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Objective(s): 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. Rhabdomyolysis was induced by intramuscular injection of glycerol on the first day of the experiment, while ALA was administered intraperitoneally for four consecutive days. Renal function parameters, oxidative stress markers, and histological changes in the kidneys were evaluated. Western blot analysis was performed to measure the levels of neutrophil gelatinase-associated lipocalin (NGAL) and tumor necrosis factor-alpha (TNF-α) proteins.Results: A significant increase in serum urea, creatinine, renal malondialdehyde, NGAl, and TNF-α protein levels was observed in glycerol-injected rats. In addition, a significant decrease in glutathione was recorded. Compared to the rhabdomyolysis group, treatment with ALA recovered kidney histological and biochemical abnormalities. Conclusion: Results suggest that rhabdomyolysis-induced AKI is associated with increased oxidative stress and inflammation. Treatment with ALA improved kidney histological abnormalities and reduced oxidative stress markers in rats. Therefore, ALA may have a potential protective effect against rhabdomyolysis-induced AKI.

Objective(s): 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 Nigella sativa seeds, has antioxidant and anti-inflammatory effects. This investigation assessed the renoprotective effect of thymoquinone on rhabdomyolysis-induced AKI in rats.Materials and Methods: Male Wistar rats were categorized into six groups (n = 6): 1. Control: (normal saline), 2. Glycerol (50 ml/kg, single dose, IM), 3–5: Glycerol + thymoquinone (1, 2.5 and 5 mg/kg, 4 days, IP), 6. Thymoquinone (5 mg/kg). On day 5, serum and kidney tissue were isolated and the amounts of serum creatinine and blood urea nitrogen (BUN), renal malondialdehyde (MDA), glutathione (GSH.), tumor necrosis factor-alpha (TNF-α), neutrophil gelatinase-associated lipocalin (NGAL), and pathological changes were evaluated. Results: Glycerol increased creatinine, BUN, MDA, TNF-α, and NGAL levels. It decreased GSH amounts and caused renal tubular necrosis, glomerular atrophy, and myoglobin cast in kidney tissue. Co-administration of glycerol and thymoquinone reduced creatinine, BUN, histopathological alterations, and MDA levels, and enhanced GSH amounts. Administration of glycerol and thymoquinone (5 mg/kg) had no significant effect on TNF-α amount but decreased NGAL protein levels. The administration of thymoquinone (5 mg/kg) alone did not display a significant difference from the control group.Conclusion: Rhabdomyolysis from glycerol injection in rats can cause kidney damage. Thymoquinone may attenuate renal dysfunction and oxidative stress. However, the TNF-α level was not significantly affected. Further studies are needed to explore the potential therapeutic effects of thymoquinone in managing AKI.

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. Patients may present with painful or painless mononeuropathy or polyneuropathy, and MRI is the perfect modality to evaluate the suspicious clinical findings that may demonstrate enlargement, thickening, and enhancement of the involved nerve or an enhancing mass lesion in the course of the nerve. Biopsy can be safely performed to confirm the diagnosis. Few articles have reported the cases of peripheral nerve involvement by lymphoma as well as MRI features of this diagnosis. In this article, we report a case of NL using MRI, ultrasound, and pathologic features and also present a brief review of relevant literature.

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. We compare the group-wise evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction (BMR), parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare alternative model evidence of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the subset of synaptic connections that are influenced by individual differences in neurotransmitter levels, as measured by 7T-MRS. We demonstrate the method using resting-state MEG (i.e., task-free recording) and 7T-MRS data from healthy adults. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. Using within-subject split-sampling of the MEG dataset (i.e., validation by means of a held-out dataset), we show that model comparison for hypothesis testing can be highly reliable. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to reveal the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions.

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. We demonstrate the importance of ultraslow potential shifts and infraslow oscillations for reliable tracking of synaptic physiology, within a neural mass model, from brain recordings that undergo pathological phase transitions. We use wide-bandwidth data (direct current (DC) to high-frequency activity), recorded using epidural and penetrating graphene micro-transistor arrays in a rodent model of acute seizures. Using this technological approach, we capture the dynamics of infraslow changes that contribute to seizure initiation (active pre-seizure DC shifts) and progression (passive DC shifts). By employing a continuous–discrete unscented Kalman filter, we track biological mechanisms from full-bandwidth data with and without active pre-seizure DC shifts during paroxysmal transitions. We then apply the same methodological approach for tracking the same parameters after application of high-pass-filtering >0.3Hz to both data sets. This approach reveals that ultraslow potential shifts play a fundamental role in the transition to seizure, and the use of high-pass-filtered data results in the loss of key information in regard to seizure onset and termination dynamics.

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., extracellular ion concentrations or synaptic efficacy) that underlie phase transitions in brain activity (e.g., paroxysmal seizure activity). The scheme is efficient and yet retains a biophysical interpretation, in virtue of being based on established neural mass models that are equipped with a slow dynamic on the parameters (such as synaptic rate constants or effective connectivity). In brief, we use an adiabatic approximation to summarise fast fluctuations in hidden neuronal states (and their expression in sensors) in terms of their second order statistics; namely, their complex cross spectra. This allows one to specify and compare models of slowly changing parameters (using Bayesian model reduction) that generate a sequence of empirical cross spectra of electrophysiological recordings. Crucially, we use the slow fluctuations in the spectral power of neuronal activity as empirical priors on changes in synaptic parameters. This introduces a circular causality, in which synaptic parameters underwrite fast neuronal activity that, in turn, induces activity-dependent plasticity in synaptic parameters. In this foundational paper, we describe the underlying model, establish its face validity using simulations and provide an illustrative application to a chemoconvulsant animal model of seizure activity.

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. The coordinates of these responses are then used as the location priors in a DCM of electrophysiological responses elicited by the same paradigm. The ensuing estimates of model parameters are then used to generate neuronal drive functions, which model pre- or post-synaptic activity for each experimental condition. These functions form the input to a model of neurovascular coupling, whose parameters are estimated from the fMRI data. Crucially, this enables one to evaluate different models of neurovascular coupling, using Bayesian model comparison – asking, for example, whether instantaneous or delayed, pre- or post-synaptic signals mediate haemodynamic responses. We provide an illustrative application of the procedure using a single-subject auditory fMRI and MEG dataset. The code and exemplar data accompanying this technical note are available through the statistical parametric mapping (SPM) software.

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. To illustrate this procedure, we generated synthetic EEG and fMRI timeseries for a mismatch negativity (or auditory oddball) paradigm, using biologically plausible model parameters (i.e., posterior expectations from a DCM of empirical, open access, EEG data). Using model inversion, we found that Bayesian fusion provided a substantial improvement in marginal likelihood or model evidence, indicating a more efficient estimation of model parameters, in relation to inverting fMRI data alone. We quantified the benefits of multimodal fusion with the information gain pertaining to neuronal and haemodynamic parameters – as measured by the Kullback-Leibler divergence between their prior and posterior densities. Remarkably, this analysis suggested that EEG data can improve estimates of haemodynamic parameters; thereby furnishing proof-of-principle that Bayesian fusion of EEG and fMRI is necessary to resolve conditional dependencies between neuronal and haemodynamic estimators. These results suggest that Bayesian fusion may offer a useful approach that exploits the complementary temporal (EEG) and spatial (fMRI) precision of different data modalities. We envisage the procedure could be applied to any multimodal dataset that can be explained by a DCM with a common neuronal parameterisation.

Introduction: Malignant salivary gland tumors are rare entities. Despite advances in surgery, radiation therapy and chemotherapy, the rate of the mortality and five-year survival has not been improved markedly over the last few decades. The activation of EGFR- RAS-RAF signaling pathway contributes to the initiation and progression of many human cancers, promising a key pathway for therapeutic molecules. Thus, the objective of this study was to evaluate BRAF mutations in salivary gland carcinomas. Methods: We designed PCR- RFLP (Polymerase Chain Reaction -Restriction Fragment Length Polymorphism) and screened 50 salivary gland carcinomas (SGCs) including mucoepidermoid carcinoma (MEC), adenoid cystic carcinoma (AdCC) and polymorphous low grade adenocarcinoma (PLGA) for the BRAF V600E mutation. Results: PCR-RFLP analyses demonstrated no mutation in BRAF exon 15 for SGC samples at position V600, which is the most commonly mutated site for BRAF in human cancer. Conclusions: According to our results SGCs didn’t acquire BRAF mutations that result in a constitutive activation of the signaling cascade downstream of EGFR, hence SGCs can be a good candidate for anti EGFR therapies.

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. Methods: The present study was performed on eighty-eight NSCLC patients who underwent bronchoscopy or surgery in Qaem Hospital, Mashhad, between 2010 and 2016. FGFR1 gene amplification was detected using real-time PCR assay on DNA extracted from paraffin-embedded tissue blocks of patients. Also, patients' clinical and demographic data, such as their survival, were evaluated. Statistical analysis was carried out using SPSS software. Results: Seventeen (19.31%) out of eighty-eight patients with NSCLC presented FGFR1 gene amplification. Besides, we found a significant association between FGFR1 amplification and cigarette smoking (p-value= 0.01; OR: 4.08). Although cases with squamous cell carcinoma (SCC) showed a higher prevalence of FGFR1 amplification compared to adenocarcinoma patients, the difference was not statistically significant (p-value> 0.05). In addition, our findings showed no relationship between FGFR1 gene amplification and other clinical and demographic factors, including age, sex, grade, tumor operability, and survival. Conclusion: The frequency of FGFR1 amplification is estimated at 20% in the current study (26% in SCC versus 11% in adenocarcinoma; p-value= 0.07). Moreover, we found a direct association between FGFR1 amplification and cigarette smoking. However, no significant relationship with survival or other factors was observed.

Background: Colorectal cancer, the third most common type of cancer is a major cause of mortality worldwide. If colorectal cancer is detected at the early stages, the 5-year survival rate is 90%. MEIS1 homeobox gene is implicated in numerous solid tumors and hematological malignancies. Therefore, the present study aims to investigate the methylation status of the MEIS1 gene in colorectal cancer. Methods: We used real-time quantitative methylation-specific PCR to detect MEIS1 promoter methylation in 42 colorectal cancer tissues and 42 normal colorectal tissues. Results: Methylation was observed only in the positive control samples - CG Genome Universal Unmethylated DNA and CG Genome Universal Methylated DNA. There was no change observed in MEIS1 promoter methylation status in 42 patients. Conclusion: The results of the current study indicated that the MEIS1 gene promoter was not methylated in the cases. Gene expression study confirmed the unmethylated status of the MEIS1 gene in the colorectal cancer process among the studied population.

Background: Swyer syndrome is a type of hypogonadism with 46,XY karyotype. This syndrome was named by Gerald Swyer, an endocrinologist. It leads to a female with normal internal genitalia (uterus, fallopian tubes, cervix, vagina), but instead of ovaries, they have non functional ovary (streak gonads). Also, they have absence of puberty because of gonadal digenesis. The current practice is to proceed gonadectomy once the diagnosis is made due to the fact that the risk of malignant transformation is high in dysgenetic gonad. In addition, hormonal replacement therapy after surgery is acceptable. Case Presentation: We present a case of gonadoblastom in right ovary in a Swyer syndrome who referred to the department of Gynecology Oncology at Ghaem Hospital, Mashhad University, Iran in 2015 for evaluation of abdomino-pelvic distention. She was a 18-year-old female with 46, XY karyotype and poor secondary sexual character and normal external genitalia. She suffered of abdominal pain. In palpation of the abdomen, an irregular mobile mass was detected in left lower quadrant. The ultrasound revealed uterine size approximate dimensions 3×2 cm (infantile) and a 19 cm pelvic mass heterogeneous and multi-loculated in left side of the pelvic cavity with possible origin of the left ovary. In addition, in right pelvic fossa, a mass about 6 cm was detected. CT-Scan showed a pelvic mass with overall dimensions of 10 cm with vicinity to the left iliac vessels, modest amounts of ascities along with evidence of peritoneal dissemination (seeding). In laparotomy we observed massive ascities and a 20 cm solid mass in left ovary and a small mass in right ovary and involvement para aortic lymph node. Pathological report indicated as stage III of dysgerminoma in left ovary and gonadoblastom in right ovary. Conclusion: This case is presented because it could have excellent prognosis if not missed opportunities of early recognizing and furthermore adequate treatment with gonadectomy.

Background and Objective: Dental implants, as one of the most frequently used medical prostheses, are widely utilized as a replacement for the lost teeth in dentistry, which can provide the patients with comfort and utility in mastication and digestion purposes. However, there is a demanding requirement for the implant mechanical quality improvements carried out by optimizing the implant size and material characteristics. The improvements made to the design variables of a dental implant can benefit the supporting bone viability and reduce the risk of bone injury and loosening implants. Therefore, the purpose of the present finite element-based study was to optimize the design variables of an implant screw in a geometrically developed implant-mandible assembly for minimizing the resultant difference of the maximum equivalent strain value in the mandible to an as possible admissible, safe limit compared with pre-implantation state, based on the Mechanostat Theory. The usage of the Mechanostat Theory as the criterion for which the difference of mandible maximum equivalent strain value after implantation was considered as an objective function to be minimized from before-implantation state, was newly addressed in this study. Methods: In order to form the 3D geometry of the mandible, a patient-specific CT image dataset was used, and a 3D model of a dental implant with relevant parts was extracted based on a literature design, after which the assembly of the mandible and implant was imported to a finite element software to analyze the biomechanical behavior of the mandible bone under a mechanical pressure load exerted on the implant crown, as the mastication equivalence. The same procedure was conducted for importing the 2nd premolar tooth geometry with the same boundary conditions of the mandible to compare the results. Results: The results indicated that there was 50.2% decline in the maximum equivalent strain difference from 44.2 με to 22.2 με as the consequence of the optimized sizes of the implant screw length and radius. Furthermore, there was a sensible amount of sensitivity for the maximum equivalent strain to the alterations in the screw radius rather than length. Conclusions: Finally, the proposed, optimized geometry for the implant screw improved the baseline design and provided a useful basis for further research.