Bioassays of inflammation pathways from combination of moringa oleifera, capsaicin and menthol

Moringa oleifera is a multi-purpose plant native to Africa and Asia. Many studies have shown the medicinal value of its edible leaves, pods and seeds in treating inflammation and various diseases. The leaf is the most investigated part of this plant for its rich secondary metabolites, vitamins and minerals and has been incorporated in various herbal-based products. Herbal-based formulation to treat the inflammation is popular in the market. However, the effectiveness of anti-inflammatory and antioxidant of M. oleifera leaves extract-based formulation with capsaicin and menthol has not been determined. Hence, this study was focused on determining the antiinflammatory and antioxidant potential of M. oleifera leaves extract-based formulation with a combination of capsaicin and menthol. In this study, methanolic extract of ovendried M. oleifera leaves (OME) produced the highest yield (38.49 ± 0.24%), total phenolic content (3.2182 ± 0.1144 mg GAE/g) and total flavonoid content (2.2017 ± 0.1168 mg QCE/g) with promising ferric reducing antioxidant power (FRAP) (5.8456 ± 0.2446 mM Fe2+) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging (88.90 ± 0.38%) activities compared to fresh leaves and ethanolic extracts. Hence, the OME of M. oleifera leaves was chosen as the main ingredient in the cream formulation. Four formulations were made with different concentrations of capsaicin (0.03, 0.075, 0.1 and 0.2%) and menthol (2.8, 2.9, 2.925 and 2.97%). F1 which had the highest capsaicin concentration showed the strongest antioxidant capacities among all the formulations. EC50 of F1 in FRAP and DPPH assays were 49.85 ± 0.17 mg/mL and 6.84 ± 0.08 mg/mL, respectively. Also, F1 had the most promising proteinase (IC50 = 2.16 ± 0.03%) and lipoxygenase inhibition activities. The results indicated that the combination of M. oleifera, capsaicin and menthol in F1 formulation was a more promising anti-inflammatory and antioxidant compared to herbal-based formulation alone due to the synergic effect of the mixture. HPLC analysis of capsaicin and GC determination of menthol gave retention times at around 4.7 and 5.6 minutes, respectively, by referring to the standard. In conclusion, the combination of OME of M. oleifera leaves with capsaicin and menthol has the potential to be used as a medicinal formulation to relieve inflammation conditions

THE INFLUENCE OF THE HAMSTRING MYOFASCIAL RELEASE ON GROUND REACTION FORCE DURING GAIT

The purpose of this study was to investigate the influence of the myofascial release on hamstring during gait in order to inform the clinical management of patients with muscular tightness of hamstring. Sixteen adult subjects with the muscle tightness of hamstring participated in this study. The peak of the vertical ground reaction force before treatment (1.114 body weight) in the stance phase is significantly higher than that (1.065 body weight) after treatment (P=0.007). The peak knee extension moment was significantly decreased across the intervention (0.48 vs. 0.33 Nm/kg, P = 0.019). The understanding of the efficacy of myofascial release on hamstring muscles is helpful to inform the clinical management of patients with muscular tightness of hamstring

4-Hydroxy­phenyl 4-fluoro­benzoate

In the title compound, C13H9FO3, the dihedral angle between the two benzene rings is 59.86 (4)°. In the crystal, inter­molecular O—H⋯H hydrogen bonds lead to molecular chains propagating in [010]

Disorder-dependent Li diffusion in Li6PS5Cl\mathrm{Li_6PS_5Cl} investigated by machine learning potential

Solid-state electrolytes with argyrodite structures, such as $\mathrm{Li_6PS_5Cl}$, have attracted considerable attention due to their superior safety compared to liquid electrolytes and higher ionic conductivity than other solid electrolytes. Although experimental efforts have been made to enhance conductivity by controlling the degree of disorder, the underlying diffusion mechanism is not yet fully understood. Moreover, existing theoretical analyses based on ab initio MD simulations have limitations in addressing various types of disorder at room temperature. In this study, we directly investigate Li-ion diffusion in $\mathrm{Li_6PS_5Cl}$ at 300 K using large-scale, long-term MD simulations empowered by machine learning potentials (MLPs). To ensure the convergence of conductivity values within an error range of 10%, we employ a 25 ns simulation using a $5\times5\times5$ supercell containing 6500 atoms. The computed Li-ion conductivity, activation energies, and equilibrium site occupancies align well with experimental observations. Notably, Li-ion conductivity peaks when Cl ions occupy 25% of the 4c sites, rather than at 50% where the disorder is maximized. This phenomenon is explained by the interplay between inter-cage and intra-cage jumps. By elucidating the key factors affecting Li-ion diffusion in $\mathrm{Li_6PS_5Cl}$, this work paves the way for optimizing ionic conductivity in the argyrodite family.Comment: 34 pages, 6 figure

Spontaneous Intraperitoneal Bladder Perforation Associated with Urothelial Carcinoma with Divergent Histologic Differentiation, Diagnosed by CT Cystography

Spontaneous bladder perforation is a very rare event. Prompt diagnosis of this injury is very important, particularly with intraperitoneal perforation, because mortality increases if surgical repair is delayed. Previous studies have reported that plain cystography is the primary modality of imaging study rather than relatively insensitive computed tomography (CT) when bladder perforation is suspected. We report here a rare case of spontaneous intraperitoneal perforation of the bladder associated with urothelial carcinoma with divergent histologic differentiation, as diagnosed with CT cystography

Metabolic pathway prediction of core microbiome based on enterotype and orotype

IntroductionIdentification of key microbiome components has been suggested to help address the maintenance of oral and intestinal health in humans. The core microbiome is similar in all individuals, whereas the diverse microbiome varies across individuals, based on their unique lifestyles and phenotypic and genotypic determinants. In this study, we aimed to predict the metabolism of core microorganisms in the gut and oral environment based on enterotyping and orotyping.Materials and methodsGut and oral samples were collected from 83 Korean women aged 50 years or older. The extracted DNA was subjected to next-generation sequencing analysis of 16S rRNA hypervariable regions V3–V4.ResultsGut bacteria were clustered into three enterotypes, while oral bacteria were clustered into three orotypes. Sixty-three of the core microbiome between the gut and oral population were correlated, and different metabolic pathways were predicted for each type. Eubacterium_g11, Actinomyces, Atopobium, and Enterococcus were significantly positively correlated between the gut and oral abundance. The four bacteria were classified as type 3 in orotype and type 2 in enterotype.ConclusionOverall, the study suggested that collapsing the human body’s multidimensional microbiome into a few categories may help characterize the microbiomes better and address health issues more deeply

Incorporating Surprisingly Popular Algorithm and Euclidean Distance-based Adaptive Topology into PSO

While many Particle Swarm Optimization (PSO) algorithms only use fitness to assess the performance of particles, in this work, we adopt Surprisingly Popular Algorithm (SPA) as a complementary metric in addition to fitness. Consequently, particles that are not widely known also have the opportunity to be selected as the learning exemplars. In addition, we propose a Euclidean distance-based adaptive topology to cooperate with SPA, where each particle only connects to k number of particles with the shortest Euclidean distance during each iteration. We also introduce the adaptive topology into heterogeneous populations to better solve large-scale problems. Specifically, the exploration sub-population better preserves the diversity of the population while the exploitation sub-population achieves fast convergence. Therefore, large-scale problems can be solved in a collaborative manner to elevate the overall performance. To evaluate the performance of our method, we conduct extensive experiments on various optimization problems, including three benchmark suites and two real-world optimization problems. The results demonstrate that our Euclidean distance-based adaptive topology outperforms the other widely adopted topologies and further suggest that our method performs significantly better than state-of-the-art PSO variants on small, medium, and large-scale problems