Customized birthweight standard for an Iranian population.

OBJECTIVE: To produce a customized birthweight standard for Iran. METHOD: Retrospective study of a pregnancy database collected from five hospitals across Iran. The cohort consisted of 4994 consecutive term births with complete data, delivered between July 2013 and November 2014. Coefficients were derived using a backwards stepwise multiple regression technique. RESULTS: Maternal height, weight in early pregnancy and parity as well as the baby's sex were identified as significant physiological variables affecting birthweight. Paternal height and weight were also significant although weaker factors. The expected 280-day birthweight, free from pathological influences, of a standard size mother (height 163 cm, weight 64 kg) in her first pregnancy was 3390 g. Pathological factors found to affect birthweight in this cohort included village housing, anemia, preexisting and gestational diabetes and preeclampsia. CONCLUSION: The analysis confirmed the main physiological variables that affect birthweight in other countries and shows paternal factors also to be significant variables. Development of a country-specific customized birthweight standard will aid clinicians in Iran to distinguish between fetuses that are either constitutionally or pathologically small, thereby avoiding unnecessary interventions, and improving identification of at-risk pregnancies and perinatal outcome.

Designing and Developing Automatic Trolley for Washing and Dressing the Wounds.

INTRODUCTION: Many items are needed for dressing including sterile dressing set, antiseptic and washing solutions, leucoplast tape, waste bin for infectious garbage, waste bin for noninfectious garbage, safe disposal trash for sharp cutting instruments, bedpan and sometimes drugs. All the items are laid out on a simple wheeled trolley. The multiplicity of items together with problems in placing tools on trolley, forgetting some items, disturbing sterile condition, falling and damaging equipment and the need for at least two people for each procedure, all are the reasons to design and develop Automatic Trolley for Washing and Dressing the Wounds. MATERIAL AND METHOD: To develop a mobile unit which meets our needs for dressing, the trolley patents registered in America and different companies were evaluated as well as the materials and methods used while dressing were considered. RESULTS: Automatic Trolley for Washing and Dressing the Wounds was designed and developed. It comprises the followings: drawer, waste bin for infectious garbage, waste bin for noninfectious garbage, shelves for serum and betadine solution, serum stand, peristaltic pump, flexible tube for connecting serum, a place for bedpan, foot pedal for serum flow, two eye-sensor chambers for solution betadine and scrub, an auxiliary work surface. CONCLUSION: Due to the usual requirements for dressing, we have designed an equipped mobile unit which covers all the objectives of dressing and increases the speed of procedure. Moreover, due to the contrived equipment on the trolley, procedures are done quickly and second person is not required to assist. Automatic Trolley for Washing and Dressing the Wounds is made up of stainless steel which could be mass housing and commercializing which would play a deserving role in improving the fundamentals of health care and wound treatment.

Application of artificial neural networks for optimization of preparation of insulin nanoparticles composed of quaternized aromatic derivatives of chitosan.

The aim of this research was to develop an artificial neural network (ANN) in order to design a nanoparticulate oral drug delivery system for insulin. The pH of polymer solution (X1), concentration ratio of polymer/insulin (X2) and polymer type (X3) in 3 level including methylated N-(4-N,N- dimethyl aminobenzyl) chitosan, methylated N-(4-pyridinyl) chitosan, and methylated N-(benzyl) chitosan are considered as the input values and the particle size, zeta potential, PdI, and entrapment efficiency (EE %) as output data. ANNs are employed to generate the best model to determining the relationships between input and response values. In this research, a multi-layer percepteron with different topologies has been tested in order to define the one with the best accuracy and performance. The optimization was used by minimizing the error between the predicted and observed values. Three training algorithms (Levenberg-Marquardt (LM), Bayesian-Regularization (BR), and Gradient Descent (GD)) were employed to train ANNs with various numbers of nodes, hidden layers and transfer functions by random selection. The accuracy of prediction data were assayed by the mean squared error (MSE).The ability of all algorithms was in the order: BR>LM>GD. Thus, BR was selected as the best algorithm.

Isolation of thermotolerant, halotolerant, facultative biosurfactant-producing bacteria.

Several facultative bacterial strains tolerant to high temperature and salinity were isolated from the oil reservoir brines of an Iranian oil field (Masjed-I Soleyman). Some of these isolates were able to grow up to 60 degrees C and at high concentration of NaCl (15% w/v). One of the isolates grew at 40 degrees C, while it was able to grow at 15% w/v NaCl. Tolerances to NaCl levels decreased as the growth temperatures were increased. Surfactant production ability was detected in some of these isolates. The use of biosurfactant is considered as an effective mechanism in microbial-enhanced oil recovery processes detected in some of these isolates. The surfactant producers were able to grow at high temperatures and salinities to about 55 degrees C and 10% w/v, respectively. These isolates exhibited morphological and physiological characteristics of the Bacillus genus. The partial sequencing of the 16S ribosomal deoxyribonucleic acid gene of the selected isolates was assigned them to Bacillus subtilis group. The biosurfactant produced by these isolates caused a substantial decrease in the surface tension of the culture media to 26.7 mN/m. By the use of thin-layer chromatography technique, the presence of the three compounds was detected in the tested biosurfactant. Infrared spectroscopy and (1)H nuclear magnetic resonance analysis were used, and the partial structural characterization of the biosurfactant mixture of the three compounds was found to be lipopeptidic in nature. The possibility of use of the selected bacterial strains reported, in the present study, in different sectors of the petroleum industry has been addressed.