Evidence for canine olfactory detection of melanoma

Precision detection of select human lung cancer biomarkers and cell lines using honeybee olfactory neural circuitry as a novel gas sensor

Human breath contains biomarkers (odorants) that can be targeted for early disease detection. It is well known that honeybees have a keen sense of smell and can detect a wide variety of odors at low concentrations. Here, we employ honeybee olfactory neuronal circuitry to classify human lung cancer volatile biomarkers at different concentrations and their mixtures at concentration ranges relevant to biomarkers in human breath from parts-per-billion to parts-per-trillion. We also validated this brain-based sensing technology by detecting human non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) cell lines using the 'smell' of the cell cultures. Different lung cancer biomarkers evoked distinct spiking response dynamics in the honeybee antennal lobe neurons indicating that those neurons encoded biomarker-specific information. By investigating lung cancer biomarker-evoked population neuronal responses from the honeybee antennal lobe, we classified individual human lung cancer biomarkers successfully (88% success rate). When we mixed six lung cancer biomarkers at different concentrations to create 'synthetic lung cancer' vs. 'synthetic healthy' human breath, honeybee population neuronal responses were able to classify those complex breath mixtures reliably with exceedingly high accuracy (93-100% success rate with a leave-one-trial-out classification method). Finally, we employed this sensor to detect human NSCLC and SCLC cell lines and we demonstrated that honeybee brain olfactory neurons could distinguish between lung cancer vs. healthy cell lines and could differentiate between different NSCLC and SCLC cell lines successfully (82% classification success rate). These results indicate that the honeybee olfactory system can be used as a sensitive biological gas sensor to detect human lung cancer.

Can scent-detection dogs detect the stress associated with trauma cue exposure in people with trauma histories? A proof-of-concept study

Introduction

Post-traumatic stress disorder (PTSD) is an impairing mental health condition with high prevalence among military and general populations alike. PTSD service dogs are a complementary and alternative intervention needing scientific validation. We investigated whether dogs can detect putative stress-related volatile organic compounds (VOCs) in the breath of people with trauma histories (54% with PTSD) exposed to personalized trauma cues.

Methods

Breath samples were collected from 26 humans over 40 experimental sessions during a calm (control breath sample) and stressed state induced by trauma cue exposure (target breath sample). Two scent detection canines were presented with the samples in a two alternative forced choice (2AFC) discrimination and yes/no detection task. The 2AFC task assessed the dogs' ability to discriminate between the two states within the breath samples of one individual. The detection task determined their ability to generalize the target odour across different individuals and different stressful events of one individual. Signal Detection Theory was applied to assess dogs' sensitivity, specificity, precision, and response bias.

Results

The dogs performed at ∼90% accuracy across all sample sets in the discrimination experiment, and at 74% and 81% accuracy, respectively, in the detection experiment. Further analysis of dog olfactory performance in relation to human donor self-reported emotional responses to trauma cue exposure suggested the dogs may have been detecting distinct endocrine stress markers. One dog's performance correlated with the human donors' self-reported fear responses and the other dog's performance correlated with the human donors' self-reported shame responses. Based on these correlations between dog performance and donor self-report measures, we speculate that the VOCs each dog was detecting likely originated from the sympathetico-adreno-medullary axis (SAM; adrenaline, noradrenaline) in the case of the first dog and the hypothalamo-pituitary-adrenal axis (HPA; glucocorticoids) in the case of the second dog.

Conclusion

Our proof-of-concept study is the first to demonstrate that some dogs can detect putative VOCs emitted by people with trauma histories when experiencing distress theoretically associated with the intrusion and arousal/reactivity symptoms of PTSD. Results have potential to improve the effectiveness and training protocol of PTSD service dogs with a focus on enhancing their alert function.

Is diagnostic performance of SARS-CoV-2 detection dogs reduced -due to virus variation- over the time?

Medical detection dogs have a high potential for use as alternative diagnostic tools not only for organic diseases, but also for infectious diseases. However, new variants emerging over time may affect the accuracy and sensitivity of diagnostic methods including medical detection dogs in case of viral pandemics. To the best of our knowledge, this is a pioneer study aimed to investigate diagnostic performances and generalization ability of SARS-CoV-2 detection dogs against the new variant after being trained with the original virus. Two SARS-CoV-2 detection dogs were used in this study. In total, 1002 samples including the Omicron variant were introduced to the dogs using a double-blinded design. Two different refresher training sessions were conducted to train the dogs to identify the scent of the Omicron variant. In the first refreshment training, mixed samples (original virus and Omicron variant) were used. The diagnostic performances of the dogs were significantly increased only after the second refreshment training where only the Omicron variant was introduced. This study illustrates that diagnostic performances of SARS-CoV-2 detection dogs were not consistent over time with the emerging new variants. Thus, refreshment training with new variant(s) should be conducted with every new variant which may affect the diagnostic performances of those dogs in such infectious outbreaks.

Harnessing insect olfactory neural circuits for detecting and discriminating human cancers

There is overwhelming evidence that presence of cancer alters cellular metabolic processes, and these changes are manifested in emitted volatile organic compound (VOC) compositions of cancer cells. Here, we take a novel forward engineering approach by developing an insect olfactory neural circuit-based VOC sensor for cancer detection. We obtained oral cancer cell culture VOC-evoked extracellular neural responses from in vivo insect (locust) antennal lobe neurons. We employed biological neural computations of the antennal lobe circuitry for generating spatiotemporal neuronal response templates corresponding to each cell culture VOC mixture, and employed these neuronal templates to distinguish oral cancer cell lines (SAS, Ca9-22, and HSC-3) vs. a non-cancer cell line (HaCaT). Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line. By using high-dimensional population neuronal response analysis and leave-one-trial-out methodology, our approach yielded high classification success for each cell line tested. Our analyses achieved 76-100% success in identifying cell lines by using the population neural response (n = 194) collected for the entire duration of the cell culture study. We also demonstrate this cancer detection technique can distinguish between different types of oral cancers and non-cancer at different time-matched points of growth. This brain-based cancer detection approach is fast as it can differentiate between VOC mixtures within 250 ms of stimulus onset. Our brain-based cancer detection system comprises a novel VOC sensing methodology that incorporates entire biological chemosensory arrays, biological signal transduction, and neuronal computations in a form of a forward-engineered technology for cancer VOC detection.

Ability of animals to detect cancer odors

The olfactory capacity of animals has long been used by humans to help with various activities, e.g., hunting, detecting mines, locating people, and diagnosing diseases. Cancer is among the leading diseases causing death worldwide. Several recent studies have underscored the benefit of using scent to detect cancer, and this paper will review the studies using animals to detect tumor scents. A large variety of animals have been used for this purpose-dogs, rodents, insects, and nematodes-and have shown their capacity to detect cancer, with a success rate close to 90%. Here we discuss these studies, their methodologies, and the animal models used. Finally, we discuss the medical perspectives for cancer diagnosis using odors.

Remote Medical Scent Detection of Cancer and Infectious Diseases With Dogs and Rats: A Systematic Review

BACKGROUND

Remote medical scent detection of cancer and infectious diseases with dogs and rats has been an increasing field of research these last 20 years. If validated, the possibility of implementing such a technique in the clinic raises many hopes. This systematic review was performed to determine the evidence and performance of such methods and assess their potential relevance in the clinic.

METHODS

Pubmed and Web of Science databases were independently searched based on PRISMA standards between 01/01/2000 and 01/05/2021. We included studies aiming at detecting cancers and infectious diseases affecting humans with dogs or rats. We excluded studies using other animals, studies aiming to detect agricultural diseases, diseases affecting animals, and others such as diabetes and neurodegenerative diseases. Only original articles were included. Data about patients' selection, samples, animal characteristics, animal training, testing configurations, and performances were recorded.

RESULTS

A total of 62 studies were included. Sensitivity and specificity varied a lot among studies: While some publications report low sensitivities of 0.17 and specificities around 0.29, others achieve rates of 1 sensitivity and specificity. Only 6 studies were evaluated in a double-blind screening-like situation. In general, the risk of performance bias was high in most evaluated studies, and the quality of the evidence found was low.

CONCLUSIONS

Medical detection using animals' sense of smell lacks evidence and performances so far to be applied in the clinic. What odors the animals detect is not well understood. Further research should be conducted, focusing on patient selection, samples (choice of materials, standardization), and testing conditions. Interpolations of such results to free running detection (direct contact with humans) should be taken with extreme caution. Considering this synthesis, we discuss the challenges and highlight the excellent odor detection threshold exhibited by animals which represents a potential opportunity to develop an accessible and non-invasive method for disease detection.

Use of a habituation-dishabituation test to determine canine olfactory sensitivity

The habituation-dishabituation (H-D) paradigm is an established measure of sensory perception in animals. However, it has rarely been applied to canine olfaction. It proposes that animals will lose interest in, or habituate to, a stimulus after successive exposures but will regain interest in, or dishabituate to, a novel stimulus if they can perceive it. This study assessed an H-D test's practicability to determine dogs' olfactory detection thresholds (ODTs) for a neutral odorant. A random selection of mixed-breed pet dogs (n = 26) participated in two H-D tests in a repeated-measures crossover design. They were first habituated to a carrier odor and then presented with either ascending concentrations of n-amyl acetate in the known ODT range (experimental condition) or repeated carrier odor presentations (control condition). No single odor concentration elicited dishabituation in the majority of the dogs. However, individual dogs dishabituated at differing experimental concentrations significantly more often than in the control condition (p = .012). These findings provide some tentative support for using this method in studying canine olfaction. However, further assessment and refinement are needed before it can be a viable alternative to traditional ODT measurement.

Green Phosphorene as a Promising Biosensor for Detection of Furan and p-Xylene as Biomarkers of Disease: A DFT Study

In this work, Green Phosphorene (GP) monolayers are studied as an electronic sensing element for detecting prostate cancer biomarkers from human urine. The adsorption of furan, C₈H₁₀ (p-xylene), and H₂O on pristine GP and S- and Si-doped GP are investigated using the density functional theory (DFT) calculation. Furan and C₈H₁₀ molecules have been considered as important biomarkers of prostate cancer patients. First-principles DFT calculations are applied, and the results divulged that pristine GP could be a promising candidate for furan and C₈H₁₀ detection. It is manifested that furan and C₈H₁₀ are physisorbed on the S-, and Si-doped GP with small adsorption energy and negligible charge transfer. However, the calculations disclose that furan and C₈H₁₀ are chemically adsorbed on the pristine GP with adsorption energy of −0.73, and −1.46 eV, respectively. Moreover, we observe that a large charge is transferred from furan to the pristine GP with amount of −0.106 e. Additionally, pristine GP shows short recovery time of 1.81 s at room temperature under the visible light, which make it a reusable sensor device. Overall, our findings propose that the pristine GP sensor is a remarkable candidate for sensing of furan and other biomarkers of prostate cancer in the urine of patients.

The Use and Potential of Biomedical Detection Dogs During a Disease Outbreak

Biomedical detection dogs offer incredible advantages during disease outbreaks that are presently unmatched by current technologies, however, dogs still face hurdles of implementation due to lack of inter-governmental cooperation and acceptance by the public health community. Here, we refine the definition of a biomedical detection dog, discuss the potential applications, capabilities, and limitations of biomedical detection dogs in disease outbreak scenarios, and the safety measures that must be considered before and during deployment. Finally, we provide recommendations on how to address and overcome the barriers to acceptance of biomedical detection dogs through a dedicated research and development investment in olfactory sciences.

Identifying SARS-COV-2 infected patients through canine olfactive detection on axillary sweat samples; study of observed sensitivities and specificities within a group of trained dogs

There is an increasing need for rapid, reliable, non-invasive, and inexpensive mass testing methods as the global COVID-19 pandemic continues. Detection dogs could be a possible solution to identify individuals infected with SARS-CoV-2. Previous studies have shown that dogs can detect SARS-CoV-2 on sweat samples. This study aims to establish the dogs’ sensitivity (true positive rate) which measures the proportion of people with COVID-19 that are correctly identified, and specificity (true negative rate) which measures the proportion of people without COVID-19 that are correctly identified. Seven search and rescue dogs were tested using a total of 218 axillary sweat samples (62 positive and 156 negative) in olfaction cones following a randomised and double-blind protocol. Sensitivity ranged from 87% to 94%, and specificity ranged from 78% to 92%, with four dogs over 90%. These results were used to calculate the positive predictive value and negative predictive value for each dog for different infection probabilities (how likely it is for an individual to be SARS-CoV-2 positive), ranging from 10–50%. These results were compared with a reference diagnostic tool which has 95% specificity and sensitivity. Negative predictive values for six dogs ranged from ≥98% at 10% infection probability to ≥88% at 50% infection probability compared with the reference tool which ranged from 99% to 95%. Positive predictive values ranged from ≥40% at 10% infection probability to ≥80% at 50% infection probability compared with the reference tool which ranged from 68% to 95%. This study confirms previous results, suggesting that dogs could play an important role in mass-testing situations. Future challenges include optimal training methods and standardisation for large numbers of detection dogs and infrastructure supporting their deployment.

Volatolomics in healthcare and its advanced detection technology

Various diseases increasingly challenge the health status and life quality of human beings. Volatolome emitted from patients has been considered as a potential family of markers, volatolomics, for diagnosis/screening. There are two fundamental issues of volatolomics in healthcare. On one hand, the solid relationship between the volatolome and specific diseases needs to be clarified and verified. On the other hand, effective methods should be explored for the precise detection of volatolome. Several comprehensive review articles had been published in this field. However, a timely and systematical summary and elaboration is still desired. In this review article, the research methodology of volatolomics in healthcare is critically considered and given out, at first. Then, the sets of volatolome according to specific diseases through different body sources and the analytical instruments for their identifications are systematically summarized. Thirdly, the advanced electronic nose and photonic nose technologies for volatile organic compounds (VOCs) detection are well introduced. The existed obstacles and future perspectives are deeply thought and discussed. This article could give a good guidance to researchers in this interdisciplinary field, not only understanding the cutting-edge detection technologies for doctors (medicinal background), but also making reference to clarify the choice of aimed VOCs during the sensor research for chemists, materials scientists, electronics engineers, etc.

Breast Cancer Detection from a Urine Sample by Dog Sniffing: A Preliminary Study for the Development of a New Screening Device, and a Literature Review

BACKGROUND

Breast cancer is a leading cause of cancer death worldwide. Several studies have demonstrated that dogs can sniff and detect cancer in the breath or urine sample of a patient. This study aims to assess whether the urine sample can be used for breast cancer screening by its fingerprints of volatile organic compounds using a single trained sniffer dog. This is a preliminary study for developing the "electronic nose" for cancer screening.

METHODS

A nine-year-old female Labrador Retriever was trained to identify cancer from urine samples of breast cancer patients. Urine samples from patients histologically diagnosed with primary breast cancer, those with non-breast malignant diseases, and healthy volunteers were obtained, and a double-blind test was performed. Total of 40 patients with breast cancer, 142 patients with non-breast malignant diseases, and 18 healthy volunteers were enrolled, and their urine samples were collected.

RESULTS

In 40 times out of 40 runs of a double-blind test, the trained dog could correctly identify urine samples of breast cancer patients. Sensitivity and specificity of this breast cancer detection method using dog sniffing were both 100%.

CONCLUSIONS

The trained dog in this study could accurately detect breast cancer from urine samples of breast cancer patients. These results indicate the feasibility of a method to detect breast cancer from urine samples using dog sniffing in the diagnosis of breast cancer. Although the methodological standardization is still an issue to be discussed, the current result warrants further study for developing a new breast cancer screening method based on volatile organic compounds in urine samples.

Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose

Rapid diagnosis is key to curtailing the Covid-19 pandemic. One path to such rapid diagnosis may rely on identifying volatile organic compounds (VOCs) emitted by the infected body, or in other words, identifying the smell of the infection. Consistent with this rationale, dogs can use their nose to identify Covid-19 patients. Given the scale of the pandemic, however, animal deployment is a challenging solution. In contrast, electronic noses (eNoses) are machines aimed at mimicking animal olfaction, and these can be deployed at scale. To test the hypothesis that SARS CoV-2 infection is associated with a body-odor detectable by an eNose, we placed a generic eNose in-line at a drive-through testing station. We applied a deep learning classifier to the eNose measurements, and achieved real-time detection of SARS CoV-2 infection at a level significantly better than chance, for both symptomatic and non-symptomatic participants. This proof of concept with a generic eNose implies that an optimized eNose may allow effective real-time diagnosis, which would provide for extensive relief in the Covid-19 pandemic.

Feasibility of integrating canine olfaction with chemical and microbial profiling of urine to detect lethal prostate cancer

Prostate cancer is the second leading cause of cancer death in men in the developed world. A more sensitive and specific detection strategy for lethal prostate cancer beyond serum prostate specific antigen (PSA) population screening is urgently needed. Diagnosis by canine olfaction, using dogs trained to detect cancer by smell, has been shown to be both specific and sensitive. While dogs themselves are impractical as scalable diagnostic sensors, machine olfaction for cancer detection is testable. However, studies bridging the divide between clinical diagnostic techniques, artificial intelligence, and molecular analysis remains difficult due to the significant divide between these disciplines. We tested the clinical feasibility of a cross-disciplinary, integrative approach to early prostate cancer biosensing in urine using trained canine olfaction, volatile organic compound (VOC) analysis by gas chromatography-mass spectroscopy (GC-MS) artificial neural network (ANN)-assisted examination, and microbial profiling in a double-blinded pilot study. Two dogs were trained to detect Gleason 9 prostate cancer in urine collected from biopsy-confirmed patients. Biopsy-negative controls were used to assess canine specificity as prostate cancer biodetectors. Urine samples were simultaneously analyzed for their VOC content in headspace via GC-MS and urinary microbiota content via 16S rDNA Illumina sequencing. In addition, the dogs' diagnoses were used to train an ANN to detect significant peaks in the GC-MS data. The canine olfaction system was 71% sensitive and between 70-76% specific at detecting Gleason 9 prostate cancer. We have also confirmed VOC differences by GC-MS and microbiota differences by 16S rDNA sequencing between cancer positive and biopsy-negative controls. Furthermore, the trained ANN identified regions of interest in the GC-MS data, informed by the canine diagnoses. Methodology and feasibility are established to inform larger-scale studies using canine olfaction, urinary VOCs, and urinary microbiota profiling to develop machine olfaction diagnostic tools. Scalable multi-disciplinary tools may then be compared to PSA screening for earlier, non-invasive, more specific and sensitive detection of clinically aggressive prostate cancers in urine samples.

Nanostructures for Biosensing, with a Brief Overview on Cancer Detection, IoT, and the Role of Machine Learning in Smart Biosensors

Biosensors are essential tools which have been traditionally used to monitor environmental pollution and detect the presence of toxic elements and biohazardous bacteria or virus in organic matter and biomolecules for clinical diagnostics. In the last couple of decades, the scientific community has witnessed their widespread application in the fields of military, health care, industrial process control, environmental monitoring, food-quality control, and microbiology. Biosensor technology has greatly evolved from in vitro studies based on the biosensing ability of organic beings to the highly sophisticated world of nanofabrication-enabled miniaturized biosensors. The incorporation of nanotechnology in the vast field of biosensing has led to the development of novel sensors and sensing mechanisms, as well as an increase in the sensitivity and performance of the existing biosensors. Additionally, the nanoscale dimension further assists the development of sensors for rapid and simple detection in vivo as well as the ability to probe single biomolecules and obtain critical information for their detection and analysis. However, the major drawbacks of this include, but are not limited to, potential toxicities associated with the unavoidable release of nanoparticles into the environment, miniaturization-induced unreliability, lack of automation, and difficulty of integrating the nanostructured-based biosensors, as well as unreliable transduction signals from these devices. Although the field of biosensors is vast, we intend to explore various nanotechnology-enabled biosensors as part of this review article and provide a brief description of their fundamental working principles and potential applications. The article aims to provide the reader a holistic overview of different nanostructures which have been used for biosensing purposes along with some specific applications in the field of cancer detection and the Internet of things (IoT), as well as a brief overview of machine-learning-based biosensing.

Analysis of Tear Fluid for Evaluation on the Concentration of the Generic Anti-Glaucoma Drug Betoptik using Multisensory Stripping Voltammetry and Multivariate Statistics

It is important to monitor the concentration of drugs after their instillation: this helps to find the right drug dosages. The proposed method is based on recognizing multidimensional images through the use of multidimensional statistics; the images are produced by multisensory electrochemical systems that provide reliable information about the tested objects. The measurements were carried out using a planar solid-state electrode. The test-system solution was a 0.05 М KCl solution, which contained the Zn2+, Cd2+, Рb2+, Cu2+ Со2+, and Hg2+ metal cations at the concentration of 5 10–5 M. A new electrochemical method for multisensory stripping voltammetry has been used to determine whether it is appropriate for determination of generic forms of the drug Betoptic, that is, Xonef, Betoftan, and Betalink EU in tear fluid. Measurements were carried out on a planar three-electrode interdigitated electrode. It has been shown that this method is effective for determination of the generics. The dynamics of changes in their concentrations over time were examined. After instillation of the generics in glaucoma patients, their concentrations in the Tear fluid remained unchanged within 12 h. The list of organic substances that can be determined by the method of multisensory stripping voltammetry has been extended.

Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study

The aim of this proof-of-concept study was to evaluate if trained dogs could discriminate between sweat samples from symptomatic COVID-19 positive individuals (SARS-CoV-2 PCR positive) and those from asymptomatic COVID-19 negative individuals. The study was conducted at 2 sites (Paris, France, and Beirut, Lebanon), followed the same training and testing protocols, and involved six detection dogs (three explosive detection dogs, one search and rescue dog, and two colon cancer detection dogs). A total of 177 individuals were recruited for the study (95 symptomatic COVID-19 positive and 82 asymptomatic COVID-19 negative individuals) from five hospitals, and one underarm sweat sample per individual was collected. The dog training sessions lasted between one and three weeks. Once trained, the dog had to mark the COVID-19 positive sample randomly placed behind one of three or four olfactory cones (the other cones contained at least one COVID-19 negative sample and between zero and two mocks). During the testing session, a COVID-19 positive sample could be used up to a maximum of three times for one dog. The dog and its handler were both blinded to the COVID-positive sample location. The success rate per dog (i.e., the number of correct indications divided by the number of trials) ranged from 76% to 100%. The lower bound of the 95% confidence interval of the estimated success rate was most of the time higher than the success rate obtained by chance after removing the number of mocks from calculations. These results provide some evidence that detection dogs may be able to discriminate between sweat samples from symptomatic COVID-19 individuals and those from asymptomatic COVID-19 negative individuals. However, due to the limitations of this proof-of-concept study (including using some COVID-19 samples more than once and potential confounding biases), these results must be confirmed in validation studies.

A review of the efficacy of a low-cost cancer screening test using cancer sniffing canines

One of the most powerful tools in fighting cancer is early detection, as it has been strongly linked to greater chances of cancer survival. However, traditional cancer screening tests can cost hundreds if not thousands of dollars and are therefore not an affordable option for many marginalized populations. From a public health perspective, it is vital to research the use of inexpensive cancer detection so that low-resourced patients have greater access to affordable cancer screening. Numerous studies dating from the early 2000s to recent years have shown extensive evidence that the exceptional olfactory system of canines allows them to detect certain odors through exhaled breath condensate that are known to be biomarkers of a variety of cancers. In addition to providing a cheaper alternative to conventional cancer screening tests, the use of cancer sniffing dogs has other benefits, including great reliability and accuracy. There are a few major types of cancer for which the "cancer dog test" proved to be remarkably effective, particularly colorectal, ovarian, and lung cancers. The test is non-invasive unlike most previous detection methods, meaning that it is also a safer option for individuals seeking cancer screening. Although the use of cancer sniffing dogs does have certain limitations and scope for error, it would provide a more affordable and accessible option for cancer screening, making it especially beneficial to low-resourced populations.

Cancer and mosquitoes - An unsuspected close connection

Cancer is a major public health issue and represents a significant burden in countries with different levels of economic wealth. In parallel, mosquito-borne infectious diseases represent a growing problem causing significant morbidity and mortality worldwide. Acknowledging that these two concerns are both globally distributed, it is essential to investigate whether they have a reciprocal connection that can fuel their respective burdens. Unfortunately, very few studies have examined the link between these two threats. This review provides an overview of the possible links between mosquitoes, mosquito-borne infectious diseases and cancer. We first focus on the impact of mosquitoes on carcinogenesis in humans including the transmission of oncogenic pathogens through mosquitoes, the immune reactions following mosquito bites, the presence of non-oncogenic mosquito-borne pathogens, and the direct transmission of cancer cells. The second part of this review deals with the direct or indirect consequences of cancer in humans on mosquito behaviour. Thirdly, we discuss the potential impacts that natural cancers in mosquitoes can have on their life history traits and therefore on their vector capacity. Finally, we discuss the most promising research avenues on this topic and the integrative public health strategies that could be envisioned in this context.

Analytical Tools for Disease Diagnosis in Animals via Fecal Volatilome

Volatilome analysis is growing in attention for the diagnosis of diseases in animals and humans. In particular, volatilome analysis in fecal samples is starting to be proposed as a fast, easy and noninvasive method for disease diagnosis. Volatilome comprises volatile organic compounds (VOCs), which are produced during both physiological and patho-physiological processes. Thus, VOCs from a pathological condition often differ from those of a healthy state and therefore the VOCs profile can be used in the detection of some diseases. Due to their strengths and advantages, feces are currently being used to obtain information related to health status in animals. However, they are complex samples, that can present problems for some analytical techniques and require special consideration in their use and preparation before analysis. This situation demands an effort to clarify which analytic options are currently being used in the research context to analyze the possibilities these offer, with the final objectives of contributing to develop a standardized methodology and to exploit feces potential as a diagnostic matrix. The current work reviews the studies focused on the diagnosis of animal diseases through fecal volatilome in order to evaluate the analytical methods used and their advantages and limitations. The alternatives found in the literature for sampling, storage, sample pretreatment, measurement and data treatment have been summarized, considering all the steps involved in the analytical process.

A detection dog for obstructive sleep apnea: could it work in diagnostics?

PURPOSE

We have previously demonstrated that dogs can be trained to distinguish the urine of patients with obstructive sleep apnea (OSA) from that of healthy controls based on olfaction. Encouraged by these promising results, we wanted to investigate if a detection dog could work as a screening tool for OSA. The objective of this study was to prospectively assess the dogs' ability to identify sleep apnea in patients with OSA suspicion.

METHODS

Urine samples were collected from 50 patients suspected of having OSA. The urine sample was classified as positive for OSA when the patient had a respiratory event index of 5/h or more. The accuracy of two trained dogs in identifying OSA was tested in a prospective blinded setting.

RESULTS

Both of the dogs correctly detected approximately half of the positive and negative samples. There were no statistically significant differences in the dogs' ability to recognize more severe cases of OSA, as compared to milder cases.

CONCLUSION

According to our study, dogs cannot be used to screen for OSA in clinical settings, most likely due to the heterogenic nature of OSA.

Effect of Handler Knowledge of the Detection Task on Canine Search Behavior and Performance

Detection dogs are commonly trained and tested under conditions in which the handler or the evaluator knows the true presence or absence of a target odor. Previous research has demonstrated that when handlers are deceived and led to believe that a target odor is present, more false alerts occur. However, many detection teams operate under unknown conditions, and it remains unclear how handler knowledge (or lack thereof) of odor presence/absence influences the dog's behavior. The aim of this study was to evaluate if knowing the number of hides placed influenced detection dog performance in an applied search environment. Professional (n = 20) and sport (n = 39) detection handler-dog teams were asked to search three separate areas (area 1 had one hide, area 2 had one hide, area 3 was blank). Handlers in the Unknown Group were not told any information on the number of hides whereas the Known Group were told there was a total of two hides in the three areas. The sport Unknown Group spent a longer duration (69.04 s) searching in area 3 compared to the sport Known Group (p = 0.004). Further, sport dogs in the Unknown group looked back to the handler more frequently. When a miss did occur, dogs of both sport and professional handlers showed an increase interest in the location of the target odor compared to a comparison location. Critically, however, there was no difference in false alerts between the Known Group and Unknown Group for sport or professional handlers. In a second experiment, fourteen professional, and thirty-nine sport teams from Experiment 1 conducted an additional search double-blind and an additional search single-blind. Both sport and professional-handler dog teams had statistically similar accuracy rate under single and double blind conditions. Overall, when handlers knew the number of hides, it led to significant changes in search behavior of the detection team but did not influence the overall false alert rates.

Humanity's Best Friend: A Dog-Centric Approach to Addressing Global Challenges

No other animal has a closer mutualistic relationship with humans than the dog (Canis familiaris). Domesticated from the Eurasian grey wolf (Canis lupus), dogs have evolved alongside humans over millennia in a relationship that has transformed dogs and the environments in which humans and dogs have co-inhabited. The story of the dog is the story of recent humanity, in all its biological and cultural complexity. By exploring human-dog-environment interactions throughout time and space, it is possible not only to understand vital elements of global history, but also to critically assess our present-day relationship with the natural world, and to begin to mitigate future global challenges. In this paper, co-authored by researchers from across the natural and social sciences, arts and humanities, we argue that a dog-centric approach provides a new model for future academic enquiry and engagement with both the public and the global environmental agenda.

Differences in the Search Behavior of Cancer Detection Dogs Trained to Have Either a Sit or Stand-Stare Final Response

Recent literature has demonstrated that dogs have the potential to detect, and communicate the presence of, various human diseases. However, there is a lack of investigation into whether commonplace training differences within the field could influence a dog's behavior during a biomedical detection task. Here we report on the behavior of four dogs trained to alert to blood plasma samples taken from individuals with ovarian cancer. One hundred trials per dog were selected from routine video recordings collected over a period of 13 months. Videos were coded frame by frame to quantify sample checking, alerting behavior, and durations of alert. Dogs had previously been trained to elicit a final response behavior once they had located the target odor. Two dogs had a “sit” response while the other two had a “stand-stare” response. Alert behavior was categorized as true positive (a correct alert to a cancer sample) or false positive (an incorrect alert to biological and non-biological controls and distractors). Hesitations were also recorded, where the dog either checks the sample twice or, spends a longer duration of time sniffing the sample than a true pass without carrying out their final response. Results show individual variation in the total frequency of false alerts elicited. However, the rate of hesitations appears to be influenced by alert style, with stand-stare dogs carrying out 40 and 32, respectively (total = 72) and sit dogs carrying out 7 and 8, respectively (total = 15). The stand-stare dogs had a non-significant difference in the duration of their true and false positive alerts. In contrast, the sit dogs showed a significant difference (p < 0.001), maintaining their false alerts for, on average, two times the duration of their true alerts. Stand-stare dogs increased the duration of time spent in contact with the port when plasma samples were present, whereas sit dogs spent on average 0.3 s in contact with the port regardless of what sample type it contained. These findings suggest that the type of operant response a biomedical detection dog has been trained may influence their sample checking and response behavior.

Two-step investigation of lung cancer detection by sniffer dogs

Early detection of lung cancer (LC) is a priority since LC is characterized by symptoms mimicking other respiratory conditions, but it remains the leading cause of oncological disease death. Properly trained dogs can perceive the volatile organic compounds (VOCs) related to cancer thanks to their acute sense of smell. The use of dogs for LC detection could be advantageous: reliably trained dogs would represent a valuable, cost-effective, non-invasive method of screening, which gives a clear-cut yes/no response. However, whether sniffer dogs are able to maintain their discriminative capacity under long-term control, and in different types of environments, needs further investigation. In this study, we sought to test two hypotheses: firstly, if dogs can be trained to perceive LC-related VOCs in human urine, a substrate which is not influenced by the carrier materials and may thus be a good candidate for large-number screening; and secondly, whether trained dogs retain their performance stability over time, even if the environment in which the tests are carried out varies. We have selected three family dogs that underwent a one-year training period (two weekly training sessions) by the clicker training method. At the end of the training, the dogs underwent two separate test phases, in two different locations, one year apart. All the other procedures had been maintained unchanged. The donors of the samples submitted to the dogs were recruited by the European Institute of Oncology (IEO), Milan, Italy. The results show that the dogs had different sensitivity (range: 45%-73%) and specificity rates (range: 89%-91%), and were deceived neither by lung conditions (that the dogs did not consider) nor by the existence of tumors in the beginning stage, that were correctly reported by the dogs. The one-year interruption of the research work and the changes in the test environment did not induce statistically significant differences in the dogs' perceptive capacity. To our knowledge, so far, these issues have never been highlighted.

Scent-sniffing dogs can discriminate between native Eurasian and invasive North American beavers

The invasion of a species can cause population reduction or extinction of a similar native species due to replacement competition. There is a potential risk that the native Eurasian beaver (Castor fiber) may eventually be competitively excluded by the invasive North American beaver (C. canadensis) from areas where they overlap in Eurasia. Yet currently available methods of census and population estimates are costly and time-consuming. In a laboratory environment, we investigated the potential of using dogs (Canis lupus familiaris) as a conservation tool to determine whether the Eurasian or the North American beaver is present in a specific beaver colony. We hypothesized that dogs can discriminate between the two beaver species, via the odorant signal of castoreum from males and females, in two floor platform experiments. We show that dogs detect scent differences between the two species, both from dead beaver samples and from scent marks collected in the field. Our results suggest that dogs can be used as an “animal biosensor” to discriminate olfactory signals of beaver species, however more tests are needed. Next step should be to test if dogs discern between beaver species in the field under a range of weather conditions and habitat types and use beaver samples collected from areas where the two species share the same habitat. So far, our results show that dogs can be used as a promising tool in the future to promote conservation of the native beaver species and eradication of the invasive one. We therefore conclude that dogs may be an efficient non-invasive tool to help conservationist to manage invasive species in Europe, and advocate for European wildlife agencies to invest in this new tool.

Biosensors to Monitor Water Quality Utilizing Insect Odorant-Binding Proteins as Detector Elements

In the developing world, the identification of clean, potable water continues to pose a pervasive challenge, and waterborne diseases due to fecal contamination of water supplies significantly threaten public health. The ability to efficiently monitor local water supplies is key to water safety, yet no low-cost, reliable method exists to detect contamination quickly. We developed an in vitro assay utilizing an odorant-binding protein (OBP), AgamOBP1, from the mosquito, Anopheles gambiae, to test for the presence of a characteristic metabolite, indole, from harmful coliform bacteria. We demonstrated that recombinantly expressed AgamOBP1 binds indole with high sensitivity. Our proof-of-concept assay is fluorescence-based and demonstrates the usefulness of insect OBPs as detector elements in novel biosensors that rapidly detect the presence of bacterial metabolic markers, and thus of coliform bacteria. We further demonstrated that rAgamOBP1 is suitable for use in portable, inexpensive "dipstick" biosensors that improve upon lateral flow technology since insect OBPs are robust, easily obtainable via recombinant expression, and resist detector "fouling." Moreover, due to their wide diversity and ligand selectivity, insect chemosensory proteins have other biosensor applications for various analytes. The techniques presented here therefore represent platform technologies applicable to various future devices.

Dogs demonstrate the existence of an epileptic seizure odour in humans

Although different studies have shown that diseases such as breast or lung cancer are associated with specific bodily odours, no study has yet tested the possibility that epileptic seizures may be reflected in an olfactory profile, probably because there is a large variety of seizure types. The question is whether a “seizure-odour”, that would be transversal to individuals and types of seizures, exists. This would be a pre requisite for potential anticipation, either by electronic systems (e.g., e-noses) or trained dogs. The aim of the present study therefore was to test whether trained dogs, as demonstrated for cancer or diabetes, may discriminate a general epileptic seizure odor (different from body odours of the same person in other contexts and common to different persons). The results were very clear: all dogs discriminated the seizure odour. The sensitivity and specificity obtained were amongst the highest shown up to now for discrimination of diseases. This constitutes a first proof that, despite the variety of seizures and individual odours, seizures are associated with olfactory characteristics. These results open a large field of research on the odour signature of seizures. Further studies will aim to look at potential applications in terms of anticipation of seizures.

Express Screening of Tear Fluid for Evaluation of the Concentration of Lanomax Using Multisensory Stripping Voltammetry and Multivariate Statistics

The drug concentrations monitoring is very important for finding the right dosage. The developed method is based on the recognition of multidimensional images, which are produced by multisensory electrochemical systems that provide reliable information on objects being tested, using multidimensional statistics. The measurements were carried out using a planar solid-state electrode. The test solution was a 0.05 M KCl solution, which contained the $ {\rm{Z}}{{\rm{n}}_2}^ + ,{\rm{C}}{{\rm{d}}_2}^ + ,{\rm{P}}{{\rm{b}}_2}^ + ,{\rm{C}}{{\rm{o}}_2}^ + $ and $ {\rm{H}}{{\rm{g}}_2}^ + $ metal cations in the concentration of 5 • 10−5 M. The efficiency of this method in determining lanosterol with accounting for changes in its concentration with over time has been demonstrated. In order to determine concentrations of Lanomax in tear fluid, a procedure for multisensory stripping voltammetry has been developed and tested. It has been shown that the effect of lacrimal fluid on metal dissolution currents in the test system lasts 12 hours after the Lanomax instillation.

A detection dog for obstructive sleep apnea

PURPOSE

We sought to assess whether a dog can be trained to distinguish obstructive sleep apnea patients from healthy controls based on the olfactory detection of urine.

METHODS

Urine samples were collected from 23 adult male obstructive sleep apnea patients and from 20 voluntary adult male volunteers. Three dogs were trained through reinforced operant conditioning.

RESULTS

Two of the three dogs correctly detected two thirds of obstructive sleep apnea patients (p < 0.000194 and p < 0.000003, respectively).

CONCLUSIONS

We found that dogs can be trained to distinguish obstructive sleep apnea patients from healthy controls based on the smell of urine. Potentially, dogs could be utilized to identify novel biomarkers or possibly screen for obstructive sleep apnea.

Volatolome of the Female Genitourinary Area: Toward the Metabolome of Cervical Cancer

BACKGROUND AND AIMS

Different Volatile Organic Compounds (VOCs) obtained from several human fluids (volatolome) has been reported as potential biomarkers for a great variety of diseases including cancer. At present, volatolomic profile data of the female genital area is scarce.

METHODS

To identify the VOCs related to the female genitourinary area of healthy and Cervical Cancer (CC)-affected women used a pad, as a non-invasive tool for sample gathering was necessary. Used pads were analyzed by Gas Chromatography-Mass Spectrometry. The data were subjected to Principal Component Analysis looking for a possible spectrum of VOCs that could help identify CC-affected patients. The diagnostic role of the VOCs was validated through Receiver Operating Characteristic (ROC) analysis. The area below the curve and the diagnostic sensitivity and specificity values were also evaluated.

RESULTS

The data showed great differences between female cancer and healthy patients groups; most of these VOCs belonging to the alkanes chemical classes. A group of VOCs were identified as common among CC patients, while others VOCs for healthy females. The ROC curve showed an optimal reach to diagnosis (89%), returning a 93% rate for sensitivity and specificity, indicating the VOCs identified in the samples could differentiate cancer patients from healthy females.

CONCLUSIONS

In summary, we have detected and identified specific VOCs from healthy women that are not present in CC-affected females and VOCs specific of CC-affected women. We are strengthening our findings to aid in the detection of VOCs that are potential biomarkers for cervical tumors.

Volatile metabolomic signature of bladder cancer cell lines based on gas chromatography-mass spectrometry

INTRODUCTION

Recent studies provide a convincing support that the presence of cancer cells in the body leads to the alteration of volatile organic compounds (VOCs) emanating from biological samples, particularly of those closely related with tumoral tissues. Thus, a great interest emerged for the study of cancer volatilome and subsequent attempts to confirm VOCs as potential diagnostic biomarkers.

OBJECTIVES

The aim of this study was to determine the volatile metabolomic signature of bladder cancer (BC) cell lines and provide an in vitro proof-of-principle that VOCs emanated into the extracellular medium may discriminate BC cells from normal bladder epithelial cells.

METHODS

VOCs in the culture media of three BC cell lines (Scaber, J82, 5637) and one normal bladder cell line (SV-HUC-1) were extracted by headspace-solid phase microextraction and analysed by gas chromatography-mass spectrometry (HS-SPME/GC-MS). Two different pH (pH 2 and 7) were used for VOCs extraction to infer the best pH to be used in in vitro metabolomic studies.

RESULTS

Multivariate analysis revealed a panel of volatile metabolites that discriminated cancerous from normal bladder cells, at both pHs, although a higher number of discriminative VOCs was obtained at neutral pH. Most of the altered metabolites were ketones and alkanes, which were generally increased in BC compared to normal cells, and alcohols, which were significantly decreased in BC cells. Among them, three metabolites, namely 2-pentadecanone, dodecanal and γ-dodecalactone (the latter only tentatively identified), stood out as particularly important metabolites and promising volatile biomarkers for BC detection. Furthermore, our results also showed the potential of VOCs in discriminating BC cell lines according to tumour grade and histological subtype.

CONCLUSIONS

We demonstrate that a GC-MS metabolomics-based approach for analysis of VOCs is a valuable strategy for identifying new and specific biomarkers that may improve BC diagnosis. Future studies should entail the validation of volatile signature found for BC cell lines in biofluids from BC patients.

Identification of Sarcosine as a Target Molecule for the Canine Olfactory Detection of Prostate Carcinoma

The hypothesis that dogs can detect malignant tumours through the identification of specific molecules is nearly 30 years old. To date, several reports have described the successful detection of distinct types of cancer. However, is still a lack of data regarding the specific molecules that can be recognized by a dog’s olfactory apparatus. Hence, we performed a study with artificially prepared, well-characterized urinary specimens that were enriched with sarcosine, a widely reported urinary biomarker for prostate cancer (PCa). For the purposes of the study, a German shepherd dog was utilized for analyses of 60 positive and 120 negative samples. Our study provides the first evidence that a sniffer dog specially trained for the olfactory detection of PCa can recognize sarcosine in artificial urine with a performance [sensitivity of 90%, specificity of 95%, and precision of 90% for the highest amount of sarcosine (10 µmol/L)] that is comparable to the identification of PCa-diagnosed subjects (sensitivity of 93.5% and specificity of 91.6%). This study casts light on the unrevealed phenomenon of PCa olfactory detection and opens the door for further studies with canine olfactory detection and cancer diagnostics.

Cross detection for odor of metabolic waste between breast and colorectal cancer using canine olfaction

Although several studies have been performed to detect cancer using canine olfaction, none have investigated whether canine olfaction trained to the specific odor of one cancer is able to detect odor related to other unfamiliar cancers. To resolve this issue, we employed breast and colorectal cancer in vitro, and investigated whether trained dogs to odor related to metabolic waste from breast cancer are able to detect it from colorectal cancer, and vice versa. The culture liquid samples used in the cultivation of cancerous cells (4T1 and CT26) were employed as an experimental group. Two different breeds of dogs were trained for the different cancer odor each other. The dogs were then tested using a double-blind method and cross-test to determine whether they could correctly detect the experimental group, which contains the specific odor for metabolic waste of familiar or unfamiliar cancer. For two cancers, both dogs regardless of whether training or non-training showed that accuracy was over 90%, and sensitivity and specificity were over 0.9, respectively. Through these results, it was verified that the superior olfactory ability of dogs can discriminate odor for metabolic waste of cancer cells from it of benign cells, and that the specific odor for metabolic waste of breast cancer has not significant differences to it of colorectal cancer. That is, it testifies that metabolic waste between breast and colorectal cancer have the common specific odor in vitro. Accordingly, a trained dogs for detecting odor for metabolic waste of breast cancer can perceive it of colorectal cancer, and vice versa. In order to the future work, we will plan in vivo experiment for the two cancers and suggest research as to what kind of cancers have the common specific odor. Furthermore, the relationship between breast and colorectal cancer should be investigated using other research methods.

The Influence of Sniffing on Airflow and Odorant Deposition in the Canine Nasal Cavity

Nasal airflow plays a critical role in olfaction by transporting odorant from the environment to the olfactory epithelium, where chemical detection occurs. Most studies of olfaction neglect the unsteadiness of sniffing and assume that nasal airflow and odorant transport are "quasi-steady," wherein reality most mammals "sniff." Here, we perform computational fluid dynamics simulations of airflow and odorant deposition in an anatomically accurate model of the coyote (Canis latrans) nasal cavity during quiet breathing, a notional quasi-steady sniff, and unsteady sniffing to: quantify the influence of unsteady sniffing, assess the validity of the quasi-steady assumption, and investigate the functional advantages of sniffing compared to breathing. Our results reveal that flow unsteadiness during sniffing does not appreciably influence qualitative (gross airflow and odorant deposition patterns) or quantitative (time-averaged olfactory flow rate and odorant uptake) measures of olfactory function. A quasi-steady approximation is, therefore, justified for simulating time-averaged olfactory function in the canine nose. Simulations of sniffing versus quiet breathing demonstrate that sniffing delivers about 2.5 times more air to the olfactory recess and results in 2.5-3 times more uptake of highly- and moderately-soluble odorants in the sensory region per unit time, suggesting one reason why dogs actively sniff. Simulations also reveal significantly different deposition patterns in the olfactory region during inspiration for different odorants, and that during expiration there is little retronasal odorant deposition in the sensory region. These results significantly improve our understanding of canine olfaction, and have several practical implications regarding computer simulation of olfactory function.

Cancer sniffer dogs: how can we translate this peculiarity in laboratory medicine? Results of a pilot study on gastrointestinal cancers

BACKGROUND

Identification of cancer biomarkers to allow early diagnosis is an urgent need for many types of tumors, whose prognosis strongly depends on the stage of the disease. Canine olfactory testing for detecting cancer is an emerging field of investigation. As an alternative, here we propose to use GC-Olfactometry (GC/O), which enables the speeding up of targeted biomarker identification and analysis. A pilot study was conducted in order to determine odor-active compounds in urine that discriminate patients with gastrointestinal cancers from control samples (healthy people).

METHODS

Headspace solid phase microextraction (HS-SPME)-GC/MS and GC-olfactometry (GC/O) analysis were performed on urine samples obtained from gastrointestinal cancer patients and healthy controls.

RESULTS

In total, 91 key odor-active compounds were found in the urine samples. Although no odor-active biomarkers present were found in cancer carrier's urine, significant differences were discovered in the odor activities of 11 compounds in the urine of healthy and diseased people. Seven of above mentioned compounds were identified: thiophene, 2-methoxythiophene, dimethyl disulphide, 3-methyl-2-pentanone, 4-(or 5-)methyl-3-hexanone, 4-ethyl guaiacol and phenylacetic acid. The other four compounds remained unknown.

CONCLUSIONS

GC/O has a big potential to identify compounds not detectable using untargeted GC/MS approach. This paves the way for further research aimed at improving and validating the performance of this technique so that the identified cancer-associated compounds may be introduced as biomarkers in clinical practice to support early cancer diagnosis.

Odor Perception by Dogs: Evaluating Two Training Approaches for Odor Learning of Sniffer Dogs

In this study, a standardized experimental set-up with various combinations of herbs as odor sources was designed. Two training approaches for sniffer dogs were compared; first, training with a pure reference odor, and second, training with a variety of odor mixtures with the target odor as a common denominator. The ability of the dogs to identify the target odor in a new context was tested. Six different herbs (basil, St. John's wort, dandelion, marjoram, parsley, ribwort) were chosen to produce reference materials in various mixtures with (positive) and without (negative) chamomile as the target odor source. The dogs were trained to show 1 of 2 different behaviors, 1 for the positive, and 1 for the negative sample as a yes/no task. Tests were double blind with one sample presented at a time. In both training approaches, dogs were able to detect chamomile as the target odor in any presented mixture with an average sensitivity of 72% and a specificity of 84%. Dogs trained with odor mixture containing the target odor had more correct indications in the transfer task.

Changes in diet associated with cancer: An evolutionary perspective

Changes in diet are frequently correlated with the occurrence and progression of malignant tumors (i.e., cancer) in both humans and other animals, but an integrated conceptual framework to interpret these changes still needs to be developed. Our aim is to provide a new perspective on dietary changes in tumor‐bearing individuals by adapting concepts from parasitology. Dietary changes may occur alongside tumor progression for several reasons: (i) as a pathological side effect with no adaptive value, (ii) as the result of self‐medication by the host to eradicate the tumor and/or to slow down its progression, (iii) as a result of host manipulation by the tumor that benefits its progression, and finally (iv) as a host tolerance strategy, to alleviate and repair damages caused by tumor progression. Surprisingly, this tolerance strategy can be beneficial for the host even if diet changes are beneficial to tumor progression, provided that cancer‐induced death occurs sufficiently late (i.e., when natural selection is weak). We argue that more data and a unifying evolutionary framework, especially during the early stages of tumorigenesis, are needed to understand the links between changes in diet and tumor progression. We argue that a focus on dietary changes accompanying tumor progression can offer novel preventive and therapeutic strategies against cancer.

Of Dogs and Men

Experiments involving dog-human social cognition have shown dogs’ close attention to human behavioral cues. Dogs remained near a fallen owner, avoided a deceptive human, and preferred a human that provided valid information about the location of a reward over an uninformative human. On the other hand, dogs showed no evidence of going for help in an emergency, having theory of mind or metacognition, or performing successive numerical discrimination. When tested for spatial memory and simultaneous numerical discrimination, dogs showed evidence of these abilities but also showed lower performance levels than found in other species.