Retention Model Research Articles

Importance of different factors for modeling nitrate transport and retention in a tile-drained agricultural catchment with distance-based generalized sensitivity analysis

Modeling of nitrate transport and retention in agricultural land use areas provides useful information to support water quality assessment and management. The accuracy and precision of model simulations are highly dependent on model input factors for which the appropriate values are generally difficult to determine and from which various uncertainties are induced into the modeling procedure. In this study, we applied a Distance-based Generalized Sensitivity Analysis (DGSA) to a high-resolution (25 × 25 m) nitrate transport and retention model for a tile-drained agricultural catchment (4.4 km2) to investigate the extent to which model input factors affect the spatially distributed nitrate retention. The input factors included the nitrate leaching from the root zone, the partitioning of nitrate into tile drainage and groundwater flux, the groundwater flux out of the catchment, the hydrogeological properties, and the denitrification rates in groundwater. The DGSA results were examined in both spatially lumped and distributed perspective. We found that the partitioning of nitrate into tile drainage and groundwater flux was the most important factor for modeling nitrate retention while the hydrogeological properties were secondary but also important. Conversely, the nitrate leaching from the root zone and denitrification rates in groundwater were noninfluential. By increasing the resolution of the DGSA analysis from catchment to model pixel, we found that input factors noninfluential on catchment scale were influential on pixel scale in discrete areas, and, as a general take-home-message, input factors influential on nitrate retention in at least 25 % of the model pixels were sensitive on catchment scale as well. Improved understanding of sensitivity of modelling nitrate retention may help the modelers and water managers to decide which input factors to prioritize in the modelling and data collection to improve the accuracy and precision of the model responses.

BART: A transferable liquid chromatography retention time library for bile acids

Identification of unknown bile acids, especially the distinguishment between isomers, requires retention times of a large number of reference standards, which are often not commercially available. Meanwhile, published retention information cannot be directly transferred across labs due to the differences between liquid chromatography (LC) systems, such as different extra column volume and dwell volume. To improve this situation, a transferrable retention time library for bile acids named BART was developed. BART was composed of isocratic retention models of 272 bile acids and a software tool to predict their gradient retention times on various LC systems. The isocratic retention times of bile acids were acquired on a Waters BEH C18 column with mobile phases of acidic ammonium acetate buffer and acetonitrile, and fit to the quadratic solvent strength model (QSSM). Segmented linear gradient retention times were calculated with holdup time (t0), dwell time (tD) and actual gradient profile corrected using 21 bile acid calibration standards. In addition to the reference system where the isocratic retention times were acquired, this approach has been validated on four other LC-MS systems in four labs with two gradient methods. Average root mean square errors (RMSE) between predicted and experimental retention times were 0.052 and 0.054 min for the two gradients tested, which were 9-fold more accurate than referring to a static retention time library. The library is freely available at https://bafinder.github.io/.

(Invited) Understanding Capacity Fade Behavior in Aqueous Organic Redox Flow Batteries Via Zero-Dimensional Models and High-Throughput Cell Cycling

Aqueous Organic Redox Flow Batteries (AORFBs) have emerged as promising and potentially disruptive technologies for the storage of electrical energy from intermittent renewable sources for use over long discharge durations when the sun isn’t shining and the wind isn’t blowing. AORFBs could become preferred over Li-ion batteries for grid-scale stationary storage due to their potentially low-cost active materials made of Earth-abundant elements, their inherent non-flammability, and the intrinsic decoupling of energy and power capacities in the flow battery design. Our group has demonstrated that calendar life, rather than cycle life, limits molecular lifetimes in AORFBs due to various molecular instabilities that lead to side reactions, thus inhibiting performance [1]. To accurately determine molecular fade rates, we utilize potentiostatic cycling to avoid artifacts caused by drifts in internal resistance and employ volumetrically unbalanced compositionally symmetric cell configurations to distinguish molecular fade from membrane crossover or the two sides drifting out of balance.We have developed a high-throughput setup for AORFBs, capable of cycling cells at elevated temperatures, providing a new dimension in the flow battery characterization space to explore multiple cell parameters simultaneously. The recent incorporation of the decay of active material into zero-dimensional cell-cycling models for AORFBs [2,3] allows for exploration of the causes of various trends seen in flow cell temporal capacity behavior. Complemented by zero-dimensional modelling, we explore temporal capacity evolution in symmetric cells driven by different capacity fade mechanisms such as active species degradation [4], self-discharge [5], and membrane crossover. Collectively, these results highlight the relevance of electrochemical techniques to understand molecular degradation in AORFBs and expedite the screening process of candidate molecules for long lifetime AORFBs, which may enable massive grid penetration of intermittent renewable energy.[1] M.-A. Goulet and M. J. Aziz, “Flow Battery Molecular Reactant Stability Determined by Symmetric Cell Cycling Methods,” Journal of The Electrochemical Society, 165, A1466 (2018).[2] S. Modak and D. G. Kwabi, “A Zero-Dimensional Model for Electrochemical Behavior and Capacity Retention in Organic Flow Cells,” Journal of the Electrochemical Society, 168, 080528 (2021).[3] B. J. Neyhouse, J. Lee, F. R. Brushett, “Connecting Material Properties and Redox Flow Cell Cycling Performance through Zero-Dimensional Models” Journal of The Electrochemical Society, 169, 090503 (2022).[4] D. G. Kwabi, Y. Ji, M. J. Aziz, “Electrolyte Lifetime in Aqueous Organic Redox Flow Batteries: A Critical Review,” Chemical Reviews, 120, 6467 (2020).[5] E. M. Fell, D. De Porcellinis, Y. Jing, V. Gutierrez-Venegas, R. G. Gordon, S. Granados-Focil, M. J. Aziz, “Long-term stability of ferri-/ferrocyanide as an electroactive component for redox flow battery applications: On the origin of apparent capacity fade,” ChemRxiv (2022). https://chemrxiv.org/engage/chemrxiv/article-details/62913087f89e5d4e6ee8828d

Transport of Oxygen-Doped Graphitic Carbon Nitride in Saturated Sand: Effects of Concentration, Grain Size, and Ionic Strength

In this study, the characteristics and transport of oxygen-doped graphitic carbon nitride (OgCN) were investigated in comparison with multi-walled carbon nanotube (MWCNT), and the transport of OgCN was evaluated under various conditions. OgCN was superior to MWCNT in transport within a quartz sand layer with less attachment and more detachment than MWCNT, which is attributable to more diverse and abundant functional groups, charges, defects, and amorphous graphitic structures. OgCN transport was well described by a one-dimensional advection–dispersion–retention model. The coefficients of retention (Smax), attachment (ka), and detachment (kd) calculated by the model were not always well-correlated with OgCN concentration and the grain size of the medium, suggesting that the OgCN transport was affected by various factors such as attachment, detachment, and pore size. However, it was clearly and significantly inhibited by ionic strength, via improved aggregation of OgCN. It is believed that the results of this study contribute to establish proper sub-surface injection strategies of carbonaceous materials for in situ chemical oxidation.

A generalized water retention model in a wide suction range considering the initial void ratio and its verification

A generalized water retention curve (WRC) model in a wide suction range considering the initial void ratio is presented in this paper. Both capillary and adsorbed water in soil pores are considered. Based on the experimental results that the adsorbed water content wa is not dependent on the initial void ratio, a new degree of saturation equation of adsorbed water is established. Meanwhile, a new degree of saturation equation of capillary water at various initial void ratios is proposed with a void ratio-related expression of the air entry value. Compared to Lu’s model, only one parameter b is introduced in the established model, which can be easily calibrated using WRCs under two initial void ratios. The measured WRC results of 5 soils are used to verify the proposed model in comparison with the other 3 widely used WRC models. The soil used in the model validation covers a wide range of soil types from sandy soil to clay soil, including clayey silty sand, sandy clay till, clayey silt, expansive soil and lateritic soil. The proposed model is well verified for its ability to describe soil water retention characteristics in a wide suction range at various initial void ratios.

A perspective on the use of deep deterministic policy gradient reinforcement learning for retention time modeling in reversed-phase liquid chromatography

Artificial intelligence and machine learning techniques are increasingly used for different tasks related to method development in liquid chromatography. In this study, the possibilities of a reinforcement learning algorithm, more specifically a deep deterministic policy gradient algorithm, are evaluated for the selection of scouting runs for retention time modeling. As a theoretical exercise, it is investigated whether such an algorithm can be trained to select scouting runs for any compound of interest allowing to retrieve its correct retention parameters for the three-parameter Neue-Kuss retention model. It is observed that three scouting runs are generally sufficient to retrieve the retention parameters with an accuracy (mean relative percentage error MRPE) of 1 % or less. When given the opportunity to select additional scouting runs, this does not lead to a significantly improved accuracy. It is also observed that the agent tends to give preference to isocratic scouting runs for retention time modeling, and is only motivated towards selecting gradient scouting runs when penalized (strongly) for large analysis/gradient times. This seems to reinforce the general power and usefulness of isocratic scouting runs for retention time modeling. Finally, the best results (lowest MRPE) are obtained when the agent manages to retrieve retention time data for % ACN at elution of the compound under consideration that spread the entire relevant range of ACN (5 % ACN to 95 % ACN) as well as possible, i.e., resulting in retention data at a low, intermediate and high % ACN. Based on the obtained results, we believe reinforcement learning holds great potential to automate and rationalize method development in liquid chromatography in the future.

Development of multiple heartcutting two-dimensional liquid chromatography with ion-pairing reversed-phase separations in both dimensions for analysis of impurities in therapeutic oligonucleotides

Oligonucleotides constitute an emerging and highly complex bioanalytical challenge and it is becoming increasingly clear that 1D methodologies are unable to fully resolve all possible impurities present in these samples. 2D-LC therefore constitutes a perfect solution wherein critical pairs can be sampled from a steep gradient 1D and separated in a shallower 2D gradient. Herein, we provide a facile 2D-LC method development approach to quickly generate high selectivity gradients utilizing ion pairing reverse phase (IPRP-IPRP). In particular we demonstrate how to iteratively generate a 12 % gradient from two training runs and then to utilize that data to predict retentions of analytes with a 2 % gradient with retention prediction errors as low as 3 and 11 %, respectively. This iterative method development workflow was applied to impurity profiling down to 1:1000 for the full-length product and phosphorothioate modified impurities. Additionally, we demonstrated the elucidation of critical pairs in complex crude pharmaceutical oligonucleotide samples by applying tailored high selectivity gradients in the second dimension. It was found that the iterative retention modeling approach allows fast and facile 2D-LC method development for complex oligonucleotide separations.

Exploring soil water retention hysteresis in the entire suction range and microstructure evolution of loess: The influence of sediment depths

Sediment depths can influence both soil structure and hydraulic processes, resulting in diverse soil-water retention properties. This study aimed to investigate the impact of sediment depths on soil-water retention hysteresis across the entire suction range, as well as the microstructure evolution of loess during the drying-wetting cycle. Laboratory tests were conducted to achieve this objective. The test results demonstrated that the water retention properties of the natural loess were significantly affected by sediment depths over the entire suction range. And the tested samples shrank considerably due to drying, while the swelling curves were almost linear induced by the wetting. Besides, the commonly used four water retention models were adopted to fit the test data, and Zhou's model showed the best-fitting performance. Furthermore, the local degree of hysteresis in the low suction range was generally larger than that in the high suction range for all samples, and the minimum local degree of hysteresis corresponded to the in-situ suction of tested samples. The average degree of hysteresis of JY-5 m, JY-15 m, and JY-30 m samples were 0.12, 0.14, and 0.13 respectively. Regarding microstructure change, the void ratios (which were smaller than the actual void ratios of soil samples) measured by the mercury intrusion porosimetry (MIP) tests became larger after undergoing the drying-wetting cycle, and most of the increased pores were primarily attributed to the formation of small mesopores in the vicinity of the main capillary pores. The results of this study contribute valuable insights into the dynamics of soil-water retention hysteresis and the associated microstructure evolution of loess.

Strategic social media marketing: An empirical analysis of sequential advertising

Social media platforms like Facebook and Twitter have emerged as effective channels for advertising that enable consumer targeting based on demographics, interests, and user behavior. Social media marketers have utilized information spillover within these platforms to reach a larger customer base. This information spillover also exists across groups of users within the platform and enhances returns from social media advertising. Thus, this information spillover can be utilized to strategically sequence targeted advertising to amplify the returns from social media ads. In this paper, we present a theoretical model for information retention and show that the sequential advertising strategy is effective in targeting groups of users on a social media platform. In addition, we provide empirical evidence through two series of randomized field experiments. From experiments for a health services organization, we find that sequential advertising campaigns provide 23% more clicks when compared to campaigns that target groups simultaneously, which translates to a saving of 18.7% in the advertising budget to achieve similar results as simultaneous advertising. Additionally, we found that sequential advertising campaigns targeting a smaller group first followed by a larger group provide 10.7% additional clicks when compared to targeting a larger group first followed by a smaller group. These results were consistent for consumer packaged goods that were advertised on Facebook and Twitter. These results provide implications for social media advertising research and practice.

Progress in and research direction of key technologies for normal-pressure shale gas exploration and development

Normal-pressure shale gas is an important object of shale gas reserves and production increase with broad resource prospects in China, but its large-scale benefit development is still confronted with technical bottlenecks. To promote the large-scale benefit development of normal-pressure shale gas, this paper systematically sorts out and summarizes the research achievements and technological progresses related to normal-pressure shale gas from the aspects of accumulation mechanism, enrichment theory, percolation mechanism, development technology, and low-cost engineering technology, and points out the difficulties and challenges to the benefit development of normal-pressure shale gas in the complex structure zones of southern China, by taking the shale gas in the Southeast Chongqing Area of the Sichuan Basin as the research object. In addition, the research direction of normal-pressure shale gas exploration and development is discussed in terms of sweet spot selection, development technology policy, low-cost drilling technology and high-efficiency fracturing technology. And the following research results are obtained. First, the accumulation mechanism of normal-pressure shale gas is clarified from the perspective of geological exploration theory; the hydrocarbon accumulation model of generation, expulsion, retention and accumulation is established; the enrichment theory of “three-factor controlling reservoir” is put forward; and the comprehensive sweetspot target evaluation system is formed. Second, as for development technology, the development technology policies of “multiple series of strata, variable well spacing, long horizontal section, small included angle, low elevation difference, strong stimulation and pressure difference controlling” are formulated. Third, as for drilling engineering, the optimal fast drilling and completion technology with “secondary structure + radical parameter + integrated guidance + unpressured leak-proof cementing” as the core is formed. Fourth, as for fracturing engineering, the low-cost and high-efficiency fracturing technology with “multi-cluster small-stage + limited-entry perforating + double temporary blocking + high-intensity sand injection + fully electric” as the core is formed. Fifth, normal-pressure shale gas is characterized by complex geological conditions, low pressure coefficient and gas content, poor resource endowment and so on, but its resource utilization still faces a series of challenges, such as uncertain productivity construction positions, low single-well productivity and ultimate recoverable reserve, high investment cost and poor economic benefit. In conclusion, the key research directions to realize the large-scale benefit development of low-grade normal-pressure shale gas are to deepen the research on the enrichment and high yield mechanism and sweet spot selection of normal-pressure shale gas, strengthen the research on the benefit development technology policy based on percolation mechanism and the key technologies for low-cost drilling, accelerate the research and development of the key technologies for low-cost and high-efficiency fracturing, and implement cost reduction and efficiency improvement continuously.

Continuum model for extraction and retention in porous media

Several natural and industrial processes involve the extraction or retention of a solute by a fluid invading a network of channels. Examples include aquifer contamination, chemical filtration, and coffee extraction. We propose a continuum equation to model these processes, parametrized by the Péclet number and the rate of mass transfer between the solid and the fluid. We study the time dependence of the extracted mass for different values of the parameter space. The continuum description is validated by combining extraction experiments with coffee and computational fluid dynamics. An analytical solution is derived for the limit of slow mass transfer, which is corroborated by numerical simulations.

Assessing Theories and Strategies Regarding Career Transition for Students with Visual Impairments

The purpose of this paper is to examine evidence-based theories and strategies that can aid in comprehending and fostering the career transitioning of students with visual impairments. Understanding the various career transitioning theories will enable career professionals and visually impaired students to achieve a successful career counselling encounter. The suggested theoretical models highlight the importance of psychological and social variables in predicting a successful transition and the attainment of good and meaningful jobs by visually impaired students. The theories discussed in this paper include Schlossberg's transition theory; Bridges’ transition framework; Psychological model for student retention; Psychology of working theory; Opportunity structure theory; Liquid modernity and life design; and Career construction theory. This article contributes to the literature on career counselling by arguing and elucidating the theoretical significance of these vocational counselling theories and strategies as they pertain to promoting career transition for visually impaired students. Theoretical knowledge could help to inform counselling methods and enable professionals, and various institutions to understand the contextual drivers of career transitioning, advocate for more inclusive workplaces, and explore solutions to reduce the number of unemployed visually impaired graduates. Career counsellors can adapt many techniques if they use an integrated theoretical approach to help visually impaired students transition from school to their potential employment. 
 
 

The Applicability of Chromatographic Retention Modeling on Chiral Stationary Phases in Reverse-Phase Mode: A Case Study for Ezetimibe and Its Impurities.

Mechanistic modeling is useful for predicting and modulating selectivity even in early chromatographic method development. This approach is also in accordance with current analytical quality using design principles and is highly welcomed by the authorities. The aim of this study was to investigate the separation behavior of two different types of chiral stationary phases (CSPs) for the separation of ezetimibe and its related substances using the mechanistic retention modeling approach offered by the Drylab software (version 4.5) package. Based on the obtained results, both CSPs presented with chemoselectivity towards the impurities of ezetimibe. The cyclodextrin-based CSP displayed a higher separation capacity and was able to separate seven related substances from the active pharmaceutical ingredient, while the cellulose-based column enabled the baseline resolution of six impurities from ezetimibe. Generally, the accuracy of predicted retention times was lower for the polysaccharide CSP, which could indicate the presence of additional secondary interactions between the analytes and the CSP. It was also demonstrated that the combination of mechanistic modeling and an experimental design approach can be applied to method development on CSPs in reverse-phase mode. The applicability of the methods was tested on spiked artificial placebo samples, while intraday and long-term (2 years) method repeatability was also challenged through comparing the obtained retention times and resolution values. The results indicated the excellent robustness of the selected setpoints. Overall, our findings indicate that the chiral columns could offer orthogonal selectivity to traditional reverse-phase columns for the separation of structurally similar compounds.

Abstract 17801: Age-Specific Normal Values for Myocardial Blood Flow on 82rb Positron Emission Tomography

Introduction: Positron emission tomography (PET) myocardial perfusion imaging (MPI) is utilized to evaluate ischemia along with myocardial blood flow (MBF). The ability to adequately augment blood flow, measured by myocardial blood flow reserve (MBFR), is a measure of overall health of the coronary circulation and associated with lower major adverse cardiovascular events (MACE) and all-cause mortality. The age-specific ranges of MBFR in patients without demonstrable coronary artery disease (CAD) has not been well established. Hypothesis/Aim: To determine the effect of age on MBF and MBFR in a cohort of patients without demonstrable CAD. Methods: Patients who underwent PET MPI studies from 2012-2022 on Siemens PET/CT cameras were included if Summed Stress Score=0, coronary calcium score=0, and left ventricular ejection fraction ≥50%. Those with prior history of MI or coronary intervention, heart/kidney/liver transplant, cirrhosis, or CKD stage IV+ were excluded. MBF was calculated using a net retention model (ImagenQ, Cardiovascular Imaging Technologies, Kansas City, MO) and multivariable linear regression models were developed to predict MBF. Results: Among 3,235 patients (age 59.5+/-12.6 years, 24.2% male) with median rest MBF 0.74 [0.61-0.92] and stress MBF 1.71 [1.41-2.10], MBFR was 2.28 [1.93-2.72]. With increasing age, rest MBF remained fairly stable while stress MBF and MBFR decreased, such that for every 10 years of age, stress MBF decreased by 0.07 [95% CI 0.05-0.08] mL/min/g and MBFR decreased by 0.12 [95% CI 0.11-0.14] after multivariable adjustment. Age-specific predicted MBFR values are documented in the Table. Conclusions: In patients without demonstrable CAD, the MBFR decreases with age. Abnormal MBFR values under 2.0 may be seen in a significant number of older patients.

370 Evaluation of Nutrient Digestibility By Calves Born from Early and Late Shedding Angus Dams

Abstract Researchers have investigated several factors that could alter fetal growth, including nutrient restriction (Valiente et al., 2021), hair shedding (Gray et al., 2011), and extreme hot and cold temperatures (Davidson et al., 2022). Hot temperatures and increased humidity percentages in the southeast United States caused researchers to investigate the hair coats of Angus cattle in the commercial production setting. An improvement in fiber digestibility and calf birth and weaning weights has been observed in Angus dams that shed 50% of the winter hair coat by May (Gray et al., 2011; Burnett et al., 2021). Our objective of this experiment was to investigate the nutrient digestibility of Angus calves born to cows that on average, shed early compared with calves from cows that shed later. Newly weaned, purebred Angus bull calves (early; n = 6, late; n = 6) were housed in metabolism crates for 10 d. Before the trial, calves had a 14-d adaption period to a 14% CP textured feed (CPC 14% Developer, CPC Commodities, Fountain Run, KY) and offered ad libitum Cynodon dactlyon hay and water. After 3 d crate acclimation period, urine, feces, orts, and hay samples were collected for 7 d. Concentrate was offered at 0.25% of average BW. Approximately 5% samples were taken of feces, and urine samples had 1 to 1.5% of 25% metaphosphoric acid added to prevent ammonia volatilization, and both collections were composited by animal. Orts were collected at 0600 h daily, dried, and composited by animal. Laboratory analysis included dry matter (DM), organic matter (OM), ash, neutral detergent fiber (NDF), acid detergent fiber (ADF), Kjeldahl N (CP), and fat. Data were analyzed using the GLM procedure of SAS 9.4 in a completely randomized design with calf as the experimental unit. Significant (P ≤ 0.05) means were separated using Fischer’s protected LSD. The model for intake included average daily DM and OM (kg) and adjusted by body weight (BW%). For digestibility analysis, the model included: DM, OM, ash, NDF, ADF, hemi-cellulose (HC), CP, and fat. The N retention model included: N retained (g/d), N retained/consumed (%), and N retained/DM intake (%). There were no differences between early or late calves for DM intake (5.502 ± 0.2774 kg/d; 2.251 ± 0.1247 %BW), or OM intake (5.199 ± 0.2591 kg/d; 2.128 ± 0.1166 %BW). There were no differences in digestibility for either group for DM, OM, Ash, NDF, ADF, HC, CP, or fat (Table 1.). There were also no differences in N retention in either group of calves (3.686 ± 2.0242 g/d; 4.366 ± 2.3964 %; 0.064 ± 0.0355 %). Further research is needed in this area to adequately understand factors influencing nutrient digestibility in calves born from early and late shedding dams.

Double porosity water retention model for bentonite-based clays with deformation considered

Double porosity water retention model for bentonite-based clays with deformation considered

Construction and validation of a predictive model for postoperative urinary retention after lumbar interbody fusion surgery

BackgroundPostoperative urine retention (POUR) after lumbar interbody fusion surgery may lead to recatheterization and prolonged hospitalization. In this study, a predictive model was constructed and validated. The objective was to provide a nomogram for estimating the risk of POUR and then reducing the incidence.MethodsA total of 423 cases of lumbar fusion surgery were included; 65 of these cases developed POUR, an incidence of 15.4%. The dataset is divided into a training set and a validation set according to time. 18 candidate variables were selected. The candidate variables were screened through LASSO regression. The stepwise regression and random forest analysis were then conducted to construct the predictive model and draw a nomogram. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and the calibration curve were used to evaluate the predictive effect of the model.ResultsThe best lambda value in LASSO was 0.025082; according to this, five significant variables were screened, including age, smoking history, surgical method, operative time, and visual analog scale (VAS) score of postoperative low back pain. A predictive model containing four variables was constructed by stepwise regression. The variables included age (β = 0.047, OR = 1.048), smoking history (β = 1.950, OR = 7.031), operative time (β = 0.022, OR = 1.022), and postoperative VAS score of low back pain (β = 2.554, OR = 12.858). A nomogram was drawn based on the results. The AUC of the ROC curve of the training set was 0.891, the validation set was 0.854 in the stepwise regression model. The calibration curves of the training set and validation set are in good agreement with the actual curves, showing that the stepwise regression model has good prediction ability. The AUC of the training set was 0.996, and that of the verification set was 0.856 in the random forest model.ConclusionThis study developed and internally validated a new nomogram and a random forest model for predicting the risk of POUR after lumbar interbody fusion surgery. Both of the nomogram and the random forest model have high accuracy in this study.

Nuclear Import and Export of YAP and TAZ.

Yes-associated Protein (YAP) and its paralog Transcriptional Coactivator with PDZ-binding Motif (TAZ) are major regulators of gene transcription/expression, primarily controlled by the Hippo pathway and the cytoskeleton. Integrating an array of chemical and mechanical signals, they impact growth, differentiation, and regeneration. Accordingly, they also play key roles in tumorigenesis and metastasis formation. Their activity is primarily regulated by their localization, that is, Hippo pathway- and/or cytoskeleton-controlled cytosolic or nuclear sequestration. While many details of such prevailing retention models have been elucidated, much less is known about their actual nuclear traffic: import and export. Although their size is not far from the cutoff for passive diffusion through the nuclear pore complex (NPC), and they do not contain any classic nuclear localization (NLS) or nuclear export signal (NES), evidence has been accumulating that their shuttling involves mediated and thus regulatable/targetable processes. The aim of this review is to summarize emerging information/concepts about their nucleocytoplasmic shuttling, encompassing the relevant structural requirements (NLS, NES), nuclear transport receptors (NTRs, karyophererins), and NPC components, along with the potential transport mechanisms and their regulation. While dissecting retention vs. transport is often challenging, the emerging picture suggests that YAP/TAZ shuttles across the NPC via multiple, non-exclusive, mediated mechanisms, constituting a novel and intriguing facet of YAP/TAZ biology.

Employee Retention in the Tourism Industry of China Amid Post Pandemic Times

Purpose: This research investigates employee retention in China's tourism industry, specifically within hotels. It explores the relationships between rewards, job satisfaction, employee engagement, and employee retention. Methodology: Cross-sectional and questionnaires were distributed online in convenient ways to collect data and enable the respondent to provide their feedback anytime and from anywhere. It was a non-probability sampling where questionnaires were distributed to respondents in the tourism industry. A set of hypotheses arising from a theoretical model of employee retention was tested using SPSS. Results and Conclusion: Empirical results revealed that all the variables significantly influenced employee retention. The research provides a clinical study on the relationship between employee retention with rewards, job satisfaction and employee engagement in the tourism industry of China, where the findings will benefit the industry and academic field as an additional review or reference for future research. Implications of research: The study benefits both the tourism industry and academia. Employers can gain a better understanding of areas for improvement in their organizations to enhance performance and meet employee needs. Human resource managers can identify factors that foster employee retention in the tourism sector. Additionally, the study provides insights into workplace culture, policies, and processes. Originality/Value: This study contributes to the literature by focusing on employee retention in China's tourism industry, shedding light on the critical factors of rewards, job satisfaction, and employee engagement. It serves as a valuable resource for industry practitioners and future researchers seeking to improve employee retention strategies in this sector.

Double-Cross-Linked Hydrogel with Long-Lasting Underwater Adhesion: Enhancement of Maxillofacial In Situ and Onlay Bone Retention.

Bone retention is a usual clinical problem existing in a lot of maxillofacial surgeries involving bone reconstruction and bone transplantation, which puts forward the requirements for bone adhesives that are stable, durable, biosafe, and biodegradable in wet environment. To relieve the suffering of patients during maxillofacial surgery with one-step operation and satisfying repair, herein, we developed a double-cross-linked A-O hydrogel named by its two components: [(3-Aminopropyl) methacrylamide]-co-{[Tris(hydroxymethyl) methyl] acrylamide} and oxidated methylcellulose. With excellent bone adhesion ability, it can maintain long-lasting stable underwater bone adhesion for over 14 days, holding a maximum adhesion strength of 2.32 MPa. Schiff-base reaction and high-density hydrogen bonds endow the hydrogel with strong cohesion and adhesion performance as well as maneuverable properties such as easy formation and injectability. A-O hydrogel not only presents rarely reported long-lasting underwater adhesion of hard tissue but also owns inherent biocompatibility and biodegradation properties with a porous structure that facilitates the survival of bone graft. Compared to the commercial cyanoacrylate adhesive (3 M Vetbond Tissue Adhesive), the A-O hydrogel is confirmed to be safer, more stable, and more effective in calvarial in situ bone retention model and onlay bone retention model of rat, providing a practical solution for the everyday scenario of clinical bone retention.