Trace Element Concentration Changes in Brain Tumors: A Review.

A prospective study was initiated to evaluate computed tomography as a method for monitoring therapeutically induced changes in brain tumors. Early postoperative scans may be misleading in the evaluation of residual tumor because of trauma to the blood-brain barrier during operation. The size of the dominant mass (17/25), enhancement (11/25), edema (11/25), and ventricular distortion (14/25) were decreased in many patients after radiation therapy. Occasional tumors increased in size during radiation therapy (3/25). Enlargement of the lateral ventricles developed in 9 of 25 patients. Computed tomography offers definite advantages over nuclide brain scans, angiography and other diagnostic studies for evaluating therapeutically induced changes in brain tumors.

The study was undertaken to determine the effects of various substances (manure, clay, charcoal, zeolite, and calcium oxide) applied to a cobalt-contaminated soil (0, 20, 40, 80, 160 and 320 mg kg−1 of soil) on the content of certain trace elements in spring barley (main crop) and white mustard (after-crop). The effect of cobalt on the contents of the trace elements was ambiguous and was either antagonistic or synergistic in nature, depending on the organ and plant species. Generally, the substances applied to soil reduced the content of most trace elements in above-ground parts of both plants and in the roots of white mustard, in contrast to the roots of spring barley. Of all the substances, calcium oxide had the strongest and generally reducing effect on the content of trace elements in the tested organs of the plants; however, its effect was the weakest in the roots of white mustard. Statement of Novelty It is difficult to find in the literature the results of studies into the effect of mineral and other amendments used in our research (manure, clay, charcoal, zeolite, and calcium oxide) on trace elements content in plants if they are used with a view to weakening the effect of cobalt on plants. We think that it is the novelty in the results of environmental sciences. The literature refer to the application of organic matter, bentonite, zeolite and calcium oxide to neutralize other heavy metals. The research was carried out in the two plants system used for phytoremediation with main crop (spring barley—Hordeum vulgare L.) and after-crop (white mustard—Synapis alba L.). The trace elements were analyzed in test plants. The results of the research allowed to select the most effective substance to support the phytoremediation of soil contaminated with cobalt.

The trigger for some cases of juvenile diabetes has been suggested to be an interaction between a virus and various trace elements. Infection with human coxsackievirus B3 (CB3) in the murine model results in viral replication and inflammation in the pancreas. To determine how infection affects the trace element balance in the pancreas. Concentrations of the following trace elements were measured in the serum and pancreas during the early phase (days 1 and 3) of CB3 infection in female Balb/c mice: aluminium, arsenic, cadmium (Cd), calcium (Ca), cobalt (Co), copper (Cu), iron (Fe), lead (Pb), magnesium (Mg), manganese (Mn), mercury (Hg), selenium, silver, vanadium (V), and zinc (Zn). The trace element concentrations were measured through inductively coupled plasma mass spectrometry. The histopathology was established by hematoxylin-eosin techniques and immunohistochemical staining of both CD4 and CD8 cells of the pancreas. Infected mice developed expected clinical signs of disease. The only changes at day 1 occurred in the serum, with a pronounced decrease in the Zn concentration and a small increase in the V concentration. At day 3, concentrations of several trace elements, including Cu, Zn, Fe, Ca, V, and Mn, showed pronounced changes in both the serum and the pancreas. Ca, Cu, Mg, Mn, and V, but none of the potentially toxic elements, accumulated in the pancreas. Cu and V concentrations increased in the serum as well. Several trace element changes, preceding the development of pancreatitis, occurred in the pancreas in this viral infection, the exact pathogenic interpretation of which warrants further studies.

Abstract: A brain tumour is described by the presence of abnormal cells in the brain's tissues. Brain tumours can be benign (not cancerous) or malignant (cancerous). The malignant brain tumour is one of the leading and common cancers in the world. There are two types of tumours, primary tumours that develop in the brain and secondary tumours that start in another region of the body and then spread to the brain. The precise identification of the size and location of a brain tumour is crucial in the diagnosis of a brain tumour and is often diagnosed with magnetic resonance imaging (MRI). This book chapter discusses the major types of brain tumours and the advancements in computeraided approaches for detecting brain tumours. The manuscript gives an overview of various recent machine learning and medical image processing approaches developed recently for the identification and classification of brain tumours. Several medical image dataset available for the research works in this domain is also briefed in this article. The major research challenges which can be addressed by the researchers in the domain of brain tumour detection are also discussed in this article. Method: This manuscript mainly discusses various medical image processing methods to detect brain tumors. Results: The manuscript discusses the efficiency of the existing schemes and the key areas where further improvement is required Conclusion: This manuscript gives an overview of various categories of brain tumors, existing methods to detect brain tumors, the critical challenges in this domain and the medical image dataset available for the study.

Background: Accuracy of preoperative brain tumor’s histopathologic differentiation is very important to determine preoperative staging, intraoperative management and postoperative therapy. Diffusion weighted magnetic resonance imaging is an advanced technique developed as an important method for brain tumor assessment. Objectives: This study aimed to investigate correlation between diffusion weighted imaging (DWI) profile and apparent diffusion coefficient (ADC) value with brain tumor’s histopathology. Methods: This study examined 86 subjects with brain tumors using magnetic resonance imaging and histopathology examination at Dr. Soetomo Teaching Hospital and evaluated DWI profile and ADC maps. The spherical ROI on ADC maps was placed on the solid part of the tumor to measure ADC value. Spearman’s correlation test was conducted to determine correlation between DWI profile and ADC values with histopathological grading and types of brain tumor. Results: There was a significant correlation between DWI profile and ADC values (p = 0.000), as well as DWI and ADC values with histopathological grading and types of brain tumor (p = 0.000). There was an inverse corelation between ADC value and histopathological grading. The higher the ADC value, the lower the brain tumor grade, while lower ADC value resulted in high tumor grade. The average ADC value of grade-1 meningiomas was 1.061±0.257 x 10-3 mm2/sec, pilocytic astrocytoma was 1.301±0.107 x 10-3 mm2/ sec, glioblastoma multiforme was 0.831±0.080 x 10-3 mm2/sec, and medulloblastomas was 0.600±0.078 x 10-3 mm2/sec. Conclusion: Evaluation on DWI profile and ADC value could provide additional information on conventional magnetic resonance imaging examination to determine histopathological grading and types of both intra and extra-axial brain tumors.

Numerous studies have demonstrated that prostaglandin H synthase-2 (PHS-2) is involved in gastrointestinal carcinogenesis, and that nonsteroidal anti-inflammatory drugs (NSAIDs), which inhibit PHS, can reduce the risk of colon cancer. In brain tumors, elevated prostaglandin production and its correlation to anaplastic grade of gliomas have been demonstrated. To determine whether the increased prostaglandin production is due to enhanced expression of PHS-2 and whether the up-regulation of PHS-2 has any correlation to histopathological findings in brain tumors, we evaluated the profile of PHS expression in several human glioma cell lines and surgical specimens from patients with various types of brain tumors. In glioma cell lines, five out of six cell lines showed constitutive expression of PHS-2, whereas PHS-1 was weakly expressed in all of them. All surgical specimens, except an ependymoma, which expressed both isozymes equally, expressed PHS-2 mRNA predominantly. Immunohistochemistry of various types of brain tumors, including six glioblastomas, nine astrocytomas, six meningiomas, five medulloblastomas, four craniopharyngiomas, three ependymomas, three neurinomas, two oligodendrogliomas, two malignant lymphomas, two dysembryoplastic neuroepitherial tumors and one metastatic brain tumor showed PHS-2 staining in most cases. In gliomas, astrocytomas (grade 2 and 3) were strongly stained, but the staining intensity of glioblastomas was relatively weak. Meningiomas and a metastatic brain tumor were also strongly stained. Our data thus suggest that most brain tumors express PHS-2, which may also play a role in tumorigenesis in the brain.

One of the most dangerous diseases is a brain tumor that may affect children as well as adults both. Brain tumors are responsible for 80-90 percent of all primary Central Nervous System (CNS) cancers. Each year, around 12,000 A brain tumor is discovered in a person. When diagnosed with a malignant brain or CNS tumor, males and the five-year survival rate for women is approximately 33% and 37% respectively. There are several types of brain tumors, including pituitary tumors, malignant tumors, benign tumors and more. Increased life expectancy for patients should be achieved by appropriate therapy, planning, and precise diagnostics. Magnetic resonance imaging is the most effective method for identifying brain tumors (MRI). Scanners produce massive volumes of picture data. The radiologist examines these pictures. Automated classification technologies such as Artificial intelligence (AI) and machine learning (ML) have regularly outperformed manual categorization in terms of accuracy. As a consequence, offering a system that employs Deep Learning Techniques and Algorithms such as ANN (Artificial Neural Networks), CNN (Convolution Neural Networks), TL (Transfer Learning) and GLCM for recognizing and tracking it will benefit doctors worldwide.

Application of mineral fertilisers can entail an increase in trace element content in the soil. In consequence, their elevated uptake by plants and transfer to further trophic chain links may occur. The aim of the research reported here was to determine the usefulness of the tested organic materials, such as humic acids, for reduction of the content of trace elements in two soils fertilised with excessive doses of nitrogen fertilisers. Soil type had a considerable effect on soil trace element content. The content of most trace elements (cadmium, lead, chromium, cobalt, nickel, manganese, and iron) was higher in loamy sand than in sand. Among the tested fertilisers, a higher content of most soil trace elements was found after the application of ammonium nitrate. Urea fertilisation led to a decrease in the content of cadmium, chromium, copper, and zinc in both soils; cobalt, manganese, and nickel in sand; and an increase in concentration of cobalt and manganese in loamy sand, relative to the subjects fertilised with ammonium nitrate. Urea ammonium nitrate solution (UAN) decreased the content of chromium, cadmium, copper, nickel, and zinc in both soils; lead in the sand; and cobalt in the loamy sand, while raising the content of lead in the loamy sand, relative to the subjects fertilised with ammonium nitrate. The impact of urea and UAN on the remaining trace element content in the soils was comparable to that effected by ammonium nitrate. The effect of humic acids on trace element content in the soil tended to be beneficial, as they reduced the soil concentrations of these elements compared to the control subject (without their application). However, it should be emphasised that their effect depended on nitrogen fertiliser form and soil type. Humic acids can effectively reduce the uptake of trace elements by some plant species.

Intraluminal thrombus thickness is not related to lower concentrations of trace elements in the wall of infrarenal abdominal aortic aneurysms

Investigating post-depositional alteration of trace elements in fish scales using tagged and recaptured wild salmon

Susceptibility analysis is an intelligent technique that not only assists decision makers in assessing the suspected severity of any sort of brain tumour in a patient but also helps them diagnose and cure these tumours. This technique has been proven more useful in those developing countries where the available health-based and funding-based resources are limited. By employing set-based operations of an arithmetical model, namely fuzzy parameterised complex intuitionistic fuzzy hypersoft set (FPCIFHSS), this study seeks to develop a robust multi-attribute decision support mechanism for appraising patients’ susceptibility to brain tumours. The FPCIFHSS is regarded as more reliable and generalised for handling information-based uncertainties because its complex components and fuzzy parameterisation are designed to deal with the periodic nature of the data and dubious parameters (sub-parameters), respectively. In the proposed FPCIFHSS-susceptibility model, some suitable types of brain tumours are approximated with respect to the most relevant symptoms (parameters) based on the expert opinions of decision makers in terms of complex intuitionistic fuzzy numbers (CIFNs). After determining the fuzzy parameterised values of multi-argument-based tuples and converting the CIFNs into fuzzy values, the scores for such types of tumours are computed based on a core matrix which relates them with fuzzy parameterised multi-argument-based tuples. The sub-intervals within [0, 1] denote the susceptibility degrees of patients corresponding to these types of brain tumours. The susceptibility of patients is examined by observing the membership of score values in the sub-intervals.

There are no good blood and serum biomarkers for detection, follow up, or prognosis of brain tumors. However, they are needed for more detailed tumor classification, better prognosis estimation and selection of an efficient therapeutic strategy. The aim of this study was to use the epigenetic changes in DNA of peripheral blood samples as a molecular marker to diagnose brain tumors as well as other diseases. We have applied a very precise thin-layer chromatography (TLC) analysis of the global amount of 5-methylcytosine (m5C) in DNA from brain tumors, colon and breast cancer tissues and peripheral blood samples of the same patients. The m5C level in tissue DNA from different brain tumor types, expressed as R coefficient, changes within the range of 0.2–1.6 and overlaps with R of that of blood samples. It negatively correlates with the WHO malignancy grade. The global DNA hypomethylation quantitative measure in blood, demonstrates a big potential for development of non-invasive applications for detection of a low and a high grade brain tumors. We have also used this approach to analyze patients with breast and colon cancers. In all these cases the m5C amount in DNA cancer tissue match with data of blood. This study is the first to demonstrate the potential role of global m5C content in blood DNA for early detection of brain tumors and others diseases. So, genomic DNA hypomethylation is a promising marker for prognosis of various neoplasms as well as other pathologies.

Preliminary study of oxidative stress biomarkers and trace elements in North Sea Harbour Seals

Royal jelly (RJ) is commercially harvested after the 4th day of queen larval age. In the current study, it was harvested after 24, 48, 72, and 96 hours after grafting of 1-day larval age queens to investigate changes in macro and trace elements associated with harvesting time. The RJ yields were significantly affected by harvest time, and the highest yield was obtained 72 hours after grafting. The highest phosphorus (P) and zinc (Zn) contents were obtained from RJ harvested 24 hours after grafting. Royal jelly harvested 48 hours after grafting had the highest concentrations of magnesium (Mg), calcium (Ca), potassium (K), sodium (Na), iron (Fe), and manganese (Mn). Likewise, RJ harvested 96 hours after grafting had higher concentrations of copper (Cu). Royal jelly harvested 72 hours after grafting showed the second rank for P, Mg, Ca, K, Na, Fe, Cu, and Mn concentrations. In descending order, P, Mg, Ca, and K were the most dominant elements in RJ harvested at different times after grafting. The Mg, Ca, K, Na, Cu, and Mn concentrations in RJ were all positively correlated, and P, Fe, and Zn were positively correlated. The P and Zn were negatively correlated with Ca, Cu, and Mn. It was concluded that macro and trace element contents in RJ can differ depending on the harvest time after grafting. We recommend harvesting RJ at 72 hours after grafting for possible use as healthy nutritional human food supplement.

The Critical Zone is an important source of trace elements to headwater streams during the snowmelt runoff period, yet the mechanisms of trace element release are poorly characterized. To evaluate changes in water chemistry in response to snowmelt, we measured trace element and major ion concentrations at three sites in the upper Provo River in northern Utah, USA, over a five–year period spanning years with below– and above–average discharge. We also sampled snowpack, ephemeral streams, and soil water to investigate trace element sources. The river drains siliciclastic bedrock above the upper site, carbonate rocks between the upper and middle sites, and volcanic rocks between the middle and lower sites, with minimal anthropogenic impacts in the watershed. Concentrations of specific trace metals (Be, Al, Cu, and Pb) and rare earth elements (represented by La and Y) increased during snowmelt runoff each year at all three sites, with decreasing concentrations from upstream to downstream. In contrast, major ion concentrations, including Ca2+ and SO42-, were similar year–round at the upper site and were diluted during snowmelt at the lower sites, with increasing concentrations from upstream to downstream. The snowmelt runoff period (April–June) accounted for >84% of the annual trace element loading, with most trace element inputs occurring above the upper sampling site. Concentration–discharge (C–Q) relationships revealed variations in solute behavior from upstream to downstream. For example, at the upstream site the trace elements had a slight positive slope in log C–log Q space, while Ca2+ and SO42- had zero slope. At the downstream sites, the trace elements had a strong positive slope and Ca2+ and SO42- had a negative slope. Trace element concentrations were relatively low in snowpack but elevated in ephemeral streams and soil water, suggesting that flushing of shallow soils by snowmelt causes increased trace element concentrations with positive C–Q relationships in the upper part of the river. Trace element loads propagate downstream where concentrations are diluted by groundwater inputs from carbonate bedrock. Our results demonstrate that soil water flushing in the Critical Zone at the headwaters of mountain streams is an important control on downstream water chemistry.