Biology subjects

Lim, W.

Publications and source records attributed to Lim, W..

34 records · Page 2Linked to original sources

bioRxiv2021

Disynaptic Effect of Hilar Cells on Pattern Separation in A Spiking Neural Network of Hippocampal Dentate Gyrus

We investigate the disynaptic effect of the hilar cells on pattern separation in a spiking neural network of the hippocampal dentate gyrus (DG). The principal granule cells (GCs) in the DG perform pattern separation, transforming similar input patterns into less-similar output patterns. In our DG network, the hilus consists of excitatory mossy cells (MCs) and inhibitory HIPP (hilar perforant path-associated) cells. Here, we consider the disynaptic effects of the MCs and the HIPP cells on the GCs, mediated by the inhibitory basket cells (BCs) in the granular layer; MC [->] BC [->] GC and HIPP [->] BC [->] GC. Disynaptic inhibition from the MCs tends to decrease the firing activity of the GCs. On the other hand, the HIPP cells disinhibit the intermediate BCs, which leads to increasing the activity of the GCs. By changing the synaptic strength K(BC,X) [from the presynaptic X (= MC or HIPP) to the postsynaptic BC] from the default value K(BC,X)*, we study the change in the pattern separation degree [S]d. When decreasing K(BC,MC) or independently increasing K(BC,HIPP) from their default values, [S]d is found to decrease (i.e., pattern separation is reduced). On the other hand, as K(BC,MC) is increased or independently K(BC,HIPP) is decreased from their default values, pattern separation becomes enhanced (i.e., [S]d increases). In this way, the disynaptic effects of the MCs and the HIPP cells on the pattern separation are opposite ones. Thus, when simultaneously varying both K(BC,MC) and K(BC,HIPP), as a result of balance between the two competing disynaptic effects of the MCs and the HIPP cells, [S]d forms a bell-shaped curve with an optimal maximum at their default values. Moreover, we also investigate population and individual behaviors of the sparsely synchronized rhythm of the GCs, and find that the amplitude measure [M]a (representing population synchronization degree) and the random-phase-locking degree [L]d (denoting individual activity degree) are strongly correlated with the pattern separation degree [S]d. Consequently, the larger the synchronization and the random phase-locking degrees of the sparsely synchronized rhythm is, the more the pattern separation becomes enhanced.

neuroscience↗

bioRxiv2021

Population and Individual Firing Behaviors in Sparsely Synchronized Rhythms in The Hippocampal Dentate Gyrus

We investigate population and individual firing behaviors in sparsely synchronized rhythms (SSRs) in a spiking neural network of the hippocampal dentate gyrus (DG). The main encoding granule cells (GCs) are grouped into lamellar clusters. In each GC cluster, there is one inhibitory (I) basket cell (BC) along with excitatory (E) GCs, and they form the E-I loop. Winner-take-all competition, leading to sparse activation of the GCs, occurs in each GC cluster. Such sparsity has been thought to enhance pattern separation performed in the DG. During the winner-take-all competition, SSRs are found to appear in each population of the GCs and the BCs through interaction of excitation of the GCs with inhibition of the BCs. Sparsely synchronized spiking stripes appear successively with the population frequency fp (= 13 Hz) in the raster plots of spikes. We also note that excitatory hilar mossy cells (MCs) control the firing activity of the GC-BC loop by providing excitation to both the GCs and the BCs. SSR also appears in the population of MCs via interaction with the GCs (i.e., GC-MC loop). Population behaviors in the SSRs are quantitatively characterized in terms of the synchronization measures. In addition, we investigate individual firing activity of GCs, BCs, and MCs in the SSRs. Individual GCs exhibit random spike skipping, leading to a multi-peaked inter-spike-interval histogram, which is well characterized in terms of the random phase-locking degree. In this case, population-averaged mean-firing-rate [Formula] is less than the population frequency fp. On the other hand, both BCs and MCs show "intrastripe" burstings within stripes, together with "interstripe" random spike skipping. Thus, the population-averaged [Formula] (X = MC and BC) is larger than fp, in contrast to the case of the GCs. MC loss may occur during epileptogenesis. With decreasing the fraction of the MCs, changes in the population and individual firings in the SSRs are also studied. Finally, quantitative association between the population/individual firing behaviors in the SSRs and the winner-take-all competition is discussed.

biophysics↗

bioRxiv2021

Dynamical Origin for Winner-Take-All Competition in A Biological Network of The Hippocampal Dentate Gyrus

We consider a biological network of the hippocampal dentate gyrus (DG). The DG is a pre-processor for pattern separation which facilitates pattern storage and retrieval in the CA3 area of the hippocampus. The main encoding cells in the DG are the granule cells (GCs) which receive the input from the entorhinal cortex (EC) and send their output to the CA3. We note that the activation degree of GCs is so low (~ 5%). This sparsity has been thought to enhance the pattern separation. We investigate the dynamical origin for winner-take-all (WTA) competition which leads to sparse activation of the GCs. The whole GCs are grouped into lamellar clusters. In each GC cluster, there is one inhibitory (I) basket cell (BC) along with excitatory (E) GCs. There are three kinds of external inputs into the GCs; the direct excitatory EC input, the indirect inhibitory EC input, mediated by the HIPP (hilar perforant path-associated) cells, and the excitatory input from the hilar mossy cells (MCs). The firing activities of the GCs are determined via competition between the external E and I inputs. The E-I conductance ratio [Formula] (given by the time average of the external E to I conductances) may represents well the degree of such external E-I input competition. It is thus found that GCs become active when their [Formula] is larger than a threshold [Formula], and then the mean firing rates of the active GCs are strongly correlated with [Formula]. In each GC cluster, the feedback inhibition of the BC may select the winner GCs. GCs with larger [Formula] than the threshold [Formula] survive, and they become winners; all the other GCs with smaller [Formula] become silent. In this way, WTA competition occurs via competition between the firing activity of the GCs and the feedback inhibition from the BC in each GC cluster. In this case, the hilar MCs are also found to play an essential role of enhancing the WTA competition in each GC cluster by exciting both the GCs and the BC. PACS numbers: 87.19.lj, 87.19.lm, 87.19.lv

neuroscience↗

bioRxiv2021

T cell circuits that sense antigen density with an ultrasensitive threshold

Overexpressed tumor associated antigens (e.g. HER2 and EGFR) are attractive targets for therapeutic T cells, but toxic cross-reaction with normal tissues expressing low antigen levels has been observed with Chimeric Antigen Receptor (CAR) T cells targeting such antigens. Inspired by natural ultrasensitive response circuits, we engineer a two-step positive feedback circuit that allows T cells to discriminate targets based on a sigmoidal antigen density threshold. In this circuit, a low affinity SynNotch receptor for HER2 controls the expression of a high affinity CAR for HER2. Increasing HER2 density thus has cooperative effects on T cells it both increases CAR expression and activation leading to a sigmoidal response. T Cells with this circuit show sharp discrimination between target cells expressing normal and disease levels of HER2, both in vitro and in vivo. One Sentence SummaryA two-step positive feedback circuit generates engineered T cells capable of killing target cells with an ultrasensitive antigen density threshold.

synthetic biology↗

bioRxiv2020

Noise regularization removes correlation artifacts in single-cell RNA-seq data preprocessing

With the rapid advancement of single-cell RNA-seq (scRNA-seq) technology, many data preprocessing methods have been proposed to address numerous systematic errors and technical variabilities inherent in this technology. While these methods have been demonstrated to be effective in recovering individual gene expression, the suitability to the inference of gene-gene associations and subsequent gene networks reconstruction have not been systemically investigated. In this study, we benchmarked five representative scRNA-seq normalization/imputation methods on human cell atlas bone marrow data with respect to their impact on inferred gene-gene associations. Our results suggested that a considerable amount of spurious correlations was introduced during the data preprocessing steps due to over-smoothing of the raw data. We proposed a model-agnostic noise regularization method that can effectively eliminate the correlation artifacts. The noise regularized gene-gene correlations were further used to reconstruct gene co-expression network and successfully revealed several known immune cell modules.

bioinformatics↗

bioRxiv2020

Effect of Diverse Temporal Recoding of Granule Cells on Pavlovian Eyeblink Conditioning in The Cerebellum

We consider the Pavlovian eyeblink conditioning (EBC) via repeated presentation of paired conditioned stimulus (tone) and unconditioned stimulus (airpuff). The influence of various temporal recoding of granule cells on the EBC is investigated in a cerebellar network where the connection probability pc from Golgi to granule cells is changed. In an optimal case of [Formula], individual granule cells show various well- and ill-matched firing patterns relative to the unconditioned stimulus. Then, these variously-recoded signals are fed into the Purkinje cells (PCs) through parallel-fibers (PFs), and the instructor climbing-fiber (CF) signals from the inferior olive depress them effectively. In the case of well-matched PF-PC synapses, their synaptic weights are strongly depressed through strong long-term depression (LTD). On the other hand, practically no LTD occurs for the ill-matched PF-PC synapses. This type of "effective" depression at the PF-PC synapses coordinates firings of PCs effectively, which then make effective inhibitory coordination on cerebellar nucleus neuron [which elicits conditioned response (CR; eyeblink)]. When the learning trial passes a threshold, acquisition of CR begins. In this case, the timing degree [T]d of CR becomes good due to presence of the ill-matched firing group which plays a role of protection barrier for the timing. With further increase in the trial, strength [S] of CR (corresponding to the amplitude of eyelid closure) increases due to strong LTD in the well-matched firing group, while its timing degree [T]d decreases. In this way, the well- and the ill-matched firing groups play their own roles for the strength and the timing of CR, respectively. Thus, with increasing the learning trial, the (overall) learning efficiency degree [L]e (taking into consideration both timing and strength of CR) for the CR is increased, and eventually it becomes saturated. By changing pc from [Formula], we also investigate the influence of various temporal recoding on the EBC. It is thus found that, the more various in temporal recoding, the more effective in learning for the Pavlovian EBC.

neuroscience↗

bioRxiv2020

The development of a novel diagnostic PCR for Madurella mycetomatis using a comparative genome approach

Eumycetoma is a neglected tropical disease characterized by large tumorous lesions. It is most commonly caused by the fungus Madurella mycetomatis which accounts for more than 70% of cases in central Africa. Currently, identification of the causative agent can only be reliably performed by a species-specific PCR. However, we recently demonstrated that our M. mycetomatis specific PCR can cross-react with Madurella pseudomycetomatis. We therefore used a comparative genome approach to develop a new M. mycetomatis specific PCR for species identification. For this we compared the published M. mycetomatis genome to genomes of other organisms in BLASTCLUST to identify unique M. mycetomatis predicted protein coding sequences. Based on 16 of these unique sequences, PCR primers were developed. The specificity of these primers was further evaluated in other eumycetoma causing agents including the Madurella sibling species. Out of the 16 tested sequences, only one was unique for M. mycetomatis and this should be used as a novel diagnostic marker for M. mycetomatis.

microbiology↗

bioRxiv2020

Effect of Diverse Recoding of Granule Cells on Optokinetic Response in A Cerebellar Ring Network with Synaptic Plasticity

We consider a cerebellar ring network for the optokinetic response (OKR), and investigate the effect of diverse recoding of granule (GR) cells on OKR by varybing the connection probability pc from Golgi to GR cells. For an optimal value of [Formula], individual GR cells exhibit diverse spiking patterns which are in-phase, anti-phase, or complex out-of-phase with respect to their population-averaged firing activity. Then, these diversely-recoded signals via parallel fibers (PFs) from GR cells are effectively depressed by the error-teaching signals via climbing fibers from the inferior olive which are also in-phase ones. Synaptic weights at in-phase PF-Purkinje cell (PC) synapses of active GR cells are strongly depressed via strong long-term depression (LTD), while those at anti-phase and complex out-of-phase PF-PC synapses are weakly depressed through weak LTD. This kind of "effective" depression (i.e., strong/weak LTD) at the PF-PC synapses causes a big modulation in firings of PCs, which then exert effective inhibitory coordination on the vestibular nucleus (VN) neuron (which evokes OKR). For the firing of the VN neuron, the learning gain degree [L]g, corresponding to the modulation gain ratio, increases with increasing the learning cycle, and it saturates at about the 300th cycle. By varying pc from [Formula], we find that a plot of saturated learning gain degree [Formula] versus pc forms a bell-shaped curve with a peak at [Formula] (where the diversity degree in spiking patterns of GR cells is also maximum). Consequently, the more diverse in recoding of GR cells, the more effective in motor learning for the OKR adaptation.

neuroscience↗

bioRxiv2019

Site-specific effects of online rTMS during a working memory task in healthy older adults.

The process of manipulating information within working memory (WM) is central to many cognitive functions, but also declines rapidly in old age. Given the importance of WM manipulation for maintaining healthy cognition, improving this process could markedly enhance health-span in older adults. The current pre-registered study tested the potential of online repetitive transcranial magnetic stimulation (rTMS) to enhance WM manipulation in healthy elderly adults. Online 5Hz rTMS was applied over the left lateral parietal cortex of 15 subjects to test the hypothesis that active rTMS would significantly improve performance compared to sham stimulation, and that these effects would be most pronounced in conditions with the highest cognitive demand. rTMS was applied while participants performed a delayed-response alphabetization task with two individually-titrated levels of difficulty. Sham stimulation was applied using an electrical sham coil that produced similar clicking sounds and somatosensory sensation as active stimulation but induced negligible effects on the brain. A stimulation site in left lateral parietal cortex was identified from fMRI activation maps and was targeted using individualized electric field modeling, stereotactic neuronavigation, and real-time robotic positioning, allowing optimal coil placement during the stimulation. Contrary to the a priori hypothesis, active rTMS significantly decreased accuracy relative to sham, and only in the hardest difficulty level. These results, therefore, demonstrate engagement of cortical WM processing, but not the anticipated facilitation, and provide a prescription for future studies that may attempt to enhance memory through application of different stimulation parameters.\n\nHighlightsO_LIThis study is one of the first attempts to enhance WM manipulation with online rTMS\nC_LIO_LIOnline 5Hz rTMS and sham were applied over the left parietal cortex of older adults\nC_LIO_LIIndividualized fMRI and electric field modeling were used to optimize targeting\nC_LIO_LIContrary to expectations, rTMS disrupted working memory manipulation abilities\nC_LIO_LIThis demonstrates that parietal cortex is involved in WM and modifiable with rTMS\nC_LI

neuroscience↗

bioRxiv2019

Effect of Interpopulation Spike-Timing-Dependent Plasticity on Synchronized Rhythms in Neuronal Networks with Inhibitory and Excitatory Populations

We consider a two-population network consisting of both inhibitory (I) interneurons and excitatory (E) pyramidal cells. This I-E neuronal network has adaptive dynamic I to E and E to I interpopulation synaptic strengths, governed by interpopulation spike-timing-dependent plasticity (STDP). In previous works without STDPs, fast sparsely synchronized rhythms, related to diverse cognitive functions, were found to appear in a range of noise intensity D for static synaptic strengths. Here, by varying D, we investigate the effect of interpopulation STDPs on fast sparsely synchronized rhythms that emerge in both the I- and the E-populations. Depending on values of D, long-term potentiation (LTP) and long-term depression (LTD) for population-averaged values of saturated interpopulation synaptic strengths are found to occur. Then, the degree of fast sparse synchronization varies due to effects of LTP and LTD. In a broad region of intermediate D, the degree of good synchronization (with higher synchronization degree) becomes decreased, while in a region of large D, the degree of bad synchronization (with lower synchronization degree) gets increased. Consequently, in each I- or E-population, the synchronization degree becomes nearly the same in a wide range of D (including both the intermediate and the large D regions). This kind of "equalization effect" is found to occur via cooperative interplay between the average occupation and pacing degrees of spikes (i.e., the average fraction of firing neurons and the average degree of phase coherence between spikes in each synchronized stripe of spikes in the raster plot of spikes) in fast sparsely synchronized rhythms. Finally, emergences of LTP and LTD of interpopulation synaptic strengths (leading to occurrence of equalization effect) are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic spike times. PACS numbers87.19.lw, 87.19.lm, 87.19.lc

neuroscience↗

bioRxiv2018

Cluster Burst Synchronization in A Scale-Free Network of Inhibitory Bursting Neurons

We consider a scale-free network of inhibitory Hindmarsh-Rose (HR) bursting neurons, and investigate coupling-induced burst synchronization by varying the average coupling strength J0. When passing a lower threshold [Formula], a transition from desynchronization to 3-cluster burst synchronization occurs due to a constructive role of inhibition to favor the cluster burst synchronization. For this case, the whole population is segregated into 3 clusters, and HR neurons in each cluster exhibit burst synchronization. However, as J0 is increased and passes an intermediate threshold [Formula], HR neurons begin to make intermittent hoppings between the 3 clusters. Due to the intermittent intercluster hoppings, the 3 clusters are integrated into a single one. In spite of break-up of the 3 clusters, burst synchronization persists in the whole population, which is well visualized in the raster plot of burst onset times where bursting stripes (composed of burst onset times and indicating burst synchronization) appear successively. With further increase in J0, intercluster hoppings are intensified, and bursting stripes also become smeared more and more due to a destructive role of inhibition to spoil the burst synchronization. Eventually, when passing a higher threshold [Formula] a transition to desynchronization occurs via complete overlap between the bursting stripes. Finally, we also investigate the effects of stochastic noise on both 3-cluster burst synchronization and intercluster hoppings.\n\nPACS numbers: 87.19.lm, 87.19.lc

neuroscience↗

bioRxiv2018

Complementary topology of maintenance and manipulation brain networks in working memory

Working memory (WM) is assumed to consist of a process that sustains memory representations in an active state (maintenance) and a process that operates on these activated representations (manipulation). Prior fMRI studies have examined maintenance and manipulation in separate task conditions, whereas in real life these processes operate simultaneously. In the current study, the neural mechanisms of maintenance and manipulation were disentangled during the same task by parametrically varying these processes. During fMRI, participants maintained consonant letters in WM while sorting them in alphabetical order. Maintenance was investigated by varying the number of letters held in WM and manipulation by varying the number of moves required to sort the list alphabetically. The study yielded three main findings. First, the degree of both maintenance and manipulation demand had significant effects on behavior that were associated with different cortical regions: maintenance was associated with bilateral prefrontal and left parietal cortex, and manipulation with right parietal activity, a link that is consistent with the role of parietal cortex in symbolic computations. Second, univariate fMRI and tractography based on diffusion-weighted imaging showed that maintenance and manipulation regions are supported by two dissociable structural networks. Finally, maintenance and manipulation functional networks became increasingly segregated with increasing demand, possibly reflecting the protection of information held in WM from interference generated by manipulation operations. These results represent a novel approach to study the brain as an adaptive system that coordinates multiple ongoing cognitive processes.\n\nSignificance StatementDespite the importance of working memory (WM) in everyday life, little is known about how the brain is able to simultaneously maintain and manipulate information stored in short-term memory buffers. We examined evidence for two distinct, concurrent cognitive functions supporting maintenance and manipulation abilities by testing brain activity as participants performed a WM alphabetization task. We found behavioral and neural evidence in support of dissociable cognitive functions associated with these two operations. Furthermore, we found that connectivity between these networks was increasingly segregated as difficulty increased, and that this effect was positively related to individual WM ability. These results provide evidence that network segregation may act as a protective mechanism to enable successful performance under increasing WM demand.

neuroscience↗

bioRxiv2018

Effect of Inhibitory Spike-Timing-Dependent Plasticity on Fast Sparsely Synchronized Rhythms in A Small-World Neuronal Network

We consider the Watts-Strogatz small-world network (SWN) consisting of inhibitory fast spiking Izhikevich interneurons. This inhibitory neuronal population has adaptive dynamic synaptic strengths governed by the inhibitory spike-timing-dependent plasticity (iSTDP). In previous works without iSTDP, fast sparsely synchronized rhythms, associated with diverse cognitive functions, were found to appear in a range of large noise intensities for fixed strong synaptic inhibition strengths. Here, we investigate the effect of iSTDP on fast sparse synchronization (FSS) by varying the noise intensity D. We employ an asymmetric anti-Hebbian time window for the iSTDP update rule [which is in contrast to the Hebbian time window for the excitatory STDP (eSTDP)]. Depending on values of D, population-averaged values of saturated synaptic inhibition strengths are potentiated [long-term potentiation (LTP)] or depressed [long-term depression (LTD)] in comparison with the initial mean value, and dispersions from the mean values of LTP/LTD are much increased when compared with the initial dispersion, independently of D. In most cases of LTD where the effect of mean LTD is dominant in comparison with the effect of dispersion, good synchronization (with higher spiking measure) is found to get better via LTD, while bad synchronization (with lower spiking measure) is found to get worse via LTP. This kind of Matthew effect in inhibitory synaptic plasticity is in contrast to that in excitatory synaptic plasticity where good (bad) synchronization gets better (worse) via LTP (LTD). Emergences of LTD and LTP of synaptic inhibition strengths are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic spike times. Furthermore, we also investigate the effects of network architecture on FSS by changing the rewiring probability p of the SWN in the presence of iSTDP.

neuroscience↗

bioRxiv2018

Burst Synchronization in A Scale-Free Neuronal Network with Inhibitory Spike-Timing-Dependent Plasticity

We are concerned about burst synchronization (BS), related to neural information processes in health and disease, in the Barabasi-Albert scale-free network (SFN) composed of inhibitory bursting Hindmarsh-Rose neurons. This inhibitory neuronal population has adaptive dynamic synaptic strengths governed by the inhibitory spike-timing-dependent plasticity (iSTDP). In previous works without considering iSTDP, BS was found to appear in a range of noise intensities for fixed synaptic inhibition strengths. In contrast, in our present work, we take into consideration iSTDP and investigate its effect on BS by varying the noise intensity. Our new main result is to find occurrence of a Matthew effect in inhibitory synaptic plasticity: good BS gets better via LTD, while bad BS get worse via LTP. This kind of Matthew effect in inhibitory synaptic plasticity is in contrast to that in excitatory synaptic plasticity where good (bad) synchronization gets better (worse) via LTP (LTD). We note that, due to inhibition, the roles of LTD and LTP in inhibitory synaptic plasticity are reversed in comparison with those in excitatory synaptic plasticity. Moreover, emergences of LTD and LTP of synaptic inhibition strengths are intensively investigated via a microscopic method based on the distributions of time delays between the preand the post-synaptic burst onset times. Finally, in the presence of iSTDP we investigate the effects of network architecture on BS by varying the symmetric attachment degree l* and the asymmetry parameter {Delta}l in the SFN.

neuroscience↗

bioRxiv2018

A systematic study of repetitive transcranial magnetic stimulation to enhance working memory manipulation abilities

A core element of human working memory (WM) is the ability to perform mental operations on information that is stored in a flexible, limited capacity buffer. Given the profound importance of such WM manipulation (WM-M) abilities, there is a concerted effort aimed at developing approaches to improve them. Past research has identified neural substrates of WM-M centered in the dorsolateral prefrontal cortex (DLPFC), thereby providing a plausible and accessible target for noninvasive neuromodulatory stimulation that can be used to alter cortical excitability and potentially lead to facilitation of WM-M. In the current study, 5Hz online repetitive transcranial magnetic stimulation (rTMS), applied over the left DLPFC, was used to test the hypothesis that active rTMS would lead to significant improvements in memory recall accuracy compared to sham stimulation, and that these effects would be most pronounced in the WM-M conditions with the highest cognitive demand (registered Clinical Trial: #NCT02767323). Participants performed a delayed response alphabetization task with three individually-titrated levels of difficulty during active and sham rTMS. Analyses revealed that active rTMS led to numerically greater accuracy relative to sham stimulation for the hardest condition; however, this effect did not survive Bonferroni correction over all task conditions. Despite the lack of robust, study-wise significant effects, when considered in isolation, the magnitude of behavioral improvement in the hardest condition was negatively correlated with parametric difficulty-related fMRI activity in the targeted brain region, suggesting that individuals with less activation benefit more from rTMS. The present findings therefore suggest evidence towards the hypothesis that active rTMS can enhance performance during difficult memory manipulation conditions; however, firm conclusions cannot be drawn given the lack of overall significant effects. These findings are discussed in the context of individualized targeting and other factors that might moderate rTMS effects.

neuroscience↗

bioRxiv2018

Addressing the Most Neglected Diseases through an Open Research Model: the Discovery of Fenarimols as Novel Drug Candidates for Eumycetoma

Eumycetoma is a chronic infectious disease characterized by a large subcutaneous mass, often caused by the fungus Madurella mycetomatis. A combination of surgery and prolonged medication is needed to treat this infection with a success rate of only 30%. There is, therefore, an urgent need to find more effective drugs for the treatment of this disease. In this study, we screened 800 diverse drug-like molecules and identified 215 molecules that were active in vitro. Minimal inhibitory concentrations were determined for the 13 most active compounds. One of the most potent compounds, a fenarimol analogue for which a large analogue library is available, led to the screening of an additional 35 compounds for their in vitro activity against M. mycetomatis hyphae, rendering four further hit compounds. To assess the in vivo potency of these hit compounds, a Galleria mellonella larvae model infected with M. mycetomatis was used. Several of the compounds identified in vitro demonstrated promising efficacy in vivo in terms of prolonged larval survival and/or reduced fungal burden. The results presented in this paper are the starting point of an Open Source Mycetoma (MycetOS) approach in which members of the global scientific community are invited to participate and contribute as equal partners. We hope that this initiative, coupled with the promising new hits we have reported, will lead to progress in drug discovery for this most neglected of neglected tropical diseases.\n\nAuthor summaryMycetoma is a poverty-associated disease that was recently recognised as a neglected tropical disease by the World Health Organisation (WHO). This disease can be caused by either bacteria (actinomycetoma) or fungi (eumycetoma). The most common causative agent of mycetoma is the fungus Madurella mycetomatis. Actinomycetoma can be easily treated, but for eumycetoma, the current and only antifungal drug used is only able to successfully treat 30% of patients. Treatment often involves prolonged medication use and amputation of the affected area. This disease is disfiguring and is a social stigma for patients in endemic countries. To improve treatment for patients, we have looked at over 800 diverse drug-like molecules and compounds in hope to develop new drugs in this study. We have identified 215 compounds with activity against M. mycetomatis in vitro and several in vivo with our Galleria mellonella larvae model. We have chosen an open source approach with this study and placed our findings in an online database and made it available to the public. We invite the global scientific community to participate in our study and contribute as equal partners as long as an open source approach is held in hopes to fast track and boost drug discovery for Eumycetoma.

pharmacology and toxicology↗