Entropy (Basel). 2025 Mar 7;27(3):280. doi: 10.3390/e27030280.

ABSTRACT

The known laws of nature in the physical sciences are well expressed in the language of mathematics, a fact that caused Eugene Wigner to wonder at the "unreasonable effectiveness" of mathematical concepts to explain physical phenomena. The biological sciences, in contrast, have resisted the formulation of precise mathematical laws that model the complexity of the living world. The limits of mathematics in biology are discussed as stemming from the impossibility of constructing a deterministic "Laplacian" model and the failure of set theory to capture the creative nature of evolutionary processes in the biosphere. Indeed, biology transcends the limits of computation. This leads to a necessity of finding new formalisms to describe biological reality, with or without strictly mathematical approaches. In the former case, mathematical expressions that do not demand numerical equivalence (equations) provide useful information without exact predictions. Examples of approximations without equal signs are given. The ineffectiveness of mathematics in biology is an invitation to expand the limits of science and to see that the creativity of nature transcends mathematical formalism.

PMID:40149204 | DOI:10.3390/e27030280

Mol Neurodegener. 2025 Mar 28;20(1):38. doi: 10.1186/s13024-025-00826-z.

ABSTRACT

Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Dementia (FTD) are overwhelmingly linked to TDP-43 dysfunction. Mutations in TDP-43 are rare, indicating that the progressive accumulation of exogenous factors - such as cellular stressors - converge on TDP-43 to play a key role in disease pathogenesis. Post translational modifications such as SUMOylation play essential roles in response to such exogenous stressors. We therefore set out to understand how SUMOylation may regulate TDP-43 in health and disease. We find that TDP-43 is regulated dynamically via SUMOylation in response to cellular stressors. When this process is blocked in vivo, we note age-dependent TDP-43 pathology and sex-specific behavioral deficits linking TDP-43 SUMOylation with aging and disease. We further find that SUMOylation is correlated with human aging and disease states. Collectively, this work presents TDP-43 SUMOylation as an early physiological response to cellular stress, disruption of which may confer a risk for TDP-43 proteinopathy.

PMID:40149017 | DOI:10.1186/s13024-025-00826-z

New Phytol. 2025 Mar 27. doi: 10.1111/nph.70101. Online ahead of print.

ABSTRACT

Robinia pseudoacacia L. (black locust) is a nitrogen (N)-fixing legume tree with significant ecological and agricultural importance. Unlike well-studied herbaceous legumes, R. pseudoacacia is a perennial woody species, representing an understudied group of legume trees that establish symbiosis with Mesorhizobium. Understanding its genomic and transcriptional responses to nodulation provides key insights into N fixation in long-lived plants and their role in ecosystem N cycling. We assembled a high-quality 699.6-Mb reference genome and performed transcriptomic analyses comparing inoculated and noninoculated plants. Differential expression and co-expression network analyses revealed organ-specific regulatory pathways, identifying key genes associated with symbiosis, nutrient transport, and stress adaptation. Unlike Medicago truncatula, which predominantly responds to nodulation in roots, R. pseudoacacia exhibited stem-centered transcriptional reprogramming, with the majority of differentially expressed genes located in stems rather than in roots. Co-expression network analysis identified gene modules associated with "leghemoglobins", metal detoxification, and systemic nutrient allocation, highlighting a coordinated long-distance response to N fixation. This study establishes R. pseudoacacia as a genomic model for nodulating trees, providing essential resources for evolutionary, ecological, and applied research. These findings have significant implications for reforestation, phytoremediation, forestry, and sustainable N management, particularly in depleted, degraded, and contaminated soil ecosystems.

PMID:40149007 | DOI:10.1111/nph.70101

J Biol Eng. 2025 Mar 27;19(1):25. doi: 10.1186/s13036-025-00493-0.

ABSTRACT

Achieving consistent and predictable gene expression from plasmids remains challenging. While much attention has focused on intra-genetic elements like promoters and ribosomal binding sites, the spatial arrangement of genes within plasmids-referred to as gene syntax-also plays a crucial role in shaping gene expression dynamics. This study addresses the largely overlooked impact of gene syntaxes on gene expression variability and accuracy. Utilizing a dual-fluorescent protein system, we systematically investigated how different gene orientations and orders affect expression profiles including mean levels, relative expression ratios, and cell-to-cell variations. We found that arbitrary gene placement on a plasmid can cause significantly different expression means and ratios. Genes aligned in the same direction as a plasmid's origin of replication (Ori) typically exhibit higher expression levels; adjacent genes in the divergent orientation tend to suppress each other's expression; altering gene order without changing orientation can yield varied expression. Despite unchanged total cell-to-cell variation across different syntaxes, gene syntaxes can also influence intrinsic and extrinsic noise. Interestingly, cell-to-cell variation appears to depend on the reporter proteins, with RFP consistently showing higher variation than GFP. Moreover, the effects of gene syntax can propagate to downstream circuits, strongly affecting the performance of incoherent feedforward loops and contributing to unpredictable outcomes in genetic networks. Our findings reveal that gene syntaxes on plasmids modulate gene expression and circuit behavior, providing valuable insights for the rational design of plasmids and genetic circuits.

PMID:40148941 | DOI:10.1186/s13036-025-00493-0

Plant Cell Environ. 2025 Mar 27. doi: 10.1111/pce.15481. Online ahead of print.

ABSTRACT

Plant reactions to stress vary with development stage and fitness. This study assessed the relationship between light and chilling stress in Arabidopsis acclimation. By analysing the transcriptome and proteome responses of expanding leaves subjected to varying light intensity and cold, 2251 and 2064 early response genes and proteins were identified, respectively. Many of these represent as a yet unknown part of the early response to cold, illustrating a development-dependent response to stress and duality in plant adaptations. While standard light promoted photosynthetic upregulation, plastid maintenance, and increased resilience, low light triggered a unique metabolic shift, prioritizing ribosome biogenesis and lipid metabolism and attenuating the expression of genes associated with plant immunity. The comparison of early response in young leaves with that in expanded ones showed striking differences, suggesting a sacrifice of expanded leaves to support young ones. Validations of selected DEGs in mutant background confirmed a role of HSP90-1, transcription factor FLZ13, and Phospholipase A1 (PLIP) in response to cold, and the PLIP family emerged as crucial in promoting acclimation and freezing stress tolerance. The findings highlight the dynamic mechanisms that enable plants to adapt to challenging environments and pave the way for the development of genetically modified crops with enhanced freezing tolerance.

PMID:40148745 | DOI:10.1111/pce.15481

Nat Rev Genet. 2025 Mar 27. doi: 10.1038/s41576-025-00835-0. Online ahead of print.

NO ABSTRACT

PMID:40148574 | DOI:10.1038/s41576-025-00835-0

Nat Microbiol. 2025 Mar 27. doi: 10.1038/s41564-025-01954-4. Online ahead of print.

ABSTRACT

Every step in common microbiome profiling protocols has variable efficiency for each microbe, for example, different DNA extraction efficiency for Gram-positive bacteria. These processing biases impede the identification of signals that are biologically interpretable and generalizable across studies. 'Batch-correction' methods have been used to address these issues computationally with some success, but they are largely non-interpretable and often require the use of an outcome variable in a manner that risks overfitting. We present DEBIAS-M (domain adaptation with phenotype estimation and batch integration across studies of the microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns bias-correction factors for each microbe in each batch that simultaneously minimize batch effects and maximize cross-study associations with phenotypes. Using diverse benchmarks including 16S rRNA and metagenomic sequencing, classification and regression, and a variety of clinical and molecular targets, we demonstrate that using DEBIAS-M improves cross-study prediction accuracy compared with commonly used batch-correction methods. Notably, we show that the inferred bias-correction factors are stable, interpretable and strongly associated with specific experimental protocols. Overall, we show that DEBIAS-M facilitates improved modelling of microbiome data and identification of interpretable signals that generalize across studies.

PMID:40148567 | DOI:10.1038/s41564-025-01954-4

Leukemia. 2025 Mar 27. doi: 10.1038/s41375-025-02575-w. Online ahead of print.

ABSTRACT

Unbiased kinome-wide CRISPR screening identified DYRK1A as a potential therapeutic target in KMT2A-rearranged (KMT2A-R) B-acute lymphoblastic leukemia (ALL). Mechanistically, we demonstrate that DYRK1A is regulated by the KMT2A fusion protein and affects cell proliferation by regulating MYC expression and ERK phosphorylation. We further observed that pharmacologic DYRK1A inhibition markedly reduced human KMT2A-R ALL cell proliferation in vitro and potently decreased leukemia proliferation in vivo in drug-treated patient-derived xenograft mouse models. DYRK1A inhibition induced expression of the proapoptotic factor BIM and reduced the expression of BCL-XL, consequently sensitizing KMT2A-R ALL cells to BCL2 inhibition. Dual inhibition of DYRK1A and BCL2 synergistically decreased KMT2A-R ALL cell survival in vitro and reduced leukemic burden in mice. Taken together, our data establishes DYRK1A as a novel therapeutic target in KMT2A-R ALL and credential dual inhibition of DYRK1A and BCL2 as an effective translational therapeutic strategy for this high-risk ALL subtype.

PMID:40148558 | DOI:10.1038/s41375-025-02575-w

Nat Rev Nephrol. 2025 Mar 27. doi: 10.1038/s41581-025-00946-1. Online ahead of print.

ABSTRACT

The application of spatially resolved mass spectrometry (MS) and MS imaging approaches for studying biomolecular processes in the kidney is rapidly growing. These powerful methods, which enable label-free and multiplexed detection of many molecular classes across omics domains (including metabolites, drugs, proteins and protein post-translational modifications), are beginning to reveal new molecular insights related to kidney health and disease. The complexity of the kidney often necessitates multiple scales of analysis for interrogating biofluids, whole organs, functional tissue units, single cells and subcellular compartments. Various MS methods can generate omics data across these spatial domains and facilitate both basic science and pathological assessment of the kidney. Optimal processes related to sample preparation and handling for different MS applications are rapidly evolving. Emerging technology and methods, improvement of spatial resolution, broader molecular characterization, multimodal and multiomics approaches and the use of machine learning and artificial intelligence approaches promise to make these applications even more valuable in the field of nephology. Overall, spatially resolved MS and MS imaging methods have the potential to fill much of the omics gap in systems biology analysis of the kidney and provide functional outputs that cannot be obtained using genomics and transcriptomic methods.

PMID:40148534 | DOI:10.1038/s41581-025-00946-1

Sci Rep. 2025 Mar 27;15(1):10617. doi: 10.1038/s41598-025-93219-7.

ABSTRACT

Mesenchymal stem cell-derived exosomes exhibit promising potential in tissue regeneration. Recent studies highlight its significant therapeutic potential in various stages of wound healing. However, the clinical translation of exosome-based therapy was hindered due to issues regarding low productivity and the lack of efficient production protocol to obtain a clinically relevant exosome quantity. Therefore, this study established a potential upscaling protocol to produce exosomes derived from canine adipose-derived mesenchymal stem cells (cAD-MSCs) and explored its potential for wound treatment. The potential upscaling protocol, termed VSCBIC-3-3D, was carried out using VSCBIC-3 in-house serum-free exosome-collecting solution in a three-dimensional (3D) culture system followed by the tangential flow filtration (TFF) isolation. Our findings suggest that culturing cAD-MSCs with VSCBIC-3 maintained cell morphology and viability. Compared to conventional two-dimensional (2D) protocols, The potential upscaling protocol increased exosome yield and concentration in conditioned medium by 2.4-fold and 3.2-fold, respectively. The quality assessment revealed enhanced purity and bioactivity of exosomes produced using the VSCBIC-3-3D protocol. In addition, the cAD-MSCs-derived exosomes were shown to significantly improve fibroblast migration, proliferation, and wound healing-related gene expression in vitro. This study collectively demonstrates that potential upscaling protocol establishment allowed robust production of exosomes from cAD-MSCs, which exhibit therapeutic potential for wound healing in vitro.

PMID:40148423 | DOI:10.1038/s41598-025-93219-7

Nat Commun. 2025 Mar 28;16(1):3020. doi: 10.1038/s41467-025-58363-8.

ABSTRACT

Phosphorylase kinase (PhK) regulates the degradation of glycogen by integrating diverse signals, providing energy to the organism. Dysfunctional mutations may directly lead to Glycogen Storage Disease type IX (GSD IX), whereas the abnormal expression of PhK is also associated with tumors. Here, we use cryo-electron microscopy (cryo-EM) to resolve its near-atomic structures in the inactive and active states. These structures reveal the interactions and relative locations of the four subunits (αβγδ) within the PhK complex. Phosphorylated α and β subunits induce PhK to present a more compact state, while Ca2+ causes sliding of the δ subunit along the helix of the γ subunit. Both actions synergistically activate PhK by enabling the de-inhibition of the γ subunit. We also identified different binding modes between PhK and its substrate, glycogen phosphorylase (GP), in two distinct states, using cross-linking mass spectrometry (XL-MS). This study provides valuable insights into the regulatory mechanisms of PhK, thereby enhancing our understanding of GSD IX and its implications in tumorigenesis.

PMID:40148320 | DOI:10.1038/s41467-025-58363-8

Genes (Basel). 2025 Feb 24;16(3):265. doi: 10.3390/genes16030265.

ABSTRACT

Background/Objectives: The accurate prediction of adverse drug reactions (ADRs) to oncological treatments still poses a clinical challenge. Chemotherapy is usually selected based on clinical trials that do not consider patient variability in ADR risk. Consequently, many patients undergo multiple treatments to find the appropriate medication or dosage, enhancing ADR risks and increasing the chance of discontinuing therapy. We first aimed to develop a pharmacogenetic model for predicting chemotherapy-induced ADRs in cancer patients (the ANTIBLASTIC DRUG MULTIPANEL PLATFORM) and then to assess its feasibility and validate this model in patients with non-small-cell lung cancer (NSCLC) undergoing oncological treatments. Methods: Seventy NSCLC patients of all stages that needed oncological treatment at our facility were enrolled, reflecting the typical population served by our institution, based on geographic and demographic characteristics. Treatments followed existing guidelines, and patients were continuously monitored for adverse reactions. We developed and used a multipanel platform based on 326 SNPs that we identified as strongly associated with response to cancer treatments. Subsequently, a network-based algorithm to link these SNPs to molecular and biological functions, as well as efficacy and adverse reactions to oncological treatments, was used. Results: Data and blood samples were collected from 70 NSCLC patients. A bioinformatic analysis of all identified SNPs highlighted five clusters of patients based on variant aggregations and the associated genes, suggesting potential susceptibility to treatment-related toxicity. We assessed the feasibility of the platform and technically validated it by comparing NSCLC patients undergoing the same course of treatment with or without ADRs against the cluster combination. An odds ratio analysis confirmed the correlation between cluster allocation and increased ADR risk, indicating specific treatment susceptibilities. Conclusions: The ANTIBLASTIC DRUG MULTIPANEL PLATFORM was easily applicable and able to predict ADRs in NSCLC patients undergoing oncological treatments. The application of this novel predictive model could significantly reduce adverse drug reactions and improve the rate of chemotherapy completion, enhancing patient outcomes and quality of life. Its potential for broader prescription management suggests significant treatment improvements in cancer patients.

PMID:40149417 | DOI:10.3390/genes16030265

Pediatr Neurol. 2025 May;166:96-102. doi: 10.1016/j.pediatrneurol.2025.03.001. Epub 2025 Mar 8.

ABSTRACT

BACKGROUND: A postmarketing analysis of the adverse events (AEs) associated with fenfluramine (FFA) was conducted using the US Food and Drug Administration's Open Public Data Program (openFDA).

METHODS: The openFDA database was queried to retrieve FFA AE reports. Two algorithms, namely, the reporting odds ratio (ROR) and proportional reporting ratio, were employed for the purpose of detecting potential safety signals.

RESULTS: From the openFDA data platform, a total of 6,269,521 AE reports were collected during the study period; the number of AE reports with FFA as the primary suspect was 2386. Of these, 1526 (63.96%) were reported by consumers or non-health professionals, 2009 (84.20%) were reported by the United States, 1053 (44.13%) were unknown indications, and serious AEs were reported in 1315 cases (55.11%). A total of 62 signals were generated. The top 10 signals included atonic seizures (ROR of 918.52, 95% confidence interval [CI]: 670.65-1257.99), seizure clusters (ROR of 787.02, 95% CI: 595.26-1040.56), mitral valve thickening (ROR of 773.94, 95% CI: 463.47-1292.38), pulmonary valve incompetence (ROR of 600.71, 95% CI: 432.09-835.13), echocardiogram abnormal (ROR of 417.13, 95% CI: 307.87-565.16), change in seizure presentation (ROR of 287.55, 95% CI: 214.81-384.91), tricuspid valve incompetence (ROR of 221.42, 95% CI: 179.68-272.84), aortic valve incompetence (ROR of 176.59, 95% CI: 131.89-236.45), tonic convulsion (ROR of 173.68, 95% CI: 110.28-273.54), and myoclonic epilepsy (ROR of 158.05, 95% CI: 102.60-243.46).

CONCLUSIONS: This study employed the openFDA database to identify safety signals associated with FFA, thereby offering significant insights for clinical monitoring and risk identification in patients undergoing FFA therapy.

PMID:40147090 | DOI:10.1016/j.pediatrneurol.2025.03.001

Comput Biol Med. 2025 Mar 26;190:110070. doi: 10.1016/j.compbiomed.2025.110070. Online ahead of print.

ABSTRACT

This study explores the development of a deep learning model using a neck-wearable piezoelectric sensor to accurately distinguish severe sleep apnea syndrome (SAS) from habitual snoring, addressing the underdiagnosis of SAS in adults. From 2018 to 2020, 60 adult habitual snorers underwent polysomnography while wearing a neck piezoelectric sensor that recorded snoring vibrations (70-250 Hz) and carotid artery pulsations (0.01-1.5 Hz). The initial dataset comprised 1167 silence, 1304 snoring, and 399 noise samples from 20 participants. Using a hybrid deep learning model comprising a one-dimensional convolutional neural network and gated-recurrent unit, the model identified snoring and apnea/hypopnea events, with sleep phases detected via pulse wave variability criteria. The model's efficacy in predicting severe SAS was assessed in the remaining 40 participants, achieving snoring detection rates of 0.88, 0.86, and 0.92, with respective loss rates of 0.39, 0.90, and 0.23. Classification accuracy for severe SAS improved from 0.85 for total sleep time to 0.90 for partial sleep time, excluding the first sleep phase, demonstrating precision of 0.84, recall of 1.00, and an F1 score of 0.91. This innovative approach of combining a hybrid deep learning model with a neck-wearable piezoelectric sensor suggests a promising route for early and precise differentiation of severe SAS from habitual snoring, aiding guiding further standard diagnostic evaluations and timely patient management. Future studies should focus on expanding the sample size, diversifying the patient population, and external validations in real-world settings to enhance the robustness and applicability of the findings.

PMID:40147187 | DOI:10.1016/j.compbiomed.2025.110070

Radiography (Lond). 2025 Mar 26;31(3):102929. doi: 10.1016/j.radi.2025.102929. Online ahead of print.

ABSTRACT

INTRODUCTION: A hybrid angio-CT system with 320-row detectors and deep learning-based reconstruction (DLR), provides additional imaging via 4D-CT angiography (CTA), potentially shortening procedure time and reducing DSA acquisitions, contrast media, and radiation dose. This study evaluates the feasibility of low-tube voltage 4D-CTA with low-contrast volume and DLR for selective renal artery embolization using a vessel phantom.

METHODS: A custom-made phantom simulating contrast-enhanced vessels filled with contrast medium was scanned. The study assessed image quality under varying image noise and vessel contrast. Quantitative analysis included peak contrast-to-noise ratio (pCNR) and image noise. Qualitative assessment was performed by seven radiologists using a 4-point scale; each radiologist independently recorded their evaluations on an assessment sheet.

RESULTS: A pCNR of approximately 15.0 was identified as the threshold for acceptable image quality. The pCNR decreased as the noise index increased (by 25-75 % when comparing a noise index of 30-70 HU).Vessels with a CT value of 500 Hounsfield units (HU) achieved sufficient image quality with a noise index of 50 HU. Dose reduction was substantial compared to traditional DSA, with effective radiation dose remaining within acceptable clinical levels.

CONCLUSION: 4D-CTA, combined with DLR, demonstrated the potential to reduce radiation and contrast agent usage while preserving diagnostic quality for renal artery angiography. Further clinical validation is required to confirm these findings in clinical settings.

IMPLICATIONS FOR PRACTICE: 4D-CTA with low-tube voltage and deep learning-based reconstruction (DLR) can reduce radiation and contrast use while maintaining image quality. This approach might improve safety, particularly in patients with renal impairment, and serve as a viable alternative to conventional DSA for selective renal artery embolization.

PMID:40147091 | DOI:10.1016/j.radi.2025.102929

Pharmacol Rev. 2025 Mar;77(2):100033. doi: 10.1016/j.pharmr.2024.100033. Epub 2024 Dec 24.

ABSTRACT

Cancer and cardiovascular disease (CVD) are the 2 biggest killers worldwide. Specific treatments have been developed for the 2 diseases. However, mutual therapeutic targets should be considered because of the overlap of cellular and molecular mechanisms. Cancer research has grown at a fast pace, leading to an increasing number of new mechanistic treatments. Some of these drugs could prove useful for treating CVD, which realizes the concept of cancer drug repurposing. This review provides a comprehensive outline of the shared hallmarks of cancer and CVD, primarily ischemic heart disease and heart failure. We focus on chronic inflammation, altered immune response, stromal and vascular cell activation, and underlying signaling pathways causing pathological tissue remodeling. There is an obvious scope for targeting those shared mechanisms, thereby achieving reciprocal preventive and therapeutic benefits. Major attention is devoted to illustrating the logic, advantages, challenges, and viable examples of drug repurposing and discussing the potential influence of sex, gender, age, and ethnicity in realizing this approach. Artificial intelligence will help to refine the personalized application of drug repurposing for patients with CVD. SIGNIFICANCE STATEMENT: Cancer and cardiovascular disease (CVD), the 2 biggest killers worldwide, share several underlying cellular and molecular mechanisms. So far, specific therapies have been developed to tackle the 2 diseases. However, the development of new cardiovascular drugs has been slow compared with cancer drugs. Understanding the intersection between pathological mechanisms of the 2 diseases provides the basis for repurposing cancer therapeutics for CVD treatment. This approach could allow the rapid development of new drugs for patients with CVDs.

PMID:40148035 | DOI:10.1016/j.pharmr.2024.100033