搜索结果：flag

In mammals, circadian rhythms are absent from embryonic stem (ES) cells and emerge during cellular differentiation, yet the profile of endogenous clock protein complexes in undifferentiated ES cells and differentiating cells remains unclear. Here we introduced 3×FLAG tags into endogenous Per1, Cry1, or Bmal1 locus in mouse ES cells to investigate core clock protein interactions before and during differentiation. The established 3×FLAG knock-in ES cells expressed the expected 3×FLAG-fusion proteins and displayed normal differentiation-coupled development of circadian gene expression rhythms. mRNA expression levels of core clock genes (Per1, Per2, Cry1, Cry2, Clock and Bmal1) were comparable between knock-in and parental cells across differentiation. The expression profiles of core clock proteins showed that PER1, CRY1/2, BMAL1, CKIδ but not CLOCK were expressed even in undifferentiated ES cells. Anti-FLAG co-immunoprecipitation revealed a progressive change in complex assembly: BMAL1 begins to interact with CLOCK, PER1, CRY1/2 and CKIδ from differentiation day 14 onward, coinciding with the emergence of circadian gene expression rhythms. In contrast, PER1 binds to CRY1/2 and CKIδ throughout the differentiation time course, including undifferentiated ES cells. These findings reveal the differentiation-coupled formation of the core clock protein complex, particularly at the interface between transcriptional activators and repressors, providing a mechanism for ensuring the emergence of robust circadian rhythms during ES cell differentiation.

As the two main variety groups in improved rice, IND (indica) and JAP (temperate japonica and tropical japonica), extensive studies have utilized (single-nucleotide polymorphisms) SNPs on 233 selected improved rice cultivars to analyze the genetic basis of agronomic traits during their improvement and to compare their similarities and differences. However, the roles of other types of variations, such as insertions and deletions (INDELs) and structural variations (SVs), remain relatively underexplored. Here, using resequencing data from 233 improved rice accessions (IND: 142, JAP: 91), we identified 811,646 INDELs and 16,231 SVs in IND, and 652,793 INDELs and 10,533 SVs in JAP. The abundance of INDELs and SVs decreased as their length increased in both variety groups. INDELs and SVs also showed an uneven distribution across the chromosomes of the two variety groups. In IND, 38.92% of INDELs and 44.1% of SVs were located within the 2 kb upstream and downstream of genes; in JAP, this proportion was 38.49% for INDELs and 43.22% for SVs. By performing genome wide association studies (GWAS) using phenotypic data of six agronomic traits (heading date, flag leaf length, flag leaf width, panicle number, plant height, and thousand grain weight) along with INDELs and SVs, we identified 3,222 significant IND-INDELs, 537 significant IND-SVs, 1,996 significant JAP-INDELs, and 286 significant JAP-SVs. Comparison of significant loci revealed that IND and JAP shared only one INDEL associated with flag leaf length and one SV associated with panicle number, suggesting distinct genetic architectures determined by INDELs and SVs for these traits in the two groups. Furthermore, haplotype analysis of candidate genes demonstrated that INDELs and SVs influence key functional genes, such as the gene TAD1 (IND-INDELs) in flag leaf length, RCN2 (IND-SVs) in heading date, PLS2 (JAP-INDELs) in plant height, and OsYLC2 (JAP-SVs) in leaf development. This study analyzed the variation patterns of INDELs and SVs during the improvement of IND and JAP varieties, and identified INDELs and SVs associated with agronomic traits. These findings will provide valuable genetic and material resources for rice breeding.

Secondary headaches require urgent recognition due to potentially devastating consequences if untreated. Despite established clinical "red flag" criteria, identifying patients needing immediate evaluation remains challenging in primary care. This study developed and evaluated a large language model (LLM)-based multi-agent clinical decision support system for interpretable secondary headache diagnosis. We first established 7 clinically relevant secondary headache red flag domains through manual review and synthesis of clinical guidelines. Based on these domains, we designed an LLM-based system using an orchestrator-specialist multi-agent architecture that decomposes diagnostic reasoning into 7 guideline-aligned agents corresponding to key red flag features. Each agent generates structured, evidence-grounded reasoning, coordinated by a central orchestrator. The system was evaluated on 90 expert-validated secondary headache cases and compared with a single-LLM baseline under 2 prompting strategies: question-based prompting (QPrompt) and guideline-based prompting (GPrompt). Five open-source LLMs (Qwen-8b, Qwen-14b, Qwen-30b, GPT-OSS-20b, and Llama-3.1-8b) were tested. The orchestrated multi-agent system with GPrompt achieved the highest red flag classification performance across models, measured by F1 score. Performance gains were consistent and more pronounced in smaller LLMs, suggesting that structured reasoning improves efficiency and accuracy beyond prompt engineering alone. The framework also produced transparent and guideline-aligned intermediate reasoning. Decomposing clinical reasoning into specialized agents enhances interpretability and diagnostic reliability compared with monolithic LLM approaches. Multi-agent orchestration provides a clinically aligned framework for explainable decision support. An orchestrator-specialist multi-agent LLM framework improves secondary headache diagnosis accuracy and transparency, supporting the development of explainable AI systems for time-constrained clinical decision-making in primary care.

Allogeneic stem cell transplantation (allo-SCT) remains the only curative treatment for most patients with acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). Unfortunately, a significant number of patients with AML/MDS will remain refractory to or subsequently relapse following allo-SCT. There is no consensus currently regarding the standard of care for relapsed AML/MDS after allo-SCT. Thirty-two patients with relapsed AML/MDS following first allo-SCT were treated with fludarabine, cytosine arabinoside, and granulocyte colony-stimulating factor, with or without idarubicin (FLAG ± Ida), followed by a second-allo-SCT from the initial donor. Patients were assessed for treatment response, acute graft-versus-host disease (aGVHD), and chronic GVHD (cGVHD). Non-relapse mortality (NRM) rates were calculated at 100 d and 1 yr. Kaplan-Meier curves were used to estimate 2- and 5-yr rates of progression-free survival and overall survival (OS). Overall, 84% of patients were able to achieve complete response after receiving FLAG ± Ida followed by second allo-SCT. Two- and five-year OS were 32% and 17%, respectively, and 2- and 5-yr disease-free survival were 20% and 6%, respectively. Overall, 85% of patients experienced GVHD. Overall, 48% of patients with aGVHD had grade 3 or higher disease; 29% of patients with cGVHD had severe disease. NRM was 19% and 31% at 100 d and 1 yr, respectively. FLAG ± Ida followed by allo-SCT appears to be a promising salvage strategy for patients with relapsed AML/MDS after allo-SCT. However, more research is needed to identify the circumstances for which this treatment option should be selected. Additionally, given the high rate of GVHD, additional research is needed to determine how to maximize the graft versus leukemia effect while minimizing the development of GVHD.

Lung cancer screening is now widely adopted across healthcare systems. Screening typically occurs in asymptomatic individuals. As symptoms of lung cancer overlap with those of chronic conditions, defining asymptomatic screening is challenging. This study outlines the frequency of symptomatic participants in a lung cancer screening trial. How common are respiratory and red flag symptoms in lung cancer screening participants and how do these symptoms impact screening outcomes? SUMMIT is a prospective observational cohort study to assess the implementation of Low-Dose Computed Tomography (LDCT) screening for lung cancer. Baseline clinical assessments collected self-reported symptoms, medical history, demographics, and spirometry. Haemoptysis (in last year) and unintentional weight loss (≥5kg in 3 months) were classified as red flag symptoms, and cough (acute: onset less than six weeks, or chronic: >6 weeks) and dyspnoea (modified Medical Research Council scale≥1) classified as non-specific symptoms. Lung cancer diagnoses within one year were ascertained. Multivariable logistic regression was used to assess associations between symptoms and lung cancer. Among 13,035 participants eligible for a baseline LDCT 76% (N=9,859) reported at least one symptom. Cough was present in 36% (N=4,707) and 66% of participants reported dyspnoea. Only 6% of participants reported red flag symptoms, including hemoptysis and weight loss. The presence of any of these symptoms was associated with higher likelihood of lung cancer diagnosis in the year following assessment (OR 1.45, p=0.03, adjusted for other baseline factors). Symptoms are commonly reported in those undergoing lung cancer screening and those with symptoms are more likely to be diagnosed with lung cancer.

Infraclavicular brachial plexus injury is an uncommon but potentially disabling complication of shoulder trauma, particularly glenohumeral dislocation and proximal humerus fracture or fracture-dislocation. Reported frequencies of neurological deficit vary widely because of heterogeneous definitions and ascertainment methods. Systematic reviews consistently identify the axillary nerve as the most commonly affected nerve following dislocation; however, multi-nerve deficits indicating cord-level involvement are clinically significant because recovery may be delayed or incomplete. Emergency care priorities for suspected infraclavicular brachial plexus injury centre on early, repeated, and well-documented neurological examination mapped to named cords and terminal branches, alongside prompt, gentle reduction of dislocations when a nerve deficit is present. Analgesia that facilitates examination without obscuring baseline deficits and imaging should be tailored to the fracture pattern and assessment of associated vascular red flags. Time-sensitive referral to orthopaedic and specialist peripheral nerve services is essential when red flags are identified. Concurrent vascular injury is a critical red flag that must be recognised early and escalated because it may compound nerve injury through compression or ischaemia and is itself limb-threatening. UK BOASt (British Orthopaedic Association Standards for Trauma) standards emphasise documentation of nerve function at the earliest opportunity and following interventions, alongside efficient referral pathways. This article is a narrative review with a pragmatic emergency department pathway proposal. It synthesises systematic reviews, large observational studies, and UK national standards. The proposed pathway is an expert-opinion synthesis that incorporates checklist-based documentation, staged imaging, and clear thresholds for escalation and specialist referral. It is intended for local adaptation and audit and has not been prospectively validated. The aim is to reduce missed injuries, optimise time-sensitive reconstructive opportunities, and mitigate medicolegal risk.

Poor reading comprehension performance by children in the United States is a continuing concern. Early identification and intervention can reduce the number of children with significant reading problems. We documented prekindergarten and kindergarten predictors of Grade 6 reading comprehension for English monolingual and Spanish-English bilingual groups and identified measures available to educators to flag children at risk for future reading comprehension problems. In Grade 6, children in the monolingual (n = 88) and bilingual (n = 95) groups completed a reading comprehension measure. These children were in a longitudinal study with previously completed code-related, vocabulary, grammar, listening comprehension, higher level language, working memory, and nonverbal IQ measures in prekindergarten and kindergarten. Data were analyzed separately by language group. We fit a series of Bayesian mixed-effects models incorporating prekindergarten and kindergarten measures as predictors. For the monolingual group, the most promising prekindergarten predictor was letter identification, and the most promising kindergarten predictors were vocabulary, grammar/morphology, and listening comprehension. For the bilingual group, the most promising prekindergarten predictors were English vocabulary, listening comprehension in Spanish, and memory updating in Spanish, and the most promising kindergarten predictor was English vocabulary. We suggest measures that could be administered in prekindergarten and kindergarten to flag students who may be at risk for future reading comprehension problems. We review other steps that schools and families may take to prevent reading comprehension problems. https://doi.org/10.23641/asha.32885270.

In test cheating detection, biclustering can be used to identify localized groups of examinees who share unusual response patterns, but an unresolved practical issue is determining how many extracted biclusters should be retained and how many examinees should be flagged. Retaining too many biclusters may increase false positives by capturing weak or noise-driven patterns, whereas retaining too few may miss meaningful cheating structures. This study proposes a changepoint-based retention rule that uses the ordered sequence of bicluster p values to identify where strong cheating-related evidence begins to give way to weaker residual patterns, thereby providing a data-driven cutoff for bicluster retention. The method was evaluated using two operational test forms with known cheating labels and a simulation study that varied cheating type, test length, and the proportion of compromised items. Label-based benchmark cutoffs were defined using the F1-score, balanced accuracy, and Youden's index, with the F1-score treated as the primary benchmark. In the empirical analysis, the estimated changepoints closely aligned with the F1-based benchmark, yielding the same sensitivity and slightly lower specificity across both forms. In the simulation study, the estimated changepoint generally approximated the F1-based benchmark but tended to select more conservative retention cutoffs, resulting in lower sensitivity and small specificity differences across conditions. These findings suggest that the proposed rule can provide a useful basis for determining how many biclusters to flag for further review in operational cheating-detection settings.

Large language models (LLMs) are increasingly applied to clinical notes, but guidance on how to adapt open-source models to specific tasks and manage annotation quality at scale is limited. We present a playbook for fine-tuning LLMs on de-identified clinical notes from patients with pancreatic cancer, spanning both pre-diagnosis and on-treatment settings. We evaluate prompting strategies, contrast open-source models with GPT-4o, and explore disease-level versus task-specific adaptation. A key contribution is an LLM-assisted adjudication workflow in which models flag notes where predictions consistently conflict with initial human labels. This approach concentrated expert review on a small fraction of cases while identifying many true annotation errors, ultimately improving downstream model performance. We further examine the use of machine-generated annotations to augment limited expert labels, showing that balanced mixtures of synthetic and human data can enhance fine-tuned models. Our findings provide practical guidance for deploying open-source LLMs in clinical contexts, offering strategies to improve accuracy, reduce annotation burden, and enable privacy-preserving, site-adapted clinical natural language processing (NLP).

Wheat is a major global food crop, and the content of essential minerals and toxic elements in the grains is crucial for human nutrition and health. However, their accumulation dynamics across developmental stages and their allocation mechanisms during grain filling remain poorly understood. Here, we systematically investigated the accumulation of essential minerals and toxic elements in field-grown wheat throughout its growth cycle and integrated source contribution analysis with temporal grain transcriptomics during grain filling. Shoot accumulation of Fe, Mn, Cu, Zn, and Cd followed a characteristic slow-fast-slow pattern, peaking at the jointing stage. Element allocation strategies were strongly influenced by phloem mobility: Cu and Zn were primarily remobilized from vegetative organs (>55% contribution), whereas Fe, Mn, and Cd were mainly derived from direct root uptake (>70%). During grain filling, ten elements exhibited three distinct temporal patterns: early accumulation (Ca), mid-phase accumulation (Mg, S, P, K, Mn, Cu, Zn, Cd) synchronized with dry matter, and continuous accumulation (Fe). Organ-level analysis further indicated that the flag leaf and node I acted primarily as transfer and regulatory hubs rather than major direct sources for grain loading. Temporal transcriptomic analysis of developing grains identified early and sustained gene expression patterns corresponding to these phased accumulation dynamics, suggesting stage-specific regulation of element import, redistribution, buffering, and deposition. Together, these results support a two-level interpretation of wheat grain mineral accumulation under the field conditions examined, in which whole-plant source dynamics interact with grain-associated handling processes. This study provides a mechanistically informed insights that may guide future efforts to improve grain mineral nutrition and reduce Cd accumulation through integrated breeding and agronomic strategies.

Biomass-derived carbon dots (CDs) have attracted increasing attention in agriculture due to their simple synthesis and low environmental impact. In this study, CDs were synthesized from guava (Psidium guajava) leaves using a hydrothermal method (200 °C, 15 h). The particles had an average size of 6.17 nm and a quantum yield of 2.46%, confirming the successful synthesis of fluorescent carbon nanomaterials from the natural precursor. The effects of CDs on rice (Oryza sativa L., variety HT1) were evaluated through both seed treatment and field application. Soaking seeds in a 200 ppm CD solution for 24 h significantly enhanced shoot and root lengths (28.87 mm and 34.00 mm, respectively) among the tested treatments. In field trials, applying CDs at the same concentration also promoted plant growth, as evidenced by improvements in plant height, leaf development, tillering, and flag leaf characteristics. These changes were reflected in yield, with the highest grain yield of 6.13 t ha-1 at 200 ppm, exceeding that of the control treatment. The observed positive effects may be due to enhanced photosynthetic activity and better control of oxidative processes in plants. Nevertheless, the effect was less pronounced at higher concentrations. This trend suggests a dose-dependent response.