This study derived a set of Australian low-risk gambling limits and explored the relative and absolute risk associated with exceeding these limits. Secondary analysis of population-representative Tasmanian and Australian Capital Territory (ACT) cross-sectional  and longitudinal studies (2027 respondents) was conducted. Balancing sensitivity and specificity, the limits were: gambling frequency of 20–30 times per year; gambling expenditure of AUD $380–$615 per year (USD $240–$388 per year); gambling expenditure comprising 0.83–1.68% of gross personal income; and two types of gambling activities per year. All limits, except number of activities, predicted subsequent harm, with limits related to gambling expenditure consistently the best-performing. Exceeding the limits generally conferred a higher degree of relative and absolute risk, with gamblers exceeding the limits being 3–20 times more likely to experience harm than those who do not, and having a 5–17% risk of experiencing harm. Only 7–12% of gamblers exceeding the limits actually experienced harm. Gambling consumption lower than the limits also conferred a considerable amount of harm. Using a relative risk method, this study derived similar limits from disparate Australian states and territories. These limits can serve as working guidelines for the consideration of researchers, clinicians, and policy makers, but need to be subject to further rigorous empirical investigation.  Gambling disorder is characterised by persistent and recurring gambling behaviour that leads to substantial impairment and disruption to personal, family, or vocational pursuits . In contIn alcohol research, there is an accumulation of evidence on the identification of alcohol intake levels that distinguish low-risk and high-risk behaviour . These cThere is now some evidence that the development of empirically derived quantitative low-risk gambling limits is possible. The literature has employed almost identical statistical methodologies: risk (dose-response) curves exploring the degree to which gambling behaviours are associated with gambling-related harm; receiver operating characteristic (ROC) analyses to identify optimal low-risk gambling limits; and regression modelling to examine the associations between these limits and gambling-related harm ,20,21,22Low-risk gambling limits have been identified in cross-sectional population-representative studies in Canada ,12,16,19In the absence of a conceptual rationale for maximising sensitivity or specificity, these low-risk gambling limits were identified using a relative risk approach that involved giving equal weighting to sensitivity  and specificity . Currie et al. , howeverMoreover, the alcohol literature has identified low-risk drinking limits based on an absolute risk approach, in which limits were statistically determined based on tolerable levels of absolute risk ,27,28. TEmpirically-derived low-risk gambling limits can be used to inform the development of formal quantitative low-risk gambling guidelines that can usefully augment the behavioural responsible gambling guidelines that are currently available ,15. It rHowever, given the argument that limits might better be made on the basis of tolerable levels of risk  and the This study involved the secondary analysis of population data from the second and third Social and Economic Impact Study (SEIS) of Gambling in Tasmania ,35, the Indices of gambling consumption on which the low-risk gambling limits are derived were gambling frequency, gambling expenditure, gambling expenditure as a proportion of personal income, and number of types of gambling activities . Given eGiven that no validated measures of gambling-related harm were available when the surveys were conducted, harm was measured using selected items from the nine-item Problem Gambling Severity Index . Using tp < 0.05. All inferential analyses were performed using a robust variance estimator to adjust for heteroscedasticity. All analyses were conducted using available cases, excluding missing data. Previously conducted bootstrapped linear regression analyses suggested that the shape of the dose-response risk curves for both datasets was either linear or r-shaped [Unless otherwise stated, all analyses were conducted in Stata-14 , employer-shaped . Low-risr-shaped ; moderatr-shaped ,40. The r-shaped  relativer-shaped . This mer-shaped . A serieLogistic regression analyses (controlling for socio-demographic characteristics) were employed to explore the degree to which exceeding each of the limits at Wave 1 of the TLGS predicted subsequent (binary) harm in Waves 2 and 3. These analyses were then repeated with the other limits as additional covariates. Wave 1 data was used to predict subsequent harm in both waves to determine the stability of the predictive ability of the limits over a longer period of time. The gambling expenditure as a proportion of gross personal income limit was removed due to multicollinearity with the gambling expenditure limit. These analyses were conducted with non-gamblers classified as having no harm and with weights for the complete sample who provided longitudinal data.A set of sliding scales (using unweighted data) was created to highlight the relative risk (proportion of gamblers experiencing harm in those exceeding the limit divided by proportion of gamblers experiencing harm in those not exceeding the limit) and absolute risk (number of people experiencing harm in relation to the population at risk) associated with different levels of gambling consumption. The limits were used as a basic metric and the relative and absolute risk was calculated for gambling consumption at increasing multiples below, at, and above each of the limits.Absolute risk was also investigated by evaluating the PPVs and NPVs for each of the limits based on the prevalence of harm. The PPVs and NPVs were explored in both the population and gambling samples from the Tasmanian SEIS and ACT datasets. PPVs and NPVs were then graphed using the sensitivity and specificity from ROC analyses against prevalence rates of harm ranging from 0% to 100% prevalence to illustrate that PPVs and NPVs are influenced by the prevalence of gambling-related harm in the population that is being tested.The optimal cut-offs in ROC analyses using the Youden Index were explored across the multiple gambling indices and gambling-related harm in the Tasmanian SEIS and ACT datasets . The limAfter controlling for socio-demographic characteristics, exceeding the gambling frequency (OR = 6.11–14.26) and gambling expenditure as a proportion of gross personal income (OR = 15.39–21.11) limits in Wave 1 of the TLGS significantly predicted gambling-related harm in both Waves 2 and 3; and exceeding the gambling expenditure limit in Wave 1 significantly predicted harm in Wave 2 only (OR = 14.23) . After cThe relative and absolute risk calculations in the sliding scales  indicateIn the Tasmanian SEIS and ACT surveys, between 6.8% and 11.5% of gamblers (3.7–7.4% of population) who exceeded the limits would actually be experiencing gambling-related harm (PPVs); and between 98.3% and 98.9% of gamblers (99.0–99.4% of population) who stayed within the limits would not be experiencing harm (NPVs) . The higThe cut-offs in ROC analyses were identified after maximising sensitivity and maximising specificity . After mAfter maximising specificity, the limits, which were all in the moderate classification accuracy range, were exceeding any of the following: a gambling frequency of 49 to 65 times per year; a gambling expenditure of AUD $1380 to $2306 per year (USD $870 to $1455); a gambling expenditure comprising 3.03 to 6.19% of an individual’s gross personal income; and two to three types of gambling activities per year . BetweenThis study aimed to replicate previous research predominantly conducted in Canada by identifying a set of empirically based low-risk gambling limits that can be used to inform the development of low-risk gambling guidelines for Australia. The definition of harm based on two or more of the seven negative consequence PGSI items produced good ROC parameters in the current study and in previous research ,12,16,23Consistent with previous longitudinal research ,19, the There were no significant interaction effects of either gender or age with the low-risk gambling limits to predict gambling-related harm. These findings suggest that each limit predicts gambling-related harm equally for men and women and across age categories. This is consistent with previous literature that suggests that the dose-response relationship between gambling behaviour and gambling-related harm is similar for men and women ,16,19 anGamblers exceeding the limits are the target audience for the promotion of limits. In this study, this group (26–60%) was considerably higher than in Canadian samples ,19, as mThis study aimed to extend the available literature by identifying the relative and absolute risk associated with exceeding the limits. The relative risk calculations indicated that exceeding the limits generally confers a higher degree of risk for gambling-related harm. The absolute risk calculations revealed that the degree of absolute risk incrementally increased as gambling consumption increased. However, only a relatively small proportion of gamblers exceeding the limits (7–12%) will actually be experiencing harm. These low PPVs, which are not unexpected given the relatively low base-rate prevalence of gambling-related harm in the population, are not unique to gambling. Similarly, low PPVs have been identified for low-risk drinking limits, which are consistently less than 10% and usually less than 5%, regardless of which risk drinking measure is employed . They maGambling consumption lower than the low-risk gambling limits identified in this study also conferred a considerable degree of risk. Combined with the previously identified linear or r-shaped risk curves identified using these datasets , these fThe ROC analyses repeated with sensitivity maximised produced limits that were approximately one-third to one-half the limits identified by balancing sensitivity and specificity, with a slight increase in false positives (6–7% of identified gamblers experienced gambling-related harm). In contrast, the ROC analyses repeated with specificity maximised produced limits that were generally two to four times higher than those which balanced sensitivity and specificity. Although there was a slight reduction in false positives (7–21% of identified gamblers experienced gambling-related harm), these limits are predominantly based on less than acceptable sensitivity estimates. In the absence of a consensus regarding the maximisation of sensitivity or specificity, these levels are not recommended for adoption as the proposed low-risk limits. Such limits are intended as a guideline to the population on ways of limiting the chances of serious gambling-related harm, and in this context, “false negatives”  matter a great deal more than “false positives”  . AccordiLimitations include deficiencies in the representativeness of the survey samples relative to the general population which, for instance, underrepresent younger adults. Although the data were weighted to compensate for this under-representation, future research is required to explore the applicability of the derived limits to young people specifically. Another deficiency is the use of self-reported measures of gambling consumption and gambling-related harm. Despite concern that self-reports underestimate gambling consumption , a stronThe identification of low-risk gambling limits can support efforts targeted at the prevention of gambling-related harm, rather than problem gambling, thereby potentially impacting on a larger segment of the population, including those for whom harm occurs below the clinical threshold of pathology ,10,11,12This is the first study to attempt to identify and evaluate evidence-based low-risk gambling limits for Australia. A relative risk method identified indicators of gambling consumption levels that reliably differentiate gamblers at lower and higher risk of gambling-related harm. This research identified similar limits across population-representative datasets produced by independent research teams from the two most socio-demographically disparate Australian jurisdictions. These limits are consistent with previous research and are able to predict subsequent gambling-related harm. The two limits related to gambling expenditure (gambling expenditure and gambling expenditure as a proportion of income) were consistently the best-performing. At least from a relative risk perspective, there is little utility in increasing these limits; in fact, gambling at any level appears to carry some level of risk for harm. These limits can serve as working guidelines for the consideration of researchers, clinicians, and policy makers but need to be subject to further rigorous empirical investigation.


The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population. A critical step in the fight against COVID-19 is effective screening of infected patients, with one of the key screening approaches being radiology examination using chest radiography. It was found in early studies that patients present abnormalities in chest radiography images that are characteristic of those infected with COVID-19. Motivated by this and inspired by the open source efforts of the research community, in this study we introduce COVID-Net, a deep convolutional neural network design tailored for the detection of COVID-19 cases from chest X-ray (CXR) images that is open source and available to the general public. To the best of the authors’ knowledge, COVID-Net is one of the first open source network designs for COVID-19 detection from CXR images at the time of initial release. We also introduce COVIDx, an open access benchmark dataset that we generated comprising of 13,975 CXR images across 13,870 patient patient cases, with the largest number of publicly available COVID-19 positive cases to the best of the authors’ knowledge. Furthermore, we investigate how COVID-Net makes predictions using an explainability method in an attempt to not only gain deeper insights into critical factors associated with COVID cases, which can aid clinicians in improved screening, but also audit COVID-Net in a responsible and transparent manner to validate that it is making decisions based on relevant information from the CXR images. By no means a production-ready solution, the hope is that the open access COVID-Net, along with the description on constructing the open source COVIDx dataset, will be leveraged and build upon by both researchers and citizen data scientists alike to accelerate the development of highly accurate yet practical deep learning solutions for detecting COVID-19 cases and accelerate treatment of those who need it the most. While RT-PCR testing is the gold standard as it is highly specific, it is a very time-consuming, laborious, and complicated manual process that is in short supply. Furthermore, the sensitivity of RT-PCR testing is highly variable and have not been reported in a clear and consistent manner to date2, and initial findings in China showing relatively poor sensitivity3. Furthermore, subsequent findings showed highly variable positive rate depending on how the specimen was collected as well as decreasing positive rate with time after symptom onset5.The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population, caused by the infection of individuals by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A critical step in the fight against COVID-19 is effective screening of infected patients, such that those infected can receive immediate treatment and care, as well as be isolated to mitigate the spread of the virus. The main screening method used for detecting COVID-19 cases is reverse transcriptase-polymerase chain reaction (RT-PCR)8, with some suggesting that radiography examination could be used as a primary tool for COVID-19 screening in epidemic areas9. For example, Huang et al.7 identified that the majority of the COVID-19 positive cases in their study presented bilateral radiographic abnormalities in CXR images, and Guan et al.8 identified COVID-19 positive cases in their study presented radiographic abnormalities such as ground-glass opacity, bilateral abnormalities, and interstitial abnormalities in CXR and CT images. While much of the recent discussion has revolved around CT imaging due to greater image detail in the acquisitions, there are several advantages to leveraging CXR imaging for COVID-19 screening amid the global COVID-19 pandemic, particularly in resource-constrained areas and heavily-affected areas:Rapid triaging CXR imaging enables rapid triaging of patients suspected of COVID-19 and can be done in parallel of viral testing (which takes time) to help relief the high volumes of patients especially in areas most affected where they have ran out of capacity , or even as standalone when viral testing isn’t an option (low supplies). Furthermore, CXR imaging can be quite effective for triaging in geographic areas where patients are instructed to stay home until the onset of advanced symptoms , since abnormalities are often seen at time of presentation when patients suspected of COVID-19 arrive at clinical sites10.Availability and accessibility CXR imaging is readily available and accessible in many clinical sites and imaging centers as it is considered standard equipment in most healthcare systems. In particular, CXR imaging is much more readily available than CT imaging, especially in developing countries where CT scanners are cost prohibitive due to high equipment and maintenance costs.Portability The existence of portable CXR systems means that imaging can be performed within an isolation room, thus significantly reducing the risk of COVID-19 transmission during transport to fixed systems such as CT scanners as well as within the rooms housing the fixed imaging systems10.As such, radiography examination can be conducted faster and have greater availability given the prevalence of chest radiology imaging systems in modern healthcare systems and the availability of portable units, making them a good complement to RT-PCR testing particularly since CXR imaging is often performed as part of standard procedure for patients with a respiratory complaint11. It is also suggested that CXR imaging may have utility for situations where patients with initial negative RT-PCR testing outcomes return to the emergency department with worsening symptoms12. Furthermore, some have suggested that as the COVID-19 pandemic progresses, there will be a greater reliance on portable CXR due to the aforementioned advantages13, and found portable CXR to be highly valuable for critically ill COVID-19 patients14. Hence, CXR are an integral part of some screening strategies that have been proposed15. However, one of the biggest bottlenecks faced is the need for expert radiologists to interpret the radiography images, since the visual indicators can be subtle. As such, computer-aided diagnostic systems that can aid radiologists to more rapidly and accurately interpret radiography images to detect COVID-19 cases is highly desired.An alternative screening method that has also been utilized for COVID-19 screening has been radiography examination, where chest radiography imaging  or computed tomography (CT) imaging) is conducted and analyzed by radiologists to look for visual indicators associated with SARS-CoV-2 viral infection. It was found in early studies that patients present abnormalities in chest radiography images that are characteristic of those infected with COVID-19Introduction of a novel deep neural network architecture that is tailored for the detection of COVID-19 cases from CXR images using a human-machine collaborative design strategy. To the best of the authors’ knowledge, COVID-Net is the first neural network architecture designed for COVID-19 detection to introduce a lightweight projection-expansion-projection-extension (PEPX) design, which enables enhanced representational capacity while greatly reducing computational complexity. Furthermore, to the best of the authors’ knowledge, COVID-Net is one of the first open source network designs for COVID-19 detection from CXR images at the time of initial release, which encourages reproducibility.20), two of which we introduced18. To the best of the authors’ knowledge, COVIDx is the largest open access benchmark dataset available in terms of the number of publicly available COVID-19 positive cases.Introduction of COVIDx, an open access benchmark dataset that we generated comprising of 13,975 CXR images across 13,870 patient cases, created as a combination and modification of five open access data repositories containing chest radiography images  and Middle East respiratory syndrome (MERS) cases) with annotated CXR and CT images, so that the research community and citizen data scientists can leverage the dataset to explore and build AI systems for COVID-19 detection.Since the time of the initial public release of the proposed COVIDx dataset and the proposed COVID-Net, a number of studies have been conducted in the area of COVID-19 detection using CXR images38, several of which have leveraged variants of the COVIDx dataset or COVID-Net to conduct such studies37. Based on a comprehensive survey of the studies in research literature, they have focused primarily on the exploration of deep learning, in particular deep convolutional neural networks, given the significant successes and state-of-the-art achieved in a variety of computer vision tasks. It is important to note that the proposed COVID-Net and corresponding COVIDx dataset continues to evolve as new patient cases are continuously added and are made available publicly on a regular basis, and thus this study represents a snapshot of the current state of COVID-Net and COVIDx.Motivated by the need for faster interpretation of radiography images, a number of artificial intelligence (AI) systems based on deep learningIn this study, a human-machine collaborative design strategy is leveraged to create COVID-Net, where human-driven principled network design prototyping is combined with machine-driven design exploration to produce a network architecture tailored for the detection of COVID-19 cases from CXR images. An open access benchmark dataset called COVIDx is also created to facilitate for training and evaluating COVID-Net. Here, we will discuss in detail the process of creating the COVIDx dataset, the architecture design methodology behind the proposed COVID-Net, the resulting network architecture, the implementation details in creating COVID-Net, and the strategy for auditing COVID-Net via explainability.16, (2) Fig. 17, established in collaboration with Fig. 18, established in collaboration with ActualMed, (4) RSNA Pneumonia Detection Challenge dataset20, which used publicly available CXR data from39, and (5) COVID-19 radiography database19. Example CXR images from the COVIDx dataset are shown in Fig. The dataset used to train and evaluate the proposed COVID-Net, which we will refer to as COVIDx, is comprised of a total of 13,975 CXR images across 13,870 patient cases. To the best of the authors’ knowledge, the proposed COVIDx dataset is the largest open access benchmark dataset in terms of the number of COVID-19 positive patient cases. To generate the COVIDx dataset, we combined and modified five different publicly available data repositories: (1) COVID-19 Image Data Collection16,  Fig. 17,16Non-COVID19 pneumonia patient cases and COVID-19 patient cases from the COVID-19 Image Data Collection17,COVID-19 patient cases from the Fig. 18COVID-19 patient cases from the ActualMed COVID-19 Chest X-ray Dataset Initiative20Patient cases who have no pneumonia  and non-COVID19 pneumonia patient cases from RSNA Pneumonia Detection Challenge dataset19COVID-19 patient cases from COVID-19 radiography databaseThe distribution of images and patient cases amongst the different infection types shown in Figs. https://github.com/lindawangg/COVID-Net.More specifically, we combined and modified the five data repositories to create the COVIDx dataset by leveraging the following types of patient cases from each of the data repositories:40 as they have been shown time and again to enable reliable neural network architectures that are easier to train to high performance, and enables deeper architectures to be built successfully.The first stage of the human-machine collaborative design strategy employed to create the proposed COVID-Net is a principled network design prototyping stage, where an initial network design prototype is constructed based on human-driven design principles and best practices. More specifically in this study, we leveraged residual architecture design principlesIn this study, we construct the initial network design prototype to make one of the following three predictions: (a) no infection , (b) non-COVID19 infection , and c) COVID-19 viral infection  COVID-19 sensitivity In this study, we leverage generative synthesishttps://github.com/lindawangg/COVID-Net. A number of interesting observations can be made with regards to the COVID-Net network arhchitecture design that was created via a human-machine collaborative design strategy.The proposed COVID-Net network architecture is shown in Fig. First-stage projection 1Expansion: 1Depth-wise representation efficient 3Second-stage projection 1Extension: 1Such a customized lightweight design pattern, which is discovered by the machine-driven design exploration strategy and not previously introduced in literature to the best of the authors’ knowledge, enables enhanced representational capacity while maintaining reduced computational complexity.It can be observed that the COVID-Net network architecture makes heavy use of a lightweight residual projection-expansion-projection-extension (PEPX) design pattern, which consists of:42. However, a disadvantage of leveraging a large number of long-range connections as done in densely-connected deep neural network architectures is a noticeable increase in computational complexity as well as memory overhead. To alleviate this, it can be observed that the COVID-Net network architecture only leverages long range connections in a sparing manner where necessary, as exhibited by the existence of four densely connected It can also be observed that the COVID-Net architecture possesses selective long-range connectivity at various areas of the network architecture. The use of long-range connectivity has been found previously to enable improved representational capacity as well as make it easier to train, with an exemplary network architecture leveraging long-range connectivity being densely-connected deep neural network architecturesFinally, it can be observed that there is considerable architectural diversity in the COVID-Net architecture. In particular, the COVID-Net network architecture is comprised of a heterogeneous mix of convolution layers with a diversity of kernel sizes . The following hyperparameters were used for training: learning rate 41, as described in “The proposed COVID-Net was pretrained on the ImageNet44, an explainability method that is a critical aspect of the generative synthesis strategy41 leveraged in the machine-driven exploration strategy used to create the proposed COVID-Net network architecture. A brief summary of the GSInquire is provided as follows.Due to the mission-critical nature of clinical applications such as COVID-19 detection that can affect the health and well-being of patients, it is important to design deep neural network architectures such as COVID-Net with responsibility and transparency in mind. Therefore, in this study, we perform an explainability-driven audit on COVID-Net to validate that it is making detection decisions based on relevant information rather than improper information . More specifically, we audit COVID-Net via an qualitative analysis to study the critical factors leveraged by COVID-Net in making detection decisions. Here, we leveraged GSInquireV of vertices E of edges S is the set of possible seeds. Finally, an inquisitor function is defined as GSInquire revolves around the notion of an inquisitor z of a decision made by a reference network x , both 45), and an indicator function x and the corresponding set x via a transformation In the scenario where the underlying goal is to obtain an interpretation The study has received ethics clearance from the University of Waterloo (42235).To evaluate the efficacy of the proposed COVID-Net, we perform both quantitative and qualitative analysis to get a better understanding of its detection performance and decision-making behaviour.x and y directions), rotation  prior to training in order to mitigate commonly-found embedded textual information in the CXR images. Furthermore, to train the tested deep neural network architectures, data augmentation was leveraged with the following augmentation types: translation  for each infection type, on the aforementioned COVIDx dataset. The test accuracy, along with the architectural complexity (in terms of number of parameters) and computational complexity (in terms of number of multiply-accumulation (MAC) operations) are shown in Table Next, we take a deeper exploration into the current limitations of the proposed COVID-Net by studying the sensitivity and PPV for each infection type, which is shown in Tables 37, the machine learning methods leveraged in these studies have been deep learning approaches. As such, we have focused this study to quantitatively compare between different deep neural network architectures to study the impact on computational efficiency and performance.We now take a deep exploration into the impact of architectural design choices made by generative synthesis during the machine-driven design exploration process on the resulting COVID-Net network architecture being able to achieve in terms of balance between computational efficiency and performance. It is important to note that, based on a thorough survey of all machine learning methods for COVID-19 detection using chest x-rays in research literatureVGG-1946 A deep neural network architecture that does not leverage residual design principles, lightweight design patterns, and have very low architectural diversity.ResNet-5040 A deep neural network architecture that leverages residual design principles and lightweight design patterns  and have moderate architectural diversity, but does not leverage lightweight PEPX design patterns and selective long-range connectivity. This architecture was leveraged in a study37 on an early variant of COVIDx to good effect. As such, a quantitative performance evaluation of this architecture enables a more direct comparison with37 and highlight the benefits of the uniqueness of the COVID-Net architecture.The choice of these two deep neural network architectures is based on the fact that they do not possess the key defining traits of COVID-Net, which are lightweight PEPX design patterns, selective long-range connectivity, and high architectural diversity, thus allowing for a better understanding of the benefits of the unique traits of COVID-Net.In order to perform this analysis, we evaluated the performances of the following deep neural network architectures for comparative purposes:It can be observed in Table mentclass2pt{minim44 in several example CXR images of COVID-19 cases are shown in Fig. As mentioned earlier, we performed an audit on the proposed COVID-Net to gain better insights into how COVID-Net makes decisions, and validate whether it is making detection decisions based on relevant information rather than erroneous information that bias decisions based on irrelevant visual indicators. The critical factors identified by GSInquire8. What this illustrates is that the proposed COVID-Net can learn to leverage visual indicators in its decision-making process that relate to those leveraged by clinicians in their decision-making process. Therefore, these observations are insightful for establishing a deeper understanding into the overlaps between the decision-making process of deep neural networks for clinical applications and the decision-making process of clinicians during radiography examination.We further explored the relationship between the critical factors identified by GSInquire and the experimental results, particularly in relationship to clinical visual indicators leveraged for radiography examination of chest CXR images for COVID-19. In the cases in the experimental results where the proposed COVID-Net correctly detects COVID-19 infections see Fig. , the criTransparency By understanding the critical factors being leveraged in COVID-19 case detection, the predictions made by the proposed COVID-Net become more transparent and trustworthy for clinicians to leverage during their screening process to aid them in making faster yet accurate assessments.New insight discovery The critical factors leveraged by the proposed COVID-Net could potentially help clinicians discover new insights into the key visual indicators associated with SARS-CoV-2 viral infection, which they can then leverage to improve screening accuracy.In addition to performance validation for more responsible and transparent design, the ability to interpret and gain insights into how the proposed COVID-Net detects COVID-19 infections is also important for a number of other reasons:In this study, we introduced COVID-Net, a deep convolutional neural network design for the detection of COVID-19 cases from CXR images that is open source and available to the general public. We also introduce COVIDx, an open access benchmark dataset that is comprised of 13,975 CXR images across 13,870 patient cases from five open access data repositories. Moreover, we investigated how COVID-Net makes predictions using an explainability method in an attempt to gain deeper insights into critical factors associated with COVID cases, which can aid clinicians in improved screening as well as improve trust and transparency when leveraging COVID-Net for accelerated computer-aided screening.By no means a production-ready solution, the hope is that the promising results achieved by COVID-Net on the COVIDx test dataset, along with the fact that it is available in open source format alongside the description on constructing the open source dataset, will lead it to be leveraged and build upon by both researchers and citizen data scientists alike to accelerate the development of highly accurate yet practical deep learning solutions for detecting COVID-19 cases from CXR images and accelerate treatment of those who need it the most. Future directions include continuing to improve sensitivity and PPV to COVID-19 infections as new data is collected, as well as extend the proposed COVID-Net to risk stratification for survival analysis, predicting risk status of patients, and predicting hospitalization duration which would be useful for triaging, patient population management, and individualized care planning.


Hemiparkinsonism-hemiatrophy syndrome (HPHA) and hemidystonia-hemiatrophy syndrome (HDHA) are rare movement disorders composed of hemidystonia or hemiparkinsonism that present with unilateral limb, face, trunk, or cerebral hemiatrophy and mostly occur following head trauma or postanoxic events. However, relatively little is known about the pathogenesis of these conditions. In our case series, we present three HPHA patients and one HDHA patient who underwent detailed neuropsychological, radiological, motor, and non-motor functional assessments with a mean follow-up of 2 years. We followed two patients who showed differences in their progression for more than 2 years: one barely progressed with no treatment, and the other exhibited levodopa-induce dyskinesia (LID) and definitive progression while receiving multiple adjunctive therapies. In addition, we performed positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) and 18F-dihydroxyphenylalanine (DOPA) in one HPHA patient who showed bilaterally symmetrical uptake of FDG with no significant increase or decrease in the cerebral hemispheres, including the striatum, but exhibited a significant reduction in the uptake of 18F-DOPA in the contralateral posterior striatum. In this study, we followed HPHA patients who showed different disease courses to explore the clinical characteristics and pathogenesis of HPHA and HDHA and illustrate the clinical heterogeneity of these diseases. Hemiparkinsonism-hemiatrophy syndrome (HPHA) is a rare form of secondary parkinsonism. Its clinical manifestations include the occurrence of unilateral atrophy on one side of the body, which often presents early in life, and ipsilateral hemiparkinsonism with different latencies and relatively slow progression. HPHA is frequently accompanied by dystonia on the same side and shows a variable response to levodopa. Hemidystonia-hemiatrophy syndrome (HD-HA) is an uncommon condition characterized by hemidystonia and hemiatrophy. In one study, hemiparesis preceded HD in 88% of HDHA cases . DystociA 28-year-old, right-handed female with hemiatrophy in her left-sided extremities and face that became apparent when she was 2 years old presented with clumsiness in her left lower limb while climbing stairs and an abnormal dragging gait that appeared gradually. The patient was otherwise healthy until she was 28 years old. At this age she began to feel weakness and slowness in her left lower limb, which gradually worsened. These symptoms were relieved after taking a break, even though she had not used any drugs over the years. She was born via cesarean section due to a lack of amniotic fluid, which resulted in a suspected history of perinatal hypoxia. There was a negative family history for any neurological disorder and no history of brain injury or exposure to toxins and medications associated with parkinsonism. On examination, the left side of her face, tongue, and limbs were smaller than those on the right side . Mild riA 55-year-old, right-handed male who was born via spontaneous vaginal delivery at term without dystocia complained of a slowness of the left arm and leg on walking that started at 50 years of age. At the same time, he also became aware of atrophy in his left-side limbs and back muscles . A serie18F-Dihydroxyphenylalanine Positron Emission Tomography (18F-DOPA PET) showed a significant reduction in the uptake of 18F-DOPA in the right posterior striatum (18F-fluorodeoxyglucose (FDG) uptake was bilaterally uniform and symmetrical. No genetic abnormalities were detected by medical exome sequencing.A 49-year-old, right-handed woman presented with left-side hemiatrophy and resting tremor. She had been aware of a left-side dragging gait while walking since she was 48 years old, and this was followed by slowness on walking 2 months later. At the same time, resting tremors appeared in the left upper limb, and a clinician observed that her body showed hemiatrophy . Her rigstriatum , while 1A 24-year-old man with a normal perinatal history had fallen from the second floor and struck the left side of his head without loss of consciousness. Since then, atrophy of his right limbs and trunk was gradually noticed, and this was followed by dystonia and motor impairment on his right side. On examination at an age of 24 years, his right limbs were significantly shorter and smaller than his left limbs , and he Hemiparkinsonism-hemiatrophy syndrome (HPHA) is a relatively rare type of secondary parkinsonism. The clinical manifestations of HPHA are heterogeneous. In the relevant HPHA-related literature, hemiatrophy  and hemihypertrophy often occur early in life, and parkinsonism onset occurs in subsequent years or decades. The interval from HA to HP was variable. The average age of onset of parkinsonism was 43.7 years in a study of 16 HPHA patients . ParkinsGowers described the relationship between hemispheric lesions and contralateral limb atrophy, which the author attributed to a head injury followed by cortical abnormalities . PenfielEighty-eight percent of HDHA patients who present with hemiparesis preceding HD, which appeared after a mean 14.7-year latency. Patients who were younger at the onset of cerebral insult tended to have a later onset of dystonia, regardless of the cause of injury . HoweverWith the exception of the brain MRI performed in case 4, which showed dilatation of the left lateral ventricle, the other three patients had normal and symmetrical brain MRI scans. The abnormal findings observed on cranial MRI in patients with HPHA can be widely grouped into four categories: (1) focal atrophy or diffuse cerebral HA, (2) single or multiple focal lesions in the basal ganglia, (3) single or multiple focal lesions outside of the basal ganglia system, which are probably incidental findings unrelated to the underlying pathophysiology, and (4) normal scans . Nine 3. Parry-RFindings observed on FDOPA-PET can reflect the function of presynaptic dopaminergic neurons. One of our HPHA patients showed a significant reduction in the uptake of 18F-DOPA in the right posterior striatum, consistent with previous reports indicating that dysfunction in presynaptic dopaminergic neurons occurs in HPHA patients. FDG-PET reveals the integrity of neurons and synaptic functions in general. FDG uptake increases with synaptic activity and decreases with neural dysfunction. In our case 3 patient, FDG uptake was bilaterally symmetrical, and no significant increase or decrease was observed, including in the striatum. This is different from what has been reported in previous investigations that showed metabolic reductions in the contralateral or bilateral striatum or cortices . Our resin vitro, an effect that was associated with impaired mitochondrial function and a smaller myofiber area  for the publication of any potentially identifiable images or data included in this article.CH, PZ, and YL wrote the manuscript. BL and ZH collected the materials. LW and YZ reviewed the whole manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The paramount discovery of passive accumulation of nanoparticles in tumoral tissues triggered the development of a wide number of different nanoparticles capable of transporting therapeutic agents to tumoral tissues in a controlled and selective way. These nanocarriers have been endowed with important capacities such as stimuli-responsive properties, targeting abilities, or the capacity to be monitored by imaging techniques. However, after decades of intense research efforts, only a few nanomedicines have reached the market. The reasons for this disappointing outcome are varied, from the high tumor-type dependence of enhanced permeation and retention (EPR) effect to the poor penetration capacity of nanocarriers within the cancerous tissue, among others. The rapid nanoparticle clearance by immune cells, considered another important barrier, which compromises the efficacy of nanomedicines, would become an important ally in the fight against cancer. In the last years, the fine-tuned ability of immune cells to recognize and engulf nanoparticles have been exploited to deliver immunoregulating agents to specific immune cell populations selectively. In this work, the recent advances carried out in the development of nanocarriers capable of operating with immune and tumoral cells in order to orchestrate an efficient antitumoral response will be presented. The combination of nanoparticles and immunotherapy would deliver powerful weapons to the clinicians that offer safer and more efficient antitumoral treatments for the patients. The paramount discovery of the passive accumulation of nanoparticles in solid tumors carried out by Maeda and Matsumura a few decades ago  opened aDuring cancer progression, tumoral cells undergoing an evolutionary process operated by immune cells known as tumor immunoediting . This prImmunity against cancer requires the iterative evolution of a series of stepwise steps known as the cancer–immunity cycle  29]. Tu. Tu29]. In this review, the use of nanocarriers designed to start over this virtuous cycle in cancer patients will be discussed, presenting some of the representative examples that illustrate the huge potential of nanomedicines to interact with immune cells and, therefore, to trigger potent self-sustained immune responses against tumors.Tumoral cells present hundreds of mutations in coding regions of their DNA due to the acquisition of specific mutations in genes that control genome stability . The mut2). This shell is in charge of the elimination of the hypoxic environment, usually present in this type of malignancy, which hampers the PDT efficacy. Thus, manganese shell generates oxygen within the tissue by the catalytic decomposition of H2O2 produced by the tumoral cells restoring normoxia, which enhances the ROS production within the tumor. ROS generation and normoxic oxygen condition favored DC maturation causing strong tumor growth inhibition  due to the overexpression of this receptor (CD44) by colorectal cancerous cells.DC are phagocytic cells that engulf cancerous cells and expose the captured tumoral antigens on their surface in order to present them to adaptive immune cells inducing the selection of specific antitumoral T lymphocytes. However, in many cases, simply the presence of tumoral antigens is not enough to induce a functional DC maturation, but it also requires the existence of danger or stress signals in the tumoral tissue . In facthibition . The capThe temperature increase is a danger signal, which facilitates DC maturation. This fact has been exploited using magnetic liposomes injected in the tumoral tissue through the generation of heat by alternative magnetic field exposition . Active reg), which induce potent immunosuppression in cancerous tissues . Th. Th2O2, reg) and the expression on the tumor membrane of membrane receptors, which induce T cell apoptosis, is one of the most known of the programmed death ligand 1 (PD-L1) [•OH radicals mediated by Hf clusters, which were rapidly transformed to 1O2 by the photosensitizers. The combination of ROS generation and IDO inhibitors released in the tumoral tissue induced a potent systemic antitumoral immune response, which reduced the tumoral growth not only in irradiated tumors but also in distant tumor nodes. Cheng et al. have synthesized an amphiphilic peptide that contained a peptide sequence cleavable by metalloproteinase-2 conjugated with a short D-peptide antagonist of PD-L1 [When a pathological process is taken place within a tissue, sentinel immune cells trigger an inflammation process, which courses with the production of several agents as cytokines, chemokines, ROS, and metalloproteinases to promote the mobilization of more immune cells capable of combating the threat. DC engulf foreign agents exposing their antigens on the cell membrane and migrate to lymphoid organs to educate adaptive immune cells ) against the threat . Mature  (PD-L1) . Peritum (PD-L1) . The com (PD-L1) . Huang e (PD-L1) . In this (PD-L1) . Once th (PD-L1) . IDO inh (PD-L1) . Low-dosof PD-L1 . These pof PD-L1 . The bloof PD-L1 . Unfortuof PD-L1 . These n2+ as a catalyst. This drug has been co-delivered in combination with oxalilplatin in a controlled manner in solid tumors employing coordination polymer-based nanoparticles [+ T cells within the tumoral tissue. The release of miR-200c induced a potent inhibition of PD-L1 expression in the tumoral cells, which facilitated their destruction by the trained T cells. In another recent example, the PD-L1 silencing approach has been accomplished employing lipid-dendrimer-calcium-phosphate (TT-LDCP) nanoparticles able to transport siRNA that blocks the expression of the PD-L1 encoding gene and a plasmid that encodes the production of IL-2 [Other types of nanoparticles that contained metallic atoms as copper  or zinc articles . DHA relarticles . Release of IL-2 . This na of IL-2 . These n of IL-2 . This rereg usually overexpress CTLA-4 on their surface, hampering the stimulation of antitumoral T cells. Thus, antibodies as ipilimumab have been employed to block the CTLA-4-B7 binding process in order to remove this brake for the immune response against tumoral cells [Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) is a molecule expressed mainly on the surface of T lymphocytes, which exerts a regulatory function in immunity. An efficient antitumoral T cell response requires the presence of co-stimulatory signals; one of them is the interaction between CD28 receptors placed on the membrane of T cells with B7-1 and B7-2 receptors located on the surface of APC. CTLA-4 binds to B7 with higher intensity than CD28 downregulating immune response of T cells. Additionally, immunosuppressive Tal cells . Furtheral cells . Chen anal cells . These nal cells . The mairegs. These cells are a specialized subpopulation of T cells that exert immunosuppressive functions favoring the tolerance to self- and nonself-antigens in order to maintain the homeostasis of tissues. Their action is caused by different mechanisms as inhibition of stimulatory CD80 signals in DC by overexpression of CTLA-4, secretion of cytokines , consumption of IL-2, metabolic alterations of tryptophan or arginine or direct depletion of cytotoxic T cells [reg depletion in melanoma-bearing mice, which reverted the immunosuppressive environment leading to a higher CD8+ T cells accumulation and activation in the tumoral tissue. Chen and co-workers have employed small polymer-coated iron oxide nanoparticles (around 30 nm of diameter) to destroy Treg in breast tumor murine models by photothermal therapy (PTT) [reg population became dominant because these cells respond more efficiently to antigens exposition than CD8+ T cells. A second irradiation round 24 h later destroyed the tumor-homing replenished Tregs whereas barely affected to freshly activated cytotoxic CD8+ T cells, which did not have time enough to reach the tumoral tissue. PTT mediated with these iron-oxide nanoparticles in combination with anti-CTLA-4 induced a significant inhibition in the tumor growth and, even more important, provided a memory effect that protected the mice against tumor re-challenge.One of the residents of tumoral tissues that play a leading role supporting the immunosuppressive tumoral environment are T T cells . Several T cells . Therefo T cells  or drugs T cells  has led  T cells . This pepy (PTT) . It is wTumors secrete different factors as collagen or thrombin, which promote platelet activation. Platelets exert a key role in tumor development and progression promoting metastasis, angiogenesis, chemoresistance, and the release of soluble factors such as sphingosin-1-phosphate or serotonin that maintain a strong tumor vessel barrier which limits the infiltration of T cells in the tumoral tissue, among others . An effeThe development of smart nanoparticles capable of transporting therapeutic agents that exhibit very different natures from small drugs, as is the case of many chemotherapeutic compounds, to large macromolecules as proteins and oligonucleotide chains have provided an incredibly powerful tool to oncologists. During the last decades, thanks to the creativity and hard work of the scientific community, a myriad of different nanocarriers endowed with remarkable properties have been reported. Thus, these nanocarriers can be engineered with the capacity to release their cargo on-demand (stimuli-responsive behavior), ability to recognize their target cell (cellular targeting), and even certain organelles inside them (organelle targeting) and can be monitored in real-time during their journey through the patient (imaging). Despite these huge efforts, the clinical effect of nanomedicines has not been as satisfactory as previously thought with only a scarce bunch of nanomedicines in the market. The existence of important barriers that reduce the number of nanoparticles that reach the cancerous tissue and that hamper their homogeneous distribution inside there seriously compromises the efficacy of nanoparticle-based therapies focused on destroying tumoral cells. In the last years, the need to switch the nanoparticle’s target to tumoral cells to the cells of the immune system is gaining huge attention in the nanomedicine community. After years struggling against the fine-tuned capacity of immune cells to capture nanoparticles, the current paradigm is changing to take advantage of this fact through the development of nanocarriers designed to interact with immune cells in order to mobilize them against the tumor. Despite the promising results harvested with this novel approach, prudence is required not to create another nanomedicine hype . The imm


Altered functioning of GABAergic interneurons expressing parvalbumin (PV) in the basal ganglia-thalamo-cortical circuit are likely to be involved in several human psychiatric disorders characterized by deficits in attention and sensory gating with dysfunctional decision-making behavior. However, the contribution of these interneurons in the ability to acquire demanding learning tasks remains unclear. Here, we combine an operant conditioning task with local field potentials simultaneously recorded in several nuclei involved in reward circuits of wild-type (WT) and PV-deficient (PVKO) mice, which are characterized by changes in firing activity of PV-expressing interneurons. In comparison with WT mice, PVKO animals presented significant deficits in the acquisition of the selected learning task. Recordings from prefrontal cortex, nucleus accumbens (NAc) and hippocampus showed significant decreases of the spectral power in beta and gamma bands in PVKO compared with WT mice particularly during the performance of the operant conditioning task. From the first to the last session, at all frequency bands the spectral power in NAc tended to increase in WT and to decrease in PVKO. Results indicate that PV deficiency impairs signaling necessary for instrumental learning and the recognition of natural rewards. PV is also highly expressed in fast-twitch muscles, where it plays a key role in the muscle relaxation rate2. The integrity of 3. Knockout mice for PV (PVKO) have been used for more than two decades as a study model to investigate the effects of the disruption of the proper functioning of PV-expressing interneurons in neural networks1. PV-expressing interneurons are characterized by fast-firing properties affecting synchronization of electrical activity in cortical networks4 and short-term plasticity in the cerebellum and striatum6. Moreover, PV-downregulation is sufficient to induce crucial changes in precision of spike timing leading to changes in firing pattern in the thalamo-cortical network8. Synchronous recruitment of fast-spiking PV-expressing interneurons generated 9.Parvalbumin (PV) is a cytosolic 10. PV-deficient mice have been shown to develop highly coherent oscillatory activity that can develop into epileptic seizures with high incidence of mortality4. Rodent models of schizophrenia are characterized by dysregulation of GABAergic interneurons11 and by deficits in sensory-evoked 12. In human schizophrenic patients, it is well established that illness symptoms correlate positively with alterations of 14. In addition to schizophrenia, the key role of PV-expressing interneurons15 has been associated with other mouse models of neurodevelopmental disorders, i.e. Autism Spectrum Disorders (ASD)16, Rett syndrome17, and Huntington Disease18. What is common across these neuropsychological disorders is that they are all characterized by deficits in attention and sensory gating, thus leading to learning and memory deficits. These findings suggest that PV-deficient mice offer as a suitable model for studying the role of PV-expressing interneurons in regional oscillatory activity and in fundamental sensorimotor and cognitive processes expressed during the acquisition of complex learning tasks. A typical experimental paradigm for this kind of study is the operant conditioning19.The lack of PV in knockout mice yields a phenotype of locomotor activity and coordination characterized by a decreased exploratory activity and by an increased tendency to move in one direction for larger distances and longer intervals before stopping or turning20. As already reported, this experimental task involved the participation of different cortical and subcortical structures including the medial prefrontal cortex (mPFC), the CA1 area of the dorsal hippocampus and the nucleus accumbens (NAc), and related nuclei21. The medial septum (MS) is a major source of cholinergic projections to the hippocampus critical for the acquisition of Pavlovian and operant conditioning paradigms23. The output nuclei of the basal ganglia send projections to a number of thalamic nuclei, including the mediodorsal (MD) nucleus of the thalamus, whose lesion provokes impairment in operant conditioning25. All these structures are rich in PV-expressing interneurons28. In order to determine ongoing changes in the oscillatory activity across the learning process, we recorded simulteneous local field potential (LFP) profiles from electrodes implanted in the mPFC, the NAc, the hippocampal CA1 area, the MS and the thalamic MD nucleus. When compared with WT mice, PVKO animals presented a substantial deficit in the acquisition of the selected operant conditioning task and important differences in the profiles and spectral powers of LFPs collected from the mentioned structures.In the present study, we have checked the behavioral abilities of PVKO and WT mice to solve an operant conditioning using a light/dark paradigm described elsewhere21, mice (n = 6 mice per group) were initially trained for the acquisition of an operant conditioning task with a fixed-ratio (1:1) schedule—namely, each lever press was reinforced with a food pellet. Training sessions were performed daily and lasted for 20 min  = 0.206; P = 0.24]. After reaching the criterion, each animal was trained in a more complex task. In this case, animals were rewarded in a 1:1 fixed-ratio schedule only during the period in which a small light bulb, located over the lever, was switched on  and to press it (“pressing-the-lever”). Immediately after, the animal had to move towards the next corridor, approach the feeder (“going-to-the-feeder”) and pick the pellet  with the last two minutes (WT-End and PVKO-End) of sessions 4-8 . At session 10 the animals achieved the criteria set to determine that operant conditioning was acquired. Hence, the rationale was to determine the dynamics of LFPs power spectra along different phases of learning the operant conditioning and compare PVKO with WT. We focused our analysis on mPFC, NAc and CA1 because these areas matched two statistical criteria  and across sessions  Figs. A, and 8A29. In the remaining band frequencies of WT mice and in all band frequencies of PVKO, we observed that operant conditioning did not affect the spectral power at mPFC throughout the acquisition stages.During the baseline condition (defined in “Hz) Fig. . For theHz) Fig. , S4.3. Isession 1 to session 10 in both WT and PVKO mice  successive sessions and/or the fixation of a maximum latency to get the reinforcement, could constitute a better measurement to assess the achievement of initial associative learning prior to true operant training. We decided to stick to the same criterion set in our laboratory for a series a previous studies for the sake of comparison –namely, the number of lever presses carried out during the light and dark periods35. Extended behavioral studies with several variants of the protocol should be considered in the future for a careful evaluation and separation of the behavioral responses associated with motivation from locomotion and motor coordination.Mice performances in executive functions show strong similarities with humans WT Fig. , S1.2. T36. A detailed analysis of LFPs simultaneously recorded in selected structures classically related to operant conditioning tasks has been carried out here in order to properly determine putative functional deficits associated to specific phases of the task. In PVKO mice we observed a decreased signal-to-noise ratio in LFP recordings during conditioning, likely to be associated with a tendency to higher firing rates observed in several brain areas of PVKO in single unit recordings37. This result could be due to a differential recruitment of PV-positive GABAergic neurons during the execution of the task modulated by the balance of excitation and inhibition (E/I)38, thus controlling and tuning the transitions between oscillatory brain states39. PV-expressing interneurons in mPFC could fire in millisecond synchrony and exert a rapid and powerful inhibition on the activation of the pyramidal cells, thus controlling the outputs of this cortical area40. However, whether mutual inhibition alone between GABAergic cells, or whether re-entrant excitation from recurrent networks of inhibitory and excitatory neurons, is necessary to develop high-frequency oscillations remains an unresolved question, because both mechanisms exist41.It was demonstrated that during tasks demanding attention, the activity of prefrontal PV-expressing interneurons is modified, with the activity being higher and in the gamma range (30-40 Hz) during attentional processing resulting in successful execution of a task42 and in mice, during a reward foraging task, these cells responded at reward leaving and encoded preceding stay duration, but did not respond to reward approach40. The activity of fast-spiking GABAergic PV-expressing interneurons is directly linked to oscillations in the 43. The spectral power comodulation analysis presented here showed interesting differences between correct and incorrect trials, but similar patterns in both PVKO and WT mice with respect to thalamo-cortical and thalamo-NAc comodulograms. On the contrary, during correct trials, the comodulation between mPFC and NAc in the [44. Moreover during correct trials, we noticed only in PVKO mice and not in WT a positive comodulation between CA1 and all other channels in the frequencies [45 showing an abnormally high proportion of coupling in the 46.Our LFPs recordings showed similar spectral power at all frequency bands during baseline condition, but significant decreases of the spectral power in 48 and expressed by 50. It is of particular interest our observation of how operant conditioning modified the spectral power for different frequency bands in the NAc throughout the learning process. From session 1 to session 10, the spectral power increased in WT and decreased in PVKO mice. It is also worth noting that in PVKO no differences were observed in spectral power between PVKO-Beginning and PVKO-End and between these measurements and powers at session 10. This significant set of changes is likely to be related with the increase contribution of food reward across training, a typical characteristic of NAc neurons51 and with some but not all neurophysiological deficits seen in GABAergic interneurons of PV-deficient mice52. During social interaction in normal conditions, the increase of the neurotransmitter DA in the NAc would excite the PV-expressing fast-spiking interneurons (PV-FSI) directly through D1-type receptors or indirectly through D2-type receptors53, and cortical projections from mPFC to NAc would contribute to maintaining the E/I balance and regulating reward-seeking processes28. This would increase the inhibitory activity of the PV-FSI on the medium spiny neurons (MSN), which would generate oscillations in 55. This might also suggest that PVKO mice are likely to be characterized by a reduced sensitivity to reward state, but our baseline condition could not reveal it because mice were left alone during LFP recordings. Both WT and PVKO strains could learn the operant conditioning task, but the differences observed in NAc LFPs suggest that the value of the reward was not encoded via the same mechanisms. Other interneurons subtypes are involved as well in the circuitry57, and altogether they may make an asymmetric contribution to regulate not only high-frequency, but also low-frequency oscillatory activities.A critical part of the associative learning process in operant conditioning, by which the brain links natural rewards or alternative rewards, such as drug or alcohol, with specific stimuli and motor response, is encoded in the nucleus accumbens58. High-frequency oscillations in the ranges of the 59, although this interpretation is challenged by new observations61. Hippocampal activity in behaving mice during exploration is characterized by 54. Gamma power and theta power of LFPs in CA1 hippocampal area were comodulated and 62. In this study, we observed a positive comodulation of power between CA1 and all other channels only during correct trials by PVKO mice in the bands [62 decreased spectral power after session 1 and stayed low till the last session of recording.The activity of fast-spiking PV-expressing interneurons in hippocampal microcircuits is thought to play a key role in network oscillationsIn conclusion, the current results suggest that the modifications of the LFP activities observed in PV-deficient mice during operant conditioning were consistent with changes in network dynamics associated with a modified encoding of reward value in the nucleus accumbens. These alterations compromised specific brain oscillations in basal ganglia-thalamo-cortical circuit recorded here throughout the operant conditioning task and also during the execution of a precise behavioral sequence (from pressing the lever until eating the pellet).2. Congenic C57Bl/6J mice could be used as control wild-type (WT) animals63. Only male animals were used in this study. Upon arrival of the PVKO mice and their littermate control to the Animal Facilities of Pablo de Olavide University, the animals were placed in individual cages provided of an enriched environment and of nesting materials. Animals were maintained in the same situation until the end of the experiments. They were provided with food and water ad libitum and maintained in a temperature-controlled environment in a 12/12 h light-dark cycle. All behavioral experiments were performed in accordance with European Union Council (2010/276:33-79/EU) guidelines and Spanish  regulations for the use of laboratory animals in chronic experiments. Experiments were also approved by the local Ethics Committee of the Pablo de Olavide University.PVKO mice ; NAc ; CA1 ; MS ; and, MD nucleus   delivered from a calibrated mask . Once anesthetized, and following surgical procedures described elesewhere35.Operant conditioning took place in two Skinner box modules  schedule  and perfused transcardially with saline and 4% phosphate-buffered paraformaldehyde. Their brains were removed, postfixed overnight at 4 °C, and cryoprotected in 30% sucrose in PBS. Sections were obtained in a microtome at 50 μm. Selected sections including brain implanted sites were mounted on gelatinized glass slides and stained using the Nissl technique with 0.1% toluidine blue to determine the location of recording electrodes  and non-parametric ) methods were used to assess the statistical significance of differences between groups, followed by the appropriate test  for all the pairwise multiple-comparison analyses35. Unless otherwise indicated, data are always represented as the mean± SEM. The performance of WT and PVKO mice during the light/dark test was assessed by mean of the light/dark (LD) coefficient defined as:L) and dark (D) periods, respectively; and T) number of lever presses . Data were analyzed offline for quantification of animal performance in the Skinner box Fig. –8. Stati21, LFP epochs lasting 2 s each were collected during the performance of the following behaviors: (i) when crossing the light beam to reach the lever; (ii) when pressing the lever; and, (iii) when crossing the light beam to reach the feeder  and the time-frequency (using the short-term Fourier transform) analyses of the LFP recordings, as well as the quantification and representation scripts, were developed in a previous study from our laboratory21 with the help of MATLAB routines and customized scripts of Chronux67 software (versions 2.11/R2014 and 2.12/R2018. Website: http://chronux.org/).For LFP analysis, we used data collected from sessions presenting significantly different performance in the operant conditioning task. Following previous studies from our laboratory68, since they included an estimation of the short-term, time-localized frequency content of the signals  between the spectral power SP(f) at a frequency k. The parameter 72, which the most commonly used spectral measure of cross-frequency couplings between two oscillations. For more details see Figs. In this work, the following spectral measures were calculated to assess the spectral couplings between different oscillatory activities from LFP recordings:To obtain the LFP spectrograms see Fig.  and the Supplementary Tables.


Cerebellar ataxia is the predominant motor feature of multiple system atrophy cerebellar subtype (MSA-C). Although repetitive transcranial magnetic stimulation (TMS) of the cerebellum is growingly applied in MSA, the mechanism is unknown. We examined dynamic connectivity changes of 20 patients with MSA and 25 healthy controls using TMS combined with electroencephalography. Observations that significantly decreased dynamic cerebello-frontal connectivity in patients have inspired attempts to modulate cerebellar connectivity in order to benefit MSA. We further explore the therapeutic potential of a 10-day treatment of cerebellar intermittent theta burst stimulation (iTBS) in MSA by a randomized, double-blind, sham-controlled trial. The functional reorganization of cerebellar networks was investigated after the end of treatment in active and sham groups. The severity of the symptoms was evaluated using the Scale for Assessment and Rating of Ataxia scores. Patients treated with active stimulation showed an improvement of cerebello-frontal connectivity and balance functions, as revealed by a significant decrease in the ataxia scores (P < 0.01). Importantly, the neural activity of frontal connectivity from 80 to 100 ms after a single TMS was significantly related to the severity of the disease. Our study provides new proof that cerebellar iTBS improves motor imbalance in MSA by acting on cerebello-cortical plasticity. Multiple system atrophy (MSA) is a fatal, progressive, neurodegenerative disease associated with disability and poor quality of life that ultimately results in an immobilized, bedridden patient. MSA with predominant cerebellar dysfunction (MSA-C) typically presents with cerebellar ataxia, and therapeutic options remain limited. There is an urgent attempt to develop new therapeutic strategies to slow the progression of MSA-C. Repetitive transcranial magnetic stimulation (rTMS), a non-invasive brain stimulation technique, influences neuroplasticity in the short and long term, both at the local cortex under the stimulating coil and at the network level throughout the brain . rTMS haTarget selection for rTMS has considerable impact on its therapeutic effect. The left primary motor area (M1) , 4, cereThere is an urgent need to integrate clinical behavioral characteristics with data from electrophysiological or functional imaging techniques. As poor temporal resolution and indirect measure of neural activity by the BOLD signal, functional magnetic imaging (fMRI) is not the best method to detect processing in neural networks. Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) enables direct probing of cortical reactivity and assessment of cortico-cortical connections on a millisecond time-scale. Most importantly, TMS-EEG enables us to study the cortical response to the TMS pulse and to characterize brain functional connectivity in time, spatial, and frequency domains . Hence, To our knowledge, there have been no studies applying TMS-EEG measures to investigate dynamic cerebello-fronto connectivity in patients with MSA and healthy subjects. Elucidating these differences is key to understanding both the neurophysiological mechanisms of cerebellum disorder and treatment effects . We hypoTwenty patients with MSA and 25 healthy controls participated in Experiment 1 . Fifty pWe recruited 20 MSA patients  and 25 healthy controls . The clinical data of Experiment 2 is shown in To better assess the association between frontal connectivity and we calculated the sum of the edges of frontal connectivity from 80 to 100 ms after single TMS in patients with MSA after iTBS intervention. The number of the edges was negatively correlated with the SARA scores in the two groups . These fThis study examines differences in cerebello-frontal connectivity in MSA patients and healthy controls using TMS-EEG measures. We found that cerebellar iTBS has a significant beneficial effect on motor imbalance in patients with MSA-C, as demonstrated by the decrease in SARA scores. Importantly, these changes are modulated by an enhancement in neural activity in the cerebellar-frontal network as measured by TMS-EEG.Compared to healthy controls, MSA patients showed significantly decreased dynamic information processing at the frontal cortex during single TMS over the cerebellum  mainly within the time window of 80 ms. These results provide the first evidence of reduced electrical activity at prefrontal cortical areas by cerebellar-evoked activity in MSA patients. Although the interconnection between the cerebellum and prefrontal cortices has been well-established in humans using fMRI –18 or nePrevious research has demonstrated temporary functional improvement after sessions of high frequency cerebellar rTMS in patients with ataxia –25 and tNeurobiologically, rTMS produces an LTP-like effect and facilitates synaptic plasticity in animal models , 30. SinThere are some limitations in the study. First, our result is limited by the relatively small sample size. There is a great need to plan large scale, sham-controlled trials to confirm the benefits of neuromodulation of the cerebellum. Second, a cross-over design might be better in a second set. Due to limited time and funding, we did not do this in this study. In addition, the potential artifacts were mainly within 60 ms after delivering the TMS pulse. The data from 50 to 70 ms were not analyzed, although important information is likely included in that range. Finally, the relatively small number of recording electrodes made precise spatial definition difficult.In conclusion, our findings provide novel evidence that iTBS over the cerebellum is potentially an effective strategy to improve motor symptoms by enhancing cerebellar-frontal connectivity reorganization in patients with MSA.We conducted two consecutive experiments. All of the enrolled participants in two experiments completed baseline assessments and a structural brain MRI. Experiment 1 was designed to clarify dynamic brain connectivity changes induced by single-pulse TMS in the time-varying network in healthy controls and patients with MSA. Participants were asked to relax and stay positioned on a semi-reclined chair for 20 minutes when recording the TMS-EEG data.Experiment 2 was a randomized, double-blind, sham-controlled study. The objective is to examine the therapeutic effects of iTBS applied over the cerebellum in MSA patients and to observe changes in the time-varying network. In the second experiment, all patients firstly underwent 20 minutes of TMS-EEG recording. Their limb kinetic function was evaluated using the scale for the assessment and rating of ataxia (SARA). Then, patients were randomly assigned to receive 10 days of real or sham rTMS therapy. At the end of the therapy day, 20 minutes of TMS-EEG recording and SARA test was again made. . The priThe patients were recruited between March 2017 and October 2019 from the Department of Neurology, Xuanwu Hospital, Capital Medical University. Inclusion criteria for patients with MSA were as follows: (1) Met the clinical criteria for probable MSA-C . (2) AgeSingle-pulse TMS was applied with a figure-of-eight coil (70 mm diameter) connected to a monophasic Magstim stimulator . The resting motor threshold (RMT) was defined as the lowest stimulation intensity that could produce at least five motor evoked potentials with wave amplitudes >50 mV among 10 trials in the right first dorsal interosseous muscle. The surface electromyography was recorded using disc-shaped Ag-Cl electrodes that were placed in a tendon-belly arrangement. The stimulating coil was positioned tangentially to the skull with the coil handle pointing backward and laterally at 45°from the anterior-posterior axis.TMS-EEG data (20 min) were acquired using a magnetic field-compatible EEG amplifier . The cap  with 32 TMS-compatible electrodes were positioned according to the 10-20 montage. The sample rate was 1024 Hz. The electrode impedances were maintained below 5 kΩ. The AFz channel was the reference and nasal tip electrodes served as ground. Single TMS (sTMS) was stimulated in the right cerebellum  . iTBS therapy applied over the bilateral cerebellum using the same scalp coordinates (1 cm inferior and 3 cm left/right to the inion). One iTBS session consisted of the following parameters: a burst of 3 pulses at 50 Hz repeated at 200-ms intervals, a short train lasting 2 seconds, an inter-train interval of 8 seconds, 300 pulses in a session. The stimulation intensity for the iTBS was set at 80% of the RMT. Three iTBS sessions were performed separately on the left and right cerebellum with a 5-min interval between sessions . The sham stimulation was performed using a Magstim placebo coil, which mimics the typical “click” of the genuine coil without magnetic stimulation. The procedures and parameters of iTBS sham stimulation were the same as the real stimulation. The treatment was applied once a day for two weeks with rest on the weekends .The pre-processing and time-varying network analyses were performed on the MATLAB platform . The pre-processing of EEG data included a bandpass filter (3-30Hz) and data segmentation. We used single TMS disturbance as the stimulus labels. For every disturbance event label, the time point corresponding to the peak of the label was set as time ‘‘0’’. Data corresponding to 0.5 s before (as baseline) and 0.4 s after ‘‘0’’ were extracted. Each segment length was 0.9 s. Considering the artifacts produced by the TMS on the EEG signals, we focused on the changes in brain networks at 80-400 ms after the single TMS stimulation. To capture the characteristics of brain connections, time-varying network analysis requires several steps to build a reliable network. First, in order to reduce the calculation load, the sampling rate is 128Hz in the final analysis by 8 times down-sampling during data processing. Next, we built a time-varying multivariate adaptive autoregressive (tv-MVAAR) model and calculated the ADTF matrix. This procedure is available in the supplementary material appendix. Last, we mapped the brain networks as previously described [Considering that phase randomization preserves the spectral structure of the time series, Fourier coefficient phases were randomly and independently shuffled to produce the corresponding reference signals. This procedure was repeated 300 times for each segment of each subject. An empirical distribution of ADTF values was created under the null hypothesis of no causal interaction in each edge. Then, the time-varying networks, which corresponded to each single trial, were further averaged across all the artifact-free trials. This averaging procedure gave the final time-varying networks.The time-varying EEG networks were analyzed using two-tailed t-test. Matlab was utilized to identify the dynamic network patterns before and after the iTBS treatment. The means and variances were used to calculate the Gauss cumulative distribution. The dynamic networks were calculated with a significance of 0.05.Clinical assessment data were analyzed using SPSS software version 19.0 . Demographic and clinical variables were compared using between-group two-sample, two-tailed t-tests or chi-squares. The sum of the edges of frontal connectivity from 80 to 100 ms after single TMS were compared using between-group two-sample, two-tailed t-tests. Pearson's correlation test was performed to examine the correlation between the sum of the edges of frontal connectivity from 80 to 100 ms and the SARA scores.Supplementary Materials


Mutator and MITE Pif/Harbinger) have shaped part of the regulatory network in each tissue, and that MITEs have provided potential new TF binding sites involved in husk tissue-specificity.Enhancers are key players in the spatio-temporal coordination of gene expression during numerous crucial processes, including tissue differentiation across development. Characterizing the transcription factors (TFs) and genes they connect, and the molecular functions underpinned is important to better characterize developmental processes. In plants, the recent molecular characterization of enhancers revealed their capacity to activate the expression of several target genes. Nevertheless, identifying these target genes at a genome-wide level is challenging, particularly for large-genome species, where enhancers and target genes can be hundreds of kilobases away. Therefore, the contribution of enhancers to plant regulatory networks remains poorly understood. Here, we investigate the enhancer-driven regulatory network of two maize tissues at different stages: leaves at seedling stage (V2-IST) and husks (bracts) at flowering. Using systems biology, we integrate genomic, epigenomic, and transcriptomic data to model the regulatory relationships between TFs and their potential target genes, and identify regulatory modules specific to husk and V2-IST. We show that leaves at the V2-IST stage are characterized by the response to hormones and macromolecules biogenesis and assembly, which are regulated by the BBR/BPC and AP2/ERF TF families, respectively. In contrast, husks are characterized by cell wall modification and response to abiotic stresses, which are, respectively, orchestrated by the C2C2/DOF and AP2/EREB families. Analysis of the corresponding enhancer sequences reveals that two different transposable element families (TIR transposon  Enhancers are key regulators of the spatio-temporal expression of genes in eukaryotes, in particular during development , 3D chromatin folding analyses showed that about 25%-40% of enhancers are not targeting their closest gene, and that 34% of enhancers potentially regulate several genes  of various superfamilies have been proposed as a source of new regulatory elements  at flowering. Taking advantage of enhancers that were previously predicted by Oka and colleagues to be active in these two organs , we retained 18,348 TFBSs corresponding to 62 transcription factors. A table containing the annotation of TFBS in each enhancer is available in Arabidopsis thaliana, we wanted to check whether the TFBSs we predicted in maize were supported by ChIP-seq and DAP-seq data in maize. The binding landscape of 32 TFs has been generated in maize leaves using DAP-seq .We first aimed to characterize the TFBS content of active enhancers in husk and V2-IST , but also from the AP2/ERF (5), HD-ZIP (2), and bHLH (1) families. More precisely, in addition to the 3 TFs of the C2C2/DOF family that had significantly more binding sites in the husk enhancers, 4 were found only in husk enhancers  than with any other samples (average inter-tissue Pearson correlation coefficient R = 0.83). Moreover, expression levels from the V2 inner immature tissues from both datasets (V2-IST and V2_L-I) are strongly correlated (average pairwise Pearson correlation coefficient R = 0.93). The principal component analysis of normalized RNA-seq data  from Oka et al. . To obtaata PCA,  show thaTo build our network, we retained only enhancers carrying at least one TFBS corresponding to expressed TFs. Of the 62 TFs for which TFBSs were identified within the 1495 enhancers, 10 were not expressed in any of our samples and were therefore filtered out. In total, 971 enhancers carried at least one TFBS corresponding to one of the 52 expressed TFs. Out of the 36,041 genes, we identified a total of 8,054 potential target genes that were located within 250 kb of one of the 971 enhancers, and that we included in the prior. Among those, 6,459 (80%) were potentially targeted by a single enhancer, 1,269 (16%) by two enhancers and 326 (4%) were potentially targeted by three enhancers or more. Conversely, each of the enhancers had an average of 10 potential target genes (ranging from 1 to 42). Our prior gene regulatory network thus contained 52 TFs that had TFBS in one of the 971 enhancers, and 8,054 genes. Each gene was connected to an average of 8.6 TFs (ranging from 1 to 33), and each TF was linked to an average of 1,310 genes .We combined the prior gene regulatory network to the co-expression matrix obtained from the mRNA-seq normalized data from the 45 samples (13 tissues). We then built sample-specific gene regulatory networks using PANDA and LIONESS . The third one, b1 enhancer, has not been assembled in AGPv4, and as such could not be included in our analysis. We found that the regulatory relationship between tb1 and the TFs binding its enhancer is stronger in husk than in V2-IST  were of similar strength in both husk and V2-IST . The 3,856 remaining genes were not significantly differentially targeted in any of the two tissues. Using a Gene Ontology enrichment analysis . We thus identified 2,075 genes that were more highly targeted by TFs in husk and 2,123 genes that were more highly targeted in V2-IST   and three V2-IST-specific modules , and Zm00001d045720/Zm00001d045721/Zm00001d045722, three genes coding for proteins of the TBL family, which is involved in trichome morphogenesis and secondary cell wall morphogenesis . The expression levels of both of these TFs positively correlate with the expression level of their target genes involved in “heterocyclic compound binding” across all 45 samples and 13 tissues , “regulation of nucleic acid-templated transcription”  and “response to hormones” . In this module, genes classified under the “response to hormones” gene ontology are regulated by BPC5, a member of the BBR/BPC TF family involved in Polycomb complex recruitment , its expression is anti-correlated with most of its target genes  and the distribution of TE families is strongly affected by distance to the closest gene, we used randomly chosen genomic sequences on the same chromosome, with the same size and distance to the closest gene than the enhancers to build χ2 expected null distributions for each enrichment test (see section 4). We then compared the χ2 obtained using the real enhancers with the expected null distribution. We found that husk-specific enhancers are enriched in miniature inverted-repeat transposable elements  as compared to the V2-IST and shared enhancers .We took advantage of the regulatory networks and modules we identified to investigate the role of transposable elements (TEs) in the tissue-specific regulation of gene expression. We first compared the TE sequence content of husk-specific and V2-IST-specific enhancers. To this end, we annotated TE in enhancers using a recently updated TE database  at flowering. To do so, we used a bipartite network-based approach integrating several layers of information from heterogeneous data: epigenetic information (providing genomic location of active enhancers), genomic information (providing gene-candidate enhancer distance and annotation of TFBSs within enhancers) and transcriptomic information from 13 different tissues sampled at different developmental stages. This allowed us to provide functional insights into the regulatory role of enhancers that are activated in a tissue-specific manner.cis-regulation.Several approaches are routinely used to analyze gene regulatory networks. Classic weighted co-expression networks allow for the detection of genes that are co-expressed in the same tissues as well as modules corresponding to major biological functions. However, they do not detect which regulators are responsible for this co-expression  is involved in salt and osmotic tolerance in poplar  involved in these functions. In addition to the to-be-expected modules, our approach also allowed us to discover regulatory modules of more unclear function, notably in husk. Husks are the bracts of the maize female inflorescence that provide a mechanical protection of the ear and growing silks (the styles of maize florets). In particular, husks ensure silks growth by protecting them from air evaporative demand and preserving their water status , thus suggesting that the JASPAR database is relevant to detect TFBS in maize genome. Nevertheless, we are still likely to be missing a number of tissue-specific functions regulated by maize-specific TFs. While some progress toward the identification of maize TFBS motifs has been made through the use of sequence conservation analyses  of the enhancers analyzed include TE sequences. This is higher than estimated in previous studies  and V2-IST (the inner part of leaves 3 and onwards of stage V2 seedlings) from the B73 maize line. Complete description of these tissues is presented in We generated 150 bases paired-end mRNA-seq data from 11 tissues. Tissue types, growing conditions and sampling are summarized in Raw illumina reads (fastq) were trimmed with Trimmomatic  lower than 0.01 were retained.Candidate enhancer sequences were extracted from the bed files containing coordinates of enhancers from Oka et al.  and the p-values by counting the number of random sequences for which TFBS coverage exceeded the one of the original enhancer.Significance of the TFBS results was tested by comparing the number of bases covered by TFBSs in original candidate enhancer sequences to this of random sequences obtained by shuffling enhancers dinucleotides. To this end, for each enhancer, we generated 1,000 random sequences using the BiasAway software .We compared the TFBS motif content of husk and V2-IST enhancers by using the AME software from the cis-regulatory region of the gene, and zero its absence. This prior edge matrix is then updated using a protein-protein interaction (PPI) matrix that represents interactions between TFs and a gene co-expression matrix. This relies on a message-passing algorithm that verifies both the “responsibility” and the “availability” of each edge  were log-transformed (logEW) using the following formula: for each sample i and edge e:In this study, the prior TF-gene interaction matrix was obtained by crossing enhancer coordinates with gene coordinates. The gene-enhancer maximal distance was set up to 250kb. This threshold is based on analysis of the enhancer-nearest gene distance distributions of Ricci et al.  and Lu eEdges that were set to 0 in the prior were set to 0 in the all the following analyses.Enhancer-gene TSS distances thus obtained were also used to compute the distributions of distances between enhancers and nearest gene TSS. Briefly, the closest gene was the one whose TSS was the closest from the gene in absolute value.e and potential target gene g, the average edge weight (avgEWg) was computed as the average of the edges (logEW) from each TF t to the gene. Only TFs with a potential factor binding site in the enhancer were included. With Te the number of TFBSs in the enhancer:In order to identify the most likely target gene of each enhancer, we computed the average edge weight for each enhancer-potential target gene pair. For each pair of enhancer limma R package version 3.28.2.To identify genes that were differentially targeted between husk and V2-IST tissues, edges weights were compared between tissues-conditions using a linear regression performed with the R bioconductor k is the tissue-condition and r the replicate.p-values under 0.01 were considered as differentially targeted.Genes that were targeted by edges with Benjamini–Hochberg corrected To identify tissue-specific regulatory modules, we first build one husk-specific and one V2-IST-specific network by averaging the LIONESS sample-specific networks across the replicates for each tissue. We then identified the TF and genes that changed the modularity of the networks between V2-IST and husk by running ALPACA . The gene ontology database used in this analysis was generated by combining publicly available annotations , and removing any redundancy.We performed Gene Ontology enrichment analyses using the R bioconductor topGO package  with an updated TE database provided by Shujun Ou  using REPEATMASKER v4.0  with Project ID NGS2017 06 AMAIZING, experiment Amaizing B73 WW. This project has been submitted from CATdb into the international repository GEO  with ProjetID GSE151455. These data are available upon request to Clementine Vitte, and will be made publicly available upon article acceptance.All steps of the experiment, from growth conditions to bioinformatic analyses, were managed in CATdb database (Gagnot et al., CV, MF, and MS conceived the experiments. CV and JJ secured the funding. CV and MF performed the experiments and analyzed the data. OT coordinated greenhouse culture, sampling strategy, and sample collection. AV, CV, JJ, and OT collected the samples. AV performed the tissue grinding and mRNA extractions. SP generated the mRNA-seq libraries. JR aligned the mRNA-seq reads. MF and CV wrote the article. JJ, MK, MS, and OT provided the expertise and feedback and corrected the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.