Identification and molecular mechanisms of novel antioxidative peptides from fermented camel milk (Kachchi breed,India) with anti-inflammatory activity in raw macrophages cell lines

The investigation was aimed at assessing anti-inflammatory and antioxidative activities along with the release of peptides with antioxidative properties during the fermentation of camel milk by Lacticaseibacillus casei (NK9). Reverse-phase high-performance liquid chromatography (RP-HPLC) was used to separate the bioactive peptides of 3 and 10 kDa (permeates and retentates). Reverse-phase liquid chromatography–mass spectrometry (RPLC/MS) was used to identify and characterise the pure bioactive peptides, and the effect of fermented camel milk on inflammation produced by lipopolysaccharide (LPS)/endotoxin in RAW 264.7 (Ralph and William's cell line) was also examined. Furthermore, docking revealed that peptides (LLNEK and IYTFPQPQSL) were predicted to inhibit myeloperoxidase (nMPO) activity by engaging with different residues in and around the human myeloperoxidase (hMPO) active site.     

Effect of soil moisture stress from flowering to grain maturity on functional properties of Sri Lankan rice flour

Functional properties of flour from rice variety BG 250 (short‐season) and BG 359 (long‐season) exposed to soil water stress from flowering to grain maturity were investigated. Protein content was reduced in both varieties but lipid was reduced only in BG 359 in response to soil moisture stress. AAM content decreased in BG 250 but unaffected in BG 359. Water stress increased swelling power, onset of pasting, peak viscosity, granular breakdown, gel hardness, and cohesiveness in both varieties. Gelatinization temperatures in both varieties were unaffected by water stress, while gelatinization enthalpy was increased in BG 359 but unchanged in BG 250. A double endotherm (type I and type II) appeared in AM–lipid complex in all the flour samples. Type I AM–lipid complex was reduced in BG 359 in response to water stress. Only a single endotherm appeared in the re‐formed AM–lipid complex in gelatinized starch. The magnitude of the ΔH of re‐formed AM–lipid complex was reduced in BG 359 in response to soil moisture stress, but unaffected in BG 250. Water stress decreased AP retrogradation in BG 359 while it was unaffected in BG 250.     

Ultra Steep Ge-Source Dopingless Tunnelling Field Effect Transistor with Enhanced Drive Current: DC to Linearity Characteristics Analysis

Silicon - Ge-source dopingless tunnelling field effect transistor (Ge-source DLTFET) with the optimization of dielectric oxide thickness under the source and the gate contacts is proposed and...     

Green emitting β$\ubeta$-SiAlON:Eu2+ phosphors derived from chemically modified perhydropolysilazanes

We report the first synthesis of β-SiAlON:Eu²⁺ phosphors from single-source precursors, perhydropolysilazane (PHPS), chemically modified with Al(OCH(CH₃)₂)₃, and EuCl₂. The reactions occurring during the precursor synthesis and the subsequent thermal conversion of polymeric precursors into β-SiAlON:Eu²⁺ phosphors have been studied by a complementary set of analytical techniques, including infrared spectroscopy, gas chromatography–mass spectrometry, thermogravimetry–mass spectrometry, X-ray diffraction (XRD), photoluminescence spectroscopy, and scanning electron microscopy. It has been clearly established that Al(OCH(CH₃)₂)₃ immediately reacted with PHPS to afford N–Al bonds at room temperature, whereas N–Eu bond formation was suggested to proceed above 600°C accompanied by the elimination of HCl up to 1000°C in flowing N₂. The subsequent 1800°C-heat treatment for 1 h under an N₂ gas pressure at 980 kPa allowed converting the single-source precursors into fine-grained β-SiAlON:Eu²⁺ phosphors. XRD analysis revealed that the Al/Si of .09 was the critical atomic ratio in the precursor synthesis to afford single-phase β-SiAlON (z = .55). Moreover, Eu²⁺-doping was found to efficiently reduce the carbon impurity in the host β-SiAlON. The polymer-derived β-SiAlON:Eu²⁺ phosphors exhibited green emission under excitation at 460 nm and achieved the highest green emission intensity at the critical dopant Eu²⁺ concentration at 1.48 at%.     

Integrated sequential fuzzy logic search models for simulating wastewater treatment plants missing influent parameters

Aiming at achieving optimum operations of wastewater treatment plant (WWTP) processes, it is essential to develop accurate predictive models for expected influent pollutant loads. To overcome limited timespan data and model complexity, this study is devoted to propose an integration of inputs' sequential search with the adaptive neuro-fuzzy inference system (ANFIS) for reducing the modelling complexity. The input data included nine influent parameters measured bi-weekly for 12 years at a WWTP, South Africa (SA). The sequential search process was used for input optimization to select the most representative inputs in modelling four parameters. The obtained results indicated a strong correlation with R² and NSE above 0.85 for the four targeted influent parameters. After validating the developed models using different criteria, the missing records were predicted throughout the study period. The integration of sequential search input optimization and ANFIS modelling was able to provide a high performance in modelling WWTP datasets.     

Dynamic response of composite panels under thermo-mechanical loading

In this communication, large amplitude flexural vibration behavior of composite curved and doubly curved panels has been studied using the finite element method. Here nonlinear governing equations of motion has been derived based on first order shear deformation theory with von Karman's kinematics, and these governing equations are solved by employing second-order time integration scheme proposed by Bathe. The efficacy of the method for the nonlinear static and dynamic response of curved panels is validated with the published results. Thereafter, the nonlinear dynamic response of cylindrical and spherical panels under thermal shock loading with and without radial pressure is investigated; the parametric study is also being carried out. This study will be valuable for the scientific community.

     

A Novel Self-Aligned Dopingless Symmetric Tunnel Field Effect Transistor (DL-STFET): A Process Variations Tolerant Design

Silicon - This work reports a novel device structure, dopingless heterojunction symmetric tunnel field effect transistor (DL-STFET), based on the work-function engineering. For realizing dopingless...     

Adenine Modification at C7 as a Viable Strategy to Potentiate the Antimalarial Activity of Quinolones

Although many quinolones have shown promise as potent antimalarials, their clinical development has been slow due to poor performance in vivo. Insights into structural modifications that can improve their therapeutic potential will be very valuable in this vibrant area of research. Our studies involving a library of quinolones which vary in substitution pattern at N1, C3, C6 and C7 positions have shown that the presence of adenine moiety at C7 can bring a noticeable improvement in activity compared to other heterocyclic groups at this location. The most potent compound emerged from this study showed IC₅₀ values of 0.38 μM and 0.75 μM against chloroquine-sensitive and -resistant (W2) strains, respectively. Docking analysis in the Q_o site of cytochrome bc1 complex revealed the contribution of a key H-bonding interaction from the adenine unit in target binding. This corroborates with compound-induced loss of mitochondrial functions. These findings not only open avenues for further exploration of antimalarial potential of adenine-modified quinolones, but also suggests broader opportunities during lead-optimization against other antimalarial targets.     

Stratum-Confined Solid-State Reaction (SC-SSR) toward Colloidal Silicon-Based Hollow Nanostructures for Bioapplications

Silicon nanostructures (SiNSs) can provide multifaceted bioapplications; but preserving their subhundred nm size during high-temperature silica-to-silicon conversion is the major bottleneck. The SC-SSR utilizes an interior metal-silicide stratum space at a predetermined radial distance inside silica nanosphere to guide the magnesiothermic reduction reaction (MTR)-mediated synthesis of hollow and porous SiNSs. In depth mechanistic study explores solid-to-hollow transformation encompassing predefined radial boundary through the participation of metal-silicide species directing the in-situ formed Si-phase accumulation within the narrow stratum. Evolving thin-porous Si-shell remains well protected by the in-situ segregated MgO emerging as a protective cast against the heat-induced deformation and interparticle sintering. Retrieved hydrophilic SiNSs (<100 nm) can be conveniently processed in different biomedia as colloidal solutions and endocytosized inside cells as photoluminescence (PL)-based bioimaging probes. Inside the cell, rattle-like SiNSs encapsulated with Pd nanocrystals can function as biorthogonal nanoreactors to catalyze intracellular synthesis of probe molecules through C-C cross coupling reaction.     

Residual UNet with Dual Attention—An ensemble residual UNet with dual attention for multi-modal and multi-class brain MRI segmentation

In this paper, we have proposed a variant of UNet for brain magnetic resonance imaging (MRI) segmentation. The proposed model, termed as Residual UNet with Dual Attention (RUDA), addresses the two significant challenges of UNet: extraction of the complex features with unclear boundaries and the problem of over-segmentation due to the redundancy caused by the skip connection usage. RUDA is constituted upon the residual blocks for extracting the complex structures. It Introduces attention into the skip connections to avoid redundancy and thereby the chance of over-segmentation. Our model segments brain MRI into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) regions, which are considered crucial informative substructures for diagnosing neurological disorders such as Alzheimer's. It has been implemented in an ensemble manner to accommodate the multi-sequence (T1-weighted, IR, and T2-FLAIR) scans. The empirical analysis shows that with an accuracy of 93.80%, RUDA outperforms the two baseline models: UNet (91.37%), ResUNet (91.44%).