bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical Consensus Statement: Vaginal Energy-Based Devices
Authors: Alshiek Jonia , Garcia Bobby , Minassian Vatche , Iglesia Cheryl B. , Clark Amanda , Sokol Eric R. , Murphy Miles , Malik Shazia A. , Kimble Alexis , Shobeiri S. Abbas 
Published: October 2024

Abstract
This clinical consensus statement on vaginal energy-based devices (EBDs) reflects an update by content experts from the American Urogynecologic Society’s EBD writing group. In 2019, the American Urogynecologic Society’s EBD writing group used a modified Delphi process to assess statements that were evaluated for consensus after a structured literature search. A total of 40 statements were assessed and divided into 5 categories: (1) patient criteria, (2) health care provider criteria, (3) efficacy, (4) safety, and (5) treatment considerations. Of the 40 statements that were assessed, 28 reached consensus and the remaining 12 did not. Lack of evidence was among the main reasons that vulvovaginal EBD treatment statements did not reach consensus. In March 2022, these statements were reassessed using the interim literature.
Surgical management of costal margin rupture associated with intercostal hernia: Evolution of techniques
Authors: Wijerathne Pradeep , Rao Jagan N. , Wijffels Mathieu M.E. , Tamburrini Alessandro , Tenconi Sara , Edwards John Gurney 
Published: October 2024

INTRODUCTION
Costal margin rupture (CMR) injuries in association with intercostal hernia (IH) are rare and symptomatic and provide a significant surgical challenge. Surgical failure rates up to 60% are reported, and optimal techniques are unclear. We have characterized these injuries and describe the evolution of our surgical management techniques.

METHODS
Patients characterized by the Sheffield Classification where CMR and IH were both present, either CMR-IH or transdiaphragmatic intercostal hernia (TDIH), were identified prospectively, and injury characteristics, patient management, and follow-up data were recorded. Surgical techniques evolved according to patient outcomes from suture repair without and then with extrathoracic mesh, to three iterations of double-layer mesh repair (DLMR). The third iteration involved DLMR with biologic mesh, titanium buttress plates applied to the ribs adjacent to the IH with intercostal nerve-sparing suture placement. Associated surgical stabilization of rib fractures, or surgical stabilization of nonunited rib fractures, was performed when required, with costal margin plate fixation where possible.

RESULTS
Of 25 patients with CMR-IH and 11 with TDIH, 25 patients underwent surgery, with 6 reoperations in 5 patients. There were 8 suture repairs and 3 extrathoracic mesh repairs: DLMR was performed in 14 patients (3 Mark [Mk] 1, 5 Mk 2, and 6 Mk 3) with 2, 1, and 0 reoperations, respectively. Costal margin stabilization with titanium plates was successful twice at the level of the seventh but failed twice out of three times at the ninth costal cartilage.
Reoperation after a failed mesh repair is particularly challenging and may require the placement of titanium buttress plates, surgical stabilization of rib fractures, and the use of stainless steel wire sutures.

CONCLUSION
Repair of CMR-IH/TDIH is challenging, but experience-based evolution of techniques has led to a durable and reproducible Mk 3 repair.

LEVEL OF EVIDENCE
Observational; Level III.
DO NOT LOSE SLEEP OVER IT: IMPLANTED BRAIN-COMPUTER INTERFACE FUNCTIONALITY DURING NIGHTTIME IN LATE-STAGE AMYOTROPHIC LATERAL SCLEROSIS
Authors: Leinders Sacha , Aarnoutse Erik J. , Branco Mariana P. , Freudenburg Zac V. , Geukes Simon H. , Schippers Anouck , Verberne Malinda S.W. , van den Boom Max , van der Vijgh Benny , Crone Nathan E. , Denison Timothy , Ramsey Nick F. , Vansteensel Mariska J. 
Published: October 2024

AbstractBackground and objectivesBrain-computer interfaces (BCIs) hold promise as augmentative and alternative communication technology for people with severe motor and speech impairment (locked-in syndrome) due to neural disease or injury. Although such BCIs should be available 24/7, to enable communication at all times, feasibility of nocturnal BCI use has not been investigated. Here, we addressed this question using data from an individual with amyotrophic lateral sclerosis (ALS) who was implanted with an electrocorticography-based BCI that enabled the generation of click-commands for spelling words and call-caregiver signals.MethodsWe investigated nocturnal dynamics of neural signal features used for BCI control, namely low (LFB: 10–30Hz) and high frequency band power (HFB: 65-95Hz). Additionally, we assessed the nocturnal performance of a BCI decoder that was trained on daytime data by quantifying the number of unintentional BCI activations at night. Finally, we developed and implemented a nightmode decoder that allowed the participant to call a caregiver at night, and assessed its performance.ResultsPower and variance in HFB and LFB were significantly higher at night than during the day in the majority of the nights, with HFB variance being higher in 88% of nights. Daytime decoders caused 245 unintended selection-clicks and 13 unintended caregiver-calls per hour when applied to night data. The developed nightmode decoder functioned error-free in 79% of nights over a period of ±1.5 years, allowing the user to reliably call the caregiver, with unintended activations occurring only once every 12 nights.DiscussionReliable nighttime use of a BCI requires decoders that are adjusted to sleep-related signal changes. This demonstration of a reliable BCI nightmode and its long-term use by an individual with advanced ALS underscores the importance of 24/7 BCI reliability.Trial registrationThis trial is registered inclinicaltrials.govunder numberNCT02224469(https://clinicaltrials.gov/study/NCT02224469?term=NCT02224469&rank=1). Date of submission to registry: August 21, 2014. Enrollment of first participant: September 7, 2015.
VIDEO BASED DETECTION OF EPILEPTIC SEIZURES USING A THREE-DIMENSIONAL CONVOLUTIONAL NEURAL NETWORK
Authors: Boyne Aidan , Yeh Hsiang J. , Allam Anthony K. , Brown Brandon M. , Tabaeizadeh Mohammad , Stern John M. , Cotton R. James , Haneef Zulfi 
Published: October 2024

ABSTRACTObjectiveSeizure detection in epilepsy monitoring units (EMU) is essential for the clinical assessment of drug-resistant epilepsy. Automated video analysis using machine learning provides a promising aid for seizure detection with resultant reduction in the resources required for diagnostic monitoring. We employ a 3D convolutional neural network with fully fine-tuned backbone layers to identify seizures from EMU videos.MethodsA two-stream inflated 3D-ConvNet architecture (I3D) classified video clips as a seizure or not a seizure. A pretrained action classification model was fine-tuned on 11 hours of video data containing 49 tonic-clonic seizures from 25 patients monitored at a large academic hospital (site A) using leave-one-patient-out cross-validation. Performance was evaluated by comparing model predictions to ground-truth annotations obtained from video-EEG review by an epileptologist on videos from site A and a separate dataset from a second large academic hospital (site B).ResultsThe model achieved leave-one subject out cross-validation F1-score of 0.960 ± 0.007 and area under the receiver operating curve (AUC) score of 0.988 ± 0.004 at site A. Evaluation on full videos successfully detected all seizures with median detection latency of 0.0 (0.0, 3.0) seconds from seizure onset. The site A model had an average false alarm rate of 1.81 alarms per hour, though 33 of the 49 videos (67%) had no false alarms. Evaluation at site B demonstrated generalizability of the model architecture and training strategy, though cross-site evaluation (site A model tested on site B data and vice versa) resulted in diminished performance.SignificanceOur model demonstrates high performance in the detection of epileptic seizures from video data using a fine-tuned I3D model and outperforms prior similar models identified in the literature. This study provides a foundation for future work in real-time EMU seizure monitoring and possibly for reliable and cost-effective at-home detection of tonic-clonic seizures.KEY POINTSWe evaluate a video-based 3-D CNN for seizure detection in patients undergoing evaluation in an EMU at 2 large academic hospitals.Our video-only model provides highly accurate detection of tonic-clonic seizures with low detection latency.The underlying model architecture requires no video preprocessing and is generalizable across two EMUs.
Diagnostic performance of Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy for detecting osteoarthritis and rheumatoid arthritis from blood serum
Authors: Mannerkorpi Minna , Das Gupta Shuvashis , Rieppo Lassi , Saarakkala Simo 
Published: October 2024

AbstractOsteoarthritis (OA) and rheumatoid arthritis (RA) are the two most common rheumatic diseases worldwide, causing pain and disability. Both conditions are highly heterogeneous, and their onset occurs insidiously with non-specific symptoms, so they are not always distinguishable from other arthritis during the initial stages. This makes early diagnosis difficult and resource-demanding in clinical environments. Here, we estimated its diagnostic performance in classifying ATR-FTIR spectra obtained from serum samples from OA patients, RA patients, and healthy controls. Altogether, 334 serum samples were obtained from 100 OA patients, 134 RA patients, and 100 healthy controls. The infrared spectral acquisition was performed on air-dried 1µl of serum with a diamond-ATR-FTIR spectrometer. Machine learning models combining Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) were trained to binary classify preprocessed ATR-FTIR spectra as follows: controls vs. OA, controls vs. RA, and OA vs. RA. For a separated test dataset and the validation dataset, the overall model performance was better in classifying OA and RA patients, followed by the RA and controls, and lastly, between OA and controls, with corresponding AUC-ROC values: 0.84, 0.76, 0.72 (test dataset) and 0.94, 0.92, 79 (validation dataset). In conclusion, this study reports robust binary classifier models to differentiate blood serum from the two most common rheumatic diseases, showing the potential of ATR-FTIR as an effective aid in rheumatic disease classification.
Subtle methodological variations substantially impact correlation test results in ecological time series
Authors: Cannistra Caroline , Hoang Linh , Yuan Alex E. , Shou Wenying 
Published: October 2024

AbstractCorrelation analyses using ecological time series can indicate phenomena such as interspecific interactions or an environmental factor that affects several populations. However, methodological choices in these analyses can significantly impact the results, potentially leading to spurious correlations or missed true associations. In this study, we explore how different decisions affect the performance of statistical tests for correlations between pairs of time series in simulated two-species ecosystems. We show that when performing nonparametric “surrogate data” tests, both the choice of statistic and the method of generating the null distribution can affect true positive and false positive rates. We also show how seemingly closely related methods of accounting for lagged correlation produce vastly different false positive rates. For methods that establish a null model by simulating the dynamics of one of the two species, we show that the choice of species simulated can influence test behavior. Additionally, we identify scenarios where the outcomes of analyses can be highly sensitive to the initial conditions of an ecosystem, even under simple mathematical models. Our results indicate the importance of thoughtful consideration and documentation of the statistical choices investigated here. To make this work broadly accessible, we include visual explanations of most methods tested in an appendix.
Synthesis and Evaluation of Carmofur Analogs as Antiproliferative Agents, Inhibitors to the Main Protease (Mpro) of SARS-CoV-2, and Membrane Rupture-Inducing Agents
Authors: Gu Tiffany , Lu Amber , Wang Xina , Brahan Natalie , Xu Lexi , Zhang Leyuan , Su Kaitlyn , Seow Kody , Vu Julia , Luk Charissa , Lee Yunseo , Raman Anirudh , Pazzi Joseph , Njoo Edward 
Published: October 2024

AbstractInitially developed as a derivatized analog of 5-fluorouracil for the treatment of colorectal cancer, carmofur has more recently demonstrated potent covalent inhibition of the main protease (Mpro) of SARS-CoV-2. Harnessing our previously described workflow for the optimized preparation of carmofur using benchtop19F NMR spectroscopy, here, we prepared and evaluated a synthetic library of nine carmofur analogs with a selection of side chain motifs or single-atom substitution to explore the diversifiability of these compounds as Mproinhibitors, where we discovered that a hexyl carbamate analog outperformed carmofur, and as antiproliferative agents in model human cell lines to identify differences in potency when the carbonyl electrophilicity and/or alkyl side chains are modified. Finally, we describe a novel workflow for the evaluation of membrane-rupturing small molecules through imaging of fluorescently labeled giant unilamellar vesicles (GUVs), and through this, we identified two lipophilic urethane analogs of carmofur bearing dodecyl urethane and octadecyl urethane side chains that have potent membrane-rupturing capability in the nanomolar range, providing insight into a potential mechanism for thein vitroactivities of lipidated 5-fluorouracil analogs.
Toward Automatic Variant Interpretation: Discordant Genetic Interpretation Across Variant Annotations for ClinVar Pathogenic Variants
Authors: Chen Yu-An , Yuan Tzu-Hang , Huang Jia-Hsing , Wang Yu-Bin , Hung Tzu-Mao , Chen Chien-Yu , Chen Pei-Lung , Hsu Jacob Shujui 
Published: October 2024

AbstractPurposeHigh-throughput sequencing has revolutionized genetic disorder diagnosis, but variant pathogenicity interpretation is still challenging. Even though the Human Genome Variation Society (HGVS) provides recommendations for variant nomenclature, discrepancies in annotation remain a significant hurdle.MethodsThis study evaluated the annotation concordance between three tools— ANNOVAR, SnpEff, and Variant Effect Predictor (VEP)—using 164,549 two-star variants from ClinVar. The analysis used HGVS nomenclature string-match comparisons to assess annotation consistency from each tool, corresponding coding impacts, and associated ACMG criteria inferred from the annotations.ResultsThe analysis revealed variable concordance rates, with 58.52% agreement for HGVSc, 84.04% for HGVSp, and 85.58% for the coding impact. SnpEff showed the highest match for HGVSc (0.988), while VEP bettered for HGVSp (0.977). The substantial discrepancies were noted in the Loss-of-Function (LoF) category. Incorrect PVS1 interpretations affected the final pathogenicity and downgraded PLP variants (ANNOVAR 55.9%, SnpEff 66.5%, VEP 67.3%), risking false negatives of clinically relevant variants in reports.ConclusionsThese findings highlight the critical challenges in accurately interpreting variant pathogenicity due to discrepancies in annotations. To enhance the reliability of genetic variant interpretation in clinical practice, standardizing transcript sets and systematically cross-validating results across multiple annotation tools is essential.Graphic abstractThis study examined the consistency of variant annotations produced by three widely used open-source tools—ANNOVAR, SnpEff, and VEP—against 164,549 ClinVar two starts variants. The investigation covers HGVS-based transcript, protein nomenclature and coding impact annotation. The results showed that none of the tools were fully consistent with ClinVar across all coding impact categories, particularly in the LoF category, which exhibited the poorest consistency. This inconsistency may lead to discrepancies in PVS1 interpretation, affecting the final pathogenicity assessment. PVS1 loss resulted in a significant downgrading of PLP variants, potentially leading to the omission of clinically relevant variants in reports.
Cholesterol sulfate prevents maternal–fetal conflict by locally modulating immune reactivity
Authors: Hirotani Kenichiro , Kunimura Kazufumi , Maeda Rae , Sugiura Yuki , Nakata Keisuke , Takahashi Masatomo , Izumi Yoshihiro , Akiyoshi Sayaka , Matsubara Keisuke , Morino Kenji , Iwasaki Takeshi , Tanaka Kaori , Aulia Fadlina , Miyata Kanjiro , Hosokawa Takanatsu , Mori Takeshi , Ohkawa Yasuyuki , Bamba Takeshi , Toh Hidehiro , Sasaki Hiroyuki , Oda Yoshinao , Uruno Takehito , Kato Kiyoko , Fukui Yoshinori 
Published: October 2024

AbstractAlthough placental mammals are at high risk of maternal–fetal immune conflict, it is unclear how the semi-allogeneic fetus avoids rejection. Cholesterol sulfate (CS) is a bioactive metabolite that inhibits leukocyte migration and activation. This study investigated the roles and cells associated with CS in pregnant mice and humans. CS was sequentially produced by maternal-derived endometrial cells and fetal-derived placental trophoblasts before and after placentation. When mated with allogeneic males, CS-deficient mice showed increased fetal resorption rates under induced placental inflammation. This phenotype disappeared when the activity of the CS-producing enzyme was restored in the placenta. Placental CS levels were reduced in patients with “villitis of unknown etiology.” Thus, we uncovered the spatiotemporal control of CS production and its relevance to local immunosuppression during pregnancy.
Leveraging zebrafish embryo phenotypic observations to advance data-driven analyses in toxicology
Authors: Michaelis Paul , Klüver Nils , Aulhorn Silke , Bohring Hannes , Bumberger Jan , Haase Kristina , Kuhnert Tobias , Küster Eberhard , Krüger Janet , Luckenbach Till , Massei Riccardo , Nerlich Lukas , Petruschke Sven , Schnicke Thomas , Schnurpel Anton , Scholz Stefan , Schweiger Nicole , Sielaff Daniel , Busch Wibke 
Published: October 2024

AbstractZebrafish have emerged as a central model organism in toxicological research. Zebrafish embryos are exempt from certain animal testing regulations which facilitates their use in toxicological testing. Next to the zebrafish embryo acute toxicity test (ZFET) according to the OECD TG 236, fish embryos are used in mechanistic investigations, chemical screenings, in ecotoxicology, and drug development. However, inconsistencies in the applied test protocols and the monitored endpoints in addition to a lack of standardized data formats, impede comprehensive meta-analyses and cross-study comparisons. To address these challenges, we developed the Integrated Effect Database for Toxicological Observations (INTOB), a comprehensive data management tool that standardizes collection of metadata and phenotypic observations using a controlled vocabulary. By incorporating data from more than 600 experiments into the database and subsequent comprehensive data analyses, we demonstrate its utility in improving the comparability and interoperability of toxicity data. Our results show that the ZFET can detect toxicity spanning seven orders of magnitude at the scale of effect concentrations. We also highlight the potential of read-across analyses based on morphological fingerprints and their connection to chemical modes of action, provide information on control variability of the ZFET, and highlight the importance of time for mechanistic understanding in chemical exposure-effect assessments. We provide the full FAIR dataset as well as the analysis workflow and demonstrate how professional data management, as enabled with INTOB, marks a significant advancement by offering a comprehensive framework for the systematic use of zebrafish embryo toxicity data, thus paving the way for more reliable, data-driven chemical risk assessment.SynopsisThis article shows how a novel data management tool for zebrafish embryo toxicity data advances comparative chemical risk assessment by enhancing data and metadata standardization, comparability, and cross-study analyses.
Structure-Guided Loop Grafting Improves Expression and Stability of Influenza Neuraminidase for Vaccine Development
Authors: Rijal Pramila , Wei Leiyan , Paesen Guido C , Stuart David I , Howarth Mark R , Huang Kuan-Ying A , Bowden Thomas A , Townsend Alain RM 
Published: October 2024

AbstractInfluenza neuraminidase is a crucial target for protective antibodies, yet the development of recombinant neuraminidase protein as a vaccine has been held back by instability and variable expression. We have taken a pragmatic approach to improving expression and stability of neuraminidase by grafting antigenic surface loops from low-expressing neuraminidase proteins onto the scaffold of high-expressing counterparts. The resulting hybrid proteins retained the antigenic properties of the loop donor while benefiting from the high-yield expression, stability, and tetrameric structure of the loop recipient. These hybrid proteins were recognised by a broad set of human monoclonal antibodies elicited by influenza infection or vaccination, with X-ray structures validating the accurate structural conformation of the grafted loops and the enzymatic cavity. Immunisation of mice with neuraminidase hybrids induced inhibitory antibodies to the loop donor and conferred protected against lethal influenza challenge. This pragmatic technique offers a robust solution for improving the expression and stability of influenza neuraminidase proteins for vaccine development.Graphical Abstract
Pre-exposure to stress reduces loss of community and genetic diversity following severe environmental disturbance
Authors: Xu Charles C.Y. , Fugère Vincent , Barbosa da Costa Naíla , Beisner Beatrix E. , Bell Graham , Cristescu Melania E. , Fussmann Gregor F. , Gonzalez Andrew , Shapiro B. Jesse , Barrett Rowan D.H. 
Published: October 2024

SummaryEnvironmental stress caused by anthropogenic impacts is increasing worldwide. Understanding the ecological and evolutionary consequences for biodiversity will be crucial for our ability to respond effectively. Historical exposure to environmental stress is expected to select for resistant species, shifting community composition towards more stress-tolerant taxa. Concurrent with this species sorting process, genotypes within resistant taxa that have the highest relative fitness under severe stress are expected to increase in frequency, leading to evolutionary adaptation. However, empirical demonstrations of these dual ecological and evolutionary processes in natural communities are lacking. Here, we provide the first evidence for simultaneous species sorting and evolutionary adaptation across multiple species within a natural freshwater bacterial community. Using a two-phase stressor experimental design (acidification pre-exposure followed by severe acidification) in aquatic mesocosms, we show that pre-exposed communities were more resistant than naïve communities to taxonomic loss when faced with severe acid stress. However, after sustained severe acidification, taxonomic richness of both pre-exposed and naïve communities eventually converged. All communities experiencing severe acidification became dominated by an acidophilic bacterium,Acidiphilium rubrum, but this species retained greater genetic diversity and followed distinct evolutionary trajectories in pre-exposed relative to naïve communities. These patterns were shared across other acidophilic species, providing repeated evidence for the impact of pre-exposure on evolutionary outcomes despite the convergence of community profiles. Our results underscore the need to consider both ecological and evolutionary processes to accurately predict the responses of natural communities to environmental change.