Fibroblast growth factor receptor 1 gene (FGFR1) amplification in non-small cell lung cancer (NSCLC) by real-time PCR.

Background: Comprehensive molecular assessment of cancers could open up new horizons for novel therapies. Fibroblast growth factor receptor 1 (FGFR1) gene amplification has been previously demonstrated in non-small cell lung cancer (NSCLC) patients. The current study aimed to evaluate the prevalence of FGFR1 gene amplification and its association with clinical and demographic data in a group of NSCLC patients.

Reliability of dynamic causal modelling of resting-state magnetoencephalography.

This study assesses the reliability of resting-state dynamic causal modelling (DCM) of magnetoencephalography (MEG) under conductance-based canonical microcircuit models, in terms of both posterior parameter estimates and model evidence. We use resting-state MEG data from two sessions, acquired 2 weeks apart, from a cohort with high between-subject variance arising from Alzheimer's disease. Our focus is not on the effect of disease, but on the reliability of the methods (as within-subject between-session agreement), which is crucial for future studies of disease progression and drug intervention.

Protective role of alpha-lipoic acid against rhabdomyolysis-induced acute kidney injury in rats.

Objectives: Rhabdomyolysis, a potentially life-threatening condition, occurs when myoglobin is released from damaged muscle cells, leading to acute kidney injury (AKI). Alpha lipoic acid (ALA), an organosulfur compound known for its anti-oxidant and anti-inflammatory properties, was examined in this study for its potential impact on rhabdomyolysis-induced AKI in rats.

Materials And Methods: Six groups of rats were included in the study, with each group consisting of six rats (n=6): Control, rhabdomyolysis, rhabdomyolysis treated with different doses of ALA (5, 10, and 20 mg/kg), and ALA alone (20 mg/kg) groups.

Primary Undifferentiated Pleomorphic Sarcoma of the Breast: A Case Report with Literature Review of Similar Cases.

Breast sarcoma is a rare but aggressive tumor. There are few case reports in the literature and several aspects of this disease are still not completely comprehended. Therefore, reporting new cases can help to enrich the literature.

Effect of verbascoside against acute kidney injury induced by rhabdomyolysis in rats.

Rhabdomyolysis is a pathological condition caused by muscle tissue degradation. In this condition, intracellular contents enter the bloodstream, and acute kidney injury (AKI) develops. Verbascoside (VB) is one of the most common phenylethanoid glycosides and has antioxidant and anti-inflammatory effects.

Renoprotective effect of thymoquinone against rhabdomyolysis-induced acute kidney injury in the rat model.

Objectives: Rhabdomyolysis leads to the release of myoglobin, sarcoplasmic proteins, and electrolytes into the blood circulation causing acute kidney injury (AKI). Thymoquinone, a natural compound found in seeds, has antioxidant and anti-inflammatory effects. This investigation assessed the renoprotective effect of thymoquinone on rhabdomyolysis-induced AKI in rats.

Recurrence of diffuse large B-cell lymphoma in sciatic and tibial nerves: A case report.

Infiltration of peripheral or cranial nerves with lymphatic cells is a rare condition that is known as neurolymphomatosis (NL). The involvement could be primary or secondary and mostly occurs in patients with a history of B-cell lymphoma. The most common peripheral nerve involved is the sciatic nerve.

Comparison of FNA-based conventional cytology specimens and digital image analysis in assessment of pancreatic lesions.

Objectives: Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is one of the most important diagnostic tools for investigation of suspected pancreatic masses, although the interpretation of the results is controversial. In recent decades, digital image analysis (DIA) has been considered in pathology. The aim of this study was to assess the DIA in the evaluation of EUS-FNA based cytopathological specimens of pancreatic masses and comparing it with conventional cytology analysis by pathologist.

Molecular Status of Mutation in Epithelial Ovarian Cancer: An Analysis of 57 Cases in the Northeast of Iran.

Background & Objective: Epithelial ovarian cancer (EOC) is the most prevalent type of ovarian cancer. Previous studies have elucidated different pathways for the progression of this malignancy. The mutation in the B-Raf proto-oncogene, serine/threonine kinase (BRAF) gene, a member of the MAPK/ERK signaling pathway, plays a role in the development of EOC.

Neurochemistry-enriched dynamic causal models of magnetoencephalography, using magnetic resonance spectroscopy.

We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters' concertation as empirical prior for synaptic physiology using ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography data (MEG). A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of individuals' neurophysiological observations. At the second level, individuals' 7T-MRS estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity.

Neurophysiological consequences of synapse loss in progressive supranuclear palsy.

Synaptic loss occurs early in many neurodegenerative diseases and contributes to cognitive impairment even in the absence of gross atrophy. Currently, for human disease there are few formal models to explain how cortical networks underlying cognition are affected by synaptic loss. We advocate that biophysical models of neurophysiology offer both a bridge from preclinical to clinical models of pathology and quantitative assays for experimental medicine.

Impact of DC-Coupled Electrophysiological Recordings for Translational Neuroscience: Case Study of Tracking Neural Dynamics in Rodent Models of Seizures.

We propose that to fully understand biological mechanisms underlying pathological brain activity with transitions (e.g., into and out of seizures), wide-bandwidth electrophysiological recordings are important.

Causal Evidence for the Multiple Demand Network in Change Detection: Auditory Mismatch Magnetoencephalography across Focal Neurodegenerative Diseases.

The multiple demand (MD) system is a network of fronto-parietal brain regions active during the organization and control of diverse cognitive operations. It has been argued that this activation may be a nonspecific signal of task difficulty. However, here we provide convergent evidence for a causal role for the MD network in the "simple task" of automatic auditory change detection, through the impairment of top-down control mechanisms.

Adiabatic dynamic causal modelling.

This technical note introduces adiabatic dynamic causal modelling, a method for inferring slow changes in biophysical parameters that control fluctuations of fast neuronal states. The application domain we have in mind is inferring slow changes in variables (e.g.

vmPFC Drives Hippocampal Processing during Autobiographical Memory Recall Regardless of Remoteness.

Our ability to recall past experiences, autobiographical memories (AMs), is crucial to cognition, endowing us with a sense of self and underwriting our capacity for autonomy. Traditional views assume that the hippocampus orchestrates event recall, whereas recent accounts propose that the ventromedial prefrontal cortex (vmPFC) instigates and coordinates hippocampal-dependent processes. Here we sought to characterize the dynamic interplay between the hippocampus and vmPFC during AM recall to adjudicate between these perspectives.

Comparing dynamic causal models of neurovascular coupling with fMRI and EEG/MEG.

This technical note presents a dynamic causal modelling (DCM) procedure for evaluating different models of neurovascular coupling in the human brain - using combined electromagnetic (M/EEG) and functional magnetic resonance imaging (fMRI) data. This procedure compares the evidence for biologically informed models of neurovascular coupling using Bayesian model comparison. First, fMRI data are used to localise regionally specific neuronal responses.

Bayesian fusion and multimodal DCM for EEG and fMRI.

This paper asks whether integrating multimodal EEG and fMRI data offers a better characterisation of functional brain architectures than either modality alone. This evaluation rests upon a dynamic causal model that generates both EEG and fMRI data from the same neuronal dynamics. We introduce the use of Bayesian fusion to provide informative (empirical) neuronal priors - derived from dynamic causal modelling (DCM) of EEG data - for subsequent DCM of fMRI data.

Identification of A Neural Mass Model of Burst Suppression.

Burst suppression includes alternating patterns of silent and fast spike activities in neuronal activities observable (in micro or macro scale) electro-physiological recordings. Biological models of burst suppression are given as dynamical systems with slow and fast states. The aim of this paper is to give a method to identify parameters of a mesoscopic model of burst suppression that can provide insights into study underlying generators of intracranial electroencephalogram (iEEG) data.

Slow-Fast Duffing Neural Mass Model.

Epileptic seizures may be initiated by random neuronal fluctuations and/or by pathological slow regulatory dynamics of ion currents. This paper presents extensions to the Jansen and Rit neural mass model (JRNMM) to replicate paroxysmal transitions in intracranial electroencephalogram (iEEG) recordings. First, the Duffing NMM (DNMM) is introduced to emulate stochastic generators of seizures.

Structure learning in coupled dynamical systems and dynamic causal modelling.

Identifying a coupled dynamical system out of many plausible candidates, each of which could serve as the underlying generator of some observed measurements, is a profoundly ill-posed problem that commonly arises when modelling real-world phenomena. In this review, we detail a set of statistical procedures for inferring the structure of nonlinear coupled dynamical systems (structure learning), which has proved useful in neuroscience research. A key focus here is the comparison of competing models of network architectures-and implicit coupling functions-in terms of their Bayesian model evidence.

A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI.

Dynamic Causal Modelling (DCM) is the predominant method for inferring effective connectivity from neuroimaging data. In the 15 years since its introduction, the neural models and statistical routines in DCM have developed in parallel, driven by the needs of researchers in cognitive and clinical neuroscience. In this guide, we step through an exemplar fMRI analysis in detail, reviewing the current implementation of DCM and demonstrating recent developments in group-level connectivity analysis.

A guide to group effective connectivity analysis, part 2: Second level analysis with PEB.

This paper provides a worked example of using Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB) to characterise inter-subject variability in neural circuitry (effective connectivity). It steps through an analysis in detail and provides a tutorial style explanation of the underlying theory and assumptions (i.e, priors).

Absence of FLT3 mutations in Iranian adult T-cell leukemia/lymphoma patients.

Adult T cell leukemia lymphoma (ATLL) is a rare disease, significantly linked to the infection by the human T-cell lymphotropic virus 1(HTLV-1). ATLL is typically preceded by decades of clinical latency during which infected cells accumulate selectable traits leading to a malignant transformation. Amongst all the HTLV-1 infected carriers only about 3-5% will develop ATLL.

Proteomics and phosphoproteomics analysis of liver in male rats exposed to bisphenol A: Mechanism of hepatotoxicity and biomarker discovery.

Bisphenol A (BPA), discovered to be an artificial estrogen, has been shown to leach from some containers and mediate oxidative damage to cells and tissues and to be involved in reproductive disorders, obesity, diabetes, and liver dysfunction. In the current study, we investigated the effects of oral chronic exposure to low dose of BPA (0.5 mg kg) on the protein and phosphoprotein expression profiles in male Wistar rat liver using a gel-based proteomics approach based on two-dimensional gel electrophoresis followed by matrix-assisted laser desorption/ionization mass spectrometry identification.

Histological Evaluation of the Effect of Platelet-rich Plasma on Pulp Regeneration in Nonvital Open Apex Teeth: An Animal Study.

Aim: Platelet-rich plasma (PRP), which is a concentration of growth factors found in platelets, may be a suitable material for pulp regeneration. The aim of this animal study was a histological evaluation of PRP on pulp regeneration in nonvital teeth with immature apices.

Materials And Methods: A total of 40 premolar dogs' teeth were chosen for this study.