Characterization of Syzygium cumini (L.) Skeels (Jamun Seed) Particulate Fillers for Their Potential Use in Polymer Composites.

Syzgium cumini (L.) Skeels powder (S. cumini powder), also known as Jamun, is well-known for its various medical and health benefits. It is especially recognized for its antidiabetic and antioxidant properties. Thus, S. cumini powder is used in various industries, such as the food and cosmetic industries. In this work, the fruit of S. cumini was utilized; its seeds were extracted, dried, and ground into powder. The ground powders were subjected to various techniques such as physicochemical tests, Fourier transform infrared (FTIR) spectroscopy, X-ray diffractometry (XRD), particle size analysis, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and antioxidant analysis. From the physicochemical tests, it was revealed that the jamun seed filler contained cellulose (43.28%), hemicellulose (19.88%), lignin (23.28%), pectin (12.58%), and wax (0.98%). The FTIR analysis supported these results. For instance, a peak at 2889 cm-1 was observed and associated with CH stretching, typically found in methyl and methylene groups, characteristic of cellulose and hemicellulose structures. The XRD results demonstrated that the crystallinity index of the jamun seed filler was 42.63%. The particle analysis indicated that the mean (average) particle size was 25.34 µm. This observation was ensured with SEM results. The EDX spectrum results showed the elemental composition of the fillers. Regarding thermal degradation, the jamun seed filler had the ability to withstand temperatures of up to 316.5 °C. Furthermore, endothermic and exothermic peaks were observed at 305 °C and 400 °C, respectively. Furthermore, the antioxidant property of the powder displayed a peak scavenging activity of 91.4%. This comprehensive study not only underscores the viability of S. cumini powder as a sustainable and effective particulate filler in polymer composites but also demonstrates its potential to enhance the mechanical properties of composites, thereby offering significant implications for the development of eco-friendly materials in various industrial applications.

Transcriptome profiling and metabolic pathway analysis towards reliable biomarker discovery in early-stage lung cancer.

Earlier diagnosis of lung cancer is crucial for reducing mortality and morbidity in high-risk patients. Liquid biopsy is a critical technique for detecting the cancer earlier and tracking the treatment outcomes. However, noninvasive biomarkers are desperately needed due to the lack of therapeutic sensitivity and early-stage diagnosis. Therefore, we have utilized transcriptomic profiling of early-stage lung cancer patients to discover promising biomarkers and their associated metabolic functions. Initially, PCA highlights the diversity level of gene expression in three stages of lung cancer samples. We have identified two major clusters consisting of highly variant genes among the three stages. Further, a total of 7742, 6611, and 643 genes were identified as DGE for stages I-III respectively. Topological analysis of the protein-protein interaction network resulted in seven candidate biomarkers such as JUN, LYN, PTK2, UBC, HSP90AA1, TP53, and UBB cumulatively for the three stages of lung cancers. Gene enrichment and KEGG pathway analyses aid in the comprehension of pathway mechanisms and regulation of identified hub genes in lung cancer. Importantly, the medial survival rates up to ~ 70 months were identified for hub genes during the Kaplan-Meier survival analysis. Moreover, the hub genes displayed the significance of risk factors during gene expression analysis using TIMER2.0 analysis. Therefore, we have reason that these biomarkers may serve as a prospective targeting candidate with higher treatment efficacy in early-stage lung cancer patients.

Sequential virtual screening collaborated with machine-learning strategies for the discovery of precise medicine against non-small cell lung cancer.

Dysregulation of MAPK pathway receptors are crucial in causing uncontrolled cell proliferation in many cancer types including non-small cell lung cancer. Due to the complications in targeting the upstream components, MEK is an appealing target to diminish this pathway activity. Hence, we have aimed to discover potent MEK inhibitors by integrating virtual screening and machine learning-based strategies. Preliminary screening was conducted on 11,808 compounds using the cavity-based pharmacophore model AADDRRR. Further, seven ML models were accessed to predict the MEK active compounds using six molecular representations. The LGB model with morgan2 fingerprints surpasses other models ensuing 0.92 accuracy and 0.83 MCC value versus test set and 0.85 accuracy and 0.70 MCC value with external set. Further, the binding ability of screened hits were examined using glide XP docking and prime-MM/GBSA calculations. Note that we have utilized three ML-based scoring functions to predict the various biological properties of the compounds. The two hit compounds such as DB06920 and DB08010 resulted excellent binding mechanism with acceptable toxicity properties against MEK. Further, 200 ns of MD simulation combined with MM-GBSA/PBSA calculations confirms that DB06920 may have stable binding conformations with MEK thus step forwarded to the experimental studies in the near future.Communicated by Ramaswamy H. Sarma.

A practical green synthesis method of Ag NPs using rosy periwinkle plant leaves for solar panel coating.

Coated silver nanoparticles (Ag NPs) are currently receiving interest because of their numerous uses in various fields of electronics, antimicrobials, manufacturing sectors, optical science, and pharmaceuticals. Among others, it gained significant attention in the power electronic system. The goal of the proposed study is to use a cost-effective coating material for solar panels; to accomplish this, silver nanoparticles were synthesized from the leaves of the Rosy Periwinkle plants. Green synthesis and characterization, such as Ultraviolet Visible Spectrometer (UV-Vis) analysis, Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), and Fourier Transform Infrared Spectroscopy (FTIR), were carried out after the silver nanoparticles have been collected prior coating. As a consequence, the effectiveness is determined based on the conductivity test, and the resulting Ag NPs are then applied to the c-si layer of the solar panel. Additionally, a modelling and experimental analysis are performed in this study to ascertain the suggested framework's ability to measure energy before and after coating panels with Ag NPs. Specifically, the Voltage Current (VI) and Power Voltage (PV) characteristics were validated in this study for analyzing the effectiveness and the obtained results revealed that the coating of green synthesized Ag NPs generated 2 % more power than the reference solar panel under the same conditions. Further, hardware testing and simulation were both used to confirm the outcomes and effectiveness of the suggested method. The open circuit voltage (Voc), short circuit current (Isc), maximum peak voltage (Vmp), maximum peak current (Imp), and efficiency are taken into account when assessing how well the suggested system performs at tracking. Moreover, the current density characteristics were evaluated with respect to various irradiation conditions for both the typical solar as well as Ag NPs coated panels. From the observation, it is noted that the efficiency level of coated panel was improved up to 19.20 %, 18 %, and 17.20 % for the irradiations of 200 W/m2, 500 W/m2, and 1000 W/m2 respectively.

Extraction, characterization and biological activity of Galactomannan rich endosperm of Borassus flabellifer (Linn.) suitable for biofabrication of tissue scaffolds.

The study deals with the isolation, purification and characterization of galactomannan from the endosperm of Borassus labellifer (Linn.) to be used for biomaterial fabrication in tissue engineering (TE) applications. The isolated Borassus flabellifer (Linn.) galactomannan (BFG) through a sequential aqueous dissolution, centrifugation and ethanol precipitation presented a total yield of 19.77 ± 1.05 % (w/w) with advantageous compositional and functional properties. BFG was found to have mannose to galactose (M/G) ratio of 1.4:1. The molecular weight of BFG was found to be 4.9 × 105 g/mol and the molecular structure analysis by FTIR and NMR spectroscopy revealed the presence of α-linked, d-galactopyranose units and ß-linked, D-mannopyranose units. Further characterization by rheometer confirmed the non-Newtonian and pseudo-plastic behavior of different BFG concentrations and structural analysis by XRD and SEM confirmed the amorphous nature of BFG with the presence of pores and cervices on the rough surface. Finally, the favorable biological activity demonstrated in response to fibroblast cells against different BFG concentrations substantiates its relevance to be used in biofabrication of tissue scaffolds.

Effect of laser surface treatment on shear bond strength between polyetheretherketone and heat-activated polymethylmethacrylate resin.

PURPOSE: To compare the shear bond strength between polyetheretherketone (PEEK) and heat activated polymethylmethacrylate (PMMA) resin after laser treatment. MATERIALS AND METHODS: A total of 128 PEEK discs were fabricated (10 mm diameter and 2 mm thickness) and allocated into two groups. Group 1 was subjected to surface treatment followed by thermal cycling for 5000 cycles and group 2 was subjected to surface treatment followed by thermal cycling for 10,000 cycles. Each group was further subdivided into four subgroups (n = 16) which were: no surface treatment; primer treatment; acid etching; and laser surface treatment. PEEK was then bonded with PMMA resin using the conventional flasking technique. The shear bond strength was evaluated using a universal testing machine with a crosshead speed of 1 mm/min. Statistical analysis was done using one-way ANOVA for comparing within groups, followed by Tukey HSD test. Student's T-test was done to evaluate between the two groups. RESULTS: In group 1, the highest shear bond strength was exhibited by the laser group (19.08 ± 0.16 MPa) followed by the acid etch group (14.84 ± 0.23 MPa), and the primer group (6.43 ± 0.20 MPa), while the least shear bond strength was observed in the no surface treatment group (4.98 ± 0.34 MPa) which was found to be significant (p < 0.05). In group 2, the highest shear bond strength was observed in the laser group (18.21 ± 0.23 MPa) followed by the acid etch group (13.77 ± 0.48 MPa), and the primer group (6.04 ± 0.11 MPa), while the least shear bond strength was observed in no surface treatment group (4.35 ± 0.21 MPa) which was found to be significant (p < 0.05). CONCLUSION: The shear bond strength between PEEK and PMMA resin was highest for specimens that were surface treated with laser and followed by specimens treated with acid etching, primer application, and without surface treatment, respectively. Increasing thermal cycling from 5000 cycles to 10,000 cycles also reduced the bond strength.

Process optimization for the pretreatment of rice husk with deep eutectic solvent for efficient sugar production.

ABSTRACTDeep eutectic solvent (DES) has been identified as a potential green solvent in biomass processing. In the present investigation, a deep eutectic solvent i.e. choline chloride: urea (ChCl/U) was synthesized and employed to pretreat rice husks. Plackett- Burman response surface methodology was used to optimize the factors which are DES molar ratio, residence time, temperature, and biomass concentration. A total of 11 experimental conditions were evaluated and the highest amount of reducing sugar was obtained when 2 g rice husk was pretreated with 1:2 ChCl/U at 80°C for 6 h i.e. 0.67 ± 0.05 mg/mL. Furthermore, scanning electron microscopy (SEM), Fourier transforms infrared (FTIR), and X-ray diffraction (XRD) studies were used to characterize the structural and compositional changes in which DES demonstrates a great performance in the pretreatment of rice husk by eliminating amorphous lignin and hemicellulose content. Therefore, the facile process used in this study has the potential to be used on a massive scale to produce fermentable sugars and other compounds.

Isolation and characterization of agro-waste biomass sapodilla seeds as reinforcement in potential polymer composite applications.

Fillers or particulate fillers find a growing utilization as reinforcement material in polymer composites due to their ability to enhance the properties of the ensuing composites. The discarded seed in sapodilla fruit is available in abundant and the shell of the seed can be used as a reinforcing filler. The primary goal of this study is to extract and characterize the sapodilla seed shell powder (SSS) physically and chemically in order to assess its potential for reinforcement as a particulate filler in polymer composites. The sapodilla seed shell filler was characterized experimentally by Physio-chemical analysis, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and Energy dispersive X-ray analysis (EDAX). The morphology and the filler size were determined by Scanning electron microscopy (SEM) and Particle size analysis. The thermal degradation behaviour was evaluated by Thermogravimetric analysis (TGA).

Forecasting determinants of recurrence in lung cancer patients exploiting various machine learning models.

Lung cancer recurrence seems to be the most leading cause of death as well as deterioration of lifespan. Proper assessment of the probability of recurrence in early-stage lung cancer is necessary to push up the treatment progress. We therefore employed machine-learning technologies to forecast post-operative recurrence risks using 174 lung cancer patient records. Six classification algorithms logistic regression, SVM, decision tree classification, random forest classification, XGBoost and lightGBM were used to predict the cancer recurrence. The patient samples were divided into training and test group with the split ratio of 3:1 for model generation and the accuracy were validated using k-fold cross-validation method. It is worth noting that the logistic regression model outperformed all the models in both training (Accuracy = 0.82) and test set (Accuracy = 0.79) on k-fold validation. Further, the optimal features (n = 7) identified using the RFE method is certainly helpful to improve the model in a high precision. The imperative risk factors associated with recurrence were identified using three feature selection methods. Importantly, our research showed that age is an important prognostic factor to be considered during the recurrence prediction. Indeed, severe concern on the identified risk factors combined with predictive models assists the physician to reduce the cancer recurrence rate in patients with lung cancer.

Computational biophysics approach towards the discovery of multi-kinase blockers for the management of MAPK pathway dysregulation.

The MAPK pathway is important in human lung cancer and is improperly activated in a substantial proportion through number of ways. Strategies on dual-targeting RAF and MEK are an alternative option to diminish the limitations in this pathway inhibition. Hence, we implemented parallel pharmacophore screening of 11,808 DrugBank compounds against RAF and MEK. ADHRR and DHHRR were modeled as a pharmacophore hypothesis for RAF and MEK respectively. Importantly, these hypotheses resulted an AUC value of > 0.90 with the external data set. As a result of phase screening, glide docking, and prime-MM/GBSA scoring, it is determined that DB08424 and DB08907 have the best chances of acting as multi-kinase inhibitors. The pi-cation interaction with key amino acid residues of both target receptors may responsible for the stronger binding with these kinases. Cumulative 600 ns MD simulation studies validate the binding ability of these compounds. Significantly, the hit compounds resulted higher number of stable conformational state with less atomic movements than the reference compound against both targets. The anti-cancer efficacy of the lead compounds was validated through machine learning-based approaches. These findings suggest that DB08424 and DB08907 might be novel molecules to be explored further experimentally to block the MAPK signaling in lung cancer patients.

Modulation of the structural information in shape-defined heterocyclic strands: the case of a (pyridine-hydrazone)2pyrazine ligand.

Metal ions (Ag+, Cd2+, Eu3+, Sm3+) and protons can, through coordination and protonation, modulate in three specific ways the structural information contained in the pyrazine-based heterocyclic strand L (obtained from 2,5-bis(methylhydrazino)pyrazine and 2 equivalents of 2-pyridinecarboxaldehyde), thus generating two linear rod-like conformations and a bent one. This conformational diversity is associated with a structural one that consists of two diprotonated forms (H2L(PF6)2 and H2L(CF3SO3)2), a polymeric architecture [AgL]n(CF3SO3)n, two rack-like complexes ([Eu2H2L3(CF3SO3)6](PF6)2 and [Sm2H2L3(CF3SO3)6](PF6)2) and a grid-like structure ([Cd4L4](CF3SO3)8).

An In Vitro Platform to Study Reversible Endothelial-to-Mesenchymal Transition.

Endothelial cells can acquire a mesenchymal phenotype in response to external stimuli through both mechanical and biological factors, using a process known as endothelial-to-mesenchymal (EndoMT) transition. EndoMT is characterized by the decrease in endothelial characteristics, increase in mesenchymal markers, and morphological changes. It has been recognized not only during development but also in different pathological conditions including organ/tissue fibrosis in adults. The ability to modulate the EndoMT process could have a therapeutic potential in many fibrotic diseases. An in vitro method is presented here to induce EndoMT with Nω-nitro-L-arginine methyl ester hydrochloride (L-NAME) and angiotensin II (Ang II) followed by a protocol to study the reversibility of EndoMT. Using this method, we furnish evidence that the combination of L-NAME and Ang II can stimulate EndoMT in Human umbilical vascular endothelial cells (HUVECs) and this process can be reversed as observed using endothelial functionality assays. This method may serve as a model to screen and identify potential pharmacological molecules to target and regulate the EndoMT process, with applications in drug discovery for human diseases.

First Report of Thoracic Carcinoma With DEK::AFF2 Rearrangement: A Case Report.

DEK::AFF2 carcinomas of the head and neck region have been recently described and reported to have aggressive clinical behavior but exceptional sensitivity to immunotherapy. We report a case of a 26-year-old female, never smoker, with a 5.2-cm left lower lobe central lung mass, with morphologic features identical to those reported for DEK::AFF2 head and neck carcinomas, including mixed papillary exophytic and invasive components, squamous/basaloid features, and monomorphic cytomorphology. DEK (exon 7)::AFF2 (exon 9) fusion was identified by whole-transcriptome RNA sequencing. This is the first report of thoracic DEK::AFF2 carcinoma, indicating that these tumors are not confined to the head and neck region but can involve both upper and lower respiratory tracts. This entity should be considered in the differential diagnosis of squamous cell carcinomas in never smokers lacking other known oncogenic mutations.

Drug repurposing combined with MM/PBSA based validation strategies towards MEK inhibitors screening.

Emergence of oncogenic mutations in the MAPK pathway gaining more impact in the recent years. Importantly, MEK is a core element of this pathway as it is easy to inhibit and is a gatekeeper of multiple malignancies. Therefore, we performed in-silico strategy to screen repurposed candidate for MEK protein using a library of 11,808 compounds from different clusters in the DrugBank database. Glide docking, Prime-MM/GBSA and QikProp analysis were implemented to retrieve the hits with high precision. The stability of the binding mode and binding affinity of the resultant hit were explored using molecular dynamic simulations and MM/PBSA approach. The results highlight that Nebivolol (DB04861) not only achieved a stable conformation in the MEK binding pocket but also displayed highest binding affinity than the other molecules investigated in our study. Taken together, we hypothesized that Nebivolol is an excellent candidate for the inhibition of MEK in NSCLC patients in future.Communicated by Ramaswamy H. Sarma.

Ethanolic extract of Pyrus pashia buch ham ex. D. Don (Kainth): A bioaccessible source of polyphenols with anti-inflammatory activity in vitro and in vivo.

ETHNOPHARMACOLOGICAL RELEVANCE: Pyrus pashia Buch ham ex. D. Don (Kainth) fruit from the Himalayan region is traditionally consumed by native people in the form of decoctions for various clinical conditions including inflammatory diseases. However, scientific studies on the biofunctional properties of Kainth fruits are still scarce. AIM OF THE STUDY: The study is aimed to investigate the anti-inflammatory effects of Kainth fruit extracts using in vitro and in vivo inflammation models. MATERIAL AND METHODS: Free, esterified and bound fractions from the Kainth ethanolic extracts were prepared for determining the anti-inflammatory effect. The levels of 5-LOX and COX-2 were determined in vitro. The protein levels of cytokines (IL-6, TNF-α & IL-10) were quantitated by ELISA method in lipopolysaccharide-stimulated RAW macrophages. Also, the anti-inflammatory potential of the Kainth fruit extracts was determined using the carrageenan-induced mice paw edema model. The bioaccessibility of Kainth fruit extracts was measured using a simulated in vitro digestion system (salivary, gastric and intestinal). RESULTS: The Kainth fruit extracts were partially purified to yield free, esterified and bound phenolics. Free and bound phenolics of Kainth fruits inhibited 5-Lipoxygenase, Cyclooxygenase-2 activities and pro-inflammatory cytokines (Interleukin-6 and tumour necrosis factor-α) expression in vitro. Also, oral administration of these extracts to the carrageenan-injected mice showed an anti-inflammatory effect by decreasing the pro-inflammatory cytokines and reducing the cellular infiltration in paw tissues. Also, both the extracts showed better bioavailability and bioaccessibility in in vitro and in vivo studies. CONCLUSIONS: The results indicated that free and bound phenolics from Kainth fruits that are rich in catechin, epicatechin, arbutin and chlorogenic acid exhibited anti-inflammatory effects and could potentially be used to treat inflammatory diseases.

Inhibition of multiple SARS-CoV-2 proteins by an antiviral biomolecule, seselin from Aegle marmelos deciphered using molecular docking analysis.

Our earlier experimental and computational report produced evidence on the antiviral nature of the compound seselin purified from the leaf extracts of Aegle marmelos against Bombyx mori Nuclear Polyhedrosis Virus (BmNPV). In the pandemic situation of COVID-19 caused by the SARS-COV-2 virus, an in silico effort to evaluate the potentiality of the seselin was made to test its efficacy against multiple targets of SARS-COV-2 such as spike protein S2, COVID-19 main protease and free enzyme of the SARS-CoV-2 (2019-nCoV) main protease. The ligand seselin showed the best interaction with receptors, spike protein S2, COVID-19 main protease and free enzyme of the SARS-CoV-2 (2019-nCoV) main protease with a binding energy of -6.3 kcal/mol, -6.9 kcal/mol and -6.7 kcal/mol, respectively. Docking analysis with three different receptors identified that all the computationally predicted lowest energy complexes were stabilized by intermolecular hydrogen bonds and stacking interactions. The amino acid residues involved in interactions were ASP1184, GLU1182, ARG1185 and SER943 for spike protein, SER1003, ALA958 and THR961 for COVID-19 main protease, and for SARS-CoV-2 (2019-nCoV) main protease, it was THR111, GLN110 and THR292. The MD simulation and MM/PBSA analysis showed that the compound seselin could effectively bind with the target receptors. The outcome of pharmacokinetic analysis suggested that the compound had favourable drugability properties. The results suggested that the seselin had inhibitory potential over multiple SARS-COV-2 targets and hold a high potential to work effectively as a novel drug for COVID-19 if evaluated in experimental setups in the foreseeable future. Communicated by Ramaswamy H. Sarma.

Kinetic modeling and statistical optimization of submerged production of anti-Parkinson's prodrug L-DOPA by Pseudomonas fluorescens.

L-DOPA, a precursor of dopamine, is the drug of choice for Parkinson's disease, which persists due to decreased levels of dopamine in the brain. Present study emphasis the microbial production of L-DOPA rather than the biotransformation of L-DOPA by L-tyrosine. The production of L-DOPA by bacterial isolates had gained more acceptance due to its more straightforward extraction and downstream processes. Pseudomonas fluorescens was used to produce the L-DOPA in a bioreactor system under submerged condition. The design of experiment-based Taguchi orthogonal array method was adopted for the optimization of production. L-9 orthogonal array using the analysis of mean approach was used to study the effect of different factors viz NaCl, lactose, tryptone, and inducer on the microbial production of L-DOPA. The method mentioned above is less time consuming and does not require any harsh chemicals, proving it to be an eco-friendly process. After optimizing selected factors, i.e., NaCl (1.2 g/l), lactose (1.5 g/l), tryptone (4 g/l), and inducer (0.1 g/l), 16.9 % of enhancement in L-DOPA production with 66.6% of process cost saving was observed. The production of L-DOPA was increased from 3.426 ± 0.08 g/l to 4.123 ± 0.05 g/l after optimization. Subsequently, unstructured kinetic models were adopted to simulate the fermentation kinetics and understand the metabolic process. Fisher' F test and determination coefficients (R2) confirmed that the Velhurst-Pearl logistic equation, Luedeking-Piret equation, and modified Luedeking-Piret equation was best fitted with the biomass production, product formation, and substrate utilization, respectively.

Anaerobic biobutanol production from black strap molasses using Clostridium acetobutylicum MTCC11274: Media engineering and kinetic analysis.

Microbial reduction of black strap molasses (BSM) by Clostridium acetobutylicum MTCC 11,274 was performed for the production of biobutanol. The optimum fermentation conditions were predicted using one factor at a time (OFAT) method. The identification of significant parameters was performed using Plackett-Burman Design (PBD). Furthermore the fermentation conditions were optimized using central composite design (CCD). The kinetics of substrate utilization and product formation were investigated. Initial pH, yeast extract concentration (g/L) and total reducing sugar concentration (g/L) were found as significant parameters affecting butanol production using C. acetobutylicum MTCC11274. The maximum butanol production under optimal condition was 10.27 + 0.82 g/L after 24 h. The waste black strap molasses obtained from sugar industry could be used as promising substrate for the production of next generation biofuel.

Comparison of ultrasound guided pulsed radiofrequency of genicular nerve with local anesthetic and steroid block for management of osteoarthritis knee pain

Background@#To compare ultrasound-guided pulsed radiofrequency (PRF) of the genicular nerve with the genicular nerve block using local anesthetic and steroid for management of osteoarthritis (OA) knee pain. @*Methods@#Thirty patients with OA knee were randomly allocated to receive either ultrasound-guided PRF of the genicular nerve (PRF group) or nerve block with bupivacaine and methylprednisolone acetate (local anesthetic steroid [LAS] group).Verbal numeric rating scale (VNRS) and Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) scores were measured at pre-procedure and 1-, 4-, and 12-weeks post-procedure. @*Results@#VNRS scores decreased significantly (P 0.999). There was also a statistically significant (P < 0.001) improvement in WOMAC scores in both groups at all follow up times. However, there was no intergroup difference in VNRS (P = 0.893) and WOMAC scores (P = 0.983). No complications were reported. @*Conclusions@#Both ultrasound-guided PRF of the genicular nerve and blocks of genicular nerve with local anesthetic and a steroid provided comparable pain relief without any complications. However, PRF of the genicular nerve is a procedure that takes much more time and equipment than the genicular nerve block.

Effect of Zirconia Silica Nanofibers on Flexural Strength of Feldspathic Ceramic - An Experimental Study.

BACKGROUND: Dental ceramics exhibit good optical and esthetic properties due to their translucency. Feldspathic ceramic is the most widely used veneering ceramic with brittleness, which accounts for most of its failure. Hence, this study was done to evaluate and compare the flexural strength of feldspathic ceramic reinforced with zirconia-silica nanofibers in the ratio of 2.5, 5, and 7.5 wt% with conventional feldspathic ceramic. MATERIALS AND METHODS: According to ISO 6872, a master die was prepared from which resin bars were fabricated with 4.0 mm in width × 1.2 mm thickness × 25.0 mm length, Zirconia-silica nanofibers were produced by sol-gel electrospinning go around with calcination and blended with feldspathic ceramic through ball milling method. The samples were prepared with 0, 2.5, 5, 7.5 wt% nanofibers reinforced ceramic. The flexural strength of the samples was evaluated using three-point bending test. RESULTS: The flexural strength values of zirconia-silica nanofibers reinforced ceramic groups were higher than control group. There was a gradual increase in the flexural strength values of felspathic ceramic groups with increase in wt% of nanofibers. CONCLUSION: The flexural strength of feldspathic ceramic samples reinforced with zirconia-silica nanofibers by 5 and 7.5 wt% were statistically significant compared to control, whereas the flexural strength of 2.5 wt% was statistically insignificant compared to the control group.