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Background: Acetamiprid (ACE) is a neonicotinoid insecticide, known in the trade market as: Mospilan, Assilan and Chipco. It is used to get rid of sucking insects. Its intake might cause toxic effects on the cerebellum. Objectives: The study aimed to determine the pathological effects of acetamiprid on the cerebellar cortex of male adult albino rats and the role of both Curcumin and Vitamin C in altering those pathological effects. Materials and methods: Forty male adult albino rats were used in this study. The rats were divided into four groups (n=10 each): group I (control) and received corn oil, group II (treated with acetamiprid orally), group III (treated with acetamiprid + Curcumin orally), group IV (treated with acetamiprid + Vitamin C orally). Cerebellar tissue samples were used for histopathological examination using light and transmission electron microscopy. Morphometric and statistical studies were done to measure Purkinje cell (PC) number and the thickness of the granule layer. Results: There was a significant structural damage of cerebellar cortical tissue in group II. Group III showed restoring of the pathological structure of cerebellar cortex compared to group II. Group IV showed less improvement compared to group III. Conclusion: Curcumin and vitamin C could have a protective effect against neurotoxicity induced by acetamiprid via their antioxidant property.

Background: Aspartame (ASP) is a non-nutritive sweetener that is greatly used in drinks, foods, beverages and pharmaceuticals. There are controversies about its safety. So, studies are important to prove or disapprove the present fears about aspartame. Objectives: It is to evaluate the effect of ASP on the postnatal development of cerebellum in rat offspring. Material and Methods: Eight male offspring of each control and experimental groups were randomly selected at the postnatal day (PND): 1,7,15.21 and 60 days. Aspartame (250 mg/kg body weight/day) was given orally to experimental group of animals during pregnancy and lactation period. Specimens were prepared for light and electron microscopic studies. Morphometric and statistical studies were done to measure the diameter of granular cells nuclei. Results: Control group of animals showed normal development of cerebellar cortex. Cerebella of the experimental group of animals showed a disrupted architecture with degenerative changes especially in Purkinje cells. Splitting and disruption of the myelin sheath were detected. Experimental group showed a highly significant decrease in the mean granular cell nuclear diameter (p < 0.001) when compared to the control group. Conclusions: Administration of aspartame during pregnancy has harmful effects on the developing cerebellum of albino rat’s offspring.

During the first week of development, human embryos form a blastocyst composed of an inner cell mass and trophectoderm (TE) cells, the latter of which are progenitors of placental trophoblast. Here, we investigated the expression of transcripts in the human TE from early to late blastocyst stages. We identified enrichment of the transcription factors GATA2, GATA3, TFAP2C and KLF5 and characterised their protein expression dynamics across TE development. By inducible overexpression and mRNA transfection, we determined that these factors, together with MYC, are sufficient to establish induced trophoblast stem cells (iTSCs) from primed human embryonic stem cells. These iTSCs self-renew and recapitulate morphological characteristics, gene expression profiles, and directed differentiation potential, similar to existing human TSCs. Systematic omission of each, or combinations of factors, revealed the crucial importance of GATA2 and GATA3 for iTSC transdifferentiation. Altogether, these findings provide insights into the transcription factor network that may be operational in the human TE and broaden the methods for establishing cellular models of early human placental progenitor cells, which may be useful in the future to model placental-associated diseases. [ABSTRACT FROM AUTHOR]

Simple Summary: Pancreatic cysts represent a category of lesions that arise in the pancreas with the potential to transform into cancer. Intraductal papillary mucinous neoplasms (IPMNs) are the most common among these cysts. Current methods to detect early cancer in IPMNs are inaccurate. This review summarizes the latest advances in the diagnosis and risk assessment of IPMNs and mainly focuses on a novel imaging technique known as confocal laser endomicroscopy. Additionally, this review explores the integration of this imaging technique with artificial intelligence to optimize decision-making in managing these lesions. Pancreatic cancer is on track to become the second leading cause of cancer-related deaths by 2030, yet there is a lack of accurate diagnostic tests for early detection. Intraductal papillary mucinous neoplasms (IPMNs) are precursors to pancreatic cancer and are increasingly being detected. Despite the development and refinement of multiple guidelines, diagnosing high-grade dysplasia or cancer in IPMNs using clinical, radiologic, endosonographic, and cyst fluid features still falls short in terms of accuracy, leading to both under- and overtreatment. EUS-guided needle-based confocal laser endomicroscopy (nCLE) is a novel technology that allows real-time optical biopsies of pancreatic cystic lesions. Emerging data has demonstrated that EUS-nCLE can diagnose and risk stratify IPMNs more accurately than conventional diagnostic tools. Implementing EUS-nCLE in clinical practice can potentially improve early diagnosis of pancreatic cancer, reduce unnecessary surgeries of IPMNs with low-grade dysplasia, and advance the field of digital pathomics. In this review, we summarize the current evidence that supports using EUS-nCLE as a diagnostic imaging biomarker for diagnosing IPMNs and for risk stratifying their degree of neoplasia. Moreover, we will present emerging data on the role of adding artificial intelligence (AI) algorithms to nCLE and integrating novel fluid biomarkers into nCLE. [ABSTRACT FROM AUTHOR]

Efficiently optimizing cropping patterns is crucial for the sustainable agriculture development, especially in arid regions like Saudi Arabia. This study specifically aimed to gradually optimize cropping patterns in Saudi Arabia over next decade. The cropping pattern of 2023 according to ministry of environment water and agriculture was assessed to identify crops with potential for optimization based on economic revenue, water consumption. Subsequently, three optimization strategies were devised: maximizing total income, minimizing total water consumption, and maximizing productivity. The strategy focused on maximizing income projected a remarkable 17.6/% increase in total agricultural income by simply increasing the current water resources by 4.2%. On the other hand, the strategy aimed at minimizing water consumption could save 13.4% of water resources, but it would result in 4.6% reduction in total income. Alternatively, the strategy prioritizing productivity maximization would lead to a significant 15.6% increase in total income while reducing water resources by 0.7%. [ABSTRACT FROM AUTHOR]

The soil‐water characteristic curve (SWCC) is a key input to many hydrological and water‐quality models that simulate water movement and solute transport in the vadose zone. Over the past four decades a considerable number of pedotransfer functions (PTFs) have been developed to predict SWCC. The goal of this study was to conduct a comprehensive evaluation of 30 PTFs, 11 discrete functions and 19 continuous functions. The SWCC predicted by different PTFs was statistically compared to SWCC measured for 2046 United States soils. The performance of each function was evaluated for soils of different textural classes and at four matric potentials: −4, −10, −33 and − 1,500 kPa. The results showed that for point PTFs, the PTF developed by Adhikary et al. (2008), was the best function to predict SWCC in very fine soils, whereas the PTF developed by Fooladmand (2011), showed the best performance in fine, medium fine, medium and coarse soils. For continuous PTFs, the PTF developed by Saxton et al. (1986), showed the best performance in very fine soil; the PTF developed by Cosby et al. (1984), showed the best performance in fine soil; the PTF developed by Rawls and Brakensiek (1985) showed the best performance in medium fine soil; and the PTF of Zacharias and Wessolek (2007), showed the best performance in medium and coarse soils. With respect to matric potentials, the PTFs of Gupta and Larson (1979), Dashtaki et al. (2010), and Hua et al. (2011), were the best performing point PTFs to predict SWCC at −4, −10, −33 and − 1,500 KPa, respectively. The continuous PTFs developed by Mayr and Jarvis (1999), Rosetta SSC (Schaap et al. 2001), Cosby et al. (1984), and Al Majou et al. (2007), showed the best performance to predict SWCC at −4, −10, −33 and − 1,500 kPa, respectively. The results of this study may be useful to hydrologic modelling as it identifies the most accurate PTF for each soil textural class and across the matric potential ranges. Highlights: Performances of 30 pedotransfer functions of SWCCs were evaluated using soil database from the USA.The pedotransfer functions were classified into 11 point functions and 19 continuous functions.The pedotransfer functions were evaluated at five soil texture classes and four matric potentialsBest‐performing pedotransfer functions were identified for each texture class and matric potential. [ABSTRACT FROM AUTHOR]