bluuebunny/crossref_metadata_2025_split huggingface dataset:
Access to Waitlisting and Posttransplant Outcomes in Patients With Failed Kidney Allografts Secondary to Recurrent Glomerulonephritis
Authors: Gately Ryan , Wong Germaine , Teixeira-Pinto Armando , Pilmore Helen , Hawley Carmel , Campbell Scott , Mulley William , Lim Wai H. 
Published: October 2024

Background.
Recurrent glomerulonephritis (GN) is an important cause of allograft loss after transplantation when GN is the primary cause of kidney failure. Retransplantation after allograft loss from recurrent disease requires careful consideration. We aimed to determine the probability of relisting and the risk of allograft loss after retransplantation in recipients with prior allograft loss from recurrent GN.

Methods.
Using data from the Australia and New Zealand Dialysis and Transplant Registry and multivariable Cox modeling, we compared the probability of waitlisting and allograft loss after second transplantation between those with and without prior allograft loss from recurrent disease.

Results.
Of 3276 patients who received a second kidney transplant, 179 (5%) lost their first allograft from recurrent GN. Between 2006 and 2021, 1524 patients with failed first allografts (6% with recurrent GN, 45% with primary GN but no disease recurrence) were relisted for transplantation. Compared with patients without primary GN, the adjusted hazard ratios (95% confidence intervals) for relisting in patients with primary GN, with and without disease recurrence, were 1.09 (0.88-1.34) and 1.16 (1.05-1.29), respectively. The respective adjusted hazard ratios for allograft loss after repeat transplantation were 0.77 (0.59-1) and 1.02 (0.9-1.16). Of the 81 patients who received a second allograft after losing their first allograft to GN recurrence, 18 patients (22%) also lost their second allograft because of recurrent GN.

Conclusions.
Patients with prior allograft loss from GN recurrence were not disadvantaged, with comparable waitlist potential and allograft outcome after repeat transplantation. However, >20% of those with prior allograft loss from disease recurrence also lost their second allografts from recurrent disease.
Risk Factors for Early Post-transplant Weight Changes Among Simultaneous Pancreas-kidney Recipients and Impact on Outcomes
Authors: Parajuli Sandesh , Tamburrini Riccardo , Aziz Fahad , Dodin Ban , Astor Brad C. , Mandelbrot Didier , Kaufman Dixon , Odorico Jon 
Published: October 2024

Background.
There are limited data about the risk factors for weight changes and the association of significant weight changes with graft and metabolic outcomes after simultaneous pancreas and kidney (SPK) transplantation.

Methods.
We included all SPK recipients with both allografts functioning for at least 6 mo post-transplant and categorized them based on the weight changes from baseline to 6 mo post-transplant. We analyzed risk factors for significant weight gain (SWG) and significant weight loss (SWL) over 6 mo post-transplant, as well as outcomes including pancreas uncensored graft failure, pancreas death-censored graft failure (DCGF), composite pancreas graft outcomes of DCGF, use of an antidiabetic agent, or hemoglobin A1C >6.5%, and kidney DCGF.

Results.
Of 280 SPK recipients, 153 (55%) experienced no significant weight change, 57 (20%) SWG, and 70 (25%) SWL. At 6 mo post-transplant, mean weight changes were 1.2% gain in the no significant weight change group, 13.4% gain in SWG, and 9.6% loss in the SWL groups. In multivariate analysis, the only factor associated with decreased risk for weight gain was older recipient age (aOR, 0.97; 95% confidence intervals, 0.95-0.99). Importantly, SWG or SWL were not associated with pancreas graft failure, P-DCGF, or K-DCGF. Interestingly in the adjusted model, SWG at 6 mo was associated with a lower risk for composite outcomes (HR, 0.35; 95% confidence intervals, 0.14-0.85).

Conclusions.
Forty-five percent of SPK recipients had significant weight changes by 6 mo post-transplant, but only 20% exhibited SWG. Likely because of proper management, weight changes were not associated with poor outcomes post-SPK transplant.
Outdoor Air Pollution Relates to Amygdala Subregion Volume and Apportionment in Early Adolescents
Authors: Morrel Jessica , Overholtzer L. Nate , Sukumaran Kirthana , Cotter Devyn L. , Cardenas-Iniguez Carlos , Tyszka J. Michael , Schwartz Joel , Hackman Daniel A. , Chen Jiu-Chiuan , Herting Megan M. 
Published: October 2024

AbstractBackgroundOutdoor air pollution is associated with an increased risk for psychopathology. Although the neural mechanisms remain unclear, air pollutants may impact mental health by altering limbic brain regions, such as the amygdala. Here, we examine the association between ambient air pollution exposure and amygdala subregion volumes in 9–10-year-olds.MethodsCross-sectional Adolescent Brain Cognitive DevelopmentSM(ABCD) Study®data from 4,473 participants (55.4% male) were leveraged. Air pollution was estimated for each participant’s primary residential address. Using the probabilistic CIT168 atlas, we quantified total amygdala and 9 distinct subregion volumes from T1- and T2-weighted images. First, we examined how criteria pollutants (i.e., fine particulate matter [PM2.5], nitrogen dioxide, ground-level ozone) and 15 PM2.5components related with total amygdala volumes using linear mixed-effect (LME) regression. Next, partial least squares correlation (PLSC) analyses were implemented to identify relationships between co-exposure to criteria pollutants as well as PM2.5components and amygdala subregion volumes. We also conducted complementary analyses to assess subregion apportionment using amygdala relative volume fractions (RVFs).ResultsNo significant associations were detected between pollutants and total amygdala volumes. Using PLSC, one latent dimension (LD) (52% variance explained) captured a positive association between calcium and several basolateral subregions. LDs were also identified for amygdala RVFs (ranging from 30% to 82% variance explained), with PM2.5and component co-exposure associated with increases in lateral, but decreases in medial and central, RVFs.ConclusionsFine particulate and its components are linked with distinct amygdala differences, potentially playing a role in risk for adolescent mental health problems.Graphical Abstract
Mechanistic Studies of Small Molecule Ligands Selective to RNA Single G Bulges
Authors: Hegde Shalakha , Akhter Sana , Tang Zhichao , Qi Chang , Yu Chenguang , Lewicka Anna , Liu Yu , Koirala Kushal , Reibarkh Mikhail , Battaile Kevin P. , Cooper Anne , Lovell Scott , Holmstrom Erik D. , Wang Xiao , Piccirilli Joseph A. , Gao Qi , Miao Yinglong , Wang Jingxin 
Published: October 2024

AbstractSmall-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated Molecular Dynamics (GaMD) simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity-relationship (SAR) studies and transverse relaxation measurements by NMR spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Strikingly, small structure perturbations on these key contributors, such as the addition of a methyl group that disrupts the planarity of the ligand resulted in > 100-fold reduction in the binding affinity. Our work deepened the understanding of RNA-small molecule interactions and integrated a new generalizable platform for the rational design of selective small-molecule RNA binders.
REPORTH: Determining orthologous locations of repetitive sequences between genomes
Authors: Bharadwaj Prajwal , van Dijk Bram , Bertels Frederic 
Published: October 2024

AbstractRepetitive sequences are a common feature of bacterial genomes. Some repetitive sequences such as REPINs are mobile within the genome but inherited only vertically from mother to daughter across bacterial genomes. Selfish elements in contrast are mobile within the genome but also travel horizontally from genome to genome. Yet, no matter the nature of the association between the repetitive elements and the host, it is difficult to study the evolutionary dynamics of repetitive sequences across genomes. If it is unclear whether two sequences in two different genomes are in orthologous positions, it is difficult to infer parameters like the replication rate, horizontal transfer rate and rate of loss. Here we present a tool to facilitate these analyses called REPORTH. REPORTH determines whether repetitive sequences in different but closely related bacterial genomes occur in orthologous genomic positions. Whether a position is orthologous or not depends on the orthology of flanking sequences. Flanking sequences are deemed orthologous if they are bidirectional best hits. All repetitive sequences that are found in orthologous positions across different genomes are grouped together. Analyses of these groups can be used to study the evolutionary dynamics of selfish repetitive elements such as insertion sequences, but also for mutualistic repetitive elements such as REPINs.
Bacteria-phage (co)evolution is constrained in a synthetic community across multiple bacteria-phage pairs
Authors: Castledine Meaghan , Padfield Daniel , Schoeman Marli , Berry Amy , Buckling Angus 
Published: October 2024

AbstractBacteriophages can be important drivers of bacterial densities, and therefore microbial community composition and function. These ecological interactions are likely to be greatly affected by evolutionary dynamics, because bacteria can rapidly evolve resistance to phage while phage can reciprocally evolve to increase infectivity. Most studies to date have explored eco-evolutionary dynamics using isolated pairs of bacteria-phage but in nature, multiple bacteria and phages coexist and (co)evolve simultaneously. How coevolution plays out in this context is poorly understood. Here, we examine how three coexisting soil bacteria (Ochrobactrumsp.,Pseudomonassp., andVariovoraxsp.) interact and evolve with three species-specific bacteriophages over eight weeks of experimental evolution, both as host-parasite pairs in isolation and as a mixed community. Across all species phage resistance evolution was inhibited in polyculture, with the most pronounced effect onOchrobactrum. Between bacteria-phage pairs there were also substantial differences in the effect of phage on host densities, and evolutionary dynamics including whether pairs coevolved. These contrasts emphasise the difficulty in generalising from monoculture to polyculture, and between bacteria-phage pairs to wider systems. Future studies should consider how multiple bacteria and phage pairs interact simultaneously to better understand how coevolutionary dynamics happen in natural communities.ImportanceThis project is unique in examining evolutionary dynamics among coexisting bacteria and their phages, rather than focus on single focal species – this makes our work more applicable to natural contexts while still working with controlled synthetic communities. While it is commonly assumed that bacteria will evolve phage resistance and coevolve with phage, this may be uncommon in more complex communities due to reduced contact rates and/or reduced mutation rates. Furthermore, the contrast in population dynamics and ability to coevolve between bacteria-phage pairs highlights the need for more pairs to be studied. Over-reliance on model systems that are known to coevolve means we lack an understanding of how wider bacteria-phage pairs interact, and to what extent results can be generalised beyond these pairs.
A genome-wide-level insight into the HSF gene family ofRhodomyrtus tomentosaand the functional divergence ofRtHSFA2aandRtHSFA2bin thermal adaption
Authors: Li Hui-Guang , Yang Ling , Fang Yujie , Wang Gui , Lyu Shanwu , Deng Shulin 
Published: October 2024

AbstractHeat shock transcription factor (HSF) is one of the most important regulatory elements in plant development and stress response.Rhohomyrtus tomentosahas many advantages in adapting to high temperature and humidity climates, whereas the inherence has barely been elucidated. In this study, we aimed to characterize the HSF family and investigate the thermal adaption mechanisms ofR. tomentosa. We identified 25 HSF genes in theR. tomentosagenome. They could be classified into three classes: HSFA, HSFB, and HSFC. Gene duplication event is a major motivation for the expansion of theRtHSFgene family. Most of the genes in the same subclass share similar conserved motifs and gene structures. Thecis-actingelements of the promoter regions ofRtHSFgenes are related to development, phytohormone signaling, and stress responses, and they vary among the genes even in the same subclass, resulting in different expression patterns. Especially, there exists subfunctionalization in theRtHSFA2subfamily in responding to various abiotic stresses,viz. RtHSFA2ais sensitive to drought, salt, and cold stresses, whilstRtHSFA2bis mainly induced by heat stress. We further prove thatRtHSFA2bmight be of more importance inR. tomentosathermotolerance, forArabidopsiswith overexpressedRtHSFA2boutperformed those withRtHSFA2aunder heat stress, andRtHSFA2bhas much higher transcription activity thanRtHSFA2ain regulating certain heat shock response (HSR) genes.RtHSFA2aplays a role in transactivatingRtHSFA2b. All these results provide a general prospect of theRtHSFgene family and enclose a basal thermal adaption mechanism ofR. tomentosa.
Harnessing Global HLA Data for Enhanced Patient Matching in iPSC Haplobanks
Authors: Maiers Martin , Sullivan Stephen , McClain Christopher , Leonhard-Melief Christina , Turner Marc L. , Turner David 
Published: October 2024

AbstractSeveral countries have either developed or are developing national induced pluripotent stem cell (iPSC) banks of cell lines derived from donors with HLA homozygous genotypes (two identical haplotypes) prevalent in their local populations to provide immune matched tissues and cells to support regenerative medicine therapies. This ‘haplobank’ approach relies on knowledge of the HLA genotypes of the population to identify the most beneficial haplotypes for patient coverage, and ultimately identify donors or cord blood units carrying two copies of the target haplotype. A potentially more efficient alternative to a national bank approach is to assess the haplotypes required to provide global patient coverage and to produce a single, global haplobank. Toward that end, we have developed an algorithm to prioritize HLA haplotypes that optimize coverage across the global population.We analyzed data from eighteen countries participating in the Global Alliance for iPS Therapy (GAiT). A representative pool of HLA genotypes, reflecting the HLA of patients, was derived by sampling from each country’s WMDA hematopoietic stem cell donor registry, or surrogate population. An algorithm was created based on HLA-A, -B and -DRB1 haplotype homozygous types with population HLA matching coverage defined by the absence of Host versus Graft (HvG) mismatches at these loci. HLA matching coverage was determined by iteratively selecting HLA haplotypes that provide the largest coverage against patient HLA genotypes sampled from the same population, excluding genotypes compatible with previous iterations. The top 10 haplotypes for each of the 18 countries were identified with patient coverage ranging from 19.5% in Brazil to 63.8% in Japan, with a mean coverage of 33.3%. In a ‘global’ model, utilizing the 180 most frequent haplotypes across all 18 populations (equivalent to 10 lines pe country), the patient coverage ranged from 54.6% in India to 81.7% in Sweden, with a mean of 68.4%. Our findings demonstrate that global collaboration could more than double the potential for patient HLA matching coverage.Interrogation of unrelated hematopoietic stem cell donor registry and cord blood bank HLA data demonstrated that HLA-A, -B, and -DRB1 homozygous donors for the top 180 global haplotypes are widely available. These results show that a globally coordinated strategy for haplobanking would reduce redundancy and allow more patients to be treated with the same investment.Visual AbstractHighlightsiPSC banks are being developed targeting HLA coverage to meet national needsGlobal collaboration has the potential to substantially increase the efficiency of this effort
Heritable non-genetic phenotypes are enriched for stress responses as a form of bet hedging
Authors: Grissom Spencer , Dixon Zachary , Singh Abhyudai , Blenner Mark 
Published: October 2024

AbstractDuring manufacturing batches, Chinese hamster ovary (CHO) cells encounter critical levels of environmental stressors such as ammonia, lactate, and osmolality accumulation that can significantly reduce cell health and productivity. It is therefore crucial that stress adaptation and resistance be factored into cell line development (CLD). In this study, we employee population-based transcriptomic and differential gene expression analysis on stress-induced CHO cells to identify biomarkers displaying both heritable and stress-responsive properties. Using this workflow, 199 genes displayed transcriptional variability characteristic of a bistable system that formed four network communities of co-fluctuating genes. These communities were enriched in genes related to the regulation of apoptotic processes and gene expression/metabolic pathways. Seven genes were identified as promising biomarkers for engineering a stress-resistant phenotype. Genetic engineering methods may be employed in the future to bias clonal populations for higher stress tolerance to manufacturing stress, therefore increasing cell health and productivity in at-scale bioreactors.
The ATP-dependent protease ClpYQ degrades cell division proteins DivIVA and Mbl inBacillus subtilis
Authors: Lanosky Taylor D. , Darnowski Michael G. , Brazeau-Henrie Jordan T. , Labana Puneet , Boddy Christopher N. 
Published: October 2024

AbstractATP-dependent proteases play key roles in bacterial protein quality control and regulation of cellular processes. ClpYQ and ClpXP are ATP-dependent proteases in the Gram-positive bacteriaBacillus subtilis. To date, no substrate proteins ofB. subtilisClpYQ have been characterized. The protease component encoded byclpQis synthetically lethal withclpPand the two genes are non-essential individually, suggesting potentially redundant roles for ClpYQ and ClpXP. Previous quantitative proteomic data predicted thatB. subtilisproteins DivIVA and Mbl, components of the divisome and elongasome respectively, are potential substrates of ClpYQ. The role of DivIVA and Mbl in cell division and elongation suggests a significant role of ClpYQ in regulating cell division through targeted degradation of key divisome and elongasome proteins. Here we confirm that DivIVA and Mbl are degraded by ClpYQ bothin vitroandin vivo, and thus identify the first two substrates of ClpYQ inB. subtilis.
Human Anti-Glycan Reactivity is Driven by the Selection of B cells Utilizing Private Antibody Gene Rearrangements that are Affinity Maturated in Germinal Centers
Authors: New J. Stewart , Fucile Christopher F. , Callahan Amanda R. , Burke Julia N. , Davis Randall S. , Duck Wayne L. , Rosenberg Alexander F. , Kearney John F. , King R. Glenn 
Published: October 2024

AbstractThe human antibody repertoire is broadly reactive with carbohydrate antigens represented in the universe of all living things, including both the host/self-as well as the commensal microflora-derived glycomes. Here we have used BCR receptor cloning and expression together with single-cell transcriptomics to analyze the B cell repertoire to the ubiquitous N-acetyl-D-glucosamine (GlcNAc) epitope in human cohorts and dissect the immune phylogeny of this predominant class of antibodies. We find that circulating anti-GlcNAc B cells exhibiting canonical BMem phenotypes emerge rapidly after birth and couple this observation with evidence for germinal center-dependent affinity maturation of carbohydrate-specific B cell receptorsin situduring early childhood. Direct analysis of individual B cell clonotypes reveals they exhibit strikingly distinct fine-specificity profiles for palettes of GlcNAc containing moieties. These results suggest that a generalized exposure to complex environmental glycans drives the steady state anti-glycan repertoire.
Multimodal learning of transcriptomes and text enables interactive single-cell RNA-seq data exploration with natural-language chats
Authors: Schaefer Moritz , Peneder Peter , Malzl Daniel , Peycheva Mihaela , Burton Jake , Hakobyan Anna , Sharma Varun , Krausgruber Thomas , Menche Jörg , Tomazou Eleni M. , Bock Christoph 
Published: October 2024

AbstractSingle-cell RNA-seq characterizes biological samples at unprecedented scale and detail, but data interpretation remains challenging. Here we introduce CellWhisperer, a multimodal machine learning model and software that connects transcriptomes and text for interactive single-cell RNA-seq data analysis. CellWhisperer enables the chat-based interrogation of transcriptome data in English language. To train our model, we created an AI-curated dataset with over a million pairs of RNA-seq profiles and matched textual annotations across a broad range of human biology, and we established a multimodal embedding of matched transcriptomes and text using contrastive learning. Our model enables free-text search and annotation of transcriptome datasets by cell types, states, and other properties in a zero-shot manner and without the need for reference datasets. Moreover, Cell-Whisperer answers questions about cells and genes in natural-language chats, using a biologically fluent large language model that we fine-tuned to analyze bulk and single-cell transcriptome data across various biological applications. We integrated CellWhisperer with the widely used CELLxGENE browser, allowing users to in-teractively explore RNA-seq data through an integrated graphical and chat interface. Our method demonstrates a new way of working with transcriptome data, leveraging the power of natural language for single-cell data analysis and establishing an important building block for future AI-based bioinformatics research assistants.
Mitochondria are absent from microglial processes performing surveillance, chemotaxis, and phagocytic engulfment
Authors: Pietramale Alicia N. , Bame Xhoela , Doty Megan E. , Hill Robert A. 
Published: October 2024

AbstractMicroglia continually surveil the brain allowing for rapid detection of tissue damage or infection. Microglial metabolism is linked to tissue homeostasis, yet how mitochondria are subcellularly partitioned in microglia and dynamically reorganize during surveillance, injury responses, and phagocytic engulfment in the intact brain are not known. Here, we performed intravital imaging of microglia mitochondria, revealing that microglial processes diverge, with some containing multiple mitochondria while others are completely void. Microglial processes that engage in minute-to-minute surveillance typically do not have mitochondria. Moreover, unlike process surveillance, mitochondrial motility does not change with animal anesthesia. Likewise, the processes that acutely chemoattract to a lesion site or initially engage with a neuron undergoing programmed cell death do not contain mitochondria. Rather, microglia mitochondria have a delayed arrival into the responding cell processes. Thus, there is subcellular heterogeneity of mitochondrial partitioning and asymmetry between mitochondrial localization and cell process motility or acute damage responses.