Enhancing Job Recommendation through LLM-based Generative Adversarial Networks

Recommending suitable jobs to users is a critical task in online recruitment platforms, as it can enhance users' satisfaction and the platforms' profitability. While existing job recommendation methods encounter challenges such as the low quality of users' resumes, which hampers their accuracy and practical effectiveness. With the rapid development of large language models (LLMs), utilizing the rich external knowledge encapsulated within them, as well as their powerful capabilities of text processing and reasoning, is a promising way to complete users' resumes for more accurate recommendations. However, directly leveraging LLMs to enhance recommendation results is not a one-size-fits-all solution, as LLMs may suffer from fabricated generation and few-shot problems, which degrade the quality of resume completion. In this paper, we propose a novel LLM-based approach for job recommendation. To alleviate the limitation of fabricated generation for LLMs, we extract accurate and valuable information beyond users' self-description, which helps the LLMs better profile users for resume completion. Specifically, we not only extract users' explicit properties (e.g., skills, interests) from their self-description but also infer users' implicit characteristics from their behaviors for more accurate and meaningful resume completion. Nevertheless, some users still suffer from few-shot problems, which arise due to scarce interaction records, leading to limited guidance for the models in generating high-quality resumes. To address this issue, we propose aligning unpaired low-quality with high-quality generated resumes by Generative Adversarial Networks (GANs), which can refine the resume representations for better recommendation results. Extensive experiments on three large real-world recruitment datasets demonstrate the effectiveness of our proposed method.Comment: 13 pages, 6 figures, 3 table

Comparative studies of the anti-thrombotic effects of saffron and HongHua based on network pharmacology

Purpose: To investigate the comparative anti-thrombotic effects of saffron and Honghua, and also to explore possible mechanisms in thrombosis based on network pharmacology. Methods: A network pharmacology model was used for bioactive components, targets and pathways for saffron and HongHua via Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), PharmMapper, Genecard, Uniprot and KEGG databases. In animal experiments, 72 rats were randomly divided into 9 groups: normal control group (NC), model control group (MC), crocetin groups (80, 40, 20 mg/kg), hydroxysafflor yellow A(HSYA) groups (80, 40, 20 mg/kg), and aspirin group (40 mg/kg). Using in vitro thrombosis models and an acute blood stasis model in vivo, the anti-thrombotic effects of these treatments on clotting time, hemorheology parameters, Thromboxane B2 (TXB2), plasmin activator inhibitor (PAI), protein C (PC), protein S (PS), and thrombinantithrombin complex (TAT) were determined and comparisons made for saffron and HongHua. Results: Five potential compounds, 16 anti-thrombotic targets and 27 pathways were predicted for saffron, while 22 compounds, 37 disease targets and 35 pathways were found for HongHua (p < 0.05). Pharmacological experiments revealed that crocetin and HSYA had significant effects on thrombus length, thrombus wet/dry mass, whole blood viscosity (WBV), erythrocyte aggregation index (EAI), clotting time and D-dimer for the high and middle groups. Unlike HSYA, crocetin also had significant and dose-dependent effects on PAI, prothrombin fragment 1+2 (F1+2) and PS and had highly significant effects on TXB2 and TAT. Conclusion: This research provides a systematic, comprehensive and comparative analysis of component, target and anti-thrombotic pathways of saffron and HongHua based on network pharmacology, and also shows that saffron has more significant anti-thrombotic effect than HongHua. Keywords: Saffron; HongHua; Network pharmacology; Anti-thrombosis; Network mode

Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1

IntroductionThe soybean cyst nematode (SCN) is a major disease in soybean production thatseriously affects soybean yield. At present, there are no studies on weighted geneco-expression network analysis (WGCNA) related to SCN resistance.MethodsHere, transcriptome data from 36 soybean roots under SCN HG Type 0 (race 3) stresswere used in WGCNA to identify significant modules.Results and DiscussionA total of 10,000 differentially expressed genes and 21 modules were identified, of which the module most related to SCN was turquoise. In addition, the hub gene GmHg1 with high connectivity was selected, and its function was verified. GmHg1 encodes serine/threonine protein kinase (PK), and the expression of GmHg1 in SCN-resistant cultivars (‘Dongnong L-204’) and SCN-susceptible cultivars (‘Heinong 37’) increased significantly after HG Type 0 stress. Soybean plants transformed with GmHg1-OX had significantly increased SCN resistance. In contrast, the GmHg1-RNAi transgenic soybean plants significantly reduced SCN resistance. In transgenic materials, the expression patterns of 11 genes with the same expression trend as the GmHg1 gene in the ‘turquoise module’ were analyzed. Analysis showed that 11genes were co-expressed with GmHg1, which may be involved in the process of soybean resistance to SCN. Our work provides a new direction for studying the Molecular mechanism of soybean resistance to SCN

Distributional benefits of tobacco tax and smoke–free workplaces in China: A modeling study

Background: Tobacco taxation and smoke–free workplaces reduce smoking, tobacco–related premature deaths and associated out–of–pocket health care expenditures. We examine the distributional consequences of a price increase in tobacco products through an excise tax hike, and of an implementation of smoke–free workplaces, in China. Methods: We use extended cost–effectiveness analysis (ECEA) to evaluate, across income quintiles of the male population (the large majority of Chinese smokers), the premature deaths averted, the change in tax revenues generated, and the financial risk protection procured (eg, poverty cases averted, defined as the number of individuals no longer facing tobacco–related out–of–pocket expenditures for disease treatment, that would otherwise impoverish them), that would follow a 75% increase in cigarette prices through substantial increments in excise tax fully passed onto consumers, and a nationwide total implementation of workplace smoking bans. Results: A 75% increase in cigarette prices would avert about 24 million premature deaths among the current Chinese male population, with a third among the bottom income quintile, increase additional tax revenues by US$46 billion annually, and prevent around 9 million poverty cases, 19$ 7 billion annually, and prevent around 4 million poverty cases, 12% of which among the bottom income quintile. Conclusions: Increased excise taxes on tobacco products and workplace smoking bans can procure large health and economic benefits to the Chinese population, especially among the poor

Retrogradely Transportable Lentivirus Tracers for Mapping Spinal Cord Locomotor Circuits

Retrograde tracing is a key facet of neuroanatomical studies involving long distance projection neurons. Previous groups have utilized a variety of tools ranging from classical chemical tracers to newer methods employing viruses for gene delivery. Here, we highlight the usage of a lentivirus that permits highly efficient retrograde transport (HiRet) from synaptic terminals within the cervical and lumbar enlargements of the spinal cord. By injecting HiRet, we can clearly identify supraspinal and propriospinal circuits innervating motor neuron pools relating to forelimb and hindlimb function. We observed robust labeling of propriospinal neurons, including high fidelity details of dendritic arbors and axon terminals seldom seen with chemical tracers. In addition, we examine changes in interneuronal circuits occurring after a thoracic contusion, highlighting populations that potentially contribute to spontaneous behavioral recovery in this lesion model. Our study demonstrates that the HiRet lentivirus is a unique tool for examining neuronal circuitry within the brain and spinal cord

Identification of QTL underlying vitamin E contents in soybean seed among multiple environments

Vitamin E (VE) in soybean seed has value for foods, medicines, cosmetics, and animal husbandry. Selection for higher VE contents in seeds along with agronomic traits was an important goal for many soybean breeders. In order to map the loci controlling the VE content, F5-derived F6 recombinant inbred lines (RILs) were advanced through single-seed-descent (SSD) to generate a population including 144 RILs. The population was derived from a cross between ‘OAC Bayfield’, a soybean cultivar with high VE content, and ‘Hefeng 25’, a soybean cultivar with low VE content. A total of 107 polymorphic simple sequence repeat markers were used to construct a genetic linkage map. Seed VE contents were analyzed by high performance liquid chromatography for multiple years and locations (Harbin in 2007 and 2008, Hulan in 2008 and Suihua in 2008). Four QTL associated with α-Toc (on four linkage groups, LGs), eight QTL associated with γ-Toc (on eight LGs), four QTL associated with δ-Toc (on four LGs) and five QTL associated with total VE (on four LGs) were identified. A major QTL was detected by marker Satt376 on linkage group C2 and associated with α-Toc (0.0012 > P > 0.0001, 5.0% < R2 < 17.0%, 25.1 < α-Toc < 30.1 μg g−1), total VE (P < 0.0001, 7.0% < R2 < 10.0%, 118.2 < total VE < 478.3 μg g−1). A second QTL detected by marker Satt286 on LG C2 was associated with γ-Toc (0.0003 > P > 0.0001, 6.0% < R2 < 13.0%, 141.5 < γ-Toc < 342.4 μg g−1) and total VE (P < 0.0001, 2.0% < R2 < 9.0%, 353.9 < total VE < 404.0 μg g−1). Another major QTL was detected by marker Satt266 on LG D1b that was associated with α-Toc (0.0002 > P > 0.0001, 4.0% < R2 < 6.0%, 27.7 < α-Toc < 43.7 μg g−1) and γ-Toc (0.0032 > P > 0.0001, 3.0% < R2 < 10.0%, 69.7 < γ-Toc < 345.7 μg g−1). Since beneficial alleles were all from ‘OAC Bayfield’, it was concluded that these three QTL would have great potential value for marker assisted selection for high VE content

Probing the Carboxyester Side Chain in Controlled Deactivation (−)-Δ8-Tetrahydrocannabinols

We recently reported on a controlled deactivation/detoxification approach for obtaining cannabinoids with improved druggability. Our design incorporates a metabolically labile ester group at strategic positions within the THC structure. We have now synthesized a series of (−)-Δ8-THC analogues encompassing a carboxyester group within the 3-alkyl chain in an effort to explore this novel cannabinergic chemotype for CB receptor binding affinity, in vitro and in vivo potency and efficacy, as well as controlled deactivation by plasma esterases. We have also probed the chain’s polar characteristics with regard to fast onset and short duration of action. Our lead molecule, namely 2-[(6aR,10aR)-6a,7,10,10a-tetrahydro-1-hydroxy-6,6,9-trimethyl-6H-dibenzo[b,d]pyran-3-yl]-2-methyl-propanoic acid 3-cyano-propyl ester (AM7438), showed picomolar affinity for CB receptors and is deactivated by plasma esterases while the respective acid metabolite is inactive. In further in vitro and in vivo experiments, the compound was found to be a remarkably potent and efficacious CB1 receptor agonist with relatively fast onset/offset of action