth in G. childressi, likely due to their high dispersal capabilities. Kinship analyses indicated a high degree of relatedness among individuals, and at least 10–20% of local recruits within a particular site. We also discovered candidate adaptive loci in G. childressi and B. heckerae that suggest differences in developmental processes and depth-related and metabolic adaptations to chemosynthetic environments.

Conclusions
These results highlight putative source communities for an important ecosystem engineer in the deep sea that may be considered in future conservation efforts. Our results also provide clues into species-specific adaptations that enable survival and potential speciation within chemosynthetic ecosystems.
Isolation of nematophagous fungi from soil samples collected from three different agro-ecologies of Ethiopia
Authors: Berhanu Maradona , Waktole Hika , Mamo Gezahegne , Terefe Getachew 
Published: June 2022

Abstract
Background
Several species of nematophagous fungi exist in nature that can capture and kill nematodes as natural predators of soil-dwelling worms. These are important in agriculture and animal husbandry as biological control agents. The diversity of nematophagous fungi found from soil had not been studied in Ethiopia.

Objective
This study aimed to isolate Nematophagous Fungi from Soil Samples Collected From three Different Agro-Ecologies of Ethiopia.

Methods
Cross-sectional study was conducted and samples were collected from three different agro-climatic zones of Ethiopia; Debre-Berhan (highland), Bishoftu (mid-altitude), and Awash (lowland). Twenty-seven soil samples were randomly taken from each of the three different agro-ecological climates (9 from each agro-ecological climatic zone). For each study site, samples were collected from the soil of decomposed animal feces/dung, agricultural/farmlands, and forest lands in triplicates.

Results
The present study disclosed that nematophagous fungi were widespread from the study area. A total of 33 species of nematophagous fungi belonging to four genera, Arthrobotryes, Paecilomyces, Monacrosporium, and Harposporium were identified. Arthrobotrys were the most commonly isolated genera followed by Paecilomyces. The six identified species were Arthrobotrys oligospora, Paecilomyces lilacinus, Arthrobotryes dactyloides, Monacosporum eudermatum, Harposporium helicoides, and Monacosporum cionopagum.

Conclusion
This study indicated that Arthrobothryes oligospora was the most common species in Bishoftu and Awash whereas. In Debre-Berhan, Paecilomyces lilacinus was the most prevalent species. Monacosporum cionapagum was not isolated from dung soil and agricultural soil whereas Harposporium helicoides and Arthrobothryes dactyloides were not found from dung and forest soil respectively.
Predictive value of LDL/HDL ratio in coronary atherosclerotic heart disease
Authors: Sun Ting , Chen Mengyun , Shen Huanhuan , PingYin  , Fan Li , Chen Xin , Wu Jun , Xu Zuojun , Zhang Junfeng 
Published: June 2022

Abstract
Background
Dyslipidemia is one of independent risk factors for coronary atherosclerotic heart disease (CAHD). We determined whether the LDL/HDL ratio is better than LDL-C or HDL-C alone in predicting the severity of CAHD.

Methods
We performed a retrospective study of 1351 patients with myocardial ischemia who underwent coronary angiography between January 2018 and December 2019 in Shanghai Ninth People’s Hospital. Spearman correlation analysis, logistic regression model, Cox proportional hazards model and multicollinearity were used to evaluate LDL/HDL ratio for predicting CAHD severity compared to LDL-C or HDL-C alone.

Results
Higher LDL/HDL ratio was seen in CAHD patients than controls (2.94 ± 1.06 vs 2.36 ± 0.78, P < 0.05). LDL/HDL ratio was significantly associated with the severity of coronary vascular stenosis. The area under the ROC curve of LDL-C, HDL-C, LDL/HDL ratio used to predict CAHD are 0.574 (95% CI 0.547–0.600, P < 0.001), 0.625 (95% CI 0.598–0.651, P < 0.001), 0.668 (95% CI 0.639–0.697, P = 0.000), respectively. The cut-off value of LDL/HDL ratio is 2.517, and the sensitivity and specificity are 65% and 61%, respectively. LDL/HDL ratio was related to the prevalence of CAHD and the odds ratio (OR) was 2.39 [95% confidence interval (CI) 1.698–2.593, P = 0.00] in multicollinearity regression model.

Conclusion
LDL/HDL ratio may become a better predictor of CAHD severity, compared to LDL-C or HDL-C.
Severe small intestinal bacterial overgrowth syndrome after jejunal feeding requiring surgical intervention: a case report and review of the literature
Authors: Aboona Majd B. , Wong Tina W. , Del Prado Paul R. , Paley Keith , Goldberg Ross F. , Weimer Samuel , Dave Harikrishna , Hobohm Dan , Smith Adam 
Published: June 2022

Abstract
Background
Small intestinal bacterial overgrowth (SIBO) is a condition of unknown prevalence characterized by an excessive amount of bacteria in the small bowel, typically resulting in vague gastrointestinal symptoms with bloating being most commonly reported. Here we describe a severe case of SIBO leading to small bowel necrosis requiring surgical intervention.

Case presentation
A 55-year-old Hispanic female with gastric outlet obstruction secondary to a newly diagnosed gastric adenocarcinoma, receiving neoadjuvant chemotherapy, developed bloody gastrostomy output and rapidly progressing nausea and abdominal distention 3 days after jejunostomy tube placement and initiation of jejunal enteral nutrition. Imaging revealed diffuse pneumatosis and portal venous gas. Surgical exploration confirmed segmental bowel necrosis requiring resection. Histologic findings were consistent with SIBO.

Conclusions
Presentation of severe SIBO in the setting of intestinal stasis secondary to gastric outlet after initiation of enteral feeds is a rare phenomenon. Early recognition and diagnosis of SIBO is critical in minimizing patient morbidity and mortality.