bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the strategies used by iranian nurses for management of provided care for patients with COVID- 19: a qualitative study
Authors: Varaei Shokoh , Caihong Zhang , Siqi Zhang , Mahmoodi Parvin , Rezaee Mehdi , Rezveh Ali Karimi , mirbazegh Seydeh fatemeh 
Published: March 2023

Abstract
Background
Nurses have been at the center of managing the COVID-19 outbreak through direct bedside care in respiratory, emergency and intensive care environments, managing hospital units, providing Covid-19 testing, vaccination and contact tracing. Thus, the present study aimed to analysis the strategies used by Iranian nurses for management of Provided Care for patients with COVID- 19.

Methods
The present study was conducted based on the conventional content analysis method and Graneheim & Lundman approach. The participants included the nurses working in the COVID-19 wards and were recruited by purposeful sampling and based on inclusion criteria. The data were collected by conducting semi-structured, in-depth, one-to-one interviews until reaching data saturation.

Results
In-depth interviews with 10 nurses represented four main categories and fifteen subcategories. Four main categories emerged in this study i.e. “justice in human resources management”, “The art and science of comprehensive nursing care”, “managers as agents of change in crisis” and “challenges and its management”.

Conclusion
The nurses’ experiences of management strategies showed that paying attention to the financial, psychological, educational, equipment needs of nurses and maintaining their safety make the suitable environment for providing high quality care for patients with covid-19.
The stromal-tumor amplifying STC1-Notch1 feedforward signal promotes the stemness of hepatocellular carcinoma
Authors: Bai Shuya , Zhao Yuchong , Chen Wei , Peng Wang , Wang Yun , Xiong Si , Aruna  , Li Yanling , Yang Yilei , Chen Shiru , Cheng Bin , Wang Ronghua 
Published: March 2023

Abstract
Background
Cancer-associated fibroblasts (CAFs), an important component of the tumor microenvironment (TME), play crucial roles in tumor stemness. It has been shown in various cancer studies that stanniocalcin-1 (STC1) is secreted by CAFs, however, its function in HCC is still not clear.

Methods
The serum concentration and intracellular expression level of STC1 were quantified by ELISA and western blotting, respectively. The role of CAF-derived STC1 in HCC stemness was investigated by sphere formation, sorafenib resistance, colony formation, and transwell migration and invasion assays in vitro and in an orthotopic liver xenograft model in vivo. An HCC tissue microarray containing 72 samples was used to evaluate the expression of STC1 and Notch1 in HCC tissues. Coimmunoprecipitation (CoIP) and dual-luciferase reporter assays were performed to further explore the underlying mechanisms. ELISAs were used to measure the serum concentration of STC1 in HCC patients.

Results
We demonstrated that CAFs were the main source of STC1 in HCC and that CAF-derived STC1 promoted HCC stemness through activation of the Notch signaling pathway. In HCC patients, the expression of STC1 was positively correlated with Notch1 expression and poor prognosis. The co-IP assay showed that STC1 directly bound to Notch1 receptors to activate the Notch signaling pathway, thereby promoting the stemness of HCC cells. Our data further demonstrated that STC1 was a direct transcriptional target of CSL in HCC cells. Furthermore, ELISA revealed that the serum STC1 concentration was higher in patients with advanced liver cancer than in patients with early liver cancer.

Conclusions
CAF-derived STC1 promoted HCC stemness via the Notch1 signaling pathway. STC1 might serve as a potential biomarker for the prognostic assessment of HCC, and the stromal-tumor amplifying STC1-Notch1 feedforward signal could constitute an effective therapeutic target for HCC patients.
Rapid non-destructive method to phenotype stomatal traits
Authors: Pathoumthong Phetdalaphone , Zhang Zhen , Roy Stuart J. , El Habti Abdeljalil 
Published: March 2023

Abstract
Background
Stomata are tiny pores on the leaf surface that are central to gas exchange. Stomatal number, size and aperture are key determinants of plant transpiration and photosynthesis, and variation in these traits can affect plant growth and productivity. Current methods to screen for stomatal phenotypes are tedious and not high throughput. This impedes research on stomatal biology and hinders efforts to develop resilient crops with optimised stomatal patterning. We have developed a rapid non-destructive method to phenotype stomatal traits in three crop species: wheat, rice and tomato.

Results
The method consists of two steps. The first is the non-destructive capture of images of the leaf surface from plants in their growing environment using a handheld microscope; a process that only takes a few seconds compared to minutes for other methods. The second is to analyse stomatal features using a machine learning model that automatically detects, counts and measures stomatal number, size and aperture. The accuracy of the machine learning model in detecting stomata ranged from 88 to 99%, depending on the species, with a high correlation between measures of number, size and aperture using the machine learning models and by measuring them manually. The rapid method was applied to quickly identify contrasting stomatal phenotypes.

Conclusions
We developed a method that combines rapid non-destructive imaging of leaf surfaces with automated image analysis. The method provides accurate data on stomatal features while significantly reducing time for data acquisition and analysis. It can be readily used to phenotype stomata in large populations in the field and in controlled environments.
VSFlow: an open-source ligand-based virtual screening tool
Authors: Jung Sascha , Vatheuer Helge , Czodrowski Paul 
Published: March 2023

AbstractLigand-based virtual screening is a widespread method in modern drug design. It allows for a rapid screening of large compound databases in order to identify similar structures. Here we report an open-source command line tool which includes a substructure-, fingerprint- and shape-based virtual screening. Most of the implemented features fully rely on the RDKit cheminformatics framework. VSFlow accepts a wide range of input file formats and is highly customizable. Additionally, a quick visualization of the screening results as pdf and/or pymol file is supported.
Graphical Abstract
Predicting oral cancer risk in patients with oral leukoplakia and oral lichenoid mucositis using machine learning
Authors: Adeoye John , Koohi-Moghadam Mohamad , Choi Siu-Wai , Zheng Li-Wu , Lo Anthony Wing Ip , Tsang Raymond King-Yin , Chow Velda Ling Yu , Akinshipo Abdulwarith , Thomson Peter , Su Yu-Xiong 
Published: March 2023

AbstractOral cancer may arise from oral leukoplakia and oral lichenoid mucositis (oral lichen planus and oral lichenoid lesions) subtypes of oral potentially malignant disorders. As not all patients will develop oral cancer in their lifetime, the availability of malignant transformation predictive platforms would assist in the individualized treatment planning and formulation of optimal follow-up regimens for these patients. Therefore, this study aims to compare and select optimal machine learning (ML)-based models for stratifying the malignant transformation status of patients with oral leukoplakia and oral lichenoid mucositis. One thousand one hundred and eighty-seven patients with oral leukoplakia and oral lichenoid mucositis treated at three tertiary health institutions in Hong Kong, Newcastle UK, and Lagos Nigeria were included in the study. Demographic, clinical, pathological, and treatment-based factors obtained at diagnosis and during follow-up were used to populate and compare forty-six machine learning-based models. These were implemented as a set of twenty-six predictors for centers with substantial data quantity and fifteen predictors for centers with insufficient data. Two best models were selected according to the number of variables. We found that the optimal ML-based risk models with twenty-six and fifteen predictors achieved an accuracy of 97% and 94% respectively following model testing. Upon external validation, both models achieved a sensitivity, specificity, and F1-score of 1, 0.88, and 0.67 on consecutive patients treated after the construction of the models. Furthermore, the 15-predictor ML model for centers with reduced data achieved a higher sensitivity for identifying oral leukoplakia and oral lichenoid mucositis patients that developed malignancies in other treatment settings compared to the binary oral epithelial dysplasia system for risk stratification (0.96 vs 0.82). These findings suggest that machine learning-based models could be useful potentially to stratify patients with oral leukoplakia and oral lichenoid mucositis according to their risk of malignant transformation in different settings.
Sustainable rural infrastructure: guidelines for roadside slope excavation
Authors: Paudyal Prabhat , Dahal Pranish , Bhandari Prakash , Dahal Bhim Kumar 
Published: March 2023

AbstractThe construction of non-engineered, equipment-based rural roads in Nepal Himalaya is one of the predominant causes of landslides. The construction frequency of such roads has significantly increased over the past decade. However, the present guidelines governing slope excavation for these roads are not based on geotechnical characterizations of sites. The current study uses the limit equilibrium method with the Mohr–Coulomb constitutive model to determine safe cut heights and slopes for varying geometric and material parameters. GeoStudio Slope/W was used to model soil slopes with various gradients, and cuts with varying depths and slope angles were modeled to calculate the factor of safety (FoS) against shear failure for different geometric and material conditions. The results of the study were visualized in design charts with FoS as the dependent variable. The analysis highlights the importance of different parameters, i.e., excavation depth, excavation slope, and existing ground slope in the FoS, in addition to the slope-forming material. Furthermore, a field study was carried out to validate the model using the clustering approach. The results from the field are similar to those from the numerical model, although some additional site-specific parameters like vegetation cover and surface runoff conditions should be considered before selecting the cut slope. Finally, this study proposes that future road construction guidelines should consider terrain parameters, hydrology, and geotechnical site conditions to promote sustainable road infrastructure and reduce future disaster risks in the Himalayan region.
Exploring equity, diversity, and inclusion in a simulation program using the SIM-EDI tool: the impact of a reflexive tool for simulation educators
Authors: Purdy Eve , Symon Ben , Marks Ruth-Ellen , Speirs Chris , Brazil Victoria 
Published: March 2023

Abstract
Background
There have been increasing calls for awareness and action related to equity, diversity, and inclusion (EDI) in simulation but a lack of practical guidance for how simulation delivery teams (SDTs) might move towards meaningful transformation. The gap between academic conversations about EDI and how to practically impact SDT attitudes, behaviors, and performance remains considerable. We designed a conversational tool, the SIM-EDI, to bridge the gap between theory and practice for SDTs by enhancing reflexivity and studied its impact locally.

Methods
We engaged in a collaborative autoethnography to explore EDI within our emergency department SDT shortly after implementing the SIM-EDI. The 12-month ethnography is informed by our team’s collection and analysis of data about ourselves and our own experiences using the tool. Data included serial interviews, field notes from simulations and SDT meetings, SDT documents, and self-reflections.

Results
We found the SIM-EDI tool could be implemented with a team with a high level of readiness. Use of the tool had several meaningful impacts including enhanced team reflexivity, normalization of conversations related to EDI and increased confidence to engage in EDI conversations with participants. Key themes throughout the process included (1) individual and team growth, (2) fear of “getting it wrong”, and (3) tension between bias towards action and need for slow reflection.

Conclusion
The SIM-EDI tool can effectively promote reflexivity among faculty in an emergency department simulation program. The tool is easy to use and implement, impacts attitudes and behaviors, and facilitates individual and team growth.
Development and validation of stability indicating HPLC–PDA method for the simultaneous determination of benzoyl peroxide and tretinoin in topical dosage form
Authors: Usman Muhammad , Abbas Tauqeer 
Published: March 2023

Abstract
Background
Acne vulgaris is a very dangerous skin disease leads to psychological disorders. Benzoyl peroxide and tretinoin in combination with topical dosage are used to improve the appearance of acne-prone skin. The study aimed to develop and validate an HPLC–PDA method for the simultaneous estimation of both drugs. Intentional modifications were implemented in the analytical method to get better optimum conditions. The final method was chosen for the reverse phase chromatographic separation by using the C18 column as a stationary phase and 0.01 M phosphate buffer adjusted pH 2.5 mixed with acetonitrile (25:75 v/v) as a mobile phase. The optimized conditions were 1.5 mL/min flow rate, 30 °C column temperature, 5 °C autosampler temperature, and 20 µL injection volume. The wavelength was chosen for detection of Benzoyl peroxide at 272 nm and Tretinoin at 353 nm by utilizing a PDA detector. All standard and sample solutions were made in methanol.

Results
The developed method exhibited peak retention times of 2.94 min for Benzoyl peroxide and 11.34 min for Tretinoin. This analytical method was proven to be robust, linear in calibration curve, accurate, precise, and specific. The forced degradation studies results showed that a high degree of specificity was obtained by separating both analytes from produced impurities completely.

Conclusions
The developed analytical method is fast, economic and stability indicating. It is useful for routine pharmaceutical analysis where the combination of benzoyl peroxide and tretinoin is formulated for their quality and safety.
Live-cell tracking of γ-H2AX kinetics reveals the distinct modes of ATM and DNA-PK in the immediate response to DNA damage
Authors: Trakarnphornsombat Watanya , Kimura Hiroshi 
Published: March 2023

ABSTRACT
DNA double-strand breaks (DSBs) are a serious form of DNA damage that can cause genetic mutation. On the induction of DSBs, histone H2AX becomes phosphorylated by kinases, including ataxia telangiectasia-mutated (ATM), ataxia telangiectasia and Rad3-related (ATR) and DNA-dependent protein kinase (DNA-PK). Phosphorylated H2AX (γ-H2AX) can be a platform to recruit DNA repair machinery. Here, we analyzed the immediate early kinetics of γ-H2AX upon laser-induced DNA damage in ATM-proficient and -deficient living cells by using fluorescently labeled antigen-binding fragments specific for γ-H2AX. The accumulation kinetics of γ-H2AX were similar in both ATM-proficient and -deficient cells. However, γ-H2AX accumulation was delayed when the cells were treated with a DNA-PK inhibitor, suggesting that DNA-PK rapidly phosphorylates H2AX at DSB sites. Ku80 (also known as XRCC5), a DNA-PK subunit, diffuses freely in the nucleus without DNA damage, whereas ATM repeatedly binds to and dissociates from chromatin. The accumulation of ATM at damage sites was regulated by the histone H4K16 acetyltransferase MOF (also known as KAT8 in mammals), but its accumulation was not necessarily reflected in the γ-H2AX level. These results suggest distinct actions of ATM and DNA-PK in immediate γ-H2AX accumulation.
Effects of deep learning on radiologists’ and radiology residents’ performance in identifying esophageal cancer on CT
Authors: Yasaka Koichiro , Hatano Sosuke , Mizuki Masumi , Okimoto Naomasa , Kubo Takatoshi , Shibata Eisuke , Watadani Takeyuki , Abe Osamu 
Published: March 2023

Objective:
To investigate the effectiveness of a deep learning model in helping radiologists or radiology residents detect esophageal cancer on contrast-enhanced CT images.

Methods:
This retrospective study included 250 and 25 patients with and without esophageal cancer, respectively, who underwent contrast-enhanced CT between December 2014 and May 2021 (mean age, 67.9 ± 10.3 years; 233 men). A deep learning model was developed using data from 200 and 25 patients with esophageal cancer as training and validation data sets, respectively. The model was then applied to the test data set, consisting of additional 25 and 25 patients with and without esophageal cancer, respectively. Four readers (one radiologist and three radiology residents) independently registered the likelihood of malignant lesions using a 3-point scale in the test data set. After the scorings were completed, the readers were allowed to reference to the deep learning model results and modify their scores, when necessary.

Results:
The area under the curve (AUC) of the deep learning model was 0.95 and 0.98 in the image- and patient-based analyses, respectively. By referencing to the deep learning model results, the AUCs for the readers were improved from 0.96/0.93/0.96/0.93 to 0.97/0.95/0.99/0.96 (p = 0.100/0.006/&lt;0.001/&lt;0.001, DeLong’s test) in the image-based analysis, with statistically significant differences noted for the three less-experienced readers. Furthermore, the AUCs for the readers tended to improve from 0.98/0.96/0.98/0.94 to 1.00/1.00/1.00/1.00 (p = 0.317/0.149/0.317/0.073, DeLong’s test) in the patient-based analysis.

Conclusion:
The deep learning model mainly helped less-experienced readers improve their performance in detecting esophageal cancer on contrast-enhanced CT.

Advances in knowledge:
A deep learning model could mainly help less-experienced readers to detect esophageal cancer by improving their diagnostic confidence and diagnostic performance.
How can policy and policymaking foster climate justice? A qualitative systematic review
Authors: Cairney Paul , Timonina Irina , Stephan Hannes 
Published: March 2023

Background: Climate change research has established a clear requirement for policy and policymaking: (1) transformational changes in policy and policymaking to foster (2) ‘climate justice’, including a ‘just transition’ (a movement towards environmental sustainability with equitable processes and outcomes). However, there is a major gap between these requirements and actual policies and policy processes. We identify how researchers use policy theories to understand this gap. Methods: We conducted a qualitative systematic review (2022) to identify peer reviewed journal articles on climate change, policy, justice, and equity in three databases (Web of Science, Scopus, Proquest). Each article had to provide a non-trivial reference to policymaking. We used an immersive and inductive approach to identify key themes and show how the use of policy theories informs climate change research. Results: A total of 108 texts meet the inclusion criteria (with some bias towards Global North research since all texts are in English). Most provide general definitions of climate justice, require fair outcomes and processes, and list what is required to meet those aims. However, they also identify unjust processes and outcomes in relation to who is recognised, gets to define the problem, and wins or loses from solutions. Researchers contrast their preferred social justice approach (informing ‘civic environmentalism) to a dominant neoliberal approach (corresponding to weak ‘ecological modernization’). Conclusions: Researchers focus on what they need from policy and policymaking to produce climate justice. Few engage meaningfully with policy theories to describe how policymaking actually works. More engagement would help to set meaningful expectations regarding policy change and avoid a needless tendency to treat policymaking like a ‘black box’.
Expectations and human rights protection: the case of Vietnam during COVID-19
Authors: Doan Hai , Nie Jing-Bao 
Published: March 2023

Background: A key part of the complexity of actual social life lies in the fact that it operates on a large web of not only prescribed norms and rules, but also explicit and especially implicit expectations which constantly interact with each other. Methods: This paper offers the first in-depth study on ‘expectations’ in bioethical and health law studies, taking Vietnamese human rights issues in response to coronavirus disease (COVID-19) as illustrations. It defines ‘expectations’ as normative imaginaries that can induce or guide actions and inactions at individual and collective levels. Results: The study suggests that ‘expectations’ is a fruitful concept for bioethical and health law studies because it helps better understand the complexity of interactions in society and patterns of thinking and acting of actors in real-world contexts. Studying expectations also has implications for how human rights and other ethical norms can be better realized in practice. From applying the concept of ‘expectations’ to study human rights issues in Vietnam, this paper also argues that for better protection of human rights, there must be changes concerning expectations of involved parties. Conclusions: Changes in expectations in turn call for changes in stimulus, knowledge, praxis, polices, laws and institutions. Meanwhile, checks and balances mechanisms must effectively constrain the materialization of undue expectations.
Utility of MALDI-TOF MS for determination of species identity and blood meal sources of primary malaria vectors on the Kenyan coast
Authors: Karisa Jonathan , Ominde Kelly , Tuwei Mercy , Bartilol Brian , Ondieki Zedekiah , Musani Harun , Wanjiku Caroline , Mwikali Kioko , Babu Lawrence , Rono Martin , Eminov Mumin , Mbogo Charles , Bejon Philip , Mwangangi Joseph , Laroche Maureen , Maia Marta 
Published: March 2023

Background: Protein analysis using matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry (MALDI-TOF MS) represents a promising tool for entomological surveillance. In this study we tested the discriminative power of this tool for measuring species and blood meal source of main Afrotropical malaria vectors on the Kenyan coast. Methods: Mosquito collections were conducted along the coastal region of Kenya. MALDI-TOF MS spectra were obtained from each individual mosquito’s cephalothorax as well as the abdomens of blood-engorged mosquitoes. The same mosquitoes were also processed using gold standard tests: polymerase chain reaction (PCR) for species identification and enzyme linked immunosorbent assay (ELISA) for blood meal source identification. Results: Of the 2,332 mosquitoes subjected to MALDI-TOF MS, 85% (1,971/2,332) were considered for database creation and validation. There was an overall accuracy of 97.5% in the identification of members of the An. gambiae (An. gambiae, 100%; An. arabiensis, 91.9%; An. merus, 97.5%; and An. quadriannulatus, 90.2%) and An. funestus (An. funestus, 94.2%; An. rivulorum, 99.4%; and An. leesoni, 94.1%) complexes. Furthermore, MALDI-TOF MS also provided accurate (94.5% accuracy) identification of blood host sources across all mosquito species. Conclusions: This study provides further evidence of the discriminative power of MALDI-TOF MS to identify sibling species and blood meal source of Afrotropical malaria vectors, further supporting its utility in entomological surveillance. The low cost per sample (<0.2USD) and high throughput nature of the method represents a cost-effective alternative to molecular methods and could enable programs to increase the number of samples analysed and therefore improve the data generated from surveillance activities.