Journal of Mathematical and Fundamental Sciences
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Antibacterial Activity of Gyrinops versteegii Fruit Extracts against Staphylococcus aureus and Escherichia coli and GC-MS Analysis
Full text linkGyrinops versteegii is widely used in the perfume, incense, and cosmetic industries as a raw material. Other potential uses of the plant are being explored, including in food and medicine. Therefore, this study carried out antibacterial assay and gas chromatography-mass spectroscopy of G. versteegii fruit extracts in three solvents with different polarities, i.e., n-hexane, dichloromethane, and methanol. The agar well diffusion method was then used to test the extracts against Staphylococcus aureus and Escherichia coli. The dichloromethane extract showed the most effective antibacterial activity against S. aureus at a concentration of 40%, with a zone of inhibition of 13.17 mm compared to E. coli, for which it was 7 mm. Furthermore, the bacterial species showed different responses to the extracts. Total and partial inhibition was shown by the G. versteegii fruit extracts against S. aureus and E. coli, respectively. Furthermore, GC-MS identified the following compounds in G. versteegii fruit extract: palmitic, oleic, and stearic acid, as well as bis-(2-ethylhexyl) phthalate, 2,3-dihydro-3,5-dihydroxy-6-methyl-4H-pyran-4-one, methyl octadec-9-enoate, squalene, and 2-monopalmitin derivates. The results showed antibacterial potency of G. versteegii fruit extract against pathogenic bacteria. Additionally, the antibacterial activity of the extract was stronger against S. aureus compared to E. coli
The Potency of Camellia Sinensis L. to Reduce Proinflammatory Cytokine Levels in the Acute Respiratory Distress Syndrome Rat Model
Full text linkThis study was conducted in order to ascertain how green tea extract (GTE) could affect inflammatory markers, including level of interleukin-(IL)-12, IL-18 of serum and lung, tumor necrosis factor (TNF)-α, gene expression of NLR family-pyrin-domain containing 3 (NLRP3) of lung, nuclear factor kappa B (NF-κB), lung histopathology, and IL-6 expression of lung tissue in lipopolysaccharide (LPS)-treated rats as ARDS animal model. Rats were given GTE at dosages of 0, 50, 400, 800 mg/kg of body weight for 28 days to boost their immune systems. The rats were then stimulated with LPS (5 g/kg of BW) and after that continued to receive GTE for 28 days. Levels of serum or lung IL-18, IL-12, TNF-α, were measured using the ELISA method; expression of lung NF-κB and NLRP3 was measured by qRT-PCR; immunohistochemistry (IHC) was implemented to assess lung IL-6 expression; and lung histopathology was evaluated through the bleeding, inflammation, and alveolus scores. GTE had the ability to lower serum IL-18, lung TNF-α, and lung IL-12 levels; suppress the lung gene expression of NF-κB, NLRP-3, IL-6 expression; and improve lung histopathology. Green tea extract inhibited inflammation in the ARDS rat model by decreasing the proinflammatory cytokine level and proinflammatory gene expression
Applying Fluorescence Dissolved Organic Matter Spectra and Phytoplankton Biology Index for Assessing Urban River Quality
Full text linkThe relationship between phytoplankton dynamics and dissolved organic matter (DOM) in aquatic systems based on fluorophore organic matter properties results in poor implementation of methods for water quality monitoring. This study aimed to investigate the relation between fluorophore organic matter and phytoplankton index and to estimate the phytoplankton index by fluorescent organic components for water quality assessment. The research was conducted by sampling urban river water, followed by measuring the biological phytoplankton index and dissolved organic matter during the wet and dry seasons. Fluorescence Excitation Emission Matrices (FEEMs) analysis combined with Parallel Factor (PARAFAC) analysis identified three main components of the fluorescence organic matter, i.e., a fulvic acid-like component (C1) and humic acid-like components (C2 and C3), in the aquatic system, whether in the dry season or the wet season. C1 was mainly generated by phytoplankton species, i.e., Nitzschia sp., Plectonema sp., Navicula sp., and Pinnularia sp., and C2 and C3 had a less significant relationship with phytoplankton species. The diversity of Bacillariophyta had a stronger contribution to the release of DOM than the diversity of Cyanobacteria. The abundance index of a particular phytoplankton species can be used to determine the organic components of FEEM-derived fluorescence organic matter
Havanensin-type Limonoids from the Stem Bark of Chisocheton pentandrus (Meliaceae)
Full text linkA new limonoid, belonging to the havanensin-type, called pentandricine E (1), alongside four other known types, i.e., trichilenone acetate (2), toonaciliatones C (3), 11α-acetoxyazadirone (4) and ceramicine I (5), were found in Chisocheton pentandrus stem bark. The structures of the isolated 1-5 were identified by NMR spectroscopy and HRTOFMS. Pentandricine E (1) displayed the highest cytotoxicity toward the MCF-7 breast cancer line with an IC50 value of 63.27 ± 0.21 mM
Synthesis, Structure, Magnetic and Antibacterial Properties of polymeric [M(Quin)2(N(CN)2)2]∞ (M = Mn(II), Co(II); Quin = quinoline)
Full text linkTwo complexes of [Mn(Quin)2(N(CN)2)2]∞ (1) and [Co(Quin)2(N(CN)2)2]∞ (2) were synthesized and characterized. The as-synthesized complexes crystallized in a triclinic lattice with a space group of P-1. The unit cell parameter of 1 was a = 7.5207(14) Å, b = 7.7729(16) Å, c = 9.5968(15) Å, α = 96.388(6) o, β = 112.617(5) o, γ = 102.751(6) o, while for complex 2 it was a = 7.3942(10) Å, b = 7.7960(10) Å, c = 9.4907(13) Å, α = 96.631(4) o, β = 112.742(4) o, γ = 102.458(4) o. The magnetic properties and antimicrobial properties of both polymeric complexes were examined by magnetic susceptibility and diffusion techniques, respectively. Complexes 1 and 2 both showed antiferromagnetic properties and had a higher inhibitory effect on the growth of Staphylococcus aureus than Salmonella typhi
Magnetic Characterization of Fine Sediment in the Solo Basin Indonesia
Full text linkThe magnetic characteristics of fine sediment samples from the Solo Basin are reported in this paper. Magnetic fine sediment was identified by magnetic susceptibility mapping based on sampling of 182 points. Then, a depth analysis (on 7 selected sampling points) was performed using X-ray fluorescence spectrometry, which showed an iron oxide content of up to 55.42%, while X-ray diffractometry confirmed magnetite minerals with crystallite size ≤100 nm. Further, the vibrating sample magnetometry results verified the magnetic characteristics under a single-domain configuration. The characteristic magnetic susceptibility map showed that there is a lithogenic effect on sediment in the Solo Basin. In addition, anthropogenic activities seem to play a pivotal role in distributing magnetic materials
Evaluation NO2 Detection Using Low-Cost Folded-Path Photometer
Full text linkThe measurement of nitrogen dioxide (NO2) in industrial and residential areas needs comprehensive and reliable instrumentation providing long-interference-free operation and minimum maintenance and recalibration. Differential optical absorption spectroscopy can be used as a direct measurement technique based on the specific absorption characteristics of NO2 following the Berr-Lambert law. This paper proposes a low-cost folded-path photometer to measure NO2 in the air. Cheap tubular acrylic was used as a detection cell with a 3D printed framework, making it compact, modular, and flexible. Evaluation of this differential optical absorption spectroscope (DOAS) was conducted by instrument test responses using NO2 gas. The estimated LOD was ~1263 ppb using a 2-nm resolution of the spectrometer and a 6-meter detection cell length. Deviation of the DOAS was estimated to be 0.8% at high concentration and 2.85% at low concentration based on the calibrated DOAS. Intercomparison of the results was conducted using two different instruments to evaluate the DOAS’s performance by measuring NO2 from motorcycle emissions, which indicated that there was a good correlation between the results. The coefficient correlation (R) was 0.649 for the DOAS- ASTM D1607 Griesz Saltzmann method pairing and 0.846 for the DOAS- electrochemical gas analyzer pairing
Magnetoresistance Features at the Magnetic Field-Induced Phase Transition in FeRh Thin Films
Full text linkThe causes of the appearance of first-order magnetic phase transitions remain a mystery. FeRh alloy is a classical material where a first-order magnetic phase transition occurs. The authors of this article studied the phase transition from the antiferromagnetic state to the ferromagnetic state in FeRh alloy. Comparison of the magnetometry and transport properties results allowed us to determine a number of differences in the mechanisms of the phase evolution during magnetic field and temperature induced transition. This article notes the priority of the rearrangement of the micromagnetic structure of the ferromagnetic phase as a result of the induction of a phase transition by a magnetic field. The main feature of the magnetic field induced phase transition compared to the temperature induced one is the change in the micromagnetic structure of the ferromagnetic phase. The growth of a ferromagnetic phase with less scattering fields leads to asymmetric behavior when a phase transition is induced near the metastable state. We also focused on the importance of taking into account the effect of magnetostriction when analyzing the evolution of the phase transition, which leads to the irreversibility of the phase transition near a zero magnetic field
Computational Study of Nocardiotide-A Analogues in the Development of Technetium-99m Radiopeptides for Cancer Imaging for Targeting Somatostatin Receptor 2
Full text linkNocardiotide-A (cWIWLVA) is a cyclic peptide with significant cytotoxicity against several cancer cells. The present research aimed to design a radiopeptide based on nocardiotide-A analogues to be labeled by technetium-99m targeting SSTR2, which is the most widely expressed receptor in several types of human cancers and used as radiopeptide target. Nocardiotide-A analogues were individually designed by replacing valine at the lead compound with lysine, arginine, histidine, asparagine, and glutamine, and this was simulated by molecular dynamics using AMBER18. A molecular docking using AutoDock 4.2 was performed and evaluated to understand the effect of chelation of technetium-99m on 99mTc-HYNIC-EDDA and 99mTc-HYNIC-tricine on the binding affinity of nocardiotide-A analogues. The molecular dynamics simulation confirmed that the designed nocardiotide-A-based peptides were stable in the binding pocket of SSTR2 for 200 ns. Moreover, the nocardiotide-A-based radiopeptides are able to interact with residues Q102, D122, Q126, and N276 by building hydrogen bonds, which are essential binding residues in SSTR2. The molecular docking simulation revealed that the best docking parameter is exhibited by 99mTc/EDDA/HYNIC-cWIWLNA and 99mTc/tricine/HYNIC-cWIWLNA with a binding free energy of –12.59 kcal/mol and –8.96 kcal/mol, respectively. Taken together, nocardiotide-A-based radiopeptides are prospective to be further developed for cancer imaging targeting SSTR2
Study of the Effect of Physical Parameters on Commercial Hydroponics Based on Internet of Things (IoT): A Case Study of Bok Coy Plants (Brassica rapa) and Water Spinach (Ipomoea Aquatica)
Full text linkPopulation growth causes the demand for food to increase. One solution that can be applied is agriculture with hydroponic technology. To increase production efficiency, one must know the physical parameters that most influence the production process. This research used an IoT system to gather accurate and precise measurement data of physical parameters to be used as a dataset for machine learning. The dataset consisted of light intensity, humidity, air temperature, and total dissolved solids (TDS). Plant growth was measured by leaf area of the plant, number of leaves, and plant stem length every 3 to 4 days. The models used in the machine learning process were linear regression, polynomial regression, and random forest regression. The machine learning results showed that the best model for predicting plant growth was random forest regression with an MAE of 8.3% and an R2 of 0.93, for both bok coy and water spinach. The variables that influence growth the most are TDS and light intensity. According to the relationship between TDS gradient and plant growth gradient, the most optimal growth can be achieved by raising the TDS gradient or by maintaining a high TDS, which can be achieved by adding nutrient solution to the tank regularly