bluuebunny/crossref_metadata_2025 huggingface dataset:
Examining Risk Factors Related to Cardiac Rehabilitation Cessation Among Patients With Advanced Heart Failure
Authors: Sidhu Sharnendra K. , Kadosh Bernard S. , Tang Ying , Sweeney Greg , Pierre Alicia , Whiteson Jonathan , Katz Edward , Reyentovich Alex , Dodson John A.
Published: October 2024

Purpose:

Cardiac rehabilitation (CR) is beneficial in heart transplant and left ventricular assist device (LVAD) recipients, but patterns of attendance remain poorly understood. We describe CR adherence and cessation in this population.

Methods:

We performed a retrospective review of heart transplant and LVAD recipients who attended ≥1 CR session at a tertiary medical center (2013-2022). Complete adherence was defined as attending 36 sessions. Primary reasons for cessation before 36 sessions were recorded. We compared post-operative complications, duration of hospitalization, and readmissions between participants with and without complete adherence using logistic and linear regressions. Among participants with complete adherence, we compared changes in metabolic equivalent of task (MET), exercise time, and peak oxygen uptake using paired sample t tests.

Results:

There were 137 heart transplant and LVAD recipients (median age 56.9 years, 74% male) who attended CR. Among them, 91% either completed 36 CR sessions or <24 sessions. Among those without complete adherence (n = 74), 72% reported medical reasons, and 15% reported personal reasons for cessation. Compared to those who completed CR, those without complete adherence experienced more post-operative complications (44% vs 24%, P = .02) and major bleeding (23% vs 7%, P = .02) prior to CR. Participants with complete adherence experienced significant improvements in exercise time (142.5 seconds), MET (0.4), and peak oxygen uptake (1.4 mL/kg/min).

Conclusions:

Nearly half of heart transplant and LVAD recipients in CR completed all 36 sessions. Those with complete adherence experienced significant improvements in exercise measures, underscoring the important benefits of CR in this population.
Delays in Treatment for Temporal Encephaloceles and Cerebrospinal Fluid Leaks
Authors: Mouzourakis Maggie , Steinwald Peter , Maxwell Anne K. , Saravia Ari , Master Adam , Mankowski Nicholas , Saunders James E. , Materne Grace M. , Noonan Kathryn
Published: October 2024

Objective

Lateral skull base defects (LSBD) pose a diagnostic challenge; however, early recognition and treatment are important to avoid sequelae. This study examines the impact of health care disparities associated with time to diagnosis and treatment for patients with LSBD.

Study Design, Setting, Patients, Intervention, Outcome Measures

Multi-institutional retrospective cohort study at four U.S. tertiary centers from 2000 to 2022. Adult patients with a primary diagnosis of CSF leak or encephalocele were included. Multivariate regressions used to analyze how age, sex, race/ethnicity, insurance, language, zip code, distance to medical center, referral patterns, diagnostic workup, and clinical course affected time to diagnosis and treatment.

Results

In 127 patients with LSBD, mean time to treatment of CSF leak or encephalocele was 13.9 months. On average, patients waited 10.6 months from initial assessment to diagnosis and saw 2 providers prior to diagnosis. Approximately 91% (115) of patients had a CT scan, and 75% (95) had an MRI. Imaging did not influence time to treatment. Older age, public insurance, and number of providers seen were associated with delays. Non-English speakers (5% of 127) encountered treatment delays, although this was not statistically significant. Fifty-eight (46%) people had private insurance. The average traveled distance for care was 62.6 miles. Clinical presentation, race, zip code, imaging, myringotomy, beta-2 transferrin, and ED workup were not found to be associated with delays to care.

Conclusion

There are significant delays in diagnosis and management of LSBD. Referral patterns did influence care. Health care disparities did not impact care; however, disparities and language barriers need to be studied further to determine contributions to delays in care.
Periprosthetic Joint Infection in Patients With Inflammatory Arthritis
Authors: Goodman Susan M. , Mannstadt Insa , Tam Kathleen , Mehta Bella , Kochen Alejandro , Shakib Lorien , Sculco Peter , Carli Alberto , Batter Stephen , Rodriguez Jose , Bass Anne R. , Blevins Jason L. , Miller Andy O. , Russell Linda , Donlin Laura , Nocon Allina , Figgie Mark
Published: October 2024

Objective

Diagnosis of periprosthetic joint infection (PJI) in patients with inflammatory arthritis (IA) is challenging, as features of IA flares can mimic infection. We aimed to cross-sectionally determine if the optimal tests to diagnose PJI in osteoarthritis were present in patients with IA flares.

Methods

We enrolled patients from October 2020 to July 2022 in 3 groups: (a) PJI—total joint arthroplasty patients undergoing revision for infection, (b) IA Flare—IA patients with a flaring native joint, and (c) IA Aseptic—total joint arthroplasty patients with IA undergoing aseptic arthroplasty revision. We compared blood and synovial fluid markers between the cohorts using Kruskal-Wallis and Fisher exact tests to assess marker sensitivity and specificity.

Results

Of 52 cases overall, 40% had rheumatoid arthritis, 20% psoriatic arthritis, and 11% osteoarthritis (in PJI group). PJI cases had higher C-reactive protein (CRP) and synovial fluid polymorphonuclear neutrophil percentage (%PMN). Alpha-defensin tested positive in 93% of PJI cases, 20% of IA Flares, and 6% of IA Aseptic (p < 0.01). Synovial white blood cell count >3000/μL and positive alpha-defensin were highly sensitive (100%) in diagnosing infection; however, specificity was 50% for white blood cell counts and 79% for alpha-defensin. PJI diagnosis was nearly 5 times more likely with positive alpha-defensin and almost 6 times more likely with %PMNs >80. Blood markers interleukin-6, procalcitonin, and d-dimer were neither sensitive nor specific, whereas erythrocyte sedimentation rate and CRP showed 80% sensitivity, but 47% and 58% respective specificities.

Conclusions

Although synovial %PMNs, CRP, and alpha-defensin are sensitive tests for diagnosing PJI, they are less specific and may be positive in IA flares.
When an underestimated zoonosis and antimicrobial resistance collide: Corynebacterium ulcerans
Authors: Mori giovanni , Errico Giulia , Giancristofaro Sara , Visentin Donatella , Castagna Antonella , Viel Laura , Dellamaria Debora , Lorenzin Giovanni , Ortalli Gaia , Scarparo Claudio , Lanzafame Massimiliano
Published: October 2024

In the European region, diphtheria is now rarely suspected in patients presenting with upper respiratory tract symptoms. C. ulcerans is the underestimated zoonosis that is replacing C. diphtheria infections in industrialised countries, but extensive human and animal prevalence studies are lacking. The range of hosts that can act as reservoirs for C. ulcerans is very broad, companion pets currently being the main source of human infection. We report a case of macrolide-resistant C. ulcerans infection with no apparent zoonotic transmission and outline the efforts required for public and zooprophylactic management of these cases. We describe the main critical issues to be addressed to comprehensively tackle this zoonosis in the future.
Pancreatic Tuberculosis Revealed by a Mass with Neoplastic Appearance: A Case Report
Authors: Hachimi Idrissi Mariam , Benass Jihane , Zegmout Adil , Tazi Imane , Ben Lahlou Yassine , Benaissa Elmostafa , Seddik Hassan , Chadli Mariama
Published: October 2024

Introduction : Pancreatic tuberculosis is an extremely rare form of extrapulmonary tuberculosis. This condition can be challenging to diagnose due to its rarity, nonspecific symptoms, and radiological features that may mimic a neoplastic origin.
Case report: A 46-year-old immunocompetent patient with no past history of tuberculosis exposure, presented with spontaneously resolving jaundice over the past month, accompanied by non specific fever episodes and general fatigue with no other associated digestive symptoms. Abdominal CT and MRI scans revealed a poorly defined, partially necrotic mass in the pancreatic head with heterogeneous hypodensity and enhancement after contrast injection. Additionally, there were nodal and hilar macro-nodal lesions with necrotic appearances, as well as peripancreatic lymphadenopathy. The patient was scheduled for an Endoscopic ultrasound (EUS) examination which revealed the presence of a heterogeneous lesion with areas of necrosis  in the posterosuperior aspect of the head and isthmus of the pancreas, accompanied by perilesional and celiac lymphadenopathies with necrotic centers. EUS-guided tissue sampling allowed the diagnosis of pancreatic tuberculosis, with both histological examination and GeneXpert MTB/RIF testing rapidly positive for Mycobacterium tuberculosis, followed by culture on solid Loewenstein-Jensen medium. The patient responded well to antitubercular chemotherapy .
Conclusion: Pancreatic tuberculosis, though rare, should be considered in cases of pancreatic masses, especially in endemic regions. Tissue samples with necrosis should be tested for Mycobacterium tuberculosis using GeneXpert and Loewenstein-Jensen culture. This work highlights the GeneXpert MTB/RIF test as highly sensitive, specific, and fast, making it ideal for diagnosing extra-pulmonary tuberculosis, particularly when smear results are negative.
Detecting Incipient Heart Failure in Asymptomatic Patients with Normal Ejection Fraction and comparisons with patients with heart failure and preserved ejection fraction using TimeSformer for classifying Echocardiography videos
Authors: Adhyapak Srilakshmi M , Menon Prahlad G
Published: October 2024

Background

Recently deep learning models have helped differentiate echocardiography images of patients with heart failure with preserved ejection fraction (HFpEF) from normal controls. Our aim was to develop a model capable of detecting early signs of heart failure in asymptomatic patients with a normal ejection fraction.

Methods

We employed the TimeSformer, a video transformer model that classifies video data using a novel attentionbased mechanism. This self-attention mechanism that diverges from traditional convolutional neural networks (CNNs). It focuses on relevant parts of the video across both space and time, split into spatial attention, which processes each frame individually, and temporal attention, which integrates information across different frames. The training and validation of the TimeSformer model were conducted on the same dataset of echocardiography videos from 50 normal controls and 80 patients diagnosed with HFpEF, employing 5-fold cross-validation to ensure robust performance evaluation.

Results

The TimeSformer model effectively identified HFpEF in patients, as all diagnosed with HFpEF were flagged as abnormal. The echocardiography assessment, along with NT pro BNP levels, supported the diagnoses, with patients showing NT pro BNP levels of 1016±32 pg/ml. Conversely, 26 out of 50 normal controls were correctly identified. While 24 normal controls were identified as abnormal. Their NT pro BNP levels were 52±12 pg/ml. At 2 years 8 (33.3%) controls identified as abnormal developed symptoms of heart failure with NT pro BNP levels of 800±41 pg/ml.

Conclusions

The TimeSformer model demonstrated capability in identifying subtle deviations indicative of incipient heart failure in videos of normal controls, despite normal NT pro BNP levels. A significant number of these controls developed heart failure with elevated NT pro BNP levels at 2 years.
Extinction vortices are driven more by a shortage of beneficial mutations than by deleterious mutation accumulation
Authors: Mawass Walid , Matheson Joseph , Hernández Ulises , Berg Jeremy , Masel Joanna
Published: October 2024

Natural populations are increasingly at risk of extinction due to climate change and habitat loss or fragmentation. The long-term viability of small populations can be threatened by an “extinction vortex” — a positive feedback loop between declining fitness and declining population size. Two distinct mechanisms can drive an extinction vortex: i) ineffective selection in small populations allows deleterious mutations to fix, driving “mutational meltdown”, and ii) fewer individuals produce fewer of the novel beneficial mutations essential for long-term adaptation, a mechanism we term “mutational drought”. We measure the relative importance of each mechanism, on the basis of how sensitive beneficial vs. deleterious components of fitness flux are to changes in census population size near the critical population size at which fitness is stable. We derive analytical results given linkage equilibrium, complemented by simulations that capture the complex linkage disequilibria that emerge under high deleterious mutation rates. Even in the absence of environmental change, mutational drought can be nearly as important as mutational meltdown. Real populations must also adapt to a changing environment, making mutational drought more important. A partial exception is that mutational drought is somewhat less important when the beneficial mutation rate is high, although its contribution remains substantial. Linkage between deleterious and beneficial mutations drives the critical population size substantially higher and increase (albeit modestly) the importance of mutational drought.
Unified knowledge-driven network inference from omics data
Authors: Rodriguez-Mier Pablo , Garrido-Rodriguez Martin , Gabor Attila , Saez-Rodriguez Julio
Published: October 2024

Analysing omics data requires computational methods to effectively handle its complexity and to derive meaningful hypotheses about molecular mechanisms. While data-driven statistical and machine learning methods can identify patterns from omics data across multiple samples, they typically require a large number of samples and they often lack interpretability and alignment with existing biological knowledge. In contrast, knowledge-based network methods integrate molecular data with prior knowledge to provide results that are biologically interpretable, but they lack both a unified mathematical framework, leading to ad-hoc solutions specific to particular data types or prior knowledge, limiting their generalisability, and a common modelling interface for programmatic manipulation, restricting method extensions. Furthermore, existing methods generally cannot perform joint network inference across multiple samples or conditions, which restricts their capacity to capture shared mechanisms, making these methods more sensitive to noise and prone to overfitting. To address these limitations, we introduce CORNETO (Constrained Optimisation for the Recovery of NETworks from Omics), a unified framework for knowledge-driven network inference. CORNETO redefines the joint inference task as a constrained optimisation problem with a penalty that induces structured sparsity, allowing for simultaneous network inference across multiple samples. The framework is highly flexible and supports a wide variety of prior knowledge networks—undirected, directed and signed graphs, as well as hypergraphs—enabling the generalisation and improvement of many network inference methods, despite their seemingly different assumptions. We demonstrate its utility by presenting novel extensions of methods for signalling, metabolism and protein-protein interactions. We show how these new methods improve the performance of traditional techniques on a diverse set of biological tasks using simulated and real data. CORNETO is available as an open-source Python package (github.com/saezlab/corneto), facilitating researchers in extending, reusing, and harmonising methods for network inference.
Multivariate Trait Evolution: Models for the Evolution of the Quantitative Genetic G-Matrix on Phylogenies
Authors: Blomberg Simone P. , Muniz Michelle , Bui Mai Ngoc , Janke Cooper
Published: October 2024

Genetic covariance matrices (G-matrices) are a key focus for research and predictions from quantitative genetic evolutionary models of multiple traits. There is a consensus among quantitative geneticists that the G-matrix can evolve through “deep” time. Yet, quantitative genetic models for the evolution of the G-matrix are conspicuously lacking. In contrast, the field of macroevolution has several stochastic models for univariate traits evolving on phylogenies. However, despite much research into multivariate phylogenetic comparative methods, analytical models of how multivariate trait matrices might evolve on phylogenies have not been considered. Here we show how three analytical models for the evolution of matrices and multivariate traits on phylogenies, based on Lie group theory, Riemannian geometry and stochastic differential (diffusion) equations, can be combined to unify quantitative genetics and macroevolutionary theory in a coherent mathematical framework. The models provide a basis for understanding how G-matrices might evolve on phylogenies, and we show how to fit models to dataviasimulation using Approximate Bayesian Computation. Such models can be used to generate and test hypotheses about the evolution of genetic variances and covariances, together with the evolution of the traits themselves, and how these might vary across a phylogeny. This unification of macroevolutionary theory and quantitative genetics is an important advance in the study of phenotypes, allowing for the construction of a synthetic quantitative theory of the evolution of species and multivariate traits over “deep” time.

Lay Summary

We unite Quantitative Genetics, the major mathematical theory of multivariate quantitative trait microevolution, with the mathematical theory of multivariate macroevolution. To do this, we allow the key component of quantitative genetic theory, the matrix of additive genetic variances and covariances (the G-matrix) to evolve along evolutionary trees. This is an advance because the G-matrix is assumed to be constant in quantitative genetics, but it has been recognised that it evolves on macroevolutionary timescales (in “deep time”). Uniting Quantitative Genetics with macroevolutionary theory allows for a more complete mathematical description of Darwin’s theory of evolution, and allows for further testing of evolutionary hypotheses.
Introgression of the sunflowerHaHB4gene in modern wheat: An advancement in resilience to deal with climate change
Authors: Ayala Francisco , Curin Facundo , Diaz-Zorita Martín , Murguía José , Montero Bulacio Enrique , Portapila Margarita , Otegui María Elena , Chan Raquel Lía , González Fernanda Gabriela
Published: October 2024

Breeding for improved tolerance to water deficit is critical to mitigate climate change impact on wheat yield. In 2020, Argentina approved the first wheat transformed with the sunflowerHaHB4gene (INDØØ412-7), which increased yield by 16% compared to the non-transformed parental Cadenza under drought conditions. Previous studies may have overestimatedHaHB4benefits, as Cadenza is a long cycle for the Pampas region. Quantifying the yield advantage ofHaHB4in modern, well-adapted cultivars and elucidating the physiological processes involved, is crucial for identifying optimal environments for this technology. In a broad network of experiments (one greenhouse and 29 field environments), anHaHB4-introgressed line of Algarrobo was compared with the conventional cultivar. Under water deficit during the reproductive phase, the yield advantage ofHaHB4was 15% in the greenhouse and 13% in the field.HaHB4improved the relative yield by 0.06 to 0.08 % per mm of water deficit. The enhanced water use and water use efficiency conferred byHaHB4, allowed maintaining growth and yield under water deficit.HaHB4showed the highest benefit with moderate heat stress (∑Tmax > 30 °C ∼40-60 °Cd). In areas prone to drought combined with heat stress,HaHB4would enhance yield stability by improving water-limited yield.

Highlights

HaHB4-introgressed wheat enhanced water-limited yield by maintaining the crop growth under moderate to severe water deficit combined with mild heat stress through increasing water use and water use efficiency.
Disentangling the CHAOS of intrinsic disorder in human proteins
Authors: Vries Ida de , Bak Jitske , Salmoral Daniel Álvarez , Xie Ren , Borza Razvan , Konijnenberg Maria , Perrakis Anastassis
Published: October 2024

Most proteins consist of both folded domains and Intrinsically Disordered Regions (IDRs). However, the widespread occurrence of intrinsic disorder in human proteins, along with its characteristics, is often overlooked by the broader communities of structural and molecular biologists. Building on the MobiDB database of intrinsically disorder in proteins, here we develop a comprehensive dataset (Comprehensive analysis ofHuman proteinsAnd their disOrderedSegments (CHAOS)). We implement empirical internally consistent definitions of what constitutes a disordered region, annotate general characteristics such as cellular location, essentiality, and post-translational modifications, and cross-reference to structure predictions from AlphaFold. Most proteins contain at least one disordered region, predominantly located at the protein termini. IDRs are less hydrophobic and are enriched in post-translational modifications compared to non-IDRs. Additionally, we discovered that proteins residing in different cellular locations possess distinct disorder profiles. Finally, the predicted AlphaFold models of proteins in CHAOS suggest that while protein disorder may be intrinsic, it does not have to be extrinsic. Hereby we enhance the visibility and understanding of intrinsic disorder in human proteins.

Key messages

83% of human proteins contain one or more intrinsically disordered regions.

Intrinsically disordered regions are predominantly located at protein termini.

The amount and location of disordered regions s differs throughout cellular compartments.

AlphaFold predicts secondary structure elements within intrinsically disordered regions and fully disordered proteins.
Multi-character assessment of caryopsis in diverse common wheat germplasm, including high protein breeds
Authors: Kosina Romuald , Tomaszewska Paulina
Published: October 2024

In 15 varieties and hybrids of common wheat, including high-protein, varieties such as Atlas 66, Nap Hal, and Lancota, the microstructural characters of the caryopsis were analysed. Among the wheats, a high variability in the correlation matrices of characters was observed. A variable relationship between the specific gravity of the caryopsis and the size of the endosperm cavity was demonstrated. Some principal components (I, II, IV and V) contained the majority of the information regarding the weight, quality, vitreousness, and aleurone layer of the caryopsis, respectively. In the ordination space of nonmetric multidimensional scaling (nmMDS), two groups of wheat were distinguished: high-protein and low-protein subaleurone layers. Endosperm morphotypes were characterised by the proportion of two types of starch tissue, cylindric and isodiametric. In the nmMDS ordination space, wheat was described by the frequency distributions of six endosperm cavity morphotypes, with more (leptokurtosis) or less (platykurtosis) cumulated variation. In the case of endosperm developmental anomalies, the intrusive growth of cell walls, particularly in the aleurone layer, was identified as playing a significant role in the formation of endosperm mosaic architecture and domains. Varietal developmental specificity was discovered in the development of acellular starch domains within the endosperm tissue and starch grain storage in the cavity (as observed in cv. Purdue).
Formation of polyphasic RNP granules by intrinsically disordered Qβ coat proteins and hairpin-containing RNA
Authors: Granik Naor , Goldberg Sarah , Amit Roee
Published: October 2024

RNA-protein (RNP) granules are fundamental components in mammalian cells where they perform multiple crucial functions. Many RNP granules form via phase separation driven by protein-protein, protein-RNA, and RNA-RNA interactions. Notably, associated proteins frequently contain intrinsically disordered regions (IDRs) which can associate with multiple partners. Previously we have shown that synthetic RNA molecules containing multiple hairpin coat-protein binding sites can phase separate, forming granules capable of selectively incorporating proteins inside. Here, we expand this platform by introducing a phage coat protein with a known IDR which facilitates protein-protein interactions. We show that the coat protein phase-separates on its ownin vivo, and that introduction of hairpin-containing RNA molecules can lead to dissolvement of the protein granules. We further demonstrate via multiple assays that RNA valency, determined by the number of hairpins present on the RNA, leads to distinctly different phase behaviors, effectively forming a polyphasic programmable RNP granule. Moreover, by incorporating the gene for a blue fluorescent protein into the RNA, we demonstrate a phase-dependent boost to protein titer. These insights not only shed light on the behavior of natural granules, but also hold profound implications for the biotechnology field, offering a blueprint for engineering cellular compartments with tailored functionalities.
Identification of a key gain-of-function residue for effector binding byin vitroshuffling of barleyMla NLRgenes
Authors: Zhang Xiaoxiao , Gao Jialing , Molloy Lucy M. , Crean Lauren M. , Williams Simon J. , Rathjen John P.
Published: October 2024

Natural plant populations maintain high resistance (R) gene diversities that provide effective pathogen resistance; however, such diversity has been reduced significantly by the genetic bottlenecks associated with plant domestication and breeding. Agricultural crops typically contain limitedRgene diversity so resistance is often short-lived as pathogens evolve rapidly to evade recognition. Themildew resistance locus A(Mla)Rgene family of barley and wheat represents a rich source of natural genetic variation that is ideal for mining disease resistance specificities.Mla Rgenes encode immune receptor proteins of the nucleotide-binding leucine-rich repeat (NLR) class that recognise unrelated plant pathogens by binding secreted virulence proteins termed effectors. The barley NLRs MLA13 and MLA7 confer resistance to different strains of the barley powdery mildew pathogen through direct interaction with the pathogen effectors AVRA13and AVRA7respectively. Using DNA shuffling, we generated a variant library by recombining theMla7andMla13genesin vitro. The variant library was cloned into yeast generating ∼4,000 independent clones and was screened for interaction with AVRA13and AVRA7using a yeast-two-hybrid (Y2H) assay. This yielded a number of clones that encode NLR proteins that interacted with AVRA13. Sequence analysis showed that the interacting MLA proteins can be clustered into three groups, all of which contain a critical residue from MLA13. While MLA13 and MLA7 differ by 30 residues across the LRR domain, the replacement of leucine to serine at this position in MLA7 facilitated interaction with AVRA13in yeast and AVRA13-dependent immune signallingin planta. We have established a pipeline that evolves MLAs to recognise distinct pathogen effectors without the requirement for protein structural knowledge and the use of rationale design. We suggest these findings represent a step towards evolving novel recognition capabilities rapidlyin vitro.
LEGEND: Identifying Co-expressed Genes in Multimodal Transcriptomic Sequencing Data
Authors: Deng Tao , Huang Mengqian , Xu Kaichen , Lu Yan , Xu Yucheng , Chen Siyu , Xie Nina , Wu Hao , Sun Xiaobo
Published: October 2024

Identifying co-expressed genes across tissue domains and cell types is essential for revealing co-functional genes involved in biological or pathological processes. While both single-cell RNA-sequencing (scRNA-seq) and spatially-resolved transcriptomic (SRT) data offer insights into gene co-expression patterns, current methods typically utilize either data type alone, potentially diluting the co-functionality signals within co-expressed gene groups. To bridge this gap, we introduce LEGEND, a novel computational method that integrates scRNA-seq and SRT data for identifying groups of co-expressed genes at both cell type and tissue domain levels. LEGEND employs an innovative hierarchical clustering algorithm designed to maximize intra-cluster redundancy and inter-cluster complementarity, effectively capturing more nuanced patterns of gene co-expression and spatial coherence. Enrichment and cofunction analyses further showcase the biological relevance of these gene clusters, and their utilities in exploring context-specific novel gene functions. Notably, LEGEND can reveal shifts in gene-gene interactions under different conditions, furnishing insights for disease-associated gene crosstalk. Moreover, LEGEND can be utilized to enhance the annotation accuracy of both spatial spots in SRT and single-cells in scRNA-seq, and pioneers in identifying genes with designated spatial expression patterns. LEGEND is available athttps://github.com/ToryDeng/LEGEND.
Cloudgene 3: Transforming Nextflow Pipelines into Powerful Web Services
Authors: Forer Lukas , Schönherr Sebastian
Published: October 2024

Nextflow has emerged as a flexible and scalable workflow system for building computational pipelines in life sciences. Simultaneously, Software-as-a-Service platforms enable researchers to concentrate on data analysis rather than on setting up pipelines locally. However, converting existing pipelines into web services can be challenging due to complexities such as handling large datasets, web development and overall security. Cloudgene 3 addresses these challenges by providing a platform that transforms Nextflow pipelines into scalable web services in just a few steps. Making pipelines available as public or private services enhances collaboration among diverse teams and improves accessibility, eliminating the need for extensive technical expertise.

Availability and Implementation

Cloudgene 3 is free available athttps://www.cloudgene.io

Contact

lukas.forer@i-med.ac.at
Chitinase-1 inhibition reverses metabolic dysregulation and restores homeostasis in MASH animal models
Authors: Drzewicka Katarzyna , Głuchowska Katarzyna , Mlącki Michał , Hofman Bartłomiej , Tuszynska Irina , Ryan Tristram , Piwowar Katarzyna , Wilczyński Bartosz , Dymkowska Dorota , Dymek Barbara , Rejczak Tomasz , Lisiecki Kamil , Gołębiowski Adam , Jagielski Adam , Muchowicz Angelika , Ryan Dylan , Zabłocki Krzysztof , O’Neill Luke A.J. , Zasłona Zbigniew
Published: October 2024

OATD-01 is a chitinase-1 (CHIT1) inhibitor, reducing inflammation and fibrosis in animal models where chronic inflammation leads to tissue remodeling. CHIT1, predominantly secreted by macrophages, is overexpressed in metabolic-dysfunction-associated steatohepatitis (MASH). In this study, we demonstrated the efficacy of OATD-01 in two murine and a rat model of MASH. RNA-Seq analysis revealed that OATD-01 reversed MASH-dysregulated genes. Apart from the attenuation of inflammation and fibrosis, OATD-01 regulated metabolic processes such as lipid metabolism and glycolysis. We demonstrated that both genetic and pharmacological inactivation of CHIT1 resulted in inhibition of glycolysis and glucose uptake in primary macrophages. As a consequence, we observed increased ATP, lower citrate and increased acetate levels, resulting in a reduced IL-1β secretion. These results revealed the key role for CHIT1 in regulating metabolism. OATD-01 is a macrophage modulator that can directly restore metabolic balance and consequently inhibit inflammation and fibrosis, supporting its use for MASH treatment.
Modulation of Host Cell Membrane Biophysics Dynamics by Neospora caninum: A Study Using LAURDAN Fluorescence with Hyperspectral Imaging and Phasor Analysis
Authors: Díaz Marcela , Robello Carlos , Cabrera Andrés , Malacrida Leonel
Published: October 2024

Neospora caninumis known to manipulate host cell organelles and recruit lipids for its survival. However, the impact of this lipid redistribution on host cell membranes remains poorly understood. This study used LAURDAN fluorescence, hyperspectral imaging, and phasor plot analysis to investigate howN. caninummodifies membrane order in Vero cells. The results revealed a significant decrease in host cell plasma and internal membrane order upon infection, suggesting that cholesterol is redistributed from the host plasma membrane to the parasitophorous vacuoles. To mimic cholesterol depletion, uninfected cells were treated with methyl-β-cyclodextrin (MBCD), which increased membrane fluidity. Conversely, replenishing infected cells with cholesterol-loaded MBCD restored membrane fluidity to levels lower than control cells, indicating cholesterol enrichment. These findings provide novel insights into howN. caninummodulates host cell membrane dynamics through lipid manipulation, potentially aiding its intracellular survival.
Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location and histology using GCN
Authors: Xue Shuailin , Zhu Fangfang , Chen Jinyu , Min Wenwen
Published: October 2024

Spatial transcriptomics technology allows for the detection of cellular transcriptome information while preserving the spatial location of cells. This capability enables researchers to better understand the cellular heterogeneity, spatial organization and functional interactions in complex biological systems. However, current technological methods are limited by low resolution, which reduces the accuracy of gene expression levels. Here, we propose scstGCN, a multimodal information fusion method based on Vision Transformer (ViT) and Graph Convolutional Network (GCN) that integrates histological images, spot-based spatial transcriptomics data and spatial location information to infer super-resolution gene expression profiles at single-cell level. We evaluated the accuracy of the super-resolution gene expression profiles generated on diverse tissue ST datasets with disease and healthy by scstGCN along with their performance in identifying spatial patterns, conducting functional enrichment analysis, and tissue annotation. The results show that scstGCN can predict super-resolution gene expression accurately, aid researchers in discovering biologically meaningful differentially expressed genes and pathways. Additionally, scstGCN can segment and annotate tissues at a finer granularity, with results demonstrating strong consistency with coarse manual annotations.

Key Points

scstGCN combines multi-modal information including histology image, spot-based spatial transcriptomics (ST) data, and physical spatial location through deep learning methods to achieve single-cell resolution of spot-based ST data without requiring single-cell references.

scstGCN employs GCN to capture complex relationships between neighboring cells, facilitating the integration of multimodal feature information based on single-cell level, and then accurately infers single-cell resolution spatial gene expression.

scstGCN can infer single-cell resolution gene expression across the entire tissue region. Through transfer learning, gene expression in three-dimensional tissues can be characterized efficiently. Furthermore, it demonstrates outstanding performance in spatial patterns enhancement, functional enrichment analysis, and annotate tissues at the high-resolution.
Secreted phospholipase PLA2G12A-driven lysophospholipid signaling via lipolytic modification of extracellular vesicles facilitates pathogenic Th17 differentiation
Authors: Mochizuki Chika , Taketomi Yoshitaka , Irie Atsushi , Kano Kuniyuki , Nagasaki Yuki , Miki Yoshimi , Ono Takashi , Nishito Yasumasa , Nakajima Takahiro , Tomabechi Yuri , Hanada Kazuharu , Shirouzu Mikako , Watanabe Takashi , Hata Kosuke , Izumi Yoshihiro , Bamba Takeshi , Chun Jerold , Kudo Kai , Kotani Ai , Endo Yusuke , Aoki Junken , Murakami Makoto
Published: October 2024

Lipogenesis-driven metabolic flux is crucial for differentiation of pathogenic Th17 cells. Although our previous CRISPR-based screening identified PLA2G12A as a key player in this process, it has remained obscure how this secreted phospholipase A2isoform controls Th17 differentiation. Here we show that global, T cell-specific, or fibroblast-specific deletion of PLA2G12A prevents Th17 differentiation and associated diseases including psoriasis and arthritis. PLA2G12A acts on Th17-derived extracellular vesicles (EVs) to produce lysophospholipids including the RORγt activator 1-oleoyl-lysophosphatidylethanolamine. These lysophospholipids are further converted by autotaxin to lysophosphatidic acid (LPA), which assists Th17 differentiation mainly via LPA2receptor. Moreover, PLA2G12A promotes the secretion and uptake of EVs by Th17 cells and alters their cargo contents. Defective Th17 differentiation by PLA2G12A deficiency is rescued by supplementation with PLA2G12A-modified EVs. Importantly, a PLA2G12A-blocking antibody prevents Th17 differentiation and ameliorates psoriasis and arthritis models. Thus, targeting the PLA2G12A-EV-lysophospholipid axis may be useful for treatment of Th17-related diseases.
Dual-site tACS over the primary motor cortices increases interhemispheric inhibition and improves bimanual dexterity: A triple-blind, randomised, sham-controlled study
Authors: Lebihan Brooke , Mobers Lauren , Daley Shannae , Battle Ruth , Leclercq Natasia , Misic Katherine , Wansbrough Kym , Vallence Ann-Maree , Tang Alexander D. , Nitsche Michael A. , Fujiyama Hakuei
Published: October 2024

Concurrent application of transcranial alternating current stimulation (tACS) over distant cortical regions has been shown to modulate functional connectivity between stimulated regions; however, the precise mechanisms remain unclear. Here, we investigated how dual-site tACS (ds-tACS) applied over the bilateral primary motor cortices (M1s) modulates connectivity between M1s. Using a cross-over sham-controlled triple-blind within- subject design, 37 (27 female, age 18-37yrs) healthy participants received tACS (1.0mA, 20Hz) over the bilateral M1s for 20 min. Before and after tACS, functional connectivity between M1s was assessed using imaginary coherence (ImCoh) measured via resting-state electroencephalography (EEG) and interhemispheric inhibition (IHI) via dual-site transcranial magnetic stimulation (TMS) protocol. Additionally, manual dexterity was assessed using the Purdue pegboard task. While ImCoh remained unchanged after simulation, spectral power analysis showed a significant decrease in beta (20 Hz) power during the tACS session. ds-tACS but not sham strengthened IHI between the M1s and improved bimanual assembly performance. These results suggest that improvement in bimanual performance may be explained by modulation in M1-M1 IHI, rather than by coupling in the oscillatory activity. As functional connectivity underlies many clinical symptoms in neurological and psychiatric disorders, these findings are invaluable in developing non-invasive therapeutic interventions that target neural networks to alleviate symptoms.
Structured Codes and Free-Text Notes: Measuring Information Complementarity in Electronic Health Records
Authors: Seinen Tom M , Kors Jan A , van Mulligen Erik M , Rijnbeek Peter R
Published: October 2024

Background

Electronic health records (EHRs) consist of both structured data (e.g., diagnostic codes) and unstructured data (e.g., clinical notes). It’s commonly believed that unstructured clinical narratives provide more comprehensive information. However, this assumption often lacks large-scale validation and direct validation methods.

Objective

This study aims to quantitatively compare the information in structured and unstructured EHR data and directly validate whether unstructured data offers more extensive information across a patient population.

Methods

We analyzed both structured and unstructured data from patient records and visits in a large Dutch primary care EHR database between January 2021 and January 2024. Clinical concepts were identified from free-text notes using an extraction framework tailored for Dutch and compared with concepts from structured data. Concept embeddings were generated to measure semantic similarity between structured and extracted concepts through cosine similarity. A similarity threshold was systematically determined via annotated matches and minimized weighted Gini impurity. We then quantified the concept overlap between structured and unstructured data across various concept domains and patient populations.

Results

In a population of 1.8 million patients, 42% of structured concepts in patient records and 25% in individual visits had similar matches in unstructured data. Conversely, only 13% of extracted concepts from records and 7% from visits had similar structured counterparts. Condition concepts had the highest overlap, followed by measurements and drug concepts. Subpopulation visits, such as those with chronic conditions or psychological disorders, showed different proportions of data overlap, indicating varied reliance on structured versus unstructured data across clinical contexts.

Conclusions

Our study demonstrates the feasibility of quantifying the information difference between structured and unstructured data, showing that the unstructured data provides important additional information in the studied database and populations. Despite some limitations, our proposed methodology proves versatile, and its application can lead to more robust and insightful observational clinical research.
Characterization of a novel neurodevelopmental rare disease caused by a mutation within the autophagy geneATG9B
Authors: Kılıç Seval , Esmen Kerem , Oto A. Miray , Kose T. Bilge , Sever-Bahçekapılı Melike , Eren-Koçak Emine , Demir Şeyda , Hız A. Semra , Karakülah Gökhan , Bağrıyanık H. Alper , Öztürk Mehmet , Diril M. Kasım
Published: October 2024

Autophagy is a highly conserved eukaryotic cellular process whose dysfunction results in human pathologies including cancer and neurodegenerative disease. First identified in yeast, ATG genes are central players in autophagy. Although their roles in cancer and neurodegenerative disease are well known, Mendelian diseases associated with ATG genes are rare. Mutations in core autophagy genesATG5andATG7have been previously reported to cause rare genetic disorders with autosomal recessive inheritance pattern.

Here we report, for the first time, a rare genetic disorder that results from a deletion/frameshift mutation in human ATG9B, the placenta specific homologue of yeast ATG9 in humans. The 11-nucleotide deletion causes a frameshift and addition of a premature stop codon, truncating the C-terminal cytosolic domain of the ATG9B protein. The pediatric patients carrying the mutant allele homozygous were children of a consanguineous marriage and displayed neurodevelopmental anomalies including mental retardation. We hypothesized that this phenotype originates during placental development.

To characterize the effects of the mutation and gain insight on the specific functions of ATG9B in a physiological setting, we used mammalian cells and generated a knock-in mouse model. Truncated ATG9B was not stable when expressed in cells. It was localized to perinuclear vesicles like the WT protein, but not to peripheral vesicles. Homozygous knock-in mice were viable, fertile and displayed no gross phenotypical abnormalities. Histomorphometry analysis of the placenta layers did not reveal a significant difference between mutant and control embryos. The assessments of neurobehavioral tests were similar in wild-type and homozygous knock-in mice. However, knock-in mice had a reduced fear memory trend, which is an amygdala-involved response.
Orchid losers and winners after fire in West Australian urban bushland: A response continuum deeply integrated with other traits
Authors: Brundrett Mark C.
Published: October 2024

Context

The Southwest Australia Floristic Region (SWAFR) is a global hotspot for plant taxonomic and functional diversity. This region has many orchids with highly specialised associations with pollinators and mycorrhizal fungi that also face increasing threats from habitat loss, grazing, weeds, fire and climate change.

Aims

To compare the fire ecology of 17 orchids with diverse ecological strategies and functional traits from an isolated urban banksia and eucalypt woodland, and develop fire response monitoring methods and management criteria.

Methods

A 72-year fire record was intersected with ∼1000 orchid locations and 4.5 km of transects to measure fire effects on orchid abundance and diversity. Key traits such as plant size, flowering, pollination, tuber depth, clonality and population dynamics were also compared using 7-11 years of baseline data.

Key results

Fire history was very complex with 58 large overlapping major fires over 5 decades, averaging 8.7% of the 63-ha area annually. Correlating fire history with orchids revealed 5 species usually lost to fire and 6 with substantial fire impacts, while 6 others benefited from fire, including 3 with strongly enhanced flowering, but even the latter could be killed by unseasonal fire. Pollination varied from moderate decreases to substantial increases, but three orchids produced seed primarily after fire. Overall, impacts of fire greatly out way benefits, as most orchids preferred long-unburnt areas, and five species were confined to them. Paradoxically,Pyrorchis nigricansrequires fire to flower, but was most productive in long-unburnt areas and primarily reproduced clonally.

Conclusions

Fire history maps revealed a spectrum of outcomes from catastrophic to beneficial for orchid species summarised by fire response indexes (FRI) and fire age safe thresholds (FAST) lasting decades. This response continuum was highly correlated with trait such as tuber depth, seed vs clonal reproduction, dispersion and lifespan. Fire was deeply integrated into the biology and ecology of SWAFR orchids which are adapted for long inter-fire intervals which maximise their diversity and abundance.

Implications

Research in an urban nature reserve provided essential tools for sustainable management of orchids that are also relevant to rare species. These tools include fire history maps, FRI and FAST. Many SWAFR orchids were most productive in long unburnt areas or intolerant to fire, and even fire tolerant orchids can be harmed by autumn fires. Thus, fire must be carefully managed in their habitats, since may orchids are most productive two or more decades after fire.
Structural insights into maturation and translation of a plant mitoribosome
Authors: Skaltsogiannis Vasileios , Nguyen Tan-Trung , Corre Nicolas , Pflieger David , Blevins Todd , Hashem Yaser , Giegé Philippe , Waltz Florent
Published: October 2024

Ribosomes are key molecular machines that translate mRNA into proteins. Mitoribosomes are specific ribosomes found in mitochondria, which have been shown to be remarkably diverse across eukaryotic lineages. In plants, they possess unique features, including additional rRNA domains stabilized by numerous pentatricopeptide repeat proteins. However, the molecular mechanisms of translation by plant mitoribosomes remain largely unknown. Here, we use cryo-electron microscopy to provide a high-resolution structural characterization of the flowering plant mitoribosome, in translating and maturation states. The structure reveals the mitoribosome bound to tRNA in the peptidyl site, along with a segment of mRNA and a nascent polypeptide. Moreover, we identify an extensive set of ribosomal RNA modifications that we confirmed by nanopore sequencing. Additionally, we observe a late assembly intermediate of the small ribosomal subunit, in complex with the RsgA assembly factor. This reveals how a plant-specific extension of RsgA blocks the mRNA channel to prevent premature mRNA association before complete small subunit maturation. Our findings elucidate key aspects of translation in flowering plant mitochondria, revealing its distinct features compared to other eukaryotic lineages.