Search Results (6,854)

This work describes the morphological changes during embryonic development and pre-hatching organ development of Octopus hubbsorum, a species with a paralarval phase in its life cycle. The morphogenesis of O. hubbsorum begins simultaneously with the first reversion, a typical characteristic of octopuses, along with the development of the embryonic shape and structure. However, this species hatches with only three well-developed suckers. Organogenesis starts after the first embryonic reversion, with the development of the eyes, optic lobes, digestive gland, arms, and mantle. The branchial and central hearts show optimal development before the second reversion. The ink sac develops in the late stages (after the second reversion), while the stomach and crop are evident only after hatching and continue to develop until the first feeding. Newly hatched organisms show a complete development of the nervous, respiratory, circulatory, and integumentary systems. During the paralarval phase, O. hubbsorum undergoes major morphological and physiological changes until it reaches the subadult phase and develops the reproductive organs. This study highlights important organogenic differences compared to species with planktonic and benthic hatchlings. Further studies are needed in species with different life strategies to expand our knowledge of the developmental biology of cephalopods. Full article

Amylin and amyloid β belong to the same protein family and activate the same receptors. Amyloid β levels are elevated in Alzheimer’s disease. Recent studies have demonstrated that amylin-based peptides can reduce the symptoms of Alzheimer’s disease in animal models. Replica exchange molecular dynamics simulation machine learning, as well as other computational analyses, were applied to improve the understanding of the amino acid residues in these amylin-based peptides. Comparisons were made between amylin, amylin-based peptides, and amyloid β. These studies converged on amylin residues 10Q, 28S, 29S, 30T, 31N, 32V, 33G, 34S, and 35N (residues 10 and 28–35) being ranked highest, meaning that they were the most likely to be involved in activating the same targets as amyloid β. Surprisingly, the amyloid β signaling domain most closely matched amylin residues 29–35 in the simulated structures. These findings suggest important residues that are structurally similar between amylin and amyloid β and are thus implicated in the activation of the amylin receptor. Full article

The importance of redox systems as fundamental elements in biology is now widely recognized across diverse fields, from ecology to cellular biology. Their connection to metabolism is particularly significant, as it plays a critical role in energy regulation and distribution within organisms. Over recent decades, metabolism has emerged as a relevant focus in studies of biological regulation, especially following its recognition as a hallmark of cancer. This shift has broadened cancer research beyond strictly genetic perspectives. The interaction between metabolism and redox systems in carcinogenesis involves the regulation of essential metabolic pathways, such as glycolysis and the Krebs cycle, as well as the involvement of redox-active components like specific amino acids and cofactors. The feedback mechanisms linking redox systems and metabolism in cancer highlight the development of redox patterns that enhance the flexibility and adaptability of tumor processes, influencing larger-scale biological phenomena such as circadian rhythms and epigenetics. Full article

Due to advances in big data technology, deep learning, and knowledge engineering, biological sequence visualization has been extensively explored. In the post-genome era, biological sequence visualization enables the visual representation of both structured and unstructured biological sequence data. However, a universal visualization method for all types of sequences has not been reported. Biological sequence data are rapidly expanding exponentially and the acquisition, extraction, fusion, and inference of knowledge from biological sequences are critical supporting technologies for visualization research. These areas are important and require in-depth exploration. This paper elaborates on a comprehensive overview of visualization methods for DNA sequences from four different perspectives—two-dimensional, three-dimensional, four-dimensional, and dynamic visualization approaches—and discusses the strengths and limitations of each method in detail. Furthermore, this paper proposes two potential future research directions for biological sequence visualization in response to the challenges of inefficient graphical feature extraction and knowledge association network generation in existing methods. The first direction is the construction of knowledge graphs for biological sequence big data, and the second direction is the cross-modal visualization of biological sequences using machine learning methods. This review is anticipated to provide valuable insights and contributions to computational biology, bioinformatics, genomic computing, genetic breeding, evolutionary analysis, and other related disciplines in the fields of biology, medicine, chemistry, statistics, and computing. It has an important reference value in biological sequence recommendation systems and knowledge question answering systems. Full article

Cell surface receptors are pivotal to cancer cell transformation, disease progression, metastasis, early detection, targeted therapy, drug responses, and clinical outcomes. Since they coordinate complex signaling communication networks in the tumor microenvironment, mapping the physical interaction partners of cell surface receptors in vivo is vital for understanding their roles, functional states, and suitability as therapeutic targets. Yet traditional methods like immunoprecipitation and affinity purification–mass spectrometry often fail to detect key but weak or transient receptor–protein interactions. Proximity labeling, a cutting-edge proteomics technology, addresses these technical challenges by enabling precise mapping of protein neighborhoods around a receptor target on the cell surface of cancer cells. This technique has been successfully applied in vitro and in vivo for proteomic mapping across various model systems. This review explores the fundamental principles, technologies, advantages, limitations, and applications of proximity labeling in cancer biology, focusing on mapping receptor microenvironments. By advancing mechanistic insights into cancer cell receptor signaling mechanisms, proximity labeling is poised to transform cancer research, improve targeted therapies, and illuminate avenues to overcome drug resistance. Full article

The rising demand for sustainable materials has led to a significant focus on developing resources from renewable systems, particularly through the integration of biological processes. Bacterial cellulose (BC) has emerged as a highly promising biomaterial, gaining attention across multiple industries, such as food, pharmaceuticals, materials science, and textiles, due to its renewable, biodegradable, and eco-friendly characteristics. Within the fashion industry, bacterial cellulose (BC) biofabrication presents a groundbreaking method for producing sustainable textiles and vegan leather. This systematic review emphasizes BC’s pivotal role in advancing sustainable materials, addressing challenges like low yields, strain instability, and high production costs, and exploring innovative biofabrication techniques to overcome these barriers. Current advancements aim to enhance the thickness, uniformity, and mechanical properties of BC layers by optimizing the environmental and nutritional conditions during Komagataeibacter cultivation and leveraging coculturing methods. Furthermore, recent innovations in synthetic biology and genetic engineering have opened new avenues for improving BC biosynthesis, making it a viable solution for the sustainable fashion industry. This review explores three core topics: (1) bacterial cellulose and its applications, (2) the biofabrication of BC for vegan leather, and (3) emerging innovations and patents utilizing bacterial cellulose as a sustainable industrial biomaterial. Full article

Mitophagy, an essential process within cellular autophagy, has a critical role in regulating key cellular functions such as reproduction, metabolism, and apoptosis. Its involvement in tumor development is complex and influenced by the cellular environment. Here, we conduct a comprehensive analysis of a mitophagy-related gene signature, composed of PRKN, PINK1, MAP1LC3A, SRC, BNIP3L, BECN1, and OPTN, across various cancer types, revealing significant differential expression patterns associated with molecular subtypes, stages, and patient outcomes. Pathway analysis revealed a complex interplay between the expression of the signature and potential effects on the activity of various cancer-related pathways in pan-cancer. Immune infiltration analysis linked the mitophagy signature with certain immune cell types, particularly OPTN with immune infiltration in melanoma. Methylation patterns correlated with gene expression and immune infiltration. Mutation analysis also showed frequent alterations in PRKN (34%), OPTN (21%), PINK1 (28%), and SRC (15%), with implications for the tumor microenvironment. We also found various correlations between the expression of the mitophagy-related genes and sensitivity in different drugs, suggesting that targeting this signature could improve therapy efficacy. Overall, our findings underscore the importance of mitophagy in cancer biology and drug resistance, as well as its potential for informing treatment strategies. Full article

Knowing which residues of a protein are important for its function is of paramount importance for understanding the molecular basis of this function and devising ways of modifying it for medical or biotechnological applications. Due to the difficulty in detecting these residues experimentally, prediction methods are essential to cope with the sequence deluge that is filling databases with uncharacterized protein sequences. Deep learning approaches are especially well suited for this task due to the large amounts of protein sequences for training them, the trivial codification of this sequence data to feed into these systems, and the intrinsic sequential nature of the data that makes them suitable for language models. As a consequence, deep learning-based approaches are being applied to the prediction of different types of functional sites and regions in proteins. This review aims to give an overview of the current landscape of methodologies so that interested users can have an idea of which kind of approaches are available for their proteins of interest. We also try to give an idea of how these systems work, as well as explain their limitations and high dependence on the training set so that users are aware of the quality of expected results. Full article

Ubiquitination is cells’ second most abundant posttranslational protein modification after phosphorylation. The ubiquitin–proteasome system (UPS) is critical in maintaining essential life processes such as cell cycle control, DNA damage repair, and apoptosis. Mutations in ubiquitination pathway genes are strongly linked to the development and spread of multiple cancers since several of the UPS family members possess oncogenic or tumor suppressor activities. This comprehensive review delves into understanding the ubiquitin code, shedding light on its role in cancer cell biology and immune evasion. Furthermore, we highlighted recent advances in the field for targeting the UPS pathway members for effective therapeutic intervention against human cancers. We also discussed the recent update on small-molecule inhibitors and PROTACs and their progress in preclinical and clinical trials. Full article

Abstract: The Australian lungfish, Neoceratodus forsteri, is one of the world’s oldest vertebrate lineages, with a slow life-history and threatened status, requiring immediate conservation efforts. The main threats to lungfish populations are degradation and availability of key macrophyte habitats, water regulation and flow modification. As this long-lived species (at least 77 years) has delayed maturity (mature at 10 years), field monitoring alone will not be enough to inform the challenge of ensuring sustainable populations. A stochastic metapopulation model was developed for the Burnett River (Southeast Queensland, Australia), an important habitat for the lungfish that is a highly regulated system with extensive water infrastructure. The model consists of three interacting populations, where the ecology and biology of the species were translated into an 80-year-class population projection matrix for each population, each with post-development streamflow, habitat and movement rules. The model highlights the longer-term interaction between dams and stream flows on habitat availability and subsequent recruitment. Through a pre-development streamflow, we quantify the impact of high regulation and development on the lungfish population in the Burnett River: a minor decline in the upstream population (e.g., 9.8% decline), a large decline in the middle population (64.2% decline), virtually no change in the downstream population (e.g., 1.2% decline) and a moderate decline in the overall metapopulation (e.g., 22.3% decline). The loss of spawning and feeding habitat remains the main reason for population decline, with implications that the loss will lead to greater pressure on remaining downstream habitat due to combined flow and dam effects and, in turn, to extended periods of recovery of spawning habitat. Our modeling approach substantially advances conservation management of this species, as it can be adapted to suit other populations in other river systems and used to test sensitivity to recovery actions. Full article

Objective: The clinical trial Effect of Modulated Auditory Stimulation on Interaural Auditory Perception (NCT0544189) aimed to determine whether an auditory intervention (AI)—“Bérard in 10”—can enhance the effect of standard therapies for people with anxiety and/or depression. Methods: Design: unblinded, randomized, controlled clinical trial. Location: Mejorada del Campo Health Centre, Madrid (Primary Care). Participants: A total of 233 patients selected by systematic sampling and meeting the following selection criteria: age of majority, absence of severe acute pathology or chronic decompensated pathology. They were evaluated with the Goldberg and Hamilton tests and classified into the Emotional Well-Being group (EWB, n = 86) or the Anxiety and/or Depression group (AD, n = 147). Just half of each group received an AI. Intervention: Listening to classical music processed through a frequency modulator (Earducator) to attenuate abnormal frequencies, 30 min per session, two sessions a day for 5 days. Main measurements: Hamilton Tests for Anxiety and Hamilton Test for Depression, at 3 and 6 months. Results: In the analysis by protocol, EWB with AI (n = 14) obtained lower scores in anxiety and depression at 3 and 6 months than EWB without AI (n = 36) (p < 0.05), the effects being large and moderate, respectively; AD with AI (n = 31) had lower scores on anxiety and depression at 3 months and anxiety at 6 months than AD without AI (n = 52) (p < 0.05), the effect being small. No damage reported. Conclusions: The AI “Bérard in 10” significantly prevents the onset of anxiety and depression and somewhat improves the effect of standard treatments in primary care. Full article

In neurons, the acquisition of a polarized morphology is achieved upon the outgrowth of a single axon from one of several neurites. Small extracellular vesicles (sEVs), such as exosomes, from diverse sources are known to promote neurite outgrowth and thus may have therapeutic potential. However, the effect of fibroblast-derived exosomes on axon elongation in neurons of the central nervous system under growth-permissive conditions remains unclear. Here, we show that fibroblast-derived sEVs promote axon outgrowth and a polarized neuronal morphology in mouse primary embryonic cortical neurons. Mechanistically, we demonstrate that the sEV-induced increase in axon outgrowth requires endogenous Wnts and core PCP components including Prickle, Vangl, Frizzled, and Dishevelled. We demonstrate that sEVs are internalized by neurons, colocalize with Wnt7b, and induce relocalization of Vangl2 to the distal axon during axon outgrowth. In contrast, sEVs derived from neurons or astrocytes do not promote axon outgrowth, while sEVs from activated astrocytes inhibit elongation. Thus, our data reveal that fibroblast-derived sEVs promote axon elongation through the Wnt-PCP pathway in a manner that is dependent on endogenous Wnts. Full article

This research utilized a mathematical model of fructose metabolism within the CellDesigner software package to investigate the effects of varying dietary fructose intake on fat metabolism. By simulating different meal patterns with varying levels of fructose, the model provided valuable insights into the relationship between fructose consumption and hepatic triglyceride accumulation. The results demonstrated a clear correlation between increased fructose intake and elevated hepatic triglycerides. Additionally, a local parametric sensitivity analysis identified glyceraldehyde-3-phosphate and pyruvate as key regulatory factors in this process. Importantly, the model accurately simulated changes in fructose concentration and its metabolites, validating its predictive capabilities. These findings underscore the importance of systems biology in elucidating the complex mechanisms underlying nutrition-related diseases. By integrating computational modeling with experimental data, researchers can gain a deeper understanding of how dietary factors influence metabolic pathways and contribute to health outcomes. Ultimately, systems biology holds the promise of enabling personalized nutrition recommendations tailored to individual needs and genetic predispositions. Full article

Background/Objectives: Bone marrow adipose tissue (BMAT) has been described as an important biomechanic and lipotoxic factor with negative impacts on skeletal and hematopoietic system regeneration. BMAT undergoes metabolic and cellular adaptations with age and disease, being a source of potential biomarkers. However, there is no evidence on the lipid profile and cellularity at different skeletal locations in osteoarthritis patients undergoing primary hip arthroplasty. Methods: Acetabular and femoral bone marrow (BM) and gluteofemoral subcutaneous adipose tissue (gfSAT) were obtained from matched patients undergoing hip replacement surgery. BM, BMAT, and gfSAT were explored at the levels of total lipids, fatty acids, and cells by using thin-layerand gas chromatography, ex vivo cellular assays, and flow cytometry. Results: BMAT content was significantly higher in femoral than in acetabular BM. Total lipid analyses revealed significantly lower triglyceride content in femoral than in acetabular BMAT and gfSAT. Frequencies of saturated palmitic, myristic, and stearic acids were higher in femoral than in acetabular BMAT and gfSAT. The content of CD45⁺CD34⁺ cells within femoral BMAT was higher than in acetabular BMAT or gfSAT. This was associated with a higher incidence of total clonogenic hematopoietic progenitors and late erythroid colonies CFU-E in femoral BMAT when compared to acetabular BMAT, similar to their BM counterparts. Conclusions: Collectively, our results indicate that the lipid profiles of hip bone and femoral BMAT impose significantly different microenvironments and distributions of cells with hematopoietic potential. These findings might bring forth new inputs for defining BMAT biology and setting novel directions in OA disease investigations. Full article

Nicotinamide mononucleotide (NMN) has emerged as a promising non-natural cofactor with significant potential to transform biocatalysis, synthetic biology, and therapeutic applications. By modulating NAD⁺ metabolism, NMN offers unique advantages in enzymatic reactions, metabolic engineering, and regenerative medicine. This review provides a comprehensive analysis of NMN’s biochemical properties, mechanisms of action, and diverse applications. Emphasis is placed on its role in addressing challenges in multi-enzyme cascades, biofuel production, and the synthesis of high-value chemicals. The paper also highlights critical research gaps, including the need for scalable NMN synthesis methods, improved integration into enzymatic systems, and comprehensive toxicity studies for therapeutic use. Emerging technologies such as AI-driven enzyme design and CRISPR-based genome engineering are discussed as transformative tools for optimizing NMN-dependent pathways. Furthermore, the synergistic potential of NMN with synthetic biology innovations, such as cell-free systems and dynamic regulatory networks, is explored, paving the way for precise and modular biotechnological solutions. Looking forward, NMN’s versatility as a cofactor positions it as a pivotal tool in advancing sustainable bioprocessing and precision medicine. Addressing current limitations through interdisciplinary approaches will enable NMN to redefine the boundaries of metabolic engineering and therapeutic innovation. This review serves as a roadmap for leveraging NMN’s potential across diverse scientific and industrial domains. Full article