Real Conditions Research Articles

Bioprinted Fibroblast Mediated Heterogeneous Tumor Microenvironment for Studying Tumor-Stroma Interaction and Drug Screening.

Cancer-associated fibroblasts (CAFs) are crucial stromal cells in the tumor microenvironment, affecting cancer growth, angiogenesis, and matrix remodeling. Developing an effective in vitro tumor model that accurately recapitulates the dynamic interplay between tumor and stromal cells remains a challenge. In this study, a 3D bioprinted fibroblast - mediated heterogeneous breast tumor model was created, with tumor cells and fibroblasts in a bionic matrix. The impact of transforming growth factor-β （TGF-β） on the dynamic transformation of normal fibroblasts into CAFs and its subsequent influence on tumor cells is further investigated. These findings reveales a profound correlation between CAFs and several critical biological processes, including epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) remodeling, gene expression profiles, and tumor progression. Furthermore, tumor models incorporating CAFs exhibits reduced drug sensitivity compared to models containing tumor cells alone or models co-cultured with normal fibroblasts. These results underscore the potential of the in vitro fibroblast-mediated heterogeneous tumor model to simulate real-life physiological conditions, thereby offering a more effective drug screening platform for elucidating tumor pathogenesis and facilitating drug design prior to animal and clinical trials. This model's establishment promotes the understanding of tumor-stromal interactions and their therapeutic implications.

A coarse-grained molecular dynamics simulation on the mechanical and thermal properties of natural rubber composites reinforced by fullerene nanoparticles.

The influence of fullerene C60 on the mechanical and thermal properties of natural rubber was systematically investigated using coarse-grained molecular dynamics simulations. The tensile results demonstrate that systems with longer NR chains exhibit reduced tensile strength. Moreover, the addition of C60 nanoparticles significantly enhanced the mechanical properties, with Young's modulus, yield strength, and tensile strength increasing by approximately 24.03%, 23.21%, and 51.61%, respectively, at a C60 concentration of 0.2 phr under a strain rate of 1e-6. Furthermore, the mechanical response was found to be strain rate-dependent, with higher strain rates leading to increased Young's modulus, yield strength, and tensile strength. Therefore, excessively high strain rates should be avoided in simulations to ensure consistency with real conditions. In terms of thermal properties, the addition of C60 nanoparticles was shown to significantly improve the thermal conductivity of natural rubber, with the optimal enhancement of 17.17% achieved at an inclusion level of approximately 0.1 phr. A comprehensive microstructural analysis, including mean square displacement, radial distribution function, coordination number, and interaction energy, revealed the reinforcement mechanisms of C60 on the mechanical and thermal properties of the nanocomposites. This study provides valuable insights into the rational design and fabrication of fullerene-reinforced natural rubber nanocomposites with superior mechanical and thermal performance. In this study, coarse-grained molecular dynamics simulations were performed using the LAMMPS software. The system used the real unit system with periodic boundary conditions. The interatomic interactions were described using the lj/expand model. The simulations were conducted at a temperature of 300K with a time step of 1fs.

Effects of Hyaluronic Acid on Three Different Cell Types of the Periodontium in a Novel Multi-Culture Cell Plate: An Exploratory Study.

Hyaluronic acid (HA) has received considerable attention in the reconstruction of lost periodontal tissues. HA has been proposed to play a role in cell proliferation, differentiation, migration, and cell-matrix as well as cell-cell interactions. Although various studies have been conducted, further research is needed to expand our knowledge based on HA such as its effects on cell proliferation and osteogenic differentiation. The aim of this study is to assess, in single- and multi-culture plate models, the effect of HA on the proliferation, viability, and function of periodontal ligament fibroblasts, osteoblasts, and gingival epithelial cells. A novel multi-culture cell plate was chosen to simulate a cell-cell communication as close as possible to a real clinical condition in an in vitro setting. We found that HA exclusively enhanced epithelial cell proliferation, while intercellular communication stimulated the proliferation and osteogenic potential of the osteoblasts, independently from HA use. The proliferation and function of the periodontal ligament fibroblasts were not changed by HA or the cellular interplay. The use of multi-culture plates could represent a promising method to investigate and compare dental biomaterials in experiments mimicking an in vivo environment.

Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions

BackgroundPost bariatric hypoglycaemic (PBH) is a late complication of weight loss surgery, characterised by critically low blood glucose levels following meal-induced glycaemic excursions. The disabling consequences of PBH underline the need for the development of a decision support system (DSS) that can warn individuals about upcoming PBH events, thus enabling preventive actions to avoid impending episodes. In view of this, we developed various algorithms based on linear and deep learning models to forecast PBH episodes in the short-term.MethodsWe leveraged a dataset obtained from 50 patients with PBH after Roux-en-Y gastric bypass, monitored for up to 50 days under unrestricted real-life conditions. Algorithms’ performance was assessed by measuring Precision, Recall, F1-score, False-alarms-per-day and Time Gain (TG).ResultsThe run-to-run forecasting algorithm based on recursive autoregressive model (rAR) outperformed the other techniques, achieving Precision of 64.38%, Recall of 84.43%, F1-score of 73.06%, a median TG of 10 min and 1 false alarm every 6 days. More complex deep learning models demonstrated similar median TG but inferior forecasting capabilities with F1-score ranging from 54.88% to 64.10%.ConclusionsReal-time forecasting of PBH events using CGM data as a single input imposes high demands on various types of prediction algorithms, with CGM data noise and rapid postprandial glucose dynamics representing the key challenges. In this study, the run-to-run rAR yielded most satisfactory results with accurate PBH event predictive capacity and few false alarms, thereby indicating potential for the development of DSS for people with PBH.

IMulch: an investigation of the influence of polymers on a terrestrial ecosystem using the example of mulch films used in agriculture

BackgroundThis article provides an overview of the iMulch joint project, which analysed the use of polyethylene (PE) and biodegradable mulch films made of a polylactide (PLA) and polybutylene adipate terephthalate (PBAT) on agricultural land as a source of microplastic. The development of a detection methodology using Raman spectroscopy and thermo-extraction desorption gas chromatography mass–spectrometry (TED-GC–MS), the adsorption behaviour, ageing in drainage water and soil, their transport behaviour in lysimeters, ecotoxicity, uptake in plants, a life cycle assessment (LCA) and upcycling were considered.ResultsThe PE film tested showed hardly any degradation or fragmentation during the ageing tests. The biodegradable films showed incipient degradation after 8 weeks in drainage water and initial degradation after 12 weeks in soil ageing experiments. Additionally no degradation could be detected in the lysimeter test within the 24 months analysed. The biodegradable films could be metabolized in laboratory tests with some microorganisms present in the soil. This indicates that these films can be degraded in the environment if the conditions for degradation are optimal. No microorganisms or fungi that could degrade the PE film within a respective period of time were detected in the soil. Adsorption of the tested substances was not observed. Incorporated in soil, mulch film microplastic showed retention of extractable pesticides. In the ecotoxicological tests, both film types showed no acute toxic effects in the earthworm Eisenia fetida and the springtail Folsomia candida. Endocrine activity was observed in eluate samples from both films. However, aged films showed fewer effects than non-aged films.ConclusionBoth types of film show no transport or degradation in the tests under real conditions, which means that they remain in the upper soil layer, where they are available to soil organisms and can lead to high concentrations in the future. As the biodegradable film could be degraded, at least under ideal conditions, we recommend its use. However, proof of degradation must first be verified under real field conditions. In addition, we recommend the use of thicker conventional mulch films to minimize the emission of plastic particles. For this purpose, a minimum lower limit for the material thickness should be defined.Graphical

Determination of Vibration Properties and Reliable Frequency Estimation for Synchronous Vibrations Through Improved Blade Tip Timing Techniques Without a Once-per-Revolution Sensor.

Synchronous vibrations, which are caused by periodic excitations, can have a severe impact on the service life of impellers. Blade Tip Timing (BTT) is a promising technique for monitoring synchronous vibrations due to its non-intrusive nature and ability to monitor all blades at once. BTT generally employs a Once-per-Revolution (OPR) sensor that is mounted on the shaft for blade identification and deflection calculation. Nevertheless, OPR sensors can be unreliable, as they may be affected by shaft vibrations, and their implementation can be restricted by space constraints. Moreover, the low number of BTT sensors typically leads to under-sampled deflection signals, which consequently hinders the estimation of the vibration frequencies due to aliasing problems. For this reason, BTT is commonly accompanied by strain gauge (SG) measurements on some blades. In this paper, improved BTT techniques are presented, which enable the determination of vibration properties of synchronous vibrations without the need for an OPR sensor and ensure a reliable frequency assessment. Specifically, the blades are identified by unique characteristics resulting from manufacturing tolerances, while the blade deflections are calculated through a novel method, which relies on the impeller's circumferential position. The proposed method enables accurate OPR-free calculation of blade deflections, by accounting for speed variations within a revolution and considering the actual blade positions on the impeller. By completely eliminating the need for an OPR sensor, the accuracy of BTT is enhanced, as the blade deflections are no longer affected by shaft vibrations, while speed variations within a revolution can be accounted for. Moreover, the implementation possibilities of BTT are improved, allowing its application in systems, where an OPR sensor cannot be instrumented due to space constraints. Subsequently, the vibration frequencies are accurately estimated, by employing an improved Multi-Sampling method based on Non-Uniform Fast Fourier Transform. This approach enables the blind analysis of BTT measurements and can identify multiple vibration frequencies. The proposed method expands the capabilities of BTT through a reliable assessment of vibration frequencies from under-sampled BTT signals. Therefore, it is no longer necessary to accompany BTT measurements with SG measurements for frequency identification. Finally, the vibration properties are determined using regression models. The proposed BTT techniques are validated through comparison with SG measurements as well as a commercial BTT system, using experimental data from a test bench of a turbocharger used for marine applications. The vibrations were recorded under real operating conditions, thus demonstrating the industrial applicability of the proposed BTT evaluation procedure.

A self-powered wireless monitoring system driven by ambient RF energy for switch rails

Purpose This study aims to develop a novel self-powered monitoring system that uses radio frequency (RF) energy harvesting and ultra-low-power management technologies for real-time condition monitoring of switch rails. Design/methodology/approach The system is designed for integration within the jump wire holes of switch rails, ensuring structural integrity and aesthetic appeal. It features a highly efficient energy harvesting mechanism combined with optimized power management for wireless sensor nodes. An on-board antenna captures ambient RF energy, managed by high-efficiency circuits to ensure stable wireless sensor operation. An ultra-low-power system-on-chip is used to acquire and transmit multimodal data on vibration and temperature from the switch rails. The data collection is enhanced through a two-threshold approach, adapting to harvested energy levels for self-energy balancing. Findings Testing revealed that the energy harvesting subsystem operated stably at distances up to 2.9 m from the RF source, charging a 200 µF capacitor to 4.2 V in just 220 s. The monitoring subsystem’s average power consumption is in the low microwatt range. Continuous operation over 30 days in real conditions resulted in only a 5 mV reduction in battery voltage, indicating successful self-powered operation and validating long-term reliability in unattended scenarios. Originality/value This research presents an innovative solution, integrating RF energy harvesting with ultra-low-power technology, which addresses the power and stability challenges faced by traditional monitoring systems.

Simulation of temperature field and optimisation of high-temperature parts for a giant mine tire

The temperature field of tires has a significant impact on the cracking aging and service life of tires. Therefore, the finite element simulations of the temperature field of the mining tire were carried out in this paper. The temperatures of the key parts of the tire were measured with the thermocouple under real working conditions. The deviation between the results of the simulation and the measurement is 1.3%. In addition, the function among the maximum temperature, the velocity and sinking amount of the tire was fitted using the simulating results of the temperature field under the nine types of working conditions. Further, based on the response surface method, the structure of the 1# strap layer with high temperature of the tire was optimised by taking the width of the strap layer, the distribution density of the steel wire and the angle of the steel wire arrangement as the independent variables, and the maximum temperature of the tire under steady rolling as the response value. Finally, the results show that the maximum temperature of the optimised model decreases by 3.06 °C compared to the original model.

A Cloud Detection System for UAV Sense and Avoid: Analysis of a Monocular Approach in Simulation and Flight Tests

In order to contribute to the operation of unmanned aerial vehicles (UAVs) according to visual flight rules (VFR), this article proposes a monocular approach for cloud detection using an electro-optical sensor. Cloud avoidance is motivated by several factors, including improving visibility for collision prevention and reducing the risks of icing and turbulence. The described workflow is based on parallelized detection, tracking and triangulation of features with prior segmentation of clouds in the image. As output, the system generates a cloud occupancy grid of the aircraft’s vicinity, which can be used for cloud avoidance calculations afterwards. The proposed methodology was tested in simulation and flight experiments. With the aim of developing cloud segmentation methods, datasets were created, one of which was made publicly available and features 5488 labeled, augmented cloud images from a real flight experiment. The trained segmentation models based on the YOLOv8 framework are able to separate clouds from the background even under challenging environmental conditions. For a performance analysis of the subsequent cloud position estimation stage, calculated and actual cloud positions are compared and feature evaluation metrics are applied. The investigations demonstrate the functionality of the approach, even if challenges become apparent under real flight conditions.

Experimental Research on the Tribological Behavior of Plastic Materials with Friction Properties, with Applications to Manipulators in the Pharmaceutical Industry

In this article, the authors present the results obtained within a complex experimental program that focuses on determining the tribological characteristics of the friction materials used in transmission belts, which are critical active components in manipulators within the pharmaceutical industry. The elements of transmission belts, having the role of ensuring the movement of cardboard packaging—used when packing the foils with medicine capsules—and stopping them during the insertion of the foils, were studied. This repetitive cycle—travel-braking—leads to the wearing of the friction material on the active surface of the belt. The experiments were carried out in a dry environment (air) by testing different types of friction materials (original belt, 3D printed TPU 60A, and TPU 95A). While the study is limited to these three materials, the results highlight the significant influence of material type and infill percentage on the coefficient of friction (COF) and wear resistance. TPU 60A achieved the highest COF at 100% infill, indicating a superior grip but experienced substantial wear, under the same conditions. Conversely, TPU 95A demonstrated a lower COF, suggesting reduced grip, but exhibited exceptional wear resistance. The aim of the research is to provide a preliminary investigation into the materials’ wear resistance and braking effectiveness. The experiments utilized appropriate samples to replicate real operational conditions, particularly focusing on the nature of contact between the moving belt and the packaging.

A systematic literature review of real-world evidence (RWE) on post-market assessment of medical devices.

The increasing use of real-world evidence (RWE) and real-world data (RWD) to assess post-market medical devices (MDs) might satisfy the urgent need for data sharing and traceability. This study sought to (i) get an overview of current practice in post-market assessments of MDs reporting on RWE/RWD; (ii) draw policy recommendations for governments and health organisations and identify a research agenda for scholars.A systematic review was undertaken until February 2024 following the PRISMA guidelines. Original peer-reviewed articles in English and incorporating RWE/RWD into any sort of post-market assessment strategy for an MD were included and their reference lists manually checked. A narrative synthesis was employed to describe evidence retrieved.Totally, 145 research articles were identified. Administrative databases were mostly utilised; clinical and/or economic evidence gathered in a short/medium time horizon the most frequently reported; other evidence types (e.g., organisational) underreported; patient perspectives rarely incorporated; the innovation complexity of MDs relatively low.To our knowledge, this study is the first in its kind to provide a comprehensive picture of how non-randomised evidence has been used when assessing MDs working in real-life conditions. The implications of this review might help health policy scholars in addressing the avenues for research in RWE for MDs and policy-makers to better understand the risks and benefits of medium and long-term use of MDs alongside clinical practice and make more informed decisions about adoption and use.

Exploring Innovative Approaches for the Analysis of Micro- and Nanoplastics: Breakthroughs in (Bio)Sensing Techniques.

Plastic pollution, particularly from microplastics (MPs) and nanoplastics (NPs), has become a critical environmental and health concern due to their widespread distribution, persistence, and potential toxicity. MPs and NPs originate from primary sources, such as cosmetic microspheres or synthetic fibers, and secondary fragmentation of larger plastics through environmental degradation. These particles, typically less than 5 mm, are found globally, from deep seabeds to human tissues, and are known to adsorb and release harmful pollutants, exacerbating ecological and health risks. Effective detection and quantification of MPs and NPs are essential for understanding and mitigating their impacts. Current analytical methods include physical and chemical techniques. Physical methods, such as optical and electron microscopy, provide morphological details but often lack specificity and are time-intensive. Chemical analyses, such as Fourier transform infrared (FTIR) and Raman spectroscopy, offer molecular specificity but face challenges with smaller particle sizes and complex matrices. Thermal analytical methods, including pyrolysis gas chromatography-mass spectrometry (Py-GC-MS), provide compositional insights but are destructive and limited in morphological analysis. Emerging (bio)sensing technologies show promise in addressing these challenges. Electrochemical biosensors offer cost-effective, portable, and sensitive platforms, leveraging principles such as voltammetry and impedance to detect MPs and their adsorbed pollutants. Plasmonic techniques, including surface plasmon resonance (SPR) and surface-enhanced Raman spectroscopy (SERS), provide high sensitivity and specificity through nanostructure-enhanced detection. Fluorescent biosensors utilizing microbial or enzymatic elements enable the real-time monitoring of plastic degradation products, such as terephthalic acid from polyethylene terephthalate (PET). Advancements in these innovative approaches pave the way for more accurate, scalable, and environmentally compatible detection solutions, contributing to improved monitoring and remediation strategies. This review highlights the potential of biosensors as advanced analytical methods, including a section on prospects that address the challenges that could lead to significant advancements in environmental monitoring, highlighting the necessity of testing the new sensing developments under real conditions (composition/matrix of the samples), which are often overlooked, as well as the study of peptides as a novel recognition element in microplastic sensing.

Dynamic Modeling and Analysis on the Cable Effect of USV/UUV System Under High-Speed Condition

This paper investigates the stability issues of the Unmanned Surface Vehicle (USV)–Unmanned Underwater Vehicle (ROV) system induced by cable loads under real marine conditions and high-speed operation. This study focuses on the dynamic coupling characteristics of cable forces affecting the unmanned platform and outlines the variation patterns of these forces under different operational scenarios. By developing the dynamic models of the USV, UC, and UUV, a comprehensive system model for the unmanned marine platform is constructed. The accuracy of the cable model is validated through experimental results, and the coupling interference effects of the cable during collaborative operations are systematically analyzed from multiple perspectives. Additionally, the cable tension and force behaviors under high-speed cruising conditions are thoroughly examined. The results provide a solid foundation for the development of cable load prediction models for collaborative marine unmanned platforms, and offer both theoretical and numerical insights for dynamic control strategies based on cable force adjustments.

Speed Advisor for Fuel Consumption Minimisation Under Real Driving Conditions

This paper deals with minimisation of fuel consumption under real driving conditions using a vehicle speed advisor. The aim is to explore the potential of speed profile optimisation in real driving conditions while assessing the suitability of an application which recommends the driver the optimal vehicle speed sequence that minimises the fuel consumption on a particular route. The speed advisor is based on solving the Optimal Control problem of covering a particular route with minimum fuel consumption with a defined time constraint. The approach presented was applied to and implemented on a real passenger vehicle to obtain a trade-off between fuel consumption and travel time for several trips on the route. Experimental results are presented with and without advisory. With speed advisor, the results approach the pareto front with lesser dispersion. On the other hand, without advisory, the dispersion is higher and largely above the pareto front.

Synthesis and anti-microbial evaluation with in silico studies of novel 2-aminothiazole benzohydrazide derivatives

BackgroundThe development of novel anti-microbial drugs for multidrug-resistant (MDR) is a significant challenge. This study aimed to synthesize various derivatives of (Z)-4-(2-aminothiazol-5-yl)-N-benzohydrazide (DT01-DT10) that are effective against a wide variety of anti-bacterial and antifungal pathogens.ResultsThe binding energy of the compounds ranged from − 9.0 to − 10.0 kcal/mol. Molecular simulations produced a major result in improving the representation of the real biological conditions with an average RMSD of 0.110 nm. The derivatives DT03, DT04, and DT06 showed overall good anti-microbial activity at lower concentrations of 1.8 µg/ml. Compound DT03 showed significant activity against Gram-positive, Gram-negative bacteria and fungal strains, with inhibition zone diameters of 17, 19 and 16 mm, respectively. Compound DT04 showed promising anti-bacterial effects against S.mutans and C.albicans, with inhibition zone diameters of 18 and 17 mm, and moderate activity against B. cereus. Compound DT06 showed enhanced activity against P.aeruginosa.ConclusionThe derivative 4-(2-amino-1,3-thiazol-5-yl)-N′-(Z)-(2-nitrophenyl) methylidene benzohydrazide (DT06), which contained a nitro group displayed potent activity at 1.8 µg/ml with an IC50 of 50.31 and a selectivity index of 61.33.Graphical abstract

Influence of Humidity on FFP Masks with Electret Filter Media Under Real-Life Wearing Conditions

Most FFP (Filtering Face Piece) masks are made from nonwoven filter media that are electrostatically charged, resulting in the additional electrostatic capture mechanism of particles. The protective effect of these masks is therefore mainly dependent on the electric field surrounding the charged fibers. Upon prolonged wear, the mask becomes saturated with exhaled air, resulting in humidification on the wearer’s side. However, speaking, coughing, or sneezing also generate droplets, which can deposit on the mask from the person wearing it, as well as from other people. In order to investigate this influence on the filtration efficiency and the existing electric field, an experimental study was carried out. To imitate human breathing, a test setup was constructed using a Sheffield Head with different types of masks. This was followed by the cyclical humidification and drying of the masks through simulated breathing. By observing these phases in detail using sample sections, it was possible to continuously record the water content in the samples, the relative humidity, and the pressure drop (breathing resistance). The results demonstrate that moisture has an impact on the filtration efficiency of the electret FFP masks when worn under real-life conditions and that the initial condition can be restored with sufficient drying time.

Synthetic Aspects and Characterization Needs in MOF Chemistry - from Discovery to Applications.

Even if MOFs are recently developed for large-scale applications, the road to applications of MOFs is long and rocky. This requires to overcome challenges associated with phase discovery, synthesis optimization, basic and advanced characterization, and computational studies. Lab-scale results need to be transferred to large-scale processes, which is often not trivial, and life-cycle analyses and techno-economic analyses need to be performed to realistically assess their potential for industrial relevance. Based on the experience in the field of stable, functional MOFs combining advanced synthesis, characterization, and modeling, this mini-review gives recommendations especially for non-specialists, for example, from chemical engineers to medical doctors, to accelerate and facilitate knowledge transfer which will ultimately lead to the application of MOFs. The recommendations will include the reporting of synthesis and characterization data as well as standardization and detailed information required for the application of data mining and machine learning techniques, which are increasingly used to accelerate the discovery of new materials and data analysis. Once a suitable MOF is identified and its key properties determined, translational studies shall finally be carried out in collaboration with end-users to validate performance under real conditions and allow understanding of the processes involved.

Long-term effects of combining anaerobic digestate with other organic waste products on soil microbial communities.

Agriculture is undergoing an agroecological transition characterized by adopting new practices to reduce chemical fertilizer inputs. In this context, digestates are emerging as sustainable substitutes for mineral fertilizers. However, large-scale application of digestates in agricultural fields requires rigorous studies to evaluate their long-term effects on soil microbial communities, which are crucial for ecosystem functioning and resilience. This study presents provides a comparative analysis in long-term field conditions of fertilization strategies combining annual applications of raw digestate with biennial applications of different organic waste products (OWPs)-biowaste compost (BIO), farmyard manure (FYM), and urban sewage sludge (SLU)-and compares them to combinations of the same OWPs with mineral fertilizers. The cumulative effects of repeated OWP applications, paired with two nitrogen sources-organic (digestate) and chemical (mineral fertilizer)-were assessed through soil physicochemical and microbial analyses. We hypothesized that the combined effect varied according to the N-supply sources and that this effect also depended on the type of OWP applied. Soil microbial communities were characterized using high-throughput sequencing targeting 16S and 18S ribosomal RNA genes, following DNA extraction from soil samples collected in 2022, six years after the initial digestate application. The results indicated that combining OWPs rich in stable and recalcitrant organic matter, such as BIO and FYM, with raw digestate, offers an improved fertilization practice. This approach maintains soil organic carbon (SOC) levels, increases soil phosphorus and potassium content, and stimulates microbial communities differently than nitrogen supplied via mineral fertilizers. While microbial biomass showed no significant variation across treatments, microbial diversity indices exhibited differences based on the type of OWP and nitrogen source. The fertilization strategies moderately influenced prokaryotic and fungal community structures, with distinct patterns depending on the OWP and nitrogen source. Notably, fungal communities responded more strongly to treatment variations than prokaryotic communities. This study provides new insights into the cumulative effects of substituting mineral fertilizers with digestates on soil microbial communities and soil physicochemical parameters. The sustainable development of agroecosystems significantly depends on a better understanding of the complex responses of soil microbial communities to different fertilization regimes. Future research should continue to assess the long-term impact of digestate application on soil microbiota in real agronomic field conditions, considering associated agricultural practices.

Biofilm Compositions and Bacterial Diversity on Kitchen Towels in Daily Use.

Towels with complex woven structures are susceptible to biofilm formation during daily use. The composition of biofilms formed on towels used under real-life conditions has yet to be studied. Thus, we investigated the color changes, structural integrity, and biofilm development on towels used continuously for 10 weeks by 12 volunteers in specific kitchen environments. Apparent biofilms composed of bacteria and extracellular polymeric substances (EPSs) were found on all used towels. The bacteria concentrations ranged from 4 to 7 log CFU/g. Proteins were the most abundant EPS, followed by polysaccharides and eDNA. A high-throughput sequencing method was employed to investigate the bacterial diversity on the towels. The predominant bacterial genera differed from towel to towel. Kocuria, Rothia, Psychrobacter, Enhydrobacter, and Pseudomonas are genera of relatively high abundance that may originate from the human body and foods. In addition, correlations among environmental factors, major bacterial genera, physical properties, and biofilm formation of the towels were analyzed, which could provide a scientific reference for maintaining towel hygiene.

Current issues of social assistance to the poor in the Russian Federation

This article addresses the practical aspects of implementing targeted social support for people in need, focusing on individual regions of the Russian Federation (RF). In the context of the crisis in financing social payments, the development of an effective concept for protecting vulnerable population groups becomes a critical task. The study presents an analysis of statistical data highlighting the socio-demographic crisis in Russian society. In particular, official data from the Federal State Statistics Service and archival materials are considered. The article characterizes the basic statutory instruments governing the mechanisms of social support for people in need in Russia. The author argues that overcoming the crisis requires efforts to align the social system of the Russian Federation with its real socio-economic conditions.