Fourier Transform Infrared Data Research Articles

Preparation, Characterization, In silico and In vitro Antimicrobial Studies of Phenothiazine-3-sulphonamide Derivatives

The antibacterial activities of phenothiazine and sulphonamide derivatives have attracted so much interest. In this study, the synthesis and characterization of phenothiazine-3-sulphonamide derivatives and evaluation of their antimicrobial activity against the following pathogenic microorganisms is reported. Two Gram-positive bacteria; (Staphylococcus aureus (ATCC: 6538) and Streptococcus pyogenes (ATCC: 27853)), two Gram-negative bacteria; (Escherichia coli(ATCC: 3008), and Salmonella typhi (ATCC: 25175)) as well as one fungus (Aspergillus fumigatus (ATCC: 10231)) were used while ciprofloxacin, gentamycin and ketoconazole served as standard drugs. The synthesis of the derivatives was achieved through a base catalyzed the reaction of 4-chloroaniline with 1-naphthylamine to form 1-(naphthalen-1-yl)benzene-1,4-diamine. This intermediate was then treated with sulphur and iodine to yield the phenothiazine derivative while subsequent treatment of the phenothiazine compound with sulphonyl chlorides gave the final products. The synthesized compounds were characterized via proton nuclear magnetic resonance (1H-NMR), carbon-13 nuclear magnetic resonance (13C-NMR) and Fourier-transform infrared (FTIR) spectroscopic techniques. The minimum inhibitory concentration (MIC) of each compound was then determined using the agar well diffusion method. To predict the binding energies and patterns of the synthesized compounds with target proteins of the above-mentioned microorganisms, molecular docking simulations were run using Autodock Vina software (version 4.2). The spectra data of the compounds for FTIR, 1H-NMR and 13C-NMR spectral data were consistent with the assigned structures of the synthesized compounds. The binding energies (kcal/mol) for in silico antimicrobial studies were in the range -5.1 to -7.6 kcal/mol. The MIC values were in the range 3.5 to 1.0 mg/L. The results of the in vitro test revealed that the synthesized compounds exhibit promising antimicrobial activity and showed excellent bactericidal and fungicidal activities. The results obtained showed that the synthesized compounds possess drug-like properties and are good starting materials for drug production.

Synthesis, Characterization and Evaluation of the Antimicrobial and Herbicidal Activities of Some Transition Metal Ions Complexes with the Tranexamic Acid.

New tranexamic acid (TXA) complexes of ferric(III), cobalt(II), nickel(II), copper(II) and zirconium(IV) were synthesized and characterized by elemental analysis (CHN), conductimetric (Λ), magnetic susceptibility investigations (μeff), Fourier transform infrared (FT-IR), proton nuclear magnetic resonance (1H-NMR), ultraviolet visible (UV-vis.), optical band gap energy (Eg) and thermal studies (TG/DTG and DTA). TXA complexes were established in 1 : 2 (metal: ligand) stoichiometric ratio according to CHN data. Based on FT-IR and 1H-NMR data the disappeared of the carboxylic proton supported the deprotonating of TXA and linked to metal ions via the carboxylate group's oxygen atom as a bidentate ligand. UV-visible spectra and magnetic moment demonstrated that all chelates have geometric octahedral structures. Eg values indicated that our complexes are more electro conductive. DTA revealed presence of water molecules in inner and outer spheres of the complexes. DTA results showed that endothermic and exothermic peaks were identified in the degradation mechanisms. The ligand and metal complexes were investigated for their antimicrobial and herbicidal efficacy. The Co(II) and Ni(II) complexes showed antimicrobial activity against some tested species. The obtained results showed a promising herbicidal effect of TXA ligand and its metal complexes particularly copper and zirconium against the three tested plants.

Caffeic acid phenethyl ester (CAPE) Chitosan capped ZnO nanoparticles: Preparation, characterization, and its potential for the treatment of prostate cancer

The synthesis of zinc oxide nanoparticles/chitosan (ZnONPs/CS) formulation loaded with Caffeic acid phenethyl ester (CAPE) was performed to evaluate its prostate cancer treatment efficiency within the scope of this research. It has been hypothesized that a dual active materials delivery system containing ZnO and CAPE loaded Chitosan (CS) nanoparticles has better bioavailability compared to single one against to cancer cells. ZnONPs were synthesized between 45 and 60 nm particle sizes and then they were capped with CS biodegradable polymer prior to load with CAPE bioactive molecule. ZnONPs/CS-CAPE system was characterized by using Fourier Transform Infrared (FTIR) for structural elucidation, Scanning Electron Microscope (SEM) for particle size determination, High Performance Liquid Chromatography (HPLC) system for determination of CAPE amount. 131I CAPE and 131I ZnONPs/CS-CAPE labeled by the Iodogen method with 131I were used in-vitro cell culture experiments. Cell viabilities (%) of CAPE and ZnONPs/CS-CAPE were examined using Cell Counting Kit-8 assay on PC-3 (human adenocarcinoma prostate), LnCaP (human carcinoma prostate), and RWPE-1 (human normal prostate). IC50 values of ZnONPs /CS -CAPE on all cells were found 2-fold lower than neat CAPE. Based on the FTIR data, the most significant spectral changes (lipid, protein, nucleic acids, glycogen) were monitored for the PC-3 and LnCaP cancer cells incubated with ZnONPs/CS-CAPE samples while being exposed to neat CAPE molecules caused small cellular changes when compared to RWPE-1 healthy cell lines.

Unraveling UVB effects: Catalase activity and molecular alterations in the stratum corneum

AimUltraviolet B (UVB) radiation can compromise the functionality of the skin barrier through various mechanisms. We hypothesize that UVB induce photochemical alterations in the components of the outermost layer of the skin, known as the stratum corneum (SC), and modulate its antioxidative defense mechanisms. Catalase is a well-known antioxidative enzyme found in the SC where it acts to scavenge reactive oxygen species. However, a detailed characterization of acute UVB exposure on the activity of native catalase in the SC is lacking. Moreover, the effects of UVB irradiation on the molecular dynamics and organization of the SC keratin and lipid components remain unclear. Thus, the aim of this work is to characterize consequences of UVB exposure on the structural and antioxidative properties of catalase, as well as on the molecular and global properties of the SC matrix surrounding the enzyme. ExperimentsThe effect of UVB irradiation on the catalase function is investigated by chronoamperometry with a skin covered oxygen electrode, which probes the activity of native catalase in the SC matrix. Circular dichroism is used to explore changes of the catalase secondary structure, and gel electrophoresis is used to detect fragmentation of the enzyme following the UVB exposure. UVB induced alterations of the SC molecular dynamics and structural features of the SC barrier, as well as its water sorption behavior, are investigated by a complementary set of techniques, including natural abundance 13C polarization transfer solid-state NMR, wide-angle X-ray diffraction, Fourier transform infrared (FTIR) spectroscopy, and dynamic vapor sorption microbalance. FindingsThe findings show that UVB exposure impairs the antioxidative function of catalase by deactivating both native catalase in the SC matrix and lyophilized catalase. However, UVB radiation does not alter the secondary structure of the catalase nor induce any observable enzyme fragmentation, which otherwise could explain deactivation of its function. NMR measurements on SC samples show a subtle increase in the molecular mobility of the terminal segments of the SC lipids, accompanied by a decrease in the mobility of lipid chain trans-gauche conformers after high doses of UVB exposure. At the same time, the NMR data suggest increased rigidity of the polypeptide backbone of the keratin filaments, while the molecular mobility of amino acid residues in random coil domains of keratin remain unaffected by UVB irradiation. The FTIR data show a consistent decrease in absorbance associated with lipid bond vibrations, relative to the main protein bands. Collectively, the NMR and FTIR data suggest a small modification in the composition of fluid and solid phases of the SC lipid and protein components after UVB exposure, unrelated to the hydration capacity of the SC tissue. To conclude, UVB deactivation of catalase is anticipated to elevate oxidative stress of the SC, which, when coupled with subtle changes in the molecular characteristics of the SC, may compromise the overall skin health and elevate the likelihood of developing skin disorders.

Solar FTIR measurements of NOx vertical distributions – Part 1: First observational evidence of a seasonal variation in the diurnal increasing rates of stratospheric NO2 and NO

Abstract. Observations of nitrogen dioxide (NO2) and nitrogen oxide (NO) in the stratosphere are relevant to understand long-term changes and variabilities in stratospheric nitrogen oxide (NOx) and ozone (O3) concentrations. Due to the versatile role of NO2 and NO in stratospheric O3 photochemistry, they are important for recovery and build-up of O3 holes in the stratosphere and therefore can indirectly affect human life. Thus, we present in this work the evaluation of NO2 and NO stratospheric partial columns (> 16 km altitude) retrieved from ground-based Fourier-transform infrared (FTIR) measurements of over 25 years at Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.) and 18 years at Garmisch (47.47° N, 11.06° E; 745 m a.s.l.), Germany. The obtained stratospheric columns are only weakly influenced by tropospheric pollution and show only a very small bias of 2.5 ± 0.2 % when comparing NO2 above Zugspitze and Garmisch. Stratospheric columns of both NO2 and NO show a diurnal increase that depends on local solar time (LST). We quantified this behavior by calculating diurnal increasing rates. Here, we find mean values for the NO2 diurnal increasing rate of (0.89 ± 0.14) × 1014 and (0.94 ± 0.14) × 1014 cm−2 h−1 at Zugspitze and Garmisch, respectively. The mean NO morning diurnal increasing rate above Zugspitze is found to be (1.42 ± 0.12) × 1014 cm−2 h−1. Regarding the seasonal dependency of these increasing rates, for the first time, we were able to experimentally detect a significant seasonal variation in both NO2 diurnal increasing rates and NO morning diurnal increasing rates with a maximum of (1.13 ± 0.04) × 1014 cm−1 h−1 for NO2 and (1.76 ± 0.25) × 1014 cm−1 h−1 for NO in September and a minimum of (0.71 ± 0.18) × 1014 cm−1 h−1 in December for NO2 and a minimum of (1.18 ± 0.41) × 1014 cm−1 h−1 in November for NO. This similar behavior may be explained by the interconnection of both species in stratospheric photochemistry. The outcome of this work is a retrieval and analysis strategy of FTIR data for NOx stratospheric columns, which can help to further validate photochemical models or improve satellite validations. The first use of this data set is shown in the companion paper (Nürnberg et al., 2023) wherein experiment-based NOx scaling factors describing the diurnal increase in the retrieved partial columns are extracted and recently published model-based scaling factors are validated.

Crystallographic insights into monovalent thallium incorporation: Exploring hydropyrochlore structure for environmental remediation

Abstract Hydropyrochlore, ideally (H2O,)2Nb2(O,OH)6(H2O), is a cubic mineral (space group Fd3m, a = 10.56-10.59 Å, Z = 8) belonging to the pyrochlore supergroup (general formula: A2−mB2X6−wY1−n). The K-rich variety of this species is unique to the Lueshe syenitic-carbonatitic deposit (D.R. Congo), where it occurs as the alteration product of primary (Ca,Na)2Nb2O6F pyrochlores. The structure of this mineral is made of a B2X6 (B = Nb, Ti; X = O, OH) framework that generates tunnels along the [110] direction, where the interstitial sites are partially occupied by water molecules and minor amounts of different cations. These features form the basis for the ion-exchange properties of hydropyrochlore, making it a promising candidate as a mineral sink for heavy metals (e.g., Tl+) dispersed in aqueous matrices, with interesting environmental implications. Tl+ incorporation was induced through imbibition experiments in a diluted Clerici solution using single crystals of hydropyrochlore from Lueshe (D.R. Congo); the modifications induced by Tl+ incorporation were then evaluated through single-crystal X-ray diffraction (SCXRD), electron microprobe analyses (EMPA) and Fourier transform infrared (FT-IR) spectroscopy. After Tl+ imbibition, a dramatic increase of the A-site electron density (n.e− from ~4 to ~60) confirms the entry of a substantial amount of Tl+ at this site (up to about 70%), leading to a lengthening of the A-X distances and the consequent expansion of the unit cell. A decrease of the site scattering at the Y' site (from ~9 to ~4 e−) also occurs, suggesting a loss of aqueous species. Although the predominance of neutral H2O molecules at the interstitial sites of hydropyrochlore from Lueshe is widely accepted by the mineralogical community, our crystal-chemical and FT-IR data provide evidence that the dominant species might be the hydronium ion, with significant implications on the nomenclature of the pyrochlore supergroup. Understanding the crystallographic aspects of hydropyrochlore as a potential waste form for monovalent thallium immobilization not only addresses a pressing environmental concern, but also contributes to the broader field of waste management.

Spectroscopic and thermal investigations on Zn2+ and Ba2+ ions modified 30TeO2-39.5B2O3-(30-x)ZnO-xBaO-0.5V2O5 (0 ≤ x ≤ 30 mol %) glass system

Melt quenching technique was employed to prepare glasses with compositional formula 30TeO2-39.5B2O3-(30-x)ZnO-xBaO-0.5V2O5 (0 ≤ x ≤ 30 mol%). Various characterization tools viz., X-ray diffraction (XRD), Energy dispersive X-ray (EDX) includes color mapping images, X-ray photoelectron spectroscopy (XPS), Fourier transform infrared (FTIR), Raman, Differential scanning calorimetry (DSC), UV–Vis absorption and Electron paramagnetic resonance (EPR) were used in this investigation for the characterization of these glasses. The XRD patterns together with DSC thermograms asserted the amorphous nature of all glasses. FTIR and Raman vibrational analyses has unveiled the formation of B-O--Ba2+-O− and Te-O−--Ba2+-O− wherein the bonds with Ba2+ ions are mostly ionic. DSC investigations disclosed that the increase of BaO at the cost of ZnO declined the crystal phases and favored the amorphosity and this behavior causes these glasses more advantageous for fiber drawing. The Urbach energy (ΔE) lies in between 0.28 and 0.57 eV and suggested the glasses containing high ZnO has less defects. EPR data validated that Ba2+ ions might surround V4+ ions as Ba2+-O-V4+=O by replacing Zn2+-O-V4+=O linkages. The other optical properties were discussed in detail by correlating the structural variations noticed from both FTIR and Raman data analyses.

Preparation, characterization and cooling performance of ZnO based Nanofluids

Nanoparticles (NPs) of Zinc Oxide (ZnO) were synthesized by the sol–gel method. These NPs were characterized for structural vibrational, morphological, optical, and electrical properties by X-ray diffraction (XRD), Fourier Transform infrared (FT-IR) spectroscopy, Scanning Electron Microscopy (SEM), UV–Visible optical absorption spectroscopy, and dielectric spectroscopy. Structural analysis confirms that all the NPs have a single-phase rutile tetragonal structure. Also from the Scherer formula, the average particle size for this compound was found to be around 10.25 nm. From SEM images, the observed NPs are spherical in shape, with an average size ranging from 10 to 100 nm. FT-IR data indicates a Zn–O vibrational bond and confirms the ZnO structure. Further, according to the optical data analysis, these NPs show an optical band gap of around 3.27 eV and follow an indirect transition. The dielectric constant (εr) and loss constant (ε) show good dispersion with the applied frequency. Also using these NPs, a nanofluid in transformer oil (mineral oil) was prepared. Further εr & εi shows good variation with the contents of NPs in the mineral oil. This nanofluid was tested for the cooling of transformers and shows some encouraging results. Based on these results, this material seems like a good candidate for transformer insulation and cooling applications.

Classification of asbestos and their nonasbestiform analogues using FTIR and multivariate data analysis

This study presents a possible application of Fourier transform infrared (FTIR) spectrometry and multivariate data analysis, principal component analysis (PCA), and partial least squares-discriminant analysis (PLS-DA) for classifying asbestos and their nonasbestiform analogues. The objectives of the study are: 1) to classify six regulated asbestos types and 2) to classify between asbestos types and their nonasbestiform analogues. The respirable fraction of six regulated asbestos types and their nonasbestiform analogues were prepared in potassium bromide pellets and collected on polyvinyl chloride membrane filters for FTIR measurement. Both PCA and PLS-DA classified asbestos types and their nonasbestiform analogues on the score plots showed a very distinct clustering of samples between the serpentine (chrysotile) and amphibole groups. The PLS-DA model provided ∼95% correct prediction with a single asbestos type in the sample, although it did not provide all correct predictions for all the challenge samples due to their inherent complexity and the limited sample number. Further studies are necessary for a better prediction level in real samples and standardization of sampling and analysis procedures.

Surface defects due to bacterial residue on shrimp shell

The changes in the surface chemistry and morphological structure of chitin forms obtained from shrimp shells (ShpS) with and without microorganisms were evaluated. Total mesophilic aerobic bacteria (TMAB), estimated Pseudomonas spp. and Enterococcus spp. were counted in Shp-S by classical cultural counting on agar medium, where the counts were 6.56 ± 0.09, 6.30 ± 0.12, and 3.15 ± 0.03 CFU/g, respectively. Fourier Transform Infrared (FTIR) Spectroscopy and Scanning Electron Microscopy (SEM)/Energy dispersed X-ray (EDX) were used to assess the surface chemistry/functional groups and morphological structure for ChTfree (non-microorganism), and ChTmo (with microorganisms). ChTfree FTIR spectra presented a detailed chitin structure by OH, NH, and CO stretching vibrations, whereas specific peaks of chitin could not be detected in ChTmo. Major differences were also found in SEM analysis for ChTfree and ChTmo. ChTfree had a flat, prominent micropore, partially homogeneous structure, while ChTmo had a layered, heterogeneous, complex dense fibrous, and lost pores form. The degree of deacetylation was calculated for ChTfree and ChTmo according to FTIR and EDX data. The results suggest that the degree of deacetylation decreases in the presence of microorganisms, affecting the production of beneficial components negatively. The findings were also supported by the molecular docking model.

Bias correction of OMI HCHO columns based on FTIR and aircraft measurements and impact on top-down emission estimates

Abstract. Spaceborne formaldehyde (HCHO) measurements constitute an excellent proxy for the sources of non-methane volatile organic compounds (NMVOCs). Past studies suggested substantial overestimations of NMVOC emissions in state-of-the-art inventories over major source regions. Here, the QA4ECV (Quality Assurance for Essential Climate Variables) retrieval of HCHO columns from OMI (Ozone Monitoring Instrument) is evaluated against (1) FTIR (Fourier-transform infrared) column observations at 26 stations worldwide and (2) aircraft in situ HCHO concentration measurements from campaigns conducted over the USA during 2012–2013. Both validation exercises show that OMI underestimates high columns and overestimates low columns. The linear regression of OMI and aircraft-based columns gives ΩOMI=0.651Ωairc+2.95×1015 molec.cm-2, with ΩOMI and Ωairc the OMI and aircraft-derived vertical columns, whereas the regression of OMI and FTIR data gives ΩOMI=0.659ΩFTIR+2.02×1015 molec.cm-2. Inverse modelling of NMVOC emissions with a global model based on OMI columns corrected for biases based on those relationships leads to much-improved agreement against FTIR data and HCHO concentrations from 11 aircraft campaigns. The optimized global isoprene emissions (∼445Tgyr-1) are 25 % higher than those obtained without bias correction. The optimized isoprene emissions bear both striking similarities and differences with recently published emissions based on spaceborne isoprene columns from the CrIS (Cross-track Infrared Sounder) sensor. Although the interannual variability of OMI HCHO columns is well understood over regions where biogenic emissions are dominant, and the HCHO trends over China and India clearly reflect anthropogenic emission changes, the observed HCHO decline over the southeastern USA remains imperfectly elucidated.

Temporal variability of atmospheric columnar CO2, CH4, CO and N2O concentrations using ground-based remote sensing FTIR Spectrometer

Solar absorption spectra collected using a ground-based Fourier Transform Infrared (FTIR) Spectrometer were used to retrieve the column-averaged concentrations (X) of CO2, CH4, CO, and N2O during the years 2016–2019 in the Suburban region of Shadnagar, Telangana, India. For the research period, the diurnal mean amplitudes of XCO2, XCH4, XCO, and XN2O are ∼ 13 ppmv, ∼50 ppbv, ∼13 ppbv, and ∼ 19 ppbv respectively. Strong seasonality at the study site is indicated by the seasonal variations of XCO2 and XCO of 18.3 ppmv and 39.2 ppbv, respectively. Additionally, we compared FTIR data to XCO2 detected by Orbiting Carbon Observatory-2 (OCO-2) and CO columns from Measurements of Pollution in the Troposphere (MOPITT). For the XCO2 and CO columns, the comparison research shows a mean relative bias between FTIR data and satellite data of 0.92 % and 0.71 %, respectively. The FTIR and satellite data show a Pearson correlation coefficient (r) of 0.71 (XCO2, N = 26 co-located) and 0.60 (CO columns, N = 44), respectively. The findings demonstrate a good agreement between our data and satellite data.

Sintesis dan Karakterisasi Nanosilika dari Limbah Silica Scaling PLTP Dieng Melalui Metode Alkali Fusion NaOH

Silica scaling is the main problem that arises in the operation of geothermal power plants (PLTP) in Dieng. Silica scaling can disrupt electricity production and cause a buildup of waste in the environment. Silica scaling has a high silica (SiO2) content so it has the potential to be used as a value-added material, namely nanosilica. One method to obtain nanosilica is alkali fusion. This research aims to obtain nanosilica from silica scaling waste from PLTP Dieng using the alkali fusion method as well as knowing the characteristics of the nanosilica produced. The alkali fusion process is carried out using NaOH as an alkali source. Then mixing silica scaling powder and NaOH at varying temperatures of 600°C, 650°C and 700°C to produce nanosilica. The resulting nanosilica was then characterized to confirm the success of the synthesis process in producing nanosilica particles. The characterization carried out included x-ray diffraction (XRD) to characterize crystallinity, Fourier transform infrared (FTIR) to characterize functional groups, transmission electron microscope (TEM) and particle size analyzer (PSA) to determine particle size. The results of this research showed that amorphous nanosilica was successfully synthesized from silica scaling using the NaOH alkali fusion method. It was found from the results of TEM and PSA characterization that the smallest particle size was produced at a fusion temperature of 650°C. Furthermore, FTIR data also confirms the existence of functional groups at wave numbers identical to silica.

Cancer Cell Targeting Via Selective Transferrin Receptor Labeling Using Protein-Derived Carbon Dots.

Carbon dot (CD) nanoparticles offer tremendous advantages as fluorescent probes in bioimaging and biosensing; however, they lack specific affinity for biomolecules, limiting their practical applications in selective targeting. Nanoparticles with intrinsic affinity for a target have applications in imaging, cytometry, therapeutics, etc. Toward that end, we report the transferrin receptor (CD71) targeting CDs, synthesized for the first time. The formation of these particles is truly groundbreaking, as direct tuning of nanoparticle affinity was achieved by simple and careful precursor selection of a protein, which has the targeting characteristic of interest. We hypothesized that the retention of the original protein's peptides on the nanoparticle surface provides the CDs with some of the function of the precursor protein, enabling selective binding to the protein's receptor. This was confirmed with FTIR (Fourier transform infrared) data and subsequent affinity-based cell assays. These transferrin (Tf)-derived CDs have been shown to possess an affinity for CD71, a cancer biomarker that is ubiquitously expressed in nearly every cancer cell line due to its central role mediating the uptake of cellular iron. The CDs were tested using the human leukemia cell line HL60 and demonstrated the selective targeting of CD71 and specific triggering of transferrin-mediated endocytosis via clathrin-coated pits. The particle characterization results reflect a carbon-based nanoparticle with bright violet fluorescence and 7.9% quantum yield in aqueous solution. These unpresented CDs proved to retain the functional properties of the precursor protein. Indicating that this process can be repeated for other disease biomarkers for applications ranging from biosensing and diagnostic bioimaging to targeted therapeutics.

Clustering honey samples with unsupervised machine learning methods using FTIR data.

This study utilizes Fourier transform infrared (FTIR) data from honey samples to cluster and categorize them based on their spectral characteristics. The aim is to group similar samples together, revealing patterns and aiding in classification. The process begins by determining the number of clusters using the elbow method, resulting in five distinct clusters. Principal Component Analysis (PCA) is then applied to reduce the dataset's dimensionality by capturing its significant variances. Hierarchical Cluster Analysis (HCA) further refines the sample clusters. 20% of the data, representing identified clusters, is randomly selected for testing, while the remainder serves as training data for a deep learning algorithm employing a multilayer perceptron (MLP). Following training, the test data are evaluated, revealing an impressive 96.15% accuracy. Accuracy measures the machine learning model's ability to predict class labels for new data accurately. This approach offers reliable honey sample clustering without necessitating extensive preprocessing. Moreover, its swiftness and cost-effectiveness enhance its practicality. Ultimately, by leveraging FTIR spectral data, this method successfully identifies similarities among honey samples, enabling efficient categorization and demonstrating promise in the field of spectral analysis in food science.

Interaction of Melatonin with Zwitterionic Model Lipid Membranes

Melatonin is a key hormone secreted by the pineal gland in the brain. It interacts strongly with cell membranes and plays a protective role in several diseases such as Alzheimer's disease, cardiovascular diseases, and cancer. Hence, studies on the interaction of melatonin with lipid bilayer membranes have gained importance. In this regard, the present study aims to analyze the influence of different concentrations (0 to 15 mol%) of melatonin on the thermal and structural properties of zwitterionic stearoyl-2-oleoyl-sn-glycero-3-phosphocholine (SOPC) lipid bilayer model systems by using Fourier transform infrared (FTIR) spectroscopy and differential scanning calorimetry (DSC). The DSC results have shown that melatonin interacts with the membrane in a concentration-dependent fashion, induces patch formation, and alters the phase behaviour by reducing the main phase transition temperature. FTIR data has shown that increasing the melatonin concentration caused a reduction in the wavenumber of C=O and PO$$_{2}^-$$ antisymmetric stretching vibrations corresponding to the ester carbonyl and phosphate groups of SOPC lipids. This indicates the possibility of strong hydrogen bonding of melatonin with the SOPC lipids and nearby water molecules in the environment, suggesting its preferential location near lipid heads at the interfacial region. These results help to understand the organization and interactions of melatonin with membranes and provide insights to develop safe melatonin-based formulations for pharmaceutical applications.

Tunable capacitive charge storage of NiCoLDH@rGO for high-energy capacitor: Performance of flexible solid-state capacitor

The compositionally tunned pristine nickel cobalt layered double hydroxides (NiCoLDHs) and NiCoLDH@reduced graphene-oxide (NiCoLDH@rGO) composites generated via the simple single-pot solvothermal method. The synthesized NiCoLDH and the NiCoLDH@rGO composites were characterized through powder X-ray diffraction (XRD), Raman spectroscopy, Fourier transformed infra-red (FT-IR) spectroscopy, scanning electron microscope (SEM) equipped with energy dispersive X-ray analysis (EDAX), high-resolution transmission electron microscope (HR-TEM), and X-ray photoelectron spectroscopy (XPS) techniques. The XRD, Raman and FT-IR data confirmed the formation of the NiCoLDH with presence of carbonate and nitrate ions in the basal space. Enhanced basal length was observed for the NiCoLDH@rGO composites. The three-electrode system was constructed to analyse the cyclic voltammetry and Galvanostatic charge-discharge studies in 1 M KOH confirmed that the pristine LDHs and the composites are electrochemically active, and the capacity could be tuned by varying (Ni2+/Co3+) mole ratio or the rGO content. The charge storage kinetics in NiCoLDH@rGO was performed through Dunn's approaches and the Power Law, affirmed as the (Ni2+/Co3+) ratio or the rGO content is increased in the composite the capacitive contribution is increased for the charge storage. The NC@RG10 (NiCoLDH with 10 wt% rGO) composite electrode could deliver an enhanced specific capacity of 963C g−1 at a current rate of 1.5 A g−1. Consequently, pristine LDH or composites as positive electrode and rGO as negative electrode was fabricated using the CR-2032 coin-type hybrid capacitor. The laboratory prototype pristine hybrid capacitor (NiCoLDH|1 M KOH|rGO) delivered an enhanced specific energy of 56 Wh kg−1 at specific power of 810 W kg−1, whereas the composite hybrid device (NC@RG10|1 M KOH|rGO) having NC@RG10 electrode delivered an enhanced specific energy of 166 Wh kg−1 at specific power of 638 W kg−1. The NC@RG10 composite-based hybrid device exhibited excellent stability with coulombic efficiency as high as 99 % even at the 10,000th charge−discharge cycle. Reduced aggregation and enhanced conductivity leading to significant capacitive contribution in the NC@RG10 composite is due to the existence of rGO and responsible for the excellent charge storage performance. The fabricated hybrid capacitor powered a red LED on a single charge for 40 min. Fascinatingly, a flexible solid-state hybrid capacitor was also fabricated that delivered an impressive specific energy of 28 Wh kg−1 at a specific power of 553 W kg−1 at a 180° bent angle.

A Simple Synthesis and Microstructure Analysis of Human Peptide LL-37@Gold Nanoparticles (Known as LL-37@AuNPs) Conjugates as Antimicrobials and Substances for Wound Healing.

The basis of the present study is a straightforward method involving fewer chemical species for conjugating gold nanoparticles (AuNPs) with the antimicrobial peptide LL-37 designated as LL-37@AuNPs. Investigating the microstructure characteristics of the resulting materials and their potential as antibacterial and wound-healing substances are the main objectives of this study. Zeta (ζ) potential, Fourier transform infrared (FTIR), X-ray diffraction (XRD), field effect scanning electron microscopy (FE-SEM), energy dispersive X-ray diffraction (EDS), transmission electron microscopy (TEM), and UV-Vis spectrophotometry were used to analyze the physico-chemical properties of LL-37@AuNPs. The magnitude of LL-37's zeta potential and the LL-37@AuNPs show that the specimens are electrically stable and resistant to flocculation and coagulation. The surface plasmon resonance (RPS) of AuNPs, which is positioned at a wavelength of about 531 nm, was found to be unaffected by the presence of the LL-37 antimicrobial peptide. The FTIR data show the functional group characteristics of the LL-37@AuNPs vibration bands, and the XRD diffractogram confirms the formation of the LL-37@AuNPs conjugate nanocomposite. Based on FE-SEM and TEM data, the bulk of AuNPs were found to have a circular shape, with an average size of about 22.88 ± 8.21 nm. It was discovered that the LL-37@AuNPs had a good ability to inhibit S. aureus from growing. The wound-healing percentage reached 85% on day 12 of the trial, significantly greater than the results of the negative controls. LL-37@AuNPs(4) is the sample that had the highest percentage of wound healing between days 3 and 12. Moreover, sample LL-37@AuNPs(4) contains 0.45 µL of LL-37, whereas sample LL-37@AuNPs(2) contains 0.22 µL of LL-37. The faster wound-healing rate in LL-37@AuNPs(4) was believed to be due to a higher concentration of LL-37, which was able to stop S. aureus from developing while suppressing the inflammation surrounding the wound. The study's findings reveal that LL-37@AuNPs might be made using a straightforward process, making them a powerful antibacterial and therapeutic substance. However, before this discovery is applied in the field of medicine, a more thorough investigation is necessary.

Dielectric, conductivity properties, elastic moduli, and gamma-ray attenuation abilities: A wide-ranging investigation into Molybdenum added ferrite nanoparticles

The auto combustion technique was employed to synthesis magnesium nano ferrite (MgMoxFe2-xO4). The impact of Mo-doped on the crystal’s structural, morphological, and elastic properties were inspected by applying x-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and Fourier transform infrared (FTIR) spectroscopy techniques. Pursuant to the XRD analysis, all samples have a cubic structure with single-phase. The average crystallite size was identified to be in the nanometer range confirmed by SEM and TEM investigations. FTIR data was implemented to assign the force constants of the octahedral and tetrahedral sites. Elastic moduli including the Poisson ratio, Young’s modulus, bulk modulus, and rigidity modulus have been estimated. The division of elastic moduli for all synthesized concentrations was interpreted using binding forces between ions of the cubic lattice spinel. Over and above, the AC conductivity (σ AC) and dielectric properties and their frequency dependence were investigated for the nano ferrites samples as a function of dopant Mo content and temperature. Finally, the radiation shielding capacities of the proposed samples against gamma and fast neutron radiation have been assessed. The findings reveal that the higher the Mo content, the lower the value of the mass attenuation coefficient. There is no significant diversity between the obtained mass attenuation coefficients for the nano and the micro. Among the samples investigated in this study, the highest Mo concentration sample had the largest fast neutron removal cross-section.

Increased interpretation of deep learning models using hierarchical cluster-based modelling

Linear prediction models based on data with large inhomogeneity or abrupt non-linearities often perform poorly because relationships between groups in the data dominate the model. Given that the data is locally linear, this can be overcome by splitting the data into smaller clusters and creating a local model within each cluster. In this study, the previously published Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) procedure was extended to deep learning, in order to increase the interpretability of the deep learning models through local modelling. Hierarchical Cluster-based Convolutional Neural Networks (HC-CNNs), Hierarchical Cluster-based Recurrent Neural Networks (HC-RNNs) and Hierarchical Cluster-based Support Vector Regression models (HC-SVRs) were implemented and tested on spectroscopic data consisting of Fourier Transform Infrared (FT-IR) measurements of raw material dry films, for prediction of average molecular weight during hydrolysis and a simulated data set constructed to contain three clusters of observations with different non-linear relationships between the independent variables and the response. HC-CNN, HC-RNN and HC-SVR outperformed HC-PLSR for the simulated data set, showing the disadvantage of PLSR for highly non-linear data, but for the FT-IR data set there was little to gain in prediction ability from using more complex models than HC-PLSR. Local modelling can ease the interpretation of deep learning models through highlighting differences in feature importance between different regions of the input or output space. Our results showed clear differences between the feature importance for the various local models, which demonstrate the advantages of a local modelling approach with regards to interpretation of deep learning models.