-
Frontiers in Sports and Active Living 2024Professional athletes navigate a multitude of unique challenges associated to sport-specific factors (e.g., training, travel and competition) and non-sport factors...
BACKGROUND
Professional athletes navigate a multitude of unique challenges associated to sport-specific factors (e.g., training, travel and competition) and non-sport factors (e.g., performance pressure, stress and anxiety) that can interfere with healthy sleep behaviors. Sleep plays a key role in proper biopsychosocial development as well as short- and long-term biological, physical, psychological, and cognitive health. As poor sleep quality is known to impair proper brain function, this study aimed to investigate the effect of sleep quality on a professional athlete's ability to train, recover, and perform, as well as their overall emotional and physical well-being.
METHODS
A cohort study was performed in 40 professional male cricket athletes from the Dutch national cricket team (mean age 26.5 ± 5.1 years). The athletes were monitored across a 22 weeks in-season training period. Sleep quality and overall emotional and physical well-being were assessed using daily sleep diaries and questionnaires which scored the readiness to train, stress levels, fatigue, muscle soreness and flu symptoms respectively. Quality of sleep and subsequent association with the consecutive elements of the well-being questionnaire were assessed through statistical using the student -test and clinical differences with the methodology of Osoba and colleagues: <5% "no change", 5%-10% "little change"; 10%-20% "moderate change"; and >20% "very much change".
RESULTS
The results demonstrated that the professional athletes assessed their sleep quality as average with a mean score of 3.4 out of 5. Lower perceived quality of sleep (<75th percentile) was correlated with a decreased readiness to train (mean score 3.2 [IQR: 3.0-4.0] vs. 3.5 [IQR: 3.0-5.0]; < 0.001) and increased extent of muscle soreness (2.7 [IQR: 2.0-3.0] vs. 2.3 [IQR: 2-3]; < 0.001), stress level (mean score 2.3 [IQR: 2.0-3.0] vs. 1.9 [IQR: 1.0-2.0]; < 0.001) and perceived fatigue (mean score 2.9 [IQR: 2.0-3.0] vs. 2.3 [IQR: 2.0-3.0]; < 0.001). Likewise, in patients with lower perceived quality of sleep, the proportion of players presenting with flu symptoms increased over 4-fold (4.1% vs. 17%; < 0.001).
CONCLUSIONS
This study highlights that good sleep quality positively influences the overall emotional and physical well-being of professional athletes. Our results emphasize the importance of targeted sleep interventions to improve sleep quality and subsequently optimize psychological and physiological wellness.
PubMed: 38903388
DOI: 10.3389/fspor.2024.1389565 -
Frontiers in Sports and Active Living 2024Intermittent fasting (IF) represents a dietary intervention similar to caloric restriction, characterized by the strategic limitation of food consumption. Among the...
INTRODUCTION
Intermittent fasting (IF) represents a dietary intervention similar to caloric restriction, characterized by the strategic limitation of food consumption. Among the diverse array of practices for IF, Ramadan IF (RIF), a religious observance in Islam, mandates that healthy adult Muslims abstain from both food and drinks during daylight hours. In sports, researchers have extensively studied IF effects on health, including sleep and physical performance, but its impact on cognitive functions during RIF remains understudied. Therefore, this study was conducted to evaluate the influence of RIF on psychomotor and cognitive performance among young female athletes.
METHODS
To achieve this purpose, a cohort of 23 female handball players, aged 17.2 ± 0.5 years, participated in a series of six testing sessions: one conducted prior to Ramadan (R0), and others during the first (R1), second (R2), third (R3), and fourth (R4) weeks of Ramadan, followed by a session in the week after Ramadan (R5). Each session involved assessments using a Simple Reaction Time Test (SRT), Choice Reaction Time Test (CRT), Vigilance Test (VT), and Mental Rotation Test (MRT). Additionally, dietary intake, body composition, and Pittsburgh Sleep Quality Index (PSQI) scores were evaluated during these periods.
RESULTS AND DISCUSSION
The obtained data illustrated that there was a decrease in SRT, CRT, VT, and MRT performances during R1 in comparison to R0 (all < .001). This reduction was also observed in R2, R3, R4, and R5. Notably, during the fourth week of Ramadan (R4), these cognitive and psychomotor parameters were significantly lower than during the earlier weeks (R1, R2, R3; all < .001). Furthermore, a gradual decrease in total PSQI scores, sleep quality, and sleep duration was observed throughout the Ramadan period, reaching the lowest levels during R4. These findings illustrate that RIF has a significantly detrimental impact on neuromuscular and cognitive abilities as well as sleep quality in young female athletes. The study also highlights a fluctuating pattern in cognitive function across the four weeks of Ramadan, with the most pronounced decline observed during the final week of fasting illustrating the importance of conducting similar studies on normal individuals from both genders with larger sample size.
PubMed: 38903387
DOI: 10.3389/fspor.2024.1362066 -
Health Psychology Research 2024Executive function impairments are among the most common dialysis side effects. The present study aims to compare the efficiency of transcranial Direct Current...
A Comparison between the Effectiveness of computerized Cognitive Rehabilitation Training and transcranial Direct Current Stimulation on Dialysis Patients' Executive Functions.
PURPOSE
Executive function impairments are among the most common dialysis side effects. The present study aims to compare the efficiency of transcranial Direct Current Stimulation (tDCS) with computerized Cognitive Rehabilitation Training (cCRT) on dialysis patients' executive functions.
RESEARCH METHOD
The present study, a quasi-experimental effort, adopted a pre-test/post-test method that included a control (sham) group.
DESIGN
The study sample consisted of 30 participants, selected through the convenience sampling method, and categorized into three groups of cCRT, tDCS, and sham participants. The cCRT participants were asked to complete 8 tasks in Captain's Log MindPower Builder software. The tDCS participants were treated with a 0.06 mA/cm2 current with the anodal electrode on F3 and the cathodal electrode on Fp2. For the sham participants, the electrodes were put on the same regions but there was no current stimulation. The treatment lasted for 10 sessions carried out every other day.
RESULTS
The results of MANCOVA showed no significant difference between the sham group and the cCRT group in any of the executive function items. . However, between the sham group and the tDCS group was detected a significant difference in spatial working memory (p \< 0.05) and a marginally significant in cognitive flexibility (p = 0.091). No significant difference was reported between cCRT and tDCS groups in any item.
CONCLUSION
According to the findings of the study, given the efficacy of tDCS on spatial working memory and cognitive flexibility for dialysis patients, it can be used to improve these skills.
PubMed: 38903127
DOI: 10.52965/001c.118447 -
Scientific Reports Jun 2024Hearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient's hearing threshold in both air and bone conduction at various...
Hearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient's hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of professionals in the field can severely delay proper diagnosis. The presented work proposes a neural network solution for classification of tonal audiometry data. The solution, based on the Bidirectional Long Short-Term Memory architecture, has been devised and evaluated for classifying audiometry results into four classes, representing normal hearing, conductive hearing loss, mixed hearing loss, and sensorineural hearing loss. The network was trained using 15,046 test results analysed and categorised by professional audiologists. The proposed model achieves 99.33% classification accuracy on datasets outside of training. In clinical application, the model allows general practitioners to independently classify tonal audiometry results for patient referral. In addition, the proposed solution provides audiologists and otolaryngologists with access to an AI decision support system that has the potential to reduce their burden, improve diagnostic accuracy, and minimise human error.
Topics: Humans; Audiometry, Pure-Tone; Neural Networks, Computer; Female; Male; Hearing Loss; Adult; Middle Aged; Hearing Loss, Sensorineural; Hearing Loss, Conductive
PubMed: 38902305
DOI: 10.1038/s41598-024-64310-2 -
JMIR Rehabilitation and Assistive... Jun 2024Impaired cognitive function is observed in many pathologies, including neurodegenerative diseases such as Alzheimer disease. At present, the pharmaceutical treatments...
BACKGROUND
Impaired cognitive function is observed in many pathologies, including neurodegenerative diseases such as Alzheimer disease. At present, the pharmaceutical treatments available to counter cognitive decline have only modest effects, with significant side effects. A nonpharmacological treatment that has received considerable attention is computerized cognitive training (CCT), which aims to maintain or improve cognitive functioning through repeated practice in standardized exercises. CCT allows for more regular and thorough training of cognitive functions directly at home, which represents a significant opportunity to prevent and fight cognitive decline. However, the presence of assistance during training seems to be an important parameter to improve patients' motivation and adherence to treatment. To compensate for the absence of a therapist during at-home CCT, a relevant option could be to include a virtual assistant to accompany patients throughout their training.
OBJECTIVE
The objective of this exploratory study was to evaluate the interest of including a virtual assistant to accompany patients during CCT. We investigated the relationship between various individual factors (eg, age, psycho-affective functioning, personality, personal motivations, and cognitive skills) and the appreciation and usefulness of a virtual assistant during CCT. This study is part of the THERADIA (Thérapies Digitales Augmentées par l'Intelligence Artificielle) project, which aims to develop an empathetic virtual assistant.
METHODS
A total of 104 participants were recruited, including 52 (50%) young adults (mean age 21.2, range 18 to 27, SD 2.9 years) and 52 (50%) older adults (mean age 67.9, range 60 to 79, SD 5.1 years). All participants were invited to the laboratory to answer several questionnaires and perform 1 CCT session, which consisted of 4 cognitive exercises supervised by a virtual assistant animated by a human pilot via the Wizard of Oz method. The participants evaluated the virtual assistant and CCT at the end of the session.
RESULTS
Analyses were performed using the Bayesian framework. The results suggest that the virtual assistant was appreciated and perceived as useful during CCT in both age groups. However, older adults rated the assistant and CCT more positively overall than young adults. Certain characteristics of users, especially their current affective state (ie, arousal, intrinsic relevance, goal conduciveness, and anxiety state), appeared to be related to their evaluation of the session.
CONCLUSIONS
This study provides, for the first time, insight into how young and older adults perceive a virtual assistant during CCT. The results suggest that such an assistant could have a beneficial influence on users' motivation, provided that it can handle different situations, particularly their emotional state. The next step of our project will be to evaluate our device with patients experiencing mild cognitive impairment and to test its effectiveness in long-term cognitive training.
PubMed: 38901017
DOI: 10.2196/48129 -
Proceedings of the National Academy of... Jun 2024Proteomics has been revolutionized by large protein language models (PLMs), which learn unsupervised representations from large corpora of sequences. These models are...
Proteomics has been revolutionized by large protein language models (PLMs), which learn unsupervised representations from large corpora of sequences. These models are typically fine-tuned in a supervised setting to adapt the model to specific downstream tasks. However, the computational and memory footprint of fine-tuning (FT) large PLMs presents a barrier for many research groups with limited computational resources. Natural language processing has seen a similar explosion in the size of models, where these challenges have been addressed by methods for parameter-efficient fine-tuning (PEFT). In this work, we introduce this paradigm to proteomics through leveraging the parameter-efficient method LoRA and training new models for two important tasks: predicting protein-protein interactions (PPIs) and predicting the symmetry of homooligomer quaternary structures. We show that these approaches are competitive with traditional FT while requiring reduced memory and substantially fewer parameters. We additionally show that for the PPI prediction task, training only the classification head also remains competitive with full FT, using five orders of magnitude fewer parameters, and that each of these methods outperform state-of-the-art PPI prediction methods with substantially reduced compute. We further perform a comprehensive evaluation of the hyperparameter space, demonstrate that PEFT of PLMs is robust to variations in these hyperparameters, and elucidate where best practices for PEFT in proteomics differ from those in natural language processing. All our model adaptation and evaluation code is available open-source at https://github.com/microsoft/peft_proteomics. Thus, we provide a blueprint to democratize the power of PLM adaptation to groups with limited computational resources.
Topics: Proteomics; Proteins; Natural Language Processing; Protein Interaction Mapping; Computational Biology; Humans; Algorithms
PubMed: 38900798
DOI: 10.1073/pnas.2405840121 -
Journal of Rehabilitation Medicine Jun 2024To explore how people with stroke, discharged to skilled nursing facilities before returning home, experience the chain of care and rehabilitation.
OBJECTIVE
To explore how people with stroke, discharged to skilled nursing facilities before returning home, experience the chain of care and rehabilitation.
DESIGN
Qualitative, semi-structured interview design.
METHODS
Thirteen stroke survivors discharged from a stroke unit to a skilled nursing facility before returning to independent living participated. Semi-structured telephone interviews were conducted 2-5 months after stroke and analysed with content analysis.
RESULTS
The analysis resulted in three categories, Organizational processes, critical and complex, Rehabilitation, the right support at the right time and Adaptation to the changed situation, with a total of 9 subcategories. The informants perceived low participation in planning and goalsetting and limited information. Support from the healthcare services was important to proceed with improvements although the amount of supported training varied. Factors hindering and facilitating managing everyday life were described, as well as lingering uncertainty of what the future would be like.
CONCLUSION
Support and rehabilitation as well as individuals' needs varied, throughout the chain of care. To enable participation in the rehabilitation, assistance in setting goals and repeated information is warranted. Tailored care and rehabilitation throughout the chain of care should be provided, followed up at home, and coordinated for smooth transitions between organizations.
Topics: Humans; Stroke Rehabilitation; Skilled Nursing Facilities; Female; Male; Patient Discharge; Aged; Middle Aged; Qualitative Research; Aged, 80 and over; Stroke; Continuity of Patient Care
PubMed: 38899476
DOI: 10.2340/jrm.v56.35240 -
Frontiers in Psychology 2024Although Cognitive Behavioral Therapy (CBT) is the most often used intervention in forensic treatment, its effectivity is not consistently supported. Interventions...
INTRODUCTION
Although Cognitive Behavioral Therapy (CBT) is the most often used intervention in forensic treatment, its effectivity is not consistently supported. Interventions incorporating knowledge from neuroscience could provide for more successful intervention methods.
METHODS
The current pilot study set out to assess the feasibility and usability of the study protocol of a 4-week neuromeditation training in adult forensic outpatients with impulse control problems. The neuromeditation training, which prompts awareness and control over brain states of restlessness with EEG neurofeedback, was offered in addition to treatment as usual (predominantly CBT).
RESULTS
Eight patients completed the neuromeditation training under guidance of their therapists. Despite some emerging obstacles, overall, the training was rated sufficiently usable and feasible by patients and their therapists.
DISCUSSION
The provided suggestions for improvement can be used to implement the intervention in treatment and set up future trials to study the effectiveness of neuromeditation in offender treatment.
PubMed: 38899124
DOI: 10.3389/fpsyg.2024.1354997 -
PCN Reports : Psychiatry and Clinical... Jun 2024
PubMed: 38899052
DOI: 10.1002/pcn5.219 -
BMC Medical Genomics Jun 2024Immunoregulatory drugs regulate the ubiquitin-proteasome system, which is the main treatment for multiple myeloma (MM) at present. In this study, bioinformatics analysis...
BACKGROUND
Immunoregulatory drugs regulate the ubiquitin-proteasome system, which is the main treatment for multiple myeloma (MM) at present. In this study, bioinformatics analysis was used to construct the risk model and evaluate the prognostic value of ubiquitination-related genes in MM.
METHODS AND RESULTS
The data on ubiquitination-related genes and MM samples were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The consistent cluster analysis and ESTIMATE algorithm were used to create distinct clusters. The MM prognostic risk model was constructed through single-factor and multiple-factor analysis. The ROC curve was plotted to compare the survival difference between high- and low-risk groups. The nomogram was used to validate the predictive capability of the risk model. A total of 87 ubiquitination-related genes were obtained, with 47 genes showing high expression in the MM group. According to the consistent cluster analysis, 4 clusters were determined. The immune infiltration, survival, and prognosis differed significantly among the 4 clusters. The tumor purity was higher in clusters 1 and 3 than in clusters 2 and 4, while the immune score and stromal score were lower in clusters 1 and 3. The proportion of B cells memory, plasma cells, and T cells CD4 naïve was the lowest in cluster 4. The model genes KLHL24, HERC6, USP3, TNIP1, and CISH were highly expressed in the high-risk group. AICAr and BMS.754,807 exhibited higher drug sensitivity in the low-risk group, whereas Bleomycin showed higher drug sensitivity in the high-risk group. The nomogram of the risk model demonstrated good efficacy in predicting the survival of MM patients using TCGA and GEO datasets.
CONCLUSIONS
The risk model constructed by ubiquitination-related genes can be effectively used to predict the prognosis of MM patients. KLHL24, HERC6, USP3, TNIP1, and CISH genes in MM warrant further investigation as therapeutic targets and to combat drug resistance.
Topics: Humans; Multiple Myeloma; Computational Biology; Prognosis; Ubiquitination; Gene Expression Regulation, Neoplastic; Biomarkers, Tumor; Nomograms; Cluster Analysis
PubMed: 38898455
DOI: 10.1186/s12920-024-01937-0