An insect neuroactive helix ring peptide called U₁₁-MYRTX-Tb1a (abbreviated as U₁₁) from the venom of the ant, Tetramorium bicarinatum. U₁₁ is a 34-amino-acid peptide that is claimed to be one of the most paralytic peptides ever reported from ant venoms acting against blowflies and honeybees. The peptide features a compact triangular ring helix structure stabilized by a single disulfide bond, which is a unique three-dimensional scaffold among animal venoms. Pharmacological assays using Drosophila S2 cells have demonstrated that U₁₁ is not cytotoxic but instead suggest that it may modulate potassium channels via the presence of a functional dyad. In our work described here, we have tested this hypothesis by investigating the action of synthetically made U₁₁ on a wide array of voltage-gated K and Na channels since it is well known that these channels play a crucial role in the phenomenon of paralysis. Using the Xenopus laevis oocyte heterologous expression system and voltage clamp, our results have not shown any modulatory effect of 1 μM U₁₁ on the activity of Kv1.1, Kv1.3, Kv1.4, Kv1.5, Shaker IR, Kv4.2, Kv7.1, Kv10.1, Kv11.1 and KQT1, nor on DmNav and BgNav. Instead, 10 μM U₁₁ caused a quick and irreversible cytolytic effect, identical to the cytotoxic effect caused by Apis mellifera venom, which indicates that U₁₁ can act as a pore-forming peptide. Interestingly, the paralytic dose (PD₅₀) on blowflies and honeybees corresponds with the concentration at which U₁₁ displays clear pore-forming activity. In conclusion, our results indicate that the insecticidal and paralytic effects caused by U₁₁ may be explained by the putative pore formation of the peptide. Full article

Radiotherapy treatment plans have become highly conformal, posing additional constraints on the accuracy of treatment delivery. Here, we explore the use of radiation-sensitive ultrasound contrast agents (superheated phase-change nanodroplets) as dosimetric radiation sensors. In a series of experiments, we irradiated perfluorobutane nanodroplets dispersed in gel phantoms at various temperatures and assessed the radiation-induced nanodroplet vaporization events using offline or online ultrasound imaging. At 25 °C and 37 °C, the nanodroplet response was only present at higher photon energies (≥10 MV) and limited to <2 vaporization events per cm² per Gy. A strong response (~2000 vaporizations per cm² per Gy) was observed at 65 °C, suggesting radiation-induced nucleation of the droplet core at a sufficiently high degree of superheat. These results emphasize the need for alternative nanodroplet formulations, with a more volatile perfluorocarbon core, to enable in vivo photon dosimetry. The current nanodroplet formulation carries potential as an innovative gel dosimeter if an appropriate gel matrix can be found to ensure reproducibility. Eventually, the proposed technology might unlock unprecedented temporal and spatial resolution in image-based dosimetry, thanks to the combination of high-frame-rate ultrasound imaging and the detection of individual vaporization events, thereby addressing some of the burning challenges of new radiotherapy innovations. Full article

This contribution compares the final sections of Acts of the Apostles and Philostratus’ Life of Apollonius of Tyana. Through this comparison, I aim to show that these two writings resemble one another in their attention to travel as a literary theme. Both Acts and Life employ this theme to communicate their message and, in their narrative endings, set up their implied readers as travelers who are meant to continue the journeys of the protagonists in these writings. At the same time, Acts and Life differ in how exactly they envision their readers to continue the journeys of their protagonists. I will argue that these similarities and differences can be explained by the shared social and intellectual climate that Acts and Life inhabit: both writings result from discourses on travel and self that were rife among intellectuals in the Roman Empire in the first three centuries of our era, irrespective of their ethnic, legal, or cultural affiliations. Full article

The hymenopteran subfamily Charipinae (Cynipoidea: Figitidae) consist of a group of parasitic wasps that are exclusive hyperparasitoids of Hemipteran. The species boundaries in Charipinae have historically been unclear. While diagnostic morphological features have been established for the stepwise separation of species, it is recommended to confirm those limits using molecular data. Here, we focus on the genera Alloxysta Förster, 1869 and Phaenoglyphis Förster, 1869, both of which contain species that are hyperparasitoids of aphids. We sequenced three genes (mitochondrial COI and 16S rDNA, and nuclear ITS2 rDNA) from specimens that were identified as belonging to five species: Alloxysta brevis (Thomson, 1862), A. castanea (Hartig, 1841), A. ramulifera (Thomson, 1862), A. victrix (Westwood, 1833), and Phaenoglyphis villosa (Hartig, 1841). The phylogeny resulting from concatenating these genes supported the species status of the five morphologically identified taxa, with P. villosa nested within Alloxysta. Our study thus indicates that these molecular markers can successfully distinguish charipine species, and also indicates that the genera Alloxysta and Phaenoglyphis may be more closely related than previously hypothesized. We also present the first estimates of genetic distances for these species. Future studies that include more species, loci, and/or genomic data will complement our research and help determine species relationships within the Charipinae subfamily. Full article

Snow and watershed models typically do not account for forest structure and shading; therefore, they display substantial uncertainty when attempting to account for forest change or when comparing hydrological response between forests with varying characteristics. This study collected snow water equivalent (SWE) measurements in a snow-dominated forest in Colorado, the United States, with variable canopy structure. The SWE measurements were integrated with 1 m Lidar derived canopy structure metrics and incoming solar radiation to create empirical SWE offset equations for four canopy structure groupings (forest gaps, south-facing forest edges, north-facing forest edges, and the interior forest) that varied in size compared to an open area. These simple equations indirectly integrate terrain shading and canopy shading and were able to estimate 40 to 70% of SWE variation in a heterogenous forested environment. The equations were then applied to a snow melt model with a 100 m grid size by applying the area-weighted average of SWE offsets from the four canopy structure groupings in each model cell. This tiled model configuration allowed for the model to better represent the subgrid heterogeneity of a forest environment that can be seen through an ensemble or range of potential outputs rather than a singular estimate. Full article

Interdisciplinary teaching approaches have gained significant importance in today’s educational landscape. Among these approaches, decision-making competence plays a pivotal role by nurturing critical thinking and problem-solving skills. Focusing on the decision-making process regarding the sensibility of using sugar-substitutes, this study addresses three key questions. (1) Do chemistry and sports and health students differ in evaluation-competence? (2) What criteria do they use in evaluating the decision-making problem? (3) How do they use ChatGPT (OpenAI, San Francisco, CA, USA), an AI tool, in decision-making? Through surveys, the study revealed two evaluation-competence factors, identified decision-making criteria, and analyzed querying behavior using ChatGPT. The results revealed nuanced differences between the two student groups in the factors of evaluation-competence. While both groups showed improvements in recognizing moral dimensions and considering alternatives, chemistry students displayed enhanced abilities in establishing evaluation criteria and empathetic thinking. Furthermore, differences emerged in the criteria selected for decision-making and querying behavior, indicating varying engagement with ChatGPT. This study offers insights into enhancing interdisciplinary education and underscores the need for tailored interventions to address diverse student needs. Full article

Background: The pandemic caused by the SARS-CoV-2 virus demonstrated the importance of prevention through a healthy diet and lifestyle, the most vulnerable people being those with severe chronic conditions, those who are overweight, and those with an unbalanced immune system. This study aims to examine the nutritional status and lifestyle behaviors of the Romanian population. Methods: The evaluation of the eating habits and lifestyle of the Romanian population in the post-pandemic period was carried out based on a cross-sectional observational study with the help of a questionnaire. Results: A total of 4704 valid answers were registered (3136 female and 1568 male respondents). Among the respondents, most of them belong to the young population, 2892 between the ages of 18 and 40, i.e., 61.5%. Most male respondents are overweight (1400) and obese (780). Most respondents indicated a tendency to consume 1–2 meals per day irregularly (p = 0.617). Only 974 respondents adopted a healthy diet, and 578 a healthy lifestyle. Conclusions: The present study reports low adherence to a healthy diet (20.7%) and healthy lifestyle (12.28%), especially among the young population (<30 years). In the current context, it reports a reduced tendency to consume vegetables and fruits among the population, below the daily average recommended by the nutrition guidelines, a tendency towards sedentary behavior, and even deficient hydration of some of the respondents; these negative aspects can create a long-term series of nutritional and psycho-emotional imbalances. Our results evidence that complex surveys among the population are regularly required to investigate nutritional or lifestyle deficiencies; moreover, it could be helpful in further educational measures in nutrition, food, and environmental safety. Full article

This perspective article delves into the current state of the art pertaining to the nutritional aspects of plant-based meat and identifies future opportunities for improvement in this line of research. A comparative overview of the macro- and micronutrients of plant-based meat products vis-à-vis conventional animal meat is presented in the initial section. This article explains the differences in their nutritional profiles, highlighting the advantages (equivalent protein content, low saturated fat, source of dietary fiber) and challenges (incomplete amino acid profile, anti-nutrients, and low bioavailability of nutrients) of plant-based alternatives. Emphasis has been placed on the health challenges posed by anti-nutrients in plant-based meat and the role of phytase as a promising solution for mitigating these concerns. The latter sections of this article highlight the ability of phytase enzymes to cause a substantial reduction in phytase activity and improve the absorption of iron and zinc from the food matrix while not affecting the textural attributes of end products. By deliberating on these critical factors, the article aims to contribute to the ongoing dialogue on the nutritional aspects of plant-based meat and the scientific strategies to mitigate the nutritional challenges currently associated with this category of alternative protein products. Full article

In the context of global climate change and the increase in drought frequency, monitoring and accurately assessing the impact of hydrological process limitations on vegetation growth is of paramount importance. Our study undertakes a comprehensive evaluation of the efficacy of satellite remote sensing vegetation indices—Normalized Difference Vegetation Index (MODIS NDVI product), kernel NDVI (kNDVI), and Solar-Induced chlorophyll Fluorescence (GOSIF product) in this regard. Initially, we applied the LightGBM-Shapley additive explanation framework to assess the influencing factors on the three vegetation indices. We found that Vapor Pressure Deficit (VPD) is the primary factor affecting vegetation in southern China (18°–30°N). Subsequently, using Gross Primary Productivity (GPP) estimates from flux tower sites as a performance benchmark, we evaluated the ability of these vegetation indices to accurately reflect vegetation GPP changes during drought conditions. Our findings indicate that SIF serves as the most effective surrogate for GPP, capturing the variability of GPP during drought periods with minimal time lag. Additionally, our study reveals that the performance of kNDVI significantly varies depending on the estimation of different kernel parameters. The application of a time-heuristic estimation method could potentially enhance kNDVI’s capacity to capture GPP dynamics more effectively during drought periods. Overall, this study demonstrates that satellite-based SIF data are more adept at monitoring vegetation responses to water stress and accurately tracking GPP anomalies caused by droughts. These findings not only provide critical insights into the selection and optimization of remote sensing vegetation product but also offer a valuable framework for future research aimed at improving our monitoring and understanding of vegetation growth status under climatic changes. Full article

Characterizing the behavior of ductile metals at high strains is essential in various fields. In the case of thin sheets, rectangular cross-section specimens are used to characterize these materials, typically by tensile tests. Unlike cylindrical specimens, flat ones pose additional challenges for the hardening characterization at high strains, especially in the post-necking phase, which, for many high-strength steels, may cover most of the plastic strain range. After the onset of global necking, the rectangular cross-sections tend to distort with respect to their original shape, as their edges progressively curve and bulge inward. The localized necking occurring after the global one in thinner specimens, further distorts the necked zone. Additionally, sheet metals usually exhibit anisotropic characteristics that affect the derivation of the stress–strain curve and need to be dealt with. No exact method exists for the stress–strain characterization of ductile thin sheets at high strains from tensile tests. Although several approximate methods are available in the literature, they either discard the post-necking range or require highly advanced and complex experimental setups not suitable for industrial applications (e.g., 3D DIC). Then, this work proposes a relatively simple methodology for the experimental characterization of anisotropic thin sheet metals through tensile tests on rectangular cross-section specimens that delivers the true stress–strain curve of the material, extended over the necking range and up to fracture, accurately assessing the anisotropy and the distortion of the neck section. The proposed methodology, employing a standard single-camera experimental setup, is illustrated here, referring to four different steels for automotive applications with reference to a single material orientation; it is intended as representative of the repeated procedure involving tensile tests along 3 or more material directions in order to describe the whole anisotropic plastic response. A detailed comparison between the novel methodology and four other common approaches is carried out, highlighting the differences and the enhanced capabilities of the novel one proposed. Full article

Managing red–green–blue (RGB) lighting conditions within structures may evoke emotions and positively influence behavior. Intelligent RGB lighting systems based on environmental data measurements can substantially enhance the perception of comfort. This study presents a challenge that requires a holistic and integrated approach to implement an automatic RGB artificial lighting control system that can be utilized in various structures and indoor environments. Initially, the challenge spans the identification of environmental variables directly impacting comfort up to the careful selection of suitable sensors. The result is the development of a sophisticated and autonomous system that can adjust RGB lighting in real time, creating environments that are both comfortable and energy-efficient. This automated system fosters the creation of appropriate atmospheres across different contexts. The identification and monitoring of environmental variables are achieved through a neuro-fuzzy control mechanism, where fuzzy rules and membership functions are defined based on late positive potential timings and the influence of artificial lighting on human emotions. The outcomes from this study are an interconnected system capable of performing both online and offline operations to enable the monitoring of environmental variables and the efficient management of artificial lighting based on these metrics. A pilot study, with reference to an EEG wave registry system, yielded significant results. These tests had a statistically relevant result with an average frequency of approximately 9.8 Hz, indicative of a state of comfort among people. Despite a 10% deviation margin, 87% of measurements during the test remained consistent. This research study contributes to human behavior by fostering a relaxing environment and enabling a reduction in energy consumption through the use of efficient lighting. Moreover, the environment intention enables the creation of stimuli in three emotional states: activation, relaxation, and neutral, allowing behavioral adaptation to an intention to occur automatically in fluctuating environmental conditions. Full article

This work focuses on the efficient quantization of convolutional neural networks (CNNs). Specifically, we introduce a method called non-uniform uniform quantization (NUUQ), a novel quantization methodology that combines the benefits of non-uniform quantization, such as high compression levels, with the advantages of uniform quantization, which enables an efficient implementation in fixed-point hardware. NUUQ is based on decoupling the quantization levels from the number of bits. This decoupling allows for a trade-off between the spatial and temporal complexity of the implementation, which can be leveraged to further reduce the spatial complexity of the CNN, without a significant performance loss. Additionally, we explore different quantization configurations and address typical use cases. The NUUQ algorithm demonstrates the capability to achieve compression levels equivalent to 2 bits without an accuracy loss and even levels equivalent to ∼1.58 bits, but with a loss in performance of only ∼0.6%. Full article

In this paper, we present an approach to the price-optimized charging of electric vehicles (EVs) based on energy flexibility. Fleet operators determine the minimum and the maximum power demand to charge EVs at a specific time and share this information as so-called power corridors (PCs) with an energy aggregator. The energy aggregator collects the predicted PCs from the fleet operators located in the same market area and aggregates the PCs. The energy provider periodically sends energy prices from the market to the energy aggregator, which purchases energy when its price is opportune. The energy aggregator calculates and delivers charge plans for each fleet operator involved and thus can pass along the purchase prices. The incentive design must ensure that fleet operators are better off by disclosing their flexibility data to the aggregator. This study can contribute to a new data-driven energy market communication system by providing insights on how to leverage the energy flexibility that EVs can offer to the energy system. Full article

In the realm of medical image analysis, the cost associated with acquiring accurately labeled data is prohibitively high. To address the issue of label scarcity, semi-supervised learning methods are employed, utilizing unlabeled data alongside a limited set of labeled data. This paper presents a novel semi-supervised medical segmentation framework, DCCLNet (deep consistency collaborative learning UNet), grounded in deep consistent co-learning. The framework synergistically integrates consistency learning from feature and input perturbations, coupled with collaborative training between CNN (convolutional neural networks) and ViT (vision transformer), to capitalize on the learning advantages offered by these two distinct paradigms. Feature perturbation involves the application of auxiliary decoders with varied feature disturbances to the main CNN backbone, enhancing the robustness of the CNN backbone through consistency constraints generated by the auxiliary and main decoders. Input perturbation employs an MT (mean teacher) architecture wherein the main network serves as the student model guided by a teacher model subjected to input perturbations. Collaborative training aims to improve the accuracy of the main networks by encouraging mutual learning between the CNN and ViT. Experiments conducted on publicly available datasets for ACDC (automated cardiac diagnosis challenge) and Prostate datasets yielded Dice coefficients of 0.890 and 0.812, respectively. Additionally, comprehensive ablation studies were performed to demonstrate the effectiveness of each methodological contribution in this study. Full article

The negatively charged extracellular matrix plays a vital role in intervertebral disc tissues, providing specific cues for cell maintenance and tissue hydration. Unfortunately, suitable biomimetics for intervertebral disc regeneration are lacking. Here, sulfated alginate was investigated as a 3D culture material due to its similarity to the charged matrix of the intervertebral disc. Precursor solutions of standard alginate, or alginate with 0.1% or 0.2% degrees of sulfation, were mixed with primary human nucleus pulposus cells, cast, and cultured for 14 days. A 0.2% degree of sulfation resulted in significantly decreased cell density and viability after 7 days of culture. Furthermore, a sulfation-dependent decrease in DNA content and metabolic activity was evident after 14 days. Interestingly, no significant differences in cell density and viability were observed between surface and core regions for sulfated alginate, unlike in standard alginate, where the cell number was significantly higher in the core than in the surface region. Due to low cell numbers, phenotypic evaluation was not achieved in sulfated alginate biomaterial. Overall, standard alginate supported human NP cell growth and viability superior to sulfated alginate; however, future research on phenotypic properties is required to decipher the biological properties of sulfated alginate in intervertebral disc cells. Full article

The purpose of this paper is to investigate the intertemporal relationship between the non-performing loan ratio and bank lending and to analyze factors affecting loan growth using data from Mongolian commercial banks. There has been a lack of research on Mongolian banks’ lending behavior due to their short history. Thus, this paper investigates the effect of the non-performing loan ratio on total loan growth using an ordinary least squares (OLS) regression model with panel data. We used bank-related variables such as the loan-to-deposit ratio, provision-to-gross loan portfolio ratio, equity-to-asset ratio, and liquidity ratio, and economic variables such as the real gross domestic product (GDP) growth rate, interest rate, and inflation rate. The results of this paper show that non-performing loans have a significant negative impact on total loan growth. The implication of this result is that non-performing loans affect banking efficiency, which, in turn, affects financial stability and the real economy. Moreover, high non-performing loans reduce banks’ profits. Also, this paper found that loss reserve and the liquidity ratio have a positive effect on total loan growth, while the effects of the loan-to-deposit ratio and the equity capital ratio were not found to be significant. Additionally, from a macro perspective, the inflation rate has a positive effect on the total loan growth rate, while the interest rate has a positive effect on total loan growth rather than a negative effect. And real gross domestic product (GDP) growth does not affect the total loan growth rate. Full article

This study investigated the antimicrobial effects of lactic acid (LA) (3%) and peracetic acid (PA) (300 ppm) on tilapia fillets (Oreochromis niloticus) by fogging (15 min) or by immersion (2 s) in a pool of Escherichia coli (NEWP 0022, ATCC 25922, and a field-isolated strain), Staphylococcus aureus (ATCC 25923 and a field-isolated strain), and Salmonella Typhimurium (ATCC 13311 and ATCC 14028), as well as the effects on the physicochemical characteristics of the fillets. Fogging was effective and the best application method to control S. Typhimurium regardless of the acid used, promoting reductions of 1.66 and 1.23 log CFU/g with PA and LA, respectively. Regarding E. coli, there were significant reductions higher than 1 log CFU/g, regardless of the treatment or acid used. For S. aureus, only immersion in PA showed no significant difference (p < 0.05). For other treatments, significant reductions of 0.98, 1.51, and 1.17 log CFU/g were observed for nebulized PA, immersion, and LA fogging, respectively. Concerning the pH of the samples, neither of the acids used differed from the control. However, treatments with LA, and fogging with PA, reduced the pH compared to immersion in PA. As for color parameters, L* and a* values showed changes regardless of the acid or method used, resulting in an improved perception of fillet quality. These results indicate that fogging and immersion are alternatives for reducing S. Typhimurium, E. coli, and S. aureus in tilapia fillets. Full article

Although trophoblast cell surface antigen 2 (Trop2)-targeting drugs are already approved or under investigation in various solid tumors, the significance of Trop2 in lymphoma is unknown. Thus, our objective was to investigate the expression of Trop2 in diffuse large B-cell lymphoma (DLBCL) through a systemic immunohistochemistry screening. We constructed a tissue microarray comprising tissue from 92 DLBCL patients, each diagnosed at the University Medical Center Hamburg-Eppendorf (2020–2022). Trop2-immunohistochemistry was carried out, and positive staining was deemed a specific membranous positivity. Four samples were derived from Epstein-Barr virus (EBV)-positive DLBCL, with one case of EBV-positive DLBCL following angioimmunoblastic T-cell lymphoma (AITL). Strong Trop2 immunostaining was detectable in 1 of 91 analyzable samples, originating from a patient with a composite EBV-positive DLBCL emerging from AITL. Therefore, we performed an additional database search to identify all cases of composite EBV-positive DLBCL emerging from AITL since 2015. Five additional cases were identified and stained for Trop2, revealing two cases with strong B-blast positivity. Our preliminary data imply that Trop2 appears absent in de novo DLBCL, whereas Trop2 is strongly expressed in cases of a rare variant of EBV-positive DLBCL. Further investigations are needed to confirm our results, particularly on the subset of EBV-positive DLBCL emerging from AITL. Full article

This work aimed to improve the oxygen transfer mass coefficient (k_La) in mixing reactors, first evaluating the effect of agitation and aeration and then evaluating the influence of the size and concentration of silica microparticles. Silicon dioxide synthesized via the sol-gel technique, commercial sand, and beach sand were characterized by particle size distribution, scanning electron microscopy, XRD, EDS, FTIR, TG/DTA, and BET. The particles presented average values of approximately 9.2, 76.9, 165.1, and 364.4 µm, with irregular surfaces and different roughness. Silica sol-gel is amorphous while beach and commercial sand have a crystalline structure consisting of silicon, oxygen, and carbon residues. Silica sol-gel presents a higher loss of mass and surface area than other silica microparticles, with a shallow mass loss and a smaller surface. Increasing aeration and agitation improves the k_La, as well as adding silica microparticles. The best k_La was found using silica microparticles with approximately 75 µm concentrations of 1.0 g L⁻¹ (silica sol-gel) and 2.0 g L⁻¹ (commercial and treated beach sand). All silica microparticles used in this work improve mass transfer performance in mixing bioreactors. Full article

This paper presents a comparative analysis of ausferritic ductile cast iron matrix obtained through heat treatment and in its raw state. Ausferrite without heat treatment was achieved by modifying the chemical composition, while nodular graphite was produced using Inmold technology. The presence of compacted graphite in the as-cast ausferritic cast iron was attributed to elements that impede the crystallization of nodular graphite. This study demonstrates that an ausferritic matrix in ductile cast iron can be achieved by incorporating molybdenum in conjunction with nickel or copper. Thermal and derivative analysis (TDA) revealed a minor thermal effect during the transformation of austenite into bainitic ferrite in as-cast ausferritic cast iron. Furthermore, the transformation of austenite in cast iron containing nickel was observed to occur at a temperature of approximately 60 °C higher than in cast iron with copper. The structure of bainitic ferrite platelets in as-cast ausferritic ductile cast iron resembled that of Austempered Ductile Iron (ADI). It was revealed that the amount of austenite in as-cast ausferritic ductile cast iron is more than double that in ADI. The carbon content of austenite was estimated theoretically, revealing that alloying additives in the as-cast ausferritic ductile cast iron reduce the solubility of carbon in austenite, thereby significantly influencing the properties of the cast iron. Full article

Supramolecular hydrogels based on low-molecular-weight compounds are a unique class of so-called “soft” materials, formed by weak non-covalent interactions between precursors at their millimolar concentrations. Due to the variety of structures that can be formed using different low-molecular-weight gelators, they are widely used in various fields of technology and medicine. In this study, we report for the first time an unusual self-assembly process of mixing a hydrosol obtained from L-cysteine and silver nitrate (cysteine–silver sol—CSS) with sodium halides. Modern instrumental techniques such as viscosimetry, UV spectroscopy, dynamic light scattering, zeta potential measurements, SEM and EDS identified that adding fluoride anions to CSS is able to form stable hydrogels of a thixotropic nature, while Cl⁻, Br⁻ and I⁻ lead to precipitation. The self-assembly process proceeds using a narrow concentration range of F⁻. An increase in the fluoride anion content in the system leads to a change in the gel network morphology from elongated structures to spherical ones. This fact is reflected in a decrease in the gel viscosity and a number of gel–sol–gel transition cycles. The mechanism of F⁻’s interaction with hydrosol includes the condensation of anions on the positive surface of the CSS nanoparticles, their binding via electrostatic forces and the formation of a resulting gel carcass. In vitro analysis showed that the hydrogels suppressed human squamous carcinoma cells at a micromolar sample concentration. The obtained soft gels could have potential applications against cutaneous malignancy and as carriers for fluoride anion and other bioactive substance delivery. Full article