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"nBackground: Langerhans cell histiocytosis (LCH) is a group of idiopathic disorders characterized by the proliferation of specialized bone marrow-derived Langerhans cells and mature eosinophils. The estimated annual incidence ranges from 0.5-2 cases per 100,000 persons per year. The pathogenesis of LCH is unknown. The prevalence of LCH seems to be higher among whites and males. The most common complaints at presentation are those related to bone lesions. Treatment consists of surgery, chemotherapy and radiotherapy alone or in combination. The age of onset varies according to the variety of LCH. Solitary lesions may occur in bones or skin. Cutaneous lesions present with firm, painless papulonodules or vesicles. "nCase report: This six-month-old baby presented with firm papulonodules on her temporal skin, but fortunately her other organs were healthy. She underwent two surgeries, separated by a one-month interval. Due to local recurrence after a short period of time, she underwent a 10-Gy dose of radiation. Her response proved good during follow-up. "nConclusion: Radiotherapy is good for controlling local recurrence in LCH, with few sequelae related to treatment.

Background: Mucositis [bucal Mucous inflamation] is the most common complication resulting from the radiotherapy in tumors of head and neck. These malignancies are often curable through radiotherapy. This complication, however, may impair the treatment process and cause malnutrition. So far no medicine has been Known to prevent this complication. Vitamin E is a stabilizer of cell membrane and is also used in mucositis treatment. The survey of oral vitamin E effect on mucositis prophylaxis in radiotherapy of head and neck malignancies. Materials and Methods: Seventy patients afflicted with head and neck malignancies referring to Imam Khomeini Hospital were randomly divided into 2groups, two of whom died during treatment process. The first group (The case group consisting of 34 patients) Consumed oral vitamin E 200 mg daily for seven days. The second group (The control group) did not use any medicine at all. The two group underwent radiotherapy. They were compared and contrasted as to mucositis severity and dysphagia during treatment. Results: In the first group, since the fourth week up to the end of the treatment, there was a lower frequency and grade of mucositis in contrast with the control group. In the fourth week, the grade two mucositis in the first group (Case group) was 20.6% and 47.5% in the control group the difference was statistically significant (P=0.024). There was also a lower frequency and grade of dysphagia in the case group since the fourth week versus the control group. In the fourth week, moderate dysphagia was 29.4% in the case group and 55.9% in the control group. The difference was statistically significant (P=0.023). Conclusion: Oral vitamin E has Proved to be effective in the Prophylaxis of Moderate and severe mucositis and dysphagia resulting from radiotherapy. It is advisable to conduct more research with more cases, lengthier duration and heavier doses.

Abstract Artificial intelligence computing adapted from biology is a suitable platform for the development of intelligent machines by imitating the functional mechanisms of the nervous system in creating high-level activities such as learning, decision making and cognition in today's systems. Here, the concentration is on improvement the cognitive potential of artificial intelligence network with a bio-inspired structure. In this regard, four spiking pattern recognition platforms for recognizing digits and letters of EMNIST, patterns of YALE, and ORL datasets are proposed. All networks are developed based on a similar structure in the input image coding, model of neurons (pyramidal neurons and interneurons) and synapses (excitatory AMPA and inhibitory GABA currents), and learning procedure. Networks 1–4 are trained on Digits, Letters, faces of YALE and ORL, respectively, with the proposed un-supervised, spatial–temporal, and sparse spike-based learning mechanism based on the biological observation of the brain learning. When the networks have reached the highest recognition accuracy in the relevant patterns, the main goal of the article, which is to achieve high-performance pattern recognition system with higher cognitive ability, is followed. The pattern recognition network that is able to detect the combination of multiple patterns which called intertwined patterns has not been discussed yet. Therefore, by integrating four trained spiking pattern recognition platforms in one system configuration, we are able to recognize intertwined patterns. These results are presented for the first time and could be the pioneer of a new generation of pattern recognition networks with a significant ability in smart machines.

Background: Patients with chronic liver failure (CLF) faced serious medical conditions including the oral cavity. Objective: To investigate the prevalence of oral mucosal lesions, saliva flow rate, and dental complications in candidates of liver transplant surgery. Methods: In this cross-sectional study, oral and dental health of 77 patients with CLF and 77 healthy individuals were assessed for oral mucosal lesions, salivation rate, DMFT (decayed, missing, filled teeth) index, and bone level. To carefully determine the indices and examine the patients thoroughly, a panoramic radiography was also taken from each participant. Results: The frequency of oral mucosal lesions in patients was significantly (p<0.001) higher than the comparison group. The most frequent lesion identified was angular cheilitis followed by candidiasis. The mean saliva flow rate in the patients (0.85 g/min) was also significantly (p<0.001) lesser than that in healthy individuals (1.58 g/min). The DMFT index and bone level were not significantly different between the two groups. Nor was a correlation between the MELD score and each of DMFT index, bone loss, or oral mucosal lesions. Conclusion: Mucosal lesions, especially fungal-related lesions, are more prevalent in the oral cavity of patients with CLF. The saliva production rate is reduced due to various medications used in this group. Patients with CLF are prone to oral infections and a thorough oro-dental examination is crucial in this group of patients. Vigorous oral hygiene instructions should be offered to liver cirrhosis individuals. [ABSTRACT FROM AUTHOR]

Purpose: Utilizing Electroencephalogram (EEG) is more than at any time in history, therefore we have introduced an open-source MATLAB function to provide simulated EEG which is as equivalent as viable to empirical EEG in a user-friendly way with ground truth that is not accessible in real EEG records. This function should be versatile due to the requirements such as the number and orientation of sources, various noises, mode of activation function, and different anatomical structures. Materials and Methods: We indicate all phases, modes, and formulas which constitute EEGg, EEG generator. This function supports selecting main sources locations and orientation, choosing SNR with white Gaussian noise, electrode numbers, and mode of activation functions. Also, users have the option to use automatic or partly automatic, or fully automatic EEG construction in EEGg. This function is ready to use at https://github.com/Avayekta/EEG. Results: EEGg is designed with several parameters that users have chosen. Hence, users can choose different variables to inspect the time and frequency aspects of synthetic EEG. Conclusion: EEGg is a multi-purpose and comprehensive function to mimic EEG but with ground-truth EEG data and adjustable parameters.

Background:Pseudomonas aeruginosa is the most common microorganism found in the sputum culture of Cystic fibrosis (CF) patients causing the pulmonary destruction. Aminoglycosides have a low diffuse rate from lipid membranes, and respiratory system secretions. Regarding the burden of pulmonary exacerbation caused by the pseudomonas aeruginosa in cystic fibrosis patients in the long term and the limited number of clinical trials focused on appropriate treatment strategies, the present study evaluated the concurrent inhaled and intravenous aminoglycoside antibiotics for pulmonary exacerbation caused by the pseudomonas aeruginosa as a safe and effective treatment in children.Method: This study was a blinded, randomized clinical trial phase conducted in a tertiary referral pediatric teaching hospital from May 2021 to May 2022. The patients were randomly allocated to receive intravenously administered ceftazidime and Amikacin alone or with inhaled Amikacin. Forced expiratory volume (FEV1), Amikacin via the level, kidney function tests, audiometry, inflammatory markers (erythrocyte sedimentation rate and C-reactive protein), hospital stay, and bacterial eradication rate were compared in two therapy groups.Results: the average FEV1 has increased by 47% in Neb + group compared to Neb− group following treatment. Hospital stay was lower in Neb + group. No renal toxicity or ototoxicity was observed in both therapy groups. Pseudomonas aeruginosa eradication rate Neb− and Neb + groups were 44% and 69%, respectively (p-value = 0.15).Conclusion: Concurrent inhaled and intravenous Amikacin is safe and effective to treat Pseudomonas aeruginosa exacerbation in CF patients. Moreover, co-delivery antibiotics’ route treatment increased the eradication rate. Although not statistically significant, never the less, it is clinically relevant. The intervention reduced the length of hospitalization in this group.Clinical Trial Registration:clinicaltrials.gov, identifier [IRCT20120415009475N10].

Background: The bidirectional brain-machine interfaces algorithms are machines that decode neural response in order to control the external device and encode position of artificial limb to proper electrical stimulation, so that the interface between brain and machine closes. Most BMI researchers typically consider four basic elements: recording technology to extract brain activity, decoding algorithm to translate brain activity to the predicted movement of the external device, external device (prosthetic limb such as a robotic arm), and encoding interface to convert the motion of the external machine to set of the electrical stimulation of the brain. New method: In this paper, we develop a novel approach for bidirectional brain-machine interface (BMI). First, we propose a neural network model for sensory cortex (S1) connected to the neural network model of motor cortex (M1) considering the topographic mapping between S1 and M1. We use 4-box model in S1 and 4-box in M1 so that each box contains 500 neurons. Individual boxes include inhibitory and excitatory neurons and synapses. Next, we develop a new BMI algorithm based on neural activity. The main concept of this BMI algorithm is to close the loop between brain and mechaical external device. Results: The sensory interface as encoding algorithm convert the location of the external device (artificial limb) into the electrical stimulation which excite the S1 model. The motor interface as decoding algorithm convert neural recordings from the M1 model into a force which causes the movement of the external device. We present the simulation results for the on line BMI which means that there is a real time information exchange between 9 boxes and 4 boxes of S1-M1 network model and the external device. Also, off line information exchange between brain of five anesthetized rats and externnal device was performed. The proposed BMI algorithm has succeeded in controlling the movement of the mechanical arm towards the target area on simulation and experimental data, so that the BMI algorithm shows acceptable WTPE and the average number of iterations of the algorithm in reaching artificial limb to the target region.Comparison with existing methods and Conclusions: In order to confirm the simulation results the 9-box model of S1-M1 network was developed and the valid “spike train” algorithm, which has good results on real data, is used to compare the performance accuracy of the proposed BMI algorithm versus “spike train” algorithm on simulation and off line experimental data of anesthetized rats. Quantitative and qualitative results confirm the proper performance of the proposed algorithm compared to algorithm “spike train” on simulations and experimental data.

Purpose: A new code based on Helmholtz decomposition is presented to separate longitudinal (pressure) and transverse (shear) components of a mixed wave field. This algorithm will help isolate shear or pressure components of an elastic wave to further concentrate on each specific wave and its physical characteristics, particularly in medical imaging instrument development and image processing techniques. Materials and Methods: Using the combination of Fourier transform and Helmholtz decomposition, first, the mathematical basis of the work is prepared. After reaching a usable formula, this basis is embedded in the Code written in MATLAB program. Then, various test data containing shear and pressure waves were created and fed to the Code to evaluate its ability to decompose the displacements into the shear and pressure waves. Results: This new algorithm successfully isolated the transverse and longitudinal wavefront of the mixed wavefield. The Code demonstrated 100% accuracy for separating the shear wave and more than 99% for the pressure wave. Moreover, the background noise was kept under 0.03% in every step. Conclusion: The results show that using Helmholtz decomposition in Fourier space on 3D data can help decompose a displacement field into its irrotational and solenoidal components with high accuracy. A weak dependency on wave thickness and contrast was observed, but the algorithm's accuracy never fell below 99%.

Background and Importance: Fracture-dislocation of the thoracic or lumbar spine (traumatic spondyloptosis) occurs in less than 5% of all spinal injuries mainly affecting the ventral direction. Case Presentation: A paraplegic young man was admitted to Shahid Kamyab Hospital in Mashhad City, Iran due to a motor vehicle accident. Computerized tomography (CT) showed a complete posterior dislocation of the T10 vertebral body on T9, with the superior articular processes of T9 bilaterally locked in the inferior endplate of T10 and complete fractures of the posterior elements. Conclusion: The spinal dislocation was re-aligned by a combination of Harrington fixation and pedicular screws leading to spinal fusion. Six months after surgery, the patient was still paraplegic but the sensory symptoms in the lower extremities and clean intermittent catheterization improved.

Elastography is an imaging technique with the ability to determine low quantities of some of the mechanical properties of tissues. The aim of our research is to design a new 3D algorithm using the Shifted Fourier Transform (SFT) to perform a quasi-static elastography. Our innovative idea is implementation of a 3D convolution instead of using three 2D convulsions. At first, we collected the raw data from Abaqus engineering software in the form of breast tissue with a coefficient of elasticity of healthy tissue and tumor tissue with a coefficient of elasticity of tumor tissue. The primary raw data consists of a number of points with x, y and z specified for tumor and healthy breast tissue. At this step, we simulated the displacements in directions of x, y and z at each point of the prescribed tissues for 15 ​mm displacement of probe in –Y direction then we collected 1831 points for tumor and 4186 points for breast before and after pressure. After applying a novel reconstruction algorithm, we convolved all images with the 3D Gabor filters to obtain phases, represented displacements of the breast and tumor images for before and after pressure. To reach this goal, we designed a Gabor filter bank based on the dimensions of the input images in different scales, directions, and deviations. Using the 3D SFT, we calculated the displacements of the breast and tumor tissues followed by 3D elastogram representation of the images. Finally, we implemented a 2D analysis of SFT in order to investigate validation of the 3D SFT. In 2D algorithm, we used three two-dimensional convulsions in XY, YZ and XZ planes. The results obtained from the small displacements marked by circles, confirmed the accuracy of the 3D SFT algorithm. These areas of interest are the tumor areas in the 2D analysis.

PurposeVentilator-Associated Pneumonia (VAP) is one of the most common nosocomial infections in the Pediatric Intensive Care Unit (PICU). Using new strategies to prevent nosocomial infections is crucial to avoid antibiotic resistance. One of these strategies is the utilization of probiotics. This study aims to investigate the efficacy of probiotic prophylaxis in preventing VAP in mechanically ventilated children.MethodThis study was a randomized, double-blind clinical trial. The study included 72 children under 12 years of age under mechanical ventilation for more than 48 h in the Mofid Children's Hospital. Patients were randomly divided into Limosilactobacillus reuteri DSM 17938 probiotic recipients (n = 38) and placebo groups (n = 34). In addition to the standard treatment, both groups received a sachet containing probiotics or a placebo twice a day. Children were screened for VAP based on clinical and laboratory evidence.ResultsThe mean age of children in the intervention and placebo groups was 4.60 ± 4.84 and 3.38 ± 3.49 years, respectively. After adjusting the other variables, it was observed that chance of VAP among probiotics compared to the placebo group was significantly decreased (OR adjusted = 0.29; 95% CI: 0.09–0.95). Also, probiotic was associated with a significantly lower chance of diarrhea than the placebo group (OR adjusted = 0.09; 95% CI: 0.01–0.96).ConclusionProbiotic utilization is effective in preventing the incidence of VAP and diarrhea in children under mechanical ventilation in the PICU.

Background: Hospitalized infants and children are usually treated with many medications in the hospital. Concurrent use of multiple drugs, known as polypharmacy, is inevitable in critically ill patients. This study aims to investigate the possible interactions as well as their type and number, and their effect on the treatment process plus the duration of hospital stay of patients. Methods: In this descriptive study, the medical records of 189 patients admitted to the ICU ward of Mofid Children's Educational Hospital in Tehran were prospectively studied over six months. The collected data included disease diagnosis, patient medication information, age and gender, and treatment interventions. Interactions between drugs were identified using Up-to-date database, with the results analyzed by SPSS software. Results: The results revealed that hospitalization increased with an increasing number of drugs. The findings also indicated a direct relationship between the number of drug interactions and the duration of hospital stay. After examining the relationship between intensive care unit (ICU) outcome and the number of drug items as well as the number of drug interactions, it was found that there is a direct relationship between the two. There was also a direct relationship between Class D plus X interactions and mortality rate along with duration of stay. Conclusion: This study showed a direct relationship between drug interactions and the duration of hospitalization. In other words, as drug interactions increased, so did the duration of hospital stay.

Background: Brain source imaging based on electroencephalogram (EEG) data aims to recover the neuron populations’ activity producing the scalp potentials. This procedure is known as the EEG inverse problem. Recently, beamformers have gained a lot of consideration in the EEG inverse problem. Objective: Beamformers lack acceptable performance in the case of correlated brain sources. These sources happen when some regions of the brain have simultaneous or correlated activities such as auditory stimulation or moving left and right extremities of the body at the same time. In this paper, we have developed a multichannel beamformer robust to correlated sources. Material and Methods: In this simulation study, we have looked at the problem of brain source imaging and beamforming from a blind source separation point of view. We focused on the spatially constraint independent component analysis (scICA) algorithm, which generally benefits from the pre-known partial information of mixing matrix, and modified the steps of the algorithm in a way that makes it more robust to correlated sources. We called the modified scICA algorithm Multichannel ICA based EEG Beamformer (MIEB). Results: We evaluated the proposed algorithm on simulated EEG data and compared its performance quantitatively with three algorithms: scICA, linearly-constrained minimum-variance (LCMV) and Dual-Core beamformers; it is considered that the latter is specially designed to reconstruct correlated sources. Conclusion: The MIEB algorithm has much better performance in terms of normalized mean squared error in recovering the correlated/uncorrelated sources both in noise free and noisy synthetic EEG signals. Therefore, it could be used as a robust beamformer in recovering correlated brain sources.

Background and Aim: Music can regulate the activity of brain structures that play a significant role in emotions. The perceived emotion techniques such as dichotic listening clarify the relationships between auditory emotional stimuli and hemispheric asymmetries in the auditory modality. We examined the impact of pleasantness/unpleasantness of music by Acceptable Noise Level (ANL) as a subjective measure of listeners’ willingness to accept background noise. Methods: In this study, 32 participants rated their pleasantness with about ten songs; then, we considered the effect of preferred pleasant and unpleasant music on dichotic music listening and acceptable background noise. There were six forced attention conditions to calculate ANL, followed by measuring the most comfortable level and background noise level for each condition. Results: The pairwise comparison analyses revealed significantly higher ANL in forced attention to pleasant music than to speech (p

The use of transcranial Electrical Stimulation (tES) in the modulation of cognitive brain functions to improve neuropsychiatric conditions has extensively increased over the decades. tES techniques have also raised new challenges associated with study design, stimulation protocol, functional specificity, and dose-response relationship. In this paper, we addressed challenges through the emerging methodology to investigate the dose-response relationship of High Definition-transcranial Direct Current Stimulation (HD tDCS), identifying the role of negative valence in tinnitus perception. In light of the neurofunctional testable framework and tES application, hypotheses were formulated to measure clinical and surrogate endpoints. We posited that conscious pairing adequately pleasant stimuli with tinnitus perception results in correction of the loudness misperception and would be reinforced by concurrent active HD-tDCS on the left Dorsolateral Prefrontal Cortex (dlPFC). The dose-response relationship between HD-tDCS specificity and the loudness perception is also modeled. We conducted a double-blind, randomized crossover pilot study with six recruited tinnitus patients. Accrued data was utilized to design a well-controlled adaptive seamless Bayesian dose-response study. The sample size (n = 47, for 90% power and 95% confidence) and optimum interims were anticipated for adaptive decision-making about efficacy, safety, and single session dose parameters. Furthermore, preliminary pilot study results were sufficient to show a significant difference (90% power, 99% confidence) within the longitudinally detected self-report tinnitus loudness between before and under positive emotion induction. This study demonstrated a research methodology used to improve emotion regulation in tinnitus patients. In the projected method, positive emotion induction is essential for promoting functional targeting under HD-tDCS anatomical specificity to indicate the efficacy and facilitate the dose-finding process. The continuous updating of prior knowledge about efficacy and dose during the exploratory stage adapts the anticipated dose-response model. Consequently, the effective dose range to make superiority neuromodulation in correcting loudness misperception of tinnitus will be redefined. Highly effective dose adapts the study to a standard randomized trial and transforms it into the confirmatory stage in which active HD-tDCS protocol is compared with a sham trial (placebo-like). Establishing the HD-tDCS intervention protocols relying on this novel method provides reliable evidence for regulatory agencies to approve or reject the efficacy and safety. Furthermore, this paper supports a technical report for designing multimodality data-driven complementary investigations in emotion regulation, including EEG-driven neuro markers, Stroop-driven attention biases, and neuroimaging-driven brain network dynamics.

This study is designed to present an agent-based model (ABM) to simulate the interactions between tumor cells and the immune system in the melanoma model. The Myeloid-derived Suppressor Cells (MDSCs) and dendritic cells (DCs) are considered in this model as immunosuppressive and antigen-presenting agents respectively. The animal experiment was performed on 68 B16F10 melanoma tumor-bearing C57BL/6 female mice to collect dynamic data for ABM implementation and validation. Animals were divided into 4 groups; group 1 was control (no treatment) while groups 2 and 3 were treated with DC vaccine and low-dose 5- fluorouracil (5-FU) respectively and group 4 was treated with both DC Vaccine and low-dose of 5-FU. The tumor growth rate, number of MDSC, and presence of CD8+/CD107a+ T cells in the tumor microenvironment were evaluated in each group. Firstly, the tumor cells, the effector immune cells, DCs, and the MDSCs have been considered as the agents of the ABM model and their interaction methods have been extracted from the literature and implemented in the model. Then, the model parameters were estimated by the dynamic data collected from animal experiments. To validate the ABM model, the simulation results were compared with the real data. The results show that the dynamics of the model agents can mimic the relations among considered immune system components to an emergent outcome compatible with real data. The simplicity of the proposed model can help to understand the results of the combinational therapy and make this model a useful tool for studying different scenarios and assessing the combinational results. Determining the role of each component helps to find critical times during tumor progression and change the tumor and immune system balance in favor of the immune system.

Purpose: For over three decades, various researchers have aimed to construct a model of breast cancer. Most of them have used an infrared thermal model to stimulate breast cancer, but in this study, a novel estimation methodology is presented to detect the breast cancer tumor using the surface measurement obtained by Passive Acoustic Thermometer (PAT). PAT is a safe method for internal temperature estimation that works based on acoustic radiation of materials with a specific temperature. Materials and Methods: This article uses a simulation framework for breast tissue simulation and tumor detection using the PAT methodologies in different scenarios. This framework supports the generation of acoustic radiation, tissue modelling, signal processing, parameter estimation, and temperature reconstruction processes. The proposed framework estimates the temperature in the frequency domain and uses the frequency spectrum of the acquired ultrasound signals captured by a single transducer. Using the proposed framework, PAT has been evaluated in breast cancer detection. Results: According to the results, obtained from the temperature estimation in scenario 3, the sub-band estimation method, which is utilized in practical experiments in this field, shows different errors in each sub-band, making it difficult to select the true estimation. Therefore, a novel formulation is proposed that provides only one estimated temperature for breast tissue with a reasonable error (1.28 degrees) for tumor detection. Conclusion: The results show that it is possible to use this framework to evaluate the PAT in different scenarios for tumor detection. In fact, this method enhances the possibility of examination of different conditions and algorithms. It also reduces the cost of practical experiments.

This article summarizes the first and second Iranian brain–computer interface competitions held in 2017 and 2018 by the National Brain Mapping Lab. Two 64-channel electroencephalography (EEG) datasets were contributed, including motor imagery as well as motor execution by three limbs. The competitors were asked to classify the type of motor imagination or execution based on EEG signals in the first competition and the type of executed motion as well as the movement onset in the second competition. Here, we provide an overview of the datasets, the tasks, the evaluation criteria, and the methods proposed by the top-ranked teams. We also report the results achieved with the submitted algorithms and discuss the organizational strategies for future campaigns.

Abstract Background In Photoacoustic imaging (PAI), the most prevalent beamforming algorithm is delay-and-sum (DAS) due to its simple implementation. However, it results in a low quality image affected by the high level of sidelobes. Coherence factor (CF) can be used to address the sidelobes in the reconstructed images by DAS, but the resolution improvement is not good enough, compared to the high resolution beamformers such as minimum variance (MV). In this paper, it is proposed to use high-resolution-CF (HRCF) weighting technique in which MV is used instead of the existing DAS in the formula of the conventional CF. Results The higher performance of HRCF is proved numerically and experimentally. The quantitative results obtained with the simulations show that at the depth of 40 mm, in comparison with DAS+CF and MV+CF, HRCF improves the full-width-half-maximum of about 91% and 15% and the signal-to-noise ratio about 40% and 14%, respectively. Conclusion Proposed method provides a high resolution along with a low level of sidelobes for PAI.

Objective: Pharmacokinetic and clinical studies recommend applying loading dose of colistin for the treatment of severe infections in the critically ill adults. Pharmacokinetic studies of colistin in children also highlight the need for a loading dose. However, there are no clinical studies evaluating the effectiveness of colistin loading dose in children. Methods: In a randomized trial, children with ventilator-associated pneumonia or central line-associated bloodstream infection (CLABSI) for whom colistin was initiated, were enrolled. Patients were randomized into two groups; loading dose and conventional dose treatment arms. In the conventional treatment arm, colistimethate sodium was initiated with maintenance dose. In the loading dose group, colistimethate sodium was commenced with a loading dose of 150,000 international unit/kg, then on the maintenance dose. Both treatment arms also received meropenem as combination therapy. Primary outcomes were overall efficacy, clinical improvement and microbiological cure. Secondary outcomes were colistin-induced nephrotoxicity and development of resistance. Findings: Thirty children completed this study. There was a significantly higher overall efficacy in the group received loading dose (42.9 vs. 6.3%, P = 0.031). There weren't any significant differences in the clinical and microbiological endpoints. In the subgroup of children with CLABSI, results illustrated a trend toward (though statistically nonsignificant) better clinical cure for patients receiving loading dose. Conclusion: This preliminary study suggests that colistin loading dose might have some benefits in critically ill children, specifically in children with CLABSI. Further trials are required to elucidate colistin best dosing strategy in critically ill children with severe infections.

Low frequency readiness potential (RP) is elicited in electroencephalograms (EEGs) as one intends to perform an imagery (IMI) or real movement (RMI). While in most brain-computer-interface (BCI) applications the challenge is to classify RPs of different limbs from the given EEG trials, the objective of this study is fast and automatic detection of RPs from the entire single channel EEG signal. The proposed algorithm has two threshold blocks based on the nonlinear Teager-Kaiser energy operator (TEO) in the first block and the morphological properties of the RP waveform as constraints in the second block. The performance is strongly influenced by the abrupt energy changes due to transients and artefacts. As the major contribution, the proposed nonlinear convex optimization algorithm enables separation of transients from low frequency components by providing a fast thresholding mechanism. Application of the proposed method to Physionet RMI dataset, BCI competitionIV-1 IMI dataset and our own left hand movement datasets of healthy subjects led to true positive rates (TPRs) of 76.5±8.27%, 83.85±11.4%, and 81.1±5.23%, number of FPs/min of 2.4±1.07, 1.4±0.7, and 1.6±0.69 and accuracy rates of 85.4±3.83%, 90±3.56%, and 91.2±2.04%. Movement onset detection latency from our automatic RP detector was -384.9±296.5 ms.As a conclusion, the proposed method outperforms state-of-the-art techniques using as low as single channel EEG making it suitable for real-time neuro-rehabilitation of paralyzed subjects suffering from stroke.

Brain shift is an important obstacle to the application of image guidance during neurosurgical interventions. There has been a growing interest in intra-operative imaging to update the image-guided surgery systems. However, due to the innate limitations of the current imaging modalities, accurate brain shift compensation continues to be a challenging task. In this study, the application of intra-operative photoacoustic imaging and registration of the intra-operative photoacoustic with pre-operative MR images are proposed to compensate for brain deformation. Finding a satisfactory registration method is challenging due to the unpredictable nature of brain deformation. In this study, the co-sparse analysis model is proposed for photoacoustic-MR image registration, which can capture the interdependency of the two modalities. The proposed algorithm works based on the minimization of mapping transform via a pair of analysis operators that are learned by the alternating direction method of multipliers. The method was evaluated using an experimental phantom and ex vivo data obtained from a mouse brain. The results of the phantom data show about 63% improvement in target registration error in comparison with the commonly used normalized mutual information method. The results proved that intra-operative photoacoustic images could become a promising tool when the brain shift invalidates pre-operative MRI.

Purpose: Internal temperature is a significant factor for medical diagnosis. There are several thermometric methods, including IR, MRI, and active ultrasonic thermometry, which have limitations for clinical applications. The new method in this field called Passive Acoustic Thermometry (PAT), which enhanced some of this limitation. PAT is a safe method for internal temperature estimation that works based on acoustic radiation of materials with a specific temperature. Several experimental studies have been carried out so far in the field of PAT. While, to the best of our knowledge, there is no simulation-based research for nonhomogeneous materials reported yet. In this article (for the first time) we proposed a simulation framework for evaluating the PAT methodologies in nonhomogeneous materials; also we proposed a new formulation for temperature estimation in PAT algorithm. Materials and Methods: This framework supports the generation of acoustic radiation, signal processing, parameter estimation, and temperature reconstruction processes. At the moment the proposed framework estimates the temperature in the frequency domain and uses the frequency spectrum of the acquired ultrasound signals captured by a single transducer. Using the proposed framework, we tried to implement the previously practical experiments and the results of the simulation are consistent with those of the practical experiments. Also, we proposed the formulation that improves the error of temperature estimation. Results: We study 6 scenarios, including 2 environments with a target at 3 different temperatures. The average error of the proposed formulation in two different nonhomogeneous materials for three different temperatures is less than 0.25°C. Conclusion: The results show that the proposed formulation is the best estimation in the formula that has been introduced until now and compare with the previous study the accuracy is enhanced 54% (from 0.79 to 0.36 deg.). Therefore, the proposed formula enhanced PAT accuracy for temperature estimation. Also, the results show that it is possible to use this framework to evaluate the PAT in different scenarios. Therefore, this method enhances the possibility of examination of different conditions and algorithms. It also reduces the cost of practical experiment.

Acoustic thermometry is one of non-invasive methods to measure the temperature inside tissue area. especially when using the thermal therapy techniques such as High Intensity Focused Ultrasound (HIFU) and other thermal based methods, thermal assessment of heated area seems to be necessary. Some of acoustic properties of medium are temperature dependent, therefore, evaluation of temperature dependent parameters will be an indirect and non-invasive approach in thermometry. In this paper some of thermometry methods based on changes in acoustic properties of medium has been reviewed. The published methods are classified in two main categories: passive and active thermometry. In the passive thermometry, the thermal measurement probes, induced no acoustic signals to the medium, but they receive the radiated signals from the heated medium. In active method, the thermometry probe transmits a signal into the heated region and receive the echoes, then the received RF signals are processed in order to measure the temperature.

Abstract Background: Postoperative nausea and vomiting (PONV) is one of the most common complications in the patients undergoing strabismus surgery. The aim of current study was comparing supplemental 80% and 40% oxygen on reducing postoperative nausea and vomiting in the pediatrics undergoing strabismus surgery. Materials and Methods: In this clinical trial study, 100 pediatric patients scheduled for strabismus surgery under general anesthesia were allocated randomly into two parallel supplemental 80% and 40% oxygen groups during surgery. PONV in patients was compared until 24hrs after operation. Results: In the first 6hrs postoperatively, PONV in the supplemental 40% and 80% oxygen groups were 48.8% and 30.6% respectively, also were 20.8% and 12.2% in the 6 to 24hrs postoperatively. Therefore, there were no significant differences between both groups in regarding of PONV in 6hrs and 6 to 24hrs postoperatively (p values were 0.18 and 0.25, respectively). Conclusion: According to our results, there is no any difference between 40% and 80% oxygen postoperatively in the pediatrics undergoing strabismus surgery.

Purpose: Passive Acoustic Thermometer (PAT) is a safe method for internal temperature estimation that works based on acoustic radiation of materials with a specific temperature. Several experimental studies have been carried out so far in the field of PAT. While, to the best of our knowledge, there is no simulation-based research reported yet. Materials and Methods: In this article (for the first time) we proposed a simulation framework for evaluating the PAT methodologies. This framework supports the generation of acoustic radiation, signal processing, parameter estimation, and temperature reconstruction processes. At the moment, the proposed framework estimates the temperature in the frequency domain and uses the frequency spectrum of the acquired ultrasound signals captured by a single transducer. Results: Using the proposed framework, we tried to implement previously practical experiments and the results of the simulation are consistent with those of the practical experiment. The mean error of temperature estimation was below 0.45 °C. The results show that it is possible to use this framework to evaluate the PAT in different scenarios. Conclusion: Therefore, this method enhances the possibility of examination of different conditions and algorithms. It also reduces the cost of practical experiment.

Purpose: Event-Related Potentials (ERPs) have been used in addiction studies to evaluate cognitive performance and craving in individuals with Substance Use Dependence (SUD). This paper reviews studies that used ERPs to investigate cue reactivity, inhibitory control and error processing in SUDs to integrate new findings. Materials and Methods: Five abused substances are included in the investigation, i.e. alcohol, nicotine, cannabis, cocaine, and methamphetamine. For each substance, the main recent findings related to the ERPs are specifically discussed, according to the latency of ERPs. Results: Individuals with SUD allocate more attention resources to the cognitive processing of substance related cues, indexed by increased amplitude of middle and late latency ERPs. Laboratory observations also show amplitude enlargement for early latency ERPs. Individuals with SUD reveal a deficiency in the inhibitory control and conscious error processing, indexed by attenuated N2 and Pe amplitude. Conclusion: This study expands the findings of previous related reviews implying that substance abusers allocate more attention resources to drug cues indexed by enlarged P3 and LPP amplitude. Regarding P3 elicited in inhibitory control tasks, there is not still convergent results, while N2 and Pe become attenuated as reported in previous reviews. The cognitive and motor inhibitory component (P3) changes show a controversial result.

Use of shock waves to temporarily increase the permeability of the cell membrane is a promising approach in drug delivery and gene therapy to allow the translocation of macromolecules and small polar molecules into the cytoplasm. Our understanding of how the characteristics of the pressure profile of shock waves, such as peak pressure and pulse duration, influences membrane properties is limited. Here we study the response of lipid bilayer membranes to shock pulses with different pressure profiles using atomistic molecular dynamics simulations. From our simulation results, we find that the transient deformation/disordering of the membrane depends on both the magnitude and the pulse duration of the pressure profile of the shock pulse. For a low pressure impulse, peak pressure has a dominant effect on membrane structural changes, while for the high pressure impulse, we find that there exists an optimal pulse duration at which membrane deformation/disordering is maximized.

This study aimed to examine the effects of chronic methamphetamine use on the topological organization of whole-brain functional connectivity network (FCN) by reconstruction of neural-activity time series at resting-state. The EEG of 36 individuals with methamphetamine use disorder (IWMUD) and 24 normal controls (NCs) were recorded, pre-processed and source-reconstructed using standardized low-resolution tomography (sLORETA). The brain FCNs of participants were constructed and between-group differences in network topological properties were investigated using graph theoretical analysis. IWMUD showed decreased characteristic path length, increased clustering coefficient and small-world index at delta and gamma frequency bands compared to NCs. Moreover, abnormal changes in inter-regional connectivity and network hubs were observed in all the frequency bands. The results suggest that the IWMUD and NCs have distinct FCNs at all the frequency bands, particularly at the delta and gamma bands, in which deviated small-world brain topology was found in IWMUD.

Background: Using conventional tDCS over the temporo-parietal junction (TPJ) we previously reported that it is possible to manipulate subjective visual vertical (SVV) and postural control. We also demonstrated that high-definition tDCS (HD-tDCS) can achieve substantially greater cortical stimulation focality than conventional tDCS. However, it is critical to establish dose-response effects using well-defined protocols with relevance to clinically meaningful applications.Objective: To conduct three pilot studies investigating polarity and intensity-dependent effects of HD-tDCS over the right TPJ on behavioral and physiological outcome measures in healthy subjects. We additionally aimed to establish the feasibility, safety, and tolerability of this stimulation protocol.Methods: We designed three separate randomized, double-blind, crossover phase I clinical trials in different cohorts of healthy adults using the same stimulation protocol. The primary outcome measure for trial 1 was SVV; trial 2, weight-bearing asymmetry (WBA); and trial 3, electroencephalography power spectral density (EEG-PSD). The HD-tDCS montage comprised a single central, and 3 surround electrodes (HD-tDCS3x1) over the right TPJ. For each study, we tested 3x2 min HD-tDCS3x1 at 1, 2 and 3 mA; with anode center, cathode center, or sham stimulation, in random order across days.Results: We found significant SVV deviation relative to baseline, specific to the cathode center condition, with consistent direction and increasing with stimulation intensity. We further showed significant WBA with direction governed by stimulation polarity (cathode center, left asymmetry; anode center, right asymmetry). EEG-PSD in the gamma band was significantly increased at 3 mA under the cathode.Conclusions: The present series of studies provide converging evidence for focal neuromodulation that can modify physiology and have behavioral consequences with clinical potential.

Implantation failure is a major limiting step for in-vitro fertilisation (IVF). Embryo implantation is the result of the interaction of the embryo with the endometrium. Oxidative stress (OS) can cause defective embryo development and retardation. Genetic polymorphisms of detoxicating enzymes, such as glutathione S-transferases (GSTs), may play an important role in the outcome of embryo implantation. GSTM1 and GSTT1 are known to be highly polymorphic. The aim of this study was to examine the association of GSTM1 and GSTT1 gene polymorphisms with IVF-ET outcome in a population in northern Iran. Blood samples were collected from 120 infertile women who underwent an IVF cycle, and 108 healthy volunteers. Genomic DNA was prepared from peripheral blood leucocytes. Genotype frequencies were determined in patients and healthy controls using polymerase chain reaction (PCR). It was found that 25.8% of the infertile women and 0% of the controls had the GSTM1 null genotype (odds ratio (OR) = 76.37; 95% CI = 4.6-1,265.7; p = 0.0025). On the other hand, 5% of the cases and 0% of the controls had the GSTT1 null genotype (OR = 12.3, 95% CI = 0.68-221/3, p = 0.088). These results suggest that GSTM1 null type might be associated with IVF outcome in a population in northern Iran. [ABSTRACT FROM AUTHOR]

Purpose: The mechanical map of liver tissue like stiffness is as important as its anatomical image for clinical purposes like staging the liver fibrosis. Acoustic radiation force-based shear waves interference patterns elastography is an interesting independent imaging rate technique which can generate shear waves in the liver tissue in any desired depth by means of the high intensity focused, long duration push beams. Because of wave attenuation and absorption process the sound wave energy is dissipated in the tissue and due to energy conservation law is turned into heat thus like any other ultrasound imaging modality, shear waves interference patterns elastography carries the risk of tissue heating and thermal ablation specially at the focal spot. Therefore, particular attention must be paid to the thermal safety assessment to shear waves interference patterns elastography. The aim of the present simulation study is the thermal safety evaluation in the liver tissue. Materials and Methods: The liver tissue has been simulated in the presence of its adjacent tissues like skin, muscle, ribs and intercostal muscles in 3 dimensions during shear waves interference patterns elastography. With 4 seconds exposure time and 2 MPa focal pressure. Results:Temperature at the focal point increases from normal body temperature (37˚C) to 47˚C. Conclusion: Thermal effects appraisal, indicates that the general tissue heating stays within the safe region.