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Age-related hearing loss (ARHL) is a common sensory impairment with complex underlying mechanisms. In our previous study, we performed a meta-analysis of genome-wide association studies (GWAS) in mice and identified a novel locus on chromosome 18 associated with ARHL specifically linked to a 32 kHz tone burst stimulus. Consequently, we investigated the role of Formin Homology 2 Domain Containing 3 (Fhod3), a newly discovered candidate gene for ARHL based on the GWAS results. We observed Fhod3 expression in auditory hair cells (HCs) primarily localized at the cuticular plate (CP). To understand the functional implications of Fhod3 in the cochlea, we generated Fhod3 overexpression mice (Pax2-Cre^+/-; Fhod3^Tg/+) (TG) and HC-specific conditional knockout mice (Atoh1-Cre^+/-; Fhod3^fl/fl) (KO). Audiological assessments in TG mice demonstrated progressive high-frequency hearing loss, characterized by predominant loss of outer hair cells, and a decreased phalloidin intensities of CP. Ultrastructural analysis revealed loss of the shortest row of stereocilia in the basal turn of the cochlea, and alterations in the cuticular plate surrounding stereocilia rootlets. Importantly, the hearing and HC phenotype in TG mice phenocopied that of the KO mice. These findings suggest that balanced expression of Fhod3 is critical for proper CP and stereocilia structure and function. Further investigation of Fhod3 related hearing impairment mechanisms may lend new insight towards the myriad mechanisms underlying ARHL, which in turn could facilitate the development of therapeutic strategies for ARHL. 

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22–24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.