Nature. 2025 Jan;637(8045):281-295. doi: 10.1038/s41586-024-08278-z. Epub 2025 Jan 8.

ABSTRACT

Microscopy and crystallography are two essential experimental methodologies for advancing modern science. They complement one another, with microscopy typically relying on lenses to image the local structures of samples, and crystallography using diffraction to determine the global atomic structure of crystals. Over the past two decades, computational microscopy, encompassing coherent diffractive imaging (CDI) and ptychography, has advanced rapidly, unifying microscopy and crystallography to overcome their limitations. Here, I review the innovative developments in CDI and ptychography, which achieve exceptional imaging capabilities across nine orders of magnitude in length scales, from resolving atomic structures in materials at sub-ångstrom resolution to quantitative phase imaging of centimetre-sized tissues, using the same principle and similar computational algorithms. These methods have been applied to determine the 3D atomic structures of crystal defects and amorphous materials, visualize oxygen vacancies in high-temperature superconductors and capture ultrafast dynamics. They have also been used for nanoscale imaging of magnetic, quantum and energy materials, nanomaterials, integrated circuits and biological specimens. By harnessing fourth-generation synchrotron radiation, X-ray-free electron lasers, high-harmonic generation, electron microscopes, optical microscopes, cutting-edge detectors and deep learning, CDI and ptychography are poised to make even greater contributions to multidisciplinary sciences in the years to come.

PMID:39780004 | DOI:10.1038/s41586-024-08278-z

Sci Rep. 2025 Jan 8;15(1):1265. doi: 10.1038/s41598-025-85608-9.

ABSTRACT

High-content analysis (HCA) holds enormous potential for drug discovery and research, but widely used methods can be cumbersome and yield inaccurate results. Noisy and redundant signals in cell images impede accurate deep learning-based image analysis. To address these issues, we introduce X-Profiler, a novel HCA method that combines cellular experiments, image processing, and deep learning modeling. X-Profiler combines the convolutional neural network and Transformer to encode high-content images, effectively filtering out noisy signals and precisely characterizing cell phenotypes. In comparative tests on drug-induced cardiotoxicity, mitochondrial toxicity classification, and compound classification, X-Profiler outperformed both DeepProfiler and CellProfiler, as two highly recognized and representative methods in this field. Our results demonstrate the utility and versatility of X-Profiler, and we anticipate its wide application in HCA for advancing drug development and disease research.

PMID:39779905 | DOI:10.1038/s41598-025-85608-9

NPJ Digit Med. 2025 Jan 8;8(1):15. doi: 10.1038/s41746-024-01329-9.

ABSTRACT

Accurate prognostication guides optimal clinical management in skin cancer. Merkel cell carcinoma (MCC) is the most aggressive form of skin cancer that often presents in advanced stages and is associated with poor survival rates. There are no personalized prognostic tools in use in MCC. We employed explainability analysis to reveal new insights into mortality risk factors for this highly aggressive cancer. We then combined deep learning feature selection with a modified XGBoost framework, to develop a web-based prognostic tool for MCC termed 'DeepMerkel'. DeepMerkel can make accurate personalised, time-dependent survival predictions for MCC from readily available clinical information. It demonstrated generalizability through high predictive performance in an international clinical cohort, out-performing current population-based prognostic staging systems. MCC and DeepMerkel provide the exemplar model of personalised machine learning prognostic tools in aggressive skin cancers.

PMID:39779875 | DOI:10.1038/s41746-024-01329-9

Sci Rep. 2025 Jan 8;15(1):1360. doi: 10.1038/s41598-024-84883-2.

ABSTRACT

The Hybrid-Brain Computer Interface (BCI) has shown improved performance, especially in classifying multi-class data. Two non-invasive BCI modules are combined to achieve an improved classification which are Electroencephalogram (EEG) and functional Near Infra-red Spectroscopy (fNIRS). Classifying contralateral and ipsilateral motor movements is found challenging among the other mental activity signals. The current work focuses on the performance of deep learning methods like - Convolutional Neural Networks (CNN) and Bidirectional Long-Short term memory (Bi-LSTM) in classifying a four-class motor execution of Right Hand, Left Hand, Right Arm and Left Arm taken from the CORE dataset. The model performance was evaluated using metrics such as Accuracy, F1 - score, Precision, Recall, AUC and ROC curve. The CNN and Hybrid CNN models have resulted in 98.3% and 99% accuracy respectively.

PMID:39779796 | DOI:10.1038/s41598-024-84883-2

BMC Pulm Med. 2025 Jan 8;25(1):9. doi: 10.1186/s12890-024-03459-y.

ABSTRACT

BACKGROUND: Acute exacerbation (AEx) of interstitial pneumonia is the most common lethal adverse event related to the pharmacological treatment of patients with lung cancer complicated with interstitial pneumonia. Although small cell lung cancer (SCLC) is linked to poor prognosis, it exhibits good response to chemotherapy. Few previous research studies have investigated the safety and efficacy of treatment for advanced SCLC complicated with idiopathic interstitial pneumonia (IIP). We conducted a single-arm phase II study to evaluate the safety and efficacy of carboplatin plus etoposide for the treatment of patients with SCLC complicated with IIP.

METHODS: Chemotherapy-naïve patients with advanced SCLC complicated with IIP were enrolled. Patients received carboplatin every 21-28 days at a dose of area under the curve 4-6 on day 1 and etoposide at a dose of 80-100 mg/m2 on days 1-3.

RESULTS: Thirty-one patients were enrolled between December 2009 and December 2022. A median of four cycles of carboplatin plus etoposide were administered. Acute exacerbation of idiopathic interstitial pneumonia was not observed; the rate of AEx was 0% (95% confidence interval [CI]: 0-9.6%, p = 0.038). The objective response rate was 83.9% (95% CI: 82.5-85.2). The median progression-free survival and overall survival were 5.9 (95% CI: 4.7-6.8) months and 14.0 (95% CI: 7.6-27.6) months, respectively. The 1-year survival rate was 61% (95% CI 41-76).

CONCLUSIONS: The carboplatin plus etoposide treatment was tolerable and effective in SCLC patients complicated with IIP.

PMID:39780119 | DOI:10.1186/s12890-024-03459-y

J Cell Mol Med. 2025 Jan;29(1):e70321. doi: 10.1111/jcmm.70321.

ABSTRACT

Pulmonary fibrosis is a pathological manifestation that occurs upon lung injury and subsequence aberrant repair with poor prognosis. However, current treatment is limited and does not distinguish different disease stages. Here, we aimed to study the differential functions of Axl, a receptor tyrosine kinase expressing on both macrophages and fibroblasts, in the whole course of pulmonary fibrosis. We used mice with Axl total knockout, conditionally knockout in macrophages or fibroblasts, or treating with Axl inhibitors in inflammation or fibrosis stages to examine the effect of temporary dysfunction of Axl on bleomycin (BLM)-induced pulmonary fibrosis. Primary bone marrow-derived monocytes and primary fibroblasts from mice were used for cell-type-specific studies. Lung tissue and plasma samples were collected from idiopathic pulmonary fibrosis (IPF) patients and healthy controls to assess the Axl levels. We found that Axl inhibited the M1 polarisation of macrophages; inhibition of Axl during acute phase exacerbated inflammatory response and subsequent pulmonary fibrosis. On the other hand, Axl promoted the proliferation and invasion of the fibroblasts, partially by accelerating the focal adhesion turnover; inhibiting Axl during the fibrotic phase significantly alleviated pulmonary fibrosis. Consistently, phosphorylated Axl levels increased in fibrotic foci in the lung sample of IPF patients. In contrast, the soluble Axl (sAxl) level decreased in their plasma as compared to healthy controls. These results indicate that Axl may sequentially and differentially regulate macrophages and fibroblasts in acute and fibrosis phases, implying the necessity of a stage-specific treatment for pulmonary fibrosis. In addition, the activated Axl on fibroblasts may be reflected by the lowered plasma sAxl level, which may act as a biomarker for IPF. Trial Registration: ClinicalTrials.gov identifier: NCT03730337.

PMID:39779468 | DOI:10.1111/jcmm.70321

Pharmacol Res. 2025 Jan 6:107587. doi: 10.1016/j.phrs.2025.107587. Online ahead of print.

ABSTRACT

Pulmonary fibrosis (PF) is a fatal disease with increasing incidence, poor prognosis, and unclear pathogenesis. Our previous research demonstrated the beneficial effects of the natural cyclopeptide Heterophyllin B (HB) in PF. However, the precise mechanism by which HB exerts its effects in PF remains unclear. Our study revealed HB's beneficial effects in alleviating PF symptoms and restoring the intestinal mucosal barrier. Subsequently, the microbiota-dependent antifibrotic efficacy of HB was verified using various delivery routes, antibiotic treatments, and faecal microbiota transplantation. Functionally, 16S rRNA sequencing, untargeted metabolomics, and co-incubation experiments revealed that the antifibrotic efficacy of HB was primarily contingent on the enrichment of Muribaculum intestinale and its metabolite, 3-hydroxybutyric acid. Mechanistically, indoleamine 2,3- dioxygenase 1 (IDO1)-mediated ferroptosis was identified as a pivotal process in initiating PF, and the anti-fibrotic efficacy of HB relies on suppressing IDO1-mediated ferroptosis. Conversely, IDO1 deficiency alleviated the symptoms of bleomycin-induced PF and ferroptosis in mice. Coincidentally, both IDO1 overexpression and ferroptosis were observed in the pulmonary tissue of patients with idiopathic PF. Collectively, this study revealed that HB alleviates PF by eliminating intestinal microecology and metabolism and highlights the feasibility of targeting IDO1 for PF treatment.

PMID:39778639 | DOI:10.1016/j.phrs.2025.107587

J Pain Symptom Manage. 2025 Jan 6:S0885-3924(25)00003-X. doi: 10.1016/j.jpainsymman.2024.12.023. Online ahead of print.

ABSTRACT

INTRODUCTION: Palliative care (PALC) is traditionally linked to end-of-life cancer care but also benefits advanced non-oncological diseases.

OBJECTIVES: This systematic review evaluated the impact of early PALC on quality of life (QOL), symptom management, advance care planning (ACP), and healthcare resource utilization (HRU) among non-oncological patients.

METHODS: PubMed, Web of Science, and Scopus databases were searched for randomized controlled trials and clinical studies published between January 2018 and April 2023. Participants were adult patients with non-oncological diseases exposed to PALC interventions compared to usual care. Outcomes included QOL, symptom management, ACP, and HRU. The risk of bias was assessed using Cochrane tools.

RESULTS: Seven studies were included involving 1118 patients. Early PALC positively affects pain interference and fatigue in heart failure (HF) patients and time until first readmission and days alive outside the hospital in end-stage liver disease (ESLD) patients. Benefits were noted in symptom burden for patients with Human Immunodeficiency Virus (HIV), anxiety and depression in stroke patients, and ACP in chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) patients. However, results for anxiety and depression in HF patients are inconsistent, and no significant differences in QOL were observed in HF, ESLD, IPF, and COPD. The intervention did not improve overall QOL in HIV.

CONCLUSIONS: The impact of early PALC on health outcomes in non-oncological diseases is inconsistent. Addressing barriers to early PALC integration and conducting further high-quality research are essential for optimizing care pathways and enhancing patient outcomes.

PMID:39778632 | DOI:10.1016/j.jpainsymman.2024.12.023

BMC Cancer. 2025 Jan 8;25(1):34. doi: 10.1186/s12885-025-13444-1.

ABSTRACT

BACKGROUND: Prostate cancer (PCa) is commonly occurred among males worldwide and its prognosis could be influenced by biochemical recurrence (BCR). MicroRNAs (miRNAs) are functional regulators in carcinogenesis, and miR-221-3p was reported as one of the significant candidates deregulated in PCa. However, its regulatory pattern in PCa BCR across literature reports was not consistent, and the targets and mechanisms in PCa malignant transition and BCR are less explored.

METHODS: In this study, an evidence-based and knowledge-guided approach was proposed to decipher the role and mechanism of miR-221-3p in PCa development. First, the literature-reported inconsistency between miR-221-3p and PCa BCR was quantitatively measured by meta-analysis. Then a knowledge-guided network strategy was applied to prioritize key targets of miR-221-3p in PCa progression based both on topological and functional characterization of genes in multi-omics miRNA-mRNA and protein-protein interaction networks. Finally, a key gene was computationally identified and experimentally validated using cell line and clinical samples through EdU assay, scratch assay, transwell assay, dual-luciferase reporter assay and the epithelial-to-mesenchymal transition (EMT)-related analysis.

RESULTS: Down-regulation of miR-221-3p was correlated with a lower biochemical recurrence-free survival (BRFS) in PCa (HR: 0.72, 95%, CI: 0.64-0.81, P < 0.00001). A significant down-regulation of miR-221-3p was observed in most of the PCa cells compared with the normal control. KPNA2 was identified as a key target of miR-221-3p and it was over-expressed in all the PCa cells and human PCa tissues. Moreover, elevated miR-221-3p inhibited the proliferation, migration, invasion, and EMT of PCa cells in vitro via directly and negatively mediating KPNA2 expression.

CONCLUSIONS: miR-221-3p down-regulation was a risk factor for PCa BRFS, and its over-expression could inhibit the malignant phenotype and EMT of PCa cells by directly targeting KPNA2. Translational and personalized applications of the findings will be conducted in the future.

PMID:39780096 | DOI:10.1186/s12885-025-13444-1

Nat Genet. 2025 Jan 6. doi: 10.1038/s41588-024-02025-w. Online ahead of print.

ABSTRACT

Convergent transcription, that is, the collision of sense and antisense transcription, is ubiquitous in mammalian genomes and believed to diminish RNA expression. Recently, antisense transcription downstream of promoters was found to be surprisingly prevalent. However, functional characteristics of affected promoters are poorly investigated. Here we show that convergent transcription marks an unexpected positively co-regulated promoter constellation. By assessing transcriptional dynamic systems, we identified co-regulated constituent promoters connected through a distinct chromatin structure. Within these cis-regulatory domains, transcription factors can regulate both constituting promoters by binding to only one of them. Convergent promoters comprise about a quarter of all active transcript start sites and initiate 5'-overlapping antisense RNAs-an RNA class believed previously to be rare. Visualization of nascent RNA molecules reveals convergent cotranscription at these loci. Together, our results demonstrate that co-regulated convergent promoters substantially expand the cis-regulatory repertoire, reveal limitations of the transcription interference model and call for adjusting the promoter concept.

PMID:39779959 | DOI:10.1038/s41588-024-02025-w

Nat Genet. 2025 Jan 8. doi: 10.1038/s41588-024-02036-7. Online ahead of print.

ABSTRACT

Single-cell genomics technologies have accelerated our understanding of cell-state heterogeneity in diverse contexts. Although single-cell RNA sequencing identifies rare populations that express specific marker transcript combinations, traditional flow sorting requires cell surface markers with high-fidelity antibodies, limiting our ability to interrogate these populations. In addition, many single-cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. In the present report, we addressed these limitations by developing Programmable Enrichment via RNA FlowFISH by sequencing (PERFF-seq), a scalable assay that enables scRNA-seq profiling of subpopulations defined by the abundance of specific RNA transcripts. Across immune populations (n = 184,126 cells) and fresh-frozen and formalin-fixed, paraffin-embedded brain tissue (n = 33,145 nuclei), we demonstrated that programmable sorting logic via RNA-based cytometry can isolate rare cell populations and uncover phenotypic heterogeneity via downstream, high-throughput, single-cell genomics analyses.

PMID:39779958 | DOI:10.1038/s41588-024-02036-7

Nat Genet. 2025 Jan 8. doi: 10.1038/s41588-024-02038-5. Online ahead of print.

ABSTRACT

The advent of single-molecule, long-read sequencing (LRS) technologies by Oxford Nanopore Technologies and Pacific Biosciences has revolutionized genomics, transcriptomics and, more recently, epigenomics research. These technologies offer distinct advantages, including the direct detection of methylated DNA and simultaneous assessment of DNA sequences spanning multiple kilobases along with their modifications at the single-molecule level. This has enabled the development of new assays for analyzing chromatin states and made it possible to integrate data for DNA methylation, chromatin accessibility, transcription factor binding and histone modifications, thereby facilitating comprehensive epigenomic profiling. Owing to recent advancements, alternative, nascent and translating transcripts can be detected using LRS approaches. This Review discusses LRS-based experimental and computational strategies for characterizing chromatin states and highlights their advantages over short-read sequencing methods. Furthermore, we demonstrate how various long-read methods can be integrated to design multi-omics studies to investigate the relationship between chromatin states and transcriptional dynamics.

PMID:39779955 | DOI:10.1038/s41588-024-02038-5

Nat Immunol. 2025 Jan 8. doi: 10.1038/s41590-024-02041-2. Online ahead of print.

ABSTRACT

Disease tolerance is an evolutionarily conserved host defense strategy that preserves tissue integrity and physiology without affecting pathogen load. Unlike host resistance, the mechanisms underlying disease tolerance remain poorly understood. In the present study, we investigated whether an adjuvant (β-glucan) can reprogram innate immunity to provide protection against influenza A virus (IAV) infection. β-Glucan treatment reduces the morbidity and mortality against IAV infection, independent of host resistance. The enhanced survival is the result of increased recruitment of neutrophils via RoRγt+ T cells in the lung tissue. β-Glucan treatment promotes granulopoiesis in a type 1 interferon-dependent manner that leads to the generation of a unique subset of immature neutrophils utilizing a mitochondrial oxidative metabolism and producing interleukin-10. Collectively, our data indicate that β-glucan reprograms hematopoietic stem cells to generate neutrophils with a new 'regulatory' function, which is required for promoting disease tolerance and maintaining lung tissue integrity against viral infection.

PMID:39779870 | DOI:10.1038/s41590-024-02041-2

Nature. 2025 Jan 8. doi: 10.1038/s41586-024-08383-z. Online ahead of print.

ABSTRACT

Plants lack specialized and mobile immune cells. Consequently, any cell type that encounters pathogens must mount immune responses and communicate with surrounding cells for successful defence. However, the diversity, spatial organization and function of cellular immune states in pathogen-infected plants are poorly understood1. Here we infect Arabidopsis thaliana leaves with bacterial pathogens that trigger or supress immune responses and integrate time-resolved single-cell transcriptomic, epigenomic and spatial transcriptomic data to identify cell states. We describe cell-state-specific gene-regulatory logic that involves transcription factors, putative cis-regulatory elements and target genes associated with disease and immunity. We show that a rare cell population emerges at the nexus of immune-active hotspots, which we designate as primary immune responder (PRIMER) cells. PRIMER cells have non-canonical immune signatures, exemplified by the expression and genome accessibility of a previously uncharacterized transcription factor, GT-3A, which contributes to plant immunity against bacterial pathogens. PRIMER cells are surrounded by another cell state (bystander) that activates genes for long-distance cell-to-cell immune signalling. Together, our findings suggest that interactions between these cell states propagate immune responses across the leaf. Our molecularly defined single-cell spatiotemporal atlas provides functional and regulatory insights into immune cell states in plants.

PMID:39779856 | DOI:10.1038/s41586-024-08383-z

Nature. 2025 Jan 8. doi: 10.1038/s41586-024-08391-z. Online ahead of print.

ABSTRACT

Transcriptional regulation, which involves a complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate to unseen cell types and conditions. Here we introduce GET (general expression transformer), an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types1,2. Relying exclusively on chromatin accessibility data and sequence information, GET achieves experimental-level accuracy in predicting gene expression even in previously unseen cell types3. GET also shows remarkable adaptability across new sequencing platforms and assays, enabling regulatory inference across a broad range of cell types and conditions, and uncovers universal and cell-type-specific transcription factor interaction networks. We evaluated its performance in prediction of regulatory activity, inference of regulatory elements and regulators, and identification of physical interactions between transcription factors and found that it outperforms current models4 in predicting lentivirus-based massively parallel reporter assay readout5,6. In fetal erythroblasts7, we identified distal (greater than 1 Mbp) regulatory regions that were missed by previous models, and, in B cells, we identified a lymphocyte-specific transcription factor-transcription factor interaction that explains the functional significance of a leukaemia risk predisposing germline mutation8-10. In sum, we provide a generalizable and accurate model for transcription together with catalogues of gene regulation and transcription factor interactions, all with cell type specificity.

PMID:39779852 | DOI:10.1038/s41586-024-08391-z

Nature. 2025 Jan 8. doi: 10.1038/s41586-024-08371-3. Online ahead of print.

ABSTRACT

Histone H3 monoaminylations at Gln5 represent an important family of epigenetic marks in brain that have critical roles in permissive gene expression1-3. We previously demonstrated that serotonylation4-10 and dopaminylation9,11-13 of Gln5 of histone H3 (H3Q5ser and H3Q5dop, respectively) are catalysed by transglutaminase 2 (TG2), and alter both local and global chromatin states. Here we found that TG2 additionally functions as an eraser and exchanger of H3 monoaminylations, including H3Q5 histaminylation (H3Q5his), which displays diurnally rhythmic expression in brain and contributes to circadian gene expression and behaviour. We found that H3Q5his, in contrast to H3Q5ser, inhibits the binding of WDR5, a core member of histone H3 Lys4 (H3K4) methyltransferase complexes, thereby antagonizing methyltransferase activities on H3K4. Taken together, these data elucidate a mechanism through which a single chromatin regulatory enzyme has the ability to sense chemical microenvironments to affect the epigenetic states of cells, the dynamics of which have critical roles in the regulation of neural rhythmicity.

PMID:39779849 | DOI:10.1038/s41586-024-08371-3

Nature. 2025 Jan 8. doi: 10.1038/s41586-024-08349-1. Online ahead of print.

ABSTRACT

Sequencing-based genetic tests have uncovered a vast array of BRCA2 sequence variants1. Owing to limited clinical, familial and epidemiological data, thousands of variants are considered to be variants of uncertain significance2-4 (VUS). Here we have utilized CRISPR-Cas9-based saturation genome editing in a humanized mouse embryonic stem cell line to determine the functional effect of VUS. We have categorized nearly all possible single nucleotide variants (SNVs) in the region that encodes the carboxylate-terminal DNA-binding domain of BRCA2. We have generated function scores for 6,551 SNVs, covering 96.4% of possible SNVs in exons 15-26 spanning BRCA2 residues 2479-3216. These variants include 1,282 SNVs that are categorized as missense VUS in the clinical variant database ClinVar, with 77.2% of these classified as benign and 20.4% classified as pathogenic using our functional score. Our assay provides evidence that 3,384 of the SNVs in the region are benign and 776 are pathogenic. Our classification aligns closely with pathogenicity data from ClinVar, orthogonal functional assays and computational meta predictors. We have integrated our embryonic stem cell-based BRCA2-saturation genome editing dataset with other available evidence and utilized the American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines for clinical classification of all possible SNVs. This classification is available as a sequence-function map and serves as a valuable resource for interpreting unidentified variants in the population and for physicians and genetic counsellors to assess BRCA2 VUS in patients.

PMID:39779848 | DOI:10.1038/s41586-024-08349-1

Sci Rep. 2025 Jan 8;15(1):1369. doi: 10.1038/s41598-025-85249-y.

ABSTRACT

Inflammatory bowel disease (IBD) is a multisystem condition that could affect the cutaneous systems, namely cutaneous extraintestinal manifestations (EIMs). It has been suggested that IBD is associated with erythema nodosum (EN), malignant melanoma (MM) and non-melanoma skin cancer (NMSC). However, the potential causal relationship between IBD and the mentioned above cutaneous EIMs is still unclear. This study aims to determine the effect of IBD on EN, MM and NMSC within a Mendelian randomization (MR) design. Summary-level data for IBD, EN, MM, NMSC were obtained from large-scale genome-wide association studies. We utilized five different methods, including the inverse variance weighted model (IVW), MR Egger, Weighted median, Simple mode, Weighted mode in the MR analysis, then the Cochran's Q test, the MR-Egger pleiotropy test, the MR-PRESSO global pleiotropy test and leave-one-out sensitivity test were used to evaluate the heterogeneity and pleiotropy of identified IVs. To further ensure the validity of our findings, we evaluated the strength of the instrumental variables using the F-statistic and estimated the statistical power of our study. Findings were verified using an independent validation dataset, as well as through different MR methods with different model assumptions. MR analysis suggested that genetically determined IBD had a detrimental causal effect on NMSC (IVW: odds ratio [OR] = 1.002037, 95% confidence interval [CI] = 1.0001150-1.003962, P = 0.03776677), but not on EN (IVW: [OR] = 1.0937191, 95% [CI] = 0.9685831-1.235022, P = 0.1484349) and MM (IVW: [OR] = 0.9998064, 95% [CI] = 0.9994885-1.000124, P = 0.2326482). Besides, a positive causal effect of IBD on NMSC was verified in an independent validation dataset (IVW: [OR] = 1.002651, 95% [CI] = 1.0006524-1.004654, P = 0.009307506). The present study corroborated the causal relationship between IBD and NMSC. In contrast, our results showed no evidence of a causal association of IBD on EN and MM. These findings provide new insights into increasing attention to patients with IBD to prevent concurrent NMSC.

PMID:39779820 | DOI:10.1038/s41598-025-85249-y

Sci Rep. 2025 Jan 8;15(1):1324. doi: 10.1038/s41598-024-83401-8.

ABSTRACT

This study aimed to address the limitations of conventional methods for measuring skeletal muscle mass for sarcopenia diagnosis by introducing an artificial intelligence (AI) system for direct computed tomography (CT) analysis. The primary focus was on enhancing simplicity, reproducibility, and convenience, and assessing the accuracy and speed of AI compared with conventional methods. A cohort of 3096 cases undergoing CT imaging up to the third lumbar (L3) level between 2011 and 2021 were included. Random division into preprocessing and sarcopenia cohorts was performed, with further random splits into training and validation cohorts for BMI_AI and Body_AI creation. Sarcopenia_AI utilizes the Skeletal Muscle Index (SMI), which is calculated as (total skeletal muscle area at L3)/(height)2. The SMI was conventionally measured twice, with the first as the AI label reference and the second for comparison. Agreement and diagnostic change rates were calculated. Three groups were randomly assigned and 10 images before and after L3 were collected for each case. AI models for body region detection (Deeplabv3) and sarcopenia diagnosis (EfficientNetV2-XL) were trained on a supercomputer, and their abilities and speed per image were evaluated. The conventional method showed a low agreement rate (κ coefficient) of 0.478 for the test cohort and 0.236 for the validation cohort, with diagnostic changes in 43% of cases. Conversely, the AI consistently produced identical results after two measurements. The AI demonstrated robust body region detection ability (intersection over Union (IoU) = 0.93), accurately detecting only the body region in all images. The AI for sarcopenia diagnosis exhibited high accuracy, with a sensitivity of 82.3%, specificity of 98.1%, and a positive predictive value of 89.5%. In conclusion, the reproducibility of the conventional method for sarcopenia diagnosis was low. The developed sarcopenia diagnostic AI, with its high positive predictive value and convenient diagnostic capabilities, is a promising alternative for addressing the shortcomings of conventional approaches.

PMID:39779762 | DOI:10.1038/s41598-024-83401-8

NPJ Biofilms Microbiomes. 2025 Jan 8;11(1):6. doi: 10.1038/s41522-024-00639-w.

ABSTRACT

This study aims to evaluate differences in gut microbiota structures between infertile women undergoing frozen embryo transfer (FET) with gestational diabetes mellitus (GDM) and healthy controls (HCs), and to identify potential markers. We comprehensively enrolled 193 infertile women undergoing FET (discovery cohort: 38 HCs and 31 GDM; validation cohort: 85 HCs and 39 GDM). Gut microbial profiles of the discovery cohort were investigated during the pre-pregnancy (Pre), first trimester (T1), and second trimester (T2). The microbial community in the HCs group remained relatively stable throughout the pregnancy, while the microbial structure alteration occurred in the GDM group during T2. A model based on ten bacteria and ten metabolites simultaneously was used to predict the risk of GDM developing in the pre-pregnancy state with the ROC value of 0.712. Algorithms on the basis of marker species and biochemical parameters can be used as effective tools for GDM risk evaluation before pregnancy.

PMID:39779730 | DOI:10.1038/s41522-024-00639-w