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Abstract The placebo response is a common phenomenon. Limited evidence is available about its magnitude in canine epilepsy trials, even though it can significantly influence the efficacy evaluation of new treatments. It was hypothesised that the placebo response is diminished when epilepsy trials are conducted in a prospective crossover design. Seizure data spanning six months from three previous multicenter epilepsy studies were analysed. The monthly seizure frequency of 60 dogs diagnosed with idiopathic epilepsy was calculated, comparing baseline data with placebo treatment. Furthermore, differentiation was made between dogs randomised to the placebo group early (Phase 1: first 3 months) or later during the study (Phase 2: second 3 months). The analysis did not reveal any placebo response in terms of monthly seizure frequency. Instead, an increase was noted during the placebo treatment period, with a mean of 2.95 seizures per month compared to 2.30 seizures per month before study entry (p = 0.0378). Additionally, a notable phase effect was observed. Dogs receiving the placebo in the second study phase exhibited a significant increase in monthly seizure frequency compared to baseline (p = 0.0036). Conversely, no significant difference from baseline was observed for dogs receiving the placebo in the first study phase. These findings underscore the considerable variability in placebo responses observed in trials for canine epilepsy, contrasting with previous limited data. The identified phase effect should be carefully considered in the design and evaluation of canine epilepsy trials to ensure a more accurate assessment of efficacy for new treatments.

BackgroundCanine cognitive dysfunction (CCD) is a common, yet underdiagnosed neurodegenerative disease affecting older dogs. Treatment is most effective when started early, so identifying mild cognitive decline in the earlier stages of the disease is considered important.Hypothesis/objectiveTo compare the results of three different standard screening questionnaires [Canine Dementia Scale (CADES), Canine Cognitive Assessment Scale (CCAS), and Canine Cognitive Dysfunction Rating Scale (CCDR)] for CCD diagnosis. Trainability, pain sensitivity, and fear were additionally assessed with the Canine Behavioral Assessment and Research Questionnaire (C-BARQ) in order to evaluate associations between the three dementia scales and behavior.MethodsAn online survey containing all the mentioned questionnaires was designed for and distributed among owners of elderly dogs.ResultsData from 597 dogs were analyzed. Overall, the scores of the three CCD questionnaires correlated well with each other, especially those of the CADES and CCAS. The CADES was more sensitive in identifying dogs with already mild to moderate cognitive impairment, while the others classified them as still undergoing normal aging. CCD scores increased for all questionnaires with age with spatial orientation being a key feature in CCD development. Trainability assessed with the C-BARQ decreased significantly with severity of CCD signs, while pain sensitivity increased. Fear and anxiety was pronounced in animals with mild but not with severe CCD. These associations based on the C-BARQ were more clearly observable in relation to CADES and CCDR than CCAS.Conclusion/clinical relevanceThe choice of screening questionnaire impacts the evaluation of cognitive status and severity of CCD. Thresholds for severity classification differ significantly and may have an impact on reliable assessment. Further longitudinal studies are required to determine which of the questionnaires investigated in this study is best suited for early detection of CCD.

Abstract Manual tools for pain assessment from facial expressions have been suggested and validated for several animal species. However, facial expression analysis performed by humans is prone to subjectivity and bias, and in many cases also requires special expertise and training. This has led to an increasing body of work on automated pain recognition, which has been addressed for several species, including cats. Even for experts, cats are a notoriously challenging species for pain assessment. A previous study compared two approaches to automated ‘pain’/‘no pain’ classification from cat facial images: a deep learning approach, and an approach based on manually annotated geometric landmarks, reaching comparable accuracy results. However, the study included a very homogeneous dataset of cats and thus further research to study generalizability of pain recognition to more realistic settings is required. This study addresses the question of whether AI models can classify ‘pain’/‘no pain’ in cats in a more realistic (multi-breed, multi-sex) setting using a more heterogeneous and thus potentially ‘noisy’ dataset of 84 client-owned cats. Cats were a convenience sample presented to the Department of Small Animal Medicine and Surgery of the University of Veterinary Medicine Hannover and included individuals of different breeds, ages, sex, and with varying medical conditions/medical histories. Cats were scored by veterinary experts using the Glasgow composite measure pain scale in combination with the well-documented and comprehensive clinical history of those patients; the scoring was then used for training AI models using two different approaches. We show that in this context the landmark-based approach performs better, reaching accuracy above 77% in pain detection as opposed to only above 65% reached by the deep learning approach. Furthermore, we investigated the explainability of such machine recognition in terms of identifying facial features that are important for the machine, revealing that the region of nose and mouth seems more important for machine pain classification, while the region of ears is less important, with these findings being consistent across the models and techniques studied here.

Abstract Background Epilepsy is the most common chronic neurological disease in dogs. More than two-thirds of these patients suffer from associated behavioural comorbidities. The latter could have their origin in partially overlapping pathomechanisms, with the intestinal microbiome as a potential key link between them. The current arsenal of drugs for epilepsy management remains limited. Most canine patients continue to have seizures despite treatment and the occurrence of comorbidities is not sufficiently addressed, limiting quality of life of affected dogs and owners. Therefore, novel additional epilepsy management options are urgently needed. The microbiome-gut-brain axis may serve as a new target for the development of innovative multimodal therapeutic approaches to overcome current shortcomings in epilepsy management. Methods A six-month prospective, randomised, double-blinded, placebo-controlled, crossover, dietary trial was designed to investigate the potential of the psychobiotic Bifidobacterium longum on behavioural comorbidities in canine epilepsy. Seizure semiology will be evaluated as a secondary outcome measure. Thirty-four privately owned dogs are planned to be included in the ongoing study meeting the following inclusion criteria: Dogs displaying increased anxiety/fear behaviour since the start of the idiopathic epilepsy. Tier II confidence level of the International Veterinary Epilepsy Task Force for the diagnosis of idiopathic epilepsy, with a maximum seizure interval of 3 month and a minimum of three generalised seizures within that period and chronically treated with at least one antiseizure drug without improvement in seizure frequency Each dog will receive the allocated supplement (probiotic vs. placebo) alongside its normal diet for a 3-month period. After a three-week wash out period, the second phase starts by administering the respective other supplement for another 3 months. Discussion The current study considers modern high-quality standards for epilepsy medication trials. Common biasing effects should be limited to a possible minimum (regression-to-the mean effect, placebo effect, observer effect), ensuring a high validity and accuracy of the acquired results, thus enabling a representative nature of the efficacy of Bifidobacterium longum as add-on supplement for dogs suffering from epilepsy and its comorbidities. This publication should provide a description of the study procedure and data acquisition methods, including prognosed statistical analysis.

The clinical sign of ataxia is related to several neurological diseases and is seen in conjunction with paresis in dogs with spinal cord injury (SCI). Endeavours to objectify canine spinal ataxia in SCI remain limited. The aim of this clinical study was to determine and quantify differences between gait characteristics of ataxic dogs with thoracolumbar myelopathy and healthy control dogs using a computer-and treadmill-based gait analysis system. Five dogs with spinal ataxia and six healthy dogs underwent video-and computer-assisted gait analysis while walking on a four-ground reaction force plate treadmill system (maximum speed of 0.7 m/s). Spatio-temporal and kinetic gait characteristics regarding the dogs’ locomotion were analysed with a focus on the individual coefficient of variation (CV), as a potential measure for quantification of the level of ataxia. Ataxic dogs with thoracolumbar SCI showed no effect on symmetry indices but higher variability in spatio-temporal and kinetic gait parameters mainly in the pelvic, but also in the thoracic limbs. Double support phase of the individual limb was prolonged in SCI dogs at the cost of the single support and swing phase. Reduced peaks of ground reaction forces (GRF) could potentially be explained by reduction of muscle strength, as a strategy of avoiding falling by taking enthusiastic steps, or by alteration of the rhythmogenic spinal circuits between the pelvic and thoracic limb pattern generators.

Abstract Background Nausea and emesis can be, among other signs, common manifestations of acute vestibular system dysfunction in dogs. Currently, antiemetic drugs, such as maropitant and metoclopramide, are used commonly, but do not appear to control nausea. A non‐placebo‐controlled preliminary study suggested good efficacy of 5‐HT3‐receptor antagonists, such as ondansetron, against nausea in dogs with vestibular syndrome. Objectives To assess and confirm the effect of ondansetron on behavior suggestive of nausea in dogs with vestibular syndrome. Animals Fourteen dogs with vestibular syndrome and clinical signs of nausea presented to a neurology service. Methods Placebo‐controlled, double‐blinded, crossover study. Behavioral assessment was performed hourly for 4 hours using an established numerical rating scale. The criteria salivation, lip licking, vocalization, restlessness, lethargy, and general nausea were scored. The occurrence of emesis was recorded. After scoring at T0 (pre‐dose) and T2 (2 hours post‐dose) either ondansetron (0.5 mg/kg) or placebo was injected IV. Two hours post‐dose, treatments were switched. Blood samples were collected to measure serum arginine vasopressin (AVP) concentration, which previously has been shown to correlate with clinical signs of nausea. Results Clinical resolution of nausea was observed 1 hour after administration of ondansetron, whereas serum AVP concentration decreased 4 hours after ondansetron administration. Conclusion and Clinical Importance Administration of ondansetron IV is beneficial for dogs with nausea secondary to acute vestibular syndrome. Ondansetron substantially and rapidly decreased clinical signs of nausea behavior and stopped emesis.

Ataxia is a clinical sign seen in several neurological diseases and has been reported as an adverse effect of anti-seizure medication such as phenobarbital (PB). Efforts to objectify canine ataxia in order to provide appropriate treatment or monitor adverse effects of drugs remain limited. Automated quantitative gait analysis can be useful for the acquisition of objective data for the evaluation and monitoring of ataxia in dogs. The aim of this prospective clinical study was to examine the gait characteristics of dogs with PB induced ataxia and compare them with healthy dogs using a computer- and treadmill-based gait analysis system. Six healthy dogs and five dogs with idiopathic epilepsy (IE) with PB-induced ataxia underwent video- and computer-assisted gait analysis during slow walking (maximum speed of 0.7 m/s) on a treadmill with four ground reaction force plates (one plate per limb). Kinetic and spatio-temporal gait parameters of dogs’ locomotion were analyzed, including individually calculated coefficients of variation. Dogs with IE treated with PB showed higher variability in spatio-temporal but not in kinetic gait parameters. Double support phase of gait cycles was increased on the cost of single support and swing phases. Body weight standardized ground reaction forces in vertical, craniocaudal, and mediolateral direction were severely affected by ataxia. Compensatory mechanisms in locomotion of dogs with PB-induced ataxia included spatio-temporal and kinetic gait characteristics, most likely in order to compensate imbalance caused by limb incoordination.

Canine cognitive dysfunction (CCD) is becoming increasingly recognized in veterinary medicine, as dogs live longer and with CCD being highly prevalent among the elderly dog population. Various studies have shown that diet and dietary supplementation can positively influence the clinical signs of CCD, especially if given at an early stage. The aim of this study was to investigate owner use of dietary supplements (DSs) in dogs with age-related behavioral changes. An observational study based on an online questionnaire for owners of dogs with age-related behavioral changes was performed. Out of a total of 394 owners who completed the survey, after noticing age-related behavioral changes, over half of the dogs received DSs (54%), whereas only 8% reported changing their dog’s base diet. The most used DS was fish oil (48%). The use of DSs should be discussed with and monitored by veterinary surgeons since many geriatric patients have multi-morbidities, may have specific nutritional requirements and receive multi-faceted medications.

BackgroundOne of the lessons learned from the coronavirus disease 2019 (COVID-19) pandemic is the importance of early, flexible, and rapidly deployable disease detection methods. Currently, diagnosis of COVID-19 requires the collection of oro/nasopharyngal swabs, nasal turbinate, anterior nares and saliva but as the pandemic continues, disease detection methods that can identify infected individuals earlier and more quickly will be crucial for slowing the spread of the virus. Previous studies have indicated that dogs can be trained to identify volatile organic compounds (VOCs) produced during respiratory infections. We sought to determine whether this approach could be applied for detection of COVID-19 in Rwanda and measured its cost-saving.MethodsOver a period of 5 months, four dogs were trained to detect VOCs in sweat samples collected from human subjects confirmed positive or negative for COVID-19 by reverse transcription polymerase chain reaction (RT-PCR) testing. Dogs were trained using a detection dog training system (DDTS) and in vivo diagnosis. Samples were collected from 5,253 participants using a cotton pad swiped in the underarm to collect sweat samples. Statistical analysis was conducted using R statistical software.FindingsFrom August to September 2021 during the Delta wave, the sensitivity of the dogs’ COVID-19 detection ranged from 75.0 to 89.9% for the lowest- and highest-performing dogs, respectively. Specificity ranged from 96.1 to 98.4%, respectively. In the second phase coinciding with the Omicron wave (January–March 2022), the sensitivity decreased substantially from 36.6 to 41.5%, while specificity remained above 95% for all four dogs. The sensitivity and specificity by any positive sample detected by at least one dog was 83.9, 95% CI: 75.8–90.2 and 94.9%; 95% CI: 93.9–95.8, respectively. The use of scent detection dogs was also found to be cost-saving compared to antigen rapid diagnostic tests, based on a marginal cost of approximately $14,000 USD for testing of the 5,253 samples which makes 2.67 USD per sample. Testing turnaround time was also faster with the scent detection dogs, at 3 h compared to 11 h with routine diagnostic testing.ConclusionThe findings from this study indicate that trained dogs can accurately identify respiratory secretion samples from asymptomatic and symptomatic COVID-19 patients timely and cost-effectively. Our findings recommend further uptake of this approach for COVID-19 detection.

Introduction Previous research demonstrated that medical scent detection dogs have the ability to distinguish SARS-CoV-2 positive from negative samples with high diagnostic accuracy. To deploy these dogs as a reliable screening method, it is mandatory to examine if canines maintain their high diagnostic accuracy in real-life screening settings. We conducted a study to evaluate the performance of medical scent detection dogs under real-life circumstances.Methods Eight dogs were trained to detect SARS-CoV-2 RT-qPCR-positive samples. Four concerts with a total of 2802 participants were held to evaluate canines’ performance in screening individuals for SARS-CoV-2 infection. Sweat samples were taken from all participants and presented in a line-up setting. In addition, every participant had been tested with a SARS-CoV-2 specific rapid antigen test and a RT-qPCR and they provided information regarding age, sex, vaccination status and medical disease history. The participants’ infection status was unknown at the time of canine testing. Safety measures such as mask wearing and distance keeping were ensured.Results The SARS-CoV-2 detection dogs achieved a diagnostic specificity of 99.93% (95% CI 99.74% to 99.99%) and a sensitivity of 81.58% (95% CI 66.58% to 90.78%), respectively. The overall rate of concordant results was 99.68%. The majority of the study population was vaccinated with varying vaccines and vaccination schemes, while several participants had chronic diseases and were under chronic medication. This did not influence dogs’ decisions.Conclusion Our results demonstrate that SARS-CoV-2 scent detection dogs achieved high diagnostic accuracy in a real-life scenario. The vaccination status, previous SARS-CoV-2 infection, chronic disease and medication of the participants did not influence the performance of the dogs in detecting the acute infection. This indicates that dogs provide a fast and reliable screening option for public events in which high-throughput screening is required.

Abstract The extraordinary olfactory sense of canines combined with the possibility to learn by operant conditioning enables dogs for their use in medical detection in a wide range of applications. Research on the ability of medical detection dogs for the identification of individuals with infectious or non-infectious diseases has been promising, but compared to the well-established and–accepted use of sniffer dogs by the police, army and customs for substances such as money, explosives or drugs, the deployment of medical detection dogs is still in its infancy. There are several factors to be considered for standardisation prior to deployment of canine scent detection dogs. Individual odours in disease consist of different volatile organic molecules that differ in magnitude, volatility and concentration. Olfaction can be influenced by various parameters like genetics, environmental conditions, age, hydration, nutrition, microbiome, conditioning, training, management factors, diseases and pharmaceuticals. This review discusses current knowledge on the function and importance of canines’ olfaction and evaluates its limitations and the potential role of the dog as a biomedical detector for infectious and non-infectious diseases.

Ataxia is an impairment of the coordination of movement or the interaction of associated muscles, accompanied by a disturbance of the gait pattern. Diagnosis of this clinical sign, and evaluation of its severity is usually done using subjective scales during neurological examination. In this exploratory study we investigated if inertial sensors in a smart phone (3 axes of accelerometer and 3 axes of gyroscope) can be used to detect ataxia. The setting involved inertial sensor data collected by smartphone placed on the dog's back while walking in a straight line. A total of 770 walking sessions were evaluated comparing the gait of 55 healthy dogs to the one of 23 dogs with ataxia. Different machine learning techniques were used with the K-nearest neighbors technique reaching 95% accuracy in discriminating between a healthy control group and ataxic dogs, indicating potential use for smartphone apps for canine ataxia diagnosis and monitoring of treatment effect.

Abstract Background The main strategy to contain the current SARS-CoV-2 pandemic remains to implement a comprehensive testing, tracing and quarantining strategy until vaccination of the population is adequate. Scent dogs could support current testing strategies. Methods Ten dogs were trained for 8 days to detect SARS-CoV-2 infections in beta-propiolactone inactivated saliva samples. The subsequent cognitive transfer performance for the recognition of non-inactivated samples were tested on three different body fluids (saliva, urine, and sweat) in a randomised, double-blind controlled study. Results Dogs were tested on a total of 5242 randomised sample presentations. Dogs detected non-inactivated saliva samples with a diagnostic sensitivity of 84% (95% CI: 62.5–94.44%) and specificity of 95% (95% CI: 93.4–96%). In a subsequent experiment to compare the scent recognition between the three non-inactivated body fluids, diagnostic sensitivity and specificity were 95% (95% CI: 66.67–100%) and 98% (95% CI: 94.87–100%) for urine, 91% (95% CI: 71.43–100%) and 94% (95% CI: 90.91–97.78%) for sweat, 82% (95% CI: 64.29–95.24%), and 96% (95% CI: 94.95–98.9%) for saliva respectively. Conclusions The scent cognitive transfer performance between inactivated and non-inactivated samples as well as between different sample materials indicates that global, specific SARS-CoV-2-associated volatile compounds are released across different body secretions, independently from the patient’s symptoms. All tested body fluids appear to be similarly suited for reliable detection of SARS-CoV-2 infected individuals.

There is a growing number of COVID-19 patients experiencing long-term symptoms months after their acute SARS-CoV-2 infection. Previous research proved dogs' ability to detect acute SARS-CoV-2 infections, but has not yet shown if dogs also indicate samples of patients with post-COVID-19 condition (Long COVID). Nine dogs, previously trained to detect samples of acute COVID-19 patients, were confronted with samples of Long COVID patients in two testing scenarios. In test scenario I (samples of acute COVID-19 vs. Long COVID) dogs achieved a mean sensitivity (for acute COVID-19) of 86.7% (95%CI: 75.4–98.0%) and a specificity of 95.8% (95%CI: 92.5–99.0%). When dogs were confronted with Long COVID and negative control samples in scenario IIa, dogs achieved a mean sensitivity (for Long COVID) of 94.4 (95%CI: 70.5–100.0%) and a specificity of 96.1% (95%CI: 87.6–100.0%). In comparison, when acute SARS-CoV-2 positive samples and negative control samples were comparatively presented (scenario IIb), a mean sensitivity of 86.9 (95%CI: 55.7–100.0%) and a specificity of 88.1% (95%CI: 82.7–93.6%) was attained. This pilot study supports the hypothesis of volatile organic compounds (VOCs) being long-term present after the initial infection in post-COVID-19 patients. Detection dogs, trained with samples of acute COVID-19 patients, also identified samples of Long COVID patients with a high sensitivity when presented next to samples of healthy individuals. This data may be used for further studies evaluating the pathophysiology underlying Long COVID and the composition of specific VOC-patterns released by SARS-CoV-2 infected patients throughout the course of this complex disease.

Abstract Background As the COVID-19 pandemic continues to spread, early, ideally real-time, identification of SARS-CoV-2 infected individuals is pivotal in interrupting infection chains. Volatile organic compounds produced during respiratory infections can cause specific scent imprints, which can be detected by trained dogs with a high rate of precision. Methods Eight detection dogs were trained for 1 week to detect saliva or tracheobronchial secretions of SARS-CoV-2 infected patients in a randomised, double-blinded and controlled study. Results The dogs were able to discriminate between samples of infected (positive) and non-infected (negative) individuals with average diagnostic sensitivity of 82.63% (95% confidence interval [CI]: 82.02–83.24%) and specificity of 96.35% (95% CI: 96.31–96.39%). During the presentation of 1012 randomised samples, the dogs achieved an overall average detection rate of 94% (±3.4%) with 157 correct indications of positive, 792 correct rejections of negative, 33 incorrect indications of negative or incorrect rejections of 30 positive sample presentations. Conclusions These preliminary findings indicate that trained detection dogs can identify respiratory secretion samples from hospitalised and clinically diseased SARS-CoV-2 infected individuals by discriminating between samples from SARS-CoV-2 infected patients and negative controls. This data may form the basis for the reliable screening method of SARS-CoV-2 infected people.

Background: Testing of possibly infected individuals remains cornerstone of containing the spread of SARS-CoV-2. Detection dogs could contribute to mass screening. Previous research demonstrated canines' ability to detect SARS-CoV-2-infections but has not investigated if dogs can differentiate between COVID-19 and other virus infections.Methods: Twelve dogs were trained to detect SARS-CoV-2 positive samples. Three test scenarios were performed to evaluate their ability to discriminate SARS-CoV-2-infections from viral infections of a different aetiology. Naso- and oropharyngeal swab samples from individuals and samples from cell culture both infected with one of 15 viruses that may cause COVID-19-like symptoms were presented as distractors in a randomised, double-blind study. Dogs were either trained with SARS-CoV-2 positive saliva samples (test scenario I and II) or with supernatant from cell cultures (test scenario III).Results: When using swab samples from individuals infected with viruses other than SARS-CoV-2 as distractors (test scenario I), dogs detected swab samples from SARS-CoV-2-infected individuals with a mean diagnostic sensitivity of 73.8% (95% CI: 66.0–81.7%) and a specificity of 95.1% (95% CI: 92.6–97.7%). In test scenario II and III cell culture supernatant from cells infected with SARS-CoV-2, cells infected with other coronaviruses and non-infected cells were presented. Dogs achieved mean diagnostic sensitivities of 61.2% (95% CI: 50.7–71.6%, test scenario II) and 75.8% (95% CI: 53.0–98.5%, test scenario III), respectively. The diagnostic specificities were 90.9% (95% CI: 87.3–94.6%, test scenario II) and 90.2% (95% CI: 81.1–99.4%, test scenario III), respectively.Conclusion: In all three test scenarios the mean specificities were above 90% which indicates that dogs can distinguish SARS-CoV-2-infections from other viral infections. However, compared to earlier studies our scent dogs achieved lower diagnostic sensitivities. To deploy COVID-19 detection dogs as a reliable screening method it is therefore mandatory to include a variety of samples from different viral respiratory tract infections in dog training to ensure a successful discrimination process.

Epileptogenesis, the gradual process that leads to epilepsy after brain injury or genetic mutations, is a complex network phenomenon, involving a variety of morphological, biochemical and functional brain alterations. Although risk factors for developing epilepsy are known, there is currently no treatment available to prevent epilepsy. We recently proposed a multitargeted, network-based approach to prevent epileptogenesis by rationally combining clinically available drugs and provided first proof-of-concept that this strategy is effective. Here we evaluated eight novel rationally chosen combinations of 14 drugs with mechanisms that target different epileptogenic processes. The combinations consisted of 2-4 different drugs per combination and were administered systemically over 5 days during the latent epileptogenic period in the intrahippocampal kainate mouse model of acquired temporal lobe epilepsy, starting 6 h after kainate. Doses and dosing intervals were based on previous pharmacokinetic and tolerability studies in mice. The incidence and frequency of spontaneous electrographic and electroclinical seizures were recorded by continuous (24/7) video linked EEG monitoring done for seven days at 4 and 12 weeks post-kainate, i.e., long after termination of drug treatment. Compared to vehicle controls, the most effective drug combination consisted of low doses of levetiracetam, atorvastatin and ceftriaxone, which markedly reduced the incidence of electrographic seizures (by 60%; p

In addition to tissues such as liver, the plasma membrane sodium-dependent citrate transporter, NaCT (SLC13A5), is highly expressed in brain neurons, but its function is not understood. Loss-of-function mutations in the human SLC13A5 gene have been associated with severe neonatal encephalopathy and pharmacoresistant seizures. The molecular mechanisms of these neurological alterations are not clear. We performed a detailed examination of a Slc13a5 deletion mouse model including video-EEG monitoring, behavioral tests, and electrophysiologic, proteomic, and metabolomic analyses of brain and cerebrospinal fluid. The experiments revealed an increased propensity for epileptic seizures, proepileptogenic neuronal excitability changes in the hippocampus, and significant citrate alterations in the CSF and brain tissue of Slc13a5 deficient mice, which may underlie the neurological abnormalities. These data demonstrate that SLC13A5 is involved in brain citrate regulation and suggest that abnormalities in this regulation can induce seizures. The present study is the first to (i) establish the Slc13a5-knockout mouse model as a helpful tool to study the neuronal functions of NaCT and characterize the molecular mechanisms by which functional deficiency of this citrate transporter causes epilepsy and impairs neuronal function; (ii) evaluate all hypotheses that have previously been suggested on theoretical grounds to explain the neurological phenotype of SLC13A5 mutations; and (iii) indicate that alterations in brain citrate levels result in neuronal network excitability and increased seizure propensity.

Epilepsy is a complex network phenomenon that, as yet, cannot be prevented or cured. We recently proposed network-based approaches to prevent epileptogenesis. For proof of concept we combined two drugs (levetiracetam and topiramate) for which in silico analysis of drug-protein interaction networks indicated a synergistic effect on a large functional network of epilepsy-relevant proteins. Using the intrahippocampal kainate mouse model of temporal lobe epilepsy, the drug combination was administered during the latent period before onset of spontaneous recurrent seizures (SRS). When SRS were periodically recorded by video-EEG monitoring after termination of treatment, a significant decrease in incidence and frequency of SRS was determined, indicating antiepileptogenic efficacy. Such efficacy was not observed following single drug treatment. Furthermore, a combination of levetiracetam and phenobarbital, for which in silico analysis of drug-protein interaction networks did not indicate any significant drug-drug interaction, was not effective to modify development of epilepsy. Surprisingly, the promising antiepileptogenic effect of the levetiracetam/topiramate combination was obtained in the absence of any significant neuroprotective or anti-inflammatory effects as indicated by multimodal brain imaging and histopathology. High throughput RNA-sequencing (RNA-seq) of the ipsilateral hippocampus of mice treated with the levetiracetam/topiramate combination showed that several genes that have been linked previously to epileptogenesis, were significantly differentially expressed, providing interesting entry points for future mechanistic studies. Overall, we have discovered a novel combination treatment with promise for prevention of epilepsy.