For modeling human intelligence, understanding emotional intelligence as well as verbal and mathematical intelligence is an important and challenging issue. In affective and personality computing, it has been reported that not only visual and audio signals but also biosignals are useful for estimating emotions and personality. Biosignals are expected to provide additional and less biased information in implicit assessment, but estimation performance can degrade if there are physiological individual differences. In this paper, considering individual physiological differences as a covariate shift, we aimed to improve the performance results in biosignal-based emotion and personality estimations. For this purpose, we constructed importance-weighted logistic regression (IW-LR) and importance-weighted support vector machine (IW-SVM), which mitigate the accuracy degradation due to physiological individual differences in the training data, and compared them with conventional LR and linear SVM (L-SVM) for estimation performance. As a result, most of the IW models outperform conventional models based on electrocardiogram (ECG) and galvanic skin response (GSR) features in emotion estimation. In the personality estimation, the IW method improves the macroaveraged F1-score for all SVM models. The best performing model (GSR model) outperformed the model with the best previously reported macroaveraged F1-score by 1.9% in personality estimation. These results indicate that importance weighting in machine learning models can reduce the effects of individual physiological differences in peripheral physiological responses and contribute to the proposal of a new model for emotion and personality estimations based on biosignals.

Recently developed Bidirectional Encoder Representations from Transformers (BERT) outperforms the state-of-the-art in many natural language processing tasks in English. Although contextual information is known to be useful for dialog act classification, fine-tuning BERT with contextual information has not been investigated, especially in head final languages such as Japanese. This paper investigates whether BERT with contextual information performs well on dialog act classification in Japanese open-domain conversation. In our proposed model, not only the utterance itself but also the information about previous utterances and turn-taking are taken into account. Results of experiments on a Japanese dialog corpus showed that the incorporation of the contextual information improved the Fl-score by 6.7 points.

In human-agent interactions, it is necessary for the systems to identify the current emotional state of the user to adapt their dialogue strategies. Nevertheless, this task is challenging because the current emotional states are not always expressed in a natural setting and change dynamically. Recent accumulated evidence has indicated the usefulness of physiological modalities to realize emotion recognition. However, the contribution of the time series physiological signals in human-agent interaction during a dialogue has not been extensively investigated. This paper presents a machine learning model based on physiological signals to estimate a user's sentiment at every exchange during a dialogue. Using a wearable sensing device, the time series physiological data including the electrodermal activity (EDA) and heart rate in addition to acoustic and visual information during a dialogue were collected. The sentiment labels were annotated by the participants themselves and by external human coders for each exchange consisting of a pair of system and participant utterances. The experimental results showed that a multimodal deep neural network (DNN) model combined with the EDA and visual features achieved an accuracy of 63.2%. In general, this task is challenging, as indicated by the accuracy of 63.0% attained by the external coders. The analysis of the sentiment estimation results for each individual indicated that the human coders often wrongly estimated the negative sentiment labels, and in this case, the performance of the DNN model was higher than that of the human coders. These results indicate that physiological signals can help in detecting the implicit aspects of negative sentiments, which are acoustically/visually indistinguishable.

An interview for a job recruiting process requires applicants to demonstrate their communication skills. Interviewees sometimes become nervous about the interview because interviewees themselves do not know their assessed score. This study investigates the relationship between the communication skill (CS) and the self-efficacy level (SE) of interviewees through multimodal modeling. We also clarify the difference between effective features in the prediction of CS and SE labels. For this purpose, we collect a novel multimodal job interview data corpus by using a job interview agent system where users experience the interview using a virtual reality head-mounted display (VR-HMD). The data corpus includes annotations of CS by third-party experts and SE annotations by the interviewees. The data corpus also includes various kinds of multimodal data, including audio, biological (i.e., physiological), gaze, and language data. We present two types of regression models, linear regression and sequential-based regression models, to predict CS, SE, and the gap (GA) between skill and self-efficacy. Finally, we report that the model with acoustic, gaze, and linguistic features has the best regression accuracy in CS prediction (correlation coefficient r = 0.637). Furthermore, the regression model with biological features achieves the best accuracy in SE prediction (r = 0.330).

Regulation of mitochondrial respiration and morphology is important for maintaining steady-state hematopoiesis, yet few studies have comparatively evaluated the effects of abnormal mitochondrial respiration and dynamics on blood-cell differentiation in isolation or combination. This study sought to explore these effects in mouse models with one or both of the following deficits: a large-scale deletion of mitochondrial DNA (ΔmtDNA), accumulated to varying extents, or knockout of the mitochondrial fission factor Drp1. Each deficit was found to independently provoke anemia but with clearly different manifestations. The former showed signs of aberrant respiration, analogous to Pearson syndrome, while the latter showed signs of abnormal mitochondrial dynamics and was associated with changes in the relative proportions of leukocyte lineages. Combining these deficits acted to amplify abnormal iron metabolism in erythropoiesis, exacerbating anemia in an additive manner. Our results indicate that mitochondrial respiration and dynamics play distinct roles in different sets of processes and cell lineages in hematopoietic differentiation.

The present study investigated whether combined ingestion of green tea catechins (GTC) and monoglucosyl hesperidin (GHES) influences the pharmacokinetic parameters of polyphenols and serum triglycerides (TG). We conducted 2 randomized, controlled trials. Study 1: 8 healthy male subjects participated in a crossover study in which they ingested a test beverage containing GHES (0, 84, 168, or 336 mg GHES) with GTC, or 336 mg GHES without GTC. After ingestion, the pharmacokinetic changes in plasma hesperetin (HEP) and catechins were measured. Study 2: 36 healthy male and female subjects (mean age, 53 ± 2 years; mean BMI, 25.2 ± 0.5 kg m-2) were recruited for a double-blind, placebo-controlled study in which they ingested a test beverage containing 165 mg GHES with 387 mg GTC or a placebo beverage daily for 4 weeks. Fasting serum TG and other lipids and glucose metabolites were analyzed. Study 1 showed that the pharmacokinetics of HEP did not differ significantly between the 336 mg GHES without GTC treatment and the 168 mg GHES with GTC treatment. Study 2 showed that continuous ingestion of 165 mg GHES and 387 mg GTC for 4 weeks significantly decreased fasting serum TG levels compared with baseline values (change in TG, -30 ± 13 mg dl-1, P = 0.040) in the intention-to-treat analysis. In conclusion, our findings suggest that GTC affects the oral bioavailability of GHES, and combined ingestion of low doses of GHES with GTC effectively improves fasting TG levels.

PURPOSE: It has been reported that tea catechins increase energy metabolism, but their effect on resting metabolic rate (RMR) remains under debate. This study aimed to examine the effect of repeated intake of tea catechins on energy metabolism in the resting state in middle-aged men and women. METHODS: A total of 30 middle-aged men and women [13 women; age (mean ± SD) 52 ± 4 years; BMI 21.9 ± 2.2 kg/m2] were recruited. A randomized, double-blind, crossover study was conducted using a tea catechin-enriched beverage (611 mg catechins, 88 mg caffeine) and a placebo beverage (0 mg catechins, 81 mg caffeine) as test beverages. After 2 weeks of continuous test beverage intake, fasting RMR and energy expenditure (EE) after the ingestion of test beverage were measured. Measurements of forehead temperature (proxy for core temperature) and skin temperature were also obtained simultaneously. RESULTS: Among participants who underwent measurements, 26 (10 women; mean age 52 ± 4 years; mean BMI 22.1 ± 2.1 kg/m2) were analyzed. The EE increased significantly after ingestion of the tea catechin beverage compared with the placebo beverage (placebo treatment: 5502 ± 757 kJ/day; catechin treatment: 5598 ± 800 kJ/day; P = 0.041). No between-treatment differences in fasting RMR or the respiratory quotient were detected. In addition, the forehead and skin temperature did not differ significantly between the placebo and catechin treatments. CONCLUSION: This study revealed that continuous intake of tea catechins with caffeine for 2 weeks significantly increased EE after ingestion of the tea catechin but not fasting RMR in middle-aged men and women. CLINICAL TRIAL REGISTRY NUMBER AND WEBSITE: This trial was registered at www.umin.ac.jp/ctr/ as UMIN000025810 and UMIN000025811.

Chlorogenic acids (CGAs) reduce blood pressure and body fat, and enhance fat metabolism. In roasted coffee, CGAs exist together with the oxidant component hydroxyhydroquinone (HHQ). HHQ counteracts the antihypertensive effects of CGA, but its effects on CGA-induced fat oxidation (FOX) are unknown. Here we assessed the effects of CGA-enriched and HHQ-reduced coffee on FOX. Fifteen healthy male volunteers (age: 38 ± 8 years (mean ± SD); BMI: 22.4 ± 1.5 kg/m²) participated in this crossover study. Subjects consumed the test beverage (coffee) containing the same amount of CGA with HHQ (CGA-HHQ(+)) or without HHQ (CGA-HHQ(−)) for four weeks. Postprandial FOX and the ratio of the biological antioxidant potential (BAP) to the derivatives of reactive oxygen metabolites (d-ROMs) as an indicator of oxidative stress were assessed. After the four-week intervention, postprandial FOX and the postprandial BAP/d-ROMs ratio were significantly higher in the CGA-HHQ(−) group compared with the CGA-HHQ(+) group (4 ± 23 mg/min, group effect: p = 0.040; 0.27 ± 0.74, group effect: p = 0.007, respectively). In conclusion, reducing the amount of HHQ facilitated the postprandial FOX effects of CGA in coffee. Our findings also suggest that the mechanism underlying the inhibition of FOX by HHQ is related to postprandial oxidative stress.

Mitochondria are dynamic organelles, and their fusion and fission regulate cellular signaling, development, and mitochondrial homeostasis, including mitochondrial DNA (mtDNA) distribution. Cardiac myocytes have a specialized cytoplasmic structure where large mitochondria are aligned into tightly packed myofibril bundles; however, recent studies have revealed that mitochondrial dynamics also plays an important role in the formation and maintenance of cardiomyocytes. Here, we precisely analyzed the role of mitochondrial fission in vivo. The mitochondrial fission GTPase, Drp1, is highly expressed in the developing neonatal heart, and muscle-specific Drp1 knockout (Drp1-KO) mice showed neonatal lethality due to dilated cardiomyopathy. The Drp1 ablation in heart and primary cultured cardiomyocytes resulted in severe mtDNA nucleoid clustering and led to mosaic deficiency of mitochondrial respiration. The functional and structural alteration of mitochondria also led to immature myofibril assembly and defective cardiomyocyte hypertrophy. Thus, the dynamics of mtDNA nucleoids regulated by mitochondrial fission is required for neonatal cardiomyocyte development by promoting homogeneous distribution of active mitochondria throughout the cardiomyocytes.

Studies in patients have suggested that the clinical phenotypes of some mitochondrial diseases might transit from one disease to another (e.g., Pearson syndrome [PS] to Kearns-Sayre syndrome) in single individuals carrying mitochondrial (mt) DNA with a common deletion (ΔmtDNA), but there is no direct experimental evidence for this. To determine whether ΔmtDNA has the pathologic potential to induce multiple mitochondrial disease phenotypes, we used trans-mitochondrial mice with a heteroplasmic state of wild-type mtDNA and ΔmtDNA (mito-miceΔ). Late-stage embryos carrying ≥50% ΔmtDNA showed abnormal hematopoiesis and iron metabolism in livers that were partly similar to PS (PS-like phenotypes), although they did not express sideroblastic anemia that is a typical symptom of PS. More than half of the neonates with PS-like phenotypes died by 1 month after birth, whereas the rest showed a decrease of ΔmtDNA load in the affected tissues, peripheral blood and liver, and they recovered from PS-like phenotypes. The proportion of ΔmtDNA in various tissues of the surviving mito-miceΔ increased with time, and Kearns-Sayre syndrome-like phenotypes were expressed when the proportion of mtDNA in various tissues reached >70-80%. Our model mouse study clearly showed that a single ΔmtDNA was responsible for at least two distinct disease phenotypes at different ages and suggested that the level and dynamics of mtDNA load in affected tissues would be important for the onset and transition of mitochondrial disease phenotypes in mice.

Mitochondrial DNA (mtDNA) mutator mice are proposed to express premature aging phenotypes including kyphosis and hair loss (alopecia) due to their carrying a nuclear-encoded mtDNA polymerase with a defective proofreading function, which causes accelerated accumulation of random mutations in mtDNA, resulting in expression of respiration defects. On the contrary, transmitochondrial mito-miceΔ carrying mtDNA with a large-scale deletion mutation (ΔmtDNA) also express respiration defects, but not express premature aging phenotypes. Here, we resolved this discrepancy by generating mtDNA mutator mice sharing the same C57BL/6J (B6J) nuclear background with that of mito-miceΔ. Expression patterns of premature aging phenotypes are very close, when we compared between homozygous mtDNA mutator mice carrying a B6J nuclear background and selected mito-miceΔ only carrying predominant amounts of ΔmtDNA, in their expression of significant respiration defects, kyphosis, and a short lifespan, but not the alopecia. Therefore, the apparent discrepancy in the presence and absence of premature aging phenotypes in mtDNA mutator mice and mito-miceΔ, respectively, is partly the result of differences in the nuclear background of mtDNA mutator mice and of the broad range of ΔmtDNA proportions of mito-miceΔ used in previous studies. We also provided direct evidence that mtDNA abnormalities in homozygous mtDNA mutator mice are responsible for respiration defects by demonstrating the co-transfer of mtDNA and respiration defects from mtDNA mutator mice into mtDNA-less (ρ(0)) mouse cells. Moreover, heterozygous mtDNA mutator mice had a normal lifespan, but frequently developed B-cell lymphoma, suggesting that the mtDNA abnormalities in heterozygous mutator mice are not sufficient to induce a short lifespan and aging phenotypes, but are able to contribute to the B-cell lymphoma development during their prolonged lifespan.