Chain of Natural Language Inference for Reducing Large Language Model Ungrounded Hallucinations

Large language models (LLMs) can generate fluent natural language texts when given relevant documents as background context. This ability has attracted considerable interest in developing industry applications of LLMs. However, LLMs are prone to generate hallucinations that are not supported by the provided sources. In this paper, we propose a hierarchical framework to detect and mitigate such ungrounded hallucination. Our framework uses Chain of Natural Language Inference (CoNLI) for hallucination detection and hallucination reduction via post-editing. Our approach achieves state-of-the-art performance on hallucination detection and enhances text quality through rewrite, using LLMs without any fine-tuning or domain-specific prompt engineering. We show that this simple plug-and-play framework can serve as an effective choice for hallucination detection and reduction, achieving competitive performance across various contexts.Comment: The source code is available at https://github.com/microsoft/CoNLI_hallucinatio

CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing

ObjectivesThis study aimed to explore the relationship between computed tomography (CT)-based radiomic phenotypes and genomic profiles, including expression of programmed cell death-ligand 1 (PD-L1) and the 10 major genes, such as epidermal growth factor receptor (EGFR), tumor protein 53 (TP53), and Kirsten rat sarcoma viral oncogene (KRAS), in patients with lung adenocarcinoma (LUAD).MethodsIn total, 288 consecutive patients with pathologically confirmed LUAD were enrolled in this retrospective study. Radiomic features were extracted from preoperative CT images, and targeted genomic data were profiled through next-generation sequencing. PD-L1 expression was assessed by immunohistochemistry staining (chi-square test or Fisher's exact test for categorical data and the Kruskal–Wallis test for continuous data). A total of 1,013 radiomic features were obtained from each patient's CT images. Consensus clustering was used to cluster patients on the basis of radiomic features.ResultsThe 288 patients were classified according to consensus clustering into four radiomic phenotypes: Cluster 1 (n = 11) involving mainly large solid masses with a maximum diameter of 5.1 ± 2.0 cm; Clusters 2 and 3 involving mainly part-solid and solid masses with maximum diameters of 2.1 ± 1.4 cm and 2.1 ± 0.9 cm, respectively; and Cluster 4 involving mostly small ground-glass opacity lesions with a maximum diameter of 1.0 ± 0.9 cm. Differences in maximum diameter, PD-L1 expression, and TP53, EGFR, BRAF, ROS1, and ERBB2 mutations among the four clusters were statistically significant. Regarding targeted therapy and immunotherapy, EGFR mutations were highest in Cluster 2 (73.1%); PD-L1 expression was highest in Cluster 1 (45.5%).ConclusionOur findings provide evidence that CT-based radiomic phenotypes could non-invasively identify LUADs with different molecular characteristics, showing the potential to provide personalized treatment decision-making support for LUAD patients

Excess mortality among patients with severe mental disorders and effects of community-based mental healthcare: a community-based prospective study in Sichuan, China.

BACKGROUND: High-quality primary care reduces premature mortality in the general population, but evidence for psychiatric patients in China is scarce. AIMS: To confirm excess mortality in patients with severe mental illness (SMI), and to examine the impact of community-based mental healthcare and other risk factors on their mortality. METHOD: We included 93 655 patients in 2012 and 100 706 in 2013 from the national mental health surveillance system in Sichuan, China to calculate the standardised mortality ratio (SMR). A total of 112 576 patients were followed up from 2009 to 2014 for model analyses. We used growth models to quantify the patterns of change for community management measures, high-risk behaviour, disease stability and medication adherence of patients over time, and then used multilevel proportional hazard models to examine the association between change patterns of management measures and mortality. RESULTS: The SMR was 6.44 (95% CI 4.94-8.26) in 2012 and 7.57 (95% CI 5.98-9.44) in 2013 among patients with SMI aged 15-34 years, and diminished with age. Unfavourable baseline socioeconomic status increased the hazard of death by 38-50%. Positive changes in high-risk behaviour, disease stability and medication adherence had a 54% (95% CI 47-60%), 69% (95% CI 63-73%) and 20% (4-33%) reduction in hazard of death, respectively, versus in those where these were unchanged. CONCLUSIONS: High excess mortality was confirmed among younger patients with SMI in Sichuan, China. Our findings on the relationships between community management and socioeconomic factors and mortality can inform community-based mental healthcare policies to reduce excess mortality among patients with SMI

Uncovering the dispersion history, adaptive evolution and selection of wheat in China

Wheat was introduced to China approximately 4500 years ago, where it adapted over a span of time to various environments in agro-ecological growing zones. We investigated 717 Chinese and 14 Iranian/Turkish geographically diverse, locally adapted wheat landraces with 27,933 DArTseq (for 717 landraces) and 312,831 Wheat660K (for a subset of 285 landraces) markers. This study highlights the adaptive evolutionary history of wheat cultivation in China. Environmental stresses and independent selection efforts have resulted in considerable genome-wide divergence at the population level in Chinese wheat landraces. In total, 148 regions of the wheat genome show signs of selection in at least one geographic area. Our data show adaptive events across geographic areas, from the xeric northwest to the mesic south, along and among homoeologous chromosomes, with fewer variations in the D genome than in the A and B genomes. Multiple variations in interdependent functional genes, such as regulatory and metabolic genes controlling germination and flowering time were characterized, showing clear allelic frequency changes corresponding to the dispersion of wheat in China. Population structure and selection data reveal that Chinese wheat spread from the northwestern Caspian Sea region to south China, adapting during its agricultural trajectory to increasingly mesic and warm climatic areas

Genome-Wide Association Study Reveals Novel Genomic Regions Associated With High Grain Protein Content in Wheat Lines Derived From Wild Emmer Wheat

Grain protein content (GPC) and yield are of two important traits in wheat, but their negative correlation has hampered their simultaneous improvement in conventional breeding. Wild emmer wheat (Triticum turgidum ssp. dicoccoides) is an important genetic resource for wheat quality improvement. In this study, we report a genome-wide association study (GWAS) using 13116 DArT-seq markers to characterize GPC in 161 wheat lines derived from wild emmer. Using a general linear model, we identified 141 markers that were significantly associated with GPC, and grouped into 48 QTL regions. Using both general linear model and mixed linear model, we identified four significant markers that were grouped into two novel QTL regions on chromosomes 2BS (QGpc.cd1-2B.1) and 7BL (QGpc.cd1-7B.2). The two QTLs have no negative effects on thousand kernel weight (TKW) and should be useful for simultaneous improvement of GPC and TKW in wheat breeding. Searches of public databases revealed 61 putative candidate/flanking genes related to GPC. The putative proteins of interest were grouped in four main categories: enzymes, kinase proteins, metal transport-related proteins, and disease resistance proteins. The linked markers and associated candidate genes provide essential information for cloning genes related to high GPC and performing marker-assisted breeding in wheat

Genome-Wide Association Study for Adult-Plant Resistance to Stripe Rust in Chinese Wheat Landraces (Triticum aestivum L.) From the Yellow and Huai River Valleys

Stripe rust (also known as yellow rust), caused by the pathogen Puccinia striiformis f. sp. tritici (Pst), is a common and serious fungal disease of wheat (Triticum aestivum L.) worldwide. To identify effective stripe rust resistance loci, a genome-wide association study was performed using 152 wheat landraces from the Yellow and Huai River Valleys in China based on Diversity Arrays Technology and simple sequence repeat markers. Phenotypic evaluation of the degree of resistance to stripe rust at the adult-plant stage under field conditions was carried out in five environments. In total, 19 accessions displayed stable, high degrees of resistance to stripe rust development when exposed to mixed races of Pst at the adult-plant stage in multi-environment field assessments. A marker–trait association analysis indicated that 51 loci were significantly associated with adult-plant resistance to stripe rust. These loci included 40 quantitative trait loci (QTL) regions for adult-plant resistance. Twenty identified resistance QTL were linked closely to previously reported yellow rust resistance genes or QTL regions, which were distributed across chromosomes 1B, 1D, 2A, 2B, 3A, 3B, 4A, 4B, 5B, 6B, 7A, 7B, and 7D. Six multi-trait QTL were detected on chromosomes 1B, 1D, 2B, 3A, 3B, and 7D. Twenty QTL were mapped to chromosomes 1D, 2A, 2D, 4B, 5B, 6A, 6B, 6D, 7A, 7B, and 7D, distant from previously identified yellow rust resistance genes. Consequently, these QTL are potentially novel loci for stripe rust resistance. Among the 20 potentially novel QTL, five (QDS.sicau-2A, QIT.sicau-4B, QDS.sicau-4B.2, QDS.sicau-6A.3, and QYr.sicau-7D) were associated with field responses at the adult-plant stage in at least two environments, and may have large effects on stripe rust resistance. The novel effective QTL for adult-plant resistance to stripe rust will improve understanding of the genetic mechanisms that control the spread of stripe rust, and will aid in the molecular marker-assisted selection-based breeding of wheat for stripe rust resistance

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

An exploration of interpictoriality: the relationship between original artworks, children’s picturebooks, and meaning-making

Abstract not currently available