bluuebunny/crossref_metadata_2025_split huggingface dataset:
The bronchiectasis microbiome: current understanding and treatment implications
Authors: Narayana Jayanth Kumar , Mac Aogáin Micheál , Hansbro Philip M. , Chotirmall Sanjay H. 
Published: November 2024

Purpose of review
Advances in DNA sequencing and analysis of the respiratory microbiome highlight its close association with bronchiectasis phenotypes, revealing fresh opportunities for diagnosis, stratification, and personalized clinical intervention. An under-recognized condition, bronchiectasis is increasingly the subject of recent large-scale, multicentre, and longitudinal clinical studies including detailed analysis of the microbiome. In this review, we summarize recent progress in our understanding of the bronchiectasis microbiome within the context of its potential use in treatment decisions.

Recent findings
Diverse microbiome profiles exist in bronchiectasis, in line with the established disease heterogeneity including treatment response. Classical microbiology has established Pseudomonas aeruginosa and Haemophilus influenza as two microbial markers of disease, while holistic microbiome analysis has uncovered important associations with less common bacterial taxa including commensal an/or pathobiont species, including the emerging role of the fungal mycobiome, virome, and interactome. Integration of airway microbiomes with other high-dimensional biological and clinical datasets holds significant promise to determining treatable traits and mechanisms of disease related to the microbiome.

Summary
The bronchiectasis microbiome is an emerging and key area of study with significant implications for understanding bronchiectasis, influencing treatment decisions and ultimately improving patient outcomes.
The correlation of acupuncture and moxibustion points for the treatment of diminished ovarian reserve and premature ovarian failure: A systematic review based on complex network
Authors: Yang Zhihong , Zhu Zhou , Yang Xiaofang , Zhang Wei , Chen Panbi , Jin Linming , Luo Qiuping , Meng Yuqiong , Liu Jiamin 
Published: November 2024

Background:
Infertility rates have risen in recent years, with diminished ovarian reserve (DOR) affecting 10% of infertile women, accounting for approximately 20% of ovarian disorders. This highlights the importance of exploring effective treatments for DOR. This study investigates acupoint compatibility rules in acupuncture and moxibustion therapies for DOR and premature ovarian failure (POF) using complex network analysis. It also provides insights into acupuncture and moxibustion approaches for managing these conditions.

Methods:
Clinical studies on acupuncture and moxibustion treatments for DOR and POF were retrieved from 5 databases, including China National Knowledge Infrastructure, SinoMed, Wanfang, CQVIP, and PubMed, covering the period from January 1, 2007, to September 15, 2024. Literature was screened based on inclusion and exclusion criteria to build a comprehensive database of acupuncture and moxibustion prescriptions for these conditions. Association rule analysis was performed using IBM SPSS Modeler 18.0, and complex network analysis was conducted with Gephi 0.9.2 software.

Results:
A total of 70 articles and 67 acupoints from 70 prescriptions were analyzed, with 665 occurrences of these acupoints. The most frequently used acupoint was Guanyuan (RN4), followed by Sanyinjiao (SP6), Zusanli (ST36), Shenque (RN8), Bladder 23 (BL23), and Zigong (EX-CA1). These acupoints were primarily related to the Ren (RN) and Bladder (BL) meridians. Jiaohui points, dorsal Yu points, and 5 Shu points were the most commonly utilized specific points. The combination of Sanyinjiao (SP6) and Guanyuan (RN4) had the strongest association. Complex network analysis revealed a small-world network effect, with 24 core acupoints, including Guanyuan (RN4) and Zusanli (ST36), serving as key nodes.

Conclusion:
Acupuncture treatments for DOR and POF primarily focus on the abdomen and lower back regions. Specific acupoints, such as rendezvous points, are frequently combined with distantly located points. These combinations are guided by therapeutic principles aimed at nourishing the kidney, strengthening the spleen, regulating liver qi, calming the heart, and promoting blood circulation.
Early Telephone-Based Frailty Screening With the Vulnerable Elders Survey in Adults Aged 75 Years and Older With Lung and Gynecological Cancer
Authors: Cabrera-Jaime Sandra , Hernández-Marfil Anais , Adamuz-Tomas Jordi , Sánchez-Martín Silvia 
Published: November 2024

BackgroundThe International Society of Geriatric Oncology recommends that all older people with cancer have a geriatric evaluation before beginning treatment.ObjectiveTo determine the prevalence of frailty in people 75 years and older diagnosed with lung or gynecological cancer and evaluate the adaptation of standard therapeutic strategies based on frailty, following the implementation of telephone-based frailty screening with the Vulnerable Elders Survey (VES-13).Interventions/MethodsWe performed a retrospective observational study in 362 people screened by an advanced practice nurse before their first oncology appointment. We collected secondary data from electronic medical records. The main variables were degree of frailty (according to VES-13 and comprehensive geriatric assessment), type of cancer treatment (standard and prescribed), treatment completion, sociodemographic characteristics, and comorbidities.ResultsThe VES-13 detected 186 people (51.4%) at risk of health deterioration, and the comprehensive geriatric assessment confirmed some degree of frailty in 157 people (43.4%), with aκcoefficient of 0.84. People with more comorbidities, greater frailty, and more geriatric syndromes were more likely to need treatment readjustment (P< .001).ConclusionsTelephone-based frailty screening by an advanced practice nurse showed high applicability, with very good agreement between the proportion of people classified as frail before the initial visit and in the subsequent geriatric assessment.Implications for PracticeA protocol for establishing frailty risk through telephone screening by an advanced practice nurse facilitates the care process and helps clinicians adapt therapeutic decision-making to the needs of each patient and their family.
GHOSTS: Generation of synthetic hospital time series for clinical machine learning research
Authors: Zhumagambetov Rustam , Giesa Niklas , Boie Sebastian D. , Haufe Stefan 
Published: November 2024

AbstractMachine learning (ML) holds great promise to support, improve, and automatize clinical decision-making in hospitals. Data protection regulations, however, hinder abundantly available routine data from being shared across sites for model training. Generative models can overcome this limitation by learning to synthesize hospital data from a target population while ensuring data privacy. Clinical time series acquired during intensive care are, however, difficult to model using established techniques, especially due to uneven sampling intervals. Here we introduce GHOSTS (Generator of Hospital Time Series), a novel generator of synthetic patient trajectories that is capable of generating heterogeneous hospital data including realistic time series with uneven sampling intervals. We further design a suite of novel benchmarks, GHOSTS-Bench. We train GHOSTS on a large cohort of patient data from the MIMIC-IV critical care dataset and measure the quality of the generated data in terms of how faithfully the distributions of individual features in the real data are approximated, how well spatio-temporal dynamics in the multivariate time series are preserved, and how well ML models trained on the generated data can solve a clinical prediction task on the real data. We observe that GHOSTS outperforms a state-of-the-art approach, DoppelGANger, with respect to these criteria.
The Accumulation of Progerin Underlies the Loss of Aortic Smooth Muscle Cells in Hutchinson-Gilford Progeria Syndrome
Authors: Kim Paul H. , Kim Joonyoung R. , Heizer Patrick J. , Jung Hyesoo , Tu Yiping , Presnell Ashley , Scheithauer Julia , Yu Rachel G. , Young Stephen G. , Fong Loren G. 
Published: November 2024

AbstractHutchinson-Gilford progeria syndrome (HGPS) is a progeroid disorder characterized by multiple aging-like phenotypes, including disease in large arteries. HGPS is caused by an internally truncated prelamin A (progerin) that cannot undergo the ZMPSTE24-mediated processing step that converts farnesyl-prelamin A to mature lamin A; consequently, progerin retains a carboxyl-terminal farnesyl lipid anchor. In cultured cells, progerin and full-length farnesyl-prelamin A (produced inZmpste24−/–cells) form an abnormal nuclear lamin meshwork accompanied by nuclear membrane ruptures and cell death; however, these proteins differ in their capacity to cause arterial disease. In a mouse model of HGPS (LmnaG609G), progerin causes loss of aortic smooth muscle cells (SMCs) by ∼12 weeks of age. In contrast, farnesyl-prelamin A inZmpste24−/–mice does not cause SMC loss—even at 21 weeks of age. In young mice, aortic levels of farnesyl-prelamin A inZmpste24−/–mice and aortic levels of progerin inLmnaG609G/+mice are the same. However, the levels of progerin and other A-type lamins increase with age inLmnaG609G/+mice, whereas farnesyl-prelamin A and lamin C levels inZmpste24−/–mice remain stable.Lmnatranscript levels are similar, implying that progerin influences nuclear lamin turnover. We identified a likely mechanism. In cultured SMCs, the phosphorylation of Ser-404 by AKT (which triggers prelamin A degradation) is reduced in progerin. In mice, AKT activity is significantly lower inLmnaG609G/+aortas than in wild-type orZmpste24−/–aortas. Our studies identify that the accumulation of progerin inLmnaG609Gaortas underlies the hallmark arterial pathology in HGPS.One Sentence SummaryThe age-related accumulation of progerin in smooth muscle cells (SMCs) explains the loss of arterial SMCs in Hutchinson-Gilford progeria syndrome.
Counterfactual Diffusion Models for Mechanistic Explainability of Artificial Intelligence Models in Pathology
Authors: Žigutytė Laura , Lenz Tim , Han Tianyu , Hewitt Katherine J. , Reitsam Nic G. , Foersch Sebastian , Carrero Zunamys I. , Unger Michaela , Pearson Alexander T. , Truhn Daniel , Kather Jakob Nikolas 
Published: November 2024

AbstractBackgroundDeep learning can extract predictive and prognostic biomarkers from histopathology whole slide images, but its interpretability remains elusive.MethodsWe develop and validate MoPaDi (Morphing histoPathology Diffusion), which generates counterfactual mechanistic explanations. MoPaDi uses diffusion autoencoders to manipulate pathology image patches and flip their biomarker status by changing the morphology. Importantly, MoPaDi includes multiple instance learning for weakly supervised problems. We validate our method on four datasets classifying tissue types, cancer types within different organs, center of slide origin, and a biomarker – microsatellite instability. Counterfactual transitions were evaluated through pathologists’ user studies and quantitative cell analysis.ResultsMoPaDi achieves excellent image reconstruction quality (multiscale structural similarity index measure 0.966–0.992) and good classification performance (AUCs 0.76–0.98). In a blinded user study for tissue-type counterfactuals, counterfactual images were realistic (63.3–73.3% of original images identified correctly). For other tasks, pathologists identified meaningful morphological features from counterfactual images.ConclusionMoPaDi generates realistic counterfactual explanations that reveal key morphological features driving deep learning model predictions in histopathology, improving interpretability.
KOnezumi-AID: A Software to Automate the Design of Multiplex Knockouts Using Target-AID
Authors: Taki Taito , Morimoto Kento , Mizuno Seiya , Kuno Akihiro 
Published: November 2024

AbstractWith the groundbreaking advancements in genome editing technologies, particularly CRISPR-Cas9, creating knockout mutants has become highly efficient. However, the CRISPR-Cas9 system introduces DNA double-strand breaks, which can increase the risk of chromosomal rear-rangements, presenting a major obstacle when attempting to knockout multiple genes simultaneously. Base editing systems like Target-AID provide a safer alternative by enabling precise base modifications without requiring DNA double-strand breaks, making them a promising solution for addressing this challenge. Nevertheless, the absence of adequate tools to support Target-AID-based gene knockouts highlights the need for a comprehensive system to design guide RNA (gRNA) for the simultaneous knockout of multiple genes. Here, we present KOnezumi-AID, a command-line tool designed to facilitate gRNA design for Target-AID-mediated genome editing. KOnezumi-AID supports gene knockout strategies by inducing premature termination codons or promoting exon skipping. It generates experiment-ready gRNA designs for both mouse and human genomes. Additionally, KOnezumi-AID offers batch processing capabilities, enabling rapid and precise gRNA design for large-scale genome editing projects such as CRISPR screening. In summary, KOnezumi-AID provides an efficient and user-friendly tool for gRNA design, streamlining genome editing workflows and advancing gene knockout research.
AutoPM3: Enhancing Variant Interpretation via LLM-driven PM3 Evidence Extraction from Scientific Literature
Authors: Li Shumin , Wang Yiding , Liu Chi-Man , Huang Yuanhua , Lam Tak-Wah , Luo Ruibang 
Published: November 2024

AbstractRare diseases, affecting 300 million people globally, often result from genetic variants. Wholegenome sequencing has made variant detection more cost-effective, but interpreting these variants remains challenging. Current clinical practice combines quantitative evidence and literature, which is complex and time-consuming. We introduce AutoPM3, a method for automating the extraction of ACMG/AMP PM3 evidence from scientific literature using open-source LLMs. It combines an optimized RAG system for text comprehension and a TableLLM equipped with Text2SQL for data extraction. We evaluated AutoPM3 using our collected PM3-Bench, a dataset from ClinGen with 1,027 variant-publication pairs. AutoPM3 significantly outperformed other methods in variant hit andin transvariant identification, thanks to the four key modules. Additionally, we wrapped AutoPM3 with a user-friendly interface to enhance its accessibility. This study presents a powerful tool to improve rare disease diagnosis workflows by facilitating PM3-relevant evidence extraction from scientific literature.
Imaging Infants and Children with Investigational Handheld Optical Coherence Tomography with Widefield Lens: A Pilot Study
Authors: Li Angela S. , Imperio Ryan , Tran-Viet Du , Mangalesh Shwetha , Prakalapakorn S. Grace , Vajzovic Lejla , Maldonado Ramiro , Freedman Sharon F. , Chen Xi 
Published: November 2024

AbstractHandheld optical coherence tomography (OCT) systems have shown promises to provide detailed evaluation of the pediatric retina. It is less stressful for preterm infants compared to binocular indirect ophthalmoscopy and shows promises for screening for retinopathy of prematurity. There are currently only one commercially available non-contact handheld OCT systems, and no commercially available widefield handheld OCT systems. Here we report and evaluate the first use of the Theia Imaging Investigational handheld OCT system with widefield lens (T1-W, Theia Imaging, Durham, NC) in pediatric subjects. We compare the OCT en face view to handheld widefield or tabletop ultra-widefield fundus photographs and evaluate the ability to visualize the vitreoretinal interface, intraretinal, subretinal and choroidal features on cross-sectional OCT scans.
High-accuracy prediction of 5-year progression-free melanoma survival using spatial proteomics and few-shot learning on primary tissue
Authors: Möller Anna , Ostalecki Christian , Hartebrodt Anne , Breininger Katharina , Erdmann Michael , Uderhardt Stefan , Baur Andreas , Blumenthal David B. 
Published: November 2024

SUMMARYEmerging techniques in imaging-based spatial proteomics (ISP) enable in-depth insights into the architecture and protein abundance of tissue(s). Explainable machine learning (xML) models promise to yield substantial advances in ISP data-based diagnosis and prognosis. However, a clinical application of these new possibilities predicting the course of a tumor has not been suggested yet. Here, we use a few-shot learning workflow on histological multi-antigen images to predict 5-year progression-free survival (PFS) in melanoma. We address the problem of a relatively small cohort (n= 22), by utilizing a pre-trained convolutional neural network (CNN) model, which we further pre-train on a proxy task for which more samples were available (n= 39) before fine-tuning for PFS prediction. Our approach yielded a model achieving an accuracy of more than 90%, outperforming baseline models trained on clinical data by around 10%. Using an xML technique, we identified immune infiltration and proteins associated with tumor progression as crucial predictors. This indicated that our models’ PFS predictions are not only highly accurate but also grounded in a relevant biological background.
Comparative antioxidant activity ofOcimum gratissimumandJatropha tanjorensis2024
Authors: Ike Emmanuel Chukwuebuka , Wokota Paschal N. , Nnenna Gabez Lynda 
Published: November 2024

AbstractIntroductionThe leaves ofOcimum gratissimumandJatropha tanjorensisare widely used together as vegetables in food and in several preparations for medicinal purposes. For this reason, their combined antioxidant potentials were evaluated to ascertain if such preparations should be encouraged or otherwise in relation to their individual antioxidant effects.Materials and Methodsthe combined extract ofO.gratissimumandJ. tanjorensis(CEOJ) were serially diluted into different concentrations; concentrations of 1.9µg/ml, 3.91µg/ml, 7.81µg/ml, 15.63µg/ml, 31.25µg/ml, 62.5µg/ml, 125µg/ml and 250µg/ml were made and used for the assays. the single extracts were also diluted into similar concentrations. DPPH in methanol was used as blank for the DPPH-free radical scavenging assay. The absorbance of the concentrations and that of the controls were read at 517nm and 562nm for the DPPH assay using a spectrophotometer.ResultsThe result of the DPPH-free radical scavenging assay showed a synergistic antioxidant effects in CEOJ with an inhibition percentage of 71.39% higher thanJ. tanjorensisalone (66.80%)O. gratissimumalone (53.56%) and ascorbic acid (56%).ConclusionThis results therefore inferred that the CEOJ produced better antioxidant activity than when used as a separate extract.
Intelligence and Cognitive Flexibility Selectively Modulate Working Memory Functioning
Authors: Zhang Heming , Meng Chun , Xu Xinyu , Hu Xin , Zhang Ziqian , Klugah-Brown Benjamin , Biswal Bharat B. 
Published: November 2024

AbstractWorking memory is a key component of intelligence, which can be underpinned by task connectome, while cognitive flexibility plays a role in adaptive and executive function that supports working memory processes. However, it remains unknown how intelligence and cognitive flexibility modulate working memory functioning, in terms of behavioural performance and task-related brain hierarchy. Current study investigated the working memory task-related behaviour and brain connectomic gradient in healthy adults together with their intelligence and cognitive flexibility measures. Results showed cognitive flexibility and intelligence were not significantly correlated with each other but with working memory function. Principal component and partial least square analysis revealed that nearly half of variance was explained by their overlap component, which linked with task gradient values of frontoparietal and ventral attention network representing executive, control and cognitive functioning. Individuals with higher intelligence and cognitive flexibility showed less distance between frontoparietal/ventral attention network and unimodal regions in gradient axis during working memory performance. Further analyses demonstrated that task gradient of frontoparietal and ventral attention network was significantly associated with working memory function, and selectively mediated by cognitive flexibility and intelligence, which may suggest partly convergent neural mechanisms for higher order functions that are involved in working memory functioning. In conclusion, current study provides new insight into the relationship among task connectomic gradient, working memory, intelligence, and cognitive flexibility, which helps understand the multi-component model of working memory and underlying task gradient principle.
MethylGPT: a foundation model for the DNA methylome
Authors: Ying Kejun , Song Jinyeop , Cui Haotian , Zhang Yikun , Li Siyuan , Chen Xingyu , Liu Hanna , Eames Alec , McCartney Daniel L , Marioni Riccardo E. , Poganik Jesse R. , Moqri Mahdi , Wang Bo , Gladyshev Vadim N. 
Published: November 2024

AbstractDNA methylation serves as a powerful biomarker for disease diagnosis and biological age assessment. However, current analytical approaches often rely on linear models that cannot capture the complex, context-dependent nature of methylation regulation. Here we present MethylGPT, a transformer-based foundation model trained on 226,555 (154,063 after QC and deduplication) human methylation profiles spanning diverse tissue types from 5,281 datasets, curated 49,156 CpG sites, and 7.6 billion training tokens. MethylGPT learns biologically meaningful representations of CpG sites, capturing both local genomic context and higher-order chromosomal features without external supervision. The model demonstrates robust methylation value prediction (Pearson R=0.929) and maintains stable performance in downstream tasks with up to 70% missing data. Applied to age prediction across multiple tissue types, MethylGPT achieves superior accuracy compared to existing methods. Analysis of the model’s attention patterns reveals distinct methylation signatures between young and old samples, with differential enrichment of developmental and aging-associated pathways. When finetuned to mortality and disease prediction across 60 major conditions using 18,859 samples from Generation Scotland, MethylGPT achieves robust predictive performance and enables systematic evaluation of intervention effects on disease risks, demonstrating potential for clinical applications. Our results demonstrate that transformer architectures can effectively model DNA methylation patterns while preserving biological interpretability, suggesting broad utility for epigenetic analysis and clinical applications.
Critical assay parameters facilitating confident detection of expression changes, fusions and short variants in RNA isolated from tissue
Authors: Kubik Slawomir , Matyszczak Izabela , Toda Nicholas , Magrinelli Elia , Helleboid Pierre-Yves , Smith Ewan , Bezrukov Fedor , Ryder Chloe , Lopez Jonathan , Harlé Alexandre , Xu Zhenyu 
Published: November 2024

ABSTRACTMolecular assays based on next-generation sequencing of RNA can provide clinically relevant information by measuring gene expression levels, identifying gene fusions, aberrant transcript isoforms and detecting small variants. Nevertheless, achieving good performance and reliable result interpretation present a significant challenge.In this work, we dissect the impact of various technical factors on the concurrent detection of several biomarker types using a hybridization enrichment-based targeted RNA sequencing applied to a cohort of more than one hundred samples derived from diverse solid tumors.We demonstrate that several critical parameters inferred from the sequencing data should be controlled to interpret the results accurately. These include molecular coverage of reference genes as a proxy of RNA conversion, DNA content measure, and the extent of target molecular coverage. We summarize our findings with recommendations allowing maximum reliable information recovery from targeted RNA sequencing data.