Biology subjects

Santos, L.

Publications and source records attributed to Santos, L..

15 recordsLinked to original sources

bioRxiv2026

In Vitro Efficacy of Paclitaxel-loaded PLGA Nanoformulations for Lung Cancer Treatment Demonstrated by Label-free Multiphoton-Fluorescence Lifetime Imaging Microscopy

Lung cancer remains the leading cause of cancer-related mortality, and despite its limited efficacy, and low specificity, chemotherapy is still commonly used as a first-line treatment. Herein, we prepare and characterize poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) for the use as a non-targeted nanocarrier drug delivery system for the chemotherapeutic drug, paclitaxel (PTX). Drug loading capability, mono-dispersity, zeta potential, morphology, and drug release profile were determined for the PLGA NPs. Furthermore, the IC50 of the loaded nanoparticles was determined to be 20 times lower than the IC50 value of free PTX in cytotoxic studies in A549 lung cancer cells. The time dependent therapeutic efficacy of both free and encapsulated PTX was assess at several time points in A549 monolayers via label-free multiphoton metabolic imaging based on the fluorescence lifetime of the metabolic cofactor NAD(P)H. Specifically, the significant continuous metabolic shift towards oxidative phosphorylation in cells treated with NPs was correlated with the NPs drug release profile, highlighting the sustained and controlled behavior of the drug delivery system. These findings underscore not only the utility of PLGA NPs as a drug delivery system with enhanced efficacy compared to free drug treatments but also the use of label-free multiphoton fluorescence lifetime imaging microscopy for non-invasive imaging, allowing the tracking of metabolic changes on cellular and subcellular level. Additionally, the presented method is extended to include more complex in vitro models allowing for assessing the cellular bioenergetic response of individual cells in 3D models in real time, paving the way for improved therapeutic strategies against lung cancer.

cancer biology↗

bioRxiv2026

Nitazoxanide activates BMP9-ALK1-SMAD signaling cascade and improves HHT vascular pathology

ObjectiveHereditary hemorrhagic telangiectasia (HHT) is a vascular genetic disorder caused by endothelial cell dysfunction and characterized by telangiectasias and arteriovenous malformations (AVMs). HHT results primarily from loss-of-function mutations affecting components of the BMP9-ALK1-ENG-SMAD signaling cascade, a pathway essential for endothelial quiescence and vascular homeostasis, and currently lacks a cure. Here, we investigated whether nitazoxanide, an orally bioavailable drug with extensive clinical use, can modulate endothelial signaling relevant to HHT. Approach and ResultsNitazoxanide treatment activated SMAD1/5/8 signaling and increased expression of the downstream target ID1 in endothelial cells, while concurrently inhibiting mTOR signaling, indicating a dual modulatory effect on pathways implicated in HHT pathogenesis. In vivo, nitazoxanide activated SMAD signaling in BMP9/10-immunoblocked mice and significantly reduced AVM formation and hypervascularization. Importantly, nitazoxanide restored SMAD1/5/8 activation and ID1 expression in patient-derived blood outgrowth endothelial cells harboring loss-of-function mutations in ALK1 or SMAD4, which exhibit impaired BMP signaling. ConclusionThese findings identify nitazoxanide as a pharmacological modulator capable of activating BMP-SMAD signaling while restraining mTOR activity, thereby overcoming key signaling defects in HHT endothelial cells. Collectively, our results highlight nitazoxanide as a promising therapeutic candidate to target endothelial dysfunction in HHT.

cell biology↗

bioRxiv2024

Adipocyte-specific deletion of Dbc1 does not recapitulate healthy obesity phenotype but suggests regulation of inflammation signaling

The protein Deleted in Breast Cancer 1 (DBC1), a regulator of several transcription factors and epigenetic modulators, plays determinant roles in metabolism regulation, obesity and aging-related processes. Knockout mice for Dbc1, develop morbid obesity but are protected against liver steatosis, insulin resistance and atherosclerosis. We have proposed that this healthy obesity phenotype was mainly due to the expansion of adipose tissue, avoiding free-fatty acid spillover and metabolic damage in peripheral tissues. To gain more insight about the role of Dbc1 in adipose cells during obesity and its impact on metabolic dysregulation, we generated a conditional Dbc1 KO mouse and backcrossed it with CRE-AdipoQ transgenic mice, aiming to abrogate Dbc1 expression in all mature adipocytes (cAT-Dbc1). cAT-Dbc1 mice showed deletion of Dbc1 specifically in mature adipocytes in different fat depots. We tested the effect of Dbc1 deletion in adipocytes on different aspects of metabolic regulation in male and female mice fed in normal chow and high-fat diets. We found that deletion of Dbc1 in mature adipocytes had no effect on weight gain, glucose tolerance and other markers of metabolic dysregulation, regardless sex. However, Dbc1 KO adipocytes displayed an mRNA expression profile consistent with increased inflammation during obesity. Our results suggest that the healthy phenotype displayed in the whole body Dbc1 KO obese mice is not due to the protein function in mature adipocytes and might involve other cell types present in adipose tissue. Instead, the specific deletion of Dbc1 in mature adipocytes highlights a novel role of Dbc1 in inflammation signaling during obesity.

physiology↗

bioRxiv2024

LDL exposure disrupts mitochondrial function and dynamics in a hippocampal neuronal cell line

Hypercholesterolemia has been associated with cognitive dysfunction and neurodegenerative disease. Moreover, this metabolic condition disrupts the blood-brain barrier, allowing Low-Density Lipoprotein (LDL) to enter the Central Nervous System. Thus, we investigated the effects of LDL exposure on mitochondrial function in a mouse hippocampal neuronal cell line (HT-22). HT-22 cells were exposed to human LDL (50 and 300 g/mL) for 24 hours. After this, intracellular lipid droplet (LD) content, cell viability, cell death, and mitochondrial parameters were performed. We found that the higher LDL concentration LDL increases LD content compared to control. Both concentrations increased the number of Annexin V-positive cells, indicating apoptosis. Moreover, in mitochondrial parameters, the exposure of LDL on hippocampal neuronal cell line leads to a decrease in mitochondrial complexes I and II in both concentrations tested and a reduction in Mitotracker Red fluorescence and Mitotracker Red and Mitotracker Green ratio in the higher concentration, indicating dysfunction in the mitochondria. The LDL incubation induces mitochondrial superoxide production and a decrease in superoxide dismutase activity in the lower concentration in HT-22 cells. Finally, hippocampal neuronal cell line exposed to LDL exhibit an increase in the expression of genes associated with mitochondrial fusion (OPA1 and Mitofusin 2) in the lower concentration. In conclusion, our findings suggest that LDL exposure induces mitochondrial dysfunction and modulation in mitochondrial dynamics in the hippocampal neuronal cells.

biochemistry↗

bioRxiv2024

Deciphering the impact of cancer cells secretome and its derived-peptide VGF on breast cancer brain metastasis

Brain metastases (BM) are one of the most serious clinical problems in breast cancer (BC) progression, associated with lower survival rates and a lack of effective therapies. Thus, to dissect the early stages of the brain metastatic process, we have searched for a brain-tropic metastatic signature on BC cells secretome, as a promising source for the discovery of new biomarkers involved in brain metastatic progression. Therefore, six specifically deregulated peptides were found to be enriched in the secretome of brain organotropic BC cells. Importantly, these secretomes caused significant blood-brain barrier (BBB) disruption, as well as microglial activation, in vitro and in vivo. We identified the VGF nerve growth factor inducible as a brain-specific peptide, promoting BBB dysfunction similar to the secretome of brain organotropic BC cells. Concerning microglial activation, a slight increase was also observed upon VGF treatment. In a series of human breast tumors, VGF was found to be expressed in both cancer cells and in the adjacent stroma. VGF-positive tumors showed a significant worse prognosis and were associated with HER2 overexpression and triple-negative molecular signatures. Finally, in a cohort including primary breast tumors and their corresponding metastatic locations to the lung, bone, and brain, we found that VGF significantly correlates with the brain metastatic site. In conclusion, we found a specific BC brain metastatic signature, where VGF was identified as a key mediator in this process. Importantly, its expression was associated with poor prognosis for BC patients, probably due to its associated increased risk of developing BM.

cancer biology↗

bioRxiv2024

FSTL1 is an antagonist of ERK1/2 phosphorylation during ciliogenesis and preadipocyte differentiation.

FSTL1 is a secreted glycoprotein that is involved in several processes in health and disease, including development, cardiovascular disease, cancer, inflammation, and obesity. The signaling pathways used by FSTL1 to act on target tissues seem to activate different intracellular mediators specific to each tissue and several of the mechanisms of action remain to be determined at the molecular level, including intracellular mediators and receptors. We have previously unveiled a novel role for FSTL1 in ciliogenesis and provided evidence for an Fstl1/cilia axis in preadipocyte differentiation. This pathway is relevant to the pathogenesis of obesity and of a group of conditions called ciliopathies since they are caused by the dysfunction of the primary cilia. This work aimed to identify intracellular mediators of FSTL1 action on ciliogenesis and adipogenesis. We analyzed ERK phosphorylation levels as well as cilia length in the absence of FSTL1 and in the presence of the pERK inhibitor U0126. We also analyzed the differentiation and cilia dynamics of U0126-treated preadipocytes and tested the ERK-mediated signaling by BMP4 in the presence of added extracellular Fstl1. Here, we propose that MAP kinase ERK is a mediator of ciliogenesis downstream of FSTL1 and provide additional data that suggest that FSTL1 antagonizes BMP non-canonical signaling to modulate ciliogenesis and adipogenesis. In sum, our data reinforce the interest on the axis FSTL1/cilia in the modulation of adipogenesis and provide evidence to add ERK to this working model.

cell biology↗

bioRxiv2023

Differences Between Human and Non-Human Primate Theory of Mind: Evidence from Computational Modeling

Can non-human primates (NHPs) represent other minds? Answering this question is difficult because primates can fail tasks due to a lack of motivation or succeed through simpler strategies. Here we address these challenges through a computational theory-testing framework for NHP Theory of Mind. In this framework, each theory combines a proposed social representation with a parameter for how often it is used. This allow us to move beyond dichotomous positions about Theory of Minds presence or absence and instead analyze graded patterns of behavior as a combination of cognitive representations and their use. We apply this approach to one of the most foundational and well-studied aspects of Theory of Mind: the relation between seeing and knowing. Our results show that only theories in which NHPs have some representation of other minds can capture the qualitative pattern of successes and failures across five classic perspective-taking paradigms. However, these theories vary in their reliance on their representations, each showing significantly lower reliance than a human baseline. These results suggest that human and NHP social cognition differ in terms of reliance and possibly also in terms of representational complexity.

animal behavior and cognition↗

bioRxiv2023

Bridging the gap between movement data and connectivity analysis using the time-explicit Step Selection Function (tSSF)

BackgroundUnderstanding how to connect habitat remnants to facilitate the movement of species is a critical task in an increasingly fragmented world impacted by human activities. The identification of dispersal routes and corridors through connectivity analysis requires measures of landscape resistance but there has been no consensus on how to calculate resistance from habitat characteristics, potentially leading to very different connectivity outcomes. MethodsWe propose a new model called the time-explicit step selection function (tSSF) that can be directly used for connectivity analysis in the context of the spatial absorbing Markov chain (SAMC) framework without requiring arbitrary transformations. The tSSF model combines a time model with a standard selection function and can provide complementary information regarding how animals use landscapes by separately assessing the drivers of time to traverse the landscape and the drivers of habitat selection. These models are illustrated using GPS-tracking data from giant anteaters (Myrmecophaga tridactyla) in the Pantanal wetlands of Brazil. ResultsThe time model revealed that the fastest movements tended to occur between 8 pm and 5 am, suggesting a crepuscular/nocturnal behavior. Giant anteaters moved faster over wetlands while moving much slower over forests and savannas, in comparison to grasslands. We found that wetlands were consistently avoided whereas forest and savannas tended to be selected. Importantly, this model revealed that selection for forest increased with temperature, suggesting that forests may act as important thermal shelters when temperatures are high. Finally, the tSSF results can be used to simulate movement and connectivity within a fragmented landscape, revealing that giant anteaters will often not use the shortest-distance path to the destination patch (because that would require traversing a wetland, an avoided habitat) and that approximately 90% of the individuals will have reached the destination patch after 49 days. ConclusionsThe approach proposed here can be used to gain a better understanding of how landscape features are perceived by individuals through the decomposition of movement patterns into a time and a habitat selection component. This approach can also help bridge the gap between movement-based models and connectivity analysis, enabling the generation of time-explicit results.

animal behavior and cognition↗

bioRxiv2023

Unveiling the role of osteosarcoma-derived secretome in premetastatic lung remodeling

Lung metastasis represents the leading cause of osteosarcoma-related death. Progress in preventing lung metastasis is pretty modest due to the inherent complexity of the metastatic process and the lack of suitable models. Herein, we provide mechanistic insights into how osteosarcoma systemically reprograms the lung microenvironment for metastatic outgrowth using metastatic mouse models and a multi-omics approach. We found that osteosarcoma-bearing mice or those preconditioned with cell-secretome harbour profound lung structural alteration with airways damage, inflammation, neutrophil infiltration, and remodelling of the extracellular matrix with deposition of fibronectin and collagen by stromal activated fibroblasts for tumour cell adhesion. These changes, supported by transcriptomic and histological data, promoted and accelerated the development of lung metastasis. Comparative proteome profiling of the cell secretome and mouse plasma identified a large number of proteins engaged in the extracellular-matrix organization, cell-matrix adhesion, neutrophil degranulation, and cytokine-mediated signalling, which were consistent with the observed lung microenvironmental changes. Moreover, we identified EFEMP1, a secreted extracellular matrix glycoprotein, as a potential risk factor for lung metastasis and a poor prognosis factor in osteosarcoma patients.

cancer biology↗

bioRxiv2022

SARS-CoV-2 immune complex triggers human monocyte necroptosis

We analyzed the ability of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) itself and SARS-CoV-2-IgG immune complexes to trigger human monocyte necroptosis. SARS-CoV-2 was able to induce monocyte necroptosis dependently of MLKL activation. Necroptosis-associated proteins (RIPK1, RIPK3 and MLKL) were involved in SARS-CoV-2 N1 gene expression in monocytes. SARS-CoV-2 immune complexes promoted monocyte necroptosis in a RIPK3- and MLKL-dependent manner, and Syk tyrosine kinase was necessary for SARS-CoV-2 immune complex-induced monocyte necroptosis, indicating the involvement of Fc{gamma} receptors on necroptosis. Finally, we provide evidence that elevated LDH levels as a marker of lytic cell death are associated with COVID-19 pathogenesis.

immunology↗

bioRxiv2021

The production of 4,182 mouse lines identifies experimental and biological variables impacting Cas9-mediated mutant mouse line production

The International Mouse Phenotyping Consortium (IMPC) systematically produces and phenotypes mouse lines with presumptive null mutations to provide insight into gene function. The IMPC now uses the programmable RNA-guided nuclease Cas9 for its increased capacity and flexibility to efficiently generate null alleles in the C57BL/6N strain. In addition to being a valuable novel and accessible research resource, the production of 3,313 knockout mouse lines using comparable protocols provides a rich dataset to analyze experimental and biological variables affecting in vivo gene engineering with Cas9. Mouse line production has two critical steps - generation of founders with the desired allele and germline transmission (GLT) of that allele from founders to offspring. A systematic evaluation of the variables impacting success rates identified gene essentiality as the primary factor influencing successful production of null alleles. Collectively, our findings provide best practice recommendations for using Cas9 to generate alleles in mouse essential genes, many of which are orthologs of genes linked to human disease.

genetics↗

bioRxiv2021

A convolutional neural network for the quality control of MRI defacing

Large-scale neuroimaging datasets present unique challenges for automated processing pipelines. Mo-tivated by a large clinical trials dataset of Multiple Sclerosis with over 235,000 MRI scans, we consider the challenge of defacing - anonymisation to remove identifying facial features. The defacing process must undergo quality control (QC) checks to ensure that the facial features have been adequately anonymised and that the brain tissue is left completely intact. Visual QC checks - particularly on a project of this scale - are time-consuming and can cause delays in preparing data. We have developed a convolutional neural network (CNN) that can assist with the QC of the application of MRI defacing; our CNN is able to distinguish between scans that are correctly defaced, and can also classify defacing failures into three sub-types to facilitate parameter tuning during remedial re-defacing. Since integrating the CNN into our anonymisation pipeline, over 75,000 scans have been processed. Strict thresholds have been applied so that ambiguous classifications are referred for visual QC checks, however all scans still undergo a time-efficient verification check before being marked as passed. After applying the thresholds, our network is 92% accurate and is able to classify nearly half of the scans without the need for protracted manual checks. Even with the introduction of the verification checks, incorporation of the CNN has reduced the time spent undertaking QC checks by 42% during initial defacing, and by 35% overall. With the help of the CNN, we have been able to successfully deface 96% of the scans in the project whilst maintaining high QC standards. In a similarly sized new project of this scale, we would expect the model to reduce the time spent on manual QC checks by 125 hours. Our approach is applicable to other projects with the potential to greatly improve the efficiency of imaging anonymisation pipelines.

neuroscience↗

bioRxiv2021

Gut microbiota diversity and C-Reactive Protein are predictors of disease severity in COVID-19 patients

Risk factors for COVID-19 disease severity are still poorly understood. Considering the pivotal role of gut microbiota on host immune and inflammatory functions, we investigated the association between changes in gut microbiota composition and the clinical severity of COVID-19. We conducted a multicentre cross-sectional study prospectively enrolling 115 COVID-19 patients categorized according to: 1) WHO Clinical Progression Scale - mild 19 (16.5%), moderate 37 (32.2%) or severe 59 (51.3%); and 2) location of recovery from COVID-19 - ambulatory 14 (household isolation; 12.2%), hospitalized in ward 40 (34.8%) or intensive care unit 61 (53.0%). Gut microbiota analysis was performed through 16S rRNA gene sequencing and data obtained was further related with clinical parameters of COVID-19 patients. Risk factors for COVID-19 severity were identified by univariate and multivariable logistic regression models. In comparison with mild COVID-19 patients, the gut microbiota of moderate and severe patients has: a) lower Firmicutes/Bacteroidetes ratio, b) higher abundance of Proteobacteria; and c) lower abundance of beneficial butyrate-producing bacteria such as Roseburia and Lachnospira genera. Multivariable regression analysis showed that Shannon index diversity (odds ratio [OR] 2.85 [95% CI 1.09-7.41]; p=0.032) and C-Reactive Protein (OR 3.45 [95% CI 1.33-8.91]; p=0.011) were risk factors for COVID-19 severe disease (a score of 6 or higher in WHO clinical progression scale). In conclusion, our results demonstrated that hospitalised moderate and severe COVID-19 patients have microbial signatures of gut dysbiosis and for the first time, the gut microbiota diversity is pointed out as a prognostic biomarker for COVID-19 disease severity.

microbiology↗

bioRxiv2021

Forest loss in Indonesian New Guinea: trends, drivers, and outlook

The rich forests of Indonesian New Guinea are threatened. We used satellite data to examine annual forest loss, road development and plantation expansion from 2001 to 2019, then developed a model to predict future deforestation in this understudied region. In 2019, 34.29 million hectares (Mha), or 83% of Indonesian New Guinea, supported old-growth forest. Over nineteen years, two percent (0.75 Mha) were cleared: 45% (0.34 Mha) converted to industrial plantations, roads, mine tailings, or other uses near cities; 55% (0.41 Mha) cleared by transient processes including selective natural timber extraction, inland water bodies-related processes, fires, and shifting agriculture. Industrial plantations expanded by 0.23 Mha, with the majority (0.21 Mha; 28% of forest loss) replacing forests and reaching 0.28 Mha in 2019 (97% oil palm; 3% pulpwood). The Trans-Papua Highway, a ~4,000 km national investment project, increased by 1,554 km. Positive correlations between highway and plantations expansion indicate these are linked processes. Plantations and roads grew rapidly after 2011, peaked in 2015/16, and declined thereafter. Indonesian government allocated 2.62 Mha of land for the development of industrial plantations (90% oil palm 10% pulpwood) of which 74% (1.95 Mha) remained forest in 2019. A spatial model predicts that an additional 4.5 Mha of forest could be cleared by 2036 if Indonesian New Guinea follows similar relationships to Indonesian Borneo. We highlight the opportunities for policy reform and the importance of working with indigenous communities, local leaders, and provincial government to protect the biological and cultural richness still embodied in this remarkable region.

ecology↗

bioRxiv2020

Whole genome sequencing for diagnosis of neurological repeat expansion disorders

BackgroundRepeat expansion (RE) disorders affect ~1 in 3000 individuals and are clinically heterogeneous diseases caused by expansions of short tandem DNA repeats. Genetic testing is often locus-specific, resulting in under diagnosis of atypical clinical presentations, especially in paediatric patients without a prior positive family history. Whole genome sequencing (WGS) is emerging as a first-line test for rare genetic disorders, but until recently REs were thought to be undetectable by this approach. MethodsWGS pipelines for RE disorder detection were deployed by the 100,000 Genomes Project and Illumina Clinical Services Laboratory. Performance was retrospectively assessed across the 13 most common neurological RE loci using 793 samples with prior orthogonal testing (182 with expanded alleles and 611 with alleles within normal size) and prospectively interrogated in 13,331 patients with suspected genetic neurological disorders. FindingsWGS RE detection showed minimum 97{middle dot}3% sensitivity and 99{middle dot}6% specificity across all 13 disease-associated loci. Applying the pipeline to patients from the 100,000 Genomes Project identified pathogenic repeat expansions which were confirmed in 69 patients, including seven paediatric patients with no reported family history of RE disorders, with a 0.09% false positive rate. InterpretationWe show here for the first time that WGS enables the detection of causative repeat expansions with high sensitivity and specificity, and that it can be used to resolve previously undiagnosed neurological disorders. This includes children with no prior suspicion of a RE disorder. These findings are leading to diagnostic implementation of this analytical pipeline in the NHS Genomic Medicine Centres in England. FundingMedical Research Council, Department of Health and Social Care, National Health Service England, National Institute for Health Research, Illumina Inc

genomics↗