The Protective Effect of N-acetylcysteine against Deltamethrin-Induced Hepatotoxicity in Mice

Background

Exposure to pesticides is of concern to public health officials worldwide. Deltamethrin is a synthetic pyrethroid pesticide which is widely used in agriculture and veterinary medicine. Deltamethrin poisoning is always one of the concerns in medical centers due to the deltamethrin induced hepatotoxicity. This study evaluated the hepato-protective effects of N-acetylcysteine (NAC) against deltamethrin induced hepatotoxicity in mice.

Methods

A total of 40 BALB/c male mice were randomly divided into four groups; the first group was used as a control (0.5 ml normal saline); Groups 2-4 were treated with NAC [160 mg/kg Body Weight (BW)], deltamethrin (50 mg/kg BW), and NAC plus deltamethrin. At 1 and 24 hr after treatment, the animals were sacrificed and blood and liver samples were obtained for analysis and the liver/body ration, hepatic enzymes as Aspartate aminotransferase (AST), Alanine Transaminase (ALT), Alkaline phosphatase (ALP), Lactate dehydrogenase (LDH), Glutathione (GSH) content and Reactive Oxygen Species (ROS) level were measured. For comparison between more than two experimental groups, one-way ANOVA following Tukey test was used by SPSS software.

Results

The deltamethrin significantly increased AST, ALT, ALP, and the level of ROS level at the end of 1 and 24 hr after treatment; while the LDH level and GSH content were decreased. Mice in the deltamethrin treated group had a higher liver/body weight ratio than in other treated groups after 24 hr. On the other hand, NAC in combination with deltamethrin significantly reduced the activities of AST, ALT, ALP, and increased GSH levels.

Conclusion

This study demonstrated that NAC has a hepatoprotective role against deltamethrin-induced toxicity.

Evaluation of short-term adverse events of COVID-19 vaccines: An observational study

Coronavirus disease 2019 (COVID-19) vaccines are the most effective tools in managing the pandemic. However, the concern about these vaccines is the occurrence of unwanted adverse events (AEs). This study aimed to evaluate the short-term AEs of COVID-19 vaccines (Sputnik V, Astrazenka, and Sinopharm). A cross-sectional study using an online questionnaire was conducted among 321 vaccinated individuals. Demographic information, history of drug use, prior infection with COVID-19, the type of vaccine, vaccination stage, local injection site complication, systemic complication, and allergic reactions were collected and evaluated. Local complications, including pain and swelling at the injection site, and systemic complications, including fever, fatigue, lethargy, lymphadenopathy, and diarrhea, were reported after the injection of the AstraZeneca vaccine was more than the other 2 vaccines; The prevalence of fatigue and lethargy was higher than other systemic complications. The least reported complication was due to lymphadenopathy. The Sinopharm vaccine showed a lower prevalence of AEs than the other 2. The rare AEs, such as facial paralysis, nasal bleeding, and urticarial, were further reported after injection of the AstraZeneca vaccine. In general, the severity of systemic complications after the second dose of the vaccine was also higher than the first dose. All 3 vaccines were safe and tolerable. The most commonly reported AEs were injection site pain (local) and fatigue and lethargy (systemic). These expected AEs occurred shortly after vaccination and indicated an early immune response after vaccination.

Efficacy and safety of licorice (Glycyrrhiza glabra) in moderately ill patients with COVID-19: a randomized controlled trial

Licorice extract (glycyrrhizin), a potent antiviral, anti-inflammatory, and antioxidant remedy, is a potential therapeutic option for COVID-19. We evaluated the efficacy and safety of licorice in patients with moderate COVID-19. In this study, 60 patients with confirmed COVID-19 were randomly assigned in a 1:1 ratio to receive licorice (at a dose of 760 mg three times a day for seven days) or control groups. The primary outcomes were SPO2, body temperature, and respiratory rate (RR) after the end of the intervention. The findings indicated that SPO2, body temperature, and RR had no significant difference between the groups at the end of the intervention. However, CRP and ALT improved in the licorice group toward the baseline. The number of patients with worse prognoses, LOS, mortality, and the incidence of adverse events were not different between the groups at the end of the study. Licorice had no beneficial effect on the clinical symptoms of COVID-19. Moreover, this intervention demonstrated a safe profile of adverse events. The confirmation of the results of this preparatory trial requires more detailed multiple-center trials with a larger sample size.

Diverse activity of miR-150 in Tumor development: shedding light on the potential mechanisms

There is a growing interest to understand the role and mechanism of action of microRNAs (miRNAs) in cancer. The miRNAs are defined as short non-coding RNAs (18-22nt) that regulate fundamental cellular processes through mRNA targeting in multicellular organisms. The miR-150 is one of the miRNAs that have a crucial role during tumor cell progression and metastasis. Based on accumulated evidence, miR-150 acts as a double-edged sword in malignant cells, leading to either tumor-suppressive or oncogenic function. An overview of miR-150 function and interactions with regulatory and signaling pathways helps to elucidate these inconsistent effects in metastatic cells. Aberrant levels of miR-150 are detectable in metastatic cells that are closely related to cancer cell migration, invasion, and angiogenesis. The ability of miR-150 in regulating of epithelial-mesenchymal transition (EMT) process, a critical stage in tumor cell migration and metastasis, has been highlighted. Depending on the cancer cells type and gene expression profile, levels of miR-150 and potential target genes in the fundamental cellular process can be different. Interaction between miR-150 and other non-coding RNAs, such as long non-coding RNAs and circular RNAs, can have a profound effect on the behavior of metastatic cells. MiR-150 plays a significant role in cancer metastasis and may be a potential therapeutic target for preventing or treating metastatic cancer.

The Influence of Noise Exposure at Different Loudness Levels on EEG Index and Types of Attention

Bachground

Noise is one of the most important harmful factors in the environment. There are limited studies on the effect of noise loudness on brain signals and attention. The main objective of this study was to investigate the relationship between exposure to different loudness levels with brain index, types of attention, and subjective evaluation.

Methods

Four noises with different loudness levels were generated. Sixty-four male students participated in this study. Each subject performed the integrated visual and auditory continuous performance test (IVA-2) test before and during exposure to noise loudness signals while their electroencephalography was recorded. Finally, the alpha-to-gamma ratio (AGR), five types of attention, and the subjective evaluation results were examined.

Results

During exposure to loudness levels, the AGR and types of attention decreased while the NASA-Tax Load Index (NASA-TLX) scores increased. The noise exposure at lower loudness levels (65 and 75 phon) leads to greater attention dysfunction than at higher loudness. The AGR was significantly changed during exposure to 65 and 75 phon and audio stimuli. This significant change was observed in exposure at all loudness levels except 85 phon and visual stimuli. The divided and sustained attention changed significantly during exposure to all loudness levels and visual stimuli. The AGR had a significant inverse correlation with the total score of NASA-TLX during noise exposure.

Conclusions

These results can lead to the design of methods to control the psychological effects of noise at specific frequencies (250 and 4000 Hz) and can prevent non-auditory damage to human cognitive performance in industrial and urban environments.

Rapid identification of bacteria by the pattern of redox reactions rate using 2',7'-dichlorodihydrofluorescein diacetate

Bacterial infection is a life-threatening situation, and its rapid diagnosis is essential for treatment. Apart from medical applications, rapid identification of bacteria is vital in the food industry or the public health system. There are various bacterial identification techniques, including molecular-based methods, immunological approaches, and biosensor-based procedures. The most commonly used methods are culture-based methods, which are time-consuming. The objective of this study is to find a fingerprint of bacteria to identify them. Three strains of bacteria were selected, and seven different concentrations of each bacterium were prepared. The bacteria were then treated with two different molar concentrations of the fluorescent fluorophore, dichlorodihydrofluorescein diacetate for 30 minutes. Then, using the fluorescence mode of a multimode reader, the fluorescence emission of each bacterium is scanned twice during 60 minutes. Plotting the difference between two scans versus the bacteria concentration results in a unique fluorescence pattern for each bacterium. Observation of the redox state of bacteria, during 90 minutes, results in a fluorescence pattern that is clearly a fingerprint of different bacteria. This pattern is independent of fluorophore concentration. Mean Squares Errors (MSE) between the fluorescence patterns of similar bacteria is less than that of different bacteria, which shows the method can properly identify the bacteria. In this study, a new label-free method is developed to detect and identify different species of bacteria by measuring the redox activity and using the fluorescence fluorophore, dichlorodihydrofluorescein diacetate. This robust and low-cost method can properly identify the bacteria, uses only one excitation and emission wavelength, and can be simply implemented with current multimode plate readers.

Assessing the Risk of Secondary Cancer Induction in Radiosensitive Organs During Trigeminal Neuralgia Treatment With Gamma Knife Radiosurgery: Impact of Extracranial Dose

Purpose

Gamma knife radiosurgery (GKRS) delivers high-dose external radiation to a small intracranial lesion. However, scattering and leaked radiation can deposit a portion of the dose outside the radiation field, which may pose a risk to radiation-sensitive patients, such as pregnant women. Trigeminal Neuralgia (TN) is treated with one of the highest GKRS doses (80-90 Gy). This study aimed to estimate the risk of secondary cancer induction in the uterus, ovaries, thyroid gland, and eyes of TN patients undergoing GKRS.

Methods

Radiation doses to the uterus, ovary, eyes, and thyroid gland were measured for 25 female TN patients, with a mean age of 35 years, utilizing Thermo Luminescent Dosimeters (TLD).

Results

The mean absorbed dose for the uterus, ovary, thyroid gland, and eyes were .63 ± .24, .471 ± .2, 8.26 ± 1.01, and 10.64 ± 1.08 cGy, respectively. Lifetime Attributable Risk (LAR) has been calculated using BEIR VII (2006) method. LAR for the uterus, ovary, and thyroid gland was 1, 2, and 23, respectively.

Conclusion

The results of this study and its comparison with standard values demonstrate that on average, mean doses to mentioned organs were smaller than their tolerance doses, and there is no limitation to treating patients suffering from TN by GK.

Gamma Knife Icon™ Single Sector Characterization Based on Monte Carlo Simulation

Purpose: Gamma Knife Radiosurgery refers to surgery using radiation to destroy intracranial tissues or lesions elusive or unsuitable for open surgery. This study aimed to simulate the Gamma Knife Icon™ (GKI™) single sector to assess various attributes of the output beam and evaluate the EGSnrc C++ Monte Carlo code capabilities to perform a complete simulation of GKI™ for more investigations. Materials and Methods: The single source is simulated, and the geometries of the 4 and 16 mm collimators are defined based on the manufacturer data. The phase space files (PSFs) are recorded at the end of each collimator, and dose distributions are saved for the final analysis process in the last step. Results: The beam spectrum has two energy peaks g1 =1.17 MeV and g2 = 1.33 MeV, and low energy photons from scattering are also evident. The Gamma Index (GI) values are less than 1 in comparing the dose profiles generated in simulation with reference data. The Full Width at Half Maximum (FWHM) is 4.55, 10.9, 5.13 (mm) and 16.7, 35.1, 17.65 (mm) for 4mm and 16 mm collimators along x, y, and z axes, respectively. The penumbra width (80%-20%) is also 1.48, 5.5, 1.54 (mm) and 3.76, 10.1, 2.78 (mm) for 4mm and 16 mm collimators along x, y, and z axes, respectively. Conclusion: Results are in good agreement with what is expected, and it is possible to perform a complete simulation of the GKI™ system using egs++ for more investigations in phantoms and patients.

Skin Cancer Detection Based on Deep Learning

BACKGROUND

The conventional procedure of skin-related disease detection is a visual inspection by a dermatologist or a primary care clinician, using a dermatoscope. The suspected patients with early signs of skin cancer are referred for biopsy and histopathological examination to ensure the correct diagnosis and the best treatment. Recent advancements in deep convolutional neural networks (CNNs) have achieved excellent performance in automated skin cancer classification with accuracy similar to that of dermatologists. However, such improvements are yet to bring about a clinically trusted and popular system for skin cancer detection.

OBJECTIVE

This study aimed to propose viable deep learning (DL) based method for the detection of skin cancer in lesion images, to help physicians in diagnosis.

MATERIAL AND METHODS

In this analytical study, a novel DL based model was proposed, in which other than the lesion image, the patient's data, including the anatomical site of the lesion, age, and gender were used as the model input to predict the type of the lesion. An Inception-ResNet-v2 CNN pretrained for object recognition was employed in the proposed model.

RESULTS

Based on the results, the proposed method achieved promising performance for various skin conditions, and also using the patient's metadata in addition to the lesion image for classification improved the classification accuracy by at least 5% in all cases investigated. On a dataset of 57536 dermoscopic images, the proposed approach achieved an accuracy of 89.3%±1.1% in the discrimination of 4 major skin conditions and 94.5%±0.9% in the classification of benign vs. malignant lesions.

CONCLUSION

The promising results highlight the efficacy of the proposed approach and indicate that the inclusion of the patient's metadata with the lesion image can enhance the skin cancer detection performance.

Compression of EMG Signals Using Deep Convolutional Autoencoders

Efficient storage and transmission of electromyogram (EMG) data are important for emerging applications such as telemedicine and big data, as a vital tool for further advancement of the field. However, due to limitations in internet speed and hardware resources, transmission and storage of EMG data are challenging. As a solution, this work proposes a new method for EMG data compression using deep convolutional autoencoders (CAE). Eight-channel EMG data from 10 subjects, and high density EMG data from 18 subjects, were investigated for compression. The CAE architecture was designed to extract an abstract data representation that is heavily compressed, but from which the salient information for classification can be effectively reconstructed. The proposed method attained efficient compression; for CR=1600, the average PRDN (percentage RMS difference normalized) was 31.5% and the wrist motions classification accuracy (CA) reduced roughly 5%. The CAE substantially outperformed the state-of-the-art high-efficiency video coding and a well known wavelet-thresholding compression technique. Moreover, by reducing the bit-resolution of the CAEs compressed data from 24 bits to 6 bits, an additional 4-fold compression was achieved without significant degradation of the reconstruction performance. Furthermore, the CAEs inter subject performance was promising; e.g. for CR=1600, the PRDN for the inter-subject case was only 2.6% less than that of the within-subject performance. The powerful EMG compression performance with remarkable reconstruction results reflects the CAEs potential as an automatic end to end approach with the ability to learn the complete encoding and decoding process. Furthermore, the excellent inter-subject performance demonstrates the generalizability and usability of the proposed approach.

High velocity impact analysis of free-free carbon nanotubes

In the present work, molecular dynamics (MD) simulations are used to investigate the impact behavior of single-walled carbon nanotubes (SWCNTs) with free boundary conditions in two directions, i.e. vertical and horizontal. To consider the effect of consecutive impacts, the number of carbon nanotubes (CNTs) participated in simulations is chosen from two to five in a row. MD results show that adding the number of impacts increases the magnitude of energy loss in both mentioned directions and reduces the maximum impact force in horizontal cases. In addition, by increasing the velocity of striker CNT from 1 km/s to the maximum value which causes any fracture, the effect of initial velocity on the impact properties and also the ultimate initial velocity for each model are investigated. It is demonstrated that the energy loss and the maximum value of impact force increase as the initial velocity of the striker increases. Also, it is found that the impact strength in the vertical direction is higher than that of the horizontal one, while the horizontal CNTs perform better in the absorption of impact energy. Moreover, for all models, the fracture mechanism of CNTs resulting from the impact process is represented and the procedure of failure is explained.

Contribution to the Ophioninae (Hymenoptera: Ichneumonidae) of Iran with the description of 16 new species and an illustrated key to the Eremotylus of the Western Palaearctic

In this study, material of Iranian Ophioninae was examined. In total, 63 species are recognized as occurring in Iran. Sixteen species are described as new to science: Enicospilus amerii Johansson sp. nov., E. apocalypticus Johansson sp. nov., E. haladai Johansson sp. nov., Enicospilus peri sp. nov., Ophion al Johansson sp. nov., Ophion angustigena Johansson sp. nov., Ophion breviflagellator Johansson sp. nov., Ophion golestanicus Johansson sp. nov., Ophion klimenkoi Johansson sp. nov., Ophion persicus Johansson sp. nov., Ophion schmidti Johansson sp. nov., Ophion sinuosus Johansson sp. nov., Ophion sistanicus Johansson sp. nov., Ophion transcarinatus Johansson sp. nov., Ophion vasi Johansson sp. nov. and Ophion xrafstra Johansson sp. nov. Sixteen species: Enicospilus combustus (Gravenhorst, 1829); E. intermedius (Johansson, 2018); E. undulatus (Gravenhorst, 1829); Ophion angularis Johansson Cederberg, 2019; Ophion bipictor Aubert, 1980; Ophion crassicornis Brock, 1982; Ophion confusus Johansson, 2019; Ophion ellenae Johansson, 2019; Ophion eremita Kokujev, 1906; Ophion kallanderi Johansson, 2019; Ophion rostralis Meyer, 1935; Ophion rufoniger Kohl, 1905; Ophion semipullatus Kokujev, 1909; Ophion tenuicornis Johansson, 2019; Hellwigiella dichromoptera (Costa, 1886) and Eremotylus curvinervis (Kriechbaumer, 1878) are new records for the fauna of Iran. Enicospilus flavocephalus (Kirby, 1900), Enicospilus monostigma (Vollenhoven, 1879) and Eremotylus sibiricus Szpligeti, 1905 are excluded from the Iranian checklist due to previous misidentifications. Enicospilus tarsalis Hedwig, 1957 syn. nov. is excluded from synonymy with E. ahngeri and instead introduced as a junior synonym of E. cruciator Viktorov, 1957. Enicospilus affinis Hedwig, 1957 stat. rev. is excluded from synonymy with E. ocellatus Shestakov, 1926 and reinstated as a valid species. Enicospilus splendidus Rousse, Soliman Gadallah, 2017 syn. nov. is a junior synonym of Enicospilus stenopsis Kohl, 1905. Enicospilus grandiflavus Townes Townes, 1973 (= E. grandis Morley) syn. nov. is synonymized with Enicospilus unicallosus (Vollenhoven, 1878). Enicospilus contributus Shestakov, 1926 is confirmed as a junior synonym of E. merdarius (Gravenhorst, 1829). Ophion fossulatus Hedwig, 1957 stat. rev. is excluded from synonymy with Ophion mocsaryi Brauns, 1899 and reinstated as a valid species close to Ophion parvulus Kriechbaumer. Ophion mocsaryi var. decedens Hedwig, 1961 syn. nov. is a synonym of Ophion bipictor Aubert, 1980. Ophion obscuratus var. heratensis Hedwig, 1961 syn. nov. is treated as a synonym of Ophion turcomanicus Szpligeti, 1905. Ophion pravinervis Kokujev, 1906, previously only known from the lost type collected in Georgia, is redescribed. Despite the relatively high number of new species here presented, the Iranian fauna most likely still harbours additional species awaiting discovery.

Evaluation of the effect of melatonin in patients with COVID-19-induced pneumonia admitted to the Intensive Care Unit: A structured summary of a study protocol for a randomized controlled trial

OBJECTIVES

We investigate the effects of melatonin, compared to the usual therapeutic regimen on clinical symptoms and laboratory signs in severely ill patients with confirmed COVID-19 who are admitted to the Intensive Care Unit (ICU).

TRIAL DESIGN

This is a single-center, open-label, randomized, clinical trial with a parallel-group design. This study is being conducted at Shahid Mohammadi Hospital, Bandar Abbas, Iran.

PARTICIPANTS

All patients admitted to the ICU of Shahid Mohammadi Hospital, Bandar Abbas, Iran, will be screened for the following criteria. Inclusion criteria 1. Age >20 years 2. Definitive diagnosis of COVID-19 based on RT-PCR or/and serological testing 3. Severe pneumonia and lung involvement in imaging 4. Signing informed consent Exclusion criteria 1. Underlying diseases, including convulsive disorders, chronic hepatic and renal diseases 2. Use of mechanical ventilation 3. History of known allergy to Melatonin 4. Pregnancy and breastfeeding INTERVENTION AND COMPARATOR: Intervention group: The standard treatment regimen for COVID-19, according to the Iranian Ministry of Health and Medical Education's protocol, along with Melatonin soft gelatin capsule (Danna Pharmaceutical Company) at a dose of 5 mg twice a day for a period of seven days.

CONTROL GROUP

The standard treatment for COVID-19 based on the Iranian Ministry of Health and Medical Education's protocol for a period of seven days.

MAIN OUTCOMES

The primary outcomes are the recovery rate of clinical symptoms and checking arterial blood gas (ABG), C-reactive protein (C-RP), Ferritin, Lactate dehydrogenase (LDH) within seven days of randomization. The secondary outcomes are time to improvement of clinical and paraclinical features and length of stay in the ICU, need for mechanical ventilation, and mortality rate within seven days of randomization.

RANDOMIZATION

Included patients will be allocated to one of the study arms using block randomization in a 1:1 ratio (each block consists of 6 patients). This randomization method ensures a balanced allocation between the arms during the study. A web-based system will generate random numbers for the allocation sequence and concealment of participants. Each number relates to one of the study arms.

BLINDING (MASKING)

This is an open-label trial without blinding and placebo control.

NUMBERS TO BE RANDOMIZED (SAMPLE SIZE)

A total of 60 participants randomizes (30 patients allocated to the intervention group and 30 patients allocated to the control group).

TRIAL STATUS

The protocol is Version 1.0, February 16, 2021. Recruitment began February 28, 2021, and is anticipated to be completed by July 31, 2021.

TRIAL REGISTRATION

The trial protocol has been registered in the Iranian Registry of Clinical Trials (IRCT). The registration number is " IRCT20200506047323N7 ". The registration date was February 16, 2021.

FULL PROTOCOL

The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest of expediting the dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

EMG-based Estimation of Wrist Motion Using Polynomial Models

Background

Myoelectric control is a method of decoding the motor intent from the electromyogram (EMG) data and using the estimated intent to control prostheses and robots. This work investigates estimation of the wrist kinematics from EMG signals using polynomial models. Due to their low complexity, polynomial models are potentially the perfect choice for EMG-kinematics modeling.

Methods

Ten ablebodied individuals participated in this study, where the EMG signals from the forearm and the wrist kinematics from the contralateral wrist were measured during mirrored contractions. Two sets of EMG features were employed including the time domain (TD) set, and TD features along with autoregressive coefficients (TDAR). Polynomial models of order 1 to 4 were applied to map the EMG signals to the wrist motions. The performance was directly compared to that of a multilayer perceptron (MLP) neural network.

Results

The estimation accuracy of the wrist kinematics improved with increasing the order of the model, but saturated at the 4^th order. When using the TD set, the MLP significantly outperformed all polynomial models. However, when using the TDAR set, the polynomial models' performance improved so that the 4^th order model performance was not significantly different than that of the MLP in two DoFs, although it was lower than MLP in one DoF.

Conclusion

These results indicate that polynomial models are not as effective as more complex models such as neural networks, in learning the highly nonlinear mapping between the EMG data and motion intent. However, using a sufficiently high number of various EMG features, would reduce the mapping nonlinearities, and thereby may increase the polynomial models' performance to levels similar to those of complex black box models.

A Deep Transfer Learning Approach to Reducing the Effect of Electrode Shift in EMG Pattern Recognition-Based Control

An important barrier to commercialization of pattern recognition myoelectric control of prostheses is the lack of robustness to confounding factors such as electrode shift, skin impedance variations, and learning effects. To overcome this challenge, a novel supervised adaptation approach based on transfer learning (TL) with convolutional neural networks (CNNs) is proposed which requires only a short training session (a few seconds for each class) to recalibrate the system. TL is proposed as a solution to the problem of insufficient calibration data due to short training times for both classification and regression-based control schemes. This approach was validated for electrode shift of roughly 2.5cm with 13 able-bodied subjects to estimate individual and combined wrist motions. With this method, the original CNN (trained before the shift) was fine-tuned with the calibration data from after shifting. The results show that the proposed technique outperforms training a CNN from scratch (random initialization of weights) or a support vector machine (SVM) using the minimal calibration data. Moreover, it demonstrates superior performance than previous LDA and QDA-based adaptation approaches. As the outcomes confirm, the proposed CNN TL method provides a practical solution for adaptation to external factors, improving the robustness of electromyogram (EMG) pattern recognition systems.

On the mechanical stability and buckling analysis of carbon nanotubes filled with ice nanotubes in the aqueous environment: A molecular dynamics simulation approach

In this article, molecular dynamics (MD) simulations are utilized to investigate the buckling behavior of carbon nanotubes (CNTs) containing ice nanotubes in the vacuum and aqueous environment. The obtained results show that unlike the critical strain, the critical buckling load of CNT containing ice nanotube is higher than that of pure CNT in the vacuum. It is also indicated that the sensitivity of critical buckling load and the critical strain of CNT containing ice nanotube to the variation of length decreases when the nanostructure is subjected to the aqueous environment. Additionally, it is observed that the calculated critical buckling load and the critical strain of CNTs filled with ice nanotubes in the aqueous environment are respectively larger and smaller than those obtained in the vacuum. It is further observed that CNTs lose their symmetric buckling mode shape as they are filled with ice nanotubes in the vacuum. The results of these simulations can be used as a benchmark for further studies in designing novel potential applications such as proton electronic-based nanoelectromechanical systems (NEMS).

Real-time, simultaneous myoelectric control using a convolutional neural network

The evolution of deep learning techniques has been transformative as they have allowed complex mappings to be trained between control inputs and outputs without the need for feature engineering. In this work, a myoelectric control system based on convolutional neural networks (CNN) is proposed as a possible alternative to traditional approaches that rely on specifically designed features. This CNN-based system is validated using a real-time Fitts' law style target acquisition test requiring single and combined wrist motions. The performance of the proposed system is then compared to that of a standard support vector machine (SVM) based myoelectric system using a set of time-domain features. Despite the prevalence and demonstrated performance of these well-known features, no significant difference (p>0.05) was found between the two methods for any of the computed control metrics. This demonstrates the potential for automated learning approaches to extract complex and rich information from stochastic biological signals. This first evaluation of the usability of a CNN in a real-time myoelectric control environment provides a basis for further exploration.

Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging

The polarization imaging technique is a powerful approach to probe microstructural and optical information of biological structures (e.g., tissue samples). Here, we have studied the polarization properties of different bacterial colonies in order to evaluate the possibility of bacterial detection and discrimination. In this regard, we have taken the backscattering Mueller matrix images of four different bacteria colonies (i.e., Escherichia coli, Lactobacillus rhamnosus, Rhodococcus erythropolis, and Staphylococcus aureus). Although the images have the potential to distinguish qualitatively different bacterial colonies, we explored more accurate and quantitative parameters criteria for discrimination of bacterial samples; more specifically, we have exploited the Mueller matrix polar decomposition (MMPD),frequency distribution histogram (FDH), and central moment analysis method. The outcomes demonstrated a superior capacity of Mueller matrix imaging, MMPD, and FDH in bacterial colonies identification and discrimination. This approach might pave the way for a reliable, efficient, and cheap way of identification of infectious diseases.

A high-throughput flow cytometry-on-a-CMOS platform for single-cell dielectric spectroscopy at microwave frequencies

This work presents a microfluidics-integrated label-free flow cytometry-on-a-CMOS platform for the characterization of the cytoplasm dielectric properties at microwave frequencies. Compared with MHz impedance cytometers, operating at GHz frequencies offers direct intracellular permittivity probing due to electric fields penetrating through the cellular membrane. To overcome the detection challenges at high frequencies, the spectrometer employs on-chip oscillator-based sensors, which embeds simultaneous frequency generation, electrode excitation, and signal detection capabilities. By employing an injection-locking phase-detection technique, the spectrometer offers state-of-the-art sensitivity, achieving a less than 1 aFrms capacitance detection limit (or 5 ppm in frequency-shift) at a 100 kHz noise filtering bandwidth, enabling high throughput (>1k cells per s), with a measured cellular SNR of more than 28 dB. With CMOS/microfluidics co-design, we distribute four sensing channels at 6.5, 11, 17.5, and 30 GHz in an arrayed format whereas the frequencies are selected to center around the water relaxation frequency at 18 GHz. An issue in the integration of CMOS and microfluidics due to size mismatch is also addressed through introducing a cost-efficient epoxy-molding technique. With 3-D hydrodynamic focusing microfluidics, we perform characterization on four different cell lines including two breast cell lines (MCF-10A and MDA-MB-231) and two leukocyte cell lines (K-562 and THP-1). After normalizing the higher frequency signals to the 6.5 GHz ones, the size-independent dielectric opacity shows a differentiable distribution at 17.5 GHz between normal (0.905 ± 0.160, mean ± std.) and highly metastatic (1.033 ± 0.107) breast cells with p ≪ 0.001.

High strain rate and high temperature response of two armour steels: Experimental testing and constitutive modelling

Under ballistic impact or blast loading, the high strain rate and high temperature behaviour of armour steels is key to their response to a given threat. This experimental and numerical investigation examines the tensile response of a class 4a improved rolled homogenous armour steel (IRHA) and a high hardness armour steel (HHA). Cylindrical tensile specimens were tested at a range of strain rates from 0.001 s-1 to 2700 s-1. Quasi-static, elevated temperature tests were performed from room temperature up to 300° C. While the HHA is strain rate insensitive, the IRHA displays a significant increase in strength across the range of loading rates reducing the ultimate strength difference between the materials from 19% at 0.001s-1 to 4.6% at 2700s-1. An inverse numerical modelling approach for constitutive model calibration is presented, which accurately captured the dynamic material behaviour. The modified Johnson-Cook strength and Cockcroft-Latham (C-L) fracture models were capable of predicting the ballistic limit of each material to within 5% of the experimental result and to within 10% for deformation under blast loading. The blast rupture threshold of both materials was significantly over-estimated by the C-L model suggesting stress state or strain rate effects may be reducing the ductility of armour steel under localised blast loading.

Phenytoin mouthwash to treat cancer therapy-induced oral mucositis: A pilot studyPrimary neuroendocrine carcinoma of breast: A rare tumor

BACKGROUND

Oral mucositis is one of the most common side effects of cancer therapy with no definite treatment. Phenytoin has positive effects on healing of mucosal and dermal wounds. In this study efficacy of 1% phenytoin mouthwash on severity of mucositis (on the basis of WHO scale), pain relief (based on Visual Analogue Scale), and improvement of patients' quality of life (on the basis of EORTC-QLQ-H and N35 questionnaire) was evaluated.

MATERIALS AND METHODS

In a pilot -double-blind randomized clinical trial, eight patients in study group were given 1% phenytoin mouthwash while eight patients in control group used normal saline. Data analysis was performed by Mann-Whitney and Repeated Measured ANOVA tests.

RESULTS

Reduction of mucositis severity was observed, but the difference was not significant. On the other hand, patients on phenytoin therapy had better pain relief (VAS# 6.75 ± 1.58 at the beginning of the study reached to # 3.75 ± 1.16 after 3 weeks in phenytoin group) and improvement in quality of life (score of QOL was 70.63 ± 5.5 that reached to 63.61 ± 6.39 in phenytoin group) than normal saline group significantly (P < 0.05).

CONCLUSION

One percent phenytoin mouthwash caused pain relief and improvement of life quality significantly in patients with mucositis due to cancer therapy, but it did not reduce the severity of mucositis in a statistically significant scale.

INVESTIGATION OF SPIRAL AND SWEEPING HOLES

Surface infrared thermography, hotwire anemometry, and thermocouple surveys were performed on two new film cooling hole geometries: spiral/rifled holes and fluidic sweeping holes. The spiral holes attempt to induce large-scale vorticity to the film cooling jet as it exits the hole to prevent the formation of the kidney shaped vortices commonly associated with film cooling jets. The fluidic sweeping hole uses a passive in-hole geometry to induce jet sweeping at frequencies that scale with blowing ratios. The spiral hole performance is compared to that of round holes with and without compound angles. The fluidic hole is of the diffusion class of holes and is therefore compared to a 777 hole and Square holes. A patent-pending spiral hole design showed the highest potential of the non-diffusion type hole configurations. Velocity contours and flow temperature were acquired at discreet cross-sections of the downstream flow field. The passive fluidic sweeping hole shows the most uniform cooling distribution but suffers from low span-averaged effectiveness levels due to enhanced mixing. The data was taken at a Reynolds number of 11,000 based on hole diameter and freestream velocity. Infrared thermography was taken for blowing ratios of 1.0, 1.5, 2.0, and 2.5 at a density ratio of 1.05. The flow inside the fluidic sweeping hole was studied using 3D unsteady RANS.

A survey of Euphorinae (Hymenoptera: Braconidae) of southern Iran, with description of a new species

A faunistic survey of Euphorinae (Hym., Braconidae) in southern Iran, as well as an updated checklist of the genera and species in Iran, are presented. Sampling was performed using Malaise traps at different locations of Hormozgan province and Qeshm Island in Persian Gulf during 2011-2013. In total, 38 species belonging to 10 genera are listed from Iran. The recorded species belong to the following genera: Allurus Forster, 1862 (two species), Chrysopophthorus Goidanich 1948 (one species), Dinocampus Forster, 1862 (one species), Ecclitura Kokujev, 1902 (one species), Leiophron Nees von Esenbeck, 1819 (10 species), Meteorus Haliday, 1835 (12 species), Perilitus Nees von Esenbeck, 1819 (five species), Syntretus Forster 1862 (three species), Wesmaelia Foerster, 1862 (one species) and Zele Curtis, 1832 (two species). Allurus lituratus (Haliday 1835), Dinocampus coccinellae (Schrank, 1802), Leiophron (Peristenus) grandiceps (Thomson 1892), Meteorus rubens (Nees, 1811) and Wesmaelia petiolata (Wollaston, 1858) are new records for Hormozgan province and Leiophron (Peristenus) grandiceps (Thomson 1892) is recorded for the first time from Iran. In addition, Meteorus breviterebratus Ameri, Talebi & Beyarslan sp. n. is newly described and illustrated. 

Study of the genus Opius Wesmael (Hymenoptera: Braconidae: Opiinae) in Southern Iran, with eleven new records

This study was carried out to determine the species of the genus Opius Wesmael, 1835 in Hormozgan province (Southern Iran). Malaise traps and sweep nets were used to obtain adult specimens from various habitats in Hormozgan province during 2011-2013. Fifteen species from the genus Opius belonging to ten subgenera were collected. The subgenera Merotrachys Fischer, 1972 and Opiostomus Fischer, 1972 and eleven species are recorded for the first time from Iran: Opius (Agnopius) nowakowskii Fischer, 1959; Opius (Agnopius) novosimilis Fischer, 1989, Opius (Allophlebus) staryi Fischer, 1958; Opius (Allotypus) damnosus Papp, 1980; Opius (Opiostomus) riphaeus Tobias, 1986; Opius (Opiothorax) minusculae Fischer, 1967; Opius (Pendopius) bajariae Fischer, 1989; Opius (Merotrachys) penetrator Fischer 1966; Opius (Hypocynodus) flavipes Szepligeti, 1898; Opius (Hypocynodus) latidens Fischer, 1990 and Opius (Hypocynodus) latipediformis Fischer 2004. A key for identification of Opius species from southern Iran is provided.

Support vector regression for improved real-time, simultaneous myoelectric control

This study describes the first application of a support vector machine (SVM) based scheme for real-time simultaneous and proportional myoelectric control of multiple degrees of freedom (DOFs). Three DOFs including wrist flexion-extension, abduction-adduction and forearm pronation-supination were investigated with 10 able-bodied subjects and two individuals with transradial limb deficiency (LD). A Fitts' law test involving real-time target acquisition tasks was conducted to compare the usability of the SVM-based control system to that of an artificial neural network (ANN) based method. Performance was assessed using the Fitts' law throughput value as well as additional metrics including completion rate, path efficiency and overshoot. The SVM-based approach outperformed the ANN-based system in every performance measure for able-bodied subjects. The SVM outperformed the ANN in path efficiency and throughput with the first LD subject and in throughput with the second LD subject. The superior performance of the SVM-based system appears to be due to its higher estimation accuracy of all DOFs during inactive and low amplitude segments (these periods were frequent during real-time control). Another advantage of the SVM-based method was that it substantially reduced the processing time for both training and real time control.