ProGroTrack: Deep Learning-Assisted Tracking of Intracellular Protein Growth Dynamics

Accurate tracking of cellular and subcellular structures, along with their dynamics, plays a pivotal role in understanding the underlying mechanisms of biological systems. This paper presents a novel approach, ProGroTrack, that combines the You Only Look Once (YOLO) and ByteTrack algorithms within the detection-based tracking (DBT) framework to track intracellular protein nanostructures. Focusing on iPAK4 protein fibers as a representative case study, we conducted a comprehensive evaluation of YOLOv5 and YOLOv8 models, revealing the superior performance of YOLOv5 on our dataset. Notably, YOLOv5x achieved an impressive mAP50 of 0.839 and F-score of 0.819. To further optimize detection capabilities, we incorporated semi-supervised learning for model improvement, resulting in enhanced performances in all metrics. Subsequently, we successfully applied our approach to track the growth behavior of iPAK4 protein fibers, revealing their two distinct growth phases consistent with a previously reported kinetic model. This research showcases the promising potential of our approach, extending beyond iPAK4 fibers. It also offers a significant advancement in precise tracking of dynamic processes in live cells, and fostering new avenues for biomedical research

Effects of force load, muscle fatigue and magnetic stimulation on surface electromyography during side arm lateral raise task: a preliminary study with healthy subjects

The aim of this study was to quantitatively investigate the effects of force load, muscle fatigue and extremely low frequency (ELF) magnetic stimulation on surface electromyography (SEMG) signal features during side arm lateral raise task. SEMG signals were recorded from 18 healthy subjects on the anterior deltoid using a BIOSEMI Active Two system during side lateral raise task (with the right arm 90 degrees away from the body) with three different loads on the forearm (0kg, 1kg and 3 kg; their order was randomized between subjects). The arm maintained the loads until the subject felt exhausted. The first 10s recording for each load was regarded as non-fatigue status and the last 10s before the subject was exhausted as fatigue status. The subject was then given a five-minute resting between different loads. Two days later, the same experiment was repeated on every subject, while this time the ELF magnetic stimulation was applied to the subject’s deltoid muscle during the five-minute rest period. Three commonly used SEMG features, including root mean square (RMS), median frequency (MDF) and sample entropy (SampEn) were analyzed and compared between different loads, non-fatigue/fatigue status, and with/without ELF magnetic stimulation. Variance analysis results showed that the effect of force load on RMS was significant (p0.05). In comparison with non-fatigue status, for all the different force loads with and without ELF stimulation, RMS was significantly larger at fatigue (all p0.05). Finally, the RMS, MDF, SampEn and their changes with force were not significantly different between with and without ELF stimulation (all p>0.05). Our study comprehensively quantified the effects of force, fatigue and the ELF magnetic stimulation on SEMG features, which may facilitate a better understanding of the underlying physiological mechanisms of muscle activities associated with force and fatigue, and of muscle physiological response to ELF magnetic stimulation

Muscle extremely low frequency magnetic stimulation eliminates the effect of fatigue on EEG-EMG coherence during the lateral raise task: a pilot quantitative investigation

The aim of this study was to quantitatively investigate the effects of force load, muscle fatigue and extremely low frequency (ELF) magnetic stimulation on electroencephalography (EEG)-electromyography (EMG) coherence during right arm lateral raise task. Eighteen healthy male subjects were recruited. EEG and EMG signals were simultaneously recorded from each subject while three different loads (0, 1 and 3kg) were added on the forearm. ELF magnetic stimulation was applied to the subject’s deltoid muscle between tasks during the resting period. Univariate ANOVA showed that all EEG-EMG coherence areas of C3, C4, CP5 and CP6 were not significantly affected by the force load (all p>0.05), and that muscle fatigue led to statistically significant reductions on the coherence area of gamma band in C3 (p=0.014) and CP5 (p=0.019). More interestingly, these statistically significant reductions disappeared with the application of muscle ELF magnetic stimulation, indicating its potential application to eliminate the effect of fatigue

Effects of force load, muscle fatigue and extremely low frequency magnetic stimulation on EEG signals during side arm lateral raise task

Objective: This study was to quantitatively investigate the effects of force load, muscle fatigue and extremely low frequency (ELF) magnetic stimulation on electroencephalography (EEG) signal features during side arm lateral raise task. Approach: EEG signals were recorded by a BIOSEMI Active Two system with Pin-Type active-electrodes from 18 healthy subjects when they performed the right arm side lateral raise task (90° away from the body) with three different loads (0 kg, 1 kg and 3 kg; their order was randomized among the subjects) on the forearm. The arm maintained the loads until the subject felt exhausted. The first 10 s recording for each load was regarded as non-fatigue status and the last 10 s before the subject was exhausted as fatigue status. The subject was then given a 5 min resting between different loads. Two days later, the same experiment was performed on each subject except that ELF magnetic stimulation was applied to the subject's deltoid muscle during the 5 min resting period. EEG features from C3 and C4 electrodes including the power of alpha, beta and gamma and sample entropy were analyzed and compared between different loads, non-fatigue/fatigue status, and with/without ELF magnetic stimulation. Main results: The key results were associated with the change of the power of alpha band. From both C3-EEG and C4-EEG, with 1 kg and 3 kg force loads, the power of alpha band was significantly smaller than that from 0 kg for both non-fatigue and fatigue periods (all p    0.05 for all the force loads except C4-EEG with ELF simulation). The power of alpha band at fatigue status was significantly increased for both C3-EEG and C4-EEG when compared with the non-fatigue status (p    0.05, except between non-fatigue and fatigue with magnetic stimulation in gamma band of C3-EEG at 1 kg, and in the SampEn at 1 kg and 3 kg force loads from C4-EEG). Significance: Our study comprehensively quantified the effects of force, fatigue and the ELF magnetic stimulation on EEG features with difference forces, fatigue status and ELF magnetic stimulation