ROCK1 is a multifunctional factor maintaining the primordial follicle reserve and follicular development in mice.

The follicle is the basic structural and functional unit of the ovary in female mammals. The excessive depletion of follicles will lead to diminished ovarian reserve or even premature ovarian failure, resulting in diminished ovarian oogenesis and endocrine function. Excessive follicular depletion is mainly due to loss of primordial follicles.

[p53 regulates primordial follicle activation through the mTOR signaling pathway].

This paper aimed to investigate the role and potential mechanism of p53 on primordial follicle activation. Firstly, the p53 mRNA expression in the ovary of neonatal mice at 3, 5, 7 and 9 days post-partum (dpp) and the subcellular localization of p53 were detected to confirm the expression pattern of p53. Secondly, 2 dpp and 3 dpp ovaries were cultured with p53 inhibitor Pifithrin-μ (PFT-μ, 5 μmol/L) or equal volume of dimethyl sulfoxide for 3 days.

ASH1L contributes to oocyte apoptosis by regulating DNA damage.

In female mammals, the size of the initially established primordial follicle pool within the ovaries determines the reproductive life span. Interestingly, the establishment of the primordial follicle pool is accompanied by a remarkable programmed oocyte loss for unclear reasons. Here, we identify a new role of ASH1-like histone lysine methyltransferase (ASH1L) in controlling the apoptosis of oocytes during meiotic prophase I in mice.

A One-Dimensional CNN-LSTM Model for Epileptic Seizure Recognition Using EEG Signal Analysis.

Frequent epileptic seizures cause damage to the human brain, resulting in memory impairment, mental decline, and so on. Therefore, it is important to detect epileptic seizures and provide medical treatment in a timely manner. Currently, medical experts recognize epileptic seizure activity through the visual inspection of electroencephalographic (EEG) signal recordings of patients based on their experience, which takes much time and effort.

MNL-Network: A Multi-Scale Non-local Network for Epilepsy Detection From EEG Signals.

Epilepsy is a prevalent neurological disorder that threatens human health in the world. The most commonly used method to detect epilepsy is using the electroencephalogram (EEG). However, epilepsy detection from the EEG is time-consuming and error-prone work because of the varying levels of experience we find in physicians.