bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Gamma-Irradiation on Electrochemical Properties of Nicos for Supercapacitor Application
Authors: Marashdeh Mohammad W. , Aljaafreh Mamduh J. , Al-Mazaideh Ghassab M. , Akhdar Hanan , Alakhras Abbas I. , Alhamarneh Ibrahim F.
Published: May 2024

We used an elementary hydrothermal approach to create this NiCoS nanohybrid. Analysis using X-ray diffraction (XRD) verified that the creation of this nanomaterial was successful. The material underwent cyclic voltammetry (CV), galvanostatic charge-discharge (GCD), testing in preparation
for its use as a supercapacitor electrode. The innovative aspect of this work was researching how electrodes’ supercapacitor qualities were affected by gamma-irradiation with an average energy of 1.25 MeV. The manufactured samples endured gamma radiation exposure with 5, 10, 15, 25,
and 50 kGy dosages. Following 5000 consecutive cycles, the sample subjected to the most significant dose of gamma radiation exhibited the lowest charge transfer resistance, maximum stability, and highest specific capacity of 253 Cg−1. Compared to the non-irradiation sample,
the gamma-ray exposed NiCoS (50 kGy) had an 85 s longer discharge duration at a current density of 0.1 Ag−1. These data indicate that gamma radiation has a positive influence on electrode performance rather than a negative one. For this reason, NiCoS may be used as an electrode
material for gamma radiation medium supercapacitors.
Investigation of AC and DC Electrical Conductivity in Ethyl Cellulose (EC) and Poly Methyl Methacrylate (PMMA) Polyblends
Authors: Sirtawar Kajal , Lamdhade Gajanan , Raulkar Kishor , Alqaed Saeed , Mustafa Jawed , Husain Shahid
Published: May 2024

The study of AC and DC electrical conductivity is crucial for understanding the behavior of charge carriers within materials and their mobility. Ethyl cellulose (EC) stands out among cellulose ethers due to its favorable electrical, mechanical, and weathering properties. Poly Methyl
Methacrylate (PMMA) is a thermoplastic known for its rigidity, transparency, and outdoor durability, making it a valuable material. Despite being insulating materials, both EC and PMMA exhibit limited free charge carriers and low mobility. In this research, AC and DC electrical properties
of Ethyl Cellulose (EC), Poly Methyl Methacrylate (PMMA), and their blends doped with tetrahydrofuran (THF) film were investigated using isothermal evaporation techniques. The investigation focused on the effects of temperature, electric field, and frequency on electrical conduction mechanisms.
Measurements were conducted across frequencies ranging from 1 KHz to 1 MHz at temperatures between 323 K and 373 K. Results indicate that AC electrical conductivity of Ethyl Cellulose (EC), Poly Methyl Methacrylate (PMMA), and their blend (EC/PMMA) increases with higher frequencies of the
applied electric field. Meanwhile, DC electrical conductivity of Ethyl Cellulose (EC), Poly Methyl Methacrylate (PMMA), and their blend (EC/PMMA) rises with increasing temperature. X-ray diffraction (XRD) analysis further supports these conductivity changes in the blend.
Physics-based modeling of the effective gas transport properties of single jersey knitted fabrics based on images
Authors: Pauly Leon , Maier Lukas , Nieken Ulrich , Gresser Goetz Theodor
Published: May 2024

In many processes and applications, the performance of textiles relies heavily on fluid transport; for example, the in-plane distribution of water and the through-plane permeation of water vapor and air. Prediction of knitted fabrics’ effective transport characteristics can enhance development workflows and bring them to new applications. Effective transport parameters that are particularly important are the permeability and diffusive mass transfer. Usually, experiments are used to determine these parameters. It is desirable to conduct a thorough investigation into how yarn structure and knitting gauge influence these properties to tailor knitted fabrics for a particular application. Our contribution in this context describes a consistent workflow to forecast the effective mass transfer characteristics of single jersey fabrics. Single jersey fabrics have been chosen for they are the simplest patterning, and are widely used in body-near worn garments. The proposed approach involves visualizing fabric samples with a light microscope, and subsequently determining relevant geometric parameters through automated image processing algorithms. With these parameters in hand, a representative elementary volume of the fabric is constructed. The yarn is modeled as an effective medium to reduce calculation time. The representative elementary volume is then used for numerical predictions of air permeability and the diffusive water vapor transport. The predicted through-plane gas transport properties are compared with experimental data to validate the approach. Six different single jersey polyester fabrics were analyzed, with different yarn structures and machine gauges. The comparison shows a good agreement between simulated and measured transport properties.
Assessing the Differentiated Impacts of COVID-19 on the Immigration Flows to Europe
Authors: González-Leonardo Miguel , Rowe Francisco , Potančoková Michaela , Goujon Anne
Published: May 2024

The immediate effects of COVID-19 on mortality, fertility, and internal and international migration have been widely studied. Particularly, immigration to high-income countries declined in 2020. However, the persistence of these declines and the extent to which they have impacted different migration flows are yet to be established. Drawing on immigration flows from Eurostat and Autoregressive Integrated Moving Average (ARIMA) time-series models, we assess the impact of COVID-19 on different immigration streams to seven European countries. We forecast counterfactual levels of immigration in 2020 and 2021 assuming no pandemic, and compare these estimates with actual immigration counts. We use regression modeling to explore the role of immigrants’ origin, distance, stringency measures, and gross domestic product (GDP) trends at origins and destinations as potential driving forces of changes in immigration during COVID-19. Our results show that, while there was a general decline in immigration during 2020, inflows returned to expected levels in 2021, except for Spain. However, drops in immigration flows from countries outside the Schengen Area to Europe persisted in 2021. Immigrants’ origin emerged as the main factor modulating immigration changes during the pandemic, and to a lesser extent stringency measures and GDP trends in destination countries. Contextual factors at origin seem to have been less important.
School effectiveness and leadership styles: The case of the holistic leadership model in Greece
Authors: Gkoros Dimitrios , Sakellariou Maria
Published: May 2024

The main question regarding school effectiveness has to do with those factors that influence student's academic performance. One of these factors is the leadership style adopted by school principals. This article investigates whether the Holistic Leadership Model is valid in the Greek context and what is the most commonly used leadership style by the principals of the effective schools. School effectiveness, student academic performance, and the effect of educational leadership on them occupy a central place in the literature review. Additionally, the Holistic Leadership Model, which is appropriated by this research effort, holds a dominant position. By employing quantitative modes of inquiry and a significant number of questionnaires, we concluded that the Holistic Leadership Model is valid in the Greek context and that the Structuring leadership style is the most frequently utilized in the effective schools of the sample.
Return to reality: What does the world ask of us?
Authors: Bøe Tore Dag , Bertelsen Bård , Sundet Rolf , Hillesund Odd Kenneth , Lidbom Per Arne
Published: May 2024

This article introduces the project Return to Reality: What Does the World Ask of Us? This project evolved from a concern that frameworks in mental health operate with knowledge as their primary mode in such a way that reality is lost from sight. This is not primarily an epistemological problem, but an ethical and existential one: ethical because a knowledge-mediated relation to the real can make us blind to the ethical imperatives found in encounters with reality; existential because to be a subject is to respond to what is real. The works of Gert Biesta are a key inspiration. We use Levinas’s, Lingis’s, and Arendt’s ideas to elaborate these concerns. A return to reality is needed; a shift from knowledge-based to reality-sensitive approaches. We relate these ideas to the Open Dialogue approach, with the key imperative of responding to the presence of those present, and to Reflecting team practices, which Tom Andersen describes as being guided by people’s bodily responses.
Sample size and power calculation for testing treatment effect heterogeneity in cluster randomized crossover designs
Authors: Wang Xueqi , Chen Xinyuan , Goldfeld Keith S , Taljaard Monica , Li Fan
Published: May 2024

The cluster randomized crossover design has been proposed to improve efficiency over the traditional parallel-arm cluster randomized design. While statistical methods have been developed for designing cluster randomized crossover trials, they have exclusively focused on testing the overall average treatment effect, with little attention to differential treatment effects across subpopulations. Recently, interest has grown in understanding whether treatment effects may vary across pre-specified patient subpopulations, such as those defined by demographic or clinical characteristics. In this article, we consider the two-treatment two-period cluster randomized crossover design under either a cross-sectional or closed-cohort sampling scheme, where it is of interest to detect the heterogeneity of treatment effect via an interaction test. Assuming a patterned correlation structure for both the covariate and the outcome, we derive new sample size formulas for testing the heterogeneity of treatment effect with continuous outcomes based on linear mixed models. Our formulas also address unequal cluster sizes and therefore allow us to analytically assess the impact of unequal cluster sizes on the power of the interaction test in cluster randomized crossover designs. We conduct simulations to confirm the accuracy of the proposed methods, and illustrate their application in two real cluster randomized crossover trials.
Phase-field damage simulation of subloop loading in TiNi SMA
Authors: Dunić Vladimir , Matsui Ryosuke , Takeda Kohei , Živković Miroslav
Published: May 2024

In practical applications, TiNi shape memory alloys (SMAs) exhibit behavior that can pose a challenge with current constitutive models and their implementations in finite element method (FEM) software. TiNi SMA devices typically operate in the forward or reverse martensitic transformation regime, which is known as subloop loading. During such cyclic loading–unloading, the hysteresis stress–strain loop changes because of material damage, which can be considered the fatigue of TiNi SMAs. During both the loading and unloading processes, the stress plateau decreases. At the same time, the accumulated (residual) martensitic transformation strain increases. In this study, the experimental investigation results and observations of the aforementioned phenomena are presented. Next, the phase-field damage model is employed, along with a modified Lagoudas constitutive model, to simulate the change in stress–strain hysteresis. Furthermore, a fatigue function is used to simulate the accumulation of martensitic transformation strain. The experimental stress–strain response is compared with the simulation results, and good quantitative and qualitative agreement is obtained. The damage and martensitic volume fraction with respect to strain are discussed for full-loop and subloop loading. The observations and conclusions, as well as open questions, are presented. Possible directions for future research are provided.
Enhancing the acoustic emission technique using fuzzy artificial bee colony-based deep learning for characterizing selective laser melted AlSi10Mg specimens
Authors: Barile Claudia , Casavola Caterina , Katamba Mpoyi Dany , Pappalettera Giovanni , Kannan Vimalathithan Paramsamy
Published: May 2024

This article presents a classification of Acoustic Emission (AE) signals from AlSi10Mg specimens produced via Selective Laser Melting (SLM). Tensile tests characterized the mechanical properties of specimens printed in different orientations (X, Y, Z, 45°). Initially, a study quantified damage modes based on the stress-strain curve and cumulative AE energy. AE signals for each specimen (X, Y, 45°, Z), across deformation stages (elastic and plastic), and damage modes were analyzed using continuous wavelet transform to extract time-frequency features. A novel convolutional neural network, based on artificial bee colonies and fuzzy C-means, was developed for scalogram classification. Data augmentation with Gaussian white noise enhanced the approach. Cross-validation ensured robustness against overfitting and suboptimal local maxima. Evaluation metrics, including the confusion matrix, precision-recall curve, and F1 score, demonstrated the algorithm's high accuracy of 92.6%, precision-recall curve of 92.5%, and F1 score of 92.5% for AE signals based on printing direction (X, Y, 45°, Z). The study highlighted the potential for improving AE signal classification related to elastic and plastic deformation stages with 100% accuracy. For damage modes, the algorithm achieved a confusion matrix accuracy of 90.6%, a precision-recall curve of 90.4%, and an F1 score of 90.5%. This approach demonstrates high accuracy in classifying AE signals across different printing orientations, deformation stages, and damage modes of AlSi10Mg specimens manufactured through SLM.
Advancing Health Equity Through Artificial Intelligence: An Educational Framework for Preparing Nurses in Clinical Practice and Research
Authors: Cary Michael P. , De Gagne Jennie C. , Kauschinger Elaine D. , Carter Brigit M.
Published: May 2024

The integration of artificial intelligence (AI) into health care offers the potential to enhance patient care, improve diagnostic precision, and broaden access to health-care services. Nurses, positioned at the forefront of patient care, play a pivotal role in utilizing AI to foster a more efficient and equitable health-care system. However, to fulfil this role, nurses will require education that prepares them with the necessary skills and knowledge for the effective and ethical application of AI. This article proposes a framework for nurses which includes AI principles, skills, competencies, and curriculum development focused on the practical use of AI, with an emphasis on care that aims to achieve health equity. By adopting this educational framework, nurses will be prepared to make substantial contributions to reducing health disparities and fostering a health-care system that is more efficient and equitable.
Quantitative detection of typical bridge surface damages based on global attention mechanism and YOLOv7 network
Authors: Ni You-Hao , Wang Hao , Mao Jian-Xiao , Xi Zhuo , Chen Zhen-Yi
Published: May 2024

Surface damages of reinforced concrete and steel bridges, for example, crack and corrosion, are usually regarded as indicators of internal structural defects, hence can be used to assess the structural health condition. Quantitative segmentation of these surface damages via computer vision is important yet challenging due to the limited accuracy of traditional semantic segmentation methods. To overcome this challenge, this study proposes a modified semantic segmentation method that can distinguish multiple surface damages, based on you only look once version 7 (YOLOv7) and global attention mechanism (GAM), namely, YOLOv7-SEG-GAM. Initially, the extended efficient layer aggregation network in the backbone network of YOLOv7 was substituted with GAM, followed by the integration of a segmentation head utilizing the three-scale feature map, thus establishing a segmentation network. Subsequently, graphical examples depicting five types of reinforced concrete and steel bridge surface damages, that is, concrete cracks, steel corrosion, exposed rebar, spalling, and efflorescence, are gathered and meticulously labeled to create a semantic segmentation dataset tailored for training the network. Afterwards, a comparative study is undertaken to analyze the effectiveness of GAM, squeeze-and-excitation networks, and convolutional block attention module in enhancing the network’s performance. Ultimately, a calibration device was developed utilizing a laser rangefinder and a smartphone to enable quantitative assessment of bridge damages in real size. Based on the identical dataset, the evaluated accuracy of YOLOv7-SEG-GAM was compared with DeepLabV3+, BiSeNet, and improved semantic segmentation networks. The results indicate that the mean pixel accuracy and mean intersection over union values achieved by YOLOv7-SEG-GAM were 0.881 and 0.782, respectively, surpassing those of DeepLabV3+ and BiSeNet. This study successfully enables pixel-level segmentation of bridge damages and offers valuable insights for quantitative segmentation.
In Vivo Anti-Hepatocellular Carcinoma Effects of the Chloroform Root Extract of Clausena excavata Burm
Authors: Waziri Peter , Auta Richard , Imam Mustapha U , Chindo Ben A , Ladan Zakari , Mohammed Zainab , Wayah Samson , Mohammed Ja'afar , Tahir Mohammed I , Ahmad Abdurrahman E , Alhassan Yusuf , Tyoapine Daniel , Agbaji Abel S
Published: May 2024

Liver cancer is the most common cancer among males in Africa. The disease has a poor prognosis and its treatment is associated with toxicity and resistance. For this reason, numerous herbal combinations are being subjected to anticancer screening to circumvent the shortcomings of the conventional anticancer drugs. In the current study, the in vivo anti-cancer effects of the chloroform root extract of the herb, Clausena excavata Burm were investigated. Liver cancer was induced in mice by a single intraperitoneal injection of diethylnitrosamine (DEN) followed by oral administration of the promoter of carcinogenesis, 2-aminoacetyl fluorine that was mixed with the mice feed. The cytotoxicity of the root extract of C. excavata on liver cancer cells was investigated using liver enzyme, histology, DNA fragmentation and caspases assays. Real time qPCR was conducted to evaluate the effect of the extract on apoptotic genes. The findings revealed that the extract of C. excavata significantly decreased the progression of hepatocarcinogenesis and the toxicity-induced production of the liver enzymes, alanine and aspartate aminotransferases. The histological analyses of the liver tissues revealed evidence of apoptotic cell death. The extract also provoked significant ( p < .05) expressions of caspase 9 protein and gene as well as other apoptotic genes (P53, P27, Apaf-1, cytochrome C, bax and bid). Therefore, we postulate that the chloroform root extract of C. excavata induces apoptosis of liver cancer in mice.
Getting cozy with causality: Advances to the causal pathway diagramming method to enhance implementation precision
Authors: Klasnja Predrag , Meza Rosemary D. , Pullmann Michael D. , Mettert Kayne D. , Hawkes Rene , Palazzo Lorella , Weiner Bryan J. , Lewis Cara C.
Published: May 2024

Background

Implementation strategies are theorized to work well when carefully matched to implementation determinants and when factors—preconditions, moderators, etc.—that influence strategy effectiveness are prospectively identified and addressed. Existing methods for strategy selection are either imprecise or require significant technical expertise and resources, undermining their utility. This article outlines refinements to causal pathway diagrams (CPDs), a method for articulating the causal process through which implementation strategies work and offers illustrations of their use.

Method

CPDs are a visualization tool to represent an implementation strategy, its mechanism(s) (i.e., the processes through which a strategy is thought to operate), determinants it is intended to address, factors that may impede or facilitate its effectiveness, and the series of outcomes that should be expected if the strategy is operating as intended. We offer principles for constructing CPDs and describe their key functions.

Results

Applications of the CPD method by study teams from two National Institute of Health-funded Implementation Science Centers and a research grant are presented. These include the use of CPDs to (a) match implementation strategies to determinants, (b) understand the conditions under which an implementation strategy works, and (c) develop causal theories of implementation strategies.

Conclusions

CPDs offer a novel method for implementers to select, understand, and improve the effectiveness of implementation strategies. They make explicit theoretical assumptions about strategy operation while supporting practical planning. Early applications have led to method refinements and guidance for the field.
Lifeworld transformations in digital capitalism
Authors: Bilić Paško
Published: May 2024

This article addresses how digitalisation has altered our world from a critical political economy perspective. It grapples with the increasing perception of technological control and dominance and argues for renewed attention to the lifeworld concept transformed by technology and capital. It proposes an analytical distinction between the ‘concrete lifeworld’ and the ‘abstract lifeworld’ to capture the nuances of contemporary technologically mediated experience in the digital society.
InGaN blue resonant cavity micro-LED with RGY quantum dot layer for broad gamut, efficient displays
Authors: Lee Tzu-Yi , Huang Chien-Chi , Hung Yu-Ying , Chen Fang-Chung , Hong Yu-Heng , Kuo Hao-Chung
Published: May 2024

The technology of RGBY micro resonant cavity light emitting diodes (micro-RCLEDs) based on quantum dots (QDs) is considered one of the most promising approaches for full-color displays. In this work, we propose a novel structure combining a high color conversion efficiency (CCE) QD photoresist (QDPR) color conversion layer (CCL) with blue light micro RCLEDs, incorporating an ultra-thin yellow color filter. The additional TiO2 particles inside the QDPR CCL can scatter light and disperse QDs, thus reducing the self-aggregation phenomenon and enhancing the eventual illumination uniformity. Considering the blue light leakage, the influences of adding different color filters are investigated by illumination design software. Finally, the introduction of low-temperature atomic layer deposition (ALD) passivation protection technology at the top of the CCL can enhance the device's reliability. The introduction of RGBY four-color subpixels provides a viable path for developing low-energy consumption, high uniformity, and efficient color conversion displays.
VCF2PCACluster: a simple, fast and memory-efficient tool for principal component analysis of tens of millions of SNPs
Authors: He Weiming , Xu Lian , Wang JingXian , Yue Zhen , Jing Yi , Tai Shuaishuai , Yang Jian , Fang Xiaodong
Published: May 2024

Principal component analysis (PCA) is an important and widely used unsupervised learning method that determines population structure based on genetic variation. Genome sequencing of thousands of individuals usually generate tens of millions of SNPs, making it challenging for PCA analysis and interpretation. Here we present VCF2PCACluster, a simple, fast and memory-efficient tool for Kinship estimation, PCA and clustering analysis, and visualization based on VCF formatted SNPs. We implemented five Kinship estimation methods and three clustering methods for its users to choose from. Moreover, unlike other PCA tools, VCF2PCACluster possesses a clustering function based on PCA result, which enabling users to automatically and clearly know about population structure. We demonstrated the same accuracy but a higher performance of this tool in performing PCA analysis on tens of millions of SNPs compared to another popular PLINK2 software, especially in peak memory usage that is independent of the number of SNPs in VCF2PCACluster.
My anesthesia Choice-HF: development and preliminary testing of a tool to facilitate conversations about anesthesia for hip fracture surgery
Authors: Neuman Mark D. , Elwyn Glyn , Graff Veena , Schmitz Viktoria , Politi Mary C.
Published: May 2024

Background

Patients often desire involvement in anesthesia decisions, yet clinicians rarely explain anesthesia options or elicit preferences. We developed My Anesthesia Choice-Hip Fracture, a conversation aid about anesthesia options for hip fracture surgery and tested its preliminary efficacy and acceptability.

Methods

We developed a 1-page, tabular format, plain-language conversation aid with feedback from anesthesiologists, decision scientists, and community advisors. We conducted an online survey of English-speaking adults aged 50 and older. Participants imagined choosing between spinal and general anesthesia for hip fracture surgery. Before and after viewing the aid, participants answered a series of questions regarding key outcomes, including decisional conflict, knowledge about anesthesia options, and acceptability of the aid.

Results

Of 364/409 valid respondents, mean age was 64 (SD 8.9) and 59% were female. The proportion indicating decisional conflict decreased after reviewing the aid (63–34%, P < 0.001). Median knowledge scores increased from 50% correct to 67% correct (P < 0.001). 83% agreed that the aid would help them discuss options and preferences. 76.4% would approve of doctors using it.

Conclusion

My Anesthesia Choice-Hip Fracture decreased decisional conflict and increased knowledge about anesthesia choices for hip fracture surgery. Respondents assessed it as acceptable for use in clinical settings.

Practice implications

Use of clinical decision aids may increase shared decision-making; further testing is warranted.
Measuring the effects of nurse-led frailty intervention on community-dwelling older people in Ethiopia: a quasi-experimental study
Authors: Kasa Ayele Semachew , Traynor Victoria , Drury Peta
Published: May 2024

Background

Despite the critical need, interventions aimed at frailty in sub-Saharan Africa are scarce, attributed to factors such as insufficient healthcare infrastructure, the pressing need to address infectious diseases, maternal and child health issues, and a general lack of awareness. Hence, the aim of this research was to develop, implement, and evaluate the effect of a nurse-led program on frailty and associated health outcomes in community-dwelling older individuals in Ethiopia.

Methods

This study utilised a pre-test, post-test, and follow-up single-group quasi-experimental design. The main outcome measure was to determine changes in the frailty levels of older individuals living in communities at three different intervals: initially (T0), immediately after the intervention (T1), and 12 weeks following the intervention (T2). Secondary outcomes were the observed changes in daily living activities, nutritional status, depression levels, and quality of life (QOL), evaluated at each of these data collection points. To analyse changes in frailty and response variables over these periods, Friedman’s ANOVA and Cochran’s Q test were employed, setting the threshold for statistical significance at P < 0.05.

Results

Sixty-six older people with a high adherence rate of 97% completed the intervention and the follow-up measurements. Participants had an average age of 66.7 ± 7.9 years, with females comprising 79.4% of the group. Notably, 12 weeks post-intervention, there was a marked decrease in frailty (χ2(2) = 101.05, p < 0.001) and depression scores (χ2(2) = 9.55, p = 0.008) compared to the baseline. However, the changes in depression, physical, mental, and environmental domains of QOL were not sustained for 12 weeks post-intervention. Study participants showed an improvement in nutritional status (χ2(2) = 25.68, p < 0.001), activity of daily living (χ2(2) = 6.00, p = 0.05), and global quality of life (χ2(2) = 20.64, p < 0.001).

Conclusions

The nurse-led intervention notably, 12 weeks post-intervention reduced frailty and depression. The intervention improved the nutritional status and some components of the quality of life of the participants. There is a need for further studies, especially with larger participant groups and stronger research designs such as randomized controlled trials (RCTs).

Trial registration

ClinicalTrials.gov: NCT05754398 (03/03/2023).
Attitudes towards seeking psychological help among community dwelling older adults enrolled in primary care in Chile
Authors: Moreno Ximena , Moreno Francisco
Published: May 2024

Background

Depression and anxiety are common mental disorders among older adults, but they are frequently underdiagnosed. Attitudes towards seeking professional mental health care is one of the barriers to access to treatment. This study was aimed at assessing the attitudes towards seeking psychological help among older adults who are enrolled in primary care in Chile, and to determine the associated factors.

Methods

This cross-sectional study recruited 233 primary care users aged 65 or more years. The Attitudes Towards Seeking Professional Psychological Help was used. Reliability and factor analysis of this scale were carried out. The average scores of the scale and factors were calculated and compared, by selected variables. Multivariate linear regression was estimated to determine factors associated with attitudes towards seeking psychological help.

Results

Three factors were identified in the attitudes towards seeking psychological help: confidence in psychologists, coping alone with emotional problems, and predisposition to seek psychological help. On average, participants had a favorable attitude towards seeking psychological help, compared with previous research. Lower level of education, and risk of social isolation were inversely associated with these attitudes.

Conclusion

Strategies to improve mental health literacy and social connection among older adults, could have an impact on factors that mediate the access to mental health care, such as attitudes towards seeking psychological help, among people who have a lower level of education or are at risk of social isolation.
Evaluating feedback reports to support documentation of veterans’ care preferences in home based primary care
Authors: Levy Cari , Kononowech Jennifer , Ersek Mary , Phibbs Ciaran S. , Scott Winifred , Sales Anne
Published: May 2024

Background

To evaluate the effectiveness of delivering feedback reports to increase completion of LST notes among VA Home Based Primary Care (HBPC) teams. The Life Sustaining Treatment Decisions Initiative (LSTDI) was implemented throughout the Veterans Health Administration (VHA) in the United States in 2017 to ensure that seriously ill Veterans have care goals and LST decisions elicited and documented.

Methods

We distributed monthly feedback reports summarizing LST template completion rates to 13 HBPC intervention sites between October 2018 and February 2020 as the sole implementation strategy. We used principal component analyses to match intervention to 26 comparison sites and used interrupted time series/segmented regression analyses to evaluate the differences in LST template completion rates between intervention and comparison sites. Data were extracted from national databases for VA HBPC in addition to interviews and surveys in a mixed methods process evaluation.

Results

LST template completion rose from 6.3 to 41.9% across both intervention and comparison HBPC teams between March 1, 2018, and February 26, 2020. There were no statistically significant differences for intervention sites that received feedback reports.

Conclusions

Feedback reports did not increase documentation of LST preferences for Veterans at intervention compared with comparison sites. Observed increases in completion rates across intervention and comparison sites can likely be attributed to implementation strategies used nationally as part of the national roll-out of the LSTDI. Our results suggest that feedback reports alone were not an effective implementation strategy to augment national implementation strategies in HBPC teams.
Molecular characterization of carbapenemase and extended spectrum beta-lactamase producing Acinetobacter baumannii isolates causing surgical site infections in Ethiopia
Authors: Worku Seble , Abebe Tamrat , Seyoum Berhanu , Alemu Bikila , Denkayehu Gebrie , Seyoum Tamrayehu , Alemayehu Dawit Hailu , Abdissa Alemseged , Beyene Getachew Tesfaye , Mihret Adane , Swedberg Göte
Published: May 2024

Background

Acinetobacter baumannii is an opportunistic pathogen that can cause a variety of nosocomial infections in humans. This study aimed to molecularly characterize extended-spectrum beta-lactamase (ESBL) producing and carbapenem-resistant Acinetobacter species isolated from surgical site infections (SSI).

Methods

A multicentre cross-sectional study was performed among SSI patients at four hospitals located in Northern, Southern, Southwest, and Central parts of Ethiopia. The isolates were identified by microbiological methods and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Antibiotic susceptibility was determined using disk diffusion. The presence of phenotypic ESBL and carbapenemase production was detected by employing standard microbiological tests, including combined disk diffusion (CDT). ESBL and carbapenem resistance determinants genes were studied by polymerase chain reaction (PCR) and sequencing.

Results

A total of 8.7% Acinetobacter species were identified from 493 culture-positive isolates out of 752 SSI wounds. The species identified by MALDI-TOF MS were 88.4% A. baumannii, 4.7% Acinetobacter pittii, 4.7% Acinetobacter soli, and 2.3% Acinetobacter lactucae. Of all isolates 93% were positive for ESBL enzymes according to the CDT. Using whole genome sequencing 62.8% of the A. baumannii harbored one or more beta-lactamase genes, and 46.5% harbored one or more carbapenemase producing genes. The distribution of beta-lactamases among Acinetobacter species by hospitals was 53.8%, 64.3%, 75%, and 75% at JUSH, TASH, DTCSH, and HUCSH respectively. Among ESBL genes, blaCTX−M alleles were detected in 21.4% of isolates; of these 83.3% were blaCTX−M−15. The predominant carbapenemase gene of blaOXA type was detected in 24 carbapenem-resistant A. baumannii followed by blaNDM alleles carried in 12 A. baumannii with blaNDM−1 as the most common.

Conclusions

The frequency of Acinetobacter species that produce metallobetalactamases (MBLs) and ESBLs that were found in this study is extremely scary and calls for strict infection prevention and control procedures in health facilities helps to set effective antibiotics stewardship.
Cancer diagnosis after emergency presentations in people with mental health and substance use conditions: a national cohort study
Authors: Cunningham Ruth , Stanley James , Imlach Fiona , Haitana Tracy , Lockett Helen , Every-Palmer Susanna , Clark Mau Te Rangimarie , Lacey Cameron , Telfer Kendra , Peterson Debbie
Published: May 2024

Background

Cancer survival and mortality outcomes for people with mental health and substance use conditions (MHSUC) are worse than for people without MHSUC, which may be partly explained by poorer access to timely and appropriate healthcare, from screening and diagnosis through to treatment and follow-up. Access and quality of healthcare can be evaluated by comparing the proportion of people who receive a cancer diagnosis following an acute or emergency hospital admission (emergency presentation) across different population groups: those diagnosed with cancer following an emergency presentation have lower survival.

Methods

National mental health service use datasets (2002–2018) were linked to national cancer registry and hospitalisation data (2006–2018), to create a study population of people aged 15 years and older with one of four cancer diagnoses: lung, prostate, breast and colorectal. The exposure group included people with a history of mental health/addiction service contact within the five years before cancer diagnosis, with a subgroup of people with a diagnosis of bipolar disorder, schizophrenia or psychotic disorders. Marginal standardised rates were used to compare emergency presentations (hospital admission within 30 days of cancer diagnosis) in the exposure and comparison groups, adjusted for age, gender (for lung and colorectal cancers), ethnicity, area deprivation and stage at diagnosis.

Results

For all four cancers, the rates of emergency presentation in the fully adjusted models were significantly higher in people with a history of mental health/addiction service use than people without (lung cancer, RR 1.19, 95% CI 1.13, 1.24; prostate cancer RR 1.69, 95% CI 1.44, 1.93; breast cancer RR 1.42, 95% CI 1.14, 1.69; colorectal cancer 1.31, 95% CI 1.22, 1.39). Rates were substantially higher in those with a diagnosis of schizophrenia, bipolar disorder or psychotic disorders.

Conclusions

Implementing pathways for earlier detection and diagnosis of cancers in people with MHSUC could reduce the rates of emergency presentation, with improved cancer survival outcomes. All health services, including cancer screening programmes, primary and secondary care, have a responsibility to ensure equitable access to healthcare for people with MHSUC.
Knockdown of CENPM activates cGAS-STING pathway to inhibit ovarian cancer by promoting pyroptosis
Authors: Xie Wei , Zhang Leiying , Shen Junjing , Lai Fengdi , Han Wenling , Liu Xiaoyan
Published: May 2024

Objective

We aimed to screen novel gene signatures for ovarian cancer (OC) and explore the role of biomarkers in OC via regulating pyroptosis using bioinformatics analysis.

Methods

Differentially expressed genes (DEGs) of OC were screened from GSE12470 and GSE16709 datasets. Hub genes were determined from protein–protein interaction networks after bioinformatics analysis. The role of Centromeric protein M (CENPM) in OC was assessed by subcutaneous tumor experiment using hematoxylin–eosin and immunohistochemical staining. Tumor metastasis was evaluated by detecting epithelial-mesenchymal transition-related proteins. The proliferation, migration, and invasion were determined using cell counting kit and transwell assay. Enzyme-linked immunosorbent assay was applied to measure inflammatory factors. The mRNA and protein expression were detected using real-time quantitative PCR and western blot.

Results

We determined 9 hub genes (KIFC1, PCLAF, CDCA5, KNTC1, MCM3, OIP5, CENPM, KIF15, and ASF1B) with high prediction value for OC. In SKOV3 and A2780 cells, the expression levels of hub genes were significantly up-regulated, compared with normal ovarian cells. CENPM was selected as a key gene. Knockdown of CENPM suppressed proliferation, migration, and invasion of OC cells. Subcutaneous tumor experiment revealed that CENPM knockdown significantly suppressed tumor growth and metastasis. Additionally, pyroptosis was promoted in OC cells and xenograft tumors after CENPM knockdown. Furthermore, CENPM knockdown activated cGAS-STING pathway and the pathway inhibitor reversed the inhibitory effect of CENPM knockdown on viability, migration, and invasion of OC cells.

Conclusion

CENPM was a novel biomarker of OC, and knockdown of CENPM inhibited OC progression by promoting pyroptosis and activating cGAS-STING pathway.
Anticancer properties and metabolomic profiling of Shorea roxburghii extracts toward gastrointestinal cancer cell lines
Authors: Janthamala Sutthiwan , Promraksa Bundit , Thanee Malinee , Duenngai Kunyarat , Jusakul Apinya , Kongpetch Sarinya , Kraiklang Ratthaphol , Thanee Kidsada , Pinlaor Porntip , Namwat Nisana , Saya Hideyuki , Techasen Anchalee
Published: May 2024

Background

Gastrointestinal cancer (GIC) ranks as the highest cause of cancer-related deaths globally. GIC patients are often diagnosed at advanced stages, limiting effective treatment options. Chemotherapy, the common GIC recommendation, has significant disadvantages such as toxicity and adverse effects. Natural products contain substances with diverse pharmacological characteristics that promise for use in cancer therapeutics. In this study, the flower of renowned Asian medicinal plant,Shorea roxburghiiwas collected and extracted to investigate its phytochemical contents, antioxidant, and anticancer properties on GIC cells.

Methods

The phytochemical contents ofShorea roxburghiiextract were assessed using suitable methods. Phenolic content was determined through the Folin-Ciocalteu method, while flavonoids were quantified using the aluminum chloride (AlCl3) method. Antioxidant activity was evaluated using the FRAP and DPPH assays. Cytotoxicity was assessed in GIC cell lines via the MTT assay. Additionally, intracellular ROS levels and apoptosis were examined through flow cytometry techniques. The correlation between GIC cell viability and phytochemicals,1H-NMR analysis was conducted.

Results

Among the four different solvent extracts, ethyl acetate extract had the highest phenolic and flavonoid contents. Water extract exhibited the strongest reducing power and DPPH scavenging activity following by ethyl acetate. Interestingly, ethyl acetate extract demonstrated the highest inhibitory activity against three GIC cell lines (KKU-213B, HepG2, AGS) with IC50values of 91.60 µg/ml, 39.38 µg/ml, and 35.59 µg/ml, while showing less toxicity to normal fibroblast cells. Ethyl acetate extract induced reactive oxygen species and apoptosis in GIC cell lines by downregulating anti-apoptotic protein Bcl-2. Metabolic profiling-based screening revealed a positive association between reduced GIC cell viability and phytochemicals like cinnamic acid and its derivatives, ferulic acid and coumaric acid.

Conclusions

This study highlights the potential of natural compounds inShorea roxburghiiin the development of more effective and safer anticancer agents as options for GIC as well as shedding light on new avenues for cancer treatment.
The effectiveness of virtual reality training on knowledge, skills and attitudes of health care professionals and students in assessing and treating mental health disorders: a systematic review
Authors: Steen Cathrine W. , Söderström Kerstin , Stensrud Bjørn , Nylund Inger Beate , Siqveland Johan
Published: May 2024

Background

Virtual reality (VR) training can enhance health professionals’ learning. However, there are ambiguous findings on the effectiveness of VR as an educational tool in mental health. We therefore reviewed the existing literature on the effectiveness of VR training on health professionals’ knowledge, skills, and attitudes in assessing and treating patients with mental health disorders.

Methods

We searched MEDLINE, PsycINFO (via Ovid), the Cochrane Library, ERIC, CINAHL (on EBSCOhost), Web of Science Core Collection, and the Scopus database for studies published from January 1985 to July 2023. We included all studies evaluating the effect of VR training interventions on attitudes, knowledge, and skills pertinent to the assessment and treatment of mental health disorders and published in English or Scandinavian languages. The quality of the evidence in randomized controlled trials was assessed with the Cochrane Risk of Bias Tool 2.0. For non-randomized studies, we assessed the quality of the studies with the ROBINS-I tool.

Results

Of 4170 unique records identified, eight studies were eligible. The four randomized controlled trials were assessed as having some concern or a high risk of overall bias. The four non-randomized studies were assessed as having a moderate to serious overall risk of bias. Of the eight included studies, four used a virtual standardized patient design to simulate training situations, two studies used interactive patient scenario training designs, while two studies used a virtual patient game design. The results suggest that VR training interventions can promote knowledge and skills acquisition.

Conclusions

The findings indicate that VR interventions can effectively train health care personnel to acquire knowledge and skills in the assessment and treatment of mental health disorders. However, study heterogeneity, prevalence of small sample sizes, and many studies with a high or serious risk of bias suggest an uncertain evidence base. Future research on the effectiveness of VR training should include assessment of immersive VR training designs and a focus on more robust studies with larger sample sizes.

Trial registration

This review was pre-registered in the Open Science Framework register with the ID-number Z8EDK.
The cost of keeping patients waiting: retrospective treatment-control study of additional healthcare utilisation for UK patients awaiting elective treatment
Authors: James Charlotte , Denholm Rachel , Wood Richard
Published: May 2024

Objective

Long waiting times for elective hospital treatments are common in many countries. This study seeks to address a deficit in the literature concerning the effect of long waits on the wider consumption of healthcare resources.

Methods

We carried out a retrospective treatment-control study in a healthcare system in South West England from 15 June 2021 to 15 December 2021. We compared weekly contacts with health services of patients waiting over 18 weeks for treatment (‘Treatments’) and people not on a waiting list (‘Controls’). Controls were matched to Treatments based on age, sex, deprivation and multimorbidity. Treatments were stratified by the clinical specialty of the awaited hospital treatment, with healthcare usage assessed over various healthcare settings. Wilcoxon signed-rank tests assessed whether there was an increase in healthcare utilisation and bootstrap resampling was used to estimate the magnitude of any differences.

Results

A total of 44,616 patients were waiting over 18 weeks (the constitutional target in England) for treatment during the study period. There was an increase (p < 0.0004) in healthcare utilisation for all specialties. Patients in the Cardiothoracic Surgery specialty had the largest increase, with 17.9 [interquartile-range: 4.3, 33.8] additional contacts with secondary care and 17.3 [-1.1, 34.1] additional prescriptions per year.

Conclusion

People waiting for treatment consume higher levels of healthcare than comparable individuals not on a waiting list. These findings are relevant for clinicians and managers in better understanding patient need and reducing harm. Results also highlight the possible ‘false economy’ in failing to promptly resolve long elective waits.