bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automated Identification of Breast Cancer Relapse in Computed Tomography Reports Using Natural Language Processing
Authors: Lee Jaimie J. , Zepeda Andres , Arbour Gregory , Isaac Kathryn V. , Ng Raymond T. , Nichol Alan M. 
Published: December 2024

PURPOSE
Breast cancer relapses are rarely collected by cancer registries because of logistical and financial constraints. Hence, we investigated natural language processing (NLP), enhanced with state-of-the-art deep learning transformer tools and large language models, to automate relapse identification in the text of computed tomography (CT) reports.

METHODS
We analyzed follow-up CT reports from patients diagnosed with breast cancer between January 1, 2005, and December 31, 2014. The reports were curated and annotated for the presence or absence of local, regional, and distant breast cancer relapses. We performed 10-fold cross-validation to evaluate models identifying different types of relapses in CT reports. Model performance was assessed with classification metrics, reported with 95% confidence intervals.

RESULTS
In our data set of 1,445 CT reports, 799 (55.3%) described any relapse, 72 (5.0%) local relapses, 97 (6.7%) regional relapses, and 743 (51.4%) distant relapses. The any-relapse model achieved an accuracy of 89.6% (87.8-91.1), with a sensitivity of 93.2% (91.4-94.9) and a specificity of 84.2% (80.9-87.1). The local relapse model achieved an accuracy of 94.6% (93.3-95.7), a sensitivity of 44.4% (32.8-56.3), and a specificity of 97.2% (96.2-98.0). The regional relapse model showed an accuracy of 93.6% (92.3-94.9), a sensitivity of 70.1% (60.0-79.1), and a specificity of 95.3% (94.2-96.5). Finally, the distant relapse model demonstrated an accuracy of 88.1% (86.2-89.7), a sensitivity of 91.8% (89.9-93.8), and a specificity of 83.7% (80.5-86.4).

CONCLUSION
We developed NLP models to identify local, regional, and distant breast cancer relapses from CT reports. Automating the identification of breast cancer relapses can enhance data collection about patient outcomes.
Real-World Outcomes in Patients With Metastatic Renal Cell Carcinoma Treated With First-Line Nivolumab Plus Ipilimumab in the United States
Authors: Doshi Gurjyot K. , Osterland Andrew J. , Shi Ping , Yim Annette , Del Tejo Viviana , Guttenplan Sarah B. , Eiffert Samantha , Yin Xin , Rosenblatt Lisa , Conkling Paul R. 
Published: December 2024

PURPOSE
Nivolumab plus ipilimumab (NIVO + IPI) is a first-in-class combination immunotherapy for the treatment of intermediate- or poor (I/P)-risk advanced or metastatic renal cell carcinoma (mRCC). Currently, there are limited real-world data regarding clinical effectiveness beyond 12-24 months from treatment initiation. In this real-world study, treatment patterns and clinical outcomes were evaluated for NIVO + IPI in a community oncology setting.

METHODS
A retrospective analysis using electronic medical record data from The US Oncology Network examined patients with I/P-risk clear cell mRCC who initiated first-line (1L) NIVO + IPI between January 4, 2018, and December 31, 2019, with follow-up until June 30, 2022. Baseline demographics, clinical characteristics, treatment patterns, clinical effectiveness, and safety outcomes were assessed descriptively. Overall survival (OS) and real-world progression-free survival (rwPFS) were analyzed using Kaplan-Meier methods.

RESULTS
Among 187 patients identified (median follow-up, 22.4 months), with median age 63 (range, 30-89) years, 74 (39.6%) patients had poor risk and 37 (19.8%) patients had Eastern Cooperative Oncology Group performance status score ≥2. Of 86 patients who received second-line therapy, 54.7% received cabozantinib and 10.5% received pazopanib. The median (95% CI) OS and rwPFS were 38.4 (24.7-46.1) months and 11.1 (7.5-15.0) months, respectively. Treatment-related adverse events (TRAEs) were reported in 89 (47.6%) patients, including fatigue (n = 25, 13.4%) and rash (n = 19, 10.2%).

CONCLUSION
This study provides data to support the understanding of the real-world utilization and long-term effectiveness of 1L NIVO + IPI in patients with I/P-risk mRCC. TRAE rates were low relative to clinical trials.
Impact of Financial Toxicity on Treatment Adherence and Quality of Life in Pancreatic Cancer
Authors: Schleimer Lauren E. , Aviki Emeline , Kalvin Hannah L. , Magnin Josephine , Sokolowski Stefania S. , Kingham T. Peter , O'Reilly Eileen M. , Varghese Anna M. , Soares Kevin C. , Drebin Jeffrey , D'Angelica Michael I. , Jarnagin William R. , Gonen Mithat , Thom Bridgette , Wei Alice C. 
Published: December 2024

PURPOSE
Financial toxicity (FT) is increasingly recognized as a major issue in cancer care. We evaluated the prevalence and risk factors for FT in patients with pancreatic ductal adenocarcinoma (PDAC) and FT associations with treatment adherence and quality of life (QOL).

METHODS
A screening questionnaire based on the Comprehensive Score for Financial Toxicity (COST) was implemented at our National Cancer Institute–designated comprehensive cancer center. Respondents with pathologic diagnosis of PDAC who completed >50% of prompts between June 2022 and June 2023 were analyzed. COST ≤16 was categorized as FT. Associations between FT and demographic and clinical factors were assessed using logistic regression, and QOL was assessed using linear regression.

RESULTS

Of the 1,888 patients with PDAC, 1,162 completed the COST questionnaire, and 1,079 met the inclusion criteria. The prevalence of FT was 23% (n = 245); 37% of patients with FT reported medication nonadherence due to cost. Demographic factors and poor performance status were associated with FT. Treatment-naïve patients were more likely to report FT compared with those on induction, adjuvant, or palliative therapy (
P
= .049). Patients experiencing FT reported worse QOL, with a median score of 5 (IQR, 4-7) versus 8 (IQR, 6-9) without FT. This relationship persisted after adjusting for demographic and clinical factors; the effect size of FT (β = –1.5; 95% CI, –1.1 to –1.9) was nearly double that of poor performance status (β = –.8; 95% CI, –1.3 to –0.4).

CONCLUSION
FT affected nearly one in four patients with PDAC at a high-volume cancer center and was associated with worse QOL and medication nonadherence. Universal screening and interventions to reduce FT are warranted. Clinical trials investigating QOL as an end point must account for potential confounding due to FT.
Afterword: Telling Stories about Unknown Lives
Authors: Alaimo Stacy 
Published: December 2024

Abstract
Despite initial skepticism regarding the idea that narrative is a potent mode for generating multispecies justice, this afterword underscores the compelling arguments in the introduction to this special section. Then, the essay offers a response to several of the ideas, analyses, and examples presented by the essays in this collection, with a focus on conceptions of relationality, the subjects of justice, not-knowing but learning, and practices of world-building. It also offers brief interpretations of Leanne Betasamosake Simpson's novel Noopiming in relation to concepts and questions raised by the special section. The afterword concludes by advocating for a multitude of practices within specific places and lifeworlds, practices that are rich with compassionate multispecies relations.
Casein kinase 1 controls components of a TORC2 signaling network in budding yeast
Authors: Lucena Rafael , Jasani Akshi , Anastasia Steph , Kellogg Douglas , Alcaide-Gavilan Maria 
Published: December 2024

ABSTRACT
Tor kinases play diverse and essential roles in control of nutrient signaling and cell growth. These kinases are assembled into two multiprotein complexes known as TORC1 and TORC2. In budding yeast, TORC2 relays nutrient-dependent signals that strongly influence growth rate and cell size. However, the mechanisms that control TORC2 signaling are poorly understood. Activation of TORC2 requires Mss4, a phosphatidylinositol 4-phosphate 5-kinase that recruits and activates downstream targets of TORC2. Localization of Mss4 to the plasma membrane is thought to be controlled by phosphorylation, and previous work has suggested that yeast homologs of casein kinase 1, Yck1 and Yck2 (referred to here collectively as Yck1/2), Control phosphorylation of Mss4. Here, we generated a new analog-sensitive allele of YCK2 and used it to test whether Yck1/2 influence localization of Mss4 or signaling in the TORC2 network. We found that Yck1/2 strongly influence Mss4 phosphorylation and localization, as well as influencing regulation of multiple components of the TORC2 network. However, inhibition of Yck1/2 causes mild effects on the best-characterized signaling axis in the TORC2 pathway, suggesting that Yck1/2 might play a larger role in influencing less well-understood aspects of TORC2 signaling.
Fibre type differences in the organisation of mononuclear cells and myonuclei at the tips of human myofibres
Authors: Hoegsbjerg Christian , Møbjerg Ask , Yeung Ching-Yan Chloé , Schjerling Peter , Krogsgaard Michael R. , Koch Manuel , Kjaer Michael , von Keudell Arvind G. , Mackey Abigail L. 
Published: December 2024

ABSTRACT
The myotendinous junction (MTJ) is a weak link in the musculoskeletal system. Here, we isolated the tips of single myofibres from healthy (non-injured) human hamstring muscles for confocal microscopy (n=6) and undertook RNAscope in situ hybridisation (n=6) to gain insight into the profiles of cells and myonuclei in this region, in a fibre type manner. A marked presence of mononuclear cells was observed coating the myofibre tips (confirmed by serial block face scanning electron microscopy and cryosection immunofluorescence), with higher numbers for type I (median 29; range 16–63) than type II (16; 9–23) myofibres (P&lt;0.05). The number of these cells expressing COL22A1 was comparable between fibre types. Myonuclear number and density gradually increased from the myofibre proper towards the tip for both fibre types (P&lt;0.05). COL22A1 was expressed by similar proportions of myonuclei in type I (median 26%; range 13–56) and type II (19%; 3–67) myofibre tips. 70% of the COL22A1-positive nuclei in the MTJ region were myonuclei, and the remaining 30% were MTJ cells. This insight refines our fundamental understanding of the human MTJ at the cell and structural levels.
A Riemannian Alternating Direction Method of Multipliers
Authors: Li Jiaxiang , Ma Shiqian , Srivastava Tejes 
Published: December 2024

We consider a class of Riemannian optimization problems where the objective is the sum of a smooth function and a nonsmooth function considered in the ambient space. This class of problems finds important applications in machine learning and statistics, such as sparse principal component analysis, sparse spectral clustering, and orthogonal dictionary learning. We propose a Riemannian alternating direction method of multipliers (ADMM) to solve this class of problems. Our algorithm adopts easily computable steps in each iteration. The iteration complexity of the proposed algorithm for obtaining an ϵ-stationary point is analyzed under mild assumptions. Existing ADMMs for solving nonconvex problems either do not allow a nonconvex constraint set or do not allow a nonsmooth objective function. Our algorithm is the first ADMM-type algorithm that minimizes a nonsmooth objective over manifold—a particular nonconvex set. Numerical experiments are conducted to demonstrate the advantage of the proposed method. Funding: The research of S. Ma was supported in part by the Office of Naval Research [Grant N00014-24-1-2705]; the National Science Foundation [Grants DMS-2243650, CCF-2308597, CCF-2311275, and ECCS-2326591]; the University of California, Davis Center for Data Science and Artificial Intelligence Research Innovative Data Science Seed Funding Program; and Rice University start-up fund.
Tailored Base-Surge Policies in Dual-Sourcing Inventory Systems with Demand Learning
Authors: Chen Boxiao , Shi Cong 
Published: December 2024

Dual-Sourcing Inventory Management Under Incomplete Information The class of dual-sourcing problems is one of the most fundamental challenges in inventory and supply chain management and is a common practice in global supply chain management. Under a dual-sourcing strategy, a firm procures items from a regular source with lower cost and longer lead time and an expedited source with higher cost and shorter lead time. We focus on Tailored Base-Surge (TBS) policies, where a constant order is placed with the regular source each period, and the expedited source follows an order-up-to rule. Although existing literature assumes that stochastic demand processes are known inputs to optimization models, decision-makers often lack this information in practice and must learn it in real time to maximize expected revenue. In “Tailored Base-Surge Policies in Dual-Sourcing Inventory Systems with Demand Learning”, B. Chen and C. Shi develop online learning algorithms for finding the optimal TBS policy, demonstrating strong theoretical and numerical performance.
Lemierre’s syndrome in a 16-year-old man associated with resolution of marked widespread ST elevation and a normal troponin level
Authors: Amini Sylvia , Meghjee Salim , Khan Muhammad Rahim 
Published: December 2024

A 16-year-old man presented to the Accident and Emergence services with a 10-day history of shortness of breath, sore throat, vomiting, diarrhoea, poor oral intake, chest pain, jaundice, diplopia and reduced urine output. He was initially treated for sepsis, however, subsequent imaging and blood cultures confirmed the diagnosis of Lemierre’s syndrome (LS). LS, also known as necrobacillosis or post-pharyngitis anaerobic septicaemia is comprised of a triad of metastatic septic emboli secondary to pharyngitis, bacteraemia, and internal jugular vein thrombophlebitis. Fusobacterium necrophorum, a Gram-negative anaerobe, is the most common culprit of LS, followed by Fusobacterium nucleatum and anaerobic bacteria such as streptococci, staphylococci, and Klebsiella. LS is also called the forgotten syndrome because although use of antibiotics at first decreased the prevalence of LS, resistance to antibiotics has caused a rise in LS and it is no longer a forgotten disease. LS should be on the differential diagnosis of chest empyema if it follows pharyngitis or tonsillitis with neck pain, lymphadenopathy and sepsis, hence taking a thorough history is the key to diagnose it earlier. It is paramount to do chest X-ray, Doppler ultrasound of the neck veins and computed tomography (CT) scan of the neck and chest to look for features of LS. LS can be fatal if not diagnosed and treated properly. Empirical antibiotic therapy should be prescribed for a minimum of 3 weeks and should cover anaerobic bacteria and Gram-negative rods.
Cyberbiosecurity: A Multidisciplinary National Security Challenge
Authors: Batarseh Feras A. 
Published: December 2024

HighlightsA high-level overview of the articles featured in this special collection.An introduction to the concept of cyberbiosecurity.Exploration of cyber-related challenges related to biological systems.Abstract. The growing frequency of threats to the food, agriculture, and water domains has increased the need for more secure foundations in the systems that support these critical infrastructures. This article introduces the concept and definition of cyberbiosecurity and provides an overview of the five papers selected for this special collection: “Cyberbiosecurity: Securing Water and Agricultural Systems (CSWAS)”. The five papers present an array of solutions relevant to developing a cyber workforce for biological systems, detecting misinformation in the agricultural domain, and utilizing artificial intelligence for agricultural production and global trade analysis. Additionally, manuscripts in this special collection present works on combating algal blooms in water bodies and disease detection in agriculture. Through this CSWAS special collection, efforts to rethink and redesign future biological systems with technology and security in mind can have a significant impact on creating more sustainable and resilient food, agriculture, and water systems. Keywords: Artificial intelligence, Cyberbiosecurity, Cyber workforce, Water and agricultural systems.
Response of summer irrigated black gram (Vigna mungo L.) to planting method and weed management methods under western agro-climatic zones of Tamil Nadu
Authors: Senthamizhselvan S , Anitta FS , Raju M , Babu RPV , Mohankumar AP 
Published: December 2024

To assess the effect of sowing methods and weed management on summer irrigated black gram yield, a field experiment was conducted during the summer season of 2024 in the Department of Pulses at Tamil Nadu Agricultural University, Coimbatore. The treatments were employed in the Split plot design and replicated thrice. The sowing methods and weed management treatments were allotted in the main and subplots, respectively. The findings showed that, among the sowing methods, furrow-irrigated raised beds recorded a lower weed density and concerning weed management, the pre-emergence (PE) application of Pendimethalin 30 % + Imazethapyr 2 % EC (ready mix) and weeding with power-operated weeder at 20 DAS resulted in lesser weeds which leads to higher weed control efficiency (79.88 %) and higher seed yield in both furrow-irrigated raised beds and pre-emergence (PE) application of Pendimethalin 30 % + Imazethapyr 2 % EC (ready mix) and weeding with power-operated weeder at 20 DAS.
Occurrence of Calophyllum apetalum Willd., in the coastal plains of Alappuzha district and evaluation of its population characteristics with respect to an evergreen forest ecosystem of the Southern Western Ghats
Authors: Raveendran M , Shaijal K 
Published: December 2024

Calophyllum apetalum Willd., commonly known as “Poon spar of Travancore”, is an evergreen tree endemic to the Western Ghats of India, thrives in riparian habitats of evergreen forests and coastal sandy regions. In this study, we investigated its distribution in Alappuzha district (coastline area) and the Kallar forest region (evergreen forest). The study analyzed relative dominance, frequency, density and the Importance Value Index (IVI) of C. apetalum, along with soil composition. This study concludes that, despite variations in terms of diversity and species richness, C. apetalum remains dominant on both the studied locations (with the highest IVI). however, there is a concerning decline in its population, additionally, this species can thrive in different soil compositions of coastal plains as well as evergreen forest, also dominant in their respective habitats.
Significant records of plants, algae, fungi, and animals in SE Europe and adjacent regions, 3
Authors: Jakob Aljaž , Štampar Laura , Lobnik Cimerman Žan , Strgulc Krajšek Simona , Vittori Miloš , Dolničar Dren 
Published: December 2024

In this paper, we present two significant records of bryophytes in Slovenia, Cryphaea heteromalla and Riccia cavernosa, which were found in new phytogeographical regions. We report the three new records of an isopod Armadillo officinalis, a species that has been considered possibly extinct in Slovenia, and a new record of bat, Plecotus macrobullaris, from the Julian Alps.
Numeral systems in Lezgic languages
Authors: Melenchenko Maksim 
Published: December 2024

Abstract
The paper presents an overview of numeral systems in Lezgic languages (East Caucasian) and discusses hypotheses about their diachronic development. Similarly to other branches of the East Caucasian family, languages of the Lezgic branch have either a decimal (base-10) or a vigesimal (base-20) system. Decimal systems are attested in languages and dialects in the northwestern part of the Lezgic area, while languages with vigesimal systems are spoken in the southeast. The article analyzes unusual features of numeral systems in several Lezgic languages: the fossilization of gender markers in a subset of decimal numerals (‘30’–‘90’), a shared decimal-based etymon for ‘40’, and north–south dialectal variation in numeral systems of Agul and Tabasaran, which are likely the result of contact influence. These phenomena challenge the traditional view that the vigesimal numeral system is original to the Lezgic languages and suggest that the hypothesis of the originality of the decimal system should not be overlooked.
Enhancing the total-field magnetic anomaly using the normalized source strength
Authors: Long Nguyen Ngoc , Pham Luan Thanh , Abdelrahman Kamal , Ai Hanbing , Nguyen Dat Viet , Duong Van-Hao , Fnais Mohammed S. , Eldosouky Ahmed M. 
Published: December 2024

Abstract
Enhancement methods of aeromagnetic data are widely used in mapping geological features. Many methods based on field gradients have been introduced to outline the source edges. However, the disadvantage of these methods is that they require the reduction to pole (RTP) or gradients of the magnetic potential directly measured by specific sensors. This study introduces a new method to enhance magnetic anomaly data without needing the RTP. This method uses the normalized source strength (NSS) calculated from the total-field magnetic anomaly, subsequently balanced by the tilt angle filter. The new method is tested on synthetic datasets and a real dataset of the Olympic Peninsula. The findings show that the presented method is less sensitive to variations in the source depth. These findings also showed that this method is less dependent on the magnetization direction and produces more precise and sharper boundaries than other methods. Thus, the presented method appears promising in providing a valuable tool for interpreting magnetic data compared to traditional methods.
Enhancing automated essay scoring with GCNs and multi-level features for robust multidimensional assessments
Authors: Tang Xiaoyi , Lin Daoyu , Li Kexin 
Published: December 2024

Abstract
The advancement of automated essay scoring (AES) is pivotal in alleviating the burdens on educators and ensuring fair and reliable writing assessments. While deep neural networks have enhanced AES accuracy, they frequently encounter challenges in capturing comprehensive contextual features and achieving generalizability across multiple dimensions of writing quality. To address these limitations, we propose GCNs-MTL+Multi-Level Features, a novel integration of graph convolutional networks (GCNs) with the pretrained BERT model and multi-task learning (MTL). Our proposed approach significantly enriches essay representation fidelity by incorporating both word-level and sentence-level features, thereby enhancing transparency and improving the robustness and accuracy of writing evaluations across holistic and analytic rating scales. By sharing representations across AES tasks, GCNs-MTL+Multi-Level Features streamlines the evaluation process, establishing a new benchmark in multidimensional writing assessments.