Application of Graph Models to the Identification of Transcriptomic Oncometabolic Pathways in Human Hepatocellular Carcinoma.

Whole-tissue transcriptomic analyses have been helpful to characterize molecular subtypes of hepatocellular carcinoma (HCC). Metabolic subtypes of human HCC have been defined, yet whether these different metabolic classes are clinically relevant or derive in actionable cancer vulnerabilities is still an unanswered question. Publicly available gene sets or gene signatures have been used to infer functional changes through gene set enrichment methods. However, metabolism-related gene signatures are poorly co-expressed when applied to a biological context. Here, we apply a simple method to infer highly consistent signatures using graph-based statistics. Using the Cancer Genome Atlas Liver Hepatocellular cohort (LIHC), we describe the main metabolic clusters and their relationship with commonly used molecular classes, and with the presence of TP53 or CTNNB1 driver mutations. We find similar results in our validation cohort, the LIRI-JP cohort. We describe how previously described metabolic subtypes could not have therapeutic relevance due to their overall downregulation when compared to non-tumoral liver, and identify N-glycan, mevalonate and sphingolipid biosynthetic pathways as the hallmark of the oncogenic shift of the use of acetyl-coenzyme A in HCC metabolism. Finally, using DepMap data, we demonstrate metabolic vulnerabilities in HCC cell lines.

Opportunities for nanomaterials in enzyme therapy.

In recent years, enzyme therapy strategies have rapidly evolved to catalyze essential biochemical reactions with therapeutic potential. These approaches hold particular promise in addressing rare genetic disorders, cancer treatment, neurodegenerative conditions, wound healing, inflammation management, and infectious disease control, among others. There are several primary reasons for the utilization of enzymes as therapeutics: their substrate specificity, their biological compatibility, and their ability to generate a high number of product molecules per enzyme unit. These features have encouraged their application in enzyme replacement therapy where the enzyme serves as the therapeutic agent to rectify abnormal metabolic and physiological processes, enzyme prodrug therapy where the enzyme initiates a clinical effect by activating prodrugs, and enzyme dynamic or starving therapy where the enzyme acts upon host substrate molecules. Currently, there are >20 commercialized products based on therapeutic enzymes, but approval rates are considerably lower than other biologicals. This has stimulated nanobiotechnology in the last years to develop nanoparticle-based solutions that integrate therapeutic enzymes. This approach aims to enhance stability, prevent rapid clearance, reduce immunogenicity, and even enable spatio-temporal activation of the therapeutic catalyst. This comprehensive review delves into emerging trends in the application of therapeutic enzymes, with a particular emphasis on the synergistic opportunities presented by incorporating enzymes into nanomaterials. Such integration holds the promise of enhancing existing therapies or even paving the way for innovative nanotherapeutic approaches.

Surgical impact of bilateral transient occlusion of uterine and utero-ovarian arteries during laparoscopic myomectomy.

The objective of this article is to compare the amount of intraoperative blood loss during laparoscopic myomectomy when performing bilateral transient clamping of the uterine and utero-ovarian arteries versus no intervention. It´s a randomized controlled prospective study carried out in the Department of Obstetrics and Gynecology Ramón y Cajal University Hospital and HM Montepríncipe-Sanchinarro University Hospital, Madrid, Spain, in women with fibroid uterus undergoing laparoscopic myomectomy. Eighty women diagnosed with symptomatic fibroid uterus were randomly assigned to undergo laparoscopic myomectomy without additional intervention (Group A) or temporary clamping of bilateral uterine and utero-ovarian arteries prior to laparoscopic myomectomy (Group B). Estimated blood loss, operating time, length of hospital stay, and postoperative hemoglobin values were compared in both groups. The number of fibroids removed was similar in both groups (p = 0.77). Estimated blood loss was lower in the group of patients with prior occlusion of uterine arteries (p = 0.025) without increasing operating time (p = 0.17) nor length of stay (p = 0.17). No patient had either intra or postoperative complications. Only two patients (2.5%) required blood transfusion after surgery. We conclude that temporary clamping of bilateral uterine arteries prior to laparoscopic myomectomy is a safe intervention that reduces blood loss without increasing operative time.

Mitochondrial Variation of Bottlenose Dolphins (Tursiops truncatus) from the Canary Islands Suggests a Key Population for Conservation with High Connectivity within the North-East Atlantic Ocean.

In recent decades, worldwide cetacean species have been protected, but they are still threatened. The bottlenose dolphin (Tursiops truncatus) is a vulnerable keystone species and a useful bioindicator of the health and balance of marine ecosystems in oceans all over the world. The genetic structure of the species is shaped by their niche specialization (along with other factors), leading to the classification of two ecotypes: coastal and pelagic. In this study, the genetic diversity, population structure, and ecotypes of bottlenose dolphins from the Canary Islands were assessed through the analysis of 49 new samples from biopsies and from stranded animals using the 636 bp portion of the mitochondrial control region and 343 individuals from databases (n = 392). The results reveal high genetic diversity in Canarian bottlenose dolphins (Hd = 0.969 and π = 0.0165) and the apparent lack of population genetic structure within this archipelago. High genetic structure (Fst, Φst) was found between the Canary Islands and coastal populations, while little to no structure was found with the pelagic populations. These results suggest that Canarian bottlenose dolphins are part of pelagic ecotype populations in the North Atlantic. The studied Special Areas of Conservation in the Canary Islands may correspond to a hotspot of genetic diversity of the species and could be a strategic area for the conservation of the oceanic ecotype of bottlenose dolphins.

Biophysical evaluation of antiparallel triplexes for biosensing and biomedical applications.

Polypyrimidine sequences can be targeted by antiparallel clamps forming triplex structures either for biosensing or therapeutic purposes. Despite its successful implementation, their biophysical properties remain to be elusive. In this work, PAGE, circular dichroism and multivariate analysis were used to evaluate the properties of PPRHs directed to SARS-CoV-2 genome. Several PPRHs designed to target various polypyrimidine sites within the viral genome were synthesized. These PPRHs displayed varying binding affinities, influenced by factors such as the length of the PPRH and its GC content. The number and position of pyrimidine interruptions relative to the 4 T loop of the PPRH was found a critical factor, affecting the binding affinity with the corresponding target. Moreover, these factors also showed to affect in the intramolecular and intermolecular equilibria of PPRHs alone and when hybridized to their corresponding targets, highlighting the polymorphic nature of these systems. Finally, the functionality of the PPRHs was evaluated in a thermal lateral flow sensing device showing a good correspondence between their biophysical properties and detection limits. These comprehensive studies contribute to the understanding of the critical factors involved in the design of PPRHs for effective targeting of biologically relevant genomes through the formation of triplex structures under neutral conditions.

Using underwater currents as an occupational enrichment method to improve the stress status in rainbow trout.

This study investigated the effects of occupational enrichment, specifically underwater currents, on the stress status of rainbow trout (Oncorhynchus mykiss). A total of 540 fish were divided into three groups: control tanks without artificial currents (CO), tanks with randomly fired underwater currents (RFC), and tanks with continuous current throughout the day (CT). After 30 days, half of the fish in each group underwent a 5-day pre-slaughter fasting (5D), while the others were fed until the day before slaughter (0D). Fish in the RFC group exhibited lower levels of plasma cortisol and acetylcholinesterase enzyme activity in hypothalamus and optic tract than other groups, suggesting an improved stress status. RFC group also showed higher levels of non-esterified fatty acids (NEFA) in 5D fish and higher liver glycogen stores, suggesting improved energy reserves. In comparison, the CT group had higher LDH levels, possibly due to their increased swimming activity. The CO group had significantly lower NEFA levels at 5D compared to the RFC group, suggesting lower energy reserves. The RFC fish had darker and yellow-reddish skin and liver color, suggesting an improved stress status and lower lipid reserves, respectively. Overall, although a significant stress response was not observed in fasted individuals, possibly due to the relatively short fasting period, the study suggests that providing occupational enrichment using randomly fired underwater currents for 1 month helped to improve stress status in rainbow trout, indicating that occupational enrichment during the grow-out phase can positively impact the welfare of rainbow trout during routine handling procedures.

Environmental enrichment improves growth and fillet quality in rainbow trout.

BACKGROUND: Some environmental enrichment methods, such as occupational enrichment (OE), can improve fish growth, but little is known about its effects on fillet quality. In this study, we evaluated the effects of OE using underwater currents on different aspects of fillet quality and muscle metabolism in rainbow trout (Oncorhynchus mykiss), before and after a handling procedure (fasting). The trout were placed in groups of 30 in separate tanks in three treatments for 30 days: no artificial currents (CON), randomly fired underwater currents (RFC), and continuous underwater currents (CUC). Additionally, half of the individuals in each treatment were fasted (5 days, 45.2 °C days). RESULTS: Slaughter weight, condition factor, and relative growth were lower in CON fish, indicating a positive effect of OE on growth. Rigor mortis, muscle pH, and muscle glycogen levels were similar among treatments, indicating no effect of OE on classical measures of fillet quality. However, significant differences were found regarding fillet colour and muscle enzymes. The fillets of RFC fish were more salmon-pink in colour, which is favoured by consumers. Also, activity levels of pyruvate kinase and glycogen phosphorylase in muscle were significantly higher in CUC fish, probably due to increased energy demands, as pumps were on continually in that treatment. CONCLUSION: Overall, RFC fish seemed to have received enough stimulation to improve growth while not being excessive in terms of exhausting the animals (avoiding negative effects on muscle metabolism), whereas OE may have provided a hormetic effect, allowing fish to better adjust to fasting. © 2023 Society of Chemical Industry.

Suitability of machine learning for atrophy and fibrosis development in neovascular age-related macular degeneration.

PURPOSE: To assess the suitability of machine learning (ML) techniques in predicting the development of fibrosis and atrophy in patients with neovascular age-related macular degeneration (nAMD), receiving anti-VEGF treatment over a 36-month period. METHODS: An extensive analysis was conducted on the use of ML to predict fibrosis and atrophy development on nAMD patients at 36 months from start of anti-VEGF treatment, using only data from the first 12 months. We use data collected according to real-world practice, which includes clinical and genetic factors. RESULTS: The ML analysis consistently identified ETDRS as a relevant factor for predicting the development of atrophy and fibrosis, confirming previous statistical analyses. Also, it was shown that genetic variables did not demonstrate statistical relevance in the prediction. Despite the complexity of predicting macular degeneration, our model was able to obtain a balance accuracy of 63% and an AUC of 0.72 when predicting the development of atrophy or fibrosis at 36 months. CONCLUSION: This study demonstrates the potential of ML techniques in predicting the development of fibrosis and atrophy in nAMD patients receiving long-term anti-VEGF treatment. The findings highlight the importance of clinical factors, particularly ETDRS (early treatment diabetic retinopathy study) visual acuity test, in predicting these outcomes. The lessons learned from this research can guide future ML-based prediction tasks in the field of ophthalmology and contribute to the design of data collection processes.

GeNNius: an ultrafast drug-target interaction inference method based on graph neural networks.

MOTIVATION: Drug-target interaction (DTI) prediction is a relevant but challenging task in the drug repurposing field. In-silico approaches have drawn particular attention as they can reduce associated costs and time commitment of traditional methodologies. Yet, current state-of-the-art methods present several limitations: existing DTI prediction approaches are computationally expensive, thereby hindering the ability to use large networks and exploit available datasets and, the generalization to unseen datasets of DTI prediction methods remains unexplored, which could potentially improve the development processes of DTI inferring approaches in terms of accuracy and robustness. RESULTS: In this work, we introduce GeNNius (Graph Embedding Neural Network Interaction Uncovering System), a Graph Neural Network (GNN)-based method that outperforms state-of-the-art models in terms of both accuracy and time efficiency across a variety of datasets. We also demonstrated its prediction power to uncover new interactions by evaluating not previously known DTIs for each dataset. We further assessed the generalization capability of GeNNius by training and testing it on different datasets, showing that this framework can potentially improve the DTI prediction task by training on large datasets and testing on smaller ones. Finally, we investigated qualitatively the embeddings generated by GeNNius, revealing that the GNN encoder maintains biological information after the graph convolutions while diffusing this information through nodes, eventually distinguishing protein families in the node embedding space. AVAILABILITY AND IMPLEMENTATION: GeNNius code is available at https://github.com/ubioinformat/GeNNius.

Optimization of iron oxide nanoparticles for MRI-guided magnetic hyperthermia tumor therapy: reassessing the role of shape in their magnetocaloric effect.

Superparamagnetic iron oxide nanoparticles have hogged the limelight in different fields of nanotechnology. Surprisingly, notwithstanding the prominent role played as agents in magnetic hyperthermia treatments, the effects of nanoparticle size and shape on the magnetic hyperthermia performance have not been entirely elucidated yet. Here, spherical or cubical magnetic nanoparticles synthesized by a thermal decomposition method with the same magnetic and hyperthermia properties are evaluated. Interestingly, spherical nanoparticles displayed significantly higher magnetic relaxivity than cubic nanoparticles; however, comparable differences were not observed in specific absorption rate (SAR), pointing out the need for additional research to better understand the connection between these two parameters. Additionally, the as-synthetized spherical nanoparticles showed negligible cytotoxicity and, therefore, were tested in vivo in tumor-bearing mice. Following intratumoral administration of these spherical nanoparticles and a single exposure to alternating magnetic fields (AMF) closely mimicking clinical conditions, a significant delay in tumor growth was observed. Although further in vivo experiments are warranted to optimize the magnetic hyperthermia conditions, our findings support the great potential of these nanoparticles as magnetic hyperthermia mediators for tumor therapy.

A Simple and Versatile Strategy for Oriented Immobilization of His-Tagged Proteins on Magnetic Nanoparticles.

Oriented and covalent immobilization of proteins on magnetic nanoparticles (MNPs) is particularly challenging as it requires both the functionality of the protein and the colloidal stability of the MNPs to be preserved. Here, we describe a simple, straightforward, and efficient strategy for MNP functionalization with proteins using metal affinity binding. Our method involves a single-step process where MNPs are functionalized using a preformed, ready-to-use nitrilotriacetic acid-divalent metal cation (NTA-M2+) complex and polyethylene glycol (PEG) molecules. As a proof-of-concept, we demonstrate the oriented immobilization of a recombinant cadherin fragment engineered with a hexahistidine tag (6His-tag) onto the MNPs. Our developed methodology is simple and direct, enabling the oriented bioconjugation of His-tagged cadherins to MNPs while preserving protein functionality and the colloidal stability of the MNPs, and could be extended to other proteins expressing a polyhistidine tag. When compared to the traditional method where NTA is first conjugated to the MNPs and afterward free metal ions are added to form the complex, this novel strategy results in a higher functionalization efficiency while avoiding MNP aggregation. Additionally, our method allows for covalent bonding of the cadherin fragments to the MNP surface while preserving functionality, making it highly versatile. Finally, our strategy not only ensures the correct orientation of the protein fragments on the MNPs but also allows for the precise control of their density. This feature enables the selective targeting of E-cadherin-expressing cells only when MNPs are decorated with a high density of cadherin fragments.

Artificial intelligence in theranostics of gastric cancer, a review.

Gastric cancer (GC) is one of the commonest cancers with high morbidity and mortality in the world. How to realize precise diagnosis and therapy of GC owns great clinical requirement. In recent years, artificial intelligence (AI) has been actively explored to apply to early diagnosis and treatment and prognosis of gastric carcinoma. Herein, we review recent advance of AI in early screening, diagnosis, therapy and prognosis of stomach carcinoma. Especially AI combined with breath screening early GC system improved 97.4 % of early GC diagnosis ratio, AI model on stomach cancer diagnosis system of saliva biomarkers obtained an overall accuracy of 97.18 %, specificity of 97.44 %, and sensitivity of 96.88 %. We also discuss concept, issues, approaches and challenges of AI applied in stomach cancer. This review provides a comprehensive view and roadmap for readers working in this field, with the aim of pushing application of AI in theranostics of stomach cancer to increase the early discovery ratio and curative ratio of GC patients.

Assessment of the presence of UV filters and UV stabilizers in stranded dolphin blubber.

The presence of ultraviolet filters (UVFs) and stabilizers (UVSs) was evaluated for the first time in the common bottlenose dolphin (Tursiops truncatus). UVFs and UVSs are compounds of growing concern because their effects on the environment are not completely known. UVFs and UVSs are added to personal care products (PCPs), such as cosmetics and products related to sun care and once released to the aquatic ecosystem, marine organisms can bioaccumulate these substances. This work aimed to determine the presence of 12 UVFs and UVSs in cetacean blubber samples to assess the pollution to which these animals of the highest trophic chain levels are exposed due to human activity. Analytical determinations were carried out using a method based on microwave-assisted extraction combined with ultrahigh-performance liquid chromatography and tandem mass spectrometry detection. The developed method was successfully applied to determine the target compounds in the blubber tissues of five necropsied common bottlenose dolphins. Three of the 12 studied compounds, namely 2-ethylhexyl 2-cyano-3,3-diphenylprop-2-enoate (octocrilene, OC), 2-hydroxy-4-methoxybenzophenone (benzophenone 3, BP3) and 3-methylbutyl (E)-3-(4methoxyphenyl) prop-2-enoate (IMC), were detected in several samples. Of the identified compounds, OC was present in all the samples and at the highest concentration within the range from 52.61 ± 18.59 to 108.0 ± 11.32 ng·g-1.

Remote Activation of Enzyme Nanohybrids for Cancer Prodrug Therapy Controlled by Magnetic Heating.

Herein, we have developed nanohybrids (nHs) to remotely activate a therapeutic enzyme for its use in Directed Enzyme Prodrug Therapy (DEPT). The coencapsulation of magnetic nanoparticles (MNPs) with horseradish peroxidase (HRP) using biomimetic silica as an entrapment matrix was optimized to obtain nanosized hybrids (∼150 nm) for remote activation of the therapeutic enzyme. HRP converts indole-3-acetic acid (3IAA) into peroxylated radicals, whereas MNPs respond to alternating magnetic fields (AMFs) becoming local hotspots. The AMF application triggered an increase in the bioconversion rate of HRP matching the activity displayed at the optimal temperature of the nHs (Topt = 50 °C) without altering the temperature of the reaction media. This showed that enzyme nanoactuation is possible with MNPs even if they are not covalently bound. After an extensive physicochemical/magnetic characterization, the spatial location of each component of the nH was deciphered, and an insulating role of the silica matrix was suggested as critical for introducing remote control over HRP. In vitro assays, using a human pancreatic cancer cell line (MIA PaCa-2), showed that only upon exposure to AMF and in the presence of the prodrug, the enzyme-loaded nHs triggered cell death. Moreover, in vivo experiments showed higher reductions in the tumor volume growth in those animals treated with nHs in the presence of 3IAA when exposed to AMF. Thus, this work demonstrates the feasibility of developing a spatiotemporally controlled DEPT strategy to overcome unwanted off-target effects.

Corrigendum: Advances on self-regulation models: A new research agenda through the SR vs ER behavior theory in different psychology contexts.

[This corrects the article DOI: 10.3389/fpsyg.2022.861493.].

Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer.

Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resistance to available therapies, such as abiraterone (Abi). A better understanding of the underlying molecular mechanisms is needed to identify effective targets to overcome resistance. Given the complexity of the transcriptional dynamics in cells, differential gene expression analysis of bulk transcriptomics data cannot provide sufficient detailed insights into resistance mechanisms. Incorporating network structures could overcome this limitation to provide a global and functional perspective of Abi resistance in mCRPC. Here, we developed TraRe, a computational method using sparse Bayesian models to examine phenotypically driven transcriptional mechanistic differences at three distinct levels: transcriptional networks, specific regulons, and individual transcription factors (TF). TraRe was applied to transcriptomic data from 46 patients with mCRPC with Abi-response clinical data and uncovered abrogated immune response transcriptional modules that showed strong differential regulation in Abi-responsive compared with Abi-resistant patients. These modules were replicated in an independent mCRPC study. Furthermore, key rewiring predictions and their associated TFs were experimentally validated in two prostate cancer cell lines with different Abi-resistance features. Among them, ELK3, MXD1, and MYB played a differential role in cell survival in Abi-sensitive and Abi-resistant cells. Moreover, ELK3 regulated cell migration capacity, which could have a direct impact on mCRPC. Collectively, these findings shed light on the underlying transcriptional mechanisms driving Abi response, demonstrating that TraRe is a promising tool for generating novel hypotheses based on identified transcriptional network disruptions. SIGNIFICANCE: The computational method TraRe built on Bayesian machine learning models for investigating transcriptional network structures shows that disruption of ELK3, MXD1, and MYB signaling cascades impacts abiraterone resistance in prostate cancer.

Subcellular localization and therapeutic efficacy of polymeric micellar nanoparticles encapsulating bedaquiline for tuberculosis treatment in zebrafish.

The combination drug regimens that have long been used to treat tuberculosis (TB), caused by Mycobacterium tuberculosis, are fraught with problems such as frequent administration, long duration of treatment, and harsh adverse effects, leading to the emergence of multidrug resistance. Moreover, there is no effective preventive vaccine against TB infection. In this context, nanoparticles (NPs) have emerged as a potential alternative method for drug delivery. Encapsulating antibiotics in biodegradable NPs has been shown to provide effective therapy and reduced toxicity against M. tuberculosis in different mammalian models, when compared to conventional free drug administration. Here, we evaluate the localization, therapeutic efficacy and toxic effects of polymeric micellar NPs encapsulating a promising but highly hydrophobic and toxic antitubercular drug bedaquiline (BQ) in zebrafish embryos infected with Mycobacterium marinum. Our study shows that the NP formulation of BQ improves survival and reduces bacterial burden in the infected embryos after treatment when compared to its free form. The intravenously injected BQ NPs have short circulation times due to their rapid and efficient uptake into the endothelial cells, as observed by correlative light and electron microscopy (CLEM).