MicroRNAs (miRNAs) are a group of endogenous noncoding small RNAs characterized by high conservation; furthermore, various studies have shown the capability of miRNAs to impact diseases. For example, a study shows that cellfree miRNAs are stable in bodily fluids, which gives circulating miRNAs the ability to be potential biomarkers for noninvasive diagnosis. Additionally, accumulating studies have supported that miRNAs can function as suppressor genes, again demonstrating their effect on disease. This review introduces this particular role of miRNAs as well as analyzes the prospect of miRNAs as biomarkers and the capacity for using miRNA-based resources to benefit mankind.

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The L3DAS22 Challenge is aimed at encouraging the development of machine learning strategies for 3D speech enhancement and 3D sound localization and detection in office-like environments. This challenge improves and extends the tasks of the L3DAS21 edition 1 . We generated a new dataset, which maintains the same general characteristics of L3DAS21 datasets, but with an extended number of data points and adding constrains that improve the baseline model's efficiency and overcome the major difficulties encountered by the participants of the previous challenge. We updated the baseline model of Task 1, using the architecture that ranked first in the previous challenge edition. We wrote a new supporting API, improving its clarity and ease-of-use. In the end, we present and discuss the results submitted by all participants. L3DAS22 Challenge website: www.l3das.com/icassp2022.

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