Extraction of Medication and Temporal Relation from Clinical Text using Neural Language Models

Clinical texts, represented in electronic medical records (EMRs), contain rich medical information and are essential for disease prediction, personalised information recommendation, clinical decision support, and medication pattern mining and measurement. Relation extractions between medication mentions and temporal information can further help clinicians better understand the patients' treatment history. To evaluate the performances of deep learning (DL) and large language models (LLMs) in medication extraction and temporal relations classification, we carry out an empirical investigation of MEDTEM project using several advanced learning structures including BiLSTM-CRF and CNN-BiLSTM for a clinical domain named entity recognition (NER), and BERT-CNN for temporal relation extraction (RE), in addition to the exploration of different word embedding techniques. Furthermore, we also designed a set of post-processing roles to generate structured output on medications and the temporal relation. Our experiments show that CNN-BiLSTM slightly wins the BiLSTM-CRF model on the i2b2-2009 clinical NER task yielding 75.67, 77.83, and 78.17 for precision, recall, and F1 scores using Macro Average. BERT-CNN model also produced reasonable evaluation scores 64.48, 67.17, and 65.03 for P/R/F1 using Macro Avg on the temporal relation extraction test set from i2b2-2012 challenges. Code and Tools from MEDTEM will be hosted at https://github.com/HECTA-UoM/MedTem</p

S100A9+CD14+ monocytes contribute to anti-PD-1 immunotherapy resistance in advanced hepatocellular carcinoma by attenuating T cell-mediated antitumor function

Abstract Background The paucity of reliable biomarkers for predicting immunotherapy efficacy in patients with advanced hepatocellular carcinoma (HCC) has emerged as a burgeoning concern with the expanding use of immunotherapy. This study endeavors to delve into the potential peripheral biomarkers capable of prognosticating efficacy in HCC patients who are poised to receive anti-PD-1 monotherapy within the phase III clinical trial, KEYNOTE394. Additionally, we sought to elucidate the underlying molecular mechanisms for resistance to immune checkpoint blockade (ICB) and propose innovative combination immunotherapy strategies for future clinical application. Methods Patient blood samples were collected for single-cell RNA sequencing to evaluate the immune cell signature before receiving ICB therapy. Subsequently, in vitro assays and in vivo murine model experiments were conducted to validate the mechanism that S100A9+CD14+ monocytes play a role in ICB resistance. Results Our study demonstrates a notable enrichment of S100A9+CD14+ monocytes in the peripheral blood of patients exhibiting suboptimal responses to anti-PD-1 therapy. Moreover, we identified the Mono_S100A9 signature as a predictive biomarker, indicative of reduced efficacy in immunotherapy and decreased survival benefits across various tumor types. Mechanistically, S100A9 activates PD-L1 transcription by directly binding to the CD274 (PD-L1) gene promoter, thereby suppressing T-cell proliferation and cytotoxicity via the PD-1/PD-L1 axis, consequently diminishing the therapeutic effectiveness of subsequent anti-PD-1 treatments. Furthermore, our in vivo studies revealed that inhibiting S100A9 can synergistically enhance the efficacy of anti-PD-1 drugs in the eradication of hepatocellular carcinoma. Conclusions Our study underscores the significance of S100A9+CD14+ monocytes in predicting inadequate response to ICB treatment and provides insights into the monocyte cell-intrinsic mechanisms of resistance to ICB therapy. We also propose a combined therapeutic approach to enhance ICB efficacy by targeting S100A9

Cationic Covalent Organic Framework Nanosheets for Fast Li-Ion Conduction

Covalent organic frameworks (COFs) with their porous structures that are accommodative of Li salts are considered to be potential candidates for solid-state fast Li⁺ conductors. However, Li salts simply infiltrated in the pores of solid-state COFs tend to be present in closely associate ion pairs, resulting in slow ionic diffusion dynamics. Here we incorporate cationic skeleton into the COF structure to split the Li salt ion pair through stronger dielectric screening. It is observed that the concentration of free Li⁺ ions in the resulting material is drastically increased, leading to a significantly improved Li⁺ conductivity in the absence of any solvent (up to 2.09 × 10^–4 S cm^–1 at 70 °C)

Additional file 1 of S100A9+CD14+ monocytes contribute to anti-PD-1 immunotherapy resistance in advanced hepatocellular carcinoma by attenuating T cell-mediated antitumor function

Additional file 1:Supplementary Fig. S1. Clinical efficacy of pembrolizumab in patients with advanced HCC. a Kaplan–Meier survival curves showing progression-free survival stratified by pembrolizumab group (red) and placebo group (blue). Significance calculated by the log-rank test. b Spider plot showing tumor responses over a long duration