Assemblage characterization of Giardia duodenalis in South Khorasan province, eastern Iran, using HRM real-time PCR method.

BACKGROUND: Giardia duodenalis is a common parasitic protozoan causing gastrointestinal illness in humans worldwide. The genetic diversity of G. duodenalis is reflected through the identification of different assemblages. In this study, we aimed to determine the assemblages of G. duodenalis in eastern Iran using nested-PCR and high-resolution melting (HRM) real-time PCR methods. METHODS: A total of 58 positive G. duodenalis, which were isolated from 1800 subjects, referred to medical center laboratories in South Khorasan province, eastern Iran, from April 2020 to March 2022, were included in this study. DNA was extracted and HRM real-time PCR was performed for assemblage characterization. RESULTS: HRM real-time PCR successfully characterized all samples. Accordingly, out of 58 positive samples, 53 (91.36%) and 5 (8.62%) were identified as assemblage A and B, respectively. CONCLUSIONS: Our findings showed that HRM real-time PCR was able to characterize the assemblages of G. duodenalis. In addition, our results suggest high prevalence of assemblage A in eastern region of Iran.

Anthropogenic depletion of Iran's aquifers.

Global groundwater assessments rank Iran among countries with the highest groundwater depletion rate using coarse spatial scales that hinder detection of regional imbalances between renewable groundwater supply and human withdrawals. Herein, we use in situ data from 12,230 piezometers, 14,856 observation wells, and groundwater extraction points to provide ground-based evidence about Iran's widespread groundwater depletion and salinity problems. While the number of groundwater extraction points increased by 84.9% from 546,000 in 2002 to over a million in 2015, the annual groundwater withdrawal decreased by 18% (from 74.6 to 61.3 km3/y) primarily due to physical limits to fresh groundwater resources (i.e., depletion and/or salinization). On average, withdrawing 5.4 km3/y of nonrenewable water caused groundwater tables to decline 10 to 100 cm/y in different regions, averaging 49 cm/y across the country. This caused elevated annual average electrical conductivity (EC) of groundwater in vast arid/semiarid areas of central and eastern Iran (16 out of 30 subbasins), indicating "very high salinity hazard" for irrigation water. The annual average EC values were generally lower in the wetter northern and western regions, where groundwater EC improvements were detected in rare cases. Our results based on high-resolution groundwater measurements reveal alarming water security threats associated with declining fresh groundwater quantity and quality due to many years of unsustainable use. Our analysis offers insights into the environmental implications and limitations of water-intensive development plans that other water-scarce countries might adopt.

Anthropogenic vs. climatic drivers: Dissecting Lake desiccation on the Iranian plateau.

Lakes are indispensable to ecological balance, supporting biodiversity and human welfare. Despite their importance, lakes around the globe are diminishing at an alarming rate, presenting substantial environmental challenges exacerbated by climate variability and human-induced pressures, such as unsustainable land management and excessive water withdrawals. This study offers an extensive analysis of the desiccation phenomena affecting major lakes on the Iranian plateau, dissecting the complex interplay of contributing factors. We examine meteorological, hydrological, and agricultural drought conditions using indices like SPI, SDI, and SPEI to gain nuanced insights into drought dynamics. This study sheds light on the factors that contribute to the drying up of lakes and quantifies the impact of anthropogenic and climatic drivers on this phenomenon. The findings indicate that the area of all lakes has declined dramatically after the change point, ranging from 51% in the Urmia Lake to an impressive rate (i.e. 100%) in Southern Hamun. Despite the stable rate of meteorological droughts (increasing in temperature by about 1 °C since the 90s and stable precipitation patterns across most basins), the research highlights the ongoing struggle against severe hydrological and agricultural drought conditions. The study delineates the predominant role of anthropogenic activities in the diminishing lake inflows and the consequential drying of the lake, accounting for approximately 100 % in five of the seven lakes.

Application of RiTiCE in understanding hydro-meteorological controls on ice break-up patterns in River Tornionjoki.

The Arctic region experiences significant annual hydrologic events, with the spring flood and ice break-up being the most prominent. River ice break-up, in particular, poses high socioeconomic and ecological expenses, including morphological changes and damage to riverine structures. This study aims to investigate the spatiotemporal patterns of river ice in the River Tornionjoki, including the timing of ice break-up at different latitudes. We utilized observation data and remote sensing techniques to track changes in ice patterns overtime on the River Tornionjoki. The study indicates that the ice break-up in the River Tornionjoki basin typically occurs during Apr-Jun based on the reach location in different latitudes; therefore, different stations behave according to their latitudinal location. We observed significant spatial variations in ice break-up timing across the basin, with an earlier break-up in the lower latitudes compared to the upper latitudes. The average ice break-up day in lower latitude stations ranges between 200-205, while in higher latitude stations the average ice break-up day ranges between 215-228.

Assessment of CMIP6 models performance in simulation precipitation and temperature over Iran and surrounding regions.

This study investigates the performance of CMIP6 models in reproducing historical temperature and precipitation data for Iran and neighboring countries (Afghanistan, Pakistan, Turkmenistan, Azerbaijan, Armenia, Turkey, and Iraq) from 1980 to 2014. Reanalysis data from the ECMWF database (ERA5) for temperature and precipitation were utilized as a reference for the period 1980-2014. Additionally, ten Atmosphere-Ocean General Circulation Models (AOGCMs) from CMIP6 were employed to simulate temperature and precipitation data for the study region based on the IPCC Sixth Assessment Report databases. The Kling-Gupta Efficiency (KGE) index was used to evaluate the accuracy of CMIP6 models in replicating daily temperature and precipitation. The results indicate that different CMIP6 models exhibit varying degrees of accuracy in simulating historical temperatures and precipitation, depending on the month and the country. For instance, the IPSL-CM6A-LR model demonstrated the best annual performance in estimating temperature in Azerbaijan (KGE = 0.5), while the HadGEM3-GC31-LL model showed the lowest annual performance in Pakistan (KGE = -1.4). Interestingly, the models were found to be more accurate in simulating temperatures during warm months compared to cold ones. Furthermore, the accuracy of different models in estimating annual precipitation varied significantly, ranging from -0.64 (MRI-EMS2-0 model in Afghanistan) to 0.05 (CMCC-ESM2 model in Armenia). Similar to temperature, the study found that models were generally more accurate in simulating precipitation during cold months compared to warm ones.

The impact of land use and land cover change on groundwater recharge in northwestern Bangladesh.

Groundwater recharge is affected by various anthropogenic activities, land use and land cover (LULC) change among these. The long-term temporal and seasonal changes in LULC have a substantial influence on groundwater flow dynamics. Therefore, assessment of the impacts of LULC changes on recharge is necessary for the sustainable management of groundwater resources. The objective of this study is to examine the effects of LULC changes on groundwater recharge in the northwestern part of Bangladesh. Spatially distributed monthly groundwater recharge was simulated using a semi-physically based water balance model. Long-term temporal LULC change analysis was conducted using LULC maps from 2006 to 2016, while wet and dry LULC maps were used to examine seasonal changes. The results show that the impervious built-up area has increased by 80.3%, whereas vegetated land cover has decreased by 16.4% over the study period. As a result, groundwater recharge in 2016 has decreased compared to the level seen in 2006. However, the decrease in recharge due to long-term temporal LULC changes is very small at the basin scale (2.6 mm/year), although the impact on regional level is larger (17.1 mm/year) due to urbanization. Seasonal LULC variations also affect recharge due to the higher potential for dry seasonal LULC compared to the wet seasonal LULC, a substantial difference (20.6 mm/year). The results reveal important information about the groundwater system and its response to land cover changes in northwestern Bangladesh.

Association of Blastocystis ST6 with higher protease activity among symptomatic subjects.

BACKGROUND: Blastocystis sp. is an anaerobic intestinal protozoan parasite of humans and a wide range of animals worldwide. In the current study the correlation between the cysteine protease activity of clinical samples of Blastocystis sp. ST1-3 and 6 with the levels of pro-inflammatory cytokines was evaluated. METHODS: Stool samples were collected from subjects with or without clinical symptoms. All samples were cultivated in DMEM medium. The bacteria were eliminated or reduced in Blastocystis sp. positive samples subtypes 1-3 and 6 by a variety of antibiotics and consecutive sub-cultures. To prepare parasite lysate, 1 × 105 Blastocystis sp. from each isolate were harvested and lysed using freeze-thaw. Protease activity of each isolate was measured and the gene expression of pro-inflammatory biomarkers in HT-29 cell line sensed by isolates was investigated using quantitative Real-time PCR. RESULTS: Protease activity assay showed inter- and intra-subtype variations among subtypes regarding the presence of symptoms, while the protease activity of symptomatic isolates was higher than asymptomatic isolates. The highest and lowest levels of protease activity were seen in ST6 and ST2, respectively. However, patterns of the expression of pro-inflammatory biomarkers in HT-29 cell line was different regarding the presence of symptoms and time points. There was no significant correlation between protease activity of different subtypes with the expression levels of pro-inflammatory biomarkers. CONCLUSIONS: Our study indicated a higher protease activity among isolates from symptomatic compared to asymptomatic subjects, suggesting functional role for proteases in clinical symptoms due to Blastocystis sp. The lack of correlation between the levels of expression of pro-inflammatory biomarkers with subtypes regarding the presence of clinical symptoms proposes the importance of host-related factors in presentation of clinical symptoms.

Inhibition of anti-inflammatory cytokines, IL-10 and TGF-ß, in Leishmania major infected macrophage by miRNAs: A new therapeutic modality against leishmaniasis.

Leishmania major (L. major) applies several mechanisms to escape the immune system. Interleukin-10 (IL-10) and Transforming Growth Factor (TGF-ß) downregulate nitric oxide synthase (iNOS) leading to the survival of Leishmania within macrophages. The miRNAs are known as the modulators of the immune system. The present study was conducted to assess the effect of synthetic miR-340 mimic on cytokines (IL-10 and TGF-ß1) involved in L. major infected macrophages. The miRNAs targeting of IL-10 and TGF-ß1 was predicted using bioinformatic tools. Relative expression of predicted miRNA, IL-10, and TGF-ß1 was measured by RT-qPCR before and after synthetic miRNA mimic transfection. Concentration of IL-10 and TGF-ß was measured in posttreatment condition using ELISA method. Also, infectivity was assessed by Giemsa staining. mmu-miR-340 received the highest score for targeting cytokines. The expression of miR-340 was downregulated in L. major infected macrophages. By contrast, expression of IL-10 and TGF-ß1 was upregulated in infected macrophages. After miRNA transfection, TGF-ß1 and IL-10 were both downregulated and interestingly, the combination of miR-340 and miR-27a had a stronger effect on the downregulation of target genes. This research revealed that transfection of infected macrophages with miR-340 alone or in combination with miR-27a mimic can reduce macrophage infectivity and might be introduced as a novel therapeutic agent for cutaneous leishmaniasis.

Integration of hard and soft supervised machine learning for flood susceptibility mapping.

Flooding is a destructive natural phenomenon that causes many casualties and property losses in different parts of the world every year. Efficient flood susceptibility mapping (FSM) can reduce the risk of this hazard, and has become the main approach in flood risk management. In this study, we evaluated the prediction ability of artificial neural network (ANN) algorithms for hard and soft supervised machine learning classification in FSM by using three ANN algorithms (multi-layer perceptron (MLP), fuzzy adaptive resonance theory (FART), self-organizing map (SOM)) with different activation functions (sigmoidal (-S), linear (-L), commitment (-C), typicality (-T)). We used integration of these models for predicting the spatial expansion probability of flood events in the Ajichay river basin, northwest Iran. Inputs to the ANN were spatial data on 10 flood influencing factors (elevation, slope, aspect, curvature, stream power index, topographic wetness index, lithology, land use, rainfall, and distance to the river). The FSMs obtained as model outputs were trained and tested using flood inventory datasets earned based on previous records of flood damage in the region for the Ajichay river basin. Sensitivity analysis using one factor-at-a-time (OFAT) and all factors-at-a-time (AFAT) demonstrated that all influencing factors had a positive impact on modeling to generate FSM, with altitude having the greatest impact and curvature the least. Model validation was carried out using total operating characteristic (TOC) with an area under the curve (AUC). The highest success rate was found for MLP-S (92.1%) and the lowest for FART-T (75.8%). The projection rate in the validation of FSMs produced by MLP-S, MLP-L, FART-C, FART-T, SOM-C, and SOM-T was found to be 90.1%, 89.6%, 71.7%, 70.8%, 83.8%, and 81.1%, respectively. While integration of hard and soft supervised machine learning classification with activation functions of MLP-S and MLP-L showed a strong flood prediction capability for proper planning and management of flood hazards, MLP-S is a promising method for predicting the spatial expansion probability of flood events.

Battling Water Limits to Growth: Lessons from Water Trends in the Central Plateau of Iran.

The Zayandeh-Rud River Basin in the central plateau of Iran continues to grapple with water shortages due to a water-intensive development path made possible by a primarily supply-oriented water management approach to battle the water limits to growth. Despite inter-basin water transfers and increasing groundwater supply, recurring water shortages and associated tensions among stakeholders underscore key weaknesses in the current water management paradigm. There was an alarming trend of groundwater depletion in the basin's four main aquifers in the 1993-2016 period as indicated by the results of the Mann-Kendall3 (MK3) test and Innovative Trend Analysis (ITA) of groundwater volume. The basin's water resources declined by more than 6 BCM in 2016 compared to 2005 based on the equivalent water height (EWH) derived from monthly data (2002-2016) from the GRACE. The extensive groundwater depletion is an unequivocal evidence of reduced water availability in the face of growing basin-wide demand, necessitating water saving in all water use sectors. Implementing an integrated water resources management plan that accounts for evolving water supply priorities, growing demand and scarcity, and institutional changes is an urgent step to alleviate the growing tensions and preempt future water insecurity problems that are bound to occur if demand management approaches are delayed.

Quantitative proteomic analysis to determine differentially expressed proteins in axenic amastigotes of Leishmania tropica and Leishmania major.

Cutaneous leishmaniasis is commonly caused by Leishmania major and Leishmania tropica. In the present study, the differential expression of proteins was identified in the amastigote-like forms of L. tropica and L. major in Iranian isolates. Initially, the samples were cultured and identified using PCR-RFLP technique. The Leishmania isolates were then grown in host-free (axenic) culture and prepared to amastigote-like forms, followed by the extraction of their proteins. To identify significant differentially expressed proteins (DEPs) of two types of Leishmania, the label-free quantitative proteomic technique was used based on sequential window acquisition of all theoretical fragment ion spectra mass spectrometry. A total of 51 up/down-DEPs (fold change >2 and p-value <.05) were identified between the axenic amastigote forms of L. major and L. tropica. Of these, 34 and 17 proteins were up-regulated in L. major and L. tropica, respectively. Several enriched GO terms were identified via biological process analyses for DEPs; furthermore, the metabolic process and translation were disclosed as top category in the up-regulated proteins of both L. major and L. tropica species. Also, the KEGG analysis revealed carbon metabolism and metabolic pathways term as the top pathways in the proteins up-regulated in L. major and L. tropica, respectively. Taken together, the numerous novel DEPs identified between the studied species could help fully understand the molecular mechanisms of pathogenesis and provide potential drug targets and vaccine candidates.

Molecular epidemiology of Enterocytozoon bieneusi and Encephalitozoon sp., among immunocompromised and immunocompetent subjects in Iran.

Intestinal microsporidiosis is known as an opportunistic infection in immunocompromised patients. The current study aimed to investigate intestinal microsporidia infection in human subjects with/without immunodeficiency. Totally, 600 stool samples were collected from immunocompromised (254) and immunocompetent (346) subjects. DNA extraction was performed and the SSU rRNA and the ITS genes were amplified to detect and characterize microsporidia and the relevant genotypes. Phylogenetic trees were drawn using MEGA7 software to illustrate the correlation between isolates. From 600 enrolled subjects, 283 and 317 were male and female, respectively. The average age ± SD of all tested subjects was 28.85 ± 26.92. The results of PCR demonstrated the presence of E. bieneusi and Encephalitozoon sp., among 10/600 (1.67%) and 26/600 (4.33%) of samples, respectively. Accordingly, E. bieneusi was seen among 4/346 (1.15%), 1/53 (1.88%), 3/124 (2.42%), and 2/63 (3.17%), and Encephalitozoon sp., was detected from 17/346 (4.91%), 3/53 (5.36%), 4/124 (3.22%) and 2/63 (3.17%) of healthy subjects, RA patients, cancer patients, and transplantation recipients, respectively. Statistical significant correlation was not seen between the presence of microsporidia and age, gender, stool appearance, and geographical region. Molecular analysis showed that all E. bieneusi were the genotype D. Phylogenetic tree demonstrated no classification according to the presence/absence of immunodeficiency, geographical locations and presence of diarrhea. The high prevalence of Encephalitozoon sp., in comparison to E. bieneusi in this study suggested the importance of this genus alongside with E. bieneusi in Iran. In addition, predominance of the genotype D highlighted the wide distribution of this genotype in Iran.

Vegetation height estimation using ubiquitous foot-based wearable platform.

Vegetation height plays a key role in many environmental applications such as landscape characterization, conservation planning and disaster management, and biodiversity assessment and monitoring. Traditionally, in situ measurements and airborne Light Detection and Ranging (LiDAR) sensors are among the commonly employed methods for vegetation height estimation. However, such methods are known for their high incurred labor, time, and infrastructure cost. The emergence of wearable technology offers a promising alternative, especially in rural environments and underdeveloped countries. A method for a locally designed data acquisition ubiquitous wearable platform has been put forward and implemented. Next, a regression model to learn vegetation height on the basis of attributes associated with a pressure sensor has been developed and tested. The proposed method has been tested in Oulu region. The results have proven particularly effective in a region where the land has a forestry structure. The linear regression model yields (r2 = 0.81 and RSME = 16.73 cm), while the use of a multi-regression model yields (r2 = 0.82 and RSME = 15.73 cm). The developed approach indicates a promising alternative in vegetation height estimation where in situ measurement, LiDAR data, or wireless sensor network is either not available or not affordable, thus facilitating and reducing the cost of ecological monitoring and environmental sustainability planning tasks.

Predicting the seedling emergence time of sugar beet (Beta vulgaris) using beta models.

Soil temperature, texture, water content and sowing depth are effective factors on the estimation of emergence time. This research aimed to test the Beta model for its adequacy in predicting the time of emergence for sugar beet. The Beta growth model as a phenological model have been used for evaluating the time of seedling emergences under both controlled environments in laboratory and field conditions. An experiment was conducted both in the laboratory with five soil textures, three sowing depths, five soil water contents and ten constant soil temperatures, under field conditions on five sowing dates (20 February, 28 March, 19 April, 10 May, and 31 May) and three sowing depths. The results demonstrated that the Beta model can predict the time of emergence. Based on the root mean square error (RMSE), the time of emergence estimated by the Beta model was in high agreement with the time of emergence measured in the laboratory. Estimation accuracy was reduced slightly by the Beta model under field conditions. The accuracy of the Beta model was influenced by the sowing date under field conditions. So, on the first and second sowing dates (with low air temperature), the estimation of time of emergence by the model was lower and on the fourth and the fifth sowing date (with warmer air temperature), was more than the duration measured. Estimation accuracy was increased by the Beta model under field conditions using soil temperature. In conclusion, the Beta model can predict the time to emergence of sugar beet seedlings in different levels of soil texture and soil water content under field conditions, and with that, the proper planting date for sugar beet seeds to overcome weeds in different soil water content can be predicted.

Differential detection of Entamoeba histolytica, Entamoeba dispar and Entamoeba moshkovskii in faecal samples using nested multiplex PCR in west of Iran.

This study aimed to determine the prevalence of Entamoeba histolytica, Entamoeba dispar and Entamoeba moshkovskii (collectively referred to as Entamoeba complex), using microscopic and molecular methods in Kurdistan Province, northwest of Iran. The relationship between positive Entamoeba species and clinical symptoms was also investigated. Eight positive Entamoeba complex, as well as four Entamoeba complex-like isolates, were detected by microscopic stool examination. DNA was extracted from all positive and from 55 randomly selected negative stool samples. PCR was performed using species-specific 18S rRNA primers for the Entamoeba complex. All positive PCR samples were sequenced. In total, 14 (1.01%) out of 1383 isolates, i.e. 12 microscopy-positive and Entamoeba complex-like isolates and two out of 55 microscopy-negative isolates, were identified via PCR and sequencing. Overall, 0.58% (8/1383) of the isolates were E. dispar, 0.14% (2/1383) E. histolytica, 0.07% (1/1383) E. moshkovskii and 0.22% (3/1383) were mixed of E. histolytica and E. dispar. Based on our findings, the prevalence of E. dispar is greater than that of E. histoltyica. On the other hand, a case of E. moshkovskii was reported for the first time in this region. It seems that some gastrointestinal symptoms may be attributed to Entamoeba species.

Development and evaluation of high-resolution melting curve analysis for rapid detection and subtyping of Blastocystis and comparison the results with sequencing.

Blastocystis is a prevalent parasite that has a wide distribution. In order to design HRM real-time PCR, primers were selected from SSU rRNA gene to amplify specific fragment with different melting temperatures for each subtype of Blastocystis. Subsequently, HRM real-time PCR was performed and melting curve analysis was done by Rotor-Gene Q software. The results of HRM real-time PCR was then compared with sequence results of "barcoding region" of SSU rRNA gene of Blastocystis. To evaluate sensitivity of test, 10-fold serial dilutions of the parasite were prepared from ~ 106 to 1 parasite per mL of stool sample and were investigated by HRM real-time PCR. In order to determine specificity of method, HRM real-time PCR was done for some microorganisms and Blastocystis-negative stool samples. In silico analysis showed that all seventeen subtypes of Blastocystis were distinguish. In vitro analysis revealed that the test discriminated subtypes with specific melting temperatures.

Hybrid green-blue-gray decentralized urban drainage systems design, a simulation-optimization framework.

Recent studies suggested hybrid green-blue-gray infrastructures (HGBGI) as the most promising urban drainage systems that can simultaneously combine reliability, resilience, and acceptability of gray infrastructures (networks of pipes) with multi-functionality, sustainability, and adaptability of green-blue infrastructures (GBI). Combining GBI and gray measures for designing new urban drainage systems forms a nonlinear multimodal mixed integer-real optimization problem that is highly constrained and intractable. For this purpose, this study presents a simulation-optimization framework to optimize urban drainage systems considering HGBGI alternatives and different degrees of centralization. The proposed framework begins with the characterization of the site under design and drawing the base graph. Then, different layouts with different degrees of centralization are generated and hydraulically designed using a recent algorithm called hanging gardens algorithm. After introducing the feasible GBI to the model, we now perform second optimization to find the optimum distribution of GBIs in a way that minimizes total life cycle costs of GBIs and pipe networks. Finally, resiliency and sustainability of different scenarios are evaluated using several design storms that provide material for final assessment and decision-making. The performance of the proposed framework is evaluated using a real large-scale case study, a part of the city of Ahvaz in Iran. Finally, results are presented and discussed with recommendations for future studies.

Amino acid mutation in Plasmodium vivax dihydrofolate reductase (dhfr) and dihydropteroate synthetase (dhps) genes in Hormozgan Province, southern Iran.

Molecular analysis of antifolate resistance-associated genes-dihydrofolate reductase (dhfr) and dihydropteroate synthetase (dhps) of Plasmodium vivax is important in predicting the emergence of drug resistance to sulphadoxine-pyrimethamine (SP). The present study aimed to determine the polymorphism of dhfr and dhps genes in P. vivax field isolates. Samples from 80 microscopically diagnosed vivax malaria cases were collected from endemic areas of malaria in Hormozgan Province of Iran, from June 2010 to November 2015. The two sets of codons at position 33, 57, 58, 117, 173 of dhfr and 382, 383, and 553 of dhps genes were analysed by direct sequencing of PCR products. The majority of the isolates (70%) harboured a wild-type allele for P. vivax dhfr (Pvdhfr) and P. vivax dhps (Pvdhps). Mutations were detected in three codons of Pvdhfr (P33L, S58R and S117N) and single codon in Pvdhps (A383G). Novel mutations that have not been identified previously at codon 459 (D459A) of Pvdhps were also observed. The high prevalence of point mutation as well as the rising triple mutation of Pvdhfr and Pvdhps genotypes necessitate change in programmes and guidelines to eliminate P. vivax in future.

Serological and molecular approaches in clinical diagnosis of ocular toxoplasmosis in Iran.

Background: Toxoplasma gondii (T. gondii) is the most common parasite that can lead to a disease called toxoplasmosis. In this study, serological and molecular complementary tests have been conducted to detect or diagnose this parasite. Methods: A total of 71 patients with clinical symptoms of ocular toxoplasmosis and 20 patients with other ocular infections were evaluated. Serum and buffy coat samples were collected and tested using enzyme-linked immunosorbent assay (ELISA) and nested polymerase chain reaction (nPCR) assessments. Superficial T. gondii B1 gene was evaluated in PCR. The ocular toxoplasmosis patients were followed-up 2 weeks after the first sampling and 4 weeks following the first laboratory testing. The main outcome measures were the efficiency of the diagnostic procedure and positive and negative predictive values (PPV and NPV). Results: Overall, of the samples, 69% were PCR+, IgG+, and IgM-, and 4.2% showed PCR+, IgG+, and IgM+. In the first follow-up, after 2 weeks, from the 41 referred patients, 29 (70%) showed PCR+, IgG+, and IgM-, which confirmed the results of the first sampling. In the second follow-up, 9 (47%) patients were PCR+, IgG+, and IgM-. A correlation was observed between the first referral and the follow-ups. Also, from 71 patients, diagnosed clinically as ocular toxoplasmosis, the disease was confirmed in 73.2% and 26.8% of those suffering from other ocular infections. Of the 20 control group samples, 55% showed PCR-, IgG+, and IgM-. The sensitivity, specificity, negative and positive predictive values, and negative and positive likelihoods were analyzed for IgG and IgM antibodies and for PCR using ELISA method. Conclusion: As the ophthalmologic signs of T. gondii may be mimicked by other infections, clinical methods may be complemented by laboratory approaches for a definite diagnosis. This would assist clinicians to achieve timely diagnosis and successful therapy and to control the infection.

Amoebiasis in Iran: a systematic review and meta-analysis.

A comprehensive meta-analysis study was performed to estimate the reliable national prevalence and molecular epidemiology of amoebiasis in Iran. Nine English and Persian databases were searched to achieve the relevant studies. Pooled estimates were generated and meta-regression was performed. We identified 71 eligible articles involving 330 930 subjects from 25 provinces to be included in the final analysis. Moreover, 17 studies compromising 462 polymerase chain reaction (PCR)-positive isolates performed molecular analysis to inter-species differentiation. The pooled prevalence of Entamoeba infection among Iranian population was about 1% (95% CI 0.8-2.0%). Moreover, regarding Human Development Index (HDI), a higher prevalence was observed in undeveloped provinces. Out of 462 PCR-positive isolates, 83% (95% CI 69-94%) and 12% (95% CI 3-24%) were Entamoeba dispar, Entamoeba histolytica, respectively. In subgroup analysis based on molecular results, in general, population prevalence of Entamoeba dispar and E. histolytica were 91% (95% CI 80-99%) and 7%, (95% CI 0-19%), respectively, while prevalence of these species in patients with gastrointestinal disorders were 75% (95% CI 45-96%) and 18% (95% CI 1-43%), respectively. Our findings indicate the low burden of amoebiasis in Iran. E. dispar, that is mostly non-pathogenic, was identified as most prevalent species. Nevertheless, we suggest more public health interventions in areas with lower HDI.