bluuebunny/crossref_metadata_2025 huggingface dataset:
Body composition, exercise-related performance parameters and associated health factors of transgender women, cisgender women and cisgender men volleyball players
Authors: Alvares Leonardo Azevedo , dos Santos Quaresma Marcus VL , Nakamoto Fernanda Patti , Santos Lívia Marcela , Navarro Lucas Soglio , Navarro Giovanna Soglio , Orozco Bruno Marcos Mazoca , Sá Beatriz Meconi Cardoso , Achkar Gabriel Barasnevicius , Marques Camila Guazzelli , Barbosa Renata Cleia Claudino , Ferreira Raphael Einsfeld Simões
Published: February 2025

Objective

The inclusion of transgender athletes in competitive sports has promoted significant dialogue and controversy among exercise-related professionals. The objective of this study was to investigate body composition, exercise-related performance parameters and associated health-related factors of transgender women (TW), cisgender women (CW) and cisgender men (CM) amateur volleyball players.

Methods

This was a cross-sectional study comprising TW, CW and CM amateur volleyball players eligible with the following characteristics: ‘gender incongruent’ (for TW only); age between 18 and 35 years; body mass index (BMI) between 18.0 and 29.9 kg/m2; ‘very active’ according to the International Physical Activity Questionnaire, and engaged in regular volleyball training for at least 1 year. All participants were assessed for body composition, blood biomarkers, handgrip strength, countermovement jump height (CMJ), squat jump height (SQJ) and maximum oxygen consumption (V̇O2max).

Results

69 amateur volleyball players were initially evaluated, but only 23 met the inclusion criteria and were included in the study (7 TW, 8 CW and 8 CM). Age (p=0.07) and BMI (p=0.26) were similar between groups. Estradiol (p=0.47), total testosterone (p=1.00) and haemoglobin (p=1.00) levels did not differ between TW and CW. However, analysis not adjusted by confounding variables showed that CM presented higher testosterone levels (p<0.001), haemoglobin levels (p=0.03), lean body mass (p=0.03), handgrip strength (p<0.001), CMJ (p<0.001), SQJ (p=0.012) and V̇O2max(mL/min) (p=0.001) compared with TW. When adjusted by confounding variables, all p values were <0.05, except for SQJ (p=0.062).

Conclusion

TW athletes displayed similar exercise performance and biomarkers compared with CW but lower results compared with CM.
Three-protein signature is associated with baseline and persistently elevated or recurrent depressive symptoms in individuals with recent-onset diabetes
Authors: Spagnuolo Maria C , Gottmann Pascal , Sommer Jana , Borgmann Sandra Olivia , Strassburger Klaus , Rathmann Wolfgang , Zaharia Oana Patricia , Trenkamp Sandra , Wagner Robert , Icks Andrea , Herder Christian , Roden Michael , Maalmi Haifa
Published: February 2025

Depression is associated with diabetes, but the underlying causes remain unclear. To better understand depression in diabetes, this study investigated associations between 135 inflammatory and neurological protein biomarkers and depressive symptoms in individuals with diabetes.

This cross-sectional study included 430 adults with a known diabetes duration <1 year from the German Diabetes Study (GDS), in whom biomarkers were measured in serum and depressive symptoms were evaluated at baseline and annually over 5 years using the Center for Epidemiological Studies Depression Scale (CES-D). Based on the information on depressive symptoms from the baseline and follow-up visits (n=305, ≥3 time points), we subdivided the sample into individuals with persistent or recurrent and transient or never depressive symptoms. We assessed the associations of each biomarker with baseline CES-D score (continuous) and persistent/recurrent depressive symptoms using multiple linear and logistic regression models, respectively.

After adjustment for covariates, we identified a three-protein signature associated with baseline CES-D score and persistent/recurrent depressive symptoms. CUB domain-containing protein 1 (CDCP1) and NAD-dependent protein deacetylase sirtuin-2 (SIRT2) were positively associated with baseline (β 1.24 (95% CI 0.19 to 2.29); β 0.89 (95% CI 0.06 to 1.72)), respectively) and persistent/recurrent depressive symptoms (OR 1.58 (95% CI 1.08 to 2.31); OR 1.32 (95% CI 1.03 to 1.71), respectively), whereas leptin receptor (LEPR) was inversely associated with baseline (β −0.99 (95% CI −1.87 to –0.11)) and persistent/recurrent depressive symptoms (OR 0.70 (95% CI 0.49 to 0.99)). However, results were not significant after adjustment for multiple testing.

In conclusion, the three-protein signature identified may provide insights into mechanisms underlying depressive symptoms in diabetes and might open new therapeutic avenues.

The trial registration number of the study isNCT01055093.
Cardiac-related neonatal collapse presenting to the emergency department: a retrospective cohort study
Authors: Kuok Manson Chon In , Lambert Jennie , Janjanam Anitha , Lillie Jon
Published: February 2025

Background

To describe the characteristics of cardiac-related neonatal collapses referred to a critical care transport service and evaluate the diagnostic accuracy and management at referral and retrieval.

Methods

Retrospective cohort analysis of cardiac-related neonatal collapses who were referred to and transferred by a paediatric intensive care retrieval team based in London, UK between 2013 and 2021. Patients with antenatal diagnoses were excluded.

Results

There were 71 neonates identified of whom 49 (69%) had structural heart defect, 12 (17%) arrhythmia and 10 (14%) with cardiomyopathy/myocarditis. Among structural defects, left ventricular outflow tract (LVOT) obstruction (71%) and mixing of circulation (22%) were the predominant pathologies. Cardiac murmur was absent in 66% of the patients. The referring teams’ diagnostic performance was suboptimal for LVOT obstruction and cardiomyopathy/myocarditis, with 63% and 30% recognised as cardiac cause of collapse at referral. Less than half of neonates with duct-dependent lesions received prostaglandin at referral, which later improved to 97% during retrieval. The number of patients requiring intubation and inotropic support also increased at various time points throughout the patient journey. 98% of patients with structural defects required cardiac interventions at a median of 1 day after admission.

Conclusions

Structural heart defect, particularly LVOT obstruction, was the leading cause of cardiac-related neonatal collapses. However, a significant portion were initially misdiagnosed leading to delay in prostaglandin administration. Our findings highlight the importance of a high index of suspicion for cardiac pathologies as a cause of neonatal collapse, which is essential for appropriate treatment and timely referral.
The fifth edition of the WHO classification of mature T cell, NK cell and stroma-derived neoplasms
Authors: Attygalle Ayoma D , Karube Kennosuke , Jeon Yoon Kyung , Cheuk Wah , Bhagat Govind , Chan John K C , Naresh Kikkeri N
Published: February 2025

The fifth edition of the WHO Classification of Haematolymphoid Tumors (WHO-HAEM5) introduces significant advancements in the understanding and diagnosis of mature T cell and NK cell, and stroma-derived neoplasms, and incorporates molecular and genetic data/findings accrued over the past years. The classification has been reorganised using a hierarchical system, employed across the fifth edition of the WHO classification of tumours of all organ systems. This review highlights recent developments, evolving concepts, and key updates since the revised fourth edition (WHO-HAEM4R). It enumerates the minimal/essential criteria necessary for diagnosis and classification, constituting not only the importance of clonality analysis in the workup of certain T cell neoplasms and the detection of infectious agents and specific genetic alterations in a subset of entities but also the applicability of these criteria in resource-constrained settings. ‘Stroma-derived neoplasms of lymphoid tissues discussed in this review is a new category introduced in HAEM5 that encompasses mesenchymal tumours occurring exclusively in lymph nodes and spleen and mesenchymal dendritic cell neoplasms previously classified as ‘histiocytic/dendritic cell neoplasms’.
Early oral feeding post gastrectomy in gastric cancer: quasi-experimental study
Authors: He Haiyan , Ma Yuanyuan , Liu Guo , Liu Shuying , Liu Qin , Yao Juan , Huang Chengcheng , Liu Jie , Zhou Liang , Wang Ting , Wang Teng , Wang Na , Deng Xiaolian , Wang Yaling
Published: February 2025

Objective

This study aims to investigate the safety and feasibility of early oral feeding in patients with gastric cancer after gastrectomy.

Methods

A total of 135 patients with gastric cancer who would receive gastrectomy were enrolled in the study, with 61 in early oral feeding group and 74 in control group. Outcomes included nutrient intake, nutritional status, gastrointestinal functions and symptoms, pain, physical activity time, clinical outcomes and inflammation markers.

Results

In comparison with control group, patients in early oral feeding group had significantly higher compliance rates of oral energy and protein intake, lower needs of parenteral nutrition and shorter postoperative oral feeding start time during hospitalisation. Moreover, the compliance rate of oral protein intake at 1 week after discharge was higher in patients with gastric cancer of early oral feeding group compared with control group. The gastrointestinal function was better in early oral feeding group, evidenced by shorter time to the first flatus and dwell time for gastric tube.

Conclusion

This study demonstrated that early oral feeding is safe and can significantly improve oral energy and oral protein intake and gastrointestinal functions during hospitalisation in patients with gastric cancer who received gastrectomy, as well as the oral protein intake after discharge.

Trial registration

Chinese Clinical Trial Registry: ChiCTR2300069202.
Analysis of Dynamic Capture Mechanism for News Feature Words in Embedded Networks
Authors: Xu Qin , Xu Feng
Published: February 2025

With the deep integration of embedded network technology and data analysis technology, the content analysis and dissemination optimization of platform media have ushered in unprecedented technological innovations. The traditional information dissemination model often relies on manually designed feature extraction methods, such as keyword-based matching, TF-IDF and other statistical methods. These methods are limited in efficiency and accuracy when dealing with large-scale, high-dimensional data. Embedded network technology can automatically extract high-level and abstract features from raw text data, significantly improving the accuracy and efficiency of feature extraction. In this context, based on the essence of embedded networks, this paper innovatively integrates and reconstructs the core elements of traditional information dissemination models, and successfully constructs a new knowledge graph model of the current situation of news dissemination. This model fully utilizes the powerful advantages of embedded networks in feature extraction and learning capabilities. It can not only accurately depict the complex dynamic changes that occur over time in news events, but also deeply reveal the potential mechanisms and laws of news dissemination. In the experimental verification phase, the model demonstrated excellent performance. Especially in identifying sudden news feature words, the average recall rate, accuracy and F-score of the model reached about 45%, 35% and 40%, respectively. This result not only indicates a significant improvement in the accuracy of the model in feature word detection, but also fully validates the enormous potential of embedded networks in the field of news communication analysis.
The Impact of Synergistic Effects Combined With the Progress of IOT Integration on Promoting High-Quality Economic Development
Authors: Sun Lulu
Published: February 2025

The application of IoT technology not only brings abundant data resources and intelligent management tools to higher education institutions, but also promotes innovation in academic research and efficient dissemination of knowledge. When the expansion of higher education scale is combined with IoT-based structural optimization, its driving effect on economic growth is significantly enhanced. On the one hand, the expansion of scale provides a vast experimental field and infinite possibilities for IoT-based structural optimization. On the other hand, the structural optimization driven by the Internet of Things ensures the accuracy and efficiency of scale expansion, effectively avoiding resource waste and low efficiency caused by blind expansion. This paper constructs a dynamic collaborative model between higher education and economic development in the context of IoT integration, and uses econometric methods to analyze in depth the specific impact of the expansion of higher education scale, IoT-driven structural optimization, and their synergistic effects on economic growth. The model results show that the expansion of higher education scale has a significant positive effect on economic growth with the help of IoT integration, and IoT-driven structural optimization has also become an important driving force for economic growth. It is particularly important that when these two work together, their driving effect on economic growth shows a clear nonlinear growth trend, further highlighting the key role of synergy and IoT integration in promoting high-quality economic development.
A Financial Risk Prediction Method Based on Conditional Random Fields
Authors: Xie Guishan
Published: February 2025

Given the volatility and complexity of financial markets, accurate risk prediction is paramount for effective risk management. Traditional methods like Support Vector Machines (SVM) and Back Propagation Neural Networks (BPNNs) have shown limitations, particularly in capturing the dependencies in sequential data inherent to financial time series. This paper proposes a novel approach to financial risk prediction using Conditional Random Fields (CRFs), leveraging their potential in sequence data modeling to address these challenges. We first elaborate on the construction of a comprehensive feature set, incorporating market data, macroeconomic indicators, and sentiment analysis from financial news, tailored to enhance the predictive power of the CRFs model. The model itself is customized with carefully designed state and observation sequences, along with feature functions specifically engineered for financial risk prediction. Experiments conducted across multiple financial datasets demonstrate the superiority of our CRF-based model over traditional and machine learning benchmarks in terms of accuracy and stability. Our findings not only contribute to the literature by filling the gap left by traditional financial risk prediction methods but also offer a robust tool for practitioners in financial risk management. This work exemplifies the potential of applying advanced sequence modeling techniques to financial risk prediction, setting a new benchmark for future research in the field.
Multitask Learning-Based Facial Landmark Detection via Signal Processing: Eliminating Artificial Auxiliary Labeling for Autonomous Driving
Authors: Dai Songyin , Zhang Chaoran , Xu Cheng , Pan WeiGuo
Published: February 2025

This study introduces a novel facial landmark detection framework that leverages signal processing techniques to eliminate the dependency on artificial auxiliary labeling. Built upon multi-task learning, the proposed method constructs auxiliary information directly from labeled facial landmarks, including inter-landmark connection distances and facial triangle angle features. By incorporating multi-task collaborative optimization, the method enforces explicit constraints on global face shape and enhances feature representation, significantly improving detection accuracy. A tailored joint loss function integrates geometric features and addresses data distribution imbalance, ensuring robust penalty for rare samples while further constraining global face geometry. Experimental evaluations on benchmark datasets, including 300W and AFLW, demonstrate that the proposed approach outperforms the existing state-of-the-art methods in terms of accuracy and reliability. Moreover, our study reveals that efficient facial landmark detection can be achieved without artificial auxiliary annotation information through a multi-task learning framework. These results establish the efficacy of the method for practical applications, such as autonomous driving systems.
Analysis of Shared Office Space using Internet of Things Technology in the Age of Artificial Intelligence
Authors: Chun Hyunjin
Published: February 2025

In the era of the 4th Industrial Revolution, the concept of ownership is decreasing and the concept of sharing is increasing. Therefore, the concepts of sharing economy are being used in various ways around the world. A sharing economy refers to an economic system in which products and services are shared and used by several people. A representative business model using a sharing economy is a sharing office. Therefore, in this study, the spatial composition of the shared office was analyzed based on the example of the globally expanding shared office. Based on the analyzed data, I would like to present an appropriate method of designing and operating a shared office. The research method of this study first conducted the literature study to analyze the characteristics and utility of the shared office. After conducting these literature studies, the researcher visited a shared office company and conducted a participant observation method. The participant observation method was based on James Spradley’s theory. The subjects of this study are WeWork in the United States and Fastfive in Korea, which are famous for shared offices.The reason for selecting these two companies is that they are representatively successful shared office companies. This study conducted in-depth interviews with people using shared offices and operators of shared offices. Based on the research results, I would like to present the future development direction of the shared office. These research results can be used as theoretical basic data when designing a shared office.
The Application of Machine Intelligence and Smart Systems in Sustainable Agriculture
Authors: Ren Xiaoqi , Wang Yunjing , Qin Peng
Published: February 2025

Against the backdrop of increasing research on the optimization and application of intelligent technology, this study reviews the relevant literature from the perspectives of machine intelligence and intelligent systems, aiming to offer new research ideas for achieving sustainable agricultural development. By analyzing 1,611 Chinese and foreign literatures from 2000 to the present, we have found that research in the field of machine intelligence and intelligent systems has experienced a three-stage development pattern of fluctuating upward, explosive growth, and slowing down through adjustment, reaching a peak in 2022. China, India, and the United States are the main countries conducting research in this field. Although cooperation among countries is frequent, collaboration between authors is less common, and academic connections are relatively weak. Currently, the field of intelligent systems is moving toward diversified development. Researchers can further enhance studies in the interdisciplinary areas of intelligent technology, laying the foundation for the application of intelligent systems and machine intelligence in sustainable agriculture.
Human Motion Pose Rapid Tracking Using Improved Deep Reinforcement Learning and Multimodal Fusion
Authors: Li Zhipeng , Yang Zengbao , Yang Ruizhu , Wang Nan , Song Wenli , Zhang Xingfu
Published: February 2025

Rapid human motion pose tracking has extensive applications in fields such as motion capture, intelligent monitoring, sports training, and physical health management. It can provide accurate data support, enhance safety monitoring, optimize training outcomes, and promote physical health. Traditional human pose tracking methods predominantly rely on either sensors or images for tracking, which often results in issues like low tracking accuracy and slow tracking speed. To address these problems, a rapid human motion pose tracking method based on improved deep reinforcement learning and multimodal fusion is proposed. First, this paper designs an overall architecture for rapid human motion pose tracking and utilizes a combination of monocular vision and sensors to extract and collect human motion data. Second, it constructs a complementary filter-based multimodal data fusion method to merge the multimodal data and extract the fused features. Finally, a multi-level attention network is employed to enhance the deep reinforcement learning network, using the fused features as input for training to achieve rapid human motion pose tracking. The results show that the proposed method can achieve efficient and stable human motion pose tracking in complex scenes, with a tracking accuracy of up to 85% and a shortest tracking time of 72[Formula: see text]ms, which has practical application value.
Atomistic modelling of the thermo-mechanical behaviour of GDZ/YSZ interphase region in bilayer thermal barrier coatings
Authors: Wu Tongyu , Shang Ruiqi , Kundalwal S. I. , Meguid S. A.
Published: February 2025

Current gas turbine engines use Yttria-Stabilized Zirconia (YSZ) as the top coat for heat shielding in HP turbines as well as combustors. Unfortunately, YSZ suffers from many drawbacks once the temperature reaches [Formula: see text]. This limits the long-term application temperature of YSZ, and a few top coat replacements have been suggested and examined. In our study, we make two major changes to the top coat. The first is to use Gadolinium Zirconate (Gd2Zr2O7 or GDZ) which enjoys better thermal properties. The second is to combine it with YSZ in a bilayer configuration, thus, making use of the combined beneficial effects of thermal shielding and mechanical strength of these top coats. In spite of the fact that GDZ/YSZ has been suggested by other authors, no work has been devoted to study the role played by the GDZ–YSZ interphase region, possible interdiffusion, its thermal properties and interphase region strength. In this study, we developed comprehensive atomistic models of the GDZ/YSZ interface using molecular dynamics (MD) with emphasis on thermo-mechanical properties of the GDZ/YSZ interphase region. This allowed us to examine the evolution of the GDZ/YSZ interphase region and compute the interface bond strength with temperature.
PRO-MTL : Parameterized Route Optimization using Multi-Task Learning
Authors: Vyas Jayant , Budhwani Jayesh , Das Debasis
Published: February 2025

In the current ridesharing scenario, finding a compatible passenger is highly challenging and largely dependent on chance. Existing algorithms prioritize the shortest route without considering future requests or traffic conditions, which reduces the likelihood of matching with another compatible passenger. This uncertainty leads to increased congestion along shortest routes and fewer ridesharing trips overall. This paper proposes a route recommendation strategy that goes beyond the shortest route, aiming to address these issues. The proposed strategy results in higher demand, reduced congestion, broader coverage of points of interests, and an increased probability of finding compatible passengers during a trip. To achieve this, we introduce a time-series forecasting method leveraging a multi-task long short-term memory model to predict demand and traffic patterns in city-zone neighborhoods. These predictions are then used to recommend optimized routes. To evaluate our approach, we tested it on three datasets containing trip and traffic details from New York City, Los Angeles, and Shenzhen. Our model demonstrated 96% accuracy and a 2% RMSE loss in predicting the expected number of passengers. Furthermore, during route recommendations, we observed a 23% increase in passenger count for 97% of trips and a reduction in travel time for the shortest path in 60% of trips. In light of the above experimentation, we believe that while our approach recommends a longer route than the shortest one (for 40% cases), it helps taxi drivers to find compatible passengers on most trips which increases the profit of ridesharing services, and reduces the waiting time for passengers.
Efficiency and Performance Optimization in Large Language Models through IB Fine-Tuning
Authors: Jo Ashly Ann , Raj Ebin Deni , Sahoo Jayakrushna
Published: February 2025

In the rapidly evolving field of Natural Language Processing (NLP), optimizing methods for fine-tuning Large Language Models (LLMs) is increasingly critical for improving generalization and performance. Fine-tuning LLMs is challenging due to high costs, overfitting, and difficulty adapting to diverse tasks. These challenges grow as LLMs scale, making traditional fine-tuning methods inefficient and expensive. To address these issues, a novel Information Bottleneck (IB) method for fine-tuning LLMs is proposed, focusing on retaining only the most critical and relevant information in the model’s internal representations. By striking a balance between information compression and predictive relevance, the IB method aims to reduce overfitting and enhance generalization. This approach also integrates reinforcement learning and continual learning to enhance LLM performance further. The proposed framework considers two key metrics: (1) compression effectiveness, which reduces redundancy and improves generalization, and (2) predictive relevance, which ensures high task-specific performance. The proposed scheme achieves scalable fine-tuning across diverse NLP tasks using a lightweight proxy model to enhance computational efficiency. The proposed framework empirical evaluations and ablation studies show that the IB method improves accuracy while significantly reducing computational costs, enabling efficient, interpretable, and adaptable LLM optimization and increasing convergence.
Integrated Analysis of Morphological Alterations, Antioxidant Capacity, and Metabolomic Profiles in Daylily Flower Buds During Storage
Authors: Lv Hongrui , He Yongji , Xu Lina , Guo Shang
Published: February 2025

Daylily flower buds are edible and medical homologous with health care functions and pharmaceutical values. However, they are about to open and deteriorate after harvest, owing to ripening and senescence. To obtain a theoretical reference for understanding the postharvest senescence mechanisms of daylily flower buds, the dynamic quality characteristics of daylily flower buds were explored by physiology, biochemistry, and widely targeted metabolomics. During the whole storage process, texture, total flavonoid contents, and antioxidant activities indicated by DPPH, ABTS, and FRAP assays appeared in declining trends. Based on widely targeted metabolomics, 518, 443, and 507 differentially accumulated metabolites (DAMs) were screened in the initial storage period (CK0 vs. CK2), mid‐storage period (CK2 vs. CK4), and the end of storage (CK4 vs. CK6), respectively. A total of 224 common DAMs in CK0 vs. CK2, CK2 vs. CK4, and CK4 vs. CK6 were closely related to the ripening and senescence of daylily. A special focus was given to the interplay between the marker flavonoids and antioxidant activities. 11 flavonoid compounds showed positive correlation with the results of antioxidant capacity, including pelargonidin 3−O−beta−D−glucoside 5−O−(6−coumaroyl−beta−D−glucoside), typhaneoside, 5‴−O−feruloyl complanatoside B, 7−neohesperidosides, taxifolin, rutin (trihydrate), rutin (hydrate), rutin (hydrate), 3,5,7,3′,4′−pentahydroxyflavylium−3−O−beta−D−xylopyranosyl−(1−2)−beta−D−glucopyranoside, kuromanin (chloride), and neoeriocitrin, which have the potential to be biomarkers for antioxidant capacity and daylily quality. The study innovatively served as a valuable guide for the senescence progress and suggested potential markers for the quality characteristics of daylily flower buds.
Comparative Study of Pectin and Kappa‐Carrageenan‐Based Films Loaded With Boswellic Acid and Acetyl‐11‐Keto‐Beta‐Boswellic Acid for Active Packaging
Authors: Shah Yasir Abbas , Bhatia Saurabh , Al-Harrasi Ahmed , Tarahi Mohammad , Khan Talha Shireen , Alam Tanveer , Koca Esra , Aydemir Levent Yurdaer
Published: February 2025

Active packaging is crucial for extending shelf life, maintaining food quality, and reducing reliance on synthetic preservatives by preventing spoilage, oxidation, and microbial contamination. In this study, boswellic acid (BA) and acetyl‐11‐keto‐beta‐boswellic acid (AKBA) were isolated from the oleo‐gum resin of Boswellia sacra and incorporated into the pectin and kappa‐carrageenan‐based films for active packaging. The fabricated films were analyzed to examine the effect of these active compounds on the mechanical, optical, barrier, chemical, structural, hydrophobic, and antioxidant properties. The incorporation of AKBA and BA into the films resulted in a decrease in transparency and tensile strength; however, the elongation at break did not show any significant variations. The film samples exhibited improved antioxidant properties as confirmed by DPPH and ABTS free radical scavenging activities. The ΔE value represented the overall color difference in AKBA‐ and BA‐loaded films as compared with the blank film sample. The FTIR spectrum of AKBA‐ and BA‐loaded films exhibited shifts and intensity changes, suggesting the intermolecular interaction within the film matrix. Moreover, the water contact angle measurements revealed that the films containing AKBA showed a noticeable increase in contact angles, reflecting an enhancement in hydrophobicity. The current study offers a valuable approach for developing active packaging films with potential applications in food packaging.
Table S9 from Clinical Efficacy of ONC201 in H3K27M-Mutant Diffuse Midline Gliomas Is Driven by Disruption of Integrated Metabolic and Epigenetic Pathways
Authors: Venneti Sriram , Kawakibi Abed Rahman , Ji Sunjong , Waszak Sebastian M. , Sweha Stefan R. , Mota Mateus , Pun Matthew , Deogharkar Akash , Chung Chan , Tarapore Rohinton S. , Ramage Samuel , Chi Andrew , Wen Patrick Y. , Arrillaga-Romany Isabel , Batchelor Tracy T. , Butowski Nicholas A. , Sumrall Ashley , Shonka Nicole , Harrison Rebecca A. , de Groot John , Mehta Minesh , Hall Matthew D. , Daghistani Doured , Cloughesy Timothy F. , Ellingson Benjamin M. , Beccaria Kevin , Varlet Pascale , Kim Michelle M. , Umemura Yoshie , Garton Hugh , Franson Andrea , Schwartz Jonathan , Jain Rajan , Kachman Maureen , Baum Heidi , Burant Charles F. , Mottl Sophie L. , Cartaxo Rodrigo T. , John Vishal , Messinger Dana , Qin Tingting , Peterson Erik , Sajjakulnukit Peter , Ravi Karthik , Waugh Alyssa , Walling Dustin , Ding Yujie , Xia Ziyun , Schwendeman Anna , Hawes Debra , Yang Fusheng , Judkins Alexander R. , Wahl Daniel , Lyssiotis Costas A. , de la Nava Daniel , Alonso Marta M. , Eze Augustine , Spitzer Jasper , Schmidt Susanne V. , Duchatel Ryan J. , Dun Matthew D. , Cain Jason E. , Jiang Li , Stopka Sylwia A. , Baquer Gerard , Regan Michael S. , Filbin Mariella G. , Agar Nathalie Y.R. , Zhao Lili , Kumar-Sinha Chandan , Mody Rajen , Chinnaiyan Arul , Kurokawa Ryo , Pratt Drew , Yadav Viveka N. , Grill Jacques , Kline Cassie , Mueller Sabine , Resnick Adam , Nazarian Javad , Allen Joshua E. , Odia Yazmin , Gardner Sharon L. , Koschmann Carl
Published: February 2025

Upregulated and downregulated genes in DIPG007 cells treated with ONC201 versus vehicle.
Table S12 from Clinical Efficacy of ONC201 in H3K27M-Mutant Diffuse Midline Gliomas Is Driven by Disruption of Integrated Metabolic and Epigenetic Pathways
Authors: Venneti Sriram , Kawakibi Abed Rahman , Ji Sunjong , Waszak Sebastian M. , Sweha Stefan R. , Mota Mateus , Pun Matthew , Deogharkar Akash , Chung Chan , Tarapore Rohinton S. , Ramage Samuel , Chi Andrew , Wen Patrick Y. , Arrillaga-Romany Isabel , Batchelor Tracy T. , Butowski Nicholas A. , Sumrall Ashley , Shonka Nicole , Harrison Rebecca A. , de Groot John , Mehta Minesh , Hall Matthew D. , Daghistani Doured , Cloughesy Timothy F. , Ellingson Benjamin M. , Beccaria Kevin , Varlet Pascale , Kim Michelle M. , Umemura Yoshie , Garton Hugh , Franson Andrea , Schwartz Jonathan , Jain Rajan , Kachman Maureen , Baum Heidi , Burant Charles F. , Mottl Sophie L. , Cartaxo Rodrigo T. , John Vishal , Messinger Dana , Qin Tingting , Peterson Erik , Sajjakulnukit Peter , Ravi Karthik , Waugh Alyssa , Walling Dustin , Ding Yujie , Xia Ziyun , Schwendeman Anna , Hawes Debra , Yang Fusheng , Judkins Alexander R. , Wahl Daniel , Lyssiotis Costas A. , de la Nava Daniel , Alonso Marta M. , Eze Augustine , Spitzer Jasper , Schmidt Susanne V. , Duchatel Ryan J. , Dun Matthew D. , Cain Jason E. , Jiang Li , Stopka Sylwia A. , Baquer Gerard , Regan Michael S. , Filbin Mariella G. , Agar Nathalie Y.R. , Zhao Lili , Kumar-Sinha Chandan , Mody Rajen , Chinnaiyan Arul , Kurokawa Ryo , Pratt Drew , Yadav Viveka N. , Grill Jacques , Kline Cassie , Mueller Sabine , Resnick Adam , Nazarian Javad , Allen Joshua E. , Odia Yazmin , Gardner Sharon L. , Koschmann Carl
Published: February 2025

Results of pathway impact analysis after performing integrated RNA-seq and metabolomics analysis using MetaboAnalyst.
Table S1 from Clinical Efficacy of ONC201 in H3K27M-Mutant Diffuse Midline Gliomas Is Driven by Disruption of Integrated Metabolic and Epigenetic Pathways
Authors: Venneti Sriram , Kawakibi Abed Rahman , Ji Sunjong , Waszak Sebastian M. , Sweha Stefan R. , Mota Mateus , Pun Matthew , Deogharkar Akash , Chung Chan , Tarapore Rohinton S. , Ramage Samuel , Chi Andrew , Wen Patrick Y. , Arrillaga-Romany Isabel , Batchelor Tracy T. , Butowski Nicholas A. , Sumrall Ashley , Shonka Nicole , Harrison Rebecca A. , de Groot John , Mehta Minesh , Hall Matthew D. , Daghistani Doured , Cloughesy Timothy F. , Ellingson Benjamin M. , Beccaria Kevin , Varlet Pascale , Kim Michelle M. , Umemura Yoshie , Garton Hugh , Franson Andrea , Schwartz Jonathan , Jain Rajan , Kachman Maureen , Baum Heidi , Burant Charles F. , Mottl Sophie L. , Cartaxo Rodrigo T. , John Vishal , Messinger Dana , Qin Tingting , Peterson Erik , Sajjakulnukit Peter , Ravi Karthik , Waugh Alyssa , Walling Dustin , Ding Yujie , Xia Ziyun , Schwendeman Anna , Hawes Debra , Yang Fusheng , Judkins Alexander R. , Wahl Daniel , Lyssiotis Costas A. , de la Nava Daniel , Alonso Marta M. , Eze Augustine , Spitzer Jasper , Schmidt Susanne V. , Duchatel Ryan J. , Dun Matthew D. , Cain Jason E. , Jiang Li , Stopka Sylwia A. , Baquer Gerard , Regan Michael S. , Filbin Mariella G. , Agar Nathalie Y.R. , Zhao Lili , Kumar-Sinha Chandan , Mody Rajen , Chinnaiyan Arul , Kurokawa Ryo , Pratt Drew , Yadav Viveka N. , Grill Jacques , Kline Cassie , Mueller Sabine , Resnick Adam , Nazarian Javad , Allen Joshua E. , Odia Yazmin , Gardner Sharon L. , Koschmann Carl
Published: February 2025

Baseline characteristics of ONC201-treated H3K27M-DMG patients included in analysis.
Supplementary Data S2 from Clinical Efficacy of ONC201 in H3K27M-Mutant Diffuse Midline Gliomas Is Driven by Disruption of Integrated Metabolic and Epigenetic Pathways
Authors: Venneti Sriram , Kawakibi Abed Rahman , Ji Sunjong , Waszak Sebastian M. , Sweha Stefan R. , Mota Mateus , Pun Matthew , Deogharkar Akash , Chung Chan , Tarapore Rohinton S. , Ramage Samuel , Chi Andrew , Wen Patrick Y. , Arrillaga-Romany Isabel , Batchelor Tracy T. , Butowski Nicholas A. , Sumrall Ashley , Shonka Nicole , Harrison Rebecca A. , de Groot John , Mehta Minesh , Hall Matthew D. , Daghistani Doured , Cloughesy Timothy F. , Ellingson Benjamin M. , Beccaria Kevin , Varlet Pascale , Kim Michelle M. , Umemura Yoshie , Garton Hugh , Franson Andrea , Schwartz Jonathan , Jain Rajan , Kachman Maureen , Baum Heidi , Burant Charles F. , Mottl Sophie L. , Cartaxo Rodrigo T. , John Vishal , Messinger Dana , Qin Tingting , Peterson Erik , Sajjakulnukit Peter , Ravi Karthik , Waugh Alyssa , Walling Dustin , Ding Yujie , Xia Ziyun , Schwendeman Anna , Hawes Debra , Yang Fusheng , Judkins Alexander R. , Wahl Daniel , Lyssiotis Costas A. , de la Nava Daniel , Alonso Marta M. , Eze Augustine , Spitzer Jasper , Schmidt Susanne V. , Duchatel Ryan J. , Dun Matthew D. , Cain Jason E. , Jiang Li , Stopka Sylwia A. , Baquer Gerard , Regan Michael S. , Filbin Mariella G. , Agar Nathalie Y.R. , Zhao Lili , Kumar-Sinha Chandan , Mody Rajen , Chinnaiyan Arul , Kurokawa Ryo , Pratt Drew , Yadav Viveka N. , Grill Jacques , Kline Cassie , Mueller Sabine , Resnick Adam , Nazarian Javad , Allen Joshua E. , Odia Yazmin , Gardner Sharon L. , Koschmann Carl
Published: February 2025

Protocol for NCT03134131, ONC201-018: Expanded Access to ONC201 for Patients with H3K27M-mutant and/or Midline High Grade Gliomas.
Supplementary Data S1 from Clinical Efficacy of ONC201 in H3K27M-Mutant Diffuse Midline Gliomas Is Driven by Disruption of Integrated Metabolic and Epigenetic Pathways
Authors: Venneti Sriram , Kawakibi Abed Rahman , Ji Sunjong , Waszak Sebastian M. , Sweha Stefan R. , Mota Mateus , Pun Matthew , Deogharkar Akash , Chung Chan , Tarapore Rohinton S. , Ramage Samuel , Chi Andrew , Wen Patrick Y. , Arrillaga-Romany Isabel , Batchelor Tracy T. , Butowski Nicholas A. , Sumrall Ashley , Shonka Nicole , Harrison Rebecca A. , de Groot John , Mehta Minesh , Hall Matthew D. , Daghistani Doured , Cloughesy Timothy F. , Ellingson Benjamin M. , Beccaria Kevin , Varlet Pascale , Kim Michelle M. , Umemura Yoshie , Garton Hugh , Franson Andrea , Schwartz Jonathan , Jain Rajan , Kachman Maureen , Baum Heidi , Burant Charles F. , Mottl Sophie L. , Cartaxo Rodrigo T. , John Vishal , Messinger Dana , Qin Tingting , Peterson Erik , Sajjakulnukit Peter , Ravi Karthik , Waugh Alyssa , Walling Dustin , Ding Yujie , Xia Ziyun , Schwendeman Anna , Hawes Debra , Yang Fusheng , Judkins Alexander R. , Wahl Daniel , Lyssiotis Costas A. , de la Nava Daniel , Alonso Marta M. , Eze Augustine , Spitzer Jasper , Schmidt Susanne V. , Duchatel Ryan J. , Dun Matthew D. , Cain Jason E. , Jiang Li , Stopka Sylwia A. , Baquer Gerard , Regan Michael S. , Filbin Mariella G. , Agar Nathalie Y.R. , Zhao Lili , Kumar-Sinha Chandan , Mody Rajen , Chinnaiyan Arul , Kurokawa Ryo , Pratt Drew , Yadav Viveka N. , Grill Jacques , Kline Cassie , Mueller Sabine , Resnick Adam , Nazarian Javad , Allen Joshua E. , Odia Yazmin , Gardner Sharon L. , Koschmann Carl
Published: February 2025

Protocol for NCT03416530, ONC201-014: ONC201 in Newly Diagnosed Diffuse Intrinsic Pontine Glioma and Recurrent/Refractory Pediatric H3K27M Gliomas.
Impact of Healthcare Provider Awareness and Guidance on the Medical Cannabis Experience
Authors: Clobes Thomas A. , Mee Marshall M. , Jimenez Jenna M. , Maldonado Jesus , Song Joshua R.
Published: February 2025

Introduction: Cannabis as a therapeutic agent is accessible to a growing number of people, though research suggests that many medical cannabis (MC) users undertake their cannabinoid therapy independently, without collaborating with a cannabis clinician or informing their primary care physician (PCP). The effects of medical collaboration or disclosure to PCP on outcomes of cannabinoid therapy is unknown. Researchers anticipate that those who collaborate with a cannabis clinician or disclose their medical cannabis use to their PCP will find MC to be more effective, will use less delta-9-tetrahydrocannabinol (THC) and more cannabidiol (CBD), and experience fewer side effects. Methods: Through an online survey, medical cannabis users reported their cannabis usage patterns, health outcomes, PCP awareness, and collaboration with cannabis clinicians. These responses were analyzed using a variety of statistical tests to search for differences in reported efficacy, specific cannabinoid, and side effects between different levels of medical professional involvement (n=988). Results: Patients who either worked with a cannabis clinician or reported their use to their PCP reported significantly higher efficacy (p < .001), and in the case of working specifically with a cannabis clinician, higher daily doses of cannabidiol were used (p < .001). CBD doses did not vary between those who had disclosed their MC use to their PCP and those who had not. There were no significant differences in THC doses or side effects identified between groups. Conclusion: The results indicated that undertaking cannabinoid therapy with PCP awareness or guidance from a cannabis clinician is associated with better outcomes.
Efficacy of functional connectome fingerprinting using tangent-space brain networks
Authors: Curic Davor , Kalasapura Venugopal Krishna Sudhanva , Davidsen Jörn
Published: February 2025

Functional connectomes (FCs) are estimations of brain region interaction derived from brain activity, often obtained from functional Magnetic Resonance Imaging recordings. Quantifying the distance between FCs is important for understanding the relation between behavior, disorders, disease, and changes in connectivity. Recently, tangent space projections, which account for the curvature of the mathematical space of FCs, have been proposed for calculating FC distances. We compare the efficacy of this approach in the context of subject identification using the Midnight Scan Club dataset, which contains repeated long session scans in both rest and task based settings. The tangent space method is found to out-perform the traditional non-tangent space method for both whole-brain data and data from individual resting state subnetworks. Certain sets of subnetworks are found to outperform others, a dichotomy which largely follows the `control' and `processing' categorization of resting state networks. Subject discriminability is also modulated by tasks, though certain subnetworks appear task independent. The uniquely long recordings of the dataset also allow for explorations of resource requirements for effective subject identification. The tangent space method is found to universally require less data, making it well suited when only short recordings are available.
Multiplex connectomics reveal altered networks in frontotemporal dementia: A multisite study
Authors: Khokhar Sunil Kumar , Kumar Manoj , Arshad Faheem , Goyal Sheetal , Tiwari Megha , Thanissery Nithin , Ramakrishnan Subasree , Nagaraj Chandana , Kashyap Rajan , Mangalore Sandhya , Gandhi Tapan K. , Alladi Suvarna , Bharath Rose Dawn ,   for the frontotemporal lobar degeneration neuroimaging initiative
Published: February 2025

A network neuroscience perspective can significantly advance the understanding of neurodegenerative disorders, particularly frontotemporal dementia (FTD). This study employed an innovative multiplex connectomics approach, integrating cortical thickness (CTH) and fluorodeoxyglucose-positron emission tomography (FDG-PET) in a dual-layer model to investigate network alterations in FTD subtypes across two geographically distinct sites. The cohort included groups of behavioural variant FTD (bvFTD), primary progressive aphasia (PPA), mild cognitive impairment (MCI), and cognitively normal (CN) individuals who were analyzed from two separate sites. Site-1 included 28-bvFTD, 20-PPA, and 27-MCI participants, whereas Site-2 included 26-bvFTD, 43-PPA, and 43-CN individuals, respectively. Utilizing CTH and FDG-PET data after standard preprocessing, a multiplex network pipeline in BRAPH2 toolbox was used to derive multiplex participation coefficient (MPC) between the groups. The analysis revealed an increase in global MPC as an indicator of disease in PPA at both sites. Additionally, nodal MPC alterations in the anterior cingulate, frontal, and temporal lobes in PPA when compared to bvFTD. Comparisons with the CN showed that nodal MPC alterations were more extensive in PPA when compared with bvFTD. These findings underscore the potential utility of multiplex connectomes for identifying network disruptions in neurodegenerative disorders, offering promising implications for future research and clinical applications.
A Cornerstone for Building a New World
Authors: Tannoury-Karam Sana
Published: February 2025

For a generation of Arab leftist intellectuals active during the interwar years, particularly during World War Two, the Soviet Union represented a ‘miraculous’ case of modernization, a success story of a country that managed to rapidly modernize and even exceed the levels of progress and sophistication of Western nations. Its trajectory since 1917 represented a model for progress achieved through socialism and internationalism. Standing firmly against Western colonialism and steadily against the Nazi war machine, the Soviet Union became the model for a modern Arab future. The Soviet Union as ‘future’ was not only a temporal construct as much as it was a spatial framework through which Arab intellectuals shifted modernization discourses of the Nahda from West-East dimensions to East-East imaginaries.
The Atomic Future
Authors: Taha Hebatalla , Olsen Pelle Valentin
Published: February 2025

In 1946, one year after the atomic bombings of Japan, Palestinian thinker ʿAli Rashid Shaʿath (1908–1967) published a book entitled Min al-binsilin ila al-qunbula al-zarriya (From Penicillin to the Atomic Bomb). An accessible work of popular science, it contains highly optimistic reflections on the future and predicts the following two events as a result of nuclear technology and energy: a workers’ utopia and world peace. This article situates Shaʿath’s voice within a global conversation about the atomic age, which led to new forms of futuristic and utopian thinking. Analyzing broader Arab articulations of the future through Shaʿath’s writing, we critically engage his embrace of atomic technology as a mode of emancipation.
Collecting Traces, Documenting Past and Present
Authors: Dakhli Leyla
Published: February 2025

One of the ways this political dream of the recent Arab Revolutions had been re-actualized is through building archives. In countries where political regimes had sought to deprive citizens of their futures by concealing traces of their past, archiving might be understood as a revolutionary gesture. This article studies archival projects born in the Arab region during the 2000s. It interprets the gesture of archiving as a way of caring for the future, and it interrogates its relation to art and aesthetics. How do aesthetics and art contribute to the gesture? What is the relationship between art and activism nurtured in these archival processes? The research is based on interviews with independent archivers who were and still are involved in the documentation of recent revolts and revolutions in the region, and it focuses on three projects: ‘Archives des luttes des femmes en Algérie’, initiated by young feminists and scholars Awel Haouati and Saadia Gacem during the Algerian Hirak (movement) of 2019–2020; the ‘Creative Memory of the Syrian Revolution’, founded by Sana Yazigi to collect and share the creativity of the Syrian revolution that started in 2011; the archive of the Lebanese ‘Committee of Families of the Disappeared and Kidnapped’, collected and created by Wadad Halwani since 1982, and later restored and curated by her son Ghassan Halwani since 2006.