While the brain has evolved robust mechanisms to counter spatial disorientation, their neural underpinnings remain unknown. To explore these underpinnings, we monitored the activity of anterodorsal thalamic head direction (HD) cells in rats while they underwent unidirectional or bidirectional rotation at different speeds and under different conditions . Under conditions that promoted disorientation, HD cells did not become quiescent but continued to fire, although their firing was no longer direction specific. Peak firing rates, burst frequency, and directionality all decreased linearly with rotation speed, consistent with previous experiments where rats were inverted or climbed walls/ceilings in zero gravity. However, access to visual landmarks spared the stability of preferred firing directions (PFDs), indicating that visual landmarks provide a stabilizing signal to the HD system while vestibular input likely maintains direction-specific firing. In addition, we found evidence that the HD system underestimated angular velocity at the beginning of head-fixed rotations, consistent with the finding that humans often underestimate rotations. When head-fixed rotations in the dark were terminated HD cells fired in bursts that matched the frequency of rotation. This postrotational bursting shared several striking similarities with postrotational “nystagmus” in the vestibulo-ocular system, consistent with the interpretation that the HD system receives input from a vestibular velocity storage mechanism that works to reduce spatial disorientation following rotation. Thus, the brain overcomes spatial disorientation through multisensory integration of different motor-sensory inputs. Head direction (HD) cells are neurons in the brain that underlie spatial orientation, but little is known about how these cells function during disorientation. To investigate this, we monitored HD cell responses in rats as they were rotated under a variety of conditions. We found that their activity fitted predictions from an attractor network model. We also found that visual and vestibular inputs differentially support stability and directionality respectively. Finally, we found evidence that HD cells may share a network associated with stabilizing gaze and velocity storage. Together, these findings add a missing piece to the HD system puzzle, help us understand the neural mechanisms of reorientation and will improve computational models of HD cells in the future.Spatial disorientation is a state characterized by an incorrect sense of orientation and motion relative to the earth’s surface . Human sNeural recordings in behaving animals have revealed several types of spatial cells including place cells, head direction (HD) cells, grid cells, and border cells . Of thesThree forms of spatial disorientation have been recognized in the literature . Type I Theoretical and experimental work suggests that HD cells form part of a continuous attractor network  that is To better understand the neural correlates and mechanisms underlying spatial disorientation and how they relate to the HD system, we monitored HD cell responses while rats underwent unidirectional or bidirectional rotations at different speeds, in the light or dark, and while passively restrained or freely moving, conditions that would promote disorientation. Under these different conditions we addressed whether anterodorsal thalamus (ADN) HD cell activity: (1) continues to fire in bursts or becomes quiescent and if this response depends on active locomotion; (2) remains directional and directionally stable, and if this stability depends on access to visual cues; (3) remains internally coherent, as expected from an attractor network; and (4) shows evidence of postrotational effects and if these effects are mitigated by the presence of visual or self-motion cues. Additionally, because both inversion and constant rotation lead to disorientation in humans  and ratsWe used three different experiment protocols.ad libitum. Throughout the experimental period animals were food restricted to lower their current weight by 10% of their presurgical weight to motivate them to forage for food pellets during recording sessions.Experiment 1 used six female Long–Evans rats (Envigo). The rats were between three and six months old at the start of the study. Rats were individually housed, maintained on a 12/12 h light/dark cycle, and provided with water We used two types of apparatus, the first was a standard recording cylinder  painted gray with a polarizing white cue card affixed to the inside wall that spanned 100°. The cylinder floor was composed of a single sheet of gray paper and changed in between recording sessions. The second was a “disorientation apparatus” which consisted of a 68.5-cm diameter circular wooden platform, painted gray and raised 38 cm from the floor on a tripod base. The platform was mounted on a lazy Susan and could be freely rotated. A low (12.7 cm) wall around the edge of the platform prevented animals sliding over the edge, particularly during the rotation sessions. During all recording sessions the disorientation apparatus was placed in the center of the room and surrounded by a black curtain 2.5 m in diameter that stretched from the floor to the ceiling.For single-unit screening, the animal was attached to a multi-wire recording cable that was connected on one end to an overhead commutator (Biela Idea Development) and to the animal’s headstage on the other end. Signals were passed through a field-effect transistor (FET) in a source-follower configuration, amplified (Grass Instruments P511), band-passed filtered , and sent through a series of window discriminators (Bak Electronics DDIS1) before being displayed on an oscilloscope (Tektronix 5113). Spike discharge was sampled at a rate of 60 Hz and stored for offline analysis .For recording, in addition to the above, an automated video-computer tracking system (Eberle Electronics) monitored neuronal discharge while simultaneously tracking the positions of two light-emitting diodes  secured to the animal’s head. The red and green LEDs were spaced 10 cm apart along the midline of the animal’s body axis and positioned over the rat’s snout and back, respectively. The LED positions and spike discharge were sampled at a rate of 60 Hz and stored for offline analysis .If a HD cell was identified on one or more of the ten recording channels, we isolated the cell’s waveform using a series of window discriminators (Bak Electronics) and conducted a recording session. The rat’s HD was determined by a two-spot video tracking system (Eberle Electronics) that monitored the location of two differently colored, light-emitting-diodes  attached to the animal’s head stage.We recorded a total of 25 HD cells. The following eight manipulations were conducted in the order described. No more than 8 min, but usually less than 2 min, passed between sessions. (1) Visual baseline 1: this 8-min session was conducted in a standard recording cylinder with a polarizing cue card and with the lights on. This session served as a baseline control for the HD cell during normal visual conditions. (2) Dark baseline: this session was 4 min long and was conducted in the same cylinder apparatus. Before the session began, the rat was blindfolded, and we changed the floor paper. The cue card was removed, and the lights were turned off. (3) Dark slow rotation: this session was 2 min long and was conducted in the disorientation apparatus. The rat remained blindfolded and the platform was manually spun at a slow rate above the vestibular threshold  in alternating directions (back and forth every 5–10 s). In this session and all other rotation sessions, the same experimenter rotated the platform to ensure a consistent spin rate and they changed their position around the apparatus at least three times during each session. (4) Dark fast rotation: this session was 2 min long and was conducted in the disorientation apparatus. The rat remained blindfolded and the platform was rotated at a medium rate  in alternating directions. (5) Dark baseline 2: this session was 4 min long and was conducted in the cylinder described before. The rat remained blindfolded and the floor paper was changed to remove olfactory cues. The lights remained off and the cue card remained absent from the cylinder. (6) Visual baseline 2: this session was 4 min long and was conducted in the cylinder described before. These sessions followed the same protocol as visual baseline 1; the rat was not blindfolded, the lights were on, and the cue card was returned to its original orientation. (7) Visual slow rotation: this session was 2 min long and was conducted in the disorientation apparatus. A white cue-curtain was hung on a portion of the floor-to-ceiling black curtain surrounding the disorientation apparatus and the lights were switched on. Otherwise, conditions were the same as those described for the Dark slow rotation sessions. (8) Visual fast rotation: this session was 2 min long and took place in the disorientation apparatus with the cue-curtain in place and the lights switched on. Otherwise, conditions were the same as those described for the Dark slow rotation sessions.Not all animals completed all eight session types. Further, a subset of recording sessions suffered from missing position tracking data and were excluded from the analyses (37/172 or 21.5% of sessions). A summary of the sessions recorded for each cell is shown in Extended Data 10.1523/ENEURO.0174-22.2022.f1-1Extended Data Figure 1-1A–C, Session and cell breakdown for Experiments 1–3. “Firing & direction” denotes sessions where cell spiking statistics  and directional statistics  were analyzed, “firing only” denotes sessions where only cell spiking statistics were analyzed. In panel C, condition descriptors for session type denote (from left to right): the starting angle relative to the cell’s PFD , rotation direction (CW or CCW), and illumination condition (light or dark). Download Figure 1-1, TIF file.Session and animal summary tables. Experiment 2 used three female Long–Evans rats (Envigo). The rats were three to six months old at the start of the study. Housing, light-dark cycle, food restriction, and water availability were the same as in Experiment 1.The same platform apparatus and room set-up that was used in Experiment 1 was used for all the baseline and rotation sessions. Only the platform apparatus was used in this experiment, including for the baseline session; the cylinder apparatus was not used for any sessions.Following one week of food restriction rats were habituated to the apparatus. For three sessions rats were placed in pairs for 20 min on the platform, and foraged for 20-mg sucrose pellets (Noyes) scattered on the floor. After these sessions the rats were then trained separately for 20 min/d and the sugar pellets were dropped in a random fashion from a food dispenser attached to the ceiling . The ratData acquisition methods and equipment were identical to those described for Experiment 1.Sessions were composed of nine sessions conducted in the following order. (1) Visual baseline 1: animals were recorded while they explored the platform apparatus for 8 min while foraging for sugar pellets. There was no rotation, the rats did not wear a blindfold, and the room lights were switched on. (2) Dark baseline 1: these differed from visual baseline 1 only in that the rat was blindfolded, the room lights were switched off, and the session’s duration was 4 min. (3–6) Dark rotation sessions: rats were blindfolded and the room lights were switched off. The experimenter rotated the platform manually at a fast speed  and constant direction for 1 min and then stopped abruptly. Each session was followed by 2 min of free movement with no rotation. Half of the sessions were clockwise (CW) rotations and half were counterclockwise (CCW) rotations.  Visual rotation sessions: these sessions were identical to the dark rotation sessions, except rats were not blindfolded and the room lights were switched on (mean rotation speed: 260 ± 43°/s). CW and CCW were balanced across these two sessions. (9) Visual baseline 2: these sessions were identical to visual baseline 1, but their duration was 4 min. In the rotation sessions the combination of blindfolding and rotating the rat was considered sufficient to disorient it and is consistent with and comparable to previous methods of producing disorientation . A summaExperiment 3 used six female Long–Evans rats (Envigo). The rats were three to six months old at the start of the study and housing, and other conditions were similar to those of Experiments 1 and 2.The apparatus consisted of two items. The first apparatus was the standard recording cylinder described above and was surrounded by a floor-to-ceiling black curtain. Sugar pellets  were automatically dropped to a semi-random location in the enclosure every 30 s. The visual landmark cue attached to the inside cylinder wall (a sheet of white cardboard) was not moved from its relative position throughout the experiments. The second apparatus consisted of the small platform mounted on a circular bearing, forming a lazy Susan turntable as described above, except the rotation of the platform was now controlled by a motor. Rats were restrained by wrapping them in a cloth with bungy cords and then placed into a Plexiglass tube (6 cm in diameter) and their heads were fixated via an implanted head bolt to a mounted bar that was attached to the set-up  Visual baseline 1: animals were recorded while they explored the platform apparatus for 8 min. There was no rotation, the rats did not wear a blindfold, and the room lights were switched on. (2) Dark rotations: the rats were restrained and head-fixed in the rotation apparatus, they were blindfolded, and the room lights were switched off. Recordings consisted of 10 s of immobility without rotation, 60 s of continuous rotation, either CW or CCW, followed by a further 30 s of immobility without rotation. Room lights were switched on and the animal’s blindfold was removed between recordings of different cells. (3) Visual rotations: these sessions were identical to dark rotations except that the room lights were switched off and the rats were not blindfolded. Sessions always included at least eight dark rotation sessions (four CW and four CCW) and these sessions started with the rat positioned facing 0°, 90°, 180°, or 270° from the target HD cell’s preferred firing direction (PFD). A subset of sessions also included four visual rotation sessions with the same starting positions. A summary of the sessions recorded for each cell is shown in Extended Data Guiding Principles in the Care and Use of Animals, were approved by the institutional care and use committee at the host institution, and adhered to the standards outlined by the National Institutes of Health Guide for the Care and Use of Laboratory Animals and the Society for Neuroscience. Surgery was conducted under aseptic conditions and animals were allowed to recover for 7 d before screening started.All procedures were conducted according to institutionally approved animal care protocols, were in accordance with the American Physiologic Society’s Electrodes consisted of a bundle of 10 25-μm diameter nichrome wires threaded through a stainless-steel cannula and attached to a modified 11 pin Augat (Experiments 1 and 2) or Mill-Max (Experiment 3) connector. This assembly was embedded in dental acrylic and could be lowered using three screws forming a tripod support for the connector and acrylic .Following training, rats returned to ad-lib feeding for 4–6 d before surgery. Rats were anesthetized with ketamine . Surgery was performed using standard stereotaxic procedures: a 10-wire drivable microelectrode  was implFollowing 7 d of recovery, each rat’s electrodes were monitored for cellular activity while the rat foraged for sugar pellets in the cylindrical screening environment. Putative HD cells were identified by monitoring activity on the microelectrodes in conjunction with the rat’s behavior and directional heading. If HD cell activity was not found, the entire electrode assembly was advanced 30–120 μm ventrally and the process repeated after at least 4 h .All cell firing was isolated using a series of window discriminators. For Experiments 1 and 2, all cell waveforms that were “accepted” and passed through the window discriminators were counted within each video frame (16.667 ms), and these data were captured by data acquisition software (LabView) and stored on a Macintosh computer. For Experiment 3, cell spikes were also captured by the window discriminators, timestamped from the beginning of the session (Eberle Electronics), and acquired by data acquisition software (LabView). The timestamps were then stored on a Macintosh computer and analyzed off-line. For all experiments, the locations of a red and a green LED that were attached either to the rat’s headstage  or to the restraint device were monitored at 60 Hz and stored on the computer and analyzed off-line at a later time. Monitoring the positions of the two LED enabled us to track the rat’s HD.smoothn; Spikes times or spike counts, along with position (LED) tracking data, were exported to MATLAB  using LabView . Tracking errors such as LED swapping were removed and position data were simultaneously interpolated and smoothed using an unsupervised, robust, discretized, n-dimensional spline smoothing algorithm  median box filter. The first and last time points when the platform rotated at a speed >∼130°/s were taken as the beginning and end of the rotation period, respectively.For Experiment 3, or sessions from Experiment 2 missing the separately recorded rotation data, we calculated the change in HD per second and smoothed this value using a moving average box filter with a 60-point (1-s) window width. The first and last time points when the platform rotated at a speed >∼60°/s were used as the beginning and end of the rotation period, respectively.angdiff) in the first 30 s of the recovery phase to the sign (±) of the cumulative angular deviation in the whole 30-s rotation phase. The same sign (±) in both would indicate that an animal continued to move its head, on average, in the same direction as in the previous rotation.After rotations in Experiment 2, rats were unrestrained during the 2-min recovery period. To determine whether animals showed a directional bias in their movements during the recovery period, we compared the sign (±) of the cumulative angular deviation (MATLAB function angdiff) in the first 30 s of the recovery phase to the sign (±) of the cumulative angular deviation in a random 30-s period taken from the first visual baseline session, before initiation of rotation. We repeated this process 1000 times per session and estimated the probability of the outcome by z-scoring the original mean difference to the shuffled values and calculating a probability as the position of the z-value (two-sided test) in the cumulative distribution function of a normal distribution with mean 0 and SD 1. This method accounts for possible biases in the animal’s behavior that were not because of rotation.To calculate the chance of these values being equal we compared the sign (±) of the cumulative angular deviation (MATLAB function angdiff).To compare statistical parameters  across the three experiments, we normalized the values by z-scoring them relative to their values from the first visual baseline session:10.1523/ENEURO.0174-22.2022.f2-1Extended Data Figure 2-1post hoc comparison . For panels D, H, and L, drift values are relative to the first visual baseline session  and the text gives the result of Holm–Bonferroni corrected v-tests for nonuniformity around a mean direction of 0°, a significant value here denotes clustering around 0° and thus a stable PFD . A, Peak firing rates in Experiment 1  = 2.3, p = 0.0317, B, Burst index in Experiment 1  = 10.3, p < 0.0001, C, Directionality in Experiment 1  = 17.6, p < 0.0001, D, PFD stability in Experiment 1. E, Peak firing rates in Experiment 2  = 7.2, p < 0.0001, F, Burst index in Experiment 2  = 5.3, p = 0.0006, G, Directionality in Experiment 2  = 112.2, p < 0.0001, H, PFD stability in Experiment 2. I, Peak firing rates in Experiment 3  = 11.4, p = 0.0001, J, Burst index in Experiment 3  = 55.3, p < 0.0001, K, Directionality in Experiment 3  = 68.8, p < 0.0001, L, PFD stability in Experiment 3. Download Figure 2-1, TIF file.Raw parameter values for all three experiments and statistical comparisons within experiments. Horizontal lines denote a significant fitglm) with the following model:zscore) before calculating the fit. The statistical deviation of the model from a constant fit was calculated using the MATLAB function coefTest. The R2 values reported were the “ordinary” values calculated by fitglm. Finally, the model representations reported in the text were calculated using the above model equation with After normalizing parameters for testing  we fitted a generalized linear model (GLM) to the data to determine the effects of each experimental manipulation across experiments. These fits were conducted in MATLAB  were calculated as the ratio of spikes emitted and time spent facing each direction. First, a HD dwell time map was calculated as the circularly kernel smoothed density estimate of all sampled HDs  and calculated parameters such as peak firing rate  for each one.circ_r; From the HD tuning curves we calculated, as a measure of directionality, the Rayleigh mean vector length  and for each shuffle recomputed a directional firing rate map and statistics as above. A cell was categorized as directionally modulated if it exhibited a Rayleigh vector greater than the 95th percentile of the shuffled values in the first visual baseline session and fired at a peak rate >5 Hz .It is well known that angular head velocity (AHV) correlates positively with cell firing rates for ADN HD cells , such thimgaussfilt with 3 × 3-pixel size filter). We generated a dwell time map by repeating this process for position data. A firing rate map was calculated by dividing the spike map by the dwell map multiplied by the position sampling interval. A map of firing probability was calculated as the ratio of the spike and dwell map. In both cases, bins containing <0.1 s of position sampling were treated as unvisited HDs.AHV was estimated as the change in HD per second smoothed using a moving average box filter with a three-point (0.05 s) window width. To determine whether decreases in peak firing rate were the result of AHV sampling we generated HD × AHV tuning curves for each cell in the first visual baseline. We first generated a HD×AHV spike map as the bivariate histogram of spike values with 6° HD bins spanning the 0–360° range and 6°/s AHV bins spanning the −300 to +300°/s range. This map was then smoothed with a 1.5 σ Gaussian filter  and burst index, between our rotation sessions and previously published data where rats were inverted (upside down). We only used spike data from Experiment 3 as these were recorded at the highest resolution (10 μs) and animals were head-fixed which was also the case during the inversion experiments. Inversion data and their upright control comparisons were taken from Shinder and Taube  manipulaBecause the data we used from the inversion experiments only included periods when the rats were facing a cell’s PFD, for comparison with the rotation disorientation data, we only included the spikes that were emitted when rats were facing within ±30° of the cell’s PFD. Only ISIs calculated during, not between, these periods were included in the ISI and burst index analyses. We also excluded spikes emitted during the first six rotations to focus on activity during full disorientation. In both cases we also excluded cells exhibiting <10 ISIs. For both experiments cells were often recorded for different numbers of sessions, and values were therefore averaged  across sessions of the same type .diff); for this comparison, burst index was defined as the proportion of ISIs with a duration <25 ms, PFD firing rate was defined as the total number of spikes emitted while facing the PFD (or ±30° of the PFD in the case of rotation sessions) divided by the total time spent facing this direction.ISIs were calculated as the amount of time between consecutive spike pairs . The data corresponding to this nearest neighbor were then substituted for the cell’s original data for all parameters . Cells with no nearest neighbor within the maximum distance were excluded, which reduced the group sizes. This approach allows repetitions of baseline values if they match multiple cells. Once this analysis was completed, groups were z-scored according to their baseline values and analyses continued as described above.To account for differences in PFD firing rates, we performed the above analyses a second time after matching each experimental and baseline group in terms of firing rate. To perform this analysis, for each cell’s PFD firing rate we found the nearest neighbor in the baseline PFD firing rate group within a maximum distance of ±1 Hz  windows. We then generated a tuning curve for each window  and calculated the PFD of each window . Because directionality and firing rates decreased significantly after 6–12 rotations, we concentrated on only the first six rotations for this analysis.CircularRegression; t tests (MATLAB function t test).Next, we used circular-linear regression to calculate the slope of these PFDs . We then found peaks in this density estimate .To detect bursts of spikes we calculated the instantaneous firing rate of a cell as a kernel smoothed density estimate of spike counts . We included only the first four interburst intervals because cells rarely continued bursting more than four times (Extended Data solve). We repeated the above process for light and dark sessions when animals were head-fixed (Experiment 3) or actively locomoting (Experiment 2). This procedure provided one value for each cell in each session type .In this way, an interval of 2 s would provide an estimate of rotation speed at 180°/s, which was the actual speed of rotation in Experiment 2 (because 2 s was the time taken to complete one rotation). We then ranked converted interburst intervals and for each cell we fitted an exponential function to the values for all sessions combined:10.1523/ENEURO.0174-22.2022.f6-1Extended Data Figure 6-1Figure 6-1, TIF file.Additional example cells showing postrotational bursting in Experiment 3, where rats were head-fixed and restrained during rotations. Example cells, one per row, left column shows activity in a dark rotation session, right column shows activity for the same cell in a rotation session in the light. Sessions are clipped to the end of the rotation phase (from 5 s before to 15 s after rotations ended). Blue lines denote the animal’s HD, red markers represent action potentials, black areas show a spike histogram (200-ms bins). Blue triangles denote detected spike bursts , blue text between two triangles gives the duration between these bursts. In the dark, cells fired bursts of spikes after the rotations ended. Initial bursts occurred at a frequency close to the rotation frequency, but the time between consecutive bursts increased steadily. In the light, postrotational bursting was absent. Download < 0 ; thus, these values were not included in the calculations.Finally, to calculate an overall vestibular time constant for each session type we averaged the time constants across all cells. For session types other than head-fixed rotations in the dark, interburst intervals either decreased immediately resulting in an extremely small time constant (head-fixed rotations in the light: mean ± SEM = 0.80 ± 0.55 s) or immediately plateaued resulting in a time constant fitdist, 0.02-s bins with a 0.04-s bandwidth Gaussian kernel). We then calculated the frequency-time power spectral density (PSD) spectrogram of this firing rate vector using 512 sample long Hanning windows with 90% overlap and a frequency resolution of 1024 (MATLAB function spectrogram). The resulting spectrograms were normalized such that 0 Hz was equal to the frequency of rotation in that session (estimated from the position tracking data) and spectrograms were z-scored column-wise to reduce PSD fluctuations within and across animals.In Experiment 2, HD cells continued to fire in bursts after rotations had ended and these bursts seemed to be at the same frequency as the preceding rotations. To test this observation, for each HD cell, we calculated an instantaneous firing rate vector as the kernel smoothed density estimate of spike times  was passed through one of the recording wires to conduct a Prussian blue reaction. Each rat was then perfused transcardially with saline followed by 10% formalin  and its brain was removed for analysis. Brains were further soaked in 10% formalin and then soaked in 2% potassium ferrocyanide . They were then soaked in 10% formalin again and then soaked in 20% sucrose for at least 24 h. The brains were frozen and then sliced on a cryostat  and mounted onto slides, which after drying were stained with cresyl violet  first foraged for small sugar pellets in a cylinder in the light for 8 min and then again while blindfolded in the dark for 4 min. For subsequent rotation sessions, rats were rotated unrestrained on a circular platform at either slow or fast speeds. Rotations were made in alternating back-and-forth directions almost continuously for 2 min with each block of rotations lasting 10–30 s before stopping and switching directions. Two test sessions were conducted in darkness while the rat was blindfolded. For a subset of recordings two additional test sessions were conducted in the light with no blindfold  first foraged for sugar pellets in baseline sessions, as in Experiment 1 above, except they were conducted on a circular platform. Sessions took place in the light (8 min) and then again while the rats were blindfolded and in the dark (4 min). In test sessions, rats were rotated unrestrained for 1 min followed immediately by a 2-min session of free exploration on the same platform. These sessions were first conducted in darkness while the rat was blindfolded, after which the sessions were repeated in the light and with no blindfold , presumably because cessation of prolonged rotation of the body elicited an illusion of self-motion in the opposite direction, which the rats may have attempted to compensate for (38). Across three rats we recorded 23 HD cells from the ADN  first foraged for sugar pellets in the cylinder and in the light for 8 min. The rats were then restrained in a Plexiglass tube, head-fixed via an implanted bolt on top of their skull, and passively rotated continuously for 1 min via a small, motorized turntable positioned inside the cylinder. They were rotated either in the light or in darkness while blindfolded . To the right is a schematic diagram showing delineated brain structures  = 1.4, p = 0.24, F = 1.1, p = 0.38, F = 1.4, p = 0.25, A number of previous studies comparing active and passive movement have reported significant suppression of the HD signal during passive restraint . Howevert tests, we found that peak firing rates and burst index scores did not differ between the baseline sessions, regardless of illumination or if they were conducted after the disorienting sessions . We first analyzed peak firing rates and burst index scores ; these normalized values are shown in sessions A,D. This10.1523/ENEURO.0174-22.2022.f2-2Extended Data Figure 2-2A, Head direction (HD) tuning curve and angular head velocity (AHV) tuning curve for an example HD cell in visual baseline session 1. B, Left, the HD × AHV spike maps for the same cell but for dark baseline session 1. Right, The HD × AHV spike tuning histogram predicted for this this cell in dark baseline session 1 based on its activity in visual baseline session 1 (shown in A) and the animal’s AHV × HD sampling in dark baseline session 1. Bins that are empty in either map are shown as empty in both maps. C, Left, The HD tuning curve observed in dark baseline session 1. Right, The HD tuning curve predicted for dark baseline session 1. D, Spike rate index: (a − b)/(a + b), where a is the sum of the actual spike map and b is the sum of the predicted spike map, for every experimental condition. Low values indicate that fewer spikes were recorded than predicted while high values indicate the reverse. Values of zero indicate that a cell fired at exactly the rate predicted, which was the case in almost every condition. Text gives the result of Holm–Bonferroni corrected t tests comparing each group to the first visual baseline session . E, Peak rate index: (a − b)/(a + b), where a is the peak firing rate in the actual HD tuning curve and b is the peak firing rate in the predicted HD tuning curve, for every experimental condition. Peak rate indices were generally less than zero, meaning that peak firing rates were lower than would be expected even when AHV tuning was taken into account. Text gives the result of Holm–Bonferroni corrected t tests as in D. Download Figure 2-2, TIF file.F = 13.5, p = 7.5 × 10−12, R2 = 0.19), we found that faster rotation speed  and, to a lesser extent, darkness  were associated with lower peak firing rates. Although ADN HD cells are known to be modulated by angular head velocity  and unidirectional rotation  did not have a significant impact on peak firing rates. Further, rotation speed and darkness did not interact to effect peak firing rates . This relationship can be visualized in Peak firing rates, however, were reduced significantly during dark rotation and fast visual rotation sessions A. By fitity AHV; , this efity AHV; . PassiveF = 96.1, p = 1.22 × 10−62, R2 = 0.59) revealed that, in order of decreasing magnitude, faster rotation speed , passive rotation  and unidirectional rotation  were all associated with decreased burst index scores. Darkness did not have a significant impact on burst index scores alone  or in interaction with rotation speed . This relationship can be visualized in Burst index scores decreased significantly in all rotation sessions, indicating that cells fired less often in a bursting mode during rotations compared with active baseline sessions. This decrease was larger in sessions with faster rotation speeds D. A GLM To compare the strength of the directional signal  across the three experiments, we normalized mean vector length values using the same approach as described above D. PFD st10.1523/ENEURO.0174-22.2022.f3-1Extended Data Figure 3-1x-axes for Experiment 3 are truncated shortly after the end of the rotation period as the animal could no longer sample directional angles. Download Figure 3-1, TIF file.PFD drift throughout baseline and rotation sessions. In all plots, filled markers represent HD cells. For Experiments 2 and 3, when a cell was recorded in one session type more than once, their responses were averaged to give a single value for each session type. Asterisks above each plot denote a significant mean direction around 0° , color corresponds to group color (see legends). The 10.1523/ENEURO.0174-22.2022.f3-3Extended Data Figure 3-3A, A pair of co-recorded HD cells in the first visual baseline session and subsequent blindfolded baseline session. B, In both sessions, the tuning curve of cell 2 is rotated to find the angular shift at which it most highly correlates with cell 1. These angles are similar and deviate by only 7°, confirming that the cells remain coherent between sessions. C, Results when the same procedure is conducted on all six pairs of co-recorded HD cells in Experiment 2. Filled markers represent cell pairs, lines and circular markers denote circular mean and SD. The angle between tuning curves in each session is compared to the angle observed in the first visual baseline. The four blindfold rotation sessions and two visual rotation sessions are averaged to give a single value for each session type. The text above each group gives the result of a v-test of nonuniformity around 0°; significance here denotes a bias for values around 0°. Cell pairs were significantly coherent in all sessions, even during rotation, except when the rat was blindfolded and rotated. However, this group also exhibits a mean direction of 0° and is nearing significant directionality for this angle. Download Figure 3-3, TIF file.10.1523/ENEURO.0174-22.2022.f3-2Extended Data Figure 3-2A, Left, Schematics representing the session types in Experiment 2, when rats were rotated unrestrained. Sessions are arranged temporally from top to bottom. Right, Two example HD cells, one per column. Tuning curves are given for baseline sessions (first and last rows). Windowed tuning curves  are shown for rotation sessions (middle rows). Black horizontal arrows denote the end of the rotation period and the start of the recovery period. During dark rotations HD cells were disrupted, they lost directionality and their tuning curves were unstable. However, in the recovery period cells quickly regained these properties, even in the absence of visual cues, although their PFDs were offset randomly from baseline. During rotations in the light, cells remained largely unaffected throughout the rotation. B, Same as A but for Experiment 3 when rats were rotated while restrained. Here, directionality decreased quickly during rotation sessions, but cells maintained roughly consistent PFDs. Tuning curves also drifted in the direction of rotation at the start of rotation sessions. Download Figure 3-2, TIF file.Example HD cells showing the impact of disorientation on HD cell tuning. F = 226.01, p = 1.24 × 10−98, R2 = 0.79) revealed that, in decreasing order of magnitude, faster rotation speeds , unidirectional rotation  and darkness  all significantly reduced directionality. There was also a significant interaction between rotation speed and darkness  such that directionality was disrupted more by increasing rotation speed in darkness than in the light. This relationship is depicted in β = −0.15, t = −1.85, p = 0.0658; all standardized β coefficients).Directionality was significantly decreased in all rotation sessions however, except for the slowest visual rotation sessions A. FittinF = 10.2, p = 5.2 × 10−9, R2 = 0.15) revealed a significant interaction between darkness and rotation speed; increasing rotation speed in the dark was associated with significantly greater drift in the cell’s PFD . Darkness alone was also associated with increased PFD drift . No other factors significantly affected drift . This relationship is shown in p = 0.0575; Extended Data PFDs were stable relative to the first visual baseline in all sessions except nonhead-fixed dark rotation sessions and this instability appeared to increase with rotation speed . In agreAs peak firing rates B and dirt(19) = 0.33, p = 0.745, Cohen’s d = 0.09), although mean vector lengths were consistently lower in the dark sessions  = −2.10, p = 0.049, Cohen’s d = 0.25). Together these results suggest that while visual cues enable HD cells to sustain greater directionality  during disorientation, they do not facilitate a faster recovery from disorientation. Example tuning curves at different periods of recovery from disorientation are shown in As with peak firing rates, directionality decreased very quickly from baseline levels after rotation onset regardless of self-locomotion C,D. In tWhen rats were restrained, HD cells maintained their PFDs during rotations even while their overall directionality  decreased, suggesting that they may have used AHV to maintain a consistent PFD [t(19) = 0.32, p = 0.7553, Cohen’s d = 0.04; two-sample t-test comparing absolute visual/dark slopes). Importantly, however, these effects were not observed in sessions where animals could actively locomote . Blue lines denote the animal’s HD, red markers represent action potentials, black bars show a spike histogram (200-ms bins). Blue triangles denote detected spike bursts , blue text between two triangles indicates the duration between these bursts. In both session types cells generally did not fire in bursts after the rotations ended. The bottom most cell (cell 7) is the only example of potential postrotational bursting that occurred in Experiment 2 during a dark rotation session. However, the number of spikes emitted was so low that these postrotational bursts did not meet our detection criteria. Download 10.1523/ENEURO.0174-22.2022.f6-3Extended Data Figure 6-3A, FFT analysis of the kernel smoothed spike counts shown in t = 0), which correspond to the activity shown in t = 1) corresponding to the postrotation bursts shown in t = 1.0 and t = 1.2. There was also a significant effect of time  = 2.12, p = 4.21 × 10−3, F = 6.21, p = 1.76 × 10−14, B, Same as A but for cells recorded during rotations where animals were free to actively locomote. Postrotation bursting is absent. Bottom, There was no significant effect of time  = 0.47, p = 0.9700, F = 0.51, p = 0.9554, Figure 6-3, TIF file.Postrotational bursting analyzed by FFT (fast Fourier transform). Finally, we sought to compare the activity of HD cells under two different conditions of disorientation: constant rotation and inversion. The rotation data we used were from Experiment 3 where spike events were accurately timestamped to enable analysis of interspike intervals (ISIs). The inversion data were taken from If cells fired with a lower number of bursts during periods of disorientation, then we would expect a decrease in both burst index and the proportion of short ISIs. To explore this possibility, we first plotted the ISIs from Experiment 3 during active locomotion in visual baseline sessions (“baseline”) and during rotation , suggesting that there was little time for the HD network to drift or lose directionality. This result is also consistent with previous reports , which sDirectionality also decreased as rotation speed increased and this occurrence was exacerbated when visual cues were absent. Similarly, HD cell PFDs were increasingly unstable as rotation speed increased in the dark. Interestingly though, stability was unaffected by the rotations when visual cues were available. Together, these results suggest that visual cues may be used to orient and stabilize the HD signal while vestibular inputs are more crucial for updating the directional tuning over short timescales of a few seconds. They also highlight the distinction between directionality  and stability , low individual directionality scores do not necessarily mean that the HD system is nonfunctional.Although the degree of directionality and stability remained higher when visual cues were available, they did not facilitate a faster recovery to baseline levels after the rotations ended. This finding suggests that vestibular postrotatory sensations must dissipate following disorientation before normal directionality can return and that visual inputs surprisingly do not speed up this process. At first glance, this finding appears to contradict the stability afforded by visual cues during rotations; however, the vestibular system is insensitive to constant unidirectional rotation , and thuExamining HD cell activity more closely during the initial 6–12 rotations, we found strong differences between head-fixed and freely moving sessions. If the rats could actively locomote, HD cells lost their directionality almost immediately during the dark rotations, but remained relatively stable if visual cues were available, consistent with their general activity during rotations as described above. However, during head-fixed sessions cells showed a consistent and characteristic response: with each revolution their tuning curves increasingly shifted in the direction of rotation whether or not visual cues were available. This cumulative shift is consistent with the gradual loss of sensitivity we would expect to occur in the vestibular system under constant unidirectional rotation . It woulWhy this cumulative drift was only observed during head-fixed rotations and not during head-free rotations is unclear. It is also unclear why cells were generally more stable during head-fixed rotations, even maintaining stable PFDs in the dark, compared with head-free rotations. One possibility is that head movements from active locomotion introduced an additional source of directional noise and complexity to the rotations, which more quickly led to disorientation in freely moving sessions. Another possibility is that self-generated movements inhibited (or suppressed) vestibular signals , which iIn dark sessions where rats were head-fixed and passively rotated, HD cells fired bursts of spikes immediately after rotations ended. These bursts initially occurred at a frequency matching the rotations, but decreased steadily postrotation . These effects were not observed in light sessions or if rats were free to actively locomote during the postrotation period. This postrotational spike bursting was also noted in an earlier brief report when unrestrained rats were rotated continuously on a turntable for ∼1 min and then stopped abruptly , but shoThis phenomenon is reminiscent of postrotation vestibulo-ocular activity, or “postrotational nystagmus”: during rotation the eyes make compensatory smooth eye movements followed by a saccade-like reset phase (when the eye movement reaches its maximum extent), to maintain a stable gaze on attended visual stimuli . These iThere are a few similarities between postrotational nystagmus and the activity we observed in HD cells. (1) Postrotation bursting in HD cells matched the frequency of rotations and this bursting decreased with time, as is observed in postrotational nystagmus. (2) Postrotational nystagmus is more apparent when visual cues are absent during the postrotation period , and is Why does postrotation HD cell activity share so many characteristics with postrotational nystagmus? One possibility may be related to the velocity storage system described above. In the monkey this system is thought to be found in the rostral portions of the vestibular nuclei, such as the caudal ventral superior vestibular nucleus, medial vestibular nucleus, and lateral vestibular nucleus . In the Future experiments could seek to test this hypothesis by lesioning the nodulus and uvula of the vestibulo-cerebellum, which are involved in “dumping” the contents of the velocity storage mechanism . AnotherIn conclusion, by monitoring responses of HD cells during spatial disorientation, we found that they never become quiescent, they continue to fire coherently even when the animal is substantially disoriented, and individual cells no longer display directional or stable firing. This finding is consistent with an attractor network model of the HD system, where activity in the network is never abolished, but only shifts to different points or becomes distributed around the attractor ring. These shifts and distributed firing lead to a decrease in peak firing rates, and if strong enough, essentially result in the loss of directional tuning altogether. When visual cues were available, they only helped to maintain directionality during disorientation by a small amount or for a short period of time in the case of fast continuous rotations. In addition to visual and vestibular inputs, we also found that the HD network exhibits postrotational activity, which shares several features with postrotational nystagmus in the vestibulo-ocular system. One interpretation of this finding is that the HD network receives input from a velocity storage process that has its origins in the vestibular system. This process is commonly associated with the vestibulo-ocular reflex and maintaining an attended visual image focused on the fovea in the face of head movements. In the HD circuit, this process could also prove advantageous following disorientation by providing an additional mechanism for stabilization based on visual cues. More generally, this velocity storage mechanism would also mediate vestibular inputs to the HD system, lengthening these high-frequency outputs, which may provide a more accurate estimation of slow head movements. Additional experiments will be needed to test this potential input directly. Thus, the HD system utilizes multisensory integration from a variety of inputs to prevent disorientation. Although strong vestibular disruption, such as that occurring during continuous rotation, appears particularly difficult for the system to overcome, it appears that vestibular input is prioritized over other sensory types.


Sarcoidosis is an immune-mediated disorder. Its immunopathology has been steadily mapped out over the past few decades. Despite this, the underpinning mechanisms for progressive fibrotic sarcoidosis is an almost uncharted area. Consequently, there has been little change in the clinical management of fibrotic sarcoidosis over the decades and an unfocused search for new therapeutics. In this review, we provide a comprehensive examination of the relevant immune findings in fibrotic and/or progressive pulmonary sarcoidosis and propose a unifying mechanism for the pathobiology of fibrosis in sarcoidosis. This review provides a comprehensive examination of relevant immune findings in fibrotic sarcoidosis and draws on these to propose a unifying mechanism for the pathobiology of disease.https://bit.ly/3TR4SaB Sarcoidosis is a multi-system immune-mediated, granulomatous disease characterised by the presence of non-necrotising epithelioid granuloma accompanied by varying degrees of lymphocytic inflammation. Activated CD4 T-cells with T-helper (Th) 1 and Th17/Th17.1 bias  drive grThe general management of pulmonary disease in sarcoidosis is relatively well established –11 and mFibrotic pulmonary sarcoidosis carries a significant mortality burden. A retrospective French cohort study of patients (n=142) with stage 4 Scadding radiograph changes (fibrosis) showed that these patients had a mortality rate of 16% at 10 years from the point of diagnosis . SarcoidA significant problem with the management of fibrotic sarcoidosis is that it is not possible to predict which patients proceed to fibrosis. Indeed, there are no large-scale prospective studies that examine the incidence and risk factors for developing fibrosis in pulmonary sarcoidosis. Many patients with fibrotic sarcoidosis can have very few symptoms during the active fibrotic stage, preventing them from seeking medical attention and possibly delaying their presentation to a stage that is less amenable to anti-inflammatory treatments. These factors, coupled with a poor understanding of the causes of progression of granulomatous inflammation to fibrosis have hampered development of robust management strategies and identification of patients for clinical trials.In this review, we draw together and discuss the findings and potential immune mechanisms underlying fibrosis in sarcoidosis. Specifically, we are interested in why some patients progress to fibrosis while others do not and the factors contributing to progression to fibrosis, rather than susceptibility to the disease itself. As very few studies have deliberately studied fibrotic sarcoidosis, we also gleaned information from publications that include chronic active sarcoidosis or progressive radiological disease and state these qualifications against the relevant reports. We considered chronic progressive active sarcoidosis as a prerequisite for fibrosis, but note that the majority of such patients do not develop fibrosis if treated and many remit spontaneously, the latter usually within 6 months. In some studies, late-stage disease was compared to Lofgren's syndrome  and these are highlighted. The definition of disease activity and disease progression varies between studies and these are emphasised where appropriate. In all cases, Scadding chest radiograph stages are defined as follows: stage 1 – no lung parenchymal abnormalities visible, mediastinal and/or bilateral hilar lymphadenopathy only; stage 2 – presence of lung parenchymal abnormalities and bilateral hilar lymphadenopathy; stage 3 – presence of lung parenchymal abnormalities but no bilateral hilar lymphadenopathy; and stage 4 – chest radiograph presence of lung fibrosis with variable lung parenchymal abnormalities and lymphadenopathy . We starTGFB1 isoforms from macrophages promote fibrosis, while those originating from regulatory T-cells (Tregs) have an opposite effect [TGFB polymorphisms may well be those for whom disease does not progress to fibrosis due to the quenching of inflammation and halting of chronic inflammation, repair and fibrosis.TGF-β is a major regulator of both physiological and pathological repair (fibrogenic) processes . Inhibite effect . In addiTGFB genetic polymorphisms were examined in patients with acute or self-remitting pulmonary sarcoidosis (n=50), chronic disease with fibrosis (n=24) and those without fibrosis (n=34) compared to those with Lofgren syndrome (n=46) and a healthy control group (n=315). Disease categories were allocated after a 4-year follow-up period. The TGFB3 4875 A (OR 7.9), TGFB3 17369 C (OR 5.1) and TGFB2 59941 G alleles (OR 2.9) were over-represented in chronic fibrotic patients compared to those with acute/self-remitting and nonfibrotic chronic sarcoidosis. Interestingly, TGFB1 gene polymorphisms were not associated with fibrosis [TGFB pathway in 32 patients with fibrosis (chest radiograph Scadding stage 4) also demonstrated an association with TGFB3 with a mutated C allele, but there was a lower TGFB2 G-allele mutation frequency [In a study on sarcoidosis, brosis n= and thosrequency . It is nrequency . Howeverrequency . Similarrequency . As it iTGFB from another angle, GREM1 polymorphisms were examined by several investigators in fibrotic sarcoidosis patients. GREM1 encodes Gremlin, which inhibits bone morphogenic proteins (BMPs), a group of growth factors from the TGF-β superfamily that counteract the action of TGF-β. The balance between TGF-β and BMP signalling is thought to be an important determinant of a fibrotic response [GREM1 polymorphisms between sarcoidosis patients without chest radiography abnormalities (n=116) compared to patients with fibrosis on chest radiography (n=59). The most significant association was with GREM1 rs1919364. Carriers of the GREM1 CC genotype at position rs1919364 were 6.4 times more likely to develop lung fibrosis [Examining the possible involvement of response , 30. Sigfibrosis .e.g. TLR4 in the plasma membrane detects lipopolysaccharide (LPS), TLR5 detects flagellin and TRL1, 2 and 6 recognise bacterial lipoproteins. Those in the endosome, such as TLR3 and TLR8, detect nucleic acids . Of these, TLR2 has been most frequently implicated in the pathogenesis of sarcoidosis [eronet al. [TLR2 polymorphisms in chronic sarcoidosis (using radiographic progression at 4 years) and found variable results in its link to chronicity [TLR1, TLR6 and TLR10 genes (which can act as co-receptors with TLR2) were absent in the fibrotic group [TLR10) and rs5743604 (TLR1) in chronic fibrotic patients differed significantly from those of healthy controls. However, there were no differences in the above allele frequencies between sarcoidosis patients with pulmonary fibrosis and those without fibrosis.Variants of the TLR genes have also been implicated in chronic and progressive sarcoidosis. TLRs are a group of pattern-recognition receptors that are integral to the ability of the innate immune system to recognise, activate and regulate the interaction between innate immune cells and microbial and other antigens . Differecoidosis –35. Heronet al.  studied ronicity . Howeveric group . FurtherTLR3 polymorphism Leu412Phe (rs3775291), which was associated with accelerated disease progression and elevated mortality risk in IPF [TLR3 polymorphism and persistent clinical disease in two cohorts of Irish and American Caucasians with pulmonary sarcoidosis. “Persistent disease” was determined at 2 years and defined as 1) patients who were at Scadding stage 2 or 3 on chest radiograph with associated abnormal pulmonary function parameters  and/or total lung capacity and or transfer factor <80% of predicted values), 2) patients with Scadding stage 4 chest radiograph, or 3) patients who were prescribed corticosteroids. In a very small sub-study (n=3 patients), activation of TLR3 in primary lung fibroblasts from 412 F-homozygous pulmonary sarcoidosis patients resulted in reduced IFNB and TLR3 expression, and reduced apoptosis and dysregulated fibroproliferative responses compared with TLR3 wild-type patients [TLR3 polymorphism with persistent disease in sarcoidosis (some of which with fibrosis) and highly progressive IPF suggests that it is possible that the TLR3 signalling pathway anomalies are involved in susceptibility to fibrotic pulmonary sarcoidosis, either via loss of function in innate immune cells like macrophages or reduced apoptosis in lung fibroblasts [In another study, the k in IPF , was evapatients . The funroblasts .ANXA11 and was the first gene linked to disease susceptibility in sarcoidosis using the genome-wide association studies approach [ANXA11 is most highly expressed in whole blood cells, particularly B lymphocytes, monocytes and some subsets of immature myeloid cells. Peripheral blood mononuclear cells (PBMCs) isolated from sarcoidosis patients who carried the ANXA11 R230C SNP were more resistant to apoptosis than the wild genotype, although this was a small study [Annexin A11 is encoded by approach , 41. Polapproach ; a findiapproach , 43. Annll study . In an AGREM1 studies [ANXA11 findings [In general, studies on polymorphisms in fibrotic sarcoidosis are small and few replicative cohorts were examined. As such, it is difficult to draw definitive conclusions from them; apart perhaps from the  studies  and the findings –43. ThesTranscriptomic studies offer the next layer of insight into possible causes of fibrotic sarcoidosis by linking gene expression in cells or tissue with possible functional abnormalities.ockstoneet al. [In one of the first transcriptomic studies in lung tissue from sarcoidosis patients, Leet al. , compareeet al. . In the eet al. . This suothet al. [IRF1), a transcription factor stimulated by type I and II (but not the anti-inflammatory type III) IFNs, was significantly different between sarcoidosis patients with reduced lung function compared to those with normal lung function [IRF1 is a critical transcription point in the IFN signalling pathway and its engagement stimulates the transcription of a specific set of pro-inflammatory chemokines which recruit both innate and adaptive immune cells to the site of activation [SPP1+ macrophages) [An important study from Khet al.  followedfunction . IRF1 istivation . This istivation  and in aophages) . Both ofothet al. [ockstoneet al. [STAT1 – and sets of genes related to IFN signalling pathways. The type II IFN (IFN-γ) signalling data are consistent with it playing a significant role in Th1-type inflammation in sarcoidosis, which is not unexpected. However, the involvement of type I IFN genes is interesting and corroborates the findings mentioned above [Khet al.  also queeet al.  and anoted above  that lined above . This raed above . Of noteed above , 53, proukmirovicet al. [a priori hypothesis, four gene modules were identified that corresponded to four clinical groups, one of which being chronic sarcoidosis. Weighted gene co-expression network analysis, a bioinformatics application for exploring the relationships between groups of gene sets (representing a module) that change together with clinical features or types, was able to match modules of genes to these four “endotypes”. For the chronic sarcoidosis endotype, a 51-gene module was identified, although the identity of the driver genes was not published. However, in the supervised analysis comparing patients with Scadding stage 1 chest radiographs (n=54) to stage 4 (n=33), gene sets that correlated with Scadding progression showed enrichment with interleukin (IL)-6, IL-8 signalling, stem cell reperfusion and IL-1 signalling pathways. In the fibrotic (stage 4) group, cell cycle, signal transduction in mTORC1 and high shear stress induced platelet activation gene sets were found to be upregulated. In terms of specific genes, there was increasing expression of PLA2G7, ID1, LGMN, SLC40A1 and CCL2 and reducing expression of PDLIM1 and AOC3 with increasing Scadding stage. Patients with reticular abnormality on CT scans showed upregulation of fibrosis-associated genes such as TGFBR1, COL3A1, TLR3, ID1, TCF4, IGFBP6, PLA2G7, FADS1, ARGHAP12 and MMP10. TLR3 is the notable finding here given previous studies, as discussed above [PLA2G7 as a pro-inflammatory pathway  that can be modulated by calorific restriction, pointing both to a potential mechanism of action for PLA2G7 in persistent disease and fibrosis, and also an accessible lifestyle-modifying treatment [The next significant advance came from Vcet al. , who pered above , 39. A rreatment .via inactivation of Unc-51-like autophagy-activating kinase and autophagosome formation [a priori hypothesis, are powerful considerations for the interpretation of other cellular findings, as discussed below.The most relevant findings here are mTORC1 upregulation in the group of patients with fibrotic CT scans and, possibly, the involvement of monocytes or monocyte-derived macrophages ) in the progression of Scadding stage 1 to stage 4 (fibrosis). Uninhibited mTOR signalling in macrophages has already been shown to be a feature of excessive granuloma formation , making ormation , a smallormation . These giaoet al. [e.g. tumour necrosis factor-α (TNF-)α. However, here, in single-cell transcriptomic analysis, the finding that macrophages of those with progressive disease have a higher expression of certain MHC II allele points more to their specific role, possibly in persistent activation of CD4 T-cells and maintenance of granuloma. In a re-analysis of five transcriptomic datasets, including those from Liaoet al. [ockstoneet al. [One caveat to these data is that they were from bulk RNA sequencing of all BAL cells and, therefore, do not pinpoint the cellular origins of the differentially expressed genes. However, newer studies using single-cell RNA sequencing should be able to address this. Single-cell RNA sequencing studies are currently limited to a few datasets in peripheral blood  and BAL oet al.  showed, oet al. . Many haoet al.  and Lockeet al. , the sameet al. . Both ILIn terms of measured protein in blood and lungs, we highlight three due to the strength of evidence and rationale.via receptors such as TLR2 and the receptor for advanced glycation end-products, and aggregates of SAA have been found in granuloma. SAA has been shown to activate NF-κB in TLR2 – expressing human cell lines and regulating experimental Th1-mediated granulomatous inflammation through IFN-γ, TNF and IL-10. Furthermore, SAA has the potential to stimulate production of TNF, IL-10 and IL-18 in lung cells from patients with sarcoidosis [SAAs are acute phase-response proteins. They are cytokine-like proteins involved in cell–cell communication in inflammatory, immune, neoplastic and protective pathways . SAA cancoidosis .henet al. [eijeret al. [ietriet al. [per se.Cnet al.  demonstrret al.  measurediet al.  on IPF svia polarisation of macrophage differentiation to M2-like, anti-inflammatory macrophages [It is not clear whether SAA drives progression or if it is a by-product of inflammation and fibrosis. SAA can aid antigen clearance and may be upregulated within fibrotic niches to perform antifibrogenic function rophages . Howeverrophages , which sechkovskyet al. [CCL-18 is a cytokine secreted by the myeloid lineage cells – macrophages, dendritic cells and keratinocytes. It can induce fibrogenesis through a multitude of mechanisms including collagen production in human lung fibroblasts . In macryet al. , who alsIn a comprehensive review of the circulating cytokines and chemokines in sarcoidosis patients, which included a comparison between fibrotic (n=19) and nonfibrotic (n=21) sarcoidosis, IL-7 was one of three cytokines (the other two were IL-5 and GM-CSF) that were significantly different between the fibrotic and controls but not between fibrotic and nonfibrotic sarcoidosis . The mosepzienet al. [hiCD16hi; nominally acknowledged as the inflammatory monocyte subset) at the time of diagnosis. In BAL cells, intermediate monocytes that were producing TNF-α without stimulation were the only correlate of disease progression. There were only two stage 4 Scadding patients, so these correlates only applied to disease activity and progression, and not fibrosis.The role of monocytes in the pathogenesis of lung fibrosis has gained traction in recent years, with increased levels in blood observed in IPF patients, and correlation with amount of fibrosis and possibly with outcome and progression , 75. An net al.  reportedin vitro model of macrophage differentiation suggested that there were two polar subsets of macrophages. Macrophages that mainly secreted pro-inflammatory cytokines were called classically activated macrophages (M1), which can be activated either by IFN-γ or LPS, and macrophages that attenuated inflammation and encouraged wound repair were referred to as alternatively activated macrophages (M2). The latter were activated by IL-4 or IL-13 [in vitro model of macrophage polarisation is unlikely to be strictly valid in vivo, and there is less evidence of this polarisation in humans. It is also now recognised that macrophage plasticity dictates the presence of several intermediate states of macrophages [hakarovet al. [Macrophages are an integral part of granuloma in sarcoidosis. For at least a decade, an or IL-13 . Fibrotirophages . For exarophages . Chakarovet al.  have alshamaeiet al. [+ M2 macrophage populations and giant cells in the lung and lymph node sections was reported with a significant association with radiological progression. However, it is unlikely that CD163+ macrophage presence is specific to fibrotic sarcoidosis as it has also been shown in IPF lungs [These caveats aside, there is evidence for M2-like macrophages in fibrotic sarcoidosis. Siet al.  examinedPF lungs , 82. A mPF lungs .enyet al. [in vitro than those isolated from patients with inactive sarcoidosis, producing more TNF-α, IL-1β and TGF-β1. These macrophages also secreted more PAI-1 (plasminogen activator inhibitor-1), which blocks fibrinolysis and promotes extracellular matrix accumulation in tissues. These findings link well with another study [via secretion of PAI-1, TGF-β1 and IL-17 within the hypoxic environment of the granuloma. However, since most active disease do not progress to fibrosis, this remains a speculation.More recent data from Jyet al.  suggest er study  that sho+ T-cells are divided into unique subsets based on the cytokines they secrete and their distinct functional abilities. The CD4+ Th17 cell subset expressing the pro-inflammatory cytokine IL-17A is emerging as an important driver of fibrosis in general [rooset al. [CD4 general –88, poss general . A large general . However general , 91–99.  general , is mark general . Brooseset al.  analysedeladaet al. [+ Th17 cells are the dominant producers of TGF-β and, when co-cultured with fibroblasts, induced collagen production. PD-1 blockade and STAT3 inhibition appear to reduce collagen production in these co-cultures. In another study, PD-1+ CD4 T-cell levels in blood were higher in patients with active sarcoidosis  compared to resolved disease [+ CD4 T-cells also demonstrated reduced proliferative capacity, and a paired BAL and blood sample comparison showed a higher level of these cells in BAL. These are important but challenging concepts as they suggest that PD-1/PD-L1 pathway activation in CD4 T-cells is associated with increased IL-17 and TGF-β production while also reducing proliferation of these cells. At the advanced end of the disease spectrum, immunohistochemical analysis of lungs of two patients with refractory fibrotic sarcoidosis showed that, in the fibrotic parts, T-cells did not express IL-23R and IL-17, and alveolar macrophages did not stain with anti-IL-17 monoclonal antibodies [eladaet al.'s [eladaet al. [In a study primarily on IPF patients, Caet al.  showed t disease , althougtibodies . This haet al.'s  findingsaet al. ) and thaaet al. –105, so attersonet al. [The archetypal Th1 and Th17.1 cytokine, IFN-γ, is an antifibrotic cytokine, yet it is the dominant mediator of pathogenesis in sarcoidosis. It is therefore an interesting conundrum as to how fibrosis ensues within this IFN-γ-rich environment. This paradox has led many to hypothesise that a transition from Th1 to Th2 pathway activation occurs in chronic sarcoidosis, perhaps as a response to persistent inflammation . Th2 cytnet al. , who ananet al. . Overallnet al. , 116. Innet al. , 118, su+ T-cells that rely on the transcription factor FOXP3 for development and function. They tend to be immunosuppressive and play a critical role in the function, establishment and maintenance of immune tolerance via multiple mechanisms including production of inhibitory cytokines (IL-10), expression of inhibitory receptors such as CTLA-4 and the ability to deplete the inflammatory environment of pro-inflammatory cytokines such as IL-2. Furthermore, Tregs can undergo reprogramming in certain tissues and acquire the ability to suppress specific cells such as TH2 effector cells, which are potent drivers of fibrosis though production of IL-13 and IL-4 [versus-host disease-induced lupus nephritis [Tregs are a specialised subset of CD4and IL-4 . Treg ceand IL-4 , dystropand IL-4 , cardiovand IL-4 , chronicephritis  and chroephritis . Sarcoidephritis , and Treephritis . The ratephritis . In an iephritis . It was ephritis . Howevere.g. SAA, nondegradable components of Mycobacterium tuberculosis or Cutibacterium acnes, silica, pine pollen; reviewed in [e.g. silica dust, could be a part of a combination of factors that come together to cause chronic fibrosis.An important clinical observation is that fibrosis in sarcoidosis typically occurs over a long period of time – 10, sometimes 20 years. Apart from rare cases of rapidly progressive fibrosis, it seems clear to us that the rate of fibrosis is much slower than that seen in IPF, connective tissue interstitial lung disease or hypersensitivity pneumonitis. This raises some interesting questions: is the pathogenesis of fibrosis in sarcoidosis different? and, intriguingly, could it be slowed down by the IFN-γ-rich milieu? Another potential contributor to this slow progression is the role of the antigen. The identity of the antigen has been elusive, but it seems from the large and definitive ACCESS study that there is no single antigen for all patients nor even an individual. Nor is it the only trigger for an immune response – host factors such as chronic stress have long been noted by clinicians to be associated with worsening of sarcoidosis and there is a well-established immunological basis for this . Notwithiewed in ), it is amuraet al. [ampet al. [Aside from immune cells, fibroblasts are also likely to be relevant players in the progression to chronic fibrosis in sarcoidosis. Stromal cells such as fibroblasts and pericytes have also been suggested as significant regulators of the immune system . It coulaet al.  showed tpet al.  found thanget al. [An area that is only just starting to take off in sarcoidosis is the role of epigenetic changes in immune cells and persistence of disease. No study has yet shown a correlation between epigenetic marks and fibrotic sarcoidosis, but Yget al.  examinedget al. , which iversus 23.3 years) [ockstoneet al. [via the recognition of PAMPS with TLR2. These mediating pathways could be facilitated by the presence of SAA in some patients, which could drive the activity of macrophages, and chronic mTORC1 signalling, which allows for the persistence of antigens in these macrophages. Although Linkeet al.'s study [via interrogation of the transcriptomic data from Lockstoneet al.’s [versus self-limiting dataset in the lungs. In addition, enrichment of the mTORC1 signalling gene set in transcriptomic data from patients with fibrotic lungs in the large lung study from the GRADS investigators strengthened the importance of this pathway in fibrotic sarcoidosis.Transplant surgeons and pathologists noted more than a decade ago that the lungs of patients with end-stage fibrotic sarcoidosis show a distinct amount of lymphocytic infiltrates , 136. Theet al. , whose s's study  on mTOR et al.’s  progresse.g. iNKT cells [The high level of T-lymphocytes and accumulation of Th17/Th17.1 cells in the lungs implicates aberrant regulatory elements for example loss of control of T-cell proliferation by immune cells with regulatory function KT cells  and TregKT cells , which wversus nonprogressive patients, where we argued that this was a minimal requirement for fibrosis. However, this is not proven and it is unclear if this is a sine qua non for fibrosis. It is also not clear which of these pathways are critical and how many of these factors have to co-exist to result in progressive fibrotic disease in sarcoidosis. Of course, one reason for the gap in understanding is the lack of a robust animal model for pulmonary sarcoidosis . Although models for granulomatous inflammation exist, e.g. Cutibacterium acnes, mycobacterial catalase–peroxidase and ESAT-6 models, leprosy, and schistosomiasis [versus nonfibrotic human disease are likely to be more informative. Lung tissue studies, ideally matched to blood analysis, are particularly needed. Such studies could also yield information on a biomarker to identify patients who are more at risk of fibrosis. Potential blood biomarkers include serum IL-17 levels, monocyte levels and CCL-18 in BAL samples.Much of this piecing together of information also involved the use of data from progressive somiasis , it is pversus nonfibrotic sarcoidosis; many had fewer than 10 fibrotic sarcoidosis patients and there are negligible murine studies of fibrotic granulomatous processes. With the data that are currently available, our perspective is that chronic fibrosis in sarcoidosis is likely to be driven by a combination of increased Th17 cells, possibly due to resistance to apoptosis, combined with primed monocyte-derived macrophages  which may respond disproportionately to infection   involved in wide-ranging cellular processes such as proliferation, differentiation and adhesion . The LckThe disease mechanism in fibrotic pulmonary sarcoidosis is poorly understood and under researched.There are very few studies that directly compare the immune profile between patients with fibrotic sarcoidosis and those who did not progress to fibrosis. The few studies that did this highlighted the importance of T-lymphocytes and chronic mTORC1 signalling in fibrotic pulmonary sarcoidosis.A better understanding of these mechanisms in fibrotic sarcoidosis has become a lot more relevant with the introduction of nintedanib as an antifibrotic for progressive fibrotic sarcoidosis.There is mechanistic evidence for the use of nintedanib in fibrotic pulmonary sarcoidosis but there is not enough clinical data yet to support its lone use in fibrotic sarcoidosis.We propose that established immunosuppressants are used first in fibrotic sarcoidosis patients or at least used with nintedanib for a period of time during the introduction of nintedanib treatment.


Additionally, incorporating specific components into the pre-designed meta-structures could further achieve diversified functionalities.Ultralight, ultrastrong, and supertough graphene aerogel metamaterials combining with multi-functionalities are promising for future military and domestic applications. However, the unsatisfactory mechanical performances and lack of the multiscale structural regulation still impede the development of graphene aerogels. Herein, we demonstrate a laser-engraving strategy toward graphene meta-aerogels (GmAs) with unusual characters. As the prerequisite, the nanofiber-reinforced networks convert the graphene walls’ deformation from the microscopic buckling to the bulk deformation during the compression process, ensuring the highly elastic, robust, and stiff nature. Accordingly, laser-engraving enables arbitrary regulation on the macro-configurations of GmAs with rich geometries and appealing characteristics such as large stretchability of 5400% reversible elongation, ultralight specific weight as small as 0.1 mg cm Graphene aerogels are highly porous and have very low density; despite this they also exhibit high mechanical strength. Here the authors present a laser-engraving strategy for producing graphene meta-aerogels with different configurations and properties. However, pursuing the unique “3U” properties for the materials community is still fraught with challenges due to mutually exclusive qualities between strength and resilience at low density5. Additionally, the lack of multiscale structural regulation from tailorable macro to well-ordered micro configurations also restricts GAs applications in multi-functional scenarios such as wearable electrical circuits, soft robots, and stimulus-responsive devices7. Therefore, building strong and elastic GAs with controllable macro and microarchitectures, as well as understanding the mechanics that drives GAs’ superior mechanical properties, are fascinating.Graphene aerogels (GAs) integrating ultralight, unexpected mechanical strength, and unprecedented fatigue resistance are promising “3U” mechanical materials fitting harsh environments in aerospace, defense, and energy-related fields6, which can to some extent regulate the arrangements of graphene sheets, rendering cellular, porous, and hyperbolic networks12. However, it faces the difficulty to obtain precise and specific shapes with high performances matching the variable application scenario6. Three-dimensional (3D) printing is also a promising extrusion technique to fabricate lattice and periodic GAs with customizable structures14. Nevertheless, the need to use a high concentration of graphene oxide (GO) dispersion for sufficient viscosity becomes a restrictive condition to downsize the printed structures15. The high viscosity makes GO strenuous to adjust the microstructure, generally leading to a purely stochastic network of GAs with weak sheet-to-sheet interactions and unsatisfactory mechanical behaviors14.On the shaping of macro-morphology, freeze-drying is a widely used method to obtain GAs with the original appearance of molds17. Belonging to the open cell model, the deformation of GAs follows three procedures in the sequence of linear elasticity, collapse, and densification throughout the compression process21. The failure of GAs is accompanied by the formation of microscopic hinges, which occur when the graphene walls approach their maximum bending moment and then collapse. Meanwhile, the elastic moduli of GAs are also associated primarily with the bending stiffness of graphene walls20. Hence, to attain high stiffness and elasticity of the GAs, efforts have been made to improve the bending stiffness of graphene walls through hydrothermal treatment, molecule crosslinking, and polymer reinforcement25. However, the specific elastic bending stiffness of a sheet-like structure is intrinsically inferior to that of tubular and fibrillar materials27.On the other hand, the interior microstructure of GAs has a strong influence on their macro-mechanical properties−3), and ultrawide Poisson’s ratio (v) range (−0.95 < v < 1.64). The microstructures of GmAs are composed of well interlocked sub-micron fibers and graphene sheets. Benefiting from the 1D nanofiber-reinforced 2D sheet structure, the bending stiffness of graphene walls increases significantly. Thus, during the compression process, the internal deformation mode of GmAs is a stable bulk deformation rather than the microscopic buckling for soft GAs, which results in the good mechanical properties of GmAs including good robustness, high strength and stiffness, and full shape recovery after arbitrary compression, outperforming most carbon aerogels. Furthermore, the simple manufacturing process allows the incorporation of other functional components into the ordered structure, enabling the production of objects with pre-defined geometry and functions. As prototypes, ceramic aerogels and magnetically responsive aerogels were prepared, indicating great potential for multi-functional applications.Herein, we present a laser-engraving strategy towards graphene meta-aerogels (GmAs) possessing multi-functional macroscopic structures and highly ordered micro-networks. GmAs can be rapidly and precisely engineered into any configurations including line, plane, 3D lattices, and hole bulks, giving record high features such as super stretchability (5400% elongation), low specific weight , stably standing on slimsy Setaria viridis  nanofibers were introduced to GA framework. Polyimide (PI) nanofibers were optimally selected because of their rigid aromatic chain structure and good processability, advantageous to firmly bind all the graphene sheets through the π−π interaction . Even with a loading ε up to 90%, the unloading ε of GmA can return 0%, proving its full recovery capabilities under large deformation  retention after 1000 cycles of 50% compression ε ) is established and directly extracted from the SEM images to statistically depict orientation frequency of graphene walls , which can further reflect the variational trend of the bending angle of graphene walls during the compression process. Specifically, under the initial state, the statistical curves for GmA and PGA exhibit the similar mountain-like shapes with the highest frequency at 90° orientation, representing the most frequent horizontal graphene walls  of graphene walls. Generally, for a plate material, its buckling occurs when it is stressed beyond the yield stress, which is in direct proportion to the D of materials20. According to the free energy density equation established by the GmA model  are of great influence on their mechanical behaviors that drive different motions, deformations, stresses and mechanical energy variations and promise applications in various fields45. However, it still lacks the suitable method to effectively adjust v for GAs. Pristine GA is a near-zero v material owing to its lamella architectures (Supplementary Movie 22) under longitude applied strain (ε11), and the v is calculated by v = −ε22/ε11. Beyond the ultralight yet robust skeleton, GmA meta-structures by laser-engraving realize the ultrawide v range. The anisotropic hole patterns on the GmA engrave with the concave or convex shapes, which form the inward or outward protrusion frameworks. When compressed, the longitude stress is divided into transverse stress along the skeleton structure, causing the skeleton to bend inward or outward  , and ultrawide Poisson’s ratio range (−0.95 < vpeak < 1.64). Moreover, the easy procedure can incorporate polymer and particles into the ordered structure enabling the yield of objects with pre-defined geometry and functions. With these impressive properties of GmAs, this work sheds light on future developing of the multi-functional aerogels with tunable meta-structure.Combining with the effective strengthened structures of 1D nanofibers reinforced 2D sheets, a laser-engraving strategy was proposed to construct GmAs with unique characters and rich functionalities, which opens up a super easy way to precisely regulate the GA structures from tailorable macro to well-ordered micro configurations. Specifically, the internal 1D nanofibers reinforced 2D frameworks ensure a stable bulk deformation process, leading to a significant improvement of its elasticity, robustness, and stiffness. Accordingly, laser-engraving achieves arbitrary structures of GmAs with record characteristics, such as the super stretchability (5400% reversible tensile strain), ultralight specific weight . The light yellow PAA solution was added into a 5 mL disposable syringe with a 22-G needle. The feed rate was set as 1.5 mL h−1. A plane covered Al foil as the collector to collect the PAA nanofibers, and the distance between the collector and needle is 15 cm. The applied positive voltage is 12 kV and the applied negative voltage is −2 kV. After electrospinning, a milk white PAA mat was prepared  (PAA), which is prepared by condensation polymerization reaction of dianhydride and diamine. Specifically, 2 g 4,4′-oxybisbenzenamine and 30 mL 2. Then PI pieces and dioxane were added into a beaker, and subsequently with a high-speed shearing treatment over 2 h by a D-130 homogenizer , a homogeneous PI dispersion was prepared. Noted that, the dioxane can be moderately added during the shearing process to avoid the aggregation of the PI nanofibers. For preparing the GmA, the 10 mg mL−1 GO dispersion was mixed with 15 mg mL−1 PI dispersion with a continuous agitation, and the amount can be tuned according to the weight ratio of PI to GO. Here, three different weight ratio was prepared including 1:10, 3:10, and 5:10, which were nominated as 0.1-GmA, 0.3-GmA, and 0.5-GmA, respectively. After mixing uniformly, the mixture was added into a home-made mold to conduct the directional freezing. The mold was a hollow cube (2.0 cm × 2.0 cm × 2.0 cm) with two open opposite face. Before using one open face was sealed by 2 mm thick polydimethylsiloxane (PDMS)  with a 355 nm laser beam at a spot size of 10 μm. The laser power was controlled to be 3 ± 0.1 W with a pulse repetition frequency of 20 kHz, and a marking velocity of 1000 mm s−1. The patterns were prepared in advance by software. The laser-engraving process is a rapid localized heating and combustion of graphene and PI. The gases generated from combustion would tear graphene layer. Residues from insufficient combustion remain on the edge of graphene. The related process was shown in Supplementary Figs. The as-prepared PI mats were cut into small pieces with an area below 0.25 cm3O4 nanoparticles 2 (Zr(SO4)2 for ZrO2-GmA) and 1.8 M urea. Assisted by the vacuum system, the gas was excluded from the GmA. And the immersed GmAs were put in 90 oC water bath for 3 h, followed by freeze-drying and an 800 oC annealing treatment at air, the TiO2-GmA was prepared. The density of TiO2-GmA and ZrO2-GmA was 46 mg cm−3 and 36 mg cm−3, respectively.For the preparation of magnetically responsive GmA, Fe−1. Thermogravimetric analysis (TGA) was characterized a TA-Q50 TGA  under a heating rate of 10 K min−1, the protect gas include air and N2. Dynamical mechanical analysis (DMA) were conducted a Q800 mechanical analyzer . Mechanical tests were conducted on an Instron 3342 universal testing machine  equipped with a 100 N load cell. Specifically, the tensile test was performed with a constant loading rate of 1 mm min−1 and a gauge length of 10 mm. For the compressive test, the samples were shaped into cubic appearance (8 mm × 8 mm × 8 mm). The compressive rate was set 8 mm min−1.Scanning electron micrographs (SEM) were performed by using a Field Emission Zeiss Gemini300 with an accelerating voltage range from 5.0 kV to 10.0 kV . Transmission electron microscopy (TEM) images were taken by the Tecnai F20 transmission electron microscope , which is operated at 200 kV. XPS spectra were conducted on an Escalab 250 photoelectron spectrometer . The Raman spectra of GO and rGO were studied by means of a LabRAM HR Evolution with a 532 nm excitation laser . The photos were taken by an iPhone 7 mobile phone . Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectra were recorded on an UATR Two FT-IR spectrometer . X-ray diffraction (XRD) patterns were collected by the use of a D8 Advance X-ray diffractometer with Cu Kα radiation  at scanning rate of 5 degree minSupplementary InformationPeer Review FileSupplementary Movie 1Supplementary Movie 2Supplementary Movie 3Supplementary Movie 4Supplementary Movie 5Supplementary Movie 6Supplementary Movie 7Supplementary Movie 8