bluuebunny/crossref_metadata_2025 huggingface dataset:
Electrocardiography-based Artificial Intelligence Algorithms Aid in Prediction of Long-term Mortality After Kidney Transplantation
Authors: Pencovich Niv , Smith Byron H. , Attia Zachi I. , Jimenez Francisco Lopez , Bentall Andrew J. , Schinstock Carrie A. , Khamash Hasan A. , Jadlowiec Caroline C. , Jarmi Tambi , Mao Shennen A. , Park Walter D. , Diwan Tayyab S. , Friedman Paul A. , Stegall Mark D.
Published: April 2024

Background.

Predicting long-term mortality postkidney transplantation (KT) using baseline clinical data presents significant challenges. This study aims to evaluate the predictive power of artificial intelligence (AI)-enabled analysis of preoperative electrocardiograms (ECGs) in forecasting long-term mortality following KT.

Methods.

We analyzed preoperative ECGs from KT recipients at three Mayo Clinic sites (Minnesota, Florida, and Arizona) between January 1, 2006, and July 30, 2021. The study involved 6 validated AI algorithms, each trained to predict future development of atrial fibrillation, aortic stenosis, low ejection fraction, hypertrophic cardiomyopathy, amyloid heart disease, and biological age. These algorithms’ outputs based on a single preoperative ECG were correlated with patient mortality data.

Results.

Among 6504 KT recipients included in the study, 1764 (27.1%) died within a median follow-up of 5.7 y (interquartile range: 3.00–9.29 y). All AI-ECG algorithms were independently associated with long-term all-cause mortality (P < 0.001). Notably, few patients had a clinical cardiac diagnosis at the time of transplant, indicating that AI-ECG scores were predictive even in asymptomatic patients. When adjusted for multiple clinical factors such as recipient age, diabetes, and pretransplant dialysis, AI algorithms for atrial fibrillation and aortic stenosis remained independently associated with long-term mortality. These algorithms also improved the C-statistic for predicting overall (C = 0.74) and cardiac-related deaths (C = 0.751).

Conclusions.

The findings suggest that AI-enabled preoperative ECG analysis can be a valuable tool in predicting long-term mortality following KT and could aid in identifying patients who may benefit from enhanced cardiac monitoring because of increased risk.
Rehabilitation exercises for kidney transplant recipients in an organ transplant ward: a best practice implementation project
Authors: Liu Huan , Liu Jia , Chen Qirong , Zeng Le , Guo Jia , Zhu Xiao , Zhang Pengpeng , Chen Jiarui , Sun Mei , Huang Xiaoting , Ding Jinfeng , Liu Lifang
Published: April 2024

Introduction and objectives:

Kidney transplantation is an effective treatment for end-stage kidney disease. Kidney transplant recipients (KTRs) are prone to experiencing reduced physical function, depression, fatigue, and lack of exercise motivation due to their sedentary lifestyle before surgery. Exercise is an effective intervention for KTRs, but it has not been properly implemented in many practice settings. This project aimed to promote evidence-based exercises as part of KTRs’ rehabilitation to improve their health outcomes.

Methods:

This project was informed by the JBI Evidence Implementation Framework. The project was conducted in the organ transplant ward of a tertiary comprehensive hospital in Changsha, China. Based on a summary of best evidence, 12 audit criteria were developed for the baseline and follow-up audits involving 30 patients and 20 nursing staff. The JBI Practical Application of Clinical Evidence System (PACES) and Getting Research into Practice (GRiP) tool were used to identify barriers and facilitators and develop targeted strategies to improve issues.

Results:

Compared with the baseline audit, significant improvements were achieved in most of the criteria in the follow-up audit, with 9 of the 12 criteria reaching 100% compliance. Notably, the 6-minute walk distance test results were significantly higher, while the Self-Rating Depression Scale and Self-Rating Anxiety Scale scores were significantly lower (p < 0.05).

Conclusions:

This project demonstrates that evidence-based practice can improve the clinical practice of rehabilitation exercises for KTRs. The GRiP strategies proved to be extremely useful, notably, the formulation of a standardized rehabilitation exercise protocol, training, and enhancement of the exercising environment. Head nurses’ leadership and decision-making also played an important role in the success of this project.

Spanish abstract:

http://links.lww.com/IJEBH/A180
Phototactic preference and its genetic basis in the planulae of the colonial Hydrozoan Hydractinia symbiolongicarpus
Authors: Birch Sydney , McGee Lindy , Provencher Curtis , DeMio Christine , Plachetzki David
Published: April 2024

Background

Marine organisms with sessile adults commonly possess motile larval stages that make settlement decisions based on integrating environmental sensory cues. Phototaxis, the movement toward or away from light, is a common behavioral characteristic of aquatic and marine metazoan larvae, and of algae, protists, and fungi. In cnidarians, behavioral genomic investigations of motile planulae larvae have been conducted in anthozoans (corals and sea anemones) and scyphozoans (true jellyfish), but such studies are presently lacking in hydrozoans. Here, we examined the behavioral genomics of phototaxis in planulae of the hydrozoanHydractinia symbiolongicarpus.

Results

A behavioral phototaxis study of day 3 planulae indicated preferential phototaxis to green (523 nm) and blue (470 nm) wavelengths of light, but not red (625 nm) wavelengths. A developmental transcriptome study where planula larvae were collected from four developmental time points for RNA-seq revealed that many genes critical to the physiology and development of ciliary photosensory systems are dynamically expressed in planula development and correspond to the expression of phototactic behavior. Microscopical investigations using immunohistochemistry andin situhybridization demonstrated that several transcripts with predicted function in photoreceptors, including cnidops class opsin, CNG ion channel, and CRX-like transcription factor, localize to ciliated bipolar sensory neurons of the aboral sensory neural plexus, which is associated with the direction of phototaxis and the site of settlement.

Conclusions

The phototactic preference displayed by planulae is consistent with the shallow sandy marine habitats they experience in nature. Our genomic investigations add further evidence of similarities between cnidops-mediated photoreceptors of hydrozoans and other cnidarians and ciliary photoreceptors as found in the eyes of humans and other bilaterians, suggesting aspects of their shared evolutionary history.
Mu Suppression During Action Observation Only in the Lower, not in the Higher, Frequency Subband
Authors: Badakul Ayşe Nur , Soyman Efe
Published: April 2024

Mu suppression – desynchronization of neural oscillations in central EEG electrodes during action execution and observation – has been widely accepted as a marker for neural mirroring. It has been conventionally and predominantly quantified in the 8-13 Hz range, corresponding to the alpha frequency band, although few studies reported differences in lower and higher subbands that together constitute the mu frequency band. In the present study, we adopted a data-driven approach to examine the spectral and temporal dynamics of mu suppression when participants watched videos depicting hand and face actions and artificial pattern movements. Our analyses in central EEG electrodes revealed that neural oscillations were significantly suppressed during action observation only in the lower (8-10.5 Hz), not in the higher (10.5-13 Hz), subband. No such subband differentiation was observed for the alpha oscillations in the occipital electrodes. In addition, in the lower subband, significantly stronger suppressions were selective for hand actions in the central EEG electrodes placed over the hand region of the sensorimotor cortices and for facial actions in the frontotemporal electrodes placed over the face region of the sensorimotor cortices. In the higher subband, such stimulus selectivity was only observed for facial actions in the frontotemporal electrodes. Furthermore, the neural oscillations in the lower, but not the higher, subband followed the precise temporal patterning of biological motion in the videos. These results indicate that neural oscillations in the lower subband show the characteristics of neural mirroring processes, whereas those in the higher subband might reflect other mechanisms.
triangulaR:an R package for identifying AIMs and building triangle plots using SNP data from hybrid zones
Authors: Wiens Ben J. , Colella Jocelyn P.
Published: April 2024

Hybridization provides a window into the speciation process and reshuffles parental alleles to produce novel recombinant genotypes. The presence or absence of specific hybrid classes across a hybrid zone can provide support for various modes of reproductive isolation. Early generation hybrid classes can be distinguished by their combination of hybrid index and interclass heterozygosity, which can be estimated with molecular data. Hybrid index and interclass heterozygosity are routinely calculated for studies of hybrid zones, but available resources for next-generation sequencing datasets are computationally demanding and tools for visualizing those metrics as a triangle plot are lacking. Here, we provide a resource for identifying ancestry- informative markers (AIMs) from SNP datasets, calculating hybrid index and interclass heterozygosity, and visualizing the relationship as a triangle plot. Our methods are implemented in the R packagetriangulaR. We validate our methods by simulating genetic data for a hybrid zone between parental groups at low, medium, and high levels of divergence. We find that accurate and precise estimates of hybrid index and interclass heterozygosity can be obtained with sample sizes as low as five individuals per parental group. We explore various allele frequency difference thresholds for AIM identification, and how this threshold influences the accuracy and precision of hybrid index and interclass heterozygosity estimates. We contextualize interpretation of triangle plots by describing the theoretical expectations for covariance of hybrid index and interclass heterozygosity under Hardy-Weinberg Equilibrium and provide recommendations for best practices for identifying AIMs and building triangle plots.
The critical role of isomiRs in accurate differential expression analysis of miRNA-seq data
Authors: Schmauch Eloi , Attia Yassine , Laitinen Pia , Turunen Tiia A. , Bartos Piia , Vaananen Mari-Anna , Malm Tarja , Tavi Pasi , Kellis Manolis , Kaikkonen Minna U , Linna-Kuosmanen Suvi
Published: April 2024

MicroRNAs (miRNAs) are crucial for the regulation of gene expression and are promising biomarkers and therapeutic targets. miRNA isoforms (isomiRs) differ in their start/end offsets, which can impact the target gene selection and non-canonical function of the miRNA species. In addition, isomiRs frequently differ in their expression patterns from their parent miRNAs, yet their roles and tissue-specific responses are currently understudied, leading to their typical omission in miRNA research. Here, we evaluate the expression differences of isomiRs across conditions and their impact on standard miRNA-seq quantification results. We analyze 28 public miRNA-seq datasets, showing significant expression pattern differences between the isomiRs and their corresponding reference miRNAs, leading to misinterpretation of differential expression signals for both. As a case study, we generate a new dataset assessing isomiR abundance under hypoxia in human endothelial cells between the nuclear and cytosolic compartments. The results suggest that isomiRs are dramatically altered in their nuclear localization in response to hypoxia, indicating a potential non-canonical effect of the species, which would be missed without isomiR-aware analysis. Our results call for a comprehensive re-evaluation of the miRNA-seq analysis practices.
Target Distance from the Visual Field and Increased Age Affect Visual Search Efficiency: Behavioral and Modeling Evidence
Authors: Akbari Fatemeh , Asivandzadehchaharmahali Samaneh , Tanha Alireza , Narmashiri Abdolvahed
Published: April 2024

Abstract

Previous research has demonstrated that visual search is influenced by environmental factors, but the effects of specific variables, such as target distance from the visual field center and age, are not well understood. To address this issue, we aim to investigate their impact on visual search task. Participants engaged in target-present and target-absent trials, revealing distinct patterns in search times. Behavioral data and drift-diffusion modeling (DDM) showed that increasing the target’s distance from the center of the visual field significantly reduces search efficiency. Additionally, age negatively impacts search performance, with older individuals exhibiting reduced efficiency. This comprehensive examination contributes to understanding cognitive mechanisms in visual processing. These findings highlight the importance of considering spatial and age-related factors in visual search tasks.
Balancing the risks of mating: biogeographic evidence of cleistogamy as a bet hedging strategy
Authors: Weissman Maya , Zhang Dafeng , Kartzinel Rebecca , Weinreich Daniel
Published: April 2024

Cleistogamy is a mating system in which plants produce some proportion of closed, autonomously self-pollinating flowers. Cleistogamous flowers differ from chasmogamous flowers, which are open flowers capable of outcrossing. Both dimorphic cleistogamy (cleistogamous and chasmogamous flowers produced on the same plant) and complete cleistogamy occur. Cleistogamy has been hypothesized to be a bet hedging strategy for reducing risk in the face of unpredictable pollinator availability. However, conflicting results across species and challenges connecting theory to data have prevented researchers from proving that cleistogamy is bet hedging. To test the bet hedging hypothesis, we investigated the distribution of over 400 cleistogamous species through biogeographical analyses. We find that cleistogamy is more prevalent in cooler, more variable environments. Additionally, we find that among cleistogamous species, complete cleistogamy is more likely to occur in warmer, more stable, tropical and subtropical environments. We hypothesize that the difference in distribution between complete and dimorphic cleistogamy may be driven by the opposing forces of selection to increase cleistogamy proportion and extinction risk, which we test using a heuristic Markov transition model. We conclude that the distribution of cleistogamy suggests that the strategy has evolved in variable environments, consistent with expectations for bet hedging.
Integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits
Authors: Okamoto Jeffrey , Yin Xianyong , Ryan Brady , Chiou Joshua , Luca Francesca , Pique-Regi Roger , Im Hae Kyung , Morrison Jean , Burant Charles , Fauman Eric B. , Laakso Markku , Boehnke Michael , Wen Xiaoquan
Published: April 2024

We present multi-integration of transcriptome-wide association studies and colocalization (Multi-INTACT), an algorithm that models multiple gene products (e.g. encoded RNA transcript and protein levels) to implicate causal genes and relevant gene products. In simulations, Multi-INTACT achieves higher power than existing methods, maintains calibrated false discovery rates, and detects the true causal gene product(s). We apply Multi-INTACT to GWAS on 1,408 metabolites, integrating the GTEx expression and UK Biobank protein QTL datasets. Multi-INTACT infers 52% to 109% more metabolite causal genes than protein-alone or expression-alone analyses and indicates both gene products are relevant for most gene nominations.
TemBERTure: Advancing protein thermostability prediction with Deep Learning and attention mechanisms
Authors: Rodella Chiara , Lazaridi Symela , Lemmin Thomas
Published: April 2024

Understanding protein thermostability is essential for various biotechnological and biological applications. However, traditional experimental methods for assessing this property are time-consuming, expensive, and error-prone. Recently, the application of Deep Learning techniques from Natural Language Processing (NLP) was extended to the field of biology, with an emphasis on protein modeling. From a linguistic perspective, the primary sequence of proteins can be viewed as a string of amino acids that follow a physicochemical grammar.

This study explores the potential of Deep Learning models trained on protein sequences to predict protein thermostability which provide improvements with respect to current approaches. We implemented TemBERTure, a Deep Learning framework to classify the thermal class (non-thermophilic or thermophilic) and predict and melting temperature of a protein, based on its primary sequence. Our findings highlight the critical role that data diversity plays on training robust models. Models trained on datasets with a wider range of sequences from various organisms exhibited superior performance compared to those with limited diversity. This emphasizes the need for a comprehensive data curation strategy that ensures a balanced representation of diverse species in the training data, to avoid the risk that the model focuses on recognizing the evolutionary lineage of the sequence rather than the intrinsic thermostability features. In order to gain more nuanced insights into protein thermostability, we propose leveraging attention scores within Deep Learning models to gain more nuanced insights into protein thermostability. We show that analyzing these scores alongside the 3D protein structure could offer a better understanding of the complex interplay between amino acid properties, their positioning, and the surrounding microenvironment, all crucial factors influencing protein thermostability.

This work sheds light on the limitations of current protein thermostability prediction methods and introduces new avenues for exploration. By emphasizing data diversity and utilizing refined attention scores, future research can pave the way for more accurate and informative methods for predicting protein thermostability.

Availability and Implementation

TemBERTure model and the data are available athttps://github.com/ibmm-unibe-ch/TemBERTure
Decoding Arc Transcription: A Live-Cell Study of Stimulation Patterns and Transcriptional Output
Authors: Kim Dong Wook , Moon Hyungseok C. , Lee Byung Hun , Park Hye Yoon
Published: April 2024

Activity-regulated cytoskeleton-associated protein (Arc) plays a crucial role in synaptic plasticity, a process integral to learning and memory. Arc transcription is induced within a few minutes of stimulation, making it a useful marker for neuronal activity. However, the specifics of the neuronal activity that triggers Arc transcription remain unknown because it has not been possible to observe mRNA transcription in live cells in real time. Using a genetically encoded RNA indicator (GERI) mouse model that expresses endogenous Arc mRNA tagged with multiple GFPs, we investigated Arc transcriptional activity in response to various electrical stimulation patterns. In dissociated hippocampal neurons, we found that the pattern of stimulation significantly affects Arc transcription. Specifically, a 10 Hz burst stimulation induced the highest rate of Arc transcription. Concurrently, the amplitudes of nuclear calcium transients also reached their peak with 10 Hz stimulation, indicating a correlation between calcium concentration and transcription. However, our dual-color single-cell imaging revealed that there were no significant differences in calcium amplitudes between Arc-positive and Arc-negative neurons upon 10 Hz burst stimulation, suggesting the involvement of other factors in the induction of Arc transcription. Our live-cell RNA imaging provides a deeper insight into the complex regulation of transcription by activity patterns and calcium signaling pathways.
Comparing cell penetration of biotherapeutics across human cell lines
Authors: Batistatou Nefeli , Kritzer Joshua A.
Published: April 2024

A major obstacle in biotherapeutics development is maximizing cell penetration. Ideally, assays would allow for optimization of cell penetration in the cell type of interest early in the drug development process. However, few assays exist to compare cell penetration across different cell types, independent of drug function. In this work, we applied the chloroalkane penetration assay (CAPA) in seven mammalian cell lines as well as primary cells. Careful controls were used to ensure data could be compared across cell lines. We compared the penetration of several peptides and drug-like oligonucleotides and saw significant differences among the cell lines. To help explain these differences, we quantified the relative activities of endocytosis pathways in these cell lines and correlated them with the penetration data. Based on these results, we knocked down clathrin in a cell line with an efficient permeability profile and observed reduced penetration of peptides, but not oligonucleotides. Finally, we used small-molecule endosomal escape enhancers and observed enhancement of cell penetration of some oligonucleotides, but only in some of the cell lines tested. CAPA data provide valuable points of comparison among different cell lines, including primary cells, for evaluating the cell penetration of various classes of peptides and oligonucleotides.

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moPepGen: Rapid and Comprehensive Identification of Non-canonical Peptides
Authors: Zhu Chenghao , Liu Lydia Y. , Ha Annie , Yamaguchi Takafumi N. , Zhu Helen , Hugh-White Rupert , Livingstone Julie , Patel Yash , Kislinger Thomas , Boutros Paul C.
Published: April 2024

Gene expression is a multi-step transformation of biological information from its storage form (DNA) into functional forms (protein and some RNAs). Regulatory activities at each step of this transformation multiply a single gene into a myriad of proteoforms. Proteogenomics is the study of how genomic and transcriptomic variation creates this proteomic diversity, and is limited by the challenges of modeling the complexities of gene-expression. We therefore created moPepGen, a graph-based algorithm that comprehensively generates non-canonical peptides in linear time. moPepGen works with multiple technologies, in multiple species and on all types of genetic and transcriptomic data. In human cancer proteomes, it enumerates previously unobservable noncanonical peptides arising from germline and somatic genomic variants, noncoding open reading frames, RNA fusions and RNA circularization. By enabling efficient detection and quantitation of previously hidden proteins in both existing and new proteomic data, moPepGen facilitates all proteogenomics applications. It is available at:https://github.com/uclahs-cds/package-moPepGen.
Decellularization of Rat Gracilis Muscle Flap as a Potential Scaffold For Skeletal Muscle Composite Allotransplantation
Authors: Dong Chenhui , Sarcon Aida K. , Zhao Chunfeng
Published: April 2024

There are limited biomaterials for skeletal muscle regeneration. This study aimed to apply a decellularization protocol in a muscle flap model and investigate its patency. Twenty-six gracilis-muscle (GM) flaps were harvested from 13 rats. GMs were divided into groups of either 1) normal (control), 2) perfusion with 1% sodium dodecyl sulfate or SDS for 48h, followed by Triton X-100 or TX100, or lastly, 3) perfusion with SDS for 72h, followed by TX100. The morphology, microcirculatory network patency, and residual DNA content (DNAC) were evaluated. Decellularized muscle (DM) for 72h was more translucent than DM-48h. Despite longer decellularization, the DM-72h microcirculatory network maintained its integrity, except when the dye infiltrated from the muscle edges. Compared to normal, all DM had significantly lower DNAC (normal of 1.44 μg/mgvs. DM-48h of 0.37 μg/mgvs. DM-72h of 0.089 μg/mg; P < 0.001). The DNAC of the DM-72h group was significantly lower than DM-48h (P< 0.001). We report successful GM flap decellularization. Longer decellularization led to lower DNAC, which did not compromise circulation. Our protocol may be applicable as a free-flap scaffold model for transplantation in the future.

Statement of clinical significance

The impact of our work involves a reproducible skeletal muscle decellularization protocol to later apply in translational research.
IL-10 dependent adaptation allows macrophages to adjust inflammatory responses to TLR4 stimulation history
Authors: Bongartz H. , Bradfield C. , Gross J. , Fraser I.D.C. , Nita-Lazar A. , Meier-Schellersheim M.
Published: April 2024

During an infection, innate immune cells must adjust nature and strength of their responses to changing pathogen abundances. To determine how stimulation of the pathogen sensing TLR4 shapes subsequent macrophage responses, we systematically varied priming and restimulation concentrations of its ligand KLA. We find that different priming strengths have very distinct effects at multiple stages of the signaling response, including receptor internalization, MAPK activation, cytokine and chemokine production, and nuclear translocation and chromatin association of NFκB and IκB members. In particular, restimulation-induced TNF-α production required KLA doses equal to or greater than those used for prior exposure, indicating that macrophages can detect and adaptively respond to changing TLR4 stimuli. Interestingly, while such adaptation was dependent on the anti-inflammatory cytokine IL-10, exogenous concentrations of IL-10 corresponding to those secreted after strong priming did not exert suppressive effects on TNF-α without such prior priming, confirming the critical role of TLR4 stimulation history.
Linkage equilibrium between rare mutations
Authors: Lyulina Anastasia S. , Liu Zhiru , Good Benjamin H.
Published: April 2024

Recombination breaks down genetic linkage by reshuffling existing variants onto new genetic backgrounds. These dynamics are traditionally quantified by examining the correlations between alleles, and how they decay as a function of the recombination rate. However, the magnitudes of these correlations are strongly influenced by other evolutionary forces like natural selection and genetic drift, making it difficult to tease out the effects of recombination. Here we introduce a theoretical framework for analyzing an alternative family of statistics that measure the homoplasy produced by recombination. We derive analytical expressions that predict how these statistics depend on the rates of recombination and recurrent mutation, the strength of negative selection and genetic drift, and the present-day frequencies of the mutant alleles. We find that the degree of homoplasy can strongly depend on this frequency scale, which reflects the underlying timescales over which these mutations occurred. We show how these scaling properties can be used to isolate the effects of recombination, and discuss their implications for the rates of horizontal gene transfer in bacteria.
Labels as a Feature: Network Homophily for Systematically Discovering human GPCR Drug-Target Interactions
Authors: Hansson Frederik G. , Madsen Niklas Gesmar , Hansen Lea G. , Jakočiūnas Tadas , Lengger Bettina , Keasling Jay D. , Jensen Michael K. , Acevedo-Rocha Carlos G. , Jensen Emil D.
Published: April 2024

Machine learning (ML) has revolutionized drug discovery by enabling the exploration of vast, uncharted chemical spaces essential for discovering novel patentable drugs. Despite the critical role of human G protein-coupled receptors (hGPCRs) in FDA-approved drugs, exhaustive in-distribution drug-target interaction (DTI) testing across all pairs of hGPCRs and known drugs is rare due to significant economic and technical challenges. This often leaves off-target effects unexplored, which poses a considerable risk to drug safety. In contrast to the traditional focus on out-of-distribution (OOD) exploration (drug discovery), we introduce a neighborhood-to-prediction model termed Chemical Space Neural Networks (CSNN) that leverages network homophily and training-free graph neural networks (GNNs) with Labels as Features (LaF). We show that CSNN’s ability to make accurate predictions strongly correlates with network homophily. Thus, LaFs strongly increase a ML model’s capacity to enhance in-distribution prediction accuracy, which we show by integrating labeled data during inference. We validate these advancements in a high-throughput yeast biosensing system (3773 DTIs, 539 compounds, 7 hGPCRs) to discover novel DTIs for FDA-approved drugs and to expand the general understanding of how to build reliable predictors to guide experimental verification.
TET2 regulates early and late transitions in exhausted CD8+T-cell differentiation and limits CAR T-cell function
Authors: Dimitri Alexander J. , Baxter Amy E. , Chen Gregory M. , Hopkins Caitlin R. , Rouin Geoffrey T. , Huang Hua , Kong Weimin , Holliday Christopher H. , Wiebking Volker , Bartoszek Robert , Drury Sydney , Dalton Katherine , Koucky Owen M. , Chen Zeyu , Giles Josephine R. , Jung In-Young , O’Connor Roddy , Collins Sierra , Everett John K. , Amses Kevin , Sherrill-Mix Scott , Chandra Aditi , Goldman Naomi , Vahedi Golnaz , Jadlowsky Julie K. , Young Regina M. , Melenhorst Jan Joseph , Maude Shannon L. , Levine Bruce L. , Frey Noelle V. , Berger Shelley L. , Grupp Stephan A. , Porter David L. , Herbst Friederike , Porteus Matthew H. , Bushman Frederic D. , Weber Evan W. , Wherry E. John , Jordan Martha S. , Fraietta Joseph A.
Published: April 2024

CD8+T-cell exhaustion hampers disease control in cancer and chronic infections and limits efficacy of T-cell−based therapies, such as CAR T-cells. Epigenetic reprogramming of CAR T-cells by targeting TET2, a methylcytosine dioxygenase that mediates active DNA demethylation, has shown therapeutic potential; however, the role of TET2 in exhausted T-cell (TEX) development is unclear. In CAR T-cell exhaustion models and chronic LCMV infection, TET2 drove the conversion from stem cell-like, self-renewing TEXprogenitors towards terminally differentiated and effector (TEFF)-like TEX. In mouse T-cells,TET2-deficient terminally differentiated TEXretained aspects of TEXprogenitor biology, alongside decreased expression of the transcription factor TOX, suggesting that TET2 potentiates terminal exhaustion. TET2 also enforced a TEFF-like terminally differentiated CD8+T-cell state in the early bifurcation between TEFFand TEX, indicating a broad role for TET2 in mediating the acquisition of an effector biology program that could be exploited therapeutically. Finally, we developed a clinically actionable strategy forTET2-targeted CAR T-cells, using CRISPR/Cas9 editing and site-specific adeno-associated virus transduction to simultaneously knock-in a CAR at theTRAClocus and a functional safety switch withinTET2. Disruption ofTET2with this safety switch in CAR T-cells restrained terminal TEXdifferentiationin vitroand enhanced anti-tumor responsesin vivo. Thus, TET2 regulates pivotal fate transitions in TEXdifferentiation and can be targeted with a safety mechanism in CAR T-cells for improved tumor control and risk mitigation.

One Sentence Summary

Modulation of exhausted CD8+T-cell differentiation by targeting TET2 improves therapeutic potential of CAR T-cells in cancer.
Laminin Receptor Characterization in Acute Myeloid Leukemia: Integrin α7β1 Defines non-Leukemic Stem Cells with Migratory Potential
Authors: Görsch Elsa , Arnone Marlon , Klimiankou Maksim , Weller Jan , Rudat Saskia , Klein Gerd , Lengerke Claudia
Published: April 2024

Interactions with the bone marrow (BM) niche are crucial for promoting self-renewal and survival of acute myeloid leukemia (AML) cells. Consequently, AML cells express a variety of surface receptors to engage with BM niche cells and extracellular matrix proteins, including laminins. Despite the association of laminin receptor expression with stemness in healthy hematopoiesis, the role of laminin receptors in AML remains poorly understood. In this study, we present a comprehensive examination of the laminin receptors integrin α3β1, α6β1, α7β1 and basal cell adhesion molecule (BCAM) in AML. We demonstrate that high mRNA expression of all four laminin receptors correlates with poor overall survival. Notably, integrin α6 and α7 display the highest cell surface presentation among the examined laminin receptors and are higher expressed on AML cells compared to healthy controls. Moreover, our results indicate that integrin α7 expression allows to distinguish between leukemic stem cells (LSC) and non-LSC populations. Specifically, integrin α7 appears to mark non-LSC with enhanced migratory potential. Together, our results confirm the association of high laminin receptor expression with poor prognosis and establish integrin α7 as marker of high migratory non-LSC.

Abstract Figure
Premeiotic 24-nt phasiRNAs are present in theZeagenus and unique in biogenesis mechanism and molecular function
Authors: Zhan Junpeng , Bélanger Sébastien , Lewis Scott , Teng Chong , McGregor Madison , Beric Aleksandra , Schon Michael A. , Nodine Michael D. , Meyers Blake C.
Published: April 2024

Reproductive phasiRNAs are broadly present in angiosperms and play crucial roles in sustaining male fertility. While the premeiotic 21-nt phasiRNAs and meiotic 24-nt phasiRNA pathways have been extensively studied in maize (Zea mays) and rice (Oryza sativa), a third putative category of reproductive phasiRNAs–named premeiotic 24-nt phasiRNAs–have recently been reported in barley (Hordeum vulgare) and wheat (Triticum aestivum). To determine whether premeiotic 24-nt phasiRNAs are also present in maize and related species and begin to characterize their biogenesis and function, we performed a comparative transcriptome and degradome analysis of premeiotic and meiotic anthers from five maize inbred lines and three teosinte species/subspecies. Our data indicate that a substantial subset of the 24-nt phasiRNA loci in maize and teosinte are already highly expressed at premeiotic phase. The premeiotic 24-nt phasiRNAs are similar to meiotic 24-nt phasiRNAs in genomic origin and dependence on DCL5 for biogenesis, however, premeiotic 24-nt phasiRNAs are unique in that they are likely (i) not triggered by microRNAs, (ii) not loaded by AGO18 proteins, and (iii) not capable of mediatingcis-cleavage. In addition, we also observed a group of premeiotic 24-nt phasiRNAs in rice using previously published data.

Together, our results indicate that the premeiotic 24-nt phasiRNAs constitute a unique class of reproductive phasiRNAs and are present more broadly in the grass family (Poaceae) than previously known.

SIGNIFICANCE

We previously reported two classes of reproductive phasiRNAs in maize, the premeiotic 21-nt phasiRNAs and the meiotic 24-nt phasiRNAs. Here we report a third class of reproductive phasiRNAs – premeiotic 24-nt phasiRNAs – that are present in theZeagenus, including all five maize inbred lines and three teosinte species/subspecies that we examined, plus rice.

We show that in theZeagenus the premeiotic 24-nt phasiRNAs are distinct from the meiotic 24-nt phasiRNAs in triggering mechanism, effector protein, and molecular function.
fMROI: a simple and adaptable toolbox for easy region-of-interest creation
Authors: Peres André , Valério Daniela , Vaz Igor , Mahdiani Morteza , Walbrin Jon , Almeida Jorge
Published: April 2024

This study introduces fMROI, an open-source software designed for creating regions-of-interest (ROIs) and visualizing magnetic resonance imaging data. fMROI offers a user-friendly graphical interface that simplifies the creation of complex ROIs. It is compatible with various operating systems and enables the integration of user-specified algorithms. Comparative analysis against popular neuroimaging software demonstrates the feasibility, applicability, and ease of use of fMROI. Notably, fMROI’s interactive graphical interface with a real-time viewer allows users to identify inconsistencies and design more accurate ROIs, saving significant time by avoiding errors before storing ROIs as NIfTI files. Additionally, fMROI supports automation through command-line accessibility, making it ideal for large-scale analyses. As an open-source platform, fMROI provides a valuable resource for researchers in the neuroimaging community, facilitating efficient ROI creation and streamlining neuroimage analysis.
Relationships between balance performance and connectivity of motor cortex with primary somatosensory cortex and cerebellum in middle aged and older adults
Authors: Sansare Ashwini , Magalhaes Thamires N.C. , Bernard Jessica A.
Published: April 2024

Connectivity of somatosensory cortex (S1) and cerebellum with the motor cortex (M1) is critical for balance control. While both S1-M1 and cerebellar-M1 connections are affected with aging, the implications of altered connectivity for balance control are not known. We investigated the relationship between S1-M1 and cerebellar-M1 connectivity and standing balance in middle-aged and older adults. Our secondary objective was to investigate how cognition affected the relationship between connectivity and balance. Our results show that greater S1-M1 and cerebellar-M1 connectivity was related to greater postural sway during standing. This may be indicative of an increase in functional recruitment of additional brain networks to maintain upright balance despite differences in network connectivity. Also, cognition moderated the relationship between S1-M1 connectivity and balance, such that those with lower cognition had a stronger relationship between connectivity and balance performance. It may be that individuals with poor cognition need increased recruitment of brain regions (compensation for cognitive declines) and in turn, higher wiring costs, which would be associated with increased functional connectivity.
Neurofilament accumulation disrupts autophagy in giant axonal neuropathy
Authors: Paumier Jean-Michel , Zewe James , Pergande Melissa R , Venkatesan Meghana , Israeli Eitan , Panja Chiranjit , Snider Natasha , Savas Jeffrey , Opal Puneet
Published: April 2024

Neurofilament accumulation is a marker of several neurodegenerative diseases, but it is the primary pathology in Giant Axonal Neuropathy (GAN). This childhood onset autosomal recessive disease is caused by loss-of-function mutations in gigaxonin, the E3 adaptor protein that is essential for neurofilament degradation. Using a combination of genetic and RNA interference (RNAi) approaches, we found that dorsal root ganglia from mice lacking gigaxonin have impaired autophagy and lysosomal degradation through two mechanisms. First, neurofilament accumulations interfere with the distribution of autophagic organelles, impairing their maturation and fusion with lysosomes. Second, the accumulations sequester the chaperone 14-3-3, a protein responsible for the localization of the transcription factor EB (TFEB), a key regulator of autophagy. This dual disruption of autophagy likely contributes to the pathogenesis of other neurodegenerative diseases with neurofilament accumulations.
Dendrite injury, but not axon injury, triggers neuroprotection in Drosophila models of neurodegenerative disease
Authors: Prange Sydney E. , Bhakta Isha N. , Sysoeva Daria , Jean Grace E. , Madisetti Anjali , Duong Ly U. , Hwu Patrick T. , Melton Jaela G. , Le Hieu H. N. , Thompson-Peer Katherine L.
Published: April 2024

Dendrite defects and loss are early cellular alterations observed across neurodegenerative diseases that play a role in early disease pathogenesis. Dendrite degeneration can be modeled by expressing pathogenic polyglutamine disease transgenes inDrosophilaneuronsin vivo. Here, we show that we can protect against dendrite loss in neurons modeling neurodegenerative polyglutamine diseases through injury to a single primary dendrite branch. We find that this neuroprotection is specific to injury-induced activation of dendrite regeneration: neither injury to the axon nor injury just to surrounding tissues induces this response. We show that the mechanism of this regenerative response is stabilization of the actin (but not microtubule) cytoskeleton. We also demonstrate that this regenerative response may extend to other neurodegenerative diseases. Together, we provide evidence that activating dendrite regeneration pathways has the potential to slow–or even reverse–dendrite loss in neurodegenerative disease.
Genomic evolution and rearrangement of CTX-Φ prophage elements in Vibrio cholerae during the 2018-2022 cholera outbreaks in The Democratic Republic of Congo
Authors: Irenge Leonid M. , Ambroise Jérôme , Bearzatto Bertrand , Durant Jean-François , Wimba Louisette K. , Gala Jean-Luc
Published: April 2024

Between 2018 and 2022, we conducted whole-genome sequencing and phylogenomic analysis on 173Vibrio choleraebacteria (172V. choleraeO1 and 1V. choleraenon-O1/non-O139 isolates) from cholera patients across four provinces in the Democratic Republic of Congo (North-Kivu, South-Kivu, Tanganyika, and Kasai Oriental). AllV. choleraeO1 isolates were classified into the AFR10d and AFR10e sublineages of AFR10 lineage, originating from the third wave of the seventh El Tor cholera pandemic (7PET). Compared to the strains analysed between 2014 and 2017, we observed only limited genetic changes in the core genome of both sublineages. However, AFR10e expanded across the four provinces, whereas AFR10d appeared to become extinct by the end of 2020. TheV. choleraeisolates from 2022 exhibited significant rearrangement in the CTX prophage and associated phage satellites. Notably, this included the tandem repeat of a novel environmental satellite phage RS1 downstream thectxB toxin gene of the CTX-Φ-3 prophage on the large chromosome, and two tandemly arrayed copies of the pre-CTX-Φ prophage precursor on the small chromosome. In conclusion, while the core genome ofV. choleraeO1 AFR10d and AFR10e sublineages showed minimal changes, significant alterations in the content and organisation of elements associated with the CTX-Φ and pre-CTX prophages were identified in AFR10eV. choleraeO1 isolated in 2022.
A Deep Learning Approach for Automated Extraction of Functional Status and New York Heart Association Class for Heart Failure Patients During Clinical Encounters
Authors: Adejumo Philip , Thangaraj Phyllis , Dhingra Lovedeep Singh , Aminorroaya Arya , Zhou Xinyu , Brandt Cynthia , Xu Hua , Krumholz Harlan M , Khera Rohan
Published: April 2024

Introduction

Serial functional status assessments are critical to heart failure (HF) management but are often described narratively in documentation, limiting their use in quality improvement or patient selection for clinical trials. We developed and validated a deep learning-based natural language processing (NLP) strategy to extract functional status assessments from unstructured clinical notes.

Methods

We identified 26,577 HF patients across outpatient services at Yale New Haven Hospital (YNHH), Greenwich Hospital (GH), and Northeast Medical Group (NMG) (mean age 76.1 years; 52.0% women). We used expert annotated notes from YNHH for model development/internal testing and from GH and NMG for external validation. The primary outcomes were NLP models to detect (a) explicit New York Heart Association (NYHA) classification, (b) HF symptoms during activity or rest, and (c) functional status assessment frequency.

Results

Among 3,000 expert-annotated notes, 13.6% mentioned NYHA class, and 26.5% described HF symptoms. The model to detect NYHA classes achieved a class-weighted AUROC of 0.99 (95% CI: 0.98-1.00) at YNHH, 0.98 (0.96-1.00) at NMG, and 0.98 (0.92-1.00) at GH. The activity-related HF symptom model achieved an AUROC of 0.94 (0.89-0.98) at YNHH, 0.94 (0.91-0.97) at NMG, and 0.95 (0.92-0.99) at GH. Deploying the NYHA model among 166,655 unannotated notes from YNHH identified 21,528 (12.9%) with NYHA mentions and 17,642 encounters (10.5%) classifiable into functional status groups based on activity-related symptoms.

Conclusions

We developed and validated an NLP approach to extract NYHA classification and activity-related HF symptoms from clinical notes, enhancing the ability to track optimal care and identify trial-eligible patients.
Comparative effectiveness of non-pharmacological interventions for primary dysmenorrhea: A protocol for a systematic review and network meta-analysis
Authors: Bao Qiong-Nan , Yao Jin , Li Ya-Qin , Zhang Xin-Yue , Chen Zheng-Hong , Xia Man-Ze , Zhong Wan-Qi , Wu Ke-Xin , Yin Zi-Han , Liang Fan-Rong
Published: April 2024

Introduction

Primary dysmenorrhea (PD) is the most common gynecological condition among young women. Although several non-pharmacological interventions have proven effective in relieving pain in patients with PD, the optimal treatment remains unknown. This systematic review and network meta-analysis (NMA) will aim to compare and rank the analgesic effects of different non-drug interventions for PD.

Methods and analysis

Randomized controlled trials of non-pharmacological interventions for PD will be identified via a search of the PubMed, Cochrane Library, Web of Science, and Embase databases until May 2024. The primary outcome will be change in pain intensity among patients with PD, while the secondary outcomes include health-related quality of life and symptoms of depression and anxiety. Two independent reviewers will perform document screening, study selection, and data extraction. The methodological quality of the included studies will be assessed using the Cochrane Risk of Bias tool (V. 2). The RevMan, Stata, and Aggregate Data Drug Information System software will be used to perform a pairwise meta-analysis and Bayesian NMA in a random-effects model. The certainty of the evidence will be rated using the Grading of Recommendations, Assessment, Development, and Evaluation System.

Ethics and dissemination

Ethical approval will not be required for this study because all data will be obtained from published research. The findings will be published in a peer-reviewed journal.

STRENGTHS AND LIMITATIONS OF THIS STUDY

This will be the first study to comprehensively compare the efficacy of non-pharmacological interventions for primary dysmenorrhea using network meta-analysis.

The study will assess both short- and long-term efficacies of various non-pharmacological interventions in mitigating pain intensity among patients with primary dysmenorrhea.

This systematic review will be conducted in compliance with the Cochrane Handbook guidelines, which will ensure methodological rigor.

Only trials from English databases will be included, which may lead to omission of eligible studies in other languages.

The efficacy of different regimens of the same non-pharmacological intervention will not be investigated in this study.
Multiple molecular links between the circadian clock and memory centers in honey bees
Authors: Roy Tiyasa , Jain Rikesh , Brockmann Axel
Published: April 2024

Time and memory are intimately linked: the capability to learn and recall varies over the day and humans and many animals can associate important events with the time of day. However, how the circadian clock and memory centers are connected is not well understood. We time-trained honey bee foragers and used RNA-sequencing and RNAscope imaging to analyze gene expression changes in focal populations of mushroom body neurons. Thus, we identified three candidate functional modules of time-memory: synchronized peak-level expression of memory-related genes during training time, anticipatory activation of transcription inpdfr-expressing neurons, andcry2andperco-expressing neurons that might represent local clocks. The complex interactions between the clock and memory centers, which appear to be more similar to mammals than other insects, might have been facilitated to optimize social foraging in honey bees.