Exploring LGBT2Q+ Intracategorical Factors in Mental Health Service Utilization: Differences in Gender Modalities, Sexual Orientations, and Ethnoracial Groups in Canada.

LGBT2Q+ (lesbian, gay, bisexual, transgender, Two-Spirit, queer, plus) Canadians face minority stressors that lead to higher mental health inequalities such as worse self-reported mental health and increased risk of mental health issues when compared to their heterosexual/straight and cisgender counterparts. However, there are within-group (intracategorical) differences within a community as large as LGBT2Q+ peoples. Guided by the Andersen Model of Healthcare Utilization, we sought to explore intracategorical differences in LGBT2Q+ Canadian predisposing, enabling, and need factors in mental health service utilization within the past year. Using data from the 2020 LGBT2Q+ Health Survey (N = 1542), modified Poisson logistic regression found that more polysexual respondents and trans/gender-diverse respondents were more likely to have utilized mental health services within the past year than their gay, lesbian, and cis male counterparts. As well, compared to White respondents, Indigenous respondents were more likely to have utilized mental health services, while other racialized respondents were associated with less utilization. Backwards elimination of Andersen model of healthcare utilization factors predicting mental health service utilization retained two predisposing factors (ethnoracial groups and gender modality) and two need factors (self-reporting living with a mood disorder and self-reporting living with an anxiety disorder). Results suggest that polysexual, trans and gender-diverse, and racialized LGBT2Q+ peoples have an increased need for mental health services due to increased specific minority stressors that cisgender, White, monosexual peoples do not face. Implications for healthcare providers are discussed on how to improve service provision to LGBT2Q+ peoples.

A mutual information measure of phase-amplitude coupling using gamma generalized linear models.

Introduction: Cross frequency coupling (CFC) between electrophysiological signals in the brain is a long-studied phenomenon and its abnormalities have been observed in conditions such as Parkinson's disease and epilepsy. More recently, CFC has been observed in stomach-brain electrophysiologic studies and thus becomes an enticing possible target for diseases involving aberrations of the gut-brain axis. However, current methods of detecting coupling, specifically phase-amplitude coupling (PAC), do not attempt to capture the phase and amplitude statistical relationships. Methods: In this paper, we first demonstrate a method of modeling these joint statistics with a flexible parametric approach, where we model the conditional distribution of amplitude given phase using a gamma distributed generalized linear model (GLM) with a Fourier basis of regressors. We perform model selection with minimum description length (MDL) principle, demonstrate a method for assessing goodness-of-fit (GOF), and showcase the efficacy of this approach in multiple electroencephalography (EEG) datasets. Secondly, we showcase how we can utilize the mutual information, which operates on the joint distribution, as a canonical measure of coupling, as it is non-zero and non-negative if and only if the phase and amplitude are not statistically independent. In addition, we build off of previous work by Martinez-Cancino et al., and Voytek et al., and show that the information density, evaluated using our method along the given sample path, is a promising measure of time-resolved PAC. Results: Using synthetically generated gut-brain coupled signals, we demonstrate that our method outperforms the existing gold-standard methods for detectable low-levels of phase-amplitude coupling through receiver operating characteristic (ROC) curve analysis. To validate our method, we test on invasive EEG recordings by generating comodulograms, and compare our method to the gold standard PAC measure, Modulation Index, demonstrating comparable performance in exploratory analysis. Furthermore, to showcase its use in joint gut-brain electrophysiology data, we generate topoplots of simultaneous high-density EEG and electrgastrography recordings and reproduce seminal work by Richter et al. that demonstrated the existence of gut-brain PAC. Using simulated data, we validate our method for different types of time-varying coupling and then demonstrate its performance to track time-varying PAC in sleep spindle EEG and mismatch negativity (MMN) datasets. Conclusions: Our new measure of PAC using Gamma GLMs and mutual information demonstrates a promising new way to compute PAC values using the full joint distribution on amplitude and phase. Our measure outperforms the most common existing measures of PAC, and show promising results in identifying time varying PAC in electrophysiological datasets. In addition, we provide for using our method with multiple comparisons and show that our measure potentially has more statistical power in electrophysiologic recordings using simultaneous gut-brain datasets.

Machine learning based DNA melt curve profiling enables automated novel genotype detection.

Surveillance for genetic variation of microbial pathogens, both within and among species, plays an important role in informing research, diagnostic, prevention, and treatment activities for disease control. However, large-scale systematic screening for novel genotypes remains challenging in part due to technological limitations. Towards addressing this challenge, we present an advancement in universal microbial high resolution melting (HRM) analysis that is capable of accomplishing both known genotype identification and novel genotype detection. Specifically, this novel surveillance functionality is achieved through time-series modeling of sequence-defined HRM curves, which is uniquely enabled by the large-scale melt curve datasets generated using our high-throughput digital HRM platform. Taking the detection of bacterial genotypes as a model application, we demonstrate that our algorithms accomplish an overall classification accuracy over 99.7% and perform novelty detection with a sensitivity of 0.96, specificity of 0.96 and Youden index of 0.92. Since HRM-based DNA profiling is an inexpensive and rapid technique, our results add support for the feasibility of its use in surveillance applications.

Minority Stressors, Social Provisions, and Past-Year Suicidal Ideation and Suicide Attempts in a Sample of Sexual Orientation and Gender Identity/Expression Minority People in Canada.

Purpose: Mental health disparities in sexual orientation and/or gender identity and/or expression (SOGIE) minority groups are well-documented, with research consistently showing higher levels of suicidality, even in Canada, considered one of the world's most accepting countries of SOGIE minority groups. Adverse outcomes in these groups are often framed using minority stress theory, with social support frequently studied as an integral buffer to these outcomes. This analysis explores facets of minority stress and social support associated with past-year suicidal ideation and suicide attempts. Methods: A cross-sectional internet survey of SOGIE diverse people in Canada (n = 1542) was conducted. Binary logistic regression calculated bivariate and multivariate factors associated with past-year suicidal ideation and suicide attempts. Backward elimination (retaining sociodemographic factors and self-rated mental health) identified salient minority stress and social support (provisions) factors. Results: Over half (56.72%) of participants had ever thought of dying by suicide, with 24.84% having attempted suicide. During the past year, 26.80% had thought of dying by suicide, with 5.32% having attempted suicide. Victimization events, and guidance (e.g., someone to talk to about important decisions) and attachment (e.g., close relationships providing emotional security) social provision subscales remained salient after backward elimination procedures. Conclusion: Our findings emphasize that a fulsome, multilevel approach considering structural, community, and individual strategies to address overt discrimination, integrating social connections and guidance, is necessary to prevent dying by suicide.

Emerging wearable technologies for multisystem monitoring and treatment of Parkinson's disease: a narrative review.

Parkinson's disease (PD) is a chronic movement disorder characterized by a variety of motor and nonmotor comorbidities, including cognitive impairment, gastrointestinal (GI) dysfunction, and autonomic/sleep disturbances. Symptoms typically fluctuate with different settings and environmental factors and thus need to be consistently monitored. Current methods, however, rely on infrequent rating scales performed in clinic. The advent of wearable technologies presents a new avenue to track objective measures of PD comorbidities longitudinally and more frequently. This narrative review discusses and proposes emerging wearable technologies that can monitor manifestations of motor, cognitive, GI, and autonomic/sleep comorbidities throughout the daily lives of PD individuals. This can provide more wholistic insight into real-time physiological versus pathological function with the potential to better assess treatments during clinical trials and allow physicians to optimize treatment regimens. Additionally, this narrative review briefly examines novel applications of wearables as therapy for PD patients.

'I don't want to have to teach every medical provider': barriers to care among non-binary people in the Canadian healthcare system.

It is well-known that trans and non-binary individuals experience worse health outcomes due to experiences of violence and discrimination. For this reason, accessible healthcare for trans and non-binary people is crucial. There is a lack of Canadian literature on the experiences of non-binary people within the healthcare system. This study sought to understand barriers to healthcare among non-binary people living in a mid-sized urban/rural region of Canada. Interviews were conducted between November 2019 to March 2020 with 12 non-binary individuals assigned female at birth, living in Waterloo Region, Ontario, Canada, as a part of a larger qualitative study exploring experiences within the community, healthcare and employment. Three broad themes were developed: erasure, barriers to access to healthcare, and assessing whether (or not) to come out. Sub-themes included institutional erasure, informational erasure, general healthcare barriers, medical transition healthcare barriers, anticipated discrimination, and assessing safety. Policy and institutional changes are needed to increase the safety and accessibility of healthcare services to non-binary individuals.

Exploring the aperiodic nature of parasympathetic activity during sleep in idiopathic gastroparesis.

The parasympathetic nervous system is necessary to regulate both sleep and digestion. Investigating abnormalities during the controlled setting of sleep can shed light on digestion, specifically for patients with idiopathic gastroparesis. In this study, we specifically investigate heartbeat-derived parasympathetic activity during sleep at very low frequencies, relevant to sleep cycle regulation. To do this, we adapt a method that extracts both periodic and aperiodic information from the power spectral density and recognize that the aperiodic activity may contain information relevant to very low frequencies. After testing on both synthetic noise data (pink and white) and overnight data from seven healthy controls and idiopathic gastroparetics, we find that the healthy controls' low-frequency aperiodic activity reflects pink noise structure, while the majority of the patients' aperiodic activity reflects white noise structure. At these low frequencies, these differences suggest differences in autonomic sleep cycle regulation.Clinical Relevance- This methodology can be optimized to track the health of the parasympathetic nervous system and suggest whether individual disease etiology is autonomic-related.

Spontaneous enteric nervous system activity precedes maturation of gastrointestinal motility.

Spontaneous neuronal network activity is essential in development of central and peripheral circuits, yet whether this is a feature of enteric nervous system development has yet to be established. Using ex vivo gastrointestinal (GI) motility assays with unbiased computational analyses, we identify a previously unknown pattern of spontaneous neurogenic GI motility. We further show that this motility is driven by cholinergic signaling, which may inform GI pharmacology for preterm patients.

Exploring the Gut-Brain Connection in Gastroparesis With Autonomic and Gastric Myoelectric Monitoring.

OBJECTIVE: The goal of this study was to identify autonomic and gastric myoelectric biomarkers from throughout the day that differentiate patients with gastroparesis, diabetics without gastroparesis, and healthy controls, while providing insight into etiology. METHODS: We collected 19 24-hour recordings of electrocardiogram (ECG) and electrogastrogram (EGG) data from healthy controls and patients with diabetic or idiopathic gastroparesis. We used physiologically and statistically rigorous models to extract autonomic and gastric myoelectric information from the ECG and EGG data, respectively. From these, we constructed quantitative indices which differentiated the distinct groups and demonstrated their application in automatic classification paradigms and as quantitative summary scores. RESULTS: We identified several differentiators that separate healthy controls from gastroparetic patient groups, specifically around sleep and meals. We also demonstrated the downstream utility of these differentiators in automatic classification and quantitative scoring paradigms. Even with this small pilot dataset, automated classifiers achieved an accuracy of 79% separating autonomic phenotypes and 65% separating gastrointestinal phenotypes. We also achieved 89% accuracy separating controls from gastroparetic patients in general and 90% accuracy separating diabetics with and without gastroparesis. These differentiators also suggested varying etiologies for different phenotypes. CONCLUSION: The differentiators we identified were able to successfully distinguish between several autonomic and gastrointestinal (GI) phenotypes using data collected while at-home with non-invasive sensors. SIGNIFICANCE: Autonomic and gastric myoelectric differentiators, obtained using at-home recording of fully non-invasive signals, can be the first step towards dynamic quantitative markers to track severity, disease progression, and treatment response for combined autonomic and GI phenotypes.

Differentiation of Bolus Texture During Deglutition via High-Density Surface Electromyography: A Pilot Study.

OBJECTIVE: Swallowing is a complex neuromuscular task. There is limited spatiotemporal data on normative surface electromyographic signal during swallow, particularly across standard textures. We hypothesize the pattern of electromyographic signal of the anterior neck varies cranio-caudally, that laterality can be evaluated, and categorization of bolus texture can be differentiated by high-density surface electromyography (HDsEMG) through signal analysis. METHODS: An HDsEMG grid of 20 electrodes captured electromyographic activity in eight healthy adult subjects across 240 total swallows. Participants swallowed five standard textures: saliva, thin liquid, puree, mixed consistency, and dry solid. Data were bandpass filtered, underwent functional alignment of signal, and then placed into binary classifier receiver operating characteristic (ROC) curves. Muscular activity was visualized by creating two-dimensional EMG heat maps. RESULTS: Signal analysis results demonstrated a positive correlation between signal amplitude and bolus texture. Greater differences of amplitude in the cranial most region of the array when compared to the caudal most region were noted in all subjects. Lateral comparison of the array revealed symmetric power levels across all subjects and textures. ROC curves demonstrated the ability to correctly classify textures within subjects in 6 of 10 texture comparisons. CONCLUSION: This pilot study suggests that utilizing HDsEMG during deglutition can noninvasively differentiate swallows of varying texture noninvasively. This may prove useful in future diagnostic and behavioral swallow applications. LEVEL OF EVIDENCE: 4 Laryngoscope, 133:2695-2703, 2023.

Non-Nutritive Suckling System for Real-Time Characterization of Intraoral Vacuum Profile in Full Term Neonates.

Infant breastfeeding diagnostics remain subjective due to the absence of instrumentation to objectively measure and understand infant oral motor skills and suckling characteristics. Qualitative diagnostic exams, such as the digital suck assessment which relies upon a clinician's gloved finger inserted into the infant's mouth, produce a diversity of diagnoses and intervention pathways due to their subjective nature. In this paper, we report on the design of a non-nutritive suckling (NNS) system which quantifies and analyzes quantitative intraoral vacuum and sucking patterns of full-term neonates in real time. In our study, we evaluate thirty neonate suckling profiles to demonstrate the technical and clinical feasibility of the system. We successfully extract the mean suck vacuum, maximum suck vacuum, frequency, burst duration, number of sucks per burst, number of sucks per minute, and number of bursts per minute. In addition, we highlight the discovery of three intraoral vacuum profile shapes that are found to be correlated to different levels of suckling characteristics. These results establish a framework for future studies to evaluate oromotor dysfunction that affect the appearance of these signals based on established normal profiles. Ultimately, with the ability to easily and quickly capture intraoral vacuum data, clinicians can more accurately perform suckling assessments to provide timely intervention and assist mothers and infants towards successful breastfeeding outcomes.

Exploring community enabling factors associated with recent HIV testing in a regional sample of gay, bisexual, and other men who have sex with men.

HIV testing and diagnosis are the gateway into treatment and eventual viral suppression. With gay, bisexual, and other men who have sex with men (GBMSM) persistently over-representing new HIV diagnoses in Canada, combined with the evolving nature of community social connection, an exploration of factors associated with recent HIV testing is warranted. As most studies of GBMSM rely on samples obtained from larger metropolitan regions, examining HIV testing from an under-researched region is necessary. With data collected from an online survey of LGBTQ+ persons 16 or older living, working, or residing in the Region of Waterloo, Ontario, Canada, we used multinomial logistic regression to explore socio-demographic, behavioural, and psychosocial factors associated with recent HIV testing for GBMSM. In the final multivariate multinomial logistic regression model: sense of belonging was associated with more recently testing, as was having an increasing proportion of LGBT friends, app use to find sex partners in the past 12 months, access to the local AIDS service organization, and general sense of belonging to local community, among other. This analysis highlights the continued importance of enabling and need factors when accessing testing, and suggests areas for further testing promotion in physical and virtual spaces frequented by GBMSM.

Wireless Heart Sensor for Capturing Cardiac Orienting Response for Prediction of Neurodevelopmental Delay in Infants.

Early identification of infants at risk of neurodevelopmental delay is an essential public health aim. Such a diagnosis allows early interventions for infants that maximally take advantage of the neural plasticity in the developing brain. Using standardized physiological developmental tests, such as the assessment of neurophysiological response to environmental events using cardiac orienting responses (CORs), is a promising and effective approach for early recognition of neurodevelopmental delay. Previous CORs have been collected on children using large bulky equipment that would not be feasible for widespread screening in routine clinical visits. We developed a portable wireless electrocardiogram (ECG) system along with a custom application for IOS tablets that, in tandem, can extract CORs with sufficient physiologic and timing accuracy to reflect the well-characterized ECG response to both auditory and visual stimuli. The sensor described here serves as an initial step in determining the extent to which COR tools are cost-effective for the early screening of children to determine who is at risk of developing neurocognitive deficits and may benefit from early interventions. We demonstrated that our approach, based on a wireless heartbeat sensor system and a custom mobile application for stimulus display and data recording, is sufficient to capture CORs from infants. The COR monitoring approach described here with mobile technology is an example of a desired standardized physiologic assessment that is a cost-and-time efficient, scalable method for early recognition of neurodevelopmental delay.

Simultaneous Gut-Brain Electrophysiology Shows Cognition and Satiety Specific Coupling.

Recent studies, using high resolution magnetoencephalography (MEG) and electrogastrography (EGG), have shown that during resting state, rhythmic gastric physiological signals are linked with cortical brain oscillations. Yet, gut-brain coupling has not been investigated with electroencephalography (EEG) during cognitive brain engagement or during hunger-related gut engagement. In this study in 14 young adults (7 females, mean ± SD age 25.71 ± 8.32 years), we study gut-brain coupling using simultaneous EEG and EGG during hunger and satiety states measured in separate visits, and compare responses both while resting as well as during a cognitively demanding working memory task. We find that EGG-EEG phase-amplitude coupling (PAC) differs based on both satiety state and cognitive effort, with greater PAC modulation observed in the resting state relative to working memory. We find a significant interaction between gut satiation levels and cognitive states in the left fronto-central brain region, with larger cognitive demand based differences in the hunger state. Furthermore, strength of PAC correlated with behavioral performance during the working memory task. Altogether, these results highlight the role of gut-brain interactions in cognition and demonstrate the feasibility of these recordings using scalable sensors.

A flexible adhesive surface electrode array capable of cervical electroneurography during a sequential autonomic stress challenge.

This study introduces a flexible, adhesive-integrated electrode array that was developed to enable non-invasive monitoring of cervical nerve activity. The device uses silver-silver chloride as the electrode material of choice and combines it with an electrode array consisting of a customized biopotential data acquisition unit and integrated graphical user interface (GUI) for visualization of real-time monitoring. Preliminary testing demonstrated this electrode design can achieve a high signal to noise ratio during cervical neural recordings. To demonstrate the capability of the surface electrodes to detect changes in cervical neuronal activity, the cold-pressor test (CPT) and a timed respiratory challenge were employed as stressors to the autonomic nervous system. This sensor system recording, a new technique, was termed Cervical Electroneurography (CEN). By applying a custom spike sorting algorithm to the electrode measurements, neural activity was classified in two ways: (1) pre-to-post CPT, and (2) during a timed respiratory challenge. Unique to this work: (1) rostral to caudal channel position-specific (cephalad to caudal) firing patterns and (2) cross challenge biotype-specific change in average CEN firing, were observed with both CPT and the timed respiratory challenge. Future work is planned to develop an ambulatory CEN recording device that could provide immediate notification of autonomic nervous system activity changes that might indicate autonomic dysregulation in healthy subjects and clinical disease states.

Automated classification of sleep and wake from single day triaxial accelerometer data.

Actigraphy allows for the remote monitoring of subjects' activity for clinical and research purposes. However, most standard methods are built for proprietary measures from specific devices that are not widely used. In this study, we develop an algorithm for classifying sleep and awake using a single day of triaxial accelerometer data, which can be acquired from all smart devices. This algorithm consists of two stages, clustering and hidden Markov modeling, and outperforms standard algorithms in sensitivity (94%), specificity (93 %), and overall accuracy (93%) across seven subjects. This method can help automate actigraphy analyses at scale using widely available technology using even a single day's worth of data. Clinical Relevance- Automated monitoring of patients' activity at home can help track recovery trajectories after surgery and injury, disease progression, treatment response.

A Mutual Information Measure of Phase-Amplitude Coupling using High Dimensional Sparse Models.

Cross frequency coupling (CFC) between electrophysiological signals in the brain has been observed and it's abnormalities have been observed in conditions such as Parkinson's disease and epilepsy. More recently, CFC has been observed in stomach-brain electrophysiologic studies and thus becomes an enticing possible target for diseases involving aberrations of the gut-brain axis. However, current methods of detecting coupling do not attempt to capture the underlying statistical relationships that give rise to this coupling. In this paper, we demonstrate a new method of calculating phase amplitude coupling by estimating the mutual information between phase and amplitude, using a flexible parametric modeling approach. Specifically, we develop an exponential generalized linear model (GLM) to model amplitude given phase, using a high dimensional basis of von-Mises function regressors and l1 regularized model selection. Using synthetically generated gut-brain coupled signals, we demonstrate that our method outperforms the existing gold-standard methods for detectable low-levels of phase amplitude coupling through receiver operating characteristic (ROC) curve analysis.

Modeling relationships between rhythmic processes and neuronal spike timing.

Neurons are embedded in complex networks, where they participate in repetitive, coordinated interactions with other neurons. Neuronal spike timing is thus predictably constrained by a range of ionic currents that shape activity at both short (milliseconds) and longer (tens to hundreds of milliseconds) timescales, but we lack analytical tools to rigorously identify these relationships. Here, we innovate a modeling approach to test the relationship between oscillations in the local field potential (LFP) and neuronal spike timing. We use kernel density estimation to relate single neuron spike timing and the phase of LFP rhythms (in simulated and hippocampal CA1 neuronal spike trains). We then combine phase and short (3 ms) spike history information within a logistic regression framework ("phaseSH models"), and show that models that leverage refractory constraints and oscillatory phase information can effectively test whether-and the degree to which-rhythmic currents (as measured from the LFP) reliably explain variance in neuronal spike trains. This approach allows researchers to systematically test the relationship between oscillatory activity and neuronal spiking dynamics as they unfold over time and as they shift to adapt to distinct behavioral conditions.NEW & NOTEWORTHY Statistical models that incorporate neural spiking history and relationships to the phase of ongoing oscillations in the local field potential robustly capture and predict neuronal engagement in rhythmic processes. These models constitute a powerful tool to systematically test explicit hypotheses regarding the specific rhythmic currents that constrain neural spiking activity over time and during different behaviors.

'Getting shut down and shut out': Exploring ACB patient perceptions on healthcare access at the physician-patient level in Canada.

PURPOSE: The experiences of African, Caribbean and Black (ACB) Canadians are seldom explored in the Canadian context. Family physicians act as a gateway to the rest of the healthcare system and are necessary to provide proper patient care. However, Canada's history with colonialism may impact the socio-cultural context in which patients receive care. METHOD: 41 participants from Waterloo Region, Ontario, were engaged in eight focus groups to discuss their experiences in the healthcare system. Data were analysed following thematic analysis. RESULTS: Style of care, racism and discrimination and a lack of cultural competence hindered access. oor Inadequate cultural competence was attributed to western and biomedical approaches, poor understanding of patients' context, physicians failing to address specific health concerns, and racism and discrimination. Participants highlighted that the two facilitators to care were having an ACB family physician and fostering positive relationships with physicians. CONCLUSION: Participants predominantly expressed dissatisfaction in physicians' approaches to care, which were compounded by experiences of racism and discrimination. Findings demonstrate how ACB patients are marginalized and excluded from the healthcare syste Iimplications for better access to care included utilizing community healthcare centres, increasing physicians' capacity around culturally inclusive care, and increasing access to ACB physicians.

Experiences of trans patients in primary care settings: findings from The OutLook Study.

BACKGROUND: Relationships between primary care providers (PCP) and trans patients remain important, necessitating discussions about gender identity, health and their intersections. METHODS: Using an online survey, we explored socio-demographic and psycho-social factors associated with: (1) disclosing gender identity; (2) discussing gender identity-related health issues; and (3) comfort sharing gender identity with PCPs, among trans people (n =112) over 16years of age, sampled in Waterloo, Ontario, Canada. Bivariate and multivariate methods using modified Poisson regression generated effect estimates. RESULTS: Age, birth presumed gender, employment status, family support, and transphobia were significantly associated with disclosing gender identity, discussing gender identity-related health issues, and comfortability sharing gender identity with PCPs. CONCLUSION: Increasing PCPs' knowledge of trans-related health issues is stressed to improve access and quality for trans patients.