bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systematic optimization of reverse phase ultra‐high‐performance liquid chromatography method for quantification of nilotinib and its related substances in bulk drug and pharmaceutical formulation using quality by design approach
Authors: Prasad Shishir Kumar , Kalpana Divekar 
Published: February 2024

AbstractA sensitive ultra‐high‐performance liquid chromatography (UHPLC) method was developed for the quantification of trace levels of nilotinib and its related substances (RSs) in the nilotinib capsule dosage form. Critical method parameters were optimized using the design of experiments, employing the ACQUITY UHPLC BEH Phenyl column (2.1 × 100 mm, 1.7 μm) at a constant flow rate of 0.6 mL/min. The isocratic mobile phase, consisting of aqueous and organic phases, achieved efficient chromatographic separation within 8 min at 261 nm. The mean retention time for nilotinib was 6.1339, and for RSs, it ranged from 2.10 to 6.91 min, with a resolution exceeding 2 for all peaks. The method demonstrated robustness, separating known impurities and degradation products. The linearity was assessed over a concentration range of 0.02–80 ppm for nilotinib and 0.015–0.12 ppm for impurities. The limit of detection and limit of quantitation (LOQ) for nilotinib were 0.01 and 0.02 μg/mL, respectively, and 0.01 and 0.015 μg/mL for individual impurities. Recovery studies at LOQ, 100%, and 150% of the specification limit yielded percent recoveries ranging from 92.27% to 102.45%. Precision results showed low relative standard deviations, below 2% for nilotinib and below 8% for impurities. This method is deemed suitable for pharmaceutical formulation quantification.
The SoS conductor: Orchestrating resources with iterative agent‐based reinforcement learning
Authors: Chen Qiliang , Heydari Babak 
Published: February 2024

AbstractWe introduce a novel resource management approach for Systems of Systems (SoS), utilizing hierarchical deep reinforcement learning, iterating with agent‐based simulation. A key innovation of this method is its ability to balance top‐down SoS management with the autonomy of individual systems. This is achieved by dynamically allocating resources to each system, thereby modifying the range of options they can autonomously choose from. This dynamic option adjustment is a powerful approach to managing the trade‐off between centralized efficiency and decentralized autonomous actions of the systems, enabling the SoS to maintain the systems' autonomy while ensuring efficient SoS governance. The method, validated through a case study, not only demonstrates the potential and efficacy of the learning framework but also reveals how, using this method, minor performance sacrifices can lead to substantial improvements in resource efficiency.
Nucleotide‐Protocell Interactions: A Reciprocal Relationship in Prebiotically Pertinent Environments
Authors: Deshpande Kshitij , Kulshreshtha Nishant Nitinidhi , Mulewar Sahil Sunil , Rajamani Sudha 
Published: February 2024

AbstractSpontaneous interactions between nucleotides and lipid membranes are likely to have played a prominent role in the emergence of life on Earth. However, the effect of nucleotides on the physicochemical properties of model protocellular membranes is relatively less understood. To this end, we aimed to discern the effect of canonical nucleotides on the properties of single‐chain amphiphile membranes under prebiotically relevant conditions of multiple wet‐dry cycles. Furthermore, the change in the critical aggregation concentration of the membranes and their stability in the presence of nucleotides was also investigated in astrobiologically relevant analogue environments. We report that different nucleotides, lipid headgroups, and the ionic makeup of the system affect lipid‐nucleotide interactions, and these, in turn, modulate the effect of nucleotides on the membrane properties. Specifically, the presence of AMP, UMP, and CMP promoted self‐assembly of oleic acid membranes and increased their stability against certain prebiotically relevant selection pressures. This study takes us a step towards an appreciable understanding of how nucleotides might have shaped the protocellular landscape of the prebiotic Earth.
Centering relationships in collegiate leadership curricula
Authors: Holder Courtney , Pursley Dana 
Published: February 2024

AbstractThe relational leadership model and the five practices of exemplary leadership are widely used models that both emphasize a relational approach to leadership and center the collegiate context as a transformative environment for practicing and developing leadership. This article highlights two different applications of these models and provides important considerations for designing relational leadership curricula and programs for college students.
Culturally relevant leadership learning in action: Applying CRLL to curriculum development and program design
Authors: Chunoo Vivechkanand S. , Devies Brittany 
Published: February 2024

AbstractMany leadership educators want to incorporate cultural relevance, cultural responsiveness, and social justice into their work but may be uncertain of how to begin. Others may already be working in culturally relevant leadership learning (CRLL) modalities and deeply desire advice on how to elevate their offerings. Here, the authors provide a brief overview of the CRLL model to explain how it can be applied in curricular and co‐curricular postsecondary educational settings. Each author then describes how they have found success implementing CRLL tenets in their areas of influence. Following those descriptions, we offer some critiques and considerations related to CRLL and conclude by suggesting resources to help educators apply CRLL to their efforts.
The craft of integrating and layering leadership theories and models for application
Authors: Correia‐Harker Benjamin P. 
Published: February 2024

AbstractTo develop transformative experiences, educators must meaningfully ground leadership development interventions in theories and models that reflect how leadership is conceptualized and operationalized within a community and/or institution. Since no single framework perfectly captures the socially constructed and multifaceted nature of leadership, educators must often pull from and weave together multiple theories and models when creating leadership development programs. This article explores consideration for leadership theory application through contextual and audience alignment, as well as considerations for integration of theory that address underlying theoretical assumptions, framework gaps, and developmental readiness. Reflection prompts are provided for each consideration so educators can envision practical implications from insights surfaced.
The critical role of endothelial cell in the toxicity associated with chimeric antigen receptor T cell therapy and intervention strategies
Authors: Zhang Qi , Zhu Xiaojian , Xiao Yi 
Published: February 2024

AbstractChimeric antigen receptor (CAR)-T cell therapy has shown promising results in patients with hematological malignancies. However, many patients still have poor prognoses or even fatal outcomes due to the life-threatening toxicities associated with the therapy. Moreover, even after improving the known influencing factors (such as number or type of CAR-T infusion) related to CAR-T cell infusion, the results remain unsatisfactory. In recent years, it has been found that endothelial cells (ECs), which are key components of the organization, play a crucial role in various aspects of immune system activation and inflammatory response. The levels of typical markers of endothelial activation positively correlated with the severity of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxic syndrome (ICANS), suggesting that ECs are important targets for intervention and toxicity prevention. This review focuses on the critical role of ECs in CRS and ICANS and the intervention strategies adopted.
Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model
Authors: Tong Yiwei , Hu Zhaoyu , Wang Haoyu , Huang Jiahui , Zhan Ying , Chai Weimin , Deng Yinhui , Yuan Ying , Shen Kunwei , Wang Yuanyuan , Chen Xiaosong , Yu Jinhua 
Published: February 2024

Abstract
Objectives
Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer. New measures are needed for a precise risk stratification to guide (de-)escalation of anti-HER2 strategy.

Methods
A total of 726 HER2 + cases who received no/single/dual anti-HER2 targeted therapies were split into three respective cohorts. A deep learning model (DeepTEPP) based on preoperative breast magnetic resonance (MR) was developed. Patients were scored and categorized into low-, moderate-, and high-risk groups. Recurrence-free survival (RFS) was compared in patients with different risk groups according to the anti-HER2 treatment they received, to validate the value of DeepTEPP in predicting treatment efficacy and guiding anti-HER2 strategy.

Results
DeepTEPP was capable of risk stratification and guiding anti-HER2 treatment strategy: DeepTEPP-Low patients (60.5%) did not derive significant RFS benefit from trastuzumab (p = 0.144), proposing an anti-HER2 de-escalation. DeepTEPP-Moderate patients (19.8%) significantly benefited from trastuzumab (p = 0.048), but did not obtain additional improvements from pertuzumab (p = 0.125). DeepTEPP-High patients (19.7%) significantly benefited from dual HER2 blockade (p = 0.045), suggesting an anti-HER2 escalation.

Conclusions
DeepTEPP represents a pioneering MR-based deep learning model that enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thereby providing valuable guidance for anti-HER2 (de-)escalation strategies. DeepTEPP provides an important reference for choosing the appropriate individualized treatment in HER2 + breast cancer patients, warranting prospective validation.

Clinical relevance statement
We built an MR-based deep learning model DeepTEPP, which enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thus guiding anti-HER2 (de-)escalation strategies in early HER2-positive breast cancer patients.

Key Points
• DeepTEPP is able to predict anti-HER2 effectiveness and to guide treatment (de-)escalation.
• DeepTEPP demonstrated an impressive prognostic efficacy for recurrence-free survival and overall survival.
• To our knowledge, this is one of the very few, also the largest study to test the efficacy of a deep learning model extracted from breast MR images on HER2-positive breast cancer survival and anti-HER2 therapy effectiveness prediction.
Mineralocorticoid receptor promotes cardiac macrophage inflammaging
Authors: Fraccarollo Daniela , Geffers Robert , Galuppo Paolo , Bauersachs Johann 
Published: February 2024

AbstractInflammaging, a pro-inflammatory status that characterizes aging and primarily involving macrophages, is a master driver of age-related diseases. Mineralocorticoid receptor (MR) activation in macrophages critically regulates inflammatory and fibrotic processes. However, macrophage-specific mechanisms and the role of the macrophage MR for the regulation of inflammation and fibrotic remodeling in the aging heart have not yet been elucidated. Transcriptome profiling of cardiac macrophages from male/female young (4 months-old), middle (12 months-old) and old (18 and 24 months-old) mice revealed that myeloid cell-restricted MR deficiency prevents macrophage differentiation toward a pro-inflammatory phenotype. Pathway enrichment analysis showed that several biological processes related to inflammation and cell metabolism were modulated by the MR in aged macrophages. Further, transcriptome analysis of aged cardiac fibroblasts revealed that macrophage MR deficiency reduced the activation of pathways related to inflammation and upregulation of ZBTB16, a transcription factor involved in fibrosis. Phenotypic characterization of macrophages showed a progressive replacement of the TIMD4+MHC-IIneg/low macrophage population by TIMD4+MHC-IIint/high and TIMD4–MHC-IIint/high macrophages in the aging heart. By integrating cell sorting and transwell experiments with TIMD4+/TIMD4–macrophages and fibroblasts from old MRflox/MRLysMCre hearts, we showed that the inflammatory crosstalk between TIMD4– macrophages and fibroblasts may imply the macrophage MR and the release of mitochondrial superoxide anions. Macrophage MR deficiency reduced the expansion of the TIMD4– macrophage population and the emergence of fibrotic niches in the aging heart, thereby protecting against cardiac inflammation, fibrosis, and dysfunction. This study highlights the MR as an important mediator of cardiac macrophage inflammaging and age-related fibrotic remodeling.
Automated detection of fatal cerebral haemorrhage in postmortem CT data
Authors: Zirn Andrea , Scheurer Eva , Lenz Claudia 
Published: February 2024

AbstractDuring the last years, the detection of different causes of death based on postmortem imaging findings became more and more relevant. Especially postmortem computed tomography (PMCT) as a non-invasive, relatively cheap, and fast technique is progressively used as an important imaging tool for supporting autopsies. Additionally, previous works showed that deep learning applications yielded robust results for in vivo medical imaging interpretation. In this work, we propose a pipeline to identify fatal cerebral haemorrhage on three-dimensional PMCT data. We retrospectively selected 81 PMCT cases from the database of our institute, whereby 36 cases suffered from a fatal cerebral haemorrhage as confirmed by autopsy. The remaining 45 cases were considered as neurologically healthy. Based on these datasets, six machine learning classifiers (k-nearest neighbour, Gaussian naive Bayes, logistic regression, decision tree, linear discriminant analysis, and support vector machine) were executed and two deep learning models, namely a convolutional neural network (CNN) and a densely connected convolutional network (DenseNet), were trained. For all algorithms, 80% of the data was randomly selected for training and 20% for validation purposes and a five-fold cross-validation was executed. The best-performing classification algorithm for fatal cerebral haemorrhage was the artificial neural network CNN, which resulted in an accuracy of 0.94 for all folds. In the future, artificial neural network algorithms may be applied by forensic pathologists as a helpful computer-assisted diagnostics tool supporting PMCT-based evaluation of cause of death.
Effectiveness of antipsychotics for managing agitated delirium in patients with advanced cancer: a secondary analysis of a multicenter prospective observational study in Japan (Phase-R)
Authors: Kurisu Ken , Inada Shuji , Maeda Isseki , Nobata Hiroyuki , Ogawa Asao , Iwase Satoru , Uchida Megumi , Akechi Tatsuo , Amano Koji , Nakajima Nobuhisa , Morita Tatsuya , Sumitani Masahiko , Yoshiuchi Kazuhiro 
Published: February 2024

Abstract
Purpose
Delirium is a common and serious comorbidity in patients with advanced cancer, necessitating effective management. Nonetheless, effective drugs for managing agitated delirium in patients with advanced cancer remain unclear in real-world settings. Thus, the present study aimed to explore an effective pharmacotherapy for this condition.

Methods
We conducted a secondary analysis of a multicenter prospective observational study in Japan. The analysis included patients with advanced cancer who presented with agitated delirium and received pharmacotherapy. Agitation was defined as a score of the Richmond Agitation-Sedation Scale for palliative care (RASS-PAL) of ≥ 1. The outcome was defined as -2 ≤ RASS-PAL ≤ 0 at 72 h after the initiation of pharmacotherapy. Multiple propensity scores were quantified using a multinomial logistic regression model, and adjusted odds ratios (ORs) were calculated for haloperidol, chlorpromazine, olanzapine, quetiapine, and risperidone.

Results
The analysis included 271 patients with agitated delirium, and 87 (32%) showed -2 ≤ RASS-PAL ≤ 0 on day 3. The propensity score-adjusted OR of olanzapine was statistically significant (OR, 2.91; 95% confidence interval, 1.12 to 7.80; P = 0.030).

Conclusions
The findings suggest that olanzapine may effectively improve delirium agitation in patients with advanced cancer.
The strategic prize game Le Her
Authors: Schwarz Wolf 
Published: February 2024

AbstractLe Her is a strategic two-person prize game the classic version of which uses a deck of cards. Despite its simple rules, the analysis of the game is surprisingly complex. I describe a modern variant of Le Her that is amenable to elementary analysis, yet retains and highlights all central aspects of the classical game. This elementary analysis combines naturally central concepts of calculus (partial derivatives, multidimensional optimization, double integrals, fixed and saddle points) with major probabilistic concepts (random variable, event, independence) and basic notions in decision theory (Nash equilibrium). Due to its stimulating context as a strategic prize game Le Her offers an attractive illustration and an appealing application of learning goals and curricular contents which are otherwise often perceived as remote and abstract.
Visualization, transformation, and analysis of execution traces with the eclipse TRACE4CPS trace tool
Authors: Hendriks Martijn , Verriet Jacques , Basten Twan 
Published: February 2024

AbstractAn execution trace is a model of a single system behavior. Execution traces occur everywhere in the system’s lifecycle as they can typically be produced by executable models, by prototypes of (sub)systems, and by the system itself during its operation. An execution trace can be visualized and analyzed with various techniques, providing insight into the dynamic behavior, performance, bottlenecks, etc., of the system. In this paper, we present the Trace tool of the Eclipse Trace4cps project for the visualization and analysis of execution traces. A prominent application is the trace-based performance engineering of embedded or cyber-physical systems. Performance is an important system quality, as it can give a competitive advantage. Reasoning about system-level performance in such systems, however, is hard due to its cross-cutting nature. We show how the Trace tool can support this by various examples. Performance engineering is not the only application of the Trace tool, however: it supports system analysis in a wide range of situations.
Robotic surgery for bowel endometriosis: a multidisciplinary management of a complex entity
Authors: Piozzi G. N. , Burea V. , Duhoky R. , Stefan S. , So C. , Wilby D. , Tsepov D. , Khan J. S. 
Published: February 2024

Abstract
Background
Bowel endometriosis impacts quality of life. Treatment requires complex surgical procedures with associated morbidity. Precision approach with robotic surgery leads to organ preservation. Bowel endometriosis requires a multidisciplinary management to improve patient outcomes. This study evaluates perioperative outcomes of bowel endometriosis undergoing multidisciplinary planning and robotic surgery.

Methods
Consecutive cases of multidisciplinary robotic bowel endometriosis procedures (January 2021–December 2022) were evaluated from a prospectively maintained database in a national endometriosis accredited centre. Patients were managed through a multidisciplinary setting including gynaecologists, colorectal robotic surgeons, and other specialists. Dyschezia (menstrual and non-cyclical) and quality of life were assessed pre- and postoperatively (6 months) through validated questionnaires.

Results
Sixty-eight consecutive cases of robotic bowel endometriosis were included. Median age was 35.0 (30.2–42.0) years. Median body mass index was 24.0 (21.0–26.7) kg/m2. Procedures performed were 48 (70.6%) shavings, 11 (16.2%) deep shavings, 3 (4.4%) disc excisions, and 6 (8.8%) segmental resections. One (1.5%) patient required temporary stoma. Median operating time was 150 (120–180) min. There were no conversions/return to theatre postoperatively. Median endometriotic nodule size was 25.0 (15.5–40.0) mm. Two (2.9%) patients developed postoperative complications. Median length of postoperative stay was 2 (2–4) days. Median follow-up was 12 (7–17) months. One (1.5%) patient recurred. Median menstrual dyschezia score improved from 5.0 (2.0–8.0) to 1.0 (0.0–5.7). Median non-cyclical dyschezia significantly improved (p < 0.001) from 1.0 (0.0–5.7) to 0.0 (0.0–2.0). Median quality of life score improved from 52.5 (35.0–70.0) to 74.5 (60.0–80.0).

Conclusions
Robotic multidisciplinary approach to bowel endometriosis provides good perioperative outcomes with improvement of dyschezia and quality of life.
The first complete chloroplast genome sequences of Pistacia eurycarpa Yalt, a horticultural important rootstock and industrial tree
Authors: Karcı Harun , Kafkas Salih 
Published: February 2024

AbstractPistacia genus is botanically classified in the Sapindales order and the Anacardiaceae family, and the member of this genus P. eurycarpa is used as a rootstock for pistachio. Due to its rich oil content, various soaps are produced from the green peels of P. eurycarpa nuts and are used in the cosmetic industry as soap. In the current study, we aimed to release the complete chloroplast genome of P. eurycarpa to detect the relationship of the members of the Sapindales and also Pistacia genus. The length of the chloroplast genome of P. eurycarpa was identified 160,693 (bp) and consisted of the distinct parts of the genomic fragments such as LSC, SSC, and IR regions. The length of the LSC was 88,410 (bp), and SSC genomic range represented a total of 19,087 (bp). Inverted regions length was 26,598 (bp). A total of 125 genes were determined within the whole chloroplast genome of P. eurycarpa. The number of simple sequence repeats (SSRs) in the chloroplast genome was computed as 74. Three main clusters defined the dendrogram of all accessions. The closest pairs of species were identified among the P. eurycarpa and P. vera species. The farthest genetic relationship was calculated among the members of the Sapindales species Mangifera indica and the Fagales species Castanea mollissima. The sequences of the chloroplast genome of P. eurycarpa species can be evaluated for the construction of the basis of the complete evolution of the order, genera, and the development of the SSRs for species-specific markers for revealing the evolution of Pistacia species for future breeding research.
The Pseudo Symmetric Crystal Structure of 1,4-Diazabicyclo[2·2·2]octane-1,4-diium bis(5-hydroxy-2,4-dinitrophenolate)
Authors: Seidel Rüdiger W. , Goddard Richard , Kolev Tsonko M. 
Published: February 2024

AbstractReaction of 4,6-dinitroresorcinol (1) and the nitrogen base 1,4-diazabicyclo[2·2·2]octane (2) affords the 1:2 salt and proton-transfer compound 1,4-diazabicyclo[2·2·2]octane-1,4-diium bis(5-hydroxy-2,4-dinitrophenolate) (3). Compound 3 crystallizes in the triclinic crystal system (space group P-1) with a = 8.3242(5) Å, b = 11.9915(7) Å, c = 12.4595(7) Å, α = 116.282(2)°, β = 100.576(3)°, γ = 101.051(2)°, 1042.30(11) Å3 and Z = 2. The dication 2-$${\text{H}}_{2}^{2+}$$

H

2

2
+

forms charge assisted donating bifurcated N+−H⋅⋅⋅O− hydrogen bonds to the phenolate moieties of two monoanions of 1. The latter exhibit an intramolecular O−H⋅⋅⋅O hydrogen bond between the hydroxy group and the nitro group in ortho position. The crystal structure of 3 features pseudo B-centering of the lattice, which relates the two crystallographically distinct monoanions of 1 by a pseudo translation. The possible B-centring is broken by the ethylene groups of 2-H22+, which are related in neighbouring molecules by centres of symmetry.
Graphical Abstract