Consistency Guided Knowledge Retrieval and Denoising in LLMs for Zero-shot Document-level Relation Triplet Extraction

Document-level Relation Triplet Extraction (DocRTE) is a fundamental task in information systems that aims to simultaneously extract entities with semantic relations from a document. Existing methods heavily rely on a substantial amount of fully labeled data. However, collecting and annotating data for newly emerging relations is time-consuming and labor-intensive. Recent advanced Large Language Models (LLMs), such as ChatGPT and LLaMA, exhibit impressive long-text generation capabilities, inspiring us to explore an alternative approach for obtaining auto-labeled documents with new relations. In this paper, we propose a Zero-shot Document-level Relation Triplet Extraction (ZeroDocRTE) framework, which generates labeled data by retrieval and denoising knowledge from LLMs, called GenRDK. Specifically, we propose a chain-of-retrieval prompt to guide ChatGPT to generate labeled long-text data step by step. To improve the quality of synthetic data, we propose a denoising strategy based on the consistency of cross-document knowledge. Leveraging our denoised synthetic data, we proceed to fine-tune the LLaMA2-13B-Chat for extracting document-level relation triplets. We perform experiments for both zero-shot document-level relation and triplet extraction on two public datasets. The experimental results illustrate that our GenRDK framework outperforms strong baselines.Comment: Accepted by WWW 202

MM-BigBench: Evaluating Multimodal Models on Multimodal Content Comprehension Tasks

The popularity of multimodal large language models (MLLMs) has triggered a recent surge in research efforts dedicated to evaluating these models. Nevertheless, existing evaluation studies of MLLMs primarily focus on the comprehension and reasoning of unimodal (vision) content, neglecting performance evaluations in the domain of multimodal (vision-language) content understanding. Beyond multimodal reasoning, tasks related to multimodal content comprehension necessitate a profound understanding of multimodal contexts, achieved through the multimodal interaction to obtain a final answer. In this paper, we introduce a comprehensive assessment framework called MM-BigBench, which incorporates a diverse range of metrics to offer an extensive evaluation of the performance of various models and instructions across a wide spectrum of diverse multimodal content comprehension tasks. Consequently, our work complements research on the performance of MLLMs in multimodal comprehension tasks, achieving a more comprehensive and holistic evaluation of MLLMs. To begin, we employ the Best Performance metric to ascertain each model's performance upper bound on different datasets. Subsequently, the Mean Relative Gain metric offers an assessment of the overall performance of various models and instructions, while the Stability metric measures their sensitivity. Furthermore, previous research centers on evaluating models independently or solely assessing instructions, neglecting the adaptability between models and instructions. We propose the Adaptability metric to quantify the adaptability between models and instructions. Our paper evaluates a total of 20 language models (14 MLLMs) on 14 multimodal datasets spanning 6 tasks, with 10 instructions for each task, and derives novel insights. Our code will be released at https://github.com/declare-lab/MM-BigBench.Comment: Undervie

The cell line ontology-based representation, integration and analysis of cell lines used in China

Abstract Background The Chinese National Infrastructure of Cell Line stores and distributes cell lines for biomedical research in China. This study aims to represent and integrate the information of NICR cell lines into the community-based Cell Line Ontology (CLO). Results We have aligned, represented, and added all identified 2704 cell line cells in NICR to CLO. We also proposed new ontology design patterns to represent the usage of cell line cells as disease models by inducing tumor formation in model organisms, and the relations between cell line cells and their expressed or overexpressed genes or proteins. The resulting CLO-NICR ontology also includes the Chinese representation of the NICR cell line information. CLO-NICR was merged into the general CLO. To serve the cell research community in China, the Chinese version of CLO-NICR was also generated and deposited in the OntoChina ontology repository. The usage of CLO-NICR was demonstrated by DL query and knowledge extraction. Conclusions In summary, all identified cell lines from NICR are represented by the semantics framework of CLO and incorporated into CLO as a most recent update. We also generated a CLO-NICR and its Chinese view (CLO-NICR-Cv). The development of CLO-NICR and CLO-NIC-Cv allows the integration of the cell lines from NICR into the community-based CLO ontology and provides an integrative platform to support different applications of CLO in China.https://deepblue.lib.umich.edu/bitstream/2027.42/148821/1/12859_2019_Article_2724.pd

Spatiotemporal Changes of Winter Wheat Planted and Harvested Areas, Photosynthesis and Grain Production in the Contiguous United States from 2008–2018

Winter wheat is a main cereal crop grown in the United States of America (USA), and the USA is the third largest wheat exporter globally. Timely and reliable in-season forecast and year-end estimation of winter wheat grain production in the USA are needed for regional and global food security. In this study, we assessed the consistency between the agricultural statistical reports and satellite-based data for winter wheat over the contiguous US (CONUS) at both the county and national scales. First, we compared the planted area estimates from the National Agricultural Statistics Service (NASS) and the Cropland Data Layer (CDL) from 2008–2018. Second, we investigated the relationship between gross primary production (GPP) estimated by the vegetation photosynthesis model (VPM) and grain production from the NASS. Lastly, we explored the in-season utility of GPPVPM in monitoring seasonal production. Strong spatiotemporal consistency of planted areas was found between the NASS and CDL datasets. However, in the Southern Great Plains, both the CDL and NASS planted acreage were noticeable larger (>20%) than the NASS harvested area, where some winter wheat fields were used as forage for cattle grazing. County-level GPPVPM was linearly related with grain production of winter wheat, with an R2 value of 0.68 across the CONUS. The relationships between grain production and GPPVPM in those counties without a substantial difference (<20%) between planted and harvested area were much stronger and their harvest index (HIGPP) values ranged from 0.2–0.3. GPPVPM in May could explain about 70–90% of the variance of winter wheat grain production. Our findings highlight the potential of GPPVPM in winter wheat monitoring, especially for those high harvested/planted ratio, which could provide useful data to guide planning and marketing for decision makers, stakeholders, and the public.This research was supported in part by research grants from the USDA National Institute of Food and Agriculture (NIFA, 2016-68002-24967), the US National Science Foundation EPSCoR program (IIA-1946093, IIA-1920946), and the NASA Geostationary Carbon Cycle Observatory (GeoCarb) Mission (GeoCarb Contract # 80LARC17C0001). Open Access fees paid for in whole or in part by the University of Oklahoma Libraries.Ye

Contrast-enhanced spectral mammography: are kinetic patterns useful for differential diagnoses of enhanced lesions?

PURPOSETo investigate the diagnostic efficiency of the kinetic curves of enhanced lesions on contrast-en-hanced spectral mammography (CESM) and whether they were similar to those of magnetic resonance imaging (MRI).METHODSTwo hundred and twelve patients with 222 enhanced lesions were included in this prospective study. Single-view craniocaudal of an affected breast was acquired at 3, 5, and 7 min after contrast media injection. The kinetic patterns of each lesion were evaluated and classified as elevated (type I), steady (type II), and depressed (type III). Statistical comparison used the chi-squared test, the receiver operating characteristic (ROC) curve, and Cohen’s kappa.RESULTSOf 222 enhanced lesions, 140 were breast cancers, and 82 were benign lesions. The distribution of the kinetic curves for breast cancer was type I, 3.57%, type II, 35.71%, and type III, 60.72%. As for benign lesions, the distribution was type I, 43.90%, type II, 45.12%, and type III, 10.98%. The difference in the enhancement patterns between benign lesions and breast cancers was significant (P < 0.001). The likelihood of breast cancer related to a type I, II, and III curve was 12.20%, 57.47%, and 90.43%, respectively. For the enhancement intensity, the area under curve (AUC) of the ROC curves was 0.702 ± 0.036; for enhancement patterns, the AUC increased to 0.819 ± 0.030. Cohen’s kappa coefficient was 0.752 (P < 0.001) regarding the kinetic curves for CESM and MRI.CONCLUSIONThe kinetic patterns on CESM show promise in differentiating between benign lesions and breast cancers, with good agreement, when compared with MRI

Paper-based microfluidics for rapid diagnostics and drug delivery

Paper is a common material that is promising for constructing microfluidic chips (lab-on-a-paper) for diagnostics and drug delivery for biomedical applications. In the past decade, extensive research on paper-based microfluidics has accumulated a large number of scientific publications in the fields of biomedical diagnosis, food safety, environmental health, drug screening and delivery. This review focuses on the recent progress on paper-based microfluidic technology with an emphasis on the design, optimization and application of the technology platform, in particular for medical diagnostics and drug delivery. Novel advances have concentrated on engineering paper devices for point-of-care (POC) diagnostics, which could be integrated with nucleic acid-based tests and isothermal amplification experiments, enabling rapid sample-to-answer assays for field testing. Among the isothermal amplification experiments, loop-mediated isothermal amplification (LAMP), an extremely sensitive nucleic acid test, specifically identifies ultralow concentrations of DNA/RNA from practical samples for diagnosing diseases. We thus mainly focus on the paper device-based LAMP assay for the rapid infectious disease diagnosis, foodborne pathogen analysis, veterinary diagnosis, plant diagnosis, and environmental public health evaluation. We also outlined progress on paper microfluidic devices for drug delivery. The paper concludes with a discussion on the challenges of this technology and our insights into how to advance science and technology towards the development of fully functional paper devices in diagnostics and drug delivery

Analysis of the effect of anti-tuberculosis treatment and lung injury in patients with tuberculosis combined with underlying disease

Objective·To investigate the impact of complications on the prognosis and lung injury of patients with tuberculosis..Methods·A retrospective cohort study was used for analysis, to select a total of 450 smear-positive tuberculosis (TB) patients, 323 males (71.8%) and 127 females (28.2%), from January to December 2018 at Shanghai Pulmonary Hospital, Tongji University School of Medicine, which were divided into non-complication group and complication group (diabetes, hypertension, liver diseases, kidney diseases and gallbladder diseases). Overall treatment outcomes and lung injuries in TB patients with and without complications were analyzed by using χ2 test. Stratified analysis of the impact of each comorbidity on the prognosis and lung injury of TB patients was performed. Kaplan-Meier analysis was used to analyze the temporal correlation between complications and tuberculosis prognosis.Results·Four hundred and fifty patients with a median age of 33 years were included, 173 of whom had complications: diabetes in 49 cases, hypertension in 23 cases, liver diseases in 83 cases, kidney diseases in 35 cases, and gallbladder diseases in 17 cases. The cure rate of TB patients without complications was 80.5%, which was significantly higher than that of the group with complications (P<0.05); the significantly lower cure rate of TB patients with diabetes, hypertension and kidney diseases at diagnosis was the key cause of anti-tuberculosis treatment failure; TB patients with diabetes and liver diseases had higher lung bacterial load and larger areas of lung damage, and TB patients with diabetes and kidney diseases had higher incidence of pulmonary cavity.Conclusion·Diabetes, hypertension and kidney diseases exacerbate lung damage and lead to lower TB cure rates. Early interventions by clinicians at the time of diagnosis can improve cure rates, shorten treatment time, and reduce medical costs for TB patients

Monitoring Prevalence and Persistence of Environmental Contamination by SARS-CoV-2 RNA in a Makeshift Hospital for Asymptomatic and Very Mild COVID-19 Patients

Objective: To investigate the details of environmental contamination status by SARS-CoV-2 in a makeshift COVID-19 hospital.Methods: Environmental samples were collected from a makeshift hospital. The extent of contamination was assessed by quantitative reverse transcription polymerase chain reaction (RT-qPCR) for SARS-CoV-2 RNA from various samples.Results: There was a wide range of total collected samples contaminated with SARS-CoV-2 RNA, ranging from 8.47% to 100%. Results revealed that 70.00% of sewage from the bathroom and 48.19% of air samples were positive. The highest rate of contamination was found from the no-touch surfaces (73.07%) and the lowest from frequently touched surfaces (33.40%). The most contaminated objects were the top surfaces of patient cubic partitions (100%). The median Ct values among strongly positive samples were 33.38 (IQR, 31.69–35.07) and 33.24 (IQR, 31.33–34.34) for ORF1ab and N genes, respectively. SARS-CoV-2 relic RNA can be detected on indoor surfaces for up to 20 days.Conclusion: The findings show a higher prevalence and persistence in detecting the presence of SARS-CoV-2 in the makeshift COVID-19 hospital setting. The contamination mode of droplet deposition may be more common than contaminated touches

Alcohol Extracts From Ganoderma lucidum Delay the Progress of Alzheimer’s Disease by Regulating DNA Methylation in Rodents

Age-related changes in methylation are involved in the occurrence and development of tumors, autoimmune disease, and nervous system disorders, including Alzheimer’s disease (AD), in elderly individuals; hence, modulation of these methylation changes may be an effective strategy to delay the progression of AD pathology. In this study, the AD model rats were used to screen the main active extracts from the mushroom, Ganoderma lucidum, for anti-aging properties, and their effects on DNA methylation were evaluated. The results of evaluation of rats treated with 100 mg/kg/day of D-galactose to induce accelerated aging showed that alcohol extracts of G. lucidum contained the main active anti-aging extract. The effects on DNA methylation of these G. lucidum extracts were then evaluated using SAMP8 and APP/PS1 AD model mice by whole genome bisulfite sequencing, and some methylation regulators including Histone H3, DNMT3A, and DNMT3B in brain tissues were up-regulated after treatment with alcohol extracts from G. lucidum. Molecular docking analysis was carried out to screen for molecules regulated by specific components, including ganoderic acid Mk, ganoderic acid C6, and lucidone A, which may be active ingredients of G. lucidum, including the methylation regulators of Histone H3, MYT, DNMT3A, and DNMT3B. Auxiliary tests also demonstrated that G. lucidum alcohol extracts could improve learning and memory function, ameliorate neuronal apoptosis and brain atrophy, and down-regulate the expression of the AD intracellular marker, Aβ1-42. We concluded that alcohol extracts from G. lucidum, including ganoderic acid and lucidone A, are the main extracts involved in delaying AD progression