bluuebunny/crossref_metadata_2025_split huggingface dataset:
Joint deep autoencoder and subgraph augmentation for inferring microbial responses to drugs
Authors: Zhou Zhecheng , Zhuo Linlin , Fu Xiangzheng , Zou Quan 
Published: January 2024

Abstract
Exploring microbial stress responses to drugs is crucial for the advancement of new therapeutic methods. While current artificial intelligence methodologies have expedited our understanding of potential microbial responses to drugs, the models are constrained by the imprecise representation of microbes and drugs. To this end, we combine deep autoencoder and subgraph augmentation technology for the first time to propose a model called JDASA-MRD, which can identify the potential indistinguishable responses of microbes to drugs. In the JDASA-MRD model, we begin by feeding the established similarity matrices of microbe and drug into the deep autoencoder, enabling to extract robust initial features of both microbes and drugs. Subsequently, we employ the MinHash and HyperLogLog algorithms to account intersections and cardinality data between microbe and drug subgraphs, thus deeply extracting the multi-hop neighborhood information of nodes. Finally, by integrating the initial node features with subgraph topological information, we leverage graph neural network technology to predict the microbes’ responses to drugs, offering a more effective solution to the ’over-smoothing’ challenge. Comparative analyses on multiple public datasets confirm that the JDASA-MRD model’s performance surpasses that of current state-of-the-art models. This research aims to offer a more profound insight into the adaptability of microbes to drugs and to furnish pivotal guidance for drug treatment strategies. Our data and code are publicly available at: https://github.com/ZZCrazy00/JDASA-MRD.
Joint regression analysis of multiple traits based on genetic relationships
Authors: Buchardt Ann-Sophie , Zhou Xiang , Ekstrøm Claus Thorn 
Published: January 2024

Abstract

Motivation
Polygenic scores (PGSs) are widely available and employed in genomic data analyses for predicting and understanding genetic architectures. Existing approaches either require information on SNP level, do not infer clusters of traits sharing genetic characteristic, or do not have any immediate predictive properties.

Results
Here, we present geneJAM, which is a novel clustering and estimation method using PGSs for inferring a genetic relationship among multiple, simultaneously measured and potentially correlated traits in a multivariate GWAS.
Using graphical lasso, we estimate a sparse covariance matrix of the PGSs and obtain clusters of traits sharing genetic characteristics. We use the clusters to specify the structure of the error covariance matrix of a generalized least squares (GLS) model and use the feasible GLS estimator for estimating a linear regression model with a certain unknown degree of correlation between the residuals.
The method suits many biology studies well with traits embedded in some genetic functioning groups and facilitates development of the PGS research. We compare the method with fully parametric techniques on simulated data and illustrate the utility of the methods by examining a heterogeneous stock mouse data set from the Wellcome Trust Centre for Human Genetics. We demonstrate that the method successfully identifies clusters of traits and increases precision, power, and computational efficiency.

Availability and implementation
GeneJAM is implemented in R and available at: https://github.com/abuchardt/geneJAM.
RPEMHC: improved prediction of MHC–peptide binding affinity by a deep learning approach based on residue–residue pair encoding
Authors: Wang Xuejiao , Wu Tingfang , Jiang Yelu , Chen Taoning , Pan Deng , Jin Zhi , Xie Jingxin , Quan Lijun , Lyu Qiang 
Published: January 2024

Abstract

Motivation
Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC–peptide binding is vital for the development of cancer therapeutic vaccines. While recent deep learning-based methods have achieved significant performance in predicting MHC–peptide binding affinity, most of them separately encode MHC molecules and peptides as inputs, potentially overlooking critical interaction information between the two.

Results
In this work, we propose RPEMHC, a new deep learning approach based on residue–residue pair encoding to predict the binding affinity between peptides and MHC, which encode an MHC molecule and a peptide as a residue–residue pair map. We evaluate the performance of RPEMHC on various MHC-II-related datasets for MHC–peptide binding prediction, demonstrating that RPEMHC achieves better or comparable performance against other state-of-the-art baselines. Moreover, we further construct experiments on MHC-I-related datasets, and experimental results demonstrate that our method can work on both two MHC classes. These extensive validations have manifested that RPEMHC is an effective tool for studying MHC–peptide interactions and can potentially facilitate the vaccine development.

Availability
The source code of the method along with trained models is freely available at https://github.com/lennylv/RPEMHC.
Autologous bone marrow mononuclear cells to treat severe traumatic brain injury in children
Authors: Cox Charles S , Notrica David M , Juranek Jenifer , Miller Jeffrey H , Triolo Fabio , Kosmach Steven , Savitz Sean I , Adelson P David , Pedroza Claudia , Olson Scott D , Scott Michael C , Kumar Akshita , Aertker Benjamin M , Caplan Henry W , Jackson Margaret L , Gill Brijesh S , Hetz Robert A , Lavoie Michael S , Ewing-Cobbs Linda 
Published: January 2024

Abstract
Autologous bone marrow mononuclear cells (BMMNCs) infused after severe traumatic brain injury have shown promise for treating the injury. We evaluated their impact in children, particularly their hypothesized ability to preserve the blood–brain barrier and diminish neuroinflammation, leading to structural CNS preservation with improved outcomes.
We performed a randomized, double-blind, placebo-sham-controlled Bayesian dose-escalation clinical trial at two children's hospitals in Houston, TX and Phoenix, AZ, USA (NCT01851083). Patients 5–17 years of age with severe traumatic brain injury (Glasgow Coma Scale score ≤ 8) were randomized to BMMNC or placebo (3:2). Bone marrow harvest, cell isolation and infusion were completed by 48 h post-injury. A Bayesian continuous reassessment method was used with cohorts of size 3 in the BMMNC group to choose the safest between two doses. Primary end points were quantitative brain volumes using MRI and microstructural integrity of the corpus callosum (diffusivity and oedema measurements) at 6 months and 12 months. Long-term functional outcomes and ventilator days, intracranial pressure monitoring days, intensive care unit days and therapeutic intensity measures were compared between groups.
Forty-seven patients were randomized, with 37 completing 1-year follow-up (23 BMMNC, 14 placebo). BMMNC treatment was associated with an almost 3-day (23%) reduction in ventilator days, 1-day (16%) reduction in intracranial pressure monitoring days and 3-day (14%) reduction in intensive care unit (ICU) days. White matter volume at 1 year in the BMMNC group was significantly preserved compared to placebo [decrease of 19 891 versus 40 491, respectively; mean difference of −20 600, 95% confidence interval (CI): −35 868 to −5332; P = 0.01], and the number of corpus callosum streamlines was reduced more in placebo than BMMNC, supporting evidence of preserved corpus callosum connectivity in the treated groups (−431 streamlines placebo versus −37 streamlines BMMNC; mean difference of −394, 95% CI: −803 to 15; P = 0.055), but this did not reach statistical significance due to high variability.
We conclude that autologous BMMNC infusion in children within 48 h after severe traumatic brain injury is safe and feasible. Our data show that BMMNC infusion led to: (i) shorter intensive care duration and decreased ICU intensity; (ii) white matter structural preservation; and (iii) enhanced corpus callosum connectivity and improved microstructural metrics.
Sex disparities in the utilization of nurse-assisted peritoneal dialysis: a mediation analysis using data from the REIN registry
Authors: Danneville Isabelle , Beaumier Mathilde , Boyer Annabel , Chatelet Valérie , Monnet Elisabeth , Edet Stéphane , Lanot Antoine , Bechade Clémence , Lobbedez Thierry 
Published: January 2024

ABSTRACT

Background
This study was carried out to evaluate the association between patient sex and the proportion of nurse-assisted peritoneal dialysis (PD) at dialysis initiation and to explore whether sex disparities in nurse-assisted PD utilization was explained by predialysis care and/or by social deprivation using mediation analysis.

Methods
This was a retrospective study using data from the Renal Epidemiology and Information Network (REIN) registry linked to the French National Healthcare Database (SNDS) of incident patients between 1 January 2017 and 30 June 2018. A regression logistic was used for statistical analysis. A mediation analysis explored the direct effect of sex on nurse-assisted PD proportion and the indirect effect through the European Deprivation Index (EDI), and the number of general practitioner (GP) and nephrologist visits before dialysis initiation.

Results
Among 1706 patients on PD, there were 637 women (37.3%) and 1069 men (62.7%). Nurse-assisted PD proportion was 332/610 (54.4%) for women vs 464/1036 (44.8%) for men. In the multivariable analysis women were more likely to be treated by nurse-assisted PD {odds ratio (OR) 1.92 [95% confidence interval (CI) 1.46–2.52]}. Nurse-assisted PD was associated with the median number of GP visits [OR 1.44 (95% CI 1.11–1.86)] and with the median number of nephrologist visits [OR 0.59 (95% CI 0.46–0.76)]. The mediation analysis showed a direct effect of sex on nurse-assisted PD [OR 1.90 (95% CI 1.80–2.01)] and an indirect effect through the median number of GP visits [OR 1.05 (95% CI 1.04–1.06], the median number of nephrologist visits [OR 1.02 (95% CI 1.02–1.03)] and quintile 5 of the EDI [OR 1.03 (95% CI 1.02–1.03)].

Conclusion
Women were more frequently treated by nurse-assisted PD than men. Differences between women and men in predialysis care and social deprivation could explain the greater utilization of nurse-assisted PD among women.
Chronic Lymphocytic Leukemia IGHV Somatic Hypermutation Detection by Targeted Capture Next-Generation Sequencing
Authors: Grants Jennifer M , May Christina , Bridgers Josh , Huang Shujun , Gillis Sierra , Meissner Barbara , Boyle Merrill , Ben-Neriah Susana , Hung Stacy , Duns Gerben , Hilton Laura , Gerrie Alina S , Marra Marco , Kridel Robert , Sabatini Peter J B , Steidl Christian , Scott David W , Karsan Aly 
Published: January 2024

Abstract

Background
Somatic hypermutation (SHM) status of the immunoglobulin heavy variable (IGHV) gene plays a crucial role in determining the prognosis and treatment of patients with chronic lymphocytic leukemia (CLL). A common approach for determining SHM status is multiplex polymerase chain reaction and Sanger sequencing of the immunoglobin heavy locus; however, this technique is low throughput, is vulnerable to failure, and does not allow multiplexing with other diagnostic assays.

Methods
Here we designed and validated a DNA targeted capture approach to detect immunoglobulin heavy variable somatic hypermutation (IGHV SHM) status as a submodule of a larger next-generation sequencing (NGS) panel that also includes probes for ATM, BIRC3, CHD2, KLHL6, MYD88, NOTCH1, NOTCH2, POT1, SF3B1, TP53, and XPO1. The assay takes as input FASTQ files and outputs a report containing IGHV SHM status and V allele usage following European Research Initiative on CLL guidelines.

Results
We validated the approach on 35 CLL patient samples, 34 of which were characterized using Sanger sequencing. The NGS panel identified the IGHV SHM status of 34 of 35 CLL patients. We showed 100% sensitivity and specificity among the 33 CLL samples with both NGS and Sanger sequencing calls. Furthermore, we demonstrated that this panel can be combined with additional targeted capture panels to detect prognostically important CLL single nucleotide variants, insertions/deletions, and copy number variants (TP53 copy number loss).

Conclusions
A targeted capture approach to IGHV SHM detection can be integrated into broader sequencing panels, allowing broad CLL prognostication in a single molecular assay.
Screening in Multiple Myeloma and Its Precursors: Are We There Yet?
Authors: Rögnvaldsson Sæmundur , Thorsteinsdóttir Sigrún , Kristinsson Sigurður Yngvi 
Published: January 2024

Abstract

Background
Multiple myeloma (MM) is a hematological malignancy that develops over years from the asymptomatic precursors, monoclonal gammopathy of undetermined significance, and smoldering multiple myeloma. Recent evidence shows that by initiating treatment at an asymptomatic stage, outcomes in MM can be significantly improved. However, a vast majority of MM patients are diagnosed after the development of symptomatic end-organ damage and cannot reap the benefits of early treatment. The precursors of MM are easily detected by serum protein electrophoresis and free light chain assay of the serum, raising the question of whether population-based screening could detect MM at an asymptomatic stage and significantly expand the availability of early treatment in MM. Screening is a hallmark of care in many malignancies, and there are accepted criteria for when screening is appropriate.

Content
Here we review the available relevant evidence for the introduction of screening and discuss whether screening for MM and its precursors fulfills these criteria. We also highlight gaps in our current knowledge, most notably a lack of data on the benefits and harms of screening and the lack of a defined target population. There are ongoing studies that may fill these critical gaps in the literature, but their results are still pending.

Summary
Screening could lead to a paradigm shift in the care of patients with MM, but critical scientific questions need to be answered before screening of healthy individuals can be recommended. In short, we should not screen for MM and its precursors—yet.
Contributions of the Microbiome-Derived Metabolome for Risk Assessment and Prognostication of Pancreatic Cancer
Authors: León-Letelier Ricardo A , Dou Rongzhang , Vykoukal Jody , Yip-Schneider Michele T , Maitra Anirban , Irajizad Ehsan , Wu Ranran , Dennison Jennifer B , Do Kim-An , Zhang Jianjun , Schmidt C Max , Hanash Samir , Fahrmann Johannes F 
Published: January 2024

Abstract

Background
Increasing evidence implicates microbiome involvement in the development and progression of pancreatic ductal adenocarcinoma (PDAC). Studies suggest that reflux of gut or oral microbiota can lead to colonization in the pancreas, resulting in dysbiosis that culminates in release of microbial toxins and metabolites that potentiate an inflammatory response and increase susceptibility to PDAC. Moreover, microbe-derived metabolites can exert direct effector functions on precursors and cancer cells, as well as other cell types, to either promote or attenuate tumor development and modulate treatment response.

Content
The occurrence of microbial metabolites in biofluids thereby enables risk assessment and prognostication of PDAC, as well as having potential for design of interception strategies. In this review, we first highlight the relevance of the microbiome for progression of precancerous lesions in the pancreas and, using liquid chromatography–mass spectrometry, provide supporting evidence that microbe-derived metabolites manifest in pancreatic cystic fluid and are associated with malignant progression of intraductal papillary mucinous neoplasm(s). We secondly summarize the biomarker potential of microbe-derived metabolite signatures for (a) identifying individuals at high risk of developing or harboring PDAC and (b) predicting response to treatment and disease outcomes.

Summary
The microbiome-derived metabolome holds considerable promise for risk assessment and prognostication of PDAC.
The effect of abatacept on T-cell activation is not long-lived in vivo
Authors: da Rosa Larissa C , Scales Hannah E , Benson Robert A , Brewer James M , McInnes Iain B , Garside Paul 
Published: January 2024

Abstract
Abatacept, a co-stimulatory blocker comprising the extracellular portion of human CTLA-4 linked to the Fc region of IgG1, is approved for the treatment of rheumatoid arthritis. By impairing the interaction between CD28 on T cells and CD80/CD86 on APCs, its mechanisms of action include the suppression of follicular T helper cells (preventing the breach of self-tolerance in B cells), inhibition of cell cycle progression holding T cells in a state described as ‘induced naïve’ and reduction in DC conditioning. However, less is known about how long these inhibitory effects might last, which is a critical question for therapeutic use in patients. Herein, employing a murine model of OVA-induced DTH, we demonstrate that the effect of abatacept is short-lived in vivo and that the inhibitory effects diminish markedly when treatment is ceased.
A rare case report of Erdheim–Chester disease with pericardial effusion, conduction abnormalities, and atrial infiltration
Authors: Yassine Charaf , Colletti Giuseppe , Ciprian Acasandrei , George Mairesse 
Published: January 2024

Abstract

Background
Erdheim–Chester disease (ECD) is a rare multisystem disorder that primarily affects adults. It is characterized by the excessive production and accumulation of histiocytes, a type of white blood cell, within multiple tissues and organs, including the cardiovascular system. The infiltration of histiocytes can cause a range of cardiovascular symptoms, including pericardial effusion, myocardial infiltration, and heart failure, among others. Despite the potential severity of these cardiovascular manifestations, ECD is often misdiagnosed or underdiagnosed, leading to delays in appropriate treatment and poor outcomes for patients. As such, there is a pressing need for increased awareness and understanding of ECD’s cardiovascular manifestations among clinicians and researchers. This article aims to highlight the importance of considering ECD as a potential underlying cause of cardiovascular complaints and to encourage further investigation into this uncommon but potentially life-threatening condition.

Case summary
A 63-year-old man presented as outpatient complaining of dyspnoea on exertion during the last 3 weeks (New York Heart Association functional class III). He had also experienced a left shoulder and bilateral knee pain over the last 6 months. The patient was found to have a massive pericardial effusion associated with ECD. While pericardial effusions can have various causes, including infection, cancer, and autoimmune disorders, ECD is one potential cause of this condition. Therefore, it is important for clinicians to consider ECD in the differential diagnosis of patients presenting with unexplained pericardial effusions, particularly in the context of other systemic symptoms suggestive of ECD. We discuss about this specific aetiology and the clinical management of this uncommon condition.

Discussion
Erdheim–Chester disease, a non-Langerhans cell histiocytosis, is a rare multisystem disorder. Diagnosis is challenging and should be suspected in the presence of a pericardial effusion with conduction abnormalities with indicators of a multisystem disease.
Effects of biocontrol Bacillus sp. strain D5 on the pathogenic Fusarium oxysporum R1 at the microscopic and molecular level in Crocus sativus L. (saffron) corm
Authors: Bhagat Nancy , Vakhlu Jyoti 
Published: January 2024

Abstract
Corm rot of saffron caused by Fusarium oxysporum is a major threat to saffron cultivation the world over. To minimize the ill effects of chemical fungicides, attention has been shifted to the use of biocontrol agents for disease management in a sustainable way. In saffron, various biocontrol agents against corm rot disease have been reported and characterized but no study has been done so far to understand their interaction at the molecular level. The present study was conducted to unravel the mechanism of action of an already characterized native biocontrol agent i.e. Bacillus sp. strain D5 (Bar D5) against F. oxsporum R1 (Fox R1) in the saffron corm. The growth inhibition of Fox R1 was observed in vitro and in planta (saffron corm) by real time imaging. Bacillus sp. strain D5 reduced Fox R1 load in infected corms by 50% as quantified by q-PCR and the colony-forming unit method. Comparative transcriptome analysis revealed upregulation and downregulation of various Fox R1 genes in presence of Bar D5. The genes related to carbon metabolism, cell wall and membrane synthesis, and growth of Fox R1 were significantly downregulated in Bar D5-primed and Fox R1-inoculated corms as compared to only Fox R1-inoculated corms.
Archaeal virus entry and egress
Authors: Kuiper Bastiaan P , Schöntag Anna M C , Oksanen Hanna M , Daum Bertram , Quax Tessa E F 
Published: January 2024

Abstract
Archaeal viruses display a high degree of structural and genomic diversity. Few details are known about the mechanisms by which these viruses enter and exit their host cells. Research on archaeal viruses has lately made significant progress due to advances in genetic tools and imaging techniques, such as cryo-electron tomography (cryo-ET). In recent years, a steady output of newly identified archaeal viral receptors and egress mechanisms has offered the first insight into how archaeal viruses interact with the archaeal cell envelope. As more details about archaeal viral entry and egress are unravelled, patterns are starting to emerge. This helps to better understand the interactions between viruses and the archaeal cell envelope and how these compare to infection strategies of viruses in other domains of life. Here, we provide an overview of recent developments in the field of archaeal viral entry and egress, shedding light onto the most elusive part of the virosphere.