Enhancing the Performance of Pathological Voice Quality Assessment System Through the Attention-Mechanism Based Neural Network.

OBJECTIVE: Doctors, nowadays, primarily use auditory-perceptual evaluation, such as the grade, roughness, breathiness, asthenia, and strain scale, to evaluate voice quality and determine the treatment. However, the results predicted by individual physicians often differ, because of subjective perceptions, and diagnosis time interval, if the patient's symptoms are hard to judge. Therefore, an accurate computerized pathological voice quality assessment system will improve the quality of assessment. METHOD: This study proposes a self_attention-based system, with a deep learning technology, named self_attention-based bidirectional long-short term memory (SA BiLSTM). Different pitches [low, normal, high], and vowels [/a/, /i/, /u/], were added into the proposed model, to make it learn how professional doctors evaluate the grade, roughness, breathiness, asthenia, and strain scale, in a high dimension view. RESULTS: The experimental results showed that the proposed system provided higher performance than the baseline system. More specifically, the macro average of the F1 score, presented as decimal, was used to compare the accuracy of classification. The (G, R, and B) of the proposed system were (0.768±0.011, 0.820±0.009, and 0.815±0.009), which is higher than the baseline systems: deep neural network (0.395±0.010, 0.312±0.019, 0.321±0.014) and convolution neural network (0.421±0.052, 0.306±0.043, 0.3250±0.032) respectively. CONCLUSIONS: The proposed system, with SA BiLSTM, pitches, and vowels, provides a more accurate way to evaluate the voice. This will be helpful for clinical voice evaluations and will improve patients' benefits from voice therapy.

A Deep Learning Based Approach to Synthesize Intelligible Speech with Limited Temporal Envelope Information.

Envelope waveforms can be extracted from multiple frequency bands of a speech signal, and envelope waveforms carry important intelligibility information for human speech communication. This study aimed to investigate whether a deep learning-based model with features of temporal envelope information could synthesize an intelligible speech, and to study the effect of reducing the number (from 8 to 2 in this work) of temporal envelope information on the intelligibility of the synthesized speech. The objective evaluation metric of short-time objective intelligibility (STOI) showed that, on average, the synthesized speech of the proposed approach provided higher STOI (i.e., 0.8) scores in each test condition; and the human listening test showed that the average word correct rate of eight listeners was higher than 97.5%. These findings indicated that the proposed deep learning-based system can be a potential approach to synthesize a highly intelligible speech with limited envelope information in the future.

Enhancement of the stability of chlorophyll using chlorophyll-encapsulated polycaprolactone microparticles based on droplet microfluidics.

Chlorophyll is a valuable bioactive compound, which is used as a natural food coloring agent and a photosensitizer for photodynamic therapy because of its antioxidant properties, antimutagenic ability, and near-infrared fluorescence. However, chlorophyll is unstable when it comes to retaining its antioxidant activity, when exposed to oxygen, high temperature, or light environments. To enhance the stability of chlorophyll, a polymer encapsulation method was proposed. Polycaprolactone (PCL) was employed to encapsulate the chlorophyll, and the particles size of the composites was controlled through droplet microfluidics. The composites (chlorophyll-encapsulated PCL particles) were characterized through UV-VIS spectrometry, SEM, optical microscopy, and light exposure. The particles were spherical, with diameters adjustable from 68 to 247 µm. Additionally, the chlorophyll-encapsulated PCL particles exhibited considerably prolonged chlorophyll stability. The solid microparticle is more convenient for storage and transportation, and have great potential for application in the food industry.

Gli2 modulates cell cycle re-entry through autophagy-mediated regulation of the length of primary cilia.

The primary cilium is a tiny cell protrusion known to transduce key extracellular signals, including those of the sonic hedgehog pathway, which activates Gli transcription factors for various cellular functions. To understand the significance of the Gli2 transcription factor in fibroblasts, we establish a Gli2-knockout NIH3T3 cell line by CRISPR/Cas9 technology. Surprisingly, NIH3T3 fibroblasts lacking Gli2 expression through gene knockout or RNA interference possess longer primary cilia after stimulation of ciliogenesis by serum starvation. This lengthening of primary cilia is associated with enhanced autophagy-mediated Ofd1 degradation, and can be reversed by pharmacological and genetic inhibition of autophagy. Meanwhile, flow cytometry reveals that Gli2-/- NIH3T3 fibroblasts exhibit a delay in cell cycle re-entry after serum re-stimulation. Ablation of their primary cilia through Kif3a knockdown rescues the delay in cell cycle re-entry. These results suggest that Gli2 plays an unexpected role in cell cycle re-entry through an autophagy-mediated regulation on ciliary length in fibroblasts.

Core-shell structure microcapsules with dual pH-responsive drug release function.

We report dual pH-responsive microcapsules manufactured by combining electrostatic droplets (ESD) and microfluidic droplets (MFD) techniques to produce monodisperse core (alginate)-shell (chitosan) structure with dual pH-responsive drug release function. The fabricated core-shell microcapsules were size controllable by tuning the synthesis parameters of the ESD and MFD systems, and were responsive in both acidic and alkaline environment, We used two model drugs (ampicillin loaded in the chitosan shell and diclofenac loaded in the alginate core) for drug delivery study. The results show that core-shell structure microcapsules have better drug release efficiency than respective core or shell particles. A biocompatibility test showed that the core-shell structure microcapsules presented positive cell viability (above 80%) when evaluated by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The results indicate that the synthesized core-shell microcapsules were a potential candidate of dual-drug carriers.