• Book : 161()
• Pub. Date : 2025
• Page : pp.101695
• Keyword :

Organism health relies on cell proliferation, migration, and differentiation. These universal processes depend on cytoplasmic reorganization driven notably by the cytoskeleton and its force-generating motors. Their activity generates forces that mechanically agitate the cell nucleus and its interior. New evidence from reproductive cell biology revealed that these cytoskeletal forces can be tuned to remodel nuclear membraneless compartments, known as biomolecular condensates, and regulate their RNA processing function for the success of subsequent cell division that is critical for fertility. Both cytoskeletal and nuclear condensate reorganization are common to numerous physiological and pathological contexts, raising the possibility that mechanical remodeling of nuclear condensates may be a much broader mechanism regulating their function. Here, we review this newfound mechanism of condensate remodeling and venture into the contexts of health and disease where it may be relevant, with a focus on reproduction, cancer, and premature aging.

• Book : 40(1)
• Pub. Date : 2025
• Page : pp.000-000
• Keyword :

• Book : 161()
• Pub. Date : 2025
• Page : pp.101697
• Keyword :

• Book : 190()
• Pub. Date : 2025
• Page : pp.117283
• Keyword :

• Book : 261()
• Pub. Date : 2025
• Page : pp.124997
• Keyword :

• Book : 431()
• Pub. Date : 2025
• Page : pp.113726
• Keyword :

• Book : 425()
• Pub. Date : 2025
• Page : pp.116339
• Keyword :

Weather is one of the important elements that greatly determines human activities, especially those related to economic factors. Therefore, understanding weather conditions using weather parameters as a reference is important for human life, so a method is needed to classify weather according to its category so that the information produced can be used for various needs. Determining weather conditions in an area will not run well without a reliable method that can analyze existing weather parameters. Therefore, in this study, the weather condition classification process was carried out using the multilayer perceptron algorithm, a type of neural network (NN) algorithm. All data analyzed were weather parameter data collected by mini weather stations placed on land. The weather parameters used were temperature, humidity, air pressure, wind speed, dew point, wind chill, daily rainfall, solar radiation, and UV index. This study was conducted in Palu city, Central Sulawesi Province, Indonesia. The classification process carried out by the multilayer perceptron algorithm was carried out on the Altair AI Studio application and produced an accuracy value of 93.87%, recall of 92.33%, and precision of 91.29%.

• Book : 37(1)
• Pub. Date : 2025
• Page : pp.540
• Keyword :

• Book : 18(1)
• Pub. Date : 2025
• Page : pp.101229
• Keyword :

• Book : 210()
• Pub. Date : 2025
• Page : pp.114708
• Keyword :