We present a case study of the periodized training by a world-class 400-m Individual Medley (IM) swimmer (4 in 2019 World Championships) in the season leading to a bronze medal in the 2018 European Championship. The complexity of this IM preparation was based on the experiences, observations and innovations of an Olympic swimming coach. Over 52 weeks, a traditional periodization model was employed using three macrocycles. A total of 15 competitions were completed in the season increasing in frequency in the third macrocycle. The training intensity distribution (TID) followed the pattern of a traditional pyramidal model in general training and polarized and threshold models during specific training before competitions. Weekly training volume ranged from 25 to 79 km, 24 to 87 km, and 25 to 90 km in each of the three macrocyles. Altitude training comprised 23% of total training weeks. Haemoglobin [Hb] increased from 14.9 to 16.0 g/100 ml and haematocrit from 45.1 to 48.1% after altitude training. Heart rate (HR) and [La] decreased at submaximal swimming intensities, while swimming velocity increased in the 8 × 100 m incremental swimming test in A2 (1.4%) and in AT (0.6%). Pull up power was increased 10% through the season.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536385 | PMC |
http://dx.doi.org/10.5114/biolsport.2022.109954 | DOI Listing |
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.
View Article and Find Full Text PDFFuture Med Chem
January 2025
School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation, Yantai University, Yantai, China.
J Sports Sci
January 2025
Department of Tourism, Sport and Society, Lincoln University, Christchurch, New Zealand.
This study investigates the effectiveness of blood flow restriction (BFR) training in maintaining athletic performance during a taper phase in basketball players. The taper phase aims to reduce external load while maintaining training intensity. Seventeen experienced basketball players were randomised into two groups: a placebo group ( = 8, 22.
View Article and Find Full Text PDFSyst 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.
View Article and Find Full Text PDFFront Biosci (Landmark Ed)
January 2025
Department of Cardiothoracic Surgery, The Affiliated Jiangyin Hospital of Nantong University, 214400 Jiangyin, Jiangsu, China.
Background: This study investigates the role of small ubiquitin-like modifier (SUMO)-specific peptidase 5 (SENP5), a key regulator of SUMOylation, in esophageal squamous cell carcinoma (ESCC), a lethal disease, and its underlying molecular mechanisms.
Methods: Differentially expressed genes between ESCC mouse oesophageal cancer tissues and normal tissues were analysed via RNA-seq; among them, SENP5 expression was upregulated, and this gene was selected for further analysis. Immunohistochemistry and western blotting were then used to validate the increased protein level of SENP5 in both mouse and human ESCC samples.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!