Retention Model Research Articles

A hysteretic water retention model incorporating the soil deformability and its application to rainfall-induced landslides

Traditional water retention models often overlook the dynamic interplay between soil structure and moisture content, leading to inaccurate predictions of unsaturated soil behaviors. In this research, based on laboratory data, van Genuchten’s soil water characteristic (van Genuchten, 1980) is modified to establish two bounding surfaces that define the permissible range of soil states in terms of the void ratio (e), suction (s), and degree of saturation (Sl). Considering a bounding surface technique, the model effectively captures hysteresis in the soil water retention behavior, encompassing main curves and scanning paths. This approach presumesthat within the permissible range of soil states, which is included between two main surfaces, the derivative of the degree of saturation by void ratio and suction relieson the soil state’s proximity to the main bounding surface. This hypothesis guarantees that the wetting–drying or compressing-swelling scanning curves transit smoothly toward their corresponding main surfaces. The derived equations for Sl are integrated into closed forms, allowing all scanning curves to be distinguished by varying values of the integration constant. Model necessitates the determination of two parameters (b and β) related to the slope and intercept of the linear line interpolating experiments in the ln(s)-ln(eSl/s) plane, which can be defined based on at least a single wetting–drying test. The model predictions are validated against various data sets, including sands and clayey soils, published in the literature. This validation demonstrates the model’s ability to reflect the behavior observed in experimental tests accurately. This new technique offers a significant advantage in the simplicity of parameter determination. Finally, this hysteretic water retention procedure is implemented into a finite element program (Code_Bright), and its performance is evaluated by simulating the behavior of a representative slope subjected to rainfall conditions.

Understanding the fundamentals of the on-off retention mechanism of oligonucleotides and their application to high throughput analysis

Ion-pair reversed-phase liquid chromatography (IP-RPLC) is clearly recognized as the gold standard for analyzing therapeutic oligonucleotides (ONs). Recent studies have shown that ONs exhibit an on-off retention behavior in IP-RPLC, meaning that minor changes in acetonitrile (ACN) proportion can significantly impact retention. However, this behavior was initially demonstrated with only a single mobile phase condition. The aim of this study is to gain a deeper understanding of ON elution behavior by measuring the S values (slope of the retention model, log k vs.%ACN) across a broad range of mobile phase conditions. We systematically calculated the S values for both a 20-mer and 100-mer model ON under various conditions, including different IP reagents, IP concentrations, mobile phase pH, column temperatures, and two different buffering acids. We demonstrated that these mobile phase conditions impact the S values in the following order: IP hydrophobicity > IP concentration > column temperature > buffering acid > mobile phase pH. The main explanation for this trend is that mobile phase conditions that reduce the ion-pair retention mechanism (such as low IP hydrophobicity or concentration) will enhance the impact of% ACN on retention, leading to higher S values.In the second part of the study, this knowledge was used to develop ultra-fast separations for two therapeutic oligonucleotides: a 20-mer antisense oligonucleotide (ASO) without phosphorothioate (PS) modifications and a large single guide RNA (sgRNA) that includes certain PS modifications. The mobile phase conditions were optimized to maximize S values, while preventing the separation of diastereomers. It is important to notice that an S-value of at least 30 is required to benefit from the use of ultra-short columns. This approach allows the successful separation of the main species (ASO and sgRNA) and related impurities in less than one minute using a 5 mm length column.

Global retention models in reversed-phase liquid chromatography. A tutorial

Global retention models in reversed-phase liquid chromatography. A tutorial

The performance of two urban flood regulation models using different input data

Increasing climate change has led to an increase in urban flood events. Events with a return period of twenty years become events with a period of two to three years. The primary objectives of this study are to evaluate the performance of flood regulation models using different input data and compare their performance for flood regulation supply (FRS) assessment. The assessment of the ecosystem services of urban FRS was performed using two models: Urban Flood Risk Mitigation (UFRM) by Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and IMECOGIP Waterflow Regulation (Retention Model) (WRRM). They rely on relatively accessible open-source data, require a short time to model each scenario and provide opportunities to interpret results in different spatial and measurement units. We performed several improvements to the input data, including updating the national ecosystem-type assessment for the case study area by connecting it with the Urban Atlas typology and proposing an approach for soil data refinement. The outputs of the two models show significant differences in FRS values for each land-use/land-cover (LULC) class. The UFRM assesses different impervious urban classes with different values, varying from very low to medium. In contrast, the WRRM assesses the FRS in densely sealed areas with one fixed value for low supply (where nearly all rainfall is transformed into runoff).

A triadic model of job retention and turnover dynamics in the hospitality industry

Purpose This study aims to examine key factors influencing hospitality employee turnover in a post-pandemic context, challenging conventional assumptions about the role of demographics and work-related factors in retention decisions. Design/methodology/approach The research adopted a comprehensive framework using the capability approach and geospatial data analysis, integrating social vulnerability indexes with survey responses from 797 hospitality employees. This study analyzed turnover intentions across demographics, job roles and regions, focusing on Florida’s I-4 corridor. Findings Individual conversion factors like age and marital status were the strongest predictors of turnover, with older and married employees less likely to leave their jobs. In contrast, traditional variables like income, education and job type did not significantly influence turnover intentions. The pandemic blurred distinctions between job roles, highlighting personal circumstances, health risks and economic pressures as critical factors. Contrary to expectations, financial assistance did not significantly reduce turnover intentions. In addition, employees’ life circumstances, such as social vulnerability, influence labor relations and turnover more than work-related conditions. Research limitations/implications This study enriches turnover literature by confirming that personal life circumstances, like age and marital status, are pivotal in understanding employee retention. It challenges conventional demographic and work-related predictors and urges future research to explore the interaction between personal and professional factors in the hospitality industry. The study’s agent-based framework deepens the understanding of how various factors shape employee decisions to stay or leave. Practical implications The findings suggest that hospitality employers must develop more localized, employee-centric retention strategies, especially for younger employees. Tailored approaches considering regional and demographic differences, such as providing career development opportunities and flexible work conditions, could foster long-term loyalty. In rural areas, retention efforts should focus on improving job satisfaction and community support, while in urban areas, strategies prioritize career progression and flexibility. Social implications The study’s findings have significant social implications, particularly in reshaping how employee retention strategies are developed in the hospitality industry. By emphasizing life circumstances over traditional work-related factors, the research highlights the importance of supporting employees’ resilience, especially for those facing social vulnerability. Employers may need to create more flexible and inclusive policies that account for personal, economic and health-related challenges. In addition, the findings suggest that financial aid alone is insufficient in reducing turnover, calling for a more holistic approach that integrates emotional and social support to foster a more stable and loyal workforce. Originality/value This study challenges traditional turnover models by shifting focus from work-related factors to life circumstances, particularly the resilience of older and married employees. It integrates three dimensions – personal (sociodemographics), social (support) and environmental (job type, pandemic challenges) – to examine their influence on employee agency. This triadic framework offers insights into how individual, social and contextual factors shape turnover decisions.

Forest ecosystem services of water-related filtration and regulation, a multi-source assessment and economic valuation in Mangla watershed

ABSTRACT Watershed forests offer crucial ecosystem services for hydrological systems. This study provides comprehensive insights into sediment retention within the Mangla watershed. We analyzed spatial layers from Sentinel-2 imagery, land use data, weather, soil properties, and terrain characteristics to identify soil erosion and sediment delivery hotspots. Using the Integrated Valuation of Environmental Services and Tradeoffs-sediment delivery ratio (InVEST-SDR) model, we quantified sediment exported to the downstream Mangla Dam. The InVEST-sediment retention (InVEST-SR) model estimated the sediment retention capacity of various land cover types. Our findings show that forests retained 20,300.70 tons of sediment in 2017 and 29,887.60 tons in 2021, making them the primary source of sediment retention. The economic value of this ecosystem service was approximately USD 2.59 trillion for 973,168.51 ha of forest in 2017 and USD 4.02 trillion for 1,023,927 ha in 2021. Understanding the dynamics and economic value of this forest ecosystem service at a large watershed scale provides essential insights for decision-making and conservation efforts aimed at protecting water resources and ecological integrity.

Ion-pair reversed-phase chromatography analysis of oligonucleotides using ultra-short (20 x 2.1 mm) columns. Tutorial

With this work, we present a comprehensive tutorial for the analysis of oligonucleotides (ONs, 5 to 100 mer) using ion-pair reversed-phase liquid chromatography (IP-RPLC) on ultra-short columns (20 × 2.1 mm). We explore the impact of ion-pairing (IP) agents on ON retention and demonstrate that while IP agents significantly influence absolute retention, their effect on selectivity is often minimal. Our findings emphasize the utility of systematic method development, including software-assisted retention modeling, to optimize gradient steepness and temperature such that resolution can be optimized for both sequence and length variants. We recommend the use of low-adsorption column hardware to minimize nonspecific interactions, which is to the benefit of improving method robustness, peak shapes and recovery (especially of shortmer impurities). Our results confirm the utility of so-called ultra-short column formats as is demonstrated by way of the example, quick run time separations and high-throughput ON analyses. The study establishes practical guidelines for developing robust, reproducible, and high-efficiency IP-RPLC methods for ONs which will be of assistance to analysts working on new therapeutics and new sequencing and diagnostic reagents alike.

On the fractionation of lignin oligomers by stepwise gradient reversed-phase liquid chromatography

With the increased interest in lignin valorization, the analytical challenge to separate a complex mixture of a vast number of phenolics has made chromatography an indispensable step in lignin analysis. High-resolution separations, such as gas chromatography, reversed-phase liquid chromatography and supercritical fluid chromatography have typically been targeting low-molecular-weight compounds, while larger lignin oligomers have received less attention. These compounds have proven to be difficult to separate due to the inherent complexity of the high-molecular-weight fraction of lignins, in fact, even high-resolving linear reversed-phase gradients elute them as one wide zone. To tackle this, in this study we show that a crude fractionation of lignin oligomers can be achieved by applying stepwise reversed-phase gradients. A commonly employed reversed-phase system with water:acetonitrile mobile phase is evaluated for this task. Special attention was devoted to uncovering the molecular level explanation of the retention phenomenon. Our results indicate that separation is mainly governed by reversed-phase retention phenomena without any major exclusion or viscosity-related effects, shown by great fits to linear retention models (R2avg = 0.9599 for five different oligomers) and apparent differences in retentivity between different stationary phases. The influence of the gradient shape was demonstrated by the comparison of stepwise gradients with different number and frequency of steps, leading to the conclusion that gradients with a low number of steps yield fewer, but better resolved fractions, while finer multi-step gradients can be used to distinguish more fractions.

Transitioning to rural practice together: a rural fellowship model (in 6 Ps).

Maintaining a robust healthcare workforce in underserved rural communities continues to be a challenge. To better meet healthcare needs in rural areas, training programs must develop innovative ways to foster transition to, and integration into, these communities. Mountain Area Health Education Center designed and implemented a 12-month post-residency Rural Fellowship program to enhance placement, transition, and retention in rural North Carolina. Utilizing a '6 Ps' framework, the program targeted physicians and pharmacists completing residency with the purpose of recruiting and supporting their transition into the first year of rural practice. To better understand Rural Fellows' experiences and the immediate impact of their Fellowship year, we conducted a semi-structured interview using a narrative technique and evaluated retention rates over time. Interviews with the eight participants, which included Fellowship alumni and current Fellows, demonstrated the impact and influence of the key curricular '6 Ps' framework. An early retention rate of 100% and a long-term retention rate of 87%, combined with expressed clarity of curricular knowledge, skills, and attitudes related to the '6 Ps', demonstrate the potential and effectiveness of this Rural Fellowship model. Participants indicated the Rural Fellowship experience supports the transition to rural practice communities and expands their clinical skills. The Rural Fellowship program demonstrates an effective model to support early career healthcare providers as they begin practice in rural communities in western North Carolina through academic opportunities, personal growth, and professional development. Implementation of this model has demonstrated the success of a rural retention model over a 6-year period. This model has the potential to target an array of clinical providers and disciplines. We started with family medicine and have expanded to psychiatry, obstetrics, pharmacy, and nursing. This study demonstrated that this model supports clinical providers during the critical transition period from residency to practice. Targeting the most important stage of one's medical training, the commencement of professional practice, this is a scalable model for other rural-based health professions education sites where rural recruitment and retention remain a problem.

Peptide retention time prediction for electrostatic repulsion-hydrophilic interaction chromatography

Electrostatic Repulsion-Hydrophilic Interaction Chromatography (ERLIC) is one of the legacy separation tools developed by Dr. Andrew Alpert and has been used for developing unique separation methods of hydrophilic compounds, including peptides. In the past it has been studied using designed peptide libraries to elucidate major features of its separation mechanism, while comprehensive peptide retention modeling for ERLIC is still lacking. In this work we employed a proteomics-derived ∼170,000 peptide retention datasets to evaluate major ERLIC retention features using the framework of our Sequence-Specific Retention Calculator model. The separation conditions were adjusted to obtain a wider proteome coverage, particularly for non-modified peptides, resulting in a superior separation orthogonality for a 2D LC combination with reversed-phase C18 LC-MS in the second dimension. The SSRCalc ERLIC model presents a consistent theme with the existing ERLIC retention mechanism, reflecting a dependence on peptide orientation and the position of charged and hydrophilic residues across the peptide backbone. R2 values of 0.935 and 0.955 accuracy were demonstrated for the standard interpretable SSRCalc model and machine learning algorithm, respectively. The effects of various PTMs on peptide retention were evaluated in this study, covering spontaneous (oxidation, deamidation) and enzymatic (N-terminal acetylation, phosphorylation, glycosylation) modifications.

Segmental retention models for representing the hydraulic properties of evolving structured soils

AbstractCommon parametrizations of soil hydraulic properties rely on unimodal curves, which cannot accurately represent the properties of many macroporous, aggregated, mixed, or compacted soils. Multimodal hydraulic curves are increasingly used to represent these structured soils in eco‐hydrological models, but the dynamics of the processes that shape soil structure—and the resulting dynamics of soil hydraulic properties—are often neglected. In cases such as compaction recovery, where the structure‐shaping process can be modeled, coupling the evolving pore volumes to soil hydraulic properties in a physically based way remains challenging. Here, we show how modeled or estimated soil structure evolution, when expressed as a time series of porosities in a few pore size classes, can be assimilated into established models of soil hydraulic properties. Our method relies on the division of retention models into smooth segments, whose water contents can be independently adjusted. We apply the approach to examples of modeled soil structure evolution from the published literature: one describing soil structure recovery after compaction and one describing structure formation as a result of organic amendment. In the cases considered, the estimated soil hydraulic conductivity varies more strongly than the modeled porosity which drives it. This shows that transport‐related soil functions can be impacted longer (after compaction) or sooner (after amendment) than suggested by the evolution of structural metrics such as porosity. In general, modeling the evolution of soil hydraulic properties in cases such as these paves the way for holistic, process‐based modeling of land management practices and their impact on soil functioning.

Molecular H2 in silicate melts

A series of hydrothermal diamond anvil cell experiments was conducted to constrain the equilibrium distribution of molecular H2 between H2O-saturated sodium aluminosilicate melts and H2O at elevated temperatures (600–800 °C) and pressures (317–1265 MPa). The distribution of H2 between the silicate liquid and the aqueous fluid was achieved through real-time monitoring of the H-H stretching vibration under in situ conditions using Raman vibrational spectroscopy. Results show that the solubility of H2 in silicate melts saturated with H2O decreases as the temperature increases, with control exerted by the mole fraction of H2O in the melt. The dissolution of H2 in the hydrous silicate melts appears to follow Henrian behavior, resembling that of an inert, neutral non-polar species. To express species solubility as a function of temperature (T in K) an empirical equation was developed:ln Km/f = 11.4 (±1.3) *1000 / T (K) − 18.7 (±1.1)where Km/f is the equilibrium constant for the reaction H2(g) = H2(melt). This equation was derived by integrating data from the current and prior experimental studies that include silicate melts with varying H2O saturation levels. It should be deemed applicable within the temperature range of 600–1450 °C and pressures ranging from 0.3 to 3 GPa. The implications are extended into developing an understanding of the H partitioning between H2-rich atmospheres blanketing magma oceans in the early history of planetary bodies. For example, transferring H from primordial atmospheric envelopes to the interior of rocky exoplanets may be less efficient than previously believed, which should be considered in models of volatile retention. Experimental data also suggest that minimal amounts of solar nebula H2 are likely to dissolve in the molten surface of primitive objects in the protoplanetary disk (∼10−5 to 10−9 mol faction H2 in melt), contradicting the highly reducing conditions observed in chondrule mineral compositions.

Novel injectable polypeptide nanoparticle encapsulated siRNA targeting TGF-β1 and COX-2 for localized fat reduction I: Preclinical invitro and animal models.

Obesity and localized fat accumulation continue to drive the demand for minimally invasive body contouring technologies including injectable compounds for local fat reduction. siRNA offers a potential for an injectable to specifically target and silence genes involved in adipogenesis with minimal inflammatory side effects. This study evaluates the efficacy of STP705, an injectable containing siRNA encapsulated within histidine-lysine polypeptide (HKP) nanoparticles targeting transforming growth factor β1 (TGF-β1) and cyclooxygenase-2 (COX-2), crucial mediators in adipocyte differentiation and fat retention, using invitro, porcine, and murine models. In vitro experiments on mouse preadipocytes and invivo trials using Diet Induced Obese (DIO) mice and Yucatan minipigs were conducted to assess the gene silencing efficiency, tissue localization, pharmacodynamics, and safety profile of STP705. STP705 effectively reduced the expression of TGF-β1 and COX-2, with a notable decrease in adipocyte volume and lipid content without adverse systemic effects. In DIO mice, the HKP-siRNA complex demonstrated precise localization to injected adipose tissue, maintaining significant gene silencing, and detectable levels of siRNA for up to 14 days post-administration. Similar results in minipigs showed a significant reduction in subcutaneous adipose tissue thickness. The results of these studies support the use of targeted siRNA therapy specifically targeting TGF-β1 and COX-2, for localized fat reduction, offering a potential minimally invasive alternative to current fat reduction methods.

Assessing Institutional Performance Using Machine Learning Algorithms

In Middle Eastern nations, social media has grown in importance in influencing political and governmental choices. In Iraq, Facebook is regarded as one of the most widely used social networking sites. The underutilization of this tool for evaluating institutional performance persists. Thus, using sentiment analysis on Facebook, this study suggests a methodology that aids organizations like the Ministry of Justice in Iraq in assessing their own performance. The model makes use of a variety of machine learning methods, including Naive Bayes, Logistic Regression, and Support Vector Machine. TF-IDF (Term Frequency-Inverse Document Frequency) was used to convert the textual data into numerical features, which is essential for effective text analysis. Additionally, features were carefully managed by utilizing both unigram and bigram models. Using datasets from (Facebook pages belonging to the Iraqi Ministry of Justice), a thorough experimental investigation was conducted. The results of our experiments showed that the SVM algorithm produced the best accuracy, at 98.311%. following the suggested model's retention of a few stop words, which was shown to significantly improve the algorithm's performance and guarantee accurate categorization of comments while maintaining the content of the phrase.

Role of In Vitro Tests in the Characterisation of Locally Applied, Locally Acting Drugs in the Throat: Application to Flurbiprofen.

Background/Objectives: For locally applied, locally acting generic drug products, comparison to an originator product based on systemic exposure is usually not feasible due to low plasma concentrations and inadequate reflection of local exposure at the site of action. Where a validated PD model exists, a comparative clinical study can be performed in healthy subjects; where no surrogate endpoint is available, patients with the relevant indication need to be enrolled, with all the associated factors which could result in lack of sensitivity. Even though the need for alternative in vitro approaches has been acknowledged by both industry and regulatory bodies, the complexity of in vivo drug delivery processes makes the development of guidance documents particularly difficult. Our objective was to present in vitro approaches less classically used and to address in vivo relevance of the selected tests. Methods: This article analyses current regulatory approaches in Europe and the U.S., and highlights the key advantages of in vitro tests in terms of their sensitivity, reliability, reproducibility and in vivo relevance using locally applied flurbiprofen in various formulations. Results: The in vitro esophageal retention (IVOR) model demonstrates that the first 6-10 min after application of different flurbiprofen formulations is important for their comparison and also offers the best correlation with in vivo data using the partial area under the concentration-time curves (pAUCs). Rheological evaluations further demonstrated that the mucoadhesive properties of the gel spray formulation are based on interaction with mucin. Conclusions: Designing a relevant in vitro test requires adequate evaluation of the complexity of the drug substance, drug product, dosing conditions and delivery processes.

Abstract B170: Advancing cancer disparities research through the integration of new data: Opportunities from the National Institutes of Health All of Us Research Program

Abstract The NIH All of Us Research Program is building one of the largest, richest, and most diverse health datasets of its kind. The program aims to promote health equity across multiple health conditions including cancer by making a comprehensive and diverse dataset available to over 10,000 vetted and registered researchers on its Researcher Workbench (RW). The RW offers access to various data types including genomics, electronic health records, physical measurements, wearable data, and survey data on social determinants of health (SDOH) and self- reported cancer diagnoses. The latest data release (Q3 2024), also known as the Curated Data Repository (CDR Version 8) includes data from over 630,000 participants, with more than 80% from populations underrepresented in biomedical research (UBR). Racial, ethnic minoritized populations and other underrepresented groups are more likely to experience health-related disparities and inequities. While previous data releases included aggregate categories, new data released in CDR Version 8 considers the interplay of self-identified categories of demographic descriptors and allows the examination of comorbidities, while emphasizing the importance of identifying appropriate comparator groups in research and considering the heterogeneity that exists within and across groups. It includes a 40% increase in array data, a 67% increase in srWGS data, and a 150% increase in long-read sequences, as well as data from expanded EHR sources, DHT devices, a new Life Functioning Survey, and racial and ethnic subcategories for more than 610,000 participants. This vast and diverse dataset release enables the examination of the intersecting impact of SDOH on cancer-related outcomes both within and across racial and ethnic populations, including populations experiencing health-related disparities and inequities. The extensive data release is facilitated by a two-pronged approach: A robust community and participant engagement model and the All of Us Health Equity strategic plan (HESP). The program employs a socioecological model for participant recruitment and retention, specifically targeting UBR groups. This multi-level approach encompasses activities ranging from targeted outreach and awareness campaigns to establishing trust and fostering collaborative partnerships with communities and participants. HESP complements these efforts by promoting the integration of equity considerations across the research lifecycle through the promotion of data equity and data justice. This community engagement and equity integrated approach guarantees that participants who reflect the demographic diversity of cancer patients in the United States and territories are actively engaged in shaping and benefiting from cancer disparities research. This session will update the scientific audience on recent data expansions available to researchers, provide examples of how that data can be used to examine disparities in cancer outcomes and prevention, and demonstrate the importance of community engagement and health equity in advancing research. Citation Format: Karriem S Watson, JoAnn Smith, Nandita Rahman, Ryan Lupi, Rubin Baskir, Romuladus Azuine, Janeth Sanchez. Advancing cancer disparities research through the integration of new data: Opportunities from the National Institutes of Health All of Us Research Program [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B170.

A synthetic review: natural history of amniote reproductive modes in light of comparative evolutionary genomics

ABSTRACTThere is a current lack of consensus on whether the ancestral parity mode was oviparity (egg‐laying) or viviparity (live‐birth) in amniotes and particularly in squamates (snakes, lizards, and amphisbaenids). How transitions between parity modes occur at the genomic level has primary importance for how science conceptualises the origin of amniotes, and highly variable parity modes in Squamata. Synthesising literature from medicine, poultry science, reproductive biology, and evolutionary biology, I review the genomics and physiology of five broad processes (here termed the ‘Main Five’) expected to change during transitions between parity modes: eggshell formation, embryonic retention, placentation, calcium transport, and maternal–fetal immune dynamics. Throughout, I offer alternative perspectives and testable hypotheses regarding proximate causes of parity mode evolution in amniotes and squamates. If viviparity did evolve early in the history of lepidosaurs, I offer the nucleation site hypothesis as a proximate explanation. The framework of this hypothesis can be extended to amniotes to infer their ancestral state. I also provide a mechanism and hypothesis on how squamates may transition from viviparity to oviparity and make predictions about the directionality of transitions in three species. After considering evidence for differing perspectives on amniote origins, I offer a framework that unifies (i) the extended embryonic retention model and (ii) the traditional model which describes the amniote egg as an adaptation to the terrestrial environment. Additionally, this review contextualises the origin of amniotes and parity mode evolution within Medawar's paradigm. Medawar posited that pregnancy could be supported by immunosuppression, inertness, evasion, or immunological barriers. I demonstrate that this does not support gestation or gravidity across most amniotes but may be an adequate paradigm to explain how the first amniote tolerated internal fertilization and delayed egg deposition. In this context, the eggshell can be thought of as an immunological barrier. If serving as a barrier underpins the origin of the amniote eggshell, there should be evidence that oviparous gravidity can be met with a lack of immunological responses in utero. Rare examples of two species that differentially express very few genes during gravidity, suggestive of an absent immunological reaction to oviparous gravidity, are two skinks Lampropholis guichenoti and Lerista bougainvillii. These species may serve as good models for the original amniote egg. Overall, this review grounds itself in the historical literature while offering a modern perspective on the origin of amniotes. I encourage the scientific community to utilise this review as a resource in evolutionary and comparative genomics studies, embrace the complexity of the system, and thoughtfully consider the frameworks proposed.

A numerical analysis of Thermo–Hydro–Mechanical behavior in the FE experiment at Mont Terri URL: Investigating capillary effects in bentonite on the disposal system

We investigated thermo–hydro–mechanical (T-H–M) coupled behavior observed during the full-scale heater emplacement experiment at the Mont-Terri underground research laboratory conducted in the Opalinus clay as part of the DECOVALEX-2023 Task C project. Utilizing the OGS-FLAC simulator, we created a three-dimensional model to simulate multiphase flow in the experiment, applying extended Philip and de Vries’ model and incorporating the anisotropic T–H–M properties of the Opalinus clay. The simulation, which included a ventilation process, spanned five years of heating experiments and successfully replicated the measured temperature, pore pressure, displacement, and relative humidity results in bentonite and host rock during the experiment. The analysis revealed that capillary pressure significantly influenced the pore pressure change in the host rock near the tunnel, while thermal pressurization became dominant with increasing distance. Consequently, we conducted a sensitivity analysis on a simplified model to evaluate the effect of capillary pressure on the disposal system. Capillarity is a dominant factor for the multiphase flow depending on the distance from the heat. Variations in capillary pressure were observed depending on the gas entry pressure and water retention model, indicating that the capillarity of unsaturated bentonite could inherently affect the T–H–M results within the disposal system.

Theoretical predictions to facilitate the method development in slalom chromatography for the separation of large DNA molecules

Slalom chromatography (SC) re-emerged in 2024 due to the availability of low adsorption ultra-high pressure liquid chromatography (UHPLC) packed columns/instruments and large modalities being investigated in the context of cell and gene therapies. The physico-chemical principles of SC retention combined with hydrodynamic chromatography (HDC) exclusion have been recently reported. In SC, DNA macromolecules are retarded because: (1) they can be stretched to lengths comparable to the particle diameter, and (2) their elastic relaxation time is long enough to maintain them in non-equilibrium extended conformations under regular UHPLC shear flow conditions. Here, a quantitative HDC-SC retention model is consolidated. A general plate height model accounting for the band broadening of long DNA biopolymers along packed beds is also derived for supporting method development and predicting speed-resolution performance in SC.For illustration, the chromatographic speed-resolution properties in SC are predicted for the separation of specific critical pairs (4.0/4.5, 10/11, and 25/27 kbp) of linear dsDNA polymers. The calculations are performed for two available custom-made particle sizes, dp= 1.7 and 2.5μm, at a constant pressure of 10,000 psi. The predictions are directly validated from experimental data acquired using low adsorption MaxPeakTM 4.6 mm i.d. Columns packed with 1.7μm BEHTM 45 Å (15 cm long column) and 2.5μm BEH 125 Å (30 cm long column) Particles, and by injecting six linear dsDNAs (λ DNA-Hind III Digest). The LC system is very low dispersion ACQUITYTM UPLCTM I-class PLUS System, and the mobile phase is a 100 mM phosphate buffer at pH 8. Maximum resolution is always achieved when the average extended lengths of linear dsDNAs are equal to a critical length, which is proportional to the particle diameter and to the square root of the applied shear rate. Most advantageously, the experimental results reveal that the relaxation times of linear dsDNAs observed under shear flow conditions are two orders of magnitude shorter than those expected in the absence of flow: this enables the detection of the longest linear dsDNAs up to 25 kbp without irremediable loss in column performance. Finally, the retention-efficiency model elaborated in this work can be used to rapidly anticipate and develop methods (selection of particle size, column length, and operating pressure) for any targeted DNA and time-resolution constraints.

Effect of Circadian Rhythm Modulated Blood Flow on Nanoparticle based Targeted Drug Delivery in Virtual In Vivo Arterial Geometries.

A novel integration of nanoparticle-based drug delivery framework with shear-rate dependent blood flow model is presented. The framework is comprised of a unique combination of mechanics-based dispersion model, an asperity model for endothelium surface roughness, and a stochastic nanoparticle-endothelial cell adhesion model. Simulations of MRI based in vivo carotid artery system showcase the effects of vessel geometry on nanoparticle adhesion and retention at the targeted site. Vessel geometry and target site location impact nanoparticle adhesion; curved and bifurcating regions favor local accumulation of drug. It is also shown that aligning drug administration with circadian rhythm and sleep cycle can enhance the efficacy of drug delivery processes. These simulations highlight the potential of the computational modeling for exploring circadian rhythm modulated blood flow for targeted drug delivery while minimizing the in vivo experimentation.