Trends in epidemiology of Hepatitis B and C Infections in Ilam Province: National Notifiable Diseases Surveillance System data

Background: Hepatitis B virus (HBV) and hepatitis C virus (HCV) infections are the main causes of severe liver failure worldwide. This study was conducted to evaluate the incidence rate and trend of these infections over six successive years from 2008 to 2013 in Ilam Province, western Iran. Methods: We studied the registered data of HBV and HCV based on the National Notifiable Diseases Surveillance System in Ilam Province from 2008 to 2013. Incidence rate per 100,000 populations was estimated for HBV and HCV infections through location, years and age groups of patients. Results: The overall incidence rate per 100,000 populations from 2008 to 2013 for HBV infection was 9.57, 5.83, 16.26, 12.44, 21.89 and 13.93, respectively. The corresponding values for HCV infection were 0.55, 0.72, 1.44, 2.69, 1.24 and 1.93, respectively and these trends for both the HBV and HCV infections were increasing. The major distribution of HBV and HCV infections was 25-44 years of age. Both HBV and HCV infections were more common in males, urban areas and married patients. Forty-one percent of cases were carriers and history of surgery was the common risk factor. Conclusions: Our results showed that HBV and HCV are prevalent in the middle-age group. Despite effective vaccination against hepatitis B, optimized blood donor screening and better sterilization procedures for blood products, trend of HBV and HCV in Ilam are increasing. Further studies should address the role other risk factors in the trend of HBV and HCV

Biochemical Basis of Cyfluthrin and DDT Resistance in Anopheles stephensi (Diptera: Culicidae) in Malarious Area of Iran

Background: Anopheles stephensi is a key urban malaria vector in the Indian subcontinent and Middle East includ­ing south and southeast of Iran. Wide application of insecticides resulted in resistance of this species to various insec­ticides in these regions. This study was conducted to reveal the role of metabolic mechanisms in the development of resistance in An. stephensi to DDT and cyfluthrin. Methods: Field mosquito specimens were collected from Chabahar Seaport, southeast corner of Iran, in 2015. Insec­ticide susceptibility and enzyme assays were conducted as recommended by WHO. Results: Mean enzyme ratios were 3.95 and 3.04 for α- esterases and 2.40 and 1.97 for β- esterases in the DDT and cyfluthrin- resistant populations correspondingly compared with the susceptible strain. The GSTs enzyme mean ac­tivity ratios were 5.07 and 2.55 in the DDT and cyfluthrin- resistant populations compared with the susceptible beech strain. The cytochrome p450s enzyme ratios were 1.11 and 1.28 in the DDT and cyfluthrin- resistant populations respectively compared with the susceptible beech strain. Conclusion: Metabolic mechanisms play a crucial role in the development of DDT and cyfluthrin resistance in An. stephensi, therefore, further evaluation of the mechanisms involved as well as implementation of proper insecticide resistance management strategies are recommended

Decomposing socioeconomic inequality in poor mental health among Iranian adult population: results from the PERSIAN cohort study

Background Socioeconomic inequality in mental health in Iran is poorly understood. This study aimed to assess socioeconomic inequality in poor mental health among Iranian adults. Methods The study used the baseline data of PERSIAN cohort study including 131,813 participants from 17 geographically distinct areas of Iran. The Erreygers Concentration index (E) was used to quantify the socioeconomic inequalities in poor mental health. Moreover, we decomposed the E to identify factors contributing to the observed socioeconomic inequality in poor mental health in Iran. Results The estimated E for poor mental health was - 0.012 (95% CI: - 0.0144, - 0.0089), indicating slightly higher concentration of mental health problem among socioeconomically disadvantaged adults in Iran. Socioeconomic inequality in poor mental health was mainly explained by gender (19.93%) and age (12.70%). Region, SES itself, and physical activity were other important factors that contributed to the concentration of poor mental health among adults with low socioeconomic status. Conclusion There exists nearly equitable distribution in poor mental health among Iranian adults, but with important variations by gender, SES, and geography. These results suggested that interventional programs in Iran should focus on should focus more on socioeconomically disadvantaged people as a whole, with particular attention to the needs of women and those living in more socially disadvantaged regions. Keywords:Mental health; Socioeconomic inequality; Concentration index; Decompositio

Neural Imaging Using Single-Photon Avalanche Diodes

Introduction: This paper analyses the ability of single-photon avalanche diodes (SPADs) for neural imaging. The current trend in the production of SPADs moves toward the minimumdark count rate (DCR) and maximum photon detection probability (PDP). Moreover, the jitter response which is the main measurement characteristic for the timing uncertainty is progressing. Methods: The neural imaging process using SPADs can be performed by means of florescence lifetime imaging (FLIM), time correlated single-photon counting (TCSPC), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). Results: This trend will result in more precise neural imaging cameras. While achieving low DCR SPADs is difficult in deep submicron technologies because of using higher doping profiles, higher PDPs are reported in green and blue part of light. Furthermore, the number of pixels integrated in the same chip is increasing with the technology progress which can result in the higher resolution of imaging. Conclusion: This study proposes implemented SPADs in Deep-submicron technologies to be used in neural imaging cameras, due to the small size pixels and higher timing accuracies

A Simulation Study of Electric Field Engineering with Multi-Level Pinned Photodiodes for Fast and Complete Charge Transfer

In a CMOS image sensor pixel, fast and complete charge transfer from pinned photodiode (PPD) is desired and necessary in some applications. In special cases such as time-of-flight imaging or large pinned photodiodes, the PPD potential well shape highly affects the charge transfer performance and should be engineered carefully. In the present work, a PPD structure named multi-level PPD is introduced and examined through simulation study. Moreover, a fast and effective way to analyze the pinning process for a lag-free design is introduced. It is concluded that the proposed PPD achieves fast and complete charge transfer without additional implementation masks or process steps. The proposed PPD is compared with a similar conventional rectangular pixel and 31% reduction in the charge transfer time is observed.Comment: This is a manuscript with 5 pages, 7 figures prepared for publication in the field of electron device

Regenerative comparator with floating capacitor for energy‐harvesting applications

Abstract An energy‐efficient regenerative comparator design is unveiled. A floating capacitor is utilized to protect the complete discharge of the preamplifier output nodes by NMOS input transistors. The introduced floating capacitor is flipped around the preamplifier to allow PMOS cross‐couple transistor charge reutilization and elevate amplification gain at the integration phase. By increasing amplification gain, the input common mode voltage of the NMOS latch that is toggled within some delay is increased, too. Therefore, the latch stage is activated strongly, and regeneration delay is reduced. Simulation results corroborate that the proposed technique reduces power consumption and input‐referred offset by more than 60% compared with results of similar previous works. Furthermore, the referred noise and delay are improved more than 30%

Neural Monitoring With CMOS Image Sensors

Implantable image sensors have several biomedical applications due to their miniature size, light weight, and low power consumption achieved through sub-micron standard CMOS (Complementary Metal Oxide Semiconductor) technologies. The main applications are in specific cell labeling, neural activity detection, and biomedical imaging. In this paper the recent research studies on implantable CMOS image sensors for neural activity monitoring of brain are being quantified and reviewed. Based on the results, the suitable implantable image sensors for brain neural monitoring should have high signal to noise ratio of above 60 dB, high dynamic range. of near 88 dB and low power consumption than the safety threshold of 4W/cm2. Moreover, it is found out that the next generation of implantable imaging device trend should reduce the pixel size and power consumption of CMOS image sensors to increase spatial resolution of sample images