bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oncointerpreter.ai enables interactive, personalized summarization of cancer diagnostics data
Authors: Tripathi Arihant , Ecker Brett , Boland Patrick , Ghodoussipour Saum , Riedlinger Gregory R , De Subhajyoti 
Published: November 2024

Abstract

Objectives
Cancer diagnosis comes as a shock to many patients, and many of them feel unprepared to handle the complexity of the life-changing event, understand technicalities of the diagnostic reports, and fully engage with the clinical team regarding the personalized clinical decision-making.

Materials and Methods
We develop Oncointerpreter.ai an interactive resource to offer personalized summarization of clinical cancer genomic and pathological data, and frame questions or address queries about therapeutic opportunities in near-real time via a graphical interface. It is built on the Mistral-7B and Llama-2 7B large language models trained on a local database trained using a large, curated corpus.

Results
We showcase its utility with case studies, where Oncointerpreter.ai extracted key clinical and molecular attributes from deidentified pathology and clinical genomics reports, summarized their contextual significance and answered queries on pertinent treatment options. Oncointerpreter also provided personalized summary of currently active clinical trials that match the patients’ disease status, their selection criteria, and geographic locations. Benchmarking and comparative assessment indicated that the model responses were generally consistent, and hallucination, ie, factually incorrect or nonsensical response was rare; treatment- and outcome related queries led to context-aware responses, and response time correlated with verbosity.

Discussion
The choice of model and domain-specific training also affected the response quality.

Conclusion
Oncointerpreter.ai can aid the existing clinical care with interactive, individualized summarization of diagnostics data to promote informed dialogs with the patients with new cancer diagnoses.

Availability
https://github.com/Siris2314/Oncointerpreter
Trabecular bone structural units and their cement lines change with age, bone volume fraction, structure, and strength in female human vertebrae
Authors: Lamarche Britney A , Thomsen Jesper Skovhus , Andreasen Christina Møller , Andersen Thomas Levin , Lievers W Brent 
Published: November 2024

Abstract
A lifetime of successive bone remodeling events leads to trabeculae which are composed of a patchwork of bone structural units (BSUs) called hemi-osteons or trabecular packets. Traditionally, only intact surface BSUs have been studied, which are those that have been created most recently. Accordingly, the complex changes in the size and distribution of BSU throughout the trabeculae have been overlooked. In this study, the BSUs within the trabeculae of the second lumbar vertebrae were manually traced, using ImageJ software, in osteopontin immunostained sections of eight young women (aged 19-38 yr) and eight older women (aged 69-96 yr). A series of BSU profile properties including area, width, length, and perimeter were quantified, along with properties of each trabecular profile such as the number of BSU and cement line length. The relationships between these properties and age, as well as selected trabecular microstructural properties assessed with microcomputed tomography, and bone strength assessed on the neighboring third lumbar vertebrae, were investigated. The median BSU profile length and perimeter decreased with age, while the median BSU profile area and width was unchanged. Moreover, age was associated with an increase in the number of BSU profiles and cement line length per trabecular profile area. However, changes in BSU profile geometry, the number of BSU profiles, and the cement line length per trabecular profile were strongly correlated with trabecular bone volume fraction, structure model index, and bone strength. Further research is needed to understand how these changes in BSU properties affect the mechanical and failure properties of trabecular bone.
BMO-GNN: Bayesian mesh optimization for graph neural networks to enhance engineering performance prediction
Authors: Park Jangseop , Kang Namwoo 
Published: November 2024

Abstract
Surrogate models are commonly used in engineering design to reduce the computational costs of simulations by approximating design variables and geometric parameters from computer-aided design (CAD) models. However, traditional surrogate models often lose critical information when simplified to lower dimensions and face challenges in handling the complexity of 3D shapes, especially in industrial datasets. To address these limitations, we propose a Bayesian graph neural network (GNN) framework that directly learns geometric features from CAD mesh representations for accurate engineering performance prediction. Our framework leverages Bayesian optimization (BO) to dynamically determine the optimal mesh element size, significantly improving model accuracy while balancing computational efficiency. This approach optimizes mesh resolution to preserve critical geometric features in 3D deep-learning-based surrogate models, adapting mesh size based on the task for high flexibility across various engineering applications. Experimental results demonstrate that mesh quality directly impacts prediction accuracy. The proposed BO-EI GNN model outperforms state-of-the-art models, including 3D CNN, SubdivNet, GCN, and GNN, in predicting mass, rim stiffness, and disk stiffness. Our method also significantly reduces computational costs compared to traditional optimization techniques. The proposed framework shows promising potential for application in finite element analysis (FEA) and other mesh-based simulations, enhancing the utility of surrogate models across various engineering fields.
Cumulative psychosocial and health disparities in US adolescent cigarette smoking, 2002-2019
Authors: Erath Tyler G , Chen Fang Fang , DeSarno Michael , Devine Derek , Leventhal Adam M , Bickel Warren K , Higgins Stephen T 
Published: November 2024

Abstract

Background
Understanding disparities in adolescent cigarette smoking is important for effective prevention.

Methods
We investigated disparities in adolescent smoking based on cumulative reported psychosocial and health risk among respondents ages 12-17 years in the US National Survey of Drug Use and Health from 2002 to 2019. Multivariable regression estimated associations of cumulative risk, survey years, and their interaction predicting past-month and daily smoking. Eleven psychosocial and health variables associated with youth smoking formed composite measures of cumulative risk, categorizing risk as low (0-2), moderate (3-4), or high (≥5). The main outcomes were weighted past-month and daily smoking by cumulative risk and time, examining prevalence and proportional change across years.

Results
Among 244 519 adolescents, greater cumulative risk predicted higher smoking prevalence across all outcomes. Compared with the low-risk category, past-month smoking odds (adjusted odds ratio) were 9.14 (95% confidence interval [CI] = 8.58 to 9.72) and 46.15 (95% CI = 43.38 to 49.10) times greater in the moderate-risk and high-risk categories. For daily smoking, odds were 14.11 (95% CI = 11.92 to 16.70) and 97.32 (95% CI = 83.06 to 114.03) times greater among the moderate-risk and high-risk categories. Regarding proportional change, the low-risk category exhibited the steepest decline (−85.1%) in past-month smoking from 2002-2003 to 2018-2019, followed by the moderate-risk (−79.2%) and high-risk (−65.7%) categories. Daily smoking declined more steeply among the low-risk (−96.5%) and moderate-risk (−90.5%) than high-risk category (−86.4%).

Conclusions
Cumulative risk is a robust predictor of adolescent smoking. Although record-setting reductions in adolescent smoking extend across risk categories, disparities favoring youth with fewer risks are evident throughout. Recognizing cumulative risk can inform the development of more targeted and effective prevention efforts.
Stacking Fault Segregation Imaging With Analytical Field Ion Microscopy
Authors: F. Morgado Felipe , Stephenson Leigh T , Bhatt Shalini , Freysoldt Christoph , Neumeier Steffen , Katnagallu Shyam , Subramanyam Aparna P A , Pietka Isabel , Hammerschmidt Thomas , Vurpillot François , Gault Baptiste 
Published: November 2024

Abstract
Stacking faults (SFs) are important structural defects that play an essential role in the deformation of engineering alloys. However, direct observation of SFs at the atomic scale can be challenging. Here, we use the analytical field ion microscopy, including density functional theory–informed contrast estimation, to image local elemental segregation at SFs in a creep-deformed solid-solution single-crystal alloy of Ni–2 at% W. The segregated atoms are imaged brightly, and time-of-flight spectrometry allows for their identification as W. We also provide the first quantitative analysis of trajectory aberration, with a deviation of approximately 0.4 nm, explaining why atom probe tomography could not resolve these segregations. Atomistic simulations of substitutional W atoms at an edge dislocation in face-centered cubic Ni using an analytic bond-order potential indicate that the experimentally observed segregation is due to the energetic preference of W for the center of the SF, contrasting with, for example, Re segregating to partial dislocations. Solute segregation to SF can hinder dislocation motion, increasing the strength of Ni-based superalloys. Yet, direct substitution of Re by W, envisaged to lower the superalloys’ costs, requires extra consideration in alloy design since these two solutes do not have comparable interactions with structural defects during deformation.
PEPSI’s non-detection of escaping hydrogen and metal lines adds to the enigma of WASP-12 b
Authors: Pai Asnodkar Anusha , Wang Ji , Broome Madelyn , Huang Chenliang , Johnson Marshall C , Ilyin Ilya , Strassmeier Klaus G , Jensen Adam 
Published: November 2024

ABSTRACT
WASP-12 b is an ultra-hot Jupiter of special interest for atmospheric studies since it is on an inspiraling orbit in an extreme environment of intense radiation and circumstellar gas. Previously claimed detections of active mass-loss from this planet are controversial across the literature. To address this controversy, we obtain two new transit observations of WASP-12 b with the optical high-resolution PEPSI spectrograph on the Large Binocular Telescope. Contrary to previous work, we do not observe planetary H$\alpha$ absorption and rule out the amplitude of previously reported detections. Our non-detection may be limited by the sensitivity of our data or could indicate weaker mass-loss than suggested by previous studies. We conduct injection-recovery experiments to place constraints on the radial extent of WASP-12 b’s escaping atmosphere as probed by Balmer lines, but find that our data do not have the sensitivity to probe down to the planet’s Roche lobe. Using physically motivated models of atmospheric escape, we explore upper limit constraints on the planet’s mass-loss rate and deem the data quality in the wavelength regime of Balmer lines insufficient to determine a physically meaningful constraint. We also conduct a spectral survey of other optical absorbers to trace atmospheric circulation but detect no additional absorption. We conclude that previous claims of H$\alpha$ absorption from the atmosphere of WASP-12 b should be reevaluated. Given the anticipated line strength of Balmer/optical features, observing the atmosphere of this faint target will require stacking more observations even with the largest telescope facilities available.
OncoSexome: the landscape of sex-based differences in oncologic diseases
Authors: Shen Xinyi , Zhang Yintao , Li Jiamin , Zhou Ying , Butensky Samuel D , Zhang Yechi , Cai Zongwei , DeWan Andrew T , Khan Sajid A , Yan Hong , Johnson Caroline H , Zhu Feng 
Published: November 2024

Abstract
The NIH policy on sex as biological variable (SABV) emphasized the importance of sex-based differences in precision oncology. Over 50% of clinically actionable oncology genes are sex-biased, indicating differences in drug efficacy. Research has identified sex differences in non-reproductive cancers, highlighting the need for comprehensive sex-based cancer data. We therefore developed OncoSexome, a multidimensional knowledge base describing sex-based differences in cancer (https://idrblab.org/OncoSexome/) across four key topics: antineoplastic drugs and responses (SDR), oncology-related biomarkers (SBM), risk factors (SRF) and microbial landscape (SML). SDR covers sex-based differences in 2051 anticancer drugs; SBM describes 12 551 sex-differential biomarkers; SRF illustrates 350 sex-dependent risk factors; SML demonstrates 1386 microbes with sex-differential abundances associated with cancer development. OncoSexome is unique in illuminating multifaceted influences of biological sex on cancer, providing both external and endogenous contributors to cancer development and describing sex-based differences for the broadest oncological classes. Given the increasing global research interest in sex-based differences, OncoSexome is expected to impact future precision oncology practices significantly.
canSAR 2024—an update to the public drug discovery knowledgebase
Authors: Gingrich Phillip W , Chitsazi Rezvan , Biswas Ansuman , Jiang Chunjie , Zhao Li , Tym Joseph E , Brammer Kevin M , Li Jun , Shu Zhigang , Maxwell David S , Tacy Jeffrey A , Mica Ioan L , Darkoh Michael , di Micco Patrizio , Russell Kaitlyn P , Workman Paul , Al-Lazikani Bissan 
Published: November 2024

Abstract
canSAR (https://cansar.ai) continues to serve as the largest publicly available platform for cancer-focused drug discovery and translational research. It integrates multidisciplinary data from disparate and otherwise siloed public data sources as well as data curated uniquely for canSAR. In addition, canSAR deploys a suite of curation and standardization tools together with AI algorithms to generate new knowledge from these integrated data to inform hypothesis generation. Here we report the latest updates to canSAR. As well as increasing available data, we provide enhancements to our algorithms to improve the offering to the user. Notably, our enhancements include a revised ligandability classifier leveraging Positive Unlabeled Learning that finds twice as many ligandable opportunities across the pocketome, and our revised chemical standardization pipeline and hierarchy better enables the aggregation of structurally related molecular records.
A survey on multimodal large language models
Authors: Yin Shukang , Fu Chaoyou , Zhao Sirui , Li Ke , Sun Xing , Xu Tong , Chen Enhong 
Published: November 2024

ABSTRACT
Recently, the multimodal large language model (MLLM) represented by GPT-4V has been a new rising research hotspot, which uses powerful large language models (LLMs) as a brain to perform multimodal tasks. The surprising emergent capabilities of the MLLM, such as writing stories based on images and optical character recognition–free math reasoning, are rare in traditional multimodal methods, suggesting a potential path to artificial general intelligence. To this end, both academia and industry have endeavored to develop MLLMs that can compete with or even outperform GPT-4V, pushing the limit of research at a surprising speed. In this paper, we aim to trace and summarize the recent progress of MLLMs. First, we present the basic formulation of the MLLM and delineate its related concepts, including architecture, training strategy and data, as well as evaluation. Then, we introduce research topics about how MLLMs can be extended to support more granularity, modalities, languages and scenarios. We continue with multimodal hallucination and extended techniques, including multimodal in-context learning, multimodal chain of thought and LLM-aided visual reasoning. To conclude the paper, we discuss existing challenges and point out promising research directions.
Risk Factors for Spotted Fever Group Rickettsioses in Kilimanjaro Region, Tanzania
Authors: Bowhay Thomas R , Rubach Matthew P , Mendes Ângelo J F , Nicholson William L , Perniciaro Jamie L , Maze Michael J , Moorthy Ganga S , Halliday Jo E B , Allan Kathryn J , Mmbaga Blandina T , Saganda Wilbrod , Lwezaula Bingileki F , Kazwala Rudovick R , Cleaveland Sarah , Sharples Katrina J , Maro Venance P , Crump John A 
Published: November 2024

Abstract

Background
Knowledge gaps exist on risk factors for spotted fever group rickettsioses (SFGR) in sub-Saharan Africa. We sought to identify SFGR risk factors in Kilimanjaro Region, Tanzania.

Methods
We recruited febrile patients presenting at 2 hospitals in Moshi from February 2012 through May 2014. Standardized clinical and risk factor questionnaires were administered. SFGR exposure was defined as a Rickettsia africae immunofluorescence antibody reciprocal titer ≥64, and acute SFGR as a ≥4-fold rise between paired sera. Logistic regression was used to identify associations.

Results
Of 1190 participants providing ≥1 serum sample, the median age was 21.8 (range, 0.3–100.2) years, 646 (54.3%) were female, and 650 (54.6%) had SFGR exposure. Of 731 participants with paired sera, 67 (9.2%) had acute SFGR. On multivariable analysis, odds of acute SFGR were higher in the age group 0–2 years (adjusted odds ratios [aORs] for older age groups, &lt;0.36; P &lt; .011), rural residence (aOR, 4.1; P = .007), and areas with maximum daily temperature &lt;26°C (aORs for higher temperature groups, &lt;0.42; P &lt; .035). Odds of SFGR exposure were higher in those working in the garden (aOR, 1.8; P = .010) and seeing a dog (aOR, 1.5; P = .010). Odds of SFGR exposure were lower in the age group 0–2 years (aORs for older age groups, &gt;1.5; P &lt; .026), female sex (aOR, 0.62; P &lt; .001), and being from the Chaga tribe (aOR, 0.68; P = .003).

Conclusions
Those aged &lt;2 years, rural residents, and persons residing in areas with cooler temperatures had increased odds of SFGR. Our results identify groups for further research on tick exposure and for targeted prevention interventions.
The transcription factor CaBBX10 promotes chlorophyll and carotenoid pigment accumulation in Capsicum annuum fruit
Authors: Wang Jin , Shan Qingyun , Yuan Qiaoling , Pan Luzhao , Wang Meiqi , Zhao Pei , Yu Feng , Dai Li , Xie Lingling , Wang Zhongyi , Dai Xiongze , Chen Li , Zou Xuexiao , Xiong Cheng , Zhu Fan , Liu Feng 
Published: November 2024

Abstract
Chlorophylls and carotenoids are 2 pivotal photosynthetic pigments directly influencing the economic value of pepper (Capsicum annuum L.) fruits. However, the coordinated regulatory mechanisms governing the accumulation of both chlorophylls and carotenoids during pepper fruit development remain elusive. In this study, pepper B-box 10 (CaBBX10), a candidate hub transcription factor, was found to play dual roles in the early development of pepper fruit. CaBBX10 virus-induced gene silencing and overexpression experiments demonstrated that the encoded transcription factor promotes both chlorophyll and carotenoid accumulation in pepper fruit. Further comprehensive analyses showed that CaBBX10 directly binds to the promoter of magnesium chelatase subunit D subunit (CaCHLD) and phytoene synthase 1 (CaPSY1), thereby activating their expression in the chlorophyll and carotenoid biosynthesis pathways, respectively. Additionally, the photomorphogenic factor CaCOP1 was found to physically interact with CaBBX10 and lead to its degradation. Therefore, CaBBX10 may serve as a critical link connecting chlorophyll and carotenoid biosynthesis to light signaling. Altogether, our findings reveal a mechanism for the complex transcriptional regulation that simultaneously promotes chlorophyll and carotenoid accumulation in pepper fruit.
Expression of the polyphenol oxidase gene MdPPO7 is modulated by MdWRKY3 to regulate browning in sliced apple fruit
Authors: Zou Hui , Li Chengzhu , Wei Xiaoyu , Xiao Qian , Tian Xiaocheng , Zhu Lingcheng , Ma Baiquan , Ma Fengwang , Li Mingjun 
Published: November 2024

Abstract
Browning is a pervasive problem in horticultural products, substantially diminishing the appearance, flavor, and nutritional value of fruit, including important fruits like apple (Malus × domestica Borkh.). In this study, we compared the physiological characteristics of the browning-resistant line ‘Rb-18’ with the susceptible variety ‘Fuji’ and found that the polyphenol oxidase (PPO) enzyme activity and phenolic content of ‘Rb-18’ were significantly lower than those in ‘Fuji’. In addition, the PPO enzyme in ‘Fuji’ showed a stronger affinity for its substrate, catechol, compared to ‘Rb-18’. Through transcriptome and RT-qPCR analyses, MdPPO7 expression was identified as contributing to flesh browning after cutting. Subsequent fruit injection and stable genetic transformation of the MdPPO7 gene into apple fruit and calli determined that syringic acid, procyanidin, phloridzin, chlorogenic acid, gallic acid, catechin, and caffeic act as its catalytic substrates in the process involved in browning. Furthermore, luciferase reporter, yeast 1-hybrid, β-glucuronidase reporter assays and ChIP-qPCR analysis demonstrated that a WRKY transcription factor (MdWRKY3) binds to the promoter region of polyphenol oxidase gene (MdPPO7) and positively regulates its expression to promote apple flesh browning. This study provides insights into the molecular regulatory mechanisms of fruit browning in fresh-cut apples and provides a theoretical basis for the generation of high-quality apple germplasm resources.
Warm glow feelings can promote green behavior
Authors: Jerit Jennifer , Shin Hwayong , Barabas Jason 
Published: November 2024

Abstract
For climate mitigation to be successful, vast numbers of people must change how they go about daily life. Social scientists have tried to promote environmentally sustainable (i.e. “green”) behavior with interventions involving cues, frames, and information, but the cumulative impact of those efforts has been modest. A growing number of studies—largely observational—suggests the promise of “warm glow” messaging that features the pleasure and satisfaction one experiences from acting sustainably. While past work has established the association between intrinsic motivations and green behavior, our study offers evidence regarding the causal effect of warm glow feelings in the climate domain. In three survey experiments administered on different national samples, we induce feelings of warm glow and examine the impact on green behavioral intentions. The treatment, an adaptation of a standard feeling induction, has a significant influence on a wide range of actions—an effect that is distinct from the influence of general positivity. Most importantly, we observe the largest treatment effects in surprising places: among Republicans, and within this subgroup, on more socially visible activities. Manipulated warm glow also increases intentions to engage in more difficult (e.g. costly, effortful) activities. Our findings are valuable for scholars and practitioners seeking to promote broad-based climate mitigation across the ideological spectrum.