Significant Differences In Performance Research Articles

비보건계열 대학생 대상 시뮬레이션 기반 심폐소생술 교육 프로그램의 효과

Objectives The purpose of this study is to develop simulation-based cardiopulmonary resuscitation education and apply it to non-health related college students to understand its effect.
 Methods This study was conducted on 54 non-health college students (27 in the experimental group and 27 in the control group). The control group received the general cardiopulmonary resuscitation (CPR) education, and the experimental group received the shortened version of the CPR education provided to the control group and the simulation-based CPR education developed in this study.
 Results Simulation-based CPR education was developed and applied in five stages: analysis, design, development, implement, and evaluation. The experimental group's cardiopulmonary resuscitation performance was 41.22±3.91 points, and the control group's cardiopulmonary resuscitation performance was 28.15±4.05 points, indicating a significant difference in cardiopulmonary resuscitation performance (Z=-6.32, p=<.001). There were no significant differences in knowledge of CPR (Z=-0.04, p=.972), confidence in performing CPR (Z=1.00, p=.922), education satisfaction (Z=-0.28, p=.782), and immersion (Z=-0.08, p=.935).
 Conclusions Simulation-based CPR education programs was found to be effective in improving CPR performance. Therefore, the simulation-based CPR program can be used as an effective educational method for non-health college students, and it is necessary to consider ways that can be applied not only to college students but also to the general public.

Adaptation and growth performance of five avocado cultivars in Ethiopia

Ethiopia has diverse agroecology with vast areas, suitable for growing subtropical and tropical fruits. Despite this potential, the avocado industry in Ethiopia is still in its infancy. This study assessed the adaptation of five avocado cultivars: Ettinger, Fuerte, Hass, Nabal, and Reed, survival rate, growth performances, fruit yield, and household contributions in Lemo district Ethiopia. The results revealed that there were significant differences in tree growth performance and yield among avocado cultivars (P < 0.05). The highest vegetative growth performance was demonstrated by Nabal, Fuerte, Ettinger, and Hass, while Reed was the lowest. In 2020, Nabal had the highest fruit yield (96 kg tree1), followed by Hass (47 kg tree1), while Fuerte had a relatively low fruit yield (39.43 kg tree1). Due to its larger fruit size, the Nabal was used for sale, while the Hass cultivar, which has a sweet taste, was mainly used for home consumption. The findings demonstrated that significant difference in management practices applied by male and female farmers. Overall, the study concluded that the Nabal, Hass, and Ettinger cultivars had a great potential for fruit production, which could improve smallholder farmers livelihood. As a result, it is necessary to scale up these avocado cultivars in the midland agroecological zone of the country.

‘Gear up and get ready’: Collaborative curriculum for radiographers supporting percutaneous nephrolithotomy in the operating theatre

IntroductionNewly qualified radiographers often find working in the operating theatre (OT) challenging and intimidating. These perceptions, which inhibit confidence, may hinder their effectiveness in interprofessional teamwork, which may in turn adversely affect patient outcomes. A collaborative education programme was designed, building upon the foundations of competency-based education (CBE) and simulation-based mastery learning (SBML) to examine its potential in mitigating these perceptions. The objective of this research was to assess participants’ experience and level of competency after attending the curated collaborative educational programme. MethodsThe programme was developed based on the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model and comprises two teaching and learning phases: educational session and simulation. A collaborative approach was undertaken to develop an assessment checklist for the interprofessional simulation. Requirements for the simulation, such as scenario design, information and storyboard, task trainer, logistics, and learners' briefing, debrief, and feedback, were identified and assembled. The radiographers’ performance was recorded using a practical skills assessment checklist and a theory assessment. ResultsTwelve radiographers participated and showed improvement in their self-rating of learning objectives before and after the programme. The median (interquartile range) score achieved in the theory assessment, out of a possible of 11, was 9.00 (7.75–9.50). The median (interquartile range) score achieved in the simulation component, out of a possible of 16, was 15.00 (14.00–15.00). There was statistically significant difference in self-perceived performance in all learning objective domains. ConclusionThe findings from the programme were promising. The use of simulation and an assessment checklist proved to be useful learning tools in preparing newly qualified radiographers for work in the OT. Implications for practiceAssessment checklists are valuable tools that should be considered to facilitate teaching and learning. The use of interprofessional simulation activities can support radiographers in developing knowledge, professional skills, and clinical competency. It should be conducted in a timely manner to facilitate the introduction to role understanding and effective communication.

Business Performance of Small and Medium Enterprises: Evaluation of Respondents

Objective: The following were the objectives of this study: 1. analysis and measurement of the business performance of small and medium enterprises in Hanoi, Vietnam; 2. comparison of assessments of the business performance of small and medium enterprises in Hanoi, Vietnam, between respondents. Method: The data used in this study are primary, including survey data obtained from the respondents. We designed a questionnaire related to the business performance of small and medium enterprises in Hanoi. We determined the observed variables (scales) of the business performance of small and medium enterprises based on previous studies and expert interview results. We use both qualitative and quantitative research methods, including descriptive statistics, reliability analysis through the Cronbach alpha coefficient, EFA analysis, the independent T test, and ANOVA analysis. Besides, the study analyzed performance data for small and medium enterprises during the period 2022–2023. Results: According to the findings of this study, five attributes of the business performance of small and medium enterprises in Hanoi were quite high. All the attributes of the variables are statistically significant. There is no statistically significant difference in the business performance of small and medium enterprises in Hanoi between these different marital statuses, work locations, and job positions. Conclusions: It was found that the business performance of small and medium enterprises in Hanoi has many positive points, despite just going through the COVID-19 pandemic and economic growth. This article is an academic contribution that enables understanding of the research developed and focuses on the business performance of small and medium enterprises in Hanoi, considering data from several reference research databases and survey results.

Physical Quality of Complete Pellets Feed Containing Peanut Waste (Arachis hypogaea) and Its Effects on Rabbit Growth Performance

This study aimed to evaluate the physical quality of complete pellets with the addition of peanut waste and the effect of its administration on the performance of rabbits. A total of 20 local male rabbits aged 12 weeks with an average body weight of 1335.60 ± 280.53 g are divided into five groups based on body weight, and then used in this study which is performed in randomized block design (RBD). The rabbits are fed on the commercial pellets as a control diet (P0) and feed pellets containing peanut waste at the level of 5% (P1), peanut waste 10% (P2), and peanut waste 15% (P3). The results show that the physical quality of the pellets was not significantly different (p&gt;0.05) in all treatments. Feeding complete pellets with the addition of peanut waste rabbits performances show no significant difference in performance (p&gt;0.05) in all treatments. In conclusion, complete pellets with the addition of peanut was can resemble the physical quality of commercial pellets (control), maintain performances

Phenotypic adaptation to temperature in the mosquito vector, Aedes aegypti.

Most models exploring the effects of climate change on mosquito-borne disease ignore thermal adaptation. However, if local adaptation leads to changes in mosquito thermal responses, "one size fits all" models could fail to capture current variation between populations and future adaptive responses to changes in temperature. Here, we assess phenotypic adaptation to temperature in Aedes aegypti, the primary vector of dengue, Zika, and chikungunya viruses. First, to explore whether there is any difference in existing thermal response of mosquitoes between populations, we used a thermal knockdown assay to examine five populations of Ae. aegypti collected from climatically diverse locations in Mexico, together with a long-standing laboratory strain. We identified significant phenotypic variation in thermal tolerance between populations. Next, to explore whether such variation can be generated by differences in temperature, we conducted an experimental passage study by establishing six replicate lines from a single field-derived population of Ae. aegypti from Mexico, maintaining half at 27°C and the other half at 31°C. After 10 generations, we found a significant difference in mosquito performance, with the lines maintained under elevated temperatures showing greater thermal tolerance. Moreover, these differences in thermal tolerance translated to shifts in the thermal performance curves for multiple life-history traits, leading to differences in overall fitness. Together, these novel findings provide compelling evidence that Ae. aegypti populations can and do differ in thermal response, suggesting that simplified thermal performance models might be insufficient for predicting the effects of climate on vector-borne disease transmission.

A Comparative Study of Resistant Dextrins and Resistant Maltodextrins from Different Tuber Crop Starches.

The anti-digestibility of resistant dextrin (RD) and resistant maltodextrin (RMD) is usually significantly affected by processing techniques, reaction conditions, and starch sources. The objective of this investigation is to elucidate the similarities and differences in the anti-digestive properties of RD and RMD prepared from three different tuber crop starches, namely, potato, cassava, and sweet potato, and to reveal the associated mechanisms. The results show that all RMDs have a microstructure characterized by irregular fragmentation and porous surfaces, no longer maintaining the original crystalline structure of starches. Conversely, RDs preserve the structural morphology of starches, featuring rough surfaces and similar crystalline structures. RDs exhibite hydrolysis rates of approximately 40%, whereas RMDs displaye rates lower than 8%. This disparity can be attributed to the reduction of α-1,4 and α-1,6 bonds and the development of a highly branched spatial structure in RMDs. The indigestible components of the three types of RDs range from 34% to 37%, whereas RMDs vary from 80% to 85%, with potato resistant maltodextrin displaying the highest content (84.96%, p < 0.05). In conclusion, there are significant differences in the processing performances between different tuber crop starches. For the preparation of RMDs, potato starch seems to be superior to sweet potato and cassava starches. These attributes lay the foundation for considering RDs and RMDs as suitable components for liquid beverages, solid dietary fiber supplements, and low glycemic index (low-GI) products.

Impact Analysis of Workforce Network Model on Engagement and Individual Performance of Employees in A Traditional, Remote, and Hybrid Workforce Network

This study focused on the impact of workforce network models (traditional, remote, and hybrid workforce networks) on the engagement and individual performance of employees of three (3) selected companies in the financial technology segment of the small business process outsourcing (BPO) industry in the Metro Manila, Philippines. Moreover, this study aims to determine the significant difference in employee engagement and individual performance among workforce network models. The sampling technique used in this study was Stratified Random Sampling to allow the three (3) companies to be proportionally represented. The researchers used stratified sampling with proportional allocation to determine the sample size per stratum to complete the one hundred (100) total sample size. The survey questionnaires were distributed through online forms to each of the respondents. This was answered three (3) times by the respondent. One for when they were in a traditional workforce network, one for when they were in a remote workforce network model, and one for when they were in a hybrid workforce network. The data collected was analyzed using Frequency Distribution, Mean, Standard Deviation, ANOVA with repeated measures, and Pairwise Comparison. The majority of the respondents were male, single, aged between 31 and 40 years old, and had worked for 5-8 years in their respective companies. This study found that employees in the hybrid workforce network have the highest level of engagement according to Kahn’s Engagement Theory in terms of (a) safety, (b) meaningfulness, and (c) availability, followed by remote than traditional workforce networks. Additionally, employees in the hybrid workforce network also have the highest level of individual performance according to Campbell’s Theory of Performance in terms of (a) job-related activities; (b) unrelated duties; (c)tasks requiring written and spoken communication; (d) evidence of effort; (e) personal discipline maintenance; (f) peer and team performance encouragement; (g) supervision and leadership and (h) management and administration of employees. Finally, this study found that there was a significant difference between the engagement and individual performance of employees in traditional, remote, and hybrid workforce network models. Keywords: human resource management, workforce network model, employee engagement, individual performance

Application of artificial neural networks in assigned leadership and academic success in medical graduates.

To apply an artificial neural networks analysis (ANN) model to identify variables that predict assigned leadership and academic success in graduates of six generations of medical school. Analytical, retrospective, comparative study. A total of 1434 graduates participated. A questionnaire was sent to them by e-mail including a voluntary participation consent. A multivariate statistical analysis using multi-layer perceptron ANN, decision trees and driver analysis was performed. The ANN identified seven independent variables that predicted professional success and eight for leadership in medical graduates. The decision trees identified significant differences in the variables professional performance (p = 0.000), age (p = 0.005) and continuing education activities (p = 0.034) related to professional success, and for leadership the variables gender (p = 0.000), high school grades (p = 0.042), performing clinical practice during the social service year (p = 0.002) and continuing education activities (p = 0.011). The ANN identified the main independent predictor variables of professional success and leadership of the graduates. This study opens up two new lines of research little studied with the techniques of in the area of medicine.

Is the Conners’ continuous performance test helpful for assessing attention deficit hyperactivity disorder in a clinical setting?

Background Despite lacking validation for Norwegian populations, the Conners Continuous Performance Test II (CCPT-II) is applied to almost one-third of children receiving an ADHD diagnosis. However, evidence of the CCPT-II’s ability to differentiate between children with and without ADHD is contradictory. Thus, this study examines how CCPT-II results correlate with ADHD symptoms reported by mothers and teachers in a sample representing ordinary child and adolescent mental health services and explores the extent to which the CCPT-II influences the diagnostic result. Methods Correlations between CCPT-II results and ADHD Rating Scale scores and a clinical diagnosis of ADHD were analysed in children aged 6–15 years (N = 69) referred to a child and adolescent psychiatric outpatient clinic. Results Total ADHD symptom scores rated by mothers correlated with hit reaction time (HRT) block change (.260), HRT inter-stimulus interval (ISI) change (.264) and CCPT-II overall index (.263), while hyperactivity subscale scores correlated with omissions (.285), HRT (.414) and variability (.400). In teachers’ ratings, total ADHD and both subscale scores correlated with commissions (.280–.382), while hyperactivity scores correlated with variability (.265). A higher number of commissions was the only significant difference in CCPT-II performance between children diagnosed with and children without ADHD. Conclusions Correlations between CCPT-II results and ADHD symptoms were all small to moderate. As such, CCPT-II results should be interpreted with caution, because they correspond to a limited degree with other sources of information.

On effectively predicting autism spectrum disorder therapy using an ensemble of classifiers

An ensemble of classifiers combines several single classifiers to deliver a final prediction or classification decision. An increasingly provoking question is whether such an ensemble can outperform the single best classifier. If so, what form of ensemble learning system (also known as multiple classifier learning systems) yields the most significant benefits in the size or diversity of the ensemble? In this paper, the ability of ensemble learning to predict and identify factors that influence or contribute to autism spectrum disorder therapy (ASDT) for intervention purposes is investigated. Given that most interventions are typically short-term in nature, henceforth, developing a robotic system that will provide the best outcome and measurement of ASDT therapy has never been so critical. In this paper, the performance of five single classifiers against several multiple classifier learning systems in exploring and predicting ASDT is investigated using a dataset of behavioural data and robot-enhanced therapy against standard human treatment based on 3000 sessions and 300 h, recorded from 61 autistic children. Experimental results show statistically significant differences in performance among the single classifiers for ASDT prediction with decision trees as the more accurate classifier. The results further show multiple classifier learning systems (MCLS) achieving better performance for ASDT prediction (especially those ensembles with three core classifiers). Additionally, the results show bagging and boosting ensemble learning as robust when predicting ASDT with multi-stage design as the most dominant architecture. It also appears that eye contact and social interaction are the most critical contributing factors to the ASDT problem among children.

Effects of fermented Chinese herb residues on growth performance, nutrient apparent digestibility, serum biochemical indices and faecal microbial flora in beef cattle

This study aimed to evaluate the effects of fermented Chinese herb residues on the growth performance, nutrient apparent digestibility, serum biochemical indices and microflora of Simmental beef cattle during the fattening period. Twenty-four healthy Simmental beef cattle with an average body weight of 358.54 ± 65.63 kg were randomly divided into four treatment groups, with 6 replicates. The dietary treatments were as follows: I: basal diet; II, III and IV: 10% corn husk in the diet was replaced by Chinese herb residue, enzyme-fermented residue, and enzyme bacteria co-fermented residue, respectively. The experimental period was 49 days. There was no significant difference in the growth performance of beef cattle (p > 0.05). The ether extract (EE) apparent digestibility of groups III and IV was significantly higher than that of group I (p < 0.05); the apparent digestibility values of nitrogen free extract (NFE) and total phosphorus (P) in group IV were significantly lower than those in the other groups (p < 0.05). The maleic dialdehyde (MDA) contents in groups I and II were significantly higher than those in groups III and IV (p < 0.05). The ACE and Chao1 indices of groups I and III were significantly higher than those of groups II and IV (p < 0.05). The Shannon indices of groups I and III were significantly higher than that of group II (p < 0.05). The abundance of Firmicutes in group III was significantly lower than that in group II (p < 0.05). In conclusion, fermented Chinese herb residues could replace 10% corn husk and be used in beef cattle breeding.

Variable sensitivity multimaterial robotic e-skin combining electronic and ionic conductivity using electrical impedance tomography

Electronic skins (e-skins) aim to replicate the capabilities of human skin by integrating electronic components and advanced materials into a flexible, thin, and stretchable substrate. Electrical impedance tomography (EIT) has recently been adopted in the area of e-skin thanks to its robustness and simplicity of fabrication compared to previous methods. However, the most common EIT configurations have limitations in terms of low sensitivities in areas far from the electrodes. Here we combine two piezoresistive materials with different conductivities and charge carriers, creating anisotropy in the sensitive part of the e-skin. The bottom layer consists of an ionically conducting hydrogel, while the top layer is a self-healing composite that conducts electrons through a percolating carbon black network. By changing the pattern of the top layer, the resulting distribution of currents in the e-skin can be tuned to locally adapt the sensitivity. This approach can be used to biomimetically adjust the sensitivities of different regions of the skin. It was demonstrated how the sensitivity increased by 500% and the localization error reduced by 40% compared to the homogeneous case, eliminating the lower sensitivity regions. This principle enables integrating the various sensing capabilities of our skins into complex 3D geometries. In addition, both layers of the developed e-skin have self-healing capabilities, showing no statistically significant difference in localization performance before the damage and after healing. The self-healing bilayer e-skin could recover full sensing capabilities after healing of severe damage.

Immediate effects of multimodal cognitive therapy in mild cognitive impairment.

Current therapeutic evidence suggests limited efficacy of the cognitive and exercise training in mild cognitive impairment (MCI) on depression, anxiety, memory retention, comprehension, calculation, concentration, orientation, dual-task performance, and sleep disorders. Nevertheless, the immediate effects of multimodal cognitive therapy (MCT) have recently developed and its individual effects remains unknown in MCI. This study aimed to compare the immediate effects of MCT on cognitive and psychological measures between young healthy and older adults with MCI. Forty young healthy and older adults with MCI underwent immediate MCT (5 minutes each), including transcranial direct current stimulation (tDCS), light therapy, computerized cognitive therapy (CCT), robotic-assisted gait training (RAGT), core breathing exercises (CBE), and music therapy. Outcome measures included memory retention, comprehension, calculation, attention, orientation, dual-task performance, awareness, depression, anxiety, and sleep disorders. The Mann-Whitney U test and Friedman's test were used at P < 0.05. Significant differences in depression, anxiety, memory retention, comprehension, calculation, attention, orientation, dual-task performance, and awareness were observed between the tDCS, CCT, and music therapy groups (P < 0.05). MCT was beneficial for mitigating depression, anxiety, memory retention, comprehension, calculation, attention, orientation, dual-task performance, and awareness.

Effects of Exercise-Induced Neuromuscular Fatigue on Jump Performance and Lower-Limb Asymmetries in Youth Female Team Sport Athletes.

The objective of the present study was to examine the effect of acute neuromuscular fatigue on unilateral jump performance and inter-limb asymmetries. Thirty elite youth female team sport athletes (age: U-14 to U-18) performed the Unilateral Countermovement Jump (UCJ) and the Unilateral Drop Jump (UDJ) (18-cm box) tests before and approximately 10 minutes after the 30-15 intermittent fitness test (30-15 IFT). A paired samples t-test showed significant reductions in UCJ jump height in the right leg after the 30-15 IFT (p = 0.018; d = 0.33), but not in the left leg (p = 0.459; d = 0.48). For the UDJ, significant reductions in jump height were shown in both the right (p < 0.001; d = 0.33) and left (p < 0.001; d = 0.33) legs. In addition, for the reactive strength index (UDJ), significant reductions were seen in the left leg after the 30-15 IFT (p < 0.001; d = 0.31), but not in the right leg (p = 0.948; d < 0.001). Only UCJ inter-limb jump height asymmetries increased significantly post 30-15 IFT (p = 0.033; d = 0.46). In conclusion, the current study indicates that the 30-15 IFT provides a sufficient dose of activity for inducing acute fatigue in elite youth female team sport athletes. Therefore, monitoring jump height in unilateral jump testing is recommended given the tests' sensitivity to detect significant differences in physical performance and inter-limb asymmetries under acutely fatigued conditions in healthy youth female athletes.

Influence of spatial frequency in visual stimuli for cVEP-based BCIs: evaluation of performance and user experience.

Code-modulated visual evoked potentials (c-VEPs) are an innovative control signal utilized in brain-computer interfaces (BCIs) with promising performance. Prior studies on steady-state visual evoked potentials (SSVEPs) have indicated that the spatial frequency of checkerboard-like stimuli influences both performance and user experience. Spatial frequency refers to the dimensions of the individual squares comprising the visual stimulus, quantified in cycles (i.e., number of black-white squares pairs) per degree of visual angle. However, the specific effects of this parameter on c-VEP-based BCIs remain unexplored. Therefore, the objective of this study is to investigate the role of spatial frequency of checkerboard-like visual stimuli in a c-VEP-based BCI. Sixteen participants evaluated selection matrices with eight spatial frequencies: C001 (0 c/°, 1×1 squares), C002 (0.15 c/°, 2×2 squares), C004 (0.3 c/°, 4×4 squares), C008 (0.6 c/°, 8×8 squares), C016 (1.2 c/°, 16×16 squares), C032 (2.4 c/°, 32×32 squares), C064 (4.79 c/°, 64×64 squares), and C128 (9.58 c/°, 128×128 squares). These conditions were tested in an online spelling task, which consisted of 18 trials each conducted on a 3×3 command interface. In addition to accuracy and information transfer rate (ITR), subjective measures regarding comfort, ocular irritation, and satisfaction were collected. Significant differences in performance and comfort were observed based on different stimulus spatial frequencies. Although all conditions achieved mean accuracy over 95% after 2.1 s of trial duration, C016 stood out in terms user experience. The proposed condition not only achieved a mean accuracy of 96.53% and 164.54 bits/min with a trial duration of 1.05s, but also was reported to be significantly more comfortable than the traditional C001 stimulus. Since both features are key for BCI development, higher spatial frequencies than the classical black-to-white stimulus might be more adequate for c-VEP systems. Hence, we assert that the spatial frequency should be carefully considered in the development of future applications for c-VEP-based BCIs.

Bidirectional EMD-RLS: Performance analysis for denoising in speech signal

Empirical Mode Decomposition (EMD) is an alternative decomposition method that allows the analysis of non-stationary and non-linear signals, decomposing them into components called Intrinsic Mode Functions (IMFs). In this paper, we introduce the bidirectional combination between EMD and the Recursive Least Squares (RLS) adaptive filter and compare it to Least Mean Square (LMS), EMD-LMS and RLS methods. The hybrid algorithm relies on the determination of vertical (IMFs indexes) and horizontal (temporal indexes) weighting coefficients. We evaluated the effectiveness of the methods by filtering sets of speech signals artificially corrupted by white Gaussian noise. To find the method that provides the greatest noise reduction and the best speech quality, we took into account the Signal-to-Noise Ratio and the Perceptual Evaluation of Speech Quality (PESQ) score. The analyzed cases showed that EMD-RLS can provide results as good as the other methods, but with a shorter learning curve than LMS and EMD-LMS, despite the higher computational cost. For a single training iteration, the methods presented PESQ scores on average equivalent to each other. However, they showed a significant difference in performance regarding noise reduction, with the best result obtained by RLS, followed by EMD-RLS, EMD-LMS and LMS.

Characterization of glucose metabolism in high-growth performance Nile tilapia (Oreochromis niloticus)

Significant differences in growth performance have been observed in fish that have undergone the same culture cycle, even under identical conditions, including genetic background, water environment, and feeding strategy. These differences may adversely affect the harvesting and subsequent processing of commercial fish. We have previously demonstrated that the genes of glucose metabolism in high-growth performance tilapia (Oreochromis niloticus) showed significant upregulation at the transcriptome level. These findings suggested that the growth performance of tilapia may be closely related to their endogenous glucose metabolism capacity. To investigate the characteristics of glucose metabolism in high-growth performance tilapia, three full-sibling families were cultured under the same environmental and feeding conditions. The high-growth performance group (HG) and low-growth performance group (LG) were screened and compared at the biochemical and transcriptional levels during the postprandial period of 0 to 7 h. Based on biochemical analysis, HG had higher levels of intestinal lipase activity (0 to 1 h), serum triglyceride content (0 to 7 h), liver acetyl coenzyme A content (1 to 4 h), and liver glycogen content (0 to 1 h and 6 to 7 h) than LG. In contrast, HG had lower serum glucose content (0 h and 2 to 4 h), ATP content (4 to 7 h), and liver pyruvate content (3 to 4 h) than LG. There were no significant differences between HG and LG in liver ATP, intestinal α-amylase, and trypsin. We conducted a comprehensive analysis of gene expression within multiple metabolic pathways, namely the tricarboxylic acid cycle, glycolysis, pentose phosphate, glycogen metabolism, gluconeogenesis, and insulin signaling pathways, during three specific post-feeding periods: 0 to 1 h, 2–5 h, and 6 to 7 h, and revealed unique gene expression patterns related to glucose metabolic pathways in HG at different stages of post-feeding. We first revealed the endogenous glucose metabolism characteristics of high-growth performance tilapia. The findings will provide novel insights for further research on quality improvement related to growth performance in fish.

Using Artificial Intelligence to Stratify Normal versus Abnormal Chest X-rays: External Validation of a Deep Learning Algorithm at East Kent Hospitals University NHS Foundation Trust.

Background: The chest radiograph (CXR) is the most frequently performed radiological examination worldwide. The increasing volume of CXRs performed in hospitals causes reporting backlogs and increased waiting times for patients, potentially compromising timely clinical intervention and patient safety. Implementing computer-aided detection (CAD) artificial intelligence (AI) algorithms capable of accurate and rapid CXR reporting could help address such limitations. A novel use for AI reporting is the classification of CXRs as 'abnormal' or 'normal'. This classification could help optimize resource allocation and aid radiologists in managing their time efficiently. Methods: qXR is a CE-marked computer-aided detection (CAD) software trained on over 4.4 million CXRs. In this retrospective cross-sectional pre-deployment study, we evaluated the performance of qXR in stratifying normal and abnormal CXRs. We analyzed 1040 CXRs from various referral sources, including general practices (GP), Accident and Emergency (A&E) departments, and inpatient (IP) and outpatient (OP) settings at East Kent Hospitals University NHS Foundation Trust. The ground truth for the CXRs was established by assessing the agreement between two senior radiologists. Results: The CAD software had a sensitivity of 99.7% and a specificity of 67.4%. The sub-group analysis showed no statistically significant difference in performance across healthcare settings, age, gender, and X-ray manufacturer. Conclusions: The study showed that qXR can accurately stratify CXRs as normal versus abnormal, potentially reducing reporting backlogs and resulting in early patient intervention, which may result in better patient outcomes.

Cognitive and affective control for adolescents in care versus their peers: implications for mental health

BackgroundMany adolescents who have been removed from the care of their biological parent(s) and placed in State or Local Authority care have experienced significant adversity, including high rates of maltreatment and other trauma(s). As a group, these young people experience far higher rates of mental health difficulties compared to their peers. While their mental health outcomes are well-documented, little is known about mechanisms that may drive this. One potential mechanism, linked to both trauma and adversity exposure and mental health, is affective control (the application of cognitive control in affective contexts).MethodsWe compared cognitive and affective control in 71 adolescents (65% girls) in care aged 11–18 (M = 14.82, SD = 2.10) and 71 age and gender-matched peers aged 11–19 years (M = 14.75, SD = 1.95). We measured cognitive and affective control using standard experimental tasks, and for those in care, we also examined associations with self-reported emotion regulation, mental health, and school well-being.ResultsAfter controlling for IQ, there was a significant group difference in affective control performance, with those in care on average performing worse across all tasks. However, further analyses showed this was driven by deficits in overall cognitive control ability, and was not specific to, or worsened by, affective stimuli. Further, we found no evidence that either cognitive or affective control was associated with emotion regulation abilities or the mental health and well-being of young people in care.ConclusionsResults suggest that cognitive and affective control may not underlie mental health for young people in care, though limitations should be considered. We discuss implications for theory and intervention development, and avenues for further research.Trial registration: https://doi.org/10.17605/OSF.IO/QJVDA