Efficacy and safety of Kumpe access catheter for pre-percutaneous nephrolithotomy renal access in modified supine percutaneous nephrolithotomy.

INTRODUCTION: Traditionally, a pigtail catheter (PCN) is placed for preoperative renal access before performing percutaneous nephrolithotomy (PCNL). However, PCN can hamper the passage of the guidewire to the ureter, due to which, access tract can be lost. Therefore, Kumpe Access Catheter (KMP) has been proposed for preoperative renal access before PCNL. In this study, we analyzed the efficacy and safety of KMP for surgical outcomes in modified supine PCNL compared to those in PCN. MATERIALS AND METHODS: From July 2017 to December 2020, 232 patients underwent modified supine PCNL at a single tertiary center, of which 151 patients were enrolled in this study after excluding patients who underwent bilateral surgery, multiple punctures, or combined operations. Enrolled patients were divided into two groups according to the type of pre-PCNL nephrostomy catheter used: PCN versus KMP. A pre-PCNL nephrostomy catheter was selected based on the radiologist's preference. A single surgeon performed all PCNL procedures. Patient characteristics and surgical outcomes, including stone-free rate, operation time, radiation exposure time (RET), and complications, were compared between the two groups. RESULTS: Of the 151 patients, 53 underwent PCN placement, and 98 underwent KMP placement for pre-PCNL nephrostomy. Patient baseline characteristics were comparable between the two groups, except for the renal stone type and multiplicity. The operation time, stone-free rate, and complication rate were not significantly different between the two groups; however, RET was significantly shorter in the KMP group. CONCLUSION: The surgical outcomes of KMP placement were comparable to those of PCN and showed shorter RET during modified supine PCNL. Based on our results, we recommend KMP placement for pre-PCNL nephrostomy, particularly for reducing RET during supine PCNL.

Cerebrospinal Fluid Metabolome in Parkinson's Disease and Multiple System Atrophy.

Parkinson's disease (PD) and multiple system atrophy (MSA) belong to the neurodegenerative group of synucleinopathies; differential diagnosis between PD and MSA is difficult, especially at early stages, owing to their clinical and biological similarities. Thus, there is a pressing need to identify metabolic biomarkers for these diseases. The metabolic profile of the cerebrospinal fluid (CSF) is reported to be altered in PD and MSA; however, the altered metabolites remain unclear. We created a single network with altered metabolites in PD and MSA based on the literature and assessed biological functions, including metabolic disorders of the nervous system, inflammation, concentration of ATP, and neurological disorder, through bioinformatics methods. Our in-silico prediction-based metabolic networks are consistent with Parkinsonism events. Although metabolomics approaches provide a more quantitative understanding of biochemical events underlying the symptoms of PD and MSA, limitations persist in covering molecules related to neurodegenerative disease pathways. Thus, omics data, such as proteomics and microRNA, help understand the altered metabolomes mechanism. In particular, integrated omics and machine learning approaches will be helpful to elucidate the pathological mechanisms of PD and MSA. This review discusses the altered metabolites between PD and MSA in the CSF and omics approaches to discover diagnostic biomarkers.

Human Bone Marrow-Derived Mesenchymal Stem Cell Applications in Neurodegenerative Disease Treatment and Integrated Omics Analysis for Successful Stem Cell Therapy.

Neurodegenerative diseases (NDDs), which are chronic and progressive diseases, are a growing health concern. Among the therapeutic methods, stem-cell-based therapy is an attractive approach to NDD treatment owing to stem cells' characteristics such as their angiogenic ability, anti-inflammatory, paracrine, and anti-apoptotic effects, and homing ability to the damaged brain region. Human bone-marrow-derived mesenchymal stem cells (hBM-MSCs) are attractive NDD therapeutic agents owing to their widespread availability, easy attainability and in vitro manipulation and the lack of ethical issues. Ex vivo hBM-MSC expansion before transplantation is essential because of the low cell numbers in bone marrow aspirates. However, hBM-MSC quality decreases over time after detachment from culture dishes, and the ability of hBM-MSCs to differentiate after detachment from culture dishes remains poorly understood. Conventional analysis of hBM-MSCs characteristics before transplantation into the brain has several limitations. However, omics analyses provide more comprehensive molecular profiling of multifactorial biological systems. Omics and machine learning approaches can handle big data and provide more detailed characterization of hBM-MSCs. Here, we provide a brief review on the application of hBM-MSCs in the treatment of NDDs and an overview of integrated omics analysis of the quality and differentiation ability of hBM-MSCs detached from culture dishes for successful stem cell therapy.

Development of Anticancer Peptides Using Artificial Intelligence and Combinational Therapy for Cancer Therapeutics.

Cancer is a group of diseases causing abnormal cell growth, altering the genome, and invading or spreading to other parts of the body. Among therapeutic peptide drugs, anticancer peptides (ACPs) have been considered to target and kill cancer cells because cancer cells have unique characteristics such as a high negative charge and abundance of microvilli in the cell membrane when compared to a normal cell. ACPs have several advantages, such as high specificity, cost-effectiveness, low immunogenicity, minimal toxicity, and high tolerance under normal physiological conditions. However, the development and identification of ACPs are time-consuming and expensive in traditional wet-lab-based approaches. Thus, the application of artificial intelligence on the approaches can save time and reduce the cost to identify candidate ACPs. Recently, machine learning (ML), deep learning (DL), and hybrid learning (ML combined DL) have emerged into the development of ACPs without experimental analysis, owing to advances in computer power and big data from the power system. Additionally, we suggest that combination therapy with classical approaches and ACPs might be one of the impactful approaches to increase the efficiency of cancer therapy.

Diesel-derived PM2.5 induces impairment of cardiac movement followed by mitochondria dysfunction in cardiomyocytes.

Particulate matter (PM) in polluted air can be exposed to the human body through inhalation, ingestion, and skin contact, accumulating in various organs throughout the body. Organ accumulation of PM is a growing health concern, particularly in the cardiovascular system. PM emissions are formed in the air by solid particles, liquid droplets, and fuel - particularly diesel - combustion. PM2.5 (size < 2.5 µm particle) is a major risk factor for approximately 200,000 premature deaths annually caused by air pollution. This study assessed the deleterious effects of diesel-derived PM2.5 exposure in HL-1 mouse cardiomyocyte cell lines. The PM2.5-induced biological changes, including ultrastructure, intracellular reactive oxygen species (ROS) generation, viability, and intracellular ATP levels, were analyzed. Moreover, we analyzed changes in transcriptomics using RNA sequencing and metabolomics using gas chromatography-tandem mass spectrometry (GC-MS/MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) in PM2.5-treated HL-1 cells. Ultrastructural analysis using transmission electron microscopy revealed disruption of mitochondrial cristae structures in a PM2.5 dose-dependent manner. The elevation of ROS levels and reduction in cell viability and ATP levels were similarly observed in a PM2.5 dose-dependently. In addition, 6,005 genes were differentially expressed (fold change cut-off ± 4) from a total of 45,777 identified genes, and 20 amino acids (AAs) were differentially expressed (fold change cut-off ± 1.2) from a total of 28 identified AAs profiles. Using bioinformatic analysis with ingenuity pathway analysis (IPA) software, we found that the changes in the transcriptome and metabolome are highly related to changes in biological functions, including homeostasis of Ca2+, depolarization of mitochondria, the function of mitochondria, synthesis of ATP, and cardiomyopathy. Moreover, an integrated single omics network was constructed by combining the transcriptome and the metabolome. In silico prediction analysis with IPA predicted that upregulation of mitochondria depolarization, ROS generation, cardiomyopathy, suppression of Ca2+ homeostasis, mitochondrial function, and ATP synthesis occurred in PM2.5-treated HL-1 cells. In particular, the cardiac movement of HL-1 was significantly reduced after PM2.5 treatment. In conclusion, our results assessed the harmful effects of PM2.5 on mitochondrial function and analyzed the biological changes related to cardiac movement, which is potentially associated with cardiovascular diseases.

Reduction in the Migration Activity of Microglia Treated with Silica-Coated Magnetic Nanoparticles and their Recovery Using Citrate.

Nanoparticles have garnered significant interest in neurological research in recent years owing to their efficient penetration of the blood-brain barrier (BBB). However, significant concerns are associated with their harmful effects, including those related to the immune response mediated by microglia, the resident immune cells in the brain, which are exposed to nanoparticles. We analysed the cytotoxic effects of silica-coated magnetic nanoparticles containing rhodamine B isothiocyanate dye [MNPs@SiO2(RITC)] in a BV2 microglial cell line using systems toxicological analysis. We performed the invasion assay and the exocytosis assay and transcriptomics, proteomics, metabolomics, and integrated triple-omics analysis, generating a single network using a machine learning algorithm. The results highlight alteration in the mechanisms of the nanotoxic effects of nanoparticles using integrated omics analysis.

Analysis of Nanotoxicity with Integrated Omics and Mechanobiology.

Nanoparticles (NPs) in biomedical applications have benefits owing to their small size. However, their intricate and sensitive nature makes an evaluation of the adverse effects of NPs on health necessary and challenging. Since there are limitations to conventional toxicological methods and omics analyses provide a more comprehensive molecular profiling of multifactorial biological systems, omics approaches are necessary to evaluate nanotoxicity. Compared to a single omics layer, integrated omics across multiple omics layers provides more sensitive and comprehensive details on NP-induced toxicity based on network integration analysis. As multi-omics data are heterogeneous and massive, computational methods such as machine learning (ML) have been applied for investigating correlation among each omics. This integration of omics and ML approaches will be helpful for analyzing nanotoxicity. To that end, mechanobiology has been applied for evaluating the biophysical changes in NPs by measuring the traction force and rigidity sensing in NP-treated cells using a sub-elastomeric pillar. Therefore, integrated omics approaches are suitable for elucidating mechanobiological effects exerted by NPs. These technologies will be valuable for expanding the safety evaluations of NPs. Here, we review the integration of omics, ML, and mechanobiology for evaluating nanotoxicity.

Effect of evaporation-induced osmotic changes in culture media in a dry-type incubator on clinical outcomes in in vitro fertilization-embryo transfer cycles.

OBJECTIVE: This study investigated whether adding outer-well medium to inhibit osmotic changes in culture media in a dry-type incubator improved the clinical outcomes of in vitro fertilization-embryo transfer (IVF-ET) cycles. METHODS: In culture dishes, the osmotic changes in media (20 µL)-covered oil with or without outer-well medium (humid or dry culture conditions, respectively) were compared after 3 days of incubation in a dry-type incubator. One-step (Origio) and G1/G2 (Vitrolife) media were used. RESULTS: The osmotic changes in the dry culture condition (308 mOsm) were higher than in the humid culture conditions (285-290 mOsm) after 3 days of incubation. In day 3 IVF-ET cycles, although the pregnancy rate did not significantly differ between the dry (46.2%) and humid culture (52.2%) groups, the rates of abortion and ongoing pregnancy were significantly better in the humid culture group (2.3% and 50.2%, respectively) than in the dry culture group (8.3% and 37.8%, respectively, p<0.05). In day 5 IVF-ET cycles, the abortion rate was significantly lower in the humid culture group (2.2%) than in the dry culture group (25.0%, p<0.01), but no statistically significant difference was observed in the rates of clinical and ongoing pregnancy between the dry (50.0% and 25.0%, respectively) and humid culture groups (59.5% and 57.3%, respectively) because of the small number of cycles. CONCLUSION: Hyperosmotic changes in media occurred in a dry-type incubator by evaporation, although the medium was covered with oil. These osmotic changes were efficiently inhibited by supplementation of outer-well medium, which resulted in improved pregnancy outcomes.

Early fragment removal on in vitro fertilization day 2 significantly improves the subsequent development and clinical outcomes of fragmented human embryos.

OBJECTIVE: To determine whether fragment removal on in vitro fertilization (IVF) day 2 improved the subsequent development and pregnancy outcomes of fragmented embryos compared to similar-grade embryos without fragment removal. METHODS: This study was a retrospective analysis involving 191 IVF cycles in which all embryos had over 10% fragmentation (grade 3 or 4) on day 2 of the IVF-embryo transfer cycle from March 2015 to December 2017. IVF cycles were divided into the fragment removal group (n=87) and the no fragment removal group (n=104) as a control cohort. Before fragment removal, embryos with fragmentation on day 2 were incubated in Ca2+- and Mg2+-free biopsy medium under paraffin oil for 30 minutes. Microsurgical fragment removal was performed with later-assisted hatching and a handmade suction micropipette that had an outer diameter of 30 µm. RESULTS: There were no significant differences in the characteristics of the patients between the control and the fragment removal groups. After fragment removal and subsequent in vitro culture for 24 hours, the number of blastomeres (7.1±1.7 vs. 6.9±1.6) was comparable between the transferred embryos in the two groups, but the morphological grade of the embryos in the fragment removal group (1.9±0.7) was significantly higher than that of the control group (3.1±0.5, p<0.01). The clinical pregnancy (43.7%) and implantation rates (25.8%) in the fragment removal group were significantly higher than those in the control group (28.8% and 14.0%, respectively; p<0.05). CONCLUSION: Early fragment removal on day 2 significantly improved the subsequent development and pregnancy outcomes of fragmented embryos.

ICSI significantly improved the pregnancy rate of patients with a high sperm DNA fragmentation index.

OBJECTIVE: Correlations between semen parameters and sperm DNA fragmentation index (DFI) were investigated to identify characteristics of sperm without DNA damage that could be used in selecting sperm for intracytoplasmic sperm injection (ICSI). Pregnancy outcomes were compared to determine whether in vitro fertilization (IVF) or ICSI is a better choice for patients who have sperm with a high-DFI. METHODS: Semen analysis was carried out in 388 patients who visited our IVF center for the first time to investigate correlations between sperm DFI and semen parameters. In addition, 1,102 IVF cycles in 867 patients were carried out in the present study; 921 cycles in the low-DFI group (DFI <30%) and 181 cycles in the high-DFI group (DFI ≥30%). Both the low- and high-DFI groups were subdivided into IVF and ICSI cycle groups. RESULTS: Sperm DFI showed significant inverse correlations with sperm motility (r=-0.435, p<0.001) and morphology (r=-0.153, p<0.05). Sperm DFI also showed significant correlations with rapid motility (r=-0.436, p<0.001), and the kinetic parameters of average-path velocity (r=-0.403) and linearity (r=-0.412). Although there was no significant difference in the pregnancy rates between IVF (48.6%) and ICSI (44.8%) in the low-DFI group, the pregnancy rate of ICSI cycles (44.8%, p<0.05) was significantly higher than IVF cycles (25.0%) in the high-DFI group. No significant difference was observed in the abortion rates between the low-DFI (52 of 921, 5.6%) and high-DFI groups (7 of 181, 3.8%). CONCLUSION: ICSI is a better choice than IVF for improving the pregnancy outcomes of patients who have sperm with a high DFI.

Efficient isolation of sperm with high DNA integrity and stable chromatin packaging by a combination of density-gradient centrifugation and magnetic-activated cell sorting.

OBJECTIVE: This study was carried out to investigate the correlations of the sperm DNA fragmentation index (DFI) with semen parameters and apoptosis, and to investigate the effects of density-gradient centrifugation (DGC) and magnetic-activated cell sorting (MACS) on reducing the proportion of sperm with DNA fragmentation and protamine deficiency. METHODS: Semen analysis and a sperm DNA fragmentation assay were performed to assess the correlations between semen parameters and the DFI in 458 semen samples. Sperm with progressive motility or non-apoptosis were isolated by DGC or MACS, respectively, in 29 normozoospermic semen samples. The effects of DGC or MACS alone and of DGC and MACS combined on reducing the amount of sperm in the sample with DNA fragmentation and protamine deficiency were investigated. RESULTS: The sperm DFI showed a significant correlation (r=-0.347, p<0.001) with sperm motility and morphology (r=-0.114, p<0.05) but not with other semen parameters. The DFI (11.5%±2.0%) of semen samples was significantly reduced by DGC (8.1%±4.1%) or MACS alone (7.4%±3.9%) (p<0.05). The DFI was significantly further reduced by a combination of DGC and MACS (4.1%±1.3%, p<0.05). Moreover, the combination of DGC and MACS (1.6%±1.1%, p<0.05) significantly reduced the protamine deficiency rate of semen samples compared to DGC (4.4%±3.2%) or MACS alone (3.4%±2.2%). CONCLUSION: The combination of DGC and MACS may be an effective method to isolate high-quality sperm with progressive motility, non-apoptosis, high DNA integrity, and low protamine deficiency in clinical use.