Determination of carboxyl content in high-yield kraft pulps using photoacoustic rapid-scan Fourier transform infrared spectroscopy

Pinus radiata kraft pulps with varying carboxyl content were studied using Fourier transform infrared photoacoustic spectroscopy (FT-IR-PAS). The examined pulp samples, with Kappa number ranging from 20.8 to 128, originated from pulping experiments conducted in flow-through reactors utilizing varying effective alkali, temperature, and cooking time. A partial least-squares (PLS) analysis was used to formulate a model that correlates the spectral data with the carboxyl content of pulp. Using three principal components, the resultant PLS model could explain approximately 98.5% of the variance in the X-matrix (spectral features) and 96.8% of the variance in the Y-matrix (measured carboxyl content). The FT-IR-PAS technique in combination with PLS analysis predicts the carboxyl content of the pulps with a high degree of accuracy. This method is much faster than the conventional titration methods and also not destructive to the pulp sample.     

Next-Generation Diagnostic with CRISPR/Cas: Beyond Nucleic Acid Detection

The early management, diagnosis, and treatment of emerging and re-emerging infections and the rising burden of non-communicable diseases (NCDs) are necessary. The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas system has recently acquired popularity as a diagnostic tool due to its ability to target specific genes. It uses Cas enzymes and a guide RNA (gRNA) to cleave target DNA or RNA. The discovery of collateral cleavage in CRISPR-Cas effectors such as Cas12a and Cas13a was intensively repurposed for the development of instrument-free, sensitive, precise and rapid point-of-care diagnostics. CRISPR/Cas demonstrated proficiency in detecting non-nucleic acid targets including protein, analyte, and hormones other than nucleic acid. CRISPR/Cas effectors can provide multiple detections simultaneously. The present review highlights the technical challenges of integrating CRISPR/Cas technology into the onsite assessment of clinical and other specimens, along with current improvements in CRISPR bio-sensing for nucleic acid and non-nucleic acid targets. It also highlights the current applications of CRISPR/Cas technologies.     

Beta-Site Amyloid Precursor Protein-Cleaving Enzyme Inhibition Partly Restores Sevoflurane-Induced Deficits on Synaptic Plasticity and Spine Loss

Evidence indicates that inhalative anesthetics enhance the β-site amyloid precursor protein (APP)-cleaving enzyme (BACE) activity, increase amyloid beta 1-42 (Aβ_1–42) aggregation, and modulate dendritic spine dynamics. However, the mechanisms of inhalative anesthetics on hippocampal dendritic spine plasticity and BACE-dependent APP processing remain unclear. In this study, hippocampal slices were incubated with equipotent isoflurane (iso), sevoflurane (sevo), or xenon (Xe) with/without pretreatment of the BACE inhibitor LY2886721 (LY). Thereafter, CA1 dendritic spine density, APP processing-related molecule expressions, nectin-3 levels, and long-term potentiation (LTP) were tested. The nectin-3 downregulation on LTP and dendritic spines were evaluated. Sevo treatment increased hippocampal mouse Aβ_1–42 (mAβ_1–42), abolished CA1-LTP, and decreased spine density and nectin-3 expressions in the CA1 region. Furthermore, CA1-nectin-3 knockdown blocked LTP and reduced spine density. Iso treatment decreased spine density and attenuated LTP. Although Xe blocked LTP, it did not affect spine density, mAβ_1–42, or nectin-3. Finally, antagonizing BACE activity partly restored sevo-induced deficits. Taken together, our study suggests that sevo partly elevates BACE activity and interferes with synaptic remodeling, whereas iso mildly modulates synaptic changes in the CA1 region of the hippocampus. On the other hand, Xe does not alternate dendritic spine remodeling.     

Controlling Degree of Inversion in MgFe2O4 Spinel Films Grown in External Magnetic Fields

Single-phase magnesium ferrite spinel films (MgFe₂O₄) were grown by magnetic field-assisted chemical vapor deposition (mfCVD) of a mixed-metal precursor compound, [MgFe₂(O^tBu)₈]. The formation of monophasic MgFe₂O₄ deposits as a function of the applied magnetic field strength (B = 0.0, 0.5, and 1.0 T) was investigated and confirmed by X-ray diffraction and photoelectron spectroscopy analyses. Thin film cross-sectional electron microscopic analysis (FIB-SEM) exhibited higher grain growth and densification in MgFe₂O₄ films obtained under the magnetic field influence when compared to spinel samples grown under zero-field conditions. Application of an external magnetic field of varying strengths during the chemical vapor deposition process resulted in a change in the light absorption properties and crystal orientation in the MgFe₂O₄ films, evident in the decreased photoabsorbance analyzed by the UV-Vis spectra and the decrease of intensity of the (400) peak in MgFe₂O₄ films grown under magnetic field. A comprehensive analysis of X-ray diffraction and X-ray magnetic circular dichroism (XMCD) results indicated a higher degree of inversion in MgFe₂O₄ deposits grown in an external magnetic field corroborated by a larger contribution of ligand field transitions of tetrahedrally coordinated Fe(III) centers affecting the visible light absorption of MgFe₂O₄ films.     

Bispidine as a Versatile Scaffold: From Topological Hosts to Transmembrane Transporters

The development of designer topological structures is a synthetically challenging endeavor. We present herein bispidine as a platform for the design of molecules with various topologies and functions. The bispidine-based acyclic molecule, which shows intriguing S-shape topology, is discussed. Single-crystal X-ray diffraction studies revealed that this molecule exists in the solid state as two conformational enantiomers. In addition, bispidine-based designer macrocycles were synthesized and investigated for ionophoric properties. Patch clamp experiments revealed that these macrocycles transport both anions and cations non-specifically with at least tenfold higher chloride conductance over the cations under the given experimental conditions. Ultramicroscopy and single-crystal X-ray crystallographic studies indicated that the self-assembling macrocycle forms a tubular assembly. Our design highlights the use of unconventional dihydrogen interactions in nanotube fabrication.     

State of the Art Metallopolymer Based Functional Nanomaterial for Photodetector and Solar Cell Application

Journal of Inorganic and Organometallic Polymers and Materials - Metallopolymeric functional nanomaterials have been gained the significant interest of researchers because of their exclusive...     

EEG based personality prediction using genetic programming

The reliable correlation between personality and brain signal ensures that inferences from cognitive processes can be achieved. This research aims primarily to predict one's personality using brain signals. On grounds of Psychology, the inference of personality in this work is performed on the basis of the Myers–Briggs Type Indicator (MBTI) personality inventory. Personality consists of different types of thinking, feeling and behavior patterns. EEG signals are produced when a person is exposed to situations or scenarios via visual information and experiences various emotions or sentiments. In this study, by evaluating brain waves while a person watches personality traits elicitation materials, the identification of the personality traits of an individual is done. The elicitation materials used for the collection of the dataset comprise approximately 50 videos with the pre-defined personality of the dramatic personae and therefore, it is considered to be the ground truth for the experimental procedure of this work. For creating a dataset, sixty participants contributed and gave brain signals. The GP model with the proposed BSH crossover, known as the BSHGP model, is implemented. The maximum performance of the BSHGP model for a 10-fold partition scheme is 84.34%.     

Isolated word language identification system with hybrid features from a deep belief network

The representation of good audio features is the first and foremost requirement for improving the identification performance of any system. Most of the representation learning approaches are based on connectionist systems to learn and extract latent features from the speech data. This research work presents a hybrid feature extraction approach to integrate Mel-Frequency Cepstral Coefficients (MFCC) features with Shifted Delta Cepstral (SDC) coefficients features, which are further stacked to Deep Belief Network (DBN), for yielding new feature representations of the speech signals. DBN is utilized for unsupervised feature learning on the extracted MFCC-SDC acoustic features. A 3-layer Back Propagation Neural Network (BPNN) classifier is initialized in terms of the learning outcomes of hidden layers of DBN for identifying language from the uttered speech. The efficiency of the proposed approach is evaluated by simulating several experimental algorithms on the user-defined database of isolated words in four languages, namely, Tamil, Malayalam, Hindi, and English, in the working platform of MATLAB. The obtained results for the proposed hybrid approach MFCC-SDC-DBN are promising. The proposed approach is also compared with the baseline feature extraction approach MFCC-SDC by utilizing traditional acoustic features and BPNN classifier. The accuracy obtained with our proposed approach is 98.1% whereas that of the baseline approach is 82%, thereby providing an overall improvement of 16.1%.     

Superior Peroxidase-Like Activity of Gold Nanorattles in Ultrasensitive H2O2 Sensing and Antioxidant Screening

Nanozymes are artificial enzyme systems which are easy to produce, highly stable and cost-effective in comparison to natural enzymes. Herein, we evaluated the peroxidase-like activity of gold nanorattles (Au NRTs) having a solid gold octahedron core and thin, porous cubic gold shell. We also prepared solid gold nanocubes and nanospheres of similar sizes and surface charge as that of Au NRTs and compared their activity with standard horse radish peroxidase (HRP). All the prepared nanostructures followed Michaelis-Menten kinetics as observed from their substrate concentration vs. initial reaction velocity plot using 3,3’,5,5’-tetramethylbenzidine (TMB) as a substrate. The kinetic parameters and the catalytic efficiency for the peroxidase-like activity of the nanostructures and HRP were calculated, and it was observed that Au NRTs possess the best nanozymatic activity with lowest K_M and highest catalytic efficiency (k_cat/K_M). The better activity of Au NRTs compared with other nanostructures and HRP could be attributed to the hollow porous structure with a solid core where different surfaces are available for reaction. Au NRTs, being the best amongst the tested nanozymes were further used for the sensing of hydrogen peroxide (H₂O₂) and were found to sense H₂O₂ down to 0.5 μM. Further, two naturally occurring antioxidants, tannic acid and ascorbic acid showed inhibitory effect on the peroxidase-like activity of Au NRTs in a concentration dependent manner which can be further used for screening of antioxidants or for determining the antioxidant potential.