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.

Identification and experimental validation of druggable epigenetic targets in hepatoblastoma.

BACKGROUND & AIMS: Hepatoblastoma (HB) is the most frequent childhood liver cancer. Patients with aggressive tumors have limited therapeutic options; therefore, a better understanding of HB pathogenesis is needed to improve treatment. HBs have a very low mutational burden; however, epigenetic alterations are increasingly recognized. We aimed to identify epigenetic regulators consistently dysregulated in HB and to evaluate the therapeutic efficacy of their targeting in clinically relevant models. METHODS: We performed a comprehensive transcriptomic analysis of 180 epigenetic genes. Data from fetal, pediatric, adult, peritumoral (n = 72) and tumoral (n = 91) tissues were integrated. Selected epigenetic drugs were tested in HB cells. The most relevant epigenetic target identified was validated in primary HB cells, HB organoids, a patient-derived xenograft model, and a genetic mouse model. Transcriptomic, proteomic and metabolomic mechanistic analyses were performed. RESULTS: Altered expression of genes regulating DNA methylation and histone modifications was consistently observed in association with molecular and clinical features of poor prognosis. The histone methyltransferase G9a was markedly upregulated in tumors with epigenetic and transcriptomic traits of increased malignancy. Pharmacological targeting of G9a significantly inhibited growth of HB cells, organoids and patient-derived xenografts. Development of HB induced by oncogenic forms of ß-catenin and YAP1 was ablated in mice with hepatocyte-specific deletion of G9a. We observed that HBs undergo significant transcriptional rewiring in genes involved in amino acid metabolism and ribosomal biogenesis. G9a inhibition counteracted these pro-tumorigenic adaptations. Mechanistically, G9a targeting potently repressed the expression of c-MYC and ATF4, master regulators of HB metabolic reprogramming. CONCLUSIONS: HBs display a profound dysregulation of the epigenetic machinery. Pharmacological targeting of key epigenetic effectors exposes metabolic vulnerabilities that can be leveraged to improve the treatment of these patients. IMPACT AND IMPLICATIONS: In spite of recent advances in the management of hepatoblastoma (HB), treatment resistance and drug toxicity are still major concerns. This systematic study reveals the remarkable dysregulation in the expression of epigenetic genes in HB tissues. Through pharmacological and genetic experimental approaches, we demonstrate that the histone-lysine-methyltransferase G9a is an excellent drug target in HB, which can also be harnessed to enhance the efficacy of chemotherapy. Furthermore, our study highlights the profound pro-tumorigenic metabolic rewiring of HB cells orchestrated by G9a in coordination with the c-MYC oncogene. From a broader perspective, our findings suggest that anti-G9a therapies may also be effective in other c-MYC-dependent tumors.

NMR-Based Mitochondria Metabolomic Profiling: A New Approach To Reveal Cancer-Associated Alterations.

Studying metabolism may assist in understanding the relationship between normal and dysfunctional mitochondrial activity and various diseases, such as neurodegenerative, cardiovascular, autoimmune, psychiatric, and cancer. Nuclear magnetic resonance-based metabolomics represents a powerful method to characterize the chemical content of complex samples and has been successfully applied to studying a range of conditions. However, an optimized methodology is lacking for analyzing isolated organelles, such as mitochondria. In this study, we report the development of a protocol to metabolically profile mitochondria from healthy, tumoral, and metastatic tissues. Encouragingly, this approach provided quantitative information about up to 45 metabolites in one comprehensive and robust analysis. Our results revealed significant differences between whole-cell and mitochondrial metabolites, which supports a more refined approach to metabolic analysis. We applied our optimized methodology to investigate aggressive and metastatic breast cancer in mouse tissues, discovering that lung mitochondria exhibit an altered metabolic fingerprint. Specific amino acids, organic acids, and lipids showed significant increases in levels when compared with mitochondria from healthy tissues. Our optimized methodology could promote a better understanding of the molecular mechanisms underlying breast cancer aggressiveness and mitochondrial-related diseases and support the optimization of new advanced therapies.

IgG antibody response to pneumococcal-conjugated vaccine (Prevenar®13) in children with immunodeficiency disorders.

Measurement of anti-pneumococcal capsular polysaccharides (anti-PnPs) IgG titers is an important tool in the immunologic assessment of patients with suspected immunodeficiency disorders (ID) to reduce the morbi-mortality and minimize severe infections. Retrospectively, we studied the relationship among anti-PnPs IgG response to 3 doses of Prevenar®13, levels of immune system components, leukocyte populations, and clinical data in children with ID. Serum samples were collected at least 4 weeks post vaccination. Subsequently, multi-serotype enzyme-linked immunosorbent assay (ELISA) was performed. Eighty-seven children (under 12 years) were enrolled. Primary immunodeficiency disorder (PID) was the most common disorder (45) followed by possible immunodeficiency disorder (POID) (19), secondary immunodeficiency disorder (SID) (15), and mixed immunodeficiency disorder (MID) (8). The median age was 3 (1.50-5.33) years, 65% of patients were male. Deficient production of anti-PnPs IgG (titer ≤ 50 mg/L) was detected in 47 patients (54%), especially in the MID group, all of them under immunosuppressive therapy. In PCV13 responders, the mean of leukocyte population levels was higher with statistically significance differences in CD4 + /CD8 + T lymphocytes (p = 0.372, p = 0.014) and CD56 + /CD16 + NK (p = 0.016). Patients with previous bone marrow transplantation were the worst PCV13 responders. Pneumococcal IgG antibody titers (post-vaccination) along with clinical and analytical markers represented.

Splicing Factor SLU7 Prevents Oxidative Stress-Mediated Hepatocyte Nuclear Factor 4α Degradation, Preserving Hepatic Differentiation and Protecting From Liver Damage.

BACKGROUND AND AIMS: Hepatocellular dedifferentiation is emerging as an important determinant in liver disease progression. Preservation of mature hepatocyte identity relies on a set of key genes, predominantly the transcription factor hepatocyte nuclear factor 4α (HNF4α) but also splicing factors like SLU7. How these factors interact and become dysregulated and the impact of their impairment in driving liver disease are not fully understood. APPROACH AND RESULTS: Expression of SLU7 and that of the adult and oncofetal isoforms of HNF4α, driven by its promoter 1 (P1) and P2, respectively, was studied in diseased human and mouse livers. Hepatic function and damage response were analyzed in wild-type and Slu7-haploinsufficient/heterozygous (Slu7+/- ) mice undergoing chronic (CCl4 ) and acute (acetaminophen) injury. SLU7 expression was restored in CCl4 -injured mice using SLU7-expressing adeno-associated viruses (AAV-SLU7). The hepatocellular SLU7 interactome was characterized by mass spectrometry. Reduced SLU7 expression in human and mouse diseased livers correlated with a switch in HNF4α P1 to P2 usage. This response was reproduced in Slu7+/- mice, which displayed increased sensitivity to chronic and acute liver injury, enhanced oxidative stress, and marked impairment of hepatic functions. AAV-SLU7 infection prevented liver injury and hepatocellular dedifferentiation. Mechanistically we demonstrate a unique role for SLU7 in the preservation of HNF4α1 protein stability through its capacity to protect the liver against oxidative stress. SLU7 is herein identified as a key component of the stress granule proteome, an essential part of the cell's antioxidant machinery. CONCLUSIONS: Our results place SLU7 at the highest level of hepatocellular identity control, identifying SLU7 as a link between stress-protective mechanisms and liver differentiation. These findings emphasize the importance of the preservation of hepatic functions in the protection from liver injury.

Characterization of anaphylaxis reveals different metabolic changes depending on severity and triggers.

BACKGROUND: Despite the increasing incidence of anaphylaxis, its underlying molecular mechanisms and biomarkers for appropriate diagnosis remain undetermined. The rapid onset and potentially fatal outcome in the absence of managed treatment prevent its study. Up today, there are still no known biomarkers that allow an unequivocal diagnosis. Therefore, the aim of this study was to explore metabolic changes in patients suffering anaphylactic reactions depending on the trigger (food and/or drug) and severity (moderate and severe) in a real-life set-up. METHODS: Eighteen episodes of anaphylaxis, one per patient, were analysed. Sera were collected during the acute phase (T1), the recovery phase (T2) and around 2-3 months after the anaphylactic reaction (T0: basal state). Reactions were classified following an exhaustive allergological evaluation for severity and trigger. Sera samples were analysed using untargeted metabolomics combining liquid chromatography coupled to mass spectrometry (LC-MS) and proton nuclear magnetic resonance spectroscopy (1 H-NMR). RESULTS: 'Food T1 vs T2' and 'moderate T1 vs T2' anaphylaxis comparisons showed clear metabolic patterns during the onset of an anaphylactic reaction, which differed from those induced by drugs, food + drug or severe anaphylaxis. Moreover, the model of food anaphylaxis was able to distinguish the well-characterized IgE (antibiotics) from non-IgE-mediated anaphylaxis (nonsteroidal anti-inflammatory drugs), suggesting a differential metabolic pathway associated with the mechanism of action. Metabolic differences between 'moderate vs severe' at the acute phase T1 and at basal state T0 were studied. Among the altered metabolites, glucose, lipids, cortisol, betaine and oleamide were observed altered. CONCLUSIONS: The results of this exploratory study provide the first evidence that different anaphylactic triggers or severity induce differential metabolic changes along time or at specific time-point, respectively. Besides, the basal status T0 might identify high-risk patients, thus opening new ways to understand, diagnose and treat anaphylaxis.

Mild Muscle Mitochondrial Fusion Distress Extends Drosophila Lifespan through an Early and Systemic Metabolome Reorganization.

In a global aging population, it is important to understand the factors affecting systemic aging and lifespan. Mitohormesis, an adaptive response caused by different insults affecting the mitochondrial network, triggers a response from the nuclear genome inducing several pathways that promote longevity and metabolic health. Understanding the role of mitochondrial function during the aging process could help biomarker identification and the development of novel strategies for healthy aging. Herein, we interfered the muscle expression of the Drosophila genes Marf and Opa1, two genes that encode for proteins promoting mitochondrial fusion, orthologues of human MFN2 and OPA1. Silencing of Marf and Opa1 in muscle increases lifespan, improves locomotor capacities in the long term, and maintains muscular integrity. A metabolomic analysis revealed that muscle down-regulation of Marf and Opa1 promotes a non-autonomous systemic metabolome reorganization, mainly affecting metabolites involved in the energetic homeostasis: carbohydrates, lipids and aminoacids. Interestingly, the differences are consistently more evident in younger flies, implying that there may exist an anticipative adaptation mediating the protective changes at the older age. We demonstrate that mild mitochondrial muscle disturbance plays an important role in Drosophila fitness and reveals metabolic connections between tissues. This study opens new avenues to explore the link of mitochondrial dynamics and inter-organ communication, as well as their relationship with muscle-related pathologies, or in which muscle aging is a risk factor for their appearance. Our results suggest that early intervention in muscle may prevent sarcopenia and promote healthy aging.

Design and Synthesis of Water-Soluble and Potent MMP-13 Inhibitors with Activity in Human Osteosarcoma Cells.

Osteoarthritis is a degenerative disease, often resulting in chronic joint pain and commonly affecting elderly people. Current treatments with anti-inflammatory drugs are palliative, making the discovery of new treatments necessary. The inhibition of matrix metalloproteinase MMP-13 is a validated strategy to prevent the progression of this common joint disorder. We recently described polybrominated benzotriazole derivatives with nanomolar inhibitory activity and a promising selectivity profile against this collagenase. In this work, we have extended the study in order to explore the influence of bromine atoms and the nature of the S1' heterocyclic interacting moiety on the solubility/selectivity balance of this type of compound. Drug target interactions have been assessed through a combination of molecular modeling studies and NMR experiments. Compound 9a has been identified as a water-soluble and highly potent inhibitor with activity in MG-63 human osteosarcoma cells.

Targeted Metabolomics Analyses Reveal Specific Metabolic Alterations in High-Grade Prostate Cancer Patients.

Prostate cancer (PCa) is a hormone-dependent tumor characterized by an extremely heterogeneous prognosis. Despite recent advances in partially uncovering some of the biological processes involved in its progression, there is still an urgent need for identifying more accurate and specific prognostic procedures to differentiate between disease stages. In this context, targeted approaches, focused on mapping dysregulated metabolic pathways, could play a critical role in identifying the mechanisms driving tumorigenesis and metastasis. In this study, a targeted analysis of the nuclear magnetic resonance-based metabolomic profile of PCa patients with different tumor grades, guided by transcriptomics profiles associated with their stages, was performed. Serum and urine samples were collected from 73 PCa patients. Samples were classified according to their Gleason score (GS) into low-GS (GS < 7) and high-GS PCa (GS ≥ 7) groups. A total of 36 metabolic pathways were found to be dysregulated in the comparison between different PCa grades. Particularly, the levels of glucose, glycine and 1-methlynicotinamide, metabolites involved in energy metabolism and nucleotide synthesis were significantly altered between both groups of patients. These results underscore the potential of targeted metabolomic profiling to characterize relevant metabolic changes involved in the progression of this neoplastic process.

Characterization of triple-negative breast cancer preclinical models provides functional evidence of metastatic progression.

Triple-negative breast cancer (TNBC), an aggressive, metastatic and recurrent breast cancer (BC) subtype, currently suffers from a lack of adequately described spontaneously metastatic preclinical models that faithfully reproduce the clinical scenario. We describe two preclinical spontaneously metastatic TNBC orthotopic murine models for the development of advanced therapeutics: an immunodeficient human MDA-MB-231-Luc model and an immunocompetent mouse 4T1 model. Furthermore, we provide a broad range of multifactorial analysis for both models that could provide relevant information for the development of new therapies and diagnostic tools. Our comparisons uncovered differential growth rates, stromal arrangements and metabolic profiles in primary tumors, and the presence of cancer-associated adipocyte infiltration in the MDA-MB-231-Luc model. Histopathological studies highlighted the more rapid metastatic spread to the lungs in the 4T1 model following a lymphatic route, while we observed both homogeneous (MDA-MB-231-Luc) and heterogeneous (4T1) metastatic spread to axillary lymph nodes. We encountered unique metabolomic signatures in each model, including crucial amino acids and cell membrane components. Hematological analysis demonstrated severe leukemoid and lymphoid reactions in the 4T1 model with the partial reestablishment of immune responses in the immunocompromised MDA-MB-231-Luc model. Additionally, we discovered ß-immunoglobulinemia and increased basal levels of G-CSF correlating with a metastatic switch, with G-CSF also promoting extramedullary hematopoiesis (both models) and causing hepatosplenomegaly (4T1 model). Overall, we believe that the characterization of these preclinical models will foster the development of advanced therapeutic strategies for TNBC treatment, especially for the treatment of patients presenting both, primary tumors and metastatic spread.

A translational approach to assess the metabolomic impact of stabilized gold nanoparticles by NMR spectroscopy.

Gold nanoparticles have high potential in the biomedical area, especially in disease diagnosis and treatment. The application of these nanoparticles requires the presence of stabilizers to avoid their agglomeration. Nowadays, there is a lack of reliable methods for characterising the effect of stabilised nanoparticles on biological systems. To this end, in this study, we apply an experimental approach based on nuclear magnetic resonance spectroscopy to study the effect of gold nanoparticles, stabilised with cerium oxide or chitosan, on a human cancer cell model. The results showed that both systems have a significant effect, even at non-toxic levels, on the cellular antioxidant system. However, although particles functionalised with chitosan exerted a strong effect on the aerobic respiration, nanoparticles stabilised with cerium oxide had a higher impact on the mechanisms associated with anaerobic energy production. Therefore, even though both systems contained similar gold nanoparticles, the presence of different stabilizers strongly influenced their mode of action and potential applications in biomedicine.

Bioinformatics tools for the analysis of NMR metabolomics studies focused on the identification of clinically relevant biomarkers.

Metabolomics, a systems biology approach focused on the global study of the metabolome, offers a tremendous potential in the analysis of clinical samples. Among other applications, metabolomics enables mapping of biochemical alterations involved in the pathogenesis of diseases, and offers the opportunity to noninvasively identify diagnostic, prognostic and predictive biomarkers that could translate into early therapeutic interventions. Particularly, metabolomics by Nuclear Magnetic Resonance (NMR) has the ability to simultaneously detect and structurally characterize an abundance of metabolic components, even when their identities are unknown. Analysis of the data generated using this experimental approach requires the application of statistical and bioinformatics tools for the correct interpretation of the results. This review focuses on the different steps involved in the metabolomics characterization of biofluids for clinical applications, ranging from the design of the study to the biological interpretation of the results. Particular emphasis is devoted to the specific procedures required for the processing and interpretation of NMR data with a focus on the identification of clinically relevant biomarkers.

Rapid two-dimensional ALSOFAST-HSQC experiment for metabolomics and fluxomics studies: application to a 13C-enriched cancer cell model treated with gold nanoparticles.

Isotope labeling enables the use of 13C-based metabolomics techniques with strongly improved resolution for a better identification of relevant metabolites and tracing of metabolic fluxes in cell and animal models, as required in fluxomics studies. However, even at high NMR-active isotope abundance, the acquisition of one-dimensional 13C and classical two-dimensional 1H,13C-HSQC experiments remains time consuming. With the aim to provide a shorter, more efficient alternative, herein we explored the ALSOFAST-HSQC experiment with its rapid acquisition scheme for the analysis of 13C-labeled metabolites in complex biological mixtures. As an initial step, the parameters of the pulse sequence were optimized to take into account the specific characteristics of the complex samples. We then applied the fast two-dimensional experiment to study the effect of different kinds of antioxidant gold nanoparticles on a HeLa cancer cell model grown on 13C glucose-enriched medium. As a result, 1H,13C-2D correlations could be obtained in a couple of seconds to few minutes, allowing a simple and reliable identification of various 13C-enriched metabolites and the determination of specific variations between the different sample groups. Thus, it was possible to monitor glucose metabolism in the cell model and study the antioxidant effect of the coated gold nanoparticles in detail. Finally, with an experiment time of only half an hour, highly resolved 1H,13C-HSQC spectra using the ALSOFAST-HSQC pulse sequence were acquired, revealing the isotope-position-patterns of the corresponding 13C-nuclei from carbon multiplets. Graphical abstract Fast NMR applied to metabolomics and fluxomics studies with gold nanoparticles.

The PipX Protein, When Not Bound to Its Targets, Has Its Signaling C-Terminal Helix in a Flexed Conformation.

PipX, an 89-residue protein, acts as a coactivator of the global nitrogen regulator NtcA in cyanobacteria. NtcA-PipX interactions are regulated by 2-oxoglutarate (2-OG), an inverse indicator of the ammonia abundance, and by PII, a protein that binds to PipX at low 2-OG concentrations. The structure of PipX, when bound to NtcA or PII, consists of an N-terminal, five-stranded ß-sheet (conforming a Tudor-like domain), and two long α-helices. These helices adopt either a flexed conformation, where they are in close contact and in an antiparallel mutual orientation, also packing against the ß-sheet, or an open conformation (observed only in the PII-PipX complex) where the last α-helix moves apart from the rest of the protein. The aim of this work was to study the structure and dynamics of isolated PipX in solution by NMR. The backbone chemical shifts, the hydrogen-exchange, and the NOE patterns indicated that the isolated, monomeric PipX structure was formed by an N-terminal five-stranded ß-sheet and two C-terminal α-helices. Furthermore, the observed NOEs between the two helices, and of α-helix2 with ß-strand2 suggested that PipX adopted a flexed conformation. The ß-strands 1 and 5 were highly flexible, as shown by the lack of interstrand backbone-backbone NOEs; in addition, the 15N-dynamics indicated that the C terminus of ß-strand4 and the following ß-turn (Phe42-Thr47), and the C-cap of α-helix1 (Arg70-Asn71) were particularly mobile. These two regions could act as hinges, allowing PipX to interact with its partners, including PlmA in the newly recognized PII-PipX-PlmA ternary complex.

A Drosophila model of GDAP1 function reveals the involvement of insulin signalling in the mitochondria-dependent neuromuscular degeneration.

Charcot-Marie-Tooth disease is a rare peripheral neuropathy for which there is no specific treatment. Some forms of Charcot-Marie-Tooth are due to mutations in the GDAP1 gene. A striking feature of mutations in GDAP1 is that they have a variable clinical manifestation, according to disease onset and progression, histology and mode of inheritance. Studies in cellular and animal models have revealed a role of GDAP1 in mitochondrial morphology and distribution, calcium homeostasis and oxidative stress. To get a better understanding of the disease mechanism we have generated models of over-expression and RNA interference of the Drosophila Gdap1 gene. In order to get an overview about the changes that Gdap1 mutations cause in our disease model, we have combined a comprehensive determination of the metabolic profile in the flies by nuclear magnetic resonance spectroscopy with gene expression analyses and biophysical tests. Our results revealed that both up- and down-regulation of Gdap1 results in an early systemic inactivation of the insulin pathway before the onset of neuromuscular degeneration, followed by an accumulation of carbohydrates and an increase in the ß-oxidation of lipids. Our findings are in line with emerging reports of energy metabolism impairments linked to different types of neural pathologies caused by defective mitochondrial function, which is not surprising given the central role of mitochondria in the control of energy metabolism. The relationship of mitochondrial dynamics with metabolism during neurodegeneration opens new avenues to understand the cause of the disease, and for the discovery of new biomarkers and treatments.

A conserved docking surface on calcineurin mediates interaction with substrates and immunosuppressants.

The phosphatase calcineurin, a target of the immunosuppressants cyclosporin A and FK506, dephosphorylates NFAT transcription factors to promote immune activation and development of the vascular and nervous systems. NFAT interacts with calcineurin through distinct binding motifs: the PxIxIT and LxVP sites. Although many calcineurin substrates contain PxIxIT motifs, the generality of LxVP-mediated interactions is unclear. We define critical residues in the LxVP motif, and we demonstrate its binding to a hydrophobic pocket at the interface of the two calcineurin subunits. Mutations in this region disrupt binding of mammalian calcineurin to NFATC1 and the interaction of yeast calcineurin with substrates including Rcn1, which contains an LxVP motif. These mutations also interfere with calcineurin-immunosuppressant binding, and an LxVP-based peptide competes with immunosuppressant-immunophilin complexes for binding to calcineurin. These studies suggest that LxVP-type sites are a common feature of calcineurin substrates, and that immunosuppressant-immunophilin complexes inhibit calcineurin by interfering with this mode of substrate recognition.

Pharmacological inhibition of the integrated stress response accelerates disease progression in an amyotrophic lateral sclerosis mouse model.

BACKGROUND AND PURPOSE: The integrated stress response (ISR) regulates translation in response to diverse stresses. ISR activation has been documented in amyotrophic lateral sclerosis (ALS) patients and ALS experimental models. In experimental models, both ISR stimulation and inhibition prevented ALS neurodegeneration; however, which mode of ISR regulation would work in patients is still debated. We previously demonstrated that the ISR modulator ISRIB (Integrated Stress Response InhiBitor, an eIF2B activator) enhances survival of neurons expressing the ALS neurotoxic allele SOD1 G93A. Here, we tested the effect of two ISRIB-like eIF2B activators (2BAct and PRXS571) in the disease progression of transgenic SOD1G93A mice. EXPERIMENTAL APPROACH: After biochemical characterization in primary neurons, SOD1G93A mice were treated with 2BAct and PRXS571. Muscle denervation of vulnerable motor units was monitored with a longitudinal electromyographic test. We used a clinical score to document disease onset and progression; force loss was determined with the hanging wire motor test. Motor neuronal survival was assessed by immunohistochemistry. KEY RESULTS: In primary neurons, 2BAct and PRXS571 relieve the ISR-imposed translational inhibition while maintaining high ATF4 levels. Electromyographic recordings evidenced an earlier and more dramatic muscle denervation in treated SOD1G93A mice that correlated with a decrease in motor neuron survival. Both compounds anticipated disease onset and shortened survival time. CONCLUSION AND IMPLICATIONS: 2BAct and PRXS571 anticipate disease onset, aggravating muscle denervation and motor neuronal death of SOD1G93A mice. This study reveals that the ISR works as a neuroprotective pathway in ALS motor neurons and reveals the toxicity that eIF2B activators may display in ALS patients.

Study of pediatric invasive pneumococcal disease in the 13-pneumococcal conjugated vaccine era.

BACKGROUND: Invasive pneumococcal disease (IPD) remains a significant concern among children under 5, despite vaccination efforts. This study assessed IPD prevalence and associated risks in pediatric population. METHODS: An observational, retrospective, multicenter study in Comunidad Valenciana, Spain, of IPD cases in children under 13 from January 2012 to September 2022. Data from the CV Microbiology Surveillance Network (RedMIVA) and medical records were reviewed. RESULTS: A total of 379 IPD cases in 377 patients were analyzed, predominantly males (54.11 %) under 5 (81.17 %). PCV13 vaccination notably reduced PCV13-serotypes IPD (p=0.0002), except serotype 3. Pneumonia was common, with half having underlying conditions (50.40 %). Worse outcomes occurred in patients with neurological disorders (ANOVA, p=0.57). Vaccine failures often involved underlying conditions (63 %) and serotypes 3 and 19A. Immunodeficiencies may relate to recurrent IPD, but evidence is limited. CONCLUSION: Despite vaccination, IPD still impacts children, influenced by immunological status, affecting severity and mortality.

Protein Biomarkers in Lung Cancer Screening: Technical Considerations and Feasibility Assessment.

Lung cancer remains the leading cause of cancer-related deaths worldwide, mainly due to late diagnosis and the presence of metastases. Several countries around the world have adopted nation-wide LDCT-based lung cancer screening that will benefit patients, shifting the stage at diagnosis to earlier stages with more therapeutic options. Biomarkers can help to optimize the screening process, as well as refine the TNM stratification of lung cancer patients, providing information regarding prognostics and recommending management strategies. Moreover, novel adjuvant strategies will clearly benefit from previous knowledge of the potential aggressiveness and biological traits of a given early-stage surgically resected tumor. This review focuses on proteins as promising biomarkers in the context of lung cancer screening. Despite great efforts, there are still no successful examples of biomarkers in lung cancer that have reached the clinics to be used in early detection and early management. Thus, the field of biomarkers in early lung cancer remains an evident unmet need. A more specific objective of this review is to present an up-to-date technical assessment of the potential use of protein biomarkers in early lung cancer detection and management. We provide an overview regarding the benefits, challenges, pitfalls and constraints in the development process of protein-based biomarkers. Additionally, we examine how a number of emerging protein analytical technologies may contribute to the optimization of novel robust biomarkers for screening and effective management of lung cancer.

An automated network-based tool to search for metabolic vulnerabilities in cancer.

The development of computational tools for the systematic prediction of metabolic vulnerabilities of cancer cells constitutes a central question in systems biology. Here, we present gmctool, a freely accessible online tool that allows us to accomplish this task in a simple, efficient and intuitive environment. gmctool exploits the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to synthetic lethality based on genome-scale metabolic networks, including a unique database of synthetic lethals computed from Human1, the most recent metabolic reconstruction of human cells. gmctool introduces qualitative and quantitative improvements over our previously developed algorithms to predict, visualize and analyze metabolic vulnerabilities in cancer, demonstrating a superior performance than competing algorithms. A detailed illustration of gmctool is presented for multiple myeloma (MM), an incurable hematological malignancy. We provide in vitro experimental evidence for the essentiality of CTPS1 (CTPS synthase) and UAP1 (UDP-N-Acetylglucosamine Pyrophosphorylase 1) in specific MM patient subgroups.