Identification and genotyping of Acanthamoeba spp. in the water resources of western Iran.

Background: Acanthamoeba spp. is opportunistic amoeba that resides in water, soil, and air. Some pathogenic genotypes of the genus of Acanthamoeba can cause granulomatous amoebic encephalitis (GAE) in people with a defective immune system. The parasite can also cause Acanthamoeba keratitis (AK) among contact lens users. This study was conducted to isolate and identify the Acanthamoeba genotypes in water resources in Lorestan province, western Iran. Methods: Collected 72 water samples from surface and groundwater (springs and aqueducts) in Lorestan province. Samples were filtered and cultured in non-nutrient 1.5% agar medium covered with Escherichia coli (E. coli) at 25 °C. DNA extraction was done and the PCR reaction was performed to detect the Acanthamoeba spp. The positive PCR products were sequenced to determine the genotypes of Acanthamoeba. Results: Out of 72 examined water samples, 23.61% were positive for Acanthamoeba sp. by PCR. From PCR-positive samples, 8 (47.05%) samples were T4 genotypes and others were other Acanthamoeba genotypes (T1-T23). Therefore, approximately half of the genotypes belong to the pathogenic T4 genotype. Conclusions: The water examined samples in western provinces of Iran have the potential risk factor for public health. Therefore, the efforts of healthcare providers are needed to identify, train, and prevention from human infections.

Molecular evaluation of Cryptosporidium spp. among breeding calves of Lorestan province Western Iran.

BACKGROUND: Cryptosporidium spp. are opportunistic intestinal protozoans with global distribution and are of great importance as zoonotic protozoans are common to humans and domestic animals, including cattle and calves. Identification and detection of parasite species using precise methods including molecular methods can be an effective step in treating and controlling parasites. OBJECTIVES: This study aimed to investigate the prevalence of Cryptosporidium among breeding calves of Khorramabad city, Lorestan province, Western Iran, using PCR. METHODS: The faecal samples were taken from 181 healthy and diarrhoeal calves and after the Ziehl Neelsen Acid-fast staining and microscopic evaluation, the genomic DNA was extracted for molecular evaluations. To detect Cryptosporidium species, specific primers targeting the SAM-1 gene of Cryptosporidium and a commercial master mix were used for PCR. RESULTS: Out of 181 faecal samples of breeding calves in Khorramabad city, 9 samples (5%) were positive for Cryptosporidium spp. using the PCR method. Statistical analysis of the data showed that there was no significant statistical relationship between Cryptosporidium infection of the calves and variables of age, breed, type of water consumption, clinical signs of diarrhoea, and sampling location, while parasite infection had a significant relationship with calf gender so that all Cryptosporidium positive samples were from male calves (p ≤ 0.05). CONCLUSIONS: Considering the presence of Cryptosporidium infection, the region's traditional grazing system, and the close relationship between livestock and humans, there is a possibility of human infection in the region. So preventive measures such as periodic animal testing with sensitive and accurate diagnostic techniques including PCR, pharmacological treatment of livestock, water hygiene and the use of industrial grazing instead of traditional grazing to improve the hygiene of food consumed by livestock are recommended.

Ultracompact temporal integrator using graphene-based long-range hybrid plasmonic waveguides.

A microdisk-resonator add-drop temporal integrator, composed of a long-range hybrid plasmonic waveguide, with graphene as the central layer, is proposed for the first time, to the best of our knowledge. The integrator benefits from a considerable integration time of ∼5.55ps, which is about 11 times longer than our previously proposed plasmonic integrator, and also is fairly comparable with the integration time of a microring-based integrator with a ring radius of 47.5 µm. Based on 3D-finite-difference time-domain simulations, the integrator, with a significantly compact footprint of ∼4µm×3µm, shows the FWHM of 53 GHz. The presented graphene-based temporal integrator, with a highly miniaturized footprint and satisfactory integration time, may find applications in ultrafast plasmonic-based signal processing systems.

Modeling land cover change dynamic using a hybrid model approach in Qeshm Island, Southern Iran.

Multiple factors including natural and human-induced ones lead to land cover change in the landscape. Therefore, identifying the pattern of land cover change can help inform land-use management and prevent associated issues which can affect the natural resources of the landscape. The aim of this study is to assess land cover change in the Qeshm Island in southern Iran by combining the resulting outputs of multiple modeling methods, cellular automata (CA), Markov chains, and artificial neural networks (ANN) based on land cover maps for the years 1996, 2006, and 2016 that have been extracted from satellite imagery (Landsat 5, 7, and 8). In order to evaluate the accuracy of modeling, the Kappa coefficient was calculated to be 0.8. Then, land cover changes for 2025 were predicted by a hybrid model (CA-Markov-ANN). The results indicate that the classes of built-up areas, vegetation, and mangrove forests have changed more significantly from 1996 to 2016 compared with other classes. Land cover maps generated in this study showed that built-up areas have grown significantly in recent decades due to the region's growing population and development of ports, commercial, and industrial areas. Due to the climate change, the land area covering vegetation has decreased dramatically. The size of the mangrove forests has increased over the time period of the study (1996-2025). The findings of this study can inform land-use planning decisions by providing them with a comprehensive overview of land cover conditions in the future.

Assessing national human footprint and implications for biodiversity conservation in Iran.

Recent global-scale studies have revealed intense levels of human activities within many protected areas worldwide. However, these analyses rely on coarse global-scale data, making their utility for informing local-scale conservation action limited. We developed a spatially explicit national human footprint index for Iran, a biologically diverse country in west Asia, based on the latest high-resolution datasets available for human pressures. We assessed the extent and intensity of human pressure within Iranian protected areas, and across the biomes and ecoregions of Iran. We found that almost one-quarter (22%) of officially protected land was under intense human pressure, mostly located in north-west and west of the country. Protected areas within temperate grasslands, savannas, and shrublands are most impacted, with two-third of their area under intense pressure. The findings provide valuable information for targeting management strategies to alleviate human pressures within protected areas, and also act as a comprehensive database to track the state of protected areas through time.

Design of ultracompact tunable fractional-order temporal differentiators based on hybrid-plasmonic phase-shifted Bragg gratings.

The design and the simulation of tunable fractional-order temporal differentiators based on Si-hybrid plasmonic phase-shifted Bragg gratings are proposed in this paper, where strong light confinement in the hybrid plasmonic waveguide is employed to significantly reduce the overall length of the differentiators. According to 2D- and 3D-FDTD simulation results, the proposed structures with overall lengths of less than 8 µm can provide arbitrary differentiation order and differentiation bandwidths as high as 1.6 THz. The differentiation order and the bandwidth of the proposed structures can be tuned in relatively wide ranges by changing the geometrical parameters of the structures. For example, the differentiation order can be changed from 0.57 to 0.97 by changing the number of the Bragg grating periods in a 3D differentiator structure. Furthermore, it is shown that using an electro-optical polymer as the low-index material of the hybrid plasmonic waveguide, the differentiation order and the central frequency of the proposed differentiators can be actively tuned through applying a proper actuating electrical field (voltage) to the structure. This property, along with the ultracompact footprint and wide bandwidth of the proposed differentiators, suggest their application in ultrafast all-optical signal-processing systems.

An advanced uracil DNA glycosylase-supplemented loop-mediated isothermal amplification (UDG-LAMP) technique used in the sensitive and specific detection of Cryptosporidium parvum, Cryptosporidium hominis, and Cryptosporidium meleagridis in AIDS patients.

The rapid and accurate detection of Cryptosporidium spp. is critically important for the prevention and timely treatment of cryptosporidiosis in AIDS patients (APs). This study was conducted to examine a UDG-LAMP technique for the first time to diagnose cryptosporidiosis in APs. After collecting demographic and clinical data, three stool samples were collected from the participants (120 volunteering APs). The microscopic examination of stained smears using the acid-fast method and the UDG-LAMP assay were performed for each sample. 10% of APs were infected with Cryptosporidium spp. The number of detected cryptosporidiosis cases using the acid-fast staining and UDG-LAMP methods were significantly different (P < 0.001). Diarrhea and weight loss were found to be significantly associated with cryptosporidiosis in patients (P < 0.05). The pretreatment of LAMP reagents with UDG successfully eliminated the likelihood of product re-amplification remaining from previous reactions. The UDG-LAMP technique could detect cryptosporidiosis in APs with high sensitivity and rapidity without carryover contamination.

Understanding the effects of different social data on selecting priority conservation areas.

Conservation success is contingent on assessing social and environmental factors so that cost-effective implementation of strategies and actions can be placed in a broad social-ecological context. Until now, the focus has been on how to include spatially explicit social data in conservation planning, whereas the value of different kinds of social data has received limited attention. In a regional systematic conservation planning case study in Australia, we examined the spatial concurrence of a range of spatially explicit social values and land-use preferences collected using a public participation geographic information system and biological data. We used Zonation to integrate the social data with the biological data in a series of spatial-prioritization scenarios to determine the effect of the different types of social data on spatial prioritization compared with biological data alone. The type of social data (i.e., conservation opportunities or constraints) significantly affected spatial prioritization outcomes. The integration of social values and land-use preferences under different scenarios was highly variable and generated spatial prioritizations 1.2-51% different from those based on biological data alone. The inclusion of conservation-compatible values and preferences added relatively few new areas to conservation priorities, whereas including noncompatible economic values and development preferences as costs significantly changed conservation priority areas (48.2% and 47.4%, respectively). Based on our results, a multifaceted conservation prioritization approach that combines spatially explicit social data with biological data can help conservation planners identify the type of social data to collect for more effective and feasible conservation actions.