Our previous studies demonstrated that emotional dysfunction associated with early life stress exacerbated nerve injury-induced mechanical allodynia. Sex differences were observed in several anxiety tests, but not in mechanical allodynia. To elucidate the mechanism underlying these findings, we have now investigated the involvement of astrocytes in emotional dysfunction and enhancement of nerve injury-induced mechanical allodynia in mice subjected to maternal separation combined with social isolation (MSSI) as an early life stress. We measured expression of glial fibrillary acidic protein (GFAP), an astrocyte maker, in each brain area by immunohistochemistry. GFAP expression in the locus coeruleus (LC) of female, but not of male mice, significantly increased after MSSI, corresponding to the behavioral changes at 7 and 12 weeks of age. Lipopolysaccharide (LPS)-treated astrocyte-derived supernatant was administered to local brain regions, including LC. Intra-LC injection of conditioned medium from cultured astrocytes treated with LPS increased GFAP expression, anxiety-like behavior and mechanical allodynia in both male and female mice. Furthermore, increases in anxiety-like behavior correlated with increased mechanical allodynia. These findings demonstrate that emotional dysfunction and enhanced nerve injury-induced mechanical allodynia after exposure to MSSI are mediated, at least in part, by astrocyte activation in the LC. Male but not female mice may show resistance to MSSI stress during growth. Pain is a complex experience that involves purely sensory aspects, such as nociceptive stimuli, as well as emotional effects and feelings of unease . While pD-serine, ATP) in response to neuronal activity including increase in the intracellular Ca2+ concentration . Astrocytes are the most numerous type of glial cell.  and are ntration . Exocyto channel  were indeceptors  or conneeceptors . These feceptors . Furthereceptors  and matreceptors . More reeceptors . Based oOn the other hand, astrocytes may influence neural networks that underlie specific behaviors, including aberrant behaviors associated with stress. For example, To examine our hypothesis, we investigated the influence of MSSI on GFAP expression levels and associated nociception and emotion in neuropathic pain states. Furthermore, to evaluate the involvement of local astrocytic activation, we developed a local activation model involving microinjection of supernatant from lipopolysaccharide (LPS)-treated astrocytes.Pregnant ddY mice at gestational day 14 and timed-pregnant Wister rats (day 16 or 17) and were obtained from Japan SLC, Inc. . The pregnant mice and rat were housed individually under standard conditions  with food and water available ad libitum. The present study was conducted in accordance with the Guiding Principles for the Care and Use of Laboratory Animals adopted by the Japanese Pharmacological Society. The Ethical Committee for Animal Experimentation of Kobe Gakuin University approved all experiments .Maternal separation combined with social isolation was performed as previously described . Pups boThe elevated plus-maze (EPM) test was performed as previously described . Mice weMice were deeply anesthetized with sodium pentobarbital (65 mg/kg), and then surgery was performed as previously described at 9 weeks of age . In brieMechanical allodynia after nerve injury was measured using the von Frey test as previously described . Mice weImmunofluorescence staining was performed as previously described  with som4 cells/cm2 in 75 cm2 culture flasks and grown in minimal essential medium supplemented with 10% fetal bovine serum. To remove small process-bearing cells (mainly oligodendrocyte progenitors and microglia from the protoplasmic cell layer), the culture flasks were shaken at 250 rpm overnight 10–14 days after seeding. The monolayer cells were trypsinized and seeded on six-well culture plates or on 15 mm glass cover slips in 24-well culture plates. At this stage, approximately 95% of the cells showed immunoreactivity for GFAP.Astrocytes were prepared from the cerebra of 1- to 2-day-old Wistar rats as described . The isoBefore treatment, astrocytes in six well-culture plates were incubated in serum-free medium for 48 h. LPS was minimally diluted using serum-free medium before treatment. After incubation in serum-free medium, the cells were treated with 1,000 ng/mL LPS for 24 h.Figure 3A). The injection site in LC was confirmed using 0.5% Trypan blue in saline.Microinjection of astrocyte culture supernatant into the LC was performed as previously described , with sot-test (for comparisons between two groups). A P-value < 0.05 was considered significant.All data are expressed as the mean ± the standard error of the mean (SEM). Significant differences were determined by a one-way analysis of variance (ANOVA) followed by Scheffe’s multiple comparison tests (for comparisons between more than three groups) or Student’s Figures 1A,B). In contrast, MSSI stress induced a significant increase in GFAP expression in the LC of female mice, compared to control female mice, at 7 weeks of age .Immunoreactivity for GFAP was observed surrounding TH positive cells in the LC. In males, MSSI stress did not affect GFAP expression in the LC at 7 weeks of age, before PSL . In other region of the brain, GFAP protein expression did not change in male and female mice . GFAP positive cells were observed surrounding TH positive cells in the LC .In male and female mice, microinjection of LPS-treated astrocyte-derived supernatant into the brainstem area, including the LC, significantly increased local GFAP expression compared to non-treated control medium . In contrast, there was no difference in the number of center zone crossings between vehicle- and LPS-treated groups . The entries into open arms (%) or the time spent in open arms (%) correlated negatively with the response time to mechanical stimuli after PSL in vehicle- or LPS-treated male mice . At 1 week after PSL, the vehicle- and LPS-treated astrocyte-derived supernatant treated mice showed an increased number of responses to mechanical stimuli compared to vehicle- and LPS-treated injected sham injured male mice. Mice injected with LPS-treated astrocyte-derived supernatant showed a tendency toward an increase in the number of responses to mechanical stimuli compared to vehicle-treated injected PSL male mice. However, the number of responses against mechanical stimuli did not change between the vehicle treated group and the LPS-treated astrocyte-derived supernatant group prior to PSL .In male mice, microinjection of LPS-treated astrocyte-derived supernatant into the brainstem area, including the LC, significantly decreased the number of open arm crossings and time spent in the open arms compared to vehicle-treated male mice . The number of crossings in the center zone was comparable to that in vehicle-treated female mice . The entries into open arms (%) or the time spent in open arms (%) correlated negatively with the response time to mechanical stimuli after PSL in vehicle- or LPS-treated female mice . At 1 week after PSL, vehicle- and LPS-treated astrocyte-derived supernatant female mice showed an increased number of responses to mechanical stimuli compared to vehicle- and LPS-treated supernatant- injected female mice. Furthermore, the number of responses to mechanical stimuli showed a significant increase in LPS-treated PSL female mice compared to vehicle-treated PSL female mice. In contrast, the number of responses to mechanical stimuli before PSL was similar in both vehicle- and LPS-treated supernatant-injected female mice .Similar results were obtained in female mice. Female mice microinjected with LPS-treated astrocyte-derived supernatant showed a decreased number of open arm crossings and time spent in the open arms compared to vehicle-treated female mice  contribute to the regulation of pain and emotion . NoradreFigures 1, 2, at 7 or 12 weeks age, the GFAP expression in the LC of MSSI stressed mice with or without PSL treated was different between male and female. These results indicate that MSSI-mediated emotional dysfunction and neuropathic pain exacerbation might be more sensitively induced or worked astrocyte activation in female stressed mice, but not male stressed mice. Therefore, our findings suggest that sex differences in LC astrocytic activation induced by MSSI are responsible, at least in part, for the sex differences in anxiety-like behavior and are mediated through the damaging effects of reactive astrocytes on female LC neurons.Our previous results demonstrated that MSSI increased anxiety-like behaviors in female but not male mice  and MSSIFurthermore, to investigate the effect of acute and region-selective activation of LC astrocytes on anxiety-like or nociceptive behaviors, we microinjected the supernatant of LPS-treated astrocytes into the LC region. We found that LC astrocytes up-regulated GFAP expression and showed morphological changes, indicating that astrocytes were activated by the supernatant injection. LPS binds to toll like receptor (TLR) 4, which is expressed in astrocytes. It is thought that these signaling-induced inflammatory responses, which are mediated by the NF-κB pathway, may result in activation of astrocytes . ActivatThe important point is that LC administration of supernatant derived from LPS-treated astrocytes increased anxiety-like behavior and GFAP expression in both male and female mice. These results indicate that activation of astrocytes in the LC might result in emotional dysfunction and exacerbated mechanical allodynia. However, the GFAP expression in the LC of MSSI mice with PSL was different between males and females. We previously showed that MSSI sex-dependently induced emotional dysfunction after nerve injury, which was associated with sex differences in the stress-induced regulation of BDNF expression . It is tWe also found that LC astrocytic dysfunction caused by MSSI contributes to the exacerbation of mechanical allodynia after PSL. Despite downregulation of MSSI-induced LC GFAP overexpression by PSL, MSSI enhanced nerve injury-induced mechanical allodynia. Many studies on the relationship between pain and astrocytic function have demonstrated that inflammation or nerve injury activates astrocytes in the spinal cord and supraspinal area, and that these activated cells contribute to the development and maintenance of persistent pain . PreviouFigures 4, 5, we found that activation of astrocytes which induced by microinjection of astrocyte conditioned medium with LPS caused emotional dysfunction and exacerbated mechanical allodynia. On the other hand, there is no increased GFAP expression following MSSI in male mice although MSSI-mediated neuropathic pain exacerbation observed in male mice (Furthermore, as shown in ale mice . This diWe found that MSSI sex-dependently activated astrocytes in the LC, as indicated by increased GFAP expression, with increases in anxiety-like behavior. These MSSI-induced activated astrocytes in the LC may contribute to the exacerbation of neuropathic pain. Furthermore, male mice, but not female mice, might acquire resistance to MSSI-induced stress during growth. We have thus identified one possible and unexpected mechanism linking emotional state with changes in the pain control system, i.e., astroglial activation in the LC.Study conception and design: KN and ST; acquisition of data: KN, MK, YK; analysis and interpretation: KN, MK and ST; drafting of the manuscript: KN and ST; critical revision of the manuscript for important intellectual content; ST, statistical analysis; KN, MK; obtained funding; KN, ST, administrative, technical, or material support; KN, MK, YK, study supervision; KN, ST. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Heart failure (HF) is a complex clinical syndrome defined by the inability of the heart to pump enough blood to meet the body’s metabolic demands. Major causes of HF are cardiomyopathies , among which the most common form is dilated cardiomyopathy (DCM). DCM is defined by ventricular chamber enlargement and systolic dysfunction with normal left ventricular wall thickness, which leads to progressive HF. Over 60 genes are linked to the etiology of DCM. Titin (TTN) is the largest known protein in biology, spanning half the cardiac sarcomere and, as such, is a basic structural and functional unit of striated muscles. It is essential for heart development as well as mechanical and regulatory functions of the sarcomere. Next-generation sequencing (NGS) in clinical DCM cohorts implicated truncating variants in titin (TTNtv) as major disease alleles, accounting for more than 25% of familial DCM cases, but these variants have also been identified in 2–3% of the general population, where these TTNtv blur diagnostic and clinical utility. Taking into account the published TTNtv and their association to DCM, it becomes clear that TTNtv harm the heart with position-dependent occurrence, being more harmful when present in the A-band TTN, presumably with dominant negative/gain-of-function mechanisms. However, these insights are challenged by the depiction of position-independent toxicity of TTNtv acting via haploinsufficient alleles, which are sufficient to induce cardiac pathology upon stress. In the current review, we provide an overview of TTN and discuss studies investigating various TTN mutations. We also present an overview of different mechanisms postulated or experimentally validated in the pathogenicity of TTNtv. DCM-causing genes are also discussed with respect to non-truncating mutations in the etiology of DCM. One way of understanding pathogenic variants is probably to understand the context in which they may or may not affect protein–protein interactions, changes in cell signaling, and substrate specificity. In this regard, we also provide a brief overview of TTN interactions in situ. Quantitative models in the risk assessment of TTNtv are also discussed. In summary, we highlight the importance of gene–environment interactions in the etiology of DCM and further mechanistic studies used to delineate the pathways which could be targeted in the management of DCM. Heart failure (HF) is a complex clinical syndrome which concerns the impaired ability of the heart to pump and/or fill with blood, resulting in inadequate cardiac output to meet metabolic demands or, more commonly, adequate cardiac output but only due to compensatory neurohormonal activation  domains, interspersed with Z-insertion sequences. Z-disk TTN ligands are shown in Fig. I-band TTN is a highly interactive structure with great potential for alternative splicing. This results in isoforms contributing to cardiac and skeletal muscle specific phenotypes. The meta-transcript  of I-band TTN is mainly composed of Ig domains, cardiac N2B region, and skeletal N2A region (which contains non-repetitive sequences and Ig domains), followed by the Pro-Glu-Val-Lys (PEVK) TTN domain, all of which contribute to TTN-related elasticity  motifs. FN-III motifs are exclusive to A-band TTN. Ig and FN-III are further arranged into two super-repeats, in which FN-III domains are bisected by Ig domains. In contrast to I-band TTN, A-band TTN is inextensible, as it provides binding sites for myosin, and, hence, functions as a stable anchor. TTN binding to myosin S1 fragments also plays a role in regulating Ca+2-calmodulin regulated mechanochemical signal transduction pathways -Nbr1-p62 and MURFs in the M-band region. MURFs work in concert with other transcription factors in order to suppress the hypertrophic gene expression program, whereas the TK-Nbr1-p62 axis activates pro-hypertrophic gene expression (Granzier and Labeit TTN is a unique protein with highly extensible (I-band TTN) and inextensible regions . In addition, it contains regions undergoing extensive regional alternative splicing  and regions which are constitutive . Alternative splicing in the A-band TTN results in the cardiac-specific N2B isoform with interspersed unique sequence (N2B-Us), N2BA, which contains the N2B and N2A sequence, and skeletal isoform N2A (without N2B sequence). All these isoforms contain the extensible PEVK region. Cardiac isoforms contain three extensible regions: tandem Ig segments, PEVK segments, and cardiac-specific N2B-Us. Upon increasing their length, Ig segments stretch first, followed by PEVK and, finally, N2B-Us segments, which stretch at the upper limit of physiological sarcomeric length , routine analysis of the TTN gene had been extremely challenging because of its size and complexity. Thus, only a few TTN mutations had previously been reported, and the general incidence and spectrum of titinopathies was significantly underestimated. Early work pointed towards the importance of TTN mutations in HCM  in TTN, are all factors that have generated considerable challenges in demystifying the functional effects of TTNtv in disease penetrance, allele dosage, and by posing challenges to clinicians in genetic risk assessment for cases identified positive for TTNtv with or without overt cardiac phenotypes  also described TTNtv high enrichment in DCM compared to the control 1000 Genomes cohort , HGMD (http://www.hgmd.cf.ac.uk/ac/index.php), and/or LOVD (http://www.LOVD.nl/TTN). We will discuss individual cohorts in their respective studies, and we will then present the re-evaluation of the pooled cohorts analyzed by Akinrinade et al. , and that the required additional stress for the DCM to emerge means that TTN insufficiency alone is unlikely to be the sole cause of DCM. Another conclusion drawn from TTNtv epidemiology studies is the differential sensitivity of TTN mutations along its length towards the DCM phenotype. It appears that I-band TTNtv are less prevalent and perhaps more tolerable compared to A-band TTNtv. As has been stated earlier in the TTN signaling section, I-band TTN is mainly a substrate for signaling and metabolic activity as compared to A-band TTN, which provides structural and functional interactions with major sarcomeric contractile protein, such as myosin heavy chain and myosin binding protein C. With A-band TTNtv, such interactions are severely compromised in DCM patients and/or are at risk from defective functions relating to stress in genotype-positive asymptomatic individuals. I-band haploinsufficiency or I-band dominant negative TTN might still contribute towards signaling events occurring at I-band TTN on rest or stress conditions without severely impairing the cardiac conditions. Further, A-band TTN exons were constituted by high PSI values compared to I-band TTN, indicating that any mutation in A-band will affect most or all of the splice variants and, hence, be more deleterious, whereas mutations in I-band variants could spare splice variants and, hence, have milder outcome. The Schafer et al.  study alhttp://www.world-heart-federation.org) published a new classification scheme for cardiomyopathies, called MOGE(S) , which accounts for the environmental triggers in the quantitative model in the background of genetic susceptibility to DCM. Implementation of MOGE(S) classification in a pilot study improved the stratification of patients with DCM, most likely by using the combination of genetic evaluation and non-genetic, environmental factors  have also been described in sarcomeric genes, Z-disk genes, cytoskeletal genes, ion channels genes, nuclear envelope genes, desmosomal genes, transcription factors genes, gamma secretase activity genes, sarcoplasmic reticulum genes Fig. . Z-disk In this context, a study by Walsh et al.  re-assesn = 176) included in the study compared to 187 missense variants found in 37.2% (n = 187) of the control population (1000 Genome Europeans) , it is more feasible to introduce truncating variants  in tissue-restricted manners as to substantially aid in understanding the pathogenic mechanisms of these variants. In this regard, Deo  introducIn summary, our current understanding on truncating and non-truncating variants in DCM and other cardiac phenotypes needs to be explored beyond simple genetic events and on the functional level. The pathogenesis of DCM needs to be addressed, in particular, beyond the explanation of haploinsufficient and dominant negative lesions. Disease-causing mutations in DCM might also be addressed in the epigenetic context. Do truncating variants in different TTN domains and/or bands dictate specific epigenetic lesions? Is there a differential epigenetic sensitivity towards haploinsufficiency or dominant negative TTNtv? How do environmental stressors shape the DCM genome and epigenome in patients with genotype-positive/phenotype-negative individuals and vice versa. The limited number of genotype-positive DCM patients presenting with the spectrum of specific cardiac phenotypes and even more limited patients with one particular mutation are the major obstacles to confidently assigning the risk carried by each variant. On the other hand, it is possible that patients with variable titinopathies could present with converging patterns of epigenetic lesions, which might aid in the development and implementation of epigenotype-specific treatment regimens  in the management of DCM.Another important issue is to identify to which extent TTNtv contribute to the phenotype in the presence of other disease-causing mutations. Therefore, in order to establish the pathogenicity of rare variants, further studies should focus on prospective longitudinal population cohorts without apparent overt cardiac phenotypes needing to be established if the occurrence of cardiac events (if any) is significant in pre-symptomatic genotype-positive individuals. This can help the geneticist in counseling such individuals, or in the design of screening programs which can help to identify further family members at risk, and, finally, develop prophylactic managements . However, considerable challenges lie ahead, including the integration of masses of genetic information and their interpretation in the biological context. This will also comprise building standard algorithms for comprehensive diagnostic workups in the evaluation and management of inherited cardiac disease.Given the gigantic size of TTN, it is expected that the TTNtv landscape of DCM will increase in much higher numbers than currently known. As discussed, truncating changes are likely to be pathogenic; however, the mechanism of pathogenicity is probably less well understood. Recent functional studies highlighting the position-independent toxicity of TTNtv raise further questions on dominant negative modes of action than previously envisaged. If evidence is generalized to broader populations of TTNtv, then the preponderance of TTNtv in the A-band requires further explanation.


Lactobacillus plantarum of which L-monosodium glutamate (L-MSG) is an inducer of its production. In order to synthesize GABA in high concentrations, L-MSG was utilized as the single inducing factor, a chemically defined medium (CDM) was used as the fermentation substrate, with L. plantarum CGMCC 1.2437T cultured in medium supplemented with or without L-MSG. High-throughput transcriptome sequencing was used to explore the differential genes expression of bacterial cells at 36 h of fermentation, where the GABA concentration of CDM with L-MSG reached the peak value and was 7.7 times higher than that of medium without L-MSG at the same timepoint. A total of 87 genes showed significant differential expression induced by L-MSG: of these, 69 were up-regulated genes and 18 were down-regulated. The up-regulated genes were assigned to biological processes and molecular function, while the down-regulated genes covered biological process, cellular process and molecular function. Interrogation of results using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, indicated carbohydrate metabolism, fatty acid synthesis and amino acid metabolism were closely associated with GABA synthesis induced by L-MSG. This study provides insights into L. plantarum-mediated GABA fermentation at the molecular level and will provide a new approach for further studies related to GABA production by the other Lactic acid bacteria.Gamma-aminobutyric acid (GABA) is an inhibitory neurotransmitter found in the central nervous system of mammals. A range of bacterial species can synthesize GABA, including  Lactobacillus plantarum . CT is the cycle number where the amplified target reaches the defined threshold; Et is the CT of the experimental gene in treated samples, Rt is the CT of GAPDH in treated samples, Ec is the CT of the experimental gene in control samples, and Rc is the CT of GAPDH in control samples [To identify expression of genes of GABA-related pathways, as well as to verify RNA-seq results, real-time reverse transcriptome PCR (RT-qPCR) was performed. The RT-qPCR was performed as previously described , and eac samples . SpecifiP < 0.05 was used as the criterion of statistical significance.Statistical analysis was performed comparing data of GABA fermented production between experimental and control groups. Data were expressed as the means ± standard deviations (SD) of triplicate determinations in two dependent experiments. To test the significance between different groups, one-way ANOVA, followed by the least-significant difference (LSD) were done by using SPSS 17.0 software . -1 during the rest time of the fermentation . However, GABA was constantly synthesized at a relatively lower rate in the medium of the control group.MSG, the substrate for GABA synthesis, significantly affected the concentration of GABA synthesized by the strain during fermentation . In the TM 2500 platform was used to perform high-throughput sequencing analysis of four L. plantarum CGMCC 1.2437T libraries  to investigate the transcriptomic response to L-MSG induction during the fermentation. Nearly 8 million raw reads per library were generated and above 96.60% of total reads were identified as clean reads . The total clean reads of the four libraries were mapped to a reference genome of L. plantarum WCFS1. Among these reads, over 97% clean reads were successfully mapped to the reference database and 3074 mapped genes per library were simultaneously obtained, which suggested that the reference was suitable. In addition, 95.09–96.28% of the clean reads were uniquely mapped to the reference genome, 47.51–48.11% were mapped to the sense strand and 47.58–48.17% were mapped to the anti-sense strand ; in contrast, the correlations between different treatments were 0.975, 0.976, 0.978 and 0.980, which were all lower than that of inter-group. Such results suggested that good consistency of gene expression profiles were presented between biological replicates, and different gene expression profiles were likely to appear because of L-MSG induction. The correlations were visualized using scatterplots  method . A totalterplots . All theL. plantarum CGMCC 1.2437T that are differentially expressed in response to L-MSG induction, the numbers of read counts were compared. The genes differentially expressed between two transcriptomes were identified with the read counts, and the absolute value of log2 Ratio > 1 and Padj < 0.05 was used as the thresholds for significant differences in gene expression. The fold changes in expression (log2 readcount) ranged from -2.77 to +4.63. Among these DEGs, only 87 genes displayed significantly (Padj < 0.05) differential expression, 69 genes  were significantly upregulated and 18 genes  were significantly downregulated. Detailed information of the up-regulation and down-regulation significantly DEGs were shown in To identify genes in the In this study, the significantly DEGs induced by L-MSG were identified with GO and KEGG enrichment analysis. The GO classification assigned 67 significantly DEGs to 487 GO terms , and thep-value) showed that the most significant metabolic pathways were the phosphotransferase system (PTS) (KEGG: lp102060), pyruvate metabolism (KEGG: lp100620), pentose and glucuronate interconversions (KEGG: lp10004), citrate cycle (KEGG: lp100020), fatty acid metabolism (KEGG: lp101212), fatty acid biosynthesis (KEGG: lp100061) and the glycolysis/gluconeogenesis pathway (KEGG: lp100010). Enrichment DEGs had the largest number in this entry of metabolic pathways, but the q value was not high, which suggests it was not a significant enrichment item.In the KEGG annotation, 87 significantly DEGs were annotated into 29 metabolic pathways . The mosThis study examined induced synthesis of GABA based on L-MSG added to the culture medium as the only differential factor between experimental group and control group. In order to eliminate the influence of other irrelevant factors, a culture medium with known chemical components was used ,31. To fL. plantarum CGMCC 1.2437T were inferred.In order to further understand the molecular mechanisms of GABA-induced synthesis, this study used high-throughput transcriptome sequencing of mRNA. Induction by L-MSG mediated notable changes at the transcriptional level were observed in metabolism related to PTS, pyruvate metabolism, and fatty acid synthesis. By comparing the metabolic pathways of the experimental and control groups in the key nodes corresponding to gene expression changes, the molecular mechanisms of GABA synthesis by L-MSG induced pdhA, pdhB, pdhC and pdhD), the gene encoding pyruvate oxidase (poxL), and the genes encoding pyruvate formate lyase (pflA and pflB) were up-regulated significantly. This means acetyl-CoA, acetyl phosphate and formate based produced by pyruvic acid were all activated by L-MSG [gabT) encoding gene expression in the experimental group was down-regulated by a factor of 0.26 times, indicating that the activity of GABA-T was inhibited.DEGs of L-MSG induced cells was mainly related to enrichment in PTS and carbohydrate metabolism. The PTS mainly relate to several phosphoenolpyruvate (PEP)-mediated sugar-phosphotransferase activities and carbohydrate metabolism involved in pyruvate metabolism and glycolysis. Various monosaccharides and disaccharides may be utilized by LAB, with three sugar transmembrane transport pathways for their cellular import. The first pathway involves active transport of glucose and the hydrolysis of ATP catalyzed by specific ATP enzymes , the secby L-MSG ,56. In tby L-MSG  found a by L-MSG . TranscrThrough the comprehensive analysis of GO enrichment and KEGG metabolic pathways, we hypothesize that the PEP-mediated sugar-phosphotransferase system was activated by L-MSG, then prompting accumulation of pyruvic acid produced by PEP, and this accumulation led to its catabolism. After 36 h of fermentation, the growth of cell reached mid-stationary period with no available carbon source due to the complete consumption of glucose in the medium, and together with its continuous decomposition led to a sharp decline of pyruvate. Therefore, GABA-T lost its transaminase activity in the absence of pyruvate leading to accumulation of GABA. After 48 h of fermentation, the accumulation of GABA in the experimental group began to decline: this maybe because the pyruvate metabolism pathways related to transamination of GABA changed, causing replenishment of intracellular pyruvate, and thus activity of GABA-T transaminase was restored. However, this hypothesis requires further study.pdhD), pyruvate decarboxylase complex-dihydrolipoic acid transacetylase (pdhC), pyruvate decarboxylase complex alpha subunit (pdhA) and beta subunit (pdhB)) were up-regulated at the transcriptional level, which participated in the process of pyruvic acid converting to acetyl-CoA. This indicates that pyruvic acid was largely converted into acetyl-CoA. Meanwhile, the accD gene which encodes acetyl-CoA decarboxylase up-regulated 1.02 times, indicating acetyl-CoA continued to be used to produce malonyl-CoA by the catalysis of acetyl-CoA decarboxylase, which was further utilized in the synthesis of fatty acids. The increase in intracellular fatty acid synthesis can then improve the stability and toughness of cell membrane [Results of this study showed that after induction by L-MSG, three enzymes  were found between the experimental and control groups. Similar results were also described by Mazzoli et al [Lc. lactis to induce the fermentation, and analyzed gene expression of induced cells. Results showed the expression of gadB in the glutamate-induced condition was similar to that of non-glutamate induced cells. These results indicated that biosynthesis of GAD has less dependence on glutamic acid or sodium glutamate in the substrates. In our research the synthesis of GABA in L. plantarum CGMCC 1.2437T maybe regulated primarily by the catalytic activity of GAD, as the biosynthesis of GAD had little effect on the yield of GABA [Metabolism of amino acids was also observed. Microbial GABA was mainly derived from glutamic acid and the decarboxylation reaction of glutamate, however, there was no clear explanation as to whether there were some connections between the synthesis or decomposition of GABA and the metabolism of glutamic acid or other amino acids. Transcriptome sequencing results of this study showed that no apparent changes of the expression of li et al . They us of GABA ,65.Lactobacillus, and found that the biosynthesis of histidine decarboxylase and ornithine decarboxylase are dependent on their catalytic substrates. When histidine and ornithine existed, the biosynthetic capacity of these two decarboxylases was significantly higher than when no substrate was present. Further research reported that the biosynthesis of tryptophan decarboxylase in Enterococcus faecalis also had a dependence on tryptophan, which is its catalytic substrate [L. plantarum CGMCC 1.2437T is primarily regulated by the catalytic activity of GAD.Pessione et al.  used proubstrate . AdditioL. plantarum CGMCC 1.2437T GABA production. The potential molecular mechanism was predicted by functional gene and pathway enrichment analysis, suggesting: (1) L-MSG induced up-regulation of gadB, which facilitated GABA synthesis; (2) L-MSG induced down-regulation of gabT, which inhibited the degradation of GABA and contributed to GABA accumulation; (3) L-MSG induced conversion of glucose to succinic acid through glycolysis and pyruvate metabolism, and the succinic acid could also inhibit the catabolic pathways of GABA; (4) L-MSG could activate the synthesis of fatty acids, which increased the membrane permeability, contributed to substrata absorption, and facilitated to cell growth and metabolism. This research presents a theoretical foundation for GABA fermentation by L. plantarum at the molecular level, provides direction for further studies, and presents and approach which may be taken for related studies.The present study showed that L-MSG could induce S1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.S4 Fig(DOCX)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.


Bacillus subtilis, two major transcriptional factors, GlnR and TnrA, are involved in a sophisticated network of adaptive responses to nitrogen availability. GlnR was reported to repress the transcription of the glnRA, tnrA and ureABC operons under conditions of excess nitrogen. As GlnR and TnrA regulators share the same DNA binding motifs, a genome-wide mapping of in vivo GlnR-binding sites was still needed to clearly define the set of GlnR/TnrA motifs directly bound by GlnR.In We used chromatin immunoprecipitation coupled with hybridization to DNA tiling arrays (ChIP-on-chip) to identify the GlnR DNA-binding sites, in vivo, at the genome scale.alsT gene as a new member of the GlnR regulon. Additionally, we characterized the GlnR secondary regulon, which is composed of promoter regions harboring a GlnR/TnrA box and bound by GlnR in vivo. However, the growth conditions revealing a GlnR-dependent regulation for this second category of genes are still unknown.We provide evidence that GlnR binds reproducibly to 61 regions on the chromosome. Among those, 20 regions overlap the previously defined in vivo TnrA-binding sites. In combination with real-time in vivo transcriptional profiling using firefly luciferase, we identified the Our findings show an extended overlap between the GlnR and TnrA in vivo binding sites. This could allow efficient and fine tuning of gene expression in response to nitrogen availability. GlnR appears to be part of complex transcriptional regulatory networks, which involves interactions between different regulatory proteins.The online version of this article (doi:10.1186/s13104-017-2703-9) contains supplementary material, which is available to authorized users. Bacillus subtilis to nitrogen availability is an example of a highly sophisticated system to detect nitrogen levels and transmit this signal to effect intracellular enzyme activity and gene regulation. In this bacterium, ammonium assimilation occurs via the glutamine synthetase-glutamate synthase (GS-GOGAT) pathway to generate glutamate, the precursor for amino acids and nucleotides biosynthesis 35]. This−1, and 5 U Benzonase ml−1 (Novagen). Wild-type cells, which did not harbor a SPA fusion, were used as a control (no-SPA containing strain). GlnRSPA, PerRSPA and No-SPA containing protein complexes were isolated and analyzed as described in . Th. ThalsT,SPA binding partners. The strain expressing the glnR-spa fusion was grown in the nitrogen-rich LB medium in exponential phase. GlnR-associated proteins were purified and identified by mass spectrometry. Strains expressing no SPA-tagged protein and a SPA fusion to PerR, a non-related protein of B. subtilis, were used as negative controls [SPA pull-down complexes  fulfilling three criteria: (1) GlnR binding in ChIP-on-chip experiments; (2) the presence of a GlnR/TnrA box; (3) GlnR-dependent expression regulation.Using the ChIP-on-chip methodology, we have identified 61 enriched DNA-regions in the ons Fig. . Hence, braB, codV, bceA, yjcN and yraH was similar in wild-type and glnR mutant cells. However, regulation of these genes is known to be driven by other transcription factors  in vivo GlnR binding in ChIP-on-Chip experiments; (2) the presence of a GlnR/TnrA motif. We propose that GlnR might play a regulatory role in specific unknown conditions. The composition of the secondary regulon cannot be clearly delimited and is opened to permutations with the primary regulon depending on the discovery of yet unknown conditions involving GlnR-dependent regulation. We assume that expression of some genes could respond to specific growth conditions leading to intermediate levels of GlnR activity, as exemplified by the regulation of egulator . MoreoveSPA pull-down complexes.Finally, we reported a set of 35 GlnR binding DNA sites, which did not harbor a canonical GlnR-binding motif, suggesting that GlnR recognizes degenerated GlnR box sequences or that other factors are required for GlnR binding at these sites. It was previously shown that a GlnR protein truncated in the C-terminal domain repressed more tightly the expression of its target genes than the wild-type GlnR . DeletioIn vitro assays could be performed to study the direct interaction between the native GlnR protein and the DNA regions that do not have a GlnR-binding motif. However, the binding of GlnR to these sites might require other unknown regulatory factors or specific conditions. It will be necessary to develop in vivo approaches to study the binding of GlnR to the newly identified targets and the consequences on the regulation of the nearest genes. Moreover, the surprising interaction detected between GnR and GltA deserve further investigations.The binding characterization of GlnR to DNA regions without evident GlnR-binding motif would be an important improvement to understand the role of GlnR and require further studies. In the light of our results, we propose that binding of GlnR and TnrA to the same DNA binding sites may allow fine control over gene expression in response to various nitrogen levels. GlnR appears to be a part of complex transcriptional regulatory networks, which involves interactions between different regulatory proteins. In vivo, GlnR is found in complex with the GltA and TnrA proteins. Further investigations are required to define the exact role of the GlnR regulator in the control of the newly identified in vivo binding sites.Additional file 1: Table S2. Oligonucleotide primers used in this study.Additional file 2: Table S1. Mapping of GlnR DNA binding sites by ChIP-on-chip. ChIP-on-chip experiments were performed and data were analysed as previously described [SPA expressing Bacillus subtilis strain.escribed  using thescribed . GlnR wa


Sleep plays an important role in memory consolidation through the facilitation of neuronal plasticity; however, how sleep accomplishes this remains to be completely understood. It has previously been demonstrated that neural oscillations are an intrinsic mechanism by which the brain precisely controls neural ensembles. Inter-regional synchronization of these oscillations is also known to facilitate long-range communication and long-term potentiation (LTP). In the present study, we investigated how the characteristic rhythms found in local field potentials (LFPs) during non-REM and REM sleep play a role in emotional memory consolidation. Chronically implanted bipolar electrodes in the lateral amygdala (LA), dorsal and ventral hippocampus , and the infra-limbic (IL), and pre-limbic (PL) prefrontal cortex were used to record LFPs across sleep-wake activity following each day of a Pavlovian cued fear conditioning paradigm. This resulted in three principle findings: (1) theta rhythms during REM sleep are highly synchronized between regions; (2) the extent of inter-regional synchronization during REM and non-REM sleep is altered by FC and EX; (3) the mean phase difference of synchronization between the LA and VH during REM sleep predicts changes in freezing after cued fear extinction. These results both oppose a currently proposed model of sleep-dependent memory consolidation and provide a novel finding which suggests that the role of REM sleep theta rhythms in memory consolidation may rely more on the relative phase-shift between neural oscillations, rather than the extent of phase synchronization. It is well-established that sleep plays an important role in learning and memory  and the lateral amygdala (LA), dorsal and ventral hippocampus . Furthermore, many changes in oscillatory synchronization observed during non-REM and REM following fear conditioning and extinction were counter-intuitive considering previous literature which suggests bidirectional roles for the PL and infra-limbic prefrontal cortex (IL). Finally, we show that the mean phase difference of synchronization between the LA and VH during REM sleep predicts changes in freezing after cued fear extinction. This suggests that the role of oscillatory synchronization in memory consolidation may rely more on the relative phase-shift between neural oscillations, rather than the extent of phase synchronization.Experiments were performed on eight naive adult male Sprague-Dawley rats . Upon arrival, the rats were housed individually with free access to food and water and maintained on a 12-h light/dark cycle. All experiments took place in the daytime during the light phase. Animals were handled once daily for a minimum for 5 min to reduce potential stress induced by experimental handling. Habituation handling began 1 week prior to surgery and continued until recording sessions. Procedures were performed in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by University of Tennessee Animal Care and Use Committee (Protocol Number: #2349-UTK). On the basis of ensuring the validity of experimental results, efforts were made to reduce the number of animals used in our experiments and to minimize any possible suffering by the animals. All experiments are conducted in compliance with the ARRIVE guidelines . All surgical procedures were performed stereotaxically under aseptic conditions. Animals were anesthetized with a mixture of ketamine  and xylazine (6.25 mg/kg i.p.), placed into a stereotaxic apparatus, and secured using blunt rodent ear bars. Once the scalp was incised, three burr holes were drilled for screw placement: one anchor screw and two ground electrode screws. Then, the bipolar electrodes were chronically implanted within the LA , VH , and DH , as shown in Figure After a postsurgical recovery period of at least 7 days, animals were habituated to the recording apparatus and sleep chambers. On the first day of experimentation , animals were habituated to a fear-conditioning chamber  with a metal grid floor for 15 min Figure . On day Immediately following each of the first 3 days of behavioral testing , rats were placed in sleep chambers, connected to the recording apparatus, and allowed 4 h of undisturbed sleep-wake activity. Behavioral measurements of fear  were recorded as a video file for offline analysis of extinction and extinction recall (days 3 and 4). Freezing was calculated as percentage during each CS presentation Figure .Electrophysiological recordings took place in sleep chambers following days 1–3 of behavioral testing through the use of a multichannel amplifier system . A swivel recording apparatus was used to maintain the head plug connection while allowing rats to move freely. Local field potentials (LFPs) from each electrode pair were high-pass filtered at 0.5 Hz to mitigate any movement-related artifacts and acquired at 1,000 Hz. After testing each day, data were moved to a computer for offline sleep scoring and electrophysiological analyses.Sleep scoring was performed manually by experts using SleepSign software  with an epoch length of 10 s, as described previously Datta, , 2007. V is the instantaneous phase difference Φx − Φy at each time point and T is the total number of time points.After all data were down sampled to 512 Hz to reduce computation time, 10 epochs of each wakefulness, non-REM, and REM sleep were chosen in a pseudorandom fashion from each animal. Phase-locking value (PLV) and spectrograms were computed using complex Morlet wavelets, as detailed elsewhere Cohen, . FrequenIn essence, if phase differences do not deviate over time the trial is highly synchronous with a mean resultant length (MRL) near 1. If the phase differences are completely random over time, the trial is asynchronous with a mean result length near 0. This creates one value for each subsequent trial.circ_mean function of the Circular Statistics Toolbox .To determine the preferred phase differences within subjects and across trials, phase differences at each time point were averaged using the  Berens, . The preAfter experimentation was completed, animals were deeply-anesthetized with a mixture of ketamine (100 mg/kg) and xylazine (10 mg/kg) and then were perfused transcardially with 1x PBS (pH 7.4) followed by 10% formalin. Brains were then dissected and placed in a 10% formalin solution for 24 h followed by a 30% sucrose solution for a minimum of 48 h. After the post-fix period, brains were sectioned on a cryostat (−20°C) at 40-μm thickness, mounted on microscope slides, and stained with cresyl violet  to confirm electrode placement.post-hoc tests were used to determine individual differences between experiment days, with a significance threshold of p < 0.05.Brown-Forsythe and Bartlett's test were conducted to confirm data homogeneity. A one-way analysis of variance (ANOVA) was used to compare both power and PLV changes in each vigilance state across experimental days . Additionally, the same test was used to compare PLV across vigilance states. Tukey's n = 70) except for DH results (n = 60). Additionally, elevated IL-PL synchrony can be seen in Figures 4–7 due to unavoidable volume conduction. Despite this, statistically significant changes are still found across experimental days. All statistics not listed in the text below can be found in Tables Unfortunately one animal was lost during experimentation and another was lacking a high quality signal for the DH; therefore, the following reports the results for seven animals  and between specific cortical and subcortical regions  during non-REM sleep, compared to both REM sleep and wakefulness.Initial qualitative analysis of PLV via spectrogram plotting revealed that wakefulness seldom displayed strong synchrony, whereas non-REM and REM sleep showed synchrony predominantly in the delta and theta frequency bands, respectively Figure . As showa, IL-DHb, IL-LAc, IL-VHd, PL-DHe, PL-LAf, PL-VHg, DH-LAh, DH-VHi, and LA-VHj. As shown in Figure b, PL-DHe, PL-VHg, DH-LAh, DH-VHi, and LA-VHj electrodes. REM sleep PLV was also found to be higher when compared to wakefulness in IL-LAc, IL-VHd, PL-DHe, PL-LAf, PL-VHg, DH-LAh, DH-VHi, and LA-VHj. Additionally, theta rhythms were found to have higher PLV in non-REM sleep compared to wakefulness in IL-PLa electrodes. In contrast to delta, these results show much stronger synchronization of theta rhythms between subcortical structures during REM sleep. However, theta synchronization is also prominent between cortical and subcortical structures.For theta rhythms, a one-way ANOVA revealed significant main effects in all 10 electrode pairings  = 4.9, p = 0.009]. Tukey's post-test further revealed that PLV decreased following EX compared to FC . Significant effects were not found for any other electrode pairs. These results show limited effects of fear conditioning and extinction on synchrony during wakefulness.During wakefulness, no significant effects were found for PLV of delta rhythms, as shown in Figure a, PL-LAb, PL-VHc, and LA-VHe electrode pairings. Compared to BL, Tukey's post-test revealed a significant increase following FC in IL-DHa electrodes. Additionally, compared to FC, a decrease was found following EX in the IL-DHa, PL-LAb, PL-VHc, and LA-VHe electrode pairs. For theta rhythms, a one-way analysis of variance revealed significant main effects of PLV on the PL-LAb and DH-LAd electrode pairs. Tukey's multiple comparisons test revealed that PLV following FC was increased compared to BL in the PL-LAb electrode pair and decreased compared to both BL and EX in DH-LAd pairings. These results show that non-REM sleep revealed greater effects for delta rather than theta synchrony.As shown in Figure g and DH-VHi electrode pairings . Furthermore, visual inspection of Figure Investigation into the preferred phase differences during vigilance states following FC and EX led to an interesting discovery. Although, strong inter-trial phase clustering was displayed within single subjects, the preferred phase differences across subjects appeared to be more evenly distributed, as displayed in Figure The present study highlights memory consolidation-associated network interactions during sleep-wake stages. The principal findings of this study are as follows: (1) theta rhythms during REM sleep are highly synchronized between regions; (2) the extent of inter-regional synchronization during REM and non-REM sleep is altered by FC and EX; (3) the mean phase difference of synchronization between the LA and VH during REM sleep predicts changes in freezing after cued fear extinction. These results are discussed to highlight a novel mechanism through which REM sleep theta rhythms may facilitate neural plasticity.In this study, we investigated the effects of fear learning and extinction on sleep-dependent oscillatory synchronization between five neural regions: the infra-limbic and pre-limbic medial prefrontal cortex , ventral and dorsal hippocampus , and the lateral amygdala (LA). We hypothesized that the levels of sleep-dependent oscillatory synchronization (recorded immediately following each day of experimentation) should increase following fear-related learning, as both sleep and oscillatory synchronization have been implicated in memory processes. In the current model of memory function in sleep, non-REM and REM sleep are responsible for system consolidation and local synaptic modification, respectively Datta, . AlthougIn addition to high baseline oscillatory synchronization, changes in oscillatory synchrony provide evidence for a role in memory consolidation. Interestingly, the changes noted in this study are not completely in line with existing literature. The dominant model of the mPFC suggests a division of labor between the PL and IL such that they are responsible for fear expression and suppression, respectively  why were the phase differences not more directly related to 180° and 0/360°; (2) and why was this only observed for one electrode pairing? The first question can likely be answered by the conduction delay of the action potential. Unless two regions have a mutual input or lie in close proximity to one another, an exactly 0° phase lag (or exactly 180° lag) should not be expected (Fell and Axmacher, In conclusion, theta oscillations during REM sleep are highly synchronized inter-regionally throughout the cortico-limbic system, suggesting that theta oscillations are a prime candidate for long-range system consolidation. Though the changes in both delta and theta synchrony were smaller than expected, the displayed changes in inter-regional synchronization in response to emotional learning further supports this hypothesis. Moreover, we hypothesize that LTP and LTD may be modulated by the phase-shift of synchronized REM sleep theta rhythms. This data provides a novel perspective on the role of neuronal rhythms found during non-REM and REM sleep in emotional memory consolidation. This study highlights the importance of a better understanding of neuronal network dynamics in order to completely elucidate sleep's role in behavioral plasticity. Further, we hope that these findings will provide a useful foundation for future investigations.MT: designed the study, performed experiments, analyzed data, and wrote manuscript. LC and PG: performed experiment. SD: designed the study and co-wrote manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Although FER can be conducted using multiple sensors, this review focuses on studies that exclusively use facial images, because visual expressions are one of the main information channels in interpersonal communication. This paper provides a brief review of researches in the field of FER conducted over the past decades. First, conventional FER approaches are described along with a summary of the representative categories of FER systems and their main algorithms. Deep-learning-based FER approaches using deep networks enabling “end-to-end” learning are then presented. This review also focuses on an up-to-date hybrid deep-learning approach combining a convolutional neural network (CNN) for the spatial features of an individual frame and long short-term memory (LSTM) for temporal features of consecutive frames. In the later part of this paper, a brief review of publicly available evaluation metrics is given, and a comparison with benchmark results, which are a standard for a quantitative comparison of FER researches, is described. This review can serve as a brief guidebook to newcomers in the field of FER, providing basic knowledge and a general understanding of the latest state-of-the-art studies, as well as to experienced researchers looking for productive directions for future work. Facial emotions are important factors in human communication that help us understand the intentions of others. In general, people infer the emotional states of other people, such as joy, sadness, and anger, using facial expressions and vocal tone. According to different surveys ,2, verbaInterest in automatic facial emotion recognition (FER)  has also been increasing recently with the rapid development of artificial intelligent techniques, including in human-computer interaction (HCI) ,4, virtuThis paper first divides researches on automatic FER into two groups according to whether the features are handcrafted or generated through the output of a deep neural network. In conventional FER approaches, the FER is composed of three major steps, as shown in In contrast to traditional approaches using handcrafted features, deep learning has emerged as a general approach to machine learning, yielding state-of-the-art results in many computer vision studies with the availability of big data .Deep-learning-based FER approaches highly reduce the dependence on face-physics-based models and other pre-processing techniques by enabling “end-to-end” learning to occur in the pipeline directly from the input images . Among tFER can also be divided into two groups according to whether it uses frame or video images . First, The facial action coding system (FACS) is a system based on facial muscle changes and can characterize facial actions to express individual human emotions as defined by Ekman and Friesen  in 1978.Facial landmarks (FLs) are visually salient points in facial regions such as the end of the nose, ends of the eye brows, and the mouth, as described in Basic emotions (BEs) are seven basic human emotions: happiness, surprise, anger, sadness, fear, disgust, and neutral, as shown in Compound emotions (CEs) are a combination of two basic emotions. Du et al.  introducMicro expressions (MEs) indicate more spontaneous and subtle facial movements that occur involuntarily. They tend to reveal a person’s genuine and underlying emotions within a short period of time. Facial action units (AUs) code the fundamental actions (46 AUs) of individual or groups of muscles typically seen when producing the facial expressions of a particular emotion , as showBefore reviewing researches related to FER, special terminology playing an important role in FER research is listed below:The focus is on providing a general understanding of the state-of-the art FER approaches, and helping new researchers understand the essential components and trends in the FER field.Various standard databases that include still images and video sequences for FER use are introduced, along with their purposes and characteristics.Key aspects are compared between conventional FER and deep-learning-based FER in terms of accuracy and resource requirements. Although deep-learning-based FER generally produces better FER accuracy than conventional FER, it also requires a large amount of processing capacity, such as a graphic processing unit (GPU) and central processing unit (CPU). Therefore, many current FER algorithms are still being used in embedded systems, including smartphones.A new direction and application for future FER studies are presented.Despite the long history related to FER, there are no comprehensive literature reviews on the topic of FER. Some review papers ,20 have The remainder of this paper is organized as follows. In For automatic FER systems, various types of conventional approaches have been studied. The commonality of these approaches is detecting the face region and extracting geometric features, appearance features, or a hybrid of geometric and appearance features on the target face. For the geometric features, the relationship between facial components is used to construct a feature vector for training ,23. GhimThe appearance features are usually extracted from the global face region  or diffeFor hybrid features, some approaches ,27 have In video sequences, many systems ,22,23,28Apart from FER of 2D images, 3D and 4D (dynamic 3D) recordings are increasingly used in expression analysis research because of the problems presented in 2D images caused by inherent variations in pose and illumination. 3D facial expression recognition generally consists of feature extraction and classification. One thing to note in 3D is that dynamic and static system are very different because of the nature of data. Static systems extract feature from statistical models such as deformable model, active shape model, analysis of 2D representations, and distance-based features. In contrast, dynamic systems utilize 3D image sequences for analysis of facial expressions such as 3D motion-based features. For FER, 3D images also use the similar conventional classification algorithms ,30. AlthSome researchers ,33,34,35Commonly, conventional approaches determine features and classifiers by experts. For feature extraction, many well-known handcrafted feature, such as HoG, LBP, distance and angle relation between landmarks are used and the pre-trained classifiers, such as SVM, AdaBoost, and random forest, are also used for FE recognition based on the extracted features. Conventional approaches require relatively lower computing power and memory than deep learning-based approaches. Therefore, these approaches are still being studied for use in real-time embedded systems because of their low computational complexity and high degree of accuracy . HoweverIn recent decades, there has been a breakthrough in deep-learning algorithms applied to the field of computer vision, including a CNN and recurrent neural network (RNN). These deep-learning-based algorithms have been used for feature extraction, classification, and recognition tasks. The main advantage of a CNN is to completely remove or highly reduce the dependence on physics-based models and/or other pre-processing techniques by enabling “end-to-end” learning directly from input images . For theA CNN contains three types of heterogeneous layers: convolution layer, max pooling layer, and fully connected layers, as shown in Breuer and Kimmel  employedZhao et al.  proposedThe cell state is a horizontal line running through the top of the diagram, as shown in A forget gate layer is used to decide what new information to store in the cell state.An input gate layer is used to decide which values will be updated in the cell.An output gate layer provides outputs based on the cell state.As we determined in our review, many approaches have adopted a CNN directly for FER use. However, because CNN-based methods cannot reflect temporal variations in the facial components, a recent hybrid approach combining a CNN for the spatial features of individual frames, and long short-term memory (LSTM) for the temporal features of consecutive frames, was developed. LSTM is a special type of RNN capable of learning long-term dependencies. LSTMs are explicitly designed to solve the long-term dependency problem using short-term memory. An LSTM has a chain-like structure, although the repeating modules have a different structure, as shown in The LSTM or RNN model for modeling sequential images has two advantages compared to standalone approaches. First, LSTM models are straightforward in terms of fine-tuning end-to-end when integrated with other models such as a CNN. Second, an LSTM supports both fixed-length and variable-length inputs or outputs . The representative studies using a combination of a CNN and an LSTM (RNN) include the following:Kahou et al.  proposedKim et al.  utilizedChu et al.  proposedHasani and Mahoor  proposedGraves et al.  used a rJain et al.  proposedCommonly, deep learning-based approaches determine features and classifiers by deep neural networks experts, unlike conventional approaches. Deep learning-based approaches extract optimal features with the desired characteristics directly from data using deep convolutional neural networks. However, it is not easy to collect a large amount of training data for the facial emotion under the different conditions enough to learn deep neural networks. Moreover, deep learning-based approaches require more a higher-level and massive computing device than convention approaches to operate training and testing . TherefoAmong the many approaches based on a standalone CNN or combination of LSTM and CNN, some representative works are shown in As determined through our review conducted thus far, the general frameworks of the hybrid CNN-LSTM and CNN-RNN-based FER approaches have similar structures, as shown in The Extended Cohn-Kanade Dataset (CK+) : CK+ conCompound Emotion (CE) : CE contDenver Intensity of Spontaneous Facial Action Database (DISFA) : DISFA cBinghamton University 3D Facial Expression (BU-3DFE) : BecauseJapanese Female Facial Expressions (JAFFE) : The JAFExtended Yale B face (B+) : This daMMI : MMI conBinghamton-Pittsburgh 3D Dynamic Spontaneous (BP4D-Spontanous) : BP4D-spThe Karolinska Directed Emotional Face (KDEF) : This daIn the field of FER, numerous databases have been used for comparative and extensive experiments. Traditionally, human facial emotions have been studied using either 2D static images or 2D video sequences. A 2D-based analysis has difficulty handling large pose variations and subtle facial behaviors. The analysis of 3D facial emotions will facilitate an examination of the fine structural changes inherent in spontaneous expressions . TherefoUnlike the databases described above, MPI facial expression database  collectsIn recent, other sensors, such as NIR camera, thermal camera, and Kinect sensors, are having interesting of FER researches because visible light image is easily changeable when there are changes in environmental illumination conditions. As the database captured from NIR camera, Oulu-CASIA NIR&VIS facial expression database  consistsAs described here, various sensors other than the camera sensor are used for FER, but there is a limitation in improving the recognition performance with only one sensor. Therefore, it is predicted that the attempts to increase the FER through the combination of various sensors, will continue in the future.Given the FER approaches, evaluation metrics of the FER approaches are crucial because they provide a standard for a quantitative comparison. In this section, a brief review of publicly available evaluation metrics and a comparison with the benchmark results are provided.Many approaches are used to evaluate the accuracy using two different experiment protocols: subject-independent and cross-dataset tasks . First, The second protocol is a cross-database task. In this task, one dataset is used entirely for testing the model, and the remaining datasets listed in The evaluation metrics of FER are classified into four methods using different attributes: precision, recall, accuracy, and F1-score.i that are correctly recognized. The recall is the number of correct recognitions of emotion i over the actual number of images with emotion i [The precision (P) is defined as TP/(TP + FP), and the recall (R) is defined as TP/(TP + FN), where TP is the number of true positives in the dataset, FN is the number of false negatives, and FP is the number of false positives. The precision is the fraction of automatic annotations of emotion motion i . The accAnother metric, the F1-score, is divided into two metrics depending on whether they use spatial or temporal data: frame-based F1-score (F1-frame) and event-based F1-score (F1-event). Each metric captures different properties of the results. This means that a frame-based F-score has predictive power in terms of spatial consistency, whereas an event-based F-score has predictive power in terms of the temporal consistency . A frameER and EP are event-based recall and precision. ER is the ratio of correctly detected events over the true events, while the EP is the ratio of correctly detected events over the detected events. F1-event considers that there is an event agreement if the overlap is above a certain threshold [An event-based F1-score is used to measure the emotion recognition performance at the segment level because emotions occur as a temporal signal.hreshold .To show a direct comparison between conventional handcrafted-feature-based approaches and deep-learning-based approaches, this review lists public results on the MMI dataset. As shown in A large-scale dataset and massive computing power are required for training as the structure becomes increasingly deep.Large numbers of manually collected and labeled datasets are needed.Large memory is demanded, and the training and testing are both time consuming. These memories demanding and computational complexities make deep learning ill-suited for deployment on mobile platforms with limited resources .Considerable skill and experience are required to select suitable hyper parameters, such as the learning rate, kernel sizes of the convolutional filters, and the number of layers. These hyper-parameters have internal dependencies that make them particularly expensive for tuning.Although they work quite well for various applications, a solid theory of CNNs is still lacking, and thus users essentially do not know why or how they work.Although deep-learning-based FER approaches have achieved great success in experimental evaluations, a number of issues remain that deserve further investigation: This paper presented a brief review of FER approaches. As we described, such approaches can be divided into two main streams: conventional FER approaches consisting of three steps, namely, face and facial component detection, feature extraction, and expression classification. The classification algorithms used in conventional FER include SVM, Adaboost, and random forest; by contrast, deep-learning-based FER approaches highly reduce the dependence on face-physics-based models and other pre-processing techniques by enabling “end-to-end” learning in the pipeline directly from the input images. As a particular type of deep learning, a CNN visualizes the input images to help understand the model learned through various FER datasets, and demonstrates the capability of networks trained on emotion detection, across both the datasets and various FER related tasks. However, because CNN-based FER methods cannot reflect the temporal variations in the facial components, hybrid approaches have been proposed by combining a CNN for the spatial features of individual frames, and an LSTM for the temporal features of consecutive frames. A few recent studies have provided an analysis of a hybrid CNN-LSTM (RNN) architecture for facial expressions that can outperform previously applied CNN approaches using temporal averaging for aggregation. However, deep-learning-based FER approaches still have a number of limitations, including the need for large-scale datasets, massive computing power, and large amounts of memory, and are time consuming for both the training and testing phases. Moreover, although a hybrid architecture has shown a superior performance, micro-expressions remain a challenging task to solve because they are more spontaneous and subtle facial movements that occur involuntarily. This paper also briefly introduced some popular databases related to FER consisting of both video sequences and still images. In a traditional dataset, human facial expressions have been studied using either static 2D images or 2D video sequences. However, because a 2D-based analysis has difficulty handling large variations in pose and subtle facial behaviors, recent datasets have considered 3D facial expressions to better facilitate an examination of the fine structural changes inherent to spontaneous expressions. Furthermore, evaluation metrics of FER-based approaches were introduced to provide standard metrics for comparison. Evaluation metrics have been widely evaluated in the field of recognition, and precision and recall are mainly used. However, a new evaluation method for recognizing consecutive facial expressions, or applying micro-expression recognition for moving images, should be proposed. Although studies on FER have been conducted over the past decade, in recent years the performance of FER has been significantly improved through a combination of deep-learning algorithms. Because FER is an important way to infuse emotion into machines, it is advantageous that various studies on its future application are being conducted. If emotional oriented deep-learning algorithms can be developed and combined with additional Internet-of-Things sensors in the future, it is expected that FER can improve its current recognition rate, including even spontaneous micro-expressions, to the same level as human beings.


Bowel endoscopy referrals from primary care have increased steadily over recent years. However, most patients do not have significant colorectal disease (SCD). Therefore, strategies to select those who would benefit most from endoscopy are of current interest. A recent study developed a multivariable diagnostic model for SCD with routine clinical information, extended with quantitative faecal calprotectin (f-C) point-of-care (POC) testing and/or qualitative POC faecal immunochemical test (FIT) for haemoglobin (f-Hb) results. This study used POC tests for both f-C and f-Hb; however, POC tests have many disadvantages and there are several reasons why quantitative measurements of f-Hb are advantageous. Quantitative faecal immunochemical tests have been used very successfully in triage of patients presenting in primary care as a rule-out test. Studies have compared f-C and f-Hb in this clinical context and consider that f-C is not required in diagnosis. A single quantitative f-Hb result, without any clinical information, could be sufficient to decide whom to refer for endoscopy and, because of the significant overlap of symptoms in those with and without SCD, could be the primary investigation performed.http://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-016-0684-5.Please see related article:  The number or requests for lower gastrointestinal endoscopy has continued to increase in recent years, partly due to the success of colorectal cancer (CRC) screening programmes and the surveillance of greater number of patients with known and treated disease, but mainly due to referrals from primary care to investigate patients with lower abdominal symptoms. As documented by Elias et al. , the majElias et al.  used datThis study used POC tests for both f-C and f-Hb, the rationale being that these can be easily executed at the time and place of patient care. However, POC tests have several disadvantages – currently available POC FITs have considerable differences with regard to their analytical detection limit . TherefoElias et al.  demonstrThere is much evidence that a single f-Hb result could be sufficient to decide whom to refer for endoscopy . Indeed,Deciding which patients presenting with lower abdominal symptoms will benefit most from endoscopy is problematic. Combined faecal biomarkers, such as f-C and f-Hb, have been advocated, but f-Hb alone has advantages. Qualitative estimates of f-Hb also provide more information than qualitative f-Hb POC tests. Simple and rapid diagnostic pathways are also advantageous. Thus, a possible strategy would be to collect a sample for qualitative measure of f-Hb from all patients presenting with lower abdominal symptoms in primary care. Following this, senior endoscopy staff could assess, taking the f-Hb results and symptoms into account, whether there is a need for the patient to undergo endoscopy. Nevertheless, there are, of course, other alternative strategies and it is hoped that future research will explore the best applications of f-Hb in the triage of the symptomatic, although these might be highly dependent on local circumstances and approaches.


Short stature or short legs is associated with cardiometabolic disease. Few studies have addressed this issue in children, incorporated repeated measures, or studied modern cohorts.We examined if change in total height, leg length and trunk length between two time points from early (median: 3.2 years) to mid-childhood (median: 7.7 years), with and without adjustment for concurrent change in adiposity (subscapular plus triceps skinfold thickness), was associated with mid-childhood cardiometabolic risk in 315 boys and 295 girls from Project Viva. The main outcome was a cardiometabolic risk score based on sex-specific internal z-scores for systolic blood pressure, waist circumference, homeostatic model assessment of insulin resistance, triglycerides and high-density lipoprotein-cholesterol.Mean (SD) total height was 97.9 (4.5) cm in boys and 97.1 (4.7) cm in girls in early childhood and 129.1 (7.2) cm in boys and 128.3 (7.9) cm in girls in mid-childhood. Trunk length constituted about half of total height. In linear regression models adjusted for parental anthropometry and socio-demographics, faster growth in total height, leg length and particularly trunk length, were associated with higher cardiometabolic risk in mid-childhood. Per 1 cm annual increase in trunk length, the cardiometabolic risk score was 0.23 z-score  higher among boys and 0.47 z-score  higher among girls. Estimates were attenuated after adjusting for adiposity .Rapid linear growth, particularly in trunk length, was associated with higher cardiometabolic risk in childhood, which was explained by relationships of linear growth with adiposity in boys, but only partly in girls. Slower fetal and infant growth followed by faster growth during childhood is positively associated with a higher risk of later coronary heart disease (CHD) and diabetes –3. StudiAlthough all studies investigating height components aim to examine how pre-pubertal growth is associated with cardiometabolic risk, studies using repeated measures during childhood are lacking. Moreover, many of the prior studies included populations at substantial nutritional or socioeconomic risk, which may not be generalizable to modern populations in developed settings. Given the contradictory findings of both faster overall linear growth and shorter leg length being associated with higher cardiometabolic risk, we hypothesized that faster pre-pubertal growth, compared to normal growth, would be associated with higher cardiometabolic risk in childhood, and that these associations might be stronger for growth in trunk length than for growth in leg length. Furthermore, we hypothesized that the associations could be influenced by adiposity. We therefore investigated how growth in total height and its components between two time points in childhood were related to mid-childhood cardiometabolic risk, including whether the associations differed by concurrent changes in adiposity, in the Boston-area Project Viva cohort, a well-nourished population.Participants were enrolled in Project Viva, during early pregnancy between 1999 and 2002, from obstetric practices of Atrius Harvard Vanguard Medical Associates in eastern Massachusetts ), with the mid-childhood cardiometabolic risk score. We then used multivariable linear regression models to examine associations of growth in total height and its components with cardiometabolic risk score and the individual cardiometabolic biomarkers. Before entering exposures as continuous variables in regression models, we ensured linearity of associations by examining exposures in sex-specific quartiles.We examined the correlations between early and mid-childhood anthropometrics using Spearman correlations. Given potential sex differences in cardiometabolic risk and childhood growth, we conducted analyses separately for boys and girls , 24, eveIn the multivariable linear regression analysis, we started with base models including child’s age at each visit, child’s race/ethnicity, and baseline (early childhood) total height, leg or trunk length (Model 1). In the models for annual growth in leg length and trunk length we then added growth in the other height component to investigate the independent contributions of each (Model 2). Additionally, we adjusted for height and BMI of both parents (Model 3), and our final model also included marital status in pregnancy and level of maternal education, as potential socioeconomic confounding factors (Model 4). Higher effect estimates for the association between growth in total height and mid-childhood cardiometabolic risk score were observed for both sexes when excluding baseline total height in the model . This coAs in our previous work investigating height components in Project Viva, we based our conclusions on models that included growth in ‘absolute’ leg length and trunk length . Some stAs children with faster linear growth may accumulate more adipose tissue , we asseWe performed a series of sensitivity analyses: We investigated associations of total height and its components with systolic blood pressure and waist circumference in the larger group of children with at least one available outcome (n = 971), and as we found similar results we report everything for the smaller subgroup with additional information on blood outcomes (n = 610). As black children typically have longer legs than white children of the same age , we condTo account for missing data, we performed multiple imputation for all 2128 mother-child pairs in Project Viva. We then limited the analysis to the 610 included participants. We provided information about the number of imputed values for all variables along with descriptive data for the 470 participants in the complete case analysis in We included 315 boys and 295 girls in the main analyses . Boys werd quartile and girls who were in the 4th quartile of growth in trunk length had a mean mid-childhood cardiometabolic risk score of 0.12 and 0.27 z-score, respectively, which were the highest scores observed across the quartiles of linear growth .By definition, the mean cohort-specific cardiometabolic risk score was 0. When investigating quartiles of linear growth we found that boys who were in the 3r growth . ChildreIn both sexes the minimally adjusted multivariable linear regression analyses showed that greater increases in total height, leg length, and trunk length were positively associated with mid-childhood cardiometabolic risk score , Model 1In general, associations with each of the five cardiometabolic outcomes were stronger for growth in trunk length than for growth in total height or leg length, although they were all largely in the same direction . A 1 cm/In boys, it was especially the positive associations of growth in total height and its components with waist circumference along with the slightly weaker associations with systolic blood pressure and HOMA-IR that contributed to the higher cardiometabolic risk score in mid-childhood, whereas for girls the positive associations of growth in total height and its components with systolic blood pressure, waist circumference and HOMA-IR, almost equally contributed to the higher cardiometabolic risk score . The patIn this longitudinal study of US children, faster linear growth as assessed by annual increases in total height, leg length, and trunk length from early to mid-childhood was associated with a higher cardiometabolic risk in mid-childhood, with strongest associations observed for increases in trunk length. These associations were primarily due to positive associations with three of the five cardiometabolic risk score components: systolic blood pressure, waist circumference, and HOMA-IR. The associations were considerably stronger in girls, who also had a higher mean level of HOMA-IR, than in boys. The associations were largely unchanged when accounting for parental anthropometrics, suggesting that the observed associations are primarily due to factors other than genetics. In boys, the associations were explained by relationships of linear growth with overall adiposity, whereas this was only partly the case in girls.Prior work in Project Viva demonstrated that growth in trunk length from early to mid-childhood is associated with an increase in systolic blood pressure during the period . In thisIn our prior work, we hypothesized that children with greater trunk length have higher blood pressures because an additional pressure is needed to overcome gravity to perfuse the brain . Even thIn contrast to our findings, among pre-pubertal children in 1937–1939 in the Boyd Orr cohort, leg length, but not trunk length, was associated with CHD in adulthood , 16. ThoSome studies among adults have found that trunk length is associated with insulin resistance and type 2 diabetes , 29, 30,Other authors hypothesized that early onset of puberty explains why both faster pre-pubertal linear growth and shorter leg length in adulthood are associated with later cardiometabolic diseases . Girls rStrengths of this study include repeated measurements of detailed anthropometry, consideration of parental anthropometry, and the availability of several different childhood cardiometabolic biomarkers. Although prospective evidence suggests that height components are related to later cardiometabolic disease, most research that includes markers of cardiometabolic health has been cross-sectional and has examined individual markers rather than a summary cardiometabolic risk score. Furthermore, we have not found any modern cohort studies investigating associations of childhood height components, or growth in height components, with cardiometabolic health.There are also limitations to this study. Project Viva represents a relatively well-educated and high-income population despite its diverse racial and ethnic backgrounds, which means that findings may not be generalizable to lower socio-economic populations and settings in developing countries. Furthermore, we assumed, for practical reasons, that total height and sitting height provide sufficient information to partition stature into trunk and leg length. Calculating leg length from total height and sitting height, instead of measuring leg length from the greater trochanter to the floor, increases the measurement error as it is based on two measurements instead of one, which could bias the results for leg length towards the null. Moreover, buttock fatness may lead to overestimation of trunk length and consequently underestimation of leg length in overweight children  which coMore rapid linear growth from early to mid-childhood, particularly in trunk length, was associated with higher cardiometabolic risk in mid-childhood, indicating that it may be of great importance to also consider linear growth when evaluating cardiometabolic biomarkers in childhood. The higher cardiometabolic risk was due to associations with not only systolic blood pressure but also waist circumference and HOMA-IR, suggesting a potential higher risk of developing hypertension, type II diabetes, and possibly cardiovascular disease later in life. The associations were explained by relationships of linear growth with overall adiposity in boys, but this was only partly the case for girls.S1 TableAbbreviations: CI, confidence interval. Model 1: Adjusted for child’s age at the early and mid-childhood visit and child’s race/ethnicity. Model 2: Model 1 + rate of growth in other height component (i.e. rate of growth in leg length adjusted for rate of growth in trunk length and vice versa). Model 3: Model 2 + maternal pre-pregnancy body mass index and height and paternal body mass index and height. Model 4: Model 3 + maternal education and marital status in pregnancy. Growth is calculated as the difference in the respective variable between early and mid-childhood visit, divided by the time elapsed in years. The cardiometabolic risk score is composed of the mean of five sex-specific internal z-scores for systolic blood pressure, waist circumference, log-transformed HOMA-IR, log-transformed triglycerides and inverted HDL-cholesterol.(DOCX)Click here for additional data file.S2 TableAbbreviations: CI, confidence interval; y, year. All estimates are adjusted for child's age at both the early and mid-childhood visit, race/ethnicity, baseline height component (early childhood), rate of growth in other height component, maternal height and pre-pregnancy body mass index, education and marital status in pregnancy, and paternal height and body mass index (Model 4). Growth/Change is calculated as the difference in the respective variable between early and mid-childhood visit, divided by the time elapsed in years.(DOCX)Click here for additional data file.S3 TableAbbreviations: BMI, body mass index; HDL, high-density lipoprotein; HOMA-IR, homeostatic model assessment of insulin resistance; y, year. Change is calculated as the difference in the respective variable between early and mid-childhood visit, divided by the time elapsed in years. The cardiometabolic risk score is composed of the mean of five sex-specific internal z-scores for systolic blood pressure, waist circumference, log-transformed HOMA-IR, log-transformed triglycerides and inverted HDL-cholesterol.(DOCX)Click here for additional data file.S4 TableAbbreviations: n, number; SD, standard deviation; SE, standard error; y, year(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.


Live-cell single-molecule imaging was introduced more than a decade ago, and has provided critical information on remodeling of the actin cytoskeleton, the motion of plasma membrane proteins, and dynamics of molecular motor proteins. Actin remodeling has been the best target for this approach because actin and its associated proteins stop diffusing when assembled, allowing visualization of single-molecules of fluorescently-labeled proteins in a state specific manner. The approach based on this simple principle is called Single-Molecule Speckle (SiMS) microscopy. For instance, spatiotemporal regulation of actin polymerization and lifetime distribution of actin filaments can be monitored directly by tracking actin SiMS. In combination with fluorescently labeled probes of various actin regulators, SiMS microscopy has contributed to clarifying the processes underlying recycling, motion and remodeling of the live-cell actin network. Recently, we introduced an electroporation-based method called eSiMS microscopy, with high efficiency, easiness and improved spatiotemporal precision. In this review, we describe the application of live-cell single-molecule imaging to cellular actin dynamics and discuss the advantages of eSiMS microscopy over previous SiMS microscopy. Remodeling of the cortical cytoskeleton plays a central role in cell locomotion, cytokinesis, endocytosis, phagocytosis and tissue organization. To elucidate the regulation of cell morphogenesis, real-time monitoring of molecular behavior in the actin cytoskeleton offers tremendous potential. The development of live-cell fluorescence single-molecule imaging has opened a window for the direct viewing of assembly and remodeling processes of the actin filament network. Many of these processes have turned out to occur much faster than predicted by in vitro biochemical data . Live-cePrior to the development of this approach, two methods were mainly employed to monitor the dynamics of actin filament turnover in live cells. In one method, researchers observed the site of incorporation of microinjected labeled actin probes ,9. TheseOn the other hand, single-molecule imaging directly visualizes assembly, dwell time and movement of individual fluorescently labeled molecules. One can also follow the change in the molecular behavior over time by only intermittently acquiring the images. In 1998, fluorescent speckle microscopy (FSM), which visualizes movement of cytoskeletal polymers in living cells with higher resolution than the above microscopy techniques, was introduced . The priIn this article, we briefly review principles and applications of SiMS microscopy. We also summarize our recent progress in SiMS methods to provide background information for our accompanying paper introducing new near infrared actin probes.2·s−1 [SiMS microscopy is an approach to monitor complex behaviors of proteins in living cells with considerably high resolution. In the original SiMS analysis, which was first introduced in 2002 , individ2·s−1 . Monomer2·s−1 ,26,27,282·s−1 .Direct visualization of single-molecule proteins in live cells has revealed unexpected molecular behaviors that are not consistent with prior knowledge from in vitro biochemical studies. For examples, at steady state in vitro, actin assembles at the barbed end (plus end) and depolymerizes at the pointed end (minus end), which is referred to as “treadmilling”. Lamellipodia, the sheet-like structure which cells extend during migration, contain a highly dense actin meshwork . In lameKd of 0.06–1 nM [−1, which is 100-times faster than the dissociation of EGFP-CP from the barbed end at 0.005 s−1 in vitro [Capping protein (CP) regulates actin polymerization by binding the barbed end of an actin filament, which blocks assembly and disassembly of actin subunits . In vitr.06–1 nM ,37,38. Sin vitro  also supin vitro .SiMS data have been used in quantitative mathematical models to investigate how complex actin dynamics is coordinated in vivo. Ryan et al. proposed a model postulating that a diffusive, autocatalytic activator promotes actin polymerization; filamentous actin accumulation in turn inhibits further activator accumulation . SimulatV600E, a cancer-associated mutant of BRAF. However, vemurafenib can paradoxically activate the Ras/RAF/MAPK pathway via activation of CRAF  through the formation of dimeric RAF complexes [SiMS analysis is often capable of revealing the rapid response of molecules to pharmacological treatment. Vemurafenib is a BRAF  enzyme inhibitor for the treatment of patients who have metastatic melanoma. The compound was developed to inhibit BRAFomplexes ,41. Suchomplexes . SiMS imomplexes . As showTo assist in the analysis of SiMS data, the imaging analysis tool, Speckle TrackerJ  has beenIn 2014, we introduced a new SiMS method, which is easy-to-use for researchers without prior background in SiMS and that achieves high spatiotemporal resolution . We callIn eSiMS, we employed an actin probe that is chemically labeled with a red fluorescent DyLight 550 dye  on lysine side chains. Electroporation-mediated delivery of DyLight 550-actin (DL550-actin) enables the labeling of cells with 100% efficiency at the optimal low density A. Note tThe actin network at the cell periphery continuously moves toward the central region, namely the retrograde actin flow ,32. The Usage of chemically labeled probes in the eSiMS method extends availability of fluorophores to a wide-range of excitation/emission wavelengths. Near infrared (NIR) emissive dyes have advantages in the imaging of thick cells and tissues, because fluorescence imaging in the long-wavelength region facilitates low autofluorescence background, low phototoxicity to cells, and deep tissue penetration ,51. In tThe new eSiMS microscopy introduced here makes it easy to use live-cell single-molecule imaging with a very high spatiotemporal resolution. With the methodological advantage, the eSiMS microscopy will help researchers extend the application of single-molecule analysis. For instance, the principles of the eSiMS method are applicable to many other proteins for monitoring various molecular dynamics in live cells. In addition, a new NIR actin probe introduced in the accompanying article will extend single-molecule analysis to monitoring actin remodeling processes in deep cellular structures with three-color imaging. The eSiMS microscopy with NIR probes will be applicable for monitoring single-molecules three-dimensionally. To carry out the three-dimensional SiMS analysis, tracking and analyzing molecular behavior, while reducing photodamage during SiMS imaging in multiple focal planes, will be some of the new challenges.