Cue-evoked persistent activity is neural activity that persists beyond stimulation of a sensory cue and has been described in many regions of the brain, including primary sensory areas. Nonetheless, the functional role that persistent activity plays in primary sensory areas is enigmatic. However, one form of persistent activity in a primary sensory area is the representation of time between a visual stimulus and a water reward. This “reward timing activity”—observed within the primary visual cortex—has been implicated in informing the timing of visually cued, reward-seeking actions. Although rewarding outcomes are sufficient to engender interval timing activity within V1, it is unclear to what extent cue-evoked persistent activity exists outside of reward conditioning, and whether temporal relationships to other outcomes  are able to engender timing activity. Here we describe the existence of cue-evoked persistent activity in mouse V1 following three conditioning strategies: pseudo-conditioning , neutral conditioning , and aversive conditioning . We find that these conditioning strategies exhibit persistent activity that takes one of three forms, a sustained increase of activity; a sustained decrease of activity; or a delayed, transient peak of activity, as previously observed following conditioning with delayed reward. However, these conditioning strategies do not result in visually cued interval timing activity, as observed following appetitive conditioning. Moreover, we find that neutral conditioning increases the magnitude of cue-evoked responses whereas aversive conditioning strongly diminished both the response magnitude and the prevalence of cue-evoked persistent activity. These results demonstrate that cue-evoked persistent activity within V1 can exist outside of conditioning visual stimuli with delayed outcomes and that this persistent activity can be uniquely modulated across different conditioning strategies using unconditioned stimuli of varying behavioral relevance. Together, these data extend our understanding of cue-evoked persistent activity within a primary sensory cortical network and its ability to be modulated by salient outcomes. Cue-evoked persistent activity can be defined as neural activity which persists beyond the presentation of a sensory cue. One such example of cue-evoked persistent activity is reward timing activity in rodent V1, wherein neurons produce a representation of time between a transient visual stimulus and a delayed water reward . This reCue-evoked persistent activity in the primary visual cortex to unpaired visual stimuli  has been observed as sustained membrane depolarizations in mouse V1 , 2016, eV1 reward timing activity is an example of interval timing activity and the ability for V1 to learn this timing activity is dependent on the release of acetylcholine (ACh) from the basal forebrain . When chHere, we investigate these two open questions: whether cue-evoked persistent activity requires temporal relationships to outcomes and whether non-rewarding outcomes can affect cue-evoked persistent activity in V1. We find that V1 neurons express persistent activity to unpaired, familiar visual stimuli and that the forms this activity takes are the forms observed during V1 reward timing. We also demonstrate that neither neutral nor aversive outcomes are able to engender timing activity within V1 neurons as previously demonstrated for rewarding outcomes. However, we find that neutral conditioning significantly increases neural response magnitude whereas aversive conditioning strongly diminishes the prevalence of cue-evoked persistent activity demonstrating that conditioning strategies which vary in their behavioral relevance differentially influence sensory-evoked responses within cortical circuits.All procedures reported here were in accordance with the US NIH Guide for the Care and Use of Laboratory Animals and were approved by the Animal Care and Use Committee at the Johns Hopkins University School of Medicine.n = 4) or aversive conditioning (n = 6). Additionally, three mice underwent neutral conditioning without experiencing pseudo-conditioning. Surgical procedures are as previously described  mice  were used in this study. Ten mice underwent pseudo-conditioning prior to undergoing neutral conditioning  and xylazine  and eyes were covered with ophthalmic ointment . The first surgery was performed to affix a head-restraint bar to the animal’s skull for training purposes and to mark sites for future craniotomies. In the first surgery, the hair covering the skull was removed (Nair), the skin cleaned with alternating 70% ethanol and iodine, then the skin was cut away. Following this, the periosteum was removed and the skull cleaned with alternating 70% ethanol and hydrogen peroxide, then the skull was dried with canned air. A total of four sites were marked for future craniotomies: two for ground screws  and two for primary visual cortex . Sites for future craniotomies were covered in a silicone elastomer (Smooth-On Body Double) and a head-post was affixed to the anterior portion of the mouse’s skull with super glue (Loctite 454). The remaining bone was covered in super glue. A second surgery was performed to implant recording electrodes. Briefly, small craniotomies were made using a dental drill for ground screws and screws were implanted into sites. Next, craniotomies were created over V1, the dura was cleaned with sterile paper points, and electrodes were brought to the surface of the brain, then implanted 500 μm below the cortical surface in accordance with stereotaxic measurements of V1 . Wires wFollowing electrode implantation, animals recovered from surgery for 5–7 days after which they were habituated to head fixation over the course of 2 days before experiencing unpaired visual stimuli. Monocular visual stimuli were presented to mice as previously described . BrieflyAnimals either underwent neutral conditioning or aversive conditioning . Seven aWhen conditioning reward timing activity in V1, the rewarding outcome does not evoke activity within V1 though it does produce a behavioral response . When inNeural activity was recorded as previously reported . Neural Analysis performed here is consistent with a report of reward timing activity in mouse V1  and is dV1 reward timing activity is an example of cue-evoked persistent activity and takes one of three forms: a sustained increase of activity until the expected time of reward (SI), a sustained decrease of activity until the time of reward (SD), or a peak of activity around the time of reward (PK). Here, we manually classified neural responses across various conditioning strategies in a blinded fashion to determine the existence of cue-evoked persistent activity outside of reward conditioning contexts. Specifically, an individual neuron was randomly selected from all recorded sessions across all animals. Then, an AUC-normalized neural response (see below) recorded during left-cue, right-cue, or sham trials was randomly selected and presented. This neural response was then classified as “Not Classified” (NC), “Sustained Increase” (SI), “Sustained Decrease” (SD), or “Peak” (PK). SI and SD responses are classified based on the presence of a sustained increase or decrease of activity after the conditioned stimulus (CS) stimulation window, respectively; conversely, PK responses are classified based on the presence of a prominent peak of neural activity after any initial visual-evoked response. Activity from the remaining trial types were presented (in a random fashion), followed by the remaining neurons (again selected randomly). These classifications were performed without knowledge of animal identity, recording session, delay time, or conditioning strategy. This blind classification process was recently used and cross-validated to classify reward timing within mouse V1 .Neural reports of time (NRTs) were calculated for each neuron with persistent activity. For SI and SD response forms, the NRT is calculated as the moment when neurons return to a baseline level of activity. For PK response forms, the NRT is the time of maximum firing rate from baseline . This calculation involved first normalizing neural activity to baseline with AUC normalization and then applying an algorithmic calculation of the NRT. This calculation strategy has previously been employed to define NRTs for V1 reward timing activity  and the To calculate an NRT, neural activity was normalized to the baseline firing rate by calculating the AUC using a sliding, 100 ms window . An AUC To determine whether the magnitude of evoked responses was affected by conditioning strategies, we calculated evoked energy scores of neural responses within the first 1 s following CS stimulation. Specifically, for a given neural PSTH we calculated the area between neural activity and baseline activity (defined as the median firing rate from 1 s before CS onset). Thus, we were able to quantify the magnitude of a response across the first second following CS stimulation. We have used a 1 s window as during this time window, the experimental epoch is identical across conditioning strategies. That is, the commonly shared time epoch is as follows: 0–0.1 s, a visual stimulus is delivered and from 0.1 to 1 s, no stimuli are delivered.To confirm recording electrode locations, standard histology procedures were undertaken. Briefly, animals were deeply anesthetized using sodium pentobarbital . After which, animals were transcardially perfused with ice cold phosphate-buffered saline (PBS) followed by ice cold 4% paraformaldehyde (PFA). Brains were immersion fixed overnight in 4% PFA and were transferred to 30% sucrose until sectioning. Brains were sectioned on a cryostat into 60 μm slices. Electrode location was verified using Nissl staining, as follows. Sections containing V1 were selected and mounted on gelatin subbed slides and air dried. These slides were then immersed in a solution containing 0.1% Cresyl violet and 1% glacial acetic acid dissolved in water for 5 min, followed by a 2-min wash in distilled water, then by 2 min in 50% ethanol, then 2 min in 70% ethanol. Stained and washed sections were air dried, immersed in xylenes then coverslipped with Permount Mounting Medium (Electron Microscopy Sciences). Histological results are shown in Cue-evoked persistent activity is evoked neural activity that persists beyond stimulation with a sensory cue. One well-studied example of this activity is V1 reward timing activity that is expressed in one of three canonical forms: a sustained increase of activity until the expected time of reward (SI), a sustained decrease of activity until the time of reward (SD), and a peak of activity around the time of reward (PK). We first investigated whether similar cue-evoked persistent activity can exist when visual cues are presented in the absence of a delayed outcome by measuring activity patterns during “pseudo-conditioning” wherein monocular visual cues were presented without a delayed outcome. We then determined the effect of pairing visual cues of varying behavioral relevance has on cue-evoked activity within V1. This was done through “neutral conditioning” and “aversive conditioning” wherein monocular visual stimuli were paired with a delayed binocular visual stimulus or a 10μA tail shock, respectively.Pseudo-conditioning, here, refers to repeated presentations of unpaired, monocular visual stimuli across several days. During this conditioning strategy, we recorded from 541 neurons across 10 animals. From this recording population, we classified a total of 1,082 neural responses . Of these responses, we find 170 were classified as having persistent activity. Specifically, these 170 responses were expressed by 121 neurons and the distributions of response forms are as follow: 81 responses expressed by 63 neurons were classified as SI, 66 responses expressed by 50 neurons were classified as SD, and 23 responses expressed by 21 neurons were classified as PK .+standard deviation = 0.80 +052 s, p > 0.05, Wilcoxon rank-sum test or χ2 goodness-of-fit test; We then used these persistent activity patterns to determine the time course of these responses. Specifically, we defined the NRT as the time that SI and SD return to baseline activity or the time of maximum activation  for PK responses . We find that we can derive a distribution of NRTs for this pseudo-conditioned population of neurons , we find 70 responses were classified as having persistent activity. Specifically, these 70 responses were expressed by 51 neurons and the distribution of response forms are as follow: 32 responses expressed by 24 neurons were classified as SI, 35 responses expressed by 26 neurons were classified as SD, and 3 responses expressed by 3 neurons were classified as PK .n = 19 NRTs) and Long Delay Sessions (n = 25 NRTs) in neutral conditioning and find that the central tendencies do not accord with the conditioned intervals . Additionally, we find that the two distributions are not significantly different from each other . To control whether this difference in training history influenced the effects of neutral conditioning on cortical activity, we compared neural response features across individual animals. In doing so we found that both groups had similar prevalence of cue-evoked persistent activity and neither group exhibited interval timing activity . HoweverHaving demonstrated that visual stimuli presented in the absence of a delayed outcome or when paired with a delayed, neutral outcome result in cue-evoked persistent activity, we sought to address whether a behaviorally-relevant, non-rewarding outcome would affect evoked responses. Specifically, we addressed whether paring a visual stimulus with a delayed, aversive outcome influences V1 cue-evoked persistent activity.2 = 67.38, p = 8.09 × 10–14, Friedman’s Test] and that a magnitude of 10 μA is the strongest to evoke a neural response that is not significantly different than spontaneous activity  or 1.5 s (Long Delay Sessions) following the visual stimulus offset. During aversive conditioning, we recorded from 861 neurons from six animals. Of the 1,722 neural responses (861 neurons × 2 cues), we find that 79 responses were classified as having persistent activity. Specifically, these 79 responses were expressed by 56 neurons and the distribution of responses forms are as follow: 50 responses expressed by 33 neurons were classified as SI, 21 responses expressed by 18 neurons were classified as SD, and 8 responses expressed by 8 neurons were classified as PK .n = 30 NRTs) and NRTs for responses recorded during Long Delay Sessions (n = 11 NRTs). We find that these distributions do not well accord with the conditioned intervals .We then determined the distribution of calculated NRTs for responses recorded during Short Delay Sessions  = 101.62, p < 1 × 10–6; χ2 goodness-of-fit test] and neutral conditioning . However, there is no significant difference in the prevalence of cue-evoked persistent activity across pseudo- and neutral conditioning [χ2 = 3.32, p = 0.068; χ2 goodness-of-fit test; The data presented thus far indicate that cue-evoked persistent activity is present across a range of conditioning strategies and that this activity is expressed in the same forms across various conditioning strategies . Moreove+standard deviation: Pseudo-Conditioning: 1.07 +2.82, Neutral Conditioning: 1.75 +3.16, Aversive Conditioning: 0.88 +2.34; 2 = 106.63, p = 7.02 × 10–24, Kruskal–Wallis test). Post hoc analyses revealed that evoked energy scores from neural responses recorded during aversive conditioning were significantly smaller than those recorded during pseudo- or neutral conditioning  consistent with the paucity of cue-evoked persistent activity within these responses. Additionally, we found that evoked energy scores of responses recorded during neutral conditioning were significantly higher compared to those scores of responses recorded during pseudo-conditioning . This pattern of evoked energy scores  is maintained even when analysis is limited to the 100 ms of CS stimulation  had significantly higher evoked energy scores than neural responses from Neutral Only animals . These results are consistent with previous mouse V1 studies which demonstrate that stimulus familiarity is sufficient to potentiate visual-evoked responses within LFP recordings  in the 1 s following CS onset  and found different values across the different conditioning strategies  and/or altering the prevalence of cue-evoked persistent activity within V1 (as seen in aversive conditioning). Furthermore, stimulus familiarity  can also affect neural responses independently of cue-evoked persistent activity prevalence. Together, these results demonstrate the myriad effects by which an animal’s training history can influence the visual cortex’s response to visual stimuli.The work here explores the nature of cue-evoked persistent activity evoked by visual stimuli within the mouse primary visual cortex. Specifically, we investigated the requirement (or lack thereof) of a conditioned outcome to elicit such activity, whether predictable temporal relationships to delayed outcomes are sufficient to engender cued-interval timing activity, and how this activity is modulated by outcomes of varying behavioral relevance. We have shown that persistent activity can exist within mouse V1 to transient, familiar visual stimuli both in the absence of an unconditioned stimulus (pseudo-conditioning) and in the context of neutral and aversive conditioning , 3, 5. TWe show here that when visual stimuli are presented in the absence of an unconditioned stimulus, V1 neurons express cue-evoked persistent activity . Such pein vivo  raising the question of how these response forms arise. Previous computational models of reward timing activity posit that these forms are the result of a core network architecture that is composed of excitatory and inhibitory cells with a specific connectivity pattern . We recein vivo . The preTogether, these results demonstrate that cue-evoked persistent activity occurs in V1 in the absence of unconditioned stimuli. Future studies may utilize longitudinal recordings and cell-specific identifications to define the manner by which this activity enables future learning and/or the network architectures that promote these patterns of neural activity.We show here that, unlike rewarding outcomes, pairing a visual stimulus with a neutral or aversive outcome is insufficient to engender interval timing activity within V1 , 5. HoweWhen the same visual stimulus is presented across several days, the magnitude of a visually-evoked neural response increases and visually-evoked behavioral movements are smaller and less frequent . These fUnlike neutral conditioning where the main effect is to strengthen the response magnitude, the main effect of aversive conditioning is to significantly reduce neural response magnitude and the prevalence of cue-evoked persistent activity within V1. Previous studies have demonstrated that in primary sensory areas, fear conditioning results in a “sparsification” of sensory responses . The netHere, we demonstrate that conditioning with a neutral or aversive outcome differentially influences cue-evoked persistent activity. Furthermore, previous work has demonstrated that similar conditioning with a rewarding outcome engenders cued-interval timing activity within V1 . How migInterval timing has been shown in the rodent primary visual cortex  and in oThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by Johns Hopkins University Animal Care and Use Committee.KM and MH designed the experiments and wrote the manuscript. KM collected and analyzed the neural data. SA and KM performed the histological verification of electrode implant strategies. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Topical rh-NGF also promotes greater axonal survival and inhibits astrocyte activity in the optic nerve. Collectively, these results suggest that topical rh-NGF exhibits neuroprotective effects on retinal neurons via influencing secondary degeneration process. As topical rh-NGF is already involved in early clinical trials, this highlights its potential in multiple indications in patients, including those affected by glaucomatous optic neuropathy.Optic neuropathy is a major cause of irreversible blindness worldwide, and no effective treatment is currently available. Secondary degeneration is believed to be the major contributor to retinal ganglion cell (RGC) death, the endpoint of optic neuropathy. Partial optic nerve transection (pONT) is an established model of optic neuropathy. Although the mechanisms of primary and secondary degeneration have been delineated in this model, until now how this is influenced by therapy is not well-understood. In this article, we describe a clinically translatable topical, neuroprotective treatment  predominantly targeting secondary degeneration in a pONT rat model. Topical application of rh-NGF twice daily for 3 weeks significantly improves RGC survival as shown by reduced RGC apoptosis  The second phase of injury is thought to be caused by the accumulation of noxious factors such as oxidative radicals, glutamate and calcium release from primarily damaged cells and peripheral immune cell activation5. Secondary neurodegeneration is believed to be the major contributor to neuronal death in CNS injuries including those affecting the spinal cord6 and in optic neuropathies, such as glaucoma, ischaemic optic neuropathy, and Leber’s hereditary optic neuropathy9.Secondary degeneration occurs commonly in the central (CNS) and peripheral (PNS) nervous systems, where injury from initial lesions can lead to widespread damage to neurons far beyond the primary injury site11. Of these, glaucoma represents the leading cause of global irreversible blindness, affecting over 60.5 million people, a figure set to double by 204012. Currently, intraocular pressure (IOP) presents the only therapeutically modifiable risk factor for glaucoma13; however, patients with well-controlled IOP can still lose vision (disease progression), necessitating the development of novel, non-IOP-dependent treatment strategies for this condition14. Neuroprotective therapies are increasingly recognized as a promising approach to slow or prevent optic neuropathy associated RGC loss16, and the use of new endpoints and biomarkers, such as DARC 17, may significantly improve their assessment and shorten their clinical development time.Optic neuropathy describes a collection of disorders characterised by damage to the optic nerve and loss of retinal ganglion cells (RGCs) due to any cause, including glaucoma, ischaemia, trauma and genetic predisposition18. NGF is thought to act through interaction with the transmembrane tyrosine kinase receptor (TrkA) and p75 neurotrophin receptor (p75NTR)20. NGF and its receptors are highly expressed throughout the visual system, from the retina to the visual cortex21. In the retina, RGCs have been shown not only to express NGF and its receptors, but also to transport NGF in a retrograde and anterograde fashion along their axons, suggesting the role of NGF in maintenance of RGC function22. Expression profiles of endogenous NGF and its receptors are found to be altered in the retina and optic nerve in experimental glaucoma associated with RGC loss25. Topical NGF application has previously been shown to be neuroprotective in glaucoma, with evidence of reduced RGC loss in experimental models and a suggestion of improved visual function in patients26. Pharmacokinetic analysis has confirmed that single topical dose of 125I-labeled NGF enabled penetrating the eye and reaching the retina and optic nerve27.Neurotrophins are a family of proteins that regulate the growth and survival of nerve cells. Nerve growth factor (NGF) is an endogenous secreted neurotrophic factor that has been widely investigated as a promising neuroprotective agent since its discovery in 195029. The pONT is a well-established animal model, induced by transecting only the dorsal axons of the optic nerve, leaving ventral axons intact but vulnerable to secondary degeneration28. Using this model, we have previously successfully quantified the components of primary and secondary degeneration and evaluated therapeutic strategies31.To establish whether the neuroprotective effects of topical NGF occur via primary or secondary neurodegenerative processes, this study investigates the effect of this therapeutic intervention on patterns of RGC loss in a partial optic nerve transection (pONT) modelin vivo with DARC and RGC survival histologically. Recently established Brn3a+ whole-retinal RGC soma counting algorithms were applied to evaluate the effect of NGF mediated neuroprotection on primary and secondary neurodegenerative processes33. Finally, to evaluate its effects on RGC axons, we assessed RGC axonal health and astrocytic activity.In the present study, we used the same model to assess the effects of topical recombinant human NGF (rh-NGF) on RGC protection by assessing both RGC apoptosis in vivo using DARC 17 imaging. Increased levels of RGC apoptosis were seen after pONT induction compared to naïve controls; however, topical rh-NGF treatment significantly reduced apoptosis, as seen in Fig. The effects of topical rh-NGF on RGC protection were firstly assessed in vivo observations, the neuroprotective effects of topical rh-NGF administration were next assessed histologically by counting the number of Brn3a+ RGC soma in retinal whole-mounts using previously well-established techniques31. Brn3a is a nuclear restricted transcription factor that has previously been reported to label 97% of the rodent RGCs (excluding melanopsin expressing RGCs) and this signal is rapidly lost by RGCs undergoing cell death processes33. RGC survival in each retinal whole-mount was assessed using three previously established parameters: mean RGC density (RGC/mm2), nearest neighbour distance (NND) and regularity index (RI). NND refers to the distance between each neuron and its nearest neighbour in the mosaic, presented as the mean NND. RI is a measure of RGC mosaic regularity calculated by dividing mean NND by the standard deviation of the NND of a population34.To corroborate our + RGC density was substantially reduced in pONT only (without NGF treatment), compared to naïve control, while less reduction of RGC density was seen in retinas treated by topical rh-NGF  (p < 0.01), accompanied by increased nearest neighbour distance (p < 0.05), and reduced regularity index (p < 0.05), respectively  and anti-rabbit glial fibrillary acidic protein (GFAP) to assess axonal survival and astrocyte activity, respectively. pONT induction was found to result in significant reduction of the intensity of NF labelled optic nerve axons, compared to naïve controls  is sampled48. To address the concerns of limitation in those approaches, we used Brn3a to label RGCs in retinal whole-mounts, and quantified all surviving RGCs by our novel algorithm32. Using this algorithm, information regarding the spatial distribution of RGCs, i.e. their spatial relationship and regularity, provides additional and valuable data to RGC density32. Furthermore, by segmenting the retina and monitoring RGC loss longitudinally, the extent of primary and secondary degeneration can be estimated.In optic nerve disease, previous NGF studies have employed either retinal cross-sectioning to quantify surviving RGCs with non-specific staining, such as hematoxylin and eosin staining32. By segmentation of the whole retina into quadrants, we further examined whether the protective effects of NGF were attributed to targeting primary and/or secondary degeneration. We found that although RGC density in the superior quarter was significantly higher in NGF treated groups than untreated group, the most pronounced improvement was identified in the inferior retina, where RGC survival in NGF treated groups was considerably comparable to that in naïve controls, which is indicative of secondary degeneration as the main target for NGF. This property of NGF would be extremely valuable for clinical application because secondary degeneration is the major concern in optic neuropathies, including normal-tension glaucoma where RGCs continue to die even at low intraocular pressures43. Perhaps counter-intuitively, the protective effect of NGF appeared to be more significant with a lower (180 µ/mg) than higher dose (540 µg/ml), in the inferior retina (p < 0.001). A possible explanation for this could be that more NGF may have been delivered to the retina with lower dosing concentrations, as supported by similar results in a previous study where a greater level of exogenous 125I-labeled NGF was transported into the retina after topically administrating of NGF at 200 µg/ml rather than 500 µg/ml27. In terms of pharmacokinetics, 125I-labeled NGF was detected in retinal ganglion cells and the optic nerve 2 hours after topical administration, followed by a peak level occurring at 6 hours but was undetectable after 48 hours27. This indicates that daily application of topical rh-NGF, described in the current study, would be at a sufficient level to provide neuroprotection after optic nerve injury.Our results showed that topical rh-NGF was indeed significantly effective in retaining RGC survival 3 weeks after partial damage of the optic nerve, evidenced by increased RGC density and regularity, and decreased average nearest neighbour distance measures. Choosing 3 weeks to evaluate topical NGF was based on our previous findings that RGC loss in the pONT model has reached a maximum level at this time point26, one patient with age-related macular degeneration (AMD) by visual acuity and focal ERG49, and five children with optic glioma and optic nerve atrophy by VEP50. In animal models, functional recovery has also been described following treatment with NGF52. Unfortunately, we were unable to perform visual functional assessment in the current study and it would be interesting to look into it in the future.Visual functional improvement following topical NGF treatment has been reported in patients, including three glaucoma patients assessed by pattern electroretinogram (PERG) and visual evoked potentials (VEPs)4. NGF mediated prevention of RGC apoptosis has been documented by others previously26. NGF also exhibits neuroprotection by inhibiting oxidative stress via a mechanism involving induction of the phosphatidylinositol 3-kinase (PI3K)/Akt1 survival pathway53. Calcium dysregulation and excitotoxicity are the major events causing neuronal death in optic neuropathy, and have been implicated in secondary degeneration55. The neurotrophins, including NGF, play a key role in control of intracellular calcium levels and regulation of synaptic plasticity. NGF appeared to act on its target cells by inducing calcium influx and intracellular calcium mobilization56. The neurotrophin-mediated presynaptic uptake of calcium has been found to stimulate presynaptic release of neurotransmitter, a key element in synaptic plasticity and long term potentiation56. NGF is also crucial in maintenance of mitochondrial structure and function. A recent study has shown that NGF pre-treatment protects endothelial cells from indomethacin-induced injury through direct action on mitochondria via receptor TrkA, and the protective effect appeared to prevent mitochondrial membrane potential (MMP) depolarization57.The mechanisms through which topical NGF is neuroprotective by mainly targeting secondary degeneration remain unclear. However, it could be associated with properties of NGF against the reactive metabolic events occurring in secondary degenerative processes, including apoptosis, oxidative stress, excitotoxicity, calcium dysregulation, and mitochondrial dysfunctionin vivo has been challenging owing to the optical transparency of these cells58. However, as RGC loss in optic neuropathies have been shown to occur by apoptosis59, apoptotic RGCs can be imaged in vivo in real time using DARC technology that utilizes fluorescently labelled Annexin V to identify retinal neuronal apoptosis62. Established in 2004, the DARC has been demonstrated to be a valuable tool in monitoring of RGC apoptosis in vivo in various animal models of retinal neurodegeneration66. A recent clinical trial (Phase 1) in glaucoma patients has further shown that DARC enables visualization of neuronal apoptosis at single cell resolution in human retina, and DARC count (apoptosis) was significantly higher in glaucoma patients and correlated with disease progression17. Using DARC, we have shown in the present study that topical rh-NGF significantly reduced RGC apoptosis (Anx488 count) induced by pONT, compared to untreated controls. This is in agreement with previous studies that the protective effect of NGF on the RGCs is mediated by inhibition of apoptosis via increasing expression of pro-survival genes and decreasing expression of pro-apoptotic genes26. NGF-mediated reduction of apoptosis may also be associated with the restoration of the NGF/proNGF ratio, as proNGF protein is neurotoxic to RGCs and markedly up-regulated after axotomy67. The capability of imaging RGC apoptosis in vivo would pave the way to evaluate NGF therapy in patients with all kinds of optic neuropathy.While RGC survival can be assessed and quantified histologically in animal models, imaging of RGCs 27. Whereas the transscleral route has been seen on insulin uptake following topical administration68, delivery into the retrobulbar space to the optic nerve and retina is supported by other studies of topically instilled drugs, including iganidipine - a Ca2+ antagonist69 and Nepafenac – a non-steroidal anti-inflammatory agent70, in rabbits. The drugs were found to reach either the retrobulbar periocular space or the retina by local penetration at functional concentrations70. Additionally, a clinical study reported that a substantial amount of drugs was found to accumulate in the periocular tissue in glaucoma patients under long-term topical administration of timolol or betaxolol, suggesting that the topically instilled drugs exert pharmacologic effects by delivery into the retrobulbar space before reaching the posterior eye71. A similar finding has been described by the manufacture, Dompe, with topically administered rh-NGF; rh-NGF is found to be present in the retina and optic nerve but absent in both the aqueous humour and vitreous humour , a key transcription factor that regulates the expression of many genes and may play a crucial role in the initial activation of astrocytes in glaucoma73. It is thus proposed that glaucomatous damage in the optic nerve axons is secondary to astrocytes-induced damage74.Glial cell activation has been implicated in optic nerve injury. Activated astrocytes, as an early event after injury, have been documented to be a major contributor to spreading and acceleration of secondary degeneration74. Similarly, activated astrocytes play a major role in the remodelling of the extracellular matrix in optic neuropathy, such as glaucoma, leading to axonal loss and retinal ganglion cell degeneration76. Therefore, controlling glial activity by modulating neurotrophic factors may have a potential to protect neurons and minimize damage79. Neurotrophic factors, such as BDNF have been reported to result in delayed activation of the microglial cells and increased RGC survival following optic nerve transection78. Modulation of NGF receptors by inhibition of p75NTR (expressed by Muller glia) was also shown to enhance TrkA-mediated survival of injured RGCs79, indicating that targeting microglial activation and modulating neurotrophic pathway may be a potential strategy to save retinal neurons following injury. Similarly, our results also show that topical rh-NGF significantly inhibits pONT induced increase in astrocyte activity (GFAP intensity) in the optic nerve, which was consistent with increased axonal survival with higher dose of rh-NGF.An important function of astrocytes is to preserve integrity of neural tissues following injury or in disease. In the brain, matured and quiescent astrocytes become reactive after injury, and reactive astrocytes form a barrier around the injured neural area to prevent further lesions, which however, may also lead to inhibition of axonal growth and functional damageIn conclusion, we have demonstrated that topical NGF is neuroprotective to RGCs and their axons after optic nerve injury. The protective effects of NGF are mainly attributed to targeting secondary degeneration. DARC imaging is a useful tool for monitoring NGF efficacy on RGC protection in real time, with implications of translating the therapy to clinic.ad libitum.Adult male Dark Agouti rats weighing 150–200 grams were used in this study and treated with procedures approved by the UK Home Office and in compliance with the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research. Animals (n = 46) were maintained in a 12-h light/12-h dark cycle with a room illuminance of 140–260 lux during the bright portion of the cycle, and provided standard food and water 30. Briefly, an incision was made in the superior conjunctiva, and the optic nerve sheath exposed. A longitudinal slit was made in the dura mater and a 0.2-mm cross cut performed in the dorsal optic nerve at a distance of 2 mm behind the eye. An ophthalmic scalpel with a steel cutting guard of 0.2-mm was used in this procedure. Damage of major ophthalmic blood vessels was avoided and verified at the end of surgery by ophthalmoscopy.Under general anaesthesia (GA), pONT was performed in the left eye of all animals, as previously describedFollowing pONT procedure, animals were topically treated with rh-NGF in two concentrations of 180 ug/ml and 540 ug/ml, respectively, twice a day for 3 weeks. Control groups included pONT without rh-NGF treatment and normal naïve animals. At least 5 animals were included in each treatment and control groups. Researchers were masked to the treatment groups. To assess whether rh-NGF reaches the retina and optic nerve after topical administration, six animals were topically treated with either hr-NGF or vehicle, twice a day for 3 days, and culled 6 hours after the last eye drops.in vivo for RGC apoptosis at baseline and 3 weeks after pONT and treatments using DARC, as we previously described66. Briefly, animals under GA were intravitreally administered with fluorescently labelled 488 annexin V and imaged in 2 hours using a confocal scanning laser ophthalmoscopy (cSLO) . The retinal images were then collected, and the number of apoptotic RGCs were manually counted by three masked observers and the normalised DARC count determined using equation [% is the percentage DARC count, which comprises an individual DARC count (DC) normalised to mean pONT DARC count (DCp) and mean naïve control DARC count .All animals were imaged equation .1\documein vivo study, and both eyes enucleated and fixed in fresh 4% paraformaldehyde at 4 °C overnight. Retinal whole-mounts and optic nerves were then dissected for immunostaining. To assess the therapeutic effects of rh-NGF on RGC protection, retinal whole-mounts were stained with an anti-mouse Brn-3a antibody  and examined under confocal microscopy . A single plane maximum intensity projection of RGC layer was then obtained following z-stack and tile scan of each retina. Optic nerves were paraffin-embedded and cross-sections obtained before immunostaining with antibodies of anti-mouse neurofilament-H  and anti-rabbit glial fibrillary acidic protein , respectively. The stained optic nerve sections were also examined under confocal microscopy and quantified by fluorescent intensity using Image J.Animals were sacrificed after 3 weeks’ 31. Briefly, a high-pass filter was applied to the 8-bit Brn3a labelled channel to remove background followed by application of a 130 intensity threshold. The ImageJ watershed algorithm was then used to separate touching particles and those within 7–21 µm size range were counted based on RGC sizes previously reported48, and only particles with a circularity >0.7 were considered to be RGCs in order to exclude blood vessels also stained by Brn3a. Once identified, a region of interest (ROI) was defined for each RGC from which RGC area, mean grey pixel intensity and centroid  was recorded. The density of RGCs (cells/mm2) was calculated by the algorithm counts divided by retinal area which was determined by applying a customised ImageJ script. The nearest neighbour distance (NND) was determined for each RGC using an ImageJ macro from which regularity index (RI) was calculated. To assess topical rh-NGF effects on primary and secondary degeneration, retinal whole-mounts were segmented into quadrants and RGC loss in superior and inferior segments evaluated31.Quantification of Brn3a labelled RGCs in retinal whole-mounts was achieved using an algorithm previously describedg for 20 min at 4 °C. The supernatants were withdrawn to be used to detect human beta-NGF concentration in the retina and optic nerve using a rat beta-NGF human SimpleStep ELISA kit ab193760 (abcam), following the manufacturer’s instructions. Briefly, a SimpleStep ELISA kit uses an affinity tag labelled capture antibody and a reporter conjugated detector antibody which immunocapture the sample analyte in solution. This entire complex  is, in turn, immobilized via immunoaffinity of an anti-tag antibody coating the well. To perform the assay, 50 µl volume of samples (duplicate) or standards (triplicate) were added to the wells, followed by 50 µl volume of the antibody mix. After 1 h incubation at room temperature on a plate shaker set to 400 rpm, the wells were washed 3 × 350 μL 1X wash buffer to remove unbound material. Then, 100 μL of TMB Development Solution was added to each well followed by an incubation for 5–10 min in the dark  on a plate shaker set to 400 rpm. During incubation, catalyzed by HRP, a blue coloration was generated. This reaction was stopped by addition of 100 μL of Stop Solution to each well, completing any colour change from blue to yellow. Signal was generated proportionally to the amount of bound analyte and the intensity was measured at 450 nm with a plate reader after 1 min on a plate shaker to mix.Six animals were sacrificed 3 days following unilateral pONT and topical treatment of either rh-NGF or vehicle. The eyes were enucleated, and the retina and the optic nerves freshly dissected on ice and stored in clean sterile tubes at −80 °C until use. To extract proteins, the retina and optic nerve samples were homogenized by bath sonication in Cell Lysis Buffer  containing protease inhibitor cocktail (P8340 Sigma) and phosphatase inhibitor cocktails 2 and 3 . Then, protein lysates were kept in a cold room on a rotating shaker for 2 h to allow complete tissue disaggregation and cell lysis. This step was followed by sample centrifugation at 10,000 × All data were analysed with Student t-test or one-way ANOVA with Bonferoni post-test versus control groups using GraphPad Prism 5 . Data were presented as means ± SEM and P < 0.05 was considered significant. N ≥ 5.Supplementary Table 1.


The expansion of intensive fish farming in recent decades has led to increase in the number of fish diseases , 2. ThisWu et al. showed that activation of macrophages using three different molecular weight COSs  correlated with different chitosan oligosaccharides molecular weights (COS-MWs) of which the COS-MW with highest molecular weight had the highest activation of macrophages. In another study, Semple et al. showed that monocyte/macrophage- RTS11 cells pre-treated with PACAP 24 h before infection, severely inhibited Flavobacterium psychrophilum growth and increased expression of pro-inflammatory cytokines together with PACAP receptors in a dose-dependent manner. Simón et al. showed that CpGs increased the survival of IgM+ B cells, induced their proliferation and differentiation to plasmablasts/plasma cells, upregulated MHC-II and co-stimulatory molecules, and increased their phagocytic capacity while Iliev et al. showed that CpG stimulation transformed the rainbow trout primary phagocytes into dendritic-like-cells exhibiting long branching pseudopodia. These dendritic-like cells expressed high pro-inflammatory genes belonging to a Th17 response (IL-17A/F1) and a Th2 response (IL-4/13) where IL-10 and IFNγ was downregulated. Both studies demonstrated that CpGs are capable of modulating both the innate and adaptive branches of the immune system in fish, thus pointing to these molecules as optimal vaccine adjuvants. To gain further insight on how these CpGs are recognized by the host, Lai et al. performed an in depth study that points out that recognition of CpGs in fish is carried out by two sensors, namely Toll-like receptor 9 (TLR9) and TLR21, consequently demonstrating that the signaling of CpGs is more complex in fish than in mammals that only use TLR9 as a CpG sensor. Wangkahart et al. showed that Yersinia ruckeri flagellin upregulated several pro-inflammatory cytokines, acute phase proteins, antimicrobial peptides and complement genes in multiple tissues after in vivo administration, results that point to flagellin as another potent immunostimulant/adjuvant for fish aquaculture.Immunostimulants (IMM) have historically been defined as substances that have the capacity to increase innate immune responses . But becin vitro models for studying immune responses to vaccine antigens or to IMM, is of great interest, to reduce the use of animals and pre-evaluate the potential of these substances through an easy method. In this sense, Wang J. et al. developed an in vitro model for studying responses to immunostimulation in the gut using rainbow trout intestinal epithelial cells (RTgutGC) propagated on conventional culture plates and transwell membranes, which they used to evaluate gut responses to stimulation by LPS and three functional feed ingredients namely; (i) mannanoligosaccharides (MOS), (ii) β-glucans, and (iii) nucleotides. MOS was found to be the most potent immunostimulant that upregulated several inflammatory cytokines such IL-1β, IL-6, IL-8, TNFα, and TGFβ at similar levels with LPS while nucleotides and β-glucans only upregulated IL-1β and IL-8. Overall, RTgutGC cells had features characteristic of functional intestinal cells and therefore offer a useful in vitro model useful for evaluating the effects of IMM and feed ingredients on gut immune responses.Developing de facto “innate immune memory” is commonly referred to as “trained immunity”  is well-documented in mammals where it is mainly done by M-cells . HoweverWang Y. et al. used the isobaric tag for relative and absolute quantification (iTRAQ), to identify protective biomarkers among 341 Aeromonas hydrophila genes expressed in response to iron starvation. By knocking out three genes that had low protease activity, they constructed three avirulent mutants as live vaccines that produced high protection in zebrafish (Danio rerio). Another approach used to identify broadly protective antigens is by performing multiple sequence alignments to identify conserved antigenic proteins protective across variant strains. Wang E. et al. used this approach to design a Yersinia ruckeri outer membrane porin F (OmpF) vaccine after identifying a highly conserved motif among 15 sequences of Yersinia species, which confered increased protection and high antibody responses in channel catfish. Similarly, the paper by Maiti et al. provides a detailed account of various in silico and bioinformatics analytical tools used to identify outer membrane protein (OMP) antigens with broad protective abilities against variant strains of different bacterial species infecting major farmed fish species in India.Pathogen diversity poses a challenge for the selection of vaccine candidates with broad protective ability across variant strains. To this aim, various techniques aimed at identifying vaccine antigen candidates with broad protective abilities are being sought. For example, Abdelhamed et al. produced a recombinant A. hydrophila ATPase protein vaccine that showed increased survival and reduced bacterial concentrations in different tissues of catfish after challenge with virulent A. hydrophila ML09-119 strain. Lange et al. showed a progressive increase of systemic and mucosal IgM levels over a period of 2 years in catfish immunized by bath using a recombinant DnaK (rDnaK) vaccine made from the Flavobacterium columnare DnaK heat-shock-protein (Hsp70 protein). Finally, Maiti et al. reviewed the use of outer membrane proteins (OMPs) as subunit, DNA and nanoparticle vaccines against different pathogens infecting farmed fish in India. In the case of intracellular replicating bacteria, an efficient vaccine should be able to evoke both humoral and cell-mediated immune responses able to eliminate infected cells. To this end, Kordon et al. developed two live attenuated vaccines (LAVs) designated as EiΔevpB, and ESC-NDKL1 against Edwardsiella ictaluri, a facultative intracellular replicating bacterium. Both LAVs elevated IFN-γ expression in lymphoid organs that correlated with increased CD207+ cells and polarization of T-helper genes in vaccinated catfish.Although there are many commercial antibacterial vaccines available for use in aquaculture, there are still some bacterial pathogens for which vaccines have not been developed or are deficient. In this Special Issue, different recombinant approaches have been explored. Jiang et al. showed that crucian carp (Carassius carassiuss) cultured at 30°C showed an increased tricarboxylic acid (TCA) cycle linked to reduced taurine and hypotaurine metabolism coupled with low unsaturated fatty acid biosynthesis, which enhanced bacterial infection in a dose-dependent manner in fish. Conversely, exogenous treatment of fish using these metabolites increased fish survival and rescued the decline of pro-inflammatory cytokine expression that included TNF-α1, TNF-α2, IL-1β1, IL-1β2, and lyz expression. This study shows that changes in the interplay between temperature and fish metabolism can be used to regulate immune protection against bacterial infection in fish.Temperature manipulation is an important factor known to alter virulence of various fish pathogens  as well Teige et al. developed a multiplexed bead antibody assay able to differentiate antibody responses induced by piscine reovirus (PRV) σ1, σ2, and σ3 antigens. In trying to elucidate factors driving the specificity of fish antibodies, Magadan et al. searched for “public” antibody clonotypes common to all individuals that may mediate universal protection against pathogens. Through CD3 spectratyping of splenic B cells 5 months after vaccination with an attenuated viral haemorrhagic septicaemia virus (VHSV) vaccine, they showed that the IgM repertoires of vaccinated fish had altered profiles for the heavy chain variables (VH) VH1, VH4, and VH5 families. The altered profile of VH5 was the only clonotype found in all vaccinated individuals, suggesting that it may contain a persisting public component, while responses associated with VH1 and VH4 varied from fish to fish. Further analysis of the variable (V), joining (J), and diversity (D) gene segments showed that the VH5 and JH5 clonotypes formed persistent public VH5JH5 IgM dominant antibodies common to all vaccinated individuals. In addition to these studies, Peñaranda et al. obtained a cell surface proteome of Atlantic salmon IgM+ B cells by mass spectrometry and comparing it to that of two adherent salmon head kidney cell lines and used it to identify specific markers of B cells, namely CD22 and CD79A, in salmon. The identification of these molecules is very important to track B cell responses to vaccines and/or immunostimulants in the future.Antibody production together with cell mediated immune responses constitute the hallmark of long-term protective immunity in vaccinated fish. As such, antibodies produced by B cells, are widely used as a measure of immune response to vaccination in fish . Along tMaekawa et al. describes the use of RNA-seq as a useful tool used to identify the universality and diversity of immune responses against different pathogens expressed in different fish species by comparing immune genes expressed in response to Nocardia seriolae in largemouth bass , Lactococcus garvieae in gray mullet , Vibrio harveyi in orange-spotted grouper (Epinephelus coioides), and Aeromonas sobria in koi carp (Cyprinus carpio). They found 39 differentially expressed immune genes that were present in all fish species having the potential to serve as universal immunological markers of protective immunity. This study suggests that common signatures of protective immunity can be identified for use across different fish species.To a large extent, the correlates of protective immunity for most fish vaccines are unknown. Moreover, whether common signatures of protective immunity across different fish species can be identified or not remains a challenge. However, novel high throughput sequencing (HTS) techniques such as RNA-seq that provide whole transcriptomes of immune genes expressed in response to different stimuli are beginning to unravel different molecular markers that could serve as signatures of protective immunity expressed by different fish species in response to different pathogens. The study performed by Overall, the ccontributions gathered in this Special Issue provide a wide range of novel approaches and technologies being developed aimed at producing highly protective vaccines for finfish. What is now required is translation of these experimental findings to the fish farming industry with the objective of reducing the disease burden in aquaculture through vaccination.All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Right ventricular (RV) remodeling and longitudinal fiber reorientation in the setting of pulmonary hypertension (PH) affects ventricular structure and function, eventually leading to RV failure. Characterizing the kinematics of myocardial fibers helps better understanding the underlying mechanisms of fiber realignment in PH. In the current work, high-frequency ultrasound imaging and structurally-informed finite element (FE) models were employed for an exploratory evaluation of the stretch-induced kinematics of RV fibers. Image-based experimental evaluation of fiber kinematics in porcine myocardium revealed the capability of affine assumptions to effectively approximate myofiber realignment in the RV free wall. The developed imaging framework provides a noninvasive modality to quantify transmural RV myofiber kinematics in large animal models. FE modeling results demonstrated that chronic pressure overload, but not solely an acute rise in pressures, results in kinematic shift of RV fibers towards the longitudinal direction. Additionally, FE simulations suggest a potential protective role for concentric hypertrophy  against fiber reorientation, while eccentric hypertrophy (RV dilation) resulted in longitudinal fiber realignment. Our study improves the current understanding of the role of different remodeling events involved in transmural myofiber reorientation in PH. Future experimentations are warranted to test the model-generated hypotheses. Pulmonary hypertension (PH) is a disease that results in RV pressure overload, ventricular remodeling, myocardial hypertrophy and fibrosis. RV failure remains the main cause of mortality in the setting of PH4. From a biomechanical perspective, RV myocardium experiences increased wall thickness, tissue stiffening, fibrosis, chamber dilation and transmural fiber reorientation in PH6. RV remodeling and fiber reorientation towards the longitudinal (apex to base) direction results in drastically different RV biomechanics, affecting the transmural distribution of wall stress7, ventricular twisting motions and filling and ejection mechanics of the RV8. Nevertheless, mechanistically, RV fiber reorientation is poorly understood and there remains a debate around the adaptive9 vs. maladaptive8 nature of fiber remodeling in PH. Characterizing the kinematics of myocardial fibers will help establishing a better understanding of the underlying mechanisms of fiber realignment in PH. However, full-thickness transmural RV fiber kinematics remains largely unexplored, mainly due to imaging difficulties caused by the RV wall thickness in large animal models and human patients, limiting our ability to study fiber kinematics transmurally. Despite high imaging resolutions, the depth limit of optical techniques such as multi-photon microscopy (100–1200 μm limit10) and long imaging time, exposure to ionizing radiation, availability and cost-effectiveness issues with diffusion tensor magnetic resonance imaging12 (DTMRI) limit their applicability for benchtop or clinical studies on RV fiber kinematics. On the other hand, ultrasound imaging is a widely available, non-ionizing, cost-effective technique capable of overcoming the depth limits of optical methods to assess cardiac structure and function.Previous studies have closely linked RV biomechanics to ventricular function13 (demonstrating active contraction) in addition to fiber stretch13 and ventricular wall thinning14 (demonstrating stretch-induced deformations). This is followed by pulmonary valve opening and systolic ejection. Myocardial contraction (fiber shortening) results in small reversible changes in fiber angles towards the longitudinal direction16, as also reflected in the torsional motion of the heart17. However, longitudinal fiber remodeling in PH has been identified as an end-stage remodeling event8 accompanied by reduced RV ejection fraction8 and diminished systolic myofiber shortening18 (minimum principle strains). While the eventual outcome of fiber remodeling may affect ventricular contractile mechanics20, decreased minimum principle strains at end-stage PH18 results in smaller myofiber kinematic shifts towards the longitudinal direction compared to normotensive loading and makes myofiber contraction less likely to mechanistically stimulate transmural fiber reorientation in PH. Motivated by this, we hypothesized that stretch-induced deformations experienced by RV myocardium , stretching of RV myocardium may lead to fiber kinematics towards different directions under different loading scenarios . Previous studies have reported an increase in stretch-activated Ca6, concentric33 and eccentric34 hypertrophy on stretch-induced RV fiber kinematics in acute and chronic pressure overload. Our exploratory study improves the current understanding of the role of different remodeling events involved in transmural reorientation of RV fibers in PH. This will help with appropriate hypothesis generation for future experimental studies on RV fiber kinematics while ongoing work focuses on development of improved imaging algorithms for coupled HFU imaging/biaxial loading.In the first stage of this study, an enhanced framework was developed and validated against histological measurements to analyze high-frequency ultrasound (HFU) images for quantification of transmural RV myofiber orientations. Stretch-induced myofiber reorientation under uniaxial loading was studied to demonstrate the feasibility of the developed framework to study RV fiber kinematics. Furthermore, due to the complexity associated with coupled biaxial loading/HFU imaging, nonlinear structurally-informed fiber embedded finite element (FE) models of the RV myocardium were developed to conduct an exploratory study on biaxial fiber kinematics. FE models were used to study the role of different remodeling events such as fibrosis36. However, to the best of our knowledge, no efforts have been made to quantify the transmural kinematics of RV myofibers using HFU imaging. In the first stage of this study an enhanced HFU imaging framework was developed to study the transmural kinematics of RVFW myofibers  of porcine RVFW  and scanned at 50 MHz using an HFU scanner . HFU images were acquired at a precision of 524 pixels/cm while the imaging probe was positioned along the apex to base direction, normal to the transmural axis of the RVFW (from epicardium to endocardium). Using a servo stage, 3D scans were generated by stacks of 2D images acquired at 102 µm increments, chosen based on the transducer elevational beam width. Since HFU scans result in high noise in the acquired images, similar to previous studies36, a nonlinear anisotropic diffusion filter (NLADF) was used to reduce the noise levels  and helps reducing the noise levels while keeping the main features of the image37. The acquired B-mode images were filtered using Eq. 1 at two different iterations, NLADF(t1) and NLADF(t2), while t2 > t1. Appropriate iteration times (t1 and t2) were manually selected by observing noise reduction in the denoised images produced by NLADF (t1 = 100 and t2 = 300 iterations for the purposes of this study). This was followed by multi-scale decomposition of fine and coarse components of the image  is the original B-mode image, C1 is the fine component of the HFU image, C2 is the coarse component, ReINLADF is the reconstructed image following NLADF and multi-scale decomposition, and α1 and α2 are the scaling gains for image reconstruction , as previously defined38 was used to establish connectivity between disconnected fiber segments, while preserving the orientation of features in the original B-mode image .Finally, the resulting image was converted to a binary format and, subsequent to skeleton extraction, myofiber orientations were detected using the Hough transform Fig. a. A Gaus6. Briefly, for each histological section, local image gradients were calculated at each pixel, followed by the formation of the second-moment tensor of the gradient map:For technical validation purposes, HFU measurements were compared with transmural histological staining of the RVFW specimen using a hematoxylin and eosin (H&E) stain. Fiber orientation of histological sections were detected using gradient based image analysis techniques, as described in our previous studiesx and Iy are the partial spatial derivatives of the image I in x and y directions, respectively (obtained using a cubic B-spline interpolation40). Dominant fiber orientations at each transmural section were acquired by evaluating the first eigenvector of the resulting second-moment tensor41. Image processing and fiber orientation analysis of histological sections were performed using the OrientationJ toolbox41 in ImageJ (imagej.nih.gov). Similar to previous studies42, for algorithm validation and comparison purposes, fiber angles measured via histology and HFU imaging were normalized to 0° at the epicardial layer to better demonstrate the transmural change in fiber angles and eliminate any tissue alignment mismatch between HFU and histological measurements.Here, H is the structure tensor (2 × 2 symmetric positive-definite matrix), w is a gaussian weighing function specifying the region of interest for integration, and I34 and approximation of RVFW stretch based on previously reported biomechanical properties for a porcine model43. Experimentally measured fiber kinematics were compared with theoretical predictions for an incompressible transversely isotropic solid with affine kinematics44:Following algorithm verification, RVFW specimens (n = 3) were harvested from the basal anterior zone of porcine myocardium and loaded using a custom displacement-controlled uniaxial loading gripper that allows real-time HFU imaging. Fiber orientations were measured and analyzed in the RV circumferential-longitudinal coordinate system when apex-to-base denotes the longitudinal direction. Transmural fiber orientations were then analyzed under a stretch ratio (λ) of 1.35 in the circumferential direction. This was chosen based on a RV systolic pressure of ≈ 105 mmHg in PHUnloaded represents the unloaded fiber orientation at each transmural section, θLoaded is the fiber angle after loading-induced realignment and λ is the amount of uniaxial stretch. We hypothesized that uniaxial loading results in transmural realignment of RV myofibers towards the loading direction. Additionally, the transmural variation of fiber angles was approximated via linear regression (fiber angles vs. %thickness). Slope of the linear fit to transmural fiber angles demonstrates the helix slope of the RVFW (change in fiber angle per unit thickness), which was hypothesized to decrease in response to uniaxial loading.Here, θWhile the developed HFU algorithm shows great potential for quantifying RV fiber kinematics, it requires imaging in the plane parallel to the RV wall . This demands at least one side of the planar RVFW specimen to be free for imaging, which complicates coupled biaxial loading and HFU imaging. Therefore, in the second stage of this study structurally-informed nonlinear-heterogenous-anisotropic FE models of the RVFW were created for an exploratory assessment of biaxial fiber kinematics under different loading scenarios. This will lay the groundwork for future experimental studies on biaxial RV fiber kinematics, while development of specialized loading grippers and improved imaging algorithms for coupled HFU imaging/biaxial loading is in progress.45. Briefly, a custom MATLAB subroutine was used to explicitly create planar fiber networks using the dominant orientation and fiber spreads (pooled standard deviation of orientation distributions from n = 3 samples) measured via HFU imaging. Myofibers, collagen and the ECM were created with 93%, 4% and 3% volume fractions48, respectively, to approximate the tissue-level biaxial properties43 of porcine RV myocardium (Table 49:b is the first invariant of the left Cauchy–Green stretch tensor and W is the strain energy function when J = det(F) = 1 ensures incompressibility (F represents the deformation gradient tensor). Collagen fibers were modeled with linear elastic properties, activated after a recruitment stretch39:The modeling techniques used in this study have been described in detail in our previous workum Table . The ECMcol is the stiffness of collagen fibers and λr is the stretch at which collagen recruitment begins . For model verification, an unconfined uniaxial loading scenario (under λ = 1.35) was simulated and compared with experimental HFU imaging measurements of RVFW fiber kinematics.Here σ represents components of the Cauchy stress tensor, Ens Table . Additions Table . To find50, we employed a two-level modeling approach to keep the computational burden tractable. While simulations were performed on a representative volume element  of the RVFW incorporating tissue level structural organization  in the circumferential and longitudinal directions, w is the RV wall thickness, a and b are geometrical measures for biventricular modeling of the left and right ventricles using Laplace-type calculations  and spacing (35.8 ± 11.2 µm) were acquired form histological measurements  are present in the model , σons Fig. a and A1 les Fig. a. EquatiH Tables . This wi56, similar to previous studies56, post-deformation fiber orientations were categorized as circumferential .Here, f2 measure was used to evaluate the agreement between experimentally measured uniaxial fiber kinematics and theoretical estimations or FE model predictions. In addition, R2 measures were also used to evaluate the goodness of fit between experimentally measured biaxial mechanical properties of the RVFW and FE model predictions.Data is presented with mean ± standard deviation (SD)/standard error of the mean (SEM), or proportion (%) of fibers post-categorization. A one-way repeated measures ANOVA with Tukey’s post-hoc was used for pairwise comparison of RV helix slope before and after loading and theoretical predictions of affine reorientation. A R2) tests were performed to evaluate if fiber proportions were dependent on the loading condition. Post-hoc Z-tests with Bonferroni correction were utilized to test the differences across different loading scenarios. Due to integer overflow issues and limitations of the χ2 test for very large sample sizes, fiber counts were down sampled by a factor of 10, post categorization. This was chosen as an optimal down sampling rate required to avoid numerical instabilities when working with very large sample sizes  from our FE model.Chi-squared . Due to the small sample size in our experimental data and proportion testing (as opposed to tests of the mean) for FE simulations, a more strict measure was chosen for statistical comparisons. For all purposes, p < 0.01 (two-sided) was considered statistically significant.Statistical comparisons were performed using the R software package42 around the sub-epicardial layers , followed by a near-linear change in transmural fiber angles . The abrupt sub-epicardial change showed high between-sample variability, ranging from 64.7 to 175.2° (n = 4).Transmural RV myofiber orientations measured via HFU imaging and histology are compared in Fig. 2 = 0.92; Fig. 42, the abrupt epicardial change is plotted with the shortest map to 0° to better demonstrate fiber realignment towards the loading direction , while showing no significant differences with theoretical predictions of uniaxial affine fiber kinematics .Uniaxial loading (n = 3) resulted in fiber realignment towards the loading direction Fig. a, b, in 2Long. = 0.94, R2Circ. = 0.99, supplementary Fig. 2 = 0.89, supplementary Fig. p < 0.001 for CPO or CPO w/o Conc. Hyp. compared to Normotensive at all transmural sections). Concentric hypertrophy resulted in significantly smaller proportions of oblique fibers throughout the RVFW thickness . Supplementary Fig. The developed structurally-informed FE model matched the mechanical properties of RV myocardium in both longitudinal and circumferential directions  HFU imaging demonstrated a strong potential for quantifying full-thickness transmural orientations of RV myofibers in large animal models; (2) Uniaxial loading resulted in fiber realignment towards the loading direction, in agreement with theoretical predictions based on affine fiber kinematics; (3) FE modeling suggested that a combination of chronic pressure overload with RVFW fibrosis and concentric and eccentric hypertrophy , but not solely an acute rise in RV pressures, may result in kinematic shift of RV fibers away from the circumferential direction; (4) Computational exploratory assessments revealed a potential protective role for concentric hypertrophy against longitudinal fiber realignment in PH, while demonstrating that eccentric hypertrophy may stimulate fiber reorientation towards the longitudinal direction.59. This resulted in differences between the HFU and histologically measured fiber spreads at endocardium, while dominant fiber orientations were accurately characterized . Decreased transmural variation in fiber orientations with increased body size has also been reported in prior investigations60.HFU imaging effectively characterized the transmural orientation distribution (dominant orientation and fiber spread) of myofibers in porcine RV myocardium Fig. . Difficuzed Fig. b. As pre8, as anticipated, we did not observe dramatic changes in fiber angles under a single cycle of passive uniaxial loading. However, RV myofibers demonstrated a strong agreement with theoretical predictions of uniaxial affine kinematics  in the myofiber niche due to progressive RV dilation. It is also worth noting that while our results demonstrate that RV dilation may induce a “kinematic shift” in myofiber orientations, progression of a kinematic shift to fiber realignment may require multiple cycles of RVFW growth and remodeling. Further long-term longitudinal growth and remodeling studies, looking at the time course of progression of different remodeling events in PH, can provide fundamental insights into the cause-consequence relations between myofiber realignment and various RV remodeling events.Parametric studies on the level of RV fibrosis did not show any effects on fiber proportions under early-systolic or end-diastolic pressures Fig. . Between61). Therefore, while this affects the magnitude of the strains calculated in our models, it is less likely to affect the ratio of longitudinal:circumferential strains 8 need to be further investigated in future fiber-level studies.There are limitations to the experimental and FE modeling techniques used in the current work. HFU images were acquired under uniaxial loading, as it is currently not feasible under biaxial loading due to the requirement of imaging normal to the transmural axis  which necessitates at least one side of the RVFW specimen to be free for imaging. Ongoing work focuses on development of improved algorithms using spatial coherence maps to facilitate 3D imaging parallel to the RV transmural axis. While demonstrating strong statistics and minimal variabilities, the small sample size (n = 3) used for our exploratory experimental analysis remains as a limitation of the current study. Although our theoretical models provide insights into the stretch-induced fiber kinematics of RV myocardium under biaxial loading, lack of an experimental control group is a limitation of the current work and future experimental studies are needed to confirm the generated hypotheses via FE modeling. Moreover, our study focused on analyzing myofiber kinematics in the basal anterior zone of the RVFW, mainly due to the feasibility of acquiring theoretical wall stress approximations for this region Eqs. –12. FutuIn conclusion, we employed HFU imaging and structurally-informed computational models for an exploratory study on the stretch-induced kinematics of RV fibers under different loading scenarios. The developed imaging framework provides a noninvasive modality to characterize the transmural fiber kinematics of RV myocardium. Simulations suggest a potential protective role for concentric RV hypertrophy  against fiber reorientation. On the other hand, accounting for eccentric hypertrophy (RV dilation) in FE models resulted in kinematic shift of fibers towards the longitudinal direction, due to altered stretch ratios in the RVFW. While this helps better understanding the role different remodeling events and biomechanical forces in transmural realignment of RV fibers in PH, future experimentations are warranted to test the model-generated hypotheses.Supplementary tables.


While these methods were optimized in sorghum [Sorghum bicolor (L.) Moench], they were developed to be applied to any species with a reference genome and high-coverage whole-genome sequencing data of individuals from the sub-populations to be characterized. An analysis of published sorghum genomes selected to represent its five main races  identified 130,120 SSR motifs. Average lengths were 23.8 bp and 95% were between 10 and 92 bp, making them suitable for NGS. Validation through targeted sequencing amplified 188 of 192 assayed SSR loci. Results highlighted the distinctness of accessions from the guinea sub-group margaritiferum from all other sorghum accessions, consistent with previous studies of nuclear and mitochondrial DNA. SSRs that efficiently fingerprinted margaritiferum individuals (Xgma1 –Xgma6) are presented. Developing similar fingerprints of other sub-populations (Xunr1 –Xunr182) was not possible due to the extensive admixture between them in the data set analyzed. In summary, these methods were able to fingerprint specific sub-populations when rates of admixture between them are low.Recent plant breeding studies of several species have demonstrated the utility of combining molecular assessments of genetic distance into trait-linked SNP genotyping during the development of parent lines to maximize yield gains due to heterosis. SSRs (Short Sequence Repeats) are the molecular marker of choice to determine genetic diversity, but the methods historically used to sequence them have been burdensome. The ability to analyze SSRs in a higher-throughput manner independent of laboratory conditions would increase their utility in molecular ecology, germplasm curation, and plant breeding programs worldwide. This project reports simple bioinformatics methods that can be used to generate genome-wide  Sorghum bicolor (L.) Moench] (2n = 2x = 20) is a drought-tolerant C4 grass species having wide genetic diversity  to assist in the selection of parent lines having greater genetic distances among them to achieve improved heterosis in grain yield , heterosis observed in grain yield and most yield components was positively correlated with greater genetic distance among parents whose % relatedness ranged from 0.18 to 0.33, as determined by SNP and SilicoDArT markers [Genetic diversity information from Diversity Arrays Technology (DArT) markers has been used in wheat [in yield . Jaccard markers . Similar markers  used RFL markers , who mea markers , who use markers ,17.de novo identified from WGS data and optimized for targeted sequencing and population structure determination, including the distinction of races and working groups. To the best of the authors’ knowledge, this is the first use of version three of the Sorghum bicolor genome assembly, which was assembled using long reads (~30 kb) as opposed to previous versions assembled from short reads (resulting in less ambiguity within repetitive regions where SSRs reside), to identify sub-population-specific SSRs at much wider genome coverage. The methods outlined herein demonstrate that large sets of SSRs can be optimized for targeted sequencing to easily analyze many different genomic locations during single runs. These runs are easily compiled into Microsoft Excel or CSV files that are accessible to those with limited bioinformatics training. This helps breeders to better understand and utilize the genetic diversity within their breeding populations without the need for expensive specialized equipment.The current study conducted a re-analysis of sorghum accessions sequenced from various published works ,22,25 asde novo identification of SSRs for sub-population determination in sorghum. This work provides the first publicly available resource to genetically differentiate sub-populations using targeted sequencing methods that are more economical than genome-wide SNPs and that also provide a more accurate picture of genetic diversity. As a proof of concept, this work identified NGS-validated SSRs that successfully differentiated the guinea working group, margaritiferum, (Xgma1 –Xgma6), from the five main races of sorghum. This work also provides an additional 182 NGS-validated SSRs for analyzing genetic diversity (Xunr1 –Xunr182). All SSRs are presented with their genomic locations and suitable primers for their extension using either gel-based or NGS techniques. Once additional WGS data is published that evenly and comprehensively represents the five main races, similar fingerprints for each of them will also be possible. Finally, these methods can be deployed in any species with a reference genome to assist molecular ecology, germplasm curation, or conservation programs.The aim of this project was the in silico analysis, and were obtained from the sequence read archive at NCBI. To distinguish samples by source, accessions from the first published data were named as published [Sorghum bicolor reference genome (Sbicolor_454_v3.0.1) [de novo SSR identification using PLINK software (version: 1.9) [The raw sequencing data of 75 sorghum accessions ,22,25 weublished ,25. The ublished  was used_v3.0.1)  was used_v3.0.1)  was usedon: 1.9)  with seton: 1.9)  for SSR K = 2–10 (--full --seed = 100 --prior = logistic). Calculation of the log-marginal likelihood lower bound (LLBO) was performed in fastSTRUCTURE to determine the optimal value K within the population of study [For the genetic analysis of sorghum populations, fastSTRUCTURE  (versionof study . Plots wof study  package of study  in RStudof study . SplitsTof study  was usedof study .n = 4), caudatum (n = 29), durra , kafir (n = 16), and margaritiferum (n = 4)) were assigned a score of 1 if there was a reference or alternative allele found in the previously published sequencing data [SSR locations for each of the six populations   VCF filehttps://www.ncbi.nlm.nih.gov/) as BioProject (PRJNA610844), with 53 BioSample accession numbers (SAMN14318439—SAMN14318491), and 53 Sequence Read Archive (SRA) submission accession numbers (SRR11252447—SRR11252499).A total of 75 sorghum WGS data sets were published with sufficient sequencing depth for analysis at the time of the study ,22,25, bIn silico SSR chromosome mapping was performed using the R [ng the R  package ng the R  in RStudng the R . SSRs wel is the number of alleles in the locus and iP and jP are the allele frequencies of the ith and jth alleles, respectively.The genetic information statistics for polymorphism information content (PIC) and heterozygosity (H)  were calS. bicolor (Sbicolor_454_v3.0.1) genome [K values, 2–10 , the genetic structure analysis depicts the margaritiferum accessions as different from the majority of accessions within the other populations  and read lengths (150 bp) used. Selected SSRs were sequenced using Illumina technology  in all 5X to signify that they are SSRs, then with gma to identify their use for determining the guinea working group margaritiferum, and finally numbered one through six in order of chromosomal and genomic location starting from the first base pair on Chromosome one to the final base pair on Chromosome ten based on the current Sorghum bicolor reference genome [Xgma1 –Xgma6, their genomic locations, repeat sequences in the reference genome, repeat sequences specific to margaritiferum, as well as their corresponding forward and reverse primers, are shown in Xgma1 –Xgma6 for the 53 accessions sequenced are presented in X to signify them as SSRs, then with unr to identify the location of their development , and numbered 1–182 by the same ordination scheme of genomic location  that amplified only in wild sorghum relatives sequenced for a separate analysis was not used to calculate PIC or H because it was not relevant to differentiating among sub-populations (The PI (Plant Introduction) numbers and accession name labels of the 53 accessions used for NGS validation of SSRs are provided in e genome . The sixlocation  as was ual. 1980 , 114 of ulations . In agreulations , common ulations . This fiXgma1 –Xgma6 are highly unique to margaritiferum accessions. For example, the Xgma2 allele in margaritiferum accessions was ten (GCC) repeats, but no Xgma2 alleles of this length were observed in non-margaritiferum accessions  repeats; whereas no Xgma4 alleles of this length were observed in non-margaritiferum accessions  repeats and all accessions were homozygous for this length  can clearly differentiate the margaritiferum accessions from all other sub-populations that contributed to this analysis.The numbers of repeats in cessions . Xgma4 acessions . The Xgms length , whereasK) for the sampled accessions, validated these findings. In silico analysis identified 163,943 SSRs in the Sorghum bicolor reference genome. Of those, 130,120 were present in 75 published WGS data sets and selected for further investigation based on read depth and sequence quality. While the six sub-populations identified shared many SSRs , each sub-population had 318 to 1,071 SSRs that were present in only that sub-population in the analyzed dataset , DArT markers, and SNPs. SSRs have advantages of increased power of discrimination among sub-populations, are more reliable, and have better repeatability than RFLPs  and SNPsThe availability of NGS-SSR pipelines enables the evaluation of genetic diversity at a throughput not previously possible, and they can be deployed in any species with a reference genome. NGS techniques are currently powerful enough that even genetically “identical” twins can be differentiated from one another . The powSorghum bicolor reference genome. To help identify margaritiferum from the remaining sub-populations, six novel SSR primer sets (Xgma1 –Xgma6) suited for targeted NGS are presented. 182 additional novel SSR primer sets (Xunr1 –Xunr182) are presented and may be used to develop similar fingerprints for the remaining sub-populations once more WGS information for each one becomes available. These SSRs are reported with their repeat motifs, the quantity of repeats in the reference genome and (where applicable) in margaritiferum accessions; forward and reverse primer sequences, and PIC and H values. This project demonstrates the amenability of SSRs to targeted sequencing and NGS and lays out a framework for future work standardizing molecular characterizations of sub-populations in sorghum.Our results divided sorghum into six distinct sub-populations  based both on genetic structure and split network mapping analyses of 75 published WGS data sets and comparisons with the S1 FigK equals 2 to 10 in order. Color depicting each population (P1-P10) shown in the corresponding legend on the right of each graph.FastSRTUCTURE plotting in ggplot2 of accessions’ genetic structure from (PDF)Click here for additional data file.S2 Figy-axis) calculated in fastSTRUCTURE and plotted against the K population size (x-axis) shows 6 is the optimum population size to maximize the marginal likelihood. Dashed line drawn at -.709 marginal likelihood for cut off between K = 5 & 7 versus K = 6.The log-marginal likelihood lower bound ((PDF)Click here for additional data file.S1 TableThis table includes the accession names and PI numbers that were grown and used for NGS sequencing.(XLSX)Click here for additional data file.S2 TableThe read count table is presented for all of the samples sequenced by NGS.(XLSX)Click here for additional data file.S3 TableXgma1 –Xgma6. The accessions are sorted based on population. The reference allele and all alternative alleles for the SSRs are included at the bottom of the table.This table includes the sequencing data for each of the 53 accessions at (XLSX)Click here for additional data file.S4 TableXgma1 –Xgma6 & Xunr1 –Xunr182. The chromosomal locations of the SSRs, the primers (forward and reverse) with their associated Tms, and the reference genome sequence are provided.This table includes the sequencing data of the 53 accessions at (XLSX)Click here for additional data file.S5 TableXgma1 –Xgma6 & Xunr1 –Xunr182 based on the 53 accessions sequencing data.This table includes the PIC and H values calculated for (XLSX)Click here for additional data file.


Small heat shock proteins are ubiquitously expressed chaperones, yet mutations in some of them cause tissue-specific diseases. Here, we will discuss how small heat shock proteins give rise to neurodegenerative disorders themselves while we will also highlight how these proteins can fulfil protective functions in neurodegenerative disorders caused by protein aggregation. The first half of this paper will be focused on how mutations in HSPB1, HSPB3, and HSPB8 are linked to inherited peripheral neuropathies like Charcot-Marie-Tooth (CMT) disease and distal hereditary motor neuropathy (dHMN). The second part of the paper will discuss how small heat shock proteins are linked to neurodegenerative disorders like Alzheimer’s, Parkinson’s, and Huntington’s disease. Small heat shock proteins (sHSPs) are molecular chaperones whose canonical function is to preserve cellular proteostasis. Unlike heat shock proteins with an ATPase domain , sHSPs are ATP-independent chaperones that recognize and bind unfolded or misfolded proteins. Target proteins are kept in a folding-competent state until ATP-dependent heat shock proteins complete the refolding process  and/or distal hereditary motor neuropathy (dHMN)  was identified in two siblings diagnosed with dHMN  amplitudes from the age of 6 months onwards, which was further supported by a significant decrease in performance on the rotarod. At the molecular level, Hspb8 aggregates were detected by immunohistochemistry in sciatic nerves of 15 months old Hspb8K141N/K141N mice but not in Hspb8+/+ animals. Additionally, in the muscle of 12-month-old Hspb8K141N/K141N mice, we also detected Hspb8-positive aggregates associated with desmin and αβ-crystallin. Interestingly, the Hspb8−/− mice did not develop any motor deficit or electrophysiological abnormalities. Aged Hspb8−/− mice showed only minor structural irregularities in the muscle which remained subclinical as the mice performed as good as age-matched controls on the rotarod.A knock-in mouse model for the K141N missense mutation was developed, mimicking the neuropathy phenotype segregating in the originally described Belgian dHMN family  the absence of Hspb8 aggregates, (ii) activation of compensatory mechanisms mimicking the role of Hspb8, and (iii) the absence of any additional toxic gain-of-function consequences of the K141N mutant. We have previously shown that mutant human HSPB8 is prone to aggregation in patient fibroblasts  together with the co-chaperone BAG3, HSP70/HSC70 (heat shock protein/cognate 70), and SQSTM1/p62  Carra  and the HSPB8 not targeting this Lys141 hot-spot were also reported  studies that attempted to unravel the pathomechanism for HSPB8 were focused on mutants targeting the Lys141 residue. However, missense mutations in In summary, it remains striking how many of the HSPB8 mutations target the same amino acid. Yet, the molecular consequences of these mutations are still poorly understood. For instance, it has been suggested that these mutants lead to protein aggregation of HSPB8. However, it is unknown whether this is driven by HSPB8 itself due to its altered biophysical properties or whether HSPB8 is subjected to an aggregation-stimulating environment such as stress granules . These outstanding questions, along with the discovery of yet unknown roles for HSPB8, are topics that will hopefully be enlightened over the following years. In addition, the availability of a mouse model that mimics the patient’s phenotype offers the potential to verify in vitro obtained hypotheses and the potential to evaluate candidate therapies for HSPB8 patients.Many neurodegenerative disorders are characterized by the accumulation of protein deposits. Such protein deposits are generated through the assembly of insoluble fibrils from otherwise soluble proteins. These fibrils can be formed by different proteins, yet they adopt a similar cross-β sheet conformation  and intracellular neurofibrillary tangles (hyperphosphorylated tau) Selkoe . It is sThe amyloid precursor protein (APP) is a transmembrane protein that is processed by different secretases. However, due to improper cleavage by β- and γ-secretases, neurotoxic Aβ peptides may be formed. These peptides go on to form insoluble amyloid fibrils which accumulate in extracellular senile plaques, a hallmark of Alzheimer’s disease.In Alzheimer patients, both HSPB5 and HSPB8 are upregulated in the brain and found to colocalize with Aβ in senile plaques , cellular and mouse models were employed to study this process in more detail. For instance, neurons cultured from HSPB1-deficient mice were shown to be more sensitive to Aβ oligomer-mediated toxicity  gene and causes neurodegenerative diseases referred to as tauopathies  intrinsically disordered protein encoded by the SCNA gene. Neither the loss of dopaminergic neurons in the substantia nigra nor the deposition of α-synuclein is specific for Parkinson’s disease; however, the combination of both is sufficient to make a definitive diagnosis  led to reduced inhibition by the sHSPs Q-induced neurodegeneration (Bilen and Bonini Drosophila) and human HSPB8 was found to counter SCA3(78)Q-mediated toxicity in the fly eye while downregulation of Dm-HSP67Bc significantly worsened the phenotype   or Lou Gehrig’s disease is a fatal neurodegenerative motor neuron disease. It affects neurons in the brain and spinal cord, leading to muscle weakness, loss of motor functions, paralysis, and breathing problems, eventually leading to death. At the molecular level, ALS is characterized by protein aggregates that accumulate as ubiquitin-positive inclusions in the cytoplasm of degenerating neurons and glia  is a 414–amino acid ribonucleoprotein that resides in the nucleus but shuttles back and forth to the cytoplasm. It is both a DNA- and RNA-binding protein. It regulates transcription either through direct binding to the DNA or by interacting with components of the transcription machinery. In addition, it plays a role in splicing, RNA shuttling, and translation.Interestingly, the vast majority of all ALS-associated mutations lay in the C-terminal low-complexity prion-like domain (PrLD)  rescued the eye degeneration whereas downregulation of HSP67Bc worsened the eye phenotype  has been linked to both familial and sporadic ALS  mice did not yield neuroprotection, while another lab found that HSPB1 overexpression delays disease progression and increases motor unit survival  also cause protein aggregation . So side-by-side comparisons would aid further in assessing the potency of each of the chaperones individually, although it is to be noted here that the results may also depend on the cell type used to perform these studies. Results should therefore be interpreted with caution when obtained from in vitro models. In vivo models can provide additional information as they not only allow to assess whether a sHSP can reduce the protein aggregation but also allow to assess whether this leads to phenotypic amelioration. Finally, once it is understood which sHSPs are most potent towards which clients, it will become key to identify ways to introduce or upregulate these specific sHSPs in the desired tissues in order to obtain the desired protective effects.Taken together, although years of research has yielded us much information about the role and link of sHSPs to neurodegeneration, the next years should allow the field to transition more towards in vivo studies and identify potential novel treatment strategies for these neurodegenerative diseases.