Fundam Res. 2022 Dec 26;4(6):1674-1687. doi: 10.1016/j.fmre.2022.12.009. eCollection 2024 Nov.

ABSTRACT

Making time-series forecasting in a robust way is a difficult task only based on the observed data of a nonlinear system. In this work, a neural network computing framework, the spatiotemporal information conversion machine (STICM), was developed to efficiently and accurately render a forecasting of a time series by employing a spatial-temporal information (STI) transformation. STICM combines the advantages of both the STI equation and the temporal convolutional network, which maps the high-dimensional/spatial data to the future temporal values of a target variable, thus naturally providing the forecasting of the target variable. From the observed variables, the STICM also infers the causal factors of the target variable in the sense of Granger causality, which are in turn selected as effective spatial information to improve the robustness of time-series forecasting. The STICM was successfully applied to both benchmark systems and real-world datasets, all of which show superior and robust performance in time-series forecasting, even when the data were perturbed by noise. From both theoretical and computational viewpoints, the STICM has great potential in practical applications in artificial intelligence or as a model-free method based only on the observed data, and also opens a new way to explore the observed high-dimensional data in a dynamical manner for machine learning.

PMID:39734521 | PMC:PMC11670686 | DOI:10.1016/j.fmre.2022.12.009

Sci Rep. 2024 Dec 28;14(1):31374. doi: 10.1038/s41598-024-82833-6.

ABSTRACT

Enhancing crops productivity to ensure food security is one of the major challenges encountering agriculture today. A promising solution is the use of biostimulants, which encompass molecules that enhance plant fitness, growth, and productivity. The regulatory metabolite zaxinone and its mimics (MiZax3 and MiZax5) showed promising results in improving the growth and yield of several crops. Here, the impact of their exogenous application on soil and rice root microbiota was investigated. Plants grown in native paddy soil were treated with zaxinone, MiZax3, and MiZax5 and the composition of bacterial and fungal communities in soil, rhizosphere, and endosphere at the tillering and the milky stage was assessed. Furthermore, shoot metabolome profile and nutrient content of the seeds were evaluated. Results show that treatment with zaxinone and its mimics predominantly influenced the root endosphere prokaryotic community, causing a partial depletion of plant-beneficial microbes at the tillering stage, followed by a recovery of the prokaryotic community structure during the milky stage. Our study provides new insights into the role of zaxinone and MiZax in the interplay between rice and its root-associated microbiota and paves the way for their practical application in the field as ecologically friendly biostimulants to enhance crop productivity.

PMID:39732893 | DOI:10.1038/s41598-024-82833-6

Cell Host Microbe. 2024 Dec 18:S1931-3128(24)00447-5. doi: 10.1016/j.chom.2024.12.002. Online ahead of print.

ABSTRACT

Gastrointestinal colonization by Clostridioides difficile is common in healthcare settings and ranges in presentation from asymptomatic carriage to lethal C. difficile infection (CDI). We used a systems biology approach to investigate why patients colonized with C. difficile have a range of clinical outcomes. Microbiota humanization of germ-free mice with fecal samples from toxigenic C. difficile carriers revealed a spectrum of virulence among clinically prevalent clade 1 lineages and identified candidate taxa, including Blautia, as markers of stable colonization. Using gnotobiotic mice engrafted with defined human microbiota, we validated strain-specific CDI severity across clade 1 strains isolated from patients. Mice engrafted with a community broadly representative of colonized patients were protected from severe disease across all strains without suppression of C. difficile colonization. These results underline the capacity of gut community structure to attenuate a diversity of pathogenic strains without inhibiting colonization, providing insight into determinants of stable C. difficile carriage.

PMID:39731916 | DOI:10.1016/j.chom.2024.12.002

EBioMedicine. 2024 Dec 27;111:105532. doi: 10.1016/j.ebiom.2024.105532. Online ahead of print.

ABSTRACT

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) and its more severe form steatohepatitis (MASH) contribute to rising morbidity and mortality rates. The storage of fat in humans is closely associated with these diseases' progression. Thus, adipose tissue metabolic homeostasis could be key in both the onset and progression of MASH.

METHODS: We conducted a case-control observational research using a systems biology-based approach to analyse liver, abdominal subcutaneous adipose tissue (SAT), omental visceral adipose tissue (VAT), and blood of n = 100 patients undergoing bariatric surgery (NCT05554224). MASH was diagnosed through histologic assessment. Whole-slide image analysis, lipidomics, proteomics, and transcriptomics were performed on tissue samples. Lipidomics and proteomics profiles were determined on plasma samples.

FINDINGS: Liver transcriptomics, proteomics, and lipidomics revealed interconnected pathways associated with inflammation, mitochondrial dysfunction, and lipotoxicity in MASH. Paired adipose tissue biopsies had larger adipocyte areas in both fat depots in MASH. Enrichment analyses of proteomics and lipidomics data confirmed the association of liver lesions with mitochondrial dysfunction in VAT. Plasma lipidomics identified candidates with high diagnostic accuracy (AUC = 0.919, 95% CI 0.840-0.979) for screening MASH.

INTERPRETATION: Mitochondrial dysfunction is also present in VAT in patients with obesity-associated MASH. This may cause a disruption in the metabolic equilibrium of lipid processing and storage, which impacts the liver and accelerates detrimental adaptative responses.

FUNDING: The project leading to these results has received funding from 'la Caixa' Foundation (HR21-00430), and from the Instituto de Salud Carlos III (ISCIII) (PI21/00510) and co-funded by the European Union.

PMID:39731853 | DOI:10.1016/j.ebiom.2024.105532

Comput Biol Chem. 2024 Dec 25;115:108329. doi: 10.1016/j.compbiolchem.2024.108329. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Castration-resistant prostate cancer (CRPC) is caused by resistance to androgen deprivation treatment and leads to the death of patients and there is almost no chance of survival. Therefore, finding a cure to overcome CRPC is challenging and important, but discovering a new drug is very time-consuming and expensive. To overcome these problems, we used Drug repositioning (drug repurposing) strategy in this study.

METHODS: Gene expression data of CRPC and primary prostate samples were extracted from the GEO database to identify DEGs. Pathway enrichment was performed to find the role of DEGs in signaling pathways. To identify hub proteins, the PPI network was reconstructed and analyzed. drug candidates were identified and to select the most effective drug, molecular docking analysis, and molecular dynamics simulation were performed. Then MTT and qRT-PCR tests were performed to check the effectiveness of the selected drug.

RESULTS: A total of 152 upregulated DEGs and 343 downregulated DEGs were identified, and after PPI network analysis, IKBKB, SNAP23, MYC, and NOTCH1 genes were introduced as hubs. drug candidates for IKBKB were identified and by examining the results of docking screening and molecular dynamics, sulfasalazine was selected as the most effective drug. Laboratory analyses proved the effectiveness of this drug and a decrease in the expression of all target genes was observed.

CONCLUSION: In this study, IKBKB key protein were identified in CRPC, and sulfasalazine was selected as a suitable candidate for drug repositioning and its effectiveness was confirmed through tests.

PMID:39731827 | DOI:10.1016/j.compbiolchem.2024.108329

Ann N Y Acad Sci. 2024 Dec 28. doi: 10.1111/nyas.15271. Online ahead of print.

ABSTRACT

What makes animal gaits so audibly rhythmic? To answer this question, we recorded the footfall sound of 19 horses and quantified the rhythmic differences in the temporal structure of three natural gaits: walk, trot, and canter. Our analyses show that each gait displays a strikingly specific rhythmic pattern and that all gaits are organized according to small-integer ratios, those found when adjacent temporal intervals are related by a mathematically simple relationship of integer numbers. Walk and trot exhibit an isochronous structure (1:1)-similar to a ticking clock-while canter is characterized by three small-integer ratios (1:1, 1:2, 2:1). While walk and trot both show isochrony, trot has a slower tempo and is more precise and accurate, like a metronome. Our results quantitatively discriminate horse gaits based on rhythm, revealing striking commonalities with human music and some animal communicative signals. Gait and vocal rhythmicity share key features, and the former likely predates the latter; we suggest this supports gait-based hypotheses for the evolution of rhythm. Specifically, the perception of locomotor rhythmicity may have evolved in different species under pressure for predator recognition and mate selection; it may have been later exapted for rhythmic vocal communication.

PMID:39731731 | DOI:10.1111/nyas.15271

Appl Microbiol Biotechnol. 2024 Dec 28;108(1):547. doi: 10.1007/s00253-024-13379-w.

ABSTRACT

Transcriptomics is a powerful approach for functional genomics and systems biology, yet it can also be used for genetic part discovery. Here, we derive constitutive and light-regulated promoters directly from transcriptomics data of the basidiomycete red yeast Xanthophyllomyces dendrorhous CBS 6938 (anamorph Phaffia rhodozyma) and use these promoters with other genetic elements to create a modular synthetic biology parts collection for this organism. X. dendrorhous is currently the sole biotechnologically relevant yeast in the Tremellomycete class-it produces large amounts of astaxanthin, especially under oxidative stress and exposure to light. Thus, we performed transcriptomics on X. dendrorhous under different wavelengths of light (red, green, blue, and ultraviolet) and oxidative stress. Differential gene expression analysis (DGE) revealed that terpenoid biosynthesis was primarily upregulated by light through crtI, while oxidative stress upregulated several genes in the pathway. Further gene ontology (GO) analysis revealed a complex survival response to ultraviolet (UV) where X. dendrorhous upregulates aromatic amino acid and tetraterpenoid biosynthesis and downregulates central carbon metabolism and respiration. The DGE data was also used to identify 26 constitutive and regulated genes, and then, putative promoters for each of the 26 genes were derived from the genome. Simultaneously, a modular cloning system for X. dendrorhous was developed, including integration sites, terminators, selection markers, and reporters. Each of the 26 putative promoters were integrated into the genome and characterized by luciferase assay in the dark and under UV light. The putative constitutive promoters were constitutive in the synthetic genetic context, but so were many of the putative regulated promoters. Notably, one putative promoter, derived from a hypothetical gene, showed ninefold activation upon UV exposure. Thus, this study reveals metabolic pathway regulation and develops a genetic parts collection for X. dendrorhous from transcriptomic data. Therefore, this study demonstrates that combining systems biology and synthetic biology into an omics-to-parts workflow can simultaneously provide useful biological insight and genetic tools for nonconventional microbes, particularly those without a related model organism. This approach can enhance current efforts to engineer diverse microbes. KEY POINTS: • Transcriptomics revealed further insights into the photobiology of X. dendrorhous, specifically metabolic nodes that are transcriptionally regulated by light. • A modular genetic part collection was developed, including 26 constitutive and regulated promoters derived from the transcriptomics of X. dendrorhous. • Omics-to-parts can be applied to nonconventional microbes for rapid "onboarding".

PMID:39731599 | DOI:10.1007/s00253-024-13379-w

Iran J Immunol. 2024 Dec 28;21(4). doi: 10.22034/iji.2024.104052.2878. Online ahead of print.

ABSTRACT

BACKGROUND: Developing effective targeted treatment approaches to overcome drug resistance remains a crucial goal in cancer research. Immunotoxins have dual functionality in cancer detection and targeted therapy.

OBJECTIVE: This study aimed to engineer a recombinant chimeric fusion protein by combining a nanobody-targeting domain with an exotoxin effector domain. The chimeric protein was designed to bind surface-expressed GRP78 on cancer cells, facilitating internalization and inducing apoptosis to inhibit proliferation and survival.

METHODS: Using a flexible linker, we designed two constructs linking VHH nanobody domains to Pseudomonas exotoxin (PE) domains II, III, and Ib. These constructs were then optimized for expression in E. coli BL21 (DE3) using the pET28a vector. Following the expression of the recombinant proteins, we purified them and tested their binding capability, cytotoxicity, and ability to induce apoptosis in breast cancer cell lines MDA-MB-231 and MCF-7, as well as in control cell lines HEK-293 and MDA-MB-468. The binding affinity was measured using a cell-based ELISA, internalization was assessed through Western blotting, cytotoxicity was evaluated by an MTT assay, and apoptosis was determined using flow cytometry with an Annexin V kit.

RESULTS: The immunotoxin specifically bound to cancer cells expressing csGRP78. The results of the cytotoxicity test showed that the cytotoxic effect of two constructs, I and II, depended on concentration and time. With an increase in both components, the effect of recombinant proteins also increased. Both constructs were able to penetrate and induce apoptosis in csGRP78+ cells.

CONCLUSION: These immunotoxin structures showed therapeutic potential against GRP78-expressing cancers, making them suitable candidates for targeted therapy pending in vivo studies.

PMID:39731471 | DOI:10.22034/iji.2024.104052.2878

Evodevo. 2024 Dec 27;15(1):16. doi: 10.1186/s13227-024-00236-0.

ABSTRACT

BACKGROUND: Fruits, with their diverse shapes, colors, and flavors, represent a fascinating aspect of plant evolution and have played a significant role in human history and nutrition. Understanding the origins and evolutionary pathways of fruits offers valuable insights into plant diversity, ecological relationships, and the development of agricultural systems. Arabidopsis thaliana (Brassicaceae, core eudicot) and Eschscholzia californica (California poppy, Papaveraceae, sister group to core eudicots) both develop dry dehiscent fruits, with two valves separating explosively from the replum-like region upon maturation. This led to the hypothesis, that homologous gene regulatory networks direct fruit development and dehiscence in both species.

RESULTS: Transcriptome analysis of separately collected valve and replum-like tissue of California poppy yielded the SEEDSTICK (STK) ortholog as candidate for dehiscence zone regulation. Expression analysis of STK orthologs from dry dehiscing fruits of legumes (Vicia faba, Glycine max and Pisum sativum) shows their involvement in fruit development. Functional analysis using Virus-Induced Gene Silencing (VIGS) showed premature rupture of fruits and clarified the roles of EscaSTK: an evolutionary conserved role in seed filling and seed coat development, and a novel role in restricting cell divisions in the inner cell layer of the valve.

CONCLUSION: Our analysis shows that the gene regulatory network described in Arabidopsis is significantly different in other dicots, even if their fruits form a dehiscence zone at the valve margins. The ortholog of STK, known to be involved in ovule development and seed abscission in Arabidopsis, was recruited to a network regulating fruit wall proliferation in California poppy. There, EscaSTK allows fruit maturation without premature capsule rupture, highlighting the importance of proper endocarp development for successful seed dispersal.

PMID:39731146 | DOI:10.1186/s13227-024-00236-0

BMC Genomics. 2024 Dec 27;25(1):1251. doi: 10.1186/s12864-024-10960-5.

ABSTRACT

Low Complexity Regions (LCRs) are segments of proteins with a low diversity of amino acid composition. These regions play important roles in proteins. However, annotations describing these functions are dispersed across databases and scientific literature. LCRAnnotationsDB aims to consolidate knowledge about LCRs and store relevant annotations in a single place. To unify redundant annotations, we assigned them categories based on similarity in function, protein structure, and biological process. Categories are organized hierarchically by linking them to Gene Ontology terms. The LCRAnnotationsDB database can be accessed at https://lcrannotdb.lcr-lab.org/ .

PMID:39731018 | DOI:10.1186/s12864-024-10960-5

Mol Med. 2024 Dec 28;30(1):280. doi: 10.1186/s10020-024-01052-x.

ABSTRACT

Vertebrates differ over 100,000-fold in responses to pro-inflammatory agonists such as bacterial lipopolysaccharide (LPS), complicating use of animal models to study human sepsis or inflammatory disorders. We compared transcriptomes of resting and LPS-exposed blood from six LPS-sensitive species (rabbit, pig, sheep, cow, chimpanzee, human) and four LPS-resilient species (mice, rats, baboon, rhesus), as well as plasma proteomes and lipidomes. Unexpectedly, at baseline, sensitive species already had enhanced expression of LPS-responsive genes relative to resilient species. After LPS stimulation, maximally different genes in resilient species included genes that detoxify LPS, diminish bacterial growth, discriminate sepsis from SIRS, and play roles in autophagy and apoptosis. The findings reveal the molecular landscape of species differences in inflammation. This may inform better selection of species for pre-clinical models and could lead to new therapeutic strategies that mimic mechanisms in inflammation-resilient species to limit inflammation without causing immunosuppression.

PMID:39730996 | DOI:10.1186/s10020-024-01052-x

Sci Rep. 2024 Dec 28;14(1):30885. doi: 10.1038/s41598-024-81866-1.

ABSTRACT

Personalized medicine aims to tailor medical treatments to individual patients, and predicting drug responses from molecular profiles using machine learning is crucial for this goal. However, the high dimensionality of the molecular profiles compared to the limited number of samples presents significant challenges. Knowledge-based feature selection methods are particularly suitable for drug response prediction, as they leverage biological insights to reduce dimensionality and improve model interpretability. This study presents the first comparative evaluation of nine different knowledge-based and data-driven feature reduction methods on cell line and tumor data. Our analysis employs six distinct machine learning models, with a total of more than 6,000 runs to ensure a robust evaluation. Our findings indicate that transcription factor activities outperform other methods in predicting drug responses, effectively distinguishing between sensitive and resistant tumors for seven of the 20 drugs evaluated.

PMID:39730699 | DOI:10.1038/s41598-024-81866-1

Nat Commun. 2024 Dec 27;15(1):10726. doi: 10.1038/s41467-024-55388-3.

ABSTRACT

Immune checkpoint blockade (ICB) has become a standard anti-cancer treatment, offering durable clinical benefits. However, the limited response rate of ICB necessitates biomarkers to predict and modulate the efficacy of the therapy. The gut microbiome's influence on ICB efficacy is of particular interest due to its modifiability through various interventions. However, gut microbiome biomarkers for ICB response have been inconsistent across different studies. Here, we identify TANB77, an uncultured and distinct bacterial clade, as the most consistent responder-enriched taxon through meta-analysis of ten independent ICB recipient cohorts. Traditional taxonomy fails to distinguish TANB77 from unrelated taxa, leading to its oversight. Mice with higher gut TANB77 abundance, either naturally or through transplantation, show improved response to anti-PD-1 therapy. Additionally, mice injected with TANB77-derived pilin-like protein exhibit improved anti-PD-1 therapy response, providing in vivo evidence for the beneficial role of the pilin-like protein. These findings suggest that pilins from the TANB77 order may enhance responses to ICB therapy across diverse cohorts of cancer patients.

PMID:39730328 | DOI:10.1038/s41467-024-55388-3

Transl Psychiatry. 2024 Dec 27;14(1):506. doi: 10.1038/s41398-024-03216-z.

ABSTRACT

The high comorbidity of major depressive disorder (MDD) with other diseases has been well-documented. However, the pairwise causal connections for MDD comorbid networks are poorly characterized. We performed Phenome-wide Mendelian randomization (MR) analyses to explore bidirectional causal associations between MDD (N = 807,553) and 877 common diseases from FinnGen datasets (N = 377,277). The inverse variance weighting method was the primary technique, and other methods (weighted median and MR-Egger) were used for sensitivity analyses. Our MR analyses showed that the genetic liability to MDD is causally associated with the risks of 324 disease phenotypes (average b: 0.339), including 46 psychiatric and behavioral disorders (average b: 0.618), 18 neurological diseases (average b: 0.348), 44 respiratory diseases (average b: 0.345), 40 digestive diseases (average b: 0.281), 18 circulatory diseases (average b: 0.237), 37 genitourinary diseases (average b: 0.271), 66 musculoskeletal and connective diseases (average b: 0.326), 22 endocrine diseases (average b: 0.302), and others. In a reverse analysis, a total of 51 genetic components predisposing to various diseases were causally associated with MDD risk (average b: 0.086), including 5 infectious diseases (average b: 0.056), 11 neurological diseases (average b: 0.106), 14 oncological diseases (average b: 0.108), and 5 psychiatric and behavioral disorders (average b: 0.114). Bidirectional causal associations were identified between MDD and 15 diseases. For most MR analyses, little evidence of heterogeneity and pleiotropy was detected. Our findings confirmed the extensive and significant causal role of genetic predisposition to MDD in contributing to human disease phenotypes, which were more pronounced than those seen in the reverse analysis of the causal influences of other diseases on MDD.

PMID:39730323 | DOI:10.1038/s41398-024-03216-z

Cell Rep Methods. 2024 Dec 20:100937. doi: 10.1016/j.crmeth.2024.100937. Online ahead of print.

ABSTRACT

Spatially resolved transcriptomics (ST) has revolutionized the field of biology by providing a powerful tool for analyzing gene expression in situ. However, current ST methods, particularly barcode-based methods, have limitations in reconstructing high-resolution images from barcodes sparsely distributed in slides. Here, we present SuperST, an algorithm that enables the reconstruction of dense matrices (higher-resolution and non-zero-inflated matrices) from low-resolution ST libraries. SuperST is based on deep image prior, which reconstructs spatial gene expression patterns as image matrices. Compared with previous methods, SuperST generated output images that more closely resembled immunofluorescence images for given gene expression maps. Furthermore, we demonstrated how one can combine images created by SuperST with computer vision algorithms. In this context, we proposed a method for extracting features from the images, which can aid in spatial clustering of genes. By providing a dense matrix for each gene in situ, SuperST can successfully address the resolution and zero-inflation issue.

PMID:39729996 | DOI:10.1016/j.crmeth.2024.100937

Mol Cell. 2024 Dec 19:S1097-2765(24)00993-6. doi: 10.1016/j.molcel.2024.11.038. Online ahead of print.

ABSTRACT

Changing environmental conditions necessitate rapid adaptation of cytoplasmic and nuclear volumes. We use the slime mold Dictyostelium discoideum, known for its ability to tolerate extreme changes in osmolarity, to assess which role nuclear pore complexes (NPCs) play in achieving nuclear volume adaptation and relieving mechanical stress. We capitalize on the unique properties of D. discoideum to quantify fluid flow across NPCs. D. discoideum has an elaborate NPC structure in situ. Its dilation state affects NPC permeability for nucleocytosolic flow. Based on mathematical concepts adapted from hydrodynamics, we conceptualize this phenomenon as porous flow across NPCs, which is distinct from canonically characterized modes of nucleocytoplasmic transport because of its dependence on pressure. Viral NPC blockage decreased nucleocytosolic flow. Our results may be relevant for any biological conditions that entail rapid nuclear size adaptation, including metastasizing cancer cells, migrating cells, or differentiating tissues.

PMID:39729993 | DOI:10.1016/j.molcel.2024.11.038

Dev Cell. 2024 Dec 19:S1534-5807(24)00722-6. doi: 10.1016/j.devcel.2024.11.022. Online ahead of print.

ABSTRACT

Two distinct lineages, pluripotent epiblast (EPI) and primitive (extra-embryonic) endoderm (PrE), arise from common inner cell mass (ICM) progenitors in mammalian embryos. To study how these sister identities are forged, we leveraged mouse embryonic stem (ES) cells and extra-embryonic endoderm (XEN) stem cells-in vitro counterparts of the EPI and PrE. Bidirectional reprogramming between ES and XEN coupled with single-cell RNA and ATAC-seq analyses showed distinct rates, efficiencies, and trajectories of state conversions, identifying drivers and roadblocks of reciprocal conversions. While GATA4-mediated ES-to-iXEN conversion was rapid and nearly deterministic, OCT4-, KLF4-, and SOX2-induced XEN-to-induced pluripotent stem (iPS) reprogramming progressed with diminished efficiency and kinetics. A dominant PrE transcriptional program, safeguarded by GATA4, alongside elevated chromatin accessibility and reduced DNA methylation of the EPI underscored the differential plasticities of the two states. Mapping in vitro to embryo trajectories tracked reprogramming cells in either direction along EPI and PrE in vivo states, without transitioning through the ICM.

PMID:39729987 | DOI:10.1016/j.devcel.2024.11.022

Mol Oncol. 2024 Dec 27. doi: 10.1002/1878-0261.13762. Online ahead of print.

ABSTRACT

Hypoxia is known to induce reprogramming of glucose metabolism in cancer. However, the impact of hypoxia on global metabolism remains poorly understood. Here, using the systems approach, we evaluated the potential crosstalk between hypoxia and global metabolism using data from > 2000 breast tumors. Tumor samples were scored for hypoxia and 90 metabolic pathways, and these metrics were subjected to an analysis pipeline. Hypoxia showed a very strong association with metabolic aggression and an overall contextual relationship with metabolism. Out of three (M1, M2, and M3) metabolic types in breast cancer, M3 exhibited the strongest relationship with hypoxia; that is, high hypoxic tumors were also metabolically deregulated. Further, the overall correlation pattern between hypoxia and metabolic pathway scores was specific to each type, with M1 showing maximal sensitivity to hypoxia, followed by M2 and then M3. Experimental validation using metabolic inhibitors on cell lines with high or low hypoxia scores further confirmed the metabolic type-dependence of hypoxia. In addition, evaluation of the impact of hypoxia on cancer pathways other than metabolic ones revealed a potential role of hypoxia in immune evasive characteristic of M3 tumors. Overall, the results suggest a complex interplay between hypoxia and metabolism in the context of human breast tumors, with potential implications for both basic cancer biology and breast cancer therapy.

PMID:39729399 | DOI:10.1002/1878-0261.13762

Elife. 2024 Dec 27;13:RP97350. doi: 10.7554/eLife.97350.

ABSTRACT

As pathogens spread in a population of hosts, immunity is built up, and the pool of susceptible individuals are depleted. This generates selective pressure, to which many human RNA viruses, such as influenza virus or SARS-CoV-2, respond with rapid antigenic evolution and frequent emergence of immune evasive variants. However, the host's immune systems adapt, and older immune responses wane, such that escape variants only enjoy a growth advantage for a limited time. If variant growth dynamics and reshaping of host-immunity operate on comparable time scales, viral adaptation is determined by eco-evolutionary interactions that are not captured by models of rapid evolution in a fixed environment. Here, we use a Susceptible/Infected model to describe the interaction between an evolving viral population in a dynamic but immunologically diverse host population. We show that depending on strain cross-immunity, heterogeneity of the host population, and durability of immune responses, escape variants initially grow exponentially, but lose their growth advantage before reaching high frequencies. Their subsequent dynamics follows an anomalous random walk determined by future escape variants and results in variant trajectories that are unpredictable. This model can explain the apparent contradiction between the clearly adaptive nature of antigenic evolution and the quasi-neutral dynamics of high-frequency variants observed for influenza viruses.

PMID:39728926 | DOI:10.7554/eLife.97350

Toxins (Basel). 2024 Dec 2;16(12):519. doi: 10.3390/toxins16120519.

ABSTRACT

The intricate combination of organic and inorganic compounds found in snake venom includes proteins, peptides, lipids, carbohydrates, nucleotides, and metal ions. These components work together to immobilise and consume prey through processes such as paralysis and hypotension. Proteins, both enzymatic and non-enzymatic, form the primary components of the venom. Based on the effects they produce, venom can be classified as neurotoxic, hemotoxic, and cytotoxic. Studies have shown that, after envenomation, proteins in snake venom also contribute significantly to the induction of inflammatory responses which can either have systemic or localized consequences. This review delves into the mechanisms by which snake venom proteins trigger inflammatory responses, focusing on key families such as phospholipase A2, metalloproteinases, serine proteases, C-type lectins, cysteine-rich secretory proteins, and L-amino acid oxidase. In addition, the role of venom proteins in activating various inflammatory pathways, including the complement system, inflammasomes, and sterile inflammation are also summarized. The available therapeutic options are examined, with a focus on antivenom therapy and its side effects. In general, this review offers a comprehensive understanding of the inflammatory mechanisms that are triggered by snake venom proteins and the side effects of antivenom treatment. All these emphasize the need for effective strategies to mitigate these detrimental effects.

PMID:39728777 | DOI:10.3390/toxins16120519