Acute Effects of Dry Needling on Myofascial Trigger Points in the Triceps Surae of Ballet Dancers: A Pilot Randomized Controlled Trial

# Background There is convincing evidence that dancers suffer injuries to the triceps surae musculature. Research on the immediate effects of dry needling (DN) is limited, and it is important to understand the acute effects of this treatment prior to performance. # Purpose The purpose of this pilot study was to assess the immediate effects of DN on myofascial trigger points in terms of skin surface temperature, pain, active and passive range of motion, and torque production in the triceps surae of ballet dancers. # Study Design Randomized, double-blinded pilot study # Methods Professional ballet dancers that fit inclusion and exclusion criteria (n=11) were randomly assigned to an experimental or control group. The dancers had three pre-determined standard point (SP) measurement spots that were used as a baseline for surface temperature comparisons. The dancers were also palpated for trigger point (TP) spots. Both SP and TP spots were marked for future measurements. The experimental group received DN, while the control group received sham DN (SHAM) to their bilateral calves at the TP spots. Immediately prior to and following treatment, both DN and SHAM groups were tested for skin surface temperature, pain, range of motion, and plantar flexion torque by blinded assessors. Paired t-tests and independent t-tests were performed to examine for differences between groups. # Results The surface temperature for the TP was higher than the SP measurements prior to intervention (Right calf p= .014; Left calf p= .031). There were no significant changes in VAS scale reported pain and ROM. The plantar flexion torque measurements showed an increase in the DN group of the left calf at the angular velocity of 60 degrees/sec. # Conclusion This was a unique pilot study examining the acute effects of DN on professional ballet dancers. The results were limited due to low sample size. However, the methodology for this study and surface temperature results invites future research. # Level of evidence Level 1

Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics

Timm W, Scherbart A, Boecker S, Kohlbacher O, Nattkemper TW. Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. BMC Bioinformatics. 2008;9(1):443.Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides and proteins, however, is the fact that absolute quantification is severely hampered by the unclear relationship between the observed peak intensity and the peptide concentration in the sample. While there are numerous approaches to circumvent this problem experimentally (e. g. labeling techniques), reliable prediction of the peak intensities from peptide sequences could provide a peptide-specific correction factor. Thus, it would be a valuable tool towards label-free absolute quantification. Results: In this work we present machine learning techniques for peak intensity prediction for MALDI mass spectra. Features encoding the peptides' physico-chemical properties as well as string-based features were extracted. A feature subset was obtained from multiple forward feature selections on the extracted features. Based on these features, two advanced machine learning methods (support vector regression and local linear maps) are shown to yield good results for this problem (Pearson correlation of 0.68 in a ten-fold cross validation). Conclusion: The techniques presented here are a useful first step going beyond the binary prediction of proteotypic peptides towards a more quantitative prediction of peak intensities. These predictions in turn will turn out to be beneficial for mass spectrometry-based quantitative proteomics

Selectivity Map for Molecular Beam Epitaxy of Advanced III-V Quantum Nanowire Networks

This is an open access article published under an ACS AuthorChoice License. See Standard ACS AuthorChoice/Editors' Choice Usage Agreement - https://pubs.acs.org/page/policy/authorchoice_termsofuse.htmlSelective-area growth is a promising technique for enabling of the fabrication of the scalable III-V nanowire networks required to test proposals for Majorana-based quantum computing devices. However, the contours of the growth parameter window resulting in selective growth remain undefined. Herein, we present a set of experimental techniques that unambiguously establish the parameter space window resulting in selective III-V nanowire networks growth by molecular beam epitaxy. Selectivity maps are constructed for both GaAs and InAs compounds based on in situ characterization of growth kinetics on GaAs(001) substrates, where the difference in group III adatom desorption rates between the III-V surface and the amorphous mask area is identified as the primary mechanism governing selectivity. The broad applicability of this method is demonstrated by the successful realization of high-quality InAs and GaAs nanowire networks on GaAs, InP, and InAs substrates of both (001) and (111)B orientations as well as homoepitaxial InSb nanowire networks. Finally, phase coherence in Aharonov-Bohm ring experiments validates the potential of these crystals for nanoelectronics and quantum transport applications. This work should enable faster and better nanoscale crystal engineering over a range of compound semiconductors for improved device performance

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three genomic nomenclature systems to all sequence data from the World Health Organization European Region available until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation, compare the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong