bluuebunny/crossref_metadata_2025_split huggingface dataset:
Regional lymph node mapping in patients with penile cancer undergoing radical inguinal lymph node dissection——retrospective cohort study
Authors: Tan Xingliang , Cai Taonong , Wang Yanjun , Wu Zhiming , Zhou Qianghua , Guo Shengjie , Li Jing , Yuan Gangjun , Liu Zhenhua , Li Zhiyong , Liu Zhicheng , Tang Yi , Zou Yuantao , Luo Sihao , Qin Zike , Zhou Fangjian , Lin Chunhua , Han Hui , Yao Kai 
Published: February 2024

Background:
Radical inguinal lymph node dissection (rILND) is the most available treatment to cure penile cancer (PC) with limited inguinal-confined disease. However, guidelines regarding acceptable boundaries of rILND are controversial, and consensus is lacking. We aimed to standardize the surgical boundaries of rILND with definite pathological evidence and explore the distribution pattern of inguinal lymph nodes (ILNs) in PC.

Methods:
A total of 414 PC patients from two centers who underwent rILND were enrolled. The ILN distribution was divided into seven zones anatomically for pathological examination. Student’s t test and Kaplan‒Meier survival analysis were used.

Results:
ILNs displayed a funnel-shaped distribution with high density in superior regions. ILNs and metastatic nodes present anywhere within the radical boundaries. Positive ILNs were mainly concentrated in zone I (51.7%) and zone II (41.3%), but there were 8.7 and 12.3% in inferior zones V and VI, respectively, and 7.1% in the deep ILNs. More importantly, a single positive ILN and first-station positive zone was detected in all seven regions. Single positive ILNs were located in zones I through VI in 40.4%, 23.6%, 6.7%, 18.0%, 4.5% and 1.1%, respectively, and 5.6% presented deep ILN metastasis directly.

Conclusion:
We established a detailed ILN distribution map and displayed lymphatic drainage patterns with definite pathological evidence using a large cohort of PC patients. Single positive ILNs and first-station metastatic zones were observed in any region, even directly with deep ILN metastasis. Only rILND can ensure tumor-free resection without the omission of positive nodes.
Evaluation of cyclosporine 0.05% and artificial tears for the management of dry eye disease following cataract surgery: a randomized controlled trial
Authors: Ahmadi Hanieh , Tahmasbian Saeed , Janbazi Maryam , Amiri Arvin , Heidari Zahra 
Published: February 2024

Purpose:
To compare the effects of cyclosporine 0.05% and artificial tears on dry eye disease following cataract surgery.

Methods:
This prospective, double-masked, randomized clinical trial enroled 60 eyes of 60 eligible cataract patients who completed the study. Patients were randomized to receive either cyclosporine 0.05% or artificial tear four times daily for 1 month following cataract surgery. Clinical assessments included refraction, corrected distance visual acuity, tear break-up time (TBUT), Schirmer’s test, and the visual analogue scale (VAS). An independent sample t-test was used to compare the means of the variables between the two groups.

Results:
Mean patient age was 64.15±9.17 (range, 45–90), of which 53% (n=32) were female. There was no significant difference in mean age (P=0.308) between the two groups. One month postoperatively, the cyclosporine 0.05% group had a significantly higher TBUT value (P=0.004). Schirmer’s result (P=0.095) and the VAS questionnaire scores (P=0.374) did not show a statistically significant difference between the two groups. There was no significant difference in the visual outcomes (P>0.05).

Conclusion:
Cyclosporine 0.05% was superior to artificial tears in improving tear stability after cataract surgery in the management of immediate postoperative dry eye. It may provide a more effective therapeutic option for the management of dry eye symptoms in the clinical setting.
ATP Citrate Lyase Drives Vascular Remodeling Diseases Development Through Metabolic-Epigenetic Reprograming
Authors: Grobs Yann , Romanet Charlotte , Lemay Sarah-Eve , Bourgeois Alice , Voisine Pierre , Theberge Charlie , Sauvaget Melanie , Breuils-Bonnet Sandra , Martineau Sandra , Kabbout Reem El , Mougin Manon , Dumais Elizabeth , Perron Jean , Flamand Nicolas , Potus François , Provencher Steeve , Boucherat Olivier , Bonnet Sebastien 
Published: February 2024

ABSTRACTOur study explores the previously uncharted role of ATP-citrate lyase (ACLY) in vascular remodeling within the pulmonary and coronary arteries, providing novel insights into the pathogenesis of pulmonary hypertension and coronary artery diseases. ACLY, involved in de novo lipid synthesis and histone acetylation, has emerged as a key regulator in sustaining vascular smooth muscle cell (VSMC) proliferation and survival.Utilizing human coronary and pulmonary artery tissues, our findings reveal an upregulation of ACLY expression during vascular remodeling processes. Inhibition of ACLY, achieved through pharmacological and molecular interventions in humans primary cultured VSMCs, leads to decreased proliferation, migration, and resistance to apoptosis. Mechanistically, these effects are associated with diminished glycolysis, lipid synthesis, GCN5-dependent histone acetylation, and FOXM1 activation.In vivo experiments, combining pharmacological and VSMC-specific ACLY knockout mice, ACLY inhibition demonstrates its efficacy in mitigating coronary artery remodeling and reducing pulmonary hypertension. Notably, initiating ACLY inhibition post-disease onset reverses pathological conditions, positioning ACLY as a promising therapeutic target.Human ex vivo tissue culture further supports our findings, showing reduced vascular remodeling in cultured human coronary artery rings and a reversal of pulmonary artery remodeling in precision-cut lung slices upon ACLY inhibition. This study introduces a groundbreaking concept, linking disparate abnormalities in vascular diseases to a common pathogenetic denominator, ACLY. The identified “multiple hit” therapeutic approach presents potential targets for addressing complex vascular diseases, offering avenues for future clinical interventions.ONE SENTENCE SUMMARYOur study delineates the pivotal role of ATP-citrate lyase in orchestrating vascular remodeling, establishing it as a compelling translational target for therapeutic interventions in pulmonary hypertension and coronary artery disease.
Conformational Space of the Translocation Domain of Botulinum Toxin: Atomistic Modeling and Mesoscopic Description of the Coiled-Coil Helix Bundle
Authors: Delort Alexandre , Cottone Grazia , Malliavin Thérèse E. , Müller Martin Michael 
Published: February 2024

AbstractThe toxicity of botulinum multi-domain neurotoxins (BoNTs) arises from a sequence of molecular events, in which the translocation of the catalytic domain through the membrane of a neurotransmitter vesicle plays a key role. A structural study (Lamet al., Nat. Comm., 2018) of the translocation domain of BoNT suggests that the interaction with the membrane is driven by the transition of anαhelical switch towards aβhairpin. Atomistic simulations in conjunction with the mesoscopicTwistermodel are used to investigate the consequences of this proposition for the toxin-membrane interaction. The conformational mobilities of the domain as well as the effect of the membrane, implicitly examined by comparing water and water-ethanol solvents, lead to the conclusion that the transition of the switch modifies the internal dynamics and the effect of membrane hydrophobicity on the whole protein. The central twoαhelices, helix 1 and helix 2, forming two coiled-coil motifs, are analyzed using theTwistermodel, in which the initial deformation of the membrane by the protein is caused by the presence of local torques arising from asymmetric positions of hydrophobic residues. Different torque distributions are observed depending on the switch conformations and permit to propose an origin for the mechanism opening the membrane.
Addressing the antibody germline bias and its effect on language models for improved antibody design
Authors: Olsen Tobias H. , Moal Iain H. , Deane Charlotte M. 
Published: February 2024

AbstractThe versatile binding properties of antibodies have made them an extremely important class of biotherapeutics. However, therapeutic antibody development is a complex, expensive and time-consuming task, with the final antibody needing to not only have strong and specific binding, but also be minimally impacted by any developability issues. The success of transformer-based language models in protein sequence space and the availability of vast amounts of antibody sequences, has led to the development of many antibody-specific language models to help guide antibody discovery and design. Antibody diversity primarily arises from V(D)J recombination, mutations within the CDRs, and/or from a small number of mutations away from the germline outside the CDRs. Consequently, a significant portion of the variable domain of all natural antibody sequences remains germline. This affects the pre-training of antibody-specific language models, where this facet of the sequence data introduces a prevailing bias towards germline residues. This poses a challenge, as mutations away from the germline are often vital for generating specific and potent binding to a target, meaning that language models need be able to suggest key mutations away from germline.In this study, we explore the implications of the germline bias, examining its impact on both general-protein and antibody-specific language models. We develop and train a series of new antibody-specific language models optimised for predicting non-germline residues. We then compare our final model, AbLang-2, with current models and show how it suggests a diverse set of valid mutations with high cumulative probability. AbLang-2 is trained on both unpaired and paired data, and is freely available (https://github.com/oxpig/AbLang2.git).
Fine-scale genetic structure and rare variant frequencies
Authors: Gagnon Laurence , Moreau Claudia , Laprise Catherine , Girard Simon L. 
Published: February 2024

AbstractIn response to the current challenge in genetic studies to make new associations, we advocate for a shift toward leveraging population fine-scale structure. Our exploration brings to light distinct fine-structure within populations having undergone a founder effect, challenging the prior perception of homogeneity. This underscores that smaller, but well-defined cohorts, demonstrate an important increase in rare variant frequencies, offering a promising avenue for new genetic variants’ discovery.
Science Education for the Youth (SEFTY): A Neuroscience Outreach Program for High School Students in Southern Nevada During the COVID-19 Pandemic
Authors: Ghani Nabih , Baker Hayley , Huntsinger Audrey , Chen Tiffany , Familara Tiffany D , Itorralba Jose Yani , Vanderford Fritz , Zhuang Xiaowei , Chang Ching-Lan , Vo Van , Oh Edwin C. 
Published: February 2024

AbstractLaboratory outreach programs for K-12 students in the United States from 2020-2022 were suspended or delayed due to COVID-19 restrictions. While Southern Nevada also observed similar closures for onsite programs, we and others hypothesized that in-person laboratory activities could be prioritized after increasing vaccine doses were available to the public and masking was encouraged. Here, we describe how the Laboratory of Neurogenetics and Precision Medicine at the University of Nevada Las Vegas (UNLV) collaborated with administrators from a local school district to conduct training activities for high school students during the COVID-19 pandemic. The Science Education for the Youth (SEFTY) program’s curriculum was constructed to incorporate experiential learning, fostering collaboration and peer-to-peer knowledge exchange. Leveraging neuroscience tools from our UNLV laboratory, we engaged with 117 high school applicants from 2021-2022. Our recruitment efforts yielded a diverse cohort, with >41% Pacific Islander and Asian students, >9% African American students, and >12% multiracial students. We assessed the impact of the SEFTY program through pre- and post-assessment student evaluations, revealing a significant improvement of 20.3% in science proficiency (p<0.001) after participating in the program. Collectively, our laboratory curriculum offers valuable insights into the capacity of an outreach program to actively foster diversity and cultivate opportunities for academic excellence, even in the challenging context of a global pandemic.Significance StatementThe Science Education for the Youth (SEFTY) program at UNLV successfully engaged 117 diverse high school students in neuroscience-based experiential learning, demonstrating the viability of in-person education during a pandemic. Significant improvements in science proficiency (20.3% increase) underscore the program’s effectiveness in fostering academic excellence and diversity. This initiative potentially serves as a model for maintaining high-quality, inclusive science education in challenging times.
Hydrodynamic Radii of Intrinsically Disordered Proteins: Fast Prediction by Minimum Dissipation Approximation and Experimental Validation
Authors: Waszkiewicz Radost , Michaś Agnieszka , Białobrzewski Michał K. , Klepka Barbara P. , Cieplak-Rotowska Maja K. , Staszałek Zuzanna , Cichocki Bogdan , Lisicki Maciej , Szymczak Piotr , Niedzwiecka Anna 
Published: February 2024

AbstractThe diffusion coefficients of globular and fully unfolded proteins can be predicted with high accuracy solely from their mass or chain length. However, this approach fails for intrinsically disordered proteins (IDPs) containing structural domains. We propose a rapid predictive methodology for estimating the diffusion coefficients of IDPs. The methodology uses accelerated conformational sampling based on self-avoiding random walks and includes hydrodynamic interactions between coarse-grained protein subunits, modeled using the generalized Rotne-Prager-Yamakawa approximation. To estimate the hydrodynamic radius, we rely on the minimum dissipation approximation recently introduced by Cichockiet al. Using a large set of experimentally measured hydrodynamic radii of IDPs over a wide range of chain lengths and domain contributions, we demonstrate that our predictions are more accurate than the Kirkwood approximation and phenomenological approaches. Our technique may prove valuable in predicting the hydrodynamic properties of both fully unstructured and multidomain disordered proteins.TOC Graphic
REL2 overexpression in theAnopheles gambiaemidgut causes major transcriptional changes but fails to induce an immune response
Authors: Hoermann Astrid , Capriotti Paolo , Del Corsano Giuseppe , Inghilterra Maria Grazia , Habtewold Tibebu , Cai Julia A. , Saini Gauri Sachiko , Nguyen Huong , Windbichler Nikolai , Christophides George K. 
Published: February 2024

AbstractThe NF-κB-like transcription factor, REL2, is a key player in the mosquito Immunodeficiency (Imd) pathway and holds promise for controlling malaria parasite infections in genetically modifiedAnopheles gambiaemosquitoes. We engineered transgenic mosquitoes overexpressing REL2 from within the bloodmeal-inducible zinc carboxypeptidase A1 (CP) host gene in the adult posterior midgut. Our results confirmed elevated REL2 expression in the posterior midgut following a bloodmeal, with the corresponding protein localized within epithelial cell nuclei. While this induced overexpression triggered substantial transcriptional changes, accompanied by notable fitness costs, the resultant reduction inPlasmodium falciparuminfection was modest. An in-depth analysis of regulatory regions of differentially regulated genes allowed us to identify direct REL2 target genes and revealed signatures indicative of potential transcriptional repressors. To account for potential impacts of host gene modification, we also created a CP knockout line that caused marginal effects on mosquito fitness. These findings shed light on the observed absence of transcriptional activation and, in some cases, induced repression of antimicrobial peptides (AMPs) presumed to be under Imd pathway control. In conclusion, our study suggests that elevated REL2 expression in the posterior midgut may induce the upregulation of negative immune regulators, facilitating control over an otherwise unrestrained immune response, and that concurrent transcriptional derepression may be needed to effectively induce the mosquito immune response. This work contributes valuable insights into the intricate regulation of midgut immunity in malaria vector mosquitoes.
Intrinsic structural disorder on proteins is involved in the interactome evolution
Authors: Bustos Diego M 
Published: February 2024

AbstractNew mathematical tools help to understanding cell functions, adaptability and evolvability to discover hidden variables to predict phenotypes that could be tested in the future in wet labs. Different models have been successfully used to discover properties of the protein-protein interaction network or interactome. We found that in the hyperbolic Popularity-Similarity model cellular proteins with highest contents of structural intrinsic disorder cluster together in many different eukaryotic interactomes and not the prokaryoticE. coli, where proteins with high levels of intrinsic disorder are very low. We also found that the normalized theta variable from the Popularity-Similarity model for a protein family correlate to the seniority of the organisms in analysis.
Scaling laws of molecular residence time
Authors: Qin Shiyi , Yang Zhi , Huang Kai 
Published: February 2024

AbstractUnderstanding the molecular residence autocorrelation function in liquid is of fundamental importance in physical and life science. Encoded in this function is not only the binding properties, but also the information of the liquid environment. Based on extensive in silico experiments and theoretical analysis, we reveal that power law residence scaling arises in both passive and active liquid, in contrast to the common sense of exponential decay. In simple homogeneous liquid, the scaling exponent depends solely on the system dimensionality. Such scaling law is robust against the superposition of diverse binding energies in single-phase liquid but can be breached if the system undergoes phase separation. Remarkably, in a dissipative system where phase separation is subject to non-equilibrium feedback controls, an anomalous power law emerges whose scaling exponent is in line with the puzzling residence scaling of transcription factors reported in recent experiments. Our results highlight the sensitivity of molecular residence to its surrounding liquid and suggest that active phase separation can serve as a scaling proofreading mechanism in gene regulation.
Multitask Knowledge-primed Neural Network for Predicting Missing Metadata and Host Phenotype based on Human Microbiome
Authors: Monshizadeh Mahsa , Hong Yuhui , Ye Yuzhen 
Published: February 2024

AbstractMicrobial signatures in the human microbiome have been linked to various human diseases, and Machine Learning (ML) models have been developed for microbiome-based disease prediction, although improvements remain to be made in accuracy, reproducibility and interpretability. On the other hand, confounding factors, including host’s gender, age and BMI can have a significant impact on human’s microbiome, complicating microbiome-based human phenotype predictions. We recently developed MicroKPNN, an interpretable ML model that achieved promising performance for human disease prediction based on microbiome data. MicroKPNN explicitly incorporates prior knowledge of microbial species into the neural network. Here we developed MicroKPNN-MT a unified model for predicting human phenotype based on microbiome data, as well as additional metadata including age, body mass index (BMI), gender and body site. In MicroKPNNMT, the metadata information, when available, will be used as additional input features for prediction, or otherwise will be predicted from microbiome data using additional decoders in the model. We applied MicroKPNN-MT to microbiome data collected in mBodyMap, covering healthy individuals and 25 different diseases, and demonstrated its potential as a predictive tool for multiple diseases, which at the same time provided predictions for much of the missing metadata (e.g., the BMI information was missing for 94% of the samples). Our results showed that incorporating real or predicted metadata helped improve the accuracy of disease predictions, and more importantly, helped improve the generalizability of the predictive models. Finally, our model enables the interpretation of predictive models and the identification of potential microbial markers affecting host phenotypes.
Resistance genes are distinct in protein-protein interaction networks according to drug class and gene mobility
Authors: Moumi Nazifa Ahmed , Brown Connor L. , Ahmed Shafayat , Vikesland Peter J. , Pruden Amy , Zhang Liqing 
Published: February 2024

AbstractWith growing calls for increased surveillance of antibiotic resistance as an escalating global health threat, improved bioinformatic tools are needed for tracking antibiotic resistance genes (ARGs) across One Health domains. Most studies to date profile ARGs using sequence homology, but such approaches provide limited information about the broader context or function of the ARG in bacterial genomes. Here we introduce a new pipeline for identifying ARGs in genomic data that employs machine learning analysis of Protein-Protein Interaction Networks (PPINs) as a means to improve predictions of ARGs while also providing vital information about the context, such as gene mobility. A random forest model was trained to effectively differentiate between ARGs and nonARGs and was validated using the PPINs of ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, andEnterobacter cloacae), which represent urgent threats to human health because they tend to be multi-antibiotic resistant. The pipeline exhibited robustness in discriminating ARGs from nonARGs, achieving an average area under the precision-recall curve of 88%. We further identified that the neighbors of ARGs, i.e., genes connected to ARGs by only one edge, were disproportionately associated with mobile genetic elements, which is consistent with the understanding that ARGs tend to be mobile compared to randomly sampled genes in the PPINs. This pipeline showcases the utility of PPINs in discerning distinctive characteristics of ARGs within a broader genomic context and in differentiating ARGs from nonARGs through network-based attributes and interaction patterns. The code for running the pipeline is publicly available athttps://github.com/NazifaMoumi/PPI-ARG-ESKAPE