Ti-30Nb-3Ag alloy with improved corrosion resistance and antibacterial properties for orthopedic and dental applications produced by mechanical alloying

Titanium alloys have gained popularity as a bioimplant material due to their biocompatibility, low modulus of elasticity, and increased strength. However, other issues, such as corrosion resistance, and infections can reduce the implant's lifespan. This paper aims to fabricate a new Ti-30Nb-3Ag at% alloy with enhanced in vitro corrosion and antibacterial properties by mechanical alloying (MA) followed by powder consolidation. XRD, SEM/EDX, and Vickers microhardness analyses were used to examine the phases compositions, microstructure, and microhardness, respectively. The in vitro corrosion performance of Ti-30Nb-3Ag alloy was inspected in a simulated body medium and artificial saliva. The alloy's antibacterial properties were evaluated in the gram-positive and negative bacterial medium. The results showed that after MA for 60 h, nanocrystalline β-Ti (BCC) and α-Ti (HCP) solid solutions were formed with crystallite sizes of 7.44 and 3.47 nm, respectively. The sintered sample exhibited densifications of 97%, with a microstructure composed of β-Ti, α-Ti, and a minor quantity of ultrafine Ti₂Ag phase. The microhardness result showed that Ti-30Nb-3Ag alloy possesses HV 491.5. Ti-30Nb-3Ag alloy has a potent antibacterial capability of 85.75% and 88.81% relative to Ti-6Al-4V alloy and CP-Ti, respectively. In vitro corrosion results revealed that the Ti-30Nb-3Ag alloy exhibited the widespread passive area in the investigated anodic regions and presented the highest impedance values in comparison with the commercial alloys, confirming its improved corrosion resistance performance in both studied mediums. Ti-30Nb-3Ag alloy possibly be a competitive bioimplant material for orthopedic and dental uses owing to its enhanced biocorrosion and antibacterial properties compared to commercial Ti-6Al-4V alloy and CP-Ti.

The microtubule end-binding proteins EB1 and Patronin modulate the spatiotemporal dynamics of myosin and pattern pulsed apical constriction

Apical constriction powers amnioserosa contraction during Drosophila dorsal closure. The nucleation, movement and dispersal of apicomedial actomyosin complexes generates pulsed apical constrictions during early closure. Persistent apicomedial and circumapical actomyosin complexes drive unpulsed constrictions that follow. Here, we show that the microtubule end-binding proteins EB1 and Patronin pattern constriction dynamics and contraction kinetics by coordinating the balance of actomyosin forces in the apical plane. We find that microtubule growth from moving Patronin platforms governs the spatiotemporal dynamics of apicomedial myosin through the regulation of RhoGTPase signaling by transient EB1-RhoGEF2 interactions. We uncover the dynamic reorganization of a subset of short non-centrosomally nucleated apical microtubules that surround the coalescing apicomedial myosin complex, trail behind it as it moves and disperse as the complex dissolves. We demonstrate that apical microtubule reorganization is sensitive to Patronin levels. Microtubule depolymerization compromised apical myosin enrichment and altered constriction dynamics. Together, our findings uncover the importance of reorganization of an intact apical microtubule meshwork, by moving Patronin platforms and growing microtubule ends, in enabling the spatiotemporal modulation of actomyosin contractility and, through it, apical constriction.

The Adverse Outcome Pathway Framework Applied to Neurological Symptoms of COVID-19

Several reports have shown that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has the potential to also be neurotropic. However, the mechanisms by which SARS-CoV-2 induces neurologic injury, including neurological and/or psychological symptoms, remain unclear. In this review, the available knowledge on the neurobiological mechanisms underlying COVID-19 was organized using the AOP framework. Four AOPs leading to neurological adverse outcomes (AO), anosmia, encephalitis, stroke, and seizure, were developed. Biological key events (KEs) identified to induce these AOs included binding to ACE2, blood–brain barrier (BBB) disruption, hypoxia, neuroinflammation, and oxidative stress. The modularity of AOPs allows the construction of AOP networks to visualize core pathways and recognize neuroinflammation and BBB disruption as shared mechanisms. Furthermore, the impact on the neurological AOPs of COVID-19 by modulating and multiscale factors such as age, psychological stress, nutrition, poverty, and food insecurity was discussed. Organizing the existing knowledge along an AOP framework can represent a valuable tool to understand disease mechanisms and identify data gaps and potentially contribute to treatment, and prevention. This AOP-aligned approach also facilitates synergy between experts from different backgrounds, while the fast-evolving and disruptive nature of COVID-19 emphasizes the need for interdisciplinarity and cross-community research.

Computational and Mathematical Methods in Medicine Glioma Brain Tumor Detection and Classification Using Convolutional Neural Network

The classification of the brain tumor image is playing a vital role in the medical image domain, and it directly assists the clinicians to understand the severity and to take an appropriate solution. The magnetic resonance imaging tool is used to analyze the brain tissues and to examine the different portion of brain circumstance. We propose the convolutional neural network database learning along with neighboring network limitation (CDBLNL) technique for brain tumor image classification in medical image processing domain. The proposed system architecture is constructed with multilayer-based metadata learning, and they have integrated with CNN layer to deliver the accurate information. The metadata-based vector encoding is used, and the type of coding estimation for extra dimension is known as sparse. In order to maintain the supervised data in terms of geometric format, the atoms of neighboring limitation are built based on a well-structured k-neighbored network. The resultant of the proposed system is considerably strong and subjective for classification. The proposed system used two different datasets, such as BRATS and REMBRANDT, and the proposed brain MRI classification technique outcome is more efficient than the other existing techniques.

Degradation of Toxic Dye and Antimicrobial and Free Radical Potential of Environmental Benign Zinc Oxide Nanoparticles

Several industries have become major contributors to waterbody contamination due to the improper removal of dyes and effluents into water bodies. Due to their carcinogenic properties and low biodegradability, dye degradation is a considerable danger to people, animals, and the oceanic environment. As part of this study, Andrographis paniculata leaf extract was used as a reducing and stabilizing agent to synthesize zinc nanoparticles and degrade dyes such as methyl red and eosin. Zinc oxide nanoparticles (ZnONPs) showed a surface plasmon resonance peak at 430 nm in the UV spectrum. The FTIR result showed a band at 597.93 cm-1 that confirmed the formation of zinc nanoparticles. AFM results revealed spherical ZnONPs. The SEM results predicted an average particle size of 60 nm for crystalline particles. Biologically synthesized zinc nanoparticles exhibited greater antibacterial activity against Pseudomonas spp. and Proteus spp. but lesser activity against Klebsiella spp. and S. aureus. At 1000 μg/ml concentration, ZnONPs had the highest antioxidant activity of 45.34%. An ultraviolet-visible spectrophotometer measured dye degradation progress between 300 and 800 nm. For methyl red, the maximum absorption peak was measured at 415 nm, and for eosin, the maximum peak value was measured between 500 and 515 nm.

A deep learning model based anomalous behavior detection for supporting verifiable access control scheme in cloud servers

Due to the growth of Big Data (BD) storage and access in cloud computing infrastructure, the detection of anomalies for Cloud Servers (CSs) is essential to ensure data confidentiality. Over the past decades, different security systems have been designed based on various methods like encryption, Access Policy (AP) control schemes, signcryption and so on. Among many security systems, a new Improved NTRU (INTRU) decryption based on the AP strategy has been suggested to secure the BD processed by the CSs. Also, the shared secret data was authenticated to defend the clients from anomalies in the cloud. But, the AP upgrade must not degrade the confidentiality of storing information, reveal trust in the CS or cause any different security challenges. It is not considered that such security challenges occur when the data owner shares its data with many CSs. Hence in this article, an INTRU with Detecting Anomalous in CS (INTRU-DACS) system is proposed that employs a deep learning-based Anomaly Detection System (ADS) to handle and secure the BD stored in the CSs. The main goal of this method is to effectively identify the abnormalities in the real world by the conduct utilization, i.e., the System Call Identifier Sequences (SCISs) created from CSs in which these conducts are associated with BD. Initially, effective data summarization is constructed via different feature states to analyze the SCISs of specific durations. After that, an anomaly identification algorithm is proposed to train and test the streaming of raw SC sequences. This observable SCs execution task of CSs is gathered from log files. The variations of such SCISs having a specified duration are random for usual and unusual sequences. So, the fact of current normal and abnormal services is recognized regarding their SCISs. Such normal and abnormal behavioral states are learned from Convolutional Neural Network-Hidden Markov Model (CNNHMM) classifier to identify the anomalies in CSs. But, it is still a challenging process because of the patterns of usual and unusual events. The performance is not effective since it models only the conduct of a huge number of SCISs created from a single CS. As a result, a Secure Access Control Scheme with DACS (SACS-DACS) system is proposed in which a Multidimensional Feature Misbehavior Server Detection method (MFMSD) is introduced for detecting anomalies in multiple CSs. In this method, large-scale SCISs of multiple CSs are extracted, including different features such as network traffic sequence features, CPU energy usage and memory usage from host logs. These extracted multidimensional features are fed to the CNNHMM that identifies the anomalies and maximizes the detection accuracy. At last, the simulation results demonstrate the effectiveness of the SACS-DACS and INTRU-DACS as compared to the INTRU.

Excellent photocatalytic performances of Co3O4-AC nanocomposites for H2 production via wastewater splitting

Natural sunlight-driven photocatalytic hydrogen production from wastewater is one of the most desirable techniques that can realize future green energy technology. Herein, we report the synthesis and the characterization of the biomass activated carbon (AC)-decorated cobalt oxide (Co₃O₄) nanocomposites for solar-stimulated photocatalytic hydrogen production from sulphide wastewater. The Co₃O₄-AC nanocomposites were ultrasonically synthesized by using hydrothermally-grown spinel Co₃O₄ nanoflakes and biomass-derived AC nanoflakes. Co₃O₄-AC showed a nanobundle-like aggregated morphology, and exhibited a large specific surface area (~133 m²/g). Through utilizing Co₃O₄-AC as a photocatalyst for photocatalytic splitting of sulphide wastewater (0.2 M) under solar irradiance with 730 W/m², an enhanced H₂ production efficiency (~70 mL/h) was achieved owing to the synergic effects from 2-dimentionally configured Co₃O₄ and AC microstructures; i.e., large surface area of Co₃O₄ and high electrical conductivity of AC. These findings suggest the nanocomposites of Co₃O₄-AC to hold great promise for the green approach of photocatalytic wastewater splitting.

Induction of antiviral and cell mediated immune responses significantly reduce viral load in an acute foot-and-mouth disease virus infection in cattle

Foot-and-mouth disease virus (FMDV) causes a severe infection in ruminant animals. Here we present an in-depth transcriptional analysis of soft-palate tissue from cattle experimentally infected with FMDV. The differentially expressed genes from two Indian cattle (Bos indicus) breeds (Malnad Gidda and Hallikar) and Holstein Friesian (HF) crossbred calves, highlighted the activation of metabolic processes, mitochondrial functions and significant enrichment of innate antiviral immune response pathways in the indigenous calves. The results of RT-qPCR based validation of 12 genes was in alignment with the transcriptome data. The indigenous calves showing lesser virus load, elicited early neutralizing antibodies and IFN-γ immune responses. This study revealed that induction of potent innate antiviral response and cell mediated immunity in indigenous cattle, especially Malnad Gidda, significantly restricted FMDV replication during acute infection. These data highlighting the molecular processes associated with host-pathogen interactions, could aid in the conception of novel strategies to prevent and control FMDV infection in cattle.

N,N-Ru(II)-p-cymene-poly(N-vinylpyrrolidone) surface functionalized gold nanoparticles: from organoruthenium complex to nanomaterial for antiproliferative activity

Organometallic Ru-arene complexes are promising as anticancer agents, but the lack of tumor uptake and poor solubility in the physiological medium impede their development. In order to deal with these challenges, we developed gold nanoparticles coated with Ru(arene)-functionalized PNVP-Py, where PNVP-Py is pyridine end-functionalized poly(N-vinylpyrrolidone). It is demonstrated that these particles exhibit higher anti-proliferative activity than the individual organometallic ruthenium(ii) complex of the type [Ru(η6-p-cymene)(NN)Cl]PF6, where NN is bis(4-methoxyphenylimino)acenaphthene, against colorectal adenocarcinoma cell lines. More specifically, a RuII(η6-p-cymene) complex containing a NN bidentate ligand has been prepared and characterized by spectral studies and X-ray crystallography. To tether the isolated complex onto the surface of the AuNPs, PNVP-Py, which contains a pyridine group at one end to coordinate to the Ru-complex and a suitable functional group at the other end to bind on the surface of the AuNPs, has been prepared and utilized to obtain the macromolecular complex [Ru(η6-p-cymene)(NN)(PNVP-Py)]Cl2. Next, stable Ru(p-cym)(NN)(PNVP-Py)@AuNPs were obtained via a ligand exchange reaction of citrate-stabilized AuNPs with a macromolecular complex by a direct 'grafting to' approach and characterized well. Despite the lower DNA cleavage activity, the nanoconjugate exhibits better cytotoxicity than the individual complex against HT-29 colorectal adenocarcinoma cells on account of its enhanced permeability across the cell membrane. The AO/EB staining assay revealed that the nanoconjugate is able to induce an apoptotic mode of cell death, which was further quantitatively evaluated by Annexin V-FITC/PI double assay. An immunofluorescence assay indicated the higher potency of the nanoconjugate to inhibit cyclin D1 gene expression that is required for cancer cell growth. To the best of our knowledge, this is the first report of the modification of an organometallic Ru(arene) complex into a Ru(arene)metallopolymer-gold nanoconjugate for the development of ruthenium-based nanomedicine for cancer treatment.

Performance Analysis of Glioma Brain Tumor Segmentation Using Ridgelet Transform and Co-Active Adaptive Neuro Fuzzy Expert System Methodology

Objective: The Glioma brain tumor detection and segmentation methods are proposed in this paper using machine learning approaches. The primary objective of this paper is to provide high level of tumor region segmentation using optimization and machine learning techniques. Methods: The boundary edge pixels are detected using Kirsch's edge detectors and then contrast adaptive histogram equalization method is applied on the edge detected pixels. Then, Ridgelet transform is applied on this enhanced brain image in order to obtain the Ridgelet multi resolution coefficients. Further, features are derived from the Ridgelet transformed coefficients and the features are optimized using Principal Component Analysis (PCA) method and these optimized features are classified into Glioma or non-Glioma brain images using Co-Active Adaptive Neuro Fuzzy Expert System (CANFES) classifier. Results: The proposed method with PCA and CANFES classification approach obtains 97.6% of sensitivity (Se), 98.56% of Specificity (sp), 98.73% of Accuracy (Acc), 98.85% of Precision (Pr), 98.11% of False Positive Rate (FPR) and 98.185 of False Negative Rate (FNR), then the proposed Glioma brain tumor detection method using CANFES classification approach only.

Digital Hearing Aids Using Automated Varying Bandwidth Finite Impulse Response Filter Banks

A human auditory system is a highly complex sensitive system which transfers the acoustic sound into neuroelectrical signals toward the brain. Hearing difficulties or deafness are the outcomes of the problems occurred at any part of the auditory system. Assistive technologies such as hearing aids are developed to improve the quality of life of the hearing impaired people. Current digital hearing aids have fixed bandwidth filter banks which cannot provide enough flexibility to match with audiogram of different hearing loss. Recently, variable bandwidth filter banks have been introduced with different technologies to match more closely with the audiogram of a particular hearing loss. This research work proposes and implements a software controlled variable bandwidth FIR filter bank using Matlab GUI. In the Matlab GUI, in the filter bank, the bandwidth of every filter is adjusted dynamically in the Matlab GUI such that it fits more closely to the audiogram of a particular hearing loss. An experiment has been conducted in the developed Matlab GUI with various hearing loss, and the results show that the proposed system matches the filter bank magnitude response very closely to the audiogram of a particular hearing loss and reduces the matching error.

Advanced Digital Signal Processing Techniques on the Classification of the Heart Sound Signals

Speech processing subject primarily depends on the digital signal processing (DSP) methods, such as convolution, discrete Fourier transform (DFT), fast Fourier transforms (FFT), finite impulse response (FIR) and infinite impulse response (IIR) filters, FFT recursive and non-recursive digital filters, FFT processing, random signal theory, adaptive filters, upsampling and downsampling, etc. Recursive and non-recursive digital filters are primarily deployed to absorb the signal of interest signals and to block the unwanted signals (noise). Broadly, low-pass, high-pass, band-pass, and band-stop filters are implemented for filtering functions. In frequent, the DSP theories can be used for further biomedical engineering domains like biomedical imaging (MRI, ultrasound, CT, X-ray, PET) and genetic signal analysis-cum-processing too. In this article, the experiments such as voiced/unvoiced detection, formants estimation using FFT and spectrograms, pitch estimation and tracking and yes/no sound classification are used. Also, the analysis of normal/abnormal heart sound signals using simple energy computation and the zero-crossing rate and their results are obtained. For the entire study, the Matlab R2018a tool is used to obtain the simulation results. At last, the criticism, feedbacks, comments, reactions from the student are detailed for the exceptional development of the course.

Revisiting FPGA Implementation of Digital Filters and Exploring Approximate Computing on Biomedical Signals

In recent years, the approximate computing becomes popular in the era of VLSI (very large scale integration) domain to arrive better power, area, and delay outcomes at the cost of lower precision loss. Also, the human beings are not so intelligent to see/observe/listen the processed digital data; means even if some of the data loss occurs human beings are unable to notice them. This behavior set the engineers to research on approximate computing which are very useful in the multimedia data processing, data communications, high-volume data storage, etc. In this study, the experiments such as hum-noise removal, filters on QRS detection are implemented on an Altera FPGA EP4CEF29C7 device using Quartus II 13.1 synthesis software tool and the simulation results on device utilization reports, the speed and the power are obtained. Simulation results reveal that the approximate computational filters offer better power, area, and speed results than the conventional ones. Also, Matlab 9.4 (R2018a) simulation was used to carry out the functional verification of the actual and approximate filters.

Optimization of Aqueous Two Phase Extraction of Proteins from Litopenaeus Vannamei Waste by Response Surface Methodology Coupled Multi-Objective Genetic Algorithm

Waste generated from industrial processing of seafood is an enormous source of commercially valuable proteins. One among the underutilized seafood waste is shrimp waste, which primarily consists of head and carapace. Litopenaeus vannamei (L. vannamei) is the widely cultivated shrimp in Asia and contributes to 90 % of aggregate shrimp production in the world. This work was focused on extraction as well as purification of value-added proteins from L. vannamei waste in a single step aqueous two phase system (ATPS). Polyethylene glycol (PEG) and trisodium citrate system were chosen for the ATPS owing to their adequate partitioning and less toxic nature. Response surface methodology (RSM) was implemented for the optimization of independent process variables such as PEG molecular weight (2000 to 6000), pH (6 to 8) and temperature (25 to 45 °C). The results obtained from RSM were further validated using a Multi-objective genetic algorithm (MGA). At the optimized condition of PEG molecular weight 2000, pH 8 and temperature 35 °C, maximum partition coefficient and protein yield were found to be 2.79 and 92.37 %, respectively. Thus, L. vannamei waste was proved to be rich in proteins, which could be processed industrially through cost-effective non-polluting ATPS extraction, and RSM coupled MGA could be a potential tool for such process optimization.

Hematological and serum biochemical profile in cattle experimentally infected with foot-and-mouth disease virus

Background and Aim:

Foot-and-mouth disease (FMD) is an acute viral infection affecting cloven-hoofed animals causing vesicular erosions in the oral cavity and interdigital space. The present study was undertaken to ascertain the time-dependent changes in clinical, hematological, and biochemical profiles in different breeds of cattle following experimental infection.

Materials and Methods:

The animals were inoculated with 1.0×10⁴ 50% bovine tongue infectious dose (BTID₅₀) by intradermolingual route. Clinical signs were observed, and blood/serum samples were collected at different time intervals.

Results:

The white blood cell count declined sharply on days 7-13 and recovered on day 14 post-FMD infection. Biochemical analysis of serum markers for vital organ profile revealed no marked damage. However, a significant increase in blood urea nitrogen (BUN) value indicated pre-renal azotemia. Transient hyperthyroidism was indicated by the rise in T3 and T4 that can be correlated with a decrease in triglyceride and total cholesterol levels. In the cardiac damage assessment study, a distinct breed difference was observed wherein Malnad Gidda calves showed no cardiac damage.

Conclusion:

Except thyroid profile, BUN, and creatine kinase-myocardial band, all other serum biochemical parameters showed no significant abnormalities, whereas lymphopenia is the only hematological change and it is suggested that effective ameliorative measures should be targeted mainly on the feed/water intake, thyroid gland, and the level of lymphocytes.

Electroencephalogram based communication system for locked in state person using mentally spelled tasks with optimized network model

Due to growth in population, Individual persons with disabilities are increasing daily. To overcome the disability especially in Locked in State (LIS) due to Spinal Cord Injury (SCI), we planned to design four states moving robot from four imagery tasks signals acquired from three electrode systems by placing the electrodes in three positions namely T1, T3 and FP1. At the time of the study we extract the features from Continuous Wavelet Transform (CWT) and trained with Optimized Neural Network model to analyze the features. The proposed network model showed the highest performances with an accuracy of 93.86 % then that of conventional network model. To confirm the performances we conduct offline test. The offline test also proved that new network model recognizing accuracy was higher than the conventional network model with recognizing accuracy of 97.50 %. To verify our result we conducted Information Transfer Rate (ITR), from this analysis we concluded that optimized network model outperforms the other network models like conventional ordinary Feed Forward Neural Network, Time Delay Neural Network and Elman Neural Networks with an accuracy of 21.67 bits per sec. By analyzing classification performances, recognizing accuracy and Information Transformation Rate (ITR), we concluded that CWT features with optimized neural network model performances were comparably greater than that of normal or conventional neural network model and also the study proved that performances of male subjects was appreciated compared to female subjects.

Diversity of hepatitis C virus infection among HIV-infected people who inject drugs in India

The availability of generic direct acting antivirals (DAAs) for hepatitis C virus (HCV) treatment has prompted many low-and-middle-income countries to launch HCV elimination programs. Because the efficacy of some of these generic DAAs varies by HCV viral subtype, information on subtype distribution can contribute important information to these elimination programs. We conducted a cross-sectional serosurvey to characterize HCV subtype diversity among HIV positive people who inject drugs (PWID) across 14 cities in India. Of 801 HIV positive PWID sampled, 639 tested HCV antibody positive (78.9%). Among 105 samples sequenced, genotype 3 (58.1%) was the most commonly observed followed by genotype 1 (36.2%) and genotype 6 (5.7%). Of the genotype 3 infections, 65% were subtype 3a and 35% were subtype 3b. Of the genotype 1 infections, 94% were subtype 1a and 6% were subtype 1b. All genotype 6 samples were subtype 6n. There was some variability in genotype diversity depending on geographic region and PWID epidemic stage with greater diversity observed in older PWID epidemics. One sequence, HY018, did not cluster with any known reference sequences in phylogenetic analysis. Nearly 80% of HIV infected PWID across India are co-infected with HCV, and subtype prevalence and genetic diversity varied by region and PWID epidemic stage. HCV elimination programs in India will need to consider HCV subtype.

In vitro anticancer activity of fucoidan extracted from Sargassum cinereum against Caco-2 cells

Fucoidan is a marine sulfated polysaccharide, which is extracted from brown seaweed that has a wide range of bioactivities including anti-cancer properties. However, the underlying mechanism of fucoidan on its anti-cancer and apoptotic activity against colon cancer cell line Caco-2 remains to be elucidated. Hence, the present study evaluated the cytotoxicity, apoptotic and anti-cancer activity of fucoidan extracted from brown seaweed Sargassum cinereum against Caco-2 cell line. Cytotoxicity, morphological examination of nuclei, mitochondrial membrane potential, flow cytometry, reactive oxygen species (ROS) formation and detection of apoptotic efficacy of fucoidan were assessed by different assay protocols. Fucoidan inhibited growth of Caco-2 cells in a dose-dependent manner. IC50 concentration of fucoidan was found to be 250 μg/ml. AO/EB, Hoechst and Annexin V/PI staining confirmed the apoptosis induced by fucoidan in Caco-2 cells. Fucoidan was also found to increase ROS production and augment mitochondrial membrane permeability. The findings of the study suggest that fucoidan exerts potent anti-cancer and apoptotic effect on Caco-2 cells by enhancing ROS production. Thus, fucoidan may be used as a promising therapeutic regimen against various cancer cell types.

PEDOT/FHA nanocomposite coatings on newly developed Ti-Nb-Zr implants: Biocompatibility and surface protection against corrosion and bacterial infections

The fabrication of bioactive polymer nanocomposite coatings with enhanced biocompatibility and surface protection has been a topic of abundant concern in orthopaedic implant applications. Herein, we electrochemically prepared a novel poly (3,4-ethylenedioxythiophene) (PEDOT) based nanocomposite coatings with different contents of fluoro hydroxyapatite (FHA) nanoparticles on a newly developed Ti-Nb-Zr (TNZ) alloy; an appropriate approach to advance the surface features of TNZ implants. FTIR, XRD, and Raman analyses of the coating confirm the successful preparation of PEDOT/FHA nanocomposite, and XPS validate the chemical interaction between FHA and PEDOT matrix. SEM and TEM examination show the uniform distribution of spherical FHA nanoparticles inside the PEDOT matrix. Hardness and contact angle measurement results showed improving in the hardness and surface wettability of the coated samples respectively. Electrochemical corrosion tests specified that the PEDOT/FHA coatings exhibit higher corrosion protection than the pure PEDOT coatings. The fabricated nanocomposite coating supports the cell adsorption and proliferation of MG-63 cells. Moreover, antibacterial studies against Gram positive and negative bacteria reveal the enhanced antibacterial performance of the coated TNZ substrates. Our results show the potential applications of PEDOT/FHA nanocomposite as a most viable coating for the orthopaedic implants.

Swertiamarin, a natural steroid, prevent bone erosion by modulating RANKL/RANK/OPG signaling

Bone erosion is a central feature of rheumatoid arthritis (RA) that is characterized by the infiltration of the synovial lining by osteoclasts and lymphocytes. In the present study, swertiamarin a major secoiridoid glycoside was evaluated for anti-osteoclastogenic property to prevent bone erosion in Freund's complete adjuvant (FCA) induced in-vivo model, in-vitro osteoblast and osteoclasts as well as in co-culture system and in-silico molecular docking analysis. The swertiamarin treatment decreased the expression of TRAP, RANKL, and RANK levels and increased the levels of OPG levels significantly in both in vitro and in vivo models. In in vitro, the compound treatment significantly increased the cell proliferation and ALP levels in osteoblast cells; the high proliferation (153.8600±5.23%) and ALP release (165.6033±4.13%) were observed at 50μg/ml concentration of swertiamarin treatment. At the same time the treatment decreased the TRAP positive cells in osteoclast cells; the high reductions of TRAP positive cells (39.32±3.19%) were observed at 50μg/ml of swertiamarin treatment. The treatment modulated the levels of pro-inflammatory cytokines, MMPs and NF-κB levels in osteoblast and osteoclast co-culture system. In in silico analysis swertiamarin had affinity towards the proteins RANK, RANKL and OPG residues with low binding energy -4.5, -3.92 and -5.77kcal/mol respectively. Thus, the results of this study revealed the anti-osteoclastogenic activity of swertiamarin on the prevention of bone destruction.

Occult HBV infection in HIV-infected adults and evaluation of pooled NAT for HBV

The study aimed to determine the prevalence of occult hepatitis B virus infection among HIV-infected persons and to evaluate the use of a pooling strategy to detect occult HBV infection in the setting of HIV infection. Five hundred and two HIV-positive individuals were tested for HBV, occult HBV and hepatitis C and D with serologic and nucleic acid testing (NAT). We also evaluated a pooled NAT strategy for screening occult HBV infection among the HIV-positive individuals. The prevalence of HBV infection among HIV-positive individuals was 32 (6.4%), and occult HBV prevalence was 10%. The pooling HBV NAT had a sensitivity of 66.7% and specificity of 100%, compared to HBV DNA NAT of individual samples. In conclusion, this study found a high prevalence of occult HBV infection among our HIV-infected population. We also demonstrated that pooled HBV NAT is highly specific, moderately sensitive and cost-effective. As conventional HBV viral load assays are expensive in resource-limited settings such as India, pooled HBV DNA NAT might be a good way for detecting occult HBV infection and will reduce HBV-associated complications.

Chitosan/nano-hydroxyapatite/nano-zirconium dioxide scaffolds with miR-590-5p for bone regeneration

Bone tissue engineering (BTE) relies on biocomposite scaffolds and bioactive molecules for bone regeneration. The present study was aimed to synthesize and characterize biocomposite scaffolds containing chitosan (CS), nano-hydroxyapatite (nHAp) and nano‑zirconium dioxide (nZrO₂) along with microRNA (miRNA) for BTE applications. miRNAs act as post-transcriptional regulator of gene expression. The fabricated biocomposite scaffolds were characterized using SEM, FT-IR and XRD analyses. The effect of a bioactive molecule (miR-590-5p) with scaffolds was tested for osteoblast differentiation at the cellular and molecular levels using mouse mesenchymal stem cells (C3H10T1/2). The results showed that CS/nHAp/nZrO₂ scaffolds promoted osteoblast differentiation, and this effect was further increased in the presence of miR-590-5p in C3H10T1/2 cells. Thus, we suggested that CS/nHAp/nZrO₂ scaffolds with miR-590-5p would have potential towards the treatment of bone defects.

Performance and emission analysis on blends of diesel, restaurant yellow grease and n-pentanol in direct-injection diesel engine

Yellow grease from restaurants is typically waste cooking oil (WCO) free from suspended food particles with free fatty acid (FFA) content less than 15%. This study proposes an approach to formulate a renewable, eco-friendly fuel by recycling WCO with diesel (D) and n-pentanol (P) to improve fuel-spray characteristics. Three ternary blends (D50-WCO45-P5, D50-WCO40-P10 and D50-WCO30-P20) were selected based on the stability tests and prepared with an objective to substitute diesel by 50% with up to 45% recycled component (WCO) and up to 20% bio-component (n-pentanol) by volume. The fuel properties of these ternary blends were measured and compared. The emission impacts of these blends on a diesel engine were analysed in comparison with diesel and D50-WCO50 (50% of diesel + 50% of WCO) under naturally articulated and EGR (exhaust gas recirculation) approaches. Doping of n-pentanol showed improved fuel properties when compared to D50-WCO50. Viscosity is reduced up to 45%. Cetane number and density were comparable to that of diesel. Addition of n-pentanol to D50-WCO50 presented improved brake specific fuel consumption (BSFC) for all ternary blends. Brake thermal efficiency (BTE) of D50-WCO30-P20 blend is comparable to diesel due to improved atomization. Smoke opacity reduced, HC emissions increased and CO emissions remained unchanged with doping n-pentanol in the WCO. NOx emission increases with increase in n-pentanol and remained lower than diesel and all load conditions. However, NOx can be decreased by up to threefold using EGR. By adopting this approach, WCO can be effectively reused as a clean energy source by negating environmental hazards before and after its use in diesel engines, instead of being dumped into sewers and landfills.

Bioactive mesoporous wollastonite particles for bone tissue engineering

The current investigation was aimed at identifying the role of mesoporous wollastonite particles on the healing of rat tibial bone defect. The bone defect was created with a 3-mm-diameter dental drill, and it was filled with mesoporous wollastonite particles. After second and fourth weeks of filling treatments, it was found that mesoporous wollastonite particles promoted bone formation as evidenced by X-ray, histological, scanning electron microscope, and energy-dispersive spectra studies. X-ray study showed the closure of drill hole as seen by high-dense radio-opacity image. Histological analysis depicted the deposition of collagen in the bone defect area in response to mesoporous wollastonite particles’ treatment. Scanning electron microscope–energy-dispersive spectra analyses of the sectioned implants also identified the deposition of apatite by these particles. Thus, our results suggested that mesoporous wollastonite particles have bioactive properties, and they can be used as a suitable filling material for promotion of bone formation in vivo.

A novel technique for detoxification of phenol from wastewater: Nanoparticle Assisted Nano Filtration (NANF)

BACKGROUND

Phenol is one of the most versatile and important organic compound. It is also a growing concern as water pollutants due to its high persistence and toxicity. Removal of Phenol from wastewaters was investigated using a novel nanoparticle adsorption and nanofiltration technique named as Nanoparticle Assisted Nano Filtration (NANF).

METHODS

The nanoparticle used for NANF study were silver nanoparticles and synthesized to three distinct average particle sizes of 10 nm, 40 nm and 70 nm. The effect of nanoparticle size, their concentrations and their tri and diparticle combinations upon phenol removal were studied.

RESULTS

Total surface areas (TSA) for various particle size and concentrations have been calculated and the highest was 4710 × 10(12 )nm(2 )for 10 nm particles and 180 ppm concentration while the lowest was for 2461 × 10(11) for 70 nm and 60 ppm concentrations. Tri and diparticle studies showed more phenol removal % than that of their individual particles, particularly for using small particles on large membrane pore size and large particles at low concentrations. These results have also been confirmed with COD and toxicity removal studies.

CONCLUSIONS

The combination of nanoparticles adsorption and nanofiltration results in high phenol removal and mineralization, leading to the conclusion that NANF has very high potential for treating toxic chemical wastewaters.