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In the Chilean indigenous culture, the tree Drimys winteri (Winteraceae) Canelo is of great importance and is considered the sacred Mapuche tree. It has antibacterial and disinfectant properties and is used in the treatment of various diseases, such as fevers, ulcers, cancers, and respiratory tract problems. The essential oil obtained from D. winteri, DW_EO, is bioactive, possesses insecticidal and repellent properties against pests, and shows activity toward plant growth regulators. It also has a phytotoxic effect against the growth and germination of weeds. The essential oil obtained from the leaves and bark of Drimys winteri has demonstrated antifungal, immunomodulatory, anti-inflammatory, and anticancer properties in in vitro and in vivo studies. It also possesses antioxidant activity and antibacterial effects. The essential oil contains monoterpenes such as zafrol, pinenes, and linalool, among others, that contribute to its bioactivity. The DW_EO and bioactive compounds have great potential in various applications in medicine, industrial food, sanitizer, and other areas.

The measurement of the grounding resistance of grounding grids in large installations as well as grounding electrodes in urban areas is addressed in this article. The resistance value is obtained using a three-pin array by measuring the fall-of-potential on the ground surface. The resistance measured by this method is adjusted to its true value using a correction factor that aligns the measured resistance with the actual value. The proposed measurement method obtains correct values of the grounding resistance even when the auxiliary and potential electrodes of the tree-pin array are close to the electrode to be measured. Thus, it can be applied to large electrodes as well as electrodes in urban areas. Several simulated examples are used to illustrate the method, and some real cases with field measurements are presented for a final validation of the method.

This study investigates the cytotoxicity profile of superparamagnetic Fe3O4-Ag decorated nanoparticles against human fibroblasts (HFF-1) and breast cancer cells (MCF-7). The nanoparticles underwent comprehensive characterization employing scanning electron microscopy (SEM), X-ray diffraction (XRD) analysis, X-ray photoelectron spectroscopy (XPS), and magnetic assays including hysteresis curves and zero-field-cooled (ZFC) plots. The nanoparticles exhibited superparamagnetic behavior as evidenced by magnetic studies. Cytotoxicity assays demonstrated that both HFF-1 and MCF-7 cells maintained nearly 100% viability upon nanoparticle exposure, underscoring the outstanding biocompatibility of Fe3O4/Ag decorated nanoparticles and suggesting their potential utility in biomedical applications such as drug delivery and magnetic targeting. Furthermore, the study analyzed the cytotoxic effects of Fe3O4 and Fe3O4-Ag decorated nanoparticles to evaluate their biocompatibility for further therapeutic efficacy. Results showed that neither type of nanoparticle significantly reduced cell viability in HFF-1 fibroblasts, indicating non-cytotoxicity at the tested concentrations. Similarly, MCF-7 breast cancer cells did not exhibit a significant change in viability when exposed to different nanoparticle concentrations, highlighting the compatibility of these nanoparticles with both healthy and cancerous cells. Additionally, the production of reactive oxygen species (ROS) by cells exposed to the nanoparticles was examined to guarantee their biosafety for further therapeutic potential. Higher concentrations (50–100 μg/mL) of Fe3O4-Ag nanoparticles decreased ROS production in both HFF-1 and MCF-7 cells, while Fe3O4 nanoparticles were more effective in generating ROS. This differential response suggests that Fe3O4-Ag nanoparticles might modulate oxidative stress more effectively, thus beneficial for future anticancer strategies due to cancer cells’ susceptibility to ROS-induced damage. These findings contribute to understanding nanoparticle interactions with cellular oxidative mechanisms, which are crucial for developing safe and effective nanoparticle-based therapies. This investigation advances our understanding of nanostructured materials in biological settings and highlights their promising prospects in biomedicine.

High-intensity ultrasound (HIU) can modify muscle structure, leading to improvements in tenderness. However, factors such as packing type and muscle complexity may attenuate the acoustic cavitation. In this research, the effect of packing thickness (40.6–70 μm) on the quality of bovine Gluteus medius and Biceps femoris treated with HIU (37 kHz, 90 W/cm2, 40 min) was evaluated. The hardness of G. medius decreased significantly as the thickness of the packing bag decreased. The wide interfibrillar and intermyofibrillar spaces corroborated the tenderizing effect. These effects are related to damage of cell structure and changes in the collagen content (3.37 ± 0.1 µg/mL). In addition, the HIU decrease the variability in the water holding capacity of the muscle produced by the use of low thickness bags during storage. The trained sensory panel described the sonicated samples in 50.8 μm bags as less hard and juicier. Contrarily, in B. femoris no significant effects were reported in the variables evaluated. B. femoris is a white muscle, with a high amount of collagen (3.59 ± 0.1 µg/mL) and little intramuscular fat. Consequently, the effect of the HIU on muscle quality is associated with the composition of the muscle fibers and the thickness of the packing bag. HIU application is recommended to improve the quality of leg muscles whenever low-thickness bags (50.8 μm or less) are used.

Site-selective thionation is a powerful strategy to access heavyatom-free small-molecule photosensitizers for photodynamic therapy. Here, a series of sulfur-substituted benzothioxanthene chromophores is synthesized and the sequential insertion of sulfur atoms is shown to result in strong and concomitant optimization of both light absorption and therapeutic activity.

This study explores cutting-edge and sustainable green methodologies and technologies for the synthesis of functional nanomaterials, with a specific focus on the removal of water contaminants and the application of kinetic adsorption models. Our research adopts a conscientious approach to environmental stewardship by synergistically employing eco-friendly silver nanoparticles, synthesized using Justicia spicigera extract as a biogenic reducing agent, in conjunction with Mexican zeolite to enhance contaminant remediation, particularly targeting Cu2+ ions. Structural analysis, utilizing X-ray diffraction (XRD) and high-resolution scanning and transmission electron microscopy (TEM and SEM), yields crucial insights into nanocomposite structure and morphology. Rigorous linear and non-linear kinetic models, encompassing pseudo-first order, pseudo-second order, Freundlich, and Langmuir, are employed to elucidate the kinetics and equilibrium behaviors of adsorption. The results underscore the remarkable efficiency of the Zeolite–Ag composite in Cu2+ ion removal, surpassing traditional materials and achieving an impressive adsorption rate of 98% for Cu. Furthermore, the Zeolite–Ag composite exhibits maximum adsorption times of 480 min. In the computational analysis, an initial mechanism for Cu2+ adsorption on zeolites is identified. The process involves rapid adsorption onto the surface of the Zeolite–Ag NP composite, followed by a gradual diffusion of ions into the cavities within the zeolite structure. Upon reaching equilibrium, a substantial reduction in copper ion concentration in the solution signifies successful removal. This research represents a noteworthy stride in sustainable contaminant removal, aligning with eco-friendly practices and supporting the potential integration of this technology into environmental applications. Consequently, it presents a promising solution for eco-conscious contaminant remediation, emphasizing the utilization of green methodologies and sustainable technologies in the development of functional nanomaterials.

Agriculture is one of the primary activities in the municipality of Acatzingo, Puebla, Mexico. Agricultural fields are affected by the indiscriminate use of pesticides and hydrocarbon spills, which expose inhabitants to the development of infectious diseases. In the present study, we assessed the likelihood of developing infectious diseases associated with environmental contamination (pesticides and hydrocarbons) in various areas of the municipality of Acatzingo, Puebla, Mexico. A questionnaire was applied to 425 people in four areas of two locations divided according to exposure to hydrocarbons and pesticides. We conducted a binomial analysis using a binary logistic regression model, and the odds ratio (OR) was calculated at p ≤ 0.05. The development of infectious diseases is significantly associated with the geographical zone (p = 0.001). The population of Acatzingo de Hidalgo had a higher predicted probability (54.8%) of developing infections. Zone 3, which is exposed to hydrocarbons, had twice the probability of contracting infections (OR = 1.833, p = 0.093). Factors such as tobacco or alcohol consumption, gender, and age did not influence the development of infectious diseases. However, minors, businesspeople, and individuals with chronic degenerative diseases were more likely to contract infectious diseases. Therefore, it is crucial to implement control and regulation in managing pesticides and hydrocarbon spills to mitigate environmental contamination and the associated risks to human health.

The design of biodegradable polymeric materials is of increasing scientific interest due to accelerating levels of plastics pollution. One area of increasing interest is the design of biodegradable polymer films based on seaweed as a raw material. The goal of the study is to explore whether machine learning techniques can be used to predict the properties of unknown compositions based on existing data from the literature. Clustering algorithms are used, which show how some ingredients components at certain concentration levels alter the mechanical properties of the films. Robust regression algorithms with three popular models, namely decision tree, random forest, and gradient boosting. Their predictive capabilities are compared, resulting in the random forest algorithm being the most stable with the greatest predictive capacity. These analyses offer a decision support system for biomaterials manufacturing and experimentation. The results and conclusions of the study indicate that bioplastics made from seaweed have promising potential as a sustainable alternative to traditional plastics, discovering interesting additives to improve the performance of biopolymers. In addition, the machine learning approaches used provide effective tools for analyzing and predicting the properties of these materials in structured but highly sparse data.

This paper addresses the lack of attention paid by the scientific community to the optimization of timber structures, specifically in the context of large-span agro-industrial constructions. The study focuses on the optimization of a three-dimensional roof composed of GL32h glulam regular double-tapered beams and purlins. Firstly, MATLAB was employed to develop a calculation software and then run the proposed optimization model based on genetic algorithms, in order to optimize the different geometries of the construction elements based on cost, as well as the optimum arrangement of the purlins and the number of beams. Moreover, statistical analyses were carried out on more than 200 optimization data points to uncover the influence of different variables in the optimization process. It was found that the snow load and span have a significant influence on the prediction of the height and width of beams and purlins, as well as the purlin spacing; while, as expected, the roof length also influences the optimal number of beams. All these findings could promote the use of timber structures; thus, achieving more sustainable and efficient construction practices.

In this work, hybrid structures formed by nanostructured layers, which contain materials, such as porous silicon (PSi), carbon nanotubes (CNTs), graphene oxide (GO), and silicon-rich oxide (SRO), were studied. The PSi layers were obtained by electrochemical etching over which CNTs and GO were deposited by spin coating. In addition, SRO layers, in which silicon nanocrystals are embedded, were obtained by hot filament chemical vapor deposition (HFCVD) technique. Photoluminescence (PL) spectra were obtained from the hybrid structures with which a comparative analysis was completed among different PL ones. The SRO layers were used to confine the CNTs and GO. The main purpose of making these hybrid structures is to modulate their PL response and obtain different emission energy regions in the PL response. It was found that the PL spectra of the CNTs/SRO and GO/SRO structures exhibit a shift towards high energies compared to those obtained from the PSi layers; likewise, the PSi/CNTs/SRO and PSi/GO/SRO structures show a similar behavior. To identify the different emission mechanisms originated by PSi, GO, CNTs, and SRO, the PL spectra were deconvolved. It was found that the Psi/CNTs/SRO and Psi/GO/SRO structures exhibit a PL shift in respect to the PSi layers, for this reason, the modulation of the PL emission of the structures makes these hybrid structures promising candidates to be applied in the field of photonic and electroluminescent devices.

The main objective of this research was to establish the evolution of badminton players’ ages in the modalities of men’s, women’s and mixed doubles in the top-100 of the World Ranking (WR) from 1994 to 2020. Data were obtained from the Badminton World Federation website (7200 entries: 3304 players) from 1994 to 2020. The highest-ranking position and the mean age of the top-100 WR badminton players were analyzed for each modality. In the men’s doubles (MD) and mixed doubles (XD) modalities, a progressive increase of mean age was observed from 1994 to 2020 (MD: 1994 = 23.91 ± 3.93 years vs. 2020 = 25.55 ± 4.40 years; p < 0.001 and XD: 1994 = 24.06 ± 3.99 years vs. 2020 = 25.34 ± 4.77 years; p = 0.004). In contrast, the women’s doubles modality did not present any change in mean age from 1994 to 2020 (~24 years; p = 0.317). In addition, women’s doubles players reached their highest ranking at an earlier age (~23 years) than men’s and mixed doubles players (~25 years). In conclusion, as often happens in other sports, elite women badminton doubles players are younger and reach their peak performance at a younger age than their male counterparts. These data could help coaches, trainers and selectors to plan the sports career of their elite players.

Reactions of group 10 transition metals with the ditopic ligand dipicolyldithiocarbamate (DPDTC) were performed. Thus, 1:2 reactions of [Ni(CH3COO)2], [Pd(COD)Cl2] or [Pt(COD)Cl2] with DPDTC produced monomeric complexes of the type [M(κ2-SCS-DPDTC)2, M = Ni (1), Pd (2) or Pt (3)] with the dithiocarbamate ligand (DTC) coordinated in a typical chelate κ2-SCS fashion. Interestingly, the reaction of [NiCl2] with DPDTC, under similar conditions, afforded the organic compound 2-(pyridin-2-ylmethyl)imidazo[1,5-a]pyri-dine-3(2 H)-thione (4) as unique product. In order to prove the ditopic nature of the ligand DPDTC, complex [Pd(κ2-SCS-DPDTC)2] (2) was further reacted with [ZnCl2] in a 1:2 M ratio to yield the trinuclear complex [Cl2Zn(κ2-NN-DPDTC-SCS-κ2)Pd(κ2-SCS-DPDTC-NN-κ2)ZnCl2] (5). The molecular structures of all compounds were determinate by typical analytical techniques including the unequivocal determination of all structures by single crystal X-ray diffraction analysis. As expected, complexes 1–3 are isostructural, and the metal centres exhibiting slightly distorted square-planar geometries. While in 5, the trinuclear nature of the complex in confirmed exhibiting a nice combination of tetrahedral-square planar-tetrahedral geometries for the Zn-Pd-Zn centres respectively. Keywords: Dithiocarbamate, Metal-sulphur complexes, Trinuclear complexes, Ditopic ligands, Hetero-aromatic compound, Di-(2-picolyl)amine cyclization

Women are two to four times more prone to anterior cruciate ligament (ACL) injuries than men. This raises questions about the role of the hormonal cycle in knee laxity, which may lead to increased tibial displacement and thus ACL tears. The objective was to update scientific knowledge on the influence of the menstrual cycle on knee laxity and the risk of ACL injury, with a focus on anterior tibial displacement, and on hormonal levels influenced or not by oral contraceptive use. Observational studies obtained from Pubmed, Web of Sciences and Scopus and published between 2015 and 2022 were included in this review. Studies were required to include data on menstrual cycle with/without oral contraceptives (OC) and knee laxity and/or ACL injury. A total of ten studies were selected for this systematic review. Three studies about hormone concentration and knee laxity showed an increase in estradiol during the ovulatory phase compared to the follicular phase. Of the five studies on OC, four showed a decrease in ACL laxity. Finally, four studies assessed ACL injury. The menstrual cycle appears to influence knee laxity in women. An increase in certain hormone levels was observed in the ovulatory and luteal phases when the anterior tibial translation was greater in the knee. However, based on the literature, we cannot conclude that there is a correlation between the menstrual cycle and the risk of ACL injury.

Soil health is a term used to describe the general state or quality of soil, and in an agroecosystem, soil health can be defined as the ability of the soil to respond to agricultural practices in a way that sustainably supports both agricultural production and the provision of other ecosystem services. Conventional agricultural practices cause deterioration in soil quality, increasing its compaction, water erosion, and salinization and decreasing soil organic matter, nutrient content, and soil biodiversity, which negatively influences the productivity and long-term sustainability of the soil. Currently, there are many evidences throughout the world that demonstrate the capability of conservation agriculture (CA) as a sustainable system to overcome these adverse effects on soil health, to avoid soil degradation and to ensure food security. CA has multiple beneficial effects on the physical, chemical, and biological properties of soil. In addition, CA can reduce the negative impacts of conventional agricultural practices on soil health while conserving the production and provision of soil ecosystem services. Today, agricultural development is facing unprecedented challenges, and CA plays a significant role in the sustainability of intensive agriculture. This review will discuss the impact of conservation agricultural practices on soil health and their role in agricultural sustainability.

Apple pomace has been proposed as a quality enhancer for gluten-free bread, but its composition and physicochemical features differ significantly depending on the apple cultivar. The objective of this article was to characterize apple pomace powder (APP) from certain varieties from the Basque Country and to study the feasibility of adding it to gluten-free bread, focusing on physicochemical and nutritional aspects. APP was obtained by washing, drying and grinding, and it was added at 0, 5, 6 and 8%, together with other ingredients, such as gluten-free flours, corn starch and whey protein. APP had a reddish-grey coloration (L* 56.49 ± 1.39, a* 11.07 ± 0.47, b* 27.69 ± 1.76), pH 4.19 ± 0.15 and Aw 0.235 ± 0.084. Pomace powder was used successfully in higher amounts than experiences reported before. Key physicochemical parameters such as specific volume (≥2.5 cm3/g) and cohesiveness or resilience values (0.538 and 0.378, respectively) suggested good acceptability for gluten-free breads with 8% APP. Additionally, breads were a source of antioxidant potential (437.66 ± 38.95 µM DPPHeq/g APP), fiber (80.13 ± 6.07 g/100 g) and micronutrients such as Cu, Mg, Mn and Fe. In conclusion, local apple varieties are a good source of raw material for gluten-free bread manufacture, which offers a solution for environmental pollution and may contribute to boosting the circular economy.

The current diagnostic and therapeutic strategies for endometriosis are limited. Although endometriosis is a benign condition, some of its traits, such as increased cell invasion, migration, tissue inflammation, and angiogenesis are similar to cancer. Here we explored the application of homing peptides for precision delivery of diagnostic and therapeutic compounds to endometriotic lesions. First, we audited a panel of peptide phages for the binding to the cultured immortalized endometriotic epithelial 12Z and eutopic stromal HESC cell lines. The bacteriophages displaying PL1 peptide that engages with angiogenic extracellular matrix overexpressed in solid tumors showed the strongest binding to both cell lines. The receptors of PL1 peptide, tenascin C domain C (TNC-C) and fibronectin Extra Domain-B (Fn-EDB), were expressed in both cells. Silver nanoparticles functionalized with synthetic PL1 peptide showed specific internalization in 12Z and HESC cells. Treatment with PL1-nanoparticles loaded with the potent antimitotic drug monomethyl auristatin E decreased the viability of endometriotic cells in 2D and 3D cultures. Finally, PL1-nanoparticless bound to the cryosections of clinical peritoneal endometriotic lesions in the areas positive for TNC-C and Fn-EDB immunoreactivities and not to sections of normal endometrium. Our findings suggest potential applications for PL1-guided nanoparticles in precision diagnosis and therapy of endometriosis.

Vegetation dynamics is very sensitive to environmental changes, particularly in arid zones where climate change is more prominent. Therefore, it is very important to investigate the response of this dynamics to those changes and understand its evolution according to different climatic factors. Remote sensing techniques provide an effective system to monitor vegetation dynamics on multiple scales using vegetation indices (VI), calculated from remote sensing reflectance measurements in the visible and infrared regions of the electromagnetic spectrum. In this study, we use the normalized difference vegetation index (NDVI), provided from the MOD13Q1 V006 at 250 m spatial resolution product derived from the MODIS sensor. NDVI is frequent in studies related to vegetation mapping, crop state indicator, biomass estimator, drought monitoring and evapotranspiration. In this paper, we use a combination of forecasts to perform time series models and predict NDVI time series derived from optical remote sensing data. The proposed ensemble is constructed using forecasting models based on time series analysis, such as Double Exponential Smoothing and autoregressive integrated moving average with explanatory variables for a better prediction performance. The method is validated using different maize plots and one olive plot. The results after combining different models show the positive influence of several weather measures, namely, temperature, precipitation, humidity and radiation.

In the present work, non-stoichiometric silicon oxide films (SiOx) deposited using a hot filament chemical vapor deposition technique at short time and simple parameters of depositions are reported. This is motivated by the numerous potential applications of SiOx films in areas such as optoelectronics. SiOx films were characterized with different spectroscopic techniques. The deposited films have interesting characteristics such as the presence of silicon nanoclusters without applying thermal annealing, in addition to a strong photoluminescence after applying thermal annealing in the vicinity of 1.5 eV, which may be attributed to the presence of small, oxidized silicon grains (less than 2 nm) or silicon nanocrystals (Si-nc). An interesting correlation was found between oxygen content, the presence of hydrogen, and the formation of defects in the material, with parameters such as the band gap and the Urbach energies. This correlation is interesting in the development of band gap engineering for this material for applications in photonic devices.

Pavement maintenance seeks to provide optimal service conditions. Before maintenance, it is necessary to know the condition of the pavement by inspection, a crucial step in deciding on the repair to be carried out. In this sense, unmanned aerial vehicles (UAVs) seem to be an economic substitute compared to the ground laser scanner for pavement inspection tasks. This research seeks to develop a method to measure potholes using 3D models generated with photographs acquired by a UAV and process them using a software based on the Structure from Motion-MultiView Stereo (SfM–MVS) technique. The contribution of this document is the proposal of recommendations for the acquisition of photographs for the realization of the models. To develop these recommendations, an experiment was carried out to evaluate the accuracy in the reconstruction of 3D models using images obtained from the variation and combination of flight planning parameters and data capture. Then, to validate these recommendations, a bumpy section of pavement was modeled using the SfM–MVS method. The results show that for heights of 10 and 15 m the use of this methodology is applicable for the measurement of the width and depth of potholes.