Background: The analysis of morphine in BIOLOGICAL SAMPLES is pivotal in clinical and forensic toxicology and indicates drug exposure, metabolism, and toxicological profile. Method: This systematic review explores the recent analytical techniques that have used the detection and quantification of morphine in forensic toxicological investigations. Articles were collected from PubMed, Scopus and Google Scholar electronic databases from 2011 until 30th September 2024. They were searched using a systematic search of English keywords including: “Morphine” OR “Analysis” OR “Analytical techniques” OR “Analytical innovations” OR “Methods” AND “BIOLOGICAL SAMPLES” OR “BIOLOGICAL matrices”. The selection criteria were based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta- Analyses). Results: From 1200 articles detected in the early systematic search, 30 articles met the inclusion criteria and included in this study. The results showed that the advanced hyphenated analytical methods couple with mass spectrometry (MS) such as Gas Chromatography- Mass Spectrometry (GC-MS), Liquid Chromatography-Mass Spectrometry (LC-MS) and related tandem GC-MS and LC-MS with recent sample preparation methods such as Quick Easy Cheap Effective Rugged Safe (QuEChERS) and Dispersive Liquid-Liquid Micro Extraction (DLLME) are the most common analytical methods for detection of morphine in BIOLOGICAL SAMPLES. Conclusion: Due to increase of morphine abuse as a worldwide concern, use of advanced analytical techniques with high sensitivity and precision in forensic toxicology setting should be recommended.

Desert growth in Iran is a major problem. A large part of the country is surrounded by vulnerable areas at risk of desertification, so that about 75% of the ecosystems of arid and semi-arid regions of the country, face the effects and consequences of desertification. Effects such as the drying up of inland lakes, sandstorms, dust and intensification of wind erosion are a clear manifestation of the growing rate of desertification in recent years in the country. In arid and semi-arid ecosystems, there is little vegetation due to lack of moisture and other adverse climatic conditions. As a result, soils are more prone to degradation, but in some of these areas, despite the lack of soil moisture, high temperatures and other unfavorable ecological conditions, the distances between plants are often covered by a community of microscopic plants, and this Communities are known as BIOLOGICAL soil crusts. BIOLOGICAL soil crusts are the association of soil mineral particles with cyanobacteria, algae, fungi, lichens, or bryophytes and are common coverings in open spaces around vascular plants in arid and semi-arid regions. BIOLOGICAL crusts significantly affect early ecosystem processes and have been described as ecological engineers in arid regions.

Atomic force microscopy (AFM) is capable of imaging the surface of sample, as well as obtaining the information about mechanical properties of SAMPLES such as elastic modulus. Nano indentation using the atomic force microscope makes it a powerful technique to determine elastic properties like the Young's modulus for BIOLOGICAL SAMPLES. JPK IP software is easy procedure and suitable to obtain elastic data and calculate young modulus.

electron microscope is one of the best methods of analysis that is widely used in various fields. The microscope provides the possibility of examining the surface and microstructure in micron and nano dimensions. Today, one of the most specialized areas of interest is BIOLOGICAL and living tissue. The observation of these SAMPLES and the investigation of their microstructures by scanning electron microscope require special preparation. Due to the high sensitivity of the SAMPLES, if any of the steps in the preparation are not carefully performed, it will cause shrinkage, collapse, or damage to the sample structure and will affect the quality of the final images, so it is very important that the conditions and procedures for tissue preparation carefully done with the standard method. There are many different techniques for preparing and analyzing various types of tissue that vary according to the type of tissue and structure. This paper study the general methods for the preparation of BIOLOGICAL SAMPLES and living tissues including: a) various fixations (chemical fixtaion and physical fixation), (b) dehydration with different percentages of alcohol, and (c) different drying methods In air, critical point dryers, freeze dryers and chemical dryers), in order to view the BIOLOGICAL structures in the closest to their living structure in a high resolution SEM is discussed.

Background and Objective: BIOLOGICAL soil crusts are a collection of lichens, mosses, fungi, cyanobacteria, etc. that are part of the soil ecosystem. Estimation of density and distribution of BIOLOGICAL soil crusts in arid and semi-arid regions of Iran, which is the subject of soil erosion and wastage is very important. Methods based on remote sensing techniques are important in terms of cost and time less efficient methods to achieve this goal. Segzi plain is one of the critical points of wind erosion in Iran and identifying and determining the distribution of BIOLOGICAL soil crusts as a soil modifier is an effective step in reducing wind erosion in the region. In this research, BSCI (BIOLOGICAL Soil Crust) index has been used to prepare the distribution map of lichen-dominated BIOLOGICAL soil crusts. Materials and Methods: The study area is part of the Sajzi Desert (Central Deserts of Iran) which is located in Isfahan province of Iran. The study area with an area of 199. 5 hectares is spread between the eastern lengths of 51o52'32" to 52o27'41" and the northern widths of 32o33'31" to 32o55'01". The average slope of Segzi plain is 1. 08 percent and its average height is 1680 meters. According to the statistics of East Isfahan Meteorological Station (Shahid Beheshti Station), the average annual rainfall in the region is 106 mm. According to the Dumarten climatic classification, the climate of the region is dry and according to the Amberge classification it is cold. The BSCI index is a combination of the relationships used to estimate vegetation and bare soil surface, and its mathematical relationship is the slope of the soil line. To calculate the soil line in an area, one must first separate the pixels that have bare soil and no vegetation. In order to calculate the soil line equation, in four seasons of a year, images of Landsat OLI 8 satellite related to 2018 were downloaded from the site of the US Geological Survey and 20 to 30 pixels of pure bare soil were extracted by drawing the reflection values of these pixels in the red and infrared band. Red near soil line coefficients were calculated for each season in the Segzi Plain. Based on BSCI index, lichen-dominated BIOLOGICAL soil crust are identified using at least VIS-NIR spectral reflection and the slope between the red and green bands compared to bare soil and dry vegetation. Using ENVI software, the distribution shells of BIOLOGICAL shells with lichen dominance were prepared in four seasons since 2018 in Segzi plain. Then, the prepared maps were validated based on land points and the total accuracy and kappa index were calculated in all four seasons. The collected lichen SAMPLES were identified based on their morphological characteristics and using a stereomicroscope, conventional microscope and common color reagents such as potassium hydroxide (KOH). After applying the BSCI index on the Landsat OLI 8 satellite image, using ENVI software, spectral profiles related to 4 points of Segzi plain in four seasons of the year were prepared and the spectral reflection in four seasons of the year in different points were examined. Results and Discussion: The slope of the soil line is lower in the rainy season, which coincides with the growth of herbaceous and annual plants, compared to the summer season, which has the least amount of rainfall, and the annual plants have dried up and become extinct. In May, the slope of the soil line was minimal (0. 39) and in late summer it has its maximum value (0. 78). In fact, the slope of the soil line has decreased from mid-August to May, and then has increased with the loss of annual vegetation and the increase of bare soil surface. The distribution maps of bio-shells in all four seasons of the year were validated during field visits and the year it was found that the highest accuracy of the map related to the map produced from Landsat 8 image is related to summer with 94% total accuracy and Kappa index equal to 0. 7412. Interpretation of the spectral profiles of the BSCI index shows that the reflections of the spectra related to the zephyr and strain prepared on the lichen dispersion points are very close to each other and also the spectral profiles of the mid-autumn and early spring are quite consistent. Whereas in the faults, which did not cover the BIOLOGICAL crust, the amount of reflection was higher and there was a slight difference between the reflection diagrams of autumn and spring. Although the reflectance values of a range of agricultural lands and the distribution points of BIOLOGICAL crusts are very close to each other, the spectral diagrams of all four seasons are very different from each other. But in all seasons of the year and in all places, the least reflection has occurred in the beginning of winter and the most reflection has occurred in summer. The climate of Segzi plain is Mediterranean and precipitation occurs in the cold season of the year. Simultaneously with the increase of precipitation from the middle of autumn, annual plants and mosses at the base of shrubs begin to grow and reach their peak in early winter and again at the beginning of spring. Decreases in rainfall have reduced their density. If the winter spectrum has the least reflection in all places. While in late summer, when the annuals and mosses have dried up, it has had the greatest spectral reflection. In Fasaran, which is a barren area and a landfill, it has shown its maximum reflection. Therefore, the BSCI index relative to the percentage of organic matter has a significant error in the detection of BIOLOGICAL soil crust and where the organic matter is high may not provide accurate diagnosis of soil bioshells. Of course, since the BSCI index is defined for the detection of throat compounds in lichen tissues. The error rate for organic matter is reduced to a minimum. As it has been observed in the final map, there is no cover of BIOLOGICAL soil crusts in Fasaran and only soil BIOLOGICAL crusts are observed in the areas around Fasaran in the agricultural areas. In agricultural areas, due to human intervention and cultivation, the amount of annual plants is different from the field of natural resources in different seasons of a year have become. Conclusion: Spectral similarity of the most important soil surface, including vegetation, the involvement of human factors in increasing or decreasing soil organic matter, bare soil, etc. limits the efficiency of the BSCI index and therefore in the time period of satellite images and regional conditions have a great impact on It has the accuracy of BSCI index.

Identification of heavy metal ions has become a global problem due to continuous industrial and human pollution. In the present study, first, the synthesis of aluminate nanostructures was done by sol-gel method. Then, in order to study and measure copper(II) ions, a modified electrochemical sensor was designed based on synthetic nanostructures. Characterization of the nanostructures and designed nanostructure sensors was performed by various techniques including Fourier transform infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FE-SEM), electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The conducted studies showed the catalytic effect of the nanostructures for copper(II) ions. Then, the measurement of the analyte was investigated on the surface of a carbon paste electrode modified with the nanostructures. For this purpose, electrochemical techniques were studied. Then, the detection limit and dynamic linear range of copper(II) ions were determined by DPV technique. Therefore, the dynamic range of the analyte was from 0.02 µM to 350.00 µM and the detection limit was found to be 1.20 nM. Finally, for investigation of the ability of the proposed method, the analyte was detected in real SAMPLES and so that acceptable recovery percentages were obtained.