bluuebunny/crossref_metadata_2025 huggingface dataset:
MAVMET trial: maraviroc and/or metformin for metabolic dysfunction associated fatty liver disease in adults with suppressed HIV
Authors: McCabe Leanne , Burns James E. , Latifoltojar Arash , Post Frank A. , Fox Julie , Pool Erica , Waters Anele , Santana Beatriz , Garvey Lucy , Johnson Margaret , McGuinness Ian , Chouhan Manil , Edwards Jonathan , Goodman Anna L. , Cooke Graham , Murphy Claire , Collaco-Moraes Yolanda , Webb Helen , Gregory Adam , Mohamed Fatima , Rauchenberger Mary , Ryder Stephen D. , Sandford Chris , Baker Jason V. , Angus Brian , Boesecke Christoph , Orkin Chloe , Punwani Shonit , Clark Andrew , Gilson Richard , Dunn David , Pett Sarah L. ,   the MAVMET Study group‡
Published: May 2024

Objective:

Metabolic dysfunction associated fatty liver disease (MAFLD) is over-represented in people with HIV (PWH). Maraviroc (MVC) and/or metformin (MET) may reduce MAFLD by influencing inflammatory pathways and fatty acid metabolism.

Design:

Open-label, 48-week randomized trial with a 2 x 2 factorial design.

Setting:

Multicenter HIV clinics.

Participants:

Nondiabetic, virologically suppressed PLWH, aged at least 35 years, with confirmed/suspected MAFLD (≥1 biochemical/anthropometric/radiological/histological features).

Intervention:

Adjunctive MVC; MET; MVC+MET vs. antiretroviral therapy (ART) alone.

Primary outcome:

Change in liver fat fraction (LFF) between baseline and week-48 using magnetic resonance proton density fat fraction (MR PDFF).

Results:

Six sites enrolled 90 participants (93% male; 81% white; median age 52 [interquartile range, IQR 47–57] years) between March 19, 2018, and November 11, 2019. Seventy percent had imaging/biopsy and at least one 1 MAFLD criteria. The analysis included 82/90 with week-0 and week-48 scans. Median baseline MR PDFF was 8.9 (4.6–17.1); 40, 38, 8, and 14% had grade zero, one, two, and three steatosis, respectively. Mean LFF increased slightly between baseline and follow-up scans: 2.22% MVC, 1.26% MET, 0.81% MVC+MET, and 1.39% ART alone. Prolonged intervention exposure (delayed week-48 scans) exhibited greater increases in MR PDFF (estimated difference 4.23% [95% confidence interval, 95% CI 2.97–5.48], P < 0.001). There were no differences in predicted change for any intervention compared to ART alone: MVC (-0.42% [95% CI -1.53 to 0.68, P = 0.45]), MET (-0.62 [-1.81 to 0.56, P = 0.30]), and MVC+MET (-1.04 [-2.74 to 0.65, P = 0.23]). Steatosis grade remained unchanged in 55% and increased in 24%.

Conclusion:

Baseline levels of liver fat were lower than predicted. Contrary to our hypothesis, neither MVC, MET, or the combination significantly reduced liver fat as measured by MRPDFF compared to ART alone.
Nonsyndromic Craniosynostosis Correlation Between Ethnicity, Race, and Pattern of Affected Suture Type: Meta-Analysis
Authors: Benaroch David , Brozynski Martina , Seyidova Nargiz , Oleru Olachi , Agandi Lorreen , Abu El Hawa Areeg A. , Taub Peter J.
Published: May 2024

Background:

Previous studies have sought to analyze risk factors associated with craniosynostosis and while syndromic craniosynostosis is often linked to genetic mutations, the factors impacting nonsyndromic cases are less investigated. The aim of current meta-analysis is to evaluate the relationship between ethnicity and suture type in nonsyndromic craniosynostosis patients.

Methods:

The search term “craniosynostosis [Title/Abstract] AND (race [Title/Abstract] OR ethnicity [Title/Abstract])) NOT (syndrome [Title/Abstract])” was used to search the PubMed, Cochrane, and MEDLINE databases. Analyses were conducted separately for each racial and ethnic group for each suture type cohort. Odds ratios were conducted for each suture cohort and confounders were adjusted using linear mixed-effect models. Because of the homogeneity of the populations and categorical nature of the classification, binary logistic regression was run on aggregate data.

Results:

The literature search yielded 165 articles. After reviewing titles, abstracts, and manuscript contents of these articles, 5 studies were ultimately included in a meta-analysis. Studies with missing data for a particular cohort or variable were excluded from the respective analysis. Hispanic children had higher odds of sagittal suture involvement (OR: 1.53, P<0.001), whereas Asian had coronal suture (OR: 2.47, P<0.001). Both Asian and African American children had significantly lower odds of sagittal suture involvement (OR: 0.50, P<0.001 and OR: 0.7, P=0.04, respectively).

Conclusion

The relationship between ethnicity and craniosynostosis has been suggested as a risk factor, but without definitive conclusion. Present meta-analysis findings demonstrated association between ethnicity and suture type, however further research with larger scale and geographically varied data is warranted.
Perception of Rhinoplasty Outcome Utilizing Patients’ Photography
Authors: Assiri Hassan , Alfaleh Moath , AlEnazi Abdulaziz , Alarfaj Ahmed
Published: May 2024

Background:

Patient satisfaction with rhinoplasty results is evaluated in a manner of subjective and qualitative values, and to a certain degree, it can indicate successful outcomes in rhinoplasty.

Methods:

The present study was a descriptive study that assessed the rhinoplasty outcome of adult patients who underwent septorhinoplasty between January 2015 and August 2023 at a single center in Saudi Arabia utilizing Rhinoplasty Outcome Evaluation scores and Nasal Obstruction Symptom Evaluation scores pre-operatively, postoperatively, and postoperatively with showing the patients their photo before surgery.

Results:

The comparison of Rhinoplasty Outcome Evaluation scores and Nasal Obstruction Symptom Evaluation scores showed statistically significant with P value of 0.000 when comparing these scores pre-operatively, postoperatively, and postoperatively with showing the patient their photos before surgery.

Conclusion:

Presenting patients with pre-operative images may help them recognize changes in their clinical appearance and, consequently, score higher on the postoperative satisfaction scale. It can help the surgeon to increase patient satisfaction postoperatively.
INSTINCT: Multi-sample integration of spatial chromatin accessibility sequencing data via stochastic domain translation
Authors: Liu Yuyao , Li Zhen , Chen Xiaoyang , Cui Xuejian , Gao Zijing , Jiang Rui
Published: May 2024

Recent advances in spatial epigenomic techniques have given rise to spatial assay for transposase-accessible chromatin using sequencing (spATAC-seq) data, enabling the characterization of epigenomic heterogeneity and spatial information simultaneously. Integrative analysis of multiple spATAC-seq samples, for which no method has been developed, allows for effective identification and elimination of unwanted non-biological factors within the data, enabling comprehensive exploration of tissue structures and providing a holistic epigenomic landscape, thereby facilitating the discovery of biological implications and the study of regulatory processes. In this article, we present INSTINCT, a method for multi-sample INtegration of Spatial chromaTIN accessibility sequencing data via stochastiC domain Translation. INSTINCT can efficiently handle the high dimensionality of spATAC-seq data and eliminate the complex noise and batch effects of samples from different conditions through a stochastic domain translation procedure. We demonstrate the superiority and robustness of INSTINCT in integrating spATAC-seq data across multiple simulated scenarios and real datasets. Additionally, we highlight the advantages of INSTINCT in spatial domain identification, visualization, spot-type annotation, and various downstream analyses, including motif enrichment analysis, expression enrichment analysis, and partitioned heritability analysis.
Amplitude entropy to capture chimera-like behavior in the altered brain dynamics during seizures
Authors: Ghosh Saptarshi , Dallmer-Zerbe Isa , Buckova Barbora Rehak , Hlinka Jaroslav
Published: May 2024

Epilepsy is a neurological disease characterized by epileptic seizures, which commonly manifest with pronounced frequency and amplitude changes in the EEG signal. In the case of focal seizures, initially localized pathological activity spreads from a so-called "onset zone" to a wider network of brain areas. Chimeras, defined as states of simultaneously occurring coherent and incoherent dynamics in symmetrically coupled networks are increasingly invoked for characterization of seizures. In particular, chimera-like states have been observed during the transition from a normal (asynchronous) to a seizure (synchronous) network state. However, chimeras in epilepsy have only been investigated with respect to the varying phases of oscillators. We propose a novel method to capture the characteristic pronounced changes in the recorded EEG amplitude during seizures by estimating chimera-like states directly from the signals in a frequency- and time-resolved manner. We test the method on a publicly available intracranial EEG dataset of 16 patients with focal epilepsy. We show that the proposed measure, titled Amplitude Entropy, is sensitive to the altered brain dynamics during seizure, demonstrating its significant increases during seizure as compared to before and after seizure. This finding is robust across patients, their seizures, and different frequency bands. In the future, Amplitude Entropy could serve not only as a feature for seizure detection, but also help in characterizing amplitude chimeras in other networked systems with characteristic amplitude dynamics.
Upregulation of FasII underlies synergistic neuropathological and behavioral defects in aDrosophilamodel of myotonic dystrophy
Authors: Koon Alex Chun , Winnie Yeung Ka Yee , Leong Lok I , Chen Zhefan Stephen , Peng Shaohong Isaac , See Fung Joyce Man , Wu Yitao , Armstrong Noah S. , Bargiela Ariadna , Moreno Nerea , Poyatos Javier , Vilchez Juan , Magneron Paul , Huguet Aline , Brewer Cassandra Kussius , Beck Erin Savner , Artero Rubén , Gomes-Pereira Mário , Gourdon Genevieve , Budnik Vivian , Frank C. Andrew , McCabe Brian D. , Chan Ho Yin Edwin
Published: May 2024

Myotonic dystrophy type 1 (DM1) is a multisystemic disorder that has been extensively studied for decades, yet our understanding of its neuropathological aspect remains rudimentary. In this study, we characterized a novel model of DM1 neuropathology by expressing untranslated expandedCUGrepeats at theDrosophilalarval neuromuscular junction. In this model, both pre- and postsynaptic expression ofCUGrepeats participate to induce reduction of synaptic boutons, increase of arbor disassembly and impairment of larval locomotor activity. We found that the expression ofCUGrepeats caused an upregulation of the cell adhesion molecule, FasII (NCAM1 in mammals), in both the motor neurons and the body wall muscles. Knockdown offasIIwas sufficient to rescue bouton numbers and locomotor impairment in this model. Further analyses identified the upregulation of the FasII-C isoform as a major contributor of these phenotypes. Remarkably, overexpressing the FasII-A-PEST+ isoform rescued the synaptic and behavioral defects, likely by outcompeting the upregulated FasII-C. Our study provided the foundation for a basic mechanism of synapse dysregulation in DM1.
Development and optimization of expected cross value for mate selection problems
Authors: Ahadi Pouya , Balasundaram Balabhaskar , Borrero Juan S. , Chen Charles
Published: May 2024

In this study, we address the mate selection problem in the hybridization stage of a breeding pipeline, which constitutes the multi-objective breeding goal key to the performance of a variety development program. The solution framework we formulate seeks to ensure that individuals with the most desirable genomic characteristics are selected to cross in order to maximize the likelihood of the inheritance of desirable genetic materials to the progeny. Unlike approaches that use phenotypic values for parental selection and evaluate individuals separately, we use a criterion that relies on the genetic architecture of traits and evaluates combinations of genomic information of the pairs of individuals. We introduce theexpected cross value(ECV) criterion that measures the expected number of desirable alleles for gametes produced by pairs of individuals sampled from a population of potential parents. We use the ECV criterion to develop an integer linear programming formulation for the parental selection problem. The formulation is capable of controlling the inbreeding level between selected mates. We evaluate the approach for two applications: (i) improving multiple target traits simultaneously, and (ii) finding a multi-parental solution to design crossing blocks. We evaluate the performance of the ECV criterion using a simulation study. Finally, we discuss how the ECV criterion and the proposed integer linear programming techniques can be applied to improve breeding efficiency while maintaining genetic diversity in a breeding program.
Haplotype-aware multiomics unveils the regulatory basis of haplodiplontic life-cycle differentiation in a cosmopolitan marine alga
Authors: Kao Tzu-Tong , Lai Ming-Wei , Wang Tzu-Haw , Yang Chia-Ling , Frada Miguel J. , Ku Chuan
Published: May 2024

Gephyrocapsa huxleyi(formerlyEmiliania huxleyi), a key coccolithophore alga influencing the global carbon cycle through photosynthesis and calcification, undergoes a haplodiplontic sexual life cycle with a calcifying non-flagellate diploid and a non-calcifying biflagellate haploid stage. To reveal the molecular basis of their morpho-physiological distinctions, we generated chromosome-level genome assemblies and compared the transcriptomes, proteomes, and methylomes for a pair of isogenic haploid and diploid model strains and conducted haplotype-aware analyses of their multiomic features. In addition to calcification and flagella, transcriptomes and proteomes of haploid and diploid cells modulate their differentiation in photosynthesis, sulfatases, DMSP degradation, DNA replication, and endomembrane system and transport. Haploid-diploid differential gene expression can be partially attributable to allelic imbalance (allele-specific expression) in diploid cells. Gene transcript abundance is positively associated with both CG and CHG gene-body DNA methylation, which can be inheritable, allele-specific, and differentiated between life-cycle phases. This multiomic study unravels the regulatory basis of unicellular algal life-cycle differentiation and provides valuable resources for investigating the ecologically important coccolithophore algae.
Deep Learning Models Can Predict Violence and Threats Against Healthcare Providers Using Clinical Notes
Authors: Dobbins Nicholas J , Chipkin Jacqueline , Byrne Tim , Ghabra Omar , Siar Julia , Sauder Mitchell , Huijon R Michael , Black Taylor M
Published: May 2024

Violence, verbal abuse, threats, and sexual harassment of healthcare providers by patients is a major challenge for healthcare organizations around the world, contributing to staff turnover, distress, absenteeism, and reduced job satisfaction and overall mental and physical health. To enable interventions prior to possible violent episodes, we trained two deep learning models to predict violence against healthcare workers 3 days prior to violent events for case and control patients. The first model is a document classification model using clinical notes, and the second a baseline regression model using largely structured data. Our document classification model achieved an F1 score of 0.75 while our model using structured data achieved an F1 of 0.72, both exceeding predictive performance of a psychia-try team who reviewed the same documents (0.5 F1). To aid in explainability and understanding of risk factors for violent events, we additionally trained a named entity recognition classifier on annotations of the same corpus, which achieved an overall F1 of 0.7. This study demonstrates the first deep learning model capable of predicting violent events within healthcare settings using clinical notes, sur-passing the first published baseline of human experts. We anticipate our methods can be generalized and extended to enable intervention at other hospital systems.
Genetically Encoded FRET Biosensor for Live-cell Visualization of Lamin A Phosphorylation at Serine 22
Authors: Liu Jian , Li Qianqian , Wang Jinfeng , Qiu Juhui , Zhou Jing , Peng Qin
Published: May 2024

Extensive phosphorylation at Serine 22 (pSer22) on lamin A is the hallmark of cell mitosis, which contributes to the breakdown of nuclear envelope. In the interphase, the pSer22 lamin A exists in low abundance and involves in mechanotransduction, virus infection and gene expression. Numerous evidence emerges to support lamin A regulation on cell function and fate by phosphorylation. However, live-cell imaging tools for visualizing the dynamics of pSer22 lamin A is yet to be established. Herein, we developed a novel lamin A phosphorylation sensor (LAPS) based on fluorescence resonance energy transfer (FRET) with high sensitivity and specificity. We observed the dynamic lamin A phosphorylation during cell cycle progression in single living cells: the increase of pSer22 modification when cells enter the mitosis and recovered upon the mitosis exit. Our biosensor also showed the gradual reduction of pSer22 modification during cell adhesion and in response to hypotonic environment. By applying LAPS, we captured the propagation of pSer22 modification from inside to outside of the inner nuclear membrane, which further led to the breakdown of nuclear envelope. Meanwhile, we found the synchronous phosphorylation of lamin A and H3S10 at mitosis entry. Inhibition of Aurora B, the responsible kinase for H3S10ph, could shorten the mitotic period without obvious effect on the pSer22 modification level of lamin A. Thus, LAPS allows the spatiotemporal visualization of lamin A phosphorylation at Serine 22 site, which will be useful for elucidating the molecular mechanisms underlying cell mitosis and mechanoresponsive processes.
The contribution of small protected areas to the big picture of forest conservation and restoration in Sweden
Authors: Svensson Johan , Lopez-Peinado Andres , Jonsson Bengt Gunnar , Singh Navinder J
Published: May 2024

In forest regions worldwide, industrial forestry has left fragments of natural forests behind. This challenges biodiversity conservation and calls for ecological restoration for sustainable forest management and conservation. The functionality of protected areas need to be improved and forest ecosystems set in a state that better favors biodiversity, resilience and provisioning of ecosystem services. Sweden contributes a substantial share of the European forests, with dominance of non-industrial forest ownership and extensive forestry footprint, and hence with immediate need for advanced conservation and restoration. Protection through voluntary nature conservation agreements and regulated biotope protection areas exists since the 1990s, with schemes involving economic compensation to landowners to facilitate conservation and restoration. Across entire Sweden and all ecoregions, we assessed their accumulated capacity over a 30-year period, including forest types protected, type of restoration management, rotation intervals, and selection of tree species. These nearly 14,000 different areas covering over 70,000ha are small, ranging in size from 5ha but rarely larger than 20ha. Their contribution is important, particularly in south Sweden with low and fragmented forest cover among many different owners. Active restoration dominates over passive set asides, coniferous forest types are less represented than more rare forest types, many different tree species are favored, and different restoration types occur but with few types dominating. In recognizing their critical importance, we find that the practices are narrow and repetitive, and that a greater restoration diversification is needed. The decreasing trend in protection is alarming since these contribute key forest type representativeness and functionality.
Bifurcation enhances temporal information encoding in the olfactory periphery
Authors: Choi Kiri , Rosenbluth Will , Graf Isabella R. , Kadakia Nirag , Emonet Thierry
Published: May 2024

Living systems continually respond to signals from the surrounding environment. Survival requires that their responses adapt quickly and robustly to the changes in the environment. One particularly challenging example is olfactory navigation in turbulent plumes, where animals experience highly intermittent odor signals while odor concentration varies over many length- and timescales. Here, we show theoretically thatDrosophilaolfactory receptor neurons (ORNs) can exploit proximity to a bifurcation point of their firing dynamics to reliably extract information about the timing and intensity of fluctuations in the odor signal, which have been shown to be critical for odor-guided navigation. Close to the bifurcation, the system is intrinsically invariant to signal variance, and information about the timing, duration, and intensity of odor fluctuations is transferred efficiently. Importantly, we find that proximity to the bifurcation is maintained by mean adaptation alone and therefore does not require any additional feedback mechanism or fine-tuning. Using a biophysical model with calcium-based feedback, we demonstrate that this mechanism can explain the measured adaptation characteristics ofDrosophilaORNs.
Plant genotype-specific modulation ofClonostachys rosea-mediated biocontrol of septoria tritici blotch disease on wheat
Authors: Chaudhary Sidhant , Zakieh Mustafa , Dubey Mukesh , Jensen Dan Funck , Grenville-Briggs Laura , Chawade Aakash , Karlsson Magnus
Published: May 2024

Background

Beneficial microorganisms can act as biological control agents (BCAs) by directly targeting pathogens or indirectly by enhancing the plant’s defense mechanisms against pathogens. However, efficiencies with which plants benefit from BCAs vary, potentially because of genetic variation in plants for plant-BCA compatibility. The aim of this study was to explore the genetic variation in winter wheat for modulation ofClonostachys rosea-mediated biocontrol of septoria tritici blotch disease caused by the fungal pathogenZymoseptoria tritici.

Results

In total, 202 winter wheat genotypes, including landraces and old cultivars grown from 1900 onwards in the Scandinavian countries, were tested under greenhouse-controlled conditions. Foliar spray applications of the pathogen and the fungal BCA in two treatments, i.e.,Z. tritici(Zt) alone andZ. triticialong withC. rosea(ZtCr) were used to assess the disease progress over time. The absence and presence ofC. roseain Zt and ZtCr, respectively, allowed the dissection of variation for plant disease resistance and biocontrol efficacy. The study showed significant phenotypic variation among plant genotypes for disease progression in both Zt and ZtCr treatments. Moreover, disease progress for individual plant genotypes differed significantly between the two treatments, indicating a plant genotype-dependent variation in biocontrol efficacy. For the phenotypic variation in disease progress and biocontrol efficacy, a genome-wide association study using a 20K single-nucleotide polymorphism (SNP) marker array was also performed. In total, five distinct SNP markers associated with disease resistance and four SNP markers associated withC. roseabiocontrol efficacy were identified.

Conclusions

This work serves as a foundation to further characterize the genetic basis of plant-BCA interactions, facilitating opportunities for concurrent breeding for disease resistance and biocontrol efficacy.
Impact of rotavirus vaccination in Malawi from 2012 to 2022 compared to model predictions before, during, and after the COVID-19 pandemic
Authors: Pitzer Virginia E. , Ndeketa Latif , Asare Ernest O. , Hungerford Daniel , Jere Khuzwayo C. , Cunliffe Nigel A.
Published: May 2024

Background

Rotarix® rotavirus vaccine was introduced into the Malawi national immunization program in October 2012. We used a previously developed mathematical models to estimate overall vaccine effectiveness over a 10-year period following rotavirus vaccine introduction.

Methods

We analyzed data on children <5 years old hospitalized with acute gastroenteritis in Blantyre, Malawi from January 2012 to June 2022, compared to pre-vaccination data. We estimated vaccine coverage before, during, and after the COVID-19 pandemic using data from rotavirus-negative children. We compared model predictions for the weekly number of rotavirus-associated gastroenteritis (RVGE) cases to the observed number by age to validate model predictions and estimate overall vaccine effectiveness.

Results

The number of RVGE and rotavirus-negative acute gastroenteritis cases declined substantially following vaccine introduction. Vaccine coverage among rotavirus-negative controls was >90% with two doses by July 2014, and declined to a low of ∼80% in October 2020, before returning to pre-pandemic levels by July 2021. Our models captured the post-vaccination trends in RVGE incidence, with 5.4% to 19.4% of observed weekly RVGE cases falling outside of the 95% prediction intervals. Comparing observed RVGE cases to the model-predicted incidence without vaccination, overall vaccine effectiveness was estimated to be 36.0% (95% prediction interval: 33.6%, 39.9%) peaking in 2014 and was highest in infants (52.5%; 95% prediction interval: 50.1%, 54.9%).

Conclusions

Overall effectiveness of rotavirus vaccination in Malawi is modest despite high vaccine coverage and has plateaued since 2016. Our mathematical models provide a validated platform for assessing strategies to improve rotavirus vaccine impact.
Ultra-Rapid Droplet Digital PCR Enables Intraoperative Tumor Quantification
Authors: Murphy Zachary R. , Bianchini Emilia C. , Smith Andrew , Körner Lisa I. , Russell Teresa , Reinecke David , Wang Yuxiu , Snuderl Matija , Orringer Daniel A. , Evrony Gilad D.
Published: May 2024

The diagnosis and treatment of tumors often depends on molecular-genetic data. However, rapid and iterative access to molecular data is not currently feasible during surgery, complicating intraoperative diagnosis and precluding measurement of tumor cell burdens at surgical margins to guide resections. To address this gap, we developed Ultra-Rapid droplet digital PCR (UR-ddPCR), which can be completed in 15 minutes from tissue to result with an accuracy comparable to standard ddPCR. We demonstrate UR-ddPCR assays for the IDH1 R132H and BRAF V600E clonal mutations that are present in many low-grade gliomas and melanomas, respectively. We illustrate the clinical feasibility of UR-ddPCR by performing it intraoperatively for 13 glioma cases. We further combine UR-ddPCR measurements with UR-stimulated Raman histology intraoperatively to estimate tumor cell densities in addition to tumor cell percentages. We anticipate that UR-ddPCR, along with future refinements in assay instrumentation, will enable novel point-of-care diagnostics and the development of molecularly-guided surgeries that improve clinical outcomes.
Artificial Intelligence in Periodontology: Performance Evaluation of ChatGPT, Claude, and Gemini on the In-service Examination
Authors: Ahmad Bushra , Saleh Khaled , Alharbi Saleh , Alqaderi Hend , Jeong Y. Natalie
Published: May 2024

Background

Artificial intelligence (AI) language models have shown potential as educational tools in healthcare, but their accuracy and reliability in periodontology education require further evaluation. In this study we aimed to assess and compare the performance of three prominent AI language models—ChatGPT-4o, Claude 3 Opus, and Gemini Advanced—with second-year periodontics residents across the United States on the American Academy of Periodontology 2024 in-service examination.

Methods

We conducted a cross-sectional study using 331 multiple-choice questions from the 2024 periodontology in-service examination. We evaluated and compared the performances of ChatGPT-4o, Claude 3 Opus, and Gemini Advanced across various question domains. The results of second-year periodontics residents served as a benchmark.

Results

ChatGPT-4o, Gemini Advanced, and Claude 3 Opus significantly outperformed second-year periodontics residents across the United States, with accuracy rates of 92.7 percent, 81.6 percent, and 78.5 percent, respectively, compared to the residents’ 61.9 percent. The differences in performance among the AI models were statistically significant (p< 0.001). Percentile rankings underscored the superior performance of the AI models, with ChatGPT-4o, Gemini Advanced, and Claude 3 Opus placing in the 99.95th, 98th, and 95th percentiles, respectively.

Conclusion

ChatGPT-4o displayed superior performance compared to Claude 3 Opus and Gemini Advanced. The results highlight the potential of AI large language models (LLMs) as educational tools in periodontology and emphasize the need for ongoing evaluation and validation as these technologies evolve. Researchers should explore both the integration of AI language models into periodontal education and their impact on learning outcomes and clinical decision-making.
Genetic ablation of GABABreceptors from oligodendrocyte precursor cells protects against demyelination in the mouse spinal cord
Authors: Gobbo D , Rieder P , Fang LP , Buttigieg E , Schablowski M , Damo E , Bosche N , Dallorto E , May P , Bai X , Kirchhoff F , Scheller A
Published: May 2024

GABAergic signaling and GABABreceptors play crucial roles in regulating the physiology of oligodendrocyte-lineage cells, including their proliferation, differentiation, and myelination. Therefore, they are promising targets for studying how spinal oligodendrocyte precursor cells (OPCs) respond to injuries and neurodegenerative diseases like multiple sclerosis. Taking advantage of the temporally controlled and cell-specific genetic removal of GABABreceptors from OPCs, our investigation addresses their specific influence on OPC behavior in the gray and white matter of the mouse spinal cord. Our results show that while GABABreceptors do not significantly alter OPC cell proliferation and differentiation under physiological conditions, they distinctly regulate the Ca2+signaling of OPCs. In addition, we investigate the impact of OPC-GABABreceptors in two models of toxic demyelination, namely the cuprizone and the lysolecithin models. The genetic removal of OPC-GABABreceptors protects against demyelination and oligodendrocyte loss. Additionally, we observe enhanced resilience to cuprizone-induced pathological alterations in OPC Ca2+signaling. Our results provide valuable insights into the potential therapeutic implications of manipulating GABABreceptors in spinal cord OPCs and deepen our understanding of the interplay between GABAergic signaling and spinal cord OPCs, providing a basis for future research.
Light and substrate composition control root exudation rates at the initial stages of soilless lettuce cultivation
Authors: de Haas Brechtje R. , Oburger Eva , Van Labeke Marie-Christine , Dhooghe Emmy , Geelen Danny
Published: May 2024

Plant root exudation is an inherent metabolic process that enhances various functions of the root system like the mobilization of nutrients and interactions with surrounding microbial communities. The role and extent of root exudation in soilless crop production is poorly investigated. Here, we analyzed soilless lettuce and show that the root exudation rate declines with plant age. Furthermore, the impact of light quality and substrate was assessed by growing soilless lettuce in 100% red light (660 nm), 100% blue light (450 nm), and white light (full-light spectrum) and in 100% perlite, 100% potting soil, or mixtures of both materials. Root exudates were collected at 10, 17 and 24 days after transplanting. The total carbon root exudation rate was influenced by light conditions and substrate composition at the earliest timepoint of the culture but not at later growth stages. The total carbohydrate exudation rate was significantly higher under pure blue and red light compared to white light. The impact of light depended on the presence of perlite in the substrate. The total phenolic compound exudation rate was most strongly influenced by the substrate composition and reached the highest level in either pure potting soil or pure perlite. These findings underscore the importance of root exudation during the initial stages of development. Light and growing media influence the exudation rate at this early stage, suggesting that exudation is an adaptive process of the soilless lettuce culture.

HIGHLIGHT

At an initial stage of development, soilless lettuce exudation rates are high and modulated by light and substrate composition, whereas older plants show lower rates that are not influenced by these environmental conditions.
Reduced temporal and spatial stability of neural activity patterns predict cognitive control deficits in children with ADHD
Authors: Gao Zhiyao , Duberg Katherine , Warren Stacie L , Zheng Li , Hinshaw Stephen P. , Menon Vinod , Cai Weidong
Published: May 2024

This study explores the neural underpinnings of cognitive control deficits in ADHD, focusing on overlooked aspects of trial-level variability of neural coding. We employed a novel computational approach to neural decoding on a single-trial basis alongside a cued stop-signal task which allowed us to distinctly probe both proactive and reactive cognitive control. Typically developing (TD) children exhibited stable neural response patterns for efficient proactive and reactive dual control mechanisms. However, neural coding was compromised in children with ADHD. Children with ADHD showed increased temporal variability and diminished spatial stability in neural responses in salience and frontal-parietal network regions, indicating disrupted neural coding during both proactive and reactive control. Moreover, this variability correlated with fluctuating task performance and with more severe symptoms of ADHD. These findings underscore the significance of modeling single-trial variability and representational similarity in understanding distinct components of cognitive control in ADHD, highlighting new perspectives on neurocognitive dysfunction in psychiatric disorders.
The diversity ofSNCAtranscripts in neurons, and its impact on antisense oligonucleotide therapeutics
Authors: Evans James R. , Gustavsson Emil K. , Doykov Ivan , Murphy David , Virdi Gurvir S. , Lachica Joanne , Röntgen Alexander , Murtada Mhd Hussein , Pang Chun Wei , Macpherson Hannah , Wernick Anna I. , Toomey Christina E. , Athauda Dilan , Choi Minee L. , Hardy John , Wood Nicholas W. , Vendruscolo Michele , Mills Kevin , Heywood Wendy , Ryten Mina , Gandhi Sonia
Published: May 2024

The role of theSNCAgene locus in driving Parkinson’s disease (PD) through rare and common genetic variation is well-recognized, but the transcriptional diversity ofSNCAin vulnerable cell types remains unclear. We performedSNCAlong-read RNA sequencing in human dopaminergic neurons and show that annotatedSNCAtranscripts account for only 5% of expression. Rather, the majority of expression (75%) at theSNCAlocus originates from transcripts with alternative 5’ and 3’ untranslated regions. Importantly, 10% originates from transcripts encoding open reading frames not previously annotated, which are translated and detectable in human postmortem brain. Defining the 3’ untranslated regions enabled the rational design of antisense oligonucleotides targeting the majority ofSNCAtranscripts, leading to the effective reversal of PD pathology, including protein aggregation, mitochondrial dysfunction, and toxicity. Resolving the complexity of theSNCAtranscriptional landscape impacts RNA therapies and highlights differences in protein isoforms and their contribution to disease.
Self-Supervised Grid Cells Without Path Integration
Authors: Pettersen Markus , Schøyen Vemund Sigmundson , Østby Mattis Dalsætra , Malthe-Sørenssen Anders , Lepperød Mikkel Elle
Published: May 2024

Grid cells, found in the medial Entorhinal Cortex, are known for their regular spatial firing patterns. These cells have been proposed as the neural solution to a range of computational tasks, from performing path integration, to serving as a metric for space. Their exact function, however, remains fiercely debated. In this work, we explore the consequences of demanding distance preservation over small spatial scales in networks subject to a capacity constraint. We consider two distinct self-supervised models, a feedforward network that learns to solve a purely spatial encoding task, and a recurrent network that solves the same problem during path integration. We find that this task leads to the emergence of highly grid cell-like representations in both networks. However, the recurrent network also features units with band-like representations. We subsequently prune velocity inputs to subsets of recurrent units, and find that their grid score is negatively correlated with path integration contribution. Thus, grid cells emerge without path integration in the feedforward network, and they appear substantially less important than band cells for path integration in the recurrent network. Our work provides a minimal model for learning grid-like spatial representations, and questions the role of grid cells as neural path integrators. Instead, it seems that distance preservation and high population capacity is a more likely candidate task for learning grid cells in artificial neural networks.
On the influence of the vascular architecture on Gradient Echo and Spin Echo BOLD fMRI signals across cortical depth: a simulation approach based on realistic 3D vascular networks
Authors: Báez-Yáñez Mario Gilberto , Siero Jeroen C.W. , Curcic Vanja , van Osch Matthias J.P. , Petridou Natalia
Published: May 2024

GE-BOLD contrast stands out as the predominant technique in functional MRI experiments for its high sensitivity and straightforward implementation. GE-BOLD exhibits rather similar sensitivity to vessels independent of their size at submillimeter resolution studies like those examining cortical columns and laminae. However, the presence of nonspecific macrovascular contributions poses a challenge to accurately isolate neuronal activity. SE-BOLD increases specificity towards small vessels, thereby enhancing its specificity to neuronal activity, due to the effective suppression of extravascular contributions caused by macrovessels with its refocusing pulse. However, even SE-BOLD measurements may not completely remove these macrovascular contributions. By simulating hemodynamic signals across cortical depth, we gain insights into vascular contributions to the laminar BOLD signal. In this study, we employed four realistic 3D vascular models to simulate oxygen saturation states in various vascular compartments, aiming to characterize both intravascular and extravascular contributions to GE and SE signals, and corresponding BOLD signal changes, across cortical depth at 7T. Simulations suggest that SE-BOLD cannot completely reduce the macrovascular contribution near the pial surface. Simulations also show that both the specificity and signal amplitude of BOLD signals at 7T depend on the spatial arrangement of large vessels throughout cortical depth and on the pial surface.
Enriched environmental intervention mitigates hippocampal cellularity and behavioral disorders in maternal protein-restricted male rat offspring
Authors: Grigoletti-Lima Gabriel Boer , Boer Patrícia Aline , Gontijo José Antonio Rocha
Published: May 2024

Background

Gestational protein intake restriction induces long-lasting harmful outcomes in the offspring’s organs and systems.

Aims

This study sought to evaluate the effects of protein restriction during pregnancy and breastfeeding in 42-day-old male offspring on the structure of the hippocampus, behavior tests related to memory and emotions, and the influence of an enriched environment on these parameters.

Results and Discussion

The current study demonstrated that maternal protein restriction during neural development causes crucial morphological changes in the hippocampus, making the LP offspring vulnerable to specific neural disorders in adulthood. In addition, it supports the ‘selfish brain’ theory, a paradigm that postulates the brain maintains its mass ‘selfishly’ by reallocating resources from other body parts when faced with nutritional stress. However, the hippocampus cellularity pattern was profoundly altered, significantly reducing the number of neurons after the breastfeeding period. This may expand the understanding of nutritional stress affecting the brain area’s constitution and its supposed effects on posterior behavioral disorders. Here, reciprocal data was observed between brain masses, changes in the hippocampus cell pattern, and decreased body mass in the LP progeny.

In conclusionit was demonstrated that neuronal composition and structure profoundly modified by dietary restriction are surprisingly restored from primordial cells by exposure to the enriched environment. In addition, we must emphasize that although we have observed a significant reduction in the number of neurons after gestational and breastfeeding periods, we demonstrated for the first time a substantial reduction in the fear-reflecting behavior, which an enriched environment exposure may revert. The enriched environment also significantly modified the discrimination ratio, increasing the ability of both progenies to discriminate between novel and familiar objects in a short time associated with reverse abnormal hippocampus cell patterns. These findings underscore the potential for environmental interventions to mitigate the effects of early=life nutritional stress on brain development and behavior.
Exploring techniques to improve machine learning’s identification of at-risk students in physics classes
Authors: Pace John , Hansen John , Stewart John
Published: May 2024

Machine learning models were constructed to predict student performance in an introductory mechanics class at a large land-grant university in the United States using data from 2061 students. Students were classified as either being at risk of failing the course (earning a D or F) or not at risk (earning an A, B, or C). The models focused on variables available in the first few weeks of the class which could potentially allow for early interventions to help at-risk students. Multiple types of variables were used in the model: in-class variables (average homework and clicker quiz scores), institutional variables [college grade point average (GPA)], and noncognitive variables (self-efficacy). The substantial imbalance between the pass and fail rates of the course, with only about 10% of students failing, required modification to the machine learning algorithms. Decision threshold tuning and upsampling were successful in improving performance for at-risk students. Logistic regression combined with a decision threshold tuned to maximize balanced accuracy yielded the strongest classifier, with a DF accuracy of 83% and an ABC accuracy of 81%. Measures of variable importance involving changes in balanced accuracy identified homework grades, clicker grades, college GPA, and the fraction of college classes successfully completed as the most important variables in predicting success in introductory physics. Noncognitive variables added little predictive power to the models. Classification models with performance near the best-performing models using the full set of variables could be constructed with very few variables (homework average, clicker scores, and college GPA) using straightforward to implement algorithms, suggesting the application of these technologies may be fairly easy to include in many physics classes.

Published by the American Physical Society
2024
Excitation signatures of isochorically heated electrons in solids at finite wave number explored from first principles
Authors: Moldabekov Zhandos A. , Gawne Thomas D. , Schwalbe Sebastian , Preston Thomas R. , Vorberger Jan , Dornheim Tobias
Published: May 2024

Ultrafast heating of solids with modern x-ray free electron lasers (XFELs) leads to a unique set of conditions characterized by the simultaneous presence of heated electrons in a cold ionic lattice. In this work, we analyze the effect of electronic heating on the dynamic structure factor (DSF) in bulk aluminum (Al) with a face-centered cubic lattice and in silicon (Si) with a crystal diamond structure using first-principles linear-response time-dependent density functional theory simulations. We find a thermally induced red shift of the collective plasmon excitation in both materials. In addition, we show that the heating of the electrons in Al can lead to the formation of a double-plasmon peak due to the extension of the Landau damping region to smaller wave numbers. Finally, we demonstrate that thermal effects generate a measurable and distinct signature (peak-valley structure) in the DSF of Si at small frequencies. Our simulations indicate a variety of new features in the spectrum of x-ray-driven solids, specifically at finite momentum transfer, which can be probed in upcoming x-ray Thomson scattering experiments at various XFEL facilities.

Published by the American Physical Society
2024
Negatively enhanced thermopower near a Van Hove singularity in electron-doped
Sr2RuO4
Authors: Nishinakayama Rei , Sato Yoshiki J. , Yamanaka Takayoshi , Maeno Yoshiteru , Yaguchi Hiroshi , Kikugawa Naoki , Okazaki Ryuji
Published: May 2024

The layered perovskite Sr2RuO4 serves as a model material of the two-dimensional (2D) Fermi liquid but also exhibits various emergent phenomena including the non-Fermi-liquid (NFL) behavior under external perturbations such as uniaxial pressure and chemical substitutions. Here we present the thermoelectric transport of electron-doped system Sr2−yLayRuO4, in which a filling-induced Lifshitz transition occurs at the Van Hove singularity (VHS) point of y≈0.2. We find that the sign of the low-temperature thermopower becomes negative only near the VHS point, where the NFL behavior has been observed in the earlier study. This observation is incompatible with either a numerical calculation within a constant relaxation-time approximation or a toy-model calculation for the 2D Lifshitz transition adopting an elastic carrier scattering. As a promising origin of the observed negatively enhanced thermopower, we propose a skewed NFL state, in which an inelastic scattering with a considerable odd-frequency term plays a crucial role to negatively enhance the thermopower.

Published by the American Physical Society
2024
Measurement of Ultrashort Biphoton Correlation Times with an Integrated Two-Color Broadband
SU(1,1)
-Interferometer
Authors: Roeder F. , Pollmann R. , Stefszky M. , Santandrea M. , Luo K.-H. , Quiring V. , Ricken R. , Eigner C. , Brecht B. , Silberhorn C.
Published: May 2024

The biphoton correlation time, a measure for the conditional uncertainty in the temporal arrival of two photons from a photon pair source, is a key performance identifier for many quantum spectroscopy applications, with shorter correlation times typically yielding better performance. Furthermore, it provides fundamental insight into the effects of dispersion on the biphoton state. Here, we show that a characteristic dependence of the width of the temporal interferogram can be exploited to obtain insights into the amount of second-order dispersion inside the interferometer and to retrieve actual and Fourier-limited ultrashort biphoton correlation times of around 100fs. In the presented scheme, we simultaneously measure spectral and temporal interferograms at the output of an SU(1,1) interferometer based on an integrated broadband parametric down-conversion source in a Ti:LiNbO3 waveguide.

Published by the American Physical Society
2024