Age determination and morphological study using otoliths in Cyprinus carpio Linnaeus, 1758 in the Southern Caspian Sea

The relationships between sagitta otolith morphology and fish size were examined for common carp in the Southern Caspian Sea; and also the aging of different length groups were determined. Statistical tests to examine correlation between left and right otoliths dimensions were carried out and no statistically significant difference between them was found. The biggest otolith had 0.032g weight belongs to an individual with BW= 428g and FL=36cm; and the smallest otolith had 0.014g for a fish with BW=220g and FL= 26cm. Regression model relations to each otolith morphometric parameter to fish length are provided. Also, the aging of this species was done by sectioning of sagitta otolith and a high significant correlations was found between fish age and morphometric parameters of both body weight and fork length and also otolith weight and length. The maximum age was determined 6+ years. The length-weight relationship was BW= 0.006 TL^3.232 (r = 0.963). According to the morphometric relationships obtained, it was concluded that otolith length and weight are good indicators of fish body weight and fork length

Age determination and morphology of otolith in Alburnus chalcoides (Guldenstaedt, 1772) in the southern Caspian Sea

The aim of this study was to provide necessary information on the age, growth and sex ratio of one of commercially important cyprinid species, Alburnus chalcoides in the southern Caspian Sea (North of Iran) from 2010 through 2011. 53 specimens of both sexes (males and females) were collected monthly. The samples were transported to the laboratory for further biological measurements and otolith extraction. The maximum and minimum age of A. chalcoides was 4+(FL=26.0 cm) and 1+ (FL= 18.1 cm), respectively. The mean fork length of A. chalcoides was 20.21±0.287 cm; and the sex ratio was 1.00: 2.12. The calculated length-weight relationships for all individuals were as W=0.141TL2.199 (R2= 0.648). Different regressions were prepared between age and morphological measurements of fish and otolith, of which the highest correlation was between age and body length as a linear regression of TL=1.959Age+16.32 (r= 0.66). There was no significant correlation between morphometric measurements of otolith and fish morphological parameters (p> 0.05), and an allometric growth was found with a slope of b=1.926 for the study area

Fluoride Concentration in Drinking Water Resources; North of Iran

Abstract Aims: Fluoride is one of the anions present in soil and water, and determining its level in drinking water is vital for preventing dental and bone diseases in societies. This research aimed to determine fluoride concentrations in drinking water sources of rural and urban areas of Babol City, Iran. Instrument & Methods: This descriptive cross-sectional study was conducted in Babol City, Iran, in 2014. 384 water samples were taken from 43 wells and 3 springs in the rural areas, and from 20 wells, 3 water reservoirs, and the water distribution system in the urban areas. Fluoride concentrations of water samples were measured with a model DR2000 spectrophotometer using the standard SPADNS method. Data were entered to SPSS 16 software and were analyzed by ANOVA test. Findings: The mean fluoride concentrations in the water samples of the deep wells were higher compared to those of the springs (p=0.01). The mean fluoride concentrations in the plains areas were higher compared to the mountainous regions (p=0.02). The mean fluoride concentrations in the wells of the urban areas, in the urban reservoirs, and in the urban water distribution system were 0.40±0.14, 0.39±0.15, and 0.40±0.15mg/l, respectively (p=0.07). Fluoride concentrations in water in urban areas during various seasons varied from 0.31 to 0.45mg/l (p=0.06). Conclusion: Fluoride concentrations in all drinking water sources in urban and rural areas of Babol are less than the ranges recommended by WHO and Iranian national standards

Simulation of environmental impact of an existing natural gas dehydration plant using a combination of thermodynamic models

A new approach was presented to improve the simulation results of an existing TEG based natural gas dehydration plant, using Aspen Plus software. Furthermore, the environmental impact of the plant was investigated. The plant consists of four main unit operations including an absorber, a flash tank, a stripper and a regenerator

ML-Peaks: Chip-seq peak detection pipeline using machine learning techniques

CHIP-Seq data is critical for identifying the locations where proteins bind to DNA, offering valuable insights into disease molecular mechanisms and potential therapeutic targets. However, identifying regions of protein binding, or peaks, in CHIP-seq data can be challenging due to limitations in peak detection methods. Current computational tools often require manual human inspection using data visualization, making it challenging and resource demanding to detect all peaks, particularly in large datasets. CHIP-seq data poses difficulties in detecting peaks due to its high background noise, low signal-to-noise ratio, and variation in the size and shape of the peaks. To overcome these challenges, we propose a data preprocessing approach using sliding window and feature reduction techniques, and the resulting features can be further used in machine learning methods. Our machine learning methodology can accurately identify peaks using a small training set, which represents a distinct advantage over commonly used statistical approaches, as it has a greater capacity for learning from data. We tested our methodology on the H3K9me3_TDH_BP CHIP-Seq dataset exploring a range of different machine learning methods, sliding window settings, and feature reduction techniques to detect peak values without human intervention. Our pipeline efficiently detected the peaks, and achieved an F1-score of 0.9644 and a false positive rate of 0.1030

Investigation and Computational Analysis of the Sulfotransferase (SOT) Gene Family in Potato (Solanum tuberosum): Insights into Sulfur Adjustment for Proper Development and Stimuli Responses

Various kinds of primary metabolisms in plants are modulated through sulfate metabolism, and sulfotransferases (SOTs), which are engaged in sulfur metabolism, catalyze sulfonation reactions. In this study, a genome-wide approach was utilized for the recognition and characterization of SOT family genes in the significant nutritional crop potato (Solanum tuberosum L.). Twenty-nine putative StSOT genes were identified in the potato genome and were mapped onto the nine S. tuberosum chromosomes. The protein motifs structure revealed two highly conserved 5′-phosphosulfate-binding (5′ PSB) regions and a 3′-phosphate-binding (3′ PB) motif that are essential for sulfotransferase activities. The protein–protein interaction networks also revealed an interesting interaction between SOTs and other proteins, such as PRTase, APS-kinase, protein phosphatase, and APRs, involved in sulfur compound biosynthesis and the regulation of flavonoid and brassinosteroid metabolic processes. This suggests the importance of sulfotransferases for proper potato growth and development and stress responses. Notably, homology modeling of StSOT proteins and docking analysis of their ligand-binding sites revealed the presence of proline, glycine, serine, and lysine in their active sites. An expression essay of StSOT genes via potato RNA-Seq data suggested engagement of these gene family members in plants’ growth and extension and responses to various hormones and biotic or abiotic stimuli. Our predictions may be informative for the functional characterization of the SOT genes in potato and other nutritional crops

Investigation and Computational Analysis of the Sulfotransferase (SOT) Gene Family in Potato (Solanum tuberosum): Insights into Sulfur Adjustment for Proper Development and Stimuli Responses

Various kinds of primary metabolisms in plants are modulated through sulfate metabolism, and sulfotransferases (SOTs), which are engaged in sulfur metabolism, catalyze sulfonation reactions. In this study, a genome-wide approach was utilized for the recognition and characterization of SOT family genes in the significant nutritional crop potato (Solanum tuberosum L.). Twenty-nine putative StSOT genes were identified in the potato genome and were mapped onto the nine S. tuberosum chromosomes. The protein motifs structure revealed two highly conserved 5′-phosphosulfate-binding (5′ PSB) regions and a 3′-phosphate-binding (3′ PB) motif that are essential for sulfotransferase activities. The protein–protein interaction networks also revealed an interesting interaction between SOTs and other proteins, such as PRTase, APS-kinase, protein phosphatase, and APRs, involved in sulfur compound biosynthesis and the regulation of flavonoid and brassinosteroid metabolic processes. This suggests the importance of sulfotransferases for proper potato growth and development and stress responses. Notably, homology modeling of StSOT proteins and docking analysis of their ligand-binding sites revealed the presence of proline, glycine, serine, and lysine in their active sites. An expression essay of StSOT genes via potato RNA-Seq data suggested engagement of these gene family members in plants’ growth and extension and responses to various hormones and biotic or abiotic stimuli. Our predictions may be informative for the functional characterization of the SOT genes in potato and other nutritional crops

Evaluating the independent impact of renal function decline on coronary artery calcification in patients undergone cardiac ct scan

Background: Cardiovascular events are the leading global cause of death. Calcification of coronary arteries is a common complication of renal failure and the leading cause of death in this population. However, its multifactorial mechanism is not fully understood. Objectives: The current study aimed to, firstly, investigate the association between renal dysfunction and the calcification of coronary arteries in patients with severe and milder stages of renal failure and, secondly, to determine the role of this variable by eliminating the effect of established confounding factors. Methods: Following a retrospective design, 261 patients with cardiovascular risk factors or atypical symptoms were investigated. Estimated GFR (glomerular filtration rate) was calculated using both Cockcroft-Gault and MDRD equations. An ECG-gated multidetector CT scan was performed to calculate CACS (coronary artery calcification score) using the Agatston method. The presence of significant CAC (coronary artery calcification) was defined as CACS > 100. Univariate and multivariate analyses were performed using binary logistic regression. Results: A total of 134 cases were diagnosed with CAC, and the mean CACS was 83.4 ± 18. According to univariate analysis, older age, male gender, systolic and diastolic blood pressure, and higher TG levels were correlated with the degree of CAC. HbA1C showed a weak correlation with CACS (P-value = 0.04). Renal insufficiency resulted in increased CAC, and lower eGFR (calculated with both Cockgraft-Gault and MDRD equations) was associated with higher calcification (P-value < 0.01). Our analysis shows that serum Ca, P, LDL, and HDL levels do not have a significant influence on calcification changes. After adjusting for confounding factors, male sex, age, triglyceride level, and eGFR were recognized as independent risk factors for CACS � 100, a marker of coronary artery atherosclerosis. However, HbA1C and systolic and diastolic blood pressure were no longer considered as factors that contribute to the risk of CAC. Conclusions: We observed a gradual and independent association between lower eGFR and higher CAC scores. © 2021, Author(s)

Comparison of heavy metals contamination and ecological risk between soils enriched with compost and chemical fertilizers in the North of Iran and ecological risk assessment

Abstract Background: Nowadays, uncontrolled use of chemical fertilizers in agriculture is one of the reasons for the entry of heavy metals into the environment. In this study, the heavy metals contamination of the soils enriched with compost and chemical fertilizers in the North of Iran and its ecological risk assessment were evaluated. Methods: In this study, 108 soil samples were collected from agricultural soils of some places of Babol in Mazandaran province. An atomic absorption spectrophotometer (PG-990) was used to determine the concentrations of lead, cadmium, and zinc in the soil samples. The assessment of soil contamination was performed by the contamination factor, degree of contamination indices, and the potential ecological risk of the heavy metals. Data were analyzed using SPSS version 22. Descriptive and chi-square tests were used to compare the mean with existing standards. Significant level was considered at P < 0.05. Results: The highest lead concentration (35.7 ± 9.5 mg/kg) was observed at 5-cm depth, and the maximum cadmium (1.1 ± 0.2 mg/kg) and zinc (88 ± 22.6 mg/kg) concentrations were observed at 15-cm depth. The results showed that lead, cadmium, and zinc concentrations in the agricultural soils enriched with compost fertilizers were acceptable, but agricultural soils enriched with chemical fertilizers indicated higher content than those enriched with compost fertilizers and higher than the maximum allowable concentration. The maximum contamination degree, pollution index, and potential ecological risk in the agricultural soils enriched with the chemical fertilizers were 15.77, 1.97, and 293.48, respectively, and these soils had low potential pollution and moderate ecological risks. Conclusion: According to the results, it is necessary to use compost fertilizers for the agricultural soils enrichment. Keywords: Heavy metals, Ecological risk assessment, Agricultural soils, Compost and chemical fertilizer