50 research outputs found
Sampling-based speech parameter generation using moment-matching networks
This paper presents sampling-based speech parameter generation using
moment-matching networks for Deep Neural Network (DNN)-based speech synthesis.
Although people never produce exactly the same speech even if we try to express
the same linguistic and para-linguistic information, typical statistical speech
synthesis produces completely the same speech, i.e., there is no
inter-utterance variation in synthetic speech. To give synthetic speech natural
inter-utterance variation, this paper builds DNN acoustic models that make it
possible to randomly sample speech parameters. The DNNs are trained so that
they make the moments of generated speech parameters close to those of natural
speech parameters. Since the variation of speech parameters is compressed into
a low-dimensional simple prior noise vector, our algorithm has lower
computation cost than direct sampling of speech parameters. As the first step
towards generating synthetic speech that has natural inter-utterance variation,
this paper investigates whether or not the proposed sampling-based generation
deteriorates synthetic speech quality. In evaluation, we compare speech quality
of conventional maximum likelihood-based generation and proposed sampling-based
generation. The result demonstrates the proposed generation causes no
degradation in speech quality.Comment: Submitted to INTERSPEECH 201
UTMOS: UTokyo-SaruLab System for VoiceMOS Challenge 2022
We present the UTokyo-SaruLab mean opinion score (MOS) prediction system
submitted to VoiceMOS Challenge 2022. The challenge is to predict the MOS
values of speech samples collected from previous Blizzard Challenges and Voice
Conversion Challenges for two tracks: a main track for in-domain prediction and
an out-of-domain (OOD) track for which there is less labeled data from
different listening tests. Our system is based on ensemble learning of strong
and weak learners. Strong learners incorporate several improvements to the
previous fine-tuning models of self-supervised learning (SSL) models, while
weak learners use basic machine-learning methods to predict scores from SSL
features. In the Challenge, our system had the highest score on several metrics
for both the main and OOD tracks. In addition, we conducted ablation studies to
investigate the effectiveness of our proposed methods.Comment: Submitted to INTERSPEECH 202
Upregulation of anti-apoptotic factors in upper motor neurons after spinal cord injury in adult zebrafish
Unlike mammals, fish motor function can recover within 6-8 weeks after spinal cord injury (SCI). The motor function of zebrafish is regulated by dual control; the upper motor neurons of the brainstem and motor neurons of the spinal cord. In this study, we aimed to investigate the framework behind the regeneration of upper motor neurons in adult zebrafish after SCI. In particular, we investigated the cell survival of axotomized upper motor neurons and its molecular machinery in zebrafish brain. As representative nuclei of upper motor neurons, we retrogradely labeled neurons in the nucleus of medial longitudinal fasciculus (NMLF) and the intermediate reticular formation (IMRF) using a tracer injected into the lesion site of the spinal cord. Four to eight neurons in each thin sections of the area of NMLF and IMRF were successfully traced at least 1-15 days after SCI. TUNEL staining and BrdU labeling assay revealed that there was no apoptosis or cell proliferation in the axotomized neurons of the brainstem at various time points after SCI. In contrast, axotomized neurons labeled with a neurotracer showed increased expression of anti-apoptotic factors, such as Bcl-2 and phospho-Akt (p-Akt), at 1-6 days after SCI. Such a rapid increase of Bcl-2 and p-Akt protein levels after SCI was quantitatively confirmed by western blot analysis. These data strongly indicate that upper motor neurons in the NMLF and IMRF can survive and regrow their axons into the spinal cord through the rapid activation of anti-apoptotic molecules after SCI. The regrowing axons from upper motor neurons reached the lesion site at 10-15 days and then crossed at 4-6 weeks after SCI. These long-distance descending axons from originally axotomized neurons have a major role in restoration of motor function after SCI. © 2012 Elsevier Ltd. All rights reserved.Thesis of Kazuhiro Ogai / 大貝 和裕 博士論文 金沢大学医薬保健学総合研究科(保健学専攻
Upregulation of Leukemia Inhibitory Factor (LIF) during the Early Stage of Optic Nerve Regeneration in Zebrafish.
Fish retinal ganglion cells (RGCs) can regenerate their axons after optic nerve injury, whereas mammalian RGCs normally fail to do so. Interleukin 6 (IL-6)-type cytokines are involved in cell differentiation, proliferation, survival, and axon regrowth; thus, they may play a role in the regeneration of zebrafish RGCs after injury. In this study, we assessed the expression of IL-6-type cytokines and found that one of them, leukemia inhibitory factor (LIF), is upregulated in zebrafish RGCs at 3 days post-injury (dpi). We then demonstrated the activation of signal transducer and activator of transcription 3 (STAT3), a downstream target of LIF, at 3–5 dpi. To determine the function of LIF, we performed a LIF knockdown experiment using LIF-specific antisense morpholino oligonucleotides (LIF MOs). LIF MOs, which were introduced into zebrafish RGCs via a severed optic nerve, reduced the expression of LIF and abrogated the activation of STAT3 in RGCs after injury. These results suggest that upregulated LIF drives Janus kinase (Jak)/STAT3 signaling in zebrafish RGCs after nerve injury. In addition, the LIF knockdown impaired axon sprouting in retinal explant culture in vitro; reduced the expression of a regeneration-associated molecule, growth-associated protein 43 (GAP-43); and delayed functional recovery after optic nerve injury in vivo. In this study, we comprehensively demonstrate the beneficial role of LIF in optic nerve regeneration and functional recovery in adult zebrafish
Associations Between Metal Levels in Whole Blood and IgE Concentrations in Pregnant Women Based on Data From the Japan Environment and Children’s Study
Background: Metal exposures could possibly affect allergic responses in pregnant women, although no studies have yet shown a clear relationship between the two, and such exposures might also affect the development of allergic diseases in children.
Methods: We investigated the relationship between metal concentrations in whole blood and immunoglobulin E (IgE; total and specific) in 14,408 pregnant women who participated in the Japan Environment and Children’s Study. The subjects submitted self-administered questionnaires, and blood samples were collected from them twice, specifically, during the first trimester and again during the second=third trimester. Concentrations of the metals Cd, Pb, Hg, Se, and Mn, as well as serum total and allergen-specific IgEs for egg white, house dust-mites (HDM), Japanese cedar pollen (JCP), animal dander, and moth, were measured. Allergen-specific IgE(s) were divided based on concentrations <0.35 or ≥0.35UA=mL, and the metal levels were divided into quartiles.
Results: Multivariable logistic regression analysis showed that there was a significant negative correlation between HDM- and animal dander-specific IgEs and Hg and Mn concentrations. Conversely, there was a significant positive relationship between JCP-specific IgE and Hg and Se concentrations.
Conclusions: Metal exposures may be related to both increases and decreases in allergen-specific IgEs in pregnant women.This work was supported by the Ministry of the Environment, Japan.Supplementary data related to this article can be found at https://doi.org/10.2188/jea.JE20180098
Clinical implication of HLA class I expression in breast cancer
<p>Abstract</p> <p>Background</p> <p>Human leukocyte antigen (HLA)-class I molecules on tumor cells have been regarded as crucial sites where cytotoxic T lymphocytes (CTL) can recognize tumor-specific antigens and are strongly associated with anti-tumor activity. However, the clinical impact of HLA class I expression in breast cancer has not been clarified.</p> <p>Methods</p> <p>A total of 212 breast cancer patients who received curative surgery from 1993 to 2003 were enrolled in the current study. HLA class I expression was examined immunohistochemically using an anti-HLA class I monoclonal antibody. The correlation between HLA class I positivity and clinical factors was analyzed.</p> <p>Results</p> <p>The downregulation of HLA class I expression in breast cancer was observed in 69 patients (32.5%). HLA class I downregulation was significantly associated with nodal involvement (p < 0.05), TNM stage (p < 0.05), lymphatic invasion (p < 0.01), and venous invasion (p < 0.05). Patients with preserved HLA class I had significantly better disease-free interval (DFI) than those with loss of HLA class I (p < 0.05). However, in multivariable analysis, HLA class I was not selected as one of the independent prognostic factors of disease-free interval.</p> <p>Conclusion</p> <p>The examination of HLA class I expression is useful for the prediction of tumor progression and recurrent risk of breast cancer via the antitumor immune system.</p