Exploring Fine-tuning ChatGPT for News Recommendation

News recommendation systems (RS) play a pivotal role in the current digital age, shaping how individuals access and engage with information. The fusion of natural language processing (NLP) and RS, spurred by the rise of large language models such as the GPT and T5 series, blurs the boundaries between these domains, making a tendency to treat RS as a language task. ChatGPT, renowned for its user-friendly interface and increasing popularity, has become a prominent choice for a wide range of NLP tasks. While previous studies have explored ChatGPT on recommendation tasks, this study breaks new ground by investigating its fine-tuning capability, particularly within the news domain. In this study, we design two distinct prompts: one designed to treat news RS as the ranking task and another tailored for the rating task. We evaluate ChatGPT's performance in news recommendation by eliciting direct responses through the formulation of these two tasks. More importantly, we unravel the pivotal role of fine-tuning data quality in enhancing ChatGPT's personalized recommendation capabilities, and illustrates its potential in addressing the longstanding challenge of the "cold item" problem in RS. Our experiments, conducted using the Microsoft News dataset (MIND), reveal significant improvements achieved by ChatGPT after fine-tuning, especially in scenarios where a user's topic interests remain consistent, treating news RS as a ranking task. This study illuminates the transformative potential of fine-tuning ChatGPT as a means to advance news RS, offering more effective news consumption experiences

Large Language Model Agent for Fake News Detection

In the current digital era, the rapid spread of misinformation on online platforms presents significant challenges to societal well-being, public trust, and democratic processes, influencing critical decision making and public opinion. To address these challenges, there is a growing need for automated fake news detection mechanisms. Pre-trained large language models (LLMs) have demonstrated exceptional capabilities across various natural language processing (NLP) tasks, prompting exploration into their potential for verifying news claims. Instead of employing LLMs in a non-agentic way, where LLMs generate responses based on direct prompts in a single shot, our work introduces FactAgent, an agentic approach of utilizing LLMs for fake news detection. FactAgent enables LLMs to emulate human expert behavior in verifying news claims without any model training, following a structured workflow. This workflow breaks down the complex task of news veracity checking into multiple sub-steps, where LLMs complete simple tasks using their internal knowledge or external tools. At the final step of the workflow, LLMs integrate all findings throughout the workflow to determine the news claim's veracity. Compared to manual human verification, FactAgent offers enhanced efficiency. Experimental studies demonstrate the effectiveness of FactAgent in verifying claims without the need for any training process. Moreover, FactAgent provides transparent explanations at each step of the workflow and during final decision-making, offering insights into the reasoning process of fake news detection for end users. FactAgent is highly adaptable, allowing for straightforward updates to its tools that LLMs can leverage within the workflow, as well as updates to the workflow itself using domain knowledge. This adaptability enables FactAgent's application to news verification across various domains

Combining Electrochemical Nitrate Reduction and Anammox for Treatment of Nitrate-Rich Wastewater: A Short Review

Treatment of nitrate-rich wastewater is important but challenging for the conventional biological denitrification process. Here, we propose combining the electrochemical reduction and anaerobic ammonium oxidation (anammox) processes together for treatment of nitrate-rich wastewater. This article reviews the mechanism and current research status of electrochemical reduction of nitrate to ammonium as well as the mechanism and applicability of the anammox process. This article discusses the principles, superiorities, and challenges of this combined process. The feasibility of the combined process depends on the efficiency of electrochemical nitrate reduction to ammonium and the conditions in the anammox process to use the reduced ammonium as the substrate to achieve deep nitrogen removal. The article provides a feasible strategy for using the electrochemical reduction and anammox combined process to treat nitrate-rich wastewater

Probing the Galactic halo with RR Lyrae stars -- IV. On the Oosterhoff dichotomy of RR Lyrae stars

We use 3653 (2661 RRab, 992 RRc) RR Lyrae stars (RRLs) with 7D (3D position, 3D velocity, and metallicity) information selected from SDSS, LAMOST, and Gaia EDR3, and divide the sample into two Oosterhoff groups (Oo I and Oo II) according to their amplitude-period behaviour in the Bailey Diagram. We present a comparative study of these two groups based on chemistry, kinematics, and dynamics. We find that Oo I RRLs are relatively more metal rich, with predominately radially dominated orbits and large eccentricities, while Oo II RRLs are relatively more metal poor, and have mildly radially dominated orbits. The Oosterhoff dichotomy of the Milky Way's halo is more apparent for the inner-halo region than for the outer-halo region. Additionally, we also search for this phenomenon in the halos of the two largest satellite galaxies, the Large and Small Magellanic clouds (LMC, SMC), and compare over different bins in metallicity. We find that the Oosterhoff dichotomy is not immutable, and varies based on position in the Galaxy and from galaxy-to-galaxy. We conclude that the Oosterhoff dichotomy is the result of a combination of stellar and galactic evolution, and that it is much more complex than the dichotomy originally identified in Galactic globular clusters

Increasing Salt Rejection of Polybenzimidazole Nanofiltration Membranes via the Addition of Immobilized and Aligned Aquaporins

Aquaporins are water channel proteins in cell membrane, highly specific for water molecules while restricting the passage of contaminants and small molecules, such as urea and boric acid. Cysteine functional groups were installed on aquaporin Z for covalent attachment to the polymer membrane matrix so that the proteins could be immobilized to the membranes and aligned in the direction of the flow. Depth profiling using x-ray photoelectron spectrometer (XPS) analysis showed the presence of functional groups corresponding to aquaporin Z modified with cysteine (Aqp-SH). Aqp-SH modified membranes showed a higher salt rejection as compared to unmodified membranes. For 2 M NaCl and CaCl2 solutions, the rejection obtained from Aqp-SH membranes was 49.3 ± 7.5% and 59.1 ± 5.1%. On the other hand, the rejections obtained for 2 M NaCl and CaCl2 solutions from unmodified membranes were 0.8 ± 0.4% and 1.3 ± 0.2% respectively. Furthermore, Aqp-SH membranes did not show a significant decrease in salt rejection with increasing feed concentrations, as was observed with other membranes. Through simulation studies, it was determined that there was approximately 24% capping of membrane pores by dispersed aquaporins

Case Report: A rare synchronous multiple gastric carcinoma achieved progression-free disease through NGS-guided serial treatment

Synchronous multiple gastric carcinoma (SMGC) is a rare condition characterized by the simultaneous occurrence of two or more primary malignant tumors in the stomach, each with its own distinct pathological morphology. SMGC differs from gastric metastases, which originate from primary gastric or non-gastric tumors. At present, the incidence of SMGC is low in China, with no established guidelines for standard treatment. Here, we report a rare case of advanced SMGC that achieved long-lasting clinical benefits through a treatment strategy informed by next-generation sequencing (NGS). Dynamically monitoring of the tumor and/or circulating cell-free DNA guided the patient’s treatment sequentially. The patient received anti-HER2 therapy, followed by immunotherapy, pembrolizumab in combination with trastuzumab and chemotherapy, and ultimately underwent successful total gastrectomy. This case highlights a novel approach of utilizing liquid biopsy-based NGS to gain insights into disease progression and molecular response to NGS-guided treatment in SMGC patients

JKA97, a Novel Benzylidene Analog of Harmine, Exerts Anti-Cancer Effects by Inducing G1 Arrest, Apoptosis, and p53-Independent Up-Regulation of p21

JKA97, a benzylidene analog of harmine, has been found to be a promising drug candidate for human cancer therapy, although the underlying molecular mechanisms have not been fully demonstrated. In this study, we evaluated the effects of JKA97 on human breast cancer cells in vitro and in vivo. JKA97 inhibited the growth and proliferation of MCF7 (p53 wild-type), MCF7 (p53 knockdown), and MDA-MB-468 (p53 mutant) cells in a dose-dependent manner. Treatment with JKA97 arrested breast cancer cells in G1 phase and induced apoptosis. JKA97 also significantly suppressed the growth of MCF7 and MDA-MB-468 xenograft tumors. It regulated the expression levels of G1 phase regulators, such as p21, p27, cyclinE, and cylinD1. JKA97 activated p21 transcription, independent of p53, but had little effect on p21 protein stability/degradation. In summary, our results suggest that JKA97 inhibits human breast cancer cell growth through activating p21, independent of p53, which provides a basis for developing this compound as a novel drug for human breast cancer therapy

Exploiting Ligand-Protein Conjugates to Monitor Ligand-Receptor Interactions

We introduce three assays for analyzing ligand-receptor interactions based on the specific conjugation of ligands to SNAP-tag fusion proteins. Conjugation of ligands to different SNAP-tag fusions permits the validation of suspected interactions in cell extracts and fixed cells as well as the establishment of high-throughput assays. The different assays allow the analysis of strong and weak interactions. Conversion of ligands into SNAP-tag substrates thus provides access to a powerful toolbox for the analysis of their interactions with proteins

Treatment as Prevention: Characterization of Partner Infections in the HIV Prevention Trials Network 052 Trial

HIV Prevention Trials Network (HPTN) 052 demonstrated that antiretroviral therapy (ART) prevents HIV transmission in serodiscordant couples. HIV from index-partner pairs was analyzed to determine the genetic linkage status of partner infections. Forty-six infections were classified as linked, indicating that the index was the likely source of the partner’s infection. Lack of viral suppression and higher index viral load were associated with linked infection. Eight linked infections were diagnosed after the index started ART: four near the time of ART initiation and four after ART failure. Linked infections were not observed when the index participant was stably suppressed on ART