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Biologically realistic computer simulations of neuronal circuits require systematic data-driven modeling of neuron type-specific synaptic activity. However, limited experimental yield, heterogeneous recordings conditions, and ambiguous neuronal identification have so far prevented the consistent characterization of synaptic signals for all connections of any neural system. We introduce a strategy to overcome these challenges and report a comprehensive synaptic quantification among all known neuron types of the hippocampal-entorhinal network. First, we reconstructed >2600 synaptic traces from ∼1200 publications into a unified computational representation of synaptic dynamics. We then trained a deep learning architecture with the resulting parameters, each annotated with detailed metadata such as recording method, solutions, and temperature. The model learned to predict the synaptic properties of all 3,120 circuit connections in arbitrary conditions with accuracy approaching the intrinsic experimental variability. Analysis of data normalized and completed with the deep learning model revealed that synaptic signals are controlled by few latent variables associated with specific molecular markers and interrelating conductance, decay time constant, and short-term plasticity. We freely release the tools and full dataset of unitary synaptic values in 32 covariate settings. Normalized synaptic data can be used in brain simulations, and to predict and test experimental hypothesis.

Byline: Keivan. Moradi, Esmaeil. Babaei, Mohammad. Hosseinpour Feizi, Reza. Safaralizadeh, Nayebali. Rezvani Background: In recent years, the study of potential epigenetic biomarkers in feces has been an attractive research approach [...]

Byline: Keivan. Moradi, Esmaeil. Babaei, Nayebali. Rezvani, Reza. Safaralizadeh, Homayoun. Bashiri, Mohammad. Feizi Background: Despite the advances in screening during the past decades, colorectal cancer (CRC) still is a leading [...]

Despite several studies performed in different provinces of Iran to identify the spectrum of α-globin gene mutations, no such study has so far been carried out in Ilam Province. A total of 274 individuals, including 201 α-thalassemia (α-thal) carriers and 73 normal subjects, originating from the northern counties of Ilam Province, participated in this study. Analysis of α-globin defects was performed using multiplex gap-polymerase chain reaction (gap-PCR), amplification refractory mutation system (ARMS)-PCR and direct sequencing, which revealed a total of 11 different mutations and 22 different genotypes. The –α3.7 (rightward) (NG_000006.1: g.34164_37967del3804), α−5 ntα (HBA2: c.95 + 2_95 + 6delTGAGG), and –α4.2 (leftward) deletions were the most prevalent mutations identified in our study, with frequencies of 66.23, 10.09 and 8.33%, respectively. In conclusion, the present study showed that the α-thal mutation spectrum in Ilam Province, at least in the northern part of the province, is different from that in other geographical regions of Iran. These results increase our knowledge about the spectrum and distribution of α-globin gene mutations in Iran. [ABSTRACT FROM AUTHOR]

Background: It is difficult to classify a small fraction of α- and β-thalassemia (α- and β-thal) carriers based on their Hb A2 levels. Here, we report the results of a molecular investigation in a cohort of thalassemia carriers with borderline Hb A2 levels originated from western Iran. Results: The documents of 5956 α- or β-thal carriers were reviewed. The frequency of individuals with borderline Hb A2 levels in this cohort was 436 (7.32%). A total of 12 different α-thal and 27 different β-thal variants were identified in this study. Conclusions: Our data showed that individuals with borderline Hb A2 are not uncommon in our population. Moreover, preselection of α- and β-thal carriers with borderline Hb A2 levels based on Hb A2, mean corpuscular volume (MCV), and mean cell hemoglobin (MCH) is not advisable in our population. Therefore, it is necessary to investigate both α- and β-globin genes in cases with borderline Hb A2 levels, especially if the partner is a carrier of β-thal or α0-thal. [ABSTRACT FROM AUTHOR]

Background: In recent years, the study of potential epigenetic biomarkers in feces has been an attractive research approach for the noninvasive diagnosis of colorectal cancer (CRC). The aim of this study was to evaluate the stool-based DNA methylation potential of SRY-Box 21 (SOX21) gene promoter as an appropriate candidate biomarker for differentiating CRC patients and healthy individuals for the first time.Methods: The MethyLight method was performed to analyze the methylation status of SOX21 gene promoter in fecal samples from 40 patients with CRC and 40 healthy controls. In addition, the diagnostic efficiency of measuring the hypermethylated SOX21 gene in the feces to the fecal occult blood test (FOBT) was compared.Results: The percentage of methylated reference (PMR) values in the stool of CRC patients (median 1.44) was higher than those of healthy individuals (median 0.00) (P < 0.001). A sensitivity of 72.5% and specificity of 100% were obtained for SOX21 gene promoter methylation status and 29 of the patients were considered as positive in methylation status. There was no significant association between PMR values and demographic/clinicopathological features (P > 0.05).Conclusion: The results of the present study demonstrated that the stool-based assay of SOX21 gene promoter methylation has a relatively high sensitivity and specificity and it may serve as a noninvasive biomarker for early detection of CRC. However, more studies with a wide range of samples are required to further confirm the role of hypermethylation of SOX21 in the early CRC diagnosis. [ABSTRACT FROM AUTHOR]

Background: Despite the advances in screening during the past decades, colorectal cancer (CRC) still is a leading cause of cancer deaths worldwide. Therefore, the development of new diagnostic methods is necessary.Aim: The aim of this study was to compare methylation changes of SRY-Box 21 (SOX21) gene promoter in tumor tissues and their normal adjacent mucosa in patients with CRC and to examine the relationship between the methylation levels and demographic/clinicopathological factors.Materials and Methods: A total of 41 CRC patients participated in the present study. After the extraction of DNA and bisulfite treatment of the samples, the methylation levels were determined by using the MethyLight method.Statistical Analysis: Two-sided Mann-Whitney U test was used to compare the median level of methylation in tumor tissues and their adjacent normal mucosa.Results: The methylation rates in tumor tissue samples were significantly higher compared to their adjacent normal mucosa (P < 0.0001). No association between demographic/clinicopathological factors and methylation status observed in tumor tissues. A receiver operating characteristics curve was constructed and tissue samples exhibited a sensitivity of 80.5% and specificity of 97.6% for SOX21 promoter methylation.Conclusion: The results of this study indicated the high potential of SOX21 gene promoter methylation as a candidate noninvasive diagnostic biomarker in stool and plasma of colorectal cancer patients. However, further studies with larger sample sizes are required to evaluate the specific role of SOX21 methylation as a biomarker for early detection of CRC. [ABSTRACT FROM AUTHOR]

The cellular and synaptic architecture of the rodent hippocampus has been described in thousands of peer‐reviewed publications. However, no human‐ or machine‐readable public catalog of synaptic electrophysiology data exists for this or any other neural system. Harnessing state‐of‐the‐art information technology, we have developed a cloud‐based toolset for identifying empirical evidence from the scientific literature pertaining to synaptic electrophysiology, for extracting the experimental data of interest, and for linking each entry to relevant text or figure excerpts. Mining more than 1,200 published journal articles, we have identified eight different signal modalities quantified by 90 different methods to measure synaptic amplitude, kinetics, and plasticity in hippocampal neurons. We have designed a data structure that both reflects the differences and maintains the existing relations among experimental modalities. Moreover, we mapped every annotated experiment to identified potential connections, that is, specific pairs of presynaptic and postsynaptic neuron types. To this aim, we leveraged Hippocampome.org, an open‐access knowledge base of morphologically, electrophysiologically, and molecularly characterized neuron types in the rodent hippocampal formation. Specifically, we have implemented a computational pipeline to systematically translate neuron type properties into formal queries in order to find all compatible potential connections. With this system, we have collected nearly 40,000 synaptic data entities covering 88% of the 3,120 potential connections in Hippocampome.org. Correcting membrane potentials with respect to liquid junction potentials significantly reduced the difference between theoretical and experimental reversal potentials, thereby enabling the accurate conversion of all synaptic amplitudes to conductance. This data set allows for large‐scale hypothesis testing of the general rules governing synaptic signals. To illustrate these applications, we confirmed several expected correlations between synaptic measurements and their covariates while suggesting previously unreported ones. We release all data open‐source at Hippocampome.org in order to further research across disciplines. [ABSTRACT FROM AUTHOR]

The author explains the mechanisms of cell coupling that act through changes in the small extracellular space of intercalated disks (ICD) which include electric field coupling, potassium (K) accumulation and capacitive coupling. Topics covered include the categories of cell coupling mechanisms in myocardial tissue and capacitive coupling simulation. The author also suggests a revision of the action potential propagation models based on the mixed excitatory effects of capacitive coupling.

In this article the authors discuss whether chaotic intermittency can explain the dynamics of bipolar disorder. According to the authors, the brain presents a large number of interacting neurons and synapses that form many feedback circuits; and these complex networks interact with the environment to produce temporally chaotic behavior which can be detected from individual nerve cells or neural ensembles.

Neuronal reconstruction-a process that transforms image volumes into 3D geometries and skeletons of cells- bottlenecks the study of brain function, connectomics and pathology. Domain scientists need exact and complete segmentations to study subtle topological differences. Existing methods are diskbound, dense-access, coupled, single-threaded, algorithmically unscalable and require manual cropping of small windows and proofreading of skeletons due to low topological accuracy. Designing a data-intensive parallel solution suited to a neurons' shape, topology and far-ranging connectivity is particularly challenging due to I/O and load-balance, yet by abstracting these vision tasks into strategically ordered specializations of search, we progressively lower memory by 4 orders of magnitude. This enables 1 mouse brain to be fully processed in-memory on a single server, at 67× the scale with 870× less memory while having 78% higher automated yield than APP2, the previous state of the art in performant reconstruction.