Discov Nano. 2025 Feb 11;20(1):26. doi: 10.1186/s11671-025-04208-8.

ABSTRACT

BACKGROUND: Infected wounds are a major health problem as infection can delay wound healing. Wound dressings play an important part in wound care by maintaining a suitable environment that promotes healing. Silver sulfadiazine dressings have been used to prevent infection in burn wounds. Presently, many commercial silver dressings have obtained FDA clearance.

RESULTS: In this study, we report on a novel silver dressing using microporous aluminosilicate zeolites, termed ABF-XenoMEM. Silver and zinc ions are encapsulated in the zeolite supercages. We show that the silver-zinc zeolite (AM30) alone is effective at inhibiting biofilm formation. The encapsulation protects the silver from rapidly precipitating in biological fluids. We exploit the negatively charged zeolite surface to associate positively charged quaternary ammonium ions (quat) with the zeolite. The combination of the AM30 with the quat enhances the antimicrobial activity. The colloidal nature of the zeolite materials makes it possible to make uniform deposits on a commercial extracellular matrix membrane to develop the final dressing (ABF-XenoMEM). The optimum loading of silver, zinc, and quat on the dressing was found to be 30, 3.7, and 221 µg/cm2. Using a colony biofilm model, the activity of ABF-XenoMEM is compared with four well-studied silver-based commercial dressings towards mature biofilms of Pseudomonas aeruginosa PAO1 (ATCC 4708) and methicillin-resistant Staphylococcus aureus (ATCC 33592). Cytotoxicity of the dressings was examined in HepG2 cells using the MTT assay.

CONCLUSION: This study shows that the ABF-XenoMEM is competitive with extensively used commercial wound dressings in a colony biofilm model. Nanozeolite-entrapped silver/zinc antimicrobials in association with quat have the potential for application in biofilm-infected wounds and require animal and clinical studies for definitive proof.

PMID:39932517 | DOI:10.1186/s11671-025-04208-8

J Gerontol A Biol Sci Med Sci. 2025 Feb 11:glaf026. doi: 10.1093/gerona/glaf026. Online ahead of print.

ABSTRACT

The aging process is universal, and it is characterized by a progressive deterioration and decrease in physiological function leading to decline on the organismal level. Nevertheless, a number of genetic and non-genetic interventions have been described, which successfully extend healthspan and lifespan in different species. Furthermore, a number of clinical trials have been evaluating the feasibility of different interventions to promote human health. The goal of the annual Biological Sciences Section of the Gerontological Society of America meeting was to share current knowledge of different topics in aging research and provide a vision of the future of aging research. The meeting gathered international experts in diverse areas of aging research including basic biology, demography, and clinical and translational studies. Specific topics included metabolism, inflammaging, epigenetic clocks, frailty, senescence, neuroscience, stem cells, reproductive aging, inter-organelle crosstalk, comparative transcriptomics of longevity, circadian clock, metabolomics, and biodemography.

PMID:39932386 | DOI:10.1093/gerona/glaf026

Elife. 2025 Feb 11;13:RP98427. doi: 10.7554/eLife.98427.

ABSTRACT

Excessive consumption of sucrose, in the form of sugar-sweetened beverages, has been implicated in the pathogenesis of metabolic dysfunction-associated fatty liver disease (MAFLD) and other related metabolic syndromes. The c-Jun N-terminal kinase (JNK) pathway plays a crucial role in response to dietary stressors, and it was demonstrated that the inhibition of the JNK pathway could potentially be used in the treatment of MAFLD. However, the intricate mechanisms underlying these interventions remain incompletely understood given their multifaceted effects across multiple tissues. In this study, we challenged rats with sucrose-sweetened water and investigated the potential effects of JNK inhibition by employing network analysis based on the transcriptome profiling obtained from hepatic and extrahepatic tissues, including visceral white adipose tissue, skeletal muscle, and brain. Our data demonstrate that JNK inhibition by JNK-IN-5A effectively reduces the circulating triglyceride accumulation and inflammation in rats subjected to sucrose consumption. Coexpression analysis and genome-scale metabolic modeling reveal that sucrose overconsumption primarily induces transcriptional dysfunction related to fatty acid and oxidative metabolism in the liver and adipose tissues, which are largely rectified after JNK inhibition at a clinically relevant dose. Skeletal muscle exhibited minimal transcriptional changes to sucrose overconsumption but underwent substantial metabolic adaptation following the JNK inhibition. Overall, our data provides novel insights into the molecular basis by which JNK inhibition exerts its metabolic effect in the metabolically active tissues. Furthermore, our findings underpin the critical role of extrahepatic metabolism in the development of diet-induced steatosis, offering valuable guidance for future studies focused on JNK-targeting for effective treatment of MAFLD.

PMID:39932177 | DOI:10.7554/eLife.98427

Inflammopharmacology. 2025 Feb 11. doi: 10.1007/s10787-025-01647-8. Online ahead of print.

ABSTRACT

In the dynamic realm of scientific inquiry, the identification and characterization of biologically active compounds derived from plant extracts have become of utmost significance. A particularly noteworthy flavonoid in this regard is aromadendrin (AMD), which can be found in a diverse range of foods, fruits, plants, and natural sources. The versatility of this compound is evident through its wide array of biological properties, including its well-documented anti-inflammatory, antioxidant, antidiabetic, neuroprotective, immunomodulatory, cardioprotective, and hepatoprotective effects. These diverse actions validate its potential utilization in addressing drug-related side effects, adverse reactions, neoplasms, ulcers, jaundice, diabetes mellitus, dermatitis, neurodegenerative diseases, cognitive disorders, polyploidy, carcinomas, common colds, and cumulative trauma disorders. This review aims to unlock the full potential of AMD and pave the way for groundbreaking advancements in the fields of medicine and nutrition. Prepare to embark on an enthralling journey as we unveil the hidden treasures and extraordinary prospects associated with AMD.

PMID:39932620 | DOI:10.1007/s10787-025-01647-8

Curr Drug Saf. 2025 Feb 7. doi: 10.2174/0115748863356840250112181406. Online ahead of print.

ABSTRACT

Pharmacovigilance is an important subject in medicine and healthcare, which aims to prevent side effects and other drug-related problems by identifying, evaluating, understanding, and avoiding them. Its main objectives are ensuring that a drug's benefits balance its hazards and improving patient safety. Within medicine and healthcare, pharmacovigilance is an essential subject that focuses on identifying, evaluating, comprehending, and preventing side effects or any other issues associated with drugs. Its main objective is to improve patient safety and ensure a drug's advantages exceed its drawbacks. Pharmacovigilance has evolved significantly as a result of technological advancements, enabling more efficient medication, safety monitoring, and management. The combination of machine learning (ML) with artificial intelligence (AI) for data analysis, adverse reaction prediction, and signal detection, electronic health records (EHRs), and mobile health (mHealth) applications have enhanced real-time data collecting and expedited the reporting of adverse drug reactions (ADRs). Pharmacovigilance plays an important role which focuses on detecting, assessing, comprehending, and averting adverse medication reactions. Making sure a drug's advantages outweigh its disadvantages is its main objective to improve patient safety. Pharmacovigilance, which balances patient safety, efficacy, and regulatory compliance in clinical trials, is necessary to promote the safe and effective use of drugs.

PMID:39931995 | DOI:10.2174/0115748863356840250112181406

Mol Pharm. 2025 Feb 11. doi: 10.1021/acs.molpharmaceut.4c01197. Online ahead of print.

ABSTRACT

Alcohol liver disease (ALD) is a chronic liver disorder resulting from long-term heavy alcohol consumption. The pathogenesis of ALD is multifactorial, and existing therapeutic agents primarily target specific aspects of the disease while presenting significant side effects, including drug-induced liver injury and hepatobiliary disease. Silibinin (SLB) has attracted widespread attention for its hepatoprotective effects and favorable safety profile. However, inherent limitations associated with SLB, such as poor solubility and bioavailability, have significantly limited its clinical application. Drug delivery systems, including liposomes, offer promising potential for the delivery of hydrophobic drugs. However, the selection of an appropriate delivery vehicle requires optimization. Ursodeoxycholic acid sodium (UAS) serves as a promising alternative to cholesterol in liposomal formulations, offering a potential strategy to mitigate the health risks associated with cholesterol. In this study, UAS was employed as the liposomal membrane material to prepare a UAS liposome loaded with SLB (SUL), and its efficacy and mechanism of action in alcoholic-induced liver injury were subsequently evaluated. The experimental results demonstrated that SUL exhibited a uniform particle size distribution, good stability, and an effective release profile in vitro. Following oral administration, SUL effectively inhibited alcohol-induced liver damage, oxidative stress, and fat accumulation. In addition, SUL regulated the expression of the kelch-1ike ECH- associated protein l (Keap1), nuclear factor erythroid 2-related factor 2 (Nrf2), and heme oxygenase 1 (HO-1) proteins, thereby exerting antioxidative stress effects. Furthermore, it also modulated apoptosis-related factors, including B-cell lymphoma-2 (Bcl-2), BCL-2-associated X (Bax), cysteinyl aspartate specific proteinase-3 (Caspase-3), and cleaved caspase-3, to mitigate hepatocyte apoptosis. In summary, SUL demonstrates enhanced therapeutic efficacy against ALD, offering a novel approach for the clinical application of SLB in the prevention and treatment of ALD.

PMID:39931930 | DOI:10.1021/acs.molpharmaceut.4c01197

J Med Virol. 2025 Feb;97(2):e70229. doi: 10.1002/jmv.70229.

ABSTRACT

The main protease (Mpro) of SARS-CoV-2 is an attractive drug target for antivirals, as this enzyme plays a key role in virus replication. Drug repurposing is a promising option for the treatment of coronavirus disease 2019 (COVID-19). Recently, a number of FDA-approved drugs have been identified as Mpro inhibitors, but stringent hit validation is lacking. In this study, we rigorously reevaluated the in vitro inhibition of the Mpro enzyme by repurposed drugs via combined experiments, including the fluorescence resonance energy transfer (FRET) assay, fluorescence polarization (FP) assay, and protease biosensor cleavage assay. Our results from a set of in vitro assays revealed that boceprevir is a potential Mpro inhibitor, but other repurposed drugs, including atazanavir, dipyridamole, entrectinib, ethacridine, glecaprevir, hydroxychloroquine, ivermectin, meisoindigo, pelitinib, raloxifene, roxatidine acetate, saquinavir, teicoplanin, thonzonium bromide, and valacyclovir, are not. Our research highlights that the use of candidate Mpro inhibitors from primary screening warrants further comprehensive studies before the reporting of new findings.

PMID:39930936 | DOI:10.1002/jmv.70229

ERJ Open Res. 2025 Feb 10;11(1):00442-2024. doi: 10.1183/23120541.00442-2024. eCollection 2025 Jan.

ABSTRACT

BACKGROUND: Pulmonary gas exchange is assessed by the transfer factor of the lungs (T L) for carbon monoxide (T LCO), and can also be measured with inhaled xenon-129 (129Xe) magnetic resonance imaging (MRI). A model has been proposed to estimate T L from 129Xe MRI metrics, but this approach has not been fully validated and does not utilise the spatial information provided by three-dimensional 129Xe MRI.

METHODS: Three models for predicting T L from 129Xe MRI metrics were compared: 1) a previously-published physiology-based model, 2) multivariable linear regression and 3) random forest regression. Models were trained on data from 150 patients with asthma and/or COPD. The random forest model was applied voxel-wise to 129Xe images to yield regional T L maps.

RESULTS: Coefficients of the physiological model were found to differ from previously reported values. All models had good prediction accuracy with small mean absolute error (MAE): 1) 1.24±0.15 mmol·min-1·kPa-1, 2) 1.01±0.06 mmol·min-1·kPa-1, 3) 0.995±0.129 mmol·min-1·kPa-1. The random forest model performed well when applied to a validation group of post-COVID-19 patients and healthy volunteers (MAE=0.840 mmol·min-1·kPa-1), suggesting good generalisability. The feasibility of producing regional maps of predicted T L was demonstrated and the whole-lung sum of the T L maps agreed with measured T LCO (MAE=1.18 mmol·min-1·kPa-1).

CONCLUSION: The best prediction of T LCO from 129Xe MRI metrics was with a random forest regression framework. Applying this model on a voxel-wise level to create parametric T L maps provides a useful tool for regional visualisation and clinical interpretation of 129Xe gas exchange MRI.

PMID:39931664 | PMC:PMC11808933 | DOI:10.1183/23120541.00442-2024

Front Cell Dev Biol. 2025 Jan 27;13:1526306. doi: 10.3389/fcell.2025.1526306. eCollection 2025.

ABSTRACT

Rare diseases affect a small percentage of an individual country's population; however, with over 7,000 in total, rare diseases represent a significant disease burden impacting up to 10% of the world's population. Despite this, there are no approved treatments for almost 95% of rare diseases, and the existing treatments are cost-intensive for the patients. More than 70% of rare diseases are genetic in nature, with patient-specific mutations. This calls for the need to have personalised and patient-specific preclinical models that can lead to effective, speedy, and affordable therapeutic options. Complex in vitro models (CIVMs), including those using induced pluripotent stem cells (iPSCs), organoids, and organs-on-chips are emerging as powerful human-based pre-clinical systems with the capacity to provide efficacy data enabling drugs to move into clinical trials. In this narrative review, we discuss how CIVMs are providing insights into biomedical research on rare diseases. We also discuss how these systems are being used in clinical trials to develop efficacy models for rare diseases. Finally, we propose recommendations on how human relevant CIVMs could be leveraged to increase translatability of basic, applied and nonclinical research outcomes in the field of rare disease therapeutics in developed as well as middle-and low-income countries.

PMID:39931243 | PMC:PMC11807990 | DOI:10.3389/fcell.2025.1526306

Ther Adv Respir Dis. 2025 Jan-Dec;19:17534666251314706. doi: 10.1177/17534666251314706.

ABSTRACT

BACKGROUND: Cystic fibrosis (CF) is characterized by chronic neutrophilic inflammation in the airways. Elexacaftor/tezacaftor/ivacaftor (ETI) therapy has demonstrably improved clinical outcomes and quality of life in people with CF (pwCF), but its effects on systemic inflammatory parameters remain unclear.

OBJECTIVE: To evaluate the impact of ETI on systemic inflammation in children and adolescents with CF.

DESIGN: Retrospective, dual-center observational, propensity score-matching study of pediatric pwCF on ETI.

METHODS: PwCF aged ⩽ 18 years treated with ETI at two Italian reference centers were included in this study. Data on immunoglobulins (Ig) (A, G, and M), γ-globulin, leukocyte levels, percent predicted forced expiratory volume in the first second (ppFEV1), sweat chloride (SC) concentration, and sputum cultures were collected at baseline, 12, and 24 months of treatment. Laboratory data of a control group (pwCF, not in ETI therapy, same demographic characteristics as the study group) were also collected.

RESULTS: Sixty-six patients (30 males, median age: 12 years, F508del homozygous: 23) were included. Mean IgG levels (SD) significantly decreased (p = 0.001) from 1168.20 mg/dl (344.41) at baseline to 1093.05 mg/dl (258.73; 12 months) and 1092.87 mg/dl (232.42; 24 months). Similar reductions were observed for IgA and γ-globulin; IgM reduction was not statistically significant. Leukocyte levels also decreased significantly from 8.04 × 103/µl (3.23 × 103) at baseline to 6.61 × 103/µl (1.74 × 103) (12 months) and 6.45 × 103/µl (1.70 × 103; 24 months). As for the control group, no significant changes in the levels of Ig, leukocytes, and γ-globulin were detected throughout the study period (p > 0.05).The mean (SD) ppFEV1 and the overall mean (SD) SC concentration significantly decreased during the follow-up. Regarding cultures, 18 (27%) of the 27 patients positive (41%) for Staphylococcus aureus at baseline became negative during treatment. Three patients (4%) with persistently positive cultures for Pseudomonas aeruginosa during the first 12 months, became negative after 24 months. One patient (1.5%), with a baseline positive culture for Pseudomonas Aeruginosa, showed negative cultures after 12 months.

CONCLUSION: ETI treatment improved respiratory outcomes and significantly reduced values of IgG, IgA, γ-globulin, and leukocytes, suggesting an effect on the systemic inflammatory response. Further research is warranted to elucidate the role of inflammatory parameters in monitoring response to therapy.

PMID:39930791 | DOI:10.1177/17534666251314706

J Pediatr Gastroenterol Nutr. 2025 Feb 10. doi: 10.1002/jpn3.70010. Online ahead of print.

ABSTRACT

OBJECTIVES: Food insecurity (FI), limited or uncertain access to adequate food, impacts every state, county, and community in the United States. The goals of this quality improvement (QI) initiative were to first achieve greater than 90% compliance with FI screening for patients seen at pediatric GI clinics within 1 year and second increase the proportion of families identified as FI connected with resources to 50% at follow-up visits.

METHODS: Using plan-do-study-act cycles, interventions were implemented to (1) educate, (2) create a screening process, (3) optimize communication with EMR utilization, and (4) connect families to resources. Descriptive statistics on all variables collected were performed. Differences between the FI and food secure groups were assessed using the Mann-Whitney test for continuous variables and the Chi-squared test for categorical variables. QIMacros® Quality Improvement/SPC Software for Excel was used to create process control charts to show improvement.

RESULTS: During the timeframe from August 29, 2022, to February 29, 2024, 2946 visits were completed in the GI clinic, and 58% (1731 patients) were screened for FI. Of the patients that were screened for FI, 13% screened positive. Compliance with FI screening improved to 90%, and connection to resources improved to 75%. Race, ethnicity, preferred language, and insurance were all significantly associated with FI, p < 0.001 CONCLUSIONS: This QI initiative demonstrates standardized FI screening improves FI identification and connection to resources.

PMID:39930736 | DOI:10.1002/jpn3.70010

Thorac Res Pract. 2025 Jan 20. doi: 10.4274/ThoracResPract.2024.24047. Online ahead of print.

ABSTRACT

OBJECTIVE: Composite Model for End-Stage Liver Disease (MELD), an adapted version of the model score excluding international normalised ratio (MELD-XI), was reported to predict outcomes in patients with organ failure. Aim of study was to evaluate the prognostic significance of the MELD-XI score and compare it with the Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation 2 (APACHE 2) scores in patients admitted to the intensive care unit (ICU) for respiratory failure.

MATERIAL AND METHODS: Out of 822 patients with respiratory failure between September 2020 and June 2023, a total of 727 patients with etiologies of chronic obstructive pulmonary disease exacerbation, cardiogenic pulmonary edema, pulmonary thromboembolism, pneumonia, bronchiectasis, kyphoscoliosis, neuromuscular diseases, obesity hypoventilation syndrome, and diffuse parenchymal lung disease were included.

RESULTS: A statistically significant correlation was found between MELD-XI, SOFA, and APACHE 2 scores. The cutoff value of the MELD-XI score was 11 on receiver operating characteristic analysis, indicating a higher risk of mortality in patients with a score of 11 or above. The APACHE 2 and SOFA scores of the MELD-XI ≥11 group were found to be higher and the Glasgow Coma Scale were lower than the MELD-XI <11 group. MELD-XI ≥11 was associated with an increased risk of mortality in overall [Hazard ratio (HR): 4.1, 95% confidence interval (CI): 2-6.4, P < 0.001] and subgroups with different etiologies in Cox regression analysis. In the multivariate analysis, MELD-XI was the most important independent variable indicating an increased risk of mortality, regardless of etiology (HR: 2.4, 95% CI: 2.0-2.5, P < 0.001).

CONCLUSION: MELD-XI is an important marker of ICU mortality in patients with respiratory failure due to different etiologies and is as effective as the SOFA and APACHE 2 in predicting mortality.

PMID:39930732 | DOI:10.4274/ThoracResPract.2024.24047

Drug Deliv. 2025 Dec;32(1):2463428. doi: 10.1080/10717544.2025.2463428. Epub 2025 Feb 10.

ABSTRACT

Nanoparticles-based gene delivery has emerged as a promising approach for the treatment of genetic diseases based on efficient delivery systems for therapeutic nucleic acids (NAs) into the target cells. For pulmonary diseases such as cystic fibrosis (CF), chronic obstructive pulmonary diseases (COPD), infectious disease or lung cancer, aerosol delivery is the best choice to locally deliver NAs into the lungs. It is, therefore, important to investigate the effects of nebulization conditions on the efficiency of delivery. To this purpose, the non-viral vector branched polyethyleneimine (b-PEI, 25 kDa) was investigated for plasmid delivery by aerosol. Two types of nebulizers, jet nebulizer and mesh nebulizer, were compared regarding the properties of the nanoparticles (NPs) formed, the efficiency of NAs delivery in vitro and in vivo models and the pulmonary deposition. The results indicate that the mesh nebulizer has a better gene delivery performance than the jet nebulizer in this application. This superiority was demonstrated in terms of size, concentration, distribution of NPs and efficiency of NAs delivery. However, pulmonary deposition appears to be similar regardless of the nebulizer used, and the difference between the two systems lies in the inhalable dose. These results underline the crucial role of nebulization techniques in optimizing aerosol-mediated gene delivery by b-PEI and highlight the potential of mesh nebulizers as promising tools to improved gene therapy. Therefore, the comparison must be performed for each gene therapy formulation to determine the most suitable nebulizer.

PMID:39930696 | DOI:10.1080/10717544.2025.2463428

Spine (Phila Pa 1976). 2025 Feb 11. doi: 10.1097/BRS.0000000000005296. Online ahead of print.

NO ABSTRACT

PMID:39931786 | DOI:10.1097/BRS.0000000000005296

Heliyon. 2025 Jan 9;11(3):e41850. doi: 10.1016/j.heliyon.2025.e41850. eCollection 2025 Feb 15.

ABSTRACT

BACKGROUND: As one of the cancers with the highest incidence and mortality rates worldwide, the timeliness and accuracy of cell type diagnosis in lung cancer are crucial for patients' treatment decisions. This study aims to develop a novel deep learning model to provide efficient, accurate, and cost-effective auxiliary diagnosis for the pathological types of lung cancer cells.

METHOD: This paper introduces a model named PortNet, designed to significantly reduce the model's parameter size and achieve lightweight characteristics without compromising classification accuracy. We incorporated 1 × 1 convolutional blocks into the Depthwise Separable Convolution architecture to further decrease the model's parameter count. Additionally, the integration of the Squeeze-and-Excitation self-attention module enhances feature representation without substantially increasing the number of parameters, thereby maintaining high predictive performance.

RESULT: Our tests demonstrated that PortNet significantly reduces the total parameter count to 2,621,827, which is over a fifth smaller compared to some mainstream CNN models, marking a substantial advancement for deployment in portable devices. We also established widely-used traditional models as benchmarks to illustrate the efficacy of PortNet. In external tests, PortNet achieved an average accuracy (ACC) of 99.89 % and Area Under the Curve (AUC) of 99.27 %. During five-fold cross-validation, PortNet maintained an average ACC of 99.51 % ± 1.50 % and F1 score of 99.50 % ± 1.51 %, showcasing its lightweight capability and exceptionally high accuracy. This presents a promising opportunity for integration into hospital systems to assist physicians in diagnosis.

CONCLUSION: This study significantly reduces the parameter count through an innovative model structure while maintaining high accuracy and stability, demonstrating outstanding performance in lung cancer cell classification tasks. The model holds the potential to become an efficient, accurate, and cost-effective auxiliary diagnostic tool for pathological classification of lung cancer in the future.

PMID:39931476 | PMC:PMC11808607 | DOI:10.1016/j.heliyon.2025.e41850

Ophthalmol Sci. 2024 Nov 28;5(2):100659. doi: 10.1016/j.xops.2024.100659. eCollection 2025 Mar-Apr.

ABSTRACT

PURPOSE: Recent studies utilized ocular images and deep learning (DL) to predict refractive error and yielded notable results. However, most studies did not address biases from imbalanced datasets or conduct external validations. To address these gaps, this study aimed to integrate the deep imbalanced regression (DIR) technique into ResNet and Vision Transformer models to predict refractive error from retinal photographs.

DESIGN: Retrospective study.

SUBJECTS: We developed the DL models using up to 103 865 images from the Singapore Epidemiology of Eye Diseases Study and the United Kingdom Biobank, with internal testing on up to 8067 images. External testing was conducted on 7043 images from the Singapore Prospective Study and 5539 images from the Beijing Eye Study. Retinal images and corresponding refractive error data were extracted.

METHODS: This retrospective study developed regression-based models, including ResNet34 with DIR, and SwinV2 (Swin Transformer) with DIR, incorporating Label Distribution Smoothing and Feature Distribution Smoothing. These models were compared against their baseline versions, ResNet34 and SwinV2, in predicting spherical and spherical equivalent (SE) power.

MAIN OUTCOME MEASURES: Mean absolute error (MAE) and coefficient of determination were used to evaluate the models' performances. The Wilcoxon signed-rank test was performed to assess statistical significance between DIR-integrated models and their baseline versions.

RESULTS: For prediction of the spherical power, ResNet34 with DIR (MAE: 0.84D) and SwinV2 with DIR (MAE: 0.77D) significantly outperformed their baseline-ResNet34 (MAE: 0.88D; P < 0.001) and SwinV2 (MAE: 0.87D; P < 0.001) in internal test. For prediction of the SE power, ResNet34 with DIR (MAE: 0.78D) and SwinV2 with DIR (MAE: 0.75D) consistently significantly outperformed its baseline-ResNet34 (MAE: 0.81D; P < 0.001) and SwinV2 (MAE: 0.78D; P < 0.05) in internal test. Similar trends were observed in external test sets for both spherical and SE power prediction.

CONCLUSIONS: Deep imbalanced regressed-integrated DL models showed potential in addressing data imbalances and improving the prediction of refractive error. These findings highlight the potential utility of combining DL models with retinal imaging for opportunistic screening of refractive errors, particularly in settings where retinal cameras are already in use.

FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

PMID:39931359 | PMC:PMC11808727 | DOI:10.1016/j.xops.2024.100659

Data Brief. 2025 Jan 21;59:111311. doi: 10.1016/j.dib.2025.111311. eCollection 2025 Apr.

ABSTRACT

A comprehensive Hog plum leaf disease dataset is greatly needed for agricultural research, precision agriculture, and efficient management of disease. It will find applications toward the formulation of machine learning models for early detection and classification of disease, thus reducing dependency on manual inspections and timely interventions. Such a dataset provides a benchmark for training and testing algorithms, further enhancing automated monitoring systems and decision-support tools in sustainable agriculture. It enables better crop management, less use of chemicals, and more focused agronomical practices. This dataset will contribute to the global research being carried out for the advancement of disease-resistant plant strategy development and efficient management practices for better agricultural productivity along with sustainability. These images have been collected from different regions of Bangladesh. In this work, two classes were used: 'Healthy' and 'Insect hole', representing different stages of disease progression. The augmentation techniques that involve flipping, rotating, scaling, translating, cropping, adding noise, adjusting brightness, adjusting contrast, and scaling expanded a dataset of 3782 images to 20,000 images. These have formed very robust deep learning training sets, hence better detection of the disease.

PMID:39931093 | PMC:PMC11808602 | DOI:10.1016/j.dib.2025.111311

Front Oncol. 2025 Jan 27;15:1507592. doi: 10.3389/fonc.2025.1507592. eCollection 2025.

ABSTRACT

Cervical cancer remains a significant global health concern, characterized by high morbidity and mortality rates. High-dose-rate brachytherapy (HDR-BT) is a critical component of cervical cancer treatment, requiring precise and efficient treatment planning. However, the process is labor-intensive, heavily reliant on operator expertise, and prone to variability due to factors such as applicator shifts and organ filling changes. Recent advancements in artificial intelligence (AI), particularly in medical image processing, offer significant potential for automating and standardizing treatment planning in HDR-BT. This review examines the progress and challenge of AI applications in HDR-BT treatment planning, focusing on automatic segmentation, applicator reconstruction, dose calculation, and plan optimization. By addressing current limitations and exploring future directions, this paper aims to guide the integration of AI into clinical practice, ultimately improving treatment accuracy, reducing preparation time, and enhancing patient outcomes.

PMID:39931087 | PMC:PMC11808022 | DOI:10.3389/fonc.2025.1507592

Biomed Rep. 2025 Jan 23;22(3):52. doi: 10.3892/br.2025.1930. eCollection 2025 Mar.

ABSTRACT

Metabolic disorders are a significant feature of fibrotic diseases. Nevertheless, the lack of sufficient proof regarding the cause-and-effect association between circulating metabolites and the promotion or prevention of idiopathic pulmonary fibrosis (IPF) persists. To assess the causal association between IPF and genetic proxies of 486 blood metabolites, a dual sample Mendelian randomization (MR) analysis was performed. Therefore, the two-sample MR technique and genome-wide association study data were employed to assess the association between 486 serum metabolites and IPF. To produce the primary outcomes, the inverse variance weighted (IVW) technique was applied, while to assess the stability and dependability of the outcomes, sensitivity analysis using MR-Egger analysis was performed. Additionally, weighted median, Cochran's Q-test, Egger intercept test and the leave-one-out method were used. The results of the present study revealed a total of 21 metabolites in blood circulation that could affect the risk of IPF (PIVW<0.05). Among them, 10 compounds were already known, namely cotinine [odds ratio (OR)=1.206; 95% confidence interval (CI), 1.002-1.452; P=0.047], hypoxanthine (OR=0.225; 95% CI, 0.056-0.899; P=0.034), aspartyl phenylalanine (OR=4.309; 95% CI, 1.084-17.131; P=0.038), acetyl-carnitine (OR=5.767; 95% CI, 1.398-23.789; P=0.015), 2-aminobutyrate (OR=0.155; 95% CI, 0.033-0.713; P=0.016), Docosapentaenoic acid (PubChem ID: 5497182; OR=0.214; 95% CI, 0.055-0.833; P=0.026), octanoyl-carnitine (PubChem ID: 177508; OR=3.398; 95% CI, 1.179-9.794; P=0.023), alpha-hydroxy-isovalerate (PubChem ID: 857803-94-2; OR=0.324; 95% CI, 0.112-0.931; P=0.036), 1,7-dimethylurate (PubChem ID: 91611; OR=0.401; 95% CI, 0.172-0.931; P=0.033) and 1-linoleoyl-glycerophosphocholine (PubChem ID: 657272; OR=6.559; 95% CI, 1.060-40.557; P=0.043). Additionally, the study also identified 11 currently unknown chemical structures. The results of Cochran's Q-test indicated that there was no significant heterogeneity, while MR-Egger's intercept analysis verified the lack of horizontal pleiotropy. The retention of one method for plotting also supported the reliability of the MR analysis. Overall, the results of the current study supported the cause-and-effect association between IPF and 21 blood metabolites, including 10 with already known chemical composition and 11 which are still awaiting determination. These findings could provide novel insights for the further investigation of the mechanism underlying the development of IPF.

PMID:39931651 | PMC:PMC11808644 | DOI:10.3892/br.2025.1930

F1000Res. 2024 Mar 22;13:216. doi: 10.12688/f1000research.142513.1. eCollection 2024.

ABSTRACT

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a disease with high mortality, and there are only two specific drugs available for therapeutic management with limitations. The study aims to identify comprehensive therapeutic mechanisms of Zingiber zerumbet rhizomes (ZZR) to treat IPF by using network pharmacology followed battery of in silico studies.

METHODS: The protein-protein interaction network was developed using Cytoscape to obtain core disease targets involved in IPF and their interactive molecules of ZZR. Based on the pharmacophore properties of phytomolecules from ZZR, the drug targets in IPF were explored. Protein-protein interaction network was built in Cytoscape to screen potential targets and components of ZZR. Molecular docking and dynamics were conducted as an empirical study to investigate the mechanism explored through network pharmacology in relation to the hub targets.

RESULTS: The network analysis conferred kaempferol derivatives that had demonstrated a promising therapeutic effect on the perturbed, robust network hubs of TGF-β1, EGFR, TNF-α, MMP2 & MMP9 reported to alter the biological process of mesenchymal transition, myofibroblast proliferation, and cellular matrix deposition in pulmonary fibrosis. The phytomolecules of ZZR act on two major significant pathways, namely the TGF-β-signaling pathway and the FOXO-signaling pathway, to inhibit IPF. Confirmational molecular docking and dynamics simulation studies possessed good stability and interactions of the protein-ligand complexes by RMSD, RMSF, rGyr, SASA, and principal component analysis (PCA). Validated molecular docking and dynamics simulations provided new insight into exploring the mechanism and multi-target effect of ZZR to treat pulmonary fibrosis by restoring the alveolar phenotype through cellular networking.

CONCLUSIONS: Network pharmacology and in silico studies confirm the multitargeted activity of ZZR in the treatment of IPF. Further in vitro and in vivo studies are to be conducted to validate these findings.

PMID:39931327 | PMC:PMC11809647 | DOI:10.12688/f1000research.142513.1