Hum Nat. 2025 Mar 13. doi: 10.1007/s12110-025-09488-8. Online ahead of print.

ABSTRACT

Automatic behavioral matching includes Rapid Facial Mimicry (RFM) and Yawn Contagion (YC) that occur when the facial expression of an individual acts as a 'mirror social releaser' and induces the same facial expression in the observer (within 1 s for RFM, and minutes for YC). Motor replication has been linked to coordination and emotional contagion, a basic form of empathy. We investigated the presence and modulating factors of Rapid Smile Mimicry (RSM) and YC in infants/toddlers from 10 to 36 months at the nursery 'Melis' (Turin, Italy). In February-May 2022, we gathered audio and/or video of all occurrences data on affiliative behaviors, smiling during play, and yawning during everyday activities. Both RSM and YC were present, as toddlers were most likely to smile (within 1 s) or yawn (within three-min) after perceiving a smile/yawn from another toddler. Sex, age, and parents' country of origin did not influence RSM and YC occurrence, probably because gonadal maturation was long to come, the age range was skewed towards the early developmental phase, and toddlers had been in the same social group for months. RSM and YC showed social modulation, thus possibly implying more than just motor resonance. Both phenomena were inversely related to affiliation levels (a social bond proxy). Because literature reports that in adults RSM and YC may increase with familiarity, our reversed result suggests that in certain toddler cohorts the same phenomena may help increase socio-emotional coordination and that the function of motoric resonance may be experience- and context-dependent.

PMID:40080328 | DOI:10.1007/s12110-025-09488-8

J Mol Neurosci. 2025 Mar 13;75(1):32. doi: 10.1007/s12031-025-02328-5.

ABSTRACT

Caloric restriction (CR) is a dietary intervention that reduces calorie intake without inducing malnutrition, demonstrating lifespan-extending effects in preclinical studies and some human trials, along with potential benefits in ameliorating age-related ailments. Caloric restriction mimetics (CRMs) are compounds mimicking CR effects, offering a potential therapeutic avenue for age-related diseases. This study explores the potential protective effects of CR on the brain neocortex (GSE11291) and the identification of CRMs using integrative bioinformatics and systems biology approaches. Our findings indicate that long-term CR activates cellular pathways improving mitochondrial function, enhancing antioxidant capacity, and reducing inflammation, potentially providing neuroprotection. The key signaling pathways enriched in our study include PPAR, mTOR, FoxO, AMPK, and Notch signaling pathways, which are crucial regulators of metabolism, cellular stress response, neuroprotection, and longevity. We identify key signaling molecules and molecular mechanisms associated with CR, including transcription factors, kinase regulators, and microRNAs linked to differentially expressed genes. Furthermore, potential CRMs such as rapamycin, replicating CR-related health benefits, are identified. Additionally, machine learning models were developed to classify small molecules based on their CNS activity and anti-inflammatory properties. As a proof of concept, we have demonstrated the ischemic neuroprotective effects of two top-ranked candidate reference molecules (CRMs) using the oxygen-glucose deprivation (OGD) model, an established in vitro stroke model. However, further investigations are essential to fully elucidate the therapeutic potential of these CRMs. In summary, our study suggests that long-term CR entails protective mechanisms preserving and safeguarding neuronal function, potentially impacting the treatment of age-related neurological diseases. Moreover, our findings contribute to the identification of potential genes and regulatory molecules involved in CR, along with potential CRMs, providing a promising foundation for future research in the field of neurological disorder treatment.

PMID:40080242 | DOI:10.1007/s12031-025-02328-5

J Proteome Res. 2025 Mar 13. doi: 10.1021/acs.jproteome.4c00864. Online ahead of print.

ABSTRACT

Mass spectrometry-based discovery of bacterial immunopeptides presented by infected cells allows untargeted discovery of bacterial antigens that can serve as vaccine candidates. However, reliable identification of bacterial epitopes is challenged by their extremely low abundance. Here, we describe an optimized bioinformatic framework to enhance the confident identification of bacterial immunopeptides. Immunopeptidomics data of cell cultures infected with Listeria monocytogenes were searched by four different search engines, PEAKS, Comet, Sage and MSFragger, followed by data-driven rescoring with MS2Rescore. Compared with individual search engine results, this integrated workflow boosted immunopeptide identification by an average of 27% and led to the high-confidence detection of 18 additional bacterial peptides (+27%) matching 15 different Listeria proteins (+36%). Despite the strong agreement between the search engines, a small number of spectra (<1%) had ambiguous matches to multiple peptides and were excluded to ensure high-confidence identifications. Finally, we demonstrate our workflow with sensitive timsTOF SCP data acquisition and find that rescoring, now with inclusion of ion mobility features, identifies 76% more peptides compared to Q Exactive HF acquisition. Together, our results demonstrate how integration of multiple search engine results along with data-driven rescoring maximizes immunopeptide identification, boosting the detection of high-confidence bacterial epitopes for vaccine development.

PMID:40080147 | DOI:10.1021/acs.jproteome.4c00864

Elife. 2025 Mar 13;13:RP97330. doi: 10.7554/eLife.97330.

ABSTRACT

Antimicrobial peptides (AMPs) are attractive candidates to combat antibiotic resistance for their capability to target biomembranes and restrict a wide range of pathogens. It is a daunting challenge to discover novel AMPs due to their sparse distributions in a vast peptide universe, especially for peptides that demonstrate potencies for both bacterial membranes and viral envelopes. Here, we establish a de novo AMP design framework by bridging a deep generative module and a graph-encoding activity regressor. The generative module learns hidden 'grammars' of AMP features and produces candidates sequentially pass antimicrobial predictor and antiviral classifiers. We discovered 16 bifunctional AMPs and experimentally validated their abilities to inhibit a spectrum of pathogens in vitro and in animal models. Notably, P076 is a highly potent bactericide with the minimal inhibitory concentration of 0.21 μM against multidrug-resistant Acinetobacter baumannii, while P002 broadly inhibits five enveloped viruses. Our study provides feasible means to uncover the sequences that simultaneously encode antimicrobial and antiviral activities, thus bolstering the function spectra of AMPs to combat a wide range of drug-resistant infections.

PMID:40079572 | DOI:10.7554/eLife.97330

J Chem Theory Comput. 2025 Mar 13. doi: 10.1021/acs.jctc.4c01774. Online ahead of print.

ABSTRACT

Protein evolution has shaped enzymes that maintain stability and function across diverse thermal environments. While sequence variation, thermal stability and conformational dynamics are known to influence an enzyme's thermal adaptation, how these factors collectively govern stability and function across diverse temperatures remains unresolved. Cytosolic malate dehydrogenase (cMDH), a citric acid cycle enzyme, is an ideal model for studying these mechanisms due to its temperature-sensitive flexibility and broad presence in species from diverse thermal environments. In this study, we employ techniques inspired by deep learning and statistical mechanics to uncover how sequence variation and conformational dynamics shape patterns of cMDH's thermal adaptation. By integrating coevolutionary models with variational autoencoders (VAE), we generate a latent generative landscape (LGL) of the cMDH sequence space, enabling us to explore mutational pathways and predict fitness using direct coupling analysis (DCA). Structure predictions via AlphaFold and molecular dynamics simulations further illuminate how variations in hydrophobic interactions and conformational flexibility contribute to the thermal stability of warm- and cold-adapted cMDH orthologs. Notably, we identify the ratio of hydrophobic contacts between two regions as a predictive order parameter for thermal stability features, providing a quantitative metric for understanding cMDH dynamics across temperatures. The integrative computational framework employed in this study provides mechanistic insights into protein adaptation at both sequence and structural levels, offering unique perspectives on the evolution of thermal stability and creating avenues for the rational design of proteins with optimized thermal properties.

PMID:40079215 | DOI:10.1021/acs.jctc.4c01774

OMICS. 2025 Mar 12. doi: 10.1089/omi.2024.0196. Online ahead of print.

ABSTRACT

Intracellular calcium signaling is a cornerstone in cell biology and a key molecular target for human health and disease. Calcium/calmodulin dependent protein kinase kinases, CAMKK1 and CAMKK2 are serine/threonine kinases that contribute to the regulation of intracellular calcium signals in response to diverse stimuli. CAMKK1 generally has stable dynamics, whereas CAMKK2 dysregulation triggers oncogenicity and neurological disorders. To differentiate the phosphosignaling hierarchy associated with predominant phosphosites of CAMKK1 and CAMKK2, we assembled and analyzed the global cellular phosphoproteome datasets. We found that predominant phosphosites in CAMKK1 and CAMKK2 are located outside the kinase domain, and their phosphomotifs are highly homologous. Further, we employed a coregulation analysis approach to these predominant phosphosites, to infer the co-occurrence patterns of phosphorylations within CAMKKs and the coregulation patterns of other protein phosphosites with CAMKK sites. We report herein that independent phosphorylations at CAMKK2 S100 and S511 increase their enzymatic activity in the presence of calcium/calmodulin. In addition, the study unveils kinase-substrate associations such as RPS6KB1 as a novel high-confidence upstream kinase of both CAMKK1 S74 and CAMKK2 S100. Further, CAMKK2 was identified as a primary orchestrator in mediating intracellular calcium signaling cascades compared to CAMKK1 based on coregulation patterns of phosphosites from proteins involved in the calcium signaling pathway. These molecular details shed promising insights into the pathophysiology of several diseases such as cancers and psychiatric disorders associated with kinase activity dysregulations of CAMKK2 and further open the avenue for novel PTM-directed therapeutic strategies to regulate CAMKK2.

PMID:40079160 | DOI:10.1089/omi.2024.0196

Biosaf Health. 2024 Jul 14;6(5):310-318. doi: 10.1016/j.bsheal.2024.07.005. eCollection 2024 Oct.

ABSTRACT

Biosafety hazards can trigger a host immune response after infection, invasion, or contact with the host. Whether infection with a microorganism results in disease or biosafety concerns depends to a large extent on the immune status of the population. Therefore, it is essential to investigate the immunological characteristics of the host and the mechanisms of biological threats and agents to protect the host more effectively. Emerging and re-emerging infectious diseases, such as the current coronavirus disease 2019 (COVID-19) pandemic, have raised concerns regarding both biosafety and immunology worldwide. Interdisciplinary studies involved in biosafety and immunology are relevant in many fields, including the development of vaccines and other immune interventions such as monoclonal antibodies and T-cells, herd immunity (or population-level barrier immunity), immunopathology, and multispecies immunity, i.e., animals and even plants. Meanwhile, advances in immunological science and technology are occurring rapidly, resulting in important research achievements that may contribute to the recognition of emerging biosafety hazards, as well as early warning, prevention, and defense systems. This review provides an overview of the interdisciplinary field of biosafety and immunology. Close collaboration and innovative application of immunology in the field of biosafety is becoming essential for human health.

PMID:40078733 | PMC:PMC11894974 | DOI:10.1016/j.bsheal.2024.07.005

Bioinform Adv. 2025 Mar 8;5(1):vbaf013. doi: 10.1093/bioadv/vbaf013. eCollection 2025.

ABSTRACT

MOTIVATION: Epigenetic assays using next-generation sequencing have furthered our understanding of the functional genomic regions and the mechanisms of gene regulation. However, a single assay produces billions of data points, with limited information about the biological process due to numerous sources of technical and biological noise. To draw biological conclusions, numerous specialized algorithms have been proposed to summarize the data into higher-order patterns, such as peak calling and the discovery of differentially methylated regions. The key principle underlying these approaches is the search for locally consistent patterns.

RESULTS: We propose L 0 segmentation as a universal framework for extracting locally coherent signals for diverse epigenetic sources. L 0 serves to compress the input signal by approximating it as a piecewise constant. We implement a highly scalable L 0 segmentation with additional loss functions designed for sequencing epigenetic data types including Poisson loss for single tracks and binomial loss for methylation/coverage data. We show that the L 0 segmentation approach retains the salient features of the data yet can identify subtle features, such as transcription end sites, missed by other analytic approaches.

AVAILABILITY AND IMPLEMENTATION: Our approach is implemented as an R package "l01segmentation" with a C++ backend. Available at https://github.com/boooooogey/l01segmentation.

PMID:40078573 | PMC:PMC11897706 | DOI:10.1093/bioadv/vbaf013

Front Microbiol. 2025 Feb 26;16:1544521. doi: 10.3389/fmicb.2025.1544521. eCollection 2025.

ABSTRACT

Fusarium wilt caused by Fusarium oxysporum f. sp. medicaginis (Fom) is an important disease affecting lucerne/alfalfa cultivations worldwide. Medicago sativa L. (lucerne) is one of the major legume crops in global forage industry. This study aimed to identify bacteria capable of biologically controlling the wilt pathogen through a comprehensive screening of bacterial isolates obtained from domesticated and wild growing Medicago seeds. Using a multi-tiered evaluation pipeline, including in vitro, soil-free and potting mix-based pathogenicity and bioprotection assay systems, the bioprotection efficacy of 34 bacterial isolates derived from Medicago seeds was initially evaluated against six Fusarium strains in vitro. Fusarium oxysporum (Fo) F5189, which has previously been characterized as a Fusarium oxysporum f. sp. medicaginis isolate causing Fusarium wilt in lucerne was selected for in planta assays. Lucerne cultivars Grazer and Sequel, representing susceptible and resistant genotypes were chosen to assess the disease progression. Pathogenicity and bioprotection time-course studies were conducted to understand the temporal dynamics of host-pathogen interactions and efficacy of the bioprotectants. The disease symptoms were scored using a disease rating index developed in this study. The results indicated variability in bioprotection efficacy across bacterial isolates, with some strains suppressing disease in both soil-free and potting mix-based systems. Paenibacillus sp. (Lu_MgY_007; NCBI: PQ756884) and Pseudomonas sp. (Lu_LA164_018; NCBI: PQ756887) were identified as promising bioprotectants against Fusarium wilt under tested growth conditions. The time-course studies highlighted the critical role of persistent biocontrol activity and precise timing of biocontrol application for achieving long-term disease suppression. Overall, the observed reduction in disease severity underscores the potential of these bioprotectants as sustainable strategies for managing Fusarium wilt in lucerne cultivars. However, comprehensive molecular-level analyses are warranted to elucidate the underlying pathogenicity and bioprotection mechanisms, offering valuable insights for the development of more precise and effective future biocontrol strategies in agricultural systems.

PMID:40078546 | PMC:PMC11897269 | DOI:10.3389/fmicb.2025.1544521

Biosaf Health. 2023 Dec 30;6(1):21-27. doi: 10.1016/j.bsheal.2023.12.005. eCollection 2024 Feb.

ABSTRACT

Monkeypox (mpox) outbreak in 2022 has caused more than 91,000 cases, has spread to 115 countries, regions, and territories, and has thus attracted much attention. The stability of poxvirus particles in the environment is recognized as an important factor in determining their transmission. However, few studies have investigated the persistence of poxviruses on material surfaces under various environmental conditions, and their sensitivity to biocides. Here, we systematically measured the stability of vaccinia virus (VACV) under different environmental conditions and sensitivity to inactivation methods via plaque assay, quantitative real-time polymerase chain reaction (qPCR), and Gaussia luciferase (G-luciferase) reporter system. The results show that VACV is stable on the surface of stainless steel, glass, clothing, plastic, towel, A4 paper, and tissue and persists much longer at 4 °C and -20 °C, but is effectively inactivated by ultraviolet (UV) irradiation, heat treatment, and chemical reagents. Our study raises the awareness of long persistence of poxviruses in the environment and provides a simple solution to inactivate poxviruses using common disinfectants, which is expected to help the control and prevention of mpox virus and future poxvirus outbreaks.

PMID:40078309 | PMC:PMC11895014 | DOI:10.1016/j.bsheal.2023.12.005

Biosaf Health. 2023 Dec 31;6(1):12-20. doi: 10.1016/j.bsheal.2023.12.006. eCollection 2024 Feb.

ABSTRACT

The coronavirus disease of 2019 (COVID-19), a global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can result in severe health complications. In addition to physical preventative measures, pharmaceutical intervention is also crucial. Numerous natural products from medicinal fungi have shown promise as potential antiviral drugs and may serve as a source of effective components with antiviral activity against SARS-CoV-2 and other coronaviruses. In this study, we developed a workflow that integrates viral infection inhibition assays at both cellular and molecular levels, as well as molecular separation and characterization, to screen and identify natural products with antiviral activity. Using this workflow, we screened 167 extracts extracted from 36 medicinal fungi using optimized extraction methods. We assessed the antiviral effects of these extracts by measuring their ability to inhibit SARS-CoV-2 infection and receptor binding domain - human angiotensin-converting enzyme 2 (RBD-hACE2) binding in vitro. Following charge- and size-based characterization of the active compounds through filtration and chromatographic fractionation, mass spectrometry characterization of the fractionated compounds revealed that the active components are polysaccharides and determined their monosaccharide residue composition. Our findings provide new insights into the antiviral potential of natural products and their screening strategies and may contribute to the development of effective antiviral therapeutics against COVID-19 and other diseases.

PMID:40078308 | PMC:PMC11894996 | DOI:10.1016/j.bsheal.2023.12.006

Philos Trans A Math Phys Eng Sci. 2025 Mar 13;383(2292):20240228. doi: 10.1098/rsta.2024.0228. Epub 2025 Mar 13.

ABSTRACT

The objective of precision medicine is to tailor interventions to an individual patient's unique characteristics. A key technology for this purpose involves medical digital twins, computational models of human biology that can be personalized and dynamically updated to incorporate patient-specific data. Certain aspects of human biology, such as the immune system, are not easily captured with physics-based models, such as differential equations. Instead, they are often multi-scale, stochastic and hybrid. This poses a challenge to existing control and optimization approaches that cannot be readily applied to such models. Recent advances in neural-network control methods hold promise in addressing complex control problems. However, the application of these approaches to biomedical systems is still in its early stages. This work employs dynamics-informed neural-network controllers as an alternative approach to control of medical digital twins. As a first use case, we focus on the control of agent-based models (ABMs), a versatile and increasingly common modelling platform in biomedicine. The effectiveness of the proposed neural-network control methods is illustrated and benchmarked against other methods with two widely used ABMs. To account for the inherent stochastic nature of the ABMs we aim to control, we quantify uncertainty in relevant model and control parameters.This article is part of the theme issue 'Uncertainty quantification for healthcare and biological systems (Part 1)'.

PMID:40078154 | DOI:10.1098/rsta.2024.0228

J Physiol. 2025 Mar 12. doi: 10.1113/JP287595. Online ahead of print.

ABSTRACT

The intrinsic cardiac nervous system (ICNS), termed as the heart's 'little brain', is the final point of neural regulation of cardiac function. Studying the dynamic behaviour of these ICNS neurons via multiscale neuronal computer models has been limited by the sparsity of electrophysiological data. We developed and analysed a computational library of neuronal electrophysiological models based on single neuron transcriptomic data obtained from ICNS neurons. Each neuronal genotype was characterized by a unique combination of ion channels identified from the transcriptomic data, using a cycle threshold cutoff that ensured the electrical excitability of the neuronal models. The parameters of the ion channel models were grounded based on passive properties (resting membrane potential, input impedance and rheobase) to avoid biasing the dynamic behaviour of the model. Consistent with experimental observations, the emergent model dynamics showed phasic activity in response to the current clamp stimulus in a majority of neuronal genotypes (61%). Additionally, 24% of the ICNS neurons showed a tonic response, 11% were phasic-to-tonic with increasing current stimulation and 3% showed tonic-to-phasic behaviour. The computational approach and the library of models bridge the gap between widely available molecular-level gene expression and sparse cellular-level electrophysiology for studying the functional role of the ICNS in cardiac regulation and pathology. KEY POINTS: Computational models were developed of neuron electrophysiology from single-cell transcriptomic data from neurons in the heart's 'little brain': the intrinsic cardiac nervous system. The single-cell transcriptomic data were thresholded to select the ion channel combinations in each neuronal model. The library of neuronal models was constrained by the passive electrical properties of the neurons and predicted a distribution of phasic and tonic responses that aligns with experimental observations. The ratios of model-predicted conductance values are correlated with the gene expression ratios from transcriptomic data. These neuron models are a first step towards connecting single-cell transcriptomic data to dynamic, predictive physiology-based models.

PMID:40077928 | DOI:10.1113/JP287595

Nutrients. 2025 Feb 27;17(5):815. doi: 10.3390/nu17050815.

ABSTRACT

Background/Objectives: Post-menopausal women are at an increased risk of developing cardiovascular disease. Menaquinone-7 (MK-7) is a fat-soluble vitamin involved in coagulation and maintaining vascular health. The aim of the post hoc analysis of this one-year study is to investigate the effects of MK-7 supplementation on the vascular parameters in pre-, peri-, and post-menopausal women. Methods: In a clinical intervention trial (NCT02404519), a total of 165 women with a low vitamin K status received either 180 µg of MK-7 daily (n = 82) or a matching placebo (n = 83) for one year. Established vascular parameters were measured before and after one year of vitamin K2 supplementation. Pre-, peri-, and post-menopausal women were subdivided according to arterial stiffness, with a high b-stiffness index defined as being greater than the overall median of 9.83. Results: The post hoc analyses showed a significant decrease in desphospho-uncarboxylated matrix Gla protein (dp-ucMGP) plasma levels after MK-7 supplementation (pre/peri, p = 0.009; post, p < 0.001). MK-7 treatment significantly attenuated vascular stiffness in post-menopausal women (placebo +49.1% ± 77.4; MK-7 +9.4% ± 67.1; p = 0.035). Post-menopausal women with a high stiffness index showed significantly improved vascular markers after MK-7 treatment, e.g., a decreased blood pressure at brachialis (-3.0% ± 9.0; p = 0.007) and an increased distensibility coefficient (+13.3% ± 32.3; p = 0.040). Conclusions: Our results confirm that menopause affects vascular health status. Post-menopausal women with an increased stiffness benefit most from MK-7 supplementation, with a significantly improved blood pressure. Further research is needed to unravel the beneficial effects of MK-7 in post-menopausal women.

PMID:40077685 | DOI:10.3390/nu17050815

Int J Mol Sci. 2025 Mar 5;26(5):2311. doi: 10.3390/ijms26052311.

ABSTRACT

T cells play diverse roles in cancer immunology, acting as tumor suppressors, cytotoxic effectors, enhancers of cytotoxic T lymphocyte responses and immune suppressors; providing memory and surveillance; modulating the tumor microenvironment (TME); or activating innate immune cells. However, cancer cells can disrupt T cell function, leading to T cell exhaustion and a weakened immune response against the tumor. The expression of exhausted T cell (Tex) markers plays a pivotal role in shaping the immune landscape of multiple cancers. Our aim was to systematically investigate the role of known T cell exhaustion (Tex) markers across multiple cancers while exploring their molecular interactions, mutation profiles, and potential implications for immunotherapy. The mRNA expression profile of six Tex markers, LAG-3, PDCD1, TIGIT, HAVCR2, CXCL13, and LAYN was investigated in pan-cancer. Utilizing data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), The Cancer Proteome Atlas (TCPA), and other repositories, we characterized the differential expression of the Tex markers, their association with the patients' survival outcome, and their mutation profile in multiple cancers. Additionally, we analyzed the effects on cancer-related pathways and immune infiltration within the TME, offering valuable insights into mechanisms of cancer immune evasion and progression. Finally, the correlation between their expression and sensitivity to multiple anti-cancer drugs was investigated extensively. Differential expression of all six markers was significantly associated with KIRC and poor prognosis in several cancers. They also played a potential activating role in apoptosis, EMT, and hormone ER pathways, as well as a potential inhibitory role in the DNA damage response and RTK oncogenic pathways. Infiltration of different immune cells was also found to be associated with the expression of the Tex-related genes in most cancer types. These findings underline that the reviving of exhausted T cells can be used to enhance the efficacy of immunotherapy in cancer patients.

PMID:40076932 | DOI:10.3390/ijms26052311

Int J Mol Sci. 2025 Feb 28;26(5):2224. doi: 10.3390/ijms26052224.

ABSTRACT

Three-dimensional genome organization reveals that gene regulatory elements, which are linearly distant on the genome, can spatially interact with target genes to regulate their expression. DNA fluorescence in situ hybridization (DNA-FISH) is an efficient method for studying the spatial proximity of genomic loci. In this study, we developed an optimized Tn5 transposome-based DNA-FISH method, termed Tn5-labeled DNA-FISH. This approach amplifies the target region and uses a self-assembled Tn5 transposome to simultaneously fragment the DNA into ~100 bp segments and label it with fluorescent oligonucleotides in a single step. This method enables the preparation of probes for regions as small as 4 kb and visualizes both endogenous and exogenous genomic loci at kb resolution. Tn5-labeled DNA-FISH provides a streamlined and cost-effective tool for probe generation, facilitating the investigation of chromatin spatial conformations, gene interactions, and genome architecture.

PMID:40076846 | DOI:10.3390/ijms26052224

Int J Mol Sci. 2025 Feb 28;26(5):2196. doi: 10.3390/ijms26052196.

ABSTRACT

The global rise in diabetes prevalence has significantly contributed to the increasing burden of atherosclerotic cardiovascular disease (ASCVD), a leading cause of morbidity and mortality in this population. Diabetes accelerates atherosclerosis through mechanisms such as hyperglycemia, oxidative stress, chronic inflammation, and epigenetic dysregulation, leading to unstable plaques and an elevated risk of cardiovascular events. Despite advancements in controlling traditional risk factors like dyslipidemia and hypertension, a considerable residual cardiovascular risk persists, highlighting the need for innovative therapeutic approaches. Emerging treatments, including sodium-glucose cotransporter 2 (SGLT2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, epigenetic modulators, and RNA-based therapies, are showing promise in addressing the unique challenges of diabetes-associated ASCVD. Precision medicine strategies, such as nanoparticle-based drug delivery and cell-specific therapies, offer further potential for mitigating cardiovascular complications. Advances in multiomics and systems biology continue to deepen our understanding of the molecular mechanisms driving diabetes-associated atherosclerosis. This review synthesizes recent advances in understanding the pathophysiology and treatment of diabetes-related atherosclerosis, offering a roadmap for future research and precision medicine approaches to mitigate cardiovascular risk in this growing population.

PMID:40076813 | DOI:10.3390/ijms26052196

Int J Mol Sci. 2025 Feb 27;26(5):2078. doi: 10.3390/ijms26052078.

ABSTRACT

Autism spectrum disorder (ASD) is a complex multifactorial neurodevelopmental disorder. Despite extensive research involving genome-wide association studies, copy number variant (CNV) testing, and genome sequencing, the comprehensive genetic landscape remains incomplete. In this context, we developed a systems biology approach to prioritize genes associated with ASD and uncover potential new candidates. A Protein-Protein Interaction (PPI) network was generated from genes associated to ASD in a public database. Leveraging gene topological properties, particularly betweenness centrality, we prioritized genes and unveiled potential novel candidates (e.g., CDC5L, RYBP, and MEOX2). To test this approach, a list of genes within CNVs of unknown significance, identified through array comparative genomic hybridization analysis in 135 ASD patients, was mapped onto the PPI network. A prioritized gene list was obtained through ranking by betweenness centrality score. Intriguingly, by over-representation analysis, significant enrichments emerged in pathways not strictly linked to ASD, including ubiquitin-mediated proteolysis and cannabinoid receptor signaling, suggesting their potential perturbation in ASD. Our systems biology approach provides a promising strategy for identifying ASD risk genes, especially in large and noisy datasets, and contributes to a deeper understanding of the disorder's complex genetic basis.

PMID:40076702 | DOI:10.3390/ijms26052078

Int J Mol Sci. 2025 Feb 21;26(5):1861. doi: 10.3390/ijms26051861.

ABSTRACT

Integrin-linked kinase (ILK) is a key scaffolding protein between extracellular matrix protein and the cytoskeleton and has been implicated previously in the pathogenesis of renal damage. However, its involvement in renal mitochondrial dysfunction remains to be elucidated. We studied the role of ILK and its downstream regulations in renal damage and mitochondria function both in vivo and vitro, using a folic acid (FA)-induced kidney disease model. Wild type (WT) and ILK conditional-knockdown (cKD-ILK) mice were injected with a single intraperitoneal dose of FA and studied after 15 days of chronic renal damage progression. Human Kidney tubular epithelial cells (HK2) were transfected with specific siRNAs targeting ILK, glycogen synthase kinase 3-β (GSK3β), or CCAAT/enhancer binding protein-β (C/EBPβ). The expressions and activities of renal ILK, GSK3β, C/EBPβ, mitochondrial oxidative phosphorylation enzymes, and mitochondrial membrane potential were assessed. Additionally, the expression of markers for fibrosis fibronectin (FN) and collagen 1 (COL1A1), for autophagy p62 and cytosolic light chain 3 (LC3B) isoforms II and I, and mitochondrial homeostasis marker carnitine palmitoyl-transferase 1A (CPT1A) were evaluated using immunoblotting, RT-qPCR, immunofluorescence, or colorimetric assays. FA upregulated ILK expression, leading to the decrease of GSK3β activity, increased tubular fibrosis, and produced mitochondrial dysfunction, both in vivo and vitro. These alterations were fully or partially reversed upon ILK depletion, mitigating FA-induced renal damage. The signaling axis composed by ILK, GSK3β, and C/EBPβ regulated CPT1A transcription as the limiting factor in the FA-based impaired mitochondrial activity. We highlight ILK as a potential therapeutical target for preserving mitochondrial function in kidney injury.

PMID:40076489 | DOI:10.3390/ijms26051861

Int J Mol Sci. 2025 Feb 21;26(5):1854. doi: 10.3390/ijms26051854.

ABSTRACT

In recent years, the emergence of insecticide resistance has been a major challenge to global public health. Understanding the molecular mechanisms of this phenomenon in mosquito vectors is paramount for the formulation of effective vector control strategies. This review explores the current knowledge of insecticide resistance mechanisms through omics approaches. Genomic, transcriptomic, proteomic, and metabolomics approaches have proven crucial to understand these resilient vectors. Genomic studies have identified multiple genes associated with insecticide resistance, while transcriptomics has revealed dynamic gene expression patterns in response to insecticide exposure and other environmental stimuli. Proteomics and metabolomics offer insights into protein expression and metabolic pathways involved in detoxification and resistance. Integrating omics data holds immense potential to expand our knowledge on the molecular basis of insecticide resistance in mosquitoes via information obtained from different omics platforms to understand regulatory mechanisms and differential expression of genes and protein, and to identify the transcription factors and novel molecules involved in the detoxification of insecticides. Eventually, these data will help construct predictive models, identify novel strategies, and develop targeted interventions to control vector-borne diseases.

PMID:40076478 | DOI:10.3390/ijms26051854