Cancer progression is an example of a rapid adaptive process where evolving new traits is essential for survival and requires a high mutation rate. Precancerous cells acquire a few key mutations that ...drive rapid population growth and carcinogenesis. Cancer genomics demonstrates that these few driver mutations occur alongside thousands of random passenger mutations—a natural consequence of cancer's elevated mutation rate. Some passengers are deleterious to cancer cells, yet have been largely ignored in cancer research. In population genetics, however, the accumulation of mildly deleterious mutations has been shown to cause population meltdown. Here we develop a stochastic population model where beneficial drivers engage in a tug-of-war with frequent mildly deleterious passengers. These passengers present a barrier to cancer progression describable by a critical population size, below which most lesions fail to progress, and a critical mutation rate, above which cancers melt down. We find support for this model in cancer age-incidence and cancer genomics data that also allow us to estimate the fitness advantage of drivers and fitness costs of passengers. We identify two regimes of adaptive evolutionary dynamics and use these regimes to understand successes and failures of different treatment strategies. A tumor's load of deleterious passengers can explain previously paradoxical treatment outcomes and suggest that it could potentially serve as a biomarker of response to mutagenic therapies. The collective deleterious effect of passengers is currently an unexploited therapeutic target. We discuss how their effects might be exacerbated by current and future therapies.
Cancer progression is driven by the accumulation of a small number of genetic alterations. However, these few driver alterations reside in a cancer genome alongside tens of thousands of additional ...mutations termed passengers. Passengers are widely believed to have no role in cancer, yet many passengers fall within protein-coding genes and other functional elements that can have potentially deleterious effects on cancer cells. Here we investigate the potential of moderately deleterious passengers to accumulate and alter the course of neoplastic progression. Our approach combines evolutionary simulations of cancer progression with an analysis of cancer sequencing data. From simulations, we find that passengers accumulate and largely evade natural selection during progression. Although individually weak, the collective burden of passengers alters the course of progression, leading to several oncological phenomena that are hard to explain with a traditional driver-centric view. We then tested the predictions of our model using cancer genomics data and confirmed that many passengers are likely damaging and have largely evaded negative selection. Finally, we use our model to explore cancer treatments that exploit the load of passengers by either (i) increasing the mutation rate or (ii) exacerbating their deleterious effects. Though both approaches lead to cancer regression, the latter is a more effective therapy. Our results suggest a unique framework for understanding cancer progression as a balance of driver and passenger mutations.
Background
The aim of this communication is to pay tribute to a nursing pioneer of our time, Professor Serara Kupe‐Mogwe, for her outstanding contribution to development of the nursing profession in ...Botswana. I pay this tribute in response to the World Health Organization’s declaration of 2020 as the Year of the Nurse and the Midwife.
Methods
Data supporting this manuscript were obtained through Internet searches, local newspapers, and interviews with those who knew her.
Results
Kupe‐Mogwe’s contributions to nursing in Botswana are presented.
Conclusion
The legacy she has left is celebrated and should be remembered.
Implications for Nursing and/or Health policy
The findings have implications for nursing education, nursing leadership, and acknowledgment of women and their contribution.
Objective: Electromyogram (EMG) contamination is often a problem in electroencephalogram (EEG) recording, particularly, for those applications such as EEG-based brain–computer interfaces that rely on ...automated measurements of EEG features. As an essential prelude to developing methods for recognizing and eliminating EMG contamination of EEG, this study defines the spectral and topographical characteristics of frontalis and temporalis muscle EMG over the entire scalp. It describes both average data and the range of individual differences.
Methods: In 25 healthy adults, signals from 64 scalp and 4 facial locations were recorded during relaxation and during defined (15, 30, or 70% of maximum) contractions of frontalis or temporalis muscles.
Results: In the average data, EMG had a broad frequency distribution from 0 to >200 Hz. Amplitude was greatest at 20–30 Hz frontally and 40–80 Hz temporally. Temporalis spectra also showed a smaller peak around 20 Hz. These spectral components attenuated and broadened centrally. Even with weak (15%) contraction, EMG was detectable (
P<0.001) near the vertex at frequencies >12 Hz in the average data and >8 Hz in some individuals.
Conclusions: Frontalis or temporalis muscle EMG recorded from the scalp has spectral and topographical features that vary substantially across individuals. EMG spectra often have peaks in the beta frequency range that resemble EEG beta peaks.
Significance: While EMG contamination is greatest at the periphery of the scalp near the active muscles, even weak contractions can produce EMG that obscures or mimics EEG alpha, mu, or beta rhythms over the entire scalp. Recognition and elimination of this contamination is likely to require recording from an appropriate set of peripheral scalp locations.
A detailed wavelength-scanned surface-enhanced Raman excitation spectroscopy (WS SERES) study of benzenethiol adsorbed on Ag nanoparticle arrays, fabricated by nanosphere lithography (NSL), is ...presented. These NSL-derived Ag nanoparticle array surfaces are both structurally well-characterized and extremely uniform in size. The WS SERES spectra are correlated, both spatially and spectrally, with the corresponding localized surface plasmon resonance (LSPR) spectra of the nanoparticle arrays. The surface-enhanced Raman scattering (SERS) spectra were measured in two excitation wavelength ranges: (1) 425−505 nm, and (2) 610−800 nm, as well as with the 532-nm line from a solid-state diode-pumped laser. The WS SERES spectra have line shapes similar to those of the LSPR spectra. The maximum SERS enhancement factor is shown to occur for excitation wavelengths that are blue-shifted with respect to the LSPR λmax of adsorbate-covered nanoparticle arrays. Three vibrational modes of benzenethiol (1575, 1081, and 1009 cm-1) are studied simultaneously on one substrate, and it is demonstrated that the smaller Raman shifted peak shows a maximum enhancement closer to the LSPR λmax than that of a larger Raman shifted peak. This is in agreement with the predictions of the electromagnetic (EM) enhancement mechanism of SERS. Enhancement factors of up to ∼108 are achieved, which is also in good agreement with our previous SERES studies.
People with severe motor disabilities can maintain an acceptable quality of life if they can communicate. Brain-computer interfaces (BCIs), which do not depend on muscle control, can provide ...communication. Four people severely disabled by ALS learned to operate a BCI with EEG rhythms recorded over sensorimotor cortex. These results suggest that a sensorimotor rhythm-based BCI could help maintain quality of life for people with ALS.
Genomic instability and high mutation rates cause cancer to acquire numerous mutations and chromosomal alterations during its somatic evolution; most are termed passengers because they do not confer ...cancer phenotypes. Evolutionary simulations and cancer genomic studies suggest that mildly deleterious passengers accumulate and can collectively slow cancer progression. Clinical data also suggest an association between passenger load and response to therapeutics, yet no causal link between the effects of passengers and cancer progression has been established. To assess this, we introduced increasing passenger loads into human cell lines and immunocompromised mouse models. We found that passengers dramatically reduced proliferative fitness (∼3% per Mb), slowed tumor growth, and reduced metastatic progression. We developed new genomic measures of damaging passenger load that can accurately predict the fitness costs of passengers in cell lines and in human breast cancers. We conclude that genomic instability and an elevated load of DNA alterations in cancer is a double-edged sword: it accelerates the accumulation of adaptive drivers, but incurs a harmful passenger load that can outweigh driver benefit. The effects of passenger alterations on cancer fitness were unrelated to enhanced immunity, as our tests were performed either in cell culture or in immunocompromised animals. Our findings refute traditional paradigms of passengers as neutral events, suggesting that passenger load reduces the fitness of cancer cells and slows or prevents progression of both primary and metastatic disease. The antitumor effects of chemotherapies can in part be due to the induction of genomic instability and increased passenger load.
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We perform nonlinear system identification (NSI) of the effects of frictional connections in the dynamics of a bolted beam assembly. The methodology utilized in this work combines experimental ...measurements with slow-flow dynamic analysis and empirical mode decomposition, and reconstructs the dynamics through reduced-order models. These are in the form of single-degree-of-freedom linear oscillators (termed intrinsic modal oscillators—IMOs) with forcing terms derived directly from the experimental measurements through slow-flow analysis. The derived reduced order models are capable of reproducing the measured dynamics, whereas the forcing terms provide important information about nonlinear damping effects. The NSI methodology is applied to model nonlinear friction effects in a bolted beam assembly. A ‘monolithic’ beam with identical geometric and material properties is also tested for comparison. Three different forcing (energy) levels were considered in the tests in order to study the energy-dependencies of the damping nonlinearities induced in the beam from the bolted joint. In all cases, the NSI methodology employed was successful in identifying the damping nonlinearities, their spatial distributions and their effects of the vibration modes of the structural component.
•Nonlinear system identification of a bolted beam assembly is performed.•Reduced order models with forcing are developed to reproduce experimental data.•The forcing terms are derived directly from the measured dynamics.•The forcing terms provide important information about nonlinear friction effects.•The damping nonlinearities, and their modal and spatial distributions are identified.
This study examines the effects of expanding the classical P300 feature space on the classification performance of data collected from a P300 speller paradigm Farwell LA, Donchin E. Talking off the ...top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroenceph Clin Neurophysiol 1988;70:510–23. Using stepwise linear discriminant analysis (SWLDA) to construct a classifier, the effects of spatial channel selection, channel referencing, data decimation, and maximum number of model features are compared with the intent of establishing a baseline not only for the SWLDA classifier, but for related P300 speller classification methods in general. By supplementing the classical P300 recording locations with posterior locations, online classification performance of P300 speller responses can be significantly improved using SWLDA and the favorable parameters derived from the offline comparative analysis.
•We describe a new method for optimizing EMD using wavelet transforms.•The method drastically reduces the effect of mode-mixing.•The method’s success and robustness is studied using a two-component ...signal.•We extract IMFs that representative of the NNMs for a beam with local nonlinearity.•The IMFs are used to prove the existence of a 3:1 internal resonance.•Energy-dependent periodic solutions are constructed using the IMFs.
Empirical mode decomposition (EMD) is a powerful technique for separating the transient responses of nonlinear and nonstationary systems into finite sets of nearly orthogonal components, called intrinsic mode functions (IMFs), which represent the dynamics on different characteristic time scales. However, a deficiency of EMD is the mixing of two or more components in a single IMF, which can drastically affect the physical meaning of the empirical decomposition results. In this paper, we present a new approached based on EMD, designated as wavelet-bounded empirical mode decomposition (WBEMD), which is a closed-loop, optimization-based solution to the problem of mode mixing. The optimization routine relies on maximizing the isolation of an IMF around a characteristic frequency. This isolation is measured by fitting a bounding function around the IMF in the frequency domain and computing the area under this function. It follows that a large (small) area corresponds to a poorly (well) separated IMF. An optimization routine is developed based on this result with the objective of minimizing the bounding-function area and with the masking signal parameters serving as free parameters, such that a well-separated IMF is extracted. As examples of application of WBEMD we apply the proposed method, first to a stationary, two-component signal, and then to the numerically simulated response of a cantilever beam with an essentially nonlinear end attachment. We find that WBEMD vastly improves upon EMD and that the extracted sets of IMFs provide insight into the underlying physics of the response of each system.
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