Pair Model Research Articles

Pre-diagnosis blood DNA methylation profiling of twin pairs discordant for breast cancer points to the importance of environmental risk factors

BackgroundAssessment of breast cancer (BC) risk generally relies on mammography, family history, reproductive history, and genotyping of major mutations. However, assessing the impact of environmental factors, such as lifestyle, health-related behavior, or external exposures, is still challenging. DNA methylation (DNAm), capturing both genetic and environmental effects, presents a promising opportunity. Previous studies have identified associations and predicted the risk of BC using DNAm in blood; however, these studies did not distinguish between genetic and environmental contributions to these DNAm sites. In this study, associations between DNAm and BC are assessed using paired twin models, which control for shared genetic and environmental effects, allowing testing for associations between DNAm and non-shared environmental exposures and behavior.ResultsPre-diagnosis blood samples of 32 monozygotic (MZ) and 76 dizygotic (DZ) female twin pairs discordant for BC were collected at the mean age of 56.0 years, with the mean age at diagnosis 66.8 years and censoring 75.2 years. We identified 212 CpGs (p < 6.4*10–8) and 15 DMRs associated with BC risk across all pairs using paired Cox proportional hazard models. All but one of the BC risks associated with CpGs were hypomethylated, and 198/212 CpGs had their DNAm associated with BC risk independent of genetic effects. According to previous literature, at least five of the top CpGs were related to estrogen signaling. Following a comprehensive two-sample Mendelian randomization analysis, we found evidence supporting a dual causal impact of DNAm at cg20145695 (gene body of NXN, rs480351) with increased risk for estrogen receptor positive BC and decreased risk for estrogen receptor negative BC.ConclusionWhile causal effects of DNAm on BC risk are rare, most of the identified CpGs associated with the risk of BC appear to be independent of genetic effects. This suggests that DNAm could serve as a valuable biomarker for environmental risk factors for BC, and may offer potential benefits as a complementary tool to current risk assessment procedures.

Probing p-wave superconductivity in UTe2 via point-contact junctions

Uranium ditelluride (UTe2) is the strongest contender to date for a p-wave superconductor in bulk form. Here we perform a spectroscopic study of the ambient pressure superconducting phase of UTe2, measuring conductance through point-contact junctions formed by metallic contacts on different crystalline facets down to 250 mK and up to 18 T. Fitting a range of qualitatively varying spectra with a Blonder-Tinkham-Klapwijk (BTK) model for p-wave pairing, we can extract gap amplitude and interface barrier strength for each junction. We find good agreement with the data for a dominant py-wave gap function with amplitude 0.26 ± 0.06 meV. Our work provides spectroscopic evidence for a gap structure consistent with the proposed spin-triplet pairing in the superconducting state of UTe2.

Paired piecewise linear regression model with fixed nodes

In this paper we develop a method for constructing a paired regression model in the class of piecewise linear continuous functions with fixed nodes. The concept of linear division of the correlation field, its partial sections and its nodes is introduced into consideration. Using the linear division of the correlation field, a class of piecewise linear functions with fixed nodes is determined. The linear division is revealed during the visual analysis of the correlation field. Using the least squares method, a system of linear equations is compiled to find point estimates of the parameters of the approximating function. With the exception of two unknown angular coefficients (unknown) this system is reduced to a tridiagonal system of equations, the unknowns of which are the nodal values of the approximating function. The tridiagonal system is solved by the run-through method. An algorithm was constructed to demonstrate the operation of the developed method. Its initial data is arrays of the corresponding values of the explanatory and dependent variables, as well as an array of numbers of the right ends of the intervals defining the nodes. An array of fixed nodes is constructed from an array of values of the explanatory variable and an array of numbers of the right ends of the intervals. Next, an array of point estimates of the parameters of the approximating function is constructed. This algorithm is implemented in Python in the form of user-defined functions.

Flow Characteristics of Asymmetric Plunger Pairs in High-Pressure Plunger Pumps

Abstract The deep-sea submersible is an essential piece of equipment for deep-sea development, serving as a crucial tool for conducting exploration and operations in the deep ocean. As the core component of the hydraulic system, the plunger pump is vital for ensuring the smooth lifting and lowering of the submersible. The plunger pair, which constitutes the most significant friction pair in plunger pumps, plays a pivotal role in determining both the service life and volumetric efficiency of the pump through its friction, lubrication, and sealing performance. This article proposes a flow model for the plunger pair in eccentric and inclined positions, considering its various orientations and placements. It elucidates the deformation and leakage characteristics of the plunger pair under different configurations, including various postures, material properties, and design parameters. The findings not only provide a theoretical foundation for the design of reciprocating seals and the evaluation of sealing performance but also contribute to the broader field of parameter design and performance assessment for other types of gap seals.

Tuning Electron-Transfer Driving Force in Photosynthetic Special Pair Models.

Visible-light excitation of a family of bimetallic ruthenium polypyridines with the formula [RuII(tpy)(bpy)(𝜇-CN)RuII(py)4L]n+ (RuRuLn+), where L = Cl-, NCS-, DMAP and ACN, was used to prepare photoinduced mixed-valence (PI-MV) MLCT states as models of the photosynthetic reaction center. Ultrafast transient absorption spectroscopy allowed to monitor photoinduced IVCT bands between 6000 and 11000 cm-1. Mulliken spin densities resulting from DFT and (TD)DFT computations revealed the modulation of the charge density distribution depending on the ligand substitution pattern. Results are consistent with PI-MV systems ranging from non-degenerate Class II to degenerate Class III, with electronic couplings between 1000 and 3500 cm-1.These findings guide the control electron localization-delocalization in charge-transfer/charge-separated excited states, like those involved in the photosynthetic reaction center.

Foundational Aspects for Incorporating Dependencies in Copula-Based Bayesian Networks Using Structured Expert Judgments, Exemplified by the Ice Sheet-Sea Level Rise Elicitation.

The work presented here marks a further advance in expert uncertainty quantification. In a recent probabilistic evaluation of ice sheet process contributions to sea level rise, tail dependence was elicited and propagated through an uncertainty analysis for the first time. The elicited correlations and tail dependencies concerned pairings of three processes: Accumulation, Discharge and Run-off, which operate on major ice sheets in the West and East Antarctic and in Greenland. The elicitation enumerated dependencies between these processes under selected global temperature change scenarios over different future time horizons. These expert judgments allowed us to populate a Paired Copula Bayesian network model to obtain the estimated contributions of these ice sheets for future sea level rise. Including positive central tendency dependence and tail dependence increases the fatness of the upper tails of projected sea level rise distributions, an amplification important for designing and evaluating possible mitigation strategies. Detailing and jointly computing distributional dependencies and tail dependencies can be crucial components of good practice for assessing the influence of uncertainties on extreme values when modelling stochastic multifactorial processes.

Vaccination strategies in a pair formation model for human papillomavirus infection: An optimal control approach.

Human papillomavirus (HPV) infection is a widespread sexually transmitted infection responsible for several cancers including anal, oropharyngeal, penile, vaginal, and cervical cancer. Despite HPV vaccines have been available for almost 20 years and are incredibly effective in preventing infection, the scale-up of vaccination has been slow in many low and middle-income countries. This analysis uses a pair model that explicitly accounts for sexual partnership formation to investigate HPV immunization programs. The optimality of vaccine interventions is analyzed using optimal control theory. We give formal proof of the existence of optimal control solutions and obtain first-order optimality conditions via Pontryagin's Maximum Principle. Extensive numerical simulations are used to investigate plausible what-if scenarios to understand under which conditions the inclusion of males should be recommended in addition to female vaccination. The results suggest that a gender-neutral vaccination program should be recommended in regions where vaccination uptake in women is still low whereas for an already existing female-only program with high uptake, it is more effective to keep increasing coverage in females.

Unconventional pairing in Ising superconductors: application to monolayer NbSe2

Abstract The presence of a non-centrosymmetric crystal structure and in-plane mirror symmetry allows an Ising spin–orbit coupling to form in some two-dimensional materials. Examples include transition metal dichalcogenide superconductors like monolayer NbSe2, MoS2, TaS2, and PbTe2, where a nontrivial nature of the superconducting state is currently being explored. In this study, we develop a microscopic formalism for Ising superconductors that captures the superconducting instability arising from a momentum-dependent spin- and charge-fluctuation-mediated pairing interaction. We apply our pairing model to the electronic structure of monolayer NbSe2, where first-principles calculations reveal the presence of strong paramagnetic fluctuations. Our calculations provide a quantitative measure of the mixing between the even- and odd-parity superconducting states and its variation with Coulomb interaction. Further, numerical analysis in the presence of an external Zeeman field reveals the role of Ising spin–orbit coupling and mixing of odd-parity superconducting state in influencing the low-temperature enhancement of the critical magnetic field.

Meshing pair geometry of the intersecting-axis internally geared screw compressor

The Intersecting-Axis Internally Geared Screw Compressor (IISC) is an emerging advanced positive displacement machine showing the potential to greatly broaden the application of screw compressor technology. The core component of the IISC is an internally geared meshing pair with the intersecting-axis gearing, while its design methodology has not been disclosed yet. To fill the gap, this paper established the geometry model for the meshing pair and discussed the influence of its core parameters on geometric performance. First, the generation model of meshing pairs was presented, and the complete parameters set of meshing pairs was defined. The established model was verified by a meshing pair manufactured by 3D printing and CNC techniques. Next, the geometric analysis model of IISCs was established such as working volume and leakage channels, which was verified by commercial 3D software. Using the analysis model, the mesh pair parameters (rotor profile, cone angle, wrap angle, and L/D ratio) were discussed to reveal the design methodology of IISCs. Finally, the variable-pitch technology was discussed, and a novel variable-pitch method was proposed to further enhance the performance of IISCs. This paper could effectively guide the design of IISCs to further promote the development of the screw compressor technology.

Impact of nuclear level density and γ-ray strength function in (n,γ) and Maxwellian-averaged cross-section of 69Zn nucleus

The present paper highlights the impact of nuclear level density (NLD) and γ-ray strength function (γ-SF) on (n,γ) and Maxwellian-averaged cross-section of 69Zn nucleus. At first, the existing NLD and γ-SF models (in TALYS statistical model code) have been utilized to understand the role of NLD and γ-SF in neutron capture reaction cross-section. It is seen that most of the combinations of existing NLDs and γ-SFs (phenomenological and/or microscopic) cannot explain the experimental data. Therefore, the microscopic exact pairing plus independent particle model (EP+IPM) and exact pairing plus phonon damping model (EP+PDM) have been carried out to calculate the NLD and γ-SF of 69Zn nucleus, respectively, by employing the exact treatment of thermal pairing. It is seen that microscopic EP+IPM NLD and EP+PDM γ-SF explain the experimental data better than all other combinations available in TALYS-1.95, indicating the impact of the exact treatment of thermal pairing correlation. In addition, the inclusion of an upbend (UB) structure in γ-SF further improves the comparison with the experimental data in the low energy region (∼0.01–0.15 MeV), indicating the possibility of having an UB structure in γ-SF of 69Zn. The 68Zn(n,γ)69Zn reaction cross-section obtained by utilizing the EP+IPM NLD and EP+PDM γ-SF including UB structure is then used to predict the Maxwellian-averaged cross-sections, and the obtained results show reasonable agreement with all the available experimental data taken from the Karlsruhe Astrophysical Database of Nucleosynthesis in Stars. The present results reflect the impact of microscopic NLD and γ-SF on the precise description and/or prediction of the astrophysical reaction cross-section.

Numerical Simulation on Lubrication and Experiment Study on Tribology Improvement of Slipper Pair at Low Speeds

A mixed lubrication model for the slipper pair of an electric piston pump is proposed to solve problems such as inadequate lubrication, extreme friction, and wear at near-zero and low speeds. The lubrication characteristics of the slipper pair were numerically calculated and simulated, and the frictional characteristics in the low-speed range were analyzed. A self-lubricating and antiwear slipper pair was developed to mitigate severe friction and wear at near-zero and low speeds. To improve the tribological properties of slippers, various concentrations of molybdenum disulfide (MoS2) powder mixed with epoxy resin (EP) were used as self-lubricating materials. The content of MoS2 ranged from 1 and 20 wt%. The optimal content of MoS2 was obtained by conducting frictional tests on the slipper pair samples as well as material examination and analysis of the slipper sample surfaces before and after the surface characterization tests. The lubrication mechanisms of the self-lubricating and antiwear slippers were determined. The EP/MoS2 composite lubricating materials exhibited excellent self-lubricating and antiwear properties, providing a new direction for the optimized design of slipper pairs and other important friction pairs in piston pumps and promising research prospects.

A Dual-Iterative Meshing Stiffness Model and Vibration Analysis for an Angular Misaligned Helical Gear Pair Considering Misalignment-Induced Contact Line Variation

Abstract Angular misalignment is a common error in gear transmission systems, significantly altering the contact and dynamic behaviors of the gear system. Conventionally, the time-varying mesh stiffness (TVMS) of helical gear pairs with angular misalignment is estimated under the assumption of a uniform load distribution along a fixed contact line. However, this simplification neglects the variations in contact line length and load distribution due to angular misalignment, thereby compromising the accuracy of TVMS predictions. To address this limitation, we propose a novel dual-iterative model for TVMS calculation in helical gears, accounting for the angular misalignment-induced contact line variation. This model combines traditional iterative calculations for gear slices with an additional iterative loop for the misalignment-induced contact line changes. Furthermore, it considers both axial and tangential meshing stiffnesses. The proposed dual-iterative TVMS model is verified by using the finite element (FE) method. Moreover, a six degree-of-freedom (DOF) dynamic model for misaligned helical gears is established to investigate the effects of misalignments on the vibration characteristics of the gear pair. An experimental setup utilizing a back-to-back helical gear test rig with adjustable angular misalignment is constructed to validate the proposed model. The experimental results exhibit a close alignment with the simulation predictions. It is concluded that the proposed model is suitable for estimating the TVMS and dynamic analysis of helical gear pairs with angular misalignment errors.

The Psychological Mechanism of Moral Leadership Influencing Responsible Subordinate Behavior

As China’s anti-corruption campaign intensifies, several of those involved in various capacities in the public sector are demonstrating slackness, a lack of moral awareness, and a weakened sense of responsibility. This study analyzes the multiple mechanisms influencing the responsible behavior of public sector personnel by combining certain key factors, such as managers’ moral leadership style, psychological security, and the notion of interactive justice. Based on social information processing theory and social exchange theory, this study constructs a dual mediation model (psychological security and interactive justice) to explore the mediating psychological mechanism of moral leadership influencing employees’ responsible behavior. The results of a two-stage paired survey and structural equation modeling analysis of civil servants from 48 departments and eight units in Shandong and Henan provinces show that moral leadership positively impacts responsible behavior. Moreover, psychological security and interactive justice play a mediating role between them. Furthermore, this study elaborates upon the mechanism of moral leadership affecting the responsible behavior of employees, which is of great value for improving the efficiency of government management and guiding civil servants to behave more responsibly.

Selection and genetic parameters of sheep of the Aginskaya breed of the Zugalay type

The results of the study of selectable traits, exterior-constitutional features of medium wool sheep of the Aginskaya breed of the Zugalay type are presented. The data of correlation-regression, variance analysis are given, according to the results of which paired and multifactor regression models have been designed. Body weight (6.4–12.6%), down length (19.3–19.7%) and awn length (13.1–16.9%) and cannon bone girth (9.1%) are characterized by the greatest variability in the studied sheep. In terms of physique indices, rams are distinguished by longer legs, better breast development, stronger bones, ewe lambs are distinguished by a more stretched, bunched and massive body with a better developed hind part. Correlation analysis of the breeding traits with external body parts indicates that live weight and wool clip in rams has a closer correlation with linear measurements in comparison with ewe lambs. In both males and females, live weight was more strongly correlated with the width in the dippers, wool clip – with the width at hips in rams, in ewe lambs the relationship was weak or practically absent. Linear regression coefficients indicate that live weight and wool clip gain in rams are predicted by an increase per unit in hip width (4.37 abs. gain; r = 0.824; p &lt; 0.001 and 0.13 abs. gain; r = 0.792; p &lt; 0.001). The coefficient of determination showed that in rams the changes in live weight and wool clip by 67.9 and 62.8% were explained by the width at hips, the influence of other factors – 32.1 and 37.2%, respectively. In multifactor regression models, 90.3 and 78.0% of changes in body weight and wool clip in rams are explained by the influence of a complex of linear measurements, in ewe lambs – by 25.7 and 17.5%, respectively, the remaining share is attributed to the influence of other factors, respectively.

Characterization of the AGR2-NPM3 axis uncovers the AGR2 involvement in PD-L1 regulation in colorectal cancer

Despite extensive research, the molecular role of AGR2 in the progression and metastasis of colorectal cancer (CRC) has not been fully characterized. We used quantitative mass spectrometry (SWATH MS) to identify differentially expressed proteins in paired CRC cell models of the SW480 and SW620 cell lines in response to AGR2 protein level manipulation. Relying on the results from SWATH MS and subsequent immunochemical validation, we selected NMP3 as the top candidate protein associated with AGR2 in CRC tumour cells in our screen. RT‒qPCR and immunochemical analysis confirmed the involvement of AGR2-mediated regulation of NPM3 at the transcriptional and posttranscriptional levels. Since PD-L1 is a constituent of the NPM3 regulatory axis, we aimed to correlate the changes in PD-L1 to the differential expression of AGR2 in our cell models. We found that AGR2 positively regulates PD-L1 levels in both SW480 and SW620 cell lines; additionally, several different CRC patient transcriptome cohorts confirmed the association of AGR2 with PD-L1. Our work reveals a new AGR2-NPM3 regulatory axis and the involvement of AGR2 in the regulation of PD-L1, which paves the way for the association of AGR2 with immune evasion in CRC cells.

Long-Term Safety and Efficacy of Janus kinase (JAK) Inhibitors in the Treatment of Rheumatoid Arthritis

Background: Janus kinase (JAK) inhibitors are a new class of drugs for the treatment of rheumatoid arthritis (RA); however, the long-term consequences of using these drugs are still not well understood. Objective: The primary objective of this research was to examine the effectiveness and safety of JAK inhibitors for the management of rheumatoid arthritis (RA) patients. Methodology: Clinical raw data of 150 RA patients receiving JAK inhibitors was collected in different tertiary care hospitals in Lahore, Pakistan from March 2023 to June 2024. till were conducted. The anti-inflammatory effect was evaluated by the Disease Activity Score in 28 joints (DAS28) and the safety profile through adverse events, laboratory markers, and patients self-reported outcomes. The SPSS version 27 applied for raw data analysis which used the paired t-tests and multiple regression models to establish the factors that determine favorable outcomes and complications. Results: JAK inhibitors also reduced the DAS28 scores from baseline to 24 months by a mean of 3. 2 ± 1. 1 (p&lt;0. 001). The findings stated that 12 percent of the patients at baseline and 45 percent of the patients at 24 months had achieved remission. The reported side effects were infections, 25%; gastrointestinal problems, 18%; and abnormal liver function tests, 10%. Severe adverse reactions were noted in 5% of the patients and no new safety issues were observed over the course of the treatment. Conclusion: JAK inhibitors have been shown to be useful in decreasing the activity of RA for the long-term use with reasonable side effects. The results provided evidence that JAK inhibitors were best treatment of rheumatoid arthritis (RA) but for best efficacy results closely monitoring and specific approach should be applied.

Representation theorems for simplicial complexes and matroidal-like properties of minimal partitioners

A pairing on an arbitrary ground set Ω is a triple P:=(U,F,Λ), with U,Λ two sets and F:U×Ω⟶Λ a map. Several properties of pairings arise after considering the Moore set system MP and the abstract simplicial complex NP on Ω, defined by taking the maximum and the minimal elements of the equivalence collections with respect to a specific equivalence relation ≈P, respectively called minimal and maximum partitioners.In the present work we first detect various sufficient conditions allowing us to represent specific subfamilies of abstract simplicial complexes as the family of all the minimal partitioners of some pairing on the same ground set. Next, we classify two suitable subcollections of pairings by using generalized matroidal-like properties of NP. More in detail, we first determine a sufficient condition on P ensuring that the family NP is a closable finitary simplicial complex and call the resulting pairings attractive. On an arbitrary ground set Ω, attractiveness, together with a finiteness condition, implies that the minimal members of the equivalence collections of each X∈MP with respect to ≈P all have the same cardinality. Nevertheless, the converse does not hold, neither in the finite case. To this regard, we find some counterexamples inducing us to introduce the class of quasi-attractive pairings. We carried out a detailed analysis of quasi-attractive pairings: for instance we characterize them from a lattice-theoretic point of view and, on a finite ground set Ω, also in term of exchange properties of suitable set systems.Finally, by taking the adjacence matrix of a simple undirected graph G as a model of pairing, we show that the Petersen graph induces an attractive pairing, while the Erdös' friendship graphs induce a quasi-attractive, but not attractive, one.

P01-15 Two-image paired inference model for automatic classification of growth inhibition in the Ames test

P01-15 Two-image paired inference model for automatic classification of growth inhibition in the Ames test

Custom GPTs Enhancing Performance and Evidence Compared with GPT-3.5, GPT-4, and GPT-4o? A Study on the Emergency Medicine Specialist Examination.

Given the widespread application of ChatGPT, we aim to evaluate its proficiency in the emergency medicine specialty written examination. Additionally, we compare the performance of GPT-3.5, GPT-4, GPTs, and GPT-4o. The research seeks to ascertain whether custom GPTs possess the essential capabilities and access to knowledge bases necessary for providing accurate information, and to explore the effectiveness and potential of personalized knowledge bases in supporting the education of medical residents. We evaluated the performance of ChatGPT-3.5, GPT-4, custom GPTs, and GPT-4o on the Emergency Medicine Specialist Examination in Taiwan. Two hundred single-choice exam questions were provided to these AI models, and their responses were recorded. Correct rates were compared among the four models, and the McNemar test was applied to paired model data to determine if there were significant changes in performance. Out of 200 questions, GPT-3.5, GPT-4, custom GPTs, and GPT-4o correctly answered 77, 105, 119, and 138 questions, respectively. GPT-4o demonstrated the highest performance, significantly better than GPT-4, which, in turn, outperformed GPT-3.5, while custom GPTs exhibited superior performance compared to GPT-4 but inferior performance compared to GPT-4o, with all p < 0.05. In the emergency medicine specialty written exam, our findings highlight the value and potential of large language models (LLMs), and highlight their strengths and limitations, especially in question types and image-inclusion capabilities. Not only do GPT-4o and custom GPTs facilitate exam preparation, but they also elevate the evidence level in responses and source accuracy, demonstrating significant potential to transform educational frameworks and clinical practices in medicine.

Impact of Pesticide Training on Safety Climate Perception Among French Cereal Farmers.

Background: The training of farmers in pesticide safety is of prime importance for reducing pesticide use and exposure through the implementation of sustainable management practices. This study aimed to assess the impact of compulsory training on the knowledge and perceptions of cereal farmers, with the help of a safety climate scale. Method: We approached cereal farmers throughout France during compulsory training and certification procedures for pesticide-related activities. Trainees were asked to complete a safety climate questionnaire at the start and end of the course. In total, 733 cereal farm managers or workers completed the questionnaire at the start of the study, 131 of whom declined to complete the questionnaire at the end of the training session, leaving 602 subjects available for pre-training/post-training comparisons. Statistical analyses were based on paired t-tests and mixed models for repeated measures. Findings: The mean safety climate score increased from 82.37 to 88.22 after the training course (7.1 %, p < .001) in both univariate and multivariate analyses. Mean increases were also found for each of its seven dimensions (p < .001), ranging from 2.8% for "rules and best practices" to 12.4% for "communication and feedback." Few covariate-by-time interactions were found to be significant. Conclusion/Application to Practice: This study demonstrates that pesticide training is highly effective in increasing safety climate perception among cereal farmers and provides hints for improving the design of educational programs. Promoting the development and facilitation of lifelong learning with continuously updated training programs should be a top priority for minimizing pesticide exposure.