Biology subjects

Lopes, R.

Publications and source records attributed to Lopes, R..

25 records · Page 2Linked to original sources

bioRxiv2021

Decoding activity in Broca's area predicts the occurrence of auditory hallucinations across subjects

BACKGROUNDFunctional magnetic resonance imaging (fMRI) capture aims at detecting auditory-verbal hallucinations (AVHs) from continuously recorded brain activity. Establishing efficient capture methods with low computational cost that easily generalize between patients remains a key objective in precision psychiatry. To address this issue, we developed a novel automatized fMRI-capture procedure for AVHs in schizophrenia patients. METHODSWe used a previously validated, but labor-intensive, personalized fMRI-capture method to train a linear classifier using machine-learning techniques. We benchmarked the performances of this classifier on 2320 AVH periods vs. resting-state periods obtained from schizophrenia patients with frequent symptoms (n=23). We characterized patterns of BOLD activity that were predictive of AVH both within- and between-subjects. Generalizability was assessed with a second independent sample gathering 2000 AVH labels (n=34 schizophrenia patients), while specificity was tested with a nonclinical control sample performing an auditory imagery task (840 labels, n=20). RESULTSOur between-subject classifier achieved high decoding accuracy (area-under-the-curve, AUC = 0.85) and discriminated AVH from rest and verbal imagery. Optimizing the parameters on the first schizophrenia dataset and testing its performance on the second dataset led to a 0.85 out-of-sample AUC (0.88 for the converse test). We showed that AVH detection critically depends on local BOLD activity patterns within Brocas area. CONCLUSIONSOur results demonstrate that it is possible to reliably detect AVH-states from BOLD signals in schizophrenia patients using a multivariate decoder without performing complex regularization procedures. These findings constitute a crucial step toward brain-based treatments for severe drug-resistant hallucinations.

neuroscience↗

bioRxiv2020

SARS-CoV-2 inhibition in human airway epithelial cells using a mucoadhesive, amphiphilic chitosan that may serve as an anti-viral nasal spray

There are currently no cures for coronavirus infections, making the prevention of infections the only course open at the present time. The COVID-19 pandemic has been difficult to prevent, as the infection is spread by respiratory droplets and thus effective, scalable and safe preventive interventions are urgently needed. We hypothesise that preventing viral entry into mammalian nasal epithelial cells may be one way to limit the spread of COVID-19. Here we show that N-palmitoyl-N-monomethyl-N,N-dimethyl-N,N,N-trimethyl-6-O-glycolchitosan (GCPQ), a positively charged polymer that has been through an extensive Good Laboratory Practice toxicology screen, is able to reduce the infectivity of SARS-COV-2 in A549ACE2+ and Vero E6 cells with a log removal value of -3 to -4 at a concentration of 10 - 100 g/ mL (p < 0.05 compared to untreated controls) and to limit infectivity in human airway epithelial cells at a concentration of 500 g/ mL (p < 0.05 compared to untreated controls). GCPQ is currently being developed as a pharmaceutical excipient in nasal and ocular formulations. GCPQs electrostatic binding to the virus, preventing viral entry into the host cells, is the most likely mechanism of viral inhibition. Radiolabelled GCPQ studies in mice show that at a dose of 10 mg/ kg, GCPQ has a long residence time in mouse nares, with 13.1% of the injected dose identified from SPECT/CT in the nares, 24 hours after nasal dosing. With a no observed adverse effect level of 18 mg/ kg in rats, following a 28-day repeat dose study, clinical testing of this polymer, as a COVID-19 prophylactic is warranted.

pharmacology and toxicology↗

bioRxiv2020

Intrusive Experiences In Post-Traumatic Stress Disorder: Treatment Response Induces Changes In The Effective Connectivity Of The Anterior Insula

BackgroundOne of the core features of posttraumatic stress disorder (PTSD) is reexperiencing the trauma. The anterior insula (AI) was proposed to play a crucial role in these intrusive experiences. However, the dynamic function of the AI in reexperiencing trauma, as well as its putative modulation by effective therapy, still need to be specified. MethodsThirty PTSD patients were enrolled and exposed to traumatic memory reactivation therapy. Resting-state fMRI scans were acquired before and after treatment. To explore AI directed influences over the rest of the brain, we referred to a mixed-model using pre/post Granger causality analysis seeded on the AI as a within-subject factor and treatment response as a between-subject factor. To further identify correlates of reexperiencing trauma, we investigated how intrusive severity affected: (i) causality maps and (ii) the spatial stability of other intrinsic brain networks. ResultsWe observed dynamic changes in AI effective connectivity in PTSD patients. Many within- and between-network causal paths were found to be less influenced by the AI after effective therapy. Insular influences were found positively correlated with flashback severity, while reexperiencing was linked with a stronger default mode network (DMN) and more unstable central executive network (CEN) connectivity. ConclusionWe showed that directed changes in AI signaling to the DMN and CEN at rest may underlie the degree of intrusive symptoms in PTSD. A positive response to treatment further induced changes in network-to-network anticorrelated patterns. Such findings may guide targeted neuromodulation strategies in PTSD patients not suitably improved by conventional treatment.

neuroscience↗

bioRxiv2020

Targeting Oncogenic Mutations in Colorectal Cancer using Cryptotanshinone

Colorectal cancer (CRC) is one of the most prevalent types of cancer in the world and ranks second in cancer deaths in the US. Despite the recent improvements in screening and treatment, the number of deaths associated with CRC is still very significant. The complexities involved in CRC therapy stem from multiple oncogenic mutations and crosstalk between abnormal pathways. This calls for using advanced molecular genetics to understand the underlying pathway interactions responsible for this cancer. In this paper, we construct the CRC pathway from the literature and using an existing public dataset on healthy vs tumor colon cells, we identify the genes/pathways that are mutated and are possibly responsible for the disease progression. We then introduce drugs in the CRC pathway, and using a boolean modeling technique, we deduce the drug combinations that produce maximum cell death. Our theoretical simulations demonstrate the effectiveness of Cryptotanshinone, a traditional Chinese herb derivative, achieved by targeting critical oncogenic mutations and enhancing cell death. Finally, we validate our theoretical results using wet lab experiments on HT29 and HCT116 human colorectal carcinoma cell lines.

systems biology↗

bioRxiv2020

Comprehensive Live-cell Imaging Analysis of Cryptotanshinone and Synergistic Drug-Screening Effects in Various Human and Canine Cancer Cell Lines

ABSTRACTBackground Several studies have highlighted both the extreme anticancer effects of Cryptotanshinone (CT), a Stat3 crippling component from Salvia miltiorrhiza, as well as other STAT3 inhibitors to fight cancer.Methods Data presented in this experiment incorporates 2 years of in vitro studies applying a comprehensive live-cell drug-screening analysis of human and canine cancer cells exposed to CT at 20 μM concentration, as well as to other drug combinations. As previously observed in other studies, dogs are natural cancer models, given to their similarity in cancer genetics, epidemiology and disease progression compared to humans.Results Results obtained from several types of human and canine cancer cells exposed to CT and varied drug combinations, verified CT efficacy at combating cancer by achieving an extremely high percentage of apoptosis within 24 hours of drug exposure.Conclusions CT anticancer efficacy in various human and canine cancer cell lines denotes its ability to interact across different biological processes and cancer regulatory cell networks, driving inhibition of cancer cell survival.View Full Text

cancer biology↗

bioRxiv2019

Neuronal programming by microbiota enables environmental regulation of intestinal motility

Environmental signals modulate the activity of the nervous system and harmonize its output with the outside world. Synaptic activity is crucial for integrating sensory and effector neural pathways but the role of transcriptional mechanisms as environmental sensors in the nervous system remains unclear. By combining a novel strategy for transcriptomic profiling of enteric neurons with microbiota manipulation, we demonstrate that the transcriptional programs of intestinal neural circuits depend on their anatomical and physiological context. We also identify the ligand-dependent transcription factor Aryl hydrocarbon Receptor (AhR) is an intrinsic regulator of enteric nervous system output. AhR is instated as a neuronal biosensor in response to microbiota colonization allowing resident enteric neurons to directly monitor and respond to the intestinal microenvironment. We suggest that AhR signaling integrates neuronal activity with host defence mechanisms towards gut homeostasis and health.\n\nOne Sentence SummaryMicrobiota induce expression of AhR in enteric neurons of the distal intestine enabling them to respond to environmental signals.

neuroscience↗

bioRxiv2018

Small effect size leads to reproducibility failure in resting-state fMRI studies

Thousands of papers using resting-state functional magnetic resonance imaging (RS-fMRI) have been published on brain disorders. Results in each paper may have survived correction for multiple comparison. However, since there have been no robust results from large scale meta-analysis, we do not know how many of published results are truly positives. The present meta-analytic work included 60 original studies, with 57 studies (4 datasets, 2266 participants) that used a between-group design and 3 studies (1 dataset, 107 participants) that employed a within-group design. To evaluate the effect size of brain disorders, a very large neuroimaging dataset ranging from neurological to psychiatric isorders together with healthy individuals have been analyzed. Parkinsons disease off levodopa (PD-off) included 687 participants from 15 studies. PD on levodopa (PD-on) included 261 participants from 9 studies. Autism spectrum disorder (ASD) included 958 participants from 27 studies. The meta-analyses of a metric named amplitude of low frequency fluctuation (ALFF) showed that the effect size (Hedges g) was 0.19 - 0.39 for the 4 datasets using between-group design and 0.46 for the dataset using within-group design. The effect size of PD-off, PD-on and ASD were 0.23, 0.39, and 0.19, respectively. Using the meta-analysis results as the robust results, the between-group design results of each study showed high false negative rates (median 99%), high false discovery rates (median 86%), and low accuracy (median 1%), regardless of whether stringent or liberal multiple comparison correction was used. The findings were similar for 4 RS-fMRI metrics including ALFF, regional homogeneity, and degree centrality, as well as for another widely used RS-fMRI metric namely seed-based functional connectivity. These observations suggest that multiple comparison correction does not control for false discoveries across multiple studies when the effect sizes are relatively small. Meta-analysis on un-thresholded t-maps is critical for the recovery of ground truth. We recommend that to achieve high reproducibility through meta-analysis, the neuroimaging research field should share raw data or, at minimum, provide un-thresholded statistical images.

neuroscience↗