Annals of Military and Health Sciences Research
Volume:17 Issue: 4, Dec 2019

Scapular dyskinesis (SD) is seen in most of the overhead athletes. It can be present in asymptomatic individuals and is believed to be a risk factor for further injury. The superior glenoid labral tear and the glenohumeral (G-H) joint instability are some of the causes of SD. Besides, because of the unstable scapula, the length-tension relationship of the internal rotator muscles would be out of balance.

This study aimed to evaluate the effect of a 6-week program of selected corrective exercises in a clearly defined population of overhead athletes with SD symptoms.

Glenohumeral internal rotation (GIR) was measured in 35 competitive female swimmers with SD, using goniometry. An experimental group performed 18 sessions of commonly described exercises, while the control group only performed daily routine exercises.

Mean and SEM of the GIR post-tests in the experimental group and control group were 46.42 ± 1.59 and 38.56 ± 1.42, respectively, and there was a significant difference between the two groups (P = 0.001), whereas there was no significant increase in pre-test (P = 0.722). Furthermore, the mean and SEM of changes in the exercise group and control group were 8.37 ± 0.0.76 and -0.19 ± 0.44, respectively, and there was a significant difference between two groups (P < 0.001).

It seems that six weeks of these exercises can cause a significant increase in GIR in young competitive female swimmers. However, we suggest that more action take place into the research for this subject.

The groundwater is known as a major water source for domestic, industrial and agricultural purposes in the Razan Plain. Therefore, the prediction of toxic and essential elements (arsenic, lead, and zinc) content in groundwater resources of this area is important.

The main aim of this study was to investigate the extreme learning machine model as a novel model for the prediction of heavy metals concentration at Razan Plain, Hamedan province, Iran.

In this descriptive study, a total of 60 groundwater specimens were collected from 20 semi-deep and deep wells across the studied area. After preparing the specimens in the laboratory, the elements’ content was detected using inductively coupled plasma-optical emission spectrometry (ICP-OES) in three replicates. In the next step, three types of machine learning methods, including, extreme learning machine (ELM), artificial neural network (ANN) and multivariate adaptive regression spline (MARS) were used to predict the heavy metals concentration in groundwater resources in Razan Plain, Hamedan, Iran. The models were trained using training data (the first 80% of the data) to find optimum values for weights and biases followed by testing using testing data (the first 20% of the data) collected from the study area. The used data were representative of the concentration of the As, Zn and Pb in Razan Plain. Three evaluation measures, correlation coefficient (r), coefficient of determination (R2) and root mean square error (RMSE) were applied to investigate the accuracy of models in estimation of heavy metals concentration.

The results showed that the mean content (µg/L) of the analyzed elements in groundwater samples of Razan Plain was 6.35 for As, 5.24 for Pb, and 32.4 for Zn. In addition, based on the findings the superiority of ELM was confirmed compared with the ANN and MARS models. ELM model decreased RMSE for ANN and MARS by 39.8% and 47.8% for As, 38.5% and 59.8% for Zn, and 64.4% and 75.5% for Pb, respectively. The results indicated that the ELM model can be successfully utilized for predicting heavy metals concentration in groundwater resources.

The developed ELM approach can be successfully applied to estimate the concentration of As, Pb, and Zn in Razan Palin.

Toxoplasmosis, with worldwide distribution, may have tissue cyst in a different organ such the brain. The mental disorder associated with toxoplasmosis among soldiers has been poorly studied.

The purpose of this study was to investigate mental disorders among soldiers with chronic toxoplasmosis.

A total of 239 soldier’s blood samples from one of the garrison in Tehran, Iran, were collected and sera were detected for IgG against T. gondii using the ELISA technique.

Of all examined, sera 69 (28.87%) were positive, who were interpreted as the chronic toxoplasmosis. There was no significant association between mental disorders and chronic toxoplasmosis. The positive chronic toxoplasmosis was significantly higher in the consumption of unpasteurized milk, undercooked meat, and juicy and soil-related occupations.

It seems that the immune system may control the parasite completely and prevalence of chronic toxoplasmosis was high in the region.

Highly sensitive and rapid monitoring of heavy metal ions such as lead and cadmium has attracted considerable interest in analytical chemistry due to serious environmental effects of these ions.

In this work, clay/carbon nanocomposite modified with an organic ligand was applied as a novel modifier for simultaneous measurement of Pb (II) and Cd (II) in water samples.

The characterization of the modifier was studied by Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) spectroscopy. The analytical performance of the method was investigated by the differential pulse anodic stripping voltammetric (DPASV) technique using a carbon paste electrode (CPE) modified with the prepared nanocomposite.

Under the selected optimized conditions, a linear voltammetric response in the range of 2.0 - 100.0 ppb was obtained for the both analyte ions. The calculated detection limits (S/N = 3) were found to be 1.1 ppb for Pb (II) and 0.7 ppb for Cd (II), which are below the World Health Organization (WHO) guideline values for lead and cadmium in drinking water. The method was successfully applied for determination of noxious Pb (II) and Cd (II) ions in real waters with acceptable recoveries for the spiked samples.

A simple, selective and sensitive electrochemical sensor was prepared and applied for simultaneous detection of Pb (II) and Cd (II). The suggested sensor demonstrated good electrochemical performance and anti-interference capability for electrochemical detection of these ions in real water samples using the DPASV method.

Malaria is an infectious disease, which is caused by different species of plasmodium. It damages social and economic growth and is also one of the leading causes of morbidity and mortality. Malaria is transmitted by female anopheles mosquitoes. Studying the epidemiology of malaria is critical, and it has been poorly studied in asymptomatic individuals, especially in boundary soldiers.

This study aimed at evaluating the prevalence of malaria in veterans.

In this cross-sectional study, a total of 300 blood samples were collected from the volunteers of a garrison in Zahedan City, Sistan and Baluchestan Province, Southeast of Iran during the spring and summer of 2017 and simultaneously, the questionnaires were completed by the subjects. Then, the samples were examined by microscopic examination and nested PCR method.

Of 300 studied samples, 4 samples (1.3%) were positive for P. vivax and had asymptomatic malaria, of which. Three samples were native to Sistan and Baluchistan and another one was native to Kerman. No species of Plasmodium was observed.

A low prevalence (1.3%) of malaria indicated that it has decreased in Sistan and Baluchistan during the last years and also using the nested PCR technique is suggested to diagnose malaria in asymptomatic patients.

Electronic health literacy has been considered a public health goal in the present century so that having electronic health literacy is essential to improve healthcare status.

This study aimed to investigate the electronic health literacy level in nurses working at selected military hospitals in Tehran in 2019.

This was a descriptive-analytical, cross-sectional study on 135 nurses in selected military hospitals in Tehran selected through a stratified convenience samplingmethod in 2019. Data were collected using a demographic questionnaire and the eHealth Literacy Scale (eHEALS) filled in by nurses. The Spearman correlation test was used to assess the relationship between research variables and Mann-Whitney and Kruskal-Wallis tests were used to compare different groups. Data were analyzed using SPSS-23 at a significance level of 0.05.

In this study, 135 questionnaires were analyzed. The mean score of the electronic health literacy of nurses was 31.72 ± 5.51. Nurses’ electronic health literacy was significantly correlated with age, working hospital, and education level (P < 0.05).

According to the results, nurses’ electronic health literacy was desirable. Also, it seems that continuing education and pursuing higher academic degrees will increase nurses’ electronic health literacy

High-intensity interval (HIIT) is a contributing factor to cardiovascular disease.

This study aimed to examine the effect of HIIT on lipid profile and C-reactive protein (CRP) in physically active (PhA) and physically inactive (PhI) women.

Forty volunteer female students (20 PhA and 20 PhI) were selected and divided into 10-person groups of PhA (control and HIIT) and PhI (control and HIIT). During six weeks, the HIIT groups performed HIITs three sessions per week. Lipid profile and CRP levels of plasma were measured in the pretest and posttest.

We showed LDL, VLDL, and cholesterol were lower and HDL levels were higher in the PhA HIIT and PhI HIIT groups than in the PhA control group (P ≤ 0.05). Changes in CRP and TG levels were not significant in the PhA HIIT, PhI HIIT, and PhA control groups (P ≥ 0.05). Moreover, LDL, VLDL, and TG levels were lower and the HDL levels were higher in the PhI HIIT group than in the PhI control group (P ≤ 0.05). However, changes in CRP levels were not significant in the PhI HIIT group and PhI control group (P ≥ 0.05).

It seems that HIIT can improve the lipid profile of PhA and PhI women, but further studies are necessary in this regard.