bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systematic Characterization of the Effectiveness of Alignment in Large Language Models for Categorical Decisions
Authors: Kohane Isaac 
Published: September 2024

AbstractAs large language models (LLMs) are increasingly deployed in high-stakes domains like healthcare, understanding how well their decision-making aligns with human preferences and values becomes crucial, especially when we recognize that there is no single gold standard for these preferences. This paper applies a systematic methodology for evaluating preference alignment in LLMs on categorical decision-making with medical triage as a domain-specific use case. It also measures how effectively an alignment procedure will change the alignment of a specific model. Key to this methodology is a novel simple measure, the Alignment Compliance Index (ACI), that quantifies how effectively a LLM can be aligned to a given preference function or gold standard. Since the ACI measures the effect rather than the process of alignment, it is applicable to alignment methods beyond the in-context learning used in this study.Using a dataset of simulated patient pairs, three frontier LLMs (GPT4o, Claude 3.5 Sonnet, and Gemini Advanced) were assessed on their ability to make triage decisions consistent with an expert clinician’s preferences. The models’ performance before and after alignment attempts was evaluated using various prompting strategies. The results reveal significant variability in alignment effectiveness across models and alignment approaches. Notably, models that performed well, as measured by ACI, pre-alignment sometimes degraded post-alignment, and small changes in the target preference function led to large shifts in model rankings.The implicit ethical principles, as understood by humans, underlying the LLMs’ decisions were also explored through targeted questioning. These findings highlight the complex, multifaceted nature of decision-making and the challenges of robustly aligning AI systems with human values. They also motivate the use of a practical set of methods and the ACI, in the near term, to understand the correspondence between the variety of human and LLM decision-making values in specific scenarios.
Postoperative Lymphatic Exudate is a Proximal Source of ctDNA and Detects Recurrence in HPV-negative Head and Neck Cancer
Authors: Lazare Seka , Gu Zhuosheng , Earland Noah , Harmon Adam , Pacula Maciej , Long Megan , Tellis Ashley , Whitfield Damion , Benson Adam , Gerndt Sophie , Harris Peter , Khalil Lucien , Ramirez Ricardo , Xu Zhongping , Wahle Benjamin , Puram Sid , Adkins Doug , Thorstad Wade , Zandberg Daniel , Chernock Rebecca , Skinner Heath , Seethala Raja , Ferris Robert L. , Francis Marra S. , Winckler Wendy , Chaudhuri Aadel A. , Zevallos Jose P. 
Published: September 2024

ABSTRACTRelapse is a major cause of failure after surgery in HPV-human papillomavirus (HPV) negative head and neck squamous cell carcinoma (HNSCC),), with up to 50% of patients recurring within 2 years. While clinicopathologic criteria exist for adjuvant treatment, these criteria are imprecise and have not changed for decades. However, no reliable method exists to tailor adjuvant therapy for individual patients based on risk of recurrence after surgery. Using an ultra-sensitive targeted sequencing approach, we demonstrate that circulating tumor DNA (ctDNA) in lymphatic exudate collected via surgical drains (“lymph”) 24 hours after surgery accurately identifies MRD and outperforms plasma in an initial cohort of 36 HNSCC patients. We then applied the lymph ctDNA test to an independent, multi-site cohort of 37 HNSCC patients, replicating the original finding. Lymph performance was particularly enhanced in locoregional relapse in both cohorts and generalized to early stage (I-II) patients. Analysis of matched plasma collected at this early timepoint was not predictive of recurrence. We demonstrate a liquid biopsy approach using a historically overlooked biofluid to potentially enable precision adjuvant therapy and achieve superior oncologic outcomes.SIGNIFICANCEPostoperative lymphatic exudate represents a novel proximal analyte for MRD detection in HPV-HNSCC designed specifically for use in the immediate post-surgical window when adjuvant therapy decisions must be made. Accurate MRD identification at this early timepoint has potential to augment traditional pathology and personalize adjuvant treatment paradigms in HPV-negative HNSCC.
Synthetic Data Generation in Motion Analysis: A Generative Deep Learning Framework
Authors: Perrone Mattia , Mell Steven , Martin John , Nho Shane J. , Simmons Scott , Malloy Philip 
Published: September 2024

AbstractGenerative deep learning has emerged as a promising data augmentation technique in recent years. This approach becomes particularly valuable in areas such as motion analysis, where it is challenging to collect substantial amounts of data. The current study introduces a data augmentation strategy that relies on a variational autoencoder to generate synthetic data of kinetic and kinematic variables. The kinematic and kinetic variables consist of hip and knee joint angles and moments, respectively, in both sagittal and frontal plane, and ground reaction forces. Statistical parametric mapping (SPM) did not detect significant differences between real and synthetic data for each of the biomechanical variables considered. To further evaluate the effectiveness of this approach, a long-short term model (LSTM) was trained both only on real data (R) and on the combination of real and synthetic data (R&S); the performance of each of these two trained models was then assessed on real test data unseen during training. The predictive model achieved comparable results in terms of nRMSE when predicting knee joint moments in the frontal (R&S: 9.86% vs R:10.72%) and sagittal plane (R&S: 9.21% vs R: 9.75%), and hip joint moments in the frontal (R&S: 16.93% vs R:16.79%) and sagittal plane (R&S: 13.29% vs R:14.60%). These findings suggest that the proposed methodology is an effective data augmentation approach in motion analysis settings.
Evaluating large language model workflows in clinical decision support: referral, triage, and diagnosis
Authors: Gaber Farieda , Shaik Maqsood , Franke Vedran , Akalin Altuna 
Published: September 2024

AbstractAccurate medical decision-making is critical for both patients and clinicians. Patients often struggle to interpret their symptoms, determine their severity, and select the right specialist. Simultaneously, clinicians face challenges in integrating complex patient data to make timely, accurate diagnoses. Recent advances in large language models (LLMs) offer the potential to bridge this gap by supporting decision-making for both patients and healthcare providers. In this study, we benchmark multiple LLM versions and an LLM-based workflow incorporating retrieval-augmented generation (RAG) on a curated dataset of 2,000 medical cases derived from the Medical Information Mart for Intensive Care database. Our findings show that these LLMs are capable of providing personalized insights into likely diagnoses, suggesting appropriate specialists, and assessing urgent care needs. These models may also support clinicians in refining diagnoses and decision-making, offering a promising approach to improving patient outcomes and streamlining healthcare delivery.
A New Approach to Identifying Elite Winter Sport Athletes’ Risk of Relative Energy Deficiency in Sport (REDs)
Authors: Smith Emily M. , Drager Kelly , Groves Erik M. , Gabel Leigh , Boyd Steven K. , Burt Lauren A. 
Published: September 2024

AbstractObjectivesRelative Energy Deficiency in Sport (REDs) is a syndrome resulting from problematic low energy availability (LEA). Low areal bone mineral density (aBMD) is a primary indicator of LEA, measured by dual X-ray absorptiometry (DXA). High-resolution peripheral quantitative computed tomography (HR-pQCT) is an advanced imaging device that provides measures of volumetric BMD (vBMD), bone microarchitecture, geometry, and strength. The objective of this study was to assess prevalence of REDs in elite winter sport athletes and to observe the associations in bone parameters using HR-pQCT in athletes identified as at-risk or not at-risk of REDs.MethodsParticipants included 101 elite athletes (24.1±4.4 SD years; 52% female). The REDs Clinical Assessment Tool (CAT2) was used to determine REDs risk. HR- pQCT scans of the non-dominant radius and left tibia were analyzed upon REDs risk grouping.ResultsSeventeen athletes (17%; 71% female) were at-risk based on the REDs CAT2. After covarying for lean mass, odds ratios (OR) suggested higher likelihood of REDs risk classification for athletes with low cortical thickness, cortical area, total vBMD, and bone strength.ConclusionsImpaired total vBMD, bone strength and cortical bone parameters were approximately twice as likely (OR: 1.9-3.0) in athletes at-risk of REDs. Results agree with the consensus statement that HR-pQCT may identify impaired bone health in athletes at-risk of REDs. Future directions should use HR-pQCT to explore REDs risk longitudinally, utilizing bone change over time as this may provide greater insight. Using advanced imaging to explore REDs risk in a population of winter high-performance athletes is novel.
Evaluating the clinical utility of hand performance information from at-home egocentric video in outpatient neurorehabilitation
Authors: Kadambi Adesh , Manzone Damian M. , Zariffa José 
Published: September 2024

AbstractBackgroundRestoring hand function is a primary focus of neurorehabilitation after stroke and spinal cord injury. However, monitoring hand use outside the clinic remains challenging. This study aims to evaluate how therapists perceive and would utilise information from a clinical decision support system (CDSS) that uses egocentric video to monitor patients’ hand use at home.MethodsFive patient-therapist dyads were recruited. Patients recorded daily activities using head-mounted cameras. Therapists reviewed dashboards of processed video data from their patients and completed semi-structured interviews and structured questionnaires. A mixed-methods approach with thematic analysis was used to evaluate the CDSS’s clinical usefulness.ResultsTherapists preferred video footage over graphical data, valuing its rich insights into their patients’ real-world activities. The information was perceived as useful for understanding patient performance at home and potentially influencing therapy planning.ConclusionsThis study demonstrates the potential of using egocentric video to inform clinical decision-making in neurorehabilitation, particularly for hand function. Therapists found the CDSS valuable for assessing real-world hand use but noted implementation challenges. Despite this, therapists across technical familiarity levels expressed trust in the system and willingness to use it regularly, indicating it could enhance their ability to tailor therapy plans to patients’ real-world activities.
Transcriptional memories mediate the plasticity of sulfide stress responses to enable acclimation inUrechis unicinctus
Authors: Zhang Wenqing , Liu Danwen , Yang Heran , Yang Tianya , Zhang Zhifeng , Ma Yubin 
Published: September 2024

AbstractTo cope with environmental stresses, organisms often adopt a memory response upon primary stress exposure to facilitate a quicker and/or stronger reaction to recurring stresses. Somatic stress memory is essential in dealing with contemporary stress. The earliest sign of somatic stress memory is a change in gene transcription levels, which alters physiology and phenotype to better cope with stress. Sulfide is a common environmental pollutant; however, some organisms have successfully colonized sulfur-rich environments. Whether stress memory plays important role in sulfide stress adaptation remains unclear. In this study, to determine whetherUrechis unicinctus, a sulfur-tolerant organism, retains the memory of previous sulfide stress, we simulated a repetitive sulfide stress/recovery system. The results showed that the tolerance ofU. unicinctusto sulfide stress was significantly increased after priming with 50 µM sulfide. Further, transcriptional memory genes (TMGs) involved in regulating sulfide stress memory were identified, classified according to their expression patterns, and functionally analyzed. TMGs involved in sulfide metabolism, sugar metabolism, and protein homeostasis pathway showed an enhanced response, whereas those related to DNA repair pathway demonstrated a modified response pattern. Our study indicated thatU. unicinctusretains memory of sulfide stress priming, which mediates plasticity to accelerate sulfide stress adaptation.
Phylogenomics and metabolic engineering reveal a conserved gene cluster in Solanaceae plants for withanolide biosynthesis
Authors: Hakim Samuel Edward , Choudhary Nancy , Malhotra Karan , Peng Jian , Arafa Ahmed , Bültemeier Arne , Friedhoff Ronja , Bauer Maximilian , Witte Claus-Peter , Herde Marco , Heretsch Philipp , Pucker Boas , Franke Jakob 
Published: September 2024

AbstractWithanolides are steroidal lactones from nightshade (Solanaceae) plants. Of the over 1,200 known representatives, many possess potent biological activities, but their drug potential has not been fully realised up until now. A central obstacle is the limited availability of minor withanolides, caused by a lack of knowledge about the underlying biosynthetic pathways. Here, we combine phylogenomics with metabolic engineering to overcome this limitation. By sequencing the genome of the medicinal plant and archetypical withanolide producer ashwagandha (Withania somnifera) and comparing the genome sequences of nine Solanaceae species, we discovered a conserved gene cluster for withanolide biosynthesis, consisting of two sub-gene clusters which differ in their expression patterns. To investigate the functions of the encoded enzymes, we established metabolic engineering platforms in yeast (Saccharomyces cerevisiae) and the model plantNicotiana benthamiana. This allowed us to reconstitute the first three oxidative steps of withanolide biosynthesis, catalysed by the cytochrome P450 monooxygenases CYP87G1, CYP88C7, and CYP749B2, leading to the aglycone of the known compound withanoside V. Our work sets the basis for the biotechnological production of withanolides in heterologous hosts and will therefore help to fully harness the drug potential of these plant steroids in the future.
The snoRNP chaperone snR190 and the Npa1 complex form a macromomecular assembly required for 60S ribosomal subunit maturation
Authors: Hamze Hussein , Jaafar Mariam , Khreiss Ali , Dominique Carine , Bourdeaux Jessie , Méndez-Godoy Alfonso , Kressler Dieter , Humbert Odile , Albert Benjamin , Henras Anthony K. , Henry Yves 
Published: September 2024

AbstractThe early steps of large-ribosomal-subunit assembly feature among the least understood steps of ribosome synthesis in eukaryotes. InSaccharomyces cerevisiae, the snR190 box C/D snoRNP chaperone and the Npa1 complex, composed of the α-solenoid scaffold proteins Npa1 and Npa2, the DEAD-box helicase Dbp6, the RNA-binding protein Nop8 and Rsa3, are likely involved in early 25S rRNA folding events. Here, we report for the first time the existence outside pre-ribosomal particles of an independent macromolecular assembly constituted by the Npa1 complex and the snR190 snoRNP chaperone. Nop8 mediates the formation of this assembly and can associate on its own with free snR190. Moreover, Nop8 RRM domain helps tether the snR190 snoRNP to pre-ribosomal particles. snR190 features a specific central stem-loop structure, which is required for high-affinity binding between free snR190 and the Npa1 complex. Deleting this extension does not prevent snR190 association with pre-ribosomal particles but impairs snR190 activity in early pre-rRNA processing events. This work establishes the importance of association with auxiliary protein complexes for optimum snoRNP chaperone activity during rRNA folding events.
Characterizing the soil microbial community associated with the fungal pathogenCoccidioides immitis
Authors: Radosevich Molly , Head Jennifer , Couper Lisa , Gomez-Weaver Amanda , Camponuri Simon , Montoya Liliam , Taylor John , Remais Justin 
Published: September 2024

AbstractCoccidioidomycosis is a fungal disease affecting humans and other mammals, caused by environmental pathogens of the genusCoccidioides. Understanding the ecological factors that shape the distribution ofCoccidioidesin soils is important for minimizing the risk of human exposure, though this remains challenging due to the pathogen’s highly variable spatial distribution. Here, we examined associations between the soil microbial community andCoccidioides immitispresence within the Carrizo Plain National Monument—a minimally disturbed grassland ecosystem, and the site of a longitudinal study examining the effects of rodents and their burrows onC. immitispresence in soils. Using internal transcribed spacer 2 (ITS2) and 16S sequencing to characterize the soil fungal and bacterial communities, we found over 30 fungal species, including several other members of the Onygenales order, that co-occurred withCoccidioidesmore frequently than expected by chance.Coccidioides-positive samples were significantly higher in microbial diversity than negative samples, an association partly driven by higherCoccidioidespresence within rodent burrows compared to surface soils. Soil source (i.e.,rodent burrow versus surface soil) explained the largest amount of variation in bacterial and fungal community diversity and composition, with soils collected from rodent burrows having higher microbial diversity than those collected from adjacent surface soils. While prior evidence is mixed regarding associations betweenCoccidioidesand microbial diversity, our study suggests that favorable microhabitats such as rodent burrows can lead to a positive association between soil diversity andCoccidioidespresence, particularly in otherwise resource-limited natural environments.
HU promotes higher-order chromosome organisation and influences DNA replication rates inStreptococcus pneumoniae
Authors: Mazzuoli Maria-Vittoria , van Raaphorst Renske , Martin Louise , Bock Florian , Thierry Agnès , Marbouty Martial , Waclawikova Barbora , Stinenbosch Jasper , Koszul Romain , Veening Jan-Willem 
Published: September 2024

AbstractNucleoid-associated proteins (NAPs) are crucial for maintaining chromosomal compaction and architecture and are actively involved in DNA replication, recombination, repair, and gene regulation. In the opportunistic pathogenStreptococcus pneumoniae,HU is the only identified NAP, and its role in chromosome conformation and other essential processes has not yet been investigated. Here, we use a multi-scale approach to explore the role of HU in chromosome conformation and segregation dynamics. By combining superresolution microscopy and whole-genome binding analysis, we describe the nucleoid as a dynamic structure where HU binds transiently across the entire nucleoid, with a preference for the origin of replication over the terminus. Reducing cellular HU levels impacts nucleoid maintenance and disrupts robust nucleoid scaling with cell size. This effect is similar to the distortion caused by fluoroquinolone-antibiotics, supporting earlier observations that HU is essential for maintaining DNA supercoiling. Furthermore, in cells lacking HU, the replication machinery is misplaced, and cells are unable to initiate and proceed with on-going replication. Chromosome conformation capture (Hi-C) experiments revealed that HU is required to maintain cohesion between the two chromosomal arms, in a similar way to the structural maintenance of the chromosome complex SMC. Together, we show that by promoting long-range chromosome interactions and supporting the architecture of the domain encompassing the origin, HU is fundamental for chromosome integrity and the intimately related processes of chromosome replication and segregation.Graphical abstract
Interaction between climatic variation and pathogen diversity shape endemic disease dynamics in the agricultural settings
Authors: Bhandari Rishi , Kaur Amanpreet , Russell Ivory , Romanus Ogonnaya Michael , Brokaw Destiny , Keinath Anthony P , Snipes Zachary , Rollins Philip , Baugher Nettie , Meadows Inga , Torrance Ty Nicholas , Dutta Bhabesh , Sikora Edward , Molinari Roberto , Soubeyrand Samuel , Potnis Neha 
Published: September 2024

AbstractRecurring outbreaks caused by endemic pathogens continue to pose problems in managing plant, wildlife, livestock and human health. Understanding how these outbreaks unfold and what drives the variability in disease epidemics across space and time is less understood, especially in the agricultural settings. In this study, we investigated the contribution of pathogen genetic diversity, climatic variation and their interaction towards disease dynamics, with an integrative approach grounded on multitype, high resolution sequencing data and analysis techniques. This investigation was carried out for bacterial spot disease epidemic by surveying tomato fields for bacterial pathogen (Xanthomonas perforans) across southeastern US over a span of three years. The strength of epidemic severity varied across space and time in the agricultural fields. Disease severity was positively associated with strain diversity, and was linked to environmental fluctuations, specifically, large variation and extreme changes in certain climatic factors. Strain-resolved metagenomics approach revealed that co-existence of multiple pathogen lineages was common in the individual fields, although accompanied by differential lineage dynamics. The co-occurring lineages displayed environmentally dependent fitness contributions. By tracing allelic frequencies in pathogen populations across temporal scales, we find evidence for asynchronous allele cycling across seasons, hinting at the presence of adaptive single-nucleotide polymorphisms (SNPs) being polymorphic in space in response to seasonality. Despite this pathogen heterogeneity, we identified positively selected loci under parallel evolution, which may explain the nature of selection pressures experienced by the pathogen. While single pathogen lineage is assumed to dominate the host in the agricultural settings, our findings challenge this notion by demonstrating genetic diversity in the pathogen population observed within a single field and linking it to the disease dynamics. Our results explain the role of pathogen genetic diversity, climate-dependent compositional dynamics, and differential fitness contributions in dictating the variability of disease epidemics in the agricultural settings. Such findings will be invaluable for building predictive models in disease epidemiology. Our high-resolution combinatorial approach exploiting high- resolution sequence data, metadata types and analysis tools, is general enough to finely investigate disease epidemics at large scales in diverse case-studies concerning plant, animal and human health.