bluuebunny/crossref_metadata_2025_split huggingface dataset:
A transient brain endothelial translatome response to endotoxin is associated with mild cognitive changes post-shock in young mice
Authors: Lu Shuhan , John Portela Iria Di , Martino Nina , Ramos Ramon Bossardi , Salinero Abigail E , Smith Rachel M , Zuloaga Kristen L , Adam Alejandro P 
Published: March 2024

AbstractSepsis-associated encephalopathy (SAE) is a common manifestation in septic patients that is associated with increased risk of long-term cognitive impairment. SAE is driven, at least in part, by brain endothelial dysfunction in response to systemic cytokine signaling. However, the mechanisms driving SAE and its consequences remain largely unknown. Here, we performed translating ribosome affinity purification and RNA-sequencing (TRAP-seq) from the brain endothelium to determine the transcriptional changes after an acute endotoxemic (LPS) challenge. LPS induced a strong acute transcriptional response in the brain endothelium that partially correlates with the whole brain transcriptional response and suggested an endothelial-specific hypoxia response. Consistent with a crucial role for IL-6, loss of the main regulator of this pathway, SOCS3, leads to a broadening of the population of genes responsive to LPS, suggesting that an overactivation of the IL-6/JAK/STAT3 pathway leads to an increased transcriptional response that could explain our prior findings of severe brain injury in these mice. To identify any potential sequelae of this acute response, we performed brain TRAP-seq following a battery of behavioral tests in mice after apparent recovery. We found that the transcriptional response returns to baseline within days post-challenge. Despite the transient nature of the response, we observed that mice that recovered from the endotoxemic shock showed mild, sex-dependent cognitive impairment, suggesting that the acute brain injury led to sustained, non-transcriptional effects. A better understanding of the transcriptional and non-transcriptional changes in response to shock is needed in order to prevent and/or revert the devastating consequences of septic shock.Abstract Figure
Opioid receptor expressing neurons of the central amygdala gate behavioral effects of ketamine in mice
Authors: Pomrenze Matthew B. , Vaillancourt Sam , Llorach Pierre , Rijsketic Daniel Ryskamp , Casey Austen B. , Gregory Nicholas , Salgado Juliana S. , Malenka Robert C. , Heifets Boris D. 
Published: March 2024

ABSTRACTKetamine has anesthetic, analgesic, and antidepressant properties which may involve multiple neuromodulatory systems. In humans, the opioid receptor (OR) antagonist naltrexone blocks the antidepressant effect of ketamine. It is unclear whether naltrexone blocks a direct effect of ketamine at ORs, or whether normal functioning of the OR system is required to realize the full antidepressant effects of treatment. In mice, the effect of ketamine on locomotion, but not analgesia or the forced swim test, was sensitive to naltrexone and was therefore used as a behavioral readout to localize the effect of naltrexone in the brain. We performed whole-brain imaging of cFos expression in ketamine-treated mice, pretreated with naltrexone or vehicle, and identified the central amygdala (CeA) as the area with greatest difference in cFos intensity. CeA neurons expressing both µOR (MOR) and PKCδ were strongly activated by naltrexone but not ketamine, and selectively interrupting MOR function in the CeA either pharmacologically or genetically blocked the locomotor effects of ketamine. These data suggest that MORs expressed in CeA neurons gate behavioral effects of ketamine but are not direct targets of ketamine.
Analysis of polyurethane/gelatin complex hydrogel system for protein imprinting
Authors: Porchkhidze Alegi , Endeladze Madona , Gogichaishvili Nana , Mikautadze Otar 
Published: March 2024

AbstractPolyurethane served as the carrier in the synthesis of a hydrogel system, incorporating membrane protein as the template, N-Vinylformamide as the monomer, and 1,4-Butanediol diglycidyl ether as the crosslinker, along with gelatin, initiated by ultraviolet radiation. This resulted in the formation of the hydrogel PUNVF-Gelatin. The study investigated the influence of varying monomer concentration, crosslinker concentration, and gelatin concentration on both the adsorption capacity for membrane protein and the imprinting efficiency. Findings revealed that optimal conditions for achieving the maximum adsorption capacity occurred when the monomer mass fraction was 5%, the crosslinker mass fraction was 3%, and the gelatin mass fraction was 0.6%.
Salidroside and itsin vivometabolite tyrosol could act directly on dopamine D2 receptors: a study using RNAseq combined with Connectivity Map analysis
Authors: Zhang Ji-Zhou , Jiang Chang , Han Jing 
Published: March 2024

AbstractSalidroside is an active ingredient in traditional Chinese medicine such as Rhodiola. Itsin vivometabolite, tyrosol, exist in olive oil and red wine. For a long time, clinical practice and research have shown that both of them have many pharmacological activities, but their targets have not reached unanimous conclusion. The present study proposed that dopamine D2 receptor (DRD2) may be the target of salidroside and tyrosol, by using RNA sequencing combined with Connectivity Map (CMAP) analysis. On this basis, molecular docking, surface plasmon resonance (SPR) and cellular thermal shift assay (CETSA) were used to verify that both salidroside and tyrosol directly bind to DRD2. The results of this study can serve as a guide for further pharmacological research on salidroside and tyrosol.
Unethical amnesia brain: Memory and metacognitive distortion induced by dishonesty
Authors: Xu Xinyi Julia , Mobbs Dean , Wu Haiyan 
Published: March 2024

ABSTRACTUnethical actions and decisions may distort human memory in two aspects: memory accuracy and metacognition. However, the neural and computational mechanisms underlying the metacognition distortion caused by repeated dishonesty remain largely unknown. Here, we performed two fMRI studies, including one replication study, with an information-sending task in the scanner. The main moral decision task in the scanner involves consistency and reward as two main factors, combined with a pre-scan and post-scan memory test together with mouse tracking. With multiple dimensions of metrics to measure metacognition, we test whether the inter-subject metacognition change correlates with how participants trade off consistency and reward. We find that the compression of representational geometry of reward in the orbitofrontal cortex (OFC) is correlated with both immediate and delayed metacognition changes. Also, the functional connectivity between the dorsolateral prefrontal cortex (DLPFC) and the left temporoparietal junction (lTPJ) under dishonest responses can predict both immediate and delayed metacognition changes in memory. These results suggest that decision-making, emotion, and memory-related brain regions together play a key role in metacognition change after immoral action, shedding light on the neural mechanism of the complex interplay between moral decisions, cognitive processes, and memory distortion.‘I did that’, says my memory.‘I could not have done that’, says my pride, and remains inexorable.Eventually - the memory yields.—Nietzsche[1]
Spatial Transcriptomics of Spinal Ependymoma in NF2-related Schwannomatosis
Authors: Burket Noah , Wang Jia , Gao Hongyu , Bell Robert , Zhang Chi , Liu Yunlong , Clapp Wade , Tailor Jignesh 
Published: March 2024

SummarySpinal ependymoma (SP-EPN) is a central nervous system (CNS) tumor that is associated with high morbidity. The only effective treatment for end-stage SP-EPN is surgery, but this is associated with high risk of injury to the sensorimotor spinal tracts and paralysis. There is a critical need to understand the cellular origins of this tumor so that disease models of tumor progression can be generated for drug development. Recent genomic studies with bulkRNA sequencing suggest the molecular signature of SP-EPN matches that of ependymal cells (EPCs). However, large-scale genomic studies can often misrepresent rare cancer stem cell populations within the tumor. In this study, we performed spatial transcriptomics (ST) on a SP-EPN resected from a patient with NF2-related neurofibromatosis to examine the spatial heterogeneity within the tumor. The SP-EPN sample exhibited cellular heterogeneity with diffuse expression of astrocytic and EPC markers, and smaller pockets with RGC or stem cell markers, as well as overlap between progenitor cell and mature cell markers. These findings suggest that there may be a developmental hierarchy within the EPC lineage in SP-EPN tumors, which may stem from aberrant radial glia cells.
Actionability of Synthetic Data in a Heterogeneous and Rare Healthcare Demographic; Adolescents and Young Adults (AYAs) with Cancer
Authors: Hogenboom J. Joshi , Gomes A. Aiara Lobo , Dekker A.L.A.J. Andre , Van Der Graaf W.T.A. Winette , Husson O. Olga , Wee L.Y.L. Leonard 
Published: March 2024

AbstractPurposeResearch on rare diseases and atypical healthcare demographics is often slowed by high inter-subject heterogeneity and overall scarcity of data. Synthetic data (SD) has been proposed as means for data sharing, enlargement, and diversification, by artificially generating ‘real’ phenomena while obscuring the ‘real’ subject data. The utility of SD is actively scrutinised in healthcare research, but the role of sample size for actionability of SD is insufficiently explored. We aim to understand the interplay of actionability and sample size by generating SD sets of varying sizes from gradually diminishing amounts of real subjects’ data. We evaluate the actionability of SD in a highly heterogeneous and rare demographic: adolescents and young adults (AYAs) with cancer.MethodologyA population-based cross-sectional cohort study of 3735 AYAs was sub-sampled at random to produce 13 training datasets of varying sample sizes. We studied four distinct generator architectures built on the open-source Synthetic Data Vault library. Each architecture was used to generate SD of varying sizes based on each aforementioned training subsets. SD actionability was assessed by comparing the resulting SD to its respective ‘real’ data against three metrics – veracity, utility, and privacy concealment.ResultsAll examined generator architectures yielded actionable data when generating SD with sizes similar to the ‘real’ data. Large SD sample size increased veracity but generally increased privacy risks. Using fewer training subjects led to faster convergence in veracity, but partially exacerbated privacy concealment issues.ConclusionSD is a potentially promising option for data sharing and data augmentation, yet sample size plays a significant role in its actionability. SD generation should go hand-in-hand with consistent scrutiny and sample size should be carefully considered in this process.
High Prevalence of the Cardiovascular-Kidney-Metabolic Syndrome Among US Adults From 1999-2020 - An analysis of the NHANES survey
Authors: Tian Zhejia , Soltani Samira , Bauersachs Johann , Schmidt-Ott Kai , Melk Anette , Schmidt Bernhard MW 
Published: March 2024

AbstractBackgroundThe cardiovascular-kidney-metabolic (CKM) syndrome is a newly defined chronic health condition from American Heart Association. We assessed the prevalence of CKM syndrome stages 0-2, which have not yet progressed to cardiovascular disease (stage 3-4) with trends analysis over the past two decades.MethodsWe used cross-sectional data provided by National Health and Nutrition Examination Survey. including non-pregnant participants aged 18 or older between 1999 and 2020. Weighted prevalence was analyzed over the course of the past 20 years and by population subgroup (including age, sex, and race/ethnicity).ResultsA total of 32848 US adults were included in our study (weighted mean age, 47.3 years; women, 51.3%). 7.9% of US adults were at stage 0 without any CKM risk factors, with 64% of this subgroup being female. 18.3% of US adults were classified as stage 1 with issues related to excess or dysfunctional adiposity without other metabolic risk factors or chronic kidney disease (CKD). More than half of the US adults (56.5%) exhibited either metabolic risk factors, CKD, or both (stage 2). Between 1999 and 2020, the CKM features increased with decreasing prevalence of stage 0 (P for trends =0.0018), not only in females but also in males.ConclusionsOur findings illustrate an exceptionally high and increasing prevalence of CKM syndrome among US adults. This emphasizes the importance of comprehensive preventive strategies targeting the life style of large parts of the population. Moreover, further risk assessment should be implemented into stage 2 cohort to define patients with exceptional cardiovascular risk.Clinical PerspectiveWhat is new?CKM syndrome is a common chronic health condition in the general population. However, the prevalence of different CKM stages using real-world data has not been reported within the general population or its subgroups.The prevalence of CKM syndrome was increasing over the past two decades. The majority of US adults were classified as stage 2.A specific population remained undefined according to the current detailed definition of each CKM syndrome stage.What are the clinical implications?The high and increasing prevalence of CKM syndrome necessitates more precise preventive strategies, tailored to different target groups with consideration of age-, sex-, and gender-disparities.Given that approximately half of the study population fell into stage 2 with a wide spectrum of risk factors, it is imperative to identify patients with exceptionally high risk through additional risk assessments. This approach would facilitate the implementation of intensified treatment measures aimed at preventing the progression to cardiovascular disease (CKM syndrome stages 3-4).
Yeast-based production platform for potent and stable heavy chain-only antibodies
Authors: Lonigro Chiara , Eeckhaut Hannah , Symakani Royan Alipour , Roose Kenny , Schepens Bert , Sedeyn Koen , De Smet Anne-Sophie , Zavala Marchan Jackeline Cecilia , Vanhaverbeke Pieter , Vanmarcke Sandrine , Claes Katrien , De Cae Sieglinde , Demol Hans , Devos Simon , Fijalkowska Daria , Nerinckx Wim , Rossey Iebe , Weyts Wannes , Abdelnabi Rana , Jochmans Dirk , Neyts Johan , Saelens Xavier , van Schie Loes , Callewaert Nico 
Published: March 2024

AbstractMonoclonal antibodies are the leading drug of the biopharmaceutical market because of their high specificity and tolerability, but the current CHO-based manufacturing platform remains expensive and time-consuming leading to limited accessibility, especially in the case of diseases with high incidence and pandemics. Therefore, there is an urgent need for an alternative production system.In this study, we present a rapid and cost-effective microbial platform for heavy chain-only antibodies (VHH-Fc) in the methylotrophic yeastKomagataella phaffii(akaPichia pastoris). We demonstrate the potential of this platform using a simplified single-gene VHH-Fc fusion construct instead of the conventional monoclonal antibody format, as this is more easily expressed inPichia pastoris. We demonstrate that thePichia-produced VHH-Fc fusion construct is stable and that aPichia-produced VHH-Fc directed against the SARS-CoV-2 spike has potent SARS-CoV-2 neutralizing activityin vitroandin vivo. We expect that this platform will pave the way towards faster and cheaper development and production of broadly neutralizing single-chain antibodies in yeast.
Predicting Phylogenetic Bootstrap Values via Machine Learning
Authors: Wiegert Julius , Höhler Dimitri , Haag Julia , Stamatakis Alexandros 
Published: March 2024

AbstractSummaryEstimating the statistical robustness of the inferred tree(s) constitutes an integral part of most phylogenetic analyses. Commonly, one computes and assigns a branch support value to each inner branch of the inferred phylogeny. The most widely used method for calculating branch support on trees inferred under Maximum Likelihood (ML) is the Standard, non-parametric Felsenstein Bootstrap Support (SBS). Due to the high computational cost of the SBS, a plethora of methods has been developed to approximate it, for instance, via the Rapid Bootstrap (RB) algorithm. There have also been attempts to devise faster, alternative support measures, such as the SH-aLRT (Shimodaira–Hasegawalike approximate Likelihood Ratio Test) or the UltraFast Bootstrap 2 (UFBoot2) method. Those faster alternatives exhibit some limitations, such as the need to assess model violations (UFBoot2) or meaningless low branch support intervals (SH-aLRT). Here, we present the Educated Bootstrap Guesser (EBG), a machine learning-based tool that predicts SBS branch support values for a given input phylogeny. EBG is on average 9.4 (σ= 5.5) times faster than UFBoot2. EBG-based SBS estimates exhibit a median absolute error of 5 when predicting SBS values between 0 and 100. Furthermore, EBG also provides uncertainty measures for all per-branch SBS predictions and thereby allows for a more rigorous and careful interpretation. EBG can predict SBS support values on a phylogeny comprising 1654 SARS-CoV2 genome sequences within 3 hours on a mid-class laptop. EBG is available under GNU GPL3.Data and Code Availabilitygithub.com/wiegertj/EBGgithub.com/wiegertj/EBG-trainContactjulius-wiegert@web.de
Modelling single-stress omics integration with HIVE enables the identification of responding signatures to multifactorial stress combinations in plants
Authors: Calia Giulia , Marguerit Sophia , Zotta Mota Ana Paula , Vidal Manon , Schuler Hannes , Miranda Brasileiro Ana Cristina , Guimaraes Patricia Messenberg , Bottini Silvia 
Published: March 2024

AbstractAll organisms are subjected to multiple stresses usually occurring at the same time, requiring the activation of the appropriate signalling pathways to respond to all or by prioritizing the response to one stress factor. Plants, as sessile organisms, are particularly impacted by the constantly changing environment that is often unfavourable or even hostile. Because of the experimental complexity of studying the response of one organism to multiple stressors simultaneously, usually experiments are conducted considering one individual stress factor at the time. An alternative consists in performingin silicointegration of those data on single stress response. Currently used methods to integrate unpaired experiments consist of performing meta-analysis or finding differentially expressed genes for each condition separately and then selecting the commonly regulated ones. Although these approaches allowed to find valuable results, they mainly identify specific signatures in response to one stress and very few signature responding to multiple stresses and lack those modulated differently in each condition.For this purpose, we developed HIVE (Horizontal Integration analysis using Variational AutoEncoders) to integrate multiple single-stress transcriptomics datasets composed of unpaired experiments. Briefly, we coupled a variational autoencoder, that alleviates batch effects, with a random forest regression and the SHAP explainer to select relevant genes modulated specifically in response to one or multiple stresses.We illustrate the functionality of HIVE to study the transcriptional changes of several different plants namelyArabidopsis thaliana, rice, maize, wheat, grapevine and peanut by collecting publicly available experiments on single stress, either biotic and/or abiotic, and jointly analyse them. HIVE performed better than the differential expression analysis, meta-analysis and the state-of-the-art tool for horizontal integration allowing to identify novel promising candidates responsible for triggering effective defence responses to multiple stresses.
Hetero-antagonism of avibactam and sulbactam with cefiderocol in carbapenem-resistantAcinetobacterspp
Authors: Wong Olivia , Mezcord Vyanka , Lopez Christina , Traglia German Matias , Pasteran Fernando , Tuttobene Marisel R. , Corso Alejandra , Tolmasky Marcelo E. , Bonomo Robert A. , Ramirez María Soledad 
Published: March 2024

AbstractThe emergence of Gram-negative bacteria resistant to multiple antibiotics, particularly carbapenem-resistant (CR)Acinetobacterstrains, poses a significant threat globally. Despite efforts to develop new antimicrobial therapies, limited progress has been made, with only two drugs—cefiderocol and sulbactam-durlobactam—showing promise for CR-Acinetobacterinfections. Cefiderocol, a siderophore cephalosporin, demonstrates promising efficacy in the treatment of Gram-negative infections. However, resistance to cefiderocol has been reported inA. baumannii. Combination therapies, such as cefiderocol with avibactam or sulbactam, show reduced MICs against cefiderocol-non-susceptible strains with in vivo efficacy, although the outcomes can be complex and species-specific. In the present work, the molecular characterization of spontaneous cefiderocol-resistant variants, a CRAB strain displaying antagonism with sulbactam and anA. lwoffiistrain showing antagonism with avibactam, were studied. The results reveal intriguing insights into the underlying mechanisms, including mutations affecting efflux pumps, transcriptional regulators, and iron homeostasis genes. Moreover, gene expression analysis reveals significant alterations in outer membrane proteins, iron homeostasis, and β-lactamases, suggesting adaptive responses to selective pressure. Understanding these mechanisms is crucial for optimizing treatment strategies and preventing adverse clinical outcomes. This study highlights the importance of preemptively assessing drug synergies to navigate the challenges posed by antimicrobial resistance in CR-Acinetobacterinfections.
Cisinhibition of co-expressed DIPs and Dprs shapes neural development
Authors: Morano Nicholas C. , Lopez Davys H. , Meltzer Hagar , Sergeeva Alina P. , Katsamba Phinikoula S. , Rostam Kevin D. , Gupta Himanshu Pawankumar , Becker Jordan E. , Bornstein Bavat , Cosmanescu Filip , Schuldiner Oren , Honig Barry , Mann Richard S. , Shapiro Lawrence 
Published: March 2024

ABSTRACTInDrosophila, two interacting adhesion protein families, Dprs and DIPs, coordinate the assembly of neural networks. While intercellular DIP/Dpr interactions have been well characterized, DIPs and Dprs are often co-expressed within the same cells, raising the question as to whether they also interact incis. We show, in cultured cells andin vivo,that DIP-α and DIP-δ can interact inciswith their ligands, Dpr6/10 and Dpr12, respectively. When co-expressed inciswith their cognate partners, these Dprs regulate the extent oftransbinding, presumably through competitivecisinteractions. We demonstrate the neurodevelopmental effects ofcisinhibition in fly motor neurons and in the mushroom body. We further show that a long disordered region of DIP-α at the C-terminus is required forcisbut nottransinteractions, likely because it alleviates geometric constraints oncisbinding. Thus, the balance betweencisandtransinteractions plays a role in controlling neural development.