Browse Articles

Influence of preoperative anti TNF alpha antibody therapy on postoperative recurrence of Crohn’s disease

Mapping relationships among gross motor skills in 16,989 children using network analysis

Abstract The development of gross motor skills during childhood is crucial for shaping more complex movements and laying the groundwork for physical activity, and subsequently lifelong health and enhanced well-being. Performance in motor skills improves throughout development, with the greatest improvements occurring during childhood. Understanding the relationships between developing gross motor skills is essential for informing educational and intervention practices. A total of 16,989 children aged 3–11 years underwent assessment of gross motor skills. Using network analysis, gross motor skills networks were constructed for the entire sample, and stratified by age and sex. The accuracy and stability of the networks were assessed, and centrality and bridge statistics were estimated for each node. The results indicated that running and two-hand catching exhibited higher centrality and bridge statistics compared to the other nodes in the all-sample network. Additionally, it was observed that the strength between nodes decreased and their distance increased with age. These results highlight the importance of specific gross motor skills due to their significant role in relation to other skills within the network. Gross motor skills progress towards increased independence and specialisation during development, indicating the importance of early educational interventions where children could benefit from educational practices focused on catching and running.

How to evaluate the quality of the clinical learning environment in health professions education? Protocol of a systematic review

Background Internships can constitute up to one third of the curriculum and during these internships, the foundation for developing specific health professional competencies is formed. The clinical learning environment (CLE) is a critical determinant of the overall quality of internships in health profession education, shaping students’ professional competencies and experiences. Objective This systematic review aims to identify and categorize assessment tools available for evaluating the quality of the CLE in health professions education. Methods This in the International Database of Education Systematic Reviews preregistered systematic review [IDESR000098] will consider peer-reviewed articles in English where instruments are developed and validated to illustrate the quality of the CLE in higher education health professions students. The search strategy will encompass multiple electronic databases, including MEDLINE, EMBASE, the Cochrane Library, ERIC, Education Research Complete, Education Database, and CINAHL. Studies will be independently assessed for risk of bias using the COSMIN Risk of Bias checklist for systematic reviews of PROMs. We will summarize and tabulate the basic characteristics of each identified tool and via a comprehensive table we will summarize the reported psychometric properties. Discussion This systematic review protocol will outline a comprehensive approach to identifying and evaluating assessment tools for measuring the quality of the CLE in health profession students. It is assumed that the findings will offer several notable advantages and impacts, which could significantly influence the quality of clinical education for health profession students.

Evaluation of radiographic knee OA progression after arthroscopic meniscectomy compared with IACI for degenerative meniscus tear

Supervised Machine Learning and Physics Machine Learning approach for prediction of peak temperature distribution in Additive Friction Stir Deposition of Aluminium Alloy

Additive friction stir deposition (AFSD) is a novel solid-state additive manufacturing technique that circumvents issues of porosity, cracking, and properties anisotropy that plague traditional powder bed fusion and directed energy deposition approaches. However, correlations between process parameters, thermal profiles, and resulting microstructure in AFSD still need to be better understood. This hinders process optimization for properties. This work employs a framework combining supervised machine learning (SML) and physics-informed neural networks (PINNs) to predict peak temperature distribution in AFSD from process parameters. Eight regression algorithms were implemented for SML modeling, while four PINNs leveraged governing equations for transport, wave propagation, heat transfer, and quantum mechanics. Across multiple statistical measures, ensemble techniques like gradient boosting proved superior for SML, with the lowest MSE of 165.78. The integrated ML approach was also applied to classify deposition quality from process factors, with logistic regression delivering robust accuracy. By fusing data-driven learning and fundamental physics, this dual methodology provides comprehensive insights into tailoring microstructure through thermal management in AFSD. The work demonstrates the power of bridging statistical and physics-based modeling for elucidating AM process-property relationships.

Author Correction: Assessment of heavy metals and microbial loads in Nile tilapia (Oreochromis niloticus) from different farms and rivers

Exploring the impact of opioid use on outcomes in allogeneic hematopoietic stem cell transplantation

Introduction Hematological malignancies and allogeneic hematopoietic cell transplantation (alloHCT) often necessitate the use of opioids due to significant pain. This study aimed to investigate the impact of opioid use on the clinical outcomes of patients undergoing alloHCT. Methods A retrospective cohort study was conducted by merging data from our local transplant database with anonymized pharmacy records obtained from the Institute for Clinical Evaluative Sciences (ICES). We analyzed 681 patients who underwent alloHCT at Princess Margaret Cancer Centre between January 2010 and December 2019. Patients who initiated opioid use within one-year post-alloHCT and had opioid prescriptions for more than 30 days were categorized as intense opioid users (IOU). Additionally, patients who started opioids before or within one-year post-alloHCT and had opioid prescriptions for less than 30 days but died while on opioids were also classified as IOU. The analytical code used for the analysis is available in the Supporting Information file. Results Among the 681 patients, 51 were identified as IOU. The two-year overall survival (OS) was significantly lower in the IOU group, with 29.4% survival compared to 53% in non-IOU (HR 1.77, 95% CI 1.26–2.48, p = 0.0008). Multivariate analysis indicated that IOU status was associated with a 2.32 times higher instantaneous rate of death compared to non-IOU (HR 2.32, 95% CI 1.5–3.5, p = 0.002). The median time for relapse was 147 days in the IOU group (range 52–393) and 209 day for non-IOU (range 96–1793), p = 0.0082. Furthermore, the relapse rate at two years was notably higher in the IOU group (31.4% vs. 16.4%, p = 0.0049). The analysis of factors independently associated with relapse-free survival (LFS) showed that IOU status, age, donor type, and cytogenetic risk were significant predictors. At two years, relapse-free survival was 29.4% in the IOU group compared to 52.5% in the non-IOU group (p < 0.001). Conclusions In our study, we found a correlation between intense opioid use in alloHCT patients and worse overall survival, particularly concerning higher relapse rates. These findings highlight the need for further research into pain management strategies to improve outcomes and reduce potential toxicity.

Isolation and assessment of antibiotic resistance of Staphylococcus aureus in the air of an underground hard coal mines

Correction: Three inhibitory phenolic acids against common ragweed (Ambrosia artemisiifolia L.) had a minimal effect on maize growth in vitro and in vivo

A novel Parrot Optimizer for robust and scalable PEMFC parameter optimization

Correction: Enhanced silk production and pupal weight in Bombyx mori through CRISPR/Cas9-mediated circadian Clock gene disruption

Comprehensive vulnerability assessment of power system nodes with wind power based on Dagum-Gini coefficient approach

Factors associated with attrition in a longitudinal study of health risk behaviours and conditions among adolescents in Ibadan, Nigeria

Background Use of longitudinal design in research improves understanding of adolescent health. In this paper, we present factors associated with attrition in a pilot longitudinal study among adolescents in Ibadan, Nigeria. Methods Adolescents were recruited from private and government-owned junior secondary schools using multi-stage sampling and interviewed over three data collection waves (2017, 2018 and 2019). Results A total of 1067 (99.4%) of the 1073 adolescents recruited were willing to participate and were interviewed in wave one. Mean age at baseline was 11.9 ± 1.2 years and 34.9% owned a personal mobile phone. Of the 1067 adolescents, 192 (18.0%) were not willing to be followed up while 875 (82.0%) were willing to be followed up by home visit (70.2%), phone call (21.3%), text message (14.3%) or online chat-based message (4.8%). Overall attrition rate (proportion of adolescents lost to follow-up during waves two and/or three compared with the baseline sample) was 66.5% with 396 (37.1%) and 315 (46.9%) respondents lost to follow-up during waves two and three respectively. Common reasons for attrition were use of pseudonyms instead of real names, which many adolescents could not remember during subsequent data collection waves, relocation to a different school or neighborhood, school drop-out and closure of two schools. Adolescents in private versus government-owned schools (AOR = 3.35; CI =  2.39 – 4.69), those who did not have personal mobile phones (AOR = 1.43, CI =  1.03 – 1.98) and those engaging in remunerated work (AOR =  2.04, CI =  1.19 – 3.49) were more likely to be lost to follow-up. Conclusions Attrition was high despite high willingness to participate in the study. Whereas technology has made follow-up of study participants in high-income countries easier, multiple, and cost intensive methods to minimize attrition may be required in low-resource settings.

Potential functional changes in native lysozyme induced by carbon nanotubes studied by molecular dynamics simulations

The effect of deferring feedback on rule-based and information-integration category learning

Previous work has shown that deferring feedback significantly impairs two-dimensional information-integration category learning, often thought to recruit an implicit learning system, but leaves intact unidimensional rule-based learning, commonly assumed to engage an explicit system. These results were taken to support the influential COmpetition between Verbal and Implicit Systems (COVIS) dual-process theory. This conclusion has subsequently been challenged by the finding that this dissociation disappears when the number of relevant dimensions is matched between tasks. However, as well as replacing a unidimensional rule-based task with a two-dimensional conjunction task, a different set of stimuli were used making it unclear which of these alterations was driving the difference in results. The current paper directly examined how both category structure and stimulus type influence the deferred feedback effect. We replicated both the original sets of results but found that deferred feedback also impaired information-integration learning to a greater extent than a conjunction task when the original stimuli were used. These results suggest that the impact of deferred feedback on category learning is more complicated than previously documented, as our findings cannot be easily explained by either COVIS or single-system accounts. Furthermore, our results highlight the critical role that the choice of stimuli has on categorization behavior and emphasize the importance of testing findings across different stimuli to ensure their robustness.

Analysis of risk factors of intracranial infection after microvascular decompression

Development of an experimental model using cold stress to assess the pathogenicity of two Moroccan AI H9N2 isolates from 2016 and 2022 in commercial broiler chickens

Since 2016, low pathogenic avian influenza virus (LPAIV) H9N2 became a major issue for poultry production in Morocco. Even though the agent was classified as low pathogenic, AI H9N2 cause significant economic losses, particularly during co-infections. Experimentally, it has been difficult to reproduce the clinical picture without appealing other viral or bacterial pathogens. Our study was carried out to evaluate a new challenge model using cold stress in commercial broilers infected with two Moroccan H9N2 viruses isolated in 2016 and 2022. One hundred twenty day-old chicks were divided into four groups: A, B, and C exposed to cold stress, and D was kept as negative control. At 21 days of age, Groups A and B were challenged by oculo-nasal route with 107 EID50 of H9N2 strains, isolated respectively during 2016 and 2022. Meanwhile, chicks of group C were exposed to only cold stress. The assessment of body weight gain, clinical signs, lesions, mortality, and oropharyngeal viral shedding was monitored for 15 days post-challenge. Results showed that cold stress exacerbated H9N2 clinical signs, allowing us to establish a scoring system and to validate the challenge model without co-infections. Gross and microscopic lesions, induced by the virus primarily in the respiratory tract, peaked at 5 dpi and significantly decreased at 15 dpi. Group B harbored the highest viral loads with viral shedding persisting beyond 11 dpi in both groups. This study demonstrates a clear clinical difference among the two isolates; A/chicken/Morocco/178-2/2022(H9N2) showed a significant increase in virulence compared to the firstly isolate A/chicken/Morocco/SF1/2016(H9N2). The novel H9N2 challenge model using cold stress will contribute to a better understanding of LPAI pathogenesis and epidemiology and allow for research closer to the field.

Cold aortic flush after ventricular fibrillation cardiac arrest reduces inflammatory reaction but not neuronal loss in the pig cerebral cortex

Abstract This study aims to retrospectively compare two resuscitation methods (extracorporeal cardiopulmonary resuscitation (ECPR) vs. emergency preservation and resuscitation (EPR)) by pathohistologically assessing pig brains in a ventricular fibrillation cardiac arrest (VFCA) model. In prospective studies from 2004 to 2006, swine underwent VFCA for 13 (n = 6), 15 (n = 14) or 17 (n = 6) minutes with ECPR (ECPR13, ECPR15 and ECPR17). Another 15 min VFCA group (n = 8) was resuscitated with EPR and chest compressions (EPR15 + CC). Brains of animals surviving for nine days (ECPR13 n = 4, ECPR15 n = 2, ECPR17 n = 1, EPR15 + CC n = 7) were harvested. Eight different brain regions were analyzed with the image analysis software QuPath using HE-staining, GFAP- and Iba1-immunohistochemistry. Only ECPR13 and EPR15 + CC animals were included in statistical analysis, due to low survival rates in the other groups. All VFCA samples showed significantly fewer viable neurons compared to shams, but no significant differences between ECPR13 and EPR15 + CC animals were observed. ECPR13 animals showed significantly more glial activation in all cerebral cortex regions compared to shams and in occipital, temporal and parietal cortex compared to EPR15 + CC. In conclusion, EPR + CC resulted in a significantly reduced inflammatory reaction in cerebral cortex compared to ECPR but did not influence the extent of neuronal death after VFCA.

Autumn protogyny and spring protandry: Mechanisms and adaptive significance in a Japanese headwater frog, Rana sakuraii

In temperate-zone vertebrates, almost all studies on protandry and protogyny are based on spring breeding migrations or breeding sites and are discussed in terms of the advantages for pairing. However, both autumn migrations and wintering conditions are also important for studies on these behaviors because, in some vertebrates, pairings occur at wintering sites before the emergence at the main breeding sites. Nevertheless, the significance of both autumn migrations and wintering conditions for pairing is scarcely recognized or studied. This study is the first to report on the mechanism and adaptive significance of “autumn protogyny and spring protandry” in a temperate-zone amphibian species. I investigated the annual migrations of Rana sakuraii, a Japanese early spring breeding (ESB) frog species, for over 21 years. This species migrates toward its breeding sites during autumn, hibernates either at the same breeding sites or close by, and breeds immediately upon emergence from hibernation. Protogynous autumn migrations and protandrous ESB migrations were clearly observed every year, depending on the same factor: the difference in threshold temperature for hibernation (which was higher for females than males). Frogs hibernated in groups under boulders in streams. Pairings began during autumn migrations and mostly ended during the aquatic hibernation period. Based on the results of this study and other related reports, I propose the hypothesis that temperate-zone ESB amphibians exhibit “autumn protogyny and spring protandry,” which are not independent and always occur together successively. Moreover, to explain the adaptive significance of these contrasting behaviors, I propose “the surefire pairing hypothesis”: these pairings occur more securely in two stages, before and after emergence at main breeding sites (i.e., “Early pairings” and “Normal pairings”). Such pairing advantages are provided by autumn protogyny and group hibernation for “Early pairings,” and by spring protandry for “Normal pairings.”.

Rapid global antenna design by simplex regressors and multi-resolution simulations

Abstract Optimization methods have been rapidly entering the realm of antenna design over the last several years. Despite many available algorithms, practical optimization is demanding due to the high electromagnetic (EM) analysis cost necessary for dependable antenna assessment. This is particularly troublesome in global parameter tuning, routinely conducted using nature-inspired procedures. Unfortunately, these methods are known for their poor computational efficiency. Surrogate modeling may mitigate this issue to a certain extent, yet dimensionality and parameter range issues severely impede the construction of accurate metamodels. This research suggests an innovative algorithm for global parameter adjustment of antenna systems. It conducts a simplex-based search in the space of the structure’s performance figures (e.g., center frequencies, bandwidth, etc.). Operating at this level regularizes the objective function. Low cost is achieved by the simplex updating strategy requiring only one EM analysis per iteration, and multi-resolution simulations. The global search state involves coarse-discretization full-wave analysis, whereas final (gradient-based) parameter tuning involves medium-fidelity simulations for sensitivity estimation and high-fidelity models for design verification. The developed algorithmic framework is validated using four microstrip antennas. The results generated in multiple runs demonstrate global search capability and remarkably low expenses, corresponding to around a hundred high-fidelity analyses on average. The performance level is competitive over local and global optimizers.