Mixed-Phoneme BERT: Improving BERT with Mixed Phoneme and Sup-Phoneme Representations for Text to Speech

Recently, leveraging BERT pre-training to improve the phoneme encoder in text to speech (TTS) has drawn increasing attention. However, the works apply pre-training with character-based units to enhance the TTS phoneme encoder, which is inconsistent with the TTS fine-tuning that takes phonemes as input. Pre-training only with phonemes as input can alleviate the input mismatch but lack the ability to model rich representations and semantic information due to limited phoneme vocabulary. In this paper, we propose MixedPhoneme BERT, a novel variant of the BERT model that uses mixed phoneme and sup-phoneme representations to enhance the learning capability. Specifically, we merge the adjacent phonemes into sup-phonemes and combine the phoneme sequence and the merged sup-phoneme sequence as the model input, which can enhance the model capacity to learn rich contextual representations. Experiment results demonstrate that our proposed Mixed-Phoneme BERT significantly improves the TTS performance with 0.30 CMOS gain compared with the FastSpeech 2 baseline. The Mixed-Phoneme BERT achieves 3x inference speedup and similar voice quality to the previous TTS pre-trained model PnG BERTComment: submitted to interspeech 202

In Situ and Operando Investigation of the Dynamic Morphological and Phase Changes of Selenium-doped Germanium Electrode during (De)Lithiation Processes

To understand the effect of selenium doping on the good cycling performance and rate capability of a Ge0.9Se0.1 electrode, the dynamic morphological and phase changes of the Ge0.9Se0.1 electrode were investigated by synchrotron-based operando transmission X-ray microscopy (TXM) imaging, X-ray diffraction (XRD), and X-ray absorption spectroscopy (XAS). The TXM results show that the Ge0.9Se0.1 particle retains its original shape after a large volume change induced by (de)lithiation and undergoes a more sudden morphological and optical density change than pure Ge. The difference between Ge0.9Se0.1 and Ge is attributed to a super-ionically conductive Li–Se–Ge network formed inside Ge0.9Se0.1 particles, which contributes to fast Li-ion pathways into the particle and nano-structuring of Ge as well as buffering the volume change of Ge. The XRD and XAS results confirm the formation of a Li–Se–Ge network and reveal that the Li–Se–Ge phase forms during the early stages of lithiation and is an inactive phase. The Li–Se–Ge network also can suppress the formation of the crystalline Li15Ge4 phase. These in situ and operando results reveal the effect of the in situ formed, super-ionically conductive, and inactive network on the cycling performance of Li-ion batteries and shed light on the design of high capacity electrode materials

The Value of Tumor Infiltrating Lymphocytes (TILs) for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer: A Systematic Review and Meta-Analysis

<div><p>Background</p><p>We carried out a systematic review and meta-analysis to evaluate the predictive roles of tumor infiltrating lymphocytes (TILs) in response to neoadjuvant chemotherapy (NAC) in breast cancer.</p><p>Method</p><p>A PubMed and Web of Science literature search was designed. Random or fixed effect models were adopted to estimate the summary odds ratio (OR). Heterogeneity and sensitivity analyses were performed to explore heterogeneity among studies and to assess the effects of study quality. Publication bias was evaluated using a funnel plot, Egger's test and Begg's test. We included studies where the predictive significance of TILs, and/or TILs subset on the pathologic complete response (pCR) were determined in NAC of breast cancer.</p><p>Results</p><p>A total of 13 published studies (including 3251 patients) were eligible. In pooled analysis, the detection of higher TILs numbers in pre-treatment biopsy was correlated with better pCR to NAC (OR = 3.93, 95% CI, 3.26–4.73). Moreover, TILs predicted higher pCR rates in triple negative (OR = 2.49, 95% CI: 1.61–3.83), HER2 positive (OR = 5.05, 95% CI: 2.86–8.92) breast cancer, but not in estrogen receptor (ER) positive (OR = 6.21, 95%CI: 0.86–45.15) patients. In multivariate analysis, TILs were still an independent marker for high pCR rate (OR = 1.41, 95% CI: 1.19–1.66). For TILs subset, higher levels of CD8+ and FOXP3+ T-lymphocytes in pre-treatment biopsy respectively predicted better pathological response to NAC (OR = 6.44, 95% CI: 2.52–16.46; OR = 2.94, 95% CI: 1.05–8.26). Only FOXP3+ lymphocytes in post-NAC breast tissue were a predictive marker for low pCR rate in univariate (OR = 0.41, 95% CI: 0.21–0.80) and multivariate (OR = 0.36, 95% CI: 0.13–0.95) analysis.</p><p>Conclusion</p><p>Higher TILs levels in pre-treatment biopsy indicated higher pCR rates for NAC. TILs subset played different roles in predicting response to NAC.</p></div

Forest plots from the random-effect meta-analysis of the efficacy of TIL subset on NAC response in pre-treatment biopsy in multivariate way.

<p>The width of horizontal line represents 95% CI of the individual studies, and the grey boxes represent the weight of each study. The diamond represents the overall summary estimate. The unbroken vertical line was set at the null value (HR = 1.0).</p

Forest plots from the fixed-effect meta-analysis of the efficacy of TILs on the NAC response stratified by infiltration locations (A) and different cutoff values (B).

<p>The width of horizontal line represents 95% CI of the individual studies, and the grey boxes represent the weight of each study. The diamond represents the overall summary estimate. The unbroken vertical line was set at the null value (HR = 1.0). Abbreviations: LPBC, lymphocyte-predominant breast cancer; TILs, tumor infiltrating lymphocytes.</p

Funnel plot for publication bias in the pooled pCR analysis based on TIL status (A) and TILs subset before (B) treatment.

<p>Funnel plot for publication bias in the pooled pCR analysis based on TIL status (A) and TILs subset before (B) treatment.</p

Forest plots from the fixed-effect meta-analysis of the efficacy of TILs on the NAC response stratified by different subtypes.

<p>The width of horizontal line represents 95% CI of the individual studies, and the grey boxes represent the weight of each study. The diamond represents the overall summary estimate. The unbroken vertical line was set at the null value (HR = 1.0). Abbreviations: TNBC, triple negative breast cancer; HER2, human epithelial growth factor receptor 2; ER, estrogen receptor.</p

Forest plots from the random-effect meta-analysis of the efficacy of TILs on the NAC response stratified by infiltration locations in multivariate way.

<p>The width of horizontal line represents 95% CI of the individual studies, and the grey boxes represent the weight of each study. The diamond represents the overall summary estimate. The unbroken vertical line was set at the null value (HR = 1.0).</p

Baseline Characteristics of Included Studies.

<p>Abbreviations: pts, patients; IHC, immunohistochemistry; HE, staining Hematoxylin-eosin staining; FOXP3, regulatory T-lymphocytes expressing forkhead box P 3 protein; NAC, neoadjuvant chemotherapy; CEF, cyclophosphamide/epirubicin/fluorouracil; CEX, epirubicin/cyclophosphamide/capecitabine; DC, docetaxel/carboplatin; EC, epirubicin/cyclophosphamide; EC-T, epirubicin/cyclophosphamide-taxane; CEF-T, cyclophosphamide/epirubicin/fluorouracil-taxane;T AC, docetaxel/doxorubicin/cyclophosphamide; NX, vinorelbine/capecitabine; TET, docetaxel-docetaxel/epirubicin; AC, doxorubicin/cyclophosphamide; AC-T, doxorubicin/cyclophosphamide-taxane; AD, doxorubicin/docetaxel; AT, doxorubicin/taxane; EC-TX, epirubicin/cyclophosphamide-docetaxel/capecitabine; EC-T-X, epirubicin/cyclophosphamide-docetaxel-capecitabine; PM, paclitaxle/non-pegylated liposomal doxorubicin; PMCb, paclitaxle/non-pegylated liposomal doxorubicin/carboplatin; H, trastuzumab; Bev, bevacizumab; L, lapatinib; EVE, everolimus; IS =  Intratumoral sites; SS =  stromal sites;BS, both sites;10% INC, 10 incr<b>em</b>ent</p><p>a, GeparDuo.</p><p><b>b</b>, GeparTrio.</p><p>Baseline Characteristics of Included Studies.</p