bluuebunny/crossref_metadata_2025_split huggingface dataset:
Health-Related Quality-of-Life Effects of Rectus Repair during Body Contouring Surgery in Postbariatric Patients: A Prospective Study
Authors: Wilting Roy , Lier Bastiaan , de Vries Claire E. , Dalaei Farima , Poulsen Lotte , Luketina Rosalia , Repo Jussi P. , Paul Marek ,   BODY-Q Network, Hoogbergen Maarten 
Published: October 2023

Background:
Massive weight loss after bariatric surgery often leads to psychological and physical dissatisfaction, resulting in an increased demand for body contouring surgery (BCS). As a result of these operations, health-related quality of life (HRQL) is improved. However, little is known about the impact of rectus plication during BCS on HRQL.

Methods:
This multicenter prospective cohort study included postbariatric primary BCS patients with a minimum follow-up period of 12 months between January of 2016 and December of 2019. Patients were divided into 2 groups based on plication status. Using the BODY-Q, a patient-reported outcome measure, HRQL was measured preoperatively and at least 12 months postoperatively. Six HRQL domains were investigated: body image, physical function, psychological function, sexual function, social function, and physical symptoms.

Results:
A total of 305 patients were included in this study: 201 of these patients (66%) did not undergo plication, whereas 104 patients (34%) did. HRQL improved significantly 12 months after BCS in all measured domains, regardless of plication status. Delta scores were significantly higher in the plication group in all HRQL domains. After adjusting for baseline score and other significant variables through multivariate linear regression, 3 scales remained significant: body image (P = 0.001), psychological function (P = 0.035), and sexual function (P = 0.035).

Conclusions:
Three of 6 HRQL domains showed significant improvement after BCS with rectus plication, predominantly body image. Preoperative counseling and surgical planning could benefit from this information. The long-term effects of rectus plication on HRQL should be explored in future research.

CLINICAL QUESTION/LEVEL OF EVIDENCE:
Therapeutic, III.
A systematic scoping review protocol to summarise and appraise the use of artificial intelligence in the analysis of digital videos of invasive general surgical procedures
Authors: King Anni , Fowler George , Macefield Rhiannon C. , Quek Fang-Fang , Walker Hamish , Thomas Charlie , Markar Sheraz , Blazeby Jane M. , Blencowe Natalie S. 
Published: October 2023

Background:
Intraoperative video recordings are a valuable addition to operative written documentation. However, the review of these videos often requires surgical expertise and takes considerable time. While a large amount of work has been undertaken to understand the role of artificial intelligence (AI) in healthcare more generally, the application of these techniques to automate the analysis of surgical videos is currently unclear. In this systematic scoping review, we sought to give a contemporary overview of the use of AI research in the analysis of digital videos of invasive general surgical procedures. We will describe and summarise the study characteristics, purpose of the applications and stage of development, to ascertain how these techniques might be applied in future research and to identify gaps in current knowledge (e.g. uncertainties about the study methods).

Methods:
Systematic searches will be conducted in OVID Medline and Embase, using terms related to ‘artificial intelligence’, ‘surgery’ and ‘video’ to identify all potentially relevant studies published since 1st January 2012. All primary studies where AI has been applied to the analysis of videos (recorded by conventional digital cameras or laparoscopic or robotic-assisted technology) of general surgical procedures will be included. Data extraction will include study characteristics, governance, details of video datasets and AI models, measures of accuracy, validation and any reported limitations.

Ethics and dissemination:
No ethical approval is required as primary data will not be collected. The results will be disseminated at relevant conferences, on social media and published in a peer-reviewed journal.
Screening of the Key Genes and Signaling Pathways for Schizophrenia Using Bioinformatics and Next Generation Sequencing Data Analysis
Authors: Vastrad Basavaraj , Vastrad Chanabasayya 
Published: October 2023

AbstractSchizophrenia is thought to be the most prevalent chronic psychiatric disorder. Numerous proteins have been identified that are associated with the occurrence and development of schizophrenia. This study aimed to identify potential core genes and pathways involved in schizophrenia, through exhaustive bioinformatic and next generation sequencing (NGS) data analyses using GSE20966 NGS data of neural progenitor cells and neurons obtained from healthy controls and patients with schizophrenia. The NGS data were downloaded from the Gene Expression Omnibus database. NGS data was processed by the DESeq2 package in R software and the differentially expressed genes (DEGs) were identified. Gene Ontology (GO) enrichment analysis and REACTOME pathway enrichment analysis were carried out to identify potential biological functions and pathways of the DEGs. Protein-protein interaction (PPI) network, module, miRNA-hub gene regulatory network and TF-hub gene regulatory network analysis were performed to identify the hub genes, miRNA and TFs. Potential hub genes were analyzed using receiver operating characteristic (ROC) curves in the R package (pROC). In this investigation, an overall 955 DEGs were identified: 478 genes were remarkably up regulated and 477 genes were distinctly down regulated. These genes were enriched for GO terms and pathways mainly involved in the multicellular organismal process, GPCR ligand binding, regulation of cellular process and amine ligand-binding receptors. MYC, FN1, CDKN2A, EEF1G, CAV1, ONECUT1, SYK, MAPK13, TFAP2A and BTK were considered the potential hub genes. miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed successfully. On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of schizophrenia and provide potential targets for further investigation.
Behavioural changes in aposematicHeliconius melpomenebutterflies in response to their predatory bird calls
Authors: Potdar Sushant , Dinakar Madhuri , Westerman Erica L. 
Published: October 2023

AbstractPrey-predator interactions have resulted in the evolution of many anti-predatory traits. One of them is the ability for prey to listen to predators and avoid them. Although prey anti-predatory behavioural responses to predator auditory cues are well described in a wide range of taxa, studies on whether butterflies change their behaviours in response to their predatory calls are lacking.Heliconiusbutterflies are unpalatable and form Müllerian mimicry rings as morphological defence strategies against their bird predators. Like many other butterflies in theNymphalidaefamily,Heliconiusbutterflies possess auditory organs, which are hypothesized to have evolved to assist with predator detection. Here we test whetherHeliconius melpomenechange their behaviour in response to their predatory bird calls by observing the behaviour of male and femaleH. m. plessiniexposed to calls ofHeliconiusavian predators: rufous-tailed jacamar, migratory Eastern kingbird, and resident tropical kingbird. We also exposed them to the calls of the toco toucan, a frugivorous bird as a control bird call, and an amplified greenhouse background noise as a noise control. We found that individuals changed their behaviour in response to jacamar calls only. Males increased their walking and fluttering behaviour, while females did not change their behaviour during the playback of the jacamar call. Intersexual behaviours like courtship, copulation, and abdomen lifting did not change in response to bird calls. Our findings suggest that despite having primary predatory defences like toxicity and being in a mimicry ring,H. m. plessinibutterflies changed their behaviour in response to predator calls. Furthermore, this response was predator specific, asH. m. plessenidid not respond to either the Eastern kingbird or the tropic kingbird calls. This suggests thatHeliconiusbutterflies may be able to differentiate predatory calls, and potentially the birds associated with those calls.HighlightsMany prey animals change their behaviour in response to their predator’s calls.Whether butterflies alter behaviour in response to bird predator calls is unknown.We show thatHeliconius melpomenechange behaviour in response to jacamar calls.Males increased walking and fluttering, but did not alter courting behaviour.H. melpomenedid not respond to predatory Eastern kingbird or tropical kingbird calls.
Meta-analysis on the effects of chemical stressors on five ecosystem functions: are there generalizable relationships?
Authors: Feckler Alexander , Schulz Ralf , Schäfer Ralf B. 
Published: October 2023

AbstractDespite considerable progress in our predictive capacity for the response of different trophic levels to chemicals, generalizable relations between chemicals and ecosystem functions are lacking. We addressed this knowledge gap by conducting the largest meta-analysis to date (136 studies; ∼350 observations) on the responses of ecosystem functions to chemicals. Based on this analysis, for selected classes of chemicals (pesticides, pharmaceuticals, and metals), we are the first to establish relations between chemical concentrations and the ecosystem functions organic matter decomposition and photosynthesis, showing monotonic dose-response relationships. These results concur with existing field data on chemical effects, which underpins the value of our findings. Taking into account the outlined research gaps and shortcomings, our findings and recommendations can be seen as a promising starting point to advance predictions of responses of ecosystem functions to selected chemical classes.
EV-Elute: a universal platform for enrichment of functional surface marker-defined extracellular vesicle subpopulations
Authors: de Voogt Willemijn S , Frunt Rowan , Leandro Raul M , Triesscheijn Casper S , Monica Bella , Paspali Ioanna , Tielemans Mark , Francois Jerney JJM , Seinen Cor W , de Jong Olivier G , Kooijmans Sander AA 
Published: October 2023

AbstractIntercellular communication via extracellular vesicles (EVs) has been identified as a vital component of a steadily expanding number of physiological and pathological processes. To accommodate these roles, EVs are equipped with specific proteins, lipids, and RNA molecules by EV-secreting cells. Consequently, EVs have highly heterogeneous molecular compositions. Given that surface molecules on EVs determine their interactions with their environment, it is conceivable that EV functionality differs between subpopulations with varying surface compositions. However, it has been technically challenging to examine such functional heterogeneity due to a lack of non-destructive methods to separate EV subpopulations based on their surface markers. Here, we used Design-of-Experiments methodology to rapidly optimize a protocol, which we name ‘EV-Elute’, to elute intact EVs from commercially available Protein G-coated magnetic beads. We captured EVs from various cell types on these beads using antibodies against CD9, CD63, CD81 and a custom-made protein binding phosphatidylserine (PS). When applying EV-Elute, over 70% of bound EVs could be recovered from the beads in a pH– and incubation time-dependent fashion. EV subpopulations were found to be devoid of co-isolated protein contaminants observed in whole EV isolates and showed intact morphology by electron microscopy. Proteinase K protection assays showed a mild and reversible decrease of EV membrane integrity during elution. Depending on the type of capturing antibody used, some antibodies remained EV-associated after elution. EV subpopulations showed uptake patterns similar to whole EV isolates in co-cultures of peripheral blood mononuclear cells and endothelial cells. However, in Cas9/sgRNA delivery assays, CD63+EVs showed a lower capacity to functionally deliver cargo as compared to CD9+, CD81+and PS+EVs. Taken together, we developed a novel, easy-to-use platform to isolate and functionally compare surface marker-defined EV subpopulations. Importantly, this platform does not require specialized equipment or reagents and is universally applicable to any capturing antibody and EV source. Hence, EV-Elute can open new opportunities to study EV functionality at the subpopulation level.
Exploring Okra-Derived Compounds as Prospective Aromatase Inhibitors: A Computational Study for Enhanced Breast Cancer Therapy
Authors: Lavanya B , Mallur Dhrithi Jayasimha , Temkar Sheshadri S , Arun V , C Benedict Paul 
Published: October 2023

AbstractBreast cancer with estrogen receptor positivity represents itself as the most prevalent malignancy among postmenopausal women. One of the promising therapeutic approach involves the use of Aromatase Inhibitors, which competitively bind to aromatase, reducing estrone and estradiol levels. While current drugs have improved survival rates, they are not without adverse effects. Consequently, this study explores the computational screening of medicinally relevant compounds derived from Okra for potential Aromatase Inhibition. Molecular Docking, employing AMDock v1.5.2, was utilized to assess binding affinities with aromatase (PDB:3EQM). Subsequently, in-depth molecular interactions were examined using Discovery Studio Visualizer v4.5, and the stability of docked complexes was evaluated via Molecular Dynamics with the GROMACS package, focusing on RMSD, RMSF, H-bond count, and SASA. The pharmacokinetic properties of the Okra compounds were predicted using admetSAR v2.0. Our findings highlight Quercetin 3-gentiobioside as a standout candidate, demonstrating superior binding affinity (-10 kcal/mol) and an Estimated Ki of 46.77 nM compared to Letrozole and other Okra compounds. Molecular dynamics analysis confirms the stability of Quercetin 3-gentiobioside binding in terms of H-bonds and conformational integrity. In conclusion, our computational investigation identifies Quercetin 3-gentiobioside, along with Quercetin 3-O-rutinoside and Hyperin, as promising candidates for preclinical studies in the pursuit of potential Aromatase Inhibitors.
Comparative Genomics Exploration of Shared lncRNA-coding genes in Human and All Annotated Plant Genomes: Potential Implications for Cancer Research
Authors: Mateiu Ligia 
Published: October 2023

AbstractSince their discovery in 1990, lncRNAs have been heavily investigated. It is already known that the genomes of plants and animals express large numbers of lncRNAs. In humans, many lncRNA are considered essential players in cancer biology, mainly acting as gene expression regulators in processes like cell proliferation, apoptosis, migration, invasion and stemness. In plants, lncRNAs are involved in vegetative growths, reproduction and stress responses. Yet, in the entirety of the animal and plant kingdoms, the functions and mechanisms of action for the majority of lncRNAs remain largely undiscovered, as do their orthology relationships. The poor conservation of the DNA sequences encoding for these transcripts is hindering the identification of lncRNAs orthologs especially among very distant evolutionary species. In this short study, using an uncomplicated, but creative bioinformatic approach, I searched for sequence homologies between human DNA and 175 annotated plant genomes from NCBI. Using stringent filtering, I found 20 human lncRNA-encoding genes overlapping plant genomic features, including lncRNAs. Evenmore, 3 of these human lncRNA-encoding genes with a potential plant ortholog are reported in multiple databases for lncRNA involved in cancers. This study opens the road for investigating the tumorigenesis in a deep homology context of lncRNAs.
Evaluation of normalization methods for predicting quantitative phenotypes in metagenomic data analysis
Authors: Wang Beibei , Luan Yihui 
Published: October 2023

AbstractSignificant advancements have been made in metagenomic research for the prediction of phenotypes based on microbiome data. While qualitative case-control predictions have received significant attention, less emphasis has been placed on predicting quantitative phenotypes. This emerging field holds great promise in revealing intricate connections between microbial communities and host health. However, the presence of heterogeneity in microbiome datasets poses a substantial challenge to the accuracy of predictions and undermines the reproducibility of models. To tackle this challenge, we investigated 22 normalization methods aimed at removing heterogeneity across multiple datasets, conducted a comprehensive review of them, and evaluated their effectiveness in predicting quantitative phenotypes using 3 simulations and 31 real datasets. The results indicate that none of these methods demonstrate significant superiority in predicting quantitative phenotypes or attain a noteworthy reduction in root mean squared error of the predictions. Given the frequent occurrence of batch effects and the satisfactory performance of batch correction methods in predicting datasets affected by these effects, we strongly recommend utilizing batch correction methods as the initial step in predicting quantitative phenotypes. In summary, the performance of normalization methods in predicting metagenomic data remains a dynamic and ongoing research area. Our study contributes to this field by undertaking a comprehensive evaluation of diverse methods and offering valuable insights into their effectiveness in predicting quantitative phenotypes.
Power and reproducibility in the external validation of brain-phenotype predictions
Authors: Rosenblatt Matthew , Tejavibulya Link , Camp Chris C. , Jiang Rongtao , Westwater Margaret L. , Noble Stephanie , Scheinost Dustin 
Published: October 2023

AbstractIdentifying reproducible and generalizable brain-phenotype associations is a central goal of neuroimaging. Consistent with this goal, prediction frameworks evaluate brain-phenotype models in unseen data. Most prediction studies train and evaluate a model in the same dataset. However, external validation, or the evaluation of a model in an external dataset, provides a better assessment of robustness and generalizability. Despite the promise of external validation and calls for its usage, the statistical power of such studies has yet to be investigated. In this work, we ran over 60 million simulations across several datasets, phenotypes, and sample sizes to better understand how the sizes of the training and external datasets affect statistical power. We found that prior external validation studies used sample sizes prone to low power, which may lead to false negatives and effect size inflation. Furthermore, increases in the external sample size led to increased simulated power directly following theoretical power curves, whereas changes in the training dataset size offset the simulated power curves. Finally, we compared the performance of a model within a dataset to the external performance. The within-dataset performance was typically withinr=0.2of the cross-dataset performance, which could help decide how to power future external validation studies. Overall, our results illustrate the importance of considering the sample sizes of both the training and external datasets when performing external validation.
Batch-effect correction in single-cell RNA sequencing data using JIVE
Authors: Hastings Joseph , Lee Donghyung , O’Connell Michael J. 
Published: October 2023

AbstractIn single-cell RNA sequencing (scRNA-seq) data analysis, addressing batch effects — technical artifacts stemming from factors such as varying sequencing technologies, equipment, and capture times — is crucial. These factors cause unwanted variation in the data and often obfuscate the underlying biological signal of interest. The Joint and Individual Variation Explained (JIVE) method can be used to extract shared biological patterns from multi-source sequencing data while adjusting for individual non-biological variations (i.e., batch effect). However, its current implementation is originally designed for bulk sequencing data, making it computationally infeasible for large-scale single-cell sequencing datasets. In this study, we enhance JIVE for large-scale scRNA-seq data by boosting its computational efficiency and tailoring it to the single-cell context. Additionally, we introduce a novel application of JIVE which we use to perform batch-effect correction on multiple scRNA-seq datasets. Our enhanced JIVE method aims to decompose scRNA-seq datasets into a joint structure capturing the true biological variability and individual structures which capture technical variability within each batch. This joint structure is then suitable for use in downstream analyses. We employed four evaluation metrics and benchmarked the results against two other popular tools, Seurat v3 and Harmony, which were developed for this purpose. We found that JIVE performed best in metrics that consider local neighborhoods (kBET and LISI) and in scenarios in which the original data contained distinct differences between batches and cell types.
A Reinterpretation of the Relationship Between Persistent and Resurgent Sodium Currents
Authors: Brown Samuel P. , Lawson Ryan J. , Moreno Jonathan D. , Ransdell Joseph L. 
Published: October 2023

AbstractThe resurgent sodium current (INaR) activates on membrane repolarization, such as during the downstroke of neuronal action potentials. Due to its unique activation properties, INaRis thought to drive high rates of repetitive neuronal firing. However, INaRis often studied in combination with the persistent or non-inactivating portion of sodium currents (INaP). We used dynamic clamp to test how INaRand INaPindividually affect repetitive firing in adult cerebellar Purkinje neurons from male and female mice. We learned INaRdoes not scale repetitive firing rates due to its rapid decay at subthreshold voltages, and that subthreshold INaPis critical in regulating neuronal firing rate. Adjustments to the Nav conductance model used in these studies revealed INaPand INaRcan be inversely scaled by adjusting occupancy in the slow inactivated kinetic state. Together with additional dynamic clamp experiments, these data suggest the regulation of sodium channel slow inactivation can fine-tune INaPand Purkinje neuron repetitive firing rates.Significance StatementAcross neuronal cell types, the resurgent sodium current (INaR) is often implicated in driving high rates of repetitive firing. Using dynamic clamp, we determined INaRis ineffective at driving subsequent action potentials, and that the subthreshold persistent sodium current (INaP) is the critical parameter for scaling repetitive firing rates. We propose INaRmeasured in native neurons may reflect a mechanism by which the magnitude of INaPis fine-tuned.