Phenotypic Discovery of SB1501, an Anti-obesity Agent,through Modulating Mitochondrial Activity

Obesity has become a pandemic that threatens the quality of life and discovering novel therapeutic agents that can reverse obesity and obesity-related metabolic disorders are necessary. Here, we aimed to identify new anti-obesity agents using a phenotype-based approach. We performed image-based high-content screening with a fluorogenic bioprobe (SF44), which visualizes cellular lipid droplets (LDs), to identify initial hit compounds. A structure-activity relationship study led us to yield a bioactive compound SB1501, which reduces cellular LDs in 3T3-L1 adipocytes without cytotoxicity. SB1501 induced the expression of gene products that regulate mitochondrial biogenesis and fatty acid oxidation in 3T3-L1 adipocytes. Daily treatment with SB1501 improved the metabolic states of db/db mice by reducing body fat mass, adipose tissue mass, food intake, and increasing glucose tolerance. The anti-obesity effect of SB1501 may result from perturbation of the PGC-1α–UCP1 regulatory axis in inguinal white adipose tissue and brown adipose tissue. These data suggest the therapeutic potential of SB1501 as an anti-obesity agent via modulating mitochondrial activities.     

Preclinical Evaluation of 99mTc-ZHER2:41071, a Second-Generation Affibody-Based HER2-Visualizing Imaging Probe with a Low Renal Uptake

Radionuclide imaging of HER2 expression in tumours may enable stratification of patients with breast, ovarian, and gastroesophageal cancers for HER2-targeting therapies. A first-generation HER2-binding affibody molecule [^99mTc]Tc-ZHER2:V2 demonstrated favorable imaging properties in preclinical studies. Thereafter, the affibody scaffold has been extensively modified, which increased its melting point, improved storage stability, and increased hydrophilicity of the surface. In this study, a second-generation affibody molecule (designated ZHER2:41071) with a new improved scaffold has been prepared and characterized. HER2-binding, biodistribution, and tumour-targeting properties of [^99mTc]Tc-labelled ZHER2:41071 were investigated. These properties were compared with properties of the first-generation affibody molecules, [^99mTc]Tc-ZHER2:V2 and [^99mTc]Tc-ZHER2:2395. [^99mTc]Tc-ZHER2:41071 bound specifically to HER2 expressing cells with an affinity of 58 ± 2 pM. The renal uptake for [^99mTc]Tc-ZHER2:41071 and [^99mTc]Tc-ZHER2:V2 was 25–30 fold lower when compared with [^99mTc]Tc-ZHER2:2395. The uptake in tumour and kidney for [^99mTc]Tc-ZHER2:41071 and [^99mTc]Tc-ZHER2:V2 in SKOV-3 xenografts was similar. In conclusion, an extensive re-engineering of the scaffold did not compromise imaging properties of the affibody molecule labelled with ^99mTc using a GGGC chelator. The new probe, [^99mTc]Tc-ZHER2:41071 provided the best tumour-to-blood ratio compared to HER2-imaging probes for single photon emission computed tomography (SPECT) described in the literature so far. [^99mTc]Tc-ZHER2:41071 is a promising candidate for further clinical translation studies.     

Research and development of liquid hydrogen (LH2) temperature monitoring system for marine applications

Monitoring the temperature in liquid hydrogen (LH₂) storage tanks on ships is important for the safety of maritime navigation. In addition, accurate temperature measurement is also required for commercial transactions. Temperature and pressure define the density of liquid hydrogen, which is directly linked to trading interests. In this study, we developed and tested a liquid hydrogen temperature monitoring system that uses platinum resistance sensors with a nominal electrical resistance of approximately 1000 Ω at room temperature, PT-1000, for marine applications. The temperature measurements were carried out using a newly developed temperature monitoring system under different pressure conditions. The measured values are compared with a calibrated reference PT-1000 resistance thermometer. We confirm a measurement accuracy of ±50 mK in a pressure range of 0.1 MPa–0.5 MPa.     

Machine Learning-Based Two-Stage Data Selection Scheme for Long-Term Influenza Forecasting

One popular strategy to reduce the enormous number of illnesses and deaths from a seasonal influenza pandemic is to obtain the influenza vaccine on time. Usually, vaccine production preparation must be done at least six months in advance, and accurate long-term influenza forecasting is essential for this. Although diverse machine learning models have been proposed for influenza forecasting, they focus on short-term forecasting, and their performance is too dependent on input variables. For a country’s long-term influenza forecasting, typical surveillance data are known to be more effective than diverse external data on the Internet. We propose a two-stage data selection scheme for worldwide surveillance data to construct a long-term forecasting model for influenza in the target country. In the first stage, using a simple forecasting model based on the country’s surveillance data, we measured the change in performance by adding surveillance data from other countries, shifted by up to 52 weeks. In the second stage, for each set of surveillance data sorted by accuracy, we incrementally added data as input if the data have a positive effect on the performance of the forecasting model in the first stage. Using the selected surveillance data, we trained a new long-term forecasting model for influenza and perform influenza forecasting for the target country. We conducted extensive experiments using six machine learning models for the three target countries to verify the effectiveness of the proposed method. We report some of the results.     

Classification of geographical origin of kimchi by volatile compounds analysis using an electronic nose

Food Science and Biotechnology - Food authenticity is one of the largest concerns in recent days. As kimchi has been a global food, its production origin has been important issue, particularly due...     

Top-down preparation of Ni–Pd–P@graphitic carbon core-shell nanostructure as a non-Pt catalyst for enhanced electrocatalytic reactions

Electrochemical reactions such as the oxygen evolution reaction (OER), oxygen reduction reaction (ORR), and methanol oxidation reaction (MOR) are essential for energy conversion applications such as water electrolysis and fuel cells. Furthermore, Pt or Ir-related materials have been extensively utilized as electrocatalysts for the OER, ORR, and MOR. To reduce the utilization of precious metals, innovative catalyst structures should be proposed. Herein, we report a bi-metallic phosphide (Ni₂P and PdP₂) structure surrounded by graphitic carbon (Ni–Pd–P/C) with an enhanced electrochemical activity as compared to conventional electrocatalysts. Despite the low Pd content of 3 at%, Ni–Pd–P/C exhibits a low overpotential of 330 mV at 10 mA cm^?2 in the OER, high specific activity (2.82 mA cm^?2 at 0.8 V) for the ORR, and a high current density of 1.101 A mg^?1 for the MOR. The superior electrochemical performance of Ni–Pd–P/C may be attributed to the synergistic effect of the bi-metallic phosphide structure and core-shell structure formed by graphitic carbon.     

Changes in bacterial community and expression of genes involved in intestinal innate immunity in the jejunum of newborn lambs during the first 24 hours of life

The newborn gut undergoes rapid colonization by commensal microorganisms and possible exposure to pathogens. The contribution of colostrum intake to host protection is well known; however, limited research exists on the intestinal innate immunity corresponding to colostrum intake during the passive immune transfer period in newborn ruminants. The aim of this study was to investigate the changes in bacterial community and expression of genes encoding toll-like receptors (TLR), mucins (MUC), antimicrobial peptides, and tight junctions in the jejunum of lambs that were fed colostrum during the first 24 h of life. Twenty-seven newborn lambs were used in this study, of which 18 lambs were bottle-fed pooled bovine colostrum within the first 2 h after birth to obtain an intake of approximately 8% of body weight. Lambs were slaughtered at 12 (n = 9) and 24 h (n = 9) after birth. The remaining 9 lambs without any feeding were slaughtered at 30 min after birth (0 h). Tissue and ligated segment samples from the jejunum were collected immediately after the lambs were slaughtered. The bacterial profile in the ligated jejunum segment was assessed using amplicon sequencing. The gene expression in the jejunum tissue was determined using quantitative real-time PCR. The relative abundances of Escherichia-Shigella, Lactobacillus, Lactococcus, and Streptococcus increased, whereas those of Sphingomonas, Phyllobacterium, Bradyrhizobium, and Rudaea decreased during the first 24 h of life. Expression of TLR2 and β-defensin 109-like was upregulated at 12 h after birth, but a recovery was detected at 24 h; TLR3, TLR5, LYZ, MUC1, MUC13, MUC20, and CLDN7 showed a higher expression level in samples taken at 24 h than in those taken at 0 h. In addition, expression level of CLDN1, CLDN4, and the junctional adhesion molecule-1 tended to be higher at 24 h than at 0 h after birth. Correlation analysis indicated that TLR2 expression was negatively correlated with the relative abundance of Lactobacillus and Bradyrhizobium, whereas TLR5 expression was positively correlated with the relative abundance of Escherichia-Shigella and Pelagibacterium. These results suggest that TLR, MUC, antimicrobial peptides, and CLDN act together and play an important role in intestinal defense during the passive immune transfer period. They are potentially associated with microbial colonization. The findings from this study provide novel information to elucidate the role of colostrum components in regulating the development of the intestinal mucosal immune barrier in newborn lambs during the passive immune transfer period.