Background: Though the artificial neural network (ANN) technique has been used to predict noise-induced hearing loss (NIHL), the established prediction models have primarily relied on cross-sectional datasets, and hence, they may not comprehensively capture the chronic nature of NIHL as a disease linked to long-term noise exposure among workers. Methods: A comprehensive dataset was utilized, encompassing eight-year longitudinal personal hearing threshold levels (HTLs) as well as information on seven personal variables and two environmental variables to establish NIHL predicting models through the ANN technique. Three subdatasets were extracted from the afirementioned comprehensive dataset to assess the advantages of the present study in NIHL predictions. Results: The dataset was gathered from 170 workers employed in a steel-making industry, with a median cumulative noise exposure and HTL of 88.40 dBA-year and 19.58 dB, respectively. Utilizing the longitudinal dataset demonstrated superior prediction capabilities compared to cross-sectional datasets. Incorporating the more comprehensive dataset led to improved NIHL predictions, particularly when considering variables such as noise pattern and use of personal protective equipment. Despite fluctuations observed in the measured HTLs, the ANN predicting models consistently revealed a discernible trend. Conclusions A consistent correlation was observed between the measured HTLs and the results obtained from the predicting models. However, it is essential to exercise caution when utilizing the model-predicted NIHLs for individual workers due to inherent personal fluctuations in HTLs. Nonetheless, these ANN models can serve as a valuable reference for the industry in effectively managing its hearing conservation program.

We have shown that myosin light chain kinase (MLCK) was required for the off-contraction in response to the electrical field stimulation (EFS) of feline esophageal smooth muscle. In this study, we investigated whether protein kinase C (PKC) may require the on-contraction in response to EFS using feline esophageal smooth muscle. The contractions were recorded using an isometric force transducer. On-contraction occurred in the presence of NG-nitro-L-arginine methyl ester (L-NAME), suggesting that nitric oxide acts as an inhibitory mediator in smooth muscle. The excitatory composition of both contractions was cholinergic dependent which was blocked by tetrodotoxin or atropine. The on-contraction was abolished in Ca2+-free buffer but reappeared in normal Ca2+-containing buffer indicating that the contraction was Ca2+ dependent. 4-aminopyridine (4-AP), voltage-dependent K+ channel blocker, significantly enhanced on-contraction. Aluminum fluoride (a G-protein activator) increased on-contraction. Pertussis toxin (a Gi inactivator) and C3 exoenzyme (a rhoA inactivator) significantly decreased on-contraction suggesting that Gi or rhoA protein may be related with Ca2+ and K+ channel. ML-9, a MLCK inhibitor, significantly inhibited on-contraction, and chelerythrine (PKC inhibitor) affected on the contraction. These results suggest that endogenous cholinergic contractions activated directly by low-frequency EFS may be mediated by Ca2+, and G proteins, such as Gi and rhoA, which resulted in the activation of MLCK, and PKC to produce the contraction in feline distal esophageal smooth muscle.
4-Aminopyridine ; Aluminum ; Aluminum Compounds ; Atropine ; Azepines ; Benzophenanthridines ; Contracts ; Esophagus ; Fluorides ; GTP-Binding Proteins ; Muscle, Smooth ; Myosin-Light-Chain Kinase ; NG-Nitroarginine Methyl Ester ; Nitric Oxide ; Pertussis Toxin ; Protein Kinase C ; rhoA GTP-Binding Protein ; Tetrodotoxin ; Transducers