Sudden sensorineural hearing loss (SSNHL) is a common condition with a rapid onset, and its worldwide frequency is increasing each year. Importantly, a significant number of patients with SSNHL do ...not respond to initial treatment, which is termed refractory sudden hearing loss (RSHL), and further treatment is not standardized in terms of type, duration, administration route, and concentration of topical steroid therapy. Dexamethasone and methylprednisolone are effective in treating RSHL, and salvage treatment typically consists of 2 weeks of steroid therapy followed by 3–6 months of follow-up. Near-continual steroid perfusion appears to be more effective than intermittent steroid injection. Furthermore, several novel therapeutic regimens have shown promising results in small-scale studies. However, the optimum treatment needs to be confirmed in larger randomized controlled trials.
Depression is a common mental illness which has brought great harm to the individuals. With recent evidence that many objective physiological signals are associated with depression, automated ...detection of depression is urgent and important for the growing concern of mental illness. We investigate the problem of classifying depression by facial expressions, which may aid in online diagnosis and rehabilitation engineering of depression. In this work, We propose a weakly supervised learning approach employing multiple instance learning (MIL) on 150 videos data from 75 depressed and 75 healthy subjects. In addition, we present a novel MIL dual-stream aggregator that considers both the instance-level and the bag-level in order to emphasize the information with symptoms. Specifically, our method named ADDMIL uses max-pooling at the instance level to capture symptom information and further integrates the contribution of each instance at the bag level using attention weights. Our method achieves 74.7% accuracy and 74.5% recall on the collected dataset, which not only improves 10.1% accuracy and 9.8% recall over the baseline but also exceeds the best accuracy result of MIL-based method by 2.1%. Our work achieves results that are comparable to the state-of-the-art methods and demonstrates that multiple instance learning has great potential for depression classification. We present for the first time a weakly supervised learning approach in the detection of depression through raw facial expressions, which may provide a new framework for other psychiatric disorders detection methods.
As a biomarker of depression, speech signal has attracted the interest of many researchers due to its characteristics of easy collection and non-invasive. However, subjects' speech variation under ...different scenes and emotional stimuli, the insufficient amount of depression speech data for deep learning, and the variable length of speech frame-level features have an impact on the recognition performance.
The above problems, this study proposes a multi-task ensemble learning method based on speaker embeddings for depression classification. First, we extract the Mel Frequency Cepstral Coefficients (MFCC), the Perceptual Linear Predictive Coefficients (PLP), and the Filter Bank (FBANK) from the out-domain dataset (CN-Celeb) and train the Resnet x-vector extractor, Time delay neural network (TDNN) x-vector extractor, and i-vector extractor. Then, we extract the corresponding speaker embeddings of fixed length from the depression speech database of the Gansu Provincial Key Laboratory of Wearable Computing. Support Vector Machine (SVM) and Random Forest (RF) are used to obtain the classification results of speaker embeddings in nine speech tasks. To make full use of the information of speech tasks with different scenes and emotions, we aggregate the classification results of nine tasks into new features and then obtain the final classification results by using Multilayer Perceptron (MLP). In order to take advantage of the complementary effects of different features, Resnet x-vectors based on different acoustic features are fused in the ensemble learning method.
Experimental results demonstrate that (1) MFCC-based Resnet x-vectors perform best among the nine speaker embeddings for depression detection; (2) interview speech is better than picture descriptions speech, and neutral stimulus is the best among the three emotional valences in the depression recognition task; (3) our multi-task ensemble learning method with MFCC-based Resnet x-vectors can effectively identify depressed patients; (4) in all cases, the combination of MFCC-based Resnet x-vectors and PLP-based Resnet x-vectors in our ensemble learning method achieves the best results, outperforming other literature studies using the depression speech database.
Our multi-task ensemble learning method with MFCC-based Resnet x-vectors can fuse the depression related information of different stimuli effectively, which provides a new approach for depression detection. The limitation of this method is that speaker embeddings extractors were pre-trained on the out-domain dataset. We will consider using the augmented in-domain dataset for pre-training to improve the depression recognition performance further.
Terpenoids have tremendous biological activities and are widely employed in food, healthcare and pharmaceutical industries. Using synthetic biology to product terpenoids from microbial cell factories ...presents a promising alternative route compared to conventional methods such as chemical synthesis or phytoextraction. The red yeast Rhodotorula mucilaginosa has been widely studied due to its natural production capacity of carotenoid and lipids, indicating a strong endogenous isoprene pathway with readily available metabolic intermediates. This study constructed several engineered strains of R. mucilaginosa with the aim of producing different terpenoids. Monoterpene α-terpineol was produced by expressing the α-terpineol synthase from Vitis vinifera. The titer of α-terpineol was further enhanced to 0.39 mg/L by overexpressing the endogenous rate-limiting gene of the MVA pathway. Overexpression of α-farnesene synthase from Malus domestica, in combination with MVA pathway rate-limiting gene resulted in significant increase in α-farnesene production, reaching a titer of 822 mg/L. The carotenoid degradation product β-ionone was produced at a titer of 0.87 mg/L by expressing the β-ionone synthase from Petunia hybrida. This study demonstrates the potential of R. mucilaginosa as a platform host for the direct biosynthesis of various terpenoids and provides insights for further development of such platforms.
•Microbial cell factories emerge as an appealing alternative to plant terpenoids.•Engineering endogenous Mevalonate pathway is an efficient method for terpenoid production.•First attempt to exploit the heterologous terpenoid biosynthetic potential of R. mucilaginosa.•Engineering precursor supply (MVA pathway) to improve the terpenoid production.
•MUC1 directly binds to JNK1 through the MUC1-CD (amino acids 1-45) region.•MUC1 increases the phosphorylation/activation of JNK1 and c-Jun under genotoxic stress.•MUC1 blocks apoptotic response of ...HCT116 cells to DNA damage via JNK1 pathway.
The MUC1 transmembrane glycoprotein is aberrantly overexpressed in diverse human carcinomas and has been shown to inhibit apoptosis induced by genotoxic agents. In the present work, we report that MUC1 binds to and activates JNK1, an important member of the mitogen-activated protein kinases (MAPK) superfamily. The physical interaction between MUC1 cytoplasmic domain (MUC1-CD) and JNK1 was established by GST-pull-down assay in vitro and co-immunoprecipitation assay in vivo. We show that MUC1 activates JNK1 and inhibits cisplatin-induced apoptosis in human colon cancer HCT116 cells. Pharmacological inhibition of JNK or knockdown of JNK significantly reduces the ability of MUC1 to inhibit cisplatin-induced apoptosis. Together, our data indicate that MUC1 can inhibit apoptosis via activating JNK1 pathway in response to genotoxic anticancer agents.
The conventional genetic screening for deafness involves 9-20 variants from four genes. This study expands screening to analyze the mutation types and frequency of hereditary deafness genes in ...Zhejiang, China, and explore the significance of in-depth deafness genetic screening in newborns.
This was a multi-centre study conducted in 5,120 newborns from 12 major hospitals in the East-West (including mountains and islands) of Zhejiang Province. Concurrent hearing and genetic screening was performed. For genetic testing, 159 variants of 22 genes were screened, including
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
, and
using next-generation sequencing. Newborns who failed to have genetic mutations or hearing screening were diagnosed audiologically at the age of 6 months.
A total of 4,893 newborns (95.57%) have passed the initial hearing screening, and 7 (0.14%) have failed in repeated screening. Of these, 446 (8.71%) newborns carried at least one genetic deafness-associated variant. High-risk pathogenic variants were found in 11 newborns (0.21%) (nine homozygotes and two compound heterozygotes), and eight of these infants have passed the hearing screening. The frequency of mutations in
,
,
,
, and
was 5.43%, 0.59%, 1.91%, 0.98%, and 0.02%, respectively. The positive rate of in-depth screening was significantly increased when compared with 20 variants in four genes of traditional testing, wherein
was increased by 97.2%,
by 21% and
by 150%. The most common mutation variants were GJB2c.235delC and SLC26A4c.919-2A > G, followed by GJB2c.299_300delAT. Homoplasmic mutation in
was the most common, including m.1555A > G, m.961T > C, m.1095T > C. All these infants have passed routine hearing screening. The positive rate of
mutation was significantly higher in newborns with high-risk factors of maternal pregnancy.
The positive rate of deafness gene mutations in the Zhejiang region is higher than that of the database, mainly in GJB2c.235delC, SLC26A4 c.919-2A > G, and m.1555A > G variants. The expanded genetic screening in the detection rate of diseasecausing variants was significantly improved. It is helpful in identifying high-risk children for follow-up intervention.
α-Terpineol is a monoterpenoid alcohol that has been widely used in the flavor, fragrance, and pharmaceutical industries because of its sensory and biological properties. However, few studies have ...focused on the microbial production of α-terpineol. The oleaginous yeast
is endowed with a natural mevalonate pathway and is a promising host in synthetic biology and biorefinery. The primary objective of this work was to engineer
for the direct biosynthesis of α-terpineol. The improvement in monoterpenoid production was achieved through the implementation of modular engineering strategies, which included the enhancement of precursor supply, blocking of downstream pathways, and disruption of competing pathways. The results of these three methods showed varying degrees of favorable outcomes in enhancing α-terpineol production. The engineered strain 5L6HE5, with competitive pathway disruption and increased substrate supply, reached the highest product titer of 1.5 mg/L, indicating that reducing lipid accumulation is an efficient method in
engineering for terpenoid synthesis. This study reveals the potential of
as a host platform for the synthesis of α-terpineol as well as other monoterpenoid compounds.
This study provides an in-depth analysis of the effects of academic mobility on higher education innovation through an empirical study on returned Chinese academics at two research universities in ...China. Based on data obtained through document analysis and semi-structured interviews with 15 academic returnees, this paper aims to examine the everyday interactions between individual returnees and their environment, with a focus on exploring how different institutional contexts affect returnees’ capacity for integration and innovation. It finds that returned academics play an important role in promoting higher education innovation in China through mobilizing their transnational capital and resources. However, their capacity to innovate is largely subject to their working environment. Evidence from the study suggests that differing institutional contexts make a substantial difference to the reintegration experiences of returnees and to their contributions to institutional changes. This paper provides a window into the changing institutional environment in China and the academic lives of returnees there. It also provides important implications for talent policy decisions.
While higher education has been considered as both an ‘engine’ for innovation and a ‘catalyst’ for sustainability development, the integration of both the ‘innovation engine’ and ‘sustainability ...catalyst’ roles is best reflected in higher education’s engagement in innovation ecosystems—the theme of this special issue, including 16 articles dealing with the topic from various perspectives. In this editorial, we outline an overarching framework about the relations between higher education and innovation ecosystem. When elaborating the framework, we provide a new definition of innovation ecosystem and identify three roles of university in innovation ecosystems, based on synthesizing relevant literature. The framework could facilitate readers to comprehend each of the collected articles and find synergy among them.
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