Hasil untuk "Pharmacy and materia medica"

Fábio Köpp, César H. Lenzi, César V. Flores et al.

In this work, we explore how astronomical observations (specifically measurements of masses, radii, and tidal deformabilities) can constrain the presence of quark matter inside neutron stars, namely the phase transition from nuclear matter to deconfined quark matter. Our approach employs Bayesian analysis to study this phenomenon. Hadronic matter is modeled using the relativistic mean-field (RMF) approximation, for which we have selected two parameter sets: \(NL3^{*}ωρ\), representing hadronic matter with nucleons only, and $EL3ωρ$ with nucleons only and $EL3ωρY$, which includes hyperons. On the other hand deconfined quark matter is modeled using the vector-MIT bag model. For our purpose, the phase transition is implemented using the Maxwell construction. Bayesian inference is performed by tuning three parameters: the bag constant (i.e. $B^{1/4}$), the vector coupling constant \(\left(G_{v}\right)\), and the Dirac sea contribution ($b_{4}$). We found that a phase transition could exist at densities below \(2.0\,n_{0}\) for both the $EL3ωρ- EL3ωρY $ and $NL3^{*}ωρ$ parametrizations. As a consequence, our results also indicate that a hybrid neutron star could have a large quark core that comprises more than \(80\%\) of its size.

Pakwan Chanprakhon, Michael F. Reid, and Jon-Paul R. Wells

We report on the synthesis and spectroscopic characterization of Sm$^{3+}$-doped K$_2$YF$_5$ microparticles. The particles were synthesized via the hydrothermal technique, yielding a particle size of approximately 20 $μ$m in length. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses confirmed their orthorhombic crystal structure. A combination of absorption and laser excited fluorescence performed on samples cooled to 10~K, allow for the determination of {56} experimental crystal-field levels. A parametrised crystal-field analysis for Sm$^{3+}$ in the C$_{\rm s}$ point group symmetry centres of K$_2$YF$_5$ yields good approximation to the data.

Yolanda Castellote-Caballero, Ana Beltrán-Arranz, Agustín Aibar-Almazán et al.

<b>Background/Objectives:</b> A mango (<i>Mangifera indica</i>) leaf extract (Zynamite^®), rich in the polyphenol mangiferin, has been demonstrated to modulate brain activity, boost cognitive function, and reduce mental fatigue. Research evidence supports that improving the solubility of this extract could significantly enhance its efficacy as an active ingredient. This study examined the effects of a soluble version of Zynamite^®, Zynamite^® S (Zyn-S), on cognitive function and mood in young adults at low doses. <b>Methods:</b> A total of 119 university students were enrolled in the study. Participants were randomly assigned to receive either 100 mg, 150 mg, or placebo in a double-blind crossover design. Short- and long-term memory were evaluated using the Rey Auditory Verbal Learning Test (RAVLT), executive functions with the Trail Making Test (TMT), processing speed with the Digit Symbol Substitution Test (DSST), and selective attention with the Stroop Color and Word Test. Additionally, mood was assessed using the Spanish short version of the Profile of Mood States (POMS). All these assessments were conducted before taking the product and at 30 min, 3 h, and 5 h post-intake. <b>Results:</b> The results demonstrated that participants who received Zynamite^® S experienced significant improvements in reduced tension, depression, and confusion, suggesting an enhancement in mental clarity and overall emotional well-being. Both interventions also improved processing speed and cognitive flexibility. However, no significant differences were observed in short- and long-term verbal memory. <b>Conclusions:</b> In summary, these findings support Zynamite^® S as a natural nootropic capable of acutely improving key cognitive functions and emotional balance at low doses in young adults, with sustained efficacy for at least five hours.

Ryo Ishida, Natsuki Yamada, Kana Sato et al.

Abstract Background Pharmacy formulary systems have been established recently in various fields of pharmacotherapies. We evaluated the effectiveness of pharmacy formulary interventions on proton pump inhibitors (PPI) used to prevent drug-induced peptic ulcers in a Japanese tertiary hospital. Methods A retrospective cohort study was conducted in Kurashiki Central Hospital. A pharmacy formulary system of PPIs was implemented on October 1, 2020. Between April 2020 and March 2021, six months before and after the implementation date of the formulary system, inpatients aged ≥ 18 years were included if they newly received drugs (low-dose aspirin, anti-platelets, or non-steroidal anti-inflammatory drugs) recommended for prophylactic PPI use for peptic ulcers within seven days from hospital admission. Eligible patients were divided into two groups based on the implementation date, and changes in PPI prescription patterns were evaluated by interrupted time series analysis, along with the risk of drug-induced peptic ulcers and drug costs. Results In total, 2,449 inpatients were included. The median age of the pre- and post-formulary group was 60 and 58 years, respectively. The proportion of the targeted PPI prescription increased by 8.75% (95% confidence interval (CI); 0.12, 17.38) in level change, without increased risk of drug-induced peptic ulcers (risk difference -0.41%, 95% CI; -1.38, 0.55). The distribution of medication days in the two groups was similar, and $1,000 per 90 patient days was saved on drug costs. Conclusion The formulary system on oral PPIs in a Japanese tertiary hospital contributed to a positive level change in the prescription patterns, without increased risk of drug-induced peptic ulcers. Although slight, the drug costs were saved.

Ping Wang, Chong Chen, Hao Liao et al.

Test of {macroscopic realism} (MR) is key to understanding the foundation of quantum mechanics. Due to the existence of the {non-invasive measurability} loophole and other interpretation loopholes, however, such test remains an open question. Here we propose a general inequality based on high-order correlations of measurements for a loophole-free test of MR at the weak signal limit. Importantly, the inequality is established using the statistics of \textit{raw data} recorded by classical devices, without requiring a specific model for the measurement process, so its violation would falsify MR without the interpretation loophole. The non-invasive measurability loophole is also closed, since the weak signal limit can be verified solely by measurement data (using the relative scaling behaviors of different orders of correlations). We demonstrate that the inequality can be broken by a quantum spin model. The inequality proposed here provides an unambiguous test of the MR principle and is also useful to characterizing {quantum coherence}.

Anna Badura, Łukasz Pałkowski, Alicja Nowaczyk et al.

Artificial neural networks (ANNs) have emerged as a valuable tool in facilitating the design of synthesis and guiding subsequent biological experiments in the systematic exploration for novel antimicrobial agents. In this paper, two multilayer perceptron-type neural networks (MLP) are designed to predict the biological activity of compounds based on their physicochemical properties and structure. This approach was tested against Enterococcus faecalis using a series of 140 imidazole derivatives. The use of quaternary ammonium salts in this research originated from their acknowledged ability to act as antiseptics and disinfectants. Additionally, they were considered promising in addressing various microorganisms, including Gram-positive bacteria. The designed regression model accurately predicted the minimum inhibitory concentration for E. faecalis growth. The coefficient of correlation between the actual values and the network predictions for the training set was R=0.91, for the test set was R=0.91, and for the validation set was R=0.97.Additionally, the classification model successfully categorized the tested compounds as predictively active or inactive against the targeted microorganism (classification accuracy: 92.86%). Sensitivity analyses highlighted specific molecular descriptors derived from the Molecular Properties block, such as log P, refractive index, molecular weight, and atom count, as pivotal factors influencing model construction. In summary, the above-mentioned discoveries emphasize the practicality of Artificial Neural Network models in forecasting the antibacterial effectiveness of quaternary ammonium salts against E. faecalis. The application of ANNs in data analysis allows for efficient optimization and cost reduction by streamlining the compound synthesis process towards achieving the desired properties. By harnessing the computational power of ANNs, researchers can effectively narrow down the pool of potential compounds, thereby expediting the discovery of promising antimicrobial substances.

B Swathika, Bharath Nagareddy, V Vijith et al.

Background: The efficiency and safety of root canal preparation are significantly influenced by the surface topographies of rotary files. Atomic force microscopy (AFM) provides high-resolution imaging that can reveal detailed surface characteristics of these instruments. Materials and Methods: In this study, three types of rotary files (File A, File B, and File C) were used to prepare the root canals of extracted human molar teeth. A total of 30 molar teeth were divided into three groups (n = 10) and prepared using one of the three rotary files. After preparation, the rotary files were analyzed using AFM to measure surface roughness parameters including average roughness (Ra), root mean square roughness (Rq), and maximum peak height (Rp). Statistical analysis was performed using ANOVA and post hoc tests to compare the differences between the groups. Results: The AFM analysis revealed significant differences in the surface topographies of the rotary files. File A exhibited a Ra of 150 nm, a root mean Rq of 180 nm, and a maximum peak height Rp of 300 nm. File B showed an average roughness (Ra) of 200 nm, a root mean Rq of 230 nm, and a maximum peak height (Rp) of 350 nm. File C had an average roughness (Ra) of 170 nm, a root mean Rq of 210 nm, and a maximum Rp of 320 nm. Statistical analysis indicated that File B had significantly higher roughness parameters compared to File A and File C (P < 0.05). Conclusion: The surface topographies of rotary files vary significantly, which may impact their performance in root canal preparation. File B, with the highest roughness parameters, may pose a greater risk of canal wall damage and debris retention. These findings underscore the importance of selecting appropriate rotary files to optimize endodontic treatment outcomes.

Cheryl Grace Pratiwi Rumahorbo, Syafruddin Ilyas, Salomo Hutahaean et al.

This research explores a contemporary approach to managing Oral Squamous Cell Carcinoma (OSCC) by integrating nano-technology into herbal production, combining Bischofia javanica leaves and Phaleria macrocarpa fruits. Benzo[a]pyrene (BaP)-induced OSCC rats were treated with nano herbals from Bischofia javanica leaves, Phaleria macrocarpa fruits, a combination of both, and Vitamin C as a control. Blood and organ analyses were compared with negative and positive controls. BaP induction in OSCC revealed cell transformation into carcinoma, confirmed by Papanicolaou staining. OSCC induction also caused significant changes in Complete Blood Count (CBC) and serum lipid profile. Nano herbals from both plants showed potential in reducing hematological and lipid damage in OSCC, especially in white blood cells, red blood cells, hemoglobin, and platelets. Statistical analysis also indicated that the combination of nano herbals was more effective in reducing (Low-Density Lipoprotein) LDL and total cholesterol levels than uncombined use while increasing (High-Density Lipoprotein) HDL levels comparable to Vitamin C. Liver and kidney functions were also significantly affected by OSCC, with nano herbals showing potential in normalizing albumin levels and positively impacting liver enzymes. In conclusion, both individually and in combination, nano herbals from Bischofia javanica leaves, and Phaleria macrocarpa fruits have the potential to be a promising treatment strategy for OSCC.

Ashwini Bachhav, Prashant L Pingale, Chandrashekhar D Upasani

Background: Transferosomes provide delivery of the drug into systemic circulation via the skin as a topical delivery system. So, this study started with the objective of formulating Etodolac transfersomal gel to enhance its skin permeation. Methodology: A total of nine transferosomes (ET-1 to ET-9) containing lecithin, different grades of span and tween, were successfully prepared using a rotary film evaporator. Results and Discussion: After primary evaluation, results were as particle sizes ranged from 222 to 421 nm, zeta potential shows results from –18.50 to –62.53 mV with PDI values 0.254 to 0.303, and the entrapment efficiency (EE%) of Etodolac in the transferosomes ranged from 54.15% to 80.25%. Additionally, the transfersomes formulations were included in carbopol 940 gels (ETC-1 to ETC-9 and EC-0 without transferosomes) and assessed for various characteristics like color, pH, homogeneity, spreadability, viscosity, and in vitro drug release study. Optimized formulation (ET4 and ETC4) underwent further analysis using SEM, TEM, DSC, FTIR, XRD, ex vivo skin permeation, skin irritation and in vivo studies. The in vivo results were compared. % edema inhibition maximum was observed with optimized transfersomal gel formulation (ETC4) as compared to the marketed formulation and plain Carbopol gel when the study was completed after 8 hrs. Conclusion: After this research, it is suggested that Etodolac Transfersomal gel (ETC4) can be considered as an alternate drug carriers system for topical delivery and it could be used to treat Rheumatoid Arthritis

Andreia Martins, Eva Maia, Isabel Praça

Complementary and alternative medicine are commonly used concomitantly with conventional medications leading to adverse drug reactions and even fatality in some cases. Furthermore, the vast possibility of herb-drug interactions prevents health professionals from remembering or manually searching them in a database. Decision support systems are a powerful tool that can be used to assist clinicians in making diagnostic and therapeutic decisions in patient care. Therefore, an original and hybrid decision support system was designed to identify herb-drug interactions, applying artificial intelligence techniques to identify new possible interactions. Different machine learning models will be used to strengthen the typical rules engine used in these cases. Thus, using the proposed system, the pharmacy community, people's first line of contact within the Healthcare System, will be able to make better and more accurate therapeutic decisions and mitigate possible adverse events.

Salah Ghamizi, Maxime Cordy, Yuejun Guo et al.

Much research on Machine Learning testing relies on empirical studies that evaluate and show their potential. However, in this context empirical results are sensitive to a number of parameters that can adversely impact the results of the experiments and potentially lead to wrong conclusions (Type I errors, i.e., incorrectly rejecting the Null Hypothesis). To this end, we survey the related literature and identify 10 commonly adopted empirical evaluation hazards that may significantly impact experimental results. We then perform a sensitivity analysis on 30 influential studies that were published in top-tier SE venues, against our hazard set and demonstrate their criticality. Our findings indicate that all 10 hazards we identify have the potential to invalidate experimental findings, such as those made by the related literature, and should be handled properly. Going a step further, we propose a point set of 10 good empirical practices that has the potential to mitigate the impact of the hazards. We believe our work forms the first step towards raising awareness of the common pitfalls and good practices within the software engineering community and hopefully contribute towards setting particular expectations for empirical research in the field of deep learning testing.

Yanis Labrak, Adrien Bazoge, Richard Dufour et al.

This paper introduces FrenchMedMCQA, the first publicly available Multiple-Choice Question Answering (MCQA) dataset in French for medical domain. It is composed of 3,105 questions taken from real exams of the French medical specialization diploma in pharmacy, mixing single and multiple answers. Each instance of the dataset contains an identifier, a question, five possible answers and their manual correction(s). We also propose first baseline models to automatically process this MCQA task in order to report on the current performances and to highlight the difficulty of the task. A detailed analysis of the results showed that it is necessary to have representations adapted to the medical domain or to the MCQA task: in our case, English specialized models yielded better results than generic French ones, even though FrenchMedMCQA is in French. Corpus, models and tools are available online.

Nikola Nedeljković, Miloš Nikolić, Petar Čanović et al.

The objective of this study was to synthesize seven novel thiourea derivatives of naproxen (<b>8</b>–<b>14</b>), examine the anti-inflammatory activity of the newly synthesized compounds, investigate the cytotoxic potential of both sets of synthesized compounds (<b>1</b>–<b>7</b> and <b>8</b>–<b>14</b>), and select the most promising anti-inflammatory and antitumor drug candidates. The results of the in vivo anti-inflammatory study clearly showed that compounds <b>8</b> and <b>9</b> were capable of decreasing paw edema, as evident from a high percentage of inhibition (44.83% and 49.29%, respectively). In addition, the results of in vitro enzyme inhibition assays demonstrated that neither of the newly synthesized compounds reached 50% inhibition of 5-LOX at concentrations lower than 100 µM. In terms of antitumor potential, derivatives <b>3</b> and <b>8</b> exhibited strong cytotoxic effects on the HeLa cell line, suggesting the involvement of the extrinsic pathway of apoptosis. According to the overall results obtained for both sets of synthesized molecules, derivatives <b>4</b> and <b>8</b> can be underlined as molecules with the strongest anti-inflammatory activity, while derivatives <b>3</b> and <b>8</b> are the most promising cytotoxic agents.

Peiliang Shen, Yuanyuan Jia, Weijia Zhou et al.

Hepatic stellate cells (HSCs) represent a significant component of hepatocellular carcinoma (HCC) microenvironments which play a critical role in tumor progression and drug resistance. Tumor-on-a-chip technology has provided a powerful in vitro platform to investigate the crosstalk between activated HSCs and HCC cells by mimicking physiological architecture with precise spatiotemporal control. Here we developed a tri-cell culture microfluidic chip to evaluate the impact of HSCs on HCC progression. On-chip analysis revealed activated HSCs contributed to endothelial invasion, HCC drug resistance and natural killer (NK) cell exhaustion. Cytokine array and RNA sequencing analysis were combined to indicate the iron-binding protein LIPOCALIN-2 (LCN-2) as a key factor in remodeling tumor microenvironments in the HCC-on-a-chip. LCN-2 targeted therapy demonstrated robust anti-tumor effects both in vitro 3D biomimetic chip and in vivo mouse model, including angiogenesis inhibition, sorafenib sensitivity promotion and NK-cell cytotoxicity enhancement. Taken together, the microfluidic platform exhibited obvious advantages in mimicking functional characteristics of tumor microenvironments and developing targeted therapies.

Hongbin Lai, Jiaqi Li, Xiaoxing Kou et al.

Extracellular vesicles (EVs) are lipid bound particles derived from their original cells, which play critical roles in intercellular communication through their cargoes, including protein, lipids, and nucleic acids. According to their biogenesis and release pathway, EVs can be divided into three categories: apoptotic vesicles (ApoVs), microvesicles (MVs), and small EVs (sEVs). Recently, the role of EVs in oral disease has received close attention. In this review, the main characteristics of EVs are described, including their classification, biogenesis, biomarkers, and components. Moreover, the therapeutic mechanism of EVs in tissue regeneration is discussed. We further summarize the current status of EVs in pulp/periodontal tissue regeneration and discuss the potential mechanisms. The therapeutic potential of EVs in pulp and periodontal regeneration might involve the promotion of tissue regeneration and immunomodulatory capabilities. Furthermore, we highlight the current challenges in the translational use of EVs. This review would provide valuable insights into the potential therapeutic strategies of EVs in dental pulp and periodontal regeneration.

Jonathan C Balloch, Julia Kim, and Jessica L Inman et al.

The exploration--exploitation trade-off in reinforcement learning (RL) is a well-known and much-studied problem that balances greedy action selection with novel experience, and the study of exploration methods is usually only considered in the context of learning the optimal policy for a single learning task. However, in the context of online task transfer, where there is a change to the task during online operation, we hypothesize that exploration strategies that anticipate the need to adapt to future tasks can have a pronounced impact on the efficiency of transfer. As such, we re-examine the exploration--exploitation trade-off in the context of transfer learning. In this work, we review reinforcement learning exploration methods, define a taxonomy with which to organize them, analyze these methods' differences in the context of task transfer, and suggest avenues for future investigation.

Linying Li, Chanhwa Lee, Daniela F. Cruz et al.

Controlled drug delivery systems can provide sustained release profiles, favorable pharmacokinetics, and improved patient adherence. Here, a reservoir-style implant comprising a biodegradable polymer, poly(ε-caprolactone) (PCL), was developed to deliver drugs subcutaneously. This work addresses a key challenge when designing these implantable drug delivery systems, namely the accurate prediction of drug release profiles when using different formulations or form factors of the implant. The ability to model and predict the release behavior of drugs from an implant based on their physicochemical properties enables rational design and optimization without extensive and laborious in vitro testing. By leveraging experimental observations, we propose a mathematical model that predicts the empirical parameters describing the drug diffusion and partitioning processes based on the physicochemical properties of the drug. We demonstrate that the model enables an adequate fit predicting empirical parameters close to experimental values for various drugs. The model was further used to predict the release performance of new drug formulations from the implant, which aligned with experimental results for implants exhibiting zero-order release kinetics. Thus, the proposed empirical models provide useful tools to inform the implant design to achieve a target release profile.

Neneng Siti Silfi Ambarwati, Mari Okatini Armandari, Wahyu Widayat et al.

Tomatoes (Solanum lycopersicum Mill.), a common vegetable in Indonesia, contain high levels of lycopene, which is good for the body. This research further investigates the activity of polar and nonpolar fractions of tomatoes as elastase and tyrosinase inhibitory, and cytotoxic agents. The extraction procedure used is maceration, fractionation through liquid-liquid fractionation, purification of phytochemical substances is achieved through the application of thin layer chromatography. Elastase and tyrosinase inhibitory activity was analyzed using spectrophotometry and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide cytotoxic assay. The result showed that the extract yield was 0.004%. The percentage of polar fraction from the extract was 2.58%, while the nonpolar fraction was 0.69%. The elastase inhibitory activity of polar and nonpolar fractions of tomato extract is 87.21% ± 7.57% and 73.12% ± 7.44%, respectively, The elastase inhibitory activity of polar and nonpolar fractions of tomato extract is 87.21% ± 7.57% and 73.12% ± 7.44%, respectively. The fractions had higher the anti-elastase activity than the positive control quercetin (65.97% ± 3.00%). The tyrosinase inhibitory activity of polar and nonpolar fractions of tomato extract is 23.71% ± 7.91% and 41.16% ± 5.41% (kojic acid as standard is 65.07% ± 0.86%), respectively. The IC50 of the cytotoxic assay to NIH 3T3 mouse embryonic fibroblast cells of the polar and nonpolar fraction of tomato extract is 1820.90 μg/mL and 1643.86 μg/mL, respectively.

Madhuri Donakonda, Srija Indrakanti, Praveen Kumar Pasala et al.

Abstract Background This study was designed to develop a reliable method for estimation of Ivacaftor and Tezacaftor in pure and its pharmaceutical dosage form by RP-HPLC in human plasma. Molecular docking studies were carried out and the results were visualized using PyMol and Discovery studio visualizer (Discovery studio visualizer ver. 2.5). The pharmacokinetic properties such as Swiss ADME and pKCSM of the Ivacaftor and its metabolites Ivacaftor M1, M6 and Tezacaftor and metabolites Tezacaftor M1, M2 were predicted. In admetSAR, web-based query tools incorporating a molecular built-in interface enable the database to be queried by SMILES. Results A simple, linear, precise, and accurate RP-HPLC method was developed and validated for the determination of Ivacaftor (IVA) and Tezacaftor (TEZ) in human plasma. Chromatographic separation was achieved isocratically on Inspire C18, (4.6 × 250 mm, 5 μm) column at 30 °C. Mobile phase consisting of methanol and 0.05% formic acid in ratio of 95:5 with flow rate of 1 mL/min with injection volume 20 μl detector used is PDA at 235 nm. The developed method was validated according to ICH guidelines and found to be linearity range was found to be for TEZ (10–50 μg/mL) and IVA (15–75 μg/mL). IVA and TEZ drugs and its metabolites were retrieved from the PubChem database and the 2D chemical structures were generated from SMILES notation by using the Chemsketch Software. The structure was viewed using Swiss-PDB Viewer to form a better understanding of the molecule for toxicity and biological activity prediction. Conclusion The results obtained by the proposed method from validation parameters and from assay confirmed that the determination of Tezacaftor (TEZ) and Ivacaftor (IVA) in their combined dosage form in human plasma was sensitive and selective method. In silico study has revealed that IVA and its metabolites IVA M1, IVA M6 are according to Lipinski rule. The oral bioactivity of IVA was found to be more when compared to its metabolites (Molinspiration) and TEZ and its metabolites TEZ M1, TEZ M2 even though they have the molecular weight > 500, but all other parameters from Molinspiration revealed better oral bioactivity of TEZ M2. Validation of the developed isocratic RP-HPLC procedure revealed that, regardless of how the sample was purified, the method was characterized by good linearity, sensitivity, reproducibility, specificity, and low values of LOD (0.090 μg/mL) and LOQ (0.275 μg/mL). From the in silico docking results, it is quite evident that metabolites of TEZ and IVA have the great potential against cystic fibrosis.

Mostafa F. Tawfeeq, Ahlam J Qassir