BMC Psychiatry. 2025 Jan 10;25(1):34. doi: 10.1186/s12888-025-06481-4.

ABSTRACT

BACKGROUND: Few new psychiatric drugs have entered the market in recent decades; in contrast, the number of drugs carrying pharmacogenomic labels continues to increase. For the foreseeable future, the advancement of psychiatry and drug therapy may hinge on personalized treatment. Currently, antipsychotic or antidepressant choices rely heavily on the clinical experience of psychiatrists and potentially lengthy iterative trials. During these trials, the clinical response to treatment in acutely depressed patients can be assessed only after several weeks of exposure to the drug. Although pharmacogenomic testing has been used in clinical care for several years, most Chinese clinicians struggle to utilize the information accurately, resulting in expensive tests that provide little real benefit to patients. Here, we demonstrate how to combine the results of pharmacogenomic testing to develop an individualized treatment plan. Our goal is to find the optimal medication regimen and dosage for the patient in the shortest possible time, control symptoms as soon as possible, and predict adverse drug reactions. This approach aims to offer a practical therapeutic idea for clinical practice.

CASE PRESENTATION: We present the case of a 27-year-old female patient experiencing a relapse of depression. Despite previous attempts with empiric medication, her symptoms remained uncontrolled, leading to exacerbation and drug withdrawal reactions. Utilizing the results of pharmacogenetic testing, we crafted an individualized treatment plan, resulting in rapid remission without any adverse drug reactions.

CONCLUSION: Recognizing the complexity of antidepressant response, our patients aim to improve their understanding, as well as that of other healthcare providers, by undergoing pharmacogenomics testing. This enhances the credibility of their medication choices. While pharmacogenomics is just one aspect considered in selecting a treatment regimen for depression, it remains a valuable tool for increasing credibility and mitigating potential adverse events.

PMID:39794795 | DOI:10.1186/s12888-025-06481-4

Pediatr Neonatol. 2024 Dec 29:S1875-9572(24)00231-6. doi: 10.1016/j.pedneo.2024.06.015. Online ahead of print.

ABSTRACT

BACKGROUND: Invasive mechanical ventilation in very-low-birth-weight infants (VLBWI) was associated with immediate and long-term complications. Nasal high-frequency oscillation (nHFO) has recently become a new non-invasive ventilation (NIV) mode for treating respiratory failure in VLBWI. This study aimed to investigate the safety and efficacy of nHFO as an alternative respiratory support to prevent intubation in VLBWI.

METHODS: A retrospective analysis was conducted using the clinical data of 42 VLBWIs with respiratory distress syndrome (RDS) who were treated in our department from August 2018 to August 2020 and met the selection criteria.

RESULTS: nHFO was used as a rescue strategy in 32 infants and a prophylactic strategy in 10 infants. It was observed that out of 42 cases, 30 cases (71.4%) were able to avoid intubation within 72 h, while 23 cases (54.8%) were successfully switched to another NIV mode from nHFO. There was a significant decrease in pCO2 and an increase in pH 1 h after using nHFO in the success group. Two cases (4.8%) of feeding intolerance associated with nHFO were noted.

CONCLUSION: This study showed that nHFO as alternative respiratory support for preterm infants with RDS might be safe and effective in reducing the need for intubation.

PMID:39794186 | DOI:10.1016/j.pedneo.2024.06.015

J Cyst Fibros. 2025 Jan 9:S1569-1993(24)01857-5. doi: 10.1016/j.jcf.2024.12.003. Online ahead of print.

NO ABSTRACT

PMID:39794183 | DOI:10.1016/j.jcf.2024.12.003

J Cyst Fibros. 2025 Jan 9:S1569-1993(24)01855-1. doi: 10.1016/j.jcf.2024.12.005. Online ahead of print.

ABSTRACT

BACKGROUND: Food insecurity (FI) is more prevalent in people with cystic fibrosis (PwCF) than the reported national prevalence, but there are limited data on the relationship between FI and health outcomes in PwCF. The objective of this study was to analyze the relationship between FI in PwCF and pulmonary and nutritional status.

METHODS: We leveraged an electronic cross-sectional survey that ascertained FI status and gave participants the option to link their survey data to their records in the Cystic Fibrosis Foundation Patient Registry (CFFPR). Linear regression and negative binomial models were used to estimate the associations in mean differences between FI and percent predicted FEV1 (ppFEV1), nutritional indices, and hospitalizations.

RESULTS: There were 1,856 respondents, 1,234 (66.5 %) of whom granted permission to link to the CFFPR. FI was present in 352 (28 %) of the respondents. FI was associated with lower ppFEV1 (-6.5; 95 % CI -9.9, -3.1); however, this was no longer statistically significant after adjusting for confounders. FI was independently associated with increased hospitalizations. Higher weight for age was significantly associated with FI in the adjusted model, but there were no significant associations between height for age or absolute weight and body mass index (BMI) in adults.

CONCLUSIONS: FI in PwCF is associated with adverse health outcomes. These results support screening for FI during routine visits. Further studies are needed to investigate causal relationships between FI and adverse clinical outcomes.

PMID:39794182 | DOI:10.1016/j.jcf.2024.12.005

Stem Cell Res. 2025 Jan 6;83:103653. doi: 10.1016/j.scr.2025.103653. Online ahead of print.

ABSTRACT

Cystic Fibrosis (CF) is a life-shortening disease that is caused by mutations in the CFTR gene, a gene that is expressed in multiple organs. There are several primary tissue models of CF disease, including nasal epithelial cultures and rectal organoids, that are effective in reporting the potential efficacy of mutation-targeted therapies called CFTR modulators. However, there is the well-documented variation in tissue dependent, therapeutic response amongst CF patients, even those with the same CF-causing mutation. Hence, there is an interest in developing strategies for comparing therapeutic efficacy in different organs relative to isogenic controls. In this study, we evaluated the CFTR chloride channel response to the highly effective CFTR modulator: Trikafta, in CF patient specific, iPSC-derived colonic and airway cultures relative to mutation-corrected (non-CF) tissues from that same individual. We measured pharmacological rescue in both tissues. This proof-of-concept study provides a roadmap for future comparisons of patient-specific CF therapeutic responses in both pulmonary and extra-pulmonary systems.

PMID:39793274 | DOI:10.1016/j.scr.2025.103653

Eur J Med Res. 2025 Jan 10;30(1):20. doi: 10.1186/s40001-024-02256-x.

ABSTRACT

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease with poor prognosis, nomogram model for its prognosis and acute exacerbation was constructed.

METHODS: Two hundred and sixty eight patients with IPF were grouped with different severity according to fibrosis area, serum Club cell secretory protein 16(CC16) was compared between these groups. All patients were randomly divided into training and testing sets. COX regression and LASSO algorithm were used to screen featured characteristics. Then nomogram models were constructed, ROC curve, calibration curve and decision curve analysis(DCA) were conducted to evaluate the performance of model. Expression of CC16 were detected in fibrotic human lung tissues, bronchoalveolar lavage fluid (BALF) and Bleomycin(BLM)-treated mouse lung tissues and serums.

RESULTS: Serum CC16 gradually increased with the severity of fibrosis, and was especially high in AE-IPF group. CC16 and diffusion capacity for carbon monoxide (DLCO) were screened as characteristic variables to construct nomogram model for IPF prognosis. The survival was significantly lower in high-risk group scored by the model. The area under ROC curves(AUCs) for 1-year and 2-year mortality prediction were 0.866 and 0.916, respectively. This model performed better than gender-age-physiology (GAP) index for predicting 2-year and 3-year mortality. Another nomogram model for acute exacerbation of IPF based on CC16, Krebs von den Lungen-6(KL-6) and DLCO was developed, the AUC was 0.815. Expression of CC16 obviously up-regulated in fibrotic lung tissues, BALF and BLM-treated mice lung tissues and serums.

CONCLUSIONS: The nomogram model based on CC16 performed good predictive ability for prognosis and acute exacerbation of IPF.

PMID:39794841 | DOI:10.1186/s40001-024-02256-x

Gene. 2025 Jan 9:149223. doi: 10.1016/j.gene.2025.149223. Online ahead of print.

NO ABSTRACT

PMID:39794204 | DOI:10.1016/j.gene.2025.149223

Ecotoxicol Environ Saf. 2025 Jan 9;289:117679. doi: 10.1016/j.ecoenv.2025.117679. Online ahead of print.

ABSTRACT

AIM: Identifying the common functional single-nucleotide polymorphisms (SNPs) that can both affect the susceptibility to idiopathic pulmonary fibrosis (IPF) and silicosis.

METHODS: We first integrated the genome-wide association studies (GWASs) of IPF and silicosis to obtain the shared SNPs. Following this, functional expression quantitative trait locus (eQTL)-SNPs were identified by the GTEx database. This was followed by the validation of the correlation between these eQTL-SNPs and silicosis susceptibility through an additional case-control study including 194 silicosis cases and 235 healthy controls.

RESULTS: A total of 10 eQTL-SNPs that may affect silicosis susceptibility (P < 0.05) were obtained after the integration of the GWASs of IPF and silicosis, and a series of rigorous selection principles. Subsequently, the results of integrating the validation stage and the screening stage indicated that the variant T allele of rs1620530 located in the MAD1L1 (additive model: OR= 1.56, 95 % CI = 1.21-2.01, P = 0.001) and the variant G allele of rs2070063 located in the SERTAD2 (additive model: OR= 1.60, 95 % CI = 1.24-2.06, P < 0.001) were associated with increased silicosis susceptibility. The joint analysis indicated the risk of developing silicosis was higher in individuals who carried more unfavorable alleles of rs1620530 and rs2070063.

CONCLUSIONS: The rs1620530 and rs2070063 may affect the silicosis susceptibility by regulating the expression of the MAD1L1 and SERTAD2, respectively. Further biological experiments are warranted to elucidate the underlying biological mechanisms between these two SNPs and the increased susceptibility to silicosis.

PMID:39793288 | DOI:10.1016/j.ecoenv.2025.117679

Microb Cell Fact. 2025 Jan 10;24(1):14. doi: 10.1186/s12934-024-02641-5.

ABSTRACT

Genome mining is a promising avenue for expanding the repertoire of microbial natural products, which are important for drug development. This approach involves predicting genetically encoded small molecules by examining bacterial genomes via accumulated knowledge of microbial biosynthesis. However, it is also important that the microbes produce the predicted molecule in practice. Here, we introduce an endophytic Streptomyces sp. N50, which was isolated from the medicinal plant Selaginella tamariscina. Upon sequencing its entire genome, 33 biosynthetic gene clusters (BGCs) were identified in a chromosome and a megaplasmid. Subsequent genome mining revealed that the new 15-deoxynaphthomycin could be produced due to the presence of an enoyl reductase domain, which is absent in the known BGC of naphthomycin, a type of ansamycin antibiotics. In addition, the engineered strain with the introduction of the global regulatory gene afsR2 into N50 successfully produced 15-deoxynaphthomycins. Furthermore, molecular network analysis via MS/MS selectively confirmed the presence of additional sulfur-containing 15-deoxynaphthomycin congeners. Eventually, six new 15-deoxynaphthomycins were isolated and elucidated from the engineered strain N50. This family of compounds is known to exhibit various biological activities. Also, the presence of quinone moieties in these compounds, which are known to activate NRF2, they were tested for their ability to activate NRF2. Among the new compounds, three (1, 5, and 6) activated the antioxidant NRF2-ARE signaling pathway. Treatment with these compounds significantly elevated NRF2 levels in HepG2 cells and further induced the expression of NRF2 target genes associated with the antioxidant response. This study suggests that the combination of genome mining, gene engineering and molecular networking is helpful for generating new small molecules as pharmaceutical candidates from microorganisms.

PMID:39794808 | DOI:10.1186/s12934-024-02641-5

BMC Genomics. 2025 Jan 10;26(1):28. doi: 10.1186/s12864-025-11210-y.

ABSTRACT

BACKGROUND: Sugarcane is a crucial crop for both sugar and bioethanol production. The nobilization breeding and utilization of wild germplasm have significantly enhanced its productivity. However, the pollen sterility in Saccharum officinarum restricts its role to being a female parent in crosses with Saccharum spontaneum during nobilization breeding, resulting in a narrow genetic basis for modern sugarcane cultivars. Mitochondria, often referred to as the intracellular "energy factories", provide energy for plant life activities, and are also implicated in cytoplasmic male sterility (CMS).

RESULTS: We performed mitochondrial genome assembly and structural analysis of two Saccharum founding species. We discovered that the proportions of repeat sequences are the primary factor contributing to the variations in mitochondrial genome structure and size between the two Saccharum species. Heterologous expression of the mitochondrial chimeric gene ORF113, which is highly expressed in male-sterile S. officinarum flowers, significantly inhibits growth and ATP synthesis in yeast cells, making it a key candidate CMS-related gene in sugarcane. Furthermore, we developed two co-dominant simple sequence repeat (SSR) markers based on the mitochondrial genome, which can effectively distinguish the cytoplasmic types of the two Saccharum species.

CONCLUSION: In this study, we identified structural variants and developed SSR molecular markers in the mitochondrial genomes of both S. officinarum and S. spontaneum. We also identified a novel mitochondrial chimeric ORF as a key candidate CMS-related gene. These findings offer valuable insights into variety identification, genetic resource development, and cross-breeding strategies in sugarcane.

PMID:39794692 | DOI:10.1186/s12864-025-11210-y

Commun Biol. 2025 Jan 10;8(1):38. doi: 10.1038/s42003-024-07444-3.

ABSTRACT

Prenatal maternal stress (PNMS) determines lifetime mental and physical health. Here, we show in rats that PNMS has consequences for placental function and fetal brain development across four generations (F0-F3). Using a systems biology approach, comprehensive DNA methylation (DNAm), miRNA, and mRNA profiling revealed a moderate impact of PNMS in the F1 generation, but drastic changes in F2 and F3 generations, suggesting compounding effects of PNMS with each successive generation. Both maternal and placental miRNA gene targets included de novo DNA methyltransferases, indicating robust PNMS-induced disruption in the complex epigenetic regulatory network between miRNAs and DNAm. Transgenerational programming mainly involved genes and biological pathways associated with neurological and psychiatric diseases which were linked to maternal-fetal crosstalk facilitated by the placenta. The highly correlated placenta-brain profiles support the use of placenta as a noninvasive biomarker resource to predict pathological changes in the neonatal brain. The transgenerational persistence of critical DNAm, miRNA and mRNA signatures may explain familial non-genetic disease risks.

PMID:39794497 | DOI:10.1038/s42003-024-07444-3

Cell Death Discov. 2025 Jan 10;11(1):2. doi: 10.1038/s41420-025-02286-2.

ABSTRACT

Oral cavity squamous cell carcinoma (OSCC) represents the most prevalent malignancy among head and neck squamous cell carcinomas (HNSCCs). Standard treatment modalities include surgical resection combined with radiation and chemotherapy. However, locoregional failure remains a critical issue affecting the prognosis of OSCC patients, largely due to tumor resistance against radiation or chemotherapy. In this study, we established a gene database related to OSCC recurrence and identified PSMA2 as a novel molecule influencing prognosis in OSCC patients. An independent Taiwanese cohort confirmed that elevated PSMA2 transcript levels were associated with poorer prognosis and contributed to the chemo- and radioresistance phenotype in OSCC. Furthermore, we confirmed that PSMA2 regulates cell cycle, mitochondrial dysfunction, and mitophagy, thereby contributing to carcinogenesis and resistance. Notably, mitophagy inducer exhibit antitumor effects in PSMA2-overexpressing OSCC xenograft mouse model. Collectively, our results provide a mechanistic understanding of the atypical function of PSMA2 in promoting OSCC recurrence.

PMID:39794329 | DOI:10.1038/s41420-025-02286-2

Trends Cancer. 2025 Jan 9:S2405-8033(24)00288-7. doi: 10.1016/j.trecan.2024.12.003. Online ahead of print.

ABSTRACT

Myeloid cells play a crucial dual role in cancer progression and response to therapy, promoting tumor growth, enabling immune suppression, and contributing to metastatic spread. The ability of these cells to modulate the immune system has made them attractive targets for therapeutic strategies aimed at shifting their function from tumor promotion to fostering antitumor immunity. Therapeutic approaches targeting myeloid cells focus on modifying their numbers, genetics, metabolism, and interactions within the tumor microenvironment. These strategies aim to reverse their suppressive functions and redirect them to support antitumor immune responses by inhibiting immunosuppressive pathways, targeting specific receptors, and promoting their differentiation into less immunosuppressive phenotypes. Here, we discuss recent approaches to clinically target tumor myeloid cells, focusing on reprogramming myeloid cells to promote antitumor immunity.

PMID:39794212 | DOI:10.1016/j.trecan.2024.12.003

Curr Biol. 2025 Jan 4:S0960-9822(24)01587-2. doi: 10.1016/j.cub.2024.11.046. Online ahead of print.

ABSTRACT

Anaphase is tightly controlled spatiotemporally to ensure proper separation of chromosomes.1,2,3 The mitotic spindle, the self-organized microtubule structure driving chromosome segregation, scales in size with the available cytoplasm.4,5,6,7 Yet, the relationship between spindle size and chromosome movement remains poorly understood. Here, we address this relationship during the cleavage divisions of the Drosophila blastoderm. We show that the speed of chromosome separation gradually decreases during the four nuclear divisions of the blastoderm. This reduction in speed is accompanied by a similar reduction in spindle length, ensuring that these two quantities are tightly linked. Using a combination of genetic and quantitative imaging approaches, we find that two processes contribute to controlling the speed at which chromosomes move in anaphase: the activity of molecular motors important for microtubule depolymerization and sliding and the cell cycle oscillator. Specifically, we found that the levels of multiple kinesin-like proteins important for microtubule depolymerization, as well as kinesin-5, contribute to setting the speed of chromosome separation. This observation is further supported by the scaling of poleward flux rate with the length of the spindle. Perturbations of the cell cycle oscillator using heterozygous mutants of mitotic kinases and phosphatases revealed that the duration of anaphase increases during the blastoderm cycles and is the major regulator of chromosome velocity. Thus, our work suggests a link between the biochemical rate of mitotic exit and the forces exerted by the spindle. Collectively, we propose that the cell cycle oscillator and spindle length set the speed of chromosome separation in anaphase.

PMID:39793565 | DOI:10.1016/j.cub.2024.11.046

Reg Anesth Pain Med. 2025 Jan 9:rapm-2024-106304. doi: 10.1136/rapm-2024-106304. Online ahead of print.

NO ABSTRACT

PMID:39793993 | DOI:10.1136/rapm-2024-106304

Eur J Cancer. 2024 Nov 16;216:115122. doi: 10.1016/j.ejca.2024.115122. Online ahead of print.

ABSTRACT

PURPOSE: MAK683, a first-in-class and highly selective allosteric inhibitor of the embryonic ectoderm development subunit of polycomb repressive complex 2, has shown sustained antitumor activity in tumor xenograft models. This first-in-human phase 1/2 study evaluated the safety, pharmacokinetics (PK), and clinical activity of single-agent MAK683 in advanced malignancies.

METHODS: MAK683 was administered fasted once daily or twice daily continuously in 28-day treatment cycles. Safety assessments included the nature of dose-limiting toxicities (DLTs) and the incidence and severity of adverse events (AEs) and serious AEs. The PK profile of MAK683 was assessed in sequential blood samples of cycles 1-6, and pharmacodynamic profiles were measured by H3K27me3 changes from baseline.

RESULTS: Overall, 139 patients (clear cell carcinoma of the ovary [CCCO], 9 [6.5%]; castration-resistant prostate cancer [CRPC], 22 [15.8 %]; diffuse large B-cell lymphoma [DLBCL], 31 [22.3%]; epithelioid sarcoma [ES], 17 [12.2 %]; gastric cancer [GC], 37 [26.6 %]; nasopharyngeal carcinoma [NPC], 17 [12.2 %]; SWI/SNF-mutated sarcoma, 6 [4.3 %]) received MAK683. Median duration of exposure was 57 days (range: 4-1006). Fifteen patients experienced 22 DLTs including thrombocytopenia (4.9 %) and febrile neutropenia (3.3 %). MAK683-related AEs were reported in 98 patients (70.5 %); 43 patients had grade 3/4 drug-related AEs, including neutropenia, thrombocytopenia, and anemia. MAK683 was quickly absorbed, with peak plasma concentrations ranging from 0.975 to 4.08 h. Median progression-free survival was 1.9 months (90 % confidence interval [CI]: 1.8-2.3), and overall response rate was 5.8 % (90 % CI: 2.52-11.03 %). Clinical activity was observed in patients with advanced DLBCL and ES.

CONCLUSION: Overall, MAK683 treatment was well tolerated, and clinical activity was observed in patients with advanced DLBCL and ES.

CLINICAL TRIAL INFORMATION: NCT02900651.

PMID:39793445 | DOI:10.1016/j.ejca.2024.115122

Medicine (Baltimore). 2025 Jan 10;104(2):e41259. doi: 10.1097/MD.0000000000041259.

ABSTRACT

RATIONALE: Malignant melanoma is a rare cancer that accounts for approximately 1% of all cancers. Primary malignant melanoma of the female genital tract accounts for approximately 3% to 7% of all malignant melanomas, and 0.3% to 0.8% of all melanomas in women. It affects postmenopausal women ages 60 to 80 years. Various hormonal factors, including puberty, pregnancy, menopause, oral contraceptive use, and human papillomavirus infection are associated with primary malignant melanoma of the vagina.

PATIENT CONCERNS: Symptoms often include vaginal bleeding, discharge, and pain; however, it can also present as pigmented or nonpigmented lesions, making diagnosis challenging.

DIAGNOSES: Diagnosis involves detailed history, physical examination, and imaging (CT, MRI, and positron emission tomography). Immunohistochemical staining for markers, such as human melanoma black-45 and Melan-A, is crucial for confirmation. The diagnosis was made through careful physical examination, imaging studies, and immunohistochemistry.

INTERVENTIONS: The treatment includes wide local excision, radical surgery, radiotherapy, chemotherapy, and immunotherapy. The prognosis of primary malignant melanoma of the vagina is usually poor owing to late diagnosis, and the 5-year survival rate is 5% to 25%.

OUTCOMES AND LESSONS: To consider the possibility of primary malignant melanoma of vagina, postmenopausal women, particularly those who with human papillomavirus infection, should be performed thorough examination regardless of symptoms of vaginal bleeding or discharge.

PMID:39792728 | DOI:10.1097/MD.0000000000041259

PLoS Comput Biol. 2025 Jan 10;21(1):e1012755. doi: 10.1371/journal.pcbi.1012755. Online ahead of print.

ABSTRACT

Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. By providing pre-trained models that can be fine-tuned for specific applications, they enable researchers to create accurate models with minimal effort and computational resources. Large scale genomics deep learning models come in two flavors: the first are large language models of DNA sequences trained in a self-supervised fashion, similar to the corresponding natural language models; the second are supervised learning models that leverage large scale genomics datasets from ENCODE and other sources. We argue that these models are the equivalent of foundation models in natural language processing in their utility, as they encode within them chromatin state in its different aspects, providing useful representations that allow quick deployment of accurate models of gene regulation. We demonstrate this premise by leveraging the recently created Sei model to develop simple, interpretable models of intron retention, and demonstrate their advantage over models based on the DNA language model DNABERT-2. Our work also demonstrates the impact of chromatin state on the regulation of intron retention. Using representations learned by Sei, our model is able to discover the involvement of transcription factors and chromatin marks in regulating intron retention, providing better accuracy than a recently published custom model developed for this purpose.

PMID:39792954 | DOI:10.1371/journal.pcbi.1012755

PLoS One. 2025 Jan 10;20(1):e0313226. doi: 10.1371/journal.pone.0313226. eCollection 2025.

ABSTRACT

Recovering diagnostic-quality cardiac MR images from highly under-sampled data is a current research focus, particularly in addressing cardiac and respiratory motion. Techniques such as Compressed Sensing (CS) and Parallel Imaging (pMRI) have been proposed to accelerate MRI data acquisition and improve image quality. However, these methods have limitations in high spatial-resolution applications, often resulting in blurring or residual artifacts. Recently, deep learning-based techniques have gained attention for their accuracy and efficiency in image reconstruction. Deep learning-based MR image reconstruction methods are divided into two categories: (a) single domain methods (image domain learning and k-space domain learning) and (b) cross/dual domain methods. Single domain methods, which typically use U-Net in either the image or k-space domain, fail to fully exploit the correlation between these domains. This paper introduces a dual-domain deep learning approach that incorporates multi-coil data consistency (MCDC) layers for reconstructing cardiac MR images from 1-D Variable Density (VD) random under-sampled data. The proposed hybrid dual-domain deep learning models integrate data from both the domains to improve image quality, reduce artifacts, and enhance overall robustness and accuracy of the reconstruction process. Experimental results demonstrate that the proposed methods outperform than conventional deep learning and CS techniques, as evidenced by higher Structural Similarity Index (SSIM), lower Root Mean Square Error (RMSE), and higher Peak Signal-to-Noise Ratio (PSNR).

PMID:39792851 | DOI:10.1371/journal.pone.0313226

Adv Sci (Weinh). 2025 Jan 10:e2407432. doi: 10.1002/advs.202407432. Online ahead of print.

ABSTRACT

Single nanoparticle analysis is crucial for various applications in biology, materials, and energy. However, precisely profiling and monitoring weakly scattering nanoparticles remains challenging. Here, it is demonstrated that deep learning-empowered plasmonic microscopy (Deep-SM) enables precise sizing and collision detection of functional chemical and biological nanoparticles. Image sequences are recorded by the state-of-the-art plasmonic microscopy during single nanoparticle collision onto the sensor surface. Deep-SM can enhance signal detection and suppresses noise by leveraging spatio-temporal correlations of the unique signal and noise characteristics in plasmonic microscopy image sequences. Deep-SM can provide significant scattering signal enhancement and noise reduction in dynamic imaging of biological nanoparticles as small as 10 nm, as well as the collision detection of metallic nanoparticle electrochemistry and quantum coupling with plasmonic microscopy. The high sensitivity and simplicity make this approach promising for routine use in nanoparticle analysis across diverse scientific fields.

PMID:39792780 | DOI:10.1002/advs.202407432