Comparative genomic analysis of the human genome and six bat genomes using unsupervised machine learning: Mb-level CpG and TFBS islands.

BACKGROUND: Emerging infectious disease-causing RNA viruses, such as the SARS-CoV-2 and Ebola viruses, are thought to rely on bats as natural reservoir hosts. Since these zoonotic viruses pose a great threat to humans, it is important to characterize the bat genome from multiple perspectives. Unsupervised machine learning methods for extracting novel information from big sequence data without prior knowledge or particular models are highly desirable for obtaining unexpected insights. We previously established a batch-learning self-organizing map (BLSOM) of the oligonucleotide composition that reveals novel genome characteristics from big sequence data. RESULTS: In this study, using the oligonucleotide BLSOM, we conducted a comparative genomic study of humans and six bat species. BLSOM is an explainable-type machine learning algorithm that reveals the diagnostic oligonucleotides contributing to sequence clustering (self-organization). When unsupervised machine learning reveals unexpected and/or characteristic features, these features can be studied in more detail via the much simpler and more direct standard distribution map method. Based on this combined strategy, we identified the Mb-level enrichment of CG dinucleotide (Mb-level CpG islands) around the termini of bat long-scaffold sequences. In addition, a class of CG-containing oligonucleotides were enriched in the centromeric and pericentromeric regions of human chromosomes. Oligonucleotides longer than tetranucleotides often represent binding motifs for a wide variety of proteins (e.g., transcription factor binding sequences (TFBSs)). By analyzing the penta- and hexanucleotide composition, we observed the evident enrichment of a wide range of hexanucleotide TFBSs in centromeric and pericentromeric heterochromatin regions on all human chromosomes. CONCLUSION: Function of transcription factors (TFs) beyond their known regulation of gene expression (e.g., TF-mediated looping interactions between two different genomic regions) has received wide attention. The Mb-level TFBS and CpG islands are thought to be involved in the large-scale nuclear organization, such as centromere and telomere clustering. TFBSs, which are enriched in centromeric and pericentromeric heterochromatin regions, are thought to play an important role in the formation of nuclear 3D structures. Our machine learning-based analysis will help us to understand the differential features of nuclear 3D structures in the human and bat genomes.

Unsupervised explainable AI for molecular evolutionary study of forty thousand SARS-CoV-2 genomes.

BACKGROUND: Unsupervised AI (artificial intelligence) can obtain novel knowledge from big data without particular models or prior knowledge and is highly desirable for unveiling hidden features in big data. SARS-CoV-2 poses a serious threat to public health and one important issue in characterizing this fast-evolving virus is to elucidate various aspects of their genome sequence changes. We previously established unsupervised AI, a BLSOM (batch-learning SOM), which can analyze five million genomic sequences simultaneously. The present study applied the BLSOM to the oligonucleotide compositions of forty thousand SARS-CoV-2 genomes. RESULTS: While only the oligonucleotide composition was given, the obtained clusters of genomes corresponded primarily to known main clades and internal divisions in the main clades. Since the BLSOM is explainable AI, it reveals which features of the oligonucleotide composition are responsible for clade clustering. Additionally, BLSOM also provided information concerning the special genomic region possibly undergoing RNA modifications. CONCLUSIONS: The BLSOM has powerful image display capabilities and enables efficient knowledge discovery about viral evolutionary processes, and it can complement phylogenetic methods based on sequence alignment.

A case of expressive-vocal amusia in a right-handed patient with left hemispheric cerebral infarction.

A 53-year-old right-handed woman had an extensive lesion in the left hemisphere due to an infarction caused by vasospasm secondary to subarachnoid bleeding. She exhibited persistent expressive-vocal amusia with no symptoms of aphasia. Evaluation of the patient's musical competence using the Montreal Battery for Evaluation of Amusia, rhythm reproduction tests, acoustic analysis of pitch upon singing familiar music, Japanese standard language tests, and other detailed clinical examinations revealed that her amusia was more dominantly related to pitch production. The intactness of her speech provided strong evidence that the right hemisphere played a major role in her linguistic processing. Data from functional magnetic resonance imaging while she was singing a familiar song, a scale, and reciting lyrics indicated that perilesional residual activation in the left hemisphere was associated with poor pitch production, while right hemispheric activation was involved in linguistic processing. The localization of infarction more anterior to the left Sylvian fissure might be related to the dominant deficits in expressive aspects of the singing of the patient. Compromised motor programming producing a single tone may have made a major contribution to her poor singing. Imperfect auditory feedback due to borderline perceptual ability or improper audio-motor associations might also have played a role.

Notable clustering of transcription-factor-binding motifs in human pericentric regions and its biological significance.

Since oligonucleotide composition in the genome sequence varies significantly among species even among those possessing the same genome G + C%, the composition has been used to distinguish a wide range of genomes and called as "genome signature". Oligonucleotides often represent motif sequences responsible for sequence-specific protein binding (e.g., transcription-factor binding). Occurrences of such motif oligonucleotides in the genome should be biased compared to those observed in random sequences and may differ among genomes and genomic portions. Self-Organizing Map (SOM) is a powerful tool for clustering high-dimensional data such as oligonucleotide composition on one plane. We previously modified the conventional SOM for genome informatics to batch learning SOM or "BLSOM". When we constructed BLSOMs to analyze pentanucleotide composition in 20-, 50-, and 100-kb sequences derived from the human genome, BLSOMs did not classify human sequences according to chromosome but revealed several specific zones composed primarily of sequences derived from pericentric regions. Interestingly, various transcription-factor-binding motifs were characteristically overrepresented in pericentric regions but underrepresented in most genomic sequences. When we focused on much shorter sequences (e.g., 1 kb), the clustering of transcription-factor-binding motifs was evident in pericentric, subtelomeric and sex chromosome pseudoautosomal regions. The biological significance of the clustering in these regions was discussed in connection with cell-type and -stage-dependent chromocenter formation and nuclear organization.

Extracellular calcium influx activates adenylate cyclase 1 and potentiates insulin secretion in MIN6 cells.

Intracellular cAMP and Ca(2+) are important second messengers that regulate insulin secretion in pancreatic ß-cells; however, the molecular mechanism underlying their mutual interaction for exocytosis is not fully understood. In the present study, we investigated the interplay between intracellular cAMP and Ca(2+) concentrations ([cAMP](i) and [Ca(2+)](i) respectively) in the pancreatic ß-cell line MIN6 using total internal reflection fluorescence microscopy. For measuring [cAMP](i), we developed a genetically encoded yellow fluorescent biosensor for cAMP [Flamindo (fluorescent cAMP indicator)], which changes fluorescence intensity with cAMP binding. Application of high-KCl or glucose to MIN6 cells induced the elevation of [cAMP](i) and exocytosis. Furthermore, application of an L-type Ca(2+) channel agonist or ionomycin to induce extracellular Ca(2+) influx evoked the elevation of [cAMP](i), whereas application of carbachol or thapsigargin, which mobilize Ca(2+) from internal stores, did not evoke the elevation of [cAMP](i). We performed RT (reverse transcription)-PCR analysis and found that Ca(2+)-sensitive Adcy1 (adenylate cyclase 1) was expressed in MIN6 cells. Knockdown of endogenous ADCY1 by small interference RNA significantly suppressed glucose-induced exocytosis and the elevation of both [cAMP](i) and [Ca(2+)](i). Taken together, the findings of the present study demonstrate that ADCY1 plays an important role in the control of pancreatic ß-cell cAMP homoeostasis and insulin secretion.

[A case of hepatocellular carcinoma complicated by pleural effusion mixed with bile after radiofrequency ablation].

An 84-year-old Japanese man was admitted with hepatocellular carcinoma (HCC). He underwent transcatheter arterial chemoembolization and percutaneous radiofrequency ablation (RFA). Three weeks later, he developed sudden-onset right pleural effusion mixed with bile. Drip infusion cholangiography-computed tomography revealed leakage of the contrast agent, which passed from the HCC to the pleural cavity through a perforation in the diaphragm. The patient's condition improved after thoracic and endoscopic nasobiliary drainage. The occurrence of pleural effusion mixed with bile is a rare complication of RFA. This case provides important information about the morbidity, prevention, and treatment of this complication.

Unsupervised AI reveals insect species-specific genome signatures.

Insects are a highly diverse phylogeny and possess a wide variety of traits, including the presence or absence of wings and metamorphosis. These diverse traits are of great interest for studying genome evolution, and numerous comparative genomic studies have examined a wide phylogenetic range of insects. Here, we analyzed 22 insects belonging to a wide phylogenetic range (Endopterygota, Paraneoptera, Polyneoptera, Palaeoptera, and other insects) by using a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions in their genomic fragments (100-kb or 1-Mb sequences), which is an unsupervised machine learning algorithm that can extract species-specific characteristics of the oligonucleotide compositions (genome signatures). The genome signature is of particular interest in terms of the mechanisms and biological significance that have caused the species-specific difference, and can be used as a powerful search needle to explore the various roles of genome sequences other than protein coding, and can be used to unveil mysteries hidden in the genome sequence. Since BLSOM is an unsupervised clustering method, the clustering of sequences was performed based on the oligonucleotide composition alone, without providing information about the species from which each fragment sequence was derived. Therefore, not only the interspecies separation, but also the intraspecies separation can be achieved. Here, we have revealed the specific genomic regions with oligonucleotide compositions distinct from the usual sequences of each insect genome, e.g., Mb-level structures found for a grasshopper Schistocerca americana. One aim of this study was to compare the genome characteristics of insects with those of vertebrates, especially humans, which are phylogenetically distant from insects. Recently, humans seem to be the "model organism" for which a large amount of information has been accumulated using a variety of cutting-edge and high-throughput technologies. Therefore, it is reasonable to use the abundant information from humans to study insect lineages. The specific regions of Mb length with distinct oligonucleotide compositions have also been previously observed in the human genome. These regions were enriched by transcription factor binding motifs (TFBSs) and hypothesized to be involved in the three-dimensional arrangement of chromosomal DNA in interphase nuclei. The present study characterized the species-specific oligonucleotide compositions (i.e., genome signatures) in insect genomes and identified specific genomic regions with distinct oligonucleotide compositions.

Novel bioinformatics strategies for prediction of directional sequence changes in influenza virus genomes and for surveillance of potentially hazardous strains.

BACKGROUND: With the remarkable increase of microbial and viral sequence data obtained from high-throughput DNA sequencers, novel tools are needed for comprehensive analysis of the big sequence data. We have developed "Batch-Learning Self-Organizing Map (BLSOM)" which can characterize very many, even millions of, genomic sequences on one plane. Influenza virus is one of zoonotic viruses and shows clear host tropism. Important issues for bioinformatics studies of influenza viruses are prediction of genomic sequence changes in the near future and surveillance of potentially hazardous strains. METHODS: To characterize sequence changes in influenza virus genomes after invasion into humans from other animal hosts, we applied BLSOMs to analyses of mono-, di-, tri-, and tetranucleotide compositions in all genome sequences of influenza A and B viruses and found clear host-dependent clustering (self-organization) of the sequences. RESULTS: Viruses isolated from humans and birds differed in mononucleotide composition from each other. In addition, host-dependent oligonucleotide compositions that could not be explained with the host-dependent mononucleotide composition were revealed by oligonucleotide BLSOMs. Retrospective time-dependent directional changes of mono- and oligonucleotide compositions, which were visualized for human strains on BLSOMs, could provide predictive information about sequence changes in newly invaded viruses from other animal hosts (e.g. the swine-derived pandemic H1N1/09). CONCLUSIONS: Basing on the host-dependent oligonucleotide composition, we proposed a strategy for prediction of directional changes of virus sequences and for surveillance of potentially hazardous strains when introduced into human populations from non-human sources. Millions of genomic sequences from infectious microbes and viruses have become available because of their medical and social importance, and BLSOM can characterize the big data and support efficient knowledge discovery.

KRN633, an inhibitor of vascular endothelial growth factor receptor tyrosine kinase, induces intrauterine growth restriction in mice.

We previously reported that treatment with KRN633, a vascular endothelial growth factor receptor tyrosine kinase inhibitor, during mid-pregnancy caused intrauterine growth restriction resulting from impairment of blood vessel growth in the labyrinthine zone of the placenta and fetal organs. However, the relative sensitivities of blood vessels in the placenta and fetal organs to vascular endothelial growth factor (VEGF) inhibitors have not been determined. In this study, we aimed to examine the effects of KRN633 on the vasculatures of organs in mother mice and their newborn pups by immunohistochemical analysis. Pregnant mice were treated daily with KRN633 (5 mg/kg) either from embryonic day 13.5 (E13.5) to E17.5 or from E13.5 to the day of delivery. The weights of the pups of KRN633-treated mice were lower than those of the pups of vehicle-treated mothers. However, no significant difference in body weight was observed between the vehicle- and KRN633-treated mice. The vascular development in the organs (the pancreas, kidney, and intestine) and intestinal lymphatic formation of the pups of KRN633-treated mothers was markedly impaired. In contrast, the KRN633 treatment showed no significant effect on the vascular beds in the organs, including the labyrinthine zone of the placenta, of the mother mice. These results suggest that blood vessels in fetal organs are likely to be more sensitive to reduced VEGF signaling than those in the mother. A partial loss of VEGF function during pregnancy could suppress vascular growth in the fetus without affecting the vasculature in the mother mouse, thereby increasing the risk of intrauterine growth restriction.

AI-based search for convergently expanding, advantageous mutations in SARS-CoV-2 by focusing on oligonucleotide frequencies.

Among mutations that occur in SARS-CoV-2, efficient identification of mutations advantageous for viral replication and transmission is important to characterize and defeat this rampant virus. Mutations rapidly expanding frequency in a viral population are candidates for advantageous mutations, but neutral mutations hitchhiking with advantageous mutations are also likely to be included. To distinguish these, we focus on mutations that appear to occur independently in different lineages and expand in frequency in a convergent evolutionary manner. Batch-learning SOM (BLSOM) can separate SARS-CoV-2 genome sequences according by lineage from only providing the oligonucleotide composition. Focusing on remarkably expanding 20-mers, each of which is only represented by one copy in the viral genome, allows us to correlate the expanding 20-mers to mutations. Using visualization functions in BLSOM, we can efficiently identify mutations that have expanded remarkably both in the Omicron lineage, which is phylogenetically distinct from other lineages, and in other lineages. Most of these mutations involved changes in amino acids, but there were a few that did not, such as an intergenic mutation.

AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome.

In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: an unsupervised AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4-6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers that appeared after the epidemic started could be connected to mutations, and the BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explain BLSOMs for various topics, such as the tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explain BLSOMs for various eukaryotes, including fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found enrichments in transcription factor-binding sequences in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) could be separated according to their corresponding amino acid.

Comparative genomics of Glandirana rugosa using unsupervised AI reveals a high CG frequency.

The Japanese wrinkled frog (Glandirana rugosa) is unique in having both XX-XY and ZZ-ZW types of sex chromosomes within the species. The genome sequencing and comparative genomics with other frogs should be important to understand mechanisms of turnover of sex chromosomes within one species or during a short period. In this study, we analyzed the newly sequenced genome of G. rugosa using a batch-learning self-organizing map which is unsupervised artificial intelligence for oligonucleotide compositions. To clarify genome characteristics of G. rugosa, we compared its short oligonucleotide compositions in all 1-Mb genomic fragments with those of other six frog species (Pyxicephalus adspersus, Rhinella marina, Spea multiplicata, Leptobrachium leishanense, Xenopus laevis, and Xenopus tropicalis). In G. rugosa, we found an Mb-level large size of repeat sequences having a high identity with the W chromosome of the African bullfrog (P. adspersus). Our study concluded that G. rugosa has unique genome characteristics with a high CG frequency, and its genome is assumed to heterochromatinize a large size of genome via methylataion of CG.

Effects of KRN633, an inhibitor of vascular endothelial growth factor receptor-2 tyrosine kinase, on vascular development of placenta and fetus of mid-pregnancy in mice.

Inhibition of the vascular endothelial growth factor (VEGF) signaling pathway during pregnancy contributes to several pathologic pregnancies, such as hypertension, preeclampsia, and intrauterine growth restriction, but its effects on the fetus have not been fully examined. To determine how inhibition of the VEGF signaling pathway affects the fetal vascular development of mid pregnancy, we treated pregnant mice daily with either the VEGF receptor-2 (VEGFR-2) tyrosine kinase inhibitor KRN633 (300 mg/kg, p.o.) or the vehicle from 13.5 to 15.5 day of pregnancy. On the 16.5 day of pregnancy, the vascular beds in the placenta and several organs of the fetus were visualized by fluorescent immunohistochemistry. All mice treated with KRN633 appeared healthy, and total numbers of fetuses per litter were unaffected. However, weights of the placenta and fetus from KRN633-treated mice were lower than those from the vehicle-treated ones. No external malformations and bleeding were observed in the placenta and fetus, whereas immunohistochemical analyses revealed that the vascular development in labyrinthine zone of placenta and fetal organs examined (skin, pancreas, kidney, and lung) were impaired by KRN633 treatment. These results suggest that inhibition of the VEGF signaling pathway during mid pregnancy suppresses vascular growth of both the placenta and fetus without obvious health impairments of mother mice and increases the risk of induction of intrauterine growth restriction.

Time-series analyses of directional sequence changes in SARS-CoV-2 genomes and an efficient search method for candidates for advantageous mutations for growth in human cells.

We first conducted time-series analysis of mono- and dinucleotide composition for over 10,000 SARS-CoV-2 genomes, as well as over 1500 Zaire ebolavirus genomes, and found clear time-series changes in the compositions on a monthly basis, which should reflect viral adaptations for efficient growth in human cells. We next developed a sequence alignment free method that extensively searches for advantageous mutations and rank them in an increase level for their intrapopulation frequency. Time-series analysis of occurrences of oligonucleotides of diverse lengths for SARS-CoV-2 genomes revealed seven distinctive mutations that rapidly expanded their intrapopulation frequency and are thought to be candidates of advantageous mutations for the efficient growth in human cells.

Mb-level CpG and TFBS islands visualized by AI and their roles in the nuclear organization of the human genome.

Unsupervised machine learning that can discover novel knowledge from big sequence data without prior knowledge or particular models is highly desirable for current genome study. We previously established a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions, which can reveal various novel genome characteristics from big sequence data, and found that transcription factor binding sequences (TFBSs) and CpG-containing oligonucleotides are enriched in human centromeric and pericentromeric regions, which support centromere clustering and form the condensed heterochromatin "chromocenter" in interphase nuclei. The number and size of chromocenters, as well as the type of centromeres gathered in individual chromocenters, vary depending on cell type. To study molecular mechanisms of cell type-dependent chromocenter formation, we analyzed distribution patterns of occurrence per Mb of hexa- and heptanucleotide TFBSs, which have been compiled by the SwissRegulon Portal, and of CpG-containing oligonucleotides. We found Mb-level islands enriched for TFBSs and CpG-containing oligonucleotides in centromeric and pericentromeric regions on all human chromosomes except chrY. Considering molecular mechanisms for cell type-dependent centromere clustering, the chromosome-dependent enrichment of a set of TFBSs and CpG-containing oligonucleotides is of particular interest, since the cellular content of TFs and methyl-CpG-binding proteins exhibits cell type-dependent regulation. A newly introduced BLSOM, which analyzed occurrences of a total of 3,946 octanucleotide TFBSs compiled by the SwissRegulon Portal, has self-organized (separated) the sequences that are characteristically enriched in TFBSs and shown that these sequences are derived primarily from centromeric and pericentromeric constitutive heterochromatin regions. Furthermore, the BLSOM identified and visualized characteristic TFBSs that are enriched in these regions. By analyzing Hi-C data for interchromosomal interactions, the present study showed that the chromatin segments supporting the interchromosomal interactions locate primarily in Mb-level TFBS and CpG islands and are thus enriched for a wide variety of TFBSs and CG-containing oligonucleotides.

Time-series analyses of directional sequence changes in SARS-CoV-2 genomes and an efficient search method for candidates for advantageous mutations for growth in human cells.

We first conducted time-series analysis of mono- and dinucleotide composition for over 10,000 SARS-CoV-2 genomes, as well as over 1500 Zaire ebolavirus genomes, and found clear time-series changes in the compositions on a monthly basis, which should reflect viral adaptations for efficient growth in human cells. We next developed a sequence alignment free method that extensively searches for advantageous mutations and rank them in an increase level for their intrapopulation frequency. Time-series analysis of occurrences of oligonucleotides of diverse lengths for SARS-CoV-2 genomes revealed seven distinctive mutations that rapidly expanded their intrapopulation frequency and are thought to be candidates of advantageous mutations for the efficient growth in human cells.

Ability of community pharmacists to promote self-care and self-medication by local residents [I]: Improvements in bone mineral density.

This study was conducted in order to establish a health management method for the elderly in a community through follow-ups of bone mineral density (BMD) measurement results over a 1-year period based on BMD measurements performed by pharmacists and a guidance program. Regarding BMD measurement results, the percent young adult mean (%YAM: mean BMD in healthy persons of the same sex aged between 51 and 82 years old) significantly increased in Period I, during which the intervention by pharmacists was performed (6 months after the start of measurements), but significantly decreased in Period II, during which this intervention was not performed (between 7 and 12 months after the start of measurements). Based on these results, lifestyle improvements were effective in Period I regardless of sex or age; however, it may be important to maintain an improved diet and subject motivation in the future. The results of this study suggest that community pharmacists play an important role in community medicine through positive intervention for local residents' health support.

An artificial intelligence approach fit for tRNA gene studies in the era of big sequence data.

Unsupervised data mining capable of extracting a wide range of knowledge from big data without prior knowledge or particular models is a timely application in the era of big sequence data accumulation in genome research. By handling oligonucleotide compositions as high-dimensional data, we have previously modified the conventional self-organizing map (SOM) for genome informatics and established BLSOM, which can analyze more than ten million sequences simultaneously. Here, we develop BLSOM specialized for tRNA genes (tDNAs) that can cluster (self-organize) more than one million microbial tDNAs according to their cognate amino acid solely depending on tetra- and pentanucleotide compositions. This unsupervised clustering can reveal combinatorial oligonucleotide motifs that are responsible for the amino acid-dependent clustering, as well as other functionally and structurally important consensus motifs, which have been evolutionarily conserved. BLSOM is also useful for identifying tDNAs as phylogenetic markers for special phylotypes. When we constructed BLSOM with 'species-unknown' tDNAs from metagenomic sequences plus 'species-known' microbial tDNAs, a large portion of metagenomic tDNAs self-organized with species-known tDNAs, yielding information on microbial communities in environmental samples. BLSOM can also enhance accuracy in the tDNA database obtained from big sequence data. This unsupervised data mining should become important for studying numerous functionally unclear RNAs obtained from a wide range of organisms.

Differential expression of nitric oxide signaling components in undifferentiated and differentiated human embryonic stem cells.

Nitric oxide (NO) is an uncharged free-radical gas that is involved in a number of physiological and pathological events. We have examined the expression of various subunits of soluble guanylyl cyclase (sGC alpha (1), alpha (2), beta (1), beta (2)), nitric oxide synthase (s) (NOS-1, -2, -3), MLC2 (cardiac marker) and a cardiac-specific transcription factor (Nkx2.5) in human embryonic stem (hES) cells (H-9 cells) and differentiated cells subjected to differentiation in cell suspension using embryoid body (EB) formation. Our results demonstrate a time-dependent increase in the expression of sGC alpha (1) and beta (1) at the mRNA and protein levels in differentiated cells compared to undifferentiated H-9 cells as examined by real-time PCR and western blot analysis. mRNA for sGC alpha (2) also showed a time-dependent increase compared to undifferentiated cells. In contrast, there was a time-dependent decrease in sGC beta (2) mRNA expression in differentiated cells compared to undifferentiated H-9 cells. In contrast to undifferentiated H-9 cells, the maximum mRNA expression of cardiac marker MLC2 and the cardiac-specific transcription factor Nkx2.5 was observed at day 14 of the differentiated H-9 cells. The protein levels of MLC2 were stable up to day 25 compared to mRNA levels, which showed a sharp decline after day 15. Using immunofluorescence, we also demonstrate positive staining of cardiac markers such as troponin I, alpha-actinin, atrial natriuretic peptide, and SGC alpha (1) at days 8-37 post-differentiation. These results clearly demonstrate the role of NO signaling components in differentiation events or physiological processes of human ES or ES cell-derived cardiomyocytes.

[Comparison of dexamethasone 8 mg and 16 mg for the prevention of acute and delayed cisplatin-induced emesis in patients with lung cancer].

We performed a retrospective study that compared the efficacy and safety of dexamethasone (DEX) 8 mg with DEX 16 mg in cases of acute and delayed emesis induced by cisplatin (CDDP) chemotherapy in patients with lung cancer. Sixty-eight lung cancer patients treated with combination cisplatin, ifosfamide, and irinotecan therapy were studied. The DEX 8 mg group and the DEX 16 mg group received DEX intravenous injection 30 min prior to CDDP. All patients then received a 5-HT(3) antagonist intravenous injection 30 min before CDDP. Protection from acute nausea (day 1) was significantly superior in the DEX 16 mg group compared with the DEX 8 mg group (DEX 8 mg, 76.5%; DEX 16 mg, 100%). Protection from delayed emesis (day 1) was significantly superior in the DEX 16 mg group compared with the DEX 8 mg group. There was no reported severe nausea (grade 3) and vomiting (grade 2) in the DEX 16 mg group. Furthermore, perphenazine hydrochloride for use as rescue medication was required by significantly fewer patients in the DEX 16 mg group than in the DEX 8 mg group (DEX 8 mg, 41.2%; DEX 16 mg, 0%). Adverse effects were observed in 10 cases (nine reports of generalized fatigability, two of headache) in the DEX 8 mg group and in 16 cases (11 reports of generalized fatigability, one of pruritus) in the DEX 16 mg group. However, because the symptoms were all mild, we did not consider that there was any safety problem. In conclusion, DEX 16 mg is a clinically useful treatment for acute and delayed emesis induced by cisplatin-induced chemotherapy in patients with lung cancer.