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Controlled-release microparticles offer a promising avenue for enhancing patient compliance and minimizing dosage frequency. In this study, we aimed to design controlled-release microparticles of Glipizide utilizing Eudragit S100 and Methocel K 100 M polymers as controlling agents. The microparticles were fabricated through a simple solvent evaporation method, employing various drug-to-polymer ratios to formulate different controlled-release batches labeled as F1 to F5. Evaluation of the microparticles encompassed a range of parameters including flow properties, particle size, morphology, percentage yield, entrapment efficiencies, percent drug loading, and dissolution studies. Additionally, various kinetic models were employed to elucidate the drug release mechanism. Furthermore, difference and similarity factors were utilized to compare the dissolution profiles of the tested formulations with a reference formulation. The compressibility index and angle of repose indicated favorable flow properties of the prepared microparticles, with values falling within the range of 8 to 10 and 25 to 29, respectively. The particle size distribution of the microparticles ranged from 95.3 to 126 μm. Encouragingly, the microparticles exhibited high percent yield (ranging from 66 to 77%), entrapment efficiency (80 to 96%), and percent drug loading (46 to 54%). All formulated batches demonstrated controlled drug release profiles extending up to 12 hours, with glipizide release following an anomalous non-Fickian diffusion pattern. However, the drug release profiles of the reference formulation and various polymeric microparticles did not meet the acceptable limits of difference and similarity factors. In-vivo studies revealed sustained hypoglycemic effects over a 12-hour period, indicating the efficacy of the controlled-release microparticles. Overall, our findings suggest the successful utilization of polymeric materials in designing controlled-release microparticles, thereby reducing dosage frequency and potentially improving patient compliance.

To improve the solubility of atorvastatin and overcome the stability issues of liquid nanoemulsion, the current study aimed to synthesize solidified SNEDDS particles with aerodynamic diameter of ≤ 3 μm. The simple and chitosan-decorated liquid SNEDDS were dried by spray drying method and evaluated for their physicochemical properties, release characteristics and aerodynamic performance. A single dose pharmacokinetic study was performed in rabbits to establish the therapeutic performance of solidified nanoemulsion with respect to LIPITOR. The liquid SNEDDS were efficiently dried with pectin (1% w/w). The chitosan decorated solidified SNEDDS (SF10) have small particle size (2.02 μm), higher tapped density (0.733 g/cm 3 ) and smooth surface as compared to uncoated solidified SNEDDS (SF8). The chitosan coated SNEDDS had higher drug content and significantly lower roughness than uncoated SNEDDS (student t-test; p  ≤ 0.01). The uncoated SNEDDS exhibited significantly higher burst drug release as compared to the chitosan coated SNEDDS due to the porous structure, amorphous nature and small size of its associated nanoemulsion. The solidified nanoemulsion had relatively lower MMAD (1.0 to 1.5 μm) that supports higher FPF values of 45–54% for the uncoated SNEDDS and chitosan coated SNEDDS, respectively. The pharmacokinetic study revealed that the solidified SNEDDS are superior with respect to its bioavailability being 1.5 times higher than LIPITOR.

Purpose Floating drug delivery systems present one of the effective strategies to treat gastric disorders including peptic ulcer. To improve the retention of Clarithromycin at the target site of H. pylori induced ulcer, the current study undertakes development of gastro-retentive drug delivery systems based on muco-adhsesion (type I) and floating (type II) properties of the beads. Method Two different types of beads were prepared by ionic gelation method. The type-I beads comprised of chitosan and tripolyphosphate (TPP) while the type-II beads contain chitosan and xanthan gum to promote floating properties. The prepared beads were analyzed for size, morphology, circularity, roughness, drug content and association efficiency. The drug release profile of the beads was determined by USP Type II method. The floating capabilities of the beads were confirmed by using floating lag and total floating time. The swelling of the beads was evaluated using water bath at an agitation speed of 100 revolutions per minute. The in-vitro evaluation of muco-adhesion was determined using the fresh chicken eggshell membranes. Results The beads ranged in size from 1.9 to 3.0 mm. The size of type-II beads (F3 and F4) was significantly higher than type-I (F1 and F2) beads. The beads of formulations containing higher concentration of polymer (F1 and F2) were more circular while the roughness of type-II beads was significantly higher than type-I ( p  ≤ 0.05). The association efficiency ranged from 92.67 ± 5.42 to 95.97 ± 2.28% for type-I and type-II beads respectively. The type-I beads have shown sustained drug release in comparison to type-II beads due to compact nature. The type-II beads float within half a minute with total floating time of about 10 h. The type-II beads achieved significantly higher swelling than type-I beads, while the mucoadhesive property of F1 and F2 was significantly higher due to the presence of chitosan. Conclusion The study reports two types of beads that can be effectively utilized in H-pylori induced peptic ulcer using improved gastric drug retention via mucoadhesive (type-I) and floating (type-II) characteristics. Graphical Abstract

Global warming promotes soil calcification and salinization processes. As a result, soil phosphorus (P) is becoming deficient in arid and semiarid areas throughout the world. In this pot study, we evaluated the potential of phosphate-solubilizing bacteria (PSB) for enhancing the growth and P uptake in maize under varying levels of lime (4.8%, 10%, 15% and 20%) and additional P supplements (farmyard manure, poultry manure, single super phosphate and rock phosphate) added at the rate of 45 mg P2O5 kg−1. Inoculation and application of P as organic manures (Poultry and farm yard manures) improved maize growth and P uptake compared to the control and soils with P applied from mineral sources. Liming adversely affected crop growth, but the use of PSB and organic manure significantly neutralized this harmful effect. Mineral P sources combined with PSB were as effective as the organic sources alone. Furthermore, while single supper phosphate showed better results than Rock phosphate, the latter performed comparably upon PSB inoculation. Thus, PSB plus P application as organic manures is an eco-friendly option to improve crop growth and P nutrition in a calcareous soil under changing climate.

The single pass transmembrane protein CD33 is enriched in phagocytic and hematopoietic cell types, such as monocytes. CD33 is thought to be associated with immune cell function, susceptibility to Alzheimer’s disease, and rare leukemias. Antagonism or genetic ablation of CD33 has been proposed to treat Alzheimer’s disease, hematological cancers, and as a selection mechanism for enriching genetically altered blood cells. To understand the impact of chronic CD33 loss or ablation, we describe individuals who we confirmed to be missing CD33 due to germline loss of function variants. Through PheWAS-based approaches using existing whole exome biobanks and bespoke phenotyping using recall-by-genotype (RBG) studies, we show that CD33 loss of function alters circulating white blood cell counts and distributions, albeit mildly and with no overt clinical pathology. These findings indicate that chronic CD33 antagonism/ablation is likely to be safe in humans.

Carbon fiber–reinforced polymers (CFRPs) are vulnerable to damage locally through machining operations due to an applied cutting force and high-temperature generation. Though traditional lubri-cooling medium will reduce the heat-generated damage of CFRPs, the use of synthetic fluids, however, significantly affects the environment and public health equally. Therefore, this paper aims to explore the milling performance of CFRPs in sustainable lubri-cooling mediums, i.e., dry, minimal lubrication (MQL), cryogenic-liquid nitrogen (N2 liquid ), and carbon dioxide (CO2 ice ). Furthermore, the correct choice of process parameters and lubri-cooling environments influences the cutting mechanism in any metal cutting operations. Accordingly, response surface methodology (RSM) is used to create a relationship between responses to machining inputs. In addition, two evolutionary techniques named Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Particle Swarm Optimization (PSO) were used to execute parametric optimization. Eventually, the performances of the adopted approaches are compared in this manuscript, which reveals the prediction made by NSGA-II and PSO is quite consistent with the experimental results. However, in view of convergence characteristics and computational time, the PSO is shown to surpass the NSGA-II approach. Moreover, empirical cumulative distribution–based data analysis indicates that all responses are good compatible with the function of the normal distribution. At the 95% confidence level, the established ANOVA models were found to be substantial. Furthermore, lubri-cooling medium was the most critical factor affecting the response parameters with a 49% contribution in minimizing F r , 46% contribution in decreasing V B , 38.89% contribution in R a , and 50.21% contribution in reducing the T value.

The focus of this research paper is on the application of water based MgO nanofluids for thermal management of a car radiator. Nanofluids of different volumetric concentrations (i.e. 0.06%, 0.09% and 0.12%) were prepared and then experimentally tested for their heat transfer performance in a car radiator. All concentrations showed enhancement in heat transfer compared to the pure base fluid. A peak heat transfer enhancement of 31% was obtained at 0.12 % volumetric concentration of MgO in basefluid. The fluid flow rate was kept in a range of 8-16 liter per minute. Lower flow rates resulted in greater heat transfer rates as compared to heat transfer rates at higher flow rates for the same volumetric concentration. Heat transfer rates were found weakly dependent on the inlet fluid temperature. An increase of 8?C in inlet temperature showed only a 6% increase in heat transfer rate. nema

Skin Cancer is an extensive and possibly dangerous disorder that requires early detection for effective treatment. Add specific global statistics on skin cancer prevalence and mortality to emphasize the importance of early detection. Example: “Skin cancer accounts for 1 in 5 diagnosed cancers globally, with melanoma causing over 60,000 deaths annually. Manual skin cancer screening is both time-intensive and expensive. Deep learning (DL) techniques have shown exceptional performance in various applications and have been applied to systematize skin cancer diagnosis. However, training DL models for skin cancer diagnosis is challenging due to limited available data and the risk of overfitting. Traditionally approaches have High computational costs, a lack of interpretability, deal with numerous hyperparameters and spatial variation have always been problems with machine learning (ML) and DL. An innovative method called adaptive learning has been developed to overcome these problems. In this research, we advise an intelligent computer-aided system for automatic skin cancer diagnosis using a two-stage transfer learning approach and Pre-trained Convolutional Neural Networks (CNNs). CNNs are well-suited for learning hierarchical features from images. Annotated skin cancer photographs are utilized to detect ROIs and reset the initial layer of the pre-trained CNN. The lower-level layers learn about the characteristics and patterns of lesions and unaffected areas by fine-tuning the model. To capture high-level, global features specific to skin cancer, we replace the fully connected (FC) layers, responsible for encoding such features, with a new FC layer based on principal component analysis (PCA). This unsupervised technique enables the mining of discriminative features from the skin cancer images, effectively mitigating overfitting concerns and letting the model adjust structural features of skin cancer images, facilitating effective detection of skin cancer features. The system shows great potential in facilitating the initial screening of skin cancer patients, empowering healthcare professionals to make timely decisions regarding patient referrals to dermatologists or specialists for further diagnosis and appropriate treatment. Our advanced adaptive fine-tuned CNN approach for automatic skin cancer diagnosis offers a valuable tool for efficient and accurate early detection. By leveraging DL and transfer learning techniques, the system has the possible to transform skin cancer diagnosis and improve patient outcomes.