Research on music therapy from 2013 to 2022: a bibliometric and visualized study.

Background: Music therapy is a rapidly evolving multidisciplinary field. But there has been no research analyzing the latest research status and development trends in this research field from a macro perspective. We aim to identify hotspots, knowledge base, and frontiers in the field of music therapy through bibliometric analysis. Methods: All data were retrieved from the Web of Science core database from January 1, 2013 to December 31, 2022.CiteSpace and Bibliometrix software were employed for bibliometric analysis and visualization analysis. Results: A total of 2,397 articles were included. In the past decade, there has been a consistent increase in the number of publications. The countries and institutions with the largest production in this field are the USA and the University of London. Based on the analysis of the total number of citations, centrality, and production, the results show that the most influential journals are PLoS One and Cochrane Database Syst Rev. Keyword co-occurrence analysis and highly cited study analysis are mainly used to analyze research hotspots in the field of music therapy, while the keyword burst analysis is employed to explore frontiers and potential developmental trends. Hot keywords include "interventions", "anxiety" and "randomized controlled trial". The burst keywords include "validity", "preterm infants", and "mild cognitive impairment". In the ranking of highly cited study, the top ranked studies are "Music-based interventions in neurological rehabilitation" and "Music interventions for improving psychological and physical outcomes in cancer patients". Conclusion: In the past decade, the research focus in music therapy was the effect of music therapy on neurological diseases and the improvement of psychological symptoms such as pain and anxiety. The neurophysiological mechanisms that bring about these therapeutic effects need to be future researched.

Using an interactive web application to identify pre-exposure prophylaxis adherence among men who have sex with men.

Background: Men who have sex with men (MSM) are at a high risk for HIV infection. While pre-exposure prophylaxis (PrEP) is an effective oral preventive strategy, its success is largely dependent on consistent medication adherence. Objective: The aim of this study was to develop the machine learning web application and evaluate the performance in predicting PrEP adherence. Methods: The PrEP prospective cohort study of the MSM population conducted in Western China from 2019 to 2023, and we collected adherence data and personal characteristics data from 747 MSM. Predictor variables were screened and the performance of several machine learning methods in predicting nonadherent behaviors were compared. Results: A total of 11 candidate variables were screened that predicted nonadherent behaviors. We developed and evaluated five machine learning models that performed well in predicting adherence. Attitudes of male sexual partners, self-efficacy, HIV testing, number of male sexual partners, and risk perception were the most important predictors of adherence. The optimal prediction model was displayed in a shiny web application for online calculation of the probability of occurrence of nonadherent behaviors among MSM. Conclusions: Machine learning performed well in predicting nonadherent behaviors among MSM. An interactive and intuitive web application can help identify individuals who may have nonadherent behaviors, resulting in improved medication adherence and increased prevention efficacy.

An internet-based self-help intervention for the reduction of consumption of ultra-processed products and increase of physical activity in Mexican university population: study protocol for a randomized controlled trial.

Introduction: The consumption of ultra-processed products has been associated with the etiology of various diseases, mainly metabolic diseases. On the other hand, physical activity acts as a protective factor that helps prevent the appearance of this type of disease. In addition to the physical effects, both the consumption of ultra-processed products (UPPs) and sedentary behaviors have been associated with a significant impact on people's mental health. These problems occur significantly in university students. Online internet interventions are an alternative that has the advantage of reaching a broader sample size and adapting to various problems. Methods: A randomized controlled clinical superiority trial with two independent groups will be developed with 176 participants. Participants in both groups will be evaluated in 5 steps: (1) pretest, (2) middle of the intervention, (3) post-test, (4) follow-up at 3 months, and (5) follow-up at 6 months. In the experimental group ("UNISALUD"), participants will receive an intervention composed of 11 sessions with interactive elements such as videos, audio, and infographics created through the user experience (UX) principles and based on the health action process approach (HAPA). The participants in the control group will be on the waiting list and will receive treatment 27 days after fulfilling the inclusion criteria. Thus, participants will not receive the treatment immediately. Discussion: The study is expected to establish the feasibility of a self-help internet-based intervention created based on the user experience methodology and the health action process model, leading to a significant decrease and increase in the consumption of UPPs, ultra-healthy products, and physical activity, respectively. Conclusion: Internet-based interventions are scarce in Latin America. Due to their potential, this study will provide data about consumption of UPPs, physical activity, and mental health of the Mexican population, which will influence the reduction of health-related complications through prevention strategies or measures.Clinical Trial Registration:ClinicalTrials.gov, NCT05834842.

Bibliometric and visual analysis of global publications on kaempferol.

Introduction: Kaempferol, a flavonoid found in numerous foods and medicinal plants, offers a range of health benefits such as anti-inflammatory, antioxidant, antiviral, anticancer, cardioprotective, and neuroprotective effects. Methods: Herein, a bibliometric and visual analysis of global publications on kaempferol was performed to map the evolution of frontiers and hotspots in the field. Using the search string TS = kaempferol, bibliometric data for this analysis was extracted from the Web of Science Core Collection database and analyzed using the VOSviewer, CiteSpace, and Scimago Graphica software. Results: As a result, by February 26, 2024, 11,214 publications were identified, comprising articles (n = 10,746, 96%) and review articles (n = 468, 4%). Globally, the annual number of kaempferol publications surpassed 100 per year since 2000, exceeded 500 per year since 2018, and further crossed the threshold of 1,000 per year starting in 2022. The major contributing countries were China, the United States of America, and India, while the top three institutes of the citations of kaempferol were the Chinese Academy of Sciences, Consejo Superio de Investigaciones Cientficas, and Uniersidade do Porto. These publications were mainly published in agricultural and food chemistry journals, food chemistry, and phytochemistry. Discussion: The keywords frequently mentioned include phenolic compounds, antioxidant activity, flavonoids, NF-kappa B, inflammation, bioactive compounds, etc. Anti-inflammation, anti-oxidation, and anti-cancer have consistently been the focus of kaempferol research, while cardiovascular protection, neuroprotection, antiviral, and anti-bacterial effects have emerged as recent highlights. The field of kaempferol research is thriving.

A unified web cloud computing platform MiMedSurv for microbiome causal mediation analysis with survival responses.

In human microbiome studies, mediation analysis has recently been spotlighted as a practical and powerful analytic tool to survey the causal roles of the microbiome as a mediator to explain the observed relationships between a medical treatment/environmental exposure and a human disease. We also note that, in a clinical research, investigators often trace disease progression sequentially in time; as such, time-to-event (e.g., time-to-disease, time-to-cure) responses, known as survival responses, are prevalent as a surrogate variable for human health or disease. In this paper, we introduce a web cloud computing platform, named as microbiome mediation analysis with survival responses (MiMedSurv), for comprehensive microbiome mediation analysis with survival responses on user-friendly web environments. MiMedSurv is an extension of our prior web cloud computing platform, named as microbiome mediation analysis (MiMed), for survival responses. The two main features that are well-distinguished are as follows. First, MiMedSurv conducts some baseline exploratory non-mediational survival analysis, not involving microbiome, to survey the disparity in survival response between medical treatments/environmental exposures. Then, MiMedSurv identifies the mediating roles of the microbiome in various aspects: (i) as a microbial ecosystem using ecological indices (e.g., alpha and beta diversity indices) and (ii) as individual microbial taxa in various hierarchies (e.g., phyla, classes, orders, families, genera, species). To illustrate its use, we survey the mediating roles of the gut microbiome between antibiotic treatment and time-to-type 1 diabetes. MiMedSurv is freely available on our web server ( http://mimedsurv.micloud.kr ).

3dRNA/DNA: 3D Structure Prediction from RNA to DNA.

There is an increasing need for determining 3D structures of DNAs, e.g., for increasing the efficiency of DNA aptamer selection. Recently, we have proposed a computational method of 3D structure prediction of DNAs, called 3dDNA, which has been integrated into our original web server 3dRNA, now renamed 3dRNA/DNA (http://biophy.hust.edu.cn/new/3dRNA). Currently, 3dDNA can only output the predicted DNA 3D structures for users but cannot rank them as an energy function for assessing DNA 3D structures is still lacking. Here, we first provide a brief introduction to 3dDNA and then introduce a new energy function, 3dDNAscore, for the assessment of DNA 3D structures. 3dDNAscore is an all-atom knowledge-based potential by integrating 86 atomic types from nucleic acids. Benchmarks demonstrate that 3dDNAscore can effectively identify near-native structures from the decoys generated by 3dDNA, thus enhancing the completeness of 3dDNA.

scRNA-Explorer: An End-user Online Tool for Single Cell RNA-seq Data Analysis Featuring Gene Correlation and Data Filtering.

In the majority of downstream analysis pipelines for single-cell RNA sequencing (scRNA-seq), techniques like dimensionality reduction and feature selection are employed to address the problem of high-dimensional nature of the data. These approaches involve mapping the data onto a lower-dimensional space, eliminating less informative genes, and pinpointing the most pertinent features. This process ultimately leads to a reduction in the number of dimensions used for downstream analysis, which in turn speeds up the computation of large-scale scRNA-seq data. Most approaches are directed to isolate from biological background the genes characterizing different cells and or the condition under study by establishing lists of differentially expressed or coexpressed genes. Herein, we present scRNA-Explorer an open-source online tool for simplified and rapid scRNA-seq analysis designed with the end user in mind. scRNA-Explorer utilizes: (i) Filtering out uninformative cells in an interactive manner via a web interface, (ii) Gene correlation analysis coupled with an extra step of evaluating the biological importance of these correlations, and (iii) Gene enrichment analysis of correlated genes in order to find gene implication in specific functions. We developed a pipeline to address the above problem. The scRNA-Explorer pipeline allows users to interrogate in an interactive manner scRNA-sequencing data sets to explore via gene expression correlations possible function(s) of a gene of interest. scRNA-Explorer can be accessed at https://bioinformatics.med.uoc.gr/shinyapps/app/scrnaexplorer.

Fungtion: A Server for Predicting and Visualizing Fungal Effector Proteins.

Fungal pathogens pose significant threats to plant health by secreting effectors that manipulate plant-host defences. However, identifying effector proteins remains challenging, in part because they lack common sequence motifs. Here, we introduce Fungtion (Fungal effector prediction), a toolkit leveraging a hybrid framework to accurately predict and visualize fungal effectors. By combining global patterns learned from pretrained protein language models with refined information from known effectors, Fungtion achieves state-of-the-art prediction performance. Additionally, the interactive visualizations we have developed enable researchers to explore both sequence- and high-level relationships between the predicted and known effectors, facilitating effector function discovery, annotation, and hypothesis formulation regarding plant-pathogen interactions. We anticipate Fungtion to be a valuable resource for biologists seeking deeper insights into fungal effector functions and for computational biologists aiming to develop future methodologies for fungal effector prediction: https://step3.erc.monash.edu/Fungtion/.

E-pRSA: Embeddings Improve the Prediction of Residue Relative Solvent Accessibility in Protein Sequence.

Knowledge of the solvent accessibility of residues in a protein is essential for different applications, including the identification of interacting surfaces in protein-protein interactions and the characterization of variations. We describe E-pRSA, a novel web server to estimate Relative Solvent Accessibility values (RSAs) of residues directly from a protein sequence. The method exploits two complementary Protein Language Models to provide fast and accurate predictions. When benchmarked on different blind test sets, E-pRSA scores at the state-of-the-art, and outperforms a previous method we developed, DeepREx, which was based on sequence profiles after Multiple Sequence Alignments. The E-pRSA web server is freely available at https://e-prsa.biocomp.unibo.it/main/ where users can submit single-sequence and batch jobs.

A Bibliometric study of the top 100 most-cited papers in high tibial osteotomy.

Background: High tibial osteotomy (HTO) is a well-established surgical procedure employed to treat medial compartment knee osteoarthritis by modifying the mechanical axis of the lower limb, thereby reducing the load on the affected joint. It has gained increased attention in recent years, resulting in numerous research advancements in this field. Methods: The top 100 most-cited papers on HTO, published between 1970 and 2023, were identified by searching the Web of Science Core Collection database. Data, including the title, author, keywords, journal, publication year, country, and institution, were extracted. Subsequently, a bibliometric analysis was performed. Results: The 100 papers collectively garnered a total of 15 833 citations, with a median of 122 and an average of 158.33 citations per article. Since the onset of the 21st century, there has been a significant increase in the number of publications and citations. Lobenhoffer authored the most published papers. The majority of papers originated from the USA. Hannover Medical School produced the most papers. Analysis of keywords in the articles revealed several research hotspots, including open-wedge osteotomy, biomechanical study, tibial slope, patellar height, Puddu plate, TomoFix plate, stability, complications, and accuracy. Conclusion: This study offers bibliometric insights into HTO, underscoring that the USA is a prominent leader in this field. HTO has garnered increasing attention since the onset of the 21st century and is expected to remain a significant research area in the future. Concurrently, the authors advise focusing on potential research hotspots, such as the navigation system, to augment the accuracy of the correction.

Harnessing Innovative Technologies to Train Nurses in Suicide Safety Planning With Hospital Patients: Formative Acceptability Evaluation of an eLearning Continuing Education Training.

BACKGROUND: Suicide is the 12th leading cause of death in the United States. Health care provider training is a top research priority identified by the National Action Alliance for Suicide Prevention; however, evidence-based approaches that target skill building are resource intensive and difficult to implement. Novel computer technologies harnessing artificial intelligence are now available, which hold promise for increasing the feasibility of providing trainees opportunities across a range of continuing education contexts to engage in skills practice with constructive feedback on performance. OBJECTIVE: This pilot study aims to evaluate the feasibility and acceptability of an eLearning training in suicide safety planning among nurses serving patients admitted to a US level 1 trauma center for acute or intensive care. The training included a didactic portion with demonstration, practice of microcounseling skills with a web-based virtual patient (Client Bot Emily), role-play with a patient actor, and automated coding and feedback on general counseling skills based on the role-play via a web-based platform (Lyssn Advisor). Secondarily, we examined learning outcomes of knowledge, confidence, and skills in suicide safety planning descriptively. METHODS: Acute and intensive care nurses were recruited between November 1, 2021, and May 31, 2022, to participate in a formative evaluation using pretraining, posttraining, and 6-month follow-up surveys, as well as observation of the nurses' performance in delivering suicide safety planning via standardized patient role-plays over 6 months and rated using the Safety Plan Intervention Rating Scale. Nurses completed the System Usability Scale after interacting with Client Bot Emily and reviewing general counseling scores based on their role-play via Lyssn Advisor. RESULTS: A total of 18 nurses participated in the study; the majority identified as female (n=17, 94%) and White (n=13, 72%). Of the 17 nurses who started the training, 82% (n=14) completed it. On average, the System Usability Scale score for Client Bot Emily was 70.3 (SD 19.7) and for Lyssn Advisor was 65.4 (SD 16.3). On average, nurses endorsed a good bit of knowledge (mean 3.1, SD 0.5) and confidence (mean 2.9, SD 0.5) after the training. After completing the training, none of the nurses scored above the expert-derived cutoff for proficiency on the Safety Plan Intervention Rating Scale (≥14); however, on average, nurses were above the cutoffs for general counseling skills per Lyssn Advisor (empathy: mean 4.1, SD 0.6; collaboration: mean 3.6, SD 0.7). CONCLUSIONS: Findings suggest the completion of the training activities and use of novel technologies within this context are feasible. Technologic modifications may enhance the training acceptability and utility, such as increasing the virtual patient conversational abilities and adding automated coding capability for specific suicide safety planning skills. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/33695.

Bibliometrics analysis on the research status and trends of small bowel adenocarcinoma: 1923-2023.

Objectives: The aim of this research is to discuss the research status, hotspots, frontiers, and development trends in the field of small bowel adenocarcinoma based on bibliometrics and visual analysis by CiteSpace software. Methods: The relevant research articles on SBA from 1923 to 2023 were retrieved from the Web of Science Core Collection database. CiteSpace software was used to form a visual knowledge map and conduct analysis for the countries/regions, journals, authors, keywords, clusters, research hotspots and frontiers of the included articles. Results: There were 921 articles included, and the number of articles published during 1923-2023 is increasing. The country with the highest number of articles published was the United States (443, 38.76%), followed by Japan (84, 9.12%) and France (72, 7.82%). The author with the highest number of publications is Ansell, Overman MJ (33, 3.58%), and the author with the highest co-citation frequency is Overman MJ (218). Journal of Clinical Oncology is the journal with the highest publication frequency. The top five cluster groups were "chemotherapy", "inflammatory bowel disease", "celiac disease", "tumor" and "small intestine". The related disease, chemotherapy drugs, and treatment regimens of SBA form the main research fields, and prognosis and diagnosis are the research hotspots and trends. Conclusion: The global research field in SBA has expanded in the past 100 years. The prognosis and new diagnosis of SBA are hotspots in this field and require further study in the future.

Testing food web theory in a large lake: The role of body size in habitat coupling in Lake Michigan.

The landscape theory of food web architecture (LTFWA) describes relationships among body size, trophic position, mobility, and energy channels that serve to couple heterogenous habitats, which in turn promotes long-term system stability. However, empirical tests of the LTFWA are rare and support differs among terrestrial, freshwater, and marine systems. Further, it is unclear whether the theory applies in highly altered ecosystems dominated by introduced species such as the Laurentian Great Lakes. Here, we provide an empirical test of the LTFWA by relating body size, trophic position, and the coupling of different energy channels using stable isotope data from species throughout the Lake Michigan food web. We found that body size was positively related to trophic position, but for a given trophic position, organisms predominately supported by pelagic energy had smaller body sizes than organisms predominately supported by nearshore benthic energy. We also found a hump-shaped trophic relationship in the food web where there is a gradual increase in the coupling of pelagic and nearshore energy channels with larger body sizes as well as higher trophic positions. This highlights the important role of body size and connectivity among habitats in structuring food webs. However, important deviations from expectations are suggestive of how species introductions and other anthropogenic impacts can affect food web structure in large lakes. First, native top predators appear to be flexible couplers that may provide food web resilience, whereas introduced top predators may confer less stability when they specialize on a single energy pathway. Second, some smaller bodied prey fish and invertebrates, in addition to mobile predators, coupled energy from pelagic and nearshore energy channels, which suggests that some prey species may also be important integrators of energy pathways in the system. We conclude that patterns predicted by the LTFWA are present in the face of species introductions and other anthropogenic stressors to a degree, but time-series evaluations are needed to fully understand the mechanisms that promote stability.

The Relationship Between Symptom Change and Use of a Web-Based Self-Help Intervention for Parents of Children With Externalizing Behavior Disorders: Exploratory Study.

BACKGROUND: Web-based self-help (WASH) has been found to be effective in the treatment of child externalizing behavior disorders. However, research on the associations of caregivers' use of WASH and symptom changes of child externalizing behaviors is lacking. OBJECTIVE: This study examined the longitudinal and reciprocal associations between the use of WASH by caregivers of children with externalizing behavior disorders and their children's externalizing behavior symptoms. METHODS: Longitudinal data of 276 families from 2 intervention conditions of a randomized controlled trial (either unguided or supported by a therapist over the phone) were analyzed. Caregiver- and clinician-rated child externalizing behavior symptoms were assessed before (T1), in the middle (T2), and after the 6-month WASH intervention (T3). Additionally, 2 indicators of the caregivers' use of the WASH intervention were considered: number of log-ins (frequency) and the percentage of completed material (intensity). Associations of caregivers' use during early (T1-T2) and late (T2-T3) treatment with child externalizing behavior symptoms were analyzed using path analyses (structural equation modeling). RESULTS: Frequency and intensity of use were higher during the first 3 months than during the next 3 months of the intervention period. The number of log-ins at early treatment was significantly but weakly associated with caregiver-reported child externalizing behavior symptoms in the long term (T3). Moreover, caregiver-reported child externalizing severity at T2 predicted the number of log-ins in the late treatment. The results were not replicated when considering the percentage of completed material as a measure of use or when considering clinician ratings of child externalizing behavior symptoms. CONCLUSIONS: The findings provide the first, albeit weak, evidence for longitudinal associations between caregivers' use of WASH and improvements in caregiver-rated child externalizing behavior symptoms. However, as the associations were rather weak and could not be replicated across different rater perspectives and operationalizations of use, further research is needed to better understand these relations and their interplay with other putative influence factors (eg, quality of the implementation of the interventions, changes in parenting behaviors). TRIAL REGISTRATION: German Clinical Trials Register DRKS00013456; https://www.drks.de/DRKS00013456. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12888-020-2481-0.

Effects of beta-blockers on quality of life and well-being in patients with myocardial infarction and preserved left ventricular function-a prespecified substudy from REDUCE-AMI.

AIMS: In the Randomized Evaluation of Decreased Usage of Beta-Blockers after Acute Myocardial Infarction (REDUCE-AMI) study, long-term beta-blocker use in patients after acute myocardial infarction (AMI) with preserved left ventricular ejection fraction demonstrated no effect on death or cardiovascular outcomes. The aim of this prespecified substudy was to investigate effects of beta-blockers on self-reported quality of life and well-being. METHODS AND RESULTS: From this parallel-group, open-label, registry-based randomized clinical trial, EQ-5D, and World Health Organization well-being index-5 (WHO-5) questionnaires were obtained at 6-10 weeks and 11-13 months after AMI in 4080 and 806 patients, respectively. We report results from intention-to-treat and on-treatment analyses for the overall population and relevant subgroups using Wilcoxon rank sum test and adjusted ordinal regression analyses. Of the 4080 individuals reporting EQ-5D (median age 64 years, 22% female), 2023 were randomized to beta-blockers. The main outcome, median EQ-5D index score, was 0.94 [interquartile range (IQR) 0.88, 0.97] in the beta-blocker group, and 0.94 (IQR 0.88, 0.97) in the no-beta-blocker group 6-10 weeks after AMI, OR 1.00 [95% CI 0.89-1.13; P > 0.9]. After 11-13 months, results remained unchanged. Findings were robust in on-treatment analyses and across relevant subgroups. Secondary outcomes, EQ-VAS and WHO-5 index score, confirmed these results. CONCLUSION: Among patients after AMI with preserved left ventricular ejection fraction, self-reported quality of life and well-being was not significantly different in individuals randomized to routine long-term beta-blocker therapy as compared to individuals with no beta-blocker use. These results appear consistent regardless of adherence to randomized treatment and across subgroups which emphasizes the need for a careful individual risk-benefit evaluation prior to initiation of beta-blocker treatment.

An Evaluation of the Content Quality, Readability, and Reliability of Publicly Available Web-Based Information on Pneumothorax Surgery in Ireland.

Introduction The internet is increasingly the first port of call for patients introduced to new treatments. Unfortunately, many websites are of poor quality, thereby limiting patients' ability to make informed health decisions. Within thoracic surgery, the treatment options for pneumothoraces may be less intuitive for patients to understand compared to procedures such as lobectomies and wedge resections. Therefore, patients must receive high-quality information to make informed treatment decisions. No study to date has evaluated online information regarding pneumothorax surgery. Knowledge regarding the same may allow physicians to recommend appropriate websites to patients and supplement remaining knowledge gaps. Objective This study aims to evaluate the content, readability, and reliability of online information regarding pneumothorax surgery. Methods A total of 11 search terms including "pneumothorax surgery," "pleurectomy," and "pleurodesis" were each entered into Google, Bing, and Yahoo. The top 20 websites found through each search were screened, yielding 660 websites. Only free websites designed for patient consumption that provided information on pneumothorax surgery were included. This criterion excluded 581 websites, leaving 79 websites to be evaluated. To evaluate website reliability, the Journal of American Medical Association (JAMA) and DISCERN benchmark criteria were applied. To evaluate the readability, 10 standardized tools were utilized including the Flesch-Kincaid Reading Ease Score. To evaluate website content, a novel, self-designed 10-part questionnaire was utilized to assess whether information deemed essential by the authors was included. It evaluated whether websites comprehensively described the surgery process for patients, including pre- and post-operative care. Website authorship and year of publication were also noted. Results The mean JAMA score was 1.69 ± 1.29 out of 4, with only nine websites achieving all four reliability criteria. The median readability score was 13.42 (IQR: 11.48-16.23), which corresponded to a 13th-14th school grade standard. Only four websites were written at a sixth-grade reading level. In the novel content questionnaire, 31.6% of websites (n = 25) did not mention any side effects of pneumothorax surgery. Similarly, 39.2% (n = 31) did not mention alternative treatment options. There was no correlation between the date of website update and JAMA (r = 0.158, p = 0.123), DISCERN (r = 0.098, p = 0.341), or readability (r = 0.053, p = 0.606) scores. Conclusion Most websites were written above the sixth-grade reading level, as recommended by the US Department of Health and Human Services. Furthermore, the exclusion of essential information regarding pneumothorax surgery from websites highlights the current gaps in online information. These findings emphasize the need to create and disseminate comprehensive, reliable websites on pneumothorax surgery that enable patients to make informed health decisions.

COVIDHealth: A novel labeled dataset and machine learning-based web application for classifying COVID-19 discourses on Twitter.

The COVID-19 pandemic has sparked widespread health-related discussions on social media platforms like Twitter (now named 'X'). However, the lack of labeled Twitter data poses significant challenges for theme-based classification and tweet aggregation. To address this gap, we developed a machine learning-based web application that automatically classifies COVID-19 discourses into five categories: health risks, prevention, symptoms, transmission, and treatment. We collected and labeled 6,667 COVID-19-related tweets using the Twitter API, and applied various feature extraction methods to extract relevant features. We then compared the performance of seven classical machine learning algorithms (Decision Tree, Random Forest, Stochastic Gradient Descent, Adaboost, K-Nearest Neighbor, Logistic Regression, and Linear SVC) and four deep learning techniques (LSTM, CNN, RNN, and BERT) for classification. Our results show that the CNN achieved the highest precision (90.41%), recall (90.4%), F1 score (90.4%), and accuracy (90.4%). The Linear SVC algorithm exhibited the highest precision (85.71%), recall (86.94%), and F1 score (86.13%) among classical machine learning approaches. Our study advances the field of health-related data analysis and classification, and offers a publicly accessible web-based tool for public health researchers and practitioners. This tool has the potential to support addressing public health challenges and enhancing awareness during pandemics. The dataset and application are accessible at https://github.com/Bishal16/COVID19-Health-Related-Data-Classification-Website.

The Web-based Open-access Reliable Decision on Synonyms (WORDS) English Vocabulary Test.

A quick and reliable test of vocabulary knowledge is a vital component of many studies looking at a range of language processing skills. Recent proliferation of online (web-based) research has generated a growing need for reliable open-access vocabulary tests that can be administered online. This data report presents the newly developed 30-item Web-based Open-access Reliable Decision on Synonyms (WORDS) English Vocabulary Test. In Experiment 1, we tested 109 participants (age range: 18-69 years) on an initial set of 51 potential multiple-choice test items in which participants read a target word (e.g., ubiquitous) and selected a (near-)synonym (e.g., omnipresent) from among three semantically unrelated foils (e.g., interpersonal, catatonic, voluminous). We conducted an item response theory analysis of participants' accuracy data to select an optimal subset of 30 items to include in the final version of the test. In Experiment 2, we verified the reliability of this 30-item version in a different sample (N = 121; 18-79 years); reliability (internal consistency) was good (Cronbach's α = 0.82). We confirmed that, consistent with numerous previous studies, (1) responses were more accurate and quicker for more frequent compared to less frequent words, and (2) older adults showed greater vocabulary knowledge compared to younger adults. The WORDS test takes on average 4 minutes (5 minutes 40 seconds including consent/debrief) to complete. It can be freely accessed via Gorilla Open Materials (https://app.gorilla.sc/openmaterials/694887), allowing ease of use and for useful comparisons between data collected by different researchers.

Acanthamoeba castellanii alone is not a growth promoter for Hordeum vulgare.

Protists are important key players in the microbial loop and influence their environment by grazing, which leads to the return of nutrients into the soil and reduces pathogen pressure on plants. Specifically, protists on and around plant roots are important for plants' development and growth. For this study, the fourth most important crop in the world, Hordeum vulgare, was selected. Seeds of H. vulgare were inoculated with Acanthamoeba castellanii alone or with additional soil bacteria at the beginning and during the experiment. The germination of the seeds and the growth of the plants in pouches were monitored over 3 weeks. No differences were found in leaf growth, root growth, root and leaf nitrogen content or ammonia content of the liquid from the pouches. In contrast, the relative increase in root and leaf dry weight showed a small difference compared to the controls. The results of this experiment demonstrated that seed inoculation with A. castellanii alone or with additional unidentified soil bacteria did not have a major effect on the growth and development of barley. Nevertheless, small changes in plant development were detected, indicating that A. castellanii should be considered for further investigation of co-inoculations with plant growth-promoting bacteria and additional nutrients.

What are the 100 most cited fungal genera?

The global diversity of fungi has been estimated between 2 to 11 million species, of which only about 155 000 have been named. Most fungi are invisible to the unaided eye, but they represent a major component of biodiversity on our planet, and play essential ecological roles, supporting life as we know it. Although approximately 20 000 fungal genera are presently recognised, the ecology of most remains undetermined. Despite all this diversity, the mycological community actively researches some fungal genera more commonly than others. This poses an interesting question: why have some fungal genera impacted mycology and related fields more than others? To address this issue, we conducted a bibliometric analysis to identify the top 100 most cited fungal genera. A thorough database search of the Web of Science, Google Scholar, and PubMed was performed to establish which genera are most cited. The most cited 10 genera are Saccharomyces, Candida, Aspergillus, Fusarium, Penicillium, Trichoderma, Botrytis, Pichia, Cryptococcus and Alternaria. Case studies are presented for the 100 most cited genera with general background, notes on their ecology and economic significance and important research advances. This paper provides a historic overview of scientific research of these genera and the prospect for further research. Citation: Bhunjun CS, Chen YJ, Phukhamsakda C, Boekhout T, Groenewald JZ, McKenzie EHC, Francisco EC, Frisvad JC, Groenewald M, Hurdeal VG, Luangsa-ard J, Perrone G, Visagie CM, Bai FY, Blaszkowski J, Braun U, de Souza FA, de Queiroz MB, Dutta AK, Gonkhom D, Goto BT, Guarnaccia V, Hagen F, Houbraken J, Lachance MA, Li JJ, Luo KY, Magurno F, Mongkolsamrit S, Robert V, Roy N, Tibpromma S, Wanasinghe DN, Wang DQ, Wei DP, Zhao CL, Aiphuk W, Ajayi-Oyetunde O, Arantes TD, Araujo JC, Begerow D, Bakhshi M, Barbosa RN, Behrens FH, Bensch K, Bezerra JDP, Bilanski P, Bradley CA, Bubner B, Burgess TI, Buyck B, Cadez N, Cai L, Calaça FJS, Campbell LJ, Chaverri P, Chen YY, Chethana KWT, Coetzee B, Costa MM, Chen Q, Custódio FA, Dai YC, Damm U, de Azevedo Santiago ALCM, De Miccolis Angelini RM, Dijksterhuis J, Dissanayake AJ, Doilom M, Dong W, Alvarez-Duarte E, Fischer M, Gajanayake AJ, Gené J, Gomdola D, Gomes AAM, Hausner G, He MQ, Hou L, Iturrieta-González I, Jami F, Jankowiak R, Jayawardena RS, Kandemir H, Kiss L, Kobmoo N, Kowalski T, Landi L, Lin CG, Liu JK, Liu XB, Loizides M, Luangharn T, Maharachchikumbura SSN, Makhathini Mkhwanazi GJ, Manawasinghe IS, Marin-Felix Y, McTaggart AR, Moreau PA, Morozova OV, Mostert L, Osiewacz HD, Pem D, Phookamsak R, Pollastro S, Pordel A, Poyntner C, Phillips AJL, Phonemany M, Promputtha I, Rathnayaka AR, Rodrigues AM, Romanazzi G, Rothmann L, Salgado-Salazar C, Sandoval-Denis M, Saupe SJ, Scholler M, Scott P, Shivas RG, Silar P, Souza-Motta CM, Silva-Filho AGS, Spies CFJ, Stchigel AM, Sterflinger K, Summerbell RC, Svetasheva TY, Takamatsu S, Theelen B, Theodoro RC, Thines M, Thongklang N, Torres R, Turchetti B, van den Brule T, Wang XW, Wartchow F, Welti S, Wijesinghe SN, Wu F, Xu R, Yang ZL, Yilmaz N, Yurkov A, Zhao L, Zhao RL, Zhou N, Hyde KD, Crous PW (2024). What are the 100 most cited fungal genera? Studies in Mycology 108: 1-411. doi: 10.3114/sim.2024.108.01.