Analyst. 2025 Jan 14. doi: 10.1039/d4an01323a. Online ahead of print.

ABSTRACT

Ergothioneine (ERG) is a natural sulfur-containing amino acid found in many organisms, including humans. It accumulates at high concentrations in red blood cells and is distributed to various organs, including the brain. ERG has numerous health benefits and antioxidant capabilities, and it has been linked to various human physiological processes, such as anti-inflammatory, neuroprotective, and anti-aging effects. Accurate, rapid, and cost-effective quantification of ERG levels in human biofluids is crucial for understanding its role in oxidative stress-related diseases. Surface-enhanced Raman scattering (SERS) is an effective approach for measuring compounds at concentrations similar to those at which ERG is present in serum. However, while SERS has been used to characterize or detect ERG, quantification has not yet been achieved due to the variability in the signal enhancement that can arise during sample preparation and analysis. This study introduces a highly efficient and reliable technique for quickly (20 min is typical per sample) measuring ERG levels in human serum using SERS. This employs an internal standard highly specific for ERG which resulted in limit of quantification values of 0.71 μM. To validate this approach, we analysed real human serum with unknown ERG levels as a blind test set and primary reference levels of ERG were produced using a targeted UHPLC-MS/MS reference method.

PMID:39807959 | DOI:10.1039/d4an01323a

New Phytol. 2025 Jan 14. doi: 10.1111/nph.20384. Online ahead of print.

ABSTRACT

Lupins are promising protein crops that accumulate toxic quinolizidine alkaloids (QAs) in the seeds, complicating their end-use. QAs are synthesized in green organs (leaves, stems, and pods) and a subset of them is transported to the seeds during fruit development. The exact sites of biosynthesis and accumulation remain unknown; however, mesophyll cells have been proposed as sources, and epidermal cells as sinks. We investigated the exact sites of QA biosynthesis and accumulation in biosynthetic organs of narrow-leafed lupin (Lupinus angustifolius) using mass spectrometry-based imaging (MSI), laser-capture microdissection coupled to RNA-Seq, and precursor feeding studies coupled to LC-MS and MSI. We found that the QAs that accumulate in seeds ('core' QAs) were evenly distributed across tissues; however, their esterified versions accumulated primarily in the epidermis. Surprisingly, RNA-Seq revealed strong biosynthetic gene expression in the epidermis, which was confirmed in leaves by quantitative real-time polymerase chain reaction. Finally, feeding studies using a stably labeled precursor showed that the lower leaf epidermis is highly biosynthetic. Our results indicate that the epidermis is a major site of QA biosynthesis in narrow-leafed lupin, challenging the current assumptions. Our work has direct implications for the elucidation of the QA biosynthesis pathway and the long-distance transport network from source to seed.

PMID:39807565 | DOI:10.1111/nph.20384

Comput Struct Biotechnol J. 2024 Mar 1;23:1076-1087. doi: 10.1016/j.csbj.2024.02.019. eCollection 2024 Dec.

ABSTRACT

DNA holds immense potential as an emerging data storage medium. However, the recovery of information in DNA storage systems faces challenges posed by various errors, including IDS errors, strand breaks, and rearrangements, inevitably introduced during synthesis, amplification, sequencing, and storage processes. Sequence reconstruction, crucial for decoding, involves inferring the DNA reference from a cluster of erroneous copies. While most methods assume equal contributions from all reads within a cluster as noisy copies of the same reference, they often overlook the existence of contaminated sequences caused by DNA breaks, rearrangements, or mis-clustering reads. To address this issue, we propose RobuSeqNet, a robust multi-read reconstruction neural network specifically designed to robustly reconstruct multiple reads, accommodating noisy clusters with strand breakage, rearrangements, and mis-clustered strands. Leveraging the attention mechanism and an elaborate network design, RobuSeqNet exhibits resilience to highly-noisy clusters and effectively deals with in-strand IDS errors. The effectiveness and robustness of the proposed method are validated on three representative next-generation sequencing datasets. Results demonstrate that RobuSeqNet maintains high sequence reconstruction success rates of 99.74%, 99.58%, and 96.44% across three datasets, even in the presence of noisy clusters containing up to 20% contaminated sequences, outperforming known sequence reconstruction models. Additionally, in scenarios without contaminated sequences, it exhibits comparable performance to existing models, achieving success rates of 99.88%, 99.82%, and 97.68% across the three datasets.

PMID:39807110 | PMC:PMC11725466 | DOI:10.1016/j.csbj.2024.02.019

Endocr Metab Immune Disord Drug Targets. 2025 Jan 9. doi: 10.2174/0118715303313654241101042033. Online ahead of print.

ABSTRACT

BACKGROUND: There is still no conclusive understanding of whether the glucokinase regulator (GCKR) gene rs780094 and rs1260326 polymorphisms predispose to gestational diabetes mellitus (GDM).

OBJECTIVE: This systematic review and meta-analysis aimed to determine the effect of the GCKR polymorphisms on GDM susceptibility.

METHODS: Seven literature databases were searched (from inception to February 17, 2024) to locate relevant studies included in further meta-analysis. Odds ratio (OR) and 95% confidence intervals (CI) in the pooled population were estimated to assess the effects of the variant allele on GDM risk.

RESULTS: For the rs780094 polymorphism, 13 datasets with 3443 GDM cases and 5930 nondiabetic controls were included. The pooled estimates in the allele model (OR: 1.19, 95% CI: 1.07~1.32), homozygote model (OR: 1.27, 95% CI: 1.10~1.47), dominant model (OR: 1.16, 95% CI: 1.03~1.31), and recessive model (OR: 1.31, 95% CI: 1.09~1.57) suggested that the C allele carriers were prone to GDM. For the rs1260326 polymorphism, five datasets with 1495 cases and 2678 controls were integrated. The statistically significant effect of the C allele was evident in the allele model (OR: 1.12, 95% CI: 1.01~1.24) and the homozygote model (OR: 1.26, 95% CI: 1.03~1.54).

CONCLUSION: This meta-analysis suggested that the C allele of the rs780094 and rs1260326 polymorphisms in the GCKR gene are significantly associated with increased risk of GDM.

PMID:39806965 | DOI:10.2174/0118715303313654241101042033

Mol Med. 2025 Jan 14;31(1):12. doi: 10.1186/s10020-025-01069-w.

ABSTRACT

The Systemic Evolutionary Theory of the Origin of Cancer (SETOC) is a recently proposed theory founded on two primary principles: the cooperative and endosymbiotic process of cell evolution as described by Lynn Margulis, and the integration of complex systems operating in eukaryotic cells, which is a core concept in systems biology. The SETOC proposes that malignant transformation occurs when cells undergo a continuous adaptation process in response to long-term injuries, leading to tissue remodeling, chronic inflammation, fibrosis, and ultimately cancer. This process involves a maladaptive response, wherein the 'endosymbiotic contract' between the nuclear-cytoplasmic system (derived from the primordial archaeal cell) and the mitochondrial system (derived from the primordial α-proteobacterium) gradually breaks down. This ultimately leads to uncoordinated behaviors and functions in transformed cells. The decoupling of the two cellular subsystems causes transformed cells to acquire phenotypic characteristics analogous to those of unicellular organisms, as well as certain biological features of embryonic development that are normally suppressed. These adaptive changes enable cancer cells to survive in the harsh tumor microenvironment characterized by low oxygen concentrations, inadequate nutrients, increased catabolic waste, and increased acidity. De-endosymbiosis reprograms the sequential metabolic functions of glycolysis, the TCA cycle, and oxidative phosphorylation (OxPhos). This leads to increased lactate fermentation (Warburg effect), respiratory chain dysfunction, and TCA cycle reversal. Here, we present an updated version of the SETOC that incorporates the fundamental principles outlined by this theory and integrates the epistemological approach used to develop it.

PMID:39806272 | DOI:10.1186/s10020-025-01069-w

Nat Aging. 2025 Jan 13. doi: 10.1038/s43587-024-00794-x. Online ahead of print.

ABSTRACT

DNA methylation marks have recently been used to build models known as epigenetic clocks, which predict calendar age. As methylation of cytosine promotes C-to-T mutations, we hypothesized that the methylation changes observed with age should reflect the accrual of somatic mutations, and the two should yield analogous aging estimates. In an analysis of multimodal data from 9,331 human individuals, we found that CpG mutations indeed coincide with changes in methylation, not only at the mutated site but with pervasive remodeling of the methylome out to ±10 kilobases. This one-to-many mapping allows mutation-based predictions of age that agree with epigenetic clocks, including which individuals are aging more rapidly or slowly than expected. Moreover, genomic loci where mutations accumulate with age also tend to have methylation patterns that are especially predictive of age. These results suggest a close coupling between the accumulation of sporadic somatic mutations and the widespread changes in methylation observed over the course of life.

PMID:39806003 | DOI:10.1038/s43587-024-00794-x

Nat Microbiol. 2025 Jan 13. doi: 10.1038/s41564-024-01891-8. Online ahead of print.

ABSTRACT

Despite ongoing antibiotic development, evolution of resistance may render candidate antibiotics ineffective. Here we studied in vitro emergence of resistance to 13 antibiotics introduced after 2017 or currently in development, compared with in-use antibiotics. Laboratory evolution showed that clinically relevant resistance arises within 60 days of antibiotic exposure in Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii and Pseudomonas aeruginosa, priority Gram-negative ESKAPE pathogens. Resistance mutations are already present in natural populations of pathogens, indicating that resistance in nature can emerge through selection of pre-existing bacterial variants. Functional metagenomics showed that mobile resistance genes to antibiotic candidates are prevalent in clinical bacterial isolates, soil and human gut microbiomes. Overall, antibiotic candidates show similar susceptibility to resistance development as antibiotics currently in use, and the corresponding resistance mechanisms overlap. However, certain combinations of antibiotics and bacterial strains were less prone to developing resistance, revealing potential narrow-spectrum antibacterial therapies that could remain effective. Finally, we develop criteria to guide efforts in developing effective antibiotic candidates.

PMID:39805953 | DOI:10.1038/s41564-024-01891-8

FEBS J. 2025 Jan 13. doi: 10.1111/febs.17398. Online ahead of print.

ABSTRACT

Vesicle trafficking is pivotal in heparan sulfate (HS) biosynthesis, influencing its spatial and temporal regulation within distinct Golgi compartments. This regulation modulates the sulfation pattern of HS, which is crucial for governing various biological processes. Here, we investigate the effects of silencing Rab1A and Rab2A expression on the localisation of 3-O-sulfotransferase-5 (3OST5) within Golgi compartments and subsequent alterations in HS structure and levels. Interestingly, silencing Rab1A led to a shift in 3OST5 localization towards the trans-Golgi, resulting in increased HS levels within 24 and 48 h, while silencing Rab2A caused 3OST5 accumulation in the cis-Golgi, with a delayed rise in HS content observed after 48 h. Furthermore, a compensatory mechanism was evident in Rab2A-silenced cells, where increased Rab1A protein expression was detected. This suggests a dynamic interplay between Rab1A and Rab2A in maintaining the fine balance of vesicle trafficking processes involved in HS biosynthesis. Additionally, we demonstrate that the trafficking of 3OST5 in COPI vesicles is facilitated by GOLPH3 protein. These findings identify novel vesicular transport mechanisms regulating HS biosynthesis and reveal a compensatory relationship between Rab1A and Rab2A in maintaining baseline HS production.

PMID:39804811 | DOI:10.1111/febs.17398

Cardiovasc Res. 2025 Jan 10:cvae267. doi: 10.1093/cvr/cvae267. Online ahead of print.

ABSTRACT

AIMS: The gastrointestinal (GI) tract is composed of distinct sub-regions, which exhibit segment-specific differences in microbial colonization and (patho)physiological characteristics. Gut microbes can be collectively considered as an active endocrine organ. Microbes produce metabolites, which can be taken up by the host and can actively communicate with the immune cells in the gut lamina propria with consequences for cardiovascular health. Variation in bacterial load and composition along the GI tract may influence the mucosal microenvironment and thus be reflected its interstitial fluid (IF). Characterization of the segment-specific microenvironment is challenging and largely unexplored because of lack of available tools.

METHODS AND RESULTS: Here, we developed methods, namely tissue centrifugation and elution, to collect IF from the mucosa of different intestinal segments. These methods were first validated in rats and mice, and the tissue elution method was subsequently translated for use in humans. These new methods allowed us to quantify microbiota-derived metabolites, mucosa-derived cytokines, and proteins at their site-of-action. Quantification of short-chain fatty acids showed enrichment in the colonic IF. Metabolite and cytokine analyses revealed differential abundances within segments, often significantly increased compared to plasma, and proteomics revealed that proteins annotated to the extracellular phase were site-specifically identifiable in IF. Lipopolysaccharide injections in rats showed significantly higher ileal IL-1β levels in IF compared to the systemic circulation, suggesting the potential of local as well as systemic effect.

CONCLUSION: Collection of IF from defined segments and the direct measurement of mediators at the site-of-action in rodents and humans bypasses the limitations of indirect analysis of faecal samples or serum, providing direct insight into this understudied compartment.

PMID:39804196 | DOI:10.1093/cvr/cvae267

Elife. 2025 Jan 13;13:RP92683. doi: 10.7554/eLife.92683.

ABSTRACT

Many applications in biomedicine and synthetic bioengineering rely on understanding, mapping, predicting, and controlling the complex behavior of chemical and genetic networks. The emerging field of diverse intelligence investigates the problem-solving capacities of unconventional agents. However, few quantitative tools exist for exploring the competencies of non-conventional systems. Here, we view gene regulatory networks (GRNs) as agents navigating a problem space and develop automated tools to map the robust goal states GRNs can reach despite perturbations. Our contributions include: (1) Adapting curiosity-driven exploration algorithms from AI to discover the range of reachable goal states of GRNs, and (2) Proposing empirical tests inspired by behaviorist approaches to assess their navigation competencies. Our data shows that models inferred from biological data can reach a wide spectrum of steady states, exhibiting various competencies in physiological network dynamics without requiring structural changes in network properties or connectivity. We also explore the applicability of these 'behavioral catalogs' for comparing evolved competencies across biological networks, for designing drug interventions in biomedical contexts and synthetic gene networks for bioengineering. These tools and the emphasis on behavior-shaping open new paths for efficiently exploring the complex behavior of biological networks. For the interactive version of this paper, please visit https://developmentalsystems.org/curious-exploration-of-grn-competencies.

PMID:39804159 | DOI:10.7554/eLife.92683

Anal Chem. 2025 Jan 13. doi: 10.1021/acs.analchem.4c04692. Online ahead of print.

ABSTRACT

Simultaneous analysis of multiple phosphorylated metabolites (phosphorylated metabolome) in biological samples is vital to reveal their physiological and pathophysiological functions, which is extremely challenging due to their low abundance in some biological matrices, high hydrophilicity, and poor chromatographic behavior. Here, we developed a new method with ion-pair reversed-phase ultrahigh-performance liquid chromatography and mass spectrometry using BEH C18 columns modified with hybrid surface technology. This method demonstrated good performances for various phosphorylated metabolites, including phosphorylated sugars and amino acids, nucleotides, NAD-based cofactors, and acyl-CoAs in a single run using standard LC systems. Specifically, the method showed good retention (capacity factor > 2) and reproducibility (ΔtR < 0.09 min, n = 6), peak symmetry (tailing factor < 2), and sensitivity (limit-of-detection < 238 fmol-on-column with QTOFMS) for all tested analytes especially for the medium- and/or long-chain acyl-CoAs. The method demonstrated reproducible applicability across numerous biological matrices, including tissue (liver), human biofluids (urine, plasma), cells, and feces, and revealed significant molecular phenotypic differences in phosphorylated metabolite composition.

PMID:39804109 | DOI:10.1021/acs.analchem.4c04692

Bio Protoc. 2025 Jan 5;15(1):e5155. doi: 10.21769/BioProtoc.5155. eCollection 2025 Jan 5.

ABSTRACT

The bone is a highly dynamic organ that undergoes continuous remodeling through an intricate balance of bone formation and degradation. Hyperactivation of the bone-degrading cells, the osteoclasts (OCs), occurs in disease conditions and hormonal changes in females, resulting in osteoporosis, a disease characterized by altered microarchitecture of the bone tissue, and increased bone fragility. Thus, building robust assays to quantify OC resorptive activity to examine the molecular mechanisms underlying bone degradation is critical. Here, we establish an in vitro model to investigate the effect of estrogen withdrawal on OCs derived from the mouse macrophage RAW 264.7 cell line in a bone biomimetic microenvironment. This simple and robust model can also be adapted to examine the effect of drugs and genetic factors influencing OC resorptive activity in addition to being compatible with fluorescent imaging. Key features • A robust in vitro protocol that allows molecular and functional studies of mature osteoclasts in response to estrogen and its withdrawal. • Generation of inorganic bone-mimetic substrates for culturing and examining osteoclast resorptive behavior. • This quantitative image-based approach is compatible with brightfield and fluorescence microscopy to assess osteoclast resorptive activity.

PMID:39803321 | PMC:PMC11717722 | DOI:10.21769/BioProtoc.5155

Nat Commun. 2025 Jan 12;16(1):614. doi: 10.1038/s41467-025-55847-5.

ABSTRACT

Immunotherapy is improving the survival of patients with metastatic non-small cell lung cancer (NSCLC), yet reliable biomarkers are needed to identify responders prospectively and optimize patient care. In this study, we explore the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We analyze baseline multimodal data from a cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, including positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information. Testing multiple integration strategies, most of them yield multimodal models surpassing both the best unimodal models and established univariate biomarkers, such as PD-L1 expression. Additionally, several multimodal combinations demonstrate improved patient risk stratification compared to models built with routine clinical features only. Our study thus provides evidence of the superiority of multimodal over unimodal approaches, advocating for the collection of large multimodal NSCLC datasets to develop and validate robust and powerful immunotherapy biomarkers.

PMID:39800784 | DOI:10.1038/s41467-025-55847-5

Signal Transduct Target Ther. 2025 Jan 13;10(1):14. doi: 10.1038/s41392-024-02114-6.

ABSTRACT

The global spread of Severe Acute Respiratory Syndrome Coronavirus 2. (SARS-CoV-2) and its variant strains, including Alpha, Beta, Gamma, Delta, and now Omicron, pose a significant challenge. With the constant evolution of the virus, Omicron and its subtypes BA.1, BA.2, BA.3, BA.4, and BA.5 have developed the capacity to evade neutralization induced by previous vaccination or infection. This evasion highlights the urgency in discovering new monoclonal antibodies (mAbs) with neutralizing activity, especially broadly neutralizing antibodies (bnAbs), to combat the virus.In the current study, we introduced a fully human neutralizing mAb, CR9, that targets Omicron variants. We demonstrated the mAb's effectiveness in inhibiting Omicron replication both in vitro and in vivo. Structural analysis using cryo-electron microscopy (cryo-EM) revealed that CR9 binds to an epitope formed by RBD residues, providing a molecular understanding of its neutralization mechanism. Given its potency and specificity, CR9 holds promise as a potential adjunct therapy for treating Omicron infections. Our findings highlight the importance of continuous mAb discovery and characterization in addressing the evolving threat of COVID-19.

PMID:39800731 | DOI:10.1038/s41392-024-02114-6

Gut Microbes. 2025 Dec;17(1):2446423. doi: 10.1080/19490976.2024.2446423. Epub 2025 Jan 12.

ABSTRACT

The therapeutic benefits of opioids are compromised by the development of analgesic tolerance, which necessitates higher dosing for pain management thereby increasing the liability for drug dependence and addiction. Rodent models indicate opposing roles of the gut microbiota in tolerance: morphine-induced gut dysbiosis exacerbates tolerance, whereas probiotics ameliorate tolerance. Not all individuals develop tolerance, which could be influenced by differences in microbiota, and yet no study design has capitalized upon this natural variation. We leveraged natural behavioral variation in a murine model of voluntary oral morphine self-administration to elucidate the mechanisms by which microbiota influences tolerance. Although all mice shared similar morphine-driven microbiota changes that largely masked informative associations with variability in tolerance, our high-resolution temporal analyses revealed a divergence in the progression of dysbiosis that best explained sustained antinociception. Mice that did not develop tolerance maintained a higher capacity for production of the short-chain fatty acid (SCFA) butyrate known to bolster intestinal barriers and promote neuronal homeostasis. Both fecal microbial transplantation (FMT) from donor mice that did not develop tolerance and dietary butyrate supplementation significantly reduced the development of tolerance independently of suppression of systemic inflammation. These findings could inform immediate therapies to extend the analgesic efficacy of opioids.

PMID:39800714 | DOI:10.1080/19490976.2024.2446423

Chin Med. 2025 Jan 12;20(1):8. doi: 10.1186/s13020-024-01056-z.

ABSTRACT

Network pharmacology plays a pivotal role in systems biology, bridging the gap between traditional Chinese medicine (TCM) theory and contemporary pharmacological research. Network pharmacology enables researchers to construct multilayered networks that systematically elucidate TCM's multi-component, multi-target mechanisms of action. This review summarizes key databases commonly used in network pharmacology, including those focused on herbs, components, diseases, and dedicated platforms for network pharmacology analysis. Additionally, we explore the growing use of network pharmacology in TCM, citing literature from Web of Science, PubMed, and CNKI over the past two decades with keywords like "network pharmacology", "TCM network pharmacology", and "herb network pharmacology". The application of network pharmacology in TCM is widespread, covering areas such as identifying the material basis of TCM efficacy, unraveling mechanisms of action, and evaluating toxicity, safety, and novel drug development. However, challenges remain, such as the lack of standardized data collection across databases and insufficient consideration of processed herbs in research. Questions also persist regarding the reliability of study outcomes. This review aims to offer valuable insights and reference points to guide future research in precision TCM network pharmacology.

PMID:39800680 | DOI:10.1186/s13020-024-01056-z

Infect Genet Evol. 2025 Jan 10:105713. doi: 10.1016/j.meegid.2025.105713. Online ahead of print.

ABSTRACT

Whole genome sequencing has been used to investigate the genomic diversity of M. tuberculosis in the northern and southern states of India, but information about the eastern part of the country is still limited. Through a sequencing-based strategy, this study seeks to comprehend the diversity and drug resistance pattern in the eastern region. A total of 102 M. tuberculosis isolates from North East (n = 54), and Odisha (n = 48) were sequenced along with 7 follow up isolates from Sikkim. The pre-XDR and XDR isolates diagnosed as per the NTEP diagnostic algorithm were subjected for phenotypic second-line liquid culture drug susceptibility testing in MGIT-960 system. After filtering out low quality isolates based on taxonomic classification and depth of coverage, variant calling was performed. We observed a high prevalence of multi-drug resistant TB (MDR-TB) lineage 2 (52/54) isolates in northeast whereas there was a mixed representation of lineage 1 (30/48) & lineage 3 (11/48) in Odisha. The MDR-TB isolates from Sikkim posed a high rate (51/53) of fluoroquinolone resistance and pairwise SNV distances (≤10) indicating possible local transmission events in the region. We observed occurrence of genetic variations in genes associated with bedaquiline and delamanid resistance. Our findings show the diversity of M. tuberculosis vary across the eastern regions, in north eastern states lineage 2 has a dominant presence while lineage 1 and 3 has mixed representation in Odisha. The high prevalence of fluoroquinolone resistance in north eastern region associated with variations in gyrA gene and may have been caused by local transmission events based on genomic similarities.

PMID:39800206 | DOI:10.1016/j.meegid.2025.105713

Mol Cells. 2025 Jan 10:100180. doi: 10.1016/j.mocell.2025.100180. Online ahead of print.

ABSTRACT

Recent advancements in fluorescence-based biosensor technologies have enabled more precise and accurate Förster Resonance Energy Transfer (FRET) imaging within Agrobacterium-mediated plant transformation systems. However, the application of FRET imaging in plant tissues remains hindered by significant challenges, particularly the time-intensive process of generating transgenic lines and the complications arising from tissue autofluorescence. In contrast, protoplast-based FRET imaging offers a rapid and efficient platform for functional screening and analysis, making it an essential tool for plant research. Nevertheless, conventional protoplast-based FRET approaches are often limited by background interference, inconsistent imaging conditions, and difficulties in quantitative analysis. Here, we present a systematic optimization of imaging conditions using the calcium biosensor D3cpv, addressing these limitations to improve both precision and efficiency in protoplast-based FRET imaging. This work serves as a practical guide for streamlining FRET imaging workflows and maximizing the utility of biosensors in plant cell studies.

PMID:39800051 | DOI:10.1016/j.mocell.2025.100180

Bioinformatics. 2025 Jan 12:btaf015. doi: 10.1093/bioinformatics/btaf015. Online ahead of print.

ABSTRACT

SUMMARY: With the increased reliance on multi-omics data for bulk and single cell analyses, the availability of robust approaches to perform unsupervised learning for clustering, visualization, and feature selection is imperative. We introduce nipalsMCIA, an implementation of multiple co-inertia analysis (MCIA) for joint dimensionality reduction that solves the objective function using an extension to Non-linear Iterative Partial Least Squares (NIPALS). We applied nipalsMCIA to both bulk and single cell datasets and observed significant speed-up over other implementations for data with a large sample size and/or feature dimension.

AVAILABILITY AND IMPLEMENTATION: nipalsMCIA is available as a Bioconductor package at https://bioconductor.org/packages/release/bioc/html/nipalsMCIA.html, and includes detailed documentation and application vignettes.

SUPPLEMENTARY MATERIALS: Supplementary Materials are available online.

PMID:39799512 | DOI:10.1093/bioinformatics/btaf015

Sci Rep. 2025 Jan 11;15(1):1718. doi: 10.1038/s41598-025-85240-7.

ABSTRACT

The effective prevention of many infectious and non-infectious diseases relies on people concurrently adopting multiple prevention behaviors. Individual characteristics, opinion leaders, and social networks have been found to explain why people take up specific prevention behaviors. However, it remains challenging to understand how these factors shape multiple interdependent behaviors. We propose a multilevel social network framework that allows us to study the effects of individual and social factors on multiple disease prevention behaviors simultaneously. We apply this approach to examine the factors explaining eight malaria prevention behaviors, using unique interview data collected from 1529 individuals in 10 hard-to-reach, malaria-endemic villages in Meghalaya, India in 2020-2022. Statistical network modelling reveals exposure to similar behaviors in one's social network as the most important factor explaining prevention behaviors. Further, we find that households indirectly shape behaviors as key contexts for social ties. Together, these two factors are crucial for explaining the observed patterns of behaviors and social networks in the data, outweighing individual characteristics, opinion leaders, and social network size. The results highlight that social network processes may facilitate or hamper disease prevention efforts that rely on a combination of behaviors. Our approach is well suited to study these processes in the context of various diseases.

PMID:39799220 | DOI:10.1038/s41598-025-85240-7