bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ensemble variational Monte Carlo for optimization of correlated excited state wave functions
Authors: Wheeler William A , Kleiner Kevin G , Wagner Lucas K 
Published: March 2024

Abstract
Variational Monte Carlo methods have recently been applied to the calculation of excited states; however, it is still an open question what objective function is most effective. A promising approach is to optimize excited states using a penalty to minimize overlap with lower eigenstates, which has the drawback that states must be computed one at a time. We derive a general framework for constructing objective functions with minima at the the lowest N eigenstates of a many-body Hamiltonian. The objective function uses a weighted average of the energies and an overlap penalty, which must satisfy several conditions. We show this objective function has a minimum at the exact eigenstates for a finite penalty, and provide a few strategies to minimize the objective function. The method is demonstrated using ab initio variational Monte Carlo to calculate the degenerate first excited state of a CO molecule.
Parametric optimization of the machining performance of Al-SiCp composite using combination of response surface methodology and desirability function
Authors: Kumar Harmesh , Wadhwa Amandeep Singh , Akhai Shalom , Kaushik Arishu 
Published: March 2024

Abstract
In this study, machining parameters such as speed, feed, and depth of cut were optimized for maximum material removal rate (MMR) of Al-SiCp composite turned with a tungsten carbide tool using response surface methodology based central composite design while keeping tool wear and surface roughness within specified limits. The influence of turning factors on flank wear and surface roughness height was investigated using regression models. ANOVA analysis is used to assess the appropriateness of the projected models and the significant factors for response optimization using the desirability method. The percentage contribution of the significant machining parameters and their interactions for optimization of the response is determined using ANOVA technique. Cutting speed is found to be the most significant factor for flank wear, average roughness height Ra and maximum roughness height Rt with contribution of 65.38%, 58.7% and 37.9% respectively for optimization of the response. Confirmation tests were carried out and the percentage error between observed and predicted value of the responses is found to be within acceptable limits, demonstrating that the created models correlates well with the experimental data. Under optimal conditions, utilizing a tungsten carbide tool can prove to be a cost-effective alternative for turning Al-SiCp composite.
The limits of concentrated power: Bureaucratic independence and electricity crises in Rwanda
Authors: Chemouni Benjamin , Dye Barnaby 
Published: March 2024

Abstract
Rwanda is a posterchild of economic success in twenty-first century Africa. Dominant explanations for the country’s growth use the political settlements framework, asserting that concentrated political power enabled long-term planning. In contrast, this article uses the case of Rwanda’s impressive boom in electricity generation to demonstrate that such concentrated power also distorts policy-making processes, creating a fiscal crisis that jeopardizes Rwanda’s economic transformation. Therefore, this article questions a central premise of the political settlements framework. Concentrated political power in Rwanda enabled rapid and ambitious construction of power plants but resulted in an oversupply crisis, plunging the sector into significant debt and raising the cost of electricity. Rwanda’s political settlement prevented experts from challenging unrealistic targets set by top politicians, which led to a headlong pursuit of electricity generation capacity. To understand this process, we assert the importance of focusing on the bureaucratic/politician relationship, which we label ‘bureaucratic independence’, rather than on the oft-used concept of ‘bureaucratic autonomy’ usually associated with the concentration of political power.
Contributing factors for career goal advancement of pharmacy learners in the Black, Indigenous, and People of Color community
Authors: Sasser Caroline W , Moss Adam , Goli Swaycha , Grego Amanda R , Knock McKenna , Morbitzer Kathryn , Mortha Sophia M , Eckel Stephen F 
Published: March 2024

Abstract

Purpose
To explore factors influencing career goals and goal attainment for pharmacy learners (eg, students, residents, fellows) who identify as part of the Black, Indigenous, and People of Color (BIPOC) community.

Methods
In late 2021 and early 2022, US-based pharmacy learners were invited to participate in two focus groups. In the first focus group, participants were asked to reflect on career goal influences, barriers, and facilitators. In the second focus group, participants were asked to provide suggestions for educational institution and healthcare organization improvement to support career goal attainment for learners in the BIPOC community. Focus group transcripts were coded using both deductive and inductive coding and thematic analysis.

Results
Fifteen learners were included in the first focus group, and 10 learners were included in the second. The most common career goal motivators were self-efficacy factors. Barriers and facilitators were often closely related. The most common barriers were financial, lack of representation, and lack of support. Common facilitators included mentorship and informal networking opportunities. Participants suggested multiple strategies for educational institutions and healthcare organizations to support BIPOC learner success, including genuine investment, representation, financial support, improved access to professional development opportunities, partnering with other professional organizations, and prioritizing diversity, equity, and inclusion (DEI) initiatives.

Conclusion
Institutions should prioritize effective, positive mentoring relationships and exposure to BIPOC professionals. Training programs and associations should consider improving financial support and lowering the cost of involvement to reduce barriers. All stakeholders should prioritize DEI in their organizational culture to promote career advancement of BIPOC learners and professionals.
Enzymatic extraction of anthocyanins from the pomace of aronia (Aronia melanocarpa)
Authors: Kim Jinman , Lee Yejin , Suh Hee-Jae , Lee Hee-Seok , Lee Chan 
Published: March 2024

Abstract
Efficient extraction of natural pigments is a key focus in enhancing the utilization of by-products for applications in the food industry. In this study, an enzymatic extraction method using Pectinex Ultra SP-L, Pectinex XXL, Novoshape, and Celluclast was used to investigate natural pigment production from the pomace of aronia, a commercially important plant. The method's performance was monitored using high-performance liquid chromatography with diode-array detection by measuring total and individual anthocyanin levels. Pectinex XXL (0.5%) yielded the highest total anthocyanin extraction (2082.41 ± 85.69 mg/100 g) in the single enzyme treatment, followed by Pectinex Ultra SP-L (0.05%), Celluclast (0.01%), and Novoshape (0.1%). Combining Pectinex XXL (0.25%) with Celluclast (0.01%) increased the extraction ratio of total anthocyanins (2 323.04 ± 61.32 mg/100 g) by ∼50.7% compared with that obtained using the solvent extraction method. This study demonstrated an effective enzymatic extraction method for application in the food industry.
Meta-DHGNN: method for CRS-related cytokines analysis in CAR-T therapy based on meta-learning directed heterogeneous graph neural network
Authors: Wei Zhenyu , Zhao Chengkui , Zhang Min , Xu Jiayu , Xu Nan , Wu Shiwei , Xin Xiaohui , Yu Lei , Feng Weixing 
Published: March 2024

Abstract
Chimeric antigen receptor T-cell (CAR-T) immunotherapy, a novel approach for treating blood cancer, is associated with the production of cytokine release syndrome (CRS), which poses significant safety concerns for patients. Currently, there is limited knowledge regarding CRS-related cytokines and the intricate relationship between cytokines and cells. Therefore, it is imperative to explore a reliable and efficient computational method to identify cytokines associated with CRS. In this study, we propose Meta-DHGNN, a directed and heterogeneous graph neural network analysis method based on meta-learning. The proposed method integrates both directed and heterogeneous algorithms, while the meta-learning module effectively addresses the issue of limited data availability. This approach enables comprehensive analysis of the cytokine network and accurate prediction of CRS-related cytokines. Firstly, to tackle the challenge posed by small datasets, a pre-training phase is conducted using the meta-learning module. Consequently, the directed algorithm constructs an adjacency matrix that accurately captures potential relationships in a more realistic manner. Ultimately, the heterogeneous algorithm employs meta-photographs and multi-head attention mechanisms to enhance the realism and accuracy of predicting cytokine information associated with positive labels. Our experimental verification on the dataset demonstrates that Meta-DHGNN achieves favorable outcomes. Furthermore, based on the predicted results, we have explored the multifaceted formation mechanism of CRS in CAR-T therapy from various perspectives and identified several cytokines, such as IFNG (IFN-γ), IFNA1, IFNB1, IFNA13, IFNA2, IFNAR1, IFNAR2, IFNGR1 and IFNGR2 that have been relatively overlooked in previous studies but potentially play pivotal roles. The significance of Meta-DHGNN lies in its ability to analyze directed and heterogeneous networks in biology effectively while also facilitating CRS risk prediction in CAR-T therapy.
Generalized reporter score-based enrichment analysis for omics data
Authors: Peng Chen , Chen Qiong , Tan Shangjin , Shen Xiaotao , Jiang Chao 
Published: March 2024

Abstract
Enrichment analysis contextualizes biological features in pathways to facilitate a systematic understanding of high-dimensional data and is widely used in biomedical research. The emerging reporter score-based analysis (RSA) method shows more promising sensitivity, as it relies on P-values instead of raw values of features. However, RSA cannot be directly applied to multi-group and longitudinal experimental designs and is often misused due to the lack of a proper tool. Here, we propose the Generalized Reporter Score-based Analysis (GRSA) method for multi-group and longitudinal omics data. A comparison with other popular enrichment analysis methods demonstrated that GRSA had increased sensitivity across multiple benchmark datasets. We applied GRSA to microbiome, transcriptome and metabolome data and discovered new biological insights in omics studies. Finally, we demonstrated the application of GRSA beyond functional enrichment using a taxonomy database. We implemented GRSA in an R package, ReporterScore, integrating with a powerful visualization module and updatable pathway databases, which is available on the Comprehensive R Archive Network (https://cran.r-project.org/web/packages/ReporterScore). We believe that the ReporterScore package will be a valuable asset for broad biomedical research fields.
ICARUS v3, a massively scalable web server for single-cell RNA-seq analysis of millions of cells
Authors: Jiang Andrew , Snell Russell G , Lehnert Klaus 
Published: March 2024

Abstract

Motivation
In recent years, improvements in throughput of single-cell RNA-seq have resulted in a significant increase in the number of cells profiled. The generation of single-cell RNA-seq datasets comprising &gt;1 million cells is becoming increasingly common, giving rise to demands for more efficient computational workflows.

Results
We present an update to our single-cell RNA-seq analysis web server application, ICARUS (available at https://launch.icarus-scrnaseq.cloud.edu.au) that allows effective analysis of large-scale single-cell RNA-seq datasets. ICARUS v3 utilizes the geometric cell sketching method to subsample cells from the overall dataset for dimensionality reduction and clustering that can be then projected to the large dataset. We then extend this functionality to select a representative subset of cells for downstream data analysis applications including differential expression analysis, gene co-expression network construction, gene regulatory network construction, trajectory analysis, cell–cell communication inference, and cell cluster associations to GWAS traits. We demonstrate analysis of single-cell RNA-seq datasets using ICARUS v3 of 1.3 million cells completed within the hour.

Availability and implementation
ICARUS is available at https://launch.icarus-scrnaseq.cloud.edu.au.
Determination of p53abn endometrial cancer: a multitask analysis using radiological-clinical nomogram on MRI
Authors: Ning Yan , Liu Wei , Wang Haijie , Zhang Feiran , Chen Xiaojun , Wang Yida , Wang Tianping , Yang Guang , Zhang He 
Published: March 2024

Abstract

Objectives
We aimed to differentiate endometrial cancer (EC) between TP53mutation (P53abn) and Non-P53abn subtypes using radiological-clinical nomogram on EC body volume MRI.

Methods
We retrospectively recruited 227 patients with pathologically proven EC from our institution. All these patients have undergone molecular pathology diagnosis based on the Cancer Genome Atlas. Clinical characteristics and histological diagnosis were recorded from the hospital information system. Radiomics features were extracted from online Pyradiomics processors. The diagnostic performance across different acquisition protocols was calculated and compared. The radiological-clinical nomogram was established to determine the nonendometrioid, high-risk, and P53abn EC group.

Results
The best MRI sequence for differentiation P53abn from the non-P53abn group was contrast-enhanced T1WI (test AUC: 0.8). The best MRI sequence both for differentiation endometrioid cancer from nonendometrioid cancer and high-risk from low- and intermediate-risk groups was apparent diffusion coefficient map (test AUC: 0.665 and 0.690). For all 3 tasks, the combined model incorporating all the best discriminative features from each sequence yielded the best performance. The combined model achieved an AUC of 0.845 in the testing cohorts for P53abn cancer identification. The MR-based radiomics diagnostic model performed better than the clinical-based model in determining P53abn EC (AUC: 0.834 vs 0.682).

Conclusion
In the present study, the diagnostic model based on the combination of both radiomics and clinical features yielded a higher performance in differentiating nonendometrioid and P53abn cancer from other EC molecular subgroups, which might help design a tailed treatment, especially for patients with high-risk EC.

Advances in knowledge
(1) The contrast-enhanced T1WI was the best MRI sequence for differentiation P53abn from the non-P53abn group (test AUC: 0.8). (2) The radiomics-based diagnostic model performed better than the clinical-based model in determining P53abn EC (AUC: 0.834 vs 0.682). (3) The proposed model derived from multi-parametric MRI images achieved a higher accuracy in P53abn EC identification (AUC: 0.845).
A model that predicts a real-time tumour surface using intra-treatment skin surface and end-of-expiration and end-of-inhalation planning CT images
Authors: Wei Ziwen , Huang Xiang , Sun Aiming , Peng Leilei , Lou Zhixia , Hu Zongtao , Wang Hongzhi , Xing Ligang , Yu Jinming , Qian Junchao 
Published: March 2024

Abstract

Objectives
To develop a mapping model between skin surface motion and internal tumour motion and deformation using end-of-exhalation (EOE) and end-of-inhalation (EOI) 3D CT images for tracking lung tumours during respiration.

Methods
Before treatment, skin and tumour surfaces were segmented and reconstructed from the EOE and the EOI 3D CT images. A non-rigid registration algorithm was used to register the EOE skin and tumour surfaces to the EOI, resulting in a displacement vector field that was then used to construct a mapping model. During treatment, the EOE skin surface was registered to the real-time, yielding a real-time skin surface displacement vector field. Using the mapping model generated, the input of a real-time skin surface can be used to calculate the real-time tumour surface. The proposed method was validated with and without simulated noise on 4D CT images from 15 patients at Léon Bérard Cancer Center and the 4D-lung dataset.

Results
The average centre position error, dice similarity coefficient (DSC), 95%-Hausdorff distance and mean distance to agreement of the tumour surfaces were 1.29 mm, 0.924, 2.76 mm, and 1.13 mm without simulated noise, respectively. With simulated noise, these values were 1.33 mm, 0.920, 2.79 mm, and 1.15 mm, respectively.

Conclusions
A patient-specific model was proposed and validated that was constructed using only EOE and EOI 3D CT images and real-time skin surface images to predict internal tumour motion and deformation during respiratory motion.

Advances in knowledge
The proposed method achieves comparable accuracy to state-of-the-art methods with fewer pre-treatment planning CT images, which holds potential for application in precise image-guided radiation therapy.
SORD-deficient rats develop a motor-predominant peripheral neuropathy unveiling novel pathophysiological insights
Authors: Rebelo Adriana P , Abad Clemer , Dohrn Maike F , Li Jian J , Tieu Ethan K , Medina Jessica , Yanick Christopher , Huang Jingyu , Zotter Brendan , Young Juan I , Saporta Mario , Scherer Steven S , Walz Katherina , Zuchner Stephan 
Published: March 2024

Abstract
Biallelic SORD mutations cause one of the most frequent forms of recessive hereditary neuropathy, estimated to affect ∼10 000 patients in North America and Europe alone. Pathogenic SORD loss-of-function changes in the encoded enzyme sorbitol dehydrogenase result in abnormally high sorbitol levels in cells and serum. How sorbitol accumulation leads to peripheral neuropathy remains to be elucidated.
A reproducible animal model for SORD neuropathy is essential to illuminate the pathogenesis of SORD deficiency and for preclinical studies of potential therapies. Therefore, we have generated a Sord knockout (KO), Sord−/−, Sprague Dawley rat, to model the human disease and to investigate the pathophysiology underlying SORD deficiency.
We have characterized the phenotype in these rats with a battery of behavioural tests as well as biochemical, physiological and comprehensive histological examinations. Sord−/− rats had remarkably increased levels of sorbitol in serum, CSF and peripheral nerve. Moreover, serum from Sord−/− rats contained significantly increased levels of neurofilament light chain, an established biomarker for axonal degeneration. Motor performance significantly declined in Sord−/− animals starting at ∼7 months of age. Gait analysis evaluated with video motion-tracking confirmed abnormal gait patterns in the hindlimbs. Motor nerve conduction velocities of the tibial nerves were slowed. Light and electron microscopy of the peripheral nervous system revealed degenerating myelinated axons, de- and remyelinated axons, and a likely pathognomonic finding—enlarged ‘ballooned’ myelin sheaths. These findings mainly affected myelinated motor axons; myelinated sensory axons were largely spared.
In summary, Sord−/− rats develop a motor-predominant neuropathy that closely resembles the human phenotype. Our studies revealed novel significant aspects of SORD deficiency, and this model will lead to an improved understanding of the pathophysiology and the therapeutic options for SORD neuropathy.
Revolutionizing Daptomycin Dosing: A Single 7–11-Hour Sample for Pragmatic Application
Authors: Angelini Jacopo , Liu Shuhan , Giuliano Simone , Flammini Sarah , Martini Luca , Tascini Carlo , Baraldo Massimo , Pai Manjunath P 
Published: March 2024

Abstract
Precision daptomycin dosing faces clinical implementation barriers despite known exposure-safety concerns with the use of twice the regulatory-approved doses. We propose achieving a single 7–11-hour post-dose plasma target concentration of 30 mg/L to 43 mg/L to be a practical starting point to facilitate precision daptomycin dosing.
Performances of acute kidney injury biomarkers vary according to sex
Authors: Faguer Stanislas , Piedrafita Alexis , Sanz Ana Belen , Siwy Justyna , Mina Ioanna K , Alves Melinda , Bousquet Paul , Marcheix Bertrand , Casemayou Audrey , Klein Julie , Minville Vincent , Breuil Benjamin , Ortiz Alberto , Schanstra Joost P 
Published: March 2024

ABSTRACT

Background
Before implementing individualized strategies to treat acute kidney injury (AKI), identifying clusters of patients with divergent pathophysiological mechanisms, diagnosis criteria or outcomes is of the utmost importance. Here we studied sex-related molecular mechanisms in cardiac bypass (CBP) surgery patients developing AKI.

Methods
We compared the characteristics of 1170 patients referred for CBP surgery using multivariate logistic regression and propensity score–based analysis. Performances of the candidate urinary biomarkers at &lt;4 h post-surgery, urinary neutrophil gelatinase-associated lipocalin (uNGAL), [IGFBP7]·[TIMP-2] product (NephroCheck) and a recently developed AKI signature of 204 urinary peptides (AKI204) to predict AKI were compared in both sexes.

Results
Incidence (∼25%) and severity of AKI were similar in men and women, even after adjustment for the usual risk factors of AKI, including baseline estimated glomerular filtration rate, age, diabetes mellitus, length of CBP and red blood cell transfusion. However, at the molecular level, performances of uNGAL, NephroCheck and AKI204 to predict AKI strongly diverged between men and women. In the full cohort, as well as in subgroups of men and women, the multimarker AKI204 signature outperformed uNGAL and NephroCheck and predicted the development of AKI significantly better in women than in men. Analysis of AKI204 at the single-peptide level suggested divergences of AKI mechanisms between sexes due to increased kidney inflammation in women (increased abundance of urinary fragments of osteopontin and uromodulin).

Conclusions
In patients referred for CBP surgery, significant clinical and biological differences between men and women as well as sexual dimorphism of AKI biomarker performances were identified. The urinary peptide signature points to sex-related molecular mechanisms underlying AKI.