Potential Model Research Articles

Establishment and characterization of turtle liver organoids provides a potential model to decode their unique adaptations

Painted turtles are remarkable for their freeze tolerance and supercooling ability along with their associated resilience to hypoxia/anoxia and oxidative stress, rendering them an ideal biomedical model for hypoxia-induced injuries (including strokes), tissue cooling during surgeries, and organ cryopreservation. Yet, such research is hindered by their seasonal reproduction and slow maturation. Here we developed and characterized adult stem cell-derived turtle liver organoids (3D self-assembled in vitro structures) from painted, snapping, and spiny softshell turtles spanning ~175My of evolution, with a subset cryopreserved. This development is, to the best of our knowledge, a first for this vertebrate Order, and complements the only other non-avian reptile organoids from snake venom glands. Preliminary characterization, including morphological, transcriptomic, and proteomic analyses, revealed organoids enriched in cholangiocytes. Deriving organoids from distant turtles and life stages demonstrates that our techniques are broadly applicable to chelonians, permitting the development of functional genomic tools currently lacking in herpetological research. Such platform could potentially support studies including genome-to-phenome mapping, gene function, genome architecture, and adaptive responses to climate change, with implications for ecological, evolutionary, and biomedical research.

Numerical Simulation of Seakeeping Performance of a Barge Using Computational Fluid Dynamics (CFD)-Modified Potential (CMP) Model

This paper explains the evaluation process of seakeeping performance for small vessels using a CFD-modified potential (CMP) model, a hybrid simulation model that modifies the damping ratio with computational fluid dynamics (CFD) after analyzing ship motion based on the linear potential theory. From the result of the motion analysis using the CMP model, the seakeeping performance of a small vessel (a barge here) was evaluated on the basis of the single significant amplitude (SSA) under the sea states 2~4. The results of the motion RAOs and seakeeping performance evaluation were verified through comparison with the results obtained by performing model tests and potential flow programs only. In all sea states, the relative errors (compared to the experiment) of roll motion using the CMP model were relatively small compared to the results using the potential flow program and tended to decrease more as the sea state increased. On the other hand, the results of pitch motion using the CMP model were underestimated in all sea states compared to the experiment. However, it is seen that they are relatively closer to the experiment compared to the results using a potential flow program only.

Risk-Quantification Method for Car-Following Behavior Considering Driving-Style Propensity

To systematically study the influence of a propensity for a particular driving style on car-following risk, a safety potential field risk-quantification method that considers driving style is proposed. First, we classify driving behaviors and construct a field-based safety potential car-following model via analogy with intermolecular interactions; second, we establish a risk-quantification model by considering driving style, risk exposure, and risk severity and classify the consequent risk into four levels, high risk, medium risk, low risk, and safe, using the fuzzy C-means algorithm. Finally, we predict the car-following risk using the LightGBM algorithm in real time. The experimental results show that the LightGBM algorithm can recognize up to 86% of medium–high risk levels compared to the Decision Tree and Random Forest Algorithms. It can achieve effective prediction of car-following risk, which provides sufficient warning information to drivers and helps improve the overall safety of vehicle operation.

Classical-trajectory model for ionizing proton-ammonia molecule collisions: the role of multiple ionization

We use an independent electron model with semi-classical approximation to electron dynamics to investigate differential cross sections for electron emission in fast collisions of protons with ammonia molecules. An effective potential model for the electronic orbitals is introduced, and utilized in the context of the classical-trajectory Monte Carlo (CTMC) approach for single-electron dynamics. Cross sections differential in electron emission angle and energy are compared with experimental data. Compared to previous scattering-theory based quantum-mechanical results the time-dependent semi-classical CTMC approach provides results of similar quality for intermediate and high ionized electron energies. We find some discrepancies in the total cross sections for q-fold ionization between the present model and independent-atom-model calculations. The double ionization cross sections are considerably larger than recent experimental data which are derived from coincidence counting of charged fragments. The calculated triple ionization cross sections exceed the experimental coincidence data for q = 3 by several orders of magnitude at intermediate energies.

Size and shapes effect on structural and phonon density of state in Ir nanoparticle and mechanical properties of Ir metal

Density Functional Theory (DFT) calculations were performed to assess the mechanical properties of an Ir metal nanocluster. The properties under investigation encompassed the bulk modulus, Poisson ratio, elastic shear modulus, and binding energy. The stability of the nanocluster was explored across various shapes, including icosahedron, octahedron, and truncated octahedron, with consideration given to different cluster sizes. The DFT results unveiled a general mechanism for amorphization in the Ir nanocluster of size 55, involving rosette-like structural transformations at the fivefold vertex. Additionally, Phonon Density of States (PDOS) was computed for the core, surface, and total atoms of Ir nanoclusters with sizes 38, 55, and 75, as well as for the Ir bulk structure. These calculations were carried out using both Quantum Sutton-Chen potential (QSC) and Gupta potential models through molecular dynamics (MD) methods. The analysis of the phonon density of states revealed that the contributions of two main peaks in low and high frequencies were associated with the surface and core atoms, respectively. Furthermore, the extension of the phonon density of states was performed for larger-sized Ir nanoclusters. Significantly, the QSC potential was utilized to investigate the adsorption of main peaks and their trends for the phonon density of states in the Ir bulk structure. The results obtained from this method were found to be in agreement with experimental data derived from cold neutron and multidetector time-of-flight spectrometer phonon measurements.

Surface modification of transition metals (TM: Mn, Fe, Co) decorated Pt-doped carbon quantum dots (Pt@CQDs) nanostructure as nonenzymatic sensors for nitrotyrosine (a biomarker for Alzheimer): Perspective from density functional theory

To develop a method for the detection of nitrotyrosine (NTS), transition metals: cobalt (Co), Iron (Fe), and Manganese (Mn) decorated Platinum-doped carbon quantum dot (Pt@CQDs) nanomaterial surfaces were computationally investigated. This study employed density functional theory (DFT) at the d3bj-B3LYP/def2SVP level of theory to gain in-depth knowledge of the adsorption, selectivity, reactivity, and trapping efficacy of nitrotyrosine (NTS) as a biomarker for Alzheimer disease. Results of the adsorption energy of the systems increased as −46.661 kcal/mol, −45.308 kcal/mol, −666.673 kcal/mol, and −12.507 kcal/mol which correspond to NTS_Co_Pt@CQDs, NTS_Fe_Pt@CQDs, NTS_Mn_Pt@CQDs, and NTS_Pt@CQDs. NTS_Mn_Pt@QDs system demonstrated the chemisorption as it has the highest adsorption energy. HOMO-LUMO analysis shows that cobalt decorated surface had the least energy gap of 1.586 eV while interaction with nitrotyrosine a decrease in the energy gap was observed particularly NTS_Pt@CQDs and NTS_Fe_Pt@CQDs exhibiting values of 1.850 eV and 1.665 eV respectively, whereas, Co_Pt@CQDs and Mn_Pt@CQDs systems showed drastic increase in the energy gap to 2.404 eV and 2.719 eV. This collective finding of this study is significant enough to present these systems as potential models for the detection and trapping of nitrotyrosine biomarkers for the diagnosis of Alzheimer's disease.

K2CO3-Modified Smectites as Basic Catalysts for Glycerol Transcarbonation to Glycerol Carbonate.

A novel and cost-effective heterogeneous catalyst for glycerol carbonate production through transesterification was developed by impregnating smectite clay with K2CO3. Comprehensive structural and chemical analyses, including X-ray diffraction Analysis (XRD), Scanning Electron Microscopy (SEM)-Electron Dispersion Spectroscopy (EDS), Fourier Transform Infrared Spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) surface area analysis measurements, were employed to characterize the catalysts. Among the various catalysts prepared, the one impregnated with 40 wt% K2CO3 on smectite and calcined at 550 °C exhibited the highest catalytic activity, primarily due to its superior basicity. To enhance the efficiency of the transesterification process, several reaction parameters were optimized, including the molar ratio between propylene carbonate and glycerol reactor loading of the catalyst and reaction temperature. The highest glycerol carbonate conversion rate, approximately 77.13% ± 1.2%, was achieved using the best catalyst under the following optimal conditions: 2 wt% reactor loading, 110 °C reaction temperature, 2:1 propylene carbonate to glycerol molar ratio, and 6h reaction duration. Furthermore, both the raw clay and the best calcined K2CO3-impregnated catalysts demonstrated remarkable stability, maintaining their high activity for up to four consecutive reaction cycles. Finally, a kinetic analysis was performed using kinetic data from several runs employing raw clay and the most active K2CO3-modified clay at different temperatures, observing that a simple reversible second-order potential kinetic model of the quasi-homogeneous type fits perfectly to such data in diverse temperature ranges.

The Special Activity of Stone–Wales Defect Graphene for the Oxygen Reduction Reaction: A Comparison Study between the Charge-Neutral Model and the Constant Potential Model Calculated by Density Functional Theory

The Special Activity of Stone–Wales Defect Graphene for the Oxygen Reduction Reaction: A Comparison Study between the Charge-Neutral Model and the Constant Potential Model Calculated by Density Functional Theory

Transcriptomic and proteomic insights into the immune response of the intestine to Aeromonas veronii infection in koi carp (Cyprinus carpio var. koi)

Intestinal mucosal immunity serves as one of the primary barriers against pathogens. The immune mechanism involved in fish intestinal defense against bacterial infection still needs further investigation. To delve into the intestinal immune mechanisms of koi carp (Cyprinus carpio var. koi) against Aeromonas veronii infection, RNA-seq and isobaric tags for relative and absolute quantitation (iTRAQ)-coupled LC-MS/MS were employed. After A. veronii infection, 7224 differently expressed genes (DEGs) and 1482 differently expressed proteins (DEPs) were detected in the intestines of koi carp. Further, the integrated analysis of transcriptomic and proteomic data revealed that 471 DEGs were matched with the corresponding DEPs (named associated DEPs/DEGs). Among the 34 immune-related associated DEPs/DEGs, 21 were in the consistent expression tendency, whereas 13 were in the opposite tendency. Moreover, the immune-related associated DEPs/DEGs exhibiting consistent expression trends were predominantly enriched in nine pathways, with five of them being linked to innate immunity: ferroptosis, phagosome, complement and coagulation cascades, MAPK signaling pathway, and NLR signaling pathway. The expression patterns of tested genes detected using quantitative real-time PCR assay were consistent with the findings from RNA-Seq and iTRAQ. A potential offense and defense model between A. veronii and koi carp was established based on insights into the immune-related pathways, DEGs, and DEPs. Overall, our comprehensive transcriptome and proteome analysis allow us to better understand the intestinal mucosal immunity of teleost and the pathogenic mechanism of A. veronii.

Integration of Land Use Potential in Energy System Optimization Models at Regional Scale: The Pantelleria Island Case Study

In the context of the energy transition, the integration of land use considerations into energy planning can provide significant improvements. In energy system optimization models (ESOMs), land use aspects can be integrated at the cost of a finer spatial resolution and a more detailed characterization of land, tailored to regional constraints and specificities. Additionally, an assessment of trade-offs with alternative land uses is necessary. Nevertheless, they are commonly neglected. This study addresses the challenge of incorporating land use aspects into ESOMs, with a focus on the unique context of Pantelleria Island. It aims to bridge the gap in methodologies for renewable energy potential assessment and model integration, considering the critical role of land pricing and availability. It combines geospatial data aggregation with model adaptation to include detailed land use aspects. The findings highlight the substantial impact of land costs on renewable energy planning, with land pricing significantly altering model outcomes. This research offers key insights for sustainable energy planning and underscores the importance of considering land use in energy transition strategies.

Development of a non-programmable sperm cryopreservation technique in dwarf surfclams Mulinia lateralis–a potential model species for bivalve research

Sperm cryopreservation technique has been published in many farmed bivalve species. One of the key factors preventing its application in aquaculture and/or cryobanking is the knowledge gap on the performance of resultant progeny at late developmental stages and subsequent generations. An effective strategy to overcome these challenges is to use a model species with a short generation interval, such as the dwarf surfclam Mulinia lateralis (three months). This study evaluated the parameters key to the development of a non-programmable sperm cryopreservation technique in this species, with a D-stage larval rate similar to control being achieved when the sperm were cryopreserved under the conditions (cryoprotectant agent: 8% dimethyl sulfoxide; equilibration period: 10 min; rack height: 4 cm; thawing temperature: 60°C and sperm to egg ratio: 1100:1) optimized. This technique is the most common method applied in bivalve and the results from this study were all within the ranges published for other bivalve species, indicating this species would be an ideal bivalve model species for addressing cryopreservation evaluation issues that need a long extended time to collect data and/or challenging field experiments.

A Systematic study on the alpha decay of superheavy nuclei using empirical diffuseness parameter in the coulomb and proximity potential model

Recent studies of Dehghani et al [Mod. Phys. Lett. A 33 14 1850080 (2018)] and Abdul-latif et al [Phys. Rev. C 100, 024601 (2019)] revealed the importance of the diffuseness parameter in the calculation of alpha decay half-lives from superheavy elements using proximity potentials. In the present paper, predictions of the empirical formula for the diffuseness parameter proposed by Abdul-latif et al is analyzed in view of the diffuseness parameter calculated by Dehghani et al using WKB method and considering deformed Woods–Saxon nuclear potential, deformed Coulomb potential, and centrifugal potential; and related theoretical aspects. From the conclusions, we propose three new empirical formulae for the diffuseness parameter. Using the diffuseness parameter calculated from the proposed empirical formula in the Coulomb and Proximity Potential Model (CPPM), the alpha decay half-life of 68 superheavy nuclei is calculated and compared with the experimental values. The inclusion of the diffuseness parameter in proximity potential improved the predictive power of the CPPM considerably.

Cuproptosis-related genes are involved in immunodeficiency following ischemic stroke.

Accumulating studies have shown that copper has a detrimental effect in cells, and the cuproptosis-related gene signatures have been constructed as clinical tools to predict prognosis in tumors. However, the heterogeneity of cuproptosis has not been fully investigated in ischemic stroke.Methods: Here, we combined the bulk RNA-seq and single cell-RNA-seq data for stroke to investigate the role of cuproptosis in stroke. We identified the cuproptosis-related differentially expressed genes (CuDEGs) in ischemic stroke. Then, we tried to find the hub genes with the machine learning method and WGCNA. We highlighted four genes identified by these methods and proposed a potential diagnostic model in ischemic stroke. Our findings revealed cuproptosis-related hub genes, which could provide useful biomarkers in ischemic stroke.

Past, present and future in the geographical distribution of Mexican Tepezmaite cycads: Genus Ceratozamia.

Ceratozamia morettii, C. brevifrons, and C. tenuis are cycads considered endangered in montane forests in the center of Veracruz state. However, the amount of theoretical and empirical information available on the historical distribution of these species and how they could be affected in the future by the effects of climate change still needs to be increased. Our objective was to generate information on the spatial distribution of the species since the last glacial maximum, present, and future. To map the spatial distribution of species, we created a potential distribution model for each species. The spatial data used for the models included 19 bioclimatic data variables in the present, at the last glacial maximum using two models (CCSM4 and MIROC), and in the future (2080) using two models of the RCP 8.5 scenario of climate change (HadGEM2-CC and MIROC5). We found that each species occupies a unique ecoregion and climatic niche. Ceratozamia morettii and C. tenuis have a similar pattern with an expansion of their distribution area since the last glacial maximum with a larger distribution area in the present and a projected reduction in their distribution under future climatic conditions. For C. brevifrons, we also showed an increase in their distributional area since the last glacial maximum. We also showed that this expansion will continue under future climatic conditions when the species reaches its maximum distributional area. Projections about the future of these endemic cycad species show changes in their habitat, highlighting that temperate zone species (C. morettii and C. tenuis) will face imminent extinction if no effort is made to protect them. On the other hand, the tropical climate species (C. brevifrons) will be favored.

Assessing Carbon Emission Reduction Potential: A Case Study of Low Carbon Demand Response Technology in Fangshan District, Beijing

Responding to the low-carbon demands of power users helps the power industry unlock carbon emission reduction potential, transmit carbon reduction responsibilities, and hold significant importance for energy conservation and carbon reduction. Currently, there is relatively limited empirical research on carbon emission demand responses in different industries. Therefore, this article, based on dynamic carbon accounting technology and combined with power planning and operation simulation data in Fangshan District, proposes a low-carbon demand response mechanism guided by user-side carbon reduction, using dynamic carbon emission factors as guiding signals. Furthermore, an assessment model for the carbon reduction potential of a low-carbon demand response technology is constructed. Finally, empirical research is conducted on the estimated carbon emission reduction of 108 enterprises in 6 different industries in Fangshan District based on the assessment model. The results indicate that carrying out low-carbon demand response can reduce enterprise carbon emissions, and changes in enterprise capacity and industry affiliation will have a significant impact on the carbon reduction effect. This study introduces a novel approach to the low-carbon development of the power system load side, offering a fresh perspective on the empirical analysis of low-carbon development for typical receiving-end power grids.

Bonding to Psychedelics: Synthesis of Molecularly Imprinted Polymers Targeting 4-Bromo-2,5-dimethoxyphenethylamine (2C-B)

The increasing interest in utilizing psychedelics for therapeutic purposes demands the development of tools capable of efficiently monitoring and accurately identifying these substances, thereby supporting medical interventions. 4-Bromo-2,5-dimethoxyphenethylamine (2C-B) has gained significant popularity as one of the most widely used psychedelic compounds in non-medical settings. In this study, we aimed to create a material with selective recognition of 2C-B by synthesizing a series of molecularly imprinted polymers (MIP) using 2C-B as the template and varying ratios of methacrylic acid (MAA) as the functional monomer (1:2, 1:3, and 1:4). Both thermal and microwave-assisted polymerization processes were employed. The molar ratio between the template molecule (2C-B) and functional monomer (MAA) was 1:4, utilizing a microwave-assisted polymerization process. Isotherm studies revealed a Langmuir’s maximum absorption capacity (Bmax) value of 115.6 μmol·mg−1 and Kd values of 26.7 μM for this material. An imprint factor of 4.2 was determined for this material, against the corresponding non-imprinted polymer. The good selectivity against 14 other new psychoactive substances highlighted the material’s potential for applications requiring selective recognition. These findings can contribute to the development of tailored materials for the detection and analysis of 2C-B, supporting advancements in non-medical use monitoring and potential therapeutic models involving psychedelics.

Construction and evaluation of immune-related diagnostic model in patients with heart failure caused by idiopathic dilated cardiomyopathy

ObjectiveThe purpose of the study was to construct the potential diagnostic model of immune-related genes during the development of heart failure caused by idiopathic dilated cardiomyopathy.MethodGSE5406 and GSE57338 were downloaded from the GEO website (https://www.ncbi.nlm.nih.gov/geo/). CIBERSORT was used for the evaluation of immune infiltration in idiopathic dilated cardiomyopathy (DCM) of GSE5406. Differently expressed genes were calculated by the limma R package and visualized by the volcano plot. The immune-related genes were downloaded from Immport, TISIDB, and InnateDB. Then the immune-related differential genes (IRDGs) were acquired from the intersection. Protein–protein interaction network (PPI) and Cytoscape were used to visualize the hub genes. Three machine learning methods such as random forest, logical regression, and elastic network regression model were adopted to construct the prediction model. The diagnostic value was also validated in GSE57338.ResultsOur study demonstrated the obvious different ratio of T cell CD4 memory activated, T cell regulatory Tregs, and neutrophils between DCM and control donors. As many as 2139 differential genes and 274 immune-related different genes were identified. These genes were mainly enriched in lipid and atherosclerosis, human cytomegalovirus infection, and cytokine-cytokine receptor interaction. At the same time, as many as fifteen hub genes were identified as the IRDGs (IFITM3, IFITM2, IFITM1, IFIT3, IFIT1, HLA-A, HLA-B, HLA-C, ADAR, STAT1, SAMHD1, RSAD2, MX1, ISG20, IRF2). Moreover, we also discovered that the elastic network and logistic regression models had a higher diagnostic value than that of random forest models based on these hub genes.ConclusionOur study demonstrated the pivotal role of immune function during the development of heart failure caused by DCM. This study may offer new opportunities for the detection and intervention of immune-related DCM.

Factors predicting the visual outcome of intracorneal ring segment for keratoconus.

To identify predictive factors and to construct predictive models using epidemiological and clinical preoperative factors for the visual acuity change after intracorneal ring segment (ICRS) implantation in patients with keratoconus. The medical records of 287 keratoconic eyes of 230 patients implanted with ICRS at Chula Refractive Surgery Center of a tertiary university hospital (Bangkok, Thailand) between January 2012 and March 2022 were retrospectively reviewed for epidemiological and clinical preoperative variables, including those derived from Scheimpflug tomography. After randomly excluding one eye for each bilateral case, the remaining 230 eyes were randomized into two groups: a training group (184 eyes) and a validation group (46 eyes). In the training group, the correlation between the interesting variables and postoperative uncorrected and corrected distance visual acuity change (ΔUDVA and ΔCDVA; logMAR scale) at 6 months was explored, and then the multiple linear regression analysis was used to develop the predictive models. The obtained models were tested using the validation group. There were 5 and 14 preoperative variables that statistically correlated with ΔUDVA and ΔCDVA respectively. Only the preoperative corrected distance visual acuity (CDVAp) strongly correlated with ΔCDVA (Beta = -0.746). Using multiple regression, the preoperative uncorrected distance visual acuity (UDVAp) and front mean keratometry were selected in the proposed model for ΔUDVA (adjusted R2 = 38.8%), while the CDVAp and index of surface variance (ISV) were selected in the model [Formula: see text] (adjusted R2 = 48.9%). The ΔUDVA and ΔCDVA models were correct in 47.83% and 63.4% of the validation group within 0.20 logMAR, respectively. Potential predictive factors and models for ICRS-induced changes in visual acuity are proposed as adjunctive tools for clinicians. Such tools could be used for case selection and during counselling before ICRS implantation to maximize surgical outcomes.

Single-cell transcriptome landscape of zebrafish liver reveals hepatocytes and immune cell interactions in understanding nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is becoming the most common chronic liver disease in the world. Immunity is the major contributing factor in NAFLD; however, the interaction of immune cells and hepatocytes in disease progression has not been fully elucidated. As a popular species for studying NAFLD, zebrafish, whose liver is a complex immune system mediated by immune cells and non-immune cells in maintaining immune tolerance and homeostasis. Understanding the cellular composition and immune environment of zebrafish liver is of great significance for its application in NAFLD. Here, we established a liver atlas that consists of 10 cell types using single-cell RNA sequencing (scRNA-seq). By examining the heterogeneity of hepatocytes and analyzing the expression of NAFLD-associated genes in the specific cluster, we provide a potential target cell model to study NAFLD. Additionally, our analysis identified two subtypes of distinct resident macrophages with inflammatory and non-inflammatory functions and characterized the successive stepwise development of T cell subclusters in the liver. Importantly, we uncovered the possible regulation of macrophages and T cells on target cells of fatty liver by analyzing the cellular interaction between hepatocytes and immune cells. Our data provide valuable information for an in-depth study of immune cells targeting hepatocytes to regulate the immune balance in NAFLD.

Insight into the nucleation behavior of tiamulin hydrogen fumarate methanol solvate in methanol-ethyl acetate binary mixtures

To investigate the nucleation behavior of tiamulin hydrogen fumarate methanol solvate (THFMS), the solubility, induction time, and metastable zone width (MSZW) of THFMS in methanol-ethyl acetate binary mixtures were measured. The nucleation potential model, which is based on the classical nucleation theory and correlates the induction time and MSZW, has been employed to deal with the experimental data and estimate the interfacial energy and the critical nucleation potential. The estimated values determined from the nucleation potential model are in accordance with the experimental values. The interfacial energy and the critical nucleation potential of THFMS steadily decrease with the increasing saturation temperature, whereas those of THFMS initially decrease and subsequently increase as the ethyl acetate content increases. The results demonstrate that an increase in saturation temperature leads to enhanced nucleation favorability, while the difficulty of nucleation initially decreases and then increases with increasing ethyl acetate content. Furthermore, the critical nucleation parameters, including the critical Gibbs free energy, the critical nucleus size, and the critical number of molecules in a nucleus, exhibit the same trend in alterations regarding both saturation temperature and ethyl acetate content.