Search Results (23)

Time delays are intrinsic to mitotic regulation, particularly within the spindle assembly checkpoint (SAC) and the spindle position checkpoint (SPOC). These delays emerge from multi-step protein activation, molecular transport, force-dependent conformational transitions, and spatial redistribution of regulatory complexes. They span seconds to minutes and strongly influence checkpoint activation, maintenance, and silencing. Increasing evidence shows that such delayed processes shape mitotic timing, checkpoint robustness, and cell-fate decisions. While classical ordinary differential equation (ODE) models assume instantaneous biochemical responses, delay differential equations (DDEs) provide a natural framework for representing these finite timescales by explicitly incorporating system history. Recent DDE-based studies have revealed how delayed signaling contributes to bistability, oscillatory responses, prolonged mitotic arrest, and variability in checkpoint outputs. This review summarizes the biological origins of delays in SAC and SPOC, including Mad2 activation, MCC assembly and turnover, APC/C reactivation, tension maturation at kinetochores, and Bfa1–Bub2 regulation of Tem1. The article further discusses how mechanistic models with explicit delays improve our understanding of SAC–SPOC ordering, error-correction dynamics, and mitotic exit control. Finally, open challenges and future directions are outlined for integrative delay-aware modeling that unifies biochemical, mechanical, and spatial processes to better explain checkpoint function and chromosomal stability. Full article

Background: End-stage renal disease (ESRD) is a growing global health concern, and hemodialysis (HD) remains the most common life-sustaining therapy for patients with advanced kidney failure. Both humoral and cellular immunity are impaired post hemodialysis, leading to immune system dysfunction. Methods: We utilized flow cytometry to quantify cell populations based on surface markers, including CD3 (total T lymphocytes), CD4 (helper T-cells), CD8 (cytotoxic T-cells), CD19 (B lymphocytes), and CD16/CD56 (natural killer (NK) cells). EDTA-blood samples were collected intravenously immediately before and after dialysis. Results: A consistent decline in CD3⁺ T lymphocytes was observed post hemodialysis. This reduction occurred across both male and female cohorts: p = 0.0342 and p = 0.0002, respectively. CD8⁺ cytotoxic T-cells decreased significantly post HD, p = 0.0003. Conversely, CD4⁺ helper T-cells exhibited a paradoxical increase, p = 0.0321. The divergent trends in CD4⁺ and CD8⁺ cells led to a statistically significant increase in the CD4/CD8 ratio post dialysis, p = 0.0005. Notably, stratification by gender uncovered that the post-HD changes in CD4⁺ and CD8⁺ T-cells were exclusive to female patients. Females demonstrated a pronounced increase in CD4⁺ cells and a sharper decline in CD8⁺ cells compared to males. CD19⁺ B lymphocytes showed a statistically significant decline post hemodialysis (p < 0.0001). While both genders exhibited reduced B-cell percentages, female patients experienced a more pronounced reduction than males. NK cells were severely depleted post dialysis in both male and female cohorts. Conclusions: Overall, the immune alterations observed in HD patients, including T-cell reduction, B-cell lymphopenia, and changes in NK cell populations, contribute to the increased risk of infections, malignancy, and cardiovascular disease in this population. Full article

The Adaptive Skip-gram (AdaGram) algorithm extends traditional word embeddings by learning multiple vector representations per word, enabling the capture of contextual meanings and polysemy. Originally implemented in Julia, AdaGram has seen limited adoption due to ecosystem fragmentation and the comparative scarcity of Julia’s machine learning tooling compared to Python’s mature frameworks. In this work, we present a Python-based reimplementation of AdaGram that facilitates broader integration with modern machine learning tools. Our implementation expands the model’s applicability beyond natural language, enabling the analysis of scientific notation—particularly chemical and physical formulas encoded in LaTeX. We detail the algorithmic foundations, preprocessing pipeline, and hyperparameter configurations needed for interdisciplinary corpora. Evaluations on real-world texts and LaTeX-encoded formulas demonstrate AdaGram’s effectiveness in unsupervised word sense disambiguation. Comparative analyses highlight the importance of corpus design and parameter tuning. This implementation opens new applications in formula-aware literature search engines, ambiguity reduction in automated scientific summarization, and cross-disciplinary concept alignment. Full article

Hypericum perforatum L. (H.P.), a plant renowned for its wound-healing properties, was investigated for antioxidant/antimicrobial efficacy, toxicological safety, and in vivo wound-healing effects in this research to develop and characterize novel nanoemulsion hydrogel (NG) formulations. NG were prepared via emulsion diffusion–solvent evaporation and polymer hydration using Cremophor RH40 and Ultrez 21/30. A D-optimal design optimized oil/surfactant ratios, considering particle size, PDI, and drug loading. Antioxidant activity was tested via DPPH, ABTS⁺, and FRAP. Toxicological assessment followed HET-CAM (ICH-endorsed) and ICCVAM guidelines. The optimized NG-2 (NE-HPM-10 + U30 0.5%) demonstrated stable and pseudoplastic flow, with a particle size of 174.8 nm, PDI of 0.274, zeta potential of −23.3 mV, and 99.83% drug loading. Release followed the Korsmeyer–Peppas model. H.P. macerates/NEs showed potent antioxidant activity (DPPH IC₅₀: 28.4 µg/mL; FRAP: 1.8 mmol, Fe²⁺/g: 0.3703 ± 0.041 mM TE/g). Antimicrobial effects against methicillin-resistant S. aureus (MIC: 12.5 µg/mL) and E. coli (MIC: 25 µg/mL) were significant. Stability studies showed no degradation. HET-CAM tests confirmed biocompatibility. Histopathology revealed accelerated re-epithelialization/collagen synthesis, with upregulated TGF-β1. The NG-2 formulation demonstrated robust antioxidant, antimicrobial, and wound-healing efficacy. Enhanced antibacterial activity and biocompatibility highlight its therapeutic potential. Clinical/pathological evaluations validated tissue regeneration without adverse effects, positioning H.P.-based nanoemulsions as promising for advanced wound care. Full article

This review explores how intuitive processes drive innovation, which we define as novel ideas, inventions, or artistic creations that cannot be logically derived from existing knowledge or sensory data. Although intuitive processes are not yet fully recognized as a formal area of scientific research, this paper examines current approaches to their study and modeling. It highlights the necessity of integrating unconventional modeling methods with neuroscience to gain deeper insights into these processes. Key experimental studies investigating extrasensory abilities—such as remote viewing, precognition, and telepathy—are reviewed, emphasizing their potential relevance to innovation. We propose that combining these unconventional modeling approaches with insights from systems neurology can provide new perspectives on the neural mechanisms underpinning intuition and creativity. This review emphasizes the critical need for further research into intuitive processes to address complex global challenges. It calls for a more open, interdisciplinary approach to scientific inquiry, promoting the exploration of unconventional forms of knowledge generation and their neural correlates. Full article

Background: The regulation of cellular proliferation and genomic integrity is controlled by complex surveillance mechanisms known as cell cycle checkpoints. Disruptions in these checkpoints can lead to developmental defects and tumorigenesis. Methods: To better understand these mechanisms, computational modeling has been employed, resulting in a dataset of 414 mathematical models in the BioModels database. These models vary significantly in detail and simulated processes, necessitating a robust analytical approach. Results: In this study, we apply the chemical organization theory (COT) to these models to gain insights into their dynamic behaviors. COT, which handles both ordinary and partial differential equations (ODEs and PDEs), is utilized to analyze the compartmentalized structures of these models. COT’s framework allows for the examination of persistent subsystems within these models, even when detailed kinetic parameters are unavailable. By computing and analyzing the lattice of organizations, we can compare and rank models based on their structural features and dynamic behavior. Conclusions: Our application of the COT reveals that models with compartmentalized organizations exhibit distinctive structural features that facilitate the understanding of phenomena such as periodicity in the cell cycle. This approach provides valuable insights into the dynamics of cell cycle control mechanisms, refining existing models and potentially guiding future research in this area. Full article

Vacuum membrane distillation (VMD) has attracted increasing interest for various applications besides seawater desalination. Experimental testing of membrane technologies such as VMD on a pilot or large scale can be laborious and costly. Machine learning techniques can be a valuable tool for predicting membrane performance on such scales. In this work, a novel hybrid model was developed based on incorporating a spotted hyena optimizer (SHO) with support vector machine (SVR) to predict the flux pressure in VMD. The SVR–SHO hybrid model was validated with experimental data and benchmarked against other machine learning tools such as artificial neural networks (ANNs), classical SVR, and multiple linear regression (MLR). The results show that the SVR–SHO predicted flux pressure with high accuracy with a correlation coefficient (R) of 0.94. However, other models showed a lower prediction accuracy than SVR–SHO with R-values ranging from 0.801 to 0.902. Global sensitivity analysis was applied to interpret the obtained result, revealing that feed temperature was the most influential operating parameter on flux, with a relative importance score of 52.71 compared to 17.69, 17.16, and 14.44 for feed flowrate, vacuum pressure intensity, and feed concentration, respectively. Full article

A coiled coil is a structural motif in proteins that consists of at least two α-helices wound around each other. For structural stabilization, these α-helices form interhelical contacts via their amino acid side chains. However, there are restrictions as to the distances along the amino acid sequence at which those contacts occur. As the spatial period of the α-helix is 3.6, the most frequent distances between hydrophobic contacts are 3, 4, and 7. Up to now, the multitude of possible decompositions of α-helices participating in coiled coils at these distances has not been explored systematically. Here, we present an algorithm that computes all non-redundant decompositions of sequence periods of hydrophobic amino acids into distances of 3, 4, and 7. Further, we examine which decompositions can be found in nature by analyzing the available data and taking a closer look at correlations between the properties of the coiled coil and its decomposition. We find that the availability of decompositions allowing for coiled-coil formation without putting too much strain on the α-helix geometry follows an oscillatory pattern in respect of period length. Our algorithm supplies the basis for exploring the possible decompositions of coiled coils of any period length. Full article

In this study, the crude extract and its isolated compounds from the stem bark of Annickia chlorantha were tested for their larvicidal, developmental, and repellent activity against the mosquito vector, Culex pipiens, besides their toxicity to the non-target aquatic organism, the zebrafish (Danio rerio). The acute larvicidal activity of isolated compounds; namely, palmatine, jatrorrhizine, columbamine, β-sitosterol, and Annickia chlorantha methanolic extract (AC), was observed. Developmentally, the larval duration was significantly prolonged when palmatine and β-sitosterol were applied, whereas the pupal duration was significantly prolonged for almost all treatments except palmatine and jatrorrhizine, where it shortened from those in the control. Acetylcholinesterase (AChE) enzyme showed different activity patterns, where it significantly increased in columbamine and β-sitosterol, and decreased in (AC), palmatine, and jatrorrhizine treatments, whereas glutathione S-transferase (GST) enzyme was significantly increased when AC methanolic extract/isolated compounds were applied, compared to the control. The adult emergence percentages were significantly decreased in all treatments, whereas tested compounds revealed non-significant (p > 0.05) changes in the sex ratio percentages, with a slight female-to-male preference presented in the AC-treated group. Additionally, the tested materials revealed repellence action; interestingly, palmatine and jatrorrhizine recorded higher levels of protection, followed by AC, columbamine, and β-sitosterol for 7 consecutive hours compared to the negative and positive control groups. The non-target assay confirms that the tested materials have very low toxic activity compared to the reported toxicity against mosquito larvae. A docking simulation was employed to better understand the interaction of the isolated compounds with the enzymes, AChE and GST. Additionally, DFT calculations revealed that the reported larvicidal activity may be due to the differing electron distributions among tested compounds. Overall, this study highlights the potential of A. chlorantha extract and its isolated compounds as effective mosquitocidal agents with a very low toxic effect on non-target organisms. Full article

In this article, the performance of a solar-powered multi-purpose supply container used as a service module for first-aid, showering, freezing, refrigeration and water generation purposes in areas of social emergency is analyzed. The average daily energy production of the solar panel is compared to the average daily energy demands of the above-mentioned types of service modules. The comparison refers to five different locations based on the Köppen–Geiger classification of climatic zones with the data for energy demand being taken from another publication. It is shown that in locations up to mid-latitudes, the supply container is not only able to power all types of modules all year round but also to provide up to 15 m³ of desalinated water per day for drinking, domestic use and irrigation purposes. This proves and quantifies the possibility of combining basic supply with efficient transport and self-sufficiency by using suitably equipped shipping containers. Thus, flexible solutions are provided to some of the most challenging problems humans will face in the future, such as natural disasters, water scarcity, starvation and homelessness. Full article

Petroleum sludge is a waste product resulting from petroleum industries and it is a major source of environmental pollution. Therefore, developing strategies aimed at reducing its environmental impact and enhance cleaner production are crucial for environmental mortar. Response surface methodology (RSM) was used in designing the experimental work. The variables considered were the amount of petroleum sludge ash (PSA) in weight percent and the ratio of sodium silicate to sodium hydroxide, while the concentration of sodium hydroxide was kept constant in the production of geopolymer mortar cured at a temperature of 60 °C for 20 h. The effects of PSA on density, compressive strength, flexural strength, water absorption, drying shrinkage, morphology, and pore size distribution were investigated. The addition of PSA in the mortar enhanced the mechanical properties significantly at an early age and 28 days of curing. Thus, PSA could be used as a precursor material in the production of geopolymer mortar for green construction sustainability. This study aimed to investigate the influence of PSA in geopolymer mortar. Full article

The massive growth of mobile users will spread to significant numbers of small cells for the Fifth Generation (5G) mobile network, which will overlap the fourth generation (4G) network. A tremendous increase in handover (HO) scenarios and HO rates will occur. Ensuring stable and reliable connection through the mobility of user equipment (UE) will become a major problem in future mobile networks. This problem will be magnified with the use of suboptimal handover control parameter (HCP) settings, which can be configured manually or automatically. Therefore, the aim of this study is to investigate the impact of different HCP settings on the performance of 5G network. Several system scenarios are proposed and investigated based on different HCP settings and mobile speed scenarios. The different mobile speeds are expected to demonstrate the influence of many proposed system scenarios on 5G network execution. We conducted simulations utilizing MATLAB software and its related tools. Evaluation comparisons were performed in terms of handover probability (HOP), ping-pong handover probability (PPHP) and outage probability (OP). The 5G network framework has been employed to evaluate the proposed system scenarios used. The simulation results reveal that there is a trade-off in the results obtained from various systems. The use of lower HCP settings provides noticeable enhancements compared to higher HCP settings in terms of OP. Simultaneously, the use of lower HCP settings provides noticeable drawbacks compared to higher HCP settings in terms of high PPHP for all scenarios of mobile speed. The simulation results show that medium HCP settings may be the acceptable solution if one of these systems is applied. This study emphasises the application of automatic self-optimisation (ASO) functions as the best solution that considers user experience. Full article

Existential vacuum and psychological burnout are becoming increasingly important issues in healthcare professions, especially nursing. This study aimed to investigate the contribution of several demographic factors including gender, work position, experience, and educational level as well as existential vacuum and locus of control (external and internal) in predicting burnout among nurses. A convenience sample of 181 nurses was selected to represent the study sample. Participants were assessed using an existence scale, locus of control scale, and burnout scale. The study showed that 40.3% of nurses had severe existential vacuum. It was found that 93.9% of nurses had experienced a moderate level of burnout. External locus of control was the most common personality trait among participating nurses in this study. It also was found that existential vacuum and external locus of control were the main predictors of psychological burnout among nurses. The findings of our study highlight major problems facing nursing, such as existential vacuum and psychological burnout. It is recommended to enhance nurses’ workplace, provide proper psychological prevention programs, and teach advocacy skills. Full article

This work provides a mathematical technique for analyzing and comparing infection dynamics models with respect to their potential long-term behavior, resulting in a hierarchy integrating all models. We apply our technique to coupled ordinary and partial differential equation models of SARS-CoV-2 infection dynamics operating on different scales, that is, within a single organism and between several hosts. The structure of a model is assessed by the theory of chemical organizations, not requiring quantitative kinetic information. We present the Hasse diagrams of organizations for the twelve virus models analyzed within this study. For comparing models, each organization is characterized by the types of species it contains. For this, each species is mapped to one out of four types, representing uninfected, infected, immune system, and bacterial species, respectively. Subsequently, we can integrate these results with those of our former work on Influenza-A virus resulting in a single joint hierarchy of 24 models. It appears that the SARS-CoV-2 models are simpler with respect to their long term behavior and thus display a simpler hierarchy with little dependencies compared to the Influenza-A models. Our results can support further development towards more complex SARS-CoV-2 models targeting the higher levels of the hierarchy. Full article

The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8–9 October 2020, we got hit by the second wave and finally decided at short notice to go fully online. On the other hand, the pandemic has made us even more aware of the importance of accelerating research in viral bioinformatics. Advances in bioinformatics have led to improved approaches to investigate viral infections and outbreaks. The International Virus Bioinformatics Meeting 2020 has attracted approximately 120 experts in virology and bioinformatics from all over the world to join the two-day virtual meeting. Despite concerns being raised that virtual meetings lack possibilities for face-to-face discussion, the participants from this small community created a highly interactive scientific environment, engaging in lively and inspiring discussions and suggesting new research directions and questions. The meeting featured five invited and twelve contributed talks, on the four main topics: (1) proteome and RNAome of RNA viruses, (2) viral metagenomics and ecology, (3) virus evolution and classification and (4) viral infections and immunology. Further, the meeting featured 20 oral poster presentations, all of which focused on specific areas of virus bioinformatics. This report summarizes the main research findings and highlights presented at the meeting. Full article