Doping Prevalence among U.S. Elite Athletes Subject to Drug Testing under the World Anti-Doping Code.

BACKGROUND: Determining the prevalence of doping within an elite athlete population is challenging due to the extreme sensitivity of the topic; however, understanding true doping prevalence is important when designing anti-doping programs and measuring their effectiveness. The objective of this study was to estimate the prevalence of doping among Olympic, Paralympic, World, and National-level competitive athletes in the United States subject to the World Anti-Doping Code. All athletes who were subject to the U.S. Anti-Doping Agency's Protocol for Olympic and Paralympic Movement Testing, a World Anti-Doping Code ("Code")-compliant anti-doping program, were invited to complete a web-delivered survey. Using a direct questioning approach, the survey items asked athletes whether they had used each specific category of banned substance / method on the World Anti-Doping Agency's Prohibited List. Multiple strategies to encourage honest reporting (e.g., protecting anonymity by collecting minimal demographic information; using an outside organization to administer the survey) and to detect inconsistent responses were used. RESULTS: Depending on the method of calculation, 6.5-9.2% of the 1,398 respondents reported using one or more prohibited substances or methods in the 12 months prior to survey administration. Specific doping prevalence rates for each individual substance / method categories ranged from 0.1% (for both diuretics / masking agents and stem cell / gene editing) to 4.2% for in-competition use of cannabinoids. CONCLUSION: Determining the prevalence of doping within different athlete populations is critical so that sport governing bodies can evaluate their anti-doping efforts and better tailor their programming. By measuring doping prevalence of specific categories of substances and methods, rather than just the overall prevalence of doping, this study also highlights where sport governing bodies should focus their future educational and detection efforts.

Differential cortical and subcortical visual processing with eyes shut.

Closing our eyes largely shuts down our ability to see. That said, our eyelids still pass some light, allowing our visual system to coarsely process information about visual scenes, such as changes in luminance. However, the specific impact of eye closure on processing within the early visual system remains largely unknown. To understand how visual processing is modulated when eyes are shut, we used functional magnetic resonance imaging (fMRI) to measure responses to a flickering visual stimulus at high (100%) and low (10%) temporal contrasts, while participants viewed the stimuli with their eyes open or closed. Interestingly, we discovered that eye closure produced a qualitatively distinct pattern of effects across the visual thalamus and visual cortex. We found that with eyes open, low temporal contrast stimuli produced smaller responses across the lateral geniculate nucleus (LGN), primary (V1) and extrastriate visual cortex (V2). However, with eyes closed, we discovered that the LGN and V1 maintained similar blood oxygenation level-dependent (BOLD) responses as the eyes open condition, despite the suppressed visual input through the eyelid. In contrast, V2 and V3 had strongly attenuated BOLD response when eyes were closed, regardless of temporal contrast. Our findings reveal a qualitatively distinct pattern of visual processing when the eyes are closed-one that is not simply an overall attenuation but rather reflects distinct responses across visual thalamocortical networks, wherein the earliest stages of processing preserve information about stimuli but are then gated off downstream in visual cortex.NEW & NOTEWORTHY When we close our eyes coarse luminance information is still accessible by the visual system. Using functional magnetic resonance imaging, we examined whether eyelid closure plays a unique role in visual processing. We discovered that while the LGN and V1 show equivalent responses when the eyes are open or closed, extrastriate cortex exhibited attenuated responses with eye closure. This suggests that when the eyes are closed, downstream visual processing is blind to this information.

The temporal specificity of BOLD fMRI is systematically related to anatomical and vascular features of the human brain.

The ability to detect fast responses with functional MRI depends on the speed of hemodynamic responses to neural activity, because hemodynamic responses act as a temporal low-pass filter smoothing out rapid changes. However, hemodynamic responses (their shape and timing) are highly variable across the brain and across stimuli. This heterogeneity of responses implies that the temporal specificity of fMRI signals, or the ability of fMRI to preserve fast information, should also vary substantially across the cortex. In this work we investigated how local differences in hemodynamic response timing impact the temporal specificity of fMRI. We conducted our research using ultra-high field (7T) fMRI at high spatiotemporal resolution, using the primary visual cortex (V1) as a model area for investigation. We used visual stimuli oscillating at slow and fast frequencies to probe the temporal specificity of individual voxels. As expected, we identified substantial variability in temporal specificity, with some voxels preserving their responses to fast neural activity more effectively than others. We investigated which voxels had the highest temporal specificity and related those to anatomical and vascular features of V1. We found that low temporal specificity is only weakly explained by the presence of large veins or cerebral cortical depth. Notably, however, temporal specificity depended strongly on a voxel's position along the anterior-posterior anatomical axis of V1, with voxels within the calcarine sulcus being capable of preserving close to 25% of their amplitude as the frequency of stimulation increased from 0.05-Hz to 0.20-Hz, and voxels nearest to the occipital pole preserving less than 18%. These results indicate that detection biases in high-resolution fMRI will depend on the anatomical and vascular features of the area being imaged, and that these biases will differ depending on the timing of the underlying neuronal activity. Importantly, this spatial heterogeneity of temporal specificity suggests that it could be exploited to achieve higher specificity in some locations, and that tailored data analysis strategies may help improve the detection and interpretation of fast fMRI responses.

Theory of Defect-Induced Crystal Field Perturbations in Rare-Earth Magnets.

We present a theory describing the single-ion anisotropy of rare-earth (RE) magnets in the presence of point defects. Taking the RE-lean 1∶12 magnet class as a prototype, we use first-principles calculations to show how the introduction of Ti substitutions into SmFe_{12} perturbs the crystal field, generating new coefficients due to the lower symmetry of the RE environment. We then demonstrate that these perturbations can be described extremely efficiently using a screened point charge model. We provide analytical expressions for the anisotropy energy that can be straightforwardly implemented in atomistic spin dynamics simulations, meaning that such simulations can be carried out for an arbitrary arrangement of point defects. The significant crystal field perturbations calculated here demonstrate that a sample that is single phase from a structural point of view can nonetheless have a dramatically varying anisotropy profile at the atomistic level if there is compositional disorder, which may influence localized magnetic objects like domain walls or skyrmions.

Distributed fMRI dynamics predict distinct EEG rhythms across sleep and wakefulness.

The brain exhibits rich oscillatory dynamics that vary across tasks and states, such as the EEG oscillations that define sleep. These oscillations play critical roles in cognition and arousal, but the brainwide mechanisms underlying them are not yet described. Using simultaneous EEG and fast fMRI in subjects drifting between sleep and wakefulness, we developed a machine learning approach to investigate which brainwide fMRI dynamics predict alpha (8-12 Hz) and delta (1-4 Hz) rhythms. We predicted moment-by-moment EEG power from fMRI activity in held-out subjects, and found that information about alpha power was represented by a remarkably small set of regions, segregated in two distinct networks linked to arousal and visual systems. Conversely, delta rhythms were diffusely represented on a large spatial scale across the cortex. These results identify distributed networks that predict delta and alpha rhythms, and establish a computational framework for investigating fMRI brainwide dynamics underlying EEG oscillations.

Improved machine learning algorithm for predicting ground state properties.

Finding the ground state of a quantum many-body system is a fundamental problem in quantum physics. In this work, we give a classical machine learning (ML) algorithm for predicting ground state properties with an inductive bias encoding geometric locality. The proposed ML model can efficiently predict ground state properties of an n-qubit gapped local Hamiltonian after learning from only [Formula: see text] data about other Hamiltonians in the same quantum phase of matter. This improves substantially upon previous results that require [Formula: see text] data for a large constant c. Furthermore, the training and prediction time of the proposed ML model scale as [Formula: see text] in the number of qubits n. Numerical experiments on physical systems with up to 45 qubits confirm the favorable scaling in predicting ground state properties using a small training dataset.

Current Understanding of the Anatomy, Physiology, and Magnetic Resonance Imaging of Neurofluids: Update From the 2022 "ISMRM Imaging Neurofluids Study group" Workshop in Rome.

Neurofluids is a term introduced to define all fluids in the brain and spine such as blood, cerebrospinal fluid, and interstitial fluid. Neuroscientists in the past millennium have steadily identified the several different fluid environments in the brain and spine that interact in a synchronized harmonious manner to assure a healthy microenvironment required for optimal neuroglial function. Neuroanatomists and biochemists have provided an incredible wealth of evidence revealing the anatomy of perivascular spaces, meninges and glia and their role in drainage of neuronal waste products. Human studies have been limited due to the restricted availability of noninvasive imaging modalities that can provide a high spatiotemporal depiction of the brain neurofluids. Therefore, animal studies have been key in advancing our knowledge of the temporal and spatial dynamics of fluids, for example, by injecting tracers with different molecular weights. Such studies have sparked interest to identify possible disruptions to neurofluids dynamics in human diseases such as small vessel disease, cerebral amyloid angiopathy, and dementia. However, key differences between rodent and human physiology should be considered when extrapolating these findings to understand the human brain. An increasing armamentarium of noninvasive MRI techniques is being built to identify markers of altered drainage pathways. During the three-day workshop organized by the International Society of Magnetic Resonance in Medicine that was held in Rome in September 2022, several of these concepts were discussed by a distinguished international faculty to lay the basis of what is known and where we still lack evidence. We envision that in the next decade, MRI will allow imaging of the physiology of neurofluid dynamics and drainage pathways in the human brain to identify true pathological processes underlying disease and to discover new avenues for early diagnoses and treatments including drug delivery. Evidence level: 1 Technical Efficacy: Stage 3.

Accelerating Nature: Induced Atomic Order in Equiatomic FeNi.

The production of locally atomically ordered FeNi (known by its meteoric mineral name, tetrataenite) is confirmed in bulk samples by simultaneous conversion X-ray and backscattered γ-ray 57 Fe Mössbauer spectroscopy. Up to 22 volume percent of the tetragonal tetrataenite phase is quantified in samples thermally treated under simultaneous magnetic- and stress-field conditions for a period of 6 weeks, with the remainder identified as the cubic FeNi alloy. In contrast, all precursor samples consist only of the cubic FeNi alloy. Data from the processed alloys are validated using Mössbauer parameters derived from natural meteoritic tetrataenite. The meteoritic tetrataenite exhibits a substantially higher degree of atomic order than do the processed samples, consistent with their low uniaxial magnetocrystalline anisotropy energy of ≈1 kJ·m-3 . These results suggest that targeted refinements to the processing conditions of FeNi will foster greater atomic order and increased magnetocrystalline anisotropy, leading to an enhanced magnetic energy product. These outcomes also suggest that deductions concerning paleomagnetic conditions of the solar system, as derived from meteoritic data, may warrant re-examination and re-evaluation. Additionally, this work strengthens the argument that tetrataenite may indeed become a member of the advanced permanent magnet portfolio, helping to meet rapidly escalating green energy imperatives.

Bonobos and chimpanzees remember familiar conspecifics for decades.

Recognition and memory of familiar conspecifics provides the foundation for complex sociality and is vital to navigating an unpredictable social world [Tibbetts and Dale, Trends Ecol. Evol. 22, 529-537 (2007)]. Human social memory incorporates content about interactions and relationships and can last for decades [Sherry and Schacter, Psychol. Rev. 94, 439-454 (1987)]. Long-term social memory likely played a key role throughout human evolution, as our ancestors increasingly built relationships that operated across distant space and time [Malone et al., Int. J. Primatol. 33, 1251-1277 (2012)]. Although individual recognition is widespread among animals and sometimes lasts for years, little is known about social memory in nonhuman apes and the shared evolutionary foundations of human social memory. In a preferential-looking eye-tracking task, we presented chimpanzees and bonobos (N = 26) with side-by-side images of a previous groupmate and a conspecific stranger of the same sex. Apes' attention was biased toward former groupmates, indicating long-term memory for past social partners. The strength of biases toward former groupmates was not impacted by the duration apart, and our results suggest that recognition may persist for at least 26 y beyond separation. We also found significant but weak evidence that, like humans, apes may remember the quality or content of these past relationships: apes' looking biases were stronger for individuals with whom they had more positive histories of social interaction. Long-lasting social memory likely provided key foundations for the evolution of human culture and sociality as they extended across time, space, and group boundaries.

Application of micro capillary blood sampling in an anti-doping setting.

Blood collection is an important facet of anti-doping testing, forming the basis of the Athlete Biological Passport (ABP). Traditional blood collection via venipuncture can be uncomfortable for athletes, especially those who are tested frequently or close to competition. Athletes may also have negative perceptions of venipuncture due to past experiences or the risks of adverse health events such as bruising, hematomas, syncope, and general discomfort that has the potential to affect performance. Advances in capillary whole blood collection technology now affords the ability to collect micro-volumetric capillary whole blood from the upper arm (or other suitable vascular location such as the abdomen) that is "needle-free" and virtually painless using devices such as the Tasso+. The present study extends previous work, by collecting microliter capillary whole blood samples via the Tasso+ EDTA device in an official anti-doping setting prior to competition, as well as requiring temperature-monitored cold chain shipping by air to the laboratory before analysis. Fifty-eight matched capillary and venous blood samples were collected under official doping control conditions by certified Doping Control Officers. No impact of sample shipment by air under cool conditions was observed on sample integrity. Provided that no visible clots were identified prior to analysis, capillary and venous blood samples showed excellent laboratory agreement for all CBC parameters, with the exception of platelets. Micro capillary blood collection provides a valid alternative to venous blood collection for ABP purposes, with the advantage of providing a more athlete-friendly experience, particularly close to competition.

Detection of capromorelin in urine following oral and dermal routes of administration.

Capromorelin is a growth hormone secretagogue. Despite promising results to alleviate muscle-wasting in the elderly, it has not advanced further in human development. Subsequent studies demonstrated capromorelin's ability to increase food intake in animals, leading to approval in the United States and Europe as an appetite stimulant for cats (Elura) and dogs (Entyce). Capromorelin is prohibited in sports due to its ability to stimulate growth hormone production and enhance performance. However, given that its veterinary preparation is formulated as a highly concentrated solution (20 or 30 mg/mL) delivered orally, incidental ingestion or dermal absorption may result in an adverse analytical finding (AAF) by way of direct exposure during oral administration to a pet. An administration study was conducted by either oral or transdermal application of capromorelin solution to mimic the scenario of inadvertent exposure to the drug. Ingestion of 30 µg of capromorelin orally (equivalent to 1 µL of Entyce) resulted in detectable amounts of capromorelin in urine for up to 48 h after administration with a maximum urinary concentration of 7 ng/mL. Importantly, when applied directly to the skin on the hands in larger quantities mimicking a pet administration exposure scenario (30 mg or 1 mL of Entyce), capromorelin was also detected reaching a maximum urinary concentration of 0.7 ng/mL. Athletes and testing authorities should be aware of the risk of an AAF arising due to incidental exposure to veterinary preparations of capromorelin. To our knowledge, before 2022, no positive test for capromorelin had ever been reported.

Differential cortical and subcortical visual processing with eyes shut.

Closing our eyes largely shuts down our ability to see. That said, our eyelids still pass some light, allowing our visual system to coarsely process information about visual scenes, such as changes in luminance. However, the specific impact of eye closure on processing within the early visual system remains largely unknown. To understand how visual processing is modulated when eyes are shut, we used functional magnetic resonance imaging (fMRI) to measure responses to a flickering visual stimulus at high (100%) and low (10%) temporal contrasts, while participants viewed the stimuli with their eyes open or closed. Interestingly, we discovered that eye closure produced a qualitatively distinct pattern of effects across the visual thalamus and visual cortex. We found that with eyes open, low temporal contrast stimuli produced smaller responses, across the lateral geniculate nucleus (LGN), primary (V1) and extrastriate visual cortex (V2). However, with eyes closed, we discovered that the LGN and V1 maintained similar BOLD responses as the eyes open condition, despite the suppressed visual input through the eyelid. In contrast, V2 and V3 had strongly attenuated BOLD response when eyes were closed, regardless of temporal contrast. Our findings reveal a qualitative distinct pattern of visual processing when the eyes are closed - one that is not simply an overall attenuation, but rather reflects distinct responses across visual thalamocortical networks, wherein the earliest stages of processing preserves information about stimuli but is then gated off downstream in visual cortex.

John B. Goodenough (1922-2023).

A giant in the fields of solid-state chemistry and physics.

Resting-state fMRI signals contain spectral signatures of local hemodynamic response timing.

Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here, we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, because differences in fMRI frequency content can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics.

Functional magnetic resonance imaging (fMRI) is a tool that can be used to non-invasively measure the activity of the human brain. Active parts of the brain require more oxygen, which increases blood flow to these areas. fMRI can detect these changes, and its signal reflects the coupling between brain activity and changes in blood flow. The mechanism that couples brain activity to blood flow is known as the 'hemodynamic response', and its timing varies across the brain. Therefore, to interpret fMRI signals correctly and use them to measure underlying brain activity, it is necessary to understand how the response changes across the brain. Current methods for probing hemodynamic response variation are either limited to specific brain regions or require patients to hold their breath ­ something not all groups of patients can do. To solve this problem, Bailes et al. investigated whether resting-state fMRI signals contain information about how the hemodynamic response changes across the brain. This information could then be used to better infer brain activity from fMRI measurements. The experiments showed that resting-state fMRI signals can be used to characterize and predict the timing of the hemodynamic response. Specifically, the frequencies in resting-state fMRI signals are impacted by changes in the hemodynamic response and can therefore be used to predict hemodynamic timing. Additionally, Bailes et al. showed that these predictions are better than those obtained in experiments requiring patients to hold their breath, which is the current gold standard. The findings also demonstrate that the information from the frequencies of resting-state fMRI signals should be interpreted carefully, as differences in these frequencies can have a non-neural origin. Bailes et al. propose a highly generalizable approach for mapping and predicting variations of the hemodynamic response across the whole brain. These findings provide insights into the time-related properties of fMRI signals that are crucial for accurate analyses. This will be of particular importance as the field moves towards fMRI studies focused on rapid neural dynamics and higher-level cognition.

Enhancing Biocidal Capability in Cuprite Coatings.

The SARS-CoV-2 global pandemic has reinvigorated interest in the creation and widespread deployment of durable, cost-effective, and environmentally benign antipathogenic coatings for high-touch public surfaces. While the contact-kill capability and mechanism of metallic copper and its alloys are well established, the biocidal activity of the refractory oxide forms remains poorly understood. In this study, commercial cuprous oxide (Cu2O, cuprite) powder was rapidly nanostructured using high-energy cryomechanical processing. Coatings made from these processed powders demonstrated a passive "contact-kill" response to Escherichia coli (E. coli) bacteria that was 4× (400%) faster than coatings made from unprocessed powder. No viable bacteria (>99.999% (5-log10) reduction) were detected in bioassays performed after two hours of exposure of E. coli to coatings of processed cuprous oxide, while a greater than 99% bacterial reduction was achieved within 30 min of exposure. Further, these coatings were hydrophobic and no external energy input was required to activate their contact-kill capability. The upregulated antibacterial response of the processed powders is positively correlated with extensive induced crystallographic disorder and microstrain in the Cu2O lattice accompanied by color changes that are consistent with an increased semiconducting bandgap energy. It is deduced that cryomilling creates well-crystallized nanoscale regions enmeshed within the highly lattice-defective particle matrix. Increasing the relative proportion of lattice-defective cuprous oxide exposed to the environment at the coating surface is anticipated to further enhance the antipathogenic capability of this abundant, inexpensive, robust, and easily handled material for wider application in contact-kill surfaces.

Beyond the symptom: the biology of fatigue.

A workshop titled "Beyond the Symptom: The Biology of Fatigue" was held virtually September 27-28, 2021. It was jointly organized by the Sleep Research Society and the Neurobiology of Fatigue Working Group of the NIH Blueprint Neuroscience Research Program. For access to the presentations and video recordings, see: https://neuroscienceblueprint.nih.gov/about/event/beyond-symptom-biology-fatigue. The goals of this workshop were to bring together clinicians and scientists who use a variety of research approaches to understand fatigue in multiple conditions and to identify key gaps in our understanding of the biology of fatigue. This workshop summary distills key issues discussed in this workshop and provides a list of promising directions for future research on this topic. We do not attempt to provide a comprehensive review of the state of our understanding of fatigue, nor to provide a comprehensive reprise of the many excellent presentations. Rather, our goal is to highlight key advances and to focus on questions and future approaches to answering them.

The impact of the human thalamus on brain-wide information processing.

The thalamus is a small, bilateral structure in the diencephalon that integrates signals from many areas of the CNS. This critical anatomical position allows the thalamus to influence whole-brain activity and adaptive behaviour. However, traditional research paradigms have struggled to attribute specific functions to the thalamus, and it has remained understudied in the human neuroimaging literature. Recent advances in analytical techniques and increased accessibility to large, high-quality data sets have brought forth a series of studies and findings that (re-)establish the thalamus as a core region of interest in human cognitive neuroscience, a field that otherwise remains cortico-centric. In this Perspective, we argue that using whole-brain neuroimaging approaches to investigate the thalamus and its interaction with the rest of the brain is key for understanding systems-level control of information processing. To this end, we highlight the role of the thalamus in shaping a range of functional signatures, including evoked activity, interregional connectivity, network topology and neuronal variability, both at rest and during the performance of cognitive tasks.