BanglaSER: A speech emotion recognition dataset for the Bangla language.

The speech emotion recognition system determines a speaker's emotional state by analyzing his/her speech audio signal. It is an essential at the same time a challenging task in human-computer interaction systems and is one of the most demanding areas of research using artificial intelligence and deep machine learning architectures. Despite being the world's seventh most widely spoken language, Bangla is still classified as one of the low-resource languages for speech emotion recognition tasks because of inadequate availability of data. There is an apparent lack of speech emotion recognition dataset to perform this type of research in Bangla language. This article presents a Bangla language-based emotional speech-audio recognition dataset to address this problem. BanglaSER is a Bangla language-based speech emotion recognition dataset. It consists of speech-audio data of 34 participating speakers from diverse age groups between 19 and 47 years, with a balanced 17 male and 17 female nonprofessional participating actors. This dataset contains 1467 Bangla speech-audio recordings of five rudimentary human emotional states, namely angry, happy, neutral, sad, and surprise. Three trials are conducted for each emotional state. Hence, the total number of recordings involves 3 statements × 3 repetitions × 4 emotional states (angry, happy, sad, and surprise) × 34 participating speakers = 1224 recordings + 3 statements × 3 repetitions × 1 emotional state (neutral) × 27 participating speakers = 243 recordings, resulting in a total number of recordings of 1467. BanglaSER dataset is created by recording speech-audios through smartphones, and laptops, having a balanced number of recordings in each category with evenly distributed participating male and female actors, and would serve as an essential training dataset for the Bangla speech emotion recognition model in terms of generalization. BanglaSER is compatible with various deep learning architectures such as Convolutional neural networks, Long short-term memory, Gated recurrent unit, Transformer, etc. The dataset is available at https://data.mendeley.com/datasets/t9h6p943xy/5 and can be used for research purposes.

Hyperactivation of nuclear receptor coactivators induces PERK-dependent cell death.

Nuclear receptor coactivators (NCOAs) function as coactivators for nuclear receptors as well as several other transcription factors and potentiate their transcriptional activity. NCOAs play an important role in biology of hormone-dependent and -independent cancers. MCB-613 is a recently described, small molecule stimulator of NCOAs and anti-neoplastic compound that leads to the death of tumour cells due to increased cellular stress. In the present study we investigated the molecular mechanism of MCB-613-induced cell death. We report that absence of NCOA3 leads to compromised activation of PERK signalling pathway during unfolded protein response (UPR). We found that chemical and genetic inhibition of NCOA3 attenuated the expression of PERK at mRNA and protein level. We show that loss of NCOA3 renders cells hypersensitive to UPR induced cell death. Our results show that MCB-613 induced cell death is attenuated in NCOA3 knockout HeLa cells and MCB-613 leads to enhanced PERK signalling in wild-type HeLa cells. The knockdown of PERK provides resistance to MCB-613 mediated cell death while knockdown of XBP1 and ATF6 have no such effect. Our results suggest that hyperstimulation of NCOA3 by MCB-613 induces cell death by evoking constitutive PERK signalling. Taken together our results point to NCOA3 as an important determinant in regulating cell fate during ER stress, with too little and too much NCOA3 both producing deleterious effects.

Immunomodulatory effects of natural polysaccharides assessed in human whole blood culture and THP-1 cells show greater sensitivity of whole blood culture.

Immunomodulatory drugs are available to maintain immune homeostasis but some have undesirable side effects. Six oligo- and poly-saccharides were assessed for their pro- and anti-inflammatory responses in two in vitro model systems, the monocytic THP-1 cell line and human whole blood cultures (HWBC). The compounds were first characterised for their molecular mass and physical properties. Following incubation with lipopolysaccharide (LPS) or the compounds, cytokine and chemokine secretion was assayed in both models and intracellular TNF-α was measured by flow cytometry in HWBC cell sub-populations. LPS, inulin, galacturonan, heteroglycan and fucoidan demonstrated pro-inflammatory properties and intracellular TNF-α expression was increased in the monocytes of HWBC. Mannan and xyloglucan did not elicit any significant responses. Inulin induced maximum cytokine secretion and heteroglycan induced maximum chemokine secretion in HWBC. This study emphasises the potential of inulin and heteroglycan as potential immunomodulatory therapeutics and that HWBC had a greater and more varied response in comparison to THP-1 cells.

The Promise of Mesenchymal Stem Cell Therapy for Diabetic Kidney Disease.

Diabetes mellitus (DM) commonly leads to progressive chronic kidney disease despite current best medical practice. The pathogenesis of diabetic kidney disease (DKD) involves a complex network of primary and secondary mechanisms with both intra-renal and systemic components. Apart from inhibition of the renin angiotensin aldosterone system, targeting individual pathogenic mediators with drug therapy has not, thus far, been proven to have high clinical value. Stem or progenitor cell therapies offer an alternative strategy for modulating complex disease processes through suppressing multiple pathogenic pathways and promoting pro-regenerative mechanisms. Mesenchymal stem cells (MSCs) have shown particular promise based on their accessibility from adult tissues and their diverse mechanisms of action including secretion of paracrine anti-inflammatory and cyto-protective factors. In this review, the progress toward clinical translation of MSC therapy for DKD is critically evaluated. Results from animal models suggest distinct potential for systemic MSC infusion to favourably modulate DKD progression. However, only a few early phase clinical trials have been initiated and efficacy in humans remains to be proven. Key knowledge gaps and research opportunities exist in this field. These include the need to gain greater understanding of in vivo mechanism of action, to identify quantifiable biomarkers of response to therapy and to define the optimal source, dose and timing of MSC administration. Given the rising prevalence of DM and DKD worldwide, continued progress toward harnessing the inherent regenerative functions of MSCs and other progenitor cells for even a subset of those affected has potential for profound societal benefits.