RESUMEN
The constrained disorder principle (CDP) defines living organisms as systems that comprise an intrinsic disorder bounded by dynamic boundaries. Water plays a substantial role in multiple biological processes affecting nucleic acids' and proteins' structure and function. The paper describes the CDP-accounted water structure dynamicity and variability in water isomers ratio. Per the CDP, the variability in the ratios between water isomers is mandated for the inherent variability of biological systems. This variability underlies water's unique functions and enables the flexibility and adaptability required to cope with internal and external environmental changes. The CDP-dependent water structures also determine energy usage. The paper presents water molecules as ultimate biosensors for stimuli in the environment and as the ultimate bioreactors that respond to perturbations by changing the structure and function of the molecules in their vicinity. Finally, it describes the potential of using water-based signatures of variability to improve artificial intelligence-based algorithms developed for correcting disturbances of biological systems by increasing the degree of disorder in systems or tightening the disorder's boundaries.
RESUMEN
Background: The brain-computer interface (BCI) is gaining much attention to treat neurological disorders and improve brain-dependent functions. Significant achievements over the last decade have focused on engineering and computation technology to enhance the recording of signals and the generation of output stimuli. Nevertheless, many challenges remain for the translation of BCIs to clinical applications. Methods: We review the relevant data on the four significant gaps in enhancing BCI's clinical implementation and effectiveness. Results: The paper describes three methods to bridge the current gaps in the clinical application of BCI. The first is using a brain-directed adjuvant with a high safety profile, which can improve the accuracy of brain signaling, summing of information, and production of stimuli. The second is implementing a second-generation artificial intelligence system that is outcome-oriented for improving data streaming, recording individualized brain-variability patterns into the algorithm, and improving closed-loop learning at the level of the brain and with the target organ. The system overcomes the compensatory mechanisms that underlie the loss of stimuli' effectiveness for ensuring sustainable effects. Finally, we use inherent brain parameters relevant to consciousness and brain function to bridge some of the described gaps. Conclusions: Combined with the currently developed techniques for enhancing effectiveness and ensuring a sustainable response, these methods can potentially improve the clinical outcome of BCI techniques.
RESUMEN
Randomness is intrinsic to many natural processes. It is also clear that, under certain conditions, disorders are not associatedwith functionality. Several examples in which overcoming, suppressing, or combining both randomness and non-randomness is required are drawn from various fields. However, the need to suppress or overcome randomness does not negateits importance under certain conditions and its significance in valid processes and organ functions. Randomness should beacknowledged rather than ignored or suppressed; it can be viewed, at worst, as a disturbing disorder that may be treated toproduce order, or, at best, as a ‘beneficial disorder’ that can be considered as a higher level of functionality.