bluuebunny/crossref_metadata_2025_split huggingface dataset:
An overview of major depression disorder: The endocannabinoid system as a potential target for therapy
Authors: Zarazúa‐Guzmán Sergio , Vicente‐Martínez Jorge Genaro , Pinos‐Rodríguez Juan Manuel , Arevalo‐Villalobos Jaime Iván 
Published: October 2024

AbstractMajor depressive disorder is the psychiatric disease with the highest global prevalence, impacting social functioning and decreasing the quality of life. The partial pathophysiological knowledge of the disease, the economic burden and the low remission rates are sufficient justification to carry out an update on the subject in the search for new therapeutic approaches and targets. The endocannabinoid system has been linked to the development of depression, and its stimulation or antagonism is a promising approach in the treatment of major depressive disorder. Cannabidiol (CBD) and its properties have been widely studied recently; its analgesic, anti‐inflammatory, antineoplastic and neuroprotective roles have even been reported in animal models and clinical trials, achieving its approved use for certain neurodegenerative pathologies. The use of CBD in depression biomodels and clinical trials has not been the exception, and here we contrast the current evidence of its administration and pharmacology against the pathological mechanisms of major depressive disorder.
Profiles of teachers' emotional labour during COVID‐19 and the consequences on mental health: A comparison between online and offline teaching
Authors: Chen Zhuo , Zuo Huang , Hua Zixun , Feng Yuanhuan , Gao Ruixiang 
Published: October 2024

AbstractBackgroundDespite increasing attention on emotional labor in teacher well‐being research, person‐centered studies are relatively scarce, particularly concerning the emotional labor of online teaching during COVID‐19 and its effects on teachers’ non‐work‐related mental health.ObjectiveThis study aims to address these gaps by examining emotional labor profiles and their consequences on job satisfaction, depression, and anxiety among Chinese teachers involved in either online or offline teaching during October–December 2022.MethodsTwo samples of teachers were analyzed altogether: one engaged in online teaching (N=605) and the other in offline teaching (N=394). Latent profile analysis was used to identify emotional labor profiles based on three strategies: surface acting, deep acting, and expression of naturally felt emotions.ResultsA total of four subgroups of emotional workers were identified: natural expressors, actors, flexible regulators, and authentic regulators. Significant differences were found between online and offline teaching, with a higher proportion of actors and fewer flexible regulators in the online condition, suggesting that the screen acts as a barrier to authentic emotional display. Among the four classes, actors scored lowest on job satisfaction and highest on depression and anxiety, whereas authentic regulators were the most adaptive, especially in online settings.ConclusionsThe findings highlight the impact of online teaching on teachers’ emotional labor profiles and mental health, with practical implications for optimizing online teaching environments and supporting teacher well‐being.
Perceptions of the present shape imagined futures: Unravelling the interplay between perceived anomie, collective future thinking and collective action in the French context
Authors: Ionescu Octavia , Collange Julie , Tavani Jean Louis 
Published: October 2024

AbstractIn four studies (Ntotal = 1832 French participants), we tested if perceiving present society as disintegrated and disregulated (i.e. perceived anomie) would foster the projection of a negative national future and feelings of collective angst; which would in turn predict increased present intentions to engage in actions aimed at defending the country. Perceived anomie was measured (Pilot Study) or manipulated (Studies 1–3). In the Pilot study, we found that perceiving high disregulation in present society was associated with the evocation of distressing national futures (e.g. war/misery), stronger collective angst and greater support for action against outgroups (e.g. closing borders). Similarly, when anomie was made salient (vs. not), participants projected more negative French futures (Study 1), believed more that the situation of France will deteriorate in the future (Study 2) and reported stronger collective angst (both studies); which in turn predicted greater support/intentions to engage in different type of defensive collective action and especially anti‐immigration actions (both studies). In Study 3, the effects were not significant despite descriptive patterns in the expected direction. Altogether, these results suggest that the way people think about the national future is shaped by their perceptions of the present and contributes to predict their current actions.
Carvedilol inhibits neuronal hyperexcitability caused by epilepsy‐associated KCNT1 mutations
Authors: Di Chang , Wu Tong , Gao Kai , Li Na , Song Huifang , Wang Lili , Sun Haojie , Yi Jingyun , Zhang Xinran , Chen Jiexin , Shah Mala , Jiang Yuwu , Huang Zhuo 
Published: October 2024

Background and PurposeKCNT1 encodes a sodium‐activated potassium channel (Slack channel), and its mutation can cause several forms of epilepsy. Traditional antiepileptic medications have limited efficacy in treating patients with KCNT1 mutations. Here, we describe one heterozygous KCNT1 mutation, M267T, in a patient with EIMFS. The pathological channel properties of this mutation and its effect on neuronal excitability were investigated. Additionally, this study aimed to develop a medication for effective prevention of KCNT1 mutation‐induced seizures.Experimental ApproachWild‐type or mutant KCNT1 plasmids were expressed heterologously in Xenopus laevis oocytes, and channel property assessment and drug screening were performed based on two‐electrode voltage‐clamp recordings. The single‐channel properties were investigated using the excised inside‐out patches from HEK293T cells. Through in utero electroporation, WT and M267T Slack channels were expressed in the hippocampal CA1 pyramidal neurons in male mice, followed by the examination of the electrical properties using the whole‐cell current‐clamp technique. The kainic acid‐induced epilepsy model in male mice was used to evalute the antiseizure effects of carvedilol.Key ResultsThe KCNT1 M267T mutation enhanced Slack channel function by increasing single‐channel open probability. Through screening 16 FDA‐approved ion channel blockers, we found that carvedilol effectively reversed the mutation‐induced gain‐of‐function channel properties. Notably, the KCNT1 M267T mutation in the mouse hippocampal CA1 pyramidal neurons affected afterhyperpolarization properties and induced neuronal hyperexcitability, which was inhibited by carvedilol. Additionally, carvedilol exhibited antiseizure effects in the kainic acid‐induced epilepsy model.Conclusion and ImplicationOur findings suggest carvedilol as a new potential candidate for treatment of epilepsies.
Parents' views on out‐of‐school learning environments
Authors: Balkan‐Kiyici Fatime , Atabek‐Yigit Elif , Yavuz‐Topaloglu Melike 
Published: October 2024

AbstractWhile there are many studies in the literature on out‐of‐school learning (OSL) environments, whose importance for learning is increasingly understood, studies involving parents and their views on these environments are rarely found. However, parents' contribution is extremely important and necessary for an efficient learning process. In this study, a survey was developed to determine parents' views on OSL environments. Thirty‐seven parents were face‐to‐face interviewed regarding to their views on OSL environments. An item pool was formed based on these interviews. Then this pre‐survey was administered to 702 voluntary parents. Exploratory and confirmatory factor analyses have performed and a survey with 21 items has been obtained. The survey has three dimensions: contribution of OSL environments to children's cognitive development; contribution of OSL environments to skill development; and parents' concerns about out‐of‐school learning environments. According to the findings, a significant number of parents are aware of the contribution of out‐of‐school learning environments in terms of both cognitive and skill acquisition. Also, it is seen that the gender of the parents and the gender of their child do not make any significant difference in their views. Parents with a bachelor's degree believe that out‐of‐school learning environments will contribute more to their children's skill and cognitive development than parents with a primary and secondary school degree.
Alterations in Neuronal Nicotinic Acetylcholine Receptors in the Pathogenesis of Various Cognitive Impairments
Authors: Guan Zhi‐Zhong 
Published: October 2024

ABSTRACTCognitive impairment is a typical symptom of both neurodegenerative and certain other diseases. In connection with these different pathologies, the etiology and neurological and metabolic changes associated with cognitive impairment must differ. Until these characteristics and differences are understood in greater detail, pharmacological treatment of the different forms of cognitive impairment remains suboptimal. Neurotransmitter receptors, including neuronal nicotinic acetylcholine receptors (nAChRs), dopamine receptors, and glutamine receptors, play key roles in the functions and metabolisms of the brain. Among these, the role of nAChRs in the development of cognitive impairment has attracted more and more attention. The present review summarizes what is presently known concerning the structure, distribution, metabolism, and function of nAChRs, as well as their involvement in major cognitive disorders such as Alzheimer's disease, Parkinson's disease, vascular dementia, schizophrenia, and diabetes mellitus. As will be discussed, the relevant scientific literature reveals clearly that the α4β2 and α7 nAChR subtypes and/or subunits of the receptors play major roles in maintaining cognitive function and in neuroprotection of the brain. Accordingly, focusing on these as targets of drug therapy can be expected to lead to breakthroughs in the treatment of cognitive disorders such as AD and schizophrenia.
Closed‐incision negative‐pressure wound therapy after Bascom's cleft lift surgery for pilonidal sinus disease: A randomized study comparing healing
Authors: Faurschou Ida Kaad , Sørensen Marlene Julia , Pedersen Allan Gorm , Rasmussen Simon Ladefoged , Erichsen Rune , Haas Susanne 
Published: October 2024

AbstractAimDespite favourable outcomes in recurrence after off‐midline closure techniques in pilonidal surgery, between 18% and 40% of patients suffer from prolonged postoperative wound healing. The aim of this work was to investigate if closed‐incision negative‐pressure wound therapy (NPWT) promotes wound healing after Bascom's cleft lift (BCL) surgery for complicated pilonidal sinus disease compared with conventional drainage and dressing.MethodPatients were randomized to either NPWT for 4–7 days or loop‐vessel drain for 24 h and a dry dressing postoperatively. Healing was evaluated by a wound care nurse blinded for randomization at 2 and 12 weeks postoperatively (primary endpoint). Healing was defined as one or no closing defects of ≤5 mm and with no undermining.ResultsAlthough we had wanted to recruit 200 patients, the study was terminated at 118 patients (NPWT group, n = 60; control group, n = 58) after interim analysis. Patients were comparable by age, sex, body mass index, previous smoking status and indication for BCL surgery. At 2 weeks 12% of patients were healed in both the NPWT and control groups [risk difference = 0.00(95% CI −0.12 to 0.11), p = 1.00]. After 12 weeks, 68% of patients were healed in the NPWT group and 72% in the control group [risk difference = −0.03 (95% CI 0.19 to 0.13), p = 0.82]. There was no significant difference in pain experienced postsurgery. In a symptom‐based questionnaire, the control group reported self‐esteem to be less affected (p = 0.015).ConclusionClosed‐incision negative‐pressure wound therapy did not significantly improve healing after BCL surgery for complicated pilonidal sinus disease.
1108. Bulbophyllum boninense (Schltr.) J.J.Sm.
Authors: Yukawa Tomohisa , Yamashita Yumi , Yoneda Kaoru 
Published: October 2024

SummaryBulbophyllum boninense (Schltr.) J.J.Sm. is illustrated and described. It is endemic to the Ogasawara (Bonin) Islands, subtropical oceanic islands in the Pacific Ocean belonging to Japan. This species grows as an epiphyte on trunks and as a lithophyte on rocks in evergreen cloud forest. It can be distinguished from closely related species by the following characters: dull yellow perianth lobes, no threads or ornaments at the apex of sepal and petal, a ciliate and pustulate petal, and a long stelidium that is semicircular at the base and curved anteriorly.
A Functional Assessment of Community Vulnerability to the Loss of Myrtaceae From Myrtle Rust
Authors: McCarthy James K. , Richardson Sarah J. , Jo Insu , Wiser Susan K. , Easdale Tomás A. , Shepherd James D. , Bellingham Peter J. 
Published: October 2024

ABSTRACTAimWoody ecosystems provide critical ecosystem functions and services but are increasingly threatened as invasive pathogens spread globally. Myrtle rust, caused by Austropuccinia psidii, arrived in New Zealand in 2017 and infects at least 12 of 18 species in the susceptible Myrtaceae plant family. Among these are species of structural, successional and cultural importance. We aim to assess whether the functional consequences of Myrtaceae loss could be mitigated if co‐occurring species with shared functional attributes are able to replace them.LocationNew Zealand (but with concepts and methodologies that apply globally).MethodsUsing a nationwide forest and shrubland plot data set, we assessed community vulnerability to the loss of Myrtaceae species by analysing proportional changes in average trait values when they are absent and produced spatial predictions indicating where species loss might have the greatest impact on community functionality. We then assessed whether compensatory infilling by co‐occurring species would mediate community vulnerability.ResultsForests and shrublands containing Kunzea ericoides and Leptospermum scoparium are highly vulnerable to their loss. Areas most vulnerable overall are the central and south‐eastern North Island, north‐eastern South Island and Stewart Island. For all species, compensatory infilling moderated the impact of their loss. However, if co‐occurring Myrtaceae were unable to respond, possibly if they were also infected, community vulnerability almost always increased because infilling species had different functional attributes, compounding the functional impact.Main ConclusionsEarly successional woody plant communities and Myrtaceae‐dominated old‐growth forests are at most risk. Our spatial assessment of species‐level functional impacts from myrtle rust will facilitate better‐informed landscape‐level responses. Management actions and monitoring can now be targeted to areas and communities at greatest risk of losing ecosystem‐level processes.
Is endoscopic ultrasound‐guided gastroenterostomy better than surgical gastrojejunostomy or duodenal stenting?
Authors: Teoh Anthony Yuen Bun , Chan Shannon Melissa , Yip Hon Chi 
Published: October 2024

ObjectivesGastrojejunostomy is a critical procedure for managing gastric outlet obstruction. While surgical gastrojejunostomy has traditionally been the standard approach, endoscopic ultrasound (EUS)‐guided gastroenterostomy has emerged as a promising endoscopic alternative. This comprehensive review aims to explore the development, techniques, outcomes, and comparative effectiveness of EUS‐guided gastroenterostomy in comparison to duodenal stenting and surgical gastrojejunostomy.MethodsA comprehensive literature search was conducted using electronic databases to identify relevant studies published up to April 2024. The search included keywords related to EUS‐guided gastrojejunostomy, surgical gastrojejunostomy, and duodenal stenting. Studies reporting on technical success, clinical success, complications, recurrence rates, quality of life, and long‐term outcomes were included for analysis.ResultsThe development of EUS‐guided gastroenterostomy has evolved significantly over the years, driven by device advancements and improved endoscopic techniques. Comparative studies have shown that the technique offers several advantages, including the ability to create an anastomosis without the need for surgery, reduced invasiveness, shorter hospital stays, and potentially improved patient outcomes as compared to duodenal stenting and surgical gastrojejunostomy.ConclusionEndoscopic ultrasound‐guided gastroenterostomy represents a promising alternative to surgical gastrojejunostomy and duodenal stenting for the management of gastric outlet obstruction. The technique has evolved significantly, offering a less invasive and more effective treatment option.
Integrated approach of machine learning, Mendelian randomization and experimental validation for biomarker discovery in diabetic nephropathy
Authors: Zhu Yidong , Liu Jun , Wang Bo 
Published: October 2024

AbstractAimTo identify potential biomarkers and explore the mechanisms underlying diabetic nephropathy (DN) by integrating machine learning, Mendelian randomization (MR) and experimental validation.MethodsMicroarray and RNA‐sequencing datasets (GSE47184, GSE96804, GSE104948, GSE104954, GSE142025 and GSE175759) were obtained from the Gene Expression Omnibus database. Differential expression analysis identified the differentially expressed genes (DEGs) between patients with DN and controls. Diverse machine learning algorithms, including least absolute shrinkage and selection operator, support vector machine‐recursive feature elimination, and random forest, were used to enhance gene selection accuracy and predictive power. We integrated summary‐level data from genome‐wide association studies on DN with expression quantitative trait loci data to identify genes with potential causal relationships to DN. The predictive performance of the biomarker gene was validated using receiver operating characteristic (ROC) curves. Gene set enrichment and correlation analyses were conducted to investigate potential mechanisms. Finally, the biomarker gene was validated using quantitative real‐time polymerase chain reaction in clinical samples from patients with DN and controls.ResultsBased on identified 314 DEGs, seven characteristic genes with high predictive performance were identified using three integrated machine learning algorithms. MR analysis revealed 219 genes with significant causal effects on DN, ultimately identifying one co‐expressed gene, carbonic anhydrase II (CA2), as a key biomarker for DN. The ROC curves demonstrated the excellent predictive performance of CA2, with area under the curve values consistently above 0.878 across all datasets. Additionally, our analysis indicated a significant association between CA2 and infiltrating immune cells in DN, providing potential mechanistic insights. This biomarker was validated using clinical samples, confirming the reliability of our findings in clinical practice.ConclusionBy integrating machine learning, MR and experimental validation, we successfully identified and validated CA2 as a promising biomarker for DN with excellent predictive performance. The biomarker may play a role in the pathogenesis and progression of DN via immune‐related pathways. These findings provide important insights into the molecular mechanisms underlying DN and may inform the development of personalized treatment strategies for this disease.
Comparing Human‐Level and Machine Learning Model Performance in White Blood Cell Morphology Assessment
Authors: Lawrence Patrick , Brown Christina 
Published: October 2024

ABSTRACTIntroductionThere is an increasing research focus on the role of machine learning in the haematology laboratory, particularly in blood cell morphologic assessment. Human‐level performance is an important baseline and goal for machine learning. This study aims to assess the interobserver variability and human‐level performance in blood cell morphologic assessment.MethodsA dataset of 1000 single white blood cell images were independently labelled by 10 doctors and morphology scientists. Interobserver variability was calculated using Fleiss' kappa. Observers' labels were then separated into consensus labels used to determine ground truth, and performance labels used to assess observer performance. A machine learning model was trained and assessed using the same cell images. Explainability images (XRAI and IG) were generated for each of the test images.ResultsThe Fleiss kappa for all 10 observers was 0.608, indicating substantial agreement between observers. The accuracy of human observers was 95%, with sensitivity 72% and specificity 97%. The accuracy of the machine learning model was 95%, with sensitivity 71% and specificity 97%. The model shared similar performance across labels when compared to humans. Explainability metrics demonstrated that the machine learning model was able to differentiate between the cytoplasm and nucleus of the cells, and used these features to perform predictions.ConclusionThe substantial, though not perfect, agreement between human observers highlights the inherent subjectivity in white blood cell morphologic assessment. A machine learning model performed similarly to human observers in single white blood cell identification. Further research is needed to compare human‐level and machine learning performance in ways that more closely reflect the typical process of morphologic assessment.
Mapping soil thickness by accounting for right‐censored data with survival probabilities and machine learning
Authors: van der Westhuizen Stephan , Heuvelink Gerard B. M. , Hofmeyr David P. , Poggio Laura , Nussbaum Madlene , Brungard Colby 
Published: October 2024

AbstractIn digital soil mapping, modelling soil thickness poses a challenge due to the prevalent issue of right‐censored data. This means that the true soil thickness exceeds the depth of sampling, and neglecting to account for the censored nature of the data can lead to poor model performance and underestimation of the true soil thickness. Survival analysis is a well‐established domain of statistical modelling that can deal with censored data. The random survival forest is a notable example of a survival‐related machine learning approach used to address right‐censored soil property data in digital soil mapping. Previous studies that employed this model either focused on mapping the probability of soil thickness exceeding certain depths, and thereby not mapping soil thickness itself, or dismissed it due to perceived poor performance. In this study, we propose an alternative survival model to map soil thickness that is based on the inverse probability of censoring weighting. In this approach, calibration data are weighted by the inverse of the probability that soil thickness exceeds a certain depth, that is, a survival probability. These weights can then be used with most machine learning models. We used the weights with a regular random forest, and compared it with a random survival forest, and other strategies for handling right‐censored data, through a comprehensive synthetic simulation study and two real‐world case studies. The results suggest that the weighted random forest model produces competitive predictions, establishing it as a viable option for mapping right‐censored soil property data.