SUMMARY ANSWER: High-throughput flagellar waveform tracking and analysis enable measurement of experimentally intractable quantities such as energy dissipation, disturbance of the surrounding medium and viscous stresses, which are not possible by tracking the sperm head alone.
WHAT IS KNOWN ALREADY: The clinical gold standard for sperm motility analysis comprises a manual analysis by a trained professional, with existing automated sperm diagnostics [computer-aided sperm analysis (CASA)] relying on tracking the sperm head and extrapolating measures. It is not currently possible with either of these approaches to track the sperm flagellar waveform for large numbers of cells in order to unlock the potential wealth of information enclosed within.
STUDY DESIGN, SIZE, DURATION: The software tool in this manuscript has been developed to enable high-throughput, repeatable, accurate and verifiable analysis of the sperm flagellar beat.
PARTICIPANTS/MATERIALS, SETTING, METHODS: Using the software tool [Flagellar Analysis and Sperm Tracking (FAST)] described in this manuscript, we have analysed 176 experimental microscopy videos and have tracked the head and flagellum of 205 progressive cells in diluted semen (DSM), 119 progressive cells in a high-viscosity medium (HVM) and 42 stuck cells in a low-viscosity medium. Unscreened donors were recruited at Birmingham Women's and Children's NHS Foundation Trust after giving informed consent.
MAIN RESULTS AND THE ROLE OF CHANCE: We describe fully automated tracking and analysis of flagellar movement for large cell numbers. The analysis is demonstrated on freely motile cells in low- and high-viscosity fluids and validated on published data of tethered cells undergoing pharmacological hyperactivation. Direct analysis of the flagellar beat reveals that the CASA measure 'beat cross frequency' does not measure beat frequency; attempting to fit a straight line between the two measures gives ${\mathrm{R}}^2$ values of 0.042 and 0.00054 for cells in DSM and HVM, respectively. A new measurement, track centroid speed, is validated as an accurate differentiator of progressive motility. Coupled with fluid mechanics codes, waveform data enable extraction of experimentally intractable quantities such as energy dissipation, disturbance of the surrounding medium and viscous stresses. We provide a powerful and accessible research tool, enabling connection of the mechanical activity of the sperm to its motility and effect on its environment.
LARGE SCALE DATA: The FAST software package and all documentation can be downloaded from www.flagellarCapture.com.
LIMITATIONS, REASONS FOR CAUTION: The FAST software package has only been tested for use with negative phase contrast microscopy. Other imaging modalities, with bright cells on a dark background, have not been tested but may work. FAST is not designed to analyse raw semen; it is specifically for precise analysis of flagellar kinematics, as that is the promising area for computer use. Flagellar capture will always require that cells are at a dilution where their paths do not frequently cross.
WIDER IMPLICATIONS OF THE FINDINGS: Combining tracked flagella with mathematical modelling has the potential to reveal new mechanistic insight. By providing the capability as a free-to-use software package, we hope that this ability to accurately quantify the flagellar waveform in large populations of motile cells will enable an abundant array of diagnostic, toxicological and therapeutic possibilities, as well as creating new opportunities for assessing and treating male subfertility.
STUDY FUNDING/COMPETING INTEREST(S): M.T.G., G.C., J.C.K-B. and D.J.S. gratefully acknowledge funding from the Engineering and Physical Sciences Research Council, Healthcare Technologies Challenge Award (Rapid Sperm Capture EP/N021096/1). J.C.K-B. is funded by a National Institute of Health Research (NIHR) and Health Education England, Senior Clinical Lectureship Grant: The role of the human sperm in healthy live birth (NIHRDH-HCS SCL-2014-05-001). This article presents independent research funded in part by the NIHR and Health Education England. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The data for experimental set (2) were funded through a Wellcome Trust-University of Birmingham Value in People Fellowship Bridging Award (E.H.O.).The authors declare no competing interests.
MATERIAL AND METHODS: The three-dimensional (3D) finite element program (ANSYS software) was used to construct the mathematical model. Two 5-unit FPD'S were simulated, one with rigid connector and another one with nonrigid connector. For analysis, each of these models were subjected to axial and oblique forces under progressive loading (180, 180, 120, 120, 80 N force on first and second molars, premolars and canine respectively) and simultaneous loading (100, 100, 100, 100, 100 N force on first and second molars, premolars and canine respectively).
RESULTS: The rigid and nonrigid connector design have effect on stress distribution in 5-unit FPDs with pier abutments.
CONCLUSION: Oblique forces produce more stresses than vertical forces. Nonrigid connector resulted in decrease in stress at the level of prosthesis and increase in stress at the level of alveolar crest.
METHODS: MMG and EMG were used to record the activity of the SCM in 32 untrained singers reciting a monotonous text and a standard folk song. Their voices were recorded and their pitch, or fundamental frequency (FF), and intensity were derived using Praat software. Instants of inhale and exhales were identified during singing from their voice recordings and the corresponding SCM MMG and EMG activities were analysed.
RESULTS: The SCM MMG, and EMG signals during breathing while singing were significantly different than breathing at rest (p < 0.001). On the other hand, MMG was relatively better correlated to voice intensity in both reading and singing than EMG. EMG was better, but not significantly, correlated with FF in both reading and singing as compared to MMG.
CONCLUSIONS: This study established MMG and EMG as the quantitative measurement tool to monitor breathing activities during singing. This is useful for applications related to singing therapy performance measure including potentially pathologically effected population. While the MMG and EMG could not distinguish FF and intensity significantly, it is useful to serve as a proxy of inhalation and exhalation levels throughout a particular singing session. Further studies are required to determine its efficacy in a therapeutic setting.