Sci Rep. 2025 Feb 12;15(1):5237. doi: 10.1038/s41598-025-89267-8.

ABSTRACT

Deep Neural Networks (DNNs) have been shown to be vulnerable to adversarial examples, significantly hindering the development of deep learning technologies in high-security domains. A key challenge is that current defense methods often lack universality, as they are effective only against certain types of adversarial attacks. This study addresses this challenge by focusing on analyzing adversarial examples through changes in model attention, and classifying attack algorithms into attention-shifting and attention-attenuation categories. Our main novelty lies in proposing two defense modules: the Feature Pyramid-based Attention Space-guided (FPAS) module to counter attention-shifting attacks, and the Attention-based Non-Local (ANL) module to mitigate attention-attenuation attacks. These modules enhance the model's defense capability with minimal intrusion into the original model. By integrating FPAS and ANL into the Wide-ResNet model within a boosting framework, we demonstrate their synergistic defense capability. Even when adversarial examples are embedded with patches, our models showed significant improvements over the baseline, enhancing the average defense rate by 5.47% and 7.74%, respectively. Extensive experiments confirm that this universal defense strategy offers comprehensive protection against adversarial attacks at a lower implementation cost compared to current mainstream defense methods, and is also adaptable for integration with existing defense strategies to further enhance adversarial robustness.

PMID:39939692 | DOI:10.1038/s41598-025-89267-8

Sci Rep. 2025 Feb 12;15(1):5202. doi: 10.1038/s41598-025-89219-2.

ABSTRACT

In this study, we investigated whether deep learning-based prediction of immediate implant placement is possible. Panoramic radiographs of 201 patients with 874 teeth (Group 1: 440 teeth difficult to place implant immediately after extraction, Group 2: 434 teeth possible of immediate implant placement after extraction) for extraction were evaluated for the training and testing of a deep learning model. DenseNet121, ResNet18, ResNet101, ResNeXt101, InceptionNetV3, and InceptionResNetV2 were used. Each model was trained using preprocessed dental data, and the dataset was divided into training, validation, and test sets to evaluate model performance. For each model, the sensitivity, precision, accuracy, balanced accuracy, and F1-score were all greater than 0.90. The results of this study confirm that deep-learning-based prediction of the possibility of immediate implant placement is possible at a fairly accurate level.

PMID:39939654 | DOI:10.1038/s41598-025-89219-2

Sci Rep. 2025 Feb 12;15(1):5173. doi: 10.1038/s41598-024-82405-8.

ABSTRACT

With the advent of new media, more people are turning to social media to share thoughts and emotions related to personal life experiences. We examined salient concerns of dementia caregivers on Twitter pre- and post-pandemic, aiming to shed light on how to better support and engage dementia caregivers post-COVID-19 pandemic. English tweets related to "dementia" and "caregiver" were extracted between 1st January 2013 and 31st December 2022. A supervised deep learning model (Bidirectional Encoder Representations from Transformers, BERT) was trained to select tweets describing individual's experience related to dementia caregiving. An unsupervised deep learning approach (BERT-based topic modelling) was applied to identify topics from selected tweets, with each topic further grouped into themes manually using thematic analysis. A total of 44,527 tweets were analysed, and stratified using the emergence of COVID-19 pandemic as a threshold. Three themes were derived: challenges of caregiving in dementia, strategies to inspire caregivers, and dementia-related stigmatization. Over time, there is a rising trend of tweets relating to dementia caregiving. Post-pandemic, challenges of caregiving remained the top discussed topic; with a notable increase in tweets related to dementia-related stigmatization (p < 0.001), especially in North America and other continents (and less so in Europe). The findings uncover a worrying trend of growing dementia-related stigmatization among the caregivers, manifested by caregivers internalizing publicly-held stigma and projecting negative stereotypes externally as a means to devalue others. The challenges faced by caregivers also remained a significant concern, highlighting the need for continued support and resources for caregivers even post-pandemic.

PMID:39939632 | DOI:10.1038/s41598-024-82405-8

Sci Rep. 2025 Feb 12;15(1):5300. doi: 10.1038/s41598-025-86777-3.

ABSTRACT

The quality control of investment casting remains a critical challenge due to defect detection, real-time processing, and data traceability inefficiencies. This study presents an innovative Blockchain-integrated IoT system for advanced inspection of casting defects, combining a ResNet-based deep learning model for defect detection and dimensional measurement with Blockchain technology to ensure data integrity and traceability. The system demonstrated a significant improvement in defect detection accuracy, achieving an F1-score of 0.94, alongside high data integrity (0.99) and traceability (0.98) metrics. Additionally, it processes each casting in an average of 2.3 s, supporting a throughput of 26 castings per minute. By addressing critical challenges in smart manufacturing, this approach enhances operational efficiency, regulatory compliance, and user confidence. While scalability and energy efficiency remain areas for improvement, the proposed method provides a transformative solution for Industry 4.0, fostering transparency and reliability in manufacturing processes.

PMID:39939622 | DOI:10.1038/s41598-025-86777-3

Environ Sci Pollut Res Int. 2025 Feb 13. doi: 10.1007/s11356-025-36087-y. Online ahead of print.

NO ABSTRACT

PMID:39939571 | DOI:10.1007/s11356-025-36087-y

J Imaging Inform Med. 2025 Feb 12. doi: 10.1007/s10278-025-01431-8. Online ahead of print.

ABSTRACT

Accurate vocal fold (VF) pose estimation is crucial for diagnosing larynx diseases that can eventually lead to VF paralysis. The videoendoscopic examination is used to assess VF motility, usually estimating the change in the anterior glottic angle (AGA). This is a subjective and time-consuming procedure requiring extensive expertise. This research proposes a deep learning framework to estimate VF pose from laryngoscopy frames acquired in the actual clinical practice. The framework performs heatmap regression relying on three anatomically relevant keypoints as a prior for AGA computation, which is estimated from the coordinates of the predicted points. The assessment of the proposed framework is performed using a newly collected dataset of 471 laryngoscopy frames from 124 patients, 28 of whom with cancer. The framework was tested in various configurations and compared with other state-of-the-art approaches (direct keypoints regression and glottal segmentation) for both pose estimation, and AGA evaluation. The proposed framework obtained the lowest root mean square error (RMSE) computed on all the keypoints (5.09, 6.56, and 6.40 pixels, respectively) among all the models tested for VF pose estimation. Also for the AGA evaluation, heatmap regression reached the lowest mean average error (MAE) ( 5 . 87 ∘ ). Results show that relying on keypoints heatmap regression allows to perform VF pose estimation with a small error, overcoming drawbacks of state-of-the-art algorithms, especially in challenging images such as pathologic subjects, presence of noise, and occlusion.

PMID:39939476 | DOI:10.1007/s10278-025-01431-8

Sci Rep. 2025 Feb 13;15(1):5319. doi: 10.1038/s41598-025-89732-4.

ABSTRACT

Complex behavior is supported by the coordination of multiple brain regions. How do brain regions coordinate absent a homunculus? We propose coordination is achieved by a controller-peripheral architecture in which peripherals (e.g., the ventral visual stream) aim to supply needed inputs to their controllers (e.g., the hippocampus and prefrontal cortex) while expending minimal resources. We developed a formal model within this framework to address how multiple brain regions coordinate to support rapid learning from a few example images. The model captured how higher-level activity in the controller shaped lower-level visual representations, affecting their precision and sparsity in a manner that paralleled brain measures. In particular, the peripheral encoded visual information to the extent needed to support the smooth operation of the controller. Alternative models optimized by gradient descent irrespective of architectural constraints could not account for human behavior or brain responses, and, typical of standard deep learning approaches, were unstable trial-by-trial learners. While previous work offered accounts of specific faculties, such as perception, attention, and learning, the controller-peripheral approach is a step toward addressing next generation questions concerning how multiple faculties coordinate.

PMID:39939457 | DOI:10.1038/s41598-025-89732-4

Eur Radiol. 2025 Feb 13. doi: 10.1007/s00330-025-11422-6. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to develop a Hashimoto's thyroiditis nodule-artificial intelligence (HTN-AI) model to optimize the diagnosis of thyroid nodules with Hashimoto's thyroiditis (HT) of which the efficiency and accuracy remain challenging.

DESIGN AND METHODS: This study included 5709 patients from 10 hospitals between January 2014 and March 2024. Among them, 5053 thyroid nodules were divided into training and testing sets in a 9:1 ratio. Then, we tested the model on an external dataset (n = 432). Finally, we prospectively recruited 224 patients with dynamic ultrasound videos acquired and employed the HTN-AI model to identify nodules from the dynamic ultrasound videos. Radiologists of varying seniority performed the categorization of thyroid nodules as benign and malignant, both with and without the assistance of the HTN-AI model, and their diagnostic performances were compared.

RESULTS: The results indicated that for the external testing set, the HTN-AI model achieved a Dice similarity coefficient (DSC) of 0.91, outperforming several other common convolutional neural network (CNN) models. Specifically, the DSCs of the HTN-AI model were similar for thyroid nodule patients with and without HT which were 0.91 ± 0.06 and 0.91 ± 0.09. Moreover, when the HTN-AI model was used to assist diagnosis, it demonstrated an improvement in the diagnostic performance of radiologists. The diagnostic areas under the receiver operating characteristic curve (AUCs) of the junior radiologists increased from 0.59, 0.59, and 0.57 to 0.68, 0.65, and 0.65.

CONCLUSIONS: This research demonstrates that the HTN-AI model has excellent performance in identifying thyroid nodules associated with HT and can assist radiologists with more accurate and efficient diagnoses of thyroid nodules.

KEY POINTS: Question The study developed an HTN-AI model aimed at assisting in the diagnosis of thyroid nodules in patients with HT. Findings The HTN-AI model achieved great performance with a Dice similarity coefficient (DSC) of 0.91, and consistent performance across patients with and without HT. Clinical relevance The HTN-AI model enhances the accuracy and efficiency of thyroid nodule diagnosis, particularly in patients with HT. By assisting radiologists at varying experience levels, this model supports improved decision-making in the management of thyroid nodules.

PMID:39939425 | DOI:10.1007/s00330-025-11422-6

J Proteomics. 2025 Feb 10:105400. doi: 10.1016/j.jprot.2025.105400. Online ahead of print.

NO ABSTRACT

PMID:39938635 | DOI:10.1016/j.jprot.2025.105400

Respir Investig. 2025 Feb 11;63(3):241-246. doi: 10.1016/j.resinv.2025.01.008. Online ahead of print.

ABSTRACT

BACKGROUND: The 6-min walk test (6MWT), used to monitor disease progression or exacerbation in interstitial lung disease, faces challenges such as requiring a 30-m walking path and difficulty assessing patients with gait disturbance. The 1-min sit-to-stand test (1STST) offers a convenient alternative, potentially addressing these issues. Despite its advantages, the effectiveness of the 1STST in patients with idiopathic pulmonary fibrosis (IPF) and progressive pulmonary fibrosis (PPF) still needs to be explored. We assessed 1STST's ability to detect exercise-induced desaturation in a randomized, crossover trial involving patients with IPF or PPF.

METHODS: Participants were divided into group A (6MWT to 1STST) and B (1STST to 6MWT), with a 30-min rest period between the tests. The primary endpoint was the difference in nadir oxygen saturation (SpO2) between the groups throughout the study. Secondary endpoints included the percentage of participants with a nadir SpO₂ <88% during the tests, a decline of ≥4% in SpO2, and the variation in Borg scores post-tests.

RESULTS: Twenty-three participants (91.3% male; mean age ± standard deviation: 77.2 ± 7.4 years) diagnosed with IPF and PPF were enrolled in this study. The difference in nadir SpO2 between the 1STST and 6MWT was 1.14% (95% confidence interval: -0.18, 2.48), with the 95% confidence intervals falling within the predefined equivalence range. No significant differences were observed in the secondary endpoints.

CONCLUSIONS: The results suggest that the 1STST is as effective as the 6MWT in detecting desaturation in patients with IPF and PPF.

TRIAL REGISTRATION: This study was registered on the website of the Japan Registry of Clinical Trials (jRCT1032230037; URL: https://jrct.niph.go.jp/).

PMID:39938407 | DOI:10.1016/j.resinv.2025.01.008

Nature. 2025 Feb 12. doi: 10.1038/s41586-024-08533-3. Online ahead of print.

ABSTRACT

Cancer mutations can create neomorphic protein-protein interactions to drive aberrant function1,2. As a substrate receptor of the CULLIN3-RING E3 ubiquitin ligase complex, KBTBD4 is recurrently mutated in medulloblastoma3, the most common embryonal brain tumour in children4. These mutations impart gain-of-function to KBTBD4 to induce aberrant degradation of the transcriptional corepressor CoREST5. However, their mechanism remains unresolved. Here we establish that KBTBD4 mutations promote CoREST degradation through engaging HDAC1/2 as the direct target of the mutant substrate receptor. Using deep mutational scanning, we chart the mutational landscape of the KBTBD4 cancer hotspot, revealing distinct preferences by which insertions and substitutions can promote gain-of-function and the critical residues involved in the hotspot interaction. Cryo-electron microscopy analysis of two distinct KBTBD4 cancer mutants bound to LSD1-HDAC1-CoREST reveals that a KBTBD4 homodimer asymmetrically engages HDAC1 with two KELCH-repeat β-propeller domains. The interface between HDAC1 and one of the KBTBD4 β-propellers is stabilized by the medulloblastoma mutations, which insert a bulky side chain into the HDAC1 active site pocket. Our structural and mutational analyses inform how this hotspot E3-neosubstrate interface can be chemically modulated. First, we unveil a converging shape-complementarity-based mechanism between gain-of-function E3 mutations and a molecular glue degrader, UM171. Second, we demonstrate that HDAC1/2 inhibitors can block the mutant KBTBD4-HDAC1 interface and proliferation of KBTBD4-mutant medulloblastoma cells. Altogether, our work reveals the structural and mechanistic basis of cancer mutation-driven neomorphic protein-protein interactions.

PMID:39939763 | DOI:10.1038/s41586-024-08533-3

Nature. 2025 Feb 12. doi: 10.1038/s41586-024-08532-4. Online ahead of print.

ABSTRACT

UM171 is a potent agonist of ex vivo human haematopoietic stem cell self-renewal1. By co-opting KBTBD4, a substrate receptor of the CUL3-RING E3 ubiquitin ligase (CRL3) complex, UM171 promotes the degradation of the LSD1-CoREST corepressor complex, thereby limiting haematopoietic stem cell attrition2,3. However, the direct target and mechanism of action of UM171 remain unclear. Here we show that UM171 acts as a molecular glue to induce high-affinity interactions between KBTBD4 and HDAC1/2 to promote corepressor degradation. Through proteomics and chemical inhibitor studies, we identify the principal target of UM171 as HDAC1/2. Cryo-electron microscopy analysis of dimeric KBTBD4 bound to UM171 and the LSD1-HDAC1-CoREST complex identifies an asymmetric assembly in which a single UM171 molecule enables a pair of KELCH-repeat propeller domains to recruit the HDAC1 catalytic domain. One KBTBD4 propeller partially masks the rim of the HDAC1 active site, which is exploited by UM171 to extend the E3-neosubstrate interface. The other propeller cooperatively strengthens HDAC1 binding through a distinct interface. The overall CoREST-HDAC1/2-KBTBD4 interaction is further buttressed by the endogenous cofactor inositol hexakisphosphate, which acts as a second molecular glue. The functional relevance of the quaternary complex interaction surfaces is demonstrated by base editor scanning of KBTBD4 and HDAC1. By delineating the direct target of UM171 and its mechanism of action, we reveal how the cooperativity offered by a dimeric CRL3 E3 can be leveraged by a small molecule degrader.

PMID:39939761 | DOI:10.1038/s41586-024-08532-4

Sci Rep. 2025 Feb 12;15(1):5204. doi: 10.1038/s41598-025-89882-5.

ABSTRACT

Patients with triple negative breast cancer (TNBC) show only modest response rates to immune checkpoint inhibitor immunotherapy, motivating ongoing efforts to identify approaches to boost efficacy. Using an immunocompetent mouse model of TNBC, we investigated combination therapy with an anti-PD-1 immunotherapy antibody plus balixafortide, a cyclic peptide inhibitor of CXCR4. Cell-based assays demonstrated that balixafortide functions as an inverse agonist, establishing a mode of action distinct from most compounds targeting CXCR4. Combination anti-PD-1 plus balixafortide significantly reduced growth of orthotopic tumors and extended overall survival relative to single agent therapy or vehicle. Adding balixafortide to anti-PD-1 increased numbers of tertiary lymphoid structures, a marker of local tumor immune responses associated with favorable response to immunotherapy in TNBC. Single cell RNA sequencing revealed that combination anti-PD-1 plus balixafortide reduced T cell exhaustion and increased markers of effector T cell activity. Combination therapy also reduced signatures of immunosuppressive myeloid derived suppressor cells (MDSCs) in tumors. MDSCs isolated from mice treated with anti-PD-1 plus balixafortide showed reduced inhibition of T cell proliferation following ex vivo stimulation. These studies demonstrate that combining inhibition of CXCR4 with anti-PD-1 to enhances responses to checkpoint inhibitor immunotherapy in TNBC, supporting future clinical trials.

PMID:39939722 | DOI:10.1038/s41598-025-89882-5

Nat Methods. 2025 Feb 12. doi: 10.1038/s41592-024-02579-x. Online ahead of print.

ABSTRACT

The ideal technology for directly investigating the relationship between genotype and phenotype would analyze both RNA and DNA genome-wide and with single-cell resolution; however, existing tools lack the throughput required for comprehensive analysis of complex tumors and tissues. We introduce a highly scalable method for jointly profiling DNA and expression following nucleosome depletion (DEFND-seq). In DEFND-seq, nuclei are nucleosome-depleted, tagmented and separated into individual droplets for messenger RNA and genomic DNA barcoding. Once nuclei have been depleted of nucleosomes, subsequent steps can be performed using the widely available 10x Genomics droplet microfluidic technology and commercial kits. We demonstrate the production of high-complexity mRNA and gDNA sequencing libraries from thousands of individual nuclei from cell lines, fresh and archived surgical specimens for associating gene expression with both copy number and single-nucleotide variants.

PMID:39939719 | DOI:10.1038/s41592-024-02579-x

Nat Commun. 2025 Feb 12;16(1):1561. doi: 10.1038/s41467-025-56873-z.

ABSTRACT

Drug-resistant bacteria pose an urgent global health threat, necessitating the development of antibacterial compounds with novel modes of action. Protein biosynthesis accounts for up to half of the energy expenditure of bacterial cells, and consequently inhibiting the efficiency or fidelity of the bacterial ribosome is a major target of existing antibiotics. Here, we describe an alternative mode of action that affects the same process: allowing translation to proceed but causing co-translational aggregation of the nascent peptidic chain. We show that treatment with an aggregation-prone peptide induces formation of polar inclusion bodies and activates the SsrA ribosome rescue pathway in bacteria. The inclusion bodies contain ribosomal proteins and ribosome hibernation factors, as well as mRNAs and cognate nascent chains of many proteins in amyloid-like structures, with a bias for membrane proteins with a fold rich in long-range beta-sheet interactions. The peptide is bactericidal against a wide range of pathogenic bacteria in planktonic growth and in biofilms, and reduces bacterial loads in mouse models of Escherichia coli and Acinetobacter baumannii infections. Our results indicate that disrupting protein homeostasis via co-translational aggregation constitutes a promising strategy for development of broad-spectrum antibacterials.

PMID:39939597 | DOI:10.1038/s41467-025-56873-z

Nat Commun. 2025 Feb 12;16(1):1585. doi: 10.1038/s41467-025-56858-y.

ABSTRACT

Biophysical cues play a crucial role in T cell biology, yet their implications in adoptive T cell therapy (ACT) remain largely unknown. Here, we investigate the effect of electrical stimuli on CD8+ T cells using a charged substrate composed of electroactive nanocomposites with tunable surface charge intensities. Electrical stimuli enhance the persistence and tumor-suppressive efficacy of transferred T cells, with effects dependent on substrate charge. Single-cell RNA-sequencing analysis unveils a decrease in virtual memory T (Tvm) cells and an increase in proliferative potential T (Tpp) cells, which exhibit superior antitumor activity and metabolic adaptations relative to those treated with uncharged substrate. ATAC-seq profiling demonstrates heightened accessibility at upstream binding sites for EGR1, a transcription factor critical for Tpp cell differentiation. Mechanistically, the charged substrate disrupts ionic TCR-lipid interactions, amplifies TCR signaling, and activates EGR1, thereby impeding Tvm polarization during ex vivo culture. Our findings thus highlight the importance of extracellular electrical stimuli in shaping T cell fate, offering potential for optimizing ACT for therapeutic applications.

PMID:39939595 | DOI:10.1038/s41467-025-56858-y

Antiviral Res. 2025 Feb 10:106099. doi: 10.1016/j.antiviral.2025.106099. Online ahead of print.

ABSTRACT

The emergence of new human viruses with epidemic or pandemic potential has reaffirmed the urgency to develop effective broad-spectrum antivirals (BSAs) as part of a strategic framework for pandemic prevention and preparedness. To this end, the host nucleotide metabolic pathway has been subject to intense investigation in the search for host-targeting agents (HTAs) with potential BSA activity. In particular, human dihydroorotate dehydrogenase (hDHODH), a rate-limiting enzyme in the de novo pyrimidine biosynthetic pathway, has been identified as a preferential target of new HTAs. Viral replication in fact relies on cellular pyrimidine replenishment, making hDHODH an ideal HTA target. The depletion of the host pyrimidine pool that ensues the pharmacological inhibition of hDHODH activity elicits effective BSA activity through three distinct mechanisms: it blocks viral DNA and RNA synthesis; it activates effector mechanisms of the host innate antiviral response; and it mitigates the virus-induced inflammatory response. However, despite the spectacular results obtained in vitro, the hDHODH inhibitors examined as mono-drug therapies in animal models of human viral infections and in clinical trials have produced disappointing levels of overall antiviral efficacy. To overcome this inherent limitation, pharmacological strategies based on multi-drug combination treatments should be considered to enable efficacy of hDHODH-targeted antiviral therapies. Here, we review the state-of-the-art of antiviral applications of hDHODH inhibitors, discuss the challenges that have emerged from their testing in animal models and human clinical trials and consider how they might be addressed to advance the development of hDHODH inhibitors as BSA for the treatment of viral diseases.

PMID:39938808 | DOI:10.1016/j.antiviral.2025.106099

J Ethnopharmacol. 2025 Feb 10:119479. doi: 10.1016/j.jep.2025.119479. Online ahead of print.

ABSTRACT

ETHNOPHARMACOLOGICAL RELEVANCE: Huachansu (HCS), a traditional Chinese medicine (TCM), has been used as an adjuvant therapy for colorectal cancer (CRC). However, its underlying mechanisms for combating CRC require further investigation.

AIM OF THIS STUDY: To comprehensively evaluate the anti-CRC effects of HCS and elucidate its underlying mechanisms, with a focus on elucidating the key pathways and targets involved.

MATERIALS AND METHODS: A series of cell experiments and xenograft tumor models were used to evaluate the inhibitory effects of HCS. The key components and potential targets of HCS against CRC were identified through network pharmacology and molecular docking. To further investigate the mechanisms, transcriptomics and proteomics were integrated, and the findings were supported by systematic pharmacological validation. Finally, the efficacy of HCS was further confirmed in CRC Patients-derived organoid and orthotopic models.

RESULTS: HCS could inhibit proliferation, disrupt the cell cycle, induce apoptosis of CRC cells, and suppress the growth of CRC xenograft tumors. Then eight components and six proteins (PIK3CA, CTNNB1, TP53, AKT1, CCND1, and CDH1) were identified as critical for HCS's anti-CRC activity. Notably, HCS inhibited the PI3K/AKT signaling pathway and glycolysis in CRC cells, with these findings validated in both in vitro and in vivo models. Additionally, HCS reduced growth in CRC patient-derived organoids and orthotopic models.

CONCLUSION: This study elucidates the mechanisms of HCS to combat CRC, offering a valuable reference for future clinical applications. It also presents a distinctive strategy for exploring TCM formulations' active components and effective mechanisms.

PMID:39938766 | DOI:10.1016/j.jep.2025.119479

Cell Syst. 2025 Feb 6:101171. doi: 10.1016/j.cels.2025.101171. Online ahead of print.

ABSTRACT

Cells of the immune system operate in dynamic microenvironments where the timing, concentration, and order of signaling molecules constantly change. Despite this complexity, immune cells manage to communicate accurately and control inflammation and infection. It is unclear how these dynamic signals are encoded and decoded and if individual cells retain the memory of past exposure to inflammatory molecules. Here, we use live-cell analysis, ATAC sequencing, and an in vivo model of sepsis to show that sequential inflammatory signals induce memory in individual macrophages through reprogramming the nuclear factor κB (NF-κB) network and the chromatin accessibility landscape. We use transcriptomic profiling and deep learning to show that transcription factor and chromatin dynamics coordinate fine-tuned macrophage responses to new inflammatory signals. This work demonstrates how macrophages retain the memory of previous signals despite single-cell variability and elucidates the mechanisms of signal-induced memory in dynamic inflammatory conditions like sepsis.

PMID:39938520 | DOI:10.1016/j.cels.2025.101171

Immunity. 2025 Feb 11;58(2):265-267. doi: 10.1016/j.immuni.2025.01.012. Epub 2025 Feb 11.

ABSTRACT

Renowned for driving interferon responses, the cGAS-STING pathway reveals a surprising role: lysosomal biogenesis. In this issue of Immunity, Xu et al. uncover how STING activates the transcription factor TFEB, linking innate immune sensing to enhanced pathogen clearance through lysosomal activity.

PMID:39938477 | DOI:10.1016/j.immuni.2025.01.012