Abstract: The present disclosure relates to PEG-lipids, cationic and/or ionizable lipids and nucleic acid-lipid particle compositions comprising the same. The present disclosure also relates to methods of making, using and delivering the described lipids and lipid-containing particles.

Abstract: Anonymization is the process to remove personal information from the data. Once the data is anonymized, the data may be used for creating machine-learning models without the risk of invading anyone's privacy. One of the keys to data anonymization is to make sure that the data is really anonymized so nobody could use the anonymized data to obtain private information. Different techniques for data anonymization are presented. Further, the data anonymization techniques are tested for true anonymization by comparing the results from these techniques to a random method of guessing. If the difference in the results is below a predetermined threshold margin, the data anonymization techniques are safe and ready for use.

Abstract: In some embodiments, a mail verification server can use probabilistic methods to determine whether a user's emails should be throttled based on the recipients to which the user sends emails. The mail verification server can estimate a number of unique recipients to which a user has sent emails in the past, and can estimate whether the rate of which the number of unique recipients increases crosses over a predetermined threshold. The mail verification server can determine that a new user has sent emails to 500 unique recipients, and can track the rate at which the number of unique recipients rises. The mail verification server can then throttle the user's emails if the rate at which the number of unique recipients rises exceeds threshold (e.g., if the number of unique recipients the user has contacted rises by 200% and/or a similar threshold).