Many organisms coordinate rhythmic motor actions with those of a partner to generate cooperative social behavior such as duet singing. The neural mechanisms that enable rhythmic interindividual coordination of motor actions are unknown. Here we investigate the neural basis of vocal duetting behavior by using an approach that enables simultaneous recordings of individual vocalizations and multiunit vocal premotor activity in songbird pairs ranging freely in their natural habitat. We find that in the duet-initiating bird, the onset of the partner’s contribution to the duet triggers a change in rhythm in the periodic neural discharges that are exclusively locked to the initiating bird’s own vocalizations. The resulting interindividually synchronized neural activity pattern elicits vocalizations that perfectly alternate between partners in the ongoing song. We suggest that rhythmic cooperative behavior requires exact interindividual coordination of premotor neural activity, which might be achieved by integration of sensory information originating from the interacting partner. Recording neural activity during coordinated behaviors in controlled environments limits opportunities for understanding natural interactions. Here, the authors record from freely moving duetting birds in their natural habitats to reveal the neural mechanisms of interindividual motor coordination. Avian duets show a high diversity in complexity and in precision of coordination between the partners’ vocal emissions. While in some bird species vocalizations from both duet partners temporally overlap to a variable degree4, other birds produce vocal duets in which the partners’ contributions alternate almost perfectly7. Growing evidence suggests that alternating vocalizations in avian duets are a direct result of the partners’ effort to avoid signal overlap8. Although the degree of temporal coordination of vocal activity seems to be an important indication of the function of duetting, temporal properties of avian duets have previously rarely been quantified in detail.Avian duetting is a rare phenomenon, which is mainly found among bird species of the southern hemisphere. Duet songs are generally defined as overlapping bouts of sounds produced by both members of a pairPlocepasser mahali, which is native to eastern and southern Africa. This cooperatively breeding species lives in mixed-sex groups consisting of a dominant breeding pair and up to eight subordinates10. All group members defend a year-round territory by producing highly coordinated duet and chorus songs throughout the day11. Duet songs of male and female P. mahali consist of introductory syllables sung by either of the partners and duet syllables emitted by both birds in a rapid but precisely timed fashion12. The temporal dynamics of male and female vocal productions during duetting are, however, unknown.A well-studied duetting songbird species is the white-browed sparrow-weaver, 13. In birds, the production of song is controlled by an interconnected network of sensory and premotor brain nuclei, the song-control system14. Nucleus HVC represents a major relay station within this distributed, recurrent network15, receives auditory information17, and generates temporally patterned premotor commands for vocal production20. During singing, individual HVC neurons are active at specific time points in the song without any temporal relation to certain parameters of single song elements, such as syllable onset21. In anesthetized songbirds, HVC neurons show selective responses to auditory presentations of the bird’s own vocalizations24. This pattern does not seem to apply to birds that are able to produce vocal duets. HVC neurons in anesthetized plain-tailed wrens (Pheugopedius euophrys), a songbird species known to sing well-coordinated duets, are not only responsive to the bird’s own part of the duet but also to the partner’s vocalizations. Most importantly, neurons in the wren’s HVC respond strongest to presentations of the complete duet sequence25. Fortune et al.25 suggest that the auditory information from both duet partners might be important for the precise coordination of vocalizations during duetting. This assumption can, however, only be tested by neural recordings in the HVC of actively duetting birds. In awake individuals of nonduetting songbird species, HVC activity is mainly premotor, and responses to auditory stimulation are suppressed during singing28. Only during nonsinging periods, HVC can be responsive to playbacks of the bird’s own song28. From this knowledge, two alternative scenarios arise that could be present in HVC during duetting: (1) As in most nonduetting songbirds, HVC in actively duetting birds only shows premotor activity correlated to the bird’s own vocal productions and is silent to auditory input, such as the partner’s contributions to the duet. (2) In contrast to nonduetting songbirds, HVC neurons in duetting birds show premotor activity when the bird itself is vocalizing and auditory activity to the partner’s vocalizations.Another large gap in knowledge exists regarding the neural mechanisms mediating the precise interindividual coordination of vocalizations during duetting29. Neurophysiological experiments are, however, usually conducted inside laboratories with caged animals limited in their ability to behave naturally30. Recent advances in the development of neurophysiological research methods have started to allow neural recordings in single laboratory animals behaving freely for a limited time within a confined outdoor area31. Here we present extracellular neural data that have been synchronously recorded for several days from pairs of socially interacting wild animals while they ranged completely free in their natural habitat. We exploited a self-developed radio-telemetric recording technique34 to investigate the neural basis of duet singing. We show that vocalizations in pairs of wild P. mahali precisely alternate during duetting. As in nonduetting birds, the neural activity in HVC of P. mahali is exclusively premotor during singing. The auditory information generated by the duet partner, however, alters the temporal parameters of HVC activity in the duet-initiating bird and thus enables the birds to alternate their vocalizations. We therefore conclude that in P. mahali, the integration of auditory information originating from the interacting partner mediates the precise interindividual coordination of vocal motor programs, which is required to generate precisely coordinated duet songs.Investigating the neural mechanisms that underlie an animal’s natural behavior is the fundamental aim of neuroethology32 onto the backs of both partners of the P. mahali pairs  shorter duration  than female syllables  longer duration  than female syllables  generally consisted of a doublet of male song elements separated by a short (median: 31.6 ms) interval of silence, female duet syllables always consisted of a single female song element. During the initiating part of the duet prior to the second bird’s song onset, male syllables were of significantly  higher vocal emission rates  than female duet-initiating syllables  than the variance in male duet syllable emission rates. Additional evidence for the lack of flexibility in vocal timing in males was provided by the male vs. female difference in the frequency of extensive syllable overlaps. Duetting birds sometimes temporally mismatched vocalizations, which resulted in a partial overlap between consecutive male and female duet syllables  larger (median: 11.4% and interquartile range: 5.6–27%) than syllable overlaps produced by female birds (median: 9.1% and interquartile range: 5.1–18.2%). In more detail, small overlaps of up to 7% of the duration of the preceding duet syllable were rather common in both sexes . Overlaps >20% of the duration of the preceding duet syllable were rare, but if present, they tended to be more often produced by male  than by female birds  longer duration (median: 214 ms and interquartile range: 192–260 ms) than duet syllables that were not overlapped (median: 199 ms and interquartile range: 180–223 ms). In contrast to overlaps, there was no difference in the frequency of gaps produced by male and female birds during duetting. In both the male to female and the female to male syllable transitions, short gaps between syllables were common, and long gaps were rare  after an overlap compared to the intervals between non-overlapped duet syllables.In accordance with the short duration of male duet-initiating syllables, these syllables were produced at significantly  lower rate  the onset of the partner’s preceding duet syllable, (B) the offset of the partner’s preceding duet syllable, or (C) the point in time when it has recognized the type of syllable the partner was currently vocalizing. In P. mahali of both sexes, we found the variance in partner-onset to own-onset latencies  to be significantly larger  than partner-offset to own-onset latencies . Locking one’s own syllable onset to the onset of the partner’s preceding syllable should, however, result in onset–onset latencies that vary only minimally. Therefore, we exclude hypothesis A. Although the less variable offset-onset latencies between male and female P. mahali duet syllables would support hypothesis B, the fact that the birds sometimes produced syllable overlaps (see above) led us to exclude this hypothesis too. To lock its own syllable onset to the point in time when a bird has recognized the partner’s preceding syllable type  requires each bird to have knowledge about the duration of each syllable type in the partner’s repertoire since latencies would depend on the duration of the partner’s preceding syllable. Syllable overlaps would be possible in cases when the duration of the partner’s preceding syllable exceeded the anticipated duration. After excluding two of the three proposed mechanisms, we suggest that to maintain vocal coordination during duetting, P. mahali adjust the time of syllable onset to the “expected” offset of the partner’s preceding syllable . One way to prove this hypothesis would be to perform syllable-type-specific analyses of P. mahali duets. Focusing on specific male–female syllable transitions eliminates variation in syllable duration and spectrotemporal composition and would therefore likely allow to determine the time point in the partner’s syllable to which a bird locks its own syllable onset. Owing to the large vocal repertoire of P. mahali, this type of analysis would, however, require a dataset comprised of several hundreds of duet songs for each pair of birds and is therefore subject of future research.Once initiated, the vocal coordination could either be maintained passively by each bird of a pair singing its own part of the duet with a temporally fixed pattern and without paying attention to the partner’s vocalizations or actively by both birds fine-tuning the timing of their vocalizations to those of the partner. The first mechanism would be highly prone to external disturbances; for example, slight variations in the song rhythm of one bird would result in a breakdown of coordination. The latter mechanism would, however, allow the birds to compensate for small temporal irregularities such as syllable overlaps. We, therefore, suggest that P. mahali, we conducted playback experiments, which included presentations of manipulated duet bouts (see “Methods”). Since our dataset was too small to enable a quantitative analysis, we present here only exemplary data. In response to the playback, the birds were highly agitated and immediately started to duet with each other , which produce a rhythmically timed pattern of premotor neural activityP. mahali raises the question of the neural substrates that enable the precise interindividual coordination of vocal productions in these birds. To find an answer to this question, we recorded extracellular neural activity in parallel with individual vocalizations during duetting in three wild P. mahali pairs in their natural habitat, the Kalahari savanna .Although the partner’s vocalizations did not result in auditory-evoked activity in HVC neurons, it might have been possible that this auditory input had modulating effects on premotor activity. We analyzed the spike rate during the production of duet syllables that were overlapped by the partner’s duet syllable and found that HVC activity was not affected by overlaps. In both the male and female HVC, the median spike rate during overlapped syllables  did not differ from the median spike rate during nonoverlapped syllables  that preceded or succeeded the overlap. Note that the difference in the median spike rate between male and female birds was not significant (one-sided Mann–Whitney p < 0.001) with the degree of interindividual synchronization of vocal activity  of neural signals was maximal at a median time shift of 255 ms  decrease in oscillation frequency of HVC activity in the duet-initiating bird right after the partner had joined the duet. During the initiating part of the duet, bursts of multiunit activity in the neural signal of male and female duet-initiating birds occurred at a median rate of 4.0 and 3.4 Hz, respectively, whereas the median burst rate dropped to 2.0 Hz in both sexes immediately after the partner started contributing to the duet  that can only be performed within a natural context.In contrast to conventional neurophysiological methods, our radio telemetric approach allows us to investigate the neural basis of an animal’s behavior under completely natural conditions. To date, neurophysiological studies have been conducted with laboratory animals that spend their lives in cages. The behavior of caged animals, however, very likely differs from that of free-living conspecifics as the latter regularly face situations due to weather conditions, hunger, or predation, which would never be experienced by laboratory animals and which probably have a very large impact on an animal’s natural behavior43. Our present study demonstrates that rhythmic social interactions that require temporal coordination are not just associated with a coherent oscillation of activity in large areas of both interacting partners’ brains43 but with an interindividually synchronized activation of small groups of neurons within the same brain nucleus in both partners. Our results strongly suggest a scenario in which the brains of two birds constitute a network that acts as a distributed circuit to organize the temporal pattern of vocal duets. We expect this to apply also to other rhythmic cooperative behaviors but experimental support provided by further dual-electrophysiological experiments in freely behaving animal models is required.Here we recorded individual vocalizations and premotor vocal activity in parallel from pairs of duetting birds to investigate how the precise interindividual coordination of motor activity during duet singing is neuronally controlled. Previous dual neuroimaging studies, performed in human subjects while they were engaged in rhythmic social interactions, showed that synchronized motor actions between subjects were accompanied by an overall synchronization of brain activity25. HVC neurons in awake and actively duetting P. mahali were, however, responsive to neither the partner’s vocalizations nor to playback of prerecorded duet bouts. It has been repeatedly shown that activity in the song-control system depends on the bird’s behavioral state46. Under anesthesia and during sleep, HVC neurons usually show strong, consistent, and highly selective auditory responses to presentations of the bird’s own vocalizations. In awake birds, however, if present, the strength of auditory responses in HVC is highly variable, and neurons are unselective for the bird’s own song. McCasland and Konishi47 reported for three different songbird species that auditory responses in HVC are completely suppressed by vocal motor activity during singing. More recently, Hamaguchi et al.48 demonstrated that, while auditory input failed to alter intracellular activity of HVC neurons during singing, the same cells responded to auditory stimulation when the bird ceased to vocalize. This may indicate that, also in the awake condition, HVC processes auditory information, but during singing, the output of this processing is subthreshold. In duetting P. mahali, we observed that auditory information generated by the partner’s syllables never elicited an auditory response but could trigger a change in vocalization rate in the duet-initiating bird. A similar observation has been made in duetting plain wrens (Cantorchilus modestus zeledoni), suggesting that vocal production in individuals who sing duets is controlled by autogenous and heterogeneous auditory feedback rather than by intrinsic fixed action patterns49. Further support for this hypothesis was provided by our finding that, during duetting, male P. mahali were able to compensate for syllable mismatches. This indicated that each bird listened to its own and the partner’s vocalizations to fine-tune the timing of vocalizations. We therefore suggest that, during duetting, the auditory information from the partner’s syllables is reaching HVC and is most likely used for the interindividual coordination of vocalizations in P. mahali. An alternative but less likely hypothesis is that, during duetting, HVC does not receive the “raw” auditory information generated by the partner but rather a premotor signal that is the result of auditory processing in downstream brain areas. Such a scenario has been demonstrated to exist in nonduetting songbirds to coordinate the premotor signals for song generated in the song-control system of both hemispheres in a way that the vocal organ is able to produce proper sounds50.Our results show that, as in most nonduetting songbirds, during singing HVC activity in duetting birds is locked to each individual’s own vocalizations. This strongly contrasts with what one would expect from the findings of a previous study in plain-tailed wrens. HVC neurons in anesthetized wrens differ in their activity pattern from that of most nonduetting songbirds by showing auditory-evoked activity not only to playbacks of the bird’s own vocalizations but also to presentations of the partners song and even further increasing their activity when stimulated with a combination of both the male and female parts of this species’ duet song53 (see ref. 4 for a contrary example). The leading role has been attributed to the bird of a pair that most frequently initiated duets53, produced overlaps most often2, determined the song rhythm4, i.e., showed less behavioral adaptation, or produced vocalizations that elicited the stronger neural responses in the HVC25. Our study, however, provides support for the assumption that male birds lead during duetting: (1) Duets were most often initiated by male P. mahali. (2) Vocal emission rates during duetting were less flexible in males than in females, which may indicate that the male was determining the song rhythm. (3) Male P. mahali produced duet syllable overlaps more often than females. Although it is well established that the emergence of leader and follower roles enhances the quality of group performance54, the factors that determine which partner adopts which role during joint actions are still not entirely clear. It has been suggested that the partner who maintains the rhythm becomes the leader and the partner who maintains the synchrony of the joint behavior becomes the follower, as maintaining synchrony requires greater adaptation55. Recently, a neural correlate of leader–follower distinctions has been described. Using dual-electroencephalogram measurements in two human participants who performed a synchronized tapping task, Konvalinka et al.56 showed that leaders but not followers exhibited a reduction in alpha and low-beta oscillations over motor and frontal areas, which may have reflected the increase in prospective planning and control required for maintaining the rhythm of joint actions57. Additional studies such as ours, which measure brain activity synchronously in pairs or groups of individuals during natural social interactions, are, however, essential to further the understanding of the neural mechanisms that underlie the coordination of joint actions.In most bird species that produce vocal duets, the females are assumed to lead during duettingP. mahali near the village of Black Rock, Northern Cape, South Africa  during February/March 2016 and November/December 2017. All investigated birds were color-banded for individual recognition. The birds were captured shortly after dusk (0800–1000 p.m.) inside their roosting nests. The sex was determined by bill color59. The male bird of all investigated pairs was likely the dominant male of the group, whereas the social status of female birds could not be determined reliably.We studied a population of wild P. mahali in Seewiesen, Germany, under permit 55.2-1-54-2532-175-2016 issued by the government of Upper Bavaria. After the initial experiments in Germany had proven that the birds only show short-term (up to a few hours) effects  while habituating to carrying the transmitters, and other aspects of their normal behavior  were not affected by the transmitters, we went to South Africa. In 2016, we only recorded the individual vocal behavior of wild P. mahali pairs with microphone transmitters. For these experiments, we received ethics approval from the University of Pretoria (permit: EC086-15). In 2017, we combined the vocal recordings with telemetric neural recordings. After paying special attention to pain management, to bird recapture, and to the possible effects of the transmitting devices on the birds’ behavior, for this second set of experiments, the University of Pretoria granted us ethics approval (permit: EC026-17) bound to additional obligations .All bird-capture permits were obtained from the Northern Cape Department of Nature Conservation. All experiments described here complied with the relevant ethical regulations for animal testing and research and were approved by the Animal Ethics Committee of the University of Pretoria. To ensure that the birds would not be restricted in their natural behavior while carrying the transmitters, we tested all devices on captive P. mahali, we equipped both birds of wild pairs with on-board radio telemetric transmitters developed at the Max-Planck-Institute for Ornithology in Seewiesen, Germany. The lightweight vocal transmitter (0.6 g), which included a miniaturized microphone , was covered by a thin silicon casing and fixed on the back of the bird  was placed below the nesting tree in the center of the birds’ territory  prior to anesthetization with isoflurane inhalation . The birds were wrapped in a thin gauze blanket and kept warm by warm water bags  and a reference electrode .After detecting stable auditory-driven neural activity with a good signal-to-noise ratio, the electrode was fixed (at depths between 217 and 360 µm below brain surface) by gluing the connector pins of the reference and the recording electrode to the skull using dental cement , and a self-made radio-telemetric transmitter (weight: 1.0 g) was connected to the pins−1, Boehringer-Ingelheim, Germany). Recording of neural and vocal activity , we could guarantee that all treated birds readily reintegrated into their group and maintained their social position. Before release at civil twilight, we administered a second analgesic injection (Metacam 0.2–0.5 mg kgn = 5) or euthanized for brain sampling by an overdose of isoflurane after applying an electrolytic lesion at the recording site (n = 6). Only pairs of birds in which both neural transmitters provided stable signals over 2 consecutive days were euthanized since only data from those birds could be used for analysis. Electrolytic lesioning was performed by connecting both the reference and the recording electrode to the DAM 80 amplifier. Timing (6 s) and current (4.5 µA) of the lesions were adjusted according to Ter Maat et al.34. To verify electrode placement, dissected brains were transferred to 4% paraformaldehyde and transported to the Max-Planck-Institute for Ornithology. Here the brains were cryocut in 30 µm sections and stained with thionin. Supplementary Fig. P. mahali with a lesion in the HVC.Constant monitoring of the treated birds certified that they did not show any sign of discomfort or altered behavior due to the treatment. All but one female bird remained at their colony for the entire experiment. At the end of the experiments, the birds were re-trapped, and the transmitters were dismounted. Birds that carried neural transmitters were either released to their home territory  that was placed in close vicinity to the roosting tree of the respective pair. We used four different duet song bouts in seven different versions: complete duet, male part only, male part only with prolonged gaps between syllables, male part only with shortened gaps between syllables, female part only, female part only with prolonged gaps and female part only with shortened gaps. All song versions were normalized to 3 dB of the maximum and bilaterally faded. Supplementary Movie P. mahali was analyzed by different persons to avoid biasing the measurements. For each bird, all 4-h sound files were initially inspected audiovisually with the software Amadeus® or Audacity® to determine the time of duet bout occurrences. Based on Voigt et al.12, a duet bout was defined as a sequence of introductory song syllables followed by male and female duet syllables. Each duet bout was surrounded by at least 1.5 s of silence and duet bouts temporally overlapped in the vocal signals of the male and female bird of a pair. The time point of the start of the first syllable and the end of the last syllable of each duet bout was noted. To obtain general timing properties, such as syllable duration and syllable interval, the start and the end of each female syllable and each male syllable element were measured in a subset of 15 to 20 duet bouts for each pair of birds. This approach follows the method used in Thorpe et al.60 to define the reaction time in duetting pairs. Onsets and offsets of vocal elements were defined by a deviation of the vocal signal from baseline activity by 5%. The onset of the first syllable element and the offset of the second syllable element in the male duet syllables served as the onset and offset for male syllables, respectively.The temporal fine structure of duet bouts for each studied pair of 61, for each syllable onset, the spectrogram  of the vocal signal of each individual of a pair was calculated within a 500-ms segment preceding and succeeding the syllable onset. To evaluate the level of uncorrelated background activity, spectrograms were constructed from randomly drawn 1-s segments of each vocal signal at random positions within a period of 3 s before and 3 s after the syllable onset62 and significant deviations from the background activity were determined by a pixelwise t test63. In the final display of the syllable-triggered average, significant (p < 0.01) pixels in the male and female vocal signals were indicated in blue and red, respectively. Each syllable-triggered average was based on at least 250 syllables that occurred during all duet bouts analyzed for a particular pair of birds. For each syllable-triggered average, the number of randomly drawn segments was equal to the number of syllable-triggered segments.In addition, a semiautomated method was used to quickly determine the onsets of female syllables and male syllable elements in all recorded duet songs. Sonograms from vocal signals were assembled from 512 point Fast Fourier Transforms (Intel Libraries) using custom written software . Each sonogram describes a syllable or any other suprathreshold sound. To determine the average activity pattern in the vocal signals of each bird of a pair in relation to syllable occurrence in the vocal signal of one of the birds, syllable-triggered averaged spectrograms were generated for each bird using a reverse correlation technique. For this, the onset of each syllable in each duet bout was extracted from the data set. In accordance with a method described by Jenison et al.ITo determine the correlation between vocal signals of both duet partners, we measured the peak and the time lag at the peak of the cross-covariance function (MATLAB®) between the upper RMS envelopes (MATLAB®) of the signals for each duet bout. The envelopes were determined using a sliding window of a length of 1000 samples. During duetting, the male and the female bird often sat close together, which theoretically opened up the possibility that the microphone of the vocal transmitter of one bird picks up the vocal signal of the partner. However, since the receptive part of the microphone was directed toward the body surface of the bird it was mounted on, and the transmitter’s plastic cover and the bird’s feathers further shielded the microphone from external sound sources, the partner’s vocalizations produced only negligible amplitude variations in the vocal traces, which were never detected by our sound analysis software and were averaged out in the RMS envelopes used for covariance analysis.−1 and from 5.7 to 35.1 spikes s−1, respectively  using the MATLAB® filtfilt function. Supplementary Fig. 62 and significant deviations from the background activity were determined by a pixelwise t test63. In the final display of the spike-triggered average, significant (p < 0.01) pixels in the male and female vocal signal were indicated in blue and red, respectively. Each spike-triggered average was based on at least 400 spikes, and for each spike-triggered average, the number of randomly drawn segments was equal to the number of spike-triggered segments.To determine the averaged activity in the vocal signals of both partners in relation to spike occurrences in the neural signal of one partner, spike-triggered averaged spectrograms were generated for each bird. For each spike, the spectrogram  of the vocal signal of each individual of a pair was calculated within a 500-ms segment preceding and succeeding the time of spike occurrence. To evaluate the level of uncorrelated background activity, spectrograms were constructed from randomly drawn 1-s segments of each vocal signal at random positions within a period of 3 s before and 3 s after spike occurrenceTo determine the correlation between neural signals of both duet partners, we measured the peak and the time lag at the peak of the cross-covariance function  between the upper RMS envelopes  of the signals for each duet bout (see above). To measure the oscillation frequency of multiunit bursts in the neural signal of one bird before and after the song onset of the second bird, we calculated the autocovariance function  between the upper RMS envelopes (MATLAB®) of the neural signal for both parts during each duet bout and performed a spectral analysis of the function by calculating the FFT (MATLAB®) with an input length that was the next power of two from the original signal length. The single-sided amplitude spectrum was plotted for the frequency range (1–10 Hz) that we expected to include the oscillation frequency of the signal, and the frequency at the peak of the spectrum was noted.Further information on research design is available in the Supplementary InformationReporting SummaryDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2


However, despite macroscopic evidence for this process, until recent it was not possible to characterize this process at the nano-scale due to the difficulty of such observations. In this study, we report nanometer-scale observations on calcite crystal surfaces and demonstrate that stress with absence of visible deformation produces fluid leakage from fluid inclusions. Atomic Force Microscopy scanning experiments on freshly cleaved calcite crystals containing visible fluid inclusions revealed the spontaneous formation of nanometer-scale hillocks on flat crystal terraces in only a few minutes, without evidence of surface dissolution. The fact the hillocks formed on flat surface in a short time was unexpected and suggests deposition of material from the inner crystal to the surface through small-scale fluid migration. We estimated the rate of this fluid mobility is by several orders of magnitude higher than the diffusion rate through vacancies estimated in calcite crystals showing that CO2–rich fluids through micro-pore and nano-pore spaces is in reality much higher than previously assumed using current predictive models.The transport of supercritical fluids is a determining factor for several geological processes and fundamental in predicting natural resource accumulation and distribution. Calcite, ubiquitous in most geological environments, may contain supercritical CO Observations of minerals in a rock at high magnification has revealed that tiny aliquots of these paleofluids can be retained in microscopic cavities that form fluids inclusions wetting grain surfaces and forming a thin, continuous film that may short-circuit transport. In non-fractured rocks, however, fluids can easily move as they are located at the grain boundary spaces2. One significant weakness in our fluid transport knowledge concerns the mechanisms controlling the fluid distribution among grains of solid rock with which they are in chemical and mechanical equilibrium. The fluid flow between grains and mineral pores has been documented at elevated temperatures and pressures3 while it is assumed to be negligible at 25 °C and 1 atmosphere4. Some earlier evidence to the contrary is, however, constituted by the self-diffusion of calcium isotopes documented in some soil carbonates5. In the case of CO2-bearing aqueous fluids, the extreme conditions required for studying displacement processes at the micrometric and nanometric scale , are such that only a limited number of studies have been published on the subject7. These small-scale phenomena, interpreted as interfacial processes, have been often neglected in continuum-scale modelling such a viscous fingering6 and wetting alteration by CO2-rich fluids8. The rheological properties of thin complex fluids is of paramount importance for gas flow in rock matrices9 and geophysical models of non active tectonic areas11. Earlier work14 suggests that fluids confined at the micrometric (or nanometric) scale may move fast and have a key role in fluid-solid reactivity. Fluid movement and solid permeability at grain boundaries have often been explained in terms of interfacial energy7, while when a small amount of fluid is trapped by surface tension, the capillarity pressure is sheared. At this scale, fluids must be present in the form of absorbed molecular films, non-equilibrium or wetting film, as well as isolated fluid inclusions maintained by steric force originated from hydrated layer at the mineral surface15.Fluids play a key role in enhancing mineral reactions and rock deformation, influencing a wide range of geological processes such as fluid-rock interaction, solution transfer, electrical conductivity, seismic wave velocity and attenuation16 and geological sequestration of CO217.In this contribution, we report nanometer-scale observations made by Atomic Force microscopy (AFM) on natural calcite crystals containing micrometric fluid inclusions and demonstrate stress-induced production of fluid leakage from what most likely are nanometric fluid inclusions, in a very short time under standard temperature and pressure conditions. Our results yield the first independent determination of nano-scale fluid movement inside a calcite matrix. The potential significance of the results to fluid transport in rock is also briefly discussed. This study points the way for future similar research on other minerals, helpful for modelling fluid transport of matter, fault lubrication during earthquakes3). Optical microscope observations of the calcite crystal denoted the presence of several fracture planes of few millimeters in length, as well as fluid inclusions organized along similar planes or occurring isolated or in small groups ; Type-2 fluid inclusions, in addition to aqueous and carbonic phases, contain halite and, in a few cases, other unidentified solids. Both fluid inclusion types occur together in planes and groups. On cooling, the homogeneous CO2 separated into liquid and vapor phases that, upon heating, homogenized to the liquid phases at temperatures ranging from −5° to 27 °C. The corresponding bulk density ranging from 0.85 to 1.15 g/cm3, which would produce internal pressures as high as 50 MPa at room temperature. The nature of dissolved salts in the aqueous solutions of both inclusion types, estimated by microthermometry (see method section), consists mostly of Na+ with salinity in the range of 5–26 wt. % NaCl equivalent. Some halite-bearing inclusions have higher salinity, the exact degree of which could not be determined because most inclusions decrepitated before total homogenization upon heating, likely due to high CO2 pressure. High Resolution Transmission Electron Microscopy observations reveal the presence of rupture of the periodicity of calcite producing several grain junctions delimiting variable size of mono-crystal domains ranging from 10 to 500 nm in diameter.We monitored the state of a freshly cleaved calcite surface using optical-quality Iceland spar from Chihuahua, Mexico 22. The surface free energy of ‘dried’ large calcite crystals is equal to 0.59 J/mol, whereas that of ‘hydrated’ crystals is 0.33 J/mol23 and may decrease by one order of magnitude for smaller nanometric sized particules24. Assuming that the fluid inclusions are in equilibrium with the mineral walls, the stress produced by the tip could be responsible for the disruption of such conditions. Thus, sub-micron fluid inclusions can move through the calcite crystal (via dislocations) to the mineral surface and cause the formation of the observed hillocks. Migration of several-micron-sized fluid inclusion has been postulated by several authors in minerals such as quartz, via dislocation or by dissolution-precipitation of the crystal walls26.In an earlier study27 and found that a 30 °C temperature increase produced a 4-fold increase in hillock volume , thus enhancing the mechanical strain undergone by the mineral. Resulting data shows that a 50% decrease in scan frequency produced a 600% increase in hillock volume Fig. . Moreove2-rich fluid inclusions located just under the surface are near their rupture limit because of the elevated internal pressure, thus even a very small mechanical strain will cause them to decrepitate and lose their fluid. This phenomenon is potentially enhanced by heat, as any temperature increase would cause the internal pressure to rise dramatically due to conservation of internal density28. Fluid inclusion decrepitation in response to heat-induced overpressure is a well-known phenomenon in fluid-inclusion studies; hairline fracture propagating from the decrepitated micrometric fluid inclusions can sometimes be observed  the fluid inclusions involved in the fluid movement are located at least 0.01 to 0.1 µm below the calcite surface, (ii) the pathway is vertical, and (iii) precipitation at the surface is instantaneous, our real-time measurements allow us to estimate a rate of fluid transport at ~5 × 10−10±0.5 m·s−1. This value does not represent a diffusion coefficient in the sense of the Ficks Law but is simply an estimation of the rate of inner fluid-mobility in our calcite matrix30. The transport rate that we calculated is about 4–5 orders of magnitude higher than that estimated by low-temperature extrapolation of solid-state diffusion vacancy experiments31. These results highlight the extreme mobility of fluids at the micro-nano fluidic scale in calcite crystals at standard pressure and temperature conditions.The observed hillock formation can be explained by the fact that COcf. Fig. . Alterna32. The CO2 coming from the fluid inclusions could mix with the thin water layer in equilibrium with ambient air at the surface33, inducing precipitation of calcium carbonate hillocks. Alternatively, these hillocks could consist of halite nanocrystals resulting from evaporation of the NaCl-rich aqueous fluid coming from fluid inclusions. However, halite precipitates formed from heat-induced decrepitation of fluid inclusions generally display varied morphologies, ranging from cubic crystals to toothpaste-like tubes28, features that were not recognized in this study. We also carried out additional experiments under dry atmosphere conditions (using toluene) and found much smaller hillocks, suggesting the importance of ambient water in the formation of the hillocks and thus validating the former hypothesis.AFM observations alone cannot provide information on the composition of these surface features. However, the fact that the hillocks grow on the surface may correspond to an eventual accumulation by epitaxial growth13. However, in case of micrometric or nanometric channel sizes, transport coefficients should take interfacial properties into account35. For simple fluid/solid interface with pressure flow represented by a slit of thickness h and slip length b, the mean velocity increases by a factor 1 + 6b/h as compared to the no-slip surfaces, suggesting that the size of the channel h drives the flow. However, our observations suggest that the interfacial structure at the solid-liquid interface could be an alternative way to generate flow. The electrical interaction between tip and surface atoms generates a stress over the mineral surface. Applying a stress E, the fluid acquires a plug flow comparable to a velocity profile, with a velocity νEO proportional to E in agreement with the Smoluchowski equation34:D, results from the competition between ion attraction at the charged surface and the entropic effects. The value of λD, is generally function of the salt concentration in the fluids . The interfacial Debye layer is electrically charged, while the remaining bulk solvent is electrically neutral. Therefore, when applying the stress, the electric driving force is located within the Debye layer only. The driving force per unit surface acting on the liquid thus becomes Fe = σE, with σ the charge of the Debye layer, which is exactly opposite to the surface charge σ = εV0/λD for weak surface potential V0. This leads to Fe ~ −ε(Vo/λD)E. Now, the fluid velocity results from the balance between this electrical driving force in the Debye layer and the viscous stress at the surface. For a no-slip boundary condition, the latter is Fη ~ ηνE0/λD, since the velocity varies on a scale given by the Debye length. If slippage is exhibited at the surface, the velocity varies on the size λD + b and the viscous stress becomes accordingly Fη ~ ηνE0/(λD + b), lower than the no-slip boundary conditions. Gathering these results, we get:0 can be identified as the potential at the plane of shear V0 = V(Zs), with Zs being of the order of one liquid layer. As expected, a strong amplification of charge transport is therefore demonstrated on a slipping surface. Generalizing this behavior to all interfacial transport phenomena, the flow fluid velocity in confined media results proportional to the applied gradient  and depends on the size L, of the interface where the fluids interacts specifically with the mineral surface. Since our observed phenomenon is proportional to the applied stress that produces a surface energy gradient, we propose that slippage amplifies the transport according to the ratio b/L, which in turn controls the interfacial transport of fluids at the micro and nanometer scale. While structural defects at the external surface of minerals have been identified as limiting steps in transport and reactivity in non-confined fluids32, fast movement of CO2-rich fluids are related to fluid-fluid and fluid-calcite interfaces.Our experimental observations show that stress applied to a calcite crystal can produce fluid migration, at least within the more external parts of the crystal. The question that arises, then, is the limiting conditions for fluid mobility and when it could be a dominant transport mechanism. In a stable fluid inclusion, the liquid resistance to driving forces increases when the channel size decreases37. Fluid transport is usually observed in poly-phase material but individual mineral grains can also exhibit clear indications of multi-path migration even when visible evidence of such paths is lacking. Quantifying this process at the micro-nanoscale for a mineral at standard external conditions, we show that fluid mobility is in reality much higher than previously assumed using current predictive models40. Our findings also suggest that mechanical stress plays a more significant role in fluid transport than previously assumed. Classical reasoning assumes local partition equilibrium at the fluid-solid interface, or, equivalently, a continuity of the chemical potential. Based on our observations and on the approach outlined above, it would seem more consistent to introduce a discontinuous flux across the interface. The magnitude of this discontinuity characterizes the kinetics of pressure solution rather than intergranular diffusion. The rheological properties of small-size fluids and their flow in carbonate rocks are of paramount importance in many geological situations. In the case of lubrication of faults, calcite is an important, and in some cases dominant mineral in seismically active regions worldwide, leading an extra anisotropy in P- or S-wave velocities. Fast fluid movement at the microscale and nanoscale have significant consequences in interpreting anisotropy in fluid-bearing rock systems during carbon crust cycling43 and geological CO2 sequestration44. High mobility of fluids in crystals may also have important implications for fluid-mediated metal transport. The origin of native gold grains observed at the surface of sulfide grains in orogenic-type deposits45 could be explained by movement of micron-size fluid inclusions commonly observed in sulfides rather than by dissolution/precipitation processes involving external fluids46. Relatively low-strain (lower than Shear Modulus) could easily trigger micro-fluids containing dissolved gold  to migrate out of the crystals, precipitating native metal like gold on the surface with no deformation of the parent sulfide minerals47, thus explaining field-scale petrographic observations.Our unexpected findings have potentially far-reaching implications for developing new fluid transport prediction models. Traditional approaches to fluid transport assume the presence of inter-grain pathways in polycrystalline materials such as micro and nano-pore tubeset al. (1985). The stage was calibrated using synthetic material to accuracies of ±0.1 °C in the temperature range covered in this study. Salinity (expressed as wt.% eq. NaCl), bulk composition, and density data were calculated by reducing raw thermometric data with the BULK and ISOC software packages of Bakker)48. The equations of state used was that of Bowers & Helgeson (1983) for the H2O–CO2–NaCl system.The fluid inclusions were identified by preparing wafers of 150 µm thickness from the calcite crystals, polished on both sides to optimise transparency. The fluid composition was estimated non-destructively, by measuring the temperatures of phase change inside the fluid inclusions, using a Linkam THMGS 600 heating-freezing stage and following the procedures in Roedder (1984) and Shepherd 2 flux just before experiments. Therefore, in order to avoid any interaction between tip and surface, the normal force applied to the samples was set to lower than 10 nN. We carried out all standard tests for imaging calcite samples: rotation, scaling, reproducibility on other sites and samples.Atomic Force Microscopy (AFM) experiments were carried out under controlled atmospheric conditions with 70% residual humidity, using a Digital Instruments Nanoscope III device. In order to eliminate the possibility of residual dust dissolution in the water film on the calcite surface (cf. below), freshly cleaved grains were cleaned with a N


Fluid volume and hemodynamic management in hemodialysis patients is an essential component of dialysis adequacy. Restoring salt and water homeostasis in hemodialysis patients has been a permanent quest by nephrologists summarized by the ‘dry weight’ probing approach. Although this clinical approach has been associated with benefits on cardiovascular outcome, it is now challenged by recent studies showing that intensity or aggressiveness to remove fluid during intermittent dialysis is associated with cardiovascular stress and potential organ damage. A more precise approach is required to improve cardiovascular outcome in this high-risk population. Fluid status assessment and monitoring rely on four components: clinical assessment, non-invasive instrumental tools , cardiac biomarkers (e.g. natriuretic peptides), and algorithm and sodium modeling to estimate mass transfer. Optimal management of fluid and sodium imbalance in dialysis patients consist in adjusting salt and fluid removal by dialysis  and by restricting salt intake and fluid gain between dialysis sessions. Modern technology using biosensors and feedback control tools embarked on dialysis machine, with sophisticated analytics will provide direct handling of sodium and water in a more precise and personalized way. It is envisaged in the near future that these tools will support physician decision making with high potential of improving cardiovascular outcome. By natu,,,,,,,,,,,,,Sodium and fluid accumulation that may occur in dialysis patients over time due to repetitive positive fluid imbalance is responsible for chronic extracellular fluid overload  with its,Assessing fluid status of dialysis patients is not an easy task from a clinical perspective. In that context, it is interesting to note that over time several tools have been proposed  to asses,1. Clinical assessment focusing on fluid status, hemodynamic stability, and patient perception was the first attempt to address this issue in developing the concept of ‘dry weight’,,,Subsequently, several tools have been proposed to help physicians in refining clinical acumen and defining more objectively ‘dry weight’ of dialysis patients2. Instrumental or technology-based tools use various non-invasive ways to assess volemia, fluid status, or hemodynamic surrogate indicators.,,Inferior vena cava diameter (IVCD) and collapsibility has been proposed to monitor intravascular volume and right atrial pressure or central venous pressure in dialysis patients with interesting findings,,Relative blood volume change (RBV) and refilling rate capacity during dialysis assessed by online blood volume sensor has been also proposed for fluid management. In expert hands, this tool provides useful information on individual patient volume status to facilitate hemodynamic guidance,,,,,,,Bioimpedance approach has been proposed over the last few years as a more objective way to assess fluid status in dialysis patients,More recently, it has also been proposed to extend the use of lung ultrasound in chronic hemodialysis patients for tracking silent fluid accumulation in the lung interstitium (extravascular edema). Interlobular septa thickening due to water accumulation reflects US beam and generates visible B line bundles (comet-like tail). A simple counting of these B lines provides an estimate of lung water excess and predictive value for patient outcomes,,,Sodium MRI has been introduced quite recently in the field of sodium and fluid assessment in chronic kidney disease patients in dialysis to assess tissue sodium accumulation,,,,,,,,3. Cardiac and vascular biomarkers have been used extensively in an attempt to disentangle fluid status and cardiac dysfunction in dialysis patients. Atrial natriuretic peptides  are the most popular ones for assessing fluid overload,,,,,4. In recent past years, several researchers have develop algorithms to quantify sodium and water mass transfer during hemodialysis sessions using either mass balance equations based on the law of conservation of mass within the dialysis/patient systemOptimal management of fluid and sodium imbalance in dialysis patients is achieved by adjusting salt and fluid removal through dialysis and salt intake restriction, and fluid gain between dialysis sessions. This is the conventional approach obtained by adjusting ‘dry weight’ according to clinical judgment and complementary tools including dialysate sodium prescription adaptation described earlier. However, this approach may be hampered by the discontinuous nature of the HD treatment and/or patient intolerance to fluid and sodium removal. An obvious solution would be to increase time and/or frequency of dialysis sessions in patients with high inter-dialytic weight gains and/or intolerance for fluid removal, as this has been shown to reduce intradialytic hemodynamic stress. However, this approach will not always be possible for financial or logistic reasons, or because of the wish of the patient.,Modern technology using biosensors and sophisticated analytics provide tools for handling directly sodium and water during hemodialysis session in a more precise and personalized way that have potential for improving patient outcomeComplementary clinical studies on a large scale should help to better characterize dialysis patients in term of diet sodium intake over prolonged time period and explore effects of this precise sodium and fluid management approach on patients intermediary and clinical endpoint outcomes.,,,Dialysis adequacy concept has evolved over time and based on patient outcomes. Due to more efficient hemodialyzers, more technically advanced hemodialysis machines, and wider use of ultrapure dialysis fluid, efficiency and biocompatibility of renal replacement therapy have improved tremendously


Goal Directed Fluid Therapy (GDFT) represents an objective fluid replacement algorithm. The effect of provider variability remains a confounder. Overhydration worsens perioperative morbidity and mortality; therefore, the impact of the calculated NPO deficit prior to the operating room may reach harm.A retrospective single-institution study analyzed patients at UC Irvine Medical Center main operating rooms from September 1, 2013 through September 1, 2015 receiving GDFT. The primary study question asked if GDFT suggested different fluid delivery after different NPO periods, while reducing inter-provider variability. We created two patient groups distinguished by 0715 surgical start time or start time after 1200. We analyzed fluid administration totals with either a 1:1 crystalloid to colloid ratio or a 3:1 ratio. We performed direct group-wise testing on total administered volume expressed as total ml, total ml/hr., and total ml/kg/hr. between the first case start (AM) and afternoon case (PM) groups. A linear regression model included all baseline covariates that differed between groups as well as plausible confounding factors for differing fluid needs. Finally, we combined all patients from both groups, and created NPO time to total administered fluid scatterplots to assess the effect of patient-reported NPO time on fluid administration.p = 0.64 and p = 0.19, respectively. In scatterplots of NPO time to fluid volumes, absolute adjusted and unadjusted R2 values are < 0.01 for each plot, indicating virtually non-existent correlations between uncorrected NPO time and fluid volumes measured.Whether reported by total administered volume or net fluid volume, and whether we expressed the sum as ml, ml/hr., or ml/kg/hr., the AM group received more fluid on average than the PM group in all cases. In the general linear models, for all significant independent variables evaluated, AM vs PM case start did not reach significance in both cases at This study showed NPO periods do not influence a patient’s volume status just prior to presentation to the operating room for surgical intervention. We hope this data will influence the practice of providers routinely replacing calculated NPO period volume deficit; particularly with those presenting with later surgical case start times. Question: Does nil-per-os (NPO) time and preoperative fasting influence fluid needs during surgery?Findings: Using multiple statistical analyses, we found no relationship between NPO time and fluid volume delivery suggested by a goal-directed fluid-therapy algorithm.Meaning: Intravenous fluid resuscitation based on historical “NPO time deficits” may not be indicated.A central and still somewhat controversial question in anesthetic care asks whether nil-per-os (NPO) period fluid-deficits need intraoperative replacement . PreviouGDFT stands as a validated and objective fluid replacement algorithm that also significantly reduces the impact of provider-related variability in fluid delivery –13, 15. This retrospective study utilized a de-identified dataset provided by the hospital information technology department. The University of California Irvine Institutional Review Board deemed the protocol IRB exempt.We extracted data for this study from our perioperative database, SIS . The initial data pull included all adult procedures in 20 main operating rooms at UC Irvine Medical Center (UCIMC) from September 1, 2013 through September 1, 2015 that were marked as receiving GDFT in the medical record (our charts include a mandatory GDFT field that must be selected yes/no before the chart can be closed).Inclusion criteria for the study were adult patients age 18 or over having open or laparoscopic abdominal procedures . For each identified case, we pulled: case, date and time; procedure; patient demographics ; patient comorbidities ; NPO time; whether or not the patient received an epidural or arterial line; intraoperative data .We sorted the data and created two groups distinguished as either AM  or PM . Cases starting between 0730 and 1200 were excluded to ensure distinct separation between the two groups. Following this, we applied further exclusions to standardize the patient cohorts and reduce variability due to surgical factors: patients less than 18 or older than 100 years; patients with estimated blood loss (EBL) greater than 500 mL or who received blood products intraoperatively; and those with congestive heart failure (CHF), end-stage renal disease (ESRD), or who were receiving dialysis. We also excluded emergency cases, patients admitted for greater than 24 h prior to surgery (since intravenous fluid could have been administered during the NPO period), and those who received hypertonic bowel preparations.We instructed all patients to fast at midnight before surgery. If patients needed any PO medications prior to surgery, we instructed them to take these with a sip of water. Patients arrived in the preoperative holding unit roughly 2 h prior to the start of surgery. Preoperative nurses obtained intravenous access and started crystalloids  at keep vein open (KVO) flows.The primary GDFT protocol in use at UCIMC during this time period was an adaptation of the stroke volume variation (SVV) protocol and is outlined in Fig. Primarily we sought to determine whether PM patients required different fluid delivery when compared to AM patients when a GDFT protocol recommended care. Our statistical approach therefore assessed this question from many possible perspectives to determine whether any evidence exists to support different fluid delivery requirements in AM compared to during PM surgery. We calculated and analyzed fluid administration totals with both a 1:1 crystalloid to colloid ratio as well as with a 3:1 crystalloid to colloid ratio.First, direct group-wise testing was performed on total administered volume  calculated as total ml, total ml/hr., and total ml/kg/hr. between the AM and PM groups. These three different calculations allowed us to check raw total, raw total corrected for duration of case, and raw total corrected for duration of case and size of patient. Second, a linear regression model was run that included all of the baseline covariates that differed between groups as well as the plausible confounding factors for differing fluid needs . Our model used a 1:1 crystalloid to colloid ratio or a 3:1 crystalloid to colloid ratio, which allowed us to evaluate the marginal influence of group (AM or PM) in light of all of the other covariates. Finally, we combined all patients from both groups and scatterplots of NPO time to total fluid  assessed the effect of patient-reported NPO time on fluid administration.We assumed group size imbalance may exist between AM and PM case starts due to the consistent morning starts in all ORs. We knew if we could pull at least 300 patients into the former and 100 patients into the latter, assuming the typical patient received 2100 ± 450 ml of fluid based on previous work , with a http://www.R-project.org). We report data as mean ± standard deviation, or as count (percentile) for categorical variables. Because we assessed any possible increase in need for fluid, we considered a p-value of < 0.05 significant with no corrections for multiple comparisons made.We performed statistical analyses using SPSS  or R . AM case starts also saw a higher proportion of laparoscopic cases than PM cases . Finally, mean NPO time was shorter in the AM group than the PM group (10.0 ± 2.5 h vs. 12.5 ± 3.1 h (median and interquartile ranges 10 [p < 0.001). Actual NPO distribution data can be found appended.Table anges 10 –12 and 1more fluid on average than the PM group in all cases. In half of the approaches to calculating fluid totals the higher AM case total was statistically significant; in the other half the difference showed was not. However, no approach to calculating fluid delivery revealed a recommendation by the GDFT algorithm to administer more total fluid volume in PM cases than any AM cases.Table p = 0.64 and p = 0.19, respectively. When raw reported NPO is used as the duration of NPO for each patient group instead of AM vs. PM groupings in the models, NPO time is also non-significant as an independent variable at p = 0.38 and p = 0.97 in the 1:1 and 3:1 fluid total models, respectively.The general linear models, seen in Tables 2 values are < 0.01 for each plot, indicating virtually non-existent correlations between uncorrected NPO time and fluid volumes measured by any of the 12 approaches in the figure.Figure Despite lengthened NPO periods for PM surgeries, the GDFT algorithm did not result in an increased fluid administration rate for PM cases compared to AM cases. This finding agrees with suggestions from previous studies that the NPO period does not significantly impact required fluid delivery , 5, 14. Our observation of greater epidural use, longer case duration, and greater use of laparoscopy in the AM group likely reflects two scenarios more likely to receive goal-directed fluid therapy: same-day surgery admit laparoscopic abdominal surgery with controlled ventilation and complex, and longer-duration, open abdominal surgeries with increased epidural usage that practically benefit from beginning earlier in the day. Therefore, complex surgery was overrepresented in the AM group as compared to the PM Group; however, our analysis did as much as possible to account for the types of differences in fluid requirement a more complex case may dictate. Specifically, removal of cases with > 500 ml of blood loss or those patients that received blood should have removed much of this variability, and correction for EBL, arterial line placement, and case duration in the models should have further corrected for this source of potential bias.NPO time difference between AM and PM surgical case starts differed by a surprisingly small number of hours (less than 3), when we expected closer to 5. The small difference likely reflects both variation in how patients follow NPO guidelines, and the fact that the recorded NPO time remains subject to both recall and reporting bias. Moreover, the distribution of NPO times suggests bias in time entry by providers, which was part of the rationale for straight splitting of the cases into first-case starts and afternoon starts (as opposed to using raw NPO time as a covariate), because the NPO time entered may not have been completely reliable. We discuss this further in the limitations below.AM starts actually received more fluid than PM starts when guided by GDFT. Some of those additional factors contributing to this finding may include patient pathology, condition, higher EBL, epidural vasoplegia, and greater insensible loss typical of more complex surgery as previously noted, though this result remains difficult to interpret in such a broad and multifactorial setting. Nevertheless, the variables affecting this previous result, namely, possible different ASA classifications among the AM vs. PM patient groups , 16, 17,Thus, we believe there remains strong evidence to support a change in focus from “replacing NPO time deficits” to thinking more about patient and surgical case complexity. Obvious factors including presenting diagnosis, comorbidities, age, body habitus, expected blood loss, and case duration should be accounted for along with fluid responsiveness. Given the preponderance of variability in the literature with regards to the reliability of void urine output during surgery as a marker of volume status, void urine output in our study did indeed independently predict recommended fluid administration from the GDFT algorithm, in line with the earlier studies in literature that did suggest the predictable nature of void urine for fluid delivery , 23. TheThe primary limitation of this study is the retrospective design. As with all retrospective studies, selection and information bias cannot be completely accounted for, and may confound the interpretation of the results. Missing or invalid data points in our database may have reduced the size and power of our study, but because the proportion of excluded and missing data was similar between the two groups, we believed the validity of the study remained intact. Additionally, excluding patients with EBL greater than 500 ml for reasons discussed above, while reducing variability, may have also introduced some selection bias. However, we used generalized linear models to help mitigate possible confounding factors and strengthen our results. The method of monitoring fluid responsiveness varied within our cohorts and we do not have specific records of which methods were used in which patients. There may be unaccounted bias in the approaches used between the AM and PM cohorts. Finally, the types of fluid used during resuscitation obviously differed from case to case and were not standardized. Despite this, there were not significant overall group differences, and we attempted to account for this in our results by creating multiple parallel analyses using different recommended replacement ratios from the literature. The consistent non-significant findings regardless of the approach used are reassuring that our findings are not approach-dependent.A limitation of the NPO time comparison between groups, and indeed a limitation of the using the NPO time in general as a covariate in the models, was that the data entry in the EMR for the NPO period was not distributed as would be expected if precise times were being entered. Entries overwhelmingly fell at the 8 h, 10 h, and 12 h blocks, with the remaining periods being more evenly distributed as might be expected for “true” times (see figure below). In looking at the raw data, it appears that particular anesthesia providers defaulted, for example, to 8 h, or 10 h, and rarely entered ‘exact’ times. This was a key part of our rationale for simply dividing the cases into AM and PM groups since the raw NPO time was unreliable.We set out to determine whether or not surgical case start time had any observable effect on intraoperative fluid requirements when guided by a GDFT protocol. Our conclusions, in agreement with prior work, suggest that NPO periods do not significantly influence a patient’s intraoperative fluid requirement and PM case starts do not require more fluids than AM case starts in any situation we could identify within our dataset. Future work could examine the repeatability of our findings in a multi-center and prospective study design.Additional file 1. GDFT Protocol UCI 2019.pdf. Appendix: GDFT Protocol.Additional file 2. GDFT Overview UCI 2019. Appendix: Overview document of our GDFT implementation.


Treatment plans were evaluated by T90, T50 and T10 target temperatures and treatment-limiting hot spots. Adequate heating is possible with the helmet. In the pre-operative case, treatment plan quality was comparable for all three models. In the post-operative case, the high-k models were more accurate than the solid model. Predictions to within ±1 °C were obtained by a 10–20-fold increased effective thermal conductivity. Accurate modelling of the temperature in CSF requires fluid dynamics, but modelling CSF as a solid with enhanced effective thermal conductivity might be a practical alternative for a convective fluid model for many applications.Hyperthermia therapy (40–44 °C) is a promising option to increase efficacy of radiotherapy/chemotherapy for brain tumours, in particular paediatric brain tumours. The Chalmers Hyperthermia Helmet is developed for this purpose. Hyperthermia treatment planning is required for treatment optimisation, but current planning systems do not involve a physically correct model of cerebrospinal fluid (CSF). This study investigates the necessity of fluid modelling for treatment planning. We made treatments plans using the Helmet for both pre-operative and post-operative cases, comparing temperature distributions predicted with three CSF models: a convective “fluid” model, a non-convective “solid” CSF model, and CSF models with increased effective thermal conductivity (“high- Hyperthermia treatment, i.e., heating tumours to fever range temperatures ca. 40–44 °C) for a prolonged time , has been proven to increase response rate and survival for a wide range of tumours in patients treated with radiotherapy ,3,4 or c0–44 °C fBrain tumours might particularly benefit from this synergistic treatment as radiotherapy leads to severe late toxicities, especially in children . The facThere are various types of malignant (primary) brain tumours, such as glioblastoma multiforme (most common in adults) and medulloblastoma (most common in children). Clinical application of hyperthermia for glioblastoma ,19,20,21There are several methods to raise the temperature in the brain, each with its own advantages and drawbacks . High-inAlthough clinical application of hyperthermia for brain tumours has been limited to glioblastoma multiforme, the most prevalent brain tumour in adults, many of the considerations  are equally valid for the treatment of medulloblastomas, the most common brain tumour in children. Even low doses of ionizing radiation to the brain can cause intellectual impairment ,31,32 asDespite these promising possibilities of adjuvant hyperthermia treatment for paediatric medulloblastoma, current standard of care is limited to post-operative radiotherapy in combination with chemotherapy, although also chemotherapy-related toxicity remains a major concern . The absHowever, current hyperthermia treatment planning systems do not model fluid dynamics in a physically correct manner, and do not take the effects of fluid flow into account, except, to some extent, blood perfusion. Blood flow through small vessels  is typically included with a greatly simplified model like Pennes’ bioheat equation , and somFor CSF specifically, heat is gained through direct absorption from the EM field and through heat exchange with directly neighbouring tissues warmer than the CSF; and heat is lost through heat exchange with tissues with a lower temperature, which in turn remove excess heat through heat exchange with blood vessels. This results in temperature differences in the CSF, which give rise to convective fluid flows, with a net effect of transporting heat upwards (against the direction of gravity). Treatment planning systems that do not model fluid flow may, as a consequence, tend to overestimate CSF-induced hot spots, and underestimate the heat distribution by the CSF.Recently, we developed a thermodynamic fluid model as an extension to our existing treatment planning system, Plan2Heat . The dirThe aim of our current research is to assess the effect of CSF flow on the temperature distribution in the human brain during microwave hyperthermia treatment using the Chalmers Hyperthermia Helmet by numerical simulations including fluid dynamics modelling. Results are compared to those obtained with standard solid models and will show whether fluid modelling is important for accurate treatment planning.3 s) was used reflecting the enhanced muscle perfusion levels in response to hyperthermic temperature elevations [An MRI scan with a 1 × 1 × 1 mm resolution was obtained from an actual patient, a 13-year old boy with a large medulloblastoma (92 mL); in the context of the current proof-of-concept study, this may be considered a valid model for various brain tumours. The scan was manually segmented by a clinician into thirteen tissue types; the most relevant ones of which are tumour, tumour cyst, CSF, white matter, grey matter, muscle, and bone. As can be seen in evations . As in pA model of the Chalmers Hyperthermia Helmet comprising a water bolus at 10 °C and 14 antennas operating at 450 MHz was created around the segmented head model ,54. The The computation of the temperature distribution uses the same segmentation and is computed based on this electromagnetic field distribution using a finite volume thermodynamic fluid model. This model was built in OpenFOAM  and implt (s) to the velocity 3). The right-hand side describes the forces acting on the fluid element: the first term is the ‘friction’ between neighbouring fluid elements quantified by the dynamic viscosity μ (Pa s), the second term is the spatial difference in pressure p (Pa). The third term drives the convection and includes the gravitational acceleration k (kg/m), which is assumed to depend linearly on the temperature. The equation governing temperature change in the fluid compartment is:pC (J/(kg K)) the specific heat per mass, k (W/(m K)) the thermal conductivity, σ (S/m) the electric conductivity, E (V/m) the electric field strength, and all other variables as in Equation (1). The reader is referred to earlier publications for full details [The left-hand side expresses the co-moving change over time  details ,48. 3 cubes were subdivided into six identical pyramids by adding a vertex at the centre of the cube, in order to increase the computational stability. For both the pre-operative case and the post-operative case, we evaluated three different models to simulate the thermal behaviour of CSF:fluid: the CSF was modelled using fluid dynamics, including convective flow;solid: the CSF was modelled as a solid, similar to current practice in available hyperthermia treatment planning systems; andk: the CSF was modelled as a solid with an n-fold increased thermal conductivity keff, with keff/k = 2, 5, 10, 20, 50 and 100.high-Meshes for thermal simulations in OpenFOAM were created and the resolution in the solid regions was kept at 1 × 1 × 1 mm; in the fluid regions, these (1 mm)keff approximates the effect of heat transport by fluid flow in a relatively simple and computationally efficient model, similar to that described by Yuan et al. [keff is that the most important effect of fluid flow on the temperature distribution is more efficient heat transport. The main advantage of this simplification is that the value of the thermal conductivity can be adjusted without any further change to existing hyperthermia treatment planning software. Similar ideas, directed mostly to the heat transport in blood vessels, have been reported in the literature [keff/k provide the possibility to study the effect of this increased effective thermal conductivity keff, and to determine whether an appropriate value could approximate the advanced fluid dynamics model.The comparison of these cases allows to evaluate the influence of fluid dynamics on the predicted temperature distributions. Fluid dynamics modelling is relatively expensive in terms of computational costs. The third case with enhanced effective thermal conductivity n et al. , allowinterature ,60. The T90, T50 and T10 at steady state for the target volume, that is, the temperature exceeded by 90%, 50% and 10% of the target volume, respectively. The target volume was split into the tumour and a 1 cm margin around the tumour, which may cover regions of special interest, such as micrometastases or non-resectable tumour residue. The tumour margin is analysed separately for solid tissues and CSF. For the grey and white matter outside the tumour margin, we determined the V41, V42, and V43, defined as the volume in which the temperature exceeds 41 °C, 42 °C and 43 °C, respectively. The same parameters were determined for the CSF outside the tumour margin. The treatment plans, i.e., the set of phase and amplitude settings for each antenna, were obtained by SAR-optimisation, but evaluated by the temperature distribution; consequently, the perceived quality of a single SAR-based set of device settings, depends on the choice of the model used to compute the temperature distribution. The treatment plans were analysed by determining the T > 44.0 °C within the macroscopic tumour including tumour cysts, and as regions with T > 43 °C outside the macroscopic tumour [k models, respectively, on the other hand. The Dice coefficient of two sets A and B is defined as 2 A∩B / (|A| + |B|), i.e., the intersection of the two sets divided by the average size of the sets, which ranges from 0 for disjoint sets to 1 for identical sets. Hot spots were defined as regions with c tumour ,62. The c tumour  to quantk methods relative to the fluid method. This part of the analysis shows how well each solid model approximates the fluid model.In the second part of the analysis, we evaluated the difference between the simulation methods, and determined the median error, interquartile range and 95%-interval of the error of the solid and high-6 cells in the CSF region (340 mL) and 3.9 × 106 cells for the solid regions; for the post-operative case, these numbers were 2.8 × 106 fluid cells (448 mL CSF) and 3.7 × 106 cells for the solid regions. Typical computation times per second simulated time were between 25 s and 97 s for the solid and high-k cases, and about 975 s and 1788 s for the pre-operative and post-operative fluid cases, respectively, using a single core of a normal desktop personal computer . Computation times may have been affected by other processes running on the same computer, but are indicative of the very large difference in computation time between the fluid model and the solid models. The pre-operative mesh comprised 2.0 × 10k models, and k models, respectively. The high-k figures are for keff/k = 10.T90, T50, and T10, shown for the pre-operative case in T90 in the CSF after an initial increase. The absence of such a delayed decrease in the tumour graph indicates that tumour temperature is not affected by the water bolus temperature. An analysis of the complete temperature distribution confirms that temperatures below 37 °C are only found in the outer 0.5–1.0 cm of the skull.We simulated the first 30 min (1800 s) of a treatment. While a typical hyperthermia treatment may last between 60 and 90 min, an equilibrium is reached long before then. The development over time of the k models are represented by the keff/k = 10 model.keff/k = 10 models. Additionally, the keff/k = 100 model misses some relatively mild hot spots. In the post-operative case, these differences are much more pronounced, especially for the tumour region. Here, the fluid model shows a much more homogeneous profile compared to the solid and keff/k = 10 models, due to the effective convective mixing in the fluid volume. The high-k models are closer to the fluid model than the solid model, but still underestimate the mixing effect, and, for larger keff, introduce a systematic cooling error.T90 and T50 in the tumour and in the solid tissues in the tumour margin may be considered equivalent, as they differ at most 0.1 °C As T90 and T50 are most indicative of clinical effect, all three simulation methods predict a comparable efficacy of this treatment plan; i.e., of the given set of phase and amplitude settings for the antennas. All three methods predict a hot spot in the tumour, although they differ in the severity . The most pronounced differences are for the T10 in the CSF surrounding the tumour: a moderate 44.7 °C hot spot for the fluid model, versus a 46.3 °C hot spot for the high-k model and an even higher 48.8 °C for the solid model. In the grey and white matter analysis, the results are qualitatively the same for all models, with the exception of the CSF outside the tumour margin, where the solid model predicts 10.8 mL of CSF ≥ 43 °C, compared to only 1.8 mL for the fluid model and 1.2 mL for the high-k model. The main thermal parameters for evaluation of the treatment plan are summarised in k model (keff/k = 20) misses the smaller hot spots predicted by the fluid model, and overestimates the size of the hot spot between the tumour and the back of the skull (Dice coefficient 0.77). As keff increases, the amount of incorrectly predicted hot spots  reduces, while the missed hot spots  increase in volume. The hot spots in the CSF are again overestimated by the solid model, but increasingly missed with increasing keff, so that the keff/k = 2 model actually performs best with regards to hot spots in the CSF (Dice coefficient 0.67). A full overview of the hot spot volumes and Dice coefficients is given in In the pre-operative case, the solid model predicts considerably more and larger hot spots in the solid tissue outside the tumour than the fluid model (Dice coefficient 0.68); while even the best performing high-T10  for the target regions and the T50 for the circumtumoral CSF. In particular, the solid model predicts a T50 of 52.2 °C for the circumtumoral CSF, compared to an almost acceptable 44.2 °C for the keff/k = 10 model and a safe and desirable 42.5 °C for the fluid model. The T90 for the solid tumour margin is predicted as 40.9 °C by the fluid model, 42.3 °C by the keff/k = 10 model, and 44.2 °C by the solid model. In the post-operative case, the differences in the treatment plan analysis are larger than in the pre-operative case. The most notable difference is found in the keff increases, the hot spots inside and surrounding the CSF decrease, until they disappear for keff/k ≥ 50. As the reference hot spot volume is practically zero, the Dice coefficients are all < 0.1 for the post-operative case and not included in The fluid model predicts almost no hot spots in the post-operative case, while the solid model predicts a large hot spot in the former tumour region, and small hot spots immediately around it. As k models with the fluid model for the pre-operative and post-operative cases, respectively, in a set of box whisker plots showing the median, interquartile range, and 95%-interval. For the pre-operative case, the median temperature difference and interquartile range are all well within ±0.1 °C. However, the solid model temperature error for the healthy tissues has a larger spread than the high-k models: the 95% interval decreases from  for the solid model to ±0.6 °C for keff/k = 50. This implies that the high-k models give a better approximation to the fluid dynamics , but may still be insufficiently precise for many applications. For the grey and white matter, a similar pattern emerges, but with generally smaller inaccuracies. For the temperature of the CSF, both outside the target region, and in particular inside the target region, the predictions by the solid and model are even less reliable; for example, the 2.5th and 97.5th percentile of the temperature difference for the CSF in the target region are −3.85 °C and 9.05 °C, respectively; these values move towards zero for increasing keff, and are −3.34 °C and 1.37 °C for the keff/k = 100 model. The CSF temperature, both inside and outside the target region, is generally underestimated for higher keff, with the interquartile range between roughly −1 °C and 0 °C.keff/k = 10 model, these numbers have shrunk to 1.8 ± 1.9 °C and 1.8 °C, respectively. For the grey and white matter, the difference between the solid and high-k models on the one hand and the fluid model on the other, are much smaller. The mean and median differences are all smaller than 0.1 °C, and the standard deviation varies from 0.2 °C  to 0.6 °C .For the post-operative case, the results are essentially similar, but magnified. The largest temperature deviations are, unsurprisingly, obtained for the solid model in the CSF-filled (former) tumour region, where the mean ± SD temperature difference is 10.6 ± 7.7 °C and the median temperature difference is 9.8 °C. For the keff leads to a lower estimated temperature in the CSF, which may easily lead to an underestimation of the fluid temperature. This is seen in both the pre-operative  for the bladder, the temperature difference between simulated and measured bladder temperatures tended to reach a plateau. A solid foundation for a fixed choice of keff for the CSF requires a larger sample of cases simulated with the fluid model. Another solution might involve adding a  heat sink term to the CSF model analogous to the blood perfusion heat sink term in Pennes’ equation, which would serve to reduce the extremely high temperatures erroneously predicted by the solid model(s). Results of bladder studies show that such a term might improve the accuracy of the results [k, with a high value for k in the direction perpendicular to the direction of gravity, and a higher value for k in de upward direction than in the downward direction; such a non-isotropic k would be quite straightforward to implement in a finite difference model. As the amount of heat transport by natural convection depends on the actual temperature differences in the fluid, a more sophisticated keff model might implement a keff that is proportional to temperature differences within the fluid volume, e.g., by relating keff to the local temperature gradient.Increasing the value for n et al.  for the  results . AnotherUncertainties in the temperature dependency of the used parameters may have caused errors in the prediction. There is little information in the literature about the relationship between temperature and various physical parameters; this is most relevant for perfusion, but also for, e.g., electric conductivity and permittivity. In this study, an increased perfusion value was used for muscle (which is hardly present in and around the treatment area), but not for other tissue types, most notably not for grey and white matter. Based on experiments with monkeys and dogs in the late eighties and early nineties, cerebral perfusion is estimated to increase about 2.5-fold in healthy tissue and about 1.5-fold in tumour tissue when the brain temperature is increased to hyperthermic temperatures ,65,66. IThe Chalmers Hyperthermia Helmet is the only brain hyperthermia applicator designed specifically for paediatric use. The fluid model simulations in this study show that the Chalmers Hyperthermia Helmet is capable of obtaining an adequate tumour temperature, without inducing unacceptable hot spots. The relatively large number of antennas (up to 16) and the wide frequency range (300–900 MHz) of the antennas, allow for a high degree of spatial steering ,54. Hot The results from this paper regarding the influence of CSF on the temperature distribution, apply equally to various alternative hyperthermia applicators that are being or have been developed for heating brain tumours, albeit that they are designed for adults, and not for paediatric applications. A group in Berlin is developing a high field-strength MR-compatible applicator comprising a ring of 16 bowtie antennas . Their iThe discussed brain hyperthermia applicators  are all MR-compatible, so that, in principle, temperature may be monitored during treatment using MR thermometry. However, especially in a post-operative scenario with a large fluid-filled pocket, these measurements may be unreliable in and around the CSF-filled pocket due to motion artefacts; this is similar to MR-thermometry in and around the urinary bladder , for whiFluid dynamics modelling is also of crucial importance for other brain heating techniques, such as magnetic nanoparticles. The first clinical results of magnetic nanoparticle heating for glioblastoma have been reported, which showed that controlled heating is quite challenging . AlthougIn the end, the exact requirements on the heating pattern and the accuracy with which the treatment can be predicted or reconstructed, depend primarily on the relevant hyperthermia mechanism, which in turn may depend on the primary treatment modality: radiotherapy and/or chemotherapy. For example, for certain chemotherapy applications, it may be particularly important to have accurate knowledge whether sufficiently high temperatures have been reached to open the blood brain barrier. When drugs are delivered using thermosensitive liposomes (nanocarriers that release their payload above a certain activation temperature), it is especially important to know the volume where the activation temperature of the liposomes has been obtained. In the case of radiotherapy, it may both be relevant to know whether the temperature was adequate to inhibit fast DNA damage repair, and to know the complete thermal dose for slow DNA damage repair. Regardless of treatment modality, accurate knowledge of presence or absence of hot spots in healthy tissue is always important.k model, an acceptable workflow might comprise doing the amplitude and phase optimisation using a computationally efficient high-k model , possibly with relaxed constraints on the temperature in the CSF. Preferably, such a plan should be validated with a final check using a (steady-state) fluid dynamics model.Using the current set-up, simulating the fluid simulations took more than 15 min (pre-operative) or almost 30 min (post-operative) of real time for each second of simulation time. Evidently, this makes the fluid dynamics model in its current form unpractical for clinical use. A lower resolution would greatly speed up the computations, but this may negatively affect the accuracy in both the spatial and temperature domains. In a well-controlled phantom experiment, we showed that the fluid solver remains accurate when using 2.5 mm-based cells instead of 1 mm-based cells , but thiHeating the brain is a promising (adjuvant) treatment option, but also challenging. For estimating thermal dose parameters for the tumour, physically correct fluid modelling may not be required. For healthy tissue, however, not taking fluid behaviour into account may lead to erroneous predictions of severe hot spots. Unfortunately, the applied thermophysical fluid model is, in its current state, not fast enough for routine clinical use. As an intermediate solution, a temperature that is accurate to within about 1 °C may be obtained for tissues (excluding CSF itself) by modelling CSF as a special solid with an increased effective thermal conductivity; this may be sufficiently accurate for clinical use, provided stringent safety margins are maintained. The optimal value for the effective thermal conductivity depends on the individual case, but a roughly 10–20-fold increase appears to best balance the different effects of convective heat transport on the temperature distribution.