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Background/aims: Rare disease drug development faces unique challenges, such as genotypic and phenotypic heterogeneity within small patient populations and a lack of established outcome measures for conditions without previously successful drug development programs. These challenges complicate the process of selecting the appropriate trial endpoints and conducting clinical trials in rare diseases. In this descriptive study, we examined novel drug approvals for non-oncologic rare diseases by the U.

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In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.

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Unveiling the role of miRNAs in Diminished Ovarian Reserve: an in silico network approach.

Syst Biol Reprod Med

December 2025

Department of Biosciences and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy.

MicroRNAs (miRNAs) have acquired an increased recognition to unravel the complex molecular mechanisms underlying Diminished Ovarian Reserve (DOR), one of the main responsible for infertility. To investigate the impact of miRNA profiles in granulosa cells and follicular fluid, crucial players in follicle development, this study employed a computational network theory approach to reconstruct potential pathways regulated by miRNAs in granulosa cells and follicular fluid of women suffering from DOR. Available data from published research were collected to create the FGC_MiRNome_MC, a representation of miRNA target genes and their interactions.

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Cellular Cholesterol Loss Impairs Synaptic Vesicle Mobility via the CAMK2/Synapsin-1 Signaling Pathway.

Front Biosci (Landmark Ed)

January 2025

Department of Neurology, Jinshan Hospital, Fudan University, 201508 Shanghai, China.

Background: Neuronal cholesterol deficiency may contribute to the synaptopathy observed in Alzheimer's disease (AD). However, the underlying mechanisms remain poorly understood. Intact synaptic vesicle (SV) mobility is crucial for normal synaptic function, whereas disrupted SV mobility can trigger the synaptopathy associated with AD.

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Background: Diabetes mellitus is associated with morphological and functional impairment of the heart primarily due to lipid toxicity caused by increased fatty acid metabolism. Extracellular signal-regulated protein kinases 1 and 2 (ERK1/2) have been implicated in the metabolism of fatty acids in the liver and skeletal muscles. However, their role in the heart in diabetes remains unclear.

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