Continually Updating Generative Retrieval on Dynamic Corpora

Generative retrieval has recently been gaining a lot of attention from the research community for its simplicity, high performance, and the ability to fully leverage the power of deep autoregressive models. However, prior work on generative retrieval has mostly investigated on static benchmarks, while realistic retrieval applications often involve dynamic environments where knowledge is temporal and accumulated over time. In this paper, we introduce a new benchmark called STREAMINGIR, dedicated to quantifying the generalizability of retrieval methods to dynamically changing corpora derived from StreamingQA, that simulates realistic retrieval use cases. On this benchmark, we conduct an in-depth comparative evaluation of bi-encoder and generative retrieval in terms of performance as well as efficiency under varying degree of supervision. Our results suggest that generative retrieval shows (1) detrimental performance when only supervised data is used for fine-tuning, (2) superior performance over bi-encoders when only unsupervised data is available, and (3) lower performance to bi-encoders when both unsupervised and supervised data is used due to catastrophic forgetting; nevertheless, we show that parameter-efficient measures can effectively mitigate the issue and result in competitive performance and efficiency with respect to the bi-encoder baseline. Our results open up a new potential for generative retrieval in practical dynamic environments. Our work will be open-sourced.Comment: Work in progres

How Well Do Large Language Models Truly Ground?

Reliance on the inherent knowledge of Large Language Models (LLMs) can cause issues such as hallucinations, lack of control, and difficulties in integrating variable knowledge. To mitigate this, LLMs can be probed to generate responses by grounding on external context, often given as input (knowledge-augmented models). Yet, previous research is often confined to a narrow view of the term "grounding", often only focusing on whether the response contains the correct answer or not, which does not ensure the reliability of the entire response. To address this limitation, we introduce a strict definition of grounding: a model is considered truly grounded when its responses (1) fully utilize necessary knowledge from the provided context, and (2) don't exceed the knowledge within the contexts. We introduce a new dataset and a grounding metric to assess this new definition and perform experiments across 13 LLMs of different sizes and training methods to provide insights into the factors that influence grounding performance. Our findings contribute to a better understanding of how to improve grounding capabilities and suggest an area of improvement toward more reliable and controllable LLM applications

Enhanced Electrochemical Performances of Hollow-Structured N-Doped Carbon Derived from a Zeolitic Imidazole Framework (ZIF-8) Coated by Polydopamine as an Anode for Lithium-Ion Batteries

Doping heteroatoms such as nitrogen (N) and boron (B) into the framework of carbon materials is one of the most efficient methods to improve the electrical performance of carbon-based electrodes. In this study, N-doped carbon has been facilely synthesized using a ZIF-8/polydopamine precursor. The polyhedral structure of ZIF-8 and the effective surface-coating capability of dopamine enabled the formation of N-doped carbon with a hollow structure. The ZIF-8 polyhedron served as a sacrificial template for hollow structures, and dopamine participated as a donor of the nitrogen element. When compared to ZIF-8-derived carbon, the HSNC electrode showed an improved reversible capacity of approximately 1398 mAh·g−1 after 100 cycles, with excellent cycling retention at a voltage range of 0.01 to 3.0 V using a current density of 0.1 A·g−1

Dual-Channel P-Type Ternary Dntt-Graphene Barristor

P-type ternary switch devices are crucial elements for the practical implementation of complementary ternary circuits. This report demonstrates a p-type ternary device showing three distinct electrical output states with controllable threshold voltage values using a dual-channel dinaphtho[2,3-b:2\u27,3\u27-f]thieno[3,2-b]-thiophene-graphene barristor structure. to obtain transfer characteristics with distinctively separated ternary states, novel structures called contact-resistive and contact-doping layers were developed. The feasibility of a complementary standard ternary inverter design around 1 V was demonstrated using the experimentally calibrated ternary device model

Detection of EGFR Mutations Using Bronchial Washing-Derived Extracellular Vesicles in Patients with Non-Small-Cell Lung Carcinoma

The detection of epidermal growth factor receptor (EGFR) mutation, based on tissue biopsy samples, provides a valuable guideline for the prognosis and precision medicine in patients with lung cancer. In this study, we aimed to examine minimally invasive bronchial washing (BW)-derived extracellular vesicles (EVs) for EGFR mutation analysis in patients with lung cancer. A lab-on-a-disc equipped with a filter with 20-nm pore diameter, Exo-Disc, was used to enrich EVs in BW samples. The overall detection sensitivity of EGFR mutations in 55 BW-derived samples was 89.7% and 31.0% for EV-derived DNA (EV-DNA) and EV-excluded cell free-DNA (EV-X-cfDNA), respectively, with 100% specificity. The detection rate of T790M in 13 matched samples was 61.5%, 10.0%, and 30.8% from BW-derived EV-DNA, plasma-derived cfDNA, and tissue samples, respectively. The acquisition of T790M resistance mutation was detected earlier in BW-derived EVs than plasma or tissue samples. The longitudinal analysis of BW-derived EVs showed excellent correlation with the disease progression measured by CT images. The EGFR mutations can be readily detected in BW-derived EVs, which demonstrates their clinical potential as a liquid-biopsy sample that may aid precise management, including assessment of the treatment response and drug resistance in patients with lung cancer

A pathogen-derived metabolite induces microglial activation via odorant receptors

Microglia (MG), the principal neuroimmune sentinels in the brain, continuously sense changes in their environment and respond to invading pathogens, toxins, and cellular debris, thereby affecting neuroinflammation. Microbial pathogens produce small metabolites that influence neuroinflammation, but the molecular mechanisms that determine whether pathogen-derived small metabolites affect microglial activation of neuroinflammation remain to be elucidated. We hypothesized that odorant receptors (ORs), the largest subfamily of G protein-coupled receptors, are involved in microglial activation by pathogen-derived small metabolites. We found that MG express high levels of two mouse ORs, Olfr110 and Olfr111, which recognize a pathogenic metabolite, 2-pentylfuran, secreted by Streptococcus pneumoniae. These interactions activate MG to engage in chemotaxis, cytokine production, phagocytosis, and reactive oxygen species generation. These effects were mediated through the G(alpha s)-cyclic adenosine monophosphate-protein kinase A-extracellular signal-regulated kinase and G(beta gamma)-phospholipase C-Ca2+ pathways. Taken together, our results reveal a novel interplay between the pathogen-derived metabolite and ORs, which has major implications for our understanding of microglial activation by pathogen recognition. Database Model data are available in the PMDB database under the accession number PM0082389.N

Piperlongumine treatment impacts heart and liver development and causes developmental delay in zebrafish (Danio rerio) embryos

Piperlongumine (PL) and piperine (PP) are alkaloids presented in long pepper (Piper longum), and they exhibit various biological activities, especially anti-cancer properties. With these regards, they are considered as future medicines with high potential. Even they are exposed to humans such a long time, their potential toxicities in the environment have not been studied. Therefore, their ecological toxicities were assessed using zebrafish embryos. PP showed low mortality and no abnormal phenotype up to 10 µM. However, PL exhibited strong acute toxicity at the concentration of 5–10 µM ranges, and abnormal development were frequently found in the range of 1–2.5 µM with pericardial and yolk sac edemas. In transgenic zebrafish embryos, PL induced an increase in the number of intersegmental vessels and delayed the early-stage development. PL treatment affected heart formation and heart rate. The presence of PL induced the expression of cytokines, inflammatory markers, and inflammasome in the embryos. The PL treatment changed the mRNA levels of the ER stress and apoptosis-related genes. In addition, ROS production was observed during early-stage development of PL-treated zebrafish embryos. These results indicate that developing PL as a medicine would require extremely meticulous strategies to prevent potential toxicity