The Korea Food Research Institute (KFRI) has successfully developed a functional ingredient derived from a smart farm-grown plant, drawing attention from both scientific and industrial circles.

Abstract

Purpose – This study explores the contagion of greenwashing strategies among ESG mutual funds. It investigates how the greenwashing behaviors of peer funds within the same family influence a fund’s decision to engage in greenwashing. The research also examines the impact of greenwashing on genuine ESG funds and explores the mechanisms through which greenwashing strategies spread across ESG mutual funds.

Design/methodology/approach – This paper employs a two-stage least squares regression model with cross-fund returns standard deviation as an instrumental variable to disentangle the peer effects of greenwashing from family-level characteristics. The analysis incorporates various fund characteristics and introduces four contagion channels through which greenwashing may influence genuine ESG funds.

Findings – The study finds greenwashing behavior in ESG funds is positively influenced by similar practices within their fund family. Larger assets under management and older funds with higher management fees show resilience against greenwashing influences, while team-managed funds are more susceptible. Additionally, socially responsible investors struggle to distinguish between genuine and greenwashing ESG funds, which may contribute to the persistence of greenwashing practices.

Originality/value – This paper contributes to the literature by delineating the mechanisms of greenwashing contagion within ESG mutual funds. It also examines the demand-side incentives for adopting greenwashing strategies, offering insights into the implications for fund flows and investor behavior. This study is among the first to analyze the contagion effects of greenwashing strategies across an extensive network of ESG funds, enriching our understanding of the broader impacts of greenwashing in the context of socially responsible investing.

The Korea Food Research Institute (KFRI), a government-funded research institution, collaborates with local distilleries to develop AI models trained on maturation data from traditional Korean spirits.

The hook effect is best explained by how the analyte signal generated from the assay is compromised due to either antibody excess or antigen excess. Reporting false negatives can also impact clinical decisions that may have adverse effects on the patient. The clinical impact of the hook effect will lead to reporting either inaccurately low or false-negative results. Six different patient pools were tested using immunoassay screening methods and also the LC-MS/MS confirmation method. For the immunoassay screening method, 50 ​μL of each patient sample is pooled together for every 100 patient samples. If there is a sample with the hook effect, it would give a very low or a negative result when the pool is tested neat and it would give a positive result when the pool is tested in a 1∶100 dilution. The drugs tested included Cannabinoids, Benzodiazepines, Amphetamines, Ecstasy, EDP, Opiates, Heroin, Cocaine, Fentanyl, Oxycodone and a combined method for Buprenorphine/Norbuprenorphine. Patient Pool number 6 showed a positive Buprenorphine and Norbuprenorphine that was traced back to the sample with the hook effect based on the suggested protocol. The random and different patient pools were prepared by using a Gilson GX241 liquid handler. The neat result for Pool number 6 showed the immunoassay for Buprenorpone and Norpuprenorphine was “Not Detected” at 2.1 ​μg/L while the LC-MS/MS result was 2,780 ​μg/L (cut-off <10 ​μg/L). However, the result for the 1 in 100 dilutions of the pool for the immunoassay was “Detected” at 37 ​μg/L without multiplying by the dilution factor. The result for the LC-MS/MS was 2,970 ​μg/L. The suggested protocol is practical and cost-effective to avoid the clinical impact of reporting either inaccurately low or false-negative results. Also, can be used for testing when suspected samples with the hook effect are investigated.

Abstract

Objective

Multiple reaction monitoring (MRM), is a highly sensitive targeted mass spectrometry technique that is used to validate discovery phase mass spectrometry data. Through this simple technique, relative protein expressions can be acquired without using commercially available antibodies.

Methods

Our previous work showed Gipie silencing of UM-HACC-2A (adenoid cystic carcinoma) cells resulted in upregulation of a plethora of immune proteins in immune cells in 3D ACC - immune co-culture model.

Results

MRM enabled determining relative protein expression of significantly upregulated immune proteins due to silencing of Gipie. Granzyme A, CD48, granzyme B, HLA class I, antigen B, HLA class I, antigen A, galectin 1, vimentin, endoplasmic reticulum chaperone BiP, and dipeptidyl peptidase 1 differential expressions were validated. Whereas coactosin-like protein expressions were found non-significant among control and Gipie silenced ACC.

Conclusions

This manuscript presents the validation data of previous discovery phase mass spectrometry and also accentuate the use of MRM in translational or preclinical studies in the field of biomedical sciences.