bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of cord plasma metabolites with birth weight: results from metabolomic and lipidomic studies of discovery and validation cohorts
Authors: Xie Y. , Fang X. , Wang A. , Xu S. , Li Y. , Xia W. 
Published: January 2024

ABSTRACTObjectiveBirth weight is a good predictor of fetal intrauterine growth and long‐term health, and several studies have evaluated the relationship between metabolites and birth weight. The aim of this study was to investigate the association of cord blood metabolomics and lipidomics with birth weight, using a two‐stage discovery and validation approach.MethodsFirstly, a pseudotargeted metabolomics approach was applied to detect metabolites in 504 cord blood samples in the discovery set enrolled from the Wuhan Healthy Baby Cohort, China. Metabolome‐wide association scan analysis and pathway enrichment were applied to identify metabolites and metabolic pathways that were significantly associated with birth weight adjusted for gestational age Z‐score (BW Z‐score). Logistic regression models were used to analyze the association of metabolites in the most significantly associated pathways with small‐for‐gestational age (SGA) at delivery and low birth weight (LBW). Subsequently, 350 cord blood samples in a validation cohort were subjected to targeted analysis to validate the metabolites identified by screening in the discovery cohort.ResultsIn the discovery set, of 2566 metabolites detected, 2418 metabolites were retained for subsequent analysis after data preprocessing. Of these, 513 metabolites were significantly associated with BW Z‐score (P‐value adjusted for false discovery rate (PFDR) < 0.05), of which 298 Kyoto Encyclopedia of Genes and Genomes (KEGG)‐annotated metabolites were included in the pathway analysis. The primary bile acid biosynthesis pathway was the most relevant metabolic pathway associated with BW Z‐score. Elevated cord plasma primary bile acids were associated with lower BW Z‐score and higher risk of SGA or LBW in the discovery and validation cohorts. In the validation set, a 2‐fold increase in taurochenodeoxycholic acid (TCDCA) and in taurocholic acid (TCA) was associated with a decrease in BW Z‐score (estimated β coefficient, −0.10 (95% CI, −0.20 to 0.00) and −0.18 (95% CI, −0.31 to −0.04), respectively), after adjusting for covariates. In addition, a 2‐fold increase in cord plasma TCDCA and of cord plasma TCA was associated with an increased risk of SGA (adjusted odds ratio (OR), 1.52 (95% CI, 1.00–2.30) and 1.77 (95% CI, 1.05–2.98), respectively). The adjusted OR for LBW, for a 2‐fold increase in TCDCA and TCA concentration, were 2.39 (95% CI, 1.00–5.71) and 3.21 (95% CI, 0.96–10.74), respectively.ConclusionsThese results indicate a significant association of elevated primary bile acids, particularly TCDCA and TCA, in cord blood with lower BW Z‐score, as well as increased risk of SGA and LBW. Abnormalities of primary bile acid metabolism may play an important role in restricted fetal development. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.
Problems of prevention of criminal offenses related to the use of water resources in Kazakhstan
Authors: Sabyr Aisulu , Ramazanova Ainur , Koishybaiuly Kuanysh , Zhanibekov Akynkozha , Apakhayev Nurlan 
Published: January 2024

AbstractThe protection of the environment and its elements is the responsibility of modern society for the possibility of its development in the future. That is why the issues of protection of this category of relations are relevant today in the legal plane. It is important to establish not only an effective mechanism for punishing the guilty but also for preventing the commission of criminal offenses against natural objects. The purpose of the study is to identify effective approaches for the prevention of crimes related to the use of water bodies. In the study, the methods of analysis and synthesis, comparison, deduction, generalization, formal legal, and abstraction were applied. As a result, it was possible to determine that the current state of water bodies in Kazakhstan is deteriorating, so they may be at a crisis level in the future. In view of this, the paper investigated the composition of a criminal offense related to the illegal use of water bodies. This made it possible to determine the current position of the legislator on the regulation of this issue in the legal dimension. In addition, the methods and tools that are used in Kazakhstan to prevent the spread of this type of criminal offense were established. Based on this, their shortcomings were analyzed, and proposals were developed to improve the process of preventing such crimes. Therefore, the place of environmental crimes in the modern criminal law doctrine was determined, and international experience in preventing such offenses was considered. The practical value of the findings is the possibility of using them to develop new national strategies and programs aimed at countering crimes in the field of water use.
EcoShap: Save Computations by only Calculating Shapley Values for Relevant Features
Authors: Jamshidi Parisa , Nowaczyk Sławomir , Rahat Mahmoud 
Published: January 2024

AbstractOne of the most widely adopted approaches for eXplainable Artificial Intelligence (XAI) involves employing of Shapley values (SVs) to determine the relative importance of input features. While based on a solid mathematical foundation derived from cooperative game theory, SVs have a significant drawback: high computational cost. Calculating the exact SV is an NP-hard problem, necessitating the use of approximations, particularly when dealing with more than twenty features. On the other hand, determining SVs for all features is seldom necessary in practice; users are primarily interested in the most important ones only. This paper introduces the Economic Hierarchical Shapley values (ecoShap) method for calculating SVs for the most crucial features only, with reduced computational cost. EcoShap iteratively expands disjoint groups of features in a tree-like manner, avoiding the expensive computations for the majority of less important features. Our experimental results across eight datasets demonstrate that the proposed technique efficiently identifies top features; at a 50% reduction in computational costs, it can determine between three and seven of the most important features.
Evaluation of Human-Understandability of Global Model Explanations Using Decision Tree
Authors: Sivaprasad Adarsa , Reiter Ehud , Tintarev Nava , Oren Nir 
Published: January 2024

AbstractIn explainable artificial intelligence (XAI) research, the predominant focus has been on interpreting models for experts and practitioners. Model agnostic and local explanation approaches are deemed interpretable and sufficient in many applications. However, in domains like healthcare, where end users are patients without AI or domain expertise, there is an urgent need for model explanations that are more comprehensible and instil trust in the model’s operations. We hypothesise that generating model explanations that are narrative, patient-specific and global (holistic of the model) would enable better understandability and enable decision-making. We test this using a decision tree model to generate both local and global explanations for patients identified as having a high risk of coronary heart disease. These explanations are presented to non-expert users. We find a strong individual preference for a specific type of explanation. The majority of participants prefer global explanations, while a smaller group prefers local explanations. A task based evaluation of mental models of these participants provide valuable feedback to enhance narrative global explanations. This, in turn, guides the design of health informatics systems that are both trustworthy and actionable.
Towards Explainable Deep Domain Adaptation
Authors: Bobek Szymon , Nowaczyk Sławomir , Pashami Sepideh , Taghiyarrenani Zahra , Nalepa Grzegorz J. 
Published: January 2024

AbstractIn many practical applications data used for training a machine learning model and the deployment data does not always preserve the same distribution. Transfer learning and, in particular, domain adaptation allows to overcome this issue, by adapting the source model to a new target data distribution and therefore generalizing the knowledge from source to target domain. In this work, we present a method that makes the adaptation process more transparent by providing two complementary explanation mechanisms. The first mechanism explains how the source and target distributions are aligned in the latent space of the domain adaptation model. The second mechanism provides descriptive explanations on how the decision boundary changes in the adapted model with respect to the source model. Along with a description of a method, we also provide initial results obtained on publicly available, real-life dataset.
Cancellation of quantum corrections on the soft curvature perturbations
Authors: Tada Yuichiro , Terada Takahiro , Tokuda Junsei 
Published: January 2024

Abstract
We study the cancellation of quantum corrections on the superhorizon curvature perturbations from subhorizon physics beyond the single-clock inflation from the viewpoint of the cosmological soft theorem. As an example, we focus on the transient ultra-slow-roll inflation scenario and compute the one-loop quantum corrections to the power spectrum of curvature perturbations taking into account nontrivial surface terms in the action. We find that Maldacena’s consistency relation is satisfied and guarantees the cancellation of contributions from the short-scale modes. As a corollary, primordial black hole production in single-field inflation scenarios is not excluded by perturbativity breakdown even for the sharp transition case in contrast to some recent claims in the literature. We also comment on the relation between the tadpole diagram in the in-in formalism and the shift of the elapsed time in the stochastic-δN formalism. We find our argument is not directly generalisable to the tensor perturbations.
Renormalization group improved photon impact factors and the high energy virtual photon scattering
Authors: Colferai Dimitri , Li Wanchen , Staśto Anna M. 
Published: January 2024

Abstract
We perform the renormalization group improved collinear resummation of the photon-gluon impact factors. We construct the resummed cross section for virtual photon-photon (γ∗γ∗) scattering which incorporates the impact factors and BFKL gluon Green’s function up to the next-to-leading logarithmic accuracy in energy. The impact factors include important kinematical effects which are responsible for the most singular poles in Mellin space at next-to-leading order. Further conditions on the resummed cross section are obtained by requiring the consistency with the collinear limits. Our analysis is consistent with previous impact factor calculations at NLO, apart from a new term proportional to CF that we find for the longitudinal polarization. Finally, we use the resummed cross section to compare with the LEP data on the γ∗γ∗ cross section and with previous calculations. The resummed result is lower than the leading logarithmic approximation but higher than the pure next-to-leading one, and is consistent with the experimental data.
The SUSY index beyond the Cardy limit
Authors: Mamroud Ohad 
Published: January 2024

Abstract
We analyze a set of contributions to the superconformal index of 4d 𝒩 = 4 SU(N) super Yang-Mills using the Bethe Ansatz approach. These contributions dominate at the large N limit, where their leading order in N reproduces various supersymmetric Euclidean black hole saddles in the dual theory, and they also dominate for finite N in high temperature Cardy-like limits. We compute the O(N0) terms, including those exponentially suppressed in the Cardy limit, and show that there are no 1/N corrections beyond them. Under certain assumptions, it implies that the gravitational perturbative series around these black hole saddles is 1-loop exact.
Local Poincaré algebra from quantum chaos
Authors: Ouseph Shoy , Furuya Keiichiro , Lashkari Nima , Leung Kwing Lam , Moosa Mudassir 
Published: January 2024

Abstract
The local two-dimensional Poincaré algebra near the horizon of an eternal AdS black hole, or in proximity to any bifurcate Killing horizon, is generated by the Killing flow and outward null translations on the horizon. In holography, this local Poincaré algebra is reflected as a pair of unitary flows in the boundary Hilbert space whose generators under modular flow grow and decay exponentially with a maximal Lyapunov exponent. This is a universal feature of many geometric vacua of quantum gravity. To explain this universality, we show that a two-dimensional Poincaré algebra emerges in any quantum system that has von Neumann subalgebras associated with half-infinite modular time intervals (modular future and past subalgebras) in a limit analogous to the near-horizon limit. In ergodic theory, quantum dynamical systems with future or past algebras are called quantum K-systems. The surprising statement is that modular K-systems are always maximally chaotic.Interacting quantum systems in the thermodynamic limit and large N theories above the Hawking-Page phase transition are examples of physical theories with future/past subalgebras. We prove that the existence of (modular) future/past von Neumann subalgebras also implies a second law of (modular) thermodynamics and the exponential decay of (modular) correlators. We generalize our results from the modular flow to any dynamical flow with a positive generator and interpret the positivity condition as quantum detailed balance.
Hypergraphs in LHC phenomenology — the next frontier of IRC-safe feature extraction
Authors: Konar Partha , Ngairangbam Vishal S. , Spannowsky Michael 
Published: January 2024

Abstract
In this study, we critically evaluate the approximation capabilities of existing infra-red and collinear (IRC) safe feature extraction algorithms, namely Energy Flow Networks (EFNs) and Energy-weighted Message Passing Networks (EMPNs). Our analysis reveals that these algorithms fall short in extracting features from any N-point correlation that isn’t a power of two, based on the complete basis of IRC safe observables, specifically C-correlators. To address this limitation, we introduce the Hypergraph Energy-weighted Message Passing Networks (H-EMPNs), designed to capture any N-point correlation among particles efficiently. Using the case study of top vs. QCD jets, which holds significant information in its 3-point correlations, we demonstrate that H-EMPNs targeting up to N=3 correlations exhibit superior performance compared to EMPNs focusing on up to N=4 correlations within jet constituents.
Inequalities for Convex Functions and Isotonic Sublinear Functionals
Authors: Otachel Zdzisław 
Published: January 2024

AbstractIn this paper, versions of the famous Jensen inequality for sublinear isotonic functionals are proved. The obtained results generalize classic Jessen’s and McShane’s inequalities. Applications to generalized means and to Hölder’s and Minkowski’s inequalities are also given.
Artificial intelligence (AI)—it’s the end of the tox as we know it (and I feel fine)*
Authors: Kleinstreuer Nicole , Hartung Thomas 
Published: January 2024

AbstractThe rapid progress of AI impacts diverse scientific disciplines, including toxicology, and has the potential to transform chemical safety evaluation. Toxicology has evolved from an empirical science focused on observing apical outcomes of chemical exposure, to a data-rich field ripe for AI integration. The volume, variety and velocity of toxicological data from legacy studies, literature, high-throughput assays, sensor technologies and omics approaches create opportunities but also complexities that AI can help address. In particular, machine learning is well suited to handle and integrate large, heterogeneous datasets that are both structured and unstructured—a key challenge in modern toxicology. AI methods like deep neural networks, large language models, and natural language processing have successfully predicted toxicity endpoints, analyzed high-throughput data, extracted facts from literature, and generated synthetic data. Beyond automating data capture, analysis, and prediction, AI techniques show promise for accelerating quantitative risk assessment by providing probabilistic outputs to capture uncertainties. AI also enables explanation methods to unravel mechanisms and increase trust in modeled predictions. However, issues like model interpretability, data biases, and transparency currently limit regulatory endorsement of AI. Multidisciplinary collaboration is needed to ensure development of interpretable, robust, and human-centered AI systems. Rather than just automating human tasks at scale, transformative AI can catalyze innovation in how evidence is gathered, data are generated, hypotheses are formed and tested, and tasks are performed to usher new paradigms in chemical safety assessment. Used judiciously, AI has immense potential to advance toxicology into a more predictive, mechanism-based, and evidence-integrated scientific discipline to better safeguard human and environmental wellbeing across diverse populations.
Factors associated with trajectories of bone marrow lesions over 4 years: data from the Osteoarthritis Initiative
Authors: Shen Ziyuan , Zhang Xiaoyue , Wang Yining , Zhu Rui , Ge Liru , Cai Guoqi 
Published: January 2024

Abstract
Objective
To identify bone marrow lesion (BML) trajectories over 4 years and their demographic and structural predictors in middle-aged and older adults with or at increased risk of knee osteoarthritis (OA).

Methods
A total of 614 participants (mean age 61 years, 62% female) from the Osteoarthritis Initiative cohort (OAI) were included. BMLs in 15 anatomical locations of the knee were measured annually from baseline to 4 years using the Magnetic Resonance Imaging Osteoarthritis Knee Score (MOAKS) method. BML trajectories were determined using latent class mixed models (LCMMs). Multinomial logistic regression was used to examine baseline characteristics that predicted BML trajectories.

Results
Three distinct BML trajectories were identified: “Mild-stable BMLs” (25.9%), “Moderate-stable BMLs” (66.4%), and “Rapid-rise BMLs” (7.7%). Compared to the “Mild-stable BMLs” trajectory, current smokers were more likely to be in the “Moderate-stable BMLs” (odds ratio [OR] 2.089, P < 0.001) and “Rapid-rise” (OR 2.462, P < 0.001) trajectories. Moreover, female sex and meniscal tears were associated with an increased risk of being in the “Rapid-rise BMLs” trajectory (OR 2.023 to 2.504, P < 0.05). Participants who had higher education levels and drank more alcohol were more likely to be in the “Rapid-rise BMLs” trajectory (OR 1.624 to 3.178, P < 0.05) and less likely to be in the “Moderate-stable BMLs” trajectory (OR 0.668 to 0.674, P < 0.05).

Conclusions
During the 4-year follow-up, most participants had relatively stable BMLs, few had enlarged BMLs, and no trajectory of decreased BMLs was identified. Sociodemographic factors, lifestyle, and knee structural pathology play roles in predicting distinct BML trajectories.
Acute and long-term toxicity in primary hypofractionated external photon radiation therapy in patients with localized prostate cancer
Authors: Lilleby Wolfgang , Kishan Amar , Geinitz Hans 
Published: January 2024

Abstract

Background
Compelling evidence exists for the iso-effectiveness and safety of moderate hypofractionated radiotherapy (Hypo-RT) schedules [1, 2]. However, international guidelines are not congruent regarding recommendation of ultrahypofractionated radiotherapy (UHF-RT) to all risk groups.

Methods
The current review gives an overview of clinically relevant toxicity extracted from major randomized controlled trials (RCT) trials comparing conventional to hypofractionated regimes in the primary setting of external photon radiation. Functional impairments are reported by using physician-rated and patient-reported scores using validated questionnaires.

Results
The uncertain radiobiology of the urethra/bladder when applying extreme hypofractionation may have contributed to worse acute urinary toxicity score in the Scandinavian UHF-RT and worse subacute toxicity in PACE-B. The observed trend of increased acute GI toxicity in several moderate Hypo-RT trials and one UHF-RT trial, the Scandinavian Hypo-RT PC trial, could be associated to the different planning margins and radiation dose schedules.

Conclusion
Nevertheless, Hypo-RT has gained ground for patients with localized PCa and further improvements may be achieved by inclusion of genetically assessed radiation sensitivity. Several RCTs in Hypo-RT have shown non-inferior outcome and well-tolerated treatment toxicity by physician-rated scores. In the future, we suggest that toxicity should be measured by patient-reported outcome (PRO) using comparable questionnaires.
Size of lymph-node metastases in prostate cancer patients undergoing radical prostatectomy: implication for imaging and oncologic follow-up of 2705 lymph-node positive patients
Authors: Falkenbach Fabian , Kachanov Mykyta , Leyh-Bannurah Sami-Ramzi , Maurer Tobias , Knipper Sophie , Köhler Daniel , Graefen Markus , Sauter Guido , Budäus Lars 
Published: January 2024

Abstract
Background
Despite modern imaging modalities, lymph-node staging before radical prostatectomy (RP) remains challenging in patients with prostate cancer (PCa). The visibility of lymph-node metastases (LNMs) is critically influenced by their size.

Objective
This study aims to describe the distribution of maximal tumor diameters (i.e., size) in LNMs of pN1-PCa at RP and its consequences on visibility in preoperative imaging and oncological outcomes.

Design, setting, and participants
A total of 2705 consecutive patients with pN1-PCa at RP, harboring a cumulative 7510 LNMs, were analyzed. Descriptive and multivariable analyses addressed the risk of micrometastases (MM)-only disease and the visibility of LNMs. Kaplan–Meier curves and Cox analyses were used for biochemical recurrence-free survival (BCRFS) stratified for MM-only disease.

Results
The median LNM size was 4.5mm (interquartile range (IQR): 2.0–9.0 mm). Of 7510 LNMs, 1966 (26%) were MM (≤ 2mm). On preoperative imaging, 526 patients (19%) showed suspicious findings (PSMA-PET/CT: 169/344, 49%). In multivariable analysis, prostate-specific antigen (PSA) (OR 0.98), age (OR 1.01), a Gleason score greater than 7 at biopsy (OR 0.73), percentage of positive cores at biopsy (OR 0.36), and neoadjuvant treatment (OR 0.51) emerged as independent predictors for less MM-only disease (p < 0.05). Patients with MM-only disease compared to those harboring larger LNMs had a longer BCRFS (median 60 versus 29 months, p < 0.0001).

Conclusion
Overall, 26% of LNMs were MM (≤ 2mm). Adverse clinical parameters were inversely associated with MM at RP. Consequently, PSMA-PET/CT did not detect a substantial proportion of LNMs. LNM size and count are relevant for prognosis.