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Cochlear hair cells are the sensory cells responsible for transduction of acoustic signals. In mammals, damaged hair cells do not regenerate, resulting in permanent hearing loss. Reprogramming of the surrounding supporting cells to functional hair cells represent a novel strategy to hearing restoration. However, cellular processes governing the efficient and functional hair cell reprogramming are not completely understood. Employing the mouse cochlear organoid system, detailed metabolomic characterizations of the expanding and differentiating organoids are performed. It is found that hair cell differentiation is associated with increased mitochondrial electron transport chain (ETC) activity and reactive oxidative species generation. Transcriptome and metabolome analyses indicate reduced expression of oxidoreductases and tricyclic acid (TCA) cycle metabolites. The metabolic decoupling between ETC and TCA cycle limits the availability of the key metabolic cofactors, α‐ketoglutarate (α‐KG) and nicotinamide adenine dinucleotide (NAD+). Reduced expression of NAD+ in cochlear supporting cells by PGC1α deficiency further impairs hair cell reprogramming, while supplementation of α‐KG and NAD+ promotes hair cell reprogramming both in vitro and in vivo. These findings reveal metabolic rewiring as a central cellular process during hair cell differentiation, and highlight the insufficiency of key metabolites as a metabolic barrier for efficient hair cell reprogramming. [ABSTRACT FROM AUTHOR]

AbstractBased on the sound speed and physical property measurements of seafloor sediments obtained in the central part of the South Yellow Sea, a multi-parameter prediction model for the sound speed of seafloor sediments based on seven parameters, including density, porosity, water content, liquid limit, plasticity index, compression coefficient, and median grain size, was developed by using the BP-AdaBoost fusion algorithm. The results show that the model, configured with 7 input layer neurons, 10 hidden layer neurons, 1 output node, a learning rate of 0.1, and 300 training iterations, achieved a correlation coefficient of 0.962. The mean absolute error (MAE) of the predicted sound speed was 10.19 m/s, and the mean relative error (MAPE) was 0.66%. These results are better than those of single-parameter and dual-parameter prediction equations and other machine learning models. The BP-AdaBoost model prediction method of sound speed of seafloor sediments established in this paper is better than the single-parameter and dual-parameter prediction equations and other prediction models, and it can provide a new way for the prediction of sound speed of seafloor sediments in the study area. [ABSTRACT FROM AUTHOR]

The in situ acoustic measurement of seafloor sediment is an important technical means to obtain the acoustic parameters of seafloor. The time‐of‐flight method is commonly used to calculate the sound speed in seafloor sediment. Accurate identification of signal feature points is essential for determining travel time or travel time difference of acoustic signals. However, the precise identification of feature points, such as the take‐off point of the first wave of a sound wave signal, is challenging. The conventional manual identification method is inefficient and prone to errors. The development of a feature point auto‐identification method is imperative for accurately calculating the travel time of acoustic signals. In this study, we employed the cross‐correlation method, the level threshold method and the short window‐long window energy ratio method to extract the acoustic travel time differences and calculate the sound speeds in seawater and in seafloor sediment. We then analysed the effectiveness of these calculated results. The sound speeds in seawater obtained through the aforementioned methods were compared with the sound speeds measured using a sound velocity profiler. The comparison revealed that these processing methods exhibit a high level of accuracy. The sound speed results in sediments show that the programme‐based auto‐identification methods significantly reduce the standard deviation compared to the manual identification method. This study successfully assessed the processing accuracy of different methods and expanded the processing methods for in situ acoustic signals of seafloor sediments. [ABSTRACT FROM AUTHOR]

The underlying molecular mechanisms of age-related hearing loss (ARHL) in humans and many strains of mice have not been fully characterized. This common age-related disorder is assumed to be closely associated with oxidative stress. Here, we demonstrate that mTORC1 signaling is highly and specifically activated in the cochlear neurosensory epithelium (NSE) in aging mice, and rapamycin injection prevents ARHL. To further examine the specific role of mTORC1 signaling in ARHL, we generated murine models with NSE-specific deletions of Raptor or Tsc1, regulators of mTORC1 signaling. Raptor- cKO mice developed hearing loss considerably more slowly than WT littermates. Conversely, Tsc1 loss led to the early- onset death of cochlear hair cells and consequently accelerated hearing loss. Tsc1-cKO cochleae showed features of oxidative stress and impaired antioxidant defenses. Treatment with rapamycin and the antioxidant N-acetylcysteine rescued Tsc1-cKO hair cells from injury in vivo. In addition, we identified the peroxisome as the initial signaling organelle involved in the regulation of mTORC1 signaling in cochlear hair cells. In summary, our findings identify overactive mTORC1 signaling as one of the critical causes of ARHL and suggest that reduction of mTORC1 activity in cochlear hair cells may be a potential strategy to prevent ARHL., Introduction Age-related hearing loss (ARHL), also known as presbycusis, is one of the most common sensory disorders in elderly individuals. This condition occurs in 25%-40% of people aged 65 years [...]

Based on the data of the acoustic and physical properties of seafloor sediments obtained on the continental shelf area of the East China Sea (ECS), prediction equations of the sediment sound speed based on single and dual parameters were established, and the correlation of the sound speed with physical parameters was discussed. The results show that the sediment sound speed (c) is strongly correlated with water content (w), density (ρ), void ratio (e), mean grain size (Mz) and median grain size (Md), and the coefficient of determination R2 of the empirical regression equation is generally greater than 0.80, while the empirical regression equation coefficient of determination R2 of the compression coefficient (a) and compression modulus (E) are slightly lower, with 0.79 and 0.73, respectively. The coefficients of determination of the dual parameter regression equations between sediment sound speed with physical property parameters are generally higher than those of the single parameter equations, which are all higher than 0.90 indicating better prediction performance. The sensitivity of the physical parameters to the sound speed was analyzed, and the result shows that the sequence of sensitivity from high to low influence on sediment sound speed is void ratio, density, compressibility coefficient, median grain size and mean grain size. The prediction equations established in this study are a good extension and supplement to marine geoacoustic models and is of great significance for obtaining the acoustic properties of the seafloor sediments on the shelf of the East China Sea. [ABSTRACT FROM AUTHOR]

To systematically study the soil and water conservation functions of different straw mulching application rates on sloping farmland in karst area of Southwest China, the observation of runoff plots was carried out with natural rainfall. The effects of six mulching gradients (0, 1.111, 2.222, 3.889, 5.556, 6.944 Mg ha−1) on soil and water conservation functions (soil moisture, nutrients, runoff and sediment yields) were showed: with an increasing straw mulching, total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), soil moisture and available nutrients increased, and high straw mulching (SM4 and SM5) made them significantly higher than control, but there was no significant difference between SM4 and SM5; the contents of soil moisture, TOC, TN, TP and available nutrients of mulching treatments in 2019 except for total potassium (TK) were higher than those in 2018; with an increasing straw mulching, the runoff and sediment yields decreased exponentially, while the straw mulching reached 5.556–6.944 Mg ha−1, it didn't change significantly. These results suggested that straw mulching about 6 Mg ha−1 should be adopted for sloping farmland in karst area of Southwest China, and appropriate K fertilizer should be added to maintain the balance of K in soil. [ABSTRACT FROM AUTHOR]

Based on the characteristics of the GaAs photoconductive semiconductor switch (PCSS) and the spark gap, a new combined switch is developed. The combined switch integrates a traditional GaAs PCSS and a normal spark gap, which could offer two to three times of self-breakdown voltage for the spark gap in nanoseconds. Compared with the traditional single GaAs PCSS, a higher peak current at the output terminal was observed in the experiments when the combined switch was used. Based on the transferred electron effect and the runaway fast electron model, the turn-on process of the GaAs PCSS and the mechanism for the formation of plasma channel in the spark gap are discussed. In addition, due to the interaction between the GaAs PCSS and the spark gap, lock-on effect is avoided in a bulk GaAs PCSS when the bias electric field is larger than the lock-on threshold, which indicates that this combined switch could improve the longevity of the GaAs PCSS under high applied voltage. Index Terms--GaAs photoconductive semiconductor, runaway fast electron, spark gap, transferred electron effect.