Development and Characterization of a low intensity vibrational system for microgravity studies.

The advent of extended-duration human spaceflight demands a better comprehension of the physiological impacts of microgravity. One primary concern is the adverse impact on the musculoskeletal system, including muscle atrophy and bone density reduction. Ground-based microgravity simulations have provided insights, with vibrational bioreactors emerging as potential mitigators of these negative effects. Despite the potential they have, the adaptation of vibrational bioreactors for space remains unfulfilled, resulting in a significant gap in microgravity research. This paper introduces the first automated low-intensity vibrational (LIV) bioreactor designed specifically for the International Space Station (ISS) environment. Our research covers the bioreactor's design and characterization, the selection of an optimal linear guide for consistent 1-axis acceleration, a thorough analysis of its thermal and diffusion dynamics, and the pioneering use of BioMed Clear resin for enhanced scaffold design. This advancement sets the stage for more authentic space-based biological studies, vital for ensuring the safety of future space explorations.

Large language models encode clinical knowledge.

Large language models (LLMs) have demonstrated impressive capabilities, but the bar for clinical applications is high. Attempts to assess the clinical knowledge of models typically rely on automated evaluations based on limited benchmarks. Here, to address these limitations, we present MultiMedQA, a benchmark combining six existing medical question answering datasets spanning professional medicine, research and consumer queries and a new dataset of medical questions searched online, HealthSearchQA. We propose a human evaluation framework for model answers along multiple axes including factuality, comprehension, reasoning, possible harm and bias. In addition, we evaluate Pathways Language Model1 (PaLM, a 540-billion parameter LLM) and its instruction-tuned variant, Flan-PaLM2 on MultiMedQA. Using a combination of prompting strategies, Flan-PaLM achieves state-of-the-art accuracy on every MultiMedQA multiple-choice dataset (MedQA3, MedMCQA4, PubMedQA5 and Measuring Massive Multitask Language Understanding (MMLU) clinical topics6), including 67.6% accuracy on MedQA (US Medical Licensing Exam-style questions), surpassing the prior state of the art by more than 17%. However, human evaluation reveals key gaps. To resolve this, we introduce instruction prompt tuning, a parameter-efficient approach for aligning LLMs to new domains using a few exemplars. The resulting model, Med-PaLM, performs encouragingly, but remains inferior to clinicians. We show that comprehension, knowledge recall and reasoning improve with model scale and instruction prompt tuning, suggesting the potential utility of LLMs in medicine. Our human evaluations reveal limitations of today's models, reinforcing the importance of both evaluation frameworks and method development in creating safe, helpful LLMs for clinical applications.

User-centred design for machine learning in health care: a case study from care management.

OBJECTIVES: Few machine learning (ML) models are successfully deployed in clinical practice. One of the common pitfalls across the field is inappropriate problem formulation: designing ML to fit the data rather than to address a real-world clinical pain point. METHODS: We introduce a practical toolkit for user-centred design consisting of four questions covering: (1) solvable pain points, (2) the unique value of ML (eg, automation and augmentation), (3) the actionability pathway and (4) the model's reward function. This toolkit was implemented in a series of six participatory design workshops with care managers in an academic medical centre. RESULTS: Pain points amenable to ML solutions included outpatient risk stratification and risk factor identification. The endpoint definitions, triggering frequency and evaluation metrics of the proposed risk scoring model were directly influenced by care manager workflows and real-world constraints. CONCLUSIONS: Integrating user-centred design early in the ML life cycle is key for configuring models in a clinically actionable way. This toolkit can guide problem selection and influence choices about the technical setup of the ML problem.

Determining breast cancer biomarker status and associated morphological features using deep learning.

Background: Breast cancer management depends on biomarkers including estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (ER/PR/HER2). Though existing scoring systems are widely used and well-validated, they can involve costly preparation and variable interpretation. Additionally, discordances between histology and expected biomarker findings can prompt repeat testing to address biological, interpretative, or technical reasons for unexpected results. Methods: We developed three independent deep learning systems (DLS) to directly predict ER/PR/HER2 status for both focal tissue regions (patches) and slides using hematoxylin-and-eosin-stained (H&E) images as input. Models were trained and evaluated using pathologist annotated slides from three data sources. Areas under the receiver operator characteristic curve (AUCs) were calculated for test sets at both a patch-level (>135 million patches, 181 slides) and slide-level (n = 3274 slides, 1249 cases, 37 sites). Interpretability analyses were performed using Testing with Concept Activation Vectors (TCAV), saliency analysis, and pathologist review of clustered patches. Results: The patch-level AUCs are 0.939 (95%CI 0.936-0.941), 0.938 (0.936-0.940), and 0.808 (0.802-0.813) for ER/PR/HER2, respectively. At the slide level, AUCs are 0.86 (95%CI 0.84-0.87), 0.75 (0.73-0.77), and 0.60 (0.56-0.64) for ER/PR/HER2, respectively. Interpretability analyses show known biomarker-histomorphology associations including associations of low-grade and lobular histology with ER/PR positivity, and increased inflammatory infiltrates with triple-negative staining. Conclusions: This study presents rapid breast cancer biomarker estimation from routine H&E slides and builds on prior advances by prioritizing interpretability of computationally learned features in the context of existing pathological knowledge.

Current and future applications of artificial intelligence in pathology: a clinical perspective.

During the last decade, a dramatic rise in the development and application of artificial intelligence (AI) tools for use in pathology services has occurred. This trend is often expected to continue and reshape the field of pathology in the coming years. The deployment of computational pathology and applications of AI tools can be considered as a paradigm shift that will change pathology services, making them more efficient and capable of meeting the needs of this era of precision medicine. Despite the success of AI models, the translational process from discovery to clinical applications has been slow. The gap between self-contained research and clinical environment may be too wide and has been largely neglected. In this review, we cover the current and prospective applications of AI in pathology. We examine its applications in diagnosis and prognosis, and we offer insights for considerations that could improve clinical applicability of these tools. Then, we discuss its potential to improve workflow efficiency, and its benefits in pathologist education. Finally, we review the factors that could influence adoption in clinical practices and the associated regulatory processes.

WU-NEAT: A clinically validated, open-source MATLAB toolbox for limited-channel neonatal EEG analysis.

BACKGROUND: Limited-channel EEG research in neonates is hindered by lack of open, accessible analytic tools. To overcome this limitation, we have created the Washington University-Neonatal EEG Analysis Toolbox (WU-NEAT), containing two of the most commonly used tools, provided in an open-source, clinically-validated package running within MATLAB. METHODS: The first algorithm is the amplitude-integrated EEG (aEEG), which is generated by filtering, rectifying and time-compressing the original EEG recording, with subsequent semi-logarithmic display. The second algorithm is the spectral edge frequency (SEF), calculated as the critical frequency below which a user-defined proportion of the EEG spectral power is located. The aEEG algorithm was validated by three experienced reviewers. Reviewers evaluated aEEG recordings of fourteen preterm/term infants, displayed twice in random order, once using a reference algorithm and again using the WU-NEAT aEEG algorithm. Using standard methodology, reviewers assigned a background pattern classification. Inter/intra-rater reliability was assessed. For the SEF, calculations were made using the same fourteen recordings, first with the reference and then with the WU-NEAT algorithm. Results were compared using Pearson's correlation coefficient. RESULTS: For the aEEG algorithm, intra- and inter-rater reliability was 100% and 98%, respectively. For the SEF, the mean±SD Pearson correlation coefficient between algorithms was 0.96±0.04. CONCLUSION: We have demonstrated a clinically-validated toolbox for generating the aEEG as well as calculating the SEF from EEG data. Open-source access will enable widespread use of common analytic algorithms which are device-independent and unlikely to become outdated as technology changes, thereby facilitating future collaborative research in neonatal EEG.

Artificial intelligence in digital breast pathology: Techniques and applications.

Breast cancer is the most common cancer and second leading cause of cancer-related death worldwide. The mainstay of breast cancer workup is histopathological diagnosis - which guides therapy and prognosis. However, emerging knowledge about the complex nature of cancer and the availability of tailored therapies have exposed opportunities for improvements in diagnostic precision. In parallel, advances in artificial intelligence (AI) along with the growing digitization of pathology slides for the primary diagnosis are a promising approach to meet the demand for more accurate detection, classification and prediction of behaviour of breast tumours. In this article, we cover the current and prospective uses of AI in digital pathology for breast cancer, review the basics of digital pathology and AI, and outline outstanding challenges in the field.

Bioresorbable pressure sensors protected with thermally grown silicon dioxide for the monitoring of chronic diseases and healing processes.

Pressures in the intracranial, intraocular and intravascular spaces are clinically useful for the diagnosis and management of traumatic brain injury, glaucoma and hypertension, respectively. Conventional devices for measuring these pressures require surgical extraction after a relevant operational time frame. Bioresorbable sensors, by contrast, eliminate this requirement, thereby minimizing the risk of infection, decreasing the costs of care and reducing distress and pain for the patient. However, the operational lifetimes of bioresorbable pressure sensors available at present fall short of many clinical needs. Here, we present materials, device structures and fabrication procedures for bioresorbable pressure sensors with lifetimes exceeding those of previous reports by at least tenfold. We demonstrate measurement accuracies that compare favourably to those of the most sophisticated clinical standards for non-resorbable devices by monitoring intracranial pressures in rats for 25 days. Assessments of the biodistribution of the constituent materials, complete blood counts, blood chemistry and magnetic resonance imaging compatibility confirm the biodegradability and clinical utility of the device. Our findings establish routes for the design and fabrication of bioresorbable pressure monitors that meet requirements for clinical use.

Comparison of step-by-step kinematics of resisted, assisted and unloaded 20-m sprint runs.

This investigation examined step-by-step kinematics of sprint running acceleration. Using a randomised counterbalanced approach, 37 female team handball players (age 17.8 ± 1.6 years, body mass 69.6 ± 9.1 kg, height 1.74 ± 0.06 m) performed resisted, assisted and unloaded 20-m sprints within a single session. 20-m sprint times and step velocity, as well as step length, step frequency, contact and flight times of each step were evaluated for each condition with a laser gun and an infrared mat. Almost all measured parameters were altered for each step under the resisted and assisted sprint conditions (η2 ≥ 0.28). The exception was step frequency, which did not differ between assisted and normal sprints. Contact time, flight time and step frequency at almost each step were different between 'fast' vs. 'slow' sub-groups (η2 ≥ 0.22). Nevertheless overall both groups responded similarly to the respective sprint conditions. No significant differences in step length were observed between groups for the respective condition. It is possible that continued exposure to assisted sprinting might allow the female team-sports players studied to adapt their coordination to the 'over-speed' condition and increase step frequency. It is notable that step-by-step kinematics in these sprints were easy to obtain using relatively inexpensive equipment with possibilities of direct feedback.

Wireless bioresorbable electronic system enables sustained nonpharmacological neuroregenerative therapy.

Peripheral nerve injuries represent a significant problem in public health, constituting 2-5% of all trauma cases1. For severe nerve injuries, even advanced forms of clinical intervention often lead to incomplete and unsatisfactory motor and/or sensory function2. Numerous studies report the potential of pharmacological approaches (for example, growth factors, immunosuppressants) to accelerate and enhance nerve regeneration in rodent models3-10. Unfortunately, few have had a positive impact in clinical practice. Direct intraoperative electrical stimulation of injured nerve tissue proximal to the site of repair has been demonstrated to enhance and accelerate functional recovery11,12, suggesting a novel nonpharmacological, bioelectric form of therapy that could complement existing surgical approaches. A significant limitation of this technique is that existing protocols are constrained to intraoperative use and limited therapeutic benefits13. Herein we introduce (i) a platform for wireless, programmable electrical peripheral nerve stimulation, built with a collection of circuit elements and substrates that are entirely bioresorbable and biocompatible, and (ii) the first reported demonstration of enhanced neuroregeneration and functional recovery in rodent models as a result of multiple episodes of electrical stimulation of injured nervous tissue.

SIG-DB: Leveraging homomorphic encryption to securely interrogate privately held genomic databases.

Genomic data are becoming increasingly valuable as we develop methods to utilize the information at scale and gain a greater understanding of how genetic information relates to biological function. Advances in synthetic biology and the decreased cost of sequencing are increasing the amount of privately held genomic data. As the quantity and value of private genomic data grows, so does the incentive to acquire and protect such data, which creates a need to store and process these data securely. We present an algorithm for the Secure Interrogation of Genomic DataBases (SIG-DB). The SIG-DB algorithm enables databases of genomic sequences to be searched with an encrypted query sequence without revealing the query sequence to the Database Owner or any of the database sequences to the Querier. SIG-DB is the first application of its kind to take advantage of locality-sensitive hashing and homomorphic encryption to allow generalized sequence-to-sequence comparisons of genomic data.

Electrical Stimulation and Bone Healing: A Review of Current Technology and Clinical Applications.

Pseudarthrosis is an exceedingly common, costly, and morbid complication in the treatment of long bone fractures and after spinal fusion surgery. Electrical bone growth stimulation (EBGS) presents a unique approach to accelerate healing and promote fusion success rates. Over the past three decades, increased experience and widespread use of EBGS devices has led to significant improvements in stimulation paradigms and clinical outcomes. In this paper, we comprehensively review the literature and examine the history, scientific evidence, available technology, and clinical applications for EBGS. We summarize indications, limitations, and provide an overview of cost-effectiveness and future directions of EBGS technology. Various models of electrical stimulation have been proposed and marketed as adjuncts for spinal fusions and long bone fractures. Clinical studies show variable safety and efficacy of EBGS under different conditions and clinical scenarios. While the results of clinical trials do not support indiscriminate EBGS utilization for any bone injury, the evidence does suggest that EBGS is desirable and cost efficient for certain orthopedic indications, especially when used in combination with standard, first-line treatments. This review should serve as a reference to inform practicing clinicians of available treatment options, facilitate evidence-based decision making, and provide a platform for further research.

The Relationship Between Multidirectional Jumping and Performance in Change of Direction Tasks.

Bourgeois, FA II, Gamble, P, Gill, ND, and McGuigan, MR. The relationship between multidirectional jumping and performance in change of direction tasks. J Strength Cond Res 32(3): 690-699, 2018-This study investigated the test-retest reliability of 2 change of direction (COD; 180 and 45° COD) sprints and 3 multidirectional jump (MDJ) tests. Variables examined were approach time (sprint before plant-step), exit time (sprint after plant-step), total time (time to completion) and MDJ approach time, and distance, respectively. Second, the ability of MDJ tests to predict performance in COD tests was examined. Twenty men (age: 27.5 ± 5.9 years; height: 1.79 ± 0.1 m; and body mass: 79.1 ± 12.0 kg) performed 5 trials for each assessment, executing left plant-leg (LT) and right plant-leg (RT) steps, on 2 testing occasions separated by 7 days. Between-session and within-session intraclass correlation coefficients (ICCs) and coefficients of variation (CVs) for all measurements were calculated. Usefulness of COD and MDJ tests was assessed using typical error and smallest worthwhile change (SWC) comparison. Results showed only one MDJ measurement generated unstable between-session reliability. Within-session reliability of approach and exit COD times, and MDJ approach times possessed confidence limits (90% CL) that extended below 0.75 ICC. All COD total times and MDJ distances presented high reliability (ICC = 0.87-0.99) with low CV (0.9-4.1%). Right-leg MDJ distances were predictors of RT COD performances (r = 0.50-0.68, p = 0.001-0.024), whereas LT MDJ distances were predictors of LT180 COD performance (r = 0.67-0.71, p = 0.001). All measurements were useful in detecting SWC in performance. These findings suggest the COD tests and MDJ distances are reliable for assessing and monitoring COD performance in similar cohorts.

Therapeutic electrical stimulation of injured peripheral nerve tissue using implantable thin-film wireless nerve stimulators.

OBJECTIVE Electrical stimulation of peripheral nerve tissue has been shown to accelerate axonal regeneration. Yet existing methods of applying electrical stimulation to injured peripheral nerves have presented significant barriers to clinical translation. In this study, the authors examined the use of a novel implantable wireless nerve stimulator capable of simultaneously delivering therapeutic electrical stimulation of injured peripheral nerve tissue and providing postoperative serial assessment of functional recovery. METHODS Flexible wireless stimulators were fabricated and implanted into Lewis rats. Thin-film implants were used to deliver brief electrical stimulation (1 hour, 20 Hz) to sciatic nerves after nerve crush or nerve transection-and-repair injuries. RESULTS Electrical stimulation of injured nerves via implanted wireless stimulators significantly improved functional recovery. Brief electrical stimulation was observed to increase the rate of functional recovery after both nerve crush and nerve transection-and-repair injuries. Wireless stimulators successfully facilitated therapeutic stimulation of peripheral nerve tissue and serial assessment of nerve recovery. CONCLUSIONS Implantable wireless stimulators can deliver therapeutic electrical stimulation to injured peripheral nerve tissue. Implantable wireless nerve stimulators might represent a novel means of facilitating therapeutic electrical stimulation in both intraoperative and postoperative settings.

GPR56/ADGRG1 regulates development and maintenance of peripheral myelin.

Myelin is a multilamellar sheath generated by specialized glia called Schwann cells (SCs) in the peripheral nervous system (PNS), which serves to protect and insulate axons for rapid neuronal signaling. In zebrafish and rodent models, we identify GPR56/ADGRG1 as a conserved regulator of PNS development and health. We demonstrate that, during SC development, GPR56-dependent RhoA signaling promotes timely radial sorting of axons. In the mature PNS, GPR56 is localized to distinct SC cytoplasmic domains, is required to establish proper myelin thickness, and facilitates organization of the myelin sheath. Furthermore, we define plectin-a scaffolding protein previously linked to SC domain organization, myelin maintenance, and a series of disorders termed "plectinopathies"-as a novel interacting partner of GPR56. Finally, we show that Gpr56 mutants develop progressive neuropathy-like symptoms, suggesting an underlying mechanism for peripheral defects in some human patients with GPR56 mutations. In sum, we define Gpr56 as a new regulator in the development and maintenance of peripheral myelin.

Population-based approaches to treatment and readmission after spinal cord injury.

BACKGROUND: Recent studies in surgical and non-surgical specialties have suggested that patients admitted on the weekend may have worse outcomes. In particular, patients with stroke and acute cardiovascular events have shown worse outcomes with weekend treatment. It is unclear whether this extends to patients with spinal cord injury (SCI). This study was designed to evaluate factors for readmission after index hospitalization for spinal cord injury. METHODS: This cohort was constructed from the State Inpatient Databases of California, New York, and Florida. For this study 14,396 patients with SCI were identified. The primary outcome measure evaluated was 30-day readmission. Secondary measures include in-hospital complications. Univariate and multivariate analysis were utilized to evaluate covariates. c2, Fisher's exact, and linear, logistic, and modified Poisson regression methods were utilized for statistical analysis. Propensity score methods were used with matched pairs analysis performed by the McNemar's Test. RESULTS: Weekend admission was not associated with increased 30- day readmission rates in multivariate analysis. Race and discharge to a facility (RR 1.60 [1.43-1.79]) or home with home care (RR 1.23 [1.07-1.42]), were statistically significant risk factors for readmission. Payor status did not affect rates of readmission. In propensity score matched pairs analysis, weekend admission was not associated with increased odds of 30-day readmission (OR 1.04 [0.89-1.21]). Patients admitted to high volume centers had significantly lower risk of readmission when compared with patients admitted to low volume centers. CONCLUSIONS: Our results suggest that the weekend effect, described previously in other patient populations, may not play as important a role in patients with SCI.

Readmission after spinal cord injury: analysis of an institutional cohort of 795 patients.

BACKGROUND: Recent studies in other fields have suggested that healthcare on the weekend may have worse outcomes. In particular, patients with stroke and acute cardiovascular events have shown worse outcomes with weekend treatment. It is unclear whether this extends to patients with spinal cord injury. This study was designed to evaluate factors for readmission after index hospitalization for spinal cord injury. METHODS: A total of 795 consecutive patients over an 11-year period were analyzed. After excluding patients with chronic spinal cord injury and surgical care at an outside hospital, 745 patients remained. The primary outcome measure evaluated was 30-day readmission. Secondary measures include perioperative complications, readmission rate when discharged on the weekend, and the effect of race and insurance status on readmission rate. Univariate and multivariate analysis were utilized to evaluate the covariates collected. The χ2 test, Fisher's exact test, and linear and logistic regression methods were utilized for statistical analysis. RESULTS: A total of 745 patients were analyzed after exclusions. Payer status did not affect length of stay, ICU length of stay, or perioperative complications. Neither weekend admission nor weekend operation affected length of stay, ICU length of stay, or readmission by 30 days. Patients undergoing weekend surgical treatment had lower perioperative complication rates (2.2% vs. 6.5% on weekday, P<0.01). Discharge on the weekend was associated with a significantly lower rate of readmission by 30 days (OR=0.07, 95% CI: 0.009-0.525, P<0.005). Payer status was associated with 30-day readmission (P<0.005). Patients with Medicare (20.8%) and Medicaid (20.1%) showed higher rates of readmission than patients with other payers. 21.1% of African-American patients were readmitted, versus 10.2% of other patients (Odds ratio: 2.2, 95% confidence interval 1.36-3.27, P<0.001). Correcting for payer status lessened but did not eliminate the effect of race on readmission. CONCLUSIONS: Weekend admission did not increase perioperative complications or hospital length of stay. After discharge, patients with Medicaid and Medicare show higher rates of 30-day readmission, as do African-American patients. The effect of race on readmission is multifactorial, and may partially explained by the increased rate of Medicaid coverage in African-Americans in our institutions catchment area.

Diffusion Assessment of Cortical Changes, Induced by Traumatic Spinal Cord Injury.

Promising treatments are being developed to promote functional recovery after spinal cord injury (SCI). Magnetic resonance imaging, specifically Diffusion Tensor Imaging (DTI) has been shown to non-invasively measure both axonal and myelin integrity following traumatic brain and SCI. A novel data-driven model-selection algorithm known as Diffusion Basis Spectrum Imaging (DBSI) has been proposed to more accurately delineate white matter injury. The objective of this study was to investigate whether DTI/DBSI changes that extend to level of the cerebral peduncle and internal capsule following a SCI could be correlated with clinical function. A prospective non-randomized cohort of 23 patients with chronic spinal cord injuries and 17 control subjects underwent cranial diffusion weighted imaging, followed by whole brain DTI and DBSI computations. Region-based analyses were performed on cerebral peduncle and internal capsule. Three subgroups of patients were included in the region-based analysis. Tract-Based Spatial Statistics (TBSS) was also applied to allow whole-brain white matter analysis between controls and all patients. Functional assessments were made using International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) as modified by the American Spinal Injury Association (ASIA) Scale. Whole brain white matter analysis using TBSS finds no statistical difference between controls and all patients. Only cervical ASIA A/B patients in cerebral peduncle showed differences from controls in DTI and DBSI results with region-based analysis. Cervical ASIA A/B SCI patients had higher levels of axonal injury and edema/tissue loss as measured by DBSI at the level of the cerebral peduncle. DTI Fractional Anisotropy (FA), Axial Diffusivity (AD) and Radial Diffusivity (RD) was able to detect differences in cervical ASIA A/B patients, but were non-specific to pathologies. Increased water fraction indicated by DBSI non-restricted isotropic diffusion fraction in the cerebral peduncle, explains the simultaneously increased DTI AD and DTI RD values. Our results further demonstrate the utility of DTI to detect disruption in axonal integrity in white matter, yet a clear shortcoming in differentiating true axonal injury from inflammation/tissue loss. Our results suggest a preservation of axonal integrity at the cortical level and has implications for future regenerative clinical trials.

Effects of a Six-Week Strength Training Programme on Change of Direction Performance in Youth Team Sport Athletes.

This study investigated the effects of eccentric phase-emphasis strength training (EPE) on unilateral strength and performance in 180- and 45-degree change of direction (COD) tasks in rugby union players. A 12-week cross-over design was used to compare the efficacy of resistance training executed with 3 s eccentric duration (EPE, n = 12) against conventional strength training, with no constraints on tempo (CON, n = 6). Players in each condition were categorised as 'fast' (FAST) or 'slow' (SLOW) using median trial times from baseline testing. Players recorded greater isometric strength improvements following EPE (ES = -0.54 to 1.80). Whilst these changes were not immediate, players improved in strength following cessation. Improvements in 180-degree COD performance was recorded at all test-points following EPE (ES = -1.32 to -0.15). Improvements in 45-degree COD performance were apparent for FAST following CON (ES = -0.96 to 0.10), but CON was deleterious for SLOW (ES = -0.60 to 1.53). Eccentric phase-emphasis strength training shows potential for sustained strength enhancement. Positive performance changes in COD tasks were category- and condition-specific. The data indicate the greatest improvement occurred at nine weeks following resistance training in these players. Performance benefits may also be specific to COD task, player category, and relative to emphasis on eccentric phase activity.