Frequency response analysis (FRA) is a widely accepted diagnostic method to assess the mechanical integrity of the active parts within a power transformer. Recent studies in the field of FRA have led to the standardization of its measurement procedure as described in the IEC and IEEE standards. However, the interpretation of FRA results is still limited to the analysis of the experts in the field. Using numerical indices is one of the methods introduced for the FRA interpretation, which quantifies the differences in FRA signatures. There are numerous indices proposed in the literature. However, there is no comprehensive comparison study to assess the sensitivity of these numerical indices against different faults. This contribution collects all indices on a single platform, compares and categories them based on their characteristics, to announce more appropriate indices as the standard ones. This paper defines the criteria for an appropriate index such as monotonicity, linearity, sensitivity, data-points dependency and index ratio. The evaluation of the indices is performed using 10 case studies from an experimental setup, molded transformer, and real power transformer cases. The results also provide useful facts and guidelines for the standardization process of numerical indices for their implementation in the FRA studies.

In genome-wide studies, over-representation analysis (ORA) against a set of genes is an essential step for biological interpretation. Many gene annotation resources and software platforms for ORA have been proposed. Recently, Medical Subject Headings (MeSH) terms, which are annotations of PubMed documents, have been used for ORA. MeSH enables the extraction of broader meaning from the gene lists and is expected to become an exhaustive annotation resource for ORA. However, the existing MeSH ORA software platforms are still not sufficient for several reasons. In this work, we developed an original MeSH ORA framework composed of six types of R packages, including MeSH.db, MeSH.AOR.db, MeSH.PCR.db, the org.MeSH.XXX.db-type packages, MeSHDbi, and meshr. Using our framework, users can easily conduct MeSH ORA. By utilizing the enriched MeSH terms, related PubMed documents can be retrieved and saved on local machines within this framework.

Pancreatic ductal adenocarcinoma has a particularly poor prognosis as it is often detected at an advanced stage and acquires resistance to chemotherapy early during its course. Stress adaptations by mitochondria, such as metabolic plasticity and regulation of apoptosis, promote cancer cell survival; however, the relationship between mitochondrial dynamics and chemoresistance in pancreatic ductal adenocarcinoma remains unclear. We here established human pancreatic cancer cell lines resistant to gemcitabine from MIA PaCa‐2 and Panc1 cells. We compared the cells before and after the acquisition of gemcitabine resistance to investigate the mitochondrial dynamics and protein expression that contribute to this resistance. The mitochondrial number increased in gemcitabine‐resistant cells after resistance acquisition, accompanied by a decrease in mitochondrial fission 1 protein, which induces peripheral mitosis, leading to mitophagy. An increase in the number of mitochondria promoted oxidative phosphorylation and increased anti‐apoptotic protein expression. Additionally, enhanced oxidative phosphorylation decreased the AMP/ATP ratio and suppressed AMPK activity, resulting in the activation of the HSF1–heat shock protein pathway, which is required for environmental stress tolerance. Synergistic effects observed with BCL2 family or HSF1 inhibition in combination with gemcitabine suggested that the upregulated expression of apoptosis‐related proteins caused by the mitochondrial increase may contribute to gemcitabine resistance. The combination of gemcitabine with BCL2 or HSF1 inhibitors may represent a new therapeutic strategy for the treatment of acquired gemcitabine resistance in pancreatic ductal adenocarcinoma.

A large number of complete microorganism genomes has been sequenced and submitted to the public database and then incorporated into our complete genome database, Genome Information Broker (GIB, ). However, when comparative genomics is carried out, researchers must be aware that there are protein-coding genes not confirmed by homology or motif search and that reliable protein-coding genes are missing. Therefore, we developed a protocol (Gene Trek in Prokaryote Space, GTPS) for finding possible protein-coding genes in bacterial genomes. GTPS assigns a degree of reliability to predicted protein-coding genes. We first systematically applied the protocol to the complete genomes of all 123 bacterial species and strains that were publicly available as of July 2003, and then to those of 183 species and strains available as of September 2004. We found a number of incorrect genes and several new ones in the genome data in question. We also found a way to estimate the total number of orthologous genes in the bacterial world.

Transfer functions of a transformer whose winding is axially displaced are measured in several connection schemes of frequency response analysis (FRA), and the sensitivities of the measured transfer functions in these connection schemes to the axial displacement are evaluated. For the objective evaluation, some numerical indices are employed, and it is found that the inductive inter‐winding measurement is the most sensitive to the axial displacement. Furthermore, a simple circuit model is proposed to reproduce the measured transfer functions. All the parameters of the proposed circuit model can be determined from the measured transfer functions in FRA. The proposed model can also reproduce the measured transfer functions with the axial displacement by varying one parameter. The variation of the parameter in reproducing the transfer function with the axial displacement show good linear relation to the amount of the axial displacement. This indicates the possibility of a quantitative diagnosis of the axial displacement by FRA.

Frequency Response Analysis (FRA) is a powerful technique to detect internal abnormalities within power transformers. However, diagnosis criteria of power transformers by FRA have not been fully established yet. In this paper, an indicator of identification degree of the two transfer functions is examined using data of real transformers and problems in practical application are discussed. Based on this discussion, an improved indicator of degree of identification between two transfer functions is proposed. The proposed indicator is applied to transfer functions of real transformers with or without some abnormalities. Based on this discussion, an objective criterion for diagnosis of abnormalities of transformer windings by FRA is proposed.