Mitochondrial stress and the dysregulated mitochondrial unfolded protein response (UPRmt) are linked to various diseases, including metabolic disorders, neurodegenerative diseases, and cancer. Mitokines, signaling molecules released by mitochondrial stress response and UPRmt, are crucial mediators of inter-organ communication and influence systemic metabolic and physiological processes. In this review, we provide a comprehensive overview of mitokines, including their regulation by exercise and lifestyle interventions and their implications for various diseases. The endocrine actions of mitokines related to mitochondrial stress and adaptations are highlighted, specifically the broad functions of fibroblast growth factor 21 and growth differentiation factor 15, as well as their specific actions in regulating inter-tissue communication and metabolic homeostasis. Finally, we discuss the potential of physiological and genetic interventions to reduce the hazards associated with dysregulated mitokine signaling and preserve an equilibrium in mitochondrial stress-induced responses. This review provides valuable insights into the mechanisms underlying mitochondrial regulation of health and disease by exploring mitokine interactions and their regulation, which will facilitate the development of targeted therapies and personalized interventions to improve health outcomes and quality of life.

Paracrine interactions are imperative for the maintenance of adipose tissue intercellular homeostasis, and intracellular organelle dysfunction results in local and systemic alterations in metabolic homeostasis. It is currently accepted that mitochondrial proteotoxic stress activates the mitochondrial unfolded protein response (UPRmt) in vitro and in vivo. The induction of mitochondrial chaperones and proteases during the UPRmt is a key cell-autonomous mechanism of mitochondrial quality control. The UPRmt also affects systemic metabolism through the secretion of cell non-autonomous peptides and cytokines (hereafter, metabokines). Mitochondrial function in adipose tissue plays a pivotal role in whole-body metabolism and human diseases. Despite continuing interest in the role of the UPRmt and quality control pathways of mitochondria in energy metabolism, studies on the roles of the UPRmt and metabokines in white adipose tissue are relatively sparse. Here, we describe the role of the UPRmt in adipose tissue, including adipocytes and resident macrophages, and the interactive roles of cell non-autonomous metabokines, particularly growth differentiation factor 15, in local adipose cellular homeostasis and systemic energy metabolism.

Background: A Korean Multicenter Prospective cohort study of Active Surveillance or Surgery (KoMPASS) for papillary thyroid microcarcinomas (PTMCs) has been initiated. The aim is to compare clinical outcomes between active surveillance (AS) and an immediate lobectomy for low-risk PTMCs. We here outline the detailed protocol for this study. Methods: Adult patients with a cytopathologically confirmed PTMC sized 6.0 to 10.0 mm by ultrasound (US) will be included. Patients will be excluded if they have a suspicious extra-thyroidal extension or metastasis of a PTMC or multiple thyroid nodules or other thyroid diseases which require a total thyroidectomy. Printed material describing the prognosis of PTMCs, and the pros and cons of each management option, will be provided to eligible patients to select their preferred intervention. For the AS group, thyroid US, thyroid function, and quality of life (QoL) parameters will be monitored every 6 months during the first year, and then annually thereafter. Disease progression will be defined as a ≥3 mm increase in maximal diameter of a PTMC, or the development of new thyroid cancers or metastases. If progression is detected, patients should undergo appropriate surgery. For the lobectomy group, a lobectomy with prophylactic central neck dissection will be done within 6 months. After initial surgery, thyroid US, thyroid function, serum thyroglobulin (Tg), anti-Tg antibody, and QoL parameters will be monitored every 6 months during the first year and annually thereafter. Disease progression will be defined in these cases as the development of new thyroid cancers or metastases. Conclusion KoMPASS findings will help to confirm the role of AS, and develop individualized management strategies, for low-risk PTMCs.

Objective: To evaluate the trueness and precision of full-arch scans acquired using five intraoral scanners and investigate the factors associated with the dimensional accuracy of the intraoral scan data. Methods: Nine adult participants (mean age, 34.3 ± 8.3 years) were recruited. Four zirconium spheres (Ø 6 mm) were bonded to the canines and the molars. Following acquisition of reference scans using an industrial-grade scanner, five intraoral scanners, namely i500, CS3600, Trios 3, iTero, and CEREC Omnicam, were used to scan the arches. Linear distances between the four reference spheres were automatically calculated, and linear mixed model analysis was performed to compare the trueness and precision of the intraoral scan data among the different scanners. Results: The absolute mean trueness and precision values for all intraoral scanners were 76.6 ± 79.3 and 56.6 ± 52.4 µm, respectively. The type of scanner and the measured linear distances had significant effects on the accuracy of the intraoral scan data. With regard to trueness, errors in the intermolar dimension and the distance from the canine to the contralateral molar were greater with Omnicam than with the other scanners. With regard to precision, the error in the linear distance from the canine to the molar in the same quadrant was greater with Omnicam and CS3600 than with the other scanners. Conclusions The dimensional accuracy of intraoral scan data may differ significantly according to the type of scanner, with the amount of error in terms of trueness being clinically significant.

Background: A Korean Multicenter Prospective cohort study of Active Surveillance or Surgery (KoMPASS) for papillary thyroid microcarcinomas (PTMCs) has been initiated. The aim is to compare clinical outcomes between active surveillance (AS) and an immediate lobectomy for low-risk PTMCs. We here outline the detailed protocol for this study. Methods: Adult patients with a cytopathologically confirmed PTMC sized 6.0 to 10.0 mm by ultrasound (US) will be included. Patients will be excluded if they have a suspicious extra-thyroidal extension or metastasis of a PTMC or multiple thyroid nodules or other thyroid diseases which require a total thyroidectomy. Printed material describing the prognosis of PTMCs, and the pros and cons of each management option, will be provided to eligible patients to select their preferred intervention. For the AS group, thyroid US, thyroid function, and quality of life (QoL) parameters will be monitored every 6 months during the first year, and then annually thereafter. Disease progression will be defined as a ≥3 mm increase in maximal diameter of a PTMC, or the development of new thyroid cancers or metastases. If progression is detected, patients should undergo appropriate surgery. For the lobectomy group, a lobectomy with prophylactic central neck dissection will be done within 6 months. After initial surgery, thyroid US, thyroid function, serum thyroglobulin (Tg), anti-Tg antibody, and QoL parameters will be monitored every 6 months during the first year and annually thereafter. Disease progression will be defined in these cases as the development of new thyroid cancers or metastases. Conclusion KoMPASS findings will help to confirm the role of AS, and develop individualized management strategies, for low-risk PTMCs.

Objective: To evaluate the trueness and precision of full-arch scans acquired using five intraoral scanners and investigate the factors associated with the dimensional accuracy of the intraoral scan data. Methods: Nine adult participants (mean age, 34.3 ± 8.3 years) were recruited. Four zirconium spheres (Ø 6 mm) were bonded to the canines and the molars. Following acquisition of reference scans using an industrial-grade scanner, five intraoral scanners, namely i500, CS3600, Trios 3, iTero, and CEREC Omnicam, were used to scan the arches. Linear distances between the four reference spheres were automatically calculated, and linear mixed model analysis was performed to compare the trueness and precision of the intraoral scan data among the different scanners. Results: The absolute mean trueness and precision values for all intraoral scanners were 76.6 ± 79.3 and 56.6 ± 52.4 µm, respectively. The type of scanner and the measured linear distances had significant effects on the accuracy of the intraoral scan data. With regard to trueness, errors in the intermolar dimension and the distance from the canine to the contralateral molar were greater with Omnicam than with the other scanners. With regard to precision, the error in the linear distance from the canine to the molar in the same quadrant was greater with Omnicam and CS3600 than with the other scanners. Conclusions The dimensional accuracy of intraoral scan data may differ significantly according to the type of scanner, with the amount of error in terms of trueness being clinically significant.

Objective: Alzheimer’s disease (AD) is the most common type of dementia and the prevalence rapidly increased as the elderly population increased worldwide. In the contemporary model of AD, it is regarded as a disease continuum involving preclinical stage to severe dementia. For accurate diagnosis and disease monitoring, objective index reflecting structural change of brain is needed to correctly assess a patient’s severity of neurodegeneration independent from the patient’s clinical symptoms. The main aim of this paper is to develop a random forest (RF) algorithm-based prediction model of AD using structural magnetic resonance imaging (MRI). Methods: We evaluated diagnostic accuracy and performance of our RF based prediction model using newly developed brain segmentation method compared with the Freesurfer’s which is a commonly used segmentation software. Results: Our RF model showed high diagnostic accuracy for differentiating healthy controls from AD and mild cognitive impairment (MCI) using structural MRI, patient characteristics, and cognitive function (HC vs. AD 93.5%, AUC 0.99; HC vs. MCI 80.8%, AUC 0.88). Moreover, segmentation processing time of our algorithm (<5 minutes) was much shorter than of Freesurfer’s (6–8 hours). Conclusion Our RF model might be an effective automatic brain segmentation tool which can be easily applied in real clinical practice.

Growth differentiation factor 15 (GDF15) is receiving great interest beyond its role as an aging and disease-related biomarker. Recent discovery of its receptor, glial cell line-derived neurotrophic factor (GDNF) family receptor α-like (GFRAL), suggests a central role in appetite regulation. However, there is also considerable evidence that GDF15 may have peripheral activity through an as-of-yet undiscovered mode of action. This raises the question as to whether increased GDF15 induction during pathophysiologic conditions also suppresses appetite. The present review will briefly introduce the discovery of GDF15 and describe the different contexts under which GDF15 is induced, focusing on its induction during mitochondrial dysfunction. We will further discuss the metabolic role of GDF15 under various pathophysiological conditions and conclude with possible therapeutic applications.

More effective production of human insulin is important, because insulin is the main medication that is used to treat multiple types of diabetes and because many people are suffering from diabetes. The current system of insulin production is based on recombinant DNA technology, and the expression vector is composed of a preproinsulin sequence that is a fused form of an artificial leader peptide and the native proinsulin. It has been reported that the sequence of the leader peptide affects the production of insulin. To analyze how the leader peptide affects the maturation of insulin structurally, we adapted several in silico simulations using 13 artificial proinsulin sequences. Three-dimensional structures of models were predicted and compared. Although their sequences had few differences, the predicted structures were somewhat different. The structures were refined by molecular dynamics simulation, and the energy of each model was estimated. Then, protein-protein docking between the models and trypsin was carried out to compare how efficiently the protease could access the cleavage sites of the proinsulin models. The results showed some concordance with experimental results that have been reported; so, we expect our analysis will be used to predict the optimized sequence of artificial proinsulin for more effective production.
Computer Simulation ; DNA, Recombinant ; Humans* ; Insulin ; Molecular Dynamics Simulation* ; Proinsulin ; Protein Sorting Signals ; Trypsin