Citrus essential oils (EOs) have various bioactivities like antioxidants, with many applications. Antioxidant activities depend on the chemical compositions of the EOs, which are affected by climate, soil, and geographical region. Thus, investigations on chemical compositions and antioxidant activities of Citrus EOs in different countries are valuable. In this study, we distilled EOs from peels of Indonesian-grown Citrus, including C. nobilis, C. limon, C. aurantifolia, C. amblycarpa, and Citrus spp.Chemical compositions of EOs were analyzed using Gas Chromatography-Mass Spectrometer (GC-MS), whereas the antioxidant activities were determined by employing 2,2-diphenyl-2-picrylhydrazyl (DPPH) method. Furthermore, principal component analysis (PCA) was applied to elucidate the main contributing compounds for antioxidant activity. The results show that all EOs possess unique chemical characteristics, with limonene as the majority constituent. For antioxidant activities, C. limon and C. amblycarpa EOs are the two strongest, IC50 values below 7.00 μL/mL. PCA approach suggests that -terpinene mainly contributes to the high antioxidant activities of C. limon and C. amblycarpa. Moreover, o-cymene, thymol, p-cymene, and α-pharnesene may also be responsible for the antioxidant activity of C. limon EO. These results are valuable information for the applications of Citrus EOs as antioxidant sources.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

In this study, we investigate the growth of EV ownership among Swedish households. Through detailed socio-economic data and the Swedish vehicle register, we are able compare characteristics of households that bought an EV in 2016 with those that became EV owners in 2020. We are thus able to describe and analyse the transition from the early EV owners to the early majority. Unlike many prior studies in the field, which are based on surveys or interviews, this study relies on registry data, thereby encompassing all car owners in Sweden. In this study, we have also scrutinized the significance of ownership mode by distinguishing between households that have chosen to purchase a car and those that have chosen to lease one. The results show that the demand for EVs has reached new consumer groups, e.g. both younger and older car buyers, and that the option to lease a car privately has broadened the market for new cars in general, and for EV’s in particular.

Citrus species essential oils (EOs) are significant sources of bioactive compounds and demonstrate diverse therapeutic effects. However, limited documentation exists regarding the phytochemicals associated with their biological activities. This study aims to assess the antioxidant activity, plant inhibitory properties, and brine shrimp cytotoxic effects of EOs derived from three Citrus species: C. sinensis, C. limon, and C. hystrix. Utilizing chemometric analysis and gas chromatography-mass spectrometry (GC-MS) fingerprints, the volatile components contributing to antioxidant activity were elucidated. The peels of the Citrus samples were hydro-distillated to obtain EOs, and subsequently subjected to antioxidant, plant inhibitory, and brine shrimp cytotoxic assays. The results indicated that C. limon EO exhibited the highest antioxidant activity, while C. hystrix and C. sinensis EOs demonstrated pronounced inhibitory effects against Aetrmia salina and Lactuca sativa, respectively. GC-MS analysis facilitated the identification of key compounds in each EO. Principal component analysis (PCA) and hierarchy cluster analysis (HCA) effectively categorized Citrus EOs based on their antioxidant properties, highlighting the proximity of C. limon and C. sinensis. Among the identified compounds, D-limonene, α-Terpineol, Caryophyllene, (+)-3-Carene, β-Pinene, (-)-Spathulenol, trans-p-Mentha-1(7),8-dien-2-ol, and trans-Verbenol were the most discriminating compounds affected the antioxidant activity of C.limon and C. sinensis EOs.

Plant cells' ability to withstand abiotic stress is strongly linked to modifications in their mechanical characteristics. Nevertheless, the lack of a workable method for consistently tracking plant cell mechanical properties severely restricts our comprehension of the mechanical alterations in plant cells under stress. With Polyethylene Glycol (PEG6000), we created a drought-like environment, and we used the Double Resonator Piezoelectric Cytometry (DRPC) method to dynamically and non-invasively track changes in the stress (ΔS) created and viscoelasticity (storage modulus G' and loss modulus G") of protoplasts and suspension cells of rice during drought stress. The findings demonstrate that, rice suspension cells and protoplasts react mechanically differently to 5%–15% PEG6000 stress, implying distinct resistance mechanisms. However, neither of them can withstand 25% PEG6000 stress, they respond mechanically similarly to 25% PEG6000 stress. The results of DRPC are further corroborated by the morphological alterations of rice cells and protoplasts observed under an optical microscope. To sum up, the DRPC technique functions as a precise cellular mechanical sensor and offers novel research tools for the evaluation of plant cell adversity and differentiating between the mechanical reactions of cells and protoplasts under abiotic stress.

In this paper, we propose a methodology for analyzing the near-field coupling between two surface mount device (SMD) inductors using a 3-dimensional electromagnetic (3D-EM) model. To develop the 3D-EM model, we first extract the effective permeability of core magnetic material in the SMD using the loss tangent in the equivalent circuit model. Then the effective permeability is used in the magnetic material for the 3D-EM modeling of SMD inductor. The validity of the proposed 3D-EM model is confirmed by comparing the impedance and S-parameters obtained from both measured and EM-simulated values for the two near-field coupled SMDs. Finally, the near-field coupling effects between the two adjacent SMD inductors are visualized in terms of magnetic coupling path visualization (CPV) using the proposed 3D-EM model, which demonstrates its usefulness for near-field coupling analysis.

Maximum likelihood estimation (MLE) is a popular method for parameter estimation in both applied probability and statistics but MLE cannot solve the problem of incomplete data or hidden data because it is impossible to maximize likelihood function from hidden data. Expectation maximum (EM) algorithm is a powerful mathematical tool for solving this problem if there is a relationship between hidden data and observed data. Such hinting relationship is specified by a mapping from hidden data to observed data or by a joint probability between hidden data and observed data. In other words, the relationship helps us know hidden data by surveying observed data. The essential ideology of EM is to maximize the expectation of likelihood function over observed data based on the hinting relationship instead of maximizing directly the likelihood function of hidden data. Pioneers in EM algorithm proved its convergence. As a result, EM algorithm produces parameter estimators as well as MLE does. This tutorial aims to provide explanations of EM algorithm in order to help researchers comprehend it. Moreover some improvements of EM algorithm are also proposed in the tutorial such as combination of EM and third-order convergence Newton-Raphson process, combination of EM and gradient descent method, and combination of EM and particle swarm optimization (PSO) algorithm.

The paper delves into the critical issue of damage detection within the guy cable of a truss steel mast, a pivotal component in structural integrity. It introduces a model wherein damage manifests as a localized cross-section reduction in a single element of the cable. Employing Discrete Wavelet Transform (DWT), a pioneering methodology, the study scrutinizes the behavior of the affected elements through static structural analyses. Signal decomposition via the Mallat pyramid algorithm facilitates comprehensive examination. Static displacements at the connection point between the cable and the truss mast serve as the measured variables. Through systematic investigation, the paper evaluates the impact of damage size and location, external loading force, and cable tension force on the efficacy of the proposed approach. Utilizing data derived from Finite Element Method (FEM) computations for wavelet analysis the authors substantiate the findings with numerical examples, thus offering valuable insights into damage detection strategies for structural health monitoring and engineering applications.

Aim: Nepal’s medicinal plants are culturally important and have diverse benefits. Senna alata belongs to the family Leguminosae and is a valuable plant utilized for medicinal and ornamental purposes. The aim of the research was to extract Senna alata leaves by successive maceration with various solvents. Methods: In this study, various methods were utilized to evaluate phytochemistry, overall phenolic and flavonoid content, in-vitro antioxidant, anti-inflammatory, cytotoxicity assay, anti-thrombolytic activity, and antibacterial activities. Results: The extractive values of Senna alata were determined as 1.58%, 0.78%, and 5.92% in hexane, ethyl acetate, and methanol, respectively. GC-MS analysis revealed major compounds such as 3-Methylmannoside, Neophytadiene, Campesterol, and Vitamin E in the leaf extract. Qualitative phytochemical screening verified the tannin content, carbohydrates, flavonoids, cardiac glycosides, glycosides, and saponins in the methanol extract. The total phenolic and flavonoid values were 46.36±4.5 mg GAE/gm and 480.4±3.055 QE/gm of dried extract, respectively. The extract exhibited significant antioxidant and anti-inflammatory activities, with IC50 values of 29.81 and 9.93, respectively. Furthermore, it demonstrated cytotoxic activity with an LC50 value of 767.85 in the brine shrimp bioassay. In terms of thrombolytic activity, the extract showed clot lysis percentages of 7.89% and 10.13% at concentrations of 10 mg/ml and 25 mg/ml, respectively. Conclusion: In conclusion, the methanolic extract of Senna alata leaves displayed therapeutic potential, including antioxidant, anti-inflammatory, cytotoxic, thrombolytic, and antibacterial effects. The existence of several chemicals via GC-MS analysis also verified plant's potential for therapeutic use.

Fungal infections caused by Candida spp. are responsible for high hospital morbidity and mortality rates. Therefore, there is a continuous search for new antifungal medicines, particularly ones with anti-Candida activity. This review analyzed articles published between 2002 and 2023 considering the anti-Candida activity of chemical compounds identified or isolated in plants of the Anacardiaceae family. In addition, the in-silico prediction of the isolated compounds described was performed. The analysis of 35 studies showed that extracts, essential oils, and compounds from the anti-Candida activity were frequently determined in vitro using the minimum inhibitory concentration (MIC). The most commonly tested species were Candida albicans, C. tropicalis, C. parapsilosis, C. glabrata, C. krusei, and C. guilliermondii, respectively. Essential oils were the most used form (37% of the studies). The isolated compounds with antifungal effects include cardanol, estragole, trans-anethole, β-caryophyllene, myrcene, catechin-3-o-rhamnoside, β-sitosterol-3-O-glucoside, 24Z-isomasticadienolic acid, oleanolic acid, and oleanolic aldehyde. The in-silico evaluation of those isolated compounds revealed the compounds' drug-likeness and possible antifungal activity. However, some of them showed high toxicity. In conclusion, compounds from the Anacardiaceae family show promise for developing new therapeutic antifungal drugs, especially in combination with conventional antifungals.

Previous high throughput screening studies indicated trans-eQTLs tend to be tissue specific. In this study, I probed if this feature can be used to identify tissue-specific gene regulatory networks. eQTL data (P<5e-8) for 16,259 genes were identified and their summary association statistics were obtained from the eQTLGene database. Next, eQTLs that display both cis and trans regulatory effects were selected and the association between their corresponding genes were examined using Mendelian randomization. A total of 169 genes that exerted trans-regulatory impacts on 692 genes were identified. 90% of the genes (N=749) aggregated into a gene regulatory network significantly enriched in hemo-immune processes. The robustness of finding was confirmed through simulation. The identified network displayed the scale-free topology. This provided the reason to examine the association of the network’s hub genes with the phenome. The outcome of analyses revealed GSDMB and ORMDL3 impact several disorders of immune origin and ALDH2 overexpression contributes to obesity. This study reports trans-eQTLs can be used to identify tissue-specific gene regulatory networks and describes a workflow to achieve this purpose. The network identified in this study showed scale-free topology indicating the hub genes of a GRN could be targeted to prevent disease outcomes.

Regulation of the diet in terms of the content of soluble and insoluble fibre is of great importance from the point of view of dietetics, microbiology of the gastrointestinal tract and immunology of the organism. Dietary fibre plays an important role in maintaining the balance between the con-tinuity of gut mucus production (intestinal mucosa), the stability of the intestinal microbiome composition, the regeneration of the intestinal epithelium and the immune status within the gut-associated lymphoid tissue (GALT) are played by pectin and their metabolic products in the form of pectin oligosaccharides. The main purpose of this review was to focus on pectin, their functions, their impact on the human's health and on some of the most promising prebiotics due to their solubility in the gastrointestinal tract in the form of pectin oligosaccharides. They have the properties of pectin, but have also additional features and postbiotics obtained in fermentation process can affect the intestinal microbiome and GALT-related immunity. They can be obtained from plant agro-wastes.

Condition-specific competition, when environmental conditions alter the outcome of competition, can foster the persistence of resident species after the invasion of a competitively superior invader. We test whether condition-specific competition can facilitate the areawide persistence of the resident and principal West Nile virus vector mosquito Culex pipiens with the competitively superior invasive, Aedes albopictus, in water from different urban container habitats. (2) Methods: We tested the effects of manipulated numbers of A. albopictus on C. pipiens survival and development in water collected from common functional and discarded containers in Baltimore, Maryland, USA. The experiment was conducted with typical numbers of larvae found in field surveys of C. pipiens and A. albopictus and container water quality. (3) Results: We found increased densities of A. albopictus negatively affected the survivorship and development of C. pipiens in water from discarded containers but had little effect in water from functional containers. This finding was driven by water from trash cans, which allowed consistently higher C. pipiens survival and development and had greater mean ammonia and nitrate concentrations that can promote microbial food than other container types. (4) Conclusions: These results suggest that the contents of different urban containers alter the effects of invasive A. albopictus competition on resident C. pipiens, that trash cans, in particular, facilitate the persistence of C. pipiens, and that there could be implications for West Nile virus risk as a result.

Conobea scoparioides (Plantaginaceae) is an herbaceous plant known as "pataqueira" that grows wild in seasonally wet areas of the Amazon region. It is used for aromatic baths and anti-protozoan remedies by the Brazilian Amazon native people. The main volatile compounds identified in the essential oil of "Pataqueira" were the phenolic monoterpenes thymol and thymol methyl ether and their precursors, the monoterpene hydrocarbons α-phellandrene and p-cymene. A hydrotalcite synthesized from blast-furnace slag exhibited a 3:2 (Mg/Al) molar ratio, and this layered double hydroxide (LDH) was evaluated as a catalyst in converting the main monoterpenes of the "Pataqueira" oil. This action significantly increased thymol content, from 41% to 95%, associated with the percentual reduction of other main components, such as thymol methyl ether, α-phellandrene, and p-cymene. The LDH reaction showed a strong tendency towards producing hydroxylated derivatives, and its behavior was similar to the hypothetical plant biosynthetic pathway, which leads to the production of the monoterpenes of "Pataqueira" oil. Thymol and its derivatives are potent antiseptics applied in pharmaceutical and hygienic products as antibacterial, antifungal, and antioxidant properties, among others. The present work reports a natural source with a high thymol content in aromatic plants from the Amazon, with evident economic value.

Nowadays, animal breeders look for effective innovations to care animal health. Use of probiotics, postbiotics, parabiotics and the other beneficial natural substances are dominated. Mundticin-like substance EM 41/3 is thermo-stable bacteriocin (postbiotic) with a broad antimicrobial spectrum. In this study its effect in broiler rabbits was assessed. Rabbits represent food-derived animal and they are also suitable animal model. The parameters tested were analyzed by validated methods. Administration of MLS EM 41/3 produced by non-autochthonous strain Enterococcus mundtii EM 41/3 lead to significant increase of parameter immunity-phagocytic activity, while it did not influence microbiota composition. It also did not influence blood biochemistry and no oxidative stress was noted. Moreover, higher growth parameters were noted and also stimulated hydrolytic activity. Finally, no negative influence on rabbit meat quality was noted. Postbiotic MLS EM 41/3 administration in feeding strategy seems to be contributing fact for rabbit health status maintaining.

Leucobryum is a moss genus that exhibits various bioactivities. However, the identification of Leucobryum species with morphology alone remains difficult. Nowadays, chemical profile analysis provides additional tools for plant classification, especially in medicinal plants. This method uses chemical similarities to identify the differences among some plants, especially for the different varieties of the same species. The objective of this study was to obtain the chemical profiles and use chemometrics to identify selected Leucobryum species found in Thailand. Lipophilic extracts from 18 samples of five taxa were analyzed with TLC and HPLC. Cluster analysis and PCA were used to investigate the similarities of the chemical profiles. PERMANOVA was performed to determine the difference among taxa. The results showed that the TLC profile could separate only the genus of the sample, while HPLC chromatograms showed separation among the Leucobryum taxa and consistent patterns within the same species. In addition, the chemical profiles of Leucobryum species were separated at the species level in PCA. The PERMANOVA showed significantly different profiles among the species (P = 0.002). Therefore, this work illustrated the potential of chemometrics as supporting evidence for species delimitation in the moss genus Leucobryum.

Fumaric acid is a chemical building block with many applications, namely in the polymer industry. The fermentative production of fumaric acid from renewable feedstock is a promising and sustainable alternative to petroleum-based chemical synthesis. The use of existing industrial side-streams as raw-material within biorefineries potentially enable production costs competitive against current chemical processes, while preventing the use of refined sugars competing with food and feed uses and avoiding purposely grow crops requiring large areas of arable land. However, most industrial side streams contain a diversity of molecules that will add complexity to the purification of fumaric acid from the fermentation broth. A process for the recovery and purification of fumaric acid from complex fermentation medium containing spent sulfite liquor (SSL) as carbon source was developed and is herein described. A simple two-stage precipitation procedure involving separation unit operations, pH and temperature manipulation and polishing through the removal of contaminants with activated carbon allowed the recovery of fumaric acid with 68.3% recovery yield with specifications meeting the requirements of the polymer industry. Further, process integration opportunities were implemented that allowed minimizing the generation of waste streams containing fumaric acid which enabled increasing the yield to 81.4% while keeping the product specifications.

The Solvency II regulatory framework specifies procedures and parameters for determining solvency capital requirements (SCRs) for insurance companies. The proposed standard SCR calculations involve two steps. The Value–at–Risk (VaR) of each risk driver is measured and, in a second step, all components are aggregated to the company’s overall SCR, using the Standard Formula. This formula has two inputs: the VaRs of the individual risk drivers and their correlations. The appropriate calibration of these input parameters has been the purpose of various Quantitative Impact Studies that have been conducted during recent years. This paper demonstrates that the parameter calibration for the equity–risk module—overall, with about 25%, the most significant risk component—is seriously flawed, giving rise to spurious and highly erratic parameter values. As a consequence, an implementation of the Standard Formula with the currently proposed calibration settings for equity–risk is likely to produce inaccurate, biased and, over time, highly erratic capital requirements.

Deoxynivalenol (DON) is a mycotoxin produced by Fusarium spp. that causes Fusarium head blight (FHB) disease in cereal crops. Ingestion of food contaminated with DON poses serious human health complications. However, the DON cytotoxicity has been mostly deduced from animal studies. In this study, we used the nematode Caenorhabditis elegans (C. elegans) as a tractable animal model to dissect the toxic effect of DON. Our results indicate that DON reduces the fecundity and lifespan of C. elegans. The real-time RT-PCR analysis showed that DON upregulates innate immunity-related genes including C17H12.8 and K08D8.5 encoding PMK-1 (mitogen activated protein kinase-1)-regulated immune effectors, and F35E12.5 encoding a CUB-like domain-containing protein. Furthermore, our RNAseq data demonstrate that out of ~ 17,000 C. elegans genes, 313 are upregulated and 166 were downregulated by DON treatment. Among the DON-upregulated genes, several are ugt genes encoding UDP-glucuronosyl transferase (UGTs) which are known to be involved in chemical detoxification. The three upregulated genes, F52F10.4 (oac-32), C10H11.6 (ugt-26) and C10H11.4 (ugt-28) encoding the O-acyltransferase homolog, UGT26 and UGT 28, respectively, are shown to contribute to DON tolerance by RNAi bacterial feeding experiment. The results of this study provide insights to the targets of DON cytotoxicity and potential mitigation measures.

Due to the low content, few studies are focused on the essential oils (EOs) of Phlomoides rotata (Benth. ex Hook. f.) Mathiesen (syn. Lamiophlomis rotata (Benth.) Kudô. This plant has been used to treat rheumatic arthritis and grasserie in China. However, such EOs may have important pharmacological activities such as anti-cancer. To identify the chemical markers (CM) in the EOs and evaluate their antioxidant activities (AAs), we firstly conduct a thoroughly investigation on their chemicals and AAs, to the best of our knowledge. Light yellow EOs with fresh and elegant smell are obtained by hydro-distillation with average yield 0.11% (volume mL/weight g). The crystals are separated from the EOs through cryoprecipitation, respectively. A total of 81 components are qualified and quantified in the EOs, crystals and EOs removed crystals, in which 44 ones are first reported. As for content, the main compounds are long-chain fatty acids (FAs) and their esters. The most abundant one n-hexadecanoic acid (palmitic acid, PA) accounting for 43.15-54.8%, 58.49-64.57% and 15.9-41.1%, in the EOs, crystals and EOs removed crystals, respectively. Seven compounds including PA, tetradecanoic acid, linoleic acid, oleic acid, methyl hexadecanoate, hexahydrofarnesyl acetone and phytol can be chosen a the CMs in these EOs. The AAs are evaluated through in vitro assays. PA presents pro-oxidant activities in a concentration dependence manner. Usually, the EOs removed crystals demonstrate stronger AAs, and the crystals demonstrate weaker AAs compared with that of the corresponding EOs, which is related to the different content of PA in these samples. This study can give some hints for the utilization of such EOs which are abundant in FAs such as PA.

Bartonella henselae is a fastidious Gram-negative intracellular bacterium which can cause cat scratch disease, endocarditis in humans and animals as well as other complications, leading to acute or chronic infections. The current treatment for Bartonella infections is not very effective due to antibiotic resistance and also persistence. To develop better therapies for persistent and chronic Bartonella infections, in this study, with the help of SYBR Green I/PI viability assay, we performed a high-throughput screening of an essential oil library against stationary phase B. henselae. We successfully identified 32 essential oils that had high activity, including four essential oils extracted from Citrus plants, three from Origanum, three from Cinnamomum, two from Pelargonium and two from Melaleuca, as well as frankincense, ylang ylang, fir needle, mountain savory (winter), citronella, spearmint, elemi, vetiver, clove bud, allspice and cedarwood essential oils. The minimal inhibitory concentration (MIC) determination of these 32 top hits indicated they were not only active against stationary phase non-growing B. henselae but also had good activity against log phase growing B. henselae. The time-kill curve by drug exposure assay showed 13 active hits, including essential oils of oregano, cinnamon bark, mountain savory (winter), cinnamon leaf, geranium, clove bud, allspice, geranium bourbon, ylang ylang, citronella, elemi and vetiver, could eradicate all stationary phase B. henselae cells within 7 days at the concentration of 0.032% (v/v). Two active ingredients, carvacrol and cinnamaldehyde, of oregano and cinnamon bark essential oils, respectively, were shown to be very active against stationary phase B. henselae such that they were able to eradicate all the bacterial cells even at the concentration ≤ 0.01% (v/v). Our finding of active essential oils may help to develop more effective treatments for persistent Bartonella infections.

One of the richest natural sources of resveratrol - the rhizome of Reynoutria japonica in East Asia is a well-known traditional herb (Hu zhang) used in various inflammatory diseases, infections, skin diseases, scald, hyperlipidemia. Although, it has been recently included in the European Pharmacopoeia, still in Europe is an untapped resource. Some of the therapeutic effects are likely to be influenced by its antioxidant properties and this in turn is frequently associated with a high stilbene content. However, some literatures suggested that other compounds than stilbenes may add to the total antioxidant capacity. Hence, the aim of this research was to examine rhizomes of R. japonica and less studied, morphologically similar species, R. sachalinensis and R. x bohemica for their phytochemical composition and antioxidant activity and to clarify the relationship between the antioxidant activity and compounds by statistical methods. HPLC/UV/ESI-MS studies of three Reynoutria species revealed 171 compounds comprising stilbenes, carbohydrates, procyanidins, flavan-3-ols, anthraquinones, phenylpropanoids, lignin oligomers, hydroxycinnamic acids, naphthalenes and their derivatives. Our studies confirmed the presence of procyanidins with high degree of polymerization, up to decamers in the rhizomes of R. japonica and brings new data on the presence of these compounds in other Reynoutria species. A procyanidin trimer digallate was described for the first time in the studied plants. Moreover, we suggested a presence of new for these species, dianthrone glycosides and previously unrecorded phenylpropanoid disaccharide esters and hydroxycinnamic acid derivatives, mainly in R. sachalinensis. Furthemore, compounds tentatively annotated as lignin oligomers were observed for the first time in studied species. The rhizomes of all Reynoutria species exhibited strong antioxidant activity. Statistical analysis demonstrated that proanthocyanidins should be considered as important contributors to the total antioxidant capacity.

Limited research has been conducted on the metabolites present in the essential oils (EOs) of Phlomoides rotata (Benth. ex Hook. f.) Mathiesen (PR, syn. Lamiophlomis rotata (Benth.) Kudô), and their potential pharmacological activities, such as antioxidant properties, are often overlooked. We conducted a metabolomics-based screening to identify the characteristic metabolites (CMs) in the EOs extracted from PR. Meanwhile, we evaluated their in vitro antioxidant activities (AOAs). The EOs obtained through hydro-distillation are characterized by a light yellow color and a fresh, elegant fragrance. Cryoprecipitation was used to separate the crystals (Crs) from the EOs, resulting in the crystal-free EOs (CFs). A total of 121 components are identified and quantified in the EOs, Crs, and CFs. Among them, 84 were reported for the first time from such EOs. The major compounds include long-chain fatty acids (LCFAs) and their esters, such as palmitic acid (PA), myristic acid (MA), linoleic acid (LA), oleic acid (OA), stearic acid, and methyl palmitate (MP). Furthermore, 11 kinds of apocarotenoids (also called norisoprenoids) were first systematically investigated. Among them, eight C13-norisoprenoids, with trans-β-damascenone (DN) being particularly notable for its flavor, were identified. A sum of 11 CMs are screened , including PA, MA, LA, OA, MP, hexahydrofarnesyl acetone, phytol (PT), DN, stearic acid, linalool, and hexanal. These CMs are biosynthesized through FAs and 2-C-Methyl-D-erythritol 4-phosphate/1-Deoxy-D-xylulose 5-phosphate pathways. The in vitro AOAs of EOs, Crs, CFs, and seven selected CMs (PA, MA, LA, OA, MP, PT, and DN) were evaluated. Generally, PA and MA exhibited pro-oxidant activities (POAs) or weak AOAs. LA and OA demonstrated POAs or weak AOAs at lower concentrations, but at higher concentrations, they displayed medium to strong AOAs. Importantly, the CFs typically exhibited stronger AOAs compared to the corresponding EOs and Crs, potentially due to variations in their PA content. Overall, this study provides valuable insights into the potential utilization of EOs from PR.

The pollution of the bays in Abidjan is a major concern for the Ivorian policy makers. In fact, the pollution of the bays induce high costs to the society while impacting population health dramatically. As a result, pollution reduction management of production activities has been undertaken in the Cocody Bay area. To our knowledge, no study has yet proposed a model to evaluate the cost-effectiveness of these pollution management strategies. A cost-effectiveness model, based on Monte Carlo simulation, was developed to assess the economic and environmental impacts of various scenarios characterized by a set of production practices, both in the short term and in the long term. The authors discuss the steps and input parameters of the model presented. The proposed model may serve as the basis for identifying an optimal production scenario defined as the scenario with the best incremental cost-effectiveness ratio considering a willingness to pay (WTP) threshold. The WTP, to be estimated based on the gross domestic product of Côte d’Ivoire, represents the opportunity costs associated with selecting the optimal scenario. The current framework can also be applied to other settings facing similar challenge.

Kininogens are multidomain glycoproteins found in the blood of most vertebrates. They are important in the blood coagulation cascade pathways - in intrinsic pathway activation leading to thrombin generation partially independently from tissue factor dependent extrinsic pathway, connecting blood coagulation with the kallikrein-kinin system. Nothing is known about the shape on atomic level therefore the endeavor to obtain the good-quality spatial structure of kininogens is important for a better understanding of their role in disease and treatment. Application of cryo-EM is important for solving the spatial structure of kininogens, drawing new frontiers in understanding the function and opening new pathways for drug development.

This study analyses regional development in one of the poorest provinces in China, Guizhou Province, between 2000 and 2012 using a multiscale and multi-mechanism framework. In general, regional inequality has been declining since 2000. In addition, economic development in Guizhou Province presented spatial agglomeration and club convergence, which shows how the development pattern of one core area, two-wing areas and a contiguous area at the edge of the province have been developed between 2006 and 2012. Multilevel regression analysis revealed that industrialization and investment level were the primary driving forces of regional economic disparity in Guizhou Province. The influences of marketization and decentralization on regional economic disparity were relatively weak. Investment level reinforced regional economic disparity and the development of core-periphery structure in the province. However, investment level actually weakened the regional economic disparity in Guizhou Province when the variable of time was considered. In addition, both the topography and urban–rural differentiation were the two main reasons for forming a core-periphery structure in Guizhou Province.

Ozonated oil has several benefits for humans, as it contributes to numerous interventions, maintaining the quality of life and the well-being of individuals. Being a natural product, it has few or almost no side effects. Thus, the study aimed to verify the sensitivity and/or resistance of fixed o “Ozonated” and “Non-Ozonated” oils from Mauritia flexuosa (Buriti), Carapa guaianensis (Andiroba) and essential “Ozonated” oils from Menta piperita (Mint), Eugenia caryophyllus (Clove) in different concentrations, against internationally known bacteria from the American Type Culture Collection – ATCC, comparing with the “Non-Ozonated” versions of the respective oils, using the Agar diffusion technique. Thus, it is evident that the ozonation of the fixed oils of Buriti and Andiroba, as well as the essential oils of Mint and Clove, provided significant results, although they were statistically different. The Buriti and Andiroba oil were ineffective in inhibiting microorganisms. On the other hand, the essential oil of Mint and Clove obtained similar activity of inhibition of microorganisms. With regard to Ozonation, the Essential Oil of “Ozonated” Clove provided greater activity than the “Non-Ozonated” one, which inhibited only one tested microorganism, in addition to producing changes in its chemical composition, requiring individualized studies for the ozonation of each essential oil.

We proposed a deep learning based chemometric data analysis technique. We trained L2 regularized sparse autoencoder end-to-end for reducing the size of the feature vector to handle the classic problem of curse of dimensionality in chemometric data analysis. We introduce a novel technique of automatic selection of nodes inside hidden layer of an autoencoder through pareto optimization. Moreover, linear regression, ϵ-SVR , and Gaussian process regressor are applied on the reduced size feature vector for the regression. We evaluated our technique on orange juice and wine dataset and results are compared against state-of-the-art methods. Quantitative results are shown on Normalized Mean Square Error (NMSE) and the results show considerable improvement in the state-of- the-art.

Densely urbanized areas, with a low percentage of green vegetation, are highly exposed to Heat Waves (HW) which nowadays are increasing in terms of frequency and intensity also in the middle-latitude regions, due to ongoing Climate Change (CC). Their negative effects may combine with those of the UHI (Urban Heat Island), a local phenomenon where air temperatures in the compact built up cores of towns increase more than those in the surrounding rural areas, with significant impact on the quality of urban environment, on citizens health and energy consumption and transport, as it has occurred in the summer of 2003 on France and Italian central-northern areas. In this context this work aims at designing and developing a methodology based on aero-spatial remote sensing (EO) at medium-high resolution and most recent GIS techniques, for the extensive characterization of the urban fabric response to these climatic impacts related to the temperature within the general framework of supporting local and national strategies and policies of adaptation to CC. Due to its extension and variety of built-up typologies, the municipality of Rome was selected as test area for the methodology development and validation. First of all, we started by operating through photointerpretation of cartography at detailed scale (CTR 1: 5000) on a reference area consisting of a transect of about 5x20 km, extending from the downtown to the suburbs and including all the built-up classes of interest. The reference built-up vulnerability classes found inside the transect were then exploited as training areas to classify the entire territory of Rome municipality. To this end, the satellite EO HR (High Resolution) multispectral data, provided by the Landsat sensors were used within a on purpose developed "supervised" classification procedure, based on data mining and “object-classification” techniques. The classification results were then exploited for implementing a calibration method, based on a typical UHI temperature distribution, derived from MODIS satellite sensor LST (Land Surface Temperature) data of the summer 2003, to obtain an analytical expression of the vulnerability model, previously introduced on a semi-empirical basis.

Several plant species produce mixtures of odorous and volatile compounds known as essential oils (EOs). These mixtures play important roles in nature and have been utilized by man for pharmaceutical and agrochemical purposes. There are more than 3000 EOs reported in the literature with approximately 300 having commercial use, including the oils from Eucalyptus species. Such oils are rich in monoterpenes and have found applications as pharmaceuticals, agrochemicals, food flavorants and in the perfume industry. Such applications are related to their diverse biological and organoleptic properties. In view of their importance, we review in this article up to date information concerning chemical composition and biological activities of essential oils from different species of Eucalyptus. Among the 900 species and subspecies of the Eucalyptus genus¸ we examined 68 species. The studies associated with these species were conducted in 27 countries. We have focused on the antimicrobial, acaricide, insecticide and herbicide activities, hoping that such information will contribute in the advances of the research in this field. It is also intended that the information herein described can be useful in the rationalization of the use of Eucalyptus EOs as components for new pharmaceutical and agrochemical applications as well as food preservatives and flavorants.

Essential oils are mixtures of compounds obtained from plants, including flowers, roots, bark, leaves, seeds,peel, fruits, wood, that have risen up in the last decades thanks to their beneficial properties as antibacterial, antifungal and anti-inflammatory agents. The aim of this study was to characterize and analyze 13 different commercial essential oils with two different techniques. The first is GC-MS, coupled with SPME, thanks to which 204 different VOCs have been identified. The results show that a total of 95 compounds was found only in one oil, while the others were found with different frequencies in many of them. The most represented class is that of terpenes, as widely reported in literature. The second technique is based on an array of chemical gas sensors. This system was used to investigate whether sensors are able to identify these products. It turned out that basil, cinnamon and carnation are the most identifiable oils with different number and typology of sensors, especially tin oxide and copper oxide nanowires, while cayeput and thyme are more mistakable samples. Thanks to this detailed study, it has been possible to reach and obtain novel insights for the future development of this type of research.

Many medicinal plants and their essential oils are used to treat or prevent diseases without the risk of mutagenicity, carcinogenicity, or teratogenicity. Eucalyptus essential oils are commonly used as preservatives, flavoring agents, and in various consumer goods. Eucalyptus leaves are being widely studied due to their volatile essential oils, including 1,8-cineole, p-cymene, α and β-pinene, limonene, citronellal, citral, eudesmol, terpinen-4-ol, terpineol, α–phellanderene, and 9β-sitosterol. Among these compounds, 1,8-cineole is the most abundant. Eucalyptus leaves are rich in flavonoids and phenolic compounds and are thus a great source of antioxidants. 2,2-diphenyl-1-picrylhydrazyl (DPPH), Ferric Reducing Antioxidant Power (FRAP), and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays are used to measure antioxidant capacity. The antioxidant activity of Eucalyptus essential oil is stronger than that of standard antibiotics like Erythromycin, Cefixime, and Gentamicin due to the presence of significant terpenoids in addition to phenolic chemicals and flavonoids. The lower the IC₅₀ value, the higher the antioxidant potential. Phenolic compounds and flavonoids are often associated with beneficial health outcomes, including anti-inflammatory and antioxidant effects, anti-cancer properties, reduced risk of cardiovascular diseases, prevention of age-related neurodegenerative diseases, and prevention of Alzheimer’s disease. Flavonoids also play an essential role in plants, including protecting against reduction, fertility, reproduction, and infection. Due to their anti-inflammatory, anti-oxidative, and immune-modulatory properties, flavonoids are crucial for pharmacological, medical, and nutraceutical applications.

The prevalence of diabetes mellitus (DM), considered one of the most common metabolic disorders, has dramatically increased and resulted in higher rate of morbidity and mortality around the world, in the past decade. It is well known that insulin resistance in target tissues and a deficiency in insulin secretion from pancreatic β-cells are the main characteristic of type 2 diabetes. The aim of this study was the bio-evaluation of compounds isolated from three selected plant species; namely, Salvia africana-lutea, Leonotis ocymifolia and Plectranthus madagascariensis, for their glucose uptake ability. Methanolic extracts were produced from the arterial part of each plant. Compounds were identified using different spectroscopic techniques. The glucose uptake ability of each compound was then evaluated in mammalian cells using 2-deoxyglucose-6-phosphate. The cytotoxicity of each compound was established via the MTT assay. Chromatographic purification of the three plant species yielded fifteen pure terpenoids. Compounds 1 (p = 0.0031), 8 (p = 0.0053), and 6 (p = 0.0086), showed a marked increase in glucose uptake, with p values of p=0.0031, p=0.0053 and p=0.0086, respectively. Additionally, 1, 4 and 6 exhibited cytotoxicity toward mammalian tissue with a decrease in cell viability of ~70%, ~68% and ~67%, respectively. The results suggested that several compounds demonstrated a marked increase in glucose uptake while two of the compounds exhibited signs of cytotoxicity. It may, therefore, be suggested that these compounds be considered as potential candidates for novel plant-derived alternative therapies in the treatment of type 2 diabetes.

Tablets are the most used solid dosage form in medical treatments. The realistic modeling 1 of such specific object shapes in computer simulations has been demonstrated already by the author 2 for bi-convex round tablets but needs to be extended for a wider range of tablet shapes. Moreover, 3 the number of tablets must be large enough to simulate industrial drum coaters, which are typically 4 used for film coating processes. Whilst this long lasting process where tablets flow continuously, 5 tablets are loaded by frequent changes of individual contacts. Using a tailored simulation tool named 6 pharmAssist , written for GPUs (modern massively parallel processors in graphics cards and HPC 7 accelerators), we implemented the widely used oblong tablet shape. We are able to simulate flows 8 involving industrial scale number of such tablets. Data mining allows for statistical analyzis of 9 pair-wise contacts of different geometric features. Our simulation results serves as an observation 10 space, which cannot be addressed by experimental analyzis and will help to avoid degradation of 11 tablets like chipping or other defect phenomena. This paper reflects current development work in 12 order to extend the DEM with a new shape class, which comprises the modelling of compacted or 13 extruded objects, which have a smooth exterior, a flat band and sharp contour edges

In this paper we describe a method which combines sentiment analysis with machine learning techniques and/or multivariate statistical analysis. By applying this methodology it is possible to classify a collection of texts into two or more groups or clusters. On the basis of a number of previously defined clusters, the novelty of the outlined approach is the use of the sentiment analysis results as input to the machine learning model or multivariate statistical analysis. Once the classifier has been obtained, we can assign a given text into one of the pre-established clusters. The groups or clusters can represent different time periods, classes of texts transcribed from different conversations, etc. The method is illustrated through an example taken from one of the two studies in which we have applied this methodology. In one of the studies, the method was used to classify press news of a volcanic eruption, while in the other study it was used to classify the conversations recorded between a chatbot with different kinds of speakers (humans or chatbots). This last study was the seminal work in which we introduced this methodology.

World health is increasingly threatened by the growing number of spice-related food hazards. Further development of reliable methods for rapid, non-targeted identification of counterfeit ingredients within the supply chain is needed. ENEA has developed a portable, user-friendly photoacoustic laser system for food fraud detection, based on a quantum cascade laser and multivariate calibration. Following a study on the authenticity of saffron, the instrument was challenged with a more elusive adulterant, olive leaves in oregano. The results show that the reported method of laser sensing and chemometric analysis was able to detect adulterants at mass ratios of at least 20% in less than five minutes.

This study aimed to screen the antibacterial activity of essential oils from different parts (leave and stem) of Salvia officinalis against some Gram positive and Gram negative bacteria using agar disc diffusion test, then the extracts were prepared by hydro distillation to extract the essential oils. Maceration and hexane extraction by Soxhlet were used to obtain crude extracts from the leave and stem. Essential oils from the leaves and the ethyl acetate extract of the leaves showed higher antimicrobial activity, while hexane extract of leaves and stems showed moderate antibacterial activity. In contrast the essential oil from the stems showed very low antibacterial activity. It was observed that the results gram positive bacteria (staphylococcus aureus) was more sensitive than Gram negative (Echerichia coli).

Chemical variability in the components of T. vogelii essential oils from eastern Uganda was identified using principal component analysis (PCA) and Agglomerative hierarchical clustering (AHC). Based on the profiles of the compounds of farnesene family three chemotypes were found: farnesol (chemotype 1), springene (β- Springene and α-Springene) and the β-Farnesene were distinctive in chemotype 2 and a mixed variety of farnesol and the Springene. In the three cases, alkybenzenes; o-xylene, m-xylene and ethylbenzene were significant components in the oil. 1,4-dihydroxy-p-menth-2-ene, 5,9-undecadien-2-one, 6,10-dimethyl, and 3-cyclohexen-1-carboxaldehyde,3,4-dimethyl were other prominent constituents. The yields of the essential oils did not vary significantly however the chemical composition varied with harvesting time during the rainy and dry seasons. In choice repellency tests, chemotype 1 and chemotype 2 were more active against Sitophilus zeamais than mixed chemotype. Farnesol was found to be effective only at a higher concentration as a repellent against S. zeamais. However, further study that aims to optimize and standardize the varieties and harvesting period needed for recommendation to smallhold farmers.

Capsule endoscopy (CE) has been a widely used medical imaging tool for the diagnosis of gastrointestinal tract abnormalities like bleeding. But the CE captures a huge number of image frames that are time-consuming and tedious tasks for medical experts to diagnose manually. To address this issue, researchers focused on the computer-aided bleeding detection system to identify bleeding automatically in real-time. This paper presents a systematic review of the available state-of-the-art computer-aided bleeding detection algorithms for capsule endoscopy. The review was carried out by searching five different repositories: Scopus, PubMed, IEEE Xplore, ACM Digital Library, and ScienceDirect for all original publications on computer-aided bleeding detection published between 2001 and 2021. The PRISMA methodology was used to perform the review, and 112 full-texts of scientific papers were reviewed. The contributions of this paper are I) a taxonomy for computer-aided bleeding detection algorithms for capsule endoscopy is identified, II) the available state-of-the-art computer-aided bleeding detection algorithms including various color spaces (RGB, HSV, etc.), feature extraction techniques, and classifiers are discussed, and III) identify the most effective algorithm for practical use cases. Finally, the paper is concluded by providing future direction for computer-aided bleeding detection research.

The leaf essential oils from five Eucalyptus spp.: E. astringens, E. camaldulensis, E. lehmanii, E. leucoxylon and E. sideroxylon growing in the same plantation area and conditions (plants with the same age and subjected to the same agronomic practices) were analyzed and evaluated for their antimicrobial activity. The essential oil yields ranged from 0.14 to 0.96% (w/w), and their chromatographic profiles were resolved into 48 compounds; among them, 11 were common to all essential oils. Terpenoids (oxygenated mono, and sesquiterpenes) dominated (55.66-76.67%) the oil profiles. Although 1,8-cineole (21.97-50.93%) was found as the main oxygenated monoterpene in all examined essential oils, principal component analysis observed and confirmed an interspecific chemical variability. Additionally, a set of distinctive chemical markers that could serve as a reliable tool for discrimination of Eucalyptus species and for authentication and quality control purposes (for commercial samples) has been defined for each essential oil. The antimicrobial disc-diffusion assay results revealed that all essential oils were endowed with a strong antimicrobial activity, with those derived from E. camaldulensis, E. lehmanii and E. leucoxylon being the most active.

Altitude is an important ecological factor that significantly affects essential oil content, yield and composition. The Origanum majorana, belonging to Origanum genus of Lamiaceae family, is a species with antibacterial and antiviral effects, widely used as a spice and also used in folk medicine for treatment of diseases such as asthma, indigestion, headache and rheumatism. In this study, conducted to examine the effects of altitude on essential oil content and composition of origanum majorana, plant samples were collected from the southern region of Turkey at the beginning of flowering period from seven different altitudes (700-800 m, 800-900 m, 900-1000 m, 1000-1100 m, 1100-1200 m, 1200-1300 m and 1300-1400 m) at 100 m intervals. The highest percentage of essential oil (6.50%) obtained by hydro-distillation was determined at 700-800 m altitudes. The GC-MS analyses revealed that low altitude affected some essential oil components positively. The linalool ratio, which is the major component of the essential oil of Origanum majorana species, was the highest at 700-800 m (79.84%) altitudes. Borneol (0.97%), linalool oxide (1.28%), trans-linalool oxide (1.47%), caryophyllene (2.78%), a- humulene (0.21%), germacrene-D (0.31%) and bicyclogermacrene (2.64%) components yielded high values at 800-900 m altitudes. Thymol (6.28%) and a-terpineol (1.04%), which have an important place in the essential oil composition, increased at 1100-1200 m altitudes; a- terpinene (0.17%), cis-sabinene hydrate (0.82%), terpinene-4-ol (0.55%) and carvacrol (21.50%) increased at 1300-1400 m altitudes.

Organic wastes and by-products from several activities, including food industries, farming, and animal husbandry, are a hygiene threat when aerobically decomposed. Therefore, their manage-ment is crucial for public health. In this direction, anaerobic digestion (AD) systems may be the solution by transforming waste into energy, which may decrease the environmental impact. However, their efficacy should be carefully examined. In this innovative study, we evaluated the physicochemical and microbial characteristics of liquid digestate (LD) retrieved from organic animal wastes in northern Greece using nanofiltration. Using treatment technologies including physical (solid-liquid separation, microfiltration and nanofiltration) and biological (anaerobic digestion), heavy metals and microbial (i.e., Salmonella spp., Escherichia coli, Enterococcus faecalis) concentrations reduced and nutrients were recovered. This work sets the basis for the efficient management of liquid digestate. Our method may enable the use of treated liquid digestate for unlimited irrigation water and other industrial applications of water. Apart from the sanitation process, the recovery of nutrients for soil fertilization seems to be a more sustainable way for fu-ture agricultural practices.

Bacteriophages (phages) are potential alternatives to chemical antimicrobials against pathogens of public health significance. Understanding the diversity and host specificity of phages is important for developing effective phage biocontrol approaches. Here, we assessed the host range, morphology, and genetic diversity of eight Salmonella enterica phages isolated from a wastewater treatment plant. The host range analysis revealed that six out of eight phages lysed more than 81% of the 43 Salmonella enterica isolates tested. The genomic sequences of all phages were determined. Whole genome sequencing data (WGS) data revealed that phage genome sizes ranged from 41 to 114 kb with GC contents be-tween 39.9 and 50.0 %. Two of the phages SB13 and SB28 represent new species Epsep-timavirus SB13 and genera Macdonaldcampvirus, respectively as designated by the In-ternational Committee for the Taxonomy of Viruses (ICTV) as per genome based taxonomic classification. One phage (SB18) belonged to the Myoviridae morphotype while the re-maining phages belonged to the Siphoviridae morphotype. The gene content analyses showed that none of the phages possessed virulence, toxin, antibiotic resistance, type I-VI toxin-antitoxin modules or lysogeny genes. Three (SB3, SB15 and SB18) out of the eight phages possessed tailspike proteins. Whole genome-based phylogeny of the eight phages with their 113 homologs revealed three clusters A, B, C and seven subclusters (A1, A2, A3, B1, B2, C1 and C2). While cluster C1 phages were predominantly isolated from animal sources, cluster B contained phages from both wastewater and animal sources. The broad host range of these phages highlights their potential use to control the presence of S. enterica in foods.

Since the outbreak of the COVID-19 pandemic, patients infected with COVID-19 may experience abnormal heart rates, posing potential health risks. This study proposes a non-contact method for measuring heart rate (HR) and heart rate variability (HRV) to effectively reduce the risk of infection and assist healthcare professionals in more accurate diagnosis and treatment. In this study, except for the different image acquisition method, other research processes and methods are similar to the research methods in [15]. The image acquisition method is changed from forehead image to palm image. The new non-contact measurement performance of the proposed method can effectively not only avoid infection concerns but also obtain heart rate and HRV quickly and conveniently, providing higher accuracy for physiological parameters, root mean square error (RMSE), and mean absolute percentage error (MAPE) compared to those in recently published papers.

This study aims to examine the non-volatile Particle Number (PN) emissions of a retrofitted Heavy-Duty Spark-Ignition (HD-SI) engine powered by liquefied petroleum gas (LPG) under both steady-state and transient conditions. The engine was tested under seven steady-state operating points to investigate the PN behavior and Particle Size Distribution (PSD) upstream and down-stream of the Three-Way Catalyst (TWC). This analysis intends to assess the impact of including particles with diameters ranging from 10 nm to 23 nm in the total particle count, a consideration for future regulations. The study employed the World Harmonized Transient Cycle (WHTC) for transient conditions to encompass the same engine working region used in the steady-state analysis. A Dekati FPS-4000 diluted the exhaust sample to measure the PSD and PN for particle diameters between 5.6 nm and 560 nm using the TSI-Engine Exhaust Particle Sizer (EEPS) 3090. Findings indicate that PN levels tend to increase downstream of the TWC under steady-state conditions in operating points with low exhaust gas temperatures and flows (equal to or less than 500 °C and 120 kg/h). Furthermore, the inclusion of particles with diameters between 10 nm and 23 nm leads to an increase in PN emissions by 17.70% to 40.84% under steady conditions and by an average of 40.06% under transient conditions, compared to measurements that only consider particles larger than 23 nm. Notably, in transient conditions, most PN emissions occur during the final 600 seconds of the cycle, linked to the most intense phase of the WHTC.

In the present study the effects of Origanum onites L. extract and essential oil of O. onites L. on the antioxidant status of the liver and brain of mice were investigated. Due to certain disadvantages of essential oils, such as poor solubility, high volatility, sensitivity to UV light and heat, formulation of liposomes with Oregano essentials (OE) was optimized and used in this study. The results demonstrated that the best composition of the lipid carriers and Oregano essentials were conducted in terms of the PDI, mean particle size and EE. The LE4 formulation contained Lipoid S100 of 45 mg, Lipoid S75 of 45 mg and 90 mg of EO. The administration of O. onites L. extract to mice for 21 days significantly decreased glutathione (GSH) level in the liver and brain of mouse as well as malondialdehyde (MDA) concentration in the liver. In the brain of mice MDA level significantly increased after this extract consumption. Whereas liposomes with OE significantly decreased GSH concentration in mouse brain and MDA concentration in mouse liver but increased (p&gt;0.05) GSH level in liver and MDA concentration in brain of mice compared with the control group. It was investigated that both, O. onites L. extract as well as liposomes with OE of this plant material make changes in the antioxidant status in the liver and brain of mice.

The global consumption of vegan foods is experiencing an expressive upward trend, underscoring the critical need for quality control measures based on nutritional and functional considerations. This study aimed to evaluate the functional quality of caviar and salmon analogs food inks, based on pulses combined with nano ingredients. The primary objective of this work was to determine the total antioxidant compounds contained in these samples using a voltammetric technique with a glassy carbon electrode. Approximately 100 mg of samples underwent ethanolic extraction (70%) with 1 hour of stirring. The voltammograms were acquired under specific conditions: 10 mL of phosphate buffer electrolyte with a pH of 3.0; an initial potential (Ei) of 0.0 V; a final potential (Ef) of 1.0 V; a pulse amplitude of 50 mV; and a scan rate of 50 mV s-1. The reference electrode used was Ag/AgCl (KCl 3 mol L-1), and the auxiliary electrode was a platinum wire. The voltammograms revealed prominent anodic current peaks at 0.76-0.78 V, which are attributed to isoflavones. Isoflavones, known secondary metabolites with substantial antioxidant potential commonly found in pulses, were identified. The total isoflavone concentrations obtained ranged from 31.5 to 64.3 mg Eq genistein 100 g-1. The results not only validated the efficacy of the electrochemical sensor for quantifying total antioxidant compounds in the samples but also demonstrated that the concentration of total isoflavones in caviar and salmon analogs fell within the expected limits.

The present study aims to evaluate the antibacterial activity of five commercially available essential oils (EOs): Lavender (LEO), Clove (CEO), Oregano (OEO), Eucalyptus (EEO), and Peppermint (PEO) against the most-known MDR Gram-positive and Gram-negative bacteria - Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922) and Pseudomonas aeruginosa (ATCC 27853) - alone and in various combinations. Gas Chromatography-Mass Spectrometry (GC-MS) analysis established their complex composition. Then, the antibacterial activity was investigated in vitro by diffusimetric antibiogram method, using sterile cellulose discs with Ø 6 mm impregnated with 10 µl of sample and sterile borosilicate glass cylinders loaded with 100 µl of sample; MIC (µg/mL) for each EO was calculated from IZD values (mm) measured after 24 hours. The following EO combinations were evaluated: OEO+CEO, CEO+EEO, CEO+PEO, LEO+EEO, and EEO+PEO. Then, the influence of each dual combination on 3 conventional antibacterial drugs – Neomycin (NEO), Tetracycline (TET), and Bacitracin (BAC) - activity was investigated. The most active EOs against S. aureus and E. coli were LEO and OEO (IZD = 40 mm). They were followed by the CEO and EEO (IZD = 20-27 mm); PEO exhibited the lowest antibacterial activity (IZD = 15-20 mm). EEO alone showed the highest inhibitory activity on P. aeruginosa (IZD = 25-35 mm). It was followed by the CEO, LEO, and EEO (IZD = 7-11 mm), while PEO proved no antibacterial action against it (IZD = 0 mm). Only one synergic action was recorded (OEO+CEO against P. aeruginosa); EEO+PEO revealed partial synergism against S. aureus and CEO+PEO additive behavior against E. coli. Two triple associations with TET showed partial synergism against E. coli, and the other 2 ones (with NEO and TET) evidenced the same behavior against S. aureus; all contained EEO+PEO or CEO+PEO. Most combinations reported indifference. However, numerous cases were of antagonism between constituents included in double and triple combinations, and EOs with the strongest antibacterial activities belong to the highest antagonistic combinations. A consistent statistical analysis supports our results, showing that EOs with moderate antibacterial activities could generate combinations with higher inhibitory effects based on synergistic or additive interactions.

Cortex Periplocae, as a traditional Chinese herbal medicine, has been widely used for autoimmune diseases, especially rheumatoid arthritis. Due to its potential pharmaceutical values, more studies about the biological activities of Cortex Periplocae have been conducted recently. Meanwhile, the adverse reaction of Cortex Periplocae is not a negligible problem in clinic. In this article, we reviewed a series of articles and summarized the recent studies of Cortex Periplocae in the areas of phytochemistry and pharmacology. More than 100 constituents have been isolated and identified from Cortex Periplocae, including steroids, cardiac glycosides, terpenoids, and fatty acid compounds. The crude extracts of Cortex Periplocae and its active compounds exhibit various biological activities, such as cardiotonic effect, anticancer action, and anti-inflammatory effect. This paper aims to provide an overall review on the bioactive ingredients, pharmacological effect, and toxicity of this plant. Furthermore, this review suggests investigating and developing new clinical usages according to the above pharmacological effects.

Segmentation of brain tumor images is a major research topic in medical imaging to have a refined detection and understanding of abnormal masses in the brain. This paper proposes a new segmentation method, consisting of three main steps, to detect brain lesions using magnetic resonance imaging (MRI). In the first step, the parts of the image delineating the skull bone are removed to exclude insignificant data. In the second step, which is the main contribution of this study, the particle swarm optimization (PSO) technique is applied to detect the block that contains the brain lesions. The fitness function, used to determine the best block among all candidate blocks, is based on a two-way fixed-effects analysis of variance (ANOVA). In the last step of the algorithm, the K-means segmentation method is used in the lesion block to classify it as tumor or not. A thorough evaluation of the proposed algorithm is performed using the MRI database provided by the Kouba imaging center in Algiers, Algeria. Estimates of the selected fitness function are first compared to those based on the sum-of-absolute-differences (SAD) dissimilarity criterion and demonstrate the efficiency and robustness of the ANOVA. The performance of the optimized brain tumor segmentation algorithm is then compared to the results of several state-of-the-art techniques, including fuzzy C-means, K-means, Otsu thresholding, local thresholding, and watershed segmentation. The results obtained using Dice coefficient, Jaccard distance, correlation coefficient, and root mean square error (RMSE) measurements demonstrate the superiority of the proposed optimized segmentation algorithm over equivalent techniques.

While some research supports utilizing plain radiography for measuring biomechanical alignment of the spine for prognosis and treatment, there are contrasting viewpoints regarding both the value and utilization of these procedures in conservative care. Evaluation of both conservative and non-conservative approaches to spinal care revealed vast differences in radiographic utilization and interpretation between orthopedic surgeons, primary care physicians, chiropractic physicians, and physical therapists, which may account for the different viewpoints and rationale in the literature. A research summary is provided regarding the various methods of spinal analysis utilized by these professions to help determine if there is any unique diagnostic or prognostic value associated with radiographic utilization that could assist in advancing conservative spinal assessment and treatment. Understanding any unique value provided through biomechanical assessment utilizing plain radiography of the spine established in the literature may help chiropractic physicians determine the appropriate use of radiographic procedures in clinical practice and how to coordinate efforts with other conservative and non-conservative professions to improve spinal healthcare.

The present study examined the volatile composition and antimicrobial and gastrointestinal activity of the essential oils of Elettaria cardamomum (L.) Maton harvested in India (EC-I) and Guatemala (EC-G). Monoterpene were present in higher concentration in EC-I (83.24%) than in EC-G (73.03%), whereas sesquiterpenes were present in higher concentration in EC-G (18.35%) than in EC-I (9.27%). Minimum inhibitory concentrations (MICs) of 0.5 and 0.1 mg/mL were demonstrated against Pseudomonas aeruginosa in EC-I and EC-G, respectively, whereas MICs of 0.125 and 1 mg/mL were demonstrated against Escherichia coli in EC-I and EC-G, respectively. The treatment with control had the highest kill-time potential, whereas the treatment with oils had shorter kill-time. EC-I was found to be more potent in the castor oil-induced diarrhoea model than EC-G. At 100 and 200 mg/kg, EC-I exhibited 40% and 80% protection, respectively, and EC-G exhibited 20% and 60% protection, respectively, in mice, whereas loperamide (positive control) exhibited 100% protection. In the in vitro experiments, EC-I inhibited both carbachol (CCh, 1 µM) and high K+ (80 mM)-induced contractions at significantly lower concentrations than EC-G. Thus, EC-I significantly inhibited P. aeruginosa and E. coli and exhibited more potent antidiarrheal and antispasmodic effects than EC-G.

Principal Component Analysis (PCA) is a method that identifies common directions within multivariate data and presents the data in as few dimensions as possible. One of the advantages of PCA is its objectivity, as the same results can be obtained regardless of who performs the analysis. However, PCA is not a robust method and is sensitive to noise. Consequently, the directions identified by PCA may deviate slightly. If we can teach PCA to account for this deviation and correct it, the results should become more comprehensible. The methods for doing this and an issue with this are presented.

Soil moisture can be an important indicator of climate change in humid and semi-arid areas. This indicator can more efficiently propose different public policies related to climate change than just using precipitation and temperature data. Given the above, the objective of this study is to evaluate changes in soil moisture in the state of Pernambuco during the period 1961-2021, using the System of Hydrological Response Units for Pernambuco. In this study, two river basins in the state of Pernambuco that represent the different climatic conditions of the state will be chosen. The results show that in the coastal region, there is a tendency towards more saturated soils, and in the semi-arid region, there is a tendency towards drier soils. With these results, it is possible to conclude that public policy decisions for the economy, environment, and society must consider this vital water balance variable.

Since the discovery of transposable elements (TEs) in Maize in the 1940s by Barbara McClintock [1] transposable elements have been described as junk, as selfish elements with no benefit to the host, and more recently as major determinants of genome structure and genome evolution. TEs are DNA sequences that are capable of moving to new sites in the genome and make additional copies while doing so. To limit the propagation of TEs, host silencing mechanisms are directed at transposon-encoded genes that are required for mobilization. The mutagenic properties of TEs, the potential of TEs to form new genes and affect gene expression, together with the host silencing mechanisms shape eukaryotic genomes and drive genome evolution. While TEs constitute more than half of the genome in many higher eukaryotes, transposable elements in the nematode C. ele-gans form a relatively small proportion of genome, about 15% [2]. Genetic studies of transposon silencing and the discovery of RNAi in C. elegans, propelled C. elegans to the forefront of studies of RNA-based mechanisms that silence TEs. Here, I will review the transposable elements that are present and active in the C. elegans genome, and the host defense mechanisms that silence these elements.

Read-Across Structure-Activity Relationship (RASAR) is an emerging cheminformatic approach that combines the usefulness of a QSAR model and similarity-based Read-Across predictions. In this work, we have generated a simple, interpretable, and transferable quantitative-RASAR (q-RASAR) model which can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials. The data set involves 29 TiO2-based nanomaterials which contain specific amounts of noble metal precursors in the form of Ag, Au, Pd, and Pt. The data set was rationally divided into training and test sets and the Read-Across-based predictions for the test set were generated using the tool Read-Across-v4.1 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. The hyperparameters were optimized based on the training set data and using this optimized setting, the Read-Across-based predictions for the test set were obtained. The optimized hyperparameters and the similarity approach, which yields the best predictions, were used to calculate the similarity and error-based RASAR descriptors using the tool RASAR-Desc-Calc-v2.0 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. These RASAR descriptors were then clubbed with the physicochemical descriptors and were subjected to features selection using the tool Best Subset Selection v2.1 available from https://dtclab.webs.com/software-tools. The final set of selected descriptors was used to develop multiple linear regression based q-RASAR models, which were validated using stringent criteria as per the OECD guidelines. Finally, a random forest model was also developed with the selected descriptors. The final machine learning model can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials superseding previously reported models in the prediction quality.

Redundancy in ship systems is provided to ensure operational resilience through equipment backups which ensures system availability and offline repairs of machinery. The electric power generation system of ships provides the most utility of all systems, hence is provided with good level of standby units to ensure reliable operations. Nonetheless, the occurrence of undesired black outs are common onboard ships and portends a serious danger to ship security and safety. Therefore, understanding the contributing factors affecting system reliability through component criticality analysis is essential to ensure a more robust maintenance and support platform for efficient ship operations. In this regard hybrid reliability and fault detection analysis were conducted to establish component criticality and related fault conditions. A case study was conducted on a ship power generation system consisting of 4 marine diesel power generation plants onboard an Offshore Patrol Vessel (OPV). Results from the reliability analysis indicate overall low system reliability of less than 70 per cent within the first 24 months of the 78 operational months. Component criticality using reliability importance measures was used to identify all components with more than 40 per cent contribution to sub systems failure. Additionally, machine learning was used to aid the reliability analysis through feature engineering and fault identification using Artificial Neural Networks classification. The ANN has identified failure patten threshold at about 200kva which can be attributed to overheating, hence establishing link between component failure and generator performance.

State Forest Management Organizations (SFMOs) play a crucial role in the European forest sector, managing almost half the forests in the region. SFMOs are often managed for timber production only whereas, being publicly owned, they should play an important role in providing a vast range of public goods (e.g. soil protection, biodiversity conservation). Their management goals depend on the history and current conditions of the forest sector at a national level, as well as different challenges and the potential for development. Although there is a lack of knowledge about the current performance of SFMOs, there have been recent changes to their management goals and practices in response to the new demands expressed by society (e.g. transparency, social inclusion). The main purpose of this study is to analyse the current situation of SFMOs by clustering them according to indicators that reflect three pillars of the common understanding of sustainable forest management (SFM) concept. With the help of Principal Component Analysis (PCA), we grouped countries according to common characteristics of the forest sector at the national level. Results show three main clusters of SFMOs in Europe. The first cluster has rather small but commercially-oriented forestry unit together with other business activities and a strong focus on public services. The second sees itself as the protector of public interest, rather than commercially-oriented organisations. The third is mainly profit-seeking. The existence of diverse SFMO clusters shows the possibility of different approaches for SFM with a focus on different goals (e.g. profit gaining, public service delivery).

A compositional data vector is a special type of multivariate observation in which the elements of the vector are non-negative and sum to a constant, usually taken to be unity. A compositional data does not have zero and only retains relative information. Furthermore, comparisons can only be made between compositional data of the same component. The relevant sample space is the standard simplex. A simplex space is a space that is a generalized form of a triangle. For compositional data, many of the operations defined in Euclidean space are meaningless. Microbiome analyzes have become popular in recent years. Operational Taxonomic Units (OTU) and Amplicon Sequence Variants (ASVs) used in microbiome analysis are one type of compositional data. The microbiome data are counts of different species within a sample and it is compositional. Although there is an order of bacterial abundance within a sample, there is no order of bacterial abundance between samples. Firmicutes and Bacteroidetes, the major phyla in the colon, have been observed in humans worldwide. Gut microbiome analyses often use the Firmicutes/Bacteroidetes ratio and principal coordinates analysis (PCoA). Alpha and beta diversities are used as indicators of bacterial flora diversity. However, misinformation is pervasive in the human microbiome literature and analysis. There is a lot of misunderstanding regarding compositional data and its analysis. An attempt was made to demonstrate how to analyze using the “National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN JMD) (Public Data).” The results showed that PCoA did not work, and principal component analysis (PCA) was useful for analyzing the gut microbiome relative diversity.

Corrugated board is a composite material characterized by strong orthotropy in both the elastic and plastic phases. Additionally, due to its layered structure, which consists of alternately arranged flat and wavy layers of paper, its mechanics becomes complicated. Therefore, a precisely selected set of laboratory tests is needed to correctly identify all the necessary material parameters of cardboard. The work attempts to define a full set of laboratory tests in order to determine material parameters describing the linear-elastic, orthotropic behavior of cardboard and the basic parameters defining popular plasticity criteria, such as the asymmetric orthotropic Hoffman criterion. For this purpose, sensitivity analysis and numerical models of several selected basic laboratory tests were used. Since the aim of the work is to choose appropriate laboratory tests necessary to correctly determine the material parameters of corrugated board (not its individual layers), the numerical models do not contain detailed cardboard geometry, but only its homogenized representation in the form of the flat shell models. All numerical models are based on the nonlinear finite element method and constitutive modelling in the form of UMAT subroutines implemented in the ABAQUS software. Based on the analyses, appropriate measurements and laboratory tests were indicated that are most sensitive to the material parameters sought.

Essential oils (EOs) have great potential in inhalation therapy for the treatment of respiratory infections, however, innovative methods for evaluation of antimicrobial activity of their vapors are still needed. The current study reports validation of the broth macrodilution volatilization method for assessment of the antibacterial properties of EOs and shows growth-inhibitory effect of Indian medicinal plants against pneumonia-causing bacteria in liquid and vapor phase. Among all samples tested, Trachyspermum ammi EO exhibited the strongest antibacterial effect against Haemophilus influenzae, with minimum inhibitory concentrations of 128 and 256 µg/mL in the liquid and vapor phases, respectively. Furthermore, Cyperus scariosus EO was found to be non-toxic to normal lung fibroblasts were assessed by modified thiazolyl blue tetrazolium bromide assay. Chemical analysis performed using gas chromatography-mass spectrometry identified α-citral, cyperotundone, and thymol as the main constituents of Cymbopogon citratus, C. scariosus, and T. ammi EOs, respectively. In addition, β-cymene was identified as the major compound of T. ammi EO vapors when analyzed using solid-phase microextraction and gas-tight syringe sampling techniques. This study demonstrates the validity of the broth macrodilution volatilization method for antimicrobial screening of volatile compounds in the vapor phase and suggests the thera-peutic potential of Indian medicinal plants in inhalation therapy.

The AREB/ABF (ABA response element binding) proteins in plants are vital for plant stress responses, but the understanding of AREB/ABFs in orchid species, an important traditional medicinal and ornamental plants, is limited. Here, twelve AREB/ABF genes were identified within three orchids’ complete genome and classified into three groups (groups I, II, and III) via a phylogenetic analysis, which was further supported by the analysis of their conserved motifs and gene structures. The cis-elements analysis showed that hormone response elements followed by light and stress responses were widely rich in AREB/ABFs. A prediction analysis of orchid ABRE/ABF-mediated regulatory network was further constructed through cis-regulatory elements (CREs) analysis of their promoter regions and revealed that several transcriptional factor (TF) gene family were abundant as the potential regulators for orchid AREB/ABFs. Expression profile analysis based on public transcriptomic data showed that most AREB/ABF genes have distinct tissue-specific expression patterns in orchid plants. Additionally, DcaABI5 as the homolog of ABA INSENSITIVE 5 (ABI5) from Arabidopsis was selected for further analysis. The results showed that Arabidopsis transgenic overexpressing DcaABI5 could rescue the ABA insensitive phenotype in the mutant abi5. Collectively, these findings will provide valuable information on AREB/ABF genes in orchids.

Dermal penetration is considered to mainly occur via passive diffusion. Therefore, a high concentration gradient of dissolved active ingredient between formulation and skin is needed to achieve an effective dermal penetration. The concentration gradient between formulation and skin can be changed by changing the amount of dissolved active ingredient in the formulation. In case of poorly soluble active ingredients this can be achieved by using nanosized drug material instead of larger sized material. The smaller size and the resulting larger surface increase the kinetic solubility and thus increase the concentration gradient of dissolved active ingredient between formulation and skin, which then results in an increased dermal penetration. In this study we demonstrated that the concentration gradient between formulation and skin can also be influenced by the number of particles being present in the formulation and by the dose (volume of formulation) applied to the skin. Particles of undissolved active ingredient are known to act as a reservoir by releasing dissolved molecules in the liquid phase of the formulation. It could now be demonstrated that the particles - once the liquid in which they are dispersed evaporates - can connect to the skin via an aqueous meniscus. The aqueous meniscus contains dissolved active ingredient and therefore creates a small local spot with a locally high concentration gradient and improved dermal penetration. Therefore, the dermal penetration can be increased with formulations that contain high amounts of particles. This can be achieved by applying formulations with high numbers of particles and/or by applying larger volumes of particle containing formulations to the skin.

Centrifugal pumps are widely employed in the oil refinery industry due to their efficiency and effectiveness in fluid transfer applications. The reliability of pumps plays a pivotal role in ensuring uninterrupted plant productivity and safe operations. Analysis of failure history data shows that bearings have been identified as critical components in oil refinery pump groups. However, traditional reliability estimation theories may not apply when data is limited or subject to right censoring. This paper addresses the complexity of estimating the Weibull distribution parameters using the maximum-likelihood method under the abovementioned conditions. The likelihood equation lacks an explicit analytical solution, necessitating the use of numerical methods for resolution. The proposed approach presented in this article leverages the Expectation-Maximization (EM) algorithm for estimating the Weibull distribution parameters. This method provides more accurate estimates of failure rates and probabilities by accounting for limited and censored data. The findings are demonstrated through a case study, showcasing the practical application of the proposed approach.

Aspergillus flavus is a pathogenic fungus that affects and contaminates several foodstuffs and is associated with cancer in humans. In Senegal, significant losses of groundnut production are mainly due to contamination caused by this species. This study evaluated in vitro antifungal activities of Cyperus articulatus, Cyperus rotundus and Lippia alba essential oils against A. flavus isolated from peanut seeds. Essential oils obtained by hydrodistillation of rhizomes of the two Cyperus species and leaves of L. alba were analyzed by GC-DIF and GC-MS. The essential oil yields from C. articulatus, C. rotundus and L. alba were 1.1%, 1.3% and 1.7%, respectively. These three samples had the following chemotypes: (i) Mustakone (21.4%)/eudesma-4(15)-7-dien-1β-ol (8.8%)/caryophyllene oxide (5.9%), (ii) caryophyllene oxide (25.2%)/ humulene epoxyde 2 (35.0%) and (iii) geranial (46.6%)/neral (34.6%). The three oils tested inhibited the growth of A. flavus at concentrations between 100 and 1000 ppm. The L. alba oil was the most effective with total clearance of A. flavus on PDA. For the essential oils of C. rotundus (93.65%) and C. articulatus (78.11%), the highest inhibition rates were obtained with 1000 ppm dose. Thus, the L. alba oil could be used safely as an effective protector of groundnuts against A. flavus.

Analyzing big data poses a great challenge for numerous researchers to explore the data structure. Dimension reduction methods can be used to reduce data dimensionality, taking it from occupying a high-dimensional space to existing in a lower-dimensional space while retaining as much information as possible. Principal Component Analysis is one of the most popular used to reduce the dimensional space. The bootstrap sample is obtained by randomly sampling n times with replacement from the original sample, the method provides easy tool to understand the interactive component and develop the process. There are not enough researches discussed the stability of PCA method using bootstrap method. In this paper, the bootstrap method is used to analyze the stability of PCA results and to estimate the number of PCA in efficient way. The method is used to estimate the number of PCA that needed to classify the data set, and the effectiveness of the discussed techniques is demonstrated through real data sets.

This study focuses on the potential medicinal properties of Campsis radicans L. extracts and its aim is to investigate the antioxidant and antiproliferative effects of these extracts on the human colon adenocarcinoma cell line (HT-29). Cytotoxic activity in the HT-29 cell line was evaluated, and the 3-dimensional structures of phenolic compounds were obtained using the GC-MS method. Docking simulations were performed with AutoDock Vina, targeting proteins that are crucial in the apoptotic pathway (Bax, Bcl-2, and Caspase-3). Drug similarities and ADMET estimates of the phenolic compounds were obtained from databases. The highest antioxidant activity of Campsis radicans L. plant was observed in ethanol and water extracts, with notable inhibition capacities. While the total phenolic content was highest in ethanol, water, and ether extracts respectively the total flavonoid content was highest in ethanol, then ether, and water extracts. Certain elements were undetectable in mineral determination, and others exceeded the toxic doses for plants. The water extract exhibited dose-dependent cytotoxic activity in the HT-29 cell line, with an IC50 value of 4.47 mg/mL. Molecular docking results revealed the binding of phenolic molecules to the active sites of apoptotic pathway proteins. The findings suggest that Campsis radicans L. plant possesses cytotoxic properties, significant phenolic and flavonoid content, and a high antioxidant capacity. These properties make it a potential candidate for treatment use, emphasizing its potential therapeutic value in the HT-29 cell line. Further research and exploration on the identified phenolic compounds could contribute to the development of novel therapeutic agents.

The pentose phosphate pathway (PPP) is one of three major pathways involved in glucose metabolism, regulated by glucose-6-phosphate dehydrogenase (G6PD), controlling NADPH formation. NADPH, in turn, regulates the balance of oxidative stress and reactive oxygen species (ROS) levels. G6PD dysfunction, affecting PPP, is implicated in neurological disorders, including epilepsy. However, PPP's role in epileptogenesis and ROS production during epileptic activity remains unclear. To clarify these points, we conducted electrophysiological and imaging analyses on mouse hippocampal brain slices. Using the specific G6PD inhibitor G6PDi-1, we assessed its effects on mouse hippocampal slices, examining intracellular ROS, glucose/oxygen consumption, and ROS production during synaptic stimulation and in the 4AP epilepsy model. G6PDi-1 increased basal intracellular ROS levels and reduced synaptically induced glucose consumption but had no impact on ROS production from synaptic stimulation. In the 4AP model, G6PDi-1 didn't significantly alter spontaneous seizure frequency or H2O2 release amplitude but increased the frequency and peak amplitude of interictal events. These findings suggest that short-term PPP inhibition has a minimal impact on synaptic circuit activity.

Cambodian spices Amomum kravanh, Citrus hystrix and Piper nigrum 'Kampot' have long history of seasoning of food products. In this study, essential oils (EOs) and supercritical CO2 extracts from all three species have been analyzed using GC-MS with two columns of different polarity, whereas EO and CO2 extract from P. nigrum fruits and CO2 extract from the peel of C. hystrix have been isolated and analyzed for the first time. The results showed that A. kravanh EO contained mostly eucalyptol (78.8/ 72.6 %), while CO2 extract was rich in oleic acid (29.26 %) and tricosane (14.74 %). C. hystrix EO was rich in β-pinene (29.95/29.45 %), followed by D-limonene (24.54/23.24 %) and sabinene (9.94/10.23 %). β-pinene (30.2/28.9 %), D-limonene (23.99/23.74 %) and sabinene (13.36/19.55 %) were also predominant in the CO2 extracts. β-Caryophyllene was the main constituent of both EO and CO2 extract from P. nigrum 'Kampot' with contents ranging from 37.84 to 55.84 %, followed by 3-carene (from 7.18 to 18.72 %). Such findings suggest that supercritical CO2 can potentially be used for extraction of all three Cambodian spices. Nevertheless, further research determining the most efficient extraction parameters will be needed before its application in the spice processing practice.

Heat stress affects the yield of medicinal plants and can reduce biomass and/or metabolite production. In order to evaluate the effect of heat-induced stress on the essential oil production in Mentha x piperita L. var. Mitcham (Mitcham mint) and Mentha x arvensis var. piperascens Malinv. ex L. H. Bailey (Japanese mint), we studied the chemical composition of the oils of the two mint species under different heat shock stress in growth chambers. The antibacterial activity of the essential oils was also evaluated; microscopic observation (fluorescence and electron transmission) was used to assess the effect of the tested samples on bacterial growth. The results obtained shed light on the mint essential oils composition and biological activity in relation to heat stress.

The development of low-cost, open-source Remotely Operated Vehicle (ROV) systems has provided almost unrestricted access for researchers looking to monitor the marine environment in ever greater resolution. Sampling microbial communities from the marine environment, however, still usually relies on Niskin-bottle sampling (ROV or CTD based), a method which introduces an inaccuracy and variability that is incompatible with metatranscriptomic analysis. Here, we describe a versatile, easily-replicated platform which achieves in situ mRNA preservation, via the addition of RNAlater to filtered microbial cells, to enhance ROV or CTD functionality.

The physiological characteristics of liquid digestate retrieved from various biogas plants based in northern Greece are presented. Preliminary photocatalysis experiments on inoculated liquid di-gestate sampled showed that disinfection is possible when pre-treated digestate with a combination of centrifuge-flocculation-μFiltration after 5.5 hours of 0.7g/L suspended TiO2 under UVA illumination for the experimental conditions is used. A novel design photocatalytic nanofiltration reactor was implemented for disinfection experiments on pre-treated liquid digestate, giving promising results. This work sets the basis for the efficient operation and engineering application of technology collaboration with photocatalysis as the final step for liquid digestate sanitation and reusable water recovery.

Accurate analysis of continuous-wave electron spin resonance (cw ESR) spectra of biological or organic free-radicals and paramagnetic metal complexes is key to understand their structure-function relationships and electrochemical properties. Current method of analysis based on simulations often fail to extract the spectral information accurately. In addition, such analyses are highly sensitive to spectral resolution and artifacts, users’ defined input parameters and spectral complexity. We introduce a simulation-independent spectral analysis approach that enables broader application of ESR. We use a wavelet packet transform-based method for extracting g values and hyperfine (A) constants directly from cw ESR spectra. We show that our method overcomes the challenges associated with simulation-based methods for analyzing poorly / partially resolved and unresolved spectra, which is a common in most cases. The accuracy and consistency of the method are demonstrated on a series of experimental spectra of organic radicals and copper-nitrogen complexes. We showed that for a two-component system, the method identifies their individual spectral features even at a relative concentration of 5% for the minor component.

Currently, algae arouse a growing interest in the pharmaceutical and cosmetic area due to the fact that they have a great diversity of bioactive compounds with the potential for pharmacological, cosmetic, and nutraceutical applications. Many of these bioactive compounds are secondary metabolites whose amounts in the algae vary with varying environmental conditions. Free radicals and other active oxygen derivatives are recognized as a natural by-product of aerobic metabolism. However, reactive oxygen species directly participate in mechanisms related to various pathological states such as cancer, diabetes, atherosclerosis, Alzheimer's, and Parkinson's, among others. Diabetes mellitus (DM) is a metabolic disease resulting from changes in glucose metabolism and/or deficient production/action of insulin. This review has as its main objective to reveal the potential antioxidant and antidiabetic capacity of algae extracts.

Omega-3 fatty acids (ω-3 FAs) are important fatty acids having the beneficial roles in human health including reducing blood pressure, lowering the risk of cardiovascular disease and exerting anti-inflammation activities. Omega-3 FAs were mainly found in fish oils, therefore, determination of these FAs is very important. This study highlighted the employment of FTIR spectroscopy combined with multivariate data analysis for determination of ω-3 FAs in fish oils. Fish oils were obtained from the extraction of corresponding fishes and subjected to purification. The oils were further subjected to FTIR spectroscopic measurement at mid infrared region (4000-450 cm-1). Fatty acid compositions of ω-3 FAs namely eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) were determined using gas chromatography with flame ionization (GC-FID), and the results from GC-FID were used as actual values. Two multivariate regressions along with wavenumbers regions or their combinations were optimized and compared to provide the best condition for prediction of EPA and DHA in fish oils. The results showed that partial least square regression (PLSR) was suitable for prediction of DHA applying the variable of absorbance values of the second derivative spectra, with the values of coefficient of determination (R2) of 0.9916 and 0.9316 in calibration and validation models, respectively. The values of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) obtained were 0.789 and 2.53. While, prediction of EPA was performed using principal component regression with R2 value of &gt; 0.72 and low values of RMSEC and RMSEC. It can be concluded that the combination of FTIR spectra and multivariate regression provides the effective tools and alternative GC-FID method for the prediction of EPA and DHA in fish oils.

A total of 473 metabolites were identified from 4 sour cherry genotypes using UPLC-TOF-MS. Untargeted metabolomics revealed the dominant chemical groups present in sour cherries. PCA showed that the diversity in sour-cherry metabolites was due to the genotype differences indicating iditol, malic acid, chlorobenzene, 2-mercaptobenzothiazole, and pyroglutamic acid as the predominant contributors. The variable importance in the projection (VIP &gt; 1.0) in partial least-squares–discriminant analysis described 20 biomarker metabolites, representing the cherry metabolome profiles. A heatmap of Pearson’s correlation analysis between the 20 biomarker metabolites and antioxidant activities identified seven antioxidant determinants that displayed the highest correlations with different types of antioxidant activities. This study of correlating metabolomics and antioxidant activities elucidated that the higher nutritional value and biological functions of select sour cherry genotypes can be useful for the development of nutraceutical and functional foods.

A series of novel isobutylchalcones (A1-A20) were prepared, evaluated for their cytotoxic activity and characterized by FTIR, ¹H NMR, ¹³C NMR, and elemental analysis data. The logic behind the design is to synthesize and compare chalcones containing electron releasing lipophilic isobutyl substituent on aromatic ring A and the B ring with aromatic ring containing a range of electron releasing and electron withdrawing groups as well as heteroaromatic rings for their cytotoxic activity. The compounds were tested against HT-29 (colon cancer), MCF-7 (breast cancer) and DU-145 (prostate cancer) cell lines using methotrexate (IC₅₀ 12 ± 1 (HT-29), 9 ±1 (MCF-7) 5 ± 1 (DU-145)) as reference standard. Compound A6 having 2,4-difluorphenyl moiety was most potent of the series against all the three cell lines and notably A6 was mainly effective against DU-145 cell lines with an IC₅₀ value of 18 µg/mL. The critical structural features required for the activity against all the cell lines were identified through pharmacophore model using PHASE^TM which has recognised a 5 point AHHRR model and is consistent with the cytotoxic activity of the tested compounds.

DNA Topoisomerase IIa (Top2A) is a nuclear enzyme that is a cancer drug target, and there is interest in identifying novel sites on the enzyme to inhibit cancer cells more selectively and to reduce off-target toxicity. The C-terminal domain (CTD) is one potential target, but it is an intrinsically disordered domain, which prevents structural analysis. Therefore, we set out to analyze the sequence of Top2A from 105 species using bioinformatic analysis including the PSICalc algorithm, entropy analysis, and other approaches. Our results demonstrate that large (10th-order) interdependent clusters are found including non-proximal positions across the major domains of Top2A. Further, CTD-specific clusters of 3rd, 4th, and 5th-order were identified that included positions that had been previously analyzed via mutation and biochemical assays. Some of these clusters coincided with positions that when mutated either increased or decreased relaxation activity. Finally, sites of low entropy (i.e., high information content) were identified and mapped as key positions in the CTD. Included in the low entropy sites are phosphorylation sites and charged positions. Together, these results help to build a clearer picture of the critical positions in the CTD and provide potential sites/regions for further analysis.

Plants of the genus Monochoria have long been utilized in food, cosmetics, and traditional herbal treatment. Thailand has the highest species diversity of this genus and a new member, Monochoria angustifolia (G. X. Wang) Boonkerd & Tungmunnithum has been recently described. This plant is called “Siam Violet Pearl” as a common name or “ไข่มุกสีม่วงแห่งสยาม” as its vernacular name in the same meaning in Thai language. Despite their importance, few researches on Monochoria species have been conducted. This study, thus, provided the results to fill in this gap by: i) determining flavonoids phytochemical profiles of 25 natural populations of M. angustifolia covering the whole floristic regions in Thailand, and ii) determining antioxidant activity using various antioxidant assays to investigate the probable mechanism. The results revealed that M. angustifolia presented a higher flavonoid content than the outgroup, M. hastata. Our results also revealed that flavonoids might be used to investigate Monochoria evolutionary connections and for botanical authentication. The various antioxidant assays revealed that M. angustifolia extracts preferentially act through a hydrogen atom transfer antioxidant mechanism. Pearson correlation analysis indicated significant correlations emphasizing that the antioxidant capacity is most probably the result of a complex phytochemical combinations rather than of a single molecule. Altogether, these results showed that this new species provide an attractive alternative starting material with phytochemical variety and antioxidant potential for the phytopharmaceutical industry.

We present a tutorial to realize a multidimensional fitting procedure capable of extracting all the relevant information contained in a sequence of charged particle images acquired as a function of time in femtosecond pump-probe experiments. The images are reproduced using a 3D fitting method, which provides the velocity (or center-of-mass kinetic energy) and angular distributions contained in the images and their time evolution. A detailed example of the method is shown through the analysis of the time-resolved predissociation dynamics of CH₃I on the B-band origin [Gitzinger et al., J. Chem. Phys. 133, 234313 (2010)]. We show that the multidimensional approach is essential for the analysis of complex images that contain several overlapping contributions where reduced dimensionality analyses cannot provide a reliable description of the features present in the image sequence. This methodology can be generalized to many types of multidimensional data analysis.

This paper focuses on optimal sensor positioning for monitoring activities of daily living and investigates different combinations of features and models on different sensor positions, i.e., the side of the waist, front of the waist, chest, thigh, head, upper arm, wrist, and ankle. Sixteen features are extracted and the feature importance is measured by using the Relief-F feature selection algorithm. Eight classification algorithms are evaluated on a dataset collected from young subjects and that collected from elderly subjects, with two different experimental settings. To deal with different sampling rates, signals with a high data rate are down-sampled and a transformation matrix is used for aligning signals to the same coordinate system. The thigh, chest, side of the waist, and front of the waist are the best four sensor positions for the first dataset (young subjects), with average accuracy values being greater than 95%. The best model obtained from the first dataset for the side of the waist is validated on the second dataset (elderly subjects). The most appropriate number of features for each sensor position is reported. The results provide a reference for building activity recognition models for different sensor positions, as well as for data acquired from different hardware platforms and subject groups.

Rhododendron chrysanthum Pall., live in Changbai Mountain being exposed to chilling temperature, high light intensities and water scarcity condition. To adapt to the harsh environment, the cold resistance mechanisms of R. chrysanthum have been successfully evolved in the long-term adaptive process. In our present work, the methods of proteomics combined with physiological and biochemical analyses were used to investigate the effects of cold stress on the photosynthesis and antioxidant system of Rhododendron chrysanthum Pall. and the molecular mechanisms involved in cold resistance of plants. A total of 153 photosynthesis related proteins were identified in present work, of which 7 proteins including Rubisco large subunit (rbcL) were up-regulated in experiment group (EG) compared with control group (CG). Simultaneously, four chlorophyll fluorescence parameters were measured in present study. The results showed that the maximum photochemical efficiency of photosystem II (Fv/Fm), actual quantum yield of PSII (Y(II)) and photochemical quenching (qP) were significantly higher in EG, whereas the non-photochemical quenching (NPQ) was notably decreased. Cold stress could lead to a significant reduction in electron transport rate (ETR) accompanied with an increase in excitation pressure (1-qP). The abundance of PetE which involved in the plants photosynthetic electron transfer was also significantly influenced by cold stress. Moreover, the up-regulated expressions and higher levels of enzymatic activities of Glutathione peroxidase (GPX) and Ascorbate peroxidases (APXs) were detected in EG. All these changes which can help plants to survive in low temperature are considered as the crucial parts of cold tolerance mechanisms. These results revealed that photosynthesis and redox adjustment play significant roles in the defense of cold-induced damage.

We define a spinor-Minkowski metric for SL(4,C). It is not a trivial generalization of the SL(2,C) metric and it involves the Minkowskian one. We define 4x4 version of the Pauli matrices and eight 4-component associated generalized eigenvectors that can be regarded as undotted covariant spinors. The 4-component spinors can be grouped into four categories. Each category transforms in its own way. The outer products of pairwise combinations of 4-component spinors can be associated with 4-vectors. Including the dotted covariant, undotted and dotted contravariant forms totally we have sixteen pairs of spinors. Eight of them live in the conjugate space which has no countepart in SL(2,C).

For this research we are selected three indicators of wheat: yield (t/ha), producer price (USD/t) and share of the harvested area under wheat in relation to the total land area of country (%). The mentioned indicators were analyzed for the period 2006-2021 in thirty-two European countries. The purpose of the research is to determine which of the mentioned indicators achieve average annual growth/decrease rates, what is the correlation between them, how European countries are grouped with their similarities and differences. The research examines the impact of the COVID-19 pandemic on the mentioned indicators in a two time phases: Phase I, before the pandemic (2006-2019); Phase II, during the pandemic (2020-2021). The methodological approach to the research topic involved the application of descriptive statistics, as the method of principal components analysis (abbr. PCA) with graphics. A positive correlation exists only between the yield of wheat and the share of the harvested area under wheat in the total area of the land (0.291). PCA method showed that countries are grouped differently depending on the observed indicator and the analyzed time phase.

This work develops a new method for vector data augmentation. The proposed method applies the Principal Component Analysis (PCA) and determines the Eigenvectors of a set of training vectors for a Machine Learning (ML) method and uses them to generate the distilled vectors. The training and the PCA distilled vectors have the same dimension. The user chooses the number of vectors to be distilled and augmented to the set of training vectors. A statistical approach determines the lowest number of vectors to be distilled such that when augmented to the original vectors the extended set trains a ML classifier to achieve a required accuracy. Hence, the novelty of this study is, the distillation of vectors with the PCA method and their use to augment the original set of vectors. The advantage that comes from the novelty is that it increases the statistics of ML classifiers. To validate the advantage, we conducted experiments with four public databases and applied four classifiers: Neural Network, Logistic Regression, Support Vector Machine with linear and polynomial kernels. For the purpose of augmentation, we conduct several distillations including nested (double distillation). The latter notion means that new vectors were distilled from already distilled vectors. We train the classifiers with three sets of vectors: original vectors; original augmented with vectors distilled by PCA; original augmented with distilled and double distilled, by PCA, vectors. The experimental results are presented in the paper, and they confirm the advantage that the PCA distilled vectors increase the classification statistics of ML methods, if the distilled vectors augment the original training vectors.

In this study, the autofrettage method, which is used to increase the durability of cylindrical parts, was applied to a barrel made of steel material according to the AISI 4340 standard. Assuming that the barrel works continuously under the pressure of 400 MPa, optimum autofrettage was performed. The stresses occurring on the barrel before and after autofretage were calculated. Additionally, analytical equivalent stress values (Von-Mises) formed on the part's wall were compared with numerical analysis results obtained with a commercial finite element program ANSYS®, and their compatibility was examined. As a result of the calculations and analysis performed, it was observed that autofretage has positive effect on increasing the pressure carrying capacity of the barrel. After autofrettage the cylindrical part, it was determined that the Von-Mises stress values formed in the part wall changed and these stresses took the lowest value at a point (elastic-plastic interface). It has been evaluated that this point gives the optimal autofretage pressure value for a certain operating pressure. After the autofrettage application, it was determined that the Von-Mises Stress value in the barrel wall decreased by 25.27 % and the pressure carrying capacity of the barrel increased without any design or dimensional change. It has been seen that the analytical and numerical analysis results are consistent with each other, and it is expected that this study will guide and contribute to the studies to be conducted on increasing the strength or lightening the weight of the parts.

Principal component analysis (PCA) is used to reduce the dimensionalities of high dimensional datasets in a variety of research areas. For example, biological macromolecules, such as proteins, exhibit many degrees of freedom, allowing them to adopt intricate structures and exhibit complex functions by undergoing large conformational changes. Therefore, molecular simulations of and experiments on proteins generate a large number of structure variations in high dimensional space. PCA and many PCA-related methods have been developed to extract key features from such structural data, and these approaches have been widely applied for over 30 years to elucidate macromolecular dynamics. This review mainly focuses on the methodological aspects of PCA and related methods, and their applications for investigating protein dynamics.

The present study was conducted to evaluate encapsulated essential oils as an alternative anticoccidial in coccidiosis vaccine challenged broiler chickens. A total of 600 day-old male broiler chicks were provided with no-added corn-soybean meal-based control diet or diets that contained either salinomycin or EO at 60 and 120 mg per kg of diet. On day 21, half of the control groups were orally challenged with a coccidiosis vaccine at 25 times higher than the recommended vaccine dose. During 22 to 28 days (i.e., one-week post coccidiosis vaccine challenge), the challenged chickens had decrease (P < 0.05) in body weight gain and feed intake but increase in feed conversion ratio compared with the non-challenged, naïve control chickens. However, dietary EO significantly counteracted (P < 0.05) coccidiosis vaccine-induced depression in body weight gain and feed intake. Increasing dietary EO linearly decreased (P < 0.05) the concentrations of the volatile fatty acids. Dietary SAL and EO affected gut morphology in chickens at 20 days posthatch. Increasing dietary EO linearly (P = 0.073) increased serum catalase activity. Collectively, our study shows that dietary EO increased coccidiosis vaccine-induced growth depression and altered gut physiology in broiler chickens.

The botanical species Ceratonia siliqua L., commonly referred to as the Carob tree, and locally as “L’Kharrûb”, holds significance as an agro-sylvo-pastoral species, and is traditionally utilized in Morocco for treating a variety of ailments. This current investigation aims to ascertain the antioxidant, antimicrobial, and cytotoxic properties of the ethanolic extract of C. siliqua leaves (CSEE). Initially, we analyzed the chemical composition of CSEE through high-performance liquid chromatography with Diode-Array Detection (HPLC-DAD). Subsequently, we conducted various assessments, including DPPH scavenging capacity, β-carotene bleaching assay, ABTS scavenging, and total antioxidant capacity assays, to evaluate the antioxidant activity of the extract. In this study, we investigated the antimicrobial properties of CSEE against five bacterial strains (two gram-positive, Staphylococcus aureus, and Enterococcus faecalis; and three gram-negative bacteria, Escherichia coli, Escherichia vekanda, and Pseudomonas aeruginosa) and two fungi (Candida albicans, and Geotrichum candidum). Additionally, we evaluated the cytotoxicity of CSEE on three human breast cancer cell lines (MCF-7, MDA-MB-231, and MDA-MB-436) and assessed the potential genotoxicity of the extract using the comet assay. Through HPLC-DAD analysis, we determined that phenolic acids and flavonoids were the primary constituents of the CSEE extract. The results of the DPPH test indicated a potent scavenging capacity of the extract with an IC50 of 302.78 ± 7.55 µg/mL, which was comparable to that of ascorbic acid with an IC50 of 260.24 ± 6.45 µg/mL. Similarly, the β-carotene test demonstrated an IC50 of 352.06 ± 12.16 µg/mL, signifying the extract's potential to inhibit oxidative damage. The ABTS assay revealed IC50 values of 48.13 ± 3.66 TE µmol/mL, indicating a strong ability of CSEE to scavenge ABTS radicals, and the TAC assay demonstrated an IC50 value of 165 ± 7.66 µg AAE/mg. The results suggest that the CSEE extract had potent antioxidant activity. Regarding its antimicrobial activity, the CSEE extract was effective against all five tested bacterial strains, indicating its broad-spectrum antibacterial properties. However, it only showed moderate activity against the two tested fungal strains, suggesting it may not be as effective against fungi. The CSEE exhibited a noteworthy dose-dependent inhibitory activity against all the tested tumor cell lines in vitro. The extract did not induce DNA damage at the concentrations of 6.25, 12.5, 25, and 50 µg/ml, as assessed by the comet assay. However, the 100 µg/ml concentration of CSEE resulted in a significant genotoxic effect compared to the negative control. A computational analysis was conducted to determine the physicochemical and pharmacokinetic characteristics of the constituent molecules present in the extract. The Prediction of Activity Spectra of Substances (PASS) test was employed to forecast the potential biological activities of these molecules. Additionally, the toxicity of the molecules was evaluated using the Protox II webserver.

Cosmetics have various characters, but there have been no studies which classified the properties of cosmetics based on their effects on skin-domesticated bacteria. In this study, we established an anaerobic culture and short-chain fatty acid measurement system using Staphylococcus epidermidis, a representative bacterium of indigenous skin bacteria. Furthermore, this system was used to extract and classify the characteristics of 9 cosmetics. Cosmetics containing ferments of rice and soy were clustered in the vicinity, although one cosmetic containing soy ferment was clustered distant from other similar cosmetics. Cosmetics from South Asia and those containing natural plant extracts were clustered in the vicinity. These results show that this method can be utilized as a cosmetics pattern map, and will provide a method to prevent growth of opportunistic bacteria.

Abstract: Steamed ginseng water (SGW), the by-product generated from the heated processing of red ginseng, with high content of active substances, better skincare activities, and large amount output ineffective utilization, resulted in environmental pollution and resource waste. In current study, UHPLC-Q-Exactive-MS/MS liquid chromatography-mass spectrometry and multivariate statistical analysis were conducted to characterize the compositional features of the repeated thermal-treated SGW. The total sugar content, total sugar content, total reducing sugar content, total non-reducing sugar content, DPPH, ABTS+, Fe3+ reducing capacity, and the hydroxyl radical scavenging abilities were employed to evaluate the gross contents variation connect with anti-oxidant activities during heat processes. The result revealed the SGW content and antioxidant activity were highly correlated, the 7th SGW sample showed the highest content and the strongest ability on anti-aging capacities. 38 significant common differential markers were screened, by the four compared SGW groups (1- and 3-, 1- and 5-, 1- and 7-, and 1- and 9) through OPLS-DA analysis. The current study showed that the thermal proceeding times could be a vital index value during the recycling operation quality control of SGW, which has a huge potential in anti-aging cosmetic raw materials, In the meanwhile, our results provided a green, sustainable, low-cost thinking of rational application on ginseng resource.

CD8+ cytotoxic T lymphocytes (CTLs) play a crucial role in anti-tumor immunity. In a previous study, we identified a subset of murine effector CTLs expressing the hepatocyte growth factor (HGF) receptor c-Met (c-Met+ CTLs) that are endowed with enhanced cytolytic capacity. HGF directly inhibited the cytolytic function of c-Met+ CTLs, both in 2D in vitro assays and in vivo, leading to reduced T cell responses against metastatic melanoma. To further investigate the role of c-Met+ CTLs in a three-dimensional (3D) setting, we studied their function within B16 melanoma spheroids and examined the impact of cell-cell contact on the modulation of inhibitory checkpoint molecules expression such as KLRG1, PD-1 and CTLA-4. Additionally, we evaluated the cytolytic capacity of human CTLs clones expressing c-Met (c-Met+) and compared it to c-Met− CTLs clones. Our results indicated that, similar to their murine counterparts, c-Met+ human CTLs clones exhibited increased cytolytic activity compared to c-Met− CTLs clones, and this enhanced function was negatively regulated by the presence of HGF. Taken together, our findings highlight the potential of targeting the HGF/c-Met pathway to modulate CTL-mediated anti-tumor immunity. This research holds promises for developing strategies to enhance the effectiveness of CTL-based immunotherapies against cancer.

In this paper, several two-dimensional clustering scenarios are given. In those scenarios, soft partitioning clustering algorithms (Fuzzy C-means (FCM) and Possibilistic c-means (PCM)) are applied. Afterward, VAT is used to investigate the clustering tendency visually, and then in order of checking cluster validation, three types of indices (e.g., PC, DI, and DBI) were used. After observing the clustering algorithms, it was evident that each of them has its limitations; however, PCM is more robust to noise than FCM as in case of FCM a noise point has to be considered as a member of any of the cluster.

The aim of this study was to investigate the physicochemical characterization and biological activities of chitosan (CH) based composite films with the incorporation of chestnut flower essential oil (CFEO). The composite films were prepared by casting method and characterized in terms of structural, morphological and mechanical properties via FT-IR, XRD, UV, SEM and TGA. The results proved the significantly increased water vapor permeability (WVP), heat resistance, antibacterial and antioxidant capabilities of CH-CFEO films. The incorporation of CH and CFEO enhanced the UV blocking, which made the film shield almost all UV light. Films with the tensile strength of 6.37 ± 0.41 MPa and elongation at break of 22.57 ± 0.35% were got with 6 mg mL-1 CFEO. Subsequently, the fruit preservation experiments also confirmed that the composite films could effectively extend the shelf life of bananas through their excellent water vapor and oxygen barrier. These desirable performances enable our newly developed composite films to be a remarkable packaging material to solve the fresh fruit preservation dilemma.

Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common one has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.

A partial least squares (PLS) quantitative chemometric method based on the analysis of the MID-FTIR spectrum of polymer inclusion membranes (PIMs) used for the extraction of Cr(VI) from aqueous media is developed. The system previously optimized considering the variables membrane composition, extraction time, and pH, is characterized in terms of its adsorption isotherm, distribution coefficient, extraction percent and enrichment factor. A Langmuir type adsorption behavior with KL = 21.99 L/mg, qmax = 0.242 mmol/g and 0&lt;RL&lt;1, indicates that metal adsorption is favorable. The characterization of the extraction reaction is performed as well showing an 1:1 Cr(VI):Aliquat 336 ratio, in agreement with solvent extraction data. The principal component analysis (PCA) of the PIMs revels a complex pattern, which is satisfactorily simplified and related to Cr(VI) concentrations through the use of a variable selection method (iPLS) in which bands in the ranges 3451–3500 cm-1 and 3751–3800 cm-1 are chosen. The final PLS model including the 100 wavelengths selected by iPLS and 10 latent variables shows excellent parameter values with RMSEC: 3.73115, RMSECV: 6.82685, Bias: -1.91847e-13, CV Bias: 0.185947, R2 Cal: 0.98145, R2 CV: 0.940902, recovery%: 104.02 ± 4.12 (=0.05), sensitivity%: 0.001547 ppb, γ: 3.8 ppb, γ- 1: 0.6 ppb-1, selectivity: 0.0155, linear range: 5.8–100 ppb, LD: 1.9 ppb, and LQ: 5.8 ppb. The developed PIM sensor is easy to implement as it requires few manipulations and reduced number of chemical compounds in comparison to other similar reported systems.

Abstract Big datasets are becoming increasingly common and can be challenging to understand and apply in public health. One method for lowering the dimensionality of these datasets and improving interpretability while minimizing information loss is data reduction using principal component analysis (PCA). It achieves this by successively maximizing variance through the creation of new, uncorrelated variables. PCA is an adaptive data analysis technique because it simplifies the process of finding new variables, or principal components, by solving an eigenvalue or eigenvector problem. These new variables are determined by the dataset being used, rather than by the analyst starting from scratch. It is also adaptable in another way because varieties of the method have been designed to adjust to various data structures and types. However, there are serious problems in the theoretical understanding and practical application of PCA in public health researchers, whereas its application is becoming popular in developing countries. Therefore, this article, which concentrated on using PCA to reduce data, began by outlining the fundamental concepts of PCA and going over what it can and cannot do, as well as when and how to use it. We also discussed the fundamental assumptions, benefits, and drawbacks of PCA. Furthermore, this article demonstrated and resolved PCA practical application problems in public health that most scholars are unaware of, such as variable preparation, variable inclusion and exclusion criteria for PCA, iteration steps, wealth index analysis, interpretation, and ranking.

In this paper we review dynamics and roughness of bonds in proteins on example of albumin, that is important from the physiological point of view. We have performed computer simulations of albumin chain. Statistics were collected by performing many simulations realizations for each experimental setting. We concentrate on hydrogen bonds, cation-π and π- π interactions and NP contacts. Histograms of hydrogen bonds length are positively skewed in contrary to histograms of interactions and HP contacts that are negatively skewed. Scaling exponents of power spectra of energies of bonds / interactions /contacts are in range -0.2 to -0.5 and significantly differ between various hydrogen bonds or interactions. Varying scaling of such spectra can be used to classify between distinct bonds or contacts. Concerning particular amino-acids, largest amount of HBO H20 bonds are between Glutamate (GLU) amino-acids and water particle, while large amount of HBO bonds are formed with Lysine (LYS). For HP contacts the mayor role plays Phenylalanine (PHE) and Leucine (LEU) amino-acids. From decay curves HBO H2O bonds decays in fastest rate, while HBO bonds and HP contacts at slowest rate. We present as well decay curves of bonds formed by particular amino-acids, that gives interesting results.

The Serra da Estrela Natural Park (NPSEs) in Portugal stands out as a well-preserved region abundant in medicinal plants, particularly known for their pharmaceutical applications in diabetes prevention and treatment. This comprehensive review explores these plants' botanical diversity, traditional uses, pharmacological applications, and chemical composition. The NPSEs boast a rich diversity with 138 medicinal plants across 55 families identified as traditionally and pharmacologically used against diabetes globally. Notably, the Asteraceae and Lamiaceae families are prevalent in anti-diabetic applications. In vitro studies reveal their significant inhibition of carbohydrate-metabolizing enzymes, and certain plant co-products regulate genes involved in carbohydrate metabolism and insulin secretion. In vivo trials demonstrate anti-diabetic effects, including glycaemia regulation, insulin secretion, antioxidant activity, and lipid profile modulation. Medicinal plants in NPSE exhibit various activities beyond anti-diabetic, such as antioxidant, anti-inflammatory, antibacterial, anticancer, and more. Chemical analysis identifies over fifty compounds like phenolic acids, flavonoids, terpenoids, and polysaccharides responsible for their efficacy against diabetes. The findings underscore the potential of NPSE medicinal plants as anti-diabetic candidates, urging further research to develop effective plant-based anti-diabetic drugs, beverages, and supplements.

In this research, an attempt was made to reduce the dimension of wavelet-ANFIS/ANN (artificial neural network/adaptive neuro-fuzzy inference system) models toward reliable forecasts as well as to decrease computational cost. In this regard, the principal component analysis was performed on the input time series decomposed by a discrete wavelet transform to feed the ANN/ANFIS models. The models were applied for dissolved oxygen (DO) forecasting in rivers which is an important variable affecting aquatic life and water quality. The current values of DO, water surface temperature, salinity, and turbidity have been considered as the input variable to forecast DO in a three-time step further. The results of the study revealed that PCA can be employed as a powerful for dimension reduction of input variables and also to detect inter-correlation of input variables. Results of the PCA-Wavelet-ANN models are compared with those obtained from Wavelet-ANN models while the earlier one has the advantage of less computational time than the later models. Dealing with ANFIS models, PCA is more beneficial to avoid Wavelet-ANFIS models creating too many rules which deteriorate the efficiency of the ANFIS models. Moreover, manipulating the Wavelet-ANFIS models utilizing PCA leads to a significant decreasing in computational time. Finally, it was found that the PCA-Wavelet-ANN/ANFIS models can provide reliable forecasts of dissolved oxygen as an important water quality indicators in rivers.