Bovine colostrum is a rich source of bioactive compounds, including growth factors, that may promote tissue regeneration. Studies suggest it has potential therapeutic benefits in humans, but further research is needed to fully understand its mechanisms of action. This study aims to review scientific articles on the use of bovine colostrum as a bioactive agent for tissue regeneration in humans and twelve articles were selected. In vitro studies show that bovine colostrum can benefit cells by reducing cell proliferation and inducing differentiation. The concentration of colostrum used has a direct impact on the results, with no positive results observed at some high concentrations (20%). Extracted portions of colostrum (EVs and IMF) showed better results than the complete colostrum. In vivo studies show that bovine colostrum is a promising natural source for wound healing, as its bioactive factors help in the orderly progression of the healing process. However, some studies did not find any benefit related to tissue regeneration, and more research is needed to explore the full potential of colostrum in regenerative medicine and to develop more effective therapies for wound healing.

Touch is important for many aspects of our daily activities. One of the most important tactile characteristics is its perceived intensity. However, quantifying the intensity of perceived tactile stimulation beyond subjective self-reports remains challenging. Here, we show that pupil responses can objectively index the intensity of tactile stimulation in the absence of overt participant responses. In Experiment 1 (n=32), we stimulated three reportedly differentially sensitive body locations (finger, forearm, calf) with a single tap of a tactor while tracking pupil responses. Tactile stimulation resulted in greater pupil dilation than a baseline without stimulation. Furthermore, pupils dilated more for the more sensitive location (finger) than for the less sensitive locations (forearm, calf). In Experiment 2 (n=20) we extended these findings by manipulating the intensity of the stimulation with three different intensities, here a short vibration, always at the little finger. Again, pupils dilated more when being stimulated at higher intensities as compared to lower intensities. In summary, pupils dilated more for more sensitive parts of the body at constant stimulation intensity and for more intense stimulation at constant location. Taken together, the results show that the intensity of perceived tactile stimulation can be objectively measured with pupil responses – and that such responses are a versatile marker for touch research. Our findings may pave the way for previously impossible objective tests of tactile sensitivity, for example in minimally conscious state patients.

Interoception is mainly related to morpho-functional characteristics of the insula, which shows hypnotizability-related differences in grey matter volume. Interoceptive accuracy (IA, measured by the heartbeat counting task and by HEP, heartbeat evoked cortical potential) is lower in high (highs) than in low hypnotizables (lows). The aim of the present study was to investigate IA in highs, lows, and medium hypnotizables (mediums), who represent most of the population (according to the Stanford Hypnotic Susceptibility Scale (SHSS), Form A), during a session including a simple relaxation (Part 1) and three trials of consecutive open eyes, closed eyes, heartbeat counting and post-counting conditions (Part 2). ECG and EEG were recorded in 14 highs, 14 mediums and 18 lows. HEP were extracted throughout the entire session and IA index was obtained for the heartbeat counting task. In Part 1, significant hypnotizability-related differences were observed in the right central region in both early and late HEP components, with lows showing positive and highs/mediums negative HEP amplitudes. In Part 2, the same group differences were limited to the early HEP component. Moreover, in the left frontal regions, only mediums modified their HEP during the counting task with respect to the open/closed eyes conditions, whereas highs displayed HEP differences between counting and post-counting rest. In conclusion, highs and mediums seem to be more similar than mediums and lows regarding HEP, despite the absence of differences in the counting task. Nonetheless, a negative correlation between SHSS scores and HEP amplitudes was observed in the regions showing group differences.

Testing is one of the most time-consuming and unpredictable processes within the software development life cycle. As a result, many Test Case Optimisation (TCO) techniques have been proposed to make this process more scalable. Object Constraint Language (OCL) was initially introduced as a constraint language to provide additional details to UML models. However, as OCL continues to evolve, an increasing number of systems are being expressed by this language. Despite this growth, a noticeable research gap exists for the testing of systems whose specifications are expressed in OCL. In our previous work, we verified the effectiveness and efficiency of performing the Test Case Prioritisation (TCP) process for these systems. In this study, we extend our previous work by integrating the Test Case Minimisation (TCM) process to determine whether TCM can also benefit the testing process under the context of OCL. The evaluation of TCO approaches often relies on well-established metrics such as the Average Percentage of Fault Detection (APFD). However, the suitability of APFD for Model-Based Testing (MBT) is not ideal. This paper addresses this limitation by proposing a modification to the APFD metric to enhance its viability for MBT scenarios. We conducted four case studies to evaluate the feasibility of integrating the TCM and TCP processes in our proposed approach. In these studies, we applied the multi-objective optimisation algorithm NSGA-II and the genetic algorithm independently to the TCM and TCP processes. The objective was to assess the effectiveness and efficiency of combining TCM and TCP in enhancing the testing phase. Through experimental analysis, the results highlight the benefits of integrating TCM and TCP in the context of OCL-based testing, providing valuable insights for practitioners and researchers aiming to optimise their testing efforts. Specifically, the main contributions of this work include: 1). We introduce the integration of the TCM process into the TCO process for systems expressed by OCL. This integration benefits the testing process further by reducing redundant test cases while ensuring sufficient coverage. 2). We comprehensively analyse the limitations associated with the commonly used metric, APFD, and then a modified version of the APFD metric has been proposed to overcome these weaknesses. 3). We systematically evaluate the effectiveness and efficiency of OCL-based TCO processes on four real-world case studies with different complexities.

Hypoxia Inducible Factor (HIF), the main actor in the cell response to hypoxia, represents a potential target in cancer therapy. HIF is involved in many biological processes such as cell proliferation, survival, apoptosis, angiogenesis, iron metabolism and glucose metabolism. This protein regulates the expressions of Lactate Dehydrogenase (LDH) and Pyruvate Dehydrogenase (PDH), both essential for the conversion of pyruvate to be used in aerobic and anaerobic pathways. HIF upregulates LDH, increasing the conversion of pyruvate into lactate which leads to higher secretion of lactic acid by the cell and reduced pH in the microenvironment. HIF indirectly downregulates PDH, decreasing the conversion of pyruvate into Acetyl Coenzyme A which leads to reduced usage of the Tricarboxylic Acid (TCA) cycle in aerobic pathways. Upregulation of HIF may promote the use of anaerobic pathways for energy production even in normal extracellular oxygen conditions. Higher use of glycolysis even in normal oxygen conditions is called the Warburg effect. In this paper, we focus on HIF variations during tumour growth and study, through a mathematical model, its impact on the two metabolic key genes PDH and LDH, to investigate its role in the emergence of the Warburg effect. Mathematical equations describing the enzymes regulation pathways were solved for each cell of the tumour represented in an agent-based model to best capture the spatio-temporal oxygen variations during tumour development caused by cell consumption and reduced diffusion inside the tumour. Simulation results show that reduced HIF degradation in normoxia can induce higher lactic acid production. The emergence of the Warburg effect appears after the first period of hypoxia before oxygen conditions return to a normal level. The results also show that targeting the upregulation of LDH and the downregulation of PDH could be relevant in therapy.

Ovarian cancer is commonly diagnosed in its late stages, and new treatment modalities are needed to improve patient outcomes and survival. We have recently established the synergistic effects of combination tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) and procaspase activating compound (PAC-1) therapies in granulosa cell tumours (GCT) of the ovary, a rare form of ovarian cancer, using a mathematical model of the effects of both drugs in a GCT cell line. Here, to understand the mechanisms of combined TRAIL and PAC-1 therapy, study the viability of this treatment strategy, and accelerate preclinical translation, we leveraged our mathematical model in combination with population pharmacokinetics (PopPK) models of both TRAIL and PAC-1 to expand a realistic heterogeneous cohort of virtual patients and optimize treatment schedules. Using this approach, we investigated treatment responses in this virtual cohort and determined optimal therapeutic schedules based on patient-specific pharmacokinetic characteristics. Our results showed that schedules with high initial doses of PAC-1 were required for therapeutic efficacy. Further analysis of individualized regimens revealed two distinct groups of virtual patients within our cohort: one with high PAC-1 elimination, and one with normal PAC-1 elimination. In the high elimination group, high weekly doses of both PAC-1 and TRAIL were necessary for therapeutic efficacy, however virtual patients in this group were predicted to have a worse prognosis when compared to those in the normal elimination group. Thus, PAC-1 pharmacokinetic characteristics, particularly clearance, can be used to identify patients most likely to respond to combined PAC-1 and TRAIL therapy. This work underlines the importance of quantitative approaches in preclinical oncology.

Intro: Long-term treatment with interferon-alfa (IFN) can reduce the disease burden of patients diagnosed with myeloproliferative neoplasms (MPN). Determining individual patient-responses to IFN-therapy may allow for efficient personalized treatment, reducing both drop out and disease burden. Methods: A mathematical model describing hematopoietic stem cells and the immune system is suggested. Considering the bone marrow and the blood allows for modelling disease dynamics both in the absence and presence of treatment. Through comprehensive modelling of the effects of IFN, the model was related to individualized patient-data consisting of longitudinal hematologic and molecular measurements. Treatment responses are modelled on a population-level, allowing for personalized predictions from a single pre-treatment data point. Results: Personalized fits were found to agree well with data. This allowed for a quantitative description of the treatment-response, yielding a mechanistic interpretation of differences between individual patients. Population-level treatment-responses were simulated. Based on pre-treatment data and the actual treatment scheduling, the population-level response was found to predict the treatment-response of particular patients accurately over a five-year period. Conclusion: Mechanism-based modelling of treatment effects demonstrates that hematologic and molecular observables can be predicted on the level of individual patients. Personalized patient-fits suggest that the effect of IFN-treatment can be quantified and interpreted through mathematical modelling, despite variation in hematologic and molecular response for different patients. Modelling suggests that both hematologic and molecular markers must be considered to avoid immediate relapse. Furthermore, personalized model-fits provides quantitative measures of the hematologic and molecular response, determining when treatment-cessation is appropriate. Proof-of-concept population-level modelling of treatment-responses from pre-treatment data successfully predicted clinical measures for a five-year period. This approach could have direct clinical relevance, offering expert guidance for clinical decisions about IFN-treatment of MPN-patients.

Bladder cancer is a common malignancy with over 80,000 estimated new cases and nearly 18,000 deaths per year in the United States alone. Therapeutic options for metastatic bladder cancer had not evolved much for nearly four decades, until recently, when five immune checkpoint inhibitors were approved by the FDA. Despite the activity of these drugs in some patients, the objective response rate for each is less than 25%. At the same time, fibroblast growth factor receptors (FGFRs) have been attractive drug targets for a variety of cancers, and in 2019 the FDA approved the first therapy targeted against FGFR3 for bladder cancer. Given the excitement around these new receptor tyrosine kinase and immune checkpoint targeted strategies, and the challenges they each may face on their own, emerging data suggest that combining these treatment options could lead to improved therapeutic outcomes. In this paper, we develop a mathematical model for FGFR3-mediated tumor growth and use it to investigate the impact of the combined administration of a small molecule inhibitor of FGFR3 and a monoclonal antibody against the PD-1/PD-L1 immune checkpoint. The model is carefully calibrated and validated with experimental data before survival benefits and dosing schedules are explored. Predictions of the model suggest that FGFR3 mutation reduces the effectiveness of anti-PD-L1 therapy, that there are regions of parameter space where each monotherapy can outperform the other, and that pretreatment with anti-PD-L1 therapy always results in greater tumor reduction even when anti-FGFR3 therapy is the more effective monotherapy.

MicroRNAs (miRNAs) are short (~22 nucleotides) non-coding RNAs that are often intricately integrated into the regulatory networks of various cellular processes and govern the cell fate decision making events associated with oncogenesis by regulating the gene expression through post-transcriptional modifications. miRNAs repress the target genes by either degrading the target mRNA or by inhibiting the process of translation. However, mathematical and computational modeling of miRNA-mediated target gene regulation in various cellular network motifs suggests that miRNAs play a much more complex role in cellular decision-making events. In this review, we give an overview of the quantitative insights obtained from such kind of mathematical modeling of miRNA mediated gene regulation by highlighting the various factors associated with miRNA regulation that are pivotal in diversifying the cell fate decisions related to oncogenesis. Intriguingly, recent experiments suggest that miRNAs can even upregulate the translation of the target protein under certain circumstances, which may lead to more complexities in miRNA-mediated gene regulations. We discussed possible avenues to explore such unusual biological observations related to miRNA’s that can be modeled to get a detailed understanding of the influence of miRNAs in the context of oncogenesis.

Once cancer is initiated, with normal cells mutated into malignant ones, a solid tumour grows, develops and spreads within its microenvironment invading the local tissue; the disease progresses and the cancer cells migrate around the body leading to metastasis, the formation of distant secondary tumours. Interactions between the tumour and its microenvironment drive this cascade of events which have devastating, if not fatal, consequences for the human host/patient. Among these interactions, biomechanical interactions are a vital component. In this paper, key biomechanical relationships are discussed through a review of modelling efforts by the mathematical and computational oncology community. The main focus is directed, naturally, towards lattice-free agent-based, force-based models of solid tumour growth and development. In such models interactions between pairs of cancer cells (as well as between cells and other structures of the tumour microenvironment) are governed by forces. These forces are ones of repulsion and adhesion, and are typically modelled via either an extended Hertz model of contact mechanics or using Johnson-Kendal-Roberts theory, both of which are discussed here. The role of the extracellular matrix in determining disease progression is outlined along with important cell-vessel interactions which combined together account for a great proportion of Hanahan and Weinberg’s “Hallmarks of Cancer”.

Introduction: The use of prostate-specific antigen (PSA) as a prognostic indicator for prostate cancer (PCa) patients is controversial, especially since it has been shown to correlate poorly with tumor burden. The poor quality of PSA as a biomarker could be explained by current guidelines not accounting for the mechanism by which it enters circulation. Given that mature blood vessels are relatively impermeable to it, we hypothesize that immature and leaky blood vessels, formed under angiogenic cues in a hypoxic tumor, facilitate PSA extravasation into circulation. Methods: To explore our hypotheses, we develop a nonlinear dynamical systems model describing the vascular growth of PCa, that explicitly links PSA leakage into circulation with changes in intra-tumoral oxygen tension and vessel permeability. The model is calibrated versus serum PSA and tumor burden time-courses from a mouse xenograft model of castration resistant PCa response to androgen deprivation. Results: The model recapitulates the experimentally observed – and counter-intuitive – phenomenon of increasing tumor burden despite decreasing serum PSA levels. The validated model is then extended to the human scale by incorporating patient-specific parameters and fitting individual PSA time-courses from patients with biochemically failing PCa. Our results highlight the limitations of using time to PSA failure as a clinical indicator of androgen deprivation efficacy. We propose an alternative indicator, namely a treatment efficacy index, for patients with castration resistant disease, to identify who would benefit most from enhanced androgen deprivation. Conclusions: A critical challenge in prostate cancer therapeutics is quantifying the relationship between serum PSA and tumor burden. Our results underscore the potential of mathematical modeling in understanding the limitations of serum PSA as a prognostic indicator. Finally, we provide a means of augmenting PSA time-courses in the diagnostic process, with changes in intra-tumoral vascularity and vascular architecture .

As a development-enhancing or a risk-promoting environment, coparenting may shape the association between maternal prenatal depressive symptoms and infant regulatory capacity. This study aimed to analyze the moderator role of positive and negative coparenting in the association between maternal prenatal depressive symptoms and infant regulatory capacity at 3 months. A sample of 103 primiparous couples (N = 206 parents) was recruited at the 1st trimester of pregnancy. Mothers reported on depressive symptoms at the 1st trimester of pregnancy, and both parents reported on depressive symptoms, coparenting, and infant regulatory capacity at 2 weeks and 3 months postpartum. Higher levels of maternal prenatal depressive symptoms and higher levels of maternal and paternal reports of negative coparenting at 2 weeks postpartum were associated with lower infant regulatory capacity at 3 months. Negative coparenting at 2 weeks postpartum accentuated the association between maternal prenatal depressive symptoms and infant regulatory capacity at 3 months. The results support a view of negative coparenting as a risk-promoting environment that can accentuate the association between maternal prenatal depressive symptoms and infant regulatory capacity. Infants in families with mothers with elevated prenatal depressive symptoms and with high levels of negative coparenting may be at high risk of low regulatory capacity.

This study addresses the assessment of metacognitive monitoring in Turkish preschool children, a critical aspect of their learning and development. A specialized paired-association task was designed to create an assessment tool targeting higher-order thinking skills in this demographic. Out of 190 participants aged 48 to 66 months, gathered from three preschools in Ankara, Turkey, the data analysis centered on 160 children, excluding those with missing or incomplete responses. The Metacognitive Thinking Test’s Judgment Part (Jp) underwent factor analysis, revealing a two-factor structure with 14 items demonstrating memory-confidence alignment. Notably, children tended to overestimate inaccurate recollections, aligning with the Dunning-Kruger effect. Despite limitations, the study offers valuable insights, shedding light on the intricate relationship between confidence and correctness in metacognitive development among young learners. This research lays the groundwork for future investigations in this domain.

Background: In addition to the elimination diet, dietary composition may influence disease severity in patients with Eosinophilic Esophagitis (EoE) through modulation of the immune response. Aim: To explore the immunomodulatory role of nutrition before and during elimination diet in adult EoE patients. Methods: Nutritional intake was assessed in 39 Dutch adult EoE patients participating in the Supplemental Elemental Trial (SET) using 3-day food diaries. In this randomized controlled trial, diagnosed patients received either a four-food elimination diet alone (FFED) or FFED with addition of an amino acid-based formula for six weeks. Multiple linear regression analyses were performed to assess associations between the intake of nutrients and food groups per 1000 kCal and peak eosinophil count/High Power Field (PEC), both at baseline and after six weeks. Results: At baseline, we found a statistically significant negative (thus favorable) relationship between the intake of protein, total fat, phosphorus, zinc, vitamin B12, folate and milk products and PEC (p<0.05), while calcium (p=0.058) and full fat cheese/curd (p=0.056) were borderline (favorably) significant. In contrast, total carbohydrates, prepacked fruit juice and white bread were significantly positively related to PEC (p<0.05) (unfavorable), while ultra-processed meals (p=0.059) were borderline (unfavorably) significant. After dietary intervention, coffee/tea were significantly negatively (favorably) related to PEC, hummus/legumes were significantly positively (unfavorably) related with PEC, while peanuts were borderline significantly positively related (p=0.058). Conclusion: Dietary composition may be related to inflammation in adult EoE patients. High quality and anti-inflammatory diets may be a promising adjuvant therapy in the dietary management of EoE.

Perspective taking and cognitive flexibility are important abilities for navigating our everyday lives. In this longitudinal study with 108 children (61 girls, mostly White), we investigated the developmental relation between Level 1 perspective taking at 27 months of age and Level 2 perspective taking at 52 months of age as well as relations to cognitive flexibility at 52 months of age. We found that early perspective taking was significantly related to later, more complex perspective taking abilities as well as to cognitive flexibility. This highlights the importance of early perspective taking abilities for later perspective understanding and flexible cognition.

This systematic literature review scrutinizes the implementation and analysis of zk-SNARK, zk-STARK, and Bulletproof non-interactive zero-knowledge proof (NIZKP) protocols in privacy-preserving applications across diverse sectors. Examining 43 research works published from 2015 to April 2023, we categorized findings into financial, medical, business, general, and other domains. Our analysis highlights significant variations in real-world performance across implementations utilizing NIZKP protocols. However, divergent methodologies in security analyses hindered conclusive comparisons. Addressing research gaps, our future endeavors aim to establish a real-world benchmark for these protocols.

The Additively-Manufactured, System-Integrated Tip (AMSIT) project is leveraging the flexibility of 3D printing to integrate several technologies in a wind turbine blade tip, while reducing the levelized cost of electricity (LCOE) produced. The design integration is demonstrated for a 200 kilowatt-scale turbine with 13-meter blades, with the outer 15% of the blade replaced with a 3D-printed design. Aerodynamic performance is enhanced through inclusion of a winglet and surface texturing, both challenging for traditional manufacturing. Longevity and durability is improved through integrated lightning and leading edge erosion protection. Increased power, reduced repair frequency, and ease of repair through blade modularity all contribute to reduced LCOE. Cost models are are extended to modern megawatt-scale designs to estimate the impact of the technology at scale, demonstrating the potential to reduce LCOE very significantly for modern onshore turbines, with even higher potential savings offshore.

There are few accurate prognostic indications of the illness’s development and severity for COVID-19, despite certain biomarkers having been investigated. The unexpected nature of COVID-19’s course, which can quickly progress from asymptomatic to severe disease, lies at the heart of the disease’s intricacy. Predicting SARS-CoV-2 pathogenicity through laboratory biomarkers and as such, identifying the patients’ illness severity at the time of initial admission would be crucial in aiding patient care. In this study, we sought to evaluate hematological, biochemical and inflammatory biomarkers in COVID-19 patients. This was a cross-sectional research with 48 COVID-19 patients (16 asymptomatic/mild, 16 moderate, and 16 severe) and 48 age-sex matched COVID-19-negative clients from Moi Teaching and Referral Hospital in Kenya. On admission, demographic information, symptoms, and laboratory test results were collected. Significantly, COVID-19 severity was associated with hemoglobin (p<0.0001), white blood cells (p=0.0022), hematocrit (p<0.0001), blood urea nitrogen (p=0.01), blood sodium (p=0.0002), potassium (p=0.0483), C-reactive protein (p=0.0002), and Lactate Dehydrogenase (p<0.0001). CRP showed a high positive connection (0.5433; p=0.0006) with COVID-19 severity, but LDH showed a mild positive correlation (0.2484; p<0.0001). When comparing asymptomatic/mild COVID-19 to severe COVID-19, discriminative accuracy for CRP and LDH was greatest (AUC:0.8867, 95% CI:0.7532-1.000) and (AUC:1.000, 95% CI:1.000-1.000), respectively. Inflammatory biomarkers, hematological and biochemical indices have the potential to complement SARS-CoV-2 testing and predict the course of COVID-19. This will be useful in designing appropriate care for COVID-19 patients through targeted therapy.