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This paper presents the mathematical model and control of a voltage source inverter (VSI) connected to an alternating current (AC) microgrid. The VSI considered in this paper is six switches three-phase Pulse Width Modulated (PWM) inverter, whose output active and reactive power is controlled in the dq reference frame. The control strategy presented here is state feedback control with disturbance cancellation. This disturbance signal is either provided by a voltage sensor or estimated using a presented extended high gain observer (EHGO). The control strategy without EHGO requires a current sensor and a voltage sensor, and the control strategy with EHGO requires only a current sensor. The EHGO is saving the requirement of a voltage sensor. The stability analysis of the presented control strategy is showing that the error is ultimately bounded in the presence of disturbance, formed due to Pulse Width Modulated (PWM) inverters. The microgrid is simulated using the SimPowerSystems Toolbox of MATLAB/Simulink. The simulation results are also showing the effectiveness of the proposed control strategy, that the output active and reactive power control is achieved with ultimately bounded errors. The comparison of the proposed control with the PI-based control scheme is also presented, and it is shown that better reference tracking with the desired settling time of “0.04 s” is achieved with the proposed control.

This paper presents the mathematical model and control of the voltage source inverter (VSI) connected to an alternating current (AC) microgrid. The VSI used in this work was a six-switch three-phase PWM inverter, whose output voltages were controlled in a synchronous (dq) reference frame via a sliding mode control strategy. The control strategy required only output voltages; other states of the system were estimated by using a high-gain observer. The power-sharing among multiple inverters was achieved by solving power flow equations of the electrical network. The stability analysis showed that the error was ultimately bound in the case of the real PWM inverter and/or with a nonlinear load in the electrical network. The microgrid was simulated using the SimPowerSystems Toolbox from MATLAB/Simulink. The simulation results show the effectiveness of the proposed control scheme. The output voltage regulation of the inverter and power-sharing was achieved with the ultimately bounded error for the linear load. Later, the nonlinear load was also included in the electrical network and the error was shown to remain ultimately bounded. The output voltage regulation and power-sharing were achieved with the nonlinear load in the system.

This study investigates the genetic basis of retinal diseases in four consanguineous families from Pakistan, focusing on mutations in the CNGA3, CACNA1F , and RPGRIP1 genes that are implicated in retinal dysfunctions such as achromatopsia, congenital stationary night blindness, and retinal dystrophies. We identified pathogenic variants in these genes, including the novel missense mutation c.955T > C; p.Cys319Arg in CNGA3 (Family 1), the frameshift mutation c.1443dupT; p.Ile482Hisfs*6 in CNGA3 (Family 2), the missense mutation c.2254G > A; p.Val752Met in CACNA1F (Family 3), and the frameshift mutation c.2789dupT; p.Pro931Thrfs*3 in RPGRIP1 (Family 4). Clinical features associated with these mutations include nystagmus, photophobia, reduced visual acuity, and color vision deficiency, with some patients progressing to complete blindness. The findings were validated through Sanger sequencing, segregation analysis, and in silico prediction tools. Additionally, molecular dynamics simulations were conducted to assess the impact of the CNGA3 p.Cys319Arg mutation on protein structure, revealing significant alterations in protein conformation and dynamics. These results highlight the significance of CNGA3, CACNA1F , and RPGRIP1 in retinal health and provide valuable insights into the genetic underpinnings of retinal disorders. Our findings contribute to improved genetic counseling, potential targeted therapies, and a deeper understanding of inherited retinal diseases.

Voriconazole (VRC) is a broad-spectrum antifungal agent belonging to BCS class II (biopharmaceutical classification system). Despite many efforts to enhance its solubility, this primary issue still remains challenging for formulation scientists. Transethosomes (TELs) are one of the potential innovative nano-carriers for improving the solubility and permeation of poorly soluble and permeable drugs. We herein report voriconazole-loaded transethosomes (VRCT) fabricated by the cold method and followed by their incorporation into carbopol 940 as a gel. The prepared VRCT were evaluated for % yield, % entrapment efficiency (EE), surface morphology, possible chemical interaction, particle size, zeta potential, and polydispersity index (PDI). The optimized formulation had a particle size of 228.2 nm, a zeta potential of −26.5 mV, and a PDI of 0.45 with enhanced % EE. Rheology, spreadability, extrudability, in vitro release, skin permeation, molecular docking, antifungal, and antileishmanial activity were also assessed for VRCT and VRC loaded transethosomal gel (VTEG). Ex-vivo permeation using rat skin depicted a transdermal flux of 22.8 µg/cm2/h with enhanced efficiency up to 4-fold. A two-fold reduction in inhibitory as well as fungicidal concentration was observed against various fungal strains by VRCT and VTEG besides similar results against L-donovani. The development of transethosomal formulation can serve as an efficient drug delivery system through a topical route with enhanced efficacy and better patient compliance.

The rapidly growing global burden of cancer poses a major challenge to public health and demands a robust approach to access promising anticancer therapeutics. In parallel, nanotechnology approaches with various pharmacological properties offer efficacious clinical outcomes. The use of new artificial variants of nanosponges (NS) as a transporter of chemotherapeutic drugs to target cells has emerged as a very promising tool. Therefore, in this research, ethylcellulose (EC) NS were prepared using the ultrasonication assisted-emulsion solvent evaporation technique. Withaferin-A (WFA), an active ingredient in Withania somnifera, has been implanted into the nanospongic framework with enhanced anticancer properties. Inside the polymeric structure, WFA was efficiently entrapped (85 ± 11%). The drug (WFA) was found to be stable within polymeric nanosponges, as demonstrated by Fourier transform infrared (FTIR) spectroscopy and differential scanning calorimetry (DSC) studies. The WFA-NS had a diameter of 117 ± 4 nm and zeta potential of −39.02 ± 5.71 mV with a polydispersity index (PDI) of 0.419 ± 0.073. In addition, scanning electron microscopy (SEM) revealed the porous surface texture of WFA-NS. In vitro anticancer activity (SRB assay) results showed that WFA–NS exhibited almost twice the anticancer efficacy against MCF-7 cells (IC50 = 1.57 ± 0.091 µM), as quantified by flow cytometry and comet tests. Moreover, fluorescence microscopy with DAPI staining and analysis of DNA fragmentation revealed apoptosis as a mechanism of cancer cell death. The anticancer activity of WFA-NS was further determined in vivo and results were compared to cisplatin. The anticancer activity of WFA-NS was further investigated in vivo, and the data were consistent to those obtained with cisplatin. At Day 10, WFA-NS (10 mg/kg) significantly reduced tumour volume to 72 ± 6%, which was comparable to cisplatin (10 mg/kg), which reduced tumour volume to 78 ± 8%. Finally, the outcomes of molecular modeling (in silico) also suggested that WFA established a stable connection with nanosponges, generating persistent hydrophobic contacts (polar and nonpolar) and helping with the attractive delayed-release features of the formulation. Collectively, all the findings support the use of WFA in nanosponges as a prototype for cancer treatment, and opened up new avenues for increasing the efficacy of natural product-derived medications.

Measles is a highly contagious illness that can spread throughout a population based on the number of susceptible or infected individuals as well as their social dynamics within the society. The measles epidemic is thought to be controlled for the suffering population using the susceptible-exposed-infectious-recovered (SEIR) epidemic model, which depicts the direct transmission of infectious diseases. To better explain the measles epidemics, we provided a nonlinear time fractional model of the disease. The solution of SEIR is obtained by using the Caputo fractional derivative operator of order μ ∈ ( 0 , 1 ] . The Homotopy perturbation transform method (HPTM) and Yang transform decomposition methodology (YTDM) have been employed to obtain the numerical solution of the time fractional model. Obtaining numerical findings in the form of a fast-convergent series significantly improves the proposed techniques accuracy. The behaviour of the approximate series solution for several fractional orders is shown graphically which are derived through Maple. A graphic representation of the behaviours of susceptible, exposed, infected, and recovered individuals are shown at different fractional order values. Figures that depict the behaviour of the projected model are used to illustrate the developed results. Finally, the present work may help you predict the behaviour of the real-world models in the wild class with respect to the model parameters. It was found that the majority of patients who receive therapy join the recovered class when various epidemiological classes were simulated at the effect of fractional parameter μ . These approaches shows to be one of the most efficient methods to solve epidemic models and control infectious diseases.

Type 2 diabetes mellitus has been a major health issue with increasing morbidity and mortality due to macrovascular and microvascular complications. The urgent need for improved methods to control hyperglycemic complications reiterates the development of innovative preventive and therapeutic treatment strategies. In this perspective, xanthone compounds in the pericarp of the mangosteen fruit, especially α-mangostin (MGN), have been recognized to restore damaged pancreatic β-cells for optimal insulin release. Therefore, taking advantage of the robust use of nanotechnology for targeted drug delivery, we herein report the preparation of MGN loaded nanosponges for anti-diabetic therapeutic applications. The nanosponges were prepared by quasi-emulsion solvent evaporation method. Physico-chemical characterization of formulated nanosponges with satisfactory outcomes was performed with Fourier transform infra-red (FTIR) spectroscopy, differential scanning calorimetry (DSC), and scanning electron microscopy (SEM). Zeta potential, hydrodynamic diameter, entrapment efficiency, drug release properties, and stability studies at stress conditions were also tested. Molecular docking analysis revealed significant interactions of α-glucosidase and MGN in a protein-ligand complex. The maximum inhibition by nanosponges against α-glucosidase was observed to be 0.9352 ± 0.0856 µM, 3.11-fold higher than acarbose. In vivo studies were conducted on diabetic rats and plasma glucose levels were estimated by HPLC. Collectively, our findings suggest that MGN-loaded nanosponges may be beneficial in the treatment of diabetes since they prolong the antidiabetic response in plasma and improve patient compliance by slowly releasing MGN and requiring less frequent doses, respectively.

Clopidogrel, an antiplatelet drug, is frequently prescribed to patients diagnosed with ischemic diseases such as those suffering from acute coronary syndromes or ischemic stroke. Despite the drug being effective in majority of the patients, some still experience ischemic events early in the treatment which might be due to poor platelet inhibition. This study aims to investigate the association of cytochrome P450 2C19 ( CYP2C19 ) loss-of-function polymorphisms, haplotypes as well as a wide range of clinical and demographic variables with platelet aggregation phenotypes to clopidogrel in a Pakistani cohort. The study comprised of a total of 120 patients diagnosed with cardiovascular diseases and were treated with clopidogrel. Antiplatelet response to clopidogrel was monitored by Helena AggRAM (HL-2-1785P) and patients with maximal platelet aggregation more than 50% were categorized as low responders and those with less than 50% as high responders. Our results show that 56.6% of patients were homozygous for the CYP2C19 wild-type allele, 38.3% of patients possessed one copy of the CYP2C19*2 allele and 5% of patients possessed both CYP2C19*2 alleles. No CYP2C19*3 allele was found in our patient cohort. There was no statistically significant difference between the high and low responder groups to clopidogrel in terms of extensive, intermediate and poor metabolizer genotypes. However, haplotype (H1), leukocyte count, random blood glucose, and history of diabetes mellitus was associated with the antiplatelet response to clopidogrel. The prevalence of clopidogrel resistance in our population was in line with that reported for other regional and global populations.

Solid lipid nanoparticles (SLNs) have the advantages of a cell-specific delivery and sustained release of hydrophobic drugs that can be exploited against infectious diseases. The topical delivery of hydrophobic drugs needs pharmaceutical strategies to enhance drug permeation, which is a challenge faced by conventional formulations containing a drug suspended in gel, creams or ointments. We report the fabrication and optimization of SLNs with sulconazole (SCZ) as a model hydrophobic drug and then a formulation of an SLN-based topical gel against fungal infections. The SLNs were optimized through excipients of glyceryl monostearate and Phospholipon® 90 H as lipids and tween 20 as a surfactant for its size, drug entrapment and sustained release and resistance against aggregation. The SCZ-SLNs were physically characterized for their particle size (89.81 ± 2.64), polydispersity index (0.311 ± 0.07), zeta potential (−26.98 ± 1.19) and encapsulation efficiency (86.52 ± 0.53). The SCZ-SLNs showed sustained release of 85.29% drug at the 12 h timepoint. The TEM results demonstrated spherical morphology, while DSC, XRD and FTIR showed the compatibility of the drug inside SLNs. SCZ-SLNs were incorporated into a gel using carbopol and were further optimized for their rheological behavior, pH, homogeneity and spreadability on the skin. The antifungal activity against Candida albicans and Trichophyton rubrum was increased in comparison to a SCZ carbopol-based gel. In vivo antifungal activity in rabbits presented faster healing of skin fungal infections. The histopathological examination of the treated skin from rabbits presented restoration of the dermal architecture. In summary, the approach of formulating SLNs into a topical gel presented an advantageous drug delivery system against mycosis.

Three-dimensional printing (3DP), known as additive layer manufacturing (ALM), is a manufacturing process in which a three-dimensional structure is constructed by successive addition of deposited layers. Fused Deposition Modeling (FDM) has evolved as the most frequently utilized ALM process because of its cost-effectiveness and ease of operation. Nevertheless, layer adhesion, delamination, and quality of the finished product remain issues associated with the FDM process parameters. These issues need to be addressed in order to satisfy the requirements commonly imposed by the conventional manufacturing industry. This work is focused on the optimization of the FDM process and post-process parameters for Polylactic acid (PLA) samples in an effort to maximize their tensile strength. Infill density and pattern type, layer height, and print temperature are the process parameters, while annealing temperature is the post-process parameter considered for the investigation. Analysis based on the Taguchi L18 orthogonal array shows that the gyroid infill pattern and annealing cycle at 90 °C results in a maximum ultimate tensile strength (UTM) of 37.15 MPa. Furthermore, the regression model developed for the five variables under study was able to predict the UTS with an accuracy of more than 96%.