Examination of Trace Metals and Their Potential Transplacental Transfer in Pregnancy

With the ever-growing concern for human health and wellbeing, the prenatal period of development requires special attention since fetuses can be exposed to various metals through the mother. Therefore, this study explored the status of selected toxic (Pb, Cd, Ni, As, Pt, Ce, Rb, Sr, U) and essential trace metals (Mn, Co, Cu, Zn, Se) in the umbilical cord (UC) sera, maternal sera, and placental tissue samples of 92 healthy women with normal pregnancies. A further aim focuses on the potential transplacental transfer of these trace metals. Based on the obtained levels of investigated elements in clinical samples, it was observed that all of the trace metals cross the placental barrier and reach the fetus. Furthermore, statistical analysis revealed significant differences in levels of toxic Ni, As, Cd, U, Sr, Rb, and essential Mn, Cu, and Zn between all three types of analyzed clinical samples. Correlation analysis highlighted As to be an element with levels that differed significantly between all tested samples. Principal component analysis (PCA) was used to enhance these findings. PCA demonstrated that Cd, Mn, Zn, Rb, Ce, U, and Sr were the most influential trace metals in distinguishing placenta from maternal and UC serum samples. As, Co, and Cu were responsible for the clustering of maternal serum samples, and PCA demonstrated that the Pt level in UC sera was responsible for the clustering of these samples. Overall, the findings of this study could contribute to a better understanding of transplacental transfer of these trace metals, and shed a light on overall levels of metal exposure in the population of healthy pregnant women and their fetuses.     

Electronic Structure and Solvation Effects from Core and Valence Photoelectron Spectroscopy of Serum Albumin

X-ray photoelectron spectroscopy of bovine serum albumin (BSA) in a liquid jet is used to investigate the electronic structure of a solvated protein, yielding insight into charge transfer mechanisms in biological systems in their natural environment. No structural damage was observed in BSA following X-ray photoelectron spectroscopy in a liquid jet sample environment. Carbon and nitrogen atoms in different chemical environments were resolved in the X-ray photoelectron spectra of both solid and solvated BSA. The calculations of charge distributions demonstrate the difficulty of assigning chemical contributions in complex systems in an aqueous environment. The high-resolution X-ray core electron spectra recorded are unchanged upon solvation. A comparison of the valence bands of BSA in both phases is also presented. These bands display a higher sensitivity to solvation effects. The ionization energy of the solvated BSA is determined at 5.7 ± 0.3 eV. Experimental results are compared with theoretical calculations to distinguish the contributions of various molecular components to the electronic structure. This comparison points towards the role of water in hole delocalization in proteins.     

The Effects of BSA-Stabilized Selenium Nanoparticles and Sodium Selenite Supplementation on the Structure,Oxidative Stress Parameters and Selenium Redox Biology in Rat Placenta

The chemical element selenium (Se) is a nonmetal that is in trace amounts indispensable for normal cellular functioning. During pregnancy, a low Se status can increase the risk of oxidative stress. However, elevated concentrations of Se in the body can also cause oxidative stress. This study aimed to compare the effects of BSA-stabilized Se nanoparticles (SeNPs, Se⁰) (BSA-bovine serum albumin) and inorganic sodium selenite (NaSe, Se⁺⁴) supplementation on the histological structure of the placenta, oxidative stress parameters and the total placental Se concentration of Wistar rats during pregnancy. Pregnant females were randomized into four groups: (i) intact controls; (ii) controls that were dosed by daily oral gavage with 8.6% bovine serum albumin (BSA) and 0.125 M vit C; (iii) the SeNP group that was administered 0.5 mg of SeNPs stabilized with 8.6% BSA and 0.125 M vit C/kg bw/day by oral gavage dosing; (iv) the NaSe group, gavage dosed with 0.5 mg Na₂SeO₃/kg bw/day. The treatment of pregnant females started on gestational day one, lasted until day 20, and on day 21 of gestation, the fetuses with the placenta were removed from the uterus. Our findings show that the mode of action of equivalent concentrations of Se in SeNPs and NaSe depended on its redox state and chemical structure. Administration of SeNPs (Se⁰) increased fetal lethality and induced changes in the antioxidative defense parameters in the placenta. The accumulation of Se in the placenta was highest in SeNP-treated animals. All obtained data indicate an increased bioavailability of Se in its organic nano form and Se⁰ redox state in comparison to its inorganic sodium selenite form and Se⁺⁴ redox state.     

Lignin Microspheres Modified with Magnetite Nanoparticles as a Selenate Highly Porous Adsorbent

Highly porous lignin-based microspheres, modified by magnetite nanoparticles, were used for the first time for the removal of selenate anions, Se(VI), from spiked and real water samples. The influence of experimental conditions: selenate concentration, adsorbent dosage and contact time on the adsorption capacity was investigated in a batch experimental mode. The FTIR, XRD, SEM techniques were used to analyze the structural and morphological properties of the native and exhausted adsorbent. The maximum adsorption capacity was found to be 69.9 mg/g for Se(VI) anions at pH 6.46 from the simulated water samples. The modified natural polymer was efficient in Se(VI) removal from the real (potable) water samples, originated from six cities in the Republic of Serbia, with an overage efficacy of 20%. The regeneration capacity of 61% in one cycle of desorption (0.5 M NaOH as desorption solution) of bio-based adsorbent was gained in this investigation. The examined material demonstrated a significant affinity for Se(VI) oxyanion, but a low potential for multi-cycle material application; consequently, the loaded sorbent could be proposed to be used as a Se fertilizer.     

Predicting body fat percentage based on gender,age and BMI by using artificial neural networks

In the human body, the relation between fat and fat-free mass (muscles, bones etc.) is necessary for the diagnosis of obesity and prediction of its comorbidities. Numerous formulas, such as Deurenberg et al., Gallagher et al., Jackson and Pollock, Jackson et al. etc., are available to predict body fat percentage (BF%) from gender (GEN), age (AGE) and body mass index (BMI). These formulas are all fairly similar and widely applicable, since they provide an easy, low-cost and non-invasive prediction of BF%. This paper presents a program solution for predicting BF% based on artificial neural network (ANN). ANN training, validation and testing are done by randomly divided dataset that includes 2755 subjects: 1332 women (GEN = 0) and 1423 men (GEN = 1), with AGE from 18 to 88 y and BMI from 16.60 to 64.60 kg/m². BF% was estimated by using Tanita bioelectrical impedance measurements (Tanita Corporation, Tokyo, Japan). ANN inputs are: GEN, AGE and BMI, and output is BF%. The predictive accuracy of our solution is 80.43%. The main goal of this paper is to promote a new approach to predicting BF% that has same complexity and costs but higher predictive accuracy than above-mentioned formulas.     

Numerical and experimental analysis of factors leading to suture dehiscence after Billroth II gastric resection

The main goal of this study was to numerically quantify risk of duodenal stump blowout after Billroth II (BII) gastric resection. Our hypothesis was that the geometry of the reconstructed tract after BII resection is one of the key factors that can lead to duodenal dehiscence. We used computational fluid dynamics (CFD) with finite element (FE) simulations of various models of BII reconstructed gastrointestinal (GI) tract, as well as non-perfused, ex vivo, porcine experimental models. As main geometrical parameters for FE postoperative models we have used duodenal stump length and inclination between gastric remnant and duodenal stump. Virtual gastric resection was performed on each of 3D FE models based on multislice Computer Tomography (CT) DICOM. According to our computer simulation the difference between maximal duodenal stump pressures for models with most and least preferable geometry of reconstructed GI tract is about 30%. We compared the resulting postoperative duodenal pressure from computer simulations with duodenal stump dehiscence pressure from the experiment. Pressure at duodenal stump after BII resection obtained by computer simulation is 4–5 times lower than the dehiscence pressure according to our experiment on isolated bowel segment. Our conclusion is that if the surgery is performed technically correct, geometry variations of the reconstructed GI tract by themselves are not sufficient to cause duodenal stump blowout. Pressure that develops in the duodenal stump after BII resection using omega loop, only in the conjunction with other risk factors can cause duodenal dehiscence. Increased duodenal pressure after BII resection is risk factor. Hence we recommend the routine use of Roux en Y anastomosis as a safer solution in terms of resulting intraluminal pressure. However, if the surgeon decides to perform BII reconstruction, results obtained with this methodology can be valuable.     

Fuzzy relation equations and reduction of fuzzy automata

We show that the state reduction problem for fuzzy automata is related to the problem of finding a solution to a particular system of fuzzy relation equations in the set of all fuzzy equivalences on its set of states. This system may consist of infinitely many equations, and finding its non-trivial solutions may be a very difficult task. For that reason we aim our attention to some instances of this system which consist of finitely many equations and are easier to solve. First, we study right invariant fuzzy equivalences, and their duals, the left invariant ones. We prove that each fuzzy automaton possesses the greatest right (resp. left) invariant fuzzy equivalence, which provides the best reduction by means of fuzzy equivalences of this type, and we give an effective procedure for computing this fuzzy equivalence, which works if the underlying structure of truth values is a locally finite residuated lattice. Moreover, we show that even better reductions can be achieved alternating reductions by means of right and left invariant fuzzy equivalences. We also study strongly right and left invariant fuzzy equivalences, which give worse reductions than right and left invariant ones, but whose computing is much easier. We give an effective procedure for computing the greatest strongly right (resp. left) invariant fuzzy equivalence, which is applicable to fuzzy automata over an arbitrary complete residuated lattice.