Impact of fermentation by Saccharomyces Cerevisiae on the macronutrient and in vitro digestion characteristics of Chinese noodles.

This study examined the impact of live bread yeast (Saccharomyces cerevisiae) on the nutritional characteristics of Asian dried noodles. Micronutrient analysis of fermented noodles revealed a 6.9% increase in the overall amino acid content, a 37.1% increase in the vitamin B content and a 63.0% decrease in the phytic acid level. Molecular weight analysis of starch and protein contents revealed moderate decrease in the fermented noodles. The in vitro digestion of fermented noodles showed a slightly faster initial acidification, four-fold decrease in the initial shear viscosity (from 8.85 to 1.94 Pa·s). The initial large food particle count (>2 mm diameter) was 19.5% lower in the fermented noodles. The fermented noodles contained slightly higher free sugar content (73.5 mg g-1 noodle) during the gastric digestion phase. The overall nutrition and digestion results indicate nutritional improvement and digestion-easing attributes in the fermented noodles.

Mechanism of inhibition of melanoma by fucoxanthin simulated in vitro digestion products in cell models constructed using human malignant melanoma cells (A375) and keratinocytes (HaCaT).

Recently, the increasing incidence of malignant melanoma has become a major public health concern owing to its poor prognosis and impact on quality of life. Consuming foods with potent antitumor compounds can help prevent melanoma and maintain skin health. Fucoxanthin (FX), a naturally occurring carotenoid found in brown algae, possesses antitumor properties. However, its bioavailability, safety risks, and in vivo effects and mechanisms against melanoma remain unclear. This research focused on evaluating the safety and prospective antimelanoma impact of simulated gastrointestinal digestion products (FX-ID) on HaCaT and A375 cells.The results indicate that FX-ID exerts negative effects on mitochondria in A375 cells, increases Bax expression, releases Cytochrome C, and activates cleaved caspase-3, ultimately promoting apoptosis. Additionally, FX-ID influences the mitogen-activated protein kinase (MAPK) pathway by enhancing cyclooxygenase-2 (COX-2) and nuclear factor kappa B (NF-κB) levels, consequently facilitating apoptosis and inflammation without significantly impacting HaCaT cells. These findings provide insight into inhibitory mechanism of FX-ID against melanoma, guiding the development of functional foods for prevention.

Peptidomic profile of human milk as influenced by fortification with different protein sources: An in vitro dynamic digestion simulation.

Fortification of human milk (HM) is often necessary to meet the nutritional requirements of preterm infants. The present experiment aimed to establish whether the supplementation of HM with either an experimental donkey milk-derived fortifier containing whole donkey milk proteins, or with a commercial bovine milk-derived fortifier containing hydrolyzed bovine whey proteins, affects peptide release differently during digestion. The experiment was conducted using an in vitro dynamic system designed to simulate the preterm infant's digestion followed by digesta analysis by means of LC-MS-MS. The different fortifiers did not appear to influence the cumulative intensity of HM peptides. Fortification had a differential impact on the release of either donkey or bovine bioactive peptides. Donkey milk peptides showed antioxidant/ACE inhibitory activities, while bovine peptides showed opioid, dipeptil- and propyl endo- peptidase inhibitory and antimicrobial activity. A slight delay in peptide release from human lactoferrin and α-lactalbumin was observed when HM was supplemented with donkey milk-derived fortifier.

RG-I pectic polysaccharides and hesperidin synergistically modulate gut microbiota: An in vitro study targeting the proportional relationship.

In this study, we investigated how different proportions blends of Rhamnogalacturonan-I pectic polysaccharides and hesperidin impact the gut microbiota and metabolites using an in vitro simulated digestion and fermentation model. The results indicated that both of them could modulate the gut microbiota and produce beneficial metabolites. However, their blends in particular proportions (such as 1:1) exhibited remarkable synergistic effects on modulating the intestinal microenvironment, surpassing the effects observed with individual components. Specifically, these blends could benefit the host by increasing short-chain fatty acids production (such as acetate), improving hesperidin bioavailability, producing more metabolites (such as hesperetin, phenolic acids), and promoting the growth of beneficial bacteria. This synergistic and additive effect was inseparable from the role of gut microbiota. Certain beneficial bacteria, such as Blautia, Faecalibacterium, and Prevotella, exhibited strong preferences for those blends, thereby contributing to host health through participating in carbohydrate and flavonoid metabolism.

Comparative proteomic analysis of donor human milk treated by high-pressure processing or Holder pasteurization on undigested proteins across dynamic simulated preterm infant digestion.

High-pressure processing (HPP) of donor human milk (DM) minimally impacts the concentration and bioactivity of some important bioactive proteins including lactoferrin, and bile salt-stimulated lipase (BSSL) compared to Holder pasteurization (HoP), yet the impact of HPP and subsequent digestion on the full array of proteins detectable by proteomics remains unclear. We investigated how HPP impacts undigested proteins in DM post-processing and across digestion by proteomic analysis. Each pool of milk (n = 3) remained raw, or was treated by HPP (500 MPa, 10 min) or HoP (62.5 °C, 30 min), and underwent dynamic in vitro digestion simulating the preterm infant. In the meal, major proteins were minimally changed post-processing. HPP-treated milk proteins better resisted proximal digestion (except for immunoglobulins, jejunum 180 min) and the extent of undigested proteins after gastric digestion of major proteins in HPP-treated milk was more similar to raw (e.g., BSSL, lactoferrin, macrophage-receptor-1, CD14, complement-c3/c4, xanthine dehydrogenase) than HoP.

Modelling Mucus Clearance in Sinuses: Thin-Film Flow Inside a Fluid-Producing Cavity Lined with an Active Surface.

The paranasal sinuses are a group of hollow spaces within the human skull, surrounding the nose. They are lined with an epithelium that contains mucus-producing cells and tiny hairlike active appendages called cilia. The cilia beat constantly to sweep mucus out of the sinus into the nasal cavity, thus maintaining a clean mucus layer within the sinuses. This process, called mucociliary clearance, is essential for a healthy nasal environment and disruption in mucus clearance leads to diseases such as chronic rhinosinusitis, specifically in the maxillary sinuses, which are the largest of the paranasal sinuses. We present here a continuum mathematical model of mucociliary clearance inside the human maxillary sinus. Using a combination of analysis and computations, we study the flow of a thin fluid film inside a fluid-producing cavity lined with an active surface: fluid is continuously produced by a wall-normal flux in the cavity and then is swept out, against gravity, due to an effective tangential flow induced by the cilia. We show that a steady layer of mucus develops over the cavity surface only when the rate of ciliary clearance exceeds a threshold, which itself depends on the rate of mucus production. We then use a scaling analysis, which highlights the competition between gravitational retention and cilia-driven drainage of mucus, to rationalise our computational results. We discuss the biological relevance of our findings, noting that measurements of mucus production and clearance rates in healthy sinuses fall within our predicted regime of steady-state mucus layer development.

YAP/TAZ drives Notch and angiogenesis mechanoregulation in silico.

Endothelial cells are key players in the cardiovascular system. Among other things, they are responsible for sprouting angiogenesis, the process of new blood vessel formation essential for both health and disease. Endothelial cells are strongly regulated by the juxtacrine signaling pathway Notch. Recent studies have shown that both Notch and angiogenesis are influenced by extracellular matrix stiffness; however, the underlying mechanisms are poorly understood. Here, we addressed this challenge by combining computational models of Notch signaling and YAP/TAZ, stiffness- and cytoskeleton-regulated mechanotransducers whose activity inhibits both Dll4 (Notch ligand) and LFng (Notch-Dll4 binding modulator). Our simulations successfully mimicked previous experiments, indicating that this YAP/TAZ-Notch crosstalk elucidates the Notch and angiogenesis mechanoresponse to stiffness. Additional simulations also identified possible strategies to control Notch activity and sprouting angiogenesis via cytoskeletal manipulations or spatial patterns of alternating stiffnesses. Our study thus inspires new experimental avenues and provides a promising modeling framework for further investigations into the role of Notch, YAP/TAZ, and mechanics in determining endothelial cell behavior during angiogenesis and similar processes.

A new approach to modeling transdermal ethanol kinetics.

Measurement of ethanol above the skin surface (supradermal) is used to monitor blood alcohol concentrations (BAC) in both legal and consumer settings. Previously, the relationship between supradermal alcohol concentration (SAC) and BAC was described using partial and ordinary differential equations (PDE model: J. Appl. Physiol. 100: 649-55, 2006). Using a range of BAC profiles by varying absorption times and peak concentrations, the PDE model accurately predicted experimental measures of SAC. Recently, other mathematical models have relied on the PDE model. This paper proposes a new approach to modeling transdermal ethanol kinetics using a mass transfer coefficient and only ordinary differential equations (ODE model). Using a range of BAC profiles, the ODE model performed very similarly to the PDE model. The ODE model had slightly slower washout rates and slightly slower times to peak SAC and to zero SAC. Similar to the PDE model, a sensitivity analysis on the ODE model showed changes in solubility and diffusivity within the stratum corneum, stratum corneum thickness, and the volume of gas above the skin affected model performance. This new model will streamline integration into larger physiologic models, reduce computation time, and decrease the time to transform skin alcohol measurements to blood alcohol concentrations.

Metabolic regulation of mitochondrial morphologies in pancreatic beta cells: coupling of bioenergetics and mitochondrial dynamics.

Cellular bioenergetics and mitochondrial dynamics are crucial for the secretion of insulin by pancreatic beta cells in response to elevated levels of blood glucose. To elucidate the interactions between energy production and mitochondrial fission/fusion dynamics, we combine live-cell mitochondria imaging with biophysical-based modeling and graph-based network analysis. The aim is to determine the mechanism that regulates mitochondrial morphology and balances metabolic demands in pancreatic beta cells. A minimalistic differential equation-based model for beta cells is constructed that includes glycolysis, oxidative phosphorylation, calcium dynamics, and fission/fusion dynamics, with ATP synthase flux and proton leak flux as main regulators of mitochondrial dynamics. The model shows that mitochondrial fission occurs in response to hyperglycemia, starvation, ATP synthase inhibition, uncoupling, and diabetic conditions, in which the rate of proton leakage exceeds the rate of mitochondrial ATP synthesis. Under these metabolic challenges, the propensities of tip-to-tip fusion events simulated from the microscopy images of the mitochondrial networks are lower than those in the control group and prevent the formation of mitochondrial networks. The study provides a quantitative framework that couples bioenergetic regulation with mitochondrial dynamics, offering insights into how mitochondria adapt to metabolic challenges.

Multibody dynamics-based musculoskeletal modeling for gait analysis: a systematic review.

Beyond qualitative assessment, gait analysis involves the quantitative evaluation of various parameters such as joint kinematics, spatiotemporal metrics, external forces, and muscle activation patterns and forces. Utilizing multibody dynamics-based musculoskeletal (MSK) modeling provides a time and cost-effective non-invasive tool for the prediction of internal joint and muscle forces. Recent advancements in the development of biofidelic MSK models have facilitated their integration into clinical decision-making processes, including quantitative diagnostics, functional assessment of prosthesis and implants, and devising data-driven gait rehabilitation protocols. Through an extensive search and meta-analysis of over 116 studies, this PRISMA-based systematic review provides a comprehensive overview of different existing multibody MSK modeling platforms, including generic templates, methods for personalization to individual subjects, and the solutions used to address statically indeterminate problems. Additionally, it summarizes post-processing techniques and the practical applications of MSK modeling tools. In the field of biomechanics, MSK modeling provides an indispensable tool for simulating and understanding human movement dynamics. However, limitations which remain elusive include the absence of MSK modeling templates based on female anatomy underscores the need for further advancements in this area.

The effects of herding and dispersal behaviour on the evolution of cooperation on complete networks.

Evolutionary graph theory has considerably advanced the process of modelling the evolution of structured populations, which models the interactions between individuals as pairwise contests. In recent years, these classical evolution models have been extended to incorporate more realistic features, e.g. multiplayer games. A recent series of papers have developed a new evolutionary framework including structure, multiplayer interactions, evolutionary dynamics, and movement. However, so far, the developed models have mainly considered independent movement without coordinated behaviour. Although the theory underlying the framework has been developed and explored in various directions, several movement mechanisms have been produced which characterise coordinated movement, for example, herding. By embedding these newly constructed movement distributions, within the evolutionary setting of the framework, we demonstrate that certain levels of aggregation and dispersal benefit specific types of individuals. Moreover, by extending existing parameters within the framework, we are not only able to develop a general process of embedding any of the considered movement distributions into the evolutionary setting on complete graphs but also analytically produce the probability of fixation of a mutant on a complete N-sized network, for the multiplayer Public Goods and Hawk-Dove games. Also, by applying weak selection methods, we extended existing previous analyses on the pairwise Hawk-Dove Game to encompass the multiplayer version considered in this paper. By producing neutrality and equilibrium conditions, we show that hawks generally do worse in our models due to the multiplayer nature of the interactions.

The evolution of multicellularity and cell differentiation symposium: bridging evolutionary cell biology and computational modelling using emerging model systems.

'The evolution of multicellularity and cell differentiation' symposium, organized as part of the EuroEvoDevo 2024 meeting on June 25-28th in Helsinki (Finland), addressed recent advances on the molecular and mechanistic basis for the evolution of multicellularity and cell differentiation in eukaryotes. The symposium involved over 100 participants and brought together 10 speakers at diverse career stages. Talks covered various topics at the interface of developmental biology, evolutionary cell biology, comparative genomics, computational biology, and ecology using animal, protist, algal and mathematical models. This symposium offered a unique opportunity for interdisciplinary dialog among researchers working on different systems, especially in promoting collaborations and aligning strategies for studying emerging model species. Moreover, it fostered opportunities to promote early career researchers in the field and opened discussions of ongoing work and unpublished results. In this Meeting Review, we aim to promote the research, capture the spirit of the meeting, and present key topics discussed within this dynamic, growing and open community.

Spatial Nonstationarity in Phenological Responses of Nearctic Birds to Climate Variability.

Climate change is shifting the phenology of migratory animals earlier; yet an understanding of how climate change leads to variable shifts across populations, species and communities remains hampered by limited spatial and taxonomic sampling. In this study, we used a hierarchical Bayesian model to analyse 88,965 site-specific arrival dates from 222 bird species over 21 years to investigate the role of temperature, snowpack, precipitation, the El-Niño/Southern Oscillation and the North Atlantic Oscillation on the spring arrival timing of Nearctic birds. Interannual variation in bird arrival on breeding grounds was most strongly explained by temperature and snowpack, and less strongly by precipitation and climate oscillations. Sensitivity of arrival timing to climatic variation exhibited spatial nonstationarity, being highly variable within and across species. A high degree of heterogeneity in phenological sensitivity suggests diverging responses to ongoing climatic changes at the population, species and community scale, with potentially negative demographic and ecological consequences.

Pharmacokinetic model-guided enoxaparin dosing in the Neonatal ICU: Retrospective cohort study to plan for prospective feasibility trial.

Traditional milligram per kilogram (mg/kg) dosing of enoxaparin in neonates frequently fails to achieve target anti-Xa levels promptly, necessitating repeated laboratory monitoring and dose adjustments. This study investigated whether a personalized dosing strategy based on predicted individual clearance and volume of distribution could improve outcomes, comparing standard-of-care (SOC) mg/kg dosing to pharmacokinetic (PK) model-informed precision dosing (MIPD). A retrospective analysis was conducted on hospitalized neonates treated with enoxaparin at less than 44 weeks postmenstrual age from 2019 to 2022. Data on demographics, drug dosing, PK model covariates, and clinical outcomes were extracted from electronic health records and analyzed using the Pumas-AI Lyv dosing tool. The primary focus was on comparing the initial SOC dose to the MIPD-recommended dose. The secondary outcome measured was the time required to achieve therapeutic anti-Xa levels. The study included 168 neonates with a median postnatal age of 15 days (range 1-149) and a median dosing weight of 3.1 kg (range: 0.82-5.2). MIPD-recommended initial doses were 20%-60% higher than SOC doses in 32% of the cases and over 60% higher in 11% of cases. Neonates who received SOC doses that were much lower than the MIPD recommendation showed the longest delays in reaching therapeutic anti-Xa levels. The results indicate that PK model-informed of enoxaparin dosing leads to higher initial dosages than SOC in neonates, potentially reducing the time to therapeutic anti-Xa levels. These findings are being utilized to define dosing limits for a prospective trial of MIPD in neonatal intensive care settings.

Predicting the first steps of evolution in randomly assembled communities.

Microbial communities can self-assemble into highly diverse states with predictable statistical properties. However, these initial states can be disrupted by rapid evolution of the resident strains. When a new mutation arises, it competes for resources with its parent strain and with the other species in the community. This interplay between ecology and evolution is difficult to capture with existing community assembly theory. Here, we introduce a mathematical framework for predicting the first steps of evolution in large randomly assembled communities that compete for substitutable resources. We show how the fitness effects of new mutations and the probability that they coexist with their parent depends on the size of the community, the saturation of its niches, and the metabolic overlap between its members. We find that successful mutations are often able to coexist with their parent strains, even in saturated communities with low niche availability. At the same time, these invading mutants often cause extinctions of metabolically distant species. Our results suggest that even small amounts of evolution can produce distinct genetic signatures in natural microbial communities.

Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects.

Understanding biotic interactions is a crucial goal in community ecology and species distribution modelling, and large strides have been made towards improving multivariate computational methods with the aim of quantifying biotic interactions and improving predictions of species occurrence. Yet, while considerable attention has been given to computational approaches and the interpretation of these quantitative tools, the importance of sampling design to reveal these biotic interactions has received little consideration. This study explores the influential role of priority effects, that is, the order of habitat colonisation, in shaping our ability to detect biotic interactions. Using a simple set of simulations, we demonstrate that commonly used cross-sectional co-occurrence data alone cannot be used to make reliable inferences on asymmetric biotic interactions, even if they perform well in predicting the occurrence of species. We then show how sampling designs that consider priority effects can recover the asymmetric effects that are lost when priority effects are ignored. Based on these findings, we urge for caution when drawing inferences on biotic interactions from cross-sectional binary co-occurrence data, and provide guidance on sampling designs that may provide the necessary data to tackle this longstanding challenge.

Variation in Oceanographic Resistance of the World's Coastlines to Invasion by Species With Planktonic Dispersal.

For marine species with planktonic dispersal, invasion of open ocean coastlines is impaired by the physical adversity of ocean currents moving larvae downstream and offshore. The extent species are affected by physical adversity depends on interactions of the currents with larval life history traits such as planktonic duration, depth and seasonality. Ecologists have struggled to understand how these traits expose species to adverse ocean currents and affect their ability to persist when introduced to novel habitat. We use a high-resolution global ocean model to isolate the role of ocean currents on the persistence of a larval-producing species introduced to every open coastline of the world. We find physical adversity to invasion varies globally by several orders of magnitude. Larval duration is the most influential life history trait because increased duration prolongs species' exposure to ocean currents. Furthermore, variation of physical adversity with life history elucidates how trade-offs between dispersal traits vary globally.

Microbial Dormancy Supports Multi-Species Coexistence Under Resource Fluctuations.

The ability for microbes to enter dormant states is adaptive under resource fluctuations and has been linked to the maintenance of diversity. Nevertheless, the mechanism by which microbial dormancy gives rise to the density-dependent feedbacks required for stable coexistence under resource fluctuations is not well understood. Via analysis of consumer-resource models, we show that the stable coexistence of dormancy and non-dormancy strategists is a consequence of the former benefiting more from resource fluctuations while simultaneously reducing overall resource variability, which sets up the requisite negative frequency dependence. Moreover, we find that dormants can coexist alongside gleaner and opportunist strategies in a competitive-exclusion-defying case of three species coexistence on a single resource. This multi-species coexistence is typically characterised by non-simple assembly rules that cannot be predicted from pairwise competition outcomes. The diversity maintained via this three-way trade-off represents a novel phenomenon that is ripe for further theoretical and empirical inquiry.

The Hierarchical Coevolutionary Units of Ecological Networks.

In ecological networks, cohesive groups of species may shape the evolution of interactions, serving as coevolutionary units. Ranging across network scales, from motifs to isolated components, elucidating which cohesive groups are more determinant for coevolution remains a challenge in ecology. We address this challenge by integrating 376 empirical mutualistic and antagonistic networks and coevolutionary models. We identified cohesive groups at four network scales containing a significant proportion of potential direct coevolutionary effects. Cohesive groups displayed hierarchical organisation, and potential coevolutionary effects overflowing lower-scale groups were contained by higher-scale groups, underscoring the hierarchy's impact. However, indirect coevolutionary effects blurred group boundaries and hierarchy, particularly under strong selection from ecological interactions. Thus, under strong selection, indirect effects render networks themselves, and not cohesive groups, as the likely coevolutionary units of ecological systems. We hypothesise hierarchical cohesive groups to also shape how other forms of direct and indirect effects propagate in ecological systems.