Int J Mol Sci. 2025 Jan 21;26(3):872. doi: 10.3390/ijms26030872.

ABSTRACT

Amyotrophic lateral sclerosis (ALS) has an interactive, multifactorial etiology that makes treatment success elusive. This study evaluates how regulatory dynamics impact disease progression and treatment. Computational models of wild-type (WT) and transgenic SOD1-G93A mouse physiology dynamics were built using the first-principles-based first-order feedback framework of dynamic meta-analysis with parameter optimization. Two in silico models were developed: a WT mouse model to simulate normal homeostasis and a SOD1-G93A ALS model to simulate ALS pathology dynamics and their response to in silico treatments. The model simulates functional molecular mechanisms for apoptosis, metal chelation, energetics, excitotoxicity, inflammation, oxidative stress, and proteomics using curated data from published SOD1-G93A mouse experiments. Temporal disease progression measures (rotarod, grip strength, body weight) were used for validation. Results illustrate that untreated SOD1-G93A ALS dynamics cannot maintain homeostasis due to a mathematical oscillating instability as determined by eigenvalue analysis. The onset and magnitude of homeostatic instability corresponded to disease onset and progression. Oscillations were associated with high feedback gain due to hypervigilant regulation. Multiple combination treatments stabilized the SOD1-G93A ALS mouse dynamics to near-normal WT homeostasis. However, treatment timing and effect size were critical to stabilization corresponding to therapeutic success. The dynamics-based approach redefines therapeutic strategies by emphasizing the restoration of homeostasis through precisely timed and stabilizing combination therapies, presenting a promising framework for application to other multifactorial neurodegenerative diseases.

PMID:39940644 | DOI:10.3390/ijms26030872

Nutrients. 2025 Jan 30;17(3):518. doi: 10.3390/nu17030518.

ABSTRACT

Micronutrient deficiencies affect over three billion people globally; there is a particularly severe problem with iron and zinc nutrition in developing countries. While several strategies exist to combat these deficiencies, biofortification has emerged as a powerful and sustainable approach to enhance the nutritional value of staple crops. This review examines recent advances in crop biofortification and their potential to address global nutritional challenges. We present successful case studies including iron-enriched cassava, nutrient-enhanced tomatoes, and omega-3-fortified oilseed crops, demonstrating the diverse possibilities for improving nutritional outcomes. The integration of novel plant-based protein production techniques has further expanded opportunities for sustainable nutrition. However, significant challenges remain, including complex environmental interactions, regulatory considerations, and sociocultural barriers to adoption. Economic analyses suggest biofortification offers substantial return on investment, with every dollar invested generating up to seventeen dollars in benefits through reduced disease burden. As global food security challenges intensify due to climate change, biofortified crops represent a crucial tool for improving nutritional outcomes, particularly in low- and middle-income countries. We conclude by examining emerging opportunities and future directions in this rapidly evolving field.

PMID:39940376 | DOI:10.3390/nu17030518

Cancer. 2025 Feb 15;131(4):e35766. doi: 10.1002/cncr.35766.

ABSTRACT

BACKGROUND: Older adults with advanced cancer are at higher risk of treatment-related toxicities, which can impair function. Relationships between clinician-rated and patient-reported toxicities with functional decline remain unclear.

METHODS: This secondary analysis of the GAP70+ trial aimed to evaluate the associations between clinician-rated (Clinician-rated common Terminology Criteria for Adverse Events [CTCAE]) and patient-reported toxicities (PRO-CTCAE) with changes in physical performance and functional outcomes in older adults receiving systemic therapy. Physical performance was measured using the Short Physical Performance Battery (SPPB; impairment: score ≤9). Functional capacity was assessed using activities of daily living (ADL) and instrumental ADL (IADL); impairment: any task difficulty. Toxicities were captured by CTCAE and PRO-CTCAE, which assess symptom severity and activity interferences. Generalized estimating equations evaluated the association of toxicity grades (0-1, 2, ≥3) within 3 months of treatment initiation with new functional impairments within 6 months.

RESULTS: Patients were age 70 to 96 years. At baseline, 82.9% had impaired SPPB, 51.5% had impaired IADL, and 27.4% had impaired ADL. Among patients without baseline impairments, 57.7%, 47.4%, and 31.0% developed new SPPB, IADL, and ADL impairments, respectively. No association was found between CTCAE toxicity and new SPPB impairment (p = .70), but higher PRO-CTCAE toxicity severity (p = .02) and interference (p = .02) were associated with new SPPB impairments. New IADL impairments were more common with higher grades of CTCAE (p = .02) severe PRO-CTCAE toxicities (p = .02).

CONCLUSION: These findings emphasize the need to assess both clinician-rated and patient-reported toxicities to understand and mitigate functional decline in older adults with advanced cancer.

PMID:39945245 | DOI:10.1002/cncr.35766

Cancers (Basel). 2025 Jan 27;17(3):437. doi: 10.3390/cancers17030437.

ABSTRACT

Objectives: The primary aim of this phase 1 trial is to establish the recommended phase 2 dose (RP2D) of tazemetostat given with a fixed dose of pembrolizumab in patients with recurrent or metastatic head and neck squamous cell carcinomas (RM-HNSCCs). Methods: A 3 + 3 dose-escalation phase 1 design was used to assess three dose-levels of tazemetostat (400, 600, and 800 mg orally, twice daily) with pembrolizumab (200 mg intravenously). Cycle 1 was 35 days (tazemetostat days 1-35; pembrolizumab day 15). Subsequent cycles were 21 days (tazemetostat days 1-21; pembrolizumab day 1). Dose-limiting toxicity (DLT), assessed during cycle 1, was defined as study-drug-related grade 4 neutropenia or thrombocytopenia, grade 3 febrile neutropenia, or grade 3-4 non-hematologic adverse events (AEs). Patients had to have completed cycle 1 to be evaluable for the DLT assessment; otherwise, an equal number of additional patients were enrolled. The RP2D was defined as the highest dose level in which zero of three or less than or equal to one of six patients experienced a DLT. Results: Twelve patients were enrolled: three on 400 mg, three on 600 mg, and six on the 800 mg dose level of tazemetostat. Three patients on the 800 mg dose level did not complete cycle 1 and were not evaluable for DLT. In the other nine patients, DLTs did not occur during cycle 1. In all 12 patients, the most common AEs included anemia (10 patients), fatigue (eight), and hyponatremia (seven). Conclusions: Among the patients with RM-HNSCCs, the RP2D of tazemetostat was 800 mg and administered twice daily when given with pembrolizumab.

PMID:39941804 | DOI:10.3390/cancers17030437

Eur J Pharm Sci. 2025 Feb 10:107039. doi: 10.1016/j.ejps.2025.107039. Online ahead of print.

ABSTRACT

Adenosine, a pervasive signaling molecule mediated by its interaction with G-protein-coupled receptor subtypes, especially the A2A adenosine receptor (A2AAR), plays a crucial role in cancer treatment. Recently, A2AAR targeting adenosine analogs have been proposed as a potential therapeutic target for cancer treatment. However, the molecules targeting A2AAR and their mode of action in inhibiting glioblastoma cell progression remain unknown. We synthesized six adenosine derivatives substituted at the 9-, 2- and/or N6- and/or 8- positions, and their anti-proliferative efficacy against the GBM cell lines LN229 and SNB19 was assessed. Molecular dynamic simulation integrated with experimental analyses, including cell cycle arrest, apoptosis assay, ligand binding assay, absorption, distribution, metabolism, excretion and toxicity (ADMET) profiling, PAMPA assay, and 3D spheroid analysis, were performed to identify the interaction efficacy of the potential derivative with A2AAR and its ability to prevent GBM cell progression. The most potent A2AAR derivative (ANR), 4-(2-((6-Amino-9-ethyl-8-(furan-2-yl)-9H-purin-2-yl)amino)ethyl)phenol (ANR 672) inhibits 5'-N-Ethylcarboxamidoadenosine (NECA)-induced cAMP validating the antagonistic property with higher cytotoxicity effect against GBM cells. ANR 672 showed higher affinity toward A2AAR (Ki=1.02 ± 0.06 nM) and exhibited significant IC50 concentrations of ∼ 60-80 µM, than FDA approved drug istredefylline. The A2AAR-ANR 672 interaction profile showed well-defined hydrogen bonds and hydrophobic contacts, indicating a typical binding mechanism inside the receptor pocket and a higher degree of conformational flexibility than the A2AAR-Istradefylline complex. The antagonist effect of ANR 672 blocked the A2AAR signaling pathway, leading to necrosis-mediated cell death and cell cycle arrest at the S-phase in both the GBM cells. ANR 672 treated 3D tumour spheroids analysis with real-time spheroid volume and cell proliferation analysis revealed the potential ability of ANR 672 against GBM cell growth. Drug-likeness assessments also showed favorable pharmacokinetic profiles for ANR 672. Further validation of blood-brain barrier crossing potential revealed that ANR 672 possesses moderate permeability. Our findings shed light on how ANR 672 exerts its GBM-suppressive effect through the interaction of A2AAR. These preclinical results suggest that A2AAR blockade could be a unique strategy for treating GBM.

PMID:39938810 | DOI:10.1016/j.ejps.2025.107039

J Cyst Fibros. 2025 Feb 11:S1569-1993(25)00056-6. doi: 10.1016/j.jcf.2025.02.006. Online ahead of print.

NO ABSTRACT

PMID:39939279 | DOI:10.1016/j.jcf.2025.02.006

Med Princ Pract. 2025 Feb 12:1-16. doi: 10.1159/000544111. Online ahead of print.

ABSTRACT

OBJECTIVE: Pseudomonas aeruginosa biofilms contribute to the persistent presence of this bacterium in the cystic fibrosis airways. P. aeruginosa produces histamine in vitro and expresses histamine receptors. We investigated whether histamine regulated P. aeruginosa biofilm formation in vitro and contributed to bacterial virulence in Galleria mellonella.

SUBJECT AND METHODS: P. aeruginosa biofilms were measured by staining bacteria adhered on polystyrene with crystal violet. Histamine concentrations were measured by ELISA. G. mellonella survival upon inoculation with P. aeruginosa was measured in the absence or presence of histamine.

RESULTS: The concentration of histamine in the BHI broth was 140 ng/ml (1.3 M). Addition to the broth of diamine oxidase (DAO), an enzyme that catabolizes histamine, reduced by ~ 3-fold the concentration of histamine and by 2-fold PAO1 strain biofilms. Addition of histamine (10-9 M - 10-4 M) to the LB medium augmented P. aeruginosa biofilms. Maximum effects were observed with concentrations of 10-5 M and 10-8 M for the mucoid NH57388A strain and the PAO1 strain, respectively. DAO reduced mucoid NH57388A biofilms induced by histamine (10-4 M) added to the LB medium. Addition of histamine to 48 h formed biofilms reduced anti-biofilm activities of gentamicin and azithromycin. Inoculation of G. mellonella with the PAO1 strain led to augmented histamine concentration in the haemolymph. Inoculation of histamine (10-8 M) reduced the survival rate of G. mellonella infected with the PAO1 strain.

CONCLUSION: Histamine produced during periods of infection may augment P. aeruginosa virulence by promoting the biofilm mode of life of this bacterium.

PMID:39938505 | DOI:10.1159/000544111

Ann Biomed Eng. 2025 Feb 12. doi: 10.1007/s10439-025-03691-5. Online ahead of print.

ABSTRACT

PURPOSE: Sleep Apnea (SA) affects an estimated 936 million adults globally, posing a significant public health concern. The gold standard for diagnosing SA, polysomnography, is costly and uncomfortable. Electroencephalogram (EEG)-based SA detection is promising due to its ability to capture distinctive sleep stage-related characteristics across different sub-band frequencies. This study aims to review and analyze research from the past decade on the potential of EEG signals in SA detection and classification focusing on various deep learning and machine learning techniques, including signal decomposition, feature extraction, feature selection, and classification methodologies.

METHOD: A systematic literature review using the preferred reporting items for systematic reviews and meta-Analysis (PRISMA) and PICO guidelines was conducted across 5 databases for publications from January 2010 to December 2024.

RESULTS: The review involved screening a total of 402 papers, with 63 selected for in-depth analysis to provide valuable insights into the application of EEG signals for SA detection. The findings underscore the potential of EEG-based methods in improving SA diagnosis.

CONCLUSION: This study provides valuable insights, showcasing significant advancements while identifying key areas for further exploration, thereby laying a strong foundation for future research in EEG-based SA detection.

PMID:39939549 | DOI:10.1007/s10439-025-03691-5

Sci Rep. 2025 Feb 12;15(1):5206. doi: 10.1038/s41598-025-89358-6.

ABSTRACT

The agriculture sector is crucial to many economies, particularly in developing regions, with post-harvest technology emerging as a key growth area. The oleaster, valued for its nutritional and medicinal properties, has traditionally been graded manually based on color and appearance. As global demand rises, there is a growing need for efficient automated grading methods. Therefore, this study aimed to develop a real-time machine vision system for classifying oleaster fruit at various grading velocities. Initially, in the offline phase, a dataset containing video frames of four different quality classes of oleaster, categorized based on the Iranian national standard, was acquired at different linear conveyor belt velocities (ranging from 4.82 to 21.51 cm/s). The Mask R-CNN algorithm was used to segment the extracted frames to obtain the position and boundary of the samples. Experimental results indicated that, with a 100% detection rate and an average instance segmentation accuracy error ranging from 4.17 to 5.79%, the Mask R-CNN algorithm is capable of accurately segmenting all classes of oleaster at all the examined grading velocity levels. The results of the fivefold cross validation indicated that the general YOLOv8x and YOLOv8n models, created using the dataset obtained from all conveyor belt velocity levels, have a similarly reliable classification performance. Therefore, given its simpler architecture and lower processing time requirements, the YOLOv8n model was used to evaluate the grading system in real-time mode. The overall classification accuracy of this model was 92%, with a sensitivity range of 87.10-94.89% for distinguishing different classes of oleaster at a grading velocity of 21.51 cm/s. The results of this study demonstrate the effectiveness of deep learning-based models in developing grading machines for the oleaster fruit.

PMID:39939355 | DOI:10.1038/s41598-025-89358-6

Nutr Metab Cardiovasc Dis. 2024 Dec 29:103841. doi: 10.1016/j.numecd.2024.103841. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: The growing global burden of diabetes and stroke poses a significant public health challenge. This study aims to analyze factors and create an interpretable stroke prediction model for diabetic patients.

METHODS AND RESULTS: Data from 20,014 patients were collected from the Affiliated Drum Tower Hospital, Medical School of Nanjing University, between 2021 and 2022. After handling the missing values, feature engineering included LASSO, SVM-RFE, and multi-factor regression techniques. The dataset was split 8:2 for training and testing, with the Synthetic Minority Oversampling Technique (SMOTE) to balance classes. Various machine learning and deep learning techniques, such as Random Forest (RF) and deep neural networks (DNN), have been utilized for model training. SHAP and a dedicated website showed the interpretability and practicality of the model. This study identified 11 factors influencing stroke incidence, with the RF and DNN algorithms achieving AUC values of 0.95 and 0.91, respectively. The Stroke Management and Analysis Risk Tool (SMART) was developed for clinical use.

PRIMARY ENDPOINT: The predictive performance of SMART in assessing stroke risk in diabetic patients was evaluated using AUC.

SECONDARY ENDPOINTS: Evaluated accuracy (precision, recall, F1-score), interpretability via SHAP values, and clinical utility, emphasizing user interface. Statistical analysis of EHR data using univariate and multivariate methods, with model validation on a separate test set.

CONCLUSIONS: An interpretable stroke-predictive model was created for patients with diabetes. This model proposes that standard clinical and laboratory parameters can predict the stroke risk in individuals with diabetes.

PMID:39939252 | DOI:10.1016/j.numecd.2024.103841

Magn Reson Imaging. 2025 Feb 10:110358. doi: 10.1016/j.mri.2025.110358. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate the use of deep learning (DL) T2-weighted turbo spin echo (TSE) imaging sequence with deep learning acceleration (T2DL) in prostate MRI regarding the necessity of hyoscine butylbromide (HBB) administration for high image quality.

METHODS: One hundred twenty consecutive patients divided into four groups (30 for each group) were included in this study. All patients received a T2DL (version 2022/23) and a conventional T2 TSE (cT2) sequence on an implemented 3 T scanner and software system. Group A received cT2 with HBB compared to T2DL without HBB with a field of view (FOV) of 130 mm and group B with a FOV of 160 mm. Group C received both sequences with a FOV of 160 mm plus HBB and group D without HBB. Two radiologists independently evaluated all imaging datasets in a blinded reading regarding motion, sharpness, noise, and diagnostic confidence. Furthermore, we analyzed quantitative parameters by calculating edge rise distance (ERD), signal-to-noise-ratio (SNR), and contrast-to-noise-ratio (CNR). Friedman test was used for group comparisons.

RESULTS: Baseline characteristics showed no significant differences between groups A-D. After HBB cT2 showed less motion artifacts, more sharpness, and a higher diagnostic confidence than T2DL, though DL sequences had significantly lower noise (p < 0.01). Quantitative analysis revealed higher SNR and CNR for T2DL sequences (p < 0.01), while edge rise distance (ERD) remained similar. Inter-reader agreement was good to excellent, with ICCs ranging from 0.84 to 0.93. T2DL acquisition time was significantly lower than for cT2.

CONCLUSIONS: In our study, cT2 sequences with HBB showed superior image quality and diagnostic confidence while the T2DL sequence offer promising potential for reducing MRI acquisition times and performed better in quantitative measures like SNR and CNR. Additional studies are required to evaluate further adjusted and developed DL applications for prostate MRI on upcoming scanner generations and to assess tumor detection rates.

PMID:39938669 | DOI:10.1016/j.mri.2025.110358

Cell Rep Med. 2025 Feb 5:101947. doi: 10.1016/j.xcrm.2025.101947. Online ahead of print.

ABSTRACT

Hypertension management is complex due to the need for multiple drug combinations and consideration of diverse outcomes. Traditional treatment effect estimation methods struggle to address this complexity, as they typically focus on binary treatments and binary outcomes. To overcome these challenges, we introduce a framework that accommodates multiple drug combinations and multiple outcomes (METO). METO uses multi-treatment encoding to handle drug combinations and sequences, distinguishing between effectiveness and safety outcomes by learning the outcome type during prediction. To mitigate confounding bias, METO employs an inverse probability weighting method for multiple treatments, assigning balance weights based on propensity scores. Evaluated on real-world data, METO achieves significant performance improvements over existing methods, with an average improvement of 6.4% in influence function-based precision of estimating heterogeneous effects. A case study demonstrates METO's ability to identify personalized antihypertensive treatments that optimize efficacy and minimize safety risks, highlighting its potential for improving hypertension treatment strategies.

PMID:39938524 | DOI:10.1016/j.xcrm.2025.101947

ACS Appl Mater Interfaces. 2025 Feb 12. doi: 10.1021/acsami.4c21657. Online ahead of print.

ABSTRACT

Biodegradable poly(β-amino) esters (PBAEs) have been a focus of interest for delivering therapeutic siRNA for several years. While no approved therapies are on the market yet, our study aims to advance PBAE-based treatments for currently "undruggable" diseases. The PBAEs used in this study are based on a recently reported step-growth copolymerization, which results in polymers with a unique balance of lipophilicity and positive charge, thereby showcasing diverse properties. Upon incubation with siRNA, these PBAEs form a unique structure and topology, which we classify as a subtype of classical polyplex, termed "micelle-embedded polyplexes" (mPolyplexes). The impact of different nebulizers on the physicochemical performance of these nanoparticles was investigated, and it was found that various mPolyplexes can be nebulized using vibrating-mesh nebulizers without the loss of gene silencing activity nor a change in physicochemical properties, setting them apart from other nanoparticles such as marketed LNPs. Finally, their therapeutic application was tested ex vivo in human precision-cut lung slices from patients with lung fibrosis. mPolyplexes mediated 52% gene silencing of matrix metalloprotease 7 (MMP7) and a downstream effect on collagen I (Col I) with 33% downregulation as determined via qPCR.

PMID:39938880 | DOI:10.1021/acsami.4c21657

Pharmacol Res Perspect. 2025 Feb;13(1):e70076. doi: 10.1002/prp2.70076.

ABSTRACT

Drug repurposing provides a cost-effective and time-saving approach to cancer therapy. Aripiprazole (ARI), a third-generation antipsychotic, has shown potential anticancer properties by modulating pathways central to tumor progression and resistance. This scoping review systematically examines evidence on ARI's anticancer effects, mechanisms of action, and translational potential. A systematic search of PubMed, EMBASE, SCOPUS, and Web of Science was conducted following PRISMA-ScR guidelines. Eligible studies included in vitro, in vivo, and clinical investigations. Data on cancer types, pathways, assays, and outcomes were extracted and synthesized to identify trends and gaps. Of 588 screened studies, 23 met inclusion criteria, spanning cancer types such as breast, colorectal, lung, and brain cancers. ARI modulates key pathways like PI3K/AKT/mTOR and Wnt/β-catenin, induces apoptosis through mitochondrial dysfunction and ER stress, and overcomes drug resistance by inhibiting P-glycoprotein activity and expression. It exhibits tumor-suppressive effects in vivo and synergizes with chemotherapy and radiotherapy. Retrospective population studies suggest ARI's prolactin-sparing properties may reduce the risk of hormone-sensitive cancers such as breast and endometrial cancer compared to antipsychotics with stronger dopamine receptor blockade. Additionally, ARI's ability to target multiple Hallmarks of Cancer highlights its promise as a repurposed anticancer agent. However, current evidence is primarily preclinical and observational, with limited clinical validation. Large-scale cohort studies and prospective trials are essential to confirm its efficacy and address translational challenges. By bridging these gaps, ARI could emerge as a valuable adjunctive therapy in oncology, leveraging its safety profile and versatility to address unmet needs in cancer treatment.

PMID:39939172 | DOI:10.1002/prp2.70076

Curr Res Transl Med. 2025 Feb 4;73(2):103498. doi: 10.1016/j.retram.2025.103498. Online ahead of print.

ABSTRACT

SARS-CoV-2 infection has been associated with long-term cardiovascular complications including myocarditis and heart failure, as well as central nervous system sequelae such as cognitive dysfunction and neuropathy. Proprotein convertase subtilisin/Kexin type 9 (PCSK9), a hepatic protease involved in cholesterol regulation, has shown associations with a spectrum of diseases potentially relevant to these Covid-19 complications, such as atherosclerosis. To identify novel human PCSK9 inhibitors, a custom virtual screening pipeline was developed employing (1) a convolutional neural network-based deep learning model, (2) molecular docking using Schrödinger with Glide scoring function, and (3) molecular dynamics (MD) simulations with Gibbs Free Energy Landscape analysis. The deep learning model was trained on a dataset of known central nervous system, cardiovascular, and anti-inflammatory acting drugs and used to screen the CMNPD database. Docking simulations were performed on shortlisted candidates, followed by MD simulations and free energy landscape analysis to evaluate binding affinities and identify key interaction residues. This multi-step in-silico approach identified promising PCSK9 inhibitor candidates with favorable binding profiles, suggesting that AI-assisted virtual screening can be a powerful tool for discovering novel therapeutic agents.

PMID:39938184 | DOI:10.1016/j.retram.2025.103498

Nature. 2025 Feb;638(8050):351-359. doi: 10.1038/s41586-024-08243-w. Epub 2025 Feb 12.

ABSTRACT

Recent advances in functional genomics and human cellular models have substantially enhanced our understanding of the structure and regulation of the human genome. However, our grasp of the molecular functions of human genes remains incomplete and biased towards specific gene classes. The Molecular Phenotypes of Null Alleles in Cells (MorPhiC) Consortium aims to address this gap by creating a comprehensive catalogue of the molecular and cellular phenotypes associated with null alleles of all human genes using in vitro multicellular systems. In this Perspective, we present the strategic vision of the MorPhiC Consortium and discuss various strategies for generating null alleles, as well as the challenges involved. We describe the cellular models and scalable phenotypic readouts that will be used in the consortium's initial phase, focusing on 1,000 protein-coding genes. The resulting molecular and cellular data will be compiled into a catalogue of null-allele phenotypes. The methodologies developed in this phase will establish best practices for extending these approaches to all human protein-coding genes. The resources generated-including engineered cell lines, plasmids, phenotypic data, genomic information and computational tools-will be made available to the broader research community to facilitate deeper insights into human gene functions.

PMID:39939790 | DOI:10.1038/s41586-024-08243-w

Ital J Pediatr. 2025 Feb 12;51(1):45. doi: 10.1186/s13052-025-01885-0.

ABSTRACT

BACKGROUND: During the pandemic, the pneumology team at Bambino Gesù Children's Hospital highlighted that telemedicine was a valuable tool for remotely managing the medical needs of children with medical complexity (CMC). Following the telemedicine experience during the emergency phase, a telemedicine service was established, and new tools were tested to optimize televisits and the overall eHealth approach for patients. In this context, the TytoHome™ device was tested for performing objective examinations remotely. This pilot study, conducted at our hospital, explored the management of CMC patients on long-term mechanical ventilation via the telemedicine platform and the TytoHome™ device.

METHODS: This study involved the treatment of 10 pediatric patients over one year using this approach. The patients were already receiving care at our hospital and were undergoing long-term mechanical ventilation (LTV) at home-4 on invasive mechanical ventilation (IMV) and 6 on non-invasive ventilation (NIV). A database was developed to collect patient data, including personal details, vital parameters, objective examinations, audio quality, and patient satisfaction. A descriptive analysis was subsequently performed using the data collected during the earlier stages of the study.

RESULTS: The utility of the TytoCare device for medically complex children was evaluated. The families were "satisfied" with the remote follow-up visits, and healthcare personnel rated the audio quality of the visits as "good."

CONCLUSIONS: In conclusion, the remote management of these patients using the Tyto device offered several advantages. In our experience, Tyto proved to be a useful tool for the remote medical management of complex patients.

PMID:39939975 | DOI:10.1186/s13052-025-01885-0

Chest. 2025 Feb;167(2):297-299. doi: 10.1016/j.chest.2024.10.019.

NO ABSTRACT

PMID:39939046 | DOI:10.1016/j.chest.2024.10.019

Nat Methods. 2025 Feb 12. doi: 10.1038/s41592-024-02580-4. Online ahead of print.

ABSTRACT

Accurate segmentation of objects in microscopy images remains a bottleneck for many researchers despite the number of tools developed for this purpose. Here, we present Segment Anything for Microscopy (μSAM), a tool for segmentation and tracking in multidimensional microscopy data. It is based on Segment Anything, a vision foundation model for image segmentation. We extend it by fine-tuning generalist models for light and electron microscopy that clearly improve segmentation quality for a wide range of imaging conditions. We also implement interactive and automatic segmentation in a napari plugin that can speed up diverse segmentation tasks and provides a unified solution for microscopy annotation across different microscopy modalities. Our work constitutes the application of vision foundation models in microscopy, laying the groundwork for solving image analysis tasks in this domain with a small set of powerful deep learning models.

PMID:39939717 | DOI:10.1038/s41592-024-02580-4

NPJ Precis Oncol. 2025 Feb 12;9(1):45. doi: 10.1038/s41698-025-00827-7.

NO ABSTRACT

PMID:39939705 | DOI:10.1038/s41698-025-00827-7