Determination of histamine in Iranian cheese using enzyme-linked immunosorbent assay (ELISA) method

Histamine is a simple chemical substance created during processing of the amine acid histidine. Histamine is also an agent in inflammation and the increased presence of histamine causes allergic reaction. Histamine may play a role in the increased prevalence of food intolerances. The objective of this study was to determine histamine contents. Forty four (44) samples of traditional and commercial cheese were analyzed by enzyme-linked immunosorbent assay (ELISA) method in Iran. In the two cheese samples of the 44 samples (4.5%), the presence of histamine was 26 and 46.7 mg/100 g. Histamine in any of the cheese samples was not higher than the tolerance limit of histamine contents (50 mg histamine/100 g) accepted by European countries. The values were comparable and in the range of the literature values. The results of this study indicate that the produced cheese and marketed cheese in Iran have concentrations below 50 mg histamine/100 g. Further studies should be done to investigate the presence of this toxin in different foodstuffs.Keywords: Histamine, cheese, enzyme-linked immunosorbent assay (ELISA), IranAfrican Journal of Biotechnology Vol. 12(3), pp. 308-31

The study of Self-care agency and some associated factors in patients with type 2 diabetes referred to the diabetes clinic of Tohid Hospital in Sanandaj in 2016

Background and Aims: Diabetes is considered as a major public health problem all over the world. Self-care behaviors is the most important strategy for controlling chronic diseases, such as diabetes. Therefore, this study was conducted to determine the self-care agency and some associated factors in patients with type 2 diabetes. Materials and Methods: This cross-sectional study was performed on a descriptive-analytic approach on 374 patients referring to the Diabetes Clinic of Tohid Hospital in Sanandaj, selected using systematic sampling. Data were collected using a questionnaire including demographic and background information questionnaire and a valid and reliable questionnaire for assessing the self-care agency of diabetic patients. Data were analyzed by using SPSS software version 16 and appropriate tests. All stages of the study were conducted according to moral standards. Results: The mean and standard deviation of self-care agency score was 58.40 ± 12.49 from 105, that is considered moderate. There was a significant difference in self-care agency of patients according to variables such as gender, ability to measure blood glucose, occupational status, history of education about diabetes, regular dental examinations and annual infusion of influenza vaccine (P<0.05). There was a significant and inverse correlation between the number of years elapsed since diabetes diagnosis and self-care agency (P<0.05 and r=0.24). Conclusion: Regarding the average self-care level in the majority of patients and the important role of self-care in controlling diabetes, the need to implement self-care education is increasingly felt in diabetic patients. Keywords: Self-care, Type 2 diabetes, Sananda

A new approach to analyzing the type of moisture inside the filter cake of hematite concentrate

Filters are widely used for dewatering in the mining industry. In general, different parameters affect vacuum filtration, such as solid percentage, vacuum level, particle size distribution, filter cloth, and chemical additives. These parameters can influence filtration properties such as cake moisture, throughput, and filter cloth lifetime. Moisture and throughput usually are used to determine the quality of filtration. In this study, new variables were used to express the filtration and characteristics of filter cake at a microscopic scale. The quality of the filter cake can be precociously analyzed using the void fraction and density of the filter cake. The present study aimed to propose some new variables to properly analyze the filtration process, improve the filtration rate, and decrease the cake moisture of Gol-E Gohar iron ore concentrate. In this regard, a series of filtration experiments were implemented using laboratory-scale bottom top-feed vacuum filters. The results showed that an increase in the solid percentage decreased the void fraction from 0.45 to 0.40 and increased cake density from 0.30 to 0.33 gr.cm-3, respectively. Increasing the particle size increased the void fraction from 0.415 to 0.43. Furthermore, the type of structural or capillary moisture of the filter cake could be determined using a void fraction

Cumulative Infiltration and Infiltration Rate Prediction Using Optimized Deep Learning Algorithms: A Study in Western Iran

Study region: Sixteen different sites from two provinces (Lorestan and Illam) in the western part of Iran were considered for the field data measurement of cumulative infiltration, infiltration rate, and other effective variables that affect infiltration process. Study focus: Soil infiltration is recognized as a fundamental process of the hydrologic cycle affecting surface runoff, soil erosion, and groundwater recharge. Hence, accurate prediction of the infiltration process is one of the most important tasks in hydrological science. As direct measurement is difficult and costly, and empirical models are inaccurate, the current study proposed a standalone, and optimized deep learning algorithm of a convolutional neural network (CNN) using gray wolf optimization (GWO), a genetic algorithm (GA), and an independent component analysis (ICA) for cumulative infiltration and infiltration rate prediction. First, 154 raw datasets were collected including the time of measuring; sand, clay, and silt percent; bulk density; soil moisture percent; infiltration rate; and cumulative infiltration using field survey. Next, 70 % of the dataset were used for model building and the remaining 30 % was used for model validation. Then, based on the correlation coefficient between input variables and outputs, different input combinations were constructed. Finally, the prediction power of each developed algorithm was evaluated using different visually-based (scatter plot, box plot and Taylor diagram) and quantitatively-based [root mean square error (RMSE), mean absolute error (MAE), the Nash-Sutcliffe efficiency (NSE), and percentage of bias (PBIAS)] metrics. New Hydrological Insights for the Region: Finding revealed that the time of measurement is more important for cumulative infiltration, while soil characteristics (i.e. silt content) are more significant in infiltration rate prediction. This shows that in the study area, silt parameter, which is the dominant constituent parameter, can control infiltration process more effectively. Effectiveness of the variables in the present study, in the order of importance are time, silt, clay, moisture content, sand, and bulk density. This can be related to the fact that most of study area is rangeland and thus, overgrazing leads to compaction of the silt soil that can lead to a slow infiltration process. Soil moisture content and bulk density are not highly effective in our study because these two factors do not significantly change across the study area. Findings demonstrated that the optimum input variable combination, is the one in which all input variables are considered. The results illustrated that CNN algorithms have a very high performance, while a metaheuristic algorithm enhanced the performance of a standalone CNN algorithm (from 7% to 28 %). The results also showed that a CNN-GWO algorithm outperformed the other algorithms, followed by CNN-ICA, CNN-GA, and CNN for both cumulative infiltration and infiltration rate prediction. All developed algorithms underestimated cumulative infiltration, while overestimating infiltration rates

Association of Diabetic Retinopathy and Sleep Quality

Sleep disorders are more common in diabetes mellitus (DM) cases rather than normal ones. In addition, this condition could be associated with diabetic retinopathy (DR) development with more inflammatory indices in circulation. In the present study, we have evaluated the association between DR and sleep quality. This cross-sectional study is a part of the second phase of the study of the elderly cohort of Amirkola City, which was conducted in 2015-2016 on all people aged 60 and higher. Of all diabetic cases, 44 cases had retinopathy and were selected as the case group. To compare two control groups, 135 diabetic patients without retinopathy and 135 people without diabetes were randomly selected. The presence and type of retinopathy were determined based on an eye physical examination by an ophthalmologist. In addition, sleep quality was evaluated based on the Pittsburgh Questionnaire. The obtained data were analyzed by ANOVA, t-test, and linear regression tests. In the present study, there was a significant difference in the score of the Pittsburgh questionnaire between people with DR (45.5±68.2) compared to diabetic people without retinopathy (76.5±48.2) and people without diabetes (95.4±36.2) (P=0.470), but diabetic people without retinopathy had significantly worse sleep quality than people without diabetes (P=0.019). Also, sleep quality in women with DR was worse than in men (P=014). In the linear regression analysis, it was observed that age, gender, diabetes, and history of depression significantly affect the sleep quality of the evaluated cases (P<0.05 for all). According to the results of the present study, DR does not negatively influence the quality of sleep, and DR is not related to sleep disorders

Age-Specific Distribution of Intraocular Pressure in Elderly Iranian Population and Its Associated Factors

Background: The purpose of this study was to determine the distribution of intraocular pressure (IOP) and assess its association with age, sex, systemic blood pressure, diabetes mellitus, body mass index (BMI) and tobacco smoking in Iranian elderly population. Methods: This cohort-based, cross-sectional study assessed elderly individuals aged 60-90 years in Amirkola, northern Iran, in 2016-2017. Past medical history, blood pressure, diabetes mellitus, BMI and tobacco smoking were recorded through an interview and physical examination. IOP was assessed using non-contact tonometry. Results: Total of 1377 individuals participated in this study, out of which 1346 IOP measurements were included for the final analysis. The mean age of participants was 69.4 &#177; 7.1 years and mean IOP was determined to be 16.7 &#177; 3.2 mmHg. Majority of the participants were males (56.1 vs 43.1), 73.8 of participants were overweight or obese, 6.1 smoked tobacco, 28.9 had diabetes mellitus and 84.9 had higher than normal blood pressure. Through multiple regression analysis, it was determined that age (&#946;=-0.132, p&#60;0.001) was negatively associated with IOP, and the presence of diabetes mellitus (&#946;=0.118, p&#60;0.001), systolic blood pressure (&#946;=0.101, p&#60;0.001), and BMI (&#946;=0.020, P=0.020) were positively associated with IOP. Conclusion: Mean IOP of individuals in this study was higher than average based on other studies. Age, was negatively and systemic blood pressure, BMI and presence of diabetes mellitus were positively associated with mean IOP of elderly Iranian population. Sex and tobacco smoking were not correlated with IOP. &#160

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

A Hybrid Microfluidic Electronic Sensing Platform for Life Science Applications

This paper presents a novel hybrid microfluidic electronic sensing platform, featuring an electronic sensor incorporated with a microfluidic structure for life science applications. This sensor with a large sensing area of 0.7 mm2 is implemented through a foundry process called Open-Gate Junction FET (OG-JFET). The proposed OG-JFET sensor with a back gate enables the charge by directly introducing the biological and chemical samples on the top of the device. This paper puts forward the design and implementation of a PDMS microfluidic structure integrated with an OG-JFET chip to direct the samples toward the sensing site. At the same time, the sensor’s gain is controlled with a back gate electrical voltage. Herein, we demonstrate and discuss the functionality and applicability of the proposed sensing platform using a chemical solution with different pH values. Additionally, we introduce a mathematical model to describe the charge sensitivity of the OG-JFET sensor. Based on the results, the maximum value of transconductance gain of the sensor is ~1 mA/V at Vgs = 0, which is decreased to ~0.42 mA/V at Vgs = 1, all in Vds = 5. Furthermore, the variation of the back-gate voltage from 1.0 V to 0.0 V increases the sensitivity from ~40 mV/pH to ~55 mV/pH. As per the experimental and simulation results and discussions in this paper, the proposed hybrid microfluidic OG-JFET sensor is a reliable and high-precision measurement platform for various life science and industrial applications

Electronic Sensing Platform (ESP) Based on Open-Gate Junction Field-Effect Transistor (OG-JFET) for Life Science Applications: Design, Modeling and Experimental Results

This paper presents a new field-effect sensor called open-gate junction gate field-effect transistor (OG-JFET) for biosensing applications. The OG-JFET consists of a p-type channel on top of an n-type layer in which the p-type serves as the sensing conductive layer between two ohmic contacted sources and drain electrodes. The structure is novel as it is based on a junction field-effect transistor with a subtle difference in that the top gate (n-type contact) has been removed to open the space for introducing the biomaterial and solution. The channel can be controlled through a back gate, enabling the sensor’s operation without a bulky electrode inside the solution. In this research, in order to demonstrate the sensor’s functionality for chemical and biosensing, we tested OG-JFET with varying pH solutions, cell adhesion (human oral neutrophils), human exhalation, and DNA molecules. Moreover, the sensor was simulated with COMSOL Multiphysics to gain insight into the sensor operation and its ion-sensitive capability. The complete simulation procedures and the physics of pH modeling is presented here, being numerically solved in COMSOL Multiphysics software. The outcome of the current study puts forward OG-JFET as a new platform for biosensing applications