Core Points - Aclarion, Inc. has adjourned its Annual Meeting of Stockholders originally scheduled for July 7, 2025, to July 21, 2025, to solicit additional votes on proposals [1][2] - The record date for stockholders entitled to vote remains May 9, 2025, and stockholders are encouraged to vote as soon as possible [2] - Proxies submitted for the Annual Meeting will be voted at the adjourned meeting unless revoked, and stockholders can change their votes before the meeting [3] Company Overview - Aclarion is a healthcare technology company utilizing Magnetic Resonance Spectroscopy (MRS) and a proprietary biomarker to enhance clinical treatments for low back and neck pain [5] - The company addresses a significant market, valued at $134.5 billion in the U.S. for low back and neck pain [5] - Aclarion is incorporating Artificial Intelligence (AI) to improve quality control in spectroscopy data and is researching AI applications to better associate MRS data with clinical outcomes [5]

Core Points - Aclarion, Inc. has announced the adjournment of its Special Meeting of Stockholders originally scheduled for February 28, 2025, to March 5, 2025, to solicit additional votes on proposals outlined in the definitive proxy statement filed with the SEC on February 3, 2025 [2][5][6] - The reconvened Special Meeting will take place at the company's corporate office in Broomfield, Colorado, and stockholders as of the record date of January 6, 2025, are encouraged to vote promptly [3][4] - Proxies submitted for the Special Meeting will remain valid unless revoked, and stockholders can change their votes until March 4, 2025, at 11:59 p.m. Mountain Time [4] Company Overview - Aclarion, Inc. is a healthcare technology company that utilizes Magnetic Resonance Spectroscopy (MRS) and a proprietary biomarker to enhance clinical treatments for low back and neck pain, addressing a market valued at $134.5 billion in the U.S. [7] - The company is integrating Artificial Intelligence (AI) into its quality control processes to identify poor MRS study data and is exploring AI and machine learning applications to analyze spectroscopy data for better clinical outcome associations [7]