Stem Cell Reports. 2025 Feb 8:102419. doi: 10.1016/j.stemcr.2025.102419. Online ahead of print.

ABSTRACT

Naive human pluripotent stem cells (hPSCs) model the pre-implantation epiblast. However, parent-specific epigenetic marks (imprints) are eroded in naive hPSCs, which represents an important deviation from the epiblast in vivo. To track the dynamics of imprint erasure during naive resetting in real time, we established a dual-colored fluorescent reporter at both alleles of the imprinted SNRPN locus. During primed-to-naive resetting, SNRPN expression becomes biallelic in most naive cells, and biallelic SNRPN expression is irreversible upon re-priming. We utilized this live-cell reporter to evaluate chemical and genetic strategies to minimize imprint erasure. Decreasing the level of MEK/ERK inhibition or overexpressing the KRAB zinc-finger protein ZFP57 protected a subset of imprints during naive resetting. Combining these two strategies protected imprint levels to a further extent than either strategy alone. This study offers an experimental tool to track and enhance imprint stability during transitions between human pluripotent states in vitro.

PMID:39952244 | DOI:10.1016/j.stemcr.2025.102419

Food Chem. 2025 Feb 10;475:143323. doi: 10.1016/j.foodchem.2025.143323. Online ahead of print.

ABSTRACT

Triterpenoid saponins, bioactive compounds with pharmaceutical relevance and functional food potential, are abundant in tea plants (Camellia sinensis), yet their structural diversity and tissue-specific distribution remain insufficiently explored. Using high-resolution mass spectrometry, Feature-based Molecular Networking, and imaging mass spectrometry (IMS), we profiled 52 tea saponins, including two novel trisaccharide saponins with unique glycosylation patterns. Aerial tissues, particularly buds and leaves, were enriched with cinnamoyl-decorated tetrasaccharide saponins, whereas roots predominantly accumulated di- and trisaccharide saponins, with significant cultivar-specific variation. IMS further revealed a compartmentalized root distribution, with di- and trisaccharide saponins localized in the epidermis and cortex, while tetrasaccharide saponins were concentrated in the stele. These findings advance understanding of the structural complexity and spatial accumulation of tea saponins, offering insights for bioactive compound extraction and informing breeding strategies to enhance saponin yield and diversity.

PMID:39952190 | DOI:10.1016/j.foodchem.2025.143323

Pediatr Radiol. 2025 Feb 14. doi: 10.1007/s00247-025-06182-w. Online ahead of print.

ABSTRACT

Tuberculosis (TB) remains a significant public health concern despite preventive measures, such as the use of the Bacille Calmette-Guérin (BCG) vaccine, which reduces the risk and severity of early-life TB infection. The adverse effects of the BCG vaccine include infection by the live-attenuated organism, more commonly seen in the immunocompromised host. This pictorial review aims to outline the imaging spectrum of BCG-vaccine-related infections in immunocompromised pediatric patients, which can be localized (BCGitis) or disseminated (BCGosis). We illustrate the more common imaging findings, including lymphadenopathy and involvement of solid organs, as well as less frequently encountered sites, such as the lungs and gastrointestinal tract, emphasizing their distinct imaging patterns. Interpretation of these findings in the context of prior administration of the BCG vaccine not only helps in the diagnosis of BCG-vaccine-related infections and guiding timely management, but can also be an early indicator of an underlying immunodeficiency disorder, prompting comprehensive immunological investigation.

PMID:39953302 | DOI:10.1007/s00247-025-06182-w

PLoS One. 2025 Feb 14;20(2):e0316721. doi: 10.1371/journal.pone.0316721. eCollection 2025.

ABSTRACT

BACKGROUND: Non-cystic fibrosis bronchiectasis (NCFBE) is a disease that exhibits dilatation of airways, airflow obstruction, persistent cough, excessive sputum production, and refractory respiratory infections. NCFBE exhibits clinical and pathological manifestations similar to key features of cystic fibrosis (CF) lung disease. In CF, pathogenesis results from dysfunction of the cystic fibrosis transmembrane conductance regulator (CFTR), and diagnosis is made by demonstrating elevated sweat chloride concentrations (typically ≥60 mEq/L), two CFTR mutations known to be causal, multi-organ tissue injury, or combination(s) of these findings.

OBJECTIVE: Based on a considerable body of evidence, we believe many patients with NCFBE have disease likely to benefit from drugs such as elexacaftor/tezacaftor/ivacaftor (ETI) that activate CFTR-dependent ion transport. ETI is currently prescribed solely for treatment of CF and has not been adequately tested or proposed for patients with NCFBE, many of whom exhibit decreased CFTR function. Accordingly, we are conducting a clinical trial of ETI in subjects carrying a diagnosis of NCFBE.

METHODS: Participants will exhibit one disease-causing CFTR mutation and/or sweat chloride measurements of 30-59 mEq/L. Cutaneous punch biopsy or blood samples will be obtained for iPS cell differentiation into airway epithelial monolayers-which will then be tested for response to ETI. Each patient will be given CFTR modulator treatment for approximately four weeks, with monitoring of clinical endpoints that include FEV1 (forced expiratory volume in one second), sweat chloride, quality of life questionnaire, and weight. The study will evaluate response of patients with NCFBE to ETI, and test usefulness of iPSC-derived airway epithelial monolayers as a novel in vitro technology for predicting clinical benefit.

TRIAL REGISTRATION: This trial is registered at clinicaltrials.gov (Identifier: NCT05743946. Date: 02/23/2023).

PMID:39951444 | DOI:10.1371/journal.pone.0316721

Opt Lett. 2025 Feb 15;50(4):1269-1272. doi: 10.1364/OL.547399.

ABSTRACT

Fourier-inspired single-pixel holography (FISH) is an effective digital holography (DH) approach that utilizes a single-pixel detector instead of a conventional camera to capture light field information. FISH combines the Fourier single-pixel imaging and off-axis holography technique, allowing one to acquire useful information directly, rather than recording the hologram in the spatial domain and filtering unwanted terms in the Fourier domain. Furthermore, we employ a deep learning technique to jointly optimize the sampling mask and the imaging enhancement model, to achieve high-quality results at a low sampling ratio. Both simulations and experimental results demonstrate the effectiveness of FISH in single-pixel phase imaging. FISH combines the strengths of single-pixel imaging (SPI) and DH, potentially expanding DH's applications to specialized spectral bands and low-light environments while equipping SPI with capabilities for phase detection and coherent gating.

PMID:39951780 | DOI:10.1364/OL.547399

Opt Lett. 2025 Feb 15;50(4):1261-1264. doi: 10.1364/OL.544342.

ABSTRACT

Self-interference digital holography extends the application of digital holography to non-coherent imaging fields such as fluorescence and scattered light, providing a new solution, to the best of our knowledge, for wide field 3D imaging of low coherence or partially coherent signals. However, cross talk information has always been an important factor limiting the resolution of this imaging method. The suppression of cross talk information is a complex nonlinear problem, and deep learning can easily obtain its corresponding nonlinear model through data-driven methods. However, in real experiments, it is difficult to obtain such paired datasets to complete training. Here, we propose an unsupervised cross talk suppression method based on a cycle-consistent generative adversarial network (CycleGAN) for self-interference digital holography. Through the introduction of a saliency constraint, the unsupervised model, named crosstalk suppressing with unsupervised neural network (CS-UNN), can learn the mapping between two image domains without requiring paired training data while avoiding distortions of the image content. Experimental analysis has shown that this method can suppress cross talk information in reconstructed images without the need for training strategies on a large number of paired datasets, providing an effective solution for the application of the self-interference digital holography technology.

PMID:39951778 | DOI:10.1364/OL.544342

Anal Chem. 2025 Feb 14. doi: 10.1021/acs.analchem.4c02796. Online ahead of print.

ABSTRACT

Surface-enhanced Raman spectroscopy (SERS) has emerged as a crucial analytical tool in the field of oncology, particularly presenting significant challenges for the diagnosis and treatment of head and neck cancer. This Review provides an overview of the current status and prospects of SERS applications, highlighting their profound impact on molecular biology-level diagnosis, tissue-level identification, HNC therapeutic monitoring, and integration with emerging technologies. The application of SERS for single-molecule assays such as epidermal growth factor receptors and PD-1/PD-L1, gene expression analysis, and tumor microenvironment characterization is also explored. This Review showcases the innovative applications of SERS in liquid biopsies such as high-throughput lateral flow analysis for ctDNA quantification and salivary diagnostics, which can offer rapid and highly sensitive assays suitable for immediate detection. At the tissue level, SERS enables cancer cell visualization and intraoperative tumor margin identification, enhancing surgical precision and decision-making. The role of SERS in radiotherapy, chemotherapy, and targeted therapy is examined along with its use in real-time pharmacokinetic studies to monitor treatment response. Furthermore, this Review delves into the synergistic relationship between SERS and artificial intelligence, encompassing machine learning and deep learning algorithms, marking the dawn of a new era in precision oncology. The integration of SERS with genomics, metabolomics, transcriptomics, proteomics, and single-cell omics at the multiomics level will revolutionize our comprehension and management of HNC. This Review offers an overview of the transformative impacts of SERS and examines future directions as well as challenges in this dynamic research field.

PMID:39951652 | DOI:10.1021/acs.analchem.4c02796

PLoS One. 2025 Feb 14;20(2):e0315143. doi: 10.1371/journal.pone.0315143. eCollection 2025.

ABSTRACT

The smart grid is on the basis of physical grid, introducing all kinds of advanced communications technology and form a new type of power grid. It can not only meet the demand of users and realize the optimal allocation of resources, but also improve the safety, economy and reliability of power supply, it has become a major trend in the future development of electric power industry. But on the other hand, the complex network architecture of smart grid and the application of various high-tech technologies have also greatly increased the probability of equipment failure and the difficulty of fault diagnosis, and timely discovery and diagnosis of problems in the operation of smart grid equipment has become a key measure to ensure the safety of power grid operation. From the current point of view, the existing smart grid equipment fault diagnosis technology has problems that the application program is more complex, and the fault diagnosis rate is generally not high, which greatly affects the efficiency of smart grid maintenance. Therefore, Based on this, this paper adopts the multimodal semantic model of deep learning and knowledge graph, and on the basis of the original target detection network YOLOv4 architecture, introduces knowledge graph to unify the characterization and storage of the input multimodal information, and innovatively combines the YOLOv4 target detection algorithm with the knowledge graph to establish a smart grid equipment fault diagnosis model. Experiments show that compared with the existing fault detection algorithms, the YOLOv4 algorithm constructed in this paper is more accurate, faster and easier to operate.

PMID:39951439 | DOI:10.1371/journal.pone.0315143

PLoS One. 2025 Feb 14;20(2):e0318998. doi: 10.1371/journal.pone.0318998. eCollection 2025.

ABSTRACT

Alzheimer's disease (AD) is a leading cause of disability worldwide. Early detection is critical for preventing progression and formulating effective treatment plans. This study aims to develop a novel deep learning (DL) model, Hybrid-RViT, to enhance the detection of AD. The proposed Hybrid-RViT model integrates the pre-trained convolutional neural network (ResNet-50) with the Vision Transformer (ViT) to classify brain MRI images across different stages of AD. The ResNet-50 adopted for transfer learning, facilitates inductive bias and feature extraction. Concurrently, ViT processes sequences of image patches to capture long-distance relationships via a self-attention mechanism, thereby functioning as a joint local-global feature extractor. The Hybrid-RViT model achieved a training accuracy of 97% and a testing accuracy of 95%, outperforming previous models. This demonstrates its potential efficacy in accurately identifying and classifying AD stages from brain MRI data. The Hybrid-RViT model, combining ResNet-50 and ViT, shows superior performance in AD detection, highlighting its potential as a valuable tool for medical professionals in interpreting and analyzing brain MRI images. This model could significantly improve early diagnosis and intervention strategies for AD.

PMID:39951414 | DOI:10.1371/journal.pone.0318998

Sci Adv. 2025 Feb 14;11(7):eadp4008. doi: 10.1126/sciadv.adp4008. Epub 2025 Feb 14.

ABSTRACT

Chimeric antigen receptor (CAR) T cells offer a promising cancer treatment, yet challenges such as limited T cell persistence hinder efficacy. Given its critical role in modulating T cell responses, it is crucial to understand how the CAR signaling architecture influences T cell function. Here, we designed a combinatorial CAR signaling domain library and performed repeated antigen stimulation assays, pooled screens, and single-cell sequencing to systematically investigate the impact of modifying CAR signaling domains on T cell activation and persistence. Our data reveal the predominant influence of membrane-proximal domains in driving T cell phenotype. Notably, CD40 costimulation was crucial for fostering robust and lasting T cell responses. Furthermore, we correlated in vitro generated CAR T cell phenotypes with clinical outcomes in patients treated with CAR T therapy, establishing the foundation for a clinically informed screening approach. This work deepens our understanding of CAR T cell biology and may guide future CAR engineering efforts.

PMID:39951542 | DOI:10.1126/sciadv.adp4008

JAMA Netw Open. 2025 Feb 3;8(2):e2459557. doi: 10.1001/jamanetworkopen.2024.59557.

ABSTRACT

IMPORTANCE: Textbooks attribute 80% of meconium-related small bowel obstructions to cystic fibrosis and 15% of colonic obstructions to Hirschsprung disease. It is unknown whether these estimates are accurate, particularly among preterm infants, whose immature bowel predisposes them to meconium-related obstruction (MRO).

OBJECTIVE: To estimate the incidence of MRO by type and to assess its association with clinical outcomes.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study of live-born infants included in the National Inpatient Sample from January 1, 2016, to December 31, 2020, used survey weighting methods to estimate the national incidence of MRO by etiology. Data were analyzed from November 27, 2023, to November 12, 2024.

EXPOSURE: MRO.

MAIN OUTCOMES AND MEASURES: The primary outcome was diagnosis with MRO. Secondary outcomes included mortality, need for abdominal surgery, hospitalization duration, and cost. Multivariable regression models were developed to evaluate characteristics associated with MRO and to assess the association of MRO of prematurity with clinical outcomes after adjusting for demographic and clinical covariates.

RESULTS: Of 3 550 796 infants, 51.2% were male and 46.7% were privately insured. Overall, 9.1% (n = 322 499) were born preterm. Of 1844 (0.1%) infants treated for MRO, 41 (2.2%) had cystic fibrosis, 60 (3.3%) had Hirschsprung disease, and 1743 (94.5%) had neither predisposing condition. Preterm infants were at highest risk for MRO, with 4.7 MRO cases per 100 000 births associated with cystic fibrosis, 4.7 MRO cases per 100 000 births associated with Hirschsprung disease, and 187.3 MRO cases per 100 000 births associated with neither predisposing condition. Among infants with neither cystic fibrosis nor Hirschsprung disease, those with gestational ages from 28 weeks to 31 weeks 6 days were most likely to develop MRO compared with term infants (adjusted odds ratio, 6.08 [95% CI, 4.27-8.67]). Among preterm infants, having an MRO was associated with a 4.2 percentage point increase in the probability of abdominal surgery (95% CI, 3.1-5.4 percentage points), a 7.3-day increase in length of stay (95% CI, 5.8-8.8 days), and a $23 215 increase in hospitalization costs (95% CI, $17 739-$28 690) compared with infants who did not have an obstruction, with no change in mortality rate (0.1 percentage point change [95% CI, -0.6 to 0.8 percentage points]).

CONCLUSIONS AND RELEVANCE: In this cohort study of over 3.5 million infants, MRO was most likely to occur among preterm infants without cystic fibrosis or Hirschsprung disease. These infants more frequently required surgery and had longer and more costly hospitalizations, indicating a need for dedicated prevention and treatment pathways for this understudied disease.

PMID:39951267 | DOI:10.1001/jamanetworkopen.2024.59557

J Bacteriol. 2025 Feb 14:e0053124. doi: 10.1128/jb.00531-24. Online ahead of print.

ABSTRACT

Phenotypic diversity in bacteria often results from adaptation to changing environmental conditions, exemplified by variable colony morphotypes. In Burkholderia pseudomallei, discrete genomic alterations and modulation of gene expression facilitate adaptation. Adapted variants of species within the Burkholderia cepacia complex (Bcc) often lose the pC3 virulence megaplasmid, impacting their colony morphology and their production of virulence factors. In this study, we characterize variants arising in Burkholderia ambifaria clinical isolates using proteomics and phenotypic tests and show that some of them have retained the pC3, indicating a distinct phase variation mechanism at play in this Bcc species. Interestingly, variants of B. ambifaria strains CEP0996 (pC3-null) and HSJ1 (pC3-positive) still share similarities in phenotypes controlled by the Cep quorum-sensing (QS) system. We further investigated the role of QS in B. ambifaria HSJ1 phase variation and confirmed that the Cep QS system is important for the emergence of variants. Given that DNA methylation is a key epigenetic factor regulating virulence factors in Burkholderia cenocepacia, we hypothesized that adenosine DNA methylation also governs phase variation in B. ambifaria HSJ1. By deleting the genes encoding putative adenosine DNA methyltransferases, we discovered that an orphan type II DNA methyltransferase inhibits the emergence of phase variants. This study is the first to demonstrate that quorum sensing and adenosine DNA methylation are two antagonistic systems independently controlling phase variation in B. ambifaria.IMPORTANCESome Burkholderia species are pathogenic to plants, animals, or humans. In immunocompromised individuals, and people suffering from cystic fibrosis, infection from the Burkholderia cepacia complex (Bcc) can lead to "cepacia syndrome." In northern Australia and southeast Asia, melioidosis caused by Burkholderia pseudomallei is prevalent among native population, particularly among people with diabetes, chronic lung or kidney disease or alcoholism. Burkholderia's phenotypic plasticity, including colony morphotype variation (CMV), enables rapid adaptation to diverse environments, enhancing its survival and pathogenicity. This study reveals phase variation as a new CMV mechanism within the Bcc group and is the first to report that quorum sensing and DNA methylation are involved in phase variation. Understanding the underlying mechanisms of CMV could lead to the development of targeted therapies against these highly antibiotic-tolerant bacteria.

PMID:39950805 | DOI:10.1128/jb.00531-24

Ann Nucl Med. 2025 Feb 14. doi: 10.1007/s12149-025-02020-z. Online ahead of print.

ABSTRACT

OBJECTIVE: Bone scintigraphy is widely employed for detecting bone metastases, with the bone scan index (BSI) gaining traction as a quantitative tool in this domain. VSBONE BSI, an automated image analysis software, identifies abnormal hyperaccumulation areas in bone scintigraphy and computes BSI scores. The software, originally developed using data from conventional gamma cameras (C-Camera), has undergone two upgrades. This study hypothesized that the upgrades enhance the diagnostic accuracy for bone metastases and assessed the software's applicability to images obtained using a cadmium-zinc-telluride detector gamma camera (CZT-Camera). The aim was to compare the diagnostic accuracy of VSBONE BSI across software versions using both conventional and CZT detectors and to evaluate its utility.

METHODS: A total of 287 patients with breast or prostate carcinoma who underwent whole-body bone scintigraphy were included. VSBONE BSI automatically analyzed and calculated the BSI. The analysis results were compared with the presence or absence of metastases for each software version by using detector type of camera. The diagnostic agreement was evaluated.

RESULTS: Receiver operating characteristic analysis showed an area under the curve (AUC) exceeding 0.7 across all groups, indicating good diagnostic performance. AUC values significantly increased with version upgrades for all patients and for breast carcinoma patients. In metastasis-negative cases, BSI values decreased with each software version upgrade, with the reduction being more pronounced in breast carcinoma patients scanned with the CZT-Camera.

CONCLUSIONS: Using the VSBONE BSI, version 2 or 3 had a higher rate of diagnostic concordance with the clinical prognosis than version 1. In metastasis-negative patients, newer software versions yielded lower BSI values, especially for breast carcinoma patients scanned using the CZT-Camera, highlighting the improved diagnostic accuracy of the updated software.

PMID:39951220 | DOI:10.1007/s12149-025-02020-z

Aging Ment Health. 2025 Feb 14:1-9. doi: 10.1080/13607863.2025.2464704. Online ahead of print.

ABSTRACT

OBJECTIVES: Dementia can change oculomotor behavior, which is detectable through eye-tracking. This study aims to systematically review and conduct a meta-analysis of current literature on the intersection between eye-tracking and artificial intelligence (AI) in detecting dementia.

METHOD: PubMed, Embase, Scopus, Web of Science, Cochrane, and IEEE databases were searched up to July 2023. All types of studies that utilized eye-tracking and AI to detect dementia and reported the performance metrics, were included. Data on the dementia type, performance, artificial intelligence, and eye-tracking paradigms were extracted. The registered protocol is available online on PROSPERO (ID: CRD42023451996).

RESULTS: Nine studies were finally included with a sample size ranging from 57 to 583 participants. Alzheimer's disease (AD) was the most common dementia type. Six studies used a machine learning model while three used a deep learning model. Meta-analysis revealed the accuracy, sensitivity, and specificity of using eye-tracking and artificial intelligence in detecting dementia, 88% [95% CI (83%-92%)], 85% [95% CI (75%-93%)], and 86% [95% CI (79%-93%)], respectively.

CONCLUSION: Eye-tracking coupled with AI revealed promising results in terms of dementia detection. Further studies must incorporate larger sample sizes, standardized guidelines, and include other dementia types.

PMID:39950960 | DOI:10.1080/13607863.2025.2464704

J Med Eng Technol. 2025 Feb 14:1-14. doi: 10.1080/03091902.2025.2463577. Online ahead of print.

ABSTRACT

Developing a robust and effective technique is crucial for interpreting a user's brainwave signals accurately in the realm of biomedical signal processing. The variability and uncertainty present in EEG patterns over time, compounded by noise, pose notable challenges, particularly in mental tasks like motor imagery. Introducing fuzzy components can enhance the system's ability to withstand noisy environments. The emergence of deep learning has significantly impacted artificial intelligence and data analysis, prompting extensive exploration into assessing and understanding brain signals. This work introduces a hybrid series architecture called FCLNET, which combines Compact-CNN to extract frequency and spatial features alongside the LSTM network for temporal feature extraction. The activation functions in the CNN architecture were implemented using type-2 fuzzy functions to tackle uncertainties. Hyperparameters of the FCLNET model are tuned by the Bayesian optimisation algorithm. The efficacy of this approach is assessed through the BCI Competition IV-2a database and the BCI Competition IV-1 database. By incorporating type-2 fuzzy activation functions and employing Bayesian optimisation for tuning, the proposed architecture indicates good classification accuracy compared to the literature. Outcomes showcase the exceptional achievements of the FCLNET model, suggesting that integrating fuzzy units into other classifiers could lead to advancements in motor imagery-based BCI systems.

PMID:39950750 | DOI:10.1080/03091902.2025.2463577

ACS Appl Mater Interfaces. 2025 Feb 14. doi: 10.1021/acsami.4c20821. Online ahead of print.

ABSTRACT

Prolonged use of digital devices and sedentary lifestyles have led to an increase in the prevalence of cervical spondylosis among young people, highlighting the urgent need for preventive measures. Recent advancements in triboelectric nanogenerators (TENGs) have shown their potential as self-powered sensors. In this study, we introduce a novel, flexible, and stretchable TENG for neck movement detection. The proposed TENG utilizes a glycerol/poly(vinyl alcohol) (GL/PVA) hydrogel and silicone rubber (GH-TENG). Through optimization of its concentration and thickness parameters and the use of environmentally friendly dopants, the sensitivity of the GH-TENG was improved to 4.50 V/kPa. Subsequently, we developed a smart neck ring with the proposed sensor for human neck movement monitoring. By leveraging the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) algorithm, sensor data can be efficiently analyzed in both spatial and temporal dimensions, achieving a promising recognition accuracy of 97.14%. Additionally, we developed a neck motion monitoring system capable of accurately identifying and recording neck movements. The system can timely alert users if they maintain the same neck posture for more than 30 min and provide corresponding recommendations. By deployment on a Raspberry Pi 4B, the system offers a portable and efficient solution for cervical health protection.

PMID:39950449 | DOI:10.1021/acsami.4c20821

J Virol. 2025 Feb 14:e0147824. doi: 10.1128/jvi.01478-24. Online ahead of print.

ABSTRACT

Influenza A viruses with fewer amino acids in the neuraminidase (NA) stalk domain are primarily isolated from chickens rather than wild ducks, indicating that a shortened NA stalk is considered an adaptation marker of avian influenza viruses (AIVs) to chickens. Experimental passages of an H7N7 nonpathogenic AIV (rgVac2-P0) in chickens resulted in a highly pathogenic variant (Vac2-P3L4) with a 34-amino-acid deletion in the NA stalk, encompassing five potential N-glycosylation sites. To investigate how amino acid truncation and deglycosylation in the NA stalk contribute to increased pathogenicity, a virus with glycosylation-deficient mutations at these sites (rgVac2-P3L4/P0NAΔGlyco) was constructed. Contrary to expectations, chickens inoculated with rgVac2-P3L4/P0NAΔGlyco exhibited variable clinical outcomes, attributed to the genetic instability of the virus. A single mutation stabilized the virus, and the mutant (rgVac2-P3L4/P0NAΔGlyco-Y65H) resulted in higher pathogenicity compared with a virus with restored glycosylation (rgVac2-P3L4/P0NA-Y65H). Glycan occupancy analysis revealed 3-4 glycans at the five potential sites. In functional analysis, glycosylation-deficient mutants, similar to the short-stalk NA virus, showed significantly reduced erythrocyte elution activity. Additionally, mutational analysis indicated variable contributions of N-glycans to elution activity across the sites. Moreover, the functionally most contributing sites of the five potential N-glycosylation motifs were consistently included in the amino acid deletions of the stalk-truncated NA in N7-subtyped field isolates, despite the varying truncation position or length. These findings suggest that the loss of glycosylation is functionally equivalent to a reduction in amino acids, and it plays a crucial role in enhancing pathogenicity in chickens and affecting NA function.IMPORTANCEAvian influenza poses significant economic challenges to the poultry industry and presents potential risks to human health. Understanding the molecular mechanisms that facilitate the emergence of chicken-adapted avian influenza viruses (AIVs) from non-pathogenic duck-origin influenza viruses is crucial for improving AIV monitoring systems in poultry and controlling this disease. Amino acid deletions in the neuraminidase (NA) stalk domain serve as one of the molecular markers for AIV adaptation to Galliformes. This study highlights the critical role of N-glycosylation in the NA stalk domain in the pathogenesis of high pathogenicity avian influenza viruses in chickens. The findings propose a novel theory that the loss of glycosylation at the NA stalk domain, rather than a reduction in stalk length, is responsible for both NA function and increased virus pathogenicity in chickens.

PMID:39950775 | DOI:10.1128/jvi.01478-24

Genetics. 2025 Feb 14:iyae215. doi: 10.1093/genetics/iyae215. Online ahead of print.

ABSTRACT

Studying mutation in healthy somatic tissues is the key for understanding the genesis of cancer and other genetic diseases. Mutation rate varies from site to site in the human genome by up to 100-fold and is influenced by numerous epigenetic and genetic factors including GC content, trinucleotide sequence context, and DNAse accessibility. These factors influence mutation at both local and regional scales and are often interrelated with one another, meaning that predicting mutability or uncovering its drivers requires modelling multiple factors and scales simultaneously. Historically, most investigations have focused either on analyzing the local sequence scale through triplet signatures or on examining the impact of epigenetic processes at larger scales, but not both concurrently. Additionally, sequencing technology limitations have restricted analyses of healthy mutations to coding regions (RNA-seq) or to those that have been influenced by selection (e.g. bulk samples from cancer tissue). Here, we leverage single-cell mutations and present a comprehensive analysis of epigenetic and genetic factors at multiple scales in the germline and 3 healthy somatic tissues. We create models that predict mutability with on average 2% error and find up to 63-fold variation among sites within the same tissue. We observe varying degrees of similarity between tissues: the mutability of genomic positions was 93.4% similar between liver and germline tissues, but sites in germline and skin were only 85.9% similar. We observe both universal and tissue-specific mutagenic processes in healthy tissues, with implications for understanding the maintenance of germline vs soma and the mechanisms underlying early tumorigenesis.

PMID:39950507 | DOI:10.1093/genetics/iyae215

Front Microbiol. 2025 Jan 30;16:1554339. doi: 10.3389/fmicb.2025.1554339. eCollection 2025.

NO ABSTRACT

PMID:39949624 | PMC:PMC11822564 | DOI:10.3389/fmicb.2025.1554339

Cell Mol Bioeng. 2025 Jan 23;18(1):71-82. doi: 10.1007/s12195-024-00841-y. eCollection 2025 Feb.

ABSTRACT

PURPOSE: Cervical and endometrial cancers pose significant challenges in women's healthcare due to their high mortality rates and limited treatment options. High throughput screening (HTS) of cervical and endometrial cancer in vitro models offers a promising avenue for drug repurposing and broadening patient treatment options. Traditional two-dimensional (2D) cell-based screenings have limited capabilities to capture crucial multicellular interactions, that are improved upon in three dimensional (3D) multicellular tissue engineered models. However, manual fabrication of the 3D platforms is both time consuming and subject to variability. Thus, the goal of this study was to utilize automated cell dispensing to fabricate 3D cell-based HTS platforms using the HP D100 Single Cell Dispenser to dispense cervical and endometrial cancer cells.

METHODS: We evaluated the effects of automated dispensing of the cancer cell lines by tuning the dispensing protocol to align with cell size measured in solution and the minimum cell number for acceptable cell viability and proliferation. We modified our previously reported coculture models of cervical and endometrial cancer to be in a 384 well plate format and measured microvessel length and cancer cell invasion.

RESULTS: Automatically and manually dispensed cells were directly compared revealing minimal differences between the dispensing methods. These findings suggest that automated dispensing of cancer cells minimally affects cell behavior and can be deployed to decrease in vitro model fabrication time.

CONCLUSIONS: By streamlining the manufacturing process, automated dispensing holds promise for enhancing efficiency and scalability of 3D in vitro HTS platforms, ultimately contributing to advancement in cancer research and treatment.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12195-024-00841-y.

PMID:39949489 | PMC:PMC11813830 | DOI:10.1007/s12195-024-00841-y