Reference Resource Research Articles

A Comparative Evaluation of Large Language Model Utility in Neuroimaging Clinical Decision Support.

Imaging utilization has increased dramatically in recent years, and at least some of these studies are not appropriate for the clinical scenario. The development of large language models (LLMs) may address this issue by providing a more accessible reference resource for ordering providers, but their relative performance is currently understudied. Evaluate and compare the relative appropriateness and usefulness of imaging recommendations generated by eight publicly available models in response to neuroradiology clinical scenarios. Twenty-four common neuroradiology clinical scenarios were selected which often yield suboptimal imaging utilization. Questions were crafted to assess the ability of LLMs to provide accurate and actionable advice. The LLMs were assessed in August 2023 using natural-language 1-2 sentence queries requesting advice about optimal image ordering given certain clinical parameters. Eight of the most well-known LLMs were chosen for evaluation: ChatGPT, GPT4, Bard (Versions 1 and 2), Bing Chat, Llama 2, Perplexity, and Claude. The models were graded by three fellowship-trained neuroradiologists on whether their advice was "optimal" or "not optimal" according to the ACR Appropriateness Criteria or the New Orleans Head CT Criteria. The raters also ranked the models based on the appropriateness, helpfulness, concision, and source-citations in their response. The models varied in their ability to deliver an "optimal" recommendation based on these scenarios as follows: ChatGPT (20/24), GPT4 (23/24), Bard 1 (13/24), Bard 2 (14/24), Bing Chat (14/24), Llama (5/24), Perplexity (19/24), and Claude (19/24). The median ranks of the LLMs were as follows: ChatGPT (3), GPT4 (1.5), Bard 1 (4.5), Bard 2 (5), Bing Chat (6), Llama (7.5), Perplexity (4), and Claude (3). Characteristic errors are described and discussed. GPT-4, ChatGPT, and Claude generally outperformed Bard, Bing Chat, and Llama 2. This study evaluates the performance of a greater variety of publicly available LLMs in settings that more closely mimic real-world use cases as well as discussing the practical challenges of doing so. This is the first study to evaluate and compare a wide range of publicly available LLMs to determine appropriateness of their neuroradiology imaging recommendations.

Full-length transcriptome assembly of black amur bream (Megalobrama terminalis) as a reference resource.

The genus Megalobrama holds significant economic value in China, with M. terminalis (Black Amur bream) ranking second in production within this group. However, lacking comprehensive genomic and transcriptomic data has impeded research progress. This study aims to fill this gap through an extensive transcriptomic analysis of M. terminalis. We utilized PacBio Isoform Sequencing to generate 558,998 subreads, totaling 45.52 Gb, which yielded 22,141 transcripts after rigorous filtering and clustering. Complementary Illumina short-read sequencing corrected 967,114 errors across these transcripts. Our analysis identified 12,426 non-redundant isoforms, with 11,872 annotated in various databases. Functional annotation indicated 11,841 isoforms matched entries in the NCBI non-redundant protein sequences database. Gene Ontology analysis categorized 10,593 isoforms, revealing strong associations with cellular processes and binding functions. Additionally, 8203 isoforms were mapped to pathways in the Kyoto Encyclopedia of Genes and Genomes, highlighting significant involvement in immune system processes and complement cascades. We notably identified key immune molecules such as alpha-2-macroglobulin and complement component 3, each with multiple isoforms, underscoring their potential roles in the immune response. Our analysis also uncovered 853 alternative splicing events, predominantly involving retained introns, along with 672 transcription factors and 426 long non-coding RNAs. The high-quality reference transcriptome generated in this study provides a valuable resource for comparative genomic studies within the Megalobrama genus, supporting future research to enhance aquaculture stocks.

VFDB 2025: an integrated resource for exploring anti-virulence compounds.

With the escalating crisis of bacterial multidrug resistance, anti-virulence therapeutic strategies have emerged as a highly promising alternative to conventional antibiotic treatments. Anti-virulence compounds are specifically designed to target virulence factors (VFs), disarming pathogens without affecting bacterial growth and thus reduce the selective pressure for resistance development. However, due to the complexity of bacterial pathogenesis, no anti-virulence small molecules have been approved for clinical use thus far, despite the documentation of hundreds of potential candidates. To provide valuable reference resources for drug design, repurposing, and target selection, the virulence factor database (VFDB, http://www.mgc.ac.cn/VFs/) has systematically collected public data on anti-virulence compounds through extensive literature mining, and further integrated this information with its existing knowledge of bacterial VFs. To date, the VFDB has curated a comprehensive dataset of 902 anti-virulence compounds across 17 superclasses reported by 262 studies worldwide. By cross-linking the current knowledge of bacterial VFs with information on relevant compounds (e.g. classification, chemical structure, molecular targets and mechanisms of action), the VFDB aims to bridge the gap between chemists and microbiologists, providing crucial insights for the development of innovative and effective antibacterial therapies to combat bacterial infections and address antibiotic resistance.

Chromosome-level genome assembly of the cashmere goat

The goat, an early domesticated ruminant, is a reliable source of cashmere, meat and milk in global agricultural production. Despite this, the genome of cashmere-rich goats has yet to be characterized. Here, we assembled the nearly complete genome of a cashmere goat from a highly economically valuable Inner Mongolian Cashmere buck, utilizing a combination of PacBio HiFi, ONT ultra-long reads, and Hi-C technologies. The size of this genome is 2.76 Gb, with a contig N50 of 95.22 Mb. All assembled sequences were anchored onto 29 autosomes and both sex chromosomes, with only two gaps present on the X chromosome. We identified 1,333.29 Mb (48.26%) of repetitive sequences and predicted 22,480 protein-coding genes. Assembly quality assessment of the genome demonstrated that our assembled cashmere goat genome surpasses the continuity, completeness, and accuracy of other published goat genomes. Taken together, we provided the first cashmere goat assembly, bridging the gap in the genome of important economic breeds of domestic goats, and providing a valuable reference resource for goat genetics and genome research.

Information is cheap, but filtering is costly: Congressional investment in reference resources

AbstractLawmakers who can supply themself with information to manage complex problems are at an advantage, but equally important is the filtering and contextualizing of applicable information. Members of Congress manage a deluge of policy and political information, and this short paper examines one strategy members of Congress use to mitigate that burden—by investing in reference material and news media to filter and summarize the policymaking environment. Using congressional disbursement data from the 116th and 117th Congress, I explain how institutional experience is associated with an office's choice to invest in more information filtering. Freshman members of the House are more likely to turn to news media or publications to provide insight into the congressional agenda, offer political context, and prioritize issues of importance. Reference investment is not tied to partisanship, ideology, lawmaking capacity, or previous office, but those junior offices who need to get up to lawmaking speed invest in external information filtering. These results illuminate how central institutional knowledge is to lawmaking in Congress, and how much an office is willing to invest to mitigate that weakness.

New Modes of Practice: A Framework Analysis of School Nurses' Accounts of Working With Children and Young People During COVID-19.

To identify new and accelerated modes of practice used by school nurses during the COVID pandemic. To create a quick reference infographic bringing together experiential evidence on the range and considerations regarding different modes of practice for use by the school nursing community of practice. A descriptive qualitative secondary data analysis of open-ended questions in a survey, and focus groups with school nurses. The pragmatic aim was to focus on changes in school nurse modes of practice to ensure continued engagement with children and young people, and school nurses' experience of the benefits and challenges of these modes of practice. Data were collected from 98 school nurse participants across a United Kingdom-wide survey (n78) in April to May 2022, and focus groups (n20) in June to July 2022, within the School Nursing in the Time of COVID project. Data from the seven open-ended questions in the survey and four questions from the focus group were analysed using the framework approach. Modes of practice fell into two categories: individual assessment and support (video-calling platforms, telephone contact, virtual messaging, walk-and-talks and home visits) and group support (wellbeing approaches, social media). Considerations for these modes rooted in school nurses' experience are described. Interpretations were used to create the summarising evidence-based infographic as a quick reference resource for school nurses. There was no 'one size fits all' approach. The modes used by school nurses were adopted or developed out of necessity or resource availability and in response to the specific needs of individuals or groups. The developed infographic provides a quick reference guide to deliver the expressed need for knowledge exchange within the school nursing community by participants in the original studies and can be used to inform current school nurse practice. The developed evidence-based infographic has stand-alone value. It has the potential to raise awareness of the range of different strategies that can be used to facilitate and/or enhance engagement with children and young people, equip school nurses with knowledge to foster innovative and responsive practice and aid critical reflection in a complex post-pandemic landscape. The infographic is a unique resource and is a first step in knowledge exchange based on experiential learning. The resource will be used as the foundation for future work to develop a co-created training resource for school nurse students (undertaking the Specialist Community Public Health Nurses course) and/or continuing professional development resource for established school nurses. This study has been conducted and reported in accordance with COREQ guidelines for qualitative research. A consultation group was closely involved with the planning, conduct and analysis of the original studies. This group consisted of representatives from professional organisations SAPHNA (School and Public Health Nurses Association) and the CPHVA (Community Practitioners' and Health Visitors' Association), a school nurse and a member of the public. SAPHNA have continued in their consultative role for this study and has provided content and usability feedback regarding the infographic. Early findings have been presented to the SN community of practice, and feedback invited, through presentation separately at the CPHVA and SAPHNA annual conference.

The authority file of names of agricultural organizations: Features and development

The experience of the CSAL in creating, maintaining and using the authority file of names of sectoral organizations is discussed. The characteristics of the authority file and information sources are given, methodological solutions for data generation are considered. The authority file is used to improve the quality of bibliographic entries by unifying access points, improving the processes of in- formation exchange and retrieval. Based on the authority file, the reference and information resource has been formed – the database “Authority File of Names of Scientific Institutions of the Agroindustrial Complex” is freely accessible via the Library’s website. The authority data on the names of scientific agricultural institutions include reference information and historical data, provide access to bibliographic information, connect resources within the single data network and enable to navigate the CSAL resources. The development of the authority file content and technology is reviewed. The content of the authority file is updated on the basis of the library collection and monitoring of data on organizations in external sources; besides, the new entries for the names of modern scientific agrarian institutions and agricultural institutions established in Russia in the 19th century are created. The OPAC-Global ILS replaced the earlier CSAL automated library and information system software, therefore the authority file was transferred into the new software environment.

Enhancing Junior Doctors' Preparedness and Satisfaction in Trauma and Orthopaedics: A Quality Improvement Project With the Development of a Comprehensive Guidebook.

Junior doctors often feel underprepared for their trauma and orthopaedics (T&O) rotation due to limited exposure during medical school and inadequate support. This project aimed to enhance junior doctors' preparedness and satisfaction during their T&O rotation by developing a comprehensive guidebook that addresses key orthopaedic knowledge and logistical challenges. A quality improvement project (QIP) was conducted at Ysbyty Gwynedd Hospital. Initial surveys identified factors contributing to poor experiences during the trauma and orthopaedics rotation, including limited knowledge of orthopaedic emergencies and a lack of useful reference resources. A guidebook was developed and refined through multiple plan-do-study-act (PDSA) cycles. The guidebook covered topics such as orthopaedic emergencies, common injuries, referral pathways, and hospital logistics, presented in an accessible flowchart format. The primary objective of achieving 75% satisfaction among junior doctors was successfully met, with satisfaction increasing from four (40%) to eight (80%) doctors in the most recent survey. Secondary outcomes included a marked improvement in the understanding of quality improvement projects, rising from three (30%) to eight (80%) doctors. Orthopaedic knowledge also saw a significant enhancement, increasing from four (40%) to nine (90%) doctors. Confidence in handling night on-call duties improved dramatically, with all 10 doctors (100%) reporting increased confidence, compared to four (40%) doctors initially.Additionally, seven doctors (70%) expressed a greater interest in pursuing a career in orthopaedic surgery. The comprehensive guidebook significantly improved junior doctors' preparedness and satisfaction during their T&O rotation. While the guidebook is a valuable resource, ongoing mentorship and hands-on experience remain essential for long-term success. Replication of this project across other departments and hospitals is recommended to assess its broader applicability and impact.

Autonomic nervous system and viscera-related responses to manual therapy: A narrative overview

BackgroundManual therapy (MT) has long-held that it physiologically impacts autonomic nervous system (ANS) and viscera-related function. This narrative review is intended to serve as a consolidated interdisciplinary resource of original studies related to physiological effects of MT as it relates to the ANS for MT clinicians and researchers new to this MT-related topic. ObjectiveThis review seeks to identify ANS and viscera-related physiological responses to MT interventions using search terms commonly used by chiropractic, massage, osteopathic, physical therapy, and structural integration clinicians and to provide a quick reference resource of original MT-related studies investigating ANS effects. MethodsFor this interdisciplinary review, the search was limited to the largest and most commonly used database (PubMed) between years 2000 and 2024, with a focus on direct ANS-related physiological outcomes. Unlike systematic reviews, assessment of scientific rigor and potential bias of included articles was beyond the scope and purpose of the current work. ResultsOriginal MT-related studies provide mixed evidence with regards to immediate and/or short term ANS and/or viscera-related responses on blood pressure, heart rate variability, skin conductance/temperature, respiratory and lymphatic changes. ConclusionsThis review identified a large number of MT and ANS-related original research in PubMed. Careful study of original MT-related research is needed with particular attention focused on the standardization of MT methodological approaches, appropriate controls, study design, appropriate populations, MT techniques, and anatomical site delivery so as to design more rigorous studies in order to arrive at definitive conclusions regarding direct effects of MT on the ANS.

HPC-T-Annotator: an HPC tool for de novo transcriptome assembly annotation

BackgroundThe availability of transcriptomic data for species without a reference genome enables the construction of de novo transcriptome assemblies as alternative reference resources from RNA-Seq data. A transcriptome provides direct information about a species’ protein-coding genes under specific experimental conditions. The de novo assembly process produces a unigenes file in FASTA format, subsequently targeted for the annotation. Homology-based annotation, a method to infer the function of sequences by estimating similarity with other sequences in a reference database, is a computationally demanding procedure.ResultsTo mitigate the computational burden, we introduce HPC-T-Annotator, a tool for de novo transcriptome homology annotation on high performance computing (HPC) infrastructures, designed for straightforward configuration via a Web interface. Once the configuration data are given, the entire parallel computing software for annotation is automatically generated and can be launched on a supercomputer using a simple command line. The output data can then be easily viewed using post-processing utilities in the form of Python notebooks integrated in the proposed software.ConclusionsHPC-T-Annotator expedites homology-based annotation in de novo transcriptome assemblies. Its efficient parallelization strategy on HPC infrastructures significantly reduces computational load and execution times, enabling large-scale transcriptome analysis and comparison projects, while its intuitive graphical interface extends accessibility to users without IT skills.

Identifying cooperating cancer driver genes in individual patients through hypergraph random walk

ObjectiveIdentifying cancer driver genes, especially rare or patient-specific cancer driver genes, is a primary goal in cancer therapy. Although researchers have proposed some methods to tackle this problem, these methods mostly identify cancer driver genes at single gene level, overlooking the cooperative relationship among cancer driver genes. Identifying cooperating cancer driver genes in individual patients is pivotal for understanding cancer etiology and advancing the development of personalized therapies. MethodsHere, we propose a novel Personalized Cooperating cancer Driver Genes (PCoDG) method by using hypergraph random walk to identify the cancer driver genes that cooperatively drive individual patient cancer progression. By leveraging the powerful ability of hypergraph in representing multi-way relationships, PCoDG first employs the personalized hypergraph to depict the complex interactions among mutated genes and differentially expressed genes of an individual patient. Then, a hypergraph random walk algorithm based on hyperedge similarity is utilized to calculate the importance scores of mutated genes, integrating these scores with signaling pathway data to identify the cooperating cancer driver genes in individual patients. ResultsThe experimental results on three TCGA cancer datasets (i.e., BRCA, LUAD, and COADREAD) demonstrate the effectiveness of PCoDG in identifying personalized cooperating cancer driver genes. These genes identified by PCoDG not only offer valuable insights into patient stratification correlating with clinical outcomes, but also provide an useful reference resource for tailoring personalized treatments. ConclusionWe propose a novel method that can effectively identify cooperating cancer driver genes for individual patients, thereby deepening our understanding of the cooperative relationship among personalized cancer driver genes and advancing the development of precision oncology.

BLEND: Probabilistic Cellular Deconvolution with Automated Reference Selection.

Cellular deconvolution aims to estimate cell type fractions from bulk transcriptomic and other omics data. Most existing deconvolution methods fail to account for the heterogeneity in cell type-specific (CTS) expression across bulk samples, ignore discrepancies between CTS expression in bulk and cell type reference data, and provide no guidance on cell type reference selection or integration. To address these issues, we introduce BLEND, a hierarchical Bayesian method that leverages multiple reference datasets. BLEND learns the most suitable references for each bulk sample by exploring the convex hulls of references and employs a "bag-of-words" representation for bulk count data for deconvolution. To speed up the computation, we provide an efficient EM algorithm for parameter estimation. Notably, BLEND requires no data transformation, normalization, cell type marker gene selection, or reference quality evaluation. Benchmarking studies on both simulated and real human brain data highlight BLEND's superior performance in various scenarios. The analysis of Alzheimer's disease data illustrates BLEND's application in real data and reference resource integration.

Utilising fatty acid prediction equations and mid‐infrared spectroscopy to estimate the seasonality changes in bovine milk from pasture‐based systems

The aim of this study was to utilise mid‐infrared spectroscopy with fatty acid (FA) predictions to characterise the seasonality‐associated changes to the FA profile of milk from Irish spring‐calving pasture‐based dairy cow production systems. A total of 546 454 individual milk records were collected from the Years 2015 to 2020, from 264 003 cows in 2400 commercial dairy farms. Significant changes occur to the predicted FA profile of milk across the year, such as increases in unsaturated FAs including C18:1 n‐9 until April. This can be associated with the increasing proportion of fresh pasture in the cows' diet, and a decrease between September and October as the cows begin to transition indoors for the winter period. The opposite trend was noted for saturated FAs and in particular C16:0, where proportions decreased until April and increased between September and November. Milk produced between April and September also coincided with the lowest spreadability index, indicating a more beneficial milk FA profile for more spreadable butter texture during this period. This work provides a valuable reference resource at a national level of the FA profile of milk from pasture‐based spring‐calving dairy systems.

Genomic Reference Resource for African Cattle: Genome Sequences and High-Density Array Variants

The diversity in genome resources is fundamental to designing genomic strategies for local breed improvement and utilisation. These resources also support gene discovery and enhance our understanding of the mechanisms of resilience with applications beyond local breeds. Here, we report the genome sequences of 555 cattle (208 of which comprise new data) and high-density (HD) array genotyping of 1,082 samples (537 new samples) from indigenous African cattle populations. The new sequences have an average genome coverage of ~30X, three times higher than the average (~10X) of the over 300 sequences already in the public domain. Following variant quality checks, we identified approximately 32.3 million sequence variants and 661,943 HD autosomal variants mapped to the Bos taurus reference genome (ARS-UCD1.2). The new datasets were generated as part of the Centre for Tropical Livestock Genetics and Health (CTLGH) Genomic Reference Resource for African Cattle (GRRFAC) initiative, which aspires to facilitate the generation of this livestock resource and hopes for its utilisation for complete indigenous breed characterisation and sustainable global livestock improvement.

Equus in Online Mendelian Inheritance in Animals (OMIA).

Online Mendelian Inheritance in Animals (OMIA is a freely available information resource, which includes information for Equus inherited traits/diseases (collectively called phenes). The database focuses on Mendelian traits and their likely causal variants (mutations). Some of these Mendelian traits are favored by humans, e.g., coat color, while others are diseases. Additions to OMIA are based on publications of peer-reviewed research. Maintaining up-to-date information in OMIA is a challenge, owing to the multiplicity of species, the increase in the number of relevant publications, and as reference genomes and methods of citation continue to evolve. This challenge has been successfully aided by contributions from scientists from around the world. In some cases, those scientists are faculty members who charge their students with curation as an educational activity. Recently, OMIA has introduced computerized lists of standardized names and synonyms (called ontologies) for breeds of Equus and other animals and for phene categories. These ontologies facilitate increased connectivity between OMIA and other online resources. OMIA is and will continue to be a major reference resource for Mendelian phenes in the genus Equus.

Towards precision cancer medicine for Aboriginal and Torres Strait Islander cancer health equity.

Delivering cancer control at scale for Aboriginal and Torres Strait Islander communities is a national priority that requires Aboriginal and Torres Strait Islander leadership and codesign, as well as significant involvement of the Aboriginal community-controlled health sector. The unique genomic variation observed among Aboriginal and Torres Strait Islander peoples may have implications for standard and precision medicine. Yet, Aboriginal and Torres Strait Islander peoples are absent from, or under-represented within, human reference genome resources, genomic studies, cancer studies, cancer cell lines, patient-derived xenografts and cancer clinical trials. Genomics-guided precision cancer medicine offers an opportunity to reduce cancer health disparities experienced by Aboriginal and Torres Strait Islander peoples through personalising prevention, diagnosis, treatment and long term management. Here, we describe what is required to ensure that Aboriginal and Torres Strait Islander peoples can receive the benefits of precision cancer medicine. Equity of access to care, an Aboriginal and Torres Strait Islander cancer workforce, and appropriate genome reference resources are important for safe and effective cancer medicine. Building Indigenous data sovereignty principles and Aboriginal and Torres Strait Islander governance into research is required to protect Aboriginal and Torres Strait Islander rights and collective interests. Aboriginal and Torres Strait Islander community engagement should be undertaken to develop an understanding of the unique cultural and ethical considerations for precision cancer research. Local and national genomic health research guidelines are needed to define a consensus best practice in genomics research with Aboriginal and Torres Strait Islander peoples.

CmPIF8-CmERF27-CmACS10-mediated ethylene biosynthesis modulates red light-induced powdery mildew resistance in oriental melon.

Powdery mildew is a serious fungal disease in protected melon cultivation that affects the growth, development and production of melon plants. Previous studies have shown that red light can improve oriental melon seedlings resistance to powdery mildew. Here, after inoculation with Podosphaera xanthii, an obligate fungal pathogen eliciting powdery mildew, we found that red light pretreatment increased ethylene production and this improved the resistance of melon seedlings to powdery mildew, and the ethylene biosynthesis gene CmACS10 played an important role in this process. By analysing the CmACS10 promoter, screening yeast one-hybrid library, it was found that CmERF27 positively regulated the expression of CmACS10, increased powdery mildew resistanceand interacted with PHYTOCHROME INTERACTING FACTOR8 (CmPIF8) at the protein level to participate in the regulation of ethylene biosynthesis to respond to the red light-induced resistance to P. xanthii, Furthermore, CmPIF8 also directly targeted the promoter of CmACS10, negatively participated in this process. In summary, this study revealed the specific mechanism by which the CmPIF8-CmERF27-CmACS10 module regulates red light-induced ethylene biosynthesis to resist P. xanthii infection, elucidate the interaction between light and plant hormones under biological stress, provide a reference and genetic resources for breeding of disease-resistant melon plants.

EXPLORING REGISTER VARIATION IN APPS AKULAKU: A SOCIOLINGUISTICS STUDY

The purpose of the research are (1) to identify the types of registers and (2) to describe the language functions used by the marketing community in Akulaku marketplace apps. This research uses qualitative methods to analyze data and use descriptive methods to explain the data. The object of this research is the written register terms found in Akulaku Marketplace apps. The theories used to classify the data are according to Halliday and Hasan's (1989) theory of register types and Jakobson's (1960) theory of language functions. According to this research, there are 90 data analyzed. The data is categorized into two types of registers, they are closed register 41 data (45,5%) and open register 49 data (54,5%). The functions of the register are referential function 14 data (15,5%), emotive function 20 data (22,2%), conative function 27 data (30%), phatic function 11 data (12,2%), poetic function 11 data or (12.2%) and metalingual function 7 data or (7,7%). This study is expected to increase knowledge of the types of registers and their functions used in marketplace buying and selling activities, while at the same time serving as a valuable resource for reference in education and, in addition, studies in linguistics, mainly in the subject of sociolinguistics.

The Carthamus tinctorius L. genome sequence provides insights into synthesis of unsaturated fatty acids

Domesticated safflower (Carthamus tinctorius L.) is a widely cultivated edible oil crop. However, despite its economic importance, the genetic basis underlying key traits such as oil content, resistance to biotic and abiotic stresses, and flowering time remains poorly understood. Here, we present the genome assembly for C. tinctorius variety Jihong01, which was obtained by integrating Oxford Nanopore Technologies (ONT) and BGI-SEQ500 sequencing results. The assembled genome was 1,061.1 Mb, and consisted of 32,379 protein-coding genes, 97.71% of which were functionally annotated. Safflower had a recent whole genome duplication (WGD) event in evolution history and diverged from sunflower approximately 37.3 million years ago. Through comparative genomic analysis at five seed development stages, we unveiled the pivotal roles of fatty acid desaturase 2 (FAD2) and fatty acid desaturase 6 (FAD6) in linoleic acid (LA) biosynthesis. Similarly, the differential gene expression analysis further reinforced the significance of these genes in regulating LA accumulation. Moreover, our investigation of seed fatty acid composition at different seed developmental stages unveiled the crucial roles of FAD2 and FAD6 in LA biosynthesis. These findings offer important insights into enhancing breeding programs for the improvement of quality traits and provide reference resource for further research on the natural properties of safflower.

Unlocking the future of patient Education: ChatGPT vs. LexiComp® as sources of patient education materials

BackgroundChatGPT is a conversational artificial intelligence technology that has shown application in various facets of healthcare. With the increased use of AI, it is imperative to assess the accuracy and comprehensibility of AI platforms. ObjectiveThis pilot project aimed to assess the understandability, readability, and accuracy of ChatGPT as a source of medication-related patient education as compared with an evidence-based medicine tertiary reference resource, LexiComp®. MethodsPatient education materials (PEMs) were obtained from ChatGPT and LexiComp® for 8 common medications (albuterol, apixaban, atorvastatin, hydrocodone/acetaminophen, insulin glargine, levofloxacin, omeprazole, and sacubitril/valsartan). PEMs were extracted, blinded, and assessed by 2 investigators independently. The primary outcome was a comparison of the Patient Education Materials Assessment Tool-printable (PEMAT-P). Secondary outcomes included Flesch reading ease, Flesch Kincaid grade level, percent passive sentences, word count, and accuracy. A 7-item accuracy checklist for each medication was generated by expert consensus among pharmacist investigators, with LexiComp® PEMs serving as the control. PEMAT-P interrater reliability was determined via intraclass correlation coefficient (ICC). Flesch reading ease, Flesch Kincaid grade level, percent passive sentences, and word count were calculated by Microsoft® Word®. Continuous data were assessed using the Student’s t-test via SPSS (version 20.0). ResultsNo difference was found in the PEMAT-P understandability score of PEMs produced by ChatGPT versus LexiComp® [77.9% (11.0) vs. 72.5% (2.4), P=0.193]. Reading level was higher with ChatGPT [8.6 (1.2) vs. 5.6 (0.3), P < 0.001). ChatGPT PEMs had a lower percentage of passive sentences and lower word count. The average accuracy score of ChatGPT PEMs was 4.25/7 (61%), with scores ranging from 29% to 86%. ConclusionDespite comparable PEMAT-P scores, ChatGPT PEMs did not meet grade level targets. Lower word count and passive text with ChatGPT PEMs could benefit patients, but the variable accuracy scores prevent routine use of ChatGPT to produce medication-related PEMs at this time.