The purpose of this study was to evaluate the usefulness of in vivo 31P magnetic resonance spectroscopy (MRS) for monitoring changes in growth-related phosphate metabolite concentration and intracellular pH value in rabbit thigh muscle implanted with VX-2 carcinoma. The time-course magnetic resonance imaging (MRI) and in vivo 31P MRS were examined weekly in the course of 10 weeks following the onset of a VX-2 carcinoma implantation. The spectra were quantitatively analyzed to obtain vital information on the time course variation of the phosphorus metabolites and intracellular pH value according to the tumor growth. Elevation in the concentrations of phosphormonoesters (PME), inorganic phosphate (Pi), and phosphodiesters (PDE) was observed over the time course of 3-4 weeks after the implantation of VX2 carcinoma, while the rest of the metabolites, PCr and ATP tended to be constant. The concentration changes of PME, Pi, and PDE were positively correlated with the volumes of tumor necrosis. The intracellular pH values decreased with the time course of tumor growth and the volumes of tumor necrosis. In vivo 31P MRS is capable of non-invasive monitoring of intracellular pH values as well as the concentration changes of phosphate metabolites during tumor growth. 
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Growth-related changes of phosphorus metabolites in VX-2 carcinoma implanted into rabbit thigh muscle: in vivo 31P MR spectroscopy 
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<div>Background: Chinchilla is a laboratory animal used in anatomical urinary tract research. Computed tomography (CT) and magnetic resonance imaging (MRI) are tools methods used in the diagnosis and assessment of kidney diseases. The aim of this study is to determine the anatomical architecture of the kidneys in chinchillas by computerized tomography and magnetic resonance imaging. 
 
Methods: A total of 12 chinchillas (6 male and 6 female) aged 18 months. After anesthesia computed tomography and magnetic resonance imaging was performed. CT and MRI were analyzed with a software program. 3D reconstruction of the obtained images was performed.&nbsp; 
 
Result: Computed tomography showed that the right kidney starts at the midline of the 1st lumbar vertebra in the transversal plane and ends at the cranial end of the 4th lumbar vertebra and the left kidney ends at the cranial end of the 3rd lumbar vertebra and the caudal end of the 5th lumbar vertebra. Pelvis renalis had higher X-ray density compared to medulla and cortex renal. The left kidney was bean-shaped and the right kidney was oval-shaped. Anatomical images were obtained on T1 contrast magnetic resonance T2 magnetic resonance images showed the corticomedullar system and the pyelocalyx system better.</div>

​​Anatomical Computed Tomography and Magnetic Resonance Imaging Architecture of the Kidneys in the Chinchilla (Chinchilla lanigera)

<div>Background: The major part of the edible oil used in Iran is supplied through imports. It is important to increase the yield of oilseed crops, especially soybeans, in non-chemical and environmentally friendly ways, along with its easy availability and low cost. The use of magnetic water as a new method, increases the yield of plants by improving solubility and access the nutrients. On the other hand, in recent years, methanol spraying as a source of carbon dioxide, which increases the concentration of this gas around the plant, enhancing the photosynthesis and plant yield. This study was conducted to study the efficacy of different intensities of magnetic water and various concentrations of methanol foliar application on agronomic traits of soybean. &nbsp; 
 
Methods: This experiment was carried out as split plot in a randomized complete block design with 3 replications during two consecutive years 2016-17. The main plot was irrigated with magnetic water in 4 intensity (0: control, 4, 8, 12mTesla) and a subplot was methanol spraying in 4 volumetric percentage (distilled water: control, 10, 20 and 30% v/v). &nbsp; 
 
Result: Photosynthetic pigments viz. (Chlorophyll a, b, carotenoid), yield attributes, seed yield, biological yield, seed protein and soybean economics were significantly affected by the magnetic water and methanol spraying. Seed yield and net return, as the most important traits increased by magnetic irrigated with 8 and 12mTesla intensities, compared to control, by 70.05-72.19% and 122.37-126.05%, respectively. Furthermore the maximum biological, stover yields and protein obtained by 8mTesla magnetic irrigation, compared to control, it showed 59.54, 54.9 and 10.07% superiority, respectively. Also, methanol foliar application at 20% concentration increased seed yield, biological yield, seed protein and net return by 19.01, 13.73, 5.24 and 26.43%, respectively.</div>

<div>Efficacy of Magnetic Water and Methanol on Agronomic Traits of Soybean (Glycine max L.)</div>

<div>Background: Humic acid is a natural bio-stimulant, which has a major influence on growth and crop quality. Also, Magnetic water treatment enhances both crop productivity and quality, which leads to the efficient use of cultivated land by using water resources available for crop production. This study aims to determine the effects of magnetized water irrigation and application of humic acid with different concentrations as a bio-stimulation on tomato plants, Solanum Lycopersicon cv. Hybrid &ldquo;86&rdquo;. 
 
Methods: The experiment was conducted during the tow growing seasons of 2018 and 2019 at the Agricultural Experimental Station Farm at Abies region, Faculty of Agriculture, Alexandria University, Egypt. The experiment design was split-plot with three replications. Two irrigation water treatments (magnetized and non-magnetic water) were arranged in the main plots and four concentrations of humic acid (0, 1, 2 and 3 g L-1) were distributed over sub-plots. 
 
Result: The results showed that irrigation with magnetized water had a positive effect on the vegetative growth traits, yield and its components and the quality of tomato fruits parameters. There was also a clear desirable effect of humic acid addition with different concentrations, as the results indicated that the use of the highest concentration of humic acid (3 g L-1) reflected the highest values for all the studied traits. The results of the interaction between irrigation with magnetized water and application of humic acid showed that the best results and the highest values for all studied characters were recorded when using magnetic water (MW) combined with 3 g L-1 of humic acid (HA), without significant differences from the interaction treatment MW combined with 2 g L-1 HA for most traits. However, the two treatments combinations MW with 2 g L-1 HA and Non-MW with 3 g L-1 HA didn&rsquo;t significant differ from each other for all studied characters at the two growing seasons. These results indicated that using the magnetic water with humic acid led to the possibility of reducing the amount of humic acid by one-third and enhances both crop productivity and quality of tomato plants. Generally, we can recommend using magnetized water irrigation with humic acid addition at concentration of 3.g L-1 or 2.g L-1 to enhance the productivity and quality of the tomato plant.&nbsp;</div>

<div>Enhancing the Productivity and Quality of Tomato using Magnetized Water and Humic Acid as Bio-stimulant Agents</div>

<div>Background: Chickpea is the third major pulse produced globally, with 11.6 million tonnes produced per annum (Merga and Haji, 2019).&nbsp;Sugar alcohols, inulin, starch are all prebiotic carbohydrates found in chickpeas (Johnson et al., 2020).&nbsp;Near-Infrared (NIR) spectroscopy is a non-destructive, versatile and powerful analytical technique. 
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Methods: Spectral data obtained from NIR spectroscopy requires application of various techniques to extract useful information from spectral data which is further used for building various models for prediction of physical or chemical components presents in agricultural crops. The main aim of this study is to apply various machine learning algorithms especially effective in predicting sugar concentration in chickpea. Sugar prediction models are developed using Linear Regression (LR), Artificial Neural Network (ANN), Random Forest (RF), Support Vector Regression (SVR) and Decision Tree Regression (DTR) algorithms. Performance of the models is evaluated using measures namely, Root Mean Square Error (RMSE), Residual Standard Error (RSE), Coefficient of Determination (R2) and Adjusted Coefficient of Determination (adjusted R2). 
 
Result: It was observed that, RF outperformed all other models in terms of accuracy for predicting sugar component from preprocessed spectra, with RMSE, RSE, R2 and adjusted R2 values of 0.054, 0.062, 0.954 and 0.937, respectively. The accuracy of the ANN model is similar to that of the RF, with minor differences in RMSE, RSE, R2 and adjusted R2 , values of 0.057, 0.067, 0.952 and 0.935.</div>

Comparing Various Machine Learning Algorithms for Sugar Prediction in Chickpea using Near-infrared Spectroscopy

<div style="text-align: justify;">The present study was conducted to investigate the effects of electromagnetic field on germination characteristics of pigweed (Amaranthus retroflexus). It was conducted in factorial randomized complete design with three replications in Tarbiat modares University, during 2013-14. Pigweed seeds were subjected to three magnetic field levels created by magnets with 4000G, 5000G and 6000G for exposure times of 5, 35 and 65 minutes followed by which the seeds were placed in petri dishes and transferred on germinator. The germination characteristics, germination percentage, time to 50% germination, germination evenness and the rate of germination &nbsp;were recorded .The sprouts were bisected in four-leaf stage and they were evaluated in their morphologic characteristics and the amount of protein and &acirc;-amylase enzymatic activity. Results indicated that the mutual effect of the magnetic field exposure duration and intensity was found significant on all the examined traits in pigweed. The highest and lowest germination in pigweed seeds were recorded with 5000G-5minutes and 6000G-65minutes treatments, respectively. The treatments in which the weed seeds were exposed to 5000G intensity for 65minutes, 6000G for 35minutes produced the highest and the lowest amounts of protein, respectively. Based on the experiment results the magnetic field exposure intensity and duration influence the germination characteristics, protein content and &acirc;-amylase enzymatic activity rate, this can be a promised method in controlling the weeds in farms.</div>

<div style="text-align: justify;">Investigating the effects of various magnetic field exposure intensities and periods in pigweed (Amaranthus retroflexus) seeds</div>

<div>Type-1 diabetes mellitus is an insulin-dependent autoimmune disease, which is very common in the human populations regardless of gender. The aim of this study was to evaluate the effects of pulsed magnetic field (PMF), a non-invasive procedure, on male and female rats with type 1 diabetes, particularly on weight loss ratios, blood glucose levels and diabetic neuropathy. Before, the experimental groups were divided into three groups as control (C (F or M), diabetes (DM (F or M), controlled diabetes (DM(F)-INS or DM(M)-INS) groups according to their sex differences, then these experimental groups were exposed to magnetic field effect (PMF). The rats in the PMF groups were exposed to the pulsed magnetic field at 50 Hz (1.5 mT intensity) for 1h/5days/month. The body weights and blood glucose levels were measured once a week over a month. Female and male diabetic rats developing diabetic neuropathy were evaluated with thermal (thermal latency) and dynamic (mechanical threshold) plantar tests. After six-weeks of PMF treatment, the weight loss rate and increased blood glucose levels due to diabetes reversed in both female and male diabetic rats upon PMF treatment (p &lt;0.05). In diabetic neuropathic female and male rats, the thermal latency values increased, while the mechanical threshold values &nbsp; decreased. The reduction in diabetic neuropathic rats were statistically significant in diabetic rats (p &lt;0.05). The increased or decreased mechanical threshold and thermal latency values in diabetic neuropathic rats were statistically significant in only male diabetic rats (p &lt;0.05). &nbsp;Our studies may imply that the effect of PMF in neuropathic pain is gender dependent further inferring that hormonal mechanisms were also important in PMF dependent regulation.&nbsp;</div>

<div>Gender-Specific differences in pulsed magnetic field exposed to diabetic neuropathic rats</div>

<div style="text-align:justify">The Study was conducted to evaluate the additive effect of selected feed additives (Glycerol, a mixture of exogenous fibrolytic enzymes (EFE), a mixture of probiotics and rumen protected methionine (RPM) under both in vitro and in vivo conditions. The optimum dose of pre-mixture of feed additives (PFA) was evaluated by in vitro gas production technique in two stages. The marginal increase in Y-max and in vitro neutral detergent fiber digestibility (IVNDFD) for each incremental increase in PFA was compared graphically and it was found to be 1.7 %. In in vivo trial, 12 crossbred HF cows were equally divided into 3 groups based on milk yield and average days in lactation. The optimized dose of PFA was added to the concentrate supplements without (T1) or with buffer (T2), control group (CG) was fed with the basal diet (roughage: concentrate ratio of 60:40). Results indicated that PFA with or without buffer had no significant effect on nutrient intake and digestibility. Fat corrected milk yield (FCM), milk fat, total solids (TS) and milk protein were significantly (P&lt;0.01) increased in TGs than that of CG. From the results, it may be concluded that optimized PFA had an additive effect on milk production efficiency but not on nutrient intake and digestibility. Further, different groups of feed additives can be evaluated for additive effect, which may pave the way for commercial product preparation.&nbsp;</div>

<div style="text-align: justify;">Evaluation of additive effect of feed additives in crossbred cows under in vitro and in vivo conditions</div>

Background: Wheat quality and safety are crucial for global food security and regional agricultural economies. Conventional analytical methods for assessing grain composition and quality-while accurate-are often time-consuming, destructive and resource-intensive. In contrast, near-infrared spectroscopy (NIR) has emerged as a rapid, non-destructive alternative that provides detailed chemical and physical insights. Recent advancements in machine learning have enhanced NIR&rsquo;s analytical capabilities by enabling the development of predictive models that accurately categorize, quantify and monitor grain quality parameters. These models-spanning from linear regression methods to intricate neural networks-enable researchers to discern significant patterns from spectral data, even amidst noise or overlapping signals. 
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Methods: This study used NIR spectroscopy and machine learning models to evaluate wheat quality across multiple Albanian regions during the 2023 harvest. NIR spectra were preprocessed using standard normalization and smoothing techniques. Machine learning models-including PLSR, SVM and random forest-were trained to predict key quality traits such as protein content and moisture. Model performance was validated using cross-validation metrics (RMSE, R&sup2;, accuracy), demonstrating the potential of NIR-ML integration for rapid, non-destructive grain assessment. 
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Result: Protein content ranged from 9.6% to 15.0%, gluten from 19.4% to 37.5% and starch from 66.3% to 71.5%, indicating consistent nutritional profiles across samples. Sedimentation index values (21.1-57.8 cm&sup3;) and moisture levels (9.8-12.5%) confirmed compliance with EU food safety standards. The integration of NIR spectroscopy with machine learning enabled rapid, non-destructive prediction of wheat quality traits, supporting scalable decision-making in agri-food systems.

Applications of Machine Learning Models in Near-infrared Spectroscopy for Small-grain Quality Control

Background: Scurrula parasitica L. is a herbaceous growing shrub of Loranthaceae family traditionally used for diuretic, tranquilizing and hypotensive activity. It shows anti-diabetic, cytotoxic, anticancer, anti-hepatoxic and immunomodulatory activity as it has secondary metabolites like alkaloids, terpenoids, phenols, flavonoids, tannins, saponins, etc. The secondary metabolites have potential antioxidant activity as they have the ability to scavenge free radicals and also improve the in vivo antioxidant status. However, no study has been conducted to evaluate their effect on in vivo antioxidant status. 
 
Methods: The in vitro antioxidant activity was estimated by three in vitro assay methods viz. DPPH free radical scavenging assay, Ferric reducing antioxidant potential (FRAP) assay and Total phenolic content (TPC) assay while the in vivo antioxidant status was&nbsp; evaluated by estimating the levels of SOD, Catalase, GPx and MDA. 
 
Result: The ethanol extract of the leaves shows maximum in vitro antioxidant activity in case of DPPH free radical scavenging assay and 50% ethanol extract shows highest antioxidant activity for FRAP assay and Total phenolic content assays. The ethanol extract of the plants improves the in vivo antioxidant status viz. Superoxide dismutase (SOD), Catalase, Glutathione peroxidise (GPx) and Malondehyde (MDA) among the STZ induced diabetic rates.