The relationship of circulating MOTS-c level with liver fibrosis and metabolic components in patients with metabolic dysfunction-associated fatty liver disease

OBJECTIVE

Mitochondrial open reading frame of the 12s ribosomal RNA type-c (MOTS-c) is a novel identified mitochondrial signal transmission peptide that plays an important role in glucose, amino acid and lipid metabolism. In this study, we aimed to investigate the relationship of circulating MOTS-c level with noninvasive scores of fibrosis and the components of metabolic syndrome (MetS) in patients with metabolic dysfunction-associated fatty liver disease (MAFLD).

PATIENTS AND METHODS

This was a single-center cross-sectional study, and the participants were divided into two groups based on their liver ultrasound results: the fatty liver group and the healthy control group. The MOTS-c level was measured by the ELISA method. Non-alcoholic fatty liver disease fibrosis score (NFS) and fibrosis 4 (FIB-4) were used to determine the level of liver fibrosis. Statistical analyses were performed using Statistical Package for Social Science 15.0 package program.

RESULTS

One hundred fifty patients (male, n=57) with MAFLD [median age 41.0 (14) years] and 84 healthy controls (male, n=34) [median age 36.0 (22) years] were included in this study. Patients with MAFLD had significantly lower MOTS-c levels than the healthy controls (p=0.009). The MOTS-c level was significantly lower in subjects with MetS (n=48) compared to those without MetS (n=186) (p=0.01). In the total population (n=234), MOTS-c levels negatively correlated with the presence of MAFLD, NFS, FIB-4, and components of MetS.

CONCLUSIONS

Individuals diagnosed with MetS and MAFLD tend to have lower levels of MOTS-c. Additionally, these lower levels are inversely correlated with both the components of MetS and noninvasive fibrosis scores. MAFLD negatively correlated to the MetS components and noninvasive scores of fibrosis.

Telemedicine-based early rule out and followup ECG algorithm for COVID-19 patients

Funding Acknowledgements

Type of funding sources: None.

Background

Drugs with the potential to prolong QT are used in the treatment of coronavirus 19 (COVID-19) pneumonia. We have developed a telemedicine-based corrected QT (QTc) follow-up algorithm that allows early rule out for follow up.

Aims

In this study, we investigated the availability and safety of the algorithm.

Study design

Retrospective cohort

Methods

Consecutive patients; administered hydroxychloroquine (HCQ) for COVID-19 pneumonia were enrolled into digital ECG recording program which includes QTc follow-up algorithm.

Results

Patients were classified into three groups as those, excluded promptly from the QTc follow-up based on two consecutive ECG findings (early rule out, n = 92) and those, for whom the follow-up was continued (n = 12) and usual care group (n = 68). Of note, 237 ECG tracings were performed in our algorithm population contrary to standard practice of daily recommended ECG monitoring which could have yielded 975 ECG tracings along with accompanied risks of exposure. This way; we ended in 738 (75.7%) fewer ECG tracings. Sustained ventricular arrhythmia or sudden cardiac death was not observed in the entire patient population.

Conclusions

It is safe to rely on telemedicine-based early rule out algorithm in COVID-19 patients, receiving hydroxychloroquine treatment. This algorithm abolished the need for further ECG in majority of patients without increased risk during follow up. These algorithms can significantly reduce the healthcare worker exposures by eliminating the need for ECG follow-up promptly.

Production and characterization of biosurfactants produced by microorganisms isolated from milk factory wastewaters

Biosurfactants or surface-active compounds are produced by microorganisms. These molecules reduce the surface tension of both aqueous solutions and hydrocarbon mixtures. In this study, the isolation and identification of biosurfactant-producing microorganisms were assessed. The characterization of biosurfactant produced by microorganisms isolated from milk factory wastewaters was investigated. For this purpose, five different microorganisms were isolated and identified. In order to determine the biosurfactant production, the 'drop-collapse' method was applied and it was determined that only three species, Yarrowia lipolytica MFW5 (yeast), Micrococcus luteus MFW1 (cocci) and Burkholderia cepacia MFW2 (bacillus), were able to produce biosurfactant. Biosurfactants produced by Yarrowia lipolytica, Micrococcus luteus and Burkholderia cepacia were coded as BS-I, BS-II and BS-III, respectively. After the initial biosurfactant production and characterization studies were completed, isolates of these three species were incubated with whey wastewaters at 35 degrees C for 10 days for biosurfactant production. At the end of the incubation period, the biosurfactants were extracted and further characterized with biochemical analysis, FTIR spectra, haemolysis test, emulsification test and determination of the surface tension.