bluuebunny/crossref_metadata_2025_split huggingface dataset:
Echocardiography Findings for Pulmonary Hypertension During Workup for Bronchoscopic Lung Volume Reduction
Authors: Mahajan Amit K. , Collar Nancy , Muldowney Frances , Gorka Paul , Duong Duy K. , Patel Priya P. , Cicenia Joseph , Hogarth Douglas K. , Nathan Steven 
Published: December 2024

Bronchoscopic lung volume reduction (BLVR) is a minimally invasive intervention that improves dyspnea and quality of life in select individuals with emphysema. Echocardiography is the initial screening tool for pulmonary hypertension (PH) in patients evaluated for BLVR. Multiple BLVR and lung volume reduction surgery (LVRS) trials have used and right ventricular systolic pressure (RVSP) of 45 mm Hg as a cutoff for potential significant PH. However, PH is established hemodynamically by right heart catheterization (RHC), not echocardiography due to notoriously inaccurate RSVP values in patients with lung disease, especially those with COPD and suboptimal acoustic imaging windows. Over a 5-year period, all patients who met PFT criteria for BLVR underwent a routine screening echocardiogram for PH. Twenty-four patients with a RVSP >45 mm Hg or suspicion of significant PH on echocardiography were subjected to RHC. Twenty-one (88%) with suspicion for significant PH based on echocardiography did not have significant PH on RHC. Three patients (12%) had significant PH based on RHC precluding them from BLVR. Ten of the 21 patients with echo suspected PH, but RHC negative PH qualified for BLVR. Twelve-month follow-up data was available for 7 of these patients post-BLVR that included change in forced expiratory volume in 1 second (FEV1), 6-minute walk distance (6MWD), and St. George’s Respiratory Questionnaire (SGRQ). The mean change in FEV1 showed an increase of 0.154 L, 6MWD increase of 42 m, and SGRQ decrease of 11.5 points. On the basis of results from this study, all patients being evaluated for BLVR found to have a RVSP over 45 mm Hg on echocardiography should undergo RHC to confirm significant PH.
Coping With Anticipatory Grief: A Qualitative Study of Parents of Children With Advanced Cancer
Authors: Ng Yong Hao , Fu Fang 
Published: December 2024

Background
Anticipatory grief is a common but understudied phenomenon among parents of children with advanced cancer. Appropriate coping with anticipatory grief may promote better adaptation before and after the death.

Objective
To explore the anticipatory grief experiences and coping approaches of such parents in Shanghai, China.

Methods
Using Husserlian phenomenology approach, 4 fathers and 16 mothers were interviewed at the Children’s Medical Center in Shanghai. The transcripts were analyzed using Colaizzi phenomenological methods.

Results
Five themes were developed. The first theme described anticipatory grief experiences characterized by trauma and chronic misery, and the next 4 themes described how the parent coped with the grief through avoidance, acceptance, hope, and being present-focused. Parents coped differently at different times—from diagnosis, the time while the child was on treatment, to the time the parents could consider the possibilities of an uncertain future. The study also found that coping with grief is an intrapersonal and interpersonal process.

Conclusion
The study offers insights into parents’ dynamic coping processes when living with grief. Nurses could play a critical role in facilitating this process of living with grief.

Implications for Practice
Oncology nurses, by understanding parents’ anticipatory grief, can align themselves with the parents’ coping processes to provide appropriate support.
SOX2-induced IL1α-mediated immune suppression drives epithelial dysplasia malignant transformation
Authors: Taner Hülya F. , Gong Wang , Fitzsimonds Zackary R. , Li Zaiye , Wu Yuesong , He Yumin , Okuyama Kohei , Cheng Wanqing , Kuczura Jung , Rajesh Sashider , Manousidaki Andriana , Feng Shuo , Lee Miki , Nör Felipe , Lanzel Emily , Demehri Shadmehr , Polverini Peter J. , Nör Jacques E. , Wang Thomas D. , Que Jianwen , Wen Haitao , Xie Yuying , Moon James J. , Lei Yu Leo 
Published: December 2024

AbstractSquamous cell carcinomas (SCC) are often preceded by potentially malignant precursor lesions, most of which remain benign. The terminal exhaustion phenotypes of effector T-cells and the accumulation of myeloid-derived suppressor cells (MDSC) have been thoroughly characterized in established SCC. However, it is unclear what precancerous lesions harbor a bona fide high risk for malignant transformation and how precancerous epithelial dysplasia drives the immune system to the point of no return. Here we show that expression of SRY-box transcription factor 2 (SOX2) in precancerous lesions imparts an irreversible risk that recruits suppressive myeloid cells by promoting the release of CCL2. We developed a unique genetically engineered mouse model (GEMM) to recapitulate the malignant transformation of epithelial dysplasia to SCC in the oral mucosa with high histologic and phenotypic fidelity. Using a combination of longitudinal human specimens and the Sox2-GEMM, we found that the myeloid cells in precancerous epithelial dysplasia exhibit a distinctive dichotomous profile featuring high levels of IL-1α-SLC2A1 and low levels of type-I interferon (IFN-I) signatures, which occurs before SCC emerges histologically. Brief priming of myeloid cells with IL-1α desensitizes them to IFN-I agonists and makes myeloid-derived suppressor cells (MDSC) even more suppressive of T-cell activation. Mechanistically, IL-1 activation represses the expression of DHHC3/7 enzymes, which are responsible for the palmitoylation of stimulator of interferon genes (STING). Early blockade of IL1 signaling using pharmacologic and genetic approaches similarly reduces MDSC and SLC2A1highmyeloid cells, suppresses epithelial dysplasia transformation, and extends survival. This work establishes a previously unrecognized SOX2-CCL2-IL1 pathway that leads to irreversible immune escape when precancerous epithelial lesions transform.
Scalable DNA Feature Generation and Transcription Factor Binding Prediction via Deep Surrogate Models
Authors: Kabir Anowarul , Inan Toki Tahmid , Rasmussen Kim , Shehu Amarda , Usheva Anny , Bishop Alan , Alexandrov Boian , Bhattarai Manish 
Published: December 2024

AbstractSimulating DNA breathing dynamics, for instance Extended Peyrard-Bishop-Dauxois (EPBD) model, across the entire human genome using traditional biophysical methods like pyDNA-EPBD is computationally prohibitive due to intensive techniques such as Markov Chain Monte Carlo (MCMC) and Langevin dynamics. To overcome this limitation, we propose a deep surrogate generative model utilizing a conditional Denoising Diffusion Probabilistic Model (DDPM) trained on DNA sequence-EPBD feature pairs. This surrogate model efficiently generates high-fidelity DNA breathing features conditioned on DNA sequences, reducing computational time from months to hours–a speedup of over 1000 times. By integrating these features into the EPBDxDNABERT-2 model, we enhance the accuracy of transcription factor (TF) binding site predictions. Experiments demonstrate that the surrogate-generated features perform comparably to those obtained from the original EPBD framework, validating the model’s efficacy and fidelity. This advancement enables real-time, genome-wide analyses, significantly accelerating genomic research and offering powerful tools for disease understanding and therapeutic development.
DemoTape: Computational demultiplexing of targeted single-cell sequencing data
Authors: Borgsmüller Nico , Kuipers Jack , Gawron Johannes , Roncador Marco , Pohly Marcel , Acar Erkin , Do Thi Huong Lan , Reisenauer Stefanie , Feldkamp Mirjam Judith , Beisel Christian , Zenz Thorsten , Moor Andreas , Beerenwinkel Niko 
Published: December 2024

AbstractBackgroundSingle-cell sequencing can provide novel insights into the understanding and treatment of diseases. In cancer, for example, intratumor heterogeneity is a major cause of treatment resistance and relapse. Although technological progress has substantially increased the throughput of sequenced cells, single-cell sequencing remains cost and labor-intensive. Multiplexing, i.e., the pooling and subsequent joint preparation and sequencing of samples, followed by a demultiplexing step, is a common practice to reduce expenses and confounding batch effects, especially in single-cell RNA sequencing.ResultsHere, we introducedemoTape, a computational demultiplexing method for targeted single-cell DNA sequencing (scDNA-seq) data based on a distance metric between individual cells at single-nucleotide polymorphisms loci. To validatedemoTape, we sequence three B-cell lymphoma patients separately and multiplexed on the Tapestri platform. We find similar genotypes, clones, and evolutionary histories in all three samples when comparing the individual with the demultiplexed samples. Using the three individually sequenced samples, we simulate multiplexed ground truth data and show thatdemoTapeoutperforms state-of-the-art demultiplexing methods designed for RNA sequencing data. Additionally, we demonstrate through downsampling that the inferred clonal composition remained largely stable for samples with fewer cells despite the inevitable loss in resolution of low-frequency clones.ConclusionsMultiplexing and subsequent genotype-based demultiplexing of scDNA-seq will reduce costs and workload, eventually allowing the sequencing of more samples. This will open new possibilities and accelerate the investigation of biological questions where cellular heterogeneity on the genomic level plays a crucial role.
Pairwise graph edit distance characterizes the impact of the construction method on pangenome graphs
Authors: Dubois Siegfried , Zytnicki Matthias , Lemaitre Claire , Faraut Thomas 
Published: December 2024

AbstractMotivationPangenome variation graphs are an increasingly used tool to perform genome analysis, aiming to replace a linear reference in a wide variety of genomic analyses. The construction of a variation graph from a collection of chromosome-size genome sequences is a difficult task that is generally addressed using a number of heuristics. The question that arises is to what extent the construction method influences the resulting graph, and the characterization of variability.ResultsWe aim to characterize the differences between variation graphs derived from the same set of genomes with a metric which expresses and pinpoint differences. We designed a pairwise variation graph comparison algorithm, which establishes an edit distance between variation graphs, threading the genomes through both graphs. We applied our method to pangenome graphs built from yeast and human chromosome collections, and demonstrate that our method effectively characterizes discordances between pangenome graph construction methods and scales to real datasets.Availabilitypancat compareis published as free Rust software under the AGPL3.0 open source license. Source code and documentation are available athttps://github.com/dubssieg/rs-pancat-compare.Contactsiegfried.dubois@inria.frSupplementary informationSupplementary data are available online athttps://doi.org/10.5281/zenodo.10932490. Code to replicate figures and analysis is available online athttps://github.com/dubssieg/pancat_paper.
A decision-theoretic model of multistability: perceptual switches as internal actions
Authors: Safavi Shervin , Dayan Peter 
Published: December 2024

AbstractPerceptual multistability has been studied for centuries using a diverse collection of approaches. Insights derived from this phenomenon range from core principles of information processing, such as perceptual inference, to high-level concerns, such as visual awareness. The dominant computational explanations of perceptual multistability are based on the Helmholtzian view of perception as inverse inference. However, these approaches struggle to account for the crucial role played by value, e.g., with percepts paired with reward dominating for longer periods than unpaired ones. In this study, we formulate perceptual multistability in terms of dynamic, value-based, choice, employing the formalism of a partially observable Markov decision process (POMDP). We use binocular rivalry as an example, considering different explicit and implicit sources of reward (and punishment) for each percept. The resulting values are time-dependent and influenced by novelty as a form of exploration. The solution of the POMDP is the optimal perceptual policy, and we show that this can replicate and explain several characteristics of binocular rivalry, ranging from classic hallmarks such as apparently spontaneous random switches with approximately gamma-distributed dominance periods to more subtle aspects such as the rich temporal dynamics of perceptual switching rates. Overall, our decision-theoretic perspective on perceptual multistability not only accounts for a wealth of unexplained data, but also opens up modern conceptions of internal reinforcement learning in service of understanding perceptual phenomena, and sensory processing more generally.
N1-methylpseudouridine mRNA modification enhances efficiency and specificity of gene overexpression by preventing Prkra-mediated global translation repression
Authors: Lu Tong , Chen Aijun , Wang Sen , Zhang Yizhuang , Yang Boya , Wang Jiasheng , Fang Hailing , Gong Qianqian , Li Ang , Liu Xiangguo , Ma Pengcheng , Mao Bingyu , Shi De-Li , Shao Ming 
Published: December 2024

AbstractIn vitro transcribed messenger RNA (IVT mRNA) has emerged as a pivotal tool in mRNA-based therapies and has been extensively employed in gene function studies and genetic tool applications. However, the IVT process generates double-stranded RNA (dsRNA) by-products that are recognized by dsRNA sensors, triggering innate immune responses. In this study, we comprehensively analyzed the detrimental effects of dsRNA by-products on early zebrafish embryos, revealing that these by-products induce cell necrosis and delay maternal-zygotic transition by reducing global translation efficiency via Prkra, a recently identified dsRNA sensor in pluripotent cells. Importantly, we demonstrate that N1-methylpseudouridine (m1φ) modification of IVT mRNAs effectively mitigates these adverse effects, as m1φ-modified dsRNAs exhibit significantly lower binding affinity to the Prkra dimer. Our findings underscore a previously overlooked challenge in the use of IVT mRNA in early embryos and offer a robust solution to enhance the fidelity of mRNA applications. Furthermore, we elucidate that m1φ modification minimizes the dsRNA-induced stress response in pluripotent cells through a distinct mechanism.
Integrating natural language processing and genome analysis enables accurate bacterial phenotype prediction
Authors: Gómez-Pérez Daniel , Keller Alexander 
Published: December 2024

AbstractUnderstanding microbial phenotypes from genomic data is crucial in areas of research including co-evolution, ecology and pathology. This study proposes a new approach to integrate literature-derived information with genomic data to study microbial traits, combining natural language processing (NLP) with functional genome analysis. We applied this methodology to publicly available data to overcome current limitations and provide novel insights into microbial phenotype prediction.We fine-tuned specialized transformer-based large language models to analyze 3.3 million open-access scientific articles, extracting a network of phenotypic information linked to bacterial strains. The network maps relationships between bacterial strains and traits such as pathogenicity, metabolic capacity, and host and biome preference. By functionally annotating reference genome assemblies for strains in the phenotypic network, we were able to predict key genes influencing phenotypes.Our findings align with known phenotypes and reveal novel correlations, leading to the identification of microbial genes relevant in particular disease and host-association phenotypes. The interconnectivity of strains within the network provided further understanding of microbial community interactions, leading to the identification of hub species by inferring trophic connections—insights challenging to extract by means of experimental work.This study demonstrates the potential of machine learning methods to uncover cross-species patterns in microbial gene-phenotype correlations. As the number of sequenced strains and literature descriptions grows exponentially, such methods become crucial for extracting meaningful information and advancing microbiology research.
Adapting COVID-19 research infrastructure to capture influenza and respiratory syncytial virus alongside SARS-CoV-2 in UK healthcare workers winter 2022/23: Results of a pilot study in the SIREN cohort
Authors: Foulkes Sarah , Munro Katie , Sparkes Dominic , Broad Jonathan , Platt Naomi , Howells Anna , Akinbami Omolola , Khawam Jameel , Joshi Palak , Russell Sophie , Norman Chris , Price Lesley , Corrigan Diane , Cole Michelle , Timelin Jean , Forster Louise , Slater Katrina , Watson Conall H , Andrews Nick , Charlett Andre ,   SIREN study group, Atti Ana , Islam Jasmin , Brown Colin S , Turner Jonathan , Hopkins Susan , Hall Victoria 
Published: December 2024

ABSTRACTIntroductionThe combination of patient illness and staff absence driven by seasonal viruses culminates in annual “winter pressures” on UK healthcare systems and has been exacerbated by COVID-19. In winter 2022/23 we ran a pilot study aiming to introduce multiplex testing to determine the incidence and burden of SARS-CoV-2, influenza and respiratory syncytial virus (RSV) in our cohort of UK healthcare workers (HCWs).MethodsThe pilot study was conducted from 28/11/2022-31/03/2023 within the SIREN prospective cohort study. Participants completed fortnightly questionnaires, capturing symptoms and sick leave, and multiplex PCR testing for SARS-CoV-2, influenza and RSV, regardless of symptoms. PCR-positivity rates by virus were calculated over time, and viruses were compared by symptoms and severity. Self-reported symptoms and associated sick leave were described. Sick leave rates were compared by vaccination status and demographics.Results5,863 participants were included, 84.6% female, 70.3% ≥45-years, and 33.4% were nurses. PCR-positivity peaked in early December for all three viruses (4.6 positives per 100 tests (95%CI 3.5, 5.7) SARS-CoV-2, 3.9 (95%CI 2.2, 5.6) influenza, 1.4 (95%CI 0.4, 2.4) RSV), declining to <0.3/100 tests after January for influenza/RSV, and around 2.5/100 tests for SARS-CoV-2. Over one-third of all infections were asymptomatic, and symptoms were similar for all viruses. 1,368 (23.3%) participants reported taking sick leave, median 4 days (range 1-59). Rates of sick leave were higher in participants with co-morbidities, working in clinical settings, and who had not been vaccinated (COVID-19 booster or seasonal influenza vaccine) versus those who had received neither vaccine (2.04 vs 1.41 sick days/100 days, adjusted Incidence Rate Ratio 1.47 (95%CI 1.38, 1.56).ConclusionThis pilot demonstrated the use of multiplex testing allowed better understanding of the impact of seasonal respiratory viruses and respective vaccines on the HCW workforce. This highlights the important information on asymptomatic infection and persisting levels of SARS-CoV-2 infection.
Exploring genetic risk factors for pneumonia using biobank resources - Insights across subpopulations
Authors: Heikkilä Anni , Sliz Eeva , Väyrynen Sara , Reis Kadri , Elnahas Abdelrahman G. , Reigo Anu , Esko Tõnu ,   Estonian Biobank Research Team,   FinnGen, Kettunen Johannes , Hautala Timo 
Published: December 2024

AbstractBackgroundPneumonia risk is influenced by demographics, chronic disease burden, lifestyle, and environmental factors. Despite genome-wide association studies (GWAS), the role of host genetics in pneumonia is still not fully understood, especially in certain subgroups.MethodsWe conducted a GWAS for pneumonia across FinnGen and Estonian Biobank (EstBB) (91,062 cases and 520,119 controls) populations. Cases with at least one pneumonia episode and subgroups based on the age at first pneumonia diagnosis, recurrent pneumonia, and asthma status were considered. We further estimated genetic correlations and causal relationships between pneumonia and other traits using linkage disequilibrium score regression and Mendelian randomization.ResultsWe identified 13 loci including 5 replicated (PTGER4, TNFRSF1A, CHRNA5, MUC5A, HLA) and 8 novel associations (PTPN22, CRP, APOE, FHIT, MAPKAPK2, TNFSF15, HNF1A, RIN3) mainly harboring genes regulating immunity or lung health associated with pneumonia across subgroups. Interestingly, novel associations included theAPOElocus with the ε4 allele having a protective effect on pneumonia. Additionally, we report genetic correlations between pneumonia and 204 other traits, and nine traits potentially causal to pneumonia risk.ConclusionsLoci associated with pneumonia harbour genes mainly related to acute inflammation, T cell development, antigen presentation and lung health. The stratified analyses demonstrate differences in genetic risk factors contributing to development of pneumonia in different patient subgroups. In summary, the findings of our study highlight the importance of immunological mechanisms at early life and in adults as well as significance of lifestyle and lung health among the elderly.
Integrative scRNA-seq and spatial transcriptomics uncovers distinct macrophage-fibroblast cross-talk in human hip synovium between patients with femoroacetabular impingement and osteoarthritis
Authors: Kulzhanova Gulzada , Klee Alexis , Botros Mina , Hansen Victoria L. , Reuter John , Tashbib Eliya Tazreena , Fadial Eloise , Ricciardi Benjamin F. , Giordano Brian , Wu Chia-Lung 
Published: December 2024

ABSTRACTFemoroacetabular impingement (FAI) and synovitis have been recognized as essential factors for developing osteoarthritis (OA) in the hip joints. However, little is known about altered synovial cellular compositions, their associated transcriptomic profiles, and cell-cell interactions between patients with FAI and hip OA. In the current study, by using integrative single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (Spatial-seq), we identified the molecular mechanisms by which synovial cells promote hip OA pathogenesis from FAI. Compared to FAI synovium, epiregulin (EREG)-enriched lining fibroblast-like synoviocytes (FLS) were significantly increased in the hip OA synovium. TheseEREG+FLS are pro-inflammatory due to their high expression ofCXCL1,IL8 (CXCL8), andMMPs. Furthermore, pseudotime analysis predicts thatEREG+FLS are potentially derived fromDPP4+PI16+sublining FLS. Importantly, analysis of cell-cell interactions indicates that fibroblast growth factor 2 (FGF2) secreted fromCOL1A1+IGFBP5+fibrotic macrophages may signal through syndecan 4 (SDC4) expressed byEREG+lining FLS, inducing the expression of IL6, IL8, MMP1, and PTGS2. The GO term analysis of activated genes downstream of FGF2-SDC4 signaling revealed that biological processes associated with inflammation and angiogenesis were upregulated in hip OA, while mechanical stimulus and skeletal muscle differentiation were dominant in FAI. Moreover, we also found thatEREG+CCL20+MMP3hilining FLS as well as most MΦ and monocyte populations are unique to hip OA patients when compared to knee OA and RA patients. The findings of this study offer a groundwork in tailoring novel targets and therapies for FAI and hip OA patients.