When Jonah Williams stepped onto the campus at the University of Alabama, it couldn’t have taken long to notice he was different. He was already a self-described “film junkie” upon arrival, not exactly the norm for a teenager whose counterparts were more likely binging on Fortnite than on football tape.
On a normal day in Tuscaloosa, it wouldn’t have been uncommon to see Williams toting a notebook that included three points of focus for that day’s practice. It was part of his routine. He also created personalized spreadsheets that detailed each opponent’s pass-rush preferences. He then turned that data into spider charts to help decipher the information.
Aroldis Chapman was nicknamed the Cuban Missile for a reason. The Yankees’ lanky left-handed closer from the Caribbean island has long been the most prominent face of the velocity explosion in modern baseball. Ever since he broke into the major leagues in 2010, few pitchers could match his 100-miles-per-hour fastball.
Until last season. A month on the injured list with left knee tendinitis sapped some power, and his average fastball speed dipped slightly from the previous season, to 98.9 m.p.h. He was still among the hardest throwers in baseball, but for the first time since 2013, Chapman was not tops: St. Louis Cardinals relief pitcher Jordan Hicks, nine years younger, claimed the title with a 100.5-m.p.h. average, according to Fangraphs.
“That’s no problem for me,” Chapman, 31, said in Spanish recently, adding later: “I’m not 20 or 22 anymore. The years pile up — not by choice.”
… After what was virtually a write-off of a season last year, Leonard has credited the Raptors medical staff for how healthy he is now.
“Me missing games isn’t just to keep me fresh,” he told reporters after a game last month. “It’s obviously making sure I don’t reinjure something that I was out for last year. [Raptors medical staff] have been doing a good job of reading images and making sure that I’m improving instead of declining on the health side.
“It feels a lot better than when I started the season. There was a little spell where it kind of plateaued but everybody brought their minds together and we figured out a way and now things are looking good and I’m feeling good.”
That’s about the deepest anyone with the Raptors has gone when explaining Leonard’s load-management plan.
What if you were told that you could potentially become a star athlete by sitting down for five minutes? An ongoing study happening at the University of Colorado Boulder may have that answer.
“It’s called inspiratory muscle strength training (IMST) — it takes about five minutes a day and in certain populations of people with obstructive sleep apnea, it has been shown to lower blood pressure,” said Dr. Daniel Craighead, a postdoctoral fellow in the integrative physiology department at CU who is heading a study involving this machine which began in October 2017.
The five-minute training involves taking 30 breaths into an IMST device which provides resistance to one’s breath. One may feel “a little bit light-headed,” said Erzsebet Nagy, a graduate student working on the study.
The CU study currently in progress involves healthy middle-aged adults practicing this exercise over the course of six weeks to see whether this machine can improve their overall health and be used in a preventative way.
USA TODAY High School Sports, Arizona Republic, Richard Obert from
… While, three-sport athletes still exist, there are not as many in this age of specialization, which began in the late 1990s. Finding those who are elite in three sports might be lost.
Guys like Nathan LaDuke, Jon Volpe, Rodney Peete, Randall McDaniel led a 1980s explosion of athletes who were the best of the best in three sports in Arizona.
Maybe not since Mike Nixon graduated from Sunnyslope (Phoenix) in 2002 and Prince Amukamara left Apollo (Glendale) in 2007, has there been an exceptional male three-sport athlete.
Transmission electron microscopy (TEM) is being pushed to new capabilities which enable studies on systems that were previously out of reach. Among recent innovations, TEM through liquid cells (LC-TEM) enables in operando observation of biological phenomena. This work applies LC-TEM to the study of biological components as they interact on an abiotic surface. Specifically, analytes or target molecules like neuropeptide Y (NPY) are observed in operando on functional graphene field-effect transistor (GFET) biosensors. Biological recognition elements (BREs) identified using biopanning with affinity to NPY are used to functionalize graphene to obtain selectivity. On working devices capable of achieving picomolar responsivity to neuropeptide Y, LC-TEM reveals translational motion, stochastic positional fluctuations due to constrained Brownian motion, and rotational dynamics of captured analyte. Coupling these observations with the electrical responses of the GFET biosensors in response to analyte capture and/or release will potentially enable new insights leading to more advanced and capable biosensor designs.
… Since the first Bluetooth headset sold in 2000, the wearable tech industry has been hard at work inserting itself into our daily lives. And by all accounts, it’s working: The number of connected wearable devices worldwide is expected to jump to 1.1 billion or more by 2022, and some experts predict that fitness trackers will generate more than $3 billion in global revenue by that same year.
But for many people, donning a health-focused device each day isn’t necessarily a good thing. Research suggests that even if you don’t ditch your tracker after the first few months, it can be difficult to develop a healthy, effective relationship with the device that’s monitoring your calories, steps, and minutes of sleep. In one study, published in the Journal of the American Medical Association, overweight participants who wore fitness trackers each day lost less weight than those who didn’t. In another, people who wore them for a full year were no healthier than they’d been at the start of the study. On the other end of the spectrum, users can become too obsessed with the data their devices are collecting, leading them to self-diagnose problems that don’t exist; they can get so invested in their stats that it drains any enjoyment from previously pleasant activities; and, in some cases, fitness trackers can even exacerbate disordered eating behaviors.
Newry-based sports tech company StatSports is weighing a flotation in about two years’ time, at which point it expects to be worth in excess of £1 billion (€1.15 billion).
The move comes as the company announced that Premier League footballers Raheem Sterling and Alex Oxlade-Chamberlain have both recently invested seven-figure sums in the company in a new funding round that values it at more than £200 million (€231 million).
Advances in technology have ushered in a new era in the measurement and interpretation of surface-recorded electromyographic (EMG) signals. These developments have included improvements in detection systems, the algorithms used to decompose the interference signals, and the strategies used to edit the identified waveforms. To evaluate the validity of the results obtained with this new technology, the purpose of this review was to compare the results achieved by decomposing surface-recorded EMG signals into the discharge times of single motor units with what is known about the rate coding characteristics of single motor units based on recordings obtained with intramuscular electrodes. The characteristics compared were peak discharge rate, saturation of discharge rate during submaximal contractions, rate coding during fast contractions, the association between oscillations in force and discharge rate, and adjustments during fatiguing contractions. The comparison indicates that some decomposition methods are able to replicate many of the findings derived from intramuscular recordings, but additional improvements in the methods are required. Critically, more effort needs to be focused on editing the waveforms identified by the decomposition algorithms. With adequate attention to detail, this technology has the potential to augment our knowledge on motor unit physiology and to provide useful approaches that are being translated into clinical practice.
Medicine & Science in Sports & Exercise journal from
INTRODUCTION:
Musculoskeletal injury rates in military personnel remain unacceptably high. Application of machine learning algorithms could be useful in multivariate models to predict injury in this population. The purpose of this study was to investigate if interaction between individual predictors, using a decision tree model, could be used to develop a population-specific algorithm of lower-extremity injury (LEI) risk. METHODS:
One hundred forty Air Force Special Forces Operators (27.4 ± 5.0 yr, 177.6 ± 5.8 cm, 83.8 ± 8.4 kg) volunteered for this prospective cohort study. Baseline testing included body composition, isokinetic strength, flexibility, aerobic/anaerobic capacity, anaerobic power, and landing biomechanics. To evaluate unilateral landing patterns, subjects jumped off two-feet from a distance (40% of their height) over a hurdle and landing single-legged on a force plate. Medical chart reviews were conducted 365 d postbaseline. χ automatic interaction detection (CHAID) was used, which compares predictor variables to LEI and assigns a population-specific “cut-point” for the most relevant predictors. RESULTS:
Twenty-seven percent of operators (n = 38) suffered LEI. A maximum knee flexion angle difference of 25.1% had the highest association with injury in this population (P = 0.006). Operators with >25.1% differences in max knee flexion angle (n = 13) suffered LEI at a 69.2% rate. Seven of the 13 Operators with >25.1% difference in max knee flexion angle weighed >81.8 kg, and 100% of those operators suffered LEI (P = 0.047; n = 7). Only 33% of operators with >25.1% difference in max knee flexion angle that weighed <81.8 kg suffered LEI.
CONCLUSIONS:
This study demonstrated increased risk of LEI over a 365-d period in Operators with greater differences in single-leg landing strategies and higher body mass. The CHAID approach can be a powerful tool to analyze population-specific risk factors for injury, along with how those factors may interact to enhance risk.
Despite increased knowledge on anterior cruciate ligament (ACL) injury mechanisms, improved surgical techniques, improved understanding of ACL biomechanics and enhanced knowledge in rehabilitation practice, return-to-sport (RTS) rates and subsequent second ACL re-injury rates after ACL reconstruction are not optimal. This narrative review discusses factors that may be highly relevant for RTS training and testing after ACL reconstruction, but which have received limited research attention to date or do not form part of the standard approach to rehabilitation. These factors include (1) explosive neuromuscular performance; (2) movement quality deficits associated with re-injury risk, particularly the need to re-train optimal sport-specific movement patterns; (3) the influence of fatigue; and (4) a lack of sport-specific re-training prior to RTS, with particular attention to an insufficient development of chronic training load. In addition, incorporating performance re-training and ensuring an athlete has restored their sport-specific profile is important. The relevance of these variables for RTS training and testing is discussed, with a new recommended model of late-stage rehabilitation and RTS training presented. Additional testing to support RTS decision making is also presented. This paper contains important information for practitioners and researchers to support optimised late-stage rehabilitation and RTS programmes and RTS testing with a view to enhancing patient outcomes after ACL reconstruction.
Causes of anterior cruciate ligament (ACL) injuries are multifactorial. Anterior cruciate ligament injury prevention should thus be approached from a multifactorial perspective as well. Training to resist fatigue is an underestimated aspect of prevention programs given that the presence of fatigue may play a crucial role in sustaining an ACL injury. Objectives
The primary objective of this literature review was to summarize research findings relating to the kinematic and kinetic effects of fatigue on single-leg landing tasks through a systematic review and meta-analysis. Other objectives were to critically appraise current approaches to examine the effects of fatigue together with elucidating and proposing an optimized approach for measuring the role of fatigue in ACL injury prevention. Methods
A systematic literature search was conducted in the databases PubMed (1978–November 2017), CINAHL (1992–November 2017), and EMBASE (1973–November 2017). The inclusion criteria were: (1) full text, (2) published in English, German, or Dutch, (3) healthy subjects, (4) average age ≥ 18 years, (5) single-leg jump landing task, (6) evaluation of the kinematics and/or kinetics of the lower extremities before and after a fatigue protocol, and (7) presentation of numerical kinematic and/or kinetic data. Participants included healthy subjects who underwent a fatigue protocol and in whom the effects of pre- and post-fatigue on three-dimensional lower extremity kinematic and kinetics were compared. Methods of data collection, patient selection, blinding, prevention of verification bias, and study design were independently assessed. Results
Twenty studies were included, in which four types of single-leg tasks were examined: the single-leg drop vertical jump, the single-leg drop landing, the single-leg hop for distance, and sidestep cutting. Fatigue seemed to mostly affect initial contact (decreased angles post-fatigue) and peak (increased angles post-fatigue) hip and knee flexion. Sagittal plane variables at initial contact were mostly affected under the single-leg hop for distance and sidestep cutting conditions whilst peak angles were affected during the single-leg drop jump. Conclusions
Training to resist fatigue is an underestimated aspect of prevention programs given that the presence of fatigue may play a crucial role in sustaining an ACL injury. Considering the small number of variables affected after fatigue, the question arises whether the same fatigue pathways are affected by the fatigue protocols used in the included laboratory studies as are experienced on the sports field. [full text]
It’s frustrating when nutrition studies seem to contradict earlier ones: “Are Eggs Good or Bad For You? New Research Rekindles Debate,” the Associated Press groused in mid-March. Though it may seem that dietary science is changing every day, that’s not really the case. I’m here to explain how nutritional research works, so you’ll have an easier time making sense of food headlines.
Let’s focus on one of the most vexing dietary issues: saturated fat. There are studies that suggest it increases cardiovascular disease risk, and studies that suggest it doesn’t. Why the apparent contradiction?
“Nutrition research is not well-funded,” says David Jenkins, Canada Research Chair in Nutrition at the University of Toronto and St. Michael’s Hospital in Toronto. For that reason, nutrition research trials usually have only 70 to 120 subjects. “When you don’t have big enough numbers, that’s when things can flip-flop,” says Jenkins.
If you’ve ever had a big breakfast right before a run, you probably learned the hard way why it’s not always the best idea. Food plus hard exercise usually equals queasiness and cramping at best—and full-on puking at worst.
“Digesting food and exercising at the same time is difficult for most athletes,” says Joshua Scott, M.D., a primary care sports medicine physician at Cedars-Sinai Kerlan-Jobe Institute in Los Angeles. But working out on an empty stomach can be tough, too. (Talk about seriously bonking.)
So what’s a runner to do? Here’s a look at the pros and cons of breakfasting before your run—and how you can fuel up without feeling sick.
The NFL has more data on its players than ever before, but evaluating prospects still involves a lot of guesswork. Here’s how some teams are getting creative to find their perfect pick.