Leveraging Large Language Models for Pre-trained Recommender Systems

Recent advancements in recommendation systems have shifted towards more comprehensive and personalized recommendations by utilizing large language models (LLM). However, effectively integrating LLM's commonsense knowledge and reasoning abilities into recommendation systems remains a challenging problem. In this paper, we propose RecSysLLM, a novel pre-trained recommendation model based on LLMs. RecSysLLM retains LLM reasoning and knowledge while integrating recommendation domain knowledge through unique designs of data, training, and inference. This allows RecSysLLM to leverage LLMs' capabilities for recommendation tasks in an efficient, unified framework. We demonstrate the effectiveness of RecSysLLM on benchmarks and real-world scenarios. RecSysLLM provides a promising approach to developing unified recommendation systems by fully exploiting the power of pre-trained language models.Comment: 13 pages, 4 figure

Enhancing Recommender Systems with Large Language Model Reasoning Graphs

Recommendation systems aim to provide users with relevant suggestions, but often lack interpretability and fail to capture higher-level semantic relationships between user behaviors and profiles. In this paper, we propose a novel approach that leverages large language models (LLMs) to construct personalized reasoning graphs. These graphs link a user's profile and behavioral sequences through causal and logical inferences, representing the user's interests in an interpretable way. Our approach, LLM reasoning graphs (LLMRG), has four components: chained graph reasoning, divergent extension, self-verification and scoring, and knowledge base self-improvement. The resulting reasoning graph is encoded using graph neural networks, which serves as additional input to improve conventional recommender systems, without requiring extra user or item information. Our approach demonstrates how LLMs can enable more logical and interpretable recommender systems through personalized reasoning graphs. LLMRG allows recommendations to benefit from both engineered recommendation systems and LLM-derived reasoning graphs. We demonstrate the effectiveness of LLMRG on benchmarks and real-world scenarios in enhancing base recommendation models.Comment: 12 pages, 6 figure

Promotion of angiogenesis and suppression of inflammatory response in skin wound healing using exosome-loaded collagen sponge

Effectively promoting skin wound healing remains a significant challenge in the medical field. Although stem cell-derived exosomes show potential in tissue regeneration, their local delivery and sustained release face challenges. To address these issues, we developed a collagen sponge based on type I and recombinant humanized type III collagen. Our study confirmed that exosomes were successfully loaded onto the sponge (sponge-Exo) and the sponge-Exo gradually released exosomes into the local milieu. The sponge-Exo played a crucial role in promoting the transition of macrophages from an inflammatory M1 phenotype to a regenerative M2 phenotype. Moreover, it enhanced the migration and proliferation of HDFs and promoted angiogenesis in HUVECs. Additionally, our findings revealed that the sponge-Exo accelerated wound healing by suppressing inflammatory response and stimulating angiogenesis in a rat full-thickness skin wounds model. Next generation sequencing (NGS) was used to explore the underlying mechanism of wound healing, and the results showed that the miRNAs (hsa-miR-21-5p and hsa-miR-29a-5p) associated with wound healing in exosomes were significantly up-regulated. These results highlight the remarkable effects of sponge-Exo on macrophage transformation, cell migration, proliferation and angiogenesis, which provide a potential prospect for the application in the field of skin wound healing

Long Non-Coding MALAT1 Functions as a Competing Endogenous RNA to Regulate Vimentin Expression by Sponging miR-30a-5p in Hepatocellular Carcinoma

Background/Aims: Hepatocellular carcinoma (HCC) has a high morbidity as well as mortality and is believed to be one of the most prevalent cancers worldwide. The long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is involved in numerous cancers, including HCC. This study aimed to explore the role of MALAT1 in HCC progression. Methods: The expression levels of MALAT1 and Vimentin in HCC tissues and relative pair-matched adjacent normal liver tissues were analyzed by RT-PCR, and immunohistochemistry. Using bioinformatics analysis and dual-luciferase assay, we examined the correlation between MALAT1 and miR-30a-5p. Dual-luciferase assay and western blotting suggested that Vimentin was a target of miR-30a-5p. A wound healing assay and transwell assays were employed to determine the effect of MALAT1 and miR-30a-5p on cell migration and invasion in HCC. Results: Our data demonstrated that the levels of MALAT1 and Vimentin were upregulated in HCC tissues and that miR-30a-5p was a direct target of MALAT1. Silenced MALAT1 and overexpressed miR-30a-5p each inhibited cell migration and invasion. Additionally, dual-luciferase assay and western blotting demonstrated that MALAT1 could competitively sponge miR-30a-5p and thereby regulate Vimentin. Conclusion: Our data suggest that MALAT1 acts as an oncogenic lncRNA that promotes HCC migration and invasion. Therefore, the MALAT1-miR-30a-5p-Vimentin axis is a potential therapeutic target and molecular biomarker in HCC

Next-generation sequencing of mitochondrial DNA reveals pathogenic variants and protective haplogroup D4 in esophageal cancer

IntroductionThe germline variations in the mitochondrial genome of esophageal cancer (EC) remain uncertain. Our study aimed to explore the distribution and pathogenicity of mitochondrial genome variations in EC, as well as to identify haplogroups associated with the development of EC.MethodsWe performed next-generation sequencing of the mitochondrial genomes from peripheral blood samples of 146 EC patients and 120 healthy controls. Variant annotation was performed using MitoMap, while pathogenicity prediction was conducted through tools such as MitoTip, SIFT, and PolyPhen2. Moreover, haplogroup classification was carried out using the Haplogrep3 platform.ResultsA total of 1299 mitochondrial variants were identified among 146 EC patients, including 171 novel (previously unreported) mutations. Compared with the healthy control group, the EC cohort exhibited a higher frequency of variants in genes such as ND2, COX1, COX2, 12S rRNA, and 16S rRNA. Three tRNA mutations (7496_T>C, 5771_A>G, and 5613_T>A) were predicted to be potentially pathogenic. Within the protein-coding regions, 14 variants were classified as deleterious based on predictions from 13 independent bioinformatic algorithms. Notably, mitochondrial haplogroup D4 was significantly associated with a decreased risk of developing EC. Furthermore, several mtDNA single-nucleotide polymorphisms (SNPs), including 302_A>AC, 1824_T>C, 1842_A>G, 3010_G>A, 8414_C>T, and 14668_C>T, showed significant associations with EC susceptibility.ConclusionWe found that the number of variations in multiple regions of the mitochondrial genome in the EC population was higher than that in the control group. Additionally, several potentially pathogenic variants were identified, and haplogroup D4 was suggested as a potentially protective haplogroup against the development of EC

Hypertension moderates the relationship between plasma beta-amyloid and cognitive impairment: a cross-sectional study in Xi’an, China

BackgroundPlasma beta-amyloid (Aβ) are important biomarkers for Alzheimer’s disease and cognitive impairment (CI), but results are controversial. It remains unclear whether hypertension modulates their relationship. This cross-sectional study investigates whether hypertension moderates the relationship between plasma Aβ and cognitive impairment (CI).MethodsThis cross-sectional study included 1488 subjects ≥ 40 years from rural areas of northwestern China. CI was defined as a Mini-Mental State Examination score lower than the cutoff. Firstly, plasma Aβ40, Aβ42, Aβ42/Aβ40 were analyzed as restricted cubic spline. Then, categories of combined plasma Aβ were created by making bisection of plasma Aβ according to average and combining them as L-Aβ40 and L-Aβ42, H-Aβ40 and L-Aβ42, L-Aβ40 and H-Aβ42, H-Aβ40 and H-Aβ42. Decreased plasma Aβ40 was defined as < 25th percentile. Multivariate logistic regression examined the relationship between plasma Aβ and CI in total population, the hypertension subgroup and the non-hypertension subgroup.Results737 participants (49.5%) had hypertension and 189 participants (12.7%) had CI. Simultaneously elevated plasma Aβ40 and Aβ42 was associated with CI in hypertension (H-Aβ40 and H-Aβ42 vs. L-Aβ40 and L-Aβ42, 21.1% vs.10.7%, P = 0.033; OR = 1.984 [95% CI, 1.067–3.691], P = 0.030) but not in the non-hypertension. Decreased plasma Aβ40 was associated with CI in the non-hypertension (14.9% vs. 9.2%, P = 0.026; OR = 1.728 [95% CI, 1.018–2.931], P = 0.043) but not in the hypertension.ConclusionHypertension is an important modulator in the relationship between plasma Aβ and CI. Simultaneously elevated plasma Aβ40 and Aβ42 in the hypertension, and decreased plasma Aβ40 in the non-hypertension, may be risk factors for CI. These findings emphasize the need to consider hypertension in CI detection

Distributed State Estimation for Flapping-Wing Micro Air Vehicles with Information Fusion Correction

In this paper, we explore a nonlinear interactive network system comprising nodalized flapping-wing micro air vehicles (FMAVs) to address the distributed H∞ state estimation problem associated with FMAVs. We enhance the model by introducing an information fusion function, leading to an information-fusionized estimator model. This model ensures both estimation accuracy and the completeness of FMAV topological information within a unified framework. To facilitate the analysis, each FMAV’s received signal is individually sampled using independent and time-varying samplers. Transforming the received signals into equivalent bounded time-varying delays through the input delay method yields a more manageable and analyzable time-varying nonlinear network error system. Subsequently, we construct a Lyapunov–Krasovskii functional (LKF) and integrate it with the refined Wirtinger and relaxed integral inequalities to derive design conditions for the FMAVs’ distributed H∞ state estimator, minimizing conservatism. Finally, we validate the effectiveness and superiority of the designed estimator through simulations

Indoor Temperature Improvement and Energy-Saving Renovations in Rural Houses of China’s Cold Region—A Case Study of Shandong Province

With the continuous implementation of a plan for reconstruction of “Beautiful Countryside” in China, the rural environment and appearance of rural houses have been significantly improved. However, those houses in cold areas of China have great trouble with indoor temperature and heating-related energy consumption. After investigating the current situation of the layout, building envelope, indoor temperature, and energy consumption of the rural houses renovated by the plan of “Beautiful Countryside” in Shandong Province, this paper puts forward the improvement measures of raising indoor temperature and reducing energy consumption. On this basis, a typical rural house was selected, and DesignBuilder was utilized to simulate the effects before and after the application of different renovation measures for this house. The results show that the main way to raise indoor temperature and reduce energy consumption is to improve the thermal insulation performance of the building envelope, including renovation of the roof, exterior walls, doors and windows, and attached sunspace. In addition, combined with the achievements of “Beautiful Countryside” reconstruction, this paper shall propose specific renovation practices which are suitable for different rural houses. Based on the level of economic development in rural areas, it also puts forward some feasible renovation paths for different rural areas, and further provides references for other areas to carry out relevant work in the future