Unmoving and uninflamed: Characterizing neuroinflammatory dysfunction in the Wistar-Kyoto rat model of depression.

Reductionistic research on depressive disorders has been hampered by the limitations of animal models. Recently, it has been hypothesized that neuroinflammation is a key player in depressive disorders. The Wistar-Kyoto (WKY) rat is an often-used animal model of depression, but no information so far exists on its neuroinflammatory profile. As such, we compared male young adult WKY rats to Wistar (WS) controls, with regard to both behavioral performance and brain levels of key neuroinflammatory markers. We first assessed anxiety- and depression-like behaviors in a battery consisting of the Elevated Plus Maze (EPM), the Novelty Suppressed Feeding (NSFT), Open Field (OFT), Social Interaction (SIT), Forced Swim (FST), Sucrose Preference (SPT), and Splash tests (ST). We found that WKY rats displayed increased NSFT feeding latency, decreased OFT center zone permanence, decreased EPM open arm permanence, decreased SIT interaction time, and increased immobility in the FST. However, WKY rats also evidenced marked hypolocomotion, which is likely to confound performance in such tests. Interestingly, WKY rats performed similarly, or even above, to WS levels in the SPT and ST, in which altered locomotion is not a significant confound. In a separate cohort, we assessed prefrontal cortex (PFC), hippocampus and amygdala levels of markers of astrocytic (GFAP, S100A10) and microglial (Iba1, CD86, Ym1) activation status, as well as of three key proinflammatory cytokines (IL-1ß, IL-6, TNF-α). There were no significant differences between strains in any of these markers, in any of the regions assessed. Overall, results highlight that behavioral data obtained with WKY rats as a model of depression must be carefully interpreted, considering the marked locomotor activity deficits displayed. Furthermore, our data suggest that, despite WKY rats replicating many depression-associated neurobiological alterations, as shown by others, this is not the case for neuroinflammation-related alterations, thus representing a novel limitation of this model.

Extracellular Vesicles as Potential Bladder Cancer Biomarkers: Take It or Leave It?

Bladder cancer (BC) is the 10th most frequently diagnosed cancer worldwide. Although urine cytology and cystoscopy are current standards for BC diagnosis, both have limited sensitivity to detect low-grade and small tumors. Moreover, effective prognostic biomarkers are lacking. Extracellular vesicles (EVs) are lipidic particles that contain nucleic acids, proteins, and metabolites, which are released by cells into the extracellular space, being crucial effectors in intercellular communication. These particles have emerged as potential tools carrying biomarkers for either diagnosis or prognosis in liquid biopsies namely urine, plasma, and serum. Herein, we review the potential of liquid biopsies EVs' cargo as BC diagnosis and prognosis biomarkers. Additionally, we address the emerging advantages and downsides of using EVs within this framework.

Adenosinergic System and BDNF Signaling Changes as a Cross-Sectional Feature of RTT: Characterization of Mecp2 Heterozygous Mouse Females.

Rett Syndrome is an X-linked neurodevelopmental disorder (RTT; OMIM#312750) associated to MECP2 mutations. MeCP2 dysfunction is seen as one cause for the deficiencies found in brain-derived neurotrophic factor (BDNF) signaling, since BDNF is one of the genes under MeCP2 jurisdiction. BDNF signaling is also dependent on the proper function of the adenosinergic system. Indeed, both BDNF signaling and the adenosinergic system are altered in Mecp2-null mice (Mecp2-/y), a representative model of severe manifestation of RTT. Considering that symptoms severity largely differs among RTT patients, we set out to investigate the BDNF and ADO signaling modifications in Mecp2 heterozygous female mice (Mecp2+/-) presenting a less severe phenotype. Symptomatic Mecp2+/- mice have lower BDNF levels in the cortex and hippocampus. This is accompanied by a loss of BDNF-induced facilitation of hippocampal long-term potentiation (LTP), which could be restored upon selective activation of adenosine A2A receptors (A2AR). While no differences were observed in the amount of adenosine in the cortex and hippocampus of Mecp2+/- mice compared with healthy littermates, the density of the A1R and A2AR subtype receptors was, respectively, upregulated and downregulated in the hippocampus. Data suggest that significant changes in BDNF and adenosine signaling pathways are present in an RTT model with a milder disease phenotype: Mecp2+/- female animals. These features strengthen the theory that boosting adenosinergic activity may be a valid therapeutic strategy for RTT patients, regardless of their genetic penetrance.

S327 phosphorylation of the presynaptic protein SEPTIN5 increases in the early stages of neurofibrillary pathology and alters the functionality of SEPTIN5.

Alzheimer's disease (AD) is the most common form of dementia, which is neuropathologically characterized by extracellular senile plaques containing amyloid-ß and intracellular neurofibrillary tangles composed of hyperphosphorylated tau protein. Previous studies have suggested a role for septin (SEPTIN) protein family members in AD-associated cellular processes. Here, we elucidated the potential role of presynaptic SEPTIN5 protein and its post-translational modifications in the molecular pathogenesis of AD. RNA and protein levels of SEPTIN5 showed a significant decrease in human temporal cortex in relation to the increasing degree of AD-related neurofibrillary pathology. Conversely, an increase in the phosphorylation of the functionally relevant SEPTIN5 phosphorylation site S327 was observed already in the early phases of AD-related neurofibrillary pathology, but not in the cerebrospinal fluid of individuals fulfilling the criteria for mild cognitive impairment due to AD. According to the mechanistic assessments, a link between SEPTIN5 S327 phosphorylation status and the effects of SEPTIN5 on amyloid precursor protein processing and markers of autophagy was discovered in mouse primary cortical neurons transduced with lentiviral constructs encoding wild type SEPTIN5 or SEPTIN5 phosphomutants (S327A and S327D). C57BL/6 J mice intrahippocampally injected with lentiviral wild type SEPTIN5 or phosphomutant constructs did not show changes in cognitive performance after five to six weeks from the start of injections. However, SEPTIN5 S327 phosphorylation status was linked to changes in short-term synaptic plasticity ex vivo at the CA3-CA1 synapse. Collectively, these data suggest that SEPTIN5 and its S327 phosphorylation status play a pivotal role in several cellular processes relevant for AD.

High Caloric Diet Induces Memory Impairment and Disrupts Synaptic Plasticity in Aged Rats.

The increasing consumption of sugar and fat seen over the last decades and the consequent overweight and obesity, were recently linked with a deleterious effect on cognition and synaptic function. A major question, which remains to be clarified, is whether obesity in the elderly is an additional risk factor for cognitive impairment. We aimed at unravelling the impact of a chronic high caloric diet (HCD) on memory performance and synaptic plasticity in aged rats. Male rats were kept on an HCD or a standard diet (control) from 1 to 24 months of age. The results showed that under an HCD, aged rats were obese and displayed significant long-term recognition memory impairment when compared to age-matched controls. Ex vivo synaptic plasticity recorded from hippocampal slices from HCD-fed aged rats revealed a reduction in the magnitude of long-term potentiation, accompanied by a decrease in the levels of the brain-derived neurotrophic factor receptors TrkB full-length (TrkB-FL). No alterations in neurogenesis were observed, as quantified by the density of immature doublecortin-positive neurons in the hippocampal dentate gyrus. This study highlights that obesity induced by a chronic HCD exacerbates age-associated cognitive decline, likely due to impaired synaptic plasticity, which might be associated with deficits in TrkB-FL signaling.

Impairment of adenosinergic system in Rett syndrome: Novel therapeutic target to boost BDNF signalling.

Rett syndrome (RTT; OMIM#312750) is mainly caused by mutations in the X-linked MECP2 gene (methyl-CpG-binding protein 2 gene; OMIM*300005), which leads to impairments in the brain-derived neurotrophic factor (BDNF) signalling. The boost of BDNF mediated effects would be a significant breakthrough but it has been hampered by the difficulty to administer BDNF to the central nervous system. Adenosine, an endogenous neuromodulator, may accomplish that role since through A2AR it potentiates BDNF synaptic actions in healthy animals. We thus characterized several hallmarks of the adenosinergic and BDNF signalling in RTT and explored whether A2AR activation could boost BDNF actions. For this study, the RTT animal model, the Mecp2 knockout (Mecp2-/y) (B6.129P2 (C)-Mecp2tm1.1Bird/J) mouse was used. Whenever possible, parallel data was also obtained from post-mortem brain samples from one RTT patient. Ex vivo extracellular recordings of field excitatory post-synaptic potentials in CA1 hippocampal area were performed to evaluate synaptic transmission and long-term potentiation (LTP). RT-PCR was used to assess mRNA levels and Western Blot or radioligand binding assays were performed to evaluate protein levels. Changes in cortical and hippocampal adenosine content were assessed by liquid chromatography with diode array detection (LC/DAD). Hippocampal ex vivo experiments revealed that the facilitatory actions of BDNF upon LTP is absent in Mecp2-/y mice and that TrkB full-length (TrkB-FL) receptor levels are significantly decreased. Extracts of the hippocampus and cortex of Mecp2-/y mice revealed less adenosine amount as well as less A2AR protein levels when compared to WT littermates, which may partially explain the deficits in adenosinergic tonus in these animals. Remarkably, the lack of BDNF effect on hippocampal LTP in Mecp2-/y mice was overcome by selective activation of A2AR with CGS21680. Overall, in Mecp2-/y mice there is an impairment on adenosinergic system and BDNF signalling. These findings set the stage for adenosine-based pharmacological therapeutic strategies for RTT, highlighting A2AR as a therapeutic target in this devastating pathology.

Challenges of BDNF-based therapies: From common to rare diseases.

Neurotrophins are a well-known family of neurotrophic factors that play an important role both in the central and peripheral nervous systems, where they modulate neuronal survival, development, function and plasticity. Brain-derived neurotrophic factor (BDNF) possesses diverse biological functions which are mediated by the activation of two main classes of receptors, the tropomyosin-related kinase (Trk) B and the p75 neurotrophin receptor (p75NTR). The therapeutic potential of BDNF has drawn attention since dysregulation of its signalling cascades has been suggested to underlie the pathogenesis of both common and rare diseases. Multiple strategies targeting this neurotrophin have been tested; most have found obstacles that ultimately hampered their effectiveness. This review focuses on the involvement of BDNF and its receptors in the pathophysiology of Alzheimer's disease (AD), Amyotrophic Lateral Sclerosis (ALS) and Rett Syndrome (RTT). We describe the known mechanisms leading to the impairment of BDNF/TrkB signalling in these disorders. Such mechanistic insight highlights how BDNF signalling compromise can take various shapes, nearly disease-specific. Therefore, BDNF-based therapeutic strategies must be specifically tailored and are more likely to succeed if a combination of resources is employed.

Outcome Prediction in Postanoxic Coma With Deep Learning.

OBJECTIVES: Visual assessment of the electroencephalogram by experienced clinical neurophysiologists allows reliable outcome prediction of approximately half of all comatose patients after cardiac arrest. Deep neural networks hold promise to achieve similar or even better performance, being more objective and consistent. DESIGN: Prospective cohort study. SETTING: Medical ICU of five teaching hospitals in the Netherlands. PATIENTS: Eight-hundred ninety-five consecutive comatose patients after cardiac arrest. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Continuous electroencephalogram was recorded during the first 3 days after cardiac arrest. Functional outcome at 6 months was classified as good (Cerebral Performance Category 1-2) or poor (Cerebral Performance Category 3-5). We trained a convolutional neural network, with a VGG architecture (introduced by the Oxford Visual Geometry Group), to predict neurologic outcome at 12 and 24 hours after cardiac arrest using electroencephalogram epochs and outcome labels as inputs. Output of the network was the probability of good outcome. Data from two hospitals were used for training and internal validation (n = 661). Eighty percent of these data was used for training and cross-validation, the remaining 20% for independent internal validation. Data from the other three hospitals were used for external validation (n = 234). Prediction of poor outcome was most accurate at 12 hours, with a sensitivity in the external validation set of 58% (95% CI, 51-65%) at false positive rate of 0% (CI, 0-7%). Good outcome could be predicted at 12 hours with a sensitivity of 48% (CI, 45-51%) at a false positive rate of 5% (CI, 0-15%) in the external validation set. CONCLUSIONS: Deep learning of electroencephalogram signals outperforms any previously reported outcome predictor of coma after cardiac arrest, including visual electroencephalogram assessment by trained electroencephalogram experts. Our approach offers the potential for objective and real time, bedside insight in the neurologic prognosis of comatose patients after cardiac arrest.

Adenosine Kinase Deficiency in the Brain Results in Maladaptive Synaptic Plasticity.

Adenosine kinase (ADK) deficiency in human patients (OMIM:614300) disrupts the methionine cycle and triggers hypermethioninemia, hepatic encephalopathy, cognitive impairment, and seizures. To identify whether this neurological phenotype is intrinsically based on ADK deficiency in the brain or if it is secondary to liver dysfunction, we generated a mouse model with a brain-wide deletion of ADK by introducing a Nestin-Cre transgene into a line of conditional ADK deficient Adkfl/fl mice. These AdkΔbrain mice developed a progressive stress-induced seizure phenotype associated with spontaneous convulsive seizures and profound deficits in hippocampus-dependent learning and memory. Pharmacological, biochemical, and electrophysiological studies suggest enhanced adenosine levels around synapses resulting in an enhanced adenosine A1 receptor (A1R)-dependent protective tone despite lower expression levels of the receptor. Theta-burst-induced LTP was enhanced in the mutants and this was dependent on adenosine A2A receptor (A2AR) and tropomyosin-related kinase B signaling, suggesting increased activation of these receptors in synaptic plasticity phenomena. Accordingly, reducing adenosine A2A receptor activity in AdkΔbrain mice restored normal associative learning and contextual memory and attenuated seizure risk. We conclude that ADK deficiency in the brain triggers neuronal adaptation processes that lead to dysregulated synaptic plasticity, cognitive deficits, and increased seizure risk. Therefore, ADK mutations have an intrinsic effect on brain physiology and may present a genetic risk factor for the development of seizures and learning impairments. Furthermore, our data show that blocking A2AR activity therapeutically can attenuate neurological symptoms in ADK deficiency. SIGNIFICANCE STATEMENT: A novel human genetic condition (OMIM #614300) that is based on mutations in the adenosine kinase (Adk) gene has been discovered recently. Affected patients develop hepatic encephalopathy, seizures, and severe cognitive impairment. To model and understand the neurological phenotype of the human mutation, we generated a new conditional knock-out mouse with a brain-specific deletion of Adk (AdkΔbrain). Similar to ADK-deficient patients, AdkΔbrain mice develop seizures and cognitive deficits. We identified increased basal synaptic transmission and enhanced adenosine A2A receptor (A2AR)-dependent synaptic plasticity as the underlying mechanisms that govern these phenotypes. Our data show that neurological phenotypes in ADK-deficient patients are intrinsic to ADK deficiency in the brain and that blocking A2AR activity therapeutically can attenuate neurological symptoms in ADK deficiency.

Improved recovery of urinary small extracellular vesicles by differential ultracentrifugation.

Extracellular vesicles (EVs) are lipid-membrane enclosed structures that are associated with several diseases, including those of genitourinary tract. Urine contains EVs derived from urinary tract cells. Owing to its non-invasive collection, urine represents a promising source of biomarkers for genitourinary disorders, including cancer. The most used method for urinary EVs separation is differential ultracentrifugation (UC), but current protocols lead to a significant loss of EVs hampering its efficiency. Moreover, UC protocols are labor-intensive, further limiting clinical application. Herein, we sought to optimize an UC protocol, reducing the time spent and improving small EVs (SEVs) yield. By testing different ultracentrifugation times at 200,000g to pellet SEVs, we found that 48 min and 60 min enabled increased SEVs recovery compared to 25 min. A step for pelleting large EVs (LEVs) was also evaluated and compared with filtering of the urine supernatant. We found that urine supernatant filtering resulted in a 1.7-fold increase on SEVs recovery, whereas washing steps resulted in a 0.5 fold-decrease on SEVs yield. Globally, the optimized UC protocol was shown to be more time efficient, recovering higher numbers of SEVs than Exoquick-TC (EXO). Furthermore, the optimized UC protocol preserved RNA quality and quantity, while reducing SEVs separation time.

Ultrafast review of ambulatory EEGs with deep learning.

OBJECTIVE: Interictal epileptiform discharges (IED) are hallmark biomarkers of epilepsy which are typically detected through visual analysis. Deep learning has shown potential in automating IED detection, which could reduce the burden of visual analysis in clinical practice. This is particularly relevant for ambulatory electroencephalograms (EEGs), as these entail longer review times. METHODS: We applied a previously trained neural network to an independent dataset of 100 ambulatory EEGs (average duration 20.6 h). From these, 42 EEGs contained IEDs, 25 were abnormal without IEDs and 33 were normal. The algorithm flagged 2 second epochs that it considered IEDs. The EEGs were provided to an expert, who used NeuroCenter EEG to review the recordings. The expert concluded if each recording contained IEDs, and was timed during the process. RESULTS: The conclusion of the reviewer was the same as the EEG report in 97% of the recordings. Three EEGs contained IEDs that were not detected based on the flagged epochs. Review time for the 100 EEGs was approximately 4 h, with half of the recordings taking <2 minutes to review. CONCLUSIONS: Our network can be used to reduce time spent on visual analysis in the clinic by 50-75 times with high reliability. SIGNIFICANCE: Given the large time reduction potential and high success rate, this algorithm can be used in the clinic to aid in visual analysis.

The Secretome of Parental and Bone Metastatic Breast Cancer Elicits Distinct Effects in Human Osteoclast Activity after Activation of ß2 Adrenergic Signaling.

The sympathetic nervous system (SNS), particularly through the ß2 adrenergic receptor (ß2-AR), has been linked with breast cancer (BC) and the development of metastatic BC, specifically in the bone. Nevertheless, the potential clinical benefits of exploiting ß2-AR antagonists as a treatment for BC and bone loss-associated symptoms remain controversial. In this work, we show that, when compared to control individuals, the epinephrine levels in a cohort of BC patients are augmented in both earlier and late stages of the disease. Furthermore, through a combination of proteomic profiling and functional in vitro studies with human osteoclasts and osteoblasts, we demonstrate that paracrine signaling from parental BC under ß2-AR activation causes a robust decrease in human osteoclast differentiation and resorption activity, which is rescued in the presence of human osteoblasts. Conversely, metastatic bone tropic BC does not display this anti-osteoclastogenic effect. In conclusion, the observed changes in the proteomic profile of BC cells under ß-AR activation that take place after metastatic dissemination, together with clinical data on epinephrine levels in BC patients, provided new insights on the sympathetic control of breast cancer and its implications on osteoclastic bone resorption.

Stress in Metastatic Breast Cancer: To the Bone and Beyond.

Breast cancer (BRCA) remains as one the most prevalent cancers diagnosed in industrialised countries. Although the overall survival rate is high, the dissemination of BRCA cells to distant organs correlates with a significantly poor prognosis. This is due to the fact that there are no efficient therapeutic strategies designed to overcome the progression of the metastasis. Over the past decade, critical associations between stress and the prevalence of BRCA metastases were uncovered. Chronic stress and the concomitant sympathetic hyperactivation have been shown to accelerate the progression of the disease and the metastases incidence, specifically to the bone. In this review, we provide a summary of the sympathetic profile on BRCA. Additionally, the current knowledge regarding the sympathetic hyperactivity, and the underlying adrenergic signalling pathways, involved on the development of BRCA metastasis to distant organs (i.e., bone, lung, liver and brain) will be revealed. Since bone is a preferential target site for BRCA metastases, greater emphasis will be given to the contribution of α2- and ß-adrenergic signalling in BRCA bone tropism and the occurrence of osteolytic lesions.

Profiling the Adrenergic System in Breast Cancer and the Development of Metastasis.

Epidemiological studies and preclinical models suggest that chronic stress might accelerate breast cancer (BC) growth and the development of metastasis via sympathetic neural mechanisms. Nevertheless, the role of each adrenergic pathway (α1, α2, and ß) in human samples remains poorly depicted. Herein, we propose to characterize the profile of the sympathetic system (e.g., release of catecholamines, expression of catecholamine metabolic enzymes and adrenoreceptors) in BC patients, and ascertain its relevance in the development of distant metastasis. Our results demonstrated that BC patients exhibited increased plasma levels of catecholamines when compared with healthy donors, and this increase was more evident in BC patients with distant metastasis. Our analysis using the BC-TCGA database revealed that the genes coding the most expressed adrenoreceptors in breast tissues (ADRA2A, ADRA2C, and ADRB2, by order of expression) as well as the catecholamine synthesizing (PNMT) and degrading enzyme (MAO-A and MAO-B) genes were downregulated in BC tissues. Importantly, the expression of ADRA2A, ADRA2C, and ADRB2 was correlated with metastatic BC and BC subtypes, and thus the prognosis of the disease. Overall, we gathered evidence that under stressful conditions, both the α2- and ß2-signaling pathways might work on a synergetic matter, thus paving the way for the development of new therapeutic approaches.

The modulatory role of internet-supported mindfulness-based cognitive therapy on extracellular vesicles and psychological distress in people who have had cancer: a protocol for a two-armed randomized controlled study.

BACKGROUND: Mindfulness-based interventions (MBIs) have been used in oncology contexts as a promising tool with numerous benefits for various health-related and psychosocial outcomes. Despite the increasing popularity of MBIs, few randomized controlled trials (RCTs) have examined their effects upon biological parameters. Specifically, no previous study has examined the effects of MBIs on extracellular vesicles (EVs), which are potentially important markers of health, disease, and stress. Moreover, the lack of RCTs is even more limited within the context of technology-mediated MBIs and long-term effects. METHODS: The current study protocol presents a two-arm, parallel, randomized controlled study investigating the effects of internet-supported mindfulness-based cognitive therapy (MBCT) compared with treatment as usual (TAU). Primary outcomes are psychological distress and EV cargo of distressed participants with previous breast, colorectal, or prostate cancer diagnoses. Secondary outcomes are self-reported psychosocial and health-related measures, and additional biological markers. Outcomes will be assessed at baseline, 4 weeks after baseline (mid-point of the intervention), 8 weeks after baseline (immediately post-intervention), 24 weeks after baseline (after booster sessions), and 52 weeks after baseline. Our goal is to recruit at least 111 participants who have been diagnosed with breast, prostate, or colorectal cancer (cancer stage I to III), are between 18 and 65 years old, and have had primary cancer treatments completed between 3 months and 5 years ago. Half of the participants will be randomized to the TAU group, and the other half will participate in an 8-week online MBCT intervention with weekly group sessions via videoconference. The intervention also includes asynchronous homework, an online retreat after the fifth week, and 4 monthly booster sessions after completion of the 8-week programme. DISCUSSION: This study will allow characterizing the effects of internet-based MBCT on psychosocial and biological indicators in the context of cancer. The effects on circulating EVs will also be investigated, as a possible neurobiological pathway underlying mind-body intervention effects. TRIAL REGISTRATION: ClinicalTrials.gov NCT04727593 (date of registration: 27 January 2021; date of record verification: 6 October 2021).

Unexpected short- and long-term effects of chronic adolescent HU-210 exposure on emotional behavior.

Chronic adolescent cannabinoid receptor agonist exposure has been shown to lead to persistent increases in depressive-like behaviors. This has been a key obstacle to the development of cannabinoid-based therapeutics. However, most of the published work has been performed with only three compounds, namely Δ9-tetrahydrocannabinol, CP55,940 and WIN55,212-2. Hypothesizing that different compounds may lead to distinct outcomes, we herein used the highly potent CB1R/CB2R full agonist HU-210, and first aimed at replicating cannabinoid-induced long-lasting effects, by exposing adolescent female Sprague-Dawley rats to increasing doses of HU-210, for 11 days and testing them at adulthood, after a 30-day drug washout. Surprisingly, HU-210 did not significantly impact adult anxious- or depressive-like behaviors. We then tested whether chronic adolescent HU-210 treatment resulted in short-term (24h) alterations in depressive-like behavior. Remarkably, HU-210 treatment simultaneously induced marked antidepressant- and prodepressant-like responses, in the modified forced swim (mFST) and sucrose preference tests (SPT), respectively. Hypothesizing that mFST results were a misleading artifact of HU-210-induced behavioral hyperreactivity to stress, we assessed plasmatic noradrenaline and corticosterone levels, under basal conditions and following an acute swim-stress episode. Notably, we found that while HU-210 did not alter basal noradrenaline or corticosterone levels, it greatly augmented the stress-induced increase in both. Our results show that, contrary to previously studied cannabinoid receptor agonists, HU-210 does not induce persisting depressive-like alterations, despite inducing marked short-term increases in stress-induced reactivity. By showing that not all cannabinoid receptor agonists may induce long-term negative effects, these results hold significant relevance for the development of cannabinoid-based therapeutics.

Urinary Extracellular Vesicles as Potential Biomarkers for Urologic Cancers: An Overview of Current Methods and Advances.

Urologic cancers are a heterogeneous group of tumors, some of which have poor prognosis. This is partly due to the unavailability of specific and sensitive diagnostic techniques and monitoring tests, ideally non- or minimally invasive. Hence, liquid biopsies are promising tools that have been gaining significant attention over the last decade. Among the different classes of biomarkers that can be isolated from biofluids, urinary extracellular vesicles (uEVs) are a promising low-invasive source of biomarkers, with the potential to improve cancer diagnosis and disease management. Different techniques have been developed to isolate and characterize the cargo of these vesicles; however, no consensus has been reached, challenging the comparison among studies. This results in a vast number of studies portraying an extensive list of uEV-derived candidate biomarkers for urologic cancers, with the potential to improve clinical outcome; however, without significant validation. Herein, we review the current published research on miRNA and protein-derived uEV for prostate, bladder and kidney cancers, focusing on different uEV isolation methods, and its implications for biomarker studies.

Machine learning for detection of interictal epileptiform discharges.

The electroencephalogram (EEG) is a fundamental tool in the diagnosis and classification of epilepsy. In particular, Interictal Epileptiform Discharges (IEDs) reflect an increased likelihood of seizures and are routinely assessed by visual analysis of the EEG. Visual assessment is, however, time consuming and prone to subjectivity, leading to a high misdiagnosis rate and motivating the development of automated approaches. Research towards automating IED detection started 45 years ago. Approaches range from mimetic methods to deep learning techniques. We review different approaches to IED detection, discussing their performance and limitations. Traditional machine learning and deep learning methods have yielded the best results so far and their application in the field is still growing. Standardization of datasets and outcome measures is necessary to compare models more objectively and decide which should be implemented in a clinical setting.

Efficient use of clinical EEG data for deep learning in epilepsy.

OBJECTIVE: Automating detection of Interictal Epileptiform Discharges (IEDs) in electroencephalogram (EEG) recordings can reduce the time spent on visual analysis for the diagnosis of epilepsy. Deep learning has shown potential for this purpose, but the scarceness of expert annotated data creates a bottleneck in the process. METHODS: We used EEGs from 50 patients with focal epilepsy, 49 patients with generalized epilepsy (IEDs were visually labeled by experts) and 67 controls. The data was filtered, downsampled and cut into two second epochs. We increased the number of input samples containing IEDs through temporal shifting and using different montages. A VGG C convolutional neural network was trained to detect IEDs. RESULTS: Using the dataset with more samples, we reduced the false positive rate from 2.11 to 0.73 detections per minute at the intersection of sensitivity and specificity. Sensitivity increased from 63% to 96% at 99% specificity. The model became less sensitive to the position of the IED in the epoch and montage. CONCLUSIONS: Temporal shifting and use of different EEG montages improves performance of deep neural networks in IED detection. SIGNIFICANCE: Dataset augmentation can reduce the need for expert annotation, facilitating the training of neural networks, potentially leading to a fundamental shift in EEG analysis.

Rare Diseases of Neurodevelopment: Maintain the Mystery or Use a Dazzling Tool for Investigation? The Case of Rett Syndrome.

The investigation on neurotransmission function during normal and pathologic development is a pivotal component needed to understand the basic mechanisms underlying neurodevelopmental pathologies. To study these diseases, many animal models have been generated which allowed to face the limited availability of human tissues and, as a consequence, most of the electrophysiology has been performed on these models of diseases. On the other hand, the technique of membrane microtransplantation in Xenopus oocytes allows the study of human functional neurotransmitter receptors thanks to the use of tissues from autopsies or surgeries, even in quantities that would not permit other kinds of functional studies. In this short article, we intend to underline how this technique is well-fit for the study of rare diseases by characterizing the electrophysiological properties of GABAA and AMPA receptors in Rett syndrome. For our purposes, we used both tissues from Rett syndrome patients and Mecp2-null mice, a well validated murine model of the same disease, in order to strengthen the solidity of our results through the comparison of the two. Our findings retrace previous results and, in the light of this, further argue in favor of Prof. Miledi's technique of membrane microtransplantation that proves itself a very useful tool of investigation in the field of neurophysiology. This article is part of a Special Issue entitled: Honoring Ricardo Miledi - outstanding neuroscientist of XX-XXI centuries.