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Background and Aims: Myeloperoxidase (MPO) plays a critical role in the innate immune response and has been suggested to be a surrogate marker of oxidative stress and inflammation, with elevated levels implicated in cardiovascular diseases, such as atherosclerosis and heart failure, as well as in conditions like rheumatoid arthritis and cancer. While MPO is well-known in leukocytes, its expression and function in human endothelial cells remain unclear. This study investigates MPO expression in patient-derived endothelial colony-forming cells (ECFCs) and its potential association with CAD and mitochondrial function., Methods: ECFCs were cultured from the peripheral blood of 93 BioHEART-CT patients. MPO expression and associated functions were examined using qRT-PCR, immunochemistry, flow cytometry, and MPO activity assays. CAD presence was defined using CT coronary angiography (CACS > 0)., Results: We report MPO presence in patient-derived ECFCs for the first time. MPO protein expression occurred in 70.7% of samples ( n = 41) which had nuclear co-localisation, an atypical observation given its conventional localisation in the granules of neutrophils and monocytes. This suggests potential alternative roles for MPO in nuclear processes. MPO mRNA expression was detected in 66.23% of samples ( n = 77). CAD patients had a lower proportion of MPO-positive ECFCs compared to non-CAD controls (57.45% vs. 80%, p = 0.04), a difference that persisted in the statin-naïve sub-cohort (53.85% vs. 84.62%, p = 0.02). Non-CAD patients with MPO expression showed upregulated mitochondrial-antioxidant genes ( AIFM2 , TXNRD1 , CAT , PRDX3 , PRDX6 ). In contrast, CAD patients with MPO gene expression had heightened mROS production and mitochondrial mass and decreased mitochondrial function compared to that of CAD patients without MPO gene expression., Conclusions: MPO is present in the nucleus of ECFCs. In non-CAD ECFCs, MPO expression is linked to upregulated mitochondrial-antioxidant genes, whereas in CAD ECFCs, it is associated with greater mitochondrial dysfunction.

This study is the first to investigate the chemical composition and antioxidant, anti-inflammatory, and cytotoxic activities of Peperomia leptostachya leaf oil. A yellow oil was obtained through hydro-distillation, with a yield of 0.1% ( w / w ). The GC-MS analysis revealed 66 compounds, constituting 99.6% of the oil. Sesquiterpene hydrocarbons predominated (70.4%), followed by monoterpene hydrocarbons (13.2%), oxygenated sesquiterpenes (12.4%), non-terpenic compounds (2.0%), and oxygenated monoterpenes (1.6%). Major constituents included germacrene D (25.1%), ( E )-caryophyllene (17.4%), bicyclogermacrene (6.6%), α -pinene (6.2%), and β -pinene (4.7%). The assessment of antioxidant capacity via 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging assay yielded a weak effect, with an IC 50 value > 100 µg/mL. The inhibition of lipopolysaccharide-induced nitric oxide production in RAW 264.7 cells was quantified using the MTT assay, showing an IC 50 value of 15.15 ± 0.68 µg/mL. Furthermore, cytotoxic effects on SK-LU-1 cell line growth were evaluated using the sulforhodamine B assay, resulting in an IC 50 value of 37.45 ± 2.43 μg/mL. The anti-inflammatory activity was notable among the analyzed bioactivities of this oil. By employing a computational model, the predominant secondary metabolites in the essential oil were selected as candidates for interaction analysis with cyclooxygenase-2, an enzyme implicated in the inflammatory response. Our findings suggest that P. leptostachya leaf oil could serve as a potential source of natural compounds with prospective therapeutic effects in treating inflammatory conditions.

The essential oils of five Vietnamese Syzygium species ( Syzygium levinei , S. acuminatissimum , S. vestitum , S. cumini , and S. buxifolium ) were first hydro-distilled and analyzed using GC-FID/MS (gas chromatography-flame ionization detection/mass spectrometry). Monoterpene hydrocarbons, sesquiterpene hydrocarbons, and oxygenated sesquiterpenoids were the main chemical classes in these oils. All these essential oils showed good-excellent antimicrobial activities against Gram-positive bacteria Enterococcus faecalis , Staphylococcus aureus , and Bacillus cereus , and the yeast Candida albicans. S. levinei leaf essential oil, rich in bicyclogermacrene (25.3%), ( E )- β -elemene (12.2%), ( E )-caryophyllene (8.2%), and β -selinene (7.4%), as well as S. acuminatissimum fruit essential oil containing ( E )-caryophyllene (14.2%), α -pinene (12.1%), caryophyllene oxide (10.9%), β -selinene (10.8%), α -selinene (8.0%), and α -humulene (5.7%), established the same MIC value of 8 µg/mL against E. faecalis and B. cereus , which were much better than the positive control streptomycin (MIC 128-256 µg/mL). The studied essential oils showed the potential to defend against mosquitoes since they caused the 24 and 48 h LC 50 values of less than 50 µg/mL against the growth of Culex quinquefasciatus and Aedes aegypti larvae. Especially, S. buxifolium leaf essential oil strongly inhibited Ae. aegypti larvae with 24 and 48 h LC 50 values of 6.73 and 6.73 µg/mL, respectively, and 24 and 48 h LC 90 values of 13.37 and 10.83 µg/mL, respectively. These findings imply that Vietnamese Syzygium essential oils might have potential for use as supplemental antibacterial agents or as "green" alternatives for the control of mosquitoes.

The maximum power point tracking (MPPT) solutions improve power generation efficiency, quickly stabilizing the output waveform of photovoltaic (PV) systems under variable operating conditions. Along with new algorithms, improved and adjusted methods to exploit energy from PV systems are increasingly being researched and proposed. However, the proposed solutions based on the traditional algorithms and their improvements have poor performance, while the advanced algorithms or hybrid methods bring high performance but need to be simplified, and the response speed is higher. Moreover, a suitable PV configuration makes choosing a simple but highly efficient algorithm, especially in low-power PV system applications such as rooftop solar power, traffic lights, and moving vehicles…where the number of PV panels is insufficient to implement flexible configurations. This paper proposes a modified version of the Perturb and Observe (MPO) algorithm to improve MPPT performance and increase convergence speed in the parallel structure of PV panels. The Short-Circuit Current (I sc ) and Open-Circuit Voltage (V oc ) are calculated directly at specific operating conditions to quickly determine the potential maximum power point (MPP) that will reduce power interruptions and increase power generation efficiency compared to periodic updates. Therefore, the proposed solution converges faster, with higher efficiency, and the output signal in static and dynamic MPPT situations is more stable. The results show that the highest efficiency in simulation and experiment is 99.99% and 99.93%, respectively, while the convergence speed is 0.01 s and 0.03 s, respectively. They are better than the traditional Perturb and Observe (P&O) algorithm, the Variable Step Size Perturb and Observe (VSSP&O) method, and the Particle Swarm Optimization (PSO) technique under the same operating conditions. In addition, its performance and convergence speed are also compared with the latest introduced algorithms. The results show that it is valuable and reliable for parallel PV configuration.

Computer vision plays a significant role in mobile robot navigation due to the wealth of information extracted from digital images. Mobile robots localize and move to the intended destination based on the captured images. Due to the complexity of the environment, obstacle avoidance still requires a complex sensor system with a high computational efficiency requirement. This study offers a real-time solution to the problem of extracting corridor scenes from a single image using a lightweight semantic segmentation model integrating with the quantization technique to reduce the numerous training parameters and computational costs. The proposed model consists of an FCN as the decoder and MobilenetV2 as the decoder (with multi-scale fusion). This combination allows us to significantly minimize computation time while achieving high precision. Moreover, in this study, we also propose to use the Balance Cross-Entropy loss function to handle diverse datasets, especially those with class imbalances and to integrate a number of techniques, for example, the Adam optimizer and Gaussian filters, to enhance segmentation performance. The results demonstrate that our model can outperform baselines across different datasets. Moreover, when being applied to practical experiments with a real mobile robot, the proposed model's performance is still consistent, supporting the optimal path planning, allowing the mobile robot to efficiently and effectively avoid the obstacles.

In this report, we focus our effort to extract cellulose nanomaterials (CNs) from an agricultural cellulosic waste, Dragon Fruit foliage (DFF). DFF was first pretreated by several mechanical treatments and then bleached by chemical treatment to obtain bleached DFF. CNs were then produced from the hydrolysis of the bleached DFF catalyzed by sulfuric acid. We obtained CNs with a small diameter (50 to 130 nm) and length (100 to 500 nm) and a height of 3 to 10 nm. The CNs have a high crystallinity (crystallinity index 84.8%), high -COOH content (0.74 mmol·g -1 ), good thermal stability and a good Cu (II) adsorption capacity with an adsorption maximum of ~103 mg·g -1 . These findings demonstrated the great potential of converting many agricultural cellulosic wastes into valuable cellulose nanomaterials.

This work aims to explore how ZnO nanoparticles enhance the mechanical, photoaging, and self‑cleaning properties of water‑borne acrylic coating. Micro/nano‑ZnO particles (at 2 wt.% of total solid resin) were dispersed into the acrylic polymer matrices using ultrasonication to understand the effect of the size of the coating properties. The effect of ZnO particles on the properties of composite coatings (25 µm of thick) have been evaluated through various tests, such as abrasion measurement, ultraviolet/condensation (UV/CON) weathering aging, and methylene blue self‑cleaning. Experimental data indicated that the incorporation of ZnO particles enhanced both abrasion resistance and methylene blue removal efficiency of the water‑borne acrylic coatings, with nano‑ZnO particles being the best. However, the weathering degradation of nanocomposite coatings was more severe as compared to the coating with micro‑ZnO (at the same ZnO content).

N-containing gaseous compounds, such as trimethylamine (TMA), triethylamine (TEA), ammonia (NH 3 ), nitrogen monoxide (NO), and nitrogen dioxide (NO 2 ) exude irritating odors and are harmful to the human respiratory system at high concentrations. In this study, we investigated the sensing responses of five sensor materials-Al-doped ZnO (AZO) nanoparticles (NPs), Pt-loaded AZO NPs, a Pt-loaded WO 3 (Pt-WO 3 ) thin film, an Au-loaded WO 3 (Au-WO 3 ) thin film, and N-doped graphene-to the five aforementioned gases at a concentration of 10 parts per million (ppm). The ZnO- and WO 3 -based materials exhibited n-type semiconducting behavior, and their responses to tertiary amines were significantly higher than those of nitric oxides. The N-doped graphene exhibited p-type semiconducting behavior and responded only to nitric oxides. The Au- and Pt-WO 3 thin films exhibited extremely high responses of approximately 100,000 for 10 ppm of triethylamine (TEA) and approximately -2700 for 10 ppm of NO 2 , respectively. These sensing responses are superior to those of previously reported sensors based on semiconducting metal oxides. On the basis of the sensing response results, we drew radar plots, which indicated that selective pattern recognition could be achieved by using the five sensing materials together. Thus, we demonstrated the possibility to distinguish each type of gas by applying the patterns to recognition techniques.